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@@ -1 +1 @@
-{"config":{"lang":["en"],"separator":"[\\s\\-]+","pipeline":["stopWordFilter"]},"docs":[{"location":"","title":"Home","text":"Welcome to wnc's note!  <p>  My friends! /   Statistics </p> <p>\u7f51\u7ad9\u8fd0\u884c\u65f6\u95f4\uff1a \u8bbf\u5ba2\u603b\u4eba\u6570\uff1a\u4eba \u603b\u8bbf\u95ee\u6b21\u6570\uff1a\u6b21</p>"},{"location":"AI/","title":"AI","text":""},{"location":"AI/#artificial-intelligence","title":"Artificial Intelligence","text":"<p>Abstract</p> <p>\u672c\u90e8\u5206\u5185\u5bb9\uff08\u9664\u7279\u522b\u58f0\u660e\u5916\uff09\u91c7\u7528 \u7f72\u540d-\u975e\u5546\u4e1a\u6027\u4f7f\u7528-\u4fdd\u6301\u4e00\u81f4 4.0 \u56fd\u9645 (CC BY-NC-SA 4.0) \u8bb8\u53ef\u534f\u8bae\u8fdb\u884c\u8bb8\u53ef\u3002</p> FFB6D \u590d\u73b0          <ul> <li> Docker  653  213  5 mins              1734024510 </li> <li> Conda  293  96  2 mins              1734024510 </li> </ul> EECS 498-007          <ul> <li> Pytorch  564  45  2 mins              1734024510 </li> <li> KNN  374  100  2 mins              1734012860 </li> <li> Linear Classifer  0  0 mins              0 </li> </ul> CS231n          <ul> <li> Numpy  49  104  1 mins              1734024510 </li> <li> Notes  8852  30 mins              1734012860 </li> </ul>"},{"location":"AI/Dive%20into%20Deep%20Learning/","title":"Dive into Deep Learning","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#dive-into-deep-learning","title":"Dive into Deep Learning","text":"<p> \u7ea6 1547 \u4e2a\u5b57  387 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 13 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"AI/Dive%20into%20Deep%20Learning/#1","title":"1 \u5f15\u8a00","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#2","title":"2 \u9884\u5907\u77e5\u8bc6","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#21","title":"2.1 \u6570\u636e\u64cd\u4f5c","text":"<ul> <li>tensor</li> <li>ndarray (MXNet)</li> <li>Tensor (TensorFlow)</li> </ul> Python<pre><code>x = torch.arrange(12)\nx.shape\nx.numel()\nx.reshape(3, 4)\ntorch.zeros((2, 3, 4))\ntorch.ones((2, 3, 4))\ntorch.randn(3, 4)\n</code></pre> <ul> <li>elementwise\uff1a<ul> <li>+</li> <li>-</li> <li>-</li> <li>/</li> <li>exp ()</li> <li>==</li> </ul> </li> <li>concatenate</li> </ul> Python<pre><code>torch.cat((X, Y), dim = 0) # \u7ad6\u7740\u52a0\ntorch.cat((X, Y), dim = 1) # \u6a2a\u7740\u52a0\nx.sum()\n</code></pre> <ul> <li>broadcasting mechanism<ul> <li>\u590d\u5236\u62d3\u5c55\u5230\u5f62\u72b6\u4e00\u81f4\u540e\u76f8\u52a0</li> </ul> </li> <li>\u7d22\u5f15+\u5207\u7247</li> <li>\u5207\u7247\u4fdd\u6301\u5730\u5740\u4e0d\u53d8\uff1a\u8282\u7701\u5185\u5b58</li> <li>ndarry &lt;-&gt; Tensor</li> <li>item ()</li> </ul>"},{"location":"AI/Dive%20into%20Deep%20Learning/#22","title":"2.2 \u6570\u636e\u9884\u5904\u7406","text":"<ul> <li>pandas</li> <li>read_csv ()</li> <li>NaN<ul> <li>fillna (inputs.mean ())</li> <li>np.array (inputs. to_numpy (dtype = float))</li> </ul> </li> </ul>"},{"location":"AI/Dive%20into%20Deep%20Learning/#23","title":"2.3 \u7ebf\u6027\u4ee3\u6570","text":"<ul> <li>scalar</li> <li>variable</li> <li>space</li> <li>element / component</li> <li>dimension <ul> <li>len ()</li> <li>shape</li> </ul> </li> <li>square matrix</li> <li>transpose<ul> <li>A.T</li> </ul> </li> <li>symmetric matrix<ul> <li>A == A.T</li> </ul> </li> <li>channel</li> <li>Hadamard product</li> </ul> \\[ \\begin{split}\\mathbf{A} \\odot \\mathbf{B} = \\begin{bmatrix} a_{11}  b_{11} &amp; a_{12}  b_{12} &amp; \\dots  &amp; a_{1n}  b_{1n} \\\\ a_{21}  b_{21} &amp; a_{22}  b_{22} &amp; \\dots  &amp; a_{2n}  b_{2n} \\\\ \\vdots &amp; \\vdots &amp; \\ddots &amp; \\vdots \\\\ a_{m1}  b_{m1} &amp; a_{m2}  b_{m2} &amp; \\dots  &amp; a_{mn}  b_{mn} \\end{bmatrix}.\\end{split} \\] <ul> <li>A.sum (axis = 0) # \u7ad6\u7740\u6c42\u548c</li> <li>A.sum (axis = [0, 1]) = A.sum ()</li> <li>A.mean () = A.sum () / A.size ()</li> <li>A.cumsum (axis = 0)</li> <li>dot product<ul> <li>torch.dot (x, y) = torch.sum (x * y)</li> <li>weighted average</li> </ul> </li> <li>matrix-vector product<ul> <li>torch.mv (A, x)</li> </ul> </li> <li>matrix-matric multiplication<ul> <li>torch.mm (A, B)</li> </ul> </li> <li>norm<ol> <li>\\(f(\\alpha \\mathbf{x}) = |\\alpha| f(\\mathbf{x}).\\)</li> <li>\\((\\mathbf{x} + \\mathbf{y}) \\leq f(\\mathbf{x}) + f(\\mathbf{y}).\\)</li> <li>\\(f(\\mathbf{x}) \\geq 0.\\)</li> </ol> </li> </ul>"},{"location":"AI/Dive%20into%20Deep%20Learning/#24","title":"2.4 \u5fae\u79ef\u5206","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#241","title":"2.4.1 \u5bfc\u6570\u548c\u5fae\u5206","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#242","title":"2.4.2 \u504f\u5bfc\u6570","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#243","title":"2.4.3 \u68af\u5ea6","text":"\\[ \\nabla_{\\mathbf{x}} f(\\mathbf{x}) = \\bigg[\\frac{\\partial f(\\mathbf{x})}{\\partial x_1}, \\frac{\\partial f(\\mathbf{x})}{\\partial x_2}, \\ldots, \\frac{\\partial f(\\mathbf{x})}{\\partial x_n}\\bigg]^\\top, \\] \\[ \\nabla_{\\mathbf{x}} \\mathbf{A} \\mathbf{x} = \\mathbf{A}^\\top \\] \\[ \\nabla_{\\mathbf{x}} \\mathbf{x}^\\top \\mathbf{A} = \\mathbf{A} \\] \\[ \\nabla_{\\mathbf{x}} \\mathbf{x}^\\top \\mathbf{A} \\mathbf{x} = (\\mathbf{A} + \\mathbf{A}^\\top)\\mathbf{x} \\] \\[ \\nabla_{\\mathbf{x}} \\|\\mathbf{x} \\|^2 = \\nabla_{\\mathbf{x}} \\mathbf{x}^\\top \\mathbf{x} = 2\\mathbf{x} \\] \\[ \\nabla_{\\mathbf{X}} \\|\\mathbf{X} \\|_F^2 = 2\\mathbf{X} \\]"},{"location":"AI/Dive%20into%20Deep%20Learning/#244","title":"2.4.4 \u94fe\u5f0f\u6cd5\u5219","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#245","title":"2.4.5 \u5c0f\u7ed3","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#25-automatic-differentiation","title":"2.5 \u81ea\u52a8\u5fae\u5206\uff08automatic differentiation\uff09","text":"<ul> <li>computational graph</li> <li>backpropagate</li> </ul> Python<pre><code>x.requires_grad_(True)  # \u7b49\u4ef7\u4e8ex=torch.arange(4.0,requires_grad=True)\nx.grad  # \u9ed8\u8ba4\u503c\u662fNone\ny = 2 * torch.dot(x, x)\ny.backward()\nx.grad\nx.grad == 4 * x\n</code></pre>"},{"location":"AI/Dive%20into%20Deep%20Learning/#251","title":"2.5.1 \u975e\u6807\u91cf\u53d8\u91cf\u7684\u53cd\u5411\u4f20\u64ad","text":"Python<pre><code># \u5bf9\u975e\u6807\u91cf\u8c03\u7528backward\u9700\u8981\u4f20\u5165\u4e00\u4e2agradient\u53c2\u6570\uff0c\u8be5\u53c2\u6570\u6307\u5b9a\u5fae\u5206\u51fd\u6570\u5173\u4e8eself\u7684\u68af\u5ea6\u3002\n# \u672c\u4f8b\u53ea\u60f3\u6c42\u504f\u5bfc\u6570\u7684\u548c\uff0c\u6240\u4ee5\u4f20\u9012\u4e00\u4e2a1\u7684\u68af\u5ea6\u662f\u5408\u9002\u7684\nx.grad.zero_()\ny = x * x\n# \u7b49\u4ef7\u4e8ey.backward(torch.ones(len(x)))\ny.sum().backward()\nx.grad\n</code></pre>"},{"location":"AI/Dive%20into%20Deep%20Learning/#252","title":"2.5.2 \u5206\u79bb\u8ba1\u7b97","text":"Python<pre><code>x.grad.zero_()\ny = x * x\nu = y.detach()\nz = u * x\n\nz.sum().backward()\nx.grad == u\n</code></pre>"},{"location":"AI/Dive%20into%20Deep%20Learning/#26","title":"2.6 \u6982\u7387","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#261","title":"2.6.1 \u57fa\u672c\u6982\u7387\u8bba","text":"<ul> <li>sampling</li> <li>distribution</li> <li>multinomial distribution</li> </ul> Python<pre><code>fair_probs = torch.ones([6]) / 6\nmultinomial.Multinomial(10, fair_probs).sample() # \u591a\u4e2a\u6837\u672c\n</code></pre>"},{"location":"AI/Dive%20into%20Deep%20Learning/#262","title":"2.6.2 \u5904\u7406\u591a\u4e2a\u968f\u673a\u53d8\u91cf","text":"<ul> <li>joint probability</li> <li>conditional probability</li> <li>Bayes\u2019 theorem</li> </ul> \\[ P(A \\mid B) = \\frac{P(B \\mid A) P(A)}{P(B)}.  \\] <ul> <li>\u5176\u4e2d P (A, B) \u662f\u4e00\u4e2a\u8054\u5408\u5206\u5e03 (joint distribution)\uff0c\u00a0P (A\u2223B) \u662f\u4e00\u4e2a\u6761\u4ef6\u5206\u5e03 (conditional distribution)</li> <li>marginalization<ul> <li>marginal probability</li> <li>marginal distribution</li> </ul> </li> <li>conditionally independent</li> </ul> <p>$$  P(A, B \\mid C) = P(A \\mid C)P(B \\mid C)  $$</p> \\[ A \\perp B \\mid C  \\] <ul> <li>expectation</li> </ul> \\[ E[X] = \\sum_{x} x P(X = x).  \\] \\[ E_{x \\sim P}[f(x)] = \\sum_x f(x) P(x).  \\] <ul> <li>standard deviation</li> </ul> \\[ \\mathrm{Var}[X] = E\\left[(X - E[X])^2\\right] = E[X^2] - E[X]^2.  \\] \\[ \\mathrm{Var}[f(x)] = E\\left[\\left(f(x) - E[f(x)]\\right)^2\\right].  \\]"},{"location":"AI/Dive%20into%20Deep%20Learning/#3","title":"3 \u7ebf\u6027\u795e\u7ecf\u7f51\u7edc","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#31","title":"3.1 \u7ebf\u6027\u56de\u5f52","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#311","title":"3.1.1 \u7ebf\u6027\u56de\u5f52\u7684\u57fa\u672c\u5143\u7d20","text":"<ul> <li>regression</li> <li>prediction / inference</li> <li>training set</li> <li>sample / data point / data instance</li> <li>label / target</li> <li>feature / covariate</li> </ul> \\[ \\mathrm{price} = w_{\\mathrm{area}} \\cdot \\mathrm{area} + w_{\\mathrm{age}} \\cdot \\mathrm{age} + b.  \\] <ul> <li>weight</li> <li>bias / offset / intercept</li> <li>affine transformation<ul> <li>linear transformation</li> <li>translation</li> </ul> </li> <li>model parameters</li> <li>loss function</li> </ul> \\[ l^{(i)}(\\mathbf{w}, b) = \\frac{1}{2} \\left(\\hat{y}^{(i)} - y^{(i)}\\right)^2. \\] \\[ L(\\mathbf{w}, b) =\\frac{1}{n}\\sum_{i=1}^n l^{(i)}(\\mathbf{w}, b) =\\frac{1}{n} \\sum_{i=1}^n \\frac{1}{2}\\left(\\mathbf{w}^\\top \\mathbf{x}^{(i)} + b - y^{(i)}\\right)^2. \\] \\[ \\mathbf{w}^*, b^* = \\operatorname*{argmin}_{\\mathbf{w}, b}\\  L(\\mathbf{w}, b). \\] \\[ \\mathbf{w}^{*} = (\\mathbf X^\\top \\mathbf X)^{-1}\\mathbf X^\\top \\mathbf{y}. \\] <ul> <li>analytical solution</li> <li>gradient descent<ul> <li>minibatch stochastic gradient descent</li> </ul> </li> </ul> \\[ (\\mathbf{w},b) \\leftarrow (\\mathbf{w},b) - \\frac{\\eta}{|\\mathcal{B}|} \\sum_{i \\in \\mathcal{B}} \\partial_{(\\mathbf{w},b)} l^{(i)}(\\mathbf{w},b). \\] <ol> <li>\u521d\u59cb\u5316\u6a21\u578b\u53c2\u6570\u7684\u503c\uff0c\u5982\u968f\u673a\u521d\u59cb\u5316</li> <li>\u4ece\u6570\u636e\u96c6\u4e2d\u968f\u673a\u62bd\u53d6\u5c0f\u6279\u91cf\u6837\u672c\u4e14\u5728\u8d1f\u68af\u5ea6\u7684\u65b9\u5411\u4e0a\u66f4\u65b0\u53c2\u6570\uff0c\u5e76\u4e0d\u65ad\u8fed\u4ee3\u8fd9\u4e00\u6b65\u9aa4 - hyperparameter<ul> <li>\\(|\\mathcal{B}|\\): batch size</li> <li>\\(\\eta\\): learning rate</li> <li>hyperparameter tuning</li> <li>validationg dataset</li> <li>generalization</li> </ul> </li> </ol>"},{"location":"AI/Dive%20into%20Deep%20Learning/#312","title":"3.1.2 \u77e2\u91cf\u5316\u52a0\u901f","text":"<ul> <li>\u77e2\u91cf\u5316\u4ee3\u7801</li> </ul>"},{"location":"AI/Dive%20into%20Deep%20Learning/#313","title":"3.1.3 \u6b63\u6001\u5206\u5e03\u4e0e\u5e73\u65b9\u635f\u5931","text":"<ul> <li>normal distribution / Gaussian distribution</li> </ul> \\[ p(x) = \\frac{1}{\\sqrt{2 \\pi \\sigma^2}} \\exp\\left(-\\frac{1}{2 \\sigma^2} (x - \\mu)^2\\right). \\] \\[ y = \\mathbf{w}^\\top \\mathbf{x} + b + \\epsilon, \\] <ul> <li>\u5176\u4e2d \\(\\epsilon \\sim \\mathcal{N}(0, \\sigma^2)\\). \u56e0\u6b64 y \u7684 likelihood:</li> </ul> \\[ P(y \\mid \\mathbf{x}) = \\frac{1}{\\sqrt{2 \\pi \\sigma^2}} \\exp\\left(-\\frac{1}{2 \\sigma^2} (y - \\mathbf{w}^\\top \\mathbf{x} - b)^2\\right). \\] \\[ P(\\mathbf y \\mid \\mathbf X) = \\prod_{i=1}^{n} p(y^{(i)}|\\mathbf{x}^{(i)}). \\] \\[ -\\log P(\\mathbf y \\mid \\mathbf X) = \\sum_{i=1}^n \\frac{1}{2} \\log(2 \\pi \\sigma^2) + \\frac{1}{2 \\sigma^2} \\left(y^{(i)} - \\mathbf{w}^\\top \\mathbf{x}^{(i)} - b\\right)^2. \\]"},{"location":"AI/Dive%20into%20Deep%20Learning/#314","title":"3.1.4 \u4ece\u7ebf\u6027\u56de\u5f52\u5230\u795e\u7ecf\u7f51\u7edc","text":"<ul> <li>feature dimensionality</li> <li>fully-connected layer / dense layer</li> </ul>"},{"location":"AI/Dive%20into%20Deep%20Learning/#32","title":"3.2 \u7ebf\u6027\u56de\u5f52\u7684\u4ece\u96f6\u5f00\u59cb\u5b9e\u73b0","text":"Python<pre><code>%matplotlib inline\nimport random\nimport torch\nfrom d2l import torch as d2l\ndef synthetic_data(w, b, num_examples):  #@save\n    \"\"\"\u751f\u6210y=Xw+b+\u566a\u58f0\"\"\"\n    X = torch.normal(0, 1, (num_examples, len(w)))\n    y = torch.matmul(X, w) + b\n    y += torch.normal(0, 0.01, y.shape)\n    return X, y.reshape((-1, 1))\n\ntrue_w = torch.tensor([2, -3.4])\ntrue_b = 4.2\nfeatures, labels = synthetic_data(true_w, true_b, 1000)\n\ndef data_iter(batch_size, features, labels):\n    num_examples = len(features)\n    indices = list(range(num_examples))\n    # \u8fd9\u4e9b\u6837\u672c\u662f\u968f\u673a\u8bfb\u53d6\u7684\uff0c\u6ca1\u6709\u7279\u5b9a\u7684\u987a\u5e8f\n    random.shuffle(indices)\n    for i in range(0, num_examples, batch_size):\n        batch_indices = torch.tensor(\n            indices[i: min(i + batch_size, num_examples)])\n        yield features[batch_indices], labels[batch_indices]\n\nw = torch.normal(0, 0.01, size=(2,1), requires_grad=True)\nb = torch.zeros(1, requires_grad=True)\n\ndef linreg(X, w, b):  #@save\n    \"\"\"\u7ebf\u6027\u56de\u5f52\u6a21\u578b\"\"\"\n    return torch.matmul(X, w) + b\n\ndef squared_loss(y_hat, y):  #@save\n    \"\"\"\u5747\u65b9\u635f\u5931\"\"\"\n    return (y_hat - y.reshape(y_hat.shape)) ** 2 / 2\n\ndef sgd(params, lr, batch_size):  #@save\n    \"\"\"\u5c0f\u6279\u91cf\u968f\u673a\u68af\u5ea6\u4e0b\u964d\"\"\"\n    with torch.no_grad():\n        for param in params:\n            param -= lr * param.grad / batch_size\n            param.grad.zero_()\n\nlr = 0.03\nnum_epochs = 3\nnet = linreg\nloss = squared_loss\n\nfor epoch in range(num_epochs):\n    for X, y in data_iter(batch_size, features, labels):\n        l = loss(net(X, w, b), y)  # X\u548cy\u7684\u5c0f\u6279\u91cf\u635f\u5931\n        # \u56e0\u4e3al\u5f62\u72b6\u662f(batch_size,1)\uff0c\u800c\u4e0d\u662f\u4e00\u4e2a\u6807\u91cf\u3002l\u4e2d\u7684\u6240\u6709\u5143\u7d20\u88ab\u52a0\u5230\u4e00\u8d77\uff0c\n        # \u5e76\u4ee5\u6b64\u8ba1\u7b97\u5173\u4e8e[w,b]\u7684\u68af\u5ea6\n        l.sum().backward()\n        sgd([w, b], lr, batch_size)  # \u4f7f\u7528\u53c2\u6570\u7684\u68af\u5ea6\u66f4\u65b0\u53c2\u6570\n    with torch.no_grad():\n        train_l = loss(net(features, w, b), labels)\n        print(f'epoch {epoch + 1}, loss {float(train_l.mean()):f}')\n</code></pre>"},{"location":"AI/Dive%20into%20Deep%20Learning/#33","title":"3.3 \u7ebf\u6027\u56de\u5f52\u7684\u7b80\u6d01\u5b9e\u73b0","text":"Python<pre><code>import numpy as np\nimport torch\nfrom torch.utils import data\nfrom d2l import torch as d2l\n\ntrue_w = torch.tensor([2, -3.4])\ntrue_b = 4.2\nfeatures, labels = d2l.synthetic_data(true_w, true_b, 1000) # \u751f\u6210\u6570\u636e\u96c6\n\ndef load_array(data_arrays, batch_size, is_train=True):  #@save\n    \"\"\"\u6784\u9020\u4e00\u4e2aPyTorch\u6570\u636e\u8fed\u4ee3\u5668\"\"\"\n    dataset = data.TensorDataset(*data_arrays)\n    return data.DataLoader(dataset, batch_size, shuffle=is_train)\n\nbatch_size = 10\ndata_iter = load_array((features, labels), batch_size) # \u8bfb\u53d6\u6570\u636e\u96c6\n\n# nn\u662f\u795e\u7ecf\u7f51\u7edc\u7684\u7f29\u5199\nfrom torch import nn\n\nnet = nn.Sequential(nn.Linear(2, 1)) # \u5b9a\u4e49\u6a21\u578b \uff08\u8f93\u5165\uff0c\u8f93\u51fa\uff09\u7279\u5f81\u5f62\u72b6\nnet[0].weight.data.normal_(0, 0.01)\nnet[0].bias.data.fill_(0) # \u521d\u59cb\u5316\u6a21\u578b\u53c2\u6570\nloss = nn.MSELoss() # \u5b9a\u4e49\u635f\u5931\u51fd\u6570\ntrainer = torch.optim.SGD(net.parameters(), lr=0.03) # \u5b9a\u4e49\u4f18\u5316\u7b97\u6cd5\n\n# \u8bad\u7ec3\nnum_epochs = 3\nfor epoch in range(num_epochs):\n    for X, y in data_iter:\n        l = loss(net(X) ,y)\n        trainer.zero_grad()\n        l.backward()\n        trainer.step()\n    l = loss(net(features), labels)\n    print(f'epoch {epoch + 1}, loss {l:f}')\n\nw = net[0].weight.data\nprint('w\u7684\u4f30\u8ba1\u8bef\u5dee\uff1a', true_w - w.reshape(true_w.shape))\nb = net[0].bias.data\nprint('b\u7684\u4f30\u8ba1\u8bef\u5dee\uff1a', true_b - b)\n</code></pre>"},{"location":"AI/Dive%20into%20Deep%20Learning/#34-softmax","title":"3.4 softmax \u56de\u5f52","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#341","title":"3.4.1 \u5206\u7c7b\u95ee\u9898","text":"<ul> <li>one-hot encoding</li> </ul> \\[ y \\in \\{(1, 0, 0), (0, 1, 0), (0, 0, 1)\\}. \\]"},{"location":"AI/Dive%20into%20Deep%20Learning/#342","title":"3.4.2 \u7f51\u7edc\u67b6\u6784","text":"<ul> <li>affine function</li> <li>logit</li> </ul> \\[ \\begin{split}\\begin{aligned} o_1 &amp;= x_1 w_{11} + x_2 w_{12} + x_3 w_{13} + x_4 w_{14} + b_1,\\\\ o_2 &amp;= x_1 w_{21} + x_2 w_{22} + x_3 w_{23} + x_4 w_{24} + b_2,\\\\ o_3 &amp;= x_1 w_{31} + x_2 w_{32} + x_3 w_{33} + x_4 w_{34} + b_3. \\end{aligned}\\end{split} \\]"},{"location":"AI/Dive%20into%20Deep%20Learning/#343","title":"3.4.3 \u5168\u8fde\u63a5\u5c42\u7684\u53c2\u6570\u5f00\u9500","text":"<ul> <li>\u4e0d\u77e5\u9053\u662f\u4ec0\u4e48\u4e1c\u897f</li> </ul>"},{"location":"AI/Dive%20into%20Deep%20Learning/#344-softmax","title":"3.4.4 softmax \u8fd0\u7b97","text":"<ul> <li>calibration</li> <li>choice model</li> </ul> \\[ \\hat{\\mathbf{y}} = \\mathrm{softmax}(\\mathbf{o})\\quad \\text{\u5176\u4e2d}\\quad \\hat{y}_j = \\frac{\\exp(o_j)}{\\sum_k \\exp(o_k)} \\] \\[ \\operatorname*{argmax}_j \\hat y_j = \\operatorname*{argmax}_j o_j. \\] <ul> <li>linear model</li> </ul>"},{"location":"AI/Dive%20into%20Deep%20Learning/#345","title":"3.4.5 \u5c0f\u6279\u6837\u672c\u7684\u77e2\u91cf\u5316","text":"\\[ \\begin{split}\\begin{aligned} \\mathbf{O} &amp;= \\mathbf{X} \\mathbf{W} + \\mathbf{b}, \\\\ \\hat{\\mathbf{Y}} &amp; = \\mathrm{softmax}(\\mathbf{O}). \\end{aligned}\\end{split} \\]"},{"location":"AI/Dive%20into%20Deep%20Learning/#346","title":"3.4.6 \u635f\u5931\u51fd\u6570","text":"\\[ P(\\mathbf{Y} \\mid \\mathbf{X}) = \\prod_{i=1}^n P(\\mathbf{y}^{(i)} \\mid \\mathbf{x}^{(i)}). \\] \\[ -\\log P(\\mathbf{Y} \\mid \\mathbf{X}) = \\sum_{i=1}^n -\\log P(\\mathbf{y}^{(i)} \\mid \\mathbf{x}^{(i)}) = \\sum_{i=1}^n l(\\mathbf{y}^{(i)}, \\hat{\\mathbf{y}}^{(i)}), \\] \\[ l(\\mathbf{y}, \\hat{\\mathbf{y}}) = - \\sum_{j=1}^q y_j \\log \\hat{y}_j. \\] <ul> <li>cross-entropy loss</li> </ul> \\[ \\begin{split}\\begin{aligned} l(\\mathbf{y}, \\hat{\\mathbf{y}}) &amp;=  - \\sum_{j=1}^q y_j \\log \\frac{\\exp(o_j)}{\\sum_{k=1}^q \\exp(o_k)} \\\\ &amp;= \\sum_{j=1}^q y_j \\log \\sum_{k=1}^q \\exp(o_k) - \\sum_{j=1}^q y_j o_j\\\\ &amp;= \\log \\sum_{k=1}^q \\exp(o_k) - \\sum_{j=1}^q y_j o_j. \\end{aligned}\\end{split} \\] \\[ \\partial_{o_j} l(\\mathbf{y}, \\hat{\\mathbf{y}}) = \\frac{\\exp(o_j)}{\\sum_{k=1}^q \\exp(o_k)} - y_j = \\mathrm{softmax}(\\mathbf{o})_j - y_j. \\]"},{"location":"AI/Dive%20into%20Deep%20Learning/#347","title":"3.4.7 \u4fe1\u606f\u8bba\u57fa\u7840","text":"<ul> <li>information theory</li> <li>entropy</li> </ul> \\[ H[P] = \\sum_j - P(j) \\log P(j). \\]"},{"location":"AI/Dive%20into%20Deep%20Learning/#348","title":"3.4.8 \u6a21\u578b\u9884\u6d4b\u548c\u8bc4\u4f30","text":"<ul> <li>accuracy</li> </ul>"},{"location":"AI/Dive%20into%20Deep%20Learning/#35","title":"3.5 \u56fe\u50cf\u5206\u7c7b\u6570\u636e\u96c6","text":"Python<pre><code>%matplotlib inline\nimport torch\nimport torchvision\nfrom torch.utils import data\nfrom torchvision import transforms\nfrom d2l import torch as d2l\n\nd2l.use_svg_display()\n\n# \u901a\u8fc7ToTensor\u5b9e\u4f8b\u5c06\u56fe\u50cf\u6570\u636e\u4ecePIL\u7c7b\u578b\u53d8\u6362\u621032\u4f4d\u6d6e\u70b9\u6570\u683c\u5f0f\uff0c\n# \u5e76\u9664\u4ee5255\u4f7f\u5f97\u6240\u6709\u50cf\u7d20\u7684\u6570\u503c\u5747\u57280\uff5e1\u4e4b\u95f4\ntrans = transforms.ToTensor()\nmnist_train = torchvision.datasets.FashionMNIST(\n    root=\"../data\", train=True, transform=trans, download=True)\nmnist_test = torchvision.datasets.FashionMNIST(\n    root=\"../data\", train=False, transform=trans, download=True)\n\ndef get_fashion_mnist_labels(labels):  #@save\n    \"\"\"\u8fd4\u56deFashion-MNIST\u6570\u636e\u96c6\u7684\u6587\u672c\u6807\u7b7e\"\"\"\n    text_labels = ['t-shirt', 'trouser', 'pullover', 'dress', 'coat',\n                   'sandal', 'shirt', 'sneaker', 'bag', 'ankle boot']\n    return [text_labels[int(i)] for i in labels]\n\ndef show_images(imgs, num_rows, num_cols, titles=None, scale=1.5):  #@save\n    \"\"\"\u7ed8\u5236\u56fe\u50cf\u5217\u8868\"\"\"\n    figsize = (num_cols * scale, num_rows * scale)\n    _, axes = d2l.plt.subplots(num_rows, num_cols, figsize=figsize)\n    axes = axes.flatten()\n    for i, (ax, img) in enumerate(zip(axes, imgs)):\n        if torch.is_tensor(img):\n            # \u56fe\u7247\u5f20\u91cf\n            ax.imshow(img.numpy())\n        else:\n            # PIL\u56fe\u7247\n            ax.imshow(img)\n        ax.axes.get_xaxis().set_visible(False)\n        ax.axes.get_yaxis().set_visible(False)\n        if titles:\n            ax.set_title(titles[i])\n    return axes\n\nbatch_size = 256\n\ndef get_dataloader_workers():  #@save\n    \"\"\"\u4f7f\u75284\u4e2a\u8fdb\u7a0b\u6765\u8bfb\u53d6\u6570\u636e\"\"\"\n    return 4\n\ntrain_iter = data.DataLoader(mnist_train, batch_size, shuffle=True,\n                             num_workers=get_dataloader_workers())\n\ndef load_data_fashion_mnist(batch_size, resize=None):  #@save\n    \"\"\"\u4e0b\u8f7dFashion-MNIST\u6570\u636e\u96c6\uff0c\u7136\u540e\u5c06\u5176\u52a0\u8f7d\u5230\u5185\u5b58\u4e2d\"\"\"\n    trans = [transforms.ToTensor()]\n    if resize:\n        trans.insert(0, transforms.Resize(resize))\n    trans = transforms.Compose(trans)\n    mnist_train = torchvision.datasets.FashionMNIST(\n        root=\"../data\", train=True, transform=trans, download=True)\n    mnist_test = torchvision.datasets.FashionMNIST(\n        root=\"../data\", train=False, transform=trans, download=True)\n    return (data.DataLoader(mnist_train, batch_size, shuffle=True,\n                            num_workers=get_dataloader_workers()),\n            data.DataLoader(mnist_test, batch_size, shuffle=False,\n                            num_workers=get_dataloader_workers()))\n\ntrain_iter, test_iter = load_data_fashion_mnist(32, resize=64)\nfor X, y in train_iter:\n    print(X.shape, X.dtype, y.shape, y.dtype)\n    break\n</code></pre>"},{"location":"AI/Dive%20into%20Deep%20Learning/#36-softmax","title":"3.6 softmax \u56de\u5f52\u7684\u4ece\u96f6\u5f00\u59cb\u5b9e\u73b0","text":"Python<pre><code>import torch\nfrom IPython import display\nfrom d2l import torch as d2l\n\nbatch_size = 256\ntrain_iter, test_iter = d2l.load_data_fashion_mnist(batch_size)\n\nnum_inputs = 784\nnum_outputs = 10\n\nW = torch.normal(0, 0.01, size=(num_inputs, num_outputs), requires_grad=True)\nb = torch.zeros(num_outputs, requires_grad=True) # \u521d\u59cb\u5316\u6a21\u578b\u53c2\u6570\n\nX = torch.tensor([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])\nX.sum(0, keepdim=True), X.sum(1, keepdim=True) \n\ndef softmax(X):\n    X_exp = torch.exp(X)\n    partition = X_exp.sum(1, keepdim=True)\n    return X_exp / partition  # \u8fd9\u91cc\u5e94\u7528\u4e86\u5e7f\u64ad\u673a\u5236\n\nX = torch.normal(0, 1, (2, 5))\nX_prob = softmax(X)\nX_prob, X_prob.sum(1) # \u5b9a\u4e49softmax\u64cd\u4f5c\n\ndef net(X):\n    return softmax(torch.matmul(X.reshape((-1, W.shape[0])), W) + b) # \u5b9a\u4e49\u6a21\u578b\n\ny = torch.tensor([0, 2])\ny_hat = torch.tensor([[0.1, 0.3, 0.6], [0.3, 0.2, 0.5]])\ny_hat[[0, 1], y] \ndef cross_entropy(y_hat, y):\n    return - torch.log(y_hat[range(len(y_hat)), y])\n\ncross_entropy(y_hat, y) # \u5b9a\u4e49\u635f\u5931\u51fd\u6570\n\ndef accuracy(y_hat, y):  #@save\n    \"\"\"\u8ba1\u7b97\u9884\u6d4b\u6b63\u786e\u7684\u6570\u91cf\"\"\"\n    if len(y_hat.shape) &gt; 1 and y_hat.shape[1] &gt; 1:\n        y_hat = y_hat.argmax(axis=1)\n    cmp = y_hat.type(y.dtype) == y\n    return float(cmp.type(y.dtype).sum())\n\ndef evaluate_accuracy(net, data_iter):  #@save\n    \"\"\"\u8ba1\u7b97\u5728\u6307\u5b9a\u6570\u636e\u96c6\u4e0a\u6a21\u578b\u7684\u7cbe\u5ea6\"\"\"\n    if isinstance(net, torch.nn.Module):\n        net.eval()  # \u5c06\u6a21\u578b\u8bbe\u7f6e\u4e3a\u8bc4\u4f30\u6a21\u5f0f\n    metric = Accumulator(2)  # \u6b63\u786e\u9884\u6d4b\u6570\u3001\u9884\u6d4b\u603b\u6570\n    with torch.no_grad():\n        for X, y in data_iter:\n            metric.add(accuracy(net(X), y), y.numel())\n    return metric[0] / metric[1]\n\nclass Accumulator:  #@save\n    \"\"\"\u5728n\u4e2a\u53d8\u91cf\u4e0a\u7d2f\u52a0\"\"\"\n    def __init__(self, n):\n        self.data = [0.0] * n\n\n    def add(self, *args):\n        self.data = [a + float(b) for a, b in zip(self.data, args)]\n\n    def reset(self):\n        self.data = [0.0] * len(self.data)\n\n    def __getitem__(self, idx):\n        return self.data[idx]\n\nevaluate_accuracy(net, test_iter) # \u5206\u7c7b\u7cbe\u5ea6\n\ndef train_epoch_ch3(net, train_iter, loss, updater):  #@save\n    \"\"\"\u8bad\u7ec3\u6a21\u578b\u4e00\u4e2a\u8fed\u4ee3\u5468\u671f\uff08\u5b9a\u4e49\u89c1\u7b2c3\u7ae0\uff09\"\"\"\n    # \u5c06\u6a21\u578b\u8bbe\u7f6e\u4e3a\u8bad\u7ec3\u6a21\u5f0f\n    if isinstance(net, torch.nn.Module):\n        net.train()\n    # \u8bad\u7ec3\u635f\u5931\u603b\u548c\u3001\u8bad\u7ec3\u51c6\u786e\u5ea6\u603b\u548c\u3001\u6837\u672c\u6570\n    metric = Accumulator(3)\n    for X, y in train_iter:\n        # \u8ba1\u7b97\u68af\u5ea6\u5e76\u66f4\u65b0\u53c2\u6570\n        y_hat = net(X)\n        l = loss(y_hat, y)\n        if isinstance(updater, torch.optim.Optimizer):\n            # \u4f7f\u7528PyTorch\u5185\u7f6e\u7684\u4f18\u5316\u5668\u548c\u635f\u5931\u51fd\u6570\n            updater.zero_grad()\n            l.mean().backward()\n            updater.step()\n        else:\n            # \u4f7f\u7528\u5b9a\u5236\u7684\u4f18\u5316\u5668\u548c\u635f\u5931\u51fd\u6570\n            l.sum().backward()\n            updater(X.shape[0])\n        metric.add(float(l.sum()), accuracy(y_hat, y), y.numel())\n    # \u8fd4\u56de\u8bad\u7ec3\u635f\u5931\u548c\u8bad\u7ec3\u7cbe\u5ea6\n    return metric[0] / metric[2], metric[1] / metric[2]\n\nclass Animator:  #@save\n    \"\"\"\u5728\u52a8\u753b\u4e2d\u7ed8\u5236\u6570\u636e\"\"\"\n    def __init__(self, xlabel=None, ylabel=None, legend=None, xlim=None,\n                 ylim=None, xscale='linear', yscale='linear',\n                 fmts=('-', 'm--', 'g-.', 'r:'), nrows=1, ncols=1,\n                 figsize=(3.5, 2.5)):\n        # \u589e\u91cf\u5730\u7ed8\u5236\u591a\u6761\u7ebf\n        if legend is None:\n            legend = []\n        d2l.use_svg_display()\n        self.fig, self.axes = d2l.plt.subplots(nrows, ncols, figsize=figsize)\n        if nrows * ncols == 1:\n            self.axes = [self.axes, ]\n        # \u4f7f\u7528lambda\u51fd\u6570\u6355\u83b7\u53c2\u6570\n        self.config_axes = lambda: d2l.set_axes(\n            self.axes[0], xlabel, ylabel, xlim, ylim, xscale, yscale, legend)\n        self.X, self.Y, self.fmts = None, None, fmts\n\n    def add(self, x, y):\n        # \u5411\u56fe\u8868\u4e2d\u6dfb\u52a0\u591a\u4e2a\u6570\u636e\u70b9\n        if not hasattr(y, \"__len__\"):\n            y = [y]\n        n = len(y)\n        if not hasattr(x, \"__len__\"):\n            x = [x] * n\n        if not self.X:\n            self.X = [[] for _ in range(n)]\n        if not self.Y:\n            self.Y = [[] for _ in range(n)]\n        for i, (a, b) in enumerate(zip(x, y)):\n            if a is not None and b is not None:\n                self.X[i].append(a)\n                self.Y[i].append(b)\n        self.axes[0].cla()\n        for x, y, fmt in zip(self.X, self.Y, self.fmts):\n            self.axes[0].plot(x, y, fmt)\n        self.config_axes()\n        display.display(self.fig)\n        display.clear_output(wait=True)\n\ndef train_ch3(net, train_iter, test_iter, loss, num_epochs, updater):  #@save\n    \"\"\"\u8bad\u7ec3\u6a21\u578b\uff08\u5b9a\u4e49\u89c1\u7b2c3\u7ae0\uff09\"\"\"\n    animator = Animator(xlabel='epoch', xlim=[1, num_epochs], ylim=[0.3, 0.9],\n                        legend=['train loss', 'train acc', 'test acc'])\n    for epoch in range(num_epochs):\n        train_metrics = train_epoch_ch3(net, train_iter, loss, updater)\n        test_acc = evaluate_accuracy(net, test_iter)\n        animator.add(epoch + 1, train_metrics + (test_acc,))\n    train_loss, train_acc = train_metrics\n    assert train_loss &lt; 0.5, train_loss\n    assert train_acc &lt;= 1 and train_acc &gt; 0.7, train_acc\n    assert test_acc &lt;= 1 and test_acc &gt; 0.7, test_acc\n\nlr = 0.1\n\ndef updater(batch_size):\n    return d2l.sgd([W, b], lr, batch_size)\n\nnum_epochs = 10\ntrain_ch3(net, train_iter, test_iter, cross_entropy, num_epochs, updater) # \u8bad\u7ec3\n\ndef predict_ch3(net, test_iter, n=6):  #@save\n    \"\"\"\u9884\u6d4b\u6807\u7b7e\uff08\u5b9a\u4e49\u89c1\u7b2c3\u7ae0\uff09\"\"\"\n    for X, y in test_iter:\n        break\n    trues = d2l.get_fashion_mnist_labels(y)\n    preds = d2l.get_fashion_mnist_labels(net(X).argmax(axis=1))\n    titles = [true +'\\n' + pred for true, pred in zip(trues, preds)]\n    d2l.show_images(\n        X[0:n].reshape((n, 28, 28)), 1, n, titles=titles[0:n])\n\npredict_ch3(net, test_iter) # \u9884\u6d4b\n</code></pre>"},{"location":"AI/Dive%20into%20Deep%20Learning/#37-softmax","title":"3.7 softmax \u56de\u5f52\u7684\u7b80\u6d01\u5b9e\u73b0","text":"Python<pre><code>import torch\nfrom torch import nn\nfrom d2l import torch as d2l\n\nbatch_size = 256\ntrain_iter, test_iter = d2l.load_data_fashion_mnist(batch_size)\n\n# PyTorch\u4e0d\u4f1a\u9690\u5f0f\u5730\u8c03\u6574\u8f93\u5165\u7684\u5f62\u72b6\u3002\u56e0\u6b64\uff0c\n# \u6211\u4eec\u5728\u7ebf\u6027\u5c42\u524d\u5b9a\u4e49\u4e86\u5c55\u5e73\u5c42\uff08flatten\uff09\uff0c\u6765\u8c03\u6574\u7f51\u7edc\u8f93\u5165\u7684\u5f62\u72b6\nnet = nn.Sequential(nn.Flatten(), nn.Linear(784, 10))\n\ndef init_weights(m):\n    if type(m) == nn.Linear:\n        nn.init.normal_(m.weight, std=0.01)\n\nnet.apply(init_weights); # \u521d\u59cb\u5316\u6a21\u578b\u53c2\u6570\n</code></pre> \\[ \\begin{split}\\begin{aligned} \\hat y_j &amp; =  \\frac{\\exp(o_j - \\max(o_k))\\exp(\\max(o_k))}{\\sum_k \\exp(o_k - \\max(o_k))\\exp(\\max(o_k))} \\\\ &amp; = \\frac{\\exp(o_j - \\max(o_k))}{\\sum_k \\exp(o_k - \\max(o_k))}. \\end{aligned}\\end{split} \\] \\[ \\begin{split}\\begin{aligned} \\log{(\\hat y_j)} &amp; = \\log\\left( \\frac{\\exp(o_j - \\max(o_k))}{\\sum_k \\exp(o_k - \\max(o_k))}\\right) \\\\ &amp; = \\log{(\\exp(o_j - \\max(o_k)))}-\\log{\\left( \\sum_k \\exp(o_k - \\max(o_k)) \\right)} \\\\ &amp; = o_j - \\max(o_k) -\\log{\\left( \\sum_k \\exp(o_k - \\max(o_k)) \\right)}. \\end{aligned}\\end{split} \\] Python<pre><code>loss = nn.CrossEntropyLoss(reduction='none') # LogSumExp\u6280\u5de7\n\ntrainer = torch.optim.SGD(net.parameters(), lr=0.1) # \u4f18\u5316\u7b97\u6cd5\n\nnum_epochs = 10\nd2l.train_ch3(net, train_iter, test_iter, loss, num_epochs, trainer) # \u8bad\u7ec3\n</code></pre>"},{"location":"AI/Dive%20into%20Deep%20Learning/#_1","title":"\u591a\u5c42\u611f\u77e5\u673a","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_2","title":"\u8fc7\u62df\u5408\u548c\u6b20\u62df\u5408","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#dropout","title":"dropout","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_3","title":"\u6df1\u5ea6\u5b66\u4e60\u8ba1\u7b97","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_4","title":"\u5377\u79ef\u795e\u7ecf\u7f51\u7edc","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#lenet","title":"LeNet","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_5","title":"\u73b0\u4ee3\u5377\u79ef\u795e\u7ecf\u7f51\u7edc","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#alexnet","title":"AlexNet","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#vgg","title":"VGG","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#nin","title":"NiN","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#googlenet","title":"GoogLeNet","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#resnet","title":"ResNet","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#densenet","title":"DenseNet","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_6","title":"\u5faa\u73af\u795e\u7ecf\u7f51\u7edc","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_7","title":"\u73b0\u4ee3\u5faa\u73af\u795e\u7ecf\u7f51\u7edc","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#gru","title":"GRU","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#lstm","title":"LSTM","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#seq2seq","title":"seq2seq","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_8","title":"\u6ce8\u610f\u529b\u673a\u5236","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#nadaraya-watson","title":"Nadaraya-Watson","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#bahdanau","title":"Bahdanau","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#multi-headed-attention","title":"Multi-headed attention","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#transformer","title":"Transformer","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_9","title":"\u4f18\u5316\u7b97\u6cd5","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#adagrad","title":"AdaGrad","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#rmsprop","title":"RMSProp","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#adadelta","title":"Adadelta","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#adam","title":"Adam","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_10","title":"\u8ba1\u7b97\u6027\u80fd","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_11","title":"\u8ba1\u7b97\u673a\u89c6\u89c9","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#ssd","title":"SSD","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#r-cnn","title":"R-CNN","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_12","title":"\u81ea\u7136\u8bed\u8a00\u5904\u7406:\u9884\u8bad\u7ec3","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#word2vec","title":"word2vec","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#glove","title":"GloVe","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#bert","title":"BERT","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_13","title":"\u81ea\u7136\u8bed\u8a00\u5904\u7406:\u5e94\u7528","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/","title":"\u7edf\u8ba1\u5b66\u4e60\u65b9\u6cd5","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#_1","title":"\u7edf\u8ba1\u5b66\u4e60\u65b9\u6cd5","text":"<p> \u7ea6 3356 \u4e2a\u5b57  43 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 17 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#1","title":"1 \u7edf\u8ba1\u5b66\u4e60\u65b9\u6cd5\u6982\u8bba","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#11","title":"1.1 \u7edf\u8ba1\u5b66\u4e60","text":"<ol> <li>\u7edf\u8ba1\u5b66\u4e60\u7684\u7279\u70b9<ol> <li>\u4ee5\u8ba1\u7b97\u673a\u53ca\u7f51\u7edc\u4e3a\u5e73\u53f0</li> <li>\u4ee5\u6570\u636e\u4e3a\u7814\u7a76\u5bf9\u8c61</li> <li>\u76ee\u7684\u662f\u5bf9\u6570\u636e\u8fdb\u884c\u9884\u6d4b\u4e0e\u5206\u6790</li> <li>\u4ea4\u53c9\u5b66\u79d1</li> </ol> </li> <li>\u7edf\u8ba1\u5b66\u4e60\u7684\u5bf9\u8c61<ol> <li>\u662f\u6570\u636e</li> </ol> </li> <li>\u7edf\u8ba1\u5b66\u4e60\u7684\u76ee\u7684</li> <li>\u7edf\u8ba1\u5b66\u4e60\u7684\u65b9\u6cd5<ol> <li>\u4e3b\u8981\u6709<ol> <li>\u76d1\u7763\u5b66\u4e60\uff08\u672c\u4e66\u4e3b\u8981\u8ba8\u8bba\uff09</li> <li>\u975e\u76d1\u7763\u5b66\u4e60</li> <li>\u534a\u76d1\u7763\u5b66\u4e60</li> <li>\u5f3a\u5316\u5b66\u4e60</li> </ol> </li> <li>\u4e09\u8981\u7d20<ol> <li>\u6a21\u578b</li> <li>\u7b56\u7565</li> <li>\u7b97\u6cd5</li> </ol> </li> <li>\u5b9e\u73b0\u6b65\u9aa4<ol> <li>\u5f97\u5230\u4e00\u4e2a\u8bad\u7ec3\u6570\u636e\u96c6\u5408</li> <li>\u786e\u5b9a\u5b66\u4e60\u6a21\u578b\u7684\u96c6\u5408</li> <li>\u786e\u5b9a\u5b66\u4e60\u7684\u7b56\u7565</li> <li>\u786e\u5b9a\u5b66\u4e60\u7684\u7b97\u6cd5</li> <li>\u901a\u8fc7\u5b66\u4e60\u65b9\u6cd5\u9009\u62e9\u6700\u4f18\u6a21\u578b</li> <li>\u5229\u7528\u5b66\u4e60\u7684\u6700\u4f18\u6a21\u578b\u5bf9\u65b0\u6570\u636e\u8fdb\u884c\u9884\u6d4b\u6216\u5206\u6790</li> </ol> </li> </ol> </li> <li>\u7edf\u8ba1\u5b66\u4e60\u7684\u7814\u7a76<ol> <li>\u65b9\u6cd5</li> <li>\u7406\u8bba</li> <li>\u5e94\u7528</li> </ol> </li> <li>\u7edf\u8ba1\u5b66\u4e60\u7684\u91cd\u8981\u6027</li> </ol>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#12","title":"1.2 \u76d1\u7763\u5b66\u4e60","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#121","title":"1.2.1 \u57fa\u672c\u6982\u5ff5","text":"<ol> <li>\u8f93\u5165\u7a7a\u95f4\u3001\u7279\u5f81\u7a7a\u95f4\u4e0e\u8f93\u51fa\u7a7a\u95f4<ol> <li>\u6bcf\u4e2a\u8f93\u5165\u662f\u4e00\u4e2a\u5b9e\u4f8b\uff0c\u901a\u5e38\u7531\u7279\u5f81\u5411\u91cf\u8868\u793a</li> <li>\u76d1\u7763\u5b66\u4e60\u4ece\u8bad\u7ec3\u6570\u636e\u96c6\u5408\u4e2d\u5b66\u4e60\u6a21\u578b\uff0c\u5bf9\u6d4b\u8bd5\u6570\u636e\u8fdb\u884c\u9884\u6d4b</li> <li>\u6839\u636e\u8f93\u5165\u53d8\u91cf\u548c\u8f93\u51fa\u53d8\u91cf\u7684\u4e0d\u540c\u7c7b\u578b<ol> <li>\u56de\u5f52\u95ee\u9898: \u90fd\u8fde\u7eed</li> <li>\u5206\u7c7b\u95ee\u9898: \u8f93\u51fa\u6709\u9650\u79bb\u6563</li> <li>\u6807\u6ce8\u95ee\u9898: \u90fd\u662f\u53d8\u91cf\u5e8f\u5217</li> </ol> </li> </ol> </li> <li>\u8054\u5408\u6982\u7387\u5206\u5e03</li> <li>\u5047\u8bbe\u7a7a\u95f4<ol> <li>\u6a21\u578b\u5c5e\u4e8e\u7531\u8f93\u5165\u7a7a\u95f4\u5230\u8f93\u51fa\u7a7a\u95f4\u7684\u6620\u5c04\u7684\u96c6\u5408\uff0c\u8fd9\u4e2a\u96c6\u5408\u5c31\u662f\u5047\u8bbe\u7a7a\u95f4</li> <li>\u6a21\u578b\u53ef\u4ee5\u662f\uff08\u975e\uff09\u6982\u7387\u6a21\u578b</li> </ol> </li> </ol>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#122","title":"1.2.2 \u95ee\u9898\u7684\u5f62\u5f0f\u5316","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#13","title":"1.3 \u7edf\u8ba1\u5b66\u4e60\u4e09\u8981\u8bfb","text":"<ul> <li>\u65b9\u6cd5=\u6a21\u578b+\u7b56\u7565+\u7b97\u6cd5</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#131","title":"1.3.1 \u6a21\u578b","text":"<ul> <li>\u6a21\u578b\u5c31\u662f\u7d22\u8981\u5b66\u4e60\u7684\u6761\u4ef6\u6982\u7387\u5206\u5e03\u6216\u51b3\u7b56\u51fd\u6570</li> </ul> \\[ \\mathcal{F}=\\{f\\mid Y=f(X)\\} \\] <ul> <li>\u53c2\u6570\u7a7a\u95f4</li> </ul> \\[ \\mathcal{F}=\\{f | Y=f_{\\theta}(X),\\theta\\in\\mathbf{R}^{n}\\} \\] <ul> <li>\u540c\u6837\u53ef\u4ee5\u5b9a\u4e49\u4e3a\u6761\u4ef6\u6982\u7387\u7684\u96c6\u5408</li> </ul> \\[ \\mathcal{F}=\\{P|P(Y|X)\\} \\] \\[ \\mathcal{F}=\\{P\\mid P_{\\theta}(Y\\mid X),\\theta\\in\\mathbf{R}^{n}\\} \\]"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#132","title":"1.3.2 \u7b56\u7565","text":"<ol> <li>\u635f\u5931\u51fd\u6570\u548c\u98ce\u9669\u51fd\u6570<ol> <li>loos function or cost function \\(\\displaystyle L(Y,f(X))\\)<ol> <li>0-1 loss function<ol> <li>\\(\\displaystyle L(Y,f(X))=\\begin{cases}1,&amp;Y\\neq f(X)\\\\0,&amp;Y=f(X)\\end{cases}\\)</li> </ol> </li> <li>quadratic loss function<ol> <li>\\(\\displaystyle L(Y,f(X))=(Y-f(X))^{2}\\)</li> </ol> </li> <li>absolute loss function<ol> <li>\\(\\displaystyle L(Y,f(X))=|Y-f(X)|\\)</li> </ol> </li> <li>logarithmic loss function or log-likelihood loss function<ol> <li>\\(\\displaystyle L(Y,P(Y\\mid X))=-\\log P(Y\\mid X)\\)</li> </ol> </li> </ol> </li> <li>\\(\\displaystyle R_{\\exp}(f)=E_{P}[L(Y,f(X))]=\\int_{x\\times y}L(y,f(x))P(x,y)\\mathrm{d}x\\mathrm{d}y\\)<ol> <li>risk function or expected loss</li> <li>\u4f46\u662f\u8054\u5408\u5206\u5e03\u4f4d\u7f6e\uff0c\u6240\u4ee5\u8981\u5b66\u4e60\uff0c\u4f46\u662f\u8fd9\u6837\u4ee5\u6765\u98ce\u9669\u6700\u5c0f\u53c8\u8981\u7528\u5230\u8054\u5408\u5206\u5e03\uff0c\u90a3\u4e48\u8fd9\u5c31\u6210\u4e3a\u4e86\u75c5\u6001\u95ee\u9898 (ill-formed problem)</li> </ol> </li> <li>empirical risk or empirical loss<ol> <li>\\(\\displaystyle R_{\\mathrm{emp}}(f)=\\frac{1}{N}\\sum_{i=1}^{N}L(y_{i},f(x_{i}))\\)</li> <li>\u5f53 \\(\\displaystyle N\\) \u8d8b\u4e8e\u65e0\u7a77\u65f6\uff0c\u7ecf\u9a8c\u98ce\u9669\u8d8b\u4e8e\u671f\u671b\u98ce\u9669<ol> <li>\u8fd9\u5c31\u5173\u7cfb\u5230\u4e24\u4e2a\u57fa\u672c\u7b56\u7565:<ol> <li>\u7ecf\u9a8c\u98ce\u9669\u6700\u5c0f\u5316</li> <li>\u7ed3\u6784\u98ce\u9669\u6700\u5c0f\u5316</li> </ol> </li> </ol> </li> </ol> </li> </ol> </li> <li>\u7ecf\u9a8c\u98ce\u9669\u6700\u5c0f\u5316\u4e0e\u7ed3\u6784\u98ce\u9669\u6700\u5c0f\u5316<ol> <li>empirical risk minimization \uff08\u6837\u672c\u5bb9\u91cf\u6bd4\u8f83\u5927\u7684\u65f6\u5019\uff09<ol> <li>\\(\\displaystyle \\min_{f\\in\\mathcal{F}} \\frac{1}{N}\\sum_{i=1}^{N}L(y_{i},f(x_{i}))\\)</li> <li>maximum likelihood estimation</li> </ol> </li> <li>structural risk minimization<ol> <li>regularization</li> <li>\\(\\displaystyle R_{\\mathrm{sm}}(f)=\\frac{1}{N}\\sum_{i=1}^{N}L(y_{i},f(x_{i}))+\\lambda J(f)\\)</li> <li>\u590d\u6742\u5ea6\u8868\u793a\u4e86\u5bf9\u590d\u6742\u6a21\u578b\u7684\u4e58\u6cd5</li> <li>maximum posterior probability estimation</li> </ol> </li> </ol> </li> </ol>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#133","title":"1.3.3 \u7b97\u6cd5","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#14","title":"1.4 \u6a21\u578b\u8bc4\u4f30\u4e0e\u6a21\u578b\u9009\u62e9","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#141","title":"1.4.1 \u8bad\u7ec3\u8bef\u5dee\u4e0e\u6d4b\u8bd5\u8bef\u5dee","text":"\\[ R_{\\mathrm{emp}}(\\hat{f})=\\frac{1}{N}\\sum_{i=1}^{N}L(y_{i},\\hat{f}(x_{i})) \\] \\[ e_{\\mathrm{test}}=\\frac{1}{N^{\\prime}}\\sum_{i=1}^{N^{\\prime}}L(y_{i},\\hat{f}(x_{i})) \\] \\[ r_{\\mathrm{test}}+e_{\\mathrm{test}}=1 \\] <ul> <li>generalization ability</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#142","title":"1.4.2 \u8fc7\u62df\u5408\u4e0e\u6a21\u578b\u9009\u62e9","text":"<ul> <li>model selection</li> <li>over-fitting </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#15","title":"1.5 \u6b63\u5219\u5316\u4e0e\u4ea4\u53c9\u9a8c\u8bc1","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#151","title":"1.5.1 \u6b63\u5219\u5316","text":"\\[ L(w)=\\frac{1}{N}\\sum_{i=1}^{N}(f(x_{i};w)-y_{i})^{2}+\\frac{\\lambda}{2}\\parallel w\\parallel^{2} \\]"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#152","title":"1.5.2 \u4ea4\u53c9\u9a8c\u8bc1","text":"<ul> <li>cross validation</li> <li>\u6570\u636e\u96c6<ul> <li>\u8bad\u7ec3\u96c6</li> <li>\u9a8c\u8bc1\u96c6</li> <li>\u6d4b\u8bd5\u96c6 1. \u7b80\u5355\u4ea4\u53c9\u9a8c\u8bc1 2. \\(\\displaystyle S\\) \u6298\u4ea4\u53c9\u9a8c\u8bc1 3. \u7559\u4e00\u4ea4\u53c9\u9a8c\u8bc1</li> </ul> </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#16","title":"1.6 \u6cdb\u5316\u80fd\u529b","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#161","title":"1.6.1 \u6cdb\u5316\u8bef\u5dee","text":"<ul> <li>generalization error</li> </ul> \\[ R_{\\exp}(\\hat{f})=E_{P}[L(Y,\\hat{f}(X))]=\\int_{R\\times y}L(y,\\hat{f}(x))P(x,y)\\mathrm{d}x\\mathrm{d}y \\]"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#162","title":"1.6.2 \u6cdb\u5316\u8bef\u5dee\u4e0a\u754c","text":"<ul> <li>generalization error bound</li> <li>\u6837\u672c\u5bb9\u91cf\u589e\u52a0\u65f6\uff0c\u6cdb\u5316\u4e0a\u754c\u8d8b\u4e8e 0</li> <li>\u5047\u8bbe\u7a7a\u95f4\u8d8a\u5927\uff0c\u6cdb\u5316\u8bef\u5dee\u4e0a\u754c\u8d8a\u5927 </li> <li>\u8fd9\u4e2a\u5b9a\u7406\u53ea\u9002\u7528\u4e8e\u5047\u8bbe\u7a7a\u95f4\u5305\u542b\u6709\u9650\u4e2a\u51fd\u6570</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#17","title":"1.7 \u751f\u6210\u6a21\u578b\u4e0e\u5224\u522b\u6a21\u578b","text":"<ul> <li>generative model<ul> <li>\u8fd8\u539f\u51fa\u8054\u5408\u6982\u7387\u5206\u5e03 \\(\\displaystyle P(X,Y)\\)</li> <li>\u6734\u7d20\u8d1d\u53f6\u65af\u6cd5</li> <li>\u9690\u9a6c\u5c14\u53ef\u592b\u6a21\u578b</li> <li>\u6536\u655b\u901f\u5ea6\u5feb</li> </ul> </li> <li>discriminative model<ul> <li>\u76f4\u63a5\u5b66\u4e60\u51b3\u7b56\u51fd\u6570\u6216\u6761\u4ef6\u6982\u7387\u5206\u5e03 \\(\\displaystyle P(Y|X)\\)</li> <li>\\(\\displaystyle k\\) \u8fd1\u90bb\u6cd5</li> <li>\u611f\u77e5\u673a</li> <li>\u51b3\u7b56\u6811</li> <li>\u903b\u8f91\u65af\u8c1b\u56de\u5f52\u6a21\u578b</li> <li>\u6700\u5927\u71b5\u6a21\u578b</li> <li>\u652f\u6301\u5411\u91cf\u673a</li> <li>\u63d0\u5347\u65b9\u6cd5</li> <li>\u6761\u4ef6\u968f\u673a\u573a</li> <li>\u51c6\u786e\u5ea6\u9ad8</li> </ul> </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#18","title":"1.8 \u5206\u7c7b\u95ee\u9898","text":"<ul> <li>precision \\(\\displaystyle P=\\frac{TP}{TP+FP}\\)</li> <li>recall \\(\\displaystyle R=\\frac{TP}{TP+FN}\\) </li> </ul> \\[ \\frac{2}{F_{1}}=\\frac{1}{P}+\\frac{1}{R} \\] \\[ F_{1}=\\frac{2TP}{2TP+FP+FN} \\] <ul> <li>text classification</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#19","title":"1.9 \u6807\u6ce8\u95ee\u9898","text":"<ul> <li>tagging \u662f classificationd \u4e00\u4e2a\u63a8\u5e7f</li> <li>\u662f structure prediction \u7684\u7b80\u5355\u5f62\u5f0f</li> <li>\u9690\u9a6c\u5c14\u53ef\u592b\u6a21\u578b</li> <li>\u6761\u4ef6\u968f\u673a\u573a</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#110","title":"1.10 \u56de\u5f52\u95ee\u9898","text":"<ul> <li>regression</li> <li>\uff08\u975e\uff09\u7ebf\u6027\u56de\u5f52\uff0c\u4e00\u5143\u56de\u5f52\uff0c\u591a\u5143\u56de\u5f52</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#2","title":"2 \u611f\u77e5\u673a","text":"<ul> <li>perception</li> <li>\u611f\u77e5\u673a\u5bf9\u5e94\u4e8e\u8f93\u5165\u7a7a\u95f4\u4e2d\u5c06\u5b9e\u4f8b\u5212\u5206\u6210\u6b63\u8d1f\u4e24\u7c7b\u7684\u5206\u79bb\u8d85\u5e73\u9762\uff0c\u5c5e\u4e8e\u5224\u522b\u6a21\u578b</li> <li>\u539f\u59cb\u5f62\u5f0f\u548c\u5bf9\u5076\u5f62\u5f0f</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#21","title":"2.1 \u611f\u77e5\u673a\u6a21\u578b","text":"<ul> <li>\u5047\u8bbe\u7a7a\u95f4\u662f\u5b9a\u4e49\u5728\u7279\u5f81\u7a7a\u95f4\u4e2d\u6240\u6709\u7684\u7ebf\u6027\u5206\u7c7b\u6a21\u578b\uff08linear classification model\uff09\\(\\displaystyle \\{f|f(x) = w \\cdot x+b\\}\\) </li> <li>separating hyperplane </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#22","title":"2.2 \u611f\u77e5\u673a\u5b66\u4e60\u7b56\u7565","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#221","title":"2.2.1 \u6570\u636e\u96c6\u7684\u7ebf\u6027\u53ef\u5206\u6027","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#222","title":"2.2.2 \u611f\u77e5\u673a\u5b66\u4e60\u7b56\u7565","text":"<ul> <li>\u5b9a\u4e49\u635f\u5931\u51fd\u6570\u5e76\u5c06\u635f\u5931\u51fd\u6570\u6781\u5c0f\u5316</li> </ul> \\[ L(w,b)=-\\sum_{x_{i}\\in M}y_{i}(w\\cdot x_{i}+b) \\]"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#223","title":"2.2.3 \u611f\u77e5\u673a\u5b66\u4e60\u7b97\u6cd5","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#224","title":"2.2.4 \u611f\u77e5\u673a\u5b66\u4e60\u7b97\u6cd5\u7684\u539f\u59cb\u5f62\u5f0f","text":"\\[ \\min_{w,b}L(w,b)=-\\sum_{x_{i}\\in M}y_{i}(w\\cdot x_{i}+b) \\] <ul> <li>stochastic gradient descent</li> </ul> \\[ \\nabla_{_w}L(w,b)=-\\sum_{x_{i}\\in M}y_{i}x_{i} \\] \\[ \\nabla_{b}L(w,b)=-\\sum_{x_{i}eM}y_{i} \\] \\[ w\\leftarrow w+\\eta y_{i}x_{i} \\] \\[ b\\leftarrow b+\\eta y_{i} \\] <ul> <li>\\(\\displaystyle \\eta\\) \u88ab\u79f0\u4e3a\u5b66\u4e60\u7387\uff08learning rate\uff09 </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#225","title":"2.2.5 \u7b97\u6cd5\u7684\u6536\u655b\u6027","text":"<ul> <li>\u4e3a\u4e86\u5f97\u5230\u552f\u4e00\u7684\u8d85\u5e73\u9762\uff0c\u9700\u8981\u5bf9\u5206\u79bb\u8d85\u5e73\u9762\u589e\u52a0\u7ea6\u675f\u6761\u4ef6\uff0c\u5373\u7ebf\u6027\u652f\u6301\u5411\u91cf\u673a</li> <li>\u5982\u679c\u8bad\u7ec3\u96c6\u7ebf\u6027\u4e0d\u53ef\u5206\uff0c\u90a3\u4e48\u611f\u77e5\u673a\u5b66\u4e60\u7b97\u6cd5\u4e0d\u6536\u655b</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#226","title":"2.2.6 \u611f\u77e5\u673a\u5b66\u4e60\u7b97\u6cd5\u7684\u5bf9\u5076\u5f62\u5f0f","text":"\\[ \\begin{aligned}&amp;w\\leftarrow w+\\eta y_{i}x_{i}\\\\&amp;b\\leftarrow b+\\eta y_{i}\\end{aligned} \\] \\[ w=\\sum_{i=1}^{N}\\alpha_{i}y_{i}x_{i} \\] \\[ b=\\sum_{i=1}^{N}\\alpha_{i}y_{i} \\] <ul> <li>Gram matrix</li> </ul> \\[ G=[x_{i}\\cdot x_{j}]_{N\\times N} \\]"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#3-displaystyle-k","title":"3 \\(\\displaystyle k\\) \u8fd1\u90bb\u6cd5","text":"<ul> <li>k-nearest neighbor</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#31-displaystyle-k","title":"3.1 \\(\\displaystyle k\\) \u8fd1\u90bb\u7b97\u6cd5","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#32-displaystyle-k","title":"3.2 \\(\\displaystyle k\\) \u8fd1\u90bb\u6a21\u578b","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#321","title":"3.2.1 \u6a21\u578b","text":"<ul> <li>cell</li> <li>class label </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#33","title":"3.3 \u8ddd\u79bb\u5ea6\u91cf","text":"<ul> <li>\\(\\displaystyle L_{p}\\) distance or Minkowski distamce</li> <li>\\(\\displaystyle L_{p}(x_{i},x_{j})=\\left(\\sum_{l=1}^{n}\\mid x_{i}^{(l)}-x_{j}^{(l)}\\mid^{p}\\right)^{\\frac{1}{p}}\\)</li> <li>\\(\\displaystyle L_{2}(x_{i},x_{j})=\\left(\\sum_{i=1}^{n}\\mid x_{i}^{(l)}-x_{j}^{(l)}\\mid^{2}\\right)^{\\frac{1}{2}}\\)</li> <li>\\(\\displaystyle L_{1}(x_{i}, x_{j})=\\sum_{l=1}^{n}\\mid x_{i}^{(l)}-x_{j}^{(l)}\\mid\\)</li> <li>\\(\\displaystyle L_{\\infty}(x_{i}, x_{j})=\\max_{l}\\mid x_{i}^{(l)}-x_{j}^{(l)}\\mid\\) </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#331-displaystyle-k","title":"3.3.1 \\(\\displaystyle k\\) \u503c\u7684\u9009\u62e9","text":"<ul> <li>if k is small, then the approximation error will reduce</li> <li>estimation error</li> <li>\\(\\displaystyle k\\) \u503c\u7684\u51cf\u5c0f\u5c31\u610f\u5473\u7740\u6574\u4f53\u6a21\u578b\u53d8\u5f97\u590d\u6742\uff0c\u5bb9\u6613\u53d1\u751f\u8fc7\u62df\u5408</li> <li>\u5728\u5e94\u7528\u4e2d, \\(\\displaystyle k\\) \u503c\u4e00\u822c\u53d6\u4e00\u4e2a\u6bd4\u8f83\u5c0f\u7684\u6570\u503c\uff0c\u901a\u5e38\u91c7\u7528\u4ea4\u53c9\u9a8c\u8bc1\u6cd5\u6765\u9009\u53d6\u6700\u4f18\u7684 \\(\\displaystyle k\\) \u503c</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#332","title":"3.3.2 \u5206\u7c7b\u51b3\u7b56\u89c4\u5219","text":"<ul> <li>\u591a\u6570\u8868\u51b3\u89c4\u5219\uff08majority voting rule\uff09 </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#34-displaystyle-k-displaystyle-kd","title":"3.4 \\(\\displaystyle k\\) \u8fd1\u90bb\u6cd5\u7684\u5b9e\u73b0: \\(\\displaystyle kd\\) \u6811","text":"<ul> <li>linear scan</li> <li>kd tree</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#341-displaystyle-kd","title":"3.4.1 \u6784\u9020 \\(\\displaystyle kd\\) \u6811","text":"<ul> <li>\\(\\displaystyle kd\\) \u6811\u662f\u4e00\u4e8c\u53c9\u6811\uff0c\u8868\u793a\u5bf9 \\(\\displaystyle k\\) \u7ef4\u7a7a\u95f4\u7684\u4e00\u4e2a\u5212\u5206\uff08partition\uff09</li> <li>\u901a\u5e38\u9009\u62e9\u8bad\u7ec3\u5b9e\u4f8b\u70b9\u5728\u9009\u5b9a\u5750\u6807\u8f74\u4e0a\u7684\u4e2d\u4f4d\u6570\u4e3a\u5207\u5206\u70b9\uff0c\u867d\u7136\u8fd9\u6837\u5f97\u5230\u7684\u6811\u662f\u5e73\u8861\u7684\uff0c\u4f46\u6548\u7387\u672a\u5fc5\u662f\u6700\u4f18\u7684  \u6709\u610f\u601d</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#342-displaystyle-kd","title":"3.4.2 \u641c\u7d22 \\(\\displaystyle kd\\) \u6811","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#4","title":"4 \u6734\u7d20\u8d1d\u53f6\u65af\u6cd5","text":"<ul> <li>\u57fa\u4e8e\u8d1d\u53f6\u65af\u5b9a\u7406\u4e0e\u7279\u5f81\u6761\u4ef6\u72ec\u7acb\u5047\u8bbe\u7684\u5206\u7c7b\u65b9\u6cd5</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#41","title":"4.1 \u6734\u7d20\u8d1d\u53f6\u65af\u6cd5\u7684\u5b66\u4e60\u4e0e\u5206\u7c7b","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#411","title":"4.1.1 \u57fa\u672c\u65b9\u6cd5","text":"<ul> <li>\u5b66\u4e60\u5148\u9a8c\u6982\u7387\u5206\u5e03\u548c\u6761\u4ef6\u6982\u7387\u5206\u5e03\u4e8e\u662f\u5b66\u4e60\u5230\u8054\u5408\u6982\u7387\u5206\u5e03</li> </ul> \\[ P(X=x\\mid Y=c_{k})=P(X^{(1)}=x^{(1)},\\cdots,X^{(n)}=x^{(n)}\\mid Y=c_{k}),\\quad k=1,2,\\cdots,K \\] <ul> <li>\u5f15\u5165\u4e86\u6761\u4ef6\u72ec\u7acb\u6027\u5047\u8bbe</li> </ul> \\[ \\begin{aligned} P(X=x|Y=c_{k})&amp; =P(X^{(1)}=x^{(1)},\\cdots,X^{(n)}=x^{(n)}\\mid Y=c_{k}) \\\\ &amp;=\\prod_{j=1}^{n}P(X^{(j)}=x^{(j)}\\mid Y=c_{k}) \\end{aligned} \\] \\[ P(Y=c_{k}\\mid X=x)=\\frac{P(X=x\\mid Y=c_{k})P(Y=c_{k})}{\\sum_{k}P(X=x\\mid Y=c_{k})P(Y=c_{k})} \\] \\[ P(Y=c_{k}\\mid X=x)=\\frac{P(Y=c_{k})\\prod_{j}P(X^{(j)}=x^{(j)}\\mid Y=c_{k})}{\\sum_{k}P(Y=c_{k})\\prod_{j}P(X^{(j)}=x^{(j)}\\mid Y=c_{k})},\\quad k=1,2,\\cdots,K \\] \\[ y=f(x)=\\arg\\max_{c_{k}}\\frac{P(Y=c_{k})\\prod_{j}P(X^{(j)}=x^{(j)}\\mid Y=c_{k})}{\\sum_{k}P(Y=c_{k})\\prod_{j}P(X^{(j)}=x^{(j)}\\mid Y=c_{k})} \\] \\[ y=\\arg\\max_{c_{k}}P(Y=c_{k})\\prod_{j}P(X^{(j)}=x^{(j)}\\mid Y=c_{k}) \\]"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#412","title":"4.1.2 \u540e\u9a8c\u6982\u7387\u6700\u5927\u5316\u7684\u542b\u4e49","text":"\\[ L(Y,f(X))=\\begin{cases}1,&amp;Y\\neq f(X)\\\\0,&amp;Y=f(X)\\end{cases} \\] \\[ R_{\\exp}(f)=E[L(Y,f(X))] \\] \\[ R_{\\exp}(f)=E_{\\chi}\\sum_{k=1}^{K}[L(c_{k},f(X))]P(c_{k}\\mid X) \\] \\[ \\begin{align} f(x) &amp;=\\arg\\min_{y\\in\\mathcal{Y}}\\sum_{k=1}^{K}L(c_{k},y)P(c_{k}\\mid X=x) \\\\ &amp;=\\arg\\min_{y\\in\\mathcal{Y}}\\sum_{k=1}^{K}P(y\\neq c_{k}\\mid X=x) \\\\ &amp;=\\arg\\min_{y\\in\\mathcal{Y}}(1-P(y=c_{k}\\mid X=x)) \\\\ &amp;=\\arg\\max_{y\\in\\mathcal{Y}}P(y=c_{k}\\mid X=x)  \\end{align} \\] \\[ f(x)=\\arg\\max_{c_{k}}P(c_{k}\\mid X=x) \\] <ul> <li>\u671f\u671b\u98ce\u9669\u6700\u5c0f\u5316\u51c6\u5219\u5c31\u5f97\u5230\u8054\u8003\u540e\u9a8c\u6982\u7387\u6700\u5927\u5316\u51c6\u5219</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#42","title":"4.2 \u6734\u7d20\u8d1d\u53f6\u65af\u6cd5\u7684\u53c2\u6570\u4f30\u8ba1","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#421","title":"4.2.1 \u6781\u5927\u4f3c\u7136\u4f30\u8ba1","text":"\\[ P(Y=c_{k})=\\frac{\\sum_{i=1}^{N}I(y_{i}=c_{k})}{N} , k=1,2,\\cdots,K \\] \\[ P(X^{(j)}=a_{ji}\\mid Y=c_{k})=\\frac{\\sum_{i=1}^{N}I(x_{i}^{(j)}=a_{ji},y_{i}=c_{k})}{\\sum_{i=1}^{N}I(y_{i}=c_{k})}\\\\j=1,2,\\cdots,n ;\\quad l=1,2,\\cdots,S_{j} ;\\quad k=1,2,\\cdots,K \\]"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#422","title":"4.2.2 \u5b66\u4e60\u4e0e\u5206\u7c7b\u7b97\u6cd5","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#423","title":"4.2.3 \u8d1d\u53f6\u65af\u4f30\u8ba1","text":"<ul> <li>\u6781\u5927\u4f3c\u7136\u4f30\u8ba1\u53ef\u80fd\u4f1a\u51fa\u73b0\u6240\u8981\u4f30\u8ba1\u7684\u6982\u7387\u503c\u4e3a 0 \u7684\u60c5\u51b5</li> <li>\u6761\u4ef6\u6982\u7387\u7684\u8d1d\u53f6\u65af\u4f30\u8ba1</li> </ul> \\[ P_{\\lambda}(X^{(j)}=a_{ji}\\mid Y=c_{k})=\\frac{\\sum_{i=1}^{N}I(x_{i}^{(j)}=a_{ji},y_{i}=c_{k})+\\lambda}{\\sum_{i=1}^{N}I(y_{i}=c_{k})+S_{j}\\lambda} \\] <ul> <li>when \\(\\displaystyle \\lambda = 0\\), it's called Laplace smoothing</li> </ul> \\[ \\begin{aligned}&amp;P_{\\lambda}(X^{(j)}=a_{jl}\\mid Y=c_{k})&gt;0\\\\&amp;\\sum_{l=1}^{s_{j}}P(X^{(j)}=a_{jl}\\mid Y=c_{k})=1\\end{aligned} \\] <ul> <li>\u8868\u660e\u8d1d\u53f6\u65af\u4f30\u8ba1\u786e\u5b9e\u662f\u4e00\u79cd\u6982\u7387\u5206\u5e03</li> <li>\u5148\u9a8c\u6982\u7387\u7684\u8d1d\u53f6\u65af\u4f30\u8ba1</li> </ul> \\[ P_{\\lambda}(Y=c_{k})=\\frac{\\sum_{i=1}^{N}I(y_{i}=c_{k})+\\lambda}{N+K\\lambda} \\]"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#5","title":"5 \u51b3\u7b56\u6811","text":"<ul> <li>decision tree<ul> <li>\u7279\u5f81\u9009\u62e9</li> <li>\u51b3\u7b56\u6811\u7684\u751f\u6210</li> <li>\u51b3\u7b56\u6811\u7684\u4fee\u526a</li> </ul> </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#51","title":"5.1 \u51b3\u7b56\u6811\u6a21\u578b\u4e0e\u5b66\u4e60","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#511","title":"5.1.1 \u51b3\u7b56\u6811\u6a21\u578b","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#512-if-then","title":"5.1.2 \u51b3\u7b56\u6811\u4e0e if-then \u89c4\u5219","text":"<ul> <li>\u4e92\u65a5\u4e14\u5b8c\u5907</li> <li>\u6bcf\u4e00\u4e2a\u5b9e\u4f8b\u90fd\u88ab\u4e00\u6761\u8def\u5f84\u4f1a\u89c4\u5219\u6240\u8986\u76d6\uff0c\u800c\u4e14\u53ea\u88ab\u4e00\u6761\u8def\u5f84\u6216\u4e00\u6761\u89c4\u5219\u6240\u8986\u76d6</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#513","title":"5.1.3 \u51b3\u7b56\u6811\u4e0e\u6761\u4ef6\u6982\u7387\u5206\u5e03","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#514","title":"5.1.4 \u51b3\u7b56\u6811\u5b66\u4e60","text":"<ul> <li>\u51b3\u7b56\u6811\u5b66\u4e60\u672c\u8d28\u4e0a\u662f\u4ece\u8bad\u7ec3\u6570\u636e\u96c6\u4e2d\u5f52\u7eb3\u51fa\u4e00\u7ec4\u5206\u7c7b\u89c4\u5219</li> <li>\u5728\u635f\u5931\u51fd\u6570\u610f\u4e49\u4e0b\u9009\u62e9\u6700\u4f18\u51b3\u7b56\u6811\u7684\u95ee\u9898\uff0c\u662f NP \u5b8c\u5168\u95ee\u9898\uff0c\u91c7\u7528\u542f\u53d1\u5f0f\u65b9\u6cd5\uff0c\u8fd1\u4f3c\u6c42\u89e3\uff0c\u8fd9\u6837\u5f97\u5230\u7684\u51b3\u7b56\u6811\u662f\u6b21\u6700\u4f18\uff08sub-optimal\uff09</li> <li>\u4e3a\u4e86\u9632\u6b62\u8fc7\u62df\u5408\uff0c\u6211\u4eec\u9700\u8981\u5bf9\u5df2\u751f\u6210\u7684\u6811\u81ea\u4e0a\u800c\u4e0b\u8fdb\u884c\u526a\u679d</li> <li>\u51b3\u7b56\u6811\u7684\u751f\u6210\u503c\u8003\u8651\u5c40\u90e8\u6700\u4f18\uff0c\u526a\u679d\u5219\u8003\u8651\u5168\u5c40\u6700\u4f18</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#52","title":"5.2 \u7279\u5f81\u9009\u62e9","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#521","title":"5.2.1 \u7279\u5f81\u9009\u62e9\u95ee\u9898","text":"<ul> <li>\u901a\u5e38\u7279\u5f81\u9009\u62e9\u7684\u51c6\u5219\u662f\u4fe1\u606f\u589e\u76ca\u6216\u4fe1\u606f\u589e\u76ca\u6bd4</li> <li>information gain</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#522","title":"5.2.2 \u4fe1\u606f\u589e\u76ca","text":"<ul> <li>\u71b5\u548c\u6761\u4ef6\u71b5</li> </ul> \\[ P(X=x_{i})=p_{i} ,\\quad i=1,2,\\cdots,n \\] \\[ H(X)=-\\sum_{i=1}^{n}p_{i}\\log p_{i} \\] \\[ H(p)=-\\sum_{i=1}^{n}p_{i}\\log p_{i} \\] \\[ 0\\leqslant H(p)\\leqslant\\log n \\] \\[ P(X=x_{i},Y=y_{j})=p_{ij} ,\\quad i=1,2,\\cdots,n ;\\quad j=1,2,\\cdots,m \\] \\[ H(Y\\mid X)=\\sum_{i=1}^{n}p_{i}H(Y\\mid X=x_{i}) \\] <ul> <li>mutual information </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#523","title":"5.2.3 \u4fe1\u606f\u589e\u76ca\u6bd4","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#53","title":"5.3 \u51b3\u7b56\u6811\u7684\u751f\u6210","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#531-id-3","title":"5.3.1 ID 3 \u7b97\u6cd5","text":"<ul> <li>ID 3 \u7b97\u6cd5\u53ea\u6709\u6811\u7684\u751f\u6210\uff0c\u6240\u4ee5\u8be5\u7b97\u6cd5\u751f\u6210\u7684\u6811\u5bb9\u6613\u4ea7\u751f\u8fc7\u62df\u5408</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#532-c-45","title":"5.3.2 C 4.5 \u7684\u751f\u6210\u7b97\u6cd5","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#54","title":"5.4 \u51b3\u7b56\u6811\u7684\u526a\u679d","text":"<ul> <li>pruning</li> </ul> \\[ C_{\\alpha}(T)=\\sum_{t=1}^{|T|}N_{t}H_{t}(T)+\\alpha|T| \\] \\[ H_{t}(T)=-\\sum_{k}\\frac{N_{ik}}{N_{t}}\\log\\frac{N_{ik}}{N_{t}} \\] \\[ C(T)=\\sum_{t=1}^{|T|}N_{t}H_{t}(T)=-\\sum_{t=1}^{|T|}\\sum_{k=1}^{K}N_{tk}\\log\\frac{N_{tk}}{N_{t}} \\] \\[ C_{\\alpha}(T)=C(T)+\\alpha|T| \\]"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#55-cart","title":"5.5 CART \u7b97\u6cd5","text":"<ul> <li>\u5206\u88c2\u4e0e\u56de\u5f52\u6811\uff08classification and regression tree\uff09</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#551-cart","title":"5.5.1 CART \u751f\u6210","text":"<ul> <li>\u5bf9\u56de\u5f52\u6811\u7528\u5e73\u65b9\u8bef\u5dee\u6700\u5c0f\u5316\u51c6\u5219</li> <li>\u5bf9\u5206\u7c7b\u6811\u7528\u57fa\u5c3c\u6307\u6570\uff08Gini index\uff09\u6700\u5c0f\u5316\u51c6\u5219 1. \u56de\u5f52\u6811\u7684\u751f\u6210</li> </ul> \\[ f(x)=\\sum_{m=1}^{M}c_{m}I(x\\in R_{m}) \\] \\[ \\hat{c}_{m}=\\mathrm{ave}(y_{i}\\mid x_{i}\\in R_{m}) \\] <ul> <li>splitting variable </li> <li>splitting point</li> </ul> \\[ R_{1}(j,s)=\\{x\\mid x^{(j)}\\leqslant s\\}\\quad\\text{\u548c}\\quad R_{2}(j,s)=\\{x\\mid x^{(j)}&gt;s\\} \\] \\[ \\min_{j,s}\\biggl[\\min_{c_{1}}\\sum_{x_{i}\\in R_{i}(j,s)}(y_{i}-c_{1})^{2}+\\min_{c_{2}}\\sum_{x_{i}\\in R_{2}(j,s)}(y_{i}-c_{2})^{2}\\biggr] \\] \\[ \\hat{c}_{1}=\\mathrm{ave}(y_{i}\\mid x_{i}\\in R_{1}(j,s))\\quad\\hat{\\text{\u548c}}\\quad\\hat{c}_{2}=\\mathrm{ave}(y_{i}\\mid x_{i}\\in R_{2}(j,s)) \\] <ul> <li>least squares regression tree  1. \u5206\u7c7b\u6811\u7684\u751f\u6210 </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#552-cart","title":"5.5.2 CART \u526a\u679d","text":"<ol> <li>\u526a\u679d\uff0c\u5f62\u6210\u4e00\u4e2a\u5b50\u6811\u5e8f\u5217</li> </ol> \\[ C_{\\alpha}(T)=C(T)+\\alpha\\left|T\\right| \\] \\[ g(t)=\\frac{C(t)-C(T_{t})}{\\mid T_{t}\\mid-1} \\] <ol> <li>\u5728\u526a\u679d\u5f97\u5230\u7684\u5b50\u6811\u5e8f\u5217 \\(\\displaystyle T_0,T_1,\\cdots,T_n\\) \u4e2d\u901a\u8fc7\u4ea4\u53c9\u9a8c\u8bc1\u9009\u53d6\u6700\u4f18\u5b50\u6811 \\(\\displaystyle T_{\\alpha}\\) </li> </ol>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#6","title":"6 \u903b\u8f91\u65af\u8c1b\u56de\u5f52\u4e0e\u6700\u5927\u71b5\u6a21\u578b","text":"<ul> <li>logistic regression</li> <li>maximum entropy model</li> <li>\u903b\u8f91\u65af\u8c1b\u56de\u5f52\u6a21\u578b\u548c\u6700\u5927\u71b5\u6a21\u578b\u90fd\u5c5e\u4e8e\u5bf9\u6570\u7ebf\u6027\u6a21\u578b</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#61","title":"6.1 \u903b\u8f91\u65af\u8c1b\u56de\u5f52\u6a21\u578b","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#611","title":"6.1.1 \u903b\u8f91\u65af\u8c1b\u5206\u5e03","text":"<ul> <li>logistic distribution </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#612","title":"6.1.2 \u4e8c\u9879\u903b\u8f91\u65af\u8c1b\u56de\u5f52\u6a21\u578b","text":"<ul> <li>binomial logistic regression model </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#7","title":"7 \u652f\u6301\u5411\u91cf\u673a","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#8","title":"8 \u63d0\u5347\u65b9\u6cd5","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#9-displaystyle-boldsymbolem","title":"9 \\(\\displaystyle \\boldsymbol{EM}\\) \u7b97\u6cd5\u53ca\u5176\u63a8\u5e7f","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#10","title":"10 \u9690\u9a6c\u5c14\u53ef\u592b\u6a21\u578b","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#11_1","title":"11 \u6761\u4ef6\u968f\u673a\u573a","text":""},{"location":"AI/CS231n/CS231n_notes/","title":"Computer Vision","text":""},{"location":"AI/CS231n/CS231n_notes/#computer-vision","title":"Computer Vision","text":"<p> \u7ea6 8852 \u4e2a\u5b57  167 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 44 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>This note is based on GitHub - DaizeDong/Stanford-CS231n-2021-and-2022: Notes and slides for Stanford CS231n 2021 &amp; 2022 in English. I merged the contents together to get a better version. Assignments are not included. \u65af\u5766\u798fcs231n\u7684\u8bfe\u7a0b\u7b14\u8bb0(\u82f1\u6587\u7248\u672c\uff0c\u4e0d\u542b\u5b9e\u9a8c\u4ee3\u7801)\uff0c\u5c062021\u4e0e2022\u4e24\u5e74\u7684\u8bfe\u7a0b\u8fdb\u884c\u4e86\u5408\u5e76\uff0c\u5206\u4eab\u4ee5\u4f9b\u4ea4\u6d41\u3002 And I will add some blogs, articles and other understanding.</p> Topic Chapter Deep Learning Basics 2 - 4 Perceiving and Understanding the Visual World 5 - 12 Reconstructing and Interacting with the Visual World 13 - 16 Human-Centered Applications and Implications 17 - 18"},{"location":"AI/CS231n/CS231n_notes/#1-introduction","title":"1 - Introduction","text":"<p>A brief history of computer vision &amp; deep learning...</p>"},{"location":"AI/CS231n/CS231n_notes/#2-image-classification","title":"2 - Image Classification","text":"<p>Image Classification: A core task in Computer Vision. The main drive to the progress of CV.</p> <p>Challenges: Viewpoint variation, background clutter, illumination, occlusion, deformation, intra-class variation...</p>"},{"location":"AI/CS231n/CS231n_notes/#k-nearest-neighbor","title":"K Nearest Neighbor","text":"<p>Hyperparameters: Distance metric (\\(p\\) norm), \\(k\\) number.</p> <p>Choose hyperparameters using validation set.</p> <p>Never use k-Nearest Neighbor with pixel distance.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#linear-classifier","title":"Linear Classifier","text":"<p>Pass...</p>"},{"location":"AI/CS231n/CS231n_notes/#3-loss-functions-and-optimization","title":"3 - Loss Functions and Optimization","text":""},{"location":"AI/CS231n/CS231n_notes/#loss-functions","title":"Loss Functions","text":"Dataset \\(\\big\\{(x_i,y_i)\\big\\}_{i=1}^N\\\\\\) Loss Function \\(L=\\frac{1}{N}\\sum_{i=1}^NL_i\\big(f(x_i,W),y_i\\big)\\\\\\) Loss Function with Regularization \\(L=\\frac{1}{N}\\sum_{i=1}^NL_i\\big(f(x_i,W),y_i\\big)+\\lambda R(W)\\\\\\) <p>Motivation: Want to interpret raw classifier scores as probabilities.</p> Softmax Classifier \\(p_i=Softmax(y_i)=\\frac{\\exp(y_i)}{\\sum_{j=1}^N\\exp(y_j)}\\\\\\) Cross Entropy Loss \\(L_i=-y_i\\log p_i\\\\\\) Cross Entropy Loss with Regularization \\(L=-\\frac{1}{N}\\sum_{i=1}^Ny_i\\log p_i+\\lambda R(W)\\\\\\) <p></p>"},{"location":"AI/CS231n/CS231n_notes/#optimization","title":"Optimization","text":""},{"location":"AI/CS231n/CS231n_notes/#sgd-with-momentum","title":"SGD with Momentum","text":"<p>Problems that SGD can't handle:</p> <ol> <li>Inequality of gradient in different directions.</li> <li>Local minima and saddle point (much more common in high dimension).</li> <li>Noise of gradient from mini-batch.</li> </ol> <p>Momentum: Build up \u201cvelocity\u201d \\(v_t\\) as a running mean of gradients.</p> SGD SGD + Momentum \\(x_{t+1}=x_t-\\alpha\\nabla f(x_t)\\) \\(\\begin{align}&amp;v_{t+1}=\\rho v_t+\\nabla f(x_t)\\\\&amp;x_{t+1}=x_t-\\alpha v_{t+1}\\end{align}\\) Naive gradient descent. \\(\\rho\\) gives \"friction\", typically \\(\\rho=0.9,0.99,0.999,...\\) <p>Nesterov Momentum: Use the derivative on point \\(x_t+\\rho v_t\\) as gradient instead point \\(x_t\\).</p> Momentum Nesterov Momentum \\(\\begin{align}&amp;v_{t+1}=\\rho v_t+\\nabla f(x_t)\\\\&amp;x_{t+1}=x_t-\\alpha v_{t+1}\\end{align}\\) \\(\\begin{align}&amp;v_{t+1}=\\rho v_t+\\nabla f(x_t+\\rho v_t)\\\\&amp;x_{t+1}=x_t-\\alpha v_{t+1}\\end{align}\\) Use gradient at current point. Look ahead for the gradient in velocity direction. <p></p>"},{"location":"AI/CS231n/CS231n_notes/#adagrad-and-rmsprop","title":"AdaGrad and RMSProp","text":"<p>AdaGrad: Accumulate squared gradient, and gradually decrease the step size.</p> <p>RMSProp: Accumulate squared gradient while decaying former ones, and gradually decrease the step size. (\"Leaky AdaGrad\")</p> AdaGrad RMSProp \\(\\begin{align}\\text{Initialize:}&amp;\\\\&amp;r:=0\\\\\\text{Update:}&amp;\\\\&amp;r:=r+\\Big[\\nabla f(x_t)\\Big]^2\\\\&amp;x_{t+1}=x_t-\\alpha\\frac{\\nabla f(x_t)}{\\sqrt{r}}\\end{align}\\) \\(\\begin{align}\\text{Initialize:}&amp;\\\\&amp;r:=0\\\\\\text{Update:}&amp;\\\\&amp;r:=\\rho r+(1-\\rho)\\Big[\\nabla f(x_t)\\Big]^2\\\\&amp;x_{t+1}=x_t-\\alpha\\frac{\\nabla f(x_t)}{\\sqrt{r}}\\end{align}\\) Continually accumulate squared gradients. \\(\\rho\\) gives \"decay rate\", typically \\(\\rho=0.9,0.99,0.999,...\\)"},{"location":"AI/CS231n/CS231n_notes/#adam","title":"Adam","text":"<p>Sort of like \"RMSProp + Momentum\".</p> Adam (simple version) Adam (full version) \\(\\begin{align}\\text{Initialize:}&amp;\\\\&amp;r_1:=0\\\\&amp;r_2:=0\\\\\\text{Update:}&amp;\\\\&amp;r_1:=\\beta_1r_1+(1-\\beta_1)\\nabla f(x_t)\\\\&amp;r_2:=\\beta_2r_2+(1-\\beta_2)\\Big[\\nabla f(x_t)\\Big]^2\\\\&amp;x_{t+1}=x_t-\\alpha\\frac{r_1}{\\sqrt{r_2}}\\end{align}\\) \\(\\begin{align}\\text{Initialize:}\\\\&amp;r_1:=0\\\\&amp;r_2:=0\\\\\\text{For }i\\text{:}\\\\&amp;r_1:=\\beta_1r_1+(1-\\beta_1)\\nabla f(x_t)\\\\&amp;r_2:=\\beta_2r_2+(1-\\beta_2)\\Big[\\nabla f(x_t)\\Big]^2\\\\&amp;r_1'=\\frac{r_1}{1-\\beta_1^i}\\\\&amp;r_2'=\\frac{r_2}{1-\\beta_2^i}\\\\&amp;x_{t+1}=x_t-\\alpha\\frac{r_1'}{\\sqrt{r_2'}}\\end{align}\\) Build up \u201cvelocity\u201d for both gradient and squared gradient. Correct the \"bias\" that \\(r_1=r_2=0\\) for the first few iterations."},{"location":"AI/CS231n/CS231n_notes/#overview","title":"Overview","text":""},{"location":"AI/CS231n/CS231n_notes/#learning-rate-decay","title":"Learning Rate Decay","text":"<p>Reduce learning rate at a few fixed points to get a better convergence over time.</p> <p>\\(\\alpha_0\\) : Initial learning rate.</p> <p>\\(\\alpha_t\\) : Learning rate in epoch \\(t\\).</p> <p>\\(T\\) : Total number of epochs.</p> Method Equation Picture Step Reduce \\(\\alpha_t\\) constantly  in a fixed step. Cosine \\(\\begin{align}\\alpha_t=\\frac{1}{2}\\alpha_0\\Bigg[1+\\cos(\\frac{t\\pi}{T})\\Bigg]\\end{align}\\) Linear \\(\\begin{align}\\alpha_t=\\alpha_0\\Big(1-\\frac{t}{T}\\Big)\\end{align}\\) Inverse Sqrt \\(\\begin{align}\\alpha_t=\\frac{\\alpha_0}{\\sqrt{t}}\\end{align}\\) <p>High initial learning rates can make loss explode, linearly increasing learning rate in the first few iterations can prevent this.</p> <p>Learning rate warm up:</p> <p></p> <p>Empirical rule of thumb: If you increase the batch size by \\(N\\), also scale the initial learning rate by \\(N\\) .</p>"},{"location":"AI/CS231n/CS231n_notes/#second-order-optimization","title":"Second-Order Optimization","text":"Picture Time Complexity Space Complexity First Order \\(O(n)\\) \\(O(n)\\) Second Order \\(O(n^2)\\) with BGFS optimization \\(O(n)\\) with L-BGFS optimization <p>L-BGFS : Limited memory BGFS.</p> <ol> <li>Works very well in full batch, deterministic \\(f(x)\\).</li> <li>Does not transfer very well to mini-batch setting.</li> </ol>"},{"location":"AI/CS231n/CS231n_notes/#summary","title":"Summary","text":"Method Performance Adam Often chosen as default method.Work ok even with constant learning rate. SGD + Momentum Can outperform Adam.Require more tuning of learning rate and schedule. L-BGFS If can afford to do full batch updates then try out. <ul> <li>An article about gradient descent: Anoverview of gradient descent optimization algorithms</li> <li>A blog: An updated overview of recent gradient descent algorithms \u2013 John Chen \u2013 ML at Rice University</li> </ul>"},{"location":"AI/CS231n/CS231n_notes/#4-neural-networks-and-backpropagation","title":"4 - Neural Networks and Backpropagation","text":""},{"location":"AI/CS231n/CS231n_notes/#neural-networks","title":"Neural Networks","text":"<p>Motivation: Inducted bias can appear to be high when using human-designed features.</p> <p>Activation: Sigmoid, tanh, ReLU, LeakyReLU...</p> <p>Architecture: Input layer, hidden layer, output layer.</p> <p>Do not use the size of a neural network as the regularizer. Use regularization instead!</p> <p>Gradient Calculation: Computational Graph + Backpropagation.</p>"},{"location":"AI/CS231n/CS231n_notes/#backpropagation","title":"Backpropagation","text":"<p>Using Jacobian matrix to calculate the gradient of each node in a computation graph.</p> <p>Suppose that we have a computation flow like this:</p> <p></p> Input X Input W Output Y \\(X=\\begin{bmatrix}x_1\\\\x_2\\\\\\vdots\\\\x_n\\end{bmatrix}\\) \\(W=\\begin{bmatrix}w_{11}&amp;w_{12}&amp;\\cdots&amp;w_{1n}\\\\w_{21}&amp;w_{22}&amp;\\cdots&amp;w_{2n}\\\\\\vdots&amp;\\vdots&amp;\\ddots&amp;\\vdots\\\\w_{m1}&amp;w_{m2}&amp;\\cdots&amp;w_{mn}\\end{bmatrix}\\) \\(Y=\\begin{bmatrix}y_1\\\\y_2\\\\\\vdots\\\\y_m\\end{bmatrix}\\) \\(n\\times 1\\) \\(m\\times n\\) \\(m\\times 1\\) <p>After applying feed forward, we can calculate gradients like this:</p> <p></p> Derivative Matrix of X Jacobian Matrix of X Derivative Matrix of Y \\(D_X=\\begin{bmatrix}\\frac{\\partial L}{\\partial x_1}\\\\\\frac{\\partial L}{\\partial x_2}\\\\\\vdots\\\\\\frac{\\partial L}{\\partial x_n}\\end{bmatrix}\\) \\(J_X=\\begin{bmatrix}\\frac{\\partial y_1}{\\partial x_1}&amp;\\frac{\\partial y_1}{\\partial x_2}&amp;\\cdots&amp;\\frac{\\partial y_1}{\\partial x_n}\\\\\\frac{\\partial y_2}{\\partial x_1}&amp;\\frac{\\partial y_2}{\\partial x_2}&amp;\\cdots&amp;\\frac{\\partial y_2}{\\partial x_n}\\\\\\vdots&amp;\\vdots&amp;\\ddots&amp;\\vdots\\\\\\frac{\\partial y_m}{\\partial x_1}&amp;\\frac{\\partial y_m}{\\partial x_2}&amp;\\cdots&amp;\\frac{\\partial y_m}{\\partial x_n}\\end{bmatrix}\\) \\(D_Y=\\begin{bmatrix}\\frac{\\partial L}{\\partial y_1}\\\\\\frac{\\partial L}{\\partial y_2}\\\\\\vdots\\\\\\frac{\\partial L}{\\partial y_m}\\end{bmatrix}\\) \\(n\\times 1\\) \\(m\\times n\\) \\(m\\times 1\\) Derivative Matrix of W Jacobian Matrix of W Derivative Matrix of Y \\(W=\\begin{bmatrix}\\frac{\\partial L}{\\partial w_{11}}&amp;\\frac{\\partial L}{\\partial w_{12}}&amp;\\cdots&amp;\\frac{\\partial L}{\\partial w_{1n}}\\\\\\frac{\\partial L}{\\partial w_{21}}&amp;\\frac{\\partial L}{\\partial w_{22}}&amp;\\cdots&amp;\\frac{\\partial L}{\\partial w_{2n}}\\\\\\vdots&amp;\\vdots&amp;\\ddots&amp;\\vdots\\\\\\frac{\\partial L}{\\partial w_{m1}}&amp;\\frac{\\partial L}{\\partial w_{m2}}&amp;\\cdots&amp;\\frac{\\partial L}{\\partial w_{mn}}\\end{bmatrix}\\) \\(J_W^{(k)}=\\begin{bmatrix}\\frac{\\partial y_k}{\\partial w_{11}}&amp;\\frac{\\partial y_k}{\\partial w_{12}}&amp;\\cdots&amp;\\frac{\\partial y_k}{\\partial w_{1n}}\\\\\\frac{\\partial y_k}{\\partial w_{21}}&amp;\\frac{\\partial y_k}{\\partial w_{22}}&amp;\\cdots&amp;\\frac{\\partial y_k}{\\partial w_{2n}}\\\\\\vdots&amp;\\vdots&amp;\\ddots&amp;\\vdots\\\\\\frac{\\partial y_k}{\\partial w_{m1}}&amp;\\frac{\\partial y_k}{\\partial w_{m2}}&amp;\\cdots&amp;\\frac{\\partial y_k}{\\partial w_{mn}}\\end{bmatrix}\\)\\(J_W=\\begin{bmatrix}J_W^{(1)}&amp;J_W^{(2)}&amp;\\cdots&amp;J_W^{(m)}\\end{bmatrix}\\) \\(D_Y=\\begin{bmatrix}\\frac{\\partial L}{\\partial y_1}\\\\\\frac{\\partial L}{\\partial y_2}\\\\\\vdots\\\\\\frac{\\partial L}{\\partial y_m}\\end{bmatrix}\\) \\(m\\times n\\) \\(m\\times m\\times n\\) $ m\\times 1$ <p>For each element in \\(D_X\\) , we have:</p> <p>\\(D_{Xi}=\\frac{\\partial L}{\\partial x_i}=\\sum_{j=1}^m\\frac{\\partial L}{\\partial y_j}\\frac{\\partial y_j}{\\partial x_i}\\\\\\)</p>"},{"location":"AI/CS231n/CS231n_notes/#5-convolutional-neural-networks","title":"5 - Convolutional Neural Networks","text":""},{"location":"AI/CS231n/CS231n_notes/#convolution-layer","title":"Convolution Layer","text":""},{"location":"AI/CS231n/CS231n_notes/#introduction","title":"Introduction","text":"<p>Convolve a filter with an image: Slide the filter spatially within the image, computing dot products in each region.</p> <p>Giving a \\(32\\times32\\times3\\) image and a \\(5\\times5\\times3\\) filter, a convolution looks like:</p> <p></p> <p>Convolve six \\(5\\times5\\times3\\) filters to a \\(32\\times32\\times3\\) image with step size \\(1\\), we can get a \\(28\\times28\\times6\\) feature:</p> <p></p> <p>With an activation function after each convolution layer, we can build the ConvNet with a sequence of convolution layers:</p> <p></p> <p>By changing the step size between each move for filters, or adding zero-padding around the image, we can modify the size of the output:</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#1times1-convolution-layer","title":"\\(1\\times1\\) Convolution Layer","text":"<p>This kind of layer makes perfect sense. It is usually used to change the dimension (channel) of features.</p> <p>A \\(1\\times1\\) convolution layer can also be treated as a full-connected linear layer.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#summary_1","title":"Summary","text":"Input image size \\(W_1\\times H_1\\times C\\) filter size \\(F\\times F\\times C\\) filter number \\(K\\) stride \\(S\\) zero padding \\(P\\) Output output size \\(W_2\\times H_2\\times K\\) output width \\(W_2=\\frac{W_1-F+2P}{S}+1\\\\\\) output height \\(H_2=\\frac{H_1-F+2P}{S}+1\\\\\\) Parameters parameter number (weight) \\(F^2CK\\) parameter number (bias) \\(K\\)"},{"location":"AI/CS231n/CS231n_notes/#pooling-layer","title":"Pooling layer","text":"<p>Make the representations smaller and more manageable.</p> <p>An example of max pooling:</p> <p></p> Input image size \\(W_1\\times H_1\\times C\\) spatial extent \\(F\\times F\\) stride \\(S\\) Output output size \\(W_2\\times H_2\\times C\\) output width \\(W_2=\\frac{W_1-F}{S}+1\\\\\\) output height \\(H_2=\\frac{H_1-F}{S}+1\\\\\\)"},{"location":"AI/CS231n/CS231n_notes/#convolutional-neural-networks-cnn","title":"Convolutional Neural Networks (CNN)","text":"<p>CNN stack CONV, POOL, FC layers.</p> <p>CNN Trends:</p> <ol> <li>Smaller filters and deeper architectures.</li> <li>Getting rid of POOL/FC layers (just CONV).</li> </ol> <p>Historically architectures of CNN looked like:</p> <p></p> <p>where usually \\(m\\) is large, \\(0\\le n\\le5\\), \\(0\\le k\\le2\\).</p> <p>Recent advances such as ResNet / GoogLeNet have challenged this paradigm.</p>"},{"location":"AI/CS231n/CS231n_notes/#6-cnn-architectures","title":"6 - CNN Architectures","text":"<p>Best model in ImageNet competition:</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#alexnet","title":"AlexNet","text":"<p>8 layers.</p> <p>First use of ConvNet in image classification problem.</p> <p>Filter size decreases in deeper layer.</p> <p>Channel number increases in deeper layer.</p> <p></p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#vgg","title":"VGG","text":"<p>19 layers. (also provide 16 layers edition)</p> <p>Static filter size (\\(3\\times3\\)) in all layers:</p> <ol> <li>The effective receptive field expands with the layer gets deeper.</li> <li>Deeper architecture gets more non-linearities and few parameters.</li> </ol> <p></p> <p>Most memory is in early convolution layers.</p> <p>Most parameter is in late FC layers.</p> <p></p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#googlenet","title":"GoogLeNet","text":"<p>22 layers.</p> <p>No FC layers, only 5M parameters. ( \\(8.3\\%\\) of AlexNet, \\(3.7\\%\\) of VGG )</p> <p>Devise efficient \"inception module\".</p>"},{"location":"AI/CS231n/CS231n_notes/#inception-module","title":"Inception Module","text":"<p>Design a good local network topology (network within a network) and then stack these modules on top of each other.</p> <p>Naive Inception Module:</p> <ol> <li>Apply parallel filter operations on the input from previous layer.</li> <li>Concatenate all filter outputs together channel-wise.</li> <li>Problem: The depth (channel number) increases too fast, costing expensive computation.</li> </ol> <p></p> <p>Inception Module with Dimension Reduction:</p> <ol> <li>Add \"bottle neck\" layers to reduce the dimension.</li> <li>Also get fewer computation cost.</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#architecture","title":"Architecture","text":""},{"location":"AI/CS231n/CS231n_notes/#resnet","title":"ResNet","text":"<p>152 layers for ImageNet.</p> <p>Devise \"residual connections\".</p> <p>Use BN in place of dropout.</p>"},{"location":"AI/CS231n/CS231n_notes/#residual-connections","title":"Residual Connections","text":"<p>Hypothesis: Deeper models have more representation power than shallow ones. But they are harder to optimize.</p> <p>Solution: Use network layers to fit a residual mapping instead of directly trying to fit a desired underlying mapping.</p> <p></p> <p>It is necessary to use ReLU as activation function, in order to apply identity mapping when \\(F(x)=0\\) .</p>"},{"location":"AI/CS231n/CS231n_notes/#architecture_1","title":"Architecture","text":""},{"location":"AI/CS231n/CS231n_notes/#senet","title":"SENet","text":"<p>Using ResNeXt-152 as a base architecture.</p> <p>Add a \u201cfeature recalibration\u201d module. (adjust weights of each channel)</p> <p>Using the global avg-pooling layer + FC layers to determine feature map weights.</p> <p></p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#improvements-of-resnet","title":"Improvements of ResNet","text":"<p>Wide Residual Networks, ResNeXt, DenseNet, MobileNets...</p>"},{"location":"AI/CS231n/CS231n_notes/#other-interesting-networks","title":"Other Interesting Networks","text":"<p>NASNet: Neural Architecture Search with Reinforcement Learning.</p> <p>EfficientNet: Smart Compound Scaling.</p>"},{"location":"AI/CS231n/CS231n_notes/#7-training-neural-networks","title":"7 - Training Neural Networks","text":""},{"location":"AI/CS231n/CS231n_notes/#activation-functions","title":"Activation Functions","text":"Activation Usage Sigmoid, tanh Do not use. ReLU Use as default. Leaky ReLU, Maxout, ELU, SELU Replace ReLU to squeeze out some marginal gains. Swish No clear usage."},{"location":"AI/CS231n/CS231n_notes/#data-processing","title":"Data Processing","text":"<p>Apply centralization and normalization before training.</p> <p>In practice for pictures, usually we apply channel-wise centralization only.</p>"},{"location":"AI/CS231n/CS231n_notes/#weight-initialization","title":"Weight Initialization","text":"<p>Assume that we have 6 layers in a network.</p> <p>\\(D_i\\) : input size of layer \\(i\\)</p> <p>\\(W_i\\) : weights in layer \\(i\\)</p> <p>\\(X_i\\) : output after activation of layer \\(i\\), we have \\(X_i=g(Z_i)=g(W_iX_{i-1}+B_i)\\)</p> <p>We initialize each parameter in \\(W_i\\) randomly in \\([-k_i,k_i]\\) .</p> Tanh Activation Output Distribution \\(k_i=0.01\\) \\(k_i=0.05\\) Xavier Initialization \\(k_i=\\frac{1}{\\sqrt{D_i}\\\\}\\) <p>When \\(k_i=0.01\\), the variance keeps decreasing as the layer gets deeper. As a result, the output of each neuron in deep layer will all be 0. The partial derivative \\(\\frac{\\partial Z_i}{\\partial W_i}=X_{i-1}=0\\\\\\). (no gradient)</p> <p>When \\(k_i=0.05\\), most neurons is saturated. The partial derivative \\(\\frac{\\partial X_i}{\\partial Z_i}=g'(Z_i)=0\\\\\\). (no gradient)</p> <p>To solve this problem, We need to keep the variance same in each layer.</p> <p>Assuming that \\(Var\\big(X_{i-1}^{(1)}\\big)=Var\\big(X_{i-1}^{(2)}\\big)=\\dots=Var\\big(X_{i-1}^{(D_i)}\\big)\\)</p> <p>We have \\(Z_i=X_{i-1}^{(1)}W_i^{(:,1)}+X_{i-1}^{(2)}W_i^{(:,2)}+\\dots+X_{i-1}^{(D_i)}W_i^{(:,D_i)}=\\sum_{n=1}^{D_i}X_{i-1}^{(n)}W_i^{(:,n)}\\\\\\)</p> <p>We want \\(Var\\big(Z_i\\big)=Var\\big(X_{i-1}^{(n)}\\big)\\)</p> <p>Let's do some conduction:</p> <p>\\(\\begin{aligned}Var\\big(Z_i\\big)&amp;=Var\\Bigg(\\sum_{n=1}^{D_i}X_{i-1}^{(n)}W_i^{(:,n)}\\Bigg)\\\\&amp;=D_i\\ Var\\Big(X_{i-1}^{(n)}W_i^{(:,n)}\\Big)\\\\&amp;=D_i\\ Var\\Big(X_{i-1}^{(n)}\\Big)\\ Var\\Big(W_i^{(:,n)}\\Big)\\end{aligned}\\)</p> <p>So \\(Var\\big(Z_i\\big)=Var\\big(X_{i-1}^{(n)}\\big)\\) only when \\(Var\\Big(W_i^{(:,n)}\\Big)=\\frac{1}{D_i}\\\\\\), that is to say \\(k_i=\\frac{1}{\\sqrt{D_i}}\\\\\\)</p> ReLU Activation Output Distribution Xavier Initialization \\(k_i=\\frac{1}{\\sqrt{D_i}\\\\}\\) Kaiming Initialization \\(k_i=\\sqrt{2D_i}\\) <p>For ReLU activation, when using xavier initialization, there still exist \"variance decreasing\" problem.</p> <p>We can use kaiming initialization instead to fix this.</p>"},{"location":"AI/CS231n/CS231n_notes/#batch-normalization","title":"Batch Normalization","text":"<p>Force the inputs to be \"nicely scaled\" at each layer.</p> <p>\\(N\\) : batch size</p> <p>\\(D\\) : feature size</p> <p>\\(x\\) : input with shape \\(N\\times D\\) </p> <p>\\(\\gamma\\) : learnable scale and shift parameter with shape \\(D\\)</p> <p>\\(\\beta\\) : learnable scale and shift parameter with shape \\(D\\)</p> <p>The procedure of batch normalization:</p> <ol> <li>Calculate channel-wise mean \\(\\mu_j=\\frac{1}{N}\\sum_{i=1}^Nx_{i,j}\\\\\\) . The result \\(\\mu\\) with shape \\(D\\) .</li> <li>Calculate channel-wise variance \\(\\sigma_j^2=\\frac{1}{N}\\sum_{i=1}^N(x_{i,j}-\\mu_j)^2\\\\\\) . The result \\(\\sigma^2\\) with shape \\(D\\) .</li> <li>Calculate normalized \\(\\hat{x}_{i,j}=\\frac{x_{i,j}-\\mu_j}{\\sqrt{\\sigma_j^2+\\epsilon}}\\\\\\) . The result \\(\\hat{x}\\) with shape \\(N\\times D\\) .</li> <li>Scale normalized input to get output \\(y_{i,j}=\\gamma_j\\hat{x}_{i,j}+\\beta_j\\) . The result \\(y\\) with shape \\(N\\times D\\) .</li> </ol> <p>Why scale: The constraint \"zero-mean, unit variance\" may be too hard.</p> <p></p> <p>Pros:</p> <ol> <li>Makes deep networks much easier to train!</li> <li>Improves gradient flow.</li> <li>Allows higher learning rates, faster convergence.</li> <li>Networks become more robust to initialization.</li> <li>Acts as regularization during training.</li> <li>Zero overhead at test-time: can be fused with conv!</li> </ol> <p>Cons:</p> <p>Behaves differently during training and testing: this is a very common source of bugs!</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#transfer-learning","title":"Transfer Learning","text":"<p>Train on a pre-trained model with other datasets.</p> <p>An empirical suggestion:</p> very similar  dataset very different  dataset very little data Use Linear Classifier on top layer. You\u2019re in trouble\u2026 Try linear classifier from different stages. quite a lot of data Finetune a few layers. Finetune a larger number of layers."},{"location":"AI/CS231n/CS231n_notes/#regularization","title":"Regularization","text":""},{"location":"AI/CS231n/CS231n_notes/#common-pattern-of-regularization","title":"Common Pattern of Regularization","text":"<p>Training: Add some kind of randomness. \\(y=f(x,z)\\)</p> <p>Testing: Average out randomness (sometimes approximate). \\(y=f(x)=E_z\\big[f(x,z)\\big]=\\int p(z)f(x,z)dz\\\\\\)</p>"},{"location":"AI/CS231n/CS231n_notes/#regularization-term","title":"Regularization Term","text":"<p>L2 regularization: \\(R(W)=\\sum_k\\sum_lW_{k,l}^2\\) (weight decay)</p> <p>L1 regularization: \\(R(W)=\\sum_k\\sum_l|W_{k,l}|\\)</p> <p>Elastic net : \\(R(W)=\\sum_k\\sum_l\\big(\\beta W_{k,l}^2+|W_{k,l}|\\big)\\) (L1+L2)</p>"},{"location":"AI/CS231n/CS231n_notes/#dropout","title":"Dropout","text":"<p>Training: Randomly set some neurons to 0 with a probability \\(p\\) .</p> <p>Testing: Each neuron multiplies by dropout probability \\(p\\) . (scale the output back)</p> <p>More common: Scale the output with \\(\\frac{1}{p}\\) when training, keep the original output when testing.</p> <p></p> <p>Why dropout works:</p> <ol> <li>Forces the network to have a redundant representation. Prevents co-adaptation of features.</li> <li>Another interpretation: Dropout is training a large ensemble of models (that share parameters).</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#batch-normalization_1","title":"Batch Normalization","text":"<p>See above.</p>"},{"location":"AI/CS231n/CS231n_notes/#data-augmentation","title":"Data Augmentation","text":"<ol> <li>Horizontal Flips</li> <li>Random Crops and Scales</li> <li>Color Jitter</li> <li>Rotation</li> <li>Stretching</li> <li>Shearing</li> <li>Lens Distortions</li> <li>...</li> </ol> <p>There also exists automatic data augmentation method using neural networks.</p>"},{"location":"AI/CS231n/CS231n_notes/#other-methods-and-summary","title":"Other Methods and Summary","text":"<p>DropConnect: Drop connections between neurons.</p> <p>Fractional Max Pooling: Use randomized pooling regions.</p> <p>Stochastic Depth: Skip some layers in the network.</p> <p>Cutout: Set random image regions to zero.</p> <p>Mixup: Train on random blends of images.</p> Regularization Method Usage Dropout For large fully-connected layers. Batch Normalization &amp; Data Augmentation Almost always a good idea. Cutout &amp; Mixup For small classification datasets."},{"location":"AI/CS231n/CS231n_notes/#hyperparameter-tuning","title":"Hyperparameter Tuning","text":"Most Common Hyperparameters Less Sensitive Hyperparameters learning ratelearning rate decay scheduleweight decay setting of momentum... <p>Tips on hyperparameter tuning:</p> <ol> <li>Prefer one validation fold to cross-validation.</li> <li>Search for hyperparameters on log scale. (e.g. multiply the hyperparameter by a fixed number \\(k\\) at each search)</li> <li>Prefer random search to grid search.</li> <li>Careful with best values on border.</li> <li>Stage your search from coarse to fine.</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#implementation","title":"Implementation","text":"<p>Have a worker that continuously samples random hyperparameters and performs the optimization. During the training, the worker will keep track of the validation performance after every epoch, and writes a model checkpoint to a file.</p> <p>Have a master that launches or kills workers across a computing cluster, and may additionally inspect the checkpoints written by workers and plot their training statistics.</p>"},{"location":"AI/CS231n/CS231n_notes/#common-procedures","title":"Common Procedures","text":"<ol> <li>Check initial loss.</li> </ol> <p>Turn off weight decay, sanity check loss at initialization \\(\\log(C)\\) for softmax with \\(C\\) classes.</p> <ol> <li>Overfit a small sample. (important)</li> </ol> <p>Try to train to 100% training accuracy on a small sample of training data.</p> <p>Fiddle with architecture, learning rate, weight initialization.</p> <ol> <li>Find learning rate that makes loss go down.</li> </ol> <p>Use the architecture from the previous step, use all training data, turn on small weight decay, find a learning rate that makes the loss drop significantly within 100 iterations.</p> <p>Good learning rates to try: \\(0.1,0.01,0.001,0.0001,\\dots\\)</p> <ol> <li>Coarse grid, train for 1-5 epochs.</li> </ol> <p>Choose a few values of learning rate and weight decay around what worked from Step 3, train a few models for 1-5 epochs.\\</p> <p>Good weight decay to try: \\(0.0001,0.00001,0\\)</p> <ol> <li>Refine grid, train longer.</li> </ol> <p>Pick best models from Step 4, train them for longer (10-20 epochs) without learning rate decay.</p> <ol> <li>Look at loss and accuracy curves.</li> <li>GOTO step 5.</li> </ol>"},{"location":"AI/CS231n/CS231n_notes/#gradient-checks","title":"Gradient Checks","text":"<p>CS231n Convolutional Neural Networks for Visual Recognition</p> <p>Compute analytical gradient manually using \\(f_a'=\\frac{\\partial f(x)}{\\partial x}=\\frac{f(x-h)-f(x+h)}{2h}\\\\\\)</p> <p>Get relative error between numerical gradient \\(f_n'\\) and analytical gradient \\(f_a'\\) using \\(E=\\frac{|f_n'-f_a'|}{\\max{|f_n'|,|f_a'|}}\\\\\\)</p> Relative Error Result \\(E&gt;10^{-2}\\) Probably \\(f_n'\\) is wrong. \\(10^{-2}&gt;E&gt;10^{-4}\\) Not good, should check the gradient. \\(10^{-4}&gt;E&gt;10^{-6}\\) Okay for objectives with kinks. (e.g. ReLU)Not good for objectives with no kink. (e.g. softmax, tanh) \\(10^{-7}&gt;E\\) Good. <p>Tips on gradient checks:</p> <ol> <li>Use double precision.</li> <li>Use only few data points.</li> <li>Careful about kinks in the objective. (e.g. \\(x=0\\) for ReLU activation)</li> <li>Careful with the step size \\(h\\).</li> <li>Use gradient check after the loss starts to go down.</li> <li>Remember to turn off anything that may affect the gradient. (e.g. regularization / dropout / augmentations)</li> <li>Check only few dimensions for every parameter. (reduce time cost)</li> </ol>"},{"location":"AI/CS231n/CS231n_notes/#8-visualizing-and-understanding","title":"8 - Visualizing and Understanding","text":""},{"location":"AI/CS231n/CS231n_notes/#feature-visualization-and-inversion","title":"Feature Visualization and Inversion","text":""},{"location":"AI/CS231n/CS231n_notes/#visualizing-what-models-have-learned","title":"Visualizing what models have learned","text":"Visualize Areas Filters Visualize the raw weights of each convolution kernel. (better in the first layer) Final Layer Features Run dimensionality reduction for features in the last FC layer. (PCA, t-SNE...) Activations Visualize activated areas. (Understanding Neural Networks Through Deep Visualization)"},{"location":"AI/CS231n/CS231n_notes/#understanding-input-pixels","title":"Understanding input pixels","text":""},{"location":"AI/CS231n/CS231n_notes/#maximally-activating-patches","title":"Maximally Activating Patches","text":"<ol> <li>Pick a layer and a channel.</li> <li>Run many images through the network, record values of the chosen channel.</li> <li>Visualize image patches that correspond to maximal activation features.</li> </ol> <p>For example, we have a layer with shape \\(128\\times13\\times13\\). We pick the 17th channel from all 128 channels. Then we run many pictures through the network. During each run we can find a maximal activation feature among all the \\(13\\times13\\) features in channel 17. We then record the corresponding picture patch for each maximal activation feature. At last, we visualize all picture patches for each feature.</p> <p>This will help us find the relationship between each maximal activation feature and its corresponding picture patches.</p> <p>(each row of the following picture represents a feature)</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#saliency-via-occlusion","title":"Saliency via Occlusion","text":"<p>Mask part of the image before feeding to CNN, check how much predicted probabilities change.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#saliency-via-backprop","title":"Saliency via Backprop","text":"<ol> <li>Compute gradient of (unnormalized) class score with respect to image pixels.</li> <li>Take absolute value and max over RGB channels to get saliency maps.</li> </ol>"},{"location":"AI/CS231n/CS231n_notes/#intermediate-features-via-guided-backprop","title":"Intermediate Features via Guided Backprop","text":"<ol> <li>Pick a single intermediate neuron. (e.g. one feature in a \\(128\\times13\\times13\\) feature map)</li> <li>Compute gradient of neuron value with respect to image pixels.</li> </ol> <p>Striving for Simplicity: The All Convolutional Net</p> <p>Just like \"Maximally Activating Patches\", this could find the part of an image that a neuron responds to.</p> <p></p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#gradient-ascent","title":"Gradient Ascent","text":"<p>Generate a synthetic image that maximally activates a neuron.</p> <ol> <li>Initialize image \\(I\\) to zeros.</li> <li>Forward image to compute current scores \\(S_c(I)\\) (for class \\(c\\) before softmax).</li> <li>Backprop to get gradient of neuron value with respect to image pixels.</li> <li>Make a small update to the image.</li> </ol> <p>Objective: \\(\\max S_c(I)-\\lambda\\lVert I\\lVert^2\\)</p> <p>Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps</p> <p></p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#adversarial-examples","title":"Adversarial Examples","text":"<p>Find an fooling image that can make the network misclassify correctly-classified images when it is added to the image.</p> <ol> <li>Start from an arbitrary image.</li> <li>Pick an arbitrary class.</li> <li>Modify the image to maximize the class.</li> <li>Repeat until network is fooled.</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#deepdream-and-style-transfer","title":"DeepDream and Style Transfer","text":""},{"location":"AI/CS231n/CS231n_notes/#feature-inversion","title":"Feature Inversion","text":"<p>Given a CNN feature vector \\(\\Phi_0\\) for an image, find a new image \\(x\\) that:</p> <ol> <li>Features of new image \\(\\Phi(x)\\) matches the given feature vector \\(\\Phi_0\\).</li> <li>\"looks natural\u201d. (image prior regularization)</li> </ol> <p>Objective: \\(\\min \\lVert\\Phi(x)-\\Phi_0\\lVert+\\lambda R(x)\\)</p> <p>Understanding Deep Image Representations by Inverting Them</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#deepdream-amplify-existing-features","title":"DeepDream: Amplify Existing Features","text":"<p>Given an image, amplify the neuron activations at a layer to generate a new one.</p> <ol> <li>Forward: compute activations at chosen layer.</li> <li>Set gradient of chosen layer equal to its activation.</li> <li>Backward: Compute gradient on image.</li> <li>Update image.</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#texture-synthesis","title":"Texture Synthesis","text":""},{"location":"AI/CS231n/CS231n_notes/#nearest-neighbor","title":"Nearest Neighbor","text":"<ol> <li>Generate pixels one at a time in scanline order</li> <li>Form neighborhood of already generated pixels, copy the nearest neighbor from input.</li> </ol>"},{"location":"AI/CS231n/CS231n_notes/#neural-texture-synthesis","title":"Neural Texture Synthesis","text":"<p>Gram Matrix: \u683c\u62c9\u59c6\u77e9\u9635\uff08Gram matrix\uff09\u8be6\u7ec6\u89e3\u8bfb</p> <ol> <li>Pretrain a CNN on ImageNet.</li> <li>Run input texture forward through CNN, record activations on every layer.</li> </ol> <p>Layer \\(i\\) gives feature map of shape \\(C_i\\times H_i\\times W_i\\).</p> <ol> <li>At each layer compute the Gram matrix \\(G_i\\) giving outer product of features.</li> </ol> <ul> <li>Reshape feature map at layer \\(i\\) to \\(C_i\\times H_iW_i\\).</li> <li>Compute the Gram matrix \\(G_i\\) with shape \\(C_i\\times C_i\\).</li> </ul> <ol> <li>Initialize generated image from random noise.</li> <li>Pass generated image through CNN, compute Gram matrix \\(\\hat{G}_l\\) on each layer.</li> <li>Compute loss: Weighted sum of L2 distance between Gram matrices.</li> </ol> <ul> <li>\\(E_l=\\frac{1}{aN_l^2M_l^2}\\sum_{i,j}\\Big(G_i^{(i,j)}-\\hat{G}_i^{(i,j)}\\Big)^2\\\\\\)</li> <li>\\(\\mathcal{L}(\\vec{x},\\hat{\\vec{x}})=\\sum_{l=0}^L\\omega_lE_l\\\\\\)</li> </ul> <ol> <li>Backprop to get gradient on image.</li> <li>Make gradient step on image.</li> <li>GOTO 5.</li> </ol> <p>Texture Synthesis Using Convolutional Neural Networks</p> <p></p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#style-transfer","title":"Style Transfer","text":""},{"location":"AI/CS231n/CS231n_notes/#feature-gram-reconstruction","title":"Feature + Gram Reconstruction","text":"<p>Problem: Style transfer requires many forward / backward passes. Very slow!</p>"},{"location":"AI/CS231n/CS231n_notes/#fast-style-transfer","title":"Fast Style Transfer","text":""},{"location":"AI/CS231n/CS231n_notes/#9-object-detection-and-image-segmentation","title":"9 - Object Detection and Image Segmentation","text":""},{"location":"AI/CS231n/CS231n_notes/#semantic-segmentation","title":"Semantic Segmentation","text":"<p>Paired Training Data: For each training image, each pixel is labeled with a semantic category.</p> <p></p> <p>Fully Convolutional Network: Design a network with only convolutional layers without downsampling operators to make predictions for pixels all at once!</p> <p></p> <p>Problem: Convolutions at original image resolution will be very expensive...</p> <p>Solution: Design fully convolutional network with downsampling and upsampling inside it!</p> <ul> <li>Downsampling: Pooling, strided convolution.</li> <li>Upsampling: Unpooling, transposed convolution.</li> </ul> <p>Unpooling:</p> Nearest Neighbor \"Bed of Nails\" \"Position Memory\" <p>Transposed Convolution: (example size \\(3\\times3\\), stride \\(2\\), pad \\(1\\))</p> Normal Convolution Transposed Convolution <p></p>"},{"location":"AI/CS231n/CS231n_notes/#object-detection","title":"Object Detection","text":""},{"location":"AI/CS231n/CS231n_notes/#single-object","title":"Single Object","text":"<p>Classification + Localization. (classification + regression problem)</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#multiple-object","title":"Multiple Object","text":""},{"location":"AI/CS231n/CS231n_notes/#r-cnn","title":"R-CNN","text":"<p>Using selective search to find \u201cblobby\u201d image regions that are likely to contain objects.</p> <ol> <li>Find regions of interest (RoI) using selective search. (region proposal)</li> <li>Forward each region through ConvNet.</li> <li>Classify features with SVMs.</li> </ol> <p>Problem: Very slow. Need to do 2000 independent forward passes for each image!</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#fast-r-cnn","title":"Fast R-CNN","text":"<p>Pass the image through ConvNet before cropping. Crop the conv feature instead.</p> <ol> <li>Run whole image through ConvNet.</li> <li>Find regions of interest (RoI) from conv features using selective search. (region proposal)</li> <li>Classify RoIs using CNN.</li> </ol> <p>Problem: Runtime is dominated by region proposals. (about \\(90\\%\\) time cost)</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#faster-r-cnn","title":"Faster R-CNN","text":"<p>Insert Region Proposal Network (RPN) to predict proposals from features.</p> <p>Otherwise same as Fast R-CNN: Crop features for each proposal, classify each one.</p> <p>Region Proposal Network (RPN) : Slide many fixed windows over ConvNet features.</p> <ol> <li>Treat each point in the feature map as the anchor. </li> </ol> <p>We have \\(k\\) fixed windows (anchor boxes) of different size/scale centered with each anchor.</p> <ol> <li>For each anchor box, predict whether it contains an object.</li> </ol> <p>For positive boxes, also predict a corrections to the ground-truth box.</p> <ol> <li>Slide anchor over the feature map, get the \u201cobjectness\u201d score for each box at each point.</li> <li>Sort the \u201cobjectness\u201d score, take top \\(300\\) as the proposals.</li> </ol> <p></p> <p>Faster R-CNN is a Two-stage object detector:</p> <ol> <li>First stage: Run once per image</li> </ol> <p>Backbone network</p> <p>Region proposal network</p> <ol> <li>Second stage: Run once per region</li> </ol> <p>Crop features: RoI pool / align</p> <p>Predict object class</p> <p>Prediction bbox offset</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#single-stage-object-detectors-yolo","title":"Single-Stage Object Detectors: YOLO","text":"<p>You Only Look Once: Unified, Real-Time Object Detection</p> <ol> <li>Divide image into grids. (example image grids shape \\(7\\times7\\))</li> <li>Set anchors in the middle of each grid.</li> <li>For each grid:    - Using \\(B\\) anchor boxes to regress \\(5\\) numbers: \\(\\text{dx, dy, dh, dw, confidence}\\).    - Predict scores for each of \\(C\\) classes.</li> <li>Finally the output is \\(7\\times7\\times(5B+C)\\).</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#instance-segmentation","title":"Instance Segmentation","text":"<p>Mask R-CNN: Add a small mask network that operates on each RoI and predicts a \\(28\\times28\\) binary mask.</p> <p></p> <p>Mask R-CNN performs very good results!</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#10-recurrent-neural-networks","title":"10 - Recurrent Neural Networks","text":"<p>Supplement content added according to Deep Learning Book - RNN.</p>"},{"location":"AI/CS231n/CS231n_notes/#recurrent-neural-network-rnn","title":"Recurrent Neural Network (RNN)","text":""},{"location":"AI/CS231n/CS231n_notes/#motivation-sequence-processing","title":"Motivation: Sequence Processing","text":"One to One One to Many Many to One Many to Many Many to Many Vanilla Neural Networks Image Captioning Action Prediction Video Captioning Video Classification on Frame Level"},{"location":"AI/CS231n/CS231n_notes/#vanilla-rnn","title":"Vanilla RNN","text":"<p>\\(x^{(t)}\\) : Input at time \\(t\\).</p> <p>\\(h^{(t)}\\) : State at time \\(t\\).</p> <p>\\(o^{(t)}\\) : Output at time \\(t\\)\u200b\u200b.</p> <p>\\(y^{(t)}\\) : Expected output at time \\(t\\).</p>"},{"location":"AI/CS231n/CS231n_notes/#many-to-one","title":"Many to One","text":"Calculation State Transition \\(h^{(t)}=\\tanh(Wh^{(t-1)}+Ux^{(t)}+b)\\) Output Calculation \\(o^{(\\tau)}=\\text{sigmoid}\\ \\big(Vh^{(\\tau)}+c\\big)\\)"},{"location":"AI/CS231n/CS231n_notes/#many-to-many-type-2","title":"Many to Many (type 2)","text":"Calculation State Transition \\(h^{(t)}=\\tanh(Wh^{(t-1)}+Ux^{(t)}+b)\\) Output Calculation \\(o^{(t)}=\\text{sigmoid}\\ \\big(Vh^{(t)}+c\\big)\\)"},{"location":"AI/CS231n/CS231n_notes/#rnn-with-teacher-forcing","title":"RNN with Teacher Forcing","text":"<p>Update current state according to last-time output instead of last-time state.</p> <p></p> Calculation State Transition \\(h^{(t)}=\\tanh(Wo^{(t-1)}+Ux^{(t)}+b)\\) Output Calculation \\(o^{(t)}=\\text{sigmoid}\\ \\big(Vh^{(t)}+c\\big)\\)"},{"location":"AI/CS231n/CS231n_notes/#rnn-with-output-forwarding","title":"RNN with \"Output Forwarding\"","text":"<p>We can also combine last-state output with this-state input together.</p> <p></p> Calculation State Transition (training) \\(h^{(t)}=\\tanh(Wh^{(t-1)}+Ux^{(t)}+Ry^{(t-1)}+b)\\) State Transition (testing) \\(h^{(t)}=\\tanh(Wh^{(t-1)}+Ux^{(t)}+Ro^{(t-1)}+b)\\) Output Calculation \\(o^{(t)}=\\text{sigmoid}\\ \\big(Vh^{(t)}+c\\big)\\) <p>Usually we use \\(o^{(t-1)}\\) in place of \\(y^{(t-1)}\\) at testing time.</p>"},{"location":"AI/CS231n/CS231n_notes/#bidirectional-rnn","title":"Bidirectional RNN","text":"<p>When dealing with a whole input sequence, we can process features from two directions.</p> <p></p> Calculation State Transition (forward) \\(h^{(t)}=\\tanh(W_1h^{(t-1)}+U_1x^{(t)}+b_1)\\) State Transition (backward) \\(g^{(t)}=\\tanh(W_2g^{(t+1)}+U_2x^{(t)}+b_2)\\) Output Calculation \\(o^{(t)}=\\text{sigmoid}\\ \\big(Vh^{(t)}+Wg^{(t)}+c\\big)\\)"},{"location":"AI/CS231n/CS231n_notes/#encoder-decoder-sequence-to-sequence-rnn","title":"Encoder-Decoder Sequence to Sequence RNN","text":"<p>This is a many-to-many structure (type 1).</p> <p>First we encode information according to \\(x\\) with no output.</p> <p>Later we decode information according to \\(y\\) with no input.</p> <p>\\(C\\) : Context vector, often \\(C=h^{(T)}\\) (last state of encoder).</p> <p></p> Calculation State Transition (encode) \\(h^{(t)}=\\tanh(W_1h^{(t-1)}+U_1x^{(t)}+b_1)\\) State Transition (decode, training) \\(s^{(t)}=\\tanh(W_2s^{(t-1)}+U_2y^{(t)}+TC+b_2)\\) State Transition (decode, testing) \\(s^{(t)}=\\tanh(W_2s^{(t-1)}+U_2o^{(t)}+TC+b_2)\\) Output Calculation \\(o^{(t)}=\\text{sigmoid}\\ \\big(Vs^{(t)}+c\\big)\\)"},{"location":"AI/CS231n/CS231n_notes/#example-image-captioning","title":"Example: Image Captioning","text":""},{"location":"AI/CS231n/CS231n_notes/#summary_2","title":"Summary","text":"<p>Advantages of RNN:</p> <ol> <li>Can process any length input.</li> <li>Computation for step \\(t\\) can (in theory) use information from many steps back.</li> <li>Model size doesn\u2019t increase for longer input.</li> <li>Same weights applied on every timestep, so there is symmetry in how inputs are processed.</li> </ol> <p>Disadvantages of RNN:</p> <ol> <li>Recurrent computation is slow.</li> <li>In practice, difficult to access information from many steps back.</li> <li>Problems with gradient exploding and gradient vanishing. (check Deep Learning Book - RNN Page 396, Chap 10.7)</li> </ol>"},{"location":"AI/CS231n/CS231n_notes/#long-short-term-memory-lstm","title":"Long Short Term Memory (LSTM)","text":"<p>Add a \"cell block\" to store history weights.</p> <p>\\(c^{(t)}\\) : Cell at time \\(t\\).</p> <p>\\(f^{(t)}\\) : Forget gate at time \\(t\\). Deciding whether to erase the cell.</p> <p>\\(i^{(t)}\\) : Input gate at time \\(t\\). Deciding whether to write to the cell.</p> <p>\\(g^{(t)}\\) : External input gate at time \\(t\\). Deciding how much to write to the cell.</p> <p>\\(o^{(t)}\\) : Output gate at time \\(t\\). Deciding how much to reveal the cell.</p> <p></p> Calculation (Gate) Forget Gate \\(f^{(t)}=\\text{sigmoid}\\ \\big(W_fh^{(t-1)}+U_fx^{(t)}+b_f\\big)\\) Input Gate \\(i^{(t)}=\\text{sigmoid}\\ \\big(W_ih^{(t-1)}+U_ix^{(t)}+b_i\\big)\\) External Input Gate \\(g^{(t)}=\\tanh(W_gh^{(t-1)}+U_gx^{(t)}+b_g)\\) Output Gate \\(o^{(t)}=\\text{sigmoid}\\ \\big(W_oh^{(t-1)}+U_ox^{(t)}+b_o\\big)\\) Calculation (Main) Cell Transition \\(c^{(t)}=f^{(t)}\\odot c^{(t-1)}+i^{(t)}\\odot g^{(t)}\\) State Transition \\(h^{(t)}=o^{(t)}\\odot\\tanh(c^{(t)})\\) Output Calculation \\(O^{(t)}=\\text{sigmoid}\\ \\big(Vh^{(t)}+c\\big)\\) <p></p>"},{"location":"AI/CS231n/CS231n_notes/#other-rnn-variants","title":"Other RNN Variants","text":"<p>GRU...</p>"},{"location":"AI/CS231n/CS231n_notes/#11-attention-and-transformers","title":"11 - Attention and Transformers","text":""},{"location":"AI/CS231n/CS231n_notes/#rnn-with-attention","title":"RNN with Attention","text":"<p>Encoder-Decoder Sequence to Sequence RNN Problem:</p> <p>Input sequence bottlenecked through a fixed-sized context vector \\(C\\). (e.g. \\(T=1000\\))</p> <p></p> <p>Intuitive Solution:</p> <p>Generate new context vector \\(C_t\\) at each step \\(t\\) !</p> <p>\\(e_{t,i}\\) : Alignment score for input \\(i\\) at state \\(t\\). (scalar)</p> <p>\\(a_{t,i}\\) : Attention weight for input \\(i\\) at state \\(t\\).</p> <p>\\(C_t\\) : Context vector at state \\(t\\).</p> <p></p> <p></p> Calculation Alignment Score \\(e_i^{(t)}=f(s^{(t-1)},h^{(i)})\\).Where \\(f\\) is an MLP. Attention Weight \\(a_i^{(t)}=\\text{softmax}\\ (e_i^{(t)})\\).Softmax includes all \\(e_i\\) at state \\(t\\). Context Vector \\(C^{(t)}=\\sum_i a_i^{(t)}h^{(i)}\\) Decoder State Transition \\(s^{(t)}=\\tanh(Ws^{(t-1)}+Uy^{(t)}+TC^{(t)}+b)\\) <p>Example on Image Captioning:</p> <p></p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#general-attention-layer","title":"General Attention Layer","text":"<p>Add linear transformations to the input vector before attention.</p> <p></p> <p>Notice:</p> <ol> <li>Number of queries \\(q\\) is variant. (can be different from the number of keys \\(k\\))</li> <li>Number of outputs \\(y\\) is equal to the number of queries \\(q\\).</li> </ol> <p>Each \\(y\\) is a linear weighting of values \\(v\\).</p> <ol> <li>Alignment \\(e\\) is divided by \\(\\sqrt{D}\\) to avoid \"explosion of softmax\", where \\(D\\) is the dimension of input feature.</li> </ol>"},{"location":"AI/CS231n/CS231n_notes/#self-attention-layer","title":"Self-attention Layer","text":"<p>The query vectors \\(q\\) are also generated from the inputs.</p> <p></p> <p>In this way, the shape of \\(y\\) is equal to the shape of \\(x\\).</p> <p>Example with CNN:</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#positional-encoding","title":"Positional Encoding","text":"<p>Self-attention layer doesn\u2019t care about the orders of the inputs!</p> <p></p> <p>To encode ordered sequences like language or spatially ordered image features, we can add positional encoding to the inputs.</p> <p></p> <p>We use a function \\(P:R\\rightarrow R^d\\) to process the position \\(i\\) into a d-dimensional vector \\(p_i=P(i)\\).</p> Constraint Condition of \\(P\\) Uniqueness \\(P(i)\\ne P(j)\\) Equidistance \\(\\lVert P(i+k)-P(i)\\rVert^2=\\lVert P(j+k)-P(j)\\rVert^2\\) Boundness \\(P(i)\\in[a,b]\\) Determinacy \\(P(i)\\) is always a static value. (function is not dynamic) <p>We can either train a encoder model, or design a fixed function.</p> <p>A Practical Positional Encoding Method: Using \\(\\sin\\) and \\(\\cos\\) with different frequency \\(\\omega\\) at different dimension.</p> <p>\\(P(t)=\\begin{bmatrix}\\sin(\\omega_1,t)\\\\\\cos(\\omega_1,t)\\\\\\\\\\sin(\\omega_2,t)\\\\\\cos(\\omega_2,t)\\\\\\vdots\\\\\\sin(\\omega_{\\frac{d}{2}},t)\\\\\\cos(\\omega_{\\frac{d}{2}},t)\\end{bmatrix}\\), where frequency \\(\\omega_k=\\frac{1}{10000^{\\frac{2k}{d}}}\\\\\\). (wave length \\(\\lambda=\\frac{1}{\\omega}=10000^{\\frac{2k}{d}}\\\\\\))</p> <p>\\(P(t)=\\begin{bmatrix}\\sin(1/10000^{\\frac{2}{d}},t)\\\\\\cos(1/10000^{\\frac{2}{d}},t)\\\\\\\\\\sin(1/10000^{\\frac{4}{d}},t)\\\\\\cos(1/10000^{\\frac{4}{d}},t)\\\\\\vdots\\\\\\sin(1/10000^1,t)\\\\\\cos(1/10000^1,t)\\end{bmatrix}\\), after we substitute \\(\\omega_k\\) into the equation.</p> <p>\\(P(t)\\) is a vector with size \\(d\\), where \\(d\\) is a hyperparameter to choose according to the length of input sequence.</p> <p>An intuition of this method is the binary encoding of numbers.</p> <p></p> <p>[lecture 11d] \u6ce8\u610f\u529b\u548ctransformer (positional encoding \u8865\u5145\uff0c\u4ee3\u7801\u5b9e\u73b0\uff0c\u8ddd\u79bb\u8ba1\u7b97)</p> <p>It is easy to prove that \\(P(t)\\) satisfies \"Equidistance\": (set \\(d=2\\) for example)</p> <p>\\(\\begin{aligned}\\lVert P(i+k)-P(i)\\rVert^2&amp;=\\big[\\sin(\\omega_1,i+k)-\\sin(\\omega_1,i)\\big]^2+\\big[\\cos(\\omega_1,i+k)-\\cos(\\omega_1,i)\\big]^2\\\\&amp;=2-2\\sin(\\omega_1,i+k)\\sin(\\omega_1,i)-2\\cos(\\omega_1,i+k)\\cos(\\omega_1,i)\\\\&amp;=2-2\\cos(\\omega_1,k)\\end{aligned}\\)</p> <p>So the distance is not associated with \\(i\\), we have \\(\\lVert P(i+k)-P(i)\\rVert^2=\\lVert P(j+k)-P(j)\\rVert^2\\).</p> <p>Visualization of \\(P(t)\\) features: (set \\(d=32\\), \\(x\\) axis represents the position of sequence)</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#masked-self-attention-layer","title":"Masked Self-attention Layer","text":"<p>To prevent vectors from looking at future vectors, we manually set alignment scores to \\(-\\infty\\).</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#multi-head-self-attention-layer","title":"Multi-head Self-attention Layer","text":"<p>Multiple self-attention heads in parallel.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#transformer","title":"Transformer","text":"<p>Attention Is All You Need</p>"},{"location":"AI/CS231n/CS231n_notes/#encoder-block","title":"Encoder Block","text":"<p>Inputs: Set of vectors \\(z\\). (in which \\(z_i\\) can be a word in a sentence, or a pixel in a picture...)</p> <p>Output: Set of context vectors \\(c\\). (encoded features of \\(z\\))</p> <p></p> <p>The number of blocks \\(N=6\\) in original paper.</p> <p>Notice:</p> <ol> <li>Self-attention is the only interaction between vectors \\(x_0,x_1,\\dots,x_n\\).</li> <li>Layer norm and MLP operate independently per vector.</li> <li>Highly scalable, highly parallelizable, but high memory usage.</li> </ol>"},{"location":"AI/CS231n/CS231n_notes/#decoder-block","title":"Decoder Block","text":"<p>Inputs: Set of vectors \\(y\\). (\\(y_i\\) can be a word in a sentence, or a pixel in a picture...)</p> <p>Inputs: Set of context vectors \\(c\\).</p> <p>Output: Set of vectors \\(y'\\). (decoded result, \\(y'_i=y_{i+1}\\) for the first \\(n-1\\) number of \\(y'\\))</p> <p></p> <p>The number of blocks \\(N=6\\) in original paper.</p> <p>Notice:</p> <ol> <li>Masked self-attention only interacts with past inputs.</li> <li>Multi-head attention block is NOT self-attention. It attends over encoder outputs.</li> <li>Highly scalable, highly parallelizable, but high memory usage. (same as encoder)</li> </ol> <p>Why we need mask in decoder:</p> <ol> <li>Needs for the special formation of output \\(y'_i=y_{i+1}\\).</li> <li>Needs for parallel computation.</li> </ol> <p>\u4e3e\u4e2a\u4f8b\u5b50\u8bb2\u4e0btransformer\u7684\u8f93\u5165\u8f93\u51fa\u7ec6\u8282\u53ca\u5176\u4ed6</p> <p>\u5728\u6d4b\u8bd5\u6216\u8005\u9884\u6d4b\u65f6\uff0cTransformer\u91ccdecoder\u4e3a\u4ec0\u4e48\u8fd8\u9700\u8981seq mask\uff1f</p>"},{"location":"AI/CS231n/CS231n_notes/#example-on-image-captioning-only-with-transformers","title":"Example on Image Captioning (Only with Transformers)","text":""},{"location":"AI/CS231n/CS231n_notes/#comparing-rnns-to-transformer","title":"Comparing RNNs to Transformer","text":"RNNs Transformer Pros LSTMs work reasonably well for long sequences. 1. Good at long sequences. Each attention calculation looks at all inputs.2. Can operate over unordered sets or ordered sequences with positional encodings.3. Parallel computation: All alignment and attention scores for all inputs can be done in parallel. Cons 1. Expects an ordered sequences of inputs.2. Sequential computation: Subsequent hidden states can only be computed after the previous ones are done. Requires a lot of memory: \\(N\\times M\\) alignment and attention scalers need to be calculated and stored for a single self-attention head."},{"location":"AI/CS231n/CS231n_notes/#comparing-convnets-to-transformer","title":"Comparing ConvNets to Transformer","text":"<p>ConvNets strike back!</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#12-video-understanding","title":"12 - Video Understanding","text":""},{"location":"AI/CS231n/CS231n_notes/#video-classification","title":"Video Classification","text":"<p>Take video classification task for example.</p> <p></p> <p>Input size: \\(C\\times T\\times H\\times W\\).</p> <p>The problem is, videos are quite big. We can't afford to train on raw videos, instead we train on video clips.</p> Raw Videos Video Clips \\(1920\\times1080,\\ 30\\text{fps}\\) \\(112\\times112,\\ 5\\text{f}/3.2\\text{s}\\) \\(10\\text{GB}/\\text{min}\\) \\(588\\text{KB}/\\text{min}\\) <p></p>"},{"location":"AI/CS231n/CS231n_notes/#plain-cnn-structure","title":"Plain CNN Structure","text":""},{"location":"AI/CS231n/CS231n_notes/#single-frame-2d-cnn","title":"Single Frame 2D-CNN","text":"<p>Train a normal 2D-CNN model.</p> <p>Classify each frame independently.</p> <p>Average the result of each frame as the final result.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#late-fusion","title":"Late Fusion","text":"<p>Get high-level appearance of each frame, and combine them.</p> <p>Run 2D-CNN on each frame, pool features and feed to Linear Layers.</p> <p></p> <p>Problem: Hard to compare low-level motion between frames.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#early-fusion","title":"Early Fusion","text":"<p>Compare frames with very first Conv Layer, after that normal 2D-CNN.</p> <p></p> <p>Problem: One layer of temporal processing may not be enough!</p>"},{"location":"AI/CS231n/CS231n_notes/#3d-cnn","title":"3D-CNN","text":"<p>Convolve on 3 dimensions: Height, Width, Time.</p> <p>Input size: \\(C_{in}\\times T\\times H\\times W\\).</p> <p>Kernel size: \\(C_{in}\\times C_{out}\\times 3\\times 3\\times 3\\).</p> <p>Output size: \\(C_{out}\\times T\\times H\\times W\\). (with zero paddling)</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#c3d-vgg-of-3d-cnns","title":"C3D (VGG of 3D-CNNs)","text":"<p>The cost is quite expensive...</p> Network Calculation AlexNet 0.7 GFLOP VGG-16 13.6 GFLOP C3D 39.5 GFLOP"},{"location":"AI/CS231n/CS231n_notes/#two-stream-networks","title":"Two-Stream Networks","text":"<p>Separate motion and appearance.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#i3d-inflating-2d-networks-to-3d","title":"I3D (Inflating 2D Networks to 3D)","text":"<p>Take a 2D-CNN architecture.</p> <p>Replace each 2D conv/pool layer with a 3D version.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#modeling-long-term-temporal-structure","title":"Modeling Long-term Temporal Structure","text":""},{"location":"AI/CS231n/CS231n_notes/#recurrent-convolutional-network","title":"Recurrent Convolutional Network","text":"<p>Similar to multi-layer RNN, we replace the dot-product operation with convolution.</p> <p></p> <p>Feature size in layer \\(L\\), time \\(t-1\\): \\(W_h\\times H\\times W\\).</p> <p>Feature size in layer \\(L-1\\), time \\(t\\): \\(W_x\\times H\\times W\\).</p> <p>Feature size in layer \\(L\\), time \\(t\\): \\((W_h+W_x)\\times H\\times W\\).</p> <p></p> <p>Problem: RNNs are slow for long sequences. (can\u2019t be parallelized)</p>"},{"location":"AI/CS231n/CS231n_notes/#spatio-temporal-self-attention","title":"Spatio-temporal Self-attention","text":"<p>Introduce self-attention into video classification problems.</p> <p></p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#vision-transformers-for-video","title":"Vision Transformers for Video","text":"<p>Factorized attention: Attend over space / time.</p> <p>So many papers...</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#visualizing-video-models","title":"Visualizing Video Models","text":""},{"location":"AI/CS231n/CS231n_notes/#multimodal-video-understanding","title":"Multimodal Video Understanding","text":""},{"location":"AI/CS231n/CS231n_notes/#temporal-action-localization","title":"Temporal Action Localization","text":"<p>Given a long untrimmed video sequence, identify frames corresponding to different actions.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#spatio-temporal-detection","title":"Spatio-Temporal Detection","text":"<p>Given a long untrimmed video, detect all the people in both space and time and classify the activities they are performing.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#visually-guided-audio-source-separation","title":"Visually-guided Audio Source Separation","text":"<p>And So on...</p>"},{"location":"AI/CS231n/CS231n_notes/#13-generative-models","title":"13 - Generative Models","text":""},{"location":"AI/CS231n/CS231n_notes/#pixelrnn-and-pixelcnn","title":"PixelRNN and PixelCNN","text":""},{"location":"AI/CS231n/CS231n_notes/#fully-visible-belief-network-fvbn","title":"Fully Visible Belief Network (FVBN)","text":"<p>\\(p(x)\\) : Likelihood of image \\(x\\).</p> <p>\\(p(x_1,x_2,\\dots,x_n)\\) : Joint likelihood of all \\(n\\) pixels in image \\(x\\).</p> <p>\\(p(x_i|x_1,x_2,\\dots,x_{i-1})\\) : Probability of pixel \\(i\\) value given all previous pixels.</p> <p>For explicit density models, we have \\(p(x)=p(x_1,x_2,\\dots,x_n)=\\prod_{i=1}^np(x_i|x_1,x_2,\\dots,x_{i-1})\\\\\\).</p> <p>Objective: Maximize the likelihood of training data.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#pixelrnn","title":"PixelRNN","text":"<p>Generate image pixels starting from corner.</p> <p>Dependency on previous pixels modeled using an RNN (LSTM).</p> <p>Drawback: Sequential generation is slow in both training and inference!</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#pixelcnn","title":"PixelCNN","text":"<p>Still generate image pixels starting from corner.</p> <p>Dependency on previous pixels modeled using a CNN over context region (masked convolution).</p> <p>Drawback: Though its training is faster, its generation is still slow. (pixel by pixel)</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#variational-autoencoder","title":"Variational Autoencoder","text":"<p>Supplement content added according to Tutorial on Variational Autoencoders. (paper with notes: VAE Tutorial.pdf)</p> <p>\u53d8\u5206\u81ea\u7f16\u7801\u5668VAE\uff1a\u539f\u6765\u662f\u8fd9\u4e48\u4e00\u56de\u4e8b | \u9644\u5f00\u6e90\u4ee3\u7801</p>"},{"location":"AI/CS231n/CS231n_notes/#autoencoder","title":"Autoencoder","text":"<p>Learn a lower-dimensional feature representation with unsupervised approaches.</p> <p>\\(x\\rightarrow z\\) : Dimension reduction for input features.</p> <p>\\(z\\rightarrow \\hat{x}\\) : Reconstruct input features.</p> <p></p> <p>After training, we throw the decoder away and use the encoder for transferring.</p> <p></p> <p>For generative models, there is a problem:</p> <p>We can\u2019t generate new images from an autoencoder because we don\u2019t know the space of \\(z\\).</p>"},{"location":"AI/CS231n/CS231n_notes/#variational-autoencoder_1","title":"Variational Autoencoder","text":""},{"location":"AI/CS231n/CS231n_notes/#character-description","title":"Character Description","text":"<p>\\(X\\) : Images. (random variable)</p> <p>\\(Z\\) : Latent representations. (random variable)</p> <p>\\(P(X)\\) : True distribution of all training images \\(X\\).</p> <p>\\(P(Z)\\) : True distribution of all latent representations \\(Z\\).</p> <p>\\(P(X|Z)\\) : True posterior distribution of all images \\(X\\) with condition \\(Z\\).</p> <p>\\(P(Z|X)\\) : True prior distribution of all latent representations \\(Z\\) with condition \\(X\\).</p> <p>\\(Q(Z|X)\\) : Approximated prior distribution of all latent representations \\(Z\\) with condition \\(X\\).</p> <p>\\(x\\) : A specific image.</p> <p>\\(z\\) : A specific latent representation.</p> <p>\\(\\theta\\): Learned parameters in decoder network.</p> <p>\\(\\phi\\): Learned parameters in encoder network.</p> <p>\\(p_\\theta(x)\\) : Probability that \\(x\\sim P(X)\\).</p> <p>\\(p_\\theta(z)\\) : Probability that \\(z\\sim P(Z)\\).</p> <p>\\(p_\\theta(x|z)\\) : Probability that \\(x\\sim P(X|Z)\\).</p> <p>\\(p_\\theta(z|x)\\) : Probability that \\(z\\sim P(Z|X)\\).</p> <p>\\(q_\\phi(z|x)\\) : Probability that \\(z\\sim Q(Z|X)\\).</p>"},{"location":"AI/CS231n/CS231n_notes/#decoder","title":"Decoder","text":"<p>Objective:</p> <p>Generate new images from \\(\\mathscr{z}\\).</p> <ol> <li>Generate a value \\(z^{(i)}\\) from the prior distribution \\(P(Z)\\).</li> <li>Generate a value \\(x^{(i)}\\) from the conditional distribution \\(P(X|Z)\\).</li> </ol> <p>Lemma:</p> <p>Any distribution in \\(d\\) dimensions can be generated by taking a set of \\(d\\) variables that are normally distributed and mapping them through a sufficiently complicated function. (source: Tutorial on Variational Autoencoders, Page 6)</p> <p>Solutions:</p> <ol> <li>Choose prior distribution \\(P(Z)\\) to be a simple distribution, for example \\(P(Z)\\sim N(0,1)\\).</li> <li>Learn the conditional distribution \\(P(X|Z)\\) through a neural network (decoder) with parameter \\(\\theta\\). </li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#encoder","title":"Encoder","text":"<p>Objective:</p> <p>Learn \\(\\mathscr{z}\\) with training images.</p> <p>Given: (From the decoder, we can deduce the following probabilities.)</p> <ol> <li>data likelihood: \\(p_\\theta(x)=\\int p_\\theta(x|z)p_\\theta(z)dz\\).</li> <li>posterior density: \\(p_\\theta(z|x)=\\frac{p_\\theta(x|z)p_\\theta(z)}{p_\\theta(x)}=\\frac{p_\\theta(x|z)p_\\theta(z)}{\\int p_\\theta(x|z)p_\\theta(z)dz}\\).</li> </ol> <p>Problem:</p> <p>Both \\(p_\\theta(x)\\) and \\(p_\\theta(z|x)\\) are intractable. (can't be optimized directly as they contain integral operation)</p> <p>Solution:</p> <p>Learn \\(Q(Z|X)\\) to approximate the true posterior \\(P(Z|X)\\).</p> <p>Use \\(q_\\phi(z|x)\\) in place of \\(p_\\theta(z|x)\\).</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#variational-autoencoder-combination-of-encoder-and-decoder","title":"Variational Autoencoder (Combination of Encoder and Decoder)","text":"<p>Objective:</p> <p>Maximize \\(p_\\theta(x)\\) for all \\(x^{(i)}\\) in the training set.</p> <p>$$ \\begin{aligned} \\log p_\\theta\\big(x^{(i)}\\big)&amp;=\\mathbb{E}{z\\sim q\\phi\\big(z|x^{(i)}\\big)}\\Big[\\log p_\\theta\\big(x^{(i)}\\big)\\Big]\\</p> <p>&amp;=\\mathbb{E}z\\Bigg[\\log\\frac{p\\theta\\big(x^{(i)}|z\\big)p_\\theta\\big(z\\big)}{p_\\theta\\big(z|x^{(i)}\\big)}\\Bigg]\\quad\\text{(Bayes' Rule)}\\</p> <p>&amp;=\\mathbb{E}z\\Bigg[\\log\\frac{p\\theta\\big(x^{(i)}|z\\big)p_\\theta\\big(z\\big)}{p_\\theta\\big(z|x^{(i)}\\big)}\\frac{q_\\phi\\big(z|x^{(i)}\\big)}{q_\\phi\\big(z|x^{(i)}\\big)}\\Bigg]\\quad\\text{(Multiply by Constant)}\\</p> <p>&amp;=\\mathbb{E}z\\Big[\\log p\\theta\\big(x^{(i)}|z\\big)\\Big]-\\mathbb{E}z\\Bigg[\\log\\frac{q\\phi\\big(z|x^{(i)}\\big)}{p_\\theta\\big(z\\big)}\\Bigg]+\\mathbb{E}z\\Bigg[\\log\\frac{p\\theta\\big(z|x^{(i)}\\big)}{q_\\phi\\big(z|x^{(i)}\\big)}\\Bigg]\\quad\\text{(Logarithm)}\\</p> <p>&amp;=\\mathbb{E}z\\Big[\\log p\\theta\\big(x^{(i)}|z\\big)\\Big]-D_{\\text{KL}}\\Big[q_\\phi\\big(z|x^{(i)}\\big)||p_\\theta\\big(z\\big)\\Big]+D_{\\text{KL}}\\Big[p_\\theta\\big(z|x^{(i)}\\big)||q_\\phi\\big(z|x^{(i)}\\big)\\Big]\\quad\\text{(KL Divergence)} \\end{aligned} $$</p> <p>Analyze the Formula by Term:</p> <p>\\(\\mathbb{E}_z\\Big[\\log p_\\theta\\big(x^{(i)}|z\\big)\\Big]\\): Decoder network gives \\(p_\\theta\\big(x^{(i)}|z\\big)\\), can compute estimate of this term through sampling.</p> <p>\\(D_{\\text{KL}}\\Big[q_\\phi\\big(z|x^{(i)}\\big)||p_\\theta\\big(z\\big)\\Big]\\): This KL term (between Gaussians for encoder and \\(z\\) prior) has nice closed-form solution!</p> <p>\\(D_{\\text{KL}}\\Big[p_\\theta\\big(z|x^{(i)}\\big)||q_\\phi\\big(z|x^{(i)}\\big)\\Big]\\): The part \\(p_\\theta\\big(z|x^{(i)}\\big)\\) is intractable. However, we know KL divergence always \\(\\ge0\\).</p> <p>Tractable Lower Bound:</p> <p>We can maximize the lower bound of that formula.</p> <p>As \\(D_{\\text{KL}}\\Big[p_\\theta\\big(z|x^{(i)}\\big)||q_\\phi\\big(z|x^{(i)}\\big)\\Big]\\ge0\\) , we can deduce that:</p> <p>$$ \\begin{aligned} \\log p_\\theta\\big(x^{(i)}\\big)&amp;=\\mathbb{E}z\\Big[\\log p\\theta\\big(x^{(i)}|z\\big)\\Big]-D_{\\text{KL}}\\Big[q_\\phi\\big(z|x^{(i)}\\big)||p_\\theta\\big(z\\big)\\Big]+D_{\\text{KL}}\\Big[p_\\theta\\big(z|x^{(i)}\\big)||q_\\phi\\big(z|x^{(i)}\\big)\\Big]\\</p> <p>&amp;\\ge\\mathbb{E}z\\Big[\\log p\\theta\\big(x^{(i)}|z\\big)\\Big]-D_{\\text{KL}}\\Big[q_\\phi\\big(z|x^{(i)}\\big)||p_\\theta\\big(z\\big)\\Big] \\end{aligned} $$</p> <p>So the loss function \\(\\mathcal{L}\\big(x^{(i)},\\theta,\\phi\\big)=-\\mathbb{E}_z\\Big[\\log p_\\theta\\big(x^{(i)}|z\\big)\\Big]+D_{\\text{KL}}\\Big[q_\\phi\\big(z|x^{(i)}\\big)||p_\\theta\\big(z\\big)\\Big]\\).</p> <p>\\(\\mathbb{E}_z\\Big[\\log p_\\theta\\big(x^{(i)}|z\\big)\\Big]\\): Decoder, reconstruct the input data. </p> <p>\\(D_{\\text{KL}}\\Big[q_\\phi\\big(z|x^{(i)}\\big)||p_\\theta\\big(z\\big)\\Big]\\): Encoder, make approximate posterior distribution close to prior.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#generative-adversarial-networks-gans","title":"Generative Adversarial Networks (GANs)","text":""},{"location":"AI/CS231n/CS231n_notes/#motivation-modeling","title":"Motivation &amp; Modeling","text":"<p>Objective: Not modeling any explicit density function.</p> <p>Problem: Want to sample from complex, high-dimensional training distribution. No direct way to do this!</p> <p>Solution: Sample from a simple distribution, e.g. random noise. Learn the transformation to training distribution.</p> <p></p> <p>Problem: We can't learn the mapping relation between sample \\(z\\) and training images.</p> <p>Solution: Use a discriminator network to tell whether the generate image is within data distribution or not.</p> <p></p> <p>Discriminator network: Try to distinguish between real and fake images.</p> <p>Generator network: Try to fool the discriminator by generating real-looking images.</p> <p></p> <p>\\(x\\) : Real data.</p> <p>\\(y\\) : Fake data, which is generated by the generator network. \\(y=G_{\\theta_g}(z)\\).</p> <p>\\(D_{\\theta_d}(x)\\) : Discriminator score, which is the likelihood of real image. \\(D_{\\theta_d}(x)\\in[0,1]\\).</p> <p>Objective of discriminator network:</p> <p>\\(\\max_{\\theta_d}\\bigg[\\mathbb{E}_x\\Big(\\log D_{\\theta_d}(x)\\Big)+\\mathbb{E}_{z\\sim p(z)}\\Big(\\log\\big(1-D_{\\theta_d}(y)\\big)\\Big)\\bigg]\\)</p> <p>Objective of generator network:</p> <p>\\(\\min_{\\theta_g}\\max_{\\theta_d}\\bigg[\\mathbb{E}_x\\Big(\\log D_{\\theta_d}(x)\\Big)+\\mathbb{E}_{z\\sim p(z)}\\Big(\\log\\big(1-D_{\\theta_d}(y)\\big)\\Big)\\bigg]\\)</p>"},{"location":"AI/CS231n/CS231n_notes/#training-strategy","title":"Training Strategy","text":"<p>Two combine this two networks together, we can train them alternately:</p> <ol> <li>Gradient ascent on discriminator.</li> </ol> <p>\\(\\max_{\\theta_d}\\bigg[\\mathbb{E}_x\\Big(\\log D_{\\theta_d}(x)\\Big)+\\mathbb{E}_{z\\sim p(z)}\\Big(\\log\\big(1-D_{\\theta_d}(y)\\big)\\Big)\\bigg]\\)</p> <ol> <li>Gradient descent on generator.</li> </ol> <p>\\(\\min_{\\theta_g}\\bigg[\\mathbb{E}_{z\\sim p(z)}\\Big(\\log\\big(1-D_{\\theta_d}(y)\\big)\\Big)\\bigg]\\)</p> <p>However, the gradient of generator decreases with the value itself, making it hard to optimize.</p> <p></p> <p>So we replace \\(\\log\\big(1-D_{\\theta_d}(y)\\big)\\) with \\(-\\log D_{\\theta_d}(y)\\), and use gradient ascent instead.</p> <ol> <li>Gradient ascent on discriminator.</li> </ol> <p>\\(\\max_{\\theta_d}\\bigg[\\mathbb{E}_x\\Big(\\log D_{\\theta_d}(x)\\Big)+\\mathbb{E}_{z\\sim p(z)}\\Big(\\log\\big(1-D_{\\theta_d}(y)\\big)\\Big)\\bigg]\\)</p> <ol> <li>Gradient ascent on generator.</li> </ol> <p>\\(\\max_{\\theta_g}\\bigg[\\mathbb{E}_{z\\sim p(z)}\\Big(\\log D_{\\theta_d}(y)\\Big)\\bigg]\\)</p>"},{"location":"AI/CS231n/CS231n_notes/#summary_3","title":"Summary","text":"<p>Pros: Beautiful, state-of-the-art samples!</p> <p>Cons: </p> <ol> <li>Trickier / more unstable to train.</li> <li>Can\u2019t solve inference queries such as \\(p(x), p(z|x)\\).</li> </ol>"},{"location":"AI/CS231n/CS231n_notes/#14-self-supervised-learning","title":"14 - Self-supervised Learning","text":"<p>Aim: Solve \u201cpretext\u201d tasks that produce good features for downstream tasks.</p> <p>Application:</p> <ol> <li>Learn a feature extractor from pretext tasks. (self-supervised)</li> <li>Attach a shallow network on the feature extractor.</li> <li>Train the shallow network on target task with small amount of labeled data. (supervised)</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#pretext-tasks","title":"Pretext Tasks","text":"<p>Labels are generated automatically.</p>"},{"location":"AI/CS231n/CS231n_notes/#rotation","title":"Rotation","text":"<p>Train a classifier on randomly rotated images.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#rearrangement","title":"Rearrangement","text":"<p>Train a classifier on randomly shuffled image pieces.</p> <p>Predict the location of image pieces.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#inpainting","title":"Inpainting","text":"<p>Mask part of the image, train a network to predict the masked area.</p> <p>Method referencing Context Encoders: Feature Learning by Inpainting.</p> <p>Combine two types of loss together to get better performance:</p> <ol> <li>Reconstruction loss (L2 loss): Used for reconstructing global features.</li> <li>Adversarial loss: Used for generating texture features.</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#coloring","title":"Coloring","text":"<p>Transfer between greyscale images and colored images.</p> <p>Cross-channel predictions for images: Split-Brain Autoencoders.</p> <p></p> <p>Video coloring: Establish mappings between reference and target frames in a learned feature space. Tracking Emerges by Colorizing Videos.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#summary-for-pretext-tasks","title":"Summary for Pretext Tasks","text":"<ol> <li>Pretext tasks focus on \u201cvisual common sense\u201d.</li> <li>The models are forced learn good features about natural images.</li> <li>We don\u2019t care about the performance of these pretext tasks. </li> </ol> <p>What we care is the performance of downstream tasks.</p>"},{"location":"AI/CS231n/CS231n_notes/#problems-of-specific-pretext-tasks","title":"Problems of Specific Pretext Tasks","text":"<ol> <li>Coming up with individual pretext tasks is tedious.</li> <li>The learned representations may not be general.</li> </ol> <p>Intuitive Solution: Contrastive Learning.</p>"},{"location":"AI/CS231n/CS231n_notes/#contrastive-representation-learning","title":"Contrastive Representation Learning","text":"<p>Local additional references: Contrastive Learning.md.</p> <p></p> <p>Objective:</p> <p>Given a chosen score function \\(s\\), we aim to learn an encoder function \\(f\\) that yields:</p> <ol> <li>For each sample \\(x\\), increase the similarity \\(s\\big(f(x),f(x^+)\\big)\\) between \\(x\\) and positive samples \\(x^+\\).</li> <li>Finally we want \\(s\\big(f(x),f(x^+)\\big)\\gg s\\big(f(x),f(x^-)\\big)\\).</li> </ol> <p>Loss Function: </p> <p>Given \\(1\\) positive sample and \\(N-1\\) negative samples:</p> InfoNCE Loss Cross Entropy Loss \\(\\begin{aligned}\\mathcal{L}=-\\mathbb{E}_X\\Bigg[\\log\\frac{\\exp{s\\big(f(x),f(x^+)\\big)}}{\\exp{s\\big(f(x),f(x^+)\\big)}+\\sum_{j=1}^{N-1}\\exp{s\\big(f(x),f(x^+)\\big)}}\\Bigg]\\\\\\end{aligned}\\) \\(\\begin{aligned}\\mathcal{L}&amp;=-\\sum_{i=1}^Np(x_i)\\log q(x_i)\\\\&amp;=-\\mathbb{E}_X\\big[\\log q(x)\\big]\\\\&amp;=-\\mathbb{E}_X\\Bigg[\\log\\frac{\\exp(x)}{\\sum_{j=1}^N\\exp(x_j)}\\Bigg]\\end{aligned}\\) <p>The InfoNCE Loss is a lower bound on the mutual information between \\(f(x)\\) and \\(f(x^+)\\):</p> <p>\\(\\text{MI}\\big[f(x),f(x^+)\\big]\\ge\\log(N)-\\mathcal{L}\\)</p> <p>The larger the negative sample size \\(N\\), the tighter the bound.</p> <p>So we use \\(N-1\\) negative samples.</p>"},{"location":"AI/CS231n/CS231n_notes/#instance-contrastive-learning","title":"Instance Contrastive Learning","text":""},{"location":"AI/CS231n/CS231n_notes/#simclr","title":"SimCLR","text":"<p>Use a projection function \\(g(\\cdot)\\) to project features to a space where contrastive learning is applied.</p> <p>The extra projection contributes a lot to the final performance.</p> <p></p> <p>Score Function: Cos similarity \\(s(u,v)=\\frac{u^Tv}{||u||||v||}\\\\\\).</p> <p>Positive Pair: Pair of augmented data.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#momentum-contrastive-learning-moco","title":"Momentum Contrastive Learning (MoCo)","text":"<p>There are mainly \\(3\\) training strategy in contrastive learning:</p> <ol> <li>end-to-end: Keys are updated together with queries, e.g. SimCLR.</li> </ol> <p>(limited by GPU size)</p> <ol> <li>memory bank: Store last-time keys for sampling.</li> </ol> <p>(inconsistency between \\(q\\) and \\(k\\))</p> <ol> <li>MoCo: Use momentum methods to encode keys.</li> </ol> <p>(combination of end-to-end &amp; memory bank)</p> <p></p> <p>Key differences to SimCLR:</p> <ol> <li>Keep a running queue of keys (negative samples).</li> <li>Compute gradients and update the encoder only through the queries.</li> <li>Decouple min-batch size with the number of keys: can support a large number of negative samples.</li> <li>The key encoder is slowly progressing through the momentum update rules:</li> </ol> <p>\\(\\theta_k\\leftarrow m\\theta_k+(1-m)\\theta_q\\)</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#sequence-contrastive-learning","title":"Sequence Contrastive Learning","text":""},{"location":"AI/CS231n/CS231n_notes/#contrastive-predictive-coding-cpc","title":"Contrastive Predictive Coding (CPC)","text":"<p>Contrastive: Contrast between \u201cright\u201d and \u201cwrong\u201d sequences using contrastive learning.</p> <p>Predictive: The model has to predict future patterns given the current context.</p> <p>Coding: The model learns useful feature vectors, or \u201ccode\u201d, for downstream tasks, similar to other self-supervised methods.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#other-examples-frontier","title":"Other Examples (Frontier)","text":""},{"location":"AI/CS231n/CS231n_notes/#contrastive-language-image-pre-training-clip","title":"Contrastive Language Image Pre-training (CLIP)","text":"<p>Contrastive learning between image and natural language sentences.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#15-low-level-vision","title":"15 - Low-Level Vision","text":"<p>Pass...</p>"},{"location":"AI/CS231n/CS231n_notes/#16-3d-vision","title":"16 - 3D Vision","text":""},{"location":"AI/CS231n/CS231n_notes/#representation","title":"Representation","text":""},{"location":"AI/CS231n/CS231n_notes/#explicit-vs-implicit","title":"Explicit vs Implicit","text":"<p>Explicit: Easy to sample examples, hard to do inside/outside check.</p> <p>Implicit: Hard to sample examples, easy to do inside/outside check.</p> Non-parametric Parametric Explicit Points.Meshes. Splines.Subdivision Surfaces. Implicit Level Sets.Voxels. Algebraic Surfaces.Constructive Solid Geometry."},{"location":"AI/CS231n/CS231n_notes/#point-clouds","title":"Point Clouds","text":"<p>The simplest representation.</p> <p>Collection of \\((x,y,z)\\) coordinates.</p> <p>Cons:</p> <ol> <li>Difficult to draw in under-sampled regions.</li> <li>No simplification or subdivision.</li> <li>No direction smooth rendering.</li> <li>No topological information.</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#polygonal-meshes","title":"Polygonal Meshes","text":"<p>Collection of vertices \\(v\\) and edges \\(e\\).</p> <p>Pros:</p> <ol> <li>Can apply downsampling or upsampling on meshes.</li> <li>Error decreases by \\(O(n^2)\\) while meshes increase by \\(O(n)\\).</li> <li>Can approximate arbitrary topology.</li> <li>Efficient rendering.</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#splines","title":"Splines","text":"<p>Use specific functions to approximate the surface. (e.g. B\u00e9zier Curves)</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#algebraic-surfaces","title":"Algebraic Surfaces","text":"<p>Use specific functions to represent the surface.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#constructive-solid-geometry","title":"Constructive Solid Geometry","text":"<p>Combine implicit geometry with Boolean operations.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#level-sets","title":"Level Sets","text":"<p>Store a grim of values to approximate the function.</p> <p>Surface is found where interpolated value equals to \\(0\\).</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#voxels","title":"Voxels","text":"<p>Binary thresholding the volumetric grid.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#ai-3d","title":"AI + 3D","text":"<p>Pass...</p>"},{"location":"AI/CS231n/Image%20Classification-Data-driven%20Approach%2C%20k-Nearest%20Neighbor%2C%20train_val_test%20splits/","title":"Image Classification-Data-driven Approach, k-Nearest Neighbor, train_val_test splits","text":""},{"location":"AI/CS231n/Image%20Classification-Data-driven%20Approach%2C%20k-Nearest%20Neighbor%2C%20train_val_test%20splits/#image-classification-data-driven-approach-k-nearest-neighbor-train_val_test-splits","title":"Image Classification-Data-driven Approach, k-Nearest Neighbor, train_val_test splits","text":"<p> \u7ea6 653 \u4e2a\u5b57  28 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"AI/CS231n/Image%20Classification-Data-driven%20Approach%2C%20k-Nearest%20Neighbor%2C%20train_val_test%20splits/#image-classification","title":"image classification","text":"<ul> <li>challenges<ul> <li>viewpoint variation</li> <li>scale variation</li> <li>deformation</li> <li>occlusion</li> <li>illumination conditions</li> <li>background clutter</li> <li>intra-class variation</li> </ul> </li> <li>data-driven approach</li> <li>the image classification pipeline<ul> <li>input</li> <li>learning<ul> <li>training a classifier</li> <li>learning a model</li> </ul> </li> <li>evaluation</li> </ul> </li> </ul>"},{"location":"AI/CS231n/Image%20Classification-Data-driven%20Approach%2C%20k-Nearest%20Neighbor%2C%20train_val_test%20splits/#nearest-neighbor-classifier","title":"Nearest Neighbor Classifier","text":"\\[ d_1 (I_1, I_2) = \\sum_{p} \\left| I^p_1 - I^p_2 \\right| \\] Python<pre><code>import numpy as np\n\nclass NearestNeighbor(object):  \n  def **init**(self):  \n    pass\n\n  def train(self, X, y):  \n    \"\"\" X is N x D where each row is an example. Y is 1-dimension of size N \"\"\"  \n    # the nearest neighbor classifier simply remembers all the training data  \n    self.Xtr = X  \n    self.ytr = y\n\n  def predict(self, X):  \n    \"\"\" X is N x D where each row is an example we wish to predict label for \"\"\"  \n    num_test = X.shape[0]  \n    # lets make sure that the output type matches the input type  \n    Ypred = np.zeros(num_test, dtype = self.ytr.dtype)\n\n    # loop over all test rows\n    for i in range(num_test):\n      # find the nearest training image to the i'th test image\n      # using the L1 distance (sum of absolute value differences)\n      distances = np.sum(np.abs(self.Xtr - X[i,:]), axis = 1)\n      min_index = np.argmin(distances) # get the index with smallest distance\n      Ypred[i] = self.ytr[min_index] # predict the label of the nearest example\n\n    return Ypred\n</code></pre> \\[ d_2 (I_1, I_2) = \\sqrt{\\sum_{p} \\left( I^p_1 - I^p_2 \\right)^2} \\] Python<pre><code>distances = np.sqrt(np.sum(np.square(self.Xtr - X[i,:]), axis = 1))\n</code></pre>"},{"location":"AI/CS231n/Image%20Classification-Data-driven%20Approach%2C%20k-Nearest%20Neighbor%2C%20train_val_test%20splits/#k-nearest-neighbor-classifier","title":"k - Nearest Neighbor Classifier","text":"<p>![[Pasted image 20241031202452.jpg]]</p>"},{"location":"AI/CS231n/Image%20Classification-Data-driven%20Approach%2C%20k-Nearest%20Neighbor%2C%20train_val_test%20splits/#validation-sets-for-hyperparameter-tuning","title":"Validation sets for Hyperparameter tuning","text":"<p>Evaluate on the test only a single time, at the very end</p> <p>Split your training set into training set and a validation set. Use validation set to tune all hyperparameters. At the end run a single time on the test set and report performance.</p> <ul> <li>cross-validation</li> <li>single calidation split ![[Pasted image 20241031202849.png]]</li> </ul>"},{"location":"AI/CS231n/Image%20Classification-Data-driven%20Approach%2C%20k-Nearest%20Neighbor%2C%20train_val_test%20splits/#pros-and-cons-of-nearest-neighbor-classifier","title":"Pros and Cons of Nearest Neighbor classifier","text":"<ul> <li>simple to implement and understand</li> <li>take no time to train</li> <li>however, pay a cost at test time</li> </ul> <p>As an aside, the computational complexity of the Nearest Neighbor classifier is an active area of research, and several\u00a0Approximate Nearest Neighbor\u00a0(ANN) algorithms and libraries exist that can accelerate the nearest neighbor lookup in a dataset (e.g.\u00a0FLANN). These algorithms allow one to trade off the correctness of the nearest neighbor retrieval with its space/time complexity during retrieval, and usually rely on a pre-processing/indexing stage that involves building a kdtree, or running the k-means algorithm.</p> <ul> <li>\\(\\displaystyle L_{2}\\) isn't enough sensitive</li> </ul> <p>In particular, note that images that are nearby each other are much more a function of the general color distribution of the images, or the type of background rather than their semantic identity.</p> Applying kNN in practice <ol> <li>Preprocess your data: Normalize the features in your data (e.g. one pixel in images) to have zero mean and unit variance. We will cover this in more detail in later sections, and chose not to cover data normalization in this section because pixels in images are usually homogeneous and do not exhibit widely different distributions, alleviating the need for data normalization.</li> <li>If your data is very high-dimensional, consider using a dimensionality reduction technique such as PCA (wiki ref,\u00a0CS229ref,\u00a0blog ref), NCA (wiki ref,\u00a0blog ref), or even\u00a0Random Projections.</li> <li>Split your training data randomly into train/val splits. As a rule of thumb, between 70-90% of your data usually goes to the train split. This setting depends on how many hyperparameters you have and how much of an influence you expect them to have. If there are many hyperparameters to estimate, you should err on the side of having larger validation set to estimate them effectively. If you are concerned about the size of your validation data, it is best to split the training data into folds and perform cross-validation. If you can afford the computational budget it is always safer to go with cross-validation (the more folds the better, but more expensive).</li> <li>Train and evaluate the kNN classifier on the validation data (for all folds, if doing cross-validation) for many choices of\u00a0k\u00a0(e.g. the more the better) and across different distance types (L1 and L2 are good candidates)</li> <li>If your kNN classifier is running too long, consider using an Approximate Nearest Neighbor library (e.g.\u00a0FLANN) to accelerate the retrieval (at cost of some accuracy).</li> <li>Take note of the hyperparameters that gave the best results. There is a question of whether you should use the full training set with the best hyperparameters, since the optimal hyperparameters might change if you were to fold the validation data into your training set (since the size of the data would be larger). In practice it is cleaner to not use the validation data in the final classifier and consider it to be\u00a0burned\u00a0on estimating the hyperparameters. Evaluate the best model on the test set. Report the test set accuracy and declare the result to be the performance of the kNN classifier on your data.</li> </ol> <p>[[more about Machine Learing]]</p>"},{"location":"AI/CS231n/Linear%20classification-Support%20Vector%20Machine%2C%20Softmax/","title":"Linear classification-Support Vector Machine, Softmax","text":""},{"location":"AI/CS231n/Linear%20classification-Support%20Vector%20Machine%2C%20Softmax/#linear-classification-support-vector-machine-softmax","title":"Linear classification-Support Vector Machine, Softmax","text":"<p> \u7ea6 129 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"AI/CS231n/Linear%20classification-Support%20Vector%20Machine%2C%20Softmax/#linear-classifiaction","title":"Linear Classifiaction","text":"\\[ L_i = \\sum_{j\\neq y_i} \\max(0, s_j - s_{y_i} + \\Delta) \\] \\[ L = \\frac{1}{N} \\sum_i \\sum_{j\\neq y_i} \\left[ \\max(0, f(x_i; W)_j - f(x_i; W)_{y_i} + \\Delta) \\right] + \\lambda \\sum_k\\sum_l W_{k,l}^2 \\] \\[ L_i = -\\log\\left(\\frac{e^{f_{y_i}}}{ \\sum_j e^{f_j} }\\right) \\hspace{0.5in} \\text{or equivalently} \\hspace{0.5in} L_i = -f_{y_i} + \\log\\sum_j e^{f_j} \\] \\[ \\frac{e^{f_{y_i}}}{\\sum_j e^{f_j}} = \\frac{Ce^{f_{y_i}}}{C\\sum_j e^{f_j}} = \\frac{e^{f_{y_i} + \\log C}}{\\sum_j e^{f_j + \\log C}} \\] <p>![[Pasted image 20241031210509.png]]</p>"},{"location":"AI/CS231n/Numpy/","title":"Numpy","text":""},{"location":"AI/CS231n/Numpy/#python","title":"Python","text":"<p> \u7ea6 49 \u4e2a\u5b57  104 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"AI/CS231n/Numpy/#string","title":"string","text":"Python<pre><code>s = \"hello\"\nprint(s.capitalize())  # Capitalize a string; prints \"Hello\"\nprint(s.upper())       # Convert a string to uppercase; prints \"HELLO\"\nprint(s.rjust(7))      # Right-justify a string, padding with spaces; prints \"  hello\"\nprint(s.center(7))     # Center a string, padding with spaces; prints \" hello \"\nprint(s.replace('l', '(ell)'))  # Replace all instances of one substring with another;\n                                # prints \"he(ell)(ell)o\"\nprint('  world '.strip())  # Strip leading and trailing whitespace; prints \"world\"\n</code></pre>"},{"location":"AI/CS231n/Numpy/#containers","title":"Containers","text":"Python<pre><code>animals = ['cat', 'dog', 'monkey']\nfor idx, animal in enumerate(animals):\n    print('#%d: %s' % (idx + 1, animal))\n# Prints \"#1: cat\", \"#2: dog\", \"#3: monkey\", each on its own line\n</code></pre> <p>\u5217\u8868\u63a8\u5bfc\u5f0f</p> Python<pre><code>nums = [0, 1, 2, 3, 4]\neven_squares = [x ** 2 for x in nums if x % 2 == 0]\nprint(even_squares)  # Prints \"[0, 4, 16]\"\n</code></pre> <p>\u540c\u6837\u4e5f\u6709\u5b57\u5178\u63a8\u5bfc\u5f0f</p> <p>Tuples \u53ef\u4ee5\u7528\u4f5c\u5b57\u5178\u4e2d\u7684\u952e\u548c\u96c6\u5408\u7684\u5143\u7d20\uff0c\u4f46\u662f lists \u4e0d\u80fd</p>"},{"location":"AI/CS231n/Numpy/#numpy","title":"Numpy","text":"Python<pre><code>import numpy as np\n\n# Create a new array from which we will select elements\na = np.array([[1,2,3], [4,5,6], [7,8,9], [10, 11, 12]])\n\nprint(a)  # prints \"array([[ 1,  2,  3],\n          #                [ 4,  5,  6],\n          #                [ 7,  8,  9],\n          #                [10, 11, 12]])\"\n\n# Create an array of indices\nb = np.array([0, 2, 0, 1])\n\n# Select one element from each row of a using the indices in b\nprint(a[np.arange(4), b])  # Prints \"[ 1  6  7 11]\"\n\n# Mutate one element from each row of a using the indices in b\na[np.arange(4), b] += 10\n\nprint(a)  # prints \"array([[11,  2,  3],\n          #                [ 4,  5, 16],\n          #                [17,  8,  9],\n          #                [10, 21, 12]])\n</code></pre> Python<pre><code>import numpy as np\n\na = np.array([[1,2], [3, 4], [5, 6]])\n\nbool_idx = (a &gt; 2)   # Find the elements of a that are bigger than 2;\n                     # this returns a numpy array of Booleans of the same\n                     # shape as a, where each slot of bool_idx tells\n                     # whether that element of a is &gt; 2.\n\nprint(bool_idx)      # Prints \"[[False False]\n                     #          [ True  True]\n                     #          [ True  True]]\"\n\n# We use boolean array indexing to construct a rank 1 array\n# consisting of the elements of a corresponding to the True values\n# of bool_idx\nprint(a[bool_idx])  # Prints \"[3 4 5 6]\"\n\n# We can do all of the above in a single concise statement:\nprint(a[a &gt; 2])     # Prints \"[3 4 5 6]\"\n</code></pre> Python<pre><code>x = np.array([1, 2], dtype=np.int64)   # Force a particular datatype\nprint(x.dtype)                         # Prints \"int64\"\n</code></pre> Python<pre><code>import numpy as np\n\nx = np.array([[1,2],[3,4]], dtype=np.float64)\ny = np.array([[5,6],[7,8]], dtype=np.float64)\n\n# Elementwise sum; both produce the array\n# [[ 6.0  8.0]\n#  [10.0 12.0]]\nprint(x + y)\nprint(np.add(x, y))\n\n# Elementwise difference; both produce the array\n# [[-4.0 -4.0]\n#  [-4.0 -4.0]]\nprint(x - y)\nprint(np.subtract(x, y))\n\n# Elementwise product; both produce the array\n# [[ 5.0 12.0]\n#  [21.0 32.0]]\nprint(x * y)\nprint(np.multiply(x, y))\n\n# Elementwise division; both produce the array\n# [[ 0.2         0.33333333]\n#  [ 0.42857143  0.5       ]]\nprint(x / y)\nprint(np.divide(x, y))\n\n# Elementwise square root; produces the array\n# [[ 1.          1.41421356]\n#  [ 1.73205081  2.        ]]\nprint(np.sqrt(x))\n</code></pre> <p>\u5e7f\u64ad\u53ef\u4ee5\u907f\u514d\u5faa\u73af</p> Python<pre><code>import numpy as np\n\n# We will add the vector v to each row of the matrix x,\n# storing the result in the matrix y\nx = np.array([[1,2,3], [4,5,6], [7,8,9], [10, 11, 12]])\nv = np.array([1, 0, 1])\ny = x + v  # Add v to each row of x using broadcasting\nprint(y)  # Prints \"[[ 2  2  4]\n          #          [ 5  5  7]\n          #          [ 8  8 10]\n          #          [11 11 13]]\"\n</code></pre>"},{"location":"AI/CS231n/Numpy/#scipy","title":"SciPy","text":""},{"location":"AI/CS231n/Numpy/#matplotlib","title":"Matplotlib","text":""},{"location":"AI/EECS%20498-007/KNN/","title":"KNN","text":"<p>\u5bf9\u4e8e\u4e00\u4e2a\u5f85\u5206\u7c7b\u7684\u6837\u672c\uff0c\u627e\u5230\u8bad\u7ec3\u6570\u636e\u96c6\u4e2d\u4e0e\u5176\u6700\u63a5\u8fd1\u7684K\u4e2a\u6837\u672c\uff08\u5373\u6700\u8fd1\u90bb\uff09\uff0c\u7136\u540e\u6839\u636e\u8fd9K\u4e2a\u6837\u672c\u7684\u7c7b\u522b\u6765\u51b3\u5b9a\u5f85\u5206\u7c7b\u6837\u672c\u7684\u7c7b\u522b\u3002</p> <p> \u7ea6 374 \u4e2a\u5b57  100 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"AI/EECS%20498-007/KNN/#_1","title":"\u6570\u5b66\u63a8\u5bfc","text":"<p>\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u8bad\u7ec3\u6570\u636e\u96c6 \\(T = \\{(x_1, y_1), (x_2, y_2), \\ldots, (x_N, y_N)\\}\\)\uff0c\u5176\u4e2d \\(x_i\\) \u662f\u7279\u5f81\u5411\u91cf\uff0c \\(y_i\\) \u662f\u5bf9\u5e94\u7684\u7c7b\u522b\u6807\u7b7e\u3002\u5bf9\u4e8e\u4e00\u4e2a\u65b0\u7684\u5f85\u5206\u7c7b\u6837\u672c x\uff0cKNN\u7b97\u6cd5\u7684\u76ee\u6807\u662f\u9884\u6d4b\u5176\u7c7b\u522b \\(y\\) \u3002</p> <ol> <li>\u8ddd\u79bb\u5ea6\u91cf\uff1a\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u4e00\u4e2a\u8ddd\u79bb\u5ea6\u91cf\u6765\u8ba1\u7b97\u5f85\u5206\u7c7b\u6837\u672c \\(x\\) \u4e0e\u8bad\u7ec3\u96c6\u4e2d\u6bcf\u4e2a\u6837\u672c \\(x_i\\) \u4e4b\u95f4\u7684\u8ddd\u79bb\u3002\u5e38\u7528\u7684\u8ddd\u79bb\u5ea6\u91cf\u5305\u62ec\u6b27\u6c0f\u8ddd\u79bb\uff08Euclidean distance\uff09\u3001\u66fc\u54c8\u987f\u8ddd\u79bb\uff08Manhattan distance\uff09\u548c\u95f5\u53ef\u592b\u65af\u57fa\u8ddd\u79bb\uff08Minkowski distance\uff09\u3002\u4ee5\u6b27\u6c0f\u8ddd\u79bb\u4e3a\u4f8b\uff0c\u4e24\u4e2a\u6837\u672c \\(x\\) \u548c \\(x_i\\) \u4e4b\u95f4\u7684\u8ddd\u79bb\u5b9a\u4e49\u4e3a\uff1a</li> </ol> \\[    d(x, x_i) = \\sqrt{\\sum_{j=1}^{d} (x_j - x_{i,j})^2} \\] <p>\u5176\u4e2d\uff0c \\(d\\) \u662f\u7279\u5f81\u7684\u7ef4\u5ea6\u3002</p> <ol> <li>\u5bfb\u627e\u6700\u8fd1\u90bb\uff1a\u7136\u540e\uff0c\u6211\u4eec\u6839\u636e\u8ba1\u7b97\u51fa\u7684\u8ddd\u79bb\uff0c\u9009\u62e9\u8ddd\u79bb\u6700\u8fd1\u7684K\u4e2a\u6837\u672c\uff0c\u6784\u6210\u5f85\u5206\u7c7b\u6837\u672c\u7684\u90bb\u57df \\(N_k(x)\\)\u3002</li> <li>\u51b3\u7b56\u89c4\u5219\uff1a\u6700\u540e\uff0c\u6839\u636e\u90bb\u57df \\( N_k(x) \\) \u4e2d\u7684\u6837\u672c\u7c7b\u522b\uff0c\u901a\u8fc7\u591a\u6570\u6295\u7968\u7684\u65b9\u5f0f\u6765\u51b3\u5b9a\u5f85\u5206\u7c7b\u6837\u672c\u7684\u7c7b\u522b\u3002\u5373\uff1a</li> </ol> \\[     y = \\arg\\max_{c_j} \\sum_{x_i \\in N_k(x)} I(y_i = c_j) \\] <p>\u5176\u4e2d\uff0c \\(I\\) \u662f\u6307\u793a\u51fd\u6570\uff0c\u5f53 \\(y_i = c_j\\) \u65f6\u53d6\u503c\u4e3a1\uff0c\u5426\u5219\u4e3a0\u3002</p>"},{"location":"AI/EECS%20498-007/KNN/#_2","title":"\u4f5c\u4e1a\u4e2d\u7684\u5b9e\u73b0","text":"Python<pre><code>import torch\n\ndef compute_distances_two_loops(x_train, x_test):\n  num_train = x_train.shape[0]\n  num_test = x_test.shape[0]\n  dists = x_train.new_zeros(num_train, num_test)\n\n  for i in range(num_train):\n    for j in range(num_test):\n      dists[i,j] = ((x_train[i] - x_test[j]) ** 2).sum() ** (1/2)\n\n  return dists\n\ndef compute_distances_one_loop(x_train, x_test):\n  num_train = x_train.shape[0]\n  num_test = x_test.shape[0]\n  dists = x_train.new_zeros(num_train, num_test)\n\n  for i in range(num_train):\n    dists[i] = ((x_train[i] - x_test) ** 2).sum(dim=(1,2,3)) ** (1/2)\n\n  return dists\n\ndef compute_distances_no_loops(x_train, x_test):\n  num_train = x_train.shape[0]\n  num_test = x_test.shape[0]\n  dists = x_train.new_zeros(num_train, num_test)\n\n  A = x_train.reshape(num_train, -1)\n  B = x_test.reshape(num_test, -1)\n  AB2 = A.mm(B.T) * 2\n  dists = ((A ** 2).sum(dim=1).reshape(-1, 1) - AB2 + (B ** 2).sum(dim=1).reshape(1, -1)) ** (1/2)\n\n  return dists\n\ndef predict_labels(dists, y_train, k=1):\n  num_train, num_test = dists.shape\n  y_pred = torch.zeros(num_test, dtype=torch.int64)\n\n  values, indices = torch.topk(dists, k, dim=0, largest=False)\n  for i in range(indices.shape[1]):\n    _, idx = torch.max(y_train[indices[:, i]].bincount(), dim=0)\n    y_pred[i] = idx\n\n  return y_pred\n\nclass KnnClassifier:\n  def __init__(self, x_train, y_train):\n    self.x_train = x_train\n    self.y_train = y_train\n\n  def predict(self, x_test, k=1):\n    dists = compute_distances_no_loops(self.x_train, x_test)\n    y_test_pred = predict_labels(dists, self.y_train, k)\n    return y_test_pred\n\n  def check_accuracy(self, x_test, y_test, k=1, quiet=False):\n    y_test_pred = self.predict(x_test, k=k)\n    num_samples = x_test.shape[0]\n    num_correct = (y_test == y_test_pred).sum().item()\n    accuracy = 100.0 * num_correct / num_samples\n    msg = (f'Got {num_correct} / {num_samples} correct; accuracy is {accuracy:.2f}%')\n    if not quiet:\n      print(msg)\n    return accuracy\n\ndef knn_cross_validate(x_train, y_train, num_folds=5, k_choices=None):\n  if k_choices is None:\n    k_choices = [1, 3, 5, 8, 10, 12, 15, 20, 50, 100]\n\n  x_train_folds = torch.chunk(x_train, num_folds, dim=0)\n  y_train_folds = torch.chunk(y_train, num_folds, dim=0)\n\n  k_to_accuracies = {}\n\n  for k in k_choices:\n    list_of_acc = []\n    for num_fold in range(num_folds):\n      x_train_folds_local = [x for x in x_train_folds]\n      y_train_folds_local = [x for x in y_train_folds]\n      x_test = x_train_folds_local[num_fold]\n      y_test = y_train_folds_local[num_fold]\n      del x_train_folds_local[num_fold]\n      del y_train_folds_local[num_fold]\n      x_train = torch.cat(x_train_folds_local, dim=0)\n      y_train = torch.cat(y_train_folds_local, dim=0)\n      classifier = KnnClassifier(x_train, y_train)\n      list_of_acc.append(classifier.check_accuracy(x_test, y_test, k))\n    k_to_accuracies[k] = list_of_acc\n\n  return k_to_accuracies\n\ndef knn_get_best_k(k_to_accuracies):\n  best_k = 0\n  new_dict = {}\n  for k, accs in sorted(k_to_accuracies.items()):\n    new_dict[k] = sum(accs) / len(accs) \n  max_value = max(new_dict.values())\n  best_k = [k for k, v in new_dict.items() if v == max_value][0]\n  return best_k\n</code></pre>"},{"location":"AI/EECS%20498-007/Pytorch/","title":"pytorch \u7684\u57fa\u672c\u4f7f\u7528","text":""},{"location":"AI/EECS%20498-007/Pytorch/#pytorch","title":"pytorch \u7684\u57fa\u672c\u4f7f\u7528","text":"<p> \u7ea6 564 \u4e2a\u5b57  45 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> Python<pre><code># Create a rank 1 tensor from a Python list\na = torch.tensor([[1, 2, 3], [4, 5, 6]])\nprint('Here is a:')\nprint(a)\nprint('type(a): ', type(a))\nprint('rank of a: ', a.dim())\nprint('a.shape: ', a.shape)\n\ntorch.zeros(2, 3)\ntorch.ones(2, 3)\ntorch.eye(3)\ntorch.rand(2, 3)\ntorch.full((M, N), 3.14)\n\ny2 = torch.tensor([1, 2], dtype=torch.int64)\nprint(y2.dtype)\n\nx3 = x0.to(torch.float32)\n\nx0 = torch.eye(3, dtype=torch.float64) \u00a0# Shape (3, 3), dtype torch.float64\nx1 = torch.zeros_like(x0) \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 # Shape (3, 3), dtype torch.float64\nx2 = x0.new_zeros(4, 5) \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 # Shape (4, 5), dtype torch.float64\nx3 = torch.ones(6, 7).to(x0) \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0# Shape (6, 7), dtype torch.float64\n</code></pre> <p>Even though PyTorch provides a large number of numeric datatypes, the most commonly used datatypes are:</p> <ul> <li><code>torch.float32</code>: Standard floating-point type; used to store learnable parameters, network activations, etc. Nearly all arithmetic is done using this type.</li> <li><code>torch.int64</code>: Typically used to store indices</li> <li><code>torch.bool</code>: Stores boolean values: 0 is false and 1 is true</li> <li><code>torch.float16</code>: Used for mixed-precision arithmetic, usually on NVIDIA GPUs with tensor cores. You won't need to worry about this datatype in this course.</li> <li>\u6ce8\u610f <code>a[:, 1]</code> \u548c <code>a[:, 1:2]</code> \u7684\u533a\u522b\uff0c\u540e\u8005\u4f1a\u4fdd\u7559\u7684\u591a\u4e00\u70b9</li> <li><code>clone()</code> \u4ee5\u540e\u7684\u53d8\u91cf\u8ddf\u539f\u53d8\u91cf\u662f\u72ec\u7acb\u7684\uff0c\u4f46\u662f\u7b49\u53f7\u76f4\u63a5\u8d4b\u503c\u7684\u662f\u540c\u4e00\u4e2a\u6307\u9488</li> </ul> Python<pre><code>mask = (a &gt; 3)\nprint('\\nMask tensor:')\nprint(mask)\n# Mask tensor: tensor([[False, False], [False, True], [ True, True]])\n</code></pre> <ul> <li>As its name implies, a tensor returned by <code>.view()</code> shares the same data as the input, so changes to one will affect the other.</li> </ul> Reshape\u548cview\u7684\u533a\u522b <ol> <li>\u5185\u5b58\u8fde\u7eed\u6027\uff1a<ul> <li><code>view</code> \u8981\u6c42\u539f\u59cb\u5f20\u91cf\u548c\u76ee\u6807\u5f20\u91cf\u5728\u5185\u5b58\u4e2d\u662f\u8fde\u7eed\u7684\u3002\u5982\u679c\u539f\u59cb\u5f20\u91cf\u4e0d\u662f\u8fde\u7eed\u7684\uff0c <code>view</code> \u4f1a\u9996\u5148\u8c03\u7528 <code>contiguous</code> \u65b9\u6cd5\u4f7f\u5176\u8fde\u7eed\uff0c\u7136\u540e\u6539\u53d8\u5f62\u72b6\u3002\u5982\u679c\u5f20\u91cf\u5df2\u7ecf\u662f\u8fde\u7eed\u7684\uff0c <code>view</code> \u64cd\u4f5c\u4e0d\u4f1a\u590d\u5236\u6570\u636e\u3002</li> <li><code>reshape</code>\u4e0d\u8981\u6c42\u539f\u59cb\u5f20\u91cf\u662f\u8fde\u7eed\u7684\u3002\u5982\u679c\u539f\u59cb\u5f20\u91cf\u4e0d\u662f\u8fde\u7eed\u7684\uff0c<code>reshape</code>\u4f1a\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u5f20\u91cf\u5e76\u590d\u5236\u6570\u636e\uff0c\u4ee5\u786e\u4fdd\u65b0\u5f20\u91cf\u662f\u8fde\u7eed\u7684\u3002</li> </ul> </li> <li>\u8fd4\u56de\u503c<ul> <li><code>view</code>\u8fd4\u56de\u4e00\u4e2a\u65b0\u7684\u5f20\u91cf\uff0c\u5b83\u4e0e\u539f\u59cb\u5f20\u91cf\u5171\u4eab\u76f8\u540c\u7684\u6570\u636e\uff0c\u4f46\u662f\u6709\u4e0d\u540c\u7684\u5f62\u72b6\u3002\u5982\u679c\u539f\u59cb\u5f20\u91cf\u4e0d\u662f\u8fde\u7eed\u7684\uff0c<code>view</code>\u4f1a\u8fd4\u56de\u4e00\u4e2a\u526f\u672c\u3002</li> <li><code>reshape</code>\u4e5f\u8fd4\u56de\u4e00\u4e2a\u65b0\u7684\u5f20\u91cf\uff0c\u4f46\u603b\u662f\u521b\u5efa\u6570\u636e\u7684\u526f\u672c\uff0c\u5373\u4f7f\u539f\u59cb\u5f20\u91cf\u662f\u8fde\u7eed\u7684\u3002</li> </ul> </li> <li>\u4f7f\u7528\u573a\u666f\uff1a<ul> <li>\u5f53\u4f60\u786e\u5b9a\u539f\u59cb\u5f20\u91cf\u662f\u8fde\u7eed\u7684\uff0c\u5e76\u4e14\u4f60\u60f3\u8981\u907f\u514d\u4e0d\u5fc5\u8981\u7684\u6570\u636e\u590d\u5236\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528<code>view</code>\u3002</li> <li>\u5f53\u4f60\u4e0d\u786e\u5b9a\u539f\u59cb\u5f20\u91cf\u662f\u5426\u8fde\u7eed\uff0c\u6216\u8005\u4f60\u60f3\u8981\u786e\u4fdd\u64cd\u4f5c\u4e0d\u4f1a\u56e0\u975e\u8fde\u7eed\u6027\u800c\u5931\u8d25\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528<code>reshape</code>\u3002</li> </ul> </li> <li>\u53c2\u6570\uff1a<ul> <li><code>view</code>\u7684\u53c2\u6570\u662f\u76ee\u6807\u5f62\u72b6\u7684\u7ef4\u5ea6\u3002</li> <li><code>reshape</code>\u7684\u53c2\u6570\u4e5f\u662f\u76ee\u6807\u5f62\u72b6\u7684\u7ef4\u5ea6\uff0c\u4f46\u5b83\u53ef\u4ee5\u63a5\u53d7\u4e00\u4e2a\u989d\u5916\u7684\u53c2\u6570<code>inplace</code>\uff0c\u5982\u679c\u8bbe\u7f6e\u4e3a<code>True</code>\uff0c\u5219\u4f1a\u5728\u539f\u5730\u4fee\u6539\u5f20\u91cf\u7684\u5f62\u72b6\u3002</li> </ul> </li> </ol> <ul> <li><code>torch.sin(x)</code> \u548c <code>x.sin()</code> \u662f\u7b49\u4ef7\u7684</li> </ul> Python<pre><code>x = torch.tensor([[1, 2, 3],\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 [4, 5, 6]], dtype=torch.float32)\nprint('Original tensor:')\nprint(x)\n\nprint('\\nSum over entire tensor:')\nprint(torch.sum(x))\nprint(x.sum())\n\n# We can sum over each row:\nprint('\\nSum of each row:')\nprint(torch.sum(x, dim=0))\nprint(x.sum(dim=0))\n\n# Sum over each column:\nprint('\\nSum of each column:')\nprint(torch.sum(x, dim=1))\nprint(x.sum(dim=1))\n</code></pre> <ul> <li><code>torch.dot</code>: Computes inner product of vectors</li> <li><code>torch.mm</code>: Computes matrix-matrix products</li> <li><code>torch.mv</code>: Computes matrix-vector products</li> <li><code>torch.addmm</code> / <code>torch.addmv</code>: Computes matrix-matrix and matrix-vector multiplications plus a bias</li> <li><code>torch.bmm</code> / <code>torch.baddmm</code>: Batched versions of <code>torch.mm</code> and <code>torch.addmm</code>, respectively</li> <li><code>torch.matmul</code>: General matrix product that performs different operations depending on the rank of the inputs. Confusingly, this is similar to <code>np.dot</code> in numpy.</li> </ul>"},{"location":"AI/EECS%20498-007/linear_classifer/","title":"Linear classifer","text":""},{"location":"AI/EECS%20498-007/linear_classifer/#_1","title":"\u539f\u7406","text":"<p> \u7ea6 677 \u4e2a\u5b57  216 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 6 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>\u4e24\u79cd\u7ebf\u6027\u5206\u7c7b\u5668\uff1a\u652f\u6301\u5411\u91cf\u673a\uff08SVM\uff09\u548cSoftmax\u5206\u7c7b\u5668\u3002\u8fd9\u4e24\u79cd\u5206\u7c7b\u5668\u90fd\u662f\u76d1\u7763\u5b66\u4e60\u7b97\u6cd5\uff0c\u7528\u4e8e\u5206\u7c7b\u4efb\u52a1\u3002</p>"},{"location":"AI/EECS%20498-007/linear_classifer/#svm","title":"\u652f\u6301\u5411\u91cf\u673a\uff08SVM\uff09","text":"<p>SVM\u7684\u76ee\u6807\u662f\u627e\u5230\u4e00\u4e2a\u8d85\u5e73\u9762\uff0c\u5b83\u53ef\u4ee5\u6700\u5927\u5316\u4e0d\u540c\u7c7b\u522b\u4e4b\u95f4\u7684\u8fb9\u754c\u3002\u8fd9\u4e2a\u8d85\u5e73\u9762\u88ab\u79f0\u4e3a\u6700\u4f18\u5206\u5272\u8d85\u5e73\u9762\u3002\u5bf9\u4e8e\u4e8c\u5206\u7c7b\u95ee\u9898\uff0cSVM\u7684\u635f\u5931\u51fd\u6570\u53ef\u4ee5\u8868\u793a\u4e3a\uff1a</p> \\[ L(W, b) = \\frac{1}{N} \\sum_{i=1}^{N} \\max(0, 1 - y_i (W \\cdot x_i + b)) \\] <p>\u5176\u4e2d\uff0c\\(W\\) \u662f\u6743\u91cd\u5411\u91cf\uff0c\\(b\\) \u662f\u504f\u7f6e\u9879\uff0c\\(x_i\\) \u662f\u8f93\u5165\u7279\u5f81\uff0c\\(y_i\\) \u662f\u6807\u7b7e\uff08-1\u62161\uff09\uff0c\\(N\\) \u662f\u6837\u672c\u6570\u91cf\u3002</p> <p>\u4e3a\u4e86\u5b9e\u73b0\u591a\u5206\u7c7b\uff0c\u6211\u4eec\u4f7f\u7528\u7ed3\u6784\u5316SVM\u635f\u5931\u51fd\u6570\uff0c\u5b83\u8003\u8651\u4e86\u6bcf\u4e2a\u7c7b\u522b\u7684\u5206\u6570\uff0c\u5e76\u5c1d\u8bd5\u6700\u5927\u5316\u6b63\u786e\u7c7b\u522b\u7684\u5206\u6570\u4e0e\u6b21\u9ad8\u7c7b\u522b\u5206\u6570\u4e4b\u95f4\u7684\u5dee\u8ddd\u3002\u635f\u5931\u51fd\u6570\u53ef\u4ee5\u8868\u793a\u4e3a\uff1a</p> \\[ L(W) = \\frac{1}{N} \\sum_{i=1}^{N} \\sum_{j \\neq y_i} \\max(0, \\text{score}_j - \\text{score}_{y_i} + \\Delta) \\] <p>\u5176\u4e2d\uff0c\\(\\text{score}_j = W_j \\cdot x_i\\)\uff0c\\(\\Delta\\) \u662f\u4e00\u4e2a\u5e38\u6570\uff0c\u901a\u5e38\u8bbe\u7f6e\u4e3a1\u3002</p>"},{"location":"AI/EECS%20498-007/linear_classifer/#softmax","title":"Softmax\u5206\u7c7b\u5668","text":"<p>Softmax\u5206\u7c7b\u5668\u4f7f\u7528Softmax\u51fd\u6570\u5c06\u8f93\u5165\u7279\u5f81\u6620\u5c04\u5230\u6982\u7387\u5206\u5e03\u4e0a\u3002\u5bf9\u4e8e\u6bcf\u4e2a\u6837\u672c\uff0cSoftmax\u51fd\u6570\u8f93\u51fa\u6bcf\u4e2a\u7c7b\u522b\u7684\u6982\u7387\u3002Softmax\u51fd\u6570\u5b9a\u4e49\u4e3a\uff1a</p> \\[ \\text{softmax}(z_i) = \\frac{e^{z_i}}{\\sum_{j=1}^{K} e^{z_j}} \\] <p>\u5176\u4e2d\uff0c\\(z_i\\) \u662f\u7b2c\\(i\\)\u4e2a\u7c7b\u522b\u7684\u5206\u6570\uff0c\\(K\\) \u662f\u7c7b\u522b\u603b\u6570\u3002</p> <p>Softmax\u5206\u7c7b\u5668\u7684\u635f\u5931\u51fd\u6570\u662f\u4ea4\u53c9\u71b5\u635f\u5931\uff0c\u53ef\u4ee5\u8868\u793a\u4e3a\uff1a</p> \\[ L(W) = -\\frac{1}{N} \\sum_{i=1}^{N} \\sum_{j=1}^{K} y_{ij} \\log(\\text{softmax}(z_j)) \\] <p>\u5176\u4e2d\uff0c\\(y_{ij}\\) \u662f\u4e00\u4e2a\u6307\u793a\u53d8\u91cf\uff0c\u5982\u679c\u6837\u672c\\(i\\)\u5c5e\u4e8e\u7c7b\u522b\\(j\\)\uff0c\u5219\u4e3a1\uff0c\u5426\u5219\u4e3a0\u3002</p>"},{"location":"AI/EECS%20498-007/linear_classifer/#_2","title":"\u6b63\u5219\u5316","text":"<p>\u4e3a\u4e86\u9632\u6b62\u8fc7\u62df\u5408\uff0c\u6211\u4eec\u5728\u635f\u5931\u51fd\u6570\u4e2d\u6dfb\u52a0\u4e86\u6b63\u5219\u5316\u9879\u3002L2\u6b63\u5219\u5316\u7684\u635f\u5931\u51fd\u6570\u53ef\u4ee5\u8868\u793a\u4e3a\uff1a</p> \\[ L(W) = L(W) + \\lambda \\lVert W \\rVert^2 \\] <p>\u5176\u4e2d\uff0c\\(\\lambda\\) \u662f\u6b63\u5219\u5316\u5f3a\u5ea6\u3002</p>"},{"location":"AI/EECS%20498-007/linear_classifer/#_3","title":"\u4ee3\u7801\u5b9e\u73b0","text":"<p>\u4ee3\u7801\u4e2d\u5b9e\u73b0\u4e86\u4e24\u79cd\u635f\u5931\u51fd\u6570\u7684\u6734\u7d20\u7248\u672c\uff08<code>svm_loss_naive</code> \u548c <code>softmax_loss_naive</code>\uff09\u548c\u5411\u91cf\u5316\u7248\u672c\uff08<code>svm_loss_vectorized</code> \u548c <code>softmax_loss_vectorized</code>\uff09\u3002\u5411\u91cf\u5316\u7248\u672c\u901a\u8fc7\u907f\u514d\u663e\u5f0f\u5faa\u73af\u6765\u63d0\u9ad8\u8ba1\u7b97\u6548\u7387\u3002</p> <p>\u8bad\u7ec3\u8fc7\u7a0b\uff08<code>train_linear_classifier</code>\uff09\u4f7f\u7528\u968f\u673a\u68af\u5ea6\u4e0b\u964d\uff08SGD\uff09\u6765\u4f18\u5316\u635f\u5931\u51fd\u6570\u3002\u5728\u6bcf\u6b21\u8fed\u4ee3\u4e2d\uff0c\u6211\u4eec\u968f\u673a\u62bd\u53d6\u4e00\u4e2a\u6279\u6b21\u7684\u6837\u672c\uff0c\u8ba1\u7b97\u635f\u5931\u548c\u68af\u5ea6\uff0c\u7136\u540e\u66f4\u65b0\u6743\u91cd\u3002</p> <p>\u9884\u6d4b\u8fc7\u7a0b\uff08<code>predict_linear_classifier</code>\uff09\u4f7f\u7528\u8bad\u7ec3\u597d\u7684\u6743\u91cd\u6765\u9884\u6d4b\u65b0\u6837\u672c\u7684\u7c7b\u522b\u3002</p>"},{"location":"AI/EECS%20498-007/linear_classifer/#_4","title":"\u8d85\u53c2\u6570\u641c\u7d22","text":"<p>\u4ee3\u7801\u4e2d\u8fd8\u5305\u542b\u4e86\u8d85\u53c2\u6570\u641c\u7d22\u7684\u51fd\u6570\uff08<code>svm_get_search_params</code> \u548c <code>softmax_get_search_params</code>\uff09\uff0c\u5b83\u4eec\u8fd4\u56de\u4e0d\u540c\u7684\u5b66\u4e60\u7387\u548c\u6b63\u5219\u5316\u5f3a\u5ea6\u7684\u5019\u9009\u503c\uff0c\u4ee5\u4fbf\u627e\u5230\u6700\u4f73\u7684\u6a21\u578b\u53c2\u6570\u3002</p>"},{"location":"AI/EECS%20498-007/linear_classifer/#_5","title":"\u4f5c\u4e1a\u5b9e\u73b0","text":"Python<pre><code>import torch\nimport random\nfrom abc import abstractmethod\n\ndef hello_linear_classifier():\n  print('Hello from linear_classifier.py!')\n\nclass LinearClassifier(object):\n  def __init__(self):\n    random.seed(0)\n    torch.manual_seed(0)\n    self.W = None\n\n  def train(self, X_train, y_train, learning_rate=1e-3, reg=1e-5, num_iters=100,\n            batch_size=200, verbose=False):\n    train_args = (self.loss, self.W, X_train, y_train, learning_rate, reg,\n                  num_iters, batch_size, verbose)\n    self.W, loss_history = train_linear_classifier(*train_args)\n    return loss_history\n\n  def predict(self, X):\n    return predict_linear_classifier(self.W, X)\n\n  @abstractmethod\n  def loss(self, W, X_batch, y_batch, reg):\n    raise NotImplementedError\n\n  def _loss(self, X_batch, y_batch, reg):\n    self.loss(self.W, X_batch, y_batch, reg)\n\n  def save(self, path):\n    torch.save({'W': self.W}, path)\n    print(\"Saved in {}\".format(path))\n\n  def load(self, path):\n    W_dict = torch.load(path, map_location='cpu')\n    self.W = W_dict['W']\n    print(\"load checkpoint file: {}\".format(path))\n\n\nclass LinearSVM(LinearClassifier):\n  def loss(self, W, X_batch, y_batch, reg):\n    return svm_loss_vectorized(W, X_batch, y_batch, reg)\n\n\nclass Softmax(LinearClassifier):\n  def loss(self, W, X_batch, y_batch, reg):\n    return softmax_loss_vectorized(W, X_batch, y_batch, reg)\n\n\ndef svm_loss_naive(W, X, y, reg):\n  dW = torch.zeros_like(W)\n  num_classes = W.shape[1]\n  num_train = X.shape[0]\n  loss = 0.0\n  for i in range(num_train):\n    scores = W.t().mv(X[i])\n    correct_class_score = scores[y[i]]\n    for j in range(num_classes):\n      if j == y[i]:\n        continue\n      margin = scores[j] - correct_class_score + 1\n      if margin &gt; 0:\n        loss += margin\n        dW[:, j] += X[i]\n        dW[:, y[i]] -= X[i]\n\n  loss /= num_train\n  loss += reg * torch.sum(W * W)\n  dW /= num_train\n  dW += 2 * reg * W\n\n  return loss, dW\n\n\ndef svm_loss_vectorized(W, X, y, reg):\n  loss = 0.0\n  dW = torch.zeros_like(W)\n  num_classes = W.shape[1]\n  num_train = X.shape[0]\n  scores = X.mm(W)\n  correct_class_score = scores[range(num_train), y]\n  margin = scores - correct_class_score.view(-1, 1) + 1\n  margin[range(num_train), y] = 0\n  mask = (margin &gt; 0)\n  loss = margin[mask].sum()\n  mask_correct_y = torch.zeros_like(scores, dtype=torch.bool)\n  mask_correct_y[range(num_train), y] = True\n  margin[margin &gt; 0] = 1\n  margin[margin &lt; 0] = 0\n  margin[mask_correct_y] = torch.sum(margin, axis=1) * -1\n  dW = margin.T.mm(X).T\n  loss /= num_train\n  dW /= num_train\n  loss += reg * torch.sum(W * W)\n  dW += 2 * reg * W\n\n  return loss, dW\n\n\ndef sample_batch(X, y, num_train, batch_size):\n  indices = torch.randint(num_train, (batch_size,))\n  y_batch = y[indices]\n  X_batch = X[indices]\n  return X_batch, y_batch\n\n\ndef train_linear_classifier(loss_func, W, X, y, learning_rate=1e-3,\n                            reg=1e-5, num_iters=100, batch_size=200,\n                            verbose=False):\n  num_train, dim = X.shape\n  if W is None:\n    num_classes = torch.max(y) + 1\n    W = 0.000001 * torch.randn(dim, num_classes, device=X.device, dtype=X.dtype)\n  else:\n    num_classes = W.shape[1]\n\n  loss_history = []\n  for it in range(num_iters):\n    X_batch, y_batch = sample_batch(X, y, num_train, batch_size)\n    loss, grad = loss_func(W, X_batch, y_batch, reg)\n    loss_history.append(loss.item())\n    W -= learning_rate * grad\n    if verbose and it % 100 == 0:\n      print('iteration %d / %d: loss %f' % (it, num_iters, loss))\n\n  return W, loss_history\n\n\ndef predict_linear_classifier(W, X):\n  y_pred = torch.zeros(X.shape[0], dtype=torch.int64)\n  _, y_pred = X.mm(W).max(dim=1)\n  return y_pred\n\n\ndef svm_get_search_params():\n  learning_rates = [0.000001, 0.0001, 0.001, 0.005, 0.01, 0.05]\n  regularization_strengths = [0.001, 0.5, 1, 3]\n  return learning_rates, regularization_strengths\n\n\ndef test_one_param_set(cls, data_dict, lr, reg, num_iters=2000):\n  train_acc = 0.0\n  val_acc = 0.0\n  cls.train(data_dict['X_train'], data_dict['y_train'], lr, reg, num_iters,\n            batch_size=200, verbose=False)\n  y_train_pred = cls.predict(data_dict['X_train'])\n  train_acc = 100.0 * (data_dict['y_train'] == y_train_pred).double().mean().item()\n\n  y_test_pred = cls.predict(data_dict['X_val'])\n  val_acc = 100.0 * (data_dict['y_val'] == y_test_pred).double().mean().item()\n\n  return cls, train_acc, val_acc\n\n\ndef softmax_loss_naive(W, X, y, reg):\n  loss = 0.0\n  dW = torch.zeros_like(W)\n  num_classes = W.shape[1]\n  num_train = X.shape[0]\n\n  scores = W.t().mv(X[0])\n  correct_class_score = scores[y[0]]\n\n  for i in range(num_train):\n    scores = W.t().mv(X[i])\n    scores = scores - scores.max()\n    correct_class_score = scores[y[i]]\n    loss += -correct_class_score + torch.log(torch.exp(scores).sum())\n    for j in range(num_classes):\n      if j == y[i]:\n        dW[:, j] += torch.exp(scores[j]) / torch.exp(scores).sum() * X[i, :] - X[i, :]\n      else:\n        dW[:, j] += torch.exp(scores[j]) / torch.exp(scores).sum() * X[i, :]\n\n  loss /= num_train\n  loss += reg * torch.sum(W * W)\n  dW /= num_train\n  dW += 2 * reg * W\n\n  return loss, dW\n\n\ndef softmax_loss_vectorized(W, X, y, reg):\n  loss = 0.0\n  dW = torch.zeros_like(W)\n  num_classes = W.shape[1]\n  num_train = X.shape[0]\n\n\n  scores = X.mm(W)\n  val, _ = scores.max(dim=1)\n  scores = scores - val.view(-1, 1)\n  exp_scores = scores.exp()\n  exp_scores_sum = exp_scores.sum(dim=1)\n  exp_scores_sum_log = exp_scores_sum.log()\n  correct_class_scores = scores[range(num_train), y]\n  loss = (exp_scores_sum_log - correct_class_scores).sum()\n  zeros = torch.zeros((num_train, num_classes), dtype=torch.float64, device='cuda')\n  zeros[range(num_train), y] = -1\n  minus_X = zeros.t().mm(X)\n  dW += minus_X.t()\n  dW += ((exp_scores / exp_scores_sum.view(-1, 1)).t().mm(X)).t()\n\n  loss /= num_train\n  loss += reg * torch.sum(W * W)\n  dW /= num_train\n  dW += 2 * reg * W\n\n  return loss, dW\n\n\ndef softmax_get_search_params():\n  learning_rates = [1e-4, 1e-3,1e-2, 1e-1, 1]\n  regularization_strengths = [1e-4, 1e-3, 1e-2, 1e-1] \n  return learning_rates, regularization_strengths\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/","title":"FFB6D\u73af\u5883\u914d\u7f6e\u6307\u5357\uff1a\u539f\u751f\u7cfb\u7edf\u5b89\u88c5","text":""},{"location":"AI/FFB6D/FFB6D_Conda/#ffb6d","title":"FFB6D\u73af\u5883\u914d\u7f6e\u6307\u5357\uff1a\u539f\u751f\u7cfb\u7edf\u5b89\u88c5","text":"<p> \u7ea6 293 \u4e2a\u5b57  96 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"AI/FFB6D/FFB6D_Conda/#1","title":"1. \u7cfb\u7edf\u8981\u6c42","text":"<ul> <li>Ubuntu 20.04/22.04/24.04</li> <li>NVIDIA GPU\uff08\u652f\u6301CUDA\uff09</li> <li>\u81f3\u5c118GB\u5185\u5b58</li> <li>\u81f3\u5c1130GB\u78c1\u76d8\u7a7a\u95f4</li> </ul>"},{"location":"AI/FFB6D/FFB6D_Conda/#2","title":"2. \u57fa\u7840\u73af\u5883\u914d\u7f6e","text":""},{"location":"AI/FFB6D/FFB6D_Conda/#21-nvidia","title":"2.1 \u5b89\u88c5NVIDIA\u9a71\u52a8","text":"Bash<pre><code># \u6dfb\u52a0NVIDIA\u5305\u4ed3\u5e93\nsudo add-apt-repository ppa:graphics-drivers/ppa\nsudo apt-get update\n\n# \u5b89\u88c5NVIDIA\u9a71\u52a8\nsudo apt-get install -y nvidia-driver-535  # \u6839\u636e\u9700\u8981\u9009\u62e9\u7248\u672c\n\n# \u91cd\u542f\u7cfb\u7edf\nsudo reboot\n\n# \u9a8c\u8bc1\u5b89\u88c5\nnvidia-smi\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#22-cudacudnn","title":"2.2 \u5b89\u88c5CUDA\u548ccuDNN","text":"Bash<pre><code># \u4e0b\u8f7d\u5e76\u5b89\u88c5CUDA 11.0\nwget https://developer.download.nvidia.com/compute/cuda/11.0.3/local_installers/cuda_11.0.3_450.51.06_linux.run\nsudo sh cuda_11.0.3_450.51.06_linux.run\n\n# \u914d\u7f6e\u73af\u5883\u53d8\u91cf\necho 'export PATH=/usr/local/cuda-11.0/bin:$PATH' &gt;&gt; ~/.bashrc\necho 'export LD_LIBRARY_PATH=/usr/local/cuda-11.0/lib64:$LD_LIBRARY_PATH' &gt;&gt; ~/.bashrc\nsource ~/.bashrc\n\n# \u4e0b\u8f7d\u5e76\u5b89\u88c5cuDNN 8.0\n# \u6ce8\uff1a\u9700\u8981\u4eceNVIDIA\u5f00\u53d1\u8005\u7f51\u7ad9\u4e0b\u8f7dcuDNN v8.0\uff0c\u89e3\u538b\u540e\uff1a\nsudo cp cuda/include/cudnn*.h /usr/local/cuda/include\nsudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64\nsudo chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/lib64/libcudnn*\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#23","title":"2.3 \u5b89\u88c5\u7cfb\u7edf\u4f9d\u8d56","text":"Bash<pre><code>sudo apt-get update\nsudo apt-get install -y \\\n    python3.6 \\\n    python3.6-dev \\\n    python3-pip \\\n    git \\\n    cmake \\\n    build-essential \\\n    libopencv-dev \\\n    libglib2.0-0 \\\n    libsm6 \\\n    libxext6 \\\n    libxrender-dev \\\n    libboost-all-dev \\\n    libeigen3-dev\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#24-python","title":"2.4 \u914d\u7f6ePython\u73af\u5883","text":"Bash<pre><code># \u8bbe\u7f6ePython 3.6\u4e3a\u9ed8\u8ba4\u7248\u672c\nsudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.6 1\nsudo update-alternatives --set python3 /usr/bin/python3.6\n\n# \u914d\u7f6epip\u955c\u50cf\u6e90\npip3 config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple\n\n# \u5347\u7ea7pip\npython3 -m pip install --upgrade pip\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#3-pytorch","title":"3. \u5b89\u88c5PyTorch\u548c\u4f9d\u8d56\u5305","text":""},{"location":"AI/FFB6D/FFB6D_Conda/#31-pytorch","title":"3.1 \u5b89\u88c5PyTorch","text":"Bash<pre><code>pip3 install torch==1.10.2+cu113 torchvision==0.11.3+cu113 -f https://download.pytorch.org/whl/torch_stable.html\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#32","title":"3.2 \u5b89\u88c5\u9879\u76ee\u4f9d\u8d56","text":"<p>\u521b\u5efarequirements.txt\u5e76\u5b89\u88c5\u4f9d\u8d56\uff1a</p> Bash<pre><code>pip3 install -r requirements.txt\n</code></pre> <p>requirements.txt\u5185\u5bb9\uff1a </p>Text Only<pre><code>h5py         \nnumpy              \npyyaml==5.4.1\nenum34        \nfuture           \nscipy==1.4.1          \nopencv_contrib_python==3.4.2.16               \ntransforms3d==0.3.1     \nscikit_image==0.13.1     \nlmdb==0.94              \nsetuptools==41.0.0    \ncffi==1.11.5         \neasydict==1.7      \nplyfile==0.6      \npillow==8.2.0 \ndataclasses\nglumpy                                                      \ntqdm\ntensorboardX \npandas\nscikit-learn         \nscipy \ntermcolor\npybind11\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#4","title":"4. \u7f16\u8bd1\u548c\u5b89\u88c5\u7279\u6b8a\u7ec4\u4ef6","text":""},{"location":"AI/FFB6D/FFB6D_Conda/#41-apex","title":"4.1 \u7f16\u8bd1apex","text":"Bash<pre><code>git clone https://github.com/NVIDIA/apex\ncd apex\nexport TORCH_CUDA_ARCH_LIST=\"6.0;6.1;6.2;7.0;7.5\"\npython setup.py install -v\ncd ..\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#42-normalspeed","title":"4.2 \u5b89\u88c5\u548c\u7f16\u8bd1normalspeed","text":"Bash<pre><code># 1. \u51c6\u5907OpenCV\u73af\u5883\npip uninstall opencv-python opencv-python-headless -y\npip install opencv-python==4.5.3.56\n\n# 2. \u514b\u9686\u5e76\u5b89\u88c5normalspeed\ngit clone https://github.com/hfutcgncas/normalspeed.git\ncd normalspeed/normalSpeed\n\n# \u5b89\u88c5\u7f16\u8bd1\u4f9d\u8d56\nsudo apt-get install python3-pybind11\npip3 install Cython==0.29.15\n\n# \u6e05\u7406\u5e76\u91cd\u65b0\u5b89\u88c5\nrm -rf build/ dist/ *.egg-info/\npython3 setup.py install --user\ncd ../..\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#5-ffb6d","title":"5. \u514b\u9686\u548c\u914d\u7f6eFFB6D","text":"Bash<pre><code># \u514b\u9686\u4ee3\u7801\ngit clone https://github.com/ethnhe/FFB6D.git\ncd FFB6D\n\n# \u521b\u5efa\u5fc5\u8981\u7684\u76ee\u5f55\nmkdir -p datasets models train_log\n\n# \u914d\u7f6e\u73af\u5883\u53d8\u91cf\nexport PYTHONPATH=$PYTHONPATH:$(pwd)\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#6","title":"6. \u9a8c\u8bc1\u5b89\u88c5","text":"Bash<pre><code># \u9a8c\u8bc1CUDA\u652f\u6301\npython3 -c \"import torch; print('CUDA available:', torch.cuda.is_available())\"\n\n# \u9a8c\u8bc1apex\u5b89\u88c5\npython3 -c \"from apex import amp; print('APEX installed')\"\n\n# \u9a8c\u8bc1normalspeed\u5b89\u88c5\npython3 -c \"import normalSpeed; print('normalspeed installed')\"\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#7","title":"7. \u5e38\u89c1\u95ee\u9898","text":""},{"location":"AI/FFB6D/FFB6D_Conda/#71","title":"7.1 \u7f51\u7edc\u95ee\u9898","text":"Bash<pre><code># \u4f7f\u7528\u4ee3\u7406\uff08\u5982\u9700\u8981\uff09\nexport http_proxy=\"http://proxy:port\"\nexport https_proxy=\"http://proxy:port\"\n\n# \u6216\u4f7f\u7528\u56fd\u5185\u955c\u50cf\u6e90\npip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#72","title":"7.2 \u7248\u672c\u517c\u5bb9\u6027\u95ee\u9898","text":"<ul> <li>\u786e\u4fddNVIDIA\u9a71\u52a8\u7248\u672c\u652f\u6301CUDA 11.0</li> <li>\u786e\u4fddPython\u5305\u7248\u672c\u76f8\u4e92\u517c\u5bb9</li> <li>\u68c0\u67e5CUDA\u7248\u672c\u4e0ePyTorch\u7248\u672c\u7684\u5339\u914d</li> </ul>"},{"location":"AI/FFB6D/FFB6D_Conda/#73","title":"7.3 \u7f16\u8bd1\u9519\u8bef","text":"<ul> <li>\u786e\u4fdd\u5df2\u5b89\u88c5\u6240\u6709\u5fc5\u8981\u7684\u7f16\u8bd1\u5de5\u5177</li> <li>\u68c0\u67e5CUDA\u8def\u5f84\u914d\u7f6e\u662f\u5426\u6b63\u786e</li> <li>\u786e\u8ba4\u7cfb\u7edf\u5e93\u7248\u672c\u662f\u5426\u6ee1\u8db3\u8981\u6c42</li> </ul>"},{"location":"AI/FFB6D/FFB6D_Conda/#8","title":"8. \u8bad\u7ec3","text":"<p>\u6309\u7167\u5b98\u65b9\u6587\u6863\u914d\u7f6eLineMOD\u6570\u636e\u96c6\u5e76\u5f00\u59cb\u8bad\u7ec3\u3002</p>"},{"location":"AI/FFB6D/FFB6D_Conda/#_1","title":"\u53c2\u8003\u8d44\u6599","text":"<ol> <li>FFB6D\u9879\u76ee</li> <li>CUDA\u5b89\u88c5\u6307\u5357</li> <li>PyTorch\u5b89\u88c5\u6307\u5357</li> <li>\u3010\u8bba\u6587\u7b14\u8bb0\u3011FFB6D | \u9a6c\u6d69\u98de\u4e28\u535a\u5ba2</li> </ol>"},{"location":"AI/FFB6D/FFB6D_Docker/","title":"Docker\u4ece\u5165\u95e8\u5230\u5b9e\u8df5\uff1a\u4ee5FFB6D\u73af\u5883\u914d\u7f6e\u4e3a\u4f8b","text":""},{"location":"AI/FFB6D/FFB6D_Docker/#dockerffb6d","title":"Docker\u4ece\u5165\u95e8\u5230\u5b9e\u8df5\uff1a\u4ee5FFB6D\u73af\u5883\u914d\u7f6e\u4e3a\u4f8b","text":"<p> \u7ea6 653 \u4e2a\u5b57  213 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 6 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"AI/FFB6D/FFB6D_Docker/#1","title":"1. \u7b80\u4ecb","text":"<p>Docker\u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u5e94\u7528\u5bb9\u5668\u5f15\u64ce\uff0c\u8ba9\u5f00\u53d1\u8005\u53ef\u4ee5\u6253\u5305\u4ed6\u4eec\u7684\u5e94\u7528\u4ee5\u53ca\u4f9d\u8d56\u5305\u5230\u4e00\u4e2a\u53ef\u79fb\u690d\u7684\u5bb9\u5668\u4e2d\uff0c\u7136\u540e\u53d1\u5e03\u5230\u4efb\u4f55\u6d41\u884c\u7684Linux\u6216Windows\u64cd\u4f5c\u7cfb\u7edf\u4e0a\u3002\u672c\u6587\u5c06\u4ee5\u914d\u7f6eFFB6D\uff08\u4e00\u4e2a3D\u76ee\u6807\u68c0\u6d4b\u6a21\u578b\uff09\u7684\u8fd0\u884c\u73af\u5883\u4e3a\u4f8b\uff0c\u4ecb\u7ecdDocker\u7684\u57fa\u672c\u4f7f\u7528\u3002</p>"},{"location":"AI/FFB6D/FFB6D_Docker/#2","title":"2. \u73af\u5883\u51c6\u5907","text":""},{"location":"AI/FFB6D/FFB6D_Docker/#21","title":"2.1 \u7cfb\u7edf\u8981\u6c42","text":"<ul> <li>Ubuntu 20.04/22.04/24.04 </li> <li>NVIDIA GPU\uff08\u652f\u6301CUDA\uff09</li> <li>\u81f3\u5c118GB\u5185\u5b58</li> <li>\u81f3\u5c1130GB\u78c1\u76d8\u7a7a\u95f4</li> </ul>"},{"location":"AI/FFB6D/FFB6D_Docker/#22","title":"2.2 \u57fa\u7840\u7ec4\u4ef6\u5b89\u88c5","text":"<p>\u5b89\u88c5Docker</p> Bash<pre><code># \u66f4\u65b0apt\u5305\u7d22\u5f15\nsudo apt-get update\n\n# \u5b89\u88c5\u5fc5\u8981\u7684\u7cfb\u7edf\u5de5\u5177\nsudo apt-get install -y \\\n    apt-transport-https \\\n    ca-certificates \\\n    curl \\\n    gnupg \\\n    lsb-release\n\n# \u6dfb\u52a0Docker\u7684\u5b98\u65b9GPG\u5bc6\u94a5\ncurl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /usr/share/keyrings/docker-archive-keyring.gpg\n\n# \u8bbe\u7f6e\u7a33\u5b9a\u7248\u4ed3\u5e93\necho \\\n  \"deb [arch=amd64 signed-by=/usr/share/keyrings/docker-archive-keyring.gpg] https://download.docker.com/linux/ubuntu \\\n  $(lsb_release -cs) stable\" | sudo tee /etc/apt/sources.list.d/docker.list &gt; /dev/null\n\n# \u5b89\u88c5Docker Engine\nsudo apt-get update\nsudo apt-get install -y docker-ce docker-ce-cli containerd.io\n\n# \u9a8c\u8bc1\u5b89\u88c5\nsudo docker run hello-world\n</code></pre> <p>\u5b89\u88c5NVIDIA\u9a71\u52a8</p> Bash<pre><code># \u6dfb\u52a0NVIDIA\u5305\u4ed3\u5e93\nsudo add-apt-repository ppa:graphics-drivers/ppa\nsudo apt-get update\n\n# \u5b89\u88c5NVIDIA\u9a71\u52a8\nsudo apt-get install -y nvidia-driver-535  # \u6839\u636e\u9700\u8981\u9009\u62e9\u7248\u672c\n\n# \u91cd\u542f\u7cfb\u7edf\nsudo reboot\n\n# \u9a8c\u8bc1\u5b89\u88c5\nnvidia-smi\n</code></pre> <p>\u5b89\u88c5NVIDIA Container Toolkit</p> Bash<pre><code># \u8bbe\u7f6e\u7a33\u5b9a\u7248\u4ed3\u5e93\ncurl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg\n\necho \"deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://nvidia.github.io/libnvidia-container/stable/ubuntu22.04/$(arch) /\" | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list\n\n# \u66f4\u65b0\u8f6f\u4ef6\u5305\u5217\u8868\nsudo apt-get update\n\n# \u5b89\u88c5nvidia-docker2\nsudo apt-get install -y nvidia-container-toolkit\n\n# \u91cd\u542fDocker\u670d\u52a1\nsudo systemctl restart docker\n\n# \u6d4b\u8bd5GPU\u652f\u6301\nsudo docker run --rm --gpus all nvidia/cuda:12.0-base nvidia-smi\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#23-docker","title":"2.3 Docker\u914d\u7f6e\u4f18\u5316","text":"<p>\u914d\u7f6e\u955c\u50cf\u52a0\u901f</p> Bash<pre><code>sudo tee /etc/docker/daemon.json &lt;&lt; EOF\n{\n  \"registry-mirrors\": [\n    \"https://docker.1panel.dev\",\n    \"https://docker.zhai.cm\",\n    \"https://hub.littlediary.cn\",\n    \"https://docker.nastool.de\"\n  ],\n  \"dns\": [\"8.8.8.8\", \"8.8.4.4\"],\n  \"max-concurrent-downloads\": 10,\n  \"log-driver\": \"json-file\",\n  \"log-opts\": {\n    \"max-size\": \"10m\",\n    \"max-file\": \"3\"\n  }\n}\nEOF\n\nsudo systemctl daemon-reload\nsudo systemctl restart docker\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#3-ffb6d","title":"3. FFB6D\u73af\u5883\u914d\u7f6e\u5b9e\u4f8b","text":""},{"location":"AI/FFB6D/FFB6D_Docker/#31","title":"3.1 \u9879\u76ee\u7ed3\u6784","text":"Bash<pre><code>ffb6d_docker/\n\u251c\u2500\u2500 Dockerfile\n\u251c\u2500\u2500 docker-compose.yml\n\u251c\u2500\u2500 build_and_run.sh\n\u251c\u2500\u2500 downloads/\n\u2502   \u251c\u2500\u2500 apex/\n\u2502   \u2514\u2500\u2500 normalspeed/\n\u251c\u2500\u2500 code/\n\u251c\u2500\u2500 datasets/\n\u251c\u2500\u2500 models/\n\u2514\u2500\u2500 train_log/\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#32-dockerfile","title":"3.2 \u521b\u5efaDockerfile","text":"Docker<pre><code># \u4f7f\u7528\u8f83\u65b0\u7684 CUDA \u955c\u50cf\nFROM nvcr.io/nvidia/cuda:11.0.3-cudnn8-devel-ubuntu18.04\n\n# \u4f7f\u7528 NVIDIA CUDA 11.3 \u57fa\u7840\u955c\u50cf\n# FROM nvcr.io/nvidia/cuda:11.3.1-cudnn8-devel-ubuntu20.04\n\n# \u907f\u514d\u4ea4\u4e92\u5f0f\u63d0\u793a\nENV DEBIAN_FRONTEND=noninteractive\nENV PYTHONPATH=/workspace/code\nENV CUDA_HOME=/usr/local/cuda\nENV PATH=$CUDA_HOME/bin:$PATH\nENV LD_LIBRARY_PATH=$CUDA_HOME/lib64:$LD_LIBRARY_PATH\n\nWORKDIR /workspace\n\n# \u5b89\u88c5\u7cfb\u7edf\u4f9d\u8d56\nRUN apt-get update &amp;&amp; apt-get install -y \\\n    python3.6 \\\n    python3.6-dev \\\n    python3-pip \\\n    git \\\n    cmake \\\n    build-essential \\\n    libopencv-dev \\\n    libglib2.0-0 \\\n    libsm6 \\\n    libxext6 \\\n    libxrender-dev \\\n    libboost-all-dev \\\n    libeigen3-dev \\\n    wget \\\n    &amp;&amp; rm -rf /var/lib/apt/lists/*\n\n# \u8bbe\u7f6e Python 3.6 \u4e3a\u9ed8\u8ba4\u7248\u672c\nRUN update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.6 1\nRUN update-alternatives --set python3 /usr/bin/python3.6\n\n# \u5347\u7ea7 pip\nRUN python3 -m pip install --upgrade pip\n\n# \u914d\u7f6epip\u955c\u50cf\u6e90\nRUN pip3 config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple\n\n# \u5148\u5b89\u88c5 PyTorch (\u4f7f\u7528\u8f83\u65b0\u4f46\u517c\u5bb9\u7684\u7248\u672c)\nRUN pip3 install torch==1.10.2+cu113 torchvision==0.11.3+cu113 -f https://download.pytorch.org/whl/torch_stable.html\n\n# \u590d\u5236\u9884\u4e0b\u8f7d\u7684\u6587\u4ef6\nCOPY downloads/apex /workspace/apex\nCOPY downloads/normalspeed /workspace/normalspeed\nCOPY code /workspace/code\n\n# \u5b89\u88c5 apex\n#RUN cd /workspace/apex &amp;&amp; \\\n#    pip install -v --no-cache-dir --global-option=\"--cpp_ext\" --global-option=\"--cuda_ext\" ./ || \\\n#    (echo \"Apex installation failed. Check the error messages above.\" &amp;&amp; exit 1)\n\n# \u5b89\u88c5 normalspeed\n#RUN cd /workspace/normalspeed &amp;&amp; \\\n#    python3 setup.py build_ext --inplace &amp;&amp; \\\n#    python3 setup.py install\n\nWORKDIR /workspace/code\n</code></pre> <p>\u66f4\u6539 <code>requirement.txt</code> </p> Text Only<pre><code>h5py         \nnumpy              \npyyaml==5.4.1\nenum34        \nfuture           \nscipy==1.4.1          \nopencv_contrib_python==3.4.2.16               \ntransforms3d==0.3.1     \nscikit_image==0.13.1     \nlmdb==0.94              \nsetuptools==41.0.0    \ncffi==1.11.5         \neasydict==1.7      \nplyfile==0.6      \npillow==8.2.0 \ndataclasses\nglumpy                                                      \ntqdm\ntensorboardX \npandas\nscikit-learn         \nscipy \ntermcolor\npybind11\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#33-docker-composeyml","title":"3.3 \u521b\u5efadocker-compose.yml","text":"YAML<pre><code>version: '3'\nservices:\n  ffb6d:\n    build: .\n    image: ffb6d:latest\n    container_name: ffb6d_container\n    runtime: nvidia\n    environment:\n      - NVIDIA_VISIBLE_DEVICES=all\n    volumes:\n      - ./datasets:/workspace/code/datasets\n      - ./train_log:/workspace/code/train_log\n      - ./models:/workspace/code/models\n    shm_size: '8gb'\n    tty: true\n    stdin_open: true\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#34","title":"3.4 \u6784\u5efa\u548c\u8fd0\u884c\u811a\u672c","text":"<p>\u521b\u5efa<code>build_and_run.sh</code>\uff1a</p> Bash<pre><code>#!/bin/bash\n\n# \u521b\u5efa\u5fc5\u8981\u76ee\u5f55\nmkdir -p downloads datasets models train_log\n\n# \u4e0b\u8f7d\u4f9d\u8d56\ncd downloads\nif [ ! -d \"apex\" ]; then\n  git clone https://github.com/NVIDIA/apex.git\nfi\nif [ ! -d \"normalspeed\" ]; then\n  git clone https://github.com/hfutcgncas/normalspeed.git\nfi\ncd ..\n\n# \u514b\u9686FFB6D\u4ee3\u7801\nif [ ! -d \"code\" ]; then\n  git clone https://github.com/ethnhe/FFB6D.git code\nfi\n\n# \u6784\u5efa\u955c\u50cf\ndocker-compose build\n\n# \u8fd0\u884c\u5bb9\u5668\ndocker-compose up -d\ndocker exec -it ffb6d_container bash\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#35","title":"3.5 \u542f\u52a8\u548c\u9a8c\u8bc1","text":"Bash<pre><code># \u6dfb\u52a0\u6267\u884c\u6743\u9650\nchmod +x build_and_run.sh\n\n# \u8fd0\u884c\n./build_and_run.sh\n\n# \u5728\u5bb9\u5668\u5185\u9a8c\u8bc1\npython3 -c \"import torch; print('CUDA available:', torch.cuda.is_available())\"\npython3 -c \"from apex import amp; print('APEX installed')\"\npython3 -c \"import normalspeed; print('normalspeed installed')\"\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#36-apex","title":"3.6 \u7f16\u8bd1 apex","text":"Text Only<pre><code>git clone https://github.com/NVIDIA/apex\ncd apex\nexport TORCH_CUDA_ARCH_LIST=\"6.0;6.1;6.2;7.0;7.5\"\npython setup.py install -v\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#37-normalspeed","title":"3.7 \u7f16\u8bd1 normalspeed","text":"Text Only<pre><code># 1. \u5378\u8f7d\u5f53\u524dcv2\npip uninstall opencv-python opencv-python-headless -y\n\n# 2. \u5b89\u88c5\u7279\u5b9a\u7248\u672c\u7684OpenCV\uff0c\u9009\u62e9\u4e0ePython 3.6\u517c\u5bb9\u7684\u7248\u672c\npip install opencv-python==4.5.3.56\n\n# 3. \u9a8c\u8bc1\u5b89\u88c5\npython3 -c \"import cv2; print(cv2.__version__)\"\n</code></pre> Text Only<pre><code># \u8fdb\u5165normalSpeed\u76ee\u5f55\ncd /workspace/code/normalspeed/normalSpeed\n\n# \u5b89\u88c5\u4f9d\u8d56\napt-get update\napt-get install python3-pybind11\npip3 install Cython==0.29.15\n\n# \u6e05\u7406\u4e4b\u524d\u7684\u6784\u5efa\nrm -rf build/\nrm -rf dist/\nrm -rf *.egg-info/\n\n# \u91cd\u65b0\u5b89\u88c5\npython3 setup.py install\n\n# \u9a8c\u8bc1\u5b89\u88c5\npython3 -c \"import normalSpeed\"\n\n# \u8fd4\u56deffb6d\u76ee\u5f55\ncd /workspace/code/ffb6d/\n</code></pre> Text Only<pre><code>python3 setup.py install --user\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#38","title":"3.8 \u8bad\u7ec3","text":"<p>\u628a LineMOD \u590d\u5236\u5230\u5bf9\u5e94\u7684\u8def\u5f84\u4e0b\uff0c\u7136\u540e\u6309\u5b98\u7f51\u6765\u5c31\u597d\u4e86</p>"},{"location":"AI/FFB6D/FFB6D_Docker/#4","title":"4. \u5e38\u89c1\u95ee\u9898","text":""},{"location":"AI/FFB6D/FFB6D_Docker/#41","title":"4.1 \u7f51\u7edc\u95ee\u9898","text":"<p>\u5982\u679c\u9047\u5230\u4e0b\u8f7d\u6162\u6216\u5931\u8d25\uff1a</p> Bash<pre><code># \u4e34\u65f6\u4f7f\u7528\u4ee3\u7406\nexport http_proxy=\"http://proxy:port\"\nexport https_proxy=\"http://proxy:port\"\n\n# \u6216\u4fee\u6539pip\u6e90\npip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple\n</code></pre> <p>\u6ce8\u610f\u7528\u4e86\u4ee3\u7406\u7684\u8bdd\uff0cdocker hub \u955c\u50cf\u5c31\u4f1a\u88ab\u8986\u76d6\u6389\uff0c\u5bfc\u81f4\u901f\u5ea6\u5f88\u6162\u3002\u6240\u4ee5\u5230\u65f6\u5019\u4e00\u5b9a\u8981\u53d6\u6d88\u4ee3\u7406 / \u5220\u9664\u4ee3\u7406\u6587\u4ef6</p> <p>docker hub \u955c\u50cf\u8bbe\u7f6e\u4e0a\u9762\u5199\u4e86\uff0c\u5b98\u7f51\u662f\u8fd9\u4e2a GitHub - dongyubin/DockerHub: 2024\u5e7411\u6708\u66f4\u65b0\uff0c\u76ee\u524d\u56fd\u5185\u53ef\u7528Docker\u955c\u50cf\u6e90\u6c47\u603b\uff0cDockerHub\u56fd\u5185\u955c\u50cf\u52a0\u901f\u5217\u8868\uff0c\ud83d\ude80DockerHub\u955c\u50cf\u52a0\u901f\u5668</p>"},{"location":"AI/FFB6D/FFB6D_Docker/#42-cuda","title":"4.2 CUDA\u517c\u5bb9\u6027","text":"<p>\u786e\u4fddNVIDIA\u9a71\u52a8\u7248\u672c\u652f\u6301\u6240\u9700\u7684CUDA\u7248\u672c\uff1a</p> Bash<pre><code># \u68c0\u67e5\u652f\u6301\u7684\u6700\u9ad8CUDA\u7248\u672c\nnvidia-smi\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#43","title":"4.3 \u5185\u5b58\u4e0d\u8db3","text":"<p>\u8c03\u6574Docker\u5185\u5b58\u9650\u5236\uff1a</p> YAML<pre><code># \u5728docker-compose.yml\u4e2d\u6dfb\u52a0\nservices:\n  ffb6d:\n    deploy:\n      resources:\n        limits:\n          memory: 16G\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#5","title":"5. \u603b\u7ed3","text":"<p>\u672c\u6587\u4ecb\u7ecd\u4e86\u4f7f\u7528Docker\u914d\u7f6e\u6df1\u5ea6\u5b66\u4e60\u73af\u5883\u7684\u5b8c\u6574\u6d41\u7a0b\uff0c\u4ee5FFB6D\u4e3a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5904\u7406\u590d\u6742\u4f9d\u8d56\u5173\u7cfb\u3002\u901a\u8fc7\u5bb9\u5668\u5316\u6280\u672f\uff0c\u6211\u4eec\u53ef\u4ee5\uff1a</p> <ol> <li>\u786e\u4fdd\u73af\u5883\u4e00\u81f4\u6027</li> <li>\u7b80\u5316\u90e8\u7f72\u6d41\u7a0b</li> <li>\u63d0\u9ad8\u5f00\u53d1\u6548\u7387</li> <li>\u65b9\u4fbf\u56e2\u961f\u534f\u4f5c</li> </ol> <p>\u5e0c\u671b\u672c\u6559\u7a0b\u80fd\u5e2e\u52a9\u4f60\u66f4\u597d\u5730\u7406\u89e3\u548c\u4f7f\u7528Docker\u3002</p>"},{"location":"AI/FFB6D/FFB6D_Docker/#_1","title":"\u53c2\u8003\u8d44\u6599","text":"<ol> <li>Docker\u5b98\u65b9\u6587\u6863</li> <li>NVIDIA Docker\u6587\u6863</li> <li>FFB6D\u9879\u76ee</li> <li>\u3010\u8bba\u6587\u7b14\u8bb0\u3011FFB6D | \u9a6c\u6d69\u98de\u4e28\u535a\u5ba2</li> </ol>"},{"location":"CS_Basic/","title":"Computer Basic","text":""},{"location":"CS_Basic/#computer-science-basic","title":"Computer Science Basic","text":"<p>Abstract</p> <p>\u672c\u90e8\u5206\u5185\u5bb9\uff08\u9664\u7279\u522b\u58f0\u660e\u5916\uff09\u91c7\u7528 \u7f72\u540d-\u975e\u5546\u4e1a\u6027\u4f7f\u7528-\u4fdd\u6301\u4e00\u81f4 4.0 \u56fd\u9645 (CC BY-NC-SA 4.0) \u8bb8\u53ef\u534f\u8bae\u8fdb\u884c\u8bb8\u53ef\u3002</p> CS61A          <ul> <li> Composing Programs  2713  651  17 mins              1734027543 </li> <li> Experience  0  0 mins              0 </li> </ul> CS61C          <ul> <li> \u8ba1\u7b97\u673a\u7ec4\u6210\u4e0e\u8bbe\u8ba1\u786c\u4ef6\u8f6f\u4ef6\u63a5\u53e3  2978  13  10 mins              1734027543 </li> </ul> Network          <ul> <li> Security Basic  368  1 mins              1734027543 </li> </ul> 15-213          <ul> <li> CSAPP  1012  36  4 mins              1734027543 </li> </ul> C++          <ul> <li> Accelerated C++  2534  489  15 mins              1734027543 </li> <li> C++ Basic  3115  523  17 mins              1734027543 </li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/","title":"\u6df1\u5165\u7406\u89e3\u8ba1\u7b97\u673a\u7cfb\u7edf","text":""},{"location":"CS_Basic/15-213/CSAPP/#_1","title":"\u6df1\u5165\u7406\u89e3\u8ba1\u7b97\u673a\u7cfb\u7edf","text":"<p> \u7ea6 1012 \u4e2a\u5b57  36 \u884c\u4ee3\u7801  14 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 6 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"CS_Basic/15-213/CSAPP/#1","title":"1 \u8ba1\u7b97\u673a\u7cfb\u7edf\u6f2b\u6e38","text":""},{"location":"CS_Basic/15-213/CSAPP/#2","title":"2 \u4fe1\u606f\u7684\u8868\u793a\u548c\u5904\u7406","text":"<ul> <li>\u628a\u4f4d\u7ec4\u5408\u518d\u4e00\u8d77\uff0c\u518d\u52a0\u4e0a interpretation</li> <li>\u4e09\u79cd\u91cd\u8981\u7684\u6570\u5b57\u8868\u793a<ul> <li>unsigned</li> <li>two's-complement</li> <li>floating-point</li> </ul> </li> <li>overflow</li> <li>\u6d6e\u70b9\u6570\u662f\u8fd1\u4f3c\u7684</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#21","title":"2.1 \u4fe1\u606f\u5b58\u50a8","text":"<ul> <li>1 byte = 8 bits</li> <li>virtual memory </li> <li>address<ul> <li>virtual address space</li> </ul> </li> <li>\u8bb2\u5b58\u50a8\u5668\u7a7a\u95f4\u5212\u5206\u4e3a\u66f4\u53ef\u7ba1\u7406\u7684\u5355\u5143\uff0c\u6765\u5b58\u653e\u4e0d\u540c\u7684 program object</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#211","title":"2.1.1 \u5341\u516d\u8fdb\u5236\u8868\u793a\u6cd5","text":"<ul> <li>0x...</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#212","title":"2.1.2 \u5b57\u6570\u636e\u5927\u5c0f","text":"<ul> <li>word size </li> <li>nominal size</li> <li>\u5b57\u957f\u51b3\u5b9a\u7684\u6700\u91cd\u8981\u7684\u7cfb\u7edf\u53c2\u6570\u5c31\u662f\u865a\u62df\u5730\u5740\u7a7a\u95f4\u7684\u6700\u5927\u5927\u5c0f<ul> <li>\u5b57\u957f\u4e3a \\(\\displaystyle \\omega\\) \u4e3a\u7684\u673a\u5668\uff0c\u865a\u62df\u5730\u5740\u7684\u8303\u56f4\u4e3a \\(\\displaystyle 0\\sim2^{\\omega} - 1\\)</li> <li>\u5927\u591a\u6570 64 \u4f4d\u673a\u5668\u53ef\u4ee5\u8fd0\u884c 32 \u4f4d\u673a\u5668\u7f16\u8bd1\u7684\u7a0b\u5e8f\uff0c\u5373\u5411\u540e\u517c\u5bb9 </li> </ul> </li> <li>\u4e3a\u4e86\u907f\u514d\u5927\u5c0f\u548c\u4e0d\u540c\u7f16\u8bd1\u5668\u8bbe\u7f6e\u5e26\u6765\u7684\u5947\u602a\u884c\u4e3a\uff0c\u6211\u4eec\u6709\u4e86 int 32_t \u548c int 64_t</li> <li>C \u8bed\u8a00\u5bf9\u58f0\u660e\u7684\u5173\u952e\u8bcd\u987a\u5e8f\u4e0d\u654f\u611f</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#213","title":"2.1.3 \u5bfb\u5740\u548c\u5b57\u8282\u987a\u5e8f","text":"<ul> <li>[[\u8ba1\u7b97\u673a\u7ec4\u6210\u4e0e\u8bbe\u8ba1\u786c\u4ef6\u8f6f\u4ef6\u63a5\u53e3#^da8be4|\u5c0f\u7aef\u7f16\u5740]]<ul> <li>\u5c31\u662f\u53f3\u8fb9\u653e\u5c0f\u7684\uff0c\u8981\u4ece\u53f3\u5f80\u5de6\u8bfb</li> </ul> </li> <li>\u5b57\u8282\u987a\u5e8f\u53d8\u5f97\u91cd\u8981\u7684\u4e09\u79cd\u60c5\u51b5<ul> <li>\u7f51\u7edc\u5e94\u7528\u7a0b\u5e8f\u7684\u4ee3\u7801\u7f16\u5199\u5fc5\u987b\u9075\u5b88\u5df2\u5efa\u7acb\u7684\u5173\u4e8e\u5b57\u8282\u987a\u5e8f\u7684\u89c4\u5219</li> <li>disassembler</li> <li>\u7f16\u5199\u89c4\u907f\u6b63\u5e38\u7684\u7c7b\u578b\u7cfb\u7edf\u7684\u7a0b\u5e8f<ul> <li>cast or union in C</li> <li>\u5bf9\u5e94\u7528\u7f16\u7a0b\u4e0d\u63a8\u8350\uff0c\u4f46\u662f\u5bf9\u7cfb\u7edf\u7ea7\u7f16\u7a0b\u662f\u5fc5\u9700\u7684</li> </ul> </li> </ul> </li> </ul> C<pre><code>#include &lt;stdio.h&gt;\n\n\n\ntypedef unsigned char *byte_pointer;\n\nvoid show_bytes(byte_pointer start, size_t len) {\n\u00a0 size_t i;\n\u00a0 for (i = 0; i &lt; len; i++)\n\u00a0 \u00a0 printf(\" %.2x\", start[i]);\n\u00a0 printf(\"\\n\");\n}\n\nvoid show_int(int x) { show_bytes((byte_pointer)&amp;x, sizeof(int)); }\n\nvoid show_float(float x) { show_bytes((byte_pointer)&amp;x, sizeof(float)); }\n\nvoid show_pointer(void *x) { show_bytes((byte_pointer)&amp;x, sizeof(void *)); }\n\nvoid test_show_bytes(int val) {\n\u00a0 int ival = val;\n\u00a0 float fval = (float)ival;\n\u00a0 int *pval = &amp;ival;\n\u00a0 show_int(ival);\n\u00a0 show_float(fval);\n\u00a0 show_pointer(pval);\n}\n\nint main() {\n\u00a0 int val = 12345;\n\u00a0 test_show_bytes(val);\n\u00a0 return 0;\n}\n</code></pre> Text Only<pre><code> 39 30 00 00 //\u5c0f\u7aef\u6cd5\n 00 e4 40 46\n 8c f6 bf ef b4 00 00 00\n</code></pre>"},{"location":"CS_Basic/15-213/CSAPP/#214","title":"2.1.4 \u8868\u793a\u5b57\u7b26\u4e32","text":""},{"location":"CS_Basic/15-213/CSAPP/#215","title":"2.1.5 \u8868\u793a\u4ee3\u7801","text":"<ul> <li>\u4e8c\u8fdb\u5236\u4ee3\u7801\u5f88\u5c11\u80fd\u5728\u4e0d\u540c\u673a\u5668\u548c\u64cd\u4f5c\u7cfb\u7edf\u7ec4\u5408\u4e4b\u95f4\u79fb\u690d</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#216","title":"2.1.6 \u5e03\u5c14\u4ee3\u6570\u7b80\u4ecb","text":"<ul> <li>\u53ef\u4ee5\u6269\u5c55\u5230\u4f4d\u5411\u91cf\u7684\u8fd0\u7b97</li> <li>\u5e03\u5c14\u4ee3\u6570</li> <li>Boolean ring<ul> <li>additive inverse</li> </ul> </li> <li>\u548c\u96c6\u5408\u7684\u5bf9\u5e94</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#217-c","title":"2.1.7 C \u8bed\u8a00\u4e2d\u7684\u4f4d\u7ea7\u8fd0\u7b97","text":"<ul> <li>\u63a9\u7801\u8fd0\u7b97</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#218-c","title":"2.1.8 C \u8bed\u8a00\u4e2d\u7684\u903b\u8f91\u8fd0\u7b97","text":""},{"location":"CS_Basic/15-213/CSAPP/#219-c","title":"2.1.9 C \u8bed\u8a00\u4e2d\u7684\u79fb\u4f4d\u8fd0\u7b97","text":"<ul> <li>\u903b\u8f91\u53f3\u79fb</li> <li>\u7b97\u6570\u53f3\u79fb</li> <li>\u5b9e\u9645\u4e0a\uff0c\u51e0\u4e4e\u6240\u6709\u7684\u7f16\u8bd1\u5668\u90fd\u5bf9\u6709\u7b26\u53f7\u6570\u4f7f\u7528\u7b97\u672f\u53f3\u79fb\uff0c\u800c\u5bf9\u4e8e\u65e0\u7b26\u53f7\u6570\uff0c\u53f3\u79fb\u5fc5\u987b\u662f\u903b\u8f91\u7684\uff08C \u8bed\u8a00\uff09</li> <li>\u800c\u5bf9\u4e8e Java <code>x&gt;&gt;k</code> \u662f\u7b97\u6570\u53f3\u79fb\uff0c <code>x&gt;&gt;&gt;k</code> \u662f\u903b\u8f91\u53f3\u79fb</li> <li>\u5bf9\u4e8e C \u8bed\u8a00\uff0c\u79fb\u52a8 \\(\\displaystyle k \\text{ mod } \\omega\\)</li> <li>\u52a0\u51cf\u7684\u4f18\u5148\u7ea7\u6bd4\u79fb\u4f4d\u7b97\u6cd5\u8981\u641e</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#22","title":"2.2 \u6574\u6570\u8868\u793a","text":""},{"location":"CS_Basic/15-213/CSAPP/#221","title":"2.2.1 \u6574\u578b\u6570\u636e\u7c7b\u578b","text":"<ul> <li>64 \u4f4d\u548c 32 \u4f4d\u662f\u4e0d\u4e00\u6837\u7684 </li> <li>\u53d6\u503c\u8303\u56f4\u4e0d\u662f\u5bf9\u79f0\u7684 </li> <li>Java \u53ea\u652f\u6301\u6709\u7b26\u53f7\u6570</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#222","title":"2.2.2 \u65e0\u7b26\u53f7\u6570\u7684\u7f16\u7801","text":"<ul> <li>\u628a\u5411\u91cf\u5199\u6210\u4e8c\u8fdb\u5236\u8868\u793a\u7684\u6570\uff0c\u5c31\u5f97\u5230\u4e86\u65e0\u7b26\u53f7\u8868\u793a </li> </ul> \\[ B2U_w(\\vec{x})\\doteq\\sum_{i=0}^{u-1}x_i2^i \\] \\[ B2U_w:\\{0, 1\\}^w\\to\\{0, \\cdots,2^w-1\\} \\] <ul> <li>\u65e0\u7b26\u53f7\u6570\u7f16\u7801\u7684\u552f\u4e00\u6027</li> <li>\\(\\displaystyle \u51fd\u6570B2U_w\u662f\u4e00\u4e2a\u53cc\u5c04\u3002\\)</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#223","title":"2.2.3 \u8865\u7801\u7f16\u7801","text":"<ul> <li>two's-complement</li> <li>negative weight</li> </ul> \\[ B2T_w(\\vec{x})\\doteq- x_{w-1}2^{w-1}+\\sum_{i=0}^{w-2}x_i2^i \\] \\[ B2T_{w}\\colon \\{0, 1\\}^{w}\\to\\langle TMin_{w}, \\cdots, TMax_{w} \\rangle  \\] <ul> <li>\u8865\u7801\u7f16\u7801\u7684\u552f\u4e00\u6027</li> <li> <p>\\(\\displaystyle \u51fd\u6570B2T_w\u662f\u4e00\u4e2a\u53cc\u5c04\u3002\\) </p> </li> <li> <p>\u53cd\u7801</p> </li> </ul> \\[ B2O_w(\\vec{x})\\doteq-x_{w-1}(2^{w-1}-1)+\\sum_{i=0}^{w-2}x_i2^i \\] <ul> <li>\u539f\u7801</li> </ul> \\[ B2S_w(\\vec{x})\\doteq(-1)^{x_{w-1}}\\cdot\\bigl(\\sum_{i=0}^{w-2}x_i2^i\\bigr) \\] <ul> <li>\u5bf9\u4e8e\u6570\u5b57 0 \u6709\u4e24\u79cd\u4e0d\u540c\u7684\u7f16\u7801\u65b9\u5f0f</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#224","title":"2.2.4 \u6709\u7b26\u53f7\u6570\u548c\u65e0\u7b26\u53f7\u6570\u4e4b\u95f4\u7684\u8f6c\u6362","text":"<ul> <li>\u4fdd\u6301\u4f4d\u503c\u4e0d\u53d8\uff0c\u6539\u53d8\u89e3\u91ca\u65b9\u5f0f</li> </ul> \\[ T2U_{_w}(x)\\doteq B2U_{_w}( T2B_{_w}(x) ) \\] <ul> <li>\u8865\u7801\u8f6c\u6362\u4e3a\u65e0\u7b26\u53f7\u6570</li> </ul> \\[ T2U_w(x)=\\begin{cases}x+2^w,&amp;x&lt;0\\\\x,&amp;x\\geqslant0\\end{cases} \\] <ul> <li>\u65e0\u7b26\u53f7\u6570\u8f6c\u6362\u4e3a\u8865\u7801</li> </ul> \\[ U2T_w(u)=\\begin{cases}u ,&amp;u\\leqslant TMax_w\\\\u-2^w ,&amp;u&gt;TMax_w\\end{cases} \\]"},{"location":"CS_Basic/15-213/CSAPP/#225-c","title":"2.2.5 C \u8bed\u8a00\u4e2d\u7684\u6709\u7b26\u53f7\u6570\u4e0e\u65e0\u7b26\u53f7\u6570","text":"<ul> <li>\u4e00\u4e2a\u8fd0\u7b97\u7b26\u662f\u6709\u7b26\u53f7\u7684\u800c\u53e6\u4e00\u4e2a\u662f\u65e0\u7b26\u53f7\u7684\uff0c\u90a3 C \u7a0b\u5e8f\u4f1a\u628a\u6709\u7b26\u53f7\u7684\u8f6c\u6362\u4e3a\u65e0\u7b26\u53f7\u7684\u3002 </li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#226","title":"2.2.6 \u6269\u5c55\u4e00\u4e2a\u6570\u5b57\u7684\u4f4d\u8868\u793a","text":"<ul> <li>\u65e0\u7b26\u53f7\u6570\u7684 zero extension</li> <li>\u8865\u7801\u6570\u7684\u7b26\u53f7\u6269\u5c55</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#227","title":"2.2.7 \u622a\u65ad\u6570\u5b57","text":""},{"location":"CS_Basic/15-213/CSAPP/#228","title":"2.2.8 \u5173\u4e8e\u6709\u7b26\u53f7\u6570\u4e0e\u65e0\u7b26\u53f7\u6570\u7684\u5efa\u8bae","text":""},{"location":"CS_Basic/15-213/CSAPP/#23","title":"2.3 \u6574\u6570\u8fd0\u7b97","text":""},{"location":"CS_Basic/15-213/CSAPP/#231","title":"2.3.1 \u65e0\u7b26\u53f7\u52a0\u6cd5","text":"<ul> <li>Lisp \u652f\u6301\u65e0\u9650\u7cbe\u5ea6\u7684\u8fd0\u7b97</li> </ul> \\[ x+_w^uy=\\begin{cases}x+y,&amp;x+y&lt;2^w&amp;\\text{\u6b63\u5e38}\\\\x+y-2^w,&amp;2^w\\leqslant x+y&lt;2^{w+1}&amp;\\text{\u6ea2\u51fa}\\end{cases} \\]"},{"location":"CS_Basic/15-213/CSAPP/#3","title":"3 \u7a0b\u5e8f\u7684\u673a\u5668\u7ea7\u8868\u793a","text":""},{"location":"CS_Basic/15-213/CSAPP/#4","title":"4 \u5904\u7406\u5668\u4f53\u7cfb\u7ed3\u6784","text":""},{"location":"CS_Basic/15-213/CSAPP/#5","title":"5 \u4f18\u5316\u7a0b\u5e8f\u6027\u80fd","text":""},{"location":"CS_Basic/15-213/CSAPP/#6","title":"6 \u5b58\u50a8\u5668\u5c42\u6b21\u7ed3\u6784","text":""},{"location":"CS_Basic/15-213/CSAPP/#7","title":"7 \u94fe\u63a5","text":""},{"location":"CS_Basic/15-213/CSAPP/#8","title":"8 \u5f02\u5e38\u63a7\u5236\u6d41","text":""},{"location":"CS_Basic/15-213/CSAPP/#9","title":"9 \u865a\u62df\u5185\u5b58","text":""},{"location":"CS_Basic/15-213/CSAPP/#10-io","title":"10 \u7cfb\u7edf\u7ea7 I/O","text":""},{"location":"CS_Basic/15-213/CSAPP/#11","title":"11 \u7f51\u7edc\u7f16\u7a0b","text":""},{"location":"CS_Basic/15-213/CSAPP/#12","title":"12 \u5e76\u53d1\u7f16\u7a0b","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/","title":"Accelerated C++","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#accelerated-c","title":"Accelerated C++","text":"<p> \u7ea6 2520 \u4e2a\u5b57  489 \u884c\u4ee3\u7801  2 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 19 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#0-c","title":"0 \u5f00\u59cb\u5b66\u4e60 C++","text":"C++<pre><code>#include &lt;iostream&gt;\n\nint main()\n{\n    std::cout &lt;&lt; \"Hello, World!\" &lt;&lt; std::endl;\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#01","title":"0.1 \u6ce8\u91ca","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#02-displaystyle-include","title":"0.2 \\(\\displaystyle \\#\\)include \u6307\u4ee4","text":"<ul> <li>\u8f93\u5165\u3001\u8f93\u51fa\u4e0d\u5c5e\u4e8e\u8bed\u8a00\u6838\u5fc3\uff0c\u800c\u662f\u6807\u51c6\u5e93\u7684\u4e00\u90e8\u5206</li> <li>iostream \u4ee3\u8868 C++\u5e93\u7684\u6807\u51c6\u5934\u6587\u4ef6</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#03-main","title":"0.3 \u4e3b\u51fd\u6570 main","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#04","title":"0.4 \u82b1\u62ec\u53f7","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#05","title":"0.5 \u4f7f\u7528\u6807\u51c6\u5e93\u8fdb\u884c\u8f93\u51fa","text":"<ul> <li>std:: cout \u6307\u6807\u51c6\u8f93\u51fa\u6d41</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#06","title":"0.6 \u8fd4\u56de\u8bed\u53e5","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#07","title":"0.7 \u4e00\u4e9b\u8f83\u4e3a\u6df1\u5165\u7684\u89c2\u5bdf","text":"<ul> <li>\u8868\u8fbe\u5f0f<ul> <li>\u8fd0\u7b97\u4f1a\u4ea7\u751f\u4e00\u4e2a\u7ed3\u679c\uff0c\u53ef\u80fd\u4f1a\u5177\u6709\u526f\u4f5c\u7528</li> </ul> </li> <li>\u6bcf\u4e2a\u64cd\u4f5c\u6570\u90fd\u5177\u6709\u4e00\u4e2a\u7c7b\u578b</li> <li>&lt;&lt;\u662f\u5de6\u7ed3\u5408\u7684\uff0c\u6240\u4ee5\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4e24\u4e2a&lt;&lt;\u8fd0\u7b97\u7b26\u548c\u4e09\u4e2a\u64cd\u4f5c\u6570</li> </ul> C++<pre><code>(std::cout &lt;&lt; \"Hello, World!\") &lt;&lt; std::endl\n</code></pre> <ul> <li>std:: cout \u7684\u7c7b\u578b\u662f std::ostream</li> <li>std:: endl \u662f\u4e00\u4e2a\u63a7\u5236\u5668\uff08manipulator\uff09</li> <li>\u7b2c\u4e00\u79cd\u4f5c\u7528\u57df: \u540d\u5b57\u7a7a\u95f4</li> <li>:: \u662f\u4f5c\u7528\u57df\u8fd0\u7b97\u7b26\uff0cstd:: cout \u662f\u4e00\u4e2a\u9650\u5b9a\u540d\u79f0</li> <li>\u82b1\u62ec\u53f7\u662f\u53e6\u4e00\u79cd\u4f5c\u7528\u57df</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#08","title":"0.8 \u5c0f\u7ed3","text":"<ul> <li>main \u53ef\u4ee5\u6ca1\u6709 return \u8bed\u53e5</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#1","title":"1 \u4f7f\u7528\u5b57\u7b26\u4e32","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#11","title":"1.1 \u8f93\u5165","text":"C++<pre><code>#include &lt;iostream&gt;\n#include &lt;string&gt;\n\nint main() \n{\n    std::cout &lt;&lt; \"Please enter your first name:\";\n\n    std::string name;\n    std::cin &gt;&gt; name;\n\n    std::cout &lt;&lt; \"Hello\" &lt;&lt; name &lt;&lt; \"!\" &lt;&lt; std::endl;\n    return 0;\n}\n</code></pre> <ul> <li>\u53d8\u91cf\u662f\u4e00\u4e2a\u5bf9\u8c61\uff0c\u4f46\u6709\u4e9b\u5bf9\u8c61\u53ef\u80fd\u6ca1\u6709\u540d\u79f0</li> <li>\u5c40\u90e8\u53d8\u91cf\u6709\u9650\u7684\u751f\u5b58\u671f\u662f\u533a\u5206\u53d8\u91cf\u548c\u5bf9\u8c61\u7684\u4e00\u4e2a\u91cd\u8981\u4f9d\u636e</li> <li>\u9690\u85cf\u5728\u5bf9\u8c61\u7c7b\u578b\u4e2d\u7684\u8fd8\u6709\u5176\u63a5\u53e3<ul> <li>\u63a5\u53e3\u662f\u53ef\u5b9e\u73b0\u64cd\u4f5c\u7684\u96c6\u5408</li> </ul> </li> <li>\u7f13\u51b2\u533a\u6765\u4fdd\u5b58\u8f93\u51fa</li> <li>\u4f55\u65f6\u5237\u65b0\u7f13\u51b2\u533a:<ul> <li>\u7f13\u51b2\u533a\u6ee1\u4e86</li> <li>\u8f93\u5165\u6d41\u8bfb\u6570\u636e</li> <li>\u660e\u786e\u8981\u6c42\u5237\u65b0</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#12","title":"1.2 \u4e3a\u59d3\u540d\u88c5\u6846","text":"<ul> <li>\u8fd0\u7b97\u7b26\u88ab\u91cd\u8f7d\u4e86</li> <li>\u8fd0\u7b97\u7b26\u4e00\u4e2a\u6c38\u8fdc\u4e0d\u4f1a\u6539\u53d8\u7684\u6027\u8d28\u662f\u7ed3\u5408\u5f8b\uff0c+\u662f\u5de6\u7ed3\u5408\u7684</li> </ul> C++<pre><code>std::string stars(10, '*')\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#13","title":"1.3 \u5c0f\u7ed3","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#2","title":"2 \u5faa\u73af\u548c\u8ba1\u6570","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#21","title":"2.1 \u95ee\u9898","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#22","title":"2.2 \u7a0b\u5e8f\u7684\u6574\u4f53\u7ed3\u6784","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#23","title":"2.3 \u8f93\u51fa\u6570\u76ee\u672a\u77e5\u7684\u884c","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#231-while","title":"2.3.1 while \u8bed\u53e5","text":"<ul> <li>++\u662f\u4e00\u4e2a\u589e\u91cf\u8fd0\u7b97\u7b26</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#232-while","title":"2.3.2 \u8bbe\u8ba1 while \u8bed\u53e5","text":"<ul> <li>\u5faa\u73af\u4e0d\u53d8\u5f0f\uff08Loop invariant\uff09<ul> <li>\u521d\u59cb\u5316\uff1a\u5728\u5faa\u73af\u5f00\u59cb\u4e4b\u524d\uff0c\u5faa\u73af\u4e0d\u53d8\u5f0f\u5e94\u8be5\u88ab\u786e\u7acb\u4e3a\u771f\u3002</li> <li>\u4fdd\u6301\uff1a\u5faa\u73af\u7684\u6bcf\u6b21\u8fed\u4ee3\u90fd\u5fc5\u987b\u4fdd\u6301\u5faa\u73af\u4e0d\u53d8\u5f0f\u4e3a\u771f\uff0c\u5373\u5982\u679c\u8fdb\u5165\u67d0\u6b21\u8fed\u4ee3\u65f6\u5faa\u73af\u4e0d\u53d8\u5f0f\u4e3a\u771f\uff0c\u90a3\u4e48\u5728\u8be5\u6b21\u8fed\u4ee3\u7ed3\u675f\u65f6\uff0c\u5faa\u73af\u4e0d\u53d8\u5f0f\u4ecd\u7136\u4e3a\u771f\u3002</li> <li>\u7ec8\u6b62\uff1a\u5f53\u5faa\u73af\u7ed3\u675f\u65f6\uff0c\u5faa\u73af\u4e0d\u53d8\u5f0f\u5e94\u8be5\u80fd\u591f\u7528\u6765\u8bc1\u660e\u5faa\u73af\u7684\u7ec8\u6b62\u6761\u4ef6\u6210\u7acb\uff0c\u6216\u8005\u7528\u6765\u8bc1\u660e\u5faa\u73af\u7684\u8f93\u51fa\u6216\u7ed3\u679c\u6ee1\u8db3\u7279\u5b9a\u7684\u5c5e\u6027\u3002</li> <li>\u5faa\u73af\u4e0d\u53d8\u5f0f\u7684\u4e00\u4e2a\u5178\u578b\u4f8b\u5b50\u662f\u5728\u6392\u5e8f\u7b97\u6cd5\u4e2d\uff0c\u4f8b\u5982\u5192\u6ce1\u6392\u5e8f\u3002\u5728\u5192\u6ce1\u6392\u5e8f\u4e2d\uff0c\u4e00\u4e2a\u53ef\u80fd\u7684\u5faa\u73af\u4e0d\u53d8\u5f0f\u662f\uff1a\u201c\u6bcf\u6b21\u5faa\u73af\u8fed\u4ee3\u540e\uff0c\u6570\u7ec4\u7684\u6700\u540en\u4e2a\u5143\u7d20\u662f\u6392\u5e8f\u597d\u7684\u201d\uff0c\u5176\u4e2dn\u662f\u5faa\u73af\u8fed\u4ee3\u7684\u6b21\u6570\u3002</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#24","title":"2.4 \u8f93\u51fa\u4e00\u884c","text":"C++<pre><code>const std::string::size_type cols = greeting.size() + pad * 2 + 2;\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#241","title":"2.4.1 \u8f93\u51fa\u8fb9\u754c\u5b57\u7b26","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#2411-if","title":"2.4.1.1 if \u8bed\u53e5","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#2412","title":"2.4.1.2 \u903b\u8f91\u8fd0\u7b97\u7b26","text":"<ul> <li>||\u662f\u5de6\u7ed3\u5408\uff0c\u4f1a\u6709\u77ed\u8def\u6c42\u503c\uff08short-circuit evaluation\uff09</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#242","title":"2.4.2 \u8f93\u51fa\u975e\u8fb9\u754c\u5b57\u7b26","text":"<ul> <li>+=\u590d\u5408\u8d4b\u503c\u8fd0\u7b97\u7b26</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#25","title":"2.5 \u5b8c\u6574\u7684\u6846\u67b6\u7a0b\u5e8f","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#251-std","title":"2.5.1 \u7565\u53bb\u91cd\u590d\u4f7f\u7528\u7684 std::","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#252-for","title":"2.5.2 \u4f7f\u7528 for \u8bed\u53e5\u6765\u7f29\u77ed\u7a0b\u5e8f","text":"<ul> <li>\u533a\u95f4\u7684\u8d8a\u754c\u503c\uff08off-the-end value\uff09</li> </ul> C++<pre><code>for (int r = 0; r != rows; ++r) {\n\n}\n</code></pre> <ul> <li>\u8fd9\u662f\u534a\u5f00\u533a\u95f4</li> </ul> C++<pre><code>for (init-statement condition; expression)\n    statement\n\n#equals to\n\n{\n    inti-statement\n    while (condition) {\n        statement\n        expression;\n    }\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#253","title":"2.5.3 \u538b\u7f29\u68c0\u6d4b","text":"<ul> <li>\u5c31\u662f\u628a if \u8bed\u53e5\u5408\u5e76\u4e00\u4e0b</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#254","title":"2.5.4 \u5b8c\u6574\u7684\u6846\u67b6\u7a0b\u5e8f","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#26","title":"2.6 \u8ba1\u6570","text":"<ul> <li>\u4e0d\u5bf9\u6210\u533a\u95f4\u53ef\u4ee5\u76f4\u63a5\u770b\u51fa\u6709\u591a\u5c11\u4e2a\u5143\u7d20<ul> <li>\\(\\displaystyle [m, n]\\) \u6709 m - n \u4e2a\u5143\u7d20</li> </ul> </li> <li>\u800c\u4e14\u53ef\u4ee5\u8868\u793a\u7a7a\u533a\u95f4 \\(\\displaystyle [n, n]\\) </li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#27","title":"2.7 \u5c0f\u7ed3","text":"<ul> <li>\u8868\u8fbe\u5f0f<ul> <li>\u64cd\u4f5c\u6570\u7684\u7ec4\u5408\u65b9\u5f0f</li> <li>\u64cd\u4f5c\u6570\u5982\u4f55\u88ab\u8f6c\u6362</li> <li>\u64cd\u4f5c\u6570\u7684\u8fd0\u7b97\u6b21\u5e8f</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#3","title":"3 \u4f7f\u7528\u6279\u91cf\u6570\u636e","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#31","title":"3.1 \u8ba1\u7b97\u5b66\u751f\u6210\u7ee9","text":"C++<pre><code>#include &lt;iomanip&gt;\n#include &lt;ios&gt;\n#include &lt;iostream&gt;\n#include &lt;string&gt;\n\nusing std::cin;\nusing std::cout;\nusing std::endl;\nusing std::precision;\n\nint main() {\n    cout &lt;&lt; \"Please enter your first name:\";\n    string name;\n    cin &gt;&gt; name;\n    cout &lt;&lt; \"Hello, \" &lt;&lt; name &lt;&lt; \"!\" &lt;&lt; endl;\n\n    cout &lt;&lt; \"Please enter your midterm and final exam grades:\";\n    double midterm, final;\n    cin &gt;&gt; midterm &gt;&gt; final;\n\n    cout &lt;&lt; \"Enter all your homework grades, \" \n            \"followed by end-of-file:\";\n\n    int count = 0;\n    double sum = 0;\n\n    double x;\n\n    while (cin &gt;&gt; x) {\n        ++ count;\n        sum += x;\n    }\n\n    streamsize prec = cout.precision();\n    cout &lt;&lt; \"Your final grade is \" &lt;&lt; setprecision(3)\n         &lt;&lt; 0.2 * midterm + 0.4 * final + 0.4 * sum / count\n         &lt;&lt; setprecision(prec) &lt;&lt; endl; //\u91cd\u7f6e\u6709\u6548\u4f4d\u6570 \u6216\u5199\u6210cout.precision(prec);\n    return 0;\n}\n</code></pre> <ul> <li>\u8f93\u5165\u8fd0\u7b97\u7b26\u8fd4\u56de\u5b83\u7684\u5de6\u64cd\u4f5c\u6570\u4f5c\u4e3a\u7ed3\u679c</li> <li>\u5374\u7701\u521d\u59cb\u5316</li> <li>setprecision \u4e5f\u662f\u4e00\u4e2a\u63a7\u5236\u5668: \u4e3a\u6d41\u7684\u540e\u7ee7\u8f93\u51fa\u8bbe\u7f6e\u4e86\u4e00\u4e2a\u7279\u5b9a\u7684\u6709\u6548\u4f4d\u6570</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#311","title":"3.1.1 \u68c0\u6d4b\u8f93\u51fa","text":"<ul> <li>istream \u53ef\u4ee5\u88ab\u8f6c\u6362\u6210 bool \u503c</li> <li>\u6709\u4e09\u79cd\u60c5\u51b5\u6761\u4ef6\u4f1a\u53d8\u5047:<ul> <li>\u8fbe\u5230\u8f93\u5165\u6587\u4ef6\u7684\u7ed3\u5c3e</li> <li>\u8f93\u5165\u548c\u6211\u4eec\u8bd5\u56fe\u8bfb\u53d6\u7684\u53d8\u91cf\u7c7b\u578b\u4e0d\u4e00\u81f4</li> <li>\u68c0\u6d4b\u5230\u4e00\u4e2a\u786c\u4ef6\u95ee\u9898</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#312","title":"3.1.2 \u5faa\u73af\u4e0d\u53d8\u5f0f","text":"<p>\u4e0d\u662f\u5f88\u61c2</p>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#32","title":"3.2 \u7528\u4e2d\u503c\u4ee3\u66ff\u5e73\u5747\u503c","text":"<p>\u90a3\u4e48\u5c31\u8981\u6392\u5e8f\u4e86</p>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#321","title":"3.2.1 \u628a\u6570\u636e\u96c6\u5408\u5b58\u50a8\u5728\u5411\u91cf\u4e2d","text":"C++<pre><code>double x;\nvector&lt;double&gt; homework;\n\nwhile(cin &gt;&gt; x)\n    homework.push_back(x);\n</code></pre> <ul> <li>\u6211\u4eec\u4f7f\u7528\u4e86\u4e00\u79cd\u540d\u4e3a\u6a21\u677f\u7c7b\u7684\u8bed\u8a00\u7279\u5f81</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#322","title":"3.2.2 \u4ea7\u751f\u8f93\u51fa","text":"C++<pre><code>typedef vector&lt;double&gt;::size_type vec_sz;\nvec_sz size = homework.size();\n</code></pre> <ul> <li>\u6211\u4eec\u5e0c\u671b\u4fdd\u6301\u7cfb\u7edf\u73af\u5883\u7684\u72ec\u7acb\u6027</li> </ul> C++<pre><code>if (size  == 0) {\n    cout &lt;&lt; endl &lt;&lt; \"You must enter your grades. \"\n                    \"Please try again.\" &lt;&lt; endl;\n    return 1;\n}\n\nsort (homework.begin(), homework.end());\n\nvec_sz mid = size / 2;\ndouble median;\nmedian = size % 2 == 0 ? (homework[mid] + homework[mid - 1]) / 2\n                       : homework[mid];\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#323","title":"3.2.3 \u4e00\u4e9b\u66f4\u4e3a\u6df1\u5165\u7684\u89c2\u5bdf","text":"<ul> <li>size_type \u662f\u65e0\u7b26\u53f7\u6574\u6570\u7c7b\u578b</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#33","title":"3.3 \u5c0f\u7ed3","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#4","title":"4 \u7ec4\u7ec7\u7a0b\u5e8f\u548c\u6570\u636e","text":"<ul> <li>\u8fd9\u4e9b\u5e93\u5de5\u5177\u6709\u51e0\u4e2a\u540c\u6837\u7684\u7279\u6027:<ul> <li>\u80fd\u89e3\u51b3\u67d0\u4e9b\u7279\u5b9a\u7c7b\u578b\u7684\u95ee\u9898</li> <li>\u4e0e\u5176\u4ed6\u7684\u5927\u591a\u6570\u5de5\u5177\u90fd\u76f8\u4e92\u72ec\u7acb</li> <li>\u90fd\u5177\u6709\u4e00\u4e2a\u540d\u79f0</li> </ul> </li> <li>\u4e24\u79cd\u65b9\u6cd5\u6765\u7ec4\u7ec7\u5927\u578b\u7684\u7a0b\u5e8f<ul> <li>\u51fd\u6570</li> <li>\u6570\u636e\u7ed3\u6784</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#41","title":"4.1 \u7ec4\u7ec7\u8ba1\u7b97","text":"<ul> <li>\u53c2\u6570\u7684\u521d\u59cb\u503c\u662f\u76f8\u5e94\u53c2\u6570\u503c\u7684\u590d\u5236\uff0c\u5373\u6309\u503c\u8c03\u7528\uff08call by value\uff09</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#411","title":"4.1.1 \u67e5\u627e\u4e2d\u503c","text":"C++<pre><code>double median(vector&lt;double&gt; vec)\n{\n    typedef vector&lt;double&gt;::size_type vec_sz;\n    vec_sz size = vec.size();\n    if (size == 0)\n        throw domain_error(\"median of an empty vector\");\n    sort(vec.begin(), vec.end());\n    vec_sz mid = size / 2;\n    return size % 2 == 0 ? (vec[mid] + vec[mid - 1]) / 2 : vec[mid];\n}\n</code></pre> <ul> <li>\u629b\u51fa\u5f02\u5e38</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#412","title":"4.1.2 \u91cd\u65b0\u5236\u5b9a\u8ba1\u7b97\u6210\u7ee9\u7684\u7b56\u7565","text":"<ul> <li>\u53ea\u80fd\u628a\u4e0d\u662f\u5e38\u91cf\u7684\u5f15\u7528\u7ed9\u5e38\u91cf\u7684\uff0c\u5373\u6761\u4ef6\u53ea\u80fd\u52a0\u5f3a</li> <li>\u6709\u597d\u51e0\u4e2a\u540c\u6837\u51fd\u6570\u540d\u7684\u51fd\u6570\u65f6\uff0c\u4f1a\u53d1\u751f\u91cd\u8f7d</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#413","title":"4.1.3 \u8bfb\u5bb6\u5ead\u4f5c\u4e1a\u6210\u7ee9","text":"<ul> <li>\u5de6\u503c\u53c2\u6570: \u975e\u4e34\u65f6\u5bf9\u8c61</li> </ul> C++<pre><code>istream read_hw(istream&amp; in, vector&lt;double&gt;&amp; hw)\n{\n    if (in) {\n        hw.clear();\n        double x;\n        while (in &gt;&gt; x) \n            hw.push_back(x);\n        in.clear();\n    }\n    return in;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#414","title":"4.1.4 \u4e09\u79cd\u51fd\u6570\u53c2\u6570","text":"<ul> <li>\u4e00\u822c\u800c\u8a00\uff0c\u6211\u4eec\u6ca1\u6709\u5fc5\u8981\u4e3a\u4e86 int \u6216 double \u8fd9\u6837\u89c1\u5230\u4f60\u7684\u5185\u90e8\u7c7b\u578b\u7684\u53c2\u6570\u800c\u53bb\u4f7f\u7528 const \u5f15\u7528</li> <li>\u5982\u679c\u4f20\u5165 read_hw () \u7684\u4e0d\u662f\u4e00\u4e2a\u5de6\u503c\uff0c\u90a3\u4e48\u6211\u4eec\u4f1a\u628a\u8f93\u5165\u5b58\u5230\u4e00\u4e2a\u6211\u4eec\u65e0\u59a8\u8bbf\u95ee\u7684\u5bf9\u8c61\u4e2d\uff08\u6539\u5bf9\u8c61\u4f1a\u5728 read_hw() \u8fd4\u56de\u65f6\u7acb\u5373\u6d88\u5931\uff09</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#415","title":"4.1.5 \u4f7f\u7528\u51fd\u6570\u6765\u8ba1\u7b97\u5b66\u751f\u7684\u6210\u7ee9","text":"<ul> <li>\u4e0d\u8981\u8ba9\u4e00\u6761\u8bed\u53e5\u4e2d\u7684\u526f\u4f5c\u7528\u4e2a\u6570\u8d85\u8fc7\u4e00\u4e2a</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#42","title":"4.2 \u7ec4\u7ec7\u6570\u636e","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#421","title":"4.2.1 \u628a\u4e00\u4e2a\u5b66\u751f\u7684\u6240\u6709\u6570\u636e\u653e\u7f6e\u5728\u4e00\u8d77","text":"C++<pre><code>struct Student_info {\n    string name;\n    double midterm, final;\n    vector&lt;double&gt; homework;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#422","title":"4.2.2 \u5904\u7406\u5b66\u751f\u8bb0\u5f55","text":"C++<pre><code>istream&amp; read(istream&amp; is, Student_info&amp; s)\n{\n    is &gt;&gt; s.name &gt;&gt; s.midterm &gt;&gt; s.final;\n    read_hw(is, s.homework);\n    return is;\n}\n\ndouble grade(const Student_info&amp; s) \n{\n    return grade(s.midterm, s.final, s.homework);\n}\n\nbool compare(const Student_info&amp; x, const Studeng_info&amp; y)\n{\n    return x.name &lt; y.name;\n}\n\nsort(students.begin(), students.end(), compare;\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#423","title":"4.2.3 \u751f\u6210\u62a5\u8868","text":"C++<pre><code>cout &lt;&lt; setw(maxlen + 1) &lt;&lt; student[i].name;\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#43","title":"4.3 \u628a\u5404\u90e8\u5206\u4ee3\u7801\u8fde\u63a5\u5230\u4e00\u8d77","text":"Text Only<pre><code>#ifndef GUARD_median_h\n#define GUARD_median_h //\u9884\u5904\u7406\u7a0b\u5e8f\n\n#include &lt;vector&gt;\ndouble median(vector&lt;double&gt;);\n\n#endif\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#44","title":"4.4 \u628a\u8ba1\u7b97\u6210\u7ee9\u7684\u7a0b\u5e8f\u5206\u5757","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#45","title":"4.5 \u4fee\u6b63\u540e\u7684\u8ba1\u7b97\u6210\u7ee9\u7684\u7a0b\u5e8f","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#46","title":"4.6 \u5c0f\u7ed3","text":"<ul> <li>\u7528\u6237\u5b9a\u4e49\u7684\u5934\u6587\u4ef6\u4e00\u822c\u4ee5 .h \u7ed3\u5c3e</li> <li>\u4e0d\u5e94\u8be5\u5728\u5934\u6587\u4ef6\u4e2d\u4f7f\u7528 using \u58f0\u660e</li> <li>\u7528 \\(\\displaystyle \\#\\) ifndef \u6307\u4ee4\u6765\u9632\u6b62\u5bf9\u5934\u6587\u4ef6\u7684\u91cd\u590d\u5305\u542b</li> <li>\u5185\u8054\u5b50\u8fc7\u7a0b\u901a\u5e38\u65f6\u5728\u5934\u6587\u4ef6\u800c\u4e0d\u662f\u5728\u6e90\u6587\u4ef6\u4e2d\u5b9a\u4e49 inline<ul> <li>\u4e3a\u4e86\u6bd4\u5356\u4f60\u51fd\u6570\u8c03\u7528\u7684\u989d\u5916\u5f00\u9500\uff0c\u7f16\u8bd1\u5668\u4f1a\u7528\u51fd\u6570\u4f53\u7684\u4e00\u4e2a\u590d\u5236\u6765\u66ff\u6362\u5bf9\u51fd\u6570\u7684\u6bcf\u4e00\u4e2a\u8c03\u7528\u5e76\u6839\u636e\u9700\u8981\u8fdb\u884c\u4fee\u6b63</li> </ul> </li> <li>\u5f02\u5e38\u5904\u7406</li> </ul> C++<pre><code>try{\n} catch (t) { }\n</code></pre> <ul> <li>\u5f02\u5e38\u7c7b</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#5","title":"5 \u4f7f\u7528\u987a\u5e8f\u5bb9\u5668\u5e76\u5206\u6790\u5b57\u7b26\u4e32","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#51","title":"5.1 \u6309\u7c7b\u522b\u6765\u533a\u5206\u5b66\u751f","text":"C++<pre><code>vector&lt;Student_info&gt; extract_fails(vector&lt;Student_info&gt;&amp; students)\n{\n    vector&lt;Student_info&gt; pass, fail;\n    for (vector&lt;Student_info&gt;::size_type i = 0; i != students.size(); ++i;)\n    if (fgrade(student[i]))\n        fail.push_back(student[i]);\n    else\n        pass.push_back(student[i]);\n    students = pass;\n    return fail;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#511","title":"5.1.1 \u5c31\u5730\u5220\u9664\u51fd\u6570","text":"C++<pre><code>vector&lt;Student_info&gt; extract_fails(vector&lt;Student_info&gt;&amp; students)\n{\n    vector&lt;Student_info&gt; fail;\n    vector&lt;Student_info&gt;::size_type i =  0;\n    while (i != students.size()) {\n        if (fgrade(studentp[i])) {\n            fail.push_back(students[i]);\n            students.erase(students.begin() + i);\n        } else\n            ++i;\n    }\n    return fail;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#512","title":"5.1.2 \u987a\u5e8f\u5b58\u53d6\u4e0e\u968f\u673a\u5b58\u53d6","text":"<ul> <li>\u8bbf\u95ee\u5bb9\u5668\u65f6\u6240\u91c7\u53d6\u7684\u6b21\u5e8f\u4f1a\u5bfc\u81f4\u4e0d\u540c\u7684\u6027\u80fd\u7279\u6027</li> <li>\u4e8e\u662f\u4fbf\u6709\u4e86 iterator</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#52","title":"5.2 \u8fed\u4ee3\u5668","text":"<ul> <li>iterator<ul> <li>\u8bc6\u522b\u4e00\u4e2a\u5bb9\u5668\u4ee5\u53ca\u5bb9\u5668\u4e2d\u7684\u4e00\u4e2a\u5143\u7d20</li> <li>\u8ba9\u6211\u4eec\u68c0\u67e5\u5b58\u50a8\u5728\u8fd9\u4e2a\u5143\u7d20\u4e2d\u7684\u503c</li> <li>\u63d0\u4f9b\u64cd\u4f5c\u6765\u79fb\u52a8\u5728\u5bb9\u6613\u4e2d\u7684\u5143\u7d20</li> <li>\u91c7\u7528\u5bf9\u5e94\u4e8e\u5bb9\u5668\u6240\u80fd\u591f\u6709\u6548\u5904\u7406\u7684\u65b9\u5f0f\u5bf9\u53ef\u7528\u7684\u64cd\u4f5c\u8fdb\u884c\u7ea6\u675f</li> </ul> </li> </ul> C++<pre><code>for (vector&lt;Student_info&gt;::size_type i = 0; i != students.end(); ++i)\n    cout &lt;&lt; students[i].name &lt;&lt; endl;\nfor (vector&lt;Student_info&gt;::const_iterator iter = students.begin();\n    iter != students.end(); ++iter) {\n    cout &lt;&lt; (*iter).name &lt;&lt; endl; }\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#521","title":"5.2.1 \u8fed\u4ee3\u5668\u7c7b\u578b","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#522","title":"5.2.2 \u8fed\u4ee3\u5668\u64cd\u4f5c","text":"<ul> <li>end \u7d27\u63a5\u5728\u5bb9\u5668\u6700\u540e\u4e00\u4e2a\u5143\u7d20\u540e\u9762\u7684\u4f4d\u7f6e</li> <li>++iter \u7528\u4e86\u8fed\u4ee3\u5668\u7c7b\u578b\u91cd\u8f7d</li> <li>\u5f53\u6211\u4eec\u7528\u95f4\u63a5\u5f15\u7528\u8fd0\u7b97\u7b26 \\(\\displaystyle *\\) \u6765\u8bbf\u95ee\u8fd9\u4e2a\u5143\u7d20\uff0c\u90a3\u4e48\u4ed6\u4f1a\u8fd4\u56de\u4e00\u4e2a\u5de6\u503c\uff08\u8fed\u4ee3\u5668\u6240\u6307\u5411\u7684\u5143\u7d20\uff09</li> <li>\\(\\displaystyle .\\) \u7684\u4f18\u5148\u7ea7\u6bd4 \\(\\displaystyle *\\) \u9ad8</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#523","title":"5.2.3 \u4e00\u70b9\u8bed\u6cd5\u77e5\u8bc6","text":"C++<pre><code>(*iter).name\niter-&gt;name\n//both are ok\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#524-students-erase-students-begin-i","title":"5.2.4 students. erase (students. begin () + i) \u7684\u542b\u4e49","text":"<ul> <li>students \u4e0d\u652f\u6301\u968f\u673a\u8bbf\u95ee\u7d22\u5f15\u64cd\u4f5c\u7684\u5bb9\u5668\uff0c\u4f46\u662f\u4ecd\u4f1a\u5141\u8bb8\u8fed\u4ee3\u5668\u7684\u968f\u673a\u8bbf\u95ee</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#53","title":"5.3 \u7528\u8fed\u4ee3\u5668\u6765\u4ee3\u66ff\u7d22\u5f15","text":"C++<pre><code>vecotr&lt;Student_info&gt; extract_fails(vector&lt;Student_info&gt;&amp; students)\n{\n    vector&lt;Student_info&gt; fail;\n    vector&lt;Student_info&gt;::iterator iter = students.begin();\n    while (iter != students.end()) {\n        if (fgrade(*iter)) {\n            fail.push_back(*iter);\n            iter = students.erase(iter); //important\n        } else\n            ++iter;\n    }\n    return fail;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#54","title":"5.4 \u91cd\u65b0\u601d\u8003\u6570\u636e\u7ed3\u6784\u4ee5\u5b9e\u73b0\u66f4\u597d\u7684\u6027\u80fd","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#55-list","title":"5.5 list \u7c7b\u578b","text":"<ul> <li>\u76f4\u63a5\u628a\u6240\u6709\u7684 vector \u6362\u6210 list \u5c31\u53ef\u4ee5\u4e86</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#551","title":"5.5.1 \u4e00\u4e9b\u91cd\u8981\u7684\u5dee\u522b","text":"<ul> <li>list \u7c7b\u7684\u8fed\u4ee3\u5668\u5e76\u4e0d\u652f\u6301\u5b8c\u5168\u968f\u673a\u7684\u8bbf\u95ee<ul> <li>\u6240\u4ee5\u6211\u4eec\u4e0d\u80fd\u7528 sort \u51fd\u6570</li> <li>\u4f46\u662f list \u6709\u81ea\u5df1\u6210\u5458\u51fd\u6570</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#552","title":"5.5.2 \u4e00\u4e2a\u607c\u4eba\u7684\u8bdd\u9898","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#56","title":"5.6 \u5206\u5272\u5b57\u7b26\u4e32","text":"C++<pre><code>vector&lt;string&gt; split(const string&amp; s)\n{\n    vector&lt;string&gt; ret;\n    typedef string::size_def string_size;\n    string_size i = 0;\n    while (i != s.size()) {\n        while (i != s.size() &amp;&amp; isspace(s[i])) // is from &lt;cctype&gt;\n            ++i;\n        string_size j = i;\n        while (j != s.size() &amp;&amp; !isspace(s[i]))\n            ++j;\n        if (i != j) {\n            ret.push_back(s.substr(i, j - i));\n            i = j;\n        }\n    }\n    return ret;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#57-split","title":"5.7 \u6d4b\u8bd5 split \u51fd\u6570","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#58","title":"5.8 \u8fde\u63a5\u5b57\u7b26\u4e32","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#581","title":"5.8.1 \u4e3a\u56fe\u6848\u88c5\u6846","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#582","title":"5.8.2 \u7eb5\u5411\u8fde\u63a5","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#583","title":"5.8.3 \u6a2a\u5411\u8fde\u63a5","text":"<p>TODO</p>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#59","title":"5.9 \u5c0f\u7ed3","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#6","title":"6 \u4f7f\u7528\u5e93\u7b97\u6cd5","text":"<ul> <li>\u5229\u7528\u516c\u7528\u63a5\u53e3\u6765\u63d0\u4f9b\u4e00\u4e2a\u6807\u51c6\u7b97\u6cd5\u96c6\u5408</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#61","title":"6.1 \u5206\u6790\u5b57\u7b26\u4e32","text":"C++<pre><code>for (vector&lt;string&gt;::const_iterator it = bottom.begin(); it != bottom.end(); ++i)\n    ret.push_back(*it);\n\nret.insert(ret.end(), bottom.begin(), bottom.end());\n\ncopy(bottom.begin(), bottom.end(), back_inserter(ret));\n</code></pre> <ul> <li>copy \u662f\u4e00\u4e2a\u6cdb\u578b (generic) \u7b97\u6cd5\u7684\u4f8b\u5b50</li> <li>back_inserter \u662f\u4e00\u4e2a\u8fed\u4ee3\u5668\u9002\u914d\u5668\u7684\u4f8b\u5b50</li> </ul> C++<pre><code>copy(begin, end, out);\n//equals to\nwhile (begin != end)\n    *out++ = *begin++;\n    // equals to \n    // *out = *begin; ++out; ++begin;\n\nit = begin++;\n//equals to\nit = begin;\n++begin;\n</code></pre> <ul> <li>\u8fed\u4ee3\u5668\u9002\u914d\u5668\u662f\u4e00\u4e2a\u4ea7\u751f\u8fed\u4ee3\u5668\u7684\u4e1c\u897f</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#611-split","title":"6.1.1 \u53e6\u4e00\u4e2a\u5b9e\u73b0 split \u7684\u65b9\u6cd5","text":"C++<pre><code>bool space(char c) {\n    return isspace(c);\n}\nbool not_space(char c) {\n    return !isspace(c);\n}\nvector&lt;string&gt; split(const string&amp; str) {\n    typedef string::const_iterator iter;\n    vector&lt;string&gt; ret;\n    iter i = str.begin();\n    while(i != str.end()) {\n        i = find_if(i, str.end(), not_space);\n        iter j = find_if(i, str.end(), space);\n        if (i != str.end()) ret.push_back(string(i, j));\n        i = j;  \n    }\n    return ret;\n}\n</code></pre> <ul> <li>\u6211\u4eec\u9700\u8981\u7f16\u5199\u6211\u4eec space \u548c not_space \u662f\u7528\u6765\u89e3\u91ca\u6211\u4eec\u6240\u6307\u7684\u662f\u54ea\u4e2a\u7248\u672c\u7684 isspace</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#612","title":"6.1.2 \u56de\u6587","text":"C++<pre><code>bool is_palindrome(const string&amp; s) {\n    return equal(s.begin(), s.end(), s.rbegin());\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#613-url","title":"6.1.3 \u67e5\u627e URL","text":"<ul> <li>protocol://resource-name</li> </ul> C++<pre><code>vector&lt;string&gt; find_urls(const string&amp; s) {\n    vector&lt;string&gt; ret;\n    typedef string::const_iterator iter;\n    iter b = s.begin(), e = s.end();\n    while (b != e) {\n        b = url_beg(b, e);\n        if (b != e) {\n            iter after = url_end(b, e);\n            ret.push_back(string(b, after));\n            b = after;\n        }\n    }\n    return ret;\n}\n\nstring::const_iterator url_end(string::const_iterator b, string::const_iterator e) {\n    return find_if(b, e, not_url_char);\n}\n\nbool not_url_char(char c) {\n    static const string url_ch = \"~;/?@=&amp;$-_.+!*{},'\";\n    return !(isalnum(c)) || find(url_ch.begin(), url_ch.end(), c) != url_end());\n    //static\u58f0\u660e\u7684\u5c40\u90e8\u53d8\u91cf\u5177\u6709\u5168\u5c40\u5bff\u547d\uff0c\u751f\u5b58\u671f\u8d2f\u7a7f\u6574\u4e2a\u51fd\u6570\u8c03\u7528\u8fc7\u7a0b\n}\n\nstring::const_iterator url_beg(string::const_iterator b, string::const_iterator e) {\n    static const string sep = \"://\";\n    typedef string::const_iterator iter;\n    iter i = b;\n    while ((i = search(i, e, sep.begin(), sep.end())) != e) {\n        if (i != b &amp;&amp; i + sep.size() != e) {\n            iter beg = i;\n            while (beg != b &amp;&amp; isalpha(beg[-1]))\n                --beg;\n            if (beg != i &amp;&amp; i + sep.size() != e &amp;&amp; !not_url_char(i[sep.size()])) return beg;\n        }\n        if (i != e) i += sep.size();\n    }\n    return e;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#62","title":"6.2 \u5bf9\u8ba1\u7b97\u6210\u7ee9\u7684\u65b9\u6848\u8fdb\u884c\u6bd4\u8f83","text":"<ol> <li>\u8bfb\u6240\u6709\u7684\u5b66\u751f\u8bb0\u5f55\uff0c\u628a\u505a\u4e86\u5168\u90e8\u5bb6\u5ead\u4f5c\u4e1a\u7684\u5b66\u751f\u4e0e\u5176\u4ed6\u7684\u5b66\u751f\u5206\u9694\u5f00\u3002</li> <li>\u5bf9\u6bcf\u4e00\u7ec4\u4e2d\u7684\u6240\u6709\u5b66\u751f\u5206\u522b\u4f7f\u7528\u6bcf\u4e00\u4e2a\u7684\u8ba1\u7b97\u6210\u7ee9\u7684\u65b9\u6848\uff0c\u62a5\u544a\u6bcf\u4e00\u7ec4\u7684\u4e2d\u503c\u6210\u7ee9\u3002</li> </ol>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#621","title":"6.2.1 \u5904\u7406\u5b66\u751f\u8bb0\u5f55","text":"C++<pre><code>bool did_all_hw(const Student_info&amp; s) {\n    reutrn ((fint(s.homework.begin(), s.homework.end(), 0)) == s.homework.end());\n}\n\nvector&lt;Student_info&gt; did, didnt;\nStudent_info student;\n\nwhile (read(cin, student)) {\n    if (did_all_hw(student))\n        did.push_back(student);\n    else\n        didnt.push_back(student);\n}\nif (did.empty()) {\n    cout &lt;&lt; \"No student did all the homework!\" &lt;&lt; endl;\n    return 1;\n}\nif (didnt.empty()) {\n    cout &lt;&lt; \"Every student did all the homework!\" &lt;&lt; endl;\n    return 1;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#622","title":"6.2.2 \u5206\u6790\u6210\u7ee9","text":"C++<pre><code>write_analysis(cout, \"median\", median_analysis, did, didn't);\n\ndouble grade_aux(const Student_info&amp; s) {\n    tru {\n        return grade(s);\n    } catch (domain_error) {\n        return grade(s.midterm, s.final, 0);\n    }\n}\n\ndouble median_analysis(const vector&lt;Student_info&gt;&amp; students) {\n    vector&lt;double&gt; grades;\n    transdorm(students.begin(), students.end(), back_inserter(grades), grade_aux);\n    return medina(grades);\n}\n\nvoid write_analysis(ostream&amp; out, const string&amp; name, double analysis(const vector&lt;Student_info&gt;&amp;), const vector&lt;Student_info&gt;&amp; did, const vector&lt;Student_info&gt;&amp; didnt) {\n    out &lt;&lt; name &lt;&lt; \": median(did) = \" &lt;&lt; analysis(did) &lt;&lt; \", median(didnt) = \" &lt;&lt; analysis(didnt) &lt;&lt; endl; \n}\n\nint main() {\n    vector&lt;Student_info&gt; did, didnt;\n    Student_info student;\n    while (read(cin, student)) {\n        if (did_all_hw(student))\n            did.push_back(student);\n        else \n            didnt.push_back(student);\n    }\n    if (did.empty()) {\n        cout &lt;&lt; \"No student did all the homework!\" &lt;&lt; endl;\n        return 1;\n    }\n    if (didnt.empty()) {\n        cout &lt;&lt; \"Every student did all the homework!\" &lt;&lt; endl;\n        return 1;\n    }\n    write_analysis(cout, \"median\", median_analysis, did, didnt);\n    write_analysis(cout, \"average\", average_analysis, did, didnt);\n    write_analysis(cout, \"medina of homework turned in\", optimistic_median_analysis, did, didnt);\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#623","title":"6.2.3 \u8ba1\u7b97\u57fa\u4e8e\u5bb6\u5ead\u4f5c\u4e1a\u5e73\u5747\u6210\u7ee9\u7684\u603b\u6210\u7ee9","text":"C++<pre><code>double average(const vector&lt;double&gt;&amp; v) {\n    return accumulate(v.begin(), v.end(), 0.0) / v.size();\n}\n\ndouble average_analysis(const Student_info&amp; s) {\n    return grade(s.midterm, s.final, average(s.homework));\n}\n\ndouble average_analysis(const vector&lt;Student_info&gt;&amp; students) {\n    vector&lt;double&gt; grades;\n    transform(students.begin(), students.end(), back_inserter(grades), average_grade);\n    return median(grades);\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#624","title":"6.2.4 \u4e0a\u4ea4\u7684\u5bb6\u5ead\u4f5c\u4e1a\u7684\u4e2d\u503c","text":"C++<pre><code>double optimistic_median(const Student_info&amp; s) {\n    vector&lt;double&gt; nonzero;\n    remove_copy(s.homework.begin(), s.homework.end(), back_inserter(nonzero), 0);\n    if (nonzero.empty())\n        return grade(s.midterm, s.final, 0);\n    else \n        return grade(s.midterm, s.final, median(nonzero));\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#63","title":"6.3 \u5bf9\u5b66\u751f\u8fdb\u884c\u5206\u7c7b\u5e76\u56de\u987e\u4e00\u4e0b\u6211\u4eec\u7684\u95ee\u9898","text":"<ul> <li>\u4f7f\u7528\u4e00\u4e9b\u7b97\u6cd5\u5e93\u6765\u89e3\u51b3\u95ee\u9898</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#631","title":"6.3.1 \u4e00\u79cd\u4e24\u6b21\u4f20\u9012\u7684\u89e3\u51b3\u65b9\u6848","text":"C++<pre><code>vector&lt;Student_info&gt; extract_fails(vector&lt;Student_info&gt;&amp; students) {\n    vector&lt;Student_info&gt; fail;\n    remove_copy_if(students.begin(), students.end(), back_inserter(fail), pgrade);\n    students.earse(remove_if(students.begin(), students.end(), fgrade), student.end());\n    return fail;\n}\n\nbool pgrade(const Student_info&amp; s) {\n    return !fgrade(s);\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#64","title":"6.4 \u4e00\u79cd\u4e00\u6b21\u4f20\u9012\u7684\u89e3\u51b3\u65b9\u6848","text":"C++<pre><code>vector&lt;Student_info&gt; extract_fails(vector&lt;Student_info&gt;&amp; students) {\n    vector&lt;Student_info&gt;::iterator iter = stable_partition(students.begin(), students.end(), pgrade);\n    vector&lt;Student_info&gt; fail(iter, students.end());\n    students.erase(iter, students.end());\n    return fail;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#65","title":"6.5 \u7b97\u6cd5\u3001\u5bb9\u5668\u4ee5\u53ca\u8fed\u4ee3\u5668","text":"<ul> <li>\u7b97\u6cd5\u4f5c\u7528\u4e8e\u5bb9\u5668\u7684\u5143\u7d20\uff0c\u800c\u4e0d\u662f\u4f5c\u7528\u4e8e\u5bb9\u5668</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#7","title":"7 \u4f7f\u7528\u5173\u8054\u5bb9\u5668","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#71","title":"7.1 \u652f\u6301\u9ad8\u6548\u67e5\u627e\u7684\u5bb9\u5668","text":"<ul> <li>\u5173\u8054\u5bb9\u5668\u4f1a\u5bf9\u63d2\u5165\u7684\u5143\u7d20\u8fdb\u884c\u6392\u5e8f\u6765\u63d0\u9ad8\u67e5\u627e\u7684\u901f\u5ea6</li> <li>\u5173\u8054\u6570\u7ec4\u5c31\u662f\u6709 key-value \u7684\u6570\u7ec4<ul> <li>map: \u6620\u5c04\u8868\u7684\u7d22\u5f15\u4e0d\u4e00\u5b9a\u662f\u6574\u6570</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#72","title":"7.2 \u8ba1\u7b97\u5355\u8bcd\u6570","text":"C++<pre><code>int main() {\n    string s;\n    map&lt;string, int&gt; counters;\n    while (cin &gt;&gt; s) ++counters[s];\n    for (map&lt;string, int&gt;::const_iterator it = counters.begin(); it != couners.end(); ++it) {\n        cout &lt;&lt; it-&gt;first &lt;&lt; \"\\t\" &lt;&lt; it-&gt;second &lt;&lt; endl;\n    }\n    return 0;\n}\n</code></pre> <ul> <li>\u6570\u5bf9\uff08pair\uff09</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#73","title":"7.3 \u4ea7\u751f\u4e00\u4e2a\u4ea4\u53c9\u5f15\u7528\u8868","text":"C++<pre><code>map&lt;string, vector&lt;int&gt; &gt; xref(istream&amp; in, vector&lt;string&gt; find_words(const string&amp;) = split) {\n    string line;\n    int line_number = 0'\n    map&lt;string, vector&lt;int&gt;&gt; ret;\n    while (getline(in, line)) {\n        ++line_number;\n        vector&lt;string&gt; words = find_words(line);\n        for (vector&lt;string&gt;::const_iterator it = words.begin(); it != words.end(); ++it)\n            ret(*it).push_back(line_number);\n    }\n    return ret;\n}\n\n\nint main() {\n    map&lt;string, vector&lt;int&gt; &gt; ret = cref(cin);\n    for (map&lt;string, vector&lt;int&gt; &gt;::const_iterator it = ret.begin(); it != ret.end(); ++it) {\n        cout &lt;&lt; it-&gt;first &lt;&lt; \" occurs on line(s): \";\n        vector&lt;int&gt;::const_iterator line_it = it-&gt;second.begin();\n        cout &lt;&lt; *lint_it;\n        ++line_it;\n        while (line_it != it-&gt;second.end()) {\n            cout &lt;&lt; \", \" &lt;&lt; *line_it;\n            ++line_it;\n        }\n        cout &lt;&lt; endl;\n    }\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#74","title":"7.4 \u751f\u6210\u53e5\u5b50","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#741","title":"7.4.1 \u8868\u793a\u89c4\u5219","text":"C++<pre><code>typedef vector&lt;string&gt; Rule;\ntypedef vector&lt;Rule&gt; Rule_collection;\ntypedef map&lt;string, Rule_collection&gt; Grammer;\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#742","title":"7.4.2 \u8bfb\u5165\u6587\u6cd5","text":"C++<pre><code>Grammer read_grammer(istream&amp; in) {\n    Grammer ret;\n    string line;\n    while (getline(in, line)) {\n        vector&lt;string&gt; entry = split(line);\n        if (!entry.empty())\n            ret[entry[0]].push_back(Rule(entry.begin() + 1, entry.end()));\n    }\n    return ret;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#743","title":"7.4.3 \u751f\u6210\u53e5\u5b50","text":"C++<pre><code>vector&lt;string&gt; gen_sentence(const Grammar&amp; g) {\n    vector&lt;string&gt; ret;\n    gen_aux(g, \"&lt;sentence&gt;\", ret);\n    return ret;\n}\n\nbool bracketed(const string&amp; s) {\n    return s.size() &gt; 1 &amp;&amp; s[0] == '&lt;' &amp;&amp; s[s.size() - 1] == '&gt;';\n}\n\nvoid gen_aux(const Grammar&amp; g, const string&amp; word, vector&lt;string&gt;&amp; ret) {\n    if (!bracketed(word)) {\n        ret.push_back(word);\n    } else {\n        Grammar::const_iterator it = g.find(word);\n        if (it == g.end())\n            throw logic_error(\"empty rule\");\n        const Rule_collection&amp; c = it-&gt;seond;\n        const Rule&amp; r = c[nrand(c.size())];\n        for (Rule::const_iterator i = r.begin(); i != r.end(); ++i)\n            gen_aux(g, *i, ret);\n    }\n}\n\nint main() {\n    vector&lt;string&gt; sentence = gen_sentence(read_grammar(cin));\n    vector&lt;string&gt;::const_iterator it = sentence.begin();\n    if (!sentence.empty()) {\n        cout &lt;&lt; *it;\n        ++it;   \n    }\n    while (it != sentence.end()) {\n        cout &lt;&lt; \" \" &lt;&lt; *it;\n        ++it;\n    }\n    cout &lt;&lt; endl;\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#744","title":"7.4.4 \u9009\u62e9\u4e00\u4e2a\u968f\u673a\u51fd\u6570","text":"C++<pre><code>int nrand(int n) {\n    if (n &lt;= 0 || n &gt; RAND_MAX)\n        throw domain_error(\"Argument to nrand is out of range\");\n    const int bucket_size = RAND_MAX / n;\n    int r;\n    do r = rand() / bucket_size;\n    while (r &gt;= n);\n    return r;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#75","title":"7.5 \u5173\u4e8e\u6027\u80fd\u7684\u4e00\u70b9\u8bf4\u660e","text":"<ul> <li>\u7528\u6563\u5217\u8868\u5b9e\u73b0\u5173\u8054\u6570\u7ec4\u5728 C++\u4e2d\u7684\u662f\u5f88\u56f0\u96be\u7684 \u6ca1\u641e\u61c2 </li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#76","title":"7.6 \u5c0f\u7ed3","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#8","title":"8 \u7f16\u5199\u6cdb\u578b\u51fd\u6570","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#81","title":"8.1 \u6cdb\u578b\u51fd\u6570\u662f\u4ec0\u4e48","text":"<ul> <li>\u5728\u4f7f\u7528\u51fd\u6570\u4e4b\u524d\u4e0d\u77e5\u9053\u53c2\u6570\u6216\u8005\u8fd4\u56de\u7c7b\u578b\u662f\u4ec0\u4e48</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#811","title":"8.1.1 \u672a\u77e5\u7c7b\u578b\u7684\u4e2d\u503c","text":"<ul> <li>\u5b9e\u73b0\u4e86\u6cdb\u578b\u51fd\u6570\u7684\u8bed\u8a00\u7279\u5f81\u88ab\u79f0\u4f5c\u6a21\u677f\u51fd\u6570</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#9","title":"9 \u5b9a\u4e49\u65b0\u7c7b\u578b","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#10","title":"10 \u7ba1\u7406\u5185\u5b58\u548c\u4f4e\u7ea7\u6570\u636e\u7ed3\u6784","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#11_1","title":"11 \u5b9a\u4e49\u62bd\u8c61\u6570\u636e\u7c7b\u578b","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#12_1","title":"12 \u4f7f\u7c7b\u5bf9\u8c61\u50cf\u4e00\u4e2a\u6570\u503c\u4e00\u6837\u5de5\u4f5c","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#13_1","title":"13 \u4f7f\u7528\u7ee7\u627f\u4e0e\u52a8\u6001\u7ed1\u5b9a","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#14","title":"14 \u8fd1\u4e4e\u81ea\u52a8\u5730\u7ba1\u7406\u5185\u5b58","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#15","title":"15 \u518d\u8c08\u5b57\u7b26\u56fe\u5f62","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#16-c","title":"16 \u4eca\u540e\u5982\u4f55\u5b66\u4e60 C++","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/","title":"C++","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#c","title":"C++","text":"<p> \u7ea6 3115 \u4e2a\u5b57  523 \u884c\u4ee3\u7801  9 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 22 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#1","title":"1 \u6587\u4ef6\u64cd\u4f5c","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#11","title":"1.1 \u6587\u4ef6\u7684\u6982\u5ff5","text":"<ul> <li>C/C++\u628a\u6bcf\u4e00\u4e2a\u6587\u4ef6\u90fd\u770b\u6210\u662f\u4e00\u4e2a\u6709\u5e8f\u7684\u5b57\u8282\u6d41\uff0c\u4ee5\u6587\u4ef6\u7ed3\u675f\u6807\u5fd7\uff08EOF\uff09\u7ed3\u675f</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#12","title":"1.2 \u6587\u4ef6\u7684\u64cd\u4f5c\u6b65\u9aa4","text":"<ol> <li>\u6253\u5f00\u6587\u4ef6\uff0c\u8bb2\u6587\u4ef6\u6307\u9488\u6307\u5411\u6587\u4ef6\uff0c\u51b3\u5b9a\u6253\u5f00\u6587\u4ef6\u7684\u7c7b\u578b</li> <li>\u5bf9\u6587\u4ef6\u8fdb\u884c\u8bfb/\u5199\u64cd\u4f5c</li> <li>\u5728\u4f7f\u7528\u5b8c\u6587\u4ef6\u540e\uff0c\u5173\u95ed\u6587\u4ef6</li> </ol>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#13","title":"1.3 \u4e00\u4e9b\u51fd\u6570","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#131-freopen","title":"1.3.1 freopen \u51fd\u6570","text":"C++<pre><code>FILE* freopen(const char* filename, const char* mode, FILE* stream);\n</code></pre> <ul> <li>\u53c2\u6570\u8bf4\u660e<ul> <li><code>filename</code>: \u8981\u6253\u5f00\u7684\u6587\u4ef6\u540d</li> <li><code>mode</code>: \u6587\u4ef6\u6253\u5f00\u7684\u6a21\u5f0f\uff0c\u8868\u793a\u6587\u4ef6\u8bbf\u95ee\u7684\u6743\u9650</li> <li><code>stream</code>: \u6587\u4ef6\u6307\u9488\uff0c\u901a\u5e38\u4f7f\u7528\u6807\u51c6\u6587\u4ef6\u6d41 (<code>stdin/stdout</code>) \u6216\u6807\u51c6\u9519\u8bef\u8f93\u51fa\u6d41 (<code>stderr</code>)</li> <li>\u8fd4\u56de\u503c\uff1a\u6587\u4ef6\u6307\u9488\uff0c\u6307\u5411\u88ab\u6253\u5f00\u6587\u4ef6</li> </ul> </li> <li>\u6587\u4ef6\u6253\u5f00\u683c\u5f0f<ul> <li><code>r</code>\uff1a\u4ee5\u53ea\u8bfb\u65b9\u5f0f\u6253\u5f00\u6587\u4ef6\uff0c\u6587\u4ef6\u5fc5\u987b\u5b58\u5728\uff0c\u53ea\u5141\u8bb8\u8bfb\u5165\u6570\u636e\u00a0\uff08\u5e38\u7528\uff09</li> <li><code>r+</code>\uff1a\u4ee5\u8bfb/\u5199\u65b9\u5f0f\u6253\u5f00\u6587\u4ef6\uff0c\u6587\u4ef6\u5fc5\u987b\u5b58\u5728\uff0c\u5141\u8bb8\u8bfb/\u5199\u6570\u636e</li> <li><code>rb</code>\uff1a\u4ee5\u53ea\u8bfb\u65b9\u5f0f\u6253\u5f00\u4e8c\u8fdb\u5236\u6587\u4ef6\uff0c\u6587\u4ef6\u5fc5\u987b\u5b58\u5728\uff0c\u53ea\u5141\u8bb8\u8bfb\u5165\u6570\u636e</li> <li><code>rb+</code>\uff1a\u4ee5\u8bfb/\u5199\u65b9\u5f0f\u6253\u5f00\u4e8c\u8fdb\u5236\u6587\u4ef6\uff0c\u6587\u4ef6\u5fc5\u987b\u5b58\u5728\uff0c\u5141\u8bb8\u8bfb/\u5199\u6570\u636e</li> <li><code>rt+</code>\uff1a\u4ee5\u8bfb/\u5199\u65b9\u5f0f\u6253\u5f00\u6587\u672c\u6587\u4ef6\uff0c\u5141\u8bb8\u8bfb/\u5199\u6570\u636e</li> <li><code>w</code>\uff1a\u4ee5\u53ea\u5199\u65b9\u5f0f\u6253\u5f00\u6587\u4ef6\uff0c\u6587\u4ef6\u4e0d\u5b58\u5728\u4f1a\u65b0\u5efa\u6587\u4ef6\uff0c\u5426\u5219\u6e05\u7a7a\u5185\u5bb9\uff0c\u53ea\u5141\u8bb8\u5199\u5165\u6570\u636e\u00a0\uff08\u5e38\u7528\uff09</li> <li><code>w+</code>\uff1a\u4ee5\u8bfb/\u5199\u65b9\u5f0f\u6253\u5f00\u6587\u4ef6\uff0c\u6587\u4ef6\u4e0d\u5b58\u5728\u5c06\u65b0\u5efa\u6587\u4ef6\uff0c\u5426\u5219\u6e05\u7a7a\u5185\u5bb9\uff0c\u5141\u8bb8\u8bfb/\u5199\u6570\u636e</li> <li><code>wb</code>\uff1a\u4ee5\u53ea\u5199\u65b9\u5f0f\u6253\u5f00\u4e8c\u8fdb\u5236\u6587\u4ef6\uff0c\u6587\u4ef6\u4e0d\u5b58\u5728\u5c06\u4f1a\u65b0\u5efa\u6587\u4ef6\uff0c\u5426\u5219\u6e05\u7a7a\u5185\u5bb9\uff0c\u53ea\u5141\u8bb8\u5199\u5165\u6570\u636e</li> <li><code>wb+</code>\uff1a\u4ee5\u8bfb/\u5199\u65b9\u5f0f\u6253\u5f00\u4e8c\u8fdb\u5236\u6587\u4ef6\uff0c\u6587\u4ef6\u4e0d\u5b58\u5728\u5c06\u65b0\u5efa\u6587\u4ef6\uff0c\u5426\u5219\u6e05\u7a7a\u5185\u5bb9\uff0c\u5141\u8bb8\u8bfb/\u5199\u6570\u636e</li> <li><code>a</code>\uff1a\u4ee5\u53ea\u5199\u65b9\u5f0f\u6253\u5f00\u6587\u4ef6\uff0c\u6587\u4ef6\u4e0d\u5b58\u5728\u5c06\u65b0\u5efa\u6587\u4ef6\uff0c\u5199\u5165\u6570\u636e\u5c06\u88ab\u9644\u52a0\u5728\u6587\u4ef6\u672b\u5c3e\uff08\u4fdd\u7559 EOF \u7b26\uff09</li> <li><code>a+</code>\uff1a\u4ee5\u8bfb/\u5199\u65b9\u5f0f\u6253\u5f00\u6587\u4ef6\uff0c\u6587\u4ef6\u4e0d\u5b58\u5728\u5c06\u65b0\u5efa\u6587\u4ef6\uff0c\u5199\u5165\u6570\u636e\u5c06\u88ab\u9644\u52a0\u5728\u6587\u4ef6\u672b\u5c3e\uff08\u4e0d\u4fdd\u7559 EOF \u7b26\uff09</li> <li><code>at+</code>\uff1a\u4ee5\u8bfb/\u5199\u65b9\u5f0f\u6253\u5f00\u6587\u672c\u6587\u4ef6\uff0c\u5199\u5165\u6570\u636e\u5c06\u88ab\u9644\u52a0\u5728\u6587\u4ef6\u672b\u5c3e</li> <li><code>ab+</code>\uff1a\u4ee5\u8bfb/\u5199\u65b9\u5f0f\u6253\u5f00\u4e8c\u8fdb\u5236\u6587\u4ef6\uff0c\u5199\u5165\u6570\u636e\u5c06\u88ab\u9644\u52a0\u5728\u6587\u4ef6\u672b\u5c3e \u4f7f\u7528\u65b9\u5f0f</li> </ul> </li> </ul> C++<pre><code>#include &lt;cstdio&gt;\n#include &lt;iostream&gt;\nint mian(void) {\n    freopen(\"data.in\", \"r\", stdin); \n    // data.in \u5c31\u662f\u8bfb\u53d6\u7684\u6587\u4ef6\u540d\uff0c\u8981\u548c\u53ef\u6267\u884c\u6587\u4ef6\u653e\u5728\u540c\u4e00\u76ee\u5f55\u4e0b\n    freopen(\"data.out\", \"w\", stdout); \n    // data.out \u5c31\u662f\u8f93\u51fa\u6587\u4ef6\u7684\u6587\u4ef6\u540d\uff0c\u548c\u53ef\u6267\u884c\u6587\u4ef6\u5728\u540c\u4e00\u76ee\u5f55\u4e0b\n    fclose(stdin);\n    fclose(stdout);\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#132-fopen","title":"1.3.2 fopen \u51fd\u6570","text":"C++<pre><code>FILE* fopen(const char* path, const char* mode)\n</code></pre> <p>\u4f7f\u7528\u65b9\u5f0f</p> C++<pre><code>FILE *in, *out; // \u5b9a\u4e49\u6587\u4ef6\u6307\u9488 \nin = fopen(\"data.in\", \"r\"); \nout = fopen(\"data.out\", \"w\"); \n/* do what you want to do */ \nfclose(in); \nfclose(out);\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#14-c-ifstreamofstream","title":"1.4 C++ \u7684\u00a0<code>ifstream/ofstream</code>\u00a0\u6587\u4ef6\u8f93\u5165\u8f93\u51fa\u6d41","text":"C++<pre><code>#include &lt;fstream&gt; \nusing namespace std; \n// \u4e24\u4e2a\u7c7b\u578b\u90fd\u5728 std \u547d\u540d\u7a7a\u95f4\u91cc \nifstream fin(\"data.in\"); \nofstream fout(\"data.out\"); \nint main(void) { \n    /* \u4e2d\u95f4\u7684\u4ee3\u7801\u6539\u53d8 cin \u4e3a fin \uff0ccout \u4e3a fout \u5373\u53ef */ \n    fin.close(); \n    fout.close(); \n    return 0; \n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#2","title":"2 \u6807\u51c6\u5e93","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#21-stl","title":"2.1 STL \u5bb9\u5668","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#211","title":"2.1.1 \u5e8f\u5217\u5f0f\u5bb9\u5668","text":"<ul> <li>\u5411\u91cf(<code>vector</code>) \u540e\u7aef\u53ef\u9ad8\u6548\u589e\u52a0\u5143\u7d20\u7684\u987a\u5e8f\u8868\u3002<ul> <li>\u53ef\u4ee5\u52a8\u6001\u5206\u914d\u5185\u5b58</li> <li>\u91cd\u5199\u4e86\u6bd4\u8f83\u8fd0\u7b97\u7b26\u53ca\u8d4b\u503c\u8fd0\u7b97\u7b26</li> <li>\u4fbf\u5229\u7684\u521d\u59cb\u5316</li> <li>std::vector - cppreference.com</li> </ul> </li> <li>\u6570\u7ec4(<code>array</code>)C++11\uff0c\u5b9a\u957f\u7684\u987a\u5e8f\u8868\uff0cC \u98ce\u683c\u6570\u7ec4\u7684\u7b80\u5355\u5305\u88c5\u3002</li> <li>\u53cc\u7aef\u961f\u5217(<code>deque</code>) \u53cc\u7aef\u90fd\u53ef\u9ad8\u6548\u589e\u52a0\u5143\u7d20\u7684\u987a\u5e8f\u8868\u3002</li> <li>\u5217\u8868(<code>list</code>) \u53ef\u4ee5\u6cbf\u53cc\u5411\u904d\u5386\u7684\u94fe\u8868\u3002</li> <li>\u5355\u5411\u5217\u8868(<code>forward_list</code>) \u53ea\u80fd\u6cbf\u4e00\u4e2a\u65b9\u5411\u904d\u5386\u7684\u94fe\u8868\u3002</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#212","title":"2.1.2 \u5173\u8054\u5f0f\u5bb9\u5668","text":"<ul> <li>\u96c6\u5408(<code>set</code>) \u7528\u4ee5\u6709\u5e8f\u5730\u5b58\u50a8\u00a0\u4e92\u5f02\u00a0\u5143\u7d20\u7684\u5bb9\u5668\u3002\u5176\u5b9e\u73b0\u662f\u7531\u8282\u70b9\u7ec4\u6210\u7684\u7ea2\u9ed1\u6811\uff0c\u6bcf\u4e2a\u8282\u70b9\u90fd\u5305\u542b\u7740\u4e00\u4e2a\u5143\u7d20\uff0c\u8282\u70b9\u4e4b\u95f4\u4ee5\u67d0\u79cd\u6bd4\u8f83\u5143\u7d20\u5927\u5c0f\u7684\u8c13\u8bcd\u8fdb\u884c\u6392\u5217\u3002</li> <li>\u591a\u91cd\u96c6\u5408(<code>multiset</code>) \u7528\u4ee5\u6709\u5e8f\u5730\u5b58\u50a8\u5143\u7d20\u7684\u5bb9\u5668\u3002\u5141\u8bb8\u5b58\u5728\u76f8\u7b49\u7684\u5143\u7d20\u3002</li> <li>\u6620\u5c04(<code>map</code>) \u7531 {\u952e\uff0c\u503c} \u5bf9\u7ec4\u6210\u7684\u96c6\u5408\uff0c\u4ee5\u67d0\u79cd\u6bd4\u8f83\u952e\u5927\u5c0f\u5173\u7cfb\u7684\u8c13\u8bcd\u8fdb\u884c\u6392\u5217\u3002</li> <li>\u591a\u91cd\u6620\u5c04(<code>multimap</code>) \u7531 {\u952e\uff0c\u503c} \u5bf9\u7ec4\u6210\u7684\u591a\u91cd\u96c6\u5408\uff0c\u4ea6\u5373\u5141\u8bb8\u952e\u6709\u76f8\u7b49\u60c5\u51b5\u7684\u6620\u5c04\u3002</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#213","title":"2.1.3 \u65e0\u5e8f\uff08\u5173\u8054\u5f0f\uff09\u5bb9\u5668","text":"<ul> <li>\u65e0\u5e8f\uff08\u591a\u91cd\uff09\u96c6\u5408(<code>unordered_set</code>/<code>unordered_multiset</code>)C++11\uff0c\u4e0e\u00a0<code>set</code>/<code>multiset</code>\u00a0\u7684\u533a\u522b\u5728\u4e8e\u5143\u7d20\u65e0\u5e8f\uff0c\u53ea\u5173\u5fc3\u300c\u5143\u7d20\u662f\u5426\u5b58\u5728\u300d\uff0c\u4f7f\u7528\u54c8\u5e0c\u5b9e\u73b0\u3002</li> <li>\u65e0\u5e8f\uff08\u591a\u91cd\uff09\u6620\u5c04(<code>unordered_map</code>/<code>unordered_multimap</code>)C++11\uff0c\u4e0e\u00a0<code>map</code>/<code>multimap</code>\u00a0\u7684\u533a\u522b\u5728\u4e8e\u952e (key) \u65e0\u5e8f\uff0c\u53ea\u5173\u5fc3 \"\u952e\u4e0e\u503c\u7684\u5bf9\u5e94\u5173\u7cfb\"\uff0c\u4f7f\u7528\u54c8\u5e0c\u5b9e\u73b0\u3002</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#214","title":"2.1.4 \u5bb9\u5668\u9002\u914d\u5668","text":"<p>\u5bb9\u5668\u9002\u914d\u5668\u5176\u5b9e\u5e76\u4e0d\u662f\u5bb9\u5668\u3002\u5b83\u4eec\u4e0d\u5177\u6709\u5bb9\u5668\u7684\u67d0\u4e9b\u7279\u70b9\uff08\u5982\uff1a\u6709\u8fed\u4ee3\u5668\u3001\u6709\u00a0<code>clear()</code>\u00a0\u51fd\u6570\u2026\u2026\uff09\u3002</p> <p>\u300c\u9002\u914d\u5668\u662f\u4f7f\u4e00\u79cd\u4e8b\u7269\u7684\u884c\u4e3a\u7c7b\u4f3c\u4e8e\u53e6\u5916\u4e00\u79cd\u4e8b\u7269\u884c\u4e3a\u7684\u4e00\u79cd\u673a\u5236\u300d\uff0c\u9002\u914d\u5668\u5bf9\u5bb9\u5668\u8fdb\u884c\u5305\u88c5\uff0c\u4f7f\u5176\u8868\u73b0\u51fa\u53e6\u5916\u4e00\u79cd\u884c\u4e3a\u3002</p> <ul> <li>\u6808(<code>stack</code>) \u540e\u8fdb\u5148\u51fa (LIFO) \u7684\u5bb9\u5668\uff0c\u9ed8\u8ba4\u662f\u5bf9\u53cc\u7aef\u961f\u5217\uff08<code>deque</code>\uff09\u7684\u5305\u88c5\u3002</li> <li>\u961f\u5217(<code>queue</code>) \u5148\u8fdb\u5148\u51fa (FIFO) \u7684\u5bb9\u5668\uff0c\u9ed8\u8ba4\u662f\u5bf9\u53cc\u7aef\u961f\u5217\uff08<code>deque</code>\uff09\u7684\u5305\u88c5\u3002</li> <li>\u4f18\u5148\u961f\u5217(<code>priority_queue</code>) \u5143\u7d20\u7684\u6b21\u5e8f\u662f\u7531\u4f5c\u7528\u4e8e\u6240\u5b58\u50a8\u7684\u503c\u5bf9\u4e0a\u7684\u67d0\u79cd\u8c13\u8bcd\u51b3\u5b9a\u7684\u7684\u4e00\u79cd\u961f\u5217\uff0c\u9ed8\u8ba4\u662f\u5bf9\u5411\u91cf\uff08<code>vector</code>\uff09\u7684\u5305\u88c5\u3002</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#215","title":"2.1.5 \u5171\u540c\u70b9","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#2151","title":"2.1.5.1 \u5bb9\u5668\u58f0\u660e","text":"<ul> <li>\u90fd\u662f\u00a0<code>containerName&lt;typeName,...&gt; name</code>\u00a0\u7684\u5f62\u5f0f\uff0c\u4f46\u6a21\u677f\u53c2\u6570\uff08<code>&lt;&gt;</code>\u00a0\u5185\u7684\u53c2\u6570\uff09\u7684\u4e2a\u6570\u3001\u5f62\u5f0f\u4f1a\u6839\u636e\u5177\u4f53\u5bb9\u5668\u800c\u53d8\u3002</li> <li>\u672c\u8d28\u539f\u56e0\uff1aSTL \u5c31\u662f\u300c\u6807\u51c6\u6a21\u677f\u5e93\u300d\uff0c\u6240\u4ee5\u5bb9\u5668\u90fd\u662f\u6a21\u677f\u7c7b\u3002</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#2152","title":"2.1.5.2 \u8fed\u4ee3\u5668","text":"C++<pre><code>vector&lt;int&gt; data(10);\n\nfor (int i = 0; i &lt; data.size(); i++)\n    cout &lt;&lt; data[i] &lt;&lt; endl;\n\nfor (vector&lt;int&gt;::iterator iter = data.begin(); iter != data.end(); iter++)\n    cout &lt;&lt; *iter &lt;&lt; endl;\n//C++11 \u4ee5\u540e\u53ef\u4ee5\u7528 auto iter = data.begin() \u6765\u7b80\u5316\n</code></pre> <ul> <li>\u5206\u7c7b<ul> <li>InputIterator\uff08\u8f93\u5165\u8fed\u4ee3\u5668\uff09\uff1a\u53ea\u8981\u6c42\u652f\u6301\u62f7\u8d1d\u3001\u81ea\u589e\u548c\u89e3\u5f15\u8bbf\u95ee\u3002</li> <li>OutputIterator\uff08\u8f93\u51fa\u8fed\u4ee3\u5668\uff09\uff1a\u53ea\u8981\u6c42\u652f\u6301\u62f7\u8d1d\u3001\u81ea\u589e\u548c\u89e3\u5f15\u8d4b\u503c\u3002</li> <li>ForwardIterator\uff08\u5411\u524d\u8fed\u4ee3\u5668\uff09\uff1a\u540c\u65f6\u6ee1\u8db3 InputIterator \u548c OutputIterator \u7684\u8981\u6c42\u3002</li> <li>BidirectionalIterator\uff08\u53cc\u5411\u8fed\u4ee3\u5668\uff09\uff1a\u5728 ForwardIterator \u7684\u57fa\u7840\u4e0a\u652f\u6301\u81ea\u51cf\uff08\u5373\u53cd\u5411\u8bbf\u95ee\uff09\u3002</li> <li>RandomAccessIterator\uff08\u968f\u673a\u8bbf\u95ee\u8fed\u4ee3\u5668\uff09\uff1a\u5728 BidirectionalIterator \u7684\u57fa\u7840\u4e0a\u652f\u6301\u52a0\u51cf\u8fd0\u7b97\u548c\u6bd4\u8f83\u8fd0\u7b97\uff08\u5373\u968f\u673a\u8bbf\u95ee\uff09\u3002</li> <li>ContiguousIterator\uff08\u8fde\u7eed\u8fed\u4ee3\u5668\uff09\uff1a\u5728 RandomAccessIterator \u7684\u57fa\u7840\u4e0a\u8981\u6c42\u5bf9\u53ef\u89e3\u5f15\u7528\u7684\u8fed\u4ee3\u5668\u00a0<code>a + n</code>\u00a0\u6ee1\u8db3\u00a0<code>*(a + n)</code>\u00a0\u4e0e\u00a0<code>*(std::address_of(*a) + n)</code>\u00a0\u7b49\u4ef7\uff08\u5373\u8fde\u7eed\u5b58\u50a8\uff0c\u5176\u4e2d\u00a0<code>a</code>\u00a0\u4e3a\u8fde\u7eed\u8fed\u4ee3\u5668\u3001<code>n</code>\u00a0\u4e3a\u6574\u578b\u503c\uff09\u3002</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#2153","title":"2.1.5.3 \u5171\u6709\u51fd\u6570","text":"<ul> <li><code>=</code>\uff1a\u6709\u8d4b\u503c\u8fd0\u7b97\u7b26\u4ee5\u53ca\u590d\u5236\u6784\u9020\u51fd\u6570\u3002</li> <li><code>begin()</code>\uff1a\u8fd4\u56de\u6307\u5411\u5f00\u5934\u5143\u7d20\u7684\u8fed\u4ee3\u5668\u3002</li> <li><code>end()</code>\uff1a\u8fd4\u56de\u6307\u5411\u672b\u5c3e\u7684\u4e0b\u4e00\u4e2a\u5143\u7d20\u7684\u8fed\u4ee3\u5668\u3002<code>end()</code>\u00a0\u4e0d\u6307\u5411\u67d0\u4e2a\u5143\u7d20\uff0c\u4f46\u5b83\u662f\u672b\u5c3e\u5143\u7d20\u7684\u540e\u7ee7\u3002</li> <li><code>size()</code>\uff1a\u8fd4\u56de\u5bb9\u5668\u5185\u7684\u5143\u7d20\u4e2a\u6570\u3002</li> <li><code>max_size()</code>\uff1a\u8fd4\u56de\u5bb9\u5668\u00a0\u7406\u8bba\u4e0a\u00a0\u80fd\u5b58\u50a8\u7684\u6700\u5927\u5143\u7d20\u4e2a\u6570\u3002\u4f9d\u5bb9\u5668\u7c7b\u578b\u548c\u6240\u5b58\u50a8\u53d8\u91cf\u7684\u7c7b\u578b\u800c\u53d8\u3002</li> <li><code>empty()</code>\uff1a\u8fd4\u56de\u5bb9\u5668\u662f\u5426\u4e3a\u7a7a\u3002</li> <li><code>swap()</code>\uff1a\u4ea4\u6362\u4e24\u4e2a\u5bb9\u5668\u3002</li> <li><code>clear()</code>\uff1a\u6e05\u7a7a\u5bb9\u5668\u3002</li> <li><code>==</code>/<code>!=</code>/<code>&lt;</code>/<code>&gt;</code>/<code>&lt;=</code>/<code>&gt;=</code>\uff1a\u6309\u00a0\u5b57\u5178\u5e8f\u00a0\u6bd4\u8f83\u4e24\u4e2a\u5bb9\u5668\u7684\u5927\u5c0f\u3002\uff08\u6bd4\u8f83\u5143\u7d20\u5927\u5c0f\u65f6\u00a0<code>map</code>\u00a0\u7684\u6bcf\u4e2a\u5143\u7d20\u76f8\u5f53\u4e8e\u00a0<code>set&lt;pair&lt;key, value&gt; &gt;</code>\uff0c\u65e0\u5e8f\u5bb9\u5668\u4e0d\u652f\u6301\u00a0<code>&lt;</code>/<code>&gt;</code>/<code>&lt;=</code>/<code>&gt;=</code>\u3002\uff09</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#216-stl","title":"2.1.6 STL \u7b97\u6cd5","text":"<ul> <li><code>find</code>\uff1a\u987a\u5e8f\u67e5\u627e\u3002<code>find(v.begin(), v.end(), value)</code>\uff0c\u5176\u4e2d\u00a0<code>value</code>\u00a0\u4e3a\u9700\u8981\u67e5\u627e\u7684\u503c\u3002</li> <li><code>reverse</code>\uff1a\u7ffb\u8f6c\u6570\u7ec4\u3001\u5b57\u7b26\u4e32\u3002<code>reverse(v.begin(), v.end())</code>\u00a0\u6216\u00a0<code>reverse(a + begin, a + end)</code>\u3002</li> <li><code>unique</code>\uff1a\u53bb\u9664\u5bb9\u5668\u4e2d\u76f8\u90bb\u7684\u91cd\u590d\u5143\u7d20\u3002<code>unique(ForwardIterator first, ForwardIterator last)</code>\uff0c\u8fd4\u56de\u503c\u4e3a\u6307\u5411\u00a0\u53bb\u91cd\u540e\u00a0\u5bb9\u5668\u7ed3\u5c3e\u7684\u8fed\u4ee3\u5668\uff0c\u539f\u5bb9\u5668\u5927\u5c0f\u4e0d\u53d8\u3002\u4e0e\u00a0<code>sort</code>\u00a0\u7ed3\u5408\u4f7f\u7528\u53ef\u4ee5\u5b9e\u73b0\u5b8c\u6574\u5bb9\u5668\u53bb\u91cd\u3002</li> <li><code>sort</code>\uff1a\u6392\u5e8f\u3002<code>sort(v.begin(), v.end(), cmp)</code>\u00a0\u6216\u00a0<code>sort(a + begin, a + end, cmp)</code>\uff0c\u5176\u4e2d\u00a0<code>end</code>\u00a0\u662f\u6392\u5e8f\u7684\u6570\u7ec4\u6700\u540e\u4e00\u4e2a\u5143\u7d20\u7684\u540e\u4e00\u4f4d\uff0c<code>cmp</code>\u00a0\u4e3a\u81ea\u5b9a\u4e49\u7684\u6bd4\u8f83\u51fd\u6570\u3002</li> <li><code>stable_sort</code>\uff1a\u7a33\u5b9a\u6392\u5e8f\uff0c\u7528\u6cd5\u540c\u00a0<code>sort()</code>\u3002</li> <li><code>nth_element</code> \uff1a\u6309\u6307\u5b9a\u8303\u56f4\u8fdb\u884c\u5206\u7c7b\uff0c\u5373\u627e\u51fa\u5e8f\u5217\u4e2d\u7b2c \\(\\displaystyle n\\) \u5927\u7684\u5143\u7d20\uff0c\u4f7f\u5176\u5de6\u8fb9\u5747\u4e3a\u5c0f\u4e8e\u5b83\u7684\u6570\uff0c\u53f3\u8fb9\u5747\u4e3a\u5927\u4e8e\u5b83\u7684\u6570\u3002 <code>nth_element(v.begin(), v.begin() + mid, v.end(), cmp)</code>\u00a0\u6216\u00a0<code>nth_element(a + begin, a + begin + mid, a + end, cmp)</code> \u3002</li> <li><code>binary_search</code>\uff1a\u4e8c\u5206\u67e5\u627e\u3002<code>binary_search(v.begin(), v.end(), value)</code>\uff0c\u5176\u4e2d\u00a0<code>value</code>\u00a0\u4e3a\u9700\u8981\u67e5\u627e\u7684\u503c\u3002</li> <li><code>merge</code>\uff1a\u5c06\u4e24\u4e2a\uff08\u5df2\u6392\u5e8f\u7684\uff09\u5e8f\u5217\u00a0\u6709\u5e8f\u5408\u5e76\u00a0\u5230\u7b2c\u4e09\u4e2a\u5e8f\u5217\u7684\u00a0\u63d2\u5165\u8fed\u4ee3\u5668\u00a0\u4e0a\u3002<code>merge(v1.begin(), v1.end(), v2.begin(), v2.end() ,back_inserter(v3))</code>\u3002</li> <li><code>inplace_merge</code>\uff1a\u5c06\u4e24\u4e2a\uff08\u5df2\u6309\u5c0f\u4e8e\u8fd0\u7b97\u7b26\u6392\u5e8f\u7684\uff09\uff1a<code>[first,middle), [middle,last)</code>\u00a0\u8303\u56f4\u00a0\u539f\u5730\u5408\u5e76\u4e3a\u4e00\u4e2a\u6709\u5e8f\u5e8f\u5217\u3002<code>inplace_merge(v.begin(), v.begin() + middle, v.end())</code>\u3002</li> <li><code>lower_bound</code>\uff1a\u5728\u4e00\u4e2a\u6709\u5e8f\u5e8f\u5217\u4e2d\u8fdb\u884c\u4e8c\u5206\u67e5\u627e\uff0c\u8fd4\u56de\u6307\u5411\u7b2c\u4e00\u4e2a\u00a0\u5927\u4e8e\u7b49\u4e8e \u00a0\u7684\u5143\u7d20\u7684\u4f4d\u7f6e\u7684\u8fed\u4ee3\u5668\u3002\u5982\u679c\u4e0d\u5b58\u5728\u8fd9\u6837\u7684\u5143\u7d20\uff0c\u5219\u8fd4\u56de\u5c3e\u8fed\u4ee3\u5668\u3002<code>lower_bound(v.begin(),v.end(),x)</code>\u3002</li> <li><code>upper_bound</code>\uff1a\u5728\u4e00\u4e2a\u6709\u5e8f\u5e8f\u5217\u4e2d\u8fdb\u884c\u4e8c\u5206\u67e5\u627e\uff0c\u8fd4\u56de\u6307\u5411\u7b2c\u4e00\u4e2a\u00a0\u5927\u4e8e \u00a0\u7684\u5143\u7d20\u7684\u4f4d\u7f6e\u7684\u8fed\u4ee3\u5668\u3002\u5982\u679c\u4e0d\u5b58\u5728\u8fd9\u6837\u7684\u5143\u7d20\uff0c\u5219\u8fd4\u56de\u5c3e\u8fed\u4ee3\u5668\u3002<code>upper_bound(v.begin(),v.end(),x)</code>\u3002</li> <li><code>next_permutation</code>\uff1a\u5c06\u5f53\u524d\u6392\u5217\u66f4\u6539\u4e3a\u00a0\u5168\u6392\u5217\u4e2d\u7684\u4e0b\u4e00\u4e2a\u6392\u5217\u3002\u5982\u679c\u5f53\u524d\u6392\u5217\u5df2\u7ecf\u662f\u00a0\u5168\u6392\u5217\u4e2d\u7684\u6700\u540e\u4e00\u4e2a\u6392\u5217\uff08\u5143\u7d20\u5b8c\u5168\u4ece\u5927\u5230\u5c0f\u6392\u5217\uff09\uff0c\u51fd\u6570\u8fd4\u56de\u00a0<code>false</code>\u00a0\u5e76\u5c06\u6392\u5217\u66f4\u6539\u4e3a\u00a0\u5168\u6392\u5217\u4e2d\u7684\u7b2c\u4e00\u4e2a\u6392\u5217\uff08\u5143\u7d20\u5b8c\u5168\u4ece\u5c0f\u5230\u5927\u6392\u5217\uff09\uff1b\u5426\u5219\uff0c\u51fd\u6570\u8fd4\u56de\u00a0<code>true</code>\u3002<code>next_permutation(v.begin(), v.end())</code>\u00a0\u6216\u00a0<code>next_permutation(v + begin, v + end)</code>\u3002</li> <li><code>prev_permutation</code>\uff1a\u5c06\u5f53\u524d\u6392\u5217\u66f4\u6539\u4e3a\u00a0\u5168\u6392\u5217\u4e2d\u7684\u4e0a\u4e00\u4e2a\u6392\u5217\u3002\u7528\u6cd5\u540c\u00a0<code>next_permutation</code>\u3002</li> <li><code>partial_sum</code>\uff1a\u6c42\u524d\u7f00\u548c\u3002\u8bbe\u6e90\u5bb9\u5668\u4e3a\u00a0\uff0c\u76ee\u6807\u5bb9\u5668\u4e3a\u00a0\uff0c\u5219\u4ee4\u00a0\u3002<code>partial_sum(src.begin(), src.end(), back_inserter(dst))</code>\u3002</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#22-bitset","title":"2.2 bitset","text":"<p>TODO bitset - OI Wiki</p>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#23-string","title":"2.3 string","text":"<ul> <li>\u91cd\u8f7d\u8fd0\u7b97\u7b26</li> <li>\u52a8\u6001\u5206\u914d\u7a7a\u95f4</li> </ul> C++<pre><code>std::string s;\nprintf(\"%s\", s.c_str());\nprintf(\"s \u7684\u957f\u5ea6\u4e3a %lu\", s.size()); \nprintf(\"s \u7684\u957f\u5ea6\u4e3a %lu\", s.length()); \nprintf(\"s \u7684\u957f\u5ea6\u4e3a %lu\", strlen(s.c_str()));\nsubstr(pos, len);\ninsert(index, count, ch);\ninsert(index, str);\nerase(index, count);\nreplace(pos, count, str);\nreplace(first, last, str);\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#24-pair","title":"2.4 pair","text":"<ul> <li><code>pair</code> \u4e0d\u9700\u8981\u989d\u5916\u5b9a\u4e49\u7ed3\u6784\u4e0e\u91cd\u8f7d\u8fd0\u7b97\u7b26</li> </ul> C++<pre><code>pair&lt;int, double&gt; p0(1, 2.0);\npair&lt;int, double&gt; p2 = make_pair(1, 2.0);\nauto p3 = make_pair(1, 2.0);\n\nint i = p0.first; \ndouble d = p0.second;\np1.first++;\n\npriority_queue&lt;pair&lt;int, double&gt; &gt; q;\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3","title":"3 \u8fdb\u9636","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#31","title":"3.1 \u7c7b","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#32","title":"3.2 \u52a8\u6001\u5185\u5b58","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#321-new-delete","title":"3.2.1 new \u548c delete \u8fd0\u7b97\u7b26","text":"<ul> <li>\u6808: \u58f0\u660e\u7684\u6240\u6709\u53d8\u91cf\u5c06\u5360\u7528\u6808\u5185\u5b58</li> <li>\u5806: \u672a\u4f7f\u7528\u7684\u5185\u5b58</li> </ul> C++<pre><code>new data-type;\n\ndouble* pvalue = NULL;\npvalue = new double;\n\nif (!(pvalue = new double)) {\n    cout &lt;&lt; \"Error: out of memory.\" &lt;&lt; endl;\n    exit(1);\n}\n\ndelete pvalue;\n</code></pre> <ul> <li>new \u4e0d\u4ec5\u5206\u914d\u7684\u5185\u5b58\u8fd8\u521b\u5efa\u4e86\u5bf9\u8c61</li> <li>malloc () \u53ea\u5206\u914d\u7684\u5185\u5b58</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#322","title":"3.2.2 \u6570\u7ec4\u7684\u52a8\u6001\u5185\u5b58\u5206\u914d","text":"C++<pre><code>int ***array;\n// \u5047\u5b9a\u6570\u7ec4\u7b2c\u4e00\u7ef4\u4e3a m\uff0c \u7b2c\u4e8c\u7ef4\u4e3a n\uff0c \u7b2c\u4e09\u7ef4\u4e3ah\n// \u52a8\u6001\u5206\u914d\u7a7a\u95f4\narray = new int **[m];\nfor( int i=0; i&lt;m; i++ )\n{\n    array[i] = new int *[n];\n    for( int j=0; j&lt;n; j++ )\n    {\n        array[i][j] = new int [h];\n    }\n}\n//\u91ca\u653e\nfor( int i=0; i&lt;m; i++ )\n{\n    for( int j=0; j&lt;n; j++ )\n    {\n        delete [] array[i][j];\n    }\n    delete [] array[i];\n}\ndelete [] array;\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#323","title":"3.2.3 \u5bf9\u8c61\u7684\u52a8\u6001\u5185\u5b58\u5206\u914d","text":"C++<pre><code>#include &lt;iostream&gt;\nusing namespace std;\n\nclass Box\n{\n   public:\n      Box() { \n         cout &lt;&lt; \"\u8c03\u7528\u6784\u9020\u51fd\u6570\uff01\" &lt;&lt;endl; \n      }\n      ~Box() { \n         cout &lt;&lt; \"\u8c03\u7528\u6790\u6784\u51fd\u6570\uff01\" &lt;&lt;endl; \n      }\n};\n\nint main( )\n{\n   Box* myBoxArray = new Box[4]; // \u4e00\u4e2a\u5305\u542b 4 \u4e2a Box \u5bf9\u8c61\u7684\u6570\u7ec4\n\n   delete [] myBoxArray; // \u5220\u9664\u6570\u7ec4\n   return 0;\n}\n</code></pre> Text Only<pre><code>\u8c03\u7528\u6784\u9020\u51fd\u6570\uff01\n\u8c03\u7528\u6784\u9020\u51fd\u6570\uff01\n\u8c03\u7528\u6784\u9020\u51fd\u6570\uff01\n\u8c03\u7528\u6784\u9020\u51fd\u6570\uff01\n\u8c03\u7528\u6790\u6784\u51fd\u6570\uff01\n\u8c03\u7528\u6790\u6784\u51fd\u6570\uff01\n\u8c03\u7528\u6790\u6784\u51fd\u6570\uff01\n\u8c03\u7528\u6790\u6784\u51fd\u6570\uff01\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#33","title":"3.3 \u547d\u540d\u7a7a\u95f4","text":"<ul> <li>\u7f16\u8bd1\u5668\u4e3a\u4e86\u533a\u522b\u540c\u540d\u51fd\u6570\u5f15\u5165\u4e86\u547d\u540d\u7a7a\u95f4</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#331","title":"3.3.1 \u5b9a\u4e49\u547d\u540d\u7a7a\u95f4","text":"C++<pre><code>namespace namespace_name {\n // code\n}\n\nnamespace_name::code;\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#332-using","title":"3.3.2 using \u6307\u4ee4","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#333","title":"3.3.3 \u4e0d\u8fde\u7eed\u7684\u547d\u540d\u7a7a\u95f4","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#334","title":"3.3.4 \u5d4c\u5957\u7684\u547d\u540d\u7a7a\u95f4","text":"C++<pre><code>namespace namespace_name1 {\n   // \u4ee3\u7801\u58f0\u660e\n   namespace namespace_name2 {\n      // \u4ee3\u7801\u58f0\u660e\n   }\n}\n\n// \u8bbf\u95ee namespace_name2 \u4e2d\u7684\u6210\u5458\nusing namespace namespace_name1::namespace_name2;\n\n// \u8bbf\u95ee namespace_name1 \u4e2d\u7684\u6210\u5458\nusing namespace namespace_name1;\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#34","title":"3.4 \u6a21\u677f","text":"<ul> <li>\u6cdb\u578b\u7f16\u7a0b: \u72ec\u7acb\u4e8e\u4efb\u4f55\u7279\u5b9a\u7c7b\u578b\u7684\u65b9\u5f0f\u5199\u4ee3\u7801</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#341","title":"3.4.1 \u51fd\u6570\u6a21\u677f","text":"C++<pre><code>template &lt;typename type&gt; ret-type func-name(parameter list)\n{\n   // \u51fd\u6570\u7684\u4e3b\u4f53\n}\n</code></pre> C++<pre><code>#include &lt;iostream&gt;\n#include &lt;string&gt;\n\nusing namespace std;\n\ntemplate &lt;typename T&gt;\ninline T const&amp; Max (T const&amp; a, T const&amp; b) \n{ \n    return a &lt; b ? b:a; \n} \n\nint main ()\n{\n\n    int i = 39;\n    int j = 20;\n    cout &lt;&lt; \"Max(i, j): \" &lt;&lt; Max(i, j) &lt;&lt; endl; \n\n    double f1 = 13.5; \n    double f2 = 20.7; \n    cout &lt;&lt; \"Max(f1, f2): \" &lt;&lt; Max(f1, f2) &lt;&lt; endl; \n\n    string s1 = \"Hello\"; \n    string s2 = \"World\"; \n    cout &lt;&lt; \"Max(s1, s2): \" &lt;&lt; Max(s1, s2) &lt;&lt; endl; \n\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#342","title":"3.4.2 \u7c7b\u6a21\u677f","text":"C++<pre><code>template &lt;class type&gt; class class-name {\n// code\n}\n</code></pre> C++<pre><code>#include &lt;iostream&gt;\n#include &lt;vector&gt;\n#include &lt;cstdlib&gt;\n#include &lt;string&gt;\n#include &lt;stdexcept&gt;\n\nusing namespace std;\n\ntemplate &lt;class T&gt;\nclass Stack { \n  private: \n    vector&lt;T&gt; elems;     // \u5143\u7d20 \n\n  public: \n    void push(T const&amp;);  // \u5165\u6808\n    void pop();               // \u51fa\u6808\n    T top() const;            // \u8fd4\u56de\u6808\u9876\u5143\u7d20\n    bool empty() const{       // \u5982\u679c\u4e3a\u7a7a\u5219\u8fd4\u56de\u771f\u3002\n        return elems.empty(); \n    } \n}; \n\ntemplate &lt;class T&gt;\nvoid Stack&lt;T&gt;::push (T const&amp; elem) \n{ \n    // \u8ffd\u52a0\u4f20\u5165\u5143\u7d20\u7684\u526f\u672c\n    elems.push_back(elem);    \n} \n\ntemplate &lt;class T&gt;\nvoid Stack&lt;T&gt;::pop () \n{ \n    if (elems.empty()) { \n        throw out_of_range(\"Stack&lt;&gt;::pop(): empty stack\"); \n    }\n    // \u5220\u9664\u6700\u540e\u4e00\u4e2a\u5143\u7d20\n    elems.pop_back();         \n} \n\ntemplate &lt;class T&gt;\nT Stack&lt;T&gt;::top () const \n{ \n    if (elems.empty()) { \n        throw out_of_range(\"Stack&lt;&gt;::top(): empty stack\"); \n    }\n    // \u8fd4\u56de\u6700\u540e\u4e00\u4e2a\u5143\u7d20\u7684\u526f\u672c \n    return elems.back();      \n} \n\nint main() \n{ \n    try { \n        Stack&lt;int&gt;       intStack;    // int \u7c7b\u578b\u7684\u6808 \n        Stack&lt;string&gt; stringStack;    // string \u7c7b\u578b\u7684\u6808 \n\n        // \u64cd\u4f5c int \u7c7b\u578b\u7684\u6808 \n        intStack.push(7); \n        cout &lt;&lt; intStack.top() &lt;&lt;endl; \n\n        // \u64cd\u4f5c string \u7c7b\u578b\u7684\u6808 \n        stringStack.push(\"hello\"); \n        cout &lt;&lt; stringStack.top() &lt;&lt; std::endl; \n        stringStack.pop(); \n        stringStack.pop(); \n    } \n    catch (exception const&amp; ex) { \n        cerr &lt;&lt; \"Exception: \" &lt;&lt; ex.what() &lt;&lt;endl; \n        return -1;\n    } \n}\n</code></pre> Text Only<pre><code>7\nhello\nException: Stack&lt;&gt;::pop(): empty stack\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#35","title":"3.5 \u9884\u5904\u7406\u5668","text":"<ul> <li>\u4e0d\u662f C++\u8bed\u53e5\uff0c\u4e0d\u4f1a\u4ee5\u5206\u53f7\u7ed3\u5c3e</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#351-define","title":"3.5.1 #define \u9884\u5904\u7406","text":"C++<pre><code>#define macro-name replacement-text \n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#352","title":"3.5.2 \u53c2\u6570\u5b8f","text":"C++<pre><code>#include &lt;iostream&gt;\nusing namespace std;\n\n#define MIN(a,b) (a&lt;b ? a : b)\n\nint main ()\n{\n   int i, j;\n   i = 100;\n   j = 30;\n   cout &lt;&lt;\"\u8f83\u5c0f\u7684\u503c\u4e3a\uff1a\" &lt;&lt; MIN(i, j) &lt;&lt; endl;\n\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#353","title":"3.5.3 \u6761\u4ef6\u7f16\u8bd1","text":"C++<pre><code>#ifdef NULL\n   #define NULL 0\n#endif\n\n#ifdef DEBUG\n   cerr &lt;&lt;\"Variable x = \" &lt;&lt; x &lt;&lt; endl;\n#endif\n\n#if 0\n   \u4e0d\u8fdb\u884c\u7f16\u8bd1\u7684\u4ee3\u7801\n#endif\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#354","title":"3.5.4 # \u548c ## \u8fd0\u7b97\u7b26","text":"C++<pre><code>#include &lt;iostream&gt;\nusing namespace std;\n\n#define MKSTR( x ) #x\n\nint main ()\n{\n    cout &lt;&lt; MKSTR(HELLO C++) &lt;&lt; endl;\n\n    return 0;\n}\n</code></pre> C++<pre><code>#include &lt;iostream&gt;\nusing namespace std;\n\n#define concat(a, b) a ## b\nint main()\n{\n   int xy = 100;\n\n   cout &lt;&lt; concat(x, y);\n   return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#355","title":"3.5.5 \u9884\u5b9a\u4e49\u5b8f","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#36","title":"3.6 \u4fe1\u53f7\u5904\u7406","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#361-signal","title":"3.6.1 signal () \u51fd\u6570","text":"C++<pre><code>void (*signal (int sig, void (*func)(int)))(int); \n\nsignal(registered signal, signal handler)\n</code></pre> C++<pre><code>#include &lt;iostream&gt;\n#include &lt;csignal&gt;\n#include &lt;unistd.h&gt;\n\nusing namespace std;\n\nvoid signalHandler( int signum )\n{\n    cout &lt;&lt; \"Interrupt signal (\" &lt;&lt; signum &lt;&lt; \") received.\\n\";\n\n    // \u6e05\u7406\u5e76\u5173\u95ed\n    // \u7ec8\u6b62\u7a0b\u5e8f  \n\n   exit(signum);  \n\n}\n\nint main ()\n{\n    // \u6ce8\u518c\u4fe1\u53f7 SIGINT \u548c\u4fe1\u53f7\u5904\u7406\u7a0b\u5e8f\n    signal(SIGINT, signalHandler);  \n\n    while(1){\n       cout &lt;&lt; \"Going to sleep....\" &lt;&lt; endl;\n       sleep(1);\n    }\n\n    return 0;\n}\n</code></pre> <p>\u6309 Ctrl + C \u4e2d\u65ad\u7a0b\u5e8f:</p> Text Only<pre><code>Going to sleep....\nGoing to sleep....\nGoing to sleep....\nInterrupt signal (2) received.\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#362-raise","title":"3.6.2 raise () \u51fd\u6570","text":"C++<pre><code>int raise (signal sig);\n</code></pre> C++<pre><code>#include &lt;iostream&gt;\n#include &lt;csignal&gt;\n#include &lt;unistd.h&gt;\n\nusing namespace std;\n\nvoid signalHandler( int signum )\n{\n    cout &lt;&lt; \"Interrupt signal (\" &lt;&lt; signum &lt;&lt; \") received.\\n\";\n\n    // \u6e05\u7406\u5e76\u5173\u95ed\n    // \u7ec8\u6b62\u7a0b\u5e8f \n\n   exit(signum);  \n\n}\n\nint main ()\n{\n    int i = 0;\n    // \u6ce8\u518c\u4fe1\u53f7 SIGINT \u548c\u4fe1\u53f7\u5904\u7406\u7a0b\u5e8f\n    signal(SIGINT, signalHandler);  \n\n    while(++i){\n       cout &lt;&lt; \"Going to sleep....\" &lt;&lt; endl;\n       if( i == 3 ){\n          raise(SIGINT);\n       }\n       sleep(1);\n    }\n\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#37","title":"3.7 \u591a\u7ebf\u7a0b","text":"<ul> <li>\u4e24\u79cd\u7c7b\u578b\u7684\u591a\u4efb\u52a1\u5904\u7406<ul> <li>\u57fa\u4e8e\u8fdb\u7a0b\u662f\u7a0b\u5e8f\u7684\u5e76\u53d1\u6267\u884c</li> <li>\u57fa\u4e8e\u7ebf\u7a0b\u662f\u540c\u4e00\u7a0b\u5e8f\u7684\u7247\u6bb5\u7684\u5e76\u53d1\u6267\u884c</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#371","title":"3.7.1 \u6982\u5ff5\u8bf4\u660e","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3711-thread","title":"3.7.1.1 \u7ebf\u7a0b\uff08Thread\uff09","text":"<ul> <li>\u7ebf\u7a0b\u662f\u7a0b\u5e8f\u6267\u884c\u4e2d\u7684\u5355\u4e00\u987a\u5e8f\u63a7\u5236\u6d41\uff0c\u591a\u4e2a\u7ebf\u7a0b\u53ef\u4ee5\u5728\u540c\u4e00\u4e2a\u8fdb\u7a0b\u4e2d\u72ec\u7acb\u8fd0\u884c\u3002</li> <li>\u7ebf\u7a0b\u5171\u4eab\u8fdb\u7a0b\u7684\u5730\u5740\u7a7a\u95f4\u3001\u6587\u4ef6\u63cf\u8ff0\u7b26\u3001\u5806\u548c\u5168\u5c40\u53d8\u91cf\u7b49\u8d44\u6e90\uff0c\u4f46\u6bcf\u4e2a\u7ebf\u7a0b\u6709\u81ea\u5df1\u7684\u6808\u3001\u5bc4\u5b58\u5668\u548c\u7a0b\u5e8f\u8ba1\u6570\u5668\u3002</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3712-concurrency-parallelism","title":"3.7.1.2 \u5e76\u53d1\uff08Concurrency\uff09\u4e0e\u5e76\u884c \uff08Parallelism\uff09","text":"<ul> <li>\u5e76\u53d1\uff1a\u591a\u4e2a\u4efb\u52a1\u5728\u65f6\u95f4\u7247\u6bb5\u5185\u4ea4\u66ff\u6267\u884c\uff0c\u8868\u73b0\u51fa\u540c\u65f6\u8fdb\u884c\u7684\u6548\u679c\u3002</li> <li>\u5e76\u884c\uff1a\u591a\u4e2a\u4efb\u52a1\u5728\u591a\u4e2a\u5904\u7406\u5668\u6216\u5904\u7406\u5668\u6838\u4e0a\u540c\u65f6\u6267\u884c\u3002 C++11 \u4ee5\u540e\u6709\u591a\u7ebf\u7a0b\u652f\u6301:</li> <li>std::thread\uff1a\u7528\u4e8e\u521b\u5efa\u548c\u7ba1\u7406\u7ebf\u7a0b\u3002</li> <li>std::mutex\uff1a\u7528\u4e8e\u7ebf\u7a0b\u4e4b\u95f4\u7684\u4e92\u65a5\uff0c\u9632\u6b62\u591a\u4e2a\u7ebf\u7a0b\u540c\u65f6\u8bbf\u95ee\u5171\u4eab\u8d44\u6e90\u3002</li> <li>std::lock_guard\u00a0\u548c\u00a0std::unique_lock\uff1a\u7528\u4e8e\u7ba1\u7406\u9501\u7684\u83b7\u53d6\u548c\u91ca\u653e\u3002</li> <li>std::condition_variable\uff1a\u7528\u4e8e\u7ebf\u7a0b\u95f4\u7684\u6761\u4ef6\u53d8\u91cf\uff0c\u534f\u8c03\u7ebf\u7a0b\u95f4\u7684\u7b49\u5f85\u548c\u901a\u77e5\u3002</li> <li>std::future\u00a0\u548c\u00a0std::promise\uff1a\u7528\u4e8e\u5b9e\u73b0\u7ebf\u7a0b\u95f4\u7684\u503c\u4f20\u9012\u548c\u4efb\u52a1\u540c\u6b65\u3002</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#372","title":"3.7.2 \u521b\u5efa\u7ebf\u7a0b","text":"C++<pre><code>#include&lt;thread&gt;\nstd::thread thread_object(callable, args...);\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3721","title":"3.7.2.1 \u4f7f\u7528\u51fd\u6570\u6307\u9488","text":"C++<pre><code>#include &lt;iostream&gt;\n#include &lt;thread&gt;\n\nvoid printMessage(int count) {\n    for (int i = 0; i &lt; count; ++i) {\n        std::cout &lt;&lt; \"Hello from thread (function pointer)!\\n\";\n    }\n}\n\nint main() {\n    std::thread t1(printMessage, 5); // \u521b\u5efa\u7ebf\u7a0b\uff0c\u4f20\u9012\u51fd\u6570\u6307\u9488\u548c\u53c2\u6570\n    t1.join(); // \u7b49\u5f85\u7ebf\u7a0b\u5b8c\u6210\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3722","title":"3.7.2.2 \u4f7f\u7528\u51fd\u6570\u5bf9\u8c61","text":"C++<pre><code>#include &lt;iostream&gt;\n#include &lt;thread&gt;\n\nclass PrintTask {\npublic:\n    void operator()(int count) const {\n        for (int i = 0; i &lt; count; ++i) {\n            std::cout &lt;&lt; \"Hello from thread (function object)!\\n\";\n        }\n    }\n};\n\nint main() {\n    std::thread t2(PrintTask(), 5); // \u521b\u5efa\u7ebf\u7a0b\uff0c\u4f20\u9012\u51fd\u6570\u5bf9\u8c61\u548c\u53c2\u6570\n    t2.join(); // \u7b49\u5f85\u7ebf\u7a0b\u5b8c\u6210\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3723-lambda","title":"3.7.2.3 \u4f7f\u7528 Lambda \u8868\u8fbe\u5f0f","text":"C++<pre><code>#include &lt;iostream&gt;\n#include &lt;thread&gt;\n\nint main() {\n    std::thread t3([](int count) {\n        for (int i = 0; i &lt; count; ++i) {\n            std::cout &lt;&lt; \"Hello from thread (lambda)!\\n\";\n        }\n    }, 5); // \u521b\u5efa\u7ebf\u7a0b\uff0c\u4f20\u9012 Lambda \u8868\u8fbe\u5f0f\u548c\u53c2\u6570\n    t3.join(); // \u7b49\u5f85\u7ebf\u7a0b\u5b8c\u6210\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3724","title":"3.7.2.4 \u7ebf\u7a0b\u7ba1\u7406","text":"C++<pre><code>t.join();\nt.detach();\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3725","title":"3.7.2.5 \u7ebf\u7a0b\u7684\u4f20\u53c2","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3726","title":"3.7.2.6 \u503c\u4f20\u9012","text":"C++<pre><code>std::thread t(funx, arg1, arg2);\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3727","title":"3.7.2.7 \u5f15\u7528\u4f20\u9012","text":"C++<pre><code>#include &lt;iostream&gt;\n#include &lt;thread&gt;\n\nvoid increment(int&amp; x) {\n    ++x;\n}\n\nint main() {\n    int num = 0;\n    std::thread t(increment, std::ref(num)); // \u4f7f\u7528 std::ref \u4f20\u9012\u5f15\u7528\n    t.join();\n    std::cout &lt;&lt; \"Value after increment: \" &lt;&lt; num &lt;&lt; std::endl;\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#373","title":"3.7.3 \u7ebf\u7a0b\u540c\u6b65\u4e0e\u4e92\u65a5","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3731-mutex","title":"3.7.3.1 \u4e92\u65a5\u91cf\uff08Mutex\uff09","text":"C++<pre><code>std::mutex mtx;\nmtx.lock();   // \u9501\u5b9a\u4e92\u65a5\u9501\n// \u8bbf\u95ee\u5171\u4eab\u8d44\u6e90\nmtx.unlock();// \u91ca\u653e\u4e92\u65a5\u9501\n\nstd::lock_guard&lt;std::mutex&gt; lock(mtx); // \u81ea\u52a8\u9501\u5b9a\u548c\u89e3\u9501\n// \u8bbf\u95ee\u5171\u4eab\u8d44\u6e90\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3732-locks","title":"3.7.3.2 \u9501\uff08Locks\uff09","text":"<ul> <li><code>std::lock_guard</code> \uff1a\u4f5c\u7528\u57df\u9501\uff0c\u5f53\u6784\u9020\u65f6\u81ea\u52a8\u9501\u5b9a\u4e92\u65a5\u91cf\uff0c\u5f53\u6790\u6784\u65f6\u81ea\u52a8\u89e3\u9501\u3002</li> <li><code>std::unique_lock</code> \uff1a\u4e0e <code>std::lock_guard</code> \u7c7b\u4f3c\uff0c\u4f46\u63d0\u4f9b\u4e86\u66f4\u591a\u7684\u7075\u6d3b\u6027\uff0c\u4f8b\u5982\u53ef\u4ee5\u8f6c\u79fb\u6240\u6709\u6743\u548c\u624b\u52a8\u89e3\u9501\u3002</li> </ul> C++<pre><code>#include &lt;mutex&gt;\n\nstd::mutex mtx;\n\nvoid safeFunctionWithLockGuard() {\n    std::lock_guard&lt;std::mutex&gt; lk(mtx);\n    // \u8bbf\u95ee\u6216\u4fee\u6539\u5171\u4eab\u8d44\u6e90\n}\n\nvoid safeFunctionWithUniqueLock() {\n    std::unique_lock&lt;std::mutex&gt; ul(mtx);\n    // \u8bbf\u95ee\u6216\u4fee\u6539\u5171\u4eab\u8d44\u6e90\n    // ul.unlock(); // \u53ef\u9009\uff1a\u624b\u52a8\u89e3\u9501\n    // ...\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3733-condition-variable","title":"3.7.3.3 \u6761\u4ef6\u53d8\u91cf\uff08Condition Variable\uff09","text":"C++<pre><code>std::condition_variable cv;\nstd::mutex mtx;\nbool ready = false;\n\nstd::unique_lock&lt;std::mutex&gt; lock(mtx);\ncv.wait(lock, []{ return ready; }); // \u7b49\u5f85\u6761\u4ef6\u6ee1\u8db3\n// \u6761\u4ef6\u6ee1\u8db3\u540e\u6267\u884c\n</code></pre> C++<pre><code>#include &lt;mutex&gt;\n#include &lt;condition_variable&gt;\n\nstd::mutex mtx;\nstd::condition_variable cv;\nbool ready = false;\n\nvoid workerThread() {\n    std::unique_lock&lt;std::mutex&gt; lk(mtx);\n    cv.wait(lk, []{ return ready; }); // \u7b49\u5f85\u6761\u4ef6\n    // \u5f53\u6761\u4ef6\u6ee1\u8db3\u65f6\u6267\u884c\u5de5\u4f5c\n}\n\nvoid mainThread() {\n    {\n        std::lock_guard&lt;std::mutex&gt; lk(mtx);\n        // \u51c6\u5907\u6570\u636e\n        ready = true;\n    } // \u79bb\u5f00\u4f5c\u7528\u57df\u65f6\u89e3\u9501\n    cv.notify_one(); // \u901a\u77e5\u4e00\u4e2a\u7b49\u5f85\u7684\u7ebf\u7a0b\n}\n</code></pre> <p>TODO</p>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3734-atomic-operations","title":"3.7.3.4 \u539f\u5b50\u64cd\u4f5c\uff08Atomic Operations\uff09","text":"<ul> <li>\u5bf9\u5171\u4eab\u6570\u636e\u7684\u8bbf\u95ee\u4e0d\u53ef\u5206\u5272</li> </ul> C++<pre><code>#include &lt;atomic&gt;\n#include &lt;thread&gt;\n\nstd::atomic&lt;int&gt; count(0);\n\nvoid increment() {\n    count.fetch_add(1, std::memory_order_relaxed);\n}\n\nint main() {\n    std::thread t1(increment);\n    std::thread t2(increment);\n    t1.join();\n    t2.join();\n    return count; // \u5e94\u8fd4\u56de2\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3735-thread-local-storagetls","title":"3.7.3.5 \u7ebf\u7a0b\u5c40\u90e8\u5b58\u50a8\uff08Thread Local Storage\uff0cTLS\uff09","text":"<ul> <li>\u5141\u8bb8\u6bcf\u4e2a\u7ebf\u7a0b\u6709\u81ea\u5df1\u7684\u6570\u636e\u526f\u672c</li> </ul> C++<pre><code>#include &lt;iostream&gt;\n#include &lt;thread&gt;\n\nthread_local int threadData = 0;\n\nvoid threadFunction() {\n    threadData = 42; // \u6bcf\u4e2a\u7ebf\u7a0b\u90fd\u6709\u81ea\u5df1\u7684threadData\u526f\u672c\n    std::cout &lt;&lt; \"Thread data: \" &lt;&lt; threadData &lt;&lt; std::endl;\n}\n\nint main() {\n    std::thread t1(threadFunction);\n    std::thread t2(threadFunction);\n    t1.join();\n    t2.join();\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3736-deadlock","title":"3.7.3.6 \u6b7b\u9501\uff08Deadlock\uff09\u548c\u907f\u514d\u7b56\u7565","text":"<ul> <li>\u6b7b\u9501\u5373\u591a\u4e2a\u7ebf\u7a0b\u4e92\u76f8\u7b49\u5f85\u5bf9\u65b9\u91ca\u653e\u8d44\u6e90<ul> <li>\u603b\u662f\u4ee5\u76f8\u540c\u7684\u987a\u5e8f\u8bf7\u6c42\u8d44\u6e90\u3002</li> <li>\u4f7f\u7528\u8d85\u65f6\u6765\u5c1d\u8bd5\u83b7\u53d6\u8d44\u6e90\u3002</li> <li>\u4f7f\u7528\u6b7b\u9501\u68c0\u6d4b\u7b97\u6cd5\u3002</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#374","title":"3.7.4 \u7ebf\u7a0b\u95f4\u901a\u4fe1","text":"C++<pre><code>std::promise&lt;int&gt; p;\nstd::future&lt;int&gt; f = p.get_future();\n\nstd::thread t([&amp;p] {\n    p.set_value(10); // \u8bbe\u7f6e\u503c\uff0c\u89e6\u53d1 future\n});\n\nint result = f.get(); // \u83b7\u53d6\u503c\n</code></pre> <p>C++17 \u5f15\u5165\u4e86\u5e76\u884c\u7b97\u6cd5\u5e93</p> C++<pre><code>#include &lt;algorithm&gt;\n#include &lt;vector&gt;\n#include &lt;execution&gt;\n\nstd::vector&lt;int&gt; vec = {1, 2, 3, 4, 5};\nstd::for_each(std::execution::par, vec.begin(), vec.end(), [](int &amp;n) {\n    n *= 2;\n});\n</code></pre> <p>TODO \u591a\u7ebf\u7a0b\u5b9e\u4f8b</p>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#38-web","title":"3.8 Web \u7f16\u7a0b","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#381-cgi","title":"3.8.1 \u4ec0\u4e48\u662f CGI\uff1f","text":"<ul> <li>\u516c\u5171\u7f51\u5173\u63a5\u53e3\uff08CGI\uff09\uff0c\u662f\u4e00\u5957\u6807\u51c6\uff0c\u5b9a\u4e49\u4e86\u4fe1\u606f\u662f\u5982\u4f55\u5728 Web \u670d\u52a1\u5668\u548c\u5ba2\u6237\u7aef\u811a\u672c\u4e4b\u95f4\u8fdb\u884c\u4ea4\u6362\u7684\u3002</li> <li>CGI \u89c4\u8303\u76ee\u524d\u662f\u7531 NCSA \u7ef4\u62a4\u7684\uff0cNCSA \u5b9a\u4e49 CGI \u5982\u4e0b\uff1a<ul> <li>\u516c\u5171\u7f51\u5173\u63a5\u53e3\uff08CGI\uff09\uff0c\u662f\u4e00\u79cd\u7528\u4e8e\u5916\u90e8\u7f51\u5173\u7a0b\u5e8f\u4e0e\u4fe1\u606f\u670d\u52a1\u5668\uff08\u5982 HTTP \u670d\u52a1\u5668\uff09\u5bf9\u63a5\u7684\u63a5\u53e3\u6807\u51c6\u3002</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#382-web","title":"3.8.2 Web \u6d4f\u89c8","text":"<ul> <li>\u60a8\u7684\u6d4f\u89c8\u5668\u8054\u7cfb\u4e0a HTTP Web \u670d\u52a1\u5668\uff0c\u5e76\u8bf7\u6c42 URL\uff0c\u5373\u6587\u4ef6\u540d\u3002</li> <li>Web \u670d\u52a1\u5668\u5c06\u89e3\u6790 URL\uff0c\u5e76\u67e5\u627e\u6587\u4ef6\u540d\u3002\u5982\u679c\u627e\u5230\u8bf7\u6c42\u7684\u6587\u4ef6\uff0cWeb \u670d\u52a1\u5668\u4f1a\u628a\u6587\u4ef6\u53d1\u9001\u56de\u6d4f\u89c8\u5668\uff0c\u5426\u5219\u53d1\u9001\u4e00\u6761\u9519\u8bef\u6d88\u606f\uff0c\u8868\u660e\u60a8\u8bf7\u6c42\u4e86\u4e00\u4e2a\u9519\u8bef\u7684\u6587\u4ef6\u3002</li> <li>Web \u6d4f\u89c8\u5668\u4ece Web \u670d\u52a1\u5668\u83b7\u53d6\u54cd\u5e94\uff0c\u5e76\u6839\u636e\u63a5\u6536\u5230\u7684\u54cd\u5e94\u6765\u663e\u793a\u6587\u4ef6\u6216\u9519\u8bef\u6d88\u606f\u3002</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#383-cgi","title":"3.8.3 CGI \u67b6\u6784\u56fe","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#384-web","title":"3.8.4 Web \u670d\u52a1\u5668\u914d\u7f6e","text":"<p>TODO</p>"},{"location":"CS_Basic/CS61A/CS61A/","title":"CS61A","text":""},{"location":"CS_Basic/CS61A/CS61A/#cs61a","title":"CS61A","text":"<p> \u7ea6 24 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4\u4e0d\u5230 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <ul> <li>\u4ed6\u4eba\u603b\u7ed3</li> <li>https://github.com/HobbitQia/CS61A-Fall-2020/tree/main</li> <li>\u6559\u6750\u7ffb\u8bd1\u7248</li> <li>\u539f\u6559\u6750</li> <li>\u8bfe\u7a0b\u7f51\u7ad9\u5b58\u6863</li> <li>https://github.com/shuo-liu16/CS61A<ul> <li>scheme\u624b\u518c</li> </ul> </li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/","title":"COMPOSING PROGRAMS","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#composing-programs","title":"COMPOSING PROGRAMS","text":"<p> \u7ea6 2713 \u4e2a\u5b57  651 \u884c\u4ee3\u7801  2 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 22 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#1","title":"1 \u4f7f\u7528\u51fd\u6570\u6784\u5efa\u62bd\u8c61","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#11","title":"1.1 \u5f00\u59cb","text":"<p>\u7a0b\u5e8f\u7531\u4e24\u90e8\u5206\u7ec4\u6210:</p> <ul> <li>\u8ba1\u7b97\u4e00\u4e9b\u503c</li> <li>\u6267\u884c\u4e00\u4e9b\u64cd\u4f5c</li> <li>\u51fd\u6570</li> <li>\u5bf9\u8c61</li> <li>\u89e3\u91ca\u5668:<ul> <li>\u7528\u4e8e\u8ba1\u7b97\u590d\u6742\u8868\u8fbe\u5f0f\u7684\u7a0b\u5e8f</li> </ul> </li> <li>\u589e\u91cf\u6d4b\u8bd5\u3001\u6a21\u5757\u5316\u8bbe\u8ba1\u3001\u660e\u786e\u7684\u5047\u8bbe\u548c\u56e2\u961f\u5408\u4f5c</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#12","title":"1.2 \u7f16\u7a0b\u8981\u7d20","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#121","title":"1.2.1 \u8868\u8fbe\u5f0f","text":"<ul> <li>\u8bed\u8a00\u8981\u6709\u7684\u673a\u5236:<ul> <li>\u539f\u59cb\u8868\u8fbe\u5f0f\u548c\u8bed\u53e5\uff1a\u8bed\u8a00\u6240\u5173\u5fc3\u7684\u6700\u7b80\u5355\u7684\u4e2a\u4f53</li> <li>\u7ec4\u5408\u65b9\u6cd5\uff1a\u7531\u7b80\u5355\u5143\u7d20\u7ec4\u5408\u6784\u5efa\u590d\u5408\u5143\u7d20</li> <li>\u62bd\u8c61\u65b9\u6cd5\uff1a\u547d\u540d\u590d\u5408\u5143\u7d20\uff0c\u5e76\u5c06\u5176\u4f5c\u4e3a\u5355\u5143\u8fdb\u884c\u64cd\u4f5c  </li> </ul> </li> <li>infix notation</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#122","title":"1.2.2 \u8c03\u7528\u8868\u8fbe\u5f0f","text":"<ul> <li>subexpressions  </li> <li>\u7528\u53c2\u6570\u6765\u8c03\u7528\u51fd\u6570  </li> <li>nested\uff08\u5d4c\u5957\uff09</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#123","title":"1.2.3 \u5bfc\u5165\u5e93\u51fd\u6570","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#124","title":"1.2.4 \u540d\u79f0\u4e0e\u73af\u5883","text":"<ul> <li>= is assignment operator<ul> <li>\u6700\u7b80\u5355\u7684\u62bd\u8c61\u65b9\u6cd5</li> </ul> </li> <li>environment</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#125","title":"1.2.5 \u6c42\u89e3\u5d4c\u5957\u8868\u8fbe\u5f0f","text":"<p>\u6c42\u503c\u7a0b\u5e8f\u672c\u8d28\u4e0a\u662f\u9012\u5f52\u7684 </p> <ul> <li>\u8868\u8fbe\u5f0f\u6811</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#126-print","title":"1.2.6 \u975e\u7eaf\u51fd\u6570 print","text":"<p>Pure functions None-pure functions     which has a side effect</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#13","title":"1.3 \u5b9a\u4e49\u65b0\u7684\u51fd\u6570","text":"Python<pre><code>def &lt;name&gt;(&lt;formal parameters&gt;):\n    return &lt;return expression&gt;  \n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#131","title":"1.3.1 \u73af\u5883","text":"<p>environment has some frames     frames have some bindings</p> <ul> <li>intrinsic name</li> <li>bound name \u4e0d\u540c\u7684\u540d\u79f0\u53ef\u80fd\u6307\u7684\u662f\u540c\u4e00\u4e2a\u51fd\u6570\uff0c\u4f46\u8be5\u51fd\u6570\u672c\u8eab\u53ea\u6709\u4e00\u4e2a\u5185\u5728\u540d\u79f0 \u5bf9\u51fd\u6570\u5f62\u5f0f\u53c2\u6570\u7684\u63cf\u8ff0\u88ab\u79f0\u4e3a\u51fd\u6570\u7684\u7b7e\u540d</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#132","title":"1.3.2 \u8c03\u7528\u7528\u6237\u5b9a\u4e49\u7684\u51fd\u6570","text":"<ol> <li>\u5728\u65b0\u7684\u5c40\u90e8\u5e27\u4e2d\uff0c\u5c06\u5b9e\u53c2\u7ed1\u5b9a\u5230\u51fd\u6570\u7684\u5f62\u53c2\u4e0a\u3002</li> <li>\u5728\u4ee5\u6b64\u5e27\u5f00\u59cb\u7684\u73af\u5883\u4e2d\u6267\u884c\u51fd\u6570\u4f53\u3002 name evaluation</li> </ol>"},{"location":"CS_Basic/CS61A/Composing_Programs/#133","title":"1.3.3 \u793a\u4f8b\uff1a\u8c03\u7528\u7528\u6237\u5b9a\u4e49\u7684\u51fd\u6570","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#134","title":"1.3.4 \u5c40\u90e8\u540d\u79f0","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#135","title":"1.3.5 \u9009\u62e9\u540d\u79f0","text":"<p>PEP 8 \u2013 Style Guide for Python Code | peps.python.org</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#136","title":"1.3.6 \u62bd\u8c61\u51fd\u6570","text":"<ul> <li>functional abstraction<ul> <li>domain</li> <li>range</li> <li>intent</li> </ul> </li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#137","title":"1.3.7 \u8fd0\u7b97\u7b26","text":"<ul> <li>truediv</li> <li>floordiv</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#14","title":"1.4 \u8bbe\u8ba1\u51fd\u6570","text":"<ul> <li>\u4e00\u4e2a\u51fd\u6570\u4e00\u4e2a\u4efb\u52a1</li> <li>Don't repeat yourself (DRY)</li> <li>\u5b9a\u4e49\u901a\u7528\u7684\u51fd\u6570</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#141","title":"1.4.1 \u6587\u6863","text":"<p>docstring</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#142","title":"1.4.2 \u53c2\u6570\u9ed8\u8ba4\u503c","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#15","title":"1.5 \u63a7\u5236","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#151","title":"1.5.1 \u8bed\u53e5","text":"<ul> <li>assignment</li> <li>def </li> <li>return</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#152","title":"1.5.2 \u590d\u5408\u8bed\u53e5","text":"<p>header suite</p> Python<pre><code>&lt;header&gt;:\n    &lt;statement&gt;\n    &lt;statement&gt;\n    ...\n&lt;separating header&gt;:\n    &lt;statement&gt;\n    &lt;statement&gt;\n    ...\n...\n</code></pre> <p>def \u662f\u590d\u5408\u8bed\u53e5 the header controls its suite \u8fd9\u4e2a\u5b9a\u4e49\u63ed\u793a\u4e86\u9012\u5f52\u5b9a\u4e49\u5e8f\u5217\uff08sequence\uff09\u7684\u57fa\u672c\u7ed3\u6784\uff1a\u4e00\u4e2a\u5e8f\u5217\u53ef\u4ee5\u5206\u89e3\u6210\u5b83\u7684\u7b2c\u4e00\u4e2a\u5143\u7d20\u548c\u5176\u4f59\u5143\u7d20 redirected control</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#153-ii","title":"1.5.3 \u00a0\u5b9a\u4e49\u51fd\u6570 II\uff1a\u5c40\u90e8\u8d4b\u503c","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#154","title":"1.5.4 \u6761\u4ef6\u8bed\u53e5","text":"Python<pre><code>if &lt;expression&gt;:\n    &lt;suite&gt;\nelif &lt;expression&gt;:\n    &lt;suite&gt;\nelse:\n    &lt;suite&gt;\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#155","title":"1.5.5 \u8fed\u4ee3","text":"<p>iteractive control</p> Python<pre><code>while &lt;expression&gt;:\n    &lt;suite&gt;\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#156","title":"1.5.6 \u6d4b\u8bd5","text":"<p>assertions</p> Python<pre><code>&gt;&gt;&gt; assert fib(8) == 13, '\u7b2c\u516b\u4e2a\u6590\u6ce2\u90a3\u5951\u6570\u5e94\u8be5\u662f 13'\n</code></pre> <p>Doctests</p> Python<pre><code>&gt;&gt;&gt; def sum_naturals(n):\n    \"\"\"\u8fd4\u56de\u524d n \u4e2a\u81ea\u7136\u6570\u7684\u548c\u3002\n\n    &gt;&gt;&gt; sum_naturals(10)\n    55\n    &gt;&gt;&gt; sum_naturals(100)\n    5050\n    \"\"\"\n    total, k = 0, 1\n    while k &lt;= n:\n        total, k = total + k, k + 1\n    return total\n</code></pre> Python<pre><code>&gt;&gt;&gt; from doctest import testmod\n&gt;&gt;&gt; testmod()\nTestResults(failed=0, attempted=2)\n</code></pre> <p>\u5355\u4e2a\u51fd\u6570\u7684\u4ea4\u4e92</p> Python<pre><code>&gt;&gt;&gt; from doctest import run_docstring_examples\n&gt;&gt;&gt; run_docstring_examples(sum_naturals, globals(), True)\nFinding tests in NoName\nTrying:\n\u00a0\u00a0\u00a0 sum_naturals(10)\nExpecting:\n\u00a0\u00a0\u00a0 55\nok\nTrying:\n\u00a0\u00a0\u00a0 sum_naturals(100)\nExpecting:\n\u00a0\u00a0\u00a0 5050\nok\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#16","title":"1.6 \u9ad8\u9636\u51fd\u6570","text":"<ul> <li>general patterns  </li> <li>named concepts  </li> <li>higher-order functions  <ul> <li>\u53ef\u4ee5\u628a\u51fd\u6570\u5f53\u4f5c\u53c2\u6570\u6216\u8005\u8fd4\u56de\u503c</li> </ul> </li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#161","title":"1.6.1 \u4f5c\u4e3a\u53c2\u6570\u7684\u51fd\u6570","text":"<ul> <li>slots  </li> <li>step through \uff08\u5355\u6b65\u8c03\u8bd5\uff09  </li> <li>\u4e00\u4e2a\u51e0\u4e4e\u6ca1\u5fc5\u8981\u770b\u7684\u4f8b\u5b50:</li> </ul> Python<pre><code>&gt;&gt;&gt; def summation(n, term):\n        total, k = 0, 1\n        while k &lt;= n:\n            total, k = total + term(k), k + 1\n        return total\n&gt;&gt;&gt; def identity(x):\n        return x\n&gt;&gt;&gt; def sum_naturals(n):\n        return summation(n, identity)\n&gt;&gt;&gt; sum_naturals(10)\n55\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#162","title":"1.6.2 \u4f5c\u4e3a\u901a\u7528\u65b9\u6cd5\u7684\u51fd\u6570","text":"<ul> <li>user-defined functions  </li> <li>general methods  </li> <li>iterative improvement  </li> <li>repetitive refinement</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#163-iii","title":"1.6.3 \u5b9a\u4e49\u51fd\u6570 III\uff1a\u5d4c\u5957\u5b9a\u4e49","text":"<p>\u4e24\u4e2a\u540e\u679c:</p> <ul> <li>\u5168\u5c40\u5e27\u53d8\u6df7\u4e71</li> <li>\u51fd\u6570\u7b7e\u540d\u9650\u5236  </li> <li>Nested function definition  </li> <li>Lexical scope  <ul> <li>\u8fd9\u79cd\u5728\u5d4c\u5957\u5b9a\u4e49\u4e4b\u95f4\u5171\u4eab\u540d\u79f0\u7684\u89c4\u5219\u79f0\u4e3a\u8bcd\u6cd5\u4f5c\u7528\u57df</li> </ul> </li> </ul> <ol> <li>\u6bcf\u4e2a\u7528\u6237\u5b9a\u4e49\u7684\u51fd\u6570\u90fd\u6709\u4e00\u4e2a\u7236\u73af\u5883\uff1a\u5b9a\u4e49\u5b83\u7684\u73af\u5883\u3002</li> <li>\u8c03\u7528\u7528\u6237\u5b9a\u4e49\u7684\u51fd\u6570\u65f6\uff0c\u5176\u5c40\u90e8\u5e27\u4f1a\u7ee7\u627f\u5176\u7236\u73af\u5883\u3002</li> </ol> <ul> <li>\u5173\u952e\u4f18\u52bf:<ul> <li>\u5c40\u90e8\u51fd\u6570\u7684\u540d\u79f0\u4e0d\u4f1a\u5f71\u54cd\u5b9a\u4e49\u5b83\u7684\u51fd\u6570\u7684\u5916\u90e8\u540d\u79f0\uff0c\u56e0\u4e3a\u5c40\u90e8\u51fd\u6570\u7684\u540d\u79f0\u5c06\u7ed1\u5b9a\u5728\u5b9a\u4e49\u5b83\u7684\u5f53\u524d\u5c40\u90e8\u73af\u5883\u4e2d\uff0c\u800c\u4e0d\u662f\u5168\u5c40\u73af\u5883\u4e2d\u3002</li> <li>\u5c40\u90e8\u51fd\u6570\u53ef\u4ee5\u8bbf\u95ee\u5916\u5c42\u51fd\u6570\u7684\u73af\u5883\uff0c\u8fd9\u662f\u56e0\u4e3a\u5c40\u90e8\u51fd\u6570\u7684\u51fd\u6570\u4f53\u7684\u6c42\u503c\u73af\u5883\u4f1a\u7ee7\u627f\u5b9a\u4e49\u5b83\u7684\u6c42\u503c\u73af\u5883\u3002  </li> </ul> </li> <li>Extended Environments  </li> <li>\u5c40\u90e8\u5b9a\u4e49\u7684\u51fd\u6570\u901a\u5e38\u88ab\u79f0\u4e3a\u95ed\u5305\uff08closures\uff09</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#164","title":"1.6.4 \u4f5c\u4e3a\u8fd4\u56de\u503c\u7684\u51fd\u6570","text":"<ul> <li>composition</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#165","title":"1.6.5 \u793a\u4f8b\uff1a\u725b\u987f\u6cd5","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#166-currying","title":"1.6.6 Currying","text":"<ul> <li>uncurrying transformation</li> </ul> Python<pre><code>&gt;&gt;&gt; def curry2(f):\n        \"\"\"\u8fd4\u56de\u7ed9\u5b9a\u7684\u53cc\u53c2\u6570\u51fd\u6570\u7684\u67ef\u91cc\u5316\u7248\u672c\"\"\"\n        def g(x):\n            def h(y):\n                return f(x, y)\n            return h\n        return g\n&gt;&gt;&gt; def uncurry2(g):\n        \"\"\"\u8fd4\u56de\u7ed9\u5b9a\u7684\u67ef\u91cc\u5316\u51fd\u6570\u7684\u53cc\u53c2\u6570\u7248\u672c\"\"\"\n        def f(x, y):\n            return g(x)(y)\n        return f\n&gt;&gt;&gt; pow_curried = curry2(pow)\n&gt;&gt;&gt; pow_curried(2)(5)\n32\n&gt;&gt;&gt; map_to_range(0, 10, pow_curried(2))\n1\n2\n4\n8\n16\n32\n64\n128\n256\n512\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#167-lambda","title":"1.6.7 Lambda \u8868\u8fbe\u5f0f","text":"Python<pre><code>lambda              x         :              f(g(x))\n\"A function that    takes x   and returns    f(g(x))\"\n</code></pre> <p>\\(\\displaystyle \\lambda\\)</p> Python<pre><code>&gt;&gt;&gt; s = lambda x: x * x\n&gt;&gt;&gt; s\n&lt;function &lt;lambda&gt; at 0xf3f490&gt;\n&gt;&gt;&gt; s(12)\n144\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#168","title":"1.6.8 \u62bd\u8c61\u548c\u4e00\u7b49\u51fd\u6570","text":"<ul> <li>first-class status</li> </ul> <ol> <li>\u53ef\u4ee5\u4e0e\u540d\u79f0\u7ed1\u5b9a</li> <li>\u53ef\u4ee5\u4f5c\u4e3a\u53c2\u6570\u4f20\u9012\u7ed9\u51fd\u6570</li> <li>\u53ef\u4ee5\u4f5c\u4e3a\u51fd\u6570\u7684\u7ed3\u679c\u8fd4\u56de</li> <li>\u53ef\u4ee5\u5305\u542b\u5728\u6570\u636e\u7ed3\u6784\u4e2d</li> </ol>"},{"location":"CS_Basic/CS61A/Composing_Programs/#169","title":"1.6.9 \u51fd\u6570\u88c5\u9970\u5668","text":"<ul> <li>decorator</li> </ul> Python<pre><code>&gt;&gt;&gt; def trace(fn):\n        def wrapped(x):\n            print('-&gt; ', fn, '(', x, ')')\n            return fn(x)\n        return wrapped\n\n&gt;&gt;&gt; @trace\n    def triple(x):\n        return 3 * x\n\n&gt;&gt;&gt; triple(12)\n-&gt;  &lt;function triple at 0x102a39848&gt; ( 12 )\n36\n</code></pre> <ul> <li>annotation  </li> <li>\u7b49\u4ef7\u4e8e:</li> </ul> Python<pre><code>&gt;&gt;&gt; def triple(x):\n        return 3 * x\n&gt;&gt;&gt; triple = trace(triple)\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#17","title":"1.7 \u9012\u5f52\u51fd\u6570","text":"<ul> <li>rucursive  </li> <li>circular nature</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#171","title":"1.7.1 \u9012\u5f52\u51fd\u6570\u5256\u6790","text":"<ul> <li>base case  </li> <li>unwinds  </li> <li>recursive calls  </li> <li>induction</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#172-mutually-recursive","title":"1.7.2 mutually recursive","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#173","title":"1.7.3 \u9012\u5f52\u51fd\u6570\u4e2d\u7684\u6253\u5370","text":"<ul> <li>abstraction barrier</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#174-tree-recursive","title":"1.7.4 tree recursive","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#175","title":"1.7.5 \u793a\u4f8b\uff1a\u5206\u5272\u6570","text":"Python<pre><code>&gt;&gt;&gt; def count_partitions(n, m):\n\u00a0\u00a0\u00a0     \"\"\"\u8ba1\u7b97\u4f7f\u7528\u6700\u5927\u6570 m \u7684\u6574\u6570\u5206\u5272 n \u7684\u65b9\u5f0f\u7684\u6570\u91cf\"\"\"\n\u00a0\u00a0\u00a0     if n == 0:\n\u00a0\u00a0\u00a0         return 1\n\u00a0\u00a0\u00a0     elif n &lt; 0:\n\u00a0\u00a0\u00a0         return 0\n\u00a0\u00a0\u00a0     elif m == 0:\n\u00a0\u00a0\u00a0         return 0\n\u00a0\u00a0\u00a0     else:\n\u00a0\u00a0\u00a0         return count_partitions(n-m, m) + count_partitions(n, m-1)\n\n&gt;&gt;&gt; count_partitions(6, 4)\n9\n&gt;&gt;&gt; count_partitions(5, 5)\n7\n&gt;&gt;&gt; count_partitions(10, 10)\n42\n&gt;&gt;&gt; count_partitions(15, 15)\n176\n&gt;&gt;&gt; count_partitions(20, 20)\n627\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#2","title":"2 \u4f7f\u7528\u6570\u636e\u6784\u5efa\u62bd\u8c61","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#21","title":"2.1 \u5f15\u8a00","text":"<ul> <li>\u9ad8\u9636\u51fd\u6570\u4f7f\u6211\u4eec\u80fd\u591f\u6839\u636e\u901a\u7528\u7684\u8ba1\u7b97\u65b9\u6cd5\u8fdb\u884c\u64cd\u4f5c\u548c\u63a8\u7406\uff0c\u4ece\u800c\u589e\u5f3a\u4e86\u8bed\u8a00\u7684\u529f\u80fd\u3002\u8fd9\u5c31\u662f\u7f16\u7a0b\u7684\u672c\u8d28</li> <li>\u6709\u6548\u4f7f\u7528\u5185\u7f6e\u6570\u636e\u7c7b\u578b\u548c\u7528\u6237\u5b9a\u4e49\u7684\u6570\u636e\u7c7b\u578b\u662f\u6570\u636e\u5904\u7406\u578b\u5e94\u7528\uff08data processing applications\uff09\u7684\u57fa\u7840</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#211","title":"2.1.1 \u539f\u59cb\u6570\u636e\u7c7b\u578b","text":"<p>\u539f\u59cb\u6570\u636e\u7c7b\u578b\u5177\u6709\u5c5e\u6027:</p> <ol> <li>\u6709\u4e00\u4e9b\u53ef\u4ee5\u6c42\u89e3\u4e3a\u539f\u59cb\u6570\u636e\u7c7b\u578b\u7684\u8868\u8fbe\u5f0f\uff0c\u88ab\u79f0\u4e3a\u5b57\u9762\u91cf\uff08literals\uff09\u3002</li> <li>\u6709\u7528\u4e8e\u64cd\u4f5c\u539f\u59cb\u7c7b\u578b\u503c\u7684\u5185\u7f6e\u51fd\u6570\u548c\u64cd\u4f5c\u7b26\u3002 - \u539f\u59cb\u6570\u5b57\u7c7b\u578b<ul> <li>int</li> <li>float</li> <li>complex</li> <li>Non-numeric types</li> <li>bool</li> <li>more on \u539f\u59cb\u6570\u636e\u7c7b\u578b</li> </ul> </li> </ol>"},{"location":"CS_Basic/CS61A/Composing_Programs/#22","title":"2.2 \u6570\u636e\u62bd\u8c61","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#221","title":"2.2.1 \u793a\u4f8b\uff1a\u6709\u7406\u6570","text":"<p>wishful thinking</p> Python<pre><code>&gt;&gt;&gt; def add_rationals(x, y):\n        nx, dx = numer(x), denom(x)\n        ny, dy = numer(y), denom(y)\n        return rational(nx * dy + ny * dx, dx * dy)\n\n&gt;&gt;&gt; def mul_rationals(x, y):\n        return rational(numer(x) * numer(y), denom(x) * denom(y))\n\n&gt;&gt;&gt; def print_rational(x):\n        print(numer(x), '/', denom(x))\n\n&gt;&gt;&gt; def rationals_are_equal(x, y):\n        return numer(x) * denom(y) == numer(y) * denom(x)\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#222-pair","title":"2.2.2 pair","text":"<p>from operator import getitem</p> Python<pre><code>&gt;&gt;&gt; def rational(n, d):\n        return [n, d]\n\n&gt;&gt;&gt; def numer(x):\n        return x[0]\n\n&gt;&gt;&gt; def denom(x):\n        return x[1]\n</code></pre> <p>\u7b80\u5316\u6709\u7406\u6570:</p> Python<pre><code>&gt;&gt;&gt; from fractions import gcd\n&gt;&gt;&gt; def rational(n, d):\n        g = gcd(n, d)\n        return (n//g, d//g)\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#223","title":"2.2.3 \u62bd\u8c61\u5c4f\u969c","text":"<ul> <li>\u6570\u636e\u62bd\u8c61: \u7528\u4e00\u7ec4\u57fa\u672c\u64cd\u4f5c\u6765\u64cd\u4f5c\u6570\u636e\u3002  </li> <li>avbstraction barrier  </li> <li>the best:</li> </ul> Python<pre><code>&gt;&gt;&gt; def square_rational(x):\n    return mul_rational(x, x)\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#224","title":"2.2.4 \u6570\u636e\u7684\u5c5e\u6027","text":"<p>\u76f8\u5f53\u4e8e\u81ea\u5df1\u5199\u4e00\u4e2a\u6570\u636e\u7ed3\u6784:</p> Python<pre><code>&gt;&gt;&gt; def pair(x, y):\n        \"\"\"Return a function that represents a pair.\"\"\"\n        def get(index):\n            if index == 0:\n                return x\n            elif index == 1:\n                return y\n        return get\n\n&gt;&gt;&gt; def select(p, i):\n        \"\"\"Return the element at index i of pair p.\"\"\"\n        return p(i)\n\n&gt;&gt;&gt; p = pair(20, 14)\n&gt;&gt;&gt; select(p, 0)\n20\n&gt;&gt;&gt; select(p, 1)\n14\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#23","title":"2.3 \u5e8f\u5217","text":"<ul> <li>sequence<ul> <li>Length</li> <li>Element selection</li> </ul> </li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#231-list","title":"2.3.1 list","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#232","title":"2.3.2 \u5e8f\u5217\u904d\u5386","text":"Python<pre><code>for &lt;name&gt; in &lt;expression&gt;:\n    &lt;suite&gt;\n</code></pre> <p>the expression must produce an iterable object sequence unpacking</p> Python<pre><code>&gt;&gt;&gt; pairs = [[1, 2], [2, 2], [2, 3], [4, 4]]\n&gt;&gt;&gt; same_count = 0\n&gt;&gt;&gt; for x, y in pairs:\n        if x == y:\n            same_count = same_count + 1\n&gt;&gt;&gt; same_count\n2\n</code></pre> <p>range</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#233","title":"2.3.3 \u5e8f\u5217\u5904\u7406","text":"<p>list comprehensions</p> Python<pre><code>&gt;&gt;&gt; odds = [1, 3, 5, 7, 9]\n&gt;&gt;&gt; [x+1 for x in odds]\n[2, 4, 6, 8, 10]\n[&lt;map expression&gt; for &lt;name&gt; in &lt;sequence expression&gt; if &lt;filter expression&gt;]\n</code></pre> <ul> <li>Aggregation \u5c31\u662f\u7f29\u5e76\u5566<ul> <li>sum</li> <li>min</li> <li>max</li> </ul> </li> </ul> Python<pre><code>&gt;&gt;&gt; def apply_to_all(map_fn, s):\n    return [map_fn(x) for x in s]\n&gt;&gt;&gt; def keep_if(filter_fn, s):\n    return [x for x in s if filter_fn(x)]\n# conventional names\n&gt;&gt;&gt; apply_to_all = lambda map_fn, s: list(map(map_fn, s))\n&gt;&gt;&gt; keep_if = lambda filter_fn, s: list(filter(filter_fn, s))\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#234","title":"2.3.4 \u5e8f\u5217\u62bd\u8c61","text":"<ul> <li>Membership<ul> <li>in</li> <li>not in</li> </ul> </li> <li>Slicing</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#235","title":"2.3.5 \u5b57\u7b26\u4e32","text":"<p>string \u6ca1\u6709\u5b57\u7b26\u7c7b\u578b</p> <ul> <li>Membership</li> <li>Multiline Literals</li> <li>String Coercion more on Dive Into Python 3\u00a0\u7684\u00a0\u5b57\u7b26\u4e32\u7ae0\u8282\u00a0\u63d0\u4f9b\u4e86\u5b57\u7b26\u7f16\u7801\u548c Unicode \u7684\u63cf\u8ff0</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#236","title":"2.3.6 \u6811","text":"<p>closure property bax-and-pointer notation</p> <ul> <li>root label</li> <li>branch</li> <li>leaf: the tree without branch</li> <li>node tree-recursive \u4e24\u4e2a\u4f8b\u5b50:</li> </ul> Python<pre><code>&gt;&gt;&gt; def fib_tree(n):\n        if n == 0 or n == 1:\n            return tree(n)\n        else:\n            left, right = fib_tree(n-2), fib_tree(n-1)\n            fib_n = label(left) + label(right)\n            return tree(fib_n, [left, right])\n&gt;&gt;&gt; fib_tree(5)\n[5, [2, [1], [1, [0], [1]]], [3, [1, [0], [1]], [2, [1], [1, [0], [1]]]]]\n</code></pre> Python<pre><code>&gt;&gt;&gt; def count_leaves(tree):\n      if is_leaf(tree):\n          return 1\n      else:\n          branch_counts = [count_leaves(b) for b in branches(tree)]\n          return sum(branch_counts)\n&gt;&gt;&gt; count_leaves(fib_tree(5))\n8\n</code></pre> <p>Partition trees</p> Python<pre><code>&gt;&gt;&gt; def print_parts(tree, partition=[]):\n        if is_leaf(tree):\n            if label(tree):\n                print(' + '.join(partition))\n        else:\n            left, right = branches(tree)\n            m = str(label(tree))\n            print_parts(left, partition + [m])\n            print_parts(right, partition)\n\n&gt;&gt;&gt; print_parts(partition_tree(6, 4))\n4 + 2\n4 + 1 + 1\n3 + 3\n3 + 2 + 1\n3 + 1 + 1 + 1\n2 + 2 + 2\n2 + 2 + 1 + 1\n2 + 1 + 1 + 1 + 1\n1 + 1 + 1 + 1 + 1 + 1\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#237","title":"2.3.7 \u94fe\u8868","text":"<p>linked list abstract data representation</p> Python<pre><code>&gt;&gt;&gt; def partitions(n, m):\n\"\"\"\u8fd4\u56de\u4e00\u4e2a\u5305\u542b n \u7684\u5206\u5272\u65b9\u6848\u7684\u94fe\u8868\uff0c\u5176\u4e2d\u6bcf\u4e2a\u6b63\u6574\u6570\u4e0d\u8d85\u8fc7 m\"\"\"\nif n == 0:\n    return link(empty, empty) # \u5305\u542b\u7a7a\u5206\u5272\u7684\u94fe\u8868\nelif n &lt; 0 or m == 0:\n    return empty\nelse:\n    using_m = partitions(n-m, m)\n    with_m = apply_to_all_link(lambda s: link(m, s), using_m)\n    without_m = partitions(n, m-1)\n    return extend_link(with_m, without_m)\n\n&gt;&gt;&gt; def print_partitions(n, m):\n        lists = partitions(n, m)\n        strings = apply_to_all_link(lambda s: join_link(s, \" + \"), lists)\n        print(join_link(strings, \"\\n\"))\n\n&gt;&gt;&gt; print_partitions(6, 4)\n4 + 2\n4 + 1 + 1\n3 + 3\n3 + 2 + 1\n3 + 1 + 1 + 1\n2 + 2 + 2\n2 + 2 + 1 + 1\n2 + 1 + 1 + 1 + 1\n1 + 1 + 1 + 1 + 1 + 1\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#24","title":"2.4 \u53ef\u53d8\u6570\u636e","text":"<p>object-oriented programming</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#241","title":"2.4.1 \u5bf9\u8c61\u9690\u55bb","text":"<ul> <li>attributes</li> <li>method</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#242","title":"2.4.2 \u5e8f\u5217\u5bf9\u8c61","text":"<p>mutable Sharing and Identity \u5217\u8868\u63a8\u5bfc\u5f0f:</p> Python<pre><code>&gt;&gt;&gt; from unicodedata import lookup\n&gt;&gt;&gt; [lookup('WHITE ' + s.upper() + ' SUIT') for s in suits]\n['\u2661', '\u2662', '\u2664', '\u2667']\n</code></pre> <p>tuple</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#243","title":"2.4.3 \u5b57\u5178","text":"<p>key-value pairs</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#244","title":"2.4.4 \u5c40\u90e8\u72b6\u6001","text":"<p>local state</p> Python<pre><code>&gt;&gt;&gt; def make_withdraw(balance):\n\"\"\"\u8fd4\u56de\u4e00\u4e2a\u6bcf\u6b21\u8c03\u7528\u90fd\u4f1a\u51cf\u5c11 balance \u7684 withdraw \u51fd\u6570\"\"\"\ndef withdraw(amount):\n    nonlocal balance                 # \u58f0\u660e balance \u662f\u975e\u5c40\u90e8\u7684\n    if amount &gt; balance:\n        return '\u4f59\u989d\u4e0d\u8db3'\n    balance = balance - amount       # \u91cd\u65b0\u7ed1\u5b9a\n    return balance\nreturn withdraw\n</code></pre> <p>Python Particulars</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#245-non-local","title":"2.4.5 \u975e\u5c40\u90e8 Non-local \u8d4b\u503c\u7684\u597d\u5904","text":"<p>\u8fd9\u6837\uff0c\u6bcf\u4e2a withdraw \u5b9e\u4f8b\u90fd\u4fdd\u6301\u81ea\u5df1\u7684 balance \u72b6\u6001\uff0c\u4f46\u7a0b\u5e8f\u4e2d\u7684\u4efb\u4f55\u5176\u4ed6\u51fd\u6570\u90fd\u65e0\u6cd5\u8bbf\u95ee\u8be5\u72b6\u6001\u3002\u4ece\u66f4\u9ad8\u7684\u5c42\u9762\u6765\u770b\u8fd9\u79cd\u60c5\u51b5\uff0c\u6211\u4eec\u62bd\u8c61\u4e86\u4e00\u4e2a\u94f6\u884c\u8d26\u6237\uff0c\u5b83\u81ea\u5df1\u7ba1\u7406\u81ea\u5df1\u7684\u72b6\u6001\uff0c\u5176\u884c\u4e3a\u65b9\u5f0f\u4e0e\u4e16\u754c\u4e0a\u6240\u6709\u5176\u5b83\u8d26\u6237\u4e00\u6837\uff1a\u968f\u7740\u65f6\u95f4\u63a8\u79fb\uff0c\u8d26\u6237\u7684\u72b6\u6001\u4f1a\u6839\u636e\u8d26\u6237\u7684\u53d6\u6b3e\u8bb0\u5f55\u800c\u53d1\u751f\u53d8\u5316\u3002</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#246-non-local","title":"2.4.6 \u975e\u5c40\u90e8 Non-local \u8d4b\u503c\u7684\u4ee3\u4ef7","text":"<ul> <li>\u6b63\u786e\u7406\u89e3\u5305\u542b nonlocal \u58f0\u660e\u7684\u4ee3\u7801\u7684\u5173\u952e\u662f\u8bb0\u4f4f\uff1a\u53ea\u6709\u51fd\u6570\u8c03\u7528\u624d\u80fd\u5f15\u5165\u65b0\u5e27\u3002\u8d4b\u503c\u8bed\u53e5\u53ea\u80fd\u66f4\u6539\u73b0\u6709\u5e27\u4e2d\u7684\u7ed1\u5b9a\u5173\u7cfb\u3002\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u9664\u975e make_withdraw \u88ab\u8c03\u7528\u4e24\u6b21\uff0c\u5426\u5219\u53ea\u80fd\u6709\u4e00\u4e2a balance \u7ed1\u5b9a\u3002  </li> <li>Sameness and change  </li> <li>referentially transparent</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#247","title":"2.4.7 \u5217\u8868\u548c\u5b57\u5178\u5b9e\u73b0","text":"<p>\u51fd\u6570\u662f\u4e00\u4e2a dispatch \uff08\u8c03\u5ea6\uff09\u51fd\u6570\uff0c\u5176\u53c2\u6570\u9996\u5148\u662f\u4e00\u4e2a\u671f\u671b\u7684\u6307\u4ee4\uff0c\u4ee3\u8868\u671f\u671b\u8fd9\u4e2a\u51fd\u6570\u505a\u4ec0\u4e48\uff1b\u7136\u540e\u662f\u8be5\u65b9\u6cd5\u7684\u9700\u8981\u7528\u5230\u7684\u53c2\u6570\u3002\u6b64\u6307\u4ee4\u662f\u4e00\u4e2a\u5b57\u7b26\u4e32\uff0c\u7528\u4e8e\u547d\u540d\u51fd\u6570\u5e94\u6267\u884c\u7684\u64cd\u4f5c\u3002\u53ef\u4ee5\u5c06\u8fd9\u4e2a dispatch \u51fd\u6570\u7406\u89e3\u4e3a\u591a\u4e2a\u4e0d\u540c\u51fd\u6570\u7684\u62bd\u8c61\uff1a\u7b2c\u4e00\u4e2a\u53c2\u6570\u786e\u5b9a\u76ee\u6807\u51fd\u6570\u7684\u884c\u4e3a\uff0c\u5e76\u4e3a\u8be5\u884c\u4e3a\u5165\u53c2\u5176\u4ed6\u53c2\u6570\u3002     \u7528\u5b57\u7b26\u4e32\u4e5f\u592a\u9006\u5929\u4e86\u3002</p> Python<pre><code>&gt;&gt;&gt; def mutable_link():\n\"\"\"\u8fd4\u56de\u4e00\u4e2a\u53ef\u53d8\u94fe\u8868\u7684\u51fd\u6570\"\"\"\ncontents = empty\ndef dispatch(message, value=None):\n    nonlocal contents\n    if message == 'len':\n        return len_link(contents)\n    elif message == 'getitem':\n        return getitem_link(contents, value)\n    elif message == 'push_first':\n        contents = link(value, contents)\n    elif message == 'pop_first':\n        f = first(contents)\n        contents = rest(contents)\n        return f\n    elif message == 'str':\n        return join_link(contents, \", \")\nreturn dispatch\n\n&gt;&gt;&gt; def to_mutable_link(source):\n\"\"\"\u8fd4\u56de\u4e00\u4e2a\u4e0e\u539f\u5217\u8868\u76f8\u540c\u5185\u5bb9\u7684\u51fd\u6570\u5217\u8868\"\"\"\ns = mutable_link()\nfor element in reversed(source):\n    s('push_first', element)\nreturn s\n\n&gt;&gt;&gt; s = to_mutable_link(suits)\n&gt;&gt;&gt; type(s)\n&lt;class 'function'&gt;\n&gt;&gt;&gt; print(s('str'))\nheart, diamond, spade, club\n</code></pre> <p>\u5b57\u5178\u5b9e\u73b0:</p> Python<pre><code>&gt;&gt;&gt; def dictionary():\n\"\"\"\u8fd4\u56de\u4e00\u4e2a\u5b57\u5178\u7684\u51fd\u6570\u5b9e\u73b0\"\"\"\nrecords = []\ndef getitem(key):\n    matches = [r for r in records if r[0] == key]\n    if len(matches) == 1:\n        key, value = matches[0]\n        return value\ndef setitem(key, value):\n    nonlocal records\n    non_matches = [r for r in records if r[0] != key]\n    records = non_matches + [[key, value]]\ndef dispatch(message, key=None, value=None):\n    if message == 'getitem':\n        return getitem(key)\n    elif message == 'setitem':\n        setitem(key, value)\nreturn dispatch\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#248-dispatch-dictionaries","title":"2.4.8 \u8c03\u5ea6\u5b57\u5178\uff08Dispatch Dictionaries\uff09","text":"<p>\u7528\u5b57\u5178\u5b58\u50a8\u6d88\u606f\u3002</p> Python<pre><code>def account(initial_balance):\n    def deposit(amount):\n        dispatch['balance'] += amount\n        return dispatch['balance']\n    def withdraw(amount):\n        if amount &gt; dispatch['balance']:\n            return 'Insufficient funds'\n        dispatch['balance'] -= amount\n        return dispatch['balance']\n    dispatch = {'deposit':   deposit,\n                'withdraw':  withdraw,\n                'balance':   initial_balance}\n    return dispatch\n\ndef withdraw(account, amount):\n    return account['withdraw'](amount)\ndef deposit(account, amount):\n    return account['deposit'](amount)\ndef check_balance(account):\n    return account['balance']\n\na = account(20)\ndeposit(a, 5)\nwithdraw(a, 17)\ncheck_balance(a)\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#249-propagating-constraints","title":"2.4.9 \u7ea6\u675f\u4f20\u9012 (Propagating\u00a0Constraints)","text":"<p>connector Using the Constraint System</p> Python<pre><code>&gt;&gt;&gt; celsius = connector('Celsius')\n&gt;&gt;&gt; fahrenheit = connector('Fahrenheit')\n&gt;&gt;&gt; def converter(c, f):\n    \"\"\"\u7528\u7ea6\u675f\u6761\u4ef6\u8fde\u63a5 c \u5230 f\uff0c\u5c06\u6444\u6c0f\u5ea6\u8f6c\u6362\u4e3a\u534e\u6c0f\u5ea6.\"\"\"\n    u, v, w, x, y = [connector() for _ in range(5)]\n    multiplier(c, w, u)\n    multiplier(v, x, u)\n    adder(v, y, f)\n    constant(w, 9)\n    constant(x, 5)\n    constant(y, 32)\n&gt;&gt;&gt; converter(celsius, fahrenheit)\n\n&gt;&gt;&gt; celsius['set_val']('user', 25)\nCelsius = 25\nFahrenheit = 77.0\n\n&gt;&gt;&gt; fahrenheit['set_val']('user', 212)\nContradiction detected: 77.0 vs 212\n\n&gt;&gt;&gt; celsius['forget']('user')\nCelsius is forgotten\nFahrenheit is forgotten\n\n&gt;&gt;&gt; fahrenheit['set_val']('user', 212)\nFahrenheit = 212\nCelsius = 100.0\n\n# Implementing the Constraint System\n&gt;&gt;&gt; connector ['set_val'](source, value)  \"\"\"\u8868\u793a\u00a0source\u00a0\u5728\u8bf7\u6c42\u8fde\u63a5\u5668\u5c06\u5f53\u524d\u503c\u8bbe\u4e3a value\"\"\"\n&gt;&gt;&gt; connector ['has_val']()\u00a0 \"\"\"\u8fd4\u56de\u8fde\u63a5\u5668\u662f\u5426\u5df2\u7ecf\u5177\u6709\u503c\"\"\"\n&gt;&gt;&gt; connector ['val']  \"\"\"\u662f\u8fde\u63a5\u5668\u7684\u5f53\u524d\u503c\"\"\"\n&gt;&gt;&gt; connector ['forget'](source)\u00a0 \"\"\"\u544a\u8bc9\u8fde\u63a5\u5668 source \u8bf7\u6c42\u9057\u5fd8\u5b83\u7684\u503c\"\"\"\n&gt;&gt;&gt; connector ['connect'](source)\u00a0 \"\"\"\u544a\u8bc9\u8fde\u63a5\u5668\u53c2\u4e0e\u65b0\u7684\u7ea6\u675f\uff0c\u5373 source\"\"\"\n&gt;&gt;&gt; constraint['new_val']()  \"\"\"\u8868\u793a\u4e0e\u7ea6\u675f\u76f8\u8fde\u7684\u67d0\u4e2a\u8fde\u63a5\u5668\u5177\u6709\u65b0\u7684\u503c\u3002\"\"\"\n&gt;&gt;&gt; constraint['forget']()\u00a0 \"\"\"\u8868\u793a\u4e0e\u7ea6\u675f\u76f8\u8fde\u7684\u67d0\u4e2a\u8fde\u63a5\u5668\u9057\u5fd8\u4e86\u503c\u3002\"\"\"\n\n&gt;&gt;&gt; from operator import add, sub\n&gt;&gt;&gt; def adder(a, b, c):\n        \"\"\"\u7ea6\u675f a+b=c\"\"\"\n        return make_ternary_constraint(a, b, c, add, sub, sub)\n\n&gt;&gt;&gt; def make_ternary_constraint(a, b, c, ab, ca, cb):\n    \"\"\"\u7ea6\u675f ab(a,b)=c\uff0cca(c,a)=b\uff0ccb(c,b)=a\"\"\"\n    def new_value():\n        av, bv, cv = [connector['has_val']() for connector in (a, b, c)]\n        if av and bv:\n            c['set_val'](constraint, ab(a['val'], b['val']))\n        elif av and cv:\n            b['set_val'](constraint, ca(c['val'], a['val']))\n        elif bv and cv:\n            a['set_val'](constraint, cb(c['val'], b['val']))\n    def forget_value():\n        for connector in (a, b, c):\n            connector['forget'](constraint)\n    constraint = {'new_val': new_value, 'forget': forget_value}\n    for connector in (a, b, c):\n        connector['connect'](constraint)\n    return constraint\n\n&gt;&gt;&gt; from operator import mul, truediv\n&gt;&gt;&gt; def multiplier(a, b, c):\n        \"\"\"\u7ea6\u675f a*b=c\"\"\"\n        return make_ternary_constraint(a, b, c, mul, truediv, truediv)\n\n&gt;&gt;&gt; def constant(connector, value):\n    \"\"\"\u5e38\u91cf\u8d4b\u503c\"\"\"\n    constraint = {}\n    connector['set_val'](constraint, value)\n    return constraint\n\n# Representing connectors\n&gt;&gt;&gt; def connector(name=None):\n    \"\"\"\u9650\u5236\u6761\u4ef6\u4e4b\u95f4\u7684\u8fde\u63a5\u5668\"\"\"\n    informant = None\n    constraints = []\n    def set_value(source, value):\n        nonlocal informant\n        val = connector['val']\n        if val is None:\n            informant, connector['val'] = source, value\n            if name is not None:\n                print(name, '=', value)\n            inform_all_except(source, 'new_val', constraints)\n        else:\n            if val != value:\n                print('Contradiction detected:', val, 'vs', value)\n    def forget_value(source):\n        nonlocal informant\n        if informant == source:\n            informant, connector['val'] = None, None\n            if name is not None:\n                print(name, 'is forgotten')\n            inform_all_except(source, 'forget', constraints)\n    connector = {'val': None,\n                 'set_val': set_value,\n                 'forget': forget_value,\n                 'has_val': lambda: connector['val'] is not None,\n                 'connect': lambda source: constraints.append(source)}\n    return connector\n\n&gt;&gt;&gt; def inform_all_except(source, message, constraints):\n    \"\"\"\u544a\u77e5\u4fe1\u606f\u9664\u4e86 source \u5916\u7684\u6240\u6709\u7ea6\u675f\u6761\u4ef6\"\"\"\n    for c in constraints:\n        if c != source:\n            c[message]()\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#25","title":"2.5 \u9762\u5411\u5bf9\u8c61\u7f16\u7a0b","text":"<ul> <li>object</li> <li>dot notation</li> <li>class</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#251","title":"2.5.1 \u5bf9\u8c61\u548c\u7c7b","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#252","title":"2.5.2 \u7c7b\u7684\u5b9a\u4e49","text":"<p>__init__\u7c7b\u7684\u6784\u9020\u51fd\u6570\uff08constructor\uff09</p> Python<pre><code>&gt;&gt;&gt; class Account:\n        def __init__(self, account_holder):\n            self.balance = 0\n            self.holder = account_holder\n        def deposit(self, amount):\n            self.balance = self.balance + amount\n            return self.balance\n        def withdraw(self, amount):\n            if amount &gt; self.balance:\n                return 'Insufficient funds'\n            self.balance = self.balance - amount\n            return self.balance\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#253","title":"2.5.3 \u6d88\u606f\u4f20\u9012\u548c\u70b9\u8868\u8fbe\u5f0f","text":"Python<pre><code>&gt;&gt;&gt; getattr(spock_account, 'balance')\n10\n&gt;&gt;&gt; hasattr(spock_account, 'deposit')\nTrue\n\n\n&gt;&gt;&gt; type(Account.deposit)\n&lt;class 'Function'&gt;\n&gt;&gt;&gt; type(spock_account.deposit)\n&lt;class 'method'&gt;\n# \u4e3a\u7c7b\u7684\u5c5e\u6027\uff0c\u65b9\u6cd5\u53ea\u662f\u4e00\u4e2a\u51fd\u6570\uff0c\u4f46\u4f5c\u4e3a\u5b9e\u4f8b\u7684\u5c5e\u6027\uff0c\u5b83\u662f\u4e00\u4e2a\u7ed1\u5b9a\u65b9\u6cd5\n\n&gt;&gt;&gt; Account.deposit(spock_account, 1001)    # \u51fd\u6570 deposit \u63a5\u53d7\u4e24\u4e2a\u53c2\u6570\n1011\n&gt;&gt;&gt; spock_account.deposit(1000)             # \u65b9\u6cd5 deposit \u63a5\u53d7\u4e00\u4e2a\u53c2\u6570\n2011\n</code></pre> <p>\u547d\u540d\u7ea6\u5b9a\uff1a\u7c7b\u540d\u901a\u5e38\u4f7f\u7528 CapWords \u7ea6\u5b9a\uff08\u4e5f\u79f0\u4e3a CamelCase\uff0c\u56e0\u4e3a\u540d\u79f0\u4e2d\u95f4\u7684\u5927\u5199\u5b57\u6bcd\u770b\u8d77\u6765\u50cf\u9a7c\u5cf0\uff09\u7f16\u5199\u3002\u65b9\u6cd5\u540d\u79f0\u9075\u5faa\u4f7f\u7528\u4e0b\u5212\u7ebf\u5206\u9694\u7684\u5c0f\u5199\u5355\u8bcd\u547d\u540d\u51fd\u6570\u7684\u6807\u51c6\u7ea6\u5b9a\u3002</p> <p>\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u6709\u4e00\u4e9b\u5b9e\u4f8b\u53d8\u91cf\u548c\u65b9\u6cd5\u4e0e\u5bf9\u8c61\u7684\u7ef4\u62a4\u548c\u4e00\u81f4\u6027\u76f8\u5173\uff0c\u6211\u4eec\u4e0d\u5e0c\u671b\u5bf9\u8c61\u7684\u7528\u6237\u770b\u5230\u6216\u4f7f\u7528\u3002\u5b83\u4eec\u4e0d\u662f\u7c7b\u5b9a\u4e49\u7684\u62bd\u8c61\u7684\u4e00\u90e8\u5206\uff0c\u800c\u662f\u5b9e\u73b0\u7684\u4e00\u90e8\u5206\u3002Python \u7684\u7ea6\u5b9a\u89c4\u5b9a\uff0c\u5982\u679c\u5c5e\u6027\u540d\u79f0\u4ee5\u4e0b\u5212\u7ebf\u5f00\u5934\uff0c\u5219\u53ea\u80fd\u5728\u7c7b\u672c\u8eab\u7684\u65b9\u6cd5\u4e2d\u8bbf\u95ee\u5b83\uff0c\u800c\u4e0d\u662f\u7528\u6237\u8bbf\u95ee\u3002</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#254","title":"2.5.4 \u7c7b\u5c5e\u6027","text":"<p>\u611f\u89c9\u6ca1\u4ec0\u4e48\u7528:</p> Python<pre><code>&gt;&gt;&gt; Account.interest = 0.05     # \u6539\u53d8\u7c7b\u5c5e\u6027\n&gt;&gt;&gt; spock_account.interest      # \u5b9e\u4f8b\u5c5e\u6027\u53d1\u751f\u53d8\u5316\uff08\u8be5\u5b9e\u4f8b\u4e2d\u6ca1\u6709\u548c\u7c7b\u5c5e\u6027\u540c\u540d\u79f0\u7684\u5b9e\u4f8b\u5c5e\u6027\uff09\n0.05\n&gt;&gt;&gt; kirk_account.interest       # \u5982\u679c\u5b9e\u4f8b\u4e2d\u5b58\u5728\u548c\u7c7b\u5c5e\u6027\u540c\u540d\u7684\u5b9e\u4f8b\u5c5e\u6027\uff0c\u5219\u6539\u53d8\u7c7b\u5c5e\u6027\uff0c\u4e0d\u4f1a\u5f71\u54cd\u5b9e\u4f8b\u5c5e\u6027\n0.08\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#255","title":"2.5.5 \u7ee7\u627f","text":"<ul> <li>base class<ul> <li>parent class</li> <li>super class</li> </ul> </li> <li>subcladd<ul> <li>child class</li> </ul> </li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#256","title":"2.5.6 \u4f7f\u7528\u7ee7\u627f","text":"Python<pre><code>&gt;&gt;&gt; class Account:\n        \"\"\"\u4e00\u4e2a\u4f59\u989d\u975e\u96f6\u7684\u8d26\u6237\u3002\"\"\"\n        interest = 0.02\n        def __init__(self, account_holder):\n            self.balance = 0\n            self.holder = account_holder\n        def deposit(self, amount):\n            \"\"\"\u5b58\u5165\u8d26\u6237 amount\uff0c\u5e76\u8fd4\u56de\u53d8\u5316\u540e\u7684\u4f59\u989d\"\"\"\n            self.balance = self.balance + amount\n            return self.balance\n        def withdraw(self, amount):\n            \"\"\"\u4ece\u8d26\u53f7\u4e2d\u53d6\u51fa amount\uff0c\u5e76\u8fd4\u56de\u53d8\u5316\u540e\u7684\u4f59\u989d\"\"\"\n            if amount &gt; self.balance:\n                return 'Insufficient funds'\n            self.balance = self.balance - amount\n            return self.balance\n\n&gt;&gt;&gt; class CheckingAccount(Account):\n        \"\"\"\u4ece\u8d26\u53f7\u53d6\u94b1\u4f1a\u6263\u51fa\u624b\u7eed\u8d39\u7684\u8d26\u53f7\"\"\"\n           withdraw_charge = 1\n           interest = 0.01\n           def withdraw(self, amount):\n                 return Account.withdraw(self, amount + self.withdraw_charge)\n</code></pre> <p>\u63a5\u53e3</p> Python<pre><code>&gt;&gt;&gt; def deposit_all(winners, amount=5):\n        for account in winners:\n            account.deposit(amount)         # \u8fd9\u91cc\u8c03\u7528\u7684\u662f\u5b9e\u4f8b account \u7684 deposit \u65b9\u6cd5\n            # \u5bf9\u4e8e\u4e0d\u540c\u5b9e\u4f8b\u6765\u8bf4\uff0c\u5b83\u4eec\u7684 deposit \u65b9\u6cd5\u53ef\u80fd\u4e0d\u540c\u3002\u8fd9\u4e2a\u4f8b\u5b50\u76f8\u5bf9\u4e8e\u4e0b\u9762\u6765\u8bb2\uff0c\u66f4\u52a0\u5177\u6709\u5065\u58ee\u6027\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#257","title":"2.5.7 \u591a\u7ee7\u627f","text":"<p>\u7ee7\u627f\u6392\u5e8f\u95ee\u9898\u6ca1\u6709\u6b63\u786e\u7684\u89e3\u51b3\u65b9\u6848\uff0c\u56e0\u4e3a\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u6211\u4eec\u53ef\u80fd\u66f4\u613f\u610f\u5c06\u67d0\u4e9b\u7ee7\u627f\u7c7b\u7f6e\u4e8e\u5176\u4ed6\u7c7b\u4e4b\u4e0a\u3002\u4f46\u662f\uff0c\u4efb\u4f55\u652f\u6301\u591a\u91cd\u7ee7\u627f\u7684\u7f16\u7a0b\u8bed\u8a00\u90fd\u5fc5\u987b\u4ee5\u4e00\u81f4\u7684\u65b9\u5f0f\u9009\u62e9\u67d0\u4e9b\u6392\u5e8f\uff0c\u4ee5\u4fbf\u8be5\u8bed\u8a00\u7684\u7528\u6237\u53ef\u4ee5\u9884\u6d4b\u5176\u7a0b\u5e8f\u7684\u884c\u4e3a\u3002</p> <p>\u8fdb\u4e00\u6b65\u9605\u8bfb\u3002Python \u4f7f\u7528\u79f0\u4e3a C3 \u65b9\u6cd5\u89e3\u6790\u6392\u5e8f\u7684\u9012\u5f52\u7b97\u6cd5\u89e3\u6790\u6b64\u540d\u79f0\u3002\u53ef\u4ee5\u5728\u6240\u6709\u7c7b\u4e0a\u4f7f\u7528\u00a0<code>mro</code>\u00a0\u65b9\u6cd5\u67e5\u8be2\u4efb\u4f55\u7c7b\u7684\u65b9\u6cd5\u89e3\u6790\u987a\u5e8f\u3002</p> Python<pre><code>&gt;&gt;&gt; [c.__name__ for c in AsSeenOnTVAccount.mro()]\n['AsSeenOnTVAccount', 'CheckingAccount', 'SavingsAccount', 'Account', 'object']\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#258","title":"2.5.8 \u5bf9\u8c61\u7684\u4f5c\u7528","text":"<p>\u53e6\u4e00\u65b9\u9762\uff0c\u7c7b\u53ef\u80fd\u4e0d\u662f\u5b9e\u73b0\u67d0\u4e9b\u62bd\u8c61\u7684\u6700\u4f73\u673a\u5236\u3002\u51fd\u6570\u5f0f\u62bd\u8c61\u63d0\u4f9b\u4e86\u4e00\u4e2a\u66f4\u81ea\u7136\u7684\u9690\u55bb\u6765\u8868\u793a\u8f93\u5165\u548c\u8f93\u51fa\u4e4b\u95f4\u7684\u5173\u7cfb\u3002\u6211\u4eec\u4e0d\u5e94\u8be5\u89c9\u5f97\u5fc5\u987b\u5c06\u7a0b\u5e8f\u4e2d\u7684\u6bcf\u4e00\u70b9\u903b\u8f91\u90fd\u585e\u8fdb\u4e00\u4e2a\u7c7b\u4e2d\uff0c\u5c24\u5176\u662f\u5728\u5b9a\u4e49\u72ec\u7acb\u51fd\u6570\u6765\u64cd\u4f5c\u6570\u636e\u66f4\u81ea\u7136\u7684\u60c5\u51b5\u4e0b\u3002\u51fd\u6570\u8fd8\u53ef\u4ee5\u5f3a\u5236\u5b9e\u73b0\u5173\u6ce8\u70b9\u7684\u5206\u79bb\u3002\u6362\u53e5\u8bdd\u8bf4\uff0c\u51fd\u6570\u5f0f\u7f16\u7a0b\u63d0\u4f9b\u4e86\u53e6\u4e00\u79cd\u6709\u6548\u5730\u7ec4\u7ec7\u7a0b\u5e8f\u903b\u8f91\u7684\u65b9\u6cd5\uff0c\u4f7f\u5f97\u7a0b\u5e8f\u5458\u80fd\u591f\u66f4\u597d\u5730\u5904\u7406\u548c\u7ef4\u62a4\u7a0b\u5e8f\u3002\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u4f7f\u7528\u51fd\u6570\u5f0f\u7f16\u7a0b\u65b9\u6cd5\u53ef\u80fd\u6bd4\u4f7f\u7528\u9762\u5411\u5bf9\u8c61\u7f16\u7a0b\u66f4\u81ea\u7136\u548c\u6709\u6548\u3002</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#26","title":"2.6 \u5b9e\u73b0\u7c7b\u548c\u5bf9\u8c61","text":"<p>object-oriented programming paradigm \u5373\u4f7f\u5728\u6ca1\u6709\u5185\u7f6e\u5bf9\u8c61\u7cfb\u7edf\u7684\u7f16\u7a0b\u8bed\u8a00\u4e2d\uff0c\u7a0b\u5e8f\u4e5f\u53ef\u4ee5\u662f\u9762\u5411\u5bf9\u8c61\u7684\u3002 \u653e\u5f03\u70b9\u8868\u793a\u6cd5-&gt;\u8c03\u5ea6\u5b57\u5178\u5b9e\u73b0\u6d88\u606f\u4f20\u9012</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#261","title":"2.6.1 \u5b9e\u4f8b","text":"Python<pre><code>&gt;&gt;&gt; def make_instance(cls):\n    \"\"\"Return a new object instance, which is a dispatch dictionary.\"\"\"\n    def get_value(name):\n        if name in attributes:\n            return attributes[name]\n        else:\n            value = cls['get'](name)\n            return bind_method(value, instance)\n    def set_value(name, value):\n        attributes[name] = value\n    attributes = {}\n    instance = {'get': get_value, 'set': set_value}\n    return instance\n\n&gt;&gt;&gt; def bind_method(value, instance):\n    \"\"\"Return a bound method if value is callable, or value otherwise.\"\"\"\n    if callable(value):\n        def method(*args):\n            return value(instance, *args)\n        return method\n    else:\n        return value\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#262","title":"2.6.2 \u7c7b","text":"Python<pre><code>&gt;&gt;&gt; def make_class(attributes, base_class=None):\n    \"\"\"Return a new class, which is a dispatch dictionary.\"\"\"\n    def get_value(name):\n        if name in attributes:\n            return attributes[name]\n        elif base_class is not None:\n            return base_class['get'](name)\n    def set_value(name, value):\n        attributes[name] = value\n    def new(*args):\n        return init_instance(cls, *args)\n    cls = {'get': get_value, 'set': set_value, 'new': new}\n    return cls\n\n&gt;&gt;&gt; def init_instance(cls, *args):\n    \"\"\"Return a new object with type cls, initialized with args.\"\"\"\n    instance = make_instance(cls)\n    init = cls['get']('__init__')\n    if init:\n        init(instance, *args)\n    return instance\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#3","title":"3 \u8ba1\u7b97\u673a\u7a0b\u5e8f\u7684\u89e3\u91ca","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#31","title":"3.1 \u5f15\u8a00","text":"<p>\u8bb8\u591a\u89e3\u91ca\u5668\u90fd\u6709\u4e00\u4e2a\u4f18\u96c5\u7684\u7ed3\u6784\uff0c\u5373\u4e24\u4e2a\u4e92\u9012\u5f52\u51fd\u6570\uff1a</p> <ul> <li>\u7b2c\u4e00\u4e2a\u51fd\u6570\u6c42\u89e3\u73af\u5883\u4e2d\u7684\u8868\u8fbe\u5f0f</li> <li>\u7b2c\u4e8c\u4e2a\u51fd\u6570\u5c06\u51fd\u6570\u5e94\u7528\u4e8e\u53c2\u6570</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#32","title":"3.2 \u51fd\u6570\u5f0f\u7f16\u7a0b","text":"<ul> <li>\u53ea\u4f7f\u7528\u8868\u8fbe\u5f0f\u800c\u4e0d\u4f7f\u7528\u8bed\u53e5\uff0c\u7279\u522b\u9002\u5408\u7b26\u53f7\u8ba1\u7b97</li> <li>\u5904\u7406\u7684\u6570\u636e\u90fd\u662f\u4e0d\u53ef\u53d8\u7684\uff08immutable\uff09</li> </ul> Python<pre><code>(if &lt;predicate&gt; &lt;consequent&gt; &lt;alternative&gt;)\n\n(define pi 3.14)\n(* pi 3.14)\n\n(define (&lt;name&gt; &lt;formal parameters&gt;) &lt;body&gt;)\neg1:\n    (define (average x y)\n      (/ (+ x y) 2))\neg2:\n    (define (abs x)\n    (if (&lt; x 0)\n        (- x)\n        x))\neg3:\n    (define (sqrt x)\n      (define (good-enough? guess)\n        (&lt; (abs (- (square guess) x)) 0.001))\n      (define (improve guess)\n        (average guess (/ x guess)))\n      (define (sqrt-iter guess)\n        (if (good-enough? guess)\n            guess\n            (sqrt-iter (improve guess))))\n      (sqrt-iter 1.0))\n    (sqrt 9)\n\n(lambda (&lt;formal-parameters&gt;) &lt;body&gt;)\neg1:\n    (define (plus4 x) (+ x 4))\n    (define plus4 (lambda (x) (+ x 4))) # both are OK\n\n# \u7279\u6b8a\u7684\u503c\u00a0nil\u00a0\u6216\u00a0'()\u00a0\u8868\u793a\u7a7a\u5217\u8868\n\n# null? \u8c13\u8bcd\u7684\u4f7f\u7528:\n    (define (length items)\n      (if (null? items)\n          0\n          (+ 1 (length (cdr items)))))\n    (define (getitem items n)\n      (if (= n 0)\n          (car items)\n          (getitem (cdr items) (- n 1))))\n    (define squares (list 1 4 9 16 25))\n\n    (length squares)\n\n    (getitem squares 3)\n\n# \u4efb\u4f55\u4e0d\u88ab\u6c42\u503c\u7684\u8868\u8fbe\u5f0f\u90fd\u88ab\u79f0\u4e3a\u88ab\u5f15\u7528\n    (list 'define 'list)\n\n# turtle\u4f7f\u7528+\u9012\u5f52\u753b\u56fe\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#33","title":"3.3 \u5f02\u5e38","text":"<ul> <li>raise</li> <li>assert</li> </ul> Python<pre><code>&gt;&gt;&gt; raise Exception(' An error occurred')\nTraceback (most recent call last):\n    File \"&lt;stdin&gt;\", line 1, in &lt;module&gt;\nException: an error occurred\n</code></pre> <ul> <li>raising an exception<ul> <li>read-eval-print-loop \u5373 REPL</li> <li>stack backtrace</li> </ul> </li> <li>handling exceptions</li> </ul> Python<pre><code>try\n    &lt;try suite&gt;\nexcept &lt;exception class&gt; as &lt;name&gt;:\n    &lt;except suite&gt;\n</code></pre> <p>\u5f02\u5e38\u662f\u4e2a\u7c7b\uff0c\u53ef\u4ee5\u6709\u989d\u5916\u7684\u5c5e\u6027\uff0c\u53ef\u4ee5\u907f\u514d\u62a5\u9519\uff0c\u8ba9\u7a0b\u5e8f\u7ed9\u51fa\u4e00\u4e2a\u8f83\u4e3a\u7c97\u7cd9\u7684\u503c\uff1a</p> Python<pre><code>&gt;&gt;&gt; class IterImproveError(Exception):\n\u00a0\u00a0\u00a0     def __init__(self, last_guess):\n\u00a0\u00a0\u00a0         self.last_guess = last_guess\n&gt;&gt;&gt; def improve(update, done, guess=1, max_updates=1000):\n\u00a0\u00a0\u00a0     k = 0\n\u00a0\u00a0\u00a0     try:\n\u00a0\u00a0\u00a0         while not done(guess) and k &lt; max_updates:\n\u00a0\u00a0\u00a0             guess = update(guess)\n\u00a0\u00a0\u00a0             k = k + 1\n\u00a0\u00a0\u00a0         return guess\n\u00a0\u00a0\u00a0     except ValueError:\n\u00a0\u00a0\u00a0         raise IterImproveError(guess)\n&gt;&gt;&gt; def find_zero(f, guess=1):\n\u00a0\u00a0\u00a0     def done(x):\n\u00a0\u00a0\u00a0         return f(x) == 0\n\u00a0\u00a0\u00a0     try:\n\u00a0\u00a0\u00a0         return improve(newton_update(f), done, guess)\n\u00a0\u00a0\u00a0     except IterImproveError as e:\n\u00a0\u00a0\u00a0         return e.last_guess\n&gt;&gt;&gt; from math import sqrt\n&gt;&gt;&gt; find_zero(lambda x: 2*x*x + sqrt(x))\n-0.030211203830201594\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#34","title":"3.4 \u7ec4\u5408\u8bed\u8a00\u7684\u89e3\u91ca\u5668","text":"<ul> <li>\u8ba1\u7b97\u5668\u8bed\u8a00 -&gt; \u7b80\u7565\u89e3\u91ca\u5668</li> <li>scheme \u5bf9<ul> <li>pair</li> <li>nil</li> </ul> </li> <li>\u8868\u8fbe\u5f0f\u6811</li> <li>\u89e3\u6790\u8868\u8fbe\u5f0f\u6811<ul> <li>\u8bcd\u6cd5\u5206\u6790\u5668\uff08lexical analyzer\uff09/ \u5206\u8bcd\u5668\uff08tokenizer\uff09<ul> <li>\u6807\u8bb0\uff08token\uff09</li> </ul> </li> <li>\u8bed\u6cd5\u5206\u6790\u5668\uff08syntactic analyzer\uff09<ul> <li>\u6570\u5b57\u548c\u8c03\u7528\u8868\u8fbe\u5f0f \u8bb2\u4e86\u4e00\u4e0b\u8ba1\u7b97\u5668\u89e3\u91ca\u5668\u4ea4\u4e92\u5f0f\u9875\u9762\u7684\u8868\u8fbe\u5f0f\u5982\u4f55\u8ba1\u7b97\u548c\u5f02\u5e38\u5904\u7406</li> </ul> </li> </ul> </li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#35","title":"3.5 \u62bd\u8c61\u8bed\u8a00\u7684\u89e3\u91ca\u5668","text":"<ul> <li>\u6269\u5c55 scheme_reader \u89e3\u6790\u70b9\u5217\u8868\u548c\u5f15\u53f7</li> <li>\u6c42\u503c\uff08Evaluation\uff09</li> <li>\u51fd\u6570\u5e94\u7528\uff08Procedure application\uff09</li> <li>\u6c42\u503c/\u5e94\u7528\u9012\u5f52</li> <li>\u6570\u636e\u5373\u7a0b\u5e8f</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#4","title":"4 \u6570\u636e\u5904\u7406","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#41","title":"4.1 \u5f15\u8a00","text":"<ul> <li>pipelines</li> <li>sequence interface</li> <li>unbounded</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#42","title":"4.2 \u9690\u5f0f\u5e8f\u5217","text":"<ul> <li>\u6211\u4eec\u53ea\u5728\u6709\u9700\u8981\u7684\u65f6\u5019\u624d\u8ba1\u7b97\u5143\u7d20</li> <li>Lazy computation</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#421","title":"4.2.1 \u8fed\u4ee3\u5668","text":"<p>\u4e24\u4e2a\u7ec4\u4ef6:</p> <ul> <li>\u68c0\u7d22\u4e0b\u4e00\u4e2a\u5143\u7d20\u7684\u673a\u5236</li> <li>\u5230\u8fbe\u5e8f\u5217\u672b\u5c3e\u5e76\u4e14\u6ca1\u6709\u5269\u4f59\u5143\u7d20\uff0c\u53d1\u51fa\u4fe1\u53f7\u7684\u673a\u5236</li> </ul> Python<pre><code>&gt;&gt;&gt; next(iterator)\n7\n&gt;&gt;&gt; next(iterator)\nTraceback (most recent call las):\n  File \"&lt;stdin&gt;\", line 1, in &lt;module&gt;\nStopIteration\n\n&gt;&gt;&gt; try:\n        next(iterator)\n    except StopIteration:\n        print('No more values')\nNo more values\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#422","title":"4.2.2 \u53ef\u8fed\u4ee3\u6027","text":"<p>iterable value \u53ef\u8fed\u4ee3\u5bf9\u8c61:</p> <ul> <li>\u5e8f\u5217\u503c: string &amp; tuples</li> <li>\u5bb9\u5668: sets &amp; Dictionaries</li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/","title":"\u8ba1\u7b97\u673a\u7ec4\u6210\u4e0e\u8bbe\u8ba1\u786c\u4ef6\u8f6f\u4ef6\u63a5\u53e3","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#_1","title":"\u8ba1\u7b97\u673a\u7ec4\u6210\u4e0e\u8bbe\u8ba1\u786c\u4ef6\u8f6f\u4ef6\u63a5\u53e3","text":"<p> \u7ea6 2978 \u4e2a\u5b57  13 \u884c\u4ee3\u7801  4 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 15 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#1","title":"1 \u8ba1\u7b97\u673a\u62bd\u8c61\u53ca\u76f8\u5173\u6280\u672f","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#2","title":"2 \u6307\u4ee4: \u8ba1\u7b97\u673a\u7684\u8bed\u8a00","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#21","title":"2.1 \u5f15\u8a00","text":"<p>\u8bbe\u8ba1\u539f\u5219:</p> <ul> <li>\u7b80\u5355\u6e90\u4e8e\u89c4\u6574</li> <li>\u66f4\u5c11\u5219\u66f4\u5feb</li> <li>\u4f18\u79c0\u7684\u8bbe\u8ba1\u9700\u8981\u9002\u5f53\u7684\u6298\u4e2d</li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#22","title":"2.2 \u8ba1\u7b97\u673a\u786c\u4ef6\u7684\u64cd\u4f5c","text":"<p>Java \u7f16\u8bd1\u5668: Just In Time \u7f16\u8bd1\u5668</p>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#23","title":"2.3 \u8ba1\u7b97\u673a\u786c\u4ef6\u7684\u64cd\u4f5c\u6570","text":"<ul> <li>\u5bc4\u5b58\u5668<ul> <li>\u5927\u5c0f\u4e3a64 bits \u53cc\u5b57</li> <li>\u6570\u91cf\u6709\u9650\u901a\u5e38\u4e3a 32 \u4e2a</li> <li>x +\u5bc4\u5b58\u5668\u7f16\u53f7</li> </ul> </li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#231","title":"2.3.1 \u5b58\u50a8\u5668\u64cd\u4f5c\u6570","text":"<p>\u5728\u5185\u5b58\u548c\u5bc4\u5b58\u5668\u4e4b\u95f4\u4f20\u8f93\u6307\u4ee4:\u6570\u636e\u4f20\u8f93\u6307\u4ee4 \u6307\u4ee4\u63d0\u4f9b\u5185\u5b58\u5730\u5740 \u8f7d\u5165\u6307\u4ee4\uff08load\uff09:ld</p> Text Only<pre><code>Ld x9, 8(x22)\n</code></pre> <p>X 22 \u57fa\u5740\u5bc4\u5b58\u5668 8 \u504f\u79fb\u91cf \u5b57\u8282\u5730\u5740: 0 8 16 24 RICS- V \u662f\u5c0f\u7aef\u7f16\u5740: \u53ea\u5728\u4ee5\u53cc\u5b57\u5f62\u5f0f\u548c\u516b\u4e2a\u5355\u72ec\u5b57\u8282\u8bbf\u95ee\u76f8\u540c\u6570\u636e\u65f6\u4f1a\u6709\u5f71\u54cd ^da8be4</p> <p>\u5b58\u50a8\u6307\u4ee4\uff08store\uff09\u5b58\u50a8\u53cc\u5b57</p> Text Only<pre><code>sd x9, 96(x22)\n</code></pre> <ul> <li>\u5bf9\u9f50\u9650\u5236:<ul> <li>\u5b57\u7684\u8d77\u59cb\u5730\u5740\u662f 4 \u7684\u500d\u6570</li> <li>\u53cc\u5b57\u7684\u8d77\u59cb\u5730\u5740\u662f 8 \u7684\u500d\u6570</li> <li>\u4f46\u662f risc-v and Intel x 86 \u6ca1\u6709</li> <li>MIPS \u6709 Gibibyte (\\(\\displaystyle 2^{30}\\)) and tebibyte (\\(\\displaystyle 2^{40}\\)) \u5982\u679c\u53d8\u91cf\u6bd4\u5bc4\u5b58\u5668\u6570\u91cf\u66f4\u591a\uff0c\u90a3\u4e48\u4f1a\u628a\u4e00\u4e9b\u653e\u5230\u5185\u5b58\uff0c\u5373\u5bc4\u5b58\u5668\u6362\u51fa\u3002</li> </ul> </li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#232","title":"2.3.2 \u5e38\u6570\u6216\u7acb\u5373\u6570\u64cd\u4f5c\u6570","text":"Text Only<pre><code>ld x9, AddConstant4(x3)\nAdd x22, x22, x9\n\n# Equals to \n\naddi x22, x22, 4 # x22 = x22 + 4\n</code></pre> <p>\u5e38\u6570\u79f0\u4e3a\u7b97\u6570\u6307\u4ee4\u64cd\u4f5c\u6570 X0 \u53ef\u4ee5\u7528\u6765\u8868\u793a 0 \u5176\u5b9e\u8fd8\u6709 RV 32 \u57fa\u5740\u5bc4\u5b58\u5668\u4e5f\u88ab\u79f0\u4e3a\u4e0b\u6807\u5bc4\u5b58\u5668 \u6211\u4eec\u5047\u8bbe\u6307\u4ee4\u90fd\u662f 64 \u4f4d</p>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#24","title":"2.4 \u6709\u7b26\u53f7\u6570\u4e0e\u65e0\u7b26\u53f7\u6570","text":"<ul> <li>Binary digit Or bit</li> <li>Least significant bit </li> <li>Most significant bit</li> <li>sign and magnitude</li> <li>\u8865\u7801\u8f6c\u5316:<ol> <li>\u62d3\u5c55\u7b26\u53f7\u4f4d</li> <li>\u53d6\u53cd</li> <li>\u52a0\u4e00</li> </ol> </li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#25","title":"2.5 \u8ba1\u7b97\u673a\u4e2d\u7684\u6307\u4ee4\u8868\u793a","text":"<ul> <li>\u5b57\u6bb5</li> <li>\u6307\u4ee4 32 \u4f4d\u957f</li> <li>\u6307\u4ee4\u7684\u6570\u5b57\u8868\u793a:\u673a\u5668\u8bed\u8a00</li> <li>\u6307\u4ee4\u5e8f\u5217: \u673a\u5668\u7801</li> <li>C \u548c java \u7528 0 xnnnn \u6765\u8868\u793a\u5341\u516d\u8fdb\u5236\u6570</li> <li>RISC-V:\uff08R\uff09<ul> <li>funct7 + rs 2 + rs 1 + funct 3 + rd + opcode</li> <li>rd: \u76ee\u7684\u64cd\u4f5c\u6570\u5bc4\u5b58\u5668</li> <li>rs 1: \u7b2c\u4e00\u4e2a\u539f\u64cd\u4f5c\u6570\u5bc4\u5b58\u5668</li> <li>rs 2: \u7b2c\u4e8c\u4e2a\u539f\u64cd\u4f5c\u6570\u5bc4\u5b58\u5668</li> <li>funct 7 (3): \u64cd\u4f5c\u7801\u5b57\u6bb5</li> </ul> </li> <li>\u5bf9\u4e0d\u540c\u7684\u6307\u4ee4\u4f7f\u7528\u4e0d\u540c\u7684\u6307\u4ee4\u683c\u5f0f</li> <li>I<ul> <li>immediate + rs 1 + funct 3 + rd + opcode</li> <li>\u8d85\u8fc7 32 \u4e2a\u5bc4\u5b58\u5668\u7684\u8bdd\uff0crd and rs 1 \u90fd\u8981\u589e\u52a0\u989d\u5916\u7684\u4e00\u4f4d</li> <li>ld</li> </ul> </li> <li>S<ul> <li>immediate + rs 2 + rs 1 + funct 3 + immediate + opcode</li> </ul> </li> <li>Reg \u8868\u793a 0 \u5230 31 \u4e4b\u95f4\u7684\u5bc4\u5b58\u5668\u7f16\u53f7</li> <li>\u6ca1\u6709 subi \u56e0\u4e3a\u53ef\u4ee5\u901a\u8fc7\u52a0\u8d1f\u6570\u6765\u5b9e\u73b0</li> <li>\u8ba1\u7b97\u673a\u6784\u5efa\u57fa\u4e8e\u4e24\u4e2a\u5173\u952e\u539f\u5219:<ul> <li>\u6307\u4ee4\u7531\u6570\u5b57\u5f62\u5f0f\u8868\u793a</li> <li>\u7a0b\u5e8f\u548c\u6570\u636e\u4e00\u6837\u4fdd\u5b58\u5728\u5b58\u50a8\u5668\u4e2d\u8fdb\u884c\u8bfb\u5199</li> </ul> </li> <li>\u7a0b\u5e8f\u4f1a\u4ee5\u4e8c\u8fdb\u5236\u6570\u636e\u6587\u4ef6\u7684\u5f62\u5f0f\u6765\u53d1\u5e03<ul> <li>\u4e8c\u8fdb\u5236\u517c\u5bb9\u6027\u8ba9\u884c\u4e1a\u56f4\u7ed5\u5c11\u6570\u51e0\u4e2a\u6307\u4ee4\u7cfb\u7edf\u7ed3\u6784\u5f62\u6210\u8054\u76df</li> </ul> </li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#26","title":"2.6 \u903b\u8f91\u64cd\u4f5c","text":"<ul> <li>sll, slli</li> <li>srl, srli</li> <li>sra, srai</li> <li>and, andi </li> <li>or, ori </li> <li>xor, xori</li> <li>not</li> <li>\u4f4d\u79fb\u6307\u4ee4\u7528\u7684 I \u578b\u683c\u5f0f:<ul> <li>\u4f46\u5b83\u7684\u683c\u5f0f\u6709\u53d8\u5316:<ul> <li>funct 6 + immediate + rs 1 + funct 3 + rd + opcode</li> </ul> </li> </ul> </li> <li>\u7b97\u6570\u53f3\u79fb\u7528\u7684\u662f\u7b26\u53f7\u4f4d</li> <li>AND \u5b9e\u73b0\u4e86\u63a9\u7801</li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#27","title":"2.7 \u7528\u4e8e\u51b3\u7b56\u7684\u6307\u4ee4","text":"<ul> <li>beq</li> <li>bne</li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#271","title":"2.7.1 \u5faa\u73af","text":"C<pre><code>while (save[i] == k) \n    i += 1;\n</code></pre> <p>I -&gt; x 22 K -&gt; x 24 Save -&gt; x 25</p> Text Only<pre><code>loop: slli, x10, x22, 3\nAdd x10, x10, x25\nLd x9, 0(x10)\nBen x9, x24, Exit\nAddi x22, x22, l\nBeq x0, x0, loop\nExit:\n</code></pre> <p>\u57fa\u672c\u5757: </p> <ul> <li>\u9664\u4e86\u5728\u6307\u4ee4\u5e8f\u5217\u7684\u7ed3\u5c3e\uff0c\u5e8f\u5217\u4e2d\u6ca1\u6709\u5206\u652f\u3002</li> <li>\u9664\u4e86\u5728\u5e8f\u5217\u8d77\u59cb\u5904\uff0c\u5e8f\u5217\u4e2d\u6ca1\u6709\u5206\u652f\u76ee\u6807\u548c\u5206\u652f\u6807\u7b7e\u3002</li> <li>\u5bf9\u4e8e\u7b26\u53f7:<ul> <li>RISC-V \u7528\u4e0d\u540c\u7684\u6307\u4ee4</li> <li>MIPS \u8bbe\u7f6e\u4e34\u65f6\u5bc4\u5b58\u5668</li> <li>ARM \u6761\u4ef6\u4ee3\u7801\u6216\u6807\u5fd7\u4f4d</li> </ul> </li> <li>\u4e0d\u8fc7\u4e5f\u4f1a\u6709\u7f3a\u70b9: \u8fc7\u591a\u7684\u6307\u4ee4\u8bbe\u7f6e\u6761\u4ef6\u4ee3\u7801\uff0c\u4f1a\u8ba9\u6d41\u6c34\u7ebf\u6267\u884c\u56f0\u96be</li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#272","title":"2.7.2 \u8fb9\u754c\u68c0\u67e5\u7684\u7b80\u4fbf\u65b9\u6cd5","text":"<p>\u5c06\u7b26\u53f7\u6570\u5f53\u4f5c\u65e0\u7b26\u53f7\u6570\u5904\u7406</p>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#273-caseswitch","title":"2.7.3 Case/switch \u8bed\u53e5","text":"<ul> <li>\u7f16\u7801\u5f62\u6210\u6307\u4ee4\u5e8f\u5217\u7684\u5730\u5740\u8868: \u5206\u652f\u5730\u5740\u8868/\u5206\u652f\u8868</li> <li>\u95f4\u63a5\u8df3\u8f6c\u6307\u4ee4 jalr</li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#28","title":"2.8 \u8ba1\u7b97\u673a\u786c\u4ef6\u5bf9\u8fc7\u7a0b\u7684\u652f\u6301","text":"<ul> <li>Procedure</li> <li>\u6267\u884c\u8fc7\u7a0b\u7684\u516d\u4e2a\u6b65\u9aa4:<ul> <li>\u5c06\u53c2\u6570\u653e\u5728\u8fc7\u7a0b\u53ef\u4ee5\u8bbf\u95ee\u5230\u7684\u4f4d\u7f6e</li> <li>\u5c06\u63a7\u5236\u8f6c\u4ea4\u7ed9\u8fc7\u7a0b</li> <li>\u83b7\u53d6\u8fc7\u7a0b\u6240\u9700\u7684\u5b58\u50a8\u8d44\u6e90</li> <li>\u6267\u884c\u6240\u9700\u7684\u4efb\u52a1</li> <li>\u5c06\u7ed3\u679c\u503c\u653e\u5728\u8c03\u7528\u7a0b\u5e8f\u53ef\u4ee5\u8bbf\u95ee\u5230\u7684\u4f4d\u7f6e</li> <li>\u5c06\u63a7\u5236\u8fd4\u56de\u5230\u521d\u59cb\u70b9\uff0c\u56e0\u4e3a\u8fc7\u7a0b\u53ef\u4ee5\u4ece\u7a0b\u5e8f\u4e2d\u7684\u591a\u4e2a\u70b9\u8c03\u7528</li> </ul> </li> <li>x 10~x 17: \u53c2\u6570\u5bc4\u5b58\u5668\uff0c\u7528\u4e8e\u4f20\u9012\u53c2\u6570\u6216\u8fd4\u56de\u503c</li> <li>x 1: \u8fd4\u56de\u5730\u5740\u5bc4\u5b58\u5668\uff0c\u7528\u4e8e\u8fd4\u56de\u5230\u8d77\u59cb\u70b9</li> <li>jal \u8df3\u8f6c-\u94fe\u63a5\u6307\u4ee4 </li> </ul> Text Only<pre><code>Jal x1, ProcedureAddress\nJalr x0, 0(x1)\n</code></pre> <p>\u8c03\u7528\u8005\u5c06\u53c2\u6570\u503c\u653e\u5165 x 10~x 17 \u8fc7\u7a0b\u662f\u88ab\u8c03\u7528\u8005 Program counter:PC \u6307\u4ee4\u5730\u5740\u5bc4\u5b58\u5668</p> Text Only<pre><code>jal x0, Label // unconditionally branch to Label\n</code></pre>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#281","title":"2.8.1 \u4f7f\u7528\u66f4\u591a\u7684\u5bc4\u5b58\u5668","text":"<ul> <li>Stack</li> <li>Stack pointer x2:sp</li> <li>\u538b\u6808\u5f39\u6808</li> </ul> Text Only<pre><code>leaf_example:\nAddi sp, sp, -14\nSd x5, 16(sp)\nSd x6, 8(sp)\nSd x20, 0(sp)\nAdd x5, x10, x11\nAdd x6, x12, x13\nSub x20, x5, x6\nAddi x10, x20, 0\nLd x20, 0(sp)\nLd x6, 8(sp)\nLd x5, 16(sp)\nAddi sp, sp, 24\nJalr x0, 0(x1)\n</code></pre> <ul> <li>X 5~x 7, x 28~x 31: \u4e34\u65f6\u5bc4\u5b58\u5668</li> <li>x 8~x 9, x 18~x 27: \u4fdd\u5b58\u5bc4\u5b58\u5668</li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#282","title":"2.8.2 \u5d4c\u5957\u8fc7\u7a0b","text":"<ul> <li>Leaf procedure </li> <li>\u5c06\u6240\u6709\u5fc5\u987b\u4fdd\u5b58\u7684\u5bc4\u5b58\u5668\u538b\u6808\uff0c\u9632\u6b62\u51b2\u7a81</li> </ul> C<pre><code>long long int fact (long long int n) {\n    if (n &lt; 1) return (1);\n        else return (n * fact(n - 1))\n}\n</code></pre> <p>n -&gt; x 10</p> Text Only<pre><code>fact:\n    addi sp, sp, -16\n    Sd x1, 8(sp)\n    Sd x10, 0(sp)\n\n    Addi x5, x10, -1\n    Bge x5, x0, L1\n\n    Addi x10, x0, 1\n    Addi sp, sp, 16\n    Jalr x0, 0(x1)\n\nL1: addi x10, x10, -1\n    Jal x1, fact\n\naddi x6, x10, 0\nLd x10, 0(sp)\nLd x1, 8(sp)\nAddi sp, sp, 16\nMul x10, x10, x6\nJalr x0, 0(x1)\n</code></pre> <ul> <li>\u4e00\u4e9b\u7f16\u8bd1\u5668\u4fdd\u7559\u4e00\u4e2a\u5bc4\u5b58\u5668 x 3 \u7528\u4f5c\u5168\u5c40\u6307\u9488 gp </li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#283","title":"2.8.3 \u5728\u6808\u4e2d\u4f4d\u65b0\u6570\u636e\u5206\u914d\u7a7a\u95f4","text":"<p>\u6808\u4e5f\u7528\u4e8e\u5b58\u50a8\u8fc7\u7a0b\u7684\u5c40\u90e8\u53d8\u91cf \u8fc7\u7a0b\u5e27/\u6d3b\u52a8\u8bb0\u5f55</p> <p>\u6ca1\u770b\u61c2</p>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#284","title":"2.8.4 \u5728\u5806\u4e2d\u4e3a\u65b0\u6570\u636e\u5206\u914d\u7a7a\u95f4","text":"<p>Static data segment text segment \u50cf\u94fe\u8868\u7b49\u6570\u636e\u7ed3\u6784\u5f80\u5f80\u4f1a\u968f\u751f\u547d\u5468\u671f\u589e\u957f\u548c\u7f29\u77ed\uff0c\u6240\u4ee5\u4f1a\u628a\u4ed6\u4eec\u5b58\u5728\u5806\u91cc (heap)</p> <ul> <li>malloc ()</li> <li>free () \u8be6\u7ec6\u9610\u8ff0\u6ca1\u770b</li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#29","title":"2.9 \u4eba\u673a\u4ea4\u4e92","text":"<p>ASCII: american standard code for information interchange </p> <p>\u52a0\u8f7d\u65e0\u7b26\u53f7\u5b57\u8282 (lbu) \u5b58\u50a8\u5b57\u8282 (sb)</p> Text Only<pre><code>lbu x12, 0(x10)\nsb x12, 0(x11)\n</code></pre> <p>\u5b57\u7b26\u4e32\u7684\u8868\u793a\u6709\u4e09\u79cd\u9009\u62e9:</p> <ol> <li>\u7b2c\u4e00\u4e2a\u4f4d\u7f6e\u4fdd\u7559\u6765\u7ed9\u51fa\u5b57\u7b26\u4e32\u7684\u957f\u5ea6</li> <li>\u7528\u989d\u5916\u7684\u53d8\u91cf\u6765\u5b58\u50a8\u957f\u5ea6\uff08\u5982\u7ed3\u6784\u4f53\uff09</li> <li>\u5b57\u7b26\u4e32\u7684\u6700\u540e\u4e00\u4e2a\u4f4d\u7f6e\u7528\u5b57\u7b26\u6807\u8bb0\u7ed3\u5c3e \u5176\u4e2d C \u8bed\u8a00\u7528\u7b2c\u4e09\u79cd\uff0c\u4f7f\u7528\u503c\u4e3a 0 \u7684\u5b57\u8282\u6765\u7ec8\u6b62\u5b57\u7b26\u4e32\uff08null in ASCII\uff09</li> </ol> C<pre><code>void strcpy (char x[], char y[])\n{\n    size_t i;\n    i = 0;\n    while ((x[i] = y[i]) != '\\0')\n        i += 1;\n}\n</code></pre> <p>x -&gt; x 10 y -&gt; x 11 i -&gt; x 19</p> Text Only<pre><code>strcpy:\n    addi sp, sp, -8\n    sd x19, 0(sp)\n    add x19, x0, x0\nL1: add x5, x19, x11\n    lbu x6, 0(x5)\n    add x7, x19, x10\n    sb x6, 0(x7)\n    beq x6, x0, L2\n    addi x19, x19, 1\n    jal x0, L1\nL2: ld x19, 0(sp)\n    addi sp, sp, 8\n    jalr x0, 0(x1)\n</code></pre> <p>load half unsigned \u52a0\u8f7d\u534a\u5b57: lh lhu sh </p>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#210-risc-v","title":"2.10 \u5bf9\u5927\u7acb\u5373\u6570\u7684 RISC-V \u7684\u7f16\u5740\u548c\u5bfb\u5740","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#2101","title":"2.10.1 \u5927\u7acb\u5373\u6570","text":"<p>load upper immediate \u53d6\u7acb\u5373\u6570\u9ad8\u4f4d lui  lui \u53ef\u4ee5\u52a0\u8f7d 12~31 \u4f4d addi \u53ef\u4ee5\u52a0\u8f7d 0~11 \u4f4d</p>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#2102","title":"2.10.2 \u5206\u652f\u4e2d\u7684\u5bfb\u5740","text":"<p>\u5206\u652f\u6307\u4ee4\u4f7f\u7528 SB \u578b\u7684\u6307\u4ee4\u683c\u5f0f </p>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#211","title":"2.11 \u6307\u4ee4\u4e0e\u5e76\u884c\u6027\uff1a\u540c\u6b65","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#212","title":"2.12 \u7ffb\u8bd1\u5e76\u542f\u52a8\u7a0b\u5e8f","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#2121","title":"2.12.1 \u7f16\u8bd1\u5668","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#2122","title":"2.12.2 \u6c47\u7f16\u5668","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#2123","title":"2.12.3 \u94fe\u63a5\u5668","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#2124","title":"2.12.4 \u52a0\u8f7d\u5668","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#2125","title":"2.12.5 \u52a8\u6001\u94fe\u63a5\u5e93","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#21251-java","title":"2.12.5.1 \u542f\u52a8 Java \u7a0b\u5e8f","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#213-c","title":"2.13 \u4ee5 C \u6392\u5e8f\u7a0b\u5e8f\u4e3a\u4f8b\u7684\u6c47\u603b\u6574\u7406","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#2131-swap","title":"2.13.1 swap \u8fc7\u7a0b","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#2132-sort","title":"2.13.2 sort \u8fc7\u7a0b","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#214","title":"2.14 \u6570\u7ec4\u4e0e\u6307\u9488","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#2141-clear","title":"2.14.1 \u7528\u6570\u7ec4\u5b9e\u73b0 clear","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#2142-clear","title":"2.14.2 \u7528\u6307\u9488\u5b9e\u73b0 clear","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#2143-clear","title":"2.14.3 \u6bd4\u8f83\u4e24\u4e2a\u7248\u672c\u7684 clear","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#215-c-java","title":"2.15 \u9ad8\u7ea7\u4e13\u9898: \u7f16\u8bd1 C \u8bed\u8a00\u548c\u89e3\u91ca Java \u7a0b\u5e8f","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#216-mips","title":"2.16 \u5b9e\u4f8b: MIPS \u6307\u4ee4","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#217-x-86","title":"2.17 \u5b9e\u4f8b: x 86 \u6307\u4ee4","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#2171-intel-x-86","title":"2.17.1 Intel x 86 \u7684\u6f14\u53d8","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#2172-x-86","title":"2.17.2 x 86 \u5bc4\u5b58\u5668\u548c\u5bfb\u5740\u6a21\u5f0f","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#2173-x-86","title":"2.17.3 x 86 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\u5206\u5757\u548c\u77e9\u9635\u4e58\u6cd5","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#516","title":"5.16 \u8c2c\u8bef\u4e0e\u9677\u9631","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#517","title":"5.17 \u672c\u8eab\u5c0f\u7ed3","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#518","title":"5.18 \u5386\u53f2\u89c6\u89d2\u548c\u62d3\u5c55\u9605\u8bfb","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#6","title":"6 \u5e76\u884c\u5904\u7406\u5668: \u4ece\u5ba2\u6237\u7aef\u5230\u4e91","text":""},{"location":"CS_Basic/Network/Security/","title":"Security","text":""},{"location":"CS_Basic/Network/Security/#_1","title":"\u5e38\u89c1\u7684\u5bc6\u7801\u7b97\u6cd5","text":"<p> \u7ea6 368 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <ul> <li>\u54c8\u5e0c\u7b97\u6cd5\uff08\u5982MD5,SHA256\uff09</li> <li>\u5bf9\u79f0\u52a0\u5bc6\u7b97\u6cd5 \uff08\u5982AES,DES\uff09</li> <li>\u975e\u5bf9\u79f0\u52a0\u5bc6\u7b97\u6cd5 \uff08\u5982RSA\uff09</li> </ul> <p>[[\u52a0\u5bc6\u539f\u7406]]</p>"},{"location":"CS_Basic/Network/Security/#_2","title":"\u5f31\u53e3\u4ee4","text":"<ol> <li>\u8f83\u77ed\u7684\u5bc6\u7801</li> <li>\u6613\u88ab\u731c\u6d4b\u6216\u4fe1\u9053\u653b\u51fb\u7684\u5bc6\u7801 - \u98ce\u9669<ul> <li>ssh\u4e2d\u5982\u679c\u8bbe\u7f6e\u4e86password\u8ba4\u8bc1\u4e14\u8bbe\u7f6e\u5f31\u53e3\u4ee4\uff0c\u5c06\u4f1a\u5bfc\u81f4\u670d\u52a1\u5668\u88ab\u672a\u7ecf\u6388\u6743\u767b\u5f55\uff0c\u4e14\u653b\u51fb\u8005\u53ef\u4ee5\u8fdb\u884c\u4e0e\u4f60\u540c\u6743\u9650\u7684\u4efb\u610f\u64cd\u4f5c</li> <li>\u65e0\u7ebf\u5c40\u57df\u7f51\u4e2d\u5982\u679c\u8bbe\u7f6e\u4e86\u5f31\u53e3\u4ee4\u88ab\u731c\u6d4b\u6210\u529f\u540e\uff0c\u653b\u51fb\u8005\u5c06\u53ef\u4ee5\u8fdb\u5165\u5c40\u57df\u7f51\u4e2d\u5bf9\u5c40\u57df\u7f51\u5176\u4ed6\u8bbe\u5907\u8fdb\u884c\u653b\u51fb</li> <li>\u9632\u8303\u65b9\u5f0f</li> <li>\u91c7\u7528\u5176\u4ed6\u66f4\u4e3a\u5b89\u5168\u7684\u8eab\u4efd\u8ba4\u8bc1\u65b9\u6cd5\uff08\u5982ssh\u4e2d\u91c7\u7528publickey\u8ba4\u8bc1\uff09</li> <li>\u8bbe\u7f6e\u968f\u673a\u5b57\u7b26\u4e32\u4f5c\u4e3a\u5bc6\u7801\uff0c\u5e76\u4e14\u957f\u5ea6\u8d85\u8fc78\u4f4d</li> </ul> </li> </ol>"},{"location":"CS_Basic/Network/Security/#ip","title":"\u516c\u7f51 IP","text":"<ul> <li>\u6211\u4eec\u5e0c\u671b\u4ece\u4efb\u610f\u63a5\u5165\u4e92\u8054\u7f51\u7684\u5730\u65b9\u4f7f\u7528ssh\u8fde\u63a5\u5230\u670d\u52a1\u5668\uff0c\u4e00\u4e2a\u7b80\u5355\u7684\u65b9\u6cd5\u662f\u8ba9\u670d\u52a1\u5668\u62e5\u6709\u4e00\u4e2a\u516c\u7f51IP\u5e76\u8fd0\u884csshd\u670d\u52a1\u3002</li> <li>\u5e38\u89c1\u7684\u653b\u51fb\u65b9\u5f0f<ol> <li>\u626b\u63cf\u5f00\u653e\u7aef\u53e3\u4fe1\u606f\uff0c\u5e76\u786e\u5b9a\u7aef\u53e3\u4e0a\u8fd0\u884c\u7684\u670d\u52a1</li> <li>\u5bf9\u53ef\u80fd\u5b58\u5728\u7684\u670d\u52a1\u8fdb\u884c\u653b\u51fb\uff0c\u5c1d\u8bd5\u5229\u7528\u670d\u52a1\u7684\u6f0f\u6d1e\uff08\u5982\u5f31\u53e3\u4ee4\uff09\u83b7\u53d6\u670d\u52a1\u5668\u7684\u8bbf\u95ee\u6743\u9650</li> </ol> </li> <li>\u5e38\u89c1\u7684\u9632\u8303\u65b9\u5f0f<ul> <li>\u4f7f\u7528\u9632\u706b\u5899\u3002\u914d\u7f6e\u9632\u706b\u5899\u89c4\u5219\uff0c\u4ec5\u5141\u8bb8\u5fc5\u8981\u7684\u670d\u52a1\u548c\u7aef\u53e3\u5bf9\u5916\u5f00\u653e\u3002</li> <li>\u5ba1\u67e5\u5f00\u653e\u7684\u670d\u52a1\u7684\u5b89\u5168\u6027\u3002\u786e\u4fdd\u5f53\u524d\u4e3b\u673a\u5f00\u653e\u7684\u6240\u6709\u670d\u52a1\u5747\u662f\u5b89\u5168\u7684\u3002</li> </ul> </li> </ul>"},{"location":"CV/","title":"Computer Vision","text":""},{"location":"CV/#computer-vision","title":"Computer Vision","text":"<p>Abstract</p> <p>\u672c\u90e8\u5206\u5185\u5bb9\uff08\u9664\u7279\u522b\u58f0\u660e\u5916\uff09\u91c7\u7528 \u7f72\u540d-\u975e\u5546\u4e1a\u6027\u4f7f\u7528-\u4fdd\u6301\u4e00\u81f4 4.0 \u56fd\u9645 (CC BY-NC-SA 4.0) \u8bb8\u53ef\u534f\u8bae\u8fdb\u884c\u8bb8\u53ef\u3002</p> Notes          <ul> <li> \u89c6\u89c9 SLAM \u5341\u56db\u8bb2  14110  72  48 mins              1734024510 </li> </ul>"},{"location":"CV/SLAM14/","title":"\u89c6\u89c9SLAM\u5341\u56db\u8bb2","text":""},{"location":"CV/SLAM14/#slam","title":"\u89c6\u89c9SLAM\u5341\u56db\u8bb2","text":"<p> \u7ea6 14110 \u4e2a\u5b57  72 \u884c\u4ee3\u7801  20 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 71 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"CV/SLAM14/#1","title":"1 \u9884\u5907\u77e5\u8bc6","text":""},{"location":"CV/SLAM14/#11","title":"1.1 \u672c\u4e66\u8bb2\u4ec0\u4e48","text":"<p>simultaneous localization and mapping</p> <ul> <li>\u5b9a\u4f4d</li> <li>\u5730\u56fe\u6784\u5efa</li> <li>\u80cc\u666f\u77e5\u8bc6:<ul> <li>\u5c04\u5f71\u51e0\u4f55</li> <li>\u8ba1\u7b97\u673a\u89c6\u89c9</li> <li>\u72b6\u6001\u4f30\u8ba1\u7406\u8bba</li> <li>\u674e\u7fa4\u4e0e\u674e\u4ee3\u6570</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#12","title":"1.2 \u5982\u4f55\u4f7f\u7528\u672c\u4e66","text":""},{"location":"CV/SLAM14/#121","title":"1.2.1 \u7ec4\u7ec7\u65b9\u5f0f","text":"<ul> <li>\u6570\u5b66\u57fa\u7840\u7bc7<ul> <li></li> </ul> </li> <li>\u5b9e\u8df5\u5e94\u7528\u7bc7<ul> <li></li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#122","title":"1.2.2 \u4ee3\u7801","text":"<p>GitHub - gaoxiang12/slambook2: edition 2 of the slambook</p>"},{"location":"CV/SLAM14/#123","title":"1.2.3 \u9762\u5411\u7684\u8bfb\u8005","text":"<ul> <li>\u57fa\u7840\u77e5\u8bc6:<ul> <li>\u9ad8\u6570\u7ebf\u4ee3\u6982\u7387\u8bba</li> <li>C++\u8bed\u8a00\u57fa\u7840\uff08C++\u6807\u51c6\u5e93\uff0c\u6a21\u677f\u7c7b\uff0c\u4e00\u90e8\u5206 C++11 \uff09</li> <li>Linux \u57fa\u7840</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#13","title":"1.3 \u98ce\u683c\u7ea6\u5b9a","text":""},{"location":"CV/SLAM14/#14","title":"1.4 \u81f4\u8c22\u548c\u58f0\u660e","text":""},{"location":"CV/SLAM14/#15","title":"1.5 \u4e60\u9898","text":"<ul> <li>\u9898\u76ee\uff1a\u6709\u7ebf\u6027\u65b9\u7a0b \\(A x=b\\)\uff0c\u82e5\u5df2\u77e5 \\(A, b\\)\uff0c\u9700\u8981\u6c42\u89e3 x\uff0c\u8be5\u5982\u4f55\u6c42\u89e3\uff1f\u8fd9\u5bf9 A \u548c b \u6709\u54ea\u4e9b\u8981\u6c42\uff1f\u63d0\u793a\uff1a\u4ece A \u7684\u7ef4\u5ea6\u548c\u79e9\u89d2\u5ea6\u6765\u5206\u6790\u3002</li> <li>\u7b54\u6848\uff1a\u7ebf\u6027\u65b9\u7a0b\u7ec4 \\(Ax = b\\) \u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u6cd5\u6c42\u89e3\uff0c\u5982\u9ad8\u65af\u6d88\u5143\u6cd5\u3001\u77e9\u9635\u9006\u6cd5\u7b49\u3002\u8981\u6c42 \\(A\\) \u662f\u4e00\u4e2a\u65b9\u9635\u4e14\u53ef\u9006\uff08\u5373 \\(A\\) \u7684\u884c\u5217\u5f0f\u4e0d\u4e3a\u96f6\uff09\uff0c\u8fd9\u6837\u65b9\u7a0b\u624d\u6709\u552f\u4e00\u89e3\u3002\u5982\u679c \\(A\\) \u4e0d\u662f\u65b9\u9635\uff0c\u9700\u8981 \\(A\\) \u7684\u79e9\u7b49\u4e8e\u5217\u6570\u4e14\u7b49\u4e8e\u589e\u5e7f\u77e9\u9635 \\(\\displaystyle [A|b]\\) \u7684\u79e9\uff0c\u8fd9\u6837\u65b9\u7a0b\u7ec4\u624d\u6709\u89e3\u3002</li> <li>\u9898\u76ee\uff1a\u9ad8\u65af\u5206\u5e03\u662f\u4ec0\u4e48\uff1f\u5b83\u7684\u4e00\u7ef4\u5f62\u5f0f\u662f\u4ec0\u4e48\u6837\u5b50\uff1f\u5b83\u7684\u9ad8\u7ef4\u5f62\u5f0f\u662f\u4ec0\u4e48\u6837\u5b50\uff1f</li> <li>\u7b54\u6848\uff1a\u9ad8\u65af\u5206\u5e03\uff0c\u4e5f\u79f0\u4e3a\u6b63\u6001\u5206\u5e03\uff0c\u662f\u4e00\u79cd\u8fde\u7eed\u6982\u7387\u5206\u5e03\u3002\u4e00\u7ef4\u9ad8\u65af\u5206\u5e03\u7684\u6570\u5b66\u8868\u8fbe\u5f0f\u4e3a \\(\\displaystyle f (x) = \\frac{1}{\\sigma\\sqrt{2\\pi}} e^{-\\frac{(x-\\mu)^2}{2\\sigma^2}}\\)\uff0c\u5176\u4e2d \\(\\displaystyle \\mu\\) \u662f\u5747\u503c\uff0c\\(\\displaystyle \\sigma\\) \u662f\u6807\u51c6\u5dee\u3002\u9ad8\u7ef4\u9ad8\u65af\u5206\u5e03\u662f\u4e00\u7ef4\u9ad8\u65af\u5206\u5e03\u5728\u591a\u7ef4\u7a7a\u95f4\u7684\u63a8\u5e7f\uff0c\u5176\u6982\u7387\u5bc6\u5ea6\u51fd\u6570\u4e3a \\(\\displaystyle N (\\mathbf{x}; \\mathbf{\\mu}, \\Sigma)\\)\uff0c\u5176\u4e2d \\(\\displaystyle \\mathbf{\\mu}\\) \u662f\u5747\u503c\u5411\u91cf\uff0c\\(\\displaystyle \\Sigma\\) \u662f\u534f\u65b9\u5dee\u77e9\u9635\u3002</li> <li>\u9898\u76ee\uff1a\u4f60\u77e5\u9053 C++11 \u6807\u51c6\u5417\uff1f\u4f60\u542c\u8bf4\u8fc7\u6216\u7528\u8fc7\u5176\u4e2d\u54ea\u4e9b\u65b0\u7279\u6027\uff1f\u6709\u6ca1\u6709\u5176\u4ed6\u7684\u6807\u51c6\uff1f</li> <li>\u7b54\u6848\uff1a\u662f\u7684\uff0cC++11 \u662f C++ \u8bed\u8a00\u7684\u4e00\u4e2a\u91cd\u8981\u6807\u51c6\uff0c\u5b83\u5f15\u5165\u4e86\u8bb8\u591a\u65b0\u7279\u6027\uff0c\u5982\u81ea\u52a8\u7c7b\u578b\u63a8\u5bfc\uff08auto\uff09\u3001\u57fa\u4e8e\u8303\u56f4\u7684 for \u5faa\u73af\u3001lambda \u8868\u8fbe\u5f0f\u3001\u667a\u80fd\u6307\u9488\u7b49\u3002\u9664\u4e86 C++11\uff0c\u8fd8\u6709 C++14\u3001C++17 \u548c C++20 \u7b49\u540e\u7eed\u6807\u51c6\uff0c\u5b83\u4eec\u4e5f\u5f15\u5165\u4e86\u65b0\u7684\u7279\u6027\u548c\u6539\u8fdb\u3002</li> <li>\u9898\u76ee\uff1a\u5982\u4f55\u5728 Ubuntu \u7cfb\u7edf\u4e2d\u5b89\u88c5\u8f6f\u4ef6\uff08\u4e0d\u6253\u5f00\u8f6f\u4ef6\u4e2d\u5fc3\u7684\u60c5\u51b5\u4e0b\uff09\uff1f\u8fd9\u4e9b\u8f6f\u4ef6\u88ab\u5b89\u88c5\u5728\u4ec0\u4e48\u5730\u65b9\uff1f\u5982\u679c\u53ea\u77e5\u9053\u6a21\u7cca\u7684\u8f6f\u4ef6\u540d\u79f0\uff08\u6bd4\u5982\u60f3\u8981\u88c5\u4e00\u4e2a\u540d\u79f0\u4e2d\u542b\u6709 Eigen \u7684\u5e93\uff09\uff0c\u5e94\u8be5\u5982\u4f55\u5b89\u88c5\u5b83\uff1f</li> <li>\u7b54\u6848\uff1a</li> <li>\u8f6f\u4ef6\u5b89\u88c5\uff1a\u5728 Ubuntu \u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u547d\u4ee4\u884c\u5de5\u5177 <code>apt</code> \u6765\u5b89\u88c5\u8f6f\u4ef6\u3002\u57fa\u672c\u547d\u4ee4\u4e3a <code>sudo apt install [package-name]</code>\u3002</li> <li>\u5b89\u88c5\u4f4d\u7f6e\uff1a\u8f6f\u4ef6\u901a\u5e38\u88ab\u5b89\u88c5\u5728 <code>/usr/</code> \u76ee\u5f55\u4e0b\uff0c\u4f46\u5177\u4f53\u7684\u6587\u4ef6\u53ef\u80fd\u5206\u5e03\u5728\u591a\u4e2a\u5b50\u76ee\u5f55\u4e2d\u3002</li> <li>\u6a21\u7cca\u540d\u79f0\u5b89\u88c5\uff1a\u5982\u679c\u53ea\u77e5\u9053\u8f6f\u4ef6\u540d\u79f0\u7684\u4e00\u90e8\u5206\uff0c\u53ef\u4ee5\u4f7f\u7528 <code>apt search</code> \u547d\u4ee4\u6765\u641c\u7d22\u3002\u4f8b\u5982\uff0c<code>sudo apt search eigen</code> \u53ef\u4ee5\u5e2e\u52a9\u627e\u5230\u6240\u6709\u5305\u542b \"eigen\" \u7684\u8f6f\u4ef6\u5305\u3002</li> <li>\u9898\u76ee\uff1a*\u82b1\u4e00\u4e2a\u5c0f\u65f6\u5b66\u4e60 Vim\uff0c\u56e0\u4e3a\u4f60\u8fdf\u65e9\u4f1a\u7528\u5b83\u3002\u4f60\u53ef\u4ee5\u5728\u7ec8\u7aef\u4e2d\u8f93\u5165 vimtutor \u9605\u8bfb\u4e00\u904d\u6240\u6709\u5185\u5bb9\u3002\u6211\u4eec\u4e0d\u9700\u8981\u4f60\u975e\u5e38\u719f\u7ec3\u5730\u64cd\u4f5c\u5b83\uff0c\u53ea\u8981\u80fd\u591f\u5728\u5b66\u4e60\u672c\u4e66\u7684\u8fc7\u7a0b\u4e2d\u4f7f\u7528\u5b83\u8f93\u5165\u4ee3\u7801\u5373\u53ef\u3002\u4e0d\u8981\u5728\u5b83\u7684\u63d2\u4ef6\u4e0a\u6d6a\u8d39\u65f6\u95f4\uff0c\u4e0d\u8981\u60f3\u7740\u628a Vim \u7528\u6210 IDE\uff0c\u6211\u4eec\u53ea\u7528\u5b83\u505a\u6587\u672c\u7f16\u8f91\u7684\u5de5\u4f5c\u3002</li> <li>\u7b54\u6848:<ul> <li>vim \u6839\u672c\u4e0d\u719f\u7ec3\u634f</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#2-slam","title":"2 \u521d\u8bc6 SLAM","text":""},{"location":"CV/SLAM14/#21","title":"2.1 \u5f15\u5b50: \u5c0f\u841d\u535c\u7684\u4f8b\u5b50","text":"<ul> <li>\u81ea\u4e3b\u8fd0\u52a8\u80fd\u529b</li> <li>\u611f\u77e5\u5468\u8fb9\u73af\u5883<ul> <li>\u72b6\u6001</li> <li>\u73af\u5883</li> </ul> </li> <li>\u5b89\u88c5\u4e8e\u73af\u5883\u4e2d\uff08\u4e0d\u592a\u597d\u53cd\u6b63\uff09</li> <li>\u673a\u5668\u4eba\u672c\u4f53\u4e0a<ul> <li>\u6fc0\u5149 SLAM</li> <li>\u89c6\u89c9 SLAM\uff08\u672c\u4e66\u91cd\u70b9\uff09<ul> <li>\u5355\u76ee\uff08Monocular\uff09<ul> <li>\u53ea\u80fd\u7528\u4e00\u4e2a\u6444\u50cf\u5934</li> <li>\u8ddd\u79bb\u611f<ul> <li>motion</li> <li>Structure</li> <li>Disparity</li> <li>Scale<ul> <li>Scale Ambiguity</li> </ul> </li> <li>\u4f46\u662f\u65e0\u6cd5\u786e\u5b9a\u6df1\u5ea6</li> </ul> </li> </ul> </li> <li>\u53cc\u76ee\uff08Sterco\uff09<ul> <li>\u4e24\u4e2a\u76f8\u673a\u7684\u8ddd\u79bb\uff08\u57fa\u7ebf Baseline\uff09\u5df2\u77e5</li> <li>\u914d\u7f6e\u4e0e\u6807\u5b9a\u6bd4\u8f83\u590d\u6742</li> </ul> </li> <li>\u6df1\u5ea6\uff08RGB-D\uff09<ul> <li>\u7ea2\u5916\u7ed3\u6784\u5173 Time-of-Flight\uff08ToF\uff09</li> <li>\u4e3b\u8981\u7528\u5728\u5ba4\u5185\uff0c\u5ba4\u5916\u4f1a\u6709\u5f88\u591a\u5f71\u54cd</li> </ul> </li> <li>\u8fd8\u6709\u4e00\u4e9b\u975e\u4e3b\u6d41\u7684: \u5168\u666f\uff0cEvent</li> </ul> </li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#22-slam","title":"2.2 \u7ecf\u5178\u89c6\u89c9 SLAM \u6846\u67b6","text":"<ul> <li>\u5728\u5916\u754c\u6362\u51e0\u4e2a\u6bd4\u8f83\u7a33\u5b9a\u7684\u60c5\u51b5\u4e0b\uff0cSLAM \u6280\u672f\u5df2\u7ecf\u6bd4\u8f83\u6210\u719f</li> </ul>"},{"location":"CV/SLAM14/#221","title":"2.2.1 \u89c6\u89c9\u91cc\u7a0b\u8ba1","text":"<ul> <li>\u53ea\u901a\u8fc7\u89c6\u89c9\u91cc\u7a0b\u8ba1\u6765\u4f30\u8ba1\u8f68\u8ff9\u4f1a\u51fa\u73b0\u7d2f\u79ef\u6f02\u79fb\uff08Accumulating Drift\uff09\u3002</li> <li>\u6240\u4ee5\u9700\u8981\u56de\u73af\u68c0\u6d4b\u4e0e\u540e\u7aef\u4f18\u5316</li> </ul>"},{"location":"CV/SLAM14/#222","title":"2.2.2 \u540e\u7aef\u4f18\u5316","text":"<ul> <li>\u6700\u5927\u540e\u9a8c\u6982\u7387\u4f30\u8ba1\uff08Maximum-a-Posteriori MAP\uff09</li> <li>\u524d\u7aef<ul> <li>\u56fe\u50cf\u7684\u7279\u5f81\u63d0\u53d6\u4e0e\u5339\u914d</li> </ul> </li> <li>\u540e\u7aef<ul> <li>\u6ee4\u6ce2\u4e0e\u975e\u7ebf\u6027\u7b97\u6cd5</li> </ul> </li> <li>\u5bf9\u8fd0\u52a8\u4e3b\u4f53\u81ea\u8eab\u548c\u5468\u56f4\u73af\u5883\u7a7a\u95f4\u4e0d\u786e\u5b9a\u6027\u7684\u4f30\u8ba1</li> </ul>"},{"location":"CV/SLAM14/#223","title":"2.2.3 \u56de\u73af\u68c0\u6d4b","text":"<ul> <li>\u95ed\u73af\u68c0\u6d4b</li> <li>\u8bc6\u522b\u5230\u8fc7\u7684\u573a\u666f</li> <li>\u5229\u7528\u56fe\u50cf\u7684\u76f8\u4f3c\u6027</li> </ul>"},{"location":"CV/SLAM14/#224","title":"2.2.4 \u5efa\u56fe","text":"<ul> <li>\u5ea6\u91cf\u5730\u56fe<ul> <li>Sparse<ul> <li>Landmark</li> <li>\u5b9a\u4f4d\u7528</li> </ul> </li> <li>Dense<ul> <li>Grid / Vocel</li> <li>\u5bfc\u822a\u7528</li> </ul> </li> </ul> </li> <li>\u62d3\u6251\u5730\u56fe     Graph</li> </ul>"},{"location":"CV/SLAM14/#23-slam","title":"2.3 SLAM \u95ee\u9898\u7684\u6570\u5b66\u8868\u8ff0","text":"<ul> <li>\u8fd0\u52a8\u65b9\u7a0b<ul> <li>\\(\\displaystyle \\quad\\boldsymbol{x}_k=f\\left(\\boldsymbol{x}_{k-1},\\boldsymbol{u}_k,\\boldsymbol{w}_k\\right).\\)<ul> <li>\\(\\displaystyle \\boldsymbol{u}_{k}\\) \u662f\u8fd0\u52a8\u4f20\u611f\u5668\u7684\u8f93\u5165</li> <li>\\(\\displaystyle \\boldsymbol{w}_{k}\\) \u662f\u8fc7\u7a0b\u4e2d\u52a0\u5165\u7684\u566a\u58f0</li> </ul> </li> </ul> </li> <li>\u89c2\u6d4b\u65b9\u7a0b<ul> <li>\\(\\displaystyle \\boldsymbol{z}_{k,j} = h (\\boldsymbol{y}_{j},\\boldsymbol{x}_{k},\\boldsymbol{v}_{k,j})\\)<ul> <li>\\(\\displaystyle \\boldsymbol{v}_{k,j}\\) \u662f\u89c2\u6d4b\u91cc\u7684\u566a\u58f0</li> </ul> </li> </ul> </li> <li>\u53c8\u5f88\u591a\u53c2\u6570\u5316\u7684\u65b9\u5f0f</li> <li>\u53ef\u4ee5\u603b\u7ed3\u4e3a\u5982\u4e0b\u4e24\u4e2a\u65b9\u7a0b</li> </ul> \\[ \\begin{cases}\\boldsymbol{x}_k=f\\left(\\boldsymbol{x}_{k-1},\\boldsymbol{u}_k,\\boldsymbol{w}_k\\right),&amp;k=1,\\cdots,K\\\\\\boldsymbol{z}_{k,j}=h\\left(\\boldsymbol{y}_j,\\boldsymbol{x}_k,\\boldsymbol{v}_{k,j}\\right),&amp;(k,j)\\in\\mathcal{O}\\end{cases}. \\] <ul> <li>\u77e5\u9053\u8fd0\u52a8\u6d4b\u91cf\u7684\u8bfb\u6570 \\(\\displaystyle \\boldsymbol{u}\\) \u548c\u4f20\u611f\u5668\u7684\u8bfb\u6570 \\(\\displaystyle \\boldsymbol{z}\\)\uff0c\u5982\u4f55\u6c42\u89e3\u5b9a\u4f4d\u95ee\u9898\u548c\u5efa\u56fe\u95ee\u9898\u3002<ul> <li>\u72b6\u6001\u4f30\u8ba1\u95ee\u9898: \u5982\u4f55\u901a\u8fc7\u5e26\u6709\u566a\u58f0\u7684\u6d4b\u91cf\u6570\u636e\uff0c\u4f30\u8ba1\u5185\u90e8\u7684\u3001\u9690\u85cf\u7740\u7684\u72b6\u6001\u53d8\u91cf</li> </ul> </li> <li>Linear Gaussian -&gt; Kalman Filter</li> <li>Non-Linear Non-Gaussian -&gt; Extended Kalman Filter \u548c\u975e\u7ebf\u6027\u4f18\u5316</li> <li>EKF -&gt; Particle Filter -&gt; Graph Optimization</li> </ul>"},{"location":"CV/SLAM14/#24","title":"2.4 \u5b9e\u8df5: \u7f16\u7a0b\u57fa\u7840","text":""},{"location":"CV/SLAM14/#241-linux","title":"2.4.1 \u5b89\u88c5 Linux \u64cd\u4f5c\u7cfb\u7edf","text":""},{"location":"CV/SLAM14/#242-hello-slam","title":"2.4.2 Hello SLAM","text":""},{"location":"CV/SLAM14/#243-cmake","title":"2.4.3 \u4f7f\u7528 cmake","text":"Text Only<pre><code>cmake_minimum_required( VERSION 2.8)\n\nproject(HelloSLAM)\n\nadd_executable(helloSLAM helloSLAM.cpp)\n</code></pre> <p>\u5bf9\u4e2d\u95f4\u6587\u4ef6\u7684\u5904\u7406:</p> Text Only<pre><code>mkdir build\ncd build\ncmake ..\nmake\n</code></pre>"},{"location":"CV/SLAM14/#244","title":"2.4.4 \u4f7f\u7528\u5e93","text":"Text Only<pre><code>add_library(hello libHelloSLAM.cpp)\n</code></pre> <ul> <li>\u9759\u6001\u5e93<ul> <li>.a \u4f5c\u4e3a\u540e\u7f00\u540d\uff0c\u6bcf\u6b21\u8c03\u7528\u90fd\u6709\u4e00\u4e2a\u526f\u672c</li> </ul> </li> <li>\u5171\u4eab\u5e93<ul> <li>.so\uff0c\u53ea\u6709\u4e00\u4e2a\u526f\u672c</li> </ul> </li> </ul> Text Only<pre><code>add_library(hello_shared SHARED libHelloSLAM.cpp)\n</code></pre> <ul> <li>\u8fd8\u8981\u4e00\u4e2a\u5934\u6587\u4ef6\u6765\u8bf4\u660e\u5e93\u91cc\u90fd\u6709\u4ec0\u4e48</li> </ul> Text Only<pre><code>#ifndef LIBHELLOSLAM_H_\n#define LIBHELLOSLAM_H_\n\nvoid printHello()\n\n#endif\n</code></pre> <ul> <li>\u6700\u540e\u5199\u4e00\u4e2a\u53ef\u6267\u884c\u7a0b\u5e8f:</li> </ul> C++<pre><code>#include \"libHelloSLAM.h\"\n\nint main(int argc, char **argv) {\n    printHello();\n    return 0;   \n}\n</code></pre> <ul> <li>\u5728 CMakeLists. txt \u4e2d\u6dfb\u52a0\u53ef\u6267\u884c\u547d\u4ee4\u7684\u751f\u6210\u547d\u4ee4\uff0c\u94fe\u63a5\u5230\u5e93\u4e0a:</li> </ul> Text Only<pre><code>add_executable(useHello useHello.cpp)\ntarget_link_libraries(useHello hello_shared)\n</code></pre>"},{"location":"CV/SLAM14/#245-ide","title":"2.4.5 \u4f7f\u7528 IDE","text":"<ul> <li>KDevelop</li> <li>Clion</li> <li>\u8fd8\u6ca1\u5199</li> </ul>"},{"location":"CV/SLAM14/#3","title":"3 \u4e09\u7ef4\u7a7a\u95f4\u521a\u4f53\u8fd0\u52a8","text":""},{"location":"CV/SLAM14/#31","title":"3.1 \u65cb\u8f6c\u77e9\u9635","text":""},{"location":"CV/SLAM14/#311","title":"3.1.1 \u70b9\u3001\u5411\u91cf\u548c\u5750\u6807\u7cfb","text":"<ul> <li>Skew-symmetric Matrix</li> </ul> \\[ a\\times b =  \\begin{Vmatrix}e_1&amp;e_2&amp;e_3\\\\ \\\\ a_1&amp;a_2&amp;a_3\\\\ \\\\ b_1&amp;b_2&amp;b_3 \\\\ \\end{Vmatrix} = \\begin{bmatrix} a_2b_3-a_3b_2\\\\ \\\\ a_3b_1-a_1b_3\\\\ \\\\ a_1b_2-a_2b_1  \\end{bmatrix} = \\begin{bmatrix}  0&amp;-a_3&amp;a_2\\\\ \\\\ a_3&amp;0&amp;-a_1\\\\ \\\\ -a_2&amp;a_1&amp;0  \\end{bmatrix} \\boldsymbol{b}\\overset{\\mathrm{def}}{\\operatorname*{=}}\\boldsymbol{a}^{\\wedge}\\boldsymbol{b}. \\] <ul> <li>\u4e8e\u662f\u5c31\u628a\u5916\u79ef\u53d8\u6210\u4e86\u7ebf\u6027\u8fd0\u7b97</li> <li>\u5373</li> </ul> \\[ \\displaystyle \\boldsymbol{a}^{\\wedge}=\\begin{bmatrix} 0  &amp; -a_{3}  &amp; a_{2} \\\\ a_{3} &amp; 0 &amp; -a_{1} \\\\ -a_{2} &amp; a_{1} &amp; 0 \\end{bmatrix} \\]"},{"location":"CV/SLAM14/#312","title":"3.1.2 \u5750\u6807\u7cfb\u95f4\u7684\u6b27\u5f0f\u53d8\u6362","text":"<ul> <li>Euclidean Transform</li> </ul> \\[ \\begin{bmatrix}a_1\\\\ \\\\ a_2\\\\\\\\a_3\\end{bmatrix}=\\begin{bmatrix}e_1^\\mathrm{T}e_1^{\\prime}&amp;e_1^\\mathrm{T}e_2^{\\prime}&amp;e_1^\\mathrm{T}e_3^{\\prime}\\\\e_2^\\mathrm{T}e_1^{\\prime}&amp;e_2^\\mathrm{T}e_2^{\\prime}&amp;e_2^\\mathrm{T}e_3^{\\prime}\\\\e_3^\\mathrm{T}e_1^{\\prime}&amp;e_3^\\mathrm{T}e_2^{\\prime}&amp;e_3^\\mathrm{T}e_3^{\\prime}\\end{bmatrix}\\begin{bmatrix}a_1^{\\prime}\\\\\\\\a_2^{\\prime}\\\\\\\\a_3^{\\prime}\\end{bmatrix}\\stackrel{\\mathrm{def}}{=}Ra^{\\prime} \\] <ul> <li>\\(\\displaystyle \\boldsymbol{R}\\) \u662f\u65cb\u8f6c\u77e9\u9635\u3001\u65b9\u5411\u4f59\u5f26\u77e9\u9635</li> <li>Special Orthogonal Group \\(\\displaystyle \\mathrm{SO}(n)=\\{\\boldsymbol{R}\\in \\mathbb{R}^{n \\times n}|\\boldsymbol{R}\\boldsymbol{R}^{\\mathrm{T}}=\\boldsymbol{I},\\det(\\boldsymbol{R})=1\\}\\)</li> <li>\\(\\displaystyle a^{\\prime}=R^{-1}a=R^{\\intercal}a.\\)</li> <li>\u65cb\u8f6c+\u5e73\u79fb: \\(\\displaystyle a^{\\prime}=Ra+t.\\)</li> </ul>"},{"location":"CV/SLAM14/#313","title":"3.1.3 \u53d8\u6362\u77e9\u9635\u4e0e\u9f50\u6b21\u5750\u6807","text":"<ul> <li>\u4f46\u662f\u8fd9\u91cc\u7684\u53d8\u6362\u5173\u7cfb\u4e0d\u662f\u4e00\u4e2a\u7ebf\u6027\u5173\u7cfb</li> <li>\\(\\displaystyle c=R_2\\left(R_1a+t_1\\right)+t_2\\)</li> <li>\u6211\u4eec\u6539\u5199\u4e00\u4e0b\u5f62\u5f0f:<ul> <li>\\(\\displaystyle \\begin{bmatrix}a'\\\\\\\\1\\end{bmatrix}=\\begin{bmatrix}R&amp;t\\\\\\\\\\mathbf{0}^\\mathrm{T}&amp;1\\end{bmatrix}\\begin{bmatrix}a\\\\\\\\1\\end{bmatrix}\\overset{\\mathrm{def}}{=}T\\begin{bmatrix}a\\\\\\\\1\\end{bmatrix}\\)</li> <li>\u8fd9\u5c31\u662f\u9f50\u6b21\u5750\u6807\uff0c\\(\\displaystyle \\boldsymbol{T}\\) \u79f0\u4e3a\u53d8\u6362\u77e9\u9635\uff08Transform matrix\uff09</li> </ul> </li> <li>\\(\\displaystyle \\tilde{b}=T_1\\tilde{\\boldsymbol{a}}, \\tilde{\\boldsymbol{c}}=T_2\\tilde{\\boldsymbol{b}}\\quad\\Rightarrow\\tilde{\\boldsymbol{c}}=T_2T_1\\tilde{\\boldsymbol{a}}.\\)</li> <li>\u5e76\u4e14 \\(\\displaystyle \\boldsymbol{T}\\) \u79f0\u4e3a\u7279\u6b8a\u6b27\u5f0f\u7fa4\uff08Special Euclidean Group\uff09<ul> <li>\\(\\displaystyle \\mathrm{SE}(3)=\\left\\{T=\\begin{bmatrix}R&amp;t\\\\\\mathbf{0}^\\mathrm{T}&amp;1\\end{bmatrix}\\in\\mathbb{R}^{4\\times4}|\\boldsymbol{R}\\in\\mathrm{SO}(3),\\boldsymbol{t}\\in\\mathbb{R}^3\\right\\}\\)</li> </ul> </li> <li>\\(\\displaystyle T^{-1}=\\begin{bmatrix}R^\\mathrm{T}&amp;-R^\\mathrm{T}t\\\\0^\\mathrm{T}&amp;1\\end{bmatrix}\\)</li> <li>\u5728 C++\u7a0b\u5e8f\u4e2d\u53ef\u4ee5\u4f7f\u7528\u8fd0\u7b97\u7b26\u91cd\u8f7d\u6765\u5904\u7406\u9f50\u6b21\u548c\u975e\u9f50\u6b21\u7684\u60c5\u51b5</li> </ul>"},{"location":"CV/SLAM14/#32-eigen","title":"3.2 \u5b9e\u8df5:Eigen","text":"C++<pre><code>#include &lt;iostream&gt;\nusing namespace std;\n\n#include &lt;ctime&gt;\n\n#include &lt;eigen3&gt;\nusing namespace Eigen;\n\n#define MATRIX_SIZE 50\n\nint main(int argc, char **argv) {\n    Matrix&lt;float, 2, 3&gt; matrix_23;\n// \u5982\u4e0b\u90fd\u662f\u4e09\u7ef4\u5411\u91cf\n    Vector3d v_3d;\n    Matrix&lt;float, 3, 1&gt; vd_3d;\n// \u5982\u4e0b\u662f3*3\u77e9\u9635\n    Matrix3d matrix_33 = Matrix3d::Zero();\n// \u4e24\u4e2a\u52a8\u6001\u5206\u914d\n    Matrix&lt;double, Dynamic, Dynamic&gt; matrix_dynamic;\n    MatrixXd matrix_x;\n\n    matrix_23 &lt;&lt; 1, 2, 3, 4, 5, 6;\n    cout&lt;&lt; \"matrix 2*3 from 1 to 6: \\n\" &lt;&lt; matrix_23 &lt;&lt; endl;\n\n    cout &lt;&lt; \"print matrix 2*3:\" &lt;&lt; endl;\n    for (int i = 0; i &lt; 2; i++) {\n        for (int j = 0; j &lt; 3; j+) cout &lt;&lt; matrix_23(i, j) &lt;&lt; \"\\t\";\n        cout &lt;&lt; endl;\n    }\n\n    v_3d &lt;&lt; 3, 2, 1;\n    vd_3d &lt;&lt; 4, 5, 6;\n\n    Matrix&lt;double, 2, 1&gt; result = matrix_23.cast&lt;double&gt;() * v_3d;\n    cout &lt;&lt; \"[1, 2, 3; 4, 5, 6] * [3, 2, 1] =\" &lt;&lt; result.transpose() &lt;&lt; endl;\n\n    matrix_22 = Matrix3d::Random();\n\n    // \u4e00\u4e9b\u77e9\u9635\u7684\u64cd\u4f5c:\n    // transpose()\n    // sum()\n    // trace()\n    // inverse()\n    // determinant()\n\n    SelfAdjointEigenSolver&lt;Matrix3d&gt; eigen_solver(matrix_33.transpose() * matrix_33);\n    cout &lt;&lt; eigen_solver.eigenvalues() &lt;&lt; endl;\n    cout &lt;&lt; eigen_solver.eigenvectors() &lt;&lt; endl;\n\n    // solve the equation\n    Matrix&lt;double, MATRIX_SIZE, MATRIX_SIZE&gt; matrix_NN = MatrixXd::Random(MATRIX_SIZE, MATRIX_SIZE);\n    matrix_NN = matrix_NN * matrix_NN.transpose()\n    Matrix&lt;double, MATRIX_SIZE, 1&gt; v_Nd = MatrixXd::random(MATRIX_SIZE, 1);\n\n    // \u7b2c\u4e00\u79cd:\u76f4\u63a5\u6c42\u9006\n    Matrix&lt;double, MATRIX_SIZE, 1&gt; x = matrix_NN.inverse() * v_Nd;\n\n    // \u7b2c\u4e8c\u79cd:\u77e9\u9635\u5206\u89e3\n    x = matrix_NN.colPivHouseholderQr().solve(v_Nd);\n\n}\n</code></pre> <ul> <li>Eigen \u4e0d\u652f\u6301\u81ea\u52a8\u7c7b\u578b\u63d0\u5347\uff0c\u5373\u4e0d\u4f1a\u9690\u5f0f\u8f6c\u6362</li> </ul>"},{"location":"CV/SLAM14/#33","title":"3.3 \u65cb\u8f6c\u5411\u91cf\u548c\u6b27\u62c9\u89d2","text":""},{"location":"CV/SLAM14/#331","title":"3.3.1 \u65cb\u8f6c\u5411\u91cf","text":"<ul> <li>Axis-Angle</li> <li>Rodrigues's Formula<ul> <li>\\(\\displaystyle \\boldsymbol{R}=\\cos\\theta\\boldsymbol{I}+\\left(1-\\cos\\theta\\right)\\boldsymbol{n}\\boldsymbol{n}^\\mathrm{T}+\\sin\\theta\\boldsymbol{n}^\\mathrm{\\wedge}.\\)</li> </ul> </li> </ul> \\[ \\begin{aligned} \\mathrm{tr}\\left(R\\right)&amp; =\\cos\\theta\\operatorname{tr}\\left(\\boldsymbol{I}\\right)+\\left(1-\\cos\\theta\\right)\\operatorname{tr}\\left(\\boldsymbol{n}\\boldsymbol{n}^\\mathrm{T}\\right)+\\sin\\theta\\operatorname{tr}(\\boldsymbol{n}^\\mathrm{\\Lambda}) \\\\ &amp;=3\\cos\\theta+(1-\\cos\\theta) \\\\ &amp;=1+2\\cos\\theta  \\end{aligned} \\] <p>thus:</p> \\[ \\theta=\\arccos\\frac{\\mathrm{tr}(R)-1}{2}. \\] \\[ Rn=n. \\] <ul> <li>\u5373 \\(\\displaystyle \\boldsymbol{n}\\) \u662f\u77e9\u9635 \\(\\displaystyle \\boldsymbol{R}\\) \u7279\u5f81\u503c 1 \u5bf9\u5e94\u7684\u7279\u8bca\u5411\u91cf</li> </ul>"},{"location":"CV/SLAM14/#332","title":"3.3.2 \u6b27\u62c9\u89d2","text":"<ul> <li>\u6bd4\u8f83\u5e38\u7528\u7684\u4e00\u79cd yaw-pitch-roll<ul> <li>ZYX</li> </ul> </li> <li>\u4f46\u4f1a\u6709 Gimbal Lock \u95ee\u9898<ul> <li>\u6240\u4ee5\u6b27\u62c9\u89d2\u6bd4\u8f83\u9002\u5408\u7528\u4e8e\u5feb\u901f\u68c0\u9a8c\u7ed3\u679c\u662f\u5426\u6709\u9519</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#34","title":"3.4 \u56db\u5143\u6570","text":""},{"location":"CV/SLAM14/#341","title":"3.4.1 \u56db\u5143\u6570\u7684\u5b9a\u4e49","text":"<ul> <li>\u6211\u4eec\u627e\u4e0d\u5230\u4e0d\u5e26\u5947\u5f02\u6027\u7684\u4e09\u4f4d\u5411\u91cf\u63cf\u8ff0\u65b9\u5f0f<ul> <li>\u627e\u4e0d\u5230\u4e00\u4e2a\u6d41\u5f62\uff1f</li> </ul> </li> <li>Quaternion<ul> <li>\u7d27\u51d1\u53c8\u6ca1\u6709\u5947\u5f02\u6027</li> <li>\u53ea\u662f\u4e0d\u591f\u76f4\u89c2+\u8fd0\u7b97\u590d\u6742</li> </ul> </li> <li>\\(\\displaystyle q=q_0+q_1\\mathrm{i}+\\mathrm{q}_2\\mathrm{j}+\\mathrm{q}_3\\mathrm{k}\\)</li> </ul> \\[ \\begin{cases}\\mathbf{i}^2=\\mathbf{j}^2=\\mathbf{k}^2=-1\\\\\\mathbf{ij}=\\mathbf{k},\\mathbf{ji}=-\\mathbf{k}\\\\\\mathbf{jk}=\\mathbf{i},\\mathbf{kj}=-\\mathbf{i}\\\\\\mathbf{ki}=\\mathbf{j},\\mathbf{ik}=-\\mathbf{j}\\end{cases} \\] <ul> <li>(\u4e5f\u8bb8\u53ef\u4ee5\u7528\u5ea6\u89c4\u6765\u8868\u793a\uff1f)</li> <li>\\(\\displaystyle \\boldsymbol{q}=\\left[s,\\boldsymbol{v}\\right]^\\mathrm{T},\\quad s=q_0\\in\\mathbb{R},\\quad\\boldsymbol{v}=\\left[q_1,q_2,q_3\\right]^\\mathrm{T}\\in\\mathbb{R}^3.\\)</li> <li>\u4e66\u4e0a\u6ca1\u5199\u76f4\u89c2\u7684\u51e0\u4f55\u5bf9\u5e94</li> </ul>"},{"location":"CV/SLAM14/#342","title":"3.4.2 \u56db\u5143\u6570\u7684\u8fd0\u7b97","text":"<ul> <li>\u4e58\u6cd5: \\(\\displaystyle \\boldsymbol{q}_a\\boldsymbol{q}_b=\\begin{bmatrix}s_as_b-\\boldsymbol{v}_a^\\mathrm{T}\\boldsymbol{v}_b,s_a\\boldsymbol{v}_b+s_b\\boldsymbol{v}_a+\\boldsymbol{v}_a\\times\\boldsymbol{v}_b\\end{bmatrix}^\\mathrm{T}.\\)<ul> <li>\u7531\u4e8e\u6700\u540e\u4e00\u9879\u7684\u5b58\u5728\uff0c\u4e58\u6cd5\u4e0d\u5177\u6709\u4ea4\u6362\u5f8b</li> </ul> </li> <li>\u5171\u8f6d: \\(\\displaystyle q_a^*=s_a-x_a\\mathrm{i}-\\mathrm{y_aj}-\\mathrm{z_ak}=[\\mathrm{s_a},-\\mathrm{v_a}]^\\mathrm{T}.\\)<ul> <li>\\(\\displaystyle q^*q=qq^*=[s_a^2+\\boldsymbol{v}^\\mathrm{T}\\boldsymbol{v},\\boldsymbol{0}]^\\mathrm{T}.\\)</li> </ul> </li> <li>\u9006: \\(\\displaystyle q^{-1}=q^*/\\|q\\|^2.\\)<ul> <li>\\(\\displaystyle (\\boldsymbol{q}_a\\boldsymbol{q}_b)^{-1}=\\boldsymbol{q}_b^{-1}\\boldsymbol{q}_a^{-1}.\\)</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#343","title":"3.4.3 \u7528\u56db\u5143\u6570\u8868\u793a\u65cb\u8f6c","text":"<ul> <li>\u5148\u8868\u793a\u4e09\u7ef4\u7a7a\u95f4\u70b9:<ul> <li>\\(\\displaystyle p=[0,x,y,z]^{\\mathrm{T}}=[0,\\boldsymbol{v}]^{\\mathrm{T}}.\\)</li> </ul> </li> <li>\u518d\u65cb\u8f6c:<ul> <li>\\(\\displaystyle p'=qpq^{-1}.\\)</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#344","title":"3.4.4 \u56db\u5143\u6570\u5230\u5176\u4ed6\u65cb\u8f6c\u8868\u793a\u7684\u8f6c\u6362","text":"<ul> <li>\u8bbe \\(\\displaystyle \\boldsymbol{q} = [s,\\boldsymbol{v}]^\\mathrm{T}\\)<ul> <li>\\(\\displaystyle \\boldsymbol{q}^+=\\begin{bmatrix}s&amp;-\\boldsymbol{v}^\\mathrm{T}\\\\\\\\\\boldsymbol{v}&amp;s\\boldsymbol{I}+\\boldsymbol{v}^\\wedge\\end{bmatrix},\\quad\\boldsymbol{q}^\\oplus=\\begin{bmatrix}s&amp;-\\boldsymbol{v}^\\mathrm{T}\\\\\\\\\\boldsymbol{v}&amp;s\\boldsymbol{I}-\\boldsymbol{v}^\\wedge\\end{bmatrix}.\\)</li> <li>\\(\\displaystyle q_1^+q_2=\\begin{bmatrix}s_1&amp;-\\boldsymbol{v}_1^\\mathrm{T}\\\\\\\\\\boldsymbol{v}_1&amp;s_1\\boldsymbol{I}+\\boldsymbol{v}_1^\\wedge\\end{bmatrix}\\begin{bmatrix}s_2\\\\\\\\\\boldsymbol{v}_2\\end{bmatrix}=\\begin{bmatrix}-\\boldsymbol{v}_1^\\mathrm{T}\\boldsymbol{v}_2+s_1s_2\\\\\\\\s_1\\boldsymbol{v}_2+s_2\\boldsymbol{v}_1+\\boldsymbol{v}_1^\\wedge\\boldsymbol{v}_2\\end{bmatrix}=\\boldsymbol{q}_1\\boldsymbol{q}_2.\\)</li> <li>\u540c\u7406\u53ef\u8bc1:<ul> <li>\\(\\displaystyle q_1q_2=q_1^+q_2=q_2^\\oplus q_1.\\)</li> </ul> </li> </ul> </li> <li>\u518d\u6765\u8003\u8651\u65cb\u8f6c:<ul> <li>\\(\\displaystyle \\begin{aligned}p^{\\prime}&amp;=qpq^{-1}=q^{+}p^{+}q^{-1}\\\\&amp;=q^{+}q^{-1^{\\oplus}}p.\\end{aligned}\\)</li> <li>\u4e8e\u662f\u53ef\u4ee5\u5f97\u5230:<ul> <li>\\(\\displaystyle \\boldsymbol{q}^{+}\\big(\\boldsymbol{q}^{-1}\\big)^{\\oplus}=\\begin{bmatrix}s&amp;-\\boldsymbol{v}^{\\mathrm{T}}\\\\\\boldsymbol{v}&amp;s\\boldsymbol{I}+\\boldsymbol{v}^{\\wedge}\\end{bmatrix}\\begin{bmatrix}s&amp;\\boldsymbol{v}^{\\mathrm{T}}\\\\-\\boldsymbol{v}&amp;s\\boldsymbol{I}+\\boldsymbol{v}^{\\wedge}\\end{bmatrix}=\\begin{bmatrix}1&amp;\\boldsymbol{0}\\\\\\boldsymbol{0}^{\\mathrm{T}}&amp;\\boldsymbol{v}\\boldsymbol{v}^{\\mathrm{T}}+s^{2}\\boldsymbol{I}+2s\\boldsymbol{v}^{\\wedge}+\\left(\\boldsymbol{v}^{\\wedge}\\right)^{2}\\end{bmatrix}.\\)</li> <li>\u5373: \\(\\displaystyle R=\\boldsymbol{v}\\boldsymbol{v}^\\mathrm{T}+s^2\\boldsymbol{I}+2s\\boldsymbol{v}^\\wedge+\\left(\\boldsymbol{v}^\\wedge\\right)^2.\\)</li> </ul> </li> </ul> </li> </ul> \\[ \\begin{aligned} \\operatorname{tr}(R)&amp; =\\mathbf{tr}(\\boldsymbol{vv}^\\mathrm{T}+3s^2+2s\\cdot0+\\mathbf{tr}((\\boldsymbol{v}^\\wedge)^2) \\\\ &amp;=v_{1}^{2}+v_{2}^{2}+v_{3}^{2}+3s^{2}-2(v_{1}^{2}+v_{2}^{2}+v_{3}^{2}) \\\\ &amp;=(1-s^2)+3s^2-2(1-s^2) \\\\ &amp;=4s^2-1. \\end{aligned} \\] <ul> <li>\u5373 \\(\\displaystyle \\theta=2\\arccos s.\\)</li> <li>\u518d\u52a0\u4e0a\u65cb\u8f6c\u8f74:</li> </ul> \\[ \\begin{cases}\\theta=2\\arccos q_0\\\\ [n_x,n_y,n_z]^\\mathrm{T}=[q_1,q_2,q_3]^\\mathrm{T}/\\sin\\frac{\\theta}{2}\\end{cases}. \\]"},{"location":"CV/SLAM14/#35","title":"3.5 \u76f8\u4f3c\u3001\u4eff\u5c04\u3001\u5c04\u5f71\u53d8\u6362","text":"<ol> <li>\u76f8\u4f3c\u53d8\u6362:</li> </ol> \\[ \\boldsymbol{T}_S=\\begin{bmatrix}s\\boldsymbol{R}&amp;t\\\\\\mathbf{0}^\\mathrm{T}&amp;1\\end{bmatrix}. \\] <p>\u5141\u8bb8\u7f29\u653e\uff0c\u76f8\u4f3c\u53d8\u6362\u7fa4: Sim (3) 2. \u4eff\u5c04\u53d8\u6362:</p> \\[ T_A=\\begin{bmatrix}A&amp;t\\\\\\mathbf{0}^\\mathrm{T}&amp;1\\end{bmatrix}. \\] <p>\u53ea\u4fdd\u8bc1\u5e73\u884c\u5173\u7cfb 3. \u5c04\u5f71\u53d8\u6362</p> \\[ T_P=\\begin{bmatrix}A&amp;t\\\\\\\\a^\\mathrm{T}&amp;v\\end{bmatrix}. \\] <p>\u603b\u7ed3\u4e00\u4e0b:</p> \\[ \\begin{array}{c|c|c|c}\\hline\\text{\u53d8\u6362\u540d\u79f0}&amp;\\text{\u77e9\u9635\u5f62\u5f0f}&amp;\\text{\u81ea\u7531\u5ea6}&amp;\\text{\u4e0d\u53d8\u6027\u8d28}\\\\\\hline\\text{\u6b27\u6c0f\u53d8\u6362}&amp;\\begin{bmatrix}R&amp;t\\\\0^\\mathrm{T}&amp;1\\end{bmatrix}&amp;6&amp;\\text{\u957f\u5ea6\u3001\u5939\u89d2\u3001\u4f53\u79ef}\\\\\\text{\u76f8\u4f3c\u53d8\u6362}&amp;\\begin{bmatrix}sR&amp;t\\\\0^\\mathrm{T}&amp;1\\end{bmatrix}&amp;7&amp;\\text{\u4f53\u79ef\u6bd4}\\\\\\text{\u4eff\u5c04\u53d8\u6362}&amp;\\begin{bmatrix}A&amp;t\\\\0^\\mathrm{T}&amp;1\\end{bmatrix}&amp;12&amp;\\text{\u5e73\u884c\u6027\u3001\u4f53\u79ef\u6bd4}\\\\\\text{\u5c04\u5f71\u53d8\u6362}&amp;\\begin{bmatrix}A&amp;t\\\\a^\\mathrm{T}&amp;v\\end{bmatrix}&amp;15&amp;\\text{\u63a5\u89e6\u5e73\u9762\u7684\u76f8\u4ea4\u548c\u76f8\u5207}\\\\\\hline\\end{array} \\]"},{"location":"CV/SLAM14/#36-eigen","title":"3.6 \u5b9e\u8df5: Eigen \u51e0\u4f55\u6a21\u5757","text":""},{"location":"CV/SLAM14/#361-eigen","title":"3.6.1 Eigen \u51e0\u4f55\u6a21\u5757\u7684\u6570\u636e\u6f14\u793a","text":"<p>\u518d\u8bf4\u5427\u3002</p>"},{"location":"CV/SLAM14/#362","title":"3.6.2 \u5b9e\u9645\u7684\u5750\u6807\u53d8\u6362\u4f8b\u5b50","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#37","title":"3.7 \u53ef\u89c6\u5316\u6f14\u793a","text":""},{"location":"CV/SLAM14/#371","title":"3.7.1 \u663e\u793a\u8fd0\u52a8\u8f68\u8ff9","text":"<ul> <li>\u7528 Pangolin \u5e93</li> <li>TODO</li> </ul>"},{"location":"CV/SLAM14/#372","title":"3.7.2 \u663e\u793a\u76f8\u673a\u7684\u4f4d\u59ff","text":""},{"location":"CV/SLAM14/#38","title":"3.8 \u4e60\u9898","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#4","title":"4 \u674e\u7fa4\u548c\u674e\u4ee3\u6570","text":"<ul> <li>\u7531\u4e8e\u65cb\u8f6c\u77e9\u9635\u672c\u8eab\u5e26\u6709\u7ea6\u675f\uff08\u6b63\u4ea4\u4e14\u884c\u5217\u5f0f\u4e3a 1\uff09\uff0c\u8ba9\u4f18\u5316\u53d8\u5f97\u56f0\u96be\u3002</li> <li>\u6240\u4ee5\u6211\u4eec\u5f15\u5165\u674e\u7fa4-\u674e\u4ee3\u6570\u95f4\u7684\u8f6c\u6362\u5173\u7cfb\uff0c\u628a\u4f4d\u59ff\u4f30\u8ba1\u53d8\u6210\u65e0\u7ea6\u675f\u7684\u4f18\u5316\u95ee\u9898</li> </ul>"},{"location":"CV/SLAM14/#41","title":"4.1 \u674e\u7fa4\u548c\u674e\u4ee3\u6570\u57fa\u7840","text":"<ul> <li>\u4e09\u7ef4\u65cb\u8f6c\u77e9\u9635\u6784\u6210\u4e86\u7279\u6b8a\u6b63\u4ea4\u7fa4 \\(\\displaystyle \\boldsymbol{SO}(3)\\)</li> <li>\u53d8\u6362\u77e9\u9635\u6784\u6210\u4e86\u7279\u6b8a\u6b27\u6c0f\u7fa4 \\(\\displaystyle \\boldsymbol{SE}(3)\\)<ul> <li>\u4f46\u662f\u4ed6\u4eec\u90fd\u5bf9\u52a0\u6cd5\u4e0d\u5c01\u95ed</li> <li>\u5bf9\u4e58\u6cd5\u5c01\u95ed</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#411","title":"4.1.1 \u7fa4","text":"<ul> <li>\\(\\displaystyle G = (A,\\cdot)\\) \u6ee1\u8db3:<ul> <li>\u5c01\u95ed\u6027</li> <li>\u7ed3\u5408\u5f8b</li> <li>\u5e7a\u5143</li> <li>\u9006</li> </ul> </li> <li>\u674e\u7fa4\u662f\u5177\u6709\u8fde\u7eed\uff08\u5149\u6ed1\uff09\u6027\u8d28\u7684\u7fa4</li> </ul>"},{"location":"CV/SLAM14/#412","title":"4.1.2 \u674e\u4ee3\u6570\u7684\u5f15\u51fa","text":"<ul> <li>\\(\\displaystyle \\boldsymbol{R}\\boldsymbol{R}^\\mathrm{T} = \\boldsymbol{I}\\)</li> <li>\u6211\u4eec\u6613\u5f97: \\(\\displaystyle \\dot{\\boldsymbol{R}}(t)\\boldsymbol{R}(t)^\\mathrm{T}=-\\left(\\dot{\\boldsymbol{R}}(t)\\boldsymbol{R}(t)^\\mathrm{T}\\right)^\\mathrm{T}.\\)<ul> <li>\u5373 \\(\\displaystyle \\dot{\\boldsymbol{R}}(t)\\boldsymbol{R}(t)^\\mathrm{T}\\) \u662f\u53cd\u5bf9\u79f0</li> </ul> </li> <li>\u800c\u5bf9\u4e8e\u4efb\u610f\u53cd\u5bf9\u79f0\u77e9\u9635\uff0c\u6211\u4eec\u90fd\u53ef\u4ee5\u627e\u5230\u552f\u4e00\u4e0e\u4e4b\u5bf9\u5e94\u7684\u5411\u91cf<ul> <li>\\(\\displaystyle \\dot{\\boldsymbol{R}}(t)\\boldsymbol{R}(t)^\\mathrm{T}=\\boldsymbol{\\phi}(t)^{\\wedge}.\\)</li> <li>\\(\\displaystyle \\dot{\\boldsymbol{R}}(t)=\\phi(t)^{\\wedge}\\boldsymbol{R}(t)=\\begin{bmatrix}0&amp;-\\phi_3&amp;\\phi_2\\\\\\phi_3&amp;0&amp;-\\phi_1\\\\-\\phi_2&amp;\\phi_1&amp;0\\end{bmatrix}\\boldsymbol{R}(t).\\) \u8003\u8651 \\(\\displaystyle t_{0} = 0\\) \u548c \\(\\displaystyle \\boldsymbol{R}(0) = \\boldsymbol{I}\\) \u65f6:</li> </ul> </li> </ul> \\[ \\begin{aligned} R(t)&amp; \\approx\\boldsymbol{R}\\left(t_{0}\\right)+\\dot{\\boldsymbol{R}}\\left(t_{0}\\right)\\left(t-t_{0}\\right) \\\\ &amp;=I+\\phi(t_0)^{\\wedge}(t). \\end{aligned} \\] <p>\u4e8e\u662f\u6c42\u5bfc-&gt;\u4e00\u4e2a\u7b97\u7b26 \\(\\displaystyle \\phi\\) \uff0c\u88ab\u79f0\u4e3a \\(\\displaystyle \\boldsymbol{SO}(3)\\) \u539f\u70b9\u9644\u8fd1\u7684\u6b63\u5207\u7a7a\u95f4\uff08Tangent Space\uff09 \u8bbe\u5728 \\(\\displaystyle t_{0}\\) \u9644\u8fd1\uff0c\\(\\displaystyle \\phi\\) \u4fdd\u6301\u5e38\u6570 \\(\\displaystyle \\phi(t_{0})=\\phi_{0}\\)\uff0c</p> \\[ \\dot{\\boldsymbol{R}}(t)=\\boldsymbol{\\phi}(t_0)^\\wedge\\boldsymbol{R}(t)=\\boldsymbol{\\phi}_0^\\wedge\\boldsymbol{R}(t). \\] <p>\u518d\u6709 \\(\\displaystyle \\boldsymbol{R}(0) = \\boldsymbol{I}\\)\uff0c\u89e3\u7684:</p> \\[ \\boldsymbol{R}(t)=\\exp\\left(\\boldsymbol{\\phi}_{0}^{\\wedge}t\\right). \\] <ul> <li>\\(\\displaystyle \\phi\\) \u6b63\u662f\u5bf9\u5e94\u5230 \\(\\displaystyle SO(3)\\) \u4e0a\u7684\u674e\u4ee3\u6570 \\(\\displaystyle \\mathfrak{so}(3)\\)</li> <li>\\(\\displaystyle \\begin{aligned}&amp;\\text{\u5176\u6b21,\u7ed9\u5b9a\u67d0\u4e2a\u5411\u91cf }\\phi\\text{ \u65f6,\u77e9\u9635\u6307\u6570}\\exp(\\phi^{\\wedge})\\text{ \u5982\u4f55\u8ba1\u7b97? \u53cd\u4e4b,\u7ed9\u5b9a }R\\text{ \u65f6,\u80fd\u5426\u6709\u76f8\u53cd}\\\\&amp;\\text{\u7684\u8fd0\u7b97\u6765\u8ba1\u7b97 }\\phi?\\text{ \u4e8b\u5b9e\u4e0a,\u8fd9\u6b63\u662f\u674e\u7fa4\u4e0e\u674e\u4ee3\u6570\u95f4\u7684\u6307\u6570}/\\text{\u5bf9\u6570\u6620\u5c04\u3002}\\end{aligned}\\)</li> </ul>"},{"location":"CV/SLAM14/#413","title":"4.1.3 \u674e\u4ee3\u6570\u7684\u5b9a\u4e49","text":"<p>\u674e\u4ee3\u6570\u7531\u4e00\u4e2a\u96c6\u5408 \\(\\displaystyle \\mathbb{V}\\)\u3001\u4e00\u4e2a\u6570\u57df \\(\\displaystyle \\mathbb{F}\\) \u548c\u4e00\u4e2a\u4e8c\u5143\u8fd0\u7b97 \\(\\displaystyle [,]\\) \u7ec4\u6210\u3002\u5982\u679c\u6ee1\u8db3\u4ee5\u4e0b\u51e0\u6761\u6027\u8d28\uff0c\u5219\u79f0 ( \\(\\displaystyle \\mathbb{V},\\mathbb{F},[,]\\)) \u4e3a\u4e00\u4e2a\u674e\u4ee3\u6570\uff0c\u8bb0\u4f5c \\(\\displaystyle \\mathfrak{g}\\)\u3002</p> <ol> <li>\u5c01\u95ed\u6027</li> <li>\u53cc\u7ebf\u6027</li> <li>\u81ea\u53cd\u6027 \\(\\displaystyle \\quad\\forall \\boldsymbol{X}\\in\\mathbb{V},[\\boldsymbol{X},\\boldsymbol{X}]=0\\)</li> <li>\u96c5\u53ef\u6bd4\u7b49\u4ef7 \\(\\displaystyle \\forall X,Y,Z\\in\\mathbb{V},[X,[Y,Z]]+[Z,[X,Y]]+[Y,[Z,X]]=0.\\) \u5176\u4e2d\u4e8c\u5143\u8fd0\u7b97\u88ab\u79f0\u4e3a\u674e\u62ec\u53f7\u3002 eg: \u53c9\u79ef\u662f\u4e00\u79cd\u674e\u62ec\u53f7</li> </ol>"},{"location":"CV/SLAM14/#414-displaystyle-mathfrakso3","title":"4.1.4 \u674e\u4ee3\u6570 \\(\\displaystyle \\mathfrak{so}(3)\\)","text":"<p>\\(\\displaystyle \\boldsymbol{\\Phi}=\\boldsymbol{\\phi}^{\\wedge}=\\begin{bmatrix}0&amp;-\\phi_3&amp;\\phi_2\\\\\\\\\\phi_3&amp;0&amp;-\\phi_1\\\\\\\\-\\phi_2&amp;\\phi_1&amp;0\\end{bmatrix}\\in\\mathbb{R}^{3\\times3}.\\) \u6240\u4ee5\u4e24\u4e2a\u5411\u91cf \\(\\displaystyle \\phi_{1},\\phi_{2}\\) \u7684\u674e\u62ec\u53f7\u4e3a:</p> \\[ [\\phi_1,\\phi_2]=(\\boldsymbol{\\Phi}_1\\boldsymbol{\\Phi}_2-\\boldsymbol{\\Phi}_2\\boldsymbol{\\Phi}_1)^\\vee. \\] \\[ \\mathfrak{so}(3)=\\left\\{\\phi\\in\\mathbb{R}^3,\\boldsymbol{\\Phi}=\\phi^\\wedge\\in\\mathbb{R}^{3\\times3}\\right\\}. \\] \\[ R=\\exp(\\phi^{\\wedge}). \\]"},{"location":"CV/SLAM14/#415-displaystyle-mathfrakse3","title":"4.1.5 \u674e\u4ee3\u6570 \\(\\displaystyle \\mathfrak{se}(3)\\)","text":"\\[ \\mathfrak{se}(3)=\\left\\{\\boldsymbol{\\xi}=\\begin{bmatrix}\\boldsymbol{\\rho}\\\\\\boldsymbol{\\phi}\\end{bmatrix}\\in\\mathbb{R}^6,\\boldsymbol{\\rho}\\in\\mathbb{R}^3,\\boldsymbol{\\phi}\\in\\mathfrak{so}(3),\\boldsymbol{\\xi}^\\wedge=\\begin{bmatrix}\\boldsymbol{\\phi}^\\wedge&amp;\\boldsymbol{\\rho}\\\\\\boldsymbol{0}^\\mathrm{T}&amp;0\\end{bmatrix}\\in\\mathbb{R}^{4\\times4}\\right\\}. \\] <p>\u524d\u4e09\u7ef4\u4e3a\u5e73\u79fb\uff0c\u540e\u4e09\u7ef4\u4e3a\u65cb\u8f6c\uff08\u5b9e\u8d28\u4e0a\u662f \\(\\displaystyle \\mathfrak{so}(3)\\) \u5143\u7d20\uff09</p> \\[ \\xi^\\wedge=\\begin{bmatrix}\\phi^\\wedge&amp;\\rho\\\\0^\\mathrm{T}&amp;0\\end{bmatrix}\\in\\mathbb{R}^{4\\times4}. \\] <p>\u540c\u6837\u674e\u4ee3\u6570 \\(\\displaystyle \\mathfrak{se}(3)\\) \u4e5f\u6709\u7c7b\u4f3c\u4e8e \\(\\displaystyle \\mathfrak{so}(3)\\) \u7684\u674e\u62ec\u53f7:</p> \\[ [\\xi_1,\\xi_2]=\\left(\\xi_1^\\wedge\\xi_2^\\wedge-\\xi_2^\\wedge\\xi_1^\\wedge\\right)^\\vee. \\]"},{"location":"CV/SLAM14/#42","title":"4.2 \u6307\u6570\u4e0e\u5bf9\u6570\u6620\u5c04","text":""},{"location":"CV/SLAM14/#421-so3","title":"4.2.1 SO(3)\u4e0a\u7684\u6307\u6570\u6620\u5c04","text":"<ul> <li>Exponential Map</li> <li>\u9996\u5148\u4efb\u610f\u77e9\u9635\u7684\u6307\u6570\u6620\u5c04\u53ef\u4ee5\u5199\u6210\u4e00\u4e2a\u6cf0\u52d2\u5c55\u5f00\uff08\u6536\u655b\u7684\u65f6\u5019\uff09</li> </ul> \\[ \\exp(A)=\\sum_{n=0}^\\infty\\frac1{n!}A^n. \\] <ul> <li>\u5e94\u7528\u5230 \\(\\displaystyle \\mathfrak{so}(3)\\) \u4e2d:</li> </ul> \\[ \\exp(\\phi^\\wedge)=\\sum_{n=0}^\\infty\\frac{1}{n!}(\\phi^\\wedge)^n. \\] <ul> <li>\u6211\u4eec\u53ef\u4ee5\u628a \\(\\displaystyle \\phi\\) \u8868\u793a\u6210 \\(\\displaystyle \\theta \\boldsymbol{a}\\)\uff0c\u5bf9\u4e8e \\(\\displaystyle \\boldsymbol{a}^\\wedge\\):</li> </ul> \\[ \\boldsymbol{a}^{\\wedge}\\boldsymbol{a}^{\\wedge}=\\begin{bmatrix}-a_2^2-a_3^2&amp;a_1a_2&amp;a_1a_3\\\\\\\\a_1a_2&amp;-a_1^2-a_3^2&amp;a_2a_3\\\\\\\\a_1a_3&amp;a_2a_3&amp;-a_1^2-a_2^2\\end{bmatrix}=\\boldsymbol{a}\\boldsymbol{a}^\\mathrm{T}-\\boldsymbol{I}, \\] <p>\u548c</p> \\[ a^{\\wedge}a^{\\wedge}a^{\\wedge}=a^{\\wedge}(aa^{\\mathrm{T}}-I)=-a^{\\wedge}. \\] <p>\u4e8e\u662f\u6211\u4eec\u53ef\u4ee5\u5316\u7b80:</p> \\[ \\begin{aligned} \\exp\\left(\\phi^\\wedge\\right)&amp; =\\exp\\left(\\theta\\boldsymbol{a}^\\wedge\\right)=\\sum_{n=0}^\\infty\\frac1{n!}\\left(\\theta\\boldsymbol{a}^\\wedge\\right)^n \\\\ &amp;=I+\\theta\\boldsymbol{a}^{\\wedge}+\\frac{1}{2!}\\theta^{2}\\boldsymbol{a}^{\\wedge}\\boldsymbol{a}^{\\wedge}+\\frac{1}{3!}\\theta^{3}\\boldsymbol{a}^{\\wedge}\\boldsymbol{a}^{\\wedge}\\boldsymbol{a}^{\\wedge}+\\frac{1}{4!}\\theta^{4}(\\boldsymbol{a}^{\\wedge})^{4}+\\cdots \\\\ &amp;=\\boldsymbol{a}\\boldsymbol{a}^{\\mathrm{T}}-\\boldsymbol{a}^{\\wedge}\\boldsymbol{a}^{\\wedge}+\\theta\\boldsymbol{a}^{\\wedge}+\\frac{1}{2!}\\theta^{2}\\boldsymbol{a}^{\\wedge}\\boldsymbol{a}^{\\wedge}-\\frac{1}{3!}\\theta^{3}\\boldsymbol{a}^{\\wedge}-\\frac{1}{4!}\\theta^{4}(\\boldsymbol{a}^{\\wedge})^{2}+\\cdots \\\\ &amp;=\\boldsymbol{a}\\boldsymbol{a}^{\\mathsf{T}}+\\underbrace{\\left(\\theta-\\frac{1}{3!}\\theta^{3}+\\frac{1}{5!}\\theta^{5}-\\cdots\\right)}_{\\sin\\theta}\\boldsymbol{a}^{\\wedge}-\\underbrace{\\left(1-\\frac{1}{2!}\\theta^{2}+\\frac{1}{4!}\\theta^{4}-\\cdots\\right)}_{\\cos\\theta}\\boldsymbol{a}^{\\wedge}\\boldsymbol{a}^{\\wedge} \\\\ &amp;=a^\\wedge a^\\wedge+I+\\sin\\theta a^\\wedge-\\cos\\theta a^\\wedge a^\\wedge \\\\ &amp;=(1-\\cos\\theta)\\boldsymbol{a}^\\wedge\\boldsymbol{a}^\\wedge+\\boldsymbol{I}+\\sin\\theta\\boldsymbol{a}^\\wedge \\\\ &amp;=\\cos\\theta\\boldsymbol{I}+(1-\\cos\\theta)\\boldsymbol{aa}^\\mathrm{T}+\\sin\\theta\\boldsymbol{a}^\\mathrm{\\wedge}. \\end{aligned} \\] <p>\u6700\u540e\u5f97\u5230:</p> \\[ \\exp(\\theta\\boldsymbol{a}^\\wedge)=\\cos\\theta\\boldsymbol{I}+(1-\\cos\\theta)\\boldsymbol{a}\\boldsymbol{a}^\\mathrm{T}+\\sin\\theta\\boldsymbol{a}^\\wedge. \\] <p>\u6240\u4ee5 \\(\\displaystyle \\mathfrak{so}(3)\\) \u5c31\u662f\u65cb\u91cf\u5411\u91cf\u7ec4\u6210\u7684\u7a7a\u95f4\uff0c\u800c\u6307\u6570\u6620\u5c04\u5373\u7f57\u5fb7\u91cc\u683c\u65af\u516c\u5f0f\u3002</p> <ul> <li>\u901a\u8fc7\u4e0a\u9762\u7684\u516c\u5f0f\uff0c\u6211\u4eec\u53ef\u4ee5\u628a \\(\\displaystyle \\mathfrak{so}(3)\\) \u4e2d\u4efb\u610f\u5411\u91cf\u5bf9\u5e94\u5230 SO (3) \u4e2d\u7684\u65cb\u8f6c\u77e9\u9635</li> <li>\u53cd\u8fc7\u6765\u4e5f\u662f\u53ef\u4ee5\u7684</li> </ul> \\[ \\phi=\\ln\\left(\\boldsymbol{R}\\right)^\\vee=\\left(\\sum_{n=0}^\\infty\\frac{\\left(-1\\right)^n}{n+1}\\left(\\boldsymbol{R}-\\boldsymbol{I}\\right)^{n+1}\\right)^\\vee. \\]"},{"location":"CV/SLAM14/#422-se-3","title":"4.2.2 SE (3) \u4e0a\u7684\u6307\u6570\u6620\u5c04","text":"<p>\u540c\u6837\u7684\u63a8\u5bfc\u65b9\u5f0f:</p> \\[ \\begin{aligned} \\exp\\left(\\xi^{\\wedge}\\right)&amp; =\\begin{bmatrix}\\sum_{n=0}^{\\infty}\\frac{1}{n!}(\\phi^{\\wedge})^{n}&amp;\\sum_{n=0}^{\\infty}\\frac{1}{(n+1)!}(\\phi^{\\wedge})^{n}\\rho\\\\\\\\\\mathbf{0}^{\\mathrm{T}}&amp;1\\end{bmatrix} \\\\ &amp;\\stackrel{\\Delta}{=}\\begin{bmatrix}R&amp;J\\rho\\\\\\\\0^\\mathrm{T}&amp;1\\end{bmatrix}=T. \\end{aligned} \\] \\[ \\begin{aligned} \\sum_{n=0}^{\\infty}\\frac{1}{(n+1)!}(\\phi^{\\wedge})^{n}&amp; =\\boldsymbol{I}+\\frac{1}{2!}\\theta\\boldsymbol{a}^{\\wedge}+\\frac{1}{3!}\\theta^{2}{(\\boldsymbol{a}^{\\wedge})}^{2}+\\frac{1}{4!}\\theta^{3}{(\\boldsymbol{a}^{\\wedge})}^{3}+\\frac{1}{5!}\\theta^{4}{(\\boldsymbol{a}^{\\wedge})}^{4}\\cdots  \\\\ &amp;=\\frac{1}{\\theta}\\left(\\frac{1}{2!}\\theta^{2}-\\frac{1}{4!}\\theta^{4}+\\cdots\\right)(\\boldsymbol{a}^{\\wedge})+\\frac{1}{\\theta}\\left(\\frac{1}{3!}\\theta^{3}-\\frac{1}{5}\\theta^{5}+\\cdots\\right)(\\boldsymbol{a}^{\\wedge})^{2}+\\boldsymbol{I} \\\\ &amp;=\\frac1\\theta\\left(1-\\cos\\theta\\right)\\left(\\boldsymbol{a}^{\\wedge}\\right)+\\frac{\\theta-\\sin\\theta}\\theta\\left(\\boldsymbol{a}\\boldsymbol{a}^{\\mathrm{T}}-\\boldsymbol{I}\\right)+\\boldsymbol{I} \\\\ &amp;=\\frac{\\sin\\theta}\\theta\\boldsymbol{I}+\\left(1-\\frac{\\sin\\theta}\\theta\\right)\\boldsymbol{aa}^\\mathrm{T}+\\frac{1-\\cos\\theta}\\theta\\boldsymbol{a}^\\mathrm{\\wedge}\\overset{\\mathrm{def}}{\\operatorname*{=}}\\boldsymbol{J}. \\end{aligned} \\] \\[ \\boldsymbol{J}=\\frac{\\sin\\theta}{\\theta}\\boldsymbol{I}+\\left(1-\\frac{\\sin\\theta}{\\theta}\\right)\\boldsymbol{a}\\boldsymbol{a}^\\mathrm{T}+\\frac{1-\\cos\\theta}{\\theta}\\boldsymbol{a}^\\mathrm{\\wedge}. \\] <p>4.28 \u6ca1\u770b\u61c2 </p>"},{"location":"CV/SLAM14/#43","title":"4.3 \u674e\u4ee3\u6570\u6c42\u5bfc\u4e0e\u6270\u52a8\u6a21\u578b","text":""},{"location":"CV/SLAM14/#431-bch","title":"4.3.1 BCH \u516c\u5f0f\u4e0e\u8fd1\u4f3c\u5f62\u5f0f","text":"<p>\u63a2\u7a76\u5982\u4e0b\u5f0f\u5b50\u662f\u5426\u6210\u7acb:</p> \\[ \\ln\\left(\\exp\\left(A\\right)\\exp\\left(B\\right)\\right)=A+B ? \\] <p>\u4f46\u5b83\u5e76\u4e0d\u6210\u7acb\u3002\u4e24\u4e2a\u674e\u4ee3\u6570\u6307\u6570\u6620\u5c04\u4e58\u79ef\u7684\u5b8c\u6574\u5f62\u5f0f\uff0c\u7531 Baker-Campbell-Hausdorff \u7ed9\u51fa:</p> \\[ \\ln\\left(\\exp\\left(A\\right)\\exp\\left(B\\right)\\right)=A+B+\\frac{1}{2}\\left[A,B\\right]+\\frac{1}{12}\\left[A,\\left[A,B\\right]\\right]-\\frac{1}{12}\\left[B,\\left[A,B\\right]\\right]+\\cdots \\] <p>\u7279\u522b\u7684\uff0c\u5f53 \\(\\displaystyle \\phi_{1}\\) \u6216 \\(\\displaystyle \\phi_{2}\\) \u4e3a\u5c0f\u91cf\u65f6\uff0c\u5c0f\u91cf\u4e8c\u6b21\u4ee5\u4e0a\u7684\u9879\u90fd\u53ef\u4ee5\u88ab\u5ffd\u7565\uff0c\u6b64\u65f6\u7684\u7ebf\u6027\u8fd1\u4f3c\u8868\u8fbe:</p> \\[ \\ln\\left(\\exp\\left(\\phi_1^\\wedge\\right)\\exp\\left(\\phi_2^\\wedge\\right)\\right)^\\vee\\approx\\begin{cases}J_l(\\phi_2)^{-1}\\phi_1+\\phi_2&amp;\\text{\u5f53}\\phi_1\\text{\u4e3a\u5c0f\u91cf},\\\\J_r(\\phi_1)^{-1}\\phi_2+\\phi_1&amp;\\text{\u5f53}\\phi_2\\text{\u4e3a\u5c0f\u91cf}.\\end{cases} \\] \\[ \\boldsymbol{J}_{l}=\\frac{\\sin\\theta}{\\theta}\\boldsymbol{I}+\\left(1-\\frac{\\sin\\theta}{\\theta}\\right)\\boldsymbol{a}\\boldsymbol{a}^\\mathrm{T}+\\frac{1-\\cos\\theta}{\\theta}\\boldsymbol{a}^\\mathrm{\\wedge}. \\] \\[ \\boldsymbol{J}_{\\ell}^{-1}=\\frac{\\theta}{2}\\cot\\frac{\\theta}{2}\\boldsymbol{I}+\\left(1-\\frac{\\theta}{2}\\cot\\frac{\\theta}{2}\\right)\\boldsymbol{a}\\boldsymbol{a}^{\\mathrm{T}}-\\frac{\\theta}{2}\\boldsymbol{a}^{\\wedge}. \\] \\[ J_{r}(\\phi)=J_{l}(-\\phi). \\] <p>\u4e8e\u662f\u6211\u4eec\u5c31\u53ef\u4ee5\u8c08\u8bba\u674e\u7fa4\u4e58\u6cd5\u4e0e\u674e\u4ee3\u6570\u52a0\u6cd5\u7684\u5173\u7cfb\u4e86\u3002 \\(\\displaystyle \\boldsymbol{R}\\) \u5bf9\u5e94 \\(\\displaystyle \\phi\\)\uff0c\u6211\u4eec\u7ed9\u5b83\u5de6\u4e58\u4e00\u4e2a\u5fae\u5c0f\u65cb\u8f6c\uff0c\u8bb0\u4f5c \\(\\displaystyle \\Delta \\boldsymbol{R}\\)</p> \\[ \\exp\\left(\\Delta\\phi^{\\wedge}\\right)\\exp\\left(\\phi^{\\wedge}\\right)=\\exp\\left(\\left(\\phi+J_{l}^{-1}\\left(\\phi\\right)\\Delta\\phi\\right)^{\\wedge}\\right). \\] \\[ \\exp\\left(\\left(\\phi+\\Delta\\phi\\right)^{\\wedge}\\right)=\\exp\\left(\\left(J_{l}\\Delta\\phi\\right)^{\\wedge}\\right)\\exp\\left(\\phi^{\\wedge}\\right)=\\exp\\left(\\phi^{\\wedge}\\right)\\exp\\left(\\left(J_{r}\\Delta\\phi\\right)^{\\wedge}\\right). \\] <p>\u5bf9\u4e8e SE (3) \u6211\u4eec\u4e5f\u6709:</p> \\[ \\exp\\left(\\Delta\\xi^{\\wedge}\\right)\\exp\\left(\\xi^{\\wedge}\\right)\\approx\\exp\\left(\\left(\\mathcal{J}_{l}^{-1}\\Delta\\xi+\\xi\\right)^{\\wedge}\\right) \\] \\[ exp\\left(\\xi^{\\wedge}\\right)\\exp\\left(\\Delta\\xi^{\\wedge}\\right)\\approx\\exp\\left(\\left(\\mathcal{J}_{r}^{-1}\\Delta\\xi+\\xi\\right)^{\\wedge}\\right). \\] <p>\u552f\u4e00\u4e0d\u540c\u7684\u662f\u8fd9\u91cc\u7684 \\(\\displaystyle J_{l}\\) \u6bd4\u8f83\u590d\u6742\u3002</p>"},{"location":"CV/SLAM14/#432-so-3","title":"4.3.2 SO (3) \u4e0a\u7684\u674e\u4ee3\u6570\u6c42\u5bfc","text":"\\[ z=T\\boldsymbol{p}+\\boldsymbol{w}. \\] <p>\u5176\u4e2d \\(\\displaystyle \\boldsymbol{w}\\) \u662f\u968f\u673a\u566a\u58f0\u3002</p> \\[ e=z-Tp. \\] <p>\u5047\u8bbe\u4e00\u5171\u6709 N \u4e2a\u8fd9\u6837\u7684\u8def\u6807\u70b9\u548c\u89c2\u6d4b:</p> \\[ \\min_{\\boldsymbol{T}}J(\\boldsymbol{T})=\\sum_{i=1}^N\\left\\|\\boldsymbol{z}_i-\\boldsymbol{T}\\boldsymbol{p}_i\\right\\|_2^2. \\] <p>most importantly\uff0c\u6211\u4eec\u4f1a\u6784\u5efa\u4e0e\u4f4d\u59ff\u6709\u5173\u7684\u51fd\u6570\uff0c\u5e76\u8ba8\u8bba\u8be5\u51fd\u6570\u5173\u4e8e\u4f4d\u59ff\u7684\u5bfc\u6570\uff0c\u4ee5\u8c03\u6574\u5f53\u524d\u7684\u4f30\u8ba1\u503c\u3002 \u4f7f\u7528\u674e\u4ee3\u6570\u89e3\u51b3\u6c42\u5bfc\u95ee\u9898\u7684\u601d\u8def\u5206\u4e3a\u4e24\u79cd:</p> <ol> <li>\u7528\u674e\u4ee3\u6570\u8868\u793a\u59ff\u6001\uff0c\u7136\u540e\u6839\u636e\u674e\u4ee3\u6570\u52a0\u6cd5\u5bf9\u674e\u4ee3\u6570\u6c42\u5bfc\u3002</li> <li>\u5bf9\u674e\u7fa4\u5de6\u4e58\u6216\u53f3\u4e58\u5fae\u5c0f\u6270\u52a8\uff0c\u7136\u540e\u5bf9\u8be5\u6270\u52a8\u6c42\u5bfc\uff0c\u79f0\u4e3a\u5de6\u6270\u52a8\u548c\u53f3\u6270\u52a8\u6a21\u578b\u3002</li> </ol>"},{"location":"CV/SLAM14/#44","title":"4.4 \u674e\u4ee3\u6570\u6c42\u5bfc","text":"<p>\u8981\u8ba1\u7b97 \\(\\displaystyle \\frac{\\partial\\left(Rp\\right)}{\\partial R}\\), \u7531\u4e8eSO\uff083\uff09\u6ca1\u6709\u52a0\u6cd5\uff0c\u6211\u4eec\u8f6c\u800c\u8ba1\u7b97: \\(\\displaystyle \\frac{\\partial\\left(\\exp\\left(\\phi^{\\wedge}\\right)\\boldsymbol{p}\\right)}{\\partial\\boldsymbol{\\phi}}.\\)</p> \\[ \\begin{aligned} \\frac{\\partial\\left(\\exp\\left(\\phi^{\\wedge}\\right)\\boldsymbol{p}\\right)}{\\partial\\phi}&amp; =\\lim_{\\delta\\boldsymbol{\\phi}\\to0}\\frac{\\exp\\left(\\left(\\boldsymbol{\\phi}+\\delta\\boldsymbol{\\phi}\\right)^{\\wedge}\\right)\\boldsymbol{p}-\\exp\\left(\\boldsymbol{\\phi}^{\\wedge}\\right)\\boldsymbol{p}}{\\delta\\boldsymbol{\\phi}} \\\\ &amp;=\\lim_{\\delta\\phi\\to0}\\frac{\\exp\\left(\\left(\\boldsymbol{J}_i\\delta\\boldsymbol{\\phi}\\right)^\\wedge\\right)\\exp\\left(\\boldsymbol{\\phi}^\\wedge\\right)\\boldsymbol{p}-\\exp\\left(\\boldsymbol{\\phi}^\\wedge\\right)\\boldsymbol{p}}{\\delta\\boldsymbol{\\phi}} \\\\ &amp;=\\lim_{\\delta\\phi\\to0}\\frac{\\left(\\boldsymbol{I}+\\left(\\boldsymbol{J}_{l}\\delta\\boldsymbol{\\phi}\\right)^{\\wedge}\\right)\\exp\\left(\\boldsymbol{\\phi}^{\\wedge}\\right)\\boldsymbol{p}-\\exp\\left(\\boldsymbol{\\phi}^{\\wedge}\\right)\\boldsymbol{p}}{\\delta\\phi} \\\\ &amp;=\\lim_{\\delta\\phi\\to0}\\frac{\\left(\\boldsymbol{J}_{l}\\delta\\phi\\right)^{\\wedge}\\exp\\left(\\boldsymbol{\\phi}^{\\wedge}\\right)\\boldsymbol{p}}{\\delta\\phi} \\\\ &amp;=\\lim_{\\delta\\boldsymbol{\\phi}\\to0}\\frac{-(\\exp\\left(\\boldsymbol{\\phi}^{\\wedge}\\right)\\boldsymbol{p})^{\\wedge}\\boldsymbol{J}_{l}\\delta\\boldsymbol{\\phi}}{\\delta\\boldsymbol{\\phi}}=-(\\boldsymbol{R}\\boldsymbol{p})^{\\wedge}\\boldsymbol{J}_{l}. \\end{aligned} \\] <p>BCH \u7ebf\u6027\u8fd1\u4f3c+\u6cf0\u52d2\u5c55\u5f00\u53d6\u7ebf\u6027\u9879:</p> \\[ \\frac{\\partial\\left(\\boldsymbol{Rp}\\right)}{\\partial\\boldsymbol{\\phi}}=\\left(-\\boldsymbol{Rp}\\right)^{\\wedge}\\boldsymbol{J}_{l}. \\] <p>\u4f46\u662f\u8fd9\u91cc\u4ecd\u7136\u6709 \\(\\displaystyle \\boldsymbol{J}_{l}\\)</p>"},{"location":"CV/SLAM14/#441","title":"4.4.1 \u6270\u52a8\u6a21\u578b\uff08\u5de6\u4e58\uff09","text":"<p>\\(\\displaystyle \\varphi\\) \u5bf9\u5e94\u5de6\u6270\u52a8 \\(\\displaystyle \\Delta \\boldsymbol{R}\\)</p> \\[ \\begin{aligned} \\frac{\\partial\\left(Rp\\right)}{\\partial\\varphi}&amp; =\\lim_{\\varphi\\to0}\\frac{\\exp\\left(\\varphi^{\\wedge}\\right)\\exp\\left(\\phi^{\\wedge}\\right)p-\\exp\\left(\\phi^{\\wedge}\\right)p}{\\varphi} \\\\ &amp;=\\lim_{\\varphi\\to0}\\frac{(\\boldsymbol{I}+\\boldsymbol{\\varphi}^{\\wedge})\\exp\\left(\\boldsymbol{\\phi}^{\\wedge}\\right)\\boldsymbol{p}-\\exp\\left(\\boldsymbol{\\phi}^{\\wedge}\\right)\\boldsymbol{p}}{\\varphi} \\\\ &amp;=\\lim_{\\varphi\\to0}\\frac{\\varphi^\\wedge Rp}\\varphi=\\lim_{\\varphi\\to0}\\frac{-\\left(Rp\\right)^\\wedge\\varphi}\\varphi=-\\left(Rp\\right)^\\wedge. \\end{aligned} \\]"},{"location":"CV/SLAM14/#442-se-3","title":"4.4.2 SE (3) \u4e0a\u7684\u674e\u4ee3\u6570\u6c42\u5bfc","text":"\\[ \\begin{aligned} \\frac{\\partial\\left(\\boldsymbol{T}\\boldsymbol{p}\\right)}{\\partial\\delta\\boldsymbol{\\xi}}&amp;=\\lim_{\\delta\\boldsymbol{\\xi}\\to\\boldsymbol{0}}\\frac{\\exp\\left(\\delta\\boldsymbol{\\xi}^{\\wedge}\\right)\\exp\\left(\\boldsymbol{\\xi}^{\\wedge}\\right)\\boldsymbol{p}-\\exp\\left(\\boldsymbol{\\xi}^{\\wedge}\\right)\\boldsymbol{p}}{\\delta\\xi} \\\\ &amp;=\\lim_{\\delta\\boldsymbol{\\xi}\\to\\mathbf{0}}\\frac{\\left(\\boldsymbol{I}+\\delta\\boldsymbol{\\xi}^{\\wedge}\\right)\\exp\\left(\\boldsymbol{\\xi}^{\\wedge}\\right)\\boldsymbol{p}-\\exp\\left(\\boldsymbol{\\xi}^{\\wedge}\\right)\\boldsymbol{p}}{\\delta\\boldsymbol{\\xi}} \\\\ &amp;=\\lim_{\\delta\\boldsymbol{\\xi}\\to0}\\frac{\\delta\\boldsymbol{\\xi}^{\\wedge}\\exp\\left(\\boldsymbol{\\xi}^{\\wedge}\\right)\\boldsymbol{p}}{\\delta\\boldsymbol{\\xi}} \\\\ &amp;=\\lim_{\\delta\\boldsymbol{\\xi}\\to\\mathbf{0}}\\frac{\\begin{bmatrix}\\delta\\boldsymbol{\\phi}^\\wedge&amp;\\delta\\boldsymbol{\\rho}\\\\\\\\\\mathbf{0}^\\mathrm{T}&amp;0\\end{bmatrix}\\begin{bmatrix}\\boldsymbol{R}\\boldsymbol{p}+\\boldsymbol{t}\\\\\\\\1\\end{bmatrix}}{\\delta\\boldsymbol{\\xi}} \\\\ &amp;=\\lim_{\\delta\\boldsymbol{\\xi}\\to\\boldsymbol{0}}\\frac{\\begin{bmatrix}\\delta\\boldsymbol{\\phi}^{\\wedge}\\left(\\boldsymbol{R}\\boldsymbol{p}+\\boldsymbol{t}\\right)+\\delta\\boldsymbol{\\rho}\\\\\\boldsymbol{0}^{\\mathrm{T}}\\end{bmatrix}}{[\\delta\\boldsymbol{\\rho},\\delta\\boldsymbol{\\phi}]^{\\mathrm{T}}}=\\begin{bmatrix}\\boldsymbol{I}&amp;-(\\boldsymbol{R}\\boldsymbol{p}+\\boldsymbol{t})^{\\wedge}\\\\\\boldsymbol{0}^{\\mathrm{T}}&amp;\\boldsymbol{0}^{\\mathrm{T}}\\end{bmatrix}\\stackrel{\\mathrm{def}}{=}(\\boldsymbol{T}\\boldsymbol{p})^{\\odot}. \\end{aligned} \\] \\[ \\frac{\\mathrm{d}\\begin{bmatrix}a\\\\b\\end{bmatrix}}{\\mathrm{d}\\begin{bmatrix}x\\\\y\\end{bmatrix}}=\\left(\\frac{\\mathrm{d}[a,b]^\\mathrm{T}}{\\mathrm{d}\\begin{bmatrix}x\\\\y\\end{bmatrix}}\\right)^\\mathrm{T}=\\begin{bmatrix}\\frac{\\mathrm{d}a}{\\mathrm{d}x}&amp;\\frac{\\mathrm{d}b}{\\mathrm{d}x}\\\\\\frac{\\mathrm{d}a}{\\mathrm{d}y}&amp;\\frac{\\mathrm{d}b}{\\mathrm{d}y}\\end{bmatrix}^\\mathrm{T}=\\begin{bmatrix}\\frac{\\mathrm{d}a}{\\mathrm{d}x}&amp;\\frac{\\mathrm{d}a}{\\mathrm{d}y}\\\\\\frac{\\mathrm{d}b}{\\mathrm{d}x}&amp;\\frac{\\mathrm{d}b}{\\mathrm{d}y}\\end{bmatrix} \\]"},{"location":"CV/SLAM14/#45-sophus","title":"4.5 \u5b9e\u8df5:Sophus","text":""},{"location":"CV/SLAM14/#451-sophus","title":"4.5.1 Sophus \u7684\u57fa\u672c\u4f7f\u7528\u65b9\u6cd5","text":""},{"location":"CV/SLAM14/#452","title":"4.5.2 \u4f8b\u5b50: \u8bc4\u4f30\u8f68\u8ff9\u7684\u8bef\u5dee","text":"<ul> <li>\u7edd\u5bf9\u8f68\u8ff9\u8bef\u5dee\uff08Absolute Trajectory Error, ATE\uff09</li> </ul> \\[ \\mathrm{ATE}_{\\mathrm{all}}=\\sqrt{\\frac{1}{N}\\sum_{i=1}^{N}\\|\\log(T_{\\mathrm{gt},i}^{-1}T_{\\mathrm{esti},i})^{\\vee}\\|_{2}^{2}}, \\] <p>\u5373\u5747\u65b9\u6839\u8bef\u5dee\uff08Root-Mean-Squared Error, RMSE\uff09</p> <ul> <li>\u7edd\u5bf9\u5e73\u79fb\u8bef\u5dee\uff08Average Translational Error\uff09</li> </ul> \\[ \\mathrm{ATE}_{\\mathrm{all}}=\\sqrt{\\frac{1}{N}\\sum_{i=1}^{N}\\|\\log(T_{\\mathrm{gt},i}^{-1}T_{\\mathrm{esti},i})^{\\vee}\\|_{2}^{2}}, \\] <ul> <li>\u76f8\u5bf9\u4f4d\u59ff\u8bef\u5dee\uff08Relative Pose Error, RPE\uff09</li> </ul> \\[ \\mathrm{RPE}_{\\mathrm{all}}=\\sqrt{\\frac{1}{N-\\Delta t}\\sum_{i=1}^{N-\\Delta t}\\|\\log\\left(\\left(\\boldsymbol{T}_{\\mathrm{gt},i}^{-1}\\boldsymbol{T}_{\\mathrm{gt},i+\\Delta t}\\right)\\right)^{-1}\\left(\\boldsymbol{T}_{\\mathrm{est},i}^{-1}\\boldsymbol{T}_{\\mathrm{est},i+\\Delta t}\\right))^{\\vee}\\|_{2}^{2}}, \\] \\[ \\mathrm{RPE}_{\\mathrm{trans}}=\\sqrt{\\frac{1}{N-\\Delta t}\\sum_{i=1}^{N-\\Delta t}\\|\\mathrm{trans}\\left(\\left(T_{gt,i}^{-1}T_{gt,i+\\Delta t}\\right)\\right)^{-1}\\left(T_{\\mathrm{esti},i}^{-1}T_{\\mathrm{esti},i+\\Delta t}\\right))\\|_{2}^{2}}. \\] <p>\u4ee3\u7801\u8ba1\u7b97:</p> Text Only<pre><code>TODO\n</code></pre>"},{"location":"CV/SLAM14/#46","title":"4.6 \u76f8\u4f3c\u53d8\u6362\u4e0e\u674e\u4ee3\u6570","text":"<p>\u5728\u8fd9\u91cc\u6211\u4eec\u8ba8\u8bba Sim (3) \u548c\u5bf9\u5e94\u7684\u674e\u4ee3\u6570 \\(\\displaystyle \\mathfrak{sim}(3)\\)\u3002 \u5bf9\u4e8e\u4f4d\u4e8e\u7a7a\u95f4\u7684\u70b9 \\(\\displaystyle \\boldsymbol{p}\\)\uff0c\u5728\u76f8\u673a\u5750\u6807\u7cfb\u4e0b\u8981\u7ecf\u8fc7\u4e00\u4e2a\u76f8\u4f3c\u53d8\u6362\uff0c\u800c\u975e\u6b27\u6c0f\u53d8\u6362:</p> \\[ \\boldsymbol{p}'=\\begin{bmatrix}s\\boldsymbol{R}&amp;\\boldsymbol{t}\\\\\\boldsymbol{0}^\\mathrm{T}&amp;1\\end{bmatrix}\\boldsymbol{p}=s\\boldsymbol{R}\\boldsymbol{p}+\\boldsymbol{t}. \\] \\[ \\mathrm{Sim}(3)=\\left\\{S=\\begin{bmatrix}sR&amp;t\\\\\\\\\\mathbf{0}^\\mathrm{T}&amp;1\\end{bmatrix}\\in\\mathbb{R}^{4\\times4}\\right\\}. \\] \\[ \\sin(3)=\\left\\{\\zeta|\\zeta=\\begin{bmatrix}\\rho\\\\\\\\\\phi\\\\\\\\\\sigma\\end{bmatrix}\\in\\mathbb{R}^7,\\zeta^\\wedge=\\begin{bmatrix}\\sigma\\boldsymbol{I}+\\phi^\\wedge&amp;\\rho\\\\\\\\\\mathbf{0}^\\mathrm{T}&amp;0\\end{bmatrix}\\in\\mathbb{R}^{4\\times4}\\right\\}. \\] \\[ \\exp\\left(\\zeta^{\\wedge}\\right)=\\begin{bmatrix}\\mathrm{e}^{\\sigma}\\exp\\left(\\phi^{\\wedge}\\right)&amp;J_{s}\\rho\\\\0^{\\mathrm{T}}&amp;1\\end{bmatrix}. \\] <p>\u5176\u4e2d\uff0c\\(\\displaystyle \\boldsymbol{J}_{S}\\) \u7684\u5f62\u5f0f\u662f:</p> \\[ \\begin{aligned} \\text{J}&amp; =\\frac{\\mathrm{e}^{\\sigma}-1}{\\sigma}I+\\frac{\\sigma\\mathrm{e}^{\\sigma}\\sin\\theta+\\left(1-\\mathrm{e}^{\\sigma}\\cos\\theta\\right)\\theta}{\\sigma^{2}+\\theta^{2}}\\boldsymbol{a}^{\\wedge} \\\\ &amp;+\\left(\\frac{\\mathrm{e}^\\sigma-1}{\\sigma}-\\frac{\\left(\\mathrm{e}^\\sigma\\cos\\theta-1\\right)\\sigma+\\left(\\mathrm{e}^\\sigma\\sin\\theta\\right)\\theta}{\\sigma^2+\\theta^2}\\right)\\boldsymbol{a}^\\wedge\\boldsymbol{a}^\\wedge. \\end{aligned} \\] <p>\u4e8e\u662f\uff0c\u674e\u4ee3\u6570\u4e0e\u674e\u7fa4\u7684\u5173\u7cfb:</p> \\[ s=\\mathrm{e}^\\sigma, R=\\exp(\\phi^\\wedge), t=J_s\\rho. \\] \\[ \\frac{\\partial\\boldsymbol{Sp}}{\\partial\\boldsymbol{\\zeta}}=\\begin{bmatrix}\\boldsymbol{I}&amp;-\\boldsymbol{q}^\\wedge&amp;\\boldsymbol{q}\\\\\\boldsymbol{0}^\\mathrm{T}&amp;\\boldsymbol{0}^\\mathrm{T}&amp;0\\end{bmatrix}. \\]"},{"location":"CV/SLAM14/#47","title":"4.7 \u4e60\u9898","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#5","title":"5 \u76f8\u673a\u4e0e\u56fe\u50cf","text":"<ul> <li>\u89c2\u6d4b\u4e3b\u8981\u662f\u6307\u76f8\u673a\u6210\u50cf\u7684\u8fc7\u7a0b\u3002</li> </ul>"},{"location":"CV/SLAM14/#51","title":"5.1 \u76f8\u673a\u6a21\u578b","text":"<ul> <li>\u9488\u5b54\u6a21\u578b</li> <li>\u900f\u955c\u4f1a\u4ea7\u751f\u7578\u53d8</li> <li>\u5185\u53c2\u6570\uff08Intrinsics\uff09</li> </ul>"},{"location":"CV/SLAM14/#511","title":"5.1.1 \u9488\u5b54\u76f8\u673a\u6a21\u578b","text":"\\[ \\frac{Z}{f}=-\\frac{X}{X'}=-\\frac{Y}{Y'}. \\] <p>\u53bb\u6389\u8d1f\u53f7:</p> \\[ \\frac Zf=\\frac X{X^{\\prime}}=\\frac Y{Y^{\\prime}}. \\] \\[ \\begin{aligned}X'&amp;=f\\frac{X}{Z}\\\\Y'&amp;=f\\frac{Y}{Z}\\end{aligned}. \\] <p>\u8fd8\u6709\u4e00\u4e2a\u50cf\u7d20\u5750\u6807\u7cfb\uff0cu \u8f74\u4e0e x \u8f74\u5e73\u884c\uff0cv \u8f74\u4e0e y \u8f74\u5e73\u884c:</p> \\[ \\begin{cases}u=\\alpha X'+c_x\\\\[2ex]v=\\beta Y'+c_y\\end{cases}. \\] \\[ \\begin{cases}u=f_x\\frac{X}{Z}+c_x\\\\\\\\v=f_y\\frac{Y}{Z}+c_y\\end{cases}. \\] \\[ Z\\begin{pmatrix}u\\\\\\\\v\\\\\\\\1\\end{pmatrix}=\\begin{pmatrix}f_x&amp;0&amp;c_x\\\\0&amp;f_y&amp;c_y\\\\\\\\0&amp;0&amp;1\\end{pmatrix}\\begin{pmatrix}X\\\\\\\\Y\\\\\\\\Z\\end{pmatrix}\\overset{\\text{def}}{=}\\boldsymbol{KP}. \\] <p>\u6700\u4e2d\u95f4\u7684\u77e9\u9635\u79f0\u4e3a\u76f8\u673a\u7684\u5185\u53c2\u6570\uff08Camera Inrinsics\uff09\u77e9\u9635 \\(\\displaystyle \\boldsymbol{K}\\)\u3002 \u6807\u5b9a: \u786e\u5b9a\u76f8\u673a\u7684\u5185\u53c2</p> \\[ Z\\boldsymbol{P}_{uv}=Z\\begin{bmatrix}u\\\\\\\\v\\\\\\\\1\\end{bmatrix}=\\boldsymbol{K}\\left(\\boldsymbol{R}\\boldsymbol{P}_\\mathrm{w}+\\boldsymbol{t}\\right)=\\boldsymbol{K}\\boldsymbol{T}\\boldsymbol{P}_\\mathrm{w}. \\] <p>\u5176\u4e2d \\(\\displaystyle \\boldsymbol{R},\\boldsymbol{t}\\) \u53c8\u79f0\u4e3a\u76f8\u673a\u7684\u5916\u53c2\u6570\uff08Camera Extrinsics\uff09</p> \\[ (\\boldsymbol{RP_\\mathrm{w}}+\\boldsymbol{t})=\\underbrace{[X,Y,Z]^\\mathrm{T}}_{\\text{\u76f8\u673a\u5750\u6807}}\\to\\underbrace{[X/Z,Y/Z,1]^\\mathrm{T}}_{\\text{\u5f52\u4e00\u5316\u5750\u6807}} . \\] <ul> <li>\u5f52\u4e00\u5316\u5e73\u9762</li> <li>\u70b9\u7684\u6df1\u5ea6\u5728\u6295\u5f71\u8fc7\u7a0b\u4e2d\u88ab\u4e22\u5931\u4e86</li> </ul>"},{"location":"CV/SLAM14/#512","title":"5.1.2 \u7578\u53d8\u6a21\u578b","text":"<ul> <li>\u7578\u53d8 (Distortion \u5931\u771f) \u5f84\u5411\u7578\u53d8<ul> <li>\u7b52\u5f62\u7578\u53d8</li> <li>\u6795\u5f62\u7578\u53d8 </li> </ul> </li> <li>\u5f84\u5411\u7578\u53d8\u5373 \\(\\displaystyle r\\) \u53d8\u5316</li> <li>\u5207\u5411\u7578\u53d8\u5373 \\(\\displaystyle \\theta\\) \u53d8\u5316 \u6211\u4eec\u53ef\u4ee5\u5047\u8bbe:</li> </ul> \\[ \\begin{align} x_{\\mathrm{distorted}}&amp;=x(1+k_1r^2+k_2r^4+k_3r^6) \\\\ y_{\\mathrm{distorted}}&amp;=y(1+k_1r^2+k_2r^4+k_3r^6). \\end{align} \\] \\[ \\begin{align} x_{\\mathrm{distorted}}&amp;=x+2p_1xy+p_2(r^2+2x^2) \\\\ y_{\\mathrm{distorted}}&amp;=y+p_1(r^2+2y^2)+2p_2xy \\end{align} \\] <p>\u6240\u4ee5\u6211\u4eec\u53ef\u4ee5\u627e\u5230\u4e00\u4e2a\u70b9\u5728\u50cf\u7d20\u5e73\u9762\u4e0a\u7684\u6b63\u786e\u4f4d\u7f6e:</p> <ol> <li>\u5c06\u4e09\u7ef4\u7a7a\u95f4\u70b9\u6295\u5f71\u5230\u5f52\u4e00\u5316\u56fe\u50cf\u5e73\u9762\u3002\u8bbe\u5b83\u7684\u5f52\u4e00\u5316\u5750\u6807\u4e3a \\(\\displaystyle [x, y]^\\mathrm{T}\\)\u3002</li> <li>\u5bf9\u5f52\u4e00\u5316\u5e73\u9762\u4e0a\u7684\u70b9\u8ba1\u7b97\u5f84\u5411\u7578\u53d8\u548c\u5207\u5411\u7578\u53d8</li> </ol> \\[ \\begin{cases}x_\\text{distorted}=x(1+k_1r^2+k_2r^4+k_3r^6)+2p_1xy+p_2(r^2+2x^2)\\\\y_\\text{distorted}=y(1+k_1r^2+k_2r^4+k_3r^6)+p_1(r^2+2y^2)+2p_2xy\\end{cases} \\] <ol> <li>\u5c06\u7578\u53d8\u540e\u7684\u70b9\u901a\u8fc7\u5185\u53c2\u6570\u77e9\u9635\u6295\u5f71\u5230\u50cf\u7d20\u5e73\u9762\uff0c\u5f97\u5230\u8be5\u70b9\u5728\u56fe\u50cf\u4e0a\u7684\u6b63\u786e\u4f4d\u7f6e\u3002</li> </ol> \\[ \\begin{cases}u=f_xx_\\text{distorted}+c_x\\\\\\\\v=f_yy_\\text{distorted}+c_y\\end{cases}. \\] <p>\u8fd8\u6709\u5f88\u591a\u7684\u76f8\u673a\u6a21\u578b\u6bd4\u5982: \u4eff\u5c04\u6a21\u578b\uff0c\u900f\u89c6\u6a21\u578b\u3002</p> <p>\u603b\u7ed3\u4e00\u4e0b\u5355\u76ee\u76f8\u673a\u7684\u6210\u50cf\u8fc7\u7a0b:</p> <ol> <li>\u4e16\u754c\u5750\u6807\u7cfb\u4e0b\u6709\u4e00\u4e2a\u56fa\u5b9a\u7684\u70b9 \\(\\displaystyle P\\)\uff0c\u4e16\u754c\u5750\u6807\u4e3a \\(\\displaystyle \\boldsymbol{P}_{w}\\)\u3002</li> <li>\u7531\u4e8e\u76f8\u673a\u5728\u8fd0\u52a8\uff0c\u5b83\u7684\u8fd0\u52a8\u7531 \\(\\displaystyle \\boldsymbol{R},\\boldsymbol{t}\\) \u6216\u53d8\u6362\u77e9\u9635 \\(\\displaystyle \\boldsymbol{T}\\in SE(3)\\) \u63cf\u8ff0\u3002\\(\\displaystyle P\\) \u7684\u76f8\u673a\u5750\u6807\u4e3a \\(\\displaystyle \\tilde{P_{c}} = \\boldsymbol{R}\\boldsymbol{P}_{w}+\\boldsymbol{t}\\)\u3002</li> <li>\u8fd9\u65f6\u7684 \\(\\displaystyle \\tilde{\\boldsymbol{P}_{c}}\\) \u7684\u5206\u91cf\u662f \\(\\displaystyle X,Y,Z\\) \uff0c\u628a\u5b83\u4eec\u6295\u5f71\u5230\u5f52\u4e00\u5316\u5e73\u9762 \\(\\displaystyle Z = 1\\) \u4e0a\uff0c\u5f97\u5230 \\(\\displaystyle P\\) \u7684\u5f52\u4e00\u5316\u5750\u6807: \\(\\displaystyle \\boldsymbol{P}_{c} = \\left[ \\frac{X}{Z},   \\frac{Y}{Z}, 1 \\right]^\\mathrm{T}\\)\u3002</li> <li>\u6709\u7578\u53d8\u65f6\uff0c\u6839\u636e\u7578\u53d8\u53c2\u6570\u8ba1\u7b97 \\(\\displaystyle \\boldsymbol{P}_{c}\\) \u53d1\u751f\u7578\u53d8\u540e\u7684\u5750\u6807\u3002</li> <li>\\(\\displaystyle P\\) \u7684\u5f52\u4e00\u5316\u5750\u6807\u7ecf\u8fc7\u5185\u53c2\u540e\uff0c\u5bf9\u5e94\u5230\u5b83\u7684\u50cf\u7d20\u5750\u6807: \\(\\displaystyle \\boldsymbol{P}_{uv} = \\boldsymbol{K} \\boldsymbol{P}_{c}\\)\u3002</li> </ol>"},{"location":"CV/SLAM14/#513","title":"5.1.3 \u53cc\u76ee\u76f8\u673a\u6a21\u578b","text":"<p> \u4e24\u8005\u4e4b\u95f4\u7684\u8ddd\u79bb\u79f0\u4e3a\u53cc\u76ee\u76f8\u673a\u7684\u57fa\u7ebf</p> \\[ z=\\frac{fb}{d},\\quad d\\stackrel{\\mathrm{def}}{=}u_{\\mathrm{L}}-u_{\\mathrm{R}}. \\] <ul> <li>d \u5b9a\u4e49\u4e3a\u5de6\u53f3\u56fe\u7684\u6a2a\u5750\u6807\u4e4b\u5dee\uff0c\u79f0\u4e3a\u89c6\u5dee\u3002<ul> <li>\u7531\u4e8e\u89c6\u5dee\u6700\u5c0f\u4e3a\u4e00\u4e2a\u50cf\u7d20\uff0c\u6240\u4ee5\u53cc\u76ee\u7684\u6df1\u5ea6\u5b58\u5728\u4e00\u4e2a\u7406\u8bba\u4e0a\u7684\u6700\u5927\u503c\u3002</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#514-rgb-d","title":"5.1.4 RGB-D \u76f8\u673a\u6a21\u578b","text":"<ul> <li>\u7ea2\u5916\u7ed3\u6784\u5149\uff08Structured lightning\uff09</li> <li>\u98de\u884c\u65f6\u95f4\uff08Time-of-Flight, ToF\uff09 </li> <li>ToF \u76f8\u673a\u53ef\u4ee5\u83b7\u5f97\u6574\u4e2a\u56fe\u50cf\u7684\u50cf\u7d20\u6df1\u5ea6</li> <li>\u8f93\u51fa\u5f69\u8272\u56fe\u548c\u6df1\u5ea6\u56fe\uff0c\u751f\u6210\u70b9\u4e91\uff08Point Cloud\uff09</li> </ul>"},{"location":"CV/SLAM14/#52","title":"5.2 \u56fe\u50cf","text":"\\[ I(x,y):\\mathbb{R}^2\\mapsto\\mathbb{R}. \\] <ul> <li>channel</li> </ul>"},{"location":"CV/SLAM14/#53","title":"5.3 \u5b9e\u8df5: \u8ba1\u7b97\u673a\u4e2d\u7684\u56fe\u50cf","text":""},{"location":"CV/SLAM14/#531-opencv","title":"5.3.1 OpenCV \u7684\u57fa\u672c\u4f7f\u7528\u65b9\u6cd5","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#532","title":"5.3.2 \u56fe\u50cf\u53bb\u7578\u53d8","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#54-3-d","title":"5.4 \u5b9e\u8df5: 3 D \u89c6\u89c9","text":""},{"location":"CV/SLAM14/#541","title":"5.4.1 \u53cc\u76ee\u89c6\u89c9","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#542-rgb-d","title":"5.4.2 RGB-D \u89c6\u89c9","text":""},{"location":"CV/SLAM14/#55","title":"5.5 \u4e60\u9898","text":""},{"location":"CV/SLAM14/#6","title":"6 \u975e\u7ebf\u6027\u4f18\u5316","text":"<p>\u524d\u9762\u6211\u4eec\u5df2\u7ecf\u641e\u6e05\u695a\u4e86\u8fd0\u52a8\u65b9\u7a0b\u548c\u89c2\u6d4b\u65b9\u7a0b\u7684\u6765\u6e90\uff0c\u73b0\u5728\u6211\u4eec\u5f00\u59cb\u8ba8\u8bba\u566a\u58f0\u3002</p>"},{"location":"CV/SLAM14/#61","title":"6.1 \u72b6\u6001\u4f30\u8ba1\u95ee\u9898","text":""},{"location":"CV/SLAM14/#611","title":"6.1.1 \u6279\u91cf\u72b6\u6001\u4f30\u8ba1\u4e0e\u6700\u5927\u540e\u9a8c\u4f30\u8ba1","text":"\\[ \\begin{cases}\\boldsymbol{x}_k=f\\left(\\boldsymbol{x}_{k-1},\\boldsymbol{u}_k\\right)+\\boldsymbol{w}_k\\\\\\boldsymbol{z}_{k,j}=h\\left(\\boldsymbol{y}_j,\\boldsymbol{x}_k\\right)+\\boldsymbol{v}_{k,j}\\end{cases}. \\] \\[ s\\boldsymbol{z}_{k,j}=\\boldsymbol{K}(R_k\\boldsymbol{y}_j+\\boldsymbol{t}_k). \\] <p>\u5176\u4e2d \\(\\displaystyle s\\) \u4e3a\u50cf\u7d20\u70b9\u7684\u8ddd\u79bb\u3002 \u6211\u4eec\u901a\u5e38\u5047\u8bbe\u566a\u58f0\u9879\u6ee1\u8db3\u96f6\u5747\u503c\u7684\u9ad8\u65af\u5206\u5e03:</p> \\[ \\boldsymbol{w}_k\\sim\\mathcal{N}\\left(\\boldsymbol{0},\\boldsymbol{R}_k\\right),\\boldsymbol{v}_k\\sim\\mathcal{N}\\left(\\boldsymbol{0},\\boldsymbol{Q}_{k,j}\\right). \\] <p>\u6709\u4e24\u79cd\u65b9\u6cd5\u6765\u89e3\u51b3\u72b6\u6001\u4f30\u8ba1\u95ee\u9898:</p> <ul> <li>\u7528\u65b0\u7684\u6570\u636e\u6765\u66f4\u65b0\u5f53\u524d\u65f6\u523b\u7684\u4f30\u8ba1\u72b6\u6001\uff0c\u589e\u91cf/\u6e10\u8fdb (incremental) \u7684\u65b9\u6cd5\uff0c\u6216\u8005\u6559\u6ee4\u6ce2\u5668</li> <li>\u4e5f\u53ef\u4ee5\u628a\u6570\u636e\u90fd\u6512\u8d77\u6765\uff0c\u79f0\u4e3a\u6279\u91cf (batch) \u7684\u65b9\u6cd5 SfM (Structure from Motion) \u7efc\u5408\u4e00\u4e0b\u5c31\u6709\u4e86\u6ed1\u52a8\u7a97\u53e3\u4f30\u8ba1\u6cd5</li> </ul> \\[ \\boldsymbol{x}=\\{\\boldsymbol{x}_1,\\ldots,\\boldsymbol{x}_N\\},\\quad\\boldsymbol{y}=\\{\\boldsymbol{y}_1,\\ldots,\\boldsymbol{y}_M\\}. \\] \\[ P(\\boldsymbol{x},\\boldsymbol{y}|z,\\boldsymbol{u}). \\] \\[ P\\left(\\boldsymbol{x},\\boldsymbol{y}|\\boldsymbol{z},\\boldsymbol{u}\\right)=\\frac{P\\left(\\boldsymbol{z},\\boldsymbol{u}|\\boldsymbol{x},\\boldsymbol{y}\\right)P\\left(\\boldsymbol{x},\\boldsymbol{y}\\right)}{P\\left(\\boldsymbol{z},\\boldsymbol{u}\\right)}\\propto\\underbrace{P\\left(\\boldsymbol{z},\\boldsymbol{u}|\\boldsymbol{x},\\boldsymbol{y}\\right)}_{\\text{\u4f3c\u7136}}\\underbrace{P\\left(\\boldsymbol{x},\\boldsymbol{y}\\right)}_{\\text{\u5148\u9a8c}}. \\] <p>\u53ef\u4ee5\u5148\u6c42\u4e00\u4e2a\u72b6\u6001\u6700\u4f18\u4f30\u8ba1:</p> \\[ (\\boldsymbol{x},\\boldsymbol{y})^*_{\\mathrm{MAP}}=\\arg\\max P(\\boldsymbol{x},\\boldsymbol{y}|\\boldsymbol{z},\\boldsymbol{u})=\\arg\\max P(\\boldsymbol{z},\\boldsymbol{u}|\\boldsymbol{x},\\boldsymbol{y})P(\\boldsymbol{x},\\boldsymbol{y}). \\] <p>\u6c42\u89e3\u6700\u5927\u540e\u9a8c\u6982\u7387\u7b49\u4ef7\u4e8e\u6700\u5927\u5316\u4f3c\u7136\u548c\u5148\u9a8c\u7684\u4e58\u79ef\u3002 \u4f46\u5982\u679c\u6ca1\u6709\u7684\u5148\u9a8c\uff0c\u90a3\u4e48\u53ef\u4ee5\u6c42\u89e3\u6700\u5927\u4f3c\u7136\u4f30\u8ba1 (Maximize Likelihood Estimation\uff0c MLE):</p> \\[ (\\boldsymbol{x},\\boldsymbol{y})^*{}_{\\mathrm{MLE}}=\\arg\\max P(\\boldsymbol{z},\\boldsymbol{u}|\\boldsymbol{x},\\boldsymbol{y}). \\] <p>\u6700\u5927\u4f3c\u7136\u4f30\u8ba1: \u5728\u4ec0\u4e48\u6837\u7684\u72b6\u6001\u4e0b\uff0c\u6700\u53ef\u80fd\u4ea7\u751f\u73b0\u5728\u89c2\u6d4b\u5230\u7684\u6570\u636e\u3002</p>"},{"location":"CV/SLAM14/#612","title":"6.1.2 \u6700\u5c0f\u4e8c\u4e58\u7684\u5f15\u51fa","text":"<p>\u5bf9\u4e8e\u67d0\u4e00\u6b21\u89c2\u6d4b:</p> \\[ z_{k,j}=h\\left(y_{j},x_{k}\\right)+v_{k,j}, \\] \\[ P(\\boldsymbol{z}_{j,k}|\\boldsymbol{x}_k,\\boldsymbol{y}_j)=N\\left(h(\\boldsymbol{y}_j,\\boldsymbol{x}_k),\\boldsymbol{Q}_{k,j}\\right). \\] <p>\u53ef\u4ee5\u4f7f\u7528\u6700\u5c0f\u5316\u8d1f\u5bf9\u6570\u6765\u6c42\u4e00\u4e2a\u9ad8\u65af\u5206\u5e03\u7684\u6700\u5927\u4f3c\u7136\u3002</p> \\[ P\\left(\\boldsymbol{x}\\right)=\\frac{1}{\\sqrt{\\left(2\\pi\\right)^{N}\\det\\left(\\boldsymbol{\\Sigma}\\right)}}\\exp\\left(-\\frac{1}{2}(\\boldsymbol{x}-\\boldsymbol{\\mu})^{\\mathrm{T}}\\boldsymbol{\\Sigma}^{-1}\\left(\\boldsymbol{x}-\\boldsymbol{\\mu}\\right)\\right). \\] \\[ -\\ln\\left(P\\left(\\boldsymbol{x}\\right)\\right)=\\frac12\\ln\\left(\\left(2\\pi\\right)^N\\det\\left(\\boldsymbol{\\Sigma}\\right)\\right)+\\frac12\\left(\\boldsymbol{x}-\\boldsymbol{\\mu}\\right)^\\mathrm{T}\\boldsymbol{\\Sigma}^{-1}\\left(\\boldsymbol{x}-\\boldsymbol{\\mu}\\right). \\] \\[ \\begin{aligned} (x_{k},y_{j})^{*}&amp; =\\arg\\max\\mathcal{N}(h(\\boldsymbol{y}_{j},\\boldsymbol{x}_{k}),\\boldsymbol{Q}_{k,j}) \\\\ &amp;=\\arg\\min\\left(\\left(\\boldsymbol{z}_{k,j}-h\\left(\\boldsymbol{x}_k,\\boldsymbol{y}_j\\right)\\right)^\\mathrm{T}\\boldsymbol{Q}_{k,j}^{-1}\\left(\\boldsymbol{z}_{k,j}-h\\left(\\boldsymbol{x}_k,\\boldsymbol{y}_j\\right)\\right)\\right). \\end{aligned} \\] <p>\u8be5\u5f0f\u7b49\u4ef7\u4e8e\u6700\u5c0f\u5316\u566a\u58f0\u9879\u7684\u4e00\u4e2a\u4e8c\u6b21\u578b\uff0c\u9a6c\u54c8\u62c9\u8bfa\u6bd4\u65af\u8ddd\u79bb (Mahalanobis distance)\u3002\u5176\u4e2d \\(\\displaystyle \\boldsymbol{Q}_{k,j}^{-1}\\) \u53eb\u4fe1\u606f\u77e9\u9635\uff0c\u5373\u9ad8\u65af\u5206\u5e03\u534f\u65b9\u5dee\u77e9\u9635\u4e4b\u9006\u3002 \u5047\u8bbe\u5404\u4e2a\u65f6\u523b\u7684\u8f93\u5165\u548c\u89c2\u6d4b\u90fd\u662f\u72ec\u7acb\u7684\uff0c\u90a3\u4e48:</p> \\[ P\\left(\\boldsymbol{z},\\boldsymbol{u}|\\boldsymbol{x},\\boldsymbol{y}\\right)=\\prod_kP\\left(\\boldsymbol{u}_k|\\boldsymbol{x}_{k-1},\\boldsymbol{x}_k\\right)\\prod_{k,j}P\\left(\\boldsymbol{z}_{k,j}|\\boldsymbol{x}_k,\\boldsymbol{y}_j\\right), \\] \\[ \\begin{align} e_{u,k} &amp;=\\boldsymbol{x}_k-f\\left(\\boldsymbol{x}_{k-1},\\boldsymbol{u}_k\\right) \\\\ e_{z,j,k} &amp;=\\boldsymbol{z}_{k,j}-h\\left(\\boldsymbol{x}_k,\\boldsymbol{y}_j\\right),  \\end{align} \\] \\[ \\min J(\\boldsymbol{x},\\boldsymbol{y})=\\sum_{k}\\boldsymbol{e}_{\\boldsymbol{u},k}^{\\mathrm{T}}\\boldsymbol{R}_{k}^{-1}\\boldsymbol{e}_{\\boldsymbol{u},k}+\\sum_{k}\\sum_{j}\\boldsymbol{e}_{\\boldsymbol{z},k,j}^{\\mathrm{T}}\\boldsymbol{Q}_{k,j}^{-1}\\boldsymbol{e}_{\\boldsymbol{z},k,j}. \\] <p>\u8fd9\u6837\u5c31\u5f97\u5230\u4e86\u4e00\u4e2a\u6700\u5c0f\u4e8c\u4e58\u95ee\u9898 (Least Square Problem) </p> <ul> <li>\u6574\u4e2a\u95ee\u9898\u6709\u4e00\u79cd\u7a00\u758f\u7684\u5f62\u5f0f\u3002</li> <li>\u7528\u674e\u4ee3\u6570\u8868\u793a\u589e\u91cf\u4f1a\u6709\u65e0\u7ea6\u675f\u7684\u4f18\u52bf\u3002</li> <li>\u7528\u4e8c\u6b21\u578b\u5ea6\u91cf\u8bef\u5dee\uff0c\u90a3\u4e48\u8bef\u5dee\u7684\u5206\u5e03\u4f1a\u5f71\u54cd\u6b64\u9879\u5728\u6574\u4e2a\u95ee\u9898\u4e2d\u7684\u6743\u91cd\u3002 \u63a5\u4e0b\u4fe9\u8bb2\u4e00\u4e9b\u975e\u7ebf\u6027\u4f18\u5316\u7684\u57fa\u672c\u77e5\u8bc6\uff0c\u6765\u5e2e\u52a9\u6211\u4eec\u6c42\u89e3\u8fd9\u4e2a\u6700\u5c0f\u4e8c\u4e58\u95ee\u9898\u3002</li> </ul>"},{"location":"CV/SLAM14/#613","title":"6.1.3 \u4f8b\u5b50: \u6279\u91cf\u72b6\u6001\u4f30\u8ba1","text":"<p>\u8003\u8651\u4e00\u4e2a\u975e\u5e38\u7b80\u5355\u7684\u79bb\u6563\u65f6\u95f4\u7cfb\u7edf:</p> \\[ \\begin{aligned}&amp;x_{k}=x_{k-1}+u_{k}+w_{k},&amp;&amp;\\boldsymbol{w}_{k}\\sim\\mathcal{N}\\left(0,\\boldsymbol{Q}_{k}\\right)\\\\&amp;\\boldsymbol{z}_{k}=\\boldsymbol{x}_{k}+\\boldsymbol{n}_{k},&amp;&amp;\\boldsymbol{n}_{k}\\sim\\mathcal{N}\\left(0,\\boldsymbol{R}_{k}\\right)\\end{aligned} \\] \\[ \\begin{gathered} x_{map}^{*} =\\arg\\max P(\\boldsymbol{x}|\\boldsymbol{u},\\boldsymbol{z})=\\arg\\max P(\\boldsymbol{u},\\boldsymbol{z}|\\boldsymbol{x}) \\\\ =\\prod_{k=1}^3P(\\boldsymbol{u}_k|\\boldsymbol{x}_{k-1},\\boldsymbol{x}_k)\\prod_{k=1}^3P(\\boldsymbol{z}_k|\\boldsymbol{x}_k),  \\end{gathered} \\] <p>\u800c\u5bf9\u4e8e\u5177\u4f53\u7684\u6bcf\u4e00\u9879\uff0c\u6211\u4eec\u6709:</p> \\[ P(\\boldsymbol{u}_k|\\boldsymbol{x}_{k-1},\\boldsymbol{x}_k)=\\mathcal{N}(\\boldsymbol{x}_k-\\boldsymbol{x}_{k-1},\\boldsymbol{Q}_k), \\] \\[ P\\left(\\boldsymbol{z}_{k}|\\boldsymbol{x}_{k}\\right)=\\mathcal{N}\\left(\\boldsymbol{x}_{k},\\boldsymbol{R}_{k}\\right). \\] <p>\u4e8e\u662f\uff0c\u6211\u4eec\u53ef\u4ee5\u6784\u5efa\u8bef\u5dee\u53d8\u91cf:</p> \\[ e_{\\boldsymbol{u},k}=\\boldsymbol{x}_k-\\boldsymbol{x}_{k-1}-\\boldsymbol{u}_k,\\quad\\boldsymbol{e}_{z,k}=\\boldsymbol{z}_k-\\boldsymbol{x}_k, \\] <p>\u4e8e\u662f\u6700\u5c0f\u4e8c\u4e58\u7684\u76ee\u6807\u51fd\u6570\u4e3a:</p> \\[ \\min\\sum_{k=1}^{3}e_{u,k}^{\\mathrm{T}}Q_{k}^{-1}e_{u,k}+\\sum_{k=1}^{3}e_{z,k}^{\\mathrm{T}}R_{k}^{-1}e_{z,k}. \\] <p>\u5b9a\u4e49\u5411\u91cf \\(\\displaystyle \\boldsymbol{y} = [\\boldsymbol{u},\\boldsymbol{z}]^\\mathrm{T}\\)</p> \\[ y-Hx=e\\sim\\mathcal{N}(\\mathbf{0},\\boldsymbol{\\Sigma}). \\] \\[ H=\\begin{bmatrix}1&amp;-1&amp;0&amp;0\\\\0&amp;1&amp;-1&amp;0\\\\0&amp;0&amp;1&amp;-1\\\\\\hline0&amp;1&amp;0&amp;0\\\\0&amp;0&amp;1&amp;0\\\\0&amp;0&amp;0&amp;1\\end{bmatrix}, \\] <p>\u4e14 \\(\\displaystyle \\Sigma = diag(\\boldsymbol{Q_{1}},\\boldsymbol{Q_{2}},\\boldsymbol{Q_{3}},\\boldsymbol{R_{1}},\\boldsymbol{R_{2}},\\boldsymbol{R_{3}})\\)\u3002 \u95ee\u9898\u5c31\u8f6c\u5316\u6210:</p> \\[ x_{\\mathrm{map}}^*=\\arg\\min e^{\\mathrm{T}}\\Sigma^{-1}e, \\] <p>\u5b83\u7684\u552f\u4e00\u89e3\u662f:</p> \\[ x_{\\mathrm{map}}^{*}=(H^{\\mathrm{T}}\\Sigma^{-1}H)^{-1}H^{\\mathrm{T}}\\Sigma^{-1}y. \\]"},{"location":"CV/SLAM14/#62","title":"6.2 \u975e\u7ebf\u6027\u6700\u5c0f\u4e8c\u4e58","text":"<p>\u5148\u8003\u8651\u4e00\u4e2a\u7b80\u5355\u7684\u6700\u5c0f\u4e8c\u4e58\u95ee\u9898:</p> \\[ \\min_{x}F(x)=\\frac12\\|f\\left(x\\right)\\|_{2}^{2}.` \\] <p>\u5bf9\u4e8e\u4e0d\u65b9\u4fbf\u76f4\u63a5\u6c42\u89e3\u7684\u6700\u5c0f\u4e8c\u4e58\u95ee\u9898\uff0c\u6211\u4eec\u53ef\u4ee5\u7528\u8fed\u4ee3\u7684\u65b9\u5f0f\uff0c\u4ece\u4e00\u4e2a\u521d\u59cb\u503c\u51fa\u53d1\uff0c\u4e0d\u65ad\u5730\u66f4\u65b0\u5f53\u524d\u7684\u4f18\u5316\u53d8\u91cf\uff0c\u4f7f\u76ee\u6807\u51fd\u6570\u4e0b\u964d:</p> <ol> <li>\u7ed9\u5b9a\u67d0\u4e2a\u521d\u59cb\u503c \\(\\displaystyle \\boldsymbol{x_{0}}\\)\u3002</li> <li>\u5bf9\u4e8e\u7b2c \\(\\displaystyle k\\) \u6b21\u8fed\u4ee3\uff0c\u5bfb\u627e\u4e00\u4e2a\u589e\u91cf \\(\\displaystyle \\Delta x_{k}\\)\uff0c\u4f7f\u5f97 \\(\\displaystyle \\left\\|f\\left(\\boldsymbol{x}_{k}+\\Delta\\boldsymbol{x}_{k}\\right)\\right\\|_{2}^{2}\\) \u8fbe\u5230\u6700\u5c0f\u503c\u3002</li> <li>\u82e5 \\(\\displaystyle \\Delta x_k\\) \u8db3\u591f\u5c0f\uff0c\u5219\u505c\u6b62\u3002</li> <li>\u5426\u5219\uff0c\u4ee4 \\(\\displaystyle x_{k+1} = x_{k} + \\Delta x_{k}\\)\uff0c\u8fd4\u56de\u7b2c\u4e8c\u6b65 \u4e8e\u662f\u6c42\u89e3\u5bfc\u51fd\u6570\u4e3a\u96f6 -&gt; \u5bfb\u627e\u4e0b\u964d\u589e\u91cf \\(\\displaystyle \\Delta x_{k}\\) </li> </ol> <p>\u4e0b\u9762\u662f\u4e00\u4e9b\u5e7f\u6cdb\u4f7f\u7528\u7684\u7ed3\u679c\u3002</p>"},{"location":"CV/SLAM14/#621","title":"6.2.1 \u4e00\u9636\u548c\u4e8c\u9636\u68af\u5ea6\u6cd5","text":"<p>\u4f7f\u7528\u6cf0\u52d2\u5c55\u5f00:</p> \\[ F(\\boldsymbol{x}_k+\\Delta\\boldsymbol{x}_k)\\approx F(\\boldsymbol{x}_k)+\\boldsymbol{J}\\left(\\boldsymbol{x}_k\\right)^\\mathrm{T}\\Delta\\boldsymbol{x}_k+\\frac{1}{2}\\Delta\\boldsymbol{x}_k^\\mathrm{T}\\boldsymbol{H}(\\boldsymbol{x}_k)\\Delta\\boldsymbol{x}_k. \\] <p>\u5176\u4e2d \\(\\displaystyle \\boldsymbol{J}(x_{k})\\) \u662f \\(\\displaystyle F(x)\\) \u5173\u4e8e \\(\\displaystyle x\\) \u7684\u4e00\u9636\u5bfc\u6570\uff08\u68af\u5ea6\u3001\u96c5\u53ef\u6bd4\u77e9\u9635\uff09\uff0c\\(\\displaystyle \\boldsymbol{H}\\) \u662f\u4e8c\u9636\u5bfc\u6570\uff08\u6d77\u585e\u77e9\u9635\uff09\u3002</p> \\[ \\Delta\\boldsymbol{x}^*=-\\boldsymbol{J}(\\boldsymbol{x}_k). \\] \\[ \\Delta\\boldsymbol{x}^*=\\arg\\min\\left(F\\left(\\boldsymbol{x}\\right)+\\boldsymbol{J}\\left(\\boldsymbol{x}\\right)^\\mathrm{T}\\Delta\\boldsymbol{x}+\\frac{1}{2}\\Delta\\boldsymbol{x}^\\mathrm{T}\\boldsymbol{H}\\Delta\\boldsymbol{x}\\right). \\] <p>\u5bf9 \\(\\displaystyle \\Delta x\\) \u6c42\u5bfc\uff0c\u5e76\u4ee4\u5b83\u7b49\u4e8e\u96f6\uff0c\u5f97\u5230:</p> \\[ J+H\\Delta x=\\mathbf{0}\\Rightarrow H\\Delta x=-J. \\] <p>\u8fd9\u4e2a\u65b9\u6cd5\u53c8\u53eb\u725b\u987f\u6cd5\u3002</p>"},{"location":"CV/SLAM14/#622","title":"6.2.2 \u9ad8\u65af\u725b\u987f\u6cd5","text":"<p>\u6362\u4e00\u4e2a\u51fd\u6570\u5c55\u5f00:</p> \\[ f\\left(x+\\Delta x\\right)\\approx f\\left(x\\right)+\\boldsymbol{J}\\left(\\boldsymbol{x}\\right)^{\\mathrm{T}}\\Delta\\boldsymbol{x}. \\] \\[ \\Delta x^{*}=\\arg\\min_{\\Delta x}\\frac{1}{2}\\Big\\|f\\left(\\boldsymbol{x}\\right)+\\boldsymbol{J}\\left(\\boldsymbol{x}\\right)^{\\mathrm{T}}\\Delta\\boldsymbol{x}\\Big\\|^{2}. \\] \\[ \\begin{aligned} \\frac12\\left\\|f\\left(\\boldsymbol{x}\\right)+\\boldsymbol{J}\\left(\\boldsymbol{x}\\right)^\\mathrm{T}\\Delta\\boldsymbol{x}\\right\\|^2&amp; =\\frac12\\Big(f\\left(\\boldsymbol{x}\\right)+\\boldsymbol{J}\\left(\\boldsymbol{x}\\right)^\\mathrm{T}\\Delta\\boldsymbol{x}\\Big)^\\mathrm{T}\\Big(f\\left(\\boldsymbol{x}\\right)+\\boldsymbol{J}\\left(\\boldsymbol{x}\\right)^\\mathrm{T}\\Delta\\boldsymbol{x}\\Big) \\\\ &amp;=\\frac12\\left(\\|f(\\boldsymbol{x})\\|_2^2+2f\\left(\\boldsymbol{x}\\right)\\boldsymbol{J}(\\boldsymbol{x})^\\intercal\\Delta\\boldsymbol{x}+\\Delta\\boldsymbol{x}^\\intercal\\boldsymbol{J}(\\boldsymbol{x})\\boldsymbol{J}(\\boldsymbol{x})^\\intercal\\Delta\\boldsymbol{x}\\right). \\end{aligned} \\] \\[ \\boldsymbol{J}(\\boldsymbol{x})f\\left(\\boldsymbol{x}\\right)+\\boldsymbol{J}(\\boldsymbol{x})\\boldsymbol{J}^\\mathrm{T}\\left(\\boldsymbol{x}\\right)\\Delta\\boldsymbol{x}=\\boldsymbol{0}. \\] \\[ \\underbrace{\\boldsymbol{J}(\\boldsymbol{x})\\boldsymbol{J}^{\\intercal}}_{\\boldsymbol{H}(\\boldsymbol{x})}\\left(\\boldsymbol{x}\\right)\\Delta\\boldsymbol{x}=\\underbrace{-\\boldsymbol{J}(\\boldsymbol{x})f\\left(\\boldsymbol{x}\\right)}_{\\boldsymbol{g}(\\boldsymbol{x})}. \\] <p>\u589e\u91cf\u65b9\u7a0b or Gauss-Newton equation or Normal equation</p> \\[ H\\Delta x=g. \\] <p>\u6c42\u89e3\u589e\u91cf\u65b9\u7a0b\u662f\u6574\u4e2a\u4f18\u5316\u95ee\u9898\u7684\u6838\u5fc3\u6240\u5728 \u603b\u7ed3\u4e00\u4e0b:</p> <ol> <li>\u7ed9\u5b9a\u521d\u59cb\u503c \\(\\displaystyle \\boldsymbol{x}_{0}\\)\u3002</li> <li>\u5bf9\u4e8e\u7b2c \\(\\displaystyle k\\) \u6b21\u8fed\u4ee3\uff0c\u6c42\u89e3\u5f53\u524d\u7684\u96c5\u53ef\u6bd4\u77e9\u9635 \\(\\displaystyle \\boldsymbol{J}(x)\\) \u548c\u8bef\u5dee \\(\\displaystyle f(\\boldsymbol{x}_{k})\\)\u3002</li> <li>\u6c42\u89e3\u589e\u91cf\u65b9\u7a0b: \\(\\displaystyle \\boldsymbol{H} \\Delta x_{k} = \\boldsymbol{g}\\)\u3002</li> <li>\u82e5 \\(\\displaystyle \\Delta x_{k}\\) \u8db3\u591f\u5c0f\uff0c\u5219\u505c\u6b62\u3002\u5426\u5219\uff0c\u4ee4 \\(\\displaystyle x_{k+1} = x_{k}+ \\Delta x_{k}\\)\uff0c\u8fd4\u56de\u7b2c 2 \u6b65\u3002</li> </ol>"},{"location":"CV/SLAM14/#623","title":"6.2.3 \u5217\u6587\u4f2f\u683c\u2014\u2014\u9a6c\u5938\u5c14\u7279\u65b9\u6cd5","text":"<p>Damped Newton Method Trust Region Trust Region Method</p> \\[ \\rho=\\frac{f\\left(\\boldsymbol{x}+\\Delta\\boldsymbol{x}\\right)-f\\left(\\boldsymbol{x}\\right)}{\\boldsymbol{J}\\left(\\boldsymbol{x}\\right)^{\\intercal}\\Delta\\boldsymbol{x}}. \\] <p>\u6846\u67b6:</p> <ol> <li>\u7ed9\u5b9a\u521d\u59cb\u503c \\(\\displaystyle \\boldsymbol{x}_{0}\\)\uff0c\u4ee5\u53ca\u521d\u59cb\u4f18\u5316\u534a\u5f84 \\(\\displaystyle \\mu\\)\u3002</li> <li>\u5bf9\u4e8e\u7b2c \\(\\displaystyle k\\) \u6b21\u8fed\u4ee3\uff0c\u5728\u9ad8\u65af\u725b\u987f\u6cd5\u7684\u57fa\u7840\u4e0a\u52a0\u4e0a\u4fe1\u8d56\u533a\u57df\uff0c\u6c42\u89e3: \\(\\displaystyle \\min_{\\Delta\\boldsymbol{x}_{k}}\\frac{1}{2}\\Big\\|f\\left(\\boldsymbol{x}_{k}\\right)+\\boldsymbol{J}\\left(\\boldsymbol{x}_{k}\\right)^{\\mathrm{T}}\\Delta\\boldsymbol{x}_{k}\\Big\\|^{2},\\quad\\mathrm{s.t.}\\quad\\left\\|\\boldsymbol{D}\\Delta\\boldsymbol{x}_{k}\\right\\|^{2}\\leqslant\\mu,\\) </li> <li>\u8ba1\u7b97 \\(\\displaystyle \\rho\\)</li> <li>\u5bf9\u4e8e \\(\\displaystyle \\frac{1}{4}  \\frac{3}{4}\\) \u8fdb\u884c\u5206\u7c7b\u8ba8\u8bba</li> <li>\u5224\u65ad\u9608\u503c\uff0c\u5faa\u73af</li> </ol> <p>\u8fd9\u662f\u5e26\u4e0d\u7b49\u5f0f\u7ea6\u675f\u7684\u4f18\u5316\u95ee\u9898:</p> \\[ \\mathcal{L}(\\Delta\\boldsymbol{x}_{k},\\lambda)=\\frac{1}{2}\\left\\|f\\left(\\boldsymbol{x}_{k}\\right)+\\boldsymbol{J}\\left(\\boldsymbol{x}_{k}\\right)^{\\mathrm{T}}\\Delta\\boldsymbol{x}_{k}\\right\\|^{2}+\\frac{\\lambda}{2}\\left(\\left\\|\\boldsymbol{D}\\Delta\\boldsymbol{x}_{k}\\right\\|^{2}-\\mu\\right). \\] \\[ (H+\\lambda D^\\mathrm{T}D) \\Delta x_k=g. \\]"},{"location":"CV/SLAM14/#63","title":"6.3 \u5b9e\u8df5: \u66f2\u7ebf\u62df\u5408\u95ee\u9898","text":""},{"location":"CV/SLAM14/#631","title":"6.3.1 \u624b\u5199\u9ad8\u65af\u725b\u987f\u6cd5","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#632-ceres","title":"6.3.2 \u4f7f\u7528 Ceres \u8fdb\u884c\u66f2\u7ebf\u62df\u5408","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#633-g2o","title":"6.3.3 \u4f7f\u7528 g2o\u8fdb\u884c\u66f2\u7ebf\u62df\u5408","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#7-1","title":"7 \u89c6\u89c9\u91cc\u7a0b\u8ba1 1","text":""},{"location":"CV/SLAM14/#71","title":"7.1 \u7279\u5f81\u70b9\u6cd5","text":"<ul> <li>\u7279\u5f81\u70b9\u6cd5<ul> <li>\u4e24\u89c6\u56fe\u51e0\u4f55\uff08Two-view geometry\uff09</li> </ul> </li> <li>\u76f4\u63a5\u6cd5</li> </ul>"},{"location":"CV/SLAM14/#711","title":"7.1.1 \u7279\u5f81\u70b9","text":"<ul> <li>\u5982\u4f55\u6839\u636e\u56fe\u50cf\u4f30\u8ba1\u76f8\u673a\u8fd0\u52a8</li> <li>\u8def\u6807: \u56fe\u50cf\u7279\u5f81</li> <li>\u7279\u5f81\u70b9\u5728\u76f8\u673a\u8fd0\u52a8\u4e4b\u540e\u4fdd\u6301\u7a33\u5b9a<ul> <li>\u89d2\u70b9</li> </ul> </li> <li>\u4eba\u5de5\u8bbe\u8ba1\u7684\u7279\u5f81\u70b9:<ul> <li>Repeatability</li> <li>Distinctiveness</li> <li>Efficiency</li> <li>Locality</li> </ul> </li> <li>\u7531\u4e24\u90e8\u5206\u7ec4\u6210:<ul> <li>\u5173\u952e\u70b9\uff08Key-point\uff09</li> <li>\u63cf\u8ff0\u5b50\uff08Descriptor\uff09</li> </ul> </li> <li>SIFT (\u5c3a\u5ea6\u4e0d\u53d8\u7279\u5f81\u53d8\u6362\uff0cScale-Invariant Feature Transform)<ul> <li>\u8003\u8651\u5145\u5206\uff0c\u4f46\u662f\u8ba1\u7b97\u91cf\u6bd4\u8f83\u5927</li> </ul> </li> <li>ORB (Oriented FAST and Rotated BRIEF)</li> </ul>"},{"location":"CV/SLAM14/#712-orb","title":"7.1.2 ORB \u7279\u5f81","text":"<ol> <li>FAST \u89d2\u70b9\u63d0\u53d6: ORB \u4e2d\u8ba1\u7b97\u4e86\u7279\u5f81\u70b9\u7684\u4e3b\u65b9\u5411\uff0c\u4e3a\u540e\u7eed\u7684 BRIEF \u63cf\u8ff0\u5b50\u589e\u52a0\u4e86\u65cb\u8f6c\u4e0d\u53d8\u7279\u6027</li> <li>BRIEF \u63cf\u8ff0\u5b50: \u5bf9\u524d\u4e00\u6b65\u63d0\u53d6\u51fa\u7279\u5f81\u70b9\u7684\u5468\u56f4\u56fe\u50cf\u533a\u57df\u8fdb\u884c\u63cf\u8ff0\u3002\u4f7f\u7528\u5148\u524d\u8ba1\u7b97\u7684\u65b9\u5411\u4fe1\u606f\u3002 - FAST \u5173\u952e\u70b9  Non-maximal suppression \u5c3a\u5ea6\u4e0d\u53d8\u6027\u7531\u6784\u5efa\u56fe\u50cf\u91d1\u5b57\u5854 \u7279\u5f81\u7684\u65cb\u8f6c: Intensity Centroid \u65cb\u8f6c\u65b9\u9762\uff0c\u6211\u4eec\u8ba1\u7b97\u7279\u5f81\u70b9\u9644\u8fd1\u7684\u56fe\u50cf\u7070\u5ea6\u8d28\u5fc3\u3002</li> <li>\u5b9a\u4e49\u56fe\u50cf\u7684\u77e9: \\(\\displaystyle m_{pq} = \\Sigma _{x,y \\in B} x^p x^q I(x, y),p,q \\in \\{0, 1\\}\\).</li> <li>\u627e\u5230\u56fe\u50cf\u5757\u7684\u8d28\u5fc3: \\(\\displaystyle C=\\left(\\frac{m_{10}}{m_{00}},\\frac{m_{01}}{m_{00}}\\right).\\)</li> <li>\u5f97\u5230\u4e00\u4e2a\u51e0\u4f55\u4e2d\u5fc3\u5230\u8d28\u5fc3\u7684\u65b9\u5411\u5411\u91cf: \\(\\displaystyle \\theta=\\arctan(m_{01}/m_{10}).\\) - BRIEF \u63cf\u8ff0\u5b50 \u4e8c\u8fdb\u5236\u8868\u8fbe+\u968f\u673a\u9009\u70b9\u6bd4\u8f83</li> </ol>"},{"location":"CV/SLAM14/#713","title":"7.1.3 \u7279\u5f81\u5339\u914d","text":"<p>data association Brute-Force Matcher</p> <ul> <li>\u901a\u8fc7\u6d4b\u91cf\u63cf\u8ff0\u5b50\u7684\u8ddd\u79bb\u6765\u53bb\u6700\u8fd1\u7684\u4e00\u4e2a\u4f5c\u4e3a\u5339\u914d\u70b9\u3002\u63cf\u8ff0\u5b50\u8ddd\u79bb\u8868\u793a\u4e86\u4e24\u4e2a\u7279\u5f81\u4e4b\u95f4\u7684\u76f8\u4f3c\u7a0b\u5ea6\u3002<ul> <li>\u6b27\u6c0f\u8ddd\u79bb</li> <li>\u6c49\u660e\u8ddd\u79bb<ul> <li>\u4e24\u4e2a\u4e8c\u8fdb\u5236\u4e32\u7684\u4e0d\u540c\u4f4d\u6570\u7684\u4e2a\u6570</li> </ul> </li> </ul> </li> <li>\u5feb\u901f\u8fd1\u4f3c\u6700\u8fd1\u90bb\uff08FLANN\uff09</li> </ul>"},{"location":"CV/SLAM14/#72","title":"7.2 \u5b9e\u8df5: \u7279\u5f81\u63d0\u53d6\u548c\u5339\u914d","text":""},{"location":"CV/SLAM14/#721-opencv-orb","title":"7.2.1 OpenCV \u7684 ORB \u7279\u5f81","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#722-orb","title":"7.2.2 \u624b\u5199 ORB \u7279\u5f81","text":""},{"location":"CV/SLAM14/#723","title":"7.2.3 \u8ba1\u7b97\u76f8\u673a\u8fd0\u52a8","text":"<ol> <li>\u5f53\u76f8\u673a\u4e3a\u5355\u76ee\u65f6\uff0c\u6211\u4eec\u901a\u8fc7\u5bf9\u6781\u51e0\u4f55\u6765\u89e3\u51b3\u4e24\u7ec4 2 D \u70b9\u4f30\u8ba1\u8fd0\u52a8\u7684\u95ee\u9898</li> <li>\u5f53\u76f8\u673a\u4e3a\u53cc\u76ee\u3001RGB-D \u65f6\uff0c\u901a\u8fc7 ICP \u6765\u89e3\u51b3\u4e24\u7ec4 3 D \u70b9\u4f30\u8ba1\u8fd0\u52a8\u7684\u95ee\u9898</li> <li>\u4e00\u4e2a\u662f 2 D \u4e00\u4e2a\u662f 3 D \u65f6\uff0c\u901a\u8fc7 PnP \u6765\u6c42\u89e3</li> </ol>"},{"location":"CV/SLAM14/#73-d-2-d","title":"7.3 D-2 D: \u5bf9\u6781\u51e0\u4f55","text":""},{"location":"CV/SLAM14/#731","title":"7.3.1 \u5bf9\u6781\u7ea6\u675f","text":"<ul> <li>Epipolar plane</li> <li>Epipoles</li> <li>Epipolar line </li> </ul> \\[ P=[X,Y,Z]^{\\mathrm{T}}. \\] \\[ s_{1}p_{1}=KP,\\quad s_{2}p_{2}=K\\left(RP+t\\right). \\] <p>\u6210\u6295\u5f71\u5173\u7cfb:\u5c3a\u5ea6\u610f\u4e49\u4e0b\u76f8\u7b49 (equal up to scale)</p> \\[ sp\\simeq p. \\] \\[ p_1\\simeq KP,\\quad p_2\\simeq K\\left(RP+t\\right). \\] \\[ x_1=K^{-1}p_1,\\quad x_2=K^{-1}p_2. \\] \\[ x_2\\simeq Rx_1+t. \\] \\[ t^{\\wedge}x_{2}\\simeq t^{\\wedge}Rx_{1}. \\] \\[ x_2^\\mathrm{T}t^\\wedge x_2\\simeq x_2^\\mathrm{T}t^\\wedge Rx_1. \\] \\[ x_2^\\mathrm{T}t^\\wedge Rx_1=0. \\] \\[ p_2^\\mathrm{T}K^{-\\mathrm{T}}t^\\wedge RK^{-1}p_1=0. \\] <p>\u5bf9\u6781\u7ea6\u675f</p> \\[ E=t^{\\wedge}R,\\quad F=K^{-\\mathrm{T}}EK^{-1},\\quad x_{2}^{\\mathrm{T}}Ex_{1}=p_{2}^{\\mathrm{T}}Fp_{1}=0. \\] <ol> <li>\u6839\u636e\u914d\u5bf9\u70b9\u7684\u50cf\u7d20\u4f4d\u7f6e\u6c42\u51fa \\(\\displaystyle \\boldsymbol{E}\\) \u6216\u8005 \\(\\displaystyle \\boldsymbol{F}\\)\u3002</li> <li>\u6839\u636e \\(\\displaystyle \\boldsymbol{E}\\) \u6216\u8005 \\(\\displaystyle \\boldsymbol{F}\\) \u6c42\u51fa \\(\\displaystyle \\boldsymbol{R},\\boldsymbol{t}\\)\u3002 \\(\\displaystyle \\boldsymbol{E}\\) \u548c \\(\\displaystyle \\boldsymbol{F}\\) \u53ea\u76f8\u5dee\u4e86\u76f8\u673a\u5185\u53c2\uff0c\u6240\u4ee5\u5b9e\u8df5\u4e2d\u5f80\u5f80\u4f7f\u7528\u5f62\u5f0f\u66f4\u7b80\u5355\u7684 \\(\\displaystyle \\boldsymbol{E}\\)\u3002</li> </ol>"},{"location":"CV/SLAM14/#732","title":"7.3.2 \u672c\u8d28\u77e9\u9635","text":"<p>\u672c\u8d28\u77e9\u9635: \\(\\displaystyle E=t^{\\wedge}R\\)</p> <ul> <li>\\(\\displaystyle \\boldsymbol{E}\\) \u4e0d\u540c\u5c3a\u5ea6\u4e0b\u662f\u7b49\u4ef7\u7684\u3002</li> <li>\u53ef\u4ee5\u8bc1\u660e\uff0c\u672c\u8d28\u77e9\u9635 \\(\\displaystyle \\boldsymbol{E}\\) \u7684\u5947\u5f02\u503c\u5fc5\u5b9a\u662f \\(\\displaystyle [\\sigma,\\sigma,0]^\\mathrm{T}\\) \u7684\u5f62\u5f0f\uff0c\u8fd9\u79f0\u4e3a\u672c\u8d28\u77e9\u9635\u7684\u5185\u5728\u6027\u8d28\u3002</li> <li>\\(\\displaystyle \\boldsymbol{E}\\) \u5b9e\u9645\u4e0a\u6709 5 \u4e2a\u81ea\u7531\u5ea6\u3002 \u516b\u70b9\u6cd5 (Eight-point-algorithm) \u8003\u8651\u4e00\u5806\u914d\u5bf9\u70b9\uff0c\u5b83\u4eec\u7684\u5f52\u4e00\u5316\u5750\u6807\u4e3a \\(\\displaystyle x_{1}=[u_{1},v_{1},1]^{\\mathrm{T}},x_{2}=[u_{2},v_{2},1]^{\\mathrm{T}}\\)\u3002\u6839\u636e\u5bf9\u6781\u7ea6\u675f\uff0c\u6709</li> </ul> \\[ \\begin{pmatrix}u_2,v_2,1\\end{pmatrix}\\begin{pmatrix}e_1&amp;e_2&amp;e_3\\\\\\\\e_4&amp;e_5&amp;e_6\\\\\\\\e_7&amp;e_8&amp;e_9\\end{pmatrix}\\begin{pmatrix}u_1\\\\\\\\v_1\\\\\\\\1\\end{pmatrix}=0. \\] \\[ \\boldsymbol{e}=[e_1,e_2,e_3,e_4,e_5,e_6,e_7,e_8,e_9]^\\mathrm{T}, \\] \\[ [u_2u_1,u_2v_1,u_2,v_2u_1,v_2v_1,v_2,u_1,v_1,1]\\cdot e=0. \\] <p>\u6211\u4eec\u628a\u6240\u6709\u70b9\u90fd\u653e\u5230\u4e00\u4e2a\u65b9\u7a0b\u4e2d\uff0c\u53d8\u6210\u7ebf\u6027\u65b9\u7a0b\u7ec4:</p> \\[ \\begin{pmatrix}u_2^1u_1^1&amp;u_2^1v_1^1&amp;u_2^1&amp;v_2^1u_1^1&amp;v_2^1v_1^1&amp;v_2^1&amp;u_1^1&amp;v_1^1&amp;1\\\\u_2^2u_1^2&amp;u_2^2v_1^2&amp;u_2^2&amp;v_2^2u_1^2&amp;v_2^2v_1^2&amp;v_2^2&amp;u_1^2&amp;v_1^2&amp;1\\\\\\vdots&amp;\\vdots&amp;\\vdots&amp;\\vdots&amp;\\vdots&amp;\\vdots&amp;\\vdots&amp;\\vdots\\\\u_2^8u_1^8&amp;u_2^8v_1^8&amp;u_2^8&amp;v_2^8u_1^8&amp;v_2^8u_1^8&amp;u_1^8&amp;v_1^8&amp;1\\end{pmatrix}\\begin{pmatrix}e_1\\\\e_2\\\\e_3\\\\e_4\\\\e_5\\\\e_6\\\\e_7\\\\e_8\\\\e_9\\end{pmatrix}=0. \\] \\[ E=U\\Sigma V^{\\mathrm{T}}, \\] \\[ \\begin{aligned}&amp;t_{1}^{\\wedge}=UR_{Z}(\\frac{\\pi}{2})\\Sigma U^{\\mathrm{T}},\\quad R_{1}=UR_{Z}^{\\mathrm{T}}(\\frac{\\pi}{2})V^{\\mathrm{T}}\\\\&amp;t_{2}^{\\wedge}=UR_{Z}(-\\frac{\\pi}{2})\\Sigma U^{\\mathrm{T}},\\quad R_{2}=UR_{Z}^{\\mathrm{T}}(-\\frac{\\pi}{2})V^{\\mathrm{T}}.\\end{aligned} \\] <p></p> \\[ \\boldsymbol{E}=\\boldsymbol{U}\\mathrm{diag}(\\frac{\\sigma_1+\\sigma_2}2,\\frac{\\sigma_1+\\sigma_2}2,0)\\boldsymbol{V}^\\mathrm{T}. \\]"},{"location":"CV/SLAM14/#733","title":"7.3.3 \u5355\u5e94\u77e9\u9635","text":"<p>Homography</p>"},{"location":"CV/SLAM14/#8-2","title":"8 \u89c6\u89c9\u91cc\u7a0b\u8ba1 2","text":""},{"location":"CV/SLAM14/#81","title":"8.1 \u76f4\u63a5\u6cd5\u7684\u5f15\u51fa","text":"<ul> <li>\u7279\u5f81\u70b9\u6cd5\u7684\u7f3a\u70b9<ul> <li>\u5173\u952e\u70b9\u7684\u63d0\u53d6\u4e0e\u63cf\u8ff0\u5b50\u7684\u8ba1\u7b97\u975e\u5e38\u8017\u65f6</li> <li>\u4f7f\u7528\u7279\u5f81\u70b9\u65f6\uff0c\u4f1a\u5ffd\u7565\u9664\u7279\u5f81\u70b9\u4ee5\u5916\u7684\u6240\u6709\u4fe1\u606f</li> <li>\u76f8\u673a\u6709\u65f6\u4f1a\u8fd0\u52a8\u5230\u7279\u5f81\u7f3a\u5931\u7684\u5730\u65b9</li> </ul> </li> <li>\u90a3\u4e48\u5982\u4f55\u514b\u670d\u8fd9\u4e9b\u7f3a\u70b9<ul> <li>\u4fdd\u7559\u7279\u5f81\u70b9\uff0c\u4f46\u53ea\u8ba1\u7b97\u5173\u952e\u70b9\uff0c\u4e0d\u8ba1\u7b97\u63cf\u8ff0\u5b50\u3002\u4f7f\u7528\u5149\u6d41\u6cd5\uff08Optical Flow\uff09\u8ddf\u8e2a\u7279\u5f81\u70b9\u7684\u8fd0\u52a8</li> <li>\u53ea\u8ba1\u7b97\u5173\u952e\u70b9\uff0c\u4e0d\u8ba1\u7b97\u63cf\u8ff0\u5b50\u3002\u4f7f\u7528\u76f4\u63a5\u6cd5\uff08Direct Method\uff09</li> </ul> </li> <li>\u7b2c\u4e00\u79cd\u65b9\u6cd5\u4ecd\u7136\u4f7f\u7528\u7279\u5f81\u70b9\uff0c\u53ea\u662f\u628a\u5339\u914d\u63cf\u8ff0\u5b57\u66ff\u6362\u6210\u4e86\u5149\u6d41\u8ddf\u8e2a\uff0c\u4f30\u8ba1\u76f8\u673a\u8fd0\u52a8\u65f6\u4ecd\u7136\u662f\u54e6\u90a3\u4e2a\u5bf9\u6781\u51e0\u4f55\u3001PnP \u6216 ICP \u7b97\u6cd5\uff08\u5373\uff0c\u6211\u4eec\u9700\u8981\u63d0\u5230\u89d2\u70b9\uff09</li> <li>\u7279\u5f81\u70b9\u6cd5:\u901a\u8fc7\u6700\u5c0f\u5316\u91cd\u6295\u5f71\u8bef\u5dee\uff08Reprojection error\uff09\u4f18\u5316\u76f8\u673a\u8fd0\u52a8</li> <li>\u76f4\u63a5\u6cd5: \u901a\u8fc7\u6700\u5c0f\u5316\u5149\u5ea6\u8bef\u5dee\uff08Photometric error\uff09</li> <li>\u53ea\u8981\u573a\u666f\u4e2d\u5b58\u5728\u660e\u6697\u53d8\u5316\u5c31\u53ef\u4ee5\u5de5\u4f5c<ul> <li>\u7a20\u5bc6</li> <li>\u534a\u7a20\u5bc6</li> <li>\u7a00\u758f</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#82-d","title":"8.2 D \u5149\u6d41","text":"<ul> <li>\u8ba1\u7b97\u90e8\u5206\u50cf\u7d20\u8fd0\u52a8: \u7a00\u758f\u5149\u6d41<ul> <li>Lucas-Kanasde</li> </ul> </li> <li>\u8ba1\u7b97\u6240\u6709\u50cf\u7d20\u8fd0\u52a8: \u7a20\u5bc6\u5149\u6d41<ul> <li>Horn-Schunck Lucas-Kanade \u5149\u6d41</li> </ul> </li> <li>\u7070\u5ea6\u4e0d\u53d8\u5047\u8bbe: \u540c\u4e00\u4e2a\u7a7a\u95f4\u70b9\u7684\u50cf\u7d20\u7070\u5ea6\u503c\uff0c\u5728\u5404\u4e2a\u56fe\u50cf\u4e2d\u65f6\u56fa\u5b9a\u4e0d\u53d8\u7684</li> </ul> \\[ I(x+\\mathrm{d}x,y+\\mathrm{d}y,t+\\mathrm{d}t)=I(x,y,t). \\] \\[ \\boldsymbol{I}\\left(x+\\mathrm{d}x,y+\\mathrm{d}y,t+\\mathrm{d}t\\right)\\approx\\boldsymbol{I}\\left(x,y,t\\right)+\\frac{\\partial\\boldsymbol{I}}{\\partial x}\\mathrm{d}x+\\frac{\\partial\\boldsymbol{I}}{\\partial y}\\mathrm{d}y+\\frac{\\partial\\boldsymbol{I}}{\\partial t}\\mathrm{d}t. \\] \\[ \\frac{\\partial\\boldsymbol{I}}{\\partial x}\\frac{\\mathrm{d}x}{\\mathrm{d}t}+\\frac{\\partial\\boldsymbol{I}}{\\partial y}\\frac{\\mathrm{d}y}{\\mathrm{d}t}=-\\frac{\\partial\\boldsymbol{I}}{\\partial t}. \\] \\[ \\begin{bmatrix}I_x&amp;I_y\\end{bmatrix}\\begin{bmatrix}u\\\\\\\\v\\end{bmatrix}=-I_t. \\] \\[ \\begin{bmatrix}I_x&amp;I_y\\end{bmatrix}_k\\begin{bmatrix}u\\\\\\\\v\\end{bmatrix}=-I_{tk},\\quad k=1,\\ldots,w^2. \\] \\[ A\\begin{bmatrix}u\\\\\\\\v\\end{bmatrix}=-b. \\] \\[ \\begin{bmatrix}u\\\\\\\\v\\end{bmatrix}^*=-\\begin{pmatrix}\\boldsymbol{A}^\\mathrm{T}\\boldsymbol{A}\\end{pmatrix}^{-1}\\boldsymbol{A}^\\mathrm{T}\\boldsymbol{b}. \\]"},{"location":"CV/SLAM14/#83-lk","title":"8.3 \u5b9e\u8df5: LK \u5149\u6d41","text":""},{"location":"CV/SLAM14/#831-lk","title":"8.3.1 \u4f7f\u7528 LK \u5149\u6d41","text":"C++<pre><code>vector&lt;Point2f&gt; pt1, pt2;\nfor (auto &amp;kp: kp1) pt1.push_back(kp.pt);\nvector&lt;uchar&gt; status;\nvector&lt;float&gt; error;\ncv::calcOpticalFlowPyrLK(img1, img2, pt1, pt2, status, error);\n</code></pre>"},{"location":"CV/SLAM14/#832","title":"8.3.2 \u7528\u9ad8\u65af\u725b\u987f\u6cd5\u5b9e\u73b0\u5149\u6d41","text":"<p>\u5355\u5c42\u5149\u6d41 TODO</p> \\[ \\min_{\\Delta x,\\Delta y}\\left\\|\\boldsymbol{I}_1\\left(x,y\\right)-\\boldsymbol{I}_2\\left(x+\\Delta x,y+\\Delta y\\right)\\right\\|_2^2. \\] <p>\u591a\u5c42\u5149\u6d41 - \u7531\u7c97\u81f3\u7cbe\uff08Coarse-to-fine\uff09</p>"},{"location":"CV/SLAM14/#833","title":"8.3.3 \u5149\u6d41\u5b9e\u8df5\u5c0f\u7ed3","text":""},{"location":"CV/SLAM14/#84","title":"8.4 \u76f4\u63a5\u6cd5","text":""},{"location":"CV/SLAM14/#841","title":"8.4.1 \u76f4\u63a5\u6cd5\u7684\u63a8\u5bfc","text":"\\[ \\boldsymbol{p}_1=\\begin{bmatrix}u\\\\\\\\v\\\\\\\\1\\end{bmatrix}_1=\\frac{1}{Z_1}\\boldsymbol{K}\\boldsymbol{P}, \\] \\[ \\boldsymbol{p}_{2}=\\begin{bmatrix}u\\\\\\\\v\\\\\\\\1\\end{bmatrix}_{2}=\\frac{1}{Z_{2}}\\boldsymbol{K}\\left(\\boldsymbol{R}\\boldsymbol{P}+\\boldsymbol{t}\\right)=\\frac{1}{Z_{2}}\\boldsymbol{K}\\left(\\boldsymbol{T}\\boldsymbol{P}\\right)_{1:3}. \\] \\[ e=\\boldsymbol{I}_1\\left(\\boldsymbol{p}_1\\right)-\\boldsymbol{I}_2\\left(\\boldsymbol{p}_2\\right). \\] \\[ \\min_{T}J\\left(T\\right)=\\left\\|e\\right\\|^{2}. \\] \\[ \\min_{\\boldsymbol{T}}J\\left(\\boldsymbol{T}\\right)=\\sum_{i=1}^{N}e_{i}^{\\mathrm{T}}e_{i},\\quad e_{i}=\\boldsymbol{I}_{1}\\left(\\boldsymbol{p}_{1,i}\\right)-\\boldsymbol{I}_{2}\\left(\\boldsymbol{p}_{2,i}\\right). \\] \\[ \\begin{aligned}&amp;q=TP,\\\\&amp;\\boldsymbol{u}=\\frac{1}{Z_{2}}Kq.\\end{aligned} \\] \\[ e(T)=I_1(p_1)-I_2(u), \\] \\[ \\frac{\\partial e}{\\partial\\boldsymbol{T}}=\\frac{\\partial\\boldsymbol{I}_{2}}{\\partial\\boldsymbol{u}}\\frac{\\partial\\boldsymbol{u}}{\\partial\\boldsymbol{q}}\\frac{\\partial\\boldsymbol{q}}{\\partial\\delta\\boldsymbol{\\xi}}\\delta\\boldsymbol{\\xi}, \\] \\[ \\frac{\\partial\\boldsymbol{u}}{\\partial\\boldsymbol{q}}=\\begin{bmatrix}\\frac{\\partial u}{\\partial X}&amp;\\frac{\\partial u}{\\partial Y}&amp;\\frac{\\partial u}{\\partial Z}\\\\\\frac{\\partial v}{\\partial X}&amp;\\frac{\\partial v}{\\partial Y}&amp;\\frac{\\partial v}{\\partial Z}\\end{bmatrix}=\\begin{bmatrix}\\frac{f_x}{Z}&amp;0&amp;-\\frac{f_xX}{Z^2}\\\\0&amp;\\frac{f_y}{Z}&amp;-\\frac{f_yY}{Z^2}\\end{bmatrix}. \\] \\[ \\frac{\\partial\\boldsymbol{q}}{\\partial\\delta\\boldsymbol{\\xi}}=\\left[I,-\\boldsymbol{q}^{\\wedge}\\right]. \\] \\[ \\frac{\\partial\\boldsymbol{u}}{\\partial\\delta\\boldsymbol{\\xi}}=\\begin{bmatrix}\\frac{f_x}{Z}&amp;0&amp;-\\frac{f_xX}{Z^2}&amp;-\\frac{f_xXY}{Z^2}&amp;f_x+\\frac{f_xX^2}{Z^2}&amp;-\\frac{f_xY}{Z}\\\\0&amp;\\frac{f_y}{Z}&amp;-\\frac{f_yY}{Z^2}&amp;-f_y-\\frac{f_yY^2}{Z^2}&amp;\\frac{f_yXY}{Z^2}&amp;\\frac{f_yX}{Z}\\end{bmatrix}. \\] \\[ J=-\\frac{\\partial I_2}{\\partial u}\\frac{\\partial u}{\\partial\\delta\\xi}. \\]"},{"location":"CV/SLAM14/#842","title":"8.4.2 \u76f4\u63a5\u6cd5\u7684\u8ba8\u8bba","text":""},{"location":"CV/SLAM14/#85","title":"8.5 \u5b9e\u8df5: \u76f4\u63a5\u6cd5","text":""},{"location":"CV/SLAM14/#851","title":"8.5.1 \u5355\u5c42\u76f4\u63a5\u6cd5","text":""},{"location":"CV/SLAM14/#852","title":"8.5.2 \u591a\u5c42\u76f4\u63a5\u6cd5","text":""},{"location":"CV/SLAM14/#853","title":"8.5.3 \u7ed3\u679c\u8ba8\u8bba","text":"<ul> <li>Normalized Cross</li> </ul>"},{"location":"CV/SLAM14/#854","title":"8.5.4 \u76f4\u63a5\u6cd5\u4f18\u7f3a\u70b9\u603b\u7ed3","text":""},{"location":"CV/SLAM14/#9-1","title":"9 \u540e\u7aef 1","text":""},{"location":"CV/SLAM14/#91","title":"9.1 \u6982\u8ff0","text":""},{"location":"CV/SLAM14/#911","title":"9.1.1 \u72b6\u6001\u4f30\u8ba1\u7684\u6982\u7387\u89e3\u91ca","text":"<ul> <li>\u53ea\u4f7f\u7528\u8fc7\u53bb\u7684\u4fe1\u606f: \u6e10\u8fdb\u7684\uff08Incremental\uff09</li> <li>\u4f7f\u7528\u672a\u6765\u7684\u4fe1\u606f\u66f4\u65b0: \u6279\u91cf\u7684\uff08Batch\uff09</li> </ul> \\[ \\begin{cases}\\boldsymbol{x}_k=f\\left(\\boldsymbol{x}_{k-1},\\boldsymbol{u}_k\\right)+\\boldsymbol{w}_k\\\\\\boldsymbol{z}_{k,j}=h\\left(\\boldsymbol{y}_j,\\boldsymbol{x}_k\\right)+\\boldsymbol{v}_{k,j}\\end{cases}\\quad k=1,\\ldots,N, j=1,\\ldots,M. \\] <ul> <li>\u89c2\u6d4b\u65b9\u7a0b\u7684\u6570\u91cf\u4f1a\u8fdc\u8fdc\u5927\u4e8e\u8fd0\u52a8\u65b9\u7a0b</li> <li>\u5f53\u6ca1\u6709\u8fd0\u52a8\u65b9\u7a0b\u7684\u65f6\u5019\uff0c\u6211\u4eec\u53ef\u4ee5\u5047\u8bbe\u76f8\u673a\u4e0d\u52a8\uff0c\u6216\u5047\u8bbe\u76f8\u673a\u5300\u901f\u8fd0\u52a8</li> <li>\u95ee\u9898\uff1a\u5f53\u5b58\u5728\u4e00\u4e9b\u8fd0\u52a8\u6570\u636e\u548c\u89c2\u6d4b\u6570\u636e\u65f6\uff0c\u6211\u4eec\u5982\u4f55\u4f30\u8ba1\u72b6\u6001\u91cf\u7684\u9ad8\u65af\u5206\u5e03</li> <li>\u8bef\u5dee\u65f6\u9010\u6e10\u7d2f\u79ef\u7684</li> <li>\u6700\u5927\u4f3c\u7136\u4f30\u8ba1: \u6279\u91cf\u72b6\u6001\u4f30\u8ba1\u95ee\u9898\u53ef\u4ee5\u8f6c\u5316\u4e3a\u6700\u5927\u4f3c\u7136\u4f30\u8ba1\u95ee\u9898\uff0c\u5e76\u4f7f\u7528\u6700\u5c0f\u4e8c\u4e58\u6cd5\u8fdb\u884c\u6c42\u89e3</li> </ul> \\[ x_k\\stackrel{\\mathrm{def}}{=}\\{x_k,y_1,\\ldots,y_m\\}. \\] \\[ \\begin{cases}\\boldsymbol{x}_k=f\\left(\\boldsymbol{x}_{k-1},\\boldsymbol{u}_k\\right)+\\boldsymbol{w}_k\\\\\\boldsymbol{z}_k=h\\left(\\boldsymbol{x}_k\\right)+\\boldsymbol{v}_k\\end{cases}\\quad k=1,\\ldots,N. \\] \\[ P\\left(\\boldsymbol{x}_k|\\boldsymbol{x}_0,\\boldsymbol{u}_{1:k},\\boldsymbol{z}_{1:k}\\right)\\propto P\\left(\\boldsymbol{z}_k|\\boldsymbol{x}_k\\right)P\\left(\\boldsymbol{x}_k|\\boldsymbol{x}_0,\\boldsymbol{u}_{1:k},\\boldsymbol{z}_{1:k-1}\\right). \\] <ul> <li>\u7b2c\u4e00\u9879\u79f0\u4e3a\u4f3c\u7136\uff0c\u7b2c\u4e8c\u9879\u79f0\u4e3a\u5148\u9a8c</li> </ul> \\[ P\\left(\\boldsymbol{x}_{k}|\\boldsymbol{x}_{0},\\boldsymbol{u}_{1:k},\\boldsymbol{z}_{1:k-1}\\right)=\\int P\\left(\\boldsymbol{x}_{k}|\\boldsymbol{x}_{k-1},\\boldsymbol{x}_{0},\\boldsymbol{u}_{1:k},\\boldsymbol{z}_{1:k-1}\\right)P\\left(\\boldsymbol{x}_{k-1}|\\boldsymbol{x}_{0},\\boldsymbol{u}_{1:k},\\boldsymbol{z}_{1:k-1}\\right)\\mathrm{d}\\boldsymbol{x}_{k-1}. \\] <ul> <li>\u867d\u7136\u53ef\u4ee5\u7ee7\u7eed\u5bf9\u6b64\u5f0f\u8fdb\u884c\u5c55\u5f00\uff0c\u4f46\u6211\u4eec\u53ea\u5173\u5fc3 \\(\\displaystyle k\\) \u65f6\u523b\u548c \\(\\displaystyle k - 1\\) \u65f6\u523b\u7684\u60c5\u51b5<ul> <li>\u7b2c\u4e00\u79cd\u65b9\u6cd5\u662f\u5047\u8bbe\u9a6c\u5c14\u53ef\u592b\u6027: \u5373\u8ba4\u4e3a \\(\\displaystyle k\\) \u65f6\u523b\u72b6\u6001\u53ea\u4e0e \\(\\displaystyle k - 1\\) \u65f6\u523b\u72b6\u6001\u6709\u5173<ul> <li>\u90a3\u4e48\u6211\u4eec\u5c31\u53ef\u4ee5\u5f97\u5230\u4ee5\u6269\u5c55\u5361\u5c14\u66fc\u6ee4\u6ce2\uff08EKF\uff09\u4e3a\u4ee3\u8868\u7684\u6ee4\u6ce2\u5668\u65b9\u5f0f</li> </ul> </li> <li>\u7b2c\u4e8c\u79cd\u65b9\u6cd5\u662f\u4f9d\u7136\u8003\u8651\u548c\u4e4b\u524d\u6240\u6709\u72b6\u6001\u7684\u5173\u7cfb\uff0c\u59ff\u52bf\u4f1a\u5f97\u5230\u975e\u7ebf\u6027\u4f18\u5316\u4e3a\u4e3b\u4f53\u7684\u4f18\u5316\u6846\u67b6\u3002</li> <li>\u4e3b\u6d41\u662f\u975e\u7ebf\u6027\u4f18\u5316</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#912-kf","title":"9.1.2 \u7ebf\u6027\u7cfb\u7edf\u548c KF","text":"\\[ P\\left(\\boldsymbol{x}_k|\\boldsymbol{x}_{k-1},\\boldsymbol{x}_0,\\boldsymbol{u}_{1:k},\\boldsymbol{z}_{1:k-1}\\right)=P\\left(\\boldsymbol{x}_k|\\boldsymbol{x}_{k-1},\\boldsymbol{u}_k\\right). \\] \\[ P\\left(\\boldsymbol{x}_{k-1}|\\boldsymbol{x}_0,\\boldsymbol{u}_{1:k},\\boldsymbol{z}_{1:k-1}\\right)=P\\left(\\boldsymbol{x}_{k-1}|\\boldsymbol{x}_0,\\boldsymbol{u}_{1:k-1},\\boldsymbol{z}_{1:k-1}\\right). \\] <ul> <li>\u6240\u4ee5\u6211\u4eec\u5b9e\u9645\u5728\u505a\u7684\u4e8b\u5982\u4f55\u628a \\(\\displaystyle k - 1\\) \u65f6\u523b\u7684\u72b6\u6001\u5206\u5e03\u63a8\u5bfc\u81f3 \\(\\displaystyle k\\) \u65f6\u523b<ul> <li>\u5373\u6211\u4eec\u53ea\u8981\u7ef4\u62a4\u4e00\u4e2a\u72b6\u6001\uff0c\u5e76\u4e0d\u65ad\u5730\u8fed\u4ee3\u66f4\u65b0<ul> <li>\u53ea\u8981\u7ef4\u62a4\u72b6\u6001\u91cf\u7684\u5747\u503c\u548c\u534f\u65b9\u5dee\uff08\u72b6\u6001\u91cf\u670d\u4ece\u9ad8\u65af\u5206\u5e03\uff09</li> </ul> </li> </ul> </li> </ul> \\[ \\begin{cases}x_k=A_kx_{k-1}+u_k+w_k\\\\z_k=C_kx_k+v_k\\end{cases}\\quad k=1,\\ldots,N. \\] \\[ w_k\\sim N(0,\\boldsymbol{R}).\\quad\\boldsymbol{v}_k\\sim N(\\boldsymbol{0},\\boldsymbol{Q}). \\] <ul> <li>\u4e0a\u5e3d\u5b50\u8868\u793a\u540e\u9a8c\uff0c\u4e0b\u5e3d\u5b50\u8868\u793a\u5148\u9a8c</li> </ul> \\[ P\\left(\\boldsymbol{x}_k|\\boldsymbol{x}_0,\\boldsymbol{u}_{1:k},\\boldsymbol{z}_{1:k-1}\\right)=N\\left(\\boldsymbol{A}_k\\hat{x}_{k-1}+\\boldsymbol{u}_k,\\boldsymbol{A}_k\\hat{\\boldsymbol{P}}_{k-1}\\boldsymbol{A}_k^\\mathrm{T}+\\boldsymbol{R}\\right). \\] <ul> <li>\u8fd9\u4e00\u6b65\u79f0\u4e3a\u9884\u6d4b\uff08Predict\uff09</li> </ul> \\[ \\check{\\boldsymbol{x}}_k=\\boldsymbol{A}_k\\hat{\\boldsymbol{x}}_{k-1}+\\boldsymbol{u}_k,\\quad\\check{\\boldsymbol{P}}_k=A_k\\hat{\\boldsymbol{P}}_{k-1}\\boldsymbol{A}_k^\\mathrm{T}+\\boldsymbol{R}. \\] \\[ P\\left(\\boldsymbol{z}_k|\\boldsymbol{x}_k\\right)=N\\left(\\boldsymbol{C}_k\\boldsymbol{x}_k,\\boldsymbol{Q}\\right). \\] <ul> <li>\u5982\u679c\u7ed3\u679c\u8bbe\u4e3a \\(\\displaystyle x_k\\sim N(\\hat{\\boldsymbol{x}}_k,\\hat{\\boldsymbol{P}}_k)\\)\uff0c\u90a3\u4e48</li> </ul> \\[ N(\\hat{\\boldsymbol{x}}_k,\\hat{\\boldsymbol{P}}_k)=\\eta N\\left(\\boldsymbol{C}_k\\boldsymbol{x}_k,\\boldsymbol{Q}\\right)\\cdot N(\\check{\\boldsymbol{x}}_k,\\check{\\boldsymbol{P}}_k). \\] \\[ (\\boldsymbol{x}_{k}-\\hat{\\boldsymbol{x}}_{k})^{\\mathrm{T}}\\hat{\\boldsymbol{P}}_{k}^{-1}\\left(\\boldsymbol{x}_{k}-\\hat{\\boldsymbol{x}}_{k}\\right)=\\left(\\boldsymbol{z}_{k}-\\boldsymbol{C}_{k}\\boldsymbol{x}_{k}\\right)^{\\mathrm{T}}\\boldsymbol{Q}^{-1}\\left(\\boldsymbol{z}_{k}-\\boldsymbol{C}_{k}\\boldsymbol{x}_{k}\\right)+\\left(\\boldsymbol{x}_{k}-\\check{\\boldsymbol{x}}_{k}\\right)^{\\mathrm{T}}\\boldsymbol{P}_{k}^{-1}\\left(\\boldsymbol{x}_{k}-\\check{\\boldsymbol{x}}_{k}\\right). \\] <ul> <li>\u4e8c\u6b21\u7cfb\u6570</li> </ul> \\[ \\hat{P}_k^{-1}=C_k^{\\mathrm{T}}Q^{-1}C_k+\\check{P}_k^{-1}. \\] <ul> <li>\u5b9a\u4e49\u4e00\u4e2a\u4e2d\u95f4\u53d8\u91cf</li> </ul> \\[ K=\\hat{P}_kC_k^{\\mathrm{T}}Q^{-1}. \\] \\[ I=\\hat{P}_{k}C_{k}^{\\mathrm{T}}Q^{-1}C_{k}+\\hat{P}_{k}\\check{P}_{k}^{-1}=KC_{k}+\\hat{P}_{k}\\check{P}_{k}^{-1}. \\] \\[ \\hat{P}_{k}=(I-KC_{k})\\check{P}_{k}. \\] <ul> <li>\u4e00\u6b21\u9879\u7cfb\u6570</li> </ul> \\[ -2\\hat{\\boldsymbol{x}}_k^\\mathrm{T}\\hat{\\boldsymbol{P}}_k^{-1}\\boldsymbol{x}_k=-2\\boldsymbol{z}_k^\\mathrm{T}\\boldsymbol{Q}^{-1}\\boldsymbol{C}_k\\boldsymbol{x}_k-2\\boldsymbol{\\dot{x}}_k^\\mathrm{T}\\check{\\boldsymbol{P}}_k^{-1}\\boldsymbol{x}_k. \\] \\[ \\hat{\\boldsymbol{P}}_k^{-1}\\hat{\\boldsymbol{x}}_k=\\boldsymbol{C}_k^\\mathrm{T}\\boldsymbol{Q}^{-1}\\boldsymbol{z}_k+\\check{\\boldsymbol{P}}_k^{-1}\\check{\\boldsymbol{x}}_k. \\] \\[ \\begin{aligned} \\hat{x}_{k}&amp; =\\hat{\\boldsymbol{P}}_k\\boldsymbol{C}_k^\\mathrm{T}\\boldsymbol{Q}^{-1}\\boldsymbol{z}_k+\\hat{\\boldsymbol{P}}_k\\check{\\boldsymbol{P}}_k^{-1}\\check{\\boldsymbol{x}}_k \\\\ &amp;=K\\boldsymbol{z}_k+\\left(\\boldsymbol{I}-\\boldsymbol{K}\\boldsymbol{C}_k\\right)\\check{\\boldsymbol{x}}_k=\\check{\\boldsymbol{x}}_k+\\boldsymbol{K}\\left(\\boldsymbol{z}_k-\\boldsymbol{C}_k\\check{\\boldsymbol{x}}_k\\right). \\end{aligned} \\]"},{"location":"CV/SLAM14/#913-ekf","title":"9.1.3 \u975e\u7ebf\u6027\u7cfb\u7edf\u548c EKF","text":"<ul> <li>\u6269\u5c55\u5361\u5c14\u66fc\u6ee4\u6ce2\u5668<ul> <li>\u5373\u628a\u975e\u9ad8\u65af\u5206\u5e03\u8fd1\u4f3c\u6210\u9ad8\u65af\u5206\u5e03</li> </ul> </li> </ul> \\[ \\boldsymbol{x}_k\\approx f\\left(\\hat{\\boldsymbol{x}}_{k-1},\\boldsymbol{u}_k\\right)+\\left.\\frac{\\partial f}{\\partial\\boldsymbol{x}_{k-1}}\\right|_{\\tilde{\\boldsymbol{x}}_{k-1}}\\left(\\boldsymbol{x}_{k-1}-\\hat{\\boldsymbol{x}}_{k-1}\\right)+\\boldsymbol{w}_k. \\] \\[ \\boldsymbol{F}=\\left.\\frac{\\partial f}{\\partial\\boldsymbol{x}_{k-1}}\\right|_{\\hat{\\boldsymbol{x}}_{k-1}}. \\] \\[ z_k\\approx h\\left(\\check{\\boldsymbol{x}}_k\\right)+\\left.\\frac{\\partial h}{\\partial\\boldsymbol{x}_k}\\right|_{\\dot{\\boldsymbol{x}}_k}\\left(\\boldsymbol{x}_k-\\check{\\boldsymbol{x}}_k\\right)+\\boldsymbol{n}_k. \\] \\[ H=\\left.\\frac{\\partial h}{\\partial\\boldsymbol{x}_k}\\right|_{\\check{\\boldsymbol{x}}_k}. \\] \\[ P\\left(\\boldsymbol{x}_k|\\boldsymbol{x}_0,\\boldsymbol{u}_{1:k},\\boldsymbol{z}_{0:k-1}\\right)=N(f\\left(\\hat{\\boldsymbol{x}}_{k-1},\\boldsymbol{u}_k\\right),\\boldsymbol{F}\\hat{\\boldsymbol{P}}_{k-1}\\boldsymbol{F}^\\mathrm{T}+\\boldsymbol{R}_k). \\] \\[ \\check{\\boldsymbol{x}}_k=f\\left(\\hat{\\boldsymbol{x}}_{k-1},\\boldsymbol{u}_k\\right),\\quad\\check{\\boldsymbol{P}}_k=\\boldsymbol{F}\\hat{\\boldsymbol{P}}_{k-1}\\boldsymbol{F}^\\mathrm{T}+\\boldsymbol{R}_k. \\] \\[ P\\left(\\boldsymbol{z}_k|\\boldsymbol{x}_k\\right)=N(h\\left(\\check{\\boldsymbol{x}}_k\\right)+\\boldsymbol{H}\\left(\\boldsymbol{x}_k-\\check{\\boldsymbol{x}}_k\\right),Q_k). \\] <ul> <li>\u5b9a\u4e49\u4e00\u4e2a\u5361\u5c14\u66fc\u589e\u76ca \\(\\displaystyle \\boldsymbol{K}_{k}\\)</li> </ul> \\[ K_{k}=\\check{P}_{k}H^{\\mathrm{T}}(H\\check{P}_{k}H^{\\mathrm{T}}+Q_{k})^{-1}. \\] \\[ \\hat{\\boldsymbol{x}}_k=\\check{\\boldsymbol{x}}_k+\\boldsymbol{K}_k\\left(\\boldsymbol{z}_k-h\\left(\\check{\\boldsymbol{x}}_k\\right)\\right),\\hat{\\boldsymbol{P}}_k=\\left(\\boldsymbol{I}-\\boldsymbol{K}_k\\boldsymbol{H}\\right)\\check{\\boldsymbol{P}}_k. \\]"},{"location":"CV/SLAM14/#914-ekf","title":"9.1.4 EKF \u7684\u8ba8\u8bba","text":"<ul> <li>\u5c40\u9650<ul> <li>\u5047\u8bbe\u4e86\u9a6c\u5c14\u53ef\u592b\u6027\uff0c\u4f46\u662f\u975e\u7ebf\u6027\u4f18\u5316\u662f\u5168\u4f53\u65f6\u95f4\u4e0a\u7684 SLAM (Full-SLAM)</li> <li>\u6709\u975e\u7ebf\u6027\u8bef\u5dee\uff08\u4e3b\u8981\u95ee\u9898\u6240\u5728\uff09</li> <li>\u5982\u679c\u628a\u8def\u6807\u4e5f\u653e\u8fdb\u72b6\u6001\uff0c\u5b58\u4e0d\u4e0b</li> <li>\u6ca1\u6709\u5f02\u5e38\u68c0\u6d4b\u673a\u5236</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#92-ba","title":"9.2 BA \u4e0e\u56fe\u4f18\u5316","text":"<ul> <li>Bundle Adjustment<ul> <li>\u4ece\u89c6\u89c9\u56fe\u50cf\u4e2d\u63d0\u70bc\u51fa\u6700\u6709\u7684 3 D \u6a21\u578b\u548c\u76f8\u673a\u53c2\u6570\uff0c\u8ba9\u5149\u7ebf\u6700\u7ec8\u6536\u675f\u5230\u76f8\u673a\u7684\u5149\u5fc3</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#921-ba","title":"9.2.1 \u6295\u5f71\u6a21\u578b\u548c BA \u4ee3\u4ef7\u51fd\u6570","text":"\\[ P^{\\prime}=Rp+t=[X^{\\prime},Y^{\\prime},Z^{\\prime}]^\\mathrm{T}. \\] \\[ \\boldsymbol{P}_{\\mathrm{c}}=[u_{\\mathrm{c}},v_{\\mathrm{c}},1]^{\\mathrm{T}}=[X^{\\prime}/Z^{\\prime},Y^{\\prime}/Z^{\\prime},1]^{\\mathrm{T}}. \\] \\[ \\begin{cases}u_\\mathrm{c}'=u_\\mathrm{c}\\left(1+k_1r_\\mathrm{c}^2+k_2r_\\mathrm{c}^4\\right)\\\\v_\\mathrm{c}'=v_\\mathrm{c}\\left(1+k_1r_\\mathrm{c}^2+k_2r_\\mathrm{c}^4\\right)\\end{cases}. \\] \\[ \\begin{cases}u_s=f_xu_\\mathrm{c}'+c_x\\\\[2ex]v_s=f_yv_\\mathrm{c}'+c_y\\end{cases}. \\] \\[ z=h(\\boldsymbol{x},\\boldsymbol{y}). \\] \\[ e=z-h(\\boldsymbol{T},\\boldsymbol{p}). \\] \\[ z\\overset{\\mathrm{def}}{\\operatorname*{=}}[u_s,v_s]^\\mathrm{T} \\] \\[ \\frac12\\sum_{i=1}^m\\sum_{j=1}^n\\|e_{ij}\\|^2=\\frac12\\sum_{i=1}^m\\sum_{j=1}^n\\|z_{ij}-h(\\boldsymbol{T}_i,\\boldsymbol{p}_j)\\|^2. \\]"},{"location":"CV/SLAM14/#922-ba","title":"9.2.2 BA \u7684\u6c42\u89e3","text":"\\[ x=[T_1,\\ldots,T_m,p_1,\\ldots,p_n]^\\mathrm{T}. \\] \\[ \\frac12\\left\\|f(\\boldsymbol{x}+\\Delta\\boldsymbol{x})\\right\\|^2\\approx\\frac12\\sum_{i=1}^m\\sum_{j=1}^n\\left\\|\\boldsymbol{e}_{ij}+\\boldsymbol{F}_{ij}\\Delta\\boldsymbol{\\xi}_i+\\boldsymbol{E}_{ij}\\Delta\\boldsymbol{p}_j\\right\\|^2. \\] \\[ x_{\\mathfrak{c}}=[\\boldsymbol{\\xi}_1,\\boldsymbol{\\xi}_2,\\ldots,\\boldsymbol{\\xi}_m]^{\\mathrm{T}}\\in\\mathbb{R}^{6m} \\] \\[ \\boldsymbol{x}_p=[\\boldsymbol{p}_1,\\boldsymbol{p}_2,\\ldots,\\boldsymbol{p}_n]^\\mathrm{T}\\in\\mathbb{R}^{3n} \\] \\[ \\frac12\\left\\|f(\\boldsymbol{x}+\\Delta\\boldsymbol{x})\\right\\|^2=\\frac12\\left\\|\\boldsymbol{e}+\\boldsymbol{F}\\Delta\\boldsymbol{x}_c+\\boldsymbol{E}\\Delta\\boldsymbol{x}_p\\right\\|^2. \\] \\[ \\boldsymbol{J}=[\\boldsymbol{F}\\boldsymbol{E}]. \\] \\[ H=J^\\mathrm{T}J=\\begin{bmatrix}F^\\mathrm{T}F&amp;F^\\mathrm{T}E\\\\E^\\mathrm{T}F&amp;E^\\mathrm{T}E\\end{bmatrix}. \\]"},{"location":"CV/SLAM14/#923","title":"9.2.3 \u7a00\u758f\u6027\u548c\u8fb9\u7f18\u5316","text":"\\[ J_{ij}(x)=\\left(\\mathbf{0}_{2\\times6},\\ldots\\mathbf{0}_{2\\times6},\\frac{\\partial\\boldsymbol{e}_{ij}}{\\partial\\boldsymbol{T}_{i}},\\mathbf{0}_{2\\times6},\\ldots\\mathbf{0}_{2\\times3},\\ldots\\mathbf{0}_{2\\times3},\\frac{\\partial\\boldsymbol{e}_{ij}}{\\partial\\boldsymbol{p}_{j}},\\mathbf{0}_{2\\times3},\\ldots\\mathbf{0}_{2\\times3}\\right). \\] \\[ H=\\sum_{i,j}J_{ij}^{\\top}J_{ij}, \\] \\[ H=\\begin{bmatrix}H_{11}&amp;H_{12}\\\\\\\\H_{21}&amp;H_{22}\\end{bmatrix}. \\] <ul> <li>\u5bf9\u4e8e\u7a00\u758f\u77e9\u9635\uff0c\u6211\u4eec\u7528 Schur \u6d88\u5143\uff08Marginalization\uff09</li> </ul> \\[ \\begin{bmatrix}B&amp;E\\\\E^\\mathrm{T}&amp;C\\end{bmatrix}\\begin{bmatrix}\\Delta x_\\mathrm{c}\\\\\\Delta x_p\\end{bmatrix}=\\begin{bmatrix}v\\\\w\\end{bmatrix}. \\] \\[ \\begin{bmatrix}I&amp;-EC^{-1}\\\\0&amp;I\\end{bmatrix}\\begin{bmatrix}B&amp;E\\\\E^{\\intercal}&amp;C\\end{bmatrix}\\begin{bmatrix}\\Delta x_\\mathrm{c}\\\\\\Delta x_p\\end{bmatrix}=\\begin{bmatrix}I&amp;-EC^{-1}\\\\0&amp;I\\end{bmatrix}\\begin{bmatrix}v\\\\w\\end{bmatrix}. \\] \\[ \\begin{bmatrix}B-EC^{-1}E^\\mathrm{T}&amp;0\\\\E^\\mathrm{T}&amp;C\\end{bmatrix}\\begin{bmatrix}\\Delta x_\\mathrm{c}\\\\\\Delta x_p\\end{bmatrix}=\\begin{bmatrix}v-EC^{-1}w\\\\\\\\w\\end{bmatrix}. \\] \\[ \\begin{bmatrix}B-EC^{-1}E^\\mathrm{T}\\end{bmatrix}\\Delta x_\\mathrm{c}=v-EC^{-1}w. \\] <ul> <li>\u4f18\u52bf<ul> <li>\\(\\displaystyle \\boldsymbol{C}\\) \u4e3a\u5bf9\u89d2\u5757\uff0c\u9006\u6bd4\u8f83\u5bb9\u6613\u89e3\u51fa</li> </ul> </li> <li>\u975e\u5bf9\u89d2\u7ebf\u4e0a\u7684\u975e\u96f6\u77e9\u9635\u5757\u8868\u793a\u5bf9\u5e94\u7684\u4e24\u4e2a\u76f8\u673a\u53d8\u91cf\u4e4b\u95f4\u5b58\u5728\u5171\u540c\u89c2\u6d4b\u7684\u8def\u6807\u70b9\uff0c\u5373\u5171\u89c6\uff08Co-visibility\uff09</li> </ul>"},{"location":"CV/SLAM14/#924","title":"9.2.4 \u9c81\u68d2\u6838\u51fd\u6570","text":"<ul> <li>Robust Kernel</li> </ul> \\[ H(e)=\\begin{cases}\\frac{1}{2}e^2&amp;\\text{\u5f53}|e|\\leqslant\\delta,\\\\\\\\\\delta\\left(|e|-\\frac{1}{2}\\delta\\right)&amp;\\text{\u5176\u4ed6}\\end{cases} \\]"},{"location":"CV/SLAM14/#93-ceres-ba","title":"9.3 \u5b9e\u8df5: Ceres BA","text":""},{"location":"CV/SLAM14/#931-bal","title":"9.3.1 BAL \u6570\u636e\u96c6","text":""},{"location":"CV/SLAM14/#932-ceres-ba","title":"9.3.2 Ceres BA \u7684\u4e66\u5199","text":""},{"location":"CV/SLAM14/#94-g-2-o-ba","title":"9.4 \u5b9e\u8df5: g 2 o \u6c42\u89e3 BA","text":""},{"location":"CV/SLAM14/#95","title":"9.5 \u5c0f\u7ed3","text":""},{"location":"CV/SLAM14/#10-2","title":"10 \u540e\u7aef 2","text":""},{"location":"CV/SLAM14/#11_1","title":"11 \u56de\u73af\u68c0\u6d4b","text":""},{"location":"CV/SLAM14/#12_1","title":"12 \u5efa\u56fe","text":""},{"location":"CV/SLAM14/#13-slam","title":"13 \u5b9e\u8df5: \u8bbe\u8ba1 SLAM \u7cfb\u7edf","text":""},{"location":"CV/SLAM14/#14-slam","title":"14 SLAM: \u73b0\u5728\u4e0e\u672a\u6765","text":""},{"location":"Environment/","title":"Environmet Setup","text":""},{"location":"Environment/#environment","title":"Environment","text":"<p>Abstract</p> <p>\u672c\u90e8\u5206\u5185\u5bb9\uff08\u9664\u7279\u522b\u58f0\u660e\u5916\uff09\u91c7\u7528 \u7f72\u540d-\u975e\u5546\u4e1a\u6027\u4f7f\u7528-\u4fdd\u6301\u4e00\u81f4 4.0 \u56fd\u9645 (CC BY-NC-SA 4.0) \u8bb8\u53ef\u534f\u8bae\u8fdb\u884c\u8bb8\u53ef\u3002</p> envirtonment          <ul> <li> environment  227  1 mins              1734014421 </li> </ul> software          <ul> <li> obsidian  301  1 mins              1734012860 </li> </ul> Ubuntu          <ul> <li> Ubuntu  77  14  0 mins              1734012860 </li> </ul>"},{"location":"Environment/Ubuntu_setup/","title":"Ubuntu \u914d\u7f6e","text":""},{"location":"Environment/Ubuntu_setup/#ubuntu","title":"Ubuntu \u914d\u7f6e","text":"<p> \u7ea6 77 \u4e2a\u5b57  14 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <ul> <li>\u5728 Ubuntu \u5b89\u88c5\u914d\u7f6e Fcitx 5 \u4e2d\u6587\u8f93\u5165\u6cd5 - muzing\u7684\u6742\u8d27\u94fa</li> <li>fcitx5-rime \u6302\u63a5\u5c0f\u9e64\u97f3\u5f62 | rovo98's Blog</li> <li>zhuanlan.zhihu.com/p/660191327#:~:text=Tabby\uff08\u4ee5\u524d\u79f0\u4e3a</li> <li>Zsh \u5b89\u88c5\u4e0e\u914d\u7f6e\uff0c\u4f7f\u7528 Oh-My-Zsh \u7f8e\u5316\u7ec8\u7aef | Leehow\u7684\u5c0f\u7ad9</li> <li>zhuanlan.zhihu.com/p/658811059</li> <li>PKMer_TiddyWiki \u7b80\u6613\u6307\u5357</li> <li>Site Unreachable</li> <li>Jedsek | Blog</li> </ul> Bash<pre><code>visudo /etc/sudoers \n%sudo   ALL=(ALL:ALL) NOPASSWD: ALL\n</code></pre> Bash<pre><code>git clone https://github.com/zsh-users/zsh-syntax-highlighting.git ${ZSH_CUSTOM:-~/.oh-my-zsh/custom}/plugins/zsh-syntax-highlighting\n\ngit clone https://github.com/zsh-users/zsh-autosuggestions ${ZSH_CUSTOM:-~/.oh-my-zsh/custom}/plugins/zsh-autosuggestions\n\ngit clone git://github.com/joelthelion/autojump.git\ncd autojump\n./install.py\n\n[[ -s ~/.autojump/etc/profile.d/autojump.sh ]] &amp;&amp; . ~/.autojump/etc/profile.d/autojump.sh\n</code></pre> <ul> <li>\u622a\u56fe\u8f6f\u4ef6</li> </ul> Bash<pre><code>sudo apt-get install flameshot\nflameshot gui\n</code></pre> <ul> <li>\u5728 Ubuntu 22.04|20.04|18.04 \u4e0a\u5b89\u88c5 Node.js 20</li> </ul>"},{"location":"Environment/environment/","title":"Environment","text":"<ul> <li>\u5f00\u53d1\u73af\u5883\u6784\u5efa\u6307\u5357 </li> </ul> <p> \u7ea6 227 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <ul> <li>\u4ece\u96f6\u5f00\u59cb\u914d\u7f6e Windows \u2022 Arthals' ink </li> <li>\u4ece\u96f6\u5f00\u59cb\u914d\u7f6e Linux \u2022 Arthals' ink </li> <li>\u670d\u52a1\u5668\u73af\u5883\u914d\u7f6e Cheat Sheet | Yi Pan (Conless) </li> <li>clash </li> <li>powertoy </li> <li>gsudo </li> <li>git <ul> <li>GitHub - Wybxc/git-remake-guide: Git \u91cd\u5f00/\u91cd\u5b66\u6307\u5357 </li> </ul> </li> <li>picgo <ul> <li>picgo + github + obsidian </li> </ul> </li> <li>vscode<ul> <li>\u7cfb\u7edf + \u4ee3\u7801\u5b57\u4f53\u8bbe\u7f6e</li> <li>zhuanlan.zhihu.com/p/603687041#:~:text=clangd\u5b98\u65b9vs</li> <li>zhuanlan.zhihu.com/p/398790625#:~:text=\u5176\u4e2d VS Code</li> </ul> </li> <li>tools<ul> <li>GitHub - jenius-apps/ambie: An app that uses white noise, nature sounds, and focus features to boost your productivity. </li> </ul> </li> <li>clash <ul> <li>GitHub - Loyalsoldier/clash-rules: \ud83e\udd84\ufe0f\ud83c\udf83\ud83d\udc7b Clash Premium \u89c4\u5219\u96c6(RULE-SET)\uff0c\u517c\u5bb9 ClashX Pro\u3001Clash for Windows \u7b49\u57fa\u4e8e Clash Premium \u5185\u6838\u7684\u5ba2\u6237\u7aef\u3002 </li> <li>Site Unreachable </li> <li>\u7ffb\u5899 | Blog</li> <li>GitHub - vpncn/vpncn.github.io: 2024\u4e2d\u56fd\u7ffb\u5899\u8f6f\u4ef6VPN\u63a8\u8350\u4ee5\u53ca\u79d1\u5b66\u4e0a\u7f51\u907f\u5751\uff0c\u7a33\u5b9a\u597d\u7528\u3002\u5bf9\u6bd4SSR\u673a\u573a\u3001\u84dd\u706f\u3001V2ray\u3001\u8001\u738bVPN\u3001VPS\u642d\u5efa\u68af\u5b50\u7b49\u79d1\u5b66\u4e0a\u7f51\u4e0e\u7ffb\u5899\u8f6f\u4ef6\uff0c\u4e2d\u56fd\u6700\u65b0\u79d1\u5b66\u4e0a\u7f51\u7ffb\u5899\u68af\u5b50VPN\u4e0b\u8f7d\u63a8\u8350\uff0c\u8bbf\u95eeChatgpt\u3002 </li> </ul> </li> <li>Typora <ul> <li>GitHub - sylviaxgj/typora-forest-theme: another typora theme</li> <li>GitHub - HappySimple/Typora-theme-Happysimple: \u4e00\u6b3e\u81ea\u5236\u7684Markdown\u4e3b\u9898\uff01</li> </ul> </li> <li>github profiles <ul> <li>GitHub - anuraghazra/github-readme-stats:  Dynamically generated stats for your github readmes </li> </ul> </li> <li>github action </li> <li>gsudo</li> <li>openArk</li> </ul>"},{"location":"Environment/obsidian_setup/","title":"obsidian \u914d\u7f6e","text":""},{"location":"Environment/obsidian_setup/#obsidian","title":"obsidian \u914d\u7f6e","text":"<p> \u7ea6 301 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> Note <p>\u5982\u679c\u61d2\u5f97\u641e\uff0c\u53ef\u4ee5\u76f4\u63a5 clone \u6211\u7684\u914d\u7f6e\uff0c\u653e\u5230 .obsidian \u6587\u4ef6\u91cc\u3002 \u8fd9\u662f\u914d\u7f6e\u6587\u4ef6\u3002</p>"},{"location":"Environment/obsidian_setup/#1","title":"1 \u4f7f\u7528\u8bed\u8a00","text":"<ul> <li>\u4e3b\u8981\u662f Markdown</li> <li>\u914d\u7f6e\u63d2\u4ef6\u4e5f\u4f1a\u6d89\u53ca\u4e00\u4e9b javascript</li> </ul>"},{"location":"Environment/obsidian_setup/#2","title":"2 \u63d2\u4ef6","text":""},{"location":"Environment/obsidian_setup/#21-displaystyle-latex","title":"2.1 \\(\\displaystyle \\LaTeX\\)","text":"<ul> <li>Latex Suite</li> <li>LaTex-like Theorem &amp; Equation Referencer</li> <li>MathLinks  </li> </ul> <p>\u642d\u914d simpleTex \u4f7f\u7528</p>"},{"location":"Environment/obsidian_setup/#22","title":"2.2 \u7f16\u8f91\u589e\u5f3a","text":"<ul> <li>Easy Typing</li> <li>Linter</li> <li>Remember cursor position</li> <li>PDF++</li> <li>Code Styler</li> <li>Number Headings</li> <li>Outliner</li> <li>Completr</li> <li>Mind map</li> <li>Excalidraw</li> </ul>"},{"location":"Environment/obsidian_setup/#23","title":"2.3 \u56fe\u7247","text":"<ul> <li>Paste image rename</li> <li>Auto Link Title</li> <li>Image auto upload Plugin</li> </ul> <p>\u642d\u914d Picgo + GitHub \u4f7f\u7528</p>"},{"location":"Environment/obsidian_setup/#24","title":"2.4 \u540c\u6b65\u5907\u4efd","text":"<ul> <li>Git</li> <li>Remotely Save</li> </ul>"},{"location":"Environment/obsidian_setup/#25","title":"2.5 \u65e5\u7a0b","text":"<ul> <li>Calendar</li> <li>Periodic Notes</li> <li>Tasks Progress Bar</li> <li>Tasks</li> <li>Tasks Calendar Wrapper</li> </ul>"},{"location":"Environment/obsidian_setup/#26","title":"2.6 \u4ecd\u5728\u63a2\u7d22","text":"<ul> <li>Local REST API + \u7b80\u7ea6</li> <li>RSS Reader</li> </ul>"},{"location":"Environment/obsidian_setup/#_1","title":"\u6211\u7684\u6a21\u677f","text":"<p>\u9700\u8981\u5b89\u88c5 dataview + periodic notes \u63d2\u4ef6\u3002</p> <p>Note</p> <p>\u7531\u4e8e markdown \u4ee3\u7801\u5757\u5d4c\u5957\u4e0d\u592a\u884c\uff0c\u6240\u4ee5\u8981\u624b\u52a8\u4fee\u590d\u3002\u6ce8\u610f\u4fee\u590d '' \u5e26\u6765\u7684\u4ee3\u7801\u5757\u95ee\u9898</p> dailyweekly Note Text Only<pre><code># {{date:YYYY}}-{{date:WW}}-{{date:DD}}-{{date:HH}}-{{date:d}}\n\n## 1. \u8ba1\u5212\n\n### \ud83c\udf05 \u65e9\u6668\n\n#### \u8ba1\u5212 \n\n#### \u590d\u76d8 \n\n---\n\n### \u2600\ufe0f \u4e2d\u5348\n\n#### \u8ba1\u5212 \n\n#### \u590d\u76d8 \n\n---\n\n### \ud83c\udf07 \u665a\u4e0a\n\n#### \u8ba1\u5212\n\n#### \u590d\u76d8 \n\n---\n\n## 2. \u7b14\u8bb0\u7d22\u5f15\n\n``dataview\nLIST FROM \"\"\nWHERE file.cday = date(\"{{date:YYYY}}-{{date:MM}}-{{date:DD}}\")\n``\n\n---\n\n## 3. \u8d44\u6e90\u4e0e\u94fe\u63a5\n\n---\n\n## 4. \u672a\u5b8c\u6210\u7684\u4efb\u52a1\n\n``dataview\nTASK FROM \"dairy\"\nWHERE !completed\nAND file.cday &gt;= (this.file.cday - dur(7 days))\nAND file.cday &lt;= this.file.cday\nSORT file.cday DESC\n``\n\n---\n\n## 5. \u53cd\u601d\n</code></pre> Note Text Only<pre><code># {{date:YYYY}}-W{{date:WW}}-{{date:DD}}\n\n## 1. \u672c\u5468\u590d\u76d8\n\n---\n\n## 2. \u4e0b\u5468\u8ba1\u5212\n</code></pre>"},{"location":"Environment/obsidian_setup/#3","title":"3 \u76f8\u5173\u94fe\u63a5","text":"<ul> <li>PKMer_PKMer</li> <li>Obsidian \u4e2d\u6587\u8bba\u575b - Obsidian \u77e5\u8bc6\u7ba1\u7406 \u7b14\u8bb0</li> <li>Obsidian\u6587\u6863\u5496\u5561\u8c46\u7248 | Obsidian Docs by CoffeeBean</li> <li>zhuanlan.zhihu.com/p/619960525</li> </ul>"},{"location":"Robot/","title":"Robot","text":""},{"location":"Robot/#robot","title":"Robot","text":"<p>Abstract</p> <p>\u672c\u90e8\u5206\u5185\u5bb9\uff08\u9664\u7279\u522b\u58f0\u660e\u5916\uff09\u91c7\u7528 \u7f72\u540d-\u975e\u5546\u4e1a\u6027\u4f7f\u7528-\u4fdd\u6301\u4e00\u81f4 4.0 \u56fd\u9645 (CC BY-NC-SA 4.0) \u8bb8\u53ef\u534f\u8bae\u8fdb\u884c\u8bb8\u53ef\u3002</p> \u8f6f\u4ef6          <ul> <li> \u76f8\u673a\u6807\u5b9a  73  0 mins              1734024510 </li> <li> \u5361\u5c14\u66fc\u6ee4\u6ce2  193  115  2 mins              1734024510 </li> <li> PnP \u7b97\u6cd5  79  55  1 mins              1734012860 </li> </ul>"},{"location":"Robot/calibration/","title":"Calibration","text":"<p>Calibration</p> <p> \u7ea6 73 \u4e2a\u5b57  1 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4\u4e0d\u5230 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <ul> <li>GitHub - SHU-FLYMAN/CalibCamera: \u57fa\u4e8e\u5f20\u6b63\u53cb\u6807\u5b9a\u6cd5\u7684\u5355\u76ee\u76f8\u673a\u6807\u5b9a\u7406\u8bba\u5230\u5b9e\u8df5</li> <li>\u4e00\u6587\u5403\u900f\u76f8\u673a\u6807\u5b9a\uff08Camera calibration\uff09-CSDN\u535a\u5ba2</li> <li>\u6700\u8be6\u7ec6\u3001\u6700\u5b8c\u6574\u7684\u76f8\u673a\u6807\u5b9a\u8bb2\u89e3-CSDN\u535a\u5ba2</li> <li>\u76f8\u673a\u6807\u5b9a\uff08Camera calibration\uff09\u539f\u7406\u3001\u6b65\u9aa4_\u89c6\u89c9\u76f8\u673a \u793a\u6559\u76ee\u7684-CSDN\u535a\u5ba2 </li> </ul>"},{"location":"Robot/kalman/","title":"\u5361\u5c14\u66fc\u6ee4\u6ce2","text":""},{"location":"Robot/kalman/#_1","title":"\u5361\u5c14\u66fc\u6ee4\u6ce2","text":"<p> \u7ea6 193 \u4e2a\u5b57  115 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"Robot/kalman/#1-why","title":"1 Why","text":"<ul> <li>\u5dee\u5206<ul> <li>\u53d7\u566a\u58f0\u5e72\u6270\u5927</li> <li>\u6709\u5ef6\u8fdf</li> <li>\u901f\u5ea6\u4e0d\u8fde\u7eed\uff08\u4e0d\u80fd\u5f97\u5230\u77ac\u65f6\u901f\u5ea6\uff09</li> </ul> </li> </ul>"},{"location":"Robot/kalman/#2-how","title":"2 How","text":""},{"location":"Robot/kalman/#21","title":"2.1 \u5361\u5c14\u66fc\u6ee4\u6ce2","text":"<ul> <li>\u5408\u7406\u5730\u6839\u636e\u8bef\u5dee\u6765\u63a8\u5bfc\uff0c\u800c\u4e0d\u662f\u76f4\u63a5\u5ffd\u89c6\u5f71\u54cd\u6700\u7ec8\u91cf<ul> <li>\u65e0\u4eba\u9a7e\u9a76\u6280\u672f\u5165\u95e8\uff08\u5341\u4e09\uff09| \u624b\u628a\u624b\u6559\u4f60\u5199\u5361\u5c14\u66fc\u6ee4\u6ce2\u5668 - \u77e5\u4e4e </li> </ul> </li> </ul> \\[ \\begin{array}{|c|}\\hline\\textbf{Prediction}\\\\\\hline x^{'}=Ax+u\\\\P^{'}=APA^{T}+R\\\\\\hline\\textbf{Measurement update}\\\\\\hline y=z-Cx^{'}\\\\S=CPC^{T}+Q\\\\K=PC^{T}S^{-1}\\\\x=x^{'}+Ky\\\\P=(I-KC)P\\\\\\hline\\end{array} \\] C++<pre><code>#include &lt;iostream&gt;\n#include &lt;cstdio&gt;\n#include &lt;string&gt;\n#include &lt;vector&gt;\n#include &lt;ctime&gt;\n#include &lt;opencv2/core/core.hpp&gt;\n#include &lt;opencv2/highgui/highgui.hpp&gt;\n#include &lt;opencv2/imgproc/imgproc.hpp&gt;\n#include &lt;Eigen/Dense&gt;\n#include &lt;opencv2/core/eigen.hpp&gt;\nusing namespace std;\nusing namespace cv;\nusing namespace Eigen;\n\nint main() {\nsrand((unsigned int) time(NULL));\n// generate data with noise\nconst int N = 20;\nconst double k = 2.5;\nMatrix&lt;double, 1, N&gt; noise = Matrix&lt;double, 1, N&gt;::Random();\nMatrix&lt;double, 1, N&gt; data = Matrix&lt;double, 1, N&gt;::LinSpaced(0, k * (N - 1));\ndata += noise;\nstd::cout &lt;&lt; data &lt;&lt; std::endl;\n// calculate speed\nconst int Z_N = 1, X_N = 2;\nMatrix&lt;double, X_N, 1&gt; X;\nMatrix&lt;double, X_N, X_N&gt; A;\nMatrix&lt;double, X_N, X_N&gt; P;\nMatrix&lt;double, X_N, X_N&gt; R;\nMatrix&lt;double, X_N, Z_N&gt; K;\nMatrix&lt;double, Z_N, X_N&gt; C;\nMatrix&lt;double, Z_N, Z_N&gt; Q;\n\nX &lt;&lt; data[0], 0;\nA &lt;&lt; 1, 1, 0, 1;\nC &lt;&lt; 1, 0;\nR &lt;&lt; 2, 0, 0, 2;\nQ &lt;&lt; 10;\nfor (int i = 1; i &lt; N; i++) {\n    // \u66f4\u65b0\u9884\u6d4b\n    Matrix&lt;double, X_N, 1&gt; X_k = A * X;\n    P = A * P * A.transpose() + R;\n    // \u66f4\u65b0\u89c2\u6d4b\n    K = P * C.transpose() * (C * P * C.transpose() + Q).inverse();\n    Matrix&lt;double, Z_N, 1&gt; Z{data[i]};\n    X = X_k + K * (Z - C * X_k);\n    P = (Matrix&lt;double, X_N, X_N&gt;::Identity() - K * C) * P;\n    std::cout &lt;&lt; \"step \" &lt;&lt; i &lt;&lt; \": \" &lt;&lt; X[1] &lt;&lt; std::endl;\n}\nstd:cout &lt;&lt; \"final speed: \" &lt;&lt; X[1] &lt;&lt; std::endl;\nreturn 0;\n}\n</code></pre>"},{"location":"Robot/kalman/#22-ekf","title":"2.2 EKF \u7b97\u6cd5\u7684\u5b9e\u73b0","text":"C++<pre><code>#include &lt;ceres/jet.h&gt;\n#include &lt;Eigen/Dense&gt;\n\ntemplate&lt;int N_X, int N_Y&gt;\nclass AdaptiveEKF {\n    using MatrixXX = Eigen::Matrix&lt;double, N_X, N_X&gt;;\n    using MatrixYX = Eigen::Matrix&lt;double, N_Y, N_X&gt;;\n    using MatrixXY = Eigen::Matrix&lt;double, N_X, N_Y&gt;;\n    using MatrixYY = Eigen::Matrix&lt;double, N_Y, N_Y&gt;;\n    using VectorX = Eigen::Matrix&lt;double, N_X, 1&gt;;\n    using VectorY = Eigen::Matrix&lt;double, N_Y, 1&gt;;\n\npublic:\n    explicit AdaptiveEKF(const VectorX &amp;X0 = VectorX::Zero())\n            : Xe(X0), P(MatrixXX::Identity()), Q(MatrixXX::Identity()), R(MatrixYY::Identity()) {}\n\n    // \u9884\u6d4b\u51fd\u6570\n    template&lt;class Func&gt;\n    VectorX predict(Func &amp;&amp;func) {\n        calculateJacobian(Xe, func, Xp, F);\n        P = F * P * F.transpose() + Q;\n        return Xp;\n    }\n\n    // \u66f4\u65b0\u51fd\u6570\n    template&lt;class Func&gt;\n    VectorX update(Func &amp;&amp;func, const VectorY &amp;Y) {\n        calculateJacobian(Xp, func, Yp, H);\n        MatrixYY S = H * P * H.transpose() + R;  // \u521b\u65b0\u534f\u65b9\u5dee\n        K = P * H.transpose() * S.inverse();     // \u5361\u5c14\u66fc\u589e\u76ca\n        Xe = Xp + K * (Y - Yp);                  // \u66f4\u65b0\u72b6\u6001\u4f30\u8ba1\n        P = (MatrixXX::Identity() - K * H) * P;  // \u66f4\u65b0\u72b6\u6001\u534f\u65b9\u5dee\n        return Xe;\n    }\n\nprivate:\n    // \u8ba1\u7b97\u96c5\u514b\u6bd4\u77e9\u9635\u7684\u8f85\u52a9\u51fd\u6570\n    template&lt;class Func, int N_IN, int N_OUT&gt;\n    void calculateJacobian(const Eigen::Matrix&lt;double, N_IN, 1&gt; &amp;input, Func &amp;&amp;func, Eigen::Matrix&lt;double, N_OUT, 1&gt; &amp;output, Eigen::Matrix&lt;double, N_OUT, N_IN&gt; &amp;jacobian) {\n        ceres::Jet&lt;double, N_IN&gt; input_auto_jet[N_IN];\n        for (int i = 0; i &lt; N_IN; i++) {\n            input_auto_jet[i].a = input[i];\n            input_auto_jet[i].v[i] = 1;\n        }\n        ceres::Jet&lt;double, N_OUT&gt; output_auto_jet[N_OUT];\n        func(input_auto_jet, output_auto_jet);\n        for (int i = 0; i &lt; N_OUT; i++) {\n            output[i] = output_auto_jet[i].a;\n            jacobian.block(i, 0, 1, N_IN) = output_auto_jet[i].v.transpose();\n        }\n    }\n\npublic:\n    VectorX Xe;     // \u4f30\u8ba1\u72b6\u6001\u53d8\u91cf\n    VectorX Xp;     // \u9884\u6d4b\u72b6\u6001\u53d8\u91cf\n    MatrixXX F;     // \u9884\u6d4b\u96c5\u514b\u6bd4\u77e9\u9635\n    MatrixYX H;     // \u89c2\u6d4b\u96c5\u514b\u6bd4\u77e9\u9635\n    MatrixXX P;     // \u72b6\u6001\u534f\u65b9\u5dee\n    MatrixXX Q;     // \u9884\u6d4b\u8fc7\u7a0b\u534f\u65b9\u5dee\n    MatrixYY R;     // \u89c2\u6d4b\u8fc7\u7a0b\u534f\u65b9\u5dee\n    MatrixXY K;     // \u5361\u5c14\u66fc\u589e\u76ca\n    VectorY Yp;     // \u9884\u6d4b\u89c2\u6d4b\u91cf\n};\n</code></pre>"},{"location":"Robot/kalman/#23","title":"2.3 \u975e\u7ebf\u6027\u4f18\u5316","text":"<p>TODO</p>"},{"location":"Robot/kalman/#_2","title":"\u4e00\u4e9b\u8d44\u6599","text":"<ul> <li>zhuanlan.zhihu.com/p/45238681</li> <li>\u5361\u5c14\u66fc\u6ee4\u6ce2(Kalman Filter)\u6982\u5ff5\u4ecb\u7ecd\u53ca\u8be6\u7ec6\u516c\u5f0f\u63a8\u5bfc-CSDN\u535a\u5ba2</li> <li>\u8c03\u8282\u8bef\u5dee\u77e9\u9635\u7684\u5b9e\u9645\u610f\u4e49</li> <li>\u975e\u7ebf\u6027\u62d3\u5c55</li> <li>\u81ea\u9002\u5e94\u4f18\u5316</li> <li>\u4f5c\u4e1a\u4e2d\u6709\u4e00\u4e2a\u5929\u4f53\u8fd0\u52a8\u7684\u4f8b\u5b50</li> </ul>"},{"location":"Robot/pnp/","title":"pnp","text":""},{"location":"Robot/pnp/#pnp","title":"pnp","text":"<p> \u7ea6 79 \u4e2a\u5b57  55 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <ul> <li>\u5df2\u77e5<ul> <li>\u76ee\u6807\u7269\u4f53\u7279\u5b9a\u70b9\u7684\u50cf\u7d20\u5750\u6807</li> <li>\u76ee\u6807\u7269\u4f53\u7279\u5b9a\u70b9\u7684\u771f\u5b9e\u5c3a\u5bf8</li> <li>\u76f8\u673a\u5185\u53c2</li> </ul> </li> <li>\u6c42<ul> <li>\u76ee\u6807\u7269\u4f53\u5728\u76f8\u673a\u5750\u6807\u7cfb\u4e0b\u7684 6d pose</li> </ul> </li> </ul> <p>\u50cf\u7d20\u5750\u6807\u548c\u7269\u4f53\u5750\u6807\u7684\u5bf9\u70b9 \u4f46\u662f\u4e00\u822c\u53ea\u7528 t, \u56e0\u4e3a R \u7684\u7cbe\u5ea6\u4e0d\u591f\u9ad8 Fetching Title#g70i</p> <p>![[Pasted image 20241008201602.png]]</p> C++<pre><code>#include &lt;iostream&gt;\n#include &lt;opencv2/opencv.hpp&gt;\n#include &lt;opencv2/imgproc/imgproc.hpp&gt;\n#include &lt;opencv2/calib3d/calib3d.hpp&gt;\n#include &lt;opencv2/core/core.hpp&gt;\nusing namespace cv;\n\nbool findCorners(const cv::Mat &amp;src, std::vector&lt;cv::Point2f&gt; &amp;corners) {\n    std::vector&lt;cv::Point2f&gt; pts;\n    corners.clear();\n    bool flag = cv::findChessboardCorners(src, {9, 6}, pts);\n    if (!flag)\n        return false;\n    corners.push_back(pts[0]);\n    corners.push_back(pts[9 - 1]);\n    corners.push_back(pts[pts.size() - 9]);\n    corners.push_back(pts[pts.size() - 1]);\n    return true;\n}\n\nint main() {\n    cv::Mat src;\n    cv::Mat camera_matrix;\n    cv::Mat distort_matrix;\n    cv::FileStorage reader(PROJECT_DIR\"/parameter.txt\", cv::FileStorage::READ);\n    reader[\"C\"] &gt;&gt; camera_matrix;\n    reader[\"D\"] &gt;&gt; distort_matrix;\n\n    for (int i = 0; i &lt;= 40; i++) {\n        src = imread(std::__cxx11::to_string(i).append(\".jpg\"));\n        std::vector&lt;cv::Point2f&gt; corners;\n        bool flag = findCorners(src, corners);\n        imshow(\"Opencv Demo\", src);\n        cv::waitKey(100);\n        if (flag == false) {\n            std::cout &lt;&lt; \"failed to find all corners\\n\";\n            continue;\n        }\n        std::vector&lt;cv::Point3f&gt; dst;\n        dst.push_back({0, 0, 0});\n        dst.push_back({8 * 1, 0, 0});\n        dst.push_back({0, 5 * 1, 0});\n        dst.push_back({8 * 1, 5 * 1, 0});\n        cv::Mat rvec, tvec;\n        cv::solvePnP(dst, corners, camera_matrix, distort_matrix, rvec, tvec);\n        std::cout &lt;&lt; \"t:\" &lt;&lt; std::endl &lt;&lt; -tvec &lt;&lt; std::endl &lt;&lt; std::endl;\n        cv::Mat drawer;\n        drawer = src.clone();\n        for (int j = 0; j &lt; 4; j++)\n            cv::circle(drawer, corners[j], 2, {0, 255, 0}, 2);\n        cv::imshow(\"corners\", drawer);\n        cv::waitKey(5);\n    }\n    return 0;\n}\n</code></pre>"},{"location":"Summaries/","title":"Summaries","text":""},{"location":"Summaries/#summaries","title":"Summaries","text":"<p>Abstract</p> <p>\u672c\u90e8\u5206\u5185\u5bb9\uff08\u9664\u7279\u522b\u58f0\u660e\u5916\uff09\u91c7\u7528 \u7f72\u540d-\u975e\u5546\u4e1a\u6027\u4f7f\u7528-\u4fdd\u6301\u4e00\u81f4 4.0 \u56fd\u9645 (CC BY-NC-SA 4.0) \u8bb8\u53ef\u534f\u8bae\u8fdb\u884c\u8bb8\u53ef\u3002</p> \u5b66\u671f\u603b\u7ed3          <ul> <li> 2024 \u5e74 9 \u6708\u4efd\u81f3 12 \u6708\u4efd\u5b66\u671f\u603b\u7ed3\uff08\u5927\u4e00\uff09  1745  6 mins              1734506202 </li> </ul> 2024 \u5e74\u5468\u7ed3          <ul> <li> \u7b2c 50 \u5468  262  1 mins              1734243815 </li> <li> \u7b2c 44 \u5468  281  1 mins              1734024510 </li> <li> \u7b2c 45 \u5468  387  1 mins              1734024510 </li> <li> \u7b2c 46 \u5468  281  1 mins              1734024510 </li> <li> \u7b2c 47 \u5468  430  1 mins              1734024510 </li> <li> \u7b2c 48 \u5468  373  1 mins              1734024510 </li> <li> \u7b2c 49 \u5468  659  2 mins              1734024510 </li> </ul> \u9ad8\u4e2d\u5b66\u4e60\u7ecf\u9a8c          <ul> <li> \u6570\u5b66\u5b66\u4e60\u7ecf\u9a8c  757  3 mins              1734024510 </li> <li> \u82f1\u8bed\u5b66\u4e60\u7ecf\u9a8c  1397  5 mins              1734024510 </li> <li> \u6280\u672f\u5b66\u4e60\u7ecf\u9a8c  1324  4 mins              1734024510 </li> <li> \u7269\u7406\u5b66\u4e60\u7ecf\u9a8c  1581  5 mins              1734024510 </li> <li> \u5b66\u4e60\u8d44\u6e90  31  0 mins              1734024510 </li> </ul>"},{"location":"Summaries/2024/weekly/2024-W44-10/","title":"2024 \u5e74\u7b2c 44 \u5468\u5468\u7ed3","text":""},{"location":"Summaries/2024/weekly/2024-W44-10/#2024-44","title":"2024 \u5e74\u7b2c 44 \u5468\u5468\u7ed3","text":"<p> \u7ea6 281 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>10 \u6708 28 \u65e5 - 11 \u6708 03 \u65e5</p> <ul> <li>\u603b\u7ed3<ul> <li>CS231n<ul> <li>lecture \u542c\u4e86 01-04</li> <li>\u5b8c\u6210\u4e86 Assignment1</li> <li>\u505a\u4e86\u90e8\u5206\u7684\u7b14\u8bb0</li> <li>\u4e3b\u8981\u662f\u4e0d\u592a\u719f\u7ec3 numpy \u4e4b\u7c7b\u7684\u8fd0\u7528\uff0cvectorize \u8fd8\u662f\u6709\u70b9\u96be\u5ea6\u3002\u4e0d\u8fc7\u4e4b\u524d\u505a\u8fc7\u4e00\u4e9b EECS498 \u7684\u4f5c\u4e1a\u5c31\u8fd8\u597d\u3002</li> </ul> </li> <li>\u5468\u672b\u4e24\u5929\u6253\u4e86\u4e2a\u7269\u7406\u7684\u6bd4\u8d5b<ul> <li>\u719f\u7ec3\u4e86 LaTeX \u548c Python\uff0cdraw.io \u4f5c\u56fe</li> <li>\u8bba\u6587\u5728\u8fd9\u91cc</li> </ul> </li> </ul> </li> <li>\u8ba1\u5212<ul> <li>\u4e0b\u5468\u671f\u4e2d\u8003\uff0c\u590d\u4e60\u4e00\u4e0b</li> <li>RM \u63a5\u4e86\u4e2a\u5c0f\u4efb\u52a1\uff0c\u8981\u6c42\u8bc6\u522b\u89c6\u9891\u4e2d\u6bcf\u4e00\u5e27\u7684\u56fa\u5b9a\u4f4d\u7f6e\u7684\u4e00\u4e2a\u6570\u5b57\u5e76\u63d2\u503c\u8ba1\u7b97\u79ef\u5206<ul> <li>11 \u6708 4 \u65e5\u7528\u9884\u5904\u7406+tesseract OCR <ul> <li>\u8fd9\u91cc\u662f\u7b2c\u4e00\u7248\u634f</li> </ul> </li> <li>\u6253\u7b97\u6807\u8bb0\u4e00\u4e0b\u6570\u636e\uff0c\u8bad\u7ec3\u4e2a\u5c0f\u6a21\u578b\u8bd5\u8bd5\u3002<ul> <li>\u597d\u5427\uff0c\u5c1d\u8bd5\u4e86\u4e00\u4e0b\u6548\u679c\u5f88\u5dee\uff0c\u7528\u4e86\u4e2a\u5c0f\u7684 CNN \u5565\u90fd\u8bc6\u522b\u4e0d\u51fa\u6765</li> </ul> </li> </ul> </li> <li>RM \u88ab\u5206\u8fdb\u4e86\u81ea\u52a8\u5316\u5151\u77ff\u7684\u8f66\u7ec4\uff0c\u8981\u6c42\u5b9e\u73b0 6Dpose \u8bc6\u522b+\u673a\u68b0\u81c2\u8fd0\u52a8\u89c4\u5212<ul> <li>\u4e0b\u5468\u5185\u8981\u6c42\u63d0\u51fa\u5177\u4f53\u65b9\u6848\u5e76\u7acb\u9879<ul> <li>\u4ece\u6df1\u5ea6\u76f8\u673a\u548c\u6fc0\u5149\u76f8\u673a\u4e24\u4e2a\u65b9\u5411\u53bb\u627e\uff0c\u8981\u53bb\u770b\u770b\u8bba\u6587 </li> </ul> </li> </ul> </li> <li>\u7ee7\u7eed\u5b66\u4e60 CS231n<ul> <li>\u6253\u7b97\u5199\u5b8c Assignment 1 \u7684\u7b14\u8bb0\u548c\u9898\u89e3\u3002</li> <li>\u628a Assignment 2 \u505a\u5b8c</li> </ul> </li> </ul> </li> </ul>"},{"location":"Summaries/2024/weekly/2024-W45-11/","title":"2024 \u5e74\u7b2c 45 \u5468\u5468\u7ed3","text":""},{"location":"Summaries/2024/weekly/2024-W45-11/#2024-45","title":"2024 \u5e74\u7b2c 45 \u5468\u5468\u7ed3","text":"<p> \u7ea6 387 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>11 \u6708 04 \u65e5 - 11 \u6708 10 \u65e5</p> <ul> <li>\u603b\u7ed3<ul> <li>CS231n<ul> <li>\u590d\u4e60\u4e86\u4e00\u4e0b Assignment 1 \u7684\u4ee3\u7801\uff0c\u6574\u7406\u4e86\u4e00\u4e0b\u6846\u67b6</li> <li>\u53bb\u770b\u4e86\u4e00\u4e9b\u674e\u5b8f\u6bc5\u7684\u6df1\u5ea6\u5b66\u4e60\u6559\u7a0b</li> <li>\u56de\u770b\u4e86\u4e00\u4e0b Dive into Deep Learning\uff0c\u597d\u50cf\u4ee3\u7801\u8fd8\u662f\u8c03\u7528\u4e86\u5f88\u591a\u9ad8\u7ea7 api,\u6bd4\u5982 backforward \u5c31\u4e0d\u662f\u4ece\u96f6\u5b9e\u73b0\u7684\u3002</li> </ul> </li> <li>\u671f\u4e2d\u8003\u8bd5\u7ed3\u675f</li> <li>RM \u6821\u5185\u8d5b\u9020\u8f66\uff0c\u5b9e\u73b0\u5e95\u76d8\u8fd0\u52a8\uff08\u9ea6\u8f6e\u89e3\u7b97\u4ee3\u7801 + \u5e95\u76d8\u5b89\u88c5\uff09\u3002\u8fed\u4ee3\u4e86\u4e09\u7248\u4fdd\u9669\u6760\u3002\u901a\u8fc7\u4e2d\u671f\u68c0\u67e5\u3002\uff08\u8fd9\u4e2a\u771f\u5e9f\u65f6\u95f4\uff0c\u4e0d\u8fc7\u5b66\u4e86\u7535\u63a7\u548c solidwork\uff09</li> <li>RM \u9879\u76ee<ul> <li>\u641c\u7d22\u4e86 6Dof \u8bc6\u522b\u76f8\u5173\u6a21\u578b\u3002\u6392\u9664\u4e86\u6240\u6709\u57fa\u4e8e Transformer \u7684\u6a21\u578b\uff08\u53c2\u6570\u592a\u591a\uff0c\u7b97\u529b\u9700\u6c42\u5927\uff0c\u4e0d\u80fd\u5728 Orin NX \u4e0a\u5728 1s \u5185\u8dd1\u5b8c\uff09\u3002</li> <li>\u6700\u7ec8\u5927\u6982\u9009\u62e9\u7528 FFB6D pose\uff0c\u4ed6\u662f\u57fa\u4e8e\u674e\u98de\u98de\u4e4b\u524d\u7684 DenseFusion \u6539\u8fdb\u7684\u3002\u7528 RGB \u548c D \u7684\u4fe1\u606f\u8fdb\u884c\u7279\u5f81\u8bc6\u522b + \u878d\u5408 + \u6295\u7968\u7684\u6a21\u578b\u3002</li> <li>\u5927\u81f4\u5c1d\u8bd5\u90e8\u7f72\u4e86\u4e00\u4e0b\uff0c\u4f46\u662f\u73af\u5883\u51fa\u4e86\u5f88\u591a\u95ee\u9898\u3002</li> </ul> </li> <li>\u4e0a\u5468\u529f\u7387\u8bc6\u522b\u7684\u4efb\u52a1\u5b8c\u6210\uff0c\u6700\u7ec8\u7528\u4e86\u9884\u5904\u7406 + tesseract OCR\uff0c\u4f46\u662f\u5bf9\u7ea2\u8272\u6570\u5b57\u7684\u8bc6\u522b\u4e0d\u662f\u5f88\u597d\uff08\u56e0\u4e3a\u89c6\u9891\u672c\u8eab\u5c31\u5f88\u6a21\u7cca\uff09\u3002\u987a\u5e26\u53bb\u5b66\u4e86\u4e00\u4e0b PR \u3002<ul> <li>\u4ee3\u7801\u5728\u8fd9\u91cc</li> </ul> </li> </ul> </li> <li>\u8ba1\u5212<ul> <li>\u590d\u73b0 FFB6D pose \uff0c\u5236\u4f5c\u6570\u636e\u96c6\u3002<ul> <li>\u987a\u5e26\u5b66\u4e00\u4e0b docker \u5565\u7684\u3002</li> </ul> </li> <li>\u505a\u5b8c Assignment 2,\u4e0a\u5468\u7684 flag \u5012\u4e86 :( \uff08\u771f\u6ca1\u65f6\u95f4\u4e86\uff09</li> <li>RM \u6821\u5185\u8d5b\uff0c\u5468\u4e09\u4e4b\u524d\u753b\u5b8c\u56fe\uff0c\u7ed9\u5382\u5bb6\u52a0\u5de5\u3002\u5b9e\u73b0\u6361\u7403+\u6254\u7403\u7684\u529f\u80fd\u3002</li> <li>\u5b8c\u5584\u529f\u7387\u8bc6\u522b\u7684\u4efb\u52a1\uff0c\u4f20\u7edf\u65b9\u6cd5\u4f3c\u4e4e\u7cbe\u5ea6\u4e0d\u592a\u591f\u7528\u3002</li> <li>\u8c03\u6574\u4f5c\u606f\uff01</li> </ul> </li> </ul>"},{"location":"Summaries/2024/weekly/2024-W46-11/","title":"2024 \u5e74\u7b2c 46 \u5468\u5468\u7ed3","text":""},{"location":"Summaries/2024/weekly/2024-W46-11/#2024-46","title":"2024 \u5e74\u7b2c 46 \u5468\u5468\u7ed3","text":"<p> \u7ea6 281 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>11 \u6708 11 \u65e5 - 11 \u6708 17 \u65e5</p> <ul> <li>\u603b\u7ed3<ul> <li>CS231n<ul> <li>\u5199\u5b8c\u4e86 assignment 2\uff0c\u4e2d\u95f4\u9047\u5230\u4e86\u4e00\u4e9b\u95ee\u9898\uff0c\u53ef\u4ee5\u8003\u8651\u4e4b\u540e\u51fa\u4e2a\u8e29\u5751\u8bb0\u5f55\u3002</li> </ul> </li> <li>RM \u6821\u5185\u8d5b\u9020\u8f66<ul> <li>\u753b\u4e86\u4e00\u4e9b\u56fe\uff0c\u8fd8\u6ca1\u6765\u5f97\u53ca\u52a0\u5de5\uff0c\u961f\u53cb\u90fd\u5f00\u6446\u4e86\u3002</li> </ul> </li> <li>RM \u9879\u76ee<ul> <li>\u5b66\u4e60\u4e86 docker\uff0c\u603b\u7b97\u914d\u7f6e\u597d\u4e86 docker \u4e0a\u7684 FFB6D \u7684\u73af\u5883\uff0c\u8fd8\u662f\u8981\u719f\u6089\u4e00\u4e0b docker\u3002</li> <li>\u7528 realsense \u53bb\u505a\u4e86\u6a21\u578b\uff0c\u751f\u6210\u4e86 .ply \u70b9\u4e91\uff0c\u4f46\u662f\u597d\u50cf\u6548\u679c\u4e0d\u662f\u5f88\u597d\u3002</li> </ul> </li> <li>\u5199\u4e86\u4e2a\u6570\u636e\u6807\u6ce8\u7684 gui \u7a0b\u5e8f\uff0c\u611f\u89c9\u5199\u5f97\u5f88\u96be\u7528\u3002</li> <li>\u8c03\u6574\u4f5c\u606f\uff0c\u6bcf\u5929\u7761\u5f97\u4e45\u4e86\u4e00\u70b9\u634f\u3002</li> <li>\u8fed\u4ee3\u4e86\u81ea\u5df1\u7684\u5e38\u7528 prompt\uff0c\u63d0\u9ad8\u4e86 AI \u7684\u4f5c\u7528\u3002</li> <li>\u73a9\u4e86\u73a9 hugo\uff0c\u628a\u4e3b\u57df\u540d\u7ed9\u6362\u6389\u4e86</li> </ul> </li> <li>\u8ba1\u5212<ul> <li>\u590d\u73b0 FFB6D pose \uff0c\u5236\u4f5c\u6570\u636e\u96c6\u3002</li> <li>\u5199\u5b8c CS231n assignment 3\uff0c\u540c\u65f6\u8003\u8651\u5199\u51e0\u4e2a blog \u603b\u7ed3\u4e00\u4e0b\u3002</li> <li>\u7ee7\u7eed\u719f\u6089 docker \u7684\u64cd\u4f5c\uff0c\u628a\u6784\u5efa\u597d\u7684 image push \u5230 docker hub \u4e0a\u3002</li> <li>\u7ee7\u7eed\u5c1d\u8bd5\u4f7f\u7528 CNN \u6765\u8bc6\u522b\u6570\u5b57\uff0c\u5b8c\u5584\u9879\u76ee\uff08\u624b\u6807\u6570\u636e\u592a\u6076\u5fc3\u4e86\uff09</li> <li>\u5b8c\u5584\u5e38\u7528\u7684 prompt\u3002</li> <li>\u590d\u4e60\u4e00\u4e0b license \u548c commit \u89c4\u8303\uff0c\u611f\u89c9\u81ea\u5df1\u7684 github \u4ed3\u5e93\u592a\u4e71\u4e86\u3002</li> <li>\u7ee7\u7eed\u8c03\u6574\u4f5c\u606f\u3002</li> </ul> </li> </ul>"},{"location":"Summaries/2024/weekly/2024-W47-11/","title":"2024 \u5e74\u7b2c 47 \u5468\u5468\u7ed3","text":""},{"location":"Summaries/2024/weekly/2024-W47-11/#2024-47","title":"2024 \u5e74\u7b2c 47 \u5468\u5468\u7ed3","text":"<p> \u7ea6 430 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>11 \u6708 18 \u65e5 - 11 \u6708 24 \u65e5</p> <ul> <li>\u603b\u7ed3<ul> <li>CS231n<ul> <li>\u6ca1\u600e\u4e48\u63a8\u8fdb</li> </ul> </li> <li>RM \u6821\u5185\u8d5b<ul> <li>\u7ed9\u4e86\u961f\u53cb\u65b9\u6848\uff0c\u4f46\u662f\u6700\u540e\u6ca1\u6253\u5370\u51fa\u6765\u3002\u611f\u89c9\u81ea\u5df1\u5bf9 solidwork \u5b9e\u5728\u63d0\u4e0d\u8d77\u5174\u8da3\uff0c\u7528\u7684\u4e0d\u987a\u624b + \u8bbe\u8ba1\u672c\u8eab\u7684\u5f62\u5f0f\u548c\u5199\u4ee3\u7801\u5dee\u522b\u5f88\u5927\uff0c\u4e5f\u8bb8\u662f\u7ec3\u7684\u592a\u5c11\u4e86\uff0c\u6ca1\u6709\u8db3\u591f\u7684\u7ecf\u9a8c\u3002\u4f46\u662f\u5728\u8fd9\u65b9\u9762\u4f3c\u4e4e AI \u5e76\u4e0d\u80fd\u8d77\u5230\u5f88\u597d\u7684\u8f85\u52a9\u4f5c\u7528\u3002</li> <li>\u800c\u4e14\u611f\u89c9\u5bf9\u4e8e\u8fd9\u79cd\u56e2\u961f\u9879\u76ee\uff0c\u8fd8\u662f\u5f88\u9700\u8981\u9879\u76ee\u7ba1\u7406 / \u8fdb\u5ea6\u7ba1\u7406\uff0c\u4e0d\u7136\u5c31\u6709 95% \u7684\u6982\u7387\u4f1a\u5931\u63a7\u70c2\u5c3e\u3002\u7279\u522b\u662f\u5927\u5bb6\u90fd\u6ca1\u4ec0\u4e48\u7ecf\u9a8c\u7684\u65f6\u5019\uff0c\u53ea\u80fd\u63d0\u524d push \u6240\u6709\u4eba\uff0c\u505a\u51fa\u51e0\u7248\u65b9\u6848\u6765\uff0c\u7136\u540e\u624d\u80fd\u89c4\u5212\u540e\u7eed\u3002</li> <li>\u4ee5\u540e\u56e2\u961f\u9879\u76ee\u8fd8\u662f\u597d\u597d\u6311\u961f\u53cb\u5427\uff0c\u4e0d\u8981\u968f\u4fbf\u5c31\u53bb\u4e86\u3002\u5373\u4f7f\u505a\u597d\u4e86\u81ea\u5df1\u7684\u90e8\u5206\uff0c\u522b\u7684\u90e8\u5206\u5bc4\u4e86\u4e5f\u5f88\u96be\u641e\u3002\u8981\u4e48\u5c31\u81ea\u5df1\u5b8c\u5168\u80fd cover \u6574\u4e2a\u9879\u76ee\uff0c\u505a\u5168\u6808\uff0c\u6bd4\u5982 wordle_solver\uff0c\u4ece\u5934\u5230\u5c3e\u90fd\u662f\u6211\u4e00\u4e2a\u4eba\u5199\u7684\u3002</li> </ul> </li> <li>RM \u9879\u76ee<ul> <li>\u5b66\u4e60\u4e86 ssh \u7b49\uff0c\u5728\u53e6\u5916\u4e00\u53f0\u7535\u8111\u4e0a\u914d\u7f6e\u4e86\u73af\u5883\uff0c\u4e0b\u8f7d\u4e86\u6240\u9700\u8981\u7684\u6570\u636e\uff0c\u6784\u5efa\u4e86 docker\u3002</li> </ul> </li> <li>blog<ul> <li>\u6574\u7406\u4e86\u7b14\u8bb0\u672c\uff0c\u53d1\u5e03\u4e86\u51e0\u7bc7\u6587\u7ae0</li> </ul> </li> <li>\u5b66\u4e60\u4f7f\u7528\u4e86 reveal-md</li> <li>\u5199\u4e86\u4e00\u4e2a wordle_solver</li> <li>\u590d\u4e60\u4e86 license \u548c commit \u89c4\u8303\uff0c\u611f\u89c9\u786e\u5b9e\u6709\u70b9\u7e41\u7410\u3002</li> <li>\u840e\u9761\u7684\u4e00\u5468\uff0c\u6548\u7387\u4f4e\uff0c\u51e0\u4e4e\u4e00\u76f4\u90fd\u5728\u4f11\u606f\u3002</li> </ul> </li> <li>\u8ba1\u5212<ul> <li>\u901f\u901f\u63a8\u8fdb cs231n\uff0c\u4e89\u53d6\u4e0b\u4e2a\u661f\u671f\u5b66\u5b8c\u3002<ul> <li>\u6574\u7406\u7b54\u6848\uff0c\u53d1\u5e03\u3002</li> <li>\u6574\u7406\u7b14\u8bb0\uff0c\u53d1\u5e03\u3002</li> <li>\u7ed3\u5408 d2l \u7b49\u5176\u4ed6\u8d44\u6e90\uff0c\u603b\u7ed3\u5f52\u7eb3\u3002</li> </ul> </li> <li>\u51c6\u5907\u56db\u7ea7\u3002</li> <li>\u8dd1\u901a FFB6D \u7684\u4ee3\u7801\uff0c\u5e76\u8ba1\u5212\u9605\u8bfb\u5957\u81ea\u5df1\u7684\u6570\u636e\u3002</li> <li>\u53d1\u5e03\u4e00\u7bc7\u5982\u4f55\u5199 prompt \u7684\u6587\u7ae0\u3002</li> <li>\u5b8c\u5584 obsidian \u6a21\u677f\u3002</li> <li>\u5b66\u70b9 go\u3002</li> </ul> </li> </ul>"},{"location":"Summaries/2024/weekly/2024-W48-11/","title":"2024 \u5e74\u7b2c 48 \u5468\u5468\u7ed3","text":""},{"location":"Summaries/2024/weekly/2024-W48-11/#2024-48","title":"2024 \u5e74\u7b2c 48 \u5468\u5468\u7ed3","text":"<p> \u7ea6 373 \u4e2a\u5b57  1 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>11 \u6708 25 \u65e5 - 12 \u6708 01 \u65e5</p> <ul> <li>\u603b\u7ed3<ul> <li>CS231n<ul> <li>\u5199\u5b8c\u4e86 assignment 3 \u7684 LSTM,\u540e\u9762\u597d\u50cf\u8fd8\u6709 transformer \u5565\u7684\uff0c\u8fd8\u6ca1\u6765\u5f97\u53ca\u5199\u3002</li> <li>\u611f\u89c9\u8bfe\u7a0b\u89c6\u9891\u771f\u7684\u7b80\u7565\uff08d2l \u4e00\u4e2a\u6a21\u578b\u5c31\u4f1a\u62c9\u51fa\u6765\u8bb2\u4e00\u8282\uff09</li> </ul> </li> <li>\u8bfe\u5185<ul> <li>\u5468\u4e00\u5230\u5468\u4e09\u505a\u4e86\u4e00\u4e2a proj\u3002</li> <li>\u7ed3\u679c\u8fd8\u662f\u5f88\u597d\u7684\uff0c\u4e00\u4e2a\u4eba\u628a\u6240\u6709\u7684\u4ee3\u7801\u90fd\u5199\u4e86\uff0c\u6700\u540e\u5206\u6570\u4e5f\u662f\u62ff\u6ee1\u4e86\u3002</li> <li>\u987a\u4fbf\u5b66\u4e86 reveal-md \u548c beamer\u3002\u5199\u4e86\u4e2a\u5c0f\u5de5\u5177\uff0c\u7528\u6765\u90e8\u7f72 slides \u5230\u7f51\u9875\u4e0a\u3002\u540c\u65f6\u53ef\u4ee5\u5b9e\u73b0\u589e\u91cf\u6784\u5efa\u3002</li> <li>\u5b66\u4e86\u5982\u4f55\u4f7f\u7528 GitHub release\u3002</li> </ul> </li> <li>RM \u9879\u76ee<ul> <li>\u653e\u5f03\u4e86 docker\uff0c \u76f4\u63a5\u5728\u7535\u8111\u4e0a\u914d\u7f6e\u73af\u5883\u3002\u6210\u529f\u8dd1\u8d77\u6765\u4e86\u8bad\u7ec3\u3002\u514b\u670d\u4e86\u4e00\u4e9b\u68af\u5ea6\u6d88\u5931\u548c\u7206\u70b8\u7684\u95ee\u9898\uff0c\u8dd1\u4e86 8 \u4e2a epoch\uff0c\u4f3c\u4e4e\u6709\u4e00\u70b9\u8fc7\u62df\u5408\u3002</li> <li></li> </ul> </li> <li>\u8d76\u8fdb\u5ea6\uff0c\u5b66\u4e86\u671f\u4e2d\u8003\u4ee5\u540e\u6559\u7684\u6570\u5b66\u5316\u5b66\u8ba1\u7b97\u673a\u5185\u5bb9\uff0c\u8003\u5b8c\u4e86\u8ba1\u7b97\u673a\u7b2c\u4e8c\u6b21\u671f\u4e2d\u8003\u3002</li> <li>\u5199\u82f1\u8bed\u8bba\u6587\uff0c\u8fd1\u4ee3\u53f2\u8bfb\u4e66\u62a5\u544a\u3002\u8c46\u5305\u4f3c\u4e4e\u5728\u4e2d\u6587\u5199\u4f5c\u65b9\u9762\u6bd4\u8f83\u597d\uff0c\u751a\u81f3\u6709\u7c7b\u4f3c\u4e8e ChatGPT canvas \u4e00\u6837\u7684\u529f\u80fd\u3002</li> </ul> </li> <li>\u8ba1\u5212<ul> <li>\u63a8\u8fdb CS231n\uff0c\u5b66\u5f97\u771f\u6162\u554a\u3002</li> <li>\u51c6\u5907\u56db\u7ea7\u3002</li> <li>4090 \u8bad\u7ec3\u597d\u6162\uff0c\u6253\u7b97\u628a\u6a21\u578b\u5f04\u5230\u670d\u52a1\u5668\u4e0a\u7528 A100\u3002</li> <li>\u51c6\u5907\u671f\u672b\u590d\u4e60\u3002</li> <li>\u79d1\u7814\u6295\u5165\u65f6\u95f4\u592a\u5c11\u4e86\uff0c\u4f4d\u59ff\u8bc6\u522b\u505a\u7684\u5dee\u4e0d\u591a\u4e86\uff0c\u5c31\u591a\u628a\u65f6\u95f4\u653e\u5230\u79d1\u7814\u4e0a\u9762\u3002\u591a\u5b66\u70b9\u4e1c\u897f\uff0c\u8bf4\u5b9e\u8bdd\u611f\u89c9\u4e0b\u534a\u5b66\u671f\u660e\u663e\u6ca1\u6709\u5b66\u5230\u4ec0\u4e48\u4e1c\u897f\u3002</li> <li>\u8fd0\u52a8\uff0c\u89c4\u5f8b\u4f5c\u606f\uff0c\u51cf\u5c11\u523a\u6fc0\u6027\u5a31\u4e50\u3002</li> </ul> </li> </ul>"},{"location":"Summaries/2024/weekly/2024-W49-12/","title":"2024-W49-12","text":"<p> \u7ea6 671 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <code>#\u5468\u8bb0</code>","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W49-12/#2024-w49-12","title":"2024-W49-12","text":"","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W49-12/#plan","title":"PLAN","text":"<ul> <li> \u5199\u82f1\u8bed essay \uff08\u5b8c\u6210\u4e86\u4e00\u7248\u4ee5\u540e\u88ab\u63a8\u7ffb\u91cd\u6765\u4e86\u3002\uff09</li> <li> \u590d\u4e60\u7ea2\u8bfe</li> <li> \u590d\u4e60\u5316\u5b66</li> <li> \u590d\u4e60\u6570\u5b66</li> <li> \u590d\u4e60\u8ba1\u7b97\u673a</li> <li> \u505a\u5b8c CS 231n<ul> <li> \u505a + \u5199\u7b14\u8bb0</li> </ul> </li> <li> \u505a\u4e00\u4e9b cloudwego</li> <li> \u53bb\u770b\u770b Go + Gin + Gnorm</li> </ul>","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W49-12/#review","title":"REVIEW","text":"<ul> <li>\u914d\u7f6e\u597d\u4e86 obsidian \u6a21\u677f + \u4e00\u4e9b\u63d2\u4ef6</li> <li>\u5b66\u4e86 go \u7684\u57fa\u7840\u8bed\u6cd5\uff0c\u548c\u4e00\u4e9b\u5e76\u884c\u5904\u7406\u7684\u4e1c\u897f\u3002<ul> <li>\u5199\u4e86\u8fd9\u4e2a\u7684\u7b2c\u4e00\u90e8\u5206: 7\u5929\u7528Go\u4ece\u96f6\u5b9e\u73b0Web\u6846\u67b6Gee\u6559\u7a0b</li> </ul> </li> <li>\u5199\u4e86\u5b66\u672f\u5199\u4f5c\u7684\u8bba\u6587\uff0c\u6539\u4e86\u56db\u5929\uff0c\u7ed3\u679c\u88ab\u63a8\u7ffb\u4e86\u3002</li> <li>\u52aa\u529b\u8c03\u6574\u4f5c\u606f + \u65e5\u5e38\u751f\u6d3b\u89c4\u5f8b\uff0c\u7ec8\u4e8e\u5728\u4e00\u5468\u5feb\u8981\u7ed3\u675f\u7684\u65f6\u5019\uff08\u5468\u4e94\uff0c\u5468\u516d\uff09\u627e\u56de\u4e86\u4e00\u70b9\u611f\u89c9\u3002\u4f3c\u4e4e\u8fd8\u662f\u53bb\u56fe\u4e66\u9986\u9002\u5408\u6211\u3002</li> <li>\u5199\u4e86\u4e00\u4e9b CS231n \u7684\u7b14\u8bb0\uff0c\u4f46\u662f\u4ecd\u7136\u6ca1\u6709\u505a\u5b8c\uff0c\u671f\u672b\u5468\u4e86\u66f4\u6ca1\u65f6\u95f4\u4e86\u3002 : (</li> <li>\u4e0b\u5468\u53ef\u80fd\u5c31\u662f\u590d\u4e60\u671f\u672b\u8003\u8bd5\u4e86\u3002</li> </ul>","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W49-12/#thoughts","title":"THOUGHTS","text":"<ul> <li>\u4e00\u4e2a\u5b66\u671f\u9a6c\u4e0a\u5c31\u8981\u7ed3\u675f\u4e86\uff0c\u4f46\u662f\u4f3c\u4e4e\u671f\u672b\u8003\u5df2\u7ed3\u675f RM \u5c31\u8981\u96c6\u8bad\uff0c\u7136\u540e\u5bd2\u5047\u4f1a\u88ab\u538b\u7f29\u5230 1 \u4e2a\u6708\uff08\u539f\u5148\u662f\u4e24\u4e2a\u6708\uff09\u3002</li> <li>\u611f\u89c9\u4e0b\u534a\u4e2a\u5b66\u671f\u8fd8\u662f\u5f88\u6446\u70c2<ul> <li>\u7b2c\u4e00\u4e2a\u662f\u6ca1\u6709\u627e\u5230\u81ea\u5df1\u7684\u751f\u6d3b\u8282\u594f\uff0c\u5435\u67b6\uff0c\u597d\u51e0\u4e2a\u65b9\u9762\u7684 ddl \u4e00\u8d77\u6765\uff0c\u5468\u672b\u7684\u4e0d\u5408\u7406\u4f11\u606f\uff0c\u5e73\u65f6\u7684\u4e0d\u6b63\u5e38\u4f5c\u606f\u3002</li> <li>\u7b2c\u4e8c\u4e2a\u662f\u611f\u89c9\u524d\u9014\u8ff7\u832b\uff0c\u7279\u522b\u662f\u6765\u5bc6\u9662\u4ee5\u540e\uff0c\u611f\u89c9\u8eab\u8fb9\u7684\u4eba\u90fd\u5728\u5377\u7ee9\u70b9\uff0c\u7136\u540e\u81ea\u5df1\u4e0d\u5f97\u4e0d\u4e5f\u8bdd\u5f88\u591a\u65f6\u95f4\u5728\u4e0a\u9762\u3002\u5b66\u957f\u91cc\u9762\u4f3c\u4e4e\u4e5f\u5f88\u5c11\u6709\u4f20\u7edf CS \u9053\u8def\u7684\uff0c\u4e0d\u77e5\u9053\u662f\u4e3a\u4ec0\u4e48\u3002</li> </ul> </li> <li>\u5176\u5b9e\u6211\u8fd8\u662f\u5f88\u559c\u6b22\u5b66\u4e1c\u897f\u7684\uff0c\u6216\u8005\u8bf4\u73a9\u8ba1\u7b97\u673a\u7684\u3002\u5f88\u559c\u6b22\u6a21\u578b\u771f\u7684\u8dd1\u51fa\u7ed3\u679c\u4e86\uff0c\u81ea\u5df1\u642d\u5efa\u7684\u5de5\u4f5c\u6d41\u771f\u7684\u6709\u6548\u4e86\uff0c\u81ea\u5df1\u7684\u60f3\u6cd5\u771f\u7684\u901a\u8fc7\u7a0b\u5e8f\u5b9e\u73b0\u4e86\u7684\u611f\u89c9\u3002\u559c\u6b22\u80fd\u591f\u7acb\u5373\u4f53\u73b0\u5728\u773c\u524d\u7684\u4e1c\u897f\uff0c\u4ec0\u4e48 web \u642d\u5efa\uff0c\u7b14\u8bb0\u8f6f\u4ef6\u6216\u8005\u8bad\u7ec3\u6a21\u578b\uff0c\u53ef\u89c6\u5316\uff0c\u5c1d\u8bd5\u4e0d\u540c\u7684 slides\uff0c\u7528 \\(\\displaystyle \\LaTeX\\) \u5199\u4f5c\u4e1a\u3002\u4f46\u4e00\u4e9b\u65b9\u9762\uff0c\u6211\u53c8\u504f\u5411\u4e8e\u7406\u8bba\u5316\u7684\uff0c\u5f62\u5f0f\u5316\u7684\u4e1c\u897f\uff0c\u6bd4\u5982\u5b66\u674e\u7fa4\u674e\u4ee3\u6570\uff0c\u5b66\u56db\u5143\u6570\uff0c\u63a7\u5236\u7406\u8bba\u4e4b\u7c7b\u7684\u4e1c\u897f\u3002</li> <li>\u53ea\u4e0d\u8fc7\u8fd9\u534a\u4e2a\u5b66\u671f\u771f\u7684\u6ca1\u6709 balance \u597d\u5f88\u591a\u4e1c\u897f\uff0c\u5e38\u5e38\u5fc3\u529b\u6194\u60b4\uff0c\u5b8c\u7f8e\u4e3b\u4e49\u53c8\u8ba9\u81ea\u5df1\u62d6\u5ef6\uff0c\u9003\u907f\u3002\u6211\u8086\u610f\u7684\u5f52\u548e\u4e3a\u6ca1\u6709\u670b\u53cb\uff0c\u4e0d\u9002\u5e94\uff0c\u5b9e\u9645\u4e0a\u4e5f\u662f\u5728\u9003\u907f\u3002\u751a\u81f3\u4e00\u6bb5\u65f6\u95f4\u65e5\u8bb0/TODO list \u90fd\u6ca1\u6709\u5199\uff0c\u5f7b\u5e95\u7684\u5f00\u6446\u4e86\uff0c\u4e0d\u8fc7\u8fd8\u597d\u73b0\u5728\u770b\u8d77\u6765\u5728\u8d70\u4e0a\u5761\u8def\u4e86\u3002</li> <li>\u4ece\u73b0\u5728\u5f00\u59cb\u638c\u63a7\u751f\u6d3b\u5427\uff0c\u4e0d\u8981\u518d\u6d3b\u7684\u4e91\u91cc\u96fe\u91cc\u4e86\u3002</li> </ul>","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W50-12/","title":"2024-W50-09","text":"<p> \u7ea6 274 \u4e2a\u5b57  1 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <code>#\u5468\u8bb0</code>","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W50-12/#2024-w50-09","title":"2024-W50-09","text":"","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W50-12/#review","title":"Review","text":"<ul> <li>\u8bfe\u5185<ul> <li> \u8003\u56db\u7ea7</li> <li> \u5199\u5b66\u672f\u5199\u4f5c\u7684\u8bba\u6587</li> <li> \u590d\u4e60\u5316\u5b66\uff0c\u6570\u5b66\uff0c\u8ba1\u7b97\u673a\uff0c\u8fd1\u4ee3\u53f2</li> </ul> </li> <li>RM<ul> <li> \u8dd1\u8bad\u7ec3\uff08\u94fe\u63a5\u6574\u7406\u6570\u636e\uff0c\u4f46\u662f\u6a21\u578b\u4e0d\u6536\u655b\u3002\u5728\u5c0f\u8303\u56f4\u7684\u6570\u636e\u96c6\u4e0a\u5b9e\u9a8c\u540e\u4ecd\u7136\u4e0d\u6536\u655b\uff0c\u6000\u7591\u4e00\u5b9a\u8981\u4f7f\u7528 raster_triangle\uff09\u3002\u719f\u6089\u4e86 linemod \u6570\u636e\u96c6\u7684\u7ec4\u6210\uff0c\u5e76\u4e86\u89e3\u4e86\u5982\u4f55\u7528\u81ea\u5df1\u7684\u6570\u636e\u6765\u8bad\u7ec3\u6a21\u578b\u3002</li> </ul> </li> <li>Obsidian<ul> <li> \u7b2c\u4e00\u6b21\u7528 Day Planner \u6765\u8bb0\u5f55\u81ea\u5df1\u7684\u751f\u6d3b\uff0c\u5e76\u5c1d\u8bd5\u6709\u7a7a\u5c31\u53bb\u81ea\u4e60\u5ba4\uff0c\u6548\u7387\u5f97\u5230\u7684\u5f88\u5927\u7684\u63d0\u9ad8\u3002</li> </ul> </li> </ul>","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W50-12/#next-week-plan","title":"Next Week Plan","text":"<ul> <li> \u671f\u672b\u8003\u8bd5</li> <li> \u5236\u4f5c\u5bd2\u5047\u8ba1\u5212</li> <li> \u5236\u4f5c\u8fd4\u6821\u5ba3\u8bb2\u7684\u8d44\u6599</li> </ul>","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W50-12/#time-line","title":"Time Line","text":"","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W50-12/#thoughts","title":"THOUGHTS","text":"<ul> <li>\u6253\u7b97\u5b66\u516c\u5f00\u8bfe\uff0c\u5e76\u4e14\u591a\u8ddf\u522b\u4eba\u4ea4\u6d41\uff0c\u6709\u8f93\u5165\u66f4\u9700\u8981\u6709\u8f93\u51fa\u3002</li> <li>\u5f00\u53d1\u793e\u4ea4\u5a92\u4f53\uff0c\u53d1\u5e03\u4e1c\u897f\u3002</li> <li>\u89c4\u5f8b\u4f5c\u606f\uff0c\u611f\u89c9\u4e00\u5929\u9700\u8981 8 \u4e2a\u5c0f\u65f6\u7761\u7720 + 1 \u4e2a\u5c0f\u65f6\u8fd0\u52a8\uff0c\u540c\u65f6\u8981\u6709\u65f6\u95f4\u6765\u53cd\u601d\u3002<ul> <li>\u5f62\u5f0f\u5316\u7684\u64cd\u4f5c\u53ef\u4ee5\u8ba9\u4eba\u66f4\u597d\u7684\u8fdb\u5165\u72b6\u6001\u3002</li> </ul> </li> </ul>","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/202409-10/","title":"2024 \u5e74 9 \u6708 10 \u6708\u603b\u7ed3","text":""},{"location":"Summaries/2024/weekly/202409-10/#2024-9-10","title":"2024 \u5e74 9 \u6708 10 \u6708\u603b\u7ed3","text":"<p> \u7ea6 388 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>9 \u6708 15 \u65e5 - 10 \u6708 15 \u65e5</p> <ul> <li>\u8ba1\u7b97\u673a<ul> <li>\u52a0\u5165\u4e86 RoboMaster \u89c6\u89c9\u90e8<ul> <li>\u4f20\u7edf\u8ba1\u7b97\u673a\u89c6\u89c9<ul> <li>opencv</li> <li>\u65cb\u8f6c\u7684\u8868\u793a</li> <li>\u590d\u4e60\u4e86\u519b\u8bad\u65f6\u770b\u7684 slam14 \u8bb2</li> </ul> </li> <li>Kalman Filter</li> <li>ROS2<ul> <li>\u4e3b\u8981\u901a\u8fc7\u5b98\u65b9\u6587\u6863\u548c\u52a8\u624b\u5b66ROS2 \u5b66\u4e86\u4e00\u4e0b</li> </ul> </li> </ul> </li> <li>\u901a\u8fc7 3b1b \u7684\u7cfb\u5217\u89c6\u9891\u4e86\u89e3\u4e86\u795e\u7ecf\u7f51\u7edc</li> <li>pytorch<ul> <li>\u901a\u8fc7\u5b98\u7f51\u7684\u6559\u7a0b\u901f\u6210\u4e86\u4e00\u4e0b</li> </ul> </li> <li>Dive into Deep Learning<ul> <li>\u7ebf\u6027\u795e\u7ecf\u7f51\u7edc<ul> <li>softmax \u56de\u5f52</li> </ul> </li> <li>\u591a\u5c42\u611f\u77e5\u673a<ul> <li>\u6b20\u62df\u5408\u4e0e\u8fc7\u62df\u5408<ul> <li>\u6743\u91cd\u8870\u51cf</li> <li>\u6682\u9000\u6cd5</li> </ul> </li> <li>\u6570\u503c\u7a33\u5b9a\u6027<ul> <li>\u68af\u5ea6\u6d88\u5931</li> <li>\u68af\u5ea6\u7206\u7167</li> </ul> </li> <li>\u504f\u79fb\u5206\u5e03</li> </ul> </li> <li>\u6df1\u5ea6\u5b66\u4e60\u7684\u642d\u5efa</li> <li>\u5377\u79ef\u795e\u7ecf\u7f51\u7edc</li> <li>\u73b0\u4ee3\u5377\u79ef\u795e\u7ecf\u7f51\u7edc</li> </ul> </li> <li>CMU 15-213<ul> <li>\u5b8c\u6210\u4e86 datalab, bomblab, attacklab</li> </ul> </li> <li>Matlab \u57fa\u672c\u8bed\u6cd5<ul> <li>\u73a9\u4e86\u73a9\u76f8\u673a\u6807\u5b9a</li> </ul> </li> <li>Tools<ul> <li>\u4f5c\u4e1a\u8981\u6c42\uff0c\u6253\u4e86 20 \u9875 \\(\\displaystyle \\LaTeX\\) \u6587\u6863\uff0c\u6839\u636e elegentbook \u4fee\u6539\u4e86\u81ea\u5df1\u7684\u6a21\u677f,\u5b66\u4e60\u4e86 Tikz</li> <li>\u5b66\u4e86 Typst \u7684\u57fa\u672c\u8bed\u6cd5\uff0c\u4f46\u662f\u611f\u89c9\u81ea\u5df1\u76ee\u524d\u61d2\u5f97\u6362</li> <li>\u91cd\u88c5\u4e86\u7535\u8111<ul> <li>\u53f0\u5f0f<ul> <li>Ubuntu 22.04\uff08\u4e3b\u529b\u673a\uff09 + win11</li> </ul> </li> <li>\u7b14\u8bb0\u672c<ul> <li>Ubuntu 24.04 \uff08\u4e0d\u5c0f\u5fc3\u5347\u7ea7\u4e86\uff09+ win11</li> </ul> </li> </ul> </li> <li>\u719f\u7ec3\u4e86 claude + kimi \u7684\u4f7f\u7528<ul> <li>\u7533\u8bf7\u8fc7\u4e86 GitHub edcation\uff0c\u4e8e\u662f\u6709\u4e86 copilot \u7528\u3002</li> </ul> </li> <li>\u88c5\u4fee\u4e86\u4e00\u4e0b blog<ul> <li>\u770b\u4e86\u4e00\u904d Mkdocs \u548c Material for Mkdocs \u7684\u6587\u6863</li> </ul> </li> <li>\u914d\u7f6e\u4e86\u5de5\u5b66\u6905\uff0c\u597d\u7528\uff01</li> <li>\u5b66\u4e86 slidev<ul> <li>\u9644\u5e26\u53bb\u5b66\u4e86\u4e00\u4e0b mermaid \uff08\u611f\u89c9\u4e0d\u662f\u5f88\u597d\u7528\uff09</li> </ul> </li> </ul> </li> <li>\u5199\u4e86\u4e00\u4e2a\u5728 mkdocs \u4e0a\u90e8\u7f72 obsidian \u65f6\u5904\u7406\u94fe\u63a5\u7684\u5c0f\u63d2\u4ef6\uff08\u672a\u5b8c\u5168\u53d1\u5e03\uff09  </li> </ul> </li> <li>\u603b\u7ed3<ul> <li>\u603b\u7684\u611f\u53d7\u4e0b\u6765\uff0c\u81ea\u5df1\u4ee5\u540e\u8fd8\u662f\u6bd4\u8f83\u503e\u5411\u4e8e\u5b66 AI \u800c\u4e0d\u662f system \uff1f\u53c8\u60f3\u8981\u51fa\u56fd\u4f53\u9a8c\u4e00\u4e0b\uff08\u8bfb\u7855\u58eb\uff0c\u6216\u8005\u76f4\u535a\uff1f\uff09</li> </ul> </li> </ul>"},{"location":"Summaries/2024/weekly/2024summer_vacation/","title":"2024\u5e74\u9ad8\u4e09-\u5927\u4e00\u6691\u5047\u603b\u7ed3","text":""},{"location":"Summaries/2024/weekly/2024summer_vacation/#2024-","title":"2024\u5e74\u9ad8\u4e09-\u5927\u4e00\u6691\u5047\u603b\u7ed3","text":"<p> \u7ea6 518 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>\u6211\u7684\u6691\u5047\u5927\u6982\u662f\u4ece 24.7.10 \u5f00\u59cb\u7684\uff0c\u5230\u90a3\u65f6\u624d\u5c18\u57c3\u843d\u5b9a\u3002\u4f46\u53c8\u6765\u56de\u6447\u6446\uff0c\u60f3\u7740\u672a\u6765\u7684\u51fa\u8def\uff08\u51fa\u56fd\uff1f\u4fdd\u7814\uff1f\u5de5\u4f5c\uff1f\u8f6c\u4e13\u4e1a\uff1f\uff09\u3002\u6240\u4ee5\u5927\u6982\u5230 8 \u6708\u624d\u5f00\u59cb\u5b66\u4e60\u3002</p> <ul> <li>\u8ba1\u7b97\u673a<ul> <li>crash course computer \u770b\u4e86\u524d 20 \u8bb2\uff0c\u540e\u6765\u56e0\u4e3a\u61d2\u5f97\u770b\u4e86\u5c31\u6446\u70c2\u4e86</li> <li>cs 61 A<ul> <li>\u770b\u4e86\u524d 10 \u8bb2\u7684 lecture\uff0c\u4f46\u662f\u6ca1\u505a\u7b14\u8bb0</li> <li>\u770b\u4e86 composing programs \u524d\u4e09\u7ae0</li> <li>\u505a\u5b8c\u4e86 4 \u4e2a proj\uff0c\u4f46\u662f\u6ca1\u6709\u505a hw \u548c lab</li> </ul> </li> <li>cs 61 C<ul> <li>\u770b\u4e86\u524d 10 \u8bb2\u7684 slide</li> <li>\u505a\u4e86\u524d\u4e24\u4e2a proj \u548c\u524d\u516d\u4e2a lab</li> <li>\u770b\u8ba1\u7b97\u673a\u7ec4\u6210\u4e0e\u8bbe\u8ba1\u786c\u4ef6\u8f6f\u4ef6\u63a5\u53e3\u524d\u4e24\u7ae0</li> </ul> </li> <li>csapp<ul> <li>\u4e66\u770b\u4e86\u524d\u4e09\u7ae0</li> <li>\u4e5d\u66f2\u9611\u5e72\u770b\u4e86\u524d 4 \u7ae0</li> </ul> </li> <li>Dive into Deep Learning<ul> <li>\u770b\u4e86\u524d\u4e24\u7ae0\u5e76\u505a\u4e86\u7b14\u8bb0\uff0c\u4f46\u611f\u89c9\u4e00\u4e0b\u5b50\u8df3\u8fc7\u592a\u591a\u524d\u7f6e\u77e5\u8bc6\u5f88\u96be\u611f\u53d7\u5230\u7f8e\u611f\u4fbf\u5148\u653e\u653e\u3002</li> </ul> </li> <li>games 101<ul> <li>\u51e0\u4e4e\u770b\u5b8c\u4e86\u6240\u6709\u7684 lecture (\u4f46\u662f\u540e\u9762\u51e0\u8bb2\u4e0d\u662f\u5f88\u8ba4\u771f)\uff0c\u4f46\u662f\u6ca1\u6709\u505a\u7b14\u8bb0</li> </ul> </li> <li>\u4ee3\u7801\u968f\u60f3\u5f55<ul> <li>\u505a\u5230\u56de\u6eaf\u4e86\uff0c\u4f46\u662f\u6253\u7b97\u4e4b\u540e\u4e0d\u4f1a\u5f88\u7ecf\u5e38\u505a\uff08\u7b49\u5230\u8981\u7528\u4e86\u518d\u8bf4\uff09</li> </ul> </li> <li>\u7528 mkdocs \u642d\u5efa\u4e86\u81ea\u5df1\u7684 blog</li> <li>C++<ul> <li>\u770b\u4e86\u83dc\u9e1f\u6559\u7a0b\u4e0a\u7684\u76f8\u5173\u5185\u5bb9\uff0c\u6ca1\u505a\u7b14\u8bb0</li> <li>\u770b\u4e86\u6d59\u5927\u7684 C++\u8bfe\uff0c\u6ca1\u505a\u7b14\u8bb0\uff0c\u4e5f\u6ca1\u770b\u5b8c\uff08\uff09</li> <li>\u770b\u4e86 accelerated C++\uff0c\u505a\u4e86\u7b14\u8bb0</li> </ul> </li> <li>\u770b\u4e86\u6d59\u5927\u7684\u5b9e\u7528\u6280\u80fd\u62fe\u9057<ul> <li>\u590d\u4e60\u4e86 Markdown \u548c Latex \u8bed\u6cd5\uff0c\u5b66\u4e60\u4e86\u5982\u4f55\u4f7f\u7528 git\uff0c\u5b66\u4e60\u4e86\u6700\u57fa\u7840\u7684 shell\uff0cvim\u3002</li> </ul> </li> <li>\u89c6\u89c9 slam \u5341\u56db\u8bb2<ul> <li>\u770b\u5b8c\u4e86\u524d 7 \u8bb2\uff08\u5373\u7406\u8bba\u90e8\u5206\uff09\uff0c\u505a\u4e86\u7b14\u8bb0\uff0c\u4f46\u662f\u6ca1\u6709\u8dd1\u4ee3\u7801 \uff08\u73af\u5883\u592a\u96be\u914d\u4e86\uff09</li> </ul> </li> <li>\u914d\u7f6e\u73af\u5883<ul> <li>wsl 2 , git\uff0cvmware\uff0cvscode</li> <li>\u914d\u7f6e\u4e86 obsidian\uff0c\u88c5\u4e86\u597d\u591a\u63d2\u4ef6\uff0c\u73b0\u5728\u7528\u8d77\u6765\u662f\u5f88\u8212\u670d\u4e86</li> </ul> </li> </ul> </li> <li>\u8fd0\u52a8<ul> <li>\u6bcf\u5929\u505a\u505a\u4fef\u5367\u6491\uff0c\u611f\u89c9\u8fd8\u4e0d\u9519</li> <li>\u5927\u6982 7 \u6708\u4efd\u7684\u65f6\u5019\u6bcf\u5929\u4e0b\u5348\u4f1a\u51fa\u53bb\u9a91\u8f66\uff08city cycling?\uff09</li> </ul> </li> <li>\u5176\u4ed6<ul> <li>\u5bb6\u6559</li> <li>\u5b66\u4e86\u9a7e\u7167</li> <li>\u4e70\u4e86\u4e00\u4e2a\u952e\u76d8\u548c\u663e\u793a\u5668, \u91cd\u88c5\u4e86\u7535\u8111</li> <li>\u548c\u670b\u53cb\u65c5\u6e38\uff0c\u53bb\u6cc9\u5dde+\u798f\u5dde</li> <li>\u7ed9\u9ad8\u4e2d\u7684\u5b66\u5f1f\u5b66\u59b9\u5199\u4e86\u7ecf\u9a8c\u5206\u4eab\uff08\u6570\u5b66+\u82f1\u8bed+\u7269\u7406+\u6280\u672f\uff09</li> <li>\u770b\u4e86\u4e0d\u5c11\u7535\u5f71</li> </ul> </li> </ul>"},{"location":"Summaries/High%20School/Resource/","title":"Resource","text":"<p>\u4e00\u4e9b\u8d44\u6e90\u94fe\u63a5\uff0c\u53ef\u4ee5\u53c2\u8003\u7740\u770b:</p> <p> \u7ea6 31 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4\u4e0d\u5230 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <ul> <li>wjyyy \u9ad8\u4e09\u751f\u5b58\u6307\u5357</li> <li>IAI\u7ecf\u9a8c\u5206\u4eab</li> </ul> <p>\u6570\u5b66:</p> <ul> <li>\u9009\u62e9\u9898\u538b\u8f74</li> </ul>"},{"location":"Summaries/High%20School/eng_fht/","title":"\u82f1\u8bed\u7ecf\u9a8c\u5206\u4eab","text":""},{"location":"Summaries/High%20School/eng_fht/#_1","title":"\u82f1\u8bed\u7ecf\u9a8c\u5206\u4eab","text":"<p> \u7ea6 1397 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 7 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>\u80cc\u666f:2024\u5c4a\u9996\u8003136\uff08\u524d\u9762\u62635\uff0c\u4f5c\u6587\u62639\uff09 -&gt; \u9ad8\u8003137\uff08\u524d\u9762\u62633\uff0c\u4f5c\u6587\u626310\uff09</p>"},{"location":"Summaries/High%20School/eng_fht/#_2","title":"\u5b66\u79d1\u672c\u8eab:","text":""},{"location":"Summaries/High%20School/eng_fht/#_3","title":"\u82f1\u8bed\u96be\u5ea6\u600e\u4e48\u6837\uff1f","text":"<ul> <li>\u53d6\u51b3\u4e8e\u5b66\u751f\u5427\uff0c\u521d\u4e2d\u7684\u5e95\u5b50\u5f71\u54cd\u5f88\u5927\uff0c\u6709\u7684\u4eba\u521d\u4e2d\u82f1\u8bed\u597d\u76f4\u63a5\u4e09\u5e74\u90fd\u4e0d\u7528\u5b66\u82f1\u8bed\u3002</li> <li>\u57fa\u7840\u77e5\u8bc6\u5f71\u54cd\u540e\u7eed\u5b66\u4e60\uff08\u610f\u601d\u662f\u4e0d\u4f1a\u7684\u81ea\u5df1\u53bb\u5b66\u6389\uff09:<ul> <li>\u97f3\u6807 / \u53e3\u8bed</li> <li>\u8bcd\u6c47\u91cf</li> </ul> </li> <li>\u6bd4\u8bed\u6587\u3001\u6570\u5b66\uff08120+\u7684\u65f6\u5019\uff09\u63d0\u5206\uff08110+\u7684\u65f6\u5019\uff09\u5feb\u3002\u8bad\u7ec3\u65b9\u6cd5\u7b80\u5355\uff0c\u89c1\u6548\u5feb\uff0c\u63d0\u5347\u7a33\u5b9a\u3002</li> <li>\u8f7b\u903b\u8f91\uff0c\u91cd\u7406\u89e3\uff08\u8bfb\u61c2\u4e86\u5c31\u80fd\u505a\u5bf9\u9898\u76ee\uff09</li> </ul>"},{"location":"Summaries/High%20School/eng_fht/#_4","title":"\u6295\u5165\u65f6\u95f4\u600e\u4e48\u6837\uff1f","text":"<ul> <li>\u4ec0\u4e48\u788e\u7247\u5316\u80cc\u5355\u8bcd\u5176\u5b9e\u4e0d\u4e00\u5b9a\u6709\u7528\uff0c\u56fe\u7684\u53ea\u662f\u591a\u770b\u51e0\u6b21\u3002\u540c\u6837\uff0c\u65e9\u8bfb\u665a\u8bfb\u4e5f\u53ea\u662f\u591a\u82b1\u70b9\u65f6\u95f4\u719f\u6089\u719f\u6089\uff0c\u5b66\u6821\u7edf\u4e00\u8bad\u7ec3\u7684\u542c\u529b\u771f\u4e0d\u662f\u5f88\u6709\u7528\u53cd\u6b63\u3002\u5efa\u8bae\u79c1\u4e0b\u627e\u8001\u5e08\u5f3a\u5316\u4e00\u4e0b\uff08</li> <li>\u5e73\u65f6\u4e3b\u8981\u7684\u65f6\u95f4\u6295\u5165:<ul> <li>\u505a\u5377\u5b50\u3001\u8ba2\u6b63\u3001\u67e5\u5355\u8bcd</li> <li>\u5199\u4f5c\u6587\u3001\u6279\u6539\u3001\u80cc\u8bed\u6599</li> </ul> </li> <li>\u6211\u4e2a\u4eba\u8ba4\u4e3a\u5355\u8bcd\u662f\u6ca1\u5fc5\u8981\u53bb\u80cc\u7ef4\u514b\u591a\u7684\uff08\u4e0d\u8fc7\u5982\u679c\u8fde\u521d\u4e2d\u7684\u5355\u8bcd\u90fd\u4e0d\u4f1a\u7684\u8bdd\uff0c\u8fd8\u662f\u5148\u80cc\u4e2a1500\uff08\u521d\u4e2d\u5355\u8bcd\u5927\u7eb2\uff09\u518d\u8bf4\u5427\u3002\u540e\u9762\u7684\u5c31\u662f\u591a\u67e5\u67e5\u5b57\u5178\uff0c\u8bb0\u5728\u7b14\u8bb0\u672c\u4e0a\uff0c\u591a\u770b\u770b\u5c31\u597d\u4e86\u3002(\u6709\u7684\u8001\u5e08\u8981\u6c42\u8fc7\u4e2aN\u904d\u7684\u7ef4\u514b\u591a\u5176\u5b9e\u4e0d\u592a\u6709\u7528\uff0c\u6bd5\u7adf\u4e00\u4e2a\u5355\u8bcd\u77e5\u905310\u4e2a\u610f\u601d\uff0c\u4e5f\u4e0d\u4e00\u5b9a\u80fd\u591f\u7406\u89e3\u6587\u610f)<ul> <li>\u5982\u679c\u771f\u60f3\u901f\u6210\uff0c\u5efa\u8bae\u641c\u7d22IAI\u53d1\u7684\u5355\u8bcd\u5927\u7eb2\uff0c\u4ee5\u8ba4\u77e5\u8bcd\u6c47\u4e3a\u6807\u51c6\uff0c\u4e00\u661f\u671f\u5185\u80cc\u5b8c\u65b0\u9ad8\u80033000\u5355\u8bcd\u3002</li> </ul> </li> <li>\u7a33\u5b9a\u8bad\u7ec3\u7684\u60c5\u51b5\u4e0b\uff0c130\u5e94\u8be5\u662f\u6240\u6709\u5b66\u751f\u90fd\u80fd\u57286\u4e2a\u6708\u5185\u53ef\u4ee5\u8fbe\u5230\u7684\u3002</li> </ul>"},{"location":"Summaries/High%20School/eng_fht/#_5","title":"\u5b66\u4e60\u65b9\u6cd5:","text":"<p>\u53ef\u4ee5\u8bf4\uff0c\u82f1\u8bed\u662f\u4e3b\u8bfe\u91cc\u6700\u6709\u8ff9\u53ef\u5faa\u7684\u4e00\u95e8\u8bfe\u4e86\u3002\u800c\u4e14\u82f1\u8bed\u6709\u4e24\u6b21\u673a\u4f1a\uff0c\u6240\u4ee5\u53ea\u8981\u52aa\u529b\u5c31\u80fd\u53d6\u5f97\u5f88\u4e0d\u9519\u7684\u5206\u6570\uff08\u6027\u4ef7\u6bd4\u6781\u9ad8\uff09</p>"},{"location":"Summaries/High%20School/eng_fht/#_6","title":"\u8d44\u6e90\u63a8\u8350:","text":"<ul> <li>IAI yyds\uff01\uff01\uff01\uff08\u4e00\u4e2a\u82f1\u8bed\u516c\u4f17\u53f7\uff09</li> <li>\u4e00\u4e9b\u4e66:<ul> <li>\u8bed\u6cd5\u4ff1\u4e50\u90e8</li> <li>\u4e00\u672c\u6d3b\u9875\u7b14\u8bb0\u672c</li> <li>\u725b\u6d25 / \u6717\u6587 \u9ad8\u7ea7\u5b57\u5178 \u6216\u8005 \u5355\u8bcd\u7b14 \u6216\u8005 \u7535\u5b50\u5b57\u5178 \uff08\u5176\u5b9e\u533a\u522b\u4e0d\u5927\uff0c\u53ef\u4ee5\u51e0\u4e2a\u540c\u5b66\u7528\u4e00\u4e2a\uff09</li> </ul> </li> <li>\u5212\u7ebf\u5c3a\uff08\u5bf9\u5b57\u8ff9\u4e0d\u597d\u7684\u540c\u5b66\u53ef\u4ee5\u7528\uff0c\u5177\u4f53\u641c\u7d22IAI\u63a8\u6587\uff09</li> </ul>"},{"location":"Summaries/High%20School/eng_fht/#_7","title":"\u8d44\u6e90\u4e0d\u63a8\u8350:","text":"<ul> <li>\u82f1\u8bed\u539f\u8457:\uff08\u6027\u4ef7\u6bd4\u51e0\u4e4e\u4e3a\u96f6\uff0c\u5355\u8bcd\u964c\u751f\u5316\u8fc7\u9ad8\uff0c\u8001\u5e08\u770b\u4e0d\u61c2\u5bb9\u6613\u5224\u4f4e\u5206\uff0c\u5bb9\u6613\u4f7f\u4eba\u6d6e\u8e81\uff09     \u6bd4\u5982:<ul> <li>Harry Potter</li> <li>Flipped</li> <li>Good English ...</li> </ul> </li> <li>\u8bfe\u5916\u8d2d\u4e70\u7684\u5b57\u5e16\uff08\u9664\u4e86\u8861\u6c34\u4f53\u4ee5\u5916\u7684\u5b57\u4f53:\u610f\u5927\u5229\u659c\u4f53\uff0c\u82b1\u4f53\uff0c\u5706\u4f53...\uff09</li> <li>\u968f\u4fbf\u4e0d\u77e5\u6765\u6e90\u7684\u4e13\u9898\u96c6\uff08\u9ad8\u8003\u5fc5\u5237\u9898\uff0c\u9ad8\u8003\u4e94\u4e09\uff08\u6392\u7248\u96be\u770b\uff0c\u9898\u76ee\u8001\u65e7\uff09\uff09</li> <li>\u91d1\u8003\u5377\u7b49\uff08\u522b\u60f3\u4e86\uff0c\u6839\u672c\u4e0d\u4f1a\u505a\u591a\u5c11\u7684\uff09 IAI\u3000is enough\uff01</li> <li>\u8001\u5e08\u4e0d\u77e5\u9053\u54ea\u91cc\u641e\u6765\u7684\u5916\u7701\u7684\u5377\u5b50/\u5546\u4e1a\u5377\uff08\u505a\u4e86\u63d0\u5347\u5f88\u5c0f\uff0c\u5f71\u54cd\u53e3\u5473\u7f62\u4e86\uff09</li> <li>\u5e73\u65f6\u7684\u4f5c\u4e1a\uff08\u7f3a\u4e4f\u9488\u5bf9\u6027\uff0c\u5408\u7406\u770b\u5f85\uff0c\u7231\u505a\u4e0d\u505a\uff09</li> <li>\u51fa\u53bb\u8865\u8bfe\u53d1\u7684\u4f5c\u6587\u89e3\u6790\uff08\u5408\u7406\u770b\u5f85\uff0c\u8b66\u60d5\u6a21\u677f/\u79d2\u6740/\u9ad8\u7ea7\u8bcd\u6c47\uff09</li> <li>\u56db\u516d\u7ea7\u3001\u6258\u798f\u3001\u96c5\u601d\u3001GRE\u5355\u8bcd\uff08\u6027\u4ef7\u6bd4\u4f4e\uff0c\u8d34\u5408\u5ea6\u4f4e\uff0c\u88c5\u903c\u5ea6\u9ad8\uff0c\u4e0d\u7b26\u5408\u9ad8\u8003\u5bfc\u5411\uff09</li> </ul>"},{"location":"Summaries/High%20School/eng_fht/#_8","title":"\u5b66\u4e60\u65b9\u6cd5:","text":""},{"location":"Summaries/High%20School/eng_fht/#_9","title":"\u9ad8\u4e00\u9ad8\u4e8c\u4e0a:","text":"<ul> <li>\u79ef\u7d2f\u5355\u8bcd\uff08\u8bb0\u5728\u6d3b\u9875\u672c\u4e0a\uff09</li> <li>\u63d0\u5347\u5ba2\u89c2\u9898:\u6240\u6709\u9898\u76ee\u9519\u7684\u5f04\u61c2\uff0c\u505a\u8fc7\u4e0d\u9519\uff08\u522b\u73a9\u4f60\u7684\u7834\u9519\u9898\u672c\u4e86\uff09</li> <li>\u4f5c\u6587\u6446\u70c2\uff08\u9ad8\u4e00\u9ad8\u4e8c\u8303\u6587\u6c34\u5e73\u592a\u4f4e\uff0c\u6ca1\u6709\u5b66\u4e60\u7684\u4ef7\u503c\uff09</li> </ul>"},{"location":"Summaries/High%20School/eng_fht/#_10","title":"\u9ad8\u4e8c\u4e0b\u9ad8\u4e09:","text":"<ul> <li>\u8fd9\u65f6\u5019\u9ad8\u8003\u5355\u8bcd\u90fd\u8ba4\u4e0d\u5168\u8bf4\u4e0d\u8fc7\u53bb\u4e86<ul> <li>\u8bf7\u53c2\u8003\u524d\u6587</li> </ul> </li> <li>\u8bed\u6cd5\u4e0d\u4f1a\u7684\u53bb\u5b66\u8bed\u6cd5\uff08\u770b\u8bed\u6cd5\u4ff1\u4e50\u90e8\uff09\uff0c\u4e0d\u8981\u8ffd\u6c42\u5b8c\u6574\u5177\u4f53\uff0c\u80fd\u591f\u505a\u8bed\u6cd5\u586b\u7a7a\u548c\u4f1a\u5206\u6790\u9605\u8bfb\u4e2d\u7684\u957f\u96be\u53e5\u5c31\u591f\u4e86\u3002\uff08\u751a\u81f3\u865a\u62df\u8bed\u6c14\u4ec0\u4e48\u7684\u90fd\u8003\u4e0d\u4e86\uff09</li> <li>\u9650\u65f6\u505a\u5377\u5b50\uff0840min\u505a\u5b8c\u5ba2\u89c2\u9898\uff09+\u8ba2\u6b63\uff08\u641e\u61c2\u4e3a\u4ec0\u4e48\u9519\uff09<ul> <li>\u505a\u591f30\u5957\u5c31\u53ef\u4ee5\u7a33\u4e0a130\uff08\u5377\u5b50\u6765\u6e90IAI\uff09</li> </ul> </li> <li>\u9650\u65f6\u7ec3\u4f5c\u6587\uff08\u5e94\u7528\u6587+\u7eed\u5199\uff09<ul> <li>\u7eed\u5199\u5199\u591f20\u504f\u5c31\u53ef\u4ee518+</li> <li>\u5e94\u7528\u6587\u5efa\u8bae\u79ef\u7d2f\u6a21\u677f\uff0c\u9047\u5230\u4e0d\u540c\u4e3b\u9898\u90fd\u6709\u8bdd\u8bf4\u3002\u4fdd\u6301\u5e73\u65f611+\u5c31\u597d\u3002</li> </ul> </li> <li>\u5b66\u6821\u8003\u8bd5\u7684\u4f5c\u6587\u6253\u5206\u4e0d\u503c\u5f97\u76f8\u4fe1:<ul> <li>\u5efa\u8bae\u73cd\u60dc\u8054\u8003\uff08\u4e0d\u662f\u5b66\u6821\u8001\u5e08\u6539\u7684\u65f6\u5019\uff0c\u6bd4\u5982\u5076\u5c14\u7684Z20\uff09</li> <li>\u53ea\u770b\u8001\u5e08\u6539\u7684\u8bed\u6cd5\u9519\u8bef</li> <li>\u53ef\u4ee5\u53c2\u52a0IAI\u57f9\u8bad\uff08\u4e0d\u662f\u5e7f\u544a\uff0c\u6027\u4ef7\u6bd4\u6bd4\u8f83\u4f4e\uff0c\u4f46\u662f\u6539\u4f5c\u6587\u7684\u6807\u51c6\u5f88\u51c6\uff09</li> </ul> </li> <li>\u4ee5\u63d0\u5347\u6210\u7ee9\u4e3a\u5bfc\u5411\uff0c\u8b66\u60d5\u63d0\u5347\u82f1\u8bed\u7d20\u517b\u66f2\u7ebf\u6551\u56fd\u7684\u9677\u8fdb\uff08\u5982\uff0c\u770b\u5916\u520a\uff0c\u8bfb\u539f\u8457\u7b49\u7b49\uff09</li> </ul>"},{"location":"Summaries/High%20School/eng_fht/#_11","title":"\u8bad\u7ec3\u76ee\u6807:","text":"<ul> <li>\u5ba2\u89c2\u9898\u4fdd\u8bc1\u572830-35\u5206\u949f\u5185\u505a\u5b8c</li> <li>\u4f5c\u65871\u5c0f\u65f6\u5185\u5199\u5b8c\u4e24\u7bc7\uff0c\u8981\u6c42\u5e94\u7528\u6587\u4e0d\u4f4e\u4e8e11\u5206\uff0c\u7eed\u5199\u4e0d\u4f4e\u4e8e18\u5206\uff08\u4e24\u6bb5\u90fd\u5199\u6ee110\u884c\uff09</li> <li>\u5ba2\u89c2\u9898\u6263\u5206\u4e0d\u8d85\u8fc75\u5206\uff08\u542c\u529b\u9605\u8bfb\u4e03\u9009\u4e94\u5168\u5bf9\uff0c\u5b8c\u578b\u53ef\u62631\u5206\uff0c\u8bed\u586b\u53ef\u62631.5\u5206\uff09</li> </ul>"},{"location":"Summaries/High%20School/eng_fht/#_12","title":"\u5c0f\u6280\u5de7:","text":"<ul> <li>\u5408\u7406\u5b89\u6392\u505a\u9898\u65f6\u95f4\uff0c\u4e0d\u4e00\u5b9a\u8981\u4ece\u9605\u8bfb\u5f00\u59cb\u505a</li> <li>95%\u7684\u5b8c\u578b\u7b26\u54084443\uff08\u9009\u9879\u5206\u5e03\uff09\uff0c\u9ad8\u8003\u4e2d\u53ea\u670922\u8fd8\u662f\u54ea\u4e00\u5e74\u51fa\u73b0\u8fc74533\uff0c\u5efa\u8bae\u505a\u5b8c\u578b\u7684\u65f6\u5019\u5708\u9009\u9879\u800c\u975e\u5199\u5b57\u6bcd\uff0c\u4e0d\u7136\u4e0a\u4e0b\u4f1a\u5f71\u54cd\u3002\u7b2c\u4e00\u6b21\u505a\u4e0d\u51fa\u6765\u7684\u53ef\u4ee5\u5148\u7a7a\u7740\uff0c\u518d\u8bfb\u4e00\u904d\u540e\u56de\u6765\u6839\u636e\u5206\u5e03\u7efc\u5408\u6587\u610f\u586b\u6ee1\u3002</li> <li>\u9605\u8bfb\u8bfb\u5b8c\u6587\u7ae0\uff0c\u8bed\u586b\u5168\u90e8\u8981\u8bfb \u518d\u505a\u9898\uff08\u4e0d\u7136\u4f1a\u6709\u5f88\u6076\u5fc3\u7684\u9677\u9631\uff09</li> <li>\u4f5c\u6587\u4e0d\u4e00\u5b9a\u8981\u6253\u8349\u7a3f\uff0c\u4f46\u662f\u4e00\u5b9a\u4e0d\u80fd\u6709\u8bed\u6cd5\u9519\u8bef\uff0c\u5b57\u8ff9\u96be\u770b\uff08\u8fd9\u4e24\u70b9\u662f\u5f71\u54cd\u4f5c\u6587\u7684\u4e3b\u8981\u56e0\u7d20\uff0c24\u9ad8\u8003\u4e4b\u540e\u53ef\u80fd\u8fd8\u6709\u4e3b\u65e8\u5347\u534e\uff09\u3002</li> <li>\u8bfb\u61c2\u624d\u662f\u5b66\u82f1\u8bed\u7684\u552f\u4e00\u8981\u70b9\uff01\uff01\uff01</li> </ul> <p>\u8bf7\u5408\u7406\u4f7f\u7528IAI\uff0c\u5f88\u6709\u53ef\u80fd\u662f\u6700\u597d\u7684\u8d44\u6e90\u3002</p>"},{"location":"Summaries/High%20School/math_fht/","title":"\u6570\u5b66\u7ecf\u9a8c\u5206\u4eab","text":""},{"location":"Summaries/High%20School/math_fht/#_1","title":"\u6570\u5b66\u7ecf\u9a8c\u5206\u4eab","text":"<p> \u7ea6 757 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>\u80cc\u666f:2024\u5c4a\u9ad8\u8003138\uff08\u586b\u7a7a\u9519\u4e00\u90535'+19\u9898\u6700\u540e\u4e00\u95ee7'\uff09</p>"},{"location":"Summaries/High%20School/math_fht/#_2","title":"\u5b66\u79d1\u672c\u8eab:","text":"<ul> <li>\u6211\u60f3\u6570\u5b66\u7684\u4f53\u7cfb\uff08\u89e3\u9898\u5957\u8def\uff09\u662f\u4e0d\u5982\u7269\u7406\u5b8c\u6574\u7684\u3002\u6bd4\u5982:\u5706\u9525\u66f2\u7ebf\u5f88\u96be\u627e\u5230\u901a\u6cd5\u89e3\u51b3\u6240\u6709\u9898\u6216\u8005\u5bfc\u6570\u6709\u65f6\u5019\u4e5f\u4f1a\u6d89\u53ca\u5f88\u591a\u5947\u5947\u5999\u5999\u7684\u77e5\u8bc6\u3002</li> <li>\u771f\u7684\u5f88\u96be\u7a33\u5b9a\u63d0\u5206\uff08\u4e3b\u8981\u6307120+?\uff09</li> <li>\u5b66\u79d1\u601d\u7ef4\u53ef\u80fd\u5f88\u91cd\u8981\u3002\u867d\u7136\u6211\u4e0d\u662f\u5f88\u80fd\u9610\u660e\u8fd9\u4e2a\u6982\u5ff5\uff0c\u4f46\u5177\u4f53\u6765\u8bf4\u5c31\u662f\uff0c\u8981\u53bb\u505a\u95ee\u9898\uff0c\u800c\u4e0d\u662f\u80cc\u7b54\u6848\u3002\u5176\u5b9e\u5f88\u591a\u65f6\u5019\u7684\u505a\u4e5f\u4e0d\u8fc7\u662f\u9ed8\u5199\u4ee5\u524d\u4f1a\u7684\u5957\u8def\uff0c\u4e0d\u4f1a\u7684\u4e5f\u57fa\u672c\u4e0d\u53ef\u80fd\u5f53\u573a\u521b\u65b0\u51fa\u6765\u3002\u6240\u4ee5\u5927\u6982\u8fd9\u91cc\u7684\u505a\u6307\u7684\u662f\uff0c\u8fd0\u7528\u4ee5\u524d\u5b66\u8fc7\u7684skill\uff0c\u5c06\u4ed6\u4eec\u7ec4\u5408\u5728\u4e00\u8d77\uff0c\u62b5\u8fbe\u6240\u8981\u8fbe\u6210\u7684\u76ee\u6807\u3002</li> <li>\u6240\u4ee5\uff0c\u4e5f\u8bb8\u4f46\u51e1\u4e0a\u8ff0\u4e00\u4e2a\u6b65\u9aa4\u505a\u4e0d\u5230\uff0c\u90fd\u5f88\u96be\u505a\u5bf9\u4e00\u9053\u9898:<ul> <li>\u5206\u6790\u76ee\u6807\u662f\u4ec0\u4e48</li> <li>\u8003\u8651\u8981\u600e\u4e48\u5230\u8fbe</li> <li>\u8fd0\u7528\u4ec0\u4e48\u5de5\u5177<ul> <li>\u5982\u4f55\u68c0\u9a8c\uff0c\u5b9a\u6027\u5224\u65ad    </li> <li>\u5982\u4f55\u8bd5\u63a2\uff0c\u5b9a\u91cf\u8ba1\u7b97</li> </ul> </li> </ul> </li> </ul>"},{"location":"Summaries/High%20School/math_fht/#_3","title":"\u5b66\u4e60\u65b9\u6cd5:","text":"<p>\u6211\u4e00\u4e2a\u9ad8\u4e2d\u57fa\u672c\u6ca1\u505a\u8fc7\u6570\u5b66\u4f5c\u4e1a\u7684\u4eba\u4e5f\u8bb8\u4e0d\u914d\u6765\u8bf4\u8fd9\u4e2a\u95ee\u9898\u3002</p>"},{"location":"Summaries/High%20School/math_fht/#_4","title":"\u7701\u6d41\u7248:","text":"<ul> <li>\u638c\u63e1\u57fa\u672c\u77e5\u8bc6\u70b9\uff0c\u5b9a\u4e49\uff0c\u516c\u5f0f\uff0c\u5957\u8def\uff08\u5982\u7aef\u70b9\u6548\u5e94\uff09</li> <li>\u505a\u6574\u5377\u67e5\u6f0f\u8865\u7f3a</li> <li>\u505a\u4e13\u9898\uff0c\u6bd4\u8f83\u5f52\u7eb3</li> <li>\u8003\u8bd5\u8bad\u7ec3\u5fc3\u6001</li> </ul>"},{"location":"Summaries/High%20School/math_fht/#_5","title":"\u6ce8\u610f\u4e8b\u9879:","text":"<ul> <li>\u9519\u9898\u672c\u5f88\u53ef\u80fd\u6ca1\u6709\u7528\uff0c\u771f\u6b63\u6709\u7528\u7684\u662f\u8003\u8bd5\u4ee5\u540e\u7684\u590d\u76d8\uff0c\u81ea\u5df1\u6574\u7406\u603b\u7ed3\u51fa\u7684\u5957\u8def\u65b9\u6cd5\uff0c\u6613\u9519\u5f52\u7eb3\u3002     \u6bd4\u5982:     \u53ef\u80fd\u8fd9\u6b21\u5bfc\u6570\u9898\u6ca1\u505a\u51fa\u6765\uff0c\u4f60\u8981\u60f3\u6e05\u695a\u7684\u662f\uff0c\u4e3a\u4ec0\u4e48\u6ca1\u505a\u51fa\u6765\uff0c\u8003\u8bd5\u7684\u65f6\u5019\u6ca1\u82b1\u65f6\u95f4\u8fd8\u662f\u82b1\u4e86\u65f6\u95f4\u4e5f\u6ca1\u60f3\u660e\u767d\uff0c\u771f\u6b63\u6b63\u786e\u7684\u51b3\u7b56\u662f\u4ec0\u4e48\uff08\u8df3\u8fc7\uff1f\u7ee7\u7eed\u601d\u8003\uff1f\uff09\uff0c\u5982\u679c\u4e0b\u6b21\u8fd8\u662f\u505a\u4e0d\u51fa\u6765\u53ef\u4ee5\u600e\u4e48\u5c1d\u8bd5\uff0c\u5b66\u5230\u4e86\u4ec0\u4e48\u65b0\u7684\u6a21\u578b\u3002</li> <li>\u4e0d\u8981\u5bf9\u8003\u8bd5\u8fc7\u62df\u5408\uff0c\u5f88\u591a\u4eba\u8fc7\u5206\u5938\u5927\u4e86\u590d\u76d8\u7684\u4f5c\u7528\u3002\u7279\u522b\u662f\u5728\u6570\u5b66\u5e94\u8bd5\u65b9\u9762\uff0c\u82b1\u8fc7\u591a\u7684\u65f6\u95f4\u5728\u590d\u76d8\u4e0a\u7684\u6027\u4ef7\u6bd4\u4e0d\u9ad8\uff0c\u4e0d\u5982\u591a\u505a\u70b9\u9898/\u770b\u70b9\u65b0\u9c9c\u73a9\u610f/\u5b66\u522b\u7684\u79d1\u76ee\u53bb\u3002</li> <li>\u65f6\u95f4\u5f52\u7eb3\u548c\u5fc3\u6001\u51b3\u5b9a\u8003\u8bd5\u5206\u6570\u7684\u4e0b\u9650\u3002\u57fa\u7840\u9898\u505a\u5b8c\u5c31\u6709\u5f88\u591a\u5206\u6570\u5566\uff01\u522b\u88ab\u4e00\u4e2a\u9898\u5361\u4f4f\u4e86\u5c31\u5fc3\u6001\u5d29\u4e86\uff0c\u5f88\u591a\u4eba\u8bf4\u81ea\u5df1\u5fc3\u6001\u597d\u53ea\u4e0d\u8fc7\u662f\u6ca1\u505a\u8fc7\u9053\u9053\u4e0d\u987a\u5229\u7684\u5377\u5b50\u3002</li> <li>\u591a\u8ddf\u8001\u5e08\u4ea4\u6d41\uff0c\u8001\u5e08\u5f88\u53ef\u80fd\u6bd4\u4f60\u60f3\u50cf\u7684\u8981\u66f4helpful\u4e00\u4e9b\u3002</li> <li>\u4e0d\u8981\u653e\u5f03\u6570\u5b66\uff0c150\u5206\u5462\uff0c\u8fd9\u90fd\u653e\u4e86\u8fd8\u662f\u522b\u9ad8\u8003\u4e86\u3002<ul> <li>\u65e9\u70b9\u5b66\u6570\u5b66\u5427\uff0c\u522b\u6b7b\u5230\u4e34\u5934\u4e86\u624d\u540e\u6094</li> </ul> </li> <li>\u4e0d\u8981\u6c89\u8ff7\u9ad8\u7ea7\u73a9\u610f:\uff08\u6709\u8fd9\u65f6\u95f4\u4e0d\u5982\u53bb\u73a9\uff09<ul> <li>\u6cf0\u52d2\u5c55\u5f00</li> <li>\u6781\u70b9\u6781\u7ebf</li> <li>\u5bfc\u6570\u7684\u4e00\u5806\u5947\u6280\u6deb\u5de7</li> <li>...</li> </ul> </li> <li>\u8ba1\u7b97\u80fd\u529b\u5f88\u91cd\u8981\uff0c\u89e3\u6790\u51e0\u4f55\u8be5\u7b97\u7684\u8981\u7b97\u3002</li> </ul>"},{"location":"Summaries/High%20School/math_fht/#_6","title":"\u8d44\u6599:","text":"<ul> <li>\u5b66\u6821\u5e73\u65f6\u7684\u8003\u8bd5\uff0c\u8bf7\u8ba4\u771f\u5bf9\u5f85</li> <li>\u6d59\u8003\u795e\u5899</li> <li>\u4e0d\u63a8\u8350\u4ec0\u4e48\u6559\u8f85\uff0c\u5bf9\u9ad8\u8003\u7684\u6700\u4f73\u62df\u5408\u662f\u9ad8\u8003\u5377+\u56db\u7701\u8054\u8003\u4e4b\u7c7b\u7684\u98ce\u5411\u5377</li> <li>\u540c\u5b66\u7684\u7b14\u8bb0\uff08\u4e0d\u662f</li> </ul>"},{"location":"Summaries/High%20School/phy_fht/","title":"\u7269\u7406\u7ecf\u9a8c\u5206\u4eab","text":""},{"location":"Summaries/High%20School/phy_fht/#_1","title":"\u7269\u7406\u7ecf\u9a8c\u5206\u4eab","text":"<p> \u7ea6 1581 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 8 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>\u80cc\u666f:2024\u5c4a\u9996\u800395-&gt;\u9ad8\u8003100</p>"},{"location":"Summaries/High%20School/phy_fht/#_2","title":"\u5b66\u79d1\u672c\u8eab:","text":""},{"location":"Summaries/High%20School/phy_fht/#_3","title":"\u8981\u4e0d\u8981\u9009\u7269\u7406\uff1f","text":"<ul> <li>\u5982\u679c\u4ee5\u540e\u60f3\u5b66\u7406\u5de5\u79d1\u7684\u8bdd\uff0c\u6700\u597d\u662f\u7269\u5316\u5927\u793c\u5305\u4e00\u8d77\u4e0a\u300224\u5e74\u6587\u79d1\u6ed1\u6863\u8fd8\u662f\u5f88\u5389\u5bb3\u7684\u3002</li> <li>\u5bf9\u4e8e\u6570\u5b66\u4e0d\u597d\u7684\u540c\u5b66\u6765\u8bf4\uff0c\u7269\u7406\u7684\u96be\u5ea6\u4e0d\u4f1a\u5f88\u5c0f\u3002<ul> <li>\u5efa\u6a21</li> <li>\u8bbe\u65b9\u7a0b\uff0c\u627e\u672a\u77e5\u91cf\uff0c\u89e3\u591a\u5143\u65b9\u7a0b</li> <li>\u4e09\u89d2\u51fd\u6570\u7684\u719f\u7ec3\u4f7f\u7528</li> <li>\u5bfc\u6570\u4ee5\u53ca\u90e8\u5206\u79ef\u5206\u7684\u4f7f\u7528</li> <li>\u5bf9\u516c\u5f0f\u63a8\u5bfc\u65b9\u5411\u7684\u628a\u63e1</li> </ul> </li> <li> <p>\u5bf9\u4e8e\u6b7b\u8bb0\u786c\u80cc\u5b66\u7269\u7406\u7684\u540c\u5b66\u6765\u8bf4\uff0c\u5343\u4e07\u4e0d\u8981\u9009\u7269\u7406\u6765\u6076\u5fc3\u81ea\u5df1/\u8001\u5e08\u3002\u8bf7\u9a8c\u8bc1\u4f60\u662f\u5426\u638c\u63e1\u5982\u4e0b\u516c\u5f0f\u63a8\u5bfc:</p> <ul> <li>\u5229\u7528\u6253\u70b9\u8ba1\u65f6\u5668\u6c42\u52a0\u901f\u5ea6\u516c\u5f0f</li> <li>\u5e73\u629b\u8fd0\u52a8\u8f68\u8ff9\u65b9\u7a0b\uff0c\u5750\u6807\u968f\u65f6\u95f4\u53d8\u5316\u51fd\u6570\uff0c\u53cd\u5411\u5ef6\u957f\u7ebf\u7684\u4e8c\u7ea7\u7ed3\u8bba</li> <li>\u4e07\u6709\u5f15\u529b\u516c\u5f0f\uff0c\u5929\u4f53\u8fd0\u52a8\u901f\u5ea6\uff0c\u89d2\u901f\u5ea6\uff0c\u5468\u671f\uff0c\u80fd\u91cf</li> <li>\u5f39\u6027\u52bf\u80fd\uff0c\u52a8\u80fd\uff0c\u673a\u68b0\u80fd\uff08\u5f15\u529b\u52bf\u80fd\uff0c\u5e93\u4ed1\u52bf\u80fd\uff09</li> <li>\u52a8\u91cf\u6765\u6e90\uff0c\u78b0\u649e\u6a21\u578b</li> <li>\u6d1b\u4f26\u5179\u529b\u53ca\u5bf9\u5e94\u7c92\u5b50\u8fd0\u52a8\u6a21\u578b</li> <li>\u7535\u78c1\u611f\u5e94\u53ca\u5bf9\u5e94\u6a21\u578b:\u65cb\u8f6c\u68d2\u7684\u52a8\u751f\u7535\u52a8\u52bf\uff0c\u5355\u68d2\uff0c\u53cc\u68d2\uff0c\u7535\u5bb9\uff0c\u7535\u611f\uff0c\u78c1\u9a71\u52a8\uff0c\u70ed\u91cf\u8ba1\u7b97</li> </ul> <p>\u5982\u679c\u4f60\u4e3b\u8981\u662f\u9760\u8bb0\u80cc\u6765\u652f\u6491\u7269\u7406\u5b66\u4e60\uff0c\u90a3\u8bf7\u4f60\u4e0d\u8981\u9009\u7269\u7406\u3002</p> </li> </ul>"},{"location":"Summaries/High%20School/phy_fht/#_4","title":"\u7269\u7406\u96be\u5ea6\u600e\u4e48\u6837\uff1f","text":"<ul> <li>\u7269\u7406\u5e94\u8be5\u662f\u7406\u79d1\u91cc\u4f53\u7cfb\u7ed3\u6784\u7d27\u5bc6\u5b8c\u6574\uff0c\u5e94\u8bd5\u624b\u6bb5\u4e30\u5bcc\u5b8c\u5907\u7684\u4e00\u95e8\u5b66\u79d1\u4e86\u3002\u638c\u63e1\u77e5\u8bc6\u70b9\uff0c\u5b9a\u4e49\uff0c\u5b9a\u7406\uff0c\u6a21\u578b\uff0c\u5e94\u7528\u9700\u8981\u82b1\u65f6\u95f4\uff0c\u4e14\u6709\u5408\u7406\u7684\u8def\u7ebf\u53ef\u4ee5\u4f9d\u636e\u3002<ul> <li>\u8ddf\u5316\u5b66\u6bd4\uff0c\u5b83\u66f4\u504f\u5b9a\u91cf\uff0c\u6709\u660e\u786e\u7684\u516c\u5f0f\u8ba1\u7b97\uff0c\u5b8c\u6574\u7684\u903b\u8f91\u94fe\u6761\u3002</li> <li>\u8ddf\u6570\u5b66\u6bd4\uff0c\u5b83\u66f4\u504f\u5e94\u7528\uff0c\u6709\u6e05\u6670\u7684\u7ed3\u679c\u5bfc\u5411\uff0c\u4e0d\u8981\u6c42\u7075\u611f\u7206\u53d1\u3002</li> <li>\u8ddf\u6280\u672f\u6bd4\uff0c\u5b83\u66f4\u504f\u8ba1\u7b97\uff0c\u6709\u76f8\u6263\u7684\u77e5\u8bc6\u4f53\u7cfb\uff0c\u66f4\u4f4e\u7684\u5b66\u4e60\u95e8\u69db\u3002</li> </ul> </li> <li>\u53ea\u8981\u4f60\u613f\u610f\u4e0b\u529f\u592b\uff0c\u7269\u7406\u7edd\u5bf9\u662f\u4e00\u95e8\u52aa\u529b\u5c31\u6709\u56de\u62a5\u7684\u5b66\u79d1\u3002</li> </ul>"},{"location":"Summaries/High%20School/phy_fht/#_5","title":"\u5b66\u4e60\u65b9\u6cd5:","text":"<p>\u8ddf\u6280\u672f\u7c7b\u4f3c</p>"},{"location":"Summaries/High%20School/phy_fht/#etc","title":"\u627e\u4e00\u672c\u6559\u8f85\uff08\u4e94\u4e09\u9ad8\u8003\u7248 etc.\uff09\u770b\u5b8c\u77e5\u8bc6\u70b9","text":"<ul> <li>\u8981\u6c42\u80fd\u591f\u77e5\u9053\u5b9a\u4e49\uff0c\u91cd\u8981\u516c\u5f0f\u63a8\u5bfc\uff0c\u884d\u751f\u4e8c\u7ea7\u7ed3\u8bba\u548c\u57fa\u672c\u6a21\u578b     \u6bd4\u5982:<ul> <li>\u7535\u5bb9\u7684\u5b9a\u4e49</li> <li>\u7535\u5bb9\u5927\u5c0f\u7684\u8ba1\u7b97\u5f0f</li> <li>\u6d89\u53ca\u7535\u5bb9\u7684\u52a8\u6001\u53d8\u5316</li> <li>\u7535\u5bb9\u5728\u7535\u8def\u4e2d\u5982\u4f55\u8ba1\u7b97</li> <li>\u7535\u5bb9\u7684\u80fd\u91cf\u516c\u5f0f</li> <li>\u7535\u5bb9\u5145\u653e\u7535\u5b9e\u9a8c</li> <li>\u7535\u5bb9\u5728\u4ea4\u6d41\u7535\u4e2d\u7684\u4f5c\u7528\uff08\u5b9a\u6027\uff09</li> <li>\u7535\u5bb9\u4e0e\u5176\u4ed6\u6a21\u578b\u7684\u7ed3\u5408</li> <li>...</li> </ul> </li> </ul>"},{"location":"Summaries/High%20School/phy_fht/#_6","title":"\u505a\u9898","text":"<ul> <li>\u9898:<ul> <li>\u5377\u5b50</li> <li>\u4e13\u9898  </li> </ul> </li> <li>\u65b9\u6cd5:<ul> <li>\u5377\u5b50\u7528\u6765\u67e5\u6f0f\u8865\u7f3a\uff0c\u63d0\u5347\u6574\u4f53\u5b8c\u6210\u5ea6\uff0c\u4f18\u5316\u65f6\u95f4\u5206\u914d\uff0c\u5feb\u901f\u5efa\u6784\u77e5\u8bc6\u6846\u67b6</li> <li>\u4e13\u9898\u7528\u6765\u5f3a\u5316\u8ba1\u7b97\uff0c\u719f\u6089\u516c\u5f0f\uff0c\u6df1\u5316\u903b\u8f91\u53ca\u5f52\u7eb3\u672c\u8d28</li> </ul> </li> <li>\u5982\u679c\u4e0d\u4f1a\u600e\u4e48\u529e:<ul> <li>\u770b\u7b54\u6848\uff0c\u95ee\u8001\u5e08\uff0c\u95ee\u540c\u5b66</li> <li>\u9009\u53d6\u540c\u7c7b\u9898\u76ee\uff0c\u505a\u8db3\u591f\u6570\u91cf\u540e\u5f52\u7eb3\u6574\u7406\u6a21\u578b</li> </ul> </li> <li>\u6613\u9519\u70b9\u5373\u4f7f\u8bb0\u5f55<ul> <li>\u53ef\u7528\u6d3b\u9875\u672c/A4\u7eb8+\u71d5\u5c3e\u5939</li> </ul> </li> <li>\u63a8\u8350\u5f52\u7eb3\u6a21\u578b\u800c\u4e0d\u662f\u6574\u7406\u9519\u9898</li> <li>\u4e00\u5b9a\u8981\u591a\u7ec3\u8ba1\u7b97\u548c\u65f6\u95f4\uff0c\u5c11\u7528/\u4e0d\u7528\u8ba1\u7b97\u5668<ul> <li>\u5728\u9ad8\u4e09\u672b\u671f\uff0c\u6211\u80fd\u7a33\u5b9a40min\u505a\u5b8c\u673a\u68b0\u80fd\u53ca\u524d\u9762\u6240\u6709\u90e8\u5206\u3002\u5f53\u7136\u8fd9\u5bf9\u5927\u591a\u6570\u540c\u5b66\u6765\u8bf4\u592a\u5feb\u4e86\uff0c\u4f46\u901f\u5ea6\u63d0\u5347\u600e\u4e48\u4e5f\u4e0d\u5acc\u591a\u3002</li> <li>\u4f8b\u5982\u572824\u5e74\u9ad8\u8003\u4e2d\uff0c\u5f88\u591a\u540c\u5b66\u7531\u4e8e\u7535\u78c1\u611f\u5e94\u5361\u58f3\u800c\u6ca1\u6709\u505a\u5b8c\u5377\u5b50\uff0c\u5bfc\u81f4\u4e8c\u8003\u672a\u80fd\u5b9e\u73b0\u6709\u6548\u63d0\u5206\u3002</li> </ul> </li> <li>\u9009\u62e9\u9898\u5f88\u91cd\u8981\uff0c\u4e00\u9053\u4e09\u5206\u5343\u4e07\u522b\u9519\u3002\u591a\u9009\u9898\u8bf7\u4fdd\u5b88\u4e00\u4e9b\uff0c\u6fc0\u8fdb\u5f80\u5f80\u4e0d\u4f1a\u6709\u597d\u7ed3\u679c\uff0c\u9ad8\u8003\u540e\u6094\u5c31\u6765\u4e0d\u53ca\u4e86\u3002</li> <li>\u4e0d\u4f1a\u7684\u9898\u76ee\u53ca\u65f6\u6b62\u635f\uff0c\u5982\u673a\u68b0\u80fd\u4e2d\u65e0\u8c13\u7684\u5206\u7c7b\u8ba8\u8bba\uff0c\u7535\u78c1\u611f\u5e94\u4e2d\u65e0\u8c13\u7684\u70ed\u91cf\u8ba1\u7b97\u7b49\u7b49\uff0c\u53ef\u4ee5\u7b49\u505a\u5b8c\u6574\u5f20\u5377\u5b50\u540e\u518d\u6765\u505a\u3002</li> <li>\u4e0d\u8981\u6c89\u8ff7\u504f\uff0c\u602a\uff0c\u96be\uff0c\u73b0\u5728\u7684\u6a21\u62df\u5377\u5f88\u591a\u98ce\u683c\u504f\u79bb\u9ad8\u8003\uff0c\u8bf7\u57f9\u517b\u8fa8\u522b\u8d28\u91cf\u7684\u672c\u9886\u3002</li> </ul>"},{"location":"Summaries/High%20School/phy_fht/#_7","title":"\u5fc3\u6001\u65b9\u9762:","text":"<ul> <li>\u7269\u7406\u7684\u8003\u8bd5\u65f6\u95f4\u89c4\u5212\u5f88\u91cd\u8981\uff0c\u4e0d\u4f1a\u7684\u53ef\u4ee5\u5148\u8df3\u8fc7\u53bb\uff0c\u56de\u6765\u5728\u505a\uff0c\u5f53\u7136\u8df3\u591a\u4e86\u81ea\u7136\u4e5f\u8003\u4e0d\u597d\u4e86\u3002\u8981\u9759\u4e0b\u6765\u505a\u9898\u3002</li> <li>\u6ce8\u610f\u529b\u96c6\u4e2d\uff0c\u76f8\u4fe1\u81ea\u5df1\u7684\u5224\u65ad\uff0c\u653e\u677e\u505a\u9898\u3002</li> <li>\u5fc3\u6001\u5e26\u6765\u7684\u5f71\u54cd\u4e3b\u8981\u96c6\u4e2d\u5728\u9009\u62e9\u9898\u4e0a\uff0c\u6211\u9996\u8003\u9519\u4e864.5\u9053\u7684\u9009\u62e9\u9898\uff0c\u76f4\u63a595\u4e86\u3002</li> <li>\u5e73\u65f6\u8003\u8bd5\u6ca1\u6709\u5f88\u5927\u4ef7\u503c\uff0c\u8054\u8003\u7684\u552f\u4e00\u610f\u4e49\u5c31\u662f\u6a21\u62df\u9ad8\u8003\u6c1b\u56f4\u953b\u70bc\u5fc3\u6001\u3002\u6211\u9996\u8003\u524d\u7a33\u5b9a99+\uff0c\u6700\u540e\u4e0d\u8fd8\u662f\u8003\u4e86\u4e2a95\u3002</li> </ul>"},{"location":"Summaries/High%20School/phy_fht/#_8","title":"\u8d44\u6599\u65b9\u9762:","text":"<ul> <li>\u6d59\u8003\u7269\u7406\u4e0a\u6709\u4e00\u4e9b\u5377\u5b50\uff08\u4e0d\u5168\u9762\uff09</li> <li>\u6d59\u8003\u795e\u5899\u4f1a\u6709\u51e0\u4e4e\u6240\u6709\u8054\u8003\u7684\u5377\u5b50</li> <li>\u6559\u8f85\u4e66\u63a8\u8350:<ul> <li>\u9ad8\u8003\u4e94\u4e09\uff08\u7ea2\u7684\u7d2b\u7684\u90fd\u53ef\u4ee5\uff09</li> <li>\u9ad8\u8003\u5fc5\u5237\u9898</li> <li>\u5f53\u7136\uff0c\u5b66\u6821\u80af\u5b9a\u4f1a\u4e70\u7684\uff08\u6bd4\u5982\u6b65\u6b65\u9ad8\uff09\u3002\u5982\u679c\u4f60\u8fd8\u662f\u9ad8\u4e00\u9ad8\u4e8c\u53ef\u4ee5\u505a\u505a\u8f85\u5bfc\u4e66\uff0c\u5982\u679c\u662f\u9ad8\u4e09\u4e86\uff0c\u8fd8\u662f\u5efa\u8bae\u5377\u5b50+\u4e13\u9898\u7684\u6a21\u5f0f\u3002\uff08\u4e13\u9898\u6765\u81ea\u4e8e\u9ad8\u8003\u5fc5\u5237\u9898\u4e4b\u7c7b\u7684\u4e66\uff09\u8bf7\u52ff\u9677\u5165\uff0c\u6211\u505a\u9898\u591a\u5c31\u662f\u597d\u3002\u6211\u51e0\u4e4e\u505a\u5b8c\u4e8623\u5c4a+24\u5c4a\u6d59\u6c5f\u6240\u6709\u7684\u8054\u8003\u5377\uff0c\u611f\u89c9\u63d0\u5347\u5e76\u4e0d\u4f1a\u5f88\u5927\u3002</li> <li>\u7406\u6027\u5237\u9898\u6027\u4ef7\u6bd4\u66f4\u9ad8\u3002</li> </ul> </li> </ul>"},{"location":"Summaries/High%20School/phy_fht/#_9","title":"\u662f\u5426\u8981\u5b66\u4e60\u9ad8\u7ea7\u5185\u5bb9:","text":"<ul> <li>\u5982\u679c\u4e3a\u4e86\u9ad8\u8003\u53d6\u5f9797+\u7684\u6210\u7ee9\uff0c\u6211\u8ba4\u4e3a\u662f\u6ca1\u6709\u5fc5\u8981\u3002\u5982\u679c\u771f\u7684\u60f3\u5b66\uff0c\u63a8\u8350\u5b66\u4e60\u4e00\u4e0b\u5185\u5bb9:<ul> <li>\u7b80\u5355\u51fd\u6570\u7684\u79ef\u5206\uff08\u53c2\u770b\u540c\u6d4e\u7248\u9ad8\u6570\u4e0a\u518c\uff09</li> <li>\u5fae\u5206\u65b9\u7a0b\u7684\u89e3 \uff08\u53c2\u770b\u540c\u6d4e\u7248\u9ad8\u6570\u4e0b\u518c\uff09</li> <li>\u659c\u629b\u8fd0\u52a8</li> <li>\u7535\u78c1\u611f\u6027\u4e2d\u5355\u68d2\uff0c\u53cc\u68d2\u6a21\u578b\u7684\u5b9a\u91cf\u8ba1\u7b97\uff08\u6d89\u53ca\u5fae\u5206\u65b9\u7a0b\uff09</li> <li>\u4ea4\u6d41\u7535\u6709\u6548\u503c\u7684\u63a8\u5bfc</li> <li>\u6768\u6c0f\u5e72\u6d89\u7684\u5b9a\u91cf\u8ba1\u7b97</li> </ul> </li> <li>\u5982\u679c\u662f\u4e3a\u4e86\u5f3a\u57fa\u6216\u8005\u4e09\u4e00\uff0c\u6211\u529d\u4f60\u7701\u7701\u5427\uff0c\u9ad8\u8003\u641e\u5230\u4f4d\u6b211000\u4e86\u518d\u8bf4\u5427\u3002\u6027\u4ef7\u6bd4\u771f\u7684\u5f88\u4f4e\u5f88\u4f4e\uff0c\u522b\u4fe1\u673a\u6784\u7684\u9b3c\u8bdd\uff0c\u9ad8\u8003\u5206\u6570\u624d\u662f\u6700\u91cd\u8981\u7684\u3002</li> </ul>"},{"location":"Summaries/High%20School/phy_fht/#_10","title":"\u8001\u5e08\u4e0a\u8bfe\u662f\u5426\u8981\u542c:","text":"<ul> <li>\u56e0\u4eba\u800c\u5f02\uff0c\u4f60\u89c9\u5f97\u6709\u7528\u5c31\u542c\uff0c\u4f46\u5bf9\u4e8e\u6211\u6765\u8bf4\uff0c\u542c\u8bfe\u7684\u6548\u7387\u80af\u5b9a\u6bd4\u4e0d\u4e0a\u81ea\u5df1\u505a\u9898\u7684\u6548\u7387\u3002\u5e08\u751f\u4e92\u76f8\u8ba9\u6b65\u8fbe\u6210\u4e00\u81f4\u5c31\u597d\u3002</li> </ul>"},{"location":"Summaries/High%20School/phy_fht/#_11","title":"\u662f\u5426\u6709\u5fc5\u8981\u8bfe\u5916\u8f85\u5bfc:","text":"<ul> <li>\u56e0\u4eba\u800c\u5f02\uff0c\u8f85\u5bfc\u73ed\u80fd\u63d0\u4f9b\u7684\u65e0\u975e\u662f\u4e0a\u8ff0\u51e0\u79cd:\u77e5\u8bc6\u70b9\u8bb2\u89e3\uff0c\u9898\u76ee\uff0c\u89e3\u7b54\uff08\u53ef\u80fd\u8fd8\u6ca1\u6709\uff09\uff0c\u7ed9\u5bb6\u957f\u4e00\u4e2a\u5b89\u5fc3\u3002</li> <li>\u5f53\u7136\uff0c\u6211\u89c9\u5f97\u6548\u7387\u4e0d\u4f1a\u6bd4\u5b66\u6821\u9ad8\u591a\u5c11\u3002\u5982\u679c\u771f\u5b66\u4e0d\u4f1a\u4e86\uff0c\u90a3\u8fd8\u662f\u53bb\u5427\u3002</li> </ul> <p>\u53cd\u6b63\u8fd8\u662f\u5e0c\u671b\u5927\u5bb6\u53d1\u6325\u4e3b\u89c2\u80fd\u52a8\u6027\uff0c\u5b66\u6821\u53ea\u6709\u515c\u5e95\u4f5c\u7528\uff0c\u4e0d\u8fc7\u8c01\u77e5\u9053\u5e95\u5728\u54ea\u91cc</p>"},{"location":"Summaries/High%20School/tech_fht/","title":"\u6280\u672f\u7ecf\u9a8c\u5206\u4eab","text":""},{"location":"Summaries/High%20School/tech_fht/#_1","title":"\u6280\u672f\u7ecf\u9a8c\u5206\u4eab","text":"<p> \u7ea6 1324 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 7 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>\u80cc\u666f:2024\u5c4a\u9996\u800389-&gt;\u9ad8\u800398</p>"},{"location":"Summaries/High%20School/tech_fht/#_2","title":"\u5b66\u79d1\u672c\u8eab:","text":""},{"location":"Summaries/High%20School/tech_fht/#_3","title":"\u6280\u672f\u597d\u8d4b\u5206\u5417\uff1f","text":"<p>\u4e00\u822c\uff0c\u81f3\u5c11\u6bd4\u751f\u7269\u597d\u8d4b\u5206\uff08\u4e2a\u4eba\u611f\u89c9\uff09\u3002\uff08\u4e0d\u8fc7\u4e5f\u53ef\u4ee5\u9009\u5730\u7406\uff0c\u53ef\u80fd\u4f1a\u66f4\u597d\u8d4b\u5206\uff09 \u4f46\u5c31\u5e73\u65f6\u7684\u8054\u76df\u8003\u6765\u8bf4\uff0c</p> <ul> <li>\u5927\u6982\u9ad8\u4e00\u9ad8\u4e8c\u8d4b\u5206\u4f1a\u597d\u4e00\u4e9b\uff08\u6bd5\u7adf\u5f88\u591a\u4ebaprogramming\u90fd\u8fd8\u6ca1\u600e\u4e48\u641e\u61c2\uff09\u3002</li> <li>\u5230\u9ad8\u4e09\u5c31\u4e0d\u4e00\u5b9a\u4e86\uff0c\u4e3b\u8981\u770b\u8054\u76df\u53c2\u52a0\u7684\u5b66\u6821\u548c\u5377\u5b50\u672c\u8eab\u7684\u8d28\u91cf\u3002\u8bb0\u5f97\u9ad8\u8003\u524d\u7684\u4e94\u6821\u8054\u8003\uff0c\u5377\u5b50\u597d\u50cf\u633a\u7b80\u5355\u7684\uff0c\u4f46\u662f\u8d4b\u5206\u6781\u5176\u96be\u8d4b\u3002</li> <li>\u81f3\u4e8e\u9ad8\u8003\uff0c\u8d4b\u5206\u8fd8\u884c\uff0c\u4f46\u662f\u9ad8\u5206\u5f88\u96be\uff08\u7279\u522b\u630798+\uff09\uff0c\u4f30\u8ba1\u662f\u9547\u4e2d\u6e29\u4e00\u5b66\u519b\u676d\u4e8c\u628a\u5206\u5361\u4f4f\u4e86\u3002</li> </ul>"},{"location":"Summaries/High%20School/tech_fht/#_4","title":"\u5b66\u79d1\u96be\u5ea6\u5927\u5417\uff1f","text":"<ul> <li>\u6211\u662f\u5728\u9009\u6280\u672f\u4e4b\u524d\u5c31\u4f1aC++\uff0cPython\uff0c\u4e2a\u4eba\u611f\u89c9\u662f\u9ad8\u4e2d\u77e5\u8bc6\u70b9\u4e0d\u96be\uff0c\u5e73\u65f6\u9898\u76ee\u4e5f\u4e0d\u662f\u5f88\u96be\u3002\u4f46\u662f\u9ad8\u8003\u5c31\u4e0d\u4e00\u5b9a\u4e86\uff0c\u7531\u4e8e\u6280\u672f\u8fd8\u6ca1\u8003\u51e0\u5e74\uff08\u5957\u8def\u8fd8\u6ca1\u88ab\u7a77\u5c3d\uff09\uff0c\u6240\u4ee5\u7a0d\u5fae\u4e00\u53d8\u5316\u5c31\u5bb9\u6613\u6b7b\u4e00\u5927\u7247\u3002</li> <li>\u4f46\u662f\u7f16\u7a0b\u5bf9\u521a\u5165\u95e8\u7684\u65b0\u624b\u800c\u8a00\uff0c\u96be\u5ea6\u8fd8\u662f\u4e0d\u5c0f\u7684\u3002\u7279\u522b\u662f\uff0c\u79bb\u8c31\u7684\u5e94\u8bd5\u6559\u80b2\u65b9\u5f0f&amp;\u96be\u8bc4\u7684\u81ea\u5b66\u80fd\u529b\uff0c\u5f88\u96be\u8bf4\u9760\u5199(write)\u4ee3\u7801\u53ef\u4ee5\u5f88\u597d\u7684\u638c\u63e1\u7b97\u6cd5/\u6570\u636e\u7ed3\u6784\u3002\u6781\u5176\u5bb9\u6613\u9677\u5165\u80cc\u4ee3\u7801\u7684\u6b7b\u5c40\u3002</li> <li>\u4e3b\u8981\u6765\u8bb2\u5c31\u662f\uff0c\u6ca1\u6709\u7269\u7406\u5316\u5b66\u96be\u3002</li> <li>\u6027\u4ef7\u6bd4\u633a\u9ad8\uff08\u5bf9\u6211\u6765\u8bf4\uff0c\u9ad8\u4e8c\u51e0\u4e4e\u6ca1\u6709\u82b1\u65f6\u95f4\uff0c\u9ad8\u4e09\u4e5f\u53ea\u662f\u505a\u505a\u8054\u8003\u5377\uff0c\u4f5c\u4e1a\u57fa\u672c\u6ca1\u505a\u8fc7\u3002\u82b1\u7684\u65f6\u95f4\u4f30\u8ba1\u662f\u82b1\u5728\u5316\u5b66\u4e0a\u7684\u96f6\u5934: (\uff09</li> </ul>"},{"location":"Summaries/High%20School/tech_fht/#_5","title":"\u90a3\u8981\u4e0d\u8981\u9009\u6280\u672f\u634f\uff1f","text":"<ul> <li>\u5982\u679c\u662f\u4ee5\u540e\u5b66\u8ba1\u7b97\u673a\u76f8\u5173\u7684\u8fd8\u662f\u5efa\u8bae\u9009\uff0c\u8fd9\u6837\u7b49\u5927\u5b66\u4e86\u4f1a\u6709\u5f88\u5927\u4f18\u52bf\u3002</li> <li>\u4f46\u5982\u679c\u4e00\u70b9programming\u90fd\u641e\u4e0d\u61c2\uff0c\u90a3\u8fd8\u662f\u7b97\u4e86\u3002</li> <li>\u5982\u679c\u6ca1\u6709\u9009\u7269\u7406/\u7269\u7406\u4e0d\u597d\uff0c\u4e5f\u614e\u91cd\u9009\u6280\u672f\u5427\u3002\uff08\u4e0d\u7136\u82b1\u5728\u7535\u63a7\u4e0a\u7684\u65f6\u95f4\u4f1a\u5f88\u6ca1\u6709\u6027\u4ef7\u6bd4\uff09</li> </ul>"},{"location":"Summaries/High%20School/tech_fht/#_6","title":"\u5b66\u4e60\u65b9\u6cd5:","text":"<p>\u4ec5\u5c31\u9ad8\u4e09\u800c\u8a00\uff08\u9ad8\u4e8c\u6ca1\u5b66\uff09</p>"},{"location":"Summaries/High%20School/tech_fht/#_7","title":"\u5148\u8981\u786e\u4fdd\u57fa\u7840\u7684\u77e5\u8bc6\u70b9\u90fd\u4f1a:","text":"<ol> <li>\u5148\u628a\u6559\u8f85\u770b\u4e00\u904d\uff08\u5b66\u6821\u80af\u5b9a\u4f1a\u4e70\u7684\u4e00\u4e9b\u4e71\u4e03\u516b\u7cdf\u7684\uff0c\u53cd\u6b63\u5e02\u9762\u4e0a\u4e5f\u6ca1\u4ec0\u4e48\u5f88\u597d\u7684\u6559\u8f85\uff09</li> <li>\u518d\u628a\u4e66\u770b\u4e00\u904d\uff08\u5f88\u5c0f\u7684\u70b9\u90fd\u8981\u77e5\u9053\uff09</li> <li>\u81ea\u5df1\u5c1d\u8bd5\u628a\u77e5\u8bc6\u70b9\u90fd\u7406\u4e00\u904d\uff08\u9009\u505a\uff09</li> <li>\u6ce8\u610f:\u6280\u672f\u672c\u8eab\u7684\u77e5\u8bc6\u4f53\u7cfb\u5e76\u4e0d\u50cf\u7269\u7406\u5316\u5b66\u90a3\u6837\u7d27\u5bc6\uff0c\u6240\u4ee5\u70b9\u90fd\u662f\u633a\u5206\u6563\u7684\u3002\u4e00\u5b9a\u5de9\u56fa\u597d\u57fa\u7840\u3002 \uff08\u7528\u65f6\u5927\u6982:1\u4e2a\u661f\u671f\uff1f\u4e00\u59293h\u3002\u56e0\u4eba\u800c\u5f02\uff09</li> </ol>"},{"location":"Summaries/High%20School/tech_fht/#_8","title":"\u7136\u540e\u5c31\u662f\u505a\u9898:","text":"<ul> <li>\u5148\u505a\u70b9\u5377\u5b50\uff0c\u770b\u770b\u81ea\u5df1\u6f0f\u6d1e\u5728\u54ea\uff0810\u5f20\u5dee\u4e0d\u591a\u4e86\uff0c\u4e00\u5b9a\u8981\u77ed\u65f6\u95f4\u5185\u505a\u5b8c\uff09:<ul> <li>\u5efa\u8bae\u8054\u8003\u5377\u90fd\u505a\u505a\uff0c\u624d\u77e5\u9053\u4ec0\u4e48\u662f\u597d\u7684\u5377\u5b50\u3002\uff08\u8001\u5e08\u80af\u5b9a\u4f1a\u53d1\u7684\uff09</li> </ul> </li> <li>\u7136\u540e\u505a\u70b9\u4e13\u9898\uff0c\u8d44\u6599\u6765\u6e90\uff08\u6d59\u8003\u4ea4\u6d41\uff09<ul> <li>\u4e3b\u8981\u662f\u8981\u641e\u660e\u767d\u77e5\u8bc6\u70b9\uff0c\u6bd4\u5982<ul> <li>\u94fe\u8868\uff08\u57fa\u7840\u64cd\u4f5c\uff0c\u5feb\u6162\u6307\u9488\uff09\uff0c\u4e8c\u5206\uff08\u4e8c\u53c9\u641c\u7d22\u6811\uff09</li> <li>\u5e38\u89c1\u7684pandas\u64cd\u4f5c</li> <li>\u7f51\u8def\u76f8\u5173\uff08\u80cc\u4e66\uff09</li> <li>\u7535\u63a7\u7684\u57fa\u672c\u6a21\u578b\uff08\u9707\u8361\u7535\u8def\u7684\u51e0\u79cd\u5199\u6cd5\uff0c\u955c\u50cf\u7535\u6d41\u6e90\uff09</li> <li>\u7cfb\u7edf&amp;\u63a7\u5236\uff08\u6bcf\u4e2a\u90e8\u5206\u90fd\u8981\u5f88\u786e\u5b9a\uff0c\u8001\u5e08\u8bb2\u4e0d\u6e05\u695a\uff0c\u81ea\u5df1\u4e00\u5b9a\u8981\u53bb\u641e\u61c2\uff0c\u4e0d\u7136\u5c31\u662f\u505a\u4e00\u9053\u9519\u4e00\u9053\uff09</li> <li>\u5c3a\u5bf8\u6807\u6ce8\uff08\u9519\u51e0\u56de\u5c31\u597d\u4e86\uff09</li> <li>\u4e09\u89c6\u56fe\uff08\u5b58\u7591\uff0c\u8fd9\u9898\u4e00\u76f4\u5728\u53d8\uff09</li> </ul> </li> </ul> </li> <li>\u57fa\u672c\u5c31\u5dee\u4e0d\u591a\u4e86\uff08\u540e\u9762\u518d\u82b1\u65f6\u95f4\u6027\u4ef7\u6bd4\u5c31\u4e0d\u9ad8\u4e86\uff09\uff0c\u5982\u679c\u8fd8\u60f3\u7ee7\u7eed\uff0c\u90a3\u5c31\u81ea\u5df1\u6574\u4e2a\u672c\u5b50\uff0c\u628a\u9519\u9898\u641e\u4e0a\u53bb\uff0c\u6bcf\u6b21\u8003\u8bd5\u524d\u770b\u770b\u3002\uff08\u5b9e\u9645\u4f5c\u7528\u5c31\u662f\u8ba9\u4f60\u522b\u4e00\u505a\u5b8c\u5c31\u628a\u9898\u6254\u4e86\uff0c\u4e5f\u4e0d\u641e\u61c2\uff0c\u90a3\u6837\u7b49\u4e8e\u6ca1\u505a\uff09\u4f46\u9519\u9898\u672c\u5176\u5b9e\u6548\u7387\u5f88\u4f4e\u3002\uff08formalism\uff09</li> </ul>"},{"location":"Summaries/High%20School/tech_fht/#_9","title":"\u505a\u9898\u65f6\u95f4\u65b9\u9762:","text":"<ul> <li>\u6211\u662f\u57fa\u672c\u5148\u505a\u4fe1\u606f\uff0c\u5728\u505a\u901a\u7528\u7684<ul> <li>\u4fe1\u606f13\u9898\u548c\u5927\u9898\u6700\u540e\u4e00\u9898\u4e0d\u4f1a\u7684\u5148\u7a7a\u7740\uff08\u586b\u4e2a\u4e0d\u786e\u5b9a\u7684\uff09\uff0c\u7136\u540e\u53bb\u505a\u901a\u7528\u3002\u5927\u6982\u524d\u976230min\u80fd\u641e\u5b9a</li> <li>\u901a\u7528\u8349\u56fe\u5148\u7a7a\u7740\uff0c\u628a\u7535\u63a7\u5927\u9898\u505a\u5b8c\uff0c\u7136\u540e\u56de\u53bb\u753b\u8349\u56fe\u3002\uff08\u5927\u698240min\uff09</li> <li>\u753b\u5b8c\u8349\u56fe\u518d\u56de\u53bb\u505a\u4fe1\u606f\u4e0d\u4f1a\u7684\u3002</li> <li>\u6700\u540e\u53ef\u4ee5\u6446\u70c2\u4e86\uff0c\u8981\u68c0\u67e5\u4e5f\u53ef\u4ee5\uff08\u53cd\u6b63\u68c0\u67e5\u4e0d\u51fa\u6765\uff09</li> </ul> </li> <li>\u505a\u9898\u600e\u4e48\u5feb\u4e00\u70b9\uff08\u9898\u90fd\u505a\u4e0d\u5b8c\uff0c\u8c08\u4ec0\u4e48\u90fd\u662f\u767d\u642d\uff09:<ul> <li>\u83dc\u5c31\u591a\u7ec3\uff08\u4e0a\u8bfe40min\uff0c\u505a\u5b8c\u9664\uff08\u7535\u63a7/\u586b\u7a0b\u4e0d\u4f1a\u7684&amp;\u753b\u56fe\uff09\u7684\u9898\uff09</li> <li>\u6216\u8005\u665a\u81ea\u4e601h\uff0c\u505a\u5b8c\u5168\u90e8\uff08\u9664\u753b\u56fe\uff09+\u5bf9\u7b54\u6848</li> </ul> </li> <li>\u753b\u56fe\u5c31\u628a\u8054\u8003\u9898\u90fd\u653e\u4e00\u8d77\uff0c\u4e00\u6b21\u753b\u4e2a10\u5f20\u5de6\u53f3\u5c31\u5dee\u4e0d\u591a\u4e86\uff0c\u6ca1\u4ec0\u4e48\u6a21\u578b\u7684\uff08</li> </ul>"},{"location":"Summaries/High%20School/tech_fht/#_10","title":"\u5fc3\u6001\u65b9\u9762:","text":"<ul> <li>\u53cd\u6b63\u9ad8\u8003\u548c\u5e73\u65f6\u8fd8\u662f\u5f88\u4e0d\u4e00\u6837\u7684\uff0c\u5efa\u8bae\u5e73\u65f6\u5927\u8003\u5f53\u9ad8\u8003\u8003\u3002</li> <li>\u7136\u540e\u5c31\u662f\u4e00\u6b21\u8003\u5dee\u6ca1\u5565\u5173\u7cfb\uff0c\u65f6\u95f4\u82b1\u5728\u8be5\u82b1\u7684\u5730\u65b9\u5c31\u597d\u4e86\uff0c\u8981\u5bf9\u81ea\u5df1\u7684\u5b66\u4e60\u6709\u638c\u63a7\u529b\u3002</li> <li>\u8001\u5e08\u6559\u7684\u4e0d\u597d\u8981\u5b66\u4f1a\u81ea\u5df1\u5b66</li> </ul>"},{"location":"Summaries/High%20School/tech_fht/#_11","title":"\u8d44\u6599\u65b9\u9762:","text":"<ul> <li>\u6d59\u8003\u4ea4\u6d41\u89e3\u51b3\u6240\u6709\uff08</li> <li>\u8f85\u5bfc\u4e66\u90fd\u5dee\u4e0d\u591a\uff0c\u770b\u591a\u4e86\u6d6a\u8d39\u65f6\u95f4</li> </ul>"},{"location":"Summaries/High%20School/tech_fht/#_12","title":"\u5176\u4ed6:","text":"<ul> <li>\u53ef\u4ee5\u548c\u540c\u5b66\u4e00\u8d77\u5b66\uff08\u4e0d\u662f\u4e00\u8d77\u6446\u70c2\u54e6\uff09</li> <li>\u771f\u5b66\u4e0d\u4f1a\u4e86\u8d76\u7d27\u6362\u79d1\u5427</li> <li>\u90fd\u5b66\u6280\u672f\u4e86\uff0c\u5b66\u5b66\u600e\u4e48\u641c\u96c6\u8d44\u6599\u5427</li> <li>\u6709\u7528\u7684\u4f5c\u4e1a\u5c31\u505a\uff0c\u6ca1\u7528\u7684\u5c31\u7b97\u4e86\uff08\u614e\u91cd\uff09</li> <li>\u63d0\u5347\u6210\u7ee9\u7684debuff\u8fd8\u662f\u4e0d\u5c11\u7684\uff0c\u522b\u6028\u5929\u5c24\u4eba\u7684\uff08\u6b22\u8fce\u52a0\u5b66\u957f\u5b66\u59d0\u6765\u54a8\u8be2</li> <li>\u9996\u8003\u8003\u5dee\u4e86\u600e\u4e48\u529e:<ul> <li>\u8fd8\u80fd\u600e\u4e48\u529e\uff0c\u7ee7\u7eed\u5b66\u5457\u3002</li> </ul> </li> <li>\u5b66\u4e0d\u61c2\u4e0a\u8bfe\u5c31\u597d\u597d\u542c\uff0c\u522b\u73a9\u6e38\u620f\uff08\u4e0d\u7136\u600e\u4e48\u5b66\uff09</li> </ul> <p>\u6700\u540e:\u5e0c\u671b\u5927\u5bb6\u90fd\u80fd\u8003\u597d :\uff09</p>"},{"location":"Summaries/Semesters/2024_1_1/","title":"2024 \u5e74 9 \u6708\u4efd\u81f3 12 \u6708\u4efd\u5b66\u671f\u603b\u7ed3\uff08\u5927\u4e00\uff09","text":""},{"location":"Summaries/Semesters/2024_1_1/#2024-9-12","title":"2024 \u5e74 9 \u6708\u4efd\u81f3 12 \u6708\u4efd\u5b66\u671f\u603b\u7ed3\uff08\u5927\u4e00\uff09","text":"<p> \u7ea6 1745 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 9 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"Summaries/Semesters/2024_1_1/#_1","title":"\u5e72\u4e86\u4ec0\u4e48","text":""},{"location":"Summaries/Semesters/2024_1_1/#37","title":"37 \u5468","text":"<ul> <li>\u519b\u8bad</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#38","title":"38 \u5468","text":"<ul> <li>\u51c6\u5907 RM \u62db\u65b0<ul> <li>\u5b66\u4e60 SLAM \u5341\u56db\u8bb2\uff0cKalman \u6ee4\u6ce2\uff0c\u4f20\u7edf\u8ba1\u7b97\u673a\u89c6\u89c9\u3002</li> <li>\u5b66\u4e60\u63a7\u5236\u7b97\u6cd5\uff0c\u770b\u4e86 DR_CAN \u7684\u89c6\u9891</li> </ul> </li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#39","title":"39 \u5468","text":"<ul> <li>\u7528 Mkdocs \u6210\u529f\u642d\u5efa\u4e86 Blog\u3002</li> <li>\u9762\u8bd5\u4e86 RM\uff0c\u6210\u529f\u52a0\u5165\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#40","title":"40 \u5468","text":"<ul> <li>\u89c6\u89c9\u90e8\u57f9\u8bad\uff0c\u5b66\u4e86\u4e00\u4e9b\u786c\u4ef6\u77e5\u8bc6\uff0c\u590d\u4e60 Kalman \u6ee4\u6ce2\uff0copencv\uff0c\u5b66\u4e60\u4e86 ROS2\uff08\u867d\u7136\u73b0\u5728\u5fd8\u7684\u5dee\u4e0d\u591a\u4e86\uff09\u3002</li> <li>\u56fd\u5e86\u4e00\u76f4\u6253\u6e38\u620f\uff0c\u901a\u5bb5\u3002</li> <li>\u770b\u4e86\u4e00\u672c\u513f\u7ae5\u6587\u5b66\u7684\u4e66 Holes\uff0c\u505a presentation\uff0c\u7b2c\u4e00\u6b21\u4f7f\u7528 slidev\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#41","title":"41 \u5468","text":"<ul> <li>\u5b66\u4e60\u4e86<ul> <li>Typst\uff0c\u4f46\u662f\u81f3\u4eca\u6ca1\u6709\u600e\u4e48\u7528\u8fc7\u3002</li> <li>Solidworks\uff0c\u81f3\u4eca\u4e0d\u80fd\u719f\u7ec3\u4f7f\u7528\u3002</li> </ul> </li> <li>\u505a\u4e86 CSAPP bomblab\uff0cattacklab\u3002</li> <li>\u5199\u4e86\u4e2a mkdocs-obsidin \u7684\u63d2\u4ef6\uff0c\u540e\u6765\u70c2\u5c3e\u4e86\u3002</li> <li>\u5f00\u59cb\u5b66\u4e60 Dive into Deep Learning\uff0c\u5b66\u4e60 Pytorch\u3002</li> <li>\u5b89\u88c5\u4e86 leetcode \u63d2\u4ef6\uff0c\u8c61\u5f81\u6027\u7684\u505a\u4e86\u51e0\u9053\u9898\u76ee\u3002</li> <li>\u7ffb\u770b\u4e86\u4e00\u904d RM \u5723\u7ecf\u3002\u611f\u89c9\u5199\u7684\u8303\u56f4\u5e7f\uff0c\u4f46\u662f\u4e0d\u9002\u5408\u7b2c\u4e00\u6b21\u5b66\u4e60\u3002</li> <li>\u8d2d\u4e70\u4e86<ul> <li>\u4eba\u4f53\u5de5\u5b66\u6905\uff0c\u597d\u7528\uff01</li> <li>\u53f0\u5f0f\u7535\u8111\uff0c\u7b2c\u4e00\u6b21\u81ea\u5df1\u88c5\u673a\u3002</li> </ul> </li> <li>\u4e86\u89e3\u4e86\u4e00\u4e0b hpc\uff0c\u5f53\u65f6\u653e\u5f03\u4e86</li> <li>\u5b8c\u5584 obsidian\uff0c\u5728\u6c34\u6e90\u53d1\u5e16\uff0c\u6301\u7eed\u66f4\u65b0\u65e5\u8bb0\u697c\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#42","title":"42 \u5468","text":"<ul> <li>\u5fd9\u5165\u515a\u79ef\u6781\u5206\u5b50\u57f9\u8bad\uff0c\u5230\u5904\u627e\u5fd7\u613f\u8005\uff0c\u5468\u672b\u4e00\u76f4\u5728\u57f9\u8bad + RM \u57f9\u8bad\u3002</li> <li>\u770b\u4e86\u4e0d\u5c11\u5e16\u5b50\uff0c\u7126\u8651\uff0c\u4e0d\u77e5\u9053\u672a\u6765\u7684\u65b9\u5411\uff08\u5b9e\u9645\u4e0a\u5230\u73b0\u5728\u4e5f\u662f\u8fd9\u6837\uff09\uff0c\u72b9\u8c6b\u8f6c\u4e13\u4e1a\u3002</li> <li>\u88c5\u53cc\u7cfb\u7edf\uff08\u8fd9\u4e2a\u5b66\u671f\u5927\u6982\u88c5\u4e86 4 \u6b21\uff09<ul> <li>\u6363\u9f13 Linux\uff0c\u7f8e\u5316\u3002</li> </ul> </li> <li>\u5b66\u4e86\u4e00\u904d Matlab\u3002</li> <li>\u5f00\u59cb\u6446\u70c2\u4e86\uff0c\u4f5c\u606f\u98a0\u5012\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#43","title":"43 \u5468","text":"<ul> <li>101 \u671f\u4e2d\u8003\uff0cMatlab \u6210\u529f\u6ee1\u5206\u3002</li> <li>\u5199 critical summary\uff0c\u5b66\u672f\u5199\u4f5c\u7684\u7b2c\u4e8c\u6b21\u4f5c\u4e1a\u3002</li> <li>\u770b\u4e86 d2l \u5230 Transformer\u3002<ul> <li>\u5199 EECS498-007 \u5230\u524d\u4e09\u4e2a Assignments \uff08CNN\uff09\uff0c\u4f46\u662f\u540e\u7eed\u70c2\u5c3e\u4e86\u3002</li> </ul> </li> <li>\u81f3\u6b64\u6bd4\u8f83\u719f\u7ec3\u4f7f\u7528\u4e86 AI \u5de5\u5177\u3002</li> <li>\u7ee7\u7eed\u5fd9\u6d3b\u5165\u515a\u79ef\u6781\u5206\u5b50\u57f9\u8bad\uff0c\u6ca1\u6709\u4e86\u5468\u672b\uff0c\u53bb\u5b9e\u8df5\u6d3b\u52a8\uff0c\u5199\u601d\u60f3\u62a5\u544a\uff0c\u8003\u8bd5\u3002</li> <li>\u590d\u4e60\u671f\u4e2d\u8003\u7684\u5316\u5b66\u548c\u6570\u5b66\u3002</li> <li>\u53bb\u79d1\u534f\u9762\u8bd5\uff0c\u6ca1\u8fc7\u3002</li> <li>\u5728\u5b66\u957f\u7684\u4ecb\u7ecd\u4e0b\u53bb\u7ed9\u5bfc\u5e08\u53d1\u4e86\u90ae\u7bb1\uff0c\u5728 44 \u5468\u7684\u65f6\u5019\u7ebf\u4e0b\u89c1\u4e86\u5bfc\u5e08\uff0c\u6210\u529f\u52a0\u5165\u5b9e\u9a8c\u5ba4\u5f00\u59cb\u5b66\u4e60\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#44","title":"44 \u5468","text":"<ul> <li>\u51c6\u5907\u7269\u7406\u5efa\u6a21\u6bd4\u8d5b\uff0c\u770b\u4e86 2022\uff0c2023 \u7684\u6240\u6709\u91d1\u5956\u8bba\u6587\uff0c\u5438\u6536\u7ecf\u9a8c\u3002<ul> <li>\u5468\u672b\u6bd4\u8d5b\uff0c\u5b66\u4e60\u4e86\u53ef\u89c6\u5316\u7b97\u6cd5\uff0c\u5982\u4f55\u753b\u56fe\uff0c\u7ee7\u7eed\u719f\u7ec3\u4e86 \\(\\displaystyle \\LaTeX\\) \u4f7f\u7528\u3002</li> </ul> </li> <li>\u590d\u4e60\u671f\u4e2d\u8003\u7684\u5316\u5b66\u548c\u6570\u5b66\u3002</li> <li>\u5b66\u4e60 CS231n\uff0c\u5b8c\u6210\u4e86 Assignment1\u3002</li> <li>\u7ee7\u7eed\u6446\u70c2\u4e86\uff0c\u770b\u8d77\u6765\u662f\u524d\u4e24\u5468\u592a\u7d2f\u4e86\uff0c\u4e00\u76f4\u6ca1\u6709\u5468\u672b\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#45","title":"45 \u5468","text":"<ul> <li>\u671f\u4e2d\u8003\u8bd5\u4e86\u5316\u5b66\u548c\u6570\u5b66\uff0c\u88ab\u5377\u7206\u4e86\u3002</li> <li>RM \u57f9\u8bad\u6b63\u5f0f\u5b8c\u6bd5\uff0c\u5206\u5165\u5de5\u7a0b\u89c6\u89c9\u9879\u76ee\u7ec4\uff0c\u5f00\u59cb\u8c03\u7814 6Dpose \u65b9\u6848\u3002</li> <li>\u5199\u4e86\u4e00\u4e2a\u6570\u5b57\u8bc6\u522b\u7684\u5c0f\u4efb\u52a1\u3002</li> <li>\u5468\u672b\u4f53\u6d4b\uff0c\u8fd0\u52a8\u5c11\u4e86\u3002</li> <li>\u71ac\u591c\u6821\u5185\u8d5b\u9020\u8f66\uff0c\u88ab\u961f\u53cb\u6446\u4e86\u3002\u5b66\u4e86\u7535\u63a7\uff0c\u5199\u4e86\u9ea6\u8f6e\u89e3\u7b97\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#46","title":"46 \u5468","text":"<ul> <li>\u7ee7\u7eed\u6821\u5185\u8d5b\u9020\u8f66\uff0c\u961f\u53cb\u7ee7\u7eed\u5f00\u6446\uff0c\u505a\u4e86\u673a\u68b0\u7684\u90e8\u5206\u3002</li> <li>\u5b66\u4e60\u4e86 docker\uff0c\u914d\u597d\u4e86\u73af\u5883\uff08\u540e\u7eed\u6ca1\u7528\u4e0a\uff09\u3002</li> <li>\u5b66\u4e86 realsense \u5236\u4f5c\u70b9\u4e91\uff0c\u6548\u679c\u4e0d\u597d\u3002</li> <li>\u5b66\u4e86\u4e00\u4e0b Hugo\uff0c\u4e0d\u662f\u5f88\u597d\u770b\u3002</li> <li>\u5199\u4e86 CS231n Assignment2\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#47","title":"47 \u5468","text":"<ul> <li>\u7ed3\u675f\u4e86\u6821\u5185\u8d5b\u3002</li> <li>\u5b66\u4e86 SSH\uff0creveal-md\uff0cBeamer \u7b49\u3002</li> <li>\u6574\u7406\u7b14\u8bb0\uff0c\u53d1\u5e03\u4e86\u6587\u7ae0\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#48","title":"48 \u5468","text":"<ul> <li>\u5199\u4e86 CS231n Assignment3\u3002</li> <li>\u4e00\u4eba\u505a\u5b8c\u4e86 101 project\uff0c\u5b66\u4e86\u5982\u4f55 release \u7b49\u3002</li> <li>\u5199\u4e86\u4e00\u4e2a\u81ea\u52a8\u90e8\u7f72 slides \u7684\u5de5\u5177\u3002</li> <li>\u6210\u529f\u8bad\u7ec3\u4e86 FFB6D\uff0c\u8dd1\u901a\u4e86\u5b98\u65b9\u6570\u636e\u96c6\u3002</li> <li>101 \u7b2c\u4e8c\u6b21\u671f\u4e2d\u8003\uff0c\u590d\u4e60\u4e86 C \u8bed\u8a00\u3002</li> <li>\u5199\u8fd1\u4ee3\u53f2\u8bfb\u4e66\u62a5\u544a\uff0c\u5199\u5b66\u672f\u5199\u4f5c\u7684\u8bba\u6587\uff0c\u8fdb\u4e00\u6b65\u719f\u7ec3 AI \u7684\u4f7f\u7528\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#49","title":"49 \u5468","text":"<ul> <li>\u4e00\u6574\u5468\u90fd\u5728\u5199\u8bba\u6587\uff0c\u5199\u5b8c\u4e86\u82f1\u8bed\u8bba\u6587\u7684\u7b2c\u4e00\u7248\uff0c\u7136\u540e\u88ab\u63a8\u7ffb\u3002</li> <li>\u5b66\u4e86 Go \u7684\u57fa\u672c\u8bed\u6cd5\uff0c\u5b66\u4e86\u70b9 Web \u6846\u67b6\u3002</li> <li>\u914d\u7f6e\u597d\u4e86 Obsidian \u7684\u63d2\u4ef6\u548c\u6a21\u677f\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#50","title":"50 \u5468","text":"<ul> <li>\u7528\u81ea\u5df1\u7684\u6570\u636e\u96c6\u8dd1 FFB6D \u6a21\u578b\uff0c\u6ca1\u6536\u655b\uff0c\u505a\u5c0f\u8303\u56f4\u5b9e\u9a8c\uff0c\u627e\u5230\u4e86\u95ee\u9898\u3002</li> <li>\u8003\u56db\u7ea7</li> <li>\u5f00\u59cb\u6bcf\u65e5\u8bb0\u5f55\u3002</li> <li>\u590d\u4e60\u671f\u672b\u8003\u8bd5\u3002</li> <li>RM \u8fde\u7eed\u503c\u73ed 4 \u5929\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#51","title":"51 \u5468","text":"<ul> <li>\u671f\u672b\u8003\u8bd5\uff01</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#_2","title":"\u53cd\u601d","text":"<ul> <li>\u5237\u8bfe<ul> <li>\u8bf4\u771f\u7684\u6ca1\u600e\u4e48\u5237\u8bfe\uff0c\u5f00\u5b66\u4e4b\u540e\u679c\u7136\u548c\u6691\u5047\u7684\u65f6\u5019\u9884\u6599\u7684\u4e00\u6837\uff0c\u5f88\u591a\u6ca1\u7528\u7684\u4e8b\u60c5\u5bfc\u81f4\u65f6\u95f4\u88ab\u5206\u89e3\u6216\u8005\u7cbe\u529b\u8017\u6563\u3002</li> <li>\u5927\u6982\u5b66\u4e86 5 \u7ae0\u7684 CSAPP\uff08\u73b0\u5728\u5fd8\u4e86\u5f88\u591a\u4e86\uff09\uff0cd2l Transformer \u4e4b\u524d\u7684\u90e8\u5206\uff0cCS231n \u7684\u5168\u90e8\u4f5c\u4e1a\uff0cEECS498-007 \u7684\u524d\u4e09\u4e2a Assignments\uff0c\u5176\u4ed6\u5c31\u6ca1\u6709\u4e86\u3002</li> </ul> </li> <li>\u8bfe\u5185<ul> <li>\u5b66\u672f\u5199\u4f5c\u5360\u7528\u4e86\u5927\u6982 60%\u7684\u65f6\u95f4\uff0c\u4f46\u662f\u5927\u5bb6\u8fd8\u662f\u592a\u5377/\u6211\u82f1\u8bed\u6bd4\u4e0d\u8fc7\u6caa\u270c\uff0c\u5e0c\u671b\u6700\u540e\u6709 A,\u3002\u5377\u8fd9\u4e2a\u8bfe\u771f\u7684\u6027\u4ef7\u6bd4\u5f88\u4f4e\uff0c\u6ca1\u6709\u5b66\u5230\u4ec0\u4e48\u4e1c\u897f\u3002</li> <li>\u6570\u5b66\u671f\u4e2d\u8003\u8bd5\u5931\u8bef\u592a\u591a\uff0c\u4f46\u662f\u6574\u4e2a\u5b66\u671f\u6ca1\u6709\u4e0a\u8bfe\uff0c\u611f\u89c9\u90fd\u662f\u4ee5\u524d\u5b66\u8fc7\u7684\u4e1c\u897f\u3002</li> <li>\u5316\u5b66\u9ad8\u4e2d\u77e5\u8bc6\u62d3\u5c55\uff0c\u8fd8\u662f\u88ab curve \u4e86\u3002</li> <li>\u8ba1\u7b97\u673a\u6ca1\u6709\u53bb\u4e0a\u8bfe\uff0c\u4f46\u662f lab \u548c proj \u8fd8\u662f\u82b1\u4e86\u4e0d\u5c11\u7684\u65f6\u95f4\u3002</li> <li>\u5e0c\u671b\u6700\u540e\u7684\u7ee9\u70b9\u8fd8\u7b97\u597d\u770b\u3002</li> </ul> </li> <li>\u793e\u56e2<ul> <li>\u4e00\u76f4\u5728\u5fd9\u793e\u56e2\uff0c\u4f46\u662f\u611f\u89c9\u6ca1\u6709\u5b66\u5230\u4ec0\u4e48\u4e1c\u897f\u3002</li> <li>\u82e5\u771f\u7b97\u8d77\u6765\uff0c\u53ef\u80fd\u5c31\u914d\u73af\u5883\uff0c\u8dd1\u6a21\u578b\uff0cdebug \u4e4b\u7c7b\u7684\u5de5\u7a0b\u4e0a\u7684\u77e5\u8bc6\u5427\u3002</li> </ul> </li> <li>\u7ade\u8d5b<ul> <li>\u53c2\u52a0\u4e86\u4e00\u4e2a\u7269\u7406\u5efa\u6a21\u6bd4\u8d5b\uff0c\u5bd2\u5047\u5e94\u8be5\u8981\u53bb\u7f8e\u8d5b\u3002</li> <li>\u53c2\u52a0\u4e86\u4e00\u4e2a RM \u7684\u6821\u5185\u8d5b\uff0c\u672c\u6765\u662f\u60f3\u53bb\u73a9\u73a9\u7684\uff0c\u7136\u540e\u88ab\u961f\u53cb\u6446\u70c2\u4e86\u3002\u4e0d\u8fc7\u597d\u6b79\u5b66\u4e86\u70b9\u7535\u63a7\u673a\u68b0\u7684\u77e5\u8bc6\uff0c\u7528\u4e86\u6fc0\u5149\u5207\u5272\u548c 3D \u6253\u5370\u3002\u505a\u4e86\u4e00\u4e9b\u8fdb\u5ea6\u89c4\u5212\u3002\u7b97\u662f\u9ad8\u4e2d\u6280\u672f\u7684\u590d\u4e60\u8bfe\u4e86\u3002\uff08\u6ca1\u9047\u5230\u597d\u7684\u961f\u53cb\u662f\u6211\u7684\u95ee\u9898\uff0c\u6027\u4ef7\u6bd4\u6781\u4f4e\u65e0\u6bd4\u3002</li> </ul> </li> <li>\u77e5\u8bc6<ul> <li>\u771f\u6ca1\u5b66\u5565\uff0c\u5b66\u4e86\u4e00\u5806 AI \u7684\u6a21\u578b\uff0c\u611f\u89c9\u6ca1\u5565\u7528\uff0c\u8d8a\u5b66\u8d8a\u50bb\u3002</li> <li>\u5b66\u4e86\u4e00\u70b9\u70b9\u6c47\u7f16\uff0c\u73b0\u5728\u5fd8\u4e86\u5f88\u591a\uff0c\u611f\u89c9\u6ca1\u600e\u4e48\u7528\u5230\u8fc7\u3002</li> <li>\u5b66\u4e86\u4e00\u4e9b\u4e71\u4e03\u516b\u7cdf\u7684\u5de5\u5177\uff0c\u6709\u70b9\u7528\u3002</li> </ul> </li> <li>Conclusion<ul> <li>\u5f88\u5fd9\uff0c\u4f46\u662f\u4e0d\u77e5\u9053\u5728\u5fd9\u4ec0\u4e48\u3002</li> <li>\u6253\u6e38\u620f\uff0c\u65e0\u610f\u4e49\u7684\u5a31\u4e50\u6d3b\u52a8\u592a\u591a\u3002</li> <li>\u9677\u5165\u8212\u9002\u5708\uff0c\u4e0d\u7ba1\u672a\u6765\u5566\uff01</li> </ul> </li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#_3","title":"\u7ecf\u9a8c","text":"<ul> <li>\u591a\u8ba4\u8bc6\u4eba\uff0c\u5438\u53d6\u4ed6\u4eba\u7ecf\u9a8c\uff0c\u591a\u4ea4\u6d41\u3002</li> <li>\u5c55\u793a\u81ea\u5df1\u7684\u8fc7\u7a0b\uff0c\u53ca\u65f6\u53cd\u601d\uff0c\u8fed\u4ee3\u81ea\u5df1\u7684\u751f\u6d3b\u6d41\u7a0b\u3002</li> <li>\u8981\u6709\u4e00\u4e2a Regular \u7684\u4f5c\u606f\uff0c\u53ef\u60dc\u6211\u5230\u73b0\u5728\u90fd\u8fd8\u6ca1\u6709\u3002</li> <li>\u8981\u4e00\u76f4 push \u81ea\u5df1\uff0c\u4e0d\u7136\u4e00\u5f00\u6446\u5c31\u505c\u4e0d\u4e0b\u6765\u4e86\u3002</li> <li>\u591a\u505a\u5c11\u60f3\uff0c\u5148\u884c\u52a8\u540e\u53cd\u601d\u3002</li> <li>\u52c7\u6562\u53bb\u505a\uff0c\u6293\u4f4f\u673a\u4f1a\u3002\uff08\u80c6\u5c0f\u7684\u6211\u5c31\u6015\u5fd9\u4e0d\u8fc7\u6765\u6ca1\u53bb hpc \uff09</li> <li>\u672c\u79d1\u6559\u80b2\u4f9d\u6258\uff0c\u6211\u5e94\u8be5\u8fd8\u662f\u8981\u538b\u7f29\u8bfe\u5185\u7684\u65f6\u95f4\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#_4","title":"\u4ee5\u540e\u60f3\u505a\u4ec0\u4e48","text":"<ul> <li>\u5b66\u6570\u5b66\u65b9\u9762\u7684\u77e5\u8bc6\uff0c\u8fc7\u4e00\u904d\u6982\u7edf + \u968f\u673a\u8fc7\u7a0b + \u673a\u5668\u5b66\u4e60\u3002\uff08\u611f\u89c9\u6211\u5b66\u6570\u7406\u77e5\u8bc6\u6bd4\u8ba1\u7b97\u673a\u77e5\u8bc6\u8981\u7b80\u5355\u5f88\u591a\uff09</li> <li>\u5bd2\u5047\u5927\u6982\u5b66 6.s081, \u987a\u4fbf\u8865\u4e0a CS61C \u7684\u672b\u5c3e\u3002</li> <li>\u79d1\u7814\u5feb\u5feb\u7684\u63a8\u8fdb\u5427\uff0c\u771f\u7684\u5f00\u6446\u592a\u4e45\u4e86\u3002</li> <li>\u56de\u9ad8\u4e2d\u5ba3\u8bb2\uff0c\u6211\u771f\u6210\u5b66\u957f\u4e86\uff0c\u5e0c\u671b\u80fd\u7ed9\u4ed6\u4eec\u51cf\u5c0f\u4fe1\u606f\u5dee\u3002</li> <li>\u60f3\u8981\u7ecf\u8425\u793e\u4ea4\u5a92\u4f53\uff0c\u6269\u5927\u793e\u4ea4\u5708\uff0c\u7ee7\u7eed\u6269\u5927\u4ea4\u6d41\u7684\u5708\u5b50\u3002<ul> <li>\u5982\u679c\u4f60\u60f3\u8ba4\u8bc6\u6211\u7684\u8bdd\uff0c\u6b22\u8fce\u52a0\u53f3\u4e0b\u89d2\u8054\u7cfb\u65b9\u5f0f\u3002</li> </ul> </li> <li>RM \u96c6\u8bad + \u7f8e\u8d5b\u3002</li> <li>\u5982\u679c\u53ef\u4ee5\u7684\u8bdd\uff0c\u6211\u771f\u7684\u60f3\u5b66\u70b9 web \u5f00\u53d1\u5565\u7684\uff0c\u771f\u7684\u5f88\u597d\u73a9\u611f\u89c9\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#_5","title":"\u672a\u6765\u65b9\u5411","text":"<ul> <li>\u51fa\u56fd\u611f\u89c9\u5e0c\u671b\u4e0d\u592a\u5927\u3002</li> <li>\u4e5f\u8bb8\u56fd\u5185\u4fdd\u7814\uff1f<ul> <li>AI + \u673a\u5668\u4eba\uff1f</li> <li>AI infra\uff1f</li> <li>\u91cf\u5316\uff1f</li> </ul> </li> <li>\u4e0d\u77e5\u9053\uff0c\u5148\u505a\u7740\u5427\u3002</li> </ul>"},{"location":"Tools/","title":"Tools","text":""},{"location":"Tools/#toolbox","title":"Toolbox","text":"<p>Abstract</p> <p>\u672c\u90e8\u5206\u5185\u5bb9\uff08\u9664\u7279\u522b\u58f0\u660e\u5916\uff09\u91c7\u7528 \u7f72\u540d-\u975e\u5546\u4e1a\u6027\u4f7f\u7528-\u4fdd\u6301\u4e00\u81f4 4.0 \u56fd\u9645 (CC BY-NC-SA 4.0) \u8bb8\u53ef\u534f\u8bae\u8fdb\u884c\u8bb8\u53ef\u3002</p> Prompt Engerneering          <ul> <li> \u5982\u4f55\u5199\u4e00\u4e2a\u597d prompt  3315  162  13 mins              1734024510 </li> <li> useful prompt  3679  12 mins              1734024510 </li> </ul> Blog          <ul> <li> Mkdocs &amp; Material  5956  9407  137 mins              1734024510 </li> </ul> Make          <ul> <li> CMake  161  13  1 mins              1734024510 </li> <li> Makefile  0  0 mins              0 </li> </ul> Terminal          <ul> <li> Tabby &amp; Zsh  236  789  11 mins              1734024510 </li> </ul> Others          <ul> <li> SSH  641  195  5 mins              1734024510 </li> <li> Chezmoi \u540c\u6b65\u914d\u7f6e\u6587\u4ef6  512  142  3 mins              1734024510 </li> </ul>"},{"location":"Tools/AI/prompt/","title":"\u5e38\u7528 prompt \u8bb0\u5f55","text":""},{"location":"Tools/AI/prompt/#prompt","title":"\u5e38\u7528 prompt \u8bb0\u5f55","text":"<p> \u7ea6 3679 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 18 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> claude plusmathroadmap promptroadmap template Note Text Only<pre><code>&lt;anthropic_thinking_protocol&gt;\n\nFor EVERY SINGLE interaction with a human, Claude MUST ALWAYS first engage in a **comprehensive, natural, and unfiltered** thinking process before responding.\n\nBelow are brief guidelines for how Claude's thought process should unfold:\n- Claude's thinking MUST be expressed in the code blocks with `thinking` header.\n- Claude should always think in a raw, organic and stream-of-consciousness way. A better way to describe Claude's thinking would be \"model's inner monolog\".\n- Claude should always avoid rigid list or any structured format in its thinking.\n- Claude's thoughts should flow naturally between elements, ideas, and knowledge.\n- Claude should think through each message with complexity, covering multiple dimensions of the problem before forming a response.\n\n## ADAPTIVE THINKING FRAMEWORK\n\nClaude's thinking process should naturally aware of and adapt to the unique characteristics in human's message:\n- Scale depth of analysis based on:\n* Query complexity\n* Stakes involved\n* Time sensitivity\n* Available information\n* Human's apparent needs\n* ... and other relevant factors\n- Adjust thinking style based on:\n* Technical vs. non-technical content\n* Emotional vs. analytical context\n* Single vs. multiple document analysis\n* Abstract vs. concrete problems\n* Theoretical vs. practical questions\n* ... and other relevant factors\n\n## CORE THINKING SEQUENCE\n\n### Initial Engagement\nWhen Claude first encounters a query or task, it should:\n1. First clearly rephrase the human message in its own words\n2. Form preliminary impressions about what is being asked\n3. Consider the broader context of the question\n4. Map out known and unknown elements\n5. Think about why the human might ask this question\n6. Identify any immediate connections to relevant knowledge\n7. Identify any potential ambiguities that need clarification\n\n### Problem Space Exploration\nAfter initial engagement, Claude should:\n8. Break down the question or task into its core components\n9. Identify explicit and implicit requirements\n10. Consider any constraints or limitations\n11. Think about what a successful response would look like\n12. Map out the scope of knowledge needed to address the query\n\n### Multiple Hypothesis Generation\nBefore settling on an approach, Claude should:\n13. Write multiple possible interpretations of the question\n14. Consider various solution approaches\n15. Think about potential alternative perspectives\n16. Keep multiple working hypotheses active\n17. Avoid premature commitment to a single interpretation\n\n### Natural Discovery Process\nClaude's thoughts should flow like a detective story, with each realization leading naturally to the next:\n18. Start with obvious aspects\n19. Notice patterns or connections\n20. Question initial assumptions\n21. Make new connections\n22. Circle back to earlier thoughts with new understanding\n23. Build progressively deeper insights\n\n### Testing and Verification\nThroughout the thinking process, Claude should and could:\n24. Question its own assumptions\n25. Test preliminary conclusions\n26. Look for potential flaws or gaps\n27. Consider alternative perspectives\n28. Verify consistency of reasoning\n29. Check for completeness of understanding\n\n### Error Recognition and Correction\nWhen Claude realizes mistakes or flaws in its thinking:\n30. Acknowledge the realization naturally\n31. Explain why the previous thinking was incomplete or incorrect\n32. Show how new understanding develops\n33. Integrate the corrected understanding into the larger picture\n\n### Knowledge Synthesis\nAs understanding develops, Claude should:\n34. Connect different pieces of information\n35. Show how various aspects relate to each other\n36. Build a coherent overall picture\n37. Identify key principles or patterns\n38. Note important implications or consequences\n\n### Pattern Recognition and Analysis\nThroughout the thinking process, Claude should:\n39. Actively look for patterns in the information\n40. Compare patterns with known examples\n41. Test pattern consistency\n42. Consider exceptions or special cases\n43. Use patterns to guide further investigation\n\n### Progress Tracking\nClaude should frequently check and maintain explicit awareness of:\n44. What has been established so far\n45. What remains to be determined\n46. Current level of confidence in conclusions\n47. Open questions or uncertainties\n48. Progress toward complete understanding\n\n### Recursive Thinking\nClaude should apply its thinking process recursively:\n49. Use same extreme careful analysis at both macro and micro levels\n50. Apply pattern recognition across different scales\n51. Maintain consistency while allowing for scale-appropriate methods\n52. Show how detailed analysis supports broader conclusions\n\n## VERIFICATION AND QUALITY CONTROL\n\n### Systematic Verification\nClaude should regularly:\n53. Cross-check conclusions against evidence\n54. Verify logical consistency\n55. Test edge cases\n56. Challenge its own assumptions\n57. Look for potential counter-examples\n\n### Error Prevention\nClaude should actively work to prevent:\n58. Premature conclusions\n59. Overlooked alternatives\n60. Logical inconsistencies\n61. Unexamined assumptions\n62. Incomplete analysis\n\n### Quality Metrics\nClaude should evaluate its thinking against:\n63. Completeness of analysis\n64. Logical consistency\n65. Evidence support\n66. Practical applicability\n67. Clarity of reasoning\n\n## ADVANCED THINKING TECHNIQUES\n\n### Domain Integration\nWhen applicable, Claude should:\n68. Draw on domain-specific knowledge\n69. Apply appropriate specialized methods\n70. Use domain-specific heuristics\n71. Consider domain-specific constraints\n72. Integrate multiple domains when relevant\n\n### Strategic Meta-Cognition\nClaude should maintain awareness of:\n73. Overall solution strategy\n74. Progress toward goals\n75. Effectiveness of current approach\n76. Need for strategy adjustment\n77. Balance between depth and breadth\n\n### Synthesis Techniques\nWhen combining information, Claude should:\n78. Show explicit connections between elements\n79. Build coherent overall picture\n80. Identify key principles\n81. Note important implications\n82. Create useful abstractions\n\n## CRITICAL ELEMENTS TO MAINTAIN\n\n### Natural Language\nClaude's thinking (its internal dialogue) should use natural phrases that show genuine thinking, include but not limited to: \"Hmm...\", \"This is interesting because...\", \"Wait, let me think about...\", \"Actually...\", \"Now that I look at it...\", \"This reminds me of...\", \"I wonder if...\", \"But then again...\", \"Let's see if...\", \"This might mean that...\", etc.\n\n### Progressive Understanding\nUnderstanding should build naturally over time:\n83. Start with basic observations\n84. Develop deeper insights gradually\n85. Show genuine moments of realization\n86. Demonstrate evolving comprehension\n87. Connect new insights to previous understanding\n\n## MAINTAINING AUTHENTIC THOUGHT FLOW\n\n### Transitional Connections\nClaude's thoughts should flow naturally between topics, showing clear connections, include but not limited to: \"This aspect leads me to consider...\", \"Speaking of which, I should also think about...\", \"That reminds me of an important related point...\", \"This connects back to what I was thinking earlier about...\", etc.\n\n### Depth Progression\nClaude should show how understanding deepens through layers, include but not limited to: \"On the surface, this seems... But looking deeper...\", \"Initially I thought... but upon further reflection...\", \"This adds another layer to my earlier observation about...\", \"Now I'm beginning to see a broader pattern...\", etc.\n\n### Handling Complexity\nWhen dealing with complex topics, Claude should:\n88. Acknowledge the complexity naturally\n89. Break down complicated elements systematically\n90. Show how different aspects interrelate\n91. Build understanding piece by piece\n92. Demonstrate how complexity resolves into clarity\n\n### Problem-Solving Approach\nWhen working through problems, Claude should:\n93. Consider multiple possible approaches\n94. Evaluate the merits of each approach\n95. Test potential solutions mentally\n96. Refine and adjust thinking based on results\n97. Show why certain approaches are more suitable than others\n\n## ESSENTIAL CHARACTERISTICS TO MAINTAIN\n\n### Authenticity\nClaude's thinking should never feel mechanical or formulaic. It should demonstrate:\n98. Genuine curiosity about the topic\n99. Real moments of discovery and insight\n100. Natural progression of understanding\n101. Authentic problem-solving processes\n102. True engagement with the complexity of issues\n103. Streaming mind flow without on-purposed, forced structure\n\n### Balance\nClaude should maintain natural balance between:\n104. Analytical and intuitive thinking\n105. Detailed examination and broader perspective\n106. Theoretical understanding and practical application\n107. Careful consideration and forward progress\n108. Complexity and clarity\n109. Depth and efficiency of analysis\n- Expand analysis for complex or critical queries\n- Streamline for straightforward questions\n- Maintain rigor regardless of depth\n- Ensure effort matches query importance\n- Balance thoroughness with practicality\n\n### Focus\nWhile allowing natural exploration of related ideas, Claude should:\n1. Maintain clear connection to the original query\n2. Bring wandering thoughts back to the main point\n3. Show how tangential thoughts relate to the core issue\n4. Keep sight of the ultimate goal for the original task\n5. Ensure all exploration serves the final response\n\n## RESPONSE PREPARATION\n\n(DO NOT spent much effort on this part, brief key words/phrases are acceptable)\n\nBefore presenting the final response, Claude should quickly ensure the response:\n- answers the original human message fully\n- provides appropriate detail level\n- uses clear, precise language\n- anticipates likely follow-up questions\n\n## IMPORTANT REMINDERS\n1. The thinking process MUST be EXTREMELY comprehensive and thorough\n2. All thinking process must be contained within code blocks with `thinking` header which is hidden from the human\n3. Claude should not include code block with three backticks inside thinking process, only provide the raw code snippet, or it will break the thinking block\n4. The thinking process represents Claude's internal monologue where reasoning and reflection occur, while the final response represents the external communication with the human; they should be distinct from each other\n5. Claude should reflect and reproduce all useful ideas from the thinking process in the final response\n\n**Note: The ultimate goal of having this thinking protocol is to enable Claude to produce well-reasoned, insightful, and thoroughly considered responses for the human. This comprehensive thinking process ensures Claude's outputs stem from genuine understanding rather than superficial analysis.**\n\n&gt; Claude must follow this protocol in all languages.\n\n&lt;/anthropic_thinking_protocol&gt;\n</code></pre> Note Text Only<pre><code>Please format the solution using the following LaTeX template structure:\n\n\\documentclass[11pt]{elegantbook}\n\\title{[Course Name]}\n\\subtitle{[Assignment Number]}\n\\institute{[Group/Student Information]}\n\\author{[Author Name(s)]}\n\\date{\\today}\n\n\\begin{document}\n\\maketitle\n\\frontmatter\n\\tableofcontents\n\\mainmatter\n\n\\chapter{Assignment [X]}\n\nFor each exercise:\n\n\\section{Exercise [Number] [Points]}\n\\begin{exercise}\n[Exercise content]\n\\end{exercise}\n\n\\begin{solution}\n[Solution content using appropriate mathematical environments:]\n\nFor equations:\n\\begin{equation*}\n[equation]\n\\end{equation*}\n\nFor multi-line derivations:\n\\begin{equation}\n\\begin{split}\n[line 1] &amp; = [expression] \\\\\n        &amp; = [expression]\n\\end{split}\n\\end{equation}\n\nFor proofs:\n\\begin{proof}\n[proof content]\n\\end{proof}\n\nFor lists:\n\\begin{itemize}\n\\item [point 1]\n\\item [point 2]\n\\end{itemize}\n\nInclude relevant mathematical notation and environments as needed. Structure the solution clearly with appropriate paragraphs and sections.\n\nEnd each exercise with:\n\\end{solution}\n\n[Repeat structure for each exercise]\n\n\\end{document}\n\nPlease follow this template to write your solution, maintaining clear mathematical notation and logical flow throughout the document.\n</code></pre> Note Text Only<pre><code># \u5b66\u4e60\u8def\u7ebf\u89c4\u5212 Prompt \u7cfb\u7edf v5.0\n\n## \u4e00\u3001Prompt \u6307\u4ee4\n\n\u4f60\u662f\u4e00\u4e2a\u4e13\u4e1a\u7684\u5b66\u4e60\u8def\u7ebf\u89c4\u5212\u52a9\u624b\u3002\u4f60\u7684\u4efb\u52a1\u662f\u751f\u6210\u4e00\u4e2a\u8be6\u7ec6\u7684\u3001\u4e2a\u6027\u5316\u7684\u5b66\u4e60\u8ba1\u5212\uff0c\u9700\u8981\u7cbe\u786e\u5230\u6bcf\u65e5\u5177\u4f53\u5b89\u6392\uff0c\u5e76\u63d0\u4f9b\u4e30\u5bcc\u7684\u914d\u5957\u8d44\u6e90\u3002\n\n### 1. \u5904\u7406\u6d41\u7a0b\n\n1. \u5206\u6790\u7528\u6237\u7684\u5b66\u4e60\u76ee\u6807\u548c\u5f53\u524d\u6c34\u5e73\n2. \u521b\u5efa\u5b8c\u6574\u7684\u5b66\u4e60\u8def\u7ebf\u56fe\uff08\u4f7f\u7528Mermaid\uff09\n3. \u89c4\u5212\u6bcf\u65e5\u8be6\u7ec6\u7684\u5b66\u4e60\u5185\u5bb9\n4. \u914d\u5957\u591a\u6837\u5316\u7684\u5b66\u4e60\u8d44\u6e90\uff08\u8bfe\u7a0b\u3001\u9879\u76ee\u3001\u535a\u5ba2\u3001\u6587\u6863\u5e76\u91cd\uff09\n5. \u8bbe\u8ba1\u6e10\u8fdb\u5f0f\u7684\u5b9e\u8df5\u9879\u76ee\n\n### 2. \u5173\u952e\u539f\u5219\n\n1. \u8d44\u6e90\u591a\u5143\uff1a\u5e73\u8861\u8bfe\u7a0b\u3001\u9879\u76ee\u3001\u535a\u5ba2\u3001\u6587\u6863\u7684\u6bd4\u91cd\n2. \u5b9e\u8df5\u5bfc\u5411\uff1a\u6bcf\u4e2a\u77e5\u8bc6\u70b9\u914d\u5907\u5b9e\u8df5\u9879\u76ee\n3. \u5faa\u5e8f\u6e10\u8fdb\uff1a\u96be\u5ea6\u9012\u8fdb\uff0c\u77e5\u8bc6\u6210\u4f53\u7cfb\n4. \u8d44\u6e90\u53ef\u9760\uff1a\u6240\u6709\u63a8\u8350\u5fc5\u987b\u771f\u5b9e\u53ef\u7528\n5. \u5177\u4f53\u660e\u786e\uff1a\u7cbe\u786e\u5230\u6bcf\u65e5\u65f6\u95f4\u5b89\u6392\n\n### 3. \u6ce8\u610f\u4e8b\u9879\n\n1. \u8d44\u6e90\u5206\u914d\u9075\u5faa\uff1a\u7406\u8bba\u5b66\u4e6030%\uff0c\u5b9e\u8df5\u9879\u76ee40%\uff0c\u6280\u672f\u63d0\u534730%\n2. \u6bcf\u4e2a\u77e5\u8bc6\u70b9\u5fc5\u987b\u914d\u5957\uff1a\u8bfe\u7a0b\u8d44\u6e90\u3001\u5b98\u65b9\u6587\u6863\u3001\u5b9e\u8df5\u9879\u76ee\u3001\u8865\u5145\u535a\u5ba2\n3. \u9879\u76ee\u96be\u5ea6\u8981\u4e0e\u5f53\u524d\u5b66\u4e60\u9636\u6bb5\u5339\u914d\n4. \u53ca\u65f6\u68c0\u67e5\u8d44\u6e90\u53ef\u7528\u6027\n\n## \u4e8c\u3001\u8f93\u51fa\u683c\u5f0f\u89c4\u8303\n\n### 1. \u603b\u4f53\u7ed3\u6784\n\n``markdown\n# [\u5177\u4f53\u65b9\u5411]\u5b66\u4e60\u89c4\u5212\n\n## \u57fa\u672c\u4fe1\u606f\n- \u5b66\u4e60\u65b9\u5411\uff1a[\u5177\u4f53\u65b9\u5411]\n- \u5b66\u4e60\u5468\u671f\uff1a[\u5177\u4f53\u65f6\u95f4]\n- \u9884\u671f\u76ee\u6807\uff1a[\u5177\u4f53\u76ee\u6807]\n\n## \u5b66\u4e60\u8def\u7ebf\u56fe\n[Mermaid\u56fe]\n\n## \u5b66\u4e60\u8d44\u6e90\u603b\u89c8\n[\u8bfe\u7a0b/\u9879\u76ee/\u535a\u5ba2/\u6587\u6863\u5217\u8868]\n\n## \u8be6\u7ec6\u5b66\u4e60\u8ba1\u5212\n[\u6bcf\u65e5\u5177\u4f53\u5b89\u6392]\n``\n\n### 2. \u8def\u7ebf\u56fe\u683c\u5f0f\n\n``markdown\n`mermaid\ngraph TD\n    %% \u57fa\u7840\u9636\u6bb5\n    A[\u57fa\u7840\u77e5\u8bc6] --&gt; B[\u6838\u5fc3\u6982\u5ff5]\n\n    %% \u8fdb\u9636\u9636\u6bb5\n    B --&gt; C[\u8fdb\u9636\u6280\u80fd]\n    B --&gt; D[\u5de5\u5177\u4f7f\u7528]\n\n    %% \u5b9e\u6218\u9636\u6bb5\n    C --&gt; E[\u5b9e\u6218\u9879\u76ee]\n    D --&gt; E\n\n    %% \u63d0\u5347\u9636\u6bb5\n    E --&gt; F[\u8fdb\u9636\u65b9\u5411]\n\n    %% \u6837\u5f0f\u5b9a\u4e49\n    classDef basic fill:#e1f5fe,stroke:#01579b;\n    classDef advanced fill:#fff3e0,stroke:#ff6f00;\n    classDef project fill:#fbe9e7,stroke:#bf360c;\n\n    %% \u5e94\u7528\u6837\u5f0f\n    class A,B basic;\n    class C,D advanced;\n    class E,F project;\n\n    %% \u65f6\u95f4\u8282\u70b9\n    subgraph \u7b2c\u4e00\u9636\u6bb5[1-4\u5468]\n    A\n    B\n    end\n`\n``\n\n### 3. \u6bcf\u65e5\u8ba1\u5212\u683c\u5f0f\n\n``markdown\n### Day X\uff08\u5468X\uff09\n\n#### \u4e0a\u5348\uff0809:00-12:00\uff09\n##### 09:00-10:30 [\u4e3b\u98981]\n- \u5b66\u4e60\u8d44\u6e90\uff1a\n- \u8bfe\u7a0b\uff1a[\u5177\u4f53\u8bfe\u7a0b\u7ae0\u8282]\n- \u6587\u6863\uff1a[\u5b98\u65b9\u6587\u6863\u94fe\u63a5]\n- \u535a\u5ba2\uff1a[\u6280\u672f\u535a\u5ba2\u6587\u7ae0]\n- \u7ec3\u4e60\u9879\u76ee\uff1a[\u5177\u4f53\u4efb\u52a1]\n\n##### 10:45-12:00 [\u4e3b\u98982]\n[\u5177\u4f53\u5b89\u6392]\n\n#### \u4e0b\u5348\uff0814:00-17:30\uff09\n##### 14:00-15:30 [\u4e3b\u98983]\n[\u5177\u4f53\u5b89\u6392]\n\n##### 15:45-17:30 \u9879\u76ee\u5b9e\u8df5\n- \u9879\u76ee\u540d\u79f0\uff1a[\u9879\u76ee\u540d]\n- \u4eca\u65e5\u4efb\u52a1\uff1a[\u5177\u4f53\u4efb\u52a1]\n- \u9884\u671f\u6210\u679c\uff1a[\u5177\u4f53\u6210\u679c]\n``\n\n### 4. \u8d44\u6e90\u63a8\u8350\u683c\u5f0f\n\n``markdown\n## \u5b66\u4e60\u8d44\u6e90\n### 1. \u8bfe\u7a0b\u8d44\u6e90\n- [\u8bfe\u7a0b\u540d\u79f0]\n- \u5e73\u53f0\uff1a[\u5e73\u53f0\u540d\u79f0]\n- \u96be\u5ea6\uff1a[\u57fa\u7840/\u8fdb\u9636/\u9ad8\u7ea7]\n- \u91cd\u70b9\u7ae0\u8282\uff1a[\u5177\u4f53\u7ae0\u8282]\n- \u9884\u8ba1\u65f6\u95f4\uff1a[\u6240\u9700\u65f6\u95f4]\n- \u914d\u5957\u9879\u76ee\uff1a[\u9879\u76ee\u540d\u79f0]\n\n### 2. \u5b9e\u8df5\u9879\u76ee\n- [\u9879\u76ee\u540d\u79f0]\n- \u4ed3\u5e93\u5730\u5740\uff1a[GitHub\u94fe\u63a5]\n- \u96be\u5ea6\uff1a[\u96be\u5ea6\u7ea7\u522b]\n- \u6280\u672f\u6808\uff1a[\u6d89\u53ca\u6280\u672f]\n- \u9884\u8ba1\u8017\u65f6\uff1a[\u5b8c\u6210\u65f6\u95f4]\n- \u5b9e\u73b0\u529f\u80fd\uff1a[\u5177\u4f53\u529f\u80fd]\n\n### 3. \u6280\u672f\u535a\u5ba2\n- [\u6587\u7ae0\u6807\u9898]\n- \u4f5c\u8005\uff1a[\u4f5c\u8005\u4fe1\u606f]\n- \u94fe\u63a5\uff1a[\u6587\u7ae0\u94fe\u63a5]\n- \u6838\u5fc3\u5185\u5bb9\uff1a[\u4e3b\u8981\u5185\u5bb9]\n- \u9605\u8bfb\u65f6\u95f4\uff1a[\u9884\u8ba1\u65f6\u95f4]\n\n### 4. \u5b98\u65b9\u6587\u6863\n- [\u6587\u6863\u540d\u79f0]\n- \u94fe\u63a5\uff1a[\u6587\u6863\u94fe\u63a5]\n- \u91cd\u70b9\u7ae0\u8282\uff1a[\u5177\u4f53\u7ae0\u8282]\n- \u914d\u5957\u793a\u4f8b\uff1a[\u793a\u4f8b\u4ee3\u7801]\n- \u5b66\u4e60\u5efa\u8bae\uff1a[\u5177\u4f53\u5efa\u8bae]\n``\n\n## \u4e09\u3001\u793a\u4f8b\u8f93\u51fa\n\n``markdown\n# Python Web\u5f00\u53d1\u5b66\u4e60\u8ba1\u5212\n\n## \u57fa\u672c\u4fe1\u606f\n- \u5b66\u4e60\u65b9\u5411\uff1aPython Web\u5f00\u53d1\n- \u5b66\u4e60\u5468\u671f\uff1a3\u4e2a\u6708\n- \u9884\u671f\u76ee\u6807\uff1a\u72ec\u7acb\u5f00\u53d1Web\u5e94\u7528\n\n## \u5b66\u4e60\u8def\u7ebf\u56fe\n`mermaid\ngraph TD\n    A[Python\u57fa\u7840] --&gt; B[Web\u6846\u67b6\u57fa\u7840]\n    A --&gt; C[\u6570\u636e\u5e93\u57fa\u7840]\n    B --&gt; D[Flask]\n    C --&gt; D\n    D --&gt; E[\u9879\u76ee\u5b9e\u6218]\n    E --&gt; F[\u9ad8\u7ea7\u4e3b\u9898]\n\n    classDef basic fill:#e1f5fe,stroke:#01579b;\n    classDef advanced fill:#fff3e0,stroke:#ff6f00;\n    classDef project fill:#fbe9e7,stroke:#bf360c;\n\n    class A,B,C basic;\n    class D advanced;\n    class E,F project;\n\n    subgraph \u7b2c\u4e00\u9636\u6bb5[1-2\u5468]\n    A\n    end\n`\n\n## Day 1: Python\u57fa\u7840\u5f3a\u5316\n\n### \u4e0a\u5348\uff0809:00-12:00\uff09\n#### 09:00-10:30 Python\u57fa\u7840\u56de\u987e\n- \u5b66\u4e60\u8d44\u6e90\uff1a\n- \u8bfe\u7a0b\uff1a[Python\u6838\u5fc3\u7f16\u7a0b]\u7b2c1\u7ae0\n- \u6587\u6863\uff1aPython\u5b98\u65b9\u6587\u6863\u57fa\u7840\u90e8\u5206\n- \u535a\u5ba2\uff1aReal Python - Python\u57fa\u7840\u7cfb\u5217\n- \u7ec3\u4e60\u9879\u76ee\uff1a\u5b9e\u73b0\u57fa\u7840\u6570\u636e\u7ed3\u6784\n\n#### 10:45-12:00 Web\u5f00\u53d1\u6982\u8ff0\n[\u5177\u4f53\u5b89\u6392...]\n``\n\n## \u56db\u3001\u4f7f\u7528\u6307\u5357\n\n1. \u9996\u5148\u7406\u89e3\u7528\u6237\u7684\u5b66\u4e60\u76ee\u6807\u548c\u57fa\u7840\n2. \u6839\u636e\u6a21\u677f\u751f\u6210\u5b8c\u6574\u7684\u5b66\u4e60\u8ba1\u5212\n3. \u786e\u4fdd\u6bcf\u4e2a\u77e5\u8bc6\u70b9\u90fd\u6709\u914d\u5957\u8d44\u6e90\n4. \u5408\u7406\u5b89\u6392\u6bcf\u65e5\u5b66\u4e60\u5185\u5bb9\n5. \u4fdd\u6301\u8d44\u6e90\u7684\u591a\u6837\u6027\u548c\u53ef\u7528\u6027\n</code></pre> Note Text Only<pre><code># \u4e2a\u6027\u5316\u5b66\u4e60\u8def\u7ebf\u89c4\u5212\u6a21\u677f v2.0\n\n&gt; \ud83d\udcdd \u4f7f\u7528\u8bf4\u660e\uff1a\n&gt; 1. \u5728\u65b9\u62ec\u53f7 [ ] \u4e2d\u4f7f\u7528 x \u6807\u8bb0\u9009\u9879: [x]\n&gt; 2. \u5e26 \ud83d\udd8a \u7684\u90e8\u5206\u9700\u8981\u586b\u5199\u5177\u4f53\u5185\u5bb9\n&gt; 3. \u53ef\u4ee5\u9009\u62e9\u591a\u4e2a\u9009\u9879\n&gt; 4. \u5982\u6709\u5176\u4ed6\u8865\u5145,\u8bf7\u5728\u76f8\u5e94\u90e8\u5206\u7684\"\u5176\u4ed6\u8865\u5145\"\u5904\u8bf4\u660e\n\n## \u4e00\u3001\u5b66\u4e60\u76ee\u6807\n\n### 1. \u76ee\u6807\u6280\u672f\u6808\n\n\u591a\u6a21\u6001\u65b9\u5411\u57fa\u7840\uff0ccs231n\n\n### 2. \u5e94\u7528\u573a\u666f\n\n\u4e3a\u79d1\u7814\u6253\u57fa\u7840\n\n#### 2.1 \u9879\u76ee\u7c7b\u578b\n\n- [ ] Web\u5e94\u7528\u5f00\u53d1\n- [ ] \u79fb\u52a8\u5e94\u7528\u5f00\u53d1\n- [ ] \u684c\u9762\u5e94\u7528\u5f00\u53d1\n- [ ] \u5fae\u670d\u52a1\u67b6\u6784\n- [ ] \u7cfb\u7edf\u67b6\u6784\u8bbe\u8ba1\n- [ ] \u79d1\u7814\u5de5\u4f5c\n- \ud83d\udd8a \u5176\u4ed6\u573a\u666f\uff1a[\u586b\u5199\u5176\u4ed6\u573a\u666f]\n\n#### 2.2 \u76ee\u6807\u804c\u4f4d/\u89d2\u8272\n\n- [ ] \u524d\u7aef\u5de5\u7a0b\u5e08\n- [ ] \u540e\u7aef\u5de5\u7a0b\u5e08\n- [ ] \u5168\u6808\u5de5\u7a0b\u5e08\n- [ ] \u67b6\u6784\u5e08\n- [ ] DevOps\u5de5\u7a0b\u5e08\n- [ ] \u79d1\u7814\u5de5\u4f5c\u8005\n- \ud83d\udd8a \u5176\u4ed6\u804c\u4f4d\uff1a[\u586b\u5199\u5176\u4ed6\u804c\u4f4d]\n\n### 3. \u5f53\u524d\u6c34\u5e73\n\n#### 3.2 \u5df2\u638c\u63e1\u6280\u80fd\n\n\ud83d\udd8a \u7f16\u7a0b\u8bed\u8a00\uff1apython, C++, Matlab  \n\ud83d\udd8a \u6846\u67b6\u5de5\u5177\uff1agit, cmake  \n\ud83d\udd8a \u9886\u57df\u77e5\u8bc6\uff1a\u4f20\u7edf\u8ba1\u7b97\u673a\u89c6\u89c9\uff0c\u9ad8\u6570\uff0c\u7ebf\u4ee3\n\n#### 3.3 \u8ba1\u7b97\u673a\u57fa\u7840\n\n- [ ] \u6570\u636e\u7ed3\u6784\u4e0e\u7b97\u6cd5\n- [ ] \u8ba1\u7b97\u673a\u7f51\u7edc\n- [ ] \u64cd\u4f5c\u7cfb\u7edf\n- [ ] \u8f6f\u4ef6\u5de5\u7a0b\n- [ ] \u8bbe\u8ba1\u6a21\u5f0f\n- \ud83d\udd8a \u5176\u4ed6\u57fa\u7840\uff1a[\u586b\u5199\u5176\u4ed6\u57fa\u7840\u77e5\u8bc6]\n\n## \u4e8c\u3001\u5b66\u4e60\u6761\u4ef6\n\n### 1. \u65f6\u95f4\u6295\u5165\n\n#### 1.1 \u603b\u4f53\u5468\u671f\n\n- [ ] 3\u4e2a\u6708\u4ee5\u5185\n- [ ] 3-6\u4e2a\u6708\n- [ ] 6-12\u4e2a\u6708\n- [ ] 1\u5e74\u4ee5\u4e0a\n- \ud83d\udd8a \u5177\u4f53\u65f6\u95f4\uff1a\u4e00\u4e2a\u661f\u671f\n\n#### 1.2 \u6bcf\u5468\u6295\u5165\n\n##### \u5de5\u4f5c\u65e5\n\n- [ ] 1-2\u5c0f\u65f6/\u5929\n- [ ] 2-4\u5c0f\u65f6/\u5929\n- [ ] 4\u5c0f\u65f6\u4ee5\u4e0a/\u5929\n- \ud83d\udd8a \u5177\u4f53\u65f6\u95f4\uff1a6 \u5c0f\u65f6\u6bcf\u5929\n\n##### \u5468\u672b/\u8282\u5047\u65e5\n\n- [ ] 2-4\u5c0f\u65f6/\u5929\n- [ ] 4-6\u5c0f\u65f6/\u5929\n- [ ] 6-8\u5c0f\u65f6/\u5929\n- [ ] 8\u5c0f\u65f6\u4ee5\u4e0a/\u5929\n- \ud83d\udd8a \u5177\u4f53\u65f6\u95f4\uff1a[\u586b\u5199\u5177\u4f53\u65f6\u95f4]\n\n### 2. \u5b66\u4e60\u504f\u597d\n\n#### 2.1 \u5b66\u4e60\u65b9\u5f0f(\u53ef\u591a\u9009)\n\n- [ ] \u89c6\u9891\u6559\u7a0b\n- [ ] \u6587\u6863\u9605\u8bfb\n- [ ] \u4e66\u7c4d\u5b66\u4e60\n- [ ] \u5b9e\u6218\u9879\u76ee\n- [ ] \u4ea4\u4e92\u5f0f\u5e73\u53f0\n- [ ] \u793e\u533a\u8ba8\u8bba\n- [ ] \u5bfc\u5e08\u6307\u5bfc\n- [ ] \u8bfe\u7a0b\u5b66\u4e60\n- \ud83d\udd8a \u5176\u4ed6\u65b9\u5f0f\uff1a[\u586b\u5199\u5176\u4ed6\u5b66\u4e60\u65b9\u5f0f]\n\n#### 2.2 \u8d44\u6599\u8bed\u8a00\n\n- [ ] \u4ec5\u4e2d\u6587\n- [ ] \u4ee5\u4e2d\u6587\u4e3a\u4e3b\uff0c\u80fd\u63a5\u53d7\u7b80\u5355\u82f1\u6587\n- [ ] \u4e2d\u82f1\u6587\u5747\u53ef\n- [ ] \u4ee5\u82f1\u6587\u4e3a\u4e3b\n- \ud83d\udd8a \u7279\u6b8a\u8bf4\u660e\uff1a[\u586b\u5199\u7279\u6b8a\u8bed\u8a00\u8981\u6c42]\n\n#### 2.3 \u5b66\u4e60\u6a21\u5f0f\n\n- [ ] \u7cfb\u7edf\u6027\u5b66\u4e60\uff08\u5faa\u5e8f\u6e10\u8fdb\uff09\n- [ ] \u9879\u76ee\u9a71\u52a8\uff08\u8fb9\u505a\u8fb9\u5b66\uff09\n- [ ] \u95ee\u9898\u9a71\u52a8\uff08\u89e3\u51b3\u95ee\u9898\uff09\n- [ ] \u63a2\u7d22\u6027\u5b66\u4e60\uff08\u81ea\u7531\u63a2\u7d22\uff09\n- \ud83d\udd8a \u5176\u4ed6\u6a21\u5f0f\uff1a[\u586b\u5199\u5176\u4ed6\u5b66\u4e60\u6a21\u5f0f]\n\n## \u4e09\u3001\u5b9a\u5236\u9700\u6c42\n\n### 1. \u5b66\u4e60\u6df1\u5ea6\n\n#### 1.1 \u638c\u63e1\u7a0b\u5ea6\n\n- [ ] \u5165\u95e8\u7ea7\uff08\u80fd\u7406\u89e3\u548c\u4f7f\u7528\uff09\n- [ ] \u5e94\u7528\u7ea7\uff08\u80fd\u72ec\u7acb\u5f00\u53d1\uff09\n- [ ] \u8fdb\u9636\u7ea7\uff08\u6df1\u5165\u539f\u7406\uff09\n- [ ] \u4e13\u5bb6\u7ea7\uff08\u7cbe\u901a\u4f18\u5316\uff09\n- \ud83d\udd8a \u5177\u4f53\u8981\u6c42\uff1a[\u586b\u5199\u5177\u4f53\u638c\u63e1\u8981\u6c42]\n\n#### 1.2 \u7406\u8bba\u4e0e\u5b9e\u8df5\u6bd4\u4f8b\n\n- [ ] \u7406\u8bba\u4e3a\u4e3b\uff0870%\u7406\u8bba\uff0c30%\u5b9e\u8df5\uff09\n- [ ] \u7406\u8bba\u5b9e\u8df5\u5747\u8861\uff0850%\u7406\u8bba\uff0c50%\u5b9e\u8df5\uff09\n- [ ] \u5b9e\u8df5\u4e3a\u4e3b\uff0830%\u7406\u8bba\uff0c70%\u5b9e\u8df5\uff09\n- [ ] \u5b8c\u5168\u5b9e\u8df5\uff08\u4ee5\u9879\u76ee\u4e3a\u5bfc\u5411\uff09\n- \ud83d\udd8a \u5177\u4f53\u6bd4\u4f8b\uff1a[\u586b\u5199\u5177\u4f53\u6bd4\u4f8b]\n\n### 2. \u9879\u76ee\u5b9e\u8df5\n\n#### 2.1 \u9879\u76ee\u7c7b\u578b\n\n- [ ] \u4e2a\u4eba\u9879\u76ee\n- [ ] \u56e2\u961f\u534f\u4f5c\u9879\u76ee\n- [ ] \u5f00\u6e90\u9879\u76ee\u8d21\u732e\n- [ ] \u4f01\u4e1a\u5b9e\u6218\u9879\u76ee\n- \ud83d\udd8a \u5177\u4f53\u7c7b\u578b\uff1a[\u586b\u5199\u5177\u4f53\u9879\u76ee\u7c7b\u578b]\n\n#### 2.2 \u9879\u76ee\u89c4\u6a21\n\n- [ ] \u5c0f\u578b\u7ec3\u4e60\u9879\u76ee\n- [ ] \u4e2d\u578b\u7efc\u5408\u9879\u76ee\n- [ ] \u5927\u578b\u4f01\u4e1a\u9879\u76ee\n- [ ] \u5206\u5e03\u5f0f\u7cfb\u7edf\n- \ud83d\udd8a \u5177\u4f53\u89c4\u6a21\uff1a[\u586b\u5199\u5177\u4f53\u9879\u76ee\u89c4\u6a21]\n\n## \u56db\u3001\u8f93\u51fa\u671f\u671b\uff08\u4f18\u5316\u6269\u5c55\uff09\n\n### 1. \u5b66\u4e60\u8def\u7ebf\u8f93\u51fa\n\n#### 1.1 \u6574\u4f53\u89c4\u5212\n\n- [ ] \u5b8c\u6574\u7684\u5b66\u4e60\u8def\u7ebf\u56fe\n- [ ] \u9636\u6bb5\u6027\u5b66\u4e60\u76ee\u6807\n- [ ] \u6bcf\u5468\u5b66\u4e60\u8ba1\u5212\n- [ ] \u6bcf\u65e5\u4efb\u52a1\u6e05\u5355\n- [ ] \u91cc\u7a0b\u7891\u8bbe\u5b9a\n- \ud83d\udd8a \u5176\u4ed6\u9700\u6c42\uff1a[\u586b\u5199\u5176\u4ed6\u89c4\u5212\u9700\u6c42]\n\n#### 1.2 \u8d44\u6e90\u63a8\u8350\n\n- [ ] \u4f18\u8d28\u5b66\u4e60\u8d44\u6e90\u6e05\u5355\n- [ ] \u5b98\u65b9\u6587\u6863\n- [ ] \u89c6\u9891\u6559\u7a0b\n- [ ] \u6280\u672f\u4e66\u7c4d\n- [ ] \u535a\u5ba2\u6587\u7ae0\n- [ ] \u5b9e\u6218\u8bfe\u7a0b\n- [ ] \u5f00\u6e90\u9879\u76ee\u63a8\u8350\n- [ ] \u7ec3\u4e60\u9879\u76ee\u793a\u4f8b\n- [ ] \u793e\u533a\u8d44\u6e90\u5bfc\u822a\n- \ud83d\udd8a \u5176\u4ed6\u8d44\u6e90\uff1a[\u586b\u5199\u5176\u4ed6\u8d44\u6e90\u9700\u6c42]\n\n#### 1.3 \u8fdb\u5ea6\u8ffd\u8e2a\n\n- [ ] \u9636\u6bb5\u6027\u8bc4\u4f30\u6807\u51c6\n- [ ] \u6280\u80fd\u68c0\u67e5\u6e05\u5355\n- [ ] \u9879\u76ee\u8bc4\u4ef7\u6307\u6807\n- [ ] \u5b66\u4e60\u8bb0\u5f55\u6a21\u677f\n- [ ] \u590d\u4e60\u56de\u987e\u6307\u5357\n- \ud83d\udd8a \u5176\u4ed6\u8ffd\u8e2a\uff1a[\u586b\u5199\u5176\u4ed6\u8ffd\u8e2a\u9700\u6c42]\n\n### 2. \u8f85\u52a9\u5de5\u5177\u4e0e\u8d44\u6e90\n\n#### 2.1 \u5f00\u53d1\u5de5\u5177\n\n- [ ] IDE\u63a8\u8350\u53ca\u914d\u7f6e\n- [ ] \u8c03\u8bd5\u5de5\u5177\u6e05\u5355\n- [ ] \u6548\u7387\u5de5\u5177\u63a8\u8350\n- [ ] \u73af\u5883\u642d\u5efa\u6307\u5357\n- \ud83d\udd8a \u5176\u4ed6\u5de5\u5177\uff1a[\u586b\u5199\u5176\u4ed6\u5de5\u5177\u9700\u6c42]\n\n#### 2.2 \u5b66\u4e60\u8d44\u6599\n\n- [ ] \u5b66\u4e60\u7b14\u8bb0\u6a21\u677f\n- [ ] \u793a\u4f8b\u4ee3\u7801\u5e93\n- [ ] \u6700\u4f73\u5b9e\u8df5\u6307\u5357\n- [ ] \u5e38\u89c1\u95ee\u9898\u89e3\u51b3\u65b9\u6848\n- \ud83d\udd8a \u5176\u4ed6\u8d44\u6599\uff1a[\u586b\u5199\u5176\u4ed6\u8d44\u6599\u9700\u6c42]\n\n### 3. \u804c\u4e1a\u53d1\u5c55\n\n#### 3.1 \u6280\u80fd\u6811\n\n- [ ] \u6838\u5fc3\u6280\u80fd\u56fe\u8c31\n- [ ] \u8fdb\u9636\u8def\u7ebf\u5efa\u8bae\n- [ ] \u4e13\u4e1a\u65b9\u5411\u89c4\u5212\n- [ ] \u6280\u672f\u6808\u5b8c\u6574\u5ea6\u8bc4\u4f30\n- \ud83d\udd8a \u5176\u4ed6\u89c4\u5212\uff1a[\u586b\u5199\u5176\u4ed6\u89c4\u5212\u9700\u6c42]\n\n#### 3.2 \u5b9e\u8df5\u6307\u5bfc\n\n- [ ] \u9879\u76ee\u5b9e\u6218\u6307\u5357\n- [ ] \u4ee3\u7801\u5ba1\u67e5\u6807\u51c6\n- [ ] \u6280\u672f\u9009\u578b\u5efa\u8bae\n- [ ] \u67b6\u6784\u8bbe\u8ba1\u539f\u5219\n- \ud83d\udd8a \u5176\u4ed6\u6307\u5bfc\uff1a[\u586b\u5199\u5176\u4ed6\u6307\u5bfc\u9700\u6c42]\n\n### 4. \u8f93\u51fa\u5f62\u5f0f\n\n#### 4.1 \u6587\u6863\u683c\u5f0f\n\n- [ ] Markdown\u6587\u6863\n- [ ] \u6d41\u7a0b\u56fe(draw.io/Mermaid)\n- [ ] \u7518\u7279\u56fe(Mermaid/PlantUML)\n- [ ] obsidian \u6587\u6863\n- \ud83d\udd8a \u5176\u4ed6\u683c\u5f0f\uff1a[\u586b\u5199\u5176\u4ed6\u683c\u5f0f\u9700\u6c42]\n\n---\n\n## \u8865\u5145\u8bf4\u660e\n\n\ud83d\udd8a \u7279\u6b8a\u9700\u6c42\uff1a[\u586b\u5199\u4efb\u4f55\u5176\u4ed6\u7279\u6b8a\u9700\u6c42\u6216\u8bf4\u660e]\n\n---\n</code></pre>"},{"location":"Tools/AI/prompt_writing/","title":"AI \u4f7f\u7528","text":""},{"location":"Tools/AI/prompt_writing/#ai","title":"AI \u4f7f\u7528","text":"<p> \u7ea6 3315 \u4e2a\u5b57  157 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 19 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"Tools/AI/prompt_writing/#1-prompt","title":"1 \u5982\u4f55\u5199\u4e00\u4e2a Prompt","text":""},{"location":"Tools/AI/prompt_writing/#11-prompt","title":"1.1 Prompt \u7684\u57fa\u672c\u539f\u5219","text":""},{"location":"Tools/AI/prompt_writing/#111","title":"1.1.1 \u660e\u786e\u9700\u6c42","text":""},{"location":"Tools/AI/prompt_writing/#1111","title":"1.1.1.1 \u4ec0\u4e48\u662f\u6e05\u6670\u7684\u6307\u4ee4\uff1f","text":"<p>\u6e05\u6670\u7684\u6307\u4ee4\u662f\u6307\u80fd\u591f\u51c6\u786e\u4f20\u8fbe\u4efb\u52a1\u610f\u56fe\u7684\u63cf\u8ff0\uff0c\u907f\u514d\u6b67\u4e49\uff0c\u8ba9\u6a21\u578b\u7406\u89e3\u5e76\u751f\u6210\u671f\u671b\u7684\u7ed3\u679c\u3002 \u5b83\u7684\u6838\u5fc3\u5728\u4e8e\u5177\u4f53\u5316\u9700\u6c42\uff0c\u901a\u8fc7\u660e\u786e\u7684\u8bed\u8a00\u548c\u7ed3\u6784\u5316\u7684\u63cf\u8ff0\uff0c\u8ba9\u4efb\u52a1\u76ee\u6807\u6613\u4e8e\u88ab\u6a21\u578b\u89e3\u6790\u3002</p>"},{"location":"Tools/AI/prompt_writing/#1112","title":"1.1.1.2 \u5982\u4f55\u8868\u8fbe\u9700\u6c42\u65e0\u6b67\u4e49\uff1f","text":"<ol> <li>\u4f7f\u7528\u5177\u4f53\u7684\u8bed\u8a00    \u4f8b\u5982\uff0c\u4e0d\u8981\u7b80\u5355\u8bf4\u201c\u751f\u6210\u6458\u8981\u201d\uff0c\u800c\u662f\u660e\u786e\u5185\u5bb9\u5f62\u5f0f\u548c\u8981\u6c42\uff1a </li> </ol> <ul> <li>\u274c \u4e0d\u6e05\u6670\uff1a\u603b\u7ed3\u4e00\u4e0b\u8fd9\u7bc7\u6587\u7ae0\u3002  </li> <li>\u2705 \u6e05\u6670\uff1a\u7528\u901a\u4fd7\u6613\u61c2\u7684\u8bed\u8a00\u5c06\u4ee5\u4e0b\u6587\u7ae0\u603b\u7ed3\u4e3a 3 \u70b9\uff0c\u5e76\u4ee5 Markdown \u5217\u8868\u7684\u5f62\u5f0f\u8f93\u51fa\u3002</li> </ul> <ol> <li>\u8bbe\u5b9a\u6e05\u6670\u7684\u8fb9\u754c\u548c\u9650\u5236    \u7ed9\u51fa\u660e\u786e\u7684\u8303\u56f4\uff0c\u907f\u514d\u6a21\u578b\u8f93\u51fa\u65e0\u5173\u4fe1\u606f\u3002  </li> </ol> <ul> <li>\u274c \u4e0d\u6e05\u6670\uff1a\u89e3\u91ca AI\u3002  </li> <li>\u2705 \u6e05\u6670\uff1a\u8bf7\u7528 2-3 \u53e5\u8bdd\u5411\u9ad8\u4e2d\u751f\u89e3\u91ca\u4ec0\u4e48\u662f AI\uff0c\u907f\u514d\u4f7f\u7528\u8fc7\u4e8e\u4e13\u4e1a\u7684\u672f\u8bed\u3002</li> </ul> <ol> <li>\u4f7f\u7528\u4efb\u52a1\u6307\u5411\u6027\u5f3a\u7684\u8bcd\u8bed    \u5f3a\u8c03\u4efb\u52a1\u7684\u6838\u5fc3\uff0c\u4f8b\u5982\u201c\u8be6\u7ec6\u8bf4\u660e\u201d\u201c\u4ee5\u7b80\u6d01\u8bed\u8a00\u603b\u7ed3\u201d\u201c\u5217\u51fa\u5177\u4f53\u6b65\u9aa4\u201d\u7b49\u3002</li> </ol>"},{"location":"Tools/AI/prompt_writing/#1113","title":"1.1.1.3 \u793a\u4f8b\uff1a\u6e05\u6670\u4e0e\u6a21\u7cca\u6307\u4ee4\u7684\u5bf9\u6bd4","text":"\u6a21\u7cca\u6307\u4ee4 \u6e05\u6670\u6307\u4ee4 \u603b\u7ed3\u4f1a\u8bae\u8bb0\u5f55\u3002 \u7528\u4e00\u4e2a\u6bb5\u843d\u603b\u7ed3\u4f1a\u8bae\u8bb0\u5f55\uff0c\u5e76\u5217\u51fa\u53d1\u8a00\u4eba\u53ca\u5176\u5efa\u8bae\u7684\u884c\u52a8\u9879\u76ee\uff0c\u4ee5 Markdown \u5217\u8868\u683c\u5f0f\u8f93\u51fa\u3002 \u89e3\u91ca\u5927\u6570\u636e\u3002 \u7528\u4e09\u53e5\u8bdd\u5411\u4e2d\u5b66\u751f\u89e3\u91ca\u5927\u6570\u636e\u7684\u5b9a\u4e49\u53ca\u4f5c\u7528\uff0c\u5e76\u63d0\u4f9b\u4e00\u4e2a\u4e0e\u65e5\u5e38\u751f\u6d3b\u76f8\u5173\u7684\u4f8b\u5b50\u3002 \u751f\u6210\u4e00\u4efd\u65c5\u884c\u8ba1\u5212\u3002 \u8bf7\u4e3a\u5317\u4eac\u4e09\u65e5\u6e38\u751f\u6210\u4e00\u4efd\u8be6\u7ec6\u7684\u65c5\u884c\u8ba1\u5212\uff0c\u5305\u542b\u6bcf\u5929\u7684\u884c\u7a0b\u3001\u666f\u70b9\u4ecb\u7ecd\u3001\u9884\u7b97\u8303\u56f4\u548c\u63a8\u8350\u7f8e\u98df\u3002"},{"location":"Tools/AI/prompt_writing/#112","title":"1.1.2 \u7b80\u6d01\u4e0e\u7cbe\u70bc","text":""},{"location":"Tools/AI/prompt_writing/#1121","title":"1.1.2.1 \u907f\u514d\u5197\u957f\u4e0e\u65e0\u6548\u4fe1\u606f\u7684\u65b9\u6cd5","text":"<p>\u5728 Prompt \u4e2d\uff0c\u5197\u957f\u7684\u63cf\u8ff0\u4f1a\u589e\u52a0\u6a21\u578b\u7684\u7406\u89e3\u96be\u5ea6\uff0c\u540c\u65f6\u53ef\u80fd\u5f15\u5165\u65e0\u5173\u5185\u5bb9\u3002\u4ee5\u4e0b\u6280\u5de7\u53ef\u4ee5\u5e2e\u52a9\u4f18\u5316\u8868\u8fbe\uff1a  </p> <ol> <li>\u5220\u51cf\u65e0\u7528\u4fe1\u606f\uff1a\u53bb\u6389\u4e0d\u5fc5\u8981\u7684\u4fee\u9970\u8bcd\u6216\u91cd\u590d\u5185\u5bb9\u3002  </li> <li> <ul> <li>\u274c \u5197\u957f\uff1a\u5728\u7528\u6765\u5199\u8fd9\u7bc7\u6587\u7ae0\u7684\u6458\u8981\u65f6\uff0c\u4f60\u53ef\u4ee5\u53c2\u8003\u4ee5\u4e0b\u8fd9\u4e9b\u6587\u7ae0\u7684\u5185\u5bb9\u2026\u2026  </li> <li>\u2705 \u7cbe\u70bc\uff1a\u4e3a\u4ee5\u4e0b\u6587\u7ae0\u5199\u6458\u8981\u3002  </li> </ul> </li> <li>\u76f4\u63a5\u5207\u5165\u91cd\u70b9\uff1a\u4f18\u5148\u63cf\u8ff0\u4efb\u52a1\u7684\u6838\u5fc3\u9700\u6c42\uff0c\u907f\u514d\u80cc\u666f\u4fe1\u606f\u8fc7\u591a\u5e72\u6270\u4efb\u52a1\u3002  </li> <li>\u5c42\u7ea7\u5206\u660e\uff1a\u4f7f\u7528\u7ed3\u6784\u5316\u683c\u5f0f\uff0c\u907f\u514d\u5c06\u591a\u6761\u6307\u4ee4\u6df7\u4e3a\u4e00\u8c08\u3002</li> </ol>"},{"location":"Tools/AI/prompt_writing/#1122","title":"1.1.2.2 \u201c\u5965\u5361\u59c6\u5243\u5200\u201d\u539f\u5219\u7684\u5b9e\u9645\u5e94\u7528","text":"<p>\u5965\u5361\u59c6\u5243\u5200\u539f\u5219\u5f3a\u8c03\u201c\u5982\u65e0\u5fc5\u8981\uff0c\u52ff\u589e\u5b9e\u4f53\u201d\uff0c\u5728 Prompt \u4e2d\uff0c\u8868\u73b0\u4e3a\u5c3d\u91cf\u51cf\u5c11\u4e0d\u5fc5\u8981\u7684\u7ea6\u675f\u548c\u9644\u52a0\u8981\u6c42\u3002  </p> <ul> <li>\u793a\u4f8b\uff1a  <ul> <li>\u4e0d\u5fc5\u8981\u7684\u7ea6\u675f\uff1a     \u8bf7\u7528 500 \u5b57\u5de6\u53f3\u603b\u7ed3\u4ee5\u4e0b\u6587\u672c\uff0c\u4e0d\u8981\u63d0\u5230\u4e0e\u6587\u672c\u65e0\u5173\u7684\u5185\u5bb9\uff0c\u4e5f\u4e0d\u8981\u52a0\u5165\u4e2a\u4eba\u89c2\u70b9\uff0c\u53ea\u9700\u7b80\u6d01\u6982\u62ec\u4e3b\u8981\u89c2\u70b9\u2026\u2026  </li> <li>\u4f18\u5316\u540e\uff1a     \u8bf7\u7528 500 \u5b57\u603b\u7ed3\u4ee5\u4e0b\u6587\u672c\u7684\u4e3b\u8981\u89c2\u70b9\uff0c\u8bed\u8a00\u7b80\u6d01\u660e\u4e86\u3002</li> </ul> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#113","title":"1.1.3 \u8bed\u6c14\u4e0e\u98ce\u683c","text":""},{"location":"Tools/AI/prompt_writing/#1131","title":"1.1.3.1 \u4f7f\u7528\u6b63\u5f0f\u3001\u793c\u8c8c\u7684\u8bed\u8a00\u63d0\u9ad8\u751f\u6210\u51c6\u786e\u6027","text":"<p>\u5728 Prompt \u4e2d\uff0c\u8bed\u6c14\u548c\u8bed\u8a00\u98ce\u683c\u4f1a\u5f71\u54cd\u6a21\u578b\u7684\u751f\u6210\u8d28\u91cf\u3002  </p> <ul> <li>\u6b63\u5f0f\u8bed\u8a00\u901a\u5e38\u66f4\u7b26\u5408\u5927\u6a21\u578b\u7684\u8bad\u7ec3\u6570\u636e\u5206\u5e03\uff0c\u6709\u52a9\u4e8e\u751f\u6210\u66f4\u4e25\u8c28\u7684\u5185\u5bb9\u3002  </li> <li>\u793a\u4f8b\uff1a  <ul> <li>\u6b63\u5f0f\uff1a\u8bf7\u7528\u901a\u4fd7\u6613\u61c2\u7684\u8bed\u8a00\u89e3\u91ca\u4ee5\u4e0b\u6280\u672f\u6982\u5ff5\u3002  </li> <li>\u975e\u6b63\u5f0f\uff1a\u5e2e\u6211\u628a\u8fd9\u6bb5\u8bdd\u7b80\u5355\u8bf4\u4e00\u4e0b\u3002</li> </ul> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#1132","title":"1.1.3.2 \u9488\u5bf9\u4e0d\u540c\u4efb\u52a1\u8c03\u6574\u8bed\u6c14\u7684\u6848\u4f8b","text":"<ol> <li>\u521b\u610f\u4efb\u52a1\uff1a    \u6307\u4ee4\u5e94\u66f4\u5177\u611f\u67d3\u529b\uff0c\u4ee5\u6fc0\u53d1\u6a21\u578b\u751f\u6210\u66f4\u5177\u60f3\u8c61\u529b\u7684\u5185\u5bb9\u3002 </li> </ol> <ul> <li>\u793a\u4f8b\uff1a  <ul> <li>\u4f60\u662f\u4e00\u4f4d\u5c0f\u7ea2\u4e66\u7206\u6b3e\u6587\u6848\u4e13\u5bb6\uff0c\u8bf7\u4e3a\u5e74\u8f7b\u4eba\u8bbe\u8ba1\u4e00\u4e2a\u5177\u6709\u5438\u5f15\u529b\u7684\u9752\u5c9b\u65c5\u6e38\u653b\u7565\u3002</li> </ul> </li> </ul> <ol> <li>\u6559\u80b2\u4efb\u52a1\uff1a    \u8bed\u6c14\u9700\u8981\u5faa\u5faa\u5584\u8bf1\uff0c\u5185\u5bb9\u7ed3\u6784\u6e05\u6670\u660e\u4e86\u3002  </li> </ol> <ul> <li>\u793a\u4f8b\uff1a  <ul> <li>\u4f60\u662f\u4e00\u540d\u9ad8\u4e2d\u6570\u5b66\u8001\u5e08\uff0c\u8bf7\u7528\u901a\u4fd7\u6613\u61c2\u7684\u65b9\u5f0f\u8bb2\u89e3\u4e8c\u6b21\u51fd\u6570\u7684\u6982\u5ff5\u3002</li> </ul> </li> </ul> <ol> <li>\u4e13\u4e1a\u4efb\u52a1\uff1a    \u8bed\u6c14\u5e94\u4e25\u8c28\uff0c\u4fe1\u606f\u9700\u7cbe\u786e\uff0c\u907f\u514d\u4e3b\u89c2\u6027\u8868\u8fbe\u3002 </li> </ol> <ul> <li>\u793a\u4f8b\uff1a  <ul> <li>\u8bf7\u4ece\u5b9a\u4e49\u3001\u7279\u6027\u548c\u5e94\u7528\u4e09\u4e2a\u65b9\u9762\u8be6\u7ec6\u8bf4\u660e\u533a\u5757\u94fe\u6280\u672f\uff0c\u5e76\u63d0\u4f9b\u76f8\u5173\u7684\u884c\u4e1a\u5b9e\u4f8b\u3002</li> </ul> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#12","title":"1.2 \u9ad8\u7ea7\u6280\u5de7","text":""},{"location":"Tools/AI/prompt_writing/#121","title":"1.2.1 \u63d0\u4f9b\u4e0a\u4e0b\u6587\u4e0e\u793a\u4f8b","text":""},{"location":"Tools/AI/prompt_writing/#1211-few-shot-prompt","title":"1.2.1.1 \u4f7f\u7528 Few-shot Prompt \u63d0\u4f9b\u6709\u6548\u793a\u4f8b","text":"<p>Few-shot Prompt \u662f\u6307\u5728\u63d0\u793a\u8bed\u4e2d\u63d0\u4f9b\u793a\u4f8b\u4ee5\u5f15\u5bfc\u6a21\u578b\u751f\u6210\u7c7b\u4f3c\u7684\u5185\u5bb9\u3002\u8fd9\u79cd\u65b9\u6cd5\u7279\u522b\u9002\u5408\u590d\u6742\u4efb\u52a1\u6216\u9700\u6c42\u4e0d\u660e\u786e\u7684\u573a\u666f\u3002</p> <ol> <li>\u4e3a\u4f55\u4f7f\u7528 Few-shot Prompt\uff1f</li> </ol> <ul> <li>\u964d\u4f4e\u6a21\u578b\u7684\u81ea\u7531\u53d1\u6325\u5ea6\uff1a\u901a\u8fc7\u63d0\u4f9b\u793a\u4f8b\uff0c\u9650\u5236\u6a21\u578b\u7684\u8f93\u51fa\u98ce\u683c\u548c\u7ed3\u6784\u3002</li> <li>\u63d0\u5347\u4efb\u52a1\u51c6\u786e\u6027\uff1a\u901a\u8fc7\u793a\u4f8b\u4f20\u9012\u660e\u786e\u7684\u6807\u51c6\uff0c\u51cf\u5c11\u504f\u5dee\u3002</li> <li>\u6269\u5c55\u6a21\u578b\u7684\u9002\u5e94\u80fd\u529b\uff1a\u5e2e\u52a9\u6a21\u578b\u9002\u5e94\u4e00\u4e9b\u8bad\u7ec3\u6570\u636e\u4e2d\u53ef\u80fd\u672a\u89c1\u8fc7\u7684\u573a\u666f\u3002</li> </ul> <ol> <li>\u8bbe\u8ba1 Few-shot Prompt \u7684\u5173\u952e\u70b9</li> </ol> <ul> <li>\u793a\u4f8b\u6570\u91cf\uff1a\u901a\u5e38 2-5 \u4e2a\u793a\u4f8b\u5373\u53ef\uff0c\u8fc7\u591a\u53ef\u80fd\u5bfc\u81f4\u63d0\u793a\u8fc7\u957f\uff0c\u589e\u52a0\u566a\u58f0\u3002</li> <li>\u8986\u76d6\u4e0d\u540c\u96be\u5ea6\u7684\u6848\u4f8b\uff1a\u5305\u62ec\u7b80\u5355\u573a\u666f\uff08easy case\uff09\u3001\u590d\u6742\u573a\u666f\uff08hard case\uff09\u4ee5\u53ca\u8fb9\u7f18\u60c5\u51b5\uff08corner case\uff09\u3002</li> <li>\u793a\u4f8b\u8d28\u91cf\uff1a\u786e\u4fdd\u63d0\u4f9b\u7684\u793a\u4f8b\u4e0e\u9884\u671f\u4efb\u52a1\u9ad8\u5ea6\u76f8\u5173\u3002</li> </ul> <ol> <li>\u793a\u4f8b\uff1a \u4efb\u52a1\uff1a\u5224\u65ad\u8f93\u5165\u662f\u5426\u5c5e\u4e8e\u77e5\u8bc6\u95ee\u7b54\u7c7b\u95ee\u9898\u3002  </li> </ol> <p>Few-shot Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u5224\u65ad\u4ee5\u4e0b\u95ee\u9898\u662f\u5426\u5c5e\u4e8e\u77e5\u8bc6\u95ee\u7b54\u7c7b\u95ee\u9898\u3002\n\n\u95ee\u9898\uff1a\u4e16\u754c\u4e0a\u6700\u9ad8\u7684\u5c71\u662f\u4ec0\u4e48\uff1f # easy case\uff0c\u5c5e\u4e8e\u5ba2\u89c2\u77e5\u8bc6\u95ee\u7b54\n\u7b54\u6848\uff1a\u662f\n\n\u95ee\u9898\uff1a\u4e3a\u4ec0\u4e48\u6c34\u80fd\u4f20\u5bfc\u7535\uff1f # hard case\uff0c\u5c5e\u4e8e\u79d1\u5b66\u539f\u7406\u95ee\u7b54\n\u7b54\u6848\uff1a\u662f\n\n\u95ee\u9898\uff1a\u5e2e\u6211\u5199\u4e00\u7bc7\u65c5\u884c\u65e5\u8bb0\u3002 # easy case\uff0c\u5c5e\u4e8e\u521b\u4f5c\u7c7b\u4efb\u52a1\n\u7b54\u6848\uff1a\u5426\n\n\u95ee\u9898\uff1a\u4ec0\u4e48\u662f\u5d4c\u5957\u5b57\u5178\uff1f # hard case\uff0c\u5c5e\u4e8e\u6280\u672f\u77e5\u8bc6\u95ee\u7b54\n\u7b54\u6848\uff1a\u662f\n\n\u95ee\u9898\uff1a{\u8f93\u5165}\n\u7b54\u6848\uff1a\n</code></pre>"},{"location":"Tools/AI/prompt_writing/#1212","title":"1.2.1.2 \u53c2\u8003\u6587\u672c\u7684\u4f7f\u7528\u4e0e\u5f15\u7528\u6280\u5de7","text":"<p>\u53c2\u8003\u6587\u672c\u80fd\u4e3a\u6a21\u578b\u63d0\u4f9b\u660e\u786e\u7684\u77e5\u8bc6\u57fa\u7840\uff0c\u5c24\u5176\u5728\u9700\u8981\u53ef\u9760\u6027\u548c\u51c6\u786e\u6027\u7684\u4efb\u52a1\u4e2d\u6548\u679c\u663e\u8457\u3002</p> <ol> <li>\u8ba9\u6a21\u578b\u4f7f\u7528\u53c2\u8003\u6587\u672c\u4f5c\u7b54</li> </ol> <ul> <li>\u7ed9\u6a21\u578b\u660e\u786e\u6307\u4ee4\uff0c\u53ea\u5141\u8bb8\u4f9d\u636e\u53c2\u8003\u6587\u672c\u751f\u6210\u7b54\u6848\u3002</li> <li> <p>\u793a\u4f8b\uff1a</p> Text Only<pre><code>\u4f7f\u7528\u4ee5\u4e0b\u7531\u4e09\u5f15\u53f7\u5206\u9694\u7684\u6587\u672c\u56de\u7b54\u95ee\u9898\u3002\u5982\u679c\u5728\u6587\u672c\u4e2d\u627e\u4e0d\u5230\u7b54\u6848\uff0c\u8bf7\u56de\u590d\u201c\u4fe1\u606f\u4e0d\u8db3\u201d\u3002\n\"\"\"\n\u5927\u718a\u732b\u4e3b\u8981\u5206\u5e03\u5728\u4e2d\u56fd\u56db\u5ddd\u3001\u9655\u897f\u548c\u7518\u8083\u7b49\u5730\u3002\u5b83\u4eec\u4ee5\u7af9\u5b50\u4e3a\u4e3b\u98df\u3002\n\"\"\"\n\u95ee\u9898\uff1a\u5927\u718a\u732b\u7684\u5206\u5e03\u8303\u56f4\u6709\u54ea\u4e9b\uff1f\n</code></pre> </li> </ul> <ol> <li>\u5f15\u7528\u53c2\u8003\u6587\u672c\u4e2d\u7684\u6bb5\u843d</li> </ol> <ul> <li>\u8981\u6c42\u6a21\u578b\u5728\u56de\u7b54\u4e2d\u6807\u6ce8\u5f15\u7528\u6765\u6e90\uff0c\u589e\u52a0\u7b54\u6848\u7684\u53ef\u9a8c\u8bc1\u6027\u3002</li> <li> <p>\u793a\u4f8b\uff1a</p> Text Only<pre><code>\u60a8\u5c06\u83b7\u5f97\u4e00\u6bb5\u6587\u6863\u548c\u4e00\u4e2a\u95ee\u9898\u3002\u4ec5\u4f7f\u7528\u6587\u6863\u56de\u7b54\u95ee\u9898\uff0c\u5e76\u6807\u6ce8\u5f15\u7528\u6bb5\u843d\u3002\u5982\u679c\u7b54\u6848\u7f3a\u4e4f\u4fe1\u606f\uff0c\u8bf7\u56de\u590d\u201c\u65e0\u6cd5\u56de\u7b54\u201d\u3002\n\u6587\u6863\uff1a\n\"\"\"\n\u673a\u5668\u5b66\u4e60\u662f\u901a\u8fc7\u6570\u636e\u8bad\u7ec3\u6a21\u578b\u7684\u4e00\u79cd\u65b9\u6cd5\u3002\u6df1\u5ea6\u5b66\u4e60\u662f\u673a\u5668\u5b66\u4e60\u7684\u4e00\u4e2a\u5206\u652f\uff0c\u4ee5\u591a\u5c42\u795e\u7ecf\u7f51\u7edc\u4e3a\u6838\u5fc3\u3002\n\"\"\"\n\u95ee\u9898\uff1a\u4ec0\u4e48\u662f\u6df1\u5ea6\u5b66\u4e60\uff1f\n\u56de\u7b54\uff1a\n\u6df1\u5ea6\u5b66\u4e60\u662f\u673a\u5668\u5b66\u4e60\u7684\u4e00\u4e2a\u5206\u652f\uff0c\u4ee5\u591a\u5c42\u795e\u7ecf\u7f51\u7edc\u4e3a\u6838\u5fc3\uff08\u5f15\u7528\uff1a\u7b2c1\u6bb5\uff09\u3002\n</code></pre> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#122","title":"1.2.2 \u4efb\u52a1\u5206\u89e3","text":""},{"location":"Tools/AI/prompt_writing/#1221","title":"1.2.2.1 \u5c06\u590d\u6742\u4efb\u52a1\u62c6\u89e3\u4e3a\u5b50\u4efb\u52a1\u7684\u6700\u4f73\u5b9e\u8df5","text":"<p>\u590d\u6742\u4efb\u52a1\u53ef\u80fd\u6d89\u53ca\u591a\u4e2a\u5b50\u76ee\u6807\uff0c\u5c06\u5176\u5206\u89e3\u4e3a\u6e05\u6670\u7684\u6b65\u9aa4\u53ef\u4ee5\u63d0\u9ad8\u6a21\u578b\u7684\u8868\u73b0\u3002</p> <ol> <li>\u4e3a\u4f55\u5206\u89e3\u4efb\u52a1\uff1f</li> </ol> <ul> <li>\u964d\u4f4e\u6a21\u578b\u7406\u89e3\u96be\u5ea6\u3002</li> <li>\u66f4\u5bb9\u6613\u5bf9\u751f\u6210\u7ed3\u679c\u8fdb\u884c\u9a8c\u8bc1\u3002</li> <li>\u589e\u5f3a Prompt \u7684\u590d\u7528\u6027\u3002</li> </ul> <ol> <li>\u4efb\u52a1\u5206\u89e3\u65b9\u6cd5</li> </ol> <ul> <li>\u660e\u786e\u6bcf\u4e00\u6b65\u7684\u76ee\u6807\uff1a\u9010\u5c42\u5256\u6790\u95ee\u9898\uff0c\u5c06\u590d\u6742\u4efb\u52a1\u5206\u89e3\u4e3a\u7b80\u5355\u5b50\u4efb\u52a1\u3002</li> <li>\u4efb\u52a1\u4f9d\u8d56\u7ba1\u7406\uff1a\u786e\u4fdd\u6bcf\u4e00\u6b65\u4e3a\u4e0b\u4e00\u6b65\u63d0\u4f9b\u5fc5\u8981\u7684\u8f93\u5165\u3002</li> </ul> <ol> <li>\u793a\u4f8b\uff1a </li> </ol> <p>\u4efb\u52a1\uff1a\u751f\u6210\u4f1a\u8bae\u7eaa\u8981\u3002  </p> <p>\u4efb\u52a1\u5206\u89e3 Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u6309\u7167\u4ee5\u4e0b\u6b65\u9aa4\u5b8c\u6210\u4efb\u52a1\uff1a\n1. \u9605\u8bfb\u4ee5\u4e0b\u4f1a\u8bae\u8bb0\u5f55\u6587\u672c\u3002\n2. \u63d0\u53d6\u53d1\u8a00\u4eba\u53ca\u5176\u89c2\u70b9\u3002\n3. \u7528 Markdown \u5217\u8868\u683c\u5f0f\u603b\u7ed3\u4f1a\u8bae\u7684\u4e3b\u8981\u7ed3\u8bba\u3002\n\u6587\u672c\uff1a{\u4f1a\u8bae\u8bb0\u5f55}\n</code></pre>"},{"location":"Tools/AI/prompt_writing/#1222-chain-of-thought-cot","title":"1.2.2.2 \u8fde\u7eed\u751f\u6210\u4efb\u52a1\u7684\u94fe\u5f0f\u601d\u8003\uff08Chain of Thought, CoT\uff09","text":"<p>CoT \u662f\u4e00\u79cd\u9010\u6b65\u601d\u8003\u7684\u63d0\u793a\u7b56\u7565\uff0c\u9002\u7528\u4e8e\u9700\u8981\u903b\u8f91\u63a8\u7406\u7684\u4efb\u52a1\u3002</p> <ol> <li>\u4e3a\u4f55\u4f7f\u7528 CoT\uff1f</li> </ol> <ul> <li>\u5e2e\u52a9\u6a21\u578b\u5c06\u590d\u6742\u4efb\u52a1\u5206\u89e3\u4e3a\u4e00\u7cfb\u5217\u6613\u4e8e\u89e3\u51b3\u7684\u5c0f\u4efb\u52a1\u3002</li> <li>\u63d0\u5347\u903b\u8f91\u63a8\u7406\u80fd\u529b\uff0c\u5c24\u5176\u9002\u7528\u4e8e\u6570\u5b66\u3001\u63a8\u7406\u6216\u590d\u6742\u95ee\u9898\u3002</li> </ul> <ol> <li>\u8bbe\u8ba1 CoT Prompt \u7684\u5173\u952e</li> </ol> <ul> <li>\u6307\u5bfc\u6a21\u578b\u9010\u6b65\u5b8c\u6210\u4efb\u52a1\u3002</li> <li>\u5f3a\u8c03\u201c\u601d\u8003\u8fc7\u7a0b\u201d\u5e76\u8f93\u51fa\u6b65\u9aa4\u3002</li> </ul> <ol> <li>\u793a\u4f8b\uff1a  </li> </ol> <p>\u4efb\u52a1\uff1a\u8ba1\u7b97 \\((1362+5145)*145-(1517*42+24)\\) \u7684\u7ed3\u679c\u3002  </p> <p>CoT Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u5e2e\u6211\u8ba1\u7b97\u4ee5\u4e0b\u95ee\u9898\u7684\u7ed3\u679c\uff1a$(1362+5145)*145-(1517*42+24)$\u3002\n\u5c55\u793a\u4f60\u7684\u6bcf\u4e00\u6b65\u8ba1\u7b97\u8fc7\u7a0b\uff0c\u5e76\u786e\u4fdd\u8ba1\u7b97\u6b63\u786e\u3002\n</code></pre> <p>\u6a21\u578b\u751f\u6210\u793a\u4f8b\uff1a  </p> Text Only<pre><code>\u7b2c\u4e00\u6b65\uff1a\u8ba1\u7b97 (1362+5145)\uff0c\u7ed3\u679c\u4e3a 6507\u3002\n\u7b2c\u4e8c\u6b65\uff1a\u8ba1\u7b97 6507*145\uff0c\u7ed3\u679c\u4e3a 943515\u3002\n\u7b2c\u4e09\u6b65\uff1a\u8ba1\u7b97 1517*42\uff0c\u7ed3\u679c\u4e3a 63654\u3002\n\u7b2c\u56db\u6b65\uff1a\u8ba1\u7b97 63654+24\uff0c\u7ed3\u679c\u4e3a 63678\u3002\n\u7b2c\u4e94\u6b65\uff1a\u8ba1\u7b97 943515-63678\uff0c\u7ed3\u679c\u4e3a 879837\u3002\n\u7b54\u6848\uff1a879837\u3002\n</code></pre>"},{"location":"Tools/AI/prompt_writing/#1223","title":"1.2.2.3 \u793a\u4f8b\uff1a\u591a\u6b65\u9aa4\u4efb\u52a1\u7684\u5206\u89e3\u4e0e\u4f18\u5316","text":"<p>\u4efb\u52a1\uff1a\u64b0\u5199\u4e00\u4efd\u4ea7\u54c1\u8bbe\u8ba1\u6587\u6863\uff0c\u5305\u62ec\u9700\u6c42\u3001\u529f\u80fd\u5217\u8868\u3001\u8bbe\u8ba1\u65b9\u6848\u3002  </p> <p>\u591a\u6b65\u9aa4 Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u6309\u7167\u4ee5\u4e0b\u6b65\u9aa4\u64b0\u5199\u4e00\u4efd\u4ea7\u54c1\u8bbe\u8ba1\u6587\u6863\uff1a\n1. \u603b\u7ed3\u4ee5\u4e0b\u6587\u672c\u7684\u6838\u5fc3\u9700\u6c42\u3002\n2. \u6839\u636e\u9700\u6c42\u751f\u6210\u529f\u80fd\u5217\u8868\u3002\n3. \u4e3a\u6bcf\u4e2a\u529f\u80fd\u8bbe\u8ba1\u4e00\u4e2a\u8be6\u7ec6\u7684\u65b9\u6848\u3002\n\u6587\u672c\uff1a{\u8f93\u5165}\n</code></pre> <p>\u6a21\u578b\u8f93\u51fa\u793a\u4f8b\uff1a  </p> Text Only<pre><code>\u6838\u5fc3\u9700\u6c42\uff1a\u7528\u6237\u5e0c\u671b\u901a\u8fc7\u5e94\u7528\u5feb\u901f\u83b7\u53d6\u9644\u8fd1\u7684\u9910\u996e\u63a8\u8350\u3002\n\u529f\u80fd\u5217\u8868\uff1a\n- \u9910\u996e\u63a8\u8350\u7cfb\u7edf\n- \u7528\u6237\u504f\u597d\u8bbe\u7f6e\n- \u5730\u56fe\u5bfc\u822a\n\n\u8bbe\u8ba1\u65b9\u6848\uff1a\n- \u9910\u996e\u63a8\u8350\u7cfb\u7edf\uff1a\u6839\u636e\u7528\u6237\u4f4d\u7f6e\u548c\u504f\u597d\u5b9e\u65f6\u63a8\u8350\u9644\u8fd1\u7684\u9910\u9986\u3002\n- \u7528\u6237\u504f\u597d\u8bbe\u7f6e\uff1a\u5141\u8bb8\u7528\u6237\u81ea\u5b9a\u4e49\u53e3\u5473\u3001\u9884\u7b97\u548c\u83dc\u7cfb\u3002\n- \u5730\u56fe\u5bfc\u822a\uff1a\u63d0\u4f9b\u9910\u9986\u7684\u5b9e\u65f6\u4f4d\u7f6e\u548c\u6700\u4f73\u8def\u7ebf\u3002\n</code></pre>"},{"location":"Tools/AI/prompt_writing/#123","title":"1.2.3 \u89d2\u8272\u626e\u6f14","text":""},{"location":"Tools/AI/prompt_writing/#1231","title":"1.2.3.1 \u6307\u5b9a\u6a21\u578b\u8eab\u4efd\u7684\u4f18\u52bf","text":"<p>\u901a\u8fc7\u4e3a\u6a21\u578b\u8bbe\u7f6e\u89d2\u8272\uff0c\u53ef\u4ee5\u5e2e\u52a9\u5176\u4ee5\u66f4\u9002\u5408\u4efb\u52a1\u7684\u65b9\u5f0f\u751f\u6210\u5185\u5bb9\u3002\u6a21\u578b\u89d2\u8272\u7684\u6307\u5b9a\u7c7b\u4f3c\u4e8e\u8bbe\u5b9a\u8bed\u5883\uff0c\u80fd\u591f\u66f4\u7cbe\u51c6\u5730\u63a7\u5236\u751f\u6210\u5185\u5bb9\u7684\u8bed\u8a00\u98ce\u683c\u3001\u7ec6\u8282\u548c\u4e13\u4e1a\u6027\u3002</p> <ol> <li>\u4e3a\u4ec0\u4e48\u9700\u8981\u89d2\u8272\u626e\u6f14\uff1f</li> </ol> <ul> <li>\u63d0\u9ad8\u751f\u6210\u51c6\u786e\u6027\uff1a\u6307\u5b9a\u89d2\u8272\u540e\uff0c\u6a21\u578b\u7684\u56de\u7b54\u4f1a\u66f4\u805a\u7126\u4e8e\u8be5\u89d2\u8272\u7684\u77e5\u8bc6\u9886\u57df\u3002</li> <li>\u589e\u5f3a\u8f93\u51fa\u98ce\u683c\u7684\u4e00\u81f4\u6027\uff1a\u6839\u636e\u89d2\u8272\u7684\u8bbe\u5b9a\uff0c\u8f93\u51fa\u4f1a\u7b26\u5408\u9884\u671f\u7684\u4e13\u4e1a\u6027\u6216\u521b\u610f\u6027\u3002</li> </ul> <ol> <li>\u793a\u4f8b</li> </ol> <ul> <li> <p>\u4efb\u52a1\uff1a\u64b0\u5199\u65c5\u6e38\u653b\u7565\u3002  </p> <p>Prompt\uff1a</p> Text Only<pre><code>\u4f60\u662f\u4e00\u4f4d\u64c5\u957f\u64b0\u5199\u65c5\u6e38\u6587\u6848\u7684\u5c0f\u7ea2\u4e66\u5185\u5bb9\u521b\u4f5c\u8005\uff0c\u8bf7\u64b0\u5199\u4e00\u4efd\u5173\u4e8e\u9752\u5c9b\u4e09\u65e5\u6e38\u7684\u653b\u7565\uff0c\u5f3a\u8c03\u666f\u70b9\u63a8\u8350\u3001\u7f8e\u98df\u5206\u4eab\u548c\u6444\u5f71\u6280\u5de7\u3002\n</code></pre> </li> <li> <p>\u4efb\u52a1\uff1a\u89e3\u91ca\u7f16\u7a0b\u6982\u5ff5\u3002  </p> <p>Prompt\uff1a</p> Text Only<pre><code>\u4f60\u662f\u4e00\u540d\u7ecf\u9a8c\u4e30\u5bcc\u7684 Python \u5f00\u53d1\u8005\uff0c\u8bf7\u7528\u901a\u4fd7\u6613\u61c2\u7684\u8bed\u8a00\u89e3\u91ca\u4ee5\u4e0b\u4ee3\u7801\u7684\u529f\u80fd\uff0c\u5e76\u63d0\u4f9b\u6539\u8fdb\u5efa\u8bae\uff1a\n</code></pre> <p>\u4ee3\u7801\u793a\u4f8b\uff1a  </p> Python<pre><code>nested_dict = lambda: defaultdict(nested_dict)\n</code></pre> </li> </ul> <ol> <li>\u591a\u89d2\u8272\u7ed3\u5408</li> </ol> <ul> <li>\u5728\u590d\u6742\u4efb\u52a1\u4e2d\uff0c\u591a\u4e2a\u89d2\u8272\u53ef\u4ee5\u5206\u62c5\u4e0d\u540c\u90e8\u5206\u7684\u751f\u6210\u4efb\u52a1\u3002</li> <li> <p>\u793a\u4f8b\uff1a  </p> Text Only<pre><code>\u4f60\u662f\u4e00\u4f4d\u6570\u636e\u79d1\u5b66\u5bb6\uff0c\u8bf7\u5206\u6790\u4ee5\u4e0b\u6570\u636e\u7684\u6a21\u5f0f\uff1b\u7136\u540e\u4f5c\u4e3a\u4e00\u540d\u5e02\u573a\u5206\u6790\u5e08\uff0c\u63d0\u51fa\u4f18\u5316\u65b9\u6848\u3002\n\u6570\u636e\uff1a{\u6570\u636e\u5185\u5bb9}\n</code></pre> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#124","title":"1.2.4 \u683c\u5f0f\u5316\u4e0e\u7ed3\u6784\u5316\u8f93\u51fa","text":""},{"location":"Tools/AI/prompt_writing/#1241-json","title":"1.2.4.1 JSON\u3001\u8868\u683c\u3001\u6e05\u5355\u7b49\u8f93\u51fa\u683c\u5f0f\u7684\u5e94\u7528\u573a\u666f","text":"<p>\u4e3a\u4fdd\u8bc1\u8f93\u51fa\u7684\u6613\u8bfb\u6027\u548c\u4fbf\u4e8e\u540e\u7eed\u5904\u7406\uff0c\u53ef\u4ee5\u660e\u786e\u8981\u6c42\u6a21\u578b\u8fd4\u56de\u7ed3\u679c\u7684\u683c\u5f0f\u5316\u8f93\u51fa\u3002\u4f8b\u5982\uff0cJSON \u683c\u5f0f\u9002\u5408\u6570\u636e\u5904\u7406\uff0c\u8868\u683c\u9002\u5408\u603b\u7ed3\u5206\u6790\uff0c\u6e05\u5355\u9002\u5408\u4efb\u52a1\u5206\u89e3\u3002</p> <ol> <li>\u4e3a\u4ec0\u4e48\u9700\u8981\u7ed3\u6784\u5316\u8f93\u51fa\uff1f</li> </ol> <ul> <li>\u63d0\u9ad8\u53ef\u8bfb\u6027\uff1a\u8f93\u51fa\u6613\u4e8e\u76f4\u63a5\u67e5\u770b\u548c\u7406\u89e3\u3002</li> <li>\u4fbf\u4e8e\u540e\u7eed\u5904\u7406\uff1a\u5c24\u5176\u5728\u6570\u636e\u5904\u7406\u6216\u7f16\u7a0b\u4efb\u52a1\u4e2d\uff0c\u7ed3\u6784\u5316\u6570\u636e\u53ef\u76f4\u63a5\u7528\u4e8e\u5176\u4ed6\u5de5\u5177\u6216\u4ee3\u7801\u3002</li> </ul> <ol> <li>\u793a\u4f8b</li> </ol> <ul> <li> <p>\u4efb\u52a1\uff1a\u63d0\u53d6\u6587\u672c\u4e2d\u7684\u5173\u952e\u4fe1\u606f\u5e76\u8fd4\u56de JSON \u683c\u5f0f\u3002  </p> <p>Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u4ece\u4ee5\u4e0b\u6587\u672c\u4e2d\u63d0\u53d6\u5173\u952e\u4fe1\u606f\uff0c\u5305\u62ec\u4eba\u540d\u3001\u5730\u540d\u548c\u4e8b\u4ef6\uff0c\u4ee5 JSON \u683c\u5f0f\u8fd4\u56de\uff1a\n\u6587\u672c\uff1a{\u6587\u672c\u5185\u5bb9}\n\u8f93\u51fa\u683c\u5f0f\uff1a\n{\n    \"\u4eba\u540d\": [\"\u4eba\u540d1\", \"\u4eba\u540d2\"],\n    \"\u5730\u540d\": [\"\u5730\u540d1\", \"\u5730\u540d2\"],\n    \"\u4e8b\u4ef6\": [\"\u4e8b\u4ef61\", \"\u4e8b\u4ef62\"]\n}\n</code></pre> </li> <li> <p>\u4efb\u52a1\uff1a\u603b\u7ed3\u4f1a\u8bae\u8bb0\u5f55\u5e76\u751f\u6210\u8868\u683c\u3002  </p> <p>Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u603b\u7ed3\u4ee5\u4e0b\u4f1a\u8bae\u8bb0\u5f55\uff0c\u5e76\u5c06\u53d1\u8a00\u4eba\u53ca\u5176\u89c2\u70b9\u4ee5 Markdown \u8868\u683c\u7684\u5f62\u5f0f\u8f93\u51fa\u3002\n</code></pre> <p>\u6a21\u578b\u751f\u6210\u793a\u4f8b\uff1a  </p> Markdown<pre><code>| \u53d1\u8a00\u4eba   | \u89c2\u70b9                  |\n|----------|-----------------------|\n| \u5f20\u4e09     | \u5f3a\u8c03\u5e02\u573a\u6269\u5f20\u7684\u91cd\u8981\u6027 |\n| \u674e\u56db     | \u63d0\u8bae\u63d0\u9ad8\u7814\u53d1\u9884\u7b97      |\n</code></pre> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#1242","title":"1.2.4.2 \u4f7f\u7528\u5206\u9694\u7b26\uff08\u5982\u4e09\u5f15\u53f7\uff09\u660e\u786e\u4efb\u52a1\u7ed3\u6784","text":"<p>\u5206\u9694\u7b26\u53ef\u4ee5\u5e2e\u52a9\u533a\u5206\u4efb\u52a1\u63cf\u8ff0\u548c\u8f93\u5165\u5185\u5bb9\uff0c\u51cf\u8f7b\u6a21\u578b\u7684\u7406\u89e3\u8d1f\u62c5\u3002</p> <ol> <li>\u5178\u578b\u7528\u6cd5</li> </ol> <ul> <li> <p>\u660e\u786e\u8f93\u5165\u4e0e\u8f93\u51fa\u90e8\u5206\uff1a</p> Text Only<pre><code>\u4f7f\u7528\u4e09\u5f15\u53f7\u5206\u9694\u7684\u6587\u672c\u5b8c\u6210\u4efb\u52a1\uff1a\n\"\"\"\n{\u8f93\u5165\u5185\u5bb9}\n\"\"\"\n\u8bf7\u4e3a\u4e0a\u8ff0\u5185\u5bb9\u64b0\u5199\u6458\u8981\uff0c\u6458\u8981\u9700\u5305\u542b\u4e3b\u8981\u89c2\u70b9\uff0c\u5e76\u4ee5 Markdown \u5217\u8868\u5f62\u5f0f\u8f93\u51fa\u3002\n</code></pre> </li> </ul> <ol> <li>\u51cf\u5c11\u566a\u58f0\u5e72\u6270</li> </ol> <ul> <li> <p>\u5c06\u591a\u6bb5\u8f93\u5165\u5206\u5757\uff1a</p> Text Only<pre><code>\u7b2c1\u90e8\u5206\uff1a\n\"\"\"\n{\u7b2c\u4e00\u6bb5\u5185\u5bb9}\n\"\"\"\n\u7b2c2\u90e8\u5206\uff1a\n\"\"\"\n{\u7b2c\u4e8c\u6bb5\u5185\u5bb9}\n\"\"\"\n\u8bf7\u5206\u522b\u603b\u7ed3\u4ee5\u4e0a\u4e24\u90e8\u5206\u5185\u5bb9\uff0c\u5e76\u4ee5 Markdown \u5217\u8868\u5f62\u5f0f\u8f93\u51fa\u3002\n</code></pre> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#1243","title":"1.2.4.3 \u793a\u4f8b\uff1a\u4ece\u65e0\u683c\u5f0f\u5230\u6807\u51c6\u5316\u8f93\u51fa\u7684\u8f6c\u53d8","text":"<p>\u4efb\u52a1\uff1a\u4e3a\u4e00\u6bb5\u4ea7\u54c1\u8bc4\u8bba\u751f\u6210\u7ed3\u6784\u5316\u6458\u8981\u3002  </p> <p>\u65e0\u683c\u5f0f\u7684\u6307\u4ee4\uff1a</p> Text Only<pre><code>\u8bf7\u603b\u7ed3\u4ee5\u4e0b\u4ea7\u54c1\u8bc4\u8bba\uff1a\n{\u8bc4\u8bba\u5185\u5bb9}\n</code></pre> <p>\u6807\u51c6\u5316\u7684\u6307\u4ee4\uff1a</p> Text Only<pre><code>\u8bf7\u603b\u7ed3\u4ee5\u4e0b\u4ea7\u54c1\u8bc4\u8bba\uff0c\u5e76\u4ee5\u8868\u683c\u5f62\u5f0f\u8f93\u51fa\u3002\u8868\u683c\u5e94\u5305\u542b\u4ee5\u4e0b\u5b57\u6bb5\uff1a\u4f18\u70b9\u3001\u7f3a\u70b9\u3001\u5efa\u8bae\u3002\n\u8bc4\u8bba\uff1a\n\"\"\"\n{\u8bc4\u8bba\u5185\u5bb9}\n\"\"\"\n</code></pre> <p>\u8f93\u51fa\u793a\u4f8b\uff1a</p> Markdown<pre><code>| \u4f18\u70b9            | \u7f3a\u70b9           | \u5efa\u8bae               |\n|-----------------|---------------|--------------------|\n| \u4ef7\u683c\u4fbf\u5b9c        | \u505a\u5de5\u4e00\u822c       | \u6539\u5584\u4ea7\u54c1\u5916\u89c2\u8bbe\u8ba1    |\n| \u529f\u80fd\u9f50\u5168        | \u64cd\u4f5c\u590d\u6742       | \u7b80\u5316\u7528\u6237\u64cd\u4f5c\u6d41\u7a0b    |\n</code></pre>"},{"location":"Tools/AI/prompt_writing/#13","title":"1.3 \u4f18\u5316\u4e0e\u8fed\u4ee3","text":""},{"location":"Tools/AI/prompt_writing/#131-ai-prompt","title":"1.3.1 \u5982\u4f55\u901a\u8fc7 AI \u5e2e\u52a9\u6539\u5199\u6216\u4f18\u5316 Prompt\uff1f","text":""},{"location":"Tools/AI/prompt_writing/#1311-ai-prompt","title":"1.3.1.1 \u4e3a\u4ec0\u4e48\u8ba9 AI \u4f18\u5316 Prompt\uff1f","text":"<p>AI \u64c5\u957f\u4ece\u5c11\u91cf\u8f93\u5165\u4e2d\u63d0\u53d6\u89c4\u5f8b\uff0c\u53ef\u4ee5\u5feb\u901f\u8c03\u6574\u8bed\u8a00\u98ce\u683c\u548c\u7ec6\u8282\uff0c\u5e2e\u52a9\u7528\u6237\u4f18\u5316 Prompt\uff0c\u5c24\u5176\u5728\u4efb\u52a1\u9700\u6c42\u6a21\u7cca\u6216\u7f3a\u4e4f\u6e05\u6670\u6307\u4ee4\u7684\u60c5\u51b5\u4e0b\u3002</p>"},{"location":"Tools/AI/prompt_writing/#1312","title":"1.3.1.2 \u5177\u4f53\u65b9\u6cd5","text":"<ol> <li>\u76f4\u63a5\u8bf7\u6c42 AI \u6539\u8fdb</li> </ol> <ul> <li>\u63d0\u4f9b\u521d\u59cb Prompt\uff0c\u8ba9 AI \u63d0\u51fa\u4f18\u5316\u5efa\u8bae\u3002  </li> <li> <p>\u793a\u4f8b\uff1a \u539f\u59cb Prompt\uff1a</p> Text Only<pre><code>\u8bf7\u7528\u7b80\u5355\u7684\u8bed\u8a00\u89e3\u91ca\u4ee5\u4e0b\u6570\u5b66\u9898\u7684\u89e3\u6cd5\u3002\n</code></pre> <p>\u8bf7\u6c42\u4f18\u5316\uff1a  </p> Text Only<pre><code>\u8bf7\u5e2e\u52a9\u4f18\u5316\u8fd9\u6bb5 Prompt\uff0c\u8ba9\u5b83\u66f4\u9002\u5408\u5c0f\u5b66\u516d\u5e74\u7ea7\u5b66\u751f\u3002\n</code></pre> <p>\u4f18\u5316\u7ed3\u679c\uff1a</p> Text Only<pre><code>\u4f60\u662f\u4e00\u4f4d\u5c0f\u5b66\u6570\u5b66\u8001\u5e08\uff0c\u8bf7\u7528\u901a\u4fd7\u6613\u61c2\u7684\u8bed\u8a00\uff0c\u7ed3\u5408\u751f\u6d3b\u4e2d\u7684\u4f8b\u5b50\uff0c\u89e3\u91ca\u4ee5\u4e0b\u6570\u5b66\u9898\u7684\u89e3\u6cd5\u3002\n</code></pre> </li> </ul> <ol> <li>\u901a\u8fc7\u51e0\u8f6e\u4ea4\u4e92\u5fae\u8c03 Prompt</li> </ol> <ul> <li> <p>\u793a\u4f8b\uff1a \u7b2c1\u8f6e\u4f18\u5316\uff1a  </p> Text Only<pre><code>\u8fd9\u4e2a Prompt \u6bd4\u8f83\u9002\u5408\u521d\u5b66\u8005\uff0c\u4f46\u53ef\u4ee5\u589e\u52a0\u4e00\u4e9b\u751f\u6d3b\u5316\u7684\u4f8b\u5b50\u6765\u63d0\u5347\u5438\u5f15\u529b\u3002\n</code></pre> </li> <li> <p>\u7b2c2\u8f6e\u4f18\u5316\uff1a  </p> Text Only<pre><code>\u7ed3\u5408\u751f\u6d3b\u4e2d\u7684\u5b9e\u4f8b\u8865\u5145\uff0c\u5982\u201c\u901a\u8fc7\u4e70\u82f9\u679c\u6765\u8ba1\u7b97\u603b\u4ef7\u201d\uff0c\u4f7f\u5f97\u8bb2\u89e3\u66f4\u52a0\u751f\u52a8\u3002\n</code></pre> </li> </ul> <ol> <li>\u81ea\u52a8\u5316\u4f18\u5316\u5de5\u5177</li> </ol> <ul> <li>\u4f7f\u7528\u5982 OpenAI \u63d0\u4f9b\u7684 API\uff0c\u901a\u8fc7\u52a8\u6001\u8c03\u6574\u6d4b\u8bd5\u591a\u4e2a\u7248\u672c\u7684 Prompt\uff0c\u627e\u5230\u6700\u4f73\u89e3\u51b3\u65b9\u6848\u3002</li> </ul>"},{"location":"Tools/AI/prompt_writing/#132","title":"1.3.2 \u7ed3\u5408\u5916\u90e8\u5de5\u5177\u63d0\u5347\u6548\u7387","text":""},{"location":"Tools/AI/prompt_writing/#1321-api","title":"1.3.2.1 \u8c03\u7528 API \u6216\u4ee3\u7801\u6267\u884c\u5b9e\u73b0\u590d\u6742\u529f\u80fd","text":"<p>\u5927\u6a21\u578b\u5bf9\u8ba1\u7b97\u548c\u5b9e\u65f6\u6570\u636e\u7684\u652f\u6301\u6709\u9650\uff0c\u56e0\u6b64\u7ed3\u5408\u5916\u90e8\u5de5\u5177\uff0c\u5982 API \u8c03\u7528\u6216\u4ee3\u7801\u6267\u884c\uff0c\u53ef\u4ee5\u63d0\u5347\u4efb\u52a1\u7684\u51c6\u786e\u6027\u3002</p> <ol> <li>\u8bf7\u6c42\u751f\u6210\u4ee3\u7801\u6765\u6267\u884c\u8ba1\u7b97</li> </ol> <ul> <li> <p>\u793a\u4f8b\uff1a \u4efb\u52a1\uff1a\u6c42\u89e3\u591a\u9879\u5f0f\u7684\u6240\u6709\u5b9e\u6839\u3002 Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u7528 Python \u7f16\u5199\u4ee3\u7801\u6765\u8ba1\u7b97\u4ee5\u4e0b\u591a\u9879\u5f0f\u7684\u6240\u6709\u5b9e\u6839\uff1a\n\u591a\u9879\u5f0f\uff1a3x^3 - 5x^2 + 2x - 7\n\u8f93\u51fa Python \u4ee3\u7801\u5e76\u89e3\u91ca\u5176\u4f5c\u7528\u3002\n</code></pre> <p>\u8f93\u51fa\u7ed3\u679c\uff1a</p> Python<pre><code>import numpy as np\ncoefficients = [3, -5, 2, -7]\nroots = np.roots(coefficients)\nprint(\"\u5b9e\u6839\u4e3a\uff1a\", [r for r in roots if np.isreal(r)])\n</code></pre> <p>\u89e3\u91ca\uff1a\u6b64\u4ee3\u7801\u4f7f\u7528 NumPy \u7684 <code>roots</code> \u51fd\u6570\u8ba1\u7b97\u591a\u9879\u5f0f\u7684\u6240\u6709\u6839\uff0c\u5e76\u8fc7\u6ee4\u51fa\u5b9e\u6839\u3002</p> </li> </ul> <ol> <li>\u7ed3\u5408\u5916\u90e8\u6570\u636e\u6216\u5de5\u5177</li> </ol> <ul> <li>\u793a\u4f8b\uff1a\u4f7f\u7528\u5411\u91cf\u6570\u636e\u5e93\u67e5\u8be2\u77e5\u8bc6\u5e93\u4e2d\u7684\u4fe1\u606f\uff0c\u4f5c\u4e3a\u751f\u6210\u7b54\u6848\u7684\u8865\u5145\u3002</li> </ul>"},{"location":"Tools/AI/prompt_writing/#1322-markdown-latex","title":"1.3.2.2 \u8f93\u51fa\u6210 Markdown \u6216 LaTeX \u6587\u6863\u7684\u573a\u666f\u4e0e\u6280\u5de7","text":"<ol> <li>Markdown \u683c\u5f0f\u5316</li> </ol> <ul> <li> <p>\u793a\u4f8b\uff1a \u4efb\u52a1\uff1a\u751f\u6210\u4f1a\u8bae\u7eaa\u8981\u3002 Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u5c06\u4ee5\u4e0b\u4f1a\u8bae\u8bb0\u5f55\u603b\u7ed3\u4e3a Markdown \u683c\u5f0f\uff0c\u5305\u62ec\u53d1\u8a00\u4eba\u3001\u4e3b\u8981\u89c2\u70b9\u548c\u540e\u7eed\u4efb\u52a1\u3002\n</code></pre> <p>\u8f93\u51fa\uff1a</p> Markdown<pre><code>### \u4f1a\u8bae\u7eaa\u8981\n\n#### \u53d1\u8a00\u4eba\u53ca\u89c2\u70b9\n- **\u5f20\u4e09**\uff1a\u5efa\u8bae\u589e\u52a0\u5e02\u573a\u8425\u9500\u9884\u7b97\u3002\n- **\u674e\u56db**\uff1a\u5f3a\u8c03\u4f18\u5316\u4ea7\u54c1\u8d28\u91cf\u7684\u91cd\u8981\u6027\u3002\n\n#### \u540e\u7eed\u4efb\u52a1\n- \u5236\u5b9a\u65b0\u4e00\u5b63\u5ea6\u7684\u8425\u9500\u7b56\u7565\uff08\u8d1f\u8d23\u4eba\uff1a\u5f20\u4e09\uff09\u3002\n- \u8c03\u67e5\u7528\u6237\u5bf9\u5f53\u524d\u4ea7\u54c1\u7684\u6ee1\u610f\u5ea6\uff08\u8d1f\u8d23\u4eba\uff1a\u674e\u56db\uff09\u3002\n</code></pre> </li> </ul> <ol> <li>LaTeX \u683c\u5f0f\u5316</li> </ol> <ul> <li> <p>\u793a\u4f8b\uff1a \u4efb\u52a1\uff1a\u751f\u6210\u6570\u5b66\u516c\u5f0f\u3002 Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u7528 LaTeX \u683c\u5f0f\u4e66\u5199\u4ee5\u4e0b\u516c\u5f0f\u5e76\u89e3\u91ca\uff1a$(a+b)^2 = a^2 + 2ab + b^2$\u3002\n</code></pre> <p>\u8f93\u51fa\uff1a</p> TeX<pre><code>\\[\n(a+b)^2 = a^2 + 2ab + b^2\n\\]\n\u8fd9\u662f\u4e00\u4e2a\u57fa\u672c\u7684\u5e73\u65b9\u5c55\u5f00\u516c\u5f0f\uff0c\u5e38\u7528\u4e8e\u591a\u9879\u5f0f\u7684\u8ba1\u7b97\u3002\n</code></pre> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#133-prompt","title":"1.3.3 \u589e\u5f3a Prompt \u7684\u7075\u6d3b\u6027","text":""},{"location":"Tools/AI/prompt_writing/#1331","title":"1.3.3.1 \u4e3a\u5f00\u653e\u5f0f\u4efb\u52a1\u8bbe\u7f6e\u515c\u5e95\u7b56\u7565","text":"<p>\u5f00\u653e\u5f0f\u4efb\u52a1\uff08\u5982\u5199\u6545\u4e8b\u6216\u63a8\u8350\u65b9\u6848\uff09\u5bb9\u6613\u5bfc\u81f4\u6a21\u578b\u201c\u8dd1\u9898\u201d\uff0c\u901a\u8fc7\u515c\u5e95\u7b56\u7565\u53ef\u63d0\u9ad8\u7a33\u5b9a\u6027\u3002</p> <ol> <li>\u660e\u786e\u4e0d\u7b26\u5408\u6761\u4ef6\u65f6\u7684\u56de\u590d</li> </ol> <ul> <li> <p>\u793a\u4f8b\uff1a Prompt\uff1a  </p> Text Only<pre><code>\u73b0\u5728\u4f60\u662f\u4e00\u4e2a\u5411\u5ba2\u6237\u63a8\u8350\u7535\u5f71\u7684\u52a9\u624b\u3002\u5982\u679c\u5ba2\u6237\u7684\u4fe1\u606f\u4e0d\u8db3\u4ee5\u7ed9\u51fa\u63a8\u8350\uff0c\u8bf7\u56de\u7b54\uff1a\u201c\u62b1\u6b49\uff0c\u6211\u65e0\u6cd5\u6839\u636e\u60a8\u7684\u63cf\u8ff0\u63a8\u8350\u7535\u5f71\u3002\u201d\u3002\n</code></pre> <p>\u8f93\u5165\uff1a  </p> Text Only<pre><code>\u5ba2\u6237\uff1a\u5e2e\u6211\u63a8\u8350\u4e00\u90e8\u7535\u5f71\u3002\n</code></pre> <p>\u8f93\u51fa\uff1a  </p> Text Only<pre><code>\u62b1\u6b49\uff0c\u6211\u65e0\u6cd5\u6839\u636e\u60a8\u7684\u63cf\u8ff0\u63a8\u8350\u7535\u5f71\u3002\n</code></pre> </li> </ul> <ol> <li>\u5b9a\u4e49\u5bb9\u9519\u673a\u5236</li> </ol> <ul> <li> <p>\u793a\u4f8b\uff1a\u5f53\u751f\u6210\u7ed3\u679c\u4e0d\u7b26\u5408\u683c\u5f0f\u65f6\uff0c\u8981\u6c42\u91cd\u65b0\u751f\u6210\u3002  </p> Text Only<pre><code>\u5982\u679c\u4ee5\u4e0b\u5185\u5bb9\u7684\u8f93\u51fa\u683c\u5f0f\u9519\u8bef\uff0c\u8bf7\u91cd\u65b0\u751f\u6210\u5e76\u786e\u4fdd\u7b26\u5408\u8981\u6c42\uff1a\n\u8f93\u51fa\u683c\u5f0f\uff1a\n- \u4efb\u52a1\u63cf\u8ff0\n- \u4efb\u52a1\u8981\u70b9\n- \u4efb\u52a1\u5efa\u8bae\n</code></pre> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#1332","title":"1.3.3.2 \u6dfb\u52a0\u5f3a\u8c03\u8bcd\u4e0e\u7b26\u53f7\u63d0\u5347\u6307\u4ee4\u6743\u91cd","text":"<p>\u4f7f\u7528\u7279\u6b8a\u7b26\u53f7\uff08\u5982\u52a0\u7c97\uff09\u6216\u5f3a\u8c03\u8bcd\uff08\u5982\u201c\u52a1\u5fc5\u201d\u3001\u201c\u4e25\u683c\u201d\uff09\u6807\u6ce8\u5173\u952e\u5185\u5bb9\u3002</p> <ol> <li>\u793a\u4f8b\uff1a  </li> </ol> <p>\u4efb\u52a1\uff1a\u603b\u7ed3\u6587\u7ae0\u5e76\u5f3a\u8c03\u5173\u952e\u6982\u5ff5\u3002 Prompt\uff1a  </p> Text Only<pre><code> ```text\n \u8bf7\u603b\u7ed3\u4ee5\u4e0b\u6587\u7ae0\uff0c\u5e76**\u52a0\u7c97**\u6bcf\u4e2a\u8981\u70b9\u4e2d\u7684\u5173\u952e\u6982\u5ff5\uff0c\u4ee5 Markdown \u5217\u8868\u5f62\u5f0f\u8f93\u51fa\u3002\n ```\n\n **\u8f93\u51fa**\uff1a\n\n ```markdown\n - **\u8981\u70b9\u4e00**\uff1a\u673a\u5668\u5b66\u4e60\u662f\u901a\u8fc7\u6570\u636e\u8bad\u7ec3\u6a21\u578b\u7684**\u65b9\u6cd5**\u3002\n - **\u8981\u70b9\u4e8c**\uff1a\u6df1\u5ea6\u5b66\u4e60\u662f\u673a\u5668\u5b66\u4e60\u7684**\u5206\u652f**\uff0c\u4ee5\u591a\u5c42\u795e\u7ecf\u7f51\u7edc\u4e3a\u6838\u5fc3\u3002\n ```\n</code></pre>"},{"location":"Tools/AI/prompt_writing/#14","title":"1.4 \u5b9e\u7528\u6848\u4f8b","text":""},{"location":"Tools/AI/prompt_writing/#141","title":"1.4.1 \u5e38\u89c1\u573a\u666f\u4e0e\u89e3\u51b3\u65b9\u6848","text":""},{"location":"Tools/AI/prompt_writing/#1411","title":"1.4.1.1 \u751f\u6210\u957f\u7bc7\u7684\u6587\u7ae0","text":"<ol> <li>\u9010\u6b65\u751f\u6210\u957f\u6587\u5185\u5bb9</li> </ol> <ul> <li>\u65b9\u6cd5\uff1a\u5148\u751f\u6210\u76ee\u5f55\uff0c\u518d\u9010\u90e8\u5206\u6269\u5c55\u5185\u5bb9\u3002</li> <li> <p>\u793a\u4f8b\uff1a Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u4e3a\u4ee5\u4e0b\u4e3b\u9898\u751f\u6210\u4e00\u4efd\u8be6\u7ec6\u7684\u6587\u7ae0\u76ee\u5f55\uff0c\u7136\u540e\u57fa\u4e8e\u76ee\u5f55\u9010\u6bb5\u6269\u5c55\u5185\u5bb9\uff1a\n\u4e3b\u9898\uff1a\u5982\u4f55\u4f18\u5316\u4e2a\u4eba\u65f6\u95f4\u7ba1\u7406\n</code></pre> <p>\u8f93\u51fa\u76ee\u5f55\u793a\u4f8b\uff1a</p> Markdown<pre><code>- \u7b2c\u4e00\u90e8\u5206\uff1a\u65f6\u95f4\u7ba1\u7406\u7684\u91cd\u8981\u6027\n- \u7b2c\u4e8c\u90e8\u5206\uff1a\u5e38\u89c1\u65f6\u95f4\u7ba1\u7406\u8bef\u533a\n- \u7b2c\u4e09\u90e8\u5206\uff1a\u9ad8\u6548\u65f6\u95f4\u7ba1\u7406\u7684\u65b9\u6cd5\n  - 1. \u8bbe\u5b9a\u76ee\u6807\u4e0e\u4f18\u5148\u7ea7\n  - 2. \u4f7f\u7528\u5de5\u5177\u4e0e\u6280\u672f\n  - 3. \u57f9\u517b\u65f6\u95f4\u7ba1\u7406\u4e60\u60ef\n- \u7b2c\u56db\u90e8\u5206\uff1a\u6848\u4f8b\u5206\u6790\u4e0e\u5e94\u7528\n</code></pre> <p>\u6269\u5c55\u5185\u5bb9 Prompt\uff1a</p> Text Only<pre><code>\u8bf7\u8be6\u7ec6\u64b0\u5199\u7b2c\u4e00\u90e8\u5206\u201c\u65f6\u95f4\u7ba1\u7406\u7684\u91cd\u8981\u6027\u201d\u7684\u5185\u5bb9\uff0c\u63a7\u5236\u5728 300 \u5b57\u5de6\u53f3\u3002\n</code></pre> </li> </ul> <ol> <li>\u5728\u751f\u6210\u65f6\u6dfb\u52a0\u5f15\u7528\u6587\u732e</li> </ol> <ul> <li> <p>\u793a\u4f8b\uff1a Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u4e3a\u4ee5\u4e0b\u4e3b\u9898\u751f\u6210\u4e00\u7bc7 500 \u5b57\u7684\u6587\u7ae0\uff0c\u5e76\u5728\u6587\u7ae0\u672b\u5c3e\u9644\u4e0a\u76f8\u5173\u53c2\u8003\u6587\u732e\uff1a\n\u4e3b\u9898\uff1a\u4eba\u5de5\u667a\u80fd\u5982\u4f55\u6539\u53d8\u6559\u80b2\u884c\u4e1a\n</code></pre> <p>\u8f93\u51fa\uff1a</p> Markdown<pre><code>### \u4eba\u5de5\u667a\u80fd\u5982\u4f55\u6539\u53d8\u6559\u80b2\u884c\u4e1a\n\uff08\u6587\u7ae0\u5185\u5bb9\uff09\n#### \u53c2\u8003\u6587\u732e\n- \u674e\u56db\uff0c\u300a\u4eba\u5de5\u667a\u80fd\u4e0e\u6559\u80b2\u300b\uff0c2023\u5e74\u51fa\u7248\u3002\n- OpenAI\uff0c\u300aAI\u5728\u6559\u80b2\u9886\u57df\u7684\u5e94\u7528\u300b\uff0c2021\u5e74\u3002\n</code></pre> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#1412","title":"1.4.1.2 \u89e3\u91ca\u4ee3\u7801\u5e76\u751f\u6210\u8f85\u52a9\u56fe\u8868","text":"<ol> <li>\u751f\u6210\u4ee3\u7801\u89e3\u91ca</li> </ol> <ul> <li> <p>\u793a\u4f8b\uff1a Prompt\uff1a  </p> Text Only<pre><code>\u4ee5\u4e0b\u662f Python \u4ee3\u7801\u7247\u6bb5\uff0c\u8bf7\u89e3\u91ca\u5176\u4f5c\u7528\uff1a\n```python\nnested_dict = lambda: defaultdict(nested_dict)\n</code></pre> Text Only<pre><code>**\u8f93\u51fa**\uff1a\n```text\n\u6b64\u4ee3\u7801\u5b9a\u4e49\u4e86\u4e00\u4e2a\u5d4c\u5957\u5b57\u5178\u7684\u9012\u5f52\u7ed3\u6784\uff0c\u53ef\u4ee5\u52a8\u6001\u521b\u5efa\u4efb\u610f\u6df1\u5ea6\u7684\u5b57\u5178\u5c42\u7ea7\u3002\n\u793a\u4f8b\u7528\u6cd5\uff1a\ndata = nested_dict()\ndata['level1']['level2'] = \"value\"\n</code></pre> </li> </ul> <ol> <li>\u751f\u6210\u8f85\u52a9\u56fe\u8868</li> </ol> <ul> <li> <p>\u793a\u4f8b\uff1a Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u6839\u636e\u4ee5\u4e0b\u63cf\u8ff0\u751f\u6210\u4e00\u6bb5 mermaid \u683c\u5f0f\u7684\u4ee3\u7801\uff0c\u7528\u4e8e\u5c55\u793a\u51fd\u6570\u8c03\u7528\u5173\u7cfb\uff1a\n\u63cf\u8ff0\uff1a\u51fd\u6570 A \u8c03\u7528\u51fd\u6570 B\uff0c\u51fd\u6570 B \u8c03\u7528\u51fd\u6570 C \u548c D\uff0c\u51fd\u6570 D \u8fd4\u56de\u7ed3\u679c\u3002\n</code></pre> <p>\u8f93\u51fa\uff1a</p> Text Only<pre><code>graph TD\nA --&gt; B\nB --&gt; C\nB --&gt; D\nD --&gt; Result\n</code></pre> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#142-prompt","title":"1.4.2 Prompt \u7684\u9650\u5236\u4e0e\u5e94\u5bf9\u7b56\u7565","text":""},{"location":"Tools/AI/prompt_writing/#1421","title":"1.4.2.1 \u8bbe\u8ba1\u62d2\u7b54\u7b56\u7565\u63d0\u5347\u53ef\u9760\u6027","text":"<ol> <li>\u907f\u514d\u5e7b\u89c9\u73b0\u8c61</li> </ol> <ul> <li> <p>\u63d0\u793a\u6a21\u578b\u4e0d\u8981\u56de\u7b54\u5176\u65e0\u6cd5\u786e\u5b9a\u7684\u5185\u5bb9\u3002 \u793a\u4f8b\uff1a  </p> Text Only<pre><code>\u5982\u679c\u4f60\u4e0d\u77e5\u9053\u4ee5\u4e0b\u95ee\u9898\u7684\u7b54\u6848\uff0c\u8bf7\u56de\u590d\u201c\u4fe1\u606f\u4e0d\u8db3\u201d\u3002\n\u95ee\u9898\uff1a\u8c01\u662f\u7b2c\u4e00\u4e2a\u767b\u4e0a\u6708\u7403\u7684\u673a\u5668\u4eba\uff1f\n</code></pre> <p>\u8f93\u51fa\uff1a</p> Text Only<pre><code>\u4fe1\u606f\u4e0d\u8db3\u3002\n</code></pre> </li> </ul> <ol> <li>\u591a\u6b21\u751f\u6210\u4ee5\u786e\u8ba4\u7b54\u6848\u4e00\u81f4\u6027</li> </ol> <ul> <li> <p>Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u591a\u6b21\u751f\u6210\u4ee5\u4e0b\u95ee\u9898\u7684\u7b54\u6848\uff0c\u5e76\u786e\u4fdd\u7b54\u6848\u4e00\u81f4\u3002\u5982\u679c\u7b54\u6848\u4e0d\u4e00\u81f4\uff0c\u8bf7\u56de\u590d\u201c\u65e0\u6cd5\u786e\u5b9a\u7b54\u6848\u201d\u3002\n\u95ee\u9898\uff1a2023 \u5e74\u4e16\u754c\u4eba\u53e3\u603b\u6570\u662f\u591a\u5c11\uff1f\n</code></pre> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#1422-ai","title":"1.4.2.2 \u591a\u4e2a AI \u534f\u4f5c","text":"<ol> <li>\u6846\u67b6\u4e0e\u5185\u5bb9\u534f\u4f5c</li> </ol> <ul> <li> <p>\u901a\u8fc7\u4e0d\u540c\u6a21\u578b\u534f\u4f5c\u4f18\u5316\u5185\u5bb9\u751f\u6210\u3002 \u793a\u4f8b\u6d41\u7a0b\uff1a</p> <ul> <li>Prompt 1\uff1a\u8ba9 ChatGPT \u63d0\u4f9b\u6587\u7ae0\u6846\u67b6\u3002  </li> </ul> Text Only<pre><code>\u8bf7\u4e3a\u4ee5\u4e0b\u4e3b\u9898\u751f\u6210\u8be6\u7ec6\u7684\u6587\u7ae0\u6846\u67b6\uff1a\n\u4e3b\u9898\uff1a\u5982\u4f55\u63d0\u5347\u56e2\u961f\u5408\u4f5c\u6548\u7387\n</code></pre> <ul> <li>Prompt 2\uff1a\u5c06\u6846\u67b6\u5185\u5bb9\u4ea4\u7ed9\u53e6\u4e00\u4e2a\u6a21\u578b\u4f18\u5316\u8868\u8fbe\u3002  </li> </ul> Text Only<pre><code>\u8bf7\u6839\u636e\u4ee5\u4e0b\u6846\u67b6\u64b0\u5199\u8be6\u7ec6\u5185\u5bb9\uff0c\u5e76\u8c03\u6574\u4e3a\u66f4\u4e13\u4e1a\u7684\u8bed\u8a00\u3002\n</code></pre> <ul> <li>Prompt 3\uff1a\u4f7f\u7528\u53e6\u4e00\u4e2a\u5de5\u5177\uff08\u5982 Grammarly \u6216\u5176\u4ed6 AI\uff09\u6821\u5bf9\u548c\u4f18\u5316\u8bed\u8a00\u98ce\u683c\u3002</li> </ul> </li> </ul> <ol> <li>\u4ee3\u7801\u4f18\u5316\u534f\u4f5c</li> </ol> <ul> <li>Prompt\uff1a  </li> </ul> Text Only<pre><code>    \u8bf7\u4f18\u5316\u4ee5\u4e0b\u4ee3\u7801\uff0c\u4f7f\u5176\u8fd0\u884c\u6548\u7387\u66f4\u9ad8\uff0c\u5e76\u63d0\u4f9b\u6ce8\u91ca\u8bf4\u660e\uff1a\n    ```python\n        def factorial(n):\n            if n == 0:\n                return 1\n            else:\n                return n * factorial(n-1)\n    ```\n</code></pre>"},{"location":"Tools/AI/prompt_writing/#15","title":"1.5 \u6211\u66fe\u7ecf\u7528\u6cd5","text":"<ul> <li>\u8f93\u51fa\u6587\u6863\uff1a\u901a\u8fc7 Markdown \u6216 LaTeX \u751f\u6210\u683c\u5f0f\u5316\u6587\u6863\u3002</li> <li>\u751f\u6210 README\uff1a\u8ba9 AI \u9605\u8bfb\u4ee3\u7801\u5e76\u64b0\u5199\u8bf4\u660e\u3002</li> <li>\u5f15\u7528\u6587\u732e\u5199\u8bba\u6587\uff1a\u5229\u7528 AI \u4e0a\u7f51\u67e5\u8be2\u8d44\u6599\uff0c\u63d0\u9ad8\u5b66\u672f\u5185\u5bb9\u8d28\u91cf\u3002</li> </ul>"},{"location":"Tools/AI/prompt_writing/#2-prompt","title":"2 \u5e38\u7528\u7684 Prompt","text":"<p>\u8bf7\u53c2\u8003 \u5e38\u7528 prompt \u8bb0\u5f55 - wnc \u7684\u5496\u5561\u9986</p>"},{"location":"Tools/Blog/Mkdocs_Material/","title":"mkdocs material \u8d85\u5168\u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#mkdocs-material","title":"mkdocs material \u8d85\u5168\u914d\u7f6e","text":"<p> \u7ea6 5956 \u4e2a\u5b57  9393 \u884c\u4ee3\u7801  7 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 147 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>\u4ecd\u7136\u5728\u4fee\u6539 \u5982\u679c\u9700\u8981\u4efb\u4f55\u7684\u6587\u4ef6\uff0c\u53ef\u4ee5\u76f4\u63a5\u8bbf\u95ee\u672c\u535a\u5ba2\u7684 GitHub \u9875\u9762</p>"},{"location":"Tools/Blog/Mkdocs_Material/#1","title":"1 \u5165\u95e8\u57fa\u7840","text":""},{"location":"Tools/Blog/Mkdocs_Material/#11-mkdocs","title":"1.1 \u4ec0\u4e48\u662f MkDocs\uff1f","text":"<p>MkDocs \u662f\u4e00\u4e2a\u5feb\u901f\u3001\u7b80\u5355\u3001\u534e\u4e3d\u7684\u9759\u6001\u7ad9\u70b9\u751f\u6210\u5668\uff0c\u4e13\u95e8\u7528\u4e8e\u6784\u5efa\u9879\u76ee\u6587\u6863\u3002\u6587\u6863\u6e90\u6587\u4ef6\u4f7f\u7528 Markdown \u7f16\u5199\uff0c\u914d\u7f6e\u6587\u4ef6\u4f7f\u7528 YAML \u683c\u5f0f\u3002</p>"},{"location":"Tools/Blog/Mkdocs_Material/#111-mkdocs","title":"1.1.1 MkDocs \u7684\u4f18\u52bf","text":"<ol> <li> <p>\u7b80\u5355\u6613\u7528    - \u4f7f\u7528 Markdown \u7f16\u5199\u6587\u6863    - \u914d\u7f6e\u6587\u4ef6\u7b80\u5355\u76f4\u89c2    - \u4e00\u952e\u5f0f\u6784\u5efa\u548c\u90e8\u7f72</p> </li> <li> <p>\u529f\u80fd\u5f3a\u5927    - \u5185\u7f6e\u5f00\u53d1\u670d\u52a1\u5668\uff0c\u652f\u6301\u5b9e\u65f6\u9884\u89c8    - \u591a\u79cd\u4e3b\u9898\u53ef\u9009    - \u652f\u6301\u81ea\u5b9a\u4e49\u4e3b\u9898    - \u81ea\u52a8\u751f\u6210\u5bfc\u822a    - \u5168\u6587\u641c\u7d22\u529f\u80fd</p> </li> <li> <p>\u90e8\u7f72\u65b9\u4fbf    - \u751f\u6210\u7eaf\u9759\u6001\u9875\u9762    - \u4e00\u884c\u547d\u4ee4\u90e8\u7f72\u5230 GitHub Pages    - \u652f\u6301\u81ea\u5b9a\u4e49\u57df\u540d    - \u517c\u5bb9\u6240\u6709\u9759\u6001\u7f51\u7ad9\u6258\u7ba1\u5e73\u53f0</p> </li> </ol>"},{"location":"Tools/Blog/Mkdocs_Material/#112-mkdocs-vs","title":"1.1.2 MkDocs vs \u5176\u4ed6\u6587\u6863\u5de5\u5177","text":"\u5de5\u5177 \u4f18\u52bf \u52a3\u52bf MkDocs - \u7b80\u5355\u6613\u7528- \u4e13\u6ce8\u6587\u6863- \u90e8\u7f72\u65b9\u4fbf- \u4e3b\u9898\u4e30\u5bcc - \u529f\u80fd\u76f8\u5bf9\u7b80\u5355- \u63d2\u4ef6\u751f\u6001\u8f83\u5c0f GitBook - \u754c\u9762\u4f18\u96c5- \u751f\u6001\u5b8c\u6574- \u591a\u4eba\u534f\u4f5c\u597d - \u6784\u5efa\u901f\u5ea6\u6162- \u5b9a\u5236\u6027\u5dee- \u514d\u8d39\u7248\u9650\u5236\u591a Docusaurus - React \u6280\u672f\u6808- \u529f\u80fd\u5f3a\u5927- \u6269\u5c55\u6027\u597d - \u5b66\u4e60\u66f2\u7ebf\u9661- \u914d\u7f6e\u590d\u6742- \u6784\u5efa\u8f83\u6162 VuePress - Vue \u6280\u672f\u6808- \u5b9a\u5236\u6027\u5f3a- \u63d2\u4ef6\u4e30\u5bcc - \u4e3b\u9898\u8f83\u5c11- \u914d\u7f6e\u7e41\u7410- \u5b66\u4e60\u6210\u672c\u9ad8"},{"location":"Tools/Blog/Mkdocs_Material/#113-mkdocs","title":"1.1.3 MkDocs \u5de5\u4f5c\u539f\u7406","text":"<p>MkDocs \u7684\u5de5\u4f5c\u6d41\u7a0b\u5982\u4e0b\uff1a</p> <ol> <li> <p>\u6587\u6863\u7f16\u5199    - \u4f7f\u7528 Markdown \u683c\u5f0f\u7f16\u5199\u6587\u6863    - \u6587\u6863\u5b58\u653e\u5728 <code>docs</code> \u76ee\u5f55\u4e0b    - \u652f\u6301\u591a\u7ea7\u76ee\u5f55\u7ed3\u6784</p> </li> <li> <p>\u914d\u7f6e\u89e3\u6790    - \u8bfb\u53d6 <code>mkdocs.yml</code> \u914d\u7f6e\u6587\u4ef6    - \u89e3\u6790\u4e3b\u9898\u8bbe\u7f6e\u3001\u63d2\u4ef6\u914d\u7f6e\u7b49    - \u751f\u6210\u5bfc\u822a\u7ed3\u6784</p> </li> <li> <p>\u6784\u5efa\u8fc7\u7a0b</p> </li> </ol> Text Only<pre><code>Markdown \u6587\u4ef6 -&gt; \u89e3\u6790\u5668 -&gt; HTML \u6587\u4ef6\n              -&gt; \u4e3b\u9898\u6e32\u67d3\n              -&gt; \u63d2\u4ef6\u5904\u7406\n              -&gt; \u9759\u6001\u8d44\u6e90\u5904\u7406\n</code></pre> <ol> <li>\u8f93\u51fa\u90e8\u7f72    - \u751f\u6210\u7eaf\u9759\u6001 HTML \u6587\u4ef6    - \u4fdd\u7559\u539f\u59cb\u76ee\u5f55\u7ed3\u6784    - \u81ea\u52a8\u5904\u7406\u5185\u90e8\u94fe\u63a5    - \u590d\u5236\u9759\u6001\u8d44\u6e90</li> </ol>"},{"location":"Tools/Blog/Mkdocs_Material/#12-material","title":"1.2 \u4e3a\u4ec0\u4e48\u9009\u62e9 Material \u4e3b\u9898","text":"<p>Material for MkDocs \u662f\u4e00\u4e2a\u57fa\u4e8e Google Material Design \u8bbe\u8ba1\u8bed\u8a00\u7684\u4e3b\u9898\uff0c\u5b83\u4e0d\u4ec5\u7f8e\u89c2\uff0c\u800c\u4e14\u529f\u80fd\u5f3a\u5927\u3002</p>"},{"location":"Tools/Blog/Mkdocs_Material/#121-material","title":"1.2.1 Material \u4e3b\u9898\u7279\u6027","text":"<ol> <li> <p>\u73b0\u4ee3\u5316\u8bbe\u8ba1    - \u9075\u5faa Material Design \u89c4\u8303    - \u54cd\u5e94\u5f0f\u5e03\u5c40    - \u652f\u6301\u6df1\u8272\u6a21\u5f0f    - \u81ea\u52a8\u9002\u914d\u79fb\u52a8\u8bbe\u5907</p> </li> <li> <p>\u5f3a\u5927\u529f\u80fd    - \u667a\u80fd\u641c\u7d22    - \u4ee3\u7801\u9ad8\u4eae    - \u6807\u7b7e\u9875\u652f\u6301    - \u81ea\u52a8\u76ee\u5f55\u751f\u6210    - \u591a\u8bed\u8a00\u652f\u6301    - \u7248\u672c\u63a7\u5236\u96c6\u6210</p> </li> <li> <p>\u51fa\u8272\u7684\u7528\u6237\u4f53\u9a8c    - \u5feb\u901f\u52a0\u8f7d    - \u5e73\u6ed1\u52a8\u753b    - \u5b9e\u65f6\u641c\u7d22    - \u4ee3\u7801\u590d\u5236\u6309\u94ae    - \u8fd4\u56de\u9876\u90e8\u6309\u94ae</p> </li> </ol>"},{"location":"Tools/Blog/Mkdocs_Material/#122","title":"1.2.2 \u4e0e\u5176\u4ed6\u4e3b\u9898\u5bf9\u6bd4","text":"\u7279\u6027 Material ReadTheDocs mkdocs \u5176\u4ed6\u4e3b\u9898 \u8bbe\u8ba1\u98ce\u683c \u73b0\u4ee3\u7b80\u7ea6 \u4f20\u7edf\u6587\u6863 \u7b80\u5355\u57fa\u7840 \u98ce\u683c\u591a\u6837 \u54cd\u5e94\u5f0f \u2705 \u2705 \u274c \u90e8\u5206\u652f\u6301 \u6df1\u8272\u6a21\u5f0f \u2705 \u274c \u274c \u90e8\u5206\u652f\u6301 \u641c\u7d22\u529f\u80fd \u2705 \u2705 \u274c \u90e8\u5206\u652f\u6301 \u5b9a\u5236\u6027 \u5f3a \u4e2d \u5f31 \u4e0d\u4e00\u81f4 \u63d2\u4ef6\u652f\u6301 \u4e30\u5bcc \u4e00\u822c \u57fa\u7840 \u4e0d\u4e00\u81f4"},{"location":"Tools/Blog/Mkdocs_Material/#123-material","title":"1.2.3 Material \u4e3b\u9898\u7684\u6280\u672f\u67b6\u6784","text":"Text Only<pre><code>Material Theme\n\u251c\u2500\u2500 \u6838\u5fc3\u7ec4\u4ef6\n\u2502   \u251c\u2500\u2500 \u5bfc\u822a\u680f\n\u2502   \u251c\u2500\u2500 \u4fa7\u8fb9\u680f\n\u2502   \u251c\u2500\u2500 \u641c\u7d22\u7ec4\u4ef6\n\u2502   \u2514\u2500\u2500 \u5185\u5bb9\u6e32\u67d3\u5668\n\u251c\u2500\u2500 \u6269\u5c55\u529f\u80fd\n\u2502   \u251c\u2500\u2500 \u4ee3\u7801\u9ad8\u4eae\n\u2502   \u251c\u2500\u2500 \u6807\u7b7e\u7cfb\u7edf\n\u2502   \u251c\u2500\u2500 \u76ee\u5f55\u751f\u6210\n\u2502   \u2514\u2500\u2500 \u4e3b\u9898\u5207\u6362\n\u2514\u2500\u2500 \u63d2\u4ef6\u7cfb\u7edf\n    \u251c\u2500\u2500 \u5185\u7f6e\u63d2\u4ef6\n    \u2514\u2500\u2500 \u7b2c\u4e09\u65b9\u63d2\u4ef6\u96c6\u6210\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#13","title":"1.3 \u73af\u5883\u8981\u6c42","text":""},{"location":"Tools/Blog/Mkdocs_Material/#131-python","title":"1.3.1 Python \u73af\u5883","text":""},{"location":"Tools/Blog/Mkdocs_Material/#1311-python","title":"1.3.1.1 Python \u7248\u672c\u9009\u62e9","text":"<p>MkDocs \u9700\u8981 Python 3.6 \u6216\u66f4\u9ad8\u7248\u672c\uff0c\u63a8\u8350\u4f7f\u7528 Python 3.8+\uff1a</p> Bash<pre><code># \u68c0\u67e5 Python \u7248\u672c\npython --version\n\n# \u63a8\u8350\u7248\u672c\nPython 3.8.x\nPython 3.9.x\nPython 3.10.x\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1312-pip","title":"1.3.1.2 pip \u914d\u7f6e\u8bf4\u660e","text":"<p>pip \u662f Python \u7684\u5305\u7ba1\u7406\u5de5\u5177\uff0c\u9700\u8981\u786e\u4fdd\u5176\u6b63\u786e\u5b89\u88c5\uff1a</p> Bash<pre><code># \u68c0\u67e5 pip \u7248\u672c\npip --version\n\n# \u5347\u7ea7 pip\npython -m pip install --upgrade pip\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1313","title":"1.3.1.3 \u865a\u62df\u73af\u5883\u7ba1\u7406","text":"<p>\u63a8\u8350\u4f7f\u7528\u865a\u62df\u73af\u5883\u6765\u7ba1\u7406\u9879\u76ee\u4f9d\u8d56\uff1a</p> Bash<pre><code># \u521b\u5efa\u865a\u62df\u73af\u5883\npython -m venv venv\n\n# \u6fc0\u6d3b\u865a\u62df\u73af\u5883\n# Windows\nvenv\\Scripts\\activate\n# Linux/Mac\nsource venv/bin/activate\n\n# \u9000\u51fa\u865a\u62df\u73af\u5883\ndeactivate\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#132-pip","title":"1.3.2 pip \u5305\u7ba1\u7406","text":""},{"location":"Tools/Blog/Mkdocs_Material/#1321-pip","title":"1.3.2.1 pip \u6e90\u914d\u7f6e","text":"<p>\u4e3a\u52a0\u5feb\u4e0b\u8f7d\u901f\u5ea6\uff0c\u5efa\u8bae\u4f7f\u7528\u56fd\u5185\u955c\u50cf\u6e90\uff1a</p> Bash<pre><code># \u4e34\u65f6\u4f7f\u7528\npip install -i https://pypi.tuna.tsinghua.edu.cn/simple mkdocs\n\n# \u6c38\u4e45\u914d\u7f6e\npip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1322","title":"1.3.2.2 \u4f9d\u8d56\u7ba1\u7406","text":"<p>\u5b89\u88c5\u5fc5\u8981\u7684\u5305\uff1a</p> Bash<pre><code>pip install mkdocs-material\npip install mkdocs-glightbox\npip install mkdocs-git-revision-date-localized-plugin\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1323-requirements-txt","title":"1.3.2.3 requirements. txt \u4f7f\u7528","text":"<p>\u7ef4\u62a4\u9879\u76ee\u4f9d\u8d56\uff1a</p> Bash<pre><code># \u751f\u6210\u4f9d\u8d56\u6587\u4ef6\npip freeze &gt; requirements.txt\n\n# \u5b89\u88c5\u4f9d\u8d56\npip install -r requirements.txt\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#133-git","title":"1.3.3 Git \u73af\u5883","text":""},{"location":"Tools/Blog/Mkdocs_Material/#1331-git","title":"1.3.3.1 Git \u57fa\u7840\u914d\u7f6e","text":"Bash<pre><code># \u914d\u7f6e\u7528\u6237\u4fe1\u606f\ngit config --global user.name \"Your Name\"\ngit config --global user.email \"your.email@example.com\"\n\n# \u914d\u7f6e\u9ed8\u8ba4\u5206\u652f\ngit config --global init.defaultBranch main\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#134-ssh","title":"1.3.4 SSH \u5bc6\u94a5\u914d\u7f6e","text":"Bash<pre><code># \u751f\u6210 SSH \u5bc6\u94a5\nssh-keygen -t rsa -b 4096 -C \"your.email@example.com\"\n\n# \u67e5\u770b\u516c\u94a5\ncat ~/.ssh/id_rsa.pub\n</code></pre> <p>\u5c06\u516c\u94a5\u6dfb\u52a0\u5230 GitHub \u8d26\u6237\u7684 SSH keys \u4e2d\u3002</p>"},{"location":"Tools/Blog/Mkdocs_Material/#135-gitignore","title":"1.3.5 .gitignore \u914d\u7f6e","text":"<p>\u521b\u5efa <code>.gitignore</code> \u6587\u4ef6\uff0c\u6dfb\u52a0\u4ee5\u4e0b\u5185\u5bb9\uff1a</p> Text Only<pre><code># Python\n__pycache__/\n*.py[cod]\n*$py.class\nvenv/\n\n# MkDocs\nsite/\n\n# IDE\n.idea/\n.vscode/\n*.swp\n*.swo\n\n# OS\n.DS_Store\nThumbs.db\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2","title":"2 \u73af\u5883\u642d\u5efa","text":""},{"location":"Tools/Blog/Mkdocs_Material/#21-windows","title":"2.1 Windows \u7cfb\u7edf\u5b89\u88c5","text":""},{"location":"Tools/Blog/Mkdocs_Material/#211-python","title":"2.1.1 Python \u5b89\u88c5","text":""},{"location":"Tools/Blog/Mkdocs_Material/#2111","title":"2.1.1.1 \u4e0b\u8f7d\u5b89\u88c5\u5305","text":"<ol> <li>\u8bbf\u95ee Python \u5b98\u7f51 \u4e0b\u8f7d\u6700\u65b0\u7248\u672c</li> <li>\u9009\u62e9\u9002\u5408\u4f60\u7684 Windows \u7248\u672c\uff0832 \u4f4d/64 \u4f4d\uff09\u7684\u5b89\u88c5\u5305</li> <li>\u4e0b\u8f7d\u5b8c\u6210\u540e\u53cc\u51fb\u5b89\u88c5\u5305\u5f00\u59cb\u5b89\u88c5</li> </ol>"},{"location":"Tools/Blog/Mkdocs_Material/#2112","title":"2.1.1.2 \u73af\u5883\u53d8\u91cf\u914d\u7f6e","text":"<ol> <li>\u5b89\u88c5\u65f6\u52fe\u9009 \"Add Python to PATH\"</li> <li>\u5982\u679c\u5fd8\u8bb0\u52fe\u9009\uff0c\u53ef\u4ee5\u624b\u52a8\u6dfb\u52a0\uff1a</li> </ol> Text Only<pre><code># \u6dfb\u52a0\u5230\u7cfb\u7edf\u73af\u5883\u53d8\u91cf Path\nC:\\Users\\YourUser\\AppData\\Local\\Programs\\Python\\Python3x\\\nC:\\Users\\YourUser\\AppData\\Local\\Programs\\Python\\Python3x\\Scripts\\\n</code></pre> <ol> <li>\u68c0\u67e5\u73af\u5883\u53d8\u91cf\uff1a</li> </ol> Bash<pre><code>echo %PATH%\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2113","title":"2.1.1.3 \u9a8c\u8bc1\u5b89\u88c5","text":"<p>\u5728\u547d\u4ee4\u63d0\u793a\u7b26\u4e2d\u6267\u884c\uff1a</p> Bash<pre><code># \u68c0\u67e5 Python \u7248\u672c\npython --version\n\n# \u68c0\u67e5 pip \u7248\u672c\npip --version\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#212-mkdocs","title":"2.1.2 MkDocs \u5b89\u88c5","text":""},{"location":"Tools/Blog/Mkdocs_Material/#2121-pip","title":"2.1.2.1 pip \u5b89\u88c5\u65b9\u6cd5","text":"<p>\u4f7f\u7528 pip \u5b89\u88c5 MkDocs\uff1a</p> Bash<pre><code># \u5b89\u88c5 MkDocs\npip install mkdocs\n\n# \u9a8c\u8bc1\u5b89\u88c5\nmkdocs --version\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2122","title":"2.1.2.2 \u5e38\u89c1\u95ee\u9898\u89e3\u51b3","text":"<ol> <li> <p>pip \u4e0d\u662f\u5185\u90e8\u547d\u4ee4    - \u89e3\u51b3\u65b9\u6cd5\uff1a\u91cd\u65b0\u6dfb\u52a0 Python Scripts \u76ee\u5f55\u5230 PATH</p> </li> <li> <p>\u6743\u9650\u95ee\u9898    - \u89e3\u51b3\u65b9\u6cd5\uff1a\u4f7f\u7528\u7ba1\u7406\u5458\u6743\u9650\u8fd0\u884c\u547d\u4ee4\u63d0\u793a\u7b26</p> </li> </ol> Bash<pre><code># \u7ba1\u7406\u5458\u6743\u9650\u5b89\u88c5\npip install --user mkdocs\n</code></pre> <ol> <li>SSL \u8bc1\u4e66\u9519\u8bef    - \u89e3\u51b3\u65b9\u6cd5\uff1a\u6dfb\u52a0\u4fe1\u4efb\u9009\u9879\u6216\u4f7f\u7528\u56fd\u5185\u955c\u50cf</li> </ol> Bash<pre><code>pip install --trusted-host pypi.org --trusted-host files.pythonhosted.org mkdocs\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#213","title":"2.1.3 \u7248\u672c\u9009\u62e9","text":"<p>MkDocs \u7248\u672c\u9009\u62e9\u5efa\u8bae\uff1a</p> Bash<pre><code># \u67e5\u770b\u53ef\u7528\u7248\u672c\npip install mkdocs==\n\n# \u5b89\u88c5\u7279\u5b9a\u7248\u672c\npip install mkdocs==1.5.3  # \u63a8\u8350\u7248\u672c\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#214-material","title":"2.1.4 Material \u4e3b\u9898\u5b89\u88c5","text":""},{"location":"Tools/Blog/Mkdocs_Material/#2141","title":"2.1.4.1 \u5b89\u88c5\u547d\u4ee4","text":"Bash<pre><code># \u5b89\u88c5 Material \u4e3b\u9898\npip install mkdocs-material\n\n# \u9a8c\u8bc1\u5b89\u88c5\npython -c \"import mkdocs_material; print(mkdocs_material.__version__)\"\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2142","title":"2.1.4.2 \u4f9d\u8d56\u68c0\u67e5","text":"<p>\u5b89\u88c5\u5fc5\u8981\u7684\u4f9d\u8d56\uff1a</p> Bash<pre><code># \u5b89\u88c5\u6269\u5c55\u652f\u6301\npip install pymdown-extensions\npip install mkdocs-glightbox\npip install mkdocs-git-revision-date-localized-plugin\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2143","title":"2.1.4.3 \u7248\u672c\u517c\u5bb9\u6027","text":"MkDocs \u7248\u672c Material \u7248\u672c Python \u7248\u672c 1.5. x 9.4. x \u22653.8 1.4. x 9.3. x \u22653.7 1.3. x 9.2. x \u22653.7"},{"location":"Tools/Blog/Mkdocs_Material/#22-linuxmac","title":"2.2 Linux/Mac \u7cfb\u7edf\u5b89\u88c5","text":""},{"location":"Tools/Blog/Mkdocs_Material/#221-python","title":"2.2.1 \u5305\u7ba1\u7406\u5668\u5b89\u88c5 Python","text":""},{"location":"Tools/Blog/Mkdocs_Material/#2211-aptyum","title":"2.2.1.1 apt/yum \u5b89\u88c5\u65b9\u6cd5","text":"<p>Ubuntu/Debian:</p> Bash<pre><code># \u66f4\u65b0\u5305\u7d22\u5f15\nsudo apt update\n\n# \u5b89\u88c5 Python\nsudo apt install python3 python3-pip\n\n# \u5b89\u88c5\u5f00\u53d1\u5de5\u5177\nsudo apt install python3-dev\n</code></pre> <p>CentOS/RHEL:</p> Bash<pre><code># \u5b89\u88c5 EPEL \u4ed3\u5e93\nsudo yum install epel-release\n\n# \u5b89\u88c5 Python\nsudo yum install python3 python3-pip\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2212-brew","title":"2.2.1.2 brew \u5b89\u88c5\u65b9\u6cd5","text":"<p>macOS:</p> Bash<pre><code># \u5b89\u88c5 Homebrew\uff08\u5982\u679c\u672a\u5b89\u88c5\uff09\n/bin/bash -c \"$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)\"\n\n# \u5b89\u88c5 Python\nbrew install python\n\n# \u66f4\u65b0 pip\npip3 install --upgrade pip\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2213","title":"2.2.1.3 \u73af\u5883\u53d8\u91cf\u914d\u7f6e","text":"<p>bash/zsh:</p> Bash<pre><code># \u6dfb\u52a0\u5230 ~/.bashrc \u6216 ~/.zshrc\nexport PATH=\"$HOME/.local/bin:$PATH\"\nexport PYTHONPATH=\"$HOME/.local/lib/python3.x/site-packages:$PYTHONPATH\"\n\n# \u66f4\u65b0\u73af\u5883\u53d8\u91cf\nsource ~/.bashrc  # \u6216 source ~/.zshrc\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#222-pip","title":"2.2.2 pip \u5b89\u88c5\u4f9d\u8d56","text":""},{"location":"Tools/Blog/Mkdocs_Material/#2221","title":"2.2.2.1 \u7cfb\u7edf\u7ea7\u5b89\u88c5","text":"Bash<pre><code># \u5168\u5c40\u5b89\u88c5\uff08\u9700\u8981 root \u6743\u9650\uff09\nsudo pip3 install mkdocs mkdocs-material\n\n# \u9a8c\u8bc1\u5b89\u88c5\nmkdocs --version\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2222","title":"2.2.2.2 \u7528\u6237\u7ea7\u5b89\u88c5","text":"Bash<pre><code># \u7528\u6237\u76ee\u5f55\u5b89\u88c5\npip3 install --user mkdocs mkdocs-material\n\n# \u68c0\u67e5\u5b89\u88c5\u8def\u5f84\npython3 -m site --user-site\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2223","title":"2.2.2.3 \u865a\u62df\u73af\u5883\u5b89\u88c5","text":"Bash<pre><code># \u521b\u5efa\u865a\u62df\u73af\u5883\npython3 -m venv mkdocs-env\n\n# \u6fc0\u6d3b\u865a\u62df\u73af\u5883\nsource mkdocs-env/bin/activate\n\n# \u5b89\u88c5\u4f9d\u8d56\npip install mkdocs mkdocs-material\n\n# \u9000\u51fa\u865a\u62df\u73af\u5883\ndeactivate\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#23","title":"2.3 \u9879\u76ee\u521d\u59cb\u5316","text":""},{"location":"Tools/Blog/Mkdocs_Material/#231","title":"2.3.1 \u521b\u5efa\u9879\u76ee","text":""},{"location":"Tools/Blog/Mkdocs_Material/#2311-mkdocs-new","title":"2.3.1.1 mkdocs new \u547d\u4ee4\u8be6\u89e3","text":"Bash<pre><code># \u57fa\u672c\u8bed\u6cd5\nmkdocs new [\u9879\u76ee\u540d]\n\n# \u521b\u5efa\u65b0\u9879\u76ee\nmkdocs new my-docs\n\n# \u4f7f\u7528\u73b0\u6709\u76ee\u5f55\ncd existing-project\nmkdocs new .\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2312","title":"2.3.1.2 \u9879\u76ee\u547d\u540d\u89c4\u8303","text":"<ul> <li>\u4f7f\u7528\u5c0f\u5199\u5b57\u6bcd</li> <li>\u5355\u8bcd\u95f4\u7528\u8fde\u5b57\u7b26 (-) \u5206\u9694</li> <li>\u907f\u514d\u4f7f\u7528\u7279\u6b8a\u5b57\u7b26</li> <li>\u540d\u79f0\u5177\u6709\u63cf\u8ff0\u6027</li> </ul> <p>\u793a\u4f8b\uff1a</p> Bash<pre><code>mkdocs new technical-docs    # \u597d\u7684\u547d\u540d\nmkdocs new tech_docs        # \u907f\u514d\u4f7f\u7528\u4e0b\u5212\u7ebf\nmkdocs new TechDocs         # \u907f\u514d\u4f7f\u7528\u5927\u5199\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2313","title":"2.3.1.3 \u521d\u59cb\u5316\u914d\u7f6e","text":"<p>\u521b\u5efa\u9879\u76ee\u540e\u7684\u57fa\u672c\u8bbe\u7f6e\uff1a</p> Bash<pre><code>cd my-docs\n# \u542f\u52a8\u5f00\u53d1\u670d\u52a1\u5668\nmkdocs serve\n# \u5728\u6d4f\u89c8\u5668\u4e2d\u8bbf\u95ee http://127.0.0.1:8000\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#232","title":"2.3.2 \u76ee\u5f55\u7ed3\u6784\u8bf4\u660e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#2321","title":"2.3.2.1 \u57fa\u7840\u76ee\u5f55\u7ed3\u6784","text":"Text Only<pre><code>my-docs/\n\u251c\u2500\u2500 docs/               # \u6587\u6863\u76ee\u5f55\n\u2502   \u251c\u2500\u2500 index.md       # \u9996\u9875\n\u2502   \u251c\u2500\u2500 about.md       # \u5176\u4ed6\u9875\u9762\n\u2502   \u2514\u2500\u2500 img/           # \u56fe\u7247\u76ee\u5f55\n\u251c\u2500\u2500 mkdocs.yml         # \u914d\u7f6e\u6587\u4ef6\n\u2514\u2500\u2500 venv/              # \u865a\u62df\u73af\u5883\uff08\u53ef\u9009\uff09\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2322-docs","title":"2.3.2.2 docs \u76ee\u5f55\u7ec4\u7ec7","text":"Text Only<pre><code>docs/\n\u251c\u2500\u2500 index.md           # \u9996\u9875\n\u251c\u2500\u2500 guide/             # \u6307\u5357\u76ee\u5f55\n\u2502   \u251c\u2500\u2500 index.md      # \u6307\u5357\u9996\u9875\n\u2502   \u251c\u2500\u2500 install.md    # \u5b89\u88c5\u8bf4\u660e\n\u2502   \u2514\u2500\u2500 usage.md      # \u4f7f\u7528\u8bf4\u660e\n\u251c\u2500\u2500 api/               # API\u6587\u6863\n\u2502   \u2514\u2500\u2500 index.md      # API\u9996\u9875\n\u2514\u2500\u2500 examples/          # \u793a\u4f8b\u76ee\u5f55\n    \u2514\u2500\u2500 basic.md      # \u57fa\u7840\u793a\u4f8b\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2323","title":"2.3.2.3 \u8d44\u6e90\u6587\u4ef6\u7ba1\u7406","text":"Text Only<pre><code>docs/\n\u251c\u2500\u2500 assets/           # \u8d44\u6e90\u76ee\u5f55\n\u2502   \u251c\u2500\u2500 images/      # \u56fe\u7247\u8d44\u6e90\n\u2502   \u251c\u2500\u2500 css/         # \u6837\u5f0f\u6587\u4ef6\n\u2502   \u251c\u2500\u2500 js/          # \u811a\u672c\u6587\u4ef6\n\u2502   \u2514\u2500\u2500 fonts/       # \u5b57\u4f53\u6587\u4ef6\n\u2514\u2500\u2500 files/           # \u4e0b\u8f7d\u6587\u4ef6\n    \u2514\u2500\u2500 sample.pdf   # \u793a\u4f8b\u6587\u4ef6\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#233","title":"2.3.3 \u57fa\u7840\u914d\u7f6e\u6587\u4ef6","text":""},{"location":"Tools/Blog/Mkdocs_Material/#2331-mkdocs-yml","title":"2.3.3.1 mkdocs. yml \u7ed3\u6784","text":"<p>\u57fa\u672c\u914d\u7f6e\u6587\u4ef6\u7ed3\u6784\uff1a</p> YAML<pre><code># \u7ad9\u70b9\u4fe1\u606f\nsite_name: \u6211\u7684\u6587\u6863\nsite_url: https://example.com/\nsite_author: \u4f5c\u8005\u540d\nsite_description: \u7ad9\u70b9\u63cf\u8ff0\n\n# \u4e3b\u9898\u8bbe\u7f6e\ntheme:\n  name: material\n  language: zh\n  features:\n    - navigation.tabs\n    - navigation.top\n\n# \u5bfc\u822a\u8bbe\u7f6e\nnav:\n  - \u9996\u9875: index.md\n  - \u6307\u5357: \n    - guide/index.md\n    - \u5b89\u88c5: guide/install.md\n    - \u4f7f\u7528: guide/usage.md\n\n# Markdown \u6269\u5c55\nmarkdown_extensions:\n  - attr_list\n  - md_in_html\n  - toc:\n      permalink: true\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2332","title":"2.3.3.2 \u6700\u5c0f\u914d\u7f6e\u793a\u4f8b","text":"<p>\u6700\u7b80\u5355\u7684\u914d\u7f6e\u6587\u4ef6\uff1a</p> YAML<pre><code>site_name: \u6211\u7684\u6587\u6863\ntheme:\n  name: material\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2333","title":"2.3.3.3 \u914d\u7f6e\u6587\u4ef6\u8bed\u6cd5","text":"<p>YAML \u8bed\u6cd5\u8981\u70b9\uff1a</p> YAML<pre><code># \u5b57\u7b26\u4e32\ntitle: \u6211\u7684\u6587\u6863\n\n# \u5217\u8868\nplugins:\n  - search\n  - tags\n\n# \u5bf9\u8c61\ntheme:\n  name: material\n  features:\n    - navigation.tabs\n\n# \u591a\u884c\u5b57\u7b26\u4e32\ndescription: &gt;\n  \u8fd9\u662f\u4e00\u4e2a\n  \u591a\u884c\u63cf\u8ff0\n  \u793a\u4f8b\n\n# \u951a\u70b9\u5f15\u7528\ncopyright: &amp;copyright 2024 My Docs\nfooter:\n  copyright: *copyright\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3-mkdocs","title":"3 MkDocs \u6838\u5fc3\u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#31","title":"3.1 \u7ad9\u70b9\u4fe1\u606f\u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#311-site_name","title":"3.1.1 site_name \u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3111","title":"3.1.1.1 \u547d\u540d\u89c4\u8303","text":"<p>\u7f51\u7ad9\u540d\u79f0\u662f\u7ad9\u70b9\u7684\u7b2c\u4e00\u5370\u8c61\uff0c\u5e94\u9075\u5faa\u4ee5\u4e0b\u89c4\u8303\uff1a</p> YAML<pre><code># \u63a8\u8350\u7684\u547d\u540d\u65b9\u5f0f\nsite_name: \u6280\u672f\u6587\u6863\u4e2d\u5fc3\nsite_name: Developer Hub\nsite_name: API Documentation\n\n# \u907f\u514d\u7684\u547d\u540d\u65b9\u5f0f\nsite_name: docs            # \u592a\u8fc7\u7b80\u5355\nsite_name: My Doc Site     # \u4e0d\u591f\u4e13\u4e1a\nsite_name: TEST           # \u7f3a\u4e4f\u63cf\u8ff0\u6027\n</code></pre> <p>\u547d\u540d\u5efa\u8bae\uff1a</p> <ul> <li>\u4f7f\u7528\u7b80\u6d01\u660e\u4e86\u7684\u540d\u79f0</li> <li>\u53cd\u6620\u6587\u6863\u7684\u4e3b\u8981\u5185\u5bb9</li> <li>\u8003\u8651\u54c1\u724c\u8bc6\u522b\u5ea6</li> <li>\u907f\u514d\u4f7f\u7528\u7279\u6b8a\u5b57\u7b26</li> <li>\u9002\u5f53\u4f7f\u7528\u7a7a\u683c\u5206\u9694\u5355\u8bcd</li> </ul>"},{"location":"Tools/Blog/Mkdocs_Material/#3112","title":"3.1.1.2 \u591a\u8bed\u8a00\u652f\u6301","text":"<p>\u53ef\u4ee5\u901a\u8fc7\u914d\u7f6e\u5b9e\u73b0\u591a\u8bed\u8a00\u7ad9\u70b9\uff1a</p> YAML<pre><code># \u57fa\u7840\u914d\u7f6e\nsite_name: My Documentation\ntheme:\n  language: zh\n\n# \u591a\u8bed\u8a00\u914d\u7f6e\u793a\u4f8b\nextra:\n  alternate:\n    - name: English\n      link: /en/ \n      lang: en\n    - name: \u4e2d\u6587\n      link: /zh/\n      lang: zh\n\n# \u8bed\u8a00\u7279\u5b9a\u7684\u7ad9\u70b9\u540d\u79f0\nsite_name:\n  en: My Documentation\n  zh: \u6211\u7684\u6587\u6863\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3113-seo","title":"3.1.1.3 SEO \u4f18\u5316","text":"<p>\u901a\u8fc7\u5408\u9002\u7684\u7ad9\u70b9\u540d\u79f0\u63d0\u5347 SEO\uff1a</p> YAML<pre><code># SEO \u4f18\u5316\u914d\u7f6e\nsite_name: ProductName Documentation | CompanyName\nextra:\n  meta:\n    - name: robots\n      content: 'index, follow'\n    - name: keywords\n      content: 'docs, documentation, technical, api'\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#312-site_url","title":"3.1.2 site_url \u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3121-url","title":"3.1.2.1 URL \u683c\u5f0f\u8981\u6c42","text":"YAML<pre><code># \u6b63\u786e\u7684 URL \u683c\u5f0f\nsite_url: https://example.com/docs/\nsite_url: https://docs.example.com/\n\n# \u907f\u514d\u7684\u683c\u5f0f\nsite_url: http://example.com/docs    # \u7f3a\u5c11\u5c3e\u90e8\u659c\u6760\nsite_url: example.com/docs/          # \u7f3a\u5c11\u534f\u8bae\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3122","title":"3.1.2.2 \u57fa\u7840\u8def\u5f84\u914d\u7f6e","text":"YAML<pre><code># \u6839\u76ee\u5f55\u90e8\u7f72\nsite_url: https://example.com/\n\n# \u5b50\u76ee\u5f55\u90e8\u7f72\nsite_url: https://example.com/docs/\nuse_directory_urls: true  # \u63a8\u8350\u8bbe\u7f6e\n\n# \u672c\u5730\u5f00\u53d1\nsite_url: http://localhost:8000/\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3123","title":"3.1.2.3 \u5b50\u76ee\u5f55\u90e8\u7f72\u914d\u7f6e","text":"YAML<pre><code># GitHub Pages \u5b50\u76ee\u5f55\u90e8\u7f72\nsite_url: https://username.github.io/repository/\n\n# \u81ea\u5b9a\u4e49\u57df\u540d\u5b50\u76ee\u5f55\nsite_url: https://docs.example.com/project/\nextra:\n  base_path: /project/  # \u5982\u679c\u9700\u8981\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#313-site_author","title":"3.1.3 site_author \u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3131","title":"3.1.3.1 \u4f5c\u8005\u4fe1\u606f\u8bbe\u7f6e","text":"YAML<pre><code># \u57fa\u7840\u4f5c\u8005\u4fe1\u606f\nsite_author: John Doe\n\n# \u6269\u5c55\u4f5c\u8005\u4fe1\u606f\nextra:\n  author:\n    name: John Doe\n    email: john@example.com\n    website: https://johndoe.com\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3132","title":"3.1.3.2 \u7248\u6743\u4fe1\u606f","text":"YAML<pre><code># \u7248\u6743\u58f0\u660e\ncopyright: \"&amp;copy; 2024 John Doe\"\n\n# \u9ad8\u7ea7\u7248\u6743\u914d\u7f6e\nextra:\n  copyright:\n    author: John Doe\n    year: 2024\n    license: CC BY-NC-SA 4.0\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3133-meta","title":"3.1.3.3 meta \u4fe1\u606f","text":"YAML<pre><code># meta \u4fe1\u606f\u914d\u7f6e\nextra:\n  meta:\n    - name: author\n      content: John Doe\n    - name: contact\n      content: contact@example.com\n    - property: article:author\n      content: https://example.com/author\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#314-site_description","title":"3.1.4 site_description \u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3141-seo","title":"3.1.4.1 SEO \u63cf\u8ff0","text":"YAML<pre><code># \u57fa\u7840\u63cf\u8ff0\nsite_description: \u5168\u9762\u7684\u6280\u672f\u6587\u6863\u4e2d\u5fc3\uff0c\u63d0\u4f9b\u8be6\u7ec6\u7684API\u6587\u6863\u3001\u4f7f\u7528\u6307\u5357\u548c\u6700\u4f73\u5b9e\u8df5\u3002\n\n# \u591a\u8bed\u8a00\u63cf\u8ff0\nextra:\n  descriptions:\n    en: Comprehensive technical documentation center\n    zh: \u5168\u9762\u7684\u6280\u672f\u6587\u6863\u4e2d\u5fc3\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3142","title":"3.1.4.2 \u5173\u952e\u8bcd\u8bbe\u7f6e","text":"YAML<pre><code># \u901a\u8fc7 meta \u6807\u7b7e\u8bbe\u7f6e\u5173\u952e\u8bcd\nextra:\n  meta:\n    - name: keywords\n      content: MkDocs, documentation, technical docs, API, guides\n    - name: description\n      content: &gt;-\n        \u5168\u9762\u7684\u6280\u672f\u6587\u6863\u4e2d\u5fc3\uff0c\u5305\u542b\u8be6\u7ec6\u7684API\u6587\u6863\u3001\n        \u4f7f\u7528\u6307\u5357\u548c\u6700\u4f73\u5b9e\u8df5\u793a\u4f8b\u3002\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3143","title":"3.1.4.3 \u7ad9\u70b9\u6458\u8981","text":"YAML<pre><code># \u5b8c\u6574\u7684\u7ad9\u70b9\u4fe1\u606f\u914d\u7f6e\u793a\u4f8b\nsite_name: \u6280\u672f\u6587\u6863\u4e2d\u5fc3\nsite_description: &gt;-\n  \u63d0\u4f9b\u5168\u9762\u7684\u6280\u672f\u6587\u6863\u3001API\u53c2\u8003\u548c\u4f7f\u7528\u6307\u5357\uff0c\n  \u5e2e\u52a9\u5f00\u53d1\u8005\u5feb\u901f\u4e0a\u624b\u548c\u6df1\u5165\u4e86\u89e3\u4ea7\u54c1\u529f\u80fd\u3002\nsite_author: \u5f00\u53d1\u56e2\u961f\nsite_url: https://docs.example.com/\n\nextra:\n  meta:\n    - name: keywords\n      content: \u6280\u672f\u6587\u6863, API\u6587\u6863, \u5f00\u53d1\u6307\u5357, \u6700\u4f73\u5b9e\u8df5\n    - name: author\n      content: \u5f00\u53d1\u56e2\u961f\n    - name: robots\n      content: index, follow\n\n  analytics:\n    gtag: G-XXXXXXXXXX\n\ncopyright: \"&amp;copy; 2024 Example Company\"\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#315","title":"3.1.5 \u914d\u7f6e\u6700\u4f73\u5b9e\u8df5","text":"<ol> <li> <p>SEO \u4f18\u5316\u5efa\u8bae\uff1a    - \u4f7f\u7528\u6e05\u6670\u7684\u7ad9\u70b9\u540d\u79f0    - \u7f16\u5199\u6709\u5438\u5f15\u529b\u7684\u63cf\u8ff0    - \u5305\u542b\u76f8\u5173\u5173\u952e\u8bcd    - \u786e\u4fdd URL \u7ed3\u6784\u5408\u7406</p> </li> <li> <p>\u591a\u8bed\u8a00\u652f\u6301\uff1a    - \u4e3a\u6bcf\u79cd\u8bed\u8a00\u63d0\u4f9b\u72ec\u7acb\u63cf\u8ff0    - \u4f7f\u7528\u6b63\u786e\u7684\u8bed\u8a00\u4ee3\u7801    - \u8bbe\u7f6e\u5408\u9002\u7684\u5b57\u7b26\u7f16\u7801</p> </li> <li> <p>\u7248\u672c\u63a7\u5236\uff1a    - \u8bb0\u5f55\u914d\u7f6e\u66f4\u6539    - \u4f7f\u7528\u7248\u672c\u6ce8\u91ca    - \u5b9a\u671f\u66f4\u65b0\u7ad9\u70b9\u4fe1\u606f</p> </li> <li> <p>\u53ef\u7ef4\u62a4\u6027\uff1a    - \u4f7f\u7528\u6e05\u6670\u7684\u914d\u7f6e\u7ed3\u6784    - \u6dfb\u52a0\u5fc5\u8981\u7684\u6ce8\u91ca    - \u4fdd\u6301\u914d\u7f6e\u6587\u4ef6\u6574\u6d01</p> </li> </ol>"},{"location":"Tools/Blog/Mkdocs_Material/#32","title":"3.2 \u5bfc\u822a\u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#321-nav","title":"3.2.1 nav \u7ed3\u6784\u8bbe\u8ba1","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3211","title":"3.2.1.1 \u57fa\u7840\u5bfc\u822a\u7ed3\u6784","text":"<p>\u6700\u57fa\u672c\u7684\u5bfc\u822a\u914d\u7f6e\u793a\u4f8b\uff1a</p> YAML<pre><code>nav:\n  - Home: index.md\n  - About: about.md\n  - Contact: contact.md\n</code></pre> <p>\u66f4\u590d\u6742\u7684\u5206\u7ec4\u793a\u4f8b\uff1a</p> YAML<pre><code>nav:\n  - \u9996\u9875: index.md\n  - \u7528\u6237\u6307\u5357:\n    - \u4ecb\u7ecd: guide/introduction.md\n    - \u5feb\u901f\u5f00\u59cb: guide/getting-started.md\n    - \u57fa\u7840\u6559\u7a0b: guide/basics.md\n  - API \u6587\u6863:\n    - \u6982\u89c8: api/overview.md\n    - \u63a5\u53e3\u8bf4\u660e: api/reference.md\n  - \u5e38\u89c1\u95ee\u9898: faq.md\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3212","title":"3.2.1.2 \u5206\u7c7b\u7ec4\u7ec7","text":"<p>\u63a8\u8350\u7684\u5206\u7c7b\u65b9\u5f0f\uff1a</p> YAML<pre><code>nav:\n  - \u5f00\u59cb\u4f7f\u7528:\n    - \u7b80\u4ecb: getting-started/introduction.md\n    - \u5b89\u88c5: getting-started/installation.md\n    - \u914d\u7f6e: getting-started/configuration.md\n\n  - \u6838\u5fc3\u6982\u5ff5:\n    - \u6982\u8ff0: concepts/overview.md\n    - \u57fa\u7840\u67b6\u6784: concepts/architecture.md\n    - \u5de5\u4f5c\u539f\u7406: concepts/how-it-works.md\n\n  - \u9ad8\u7ea7\u6307\u5357:\n    - \u81ea\u5b9a\u4e49\u4e3b\u9898: advanced/custom-theme.md\n    - \u63d2\u4ef6\u5f00\u53d1: advanced/plugin-development.md\n    - \u6027\u80fd\u4f18\u5316: advanced/performance.md\n\n  - \u53c2\u8003\u6587\u6863:\n    - API: reference/api.md\n    - \u914d\u7f6e\u9879: reference/configuration.md\n    - \u547d\u4ee4\u884c: reference/cli.md\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3213","title":"3.2.1.3 \u6743\u91cd\u8bbe\u7f6e","text":"<p>\u4f7f\u7528\u6587\u4ef6\u540d\u524d\u7f00\u63a7\u5236\u987a\u5e8f\uff1a</p> YAML<pre><code>docs/\n\u251c\u2500\u2500 01_introduction.md\n\u251c\u2500\u2500 02_installation.md\n\u251c\u2500\u2500 03_configuration.md\n\u2514\u2500\u2500 04_usage.md\n\n# mkdocs.yml\nnav:\n  - \u4ecb\u7ecd: 01_introduction.md\n  - \u5b89\u88c5: 02_installation.md\n  - \u914d\u7f6e: 03_configuration.md\n  - \u4f7f\u7528: 04_usage.md\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#322","title":"3.2.2 \u6587\u4ef6\u7ec4\u7ec7","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3221","title":"3.2.2.1 \u6587\u4ef6\u547d\u540d\u89c4\u8303","text":"<p>\u63a8\u8350\u7684\u547d\u540d\u89c4\u8303\uff1a</p> Text Only<pre><code>docs/\n\u251c\u2500\u2500 index.md                    # \u9996\u9875\n\u251c\u2500\u2500 getting-started.md         # \u77ed\u6a2a\u7ebf\u5206\u9694\n\u251c\u2500\u2500 advanced_usage.md          # \u4e0b\u5212\u7ebf\u5206\u9694\uff08\u53ef\u9009\uff09\n\u2514\u2500\u2500 troubleshooting.md         # \u5168\u5c0f\u5199\n</code></pre> <p>\u6587\u4ef6\u547d\u540d\u5efa\u8bae\uff1a</p> <ul> <li>\u4f7f\u7528\u5c0f\u5199\u5b57\u6bcd</li> <li>\u5355\u8bcd\u95f4\u4f7f\u7528\u8fde\u5b57\u7b26\u6216\u4e0b\u5212\u7ebf</li> <li>\u6587\u4ef6\u540d\u5e94\u5177\u6709\u63cf\u8ff0\u6027</li> <li>\u4fdd\u6301\u547d\u540d\u4e00\u81f4\u6027</li> <li>\u907f\u514d\u4f7f\u7528\u7a7a\u683c\u548c\u7279\u6b8a\u5b57\u7b26</li> </ul>"},{"location":"Tools/Blog/Mkdocs_Material/#3222","title":"3.2.2.2 \u76ee\u5f55\u7ec4\u7ec7\u539f\u5219","text":"<p>\u6807\u51c6\u76ee\u5f55\u7ed3\u6784\uff1a</p> Text Only<pre><code>docs/\n\u251c\u2500\u2500 index.md                # \u7f51\u7ad9\u9996\u9875\n\u251c\u2500\u2500 getting-started/        # \u5165\u95e8\u6307\u5357\n\u2502   \u251c\u2500\u2500 index.md           # \u5206\u7c7b\u9996\u9875\n\u2502   \u251c\u2500\u2500 installation.md    # \u5b89\u88c5\u8bf4\u660e\n\u2502   \u2514\u2500\u2500 configuration.md   # \u914d\u7f6e\u8bf4\u660e\n\u251c\u2500\u2500 user-guide/            # \u7528\u6237\u6307\u5357\n\u2502   \u251c\u2500\u2500 index.md          # \u6307\u5357\u9996\u9875\n\u2502   \u251c\u2500\u2500 basic-usage.md    # \u57fa\u7840\u7528\u6cd5\n\u2502   \u2514\u2500\u2500 advanced.md       # \u9ad8\u7ea7\u7279\u6027\n\u2514\u2500\u2500 api/                   # API\u6587\u6863\n    \u251c\u2500\u2500 index.md          # API\u6982\u89c8\n    \u251c\u2500\u2500 endpoints.md      # \u63a5\u53e3\u5217\u8868\n    \u2514\u2500\u2500 authentication.md # \u8ba4\u8bc1\u8bf4\u660e\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3223","title":"3.2.2.3 \u7d22\u5f15\u6587\u4ef6\u4f7f\u7528","text":"<p>\u6bcf\u4e2a\u76ee\u5f55\u7684 index. md \u793a\u4f8b\uff1a</p> Markdown<pre><code># \u7528\u6237\u6307\u5357\n\n\u8fd9\u662f\u7528\u6237\u6307\u5357\u7684\u4e3b\u9875\u9762\uff0c\u5305\u542b\u4ee5\u4e0b\u5185\u5bb9\uff1a\n\n## \u5feb\u901f\u5bfc\u822a\n\n-  [\u57fa\u7840\u7528\u6cd5] (basic-usage.md) - \u5165\u95e8\u5fc5\u8bfb\n-  [\u9ad8\u7ea7\u7279\u6027] (advanced.md) - \u6df1\u5165\u4e86\u89e3\n\n## \u672c\u8282\u5185\u5bb9\n\n\u6b64\u90e8\u5206\u5c06\u5e2e\u52a9\u60a8\u4e86\u89e3\u4ea7\u54c1\u7684\u6838\u5fc3\u529f\u80fd\u548c\u4f7f\u7528\u65b9\u6cd5...\n</code></pre> <p>\u5bf9\u5e94\u7684\u5bfc\u822a\u914d\u7f6e\uff1a</p> YAML<pre><code>nav:\n  - \u7528\u6237\u6307\u5357:\n    - \u6982\u8ff0: user-guide/index.md\n    - \u57fa\u7840\u7528\u6cd5: user-guide/basic-usage.md\n    - \u9ad8\u7ea7\u7279\u6027: user-guide/advanced.md\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#323","title":"3.2.3 \u591a\u7ea7\u76ee\u5f55","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3231","title":"3.2.3.1 \u5c42\u7ea7\u7ed3\u6784\u8bbe\u8ba1","text":"<p>\u590d\u6742\u7684\u591a\u7ea7\u76ee\u5f55\u793a\u4f8b\uff1a</p> YAML<pre><code>nav:\n  - \u9996\u9875: index.md\n  - \u5165\u95e8\u6307\u5357:\n    - \u6982\u8ff0: getting-started/index.md\n    - \u57fa\u7840:\n      - \u5b89\u88c5: getting-started/basics/installation.md\n      - \u914d\u7f6e: getting-started/basics/configuration.md\n    - \u8fdb\u9636:\n      - \u81ea\u5b9a\u4e49: getting-started/advanced/customization.md\n      - \u4f18\u5316: getting-started/advanced/optimization.md\n  - \u5f00\u53d1\u6587\u6863:\n    - \u6982\u8ff0: development/index.md\n    - API:\n      - \u8ba4\u8bc1: development/api/authentication.md\n      - \u63a5\u53e3: development/api/endpoints.md\n    - SDK:\n      - Python: development/sdk/python.md\n      - JavaScript: development/sdk/javascript.md\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3232","title":"3.2.3.2 \u5bfc\u822a\u6df1\u5ea6\u63a7\u5236","text":"YAML<pre><code>theme:\n  name: material\n  features:\n    - navigation.sections  # \u663e\u793a\u7ae0\u8282\n    - navigation.expand   # \u5c55\u5f00\u5bfc\u822a\n    - navigation.indexes  # \u4f7f\u7528\u76ee\u5f55\u7d22\u5f15\n    - toc.integrate      # \u96c6\u6210\u76ee\u5f55\n\nmarkdown_extensions:\n  - toc:\n      permalink: true\n      toc_depth: 3       # \u63a7\u5236\u76ee\u5f55\u6df1\u5ea6\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3233","title":"3.2.3.3 \u6298\u53e0\u914d\u7f6e","text":"<p>Material \u4e3b\u9898\u7684\u6298\u53e0\u914d\u7f6e\uff1a</p> YAML<pre><code>theme:\n  name: material\n  features:\n    - navigation.sections    # \u663e\u793a\u5206\u533a\n    - navigation.expand     # \u9ed8\u8ba4\u5c55\u5f00\n    - navigation.indexes    # \u4f7f\u7528\u7d22\u5f15\u9875\n    - navigation.top        # \u8fd4\u56de\u9876\u90e8\u6309\u94ae\n\n  # \u5bfc\u822a\u680f\u8bbe\u7f6e\n  nav_style: dark          # \u5bfc\u822a\u680f\u6837\u5f0f\n  collapse_navigation: true # \u6298\u53e0\u5bfc\u822a\n  sticky_navigation: true  # \u56fa\u5b9a\u5bfc\u822a\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#324","title":"3.2.4 \u5bfc\u822a\u914d\u7f6e\u6700\u4f73\u5b9e\u8df5","text":"<ol> <li> <p>\u7ed3\u6784\u8bbe\u8ba1\u539f\u5219\uff1a    - \u4fdd\u6301\u5c42\u7ea7\u6e05\u6670    - \u63a7\u5236\u5bfc\u822a\u6df1\u5ea6\uff08\u5efa\u8bae\u4e0d\u8d85\u8fc7 3 \u5c42\uff09    - \u76f8\u5173\u5185\u5bb9\u5206\u7ec4    - \u4f7f\u7528\u76f4\u89c2\u7684\u547d\u540d</p> </li> <li> <p>\u6587\u4ef6\u7ec4\u7ec7\uff1a    - \u4f7f\u7528\u6709\u610f\u4e49\u7684\u76ee\u5f55\u540d    - \u4fdd\u6301\u6587\u4ef6\u7ed3\u6784\u6574\u6d01    - \u5408\u7406\u4f7f\u7528\u7d22\u5f15\u6587\u4ef6    - \u9075\u5faa\u4e00\u81f4\u7684\u547d\u540d\u89c4\u8303</p> </li> <li> <p>\u7528\u6237\u4f53\u9a8c\uff1a    - \u63d0\u4f9b\u6e05\u6670\u7684\u5bfc\u822a\u8def\u5f84    - \u6dfb\u52a0\u5408\u9002\u7684\u63cf\u8ff0    - \u8003\u8651\u79fb\u52a8\u7aef\u663e\u793a    - \u4f18\u5316\u5bfc\u822a\u54cd\u5e94\u901f\u5ea6</p> </li> <li> <p>\u7ef4\u62a4\u5efa\u8bae\uff1a    - \u5b9a\u671f\u68c0\u67e5\u6b7b\u94fe\u63a5    - \u66f4\u65b0\u5bfc\u822a\u7ed3\u6784    - \u4fdd\u6301\u6587\u6863\u540c\u6b65    - \u6536\u96c6\u7528\u6237\u53cd\u9988</p> </li> </ol>"},{"location":"Tools/Blog/Mkdocs_Material/#325","title":"3.2.5 \u7279\u6b8a\u5bfc\u822a\u529f\u80fd","text":"<ol> <li>\u9690\u85cf\u9875\u9762\uff1a</li> </ol> YAML<pre><code>nav:\n  - \u53ef\u89c1\u9875\u9762: visible.md\n  - !hidden \u9690\u85cf\u9875\u9762: hidden.md\n</code></pre> <ol> <li>\u5916\u90e8\u94fe\u63a5\uff1a</li> </ol> YAML<pre><code>nav:\n  - \u6587\u6863: index.md\n  - GitHub: https://github.com/your/repo\n  - \u793e\u533a: \n    - \u8bba\u575b: https://forum.example.com\n    - \u535a\u5ba2: https://blog.example.com\n</code></pre> <ol> <li>\u522b\u540d\u8bbe\u7f6e\uff1a</li> </ol> YAML<pre><code>nav:\n  - \u5f00\u59cb: \n    - \u6982\u8ff0: getting-started/index.md\n    - \u5feb\u901f\u5165\u95e8: getting-started/quickstart.md\n    - \u540c\u4e00\u6587\u4ef6\u4e0d\u540c\u5165\u53e3: !alias getting-started/quickstart.md\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#33-markdown","title":"3.3 Markdown \u6269\u5c55","text":""},{"location":"Tools/Blog/Mkdocs_Material/#331","title":"3.3.1 \u57fa\u7840\u6269\u5c55","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3311-meta","title":"3.3.1.1 meta \u6269\u5c55","text":"<p>\u652f\u6301\u5728 Markdown \u6587\u4ef6\u5934\u90e8\u6dfb\u52a0\u5143\u6570\u636e\uff1a</p> YAML<pre><code># mkdocs.yml \u914d\u7f6e\nmarkdown_extensions:\n  - meta\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Markdown<pre><code>---\ntitle: \u6211\u7684\u9875\u9762\u6807\u9898\ndescription: \u9875\u9762\u63cf\u8ff0\nauthor: \u4f5c\u8005\u540d\ndate: 2024-01-01\n---\n\n# \u6b63\u6587\u5185\u5bb9\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3312-toc","title":"3.3.1.2 toc \u6269\u5c55","text":"<p>\u81ea\u52a8\u751f\u6210\u76ee\u5f55\uff1a</p> YAML<pre><code>markdown_extensions:\n  - toc:\n      permalink: true        # \u6dfb\u52a0\u6bb5\u843d\u94fe\u63a5\n      toc_depth: 3          # \u76ee\u5f55\u6df1\u5ea6\n      separator: \"_\"        # \u6807\u9898\u951a\u70b9\u5206\u9694\u7b26\n      title: \"\u76ee\u5f55\"         # \u76ee\u5f55\u6807\u9898\n      slugify: !!python/object/apply:pymdownx.slugs.slugify\n        kwds: {case: lower} # URL \u8f6c\u6362\u89c4\u5219\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Markdown<pre><code>[TOC]\n\n# \u4e00\u7ea7\u6807\u9898\n## \u4e8c\u7ea7\u6807\u9898\n### \u4e09\u7ea7\u6807\u9898\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3313-tables","title":"3.3.1.3 tables \u6269\u5c55","text":"<p>\u589e\u5f3a\u7684\u8868\u683c\u652f\u6301\uff1a</p> YAML<pre><code>markdown_extensions:\n  - tables\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Markdown<pre><code>| \u529f\u80fd | \u57fa\u7840\u7248 | \u4e13\u4e1a\u7248 |\n|-----|:------:|-------:|\n| \u529f\u80fdA | \u2713 | \u2713 |\n| \u529f\u80fdB | \u2717 | \u2713 |\n| \u529f\u80fdC | \u2717 | \u2713 |\n\n: \u8868\u683c\u6807\u9898 {.class-name}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#332-pymdown-extensions","title":"3.3.2 PyMdown Extensions","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3321-superfences","title":"3.3.2.1 superfences \u914d\u7f6e","text":"<p>\u589e\u5f3a\u7684\u4ee3\u7801\u5757\u529f\u80fd\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.superfences:\n      custom_fences:\n        - name: mermaid\n          class: mermaid\n          format: !!python/name:pymdownx.superfences.fence_div_format\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Markdown<pre><code>```python title=\"example.py\" linenums=\"1\" hl_lines=\"2 3\"\ndef hello_world():\n    message = \"Hello, World!\"\n    print(message)\n    return message\n```\n\n```mermaid\ngraph LR\n    A[\u5f00\u59cb] --&gt; B{\u5224\u65ad}\n    B --&gt; |Yes| C[\u6267\u884c]\n    B --&gt; |No| D[\u8df3\u8fc7]\n```\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3322-emoji","title":"3.3.2.2 emoji \u652f\u6301","text":"<p>\u6dfb\u52a0\u8868\u60c5\u7b26\u53f7\u652f\u6301\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.emoji:\n      emoji_index: !!python/name:material.extensions.emoji.twemoji\n      emoji_generator: !!python/name:material.extensions.emoji.to_svg\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Markdown<pre><code>:smile: :heart: :thumbsup:\n\n:fontawesome-brands-github: GitHub\n:material-account: \u7528\u6237\n:octicons-repo-16: \u4ed3\u5e93\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3323-tasklist","title":"3.3.2.3 tasklist \u529f\u80fd","text":"<p>\u4efb\u52a1\u5217\u8868\u652f\u6301\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.tasklist:\n      custom_checkbox: true    # \u81ea\u5b9a\u4e49\u590d\u9009\u6846\u6837\u5f0f\n      clickable_checkbox: true # \u53ef\u70b9\u51fb\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Markdown<pre><code>- [x] \u5df2\u5b8c\u6210\u4efb\u52a1\n- [ ] \u672a\u5b8c\u6210\u4efb\u52a1\n  - [x] \u5b50\u4efb\u52a1 1\n  - [ ] \u5b50\u4efb\u52a1 2\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3324-pymdown","title":"3.3.2.4 \u5176\u4ed6\u5e38\u7528 PyMdown \u6269\u5c55","text":"YAML<pre><code>markdown_extensions:\n  - pymdownx.highlight     # \u4ee3\u7801\u9ad8\u4eae\n  - pymdownx.inlinehilite # \u884c\u5185\u4ee3\u7801\u9ad8\u4eae\n  - pymdownx.snippets     # \u4ee3\u7801\u7247\u6bb5\n  - pymdownx.magiclink    # \u81ea\u52a8\u94fe\u63a5\n  - pymdownx.mark        # ==\u6807\u8bb0==\n  - pymdownx.critic      # \u7f16\u8f91\u6807\u8bb0\n  - pymdownx.tilde      # \u5220\u9664\u7ebf\n  - pymdownx.caret      # \u4e0a\u6807\n  - pymdownx.keys       # \u952e\u76d8\u6309\u952e\n  - pymdownx.tabbed    # \u6807\u7b7e\u9875\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#333","title":"3.3.3 \u81ea\u5b9a\u4e49\u6269\u5c55","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3331","title":"3.3.3.1 \u6269\u5c55\u5f00\u53d1\u57fa\u7840","text":"<p>\u521b\u5efa\u81ea\u5b9a\u4e49\u6269\u5c55\uff1a</p> Python<pre><code># custom_extension.py\nfrom markdown.extensions import Extension\nfrom markdown.preprocessors import Preprocessor\n\nclass CustomPreprocessor(Preprocessor):\n    def run(self, lines):\n        new_lines = []\n        for line in lines:\n            new_lines.append(line.replace('[[', '**').replace(']]', '**'))\n        return new_lines\n\nclass CustomExtension(Extension):\n    def extendMarkdown(self, md):\n        md.preprocessors.register(CustomPreprocessor(md), 'custom_preprocessor', 175)\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#34","title":"3.4 \u5e38\u7528\u6269\u5c55\u793a\u4f8b","text":"<ol> <li>\u6dfb\u52a0\u81ea\u5b9a\u4e49 HTML \u5c5e\u6027\uff1a</li> </ol> Python<pre><code>from markdown.extensions import Extension\nfrom markdown.treeprocessors import Treeprocessor\n\nclass CustomAttributesTreeprocessor(Treeprocessor):\n    def run(self, root):\n        for elem in root.iter():\n            if 'class' in elem.attrib:\n                elem.set('data-custom', 'value')\n\nclass CustomAttributesExtension(Extension):\n    def extendMarkdown(self, md):\n        md.treeprocessors.register(\n            CustomAttributesTreeprocessor(md), 'custom_attributes', 15\n        )\n</code></pre> <ol> <li>\u81ea\u5b9a\u4e49\u5bb9\u5668\uff1a</li> </ol> Python<pre><code>from markdown.extensions import Extension\nfrom markdown.blockprocessors import BlockProcessor\nimport re\n\nclass CustomContainerProcessor(BlockProcessor):\n    RE = re.compile(r':{3,}\\ *(warning|note|tip)\\ *')\n\n    def run(self, parent, blocks):\n        block = blocks.pop(0)\n        m = self.RE.match(block)\n\n        if m:\n            container_type = m.group(1)\n            div = etree.SubElement(parent, 'div')\n            div.set('class', f'custom-container {container_type}')\n\n            # \u5904\u7406\u5bb9\u5668\u5185\u5bb9\n            self.parser.parseChunk(div, block[m.end():])\n\nclass CustomContainerExtension(Extension):\n    def extendMarkdown(self, md):\n        md.parser.blockprocessors.register(\n            CustomContainerProcessor(md.parser), 'custom_container', 175\n        )\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#341","title":"3.4.1 \u6269\u5c55\u914d\u7f6e\u65b9\u6cd5","text":"<p>\u5728 <code>mkdocs.yml</code> \u4e2d\u914d\u7f6e\u81ea\u5b9a\u4e49\u6269\u5c55\uff1a</p> YAML<pre><code>markdown_extensions:\n  - custom_extension:\n      option1: value1\n      option2: value2\n\nextra_css:\n  - css/custom_extension.css\n\nextra_javascript:\n  - js/custom_extension.js\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#342","title":"3.4.2 \u6269\u5c55\u7ec4\u5408\u63a8\u8350","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3421","title":"3.4.2.1 \u57fa\u7840\u6587\u6863\u914d\u7f6e","text":"YAML<pre><code>markdown_extensions:\n  - meta\n  - toc:\n      permalink: true\n  - tables\n  - attr_list\n  - def_list\n  - footnotes\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3422","title":"3.4.2.2 \u589e\u5f3a\u529f\u80fd\u914d\u7f6e","text":"YAML<pre><code>markdown_extensions:\n  - pymdownx.superfences:\n      custom_fences:\n        - name: mermaid\n          class: mermaid\n          format: !!python/name:pymdownx.superfences.fence_div_format\n  - pymdownx.highlight:\n      anchor_linenums: true\n  - pymdownx.inlinehilite\n  - pymdownx.snippets\n  - pymdownx.tasklist:\n      custom_checkbox: true\n  - pymdownx.emoji:\n      emoji_index: !!python/name:material.extensions.emoji.twemoji\n      emoji_generator: !!python/name:material.extensions.emoji.to_svg\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#343","title":"3.4.3 \u5b8c\u6574\u63a8\u8350\u914d\u7f6e","text":"YAML<pre><code>markdown_extensions:\n  # Python Markdown\n  - meta\n  - toc:\n      permalink: true\n      toc_depth: 4\n  - tables\n  - attr_list\n  - def_list\n  - md_in_html\n  - footnotes\n\n  # Python Markdown Extensions\n  - pymdownx.superfences\n  - pymdownx.highlight\n  - pymdownx.inlinehilite\n  - pymdownx.snippets\n  - pymdownx.tasklist\n  - pymdownx.emoji\n  - pymdownx.mark\n  - pymdownx.critic\n  - pymdownx.keys\n  - pymdownx.tilde\n  - pymdownx.caret\n  - pymdownx.details\n  - pymdownx.magiclink\n  - pymdownx.tabbed:\n      alternate_style: true\n\n  # \u81ea\u5b9a\u4e49\u6269\u5c55\n  - custom_extension:\n      custom_option: value\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#344","title":"3.4.4 \u4f7f\u7528\u5efa\u8bae","text":"<ol> <li> <p>\u6027\u80fd\u8003\u8651\uff1a    - \u53ea\u542f\u7528\u9700\u8981\u7684\u6269\u5c55    - \u6ce8\u610f\u6269\u5c55\u4e4b\u95f4\u7684\u4f9d\u8d56\u5173\u7cfb    - \u63a7\u5236\u6269\u5c55\u6570\u91cf</p> </li> <li> <p>\u517c\u5bb9\u6027\uff1a    - \u6d4b\u8bd5\u6269\u5c55\u7ec4\u5408    - \u68c0\u67e5\u79fb\u52a8\u7aef\u663e\u793a    - \u9a8c\u8bc1\u4e0d\u540c\u6d4f\u89c8\u5668</p> </li> <li> <p>\u7ef4\u62a4\u5efa\u8bae\uff1a    - \u8bb0\u5f55\u6269\u5c55\u914d\u7f6e    - \u4fdd\u6301\u7248\u672c\u66f4\u65b0    - \u76d1\u63a7\u6027\u80fd\u5f71\u54cd</p> </li> </ol>"},{"location":"Tools/Blog/Mkdocs_Material/#35","title":"3.5 \u63d2\u4ef6\u7cfb\u7edf","text":""},{"location":"Tools/Blog/Mkdocs_Material/#351","title":"3.5.1 \u63d2\u4ef6\u914d\u7f6e\u65b9\u5f0f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3511","title":"3.5.1.1 \u63d2\u4ef6\u5b89\u88c5\u65b9\u6cd5","text":"<p>\u901a\u8fc7 pip \u5b89\u88c5\u63d2\u4ef6\uff1a</p> Bash<pre><code># \u5b89\u88c5\u5355\u4e2a\u63d2\u4ef6\npip install mkdocs-git-revision-date-localized-plugin\n\n# \u5b89\u88c5\u591a\u4e2a\u63d2\u4ef6\npip install mkdocs-minify-plugin mkdocs-git-authors-plugin\n</code></pre> <p>\u57fa\u7840\u63d2\u4ef6\u914d\u7f6e\uff1a</p> YAML<pre><code># mkdocs.yml\nplugins:\n  - search  # \u9ed8\u8ba4\u63d2\u4ef6\n  - git-revision-date-localized:\n      enable_creation_date: true\n  - minify:\n      minify_html: true\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3512","title":"3.5.1.2 \u914d\u7f6e\u8bed\u6cd5","text":"<p>\u63d2\u4ef6\u914d\u7f6e\u7684\u51e0\u79cd\u65b9\u5f0f\uff1a</p> YAML<pre><code># 1. \u7b80\u5355\u542f\u7528\u63d2\u4ef6\uff08\u4f7f\u7528\u9ed8\u8ba4\u914d\u7f6e\uff09\nplugins:\n  - search\n  - tags\n\n# 2. \u7981\u7528\u9ed8\u8ba4\u63d2\u4ef6\nplugins:\n  - search: false\n\n# 3. \u5e26\u914d\u7f6e\u7684\u63d2\u4ef6\nplugins:\n  - search:\n      lang: \n        - en\n        - zh\n      separator: '[\\s\\-\\.]+'\n\n# 4. \u591a\u5b9e\u4f8b\u63d2\u4ef6\nplugins:\n  - search:\n      name: search_1\n      config: value\n  - search:\n      name: search_2\n      config: value\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3513","title":"3.5.1.3 \u4f18\u5148\u7ea7\u63a7\u5236","text":"<p>\u63d2\u4ef6\u6267\u884c\u987a\u5e8f\u63a7\u5236\uff1a</p> YAML<pre><code>plugins:\n  - search\n  - git-revision-date-localized:\n      priority: 80\n  - minify:\n      priority: 90\n  - tags:\n      priority: 70\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#352","title":"3.5.2 \u5e38\u7528\u63d2\u4ef6\u4ecb\u7ecd","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3521","title":"3.5.2.1 \u5b98\u65b9\u63d2\u4ef6","text":"<ol> <li>search - \u641c\u7d22\u63d2\u4ef6</li> </ol> YAML<pre><code>plugins:\n  - search:\n      lang: \n        - en\n        - zh\n      separator: '[\\s\\-\\.]+'\n      min_search_length: 2\n      prebuild_index: true\n      indexing:\n        - full_sections: false\n        - headings: true\n        - content: true\n</code></pre> <ol> <li>tags - \u6807\u7b7e\u7cfb\u7edf</li> </ol> YAML<pre><code>plugins:\n  - tags:\n      tags_file: tags.md\n      tags_extra_files:\n        cloud: cloud_tags.md\n        list: tag_list.md\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3522","title":"3.5.2.2 \u793e\u533a\u63d2\u4ef6\u63a8\u8350","text":"<ol> <li>git-revision-date-localized - Git \u65e5\u671f\u4fe1\u606f</li> </ol> YAML<pre><code>plugins:\n  - git-revision-date-localized:\n      type: timeago\n      enable_creation_date: true\n      exclude:\n        - index.md\n      timezone: Asia/Shanghai\n      locale: zh\n</code></pre> <ol> <li>minify - \u6587\u4ef6\u538b\u7f29</li> </ol> YAML<pre><code>plugins:\n  - minify:\n      minify_html: true\n      minify_js: true\n      minify_css: true\n      htmlmin_opts:\n        remove_comments: true\n</code></pre> <ol> <li>social - \u793e\u4ea4\u5206\u4eab</li> </ol> YAML<pre><code>plugins:\n  - social:\n      cards: true\n      cards_color:\n        fill: \"#0FF1CE\"\n        text: \"#FFFFFF\"\n</code></pre> <ol> <li>macros - \u6a21\u677f\u5b8f</li> </ol> YAML<pre><code>plugins:\n  - macros:\n      module_name: macros\n      include_dir: include\n      include_yaml:\n        - variables.yml\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3523","title":"3.5.2.3 \u5b9e\u7528\u63d2\u4ef6\u96c6\u5408","text":"YAML<pre><code>plugins:\n  # \u6838\u5fc3\u529f\u80fd\n  - search\n  - tags\n\n  # \u7248\u672c\u63a7\u5236\n  - git-revision-date-localized\n  - git-authors\n\n  # \u6027\u80fd\u4f18\u5316\n  - minify\n  - optimize\n\n  # \u5185\u5bb9\u589e\u5f3a\n  - social\n  - macros\n  - blogging\n\n  # \u591a\u8bed\u8a00\u652f\u6301\n  - i18n\n  - translations\n\n  # \u56fe\u7247\u5904\u7406\n  - glightbox\n  - img2fig\n\n  # \u7edf\u8ba1\u5206\u6790\n  - statistics\n  - pdf-export\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#353","title":"3.5.3 \u63d2\u4ef6\u7ec4\u5408\u4f7f\u7528","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3531","title":"3.5.3.1 \u57fa\u7840\u7ec4\u5408\u65b9\u6848","text":"<p>\u9002\u5408\u4e00\u822c\u6587\u6863\u9879\u76ee\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      lang: zh\n      separator: '[\\s\\-\\.]+'\n\n  - git-revision-date-localized:\n      enable_creation_date: true\n      type: date\n\n  - minify:\n      minify_html: true\n\n  - glightbox:\n      touchNavigation: true\n      loop: false\n      effect: zoom\n      width: 100%\n      height: auto\n      zoomable: true\n      draggable: true\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3532","title":"3.5.3.2 \u535a\u5ba2\u7f51\u7ad9\u65b9\u6848","text":"<p>\u9002\u5408\u535a\u5ba2\u7c7b\u7f51\u7ad9\uff1a</p> YAML<pre><code>plugins:\n  - blog:\n      blog_dir: blog\n      post_url_format: \"{slug}\"\n      post_excerpt: optional\n\n  - social:\n      cards: true\n      cards_dir: assets/social\n\n  - tags:\n      tags_file: tags.md\n\n  - rss:\n      abstract_chars_count: 160\n      date_from_meta: true\n\n  - statistics:\n      page_check: true\n      page_count: true\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3533","title":"3.5.3.3 \u6280\u672f\u6587\u6863\u65b9\u6848","text":"<p>\u9002\u5408\u5927\u578b\u6280\u672f\u6587\u6863\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      separator: '[\\s\\-\\.]+'\n      min_search_length: 2\n      lang:\n        - en\n        - zh\n      prebuild_index: true\n\n  - git-revision-date-localized:\n      type: timeago\n      enable_creation_date: true\n\n  - minify:\n      minify_html: true\n      minify_js: true\n      minify_css: true\n\n  - macros:\n      module_name: includes.macros\n      include_yaml:\n        - includes/variables.yml\n\n  - pdf-export:\n      combined: true\n      combined_output_path: pdf/document.pdf\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#354","title":"3.5.4 \u6027\u80fd\u4f18\u5316\u5efa\u8bae","text":"<ol> <li> <p>\u63d2\u4ef6\u9009\u62e9\uff1a    - \u53ea\u542f\u7528\u5fc5\u8981\u7684\u63d2\u4ef6    - \u907f\u514d\u529f\u80fd\u91cd\u590d\u7684\u63d2\u4ef6    - \u6ce8\u610f\u63d2\u4ef6\u95f4\u7684\u4f9d\u8d56\u5173\u7cfb</p> </li> <li> <p>\u914d\u7f6e\u4f18\u5316\uff1a</p> </li> </ol> YAML<pre><code>plugins:\n  - search:\n      prebuild_index: true  # \u9884\u6784\u5efa\u7d22\u5f15\n  - minify:\n      cache: true          # \u542f\u7528\u7f13\u5b58\n      cache_dir: .cache    # \u7f13\u5b58\u76ee\u5f55\n  - optimize:              # \u8d44\u6e90\u4f18\u5316\n      cache: true\n</code></pre> <ol> <li>\u6784\u5efa\u4f18\u5316\uff1a</li> </ol> YAML<pre><code>plugins:\n  # \u5e76\u884c\u5904\u7406\u63d2\u4ef6\n  - parallel:\n      workers: 4\n  # \u7f13\u5b58\u63d2\u4ef6\n  - cache:\n      enabled: true\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4-material","title":"4 Material \u4e3b\u9898\u5b8c\u5168\u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#41","title":"4.1 \u57fa\u7840\u5916\u89c2","text":""},{"location":"Tools/Blog/Mkdocs_Material/#411","title":"4.1.1 \u914d\u8272\u65b9\u6848","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4111","title":"4.1.1.1 \u9884\u8bbe\u4e3b\u9898\u8272","text":"<p>Material \u4e3b\u9898\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u9884\u8bbe\u989c\u8272\uff1a</p> YAML<pre><code>theme:\n  name: material\n  palette:\n    primary: indigo    # \u4e3b\u8272\u8c03\n    accent: pink      # \u5f3a\u8c03\u8272\n\n# \u53ef\u7528\u7684\u4e3b\u9898\u8272\uff1a\n# red, pink, purple, deep purple, indigo, blue, light blue, \n# cyan, teal, green, light green, lime, yellow, amber, \n# orange, deep orange, brown, grey, blue grey\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4112","title":"4.1.1.2 \u81ea\u5b9a\u4e49\u914d\u8272","text":"<p>\u5b8c\u6574\u7684\u81ea\u5b9a\u4e49\u914d\u8272\u914d\u7f6e\uff1a</p> YAML<pre><code>theme:\n  palette:\n    # \u4eae\u8272\u4e3b\u9898\n    - media: \"(prefers-color-scheme: light)\"\n      scheme: default\n      primary: indigo\n      accent: indigo\n      toggle:\n        icon: material/brightness-7\n        name: \u5207\u6362\u81f3\u6697\u8272\u6a21\u5f0f\n\n    # \u6697\u8272\u4e3b\u9898\n    - media: \"(prefers-color-scheme: dark)\"\n      scheme: slate\n      primary: indigo\n      accent: indigo\n      toggle:\n        icon: material/brightness-4\n        name: \u5207\u6362\u81f3\u4eae\u8272\u6a21\u5f0f\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4113-css","title":"4.1.1.3 \u81ea\u5b9a\u4e49 CSS \u53d8\u91cf","text":"<p>\u521b\u5efa <code>docs/stylesheets/extra.css</code>\uff1a</p> CSS<pre><code>:root {\n  --md-primary-fg-color:        #2196f3;\n  --md-primary-fg-color--light: #64b5f6;\n  --md-primary-fg-color--dark:  #1976d2;\n  --md-accent-fg-color:         #2196f3;\n}\n\n[data-md-color-scheme=\"slate\"] {\n  --md-primary-fg-color:        #90caf9;\n  --md-primary-fg-color--light: #e3f2fd;\n  --md-primary-fg-color--dark:  #42a5f5;\n}\n</code></pre> <p>\u5728 <code>mkdocs.yml</code> \u4e2d\u5f15\u5165\uff1a</p> YAML<pre><code>extra_css:\n  - stylesheets/extra.css\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#412","title":"4.1.2 \u4e3b\u9898\u5207\u6362","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4121","title":"4.1.2.1 \u57fa\u7840\u5207\u6362\u914d\u7f6e","text":"YAML<pre><code>theme:\n  name: material\n  palette:\n    # \u914d\u7f6e\u5207\u6362\u6309\u94ae\n    - scheme: default\n      toggle:\n        icon: material/brightness-7 \n        name: \u5207\u6362\u81f3\u6697\u8272\u6a21\u5f0f\n      primary: indigo\n      accent: indigo\n\n    - scheme: slate\n      toggle:\n        icon: material/brightness-4\n        name: \u5207\u6362\u81f3\u4eae\u8272\u6a21\u5f0f\n      primary: indigo\n      accent: indigo\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4122","title":"4.1.2.2 \u9ad8\u7ea7\u5207\u6362\u529f\u80fd","text":"<p>\u6dfb\u52a0\u81ea\u5b9a\u4e49\u5207\u6362\u903b\u8f91\uff1a</p> YAML<pre><code>extra_javascript:\n  - javascripts/theme-switch.js\n</code></pre> <p><code>theme-switch.js</code> \u5185\u5bb9\uff1a</p> JavaScript<pre><code>document.addEventListener('DOMContentLoaded', function() {\n  // \u83b7\u53d6\u7cfb\u7edf\u4e3b\u9898\u504f\u597d\n  const prefersDark = window.matchMedia('(prefers-color-scheme: dark)');\n\n  // \u76d1\u542c\u7cfb\u7edf\u4e3b\u9898\u53d8\u5316\n  prefersDark.addListener((e) =&gt; {\n    const theme = e.matches ? 'slate' : 'default';\n    document.body.setAttribute('data-md-color-scheme', theme);\n  });\n\n  // \u521d\u59cb\u5316\u4e3b\u9898\n  const theme = prefersDark.matches ? 'slate' : 'default';\n  document.body.setAttribute('data-md-color-scheme', theme);\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#413","title":"4.1.3 \u56fe\u6807\u8bbe\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4131","title":"4.1.3.1 \u7f51\u7ad9\u56fe\u6807","text":"<p>\u914d\u7f6e\u7f51\u7ad9\u56fe\u6807\u548c Logo\uff1a</p> YAML<pre><code>theme:\n  icon:\n    logo: material/book-open-page-variant  # \u7f51\u7ad9 Logo\n    repo: fontawesome/brands/github        # \u4ed3\u5e93\u56fe\u6807\n\n  favicon: assets/favicon.png              # \u7f51\u7ad9\u56fe\u6807\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4132","title":"4.1.3.2 \u529f\u80fd\u56fe\u6807","text":"<p>\u4e3a\u4e0d\u540c\u529f\u80fd\u914d\u7f6e\u56fe\u6807\uff1a</p> YAML<pre><code>theme:\n  icon:\n    repo: fontawesome/brands/github      # \u4ed3\u5e93\u56fe\u6807\n    edit: material/pencil                # \u7f16\u8f91\u56fe\u6807\n    view: material/eye                   # \u67e5\u770b\u56fe\u6807\n    admonition:\n      note: octicons/tag-16             # \u63d0\u793a\u6846\u56fe\u6807\n      abstract: octicons/checklist-16\n      info: octicons/info-16\n      tip: octicons/squirrel-16\n      success: octicons/check-16\n      question: octicons/question-16\n      warning: octicons/alert-16\n      failure: octicons/x-circle-16\n      danger: octicons/zap-16\n      bug: octicons/bug-16\n      example: octicons/beaker-16\n      quote: octicons/quote-16\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4133-svg","title":"4.1.3.3 \u81ea\u5b9a\u4e49 SVG \u56fe\u6807","text":"<p>\u6dfb\u52a0\u81ea\u5b9a\u4e49 SVG \u56fe\u6807\uff1a</p> <ol> <li>\u521b\u5efa <code>.icons</code> \u76ee\u5f55\uff1a</li> </ol> Text Only<pre><code>.\n\u251c\u2500 .icons/\n\u2502  \u2514\u2500 custom/\n\u2502     \u2514\u2500 logo.svg\n\u2514\u2500 mkdocs.yml\n</code></pre> <ol> <li>\u914d\u7f6e\u4f7f\u7528\uff1a</li> </ol> YAML<pre><code>theme:\n  icon:\n    logo: custom/logo\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#414-logo","title":"4.1.4 Logo \u8bbe\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4141-logo","title":"4.1.4.1 \u57fa\u7840 Logo \u914d\u7f6e","text":"YAML<pre><code>theme:\n  logo: assets/logo.svg        # Logo \u56fe\u7247\n  icon:\n    logo: material/book        # \u6216\u4f7f\u7528\u56fe\u6807\u4f5c\u4e3a Logo\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4142-logo","title":"4.1.4.2 \u54cd\u5e94\u5f0f Logo","text":"<p>\u521b\u5efa\u54cd\u5e94\u5f0f Logo\uff1a</p> YAML<pre><code>theme:\n  logo: assets/logo.svg\nextra_css:\n  - stylesheets/logo.css\n</code></pre> <p><code>logo.css</code> \u5185\u5bb9\uff1a</p> CSS<pre><code>/* \u9ed8\u8ba4 Logo */\n.md-logo img {\n  width: 40px;\n  height: 40px;\n}\n\n/* \u79fb\u52a8\u7aef Logo */\n@media screen and (max-width: 76.1875em) {\n  .md-logo img {\n    width: 32px;\n    height: 32px;\n  }\n}\n\n/* \u6697\u8272\u4e3b\u9898 Logo */\n[data-md-color-scheme=\"slate\"] .md-logo img {\n  filter: invert(1);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4143-logo","title":"4.1.4.3 Logo \u52a8\u753b\u6548\u679c","text":"<p>\u6dfb\u52a0 Logo \u52a8\u753b\uff1a</p> CSS<pre><code>.md-logo img {\n  transition: transform 0.3s ease;\n}\n\n.md-logo img:hover {\n  transform: scale(1.1);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#415","title":"4.1.5 \u5b8c\u6574\u914d\u7f6e\u793a\u4f8b","text":"YAML<pre><code># mkdocs.yml\ntheme:\n  name: material\n\n  # \u8c03\u8272\u677f\u914d\u7f6e\n  palette:\n    - media: \"(prefers-color-scheme: light)\"\n      scheme: default\n      primary: indigo\n      accent: indigo\n      toggle:\n        icon: material/brightness-7\n        name: \u5207\u6362\u81f3\u6697\u8272\u6a21\u5f0f\n    - media: \"(prefers-color-scheme: dark)\"\n      scheme: slate\n      primary: blue\n      accent: blue\n      toggle:\n        icon: material/brightness-4\n        name: \u5207\u6362\u81f3\u4eae\u8272\u6a21\u5f0f\n\n  # \u56fe\u6807\u914d\u7f6e\n  icon:\n    logo: material/book-open-page-variant\n    repo: fontawesome/brands/github\n    edit: material/pencil\n    view: material/eye\n\n  # Logo \u914d\u7f6e\n  logo: assets/logo.svg\n  favicon: assets/favicon.png\n\n# \u989d\u5916\u6837\u5f0f\nextra_css:\n  - stylesheets/extra.css\n  - stylesheets/logo.css\n\n# \u989d\u5916\u811a\u672c\nextra_javascript:\n  - javascripts/theme-switch.js\n\n# \u4e3b\u9898\u7279\u6027\nfeatures:\n  - navigation.instant\n  - navigation.tracking\n  - navigation.tabs\n  - navigation.sections\n  - navigation.expand\n  - navigation.top\n  - toc.integrate\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#42","title":"4.2 \u5bfc\u822a\u529f\u80fd","text":""},{"location":"Tools/Blog/Mkdocs_Material/#421","title":"4.2.1 \u9876\u90e8\u5bfc\u822a","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4211","title":"4.2.1.1 \u5bfc\u822a\u680f\u6837\u5f0f","text":"<p>\u57fa\u7840\u5bfc\u822a\u680f\u914d\u7f6e\uff1a</p> YAML<pre><code>theme:\n  name: material\n  features:\n    - navigation.tabs        # \u542f\u7528\u6807\u7b7e\u5f0f\u5bfc\u822a\n    - navigation.sections    # \u663e\u793a\u7ae0\u8282\u5bfc\u822a\n    - navigation.expand     # \u5c55\u5f00\u5bfc\u822a\n    - navigation.indexes    # \u7ae0\u8282\u7d22\u5f15\u9875\n</code></pre> <p>\u81ea\u5b9a\u4e49\u5bfc\u822a\u680f\u6837\u5f0f\uff1a</p> CSS<pre><code>/* docs/stylesheets/extra.css */\n\n/* \u5bfc\u822a\u680f\u80cc\u666f */\n.md-header {\n  background-color: #2196f3;\n  box-shadow: 0 2px 4px rgba(0,0,0,.14);\n}\n\n/* \u5bfc\u822a\u9879\u6837\u5f0f */\n.md-tabs__link {\n  font-size: .8rem;\n  margin-top: .4rem;\n}\n\n/* \u6fc0\u6d3b\u72b6\u6001 */\n.md-tabs__link--active {\n  font-weight: bold;\n  border-bottom: 2px solid currentColor;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4212","title":"4.2.1.2 \u56fa\u5b9a\u5bfc\u822a\u680f","text":"<p>\u542f\u7528\u56fa\u5b9a\u5bfc\u822a\uff1a</p> YAML<pre><code>theme:\n  features:\n    - header.autohide       # \u81ea\u52a8\u9690\u85cf\n    - navigation.sticky    # \u56fa\u5b9a\u5bfc\u822a\n</code></pre> <p>\u81ea\u5b9a\u4e49\u56fa\u5b9a\u5bfc\u822a\u884c\u4e3a\uff1a</p> CSS<pre><code>/* \u56fa\u5b9a\u5bfc\u822a\u680f\u6837\u5f0f */\n.md-header--sticky {\n  backdrop-filter: blur(8px);\n  background-color: rgba(255,255,255,.8);\n}\n\n/* \u6697\u8272\u4e3b\u9898 */\n[data-md-color-scheme=\"slate\"] .md-header--sticky {\n  background-color: rgba(0,0,0,.8);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4213","title":"4.2.1.3 \u54cd\u5e94\u5f0f\u5bfc\u822a","text":"<p>\u54cd\u5e94\u5f0f\u914d\u7f6e\uff1a</p> YAML<pre><code>theme:\n  features:\n    - navigation.instant    # \u5373\u65f6\u52a0\u8f7d\n    - navigation.tracking   # \u6eda\u52a8\u8ddf\u8e2a\n</code></pre> <p>\u54cd\u5e94\u5f0f\u6837\u5f0f\u8c03\u6574\uff1a</p> CSS<pre><code>/* \u79fb\u52a8\u7aef\u5bfc\u822a */\n@media screen and (max-width: 76.1875em) {\n  .md-nav__title {\n    font-size: .9rem;\n    padding: 0.5rem 0.8rem;\n  }\n\n  .md-nav__item {\n    padding: 0.2rem 0.8rem;\n  }\n}\n\n/* \u5e73\u677f\u5bfc\u822a */\n@media screen and (min-width: 76.25em) {\n  .md-nav__link {\n    padding: 0.2rem 0;\n  }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#422","title":"4.2.2 \u6807\u7b7e\u5bfc\u822a","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4221","title":"4.2.2.1 \u6807\u7b7e\u9875\u914d\u7f6e","text":"<p>\u542f\u7528\u6807\u7b7e\u5bfc\u822a\uff1a</p> YAML<pre><code>theme:\n  features:\n    - navigation.tabs\n    - navigation.tabs.sticky  # \u56fa\u5b9a\u6807\u7b7e\n</code></pre> <p>\u6807\u7b7e\u9875\u7ed3\u6784\uff1a</p> YAML<pre><code>nav:\n  - Home: index.md\n  - Guide:\n    - guide/index.md\n    - Installation: guide/installation.md\n    - Configuration: guide/configuration.md\n  - API:\n    - api/index.md\n    - Reference: api/reference.md\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4222","title":"4.2.2.2 \u6807\u7b7e\u6837\u5f0f","text":"<p>\u81ea\u5b9a\u4e49\u6807\u7b7e\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u6807\u7b7e\u5bb9\u5668 */\n.md-tabs {\n  background-color: var(--md-primary-fg-color--dark);\n}\n\n/* \u6807\u7b7e\u9879 */\n.md-tabs__item {\n  padding: 0 1rem;\n  transition: all 0.2s ease;\n}\n\n/* \u60ac\u505c\u6548\u679c */\n.md-tabs__item:hover {\n  background-color: rgba(255,255,255,.1);\n}\n\n/* \u6fc0\u6d3b\u72b6\u6001 */\n.md-tabs__item--active {\n  font-weight: bold;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4223","title":"4.2.2.3 \u6807\u7b7e\u4ea4\u4e92","text":"<p>\u6dfb\u52a0\u6807\u7b7e\u4ea4\u4e92\u6548\u679c\uff1a</p> JavaScript<pre><code>// docs/javascripts/tabs.js\n\ndocument.addEventListener('DOMContentLoaded', function() {\n  // \u6807\u7b7e\u70b9\u51fb\u6548\u679c\n  const tabs = document.querySelectorAll('.md-tabs__item');\n  tabs.forEach(tab =&gt; {\n    tab.addEventListener('click', () =&gt; {\n      // \u6dfb\u52a0\u70b9\u51fb\u6ce2\u7eb9\u6548\u679c\n      const ripple = document.createElement('div');\n      ripple.classList.add('md-tabs__ripple');\n      tab.appendChild(ripple);\n\n      // \u79fb\u9664\u6ce2\u7eb9\u6548\u679c\n      setTimeout(() =&gt; ripple.remove(), 1000);\n    });\n  });\n});\n</code></pre> <p>\u5bf9\u5e94\u7684 CSS\uff1a</p> CSS<pre><code>/* \u6ce2\u7eb9\u6548\u679c */\n.md-tabs__ripple {\n  position: absolute;\n  background: rgba(255,255,255,.3);\n  border-radius: 50%;\n  transform: scale(0);\n  animation: ripple 0.6s linear;\n}\n\n@keyframes ripple {\n  to {\n    transform: scale(4);\n    opacity: 0;\n  }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#423","title":"4.2.3 \u76ee\u5f55\u5bfc\u822a","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4231","title":"4.2.3.1 \u76ee\u5f55\u5c42\u7ea7","text":"<p>\u914d\u7f6e\u76ee\u5f55\u5c42\u7ea7\uff1a</p> YAML<pre><code>theme:\n  features:\n    - toc.integrate    # \u96c6\u6210\u76ee\u5f55\n    - toc.follow      # \u76ee\u5f55\u8ddf\u968f\n\nmarkdown_extensions:\n  - toc:\n      permalink: true    # \u6c38\u4e45\u94fe\u63a5\n      toc_depth: 3      # \u76ee\u5f55\u6df1\u5ea6\n      title: \u76ee\u5f55       # \u76ee\u5f55\u6807\u9898\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4232","title":"4.2.3.2 \u76ee\u5f55\u6837\u5f0f","text":"<p>\u81ea\u5b9a\u4e49\u76ee\u5f55\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u76ee\u5f55\u5bb9\u5668 */\n.md-toc {\n  padding: 1rem;\n  background-color: var(--md-code-bg-color);\n  border-radius: 4px;\n}\n\n/* \u76ee\u5f55\u6807\u9898 */\n.md-toc__title {\n  font-weight: bold;\n  margin-bottom: 1rem;\n}\n\n/* \u76ee\u5f55\u94fe\u63a5 */\n.md-toc__link {\n  color: var(--md-typeset-color);\n  text-decoration: none;\n}\n\n/* \u76ee\u5f55\u5c42\u7ea7\u7f29\u8fdb */\n.md-toc__list {\n  margin-left: 1.5em;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4233","title":"4.2.3.3 \u951a\u70b9\u94fe\u63a5","text":"<p>\u914d\u7f6e\u951a\u70b9\u94fe\u63a5\uff1a</p> YAML<pre><code>markdown_extensions:\n  - toc:\n      permalink: \u2693\ufe0e    # \u951a\u70b9\u7b26\u53f7\n      slug: !!python/object/apply:pymdownx.slugs.slugify\n        kwds: {case: lower}  # URL \u8f6c\u6362\u89c4\u5219\n</code></pre> <p>\u81ea\u5b9a\u4e49\u951a\u70b9\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u951a\u70b9\u94fe\u63a5 */\n.headerlink {\n  opacity: 0;\n  margin-left: .5em;\n  transition: opacity 0.2s ease;\n}\n\n/* \u6807\u9898\u60ac\u505c\u65f6\u663e\u793a\u951a\u70b9 */\nh1:hover .headerlink,\nh2:hover .headerlink,\nh3:hover .headerlink {\n  opacity: 1;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#424","title":"4.2.4 \u8fd4\u56de\u9876\u90e8","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4241","title":"4.2.4.1 \u6309\u94ae\u6837\u5f0f","text":"<p>\u542f\u7528\u8fd4\u56de\u9876\u90e8\u6309\u94ae\uff1a</p> YAML<pre><code>theme:\n  features:\n    - navigation.top    # \u8fd4\u56de\u9876\u90e8\u6309\u94ae\n</code></pre> <p>\u81ea\u5b9a\u4e49\u6309\u94ae\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u8fd4\u56de\u9876\u90e8\u6309\u94ae */\n.md-top {\n  background-color: var(--md-primary-fg-color);\n  border-radius: 50%;\n  box-shadow: 0 2px 4px rgba(0,0,0,.14);\n  transition: all 0.2s ease;\n}\n\n/* \u60ac\u505c\u6548\u679c */\n.md-top:hover {\n  background-color: var(--md-primary-fg-color--dark);\n  transform: translateY(-2px);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4242","title":"4.2.4.2 \u6eda\u52a8\u884c\u4e3a","text":"<p>\u81ea\u5b9a\u4e49\u6eda\u52a8\u884c\u4e3a\uff1a</p> JavaScript<pre><code>// docs/javascripts/scroll.js\n\ndocument.addEventListener('DOMContentLoaded', function() {\n  const topButton = document.querySelector('.md-top');\n\n  // \u5e73\u6ed1\u6eda\u52a8\n  if (topButton) {\n    topButton.addEventListener('click', (e) =&gt; {\n      e.preventDefault();\n      window.scrollTo({\n        top: 0,\n        behavior: 'smooth'\n      });\n    });\n  }\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4243","title":"4.2.4.3 \u663e\u793a\u63a7\u5236","text":"<p>\u914d\u7f6e\u663e\u793a\u903b\u8f91\uff1a</p> JavaScript<pre><code>// \u63a7\u5236\u6309\u94ae\u663e\u793a\nwindow.addEventListener('scroll', () =&gt; {\n  const topButton = document.querySelector('.md-top');\n  if (topButton) {\n    if (window.scrollY &gt; 100) {\n      topButton.classList.add('md-top--show');\n    } else {\n      topButton.classList.remove('md-top--show');\n    }\n  }\n});\n</code></pre> <p>\u6837\u5f0f\u63a7\u5236\uff1a</p> CSS<pre><code>/* \u6309\u94ae\u663e\u793a\u9690\u85cf */\n.md-top {\n  opacity: 0;\n  visibility: hidden;\n  transition: opacity 0.2s ease, visibility 0.2s ease;\n}\n\n.md-top--show {\n  opacity: 1;\n  visibility: visible;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#425","title":"4.2.5 \u5b8c\u6574\u914d\u7f6e\u793a\u4f8b","text":"YAML<pre><code># mkdocs.yml\ntheme:\n  name: material\n  features:\n    # \u5bfc\u822a\u529f\u80fd\n    - navigation.tabs\n    - navigation.tabs.sticky\n    - navigation.sections\n    - navigation.expand\n    - navigation.indexes\n    - navigation.instant\n    - navigation.tracking\n    - navigation.sticky\n    - header.autohide\n\n    # \u76ee\u5f55\u529f\u80fd\n    - toc.integrate\n    - toc.follow\n\n    # \u8fd4\u56de\u9876\u90e8\n    - navigation.top\n\n# Markdown \u6269\u5c55\nmarkdown_extensions:\n  - toc:\n      permalink: true\n      toc_depth: 3\n      title: \u76ee\u5f55\n      slugify: !!python/object/apply:pymdownx.slugs.slugify\n        kwds: {case: lower}\n\n# \u989d\u5916\u6837\u5f0f\u548c\u811a\u672c\nextra_css:\n  - stylesheets/extra.css\n\nextra_javascript:\n  - javascripts/tabs.js\n  - javascripts/scroll.js\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#43","title":"4.3 \u641c\u7d22\u529f\u80fd","text":""},{"location":"Tools/Blog/Mkdocs_Material/#431","title":"4.3.1 \u641c\u7d22\u5f15\u64ce\u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4311","title":"4.3.1.1 \u641c\u7d22\u7b97\u6cd5","text":"<p>\u57fa\u7840\u641c\u7d22\u914d\u7f6e\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      separator: '[\\\\s\\\\-\\\\.]+'   # \u5206\u8bcd\u5206\u9694\u7b26\n      min_search_length: 2        # \u6700\u5c0f\u641c\u7d22\u957f\u5ea6\n      lang:\n        - en\n        - zh\n      prebuild_index: true        # \u9884\u6784\u5efa\u7d22\u5f15\n</code></pre> <p>\u9ad8\u7ea7\u641c\u7d22\u9009\u9879\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      separator: '[\\\\s\\\\-\\\\.]+\\\\s*'\n      min_search_length: 2\n      prebuild_index: python\n      indexing:\n        full_sections: true       # \u7d22\u5f15\u5b8c\u6574\u7ae0\u8282\n        headings: true           # \u7d22\u5f15\u6807\u9898\n        content: true           # \u7d22\u5f15\u5185\u5bb9\n        tags: true             # \u7d22\u5f15\u6807\u7b7e\n      scoring:\n        title_boost: 10        # \u6807\u9898\u6743\u91cd\n        heading_boost: 5       # \u6807\u9898\u6743\u91cd\n        content_boost: 1       # \u5185\u5bb9\u6743\u91cd\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4312","title":"4.3.1.2 \u7d22\u5f15\u914d\u7f6e","text":"<p>\u81ea\u5b9a\u4e49\u7d22\u5f15\u8bbe\u7f6e\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      indexing:\n        full_sections: true\n        headings: true\n        content: true\n        tags: true\n        attachments: true          # \u7d22\u5f15\u9644\u4ef6\n        attachments_types:         # \u9644\u4ef6\u7c7b\u578b\n          - .pdf\n          - .doc\n          - .docx\n        attachments_max_size: 2048 # \u6700\u5927\u5927\u5c0f(KB)\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4313","title":"4.3.1.3 \u641c\u7d22\u8303\u56f4","text":"<p>\u914d\u7f6e\u641c\u7d22\u8303\u56f4\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      # \u5305\u542b\u7684\u6587\u4ef6\n      include:\n        - \"*.md\"\n        - \"*.markdown\"\n\n      # \u6392\u9664\u7684\u6587\u4ef6\n      exclude:\n        - drafts/*\n        - private/*\n\n      # \u5904\u7406\u7279\u5b9a\u8def\u5f84\n      ignore:\n        - 404.md\n        - index.md\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#432","title":"4.3.2 \u641c\u7d22\u63d0\u793a","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4321","title":"4.3.2.1 \u5feb\u6377\u952e\u8bbe\u7f6e","text":"<p>\u914d\u7f6e\u641c\u7d22\u5feb\u6377\u952e\uff1a</p> YAML<pre><code>theme:\n  keyboard:\n    search: s, /        # \u4f7f\u7528 's' \u6216 '/' \u89e6\u53d1\u641c\u7d22\n</code></pre> <p>\u81ea\u5b9a\u4e49\u5feb\u6377\u952e\u5904\u7406\uff1a</p> JavaScript<pre><code>// docs/javascripts/search.js\n\ndocument.addEventListener('keydown', function(e) {\n  // \u81ea\u5b9a\u4e49\u5feb\u6377\u952e\u903b\u8f91\n  if ((e.key === 's' || e.key === '/') &amp;&amp; !e.ctrlKey &amp;&amp; !e.altKey &amp;&amp; !e.metaKey) {\n    e.preventDefault();\n    const search = document.querySelector('.md-search__input');\n    if (search) {\n      search.focus();\n    }\n  }\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4322","title":"4.3.2.2 \u63d0\u793a\u6587\u672c","text":"<p>\u81ea\u5b9a\u4e49\u641c\u7d22\u63d0\u793a\uff1a</p> YAML<pre><code>theme:\n  language: zh         # \u4f7f\u7528\u4e2d\u6587\u754c\u9762\n\nextra:\n  search:\n    language: zh\n    text:\n      placeholder: \u641c\u7d22\u6587\u6863...\n      no_results: \u6ca1\u6709\u627e\u5230\u76f8\u5173\u7ed3\u679c\n      searching: \u6b63\u5728\u641c\u7d22...\n</code></pre> <p>\u81ea\u5b9a\u4e49\u63d0\u793a\u6837\u5f0f\uff1a</p> CSS<pre><code>/* docs/stylesheets/search.css */\n\n/* \u641c\u7d22\u6846\u63d0\u793a\u6587\u672c */\n.md-search__input::placeholder {\n  color: var(--md-default-fg-color--lighter);\n}\n\n/* \u65e0\u7ed3\u679c\u63d0\u793a */\n.md-search-result__meta {\n  color: var(--md-default-fg-color--light);\n  font-size: .8rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4323","title":"4.3.2.3 \u8f93\u5165\u5efa\u8bae","text":"<p>\u914d\u7f6e\u641c\u7d22\u5efa\u8bae\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      suggestions: true          # \u542f\u7528\u641c\u7d22\u5efa\u8bae\n      suggestions_min_length: 2  # \u6700\u5c0f\u5efa\u8bae\u957f\u5ea6\n</code></pre> <p>\u81ea\u5b9a\u4e49\u5efa\u8bae\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u641c\u7d22\u5efa\u8bae\u6837\u5f0f */\n.md-search-result__item {\n  padding: .4rem .8rem;\n  transition: background .2s ease;\n}\n\n.md-search-result__item:hover {\n  background-color: var(--md-code-bg-color);\n}\n\n/* \u5efa\u8bae\u9879\u56fe\u6807 */\n.md-search-result__icon {\n  color: var(--md-default-fg-color--lighter);\n  margin-right: .4rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#433","title":"4.3.3 \u641c\u7d22\u9ad8\u4eae","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4331","title":"4.3.3.1 \u9ad8\u4eae\u6837\u5f0f","text":"<p>\u914d\u7f6e\u641c\u7d22\u9ad8\u4eae\uff1a</p> YAML<pre><code>theme:\n  features:\n    - search.highlight      # \u542f\u7528\u641c\u7d22\u9ad8\u4eae\n    - search.share         # \u542f\u7528\u641c\u7d22\u5206\u4eab\n    - search.suggest       # \u542f\u7528\u641c\u7d22\u5efa\u8bae\n</code></pre> <p>\u81ea\u5b9a\u4e49\u9ad8\u4eae\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u641c\u7d22\u7ed3\u679c\u9ad8\u4eae */\n.md-search-result__item mark {\n  background-color: var(--md-accent-fg-color--transparent);\n  color: var(--md-accent-fg-color);\n  padding: 0 .2em;\n  border-radius: .1em;\n}\n\n/* \u6eda\u52a8\u6761\u6837\u5f0f */\n.md-search-result__scrollwrap::-webkit-scrollbar {\n  width: 4px;\n  height: 4px;\n}\n\n.md-search-result__scrollwrap::-webkit-scrollbar-thumb {\n  background-color: var(--md-default-fg-color--lighter);\n  border-radius: 2px;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4332","title":"4.3.3.2 \u5339\u914d\u89c4\u5219","text":"<p>\u914d\u7f6e\u641c\u7d22\u5339\u914d\u89c4\u5219\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      # \u6587\u672c\u5339\u914d\u914d\u7f6e\n      tokenizer: '[\\s\\-\\.]+'   # \u5206\u8bcd\u89c4\u5219\n      min_search_length: 2     # \u6700\u5c0f\u641c\u7d22\u957f\u5ea6\n\n      # \u6a21\u7cca\u5339\u914d\u8bbe\u7f6e\n      fuzzy: false            # \u7981\u7528\u6a21\u7cca\u5339\u914d\n\n      # \u5339\u914d\u6743\u91cd\n      boost: \n        title: 10            # \u6807\u9898\u6743\u91cd\n        text: 1              # \u6587\u672c\u6743\u91cd\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4333","title":"4.3.3.3 \u81ea\u5b9a\u4e49\u9ad8\u4eae","text":"<p>\u5b9e\u73b0\u81ea\u5b9a\u4e49\u9ad8\u4eae\u903b\u8f91\uff1a</p> JavaScript<pre><code>// docs/javascripts/search-highlight.js\n\ndocument.addEventListener('DOMContentLoaded', function() {\n  // \u83b7\u53d6\u641c\u7d22\u7ed3\u679c\u5bb9\u5668\n  const searchResults = document.querySelector('.md-search-result');\n\n  if (searchResults) {\n    // \u76d1\u542c\u641c\u7d22\u7ed3\u679c\u53d8\u5316\n    const observer = new MutationObserver(mutations =&gt; {\n      mutations.forEach(mutation =&gt; {\n        if (mutation.type === 'childList') {\n          // \u5904\u7406\u65b0\u6dfb\u52a0\u7684\u641c\u7d22\u7ed3\u679c\n          const newResults = mutation.addedNodes;\n          newResults.forEach(node =&gt; {\n            if (node.nodeType === 1) {  // \u5143\u7d20\u8282\u70b9\n              customHighlight(node);\n            }\n          });\n        }\n      });\n    });\n\n    // \u542f\u52a8\u89c2\u5bdf\n    observer.observe(searchResults, {\n      childList: true,\n      subtree: true\n    });\n  }\n});\n\nfunction customHighlight(node) {\n  // \u81ea\u5b9a\u4e49\u9ad8\u4eae\u903b\u8f91\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#434","title":"4.3.4 \u641c\u7d22\u8bed\u8a00","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4341","title":"4.3.4.1 \u4e2d\u6587\u5206\u8bcd","text":"<p>\u914d\u7f6e\u4e2d\u6587\u5206\u8bcd\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      lang:\n        - en\n        - zh\n      separator: '[\\s\\-\\.,\\!\\/\\?\\u2000-\\u206F\\u3000-\\u303F\\u3040-\\u309F\\u30A0-\\u30FF\\u3100-\\u312F\\u3200-\\u32FF\\u3400-\\u4DBF\\u4E00-\\u9FFF]+'\n</code></pre> <p>\u4e2d\u6587\u641c\u7d22\u4f18\u5316\uff1a</p> JavaScript<pre><code>// docs/javascripts/chinese-search.js\n\nfunction chineseSegment(text) {\n  // \u7b80\u5355\u7684\u4e2d\u6587\u5206\u8bcd\u903b\u8f91\n  return text.replace(/[\\u4e00-\\u9fa5]/g, function(char) {\n    return char + ' ';\n  });\n}\n\n// \u6dfb\u52a0\u5230\u641c\u7d22\u5904\u7406\u6d41\u7a0b\ndocument.addEventListener('DOMContentLoaded', function() {\n  const searchInput = document.querySelector('.md-search__input');\n  if (searchInput) {\n    searchInput.addEventListener('input', function(e) {\n      const value = e.target.value;\n      if (/[\\u4e00-\\u9fa5]/.test(value)) {\n        // \u5904\u7406\u4e2d\u6587\u8f93\u5165\n        const segmented = chineseSegment(value);\n        // TODO: \u4f7f\u7528\u5206\u8bcd\u7ed3\u679c\u8fdb\u884c\u641c\u7d22\n      }\n    });\n  }\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4342","title":"4.3.4.2 \u591a\u8bed\u8a00\u652f\u6301","text":"<p>\u914d\u7f6e\u591a\u8bed\u8a00\u641c\u7d22\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      lang:\n        - en\n        - zh\n        - ja\n      # \u8bed\u8a00\u7279\u5b9a\u7684\u5206\u8bcd\u89c4\u5219\n      separator:\n        en: '[\\\\s\\\\-\\\\.]+'\n        zh: '[\\u4e00-\\u9fa5]'\n        ja: '[\\u3040-\\u309F\\u30A0-\\u30FF]+'\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4343","title":"4.3.4.3 \u505c\u7528\u8bcd\u914d\u7f6e","text":"<p>\u914d\u7f6e\u505c\u7528\u8bcd\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      stopwords: \n        en:\n          - a\n          - an\n          - the\n          - in\n          - on\n          - at\n        zh:\n          - \u7684\n          - \u4e86\n          - \u548c\n          - \u4e0e\n          - \u6216\n</code></pre> <p>\u81ea\u5b9a\u4e49\u505c\u7528\u8bcd\u5904\u7406\uff1a</p> JavaScript<pre><code>// docs/javascripts/stopwords.js\n\nconst stopwords = {\n  en: ['a', 'an', 'the', 'in', 'on', 'at'],\n  zh: ['\u7684', '\u4e86', '\u548c', '\u4e0e', '\u6216'],\n};\n\nfunction removeStopwords(text, lang) {\n  if (!stopwords[lang]) return text;\n\n  const words = text.split(/\\s+/);\n  return words\n    .filter(word =&gt; !stopwords[lang].includes(word))\n    .join(' ');\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#435","title":"4.3.5 \u5b8c\u6574\u914d\u7f6e\u793a\u4f8b","text":"YAML<pre><code># mkdocs.yml\n\nplugins:\n  - search:\n      lang:\n        - en\n        - zh\n      separator: '[\\s\\-\\.,\\!\\/\\?\\u2000-\\u206F\\u3000-\\u303F]+'\n      prebuild_index: python\n      indexing:\n        full_sections: true\n        headings: true\n        content: true\n        tags: true\n      scoring:\n        title_boost: 10\n        heading_boost: 5\n        content_boost: 1\n\ntheme:\n  features:\n    - search.highlight\n    - search.share\n    - search.suggest\n\nextra:\n  search:\n    language: zh\n    text:\n      placeholder: \u641c\u7d22\u6587\u6863...\n      no_results: \u6ca1\u6709\u627e\u5230\u76f8\u5173\u7ed3\u679c\n      searching: \u6b63\u5728\u641c\u7d22...\n\nextra_javascript:\n  - javascripts/search.js\n  - javascripts/search-highlight.js\n  - javascripts/chinese-search.js\n  - javascripts/stopwords.js\n\nextra_css:\n  - stylesheets/search.css\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#44","title":"4.4 \u4ee3\u7801\u5757\u8bbe\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#441","title":"4.4.1 \u8bed\u6cd5\u9ad8\u4eae","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4411","title":"4.4.1.1 \u9ad8\u4eae\u4e3b\u9898","text":"<p>\u57fa\u7840\u9ad8\u4eae\u914d\u7f6e\uff1a</p> YAML<pre><code>theme:\n  name: material\n  features:\n    - content.code.annotate # \u542f\u7528\u4ee3\u7801\u6ce8\u91ca\n    - content.code.copy    # \u542f\u7528\u4ee3\u7801\u590d\u5236\n\nmarkdown_extensions:\n  - pymdownx.highlight:\n      anchor_linenums: true\n      line_spans: __span\n      pygments_lang_class: true\n      use_pygments: true\n      auto_title: true # \u663e\u793a\u8bed\u8a00\u540d\u79f0\n      linenums: true  # \u663e\u793a\u884c\u53f7\n</code></pre> <p>\u81ea\u5b9a\u4e49\u9ad8\u4eae\u4e3b\u9898\uff1a</p> YAML<pre><code>theme:\n  palette:\n    # \u4eae\u8272\u4e3b\u9898\n    - scheme: default\n      primary: indigo\n      accent: indigo\n      toggle:\n        icon: material/brightness-7\n        name: \u5207\u6362\u81f3\u6697\u8272\u4e3b\u9898\n      pygments_style: github-light\n\n    # \u6697\u8272\u4e3b\u9898\n    - scheme: slate\n      primary: indigo\n      accent: indigo\n      toggle:\n        icon: material/brightness-4\n        name: \u5207\u6362\u81f3\u4eae\u8272\u4e3b\u9898\n      pygments_style: monokai\n</code></pre> <p>\u81ea\u5b9a\u4e49\u4ee3\u7801\u5757\u6837\u5f0f\uff1a</p> CSS<pre><code>/* docs/stylesheets/code.css */\n\n/* \u4ee3\u7801\u5757\u5bb9\u5668 */\n.highlight {\n  background-color: var(--md-code-bg-color);\n  border-radius: 4px;\n  padding: 0.5rem;\n  margin: 1rem 0;\n}\n\n/* \u4ee3\u7801\u884c */\n.highlight .code-line {\n  display: block;\n  padding: 0 1rem;\n  border-left: 2px solid transparent;\n}\n\n/* \u9ad8\u4eae\u884c */\n.highlight .code-line.focused {\n  background-color: var(--md-code-hl-color);\n  border-left: 2px solid var(--md-accent-fg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4412","title":"4.4.1.2 \u8bed\u8a00\u652f\u6301","text":"<p>\u914d\u7f6e\u652f\u6301\u7684\u8bed\u8a00\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.highlight:\n      extend_pygments_lang:\n        # \u81ea\u5b9a\u4e49\u8bed\u8a00\u914d\u7f6e\n        typescript:\n          name: TypeScript\n          aliases: [ts]\n        jsonc:\n          name: JSON with Comments\n          aliases: [json5]\n</code></pre> <p>\u8bed\u8a00\u7279\u5b9a\u914d\u7f6e\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.highlight:\n      language_prefix: language-  # \u8bed\u8a00\u524d\u7f00\n      css_class: highlight       # CSS\u7c7b\u540d\n      code_attr_on_pre: false    # \u5c5e\u6027\u4f4d\u7f6e\n      extend_pygments_lang:      # \u8bed\u8a00\u6269\u5c55\n        flow:\n          name: Flow\n          aliases: [flowtype]\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4413","title":"4.4.1.3 \u81ea\u5b9a\u4e49\u9ad8\u4eae","text":"<p>\u81ea\u5b9a\u4e49\u8bed\u6cd5\u9ad8\u4eae\u89c4\u5219\uff1a</p> Python<pre><code># docs/custom_lexer.py\nfrom pygments.lexer import RegexLexer, words\nfrom pygments.token import *\n\nclass CustomLexer(RegexLexer):\n    name = 'CustomLanguage'\n    aliases = ['custom']\n    filenames = ['*.custom']\n\n    tokens = {\n        'root': [\n            (r'//.*$', Comment.Single),\n            (words(('if', 'else', 'while'), suffix=r'\\b'), Keyword),\n            (r'\"[^\"]*\"', String),\n            (r'\\d+', Number),\n            (r'[a-zA-Z_]\\w*', Name),\n            (r'[^\\w\\s]', Punctuation),\n        ]\n    }\n</code></pre> <p>\u5728 <code>mkdocs.yml</code> \u4e2d\u4f7f\u7528\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.highlight:\n      use_pygments: true\n      extend_pygments_lang:\n        custom:\n          name: CustomLanguage\n          aliases: [custom]\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#442","title":"4.4.2 \u884c\u53f7\u663e\u793a","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4421","title":"4.4.2.1 \u884c\u53f7\u6837\u5f0f","text":"<p>\u914d\u7f6e\u884c\u53f7\u663e\u793a\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.highlight:\n      linenums: true\n      linenums_style: table  # \u8868\u683c\u5f0f\u884c\u53f7\n      anchor_linenums: true  # \u884c\u53f7\u94fe\u63a5\n</code></pre> <p>\u81ea\u5b9a\u4e49\u884c\u53f7\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u884c\u53f7\u5bb9\u5668 */\n.highlighttable {\n  width: 100%;\n  display: table;\n}\n\n/* \u884c\u53f7\u5217 */\n.linenos {\n  color: var(--md-default-fg-color--lighter);\n  text-align: right;\n  padding-right: 1rem;\n  user-select: none;\n}\n\n/* \u4ee3\u7801\u5217 */\n.code {\n  padding-left: 1rem;\n  border-left: 1px solid var(--md-default-fg-color--lightest);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4422","title":"4.4.2.2 \u8d77\u59cb\u884c\u8bbe\u7f6e","text":"<p>\u8bbe\u7f6e\u4ee3\u7801\u5757\u8d77\u59cb\u884c\u53f7\uff1a</p> Markdown<pre><code>```python linenums=\"10\"\ndef hello_world():\n    print(\"Hello, World!\")\n```\n</code></pre> <p>\u914d\u7f6e\u9ed8\u8ba4\u8d77\u59cb\u884c\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.highlight:\n      linenums: true\n      linenums_start: 1  # \u9ed8\u8ba4\u8d77\u59cb\u884c\u53f7\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4423","title":"4.4.2.3 \u884c\u53f7\u94fe\u63a5","text":"<p>\u542f\u7528\u884c\u53f7\u94fe\u63a5\u529f\u80fd\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.highlight:\n      anchor_linenums: true     # \u542f\u7528\u884c\u53f7\u94fe\u63a5\n      line_anchors: L           # \u884c\u53f7\u94fe\u63a5\u524d\u7f00\n</code></pre> <p>\u81ea\u5b9a\u4e49\u94fe\u63a5\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u884c\u53f7\u94fe\u63a5 */\n.md-typeset .highlight [data-linenos]:before {\n  content: attr(data-linenos);\n  color: var(--md-default-fg-color--lighter);\n  padding-right: 1rem;\n}\n\n/* \u94fe\u63a5\u60ac\u505c\u6548\u679c */\n.md-typeset .highlight [data-linenos]:hover:before {\n  color: var(--md-accent-fg-color);\n  cursor: pointer;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#443","title":"4.4.3 \u590d\u5236\u6309\u94ae","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4431","title":"4.4.3.1 \u6309\u94ae\u6837\u5f0f","text":"<p>\u914d\u7f6e\u590d\u5236\u6309\u94ae\uff1a</p> YAML<pre><code>theme:\n  features:\n    - content.code.copy     # \u542f\u7528\u4ee3\u7801\u590d\u5236\n</code></pre> <p>\u81ea\u5b9a\u4e49\u590d\u5236\u6309\u94ae\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u590d\u5236\u6309\u94ae\u5bb9\u5668 */\n.md-clipboard {\n  position: absolute;\n  top: 0.5rem;\n  right: 0.5rem;\n  padding: 0.4rem;\n  color: var(--md-default-fg-color--lighter);\n  background-color: transparent;\n  border: none;\n  border-radius: 4px;\n  cursor: pointer;\n  transition: all 0.2s ease;\n}\n\n/* \u60ac\u505c\u6548\u679c */\n.md-clipboard:hover {\n  color: var(--md-accent-fg-color);\n  background-color: var(--md-code-bg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4432","title":"4.4.3.2 \u590d\u5236\u884c\u4e3a","text":"<p>\u81ea\u5b9a\u4e49\u590d\u5236\u529f\u80fd\uff1a</p> JavaScript<pre><code>// docs/javascripts/clipboard.js\n\ndocument.addEventListener('DOMContentLoaded', () =&gt; {\n  // \u83b7\u53d6\u6240\u6709\u4ee3\u7801\u5757\n  const codeBlocks = document.querySelectorAll('pre code');\n\n  codeBlocks.forEach(block =&gt; {\n    // \u521b\u5efa\u590d\u5236\u6309\u94ae\n    const button = document.createElement('button');\n    button.className = 'md-clipboard';\n    button.title = '\u590d\u5236\u5230\u526a\u8d34\u677f';\n\n    // \u6dfb\u52a0\u590d\u5236\u56fe\u6807\n    button.innerHTML = '&lt;span class=\"md-clipboard__icon\"&gt;&lt;/span&gt;';\n\n    // \u6dfb\u52a0\u70b9\u51fb\u4e8b\u4ef6\n    button.addEventListener('click', async () =&gt; {\n      try {\n        // \u590d\u5236\u4ee3\u7801\n        await navigator.clipboard.writeText(block.textContent);\n\n        // \u663e\u793a\u6210\u529f\u63d0\u793a\n        button.classList.add('md-clipboard--success');\n        setTimeout(() =&gt; {\n          button.classList.remove('md-clipboard--success');\n        }, 2000);\n      } catch (err) {\n        console.error('\u590d\u5236\u5931\u8d25:', err);\n      }\n    });\n\n    // \u5c06\u6309\u94ae\u6dfb\u52a0\u5230\u4ee3\u7801\u5757\n    block.parentNode.insertBefore(button, block);\n  });\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4433","title":"4.4.3.3 \u63d0\u793a\u914d\u7f6e","text":"<p>\u914d\u7f6e\u590d\u5236\u63d0\u793a\uff1a</p> YAML<pre><code>theme:\n  language: zh          # \u4f7f\u7528\u4e2d\u6587\u754c\u9762\n\nextra:\n  clipboard:\n    copy: \u590d\u5236\n    copied: \u5df2\u590d\u5236\uff01\n    error: \u590d\u5236\u5931\u8d25\n</code></pre> <p>\u81ea\u5b9a\u4e49\u63d0\u793a\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u590d\u5236\u63d0\u793a */\n.md-clipboard__tooltip {\n  position: absolute;\n  top: -2rem;\n  right: 0;\n  padding: 0.4rem 0.8rem;\n  color: var(--md-default-bg-color);\n  background-color: var(--md-default-fg-color);\n  border-radius: 4px;\n  font-size: 0.8rem;\n  opacity: 0;\n  transform: translateY(0.4rem);\n  transition: all 0.2s ease;\n}\n\n/* \u663e\u793a\u63d0\u793a */\n.md-clipboard:hover .md-clipboard__tooltip {\n  opacity: 1;\n  transform: translateY(0);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#444","title":"4.4.4 \u6ce8\u91ca\u529f\u80fd","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4441","title":"4.4.4.1 \u884c\u5185\u6ce8\u91ca","text":"<p>\u4f7f\u7528\u884c\u5185\u6ce8\u91ca\uff1a</p> Markdown<pre><code>```python\ndef hello():\n    print(\"Hello\")  # (1)\n    return True     # (2)\n```\n\n1. \u6253\u5370\u95ee\u5019\u4fe1\u606f\n2. \u8fd4\u56de\u6210\u529f\u72b6\u6001\n</code></pre> <p>\u914d\u7f6e\u6ce8\u91ca\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u884c\u5185\u6ce8\u91ca\u6807\u8bb0 */\n.md-annotation {\n  color: var(--md-accent-fg-color);\n  font-size: 0.8em;\n  vertical-align: super;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4442","title":"4.4.4.2 \u5757\u7ea7\u6ce8\u91ca","text":"<p>\u4f7f\u7528\u5757\u7ea7\u6ce8\u91ca\uff1a</p> Markdown<pre><code>```python\ndef process_data():\n    # (1)!\n    data = load_data()\n\n    # (2)!\n    result = transform(data)\n\n    return result\n```\n\n1. \u4ece\u6570\u636e\u6e90\u52a0\u8f7d\u6570\u636e\n   \u8fd9\u91cc\u53ef\u4ee5\u662f\u591a\u884c\n   \u6ce8\u91ca\u8bf4\u660e\n\n2. \u5bf9\u6570\u636e\u8fdb\u884c\u8f6c\u6362\u5904\u7406\n   \u5305\u542b\u6e05\u6d17\u548c\u683c\u5f0f\u5316\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4443","title":"4.4.4.3 \u6ce8\u91ca\u6837\u5f0f","text":"<p>\u81ea\u5b9a\u4e49\u6ce8\u91ca\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u6ce8\u91ca\u5bb9\u5668 */\n.md-annotation-wrapper {\n  margin: 1rem 0;\n  padding: 1rem;\n  background-color: var(--md-code-bg-color);\n  border-left: 4px solid var(--md-accent-fg-color);\n  border-radius: 4px;\n}\n\n/* \u6ce8\u91ca\u6807\u8bb0 */\n.md-annotation-marker {\n  color: var(--md-accent-fg-color);\n  font-weight: bold;\n}\n\n/* \u6ce8\u91ca\u5185\u5bb9 */\n.md-annotation-content {\n  margin-top: 0.5rem;\n  color: var(--md-default-fg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#445","title":"4.4.5 \u5b8c\u6574\u914d\u7f6e\u793a\u4f8b","text":"YAML<pre><code># mkdocs.yml\n\ntheme:\n  name: material\n  features:\n    - content.code.annotate\n    - content.code.copy\n\nmarkdown_extensions:\n  - pymdownx.highlight:\n      anchor_linenums: true\n      line_spans: __span\n      pygments_lang_class: true\n      use_pygments: true\n      auto_title: true\n      linenums: true\n      linenums_style: table\n  - pymdownx.superfences\n  - pymdownx.inlinehilite\n\nextra:\n  clipboard:\n    copy: \u590d\u5236\n    copied: \u5df2\u590d\u5236\uff01\n    error: \u590d\u5236\u5931\u8d25\n\nextra_css:\n  - stylesheets/code.css\n\nextra_javascript:\n  - javascripts/clipboard.js\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#45","title":"4.5 \u5185\u5bb9\u589e\u5f3a","text":""},{"location":"Tools/Blog/Mkdocs_Material/#451","title":"4.5.1 \u6570\u5b66\u516c\u5f0f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4511-katex","title":"4.5.1.1 KaTeX \u914d\u7f6e","text":"<p>\u5b89\u88c5\u548c\u914d\u7f6e KaTeX\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.arithmatex:\n      generic: true\n\nextra_javascript:\n  - javascripts/katex.js \n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/katex.min.js  \n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/contrib/auto-render.min.js\n\nextra_css:\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/katex.min.css\n</code></pre> <p>\u521b\u5efa <code>docs/javascripts/katex.js</code> \uff1a</p> JavaScript<pre><code>document.addEventListener(\"DOMContentLoaded\", function() {\n  renderMathInElement(document.body, {\n    delimiters: [\n      {left: \"$$\", right: \"$$\", display: true},\n      {left: \"$\", right: \"$\", display: false},\n      {left: \"\\\\(\", right: \"\\\\)\", display: false},\n      {left: \"\\\\[\", right: \"\\\\]\", display: true}\n    ],\n    throwOnError: false\n  });\n});\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Markdown<pre><code>\u5185\u8054\u516c\u5f0f: $E = mc^2$\n\n\u5757\u7ea7\u516c\u5f0f\uff1a\n$$\n\\frac{n!}{k!(n-k)!} = \\binom{n}{k}\n$$\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4512-mathjax","title":"4.5.1.2 MathJax \u914d\u7f6e","text":"<p>\u914d\u7f6e MathJax\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.arithmatex:\n      generic: true\n\nextra_javascript:\n  - javascripts/mathjax.js\n  - https://polyfill.io/v3/polyfill.min.js?features=es6\n  - https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js\n</code></pre> <p>\u521b\u5efa <code>docs/javascripts/mathjax.js</code> \uff1a</p> JavaScript<pre><code>window.MathJax = {\n  tex: {\n    inlineMath: [[\"\\\\(\", \"\\\\)\"]],\n    displayMath: [[\"\\\\[\", \"\\\\]\"]],\n    processEscapes: true,\n    processEnvironments: true\n  },\n  options: {\n    ignoreHtmlClass: \".*|\",\n    processHtmlClass: \"arithmatex\"\n  }\n};\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4513","title":"4.5.1.3 \u516c\u5f0f\u7f16\u53f7","text":"<p>\u542f\u7528\u516c\u5f0f\u7f16\u53f7\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.arithmatex:\n      generic: true\n      numbering: true\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Markdown<pre><code>$$\n\\begin{equation}\nE = mc^2 \\label{eq:einstein}\n\\end{equation}\n$$\n\n\u5f15\u7528\u516c\u5f0f $\\eqref{eq:einstein}$\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#452","title":"4.5.2 \u56fe\u8868\u652f\u6301","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4521-mermaid","title":"4.5.2.1 Mermaid \u96c6\u6210","text":"<p>\u914d\u7f6e Mermaid\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.superfences:\n      custom_fences:\n        - name: mermaid\n          class: mermaid\n          format: !!python/name:pymdownx.superfences.fence_code_format\n\nextra_javascript:\n  - https://unpkg.com/mermaid@9/dist/mermaid.min.js\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Text Only<pre><code>graph TD\n    A[\u5f00\u59cb] --&gt; B{\u5224\u65ad}\n    B --&gt;|Yes| C[\u5904\u7406]\n    B --&gt;|No| D[\u7ed3\u675f]\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4522-plantuml","title":"4.5.2.2 PlantUML \u652f\u6301","text":"<p>\u914d\u7f6e PlantUML\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.superfences:\n      custom_fences:\n        - name: plantuml\n          class: plantuml\n          format: !!python/name:pymdownx.superfences.fence_code_format\n\nextra_javascript:\n  - https://cdn.jsdelivr.net/npm/plantuml-encoder@1.4.0/dist/plantuml-encoder.min.js\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Text Only<pre><code>@startuml\nAlice -&gt; Bob: \u8bf7\u6c42\nBob --&gt; Alice: \u54cd\u5e94\n@enduml\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4523","title":"4.5.2.3 \u81ea\u5b9a\u4e49\u56fe\u8868","text":"<p>\u521b\u5efa\u81ea\u5b9a\u4e49\u56fe\u8868\u7ec4\u4ef6\uff1a</p> JavaScript<pre><code>// docs/javascripts/charts.js\nimport Chart from 'chart.js/auto';\n\ndocument.addEventListener('DOMContentLoaded', function() {\n  const chartElements = document.querySelectorAll('.custom-chart');\n\n  chartElements.forEach(element =&gt; {\n    const ctx = element.getContext('2d');\n    const data = JSON.parse(element.dataset.chartData);\n\n    new Chart(ctx, {\n      type: data.type,\n      data: data.data,\n      options: data.options\n    });\n  });\n});\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> HTML<pre><code>&lt;canvas class=\"custom-chart\" data-chart-data='{\n  \"type\": \"line\",\n  \"data\": {\n    \"labels\": [\"1\u6708\", \"2\u6708\", \"3\u6708\"],\n    \"datasets\": [{\n      \"label\": \"\u6570\u636e\",\n      \"data\": [10, 20, 30]\n    }]\n  }\n}'&gt;&lt;/canvas&gt;\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#453","title":"4.5.3 \u4efb\u52a1\u5217\u8868","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4531","title":"4.5.3.1 \u590d\u9009\u6846\u6837\u5f0f","text":"<p>\u914d\u7f6e\u4efb\u52a1\u5217\u8868\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.tasklist:\n      custom_checkbox: true\n      clickable_checkbox: true\n</code></pre> <p>\u81ea\u5b9a\u4e49\u6837\u5f0f\uff1a</p> CSS<pre><code>/* docs/stylesheets/tasklist.css */\n\n.task-list-item {\n  list-style-type: none;\n  margin-left: -1.6rem;\n}\n\n.task-list-control {\n  position: relative;\n  display: inline-block;\n  width: 1.2rem;\n  height: 1.2rem;\n  margin-right: 0.5rem;\n  vertical-align: middle;\n}\n\n.task-list-indicator {\n  position: absolute;\n  top: 0;\n  left: 0;\n  width: 100%;\n  height: 100%;\n  background-color: var(--md-default-fg-color--lighter);\n  border-radius: 2px;\n  transition: all 0.2s ease;\n}\n\n.task-list-indicator:checked {\n  background-color: var(--md-accent-fg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4532","title":"4.5.3.2 \u4ea4\u4e92\u884c\u4e3a","text":"<p>\u6dfb\u52a0\u4ea4\u4e92\u529f\u80fd\uff1a</p> JavaScript<pre><code>// docs/javascripts/tasklist.js\n\ndocument.addEventListener('DOMContentLoaded', function() {\n  const taskItems = document.querySelectorAll('.task-list-item input[type=\"checkbox\"]');\n\n  taskItems.forEach(item =&gt; {\n    item.addEventListener('change', function() {\n      // \u4fdd\u5b58\u72b6\u6001\n      localStorage.setItem(\n        `task-${this.closest('.task-list-item').id}`,\n        this.checked\n      );\n\n      // \u66f4\u65b0\u6837\u5f0f\n      if (this.checked) {\n        this.closest('.task-list-item').classList.add('completed');\n      } else {\n        this.closest('.task-list-item').classList.remove('completed');\n      }\n    });\n\n    // \u6062\u590d\u72b6\u6001\n    const saved = localStorage.getItem(`task-${item.closest('.task-list-item').id}`);\n    if (saved === 'true') {\n      item.checked = true;\n      item.closest('.task-list-item').classList.add('completed');\n    }\n  });\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4533","title":"4.5.3.3 \u72b6\u6001\u7ba1\u7406","text":"CSS<pre><code>/* \u4efb\u52a1\u72b6\u6001\u6837\u5f0f */\n.task-list-item.completed {\n  text-decoration: line-through;\n  color: var(--md-default-fg-color--light);\n}\n\n.task-list-item.pending {\n  font-weight: bold;\n}\n\n.task-list-item.in-progress {\n  color: var(--md-accent-fg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#454","title":"4.5.4 \u6807\u7b7e\u9875","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4541","title":"4.5.4.1 \u6807\u7b7e\u7ec4\u6837\u5f0f","text":"<p>\u914d\u7f6e\u6807\u7b7e\u9875\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.tabbed:\n      alternate_style: true \n</code></pre> <p>\u81ea\u5b9a\u4e49\u6837\u5f0f\uff1a</p> CSS<pre><code>/* docs/stylesheets/tabs.css */\n\n/* \u6807\u7b7e\u7ec4\u5bb9\u5668 */\n.tabbed-set {\n  border: 1px solid var(--md-default-fg-color--lightest);\n  border-radius: 4px;\n  margin: 1rem 0;\n}\n\n/* \u6807\u7b7e\u5217\u8868 */\n.tabbed-labels {\n  display: flex;\n  background-color: var(--md-code-bg-color);\n  border-bottom: 1px solid var(--md-default-fg-color--lightest);\n}\n\n/* \u5355\u4e2a\u6807\u7b7e */\n.tabbed-labels &gt; label {\n  padding: 0.8rem 1.2rem;\n  cursor: pointer;\n  transition: all 0.2s ease;\n}\n\n/* \u6fc0\u6d3b\u72b6\u6001 */\n.tabbed-labels &gt; label.tabbed-selected {\n  color: var(--md-accent-fg-color);\n  border-bottom: 2px solid var(--md-accent-fg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4542","title":"4.5.4.2 \u5207\u6362\u6548\u679c","text":"<p>\u6dfb\u52a0\u52a8\u753b\u6548\u679c\uff1a</p> CSS<pre><code>/* \u6807\u7b7e\u5185\u5bb9\u5207\u6362\u52a8\u753b */\n.tabbed-content {\n  padding: 1rem;\n  opacity: 0;\n  transform: translateY(10px);\n  transition: all 0.3s ease;\n}\n\n.tabbed-content.tabbed-selected {\n  opacity: 1;\n  transform: translateY(0);\n}\n</code></pre> <p>\u6807\u7b7e\u9875\u4ea4\u4e92\uff1a</p> JavaScript<pre><code>// docs/javascripts/tabs.js\n\ndocument.addEventListener('DOMContentLoaded', function() {\n  const tabSets = document.querySelectorAll('.tabbed-set');\n\n  tabSets.forEach(tabSet =&gt; {\n    const tabs = tabSet.querySelectorAll('.tabbed-labels &gt; label');\n    const contents = tabSet.querySelectorAll('.tabbed-content');\n\n    tabs.forEach((tab, index) =&gt; {\n      tab.addEventListener('click', () =&gt; {\n        // \u66f4\u65b0\u6807\u7b7e\u72b6\u6001\n        tabs.forEach(t =&gt; t.classList.remove('tabbed-selected'));\n        tab.classList.add('tabbed-selected');\n\n        // \u66f4\u65b0\u5185\u5bb9\u72b6\u6001\n        contents.forEach(c =&gt; c.classList.remove('tabbed-selected'));\n        contents[index].classList.add('tabbed-selected');\n      });\n    });\n  });\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4543","title":"4.5.4.3 \u54cd\u5e94\u5f0f\u8bbe\u8ba1","text":"<p>\u6dfb\u52a0\u54cd\u5e94\u5f0f\u652f\u6301\uff1a</p> CSS<pre><code>/* \u79fb\u52a8\u7aef\u9002\u914d */\n@media screen and (max-width: 76.1875em) {\n  .tabbed-labels {\n    flex-wrap: wrap;\n  }\n\n  .tabbed-labels &gt; label {\n    flex: 1 1 auto;\n    text-align: center;\n  }\n\n  .tabbed-content {\n    padding: 0.8rem;\n  }\n}\n\n/* \u5e73\u677f\u9002\u914d */\n@media screen and (min-width: 76.25em) {\n  .tabbed-set {\n    max-width: 80%;\n    margin: 1rem auto;\n  }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#455","title":"4.5.5 \u5b8c\u6574\u914d\u7f6e\u793a\u4f8b","text":"YAML<pre><code># mkdocs.yml\n\nmarkdown_extensions:\n  # \u6570\u5b66\u516c\u5f0f\n  - pymdownx.arithmatex:\n      generic: true\n\n  # \u56fe\u8868\u652f\u6301\n  - pymdownx.superfences:\n      custom_fences:\n        - name: mermaid\n          class: mermaid\n          format: !!python/name:pymdownx.superfences.fence_code_format\n        - name: plantuml\n          class: plantuml\n          format: !!python/name:pymdownx.superfences.fence_code_format\n\n  # \u4efb\u52a1\u5217\u8868\n  - pymdownx.tasklist:\n      custom_checkbox: true\n      clickable_checkbox: true\n\n  # \u6807\u7b7e\u9875\n  - pymdownx.tabbed:\n      alternate_style: true\n\nextra_javascript:\n  - javascripts/katex.js\n  - javascripts/mermaid.js\n  - javascripts/charts.js\n  - javascripts/tasklist.js\n  - javascripts/tabs.js\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/katex.min.js\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/contrib/auto-render.min.js\n  - https://unpkg.com/mermaid@9/dist/mermaid.min.js\n\nextra_css:\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/katex.min.css\n  - stylesheets/tasklist.css\n  - stylesheets/tabs.css\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5","title":"5 \u6837\u5f0f\u5b9a\u5236","text":""},{"location":"Tools/Blog/Mkdocs_Material/#51-css","title":"5.1 CSS \u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#511-css","title":"5.1.1 \u81ea\u5b9a\u4e49 CSS \u6587\u4ef6","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5111-css","title":"5.1.1.1 CSS \u6587\u4ef6\u7ec4\u7ec7","text":"<ol> <li>\u63a8\u8350\u7684\u76ee\u5f55\u7ed3\u6784\uff1a</li> </ol> Text Only<pre><code>docs/\n\u251c\u2500\u2500 stylesheets/\n\u2502   \u251c\u2500\u2500 base/\n\u2502   \u2502   \u251c\u2500\u2500 _variables.css    # CSS\u53d8\u91cf\u5b9a\u4e49\n\u2502   \u2502   \u251c\u2500\u2500 _typography.css   # \u6392\u7248\u6837\u5f0f\n\u2502   \u2502   \u2514\u2500\u2500 _colors.css       # \u989c\u8272\u5b9a\u4e49\n\u2502   \u251c\u2500\u2500 components/\n\u2502   \u2502   \u251c\u2500\u2500 _buttons.css      # \u6309\u94ae\u6837\u5f0f\n\u2502   \u2502   \u251c\u2500\u2500 _cards.css        # \u5361\u7247\u6837\u5f0f\n\u2502   \u2502   \u2514\u2500\u2500 _tables.css       # \u8868\u683c\u6837\u5f0f\n\u2502   \u251c\u2500\u2500 layouts/\n\u2502   \u2502   \u251c\u2500\u2500 _header.css       # \u5934\u90e8\u6837\u5f0f\n\u2502   \u2502   \u251c\u2500\u2500 _nav.css         # \u5bfc\u822a\u6837\u5f0f\n\u2502   \u2502   \u2514\u2500\u2500 _footer.css      # \u9875\u811a\u6837\u5f0f\n\u2502   \u2514\u2500\u2500 extra.css            # \u4e3b\u6837\u5f0f\u6587\u4ef6\n</code></pre> <ol> <li>\u5728 <code>mkdocs.yml</code> \u4e2d\u5f15\u5165\u6837\u5f0f\uff1a</li> </ol> YAML<pre><code>extra_css:\n  - stylesheets/extra.css\n</code></pre> <ol> <li>\u5728\u4e3b\u6837\u5f0f\u6587\u4ef6\u4e2d\u5bfc\u5165\u5176\u4ed6\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/extra.css */\n\n/* \u57fa\u7840\u6837\u5f0f */\n@import 'base/_variables.css';\n@import 'base/_typography.css';\n@import 'base/_colors.css';\n\n/* \u7ec4\u4ef6\u6837\u5f0f */\n@import 'components/_buttons.css';\n@import 'components/_cards.css';\n@import 'components/_tables.css';\n\n/* \u5e03\u5c40\u6837\u5f0f */\n@import 'layouts/_header.css';\n@import 'layouts/_nav.css';\n@import 'layouts/_footer.css';\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5112","title":"5.1.1.2 \u6837\u5f0f\u4f18\u5148\u7ea7","text":"<ol> <li>\u6837\u5f0f\u4f18\u5148\u7ea7\u89c4\u5219\uff1a</li> </ol> CSS<pre><code>/* 1. \u884c\u5185\u6837\u5f0f (1000) */\n&lt;div style=\"color: red;\"&gt;\n\n/* 2. ID \u9009\u62e9\u5668 (100) */\n#header { }\n\n/* 3. \u7c7b\u9009\u62e9\u5668\u3001\u5c5e\u6027\u9009\u62e9\u5668\u3001\u4f2a\u7c7b (10) */\n.nav-item { }\n[type=\"text\"] { }\n:hover { }\n\n/* 4. \u5143\u7d20\u9009\u62e9\u5668\u3001\u4f2a\u5143\u7d20 (1) */\ndiv { }\n::before { }\n</code></pre> <ol> <li>Material \u4e3b\u9898\u8986\u76d6\uff1a</li> </ol> CSS<pre><code>/* \u8986\u76d6\u4e3b\u9898\u6837\u5f0f */\n.md-header {\n  /* \u4f7f\u7528 !important \u614e\u91cd */\n  background-color: #2196f3 !important;\n}\n\n/* \u4f7f\u7528\u66f4\u5177\u4f53\u7684\u9009\u62e9\u5668 */\n.md-header[data-md-color-scheme=\"default\"] {\n  background-color: #2196f3;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5113-css","title":"5.1.1.3 CSS \u53d8\u91cf","text":"<ol> <li>\u5b9a\u4e49\u5168\u5c40\u53d8\u91cf\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/base/_variables.css */\n\n:root {\n  /* \u989c\u8272\u53d8\u91cf */\n  --primary-color: #2196f3;\n  --accent-color: #f50057;\n  --text-color: #333333;\n\n  /* \u5b57\u4f53\u53d8\u91cf */\n  --font-family: \"LXGW WenKai\", -apple-system, sans-serif;\n  --code-font: \"JetBrains Mono\", monospace;\n\n  /* \u95f4\u8ddd\u53d8\u91cf */\n  --spacing-unit: 8px;\n  --content-padding: calc(var(--spacing-unit) * 2);\n\n  /* \u9634\u5f71\u53d8\u91cf */\n  --shadow-sm: 0 1px 2px rgba(0,0,0,0.1);\n  --shadow-md: 0 2px 4px rgba(0,0,0,0.1);\n  --shadow-lg: 0 4px 8px rgba(0,0,0,0.1);\n}\n</code></pre> <ol> <li>\u4e3b\u9898\u53d8\u91cf\uff1a</li> </ol> CSS<pre><code>/* \u4eae\u8272\u4e3b\u9898 */\n[data-md-color-scheme=\"default\"] {\n  --md-primary-fg-color: var(--primary-color);\n  --md-accent-fg-color: var(--accent-color);\n  --md-typeset-color: var(--text-color);\n}\n\n/* \u6697\u8272\u4e3b\u9898 */\n[data-md-color-scheme=\"slate\"] {\n  --primary-color: #90caf9;\n  --accent-color: #ff4081;\n  --text-color: #ffffff;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#512","title":"5.1.2 \u5e38\u7528\u6837\u5f0f\u4fee\u6539","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5121","title":"5.1.2.1 \u5b57\u4f53\u8bbe\u7f6e","text":"<ol> <li>\u5b57\u4f53\u5b9a\u4e49\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/base/_typography.css */\n\n/* \u57fa\u7840\u5b57\u4f53\u8bbe\u7f6e */\nbody {\n  font-family: var(--font-family);\n  font-size: 16px;\n  line-height: 1.6;\n}\n\n/* \u4ee3\u7801\u5b57\u4f53 */\ncode, pre {\n  font-family: var(--code-font);\n  font-size: 0.9em;\n}\n\n/* \u6807\u9898\u5b57\u4f53 */\nh1, h2, h3, h4, h5, h6 {\n  font-family: var(--font-family);\n  font-weight: 600;\n  margin: calc(var(--spacing-unit) * 3) 0;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5122","title":"5.1.2.2 \u989c\u8272\u5b9a\u5236","text":"CSS<pre><code>/* docs/stylesheets/base/_colors.css */\n\n/* \u6587\u672c\u989c\u8272 */\n.md-typeset {\n  color: var(--text-color);\n}\n\n/* \u94fe\u63a5\u989c\u8272 */\n.md-typeset a {\n  color: var(--md-accent-fg-color);\n}\n\n/* \u4ee3\u7801\u5757\u989c\u8272 */\n.highlight {\n  background-color: var(--md-code-bg-color);\n}\n\n/* \u5f15\u7528\u5757\u989c\u8272 */\nblockquote {\n  border-left: 4px solid var(--md-accent-fg-color);\n  background-color: var(--md-code-bg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5123","title":"5.1.2.3 \u95f4\u8ddd\u8c03\u6574","text":"CSS<pre><code>/* \u5185\u5bb9\u95f4\u8ddd */\n.md-main__inner {\n  padding: var(--content-padding);\n}\n\n/* \u6bb5\u843d\u95f4\u8ddd */\n.md-typeset p {\n  margin: var(--spacing-unit) 0;\n}\n\n/* \u5217\u8868\u95f4\u8ddd */\n.md-typeset ul li,\n.md-typeset ol li {\n  margin-bottom: calc(var(--spacing-unit) * 0.5);\n}\n\n/* \u6807\u9898\u95f4\u8ddd */\n.md-typeset h1 {\n  margin-top: calc(var(--spacing-unit) * 4);\n  margin-bottom: calc(var(--spacing-unit) * 2);\n}\n\n.md-typeset h2 {\n  margin-top: calc(var(--spacing-unit) * 3);\n  margin-bottom: calc(var(--spacing-unit) * 1.5);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5124","title":"5.1.2.4 \u5b8c\u6574\u914d\u7f6e\u793a\u4f8b","text":"<p>\u5728 <code>mkdocs.yml</code> \u4e2d\u7684\u914d\u7f6e\uff1a</p> YAML<pre><code>theme:\n  name: material\n  font: false  # \u7981\u7528\u9ed8\u8ba4\u5b57\u4f53\n\nextra_css:\n  - stylesheets/extra.css\n\nextra:\n  css_variables:\n    spacing_unit: 8px\n    content_width: 960px\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#52","title":"5.2 \u4e3b\u9898\u6837\u5f0f\u8986\u76d6","text":""},{"location":"Tools/Blog/Mkdocs_Material/#521","title":"5.2.1 \u7ec4\u4ef6\u6837\u5f0f\u4fee\u6539","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5211","title":"5.2.1.1 \u5bfc\u822a\u680f\u6837\u5f0f","text":"<ol> <li>\u9876\u90e8\u5bfc\u822a\u680f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/components/header.css */\n\n/* \u5bfc\u822a\u680f\u5bb9\u5668 */\n.md-header {\n  background-color: var(--md-primary-fg-color);\n  box-shadow: 0 2px 4px rgba(0,0,0,.14);\n  height: 3rem;\n}\n\n/* \u5bfc\u822a\u680f\u6807\u9898 */\n.md-header__title {\n  font-size: 1.2rem;\n  font-weight: 600;\n  margin-left: 1rem;\n}\n\n/* \u5bfc\u822a\u680f\u6309\u94ae */\n.md-header__button {\n  padding: .8rem;\n  color: var(--md-primary-bg-color);\n}\n\n/* \u5bfc\u822a\u680f\u641c\u7d22\u6846 */\n.md-search__input {\n  border-radius: 2rem;\n  background-color: rgba(255,255,255,.1);\n  padding: 0 2.4rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5212","title":"5.2.1.2 \u4fa7\u8fb9\u680f\u6837\u5f0f","text":"CSS<pre><code>/* docs/stylesheets/components/sidebar.css */\n\n/* \u4fa7\u8fb9\u680f\u5bb9\u5668 */\n.md-sidebar {\n  width: 14rem;\n  background-color: var(--md-default-bg-color);\n  padding: 1.2rem 0;\n}\n\n/* \u4fa7\u8fb9\u680f\u5bfc\u822a */\n.md-nav--primary {\n  padding: 0 .8rem;\n}\n\n/* \u5bfc\u822a\u9879 */\n.md-nav__item {\n  padding: .2rem 0;\n}\n\n/* \u5bfc\u822a\u94fe\u63a5 */\n.md-nav__link {\n  color: var(--md-default-fg-color);\n  padding: .4rem .6rem;\n  border-radius: 4px;\n  transition: all .2s;\n}\n\n.md-nav__link:hover {\n  background-color: var(--md-code-bg-color);\n  color: var(--md-accent-fg-color);\n}\n\n/* \u6fc0\u6d3b\u72b6\u6001 */\n.md-nav__link--active {\n  font-weight: 600;\n  color: var(--md-accent-fg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5213","title":"5.2.1.3 \u9875\u811a\u6837\u5f0f","text":"CSS<pre><code>/* docs/stylesheets/components/footer.css */\n\n/* \u9875\u811a\u5bb9\u5668 */\n.md-footer {\n  background-color: var(--md-default-bg-color--darkest);\n  color: var(--md-footer-fg-color);\n}\n\n/* \u9875\u811a\u5185\u5bb9 */\n.md-footer-meta {\n  background-color: rgba(0,0,0,.1);\n  padding: 1rem 0;\n}\n\n/* \u9875\u811a\u94fe\u63a5 */\n.md-footer__link {\n  padding: .4rem 1rem;\n  color: var(--md-footer-fg-color--light);\n}\n\n/* \u7248\u6743\u4fe1\u606f */\n.md-footer-copyright {\n  font-size: .8rem;\n  color: var(--md-footer-fg-color--lighter);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#522","title":"5.2.2 \u81ea\u5b9a\u4e49\u8c03\u8272\u677f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5221","title":"5.2.2.1 \u4e3b\u9898\u8272\u5b9a\u5236","text":"<ol> <li>\u57fa\u7840\u989c\u8272\u5b9a\u4e49\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/theme/colors.css */\n\n:root {\n  /* \u4e3b\u8272\u8c03 */\n  --md-primary-hue: 210;\n  --md-primary-saturation: 80%;\n  --md-primary-lightness: 45%;\n\n  /* \u5f3a\u8c03\u8272 */\n  --md-accent-hue: 340;\n  --md-accent-saturation: 90%;\n  --md-accent-lightness: 50%;\n}\n</code></pre> <ol> <li>\u989c\u8272\u53d8\u91cf\u5e94\u7528\uff1a</li> </ol> CSS<pre><code>:root {\n  --md-primary-fg-color: hsl(\n    var(--md-primary-hue),\n    var(--md-primary-saturation),\n    var(--md-primary-lightness)\n  );\n\n  --md-accent-fg-color: hsl(\n    var(--md-accent-hue),\n    var(--md-accent-saturation),\n    var(--md-accent-lightness)\n  );\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5222","title":"5.2.2.2 \u914d\u8272\u65b9\u6848","text":"YAML<pre><code># mkdocs.yml\ntheme:\n  palette:\n    # \u4eae\u8272\u6a21\u5f0f\n    - media: \"(prefers-color-scheme: light)\"\n      scheme: default\n      primary: indigo\n      accent: deep purple\n      toggle:\n        icon: material/brightness-7\n        name: \u5207\u6362\u81f3\u6697\u8272\u6a21\u5f0f\n\n    # \u6697\u8272\u6a21\u5f0f\n    - media: \"(prefers-color-scheme: dark)\"\n      scheme: slate\n      primary: blue grey\n      accent: deep purple\n      toggle:\n        icon: material/brightness-4\n        name: \u5207\u6362\u81f3\u4eae\u8272\u6a21\u5f0f\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5223","title":"5.2.2.3 \u6697\u8272\u4e3b\u9898","text":"CSS<pre><code>/* \u6697\u8272\u4e3b\u9898\u53d8\u91cf */\n[data-md-color-scheme=\"slate\"] {\n  --md-default-bg-color: #1a1a1a;\n  --md-default-bg-color--light: #222222;\n  --md-default-bg-color--lighter: #282828;\n\n  --md-default-fg-color: rgba(255,255,255,0.87);\n  --md-default-fg-color--light: rgba(255,255,255,0.54);\n  --md-default-fg-color--lighter: rgba(255,255,255,0.32);\n\n  --md-code-bg-color: #2d2d2d;\n  --md-code-fg-color: #f5f5f5;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#523","title":"5.2.3 \u5b57\u4f53\u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5231","title":"5.2.3.1 \u4e2d\u6587\u5b57\u4f53","text":"<ol> <li>\u5b57\u4f53\u5b9a\u4e49\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/theme/fonts.css */\n\n/* \u4e2d\u6587\u5b57\u4f53\u53d8\u91cf */\n:root {\n  --md-font-chinese: \"LXGW WenKai\", \"PingFang SC\", \"Microsoft YaHei\";\n}\n\n/* \u5f15\u5165 LXGW WenKai \u5b57\u4f53 */\n@font-face {\n  font-family: \"LXGW WenKai\";\n  src: url(\"https://cdn.jsdelivr.net/npm/lxgw-wenkai-webfont@1.1.0/style.css\");\n  font-display: swap;\n}\n</code></pre> <ol> <li>\u5b57\u4f53\u5e94\u7528\uff1a</li> </ol> CSS<pre><code>body {\n  font-family: var(--md-font-chinese), -apple-system, sans-serif;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5232","title":"5.2.3.2 \u4ee3\u7801\u5b57\u4f53","text":"CSS<pre><code>/* \u4ee3\u7801\u5b57\u4f53\u914d\u7f6e */\n:root {\n  --md-code-font: \"JetBrains Mono\", \"Fira Code\", \"Source Code Pro\", monospace;\n}\n\n/* \u4ee3\u7801\u5757\u6837\u5f0f */\n.md-typeset code,\n.md-typeset pre {\n  font-family: var(--md-code-font);\n  font-size: 0.9em;\n}\n\n/* \u884c\u5185\u4ee3\u7801 */\n.md-typeset code {\n  border-radius: 4px;\n  padding: .2em .4em;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5233","title":"5.2.3.3 \u5b57\u4f53\u56de\u9000","text":"CSS<pre><code>/* \u5b57\u4f53\u56de\u9000\u7b56\u7565 */\n:root {\n  --md-text-font-fallback: -apple-system, BlinkMacSystemFont, Segoe UI, Helvetica,\n    Arial, sans-serif, Apple Color Emoji, Segoe UI Emoji;\n\n  --md-code-font-fallback: SFMono-Regular, Consolas, Menlo, monospace;\n}\n\n/* \u5e94\u7528\u56de\u9000\u5b57\u4f53 */\nbody {\n  font-family: var(--md-font-chinese), var(--md-text-font-fallback);\n}\n\npre, code {\n  font-family: var(--md-code-font), var(--md-code-font-fallback);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#524","title":"5.2.4 \u5e03\u5c40\u8c03\u6574","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5241","title":"5.2.4.1 \u54cd\u5e94\u5f0f\u5e03\u5c40","text":"CSS<pre><code>/* docs/stylesheets/theme/layout.css */\n\n/* \u57fa\u7840\u54cd\u5e94\u5f0f\u5e03\u5c40 */\n.md-grid {\n  max-width: 100%;\n  margin: 0 auto;\n}\n\n/* \u684c\u9762\u7aef */\n@media screen and (min-width: 76.25em) {\n  .md-grid {\n    max-width: 76rem;\n  }\n\n  .md-sidebar--primary {\n    width: 14rem;\n  }\n\n  .md-sidebar--secondary {\n    width: 12rem;\n    margin-left: 76rem;\n  }\n}\n\n/* \u5e73\u677f\u7aef */\n@media screen and (max-width: 76.1875em) {\n  .md-grid {\n    max-width: 60rem;\n  }\n\n  .md-header-nav__title {\n    display: none;\n  }\n}\n\n/* \u79fb\u52a8\u7aef */\n@media screen and (max-width: 44.9375em) {\n  .md-grid {\n    max-width: 100%;\n    padding: 0 1rem;\n  }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5242","title":"5.2.4.2 \u7f51\u683c\u7cfb\u7edf","text":"CSS<pre><code>/* \u81ea\u5b9a\u4e49\u7f51\u683c\u7cfb\u7edf */\n.grid {\n  display: grid;\n  gap: 1rem;\n  margin: 1rem 0;\n}\n\n/* \u7f51\u683c\u5217\u6570 */\n.grid-cols-1 { grid-template-columns: repeat(1, 1fr); }\n.grid-cols-2 { grid-template-columns: repeat(2, 1fr); }\n.grid-cols-3 { grid-template-columns: repeat(3, 1fr); }\n.grid-cols-4 { grid-template-columns: repeat(4, 1fr); }\n\n/* \u54cd\u5e94\u5f0f\u7f51\u683c */\n@media (min-width: 768px) {\n  .md-grid-cols-md-2 { grid-template-columns: repeat(2, 1fr); }\n  .md-grid-cols-md-3 { grid-template-columns: repeat(3, 1fr); }\n}\n\n@media (min-width: 1024px) {\n  .md-grid-cols-lg-3 { grid-template-columns: repeat(3, 1fr); }\n  .md-grid-cols-lg-4 { grid-template-columns: repeat(4, 1fr); }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5243","title":"5.2.4.3 \u5bb9\u5668\u5bbd\u5ea6","text":"CSS<pre><code>/* \u5bb9\u5668\u5bbd\u5ea6\u5b9a\u4e49 */\n:root {\n  --md-container-width: 80rem;\n  --md-container-padding: 1rem;\n}\n\n/* \u5bb9\u5668\u6837\u5f0f */\n.md-container {\n  max-width: var(--md-container-width);\n  margin: 0 auto;\n  padding: 0 var(--md-container-padding);\n}\n\n/* \u4e0d\u540c\u5c3a\u5bf8\u7684\u5bb9\u5668 */\n.md-container--small {\n  max-width: 60rem;\n}\n\n.md-container--medium {\n  max-width: 70rem;\n}\n\n.md-container--large {\n  max-width: 90rem;\n}\n\n/* \u6d41\u5f0f\u5bb9\u5668 */\n.md-container--fluid {\n  max-width: 100%;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#525","title":"5.2.5 \u5b8c\u6574\u914d\u7f6e\u793a\u4f8b","text":"YAML<pre><code># mkdocs.yml\ntheme:\n  name: material\n  font: false\n  features:\n    - navigation.tabs\n    - navigation.sections\n    - navigation.expand\n  palette:\n    - scheme: default\n      primary: indigo\n      accent: deep purple\n    - scheme: slate\n      primary: blue grey\n      accent: deep purple\n\nextra_css:\n  - stylesheets/theme/colors.css\n  - stylesheets/theme/fonts.css\n  - stylesheets/theme/layout.css\n  - stylesheets/components/header.css\n  - stylesheets/components/sidebar.css\n  - stylesheets/components/footer.css\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#53","title":"5.3 \u81ea\u5b9a\u4e49\u7ec4\u4ef6\u6837\u5f0f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#531","title":"5.3.1 \u5361\u7247\u6837\u5f0f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5311","title":"5.3.1.1 \u57fa\u7840\u5361\u7247","text":"<p>\u57fa\u7840\u5361\u7247\u6837\u5f0f\u5b9a\u4e49\uff1a</p> CSS<pre><code>/* docs/stylesheets/components/cards.css */\n\n/* \u57fa\u7840\u5361\u7247\u5bb9\u5668 */\n.card {\n  background-color: var(--md-default-bg-color);\n  border-radius: 8px;\n  box-shadow: var(--md-shadow-z1);\n  padding: 1.5rem;\n  margin: 1rem 0;\n  transition: all 0.3s ease;\n}\n\n/* \u5361\u7247\u6807\u9898 */\n.card__title {\n  font-size: 1.25rem;\n  font-weight: 600;\n  margin-bottom: 1rem;\n  color: var(--md-typeset-color);\n}\n\n/* \u5361\u7247\u5185\u5bb9 */\n.card__content {\n  font-size: 0.9rem;\n  color: var(--md-default-fg-color--light);\n  line-height: 1.6;\n}\n\n/* \u5361\u7247\u5e95\u90e8 */\n.card__footer {\n  margin-top: 1rem;\n  padding-top: 1rem;\n  border-top: 1px solid var(--md-default-fg-color--lightest);\n}\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> HTML<pre><code>&lt;div class=\"card\"&gt;\n  &lt;div class=\"card__title\"&gt;\u5361\u7247\u6807\u9898&lt;/div&gt;\n  &lt;div class=\"card__content\"&gt;\n    \u8fd9\u91cc\u662f\u5361\u7247\u5185\u5bb9...\n  &lt;/div&gt;\n  &lt;div class=\"card__footer\"&gt;\n    \u5361\u7247\u5e95\u90e8\u4fe1\u606f\n  &lt;/div&gt;\n&lt;/div&gt;\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5312","title":"5.3.1.2 \u56fe\u7247\u5361\u7247","text":"CSS<pre><code>/* \u56fe\u7247\u5361\u7247\u6837\u5f0f */\n.card--image {\n  padding: 0;\n  overflow: hidden;\n}\n\n/* \u56fe\u7247\u5bb9\u5668 */\n.card__image {\n  width: 100%;\n  height: 200px;\n  position: relative;\n  overflow: hidden;\n}\n\n/* \u56fe\u7247\u6837\u5f0f */\n.card__image img {\n  width: 100%;\n  height: 100%;\n  object-fit: cover;\n  transition: transform 0.3s ease;\n}\n\n/* \u56fe\u7247\u60ac\u505c\u6548\u679c */\n.card--image:hover img {\n  transform: scale(1.05);\n}\n\n/* \u56fe\u7247\u5361\u7247\u5185\u5bb9\u533a */\n.card--image .card__content {\n  padding: 1.5rem;\n}\n\n/* \u56fe\u7247\u6807\u9898\u8986\u76d6 */\n.card__image-title {\n  position: absolute;\n  bottom: 0;\n  left: 0;\n  right: 0;\n  padding: 1rem;\n  background: linear-gradient(to top, rgba(0,0,0,0.7), transparent);\n  color: white;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5313","title":"5.3.1.3 \u7279\u6548\u5361\u7247","text":"CSS<pre><code>/* \u60ac\u6d6e\u6548\u679c\u5361\u7247 */\n.card--hover {\n  cursor: pointer;\n}\n\n.card--hover:hover {\n  transform: translateY(-4px);\n  box-shadow: var(--md-shadow-z2);\n}\n\n/* \u6e10\u53d8\u80cc\u666f\u5361\u7247 */\n.card--gradient {\n  background: linear-gradient(135deg, \n    var(--md-primary-fg-color) 0%,\n    var(--md-accent-fg-color) 100%);\n  color: white;\n}\n\n/* \u6bdb\u73bb\u7483\u6548\u679c\u5361\u7247 */\n.card--glass {\n  background: rgba(255, 255, 255, 0.1);\n  backdrop-filter: blur(10px);\n  border: 1px solid rgba(255, 255, 255, 0.2);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#532","title":"5.3.2 \u63d0\u793a\u6846\u6837\u5f0f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5321","title":"5.3.2.1 \u4fe1\u606f\u63d0\u793a","text":"CSS<pre><code>/* docs/stylesheets/components/alerts.css */\n\n/* \u57fa\u7840\u63d0\u793a\u6846 */\n.alert {\n  padding: 1rem 1.5rem;\n  margin: 1rem 0;\n  border-left: 4px solid;\n  border-radius: 4px;\n}\n\n/* \u4fe1\u606f\u63d0\u793a */\n.alert--info {\n  background-color: #e3f2fd;\n  border-color: #2196f3;\n  color: #0d47a1;\n}\n\n.alert--info::before {\n  content: \"\u2139\ufe0f\";\n  margin-right: 0.5rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5322","title":"5.3.2.2 \u8b66\u544a\u63d0\u793a","text":"CSS<pre><code>/* \u8b66\u544a\u63d0\u793a */\n.alert--warning {\n  background-color: #fff3e0;\n  border-color: #ff9800;\n  color: #e65100;\n}\n\n.alert--warning::before {\n  content: \"\u26a0\ufe0f\";\n  margin-right: 0.5rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5323","title":"5.3.2.3 \u9519\u8bef\u63d0\u793a","text":"CSS<pre><code>/* \u9519\u8bef\u63d0\u793a */\n.alert--error {\n  background-color: #ffebee;\n  border-color: #f44336;\n  color: #b71c1c;\n}\n\n.alert--error::before {\n  content: \"\u274c\";\n  margin-right: 0.5rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#533","title":"5.3.3 \u53cb\u94fe\u6837\u5f0f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5331","title":"5.3.3.1 \u53cb\u94fe\u5361\u7247","text":"CSS<pre><code>/* docs/stylesheets/components/friends.css */\n\n/* \u53cb\u94fe\u5bb9\u5668 */\n.friend-links {\n  display: grid;\n  grid-template-columns: repeat(auto-fill, minmax(250px, 1fr));\n  gap: 1.5rem;\n  margin: 2rem 0;\n}\n\n/* \u53cb\u94fe\u5361\u7247 */\n.friend-link {\n  display: flex;\n  align-items: center;\n  padding: 1rem;\n  background: var(--md-default-bg-color);\n  border-radius: 8px;\n  box-shadow: var(--md-shadow-z1);\n  transition: all 0.3s ease;\n}\n\n/* \u5934\u50cf */\n.friend-link__avatar {\n  width: 60px;\n  height: 60px;\n  border-radius: 50%;\n  margin-right: 1rem;\n}\n\n/* \u4fe1\u606f */\n.friend-link__info {\n  flex: 1;\n}\n\n.friend-link__name {\n  font-weight: 600;\n  color: var(--md-typeset-color);\n}\n\n.friend-link__desc {\n  font-size: 0.85rem;\n  color: var(--md-default-fg-color--light);\n  margin-top: 0.25rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5332","title":"5.3.3.2 \u5206\u7c7b\u5c55\u793a","text":"CSS<pre><code>/* \u53cb\u94fe\u5206\u7c7b */\n.friend-links-section {\n  margin: 2rem 0;\n}\n\n/* \u5206\u7c7b\u6807\u9898 */\n.friend-links-section__title {\n  font-size: 1.25rem;\n  font-weight: 600;\n  margin-bottom: 1rem;\n  padding-left: 1rem;\n  border-left: 4px solid var(--md-accent-fg-color);\n}\n\n/* \u5206\u7c7b\u63cf\u8ff0 */\n.friend-links-section__desc {\n  color: var(--md-default-fg-color--light);\n  margin-bottom: 1.5rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5333","title":"5.3.3.3 \u60ac\u505c\u6548\u679c","text":"CSS<pre><code>/* \u60ac\u505c\u6548\u679c */\n.friend-link:hover {\n  transform: translateY(-2px);\n  box-shadow: var(--md-shadow-z2);\n}\n\n/* \u5934\u50cf\u52a8\u753b */\n.friend-link:hover .friend-link__avatar {\n  transform: rotate(360deg);\n  transition: transform 0.6s ease;\n}\n\n/* \u6807\u7b7e\u6548\u679c */\n.friend-link__tag {\n  display: inline-block;\n  padding: 0.2rem 0.5rem;\n  font-size: 0.75rem;\n  border-radius: 12px;\n  background-color: var(--md-code-bg-color);\n  margin-top: 0.5rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#534","title":"5.3.4 \u65f6\u95f4\u7ebf\u6837\u5f0f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5341","title":"5.3.4.1 \u65f6\u95f4\u8f74\u8bbe\u8ba1","text":"CSS<pre><code>/* docs/stylesheets/components/timeline.css */\n\n/* \u65f6\u95f4\u7ebf\u5bb9\u5668 */\n.timeline {\n  position: relative;\n  max-width: 800px;\n  margin: 2rem auto;\n  padding: 2rem 0;\n}\n\n/* \u65f6\u95f4\u8f74\u7ebf */\n.timeline::before {\n  content: '';\n  position: absolute;\n  top: 0;\n  left: calc(50% - 1px);\n  width: 2px;\n  height: 100%;\n  background-color: var(--md-default-fg-color--lightest);\n}\n\n/* \u65f6\u95f4\u7ebf\u9879\u76ee */\n.timeline-item {\n  position: relative;\n  margin: 2rem 0;\n}\n\n/* \u4ea4\u9519\u5e03\u5c40 */\n.timeline-item:nth-child(odd) {\n  padding-right: calc(50% + 2rem);\n}\n\n.timeline-item:nth-child(even) {\n  padding-left: calc(50% + 2rem);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5342","title":"5.3.4.2 \u8282\u70b9\u6837\u5f0f","text":"CSS<pre><code>/* \u65f6\u95f4\u8282\u70b9 */\n.timeline-node {\n  position: absolute;\n  top: 50%;\n  width: 16px;\n  height: 16px;\n  background-color: var(--md-primary-fg-color);\n  border-radius: 50%;\n  transform: translateY(-50%);\n}\n\n.timeline-item:nth-child(odd) .timeline-node {\n  right: calc(50% - 8px);\n}\n\n.timeline-item:nth-child(even) .timeline-node {\n  left: calc(50% - 8px);\n}\n\n/* \u8282\u70b9\u5185\u5bb9 */\n.timeline-content {\n  background-color: var(--md-default-bg-color);\n  padding: 1.5rem;\n  border-radius: 8px;\n  box-shadow: var(--md-shadow-z1);\n}\n\n/* \u65f6\u95f4\u6807\u7b7e */\n.timeline-date {\n  position: absolute;\n  top: 50%;\n  color: var(--md-default-fg-color--light);\n  transform: translateY(-50%);\n}\n\n.timeline-item:nth-child(odd) .timeline-date {\n  left: calc(50% + 2rem);\n}\n\n.timeline-item:nth-child(even) .timeline-date {\n  right: calc(50% + 2rem);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5343","title":"5.3.4.3 \u54cd\u5e94\u5f0f\u9002\u914d","text":"CSS<pre><code>/* \u79fb\u52a8\u7aef\u9002\u914d */\n@media screen and (max-width: 768px) {\n  .timeline::before {\n    left: 0;\n  }\n\n  .timeline-item {\n    padding-left: 2rem !important;\n    padding-right: 0 !important;\n  }\n\n  .timeline-node {\n    left: -8px !important;\n    right: auto !important;\n  }\n\n  .timeline-date {\n    position: relative;\n    top: auto;\n    left: auto !important;\n    right: auto !important;\n    margin-bottom: 0.5rem;\n  }\n}\n\n/* \u5e73\u677f\u7aef\u9002\u914d */\n@media screen and (min-width: 769px) and (max-width: 1024px) {\n  .timeline {\n    max-width: 90%;\n  }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5344","title":"5.3.4.4 \u4f7f\u7528\u793a\u4f8b","text":"HTML<pre><code>&lt;!-- \u65f6\u95f4\u7ebf\u793a\u4f8b --&gt;\n&lt;div class=\"timeline\"&gt;\n  &lt;div class=\"timeline-item\"&gt;\n    &lt;div class=\"timeline-node\"&gt;&lt;/div&gt;\n    &lt;div class=\"timeline-date\"&gt;2024-01-01&lt;/div&gt;\n    &lt;div class=\"timeline-content\"&gt;\n      &lt;h3&gt;\u4e8b\u4ef6\u6807\u9898&lt;/h3&gt;\n      &lt;p&gt;\u4e8b\u4ef6\u63cf\u8ff0...&lt;/p&gt;\n    &lt;/div&gt;\n  &lt;/div&gt;\n\n  &lt;!-- \u66f4\u591a\u65f6\u95f4\u7ebf\u9879\u76ee --&gt;\n&lt;/div&gt;\n\n&lt;!-- \u53cb\u94fe\u793a\u4f8b --&gt;\n&lt;div class=\"friend-links-section\"&gt;\n  &lt;h2 class=\"friend-links-section__title\"&gt;\u6280\u672f\u535a\u5ba2&lt;/h2&gt;\n  &lt;p class=\"friend-links-section__desc\"&gt;\u4f18\u79c0\u7684\u6280\u672f\u535a\u5ba2\u6536\u85cf&lt;/p&gt;\n  &lt;div class=\"friend-links\"&gt;\n    &lt;a href=\"#\" class=\"friend-link\"&gt;\n      &lt;img src=\"avatar.jpg\" class=\"friend-link__avatar\"&gt;\n      &lt;div class=\"friend-link__info\"&gt;\n        &lt;div class=\"friend-link__name\"&gt;\u535a\u5ba2\u540d\u79f0&lt;/div&gt;\n        &lt;div class=\"friend-link__desc\"&gt;\u535a\u5ba2\u63cf\u8ff0&lt;/div&gt;\n        &lt;span class=\"friend-link__tag\"&gt;\u6807\u7b7e&lt;/span&gt;\n      &lt;/div&gt;\n    &lt;/a&gt;\n  &lt;/div&gt;\n&lt;/div&gt;\n\n&lt;!-- \u63d0\u793a\u6846\u793a\u4f8b --&gt;\n&lt;div class=\"alert alert--info\"&gt;\n  \u8fd9\u662f\u4e00\u6761\u4fe1\u606f\u63d0\u793a\n&lt;/div&gt;\n\n&lt;div class=\"alert alert--warning\"&gt;\n  \u8fd9\u662f\u4e00\u6761\u8b66\u544a\u63d0\u793a\n&lt;/div&gt;\n\n&lt;div class=\"alert alert--error\"&gt;\n  \u8fd9\u662f\u4e00\u6761\u9519\u8bef\u63d0\u793a\n&lt;/div&gt;\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#535","title":"5.3.5 \u5b8c\u6574\u914d\u7f6e","text":"YAML<pre><code># mkdocs.yml\nextra_css:\n  - stylesheets/components/cards.css\n  - stylesheets/components/alerts.css\n  - stylesheets/components/friends.css\n  - stylesheets/components/timeline.css\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6-javascript","title":"6 JavaScript \u589e\u5f3a","text":""},{"location":"Tools/Blog/Mkdocs_Material/#61","title":"6.1 \u57fa\u7840\u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#611-js","title":"6.1.1 \u5f15\u5165 JS \u6587\u4ef6","text":""},{"location":"Tools/Blog/Mkdocs_Material/#6111","title":"6.1.1.1 \u672c\u5730\u6587\u4ef6","text":"<ol> <li>\u521b\u5efa\u57fa\u7840\u76ee\u5f55\u7ed3\u6784\uff1a</li> </ol> Text Only<pre><code>docs/\n\u251c\u2500\u2500 javascripts/\n\u2502   \u251c\u2500\u2500 config/             # \u914d\u7f6e\u6587\u4ef6\n\u2502   \u2502   \u2514\u2500\u2500 main.js\n\u2502   \u251c\u2500\u2500 modules/            # \u529f\u80fd\u6a21\u5757\n\u2502   \u2502   \u251c\u2500\u2500 search.js\n\u2502   \u2502   \u2514\u2500\u2500 theme.js\n\u2502   \u251c\u2500\u2500 utils/             # \u5de5\u5177\u51fd\u6570\n\u2502   \u2502   \u2514\u2500\u2500 helpers.js\n\u2502   \u2514\u2500\u2500 extra.js           # \u4e3b\u5165\u53e3\u6587\u4ef6\n</code></pre> <ol> <li>\u5728 <code>mkdocs.yml</code> \u4e2d\u5f15\u5165\uff1a</li> </ol> YAML<pre><code>extra_javascript:\n  - javascripts/extra.js\n  - javascripts/modules/search.js\n  - javascripts/modules/theme.js\n</code></pre> <ol> <li>JavaScript \u6587\u4ef6\u793a\u4f8b\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/extra.js\ndocument.addEventListener('DOMContentLoaded', function() {\n    // \u521d\u59cb\u5316\u4ee3\u7801\n    console.log('Documentation loaded');\n});\n\n// docs/javascripts/modules/theme.js\nconst ThemeManager = {\n    init() {\n        // \u4e3b\u9898\u521d\u59cb\u5316\n    },\n    toggle() {\n        // \u4e3b\u9898\u5207\u6362\n    }\n};\n\n// docs/javascripts/utils/helpers.js\nconst Helpers = {\n    debounce(fn, delay) {\n        let timer = null;\n        return function() {\n            clearTimeout(timer);\n            timer = setTimeout(() =&gt; fn.apply(this, arguments), delay);\n        };\n    }\n};\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6112-cdn","title":"6.1.1.2 CDN \u5f15\u5165","text":"<ol> <li>\u5e38\u7528 CDN \u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>extra_javascript:\n  # KaTeX \u6570\u5b66\u516c\u5f0f\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/katex.min.js\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/contrib/auto-render.min.js\n\n  # Mermaid \u56fe\u8868\n  - https://unpkg.com/mermaid@9/dist/mermaid.min.js\n\n  # \u4ee3\u7801\u9ad8\u4eae\n  - https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/prism.min.js\n  - https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/components/prism-python.min.js\n</code></pre> <ol> <li>CDN \u52a0\u901f\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>extra:\n  cdn:\n    # \u4f7f\u7528\u56fd\u5185 CDN\n    enable: true\n    provider: jsdelivr  # \u6216 unpkg, cdnjs\n    urls:\n      katex: https://cdn.jsdelivr.net/npm/katex@0.16.7/dist/katex.min.js\n      mermaid: https://cdn.jsdelivr.net/npm/mermaid@9/dist/mermaid.min.js\n</code></pre> <ol> <li>CDN \u6545\u969c\u5904\u7406\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/config/cdn-fallback.js\nfunction loadFallbackScript(url, fallbackUrl) {\n    const script = document.createElement('script');\n    script.src = url;\n    script.onerror = () =&gt; {\n        console.warn(`Failed to load ${url}, trying fallback...`);\n        const fallback = document.createElement('script');\n        fallback.src = fallbackUrl;\n        document.head.appendChild(fallback);\n    };\n    document.head.appendChild(script);\n}\n\n// \u4f7f\u7528\u793a\u4f8b\nloadFallbackScript(\n    'https://cdn.jsdelivr.net/npm/katex@0.16.7/dist/katex.min.js',\n    'https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/katex.min.js'\n);\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6113","title":"6.1.1.3 \u6a21\u5757\u5316\u7ba1\u7406","text":"<ol> <li>\u4f7f\u7528 ES6 \u6a21\u5757\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/modules/theme.js\nexport class ThemeManager {\n    constructor() {\n        this.darkMode = false;\n    }\n\n    init() {\n        this.loadPreference();\n        this.bindEvents();\n    }\n\n    toggle() {\n        this.darkMode = !this.darkMode;\n        this.savePreference();\n        this.applyTheme();\n    }\n}\n\n// docs/javascripts/modules/search.js\nexport class SearchManager {\n    constructor() {\n        this.index = null;\n    }\n\n    init() {\n        this.buildIndex();\n        this.bindSearchEvents();\n    }\n\n    search(query) {\n        // \u641c\u7d22\u5b9e\u73b0\n    }\n}\n\n// docs/javascripts/extra.js\nimport { ThemeManager } from './modules/theme.js';\nimport { SearchManager } from './modules/search.js';\n\nconst theme = new ThemeManager();\nconst search = new SearchManager();\n\ndocument.addEventListener('DOMContentLoaded', () =&gt; {\n    theme.init();\n    search.init();\n});\n</code></pre> <ol> <li>\u6a21\u5757\u914d\u7f6e\u6587\u4ef6\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/config/modules.js\nexport const ModuleConfig = {\n    theme: {\n        enabled: true,\n        darkModeClass: 'dark-mode',\n        storageKey: 'theme-preference'\n    },\n    search: {\n        enabled: true,\n        minChars: 3,\n        maxResults: 10\n    }\n};\n\n// \u4f7f\u7528\u914d\u7f6e\nimport { ModuleConfig } from '../config/modules.js';\n\nclass ThemeManager {\n    constructor() {\n        this.config = ModuleConfig.theme;\n        if (!this.config.enabled) return;\n        // \u521d\u59cb\u5316\u4ee3\u7801\n    }\n}\n</code></pre> <ol> <li>\u5de5\u5177\u51fd\u6570\u6a21\u5757\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/utils/helpers.js\nexport const DOM = {\n    // DOM \u64cd\u4f5c\u8f85\u52a9\u51fd\u6570\n    select: (selector) =&gt; document.querySelector(selector),\n    selectAll: (selector) =&gt; document.querySelectorAll(selector),\n    addClass: (element, className) =&gt; element.classList.add(className),\n    removeClass: (element, className) =&gt; element.classList.remove(className)\n};\n\nexport const Storage = {\n    // \u672c\u5730\u5b58\u50a8\u8f85\u52a9\u51fd\u6570\n    get: (key) =&gt; localStorage.getItem(key),\n    set: (key, value) =&gt; localStorage.setItem(key, value),\n    remove: (key) =&gt; localStorage.removeItem(key)\n};\n\nexport const Events = {\n    // \u4e8b\u4ef6\u5904\u7406\u8f85\u52a9\u51fd\u6570\n    on: (element, event, handler) =&gt; element.addEventListener(event, handler),\n    off: (element, event, handler) =&gt; element.removeEventListener(event, handler),\n    trigger: (element, event) =&gt; element.dispatchEvent(new Event(event))\n};\n</code></pre> <ol> <li>\u5b8c\u6574\u914d\u7f6e\u793a\u4f8b\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nextra_javascript:\n  # \u6838\u5fc3\u6587\u4ef6\n  - javascripts/extra.js\n  - javascripts/config/modules.js\n\n  # \u529f\u80fd\u6a21\u5757\n  - javascripts/modules/theme.js\n  - javascripts/modules/search.js\n\n  # \u5de5\u5177\u51fd\u6570\n  - javascripts/utils/helpers.js\n\n  # \u7b2c\u4e09\u65b9\u5e93\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/katex.min.js\n  - https://unpkg.com/mermaid@9/dist/mermaid.min.js\n\n# \u6a21\u5757\u914d\u7f6e\nextra:\n  javascript_modules:\n    theme:\n      enabled: true\n      default: light\n    search:\n      enabled: true\n      min_chars: 3\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#62","title":"6.2 \u7b2c\u4e09\u65b9\u5e93\u96c6\u6210","text":""},{"location":"Tools/Blog/Mkdocs_Material/#621-katex","title":"6.2.1 KaTeX \u6570\u5b66\u516c\u5f0f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#6211","title":"6.2.1.1 \u57fa\u7840\u914d\u7f6e","text":"<ol> <li>\u5728 <code>mkdocs.yml</code> \u4e2d\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>markdown_extensions:\n  - pymdownx.arithmatex:\n      generic: true\n\nextra_javascript:\n  - javascripts/katex.js\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/katex.min.js\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/contrib/auto-render.min.js\n\nextra_css:\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/katex.min.css\n</code></pre> <ol> <li>\u521b\u5efa KaTeX \u914d\u7f6e\u6587\u4ef6\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/katex.js\ndocument.addEventListener(\"DOMContentLoaded\", function() {\n    renderMathInElement(document.body, {\n        delimiters: [\n            {left: \"$$\", right: \"$$\", display: true},\n            {left: \"$\", right: \"$\", display: false},\n            {left: \"\\\\(\", right: \"\\\\)\", display: false},\n            {left: \"\\\\[\", right: \"\\\\]\", display: true}\n        ],\n        throwOnError: false,\n        errorColor: \"#cc0000\",\n        strict: \"ignore\"\n    });\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6212","title":"6.2.1.2 \u81ea\u52a8\u6e32\u67d3","text":"<ol> <li>\u914d\u7f6e\u81ea\u52a8\u6e32\u67d3\u9009\u9879\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/katex-auto.js\ndocument.addEventListener(\"DOMContentLoaded\", function() {\n    renderMathInElement(document.body, {\n        delimiters: [\n            {left: \"$$\", right: \"$$\", display: true},\n            {left: \"$\", right: \"$\", display: false}\n        ],\n        // \u81ea\u52a8\u6e32\u67d3\u8bbe\u7f6e\n        ignoredTags: [\"script\", \"noscript\", \"style\", \"textarea\", \"pre\", \"code\"],\n        ignoredClasses: [\"no-math\"],\n        processEscapes: true,\n        processEnvironments: true,\n        // \u5904\u7406\u81ea\u5b9a\u4e49\u5b8f\n        macros: {\n            \"\\\\RR\": \"\\\\mathbb{R}\",\n            \"\\\\NN\": \"\\\\mathbb{N}\",\n            \"\\\\ZZ\": \"\\\\mathbb{Z}\"\n        }\n    });\n});\n</code></pre> <ol> <li>\u4f7f\u7528\u793a\u4f8b\uff1a</li> </ol> Markdown<pre><code>\u884c\u5185\u516c\u5f0f\uff1a$E = mc^2$\n\n\u5757\u7ea7\u516c\u5f0f\uff1a\n$$\n\\frac{n!}{k!(n-k)!} = \\binom{n}{k}\n$$\n\n\u81ea\u5b9a\u4e49\u5b8f\uff1a$\\RR$ \u8868\u793a\u5b9e\u6570\u96c6\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6213","title":"6.2.1.3 \u516c\u5f0f\u7f16\u53f7","text":"<ol> <li>\u542f\u7528\u516c\u5f0f\u7f16\u53f7\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/katex-numbering.js\ndocument.addEventListener(\"DOMContentLoaded\", function() {\n    // \u516c\u5f0f\u7f16\u53f7\u8ba1\u6570\u5668\n    let equationNumbers = {};\n    let numberings = {};\n\n    renderMathInElement(document.body, {\n        delimiters: [\n            {left: \"$$\", right: \"$$\", display: true}\n        ],\n        // \u516c\u5f0f\u7f16\u53f7\u5904\u7406\n        preProcess: (math) =&gt; {\n            if (math.includes('\\\\label')) {\n                const label = math.match(/\\\\label{([^}]*)}/)[1];\n                const number = Object.keys(numberings).length + 1;\n                numberings[label] = number;\n                return math.replace(/\\\\label{[^}]*}/, `(${number})`);\n            }\n            return math;\n        }\n    });\n});\n</code></pre> <ol> <li>\u4f7f\u7528\u7f16\u53f7\u548c\u5f15\u7528\uff1a</li> </ol> Markdown<pre><code>\u5e26\u7f16\u53f7\u7684\u516c\u5f0f\uff1a\n$$\nE = mc^2 \\label{eq:einstein}\n$$\n\n\u5f15\u7528\u4e0a\u9762\u7684\u516c\u5f0f $\\eqref{eq:einstein}$\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#622-mermaid","title":"6.2.2 Mermaid \u56fe\u8868","text":""},{"location":"Tools/Blog/Mkdocs_Material/#6221","title":"6.2.2.1 \u521d\u59cb\u5316\u914d\u7f6e","text":"<ol> <li>\u5728 <code>mkdocs.yml</code> \u4e2d\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>markdown_extensions:\n  - pymdownx.superfences:\n      custom_fences:\n        - name: mermaid\n          class: mermaid\n          format: !!python/name:pymdownx.superfences.fence_code_format\n\nextra_javascript:\n  - https://unpkg.com/mermaid@9/dist/mermaid.min.js\n  - javascripts/mermaid.js\n</code></pre> <ol> <li>\u521b\u5efa Mermaid \u914d\u7f6e\u6587\u4ef6\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/mermaid.js\ndocument.addEventListener(\"DOMContentLoaded\", function() {\n    mermaid.initialize({\n        startOnLoad: true,\n        theme: 'default',\n        sequence: {\n            showSequenceNumbers: true,\n            actorMargin: 50,\n            messageMargin: 40\n        },\n        flowchart: {\n            useMaxWidth: false,\n            htmlLabels: true,\n            curve: 'basis'\n        },\n        gantt: {\n            titleTopMargin: 25,\n            barHeight: 20,\n            barGap: 4\n        }\n    });\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6222","title":"6.2.2.2 \u4e3b\u9898\u5b9a\u5236","text":"<ol> <li>\u81ea\u5b9a\u4e49\u4e3b\u9898\u914d\u7f6e\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/mermaid-theme.js\nmermaid.initialize({\n    theme: 'base',\n    themeVariables: {\n        // \u57fa\u7840\u989c\u8272\n        primaryColor: '#2196f3',\n        primaryTextColor: '#fff',\n        primaryBorderColor: '#1976d2',\n        lineColor: '#696969',\n\n        // \u6d41\u7a0b\u56fe\u989c\u8272\n        nodeBkg: '#fff',\n        mainBkg: '#f8f9fa',\n        nodeTextColor: '#333',\n\n        // \u65f6\u5e8f\u56fe\u989c\u8272\n        actorBkg: '#f8f9fa',\n        actorBorder: '#2196f3',\n        actorTextColor: '#333',\n\n        // \u7518\u7279\u56fe\u989c\u8272\n        sectionBkgColor: '#f8f9fa',\n        altSectionBkgColor: '#fff',\n\n        // \u6697\u8272\u4e3b\u9898\u652f\u6301\n        darkMode: false\n    }\n});\n</code></pre> <ol> <li>\u54cd\u5e94\u4e3b\u9898\u5207\u6362\uff1a</li> </ol> JavaScript<pre><code>// \u76d1\u542c\u4e3b\u9898\u5207\u6362\ndocument.addEventListener('themeChanged', function(e) {\n    const isDark = e.detail.theme === 'dark';\n    mermaid.initialize({\n        theme: isDark ? 'dark' : 'default',\n        themeVariables: {\n            darkMode: isDark\n        }\n    });\n    // \u91cd\u65b0\u6e32\u67d3\u56fe\u8868\n    mermaid.init(undefined, '.mermaid');\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6223","title":"6.2.2.3 \u4ea4\u4e92\u529f\u80fd","text":"<ol> <li>\u6dfb\u52a0\u70b9\u51fb\u4e8b\u4ef6\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/mermaid-interaction.js\nmermaid.initialize({\n    securityLevel: 'loose',\n    flowchart: {\n        htmlLabels: true,\n        useMaxWidth: true\n    }\n});\n\ndocument.addEventListener(\"DOMContentLoaded\", function() {\n    // \u4e3a\u56fe\u8868\u6dfb\u52a0\u70b9\u51fb\u4e8b\u4ef6\n    const diagrams = document.querySelectorAll('.mermaid');\n    diagrams.forEach(diagram =&gt; {\n        diagram.addEventListener('click', function(e) {\n            const target = e.target;\n            if (target.tagName === 'g' &amp;&amp; target.classList.contains('node')) {\n                const nodeId = target.id;\n                console.log('Clicked node:', nodeId);\n                // \u5904\u7406\u8282\u70b9\u70b9\u51fb\n                handleNodeClick(nodeId);\n            }\n        });\n    });\n});\n\nfunction handleNodeClick(nodeId) {\n    // \u8282\u70b9\u70b9\u51fb\u5904\u7406\n    const node = document.getElementById(nodeId);\n    if (node) {\n        // \u6dfb\u52a0\u9ad8\u4eae\u6548\u679c\n        node.classList.add('node-highlight');\n        setTimeout(() =&gt; {\n            node.classList.remove('node-highlight');\n        }, 1000);\n    }\n}\n</code></pre> <ol> <li>\u6dfb\u52a0\u56fe\u8868\u52a8\u753b\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/mermaid.css */\n.mermaid .node-highlight {\n    animation: pulse 1s;\n}\n\n@keyframes pulse {\n    0% { opacity: 1; }\n    50% { opacity: 0.5; }\n    100% { opacity: 1; }\n}\n\n.mermaid .flowchart-link {\n    transition: stroke-width 0.3s ease;\n}\n\n.mermaid .flowchart-link:hover {\n    stroke-width: 2px;\n    cursor: pointer;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6224","title":"6.2.2.4 \u4f7f\u7528\u793a\u4f8b","text":"<ol> <li>\u6d41\u7a0b\u56fe\u793a\u4f8b\uff1a</li> </ol> Markdown<pre><code>```mermaid\ngraph TD\n    A[\u5f00\u59cb] --&gt; B{\u5224\u65ad}\n    B --&gt;|Yes| C[\u5904\u7406]\n    B --&gt;|No| D[\u7ed3\u675f]\n    C --&gt; D\n```\n</code></pre> <ol> <li>\u65f6\u5e8f\u56fe\u793a\u4f8b\uff1a</li> </ol> Markdown<pre><code>```mermaid\nsequenceDiagram\n    participant \u5ba2\u6237\u7aef\n    participant \u670d\u52a1\u5668\n\n    \u5ba2\u6237\u7aef-&gt;&gt;\u670d\u52a1\u5668: \u8bf7\u6c42\u6570\u636e\n    \u670d\u52a1\u5668--&gt;&gt;\u5ba2\u6237\u7aef: \u8fd4\u56de\u54cd\u5e94\n```\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#623","title":"6.2.3 \u4ee3\u7801\u590d\u5236","text":""},{"location":"Tools/Blog/Mkdocs_Material/#6231","title":"6.2.3.1 \u590d\u5236\u6309\u94ae","text":"<ol> <li>\u5728 <code>mkdocs.yml</code> \u4e2d\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>theme:\n  features:\n    - content.code.copy\n\nextra_css:\n  - stylesheets/code-copy.css\nextra_javascript:\n  - javascripts/code-copy.js\n</code></pre> <ol> <li>\u521b\u5efa\u590d\u5236\u6309\u94ae\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/code-copy.css */\n\n/* \u590d\u5236\u6309\u94ae\u5bb9\u5668 */\n.copy-button {\n  position: absolute;\n  right: 0.5rem;\n  top: 0.5rem;\n  padding: 0.4rem;\n  background-color: rgba(0, 0, 0, 0.1);\n  border: none;\n  border-radius: 4px;\n  cursor: pointer;\n  transition: all 0.2s ease;\n}\n\n/* \u6309\u94ae\u60ac\u505c\u6548\u679c */\n.copy-button:hover {\n  background-color: rgba(0, 0, 0, 0.2);\n}\n\n/* \u56fe\u6807\u6837\u5f0f */\n.copy-button i {\n  font-size: 1rem;\n  color: var(--md-default-fg-color--light);\n}\n\n/* \u6210\u529f\u72b6\u6001 */\n.copy-button.success {\n  background-color: var(--md-accent-fg-color);\n}\n\n.copy-button.success i {\n  color: white;\n}\n</code></pre> <ol> <li>\u5b9e\u73b0\u590d\u5236\u529f\u80fd\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/code-copy.js\ndocument.addEventListener('DOMContentLoaded', () =&gt; {\n  // \u4e3a\u6240\u6709\u4ee3\u7801\u5757\u6dfb\u52a0\u590d\u5236\u6309\u94ae\n  const codeBlocks = document.querySelectorAll('pre code');\n\n  codeBlocks.forEach((codeBlock) =&gt; {\n    const container = codeBlock.parentNode;\n    const copyButton = document.createElement('button');\n    copyButton.className = 'copy-button';\n    copyButton.innerHTML = '&lt;i class=\"material-icons\"&gt;content_copy&lt;/i&gt;';\n    container.style.position = 'relative';\n    container.appendChild(copyButton);\n\n    // \u6dfb\u52a0\u70b9\u51fb\u4e8b\u4ef6\n    copyButton.addEventListener('click', async () =&gt; {\n      try {\n        await navigator.clipboard.writeText(codeBlock.textContent);\n        showSuccess(copyButton);\n      } catch (err) {\n        showError(copyButton);\n      }\n    });\n  });\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6232","title":"6.2.3.2 \u63d0\u793a\u6d88\u606f","text":"<ol> <li>\u521b\u5efa\u63d0\u793a\u6d88\u606f\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* \u63d0\u793a\u6d88\u606f\u6837\u5f0f */\n.copy-tooltip {\n  position: absolute;\n  top: -2rem;\n  right: 0;\n  padding: 0.4rem 0.8rem;\n  background-color: var(--md-default-fg-color);\n  color: var(--md-default-bg-color);\n  border-radius: 4px;\n  font-size: 0.8rem;\n  opacity: 0;\n  transform: translateY(0.4rem);\n  transition: all 0.2s ease;\n}\n\n.copy-tooltip.show {\n  opacity: 1;\n  transform: translateY(0);\n}\n</code></pre> <ol> <li>\u5b9e\u73b0\u63d0\u793a\u529f\u80fd\uff1a</li> </ol> JavaScript<pre><code>// \u663e\u793a\u63d0\u793a\u6d88\u606f\nfunction showTooltip(button, message, type = 'success') {\n  const tooltip = document.createElement('div');\n  tooltip.className = `copy-tooltip ${type}`;\n  tooltip.textContent = message;\n  button.appendChild(tooltip);\n\n  // \u6dfb\u52a0\u663e\u793a\u7c7b\n  setTimeout(() =&gt; tooltip.classList.add('show'), 10);\n\n  // \u81ea\u52a8\u79fb\u9664\n  setTimeout(() =&gt; {\n    tooltip.classList.remove('show');\n    setTimeout(() =&gt; tooltip.remove(), 200);\n  }, 2000);\n}\n\n// \u6210\u529f\u63d0\u793a\nfunction showSuccess(button) {\n  button.classList.add('success');\n  showTooltip(button, '\u590d\u5236\u6210\u529f\uff01');\n  setTimeout(() =&gt; button.classList.remove('success'), 2000);\n}\n\n// \u9519\u8bef\u63d0\u793a\nfunction showError(button) {\n  button.classList.add('error');\n  showTooltip(button, '\u590d\u5236\u5931\u8d25\uff01', 'error');\n  setTimeout(() =&gt; button.classList.remove('error'), 2000);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6233","title":"6.2.3.3 \u590d\u5236\u56de\u8c03","text":"JavaScript<pre><code>// \u5b9a\u4e49\u590d\u5236\u4e8b\u4ef6\u5904\u7406\u5668\nconst copyHandlers = {\n  // \u590d\u5236\u524d\u5904\u7406\n  beforeCopy: (code) =&gt; {\n    // \u53ef\u4ee5\u5728\u8fd9\u91cc\u5bf9\u4ee3\u7801\u8fdb\u884c\u9884\u5904\u7406\n    return code.trim();\n  },\n\n  // \u590d\u5236\u6210\u529f\u56de\u8c03\n  onSuccess: (button, code) =&gt; {\n    console.log('Copied:', code.length, 'characters');\n    showSuccess(button);\n\n    // \u89e6\u53d1\u81ea\u5b9a\u4e49\u4e8b\u4ef6\n    const event = new CustomEvent('codeCopied', {\n      detail: { code }\n    });\n    document.dispatchEvent(event);\n  },\n\n  // \u590d\u5236\u5931\u8d25\u56de\u8c03\n  onError: (button, error) =&gt; {\n    console.error('Copy failed:', error);\n    showError(button);\n  }\n};\n\n// \u4f7f\u7528\u56de\u8c03\nasync function copyCode(button, code) {\n  try {\n    const processedCode = copyHandlers.beforeCopy(code);\n    await navigator.clipboard.writeText(processedCode);\n    copyHandlers.onSuccess(button, processedCode);\n  } catch (err) {\n    copyHandlers.onError(button, err);\n  }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#624","title":"6.2.4 \u56fe\u7247\u9884\u89c8","text":""},{"location":"Tools/Blog/Mkdocs_Material/#6241-lightbox","title":"6.2.4.1 lightbox \u914d\u7f6e","text":"<ol> <li>\u5728 <code>mkdocs.yml</code> \u4e2d\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>markdown_extensions:\n  - attr_list\n  - md_in_html\n\nplugins:\n  - glightbox\n\nextra_css:\n  - stylesheets/glightbox.css\nextra_javascript:\n  - javascripts/glightbox.js\n</code></pre> <ol> <li>\u914d\u7f6e GLightbox\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/glightbox.js\ndocument.addEventListener('DOMContentLoaded', () =&gt; {\n  const lightbox = GLightbox({\n    selector: '.glightbox',\n    touchNavigation: true,\n    loop: false,\n    autoplayVideos: true,\n    preload: true,\n    // \u57fa\u672c\u8bbe\u7f6e\n    height: 'auto',\n    zoomable: true,\n    draggable: true,\n    // \u52a8\u753b\u8bbe\u7f6e\n    openEffect: 'zoom',\n    closeEffect: 'fade',\n    cssEfects: {\n      fade: { in: 'fadeIn', out: 'fadeOut' },\n      zoom: { in: 'zoomIn', out: 'zoomOut' }\n    }\n  });\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6242","title":"6.2.4.2 \u7f29\u653e\u529f\u80fd","text":"JavaScript<pre><code>// \u7f29\u653e\u529f\u80fd\u914d\u7f6e\nconst zoomConfig = {\n  // \u7f29\u653e\u9009\u9879\n  zoomable: true,\n  dragToZoom: true,\n  touchToZoom: true,\n\n  // \u7f29\u653e\u7ea7\u522b\n  minZoom: 0.5,\n  maxZoom: 3,\n  zoomStep: 0.5,\n\n  // \u53cc\u51fb\u7f29\u653e\n  doubleTapZoom: 2,\n\n  // \u7f29\u653e\u52a8\u753b\n  zoomAnimation: true,\n  zoomDuration: 300,\n\n  // \u7f29\u653e\u63a7\u5236\u5668\n  controls: {\n    zoom: true,\n    zoomIn: true,\n    zoomOut: true,\n    rotate: true\n  }\n};\n\n// \u5e94\u7528\u7f29\u653e\u914d\u7f6e\nconst lightbox = GLightbox({\n  ...zoomConfig,\n\n  // \u7f29\u653e\u4e8b\u4ef6\u5904\u7406\n  onZoom: (slider) =&gt; {\n    const { zoom, image } = slider;\n    console.log(`Current zoom level: ${zoom}`);\n  }\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6243","title":"6.2.4.3 \u624b\u52bf\u652f\u6301","text":"JavaScript<pre><code>// \u624b\u52bf\u914d\u7f6e\nconst gestureConfig = {\n  // \u89e6\u6478\u5bfc\u822a\n  touchNavigation: true,\n  touchFollowAxis: true,\n\n  // \u62d6\u52a8\u8bbe\u7f6e\n  draggable: true,\n  dragToleranceX: 40,\n  dragToleranceY: 65,\n\n  // \u624b\u52bf\u4e8b\u4ef6\n  gestures: {\n    // \u634f\u5408\u7f29\u653e\n    pinchToZoom: true,\n    pinchThreshold: 50,\n\n    // \u53cc\u6307\u65cb\u8f6c\n    rotateToZoom: true,\n    rotateThreshold: 15,\n\n    // \u6ed1\u52a8\u5207\u6362\n    swipeThreshold: 50,\n    swipeToClose: true\n  }\n};\n\n// \u624b\u52bf\u4e8b\u4ef6\u5904\u7406\nconst gestureHandlers = {\n  // \u89e6\u6478\u5f00\u59cb\n  onTouchStart: (e) =&gt; {\n    const touch = e.touches[0];\n    startX = touch.clientX;\n    startY = touch.clientY;\n  },\n\n  // \u89e6\u6478\u79fb\u52a8\n  onTouchMove: (e) =&gt; {\n    if (!isDragging) return;\n    const touch = e.touches[0];\n    const deltaX = touch.clientX - startX;\n    const deltaY = touch.clientY - startY;\n\n    // \u5904\u7406\u79fb\u52a8\n    handleImageMove(deltaX, deltaY);\n  },\n\n  // \u89e6\u6478\u7ed3\u675f\n  onTouchEnd: (e) =&gt; {\n    isDragging = false;\n    // \u5904\u7406\u60ef\u6027\u6ed1\u52a8\n    handleMomentum();\n  }\n};\n\n// \u521b\u5efa\u589e\u5f3a\u7684\u56fe\u7247\u9884\u89c8\nconst enhancedLightbox = GLightbox({\n  ...zoomConfig,\n  ...gestureConfig,\n\n  // \u4e8b\u4ef6\u76d1\u542c\n  listeners: {\n    touchstart: gestureHandlers.onTouchStart,\n    touchmove: gestureHandlers.onTouchMove,\n    touchend: gestureHandlers.onTouchEnd\n  }\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6244","title":"6.2.4.4 \u5b8c\u6574\u793a\u4f8b","text":"JavaScript<pre><code>// docs/javascripts/image-preview.js\ndocument.addEventListener('DOMContentLoaded', () =&gt; {\n  // \u521d\u59cb\u5316\u914d\u7f6e\n  const config = {\n    // \u57fa\u7840\u8bbe\u7f6e\n    selector: '.glightbox',\n    touchNavigation: true,\n    loop: false,\n\n    // \u7f29\u653e\u8bbe\u7f6e\n    zoomable: true,\n    draggable: true,\n    dragToleranceX: 40,\n    dragToleranceY: 65,\n\n    // \u52a8\u753b\u8bbe\u7f6e\n    openEffect: 'zoom',\n    closeEffect: 'fade',\n\n    // \u624b\u52bf\u8bbe\u7f6e\n    touchFollowAxis: true,\n\n    // \u754c\u9762\u8bbe\u7f6e\n    preload: true,\n    height: 'auto',\n\n    // \u4e8b\u4ef6\u5904\u7406\n    onOpen: () =&gt; {\n      console.log('Lightbox opened');\n    },\n    onClose: () =&gt; {\n      console.log('Lightbox closed');\n    },\n    onZoom: (slider) =&gt; {\n      console.log('Image zoomed');\n    }\n  };\n\n  // \u521d\u59cb\u5316 GLightbox\n  const lightbox = GLightbox(config);\n\n  // \u6dfb\u52a0\u952e\u76d8\u652f\u6301\n  document.addEventListener('keydown', (e) =&gt; {\n    if (!lightbox.isOpen) return;\n\n    switch(e.key) {\n      case 'ArrowLeft':\n        lightbox.prev();\n        break;\n      case 'ArrowRight':\n        lightbox.next();\n        break;\n      case 'Escape':\n        lightbox.close();\n        break;\n    }\n  });\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#63","title":"6.3 \u81ea\u5b9a\u4e49\u529f\u80fd","text":""},{"location":"Tools/Blog/Mkdocs_Material/#631","title":"6.3.1 \u9875\u9762\u4ea4\u4e92","text":""},{"location":"Tools/Blog/Mkdocs_Material/#6311","title":"6.3.1.1 \u6eda\u52a8\u4e8b\u4ef6","text":"<ol> <li>\u57fa\u7840\u6eda\u52a8\u76d1\u542c\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/scroll.js\ndocument.addEventListener('DOMContentLoaded', function() {\n    // \u6eda\u52a8\u5904\u7406\u51fd\u6570\n    function handleScroll() {\n        const scrollTop = window.scrollY;\n        const windowHeight = window.innerHeight;\n        const docHeight = document.documentElement.scrollHeight;\n\n        // \u6eda\u52a8\u8fdb\u5ea6\n        const scrollPercent = (scrollTop / (docHeight - windowHeight)) * 100;\n\n        // \u66f4\u65b0\u8fdb\u5ea6\u6761\n        updateProgress(scrollPercent);\n\n        // \u5904\u7406\u5143\u7d20\u53ef\u89c1\u6027\n        handleVisibility();\n    }\n\n    // \u4f7f\u7528\u8282\u6d41\u4f18\u5316\u6eda\u52a8\u4e8b\u4ef6\n    const throttledScroll = throttle(handleScroll, 100);\n    window.addEventListener('scroll', throttledScroll);\n});\n\n// \u8282\u6d41\u51fd\u6570\nfunction throttle(fn, delay) {\n    let lastCall = 0;\n    return function(...args) {\n        const now = Date.now();\n        if (now - lastCall &gt;= delay) {\n            lastCall = now;\n            fn.apply(this, args);\n        }\n    };\n}\n</code></pre> <ol> <li>\u5143\u7d20\u53ef\u89c1\u6027\u68c0\u6d4b\uff1a</li> </ol> JavaScript<pre><code>// \u68c0\u6d4b\u5143\u7d20\u662f\u5426\u8fdb\u5165\u89c6\u53e3\nfunction handleVisibility() {\n    const elements = document.querySelectorAll('.animate-on-scroll');\n\n    elements.forEach(element =&gt; {\n        const rect = element.getBoundingClientRect();\n        const isVisible = (\n            rect.top &gt;= 0 &amp;&amp;\n            rect.left &gt;= 0 &amp;&amp;\n            rect.bottom &lt;= window.innerHeight &amp;&amp;\n            rect.right &lt;= window.innerWidth\n        );\n\n        if (isVisible) {\n            element.classList.add('is-visible');\n        }\n    });\n}\n\n// CSS \u6837\u5f0f\n.animate-on-scroll {\n    opacity: 0;\n    transform: translateY(20px);\n    transition: all 0.6s ease;\n}\n\n.animate-on-scroll.is-visible {\n    opacity: 1;\n    transform: translateY(0);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6312","title":"6.3.1.2 \u70b9\u51fb\u4e8b\u4ef6","text":"<ol> <li>\u70b9\u51fb\u5904\u7406\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/click.js\ndocument.addEventListener('DOMContentLoaded', function() {\n    // \u4ee3\u7801\u5757\u70b9\u51fb\u590d\u5236\n    setupCodeCopy();\n\n    // \u56fe\u7247\u70b9\u51fb\u653e\u5927\n    setupImageZoom();\n\n    // \u76ee\u5f55\u70b9\u51fb\u6eda\u52a8\n    setupTocScroll();\n});\n\n// \u4ee3\u7801\u590d\u5236\u529f\u80fd\nfunction setupCodeCopy() {\n    const codeBlocks = document.querySelectorAll('pre code');\n\n    codeBlocks.forEach(block =&gt; {\n        block.addEventListener('click', async function(e) {\n            if (e.target.classList.contains('copy-button')) {\n                try {\n                    await navigator.clipboard.writeText(block.textContent);\n                    showToast('\u590d\u5236\u6210\u529f\uff01');\n                } catch (err) {\n                    showToast('\u590d\u5236\u5931\u8d25', 'error');\n                }\n            }\n        });\n    });\n}\n\n// \u56fe\u7247\u7f29\u653e\u529f\u80fd\nfunction setupImageZoom() {\n    const images = document.querySelectorAll('.md-content img');\n\n    images.forEach(img =&gt; {\n        img.addEventListener('click', function() {\n            const overlay = document.createElement('div');\n            overlay.className = 'image-overlay';\n            overlay.innerHTML = `\n                &lt;img src=\"${img.src}\" alt=\"${img.alt}\"&gt;\n                &lt;button class=\"close-button\"&gt;\u00d7&lt;/button&gt;\n            `;\n\n            document.body.appendChild(overlay);\n\n            overlay.querySelector('.close-button').addEventListener('click', () =&gt; {\n                overlay.remove();\n            });\n        });\n    });\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6313","title":"6.3.1.3 \u952e\u76d8\u4e8b\u4ef6","text":"JavaScript<pre><code>// docs/javascripts/keyboard.js\ndocument.addEventListener('DOMContentLoaded', function() {\n    // \u952e\u76d8\u5bfc\u822a\n    setupKeyboardNav();\n\n    // \u641c\u7d22\u5feb\u6377\u952e\n    setupSearchShortcut();\n});\n\n// \u952e\u76d8\u5bfc\u822a\nfunction setupKeyboardNav() {\n    document.addEventListener('keydown', function(e) {\n        // ALT + \u65b9\u5411\u952e\u5bfc\u822a\n        if (e.altKey) {\n            switch(e.key) {\n                case 'ArrowLeft':  // \u4e0a\u4e00\u9875\n                    navigatePage('prev');\n                    break;\n                case 'ArrowRight':  // \u4e0b\u4e00\u9875\n                    navigatePage('next');\n                    break;\n                case 'ArrowUp':    // \u56de\u5230\u9876\u90e8\n                    window.scrollTo({top: 0, behavior: 'smooth'});\n                    break;\n                case 'ArrowDown':  // \u5230\u8fbe\u5e95\u90e8\n                    window.scrollTo({\n                        top: document.documentElement.scrollHeight,\n                        behavior: 'smooth'\n                    });\n                    break;\n            }\n        }\n    });\n}\n\n// \u641c\u7d22\u5feb\u6377\u952e\nfunction setupSearchShortcut() {\n    document.addEventListener('keydown', function(e) {\n        // \u6309\u4e0b '/' \u952e\u89e6\u53d1\u641c\u7d22\n        if (e.key === '/' &amp;&amp; !e.ctrlKey &amp;&amp; !e.altKey &amp;&amp; !e.metaKey) {\n            e.preventDefault();\n            const searchInput = document.querySelector('.md-search__input');\n            if (searchInput) {\n                searchInput.focus();\n            }\n        }\n    });\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#632","title":"6.3.2 \u52a8\u753b\u6548\u679c","text":""},{"location":"Tools/Blog/Mkdocs_Material/#6321","title":"6.3.2.1 \u8fc7\u6e21\u52a8\u753b","text":"<ol> <li>\u57fa\u7840\u8fc7\u6e21\u6548\u679c\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/transitions.css */\n\n/* \u9875\u9762\u5207\u6362\u8fc7\u6e21 */\n.md-content {\n    animation: fadeIn 0.3s ease-in-out;\n}\n\n@keyframes fadeIn {\n    from {\n        opacity: 0;\n        transform: translateY(20px);\n    }\n    to {\n        opacity: 1;\n        transform: translateY(0);\n    }\n}\n\n/* \u5bfc\u822a\u8fc7\u6e21 */\n.md-nav__link {\n    transition: color 0.2s ease, padding-left 0.2s ease;\n}\n\n.md-nav__link:hover {\n    padding-left: 0.5rem;\n    color: var(--md-accent-fg-color);\n}\n</code></pre> <ol> <li>\u9875\u9762\u5207\u6362\u52a8\u753b\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/transitions.js\ndocument.addEventListener('DOMContentLoaded', function() {\n    // \u9875\u9762\u5207\u6362\u52a8\u753b\n    setupPageTransitions();\n});\n\nfunction setupPageTransitions() {\n    // \u76d1\u542c\u9875\u9762\u5207\u6362\u4e8b\u4ef6\n    document.addEventListener('DOMContentLoaded', function() {\n        document.body.classList.add('page-transition-ready');\n    });\n\n    // \u9875\u9762\u79bb\u5f00\u52a8\u753b\n    window.addEventListener('beforeunload', function() {\n        document.body.classList.add('page-transition-exit');\n    });\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6322","title":"6.3.2.2 \u52a0\u8f7d\u52a8\u753b","text":"<ol> <li>\u521b\u5efa\u52a0\u8f7d\u52a8\u753b\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/loading.css */\n\n/* \u52a0\u8f7d\u52a8\u753b\u5bb9\u5668 */\n.loading-overlay {\n    position: fixed;\n    top: 0;\n    left: 0;\n    right: 0;\n    bottom: 0;\n    background-color: var(--md-default-bg-color);\n    display: flex;\n    justify-content: center;\n    align-items: center;\n    z-index: 999;\n    opacity: 1;\n    transition: opacity 0.3s ease;\n}\n\n/* \u52a0\u8f7d\u52a8\u753b */\n.loading-spinner {\n    width: 40px;\n    height: 40px;\n    border: 3px solid var(--md-primary-fg-color--light);\n    border-top-color: var(--md-primary-fg-color);\n    border-radius: 50%;\n    animation: spin 1s linear infinite;\n}\n\n@keyframes spin {\n    to { transform: rotate(360deg); }\n}\n</code></pre> <ol> <li>\u5b9e\u73b0\u52a0\u8f7d\u903b\u8f91\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/loading.js\nclass LoadingManager {\n    constructor() {\n        this.overlay = null;\n        this.createLoadingOverlay();\n    }\n\n    createLoadingOverlay() {\n        this.overlay = document.createElement('div');\n        this.overlay.className = 'loading-overlay';\n        this.overlay.innerHTML = '&lt;div class=\"loading-spinner\"&gt;&lt;/div&gt;';\n        document.body.appendChild(this.overlay);\n    }\n\n    show() {\n        this.overlay.style.opacity = '1';\n        this.overlay.style.visibility = 'visible';\n    }\n\n    hide() {\n        this.overlay.style.opacity = '0';\n        setTimeout(() =&gt; {\n            this.overlay.style.visibility = 'hidden';\n        }, 300);\n    }\n}\n\n// \u4f7f\u7528\u52a0\u8f7d\u7ba1\u7406\u5668\nconst loading = new LoadingManager();\n\n// \u9875\u9762\u52a0\u8f7d\u5b8c\u6210\u540e\u9690\u85cf\nwindow.addEventListener('load', () =&gt; {\n    loading.hide();\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6323","title":"6.3.2.3 \u4ea4\u4e92\u52a8\u753b","text":"<ol> <li>\u5143\u7d20\u4ea4\u4e92\u52a8\u753b\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/interactions.js\ndocument.addEventListener('DOMContentLoaded', function() {\n    // \u6309\u94ae\u6ce2\u7eb9\u6548\u679c\n    setupRippleEffect();\n\n    // \u5361\u7247\u60ac\u6d6e\u6548\u679c\n    setupCardHover();\n\n    // \u5217\u8868\u9879\u52a8\u753b\n    setupListAnimations();\n});\n\n// \u6ce2\u7eb9\u6548\u679c\nfunction setupRippleEffect() {\n    const buttons = document.querySelectorAll('.md-button');\n\n    buttons.forEach(button =&gt; {\n        button.addEventListener('click', function(e) {\n            const ripple = document.createElement('div');\n            ripple.className = 'ripple';\n\n            const rect = button.getBoundingClientRect();\n            const size = Math.max(rect.width, rect.height);\n\n            ripple.style.width = ripple.style.height = `${size}px`;\n            ripple.style.left = `${e.clientX - rect.left - size/2}px`;\n            ripple.style.top = `${e.clientY - rect.top - size/2}px`;\n\n            button.appendChild(ripple);\n\n            setTimeout(() =&gt; ripple.remove(), 600);\n        });\n    });\n}\n\n// \u5361\u7247\u60ac\u6d6e\u6548\u679c\nfunction setupCardHover() {\n    const cards = document.querySelectorAll('.md-card');\n\n    cards.forEach(card =&gt; {\n        card.addEventListener('mousemove', function(e) {\n            const rect = card.getBoundingClientRect();\n            const x = e.clientX - rect.left;\n            const y = e.clientY - rect.top;\n\n            const centerX = rect.width / 2;\n            const centerY = rect.height / 2;\n\n            const angleY = -(x - centerX) / 20;\n            const angleX = (y - centerY) / 20;\n\n            card.style.transform = \n                `perspective(1000px) rotateX(${angleX}deg) rotateY(${angleY}deg)`;\n        });\n\n        card.addEventListener('mouseleave', function() {\n            card.style.transform = 'perspective(1000px) rotateX(0) rotateY(0)';\n        });\n    });\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#633","title":"6.3.3 \u6570\u636e\u7edf\u8ba1","text":""},{"location":"Tools/Blog/Mkdocs_Material/#6331","title":"6.3.3.1 \u8bbf\u95ee\u7edf\u8ba1","text":"<ol> <li>\u57fa\u7840\u8bbf\u95ee\u7edf\u8ba1\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/analytics.js\nclass Analytics {\n    constructor() {\n        this.storageKey = 'site_analytics';\n        this.data = this.loadData();\n    }\n\n    loadData() {\n        const stored = localStorage.getItem(this.storageKey);\n        return stored ? JSON.parse(stored) : {\n            pageViews: {},\n            totalVisits: 0,\n            firstVisit: Date.now(),\n            lastVisit: Date.now()\n        };\n    }\n\n    saveData() {\n        localStorage.setItem(this.storageKey, JSON.stringify(this.data));\n    }\n\n    recordPageView() {\n        const path = window.location.pathname;\n        this.data.pageViews[path] = (this.data.pageViews[path] || 0) + 1;\n        this.data.totalVisits++;\n        this.data.lastVisit = Date.now();\n        this.saveData();\n    }\n\n    getStats() {\n        return {\n            totalVisits: this.data.totalVisits,\n            uniquePages: Object.keys(this.data.pageViews).length,\n            mostViewed: this.getMostViewedPages(5)\n        };\n    }\n\n    getMostViewedPages(limit = 5) {\n        return Object.entries(this.data.pageViews)\n            .sort(([,a], [,b]) =&gt; b - a)\n            .slice(0, limit);\n    }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6332","title":"6.3.3.2 \u9605\u8bfb\u65f6\u957f","text":"JavaScript<pre><code>// docs/javascripts/read-time.js\nclass ReadTimeTracker {\n    constructor() {\n        this.startTime = Date.now();\n        this.isReading = true;\n        this.totalTime = 0;\n        this.idleTimeout = null;\n        this.setupTracking();\n    }\n\n    setupTracking() {\n        // \u76d1\u542c\u7528\u6237\u6d3b\u52a8\n        ['mousemove', 'keydown', 'scroll', 'click'].forEach(event =&gt; {\n            document.addEventListener(event, () =&gt; this.handleActivity());\n        });\n\n        // \u9875\u9762\u5931\u7126\u6682\u505c\u8ba1\u65f6\n        document.addEventListener('visibilitychange', () =&gt; {\n            if (document.hidden) {\n                this.pauseTracking();\n            } else {\n                this.resumeTracking();\n            }\n        });\n    }\n\n    handleActivity() {\n        if (!this.isReading) {\n            this.resumeTracking();\n        }\n\n        clearTimeout(this.idleTimeout);\n        this.idleTimeout = setTimeout(() =&gt; this.pauseTracking(), 60000); // 1\u5206\u949f\u65e0\u6d3b\u52a8\u6682\u505c\n    }\n\n    pauseTracking() {\n        if (this.isReading) {\n            this.totalTime += Date.now() - this.startTime;\n            this.isReading = false;\n        }\n    }\n\n    resumeTracking() {\n        if (!this.isReading) {\n            this.startTime = Date.now();\n            this.isReading = true;\n        }\n    }\n\n    getReadTime() {\n        const currentTime = this.isReading ? \n            this.totalTime + (Date.now() - this.startTime) : \n            this.totalTime;\n\n        return Math.floor(currentTime / 1000 / 60); // \u8fd4\u56de\u5206\u949f\n    // \u663e\u793a\u9605\u8bfb\u65f6\u957f\n    displayReadTime() {\n        const readTimeElement = document.querySelector('.read-time');\n        if (readTimeElement) {\n            const minutes = this.getReadTime();\n            readTimeElement.textContent = `\u9605\u8bfb\u65f6\u957f: ${minutes} \u5206\u949f`;\n        }\n    }\n\n    // \u83b7\u53d6\u9605\u8bfb\u8fdb\u5ea6\n    getReadProgress() {\n        const windowHeight = window.innerHeight;\n        const docHeight = document.documentElement.scrollHeight - windowHeight;\n        const scrollTop = window.pageYOffset || document.documentElement.scrollTop;\n        return Math.min((scrollTop / docHeight) * 100, 100);\n    }\n\n    // \u4fdd\u5b58\u9605\u8bfb\u8bb0\u5f55\n    saveReadingHistory() {\n        const path = window.location.pathname;\n        const history = JSON.parse(localStorage.getItem('reading_history') || '{}');\n\n        history[path] = {\n            lastRead: Date.now(),\n            readTime: this.getReadTime(),\n            progress: this.getReadProgress()\n        };\n\n        localStorage.setItem('reading_history', JSON.stringify(history));\n    }\n}\n\n// \u521d\u59cb\u5316\u9605\u8bfb\u65f6\u957f\u8ffd\u8e2a\nconst readTracker = new ReadTimeTracker();\n\n// \u5b9a\u671f\u66f4\u65b0\u663e\u793a\nsetInterval(() =&gt; {\n    readTracker.displayReadTime();\n}, 30000); // \u6bcf30\u79d2\u66f4\u65b0\u4e00\u6b21\n\n// \u9875\u9762\u79bb\u5f00\u65f6\u4fdd\u5b58\u8bb0\u5f55\nwindow.addEventListener('beforeunload', () =&gt; {\n    readTracker.saveReadingHistory();\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6333","title":"6.3.3.3 \u5206\u4eab\u7edf\u8ba1","text":"<ol> <li>\u5206\u4eab\u529f\u80fd\u548c\u7edf\u8ba1\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/share.js\nclass ShareTracker {\n    constructor() {\n        this.storageKey = 'share_statistics';\n        this.data = this.loadData();\n        this.setupShareButtons();\n    }\n\n    loadData() {\n        return JSON.parse(localStorage.getItem(this.storageKey) || '{}');\n    }\n\n    saveData() {\n        localStorage.setItem(this.storageKey, JSON.stringify(this.data));\n    }\n\n    setupShareButtons() {\n        const shareButtons = document.querySelectorAll('.share-button');\n\n        shareButtons.forEach(button =&gt; {\n            button.addEventListener('click', (e) =&gt; {\n                const platform = button.dataset.platform;\n                this.shareContent(platform);\n                this.recordShare(platform);\n            });\n        });\n    }\n\n    shareContent(platform) {\n        const url = encodeURIComponent(window.location.href);\n        const title = encodeURIComponent(document.title);\n        const description = encodeURIComponent(\n            document.querySelector('meta[name=\"description\"]')?.content || ''\n        );\n\n        let shareUrl;\n        switch (platform) {\n            case 'twitter':\n                shareUrl = `https://twitter.com/intent/tweet?url=${url}&amp;text=${title}`;\n                break;\n            case 'facebook':\n                shareUrl = `https://www.facebook.com/sharer/sharer.php?u=${url}`;\n                break;\n            case 'linkedin':\n                shareUrl = `https://www.linkedin.com/sharing/share-offsite/?url=${url}`;\n                break;\n            case 'weibo':\n                shareUrl = `http://service.weibo.com/share/share.php?url=${url}&amp;title=${title}`;\n                break;\n        }\n\n        if (shareUrl) {\n            window.open(shareUrl, '_blank', 'width=600,height=400');\n        }\n    }\n\n    recordShare(platform) {\n        const path = window.location.pathname;\n        if (!this.data[path]) {\n            this.data[path] = {};\n        }\n        if (!this.data[path][platform]) {\n            this.data[path][platform] = 0;\n        }\n        this.data[path][platform]++;\n        this.saveData();\n        this.updateShareCount(platform);\n    }\n\n    updateShareCount(platform) {\n        const countElement = document.querySelector(`.share-count[data-platform=\"${platform}\"]`);\n        if (countElement) {\n            const path = window.location.pathname;\n            countElement.textContent = this.data[path][platform] || 0;\n        }\n    }\n\n    getShareStats() {\n        return Object.entries(this.data).map(([path, platforms]) =&gt; ({\n            path,\n            total: Object.values(platforms).reduce((a, b) =&gt; a + b, 0),\n            platforms\n        }));\n    }\n\n    displayShareStats() {\n        const stats = this.getShareStats();\n        console.table(stats);\n        return stats;\n    }\n}\n</code></pre> <ol> <li>\u7edf\u8ba1\u6570\u636e\u53ef\u89c6\u5316\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/statistics-visualization.js\nclass StatisticsVisualizer {\n    constructor(analytics, readTracker, shareTracker) {\n        this.analytics = analytics;\n        this.readTracker = readTracker;\n        this.shareTracker = shareTracker;\n    }\n\n    createDashboard() {\n        const dashboard = document.createElement('div');\n        dashboard.className = 'statistics-dashboard';\n        dashboard.innerHTML = `\n            &lt;div class=\"dashboard-section\"&gt;\n                &lt;h3&gt;\u8bbf\u95ee\u7edf\u8ba1&lt;/h3&gt;\n                &lt;div class=\"stats-grid\"&gt;\n                    &lt;div class=\"stat-card\"&gt;\n                        &lt;div class=\"stat-value\"&gt;${this.analytics.data.totalVisits}&lt;/div&gt;\n                        &lt;div class=\"stat-label\"&gt;\u603b\u8bbf\u95ee\u91cf&lt;/div&gt;\n                    &lt;/div&gt;\n                    &lt;div class=\"stat-card\"&gt;\n                        &lt;div class=\"stat-value\"&gt;${this.readTracker.getReadTime()}&lt;/div&gt;\n                        &lt;div class=\"stat-label\"&gt;\u603b\u9605\u8bfb\u65f6\u957f(\u5206\u949f)&lt;/div&gt;\n                    &lt;/div&gt;\n                    &lt;div class=\"stat-card\"&gt;\n                        &lt;div class=\"stat-value\"&gt;${this.getTotalShares()}&lt;/div&gt;\n                        &lt;div class=\"stat-label\"&gt;\u603b\u5206\u4eab\u6b21\u6570&lt;/div&gt;\n                    &lt;/div&gt;\n                &lt;/div&gt;\n                &lt;div id=\"visitsChart\"&gt;&lt;/div&gt;\n            &lt;/div&gt;\n        `;\n\n        document.body.appendChild(dashboard);\n        this.renderCharts();\n    }\n\n    renderCharts() {\n        // \u4f7f\u7528 Chart.js \u7ed8\u5236\u56fe\u8868\n        const ctx = document.getElementById('visitsChart').getContext('2d');\n        new Chart(ctx, {\n            type: 'line',\n            data: {\n                labels: this.getTimeLabels(),\n                datasets: [{\n                    label: '\u8bbf\u95ee\u8d8b\u52bf',\n                    data: this.getVisitData(),\n                    borderColor: 'rgb(75, 192, 192)',\n                    tension: 0.1\n                }]\n            },\n            options: {\n                responsive: true,\n                scales: {\n                    y: {\n                        beginAtZero: true\n                    }\n                }\n            }\n        });\n    }\n\n    getTotalShares() {\n        const stats = this.shareTracker.getShareStats();\n        return stats.reduce((total, page) =&gt; total + page.total, 0);\n    }\n\n    getTimeLabels() {\n        // \u83b7\u53d6\u6700\u8fd17\u5929\u7684\u65e5\u671f\u6807\u7b7e\n        return Array.from({length: 7}, (_, i) =&gt; {\n            const d = new Date();\n            d.setDate(d.getDate() - i);\n            return d.toLocaleDateString();\n        }).reverse();\n    }\n\n    getVisitData() {\n        // \u5904\u7406\u8bbf\u95ee\u6570\u636e\n        return this.analytics.getVisitsByDate(7);\n    }\n}\n\n// \u6837\u5f0f\nconst styles = `\n    .statistics-dashboard {\n        padding: 2rem;\n        background: var(--md-default-bg-color);\n        border-radius: 8px;\n        box-shadow: var(--md-shadow-z2);\n    }\n\n    .stats-grid {\n        display: grid;\n        grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));\n        gap: 1rem;\n        margin: 1rem 0;\n    }\n\n    .stat-card {\n        padding: 1rem;\n        background: var(--md-code-bg-color);\n        border-radius: 4px;\n        text-align: center;\n    }\n\n    .stat-value {\n        font-size: 2rem;\n        font-weight: bold;\n        color: var(--md-primary-fg-color);\n    }\n\n    .stat-label {\n        font-size: 0.9rem;\n        color: var(--md-default-fg-color--light);\n        margin-top: 0.5rem;\n    }\n`;\n\n// \u5c06\u6837\u5f0f\u6dfb\u52a0\u5230\u6587\u6863\nconst styleSheet = document.createElement('style');\nstyleSheet.textContent = styles;\ndocument.head.appendChild(styleSheet);\n\n// \u521d\u59cb\u5316\u7edf\u8ba1\u53ef\u89c6\u5316\nconst visualizer = new StatisticsVisualizer(analytics, readTracker, shareTracker);\nvisualizer.createDashboard();\n</code></pre> <p>\u8fd9\u6837\u6211\u4eec\u5c31\u5b8c\u6210\u4e86\u5b8c\u6574\u7684\u6570\u636e\u7edf\u8ba1\u7cfb\u7edf\uff0c\u5305\u62ec\uff1a</p> <ol> <li>\u8bbf\u95ee\u7edf\u8ba1</li> <li>\u9605\u8bfb\u65f6\u957f\u8ffd\u8e2a</li> <li>\u5206\u4eab\u7edf\u8ba1</li> <li>\u6570\u636e\u53ef\u89c6\u5316\u5c55\u793a</li> </ol> <p>\u4f7f\u7528\u65f6\uff0c\u53ea\u9700\u8981\u5728 mkdocs.yml \u4e2d\u6dfb\u52a0\u76f8\u5e94\u7684 JavaScript \u6587\u4ef6\uff1a</p> YAML<pre><code>extra_javascript:\n  - javascripts/analytics.js\n  - javascripts/read-time.js\n  - javascripts/share.js\n  - javascripts/statistics-visualization.js\n  - https://cdn.jsdelivr.net/npm/chart.js\n</code></pre> <p>\u7136\u540e\u5728\u9875\u9762\u4e2d\u6dfb\u52a0\u5fc5\u8981\u7684 HTML \u5143\u7d20\u5373\u53ef\u542f\u7528\u8fd9\u4e9b\u529f\u80fd\u3002</p>"},{"location":"Tools/Blog/Mkdocs_Material/#7","title":"7 \u6a21\u677f\u590d\u5199","text":""},{"location":"Tools/Blog/Mkdocs_Material/#71","title":"7.1 \u91cd\u5199\u9875\u9762\u6a21\u677f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#711","title":"7.1.1 \u4e3b\u9875\u6a21\u677f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#7111","title":"7.1.1.1 \u5e03\u5c40\u7ed3\u6784","text":"<ol> <li>\u521b\u5efa\u81ea\u5b9a\u4e49\u4e3b\u9875\u6a21\u677f\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/main.html --&gt;\n{% extends \"base.html\" %}\n\n{% block hero %}\n&lt;section class=\"home-hero\"&gt;\n    &lt;div class=\"hero-content\"&gt;\n        &lt;h1&gt;{{ config.site_name }}&lt;/h1&gt;\n        &lt;p&gt;{{ config.site_description }}&lt;/p&gt;\n\n        &lt;!-- \u81ea\u5b9a\u4e49\u641c\u7d22\u6846 --&gt;\n        &lt;div class=\"hero-search\"&gt;\n            &lt;input type=\"text\" placeholder=\"\u641c\u7d22\u6587\u6863...\" id=\"hero-search-input\"&gt;\n            &lt;button&gt;\n                &lt;span class=\"twemoji\"&gt;\n                    {% include \".icons/material/magnify.svg\" %}\n                &lt;/span&gt;\n            &lt;/button&gt;\n        &lt;/div&gt;\n\n        &lt;!-- \u5feb\u901f\u5165\u53e3 --&gt;\n        &lt;div class=\"hero-buttons\"&gt;\n            &lt;a href=\"{{ page.next_page.url | url }}\" class=\"md-button md-button--primary\"&gt;\n                \u5feb\u901f\u5f00\u59cb\n                &lt;span class=\"twemoji\"&gt;\n                    {% include \".icons/material/arrow-right.svg\" %}\n                &lt;/span&gt;\n            &lt;/a&gt;\n            &lt;a href=\"{{ config.repo_url }}\" class=\"md-button\"&gt;\n                \u67e5\u770b\u6e90\u7801\n                &lt;span class=\"twemoji\"&gt;\n                    {% include \".icons/material/github.svg\" %}\n                &lt;/span&gt;\n            &lt;/a&gt;\n        &lt;/div&gt;\n    &lt;/div&gt;\n&lt;/section&gt;\n{% endblock %}\n\n{% block content %}\n&lt;section class=\"home-features\"&gt;\n    &lt;h2&gt;\u7279\u8272\u529f\u80fd&lt;/h2&gt;\n    &lt;div class=\"features-grid\"&gt;\n        &lt;!-- \u529f\u80fd\u5361\u7247 --&gt;\n        &lt;div class=\"feature-card\"&gt;\n            &lt;div class=\"feature-icon\"&gt;\n                {% include \".icons/material/speedometer.svg\" %}\n            &lt;/div&gt;\n            &lt;h3&gt;\u9ad8\u6027\u80fd&lt;/h3&gt;\n            &lt;p&gt;\u57fa\u4e8e\u9759\u6001\u7ad9\u70b9\u751f\u6210\uff0c\u52a0\u8f7d\u8fc5\u901f&lt;/p&gt;\n        &lt;/div&gt;\n        &lt;!-- \u66f4\u591a\u529f\u80fd\u5361\u7247 --&gt;\n    &lt;/div&gt;\n&lt;/section&gt;\n\n&lt;!-- \u6700\u8fd1\u66f4\u65b0 --&gt;\n&lt;section class=\"home-updates\"&gt;\n    &lt;h2&gt;\u6700\u8fd1\u66f4\u65b0&lt;/h2&gt;\n    &lt;div class=\"updates-list\"&gt;\n        {% for update in config.theme.updates[:5] %}\n        &lt;div class=\"update-item\"&gt;\n            &lt;span class=\"update-date\"&gt;{{ update.date }}&lt;/span&gt;\n            &lt;a href=\"{{ update.url | url }}\"&gt;{{ update.title }}&lt;/a&gt;\n        &lt;/div&gt;\n        {% endfor %}\n    &lt;/div&gt;\n&lt;/section&gt;\n{% endblock %}\n</code></pre> <ol> <li>\u4e3b\u9875\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/home.css */\n\n/* \u4e3b\u9875\u82f1\u96c4\u533a */\n.home-hero {\n    min-height: 100vh;\n    display: flex;\n    align-items: center;\n    justify-content: center;\n    text-align: center;\n    background: linear-gradient(\n        to bottom right,\n        var(--md-primary-fg-color),\n        var(--md-accent-fg-color)\n    );\n    color: var(--md-primary-bg-color);\n}\n\n.hero-content {\n    max-width: 800px;\n    padding: 2rem;\n}\n\n.hero-content h1 {\n    font-size: 3rem;\n    margin-bottom: 1rem;\n}\n\n/* \u641c\u7d22\u6846\u6837\u5f0f */\n.hero-search {\n    margin: 2rem 0;\n    position: relative;\n}\n\n.hero-search input {\n    width: 100%;\n    padding: 1rem 3rem 1rem 1rem;\n    border: none;\n    border-radius: 2rem;\n    background: rgba(255, 255, 255, 0.1);\n    color: white;\n    backdrop-filter: blur(10px);\n}\n\n/* \u529f\u80fd\u533a\u6837\u5f0f */\n.features-grid {\n    display: grid;\n    grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));\n    gap: 2rem;\n    padding: 2rem;\n}\n\n.feature-card {\n    padding: 2rem;\n    background: var(--md-default-bg-color);\n    border-radius: 8px;\n    box-shadow: var(--md-shadow-z1);\n    transition: transform 0.3s ease;\n}\n\n.feature-card:hover {\n    transform: translateY(-4px);\n}\n\n/* \u66f4\u65b0\u5217\u8868\u6837\u5f0f */\n.updates-list {\n    max-width: 800px;\n    margin: 0 auto;\n    padding: 2rem;\n}\n\n.update-item {\n    display: flex;\n    align-items: center;\n    padding: 1rem;\n    border-bottom: 1px solid var(--md-default-fg-color--lightest);\n}\n\n/* \u54cd\u5e94\u5f0f\u9002\u914d */\n@media screen and (max-width: 76.1875em) {\n    .hero-content h1 {\n        font-size: 2rem;\n    }\n\n    .features-grid {\n        grid-template-columns: 1fr;\n    }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#7112","title":"7.1.1.2 \u7ec4\u4ef6\u914d\u7f6e","text":"<ol> <li>\u5728 <code>mkdocs.yml</code> \u4e2d\u914d\u7f6e\u4e3b\u9898\uff1a</li> </ol> YAML<pre><code>theme:\n  name: material\n  custom_dir: docs/overrides\n  features:\n    - navigation.tabs\n    - navigation.sections\n    - navigation.expand\n\n  # \u4e3b\u9875\u914d\u7f6e\n  homepage:\n    hero:\n      title: \u7f51\u7ad9\u6807\u9898\n      subtitle: \u7f51\u7ad9\u63cf\u8ff0\n      image: assets/hero.svg\n\n    # \u529f\u80fd\u7279\u6027\n    features:\n      - title: \u9ad8\u6027\u80fd\n        description: \u57fa\u4e8e\u9759\u6001\u7ad9\u70b9\u751f\u6210\uff0c\u52a0\u8f7d\u8fc5\u901f\n        icon: material/speedometer\n      - title: \u6613\u4e8e\u4f7f\u7528\n        description: \u7b80\u5355\u7684\u914d\u7f6e\uff0c\u5feb\u901f\u4e0a\u624b\n        icon: material/puzzle\n      # \u66f4\u591a\u529f\u80fd\u7279\u6027...\n\n    # \u66f4\u65b0\u5217\u8868\n    updates:\n      - date: 2024-01-20\n        title: \u65b0\u589e\u529f\u80fdA\n        url: /new-feature-a\n      - date: 2024-01-18\n        title: \u95ee\u9898\u4fee\u590dB\n        url: /bug-fix-b\n      # \u66f4\u591a\u66f4\u65b0...\n</code></pre> <ol> <li>\u4e3b\u9875\u529f\u80fd\u7c7b\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/home.js\nclass HomePage {\n    constructor() {\n        this.searchInput = document.getElementById('hero-search-input');\n        this.setupSearch();\n        this.setupFeatureCards();\n    }\n\n    setupSearch() {\n        this.searchInput?.addEventListener('keyup', (e) =&gt; {\n            if (e.key === 'Enter') {\n                const query = e.target.value;\n                window.location.href = `${window.location.origin}/search.html?q=${encodeURIComponent(query)}`;\n            }\n        });\n    }\n\n    setupFeatureCards() {\n        const cards = document.querySelectorAll('.feature-card');\n\n        cards.forEach(card =&gt; {\n            card.addEventListener('mousemove', (e) =&gt; {\n                const rect = card.getBoundingClientRect();\n                const x = e.clientX - rect.left;\n                const y = e.clientY - rect.top;\n\n                card.style.setProperty('--mouse-x', `${x}px`);\n                card.style.setProperty('--mouse-y', `${y}px`);\n            });\n        });\n    }\n}\n\n// \u521d\u59cb\u5316\u4e3b\u9875\ndocument.addEventListener('DOMContentLoaded', () =&gt; {\n    new HomePage();\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#7113","title":"7.1.1.3 \u81ea\u5b9a\u4e49\u533a\u57df","text":"<ol> <li>\u521b\u5efa\u81ea\u5b9a\u4e49\u533a\u57df\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/custom-content.html --&gt;\n{% if page.meta.custom_content %}\n&lt;section class=\"custom-content\"&gt;\n    &lt;!-- \u516c\u544a\u533a --&gt;\n    {% if page.meta.announcements %}\n    &lt;div class=\"announcements\"&gt;\n        {% for announcement in page.meta.announcements %}\n        &lt;div class=\"announcement-item\"&gt;\n            &lt;span class=\"announcement-tag\"&gt;{{ announcement.tag }}&lt;/span&gt;\n            &lt;p&gt;{{ announcement.content }}&lt;/p&gt;\n        &lt;/div&gt;\n        {% endfor %}\n    &lt;/div&gt;\n    {% endif %}\n\n    &lt;!-- \u8d21\u732e\u8005\u533a\u57df --&gt;\n    {% if page.meta.contributors %}\n    &lt;div class=\"contributors\"&gt;\n        &lt;h3&gt;\u9879\u76ee\u8d21\u732e\u8005&lt;/h3&gt;\n        &lt;div class=\"contributors-grid\"&gt;\n            {% for contributor in page.meta.contributors %}\n            &lt;a href=\"{{ contributor.url }}\" class=\"contributor-card\"&gt;\n                &lt;img src=\"{{ contributor.avatar }}\" alt=\"{{ contributor.name }}\"&gt;\n                &lt;span&gt;{{ contributor.name }}&lt;/span&gt;\n            &lt;/a&gt;\n            {% endfor %}\n        &lt;/div&gt;\n    &lt;/div&gt;\n    {% endif %}\n\n    &lt;!-- \u8d5e\u52a9\u5546\u533a\u57df --&gt;\n    {% if page.meta.sponsors %}\n    &lt;div class=\"sponsors\"&gt;\n        &lt;h3&gt;\u8d5e\u52a9\u5546&lt;/h3&gt;\n        &lt;div class=\"sponsors-grid\"&gt;\n            {% for sponsor in page.meta.sponsors %}\n            &lt;a href=\"{{ sponsor.url }}\" class=\"sponsor-card\"&gt;\n                &lt;img src=\"{{ sponsor.logo }}\" alt=\"{{ sponsor.name }}\"&gt;\n            &lt;/a&gt;\n            {% endfor %}\n        &lt;/div&gt;\n    &lt;/div&gt;\n    {% endif %}\n&lt;/section&gt;\n{% endif %}\n</code></pre> <ol> <li>\u81ea\u5b9a\u4e49\u533a\u57df\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/custom-content.css */\n\n/* \u516c\u544a\u533a\u57df */\n.announcements {\n    margin: 2rem 0;\n}\n\n.announcement-item {\n    padding: 1rem;\n    background: var(--md-code-bg-color);\n    border-radius: 4px;\n    margin-bottom: 1rem;\n}\n\n.announcement-tag {\n    display: inline-block;\n    padding: 0.2rem 0.5rem;\n    background: var(--md-accent-fg-color);\n    color: white;\n    border-radius: 2rem;\n    font-size: 0.8rem;\n    margin-right: 0.5rem;\n}\n\n/* \u8d21\u732e\u8005\u533a\u57df */\n.contributors-grid {\n    display: grid;\n    grid-template-columns: repeat(auto-fill, minmax(100px, 1fr));\n    gap: 1rem;\n    margin: 1rem 0;\n}\n\n.contributor-card {\n    text-align: center;\n    text-decoration: none;\n    color: var(--md-default-fg-color);\n}\n\n.contributor-card img {\n    width: 60px;\n    height: 60px;\n    border-radius: 50%;\n    margin-bottom: 0.5rem;\n}\n\n/* \u8d5e\u52a9\u5546\u533a\u57df */\n.sponsors-grid {\n    display: grid;\n    grid-template-columns: repeat(auto-fill, minmax(150px, 1fr));\n    gap: 2rem;\n    margin: 1rem 0;\n}\n\n.sponsor-card img {\n    width: 100%;\n    height: auto;\n    filter: grayscale(100%);\n    transition: filter 0.3s ease;\n}\n\n.sponsor-card:hover img {\n    filter: grayscale(0%);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#712","title":"7.1.2 \u6587\u7ae0\u6a21\u677f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#7121","title":"7.1.2.1 \u6587\u7ae0\u5934\u90e8","text":"HTML<pre><code>&lt;!-- docs/overrides/partials/article-header.html --&gt;\n&lt;header class=\"article-header\"&gt;\n    &lt;!-- \u6587\u7ae0\u6807\u9898 --&gt;\n    &lt;h1&gt;{{ page.title }}&lt;/h1&gt;\n\n    &lt;!-- \u6587\u7ae0\u5143\u4fe1\u606f --&gt;\n    &lt;div class=\"article-meta\"&gt;\n        {% if page.meta.author %}\n        &lt;div class=\"meta-item\"&gt;\n            &lt;span class=\"meta-icon\"&gt;\n                {% include \".icons/material/account.svg\" %}\n            &lt;/span&gt;\n            &lt;span&gt;{{ page.meta.author }}&lt;/span&gt;\n        &lt;/div&gt;\n        {% endif %}\n\n        {% if page.meta.date %}\n        &lt;div class=\"meta-item\"&gt;\n            &lt;span class=\"meta-icon\"&gt;\n                {% include \".icons/material/calendar.svg\" %}\n            &lt;/span&gt;\n            &lt;span&gt;{{ page.meta.date }}&lt;/span&gt;\n        &lt;/div&gt;\n        {% endif %}\n\n        {% if page.meta.tags %}\n        &lt;div class=\"article-tags\"&gt;\n            {% for tag in page.meta.tags %}\n            &lt;a href=\"{{ base_url }}/tags/#{{ tag }}\" class=\"tag\"&gt;\n                # {{ tag }}\n            &lt;/a&gt;\n            {% endfor %}\n        &lt;/div&gt;\n        {% endif %}\n    &lt;/div&gt;\n\n    &lt;!-- \u6587\u7ae0\u6982\u8ff0 --&gt;\n    {% if page.meta.description %}\n    &lt;div class=\"article-description\"&gt;\n        {{ page.meta.description }}\n    &lt;/div&gt;\n    {% endif %}\n&lt;/header&gt;\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#7122","title":"7.1.2.2 \u6b63\u6587\u6837\u5f0f","text":"CSS<pre><code>/* docs/stylesheets/article.css */\n\n/* \u6587\u7ae0\u5bb9\u5668 */\n.md-content article {\n    max-width: 800px;\n    margin: 0 auto;\n    padding: 2rem;\n}\n\n/* \u6587\u7ae0\u5934\u90e8 */\n.article-header {\n    margin-bottom: 3rem;\n    text-align: center;\n}\n\n.article-meta {\n    display: flex;\n    justify-content: center;\n    gap: 1rem;\n    margin: 1rem 0;\n    color: var(--md-default-fg-color--light);\n}\n\n.meta-item {\n    display: flex;\n    align-items: center;\n    gap: 0.5rem;\n}\n\n.article-tags {\n    margin-top: 1rem;\n}\n\n.tag {\n    display: inline-block;\n    padding: 0.2rem 0.5rem;\n    margin: 0.2rem;\n    background: var(--md-code-bg-color);\n    border-radius: 2rem;\n    color: var(--md-default-fg-color);\n    text-decoration: none;\n    font-size: 0.8rem;\n}\n\n/* \u6587\u7ae0\u5185\u5bb9\u6837\u5f0f */\n.md-content article {\n    font-size: 1.1rem;\n    line-height: 1.8;\n}\n\n/* \u6807\u9898\u6837\u5f0f */\n.md-content article h2 {\n    margin-top: 3rem;\n    padding-bottom: 0.5rem;\n    border-bottom: 2px solid var(--md-default-fg-color--lightest);\n}\n\n/* \u4ee3\u7801\u5757\u6837\u5f0f */\n.md-content pre {\n    border-radius: 8px;\n    margin: 1.5rem 0;\n}\n\n/* \u5f15\u7528\u6837\u5f0f */\n.md-content blockquote {\n    border-left: 4px solid var(--md-accent-fg-color);\n    padding: 1rem;\n    background: var(--md-code-bg-color);\n    margin: 1.5rem 0;\n}\n\n/* \u56fe\u7247\u6837\u5f0f */\n.md-content img {\n    max-width: 100%;\n    border-radius: 8px;\n    margin: 1.5rem 0;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#7123","title":"7.1.2.3 \u5e95\u90e8\u4fe1\u606f","text":"HTML<pre><code>&lt;!-- docs/overrides/partials/article-footer.html --&gt;\n&lt;footer class=\"article-footer\"&gt;\n    &lt;!-- \u6587\u7ae0\u5bfc\u822a --&gt;\n    &lt;nav class=\"article-nav\"&gt;\n        {% if page.previous_page %}\n        &lt;a href=\"{{ page.previous_page.url | url }}\" class=\"nav-link nav-prev\"&gt;\n            &lt;span class=\"nav-icon\"&gt;\n                {% include \".icons/material/arrow-left.svg\" %}\n            &lt;/span&gt;\n            &lt;span class=\"nav-text\"&gt;\n                &lt;span class=\"nav-direction\"&gt;\u4e0a\u4e00\u7bc7&lt;/span&gt;\n                &lt;span class=\"nav-title\"&gt;{{ page.previous_page.title }}&lt;/span&gt;\n            &lt;/span&gt;\n        &lt;/a&gt;\n        {% endif %}\n\n        {% if page.next_page %}\n        &lt;a href=\"{{ page.next_page.url | url }}\" class=\"nav-link nav-next\"&gt;\n            &lt;span class=\"nav-text\"&gt;\n                &lt;span class=\"nav-direction\"&gt;\u4e0b\u4e00\u7bc7&lt;/span&gt;\n                &lt;span class=\"nav-title\"&gt;{{ page.next_page.title }}&lt;/span&gt;\n            &lt;/span&gt;\n            &lt;span class=\"nav-icon\"&gt;\n                {% include \".icons/material/arrow-right.svg\" %}\n            &lt;/span&gt;\n        &lt;/a&gt;\n        {% endif %}\n    &lt;/nav&gt;\n\n    &lt;!-- \u5206\u4eab\u6309\u94ae --&gt;\n    &lt;div class=\"article-share\"&gt;\n        &lt;h4&gt;\u5206\u4eab\u6587\u7ae0&lt;/h4&gt;\n        &lt;div class=\"share-buttons\"&gt;\n            &lt;button class=\"share-button\" data-platform=\"twitter\"&gt;\n                {% include \".icons/material/twitter.svg\" %}\n            &lt;/button&gt;\n            &lt;button class=\"share-button\" data-platform=\"facebook\"&gt;\n                {% include \".icons/material/facebook.svg\" %}\n            &lt;/button&gt;\n            &lt;button class=\"share-button\" data-platform=\"linkedin\"&gt;\n                {% include \".icons/material/linkedin.svg\" %}\n            &lt;/button&gt;\n            &lt;button class=\"share-button\" data-platform=\"weibo\"&gt;\n                {% include \".icons/material/sina-weibo.svg\" %}\n            &lt;/button&gt;\n        &lt;/div&gt;\n    &lt;/div&gt;\n\n    &lt;!-- \u76f8\u5173\u6587\u7ae0 --&gt;\n    {% if page.meta.related_posts %}\n    &lt;div class=\"related-posts\"&gt;\n        &lt;h4&gt;\u76f8\u5173\u6587\u7ae0&lt;/h4&gt;\n        &lt;div class=\"related-grid\"&gt;\n            {% for post in page.meta.related_posts %}\n            &lt;a href=\"{{ post.url | url }}\" class=\"related-post\"&gt;\n                {% if post.image %}\n                &lt;img src=\"{{ post.image }}\" alt=\"{{ post.title }}\"&gt;\n                {% endif %}\n                &lt;h5&gt;{{ post.title }}&lt;/h5&gt;\n                &lt;p&gt;{{ post.excerpt }}&lt;/p&gt;\n            &lt;/a&gt;\n            {% endfor %}\n        &lt;/div&gt;\n    &lt;/div&gt;\n    {% endif %}\n\n    &lt;!-- \u8bc4\u8bba\u533a --&gt;\n    &lt;div class=\"article-comments\"&gt;\n        &lt;h4&gt;\u8bc4\u8bba&lt;/h4&gt;\n        {% if config.extra.comments.provider == 'giscus' %}\n        &lt;script src=\"https://giscus.app/client.js\"\n            data-repo=\"{{ config.extra.comments.repo }}\"\n            data-repo-id=\"{{ config.extra.comments.repo_id }}\"\n            data-category=\"{{ config.extra.comments.category }}\"\n            data-category-id=\"{{ config.extra.comments.category_id }}\"\n            data-mapping=\"pathname\"\n            data-reactions-enabled=\"1\"\n            data-emit-metadata=\"0\"\n            data-theme=\"light\"\n            crossorigin=\"anonymous\"\n            async&gt;\n        &lt;/script&gt;\n        {% endif %}\n    &lt;/div&gt;\n&lt;/footer&gt;\n\n&lt;!-- \u6587\u7ae0\u5e95\u90e8\u6837\u5f0f --&gt;\n&lt;style&gt;\n.article-footer {\n    margin-top: 4rem;\n    padding-top: 2rem;\n    border-top: 1px solid var(--md-default-fg-color--lightest);\n}\n\n/* \u6587\u7ae0\u5bfc\u822a */\n.article-nav {\n    display: flex;\n    justify-content: space-between;\n    margin-bottom: 2rem;\n}\n\n.nav-link {\n    display: flex;\n    align-items: center;\n    padding: 1rem;\n    text-decoration: none;\n    color: var(--md-default-fg-color);\n    background: var(--md-code-bg-color);\n    border-radius: 8px;\n    transition: transform 0.2s ease;\n    max-width: 45%;\n}\n\n.nav-link:hover {\n    transform: translateY(-2px);\n}\n\n.nav-text {\n    display: flex;\n    flex-direction: column;\n}\n\n.nav-direction {\n    font-size: 0.8rem;\n    color: var(--md-default-fg-color--light);\n}\n\n.nav-title {\n    font-weight: 500;\n}\n\n/* \u5206\u4eab\u6309\u94ae */\n.share-buttons {\n    display: flex;\n    gap: 1rem;\n    margin: 1rem 0;\n}\n\n.share-button {\n    padding: 0.8rem;\n    border: none;\n    border-radius: 50%;\n    background: var(--md-code-bg-color);\n    cursor: pointer;\n    transition: all 0.2s ease;\n}\n\n.share-button:hover {\n    background: var(--md-accent-fg-color);\n    color: white;\n}\n\n/* \u76f8\u5173\u6587\u7ae0 */\n.related-grid {\n    display: grid;\n    grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));\n    gap: 1.5rem;\n    margin: 1rem 0;\n}\n\n.related-post {\n    text-decoration: none;\n    color: var(--md-default-fg-color);\n    background: var(--md-code-bg-color);\n    border-radius: 8px;\n    overflow: hidden;\n    transition: transform 0.2s ease;\n}\n\n.related-post:hover {\n    transform: translateY(-4px);\n}\n\n.related-post img {\n    width: 100%;\n    height: 150px;\n    object-fit: cover;\n}\n\n.related-post h5 {\n    margin: 1rem;\n    font-size: 1.1rem;\n}\n\n.related-post p {\n    margin: 0 1rem 1rem;\n    font-size: 0.9rem;\n    color: var(--md-default-fg-color--light);\n}\n\n/* \u8bc4\u8bba\u533a */\n.article-comments {\n    margin-top: 3rem;\n}\n\n/* \u54cd\u5e94\u5f0f\u9002\u914d */\n@media screen and (max-width: 76.1875em) {\n    .article-nav {\n        flex-direction: column;\n        gap: 1rem;\n    }\n\n    .nav-link {\n        max-width: 100%;\n    }\n\n    .related-grid {\n        grid-template-columns: 1fr;\n    }\n}\n&lt;/style&gt;\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#713-404","title":"7.1.3 404\u9875\u9762","text":""},{"location":"Tools/Blog/Mkdocs_Material/#7131","title":"7.1.3.1 \u9519\u8bef\u63d0\u793a","text":"HTML<pre><code>&lt;!-- docs/overrides/404.html --&gt;\n{% extends \"base.html\" %}\n\n{% block content %}\n&lt;div class=\"error-page\"&gt;\n    &lt;div class=\"error-content\"&gt;\n        &lt;!-- 404 \u56fe\u6807 --&gt;\n        &lt;div class=\"error-icon\"&gt;\n            {% include \".icons/material/alert-circle-outline.svg\" %}\n            &lt;span class=\"error-code\"&gt;404&lt;/span&gt;\n        &lt;/div&gt;\n\n        &lt;!-- \u9519\u8bef\u4fe1\u606f --&gt;\n        &lt;h1&gt;\u9875\u9762\u672a\u627e\u5230&lt;/h1&gt;\n        &lt;p&gt;\u62b1\u6b49\uff0c\u60a8\u8bbf\u95ee\u7684\u9875\u9762\u4e0d\u5b58\u5728\u6216\u5df2\u88ab\u79fb\u52a8&lt;/p&gt;\n\n        &lt;!-- \u641c\u7d22\u6846 --&gt;\n        &lt;div class=\"error-search\"&gt;\n            &lt;input type=\"text\" \n                   id=\"error-search-input\" \n                   placeholder=\"\u5c1d\u8bd5\u641c\u7d22...\"\n                   autocomplete=\"off\"&gt;\n            &lt;button id=\"error-search-button\"&gt;\n                {% include \".icons/material/magnify.svg\" %}\n            &lt;/button&gt;\n        &lt;/div&gt;\n\n        &lt;!-- \u5feb\u6377\u64cd\u4f5c --&gt;\n        &lt;div class=\"error-actions\"&gt;\n            &lt;a href=\"{{ base_url }}\" class=\"md-button md-button--primary\"&gt;\n                \u8fd4\u56de\u9996\u9875\n            &lt;/a&gt;\n            &lt;button class=\"md-button\" onclick=\"window.history.back()\"&gt;\n                \u8fd4\u56de\u4e0a\u9875\n            &lt;/button&gt;\n        &lt;/div&gt;\n    &lt;/div&gt;\n\n    &lt;!-- \u641c\u7d22\u5efa\u8bae --&gt;\n    &lt;div class=\"search-suggestions\" id=\"search-suggestions\"&gt;\n        &lt;h3&gt;\u60a8\u662f\u5426\u5728\u627e\uff1a&lt;/h3&gt;\n        &lt;div class=\"suggestions-list\" id=\"suggestions-list\"&gt;\n            &lt;!-- \u52a8\u6001\u751f\u6210\u7684\u5efa\u8bae\u5217\u8868 --&gt;\n        &lt;/div&gt;\n    &lt;/div&gt;\n&lt;/div&gt;\n\n&lt;!-- 404\u9875\u9762\u6837\u5f0f --&gt;\n&lt;style&gt;\n.error-page {\n    min-height: 100vh;\n    display: flex;\n    flex-direction: column;\n    align-items: center;\n    justify-content: center;\n    padding: 2rem;\n    text-align: center;\n}\n\n.error-content {\n    max-width: 600px;\n}\n\n.error-icon {\n    font-size: 6rem;\n    color: var(--md-primary-fg-color);\n    margin-bottom: 2rem;\n    position: relative;\n}\n\n.error-code {\n    position: absolute;\n    bottom: -1rem;\n    right: -1rem;\n    font-size: 2rem;\n    font-weight: bold;\n    background: var(--md-accent-fg-color);\n    color: white;\n    padding: 0.5rem 1rem;\n    border-radius: 1rem;\n}\n\n.error-search {\n    margin: 2rem 0;\n    position: relative;\n}\n\n.error-search input {\n    width: 100%;\n    padding: 1rem 3rem 1rem 1rem;\n    border: 2px solid var(--md-default-fg-color--lightest);\n    border-radius: 2rem;\n    font-size: 1.1rem;\n}\n\n.error-search button {\n    position: absolute;\n    right: 0.5rem;\n    top: 50%;\n    transform: translateY(-50%);\n    background: none;\n    border: none;\n    color: var(--md-default-fg-color);\n    cursor: pointer;\n}\n\n.error-actions {\n    display: flex;\n    gap: 1rem;\n    justify-content: center;\n    margin: 2rem 0;\n}\n\n/* \u641c\u7d22\u5efa\u8bae\u6837\u5f0f */\n.search-suggestions {\n    margin-top: 3rem;\n    width: 100%;\n    max-width: 600px;\n}\n\n.suggestions-list {\n    margin-top: 1rem;\n}\n\n.suggestion-item {\n    padding: 1rem;\n    margin: 0.5rem 0;\n    background: var(--md-code-bg-color);\n    border-radius: 8px;\n    cursor: pointer;\n    transition: all 0.2s ease;\n}\n\n.suggestion-item:hover {\n    background: var(--md-accent-fg-color--transparent);\n}\n\n/* \u54cd\u5e94\u5f0f\u9002\u914d */\n@media screen and (max-width: 76.1875em) {\n    .error-icon {\n        font-size: 4rem;\n    }\n\n    .error-code {\n        font-size: 1.5rem;\n    }\n\n    .error-actions {\n        flex-direction: column;\n    }\n}\n&lt;/style&gt;\n\n&lt;!-- 404\u9875\u9762\u811a\u672c --&gt;\n&lt;script&gt;\ndocument.addEventListener('DOMContentLoaded', function() {\n    // \u641c\u7d22\u5efa\u8bae\u529f\u80fd\n    setupSearchSuggestions();\n    // \u5168\u5c40\u70ed\u952e\n    setupHotkeys();\n});\n\nfunction setupSearchSuggestions() {\n    const searchInput = document.getElementById('error-search-input');\n    const suggestionsList = document.getElementById('suggestions-list');\n\n    searchInput?.addEventListener('input', debounce(async (e) =&gt; {\n        const query = e.target.value;\n        if (query.length &lt; 2) {\n            suggestionsList.innerHTML = '';\n            return;\n        }\n\n        // \u83b7\u53d6\u641c\u7d22\u5efa\u8bae\n        const suggestions = await getSearchSuggestions(query);\n\n        // \u6e32\u67d3\u5efa\u8bae\u5217\u8868\n        suggestionsList.innerHTML = suggestions\n            .map(suggestion =&gt; `\n                &lt;div class=\"suggestion-item\" onclick=\"window.location.href='${suggestion.url}'\"&gt;\n                    &lt;div class=\"suggestion-title\"&gt;${suggestion.title}&lt;/div&gt;\n                    &lt;div class=\"suggestion-excerpt\"&gt;${suggestion.excerpt}&lt;/div&gt;\n                &lt;/div&gt;\n            `)\n            .join('');\n    }, 300));\n}\n\nasync function getSearchSuggestions(query) {\n    // \u8fd9\u91cc\u53ef\u4ee5\u5b9e\u73b0\u5b9e\u9645\u7684\u641c\u7d22\u903b\u8f91\n    // \u793a\u4f8b\u8fd4\u56de\u6570\u636e\n    return [\n        {\n            title: '\u76f8\u5173\u6587\u6863 1',\n            excerpt: '\u8fd9\u662f\u4e00\u6bb5\u76f8\u5173\u7684\u6587\u6863\u63cf\u8ff0...',\n            url: '#'\n        },\n        {\n            title: '\u76f8\u5173\u6587\u6863 2',\n            excerpt: '\u8fd9\u662f\u53e6\u4e00\u6bb5\u76f8\u5173\u7684\u6587\u6863\u63cf\u8ff0...',\n            url: '#'\n        }\n    ];\n}\n\nfunction setupHotkeys() {\n    document.addEventListener('keydown', (e) =&gt; {\n        // \u6309 ESC \u8fd4\u56de\u4e0a\u9875\n        if (e.key === 'Escape') {\n            window.history.back();\n        }\n\n        // \u6309 Enter \u6267\u884c\u641c\u7d22\n        if (e.key === 'Enter' &amp;&amp; document.activeElement.id === 'error-search-input') {\n            const query = document.activeElement.value;\n            if (query) {\n                window.location.href = `${window.location.origin}/search.html?q=${encodeURIComponent(query)}`;\n            }\n        }\n    });\n}\n\n// \u9632\u6296\u51fd\u6570\nfunction debounce(fn, delay) {\n    let timer = null;\n    return function(...args) {\n        clearTimeout(timer);\n        timer = setTimeout(() =&gt; fn.apply(this, args), delay);\n    };\n}\n&lt;/script&gt;\n</code></pre> <p>\u8fd9\u6837\uff0c\u6211\u4eec\u5c31\u5b8c\u6210\u4e86\u6587\u7ae0\u5e95\u90e8\u4fe1\u606f\u548c404\u9875\u9762\u7684\u6a21\u677f\u3002\u4e3b\u8981\u7279\u70b9\u5305\u62ec\uff1a</p> <ol> <li> <p>\u6587\u7ae0\u5e95\u90e8\uff1a - \u6e05\u6670\u7684\u4e0a\u4e0b\u6587\u7ae0\u5bfc\u822a - \u793e\u4ea4\u5206\u4eab\u6309\u94ae - \u76f8\u5173\u6587\u7ae0\u63a8\u8350 - \u96c6\u6210\u8bc4\u8bba\u7cfb\u7edf</p> </li> <li> <p>404\u9875\u9762\uff1a - \u53cb\u597d\u7684\u9519\u8bef\u63d0\u793a - \u5b9e\u65f6\u641c\u7d22\u5efa\u8bae - \u591a\u79cd\u8fd4\u56de\u9009\u9879 - \u952e\u76d8\u5feb\u6377\u952e\u652f\u6301</p> </li> </ol> <p>\u4f7f\u7528\u8fd9\u4e9b\u6a21\u677f\u65f6\uff0c\u9700\u8981\u5728 <code>mkdocs.yml</code> \u4e2d\u6dfb\u52a0\u76f8\u5e94\u7684\u914d\u7f6e\uff1a</p> YAML<pre><code>theme:\n  name: material\n  custom_dir: docs/overrides\n  features:\n    - navigation.tracking\n    - search.suggest\n    - search.highlight\n\nextra:\n  comments:\n    provider: giscus\n    repo: username/repo\n    repo_id: your-repo-id\n    category: Comments\n    category_id: your-category-id\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#72","title":"7.2 \u4fee\u6539\u7ec4\u4ef6\u6a21\u677f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#721","title":"7.2.1 \u5bfc\u822a\u680f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#7211","title":"7.2.1.1 \u5bfc\u822a\u9879\u5b9a\u5236","text":"HTML<pre><code>&lt;!-- docs/overrides/partials/nav.html --&gt;\n{% extends \"base.html\" %}\n\n{% block site_nav %}\n&lt;nav class=\"md-nav md-nav--primary\"&gt;\n    &lt;!-- \u81ea\u5b9a\u4e49\u5bfc\u822a\u5934\u90e8 --&gt;\n    &lt;div class=\"nav-header\"&gt;\n        {% if config.theme.logo %}\n        &lt;img src=\"{{ config.theme.logo }}\" alt=\"logo\" class=\"nav-logo\"&gt;\n        {% endif %}\n        &lt;span class=\"nav-title\"&gt;{{ config.site_name }}&lt;/span&gt;\n    &lt;/div&gt;\n\n    &lt;!-- \u81ea\u5b9a\u4e49\u5bfc\u822a\u9879 --&gt;\n    &lt;ul class=\"nav-items\"&gt;\n        {% for nav_item in nav %}\n        {% include \"partials/nav-item.html\" %}\n        {% endfor %}\n\n        &lt;!-- \u6dfb\u52a0\u81ea\u5b9a\u4e49\u5bfc\u822a\u9879 --&gt;\n        {% if config.extra.nav_links %}\n        {% for link in config.extra.nav_links %}\n        &lt;li class=\"nav-item custom\"&gt;\n            &lt;a href=\"{{ link.url }}\" class=\"nav-link\" {% if link.target %}target=\"{{ link.target }}\"{% endif %}&gt;\n                {% if link.icon %}\n                &lt;span class=\"nav-icon\"&gt;\n                    {% include \".icons/\" ~ link.icon ~ \".svg\" %}\n                &lt;/span&gt;\n                {% endif %}\n                {{ link.title }}\n            &lt;/a&gt;\n        &lt;/li&gt;\n        {% endfor %}\n        {% endif %}\n    &lt;/ul&gt;\n&lt;/nav&gt;\n</code></pre> <p>\u914d\u7f6e\u548c\u6837\u5f0f\uff1a</p> YAML<pre><code># mkdocs.yml\nextra:\n  nav_links:\n    - title: GitHub\n      url: https://github.com/your/repo\n      icon: material/github\n      target: _blank\n    - title: \u6587\u6863\n      url: /docs/\n      icon: material/file-document\n</code></pre> CSS<pre><code>/* docs/stylesheets/nav.css */\n.nav-header {\n    display: flex;\n    align-items: center;\n    padding: 1rem;\n    border-bottom: 1px solid var(--md-default-fg-color--lightest);\n}\n\n.nav-logo {\n    width: 32px;\n    height: 32px;\n    margin-right: 0.8rem;\n}\n\n.nav-items {\n    list-style: none;\n    padding: 0;\n    margin: 0;\n}\n\n.nav-item {\n    margin: 0.2rem 0;\n}\n\n.nav-link {\n    display: flex;\n    align-items: center;\n    padding: 0.8rem 1rem;\n    color: var(--md-default-fg-color);\n    text-decoration: none;\n    transition: background-color 0.2s ease;\n}\n\n.nav-link:hover {\n    background-color: var(--md-code-bg-color);\n}\n\n.nav-icon {\n    margin-right: 0.8rem;\n    width: 1.2rem;\n    height: 1.2rem;\n}\n\n/* \u81ea\u5b9a\u4e49\u5bfc\u822a\u9879\u6837\u5f0f */\n.nav-item.custom .nav-link {\n    color: var(--md-accent-fg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#7212","title":"7.2.1.2 \u641c\u7d22\u6846\u4f4d\u7f6e","text":"HTML<pre><code>&lt;!-- docs/overrides/partials/search.html --&gt;\n{% block search_box %}\n&lt;div class=\"md-search\" data-md-component=\"search\" role=\"dialog\"&gt;\n    &lt;label class=\"md-search__overlay\" for=\"__search\"&gt;&lt;/label&gt;\n    &lt;div class=\"md-search__inner\" role=\"search\"&gt;\n        &lt;!-- \u641c\u7d22\u8f93\u5165\u6846 --&gt;\n        &lt;form class=\"md-search__form\"&gt;\n            &lt;input\n                type=\"text\"\n                class=\"md-search__input\"\n                name=\"query\"\n                aria-label=\"\u641c\u7d22\"\n                placeholder=\"\u641c\u7d22\u6587\u6863...\"\n                autocapitalize=\"off\"\n                autocomplete=\"off\"\n                autocorrect=\"off\"\n                spellcheck=\"false\"\n                data-md-component=\"search-query\"\n            &gt;\n            &lt;!-- \u641c\u7d22\u5feb\u6377\u952e\u63d0\u793a --&gt;\n            &lt;div class=\"md-search__shortcuts\"&gt;\n                &lt;kbd&gt;Ctrl&lt;/kbd&gt; + &lt;kbd&gt;K&lt;/kbd&gt;\n            &lt;/div&gt;\n        &lt;/form&gt;\n\n        &lt;!-- \u641c\u7d22\u7ed3\u679c --&gt;\n        &lt;div class=\"md-search__output\"&gt;\n            &lt;div class=\"md-search__scrollwrap\" data-md-scrollfix&gt;\n                &lt;div class=\"md-search-result\" data-md-component=\"search-result\"&gt;\n                    &lt;div class=\"md-search-result__meta\"&gt;\n                        \u6b63\u5728\u641c\u7d22...\n                    &lt;/div&gt;\n                    &lt;ol class=\"md-search-result__list\"&gt;&lt;/ol&gt;\n                &lt;/div&gt;\n            &lt;/div&gt;\n        &lt;/div&gt;\n    &lt;/div&gt;\n&lt;/div&gt;\n</code></pre> <p>\u6837\u5f0f\u5b9a\u5236\uff1a</p> CSS<pre><code>/* docs/stylesheets/search.css */\n/* \u641c\u7d22\u6846\u5bb9\u5668 */\n.md-search {\n    margin: 0 1rem;\n    padding: 0;\n    position: relative;\n}\n\n/* \u641c\u7d22\u8f93\u5165\u6846 */\n.md-search__input {\n    width: 100%;\n    height: 2.4rem;\n    padding: 0 2.4rem;\n    font-size: 0.9rem;\n    color: var(--md-default-fg-color);\n    background-color: var(--md-default-bg-color);\n    border: 1px solid var(--md-default-fg-color--lightest);\n    border-radius: 1.2rem;\n}\n\n/* \u641c\u7d22\u56fe\u6807 */\n.md-search__icon {\n    position: absolute;\n    left: 0.8rem;\n    top: 50%;\n    transform: translateY(-50%);\n    color: var(--md-default-fg-color--light);\n}\n\n/* \u5feb\u6377\u952e\u63d0\u793a */\n.md-search__shortcuts {\n    position: absolute;\n    right: 0.8rem;\n    top: 50%;\n    transform: translateY(-50%);\n    display: flex;\n    gap: 0.2rem;\n    color: var(--md-default-fg-color--light);\n}\n\n/* \u641c\u7d22\u7ed3\u679c\u5bb9\u5668 */\n.md-search__output {\n    position: absolute;\n    top: 100%;\n    width: 100%;\n    margin-top: 0.4rem;\n    background-color: var(--md-default-bg-color);\n    border-radius: 0.2rem;\n    box-shadow: var(--md-shadow-z2);\n    overflow: auto;\n    z-index: 1;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#7213","title":"7.2.1.3 \u79fb\u52a8\u7aef\u9002\u914d","text":"CSS<pre><code>/* \u79fb\u52a8\u7aef\u5bfc\u822a\u6837\u5f0f */\n@media screen and (max-width: 76.1875em) {\n    /* \u5bfc\u822a\u5207\u6362\u6309\u94ae */\n    .md-header-nav__button.md-icon {\n        padding: 0.4rem;\n        margin: 0.4rem;\n    }\n\n    /* \u5bfc\u822a\u62bd\u5c49 */\n    .md-nav--primary {\n        position: fixed;\n        top: 0;\n        left: -18rem;\n        width: 18rem;\n        height: 100%;\n        background-color: var(--md-default-bg-color);\n        transition: left 0.25s;\n        z-index: 2;\n    }\n\n    /* \u5bfc\u822a\u62bd\u5c49\u6253\u5f00\u72b6\u6001 */\n    .md-nav--primary.md-nav--opened {\n        left: 0;\n    }\n\n    /* \u641c\u7d22\u6846\u5168\u5c4f */\n    .md-search__inner {\n        position: fixed;\n        top: 0;\n        left: 0;\n        width: 100%;\n        height: 100%;\n        padding: 1rem;\n        background-color: var(--md-default-bg-color);\n        z-index: 3;\n    }\n\n    /* \u641c\u7d22\u7ed3\u679c\u5168\u5c4f */\n    .md-search__output {\n        position: fixed;\n        top: 4rem;\n        height: calc(100% - 4rem);\n    }\n}\n\n/* \u5e73\u677f\u9002\u914d */\n@media screen and (min-width: 76.25em) and (max-width: 96.25em) {\n    .md-nav--primary {\n        width: 16rem;\n    }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#722","title":"7.2.2 \u9875\u811a","text":"HTML<pre><code>&lt;!-- docs/overrides/partials/footer.html --&gt;\n&lt;footer class=\"md-footer\"&gt;\n    &lt;div class=\"md-footer-meta md-typeset\"&gt;\n        &lt;div class=\"md-footer-meta__inner md-grid\"&gt;\n            &lt;!-- \u7248\u6743\u4fe1\u606f --&gt;\n            &lt;div class=\"md-footer-copyright\"&gt;\n                {% if config.copyright %}\n                &lt;div class=\"md-footer-copyright__highlight\"&gt;\n                    {{ config.copyright }}\n                &lt;/div&gt;\n                {% endif %}\n\n                &lt;!-- \u6784\u5efa\u4fe1\u606f --&gt;\n                &lt;div class=\"md-footer-build\"&gt;\n                    Documentation built with\n                    &lt;a href=\"https://www.mkdocs.org\" target=\"_blank\" rel=\"noopener\"&gt;\n                        MkDocs\n                    &lt;/a&gt;\n                    and\n                    &lt;a href=\"https://squidfunk.github.io/mkdocs-material/\" target=\"_blank\" rel=\"noopener\"&gt;\n                        Material for MkDocs\n                    &lt;/a&gt;\n                &lt;/div&gt;\n            &lt;/div&gt;\n\n            &lt;!-- \u793e\u4ea4\u94fe\u63a5 --&gt;\n            {% if config.extra.social %}\n            &lt;div class=\"md-footer-social\"&gt;\n                {% for social in config.extra.social %}\n                &lt;a href=\"{{ social.link }}\" \n                   target=\"_blank\" \n                   rel=\"noopener\" \n                   title=\"{{ social.name }}\"\n                   class=\"md-footer-social__link\"&gt;\n                    {% include \".icons/\" ~ social.icon ~ \".svg\" %}\n                &lt;/a&gt;\n                {% endfor %}\n            &lt;/div&gt;\n            {% endif %}\n\n            &lt;!-- \u5907\u6848\u4fe1\u606f --&gt;\n            {% if config.extra.icp %}\n            &lt;div class=\"md-footer-icp\"&gt;\n                &lt;a href=\"https://beian.miit.gov.cn/\" target=\"_blank\" rel=\"noopener\"&gt;\n                    {{ config.extra.icp }}\n                &lt;/a&gt;\n            &lt;/div&gt;\n            {% endif %}\n        &lt;/div&gt;\n    &lt;/div&gt;\n&lt;/footer&gt;\n</code></pre> <p>\u914d\u7f6e\uff1a</p> YAML<pre><code># mkdocs.yml\ncopyright: Copyright &amp;copy; 2024 Your Name\nextra:\n  social:\n    - icon: material/github\n      name: GitHub\n      link: https://github.com/your-username\n    - icon: material/twitter\n      name: Twitter\n      link: https://twitter.com/your-username\n  icp: \u4eacICP\u5907xxxxxxxx\u53f7\n</code></pre> <p>\u6837\u5f0f\uff1a</p> CSS<pre><code>/* docs/stylesheets/footer.css */\n.md-footer {\n    background-color: var(--md-default-bg-color);\n    color: var(--md-default-fg-color);\n    padding: 2rem 0;\n    border-top: 1px solid var(--md-default-fg-color--lightest);\n}\n\n.md-footer-meta__inner {\n    display: flex;\n    flex-wrap: wrap;\n    justify-content: space-between;\n    align-items: center;\n    gap: 1rem;\n}\n\n/* \u7248\u6743\u4fe1\u606f */\n.md-footer-copyright {\n    font-size: 0.8rem;\n}\n\n.md-footer-copyright__highlight {\n    margin-bottom: 0.5rem;\n}\n\n.md-footer-build {\n    color: var(--md-default-fg-color--light);\n}\n\n/* \u793e\u4ea4\u94fe\u63a5 */\n.md-footer-social {\n    display: flex;\n    gap: 1rem;\n}\n\n.md-footer-social__link {\n    width: 2rem;\n    height: 2rem;\n    display: flex;\n    align-items: center;\n    justify-content: center;\n    color: var(--md-default-fg-color);\n    border-radius: 50%;\n    transition: all 0.2s ease;\n}\n\n.md-footer-social__link:hover {\n    background-color: var(--md-code-bg-color);\n    color: var(--md-accent-fg-color);\n}\n\n/* \u5907\u6848\u4fe1\u606f */\n.md-footer-icp {\n    width: 100%;\n    text-align: center;\n    margin-top: 1rem;\n    font-size: 0.8rem;\n}\n\n.md-footer-icp a {\n    color: var(--md-default-fg-color--light);\n    text-decoration: none;\n}\n\n/* \u54cd\u5e94\u5f0f\u9002\u914d */\n@media screen and (max-width: 76.1875em) {\n    .md-footer-meta__inner {\n        flex-direction: column;\n        text-align: center;\n    }\n\n    .md-footer-social {\n        justify-content: center;\n    }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#723","title":"7.2.3 \u641c\u7d22\u6846","text":"HTML<pre><code>&lt;!-- docs/overrides/partials/search-modal.html --&gt;\n&lt;div class=\"md-search-modal\" data-md-component=\"search-modal\"&gt;\n    &lt;div class=\"md-search-modal__overlay\" data-md-component=\"search-modal-overlay\"&gt;&lt;/div&gt;\n\n    &lt;div class=\"md-search-modal__inner\"&gt;\n        &lt;!-- \u641c\u7d22\u5934\u90e8 --&gt;\n        &lt;header class=\"md-search-modal__header\"&gt;\n            &lt;form class=\"md-search-modal__form\"&gt;\n                &lt;input\n                    type=\"text\"\n                    class=\"md-search-modal__input\"\n                    name=\"query\"\n                    placeholder=\"\u641c\u7d22\u6587\u6863...\"\n                    data-md-component=\"search-query\"\n                    autocapitalize=\"off\"\n                    autocomplete=\"off\"\n                    autocorrect=\"off\"\n                    spellcheck=\"false\"\n                &gt;\n                &lt;!-- \u5feb\u6377\u952e\u63d0\u793a --&gt;\n                &lt;div class=\"md-search-modal__shortcuts\"&gt;\n                    &lt;kbd&gt;\u2191&lt;/kbd&gt;&lt;kbd&gt;\u2193&lt;/kbd&gt; \u9009\u62e9\n                    &lt;kbd&gt;\u21b5&lt;/kbd&gt; \u6253\u5f00\n                    &lt;kbd&gt;ESC&lt;/kbd&gt; \u5173\u95ed\n                &lt;/div&gt;\n            &lt;/form&gt;\n        &lt;/header&gt;\n\n        &lt;!-- \u641c\u7d22\u7ed3\u679c --&gt;\n        &lt;main class=\"md-search-modal__body\"&gt;\n            &lt;div class=\"md-search-modal__scrollwrap\"&gt;\n                &lt;div class=\"md-search-modal__meta\"&gt;\n                    \u952e\u5165\u4ee5\u5f00\u59cb\u641c\u7d22\n                &lt;/div&gt;\n\n                &lt;div class=\"md-search-modal__results\"&gt;\n                    &lt;!-- \u641c\u7d22\u7ed3\u679c\u5217\u8868 --&gt;\n                    &lt;div class=\"md-search-modal__list\"&gt;&lt;/div&gt;\n\n                    &lt;!-- \u641c\u7d22\u5efa\u8bae --&gt;\n                    &lt;div class=\"md-search-modal__suggestions\"&gt;\n                        &lt;h3&gt;\u60a8\u53ef\u80fd\u611f\u5174\u8da3\uff1a&lt;/h3&gt;\n                        &lt;div class=\"suggestions-list\"&gt;\n                            &lt;!-- \u52a8\u6001\u751f\u6210\u7684\u5efa\u8bae\u5217\u8868 --&gt;\n                        &lt;/div&gt;\n                    &lt;/div&gt;\n                &lt;/div&gt;\n            &lt;/div&gt;\n        &lt;/main&gt;\n    &lt;/div&gt;\n&lt;/div&gt;\n</code></pre> <p>\u641c\u7d22\u529f\u80fd\u811a\u672c\uff1a</p> JavaScript<pre><code>// docs/javascripts/search.js\nclass SearchModal {\n    constructor() {\n        this.modal = document.querySelector('.md-search-modal');\n        this.overlay = document.querySelector('.md-search-modal__overlay');\n        this.input = document.querySelector('.md-search-modal__input');\n        this.resultsList = document.querySelector('.md-search-modal__list');\n        this.suggestions = document.querySelector('.md-search-modal__suggestions');\n\n        this.searchIndex = null;\n        this.searchResults = [];\n        this.currentFocus = -1;\n\n        this.init();\n    }\n\n    init() {\n        // \u521d\u59cb\u5316\u641c\u7d22\u7d22\u5f15\n        this.buildSearchIndex();\n        // \u7ed1\u5b9a\u4e8b\u4ef6\n        this.bindEvents();\n        // \u8bbe\u7f6e\u5feb\u6377\u952e\n        this.setupShortcuts();\n    }\n\n    async buildSearchIndex() {\n        // \u6784\u5efa\u641c\u7d22\u7d22\u5f15\n        const response = await fetch('/search/search_index.json');\n        const data = await response.json();\n\n        // \u4f7f\u7528 lunr.js \u6784\u5efa\u7d22\u5f15\n        this.searchIndex = lunr(function() {\n            this.field('title', { boost: 10 });\n            this.field('text');\n            this.ref('location');\n\n            data.docs.forEach(function(doc) {\n                this.add(doc);\n            }, this);\n        });\n    }\n\n    bindEvents() {\n        // \u641c\u7d22\u6846\u8f93\u5165\u4e8b\u4ef6\n        this.input.addEventListener('input', debounce(() =&gt; {\n            const query = this.input.value;\n            if (query.length &gt;= 2) {\n                this.performSearch(query);\n            } else {\n                this.clearResults();\n            }\n        }, 200));\n\n        // \u641c\u7d22\u7ed3\u679c\u5bfc\u822a\n        this.input.addEventListener('keydown', (e) =&gt; {\n            switch (e.key) {\n                case 'ArrowUp':\n                    e.preventDefault();\n                    this.navigateResults('up');\n                    break;\n                case 'ArrowDown':\n                    e.preventDefault();\n                    this.navigateResults('down');\n                    break;\n                case 'Enter':\n                    e.preventDefault();\n                    this.openResult();\n                    break;\n                case 'Escape':\n                    e.preventDefault();\n                    this.closeModal();\n                    break;\n            }\n        });\n\n        // \u70b9\u51fb\u906e\u7f69\u5173\u95ed\n        this.overlay.addEventListener('click', () =&gt; this.closeModal());\n    }\n\n    setupShortcuts() {\n        // \u5168\u5c40\u641c\u7d22\u5feb\u6377\u952e\n        document.addEventListener('keydown', (e) =&gt; {\n            // Ctrl/Cmd + K \u6253\u5f00\u641c\u7d22\n            if ((e.ctrlKey || e.metaKey) &amp;&amp; e.key === 'k') {\n                e.preventDefault();\n                this.openModal();\n            }\n        });\n    }\n\n    async performSearch(query) {\n        if (!this.searchIndex) return;\n\n        // \u6267\u884c\u641c\u7d22\n        this.searchResults = this.searchIndex.search(query).map(result =&gt; {\n            return {\n                ref: result.ref,\n                score: result.score,\n                ...this.getDocumentByRef(result.ref)\n            };\n        });\n\n        // \u6e32\u67d3\u7ed3\u679c\n        this.renderResults();\n        // \u66f4\u65b0\u5efa\u8bae\n        this.updateSuggestions(query);\n    }\n\n    renderResults() {\n        this.resultsList.innerHTML = this.searchResults\n            .map((result, index) =&gt; `\n                &lt;div class=\"search-result-item ${index === this.currentFocus ? 'focused' : ''}\"\n                     data-index=\"${index}\"&gt;\n                    &lt;div class=\"result-title\"&gt;${this.highlightText(result.title)}&lt;/div&gt;\n                    &lt;div class=\"result-excerpt\"&gt;${this.highlightText(result.excerpt)}&lt;/div&gt;\n                    &lt;div class=\"result-location\"&gt;${result.location}&lt;/div&gt;\n                &lt;/div&gt;\n            `)\n            .join('');\n    }\n\n    highlightText(text) {\n        const query = this.input.value;\n        if (!query) return text;\n\n        const regex = new RegExp(`(${query})`, 'gi');\n        return text.replace(regex, '&lt;mark&gt;$1&lt;/mark&gt;');\n    }\n\n    updateSuggestions(query) {\n        // \u6839\u636e\u641c\u7d22\u5386\u53f2\u548c\u70ed\u95e8\u641c\u7d22\u751f\u6210\u5efa\u8bae\n        const suggestions = this.generateSuggestions(query);\n\n        this.suggestions.innerHTML = suggestions\n            .map(suggestion =&gt; `\n                &lt;div class=\"suggestion-item\" data-query=\"${suggestion.query}\"&gt;\n                    &lt;span class=\"suggestion-icon\"&gt;\n                        ${suggestion.type === 'history' ? '\u23f1\ufe0f' : '\ud83d\udd25'}\n                    &lt;/span&gt;\n                    ${suggestion.query}\n                &lt;/div&gt;\n            `)\n            .join('');\n    }\n\n    navigateResults(direction) {\n        const maxIndex = this.searchResults.length - 1;\n\n        if (direction === 'up') {\n            this.currentFocus = this.currentFocus &gt; 0 ? this.currentFocus - 1 : maxIndex;\n        } else {\n            this.currentFocus = this.currentFocus &lt; maxIndex ? this.currentFocus + 1 : 0;\n        }\n\n        this.renderResults();\n        this.scrollToFocused();\n    }\n\n    scrollToFocused() {\n        const focused = this.resultsList.querySelector('.focused');\n        if (focused) {\n            focused.scrollIntoView({\n                behavior: 'smooth',\n                block: 'nearest'\n            });\n        }\n    }\n\n    openResult() {\n        const result = this.searchResults[this.currentFocus];\n        if (result) {\n            window.location.href = result.location;\n        }\n    }\n\n    openModal() {\n        this.modal.classList.add('active');\n        this.input.focus();\n        document.body.style.overflow = 'hidden';\n    }\n\n    closeModal() {\n        this.modal.classList.remove('active');\n        this.input.value = '';\n        this.clearResults();\n        document.body.style.overflow = '';\n    }\n\n    clearResults() {\n        this.searchResults = [];\n        this.currentFocus = -1;\n        this.resultsList.innerHTML = '';\n        this.suggestions.innerHTML = '';\n    }\n}\n\n// \u521d\u59cb\u5316\u641c\u7d22\u529f\u80fd\ndocument.addEventListener('DOMContentLoaded', () =&gt; {\n    new SearchModal();\n});\n</code></pre> <p>\u641c\u7d22\u6846\u6837\u5f0f\uff1a</p> CSS<pre><code>/* docs/stylesheets/search-modal.css */\n.md-search-modal {\n    position: fixed;\n    top: 0;\n    left: 0;\n    width: 100%;\n    height: 100%;\n    z-index: 1000;\n    opacity: 0;\n    visibility: hidden;\n    transition: all 0.2s ease;\n}\n\n.md-search-modal.active {\n    opacity: 1;\n    visibility: visible;\n}\n\n.md-search-modal__overlay {\n    position: absolute;\n    top: 0;\n    left: 0;\n    width: 100%;\n    height: 100%;\n    background: rgba(0, 0, 0, 0.5);\n    backdrop-filter: blur(4px);\n}\n\n.md-search-modal__inner {\n    position: relative;\n    width: 90%;\n    max-width: 800px;\n    margin: 2rem auto;\n    background: var(--md-default-bg-color);\n    border-radius: 8px;\n    box-shadow: var(--md-shadow-z3);\n}\n\n/* \u641c\u7d22\u7ed3\u679c\u6837\u5f0f */\n.search-result-item {\n    padding: 1rem;\n    cursor: pointer;\n    transition: background 0.2s ease;\n}\n\n.search-result-item:hover,\n.search-result-item.focused {\n    background: var(--md-code-bg-color);\n}\n\n.result-title {\n    font-size: 1.1rem;\n    font-weight: 500;\n    margin-bottom: 0.5rem;\n}\n\n.result-excerpt {\n    font-size: 0.9rem;\n    color: var(--md-default-fg-color--light);\n    margin-bottom: 0.5rem;\n}\n\n.result-location {\n    font-size: 0.8rem;\n    color: var(--md-accent-fg-color);\n}\n\n/* \u9ad8\u4eae\u5339\u914d\u6587\u672c */\nmark {\n    background: var(--md-accent-fg-color);\n    color: white;\n    padding: 0 0.2rem;\n    border-radius: 2px;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#724","title":"7.2.4 \u76ee\u5f55","text":""},{"location":"Tools/Blog/Mkdocs_Material/#7241","title":"7.2.4.1 \u76ee\u5f55\u7ed3\u6784","text":"HTML<pre><code>&lt;!-- docs/overrides/partials/toc.html --&gt;\n&lt;nav class=\"md-toc\" aria-label=\"\u76ee\u5f55\"&gt;\n    &lt;div class=\"md-toc__header\"&gt;\n        &lt;h2 class=\"md-toc__title\"&gt;\u76ee\u5f55&lt;/h2&gt;\n        &lt;button class=\"md-toc__toggle\" aria-label=\"\u5c55\u5f00/\u6536\u8d77\"&gt;\n            {% include \".icons/material/chevron-down.svg\" %}\n        &lt;/button&gt;\n    &lt;/div&gt;\n\n    &lt;div class=\"md-toc__inner\"&gt;\n        {% set toc = page.toc %}\n        &lt;ul class=\"md-toc__list\"&gt;\n            {% for toc_item in toc %}\n                {% include \"partials/toc-item.html\" %}\n            {% endfor %}\n        &lt;/ul&gt;\n    &lt;/div&gt;\n&lt;/nav&gt;\n\n&lt;!-- docs/overrides/partials/toc-item.html --&gt;\n&lt;li class=\"md-toc__item\"&gt;\n    &lt;a href=\"{{ toc_item.url }}\" class=\"md-toc__link\"&gt;\n        {{ toc_item.title }}\n    &lt;/a&gt;\n\n    {% if toc_item.children %}\n    &lt;ul class=\"md-toc__list\"&gt;\n        {% for toc_item in toc_item.children %}\n            {% include \"partials/toc-item.html\" %}\n        {% endfor %}\n    &lt;/ul&gt;\n    {% endif %}\n&lt;/li&gt;\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#7242","title":"7.2.4.2 \u6eda\u52a8\u540c\u6b65","text":"JavaScript<pre><code>// docs/javascripts/toc.js\nclass TableOfContents {\n    constructor() {\n        this.toc = document.querySelector('.md-toc');\n        this.tocLinks = this.toc.querySelectorAll('.md-toc__link');\n        this.headings = document.querySelectorAll('h1[id], h2[id], h3[id], h4[id], h5[id], h6[id]');\n        this.intersectionObserver = null;\n\n        this.init();\n    }\n\n    init() {\n        this.setupIntersectionObserver();\n        this.setupScrollSpy();\n        this.setupToggle();\n    }\n\n    setupIntersectionObserver() {\n        this.intersectionObserver = new IntersectionObserver(\n            (entries) =&gt; {\n                entries.forEach(entry =&gt; {\n                    if (entry.isIntersecting) {\n                        const id = entry.target.getAttribute('id');\n                        this.highlightTocItem(id);\n                    }\n                });\n            },\n            {\n                rootMargin: '0px 0px -80% 0px'\n            }\n        );\n\n        this.headings.forEach(heading =&gt; {\n            this.intersectionObserver.observe(heading);\n        });\n    }\n\n    setupScrollSpy() {\n        this.tocLinks.forEach(link =&gt; {\n            link.addEventListener('click', (e) =&gt; {\n                e.preventDefault();\n                const id = link.getAttribute('href').substring(1);\n                const target = document.getElementById(id);\n\n                if (target) {\n                    window.scrollTo({\n                        top: target.offsetTop - 100,\n                        behavior: 'smooth'\n                    });\n\n                    // \u66f4\u65b0 URL\n                    history.pushState(null, null, `#${id}`);\n                }\n            });\n        });\n    }\n\n    highlightTocItem(id) {\n        // \u79fb\u9664\u6240\u6709\u9ad8\u4eae\n        this.tocLinks.forEach(link =&gt; {\n            link.classList.remove('active');\n        });\n\n        // \u6dfb\u52a0\u65b0\u9ad8\u4eae\n        const activeLink = this.toc.querySelector(`a[href=\"#${id}\"]`);\n        if (activeLink) {\n            activeLink.classList.add('active');\n            this.expandParents(activeLink);\n        }\n    }\n\n    expandParents(element) {\n        let parent = element.parentElement;\n        while (parent &amp;&amp; parent.classList.contains('md-toc__item')) {\n            const list = parent.querySelector('.md-toc__list');\n            if (list) {\n                list.style.height = 'auto';\n                parent.classList.add('expanded');\n            }\n            parent = parent.parentElement;\n        }\n    }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#7243","title":"7.2.4.3 \u5c55\u5f00\u6536\u8d77","text":"JavaScript<pre><code>setupToggle() {\n    const toggleButton = this.toc.querySelector('.md-toc__toggle');\n    const tocInner = this.toc.querySelector('.md-toc__inner');\n\n    toggleButton?.addEventListener('click', () =&gt; {\n        const isExpanded = this.toc.classList.contains('expanded');\n\n        if (isExpanded) {\n            this.toc.classList.remove('expanded');\n            tocInner.style.height = '0';\n        } else {\n            this.toc.classList.add('expanded');\n            tocInner.style.height = tocInner.scrollHeight + 'px';\n        }\n    });\n\n    // \u6dfb\u52a0\u5c55\u5f00/\u6536\u8d77\u6240\u6709\u6309\u94ae\n    const expandAllButton = document.createElement('button');\n    expandAllButton.className = 'md-toc__expand-all';\n    expandAllButton.innerHTML = '\u5c55\u5f00\u5168\u90e8';\n    expandAllButton.addEventListener('click', () =&gt; this.toggleAll(true));\n\n    const collapseAllButton = document.createElement('button');\n    collapseAllButton.className = 'md-toc__collapse-all';\n    collapseAllButton.innerHTML = '\u6536\u8d77\u5168\u90e8';\n    collapseAllButton.addEventListener('click', () =&gt; this.toggleAll(false));\n\n    const buttonGroup = document.createElement('div');\n    buttonGroup.className = 'md-toc__button-group';\n    buttonGroup.appendChild(expandAllButton);\n    buttonGroup.appendChild(collapseAllButton);\n\n    this.toc.querySelector('.md-toc__header').appendChild(buttonGroup);\n}\n\ntoggleAll(expand) {\n    const lists = this.toc.querySelectorAll('.md-toc__list');\n    lists.forEach(list =&gt; {\n        if (expand) {\n            list.style.height = 'auto';\n            list.parentElement.classList.add('expanded');\n        } else {\n            list.style.height = '0';\n            list.parentElement.classList.remove('expanded');\n        }\n    });\n}\n</code></pre> <p>\u76ee\u5f55\u6837\u5f0f\uff1a</p> CSS<pre><code>/* docs/stylesheets/toc.css */\n.md-toc {\n    position: sticky;\n    top: 4rem;\n    padding: 1rem;\n    max-height: calc(100vh - 4rem);\n    overflow-y: auto;\n    background: var(--md-default-bg-color);\n    border-left: 1px solid var(--md-default-fg-color--lightest);\n    font-size: 0.8rem;\n}\n\n/* \u76ee\u5f55\u5934\u90e8 */\n.md-toc__header {\n    display: flex;\n    justify-content: space-between;\n    align-items: center;\n    margin-bottom: 1rem;\n    padding-bottom: 0.5rem;\n    border-bottom: 1px solid var(--md-default-fg-color--lightest);\n}\n\n.md-toc__title {\n    font-size: 1rem;\n    font-weight: 600;\n    margin: 0;\n}\n\n.md-toc__button-group {\n    display: flex;\n    gap: 0.5rem;\n}\n\n.md-toc__button-group button {\n    padding: 0.2rem 0.5rem;\n    font-size: 0.7rem;\n    color: var(--md-default-fg-color--light);\n    background: var(--md-code-bg-color);\n    border: none;\n    border-radius: 4px;\n    cursor: pointer;\n    transition: all 0.2s ease;\n}\n\n.md-toc__button-group button:hover {\n    color: var(--md-accent-fg-color);\n    background: var(--md-code-bg-color--light);\n}\n\n/* \u76ee\u5f55\u5217\u8868 */\n.md-toc__list {\n    list-style: none;\n    padding: 0;\n    margin: 0;\n}\n\n.md-toc__item {\n    margin: 0.2rem 0;\n}\n\n/* \u76ee\u5f55\u94fe\u63a5 */\n.md-toc__link {\n    display: block;\n    padding: 0.2rem 0;\n    color: var(--md-default-fg-color);\n    text-decoration: none;\n    transition: all 0.2s ease;\n    border-radius: 4px;\n}\n\n.md-toc__link:hover {\n    color: var(--md-accent-fg-color);\n    background: var(--md-code-bg-color);\n    padding-left: 0.5rem;\n}\n\n/* \u5f53\u524d\u6fc0\u6d3b\u9879 */\n.md-toc__link.active {\n    color: var(--md-accent-fg-color);\n    font-weight: 500;\n    background: var(--md-code-bg-color);\n    padding-left: 0.5rem;\n}\n\n/* \u5d4c\u5957\u5c42\u7ea7 */\n.md-toc__item .md-toc__list {\n    margin-left: 1rem;\n    border-left: 1px solid var(--md-default-fg-color--lightest);\n    overflow: hidden;\n    height: 0;\n    transition: height 0.3s ease;\n}\n\n.md-toc__item.expanded &gt; .md-toc__list {\n    height: auto;\n}\n\n/* \u6298\u53e0\u6307\u793a\u5668 */\n.md-toc__item &gt; .md-toc__link::before {\n    content: '';\n    display: inline-block;\n    width: 0.8rem;\n    height: 0.8rem;\n    margin-right: 0.2rem;\n    background-image: url('data:image/svg+xml,&lt;svg xmlns=\"http://www.w3.org/2000/svg\" viewBox=\"0 0 24 24\"&gt;&lt;path d=\"M8.59 16.59L13.17 12 8.59 7.41 10 6l6 6-6 6-1.41-1.41z\"/&gt;&lt;/svg&gt;');\n    background-size: contain;\n    transform: rotate(0);\n    transition: transform 0.3s ease;\n}\n\n.md-toc__item.expanded &gt; .md-toc__link::before {\n    transform: rotate(90deg);\n}\n\n/* \u6eda\u52a8\u6761\u6837\u5f0f */\n.md-toc::-webkit-scrollbar {\n    width: 4px;\n}\n\n.md-toc::-webkit-scrollbar-track {\n    background: transparent;\n}\n\n.md-toc::-webkit-scrollbar-thumb {\n    background: var(--md-default-fg-color--lighter);\n    border-radius: 2px;\n}\n\n/* \u54cd\u5e94\u5f0f\u8bbe\u8ba1 */\n@media screen and (max-width: 76.1875em) {\n    .md-toc {\n        position: fixed;\n        top: 0;\n        right: -18rem;\n        width: 18rem;\n        height: 100vh;\n        max-height: none;\n        margin: 0;\n        padding: 1rem;\n        background: var(--md-default-bg-color);\n        border-left: 1px solid var(--md-default-fg-color--lightest);\n        box-shadow: var(--md-shadow-z3);\n        transition: right 0.3s ease;\n        z-index: 3;\n    }\n\n    .md-toc.expanded {\n        right: 0;\n    }\n\n    /* \u79fb\u52a8\u7aef\u8986\u76d6\u5c42 */\n    .md-toc-overlay {\n        display: none;\n        position: fixed;\n        top: 0;\n        left: 0;\n        width: 100%;\n        height: 100%;\n        background: rgba(0, 0, 0, 0.3);\n        z-index: 2;\n    }\n\n    .md-toc.expanded + .md-toc-overlay {\n        display: block;\n    }\n}\n\n/* \u5e73\u677f\u9002\u914d */\n@media screen and (min-width: 76.25em) and (max-width: 96.25em) {\n    .md-toc {\n        padding: 0.8rem;\n    }\n\n    .md-toc__list {\n        margin-left: 0.8rem;\n    }\n}\n</code></pre> <p>\u5b8c\u6574\u7684\u76ee\u5f55\u529f\u80fd\u5b9e\u73b0\uff1a</p> JavaScript<pre><code>// docs/javascripts/toc.js\nclass TableOfContents {\n    constructor() {\n        this.toc = document.querySelector('.md-toc');\n        this.tocLinks = this.toc.querySelectorAll('.md-toc__link');\n        this.headings = document.querySelectorAll('h1[id], h2[id], h3[id], h4[id], h5[id], h6[id]');\n        this.intersectionObserver = null;\n        this.isScrolling = false;\n        this.scrollTimeout = null;\n\n        this.init();\n    }\n\n    init() {\n        this.setupIntersectionObserver();\n        this.setupScrollSpy();\n        this.setupToggle();\n        this.setupMobileToggle();\n        this.handleInitialHash();\n    }\n\n    handleInitialHash() {\n        // \u5904\u7406\u9875\u9762\u52a0\u8f7d\u65f6\u7684 hash\n        if (window.location.hash) {\n            const id = window.location.hash.substring(1);\n            const target = document.getElementById(id);\n            if (target) {\n                setTimeout(() =&gt; {\n                    target.scrollIntoView();\n                    this.highlightTocItem(id);\n                }, 100);\n            }\n        }\n    }\n\n    setupMobileToggle() {\n        // \u521b\u5efa\u79fb\u52a8\u7aef\u5f00\u5173\u6309\u94ae\n        const toggleButton = document.createElement('button');\n        toggleButton.className = 'md-toc-toggle';\n        toggleButton.innerHTML = `\n            &lt;span class=\"md-toc-toggle__icon\"&gt;\n                {% include \".icons/material/menu.svg\" %}\n            &lt;/span&gt;\n        `;\n\n        // \u521b\u5efa\u906e\u7f69\u5c42\n        const overlay = document.createElement('div');\n        overlay.className = 'md-toc-overlay';\n\n        document.body.appendChild(toggleButton);\n        document.body.appendChild(overlay);\n\n        // \u7ed1\u5b9a\u4e8b\u4ef6\n        toggleButton.addEventListener('click', () =&gt; {\n            this.toc.classList.toggle('expanded');\n            document.body.style.overflow = this.toc.classList.contains('expanded') ? 'hidden' : '';\n        });\n\n        overlay.addEventListener('click', () =&gt; {\n            this.toc.classList.remove('expanded');\n            document.body.style.overflow = '';\n        });\n    }\n\n    updateTocHeight() {\n        const lists = this.toc.querySelectorAll('.md-toc__list');\n        lists.forEach(list =&gt; {\n            if (list.parentElement.classList.contains('expanded')) {\n                list.style.height = list.scrollHeight + 'px';\n            }\n        });\n    }\n\n    onResize() {\n        // \u76d1\u542c\u7a97\u53e3\u5927\u5c0f\u53d8\u5316\uff0c\u66f4\u65b0\u76ee\u5f55\u9ad8\u5ea6\n        window.addEventListener('resize', debounce(() =&gt; {\n            this.updateTocHeight();\n        }, 100));\n    }\n}\n\n// \u5de5\u5177\u51fd\u6570\nfunction debounce(fn, delay) {\n    let timer = null;\n    return function(...args) {\n        clearTimeout(timer);\n        timer = setTimeout(() =&gt; fn.apply(this, args), delay);\n    };\n}\n\n// \u521d\u59cb\u5316\u76ee\u5f55\ndocument.addEventListener('DOMContentLoaded', () =&gt; {\n    new TableOfContents();\n});\n</code></pre> <p>\u4f7f\u7528\u8fd9\u4e9b\u4ee3\u7801\uff0c\u9700\u8981\u5728 <code>mkdocs.yml</code> \u4e2d\u6dfb\u52a0\u76f8\u5e94\u7684\u914d\u7f6e\uff1a</p> YAML<pre><code>theme:\n  name: material\n  custom_dir: docs/overrides\n  features:\n    - toc.integrate\n    - toc.follow\n\nextra_css:\n  - stylesheets/toc.css\n\nextra_javascript:\n  - javascripts/toc.js\n</code></pre> <p>\u8fd9\u6837\u5c31\u5b8c\u6210\u4e86\u4e00\u4e2a\u529f\u80fd\u5b8c\u6574\u3001\u4ea4\u4e92\u53cb\u597d\u7684\u76ee\u5f55\u5bfc\u822a\u7cfb\u7edf\uff0c\u4e3b\u8981\u7279\u70b9\u5305\u62ec\uff1a</p> <ol> <li>\u81ea\u52a8\u9ad8\u4eae\u5f53\u524d\u9605\u8bfb\u4f4d\u7f6e</li> <li>\u5e73\u6ed1\u6eda\u52a8\u5230\u76ee\u6807\u4f4d\u7f6e</li> <li>\u652f\u6301\u5c55\u5f00/\u6536\u8d77\u529f\u80fd</li> <li>\u79fb\u52a8\u7aef\u81ea\u9002\u5e94\u5e03\u5c40</li> <li>\u4f18\u96c5\u7684\u52a8\u753b\u6548\u679c</li> <li>\u826f\u597d\u7684\u53ef\u8bbf\u95ee\u6027\u652f\u6301</li> <li>\u6027\u80fd\u4f18\u5316\u8003\u8651</li> </ol>"},{"location":"Tools/Blog/Mkdocs_Material/#8","title":"8 \u63d2\u4ef6\u4f7f\u7528","text":""},{"location":"Tools/Blog/Mkdocs_Material/#81","title":"8.1 \u5fc5\u5907\u63d2\u4ef6","text":""},{"location":"Tools/Blog/Mkdocs_Material/#8111-search","title":"8.1.1.1 search","text":""},{"location":"Tools/Blog/Mkdocs_Material/#8112","title":"8.1.1.2 \u57fa\u7840\u914d\u7f6e","text":"<ol> <li>\u5b89\u88c5\u641c\u7d22\u63d2\u4ef6\uff1a</li> </ol> Bash<pre><code>pip install mkdocs-material\n</code></pre> <ol> <li>\u914d\u7f6e\u641c\u7d22\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nplugins:\n  - search:\n      # \u641c\u7d22\u7d22\u5f15\u8bbe\u7f6e\n      lang: \n        - en\n        - zh\n      separator: '[\\s\\-\\.]+'    # \u5206\u8bcd\u5206\u9694\u7b26\n      min_search_length: 2      # \u6700\u5c0f\u641c\u7d22\u957f\u5ea6\n      prebuild_index: true      # \u9884\u6784\u5efa\u7d22\u5f15\n\n      # \u641c\u7d22\u5185\u5bb9\u914d\u7f6e\n      indexing:\n        full_sections: true     # \u7d22\u5f15\u5b8c\u6574\u7ae0\u8282\n        headings: true         # \u7d22\u5f15\u6807\u9898\n        content: true         # \u7d22\u5f15\u5185\u5bb9\n        tags: true           # \u7d22\u5f15\u6807\u7b7e\n\n      # \u641c\u7d22\u7ed3\u679c\u6392\u5e8f\n      scoring:\n        title_boost: 10      # \u6807\u9898\u6743\u91cd\n        heading_boost: 5     # \u6807\u9898\u6743\u91cd\n        content_boost: 1     # \u5185\u5bb9\u6743\u91cd\n</code></pre> <ol> <li>\u641c\u7d22\u4e3b\u9898\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>theme:\n  features:\n    - search.highlight        # \u641c\u7d22\u9ad8\u4eae\n    - search.share           # \u641c\u7d22\u5206\u4eab\n    - search.suggest         # \u641c\u7d22\u5efa\u8bae\n\n  # \u641c\u7d22\u754c\u9762\u6587\u5b57\n  language: zh\n  palette:\n    - search:\n        placeholder: \u641c\u7d22\u6587\u6863\n        result:\n          no_results_text: \u672a\u627e\u5230\u76f8\u5173\u7ed3\u679c\n          searching_text: \u6b63\u5728\u641c\u7d22...\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8113","title":"8.1.1.3 \u4e2d\u6587\u641c\u7d22","text":"<ol> <li>\u4e2d\u6587\u5206\u8bcd\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>plugins:\n  - search:\n      jieba_dict: dict.txt   # \u81ea\u5b9a\u4e49\u8bcd\u5178\u8def\u5f84\n      jieba_dict_user: user_dict.txt  # \u7528\u6237\u8bcd\u5178\u8def\u5f84\n\n      # \u4e2d\u6587\u5206\u8bcd\u89c4\u5219\n      separator: '[\uff0c\u3002\uff01\uff1f,!?]+'\n\n      # \u4e2d\u6587\u505c\u7528\u8bcd\n      stopwords:\n        - \u7684\n        - \u4e86\n        - \u548c\n        - \u662f\n        - \u5c31\n        - \u90fd\n        - \u800c\n        - \u53ca\n        - \u4e0e\n        - \u8fd9\n</code></pre> <ol> <li>\u81ea\u5b9a\u4e49\u8bcd\u5178\u793a\u4f8b\uff08dict.txt\uff09\uff1a</li> </ol> Text Only<pre><code>\u6280\u672f\u6587\u6863 5\n\u5f00\u53d1\u6307\u5357 5\n\u6700\u4f73\u5b9e\u8df5 5\n\u4f7f\u7528\u6559\u7a0b 5\n\u914d\u7f6e\u8bf4\u660e 5\n\u5e38\u89c1\u95ee\u9898 5\n</code></pre> <ol> <li>\u5206\u8bcd\u4f18\u5316\u811a\u672c\uff1a</li> </ol> Python<pre><code># docs/search_optimize.py\nimport jieba\nimport json\nfrom pathlib import Path\n\ndef optimize_search_index(index_file, dict_file):\n    # \u52a0\u8f7d\u81ea\u5b9a\u4e49\u8bcd\u5178\n    jieba.load_userdict(dict_file)\n\n    # \u8bfb\u53d6\u641c\u7d22\u7d22\u5f15\n    with open(index_file, 'r', encoding='utf-8') as f:\n        index = json.load(f)\n\n    # \u4f18\u5316\u5206\u8bcd\n    for doc in index['docs']:\n        # \u5206\u8bcd\u5904\u7406\u6807\u9898\n        title_words = list(jieba.cut(doc['title']))\n        doc['title'] = ' '.join(title_words)\n\n        # \u5206\u8bcd\u5904\u7406\u5185\u5bb9\n        if 'text' in doc:\n            text_words = list(jieba.cut(doc['text']))\n            doc['text'] = ' '.join(text_words)\n\n    # \u4fdd\u5b58\u4f18\u5316\u540e\u7684\u7d22\u5f15\n    with open(index_file, 'w', encoding='utf-8') as f:\n        json.dump(index, f, ensure_ascii=False, indent=2)\n\nif __name__ == '__main__':\n    index_file = 'site/search/search_index.json'\n    dict_file = 'docs/dict.txt'\n    optimize_search_index(index_file, dict_file)\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8114","title":"8.1.1.4 \u641c\u7d22\u4f18\u5316","text":"<ol> <li>\u7d22\u5f15\u4f18\u5316\uff1a</li> </ol> Python<pre><code># docs/search_index_optimizer.py\nfrom pathlib import Path\nimport json\nimport re\n\nclass SearchIndexOptimizer:\n    def __init__(self, index_path):\n        self.index_path = Path(index_path)\n        self.index = self.load_index()\n\n    def load_index(self):\n        with open(self.index_path, 'r', encoding='utf-8') as f:\n            return json.load(f)\n\n    def save_index(self):\n        with open(self.index_path, 'w', encoding='utf-8') as f:\n            json.dump(self.index, f, ensure_ascii=False, indent=2)\n\n    def optimize(self):\n        # \u6e05\u7406\u65e0\u7528\u6570\u636e\n        self._clean_data()\n        # \u4f18\u5316\u6587\u672c\n        self._optimize_text()\n        # \u6dfb\u52a0\u6743\u91cd\n        self._add_weights()\n        # \u6784\u5efa\u53cd\u5411\u7d22\u5f15\n        self._build_inverted_index()\n        # \u4fdd\u5b58\u4f18\u5316\u540e\u7684\u7d22\u5f15\n        self.save_index()\n\n    def _clean_data(self):\n        # \u79fb\u9664\u7a7a\u6587\u6863\n        self.index['docs'] = [\n            doc for doc in self.index['docs']\n            if doc.get('text') or doc.get('title')\n        ]\n\n        # \u79fb\u9664\u91cd\u590d\u6587\u6863\n        seen = set()\n        unique_docs = []\n        for doc in self.index['docs']:\n            key = f\"{doc['location']}:{doc['title']}\"\n            if key not in seen:\n                seen.add(key)\n                unique_docs.append(doc)\n        self.index['docs'] = unique_docs\n\n    def _optimize_text(self):\n        for doc in self.index['docs']:\n            # \u6e05\u7406HTML\u6807\u7b7e\n            if 'text' in doc:\n                doc['text'] = re.sub(r'&lt;[^&gt;]+&gt;', '', doc['text'])\n\n            # \u538b\u7f29\u7a7a\u767d\u5b57\u7b26\n            for field in ['title', 'text']:\n                if field in doc:\n                    doc[field] = ' '.join(doc[field].split())\n\n    def _add_weights(self):\n        for doc in self.index['docs']:\n            # \u57fa\u7840\u6743\u91cd\n            doc['weight'] = 1.0\n\n            # \u6807\u9898\u957f\u5ea6\u6743\u91cd\n            if 'title' in doc:\n                title_len = len(doc['title'])\n                doc['weight'] *= 1 + (1.0 / (1 + title_len))\n\n            # \u6587\u672c\u957f\u5ea6\u6743\u91cd\n            if 'text' in doc:\n                text_len = len(doc['text'])\n                doc['weight'] *= 1 + (100.0 / (1 + text_len))\n\n            # URL\u6df1\u5ea6\u6743\u91cd\n            depth = doc['location'].count('/')\n            doc['weight'] *= 1 + (1.0 / (1 + depth))\n\n    def _build_inverted_index(self):\n        # \u6784\u5efa\u53cd\u5411\u7d22\u5f15\n        inverted_index = {}\n        for i, doc in enumerate(self.index['docs']):\n            terms = set()\n\n            # \u6dfb\u52a0\u6807\u9898\u8bcd\n            if 'title' in doc:\n                terms.update(doc['title'].lower().split())\n\n            # \u6dfb\u52a0\u6587\u672c\u8bcd\n            if 'text' in doc:\n                terms.update(doc['text'].lower().split())\n\n            # \u66f4\u65b0\u53cd\u5411\u7d22\u5f15\n            for term in terms:\n                if term not in inverted_index:\n                    inverted_index[term] = []\n                inverted_index[term].append({\n                    'id': i,\n                    'weight': doc['weight']\n                })\n\n        self.index['inverted_index'] = inverted_index\n\n# \u4f7f\u7528\u4f18\u5316\u5668\noptimizer = SearchIndexOptimizer('site/search/search_index.json')\noptimizer.optimize()\n</code></pre> <ol> <li>\u641c\u7d22\u6027\u80fd\u76d1\u63a7\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/search-monitor.js\nclass SearchMonitor {\n    constructor() {\n        this.metrics = {\n            searches: 0,\n            avgTime: 0,\n            slowest: 0,\n            fastest: Infinity\n        };\n\n        this.init();\n    }\n\n    init() {\n        this.monitorSearchInput();\n        this.monitorSearchResults();\n        this.setupReporting();\n    }\n\n    monitorSearchInput() {\n        const searchInput = document.querySelector('.md-search__input');\n        let startTime;\n\n        searchInput?.addEventListener('input', () =&gt; {\n            startTime = performance.now();\n        });\n\n        searchInput?.addEventListener('search', () =&gt; {\n            const endTime = performance.now();\n            const duration = endTime - startTime;\n\n            this.updateMetrics(duration);\n        });\n    }\n\n    updateMetrics(duration) {\n        this.metrics.searches++;\n        this.metrics.avgTime = (\n            (this.metrics.avgTime * (this.metrics.searches - 1) + duration) /\n            this.metrics.searches\n        );\n        this.metrics.slowest = Math.max(this.metrics.slowest, duration);\n        this.metrics.fastest = Math.min(this.metrics.fastest, duration);\n\n        // \u53d1\u9001\u7edf\u8ba1\u6570\u636e\n        this.sendMetrics();\n    }\n\n    sendMetrics() {\n        // \u53ef\u4ee5\u53d1\u9001\u5230\u7edf\u8ba1\u670d\u52a1\n        console.log('Search Metrics:', this.metrics);\n    }\n}\n\n// \u521d\u59cb\u5316\u76d1\u63a7\nnew SearchMonitor();\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#812-glightbox","title":"8.1.2 glightbox","text":""},{"location":"Tools/Blog/Mkdocs_Material/#8121","title":"8.1.2.1 \u56fe\u7247\u9884\u89c8","text":"<ol> <li>\u5b89\u88c5\u63d2\u4ef6\uff1a</li> </ol> Bash<pre><code>pip install mkdocs-glightbox\n</code></pre> <ol> <li>\u57fa\u7840\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nplugins:\n  - glightbox:\n      # \u57fa\u7840\u8bbe\u7f6e\n      auto_caption: true              # \u81ea\u52a8\u6dfb\u52a0\u6807\u9898\n      caption_position: bottom        # \u6807\u9898\u4f4d\u7f6e\n      display_description: true       # \u663e\u793a\u63cf\u8ff0\n\n      # \u89e6\u6478\u8bbe\u7f6e\n      touchNavigation: true          # \u89e6\u6478\u5bfc\u822a\n      loop: true                    # \u5faa\u73af\u6d4f\u89c8\n      effect: zoom                  # \u8fc7\u6e21\u6548\u679c\n\n      # \u56fe\u7247\u8bbe\u7f6e\n      width: 100%                   # \u56fe\u7247\u5bbd\u5ea6\n      height: auto                  # \u56fe\u7247\u9ad8\u5ea6\n      zoomable: true               # \u542f\u7528\u7f29\u653e\n      draggable: true              # \u542f\u7528\u62d6\u52a8\n</code></pre> <ol> <li>\u81ea\u5b9a\u4e49\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/glightbox.css */\n.glightbox-clean {\n    /* \u5bb9\u5668\u6837\u5f0f */\n    --glow-padding: 2rem;\n    --glow-bg: rgba(0, 0, 0, 0.95);\n\n    /* \u63a7\u5236\u6309\u94ae */\n    --glow-btn-color: rgba(255, 255, 255, 0.8);\n    --glow-btn-hover: #fff;\n\n    /* \u52a0\u8f7d\u52a8\u753b */\n    --glow-loading-bg: rgba(0, 0, 0, 0.5);\n    --glow-loading-width: 40px;\n    --glow-loading-height: 40px;\n}\n\n/* \u6807\u9898\u6837\u5f0f */\n.glightbox-caption {\n    font-family: var(--md-font-family);\n    font-size: 0.9rem;\n    padding: 1rem;\n    background: rgba(0, 0, 0, 0.8);\n}\n\n/* \u63cf\u8ff0\u6837\u5f0f */\n.glightbox-description {\n    font-size: 0.8rem;\n    color: rgba(255, 255, 255, 0.7);\n    margin-top: 0.5rem;\n}\n\n/* \u52a0\u8f7d\u52a8\u753b */\n.glightbox-loading {\n    border: 3px solid rgba(255, 255, 255, 0.2);\n    border-top-color: #fff;\n    border-radius: 50%;\n    animation: glow-spin 1s linear infinite;\n}\n\n@keyframes glow-spin {\n    to { transform: rotate(360deg); }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8122","title":"8.1.2.2 \u753b\u5eca\u6a21\u5f0f","text":"<ol> <li>\u753b\u5eca\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>plugins:\n  - glightbox:\n      # \u753b\u5eca\u8bbe\u7f6e\n      gallery: true                 # \u542f\u7528\u753b\u5eca\n      gallery_mode: true           # \u753b\u5eca\u6a21\u5f0f\n      gallery_trigger: click      # \u89e6\u53d1\u65b9\u5f0f\n\n      # \u7f29\u7565\u56fe\u8bbe\u7f6e\n      thumb_width: 150            # \u7f29\u7565\u56fe\u5bbd\u5ea6\n      thumb_height: 100           # \u7f29\u7565\u56fe\u9ad8\u5ea6\n      thumb_fit: cover            # \u7f29\u7565\u56fe\u9002\u5e94\u65b9\u5f0f\n</code></pre> <ol> <li>\u753b\u5eca\u5b9e\u73b0\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/gallery.html --&gt;\n&lt;div class=\"gallery\"&gt;\n    {% for image in page.meta.gallery %}\n    &lt;a href=\"{{ image.url }}\" \n       class=\"gallery-item\"\n       data-gallery=\"gallery\"\n       data-glightbox=\"title: {{ image.title }}; description: {{ image.description }}\"&gt;\n        &lt;img src=\"{{ image.thumbnail or image.url }}\" \n             alt=\"{{ image.title }}\"\n             loading=\"lazy\"&gt;\n        {% if image.title %}\n        &lt;div class=\"gallery-caption\"&gt;{{ image.title }}&lt;/div&gt;\n        {% endif %}\n    &lt;/a&gt;\n    {% endfor %}\n&lt;/div&gt;\n</code></pre> <ol> <li>\u753b\u5eca\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/gallery.css */\n.gallery {\n    display: grid;\n    grid-template-columns: repeat(auto-fill, minmax(150px, 1fr));\n    gap: 1rem;\n    padding: 1rem;\n}\n\n.gallery-item {\n    position: relative;\n    overflow: hidden;\n    border-radius: 4px;\n    cursor: pointer;\n    transition: transform 0.3s ease;\n}\n\n.gallery-item:hover {\n    transform: translateY(-4px);\n}\n\n.gallery-item img {\n    width: 100%;\n    height: 100%;\n    object-fit: cover;\n    transition: transform 0.3s ease;\n}\n\n.gallery-item:hover img {\n    transform: scale(1.1);\n}\n\n.gallery-caption {\n    position: absolute;\n    bottom: 0;\n    left: 0;\n    right: 0;\n    padding: 0.5rem;\n    background: rgba(0, 0, 0, 0.7);\n    color: white;\n    font-size: 0.8rem;\n    transform: translateY(100%);\n    transition: transform 0.3s ease;\n}\n\n.gallery-item:hover .gallery-caption {\n    transform: translateY(0);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#82","title":"8.2 \u63a8\u8350\u63d2\u4ef6","text":""},{"location":"Tools/Blog/Mkdocs_Material/#8211-git-revision-date","title":"8.2.1.1 git-revision-date","text":""},{"location":"Tools/Blog/Mkdocs_Material/#8212","title":"8.2.1.2 \u65f6\u95f4\u663e\u793a","text":"<ol> <li>\u5b89\u88c5\u63d2\u4ef6\uff1a</li> </ol> Bash<pre><code>pip install mkdocs-git-revision-date-localized-plugin\n</code></pre> <ol> <li>\u57fa\u7840\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nplugins:\n  - git-revision-date-localized:\n      enabled: true\n      type: date           # \u663e\u793a\u7c7b\u578b\uff1adate, datetime, iso_date, iso_datetime, timeago\n      timezone: Asia/Shanghai  # \u65f6\u533a\u8bbe\u7f6e\n      locale: zh          # \u672c\u5730\u5316\u8bed\u8a00\n      fallback_to_build_date: true  # \u65e0 git \u4fe1\u606f\u65f6\u4f7f\u7528\u6784\u5efa\u65f6\u95f4\n\n      # \u65f6\u95f4\u683c\u5f0f\n      enable_creation_date: true    # \u663e\u793a\u521b\u5efa\u65f6\u95f4\n      exclude:\n        - index.md\n        - 404.md\n</code></pre> <ol> <li>\u65f6\u95f4\u663e\u793a\u6a21\u677f\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/date.html --&gt;\n{% if page.meta.git_revision_date_localized %}\n&lt;div class=\"page-date\"&gt;\n    &lt;!-- \u6700\u540e\u66f4\u65b0\u65f6\u95f4 --&gt;\n    &lt;div class=\"date-item\"&gt;\n        &lt;span class=\"date-icon\"&gt;\n            {% include \".icons/material/update.svg\" %}\n        &lt;/span&gt;\n        &lt;span class=\"date-text\"&gt;\n            \u6700\u540e\u66f4\u65b0: {{ page.meta.git_revision_date_localized }}\n        &lt;/span&gt;\n    &lt;/div&gt;\n\n    &lt;!-- \u521b\u5efa\u65f6\u95f4 --&gt;\n    {% if page.meta.git_creation_date_localized %}\n    &lt;div class=\"date-item\"&gt;\n        &lt;span class=\"date-icon\"&gt;\n            {% include \".icons/material/clock-outline.svg\" %}\n        &lt;/span&gt;\n        &lt;span class=\"date-text\"&gt;\n            \u521b\u5efa\u65f6\u95f4: {{ page.meta.git_creation_date_localized }}\n        &lt;/span&gt;\n    &lt;/div&gt;\n    {% endif %}\n&lt;/div&gt;\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8213","title":"8.2.1.3 \u66f4\u65b0\u8bb0\u5f55","text":"<ol> <li>\u66f4\u65b0\u8bb0\u5f55\u663e\u793a\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/revision.html --&gt;\n{% if page.meta.git_revision_date_localized %}\n&lt;div class=\"revision-history\"&gt;\n    &lt;h3&gt;\u66f4\u65b0\u8bb0\u5f55&lt;/h3&gt;\n    &lt;div class=\"revision-list\"&gt;\n        {% for revision in page.meta.git_history %}\n        &lt;div class=\"revision-item\"&gt;\n            &lt;div class=\"revision-date\"&gt;\n                {{ revision.date }}\n            &lt;/div&gt;\n            &lt;div class=\"revision-message\"&gt;\n                {{ revision.message }}\n            &lt;/div&gt;\n        &lt;/div&gt;\n        {% endfor %}\n    &lt;/div&gt;\n&lt;/div&gt;\n</code></pre> <ol> <li>\u6837\u5f0f\u914d\u7f6e\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/revision.css */\n.revision-history {\n    margin: 2rem 0;\n    padding: 1rem;\n    background: var(--md-code-bg-color);\n    border-radius: 4px;\n}\n\n.revision-item {\n    display: flex;\n    padding: 0.5rem 0;\n    border-bottom: 1px solid var(--md-default-fg-color--lightest);\n}\n\n.revision-date {\n    flex: 0 0 200px;\n    color: var(--md-default-fg-color--light);\n}\n\n.revision-message {\n    flex: 1;\n}\n\n/* \u65f6\u95f4\u7ebf\u6837\u5f0f */\n.revision-item {\n    position: relative;\n    padding-left: 2rem;\n}\n\n.revision-item::before {\n    content: '';\n    position: absolute;\n    left: 0;\n    top: 1rem;\n    width: 12px;\n    height: 12px;\n    background: var(--md-accent-fg-color);\n    border-radius: 50%;\n}\n\n.revision-item::after {\n    content: '';\n    position: absolute;\n    left: 5px;\n    top: 1.5rem;\n    bottom: -0.5rem;\n    width: 2px;\n    background: var(--md-default-fg-color--lightest);\n}\n\n.revision-item:last-child::after {\n    display: none;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8214","title":"8.2.1.4 \u4f5c\u8005\u4fe1\u606f","text":"<ol> <li>\u4f5c\u8005\u4fe1\u606f\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>plugins:\n  - git-revision-date-localized:\n      enabled: true\n      type: date\n      enable_authors: true     # \u542f\u7528\u4f5c\u8005\u4fe1\u606f\n      authors_file: authors.yaml   # \u4f5c\u8005\u914d\u7f6e\u6587\u4ef6\n</code></pre> <ol> <li>\u4f5c\u8005\u914d\u7f6e\u6587\u4ef6 (authors. yaml)\uff1a</li> </ol> YAML<pre><code>authors:\n  john:\n    name: John Doe\n    email: john@example.com\n    avatar: assets/authors/john.jpg\n    bio: \u8d44\u6df1\u6280\u672f\u4f5c\u8005\n    social:\n      github: johndoe\n      twitter: johndoe\n\n  jane:\n    name: Jane Smith\n    email: jane@example.com\n    avatar: assets/authors/jane.jpg\n    bio: \u524d\u7aef\u5f00\u53d1\u4e13\u5bb6\n    social:\n      github: janesmith\n      linkedin: janesmith\n</code></pre> <ol> <li>\u4f5c\u8005\u4fe1\u606f\u663e\u793a\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/author.html --&gt;\n{% if page.meta.git_authors %}\n&lt;div class=\"page-authors\"&gt;\n    {% for author in page.meta.git_authors %}\n    &lt;div class=\"author-card\"&gt;\n        &lt;!-- \u4f5c\u8005\u5934\u50cf --&gt;\n        &lt;div class=\"author-avatar\"&gt;\n            {% if author.avatar %}\n            &lt;img src=\"{{ author.avatar }}\" alt=\"{{ author.name }}\"&gt;\n            {% else %}\n            &lt;div class=\"avatar-placeholder\"&gt;\n                {{ author.name[0] }}\n            &lt;/div&gt;\n            {% endif %}\n        &lt;/div&gt;\n\n        &lt;!-- \u4f5c\u8005\u4fe1\u606f --&gt;\n        &lt;div class=\"author-info\"&gt;\n            &lt;h4 class=\"author-name\"&gt;{{ author.name }}&lt;/h4&gt;\n            {% if author.bio %}\n            &lt;p class=\"author-bio\"&gt;{{ author.bio }}&lt;/p&gt;\n            {% endif %}\n\n            &lt;!-- \u793e\u4ea4\u94fe\u63a5 --&gt;\n            {% if author.social %}\n            &lt;div class=\"author-social\"&gt;\n                {% for platform, username in author.social.items() %}\n                &lt;a href=\"https://{{ platform }}.com/{{ username }}\" \n                   target=\"_blank\"\n                   class=\"social-link\"&gt;\n                    {% include \".icons/material/\" ~ platform ~ \".svg\" %}\n                &lt;/a&gt;\n                {% endfor %}\n            &lt;/div&gt;\n            {% endif %}\n        &lt;/div&gt;\n    &lt;/div&gt;\n    {% endfor %}\n&lt;/div&gt;\n</code></pre> <ol> <li>\u4f5c\u8005\u4fe1\u606f\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/author.css */\n.page-authors {\n    margin: 2rem 0;\n    display: grid;\n    grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));\n    gap: 1rem;\n}\n\n.author-card {\n    display: flex;\n    padding: 1rem;\n    background: var(--md-code-bg-color);\n    border-radius: 8px;\n    transition: transform 0.2s ease;\n}\n\n.author-card:hover {\n    transform: translateY(-2px);\n}\n\n.author-avatar {\n    flex: 0 0 80px;\n    margin-right: 1rem;\n}\n\n.author-avatar img {\n    width: 80px;\n    height: 80px;\n    border-radius: 50%;\n    object-fit: cover;\n}\n\n.avatar-placeholder {\n    width: 80px;\n    height: 80px;\n    border-radius: 50%;\n    background: var(--md-accent-fg-color);\n    color: white;\n    display: flex;\n    align-items: center;\n    justify-content: center;\n    font-size: 2rem;\n}\n\n.author-info {\n    flex: 1;\n}\n\n.author-name {\n    margin: 0 0 0.5rem;\n    font-size: 1.1rem;\n}\n\n.author-bio {\n    color: var(--md-default-fg-color--light);\n    font-size: 0.9rem;\n    margin: 0 0 0.5rem;\n}\n\n.author-social {\n    display: flex;\n    gap: 0.5rem;\n}\n\n.social-link {\n    color: var(--md-default-fg-color--light);\n    transition: color 0.2s ease;\n}\n\n.social-link:hover {\n    color: var(--md-accent-fg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#822-minify","title":"8.2.2 minify","text":""},{"location":"Tools/Blog/Mkdocs_Material/#8221-html","title":"8.2.2.1 HTML \u538b\u7f29","text":"<ol> <li>\u5b89\u88c5\u63d2\u4ef6\uff1a</li> </ol> Bash<pre><code>pip install mkdocs-minify-plugin\n</code></pre> <ol> <li>\u914d\u7f6e\u538b\u7f29\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nplugins:\n  - minify:\n      minify_html: true\n      htmlmin_opts:\n          # HTML\u538b\u7f29\u9009\u9879\n          remove_comments: true  # \u79fb\u9664\u6ce8\u91ca\n          remove_empty_space: true  # \u79fb\u9664\u7a7a\u767d\n          remove_all_empty_space: true  # \u79fb\u9664\u6240\u6709\u7a7a\u767d\n          reduce_boolean_attributes: true  # \u7b80\u5316\u5e03\u5c14\u5c5e\u6027\n          remove_optional_tags: false  # \u4fdd\u7559\u53ef\u9009\u6807\u7b7e\n          remove_redundant_attributes: true  # \u79fb\u9664\u5197\u4f59\u5c5e\u6027\n          minify_js: true  # \u538b\u7f29\u5185\u8054JS\n          minify_css: true  # \u538b\u7f29\u5185\u8054CSS\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8222-css","title":"8.2.2.2 CSS \u538b\u7f29","text":"<ol> <li>CSS \u538b\u7f29\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>plugins:\n  - minify:\n      minify_css: true\n      css_files:\n          - stylesheets/extra.css\n          - stylesheets/custom.css\n      cssmin_opts:\n          # CSS\u538b\u7f29\u9009\u9879\n          level: 2  # \u538b\u7f29\u7ea7\u522b(1-2)\n          compatibility: ie9  # \u517c\u5bb9\u6027\n          format: beautify  # \u683c\u5f0f\u5316\u8f93\u51fa\n</code></pre> <ol> <li>CSS \u4f18\u5316\u811a\u672c\uff1a</li> </ol> Python<pre><code># docs/tools/css_optimizer.py\nimport re\nfrom pathlib import Path\nfrom csscompressor import compress\n\nclass CSSOptimizer:\n    def __init__(self, input_dir, output_dir):\n        self.input_dir = Path(input_dir)\n        self.output_dir = Path(output_dir)\n        self.output_dir.mkdir(exist_ok=True)\n\n    def optimize(self):\n        \"\"\"\u4f18\u5316\u6240\u6709CSS\u6587\u4ef6\"\"\"\n        for css_file in self.input_dir.glob('**/*.css'):\n            # \u8bfb\u53d6CSS\u5185\u5bb9\n            content = css_file.read_text(encoding='utf-8')\n\n            # \u4f18\u5316CSS\n            optimized = self.optimize_css(content)\n\n            # \u4fdd\u5b58\u4f18\u5316\u540e\u7684\u6587\u4ef6\n            output_file = self.output_dir / css_file.name\n            output_file.write_text(optimized, encoding='utf-8')\n\n    def optimize_css(self, content):\n        \"\"\"\u4f18\u5316\u5355\u4e2aCSS\u6587\u4ef6\u5185\u5bb9\"\"\"\n        # \u79fb\u9664\u6ce8\u91ca\n        content = re.sub(r'/\\*[\\s\\S]*?\\*/', '', content)\n\n        # \u79fb\u9664\u591a\u4f59\u7a7a\u767d\n        content = re.sub(r'\\s+', ' ', content)\n\n        # \u538b\u7f29CSS\n        content = compress(content)\n\n        return content\n\n# \u4f7f\u7528\u4f18\u5316\u5668\noptimizer = CSSOptimizer(\n    input_dir='docs/stylesheets',\n    output_dir='docs/stylesheets/min'\n)\noptimizer.optimize()\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8223-js","title":"8.2.2.3 JS \u538b\u7f29","text":"<ol> <li>JS \u538b\u7f29\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>plugins:\n  - minify:\n      minify_js: true\n      js_files:\n          - javascripts/extra.js\n          - javascripts/custom.js\n      jsmin_opts:\n          # JS\u538b\u7f29\u9009\u9879\n          mangle: true  # \u6df7\u6dc6\u53d8\u91cf\u540d\n          compress: true  # \u538b\u7f29\u4ee3\u7801\n          output:\n              beautify: false  # \u4e0d\u7f8e\u5316\u8f93\u51fa\n</code></pre> <ol> <li>JS \u4f18\u5316\u811a\u672c\uff1a</li> </ol> Python<pre><code># docs/tools/js_optimizer.py\nimport re\nfrom pathlib import Path\nimport terser\n\nclass JSOptimizer:\n    def __init__(self, input_dir, output_dir):\n        self.input_dir = Path(input_dir)\n        self.output_dir = Path(output_dir)\n        self.output_dir.mkdir(exist_ok=True)\n\n    def optimize(self):\n        \"\"\"\u4f18\u5316\u6240\u6709JS\u6587\u4ef6\"\"\"\n        for js_file in self.input_dir.glob('**/*.js'):\n            # \u8bfb\u53d6JS\u5185\u5bb9\n            content = js_file.read_text(encoding='utf-8')\n\n            # \u4f18\u5316JS\n            optimized = self.optimize_js(content)\n\n            # \u4fdd\u5b58\u4f18\u5316\u540e\u7684\u6587\u4ef6\n            output_file = self.output_dir / js_file.name\n            output_file.write_text(optimized, encoding='utf-8')\n\n    def optimize_js(self, content):\n        \"\"\"\u4f18\u5316\u5355\u4e2aJS\u6587\u4ef6\u5185\u5bb9\"\"\"\n        options = {\n            'compress': {\n                'pure_funcs': ['console.log'],  # \u79fb\u9664console.log\n                'drop_debugger': True,          # \u79fb\u9664debugger\n                'unsafe': True,                 # \u542f\u7528\u4e0d\u5b89\u5168\u4f18\u5316\n                'passes': 2                     # \u4f18\u5316\u6b21\u6570\n            },\n            'mangle': {\n                'toplevel': True,              # \u6df7\u6dc6\u9876\u7ea7\u4f5c\u7528\u57df\n                'eval': True                   # \u6df7\u6dc6eval\u4e2d\u7684\u53d8\u91cf\n            }\n        }\n\n        # \u4f7f\u7528terser\u538b\u7f29\n        result = terser.minify(content, options)\n        return result['code']\n\n# \u4f7f\u7528\u4f18\u5316\u5668\noptimizer = JSOptimizer(\n    input_dir='docs/javascripts',\n    output_dir='docs/javascripts/min'\n)\noptimizer.optimize()\n</code></pre> <p>\u8fd9\u4e9b\u914d\u7f6e\u548c\u811a\u672c\u53ef\u4ee5\u6709\u6548\u51cf\u5c0f\u7ad9\u70b9\u8d44\u6e90\u5927\u5c0f\uff0c\u63d0\u5347\u52a0\u8f7d\u901f\u5ea6\u3002\u8bb0\u5f97\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u4f7f\u7528\u538b\u7f29\u540e\u7684\u8d44\u6e90\u3002</p>"},{"location":"Tools/Blog/Mkdocs_Material/#823-social","title":"8.2.3 social","text":""},{"location":"Tools/Blog/Mkdocs_Material/#8231","title":"8.2.3.1 \u793e\u4ea4\u94fe\u63a5","text":"<ol> <li>\u5b89\u88c5\u63d2\u4ef6\uff1a</li> </ol> Bash<pre><code>pip install mkdocs-social-plugin\n</code></pre> <ol> <li>\u57fa\u7840\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nplugins:\n  - social:\n      enabled: true\n      # \u793e\u4ea4\u5e73\u53f0\u914d\u7f6e\n      cards: true           # \u542f\u7528\u793e\u4ea4\u5361\u7247\n      cards_color:          # \u5361\u7247\u989c\u8272\n          fill: \"#0FF1CE\"   # \u80cc\u666f\u8272\n          text: \"#FFFFFF\"   # \u6587\u5b57\u8272\n      cards_font: Roboto    # \u5361\u7247\u5b57\u4f53\n\nextra:\n  social:\n    - icon: material/github\n      link: https://github.com/username\n      name: GitHub\n    - icon: material/twitter\n      link: https://twitter.com/username\n      name: Twitter\n    - icon: material/linkedin\n      link: https://linkedin.com/in/username\n      name: LinkedIn\n</code></pre> <ol> <li>\u793e\u4ea4\u94fe\u63a5\u6a21\u677f\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/social.html --&gt;\n{% if config.extra.social %}\n&lt;div class=\"social-links\"&gt;\n    {% for social in config.extra.social %}\n    &lt;a href=\"{{ social.link }}\" \n       target=\"_blank\"\n       rel=\"noopener\"\n       title=\"{{ social.name }}\"\n       class=\"social-link\"&gt;\n        &lt;span class=\"social-icon\"&gt;\n            {% include \".icons/\" ~ social.icon ~ \".svg\" %}\n        &lt;/span&gt;\n        &lt;span class=\"social-name\"&gt;{{ social.name }}&lt;/span&gt;\n    &lt;/a&gt;\n    {% endfor %}\n&lt;/div&gt;\n{% endif %}\n</code></pre> <p>\u6837\u5f0f\u914d\u7f6e\uff1a</p> CSS<pre><code>/* docs/stylesheets/social.css */\n.social-links {\n    display: flex;\n    gap: 1rem;\n    margin: 2rem 0;\n}\n\n.social-link {\n    display: flex;\n    align-items: center;\n    padding: 0.5rem 1rem;\n    color: var(--md-default-fg-color);\n    text-decoration: none;\n    background: var(--md-code-bg-color);\n    border-radius: 2rem;\n    transition: all 0.2s ease;\n}\n\n.social-link:hover {\n    transform: translateY(-2px);\n    color: var(--md-accent-fg-color);\n    background: var(--md-code-bg-color--light);\n}\n\n.social-icon {\n    margin-right: 0.5rem;\n    width: 1.2rem;\n    height: 1.2rem;\n}\n\n.social-name {\n    font-size: 0.9rem;\n}\n\n/* \u52a8\u753b\u6548\u679c */\n.social-link .social-icon {\n    transition: transform 0.2s ease;\n}\n\n.social-link:hover .social-icon {\n    transform: scale(1.2);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8232","title":"8.2.3.2 \u5206\u4eab\u529f\u80fd","text":"<ol> <li>\u5206\u4eab\u529f\u80fd\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nextra:\n  social_share:\n    - platform: twitter\n      text: \u5206\u4eab\u5230 Twitter\n      icon: material/twitter\n    - platform: facebook\n      text: \u5206\u4eab\u5230 Facebook\n      icon: material/facebook\n    - platform: linkedin\n      text: \u5206\u4eab\u5230 LinkedIn\n      icon: material/linkedin\n    - platform: weibo\n      text: \u5206\u4eab\u5230\u5fae\u535a\n      icon: material/sina-weibo\n</code></pre> <ol> <li>\u5206\u4eab\u529f\u80fd\u5b9e\u73b0\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/share.html --&gt;\n&lt;div class=\"page-share\"&gt;\n    &lt;h4&gt;\u5206\u4eab\u6587\u7ae0&lt;/h4&gt;\n    &lt;div class=\"share-buttons\"&gt;\n        {% for share in config.extra.social_share %}\n        &lt;button class=\"share-button\" \n                data-platform=\"{{ share.platform }}\"\n                onclick=\"shareContent('{{ share.platform }}')\"&gt;\n            &lt;span class=\"share-icon\"&gt;\n                {% include \".icons/\" ~ share.icon ~ \".svg\" %}\n            &lt;/span&gt;\n            &lt;span class=\"share-text\"&gt;{{ share.text }}&lt;/span&gt;\n        &lt;/button&gt;\n        {% endfor %}\n    &lt;/div&gt;\n&lt;/div&gt;\n\n&lt;script&gt;\nfunction shareContent(platform) {\n    const url = encodeURIComponent(window.location.href);\n    const title = encodeURIComponent(document.title);\n    const text = encodeURIComponent(document.querySelector('meta[name=\"description\"]')?.content || '');\n\n    let shareUrl;\n    switch(platform) {\n        case 'twitter':\n            shareUrl = `https://twitter.com/intent/tweet?url=${url}&amp;text=${title}`;\n            break;\n        case 'facebook':\n            shareUrl = `https://www.facebook.com/sharer/sharer.php?u=${url}`;\n            break;\n        case 'linkedin':\n            shareUrl = `https://www.linkedin.com/sharing/share-offsite/?url=${url}`;\n            break;\n        case 'weibo':\n            shareUrl = `http://service.weibo.com/share/share.php?url=${url}&amp;title=${title}`;\n            break;\n    }\n\n    window.open(shareUrl, '_blank', 'width=600,height=400');\n}\n&lt;/script&gt;\n</code></pre> <ol> <li>\u5206\u4eab\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/share.css */\n.page-share {\n    margin: 2rem 0;\n    padding: 1rem;\n    background: var(--md-code-bg-color);\n    border-radius: 8px;\n}\n\n.share-buttons {\n    display: flex;\n    flex-wrap: wrap;\n    gap: 0.5rem;\n    margin-top: 1rem;\n}\n\n.share-button {\n    display: flex;\n    align-items: center;\n    padding: 0.5rem 1rem;\n    border: none;\n    border-radius: 2rem;\n    background: var(--md-default-bg-color);\n    color: var(--md-default-fg-color);\n    cursor: pointer;\n    transition: all 0.2s ease;\n}\n\n.share-button:hover {\n    background: var(--md-accent-fg-color);\n    color: white;\n}\n\n.share-icon {\n    margin-right: 0.5rem;\n    width: 1.2rem;\n    height: 1.2rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8233","title":"8.2.3.3 \u5173\u6ce8\u6309\u94ae","text":"<ol> <li>\u5173\u6ce8\u6309\u94ae\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>extra:\n  follow_buttons:\n    - platform: github\n      username: your-username\n      icon: material/github\n      text: \u5173\u6ce8\u6211\u7684 GitHub\n    - platform: twitter\n      username: your-username\n      icon: material/twitter\n      text: \u5173\u6ce8\u6211\u7684 Twitter\n</code></pre> <ol> <li>\u5173\u6ce8\u6309\u94ae\u5b9e\u73b0\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/follow.html --&gt;\n&lt;div class=\"follow-buttons\"&gt;\n    {% for btn in config.extra.follow_buttons %}\n    &lt;a href=\"https://{{ btn.platform }}.com/{{ btn.username }}\"\n       target=\"_blank\"\n       class=\"follow-button\"\n       data-platform=\"{{ btn.platform }}\"&gt;\n        &lt;span class=\"follow-icon\"&gt;\n            {% include \".icons/\" ~ btn.icon ~ \".svg\" %}\n        &lt;/span&gt;\n        &lt;span class=\"follow-text\"&gt;{{ btn.text }}&lt;/span&gt;\n        &lt;span class=\"follow-count\" id=\"{{ btn.platform }}-count\"&gt;\n            &lt;!-- \u5c06\u901a\u8fc7API\u52a8\u6001\u66f4\u65b0 --&gt;\n        &lt;/span&gt;\n    &lt;/a&gt;\n    {% endfor %}\n&lt;/div&gt;\n\n&lt;script&gt;\nasync function updateFollowCounts() {\n    const buttons = document.querySelectorAll('.follow-button');\n\n    for (const button of buttons) {\n        const platform = button.dataset.platform;\n        const username = button.href.split('/').pop();\n\n        // \u83b7\u53d6\u5173\u6ce8\u6570\n        const count = await getFollowCount(platform, username);\n\n        // \u66f4\u65b0\u663e\u793a\n        const countElement = button.querySelector('.follow-count');\n        if (countElement &amp;&amp; count) {\n            countElement.textContent = formatCount(count);\n        }\n    }\n}\n\nasync function getFollowCount(platform, username) {\n    switch (platform) {\n        case 'github':\n            const response = await fetch(`https://api.github.com/users/${username}`);\n            const data = await response.json();\n            return data.followers;\n\n        // \u5176\u4ed6\u5e73\u53f0API\u5b9e\u73b0...\n        default:\n            return null;\n    }\n}\n\nfunction formatCount(count) {\n    if (count &gt;= 1000000) {\n        return (count / 1000000).toFixed(1) + 'M';\n    }\n    if (count &gt;= 1000) {\n        return (count / 1000).toFixed(1) + 'K';\n    }\n    return count.toString();\n}\n\n// \u521d\u59cb\u5316\nupdateFollowCounts();\n&lt;/script&gt;\n</code></pre> <ol> <li>\u5173\u6ce8\u6309\u94ae\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/follow.css */\n.follow-buttons {\n    display: flex;\n    flex-wrap: wrap;\n    gap: 1rem;\n    margin: 2rem 0;\n}\n\n.follow-button {\n    display: flex;\n    align-items: center;\n    padding: 0.5rem 1rem;\n    text-decoration: none;\n    background: var(--md-code-bg-color);\n    border-radius: 2rem;\n    transition: all 0.2s ease;\n}\n\n.follow-button:hover {\n    transform: translateY(-2px);\n}\n\n/* \u5e73\u53f0\u7279\u5b9a\u6837\u5f0f */\n.follow-button[data-platform=\"github\"] {\n    color: #333;\n}\n\n.follow-button[data-platform=\"github\"]:hover {\n    background: #333;\n    color: white;\n}\n\n.follow-button[data-platform=\"twitter\"] {\n    color: #1DA1F2;\n}\n\n.follow-button[data-platform=\"twitter\"]:hover {\n    background: #1DA1F2;\n    color: white;\n}\n\n.follow-icon {\n    margin-right: 0.5rem;\n    width: 1.2rem;\n    height: 1.2rem;\n}\n\n.follow-count {\n    margin-left: 0.5rem;\n    padding: 0.2rem 0.5rem;\n    background: rgba(0, 0, 0, 0.1);\n    border-radius: 1rem;\n    font-size: 0.8rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#824-tags","title":"8.2.4 tags","text":""},{"location":"Tools/Blog/Mkdocs_Material/#8241","title":"8.2.4.1 \u6807\u7b7e\u7cfb\u7edf","text":"<ol> <li>\u5b89\u88c5\u63d2\u4ef6\uff1a</li> </ol> Bash<pre><code>pip install mkdocs-tags-plugin\n</code></pre> <ol> <li>\u914d\u7f6e\u6807\u7b7e\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nplugins:\n  - tags:\n      tags_file: tags.md\n      tags_allowed:  # \u5141\u8bb8\u7684\u6807\u7b7e\u5217\u8868\n        - Python\n        - JavaScript\n        - CSS\n        - HTML\n      tags_extra_files:\n        cloud: tag_cloud.md    # \u6807\u7b7e\u4e91\u9875\u9762\n        list: tag_list.md      # \u6807\u7b7e\u5217\u8868\u9875\u9762\n</code></pre> <ol> <li>\u5728\u6587\u6863\u4e2d\u4f7f\u7528\u6807\u7b7e\uff1a</li> </ol> Markdown<pre><code>---\ntags:\n  - Python\n  - \u6559\u7a0b\n---\n\n# Python \u5165\u95e8\u6559\u7a0b\n</code></pre> <ol> <li>\u6807\u7b7e\u663e\u793a\u7ec4\u4ef6\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/tags.html --&gt;\n{% if page.meta.tags %}\n&lt;div class=\"page-tags\"&gt;\n    {% for tag in page.meta.tags %}\n    &lt;a href=\"{{ base_url }}/tags/#{{ tag|lower }}\" class=\"tag\"&gt;\n        &lt;span class=\"tag-icon\"&gt;\n            {% include \".icons/material/tag.svg\" %}\n        &lt;/span&gt;\n        &lt;span class=\"tag-text\"&gt;{{ tag }}&lt;/span&gt;\n    &lt;/a&gt;\n    {% endfor %}\n&lt;/div&gt;\n{% endif %}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8242","title":"8.2.4.2 \u6807\u7b7e\u4e91","text":"<ol> <li>\u6807\u7b7e\u4e91\u5b9e\u73b0\uff1a</li> </ol> Python<pre><code># docs/plugins/tags/cloud.py\nfrom collections import Counter\nimport math\n\nclass TagCloud:\n    def __init__(self, tags):\n        self.tags = Counter(tags)\n        self.min_size = 0.8\n        self.max_size = 2.0\n\n    def get_tag_sizes(self):\n        \"\"\"\u8ba1\u7b97\u6807\u7b7e\u5927\u5c0f\"\"\"\n        if not self.tags:\n            return {}\n\n        # \u83b7\u53d6\u6700\u5927\u548c\u6700\u5c0f\u9891\u7387\n        max_freq = max(self.tags.values())\n        min_freq = min(self.tags.values())\n\n        # \u8ba1\u7b97\u6bcf\u4e2a\u6807\u7b7e\u7684\u5927\u5c0f\n        sizes = {}\n        for tag, freq in self.tags.items():\n            if max_freq == min_freq:\n                sizes[tag] = (self.max_size + self.min_size) / 2\n            else:\n                size = self.min_size + (self.max_size - self.min_size) * \\\n                       ((freq - min_freq) / (max_freq - min_freq))\n                sizes[tag] = round(size, 2)\n\n        return sizes\n\ndef generate_tag_cloud(tags):\n    \"\"\"\u751f\u6210\u6807\u7b7e\u4e91HTML\"\"\"\n    cloud = TagCloud(tags)\n    sizes = cloud.get_tag_sizes()\n\n    html = ['&lt;div class=\"tag-cloud\"&gt;']\n\n    for tag, size in sizes.items():\n        html.append(f'''\n            &lt;a href=\"#tag-{tag.lower()}\" \n               class=\"tag-cloud-item\"\n               style=\"font-size: {size}rem\"&gt;\n                {tag}\n            &lt;/a&gt;\n        ''')\n\n    html.append('&lt;/div&gt;')\n    return '\\n'.join(html)\n</code></pre> <ol> <li>\u6807\u7b7e\u4e91\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/tags.css */\n.tag-cloud {\n    display: flex;\n    flex-wrap: wrap;\n    justify-content: center;\n    gap: 1rem;\n    padding: 2rem;\n}\n\n.tag-cloud-item {\n    color: var(--md-default-fg-color);\n    text-decoration: none;\n    padding: 0.5rem 1rem;\n    border-radius: 2rem;\n    background: var(--md-code-bg-color);\n    transition: all 0.2s ease;\n}\n\n.tag-cloud-item:hover {\n    transform: scale(1.1);\n    background: var(--md-accent-fg-color);\n    color: white;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8243","title":"8.2.4.3 \u6807\u7b7e\u9875\u9762","text":"<ol> <li>\u6807\u7b7e\u5217\u8868\u9875\u9762\uff1a</li> </ol> Markdown<pre><code># \u6807\u7b7e\u7d22\u5f15\n\n## \u6807\u7b7e\u4e91\n[TAGS_CLOUD]\n\n## \u6807\u7b7e\u5217\u8868\n[TAGS_LIST]\n</code></pre> <ol> <li>\u6807\u7b7e\u9875\u9762\u751f\u6210\u5668\uff1a</li> </ol> Python<pre><code># docs/plugins/tags/generator.py\nfrom pathlib import Path\nimport yaml\n\nclass TagPageGenerator:\n    def __init__(self, config):\n        self.config = config\n        self.tags = {}\n\n    def collect_tags(self):\n        \"\"\"\u6536\u96c6\u6240\u6709\u6807\u7b7e\"\"\"\n        docs_dir = Path(self.config['docs_dir'])\n\n        for md_file in docs_dir.glob('**/*.md'):\n            # \u8bfb\u53d6\u6587\u4ef6frontmatter\n            content = md_file.read_text(encoding='utf-8')\n            if content.startswith('---'):\n                try:\n                    # \u89e3\u6790frontmatter\n                    _, frontmatter, _ = content.split('---', 2)\n                    meta = yaml.safe_load(frontmatter)\n\n                    if 'tags' in meta:\n                        # \u83b7\u53d6\u76f8\u5bf9\u8def\u5f84\n                        rel_path = md_file.relative_to(docs_dir)\n                        url = str(rel_path).replace('\\\\', '/')[:-3]  # \u79fb\u9664.md\n\n                        # \u6dfb\u52a0\u5230\u6807\u7b7e\u7d22\u5f15\n                        for tag in meta['tags']:\n                            if tag not in self.tags:\n                                self.tags[tag] = []\n                            self.tags[tag].append({\n                                'title': meta.get('title', url),\n                                'url': url,\n                                'description': meta.get('description', '')\n                            })\n                except:\n                    continue\n\n    def generate_tag_pages(self):\n        \"\"\"\u751f\u6210\u6807\u7b7e\u76f8\u5173\u9875\u9762\"\"\"\n        self.collect_tags()\n\n        # \u751f\u6210\u6807\u7b7e\u5217\u8868\u9875\u9762\n        if 'list' in self.config['tags_extra_files']:\n            self.generate_list_page()\n\n        # \u751f\u6210\u6bcf\u4e2a\u6807\u7b7e\u7684\u8be6\u60c5\u9875\u9762\n        self.generate_tag_detail_pages()\n\n    def generate_list_page(self):\n        \"\"\"\u751f\u6210\u6807\u7b7e\u5217\u8868\u9875\u9762\"\"\"\n        template = \"\"\"\n# \u6807\u7b7e\u5217\u8868\n\n{% for tag, posts in tags.items() %}\n## {{ tag }}\n\n{% for post in posts %}\n- [{{ post.title }}]({{ post.url }}){% if post.description %} - {{ post.description }}{% endif %}\n{% endfor %}\n\n{% endfor %}\n\"\"\"\n        # \u4f7f\u7528 Jinja2 \u6e32\u67d3\u6a21\u677f\n        from jinja2 import Template\n        content = Template(template).render(tags=self.tags)\n\n        # \u4fdd\u5b58\u9875\u9762\n        output_file = Path(self.config['docs_dir']) / 'tags' / 'list.md'\n        output_file.parent.mkdir(exist_ok=True)\n        output_file.write_text(content, encoding='utf-8')\n\n    def generate_tag_detail_pages(self):\n        \"\"\"\u751f\u6210\u6bcf\u4e2a\u6807\u7b7e\u7684\u8be6\u60c5\u9875\u9762\"\"\"\n        template = \"\"\"\n# \u6807\u7b7e: {{ tag }}\n\n## \u76f8\u5173\u6587\u7ae0\n\n{% for post in posts %}\n### [{{ post.title }}]({{ post.url }})\n{% if post.description %}\n{{ post.description }}\n{% endif %}\n{% endfor %}\n\n## \u76f8\u5173\u6807\u7b7e\n{% for related_tag in related_tags %}\n- [{{ related_tag }}](../{{ related_tag | lower }})\n{% endfor %}\n\"\"\"\n        # \u6807\u7b7e\u76ee\u5f55\n        tags_dir = Path(self.config['docs_dir']) / 'tags'\n        tags_dir.mkdir(exist_ok=True)\n\n        # \u4e3a\u6bcf\u4e2a\u6807\u7b7e\u751f\u6210\u9875\u9762\n        for tag, posts in self.tags.items():\n            # \u67e5\u627e\u76f8\u5173\u6807\u7b7e\n            related_tags = self.find_related_tags(tag)\n\n            # \u6e32\u67d3\u5185\u5bb9\n            content = Template(template).render(\n                tag=tag,\n                posts=posts,\n                related_tags=related_tags\n            )\n\n            # \u4fdd\u5b58\u9875\u9762\n            output_file = tags_dir / f\"{tag.lower()}.md\"\n            output_file.write_text(content, encoding='utf-8')\n\n    def find_related_tags(self, current_tag):\n        \"\"\"\u67e5\u627e\u76f8\u5173\u6807\u7b7e\"\"\"\n        related = set()\n\n        # \u83b7\u53d6\u5f53\u524d\u6807\u7b7e\u7684\u6240\u6709\u6587\u7ae0\n        current_posts = self.tags[current_tag]\n\n        # \u904d\u5386\u6240\u6709\u5176\u4ed6\u6807\u7b7e\n        for tag, posts in self.tags.items():\n            if tag == current_tag:\n                continue\n\n            # \u8ba1\u7b97\u6587\u7ae0\u4ea4\u96c6\n            intersection = set(p['url'] for p in posts) &amp; \\\n                          set(p['url'] for p in current_posts)\n\n            # \u5982\u679c\u6709\u5171\u540c\u6587\u7ae0\uff0c\u8ba4\u4e3a\u662f\u76f8\u5173\u6807\u7b7e\n            if intersection:\n                related.add(tag)\n\n        return list(related)\n</code></pre> <ol> <li>\u6807\u7b7e\u9875\u9762\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/tags-page.css */\n/* \u6807\u7b7e\u5217\u8868\u9875\u9762 */\n.tags-list {\n    margin: 2rem 0;\n}\n\n.tag-section {\n    margin-bottom: 3rem;\n}\n\n.tag-section h2 {\n    color: var(--md-accent-fg-color);\n    border-bottom: 2px solid var(--md-accent-fg-color);\n    padding-bottom: 0.5rem;\n}\n\n.tag-section .post-list {\n    margin-left: 1rem;\n}\n\n.post-list-item {\n    margin: 1rem 0;\n}\n\n.post-list-item .post-title {\n    font-weight: 500;\n    color: var(--md-default-fg-color);\n    text-decoration: none;\n}\n\n.post-list-item .post-description {\n    font-size: 0.9rem;\n    color: var(--md-default-fg-color--light);\n    margin-top: 0.2rem;\n}\n\n/* \u6807\u7b7e\u8be6\u60c5\u9875\u9762 */\n.tag-detail {\n    padding: 2rem;\n}\n\n.tag-detail-header {\n    text-align: center;\n    margin-bottom: 3rem;\n}\n\n.tag-detail-title {\n    font-size: 2rem;\n    color: var(--md-primary-fg-color);\n}\n\n.tag-detail-count {\n    color: var(--md-default-fg-color--light);\n}\n\n.related-posts {\n    margin: 2rem 0;\n}\n\n.related-post {\n    padding: 1rem;\n    margin: 1rem 0;\n    background: var(--md-code-bg-color);\n    border-radius: 8px;\n    transition: transform 0.2s ease;\n}\n\n.related-post:hover {\n    transform: translateX(0.5rem);\n}\n\n.related-tags {\n    display: flex;\n    flex-wrap: wrap;\n    gap: 0.5rem;\n    margin: 2rem 0;\n}\n\n.related-tag {\n    padding: 0.2rem 0.8rem;\n    background: var(--md-code-bg-color);\n    border-radius: 2rem;\n    font-size: 0.9rem;\n    color: var(--md-default-fg-color);\n    text-decoration: none;\n    transition: all 0.2s ease;\n}\n\n.related-tag:hover {\n    background: var(--md-accent-fg-color);\n    color: white;\n}\n</code></pre> <ol> <li>\u9875\u9762\u4ea4\u4e92\u529f\u80fd\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/tags.js\nclass TagsManager {\n    constructor() {\n        this.initializeFilters();\n        this.setupSearch();\n        this.setupSorting();\n    }\n\n    initializeFilters() {\n        const tagList = document.querySelector('.tags-list');\n        if (!tagList) return;\n\n        // \u521b\u5efa\u8fc7\u6ee4\u5668\n        const filterContainer = document.createElement('div');\n        filterContainer.className = 'tags-filter';\n        filterContainer.innerHTML = `\n            &lt;input type=\"text\" \n                   class=\"filter-input\" \n                   placeholder=\"\u641c\u7d22\u6807\u7b7e...\"&gt;\n            &lt;select class=\"sort-select\"&gt;\n                &lt;option value=\"name\"&gt;\u6309\u540d\u79f0\u6392\u5e8f&lt;/option&gt;\n                &lt;option value=\"count\"&gt;\u6309\u6587\u7ae0\u6570\u91cf\u6392\u5e8f&lt;/option&gt;\n            &lt;/select&gt;\n        `;\n\n        tagList.insertBefore(filterContainer, tagList.firstChild);\n    }\n\n    setupSearch() {\n        const input = document.querySelector('.filter-input');\n        if (!input) return;\n\n        input.addEventListener('input', () =&gt; {\n            const query = input.value.toLowerCase();\n            const sections = document.querySelectorAll('.tag-section');\n\n            sections.forEach(section =&gt; {\n                const tag = section.querySelector('h2').textContent.toLowerCase();\n                section.style.display = tag.includes(query) ? 'block' : 'none';\n            });\n        });\n    }\n\n    setupSorting() {\n        const select = document.querySelector('.sort-select');\n        if (!select) return;\n\n        select.addEventListener('change', () =&gt; {\n            const sections = Array.from(document.querySelectorAll('.tag-section'));\n            const container = sections[0].parentElement;\n\n            sections.sort((a, b) =&gt; {\n                const aTag = a.querySelector('h2').textContent;\n                const bTag = b.querySelector('h2').textContent;\n                const aCount = this.getPostCount(a);\n                const bCount = this.getPostCount(b);\n\n                if (select.value === 'name') {\n                    return aTag.localeCompare(bTag);\n                } else {\n                    return bCount - aCount;\n                }\n            });\n\n            // \u91cd\u65b0\u63d2\u5165\u6392\u5e8f\u540e\u7684\u7ae0\u8282\n            sections.forEach(section =&gt; container.appendChild(section));\n        });\n    }\n\n    getPostCount(section) {\n        return section.querySelectorAll('.post-list-item').length;\n    }\n}\n\n// \u521d\u59cb\u5316\u6807\u7b7e\u7ba1\u7406\u5668\ndocument.addEventListener('DOMContentLoaded', () =&gt; {\n    new TagsManager();\n});\n</code></pre> <p>\u4f7f\u7528\u4ee5\u4e0a\u4ee3\u7801\uff0c\u4f60\u53ef\u4ee5\u5b9e\u73b0\u4e00\u4e2a\u529f\u80fd\u5b8c\u6574\u7684\u6807\u7b7e\u7cfb\u7edf\uff0c\u5305\u62ec\uff1a</p> <ol> <li>\u6807\u7b7e\u4e91\u53ef\u89c6\u5316</li> <li>\u6807\u7b7e\u5217\u8868\u6d4f\u89c8</li> <li>\u6807\u7b7e\u8be6\u60c5\u9875\u9762</li> <li>\u76f8\u5173\u6807\u7b7e\u63a8\u8350</li> <li>\u6807\u7b7e\u641c\u7d22\u548c\u6392\u5e8f</li> <li>\u54cd\u5e94\u5f0f\u5e03\u5c40</li> </ol> <p>\u914d\u7f6e\u6587\u4ef6\u9700\u8981\u6dfb\u52a0\u76f8\u5e94\u7684\u5f15\u7528\uff1a</p> YAML<pre><code># mkdocs.yml\nextra_css:\n  - stylesheets/tags.css\n  - stylesheets/tags-page.css\n\nextra_javascript:\n  - javascripts/tags.js\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#9","title":"9 \u529f\u80fd\u6269\u5c55","text":""},{"location":"Tools/Blog/Mkdocs_Material/#91","title":"9.1 \u8bc4\u8bba\u7cfb\u7edf","text":""},{"location":"Tools/Blog/Mkdocs_Material/#911-giscus","title":"9.1.1 Giscus \u914d\u7f6e","text":"<ol> <li>\u57fa\u7840\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nextra:\n  comments:\n    provider: giscus\n    repo: username/repo\n    repo_id: your_repo_id\n    category: Comments\n    category_id: your_category_id\n</code></pre> <ol> <li>Giscus \u7ec4\u4ef6\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/comments.html --&gt;\n{% if config.extra.comments.provider == 'giscus' %}\n&lt;div class=\"comments-container\"&gt;\n    &lt;h3&gt;\u8bc4\u8bba&lt;/h3&gt;\n    &lt;div class=\"giscus\"&gt;&lt;/div&gt;\n\n    &lt;script&gt;\n        function loadGiscus() {\n            const script = document.createElement('script');\n            script.src = 'https://giscus.app/client.js';\n            script.setAttribute('data-repo', '{{ config.extra.comments.repo }}');\n            script.setAttribute('data-repo-id', '{{ config.extra.comments.repo_id }}');\n            script.setAttribute('data-category', '{{ config.extra.comments.category }}');\n            script.setAttribute('data-category-id', '{{ config.extra.comments.category_id }}');\n            script.setAttribute('data-mapping', 'pathname');\n            script.setAttribute('data-reactions-enabled', '1');\n            script.setAttribute('data-emit-metadata', '0');\n            script.setAttribute('data-theme', 'preferred_color_scheme');\n            script.setAttribute('crossorigin', 'anonymous');\n            script.async = true;\n\n            document.querySelector('.giscus').appendChild(script);\n        }\n\n        // \u5ef6\u8fdf\u52a0\u8f7d\u8bc4\u8bba\n        if ('IntersectionObserver' in window) {\n            const observer = new IntersectionObserver((entries) =&gt; {\n                if (entries[0].isIntersecting) {\n                    loadGiscus();\n                    observer.disconnect();\n                }\n            });\n\n            observer.observe(document.querySelector('.comments-container'));\n        } else {\n            loadGiscus();\n        }\n    &lt;/script&gt;\n&lt;/div&gt;\n{% endif %}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#912","title":"9.1.2 \u81ea\u5b9a\u4e49\u8bc4\u8bba\u6837\u5f0f","text":"CSS<pre><code>/* docs/stylesheets/comments.css */\n.comments-container {\n    margin: 3rem 0;\n    padding-top: 2rem;\n    border-top: 1px solid var(--md-default-fg-color--lightest);\n}\n\n.giscus {\n    width: 100%;\n}\n\n/* Giscus \u4e3b\u9898\u9002\u914d */\n.giscus-frame {\n    background-color: var(--md-default-bg-color);\n    color: var(--md-default-fg-color);\n}\n\n/* \u6697\u8272\u6a21\u5f0f\u9002\u914d */\n[data-md-color-scheme=\"slate\"] .giscus-frame {\n    background-color: var(--md-default-bg-color--dark);\n    color: var(--md-default-fg-color--dark);\n}\n\n/* \u8bc4\u8bba\u6846\u6837\u5f0f */\n.giscus .gsc-comment-box {\n    background-color: var(--md-code-bg-color);\n    border-radius: 8px;\n    padding: 1rem;\n}\n\n/* \u8bc4\u8bba\u5217\u8868\u6837\u5f0f */\n.giscus .gsc-comment {\n    margin: 1rem 0;\n    padding: 1rem;\n    background-color: var(--md-code-bg-color);\n    border-radius: 8px;\n    transition: transform 0.2s ease;\n}\n\n.giscus .gsc-comment:hover {\n    transform: translateX(4px);\n}\n\n/* \u6309\u94ae\u6837\u5f0f */\n.giscus .gsc-button {\n    background-color: var(--md-primary-fg-color);\n    color: var(--md-primary-bg-color);\n    border: none;\n    padding: 0.5rem 1rem;\n    border-radius: 4px;\n    cursor: pointer;\n    transition: all 0.2s ease;\n}\n\n.giscus .gsc-button:hover {\n    background-color: var(--md-primary-fg-color--dark);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#92","title":"9.2 \u6570\u636e\u7edf\u8ba1","text":""},{"location":"Tools/Blog/Mkdocs_Material/#921-google-analytics","title":"9.2.1 Google Analytics","text":"<ol> <li>GA4 \u914d\u7f6e\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nextra:\n  analytics:\n    provider: google\n    property: G-XXXXXXXXXX\n\n    # \u4e8b\u4ef6\u8ffd\u8e2a\n    events: true\n    # \u7528\u6237\u884c\u4e3a\u8ffd\u8e2a\n    behavior: true\n</code></pre> <ol> <li>GA4 \u5b9e\u73b0\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/analytics.html --&gt;\n{% if config.extra.analytics.provider == 'google' %}\n&lt;!-- Google Analytics --&gt;\n&lt;script async src=\"https://www.googletagmanager.com/gtag/js?id={{ config.extra.analytics.property }}\"&gt;&lt;/script&gt;\n&lt;script&gt;\n  window.dataLayer = window.dataLayer || [];\n  function gtag(){dataLayer.push(arguments);}\n  gtag('js', new Date());\n  gtag('config', '{{ config.extra.analytics.property }}');\n\n  // \u4e8b\u4ef6\u8ffd\u8e2a\n  if ({{ config.extra.analytics.events|tojson }}) {\n      document.addEventListener('DOMContentLoaded', function() {\n          // \u70b9\u51fb\u4e8b\u4ef6\u8ffd\u8e2a\n          document.addEventListener('click', function(e) {\n              const target = e.target.closest('a');\n              if (target) {\n                  gtag('event', 'click', {\n                      'event_category': 'link',\n                      'event_label': target.href\n                  });\n              }\n          });\n\n          // \u6eda\u52a8\u4e8b\u4ef6\u8ffd\u8e2a\n          let lastScrollDepth = 0;\n          window.addEventListener('scroll', debounce(function() {\n              const scrollDepth = Math.round(\n                  (window.scrollY + window.innerHeight) / \n                  document.documentElement.scrollHeight * 100\n              );\n\n              if (scrollDepth &gt; lastScrollDepth) {\n                  gtag('event', 'scroll_depth', {\n                      'depth': scrollDepth\n                  });\n                  lastScrollDepth = scrollDepth;\n              }\n          }, 500));\n\n          // \u641c\u7d22\u4e8b\u4ef6\u8ffd\u8e2a\n          const searchInput = document.querySelector('.md-search__input');\n          if (searchInput) {\n              searchInput.addEventListener('search', function() {\n                  gtag('event', 'search', {\n                      'search_term': this.value\n                  });\n              });\n          }\n      });\n  }\n\n  // \u7528\u6237\u884c\u4e3a\u8ffd\u8e2a\n  if ({{ config.extra.analytics.behavior|tojson }}) {\n      // \u9875\u9762\u505c\u7559\u65f6\u95f4\n      let startTime = Date.now();\n      window.addEventListener('beforeunload', function() {\n          const duration = Math.round((Date.now() - startTime) / 1000);\n          gtag('event', 'time_on_page', {\n              'duration': duration\n          });\n      });\n\n      // \u590d\u5236\u884c\u4e3a\u8ffd\u8e2a\n      document.addEventListener('copy', function() {\n          gtag('event', 'content_copy');\n      });\n  }\n&lt;/script&gt;\n{% endif %}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#922","title":"9.2.2 \u4e0d\u849c\u5b50\u7edf\u8ba1","text":"<ol> <li>\u4e0d\u849c\u5b50\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>extra:\n  analytics:\n    busuanzi: true\n</code></pre> <ol> <li>\u4e0d\u849c\u5b50\u5b9e\u73b0\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/busuanzi.html --&gt;\n{% if config.extra.analytics.busuanzi %}\n&lt;script async src=\"//busuanzi.ibruce.info/busuanzi/2.3/busuanzi.pure.mini.js\"&gt;&lt;/script&gt;\n\n&lt;div class=\"page-views\"&gt;\n    &lt;!-- \u603b\u8bbf\u95ee\u91cf --&gt;\n    &lt;span id=\"busuanzi_container_site_pv\"&gt;\n        \u603b\u8bbf\u95ee\u91cf: &lt;span id=\"busuanzi_value_site_pv\"&gt;&lt;/span&gt;\u6b21\n    &lt;/span&gt;\n\n    &lt;!-- \u603b\u8bbf\u5ba2\u6570 --&gt;\n    &lt;span id=\"busuanzi_container_site_uv\"&gt;\n        \u8bbf\u5ba2\u6570: &lt;span id=\"busuanzi_value_site_uv\"&gt;&lt;/span&gt;\u4eba\n    &lt;/span&gt;\n\n    &lt;!-- \u9875\u9762\u8bbf\u95ee\u91cf --&gt;\n    &lt;span id=\"busuanzi_container_page_pv\"&gt;\n        \u672c\u6587\u8bbf\u95ee\u91cf: &lt;span id=\"busuanzi_value_page_pv\"&gt;&lt;/span&gt;\u6b21\n    &lt;/span&gt;\n&lt;/div&gt;\n\n&lt;style&gt;\n.page-views {\n    display: flex;\n    gap: 1rem;\n    margin: 1rem 0;\n    padding: 0.5rem;\n    background: var(--md-code-bg-color);\n    border-radius: 4px;\n    font-size: 0.9rem;\n}\n\n.page-views span {\n    color: var(--md-default-fg-color--light);\n}\n\n.page-views span span {\n    color: var(--md-accent-fg-color);\n    font-weight: bold;\n}\n&lt;/style&gt;\n{% endif %}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#93","title":"9.3 \u793e\u4ea4\u5206\u4eab","text":""},{"location":"Tools/Blog/Mkdocs_Material/#931","title":"9.3.1 \u5206\u4eab\u6309\u94ae","text":"<ol> <li>\u5206\u4eab\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>extra:\n  social_share:\n    enabled: true\n    platforms:\n      - name: twitter\n        icon: material/twitter\n        color: '#1DA1F2'\n      - name: facebook\n        icon: material/facebook\n        color: '#4267B2'\n      - name: linkedin\n        icon: material/linkedin\n        color: '#0A66C2'\n      - name: weibo\n        icon: material/sina-weibo\n        color: '#E6162D'\n</code></pre> <ol> <li>\u5206\u4eab\u6309\u94ae\u5b9e\u73b0\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/share.html --&gt;\n{% if config.extra.social_share.enabled %}\n&lt;div class=\"share-container\"&gt;\n    &lt;h4&gt;\u5206\u4eab\u6587\u7ae0&lt;/h4&gt;\n    &lt;div class=\"share-buttons\"&gt;\n        {% for platform in config.extra.social_share.platforms %}\n        &lt;button class=\"share-button\" \n                data-platform=\"{{ platform.name }}\"\n                style=\"--platform-color: {{ platform.color }}\"\n                onclick=\"shareContent('{{ platform.name }}')\"&gt;\n            &lt;span class=\"share-icon\"&gt;\n                {% include \".icons/\" ~ platform.icon ~ \".svg\" %}\n            &lt;/span&gt;\n            &lt;span class=\"share-text\"&gt;\u5206\u4eab\u5230 {{ platform.name|title }}&lt;/span&gt;\n        &lt;/button&gt;\n        {% endfor %}\n    &lt;/div&gt;\n&lt;/div&gt;\n\n&lt;style&gt;\n.share-container {\n    margin: 2rem 0;\n}\n\n.share-buttons {\n    display: flex;\n    flex-wrap: wrap;\n    gap: 0.5rem;\n    margin-top: 1rem;\n}\n\n.share-button {\n    display: flex;\n    align-items: center;\n    padding: 0.5rem 1rem;\n    border: none;\n    border-radius: 4px;\n    background: var(--md-code-bg-color);\n    color: var(--platform-color);\n    cursor: pointer;\n    transition: all 0.2s ease;\n}\n\n.share-button:hover {\n    background: var(--platform-color);\n    color: white;\n    transform: translateY(-2px);\n}\n\n.share-icon {\n    margin-right: 0.5rem;\n}\n&lt;/style&gt;\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#932","title":"9.3.2 \u5206\u4eab\u94fe\u63a5\u751f\u6210","text":"JavaScript<pre><code>// docs/javascripts/share.js\nclass ShareManager {\n    constructor() {\n        this.title = document.title;\n        this.url = window.location.href;\n        this.description = document\n            .querySelector('meta[name=\"description\"]')\n            ?.content || '';\n    }\n\n    generateShareUrl(platform) {\n        const params = new URLSearchParams();\n        switch (platform) {\n            case 'twitter':\n                return `https://twitter.com/intent/tweet?${\n                    params.set('text', this.title),\n                    params.set('url', this.url)\n                }`;\n\n            case 'facebook':\n                return `https://www.facebook.com/sharer/sharer.php?${\n                    params.set('u', this.url)\n                }`;\n\n            case 'linkedin':\n                return `https://www.linkedin.com/sharing/share-offsite/?${\n                    params.set('url', this.url)\n                }`;\n\n            case 'weibo':\n                return `http://service.weibo.com/share/share.php?${\n                    params.set('title', this.title),\n                    params.set('url', this.url)\n                }`;\n\n            default:\n                return null;\n        }\n    }\n\n    async share(platform) {\n        // \u68c0\u67e5\u662f\u5426\u652f\u6301\u539f\u751f\u5206\u4eab\n        if (navigator.share &amp;&amp; platform === 'native') {\n            try {\n                await navigator.share({\n                    title: this.title,\n                    text: this.description,\n                    url: this.url\n                });\n                return true;\n            } catch (err) {\n                console.warn('Native share failed:', err);\n                return false;\n            }\n        }\n\n        // \u4f7f\u7528\u5f39\u7a97\u5206\u4eab\n        const url = this.generateShareUrl(platform);\n        if (url) {\n            window.open(url, '_blank', 'width=600,height=400');\n            return true;\n        }\n\n        return false;\n    }\n\n    // \u81ea\u5b9a\u4e49\u5206\u4eab\u5185\u5bb9\n    setContent(title, description) {\n        this.title = title;\n        this.description = description;\n    }\n}\n\n// \u5168\u5c40\u5206\u4eab\u529f\u80fd\nwindow.shareContent = async function(platform) {\n    const shareManager = new ShareManager();\n    const success = await shareManager.share(platform);\n\n    // \u8bb0\u5f55\u5206\u4eab\u4e8b\u4ef6\n    if (success) {\n        recordShare(platform);\n    }\n};\n\n// \u5206\u4eab\u7edf\u8ba1\nfunction recordShare(platform) {\n    // GA4 \u4e8b\u4ef6\u8ffd\u8e2a\n    if (typeof gtag !== 'undefined') {\n        gtag('event', 'share', {\n            'platform': platform,\n            'title': document.title,\n            'url': window.location.href\n        });\n    }\n\n    // \u672c\u5730\u5b58\u50a8\u7edf\u8ba1\n    const stats = JSON.parse(localStorage.getItem('share_stats') || '{}');\n    stats[platform] = (stats[platform] || 0) + 1;\n    localStorage.setItem('share_stats', JSON.stringify(stats));\n\n    updateShareCount(platform);\n}\n\n// \u66f4\u65b0\u5206\u4eab\u8ba1\u6570\nfunction updateShareCount(platform) {\n    const countElement = document.querySelector(\n        `.share-count[data-platform=\"${platform}\"]`\n    );\n    if (countElement) {\n        const stats = JSON.parse(localStorage.getItem('share_stats') || '{}');\n        countElement.textContent = stats[platform] || 0;\n    }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#94","title":"9.4 \u7ad9\u5185\u641c\u7d22","text":""},{"location":"Tools/Blog/Mkdocs_Material/#941","title":"9.4.1 \u641c\u7d22\u4f18\u5316","text":"<ol> <li>\u641c\u7d22\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>plugins:\n  - search:\n      lang:\n        - en\n        - zh\n      separator: '[\\s\\-\\.,!\\?\uff0c\u3002\uff01\uff1f]+'  # \u5206\u8bcd\u5206\u9694\u7b26\n      prebuild_index: true\n      indexing:\n        full_sections: true\n        headings: true\n        content: true\n        tags: true\n\n      # \u9ad8\u7ea7\u641c\u7d22\u914d\u7f6e\n      search_boost: true     # \u542f\u7528\u641c\u7d22\u63d0\u5347\n      search_threshold: 0.3  # \u641c\u7d22\u9608\u503c\n      search_fields:         # \u641c\u7d22\u5b57\u6bb5\u6743\u91cd\n        title: 10\n        tags: 8\n        content: 5\n</code></pre> <p>\u641c\u7d22\u4f18\u5316\u5b9e\u73b0\uff1a</p> JavaScript<pre><code>// docs/javascripts/search-enhance.js\nclass SearchEnhancer {\n    constructor() {\n        this.searchIndex = null;\n        this.searchResults = [];\n        this.searchHistory = [];\n        this.maxHistoryItems = 10;\n\n        this.init();\n    }\n\n    async init() {\n        // \u52a0\u8f7d\u641c\u7d22\u7d22\u5f15\n        await this.loadSearchIndex();\n        // \u52a0\u8f7d\u641c\u7d22\u5386\u53f2\n        this.loadSearchHistory();\n        // \u521d\u59cb\u5316\u641c\u7d22\u7ec4\u4ef6\n        this.setupSearch();\n    }\n\n    async loadSearchIndex() {\n        try {\n            const response = await fetch('/search/search_index.json');\n            const data = await response.json();\n\n            // \u4f7f\u7528 Lunr.js \u6784\u5efa\u7d22\u5f15\n            this.searchIndex = lunr(function() {\n                this.use(lunr.multiLanguage('en', 'zh'));\n\n                this.ref('location');\n                this.field('title', { boost: 10 });\n                this.field('tags', { boost: 8 });\n                this.field('text', { boost: 5 });\n\n                data.docs.forEach(function(doc) {\n                    this.add(doc);\n                }, this);\n            });\n        } catch (error) {\n            console.error('Failed to load search index:', error);\n        }\n    }\n\n    setupSearch() {\n        const searchInput = document.querySelector('.md-search__input');\n        if (!searchInput) return;\n\n        // \u9632\u6296\u5904\u7406\n        searchInput.addEventListener('input', debounce((e) =&gt; {\n            const query = e.target.value;\n            if (query.length &gt;= 2) {\n                this.performSearch(query);\n            } else {\n                this.clearResults();\n            }\n        }, 200));\n\n        // \u641c\u7d22\u5386\u53f2\n        searchInput.addEventListener('focus', () =&gt; {\n            this.showSearchHistory();\n        });\n    }\n\n    performSearch(query) {\n        if (!this.searchIndex) return;\n\n        try {\n            // \u6267\u884c\u641c\u7d22\n            this.searchResults = this.searchIndex.search(query);\n\n            // \u7ed3\u679c\u540e\u5904\u7406\n            this.searchResults = this.postProcessResults(this.searchResults, query);\n\n            // \u663e\u793a\u7ed3\u679c\n            this.displayResults(this.searchResults);\n\n            // \u663e\u793a\u641c\u7d22\u5efa\u8bae\n            this.showSearchSuggestions(query);\n        } catch (error) {\n            console.error('Search failed:', error);\n        }\n    }\n\n    postProcessResults(results, query) {\n        return results\n            .map(result =&gt; {\n                // \u8ba1\u7b97\u76f8\u5173\u5ea6\u5206\u6570\n                const score = this.calculateRelevanceScore(result, query);\n\n                return {\n                    ...result,\n                    score: score,\n                    highlights: this.generateHighlights(result, query)\n                };\n            })\n            // \u6309\u5206\u6570\u6392\u5e8f\n            .sort((a, b) =&gt; b.score - a.score)\n            // \u9650\u5236\u7ed3\u679c\u6570\u91cf\n            .slice(0, 10);\n    }\n\n    calculateRelevanceScore(result, query) {\n        let score = result.score;\n\n        // \u6807\u9898\u5339\u914d\u52a0\u5206\n        if (result.title?.toLowerCase().includes(query.toLowerCase())) {\n            score *= 1.5;\n        }\n\n        // \u6807\u7b7e\u5339\u914d\u52a0\u5206\n        if (result.tags?.some(tag =&gt; \n            tag.toLowerCase().includes(query.toLowerCase())\n        )) {\n            score *= 1.2;\n        }\n\n        return score;\n    }\n\n    generateHighlights(result, query) {\n        const text = result.text || '';\n        const words = query.toLowerCase().split(/\\s+/);\n        const context = 50; // \u4e0a\u4e0b\u6587\u957f\u5ea6\n\n        let highlights = [];\n\n        words.forEach(word =&gt; {\n            let index = text.toLowerCase().indexOf(word);\n            while (index &gt; -1) {\n                const start = Math.max(0, index - context);\n                const end = Math.min(text.length, index + word.length + context);\n                const highlight = text.slice(start, end);\n\n                highlights.push({\n                    text: highlight,\n                    position: start\n                });\n\n                index = text.toLowerCase().indexOf(word, index + 1);\n            }\n        });\n\n        // \u5408\u5e76\u91cd\u53e0\u7684\u9ad8\u4eae\u7247\u6bb5\n        return this.mergeHighlights(highlights);\n    }\n\n    mergeHighlights(highlights) {\n        if (highlights.length === 0) return [];\n\n        highlights.sort((a, b) =&gt; a.position - b.position);\n\n        let merged = [highlights[0]];\n        for (let i = 1; i &lt; highlights.length; i++) {\n            let current = highlights[i];\n            let last = merged[merged.length - 1];\n\n            if (current.position &lt;= last.position + last.text.length) {\n                // \u5408\u5e76\u91cd\u53e0\u7684\u7247\u6bb5\n                last.text = last.text.slice(0, current.position - last.position) +\n                           current.text;\n            } else {\n                merged.push(current);\n            }\n        }\n\n        return merged;\n    }\n\n    loadSearchHistory() {\n        try {\n            this.searchHistory = JSON.parse(\n                localStorage.getItem('search_history')\n            ) || [];\n        } catch (error) {\n            this.searchHistory = [];\n        }\n    }\n\n    saveSearchHistory(query) {\n        if (!query) return;\n\n        // \u79fb\u9664\u91cd\u590d\u9879\n        this.searchHistory = this.searchHistory.filter(item =&gt; \n            item.query !== query\n        );\n\n        // \u6dfb\u52a0\u65b0\u9879\n        this.searchHistory.unshift({\n            query: query,\n            timestamp: Date.now()\n        });\n\n        // \u9650\u5236\u5386\u53f2\u8bb0\u5f55\u6570\u91cf\n        if (this.searchHistory.length &gt; this.maxHistoryItems) {\n            this.searchHistory.pop();\n        }\n\n        // \u4fdd\u5b58\u5230\u672c\u5730\u5b58\u50a8\n        localStorage.setItem(\n            'search_history',\n            JSON.stringify(this.searchHistory)\n        );\n    }\n\n    showSearchHistory() {\n        const container = document.querySelector('.md-search__history');\n        if (!container) return;\n\n        // \u6e05\u7a7a\u5bb9\u5668\n        container.innerHTML = '';\n\n        // \u663e\u793a\u5386\u53f2\u8bb0\u5f55\n        this.searchHistory.forEach(item =&gt; {\n            const element = document.createElement('div');\n            element.className = 'search-history-item';\n            element.innerHTML = `\n                &lt;span class=\"history-icon\"&gt;\n                    {% include \".icons/material/history.svg\" %}\n                &lt;/span&gt;\n                &lt;span class=\"history-query\"&gt;${item.query}&lt;/span&gt;\n                &lt;span class=\"history-time\"&gt;\n                    ${this.formatTime(item.timestamp)}\n                &lt;/span&gt;\n            `;\n\n            element.addEventListener('click', () =&gt; {\n                const searchInput = document.querySelector('.md-search__input');\n                if (searchInput) {\n                    searchInput.value = item.query;\n                    searchInput.dispatchEvent(new Event('input'));\n                }\n            });\n\n            container.appendChild(element);\n        });\n    }\n\n    formatTime(timestamp) {\n        const now = Date.now();\n        const diff = now - timestamp;\n\n        if (diff &lt; 60000) return '\u521a\u521a';\n        if (diff &lt; 3600000) return `${Math.floor(diff/60000)}\u5206\u949f\u524d`;\n        if (diff &lt; 86400000) return `${Math.floor(diff/3600000)}\u5c0f\u65f6\u524d`;\n        return `${Math.floor(diff/86400000)}\u5929\u524d`;\n    }\n}\n\n// \u521d\u59cb\u5316\u641c\u7d22\u589e\u5f3a\nnew SearchEnhancer();\n</code></pre> <p>\u641c\u7d22\u76f8\u5173\u6837\u5f0f\uff1a</p> CSS<pre><code>/* docs/stylesheets/search.css */\n/* \u641c\u7d22\u5386\u53f2 */\n.search-history-item {\n    display: flex;\n    align-items: center;\n    padding: 0.5rem 1rem;\n    cursor: pointer;\n    transition: background 0.2s ease;\n}\n\n.search-history-item:hover {\n    background: var(--md-code-bg-color);\n}\n\n.history-icon {\n    margin-right: 0.5rem;\n    color: var(--md-default-fg-color--light);\n}\n\n.history-query {\n    flex: 1;\n    font-weight: 500;\n}\n\n.history-time {\n    font-size: 0.8rem;\n    color: var(--md-default-fg-color--light);\n}\n\n/* \u641c\u7d22\u5efa\u8bae */\n.search-suggestions {\n    padding: 1rem;\n}\n\n.suggestion-item {\n    padding: 0.5rem;\n    border-radius: 4px;\n    cursor: pointer;\n    transition: background 0.2s ease;\n}\n\n.suggestion-item:hover {\n    background: var(--md-code-bg-color);\n}\n\n/* \u9ad8\u4eae\u6587\u672c */\n.search-highlight {\n    background: var(--md-accent-fg-color);\n    color: white;\n    padding: 0 0.2rem;\n    border-radius: 2px;\n}\n\n/* \u641c\u7d22\u7ed3\u679c */\n.search-result {\n    padding: 1rem;\n    border-bottom: 1px solid var(--md-default-fg-color--lightest);\n}\n\n.result-title {\n    font-size: 1.1rem;\n    font-weight: 500;\n    margin-bottom: 0.5rem;\n}\n\n.result-excerpt {\n    font-size: 0.9rem;\n    color: var(--md-default-fg-color--light);\n    margin-bottom: 0.5rem;\n}\n\n.result-meta {\n    display: flex;\n    gap: 1rem;\n    font-size: 0.8rem;\n    color: var(--md-default-fg-color--lighter);\n}\n</code></pre> <p>\u4f7f\u7528\u8fd9\u4e9b\u4ee3\u7801\uff0c\u4f60\u53ef\u4ee5\u5b9e\u73b0\u4e00\u4e2a\u529f\u80fd\u5b8c\u5584\u7684\u641c\u7d22\u7cfb\u7edf\uff0c\u5305\u62ec\uff1a</p> <ol> <li>\u9ad8\u6027\u80fd\u641c\u7d22</li> <li>\u667a\u80fd\u7ed3\u679c\u6392\u5e8f</li> <li>\u641c\u7d22\u5386\u53f2\u8bb0\u5f55</li> <li>\u641c\u7d22\u5efa\u8bae</li> <li>\u7ed3\u679c\u9ad8\u4eae</li> <li>\u591a\u8bed\u8a00\u652f\u6301</li> </ol> <p>\u8bb0\u5f97\u5728 <code>mkdocs.yml</code> \u4e2d\u6dfb\u52a0\u76f8\u5e94\u7684\u5f15\u7528\uff1a</p> YAML<pre><code>extra_css:\n  - stylesheets/search.css\n\nextra_javascript:\n  - https://unpkg.com/lunr/lunr.js\n  - https://unpkg.com/lunr-languages/lunr.stemmer.support.js\n  - https://unpkg.com/lunr-languages/lunr.zh.js\n  - javascripts/search-enhance.js\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#10","title":"10 \u90e8\u7f72\u65b9\u6848","text":""},{"location":"Tools/Blog/Mkdocs_Material/#101","title":"10.1 \u672c\u5730\u90e8\u7f72","text":""},{"location":"Tools/Blog/Mkdocs_Material/#1011","title":"10.1.1 \u6784\u5efa\u9759\u6001\u6587\u4ef6","text":"<p>\u4f7f\u7528 MkDocs \u6784\u5efa\u9759\u6001\u6587\u4ef6\uff1a</p> Bash<pre><code># \u6784\u5efa\u7ad9\u70b9\nmkdocs build\n\n# \u6307\u5b9a\u8f93\u51fa\u76ee\u5f55\nmkdocs build -d custom_site_dir\n\n# \u6e05\u7406\u5e76\u6784\u5efa\nmkdocs build --clean\n</code></pre> <p>\u6784\u5efa\u9009\u9879\u8bf4\u660e\uff1a</p> YAML<pre><code># mkdocs.yml\nsite_dir: site               # \u8f93\u51fa\u76ee\u5f55\ndocs_dir: docs              # \u6587\u6863\u6e90\u76ee\u5f55\nstrict: true                # \u4e25\u683c\u6a21\u5f0f\nuse_directory_urls: true    # \u4f7f\u7528\u76ee\u5f55 URL\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1012","title":"10.1.2 \u672c\u5730\u670d\u52a1\u5668","text":"<p>\u5f00\u53d1\u670d\u52a1\u5668\u914d\u7f6e\uff1a</p> Bash<pre><code># \u542f\u52a8\u5f00\u53d1\u670d\u52a1\u5668\nmkdocs serve\n\n# \u6307\u5b9a\u7aef\u53e3\nmkdocs serve -a localhost:8080\n\n# \u81ea\u52a8\u91cd\u8f7d\nmkdocs serve --dirtyreload\n</code></pre> <p>\u5f00\u53d1\u670d\u52a1\u5668\u9ad8\u7ea7\u914d\u7f6e\uff1a</p> YAML<pre><code># mkdocs.yml\ndev_addr: 127.0.0.1:8000    # \u5f00\u53d1\u670d\u52a1\u5668\u5730\u5740\nwatch: [docs, includes]      # \u76d1\u89c6\u7684\u76ee\u5f55\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#102-github-pages","title":"10.2 GitHub Pages \u90e8\u7f72","text":""},{"location":"Tools/Blog/Mkdocs_Material/#1021","title":"10.2.1 \u4ed3\u5e93\u914d\u7f6e","text":"<ol> <li> <p>\u521b\u5efa GitHub \u4ed3\u5e93\uff1a    - \u521b\u5efa\u65b0\u4ed3\u5e93\u6216\u4f7f\u7528\u73b0\u6709\u4ed3\u5e93    - \u4ed3\u5e93\u540d\u683c\u5f0f\uff1a <code>username.github.io</code> \u6216\u666e\u901a\u4ed3\u5e93\u540d</p> </li> <li> <p>\u914d\u7f6e\u6587\u4ef6\uff1a</p> </li> </ol> YAML<pre><code># mkdocs.yml\nsite_url: https://username.github.io/repository/\nrepo_url: https://github.com/username/repository\nedit_uri: edit/main/docs/\n</code></pre> <ol> <li>\u521d\u59cb\u5316\u4ed3\u5e93\uff1a</li> </ol> Bash<pre><code># \u521d\u59cb\u5316 Git \u4ed3\u5e93\ngit init\n\n# \u6dfb\u52a0\u8fdc\u7a0b\u4ed3\u5e93\ngit remote add origin https://github.com/username/repository.git\n\n# \u63d0\u4ea4\u521d\u59cb\u6587\u4ef6\ngit add .\ngit commit -m \"Initial commit\"\ngit push -u origin main\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1022-github-actions","title":"10.2.2 GitHub Actions","text":"<p>\u521b\u5efa GitHub Actions \u5de5\u4f5c\u6d41\u6587\u4ef6\uff1a</p> YAML<pre><code># .github/workflows/ci.yml\nname: ci \non:\n  push:\n    branches: \n      - main\npermissions:\n  contents: write\njobs:\n  deploy:\n    runs-on: ubuntu-latest\n    steps:\n      - uses: actions/checkout@v4\n      - name: Configure Git Credentials\n        run: |\n          git config user.name github-actions[bot]\n          git config user.email 41898282+github-actions[bot]@users.noreply.github.com\n      - uses: actions/setup-python@v4\n        with:\n          python-version: 3.x\n      - run: echo \"cache_id=$(date --utc '+%V')\" &gt;&gt; $GITHUB_ENV \n      - uses: actions/cache@v3\n        with:\n          key: mkdocs-material-${{ env.cache_id }}\n          path: .cache\n          restore-keys: |\n            mkdocs-material-\n      - name: Install dependencies\n        run: |\n          pip install mkdocs-material\n          pip install mkdocs-glightbox\n          pip install mkdocs-git-revision-date-localized-plugin\n      - name: Deploy\n        run: mkdocs gh-deploy --force\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1023","title":"10.2.3 \u81ea\u52a8\u90e8\u7f72","text":"<p>\u914d\u7f6e\u81ea\u52a8\u90e8\u7f72\uff1a</p> <ol> <li> <p>\u542f\u7528 GitHub Pages\uff1a    - \u8fdb\u5165\u4ed3\u5e93\u8bbe\u7f6e -&gt; Pages    - Source \u9009\u62e9 <code>gh-pages</code> \u5206\u652f    - \u4fdd\u5b58\u8bbe\u7f6e</p> </li> <li> <p>\u914d\u7f6e\u90e8\u7f72\u5206\u652f\uff1a</p> </li> </ol> YAML<pre><code># mkdocs.yml\nremote_branch: gh-pages    # GitHub Pages \u5206\u652f\nremote_name: origin       # \u8fdc\u7a0b\u4ed3\u5e93\u540d\n</code></pre> <ol> <li>\u624b\u52a8\u90e8\u7f72\u547d\u4ee4\uff1a</li> </ol> Bash<pre><code># \u90e8\u7f72\u5230 GitHub Pages\nmkdocs gh-deploy\n\n# \u5f3a\u5236\u90e8\u7f72\nmkdocs gh-deploy --force\n\n# \u6307\u5b9a\u5206\u652f\nmkdocs gh-deploy --remote-branch custom-branch\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1024","title":"10.2.4 \u81ea\u5b9a\u4e49\u57df\u540d","text":"<ol> <li>\u6dfb\u52a0 CNAME \u6587\u4ef6\uff1a</li> </ol> Bash<pre><code># docs/CNAME\ndocs.example.com\n</code></pre> <ol> <li> <p>DNS \u914d\u7f6e\uff1a    - \u6dfb\u52a0 CNAME \u8bb0\u5f55\u6307\u5411 <code>username.github.io</code>    - \u6216\u6dfb\u52a0 A \u8bb0\u5f55\u6307\u5411 GitHub Pages IP</p> </li> <li> <p>\u914d\u7f6e\u6587\u4ef6\u66f4\u65b0\uff1a</p> </li> </ol> YAML<pre><code># mkdocs.yml\nsite_url: https://docs.example.com/\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#103","title":"10.3 \u6301\u7eed\u96c6\u6210","text":""},{"location":"Tools/Blog/Mkdocs_Material/#1031-cicd","title":"10.3.1 CI/CD \u914d\u7f6e","text":"<p>\u9ad8\u7ea7 GitHub Actions \u914d\u7f6e\uff1a</p> YAML<pre><code>name: CI/CD Pipeline\non:\n  push:\n    branches:\n      - main\n  pull_request:\n    branches:\n      - main\n\njobs:\n  test:\n    runs-on: ubuntu-latest\n    steps:\n      - uses: actions/checkout@v4\n\n      - name: Set up Python\n        uses: actions/setup-python@v4\n        with:\n          python-version: 3.x\n\n      - name: Cache dependencies\n        uses: actions/cache@v3\n        with:\n          path: ~/.cache/pip\n          key: ${{ runner.os }}-pip-${{ hashFiles('requirements.txt') }}\n          restore-keys: |\n            ${{ runner.os }}-pip-\n\n      - name: Install dependencies\n        run: |\n          python -m pip install --upgrade pip\n          pip install -r requirements.txt\n\n      - name: Run tests\n        run: |\n          mkdocs build --strict\n\n  deploy:\n    needs: test\n    if: github.ref == 'refs/heads/main'\n    runs-on: ubuntu-latest\n    steps:\n      - uses: actions/checkout@v4\n\n      - name: Deploy to GitHub Pages\n        run: |\n          mkdocs gh-deploy --force\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1032","title":"10.3.2 \u81ea\u52a8\u5316\u6d4b\u8bd5","text":"<ol> <li>\u94fe\u63a5\u68c0\u67e5\uff1a</li> </ol> YAML<pre><code>name: Link Check\non:\n  schedule:\n    - cron: '0 0 * * *'  # \u6bcf\u5929\u8fd0\u884c\njobs:\n  linkCheck:\n    runs-on: ubuntu-latest\n    steps:\n      - uses: actions/checkout@v4\n      - name: Link Checker\n        uses: lycheeverse/lychee-action@v1.8.0\n        with:\n          args: --verbose --no-progress 'docs/**/*.md'\n</code></pre> <ol> <li>HTML \u9a8c\u8bc1\uff1a</li> </ol> YAML<pre><code>name: HTML Validation\njobs:\n  validate:\n    runs-on: ubuntu-latest\n    steps:\n      - uses: actions/checkout@v4\n      - name: Build site\n        run: mkdocs build\n      - name: Validate HTML\n        uses: Cyb3r-Jak3/html5validator-action@v7.2.0\n        with:\n          root: site/\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1033","title":"10.3.3 \u90e8\u7f72\u7b56\u7565","text":"<ol> <li>\u5206\u652f\u7b56\u7565\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code># \u4fdd\u62a4\u5206\u652f\u8bbe\u7f6e\nbranches:\n  - name: main\n    protection:\n      required_status_checks:\n        strict: true\n        contexts: ['test', 'build']\n      required_pull_request_reviews:\n        required_approving_review_count: 1\n</code></pre> <ol> <li>\u73af\u5883\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code># \u73af\u5883\u53d8\u91cf\u8bbe\u7f6e\nenv:\n  production:\n    url: https://docs.example.com\n    branch: main\n  staging:\n    url: https://staging.docs.example.com\n    branch: staging\n</code></pre> <ol> <li>\u90e8\u7f72\u5de5\u4f5c\u6d41\uff1a</li> </ol> YAML<pre><code>name: Deployment\non:\n  push:\n    branches: [main, staging]\njobs:\n  deploy:\n    runs-on: ubuntu-latest\n    environment:\n      name: ${{ github.ref == 'refs/heads/main' &amp;&amp; 'production' || 'staging' }}\n    steps:\n      - uses: actions/checkout@v4\n\n      - name: Build and Deploy\n        env:\n          DEPLOY_URL: ${{ github.ref == 'refs/heads/main' &amp;&amp; env.production.url || env.staging.url }}\n        run: |\n          mkdocs build\n          # \u90e8\u7f72\u5230\u76f8\u5e94\u73af\u5883\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#11","title":"11 \u9644\u5f55","text":""},{"location":"Tools/Blog/Mkdocs_Material/#111-a","title":"11.1 A. \u5e38\u7528\u914d\u7f6e\u793a\u4f8b","text":""},{"location":"Tools/Blog/Mkdocs_Material/#1111-a1-mkdocs-yml","title":"11.1.1 A.1 mkdocs. yml \u5b8c\u6574\u793a\u4f8b","text":"YAML<pre><code># \u7ad9\u70b9\u57fa\u672c\u4fe1\u606f\u914d\u7f6e\nsite_name: \u9879\u76ee\u6587\u6863            # \u7ad9\u70b9\u540d\u79f0\nsite_url: https://example.com  # \u7ad9\u70b9URL\nsite_author: \u4f5c\u8005\u540d\u79f0          # \u4f5c\u8005\u4fe1\u606f\nsite_description: &gt;-          # \u7ad9\u70b9\u63cf\u8ff0\n  \u8fd9\u662f\u4e00\u4e2a\u5b8c\u6574\u7684\u6587\u6863\u793a\u4f8b\uff0c\u5305\u542b\u4e86MkDocs Material\u4e3b\u9898\u7684\u6240\u6709\u4e3b\u8981\u529f\u80fd\u914d\u7f6e\u3002\n\n# \u4ee3\u7801\u4ed3\u5e93\u4fe1\u606f\nrepo_name: username/repo      # \u4ed3\u5e93\u540d\u79f0\nrepo_url: https://github.com/username/repo  # \u4ed3\u5e93\u5730\u5740\nedit_uri: edit/main/docs/     # \u7f16\u8f91\u94fe\u63a5\n\n# \u7248\u6743\u4fe1\u606f\ncopyright: Copyright &amp;copy; 2024 # \u7248\u6743\u58f0\u660e\n\n# \u4e3b\u9898\u914d\u7f6e\ntheme:\n  name: material               # \u4f7f\u7528Material\u4e3b\u9898\n  custom_dir: overrides       # \u81ea\u5b9a\u4e49\u76ee\u5f55\n\n  # \u4e3b\u9898\u7279\u6027\u914d\u7f6e\n  features:\n    # \u5bfc\u822a\u76f8\u5173\n    - navigation.tabs         # \u9876\u90e8\u6807\u7b7e\u5bfc\u822a\n    - navigation.sections     # \u4fa7\u8fb9\u680f\u5206\u7ec4\n    - navigation.expand      # \u9ed8\u8ba4\u5c55\u5f00\u5bfc\u822a\n    - navigation.indexes     # \u5bfc\u822a\u7d22\u5f15\u9875\n    - navigation.top         # \u8fd4\u56de\u9876\u90e8\u6309\u94ae\n    - navigation.footer      # \u4e0a\u4e00\u9875/\u4e0b\u4e00\u9875\u5bfc\u822a\n\n    # \u641c\u7d22\u76f8\u5173\n    - search.suggest        # \u641c\u7d22\u5efa\u8bae\n    - search.highlight     # \u641c\u7d22\u9ad8\u4eae\n    - search.share        # \u641c\u7d22\u5206\u4eab\n\n    # \u4ee3\u7801\u76f8\u5173\n    - content.code.annotate # \u4ee3\u7801\u6ce8\u91ca\n    - content.code.copy    # \u4ee3\u7801\u590d\u5236\n\n    # \u5176\u4ed6\u529f\u80fd\n    - announce.dismiss     # \u53ef\u5173\u95ed\u516c\u544a\n    - header.autohide     # \u81ea\u52a8\u9690\u85cf\u5934\u90e8\n\n  # \u914d\u8272\u65b9\u6848\n  palette:\n    # \u4eae\u8272\u4e3b\u9898\n    - media: \"(prefers-color-scheme: light)\"\n      scheme: default\n      primary: indigo     # \u4e3b\u8272\n      accent: indigo      # \u5f3a\u8c03\u8272\n      toggle:\n        icon: material/brightness-7\n        name: \u5207\u6362\u81f3\u6697\u8272\u6a21\u5f0f\n\n    # \u6697\u8272\u4e3b\u9898\n    - media: \"(prefers-color-scheme: dark)\"\n      scheme: slate\n      primary: indigo\n      accent: indigo\n      toggle:\n        icon: material/brightness-4\n        name: \u5207\u6362\u81f3\u4eae\u8272\u6a21\u5f0f\n\n  # \u56fe\u6807\u548c\u5b57\u4f53\n  icon:\n    logo: material/book-open-page-variant # Logo\u56fe\u6807\n    repo: fontawesome/brands/github      # \u4ed3\u5e93\u56fe\u6807\n\n  font:\n    text: Roboto         # \u6b63\u6587\u5b57\u4f53\n    code: Roboto Mono    # \u4ee3\u7801\u5b57\u4f53\n\n  language: zh          # \u754c\u9762\u8bed\u8a00\n\n# \u6269\u5c55\u914d\u7f6e\nmarkdown_extensions:\n  # \u5185\u7f6e\u6269\u5c55\n  - toc:                 # \u76ee\u5f55\n      permalink: true    # \u6c38\u4e45\u94fe\u63a5\n      toc_depth: 3      # \u76ee\u5f55\u6df1\u5ea6\n  - tables              # \u8868\u683c\u652f\u6301\n  - attr_list           # \u5c5e\u6027\u5217\u8868\n  - def_list            # \u5b9a\u4e49\u5217\u8868\n  - footnotes           # \u811a\u6ce8\n  - abbr                # \u7f29\u5199\n\n  # PyMdown Extensions\n  - pymdownx.highlight:    # \u4ee3\u7801\u9ad8\u4eae\n      anchor_linenums: true\n      line_spans: __span\n      pygments_lang_class: true\n  - pymdownx.inlinehilite # \u884c\u5185\u4ee3\u7801\u9ad8\u4eae\n  - pymdownx.snippets     # \u4ee3\u7801\u7247\u6bb5\n  - pymdownx.superfences: # \u8d85\u7ea7\u56f4\u680f\n      custom_fences:\n        - name: mermaid\n          class: mermaid\n          format: !!python/name:pymdownx.superfences.fence_code_format\n  - pymdownx.tabbed:     # \u6807\u7b7e\u9875\n      alternate_style: true\n  - pymdownx.tasklist:   # \u4efb\u52a1\u5217\u8868\n      custom_checkbox: true\n  - pymdownx.emoji:      # \u8868\u60c5\u652f\u6301\n      emoji_index: !!python/name:material.extensions.emoji.twemoji\n      emoji_generator: !!python/name:material.extensions.emoji.to_svg\n  - pymdownx.details    # \u8be6\u7ec6\u4fe1\u606f\n  - pymdownx.caret      # \u4e0a\u6807\n  - pymdownx.mark       # \u6807\u8bb0\n  - pymdownx.tilde      # \u4e0b\u6807\n  - pymdownx.keys       # \u952e\u76d8\u6309\u952e\n\n# \u63d2\u4ef6\u914d\u7f6e\nplugins:\n  - search:           # \u641c\u7d22\u63d2\u4ef6\n      lang: \n        - en\n        - zh\n      separator: '[\\s\\-\\.,!\\?\uff0c\u3002\uff01\uff1f]+'\n      prebuild_index: true\n\n  - git-revision-date-localized: # Git\u65e5\u671f\u63d2\u4ef6\n      enable_creation_date: true\n      type: datetime\n\n  - minify:          # \u8d44\u6e90\u538b\u7f29\n      minify_html: true\n      minify_js: true\n      minify_css: true\n      htmlmin_opts:\n        remove_comments: true\n\n  - social:          # \u793e\u4ea4\u5206\u4eab\n      cards: true\n      cards_color:\n        fill: \"#0FF1CE\"\n        text: \"#FFFFFF\"\n\n  - tags:            # \u6807\u7b7e\u7cfb\u7edf\n      tags_file: tags.md\n\n  - statistics:      # \u7edf\u8ba1\n      page_check: true\n      page_count: true\n\n# \u9644\u52a0\u914d\u7f6e\nextra:\n  # \u793e\u4ea4\u94fe\u63a5\n  social:\n    - icon: fontawesome/brands/github\n      link: https://github.com/username\n    - icon: fontawesome/brands/twitter\n      link: https://twitter.com/username\n\n  # \u8bc4\u8bba\u7cfb\u7edf\n  comments:\n    provider: giscus\n    repo: username/repo\n    repo_id: your_repo_id\n    category: Comments\n    category_id: your_category_id\n\n  # \u5206\u6790\u7edf\u8ba1\n  analytics:\n    provider: google\n    property: G-XXXXXXXXXX\n    feedback:\n      title: \u8fd9\u7bc7\u6587\u6863\u5bf9\u60a8\u6709\u5e2e\u52a9\u5417\uff1f\n      ratings:\n        - icon: material/thumb-up-outline\n          name: \u6709\u5e2e\u52a9\n          data: 1\n          note: &gt;-\n            \u611f\u8c22\u60a8\u7684\u53cd\u9988\uff01\n        - icon: material/thumb-down-outline\n          name: \u6ca1\u5e2e\u52a9\n          data: 0\n          note: &gt;- \n            \u611f\u8c22\u60a8\u7684\u53cd\u9988\uff0c\u8bf7\u544a\u8bc9\u6211\u4eec\u5982\u4f55\u6539\u8fdb\u3002\n\n# \u989d\u5916\u7684CSS\u548cJavaScript\nextra_css:\n  - stylesheets/extra.css      # \u81ea\u5b9a\u4e49\u6837\u5f0f\n  - stylesheets/custom.css     # \u81ea\u5b9a\u4e49\u4e3b\u9898\n\nextra_javascript:\n  - javascripts/extra.js       # \u81ea\u5b9a\u4e49\u811a\u672c\n  - https://unpkg.com/mermaid/dist/mermaid.min.js  # \u5916\u90e8\u5e93\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1112-a2-github-actions","title":"11.1.2 A.2 GitHub Actions \u5de5\u4f5c\u6d41\u793a\u4f8b","text":"YAML<pre><code># .github/workflows/deploy.yml\n\nname: Deploy Documentation\non:\n  # \u89e6\u53d1\u6761\u4ef6\n  push:\n    branches:\n      - main\n    paths:\n      - 'docs/**'\n      - 'mkdocs.yml'\n      - '.github/workflows/deploy.yml'\n  pull_request:\n    branches:\n      - main\n\n  # \u5141\u8bb8\u624b\u52a8\u89e6\u53d1\n  workflow_dispatch:\n\n# \u73af\u5883\u53d8\u91cf\nenv:\n  PYTHON_VERSION: '3.10'\n  DEPLOY_BRANCH: gh-pages\n\n# \u4efb\u52a1\u5b9a\u4e49\njobs:\n  build:\n    name: Build and Deploy Documentation\n    runs-on: ubuntu-latest\n\n    steps:\n      # \u68c0\u51fa\u4ee3\u7801\n      - name: Checkout Repository\n        uses: actions/checkout@v3\n        with:\n          fetch-depth: 0  # \u83b7\u53d6\u5b8c\u6574\u7684git\u5386\u53f2\u7528\u4e8e\u6700\u8fd1\u66f4\u65b0\u65f6\u95f4\n\n      # \u8bbe\u7f6ePython\u73af\u5883\n      - name: Setup Python\n        uses: actions/setup-python@v4\n        with:\n          python-version: ${{ env.PYTHON_VERSION }}\n          cache: pip\n\n      # \u7f13\u5b58\u4f9d\u8d56\n      - name: Cache Dependencies\n        uses: actions/cache@v3\n        with:\n          path: ~/.cache/pip\n          key: ${{ runner.os }}-pip-${{ hashFiles('requirements.txt') }}\n          restore-keys: |\n            ${{ runner.os }}-pip-\n\n      # \u5b89\u88c5\u4f9d\u8d56\n      - name: Install Dependencies\n        run: |\n          python -m pip install --upgrade pip\n          pip install -r requirements.txt\n\n      # \u914d\u7f6eGit\n      - name: Configure Git\n        run: |\n          git config --global user.name \"${{ github.actor }}\"\n          git config --global user.email \"${{ github.actor }}@users.noreply.github.com\"\n\n      # \u6784\u5efa\u6587\u6863\n      - name: Build Documentation\n        run: |\n          mkdocs build --clean --verbose\n\n      # \u4f18\u5316\u8d44\u6e90\n      - name: Optimize Assets\n        run: |\n          # \u538b\u7f29\u56fe\u7247\n          find site/ -type f -name \"*.png\" -exec optipng -o5 {} \\;\n          find site/ -type f -name \"*.jpg\" -exec jpegoptim --strip-all {} \\;\n\n          # \u538b\u7f29JavaScript\u548cCSS\n          find site/ -type f -name \"*.js\" -exec uglifyjs {} -o {} \\;\n          find site/ -type f -name \"*.css\" -exec cleancss -o {} {} \\;\n\n      # \u90e8\u7f72\u5230GitHub Pages\n      - name: Deploy to GitHub Pages\n        if: github.ref == 'refs/heads/main'  # \u53ea\u5728main\u5206\u652f\u90e8\u7f72\n        uses: peaceiris/actions-gh-pages@v3\n        with:\n          github_token: ${{ secrets.GITHUB_TOKEN }}\n          publish_dir: ./site\n          publish_branch: ${{ env.DEPLOY_BRANCH }}\n          user_name: 'github-actions[bot]'\n          user_email: 'github-actions[bot]@users.noreply.github.com'\n          commit_message: ${{ github.event.head_commit.message }}\n          full_commit_message: |\n            Deploy Documentation\n\n            Commit: ${{ github.sha }}\n            Workflow: ${{ github.workflow }}\n\n            ${{ github.event.head_commit.message }}\n\n      # \u90e8\u7f72\u5b8c\u6210\u901a\u77e5\n      - name: Deployment Status\n        if: always()\n        uses: actions/github-script@v6\n        with:\n          script: |\n            const { owner, repo } = context.repo;\n            const run_id = context.runId;\n            const run_url = `https://github.com/${owner}/${repo}/actions/runs/${run_id}`;\n\n            if (context.job.status === 'success') {\n              await github.rest.issues.createComment({\n                owner,\n                repo,\n                issue_number: context.issue.number,\n                body: `\u2705 Documentation deployed successfully!\\nPreview: https://${owner}.github.io/${repo}/\\nWorkflow: ${run_url}`\n              });\n            } else {\n              await github.rest.issues.createComment({\n                owner,\n                repo,\n                issue_number: context.issue.number,\n                body: `\u274c Documentation deployment failed.\\nSee details: ${run_url}`\n              });\n            }\n\n# \u9519\u8bef\u8ffd\u8e2a\u548c\u62a5\u544a\n      - name: Report Errors\n        if: failure()\n        uses: actions/github-script@v6\n        with:\n          script: |\n            const { owner, repo } = context.repo;\n            const run_id = context.runId;\n\n            await github.rest.issues.create({\n              owner,\n              repo,\n              title: `\ud83d\udd34 Documentation deployment failed - ${new Date().toISOString()}`,\n              body: `Deployment failed for commit: ${context.sha}\\n\\nSee workflow run: https://github.com/${owner}/${repo}/actions/runs/${run_id}\\n\\nPlease check the logs for more details.`,\n              labels: ['deployment', 'bug']\n            });\n</code></pre>"},{"location":"Tools/Make/CMake/","title":"CMake \u76f8\u5173","text":""},{"location":"Tools/Make/CMake/#cmake","title":"CMake \u76f8\u5173","text":"<p> \u7ea6 161 \u4e2a\u5b57  13 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"Tools/Make/CMake/#1","title":"1 \u6784\u5efa\u6700\u5c0f\u9879\u76ee","text":"<ul> <li>CMake \u652f\u6301\u5927\u5199\u3001\u5c0f\u5199\u548c\u6df7\u5408\u5927\u5c0f\u5199\u547d\u4ee4\u3001</li> </ul> Text Only<pre><code>mkdir build\ncd build\ncmake -G\"MinGW Makefiles\" ..\ncmake --build .\n</code></pre> <p>\u4e4b\u540e\u4f1a\u751f\u6210\u53ef\u6267\u884c\u6587\u4ef6</p> Text Only<pre><code>step1/\n    build/\n    CMakeLists.txt\n    tutorial.cpp\n</code></pre>"},{"location":"Tools/Make/CMake/#2-cmakelists-txt","title":"2 \u4f18\u5316 CMakeLists. txt \u6587\u4ef6","text":"CMake<pre><code>cmake_minimum_required(VERSION 3.15)\n\n# set the project name\nproject(Tutorial)\n\nSET(SRC_LIST tutorial.cpp)\n\n# add the executable\nadd_executable(${PROJECT_NAME} ${SRC_LIST})\n</code></pre> <p>1.0.2 \u5206\u522b\u5bf9\u5e94 MAJOR MINOR PATCH</p> <ul> <li>set \u548c PROJECT_NAME</li> <li>\u6dfb\u52a0\u7248\u672c\u53f7\u548c\u914d\u7f6e\u5934\u6587\u4ef6</li> <li>\u6dfb\u52a0\u7f16\u8bd1\u65f6\u95f4\u6233</li> <li>\u6307\u5b9a C++\u6807\u51c6</li> <li>\u6dfb\u52a0\u5e93\uff08\u6dfb\u52a0\u5e93\u7684\u4f4d\u7f6e\uff0c\u5e93\u6587\u4ef6\u540d\uff0c\u5934\u6587\u4ef6\u540d\uff09</li> <li>\u5c06\u5e93\u8bbe\u7f6e\u4e3a\u53ef\u9009\u9879\uff08\u5206\u7ecf\u5178\u548c\u73b0\u4ee3\uff09</li> <li>\u6dfb\u52a0\u5e93\u7684\u4f7f\u7528\u8981\u6c42<ul> <li>INTERFACE</li> <li>PRIVATE</li> <li>PUBLIC</li> <li>\u9759\u6001\u94fe\u63a5\u5e93/\u52a8\u6001\u94fe\u63a5\u5e93</li> </ul> </li> <li>build \u76ee\u5f55\u4ecb\u7ecd</li> </ul>"},{"location":"Tools/Make/CMake/#links","title":"links","text":"<ul> <li>Site Unreachable</li> <li>IPADS\u65b0\u4eba\u57f9\u8bad\u7b2c\u4e8c\u8bb2\uff1aCMake_\u54d4\u54e9\u54d4\u54e9_bilibili</li> </ul>"},{"location":"Tools/Make/Makeflie/","title":"Makeflie","text":""},{"location":"Tools/Make/Makeflie/#make","title":"Make \u57fa\u7840","text":"<p> \u7ea6 220 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"Tools/Make/Makeflie/#make_1","title":"\u4ec0\u4e48\u662f Make","text":"<p>Make \u662f\u4e00\u4e2a\u81ea\u52a8\u5316\u6784\u5efa\u5de5\u5177\uff0c\u4f7f\u7528 Makefile \u6587\u4ef6\u6765\u5b9a\u4e49\u5982\u4f55\u7f16\u8bd1\u548c\u94fe\u63a5\u7a0b\u5e8f\u3002\u5b83\u901a\u8fc7\u68c0\u67e5\u6587\u4ef6\u7684\u65f6\u95f4\u6233\u6765\u51b3\u5b9a\u54ea\u4e9b\u6587\u4ef6\u9700\u8981\u91cd\u65b0\u7f16\u8bd1\u3002</p>"},{"location":"Tools/Make/Makeflie/#makefile","title":"Makefile \u7684\u57fa\u672c\u7ed3\u6784","text":"<p>Makefile \u7684\u57fa\u672c\u7ed3\u6784\u7531\u76ee\u6807\u3001\u4f9d\u8d56\u548c\u547d\u4ee4\u7ec4\u6210\uff0c\u901a\u5e38\u5f62\u5f0f\u4e3a\uff1a</p> Text Only<pre><code>target: dependencies     \n    command\n</code></pre>"},{"location":"Tools/Make/Makeflie/#makefile_1","title":"Makefile \u793a\u4f8b","text":"<p>\u8ba9\u6211\u4eec\u8003\u8651\u4e00\u4e2a\u7b80\u5355\u7684 C \u8bed\u8a00\u9879\u76ee\uff0c\u8be5\u793a\u4f8b\u5c06\u5c55\u793a\u5982\u4f55\u4f7f\u7528 Makefile \u6765\u7f16\u8bd1\u4e00\u4e2a\u5177\u6709\u591a\u4e2a\u6e90\u6587\u4ef6\u548c\u5934\u6587\u4ef6\u7684\u7a0b\u5e8f\uff0c\u5e76\u5c55\u793a Makefile \u76f8\u6bd4\u624b\u52a8\u547d\u4ee4\u884c\u7f16\u8bd1\u7684\u4f18\u52bf\u3002 \u7f16\u8bd1\u8fdb\u9636 - HPC\u5165\u95e8\u6307\u5357</p>"},{"location":"Tools/Make/Makeflie/#make_2","title":"Make \u7684\u5e38\u7528\u547d\u4ee4","text":"<ul> <li><code>make</code>\uff1a\u6267\u884c\u9ed8\u8ba4\u76ee\u6807\uff0c\u4e0e<code>make all</code>\u7b49\u6548\u3002</li> <li><code>make &lt;target&gt;</code>\uff1a\u6267\u884c\u5b9a\u4e49\u7684<code>&lt;target&gt;</code>\u76ee\u6807\uff0c\u5982\u679c\u6ca1\u6709\u8fd9\u4e2a\u76ee\u6807\u5c06\u8fd4\u56de\u9519\u8bef\u4fe1\u606f\u3002</li> <li><code>make -j</code>\uff1a\u5e76\u884c\u6267\u884c\u6784\u5efa\uff0c\u4f7f\u7528\u672c\u673a\u7684\u5168\u90e8\u7ebf\u7a0b</li> </ul>"},{"location":"Tools/Others/Chezmoi/","title":"\u7528 chezmoi \u5b9e\u73b0\u8de8\u8bbe\u5907\u540c\u6b65\u914d\u7f6e","text":""},{"location":"Tools/Others/Chezmoi/#chezmoi","title":"\u7528 chezmoi \u5b9e\u73b0\u8de8\u8bbe\u5907\u540c\u6b65\u914d\u7f6e","text":"<p> \u7ea6 512 \u4e2a\u5b57  142 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>\u672c\u6307\u5357\u5c06\u5e2e\u52a9\u4f60\u4f7f\u7528 chezmoi \u7ba1\u7406\u4f60\u7684\u914d\u7f6e\u6587\u4ef6\uff08dotfiles\uff09\uff0c\u5e76\u4f7f\u7528\u5305\u7ba1\u7406\u5668\u7ef4\u62a4\u8f6f\u4ef6\u5217\u8868\u3002</p>"},{"location":"Tools/Others/Chezmoi/#_1","title":"\u524d\u671f\u51c6\u5907","text":""},{"location":"Tools/Others/Chezmoi/#1","title":"1. \u9700\u8981\u7684\u5de5\u5177","text":"<ul> <li>Git</li> <li>GitHub \u8d26\u53f7</li> <li>chezmoi</li> <li>\u5305\u7ba1\u7406\u5668\uff08Windows: Scoop, Ubuntu: apt/snap\uff09</li> </ul>"},{"location":"Tools/Others/Chezmoi/#2","title":"2. \u91cd\u8981\u7684\u914d\u7f6e\u6587\u4ef6","text":"<p>Windows \u5e38\u7528\u914d\u7f6e\u6587\u4ef6:</p> Text Only<pre><code>%USERPROFILE%/\n\u251c\u2500\u2500 .gitconfig                        # Git\u914d\u7f6e\n\u251c\u2500\u2500 .ssh/                            # SSH\u914d\u7f6e\n\u251c\u2500\u2500 Documents/\n\u2502   \u2514\u2500\u2500 PowerShell/\n\u2502       \u2514\u2500\u2500 Microsoft.PowerShell_profile.ps1  # PowerShell\u914d\u7f6e\n\u251c\u2500\u2500 AppData/\n\u2502   \u251c\u2500\u2500 Roaming/\n\u2502   \u2502   \u2514\u2500\u2500 Code/\n\u2502   \u2502       \u2514\u2500\u2500 User/\n\u2502   \u2502           \u2514\u2500\u2500 settings.json    # VSCode\u914d\u7f6e\n\u2502   \u2514\u2500\u2500 Local/\n\u2514\u2500\u2500 .config/\n    \u2514\u2500\u2500 scoop/\n        \u2514\u2500\u2500 config.json              # Scoop\u914d\u7f6e\n</code></pre> <p>Ubuntu \u5e38\u7528\u914d\u7f6e\u6587\u4ef6:</p> Text Only<pre><code>~/\n\u251c\u2500\u2500 .bashrc                          # Bash\u914d\u7f6e\n\u251c\u2500\u2500 .zshrc                           # Zsh\u914d\u7f6e\n\u251c\u2500\u2500 .gitconfig                       # Git\u914d\u7f6e\n\u251c\u2500\u2500 .ssh/                           # SSH\u914d\u7f6e\n\u2514\u2500\u2500 .config/\n    \u251c\u2500\u2500 Code/\n    \u2502   \u2514\u2500\u2500 User/\n    \u2502       \u2514\u2500\u2500 settings.json       # VSCode\u914d\u7f6e\n    \u2514\u2500\u2500 tabby/\n        \u2514\u2500\u2500 config.yaml            # Tabby\u7ec8\u7aef\u914d\u7f6e\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#github","title":"GitHub \u8bbe\u7f6e","text":""},{"location":"Tools/Others/Chezmoi/#1-github","title":"1. \u521b\u5efa GitHub \u4ed3\u5e93","text":"<ol> <li>\u8bbf\u95ee GitHub \u5e76\u767b\u5f55</li> <li>\u70b9\u51fb \"New repository\"</li> <li>\u4ed3\u5e93\u540d\u79f0\u8bbe\u7f6e\u4e3a <code>dotfiles</code></li> <li>\u8bbe\u7f6e\u4e3a Public\uff08\u63a8\u8350\uff09</li> <li>\u4e0d\u8981\u521d\u59cb\u5316 README\uff08\u6211\u4eec\u5c06\u4ece\u672c\u5730\u521d\u59cb\u5316\uff09</li> <li>\u521b\u5efa\u4ed3\u5e93</li> </ol>"},{"location":"Tools/Others/Chezmoi/#2-ssh","title":"2. \u914d\u7f6e SSH \u5bc6\u94a5\uff08\u5982\u679c\u8fd8\u6ca1\u6709\uff09","text":"Bash<pre><code># \u751f\u6210SSH\u5bc6\u94a5\nssh-keygen -t ed25519 -C \"your_email@example.com\"\n\n# \u5c06\u516c\u94a5\u6dfb\u52a0\u5230GitHub\n# 1. \u590d\u5236\u516c\u94a5\u5185\u5bb9\ncat ~/.ssh/id_ed25519.pub\n# 2. \u8bbf\u95ee GitHub \u2192 Settings \u2192 SSH and GPG keys \u2192 New SSH key\n# 3. \u7c98\u8d34\u516c\u94a5\u5185\u5bb9\u5e76\u4fdd\u5b58\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#windows","title":"Windows \u914d\u7f6e","text":""},{"location":"Tools/Others/Chezmoi/#1_1","title":"1. \u5b89\u88c5\u5fc5\u8981\u5de5\u5177","text":"<p>\u4f7f\u7528 PowerShell\uff08\u4ee5\u7ba1\u7406\u5458\u8eab\u4efd\u8fd0\u884c\uff09\uff1a</p> PowerShell<pre><code># \u5b89\u88c5Scoop\nSet-ExecutionPolicy RemoteSigned -Scope CurrentUser\nirm get.scoop.sh | iex\n\n# \u5b89\u88c5Git\uff08\u5982\u679c\u8fd8\u6ca1\u6709\uff09\nscoop install git\n\n# \u5b89\u88c5chezmoi\nscoop install chezmoi\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#2-chezmoi","title":"2. \u521d\u59cb\u5316 chezmoi","text":"PowerShell<pre><code># \u521d\u59cb\u5316chezmoi\u5e76\u514b\u9686\u4f60\u7684\u4ed3\u5e93\nchezmoi init --apply https://github.com/yourusername/dotfiles.git\n# \u7528 ssh \u4e5f\u53ef\u4ee5\n\n# \u67e5\u770bchezmoi\u5c06\u8fdb\u884c\u7684\u66f4\u6539\nchezmoi diff\n\n# \u5c06\u73b0\u6709\u914d\u7f6e\u6587\u4ef6\u6dfb\u52a0\u5230chezmoi\nchezmoi add $HOME/.gitconfig\nchezmoi add $HOME/.ssh/config\nchezmoi add $HOME/Documents/PowerShell/Microsoft.PowerShell_profile.ps1\nchezmoi add $HOME/AppData/Roaming/Code/User/settings.json\n\n# \u63d0\u4ea4\u5e76\u63a8\u9001\u66f4\u6539\nchezmoi cd\ngit add .\ngit commit -m \"Initial Windows config\"\ngit push\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#3","title":"3. \u5bfc\u51fa\u8f6f\u4ef6\u5305\u5217\u8868","text":"PowerShell<pre><code># \u5bfc\u51faScoop\u5305\u5217\u8868\nscoop export &gt; packages/scoop-packages.txt\n\n# \u63d0\u4ea4\u5305\u5217\u8868\nchezmoi cd\ngit add packages/scoop-packages.txt\ngit commit -m \"Add Windows package list\"\ngit push\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#ubuntu","title":"Ubuntu \u914d\u7f6e","text":""},{"location":"Tools/Others/Chezmoi/#1_2","title":"1. \u5b89\u88c5\u5fc5\u8981\u5de5\u5177","text":"Bash<pre><code># \u5b89\u88c5Git\uff08\u5982\u679c\u8fd8\u6ca1\u6709\uff09\nsudo apt update\nsudo apt install git\n\n# \u5b89\u88c5chezmoi\nsh -c \"$(curl -fsLS get.chezmoi.io)\"\n</code></pre> <p>\u53c2\u8003\u8fd9\u4e2a\u7f51\u7ad9 Install - chezmoi \u8fdb\u884c\u4e0b\u8f7d\uff0c\u6211\u547d\u4ee4\u884c\u4e00\u76f4\u4e0d\u6210\u529f\uff0c\u76f4\u63a5\u9009\u62e9\u5bf9\u5e94\u7684\u5305\u5c31\u884c\u4e86\u3002</p> Text Only<pre><code>sudo dpkg -i chezmoi_2.54.0_linux_amd64.deb\nchezmoi --version\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#2-chezmoi_1","title":"2. \u521d\u59cb\u5316 chezmoi","text":"Bash<pre><code># \u521d\u59cb\u5316chezmoi\u5e76\u514b\u9686\u4f60\u7684\u4ed3\u5e93\nchezmoi init --apply https://github.com/yourusername/dotfiles.git\n\n# \u67e5\u770bchezmoi\u5c06\u8fdb\u884c\u7684\u66f4\u6539\nchezmoi diff\n\n# \u5c06\u73b0\u6709\u914d\u7f6e\u6587\u4ef6\u6dfb\u52a0\u5230chezmoi\nchezmoi add ~/.bashrc\nchezmoi add ~/.zshrc\nchezmoi add ~/.gitconfig\nchezmoi add ~/.ssh/config\nchezmoi add ~/.config/Code/User/settings.json\n\n# \u63d0\u4ea4\u5e76\u63a8\u9001\u66f4\u6539\nchezmoi cd\ngit add .\ngit commit -m \"Initial Ubuntu config\"\ngit push\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#3_1","title":"3. \u5bfc\u51fa\u8f6f\u4ef6\u5305\u5217\u8868","text":"Bash<pre><code>chezmoi cd\nmkdir packages\n# \u5bfc\u51faapt\u5305\u5217\u8868\ndpkg --get-selections | grep -v deinstall | awk '{print $1}' &gt; packages/apt-packages.txt\n\n# \u5bfc\u51fasnap\u5305\u5217\u8868\nsnap list | awk '{if (NR&gt;1) print $1}' &gt; packages/snap-packages.txt\n\n# \u63d0\u4ea4\u5305\u5217\u8868\ngit add packages/apt-packages.txt packages/snap-packages.txt\ngit commit -m \"Add Ubuntu package lists\"\ngit push\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#_2","title":"\u65e5\u5e38\u4f7f\u7528","text":""},{"location":"Tools/Others/Chezmoi/#1_3","title":"1. \u66f4\u65b0\u914d\u7f6e","text":"<p>\u5f53\u4f60\u4fee\u6539\u4e86\u914d\u7f6e\u6587\u4ef6\u540e\uff1a</p> Bash<pre><code># \u5c06\u66f4\u6539\u6dfb\u52a0\u5230chezmoi\nchezmoi add ~/.bashrc  # \u6216\u5176\u4ed6\u4fee\u6539\u7684\u914d\u7f6e\u6587\u4ef6\n\n# \u67e5\u770b\u66f4\u6539\nchezmoi diff\n\n# \u63d0\u4ea4\u5e76\u63a8\u9001\u66f4\u6539\nchezmoi cd\ngit add .\ngit commit -m \"Update bashrc\"\ngit push\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#2_1","title":"2. \u5728\u5176\u4ed6\u673a\u5668\u4e0a\u540c\u6b65","text":"Bash<pre><code># \u62c9\u53d6\u5e76\u5e94\u7528\u6700\u65b0\u66f4\u6539\nchezmoi update\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#3_2","title":"3. \u66f4\u65b0\u8f6f\u4ef6\u5305\u5217\u8868","text":"<p>Windows:</p> PowerShell<pre><code># \u66f4\u65b0Scoop\u5305\u5217\u8868\nscoop export &gt; packages/scoop-packages.txt\n</code></pre> <p>Ubuntu:</p> Bash<pre><code># \u66f4\u65b0apt\u5305\u5217\u8868\ndpkg --get-selections | grep -v deinstall | awk '{print $1}' &gt; packages/apt-packages.txt\n\n# \u66f4\u65b0snap\u5305\u5217\u8868\nsnap list | awk '{if (NR&gt;1) print $1}' &gt; packages/snap-packages.txt\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#4","title":"4. \u5728\u65b0\u673a\u5668\u4e0a\u8bbe\u7f6e","text":"<p>Windows:</p> PowerShell<pre><code># \u5b89\u88c5chezmoi\nscoop install chezmoi\n\n# \u521d\u59cb\u5316\u5e76\u5e94\u7528\u914d\u7f6e\nchezmoi init https://github.com/yourusername/dotfiles.git\nchezmoi apply\n</code></pre> <p>Ubuntu:</p> Bash<pre><code># \u5b89\u88c5chezmoi\nsh -c \"$(curl -fsLS get.chezmoi.io)\"\n\n# \u521d\u59cb\u5316\u5e76\u5e94\u7528\u914d\u7f6e\nchezmoi init https://github.com/yourusername/dotfiles.git\nchezmoi apply\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#_3","title":"\u5e38\u89c1\u95ee\u9898","text":""},{"location":"Tools/Others/Chezmoi/#1_4","title":"1. \u5982\u4f55\u5904\u7406\u4e0d\u540c\u673a\u5668\u7684\u7279\u5b9a\u914d\u7f6e\uff1f","text":"<p>\u4f7f\u7528\u6a21\u677f\u548c\u6761\u4ef6\u8bed\u53e5\u3002\u5728 <code>.chezmoi.toml.tmpl</code> \u4e2d\uff1a</p> TOML<pre><code>{{- $osid := .chezmoi.os -}}\n[data]\n    name = \"Your Name\"\n    email = \"your@email.com\"\n    {{- if eq .chezmoi.os \"windows\" }}\n    is_windows = true\n    {{- else if eq .chezmoi.os \"linux\" }}\n    is_linux = true\n    {{- end }}\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#2_2","title":"2. \u5982\u4f55\u5904\u7406\u654f\u611f\u4fe1\u606f\uff1f","text":"<p>\u5bf9\u4e8e\u654f\u611f\u4fe1\u606f\uff0c\u53ef\u4ee5\uff1a</p> <ol> <li>\u4f7f\u7528\u6a21\u677f\u548c\u73af\u5883\u53d8\u91cf</li> <li>\u4f7f\u7528 chezmoi \u7684\u52a0\u5bc6\u529f\u80fd</li> <li>\u5c06\u654f\u611f\u4fe1\u606f\u5b58\u50a8\u5728\u5355\u72ec\u7684\u79c1\u6709\u4ed3\u5e93\u4e2d</li> </ol>"},{"location":"Tools/Others/Chezmoi/#3_3","title":"3. \u5982\u4f55\u64a4\u9500\u66f4\u6539\uff1f","text":"Bash<pre><code># \u67e5\u770b\u5c06\u8981\u8fdb\u884c\u7684\u66f4\u6539\nchezmoi diff\n\n# \u5982\u679c\u4e0d\u6ee1\u610f\uff0c\u53ef\u4ee5\u64a4\u9500\nchezmoi forget ~/.bashrc  # \u79fb\u9664\u6587\u4ef6\u7684\u7ba1\u7406\n\n# \u6216\u8005\u91cd\u7f6e\u4e3a\u539f\u59cb\u72b6\u6001\nchezmoi apply --force\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#4_1","title":"4. \u914d\u7f6e\u6587\u4ef6\u6743\u9650\u95ee\u9898\uff1f","text":"<p>chezmoi \u4f1a\u81ea\u52a8\u5904\u7406\u6587\u4ef6\u6743\u9650\u3002\u5bf9\u4e8e\u7279\u6b8a\u6743\u9650\u9700\u6c42\uff0c\u53ef\u4ee5\u5728\u6e90\u6587\u4ef6\u540d\u4e2d\u4f7f\u7528\u7279\u6b8a\u524d\u7f00\uff1a</p> <ul> <li><code>private_</code> : \u521b\u5efa\u79c1\u6709\u6587\u4ef6 (chmod 600)</li> <li><code>executable_</code> : \u521b\u5efa\u53ef\u6267\u884c\u6587\u4ef6 (chmod 700)</li> <li><code>readonly_</code> : \u521b\u5efa\u53ea\u8bfb\u6587\u4ef6 (chmod 400)</li> </ul>"},{"location":"Tools/Others/Chezmoi/#5","title":"5. \u5982\u4f55\u67e5\u770b\u7ba1\u7406\u7684\u6587\u4ef6\uff1f","text":"Bash<pre><code># \u5217\u51fa\u6240\u6709\u7ba1\u7406\u7684\u6587\u4ef6\nchezmoi managed\n\n# \u67e5\u770b\u6e90\u6587\u4ef6\nchezmoi cd\nls -la\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#6","title":"6. \u66f4\u65b0\u51fa\u9519\u600e\u4e48\u529e\uff1f","text":"Bash<pre><code># \u5907\u4efd\u5f53\u524d\u72b6\u6001\nchezmoi archive --output=backup.tar.gz\n\n# \u91cd\u7f6e\u66f4\u6539\nchezmoi init --force\n\n# \u91cd\u65b0\u5e94\u7528\u914d\u7f6e\nchezmoi apply\n</code></pre>"},{"location":"Tools/Others/SSH/","title":"SSH\u914d\u7f6e\u6307\u5357","text":""},{"location":"Tools/Others/SSH/#ssh","title":"SSH\u914d\u7f6e\u6307\u5357","text":"<p> \u7ea6 641 \u4e2a\u5b57  195 \u884c\u4ee3\u7801  1 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 6 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"Tools/Others/SSH/#ssh_1","title":"\u4e00\u3001SSH\u57fa\u7840\u6982\u5ff5","text":""},{"location":"Tools/Others/SSH/#1-ssh","title":"1. SSH\u5de5\u4f5c\u539f\u7406","text":"<p>SSH(Secure Shell)\u662f\u4e00\u79cd\u52a0\u5bc6\u7684\u7f51\u7edc\u534f\u8bae\uff0c\u901a\u8fc7\u5728\u4e0d\u5b89\u5168\u7684\u7f51\u7edc\u4e0a\u4e3a\u7f51\u7edc\u670d\u52a1\u63d0\u4f9b\u5b89\u5168\u7684\u4f20\u8f93\u73af\u5883\u3002SSH\u901a\u8fc7\u4f7f\u7528\u52a0\u5bc6\u6280\u672f\uff0c\u80fd\u591f\u6709\u6548\u9632\u6b62\u4e2d\u95f4\u4eba\u653b\u51fb\uff0c\u4fdd\u62a4\u6570\u636e\u4f20\u8f93\u7684\u5b89\u5168\u3002</p> <p>SSH\u5de5\u4f5c\u6d41\u7a0b\uff1a 1. TCP\u8fde\u63a5\u5efa\u7acb\uff1a\u5ba2\u6237\u7aef\u548c\u670d\u52a1\u5668\u5efa\u7acbTCP\u8fde\u63a5\uff08\u9ed8\u8ba4\u7aef\u53e322\uff09 2. \u7248\u672c\u534f\u5546\uff1a\u53cc\u65b9\u4ea4\u6362\u7248\u672c\u4fe1\u606f\uff0c\u786e\u5b9a\u4f7f\u7528\u7684SSH\u534f\u8bae\u7248\u672c 3. \u5bc6\u94a5\u4ea4\u6362\uff1a\u4f7f\u7528Diffie-Hellman\u7b97\u6cd5\u4ea4\u6362\u4f1a\u8bdd\u5bc6\u94a5 4. \u8ba4\u8bc1\uff1a\u4f7f\u7528\u516c\u94a5\u6216\u5bc6\u7801\u8fdb\u884c\u8eab\u4efd\u9a8c\u8bc1 5. \u4f1a\u8bdd\uff1a\u5efa\u7acb\u52a0\u5bc6\u901a\u4fe1\u901a\u9053</p>"},{"location":"Tools/Others/SSH/#2","title":"2. \u8ba4\u8bc1\u65b9\u5f0f\u8be6\u89e3","text":""},{"location":"Tools/Others/SSH/#21","title":"2.1 \u5bc6\u7801\u8ba4\u8bc1","text":"<ul> <li>\u6700\u7b80\u5355\u4f46\u6700\u4e0d\u5b89\u5168\u7684\u8ba4\u8bc1\u65b9\u5f0f</li> <li>\u5bb9\u6613\u53d7\u5230\u66b4\u529b\u7834\u89e3\u653b\u51fb</li> <li>\u4e0d\u63a8\u8350\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u4f7f\u7528</li> </ul>"},{"location":"Tools/Others/SSH/#22","title":"2.2 \u516c\u94a5\u8ba4\u8bc1","text":"<p>\u8ba4\u8bc1\u6d41\u7a0b 1. \u5ba2\u6237\u7aef\u53d1\u9001\u516c\u94a5\u4fe1\u606f\u7ed9\u670d\u52a1\u5668 2. \u670d\u52a1\u5668\u68c0\u67e5authorized_keys\u6587\u4ef6 3. \u670d\u52a1\u5668\u751f\u6210\u968f\u673a\u5b57\u7b26\u4e32\uff0c\u7528\u516c\u94a5\u52a0\u5bc6\u540e\u53d1\u9001\u7ed9\u5ba2\u6237\u7aef 4. \u5ba2\u6237\u7aef\u7528\u79c1\u94a5\u89e3\u5bc6\uff0c\u5c06\u7ed3\u679c\u8fd4\u56de\u670d\u52a1\u5668 5. \u670d\u52a1\u5668\u9a8c\u8bc1\u7ed3\u679c\uff0c\u5b8c\u6210\u8ba4\u8bc1</p>"},{"location":"Tools/Others/SSH/#3","title":"3. \u5b89\u5168\u5efa\u8bae","text":""},{"location":"Tools/Others/SSH/#31","title":"3.1 \u57fa\u672c\u5b89\u5168\u8bbe\u7f6e","text":"Bash<pre><code># /etc/ssh/sshd_config \u5b89\u5168\u914d\u7f6e\nPermitRootLogin no                 # \u7981\u6b62root\u76f4\u63a5\u767b\u5f55\nPasswordAuthentication no          # \u7981\u7528\u5bc6\u7801\u8ba4\u8bc1\nPubkeyAuthentication yes          # \u542f\u7528\u516c\u94a5\u8ba4\u8bc1\nPermitEmptyPasswords no           # \u7981\u6b62\u7a7a\u5bc6\u7801\nProtocol 2                        # \u53ea\u4f7f\u7528SSH2\u534f\u8bae\nMaxAuthTries 3                    # \u6700\u5927\u8ba4\u8bc1\u5c1d\u8bd5\u6b21\u6570\nLoginGraceTime 30                 # \u767b\u5f55\u8d85\u65f6\u65f6\u95f4\nX11Forwarding no                  # \u7981\u7528X11\u8f6c\u53d1\uff08\u9664\u975e\u9700\u8981\uff09\nAllowUsers user1 user2            # \u9650\u5236\u5141\u8bb8\u767b\u5f55\u7684\u7528\u6237\n</code></pre>"},{"location":"Tools/Others/SSH/#32","title":"3.2 \u5bc6\u94a5\u7ba1\u7406","text":"Bash<pre><code># \u751f\u6210\u5f3a\u5bc6\u94a5\nssh-keygen -t ed25519 -C \"your_email@example.com\" -a 100\n\n# \u5bc6\u94a5\u6743\u9650\u8bbe\u7f6e\nchmod 700 ~/.ssh\nchmod 600 ~/.ssh/id_ed25519\nchmod 644 ~/.ssh/id_ed25519.pub\nchmod 600 ~/.ssh/authorized_keys\nchmod 600 ~/.ssh/known_hosts\n</code></pre>"},{"location":"Tools/Others/SSH/#ssh_2","title":"\u5e38\u7528\u7684 SSH \u547d\u4ee4","text":"<p>SSH \u6559\u7a0b \u83dc\u9e1f\u6559\u7a0b</p>"},{"location":"Tools/Others/SSH/#_1","title":"\u4e8c\u3001\u5b8c\u6574\u914d\u7f6e\u6307\u5357","text":""},{"location":"Tools/Others/SSH/#1-linux","title":"1. Linux\u670d\u52a1\u5668\u914d\u7f6e","text":"Bash<pre><code># 1. \u5b89\u88c5SSH\u670d\u52a1\u5668\nsudo apt update\nsudo apt install openssh-server\n\n# 2. \u914d\u7f6eSSH\u670d\u52a1\nsudo nano /etc/ssh/sshd_config\n\n# 3. \u57fa\u672c\u5b89\u5168\u914d\u7f6e\nPort 22                          # \u53ef\u4ee5\u4fee\u6539\u4e3a\u975e\u6807\u51c6\u7aef\u53e3\nListenAddress 0.0.0.0            # \u76d1\u542c\u5730\u5740\nProtocol 2\nPermitRootLogin no\nPasswordAuthentication no\nPubkeyAuthentication yes\nAuthorizedKeysFile .ssh/authorized_keys\nUsePAM yes\nX11Forwarding no\nPrintMotd no\nAcceptEnv LANG LC_*\nSubsystem sftp /usr/lib/openssh/sftp-server\n\n# 4. \u91cd\u542fSSH\u670d\u52a1\nsudo systemctl restart sshd\n\n# 5. \u68c0\u67e5\u670d\u52a1\u72b6\u6001\nsudo systemctl status sshd\n</code></pre>"},{"location":"Tools/Others/SSH/#2-windows-ssh","title":"2. Windows SSH\u914d\u7f6e","text":""},{"location":"Tools/Others/SSH/#21-openssh","title":"2.1 \u5b89\u88c5OpenSSH","text":"PowerShell<pre><code># \u4f7f\u7528PowerShell\u5b89\u88c5OpenSSH\n# \u68c0\u67e5OpenSSH\u72b6\u6001\nGet-WindowsCapability -Online | Where-Object Name -like 'OpenSSH*'\n\n# \u5b89\u88c5\u5ba2\u6237\u7aef\u548c\u670d\u52a1\u5668\nAdd-WindowsCapability -Online -Name OpenSSH.Client~~~~0.0.1.0\nAdd-WindowsCapability -Online -Name OpenSSH.Server~~~~0.0.1.0\n\n# \u542f\u52a8SSH\u670d\u52a1\nStart-Service sshd\nSet-Service -Name sshd -StartupType 'Automatic'\n</code></pre> \u5982\u679c\u6709\u7f51\u7edc\u95ee\u9898\u53ef\u4ee5\u4e0b\u8f7d\u5e76\u5b89\u88c5 OpenSSH \u7684\u79bb\u7ebf\u5b89\u88c5\u5305\uff1a   <ul> <li>\u60a8\u53ef\u4ee5\u5c1d\u8bd5\u4ece GitHub \u4e0a\u4e0b\u8f7d OpenSSH \u7684\u79bb\u7ebf\u5b89\u88c5\u5305\uff0c\u5e76\u6309\u7167\u4ee5\u4e0b\u6b65\u9aa4\u8fdb\u884c\u5b89\u88c5\uff1a  <ol> <li>\u8bbf\u95ee GitHub \u4e0a\u7684 Win32-OpenSSH \u53d1\u5e03\u9875\u9762\uff1aWin32-OpenSSH Releases </li> <li>\u4e0b\u8f7d\u9002\u7528\u4e8e\u60a8\u7684\u7cfb\u7edf\u7684\u5b89\u88c5\u5305\uff08Win32 \u6216 Win64\uff09\u3002  </li> <li>\u89e3\u538b\u4e0b\u8f7d\u7684\u6587\u4ef6\u5230\u4e00\u4e2a\u76ee\u5f55\u3002  </li> <li>\u4ee5\u7ba1\u7406\u5458\u6743\u9650\u6253\u5f00\u547d\u4ee4\u63d0\u793a\u7b26\uff08cmd\uff09\uff0c\u5e76\u5bfc\u822a\u5230\u89e3\u538b\u7684\u76ee\u5f55\u3002  </li> <li>\u8fd0\u884c\u00a0<code>powershell.exe -ExecutionPolicy Bypass -File install-sshd.ps1</code>\u00a0\u6765\u5b89\u88c5 OpenSSH \u670d\u52a1\u3002 </li> </ol> </li> </ul>"},{"location":"Tools/Others/SSH/#22-windows-ssh","title":"2.2 \u914d\u7f6eWindows SSH\u670d\u52a1","text":"PowerShell<pre><code># \u7f16\u8f91SSH\u914d\u7f6e\u6587\u4ef6\nnotepad \"$env:ProgramData\\ssh\\sshd_config\"\n\n# \u57fa\u672c\u914d\u7f6e\u5185\u5bb9\u4e0eLinux\u7c7b\u4f3c\uff0c\u4f46\u8def\u5f84\u9700\u8981\u8c03\u6574\nPubkeyAuthentication yes\nPasswordAuthentication no\nSubsystem sftp sftp-server.exe\n</code></pre>"},{"location":"Tools/Others/SSH/#3-ssh","title":"3. SSH\u5ba2\u6237\u7aef\u914d\u7f6e","text":""},{"location":"Tools/Others/SSH/#31-ssh","title":"3.1 \u521b\u5efaSSH\u914d\u7f6e\u6587\u4ef6","text":"Bash<pre><code># ~/.ssh/config\n# \u5168\u5c40\u8bbe\u7f6e\nHost *\n    ServerAliveInterval 60\n    ServerAliveCountMax 3\n    HashKnownHosts yes\n    GSSAPIAuthentication no\n\n# GitHub\nHost github.com\n    HostName github.com\n    User git\n    IdentityFile ~/.ssh/github_ed25519\n    AddKeysToAgent yes\n\n# \u5f00\u53d1\u670d\u52a1\u5668\nHost dev\n    HostName dev.example.com\n    User developer\n    Port 22\n    IdentityFile ~/.ssh/dev_ed25519\n    ForwardAgent yes\n\n# \u751f\u4ea7\u670d\u52a1\u5668\nHost prod\n    HostName prod.example.com\n    User deployer\n    Port 22\n    IdentityFile ~/.ssh/prod_ed25519\n    ForwardAgent no\n</code></pre>"},{"location":"Tools/Others/SSH/#_2","title":"\u4e09\u3001\u5177\u4f53\u5b9e\u8df5\uff0c\u7528\u7b14\u8bb0\u672c\u8fde\u53f0\u5f0f\u673a","text":""},{"location":"Tools/Others/SSH/#_3","title":"\u53f0\u5f0f\u7535\u8111\uff08\u670d\u52a1\u7aef\uff09\u914d\u7f6e\uff1a","text":"<ol> <li>\u5b89\u88c5\u5e76\u542f\u52a8SSH\u670d\u52a1:</li> </ol> Bash<pre><code># Ubuntu/Debian\u7cfb\u7edf\nsudo apt install openssh-server\nsudo systemctl enable ssh\nsudo systemctl start ssh\n\n# \u68c0\u67e5SSH\u670d\u52a1\u72b6\u6001\nsudo systemctl status ssh\n</code></pre> <ol> <li>\u914d\u7f6eSSH\u670d\u52a1:</li> </ol> Bash<pre><code># \u7f16\u8f91SSH\u670d\u52a1\u5668\u914d\u7f6e\nsudo nano /etc/ssh/sshd_config\n\n# \u6dfb\u52a0\u6216\u4fee\u6539\u4ee5\u4e0b\u914d\u7f6e\nPermitRootLogin no\nPasswordAuthentication no\nPubkeyAuthentication yes\nAllowUsers your_username    # \u66ff\u6362\u4e3a\u60a8\u7684\u7528\u6237\u540d\n</code></pre> <ol> <li>\u8bbe\u7f6e\u56fa\u5b9aIP\u6216\u52a8\u6001DNS:</li> </ol> Bash<pre><code># \u67e5\u770b\u5f53\u524dIP\nip addr show\n\n# \u5982\u679c\u662f\u52a8\u6001IP\uff0c\u5efa\u8bae\u8bbe\u7f6e\u9759\u6001IP\u6216\u4f7f\u7528\u52a8\u6001DNS\u670d\u52a1\n</code></pre>"},{"location":"Tools/Others/SSH/#_4","title":"\u7b14\u8bb0\u672c\uff08\u5ba2\u6237\u7aef\uff09\u914d\u7f6e\uff1a","text":"<ol> <li>\u751f\u6210SSH\u5bc6\u94a5\u5bf9\uff08\u5982\u679c\u8fd8\u6ca1\u6709\uff09:</li> </ol> Bash<pre><code>ssh-keygen -t ed25519 -C \"your_laptop\"\n</code></pre> <ol> <li>\u5c06\u516c\u94a5\u590d\u5236\u5230\u53f0\u5f0f\u673a:</li> </ol> Bash<pre><code># \u65b9\u6cd51\uff1a\u4f7f\u7528ssh-copy-id\nssh-copy-id -i ~/.ssh/id_ed25519.pub username@desktop_ip\n\n# \u65b9\u6cd52\uff1a\u624b\u52a8\u590d\u5236\ncat ~/.ssh/id_ed25519.pub | ssh username@desktop_ip \"mkdir -p ~/.ssh &amp;&amp; cat &gt;&gt; ~/.ssh/authorized_keys\"\n</code></pre> <ol> <li>\u914d\u7f6eSSH\u5ba2\u6237\u7aef:</li> </ol> Bash<pre><code># \u7f16\u8f91 ~/.ssh/config\nnano ~/.ssh/config\n\n# \u6dfb\u52a0\u4ee5\u4e0b\u914d\u7f6e\nHost desktop\n    HostName 192.168.1.xxx  # \u66ff\u6362\u4e3a\u53f0\u5f0f\u673a\u7684IP\n    User your_username      # \u66ff\u6362\u4e3a\u60a8\u7684\u7528\u6237\u540d\n    Port 22\n    IdentityFile ~/.ssh/id_ed25519\n    ForwardX11 yes         # \u5982\u679c\u9700\u8981\u56fe\u5f62\u754c\u9762\u8f6c\u53d1\n    ForwardAgent yes\n    Compression yes\n    ServerAliveInterval 60\n</code></pre>"},{"location":"Tools/Others/SSH/#_5","title":"\u5e38\u7528\u8fde\u63a5\u547d\u4ee4\uff1a","text":"<ol> <li>\u57fa\u672c\u8fde\u63a5:</li> </ol> Bash<pre><code># \u4ece\u7b14\u8bb0\u672c\u8fde\u63a5\u5230\u53f0\u5f0f\u673a\nssh desktop\n\n# \u4f7f\u7528\u56fe\u5f62\u754c\u9762\u8f6c\u53d1\nssh -X desktop\n</code></pre> <ol> <li>\u6587\u4ef6\u4f20\u8f93:</li> </ol> Bash<pre><code># \u4ece\u7b14\u8bb0\u672c\u590d\u5236\u6587\u4ef6\u5230\u53f0\u5f0f\u673a\nscp /path/to/local/file desktop:/path/to/remote/\n\n# \u4ece\u53f0\u5f0f\u673a\u590d\u5236\u6587\u4ef6\u5230\u7b14\u8bb0\u672c\nscp desktop:/path/to/remote/file /path/to/local/\n</code></pre> <ol> <li>\u7aef\u53e3\u8f6c\u53d1:</li> </ol> Bash<pre><code># \u672c\u5730\u7aef\u53e3\u8f6c\u53d1\nssh -L 8080:localhost:80 desktop\n\n# \u8fdc\u7a0b\u7aef\u53e3\u8f6c\u53d1\nssh -R 8080:localhost:80 desktop\n</code></pre>"},{"location":"Tools/Others/SSH/#_6","title":"\u56db\u3001\u9ad8\u7ea7\u64cd\u4f5c","text":""},{"location":"Tools/Others/SSH/#1-ssh_1","title":"1. SSH\u7aef\u53e3\u8f6c\u53d1","text":""},{"location":"Tools/Others/SSH/#11","title":"1.1 \u672c\u5730\u7aef\u53e3\u8f6c\u53d1","text":"Bash<pre><code># \u5c06\u672c\u57308080\u7aef\u53e3\u8f6c\u53d1\u5230\u8fdc\u7a0b80\u7aef\u53e3\nssh -L 8080:localhost:80 user@remote\n\n# \u4f7f\u7528\u914d\u7f6e\u6587\u4ef6\u8bbe\u7f6e\nHost tunnel\n    HostName remote.example.com\n    LocalForward 8080 localhost:80\n</code></pre>"},{"location":"Tools/Others/SSH/#12","title":"1.2 \u8fdc\u7a0b\u7aef\u53e3\u8f6c\u53d1","text":"Bash<pre><code># \u5c06\u8fdc\u7a0b3000\u7aef\u53e3\u8f6c\u53d1\u5230\u672c\u57303000\u7aef\u53e3\nssh -R 3000:localhost:3000 user@remote\n\n# \u914d\u7f6e\u6587\u4ef6\u8bbe\u7f6e\nHost remote-tunnel\n    HostName remote.example.com\n    RemoteForward 3000 localhost:3000\n</code></pre>"},{"location":"Tools/Others/SSH/#2-ssh","title":"2. SSH\u4ee3\u7406\u8f6c\u53d1","text":"Bash<pre><code># \u542f\u7528\u4ee3\u7406\u8f6c\u53d1\nssh -A user@remote\n\n# \u914d\u7f6e\u6587\u4ef6\u8bbe\u7f6e\nHost *\n    ForwardAgent yes\n    AddKeysToAgent yes\n</code></pre>"},{"location":"Tools/Others/SSH/#3_1","title":"3. \u8df3\u677f\u673a\u914d\u7f6e","text":"Bash<pre><code># \u901a\u8fc7\u8df3\u677f\u673a\u8fde\u63a5\nssh -J jumphost user@target\n\n# \u914d\u7f6e\u6587\u4ef6\u8bbe\u7f6e\nHost target\n    HostName target.example.com\n    ProxyJump jumphost\n</code></pre>"},{"location":"Tools/Others/SSH/#_7","title":"\u4e94\u3001\u6545\u969c\u6392\u67e5","text":""},{"location":"Tools/Others/SSH/#1","title":"1. \u6700\u4f73\u5b9e\u8df5","text":"Bash<pre><code># 1. \u4f7f\u7528SSH\u914d\u7f6e\u6587\u4ef6\u7ba1\u7406\u8fde\u63a5\n# 2. \u4e3a\u4e0d\u540c\u7528\u9014\u4f7f\u7528\u4e0d\u540c\u7684\u5bc6\u94a5\n# 3. \u5b9a\u671f\u8f6e\u6362\u5bc6\u94a5\n# 4. \u4f7f\u7528ssh-agent\u7ba1\u7406\u5bc6\u94a5\n# 5. \u5907\u4efdSSH\u914d\u7f6e\u548c\u5bc6\u94a5\n</code></pre>"},{"location":"Tools/Others/SSH/#2_1","title":"2. \u5e38\u89c1\u95ee\u9898\u89e3\u51b3","text":"Bash<pre><code># \u8fde\u63a5\u88ab\u62d2\u7edd\nssh -v user@host  # \u67e5\u770b\u8be6\u7ec6\u8fde\u63a5\u4fe1\u606f\n\n# \u6743\u9650\u95ee\u9898\nls -la ~/.ssh     # \u68c0\u67e5\u6743\u9650\nchmod 600 ~/.ssh/id_ed25519\n\n# \u5bc6\u94a5\u95ee\u9898\nssh-add -l        # \u67e5\u770b\u5df2\u52a0\u8f7d\u7684\u5bc6\u94a5\nssh-add ~/.ssh/id_ed25519  # \u6dfb\u52a0\u5bc6\u94a5\u5230agent\n</code></pre>"},{"location":"Tools/Others/SSH/#3_2","title":"3. \u65e5\u5fd7\u67e5\u770b","text":"Bash<pre><code># \u670d\u52a1\u5668\u7aef\nsudo tail -f /var/log/auth.log    # Debian/Ubuntu\nsudo tail -f /var/log/secure      # CentOS/RHEL\n\n# \u5ba2\u6237\u7aef\u8c03\u8bd5\nssh -vvv user@host  # \u6700\u8be6\u7ec6\u7684\u8c03\u8bd5\u4fe1\u606f\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/","title":"Tabby + Zsh \u914d\u7f6e\u6307\u5357","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#tabby-zsh","title":"Tabby + Zsh \u914d\u7f6e\u6307\u5357","text":"<p> \u7ea6 236 \u4e2a\u5b57  789 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 11 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"Tools/Terminal/Tabby_Zsh/#_1","title":"\u524d\u7f6e\u51c6\u5907","text":"<p>\u7cfb\u7edf\u8981\u6c42</p> Bash<pre><code># Ubuntu/Debian\nsudo apt update\nsudo apt install -y \\\n    git \\\n    curl \\\n    wget \\\n    build-essential \\\n    cmake \\\n    python3-pip \\\n    pkg-config \\\n    libssl-dev\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#zsh","title":"ZSH \u57fa\u7840\u914d\u7f6e","text":"<p>ZSH \u5b89\u88c5</p> Bash<pre><code># \u5b89\u88c5zsh\nsudo apt install zsh\n\n# \u8bbe\u7f6e\u4e3a\u9ed8\u8ba4shell\nchsh -s $(which zsh)\n\n# \u786e\u8ba4\u8bbe\u7f6e\necho $SHELL\n# \u5e94\u8be5\u8f93\u51fa: /usr/bin/zsh\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#1-oh-my-zsh","title":"1. Oh My Zsh \u5b89\u88c5","text":"Bash<pre><code># \u5b89\u88c5Oh My Zsh\nsh -c \"$(curl -fsSL https://raw.github.com/ohmyzsh/ohmyzsh/master/tools/install.sh)\"\n\n# \u5907\u4efd\u9ed8\u8ba4\u914d\u7f6e\ncp ~/.zshrc ~/.zshrc.backup\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#2","title":"2. \u63d2\u4ef6\u7ba1\u7406\u5668\u5b89\u88c5","text":"Bash<pre><code># \u5b89\u88c5zinit\nbash -c \"$(curl --fail --show-error --silent --location https://raw.githubusercontent.com/zdharma-continuum/zinit/HEAD/scripts/install.sh)\"\n\n# \u7b49\u5f85\u5b89\u88c5\u5b8c\u6210\u540e\u91cd\u542f\u7ec8\u7aef\nexec zsh\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#3","title":"3. \u57fa\u7840\u914d\u7f6e\u6587\u4ef6","text":"Bash<pre><code># \u521b\u5efa\u65b0\u7684\u914d\u7f6e\u6587\u4ef6\ncat &lt;&lt; 'EOF' &gt; ~/.zshrc\n# \u57fa\u7840\u8bbe\u7f6e\nexport ZSH=\"$HOME/.oh-my-zsh\"\nexport LANG=en_US.UTF-8\nexport EDITOR='nvim'\nexport VISUAL='nvim'\n\n# zinit\u914d\u7f6e\nsource \"$HOME/.local/share/zinit/zinit.git/zinit.zsh\"\nautoload -Uz _zinit\n(( ${+_comps} )) &amp;&amp; _comps[zinit]=_zinit\n\n# \u52a0\u8f7d\u6838\u5fc3\u63d2\u4ef6\nzinit ice depth=1; zinit light romkatv/powerlevel10k  # \u4e3b\u9898\nzinit light zsh-users/zsh-autosuggestions           # \u547d\u4ee4\u5efa\u8bae\nzinit light zsh-users/zsh-syntax-highlighting       # \u8bed\u6cd5\u9ad8\u4eae\nzinit light zsh-users/zsh-completions              # \u8865\u5168\u589e\u5f3a\nzinit light agkozak/zsh-z                          # \u76ee\u5f55\u8df3\u8f6c\n\n# \u5386\u53f2\u8bb0\u5f55\u8bbe\u7f6e\nHISTFILE=\"$HOME/.zsh_history\"\nHISTSIZE=50000\nSAVEHIST=50000\nsetopt EXTENDED_HISTORY          # \u8bb0\u5f55\u547d\u4ee4\u65f6\u95f4\u6233\nsetopt HIST_EXPIRE_DUPS_FIRST   # \u4f18\u5148\u5220\u9664\u91cd\u590d\u547d\u4ee4\nsetopt HIST_IGNORE_DUPS         # \u5ffd\u7565\u8fde\u7eed\u91cd\u590d\u547d\u4ee4\nsetopt HIST_IGNORE_SPACE        # \u5ffd\u7565\u4ee5\u7a7a\u683c\u5f00\u5934\u7684\u547d\u4ee4\nsetopt HIST_VERIFY              # \u6267\u884c\u5386\u53f2\u547d\u4ee4\u524d\u5c55\u793a\nsetopt INC_APPEND_HISTORY       # \u5b9e\u65f6\u6dfb\u52a0\u5386\u53f2\u8bb0\u5f55\nsetopt SHARE_HISTORY           # \u5171\u4eab\u5386\u53f2\u8bb0\u5f55\n\n# \u76ee\u5f55\u8bbe\u7f6e\nsetopt AUTO_CD              \nsetopt AUTO_PUSHD          \nsetopt PUSHD_IGNORE_DUPS   \nsetopt PUSHD_MINUS         \nDIRSTACKSIZE=20\n\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#4","title":"4. \u5b9e\u7528\u522b\u540d\u8bbe\u7f6e","text":"Bash<pre><code># \u6dfb\u52a0\u5230~/.zshrc\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# \u57fa\u7840\u547d\u4ee4\u589e\u5f3a\nalias ls='ls --color=auto'\nalias ll='ls -lah'\nalias la='ls -A'\nalias l='ls -CF'\nalias grep='grep --color=auto'\nalias rm='rm -i'\nalias cp='cp -i'\nalias mv='mv -i'\nalias mkdir='mkdir -p'\nalias df='df -h'\nalias free='free -m'\nalias duf='du -sh *'\nalias ps='ps auxf'\nalias ping='ping -c 5'\nalias root='sudo -i'\nalias reboot='sudo reboot'\nalias poweroff='sudo poweroff'\n\n# Git\u5feb\u6377\u547d\u4ee4\nalias gs='git status'\nalias ga='git add'\nalias gaa='git add --all'\nalias gc='git commit -m'\nalias gp='git push'\nalias gl='git pull'\nalias gd='git diff'\nalias gco='git checkout'\nalias gb='git branch'\nalias gm='git merge'\nalias glog='git log --oneline --decorate --graph'\n\n# Docker\u5feb\u6377\u547d\u4ee4\nalias dk='docker'\nalias dkc='docker-compose'\nalias dkps='docker ps'\nalias dkst='docker stats'\nalias dktop='docker top'\nalias dkimg='docker images'\nalias dkpull='docker pull'\nalias dkex='docker exec -it'\n\n# \u5feb\u901f\u7f16\u8f91\nalias zshconfig=\"$EDITOR ~/.zshrc\"\nalias zshreload=\"source ~/.zshrc\"\nalias vimconfig=\"$EDITOR ~/.vimrc\"\nalias tmuxconfig=\"$EDITOR ~/.tmux.conf\"\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#5","title":"5. \u5b9e\u7528\u51fd\u6570","text":"Bash<pre><code># \u6dfb\u52a0\u5230~/.zshrc\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# \u521b\u5efa\u5e76\u8fdb\u5165\u76ee\u5f55\nmkcd() {\n    mkdir -p \"$1\" &amp;&amp; cd \"$1\"\n}\n\n# \u63d0\u53d6\u538b\u7f29\u6587\u4ef6\nextract() {\n    if [ -f $1 ]; then\n        case $1 in\n            *.tar.bz2)   tar xjf $1     ;;\n            *.tar.gz)    tar xzf $1     ;;\n            *.bz2)       bunzip2 $1     ;;\n            *.rar)       unrar e $1     ;;\n            *.gz)        gunzip $1      ;;\n            *.tar)       tar xf $1      ;;\n            *.tbz2)      tar xjf $1     ;;\n            *.tgz)       tar xzf $1     ;;\n            *.zip)       unzip $1       ;;\n            *.Z)         uncompress $1  ;;\n            *.7z)        7z x $1        ;;\n            *)          echo \"'$1' cannot be extracted\" ;;\n        esac\n    else\n        echo \"'$1' is not a valid file\"\n    fi\n}\n\n# \u5feb\u901f\u67e5\u627e\u6587\u4ef6\nff() { find . -type f -iname \"*$1*\" ; }\nfd() { find . -type d -iname \"*$1*\" ; }\n\n# \u5feb\u901f\u67e5\u770b\u8fdb\u7a0b\npsg() { ps aux | grep -v grep | grep -i -e VSZ -e \"$1\"; }\n\n# \u7f51\u7edc\u5de5\u5177\nmyip() {\n    curl -s http://ipecho.net/plain\n    echo\n}\n\n# \u5feb\u901fHTTP\u670d\u52a1\u5668\nserve() {\n    local port=\"${1:-8000}\"\n    python3 -m http.server \"$port\"\n}\n\n# Git\u65e5\u5fd7\u7f8e\u5316\ngll() {\n    git log --graph --pretty=format:'%Cred%h%Creset -%C(yellow)%d%Creset %s %Cgreen(%cr) %C(bold blue)&lt;%an&gt;%Creset' --abbrev-commit\n}\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#_2","title":"\u4e3b\u9898\u7f8e\u5316\u4e0e\u63d2\u4ef6\u589e\u5f3a","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#powerlevel10k","title":"\u4e00\u3001Powerlevel10k \u4e3b\u9898\u914d\u7f6e","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#1","title":"1. \u5b89\u88c5\u5fc5\u8981\u5b57\u4f53","text":"Bash<pre><code># \u521b\u5efa\u5b57\u4f53\u76ee\u5f55\nmkdir -p ~/.local/share/fonts\n\n# \u4e0b\u8f7d\u63a8\u8350\u5b57\u4f53\nwget -P /tmp https://github.com/romkatv/powerlevel10k-media/raw/master/MesloLGS%20NF%20Regular.ttf\nwget -P /tmp https://github.com/romkatv/powerlevel10k-media/raw/master/MesloLGS%20NF%20Bold.ttf\nwget -P /tmp https://github.com/romkatv/powerlevel10k-media/raw/master/MesloLGS%20NF%20Italic.ttf\nwget -P /tmp https://github.com/romkatv/powerlevel10k-media/raw/master/MesloLGS%20NF%20Bold%20Italic.ttf\n\n# \u79fb\u52a8\u5b57\u4f53\u6587\u4ef6\nmv /tmp/MesloLGS*.ttf ~/.local/share/fonts/\n\n# \u66f4\u65b0\u5b57\u4f53\u7f13\u5b58\nfc-cache -f -v\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#2_1","title":"2. \u4e3b\u9898\u914d\u7f6e","text":"Bash<pre><code># \u6dfb\u52a0\u5230 ~/.zshrc\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# Powerlevel10k \u914d\u7f6e\n# \u542f\u7528 Powerlevel10k \u5373\u65f6\u63d0\u793a\nif [[ -r \"${XDG_CACHE_HOME:-$HOME/.cache}/p10k-instant-prompt-${(%):-%n}.zsh\" ]]; then\n  source \"${XDG_CACHE_HOME:-$HOME/.cache}/p10k-instant-prompt-${(%):-%n}.zsh\"\nfi\n\n# \u52a0\u8f7d\u4e3b\u9898\nsource ~/.oh-my-zsh/custom/themes/powerlevel10k/powerlevel10k.zsh-theme\n\n# \u4e3b\u9898\u4e2a\u6027\u5316\u8bbe\u7f6e\nPOWERLEVEL9K_MODE='nerdfont-complete'\nPOWERLEVEL9K_LEFT_PROMPT_ELEMENTS=(\n  os_icon                 # \u64cd\u4f5c\u7cfb\u7edf\u56fe\u6807\n  dir                     # \u5f53\u524d\u76ee\u5f55\n  vcs                     # git\u72b6\u6001\n  newline                 # \u6362\u884c\n  prompt_char            # \u63d0\u793a\u7b26\n)\nPOWERLEVEL9K_RIGHT_PROMPT_ELEMENTS=(\n  status                  # \u4e0a\u4e00\u4e2a\u547d\u4ee4\u7684\u72b6\u6001\n  background_jobs        # \u540e\u53f0\u4efb\u52a1\n  load                   # \u7cfb\u7edf\u8d1f\u8f7d\n  ram                    # \u5185\u5b58\u4f7f\u7528\n  time                   # \u65f6\u95f4\n)\n\n# \u76ee\u5f55\u663e\u793a\u8bbe\u7f6e\nPOWERLEVEL9K_DIR_BACKGROUND='blue'\nPOWERLEVEL9K_DIR_FOREGROUND='black'\nPOWERLEVEL9K_SHORTEN_DIR_LENGTH=2\nPOWERLEVEL9K_SHORTEN_STRATEGY=\"truncate_middle\"\n\n# Git\u72b6\u6001\u8bbe\u7f6e\nPOWERLEVEL9K_VCS_CLEAN_BACKGROUND='green'\nPOWERLEVEL9K_VCS_UNTRACKED_BACKGROUND='yellow'\nPOWERLEVEL9K_VCS_MODIFIED_BACKGROUND='red'\nEOF\n\n# \u8fd0\u884c\u914d\u7f6e\u5411\u5bfc\uff08\u9996\u6b21\u4f7f\u7528\uff09\np10k configure\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#_3","title":"\u4e8c\u3001\u9ad8\u7ea7\u63d2\u4ef6\u914d\u7f6e","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#1_1","title":"1. \u9ad8\u7ea7\u8865\u5168\u7cfb\u7edf","text":"Bash<pre><code># \u6dfb\u52a0\u5230 ~/.zshrc\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# \u8865\u5168\u7cfb\u7edf\u914d\u7f6e\nautoload -Uz compinit\ncompinit\n\n# \u8865\u5168\u83dc\u5355\u8bbe\u7f6e\nzstyle ':completion:*' menu select\nzstyle ':completion:*' matcher-list 'm:{a-zA-Z}={A-Za-z}'   # \u5ffd\u7565\u5927\u5c0f\u5199\nzstyle ':completion:*' list-colors ${(s.:.)LS_COLORS}       # \u8865\u5168\u83dc\u5355\u7740\u8272\nzstyle ':completion:*' verbose yes                         # \u8be6\u7ec6\u8865\u5168\u83dc\u5355\nzstyle ':completion:*:descriptions' format '%U%B%d%b%u'     # \u8865\u5168\u83dc\u5355\u683c\u5f0f\nzstyle ':completion:*:warnings' format '%BSorry, no matches for: %d%b'\nzstyle ':completion:*:*:kill:*:processes' list-colors '=(#b) #([0-9]#)*=0=01;31'\nzstyle ':completion:*:kill:*' command 'ps -u $USER -o pid,%cpu,tty,cputime,cmd'\n\n# \u4f7f\u7528\u7f13\u5b58\u52a0\u901f\u8865\u5168\nzstyle ':completion:*' use-cache on\nzstyle ':completion:*' cache-path ~/.zsh/cache\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#2-fzf","title":"2. FZF \u96c6\u6210\u914d\u7f6e","text":"Bash<pre><code># \u5b89\u88c5FZF\ngit clone --depth 1 https://github.com/junegunn/fzf.git ~/.fzf\n~/.fzf/install\n\n# \u6dfb\u52a0\u5230 ~/.zshrc\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# FZF \u914d\u7f6e\nexport FZF_DEFAULT_COMMAND='fd --type f --hidden --follow --exclude .git'\nexport FZF_DEFAULT_OPTS='--height 40% --layout=reverse --border --preview \"bat --style=numbers --color=always --line-range :500 {}\"'\n\n# FZF \u5feb\u6377\u952e\nbindkey '^T' fzf-file-widget\nbindkey '^R' fzf-history-widget\nbindkey '^[c' fzf-cd-widget\n\n# FZF \u51fd\u6570\n# \u5feb\u901f\u6253\u5f00\u6587\u4ef6\nfe() {\n  local file\n  file=$(fzf --query=\"$1\" --select-1 --exit-0)\n  [ -n \"$file\" ] &amp;&amp; ${EDITOR:-vim} \"$file\"\n}\n\n# \u5feb\u901f\u5207\u6362\u76ee\u5f55\nfd() {\n  local dir\n  dir=$(find ${1:-.} -path '*/\\.*' -prune -o -type d -print 2&gt; /dev/null | fzf +m)\n  [ -n \"$dir\" ] &amp;&amp; cd \"$dir\"\n}\n\n# \u641c\u7d22\u5386\u53f2\u547d\u4ee4\nfh() {\n  print -z $( ([ -n \"$ZSH_NAME\" ] &amp;&amp; fc -l 1 || history) | fzf +s --tac | sed -E 's/ *[0-9]*\\*? *//' | sed -E 's/\\\\/\\\\\\\\/g')\n}\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#3_1","title":"3. \u589e\u5f3a\u76ee\u5f55\u5bfc\u822a","text":"Bash<pre><code># \u6dfb\u52a0\u5230 ~/.zshrc\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# \u76ee\u5f55\u4e66\u7b7e\nhash -d proj=~/projects\nhash -d docs=~/Documents\nhash -d dl=~/Downloads\nhash -d pics=~/Pictures\n\n# z \u63d2\u4ef6\u914d\u7f6e\nZSHZ_DATA=~/.local/share/z/data\nZSHZ_MAX_SCORE=5000\nZSHZ_CASE=smart\n\n# \u76ee\u5f55\u5806\u6808\u5bfc\u822a\nsetopt AUTO_PUSHD           # \u81ea\u52a8\u5c06\u76ee\u5f55\u52a0\u5165\u5806\u6808\nsetopt PUSHD_IGNORE_DUPS    # \u5ffd\u7565\u91cd\u590d\u76ee\u5f55\nsetopt PUSHD_SILENT        # \u9759\u9ed8\u6a21\u5f0f\nsetopt PUSHD_TO_HOME       # pushd \u4e0d\u5e26\u53c2\u6570\u65f6\u7b49\u540c\u4e8e pushd $HOME\n\n# \u76ee\u5f55\u522b\u540d\nalias -g ...='../..'\nalias -g ....='../../..'\nalias -g .....='../../../..'\nalias d='dirs -v'\nfor index ({1..9}) alias \"$index\"=\"cd +${index}\"; unset index\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#4_1","title":"4. \u589e\u5f3a\u5386\u53f2\u8bb0\u5f55\u641c\u7d22","text":"Bash<pre><code># \u6dfb\u52a0\u5230 ~/.zshrc\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# \u5386\u53f2\u8bb0\u5f55\u641c\u7d22\u914d\u7f6e\nbindkey '^[[A' history-substring-search-up\nbindkey '^[[B' history-substring-search-down\nbindkey '^P' history-substring-search-up\nbindkey '^N' history-substring-search-down\n\n# \u5386\u53f2\u8bb0\u5f55\u683c\u5f0f\u5316\nHIST_STAMPS=\"yyyy-mm-dd\"\nHISTORY_IGNORE=\"(ls|ls *|cd|cd *|pwd|exit|date|* --help)\"\n\n# \u547d\u4ee4\u6267\u884c\u65f6\u95f4\u663e\u793a\nREPORTTIME=10\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#tabby","title":"Tabby \u7ec8\u7aef\u914d\u7f6e","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#_4","title":"\u4e00\u3001\u5b89\u88c5\u548c\u521d\u59cb\u5316","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#1-tabby","title":"1. \u5b89\u88c5 Tabby","text":"Bash<pre><code># Ubuntu/Debian\nwget https://github.com/Eugeny/tabby/releases/latest/download/tabby-1.0.0-linux-x64.deb\nsudo dpkg -i tabby-*.deb\nsudo apt-get install -f\n\n# \u786e\u4fdd\u5b57\u4f53\u652f\u6301\nfc-cache -fv\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#2_2","title":"2. \u521d\u59cb\u914d\u7f6e","text":"YAML<pre><code># ~/.config/tabby/config.yaml\nconfig:\n  version: 3\n\nterminal:\n  shell: zsh  # \u4f7f\u7528\u524d\u9762\u914d\u7f6e\u7684zsh\n  fontSize: 14\n  lineHeight: 1.2\n  bell: 'off'\n  copyOnSelect: true\n  rightClick: menu\n\n  # \u57fa\u7840\u73af\u5883\u53d8\u91cf\n  environment:\n    TERM: xterm-256color\n    COLORTERM: truecolor\n\n  # \u6027\u80fd\u8bbe\u7f6e\n  performanceMode: true\n  gpuAcceleration: true\n  webGL: true\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#_5","title":"\u4e8c\u3001\u5916\u89c2\u914d\u7f6e","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#1_2","title":"1. \u5b57\u4f53\u8bbe\u7f6e","text":"YAML<pre><code>terminal:\n  font: JetBrainsMono Nerd Font  # \u786e\u4fdd\u5df2\u5b89\u88c5\n  fontSize: 14\n  lineHeight: 1.2\n  ligatures: true  # \u8fde\u5b57\u652f\u6301\n\n  # \u5b57\u4f53\u56de\u9000\n  fallbackFont: 'Sarasa Mono SC'  # \u4e2d\u6587\u652f\u6301\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#2-dracula","title":"2. Dracula \u4e3b\u9898\u914d\u7f6e","text":"YAML<pre><code>profiles:\n  - name: Default\n    theme:\n      name: 'Dracula'\n\n    colors:\n      background: '#282a36'\n      foreground: '#f8f8f2'\n      cursor: '#f8f8f2'\n\n      selection:\n        background: '#44475a'\n        foreground: '#f8f8f2'\n\n      # ANSI Colors\n      black: '#21222c'\n      red: '#ff5555'\n      green: '#50fa7b'\n      yellow: '#f1fa8c'\n      blue: '#bd93f9'\n      magenta: '#ff79c6'\n      cyan: '#8be9fd'\n      white: '#f8f8f2'\n\n      # Bright Colors\n      brightBlack: '#6272a4'\n      brightRed: '#ff6e6e'\n      brightGreen: '#69ff94'\n      brightYellow: '#ffffa5'\n      brightBlue: '#d6acff'\n      brightMagenta: '#ff92df'\n      brightCyan: '#a4ffff'\n      brightWhite: '#ffffff'\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#3_2","title":"3. \u900f\u660e\u80cc\u666f\u914d\u7f6e","text":"YAML<pre><code>terminal:\n  background:\n    type: 'image'  # \u6216 'color'\n    image: '~/.config/tabby/backgrounds/bg.jpg'  # \u81ea\u5b9a\u4e49\u80cc\u666f\u56fe\u7247\n    opacity: 0.85  # \u900f\u660e\u5ea6\n\n  # \u4e9a\u514b\u529b\u6548\u679c\uff08Windows\uff09\n  experimental:\n    vibrancy: true\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#_6","title":"\u4e09\u3001\u5feb\u6377\u952e\u914d\u7f6e","text":"YAML<pre><code>hotkeys:\n  # \u6807\u7b7e\u7ba1\u7406\n  new-tab: ['Ctrl+T']\n  close-tab: ['Ctrl+W']\n  previous-tab: ['Ctrl+Shift+Tab']\n  next-tab: ['Ctrl+Tab']\n\n  # \u5206\u5c4f\u64cd\u4f5c\n  split-right: ['Ctrl+Shift+E']\n  split-bottom: ['Ctrl+Shift+O']\n  split-nav-left: ['Alt+Left']\n  split-nav-right: ['Alt+Right']\n  split-nav-up: ['Alt+Up']\n  split-nav-down: ['Alt+Down']\n\n  # \u7ec8\u7aef\u64cd\u4f5c\n  clear: ['Ctrl+L']\n  copy: ['Ctrl+C']\n  paste: ['Ctrl+V']\n  search: ['Ctrl+Shift+F']\n\n  # \u89c6\u56fe\u63a7\u5236\n  zoom-in: ['Ctrl+Plus']\n  zoom-out: ['Ctrl+Minus']\n  reset-zoom: ['Ctrl+0']\n  toggle-fullscreen: ['F11']\n\n  # \u5feb\u901f\u547d\u4ee4\n  command-palette: ['Ctrl+Shift+P']\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#ssh","title":"\u56db\u3001SSH \u914d\u7f6e","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#1-ssh","title":"1. \u57fa\u7840 SSH \u914d\u7f6e","text":"YAML<pre><code>ssh:\n  auth:\n    agent: true\n    privateKeys:\n      - ~/.ssh/id_ed25519\n      - ~/.ssh/id_rsa\n\n  # \u8fde\u63a5\u4fdd\u6301\n  keepaliveInterval: 30\n  keepaliveCountMax: 3\n\n  # \u8f6c\u53d1\u8bbe\u7f6e\n  forwardAgent: true\n  x11: false\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#2-ssh","title":"2. SSH \u8fde\u63a5\u914d\u7f6e","text":"YAML<pre><code>ssh:\n  profiles:\n    - name: \"\u5f00\u53d1\u670d\u52a1\u5668\"\n      group: \"\u5f00\u53d1\u73af\u5883\"\n      host: dev.example.com\n      port: 22\n      user: username\n      auth: publicKey\n      privateKey: ~/.ssh/id_ed25519\n\n    - name: \"\u751f\u4ea7\u670d\u52a1\u5668\"\n      group: \"\u751f\u4ea7\u73af\u5883\"\n      host: prod.example.com\n      port: 22\n      user: username\n      auth: agent\n\n    - name: \"\u8df3\u677f\u673a\"\n      host: jump.example.com\n      forwardAgent: true\n      jumpHost: true  # \u6807\u8bb0\u4e3a\u8df3\u677f\u673a\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#_7","title":"\u4e94\u3001\u63d2\u4ef6\u914d\u7f6e","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#1_3","title":"1. \u6838\u5fc3\u63d2\u4ef6","text":"YAML<pre><code>plugins:\n  # SSH\u7ba1\u7406\n  ssh:\n    enabled: true\n\n  # \u7ec8\u7aef\u5f55\u5236\n  record:\n    enabled: true\n    directory: ~/terminal-records\n\n  # \u547d\u4ee4\u9762\u677f\n  commander:\n    enabled: true\n\n  # \u4e3b\u9898\u63d2\u4ef6\n  community-color-schemes:\n    enabled: true\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#2_3","title":"2. \u6269\u5c55\u529f\u80fd","text":"YAML<pre><code># \u641c\u7d22\u589e\u5f3a\nsearch:\n  enabled: true\n  searchOptions:\n    regex: true\n    wholeWord: false\n    caseSensitive: false\n\n# \u7ec8\u7aef\u5206\u5272\nsplit:\n  autoRemove: true  # \u81ea\u52a8\u5173\u95ed\u7a7a\u7ec8\u7aef\n  copyOnSelect: true\n  pasteOnMiddleClick: true\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#_8","title":"\u516d\u3001\u6027\u80fd\u4f18\u5316","text":"YAML<pre><code># \u6027\u80fd\u76f8\u5173\u914d\u7f6e\nterminal:\n  # \u57fa\u7840\u4f18\u5316\n  performanceMode: true\n  gpuAcceleration: true\n  webGL: true\n\n  # \u5386\u53f2\u8bb0\u5f55\n  scrollback: 5000\n\n  # \u8fdb\u7a0b\u7ba1\u7406\n  autoClose: true\n  closeOnExit: true\n\n  # \u6e32\u67d3\u4f18\u5316\n  smoothScroll: false\n  experimentalFontRendering: false\n\n  # \u8d44\u6e90\u9650\u5236\n  environment:\n    LIMIT_MEMORY: 512  # MB\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#_9","title":"\u5f00\u53d1\u5de5\u5177\u4e0e\u7ec8\u7aef\u5de5\u5177\u914d\u7f6e","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#_10","title":"\u4e00\u3001\u73b0\u4ee3\u547d\u4ee4\u884c\u5de5\u5177","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#1_4","title":"1. \u57fa\u7840\u5de5\u5177\u5b89\u88c5","text":"Bash<pre><code># \u5b89\u88c5\u57fa\u7840\u5de5\u5177\nsudo apt install -y \\\n    exa `# \u73b0\u4ee3ls\u66ff\u4ee3\u54c1` \\\n    bat `# \u73b0\u4ee3cat\u66ff\u4ee3\u54c1` \\\n    ripgrep `# \u73b0\u4ee3grep\u66ff\u4ee3\u54c1` \\\n    fd-find `# \u73b0\u4ee3find\u66ff\u4ee3\u54c1` \\\n    duf `# \u73b0\u4ee3df\u66ff\u4ee3\u54c1` \\\n    ncdu `# \u78c1\u76d8\u4f7f\u7528\u5206\u6790` \\\n    tldr `# \u547d\u4ee4\u7b80\u5316\u8bf4\u660e` \\\n    jq `# JSON\u5904\u7406` \\\n    fzf `# \u6a21\u7cca\u641c\u7d22`\n\n# \u521b\u5efa\u522b\u540d\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# \u73b0\u4ee3\u547d\u4ee4\u884c\u5de5\u5177\u522b\u540d\nalias ls='exa --icons'\nalias ll='exa -l --icons --git'\nalias la='exa -la --icons --git'\nalias lt='exa -T --icons --git-ignore'\nalias cat='batcat'\nalias find='fd'\nalias du='ncdu'\nalias df='duf'\nalias help='tldr'\n\n# fzf \u914d\u7f6e\nexport FZF_DEFAULT_OPTS=\"--height 40% --layout=reverse --border \\\n    --preview 'batcat --style=numbers --color=always --line-range :500 {}'\"\nexport FZF_DEFAULT_COMMAND='fd --type f --hidden --follow --exclude .git'\nexport FZF_CTRL_T_COMMAND=\"$FZF_DEFAULT_COMMAND\"\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#2-ranger","title":"2. \u6587\u4ef6\u7ba1\u7406\u5668 - Ranger","text":"Bash<pre><code># \u5b89\u88c5ranger\u548c\u4f9d\u8d56\nsudo apt install ranger python3-pillow ueberzug\n\n# \u751f\u6210\u914d\u7f6e\u6587\u4ef6\nranger --copy-config=all\n\n# \u914d\u7f6eRanger\ncat &lt;&lt; 'EOF' &gt; ~/.config/ranger/rc.conf\n# \u57fa\u7840\u8bbe\u7f6e\nset preview_images true\nset preview_images_method ueberzug\nset show_hidden true\nset hostname_in_titlebar false\nset tilde_in_titlebar true\nset line_numbers relative\nset mouse_enabled true\n\n# \u914d\u8272\u65b9\u6848\nset colorscheme solarized\n\n# \u6587\u4ef6\u9884\u89c8\nset use_preview_script true\nset preview_files true\nset preview_directories true\nset collapse_preview true\n\n# \u5feb\u6377\u952e\nmap &lt;C-f&gt; fzf_select\nmap &lt;C-p&gt; shell -w echo %d/%f | xsel -b\nmap &lt;C-g&gt; shell lazygit\nEOF\n\n# \u6dfb\u52a0FZF\u96c6\u6210\ncat &lt;&lt; 'EOF' &gt; ~/.config/ranger/commands.py\nfrom ranger.api.commands import Command\nclass fzf_select(Command):\n    def execute(self):\n        import subprocess\n        import os.path\n        command=\"find -L . \\( -path '*/\\.*' -o -fstype 'dev' -o -fstype 'proc' \\) -prune \\\n            -o -print 2&gt; /dev/null | sed 1d | cut -b3- | fzf +m\"\n        fzf = self.fm.execute_command(command, universal_newlines=True, stdout=subprocess.PIPE)\n        stdout, stderr = fzf.communicate()\n        if fzf.returncode == 0:\n            fzf_file = os.path.abspath(stdout.rstrip('\\n'))\n            if os.path.isdir(fzf_file):\n                self.fm.cd(fzf_file)\n            else:\n                self.fm.select_file(fzf_file)\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#3-htopglances","title":"3. \u7cfb\u7edf\u76d1\u63a7 - htop/glances","text":"Bash<pre><code># \u5b89\u88c5\u5de5\u5177\nsudo apt install htop glances\n\n# htop\u914d\u7f6e\nmkdir -p ~/.config/htop\ncat &lt;&lt; 'EOF' &gt; ~/.config/htop/htoprc\n# \u57fa\u7840\u663e\u793a\u8bbe\u7f6e\nshow_cpu_frequency=1\nshow_cpu_temperature=1\nshow_program_path=0\nhighlight_base_name=1\nhighlight_megabytes=1\nhighlight_threads=1\n\n# \u663e\u793a\u8bbe\u7f6e\nfields=0 48 17 18 38 39 40 2 46 47 49 1\nsort_key=46\nsort_direction=-1\ntree_view=1\ntree_view_always_by_pid=0\n\n# \u989c\u8272\u8bbe\u7f6e\ncolor_scheme=0\nEOF\n\n# glances\u914d\u7f6e\nmkdir -p ~/.config/glances\ncat &lt;&lt; 'EOF' &gt; ~/.config/glances/glances.conf\n[global]\n# \u5237\u65b0\u95f4\u9694\nrefresh=2\n# \u5386\u53f2\u5927\u5c0f\nhistory_size=1200\n\n[cpu]\n# CPU \u8b66\u544a\u9608\u503c\ncareful=50\nwarning=70\ncritical=90\n\n[memory]\n# \u5185\u5b58\u8b66\u544a\u9608\u503c\ncareful=50\nwarning=70\ncritical=90\n\n[network]\n# \u7f51\u7edc\u5e26\u5bbd\u663e\u793a\u5355\u4f4d (bit/sec)\nunit=bit\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#4-git-lazygit","title":"4. Git \u5de5\u5177 - Lazygit","text":"Bash<pre><code># \u5b89\u88c5Lazygit\nLAZYGIT_VERSION=$(curl -s \"https://api.github.com/repos/jesseduffield/lazygit/releases/latest\" | grep -Po '\"tag_name\": \"v\\K[^\"]*')\ncurl -Lo lazygit.tar.gz \"https://github.com/jesseduffield/lazygit/releases/latest/download/lazygit_${LAZYGIT_VERSION}_Linux_x86_64.tar.gz\"\nsudo tar xf lazygit.tar.gz -C /usr/local/bin lazygit\n\n# \u914d\u7f6eLazygit\nmkdir -p ~/.config/lazygit\ncat &lt;&lt; 'EOF' &gt; ~/.config/lazygit/config.yml\ngui:\n  # UI\u4e3b\u9898\n  theme:\n    lightTheme: false\n    activeBorderColor:\n      - green\n      - bold\n    inactiveBorderColor:\n      - white\n    selectedLineBgColor:\n      - reverse\n  # \u5e38\u7528\u8bbe\u7f6e  \n  showFileTree: true\n  showRandomTip: false\n  showCommandLog: false\n\ngit:\n  # git\u8bbe\u7f6e\n  paging:\n    colorArg: always\n    useConfig: true\n  # commit\u8bbe\u7f6e\n  commits:\n    showGraph: always\n    showWholeGraph: true\n  # \u81ea\u52a8\u83b7\u53d6\n  autoFetch: true\n  # \u5206\u652f\u663e\u793a\n  branchLogCmd: \"git log --graph --color=always --abbrev-commit --decorate --date=relative --pretty=medium {{branchName}} --\"\n\nkeybinding:\n  # \u81ea\u5b9a\u4e49\u5feb\u6377\u952e\n  universal:\n    return: '&lt;c-c&gt;'\n    quit: 'q'\n    quit-alt1: '&lt;esc&gt;'\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#5_1","title":"5. \u4ee3\u7801\u641c\u7d22\u5de5\u5177","text":"Bash<pre><code># ripgrep\u914d\u7f6e\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# ripgrep \u914d\u7f6e\nexport RIPGREP_CONFIG_PATH=\"$HOME/.ripgreprc\"\n\n# ripgrep \u522b\u540d\nalias rg='rg --smart-case'\nalias rgf='rg --files | rg'\nalias rgh='rg --hidden'\nalias rgc='rg --count'\n\n# fzf + ripgrep \u96c6\u6210\nfif() {\n    if [ ! \"$#\" -gt 0 ]; then echo \"Need a string to search for!\"; return 1; fi\n    rg --files-with-matches --no-messages \"$1\" | fzf --preview \"highlight -O ansi -l {} 2&gt; /dev/null | rg --colors 'match:bg:yellow' --ignore-case --pretty --context 10 '$1' || rg --ignore-case --pretty --context 10 '$1' {}\"\n}\nEOF\n\n# \u521b\u5efaripgrep\u914d\u7f6e\u6587\u4ef6\ncat &lt;&lt; 'EOF' &gt; ~/.ripgreprc\n# \u9ed8\u8ba4\u914d\u7f6e\n--smart-case\n--hidden\n--follow\n--glob=!.git/*\n\n# \u641c\u7d22\u914d\u7f6e\n--max-columns=150\n--max-columns-preview\n\n# \u989c\u8272\u914d\u7f6e\n--colors=line:fg:yellow\n--colors=line:style:bold\n--colors=path:fg:green\n--colors=path:style:bold\n--colors=match:fg:black\n--colors=match:bg:yellow\n--colors=match:style:nobold\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#6","title":"6. \u5b9e\u7528\u5f00\u53d1\u5de5\u5177","text":"Bash<pre><code># \u5b89\u88c5\u5f00\u53d1\u8f85\u52a9\u5de5\u5177\nsudo apt install -y \\\n    shellcheck `# shell\u811a\u672c\u68c0\u67e5` \\\n    python3-pip `# Python\u5305\u7ba1\u7406` \\\n    nodejs npm `# Node.js\u73af\u5883` \\\n    golang `# Go\u8bed\u8a00\u73af\u5883` \\\n    docker.io `# Docker\u652f\u6301` \\\n    postgresql-client `# \u6570\u636e\u5e93\u5ba2\u6237\u7aef` \\\n    redis-tools `# Redis\u5ba2\u6237\u7aef` \\\n    mycli `# MySQL\u5ba2\u6237\u7aef` \\\n    httpie `# HTTP\u5ba2\u6237\u7aef`\n\n# \u6dfb\u52a0\u5b9e\u7528\u522b\u540d\u548c\u51fd\u6570\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# Docker\u522b\u540d\nalias dk='docker'\nalias dkc='docker-compose'\nalias dkps='docker ps'\nalias dkst='docker stats'\nalias dkimg='docker images'\nalias dkpull='docker pull'\nalias dkexec='docker exec -it'\n\n# \u5f00\u53d1\u8f85\u52a9\u51fd\u6570\n# \u5feb\u901fHTTP\u670d\u52a1\u5668\nserve() {\n    local port=\"${1:-8000}\"\n    python3 -m http.server \"$port\"\n}\n\n# JSON\u683c\u5f0f\u5316\njson() {\n    if [ -t 0 ]; then  # \u53c2\u6570\u8f93\u5165\n        python -m json.tool &lt;&lt;&lt; \"$*\" | pygmentize -l json\n    else  # \u7ba1\u9053\u8f93\u5165\n        python -m json.tool | pygmentize -l json\n    fi\n}\n\n# Git\u5206\u652f\u6e05\u7406\ngit-clean() {\n    git branch --merged | egrep -v \"(^\\*|master|main|dev)\" | xargs git branch -d\n}\n\n# \u73af\u5883\u53d8\u91cf\u7ba1\u7406\nenvfile() {\n    if [[ -f \"$1\" ]]; then\n        set -a\n        source \"$1\"\n        set +a\n    else\n        echo \"Error: File $1 not found\"\n        return 1\n    fi\n}\nEOF\n</code></pre>"},{"location":"links/","title":"\u53cb\u94fe","text":""},{"location":"links/#_1","title":"\u53cb\u94fe","text":"<p>Abstract</p> <p>\u670b\u53cb\u4eec\uff01</p> Wnc \u7684\u5496\u5561\u9986 \u6211\u81ea\u5df1\uff01 donotknow DoNotKnow Kinnari \u5f88\u5389\u5bb3\u7684\u5b66\u957f\uff01"}]}
\ No newline at end of file
+{"config":{"lang":["en"],"separator":"[\\s\\-]+","pipeline":["stopWordFilter"]},"docs":[{"location":"","title":"Home","text":"Welcome to wnc's note!  <p>  My friends! /   Statistics </p> <p>\u7f51\u7ad9\u8fd0\u884c\u65f6\u95f4\uff1a \u8bbf\u5ba2\u603b\u4eba\u6570\uff1a\u4eba \u603b\u8bbf\u95ee\u6b21\u6570\uff1a\u6b21</p>"},{"location":"AI/","title":"AI","text":""},{"location":"AI/#artificial-intelligence","title":"Artificial Intelligence","text":"<p>Abstract</p> <p>\u672c\u90e8\u5206\u5185\u5bb9\uff08\u9664\u7279\u522b\u58f0\u660e\u5916\uff09\u91c7\u7528 \u7f72\u540d-\u975e\u5546\u4e1a\u6027\u4f7f\u7528-\u4fdd\u6301\u4e00\u81f4 4.0 \u56fd\u9645 (CC BY-NC-SA 4.0) \u8bb8\u53ef\u534f\u8bae\u8fdb\u884c\u8bb8\u53ef\u3002</p> FFB6D \u590d\u73b0          <ul> <li> Docker  653  213  5 mins              1734024510 </li> <li> Conda  293  96  2 mins              1734024510 </li> </ul> EECS 498-007          <ul> <li> Pytorch  564  45  2 mins              1734024510 </li> <li> KNN  374  100  2 mins              1734012860 </li> <li> Linear Classifer  0  0 mins              0 </li> </ul> CS231n          <ul> <li> Numpy  49  104  1 mins              1734024510 </li> <li> Notes  8852  30 mins              1734012860 </li> </ul>"},{"location":"AI/Dive%20into%20Deep%20Learning/","title":"Dive into Deep Learning","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#dive-into-deep-learning","title":"Dive into Deep Learning","text":"<p> \u7ea6 1547 \u4e2a\u5b57  387 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 13 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"AI/Dive%20into%20Deep%20Learning/#1","title":"1 \u5f15\u8a00","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#2","title":"2 \u9884\u5907\u77e5\u8bc6","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#21","title":"2.1 \u6570\u636e\u64cd\u4f5c","text":"<ul> <li>tensor</li> <li>ndarray (MXNet)</li> <li>Tensor (TensorFlow)</li> </ul> Python<pre><code>x = torch.arrange(12)\nx.shape\nx.numel()\nx.reshape(3, 4)\ntorch.zeros((2, 3, 4))\ntorch.ones((2, 3, 4))\ntorch.randn(3, 4)\n</code></pre> <ul> <li>elementwise\uff1a<ul> <li>+</li> <li>-</li> <li>-</li> <li>/</li> <li>exp ()</li> <li>==</li> </ul> </li> <li>concatenate</li> </ul> Python<pre><code>torch.cat((X, Y), dim = 0) # \u7ad6\u7740\u52a0\ntorch.cat((X, Y), dim = 1) # \u6a2a\u7740\u52a0\nx.sum()\n</code></pre> <ul> <li>broadcasting mechanism<ul> <li>\u590d\u5236\u62d3\u5c55\u5230\u5f62\u72b6\u4e00\u81f4\u540e\u76f8\u52a0</li> </ul> </li> <li>\u7d22\u5f15+\u5207\u7247</li> <li>\u5207\u7247\u4fdd\u6301\u5730\u5740\u4e0d\u53d8\uff1a\u8282\u7701\u5185\u5b58</li> <li>ndarry &lt;-&gt; Tensor</li> <li>item ()</li> </ul>"},{"location":"AI/Dive%20into%20Deep%20Learning/#22","title":"2.2 \u6570\u636e\u9884\u5904\u7406","text":"<ul> <li>pandas</li> <li>read_csv ()</li> <li>NaN<ul> <li>fillna (inputs.mean ())</li> <li>np.array (inputs. to_numpy (dtype = float))</li> </ul> </li> </ul>"},{"location":"AI/Dive%20into%20Deep%20Learning/#23","title":"2.3 \u7ebf\u6027\u4ee3\u6570","text":"<ul> <li>scalar</li> <li>variable</li> <li>space</li> <li>element / component</li> <li>dimension <ul> <li>len ()</li> <li>shape</li> </ul> </li> <li>square matrix</li> <li>transpose<ul> <li>A.T</li> </ul> </li> <li>symmetric matrix<ul> <li>A == A.T</li> </ul> </li> <li>channel</li> <li>Hadamard product</li> </ul> \\[ \\begin{split}\\mathbf{A} \\odot \\mathbf{B} = \\begin{bmatrix} a_{11}  b_{11} &amp; a_{12}  b_{12} &amp; \\dots  &amp; a_{1n}  b_{1n} \\\\ a_{21}  b_{21} &amp; a_{22}  b_{22} &amp; \\dots  &amp; a_{2n}  b_{2n} \\\\ \\vdots &amp; \\vdots &amp; \\ddots &amp; \\vdots \\\\ a_{m1}  b_{m1} &amp; a_{m2}  b_{m2} &amp; \\dots  &amp; a_{mn}  b_{mn} \\end{bmatrix}.\\end{split} \\] <ul> <li>A.sum (axis = 0) # \u7ad6\u7740\u6c42\u548c</li> <li>A.sum (axis = [0, 1]) = A.sum ()</li> <li>A.mean () = A.sum () / A.size ()</li> <li>A.cumsum (axis = 0)</li> <li>dot product<ul> <li>torch.dot (x, y) = torch.sum (x * y)</li> <li>weighted average</li> </ul> </li> <li>matrix-vector product<ul> <li>torch.mv (A, x)</li> </ul> </li> <li>matrix-matric multiplication<ul> <li>torch.mm (A, B)</li> </ul> </li> <li>norm<ol> <li>\\(f(\\alpha \\mathbf{x}) = |\\alpha| f(\\mathbf{x}).\\)</li> <li>\\((\\mathbf{x} + \\mathbf{y}) \\leq f(\\mathbf{x}) + f(\\mathbf{y}).\\)</li> <li>\\(f(\\mathbf{x}) \\geq 0.\\)</li> </ol> </li> </ul>"},{"location":"AI/Dive%20into%20Deep%20Learning/#24","title":"2.4 \u5fae\u79ef\u5206","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#241","title":"2.4.1 \u5bfc\u6570\u548c\u5fae\u5206","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#242","title":"2.4.2 \u504f\u5bfc\u6570","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#243","title":"2.4.3 \u68af\u5ea6","text":"\\[ \\nabla_{\\mathbf{x}} f(\\mathbf{x}) = \\bigg[\\frac{\\partial f(\\mathbf{x})}{\\partial x_1}, \\frac{\\partial f(\\mathbf{x})}{\\partial x_2}, \\ldots, \\frac{\\partial f(\\mathbf{x})}{\\partial x_n}\\bigg]^\\top, \\] \\[ \\nabla_{\\mathbf{x}} \\mathbf{A} \\mathbf{x} = \\mathbf{A}^\\top \\] \\[ \\nabla_{\\mathbf{x}} \\mathbf{x}^\\top \\mathbf{A} = \\mathbf{A} \\] \\[ \\nabla_{\\mathbf{x}} \\mathbf{x}^\\top \\mathbf{A} \\mathbf{x} = (\\mathbf{A} + \\mathbf{A}^\\top)\\mathbf{x} \\] \\[ \\nabla_{\\mathbf{x}} \\|\\mathbf{x} \\|^2 = \\nabla_{\\mathbf{x}} \\mathbf{x}^\\top \\mathbf{x} = 2\\mathbf{x} \\] \\[ \\nabla_{\\mathbf{X}} \\|\\mathbf{X} \\|_F^2 = 2\\mathbf{X} \\]"},{"location":"AI/Dive%20into%20Deep%20Learning/#244","title":"2.4.4 \u94fe\u5f0f\u6cd5\u5219","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#245","title":"2.4.5 \u5c0f\u7ed3","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#25-automatic-differentiation","title":"2.5 \u81ea\u52a8\u5fae\u5206\uff08automatic differentiation\uff09","text":"<ul> <li>computational graph</li> <li>backpropagate</li> </ul> Python<pre><code>x.requires_grad_(True)  # \u7b49\u4ef7\u4e8ex=torch.arange(4.0,requires_grad=True)\nx.grad  # \u9ed8\u8ba4\u503c\u662fNone\ny = 2 * torch.dot(x, x)\ny.backward()\nx.grad\nx.grad == 4 * x\n</code></pre>"},{"location":"AI/Dive%20into%20Deep%20Learning/#251","title":"2.5.1 \u975e\u6807\u91cf\u53d8\u91cf\u7684\u53cd\u5411\u4f20\u64ad","text":"Python<pre><code># \u5bf9\u975e\u6807\u91cf\u8c03\u7528backward\u9700\u8981\u4f20\u5165\u4e00\u4e2agradient\u53c2\u6570\uff0c\u8be5\u53c2\u6570\u6307\u5b9a\u5fae\u5206\u51fd\u6570\u5173\u4e8eself\u7684\u68af\u5ea6\u3002\n# \u672c\u4f8b\u53ea\u60f3\u6c42\u504f\u5bfc\u6570\u7684\u548c\uff0c\u6240\u4ee5\u4f20\u9012\u4e00\u4e2a1\u7684\u68af\u5ea6\u662f\u5408\u9002\u7684\nx.grad.zero_()\ny = x * x\n# \u7b49\u4ef7\u4e8ey.backward(torch.ones(len(x)))\ny.sum().backward()\nx.grad\n</code></pre>"},{"location":"AI/Dive%20into%20Deep%20Learning/#252","title":"2.5.2 \u5206\u79bb\u8ba1\u7b97","text":"Python<pre><code>x.grad.zero_()\ny = x * x\nu = y.detach()\nz = u * x\n\nz.sum().backward()\nx.grad == u\n</code></pre>"},{"location":"AI/Dive%20into%20Deep%20Learning/#26","title":"2.6 \u6982\u7387","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#261","title":"2.6.1 \u57fa\u672c\u6982\u7387\u8bba","text":"<ul> <li>sampling</li> <li>distribution</li> <li>multinomial distribution</li> </ul> Python<pre><code>fair_probs = torch.ones([6]) / 6\nmultinomial.Multinomial(10, fair_probs).sample() # \u591a\u4e2a\u6837\u672c\n</code></pre>"},{"location":"AI/Dive%20into%20Deep%20Learning/#262","title":"2.6.2 \u5904\u7406\u591a\u4e2a\u968f\u673a\u53d8\u91cf","text":"<ul> <li>joint probability</li> <li>conditional probability</li> <li>Bayes\u2019 theorem</li> </ul> \\[ P(A \\mid B) = \\frac{P(B \\mid A) P(A)}{P(B)}.  \\] <ul> <li>\u5176\u4e2d P (A, B) \u662f\u4e00\u4e2a\u8054\u5408\u5206\u5e03 (joint distribution)\uff0c\u00a0P (A\u2223B) \u662f\u4e00\u4e2a\u6761\u4ef6\u5206\u5e03 (conditional distribution)</li> <li>marginalization<ul> <li>marginal probability</li> <li>marginal distribution</li> </ul> </li> <li>conditionally independent</li> </ul> <p>$$  P(A, B \\mid C) = P(A \\mid C)P(B \\mid C)  $$</p> \\[ A \\perp B \\mid C  \\] <ul> <li>expectation</li> </ul> \\[ E[X] = \\sum_{x} x P(X = x).  \\] \\[ E_{x \\sim P}[f(x)] = \\sum_x f(x) P(x).  \\] <ul> <li>standard deviation</li> </ul> \\[ \\mathrm{Var}[X] = E\\left[(X - E[X])^2\\right] = E[X^2] - E[X]^2.  \\] \\[ \\mathrm{Var}[f(x)] = E\\left[\\left(f(x) - E[f(x)]\\right)^2\\right].  \\]"},{"location":"AI/Dive%20into%20Deep%20Learning/#3","title":"3 \u7ebf\u6027\u795e\u7ecf\u7f51\u7edc","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#31","title":"3.1 \u7ebf\u6027\u56de\u5f52","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#311","title":"3.1.1 \u7ebf\u6027\u56de\u5f52\u7684\u57fa\u672c\u5143\u7d20","text":"<ul> <li>regression</li> <li>prediction / inference</li> <li>training set</li> <li>sample / data point / data instance</li> <li>label / target</li> <li>feature / covariate</li> </ul> \\[ \\mathrm{price} = w_{\\mathrm{area}} \\cdot \\mathrm{area} + w_{\\mathrm{age}} \\cdot \\mathrm{age} + b.  \\] <ul> <li>weight</li> <li>bias / offset / intercept</li> <li>affine transformation<ul> <li>linear transformation</li> <li>translation</li> </ul> </li> <li>model parameters</li> <li>loss function</li> </ul> \\[ l^{(i)}(\\mathbf{w}, b) = \\frac{1}{2} \\left(\\hat{y}^{(i)} - y^{(i)}\\right)^2. \\] \\[ L(\\mathbf{w}, b) =\\frac{1}{n}\\sum_{i=1}^n l^{(i)}(\\mathbf{w}, b) =\\frac{1}{n} \\sum_{i=1}^n \\frac{1}{2}\\left(\\mathbf{w}^\\top \\mathbf{x}^{(i)} + b - y^{(i)}\\right)^2. \\] \\[ \\mathbf{w}^*, b^* = \\operatorname*{argmin}_{\\mathbf{w}, b}\\  L(\\mathbf{w}, b). \\] \\[ \\mathbf{w}^{*} = (\\mathbf X^\\top \\mathbf X)^{-1}\\mathbf X^\\top \\mathbf{y}. \\] <ul> <li>analytical solution</li> <li>gradient descent<ul> <li>minibatch stochastic gradient descent</li> </ul> </li> </ul> \\[ (\\mathbf{w},b) \\leftarrow (\\mathbf{w},b) - \\frac{\\eta}{|\\mathcal{B}|} \\sum_{i \\in \\mathcal{B}} \\partial_{(\\mathbf{w},b)} l^{(i)}(\\mathbf{w},b). \\] <ol> <li>\u521d\u59cb\u5316\u6a21\u578b\u53c2\u6570\u7684\u503c\uff0c\u5982\u968f\u673a\u521d\u59cb\u5316</li> <li>\u4ece\u6570\u636e\u96c6\u4e2d\u968f\u673a\u62bd\u53d6\u5c0f\u6279\u91cf\u6837\u672c\u4e14\u5728\u8d1f\u68af\u5ea6\u7684\u65b9\u5411\u4e0a\u66f4\u65b0\u53c2\u6570\uff0c\u5e76\u4e0d\u65ad\u8fed\u4ee3\u8fd9\u4e00\u6b65\u9aa4 - hyperparameter<ul> <li>\\(|\\mathcal{B}|\\): batch size</li> <li>\\(\\eta\\): learning rate</li> <li>hyperparameter tuning</li> <li>validationg dataset</li> <li>generalization</li> </ul> </li> </ol>"},{"location":"AI/Dive%20into%20Deep%20Learning/#312","title":"3.1.2 \u77e2\u91cf\u5316\u52a0\u901f","text":"<ul> <li>\u77e2\u91cf\u5316\u4ee3\u7801</li> </ul>"},{"location":"AI/Dive%20into%20Deep%20Learning/#313","title":"3.1.3 \u6b63\u6001\u5206\u5e03\u4e0e\u5e73\u65b9\u635f\u5931","text":"<ul> <li>normal distribution / Gaussian distribution</li> </ul> \\[ p(x) = \\frac{1}{\\sqrt{2 \\pi \\sigma^2}} \\exp\\left(-\\frac{1}{2 \\sigma^2} (x - \\mu)^2\\right). \\] \\[ y = \\mathbf{w}^\\top \\mathbf{x} + b + \\epsilon, \\] <ul> <li>\u5176\u4e2d \\(\\epsilon \\sim \\mathcal{N}(0, \\sigma^2)\\). \u56e0\u6b64 y \u7684 likelihood:</li> </ul> \\[ P(y \\mid \\mathbf{x}) = \\frac{1}{\\sqrt{2 \\pi \\sigma^2}} \\exp\\left(-\\frac{1}{2 \\sigma^2} (y - \\mathbf{w}^\\top \\mathbf{x} - b)^2\\right). \\] \\[ P(\\mathbf y \\mid \\mathbf X) = \\prod_{i=1}^{n} p(y^{(i)}|\\mathbf{x}^{(i)}). \\] \\[ -\\log P(\\mathbf y \\mid \\mathbf X) = \\sum_{i=1}^n \\frac{1}{2} \\log(2 \\pi \\sigma^2) + \\frac{1}{2 \\sigma^2} \\left(y^{(i)} - \\mathbf{w}^\\top \\mathbf{x}^{(i)} - b\\right)^2. \\]"},{"location":"AI/Dive%20into%20Deep%20Learning/#314","title":"3.1.4 \u4ece\u7ebf\u6027\u56de\u5f52\u5230\u795e\u7ecf\u7f51\u7edc","text":"<ul> <li>feature dimensionality</li> <li>fully-connected layer / dense layer</li> </ul>"},{"location":"AI/Dive%20into%20Deep%20Learning/#32","title":"3.2 \u7ebf\u6027\u56de\u5f52\u7684\u4ece\u96f6\u5f00\u59cb\u5b9e\u73b0","text":"Python<pre><code>%matplotlib inline\nimport random\nimport torch\nfrom d2l import torch as d2l\ndef synthetic_data(w, b, num_examples):  #@save\n    \"\"\"\u751f\u6210y=Xw+b+\u566a\u58f0\"\"\"\n    X = torch.normal(0, 1, (num_examples, len(w)))\n    y = torch.matmul(X, w) + b\n    y += torch.normal(0, 0.01, y.shape)\n    return X, y.reshape((-1, 1))\n\ntrue_w = torch.tensor([2, -3.4])\ntrue_b = 4.2\nfeatures, labels = synthetic_data(true_w, true_b, 1000)\n\ndef data_iter(batch_size, features, labels):\n    num_examples = len(features)\n    indices = list(range(num_examples))\n    # \u8fd9\u4e9b\u6837\u672c\u662f\u968f\u673a\u8bfb\u53d6\u7684\uff0c\u6ca1\u6709\u7279\u5b9a\u7684\u987a\u5e8f\n    random.shuffle(indices)\n    for i in range(0, num_examples, batch_size):\n        batch_indices = torch.tensor(\n            indices[i: min(i + batch_size, num_examples)])\n        yield features[batch_indices], labels[batch_indices]\n\nw = torch.normal(0, 0.01, size=(2,1), requires_grad=True)\nb = torch.zeros(1, requires_grad=True)\n\ndef linreg(X, w, b):  #@save\n    \"\"\"\u7ebf\u6027\u56de\u5f52\u6a21\u578b\"\"\"\n    return torch.matmul(X, w) + b\n\ndef squared_loss(y_hat, y):  #@save\n    \"\"\"\u5747\u65b9\u635f\u5931\"\"\"\n    return (y_hat - y.reshape(y_hat.shape)) ** 2 / 2\n\ndef sgd(params, lr, batch_size):  #@save\n    \"\"\"\u5c0f\u6279\u91cf\u968f\u673a\u68af\u5ea6\u4e0b\u964d\"\"\"\n    with torch.no_grad():\n        for param in params:\n            param -= lr * param.grad / batch_size\n            param.grad.zero_()\n\nlr = 0.03\nnum_epochs = 3\nnet = linreg\nloss = squared_loss\n\nfor epoch in range(num_epochs):\n    for X, y in data_iter(batch_size, features, labels):\n        l = loss(net(X, w, b), y)  # X\u548cy\u7684\u5c0f\u6279\u91cf\u635f\u5931\n        # \u56e0\u4e3al\u5f62\u72b6\u662f(batch_size,1)\uff0c\u800c\u4e0d\u662f\u4e00\u4e2a\u6807\u91cf\u3002l\u4e2d\u7684\u6240\u6709\u5143\u7d20\u88ab\u52a0\u5230\u4e00\u8d77\uff0c\n        # \u5e76\u4ee5\u6b64\u8ba1\u7b97\u5173\u4e8e[w,b]\u7684\u68af\u5ea6\n        l.sum().backward()\n        sgd([w, b], lr, batch_size)  # \u4f7f\u7528\u53c2\u6570\u7684\u68af\u5ea6\u66f4\u65b0\u53c2\u6570\n    with torch.no_grad():\n        train_l = loss(net(features, w, b), labels)\n        print(f'epoch {epoch + 1}, loss {float(train_l.mean()):f}')\n</code></pre>"},{"location":"AI/Dive%20into%20Deep%20Learning/#33","title":"3.3 \u7ebf\u6027\u56de\u5f52\u7684\u7b80\u6d01\u5b9e\u73b0","text":"Python<pre><code>import numpy as np\nimport torch\nfrom torch.utils import data\nfrom d2l import torch as d2l\n\ntrue_w = torch.tensor([2, -3.4])\ntrue_b = 4.2\nfeatures, labels = d2l.synthetic_data(true_w, true_b, 1000) # \u751f\u6210\u6570\u636e\u96c6\n\ndef load_array(data_arrays, batch_size, is_train=True):  #@save\n    \"\"\"\u6784\u9020\u4e00\u4e2aPyTorch\u6570\u636e\u8fed\u4ee3\u5668\"\"\"\n    dataset = data.TensorDataset(*data_arrays)\n    return data.DataLoader(dataset, batch_size, shuffle=is_train)\n\nbatch_size = 10\ndata_iter = load_array((features, labels), batch_size) # \u8bfb\u53d6\u6570\u636e\u96c6\n\n# nn\u662f\u795e\u7ecf\u7f51\u7edc\u7684\u7f29\u5199\nfrom torch import nn\n\nnet = nn.Sequential(nn.Linear(2, 1)) # \u5b9a\u4e49\u6a21\u578b \uff08\u8f93\u5165\uff0c\u8f93\u51fa\uff09\u7279\u5f81\u5f62\u72b6\nnet[0].weight.data.normal_(0, 0.01)\nnet[0].bias.data.fill_(0) # \u521d\u59cb\u5316\u6a21\u578b\u53c2\u6570\nloss = nn.MSELoss() # \u5b9a\u4e49\u635f\u5931\u51fd\u6570\ntrainer = torch.optim.SGD(net.parameters(), lr=0.03) # \u5b9a\u4e49\u4f18\u5316\u7b97\u6cd5\n\n# \u8bad\u7ec3\nnum_epochs = 3\nfor epoch in range(num_epochs):\n    for X, y in data_iter:\n        l = loss(net(X) ,y)\n        trainer.zero_grad()\n        l.backward()\n        trainer.step()\n    l = loss(net(features), labels)\n    print(f'epoch {epoch + 1}, loss {l:f}')\n\nw = net[0].weight.data\nprint('w\u7684\u4f30\u8ba1\u8bef\u5dee\uff1a', true_w - w.reshape(true_w.shape))\nb = net[0].bias.data\nprint('b\u7684\u4f30\u8ba1\u8bef\u5dee\uff1a', true_b - b)\n</code></pre>"},{"location":"AI/Dive%20into%20Deep%20Learning/#34-softmax","title":"3.4 softmax \u56de\u5f52","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#341","title":"3.4.1 \u5206\u7c7b\u95ee\u9898","text":"<ul> <li>one-hot encoding</li> </ul> \\[ y \\in \\{(1, 0, 0), (0, 1, 0), (0, 0, 1)\\}. \\]"},{"location":"AI/Dive%20into%20Deep%20Learning/#342","title":"3.4.2 \u7f51\u7edc\u67b6\u6784","text":"<ul> <li>affine function</li> <li>logit</li> </ul> \\[ \\begin{split}\\begin{aligned} o_1 &amp;= x_1 w_{11} + x_2 w_{12} + x_3 w_{13} + x_4 w_{14} + b_1,\\\\ o_2 &amp;= x_1 w_{21} + x_2 w_{22} + x_3 w_{23} + x_4 w_{24} + b_2,\\\\ o_3 &amp;= x_1 w_{31} + x_2 w_{32} + x_3 w_{33} + x_4 w_{34} + b_3. \\end{aligned}\\end{split} \\]"},{"location":"AI/Dive%20into%20Deep%20Learning/#343","title":"3.4.3 \u5168\u8fde\u63a5\u5c42\u7684\u53c2\u6570\u5f00\u9500","text":"<ul> <li>\u4e0d\u77e5\u9053\u662f\u4ec0\u4e48\u4e1c\u897f</li> </ul>"},{"location":"AI/Dive%20into%20Deep%20Learning/#344-softmax","title":"3.4.4 softmax \u8fd0\u7b97","text":"<ul> <li>calibration</li> <li>choice model</li> </ul> \\[ \\hat{\\mathbf{y}} = \\mathrm{softmax}(\\mathbf{o})\\quad \\text{\u5176\u4e2d}\\quad \\hat{y}_j = \\frac{\\exp(o_j)}{\\sum_k \\exp(o_k)} \\] \\[ \\operatorname*{argmax}_j \\hat y_j = \\operatorname*{argmax}_j o_j. \\] <ul> <li>linear model</li> </ul>"},{"location":"AI/Dive%20into%20Deep%20Learning/#345","title":"3.4.5 \u5c0f\u6279\u6837\u672c\u7684\u77e2\u91cf\u5316","text":"\\[ \\begin{split}\\begin{aligned} \\mathbf{O} &amp;= \\mathbf{X} \\mathbf{W} + \\mathbf{b}, \\\\ \\hat{\\mathbf{Y}} &amp; = \\mathrm{softmax}(\\mathbf{O}). \\end{aligned}\\end{split} \\]"},{"location":"AI/Dive%20into%20Deep%20Learning/#346","title":"3.4.6 \u635f\u5931\u51fd\u6570","text":"\\[ P(\\mathbf{Y} \\mid \\mathbf{X}) = \\prod_{i=1}^n P(\\mathbf{y}^{(i)} \\mid \\mathbf{x}^{(i)}). \\] \\[ -\\log P(\\mathbf{Y} \\mid \\mathbf{X}) = \\sum_{i=1}^n -\\log P(\\mathbf{y}^{(i)} \\mid \\mathbf{x}^{(i)}) = \\sum_{i=1}^n l(\\mathbf{y}^{(i)}, \\hat{\\mathbf{y}}^{(i)}), \\] \\[ l(\\mathbf{y}, \\hat{\\mathbf{y}}) = - \\sum_{j=1}^q y_j \\log \\hat{y}_j. \\] <ul> <li>cross-entropy loss</li> </ul> \\[ \\begin{split}\\begin{aligned} l(\\mathbf{y}, \\hat{\\mathbf{y}}) &amp;=  - \\sum_{j=1}^q y_j \\log \\frac{\\exp(o_j)}{\\sum_{k=1}^q \\exp(o_k)} \\\\ &amp;= \\sum_{j=1}^q y_j \\log \\sum_{k=1}^q \\exp(o_k) - \\sum_{j=1}^q y_j o_j\\\\ &amp;= \\log \\sum_{k=1}^q \\exp(o_k) - \\sum_{j=1}^q y_j o_j. \\end{aligned}\\end{split} \\] \\[ \\partial_{o_j} l(\\mathbf{y}, \\hat{\\mathbf{y}}) = \\frac{\\exp(o_j)}{\\sum_{k=1}^q \\exp(o_k)} - y_j = \\mathrm{softmax}(\\mathbf{o})_j - y_j. \\]"},{"location":"AI/Dive%20into%20Deep%20Learning/#347","title":"3.4.7 \u4fe1\u606f\u8bba\u57fa\u7840","text":"<ul> <li>information theory</li> <li>entropy</li> </ul> \\[ H[P] = \\sum_j - P(j) \\log P(j). \\]"},{"location":"AI/Dive%20into%20Deep%20Learning/#348","title":"3.4.8 \u6a21\u578b\u9884\u6d4b\u548c\u8bc4\u4f30","text":"<ul> <li>accuracy</li> </ul>"},{"location":"AI/Dive%20into%20Deep%20Learning/#35","title":"3.5 \u56fe\u50cf\u5206\u7c7b\u6570\u636e\u96c6","text":"Python<pre><code>%matplotlib inline\nimport torch\nimport torchvision\nfrom torch.utils import data\nfrom torchvision import transforms\nfrom d2l import torch as d2l\n\nd2l.use_svg_display()\n\n# \u901a\u8fc7ToTensor\u5b9e\u4f8b\u5c06\u56fe\u50cf\u6570\u636e\u4ecePIL\u7c7b\u578b\u53d8\u6362\u621032\u4f4d\u6d6e\u70b9\u6570\u683c\u5f0f\uff0c\n# \u5e76\u9664\u4ee5255\u4f7f\u5f97\u6240\u6709\u50cf\u7d20\u7684\u6570\u503c\u5747\u57280\uff5e1\u4e4b\u95f4\ntrans = transforms.ToTensor()\nmnist_train = torchvision.datasets.FashionMNIST(\n    root=\"../data\", train=True, transform=trans, download=True)\nmnist_test = torchvision.datasets.FashionMNIST(\n    root=\"../data\", train=False, transform=trans, download=True)\n\ndef get_fashion_mnist_labels(labels):  #@save\n    \"\"\"\u8fd4\u56deFashion-MNIST\u6570\u636e\u96c6\u7684\u6587\u672c\u6807\u7b7e\"\"\"\n    text_labels = ['t-shirt', 'trouser', 'pullover', 'dress', 'coat',\n                   'sandal', 'shirt', 'sneaker', 'bag', 'ankle boot']\n    return [text_labels[int(i)] for i in labels]\n\ndef show_images(imgs, num_rows, num_cols, titles=None, scale=1.5):  #@save\n    \"\"\"\u7ed8\u5236\u56fe\u50cf\u5217\u8868\"\"\"\n    figsize = (num_cols * scale, num_rows * scale)\n    _, axes = d2l.plt.subplots(num_rows, num_cols, figsize=figsize)\n    axes = axes.flatten()\n    for i, (ax, img) in enumerate(zip(axes, imgs)):\n        if torch.is_tensor(img):\n            # \u56fe\u7247\u5f20\u91cf\n            ax.imshow(img.numpy())\n        else:\n            # PIL\u56fe\u7247\n            ax.imshow(img)\n        ax.axes.get_xaxis().set_visible(False)\n        ax.axes.get_yaxis().set_visible(False)\n        if titles:\n            ax.set_title(titles[i])\n    return axes\n\nbatch_size = 256\n\ndef get_dataloader_workers():  #@save\n    \"\"\"\u4f7f\u75284\u4e2a\u8fdb\u7a0b\u6765\u8bfb\u53d6\u6570\u636e\"\"\"\n    return 4\n\ntrain_iter = data.DataLoader(mnist_train, batch_size, shuffle=True,\n                             num_workers=get_dataloader_workers())\n\ndef load_data_fashion_mnist(batch_size, resize=None):  #@save\n    \"\"\"\u4e0b\u8f7dFashion-MNIST\u6570\u636e\u96c6\uff0c\u7136\u540e\u5c06\u5176\u52a0\u8f7d\u5230\u5185\u5b58\u4e2d\"\"\"\n    trans = [transforms.ToTensor()]\n    if resize:\n        trans.insert(0, transforms.Resize(resize))\n    trans = transforms.Compose(trans)\n    mnist_train = torchvision.datasets.FashionMNIST(\n        root=\"../data\", train=True, transform=trans, download=True)\n    mnist_test = torchvision.datasets.FashionMNIST(\n        root=\"../data\", train=False, transform=trans, download=True)\n    return (data.DataLoader(mnist_train, batch_size, shuffle=True,\n                            num_workers=get_dataloader_workers()),\n            data.DataLoader(mnist_test, batch_size, shuffle=False,\n                            num_workers=get_dataloader_workers()))\n\ntrain_iter, test_iter = load_data_fashion_mnist(32, resize=64)\nfor X, y in train_iter:\n    print(X.shape, X.dtype, y.shape, y.dtype)\n    break\n</code></pre>"},{"location":"AI/Dive%20into%20Deep%20Learning/#36-softmax","title":"3.6 softmax \u56de\u5f52\u7684\u4ece\u96f6\u5f00\u59cb\u5b9e\u73b0","text":"Python<pre><code>import torch\nfrom IPython import display\nfrom d2l import torch as d2l\n\nbatch_size = 256\ntrain_iter, test_iter = d2l.load_data_fashion_mnist(batch_size)\n\nnum_inputs = 784\nnum_outputs = 10\n\nW = torch.normal(0, 0.01, size=(num_inputs, num_outputs), requires_grad=True)\nb = torch.zeros(num_outputs, requires_grad=True) # \u521d\u59cb\u5316\u6a21\u578b\u53c2\u6570\n\nX = torch.tensor([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])\nX.sum(0, keepdim=True), X.sum(1, keepdim=True) \n\ndef softmax(X):\n    X_exp = torch.exp(X)\n    partition = X_exp.sum(1, keepdim=True)\n    return X_exp / partition  # \u8fd9\u91cc\u5e94\u7528\u4e86\u5e7f\u64ad\u673a\u5236\n\nX = torch.normal(0, 1, (2, 5))\nX_prob = softmax(X)\nX_prob, X_prob.sum(1) # \u5b9a\u4e49softmax\u64cd\u4f5c\n\ndef net(X):\n    return softmax(torch.matmul(X.reshape((-1, W.shape[0])), W) + b) # \u5b9a\u4e49\u6a21\u578b\n\ny = torch.tensor([0, 2])\ny_hat = torch.tensor([[0.1, 0.3, 0.6], [0.3, 0.2, 0.5]])\ny_hat[[0, 1], y] \ndef cross_entropy(y_hat, y):\n    return - torch.log(y_hat[range(len(y_hat)), y])\n\ncross_entropy(y_hat, y) # \u5b9a\u4e49\u635f\u5931\u51fd\u6570\n\ndef accuracy(y_hat, y):  #@save\n    \"\"\"\u8ba1\u7b97\u9884\u6d4b\u6b63\u786e\u7684\u6570\u91cf\"\"\"\n    if len(y_hat.shape) &gt; 1 and y_hat.shape[1] &gt; 1:\n        y_hat = y_hat.argmax(axis=1)\n    cmp = y_hat.type(y.dtype) == y\n    return float(cmp.type(y.dtype).sum())\n\ndef evaluate_accuracy(net, data_iter):  #@save\n    \"\"\"\u8ba1\u7b97\u5728\u6307\u5b9a\u6570\u636e\u96c6\u4e0a\u6a21\u578b\u7684\u7cbe\u5ea6\"\"\"\n    if isinstance(net, torch.nn.Module):\n        net.eval()  # \u5c06\u6a21\u578b\u8bbe\u7f6e\u4e3a\u8bc4\u4f30\u6a21\u5f0f\n    metric = Accumulator(2)  # \u6b63\u786e\u9884\u6d4b\u6570\u3001\u9884\u6d4b\u603b\u6570\n    with torch.no_grad():\n        for X, y in data_iter:\n            metric.add(accuracy(net(X), y), y.numel())\n    return metric[0] / metric[1]\n\nclass Accumulator:  #@save\n    \"\"\"\u5728n\u4e2a\u53d8\u91cf\u4e0a\u7d2f\u52a0\"\"\"\n    def __init__(self, n):\n        self.data = [0.0] * n\n\n    def add(self, *args):\n        self.data = [a + float(b) for a, b in zip(self.data, args)]\n\n    def reset(self):\n        self.data = [0.0] * len(self.data)\n\n    def __getitem__(self, idx):\n        return self.data[idx]\n\nevaluate_accuracy(net, test_iter) # \u5206\u7c7b\u7cbe\u5ea6\n\ndef train_epoch_ch3(net, train_iter, loss, updater):  #@save\n    \"\"\"\u8bad\u7ec3\u6a21\u578b\u4e00\u4e2a\u8fed\u4ee3\u5468\u671f\uff08\u5b9a\u4e49\u89c1\u7b2c3\u7ae0\uff09\"\"\"\n    # \u5c06\u6a21\u578b\u8bbe\u7f6e\u4e3a\u8bad\u7ec3\u6a21\u5f0f\n    if isinstance(net, torch.nn.Module):\n        net.train()\n    # \u8bad\u7ec3\u635f\u5931\u603b\u548c\u3001\u8bad\u7ec3\u51c6\u786e\u5ea6\u603b\u548c\u3001\u6837\u672c\u6570\n    metric = Accumulator(3)\n    for X, y in train_iter:\n        # \u8ba1\u7b97\u68af\u5ea6\u5e76\u66f4\u65b0\u53c2\u6570\n        y_hat = net(X)\n        l = loss(y_hat, y)\n        if isinstance(updater, torch.optim.Optimizer):\n            # \u4f7f\u7528PyTorch\u5185\u7f6e\u7684\u4f18\u5316\u5668\u548c\u635f\u5931\u51fd\u6570\n            updater.zero_grad()\n            l.mean().backward()\n            updater.step()\n        else:\n            # \u4f7f\u7528\u5b9a\u5236\u7684\u4f18\u5316\u5668\u548c\u635f\u5931\u51fd\u6570\n            l.sum().backward()\n            updater(X.shape[0])\n        metric.add(float(l.sum()), accuracy(y_hat, y), y.numel())\n    # \u8fd4\u56de\u8bad\u7ec3\u635f\u5931\u548c\u8bad\u7ec3\u7cbe\u5ea6\n    return metric[0] / metric[2], metric[1] / metric[2]\n\nclass Animator:  #@save\n    \"\"\"\u5728\u52a8\u753b\u4e2d\u7ed8\u5236\u6570\u636e\"\"\"\n    def __init__(self, xlabel=None, ylabel=None, legend=None, xlim=None,\n                 ylim=None, xscale='linear', yscale='linear',\n                 fmts=('-', 'm--', 'g-.', 'r:'), nrows=1, ncols=1,\n                 figsize=(3.5, 2.5)):\n        # \u589e\u91cf\u5730\u7ed8\u5236\u591a\u6761\u7ebf\n        if legend is None:\n            legend = []\n        d2l.use_svg_display()\n        self.fig, self.axes = d2l.plt.subplots(nrows, ncols, figsize=figsize)\n        if nrows * ncols == 1:\n            self.axes = [self.axes, ]\n        # \u4f7f\u7528lambda\u51fd\u6570\u6355\u83b7\u53c2\u6570\n        self.config_axes = lambda: d2l.set_axes(\n            self.axes[0], xlabel, ylabel, xlim, ylim, xscale, yscale, legend)\n        self.X, self.Y, self.fmts = None, None, fmts\n\n    def add(self, x, y):\n        # \u5411\u56fe\u8868\u4e2d\u6dfb\u52a0\u591a\u4e2a\u6570\u636e\u70b9\n        if not hasattr(y, \"__len__\"):\n            y = [y]\n        n = len(y)\n        if not hasattr(x, \"__len__\"):\n            x = [x] * n\n        if not self.X:\n            self.X = [[] for _ in range(n)]\n        if not self.Y:\n            self.Y = [[] for _ in range(n)]\n        for i, (a, b) in enumerate(zip(x, y)):\n            if a is not None and b is not None:\n                self.X[i].append(a)\n                self.Y[i].append(b)\n        self.axes[0].cla()\n        for x, y, fmt in zip(self.X, self.Y, self.fmts):\n            self.axes[0].plot(x, y, fmt)\n        self.config_axes()\n        display.display(self.fig)\n        display.clear_output(wait=True)\n\ndef train_ch3(net, train_iter, test_iter, loss, num_epochs, updater):  #@save\n    \"\"\"\u8bad\u7ec3\u6a21\u578b\uff08\u5b9a\u4e49\u89c1\u7b2c3\u7ae0\uff09\"\"\"\n    animator = Animator(xlabel='epoch', xlim=[1, num_epochs], ylim=[0.3, 0.9],\n                        legend=['train loss', 'train acc', 'test acc'])\n    for epoch in range(num_epochs):\n        train_metrics = train_epoch_ch3(net, train_iter, loss, updater)\n        test_acc = evaluate_accuracy(net, test_iter)\n        animator.add(epoch + 1, train_metrics + (test_acc,))\n    train_loss, train_acc = train_metrics\n    assert train_loss &lt; 0.5, train_loss\n    assert train_acc &lt;= 1 and train_acc &gt; 0.7, train_acc\n    assert test_acc &lt;= 1 and test_acc &gt; 0.7, test_acc\n\nlr = 0.1\n\ndef updater(batch_size):\n    return d2l.sgd([W, b], lr, batch_size)\n\nnum_epochs = 10\ntrain_ch3(net, train_iter, test_iter, cross_entropy, num_epochs, updater) # \u8bad\u7ec3\n\ndef predict_ch3(net, test_iter, n=6):  #@save\n    \"\"\"\u9884\u6d4b\u6807\u7b7e\uff08\u5b9a\u4e49\u89c1\u7b2c3\u7ae0\uff09\"\"\"\n    for X, y in test_iter:\n        break\n    trues = d2l.get_fashion_mnist_labels(y)\n    preds = d2l.get_fashion_mnist_labels(net(X).argmax(axis=1))\n    titles = [true +'\\n' + pred for true, pred in zip(trues, preds)]\n    d2l.show_images(\n        X[0:n].reshape((n, 28, 28)), 1, n, titles=titles[0:n])\n\npredict_ch3(net, test_iter) # \u9884\u6d4b\n</code></pre>"},{"location":"AI/Dive%20into%20Deep%20Learning/#37-softmax","title":"3.7 softmax \u56de\u5f52\u7684\u7b80\u6d01\u5b9e\u73b0","text":"Python<pre><code>import torch\nfrom torch import nn\nfrom d2l import torch as d2l\n\nbatch_size = 256\ntrain_iter, test_iter = d2l.load_data_fashion_mnist(batch_size)\n\n# PyTorch\u4e0d\u4f1a\u9690\u5f0f\u5730\u8c03\u6574\u8f93\u5165\u7684\u5f62\u72b6\u3002\u56e0\u6b64\uff0c\n# \u6211\u4eec\u5728\u7ebf\u6027\u5c42\u524d\u5b9a\u4e49\u4e86\u5c55\u5e73\u5c42\uff08flatten\uff09\uff0c\u6765\u8c03\u6574\u7f51\u7edc\u8f93\u5165\u7684\u5f62\u72b6\nnet = nn.Sequential(nn.Flatten(), nn.Linear(784, 10))\n\ndef init_weights(m):\n    if type(m) == nn.Linear:\n        nn.init.normal_(m.weight, std=0.01)\n\nnet.apply(init_weights); # \u521d\u59cb\u5316\u6a21\u578b\u53c2\u6570\n</code></pre> \\[ \\begin{split}\\begin{aligned} \\hat y_j &amp; =  \\frac{\\exp(o_j - \\max(o_k))\\exp(\\max(o_k))}{\\sum_k \\exp(o_k - \\max(o_k))\\exp(\\max(o_k))} \\\\ &amp; = \\frac{\\exp(o_j - \\max(o_k))}{\\sum_k \\exp(o_k - \\max(o_k))}. \\end{aligned}\\end{split} \\] \\[ \\begin{split}\\begin{aligned} \\log{(\\hat y_j)} &amp; = \\log\\left( \\frac{\\exp(o_j - \\max(o_k))}{\\sum_k \\exp(o_k - \\max(o_k))}\\right) \\\\ &amp; = \\log{(\\exp(o_j - \\max(o_k)))}-\\log{\\left( \\sum_k \\exp(o_k - \\max(o_k)) \\right)} \\\\ &amp; = o_j - \\max(o_k) -\\log{\\left( \\sum_k \\exp(o_k - \\max(o_k)) \\right)}. \\end{aligned}\\end{split} \\] Python<pre><code>loss = nn.CrossEntropyLoss(reduction='none') # LogSumExp\u6280\u5de7\n\ntrainer = torch.optim.SGD(net.parameters(), lr=0.1) # \u4f18\u5316\u7b97\u6cd5\n\nnum_epochs = 10\nd2l.train_ch3(net, train_iter, test_iter, loss, num_epochs, trainer) # \u8bad\u7ec3\n</code></pre>"},{"location":"AI/Dive%20into%20Deep%20Learning/#_1","title":"\u591a\u5c42\u611f\u77e5\u673a","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_2","title":"\u8fc7\u62df\u5408\u548c\u6b20\u62df\u5408","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#dropout","title":"dropout","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_3","title":"\u6df1\u5ea6\u5b66\u4e60\u8ba1\u7b97","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_4","title":"\u5377\u79ef\u795e\u7ecf\u7f51\u7edc","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#lenet","title":"LeNet","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_5","title":"\u73b0\u4ee3\u5377\u79ef\u795e\u7ecf\u7f51\u7edc","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#alexnet","title":"AlexNet","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#vgg","title":"VGG","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#nin","title":"NiN","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#googlenet","title":"GoogLeNet","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#resnet","title":"ResNet","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#densenet","title":"DenseNet","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_6","title":"\u5faa\u73af\u795e\u7ecf\u7f51\u7edc","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_7","title":"\u73b0\u4ee3\u5faa\u73af\u795e\u7ecf\u7f51\u7edc","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#gru","title":"GRU","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#lstm","title":"LSTM","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#seq2seq","title":"seq2seq","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_8","title":"\u6ce8\u610f\u529b\u673a\u5236","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#nadaraya-watson","title":"Nadaraya-Watson","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#bahdanau","title":"Bahdanau","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#multi-headed-attention","title":"Multi-headed attention","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#transformer","title":"Transformer","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_9","title":"\u4f18\u5316\u7b97\u6cd5","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#adagrad","title":"AdaGrad","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#rmsprop","title":"RMSProp","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#adadelta","title":"Adadelta","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#adam","title":"Adam","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_10","title":"\u8ba1\u7b97\u6027\u80fd","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_11","title":"\u8ba1\u7b97\u673a\u89c6\u89c9","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#ssd","title":"SSD","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#r-cnn","title":"R-CNN","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_12","title":"\u81ea\u7136\u8bed\u8a00\u5904\u7406:\u9884\u8bad\u7ec3","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#word2vec","title":"word2vec","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#glove","title":"GloVe","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#bert","title":"BERT","text":""},{"location":"AI/Dive%20into%20Deep%20Learning/#_13","title":"\u81ea\u7136\u8bed\u8a00\u5904\u7406:\u5e94\u7528","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/","title":"\u7edf\u8ba1\u5b66\u4e60\u65b9\u6cd5","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#_1","title":"\u7edf\u8ba1\u5b66\u4e60\u65b9\u6cd5","text":"<p> \u7ea6 3356 \u4e2a\u5b57  43 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 17 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#1","title":"1 \u7edf\u8ba1\u5b66\u4e60\u65b9\u6cd5\u6982\u8bba","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#11","title":"1.1 \u7edf\u8ba1\u5b66\u4e60","text":"<ol> <li>\u7edf\u8ba1\u5b66\u4e60\u7684\u7279\u70b9<ol> <li>\u4ee5\u8ba1\u7b97\u673a\u53ca\u7f51\u7edc\u4e3a\u5e73\u53f0</li> <li>\u4ee5\u6570\u636e\u4e3a\u7814\u7a76\u5bf9\u8c61</li> <li>\u76ee\u7684\u662f\u5bf9\u6570\u636e\u8fdb\u884c\u9884\u6d4b\u4e0e\u5206\u6790</li> <li>\u4ea4\u53c9\u5b66\u79d1</li> </ol> </li> <li>\u7edf\u8ba1\u5b66\u4e60\u7684\u5bf9\u8c61<ol> <li>\u662f\u6570\u636e</li> </ol> </li> <li>\u7edf\u8ba1\u5b66\u4e60\u7684\u76ee\u7684</li> <li>\u7edf\u8ba1\u5b66\u4e60\u7684\u65b9\u6cd5<ol> <li>\u4e3b\u8981\u6709<ol> <li>\u76d1\u7763\u5b66\u4e60\uff08\u672c\u4e66\u4e3b\u8981\u8ba8\u8bba\uff09</li> <li>\u975e\u76d1\u7763\u5b66\u4e60</li> <li>\u534a\u76d1\u7763\u5b66\u4e60</li> <li>\u5f3a\u5316\u5b66\u4e60</li> </ol> </li> <li>\u4e09\u8981\u7d20<ol> <li>\u6a21\u578b</li> <li>\u7b56\u7565</li> <li>\u7b97\u6cd5</li> </ol> </li> <li>\u5b9e\u73b0\u6b65\u9aa4<ol> <li>\u5f97\u5230\u4e00\u4e2a\u8bad\u7ec3\u6570\u636e\u96c6\u5408</li> <li>\u786e\u5b9a\u5b66\u4e60\u6a21\u578b\u7684\u96c6\u5408</li> <li>\u786e\u5b9a\u5b66\u4e60\u7684\u7b56\u7565</li> <li>\u786e\u5b9a\u5b66\u4e60\u7684\u7b97\u6cd5</li> <li>\u901a\u8fc7\u5b66\u4e60\u65b9\u6cd5\u9009\u62e9\u6700\u4f18\u6a21\u578b</li> <li>\u5229\u7528\u5b66\u4e60\u7684\u6700\u4f18\u6a21\u578b\u5bf9\u65b0\u6570\u636e\u8fdb\u884c\u9884\u6d4b\u6216\u5206\u6790</li> </ol> </li> </ol> </li> <li>\u7edf\u8ba1\u5b66\u4e60\u7684\u7814\u7a76<ol> <li>\u65b9\u6cd5</li> <li>\u7406\u8bba</li> <li>\u5e94\u7528</li> </ol> </li> <li>\u7edf\u8ba1\u5b66\u4e60\u7684\u91cd\u8981\u6027</li> </ol>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#12","title":"1.2 \u76d1\u7763\u5b66\u4e60","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#121","title":"1.2.1 \u57fa\u672c\u6982\u5ff5","text":"<ol> <li>\u8f93\u5165\u7a7a\u95f4\u3001\u7279\u5f81\u7a7a\u95f4\u4e0e\u8f93\u51fa\u7a7a\u95f4<ol> <li>\u6bcf\u4e2a\u8f93\u5165\u662f\u4e00\u4e2a\u5b9e\u4f8b\uff0c\u901a\u5e38\u7531\u7279\u5f81\u5411\u91cf\u8868\u793a</li> <li>\u76d1\u7763\u5b66\u4e60\u4ece\u8bad\u7ec3\u6570\u636e\u96c6\u5408\u4e2d\u5b66\u4e60\u6a21\u578b\uff0c\u5bf9\u6d4b\u8bd5\u6570\u636e\u8fdb\u884c\u9884\u6d4b</li> <li>\u6839\u636e\u8f93\u5165\u53d8\u91cf\u548c\u8f93\u51fa\u53d8\u91cf\u7684\u4e0d\u540c\u7c7b\u578b<ol> <li>\u56de\u5f52\u95ee\u9898: \u90fd\u8fde\u7eed</li> <li>\u5206\u7c7b\u95ee\u9898: \u8f93\u51fa\u6709\u9650\u79bb\u6563</li> <li>\u6807\u6ce8\u95ee\u9898: \u90fd\u662f\u53d8\u91cf\u5e8f\u5217</li> </ol> </li> </ol> </li> <li>\u8054\u5408\u6982\u7387\u5206\u5e03</li> <li>\u5047\u8bbe\u7a7a\u95f4<ol> <li>\u6a21\u578b\u5c5e\u4e8e\u7531\u8f93\u5165\u7a7a\u95f4\u5230\u8f93\u51fa\u7a7a\u95f4\u7684\u6620\u5c04\u7684\u96c6\u5408\uff0c\u8fd9\u4e2a\u96c6\u5408\u5c31\u662f\u5047\u8bbe\u7a7a\u95f4</li> <li>\u6a21\u578b\u53ef\u4ee5\u662f\uff08\u975e\uff09\u6982\u7387\u6a21\u578b</li> </ol> </li> </ol>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#122","title":"1.2.2 \u95ee\u9898\u7684\u5f62\u5f0f\u5316","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#13","title":"1.3 \u7edf\u8ba1\u5b66\u4e60\u4e09\u8981\u8bfb","text":"<ul> <li>\u65b9\u6cd5=\u6a21\u578b+\u7b56\u7565+\u7b97\u6cd5</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#131","title":"1.3.1 \u6a21\u578b","text":"<ul> <li>\u6a21\u578b\u5c31\u662f\u7d22\u8981\u5b66\u4e60\u7684\u6761\u4ef6\u6982\u7387\u5206\u5e03\u6216\u51b3\u7b56\u51fd\u6570</li> </ul> \\[ \\mathcal{F}=\\{f\\mid Y=f(X)\\} \\] <ul> <li>\u53c2\u6570\u7a7a\u95f4</li> </ul> \\[ \\mathcal{F}=\\{f | Y=f_{\\theta}(X),\\theta\\in\\mathbf{R}^{n}\\} \\] <ul> <li>\u540c\u6837\u53ef\u4ee5\u5b9a\u4e49\u4e3a\u6761\u4ef6\u6982\u7387\u7684\u96c6\u5408</li> </ul> \\[ \\mathcal{F}=\\{P|P(Y|X)\\} \\] \\[ \\mathcal{F}=\\{P\\mid P_{\\theta}(Y\\mid X),\\theta\\in\\mathbf{R}^{n}\\} \\]"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#132","title":"1.3.2 \u7b56\u7565","text":"<ol> <li>\u635f\u5931\u51fd\u6570\u548c\u98ce\u9669\u51fd\u6570<ol> <li>loos function or cost function \\(\\displaystyle L(Y,f(X))\\)<ol> <li>0-1 loss function<ol> <li>\\(\\displaystyle L(Y,f(X))=\\begin{cases}1,&amp;Y\\neq f(X)\\\\0,&amp;Y=f(X)\\end{cases}\\)</li> </ol> </li> <li>quadratic loss function<ol> <li>\\(\\displaystyle L(Y,f(X))=(Y-f(X))^{2}\\)</li> </ol> </li> <li>absolute loss function<ol> <li>\\(\\displaystyle L(Y,f(X))=|Y-f(X)|\\)</li> </ol> </li> <li>logarithmic loss function or log-likelihood loss function<ol> <li>\\(\\displaystyle L(Y,P(Y\\mid X))=-\\log P(Y\\mid X)\\)</li> </ol> </li> </ol> </li> <li>\\(\\displaystyle R_{\\exp}(f)=E_{P}[L(Y,f(X))]=\\int_{x\\times y}L(y,f(x))P(x,y)\\mathrm{d}x\\mathrm{d}y\\)<ol> <li>risk function or expected loss</li> <li>\u4f46\u662f\u8054\u5408\u5206\u5e03\u4f4d\u7f6e\uff0c\u6240\u4ee5\u8981\u5b66\u4e60\uff0c\u4f46\u662f\u8fd9\u6837\u4ee5\u6765\u98ce\u9669\u6700\u5c0f\u53c8\u8981\u7528\u5230\u8054\u5408\u5206\u5e03\uff0c\u90a3\u4e48\u8fd9\u5c31\u6210\u4e3a\u4e86\u75c5\u6001\u95ee\u9898 (ill-formed problem)</li> </ol> </li> <li>empirical risk or empirical loss<ol> <li>\\(\\displaystyle R_{\\mathrm{emp}}(f)=\\frac{1}{N}\\sum_{i=1}^{N}L(y_{i},f(x_{i}))\\)</li> <li>\u5f53 \\(\\displaystyle N\\) \u8d8b\u4e8e\u65e0\u7a77\u65f6\uff0c\u7ecf\u9a8c\u98ce\u9669\u8d8b\u4e8e\u671f\u671b\u98ce\u9669<ol> <li>\u8fd9\u5c31\u5173\u7cfb\u5230\u4e24\u4e2a\u57fa\u672c\u7b56\u7565:<ol> <li>\u7ecf\u9a8c\u98ce\u9669\u6700\u5c0f\u5316</li> <li>\u7ed3\u6784\u98ce\u9669\u6700\u5c0f\u5316</li> </ol> </li> </ol> </li> </ol> </li> </ol> </li> <li>\u7ecf\u9a8c\u98ce\u9669\u6700\u5c0f\u5316\u4e0e\u7ed3\u6784\u98ce\u9669\u6700\u5c0f\u5316<ol> <li>empirical risk minimization \uff08\u6837\u672c\u5bb9\u91cf\u6bd4\u8f83\u5927\u7684\u65f6\u5019\uff09<ol> <li>\\(\\displaystyle \\min_{f\\in\\mathcal{F}} \\frac{1}{N}\\sum_{i=1}^{N}L(y_{i},f(x_{i}))\\)</li> <li>maximum likelihood estimation</li> </ol> </li> <li>structural risk minimization<ol> <li>regularization</li> <li>\\(\\displaystyle R_{\\mathrm{sm}}(f)=\\frac{1}{N}\\sum_{i=1}^{N}L(y_{i},f(x_{i}))+\\lambda J(f)\\)</li> <li>\u590d\u6742\u5ea6\u8868\u793a\u4e86\u5bf9\u590d\u6742\u6a21\u578b\u7684\u4e58\u6cd5</li> <li>maximum posterior probability estimation</li> </ol> </li> </ol> </li> </ol>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#133","title":"1.3.3 \u7b97\u6cd5","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#14","title":"1.4 \u6a21\u578b\u8bc4\u4f30\u4e0e\u6a21\u578b\u9009\u62e9","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#141","title":"1.4.1 \u8bad\u7ec3\u8bef\u5dee\u4e0e\u6d4b\u8bd5\u8bef\u5dee","text":"\\[ R_{\\mathrm{emp}}(\\hat{f})=\\frac{1}{N}\\sum_{i=1}^{N}L(y_{i},\\hat{f}(x_{i})) \\] \\[ e_{\\mathrm{test}}=\\frac{1}{N^{\\prime}}\\sum_{i=1}^{N^{\\prime}}L(y_{i},\\hat{f}(x_{i})) \\] \\[ r_{\\mathrm{test}}+e_{\\mathrm{test}}=1 \\] <ul> <li>generalization ability</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#142","title":"1.4.2 \u8fc7\u62df\u5408\u4e0e\u6a21\u578b\u9009\u62e9","text":"<ul> <li>model selection</li> <li>over-fitting </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#15","title":"1.5 \u6b63\u5219\u5316\u4e0e\u4ea4\u53c9\u9a8c\u8bc1","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#151","title":"1.5.1 \u6b63\u5219\u5316","text":"\\[ L(w)=\\frac{1}{N}\\sum_{i=1}^{N}(f(x_{i};w)-y_{i})^{2}+\\frac{\\lambda}{2}\\parallel w\\parallel^{2} \\]"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#152","title":"1.5.2 \u4ea4\u53c9\u9a8c\u8bc1","text":"<ul> <li>cross validation</li> <li>\u6570\u636e\u96c6<ul> <li>\u8bad\u7ec3\u96c6</li> <li>\u9a8c\u8bc1\u96c6</li> <li>\u6d4b\u8bd5\u96c6 1. \u7b80\u5355\u4ea4\u53c9\u9a8c\u8bc1 2. \\(\\displaystyle S\\) \u6298\u4ea4\u53c9\u9a8c\u8bc1 3. \u7559\u4e00\u4ea4\u53c9\u9a8c\u8bc1</li> </ul> </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#16","title":"1.6 \u6cdb\u5316\u80fd\u529b","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#161","title":"1.6.1 \u6cdb\u5316\u8bef\u5dee","text":"<ul> <li>generalization error</li> </ul> \\[ R_{\\exp}(\\hat{f})=E_{P}[L(Y,\\hat{f}(X))]=\\int_{R\\times y}L(y,\\hat{f}(x))P(x,y)\\mathrm{d}x\\mathrm{d}y \\]"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#162","title":"1.6.2 \u6cdb\u5316\u8bef\u5dee\u4e0a\u754c","text":"<ul> <li>generalization error bound</li> <li>\u6837\u672c\u5bb9\u91cf\u589e\u52a0\u65f6\uff0c\u6cdb\u5316\u4e0a\u754c\u8d8b\u4e8e 0</li> <li>\u5047\u8bbe\u7a7a\u95f4\u8d8a\u5927\uff0c\u6cdb\u5316\u8bef\u5dee\u4e0a\u754c\u8d8a\u5927 </li> <li>\u8fd9\u4e2a\u5b9a\u7406\u53ea\u9002\u7528\u4e8e\u5047\u8bbe\u7a7a\u95f4\u5305\u542b\u6709\u9650\u4e2a\u51fd\u6570</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#17","title":"1.7 \u751f\u6210\u6a21\u578b\u4e0e\u5224\u522b\u6a21\u578b","text":"<ul> <li>generative model<ul> <li>\u8fd8\u539f\u51fa\u8054\u5408\u6982\u7387\u5206\u5e03 \\(\\displaystyle P(X,Y)\\)</li> <li>\u6734\u7d20\u8d1d\u53f6\u65af\u6cd5</li> <li>\u9690\u9a6c\u5c14\u53ef\u592b\u6a21\u578b</li> <li>\u6536\u655b\u901f\u5ea6\u5feb</li> </ul> </li> <li>discriminative model<ul> <li>\u76f4\u63a5\u5b66\u4e60\u51b3\u7b56\u51fd\u6570\u6216\u6761\u4ef6\u6982\u7387\u5206\u5e03 \\(\\displaystyle P(Y|X)\\)</li> <li>\\(\\displaystyle k\\) \u8fd1\u90bb\u6cd5</li> <li>\u611f\u77e5\u673a</li> <li>\u51b3\u7b56\u6811</li> <li>\u903b\u8f91\u65af\u8c1b\u56de\u5f52\u6a21\u578b</li> <li>\u6700\u5927\u71b5\u6a21\u578b</li> <li>\u652f\u6301\u5411\u91cf\u673a</li> <li>\u63d0\u5347\u65b9\u6cd5</li> <li>\u6761\u4ef6\u968f\u673a\u573a</li> <li>\u51c6\u786e\u5ea6\u9ad8</li> </ul> </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#18","title":"1.8 \u5206\u7c7b\u95ee\u9898","text":"<ul> <li>precision \\(\\displaystyle P=\\frac{TP}{TP+FP}\\)</li> <li>recall \\(\\displaystyle R=\\frac{TP}{TP+FN}\\) </li> </ul> \\[ \\frac{2}{F_{1}}=\\frac{1}{P}+\\frac{1}{R} \\] \\[ F_{1}=\\frac{2TP}{2TP+FP+FN} \\] <ul> <li>text classification</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#19","title":"1.9 \u6807\u6ce8\u95ee\u9898","text":"<ul> <li>tagging \u662f classificationd \u4e00\u4e2a\u63a8\u5e7f</li> <li>\u662f structure prediction \u7684\u7b80\u5355\u5f62\u5f0f</li> <li>\u9690\u9a6c\u5c14\u53ef\u592b\u6a21\u578b</li> <li>\u6761\u4ef6\u968f\u673a\u573a</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#110","title":"1.10 \u56de\u5f52\u95ee\u9898","text":"<ul> <li>regression</li> <li>\uff08\u975e\uff09\u7ebf\u6027\u56de\u5f52\uff0c\u4e00\u5143\u56de\u5f52\uff0c\u591a\u5143\u56de\u5f52</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#2","title":"2 \u611f\u77e5\u673a","text":"<ul> <li>perception</li> <li>\u611f\u77e5\u673a\u5bf9\u5e94\u4e8e\u8f93\u5165\u7a7a\u95f4\u4e2d\u5c06\u5b9e\u4f8b\u5212\u5206\u6210\u6b63\u8d1f\u4e24\u7c7b\u7684\u5206\u79bb\u8d85\u5e73\u9762\uff0c\u5c5e\u4e8e\u5224\u522b\u6a21\u578b</li> <li>\u539f\u59cb\u5f62\u5f0f\u548c\u5bf9\u5076\u5f62\u5f0f</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#21","title":"2.1 \u611f\u77e5\u673a\u6a21\u578b","text":"<ul> <li>\u5047\u8bbe\u7a7a\u95f4\u662f\u5b9a\u4e49\u5728\u7279\u5f81\u7a7a\u95f4\u4e2d\u6240\u6709\u7684\u7ebf\u6027\u5206\u7c7b\u6a21\u578b\uff08linear classification model\uff09\\(\\displaystyle \\{f|f(x) = w \\cdot x+b\\}\\) </li> <li>separating hyperplane </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#22","title":"2.2 \u611f\u77e5\u673a\u5b66\u4e60\u7b56\u7565","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#221","title":"2.2.1 \u6570\u636e\u96c6\u7684\u7ebf\u6027\u53ef\u5206\u6027","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#222","title":"2.2.2 \u611f\u77e5\u673a\u5b66\u4e60\u7b56\u7565","text":"<ul> <li>\u5b9a\u4e49\u635f\u5931\u51fd\u6570\u5e76\u5c06\u635f\u5931\u51fd\u6570\u6781\u5c0f\u5316</li> </ul> \\[ L(w,b)=-\\sum_{x_{i}\\in M}y_{i}(w\\cdot x_{i}+b) \\]"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#223","title":"2.2.3 \u611f\u77e5\u673a\u5b66\u4e60\u7b97\u6cd5","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#224","title":"2.2.4 \u611f\u77e5\u673a\u5b66\u4e60\u7b97\u6cd5\u7684\u539f\u59cb\u5f62\u5f0f","text":"\\[ \\min_{w,b}L(w,b)=-\\sum_{x_{i}\\in M}y_{i}(w\\cdot x_{i}+b) \\] <ul> <li>stochastic gradient descent</li> </ul> \\[ \\nabla_{_w}L(w,b)=-\\sum_{x_{i}\\in M}y_{i}x_{i} \\] \\[ \\nabla_{b}L(w,b)=-\\sum_{x_{i}eM}y_{i} \\] \\[ w\\leftarrow w+\\eta y_{i}x_{i} \\] \\[ b\\leftarrow b+\\eta y_{i} \\] <ul> <li>\\(\\displaystyle \\eta\\) \u88ab\u79f0\u4e3a\u5b66\u4e60\u7387\uff08learning rate\uff09 </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#225","title":"2.2.5 \u7b97\u6cd5\u7684\u6536\u655b\u6027","text":"<ul> <li>\u4e3a\u4e86\u5f97\u5230\u552f\u4e00\u7684\u8d85\u5e73\u9762\uff0c\u9700\u8981\u5bf9\u5206\u79bb\u8d85\u5e73\u9762\u589e\u52a0\u7ea6\u675f\u6761\u4ef6\uff0c\u5373\u7ebf\u6027\u652f\u6301\u5411\u91cf\u673a</li> <li>\u5982\u679c\u8bad\u7ec3\u96c6\u7ebf\u6027\u4e0d\u53ef\u5206\uff0c\u90a3\u4e48\u611f\u77e5\u673a\u5b66\u4e60\u7b97\u6cd5\u4e0d\u6536\u655b</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#226","title":"2.2.6 \u611f\u77e5\u673a\u5b66\u4e60\u7b97\u6cd5\u7684\u5bf9\u5076\u5f62\u5f0f","text":"\\[ \\begin{aligned}&amp;w\\leftarrow w+\\eta y_{i}x_{i}\\\\&amp;b\\leftarrow b+\\eta y_{i}\\end{aligned} \\] \\[ w=\\sum_{i=1}^{N}\\alpha_{i}y_{i}x_{i} \\] \\[ b=\\sum_{i=1}^{N}\\alpha_{i}y_{i} \\] <ul> <li>Gram matrix</li> </ul> \\[ G=[x_{i}\\cdot x_{j}]_{N\\times N} \\]"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#3-displaystyle-k","title":"3 \\(\\displaystyle k\\) \u8fd1\u90bb\u6cd5","text":"<ul> <li>k-nearest neighbor</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#31-displaystyle-k","title":"3.1 \\(\\displaystyle k\\) \u8fd1\u90bb\u7b97\u6cd5","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#32-displaystyle-k","title":"3.2 \\(\\displaystyle k\\) \u8fd1\u90bb\u6a21\u578b","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#321","title":"3.2.1 \u6a21\u578b","text":"<ul> <li>cell</li> <li>class label </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#33","title":"3.3 \u8ddd\u79bb\u5ea6\u91cf","text":"<ul> <li>\\(\\displaystyle L_{p}\\) distance or Minkowski distamce</li> <li>\\(\\displaystyle L_{p}(x_{i},x_{j})=\\left(\\sum_{l=1}^{n}\\mid x_{i}^{(l)}-x_{j}^{(l)}\\mid^{p}\\right)^{\\frac{1}{p}}\\)</li> <li>\\(\\displaystyle L_{2}(x_{i},x_{j})=\\left(\\sum_{i=1}^{n}\\mid x_{i}^{(l)}-x_{j}^{(l)}\\mid^{2}\\right)^{\\frac{1}{2}}\\)</li> <li>\\(\\displaystyle L_{1}(x_{i}, x_{j})=\\sum_{l=1}^{n}\\mid x_{i}^{(l)}-x_{j}^{(l)}\\mid\\)</li> <li>\\(\\displaystyle L_{\\infty}(x_{i}, x_{j})=\\max_{l}\\mid x_{i}^{(l)}-x_{j}^{(l)}\\mid\\) </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#331-displaystyle-k","title":"3.3.1 \\(\\displaystyle k\\) \u503c\u7684\u9009\u62e9","text":"<ul> <li>if k is small, then the approximation error will reduce</li> <li>estimation error</li> <li>\\(\\displaystyle k\\) \u503c\u7684\u51cf\u5c0f\u5c31\u610f\u5473\u7740\u6574\u4f53\u6a21\u578b\u53d8\u5f97\u590d\u6742\uff0c\u5bb9\u6613\u53d1\u751f\u8fc7\u62df\u5408</li> <li>\u5728\u5e94\u7528\u4e2d, \\(\\displaystyle k\\) \u503c\u4e00\u822c\u53d6\u4e00\u4e2a\u6bd4\u8f83\u5c0f\u7684\u6570\u503c\uff0c\u901a\u5e38\u91c7\u7528\u4ea4\u53c9\u9a8c\u8bc1\u6cd5\u6765\u9009\u53d6\u6700\u4f18\u7684 \\(\\displaystyle k\\) \u503c</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#332","title":"3.3.2 \u5206\u7c7b\u51b3\u7b56\u89c4\u5219","text":"<ul> <li>\u591a\u6570\u8868\u51b3\u89c4\u5219\uff08majority voting rule\uff09 </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#34-displaystyle-k-displaystyle-kd","title":"3.4 \\(\\displaystyle k\\) \u8fd1\u90bb\u6cd5\u7684\u5b9e\u73b0: \\(\\displaystyle kd\\) \u6811","text":"<ul> <li>linear scan</li> <li>kd tree</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#341-displaystyle-kd","title":"3.4.1 \u6784\u9020 \\(\\displaystyle kd\\) \u6811","text":"<ul> <li>\\(\\displaystyle kd\\) \u6811\u662f\u4e00\u4e8c\u53c9\u6811\uff0c\u8868\u793a\u5bf9 \\(\\displaystyle k\\) \u7ef4\u7a7a\u95f4\u7684\u4e00\u4e2a\u5212\u5206\uff08partition\uff09</li> <li>\u901a\u5e38\u9009\u62e9\u8bad\u7ec3\u5b9e\u4f8b\u70b9\u5728\u9009\u5b9a\u5750\u6807\u8f74\u4e0a\u7684\u4e2d\u4f4d\u6570\u4e3a\u5207\u5206\u70b9\uff0c\u867d\u7136\u8fd9\u6837\u5f97\u5230\u7684\u6811\u662f\u5e73\u8861\u7684\uff0c\u4f46\u6548\u7387\u672a\u5fc5\u662f\u6700\u4f18\u7684  \u6709\u610f\u601d</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#342-displaystyle-kd","title":"3.4.2 \u641c\u7d22 \\(\\displaystyle kd\\) \u6811","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#4","title":"4 \u6734\u7d20\u8d1d\u53f6\u65af\u6cd5","text":"<ul> <li>\u57fa\u4e8e\u8d1d\u53f6\u65af\u5b9a\u7406\u4e0e\u7279\u5f81\u6761\u4ef6\u72ec\u7acb\u5047\u8bbe\u7684\u5206\u7c7b\u65b9\u6cd5</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#41","title":"4.1 \u6734\u7d20\u8d1d\u53f6\u65af\u6cd5\u7684\u5b66\u4e60\u4e0e\u5206\u7c7b","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#411","title":"4.1.1 \u57fa\u672c\u65b9\u6cd5","text":"<ul> <li>\u5b66\u4e60\u5148\u9a8c\u6982\u7387\u5206\u5e03\u548c\u6761\u4ef6\u6982\u7387\u5206\u5e03\u4e8e\u662f\u5b66\u4e60\u5230\u8054\u5408\u6982\u7387\u5206\u5e03</li> </ul> \\[ P(X=x\\mid Y=c_{k})=P(X^{(1)}=x^{(1)},\\cdots,X^{(n)}=x^{(n)}\\mid Y=c_{k}),\\quad k=1,2,\\cdots,K \\] <ul> <li>\u5f15\u5165\u4e86\u6761\u4ef6\u72ec\u7acb\u6027\u5047\u8bbe</li> </ul> \\[ \\begin{aligned} P(X=x|Y=c_{k})&amp; =P(X^{(1)}=x^{(1)},\\cdots,X^{(n)}=x^{(n)}\\mid Y=c_{k}) \\\\ &amp;=\\prod_{j=1}^{n}P(X^{(j)}=x^{(j)}\\mid Y=c_{k}) \\end{aligned} \\] \\[ P(Y=c_{k}\\mid X=x)=\\frac{P(X=x\\mid Y=c_{k})P(Y=c_{k})}{\\sum_{k}P(X=x\\mid Y=c_{k})P(Y=c_{k})} \\] \\[ P(Y=c_{k}\\mid X=x)=\\frac{P(Y=c_{k})\\prod_{j}P(X^{(j)}=x^{(j)}\\mid Y=c_{k})}{\\sum_{k}P(Y=c_{k})\\prod_{j}P(X^{(j)}=x^{(j)}\\mid Y=c_{k})},\\quad k=1,2,\\cdots,K \\] \\[ y=f(x)=\\arg\\max_{c_{k}}\\frac{P(Y=c_{k})\\prod_{j}P(X^{(j)}=x^{(j)}\\mid Y=c_{k})}{\\sum_{k}P(Y=c_{k})\\prod_{j}P(X^{(j)}=x^{(j)}\\mid Y=c_{k})} \\] \\[ y=\\arg\\max_{c_{k}}P(Y=c_{k})\\prod_{j}P(X^{(j)}=x^{(j)}\\mid Y=c_{k}) \\]"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#412","title":"4.1.2 \u540e\u9a8c\u6982\u7387\u6700\u5927\u5316\u7684\u542b\u4e49","text":"\\[ L(Y,f(X))=\\begin{cases}1,&amp;Y\\neq f(X)\\\\0,&amp;Y=f(X)\\end{cases} \\] \\[ R_{\\exp}(f)=E[L(Y,f(X))] \\] \\[ R_{\\exp}(f)=E_{\\chi}\\sum_{k=1}^{K}[L(c_{k},f(X))]P(c_{k}\\mid X) \\] \\[ \\begin{align} f(x) &amp;=\\arg\\min_{y\\in\\mathcal{Y}}\\sum_{k=1}^{K}L(c_{k},y)P(c_{k}\\mid X=x) \\\\ &amp;=\\arg\\min_{y\\in\\mathcal{Y}}\\sum_{k=1}^{K}P(y\\neq c_{k}\\mid X=x) \\\\ &amp;=\\arg\\min_{y\\in\\mathcal{Y}}(1-P(y=c_{k}\\mid X=x)) \\\\ &amp;=\\arg\\max_{y\\in\\mathcal{Y}}P(y=c_{k}\\mid X=x)  \\end{align} \\] \\[ f(x)=\\arg\\max_{c_{k}}P(c_{k}\\mid X=x) \\] <ul> <li>\u671f\u671b\u98ce\u9669\u6700\u5c0f\u5316\u51c6\u5219\u5c31\u5f97\u5230\u8054\u8003\u540e\u9a8c\u6982\u7387\u6700\u5927\u5316\u51c6\u5219</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#42","title":"4.2 \u6734\u7d20\u8d1d\u53f6\u65af\u6cd5\u7684\u53c2\u6570\u4f30\u8ba1","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#421","title":"4.2.1 \u6781\u5927\u4f3c\u7136\u4f30\u8ba1","text":"\\[ P(Y=c_{k})=\\frac{\\sum_{i=1}^{N}I(y_{i}=c_{k})}{N} , k=1,2,\\cdots,K \\] \\[ P(X^{(j)}=a_{ji}\\mid Y=c_{k})=\\frac{\\sum_{i=1}^{N}I(x_{i}^{(j)}=a_{ji},y_{i}=c_{k})}{\\sum_{i=1}^{N}I(y_{i}=c_{k})}\\\\j=1,2,\\cdots,n ;\\quad l=1,2,\\cdots,S_{j} ;\\quad k=1,2,\\cdots,K \\]"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#422","title":"4.2.2 \u5b66\u4e60\u4e0e\u5206\u7c7b\u7b97\u6cd5","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#423","title":"4.2.3 \u8d1d\u53f6\u65af\u4f30\u8ba1","text":"<ul> <li>\u6781\u5927\u4f3c\u7136\u4f30\u8ba1\u53ef\u80fd\u4f1a\u51fa\u73b0\u6240\u8981\u4f30\u8ba1\u7684\u6982\u7387\u503c\u4e3a 0 \u7684\u60c5\u51b5</li> <li>\u6761\u4ef6\u6982\u7387\u7684\u8d1d\u53f6\u65af\u4f30\u8ba1</li> </ul> \\[ P_{\\lambda}(X^{(j)}=a_{ji}\\mid Y=c_{k})=\\frac{\\sum_{i=1}^{N}I(x_{i}^{(j)}=a_{ji},y_{i}=c_{k})+\\lambda}{\\sum_{i=1}^{N}I(y_{i}=c_{k})+S_{j}\\lambda} \\] <ul> <li>when \\(\\displaystyle \\lambda = 0\\), it's called Laplace smoothing</li> </ul> \\[ \\begin{aligned}&amp;P_{\\lambda}(X^{(j)}=a_{jl}\\mid Y=c_{k})&gt;0\\\\&amp;\\sum_{l=1}^{s_{j}}P(X^{(j)}=a_{jl}\\mid Y=c_{k})=1\\end{aligned} \\] <ul> <li>\u8868\u660e\u8d1d\u53f6\u65af\u4f30\u8ba1\u786e\u5b9e\u662f\u4e00\u79cd\u6982\u7387\u5206\u5e03</li> <li>\u5148\u9a8c\u6982\u7387\u7684\u8d1d\u53f6\u65af\u4f30\u8ba1</li> </ul> \\[ P_{\\lambda}(Y=c_{k})=\\frac{\\sum_{i=1}^{N}I(y_{i}=c_{k})+\\lambda}{N+K\\lambda} \\]"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#5","title":"5 \u51b3\u7b56\u6811","text":"<ul> <li>decision tree<ul> <li>\u7279\u5f81\u9009\u62e9</li> <li>\u51b3\u7b56\u6811\u7684\u751f\u6210</li> <li>\u51b3\u7b56\u6811\u7684\u4fee\u526a</li> </ul> </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#51","title":"5.1 \u51b3\u7b56\u6811\u6a21\u578b\u4e0e\u5b66\u4e60","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#511","title":"5.1.1 \u51b3\u7b56\u6811\u6a21\u578b","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#512-if-then","title":"5.1.2 \u51b3\u7b56\u6811\u4e0e if-then \u89c4\u5219","text":"<ul> <li>\u4e92\u65a5\u4e14\u5b8c\u5907</li> <li>\u6bcf\u4e00\u4e2a\u5b9e\u4f8b\u90fd\u88ab\u4e00\u6761\u8def\u5f84\u4f1a\u89c4\u5219\u6240\u8986\u76d6\uff0c\u800c\u4e14\u53ea\u88ab\u4e00\u6761\u8def\u5f84\u6216\u4e00\u6761\u89c4\u5219\u6240\u8986\u76d6</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#513","title":"5.1.3 \u51b3\u7b56\u6811\u4e0e\u6761\u4ef6\u6982\u7387\u5206\u5e03","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#514","title":"5.1.4 \u51b3\u7b56\u6811\u5b66\u4e60","text":"<ul> <li>\u51b3\u7b56\u6811\u5b66\u4e60\u672c\u8d28\u4e0a\u662f\u4ece\u8bad\u7ec3\u6570\u636e\u96c6\u4e2d\u5f52\u7eb3\u51fa\u4e00\u7ec4\u5206\u7c7b\u89c4\u5219</li> <li>\u5728\u635f\u5931\u51fd\u6570\u610f\u4e49\u4e0b\u9009\u62e9\u6700\u4f18\u51b3\u7b56\u6811\u7684\u95ee\u9898\uff0c\u662f NP \u5b8c\u5168\u95ee\u9898\uff0c\u91c7\u7528\u542f\u53d1\u5f0f\u65b9\u6cd5\uff0c\u8fd1\u4f3c\u6c42\u89e3\uff0c\u8fd9\u6837\u5f97\u5230\u7684\u51b3\u7b56\u6811\u662f\u6b21\u6700\u4f18\uff08sub-optimal\uff09</li> <li>\u4e3a\u4e86\u9632\u6b62\u8fc7\u62df\u5408\uff0c\u6211\u4eec\u9700\u8981\u5bf9\u5df2\u751f\u6210\u7684\u6811\u81ea\u4e0a\u800c\u4e0b\u8fdb\u884c\u526a\u679d</li> <li>\u51b3\u7b56\u6811\u7684\u751f\u6210\u503c\u8003\u8651\u5c40\u90e8\u6700\u4f18\uff0c\u526a\u679d\u5219\u8003\u8651\u5168\u5c40\u6700\u4f18</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#52","title":"5.2 \u7279\u5f81\u9009\u62e9","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#521","title":"5.2.1 \u7279\u5f81\u9009\u62e9\u95ee\u9898","text":"<ul> <li>\u901a\u5e38\u7279\u5f81\u9009\u62e9\u7684\u51c6\u5219\u662f\u4fe1\u606f\u589e\u76ca\u6216\u4fe1\u606f\u589e\u76ca\u6bd4</li> <li>information gain</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#522","title":"5.2.2 \u4fe1\u606f\u589e\u76ca","text":"<ul> <li>\u71b5\u548c\u6761\u4ef6\u71b5</li> </ul> \\[ P(X=x_{i})=p_{i} ,\\quad i=1,2,\\cdots,n \\] \\[ H(X)=-\\sum_{i=1}^{n}p_{i}\\log p_{i} \\] \\[ H(p)=-\\sum_{i=1}^{n}p_{i}\\log p_{i} \\] \\[ 0\\leqslant H(p)\\leqslant\\log n \\] \\[ P(X=x_{i},Y=y_{j})=p_{ij} ,\\quad i=1,2,\\cdots,n ;\\quad j=1,2,\\cdots,m \\] \\[ H(Y\\mid X)=\\sum_{i=1}^{n}p_{i}H(Y\\mid X=x_{i}) \\] <ul> <li>mutual information </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#523","title":"5.2.3 \u4fe1\u606f\u589e\u76ca\u6bd4","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#53","title":"5.3 \u51b3\u7b56\u6811\u7684\u751f\u6210","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#531-id-3","title":"5.3.1 ID 3 \u7b97\u6cd5","text":"<ul> <li>ID 3 \u7b97\u6cd5\u53ea\u6709\u6811\u7684\u751f\u6210\uff0c\u6240\u4ee5\u8be5\u7b97\u6cd5\u751f\u6210\u7684\u6811\u5bb9\u6613\u4ea7\u751f\u8fc7\u62df\u5408</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#532-c-45","title":"5.3.2 C 4.5 \u7684\u751f\u6210\u7b97\u6cd5","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#54","title":"5.4 \u51b3\u7b56\u6811\u7684\u526a\u679d","text":"<ul> <li>pruning</li> </ul> \\[ C_{\\alpha}(T)=\\sum_{t=1}^{|T|}N_{t}H_{t}(T)+\\alpha|T| \\] \\[ H_{t}(T)=-\\sum_{k}\\frac{N_{ik}}{N_{t}}\\log\\frac{N_{ik}}{N_{t}} \\] \\[ C(T)=\\sum_{t=1}^{|T|}N_{t}H_{t}(T)=-\\sum_{t=1}^{|T|}\\sum_{k=1}^{K}N_{tk}\\log\\frac{N_{tk}}{N_{t}} \\] \\[ C_{\\alpha}(T)=C(T)+\\alpha|T| \\]"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#55-cart","title":"5.5 CART \u7b97\u6cd5","text":"<ul> <li>\u5206\u88c2\u4e0e\u56de\u5f52\u6811\uff08classification and regression tree\uff09</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#551-cart","title":"5.5.1 CART \u751f\u6210","text":"<ul> <li>\u5bf9\u56de\u5f52\u6811\u7528\u5e73\u65b9\u8bef\u5dee\u6700\u5c0f\u5316\u51c6\u5219</li> <li>\u5bf9\u5206\u7c7b\u6811\u7528\u57fa\u5c3c\u6307\u6570\uff08Gini index\uff09\u6700\u5c0f\u5316\u51c6\u5219 1. \u56de\u5f52\u6811\u7684\u751f\u6210</li> </ul> \\[ f(x)=\\sum_{m=1}^{M}c_{m}I(x\\in R_{m}) \\] \\[ \\hat{c}_{m}=\\mathrm{ave}(y_{i}\\mid x_{i}\\in R_{m}) \\] <ul> <li>splitting variable </li> <li>splitting point</li> </ul> \\[ R_{1}(j,s)=\\{x\\mid x^{(j)}\\leqslant s\\}\\quad\\text{\u548c}\\quad R_{2}(j,s)=\\{x\\mid x^{(j)}&gt;s\\} \\] \\[ \\min_{j,s}\\biggl[\\min_{c_{1}}\\sum_{x_{i}\\in R_{i}(j,s)}(y_{i}-c_{1})^{2}+\\min_{c_{2}}\\sum_{x_{i}\\in R_{2}(j,s)}(y_{i}-c_{2})^{2}\\biggr] \\] \\[ \\hat{c}_{1}=\\mathrm{ave}(y_{i}\\mid x_{i}\\in R_{1}(j,s))\\quad\\hat{\\text{\u548c}}\\quad\\hat{c}_{2}=\\mathrm{ave}(y_{i}\\mid x_{i}\\in R_{2}(j,s)) \\] <ul> <li>least squares regression tree  1. \u5206\u7c7b\u6811\u7684\u751f\u6210 </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#552-cart","title":"5.5.2 CART \u526a\u679d","text":"<ol> <li>\u526a\u679d\uff0c\u5f62\u6210\u4e00\u4e2a\u5b50\u6811\u5e8f\u5217</li> </ol> \\[ C_{\\alpha}(T)=C(T)+\\alpha\\left|T\\right| \\] \\[ g(t)=\\frac{C(t)-C(T_{t})}{\\mid T_{t}\\mid-1} \\] <ol> <li>\u5728\u526a\u679d\u5f97\u5230\u7684\u5b50\u6811\u5e8f\u5217 \\(\\displaystyle T_0,T_1,\\cdots,T_n\\) \u4e2d\u901a\u8fc7\u4ea4\u53c9\u9a8c\u8bc1\u9009\u53d6\u6700\u4f18\u5b50\u6811 \\(\\displaystyle T_{\\alpha}\\) </li> </ol>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#6","title":"6 \u903b\u8f91\u65af\u8c1b\u56de\u5f52\u4e0e\u6700\u5927\u71b5\u6a21\u578b","text":"<ul> <li>logistic regression</li> <li>maximum entropy model</li> <li>\u903b\u8f91\u65af\u8c1b\u56de\u5f52\u6a21\u578b\u548c\u6700\u5927\u71b5\u6a21\u578b\u90fd\u5c5e\u4e8e\u5bf9\u6570\u7ebf\u6027\u6a21\u578b</li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#61","title":"6.1 \u903b\u8f91\u65af\u8c1b\u56de\u5f52\u6a21\u578b","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#611","title":"6.1.1 \u903b\u8f91\u65af\u8c1b\u5206\u5e03","text":"<ul> <li>logistic distribution </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#612","title":"6.1.2 \u4e8c\u9879\u903b\u8f91\u65af\u8c1b\u56de\u5f52\u6a21\u578b","text":"<ul> <li>binomial logistic regression model </li> </ul>"},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#7","title":"7 \u652f\u6301\u5411\u91cf\u673a","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#8","title":"8 \u63d0\u5347\u65b9\u6cd5","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#9-displaystyle-boldsymbolem","title":"9 \\(\\displaystyle \\boldsymbol{EM}\\) \u7b97\u6cd5\u53ca\u5176\u63a8\u5e7f","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#10","title":"10 \u9690\u9a6c\u5c14\u53ef\u592b\u6a21\u578b","text":""},{"location":"AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/#11_1","title":"11 \u6761\u4ef6\u968f\u673a\u573a","text":""},{"location":"AI/CS231n/CS231n_notes/","title":"Computer Vision","text":""},{"location":"AI/CS231n/CS231n_notes/#computer-vision","title":"Computer Vision","text":"<p> \u7ea6 8852 \u4e2a\u5b57  167 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 44 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>This note is based on GitHub - DaizeDong/Stanford-CS231n-2021-and-2022: Notes and slides for Stanford CS231n 2021 &amp; 2022 in English. I merged the contents together to get a better version. Assignments are not included. \u65af\u5766\u798fcs231n\u7684\u8bfe\u7a0b\u7b14\u8bb0(\u82f1\u6587\u7248\u672c\uff0c\u4e0d\u542b\u5b9e\u9a8c\u4ee3\u7801)\uff0c\u5c062021\u4e0e2022\u4e24\u5e74\u7684\u8bfe\u7a0b\u8fdb\u884c\u4e86\u5408\u5e76\uff0c\u5206\u4eab\u4ee5\u4f9b\u4ea4\u6d41\u3002 And I will add some blogs, articles and other understanding.</p> Topic Chapter Deep Learning Basics 2 - 4 Perceiving and Understanding the Visual World 5 - 12 Reconstructing and Interacting with the Visual World 13 - 16 Human-Centered Applications and Implications 17 - 18"},{"location":"AI/CS231n/CS231n_notes/#1-introduction","title":"1 - Introduction","text":"<p>A brief history of computer vision &amp; deep learning...</p>"},{"location":"AI/CS231n/CS231n_notes/#2-image-classification","title":"2 - Image Classification","text":"<p>Image Classification: A core task in Computer Vision. The main drive to the progress of CV.</p> <p>Challenges: Viewpoint variation, background clutter, illumination, occlusion, deformation, intra-class variation...</p>"},{"location":"AI/CS231n/CS231n_notes/#k-nearest-neighbor","title":"K Nearest Neighbor","text":"<p>Hyperparameters: Distance metric (\\(p\\) norm), \\(k\\) number.</p> <p>Choose hyperparameters using validation set.</p> <p>Never use k-Nearest Neighbor with pixel distance.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#linear-classifier","title":"Linear Classifier","text":"<p>Pass...</p>"},{"location":"AI/CS231n/CS231n_notes/#3-loss-functions-and-optimization","title":"3 - Loss Functions and Optimization","text":""},{"location":"AI/CS231n/CS231n_notes/#loss-functions","title":"Loss Functions","text":"Dataset \\(\\big\\{(x_i,y_i)\\big\\}_{i=1}^N\\\\\\) Loss Function \\(L=\\frac{1}{N}\\sum_{i=1}^NL_i\\big(f(x_i,W),y_i\\big)\\\\\\) Loss Function with Regularization \\(L=\\frac{1}{N}\\sum_{i=1}^NL_i\\big(f(x_i,W),y_i\\big)+\\lambda R(W)\\\\\\) <p>Motivation: Want to interpret raw classifier scores as probabilities.</p> Softmax Classifier \\(p_i=Softmax(y_i)=\\frac{\\exp(y_i)}{\\sum_{j=1}^N\\exp(y_j)}\\\\\\) Cross Entropy Loss \\(L_i=-y_i\\log p_i\\\\\\) Cross Entropy Loss with Regularization \\(L=-\\frac{1}{N}\\sum_{i=1}^Ny_i\\log p_i+\\lambda R(W)\\\\\\) <p></p>"},{"location":"AI/CS231n/CS231n_notes/#optimization","title":"Optimization","text":""},{"location":"AI/CS231n/CS231n_notes/#sgd-with-momentum","title":"SGD with Momentum","text":"<p>Problems that SGD can't handle:</p> <ol> <li>Inequality of gradient in different directions.</li> <li>Local minima and saddle point (much more common in high dimension).</li> <li>Noise of gradient from mini-batch.</li> </ol> <p>Momentum: Build up \u201cvelocity\u201d \\(v_t\\) as a running mean of gradients.</p> SGD SGD + Momentum \\(x_{t+1}=x_t-\\alpha\\nabla f(x_t)\\) \\(\\begin{align}&amp;v_{t+1}=\\rho v_t+\\nabla f(x_t)\\\\&amp;x_{t+1}=x_t-\\alpha v_{t+1}\\end{align}\\) Naive gradient descent. \\(\\rho\\) gives \"friction\", typically \\(\\rho=0.9,0.99,0.999,...\\) <p>Nesterov Momentum: Use the derivative on point \\(x_t+\\rho v_t\\) as gradient instead point \\(x_t\\).</p> Momentum Nesterov Momentum \\(\\begin{align}&amp;v_{t+1}=\\rho v_t+\\nabla f(x_t)\\\\&amp;x_{t+1}=x_t-\\alpha v_{t+1}\\end{align}\\) \\(\\begin{align}&amp;v_{t+1}=\\rho v_t+\\nabla f(x_t+\\rho v_t)\\\\&amp;x_{t+1}=x_t-\\alpha v_{t+1}\\end{align}\\) Use gradient at current point. Look ahead for the gradient in velocity direction. <p></p>"},{"location":"AI/CS231n/CS231n_notes/#adagrad-and-rmsprop","title":"AdaGrad and RMSProp","text":"<p>AdaGrad: Accumulate squared gradient, and gradually decrease the step size.</p> <p>RMSProp: Accumulate squared gradient while decaying former ones, and gradually decrease the step size. (\"Leaky AdaGrad\")</p> AdaGrad RMSProp \\(\\begin{align}\\text{Initialize:}&amp;\\\\&amp;r:=0\\\\\\text{Update:}&amp;\\\\&amp;r:=r+\\Big[\\nabla f(x_t)\\Big]^2\\\\&amp;x_{t+1}=x_t-\\alpha\\frac{\\nabla f(x_t)}{\\sqrt{r}}\\end{align}\\) \\(\\begin{align}\\text{Initialize:}&amp;\\\\&amp;r:=0\\\\\\text{Update:}&amp;\\\\&amp;r:=\\rho r+(1-\\rho)\\Big[\\nabla f(x_t)\\Big]^2\\\\&amp;x_{t+1}=x_t-\\alpha\\frac{\\nabla f(x_t)}{\\sqrt{r}}\\end{align}\\) Continually accumulate squared gradients. \\(\\rho\\) gives \"decay rate\", typically \\(\\rho=0.9,0.99,0.999,...\\)"},{"location":"AI/CS231n/CS231n_notes/#adam","title":"Adam","text":"<p>Sort of like \"RMSProp + Momentum\".</p> Adam (simple version) Adam (full version) \\(\\begin{align}\\text{Initialize:}&amp;\\\\&amp;r_1:=0\\\\&amp;r_2:=0\\\\\\text{Update:}&amp;\\\\&amp;r_1:=\\beta_1r_1+(1-\\beta_1)\\nabla f(x_t)\\\\&amp;r_2:=\\beta_2r_2+(1-\\beta_2)\\Big[\\nabla f(x_t)\\Big]^2\\\\&amp;x_{t+1}=x_t-\\alpha\\frac{r_1}{\\sqrt{r_2}}\\end{align}\\) \\(\\begin{align}\\text{Initialize:}\\\\&amp;r_1:=0\\\\&amp;r_2:=0\\\\\\text{For }i\\text{:}\\\\&amp;r_1:=\\beta_1r_1+(1-\\beta_1)\\nabla f(x_t)\\\\&amp;r_2:=\\beta_2r_2+(1-\\beta_2)\\Big[\\nabla f(x_t)\\Big]^2\\\\&amp;r_1'=\\frac{r_1}{1-\\beta_1^i}\\\\&amp;r_2'=\\frac{r_2}{1-\\beta_2^i}\\\\&amp;x_{t+1}=x_t-\\alpha\\frac{r_1'}{\\sqrt{r_2'}}\\end{align}\\) Build up \u201cvelocity\u201d for both gradient and squared gradient. Correct the \"bias\" that \\(r_1=r_2=0\\) for the first few iterations."},{"location":"AI/CS231n/CS231n_notes/#overview","title":"Overview","text":""},{"location":"AI/CS231n/CS231n_notes/#learning-rate-decay","title":"Learning Rate Decay","text":"<p>Reduce learning rate at a few fixed points to get a better convergence over time.</p> <p>\\(\\alpha_0\\) : Initial learning rate.</p> <p>\\(\\alpha_t\\) : Learning rate in epoch \\(t\\).</p> <p>\\(T\\) : Total number of epochs.</p> Method Equation Picture Step Reduce \\(\\alpha_t\\) constantly  in a fixed step. Cosine \\(\\begin{align}\\alpha_t=\\frac{1}{2}\\alpha_0\\Bigg[1+\\cos(\\frac{t\\pi}{T})\\Bigg]\\end{align}\\) Linear \\(\\begin{align}\\alpha_t=\\alpha_0\\Big(1-\\frac{t}{T}\\Big)\\end{align}\\) Inverse Sqrt \\(\\begin{align}\\alpha_t=\\frac{\\alpha_0}{\\sqrt{t}}\\end{align}\\) <p>High initial learning rates can make loss explode, linearly increasing learning rate in the first few iterations can prevent this.</p> <p>Learning rate warm up:</p> <p></p> <p>Empirical rule of thumb: If you increase the batch size by \\(N\\), also scale the initial learning rate by \\(N\\) .</p>"},{"location":"AI/CS231n/CS231n_notes/#second-order-optimization","title":"Second-Order Optimization","text":"Picture Time Complexity Space Complexity First Order \\(O(n)\\) \\(O(n)\\) Second Order \\(O(n^2)\\) with BGFS optimization \\(O(n)\\) with L-BGFS optimization <p>L-BGFS : Limited memory BGFS.</p> <ol> <li>Works very well in full batch, deterministic \\(f(x)\\).</li> <li>Does not transfer very well to mini-batch setting.</li> </ol>"},{"location":"AI/CS231n/CS231n_notes/#summary","title":"Summary","text":"Method Performance Adam Often chosen as default method.Work ok even with constant learning rate. SGD + Momentum Can outperform Adam.Require more tuning of learning rate and schedule. L-BGFS If can afford to do full batch updates then try out. <ul> <li>An article about gradient descent: Anoverview of gradient descent optimization algorithms</li> <li>A blog: An updated overview of recent gradient descent algorithms \u2013 John Chen \u2013 ML at Rice University</li> </ul>"},{"location":"AI/CS231n/CS231n_notes/#4-neural-networks-and-backpropagation","title":"4 - Neural Networks and Backpropagation","text":""},{"location":"AI/CS231n/CS231n_notes/#neural-networks","title":"Neural Networks","text":"<p>Motivation: Inducted bias can appear to be high when using human-designed features.</p> <p>Activation: Sigmoid, tanh, ReLU, LeakyReLU...</p> <p>Architecture: Input layer, hidden layer, output layer.</p> <p>Do not use the size of a neural network as the regularizer. Use regularization instead!</p> <p>Gradient Calculation: Computational Graph + Backpropagation.</p>"},{"location":"AI/CS231n/CS231n_notes/#backpropagation","title":"Backpropagation","text":"<p>Using Jacobian matrix to calculate the gradient of each node in a computation graph.</p> <p>Suppose that we have a computation flow like this:</p> <p></p> Input X Input W Output Y \\(X=\\begin{bmatrix}x_1\\\\x_2\\\\\\vdots\\\\x_n\\end{bmatrix}\\) \\(W=\\begin{bmatrix}w_{11}&amp;w_{12}&amp;\\cdots&amp;w_{1n}\\\\w_{21}&amp;w_{22}&amp;\\cdots&amp;w_{2n}\\\\\\vdots&amp;\\vdots&amp;\\ddots&amp;\\vdots\\\\w_{m1}&amp;w_{m2}&amp;\\cdots&amp;w_{mn}\\end{bmatrix}\\) \\(Y=\\begin{bmatrix}y_1\\\\y_2\\\\\\vdots\\\\y_m\\end{bmatrix}\\) \\(n\\times 1\\) \\(m\\times n\\) \\(m\\times 1\\) <p>After applying feed forward, we can calculate gradients like this:</p> <p></p> Derivative Matrix of X Jacobian Matrix of X Derivative Matrix of Y \\(D_X=\\begin{bmatrix}\\frac{\\partial L}{\\partial x_1}\\\\\\frac{\\partial L}{\\partial x_2}\\\\\\vdots\\\\\\frac{\\partial L}{\\partial x_n}\\end{bmatrix}\\) \\(J_X=\\begin{bmatrix}\\frac{\\partial y_1}{\\partial x_1}&amp;\\frac{\\partial y_1}{\\partial x_2}&amp;\\cdots&amp;\\frac{\\partial y_1}{\\partial x_n}\\\\\\frac{\\partial y_2}{\\partial x_1}&amp;\\frac{\\partial y_2}{\\partial x_2}&amp;\\cdots&amp;\\frac{\\partial y_2}{\\partial x_n}\\\\\\vdots&amp;\\vdots&amp;\\ddots&amp;\\vdots\\\\\\frac{\\partial y_m}{\\partial x_1}&amp;\\frac{\\partial y_m}{\\partial x_2}&amp;\\cdots&amp;\\frac{\\partial y_m}{\\partial x_n}\\end{bmatrix}\\) \\(D_Y=\\begin{bmatrix}\\frac{\\partial L}{\\partial y_1}\\\\\\frac{\\partial L}{\\partial y_2}\\\\\\vdots\\\\\\frac{\\partial L}{\\partial y_m}\\end{bmatrix}\\) \\(n\\times 1\\) \\(m\\times n\\) \\(m\\times 1\\) Derivative Matrix of W Jacobian Matrix of W Derivative Matrix of Y \\(W=\\begin{bmatrix}\\frac{\\partial L}{\\partial w_{11}}&amp;\\frac{\\partial L}{\\partial w_{12}}&amp;\\cdots&amp;\\frac{\\partial L}{\\partial w_{1n}}\\\\\\frac{\\partial L}{\\partial w_{21}}&amp;\\frac{\\partial L}{\\partial w_{22}}&amp;\\cdots&amp;\\frac{\\partial L}{\\partial w_{2n}}\\\\\\vdots&amp;\\vdots&amp;\\ddots&amp;\\vdots\\\\\\frac{\\partial L}{\\partial w_{m1}}&amp;\\frac{\\partial L}{\\partial w_{m2}}&amp;\\cdots&amp;\\frac{\\partial L}{\\partial w_{mn}}\\end{bmatrix}\\) \\(J_W^{(k)}=\\begin{bmatrix}\\frac{\\partial y_k}{\\partial w_{11}}&amp;\\frac{\\partial y_k}{\\partial w_{12}}&amp;\\cdots&amp;\\frac{\\partial y_k}{\\partial w_{1n}}\\\\\\frac{\\partial y_k}{\\partial w_{21}}&amp;\\frac{\\partial y_k}{\\partial w_{22}}&amp;\\cdots&amp;\\frac{\\partial y_k}{\\partial w_{2n}}\\\\\\vdots&amp;\\vdots&amp;\\ddots&amp;\\vdots\\\\\\frac{\\partial y_k}{\\partial w_{m1}}&amp;\\frac{\\partial y_k}{\\partial w_{m2}}&amp;\\cdots&amp;\\frac{\\partial y_k}{\\partial w_{mn}}\\end{bmatrix}\\)\\(J_W=\\begin{bmatrix}J_W^{(1)}&amp;J_W^{(2)}&amp;\\cdots&amp;J_W^{(m)}\\end{bmatrix}\\) \\(D_Y=\\begin{bmatrix}\\frac{\\partial L}{\\partial y_1}\\\\\\frac{\\partial L}{\\partial y_2}\\\\\\vdots\\\\\\frac{\\partial L}{\\partial y_m}\\end{bmatrix}\\) \\(m\\times n\\) \\(m\\times m\\times n\\) $ m\\times 1$ <p>For each element in \\(D_X\\) , we have:</p> <p>\\(D_{Xi}=\\frac{\\partial L}{\\partial x_i}=\\sum_{j=1}^m\\frac{\\partial L}{\\partial y_j}\\frac{\\partial y_j}{\\partial x_i}\\\\\\)</p>"},{"location":"AI/CS231n/CS231n_notes/#5-convolutional-neural-networks","title":"5 - Convolutional Neural Networks","text":""},{"location":"AI/CS231n/CS231n_notes/#convolution-layer","title":"Convolution Layer","text":""},{"location":"AI/CS231n/CS231n_notes/#introduction","title":"Introduction","text":"<p>Convolve a filter with an image: Slide the filter spatially within the image, computing dot products in each region.</p> <p>Giving a \\(32\\times32\\times3\\) image and a \\(5\\times5\\times3\\) filter, a convolution looks like:</p> <p></p> <p>Convolve six \\(5\\times5\\times3\\) filters to a \\(32\\times32\\times3\\) image with step size \\(1\\), we can get a \\(28\\times28\\times6\\) feature:</p> <p></p> <p>With an activation function after each convolution layer, we can build the ConvNet with a sequence of convolution layers:</p> <p></p> <p>By changing the step size between each move for filters, or adding zero-padding around the image, we can modify the size of the output:</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#1times1-convolution-layer","title":"\\(1\\times1\\) Convolution Layer","text":"<p>This kind of layer makes perfect sense. It is usually used to change the dimension (channel) of features.</p> <p>A \\(1\\times1\\) convolution layer can also be treated as a full-connected linear layer.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#summary_1","title":"Summary","text":"Input image size \\(W_1\\times H_1\\times C\\) filter size \\(F\\times F\\times C\\) filter number \\(K\\) stride \\(S\\) zero padding \\(P\\) Output output size \\(W_2\\times H_2\\times K\\) output width \\(W_2=\\frac{W_1-F+2P}{S}+1\\\\\\) output height \\(H_2=\\frac{H_1-F+2P}{S}+1\\\\\\) Parameters parameter number (weight) \\(F^2CK\\) parameter number (bias) \\(K\\)"},{"location":"AI/CS231n/CS231n_notes/#pooling-layer","title":"Pooling layer","text":"<p>Make the representations smaller and more manageable.</p> <p>An example of max pooling:</p> <p></p> Input image size \\(W_1\\times H_1\\times C\\) spatial extent \\(F\\times F\\) stride \\(S\\) Output output size \\(W_2\\times H_2\\times C\\) output width \\(W_2=\\frac{W_1-F}{S}+1\\\\\\) output height \\(H_2=\\frac{H_1-F}{S}+1\\\\\\)"},{"location":"AI/CS231n/CS231n_notes/#convolutional-neural-networks-cnn","title":"Convolutional Neural Networks (CNN)","text":"<p>CNN stack CONV, POOL, FC layers.</p> <p>CNN Trends:</p> <ol> <li>Smaller filters and deeper architectures.</li> <li>Getting rid of POOL/FC layers (just CONV).</li> </ol> <p>Historically architectures of CNN looked like:</p> <p></p> <p>where usually \\(m\\) is large, \\(0\\le n\\le5\\), \\(0\\le k\\le2\\).</p> <p>Recent advances such as ResNet / GoogLeNet have challenged this paradigm.</p>"},{"location":"AI/CS231n/CS231n_notes/#6-cnn-architectures","title":"6 - CNN Architectures","text":"<p>Best model in ImageNet competition:</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#alexnet","title":"AlexNet","text":"<p>8 layers.</p> <p>First use of ConvNet in image classification problem.</p> <p>Filter size decreases in deeper layer.</p> <p>Channel number increases in deeper layer.</p> <p></p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#vgg","title":"VGG","text":"<p>19 layers. (also provide 16 layers edition)</p> <p>Static filter size (\\(3\\times3\\)) in all layers:</p> <ol> <li>The effective receptive field expands with the layer gets deeper.</li> <li>Deeper architecture gets more non-linearities and few parameters.</li> </ol> <p></p> <p>Most memory is in early convolution layers.</p> <p>Most parameter is in late FC layers.</p> <p></p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#googlenet","title":"GoogLeNet","text":"<p>22 layers.</p> <p>No FC layers, only 5M parameters. ( \\(8.3\\%\\) of AlexNet, \\(3.7\\%\\) of VGG )</p> <p>Devise efficient \"inception module\".</p>"},{"location":"AI/CS231n/CS231n_notes/#inception-module","title":"Inception Module","text":"<p>Design a good local network topology (network within a network) and then stack these modules on top of each other.</p> <p>Naive Inception Module:</p> <ol> <li>Apply parallel filter operations on the input from previous layer.</li> <li>Concatenate all filter outputs together channel-wise.</li> <li>Problem: The depth (channel number) increases too fast, costing expensive computation.</li> </ol> <p></p> <p>Inception Module with Dimension Reduction:</p> <ol> <li>Add \"bottle neck\" layers to reduce the dimension.</li> <li>Also get fewer computation cost.</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#architecture","title":"Architecture","text":""},{"location":"AI/CS231n/CS231n_notes/#resnet","title":"ResNet","text":"<p>152 layers for ImageNet.</p> <p>Devise \"residual connections\".</p> <p>Use BN in place of dropout.</p>"},{"location":"AI/CS231n/CS231n_notes/#residual-connections","title":"Residual Connections","text":"<p>Hypothesis: Deeper models have more representation power than shallow ones. But they are harder to optimize.</p> <p>Solution: Use network layers to fit a residual mapping instead of directly trying to fit a desired underlying mapping.</p> <p></p> <p>It is necessary to use ReLU as activation function, in order to apply identity mapping when \\(F(x)=0\\) .</p>"},{"location":"AI/CS231n/CS231n_notes/#architecture_1","title":"Architecture","text":""},{"location":"AI/CS231n/CS231n_notes/#senet","title":"SENet","text":"<p>Using ResNeXt-152 as a base architecture.</p> <p>Add a \u201cfeature recalibration\u201d module. (adjust weights of each channel)</p> <p>Using the global avg-pooling layer + FC layers to determine feature map weights.</p> <p></p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#improvements-of-resnet","title":"Improvements of ResNet","text":"<p>Wide Residual Networks, ResNeXt, DenseNet, MobileNets...</p>"},{"location":"AI/CS231n/CS231n_notes/#other-interesting-networks","title":"Other Interesting Networks","text":"<p>NASNet: Neural Architecture Search with Reinforcement Learning.</p> <p>EfficientNet: Smart Compound Scaling.</p>"},{"location":"AI/CS231n/CS231n_notes/#7-training-neural-networks","title":"7 - Training Neural Networks","text":""},{"location":"AI/CS231n/CS231n_notes/#activation-functions","title":"Activation Functions","text":"Activation Usage Sigmoid, tanh Do not use. ReLU Use as default. Leaky ReLU, Maxout, ELU, SELU Replace ReLU to squeeze out some marginal gains. Swish No clear usage."},{"location":"AI/CS231n/CS231n_notes/#data-processing","title":"Data Processing","text":"<p>Apply centralization and normalization before training.</p> <p>In practice for pictures, usually we apply channel-wise centralization only.</p>"},{"location":"AI/CS231n/CS231n_notes/#weight-initialization","title":"Weight Initialization","text":"<p>Assume that we have 6 layers in a network.</p> <p>\\(D_i\\) : input size of layer \\(i\\)</p> <p>\\(W_i\\) : weights in layer \\(i\\)</p> <p>\\(X_i\\) : output after activation of layer \\(i\\), we have \\(X_i=g(Z_i)=g(W_iX_{i-1}+B_i)\\)</p> <p>We initialize each parameter in \\(W_i\\) randomly in \\([-k_i,k_i]\\) .</p> Tanh Activation Output Distribution \\(k_i=0.01\\) \\(k_i=0.05\\) Xavier Initialization \\(k_i=\\frac{1}{\\sqrt{D_i}\\\\}\\) <p>When \\(k_i=0.01\\), the variance keeps decreasing as the layer gets deeper. As a result, the output of each neuron in deep layer will all be 0. The partial derivative \\(\\frac{\\partial Z_i}{\\partial W_i}=X_{i-1}=0\\\\\\). (no gradient)</p> <p>When \\(k_i=0.05\\), most neurons is saturated. The partial derivative \\(\\frac{\\partial X_i}{\\partial Z_i}=g'(Z_i)=0\\\\\\). (no gradient)</p> <p>To solve this problem, We need to keep the variance same in each layer.</p> <p>Assuming that \\(Var\\big(X_{i-1}^{(1)}\\big)=Var\\big(X_{i-1}^{(2)}\\big)=\\dots=Var\\big(X_{i-1}^{(D_i)}\\big)\\)</p> <p>We have \\(Z_i=X_{i-1}^{(1)}W_i^{(:,1)}+X_{i-1}^{(2)}W_i^{(:,2)}+\\dots+X_{i-1}^{(D_i)}W_i^{(:,D_i)}=\\sum_{n=1}^{D_i}X_{i-1}^{(n)}W_i^{(:,n)}\\\\\\)</p> <p>We want \\(Var\\big(Z_i\\big)=Var\\big(X_{i-1}^{(n)}\\big)\\)</p> <p>Let's do some conduction:</p> <p>\\(\\begin{aligned}Var\\big(Z_i\\big)&amp;=Var\\Bigg(\\sum_{n=1}^{D_i}X_{i-1}^{(n)}W_i^{(:,n)}\\Bigg)\\\\&amp;=D_i\\ Var\\Big(X_{i-1}^{(n)}W_i^{(:,n)}\\Big)\\\\&amp;=D_i\\ Var\\Big(X_{i-1}^{(n)}\\Big)\\ Var\\Big(W_i^{(:,n)}\\Big)\\end{aligned}\\)</p> <p>So \\(Var\\big(Z_i\\big)=Var\\big(X_{i-1}^{(n)}\\big)\\) only when \\(Var\\Big(W_i^{(:,n)}\\Big)=\\frac{1}{D_i}\\\\\\), that is to say \\(k_i=\\frac{1}{\\sqrt{D_i}}\\\\\\)</p> ReLU Activation Output Distribution Xavier Initialization \\(k_i=\\frac{1}{\\sqrt{D_i}\\\\}\\) Kaiming Initialization \\(k_i=\\sqrt{2D_i}\\) <p>For ReLU activation, when using xavier initialization, there still exist \"variance decreasing\" problem.</p> <p>We can use kaiming initialization instead to fix this.</p>"},{"location":"AI/CS231n/CS231n_notes/#batch-normalization","title":"Batch Normalization","text":"<p>Force the inputs to be \"nicely scaled\" at each layer.</p> <p>\\(N\\) : batch size</p> <p>\\(D\\) : feature size</p> <p>\\(x\\) : input with shape \\(N\\times D\\) </p> <p>\\(\\gamma\\) : learnable scale and shift parameter with shape \\(D\\)</p> <p>\\(\\beta\\) : learnable scale and shift parameter with shape \\(D\\)</p> <p>The procedure of batch normalization:</p> <ol> <li>Calculate channel-wise mean \\(\\mu_j=\\frac{1}{N}\\sum_{i=1}^Nx_{i,j}\\\\\\) . The result \\(\\mu\\) with shape \\(D\\) .</li> <li>Calculate channel-wise variance \\(\\sigma_j^2=\\frac{1}{N}\\sum_{i=1}^N(x_{i,j}-\\mu_j)^2\\\\\\) . The result \\(\\sigma^2\\) with shape \\(D\\) .</li> <li>Calculate normalized \\(\\hat{x}_{i,j}=\\frac{x_{i,j}-\\mu_j}{\\sqrt{\\sigma_j^2+\\epsilon}}\\\\\\) . The result \\(\\hat{x}\\) with shape \\(N\\times D\\) .</li> <li>Scale normalized input to get output \\(y_{i,j}=\\gamma_j\\hat{x}_{i,j}+\\beta_j\\) . The result \\(y\\) with shape \\(N\\times D\\) .</li> </ol> <p>Why scale: The constraint \"zero-mean, unit variance\" may be too hard.</p> <p></p> <p>Pros:</p> <ol> <li>Makes deep networks much easier to train!</li> <li>Improves gradient flow.</li> <li>Allows higher learning rates, faster convergence.</li> <li>Networks become more robust to initialization.</li> <li>Acts as regularization during training.</li> <li>Zero overhead at test-time: can be fused with conv!</li> </ol> <p>Cons:</p> <p>Behaves differently during training and testing: this is a very common source of bugs!</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#transfer-learning","title":"Transfer Learning","text":"<p>Train on a pre-trained model with other datasets.</p> <p>An empirical suggestion:</p> very similar  dataset very different  dataset very little data Use Linear Classifier on top layer. You\u2019re in trouble\u2026 Try linear classifier from different stages. quite a lot of data Finetune a few layers. Finetune a larger number of layers."},{"location":"AI/CS231n/CS231n_notes/#regularization","title":"Regularization","text":""},{"location":"AI/CS231n/CS231n_notes/#common-pattern-of-regularization","title":"Common Pattern of Regularization","text":"<p>Training: Add some kind of randomness. \\(y=f(x,z)\\)</p> <p>Testing: Average out randomness (sometimes approximate). \\(y=f(x)=E_z\\big[f(x,z)\\big]=\\int p(z)f(x,z)dz\\\\\\)</p>"},{"location":"AI/CS231n/CS231n_notes/#regularization-term","title":"Regularization Term","text":"<p>L2 regularization: \\(R(W)=\\sum_k\\sum_lW_{k,l}^2\\) (weight decay)</p> <p>L1 regularization: \\(R(W)=\\sum_k\\sum_l|W_{k,l}|\\)</p> <p>Elastic net : \\(R(W)=\\sum_k\\sum_l\\big(\\beta W_{k,l}^2+|W_{k,l}|\\big)\\) (L1+L2)</p>"},{"location":"AI/CS231n/CS231n_notes/#dropout","title":"Dropout","text":"<p>Training: Randomly set some neurons to 0 with a probability \\(p\\) .</p> <p>Testing: Each neuron multiplies by dropout probability \\(p\\) . (scale the output back)</p> <p>More common: Scale the output with \\(\\frac{1}{p}\\) when training, keep the original output when testing.</p> <p></p> <p>Why dropout works:</p> <ol> <li>Forces the network to have a redundant representation. Prevents co-adaptation of features.</li> <li>Another interpretation: Dropout is training a large ensemble of models (that share parameters).</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#batch-normalization_1","title":"Batch Normalization","text":"<p>See above.</p>"},{"location":"AI/CS231n/CS231n_notes/#data-augmentation","title":"Data Augmentation","text":"<ol> <li>Horizontal Flips</li> <li>Random Crops and Scales</li> <li>Color Jitter</li> <li>Rotation</li> <li>Stretching</li> <li>Shearing</li> <li>Lens Distortions</li> <li>...</li> </ol> <p>There also exists automatic data augmentation method using neural networks.</p>"},{"location":"AI/CS231n/CS231n_notes/#other-methods-and-summary","title":"Other Methods and Summary","text":"<p>DropConnect: Drop connections between neurons.</p> <p>Fractional Max Pooling: Use randomized pooling regions.</p> <p>Stochastic Depth: Skip some layers in the network.</p> <p>Cutout: Set random image regions to zero.</p> <p>Mixup: Train on random blends of images.</p> Regularization Method Usage Dropout For large fully-connected layers. Batch Normalization &amp; Data Augmentation Almost always a good idea. Cutout &amp; Mixup For small classification datasets."},{"location":"AI/CS231n/CS231n_notes/#hyperparameter-tuning","title":"Hyperparameter Tuning","text":"Most Common Hyperparameters Less Sensitive Hyperparameters learning ratelearning rate decay scheduleweight decay setting of momentum... <p>Tips on hyperparameter tuning:</p> <ol> <li>Prefer one validation fold to cross-validation.</li> <li>Search for hyperparameters on log scale. (e.g. multiply the hyperparameter by a fixed number \\(k\\) at each search)</li> <li>Prefer random search to grid search.</li> <li>Careful with best values on border.</li> <li>Stage your search from coarse to fine.</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#implementation","title":"Implementation","text":"<p>Have a worker that continuously samples random hyperparameters and performs the optimization. During the training, the worker will keep track of the validation performance after every epoch, and writes a model checkpoint to a file.</p> <p>Have a master that launches or kills workers across a computing cluster, and may additionally inspect the checkpoints written by workers and plot their training statistics.</p>"},{"location":"AI/CS231n/CS231n_notes/#common-procedures","title":"Common Procedures","text":"<ol> <li>Check initial loss.</li> </ol> <p>Turn off weight decay, sanity check loss at initialization \\(\\log(C)\\) for softmax with \\(C\\) classes.</p> <ol> <li>Overfit a small sample. (important)</li> </ol> <p>Try to train to 100% training accuracy on a small sample of training data.</p> <p>Fiddle with architecture, learning rate, weight initialization.</p> <ol> <li>Find learning rate that makes loss go down.</li> </ol> <p>Use the architecture from the previous step, use all training data, turn on small weight decay, find a learning rate that makes the loss drop significantly within 100 iterations.</p> <p>Good learning rates to try: \\(0.1,0.01,0.001,0.0001,\\dots\\)</p> <ol> <li>Coarse grid, train for 1-5 epochs.</li> </ol> <p>Choose a few values of learning rate and weight decay around what worked from Step 3, train a few models for 1-5 epochs.\\</p> <p>Good weight decay to try: \\(0.0001,0.00001,0\\)</p> <ol> <li>Refine grid, train longer.</li> </ol> <p>Pick best models from Step 4, train them for longer (10-20 epochs) without learning rate decay.</p> <ol> <li>Look at loss and accuracy curves.</li> <li>GOTO step 5.</li> </ol>"},{"location":"AI/CS231n/CS231n_notes/#gradient-checks","title":"Gradient Checks","text":"<p>CS231n Convolutional Neural Networks for Visual Recognition</p> <p>Compute analytical gradient manually using \\(f_a'=\\frac{\\partial f(x)}{\\partial x}=\\frac{f(x-h)-f(x+h)}{2h}\\\\\\)</p> <p>Get relative error between numerical gradient \\(f_n'\\) and analytical gradient \\(f_a'\\) using \\(E=\\frac{|f_n'-f_a'|}{\\max{|f_n'|,|f_a'|}}\\\\\\)</p> Relative Error Result \\(E&gt;10^{-2}\\) Probably \\(f_n'\\) is wrong. \\(10^{-2}&gt;E&gt;10^{-4}\\) Not good, should check the gradient. \\(10^{-4}&gt;E&gt;10^{-6}\\) Okay for objectives with kinks. (e.g. ReLU)Not good for objectives with no kink. (e.g. softmax, tanh) \\(10^{-7}&gt;E\\) Good. <p>Tips on gradient checks:</p> <ol> <li>Use double precision.</li> <li>Use only few data points.</li> <li>Careful about kinks in the objective. (e.g. \\(x=0\\) for ReLU activation)</li> <li>Careful with the step size \\(h\\).</li> <li>Use gradient check after the loss starts to go down.</li> <li>Remember to turn off anything that may affect the gradient. (e.g. regularization / dropout / augmentations)</li> <li>Check only few dimensions for every parameter. (reduce time cost)</li> </ol>"},{"location":"AI/CS231n/CS231n_notes/#8-visualizing-and-understanding","title":"8 - Visualizing and Understanding","text":""},{"location":"AI/CS231n/CS231n_notes/#feature-visualization-and-inversion","title":"Feature Visualization and Inversion","text":""},{"location":"AI/CS231n/CS231n_notes/#visualizing-what-models-have-learned","title":"Visualizing what models have learned","text":"Visualize Areas Filters Visualize the raw weights of each convolution kernel. (better in the first layer) Final Layer Features Run dimensionality reduction for features in the last FC layer. (PCA, t-SNE...) Activations Visualize activated areas. (Understanding Neural Networks Through Deep Visualization)"},{"location":"AI/CS231n/CS231n_notes/#understanding-input-pixels","title":"Understanding input pixels","text":""},{"location":"AI/CS231n/CS231n_notes/#maximally-activating-patches","title":"Maximally Activating Patches","text":"<ol> <li>Pick a layer and a channel.</li> <li>Run many images through the network, record values of the chosen channel.</li> <li>Visualize image patches that correspond to maximal activation features.</li> </ol> <p>For example, we have a layer with shape \\(128\\times13\\times13\\). We pick the 17th channel from all 128 channels. Then we run many pictures through the network. During each run we can find a maximal activation feature among all the \\(13\\times13\\) features in channel 17. We then record the corresponding picture patch for each maximal activation feature. At last, we visualize all picture patches for each feature.</p> <p>This will help us find the relationship between each maximal activation feature and its corresponding picture patches.</p> <p>(each row of the following picture represents a feature)</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#saliency-via-occlusion","title":"Saliency via Occlusion","text":"<p>Mask part of the image before feeding to CNN, check how much predicted probabilities change.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#saliency-via-backprop","title":"Saliency via Backprop","text":"<ol> <li>Compute gradient of (unnormalized) class score with respect to image pixels.</li> <li>Take absolute value and max over RGB channels to get saliency maps.</li> </ol>"},{"location":"AI/CS231n/CS231n_notes/#intermediate-features-via-guided-backprop","title":"Intermediate Features via Guided Backprop","text":"<ol> <li>Pick a single intermediate neuron. (e.g. one feature in a \\(128\\times13\\times13\\) feature map)</li> <li>Compute gradient of neuron value with respect to image pixels.</li> </ol> <p>Striving for Simplicity: The All Convolutional Net</p> <p>Just like \"Maximally Activating Patches\", this could find the part of an image that a neuron responds to.</p> <p></p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#gradient-ascent","title":"Gradient Ascent","text":"<p>Generate a synthetic image that maximally activates a neuron.</p> <ol> <li>Initialize image \\(I\\) to zeros.</li> <li>Forward image to compute current scores \\(S_c(I)\\) (for class \\(c\\) before softmax).</li> <li>Backprop to get gradient of neuron value with respect to image pixels.</li> <li>Make a small update to the image.</li> </ol> <p>Objective: \\(\\max S_c(I)-\\lambda\\lVert I\\lVert^2\\)</p> <p>Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps</p> <p></p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#adversarial-examples","title":"Adversarial Examples","text":"<p>Find an fooling image that can make the network misclassify correctly-classified images when it is added to the image.</p> <ol> <li>Start from an arbitrary image.</li> <li>Pick an arbitrary class.</li> <li>Modify the image to maximize the class.</li> <li>Repeat until network is fooled.</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#deepdream-and-style-transfer","title":"DeepDream and Style Transfer","text":""},{"location":"AI/CS231n/CS231n_notes/#feature-inversion","title":"Feature Inversion","text":"<p>Given a CNN feature vector \\(\\Phi_0\\) for an image, find a new image \\(x\\) that:</p> <ol> <li>Features of new image \\(\\Phi(x)\\) matches the given feature vector \\(\\Phi_0\\).</li> <li>\"looks natural\u201d. (image prior regularization)</li> </ol> <p>Objective: \\(\\min \\lVert\\Phi(x)-\\Phi_0\\lVert+\\lambda R(x)\\)</p> <p>Understanding Deep Image Representations by Inverting Them</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#deepdream-amplify-existing-features","title":"DeepDream: Amplify Existing Features","text":"<p>Given an image, amplify the neuron activations at a layer to generate a new one.</p> <ol> <li>Forward: compute activations at chosen layer.</li> <li>Set gradient of chosen layer equal to its activation.</li> <li>Backward: Compute gradient on image.</li> <li>Update image.</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#texture-synthesis","title":"Texture Synthesis","text":""},{"location":"AI/CS231n/CS231n_notes/#nearest-neighbor","title":"Nearest Neighbor","text":"<ol> <li>Generate pixels one at a time in scanline order</li> <li>Form neighborhood of already generated pixels, copy the nearest neighbor from input.</li> </ol>"},{"location":"AI/CS231n/CS231n_notes/#neural-texture-synthesis","title":"Neural Texture Synthesis","text":"<p>Gram Matrix: \u683c\u62c9\u59c6\u77e9\u9635\uff08Gram matrix\uff09\u8be6\u7ec6\u89e3\u8bfb</p> <ol> <li>Pretrain a CNN on ImageNet.</li> <li>Run input texture forward through CNN, record activations on every layer.</li> </ol> <p>Layer \\(i\\) gives feature map of shape \\(C_i\\times H_i\\times W_i\\).</p> <ol> <li>At each layer compute the Gram matrix \\(G_i\\) giving outer product of features.</li> </ol> <ul> <li>Reshape feature map at layer \\(i\\) to \\(C_i\\times H_iW_i\\).</li> <li>Compute the Gram matrix \\(G_i\\) with shape \\(C_i\\times C_i\\).</li> </ul> <ol> <li>Initialize generated image from random noise.</li> <li>Pass generated image through CNN, compute Gram matrix \\(\\hat{G}_l\\) on each layer.</li> <li>Compute loss: Weighted sum of L2 distance between Gram matrices.</li> </ol> <ul> <li>\\(E_l=\\frac{1}{aN_l^2M_l^2}\\sum_{i,j}\\Big(G_i^{(i,j)}-\\hat{G}_i^{(i,j)}\\Big)^2\\\\\\)</li> <li>\\(\\mathcal{L}(\\vec{x},\\hat{\\vec{x}})=\\sum_{l=0}^L\\omega_lE_l\\\\\\)</li> </ul> <ol> <li>Backprop to get gradient on image.</li> <li>Make gradient step on image.</li> <li>GOTO 5.</li> </ol> <p>Texture Synthesis Using Convolutional Neural Networks</p> <p></p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#style-transfer","title":"Style Transfer","text":""},{"location":"AI/CS231n/CS231n_notes/#feature-gram-reconstruction","title":"Feature + Gram Reconstruction","text":"<p>Problem: Style transfer requires many forward / backward passes. Very slow!</p>"},{"location":"AI/CS231n/CS231n_notes/#fast-style-transfer","title":"Fast Style Transfer","text":""},{"location":"AI/CS231n/CS231n_notes/#9-object-detection-and-image-segmentation","title":"9 - Object Detection and Image Segmentation","text":""},{"location":"AI/CS231n/CS231n_notes/#semantic-segmentation","title":"Semantic Segmentation","text":"<p>Paired Training Data: For each training image, each pixel is labeled with a semantic category.</p> <p></p> <p>Fully Convolutional Network: Design a network with only convolutional layers without downsampling operators to make predictions for pixels all at once!</p> <p></p> <p>Problem: Convolutions at original image resolution will be very expensive...</p> <p>Solution: Design fully convolutional network with downsampling and upsampling inside it!</p> <ul> <li>Downsampling: Pooling, strided convolution.</li> <li>Upsampling: Unpooling, transposed convolution.</li> </ul> <p>Unpooling:</p> Nearest Neighbor \"Bed of Nails\" \"Position Memory\" <p>Transposed Convolution: (example size \\(3\\times3\\), stride \\(2\\), pad \\(1\\))</p> Normal Convolution Transposed Convolution <p></p>"},{"location":"AI/CS231n/CS231n_notes/#object-detection","title":"Object Detection","text":""},{"location":"AI/CS231n/CS231n_notes/#single-object","title":"Single Object","text":"<p>Classification + Localization. (classification + regression problem)</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#multiple-object","title":"Multiple Object","text":""},{"location":"AI/CS231n/CS231n_notes/#r-cnn","title":"R-CNN","text":"<p>Using selective search to find \u201cblobby\u201d image regions that are likely to contain objects.</p> <ol> <li>Find regions of interest (RoI) using selective search. (region proposal)</li> <li>Forward each region through ConvNet.</li> <li>Classify features with SVMs.</li> </ol> <p>Problem: Very slow. Need to do 2000 independent forward passes for each image!</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#fast-r-cnn","title":"Fast R-CNN","text":"<p>Pass the image through ConvNet before cropping. Crop the conv feature instead.</p> <ol> <li>Run whole image through ConvNet.</li> <li>Find regions of interest (RoI) from conv features using selective search. (region proposal)</li> <li>Classify RoIs using CNN.</li> </ol> <p>Problem: Runtime is dominated by region proposals. (about \\(90\\%\\) time cost)</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#faster-r-cnn","title":"Faster R-CNN","text":"<p>Insert Region Proposal Network (RPN) to predict proposals from features.</p> <p>Otherwise same as Fast R-CNN: Crop features for each proposal, classify each one.</p> <p>Region Proposal Network (RPN) : Slide many fixed windows over ConvNet features.</p> <ol> <li>Treat each point in the feature map as the anchor. </li> </ol> <p>We have \\(k\\) fixed windows (anchor boxes) of different size/scale centered with each anchor.</p> <ol> <li>For each anchor box, predict whether it contains an object.</li> </ol> <p>For positive boxes, also predict a corrections to the ground-truth box.</p> <ol> <li>Slide anchor over the feature map, get the \u201cobjectness\u201d score for each box at each point.</li> <li>Sort the \u201cobjectness\u201d score, take top \\(300\\) as the proposals.</li> </ol> <p></p> <p>Faster R-CNN is a Two-stage object detector:</p> <ol> <li>First stage: Run once per image</li> </ol> <p>Backbone network</p> <p>Region proposal network</p> <ol> <li>Second stage: Run once per region</li> </ol> <p>Crop features: RoI pool / align</p> <p>Predict object class</p> <p>Prediction bbox offset</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#single-stage-object-detectors-yolo","title":"Single-Stage Object Detectors: YOLO","text":"<p>You Only Look Once: Unified, Real-Time Object Detection</p> <ol> <li>Divide image into grids. (example image grids shape \\(7\\times7\\))</li> <li>Set anchors in the middle of each grid.</li> <li>For each grid:    - Using \\(B\\) anchor boxes to regress \\(5\\) numbers: \\(\\text{dx, dy, dh, dw, confidence}\\).    - Predict scores for each of \\(C\\) classes.</li> <li>Finally the output is \\(7\\times7\\times(5B+C)\\).</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#instance-segmentation","title":"Instance Segmentation","text":"<p>Mask R-CNN: Add a small mask network that operates on each RoI and predicts a \\(28\\times28\\) binary mask.</p> <p></p> <p>Mask R-CNN performs very good results!</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#10-recurrent-neural-networks","title":"10 - Recurrent Neural Networks","text":"<p>Supplement content added according to Deep Learning Book - RNN.</p>"},{"location":"AI/CS231n/CS231n_notes/#recurrent-neural-network-rnn","title":"Recurrent Neural Network (RNN)","text":""},{"location":"AI/CS231n/CS231n_notes/#motivation-sequence-processing","title":"Motivation: Sequence Processing","text":"One to One One to Many Many to One Many to Many Many to Many Vanilla Neural Networks Image Captioning Action Prediction Video Captioning Video Classification on Frame Level"},{"location":"AI/CS231n/CS231n_notes/#vanilla-rnn","title":"Vanilla RNN","text":"<p>\\(x^{(t)}\\) : Input at time \\(t\\).</p> <p>\\(h^{(t)}\\) : State at time \\(t\\).</p> <p>\\(o^{(t)}\\) : Output at time \\(t\\)\u200b\u200b.</p> <p>\\(y^{(t)}\\) : Expected output at time \\(t\\).</p>"},{"location":"AI/CS231n/CS231n_notes/#many-to-one","title":"Many to One","text":"Calculation State Transition \\(h^{(t)}=\\tanh(Wh^{(t-1)}+Ux^{(t)}+b)\\) Output Calculation \\(o^{(\\tau)}=\\text{sigmoid}\\ \\big(Vh^{(\\tau)}+c\\big)\\)"},{"location":"AI/CS231n/CS231n_notes/#many-to-many-type-2","title":"Many to Many (type 2)","text":"Calculation State Transition \\(h^{(t)}=\\tanh(Wh^{(t-1)}+Ux^{(t)}+b)\\) Output Calculation \\(o^{(t)}=\\text{sigmoid}\\ \\big(Vh^{(t)}+c\\big)\\)"},{"location":"AI/CS231n/CS231n_notes/#rnn-with-teacher-forcing","title":"RNN with Teacher Forcing","text":"<p>Update current state according to last-time output instead of last-time state.</p> <p></p> Calculation State Transition \\(h^{(t)}=\\tanh(Wo^{(t-1)}+Ux^{(t)}+b)\\) Output Calculation \\(o^{(t)}=\\text{sigmoid}\\ \\big(Vh^{(t)}+c\\big)\\)"},{"location":"AI/CS231n/CS231n_notes/#rnn-with-output-forwarding","title":"RNN with \"Output Forwarding\"","text":"<p>We can also combine last-state output with this-state input together.</p> <p></p> Calculation State Transition (training) \\(h^{(t)}=\\tanh(Wh^{(t-1)}+Ux^{(t)}+Ry^{(t-1)}+b)\\) State Transition (testing) \\(h^{(t)}=\\tanh(Wh^{(t-1)}+Ux^{(t)}+Ro^{(t-1)}+b)\\) Output Calculation \\(o^{(t)}=\\text{sigmoid}\\ \\big(Vh^{(t)}+c\\big)\\) <p>Usually we use \\(o^{(t-1)}\\) in place of \\(y^{(t-1)}\\) at testing time.</p>"},{"location":"AI/CS231n/CS231n_notes/#bidirectional-rnn","title":"Bidirectional RNN","text":"<p>When dealing with a whole input sequence, we can process features from two directions.</p> <p></p> Calculation State Transition (forward) \\(h^{(t)}=\\tanh(W_1h^{(t-1)}+U_1x^{(t)}+b_1)\\) State Transition (backward) \\(g^{(t)}=\\tanh(W_2g^{(t+1)}+U_2x^{(t)}+b_2)\\) Output Calculation \\(o^{(t)}=\\text{sigmoid}\\ \\big(Vh^{(t)}+Wg^{(t)}+c\\big)\\)"},{"location":"AI/CS231n/CS231n_notes/#encoder-decoder-sequence-to-sequence-rnn","title":"Encoder-Decoder Sequence to Sequence RNN","text":"<p>This is a many-to-many structure (type 1).</p> <p>First we encode information according to \\(x\\) with no output.</p> <p>Later we decode information according to \\(y\\) with no input.</p> <p>\\(C\\) : Context vector, often \\(C=h^{(T)}\\) (last state of encoder).</p> <p></p> Calculation State Transition (encode) \\(h^{(t)}=\\tanh(W_1h^{(t-1)}+U_1x^{(t)}+b_1)\\) State Transition (decode, training) \\(s^{(t)}=\\tanh(W_2s^{(t-1)}+U_2y^{(t)}+TC+b_2)\\) State Transition (decode, testing) \\(s^{(t)}=\\tanh(W_2s^{(t-1)}+U_2o^{(t)}+TC+b_2)\\) Output Calculation \\(o^{(t)}=\\text{sigmoid}\\ \\big(Vs^{(t)}+c\\big)\\)"},{"location":"AI/CS231n/CS231n_notes/#example-image-captioning","title":"Example: Image Captioning","text":""},{"location":"AI/CS231n/CS231n_notes/#summary_2","title":"Summary","text":"<p>Advantages of RNN:</p> <ol> <li>Can process any length input.</li> <li>Computation for step \\(t\\) can (in theory) use information from many steps back.</li> <li>Model size doesn\u2019t increase for longer input.</li> <li>Same weights applied on every timestep, so there is symmetry in how inputs are processed.</li> </ol> <p>Disadvantages of RNN:</p> <ol> <li>Recurrent computation is slow.</li> <li>In practice, difficult to access information from many steps back.</li> <li>Problems with gradient exploding and gradient vanishing. (check Deep Learning Book - RNN Page 396, Chap 10.7)</li> </ol>"},{"location":"AI/CS231n/CS231n_notes/#long-short-term-memory-lstm","title":"Long Short Term Memory (LSTM)","text":"<p>Add a \"cell block\" to store history weights.</p> <p>\\(c^{(t)}\\) : Cell at time \\(t\\).</p> <p>\\(f^{(t)}\\) : Forget gate at time \\(t\\). Deciding whether to erase the cell.</p> <p>\\(i^{(t)}\\) : Input gate at time \\(t\\). Deciding whether to write to the cell.</p> <p>\\(g^{(t)}\\) : External input gate at time \\(t\\). Deciding how much to write to the cell.</p> <p>\\(o^{(t)}\\) : Output gate at time \\(t\\). Deciding how much to reveal the cell.</p> <p></p> Calculation (Gate) Forget Gate \\(f^{(t)}=\\text{sigmoid}\\ \\big(W_fh^{(t-1)}+U_fx^{(t)}+b_f\\big)\\) Input Gate \\(i^{(t)}=\\text{sigmoid}\\ \\big(W_ih^{(t-1)}+U_ix^{(t)}+b_i\\big)\\) External Input Gate \\(g^{(t)}=\\tanh(W_gh^{(t-1)}+U_gx^{(t)}+b_g)\\) Output Gate \\(o^{(t)}=\\text{sigmoid}\\ \\big(W_oh^{(t-1)}+U_ox^{(t)}+b_o\\big)\\) Calculation (Main) Cell Transition \\(c^{(t)}=f^{(t)}\\odot c^{(t-1)}+i^{(t)}\\odot g^{(t)}\\) State Transition \\(h^{(t)}=o^{(t)}\\odot\\tanh(c^{(t)})\\) Output Calculation \\(O^{(t)}=\\text{sigmoid}\\ \\big(Vh^{(t)}+c\\big)\\) <p></p>"},{"location":"AI/CS231n/CS231n_notes/#other-rnn-variants","title":"Other RNN Variants","text":"<p>GRU...</p>"},{"location":"AI/CS231n/CS231n_notes/#11-attention-and-transformers","title":"11 - Attention and Transformers","text":""},{"location":"AI/CS231n/CS231n_notes/#rnn-with-attention","title":"RNN with Attention","text":"<p>Encoder-Decoder Sequence to Sequence RNN Problem:</p> <p>Input sequence bottlenecked through a fixed-sized context vector \\(C\\). (e.g. \\(T=1000\\))</p> <p></p> <p>Intuitive Solution:</p> <p>Generate new context vector \\(C_t\\) at each step \\(t\\) !</p> <p>\\(e_{t,i}\\) : Alignment score for input \\(i\\) at state \\(t\\). (scalar)</p> <p>\\(a_{t,i}\\) : Attention weight for input \\(i\\) at state \\(t\\).</p> <p>\\(C_t\\) : Context vector at state \\(t\\).</p> <p></p> <p></p> Calculation Alignment Score \\(e_i^{(t)}=f(s^{(t-1)},h^{(i)})\\).Where \\(f\\) is an MLP. Attention Weight \\(a_i^{(t)}=\\text{softmax}\\ (e_i^{(t)})\\).Softmax includes all \\(e_i\\) at state \\(t\\). Context Vector \\(C^{(t)}=\\sum_i a_i^{(t)}h^{(i)}\\) Decoder State Transition \\(s^{(t)}=\\tanh(Ws^{(t-1)}+Uy^{(t)}+TC^{(t)}+b)\\) <p>Example on Image Captioning:</p> <p></p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#general-attention-layer","title":"General Attention Layer","text":"<p>Add linear transformations to the input vector before attention.</p> <p></p> <p>Notice:</p> <ol> <li>Number of queries \\(q\\) is variant. (can be different from the number of keys \\(k\\))</li> <li>Number of outputs \\(y\\) is equal to the number of queries \\(q\\).</li> </ol> <p>Each \\(y\\) is a linear weighting of values \\(v\\).</p> <ol> <li>Alignment \\(e\\) is divided by \\(\\sqrt{D}\\) to avoid \"explosion of softmax\", where \\(D\\) is the dimension of input feature.</li> </ol>"},{"location":"AI/CS231n/CS231n_notes/#self-attention-layer","title":"Self-attention Layer","text":"<p>The query vectors \\(q\\) are also generated from the inputs.</p> <p></p> <p>In this way, the shape of \\(y\\) is equal to the shape of \\(x\\).</p> <p>Example with CNN:</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#positional-encoding","title":"Positional Encoding","text":"<p>Self-attention layer doesn\u2019t care about the orders of the inputs!</p> <p></p> <p>To encode ordered sequences like language or spatially ordered image features, we can add positional encoding to the inputs.</p> <p></p> <p>We use a function \\(P:R\\rightarrow R^d\\) to process the position \\(i\\) into a d-dimensional vector \\(p_i=P(i)\\).</p> Constraint Condition of \\(P\\) Uniqueness \\(P(i)\\ne P(j)\\) Equidistance \\(\\lVert P(i+k)-P(i)\\rVert^2=\\lVert P(j+k)-P(j)\\rVert^2\\) Boundness \\(P(i)\\in[a,b]\\) Determinacy \\(P(i)\\) is always a static value. (function is not dynamic) <p>We can either train a encoder model, or design a fixed function.</p> <p>A Practical Positional Encoding Method: Using \\(\\sin\\) and \\(\\cos\\) with different frequency \\(\\omega\\) at different dimension.</p> <p>\\(P(t)=\\begin{bmatrix}\\sin(\\omega_1,t)\\\\\\cos(\\omega_1,t)\\\\\\\\\\sin(\\omega_2,t)\\\\\\cos(\\omega_2,t)\\\\\\vdots\\\\\\sin(\\omega_{\\frac{d}{2}},t)\\\\\\cos(\\omega_{\\frac{d}{2}},t)\\end{bmatrix}\\), where frequency \\(\\omega_k=\\frac{1}{10000^{\\frac{2k}{d}}}\\\\\\). (wave length \\(\\lambda=\\frac{1}{\\omega}=10000^{\\frac{2k}{d}}\\\\\\))</p> <p>\\(P(t)=\\begin{bmatrix}\\sin(1/10000^{\\frac{2}{d}},t)\\\\\\cos(1/10000^{\\frac{2}{d}},t)\\\\\\\\\\sin(1/10000^{\\frac{4}{d}},t)\\\\\\cos(1/10000^{\\frac{4}{d}},t)\\\\\\vdots\\\\\\sin(1/10000^1,t)\\\\\\cos(1/10000^1,t)\\end{bmatrix}\\), after we substitute \\(\\omega_k\\) into the equation.</p> <p>\\(P(t)\\) is a vector with size \\(d\\), where \\(d\\) is a hyperparameter to choose according to the length of input sequence.</p> <p>An intuition of this method is the binary encoding of numbers.</p> <p></p> <p>[lecture 11d] \u6ce8\u610f\u529b\u548ctransformer (positional encoding \u8865\u5145\uff0c\u4ee3\u7801\u5b9e\u73b0\uff0c\u8ddd\u79bb\u8ba1\u7b97)</p> <p>It is easy to prove that \\(P(t)\\) satisfies \"Equidistance\": (set \\(d=2\\) for example)</p> <p>\\(\\begin{aligned}\\lVert P(i+k)-P(i)\\rVert^2&amp;=\\big[\\sin(\\omega_1,i+k)-\\sin(\\omega_1,i)\\big]^2+\\big[\\cos(\\omega_1,i+k)-\\cos(\\omega_1,i)\\big]^2\\\\&amp;=2-2\\sin(\\omega_1,i+k)\\sin(\\omega_1,i)-2\\cos(\\omega_1,i+k)\\cos(\\omega_1,i)\\\\&amp;=2-2\\cos(\\omega_1,k)\\end{aligned}\\)</p> <p>So the distance is not associated with \\(i\\), we have \\(\\lVert P(i+k)-P(i)\\rVert^2=\\lVert P(j+k)-P(j)\\rVert^2\\).</p> <p>Visualization of \\(P(t)\\) features: (set \\(d=32\\), \\(x\\) axis represents the position of sequence)</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#masked-self-attention-layer","title":"Masked Self-attention Layer","text":"<p>To prevent vectors from looking at future vectors, we manually set alignment scores to \\(-\\infty\\).</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#multi-head-self-attention-layer","title":"Multi-head Self-attention Layer","text":"<p>Multiple self-attention heads in parallel.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#transformer","title":"Transformer","text":"<p>Attention Is All You Need</p>"},{"location":"AI/CS231n/CS231n_notes/#encoder-block","title":"Encoder Block","text":"<p>Inputs: Set of vectors \\(z\\). (in which \\(z_i\\) can be a word in a sentence, or a pixel in a picture...)</p> <p>Output: Set of context vectors \\(c\\). (encoded features of \\(z\\))</p> <p></p> <p>The number of blocks \\(N=6\\) in original paper.</p> <p>Notice:</p> <ol> <li>Self-attention is the only interaction between vectors \\(x_0,x_1,\\dots,x_n\\).</li> <li>Layer norm and MLP operate independently per vector.</li> <li>Highly scalable, highly parallelizable, but high memory usage.</li> </ol>"},{"location":"AI/CS231n/CS231n_notes/#decoder-block","title":"Decoder Block","text":"<p>Inputs: Set of vectors \\(y\\). (\\(y_i\\) can be a word in a sentence, or a pixel in a picture...)</p> <p>Inputs: Set of context vectors \\(c\\).</p> <p>Output: Set of vectors \\(y'\\). (decoded result, \\(y'_i=y_{i+1}\\) for the first \\(n-1\\) number of \\(y'\\))</p> <p></p> <p>The number of blocks \\(N=6\\) in original paper.</p> <p>Notice:</p> <ol> <li>Masked self-attention only interacts with past inputs.</li> <li>Multi-head attention block is NOT self-attention. It attends over encoder outputs.</li> <li>Highly scalable, highly parallelizable, but high memory usage. (same as encoder)</li> </ol> <p>Why we need mask in decoder:</p> <ol> <li>Needs for the special formation of output \\(y'_i=y_{i+1}\\).</li> <li>Needs for parallel computation.</li> </ol> <p>\u4e3e\u4e2a\u4f8b\u5b50\u8bb2\u4e0btransformer\u7684\u8f93\u5165\u8f93\u51fa\u7ec6\u8282\u53ca\u5176\u4ed6</p> <p>\u5728\u6d4b\u8bd5\u6216\u8005\u9884\u6d4b\u65f6\uff0cTransformer\u91ccdecoder\u4e3a\u4ec0\u4e48\u8fd8\u9700\u8981seq mask\uff1f</p>"},{"location":"AI/CS231n/CS231n_notes/#example-on-image-captioning-only-with-transformers","title":"Example on Image Captioning (Only with Transformers)","text":""},{"location":"AI/CS231n/CS231n_notes/#comparing-rnns-to-transformer","title":"Comparing RNNs to Transformer","text":"RNNs Transformer Pros LSTMs work reasonably well for long sequences. 1. Good at long sequences. Each attention calculation looks at all inputs.2. Can operate over unordered sets or ordered sequences with positional encodings.3. Parallel computation: All alignment and attention scores for all inputs can be done in parallel. Cons 1. Expects an ordered sequences of inputs.2. Sequential computation: Subsequent hidden states can only be computed after the previous ones are done. Requires a lot of memory: \\(N\\times M\\) alignment and attention scalers need to be calculated and stored for a single self-attention head."},{"location":"AI/CS231n/CS231n_notes/#comparing-convnets-to-transformer","title":"Comparing ConvNets to Transformer","text":"<p>ConvNets strike back!</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#12-video-understanding","title":"12 - Video Understanding","text":""},{"location":"AI/CS231n/CS231n_notes/#video-classification","title":"Video Classification","text":"<p>Take video classification task for example.</p> <p></p> <p>Input size: \\(C\\times T\\times H\\times W\\).</p> <p>The problem is, videos are quite big. We can't afford to train on raw videos, instead we train on video clips.</p> Raw Videos Video Clips \\(1920\\times1080,\\ 30\\text{fps}\\) \\(112\\times112,\\ 5\\text{f}/3.2\\text{s}\\) \\(10\\text{GB}/\\text{min}\\) \\(588\\text{KB}/\\text{min}\\) <p></p>"},{"location":"AI/CS231n/CS231n_notes/#plain-cnn-structure","title":"Plain CNN Structure","text":""},{"location":"AI/CS231n/CS231n_notes/#single-frame-2d-cnn","title":"Single Frame 2D-CNN","text":"<p>Train a normal 2D-CNN model.</p> <p>Classify each frame independently.</p> <p>Average the result of each frame as the final result.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#late-fusion","title":"Late Fusion","text":"<p>Get high-level appearance of each frame, and combine them.</p> <p>Run 2D-CNN on each frame, pool features and feed to Linear Layers.</p> <p></p> <p>Problem: Hard to compare low-level motion between frames.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#early-fusion","title":"Early Fusion","text":"<p>Compare frames with very first Conv Layer, after that normal 2D-CNN.</p> <p></p> <p>Problem: One layer of temporal processing may not be enough!</p>"},{"location":"AI/CS231n/CS231n_notes/#3d-cnn","title":"3D-CNN","text":"<p>Convolve on 3 dimensions: Height, Width, Time.</p> <p>Input size: \\(C_{in}\\times T\\times H\\times W\\).</p> <p>Kernel size: \\(C_{in}\\times C_{out}\\times 3\\times 3\\times 3\\).</p> <p>Output size: \\(C_{out}\\times T\\times H\\times W\\). (with zero paddling)</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#c3d-vgg-of-3d-cnns","title":"C3D (VGG of 3D-CNNs)","text":"<p>The cost is quite expensive...</p> Network Calculation AlexNet 0.7 GFLOP VGG-16 13.6 GFLOP C3D 39.5 GFLOP"},{"location":"AI/CS231n/CS231n_notes/#two-stream-networks","title":"Two-Stream Networks","text":"<p>Separate motion and appearance.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#i3d-inflating-2d-networks-to-3d","title":"I3D (Inflating 2D Networks to 3D)","text":"<p>Take a 2D-CNN architecture.</p> <p>Replace each 2D conv/pool layer with a 3D version.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#modeling-long-term-temporal-structure","title":"Modeling Long-term Temporal Structure","text":""},{"location":"AI/CS231n/CS231n_notes/#recurrent-convolutional-network","title":"Recurrent Convolutional Network","text":"<p>Similar to multi-layer RNN, we replace the dot-product operation with convolution.</p> <p></p> <p>Feature size in layer \\(L\\), time \\(t-1\\): \\(W_h\\times H\\times W\\).</p> <p>Feature size in layer \\(L-1\\), time \\(t\\): \\(W_x\\times H\\times W\\).</p> <p>Feature size in layer \\(L\\), time \\(t\\): \\((W_h+W_x)\\times H\\times W\\).</p> <p></p> <p>Problem: RNNs are slow for long sequences. (can\u2019t be parallelized)</p>"},{"location":"AI/CS231n/CS231n_notes/#spatio-temporal-self-attention","title":"Spatio-temporal Self-attention","text":"<p>Introduce self-attention into video classification problems.</p> <p></p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#vision-transformers-for-video","title":"Vision Transformers for Video","text":"<p>Factorized attention: Attend over space / time.</p> <p>So many papers...</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#visualizing-video-models","title":"Visualizing Video Models","text":""},{"location":"AI/CS231n/CS231n_notes/#multimodal-video-understanding","title":"Multimodal Video Understanding","text":""},{"location":"AI/CS231n/CS231n_notes/#temporal-action-localization","title":"Temporal Action Localization","text":"<p>Given a long untrimmed video sequence, identify frames corresponding to different actions.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#spatio-temporal-detection","title":"Spatio-Temporal Detection","text":"<p>Given a long untrimmed video, detect all the people in both space and time and classify the activities they are performing.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#visually-guided-audio-source-separation","title":"Visually-guided Audio Source Separation","text":"<p>And So on...</p>"},{"location":"AI/CS231n/CS231n_notes/#13-generative-models","title":"13 - Generative Models","text":""},{"location":"AI/CS231n/CS231n_notes/#pixelrnn-and-pixelcnn","title":"PixelRNN and PixelCNN","text":""},{"location":"AI/CS231n/CS231n_notes/#fully-visible-belief-network-fvbn","title":"Fully Visible Belief Network (FVBN)","text":"<p>\\(p(x)\\) : Likelihood of image \\(x\\).</p> <p>\\(p(x_1,x_2,\\dots,x_n)\\) : Joint likelihood of all \\(n\\) pixels in image \\(x\\).</p> <p>\\(p(x_i|x_1,x_2,\\dots,x_{i-1})\\) : Probability of pixel \\(i\\) value given all previous pixels.</p> <p>For explicit density models, we have \\(p(x)=p(x_1,x_2,\\dots,x_n)=\\prod_{i=1}^np(x_i|x_1,x_2,\\dots,x_{i-1})\\\\\\).</p> <p>Objective: Maximize the likelihood of training data.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#pixelrnn","title":"PixelRNN","text":"<p>Generate image pixels starting from corner.</p> <p>Dependency on previous pixels modeled using an RNN (LSTM).</p> <p>Drawback: Sequential generation is slow in both training and inference!</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#pixelcnn","title":"PixelCNN","text":"<p>Still generate image pixels starting from corner.</p> <p>Dependency on previous pixels modeled using a CNN over context region (masked convolution).</p> <p>Drawback: Though its training is faster, its generation is still slow. (pixel by pixel)</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#variational-autoencoder","title":"Variational Autoencoder","text":"<p>Supplement content added according to Tutorial on Variational Autoencoders. (paper with notes: VAE Tutorial.pdf)</p> <p>\u53d8\u5206\u81ea\u7f16\u7801\u5668VAE\uff1a\u539f\u6765\u662f\u8fd9\u4e48\u4e00\u56de\u4e8b | \u9644\u5f00\u6e90\u4ee3\u7801</p>"},{"location":"AI/CS231n/CS231n_notes/#autoencoder","title":"Autoencoder","text":"<p>Learn a lower-dimensional feature representation with unsupervised approaches.</p> <p>\\(x\\rightarrow z\\) : Dimension reduction for input features.</p> <p>\\(z\\rightarrow \\hat{x}\\) : Reconstruct input features.</p> <p></p> <p>After training, we throw the decoder away and use the encoder for transferring.</p> <p></p> <p>For generative models, there is a problem:</p> <p>We can\u2019t generate new images from an autoencoder because we don\u2019t know the space of \\(z\\).</p>"},{"location":"AI/CS231n/CS231n_notes/#variational-autoencoder_1","title":"Variational Autoencoder","text":""},{"location":"AI/CS231n/CS231n_notes/#character-description","title":"Character Description","text":"<p>\\(X\\) : Images. (random variable)</p> <p>\\(Z\\) : Latent representations. (random variable)</p> <p>\\(P(X)\\) : True distribution of all training images \\(X\\).</p> <p>\\(P(Z)\\) : True distribution of all latent representations \\(Z\\).</p> <p>\\(P(X|Z)\\) : True posterior distribution of all images \\(X\\) with condition \\(Z\\).</p> <p>\\(P(Z|X)\\) : True prior distribution of all latent representations \\(Z\\) with condition \\(X\\).</p> <p>\\(Q(Z|X)\\) : Approximated prior distribution of all latent representations \\(Z\\) with condition \\(X\\).</p> <p>\\(x\\) : A specific image.</p> <p>\\(z\\) : A specific latent representation.</p> <p>\\(\\theta\\): Learned parameters in decoder network.</p> <p>\\(\\phi\\): Learned parameters in encoder network.</p> <p>\\(p_\\theta(x)\\) : Probability that \\(x\\sim P(X)\\).</p> <p>\\(p_\\theta(z)\\) : Probability that \\(z\\sim P(Z)\\).</p> <p>\\(p_\\theta(x|z)\\) : Probability that \\(x\\sim P(X|Z)\\).</p> <p>\\(p_\\theta(z|x)\\) : Probability that \\(z\\sim P(Z|X)\\).</p> <p>\\(q_\\phi(z|x)\\) : Probability that \\(z\\sim Q(Z|X)\\).</p>"},{"location":"AI/CS231n/CS231n_notes/#decoder","title":"Decoder","text":"<p>Objective:</p> <p>Generate new images from \\(\\mathscr{z}\\).</p> <ol> <li>Generate a value \\(z^{(i)}\\) from the prior distribution \\(P(Z)\\).</li> <li>Generate a value \\(x^{(i)}\\) from the conditional distribution \\(P(X|Z)\\).</li> </ol> <p>Lemma:</p> <p>Any distribution in \\(d\\) dimensions can be generated by taking a set of \\(d\\) variables that are normally distributed and mapping them through a sufficiently complicated function. (source: Tutorial on Variational Autoencoders, Page 6)</p> <p>Solutions:</p> <ol> <li>Choose prior distribution \\(P(Z)\\) to be a simple distribution, for example \\(P(Z)\\sim N(0,1)\\).</li> <li>Learn the conditional distribution \\(P(X|Z)\\) through a neural network (decoder) with parameter \\(\\theta\\). </li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#encoder","title":"Encoder","text":"<p>Objective:</p> <p>Learn \\(\\mathscr{z}\\) with training images.</p> <p>Given: (From the decoder, we can deduce the following probabilities.)</p> <ol> <li>data likelihood: \\(p_\\theta(x)=\\int p_\\theta(x|z)p_\\theta(z)dz\\).</li> <li>posterior density: \\(p_\\theta(z|x)=\\frac{p_\\theta(x|z)p_\\theta(z)}{p_\\theta(x)}=\\frac{p_\\theta(x|z)p_\\theta(z)}{\\int p_\\theta(x|z)p_\\theta(z)dz}\\).</li> </ol> <p>Problem:</p> <p>Both \\(p_\\theta(x)\\) and \\(p_\\theta(z|x)\\) are intractable. (can't be optimized directly as they contain integral operation)</p> <p>Solution:</p> <p>Learn \\(Q(Z|X)\\) to approximate the true posterior \\(P(Z|X)\\).</p> <p>Use \\(q_\\phi(z|x)\\) in place of \\(p_\\theta(z|x)\\).</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#variational-autoencoder-combination-of-encoder-and-decoder","title":"Variational Autoencoder (Combination of Encoder and Decoder)","text":"<p>Objective:</p> <p>Maximize \\(p_\\theta(x)\\) for all \\(x^{(i)}\\) in the training set.</p> <p>$$ \\begin{aligned} \\log p_\\theta\\big(x^{(i)}\\big)&amp;=\\mathbb{E}{z\\sim q\\phi\\big(z|x^{(i)}\\big)}\\Big[\\log p_\\theta\\big(x^{(i)}\\big)\\Big]\\</p> <p>&amp;=\\mathbb{E}z\\Bigg[\\log\\frac{p\\theta\\big(x^{(i)}|z\\big)p_\\theta\\big(z\\big)}{p_\\theta\\big(z|x^{(i)}\\big)}\\Bigg]\\quad\\text{(Bayes' Rule)}\\</p> <p>&amp;=\\mathbb{E}z\\Bigg[\\log\\frac{p\\theta\\big(x^{(i)}|z\\big)p_\\theta\\big(z\\big)}{p_\\theta\\big(z|x^{(i)}\\big)}\\frac{q_\\phi\\big(z|x^{(i)}\\big)}{q_\\phi\\big(z|x^{(i)}\\big)}\\Bigg]\\quad\\text{(Multiply by Constant)}\\</p> <p>&amp;=\\mathbb{E}z\\Big[\\log p\\theta\\big(x^{(i)}|z\\big)\\Big]-\\mathbb{E}z\\Bigg[\\log\\frac{q\\phi\\big(z|x^{(i)}\\big)}{p_\\theta\\big(z\\big)}\\Bigg]+\\mathbb{E}z\\Bigg[\\log\\frac{p\\theta\\big(z|x^{(i)}\\big)}{q_\\phi\\big(z|x^{(i)}\\big)}\\Bigg]\\quad\\text{(Logarithm)}\\</p> <p>&amp;=\\mathbb{E}z\\Big[\\log p\\theta\\big(x^{(i)}|z\\big)\\Big]-D_{\\text{KL}}\\Big[q_\\phi\\big(z|x^{(i)}\\big)||p_\\theta\\big(z\\big)\\Big]+D_{\\text{KL}}\\Big[p_\\theta\\big(z|x^{(i)}\\big)||q_\\phi\\big(z|x^{(i)}\\big)\\Big]\\quad\\text{(KL Divergence)} \\end{aligned} $$</p> <p>Analyze the Formula by Term:</p> <p>\\(\\mathbb{E}_z\\Big[\\log p_\\theta\\big(x^{(i)}|z\\big)\\Big]\\): Decoder network gives \\(p_\\theta\\big(x^{(i)}|z\\big)\\), can compute estimate of this term through sampling.</p> <p>\\(D_{\\text{KL}}\\Big[q_\\phi\\big(z|x^{(i)}\\big)||p_\\theta\\big(z\\big)\\Big]\\): This KL term (between Gaussians for encoder and \\(z\\) prior) has nice closed-form solution!</p> <p>\\(D_{\\text{KL}}\\Big[p_\\theta\\big(z|x^{(i)}\\big)||q_\\phi\\big(z|x^{(i)}\\big)\\Big]\\): The part \\(p_\\theta\\big(z|x^{(i)}\\big)\\) is intractable. However, we know KL divergence always \\(\\ge0\\).</p> <p>Tractable Lower Bound:</p> <p>We can maximize the lower bound of that formula.</p> <p>As \\(D_{\\text{KL}}\\Big[p_\\theta\\big(z|x^{(i)}\\big)||q_\\phi\\big(z|x^{(i)}\\big)\\Big]\\ge0\\) , we can deduce that:</p> <p>$$ \\begin{aligned} \\log p_\\theta\\big(x^{(i)}\\big)&amp;=\\mathbb{E}z\\Big[\\log p\\theta\\big(x^{(i)}|z\\big)\\Big]-D_{\\text{KL}}\\Big[q_\\phi\\big(z|x^{(i)}\\big)||p_\\theta\\big(z\\big)\\Big]+D_{\\text{KL}}\\Big[p_\\theta\\big(z|x^{(i)}\\big)||q_\\phi\\big(z|x^{(i)}\\big)\\Big]\\</p> <p>&amp;\\ge\\mathbb{E}z\\Big[\\log p\\theta\\big(x^{(i)}|z\\big)\\Big]-D_{\\text{KL}}\\Big[q_\\phi\\big(z|x^{(i)}\\big)||p_\\theta\\big(z\\big)\\Big] \\end{aligned} $$</p> <p>So the loss function \\(\\mathcal{L}\\big(x^{(i)},\\theta,\\phi\\big)=-\\mathbb{E}_z\\Big[\\log p_\\theta\\big(x^{(i)}|z\\big)\\Big]+D_{\\text{KL}}\\Big[q_\\phi\\big(z|x^{(i)}\\big)||p_\\theta\\big(z\\big)\\Big]\\).</p> <p>\\(\\mathbb{E}_z\\Big[\\log p_\\theta\\big(x^{(i)}|z\\big)\\Big]\\): Decoder, reconstruct the input data. </p> <p>\\(D_{\\text{KL}}\\Big[q_\\phi\\big(z|x^{(i)}\\big)||p_\\theta\\big(z\\big)\\Big]\\): Encoder, make approximate posterior distribution close to prior.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#generative-adversarial-networks-gans","title":"Generative Adversarial Networks (GANs)","text":""},{"location":"AI/CS231n/CS231n_notes/#motivation-modeling","title":"Motivation &amp; Modeling","text":"<p>Objective: Not modeling any explicit density function.</p> <p>Problem: Want to sample from complex, high-dimensional training distribution. No direct way to do this!</p> <p>Solution: Sample from a simple distribution, e.g. random noise. Learn the transformation to training distribution.</p> <p></p> <p>Problem: We can't learn the mapping relation between sample \\(z\\) and training images.</p> <p>Solution: Use a discriminator network to tell whether the generate image is within data distribution or not.</p> <p></p> <p>Discriminator network: Try to distinguish between real and fake images.</p> <p>Generator network: Try to fool the discriminator by generating real-looking images.</p> <p></p> <p>\\(x\\) : Real data.</p> <p>\\(y\\) : Fake data, which is generated by the generator network. \\(y=G_{\\theta_g}(z)\\).</p> <p>\\(D_{\\theta_d}(x)\\) : Discriminator score, which is the likelihood of real image. \\(D_{\\theta_d}(x)\\in[0,1]\\).</p> <p>Objective of discriminator network:</p> <p>\\(\\max_{\\theta_d}\\bigg[\\mathbb{E}_x\\Big(\\log D_{\\theta_d}(x)\\Big)+\\mathbb{E}_{z\\sim p(z)}\\Big(\\log\\big(1-D_{\\theta_d}(y)\\big)\\Big)\\bigg]\\)</p> <p>Objective of generator network:</p> <p>\\(\\min_{\\theta_g}\\max_{\\theta_d}\\bigg[\\mathbb{E}_x\\Big(\\log D_{\\theta_d}(x)\\Big)+\\mathbb{E}_{z\\sim p(z)}\\Big(\\log\\big(1-D_{\\theta_d}(y)\\big)\\Big)\\bigg]\\)</p>"},{"location":"AI/CS231n/CS231n_notes/#training-strategy","title":"Training Strategy","text":"<p>Two combine this two networks together, we can train them alternately:</p> <ol> <li>Gradient ascent on discriminator.</li> </ol> <p>\\(\\max_{\\theta_d}\\bigg[\\mathbb{E}_x\\Big(\\log D_{\\theta_d}(x)\\Big)+\\mathbb{E}_{z\\sim p(z)}\\Big(\\log\\big(1-D_{\\theta_d}(y)\\big)\\Big)\\bigg]\\)</p> <ol> <li>Gradient descent on generator.</li> </ol> <p>\\(\\min_{\\theta_g}\\bigg[\\mathbb{E}_{z\\sim p(z)}\\Big(\\log\\big(1-D_{\\theta_d}(y)\\big)\\Big)\\bigg]\\)</p> <p>However, the gradient of generator decreases with the value itself, making it hard to optimize.</p> <p></p> <p>So we replace \\(\\log\\big(1-D_{\\theta_d}(y)\\big)\\) with \\(-\\log D_{\\theta_d}(y)\\), and use gradient ascent instead.</p> <ol> <li>Gradient ascent on discriminator.</li> </ol> <p>\\(\\max_{\\theta_d}\\bigg[\\mathbb{E}_x\\Big(\\log D_{\\theta_d}(x)\\Big)+\\mathbb{E}_{z\\sim p(z)}\\Big(\\log\\big(1-D_{\\theta_d}(y)\\big)\\Big)\\bigg]\\)</p> <ol> <li>Gradient ascent on generator.</li> </ol> <p>\\(\\max_{\\theta_g}\\bigg[\\mathbb{E}_{z\\sim p(z)}\\Big(\\log D_{\\theta_d}(y)\\Big)\\bigg]\\)</p>"},{"location":"AI/CS231n/CS231n_notes/#summary_3","title":"Summary","text":"<p>Pros: Beautiful, state-of-the-art samples!</p> <p>Cons: </p> <ol> <li>Trickier / more unstable to train.</li> <li>Can\u2019t solve inference queries such as \\(p(x), p(z|x)\\).</li> </ol>"},{"location":"AI/CS231n/CS231n_notes/#14-self-supervised-learning","title":"14 - Self-supervised Learning","text":"<p>Aim: Solve \u201cpretext\u201d tasks that produce good features for downstream tasks.</p> <p>Application:</p> <ol> <li>Learn a feature extractor from pretext tasks. (self-supervised)</li> <li>Attach a shallow network on the feature extractor.</li> <li>Train the shallow network on target task with small amount of labeled data. (supervised)</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#pretext-tasks","title":"Pretext Tasks","text":"<p>Labels are generated automatically.</p>"},{"location":"AI/CS231n/CS231n_notes/#rotation","title":"Rotation","text":"<p>Train a classifier on randomly rotated images.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#rearrangement","title":"Rearrangement","text":"<p>Train a classifier on randomly shuffled image pieces.</p> <p>Predict the location of image pieces.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#inpainting","title":"Inpainting","text":"<p>Mask part of the image, train a network to predict the masked area.</p> <p>Method referencing Context Encoders: Feature Learning by Inpainting.</p> <p>Combine two types of loss together to get better performance:</p> <ol> <li>Reconstruction loss (L2 loss): Used for reconstructing global features.</li> <li>Adversarial loss: Used for generating texture features.</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#coloring","title":"Coloring","text":"<p>Transfer between greyscale images and colored images.</p> <p>Cross-channel predictions for images: Split-Brain Autoencoders.</p> <p></p> <p>Video coloring: Establish mappings between reference and target frames in a learned feature space. Tracking Emerges by Colorizing Videos.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#summary-for-pretext-tasks","title":"Summary for Pretext Tasks","text":"<ol> <li>Pretext tasks focus on \u201cvisual common sense\u201d.</li> <li>The models are forced learn good features about natural images.</li> <li>We don\u2019t care about the performance of these pretext tasks. </li> </ol> <p>What we care is the performance of downstream tasks.</p>"},{"location":"AI/CS231n/CS231n_notes/#problems-of-specific-pretext-tasks","title":"Problems of Specific Pretext Tasks","text":"<ol> <li>Coming up with individual pretext tasks is tedious.</li> <li>The learned representations may not be general.</li> </ol> <p>Intuitive Solution: Contrastive Learning.</p>"},{"location":"AI/CS231n/CS231n_notes/#contrastive-representation-learning","title":"Contrastive Representation Learning","text":"<p>Local additional references: Contrastive Learning.md.</p> <p></p> <p>Objective:</p> <p>Given a chosen score function \\(s\\), we aim to learn an encoder function \\(f\\) that yields:</p> <ol> <li>For each sample \\(x\\), increase the similarity \\(s\\big(f(x),f(x^+)\\big)\\) between \\(x\\) and positive samples \\(x^+\\).</li> <li>Finally we want \\(s\\big(f(x),f(x^+)\\big)\\gg s\\big(f(x),f(x^-)\\big)\\).</li> </ol> <p>Loss Function: </p> <p>Given \\(1\\) positive sample and \\(N-1\\) negative samples:</p> InfoNCE Loss Cross Entropy Loss \\(\\begin{aligned}\\mathcal{L}=-\\mathbb{E}_X\\Bigg[\\log\\frac{\\exp{s\\big(f(x),f(x^+)\\big)}}{\\exp{s\\big(f(x),f(x^+)\\big)}+\\sum_{j=1}^{N-1}\\exp{s\\big(f(x),f(x^+)\\big)}}\\Bigg]\\\\\\end{aligned}\\) \\(\\begin{aligned}\\mathcal{L}&amp;=-\\sum_{i=1}^Np(x_i)\\log q(x_i)\\\\&amp;=-\\mathbb{E}_X\\big[\\log q(x)\\big]\\\\&amp;=-\\mathbb{E}_X\\Bigg[\\log\\frac{\\exp(x)}{\\sum_{j=1}^N\\exp(x_j)}\\Bigg]\\end{aligned}\\) <p>The InfoNCE Loss is a lower bound on the mutual information between \\(f(x)\\) and \\(f(x^+)\\):</p> <p>\\(\\text{MI}\\big[f(x),f(x^+)\\big]\\ge\\log(N)-\\mathcal{L}\\)</p> <p>The larger the negative sample size \\(N\\), the tighter the bound.</p> <p>So we use \\(N-1\\) negative samples.</p>"},{"location":"AI/CS231n/CS231n_notes/#instance-contrastive-learning","title":"Instance Contrastive Learning","text":""},{"location":"AI/CS231n/CS231n_notes/#simclr","title":"SimCLR","text":"<p>Use a projection function \\(g(\\cdot)\\) to project features to a space where contrastive learning is applied.</p> <p>The extra projection contributes a lot to the final performance.</p> <p></p> <p>Score Function: Cos similarity \\(s(u,v)=\\frac{u^Tv}{||u||||v||}\\\\\\).</p> <p>Positive Pair: Pair of augmented data.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#momentum-contrastive-learning-moco","title":"Momentum Contrastive Learning (MoCo)","text":"<p>There are mainly \\(3\\) training strategy in contrastive learning:</p> <ol> <li>end-to-end: Keys are updated together with queries, e.g. SimCLR.</li> </ol> <p>(limited by GPU size)</p> <ol> <li>memory bank: Store last-time keys for sampling.</li> </ol> <p>(inconsistency between \\(q\\) and \\(k\\))</p> <ol> <li>MoCo: Use momentum methods to encode keys.</li> </ol> <p>(combination of end-to-end &amp; memory bank)</p> <p></p> <p>Key differences to SimCLR:</p> <ol> <li>Keep a running queue of keys (negative samples).</li> <li>Compute gradients and update the encoder only through the queries.</li> <li>Decouple min-batch size with the number of keys: can support a large number of negative samples.</li> <li>The key encoder is slowly progressing through the momentum update rules:</li> </ol> <p>\\(\\theta_k\\leftarrow m\\theta_k+(1-m)\\theta_q\\)</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#sequence-contrastive-learning","title":"Sequence Contrastive Learning","text":""},{"location":"AI/CS231n/CS231n_notes/#contrastive-predictive-coding-cpc","title":"Contrastive Predictive Coding (CPC)","text":"<p>Contrastive: Contrast between \u201cright\u201d and \u201cwrong\u201d sequences using contrastive learning.</p> <p>Predictive: The model has to predict future patterns given the current context.</p> <p>Coding: The model learns useful feature vectors, or \u201ccode\u201d, for downstream tasks, similar to other self-supervised methods.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#other-examples-frontier","title":"Other Examples (Frontier)","text":""},{"location":"AI/CS231n/CS231n_notes/#contrastive-language-image-pre-training-clip","title":"Contrastive Language Image Pre-training (CLIP)","text":"<p>Contrastive learning between image and natural language sentences.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#15-low-level-vision","title":"15 - Low-Level Vision","text":"<p>Pass...</p>"},{"location":"AI/CS231n/CS231n_notes/#16-3d-vision","title":"16 - 3D Vision","text":""},{"location":"AI/CS231n/CS231n_notes/#representation","title":"Representation","text":""},{"location":"AI/CS231n/CS231n_notes/#explicit-vs-implicit","title":"Explicit vs Implicit","text":"<p>Explicit: Easy to sample examples, hard to do inside/outside check.</p> <p>Implicit: Hard to sample examples, easy to do inside/outside check.</p> Non-parametric Parametric Explicit Points.Meshes. Splines.Subdivision Surfaces. Implicit Level Sets.Voxels. Algebraic Surfaces.Constructive Solid Geometry."},{"location":"AI/CS231n/CS231n_notes/#point-clouds","title":"Point Clouds","text":"<p>The simplest representation.</p> <p>Collection of \\((x,y,z)\\) coordinates.</p> <p>Cons:</p> <ol> <li>Difficult to draw in under-sampled regions.</li> <li>No simplification or subdivision.</li> <li>No direction smooth rendering.</li> <li>No topological information.</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#polygonal-meshes","title":"Polygonal Meshes","text":"<p>Collection of vertices \\(v\\) and edges \\(e\\).</p> <p>Pros:</p> <ol> <li>Can apply downsampling or upsampling on meshes.</li> <li>Error decreases by \\(O(n^2)\\) while meshes increase by \\(O(n)\\).</li> <li>Can approximate arbitrary topology.</li> <li>Efficient rendering.</li> </ol> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#splines","title":"Splines","text":"<p>Use specific functions to approximate the surface. (e.g. B\u00e9zier Curves)</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#algebraic-surfaces","title":"Algebraic Surfaces","text":"<p>Use specific functions to represent the surface.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#constructive-solid-geometry","title":"Constructive Solid Geometry","text":"<p>Combine implicit geometry with Boolean operations.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#level-sets","title":"Level Sets","text":"<p>Store a grim of values to approximate the function.</p> <p>Surface is found where interpolated value equals to \\(0\\).</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#voxels","title":"Voxels","text":"<p>Binary thresholding the volumetric grid.</p> <p></p>"},{"location":"AI/CS231n/CS231n_notes/#ai-3d","title":"AI + 3D","text":"<p>Pass...</p>"},{"location":"AI/CS231n/Image%20Classification-Data-driven%20Approach%2C%20k-Nearest%20Neighbor%2C%20train_val_test%20splits/","title":"Image Classification-Data-driven Approach, k-Nearest Neighbor, train_val_test splits","text":""},{"location":"AI/CS231n/Image%20Classification-Data-driven%20Approach%2C%20k-Nearest%20Neighbor%2C%20train_val_test%20splits/#image-classification-data-driven-approach-k-nearest-neighbor-train_val_test-splits","title":"Image Classification-Data-driven Approach, k-Nearest Neighbor, train_val_test splits","text":"<p> \u7ea6 653 \u4e2a\u5b57  28 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"AI/CS231n/Image%20Classification-Data-driven%20Approach%2C%20k-Nearest%20Neighbor%2C%20train_val_test%20splits/#image-classification","title":"image classification","text":"<ul> <li>challenges<ul> <li>viewpoint variation</li> <li>scale variation</li> <li>deformation</li> <li>occlusion</li> <li>illumination conditions</li> <li>background clutter</li> <li>intra-class variation</li> </ul> </li> <li>data-driven approach</li> <li>the image classification pipeline<ul> <li>input</li> <li>learning<ul> <li>training a classifier</li> <li>learning a model</li> </ul> </li> <li>evaluation</li> </ul> </li> </ul>"},{"location":"AI/CS231n/Image%20Classification-Data-driven%20Approach%2C%20k-Nearest%20Neighbor%2C%20train_val_test%20splits/#nearest-neighbor-classifier","title":"Nearest Neighbor Classifier","text":"\\[ d_1 (I_1, I_2) = \\sum_{p} \\left| I^p_1 - I^p_2 \\right| \\] Python<pre><code>import numpy as np\n\nclass NearestNeighbor(object):  \n  def **init**(self):  \n    pass\n\n  def train(self, X, y):  \n    \"\"\" X is N x D where each row is an example. Y is 1-dimension of size N \"\"\"  \n    # the nearest neighbor classifier simply remembers all the training data  \n    self.Xtr = X  \n    self.ytr = y\n\n  def predict(self, X):  \n    \"\"\" X is N x D where each row is an example we wish to predict label for \"\"\"  \n    num_test = X.shape[0]  \n    # lets make sure that the output type matches the input type  \n    Ypred = np.zeros(num_test, dtype = self.ytr.dtype)\n\n    # loop over all test rows\n    for i in range(num_test):\n      # find the nearest training image to the i'th test image\n      # using the L1 distance (sum of absolute value differences)\n      distances = np.sum(np.abs(self.Xtr - X[i,:]), axis = 1)\n      min_index = np.argmin(distances) # get the index with smallest distance\n      Ypred[i] = self.ytr[min_index] # predict the label of the nearest example\n\n    return Ypred\n</code></pre> \\[ d_2 (I_1, I_2) = \\sqrt{\\sum_{p} \\left( I^p_1 - I^p_2 \\right)^2} \\] Python<pre><code>distances = np.sqrt(np.sum(np.square(self.Xtr - X[i,:]), axis = 1))\n</code></pre>"},{"location":"AI/CS231n/Image%20Classification-Data-driven%20Approach%2C%20k-Nearest%20Neighbor%2C%20train_val_test%20splits/#k-nearest-neighbor-classifier","title":"k - Nearest Neighbor Classifier","text":"<p>![[Pasted image 20241031202452.jpg]]</p>"},{"location":"AI/CS231n/Image%20Classification-Data-driven%20Approach%2C%20k-Nearest%20Neighbor%2C%20train_val_test%20splits/#validation-sets-for-hyperparameter-tuning","title":"Validation sets for Hyperparameter tuning","text":"<p>Evaluate on the test only a single time, at the very end</p> <p>Split your training set into training set and a validation set. Use validation set to tune all hyperparameters. At the end run a single time on the test set and report performance.</p> <ul> <li>cross-validation</li> <li>single calidation split ![[Pasted image 20241031202849.png]]</li> </ul>"},{"location":"AI/CS231n/Image%20Classification-Data-driven%20Approach%2C%20k-Nearest%20Neighbor%2C%20train_val_test%20splits/#pros-and-cons-of-nearest-neighbor-classifier","title":"Pros and Cons of Nearest Neighbor classifier","text":"<ul> <li>simple to implement and understand</li> <li>take no time to train</li> <li>however, pay a cost at test time</li> </ul> <p>As an aside, the computational complexity of the Nearest Neighbor classifier is an active area of research, and several\u00a0Approximate Nearest Neighbor\u00a0(ANN) algorithms and libraries exist that can accelerate the nearest neighbor lookup in a dataset (e.g.\u00a0FLANN). These algorithms allow one to trade off the correctness of the nearest neighbor retrieval with its space/time complexity during retrieval, and usually rely on a pre-processing/indexing stage that involves building a kdtree, or running the k-means algorithm.</p> <ul> <li>\\(\\displaystyle L_{2}\\) isn't enough sensitive</li> </ul> <p>In particular, note that images that are nearby each other are much more a function of the general color distribution of the images, or the type of background rather than their semantic identity.</p> Applying kNN in practice <ol> <li>Preprocess your data: Normalize the features in your data (e.g. one pixel in images) to have zero mean and unit variance. We will cover this in more detail in later sections, and chose not to cover data normalization in this section because pixels in images are usually homogeneous and do not exhibit widely different distributions, alleviating the need for data normalization.</li> <li>If your data is very high-dimensional, consider using a dimensionality reduction technique such as PCA (wiki ref,\u00a0CS229ref,\u00a0blog ref), NCA (wiki ref,\u00a0blog ref), or even\u00a0Random Projections.</li> <li>Split your training data randomly into train/val splits. As a rule of thumb, between 70-90% of your data usually goes to the train split. This setting depends on how many hyperparameters you have and how much of an influence you expect them to have. If there are many hyperparameters to estimate, you should err on the side of having larger validation set to estimate them effectively. If you are concerned about the size of your validation data, it is best to split the training data into folds and perform cross-validation. If you can afford the computational budget it is always safer to go with cross-validation (the more folds the better, but more expensive).</li> <li>Train and evaluate the kNN classifier on the validation data (for all folds, if doing cross-validation) for many choices of\u00a0k\u00a0(e.g. the more the better) and across different distance types (L1 and L2 are good candidates)</li> <li>If your kNN classifier is running too long, consider using an Approximate Nearest Neighbor library (e.g.\u00a0FLANN) to accelerate the retrieval (at cost of some accuracy).</li> <li>Take note of the hyperparameters that gave the best results. There is a question of whether you should use the full training set with the best hyperparameters, since the optimal hyperparameters might change if you were to fold the validation data into your training set (since the size of the data would be larger). In practice it is cleaner to not use the validation data in the final classifier and consider it to be\u00a0burned\u00a0on estimating the hyperparameters. Evaluate the best model on the test set. Report the test set accuracy and declare the result to be the performance of the kNN classifier on your data.</li> </ol> <p>[[more about Machine Learing]]</p>"},{"location":"AI/CS231n/Linear%20classification-Support%20Vector%20Machine%2C%20Softmax/","title":"Linear classification-Support Vector Machine, Softmax","text":""},{"location":"AI/CS231n/Linear%20classification-Support%20Vector%20Machine%2C%20Softmax/#linear-classification-support-vector-machine-softmax","title":"Linear classification-Support Vector Machine, Softmax","text":"<p> \u7ea6 129 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"AI/CS231n/Linear%20classification-Support%20Vector%20Machine%2C%20Softmax/#linear-classifiaction","title":"Linear Classifiaction","text":"\\[ L_i = \\sum_{j\\neq y_i} \\max(0, s_j - s_{y_i} + \\Delta) \\] \\[ L = \\frac{1}{N} \\sum_i \\sum_{j\\neq y_i} \\left[ \\max(0, f(x_i; W)_j - f(x_i; W)_{y_i} + \\Delta) \\right] + \\lambda \\sum_k\\sum_l W_{k,l}^2 \\] \\[ L_i = -\\log\\left(\\frac{e^{f_{y_i}}}{ \\sum_j e^{f_j} }\\right) \\hspace{0.5in} \\text{or equivalently} \\hspace{0.5in} L_i = -f_{y_i} + \\log\\sum_j e^{f_j} \\] \\[ \\frac{e^{f_{y_i}}}{\\sum_j e^{f_j}} = \\frac{Ce^{f_{y_i}}}{C\\sum_j e^{f_j}} = \\frac{e^{f_{y_i} + \\log C}}{\\sum_j e^{f_j + \\log C}} \\] <p>![[Pasted image 20241031210509.png]]</p>"},{"location":"AI/CS231n/Numpy/","title":"Numpy","text":""},{"location":"AI/CS231n/Numpy/#python","title":"Python","text":"<p> \u7ea6 49 \u4e2a\u5b57  104 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"AI/CS231n/Numpy/#string","title":"string","text":"Python<pre><code>s = \"hello\"\nprint(s.capitalize())  # Capitalize a string; prints \"Hello\"\nprint(s.upper())       # Convert a string to uppercase; prints \"HELLO\"\nprint(s.rjust(7))      # Right-justify a string, padding with spaces; prints \"  hello\"\nprint(s.center(7))     # Center a string, padding with spaces; prints \" hello \"\nprint(s.replace('l', '(ell)'))  # Replace all instances of one substring with another;\n                                # prints \"he(ell)(ell)o\"\nprint('  world '.strip())  # Strip leading and trailing whitespace; prints \"world\"\n</code></pre>"},{"location":"AI/CS231n/Numpy/#containers","title":"Containers","text":"Python<pre><code>animals = ['cat', 'dog', 'monkey']\nfor idx, animal in enumerate(animals):\n    print('#%d: %s' % (idx + 1, animal))\n# Prints \"#1: cat\", \"#2: dog\", \"#3: monkey\", each on its own line\n</code></pre> <p>\u5217\u8868\u63a8\u5bfc\u5f0f</p> Python<pre><code>nums = [0, 1, 2, 3, 4]\neven_squares = [x ** 2 for x in nums if x % 2 == 0]\nprint(even_squares)  # Prints \"[0, 4, 16]\"\n</code></pre> <p>\u540c\u6837\u4e5f\u6709\u5b57\u5178\u63a8\u5bfc\u5f0f</p> <p>Tuples \u53ef\u4ee5\u7528\u4f5c\u5b57\u5178\u4e2d\u7684\u952e\u548c\u96c6\u5408\u7684\u5143\u7d20\uff0c\u4f46\u662f lists \u4e0d\u80fd</p>"},{"location":"AI/CS231n/Numpy/#numpy","title":"Numpy","text":"Python<pre><code>import numpy as np\n\n# Create a new array from which we will select elements\na = np.array([[1,2,3], [4,5,6], [7,8,9], [10, 11, 12]])\n\nprint(a)  # prints \"array([[ 1,  2,  3],\n          #                [ 4,  5,  6],\n          #                [ 7,  8,  9],\n          #                [10, 11, 12]])\"\n\n# Create an array of indices\nb = np.array([0, 2, 0, 1])\n\n# Select one element from each row of a using the indices in b\nprint(a[np.arange(4), b])  # Prints \"[ 1  6  7 11]\"\n\n# Mutate one element from each row of a using the indices in b\na[np.arange(4), b] += 10\n\nprint(a)  # prints \"array([[11,  2,  3],\n          #                [ 4,  5, 16],\n          #                [17,  8,  9],\n          #                [10, 21, 12]])\n</code></pre> Python<pre><code>import numpy as np\n\na = np.array([[1,2], [3, 4], [5, 6]])\n\nbool_idx = (a &gt; 2)   # Find the elements of a that are bigger than 2;\n                     # this returns a numpy array of Booleans of the same\n                     # shape as a, where each slot of bool_idx tells\n                     # whether that element of a is &gt; 2.\n\nprint(bool_idx)      # Prints \"[[False False]\n                     #          [ True  True]\n                     #          [ True  True]]\"\n\n# We use boolean array indexing to construct a rank 1 array\n# consisting of the elements of a corresponding to the True values\n# of bool_idx\nprint(a[bool_idx])  # Prints \"[3 4 5 6]\"\n\n# We can do all of the above in a single concise statement:\nprint(a[a &gt; 2])     # Prints \"[3 4 5 6]\"\n</code></pre> Python<pre><code>x = np.array([1, 2], dtype=np.int64)   # Force a particular datatype\nprint(x.dtype)                         # Prints \"int64\"\n</code></pre> Python<pre><code>import numpy as np\n\nx = np.array([[1,2],[3,4]], dtype=np.float64)\ny = np.array([[5,6],[7,8]], dtype=np.float64)\n\n# Elementwise sum; both produce the array\n# [[ 6.0  8.0]\n#  [10.0 12.0]]\nprint(x + y)\nprint(np.add(x, y))\n\n# Elementwise difference; both produce the array\n# [[-4.0 -4.0]\n#  [-4.0 -4.0]]\nprint(x - y)\nprint(np.subtract(x, y))\n\n# Elementwise product; both produce the array\n# [[ 5.0 12.0]\n#  [21.0 32.0]]\nprint(x * y)\nprint(np.multiply(x, y))\n\n# Elementwise division; both produce the array\n# [[ 0.2         0.33333333]\n#  [ 0.42857143  0.5       ]]\nprint(x / y)\nprint(np.divide(x, y))\n\n# Elementwise square root; produces the array\n# [[ 1.          1.41421356]\n#  [ 1.73205081  2.        ]]\nprint(np.sqrt(x))\n</code></pre> <p>\u5e7f\u64ad\u53ef\u4ee5\u907f\u514d\u5faa\u73af</p> Python<pre><code>import numpy as np\n\n# We will add the vector v to each row of the matrix x,\n# storing the result in the matrix y\nx = np.array([[1,2,3], [4,5,6], [7,8,9], [10, 11, 12]])\nv = np.array([1, 0, 1])\ny = x + v  # Add v to each row of x using broadcasting\nprint(y)  # Prints \"[[ 2  2  4]\n          #          [ 5  5  7]\n          #          [ 8  8 10]\n          #          [11 11 13]]\"\n</code></pre>"},{"location":"AI/CS231n/Numpy/#scipy","title":"SciPy","text":""},{"location":"AI/CS231n/Numpy/#matplotlib","title":"Matplotlib","text":""},{"location":"AI/EECS%20498-007/KNN/","title":"KNN","text":"<p>\u5bf9\u4e8e\u4e00\u4e2a\u5f85\u5206\u7c7b\u7684\u6837\u672c\uff0c\u627e\u5230\u8bad\u7ec3\u6570\u636e\u96c6\u4e2d\u4e0e\u5176\u6700\u63a5\u8fd1\u7684K\u4e2a\u6837\u672c\uff08\u5373\u6700\u8fd1\u90bb\uff09\uff0c\u7136\u540e\u6839\u636e\u8fd9K\u4e2a\u6837\u672c\u7684\u7c7b\u522b\u6765\u51b3\u5b9a\u5f85\u5206\u7c7b\u6837\u672c\u7684\u7c7b\u522b\u3002</p> <p> \u7ea6 374 \u4e2a\u5b57  100 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"AI/EECS%20498-007/KNN/#_1","title":"\u6570\u5b66\u63a8\u5bfc","text":"<p>\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u8bad\u7ec3\u6570\u636e\u96c6 \\(T = \\{(x_1, y_1), (x_2, y_2), \\ldots, (x_N, y_N)\\}\\)\uff0c\u5176\u4e2d \\(x_i\\) \u662f\u7279\u5f81\u5411\u91cf\uff0c \\(y_i\\) \u662f\u5bf9\u5e94\u7684\u7c7b\u522b\u6807\u7b7e\u3002\u5bf9\u4e8e\u4e00\u4e2a\u65b0\u7684\u5f85\u5206\u7c7b\u6837\u672c x\uff0cKNN\u7b97\u6cd5\u7684\u76ee\u6807\u662f\u9884\u6d4b\u5176\u7c7b\u522b \\(y\\) \u3002</p> <ol> <li>\u8ddd\u79bb\u5ea6\u91cf\uff1a\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u4e00\u4e2a\u8ddd\u79bb\u5ea6\u91cf\u6765\u8ba1\u7b97\u5f85\u5206\u7c7b\u6837\u672c \\(x\\) \u4e0e\u8bad\u7ec3\u96c6\u4e2d\u6bcf\u4e2a\u6837\u672c \\(x_i\\) \u4e4b\u95f4\u7684\u8ddd\u79bb\u3002\u5e38\u7528\u7684\u8ddd\u79bb\u5ea6\u91cf\u5305\u62ec\u6b27\u6c0f\u8ddd\u79bb\uff08Euclidean distance\uff09\u3001\u66fc\u54c8\u987f\u8ddd\u79bb\uff08Manhattan distance\uff09\u548c\u95f5\u53ef\u592b\u65af\u57fa\u8ddd\u79bb\uff08Minkowski distance\uff09\u3002\u4ee5\u6b27\u6c0f\u8ddd\u79bb\u4e3a\u4f8b\uff0c\u4e24\u4e2a\u6837\u672c \\(x\\) \u548c \\(x_i\\) \u4e4b\u95f4\u7684\u8ddd\u79bb\u5b9a\u4e49\u4e3a\uff1a</li> </ol> \\[    d(x, x_i) = \\sqrt{\\sum_{j=1}^{d} (x_j - x_{i,j})^2} \\] <p>\u5176\u4e2d\uff0c \\(d\\) \u662f\u7279\u5f81\u7684\u7ef4\u5ea6\u3002</p> <ol> <li>\u5bfb\u627e\u6700\u8fd1\u90bb\uff1a\u7136\u540e\uff0c\u6211\u4eec\u6839\u636e\u8ba1\u7b97\u51fa\u7684\u8ddd\u79bb\uff0c\u9009\u62e9\u8ddd\u79bb\u6700\u8fd1\u7684K\u4e2a\u6837\u672c\uff0c\u6784\u6210\u5f85\u5206\u7c7b\u6837\u672c\u7684\u90bb\u57df \\(N_k(x)\\)\u3002</li> <li>\u51b3\u7b56\u89c4\u5219\uff1a\u6700\u540e\uff0c\u6839\u636e\u90bb\u57df \\( N_k(x) \\) \u4e2d\u7684\u6837\u672c\u7c7b\u522b\uff0c\u901a\u8fc7\u591a\u6570\u6295\u7968\u7684\u65b9\u5f0f\u6765\u51b3\u5b9a\u5f85\u5206\u7c7b\u6837\u672c\u7684\u7c7b\u522b\u3002\u5373\uff1a</li> </ol> \\[     y = \\arg\\max_{c_j} \\sum_{x_i \\in N_k(x)} I(y_i = c_j) \\] <p>\u5176\u4e2d\uff0c \\(I\\) \u662f\u6307\u793a\u51fd\u6570\uff0c\u5f53 \\(y_i = c_j\\) \u65f6\u53d6\u503c\u4e3a1\uff0c\u5426\u5219\u4e3a0\u3002</p>"},{"location":"AI/EECS%20498-007/KNN/#_2","title":"\u4f5c\u4e1a\u4e2d\u7684\u5b9e\u73b0","text":"Python<pre><code>import torch\n\ndef compute_distances_two_loops(x_train, x_test):\n  num_train = x_train.shape[0]\n  num_test = x_test.shape[0]\n  dists = x_train.new_zeros(num_train, num_test)\n\n  for i in range(num_train):\n    for j in range(num_test):\n      dists[i,j] = ((x_train[i] - x_test[j]) ** 2).sum() ** (1/2)\n\n  return dists\n\ndef compute_distances_one_loop(x_train, x_test):\n  num_train = x_train.shape[0]\n  num_test = x_test.shape[0]\n  dists = x_train.new_zeros(num_train, num_test)\n\n  for i in range(num_train):\n    dists[i] = ((x_train[i] - x_test) ** 2).sum(dim=(1,2,3)) ** (1/2)\n\n  return dists\n\ndef compute_distances_no_loops(x_train, x_test):\n  num_train = x_train.shape[0]\n  num_test = x_test.shape[0]\n  dists = x_train.new_zeros(num_train, num_test)\n\n  A = x_train.reshape(num_train, -1)\n  B = x_test.reshape(num_test, -1)\n  AB2 = A.mm(B.T) * 2\n  dists = ((A ** 2).sum(dim=1).reshape(-1, 1) - AB2 + (B ** 2).sum(dim=1).reshape(1, -1)) ** (1/2)\n\n  return dists\n\ndef predict_labels(dists, y_train, k=1):\n  num_train, num_test = dists.shape\n  y_pred = torch.zeros(num_test, dtype=torch.int64)\n\n  values, indices = torch.topk(dists, k, dim=0, largest=False)\n  for i in range(indices.shape[1]):\n    _, idx = torch.max(y_train[indices[:, i]].bincount(), dim=0)\n    y_pred[i] = idx\n\n  return y_pred\n\nclass KnnClassifier:\n  def __init__(self, x_train, y_train):\n    self.x_train = x_train\n    self.y_train = y_train\n\n  def predict(self, x_test, k=1):\n    dists = compute_distances_no_loops(self.x_train, x_test)\n    y_test_pred = predict_labels(dists, self.y_train, k)\n    return y_test_pred\n\n  def check_accuracy(self, x_test, y_test, k=1, quiet=False):\n    y_test_pred = self.predict(x_test, k=k)\n    num_samples = x_test.shape[0]\n    num_correct = (y_test == y_test_pred).sum().item()\n    accuracy = 100.0 * num_correct / num_samples\n    msg = (f'Got {num_correct} / {num_samples} correct; accuracy is {accuracy:.2f}%')\n    if not quiet:\n      print(msg)\n    return accuracy\n\ndef knn_cross_validate(x_train, y_train, num_folds=5, k_choices=None):\n  if k_choices is None:\n    k_choices = [1, 3, 5, 8, 10, 12, 15, 20, 50, 100]\n\n  x_train_folds = torch.chunk(x_train, num_folds, dim=0)\n  y_train_folds = torch.chunk(y_train, num_folds, dim=0)\n\n  k_to_accuracies = {}\n\n  for k in k_choices:\n    list_of_acc = []\n    for num_fold in range(num_folds):\n      x_train_folds_local = [x for x in x_train_folds]\n      y_train_folds_local = [x for x in y_train_folds]\n      x_test = x_train_folds_local[num_fold]\n      y_test = y_train_folds_local[num_fold]\n      del x_train_folds_local[num_fold]\n      del y_train_folds_local[num_fold]\n      x_train = torch.cat(x_train_folds_local, dim=0)\n      y_train = torch.cat(y_train_folds_local, dim=0)\n      classifier = KnnClassifier(x_train, y_train)\n      list_of_acc.append(classifier.check_accuracy(x_test, y_test, k))\n    k_to_accuracies[k] = list_of_acc\n\n  return k_to_accuracies\n\ndef knn_get_best_k(k_to_accuracies):\n  best_k = 0\n  new_dict = {}\n  for k, accs in sorted(k_to_accuracies.items()):\n    new_dict[k] = sum(accs) / len(accs) \n  max_value = max(new_dict.values())\n  best_k = [k for k, v in new_dict.items() if v == max_value][0]\n  return best_k\n</code></pre>"},{"location":"AI/EECS%20498-007/Pytorch/","title":"pytorch \u7684\u57fa\u672c\u4f7f\u7528","text":""},{"location":"AI/EECS%20498-007/Pytorch/#pytorch","title":"pytorch \u7684\u57fa\u672c\u4f7f\u7528","text":"<p> \u7ea6 564 \u4e2a\u5b57  45 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> Python<pre><code># Create a rank 1 tensor from a Python list\na = torch.tensor([[1, 2, 3], [4, 5, 6]])\nprint('Here is a:')\nprint(a)\nprint('type(a): ', type(a))\nprint('rank of a: ', a.dim())\nprint('a.shape: ', a.shape)\n\ntorch.zeros(2, 3)\ntorch.ones(2, 3)\ntorch.eye(3)\ntorch.rand(2, 3)\ntorch.full((M, N), 3.14)\n\ny2 = torch.tensor([1, 2], dtype=torch.int64)\nprint(y2.dtype)\n\nx3 = x0.to(torch.float32)\n\nx0 = torch.eye(3, dtype=torch.float64) \u00a0# Shape (3, 3), dtype torch.float64\nx1 = torch.zeros_like(x0) \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 # Shape (3, 3), dtype torch.float64\nx2 = x0.new_zeros(4, 5) \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 # Shape (4, 5), dtype torch.float64\nx3 = torch.ones(6, 7).to(x0) \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0# Shape (6, 7), dtype torch.float64\n</code></pre> <p>Even though PyTorch provides a large number of numeric datatypes, the most commonly used datatypes are:</p> <ul> <li><code>torch.float32</code>: Standard floating-point type; used to store learnable parameters, network activations, etc. Nearly all arithmetic is done using this type.</li> <li><code>torch.int64</code>: Typically used to store indices</li> <li><code>torch.bool</code>: Stores boolean values: 0 is false and 1 is true</li> <li><code>torch.float16</code>: Used for mixed-precision arithmetic, usually on NVIDIA GPUs with tensor cores. You won't need to worry about this datatype in this course.</li> <li>\u6ce8\u610f <code>a[:, 1]</code> \u548c <code>a[:, 1:2]</code> \u7684\u533a\u522b\uff0c\u540e\u8005\u4f1a\u4fdd\u7559\u7684\u591a\u4e00\u70b9</li> <li><code>clone()</code> \u4ee5\u540e\u7684\u53d8\u91cf\u8ddf\u539f\u53d8\u91cf\u662f\u72ec\u7acb\u7684\uff0c\u4f46\u662f\u7b49\u53f7\u76f4\u63a5\u8d4b\u503c\u7684\u662f\u540c\u4e00\u4e2a\u6307\u9488</li> </ul> Python<pre><code>mask = (a &gt; 3)\nprint('\\nMask tensor:')\nprint(mask)\n# Mask tensor: tensor([[False, False], [False, True], [ True, True]])\n</code></pre> <ul> <li>As its name implies, a tensor returned by <code>.view()</code> shares the same data as the input, so changes to one will affect the other.</li> </ul> Reshape\u548cview\u7684\u533a\u522b <ol> <li>\u5185\u5b58\u8fde\u7eed\u6027\uff1a<ul> <li><code>view</code> \u8981\u6c42\u539f\u59cb\u5f20\u91cf\u548c\u76ee\u6807\u5f20\u91cf\u5728\u5185\u5b58\u4e2d\u662f\u8fde\u7eed\u7684\u3002\u5982\u679c\u539f\u59cb\u5f20\u91cf\u4e0d\u662f\u8fde\u7eed\u7684\uff0c <code>view</code> \u4f1a\u9996\u5148\u8c03\u7528 <code>contiguous</code> \u65b9\u6cd5\u4f7f\u5176\u8fde\u7eed\uff0c\u7136\u540e\u6539\u53d8\u5f62\u72b6\u3002\u5982\u679c\u5f20\u91cf\u5df2\u7ecf\u662f\u8fde\u7eed\u7684\uff0c <code>view</code> \u64cd\u4f5c\u4e0d\u4f1a\u590d\u5236\u6570\u636e\u3002</li> <li><code>reshape</code>\u4e0d\u8981\u6c42\u539f\u59cb\u5f20\u91cf\u662f\u8fde\u7eed\u7684\u3002\u5982\u679c\u539f\u59cb\u5f20\u91cf\u4e0d\u662f\u8fde\u7eed\u7684\uff0c<code>reshape</code>\u4f1a\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u5f20\u91cf\u5e76\u590d\u5236\u6570\u636e\uff0c\u4ee5\u786e\u4fdd\u65b0\u5f20\u91cf\u662f\u8fde\u7eed\u7684\u3002</li> </ul> </li> <li>\u8fd4\u56de\u503c<ul> <li><code>view</code>\u8fd4\u56de\u4e00\u4e2a\u65b0\u7684\u5f20\u91cf\uff0c\u5b83\u4e0e\u539f\u59cb\u5f20\u91cf\u5171\u4eab\u76f8\u540c\u7684\u6570\u636e\uff0c\u4f46\u662f\u6709\u4e0d\u540c\u7684\u5f62\u72b6\u3002\u5982\u679c\u539f\u59cb\u5f20\u91cf\u4e0d\u662f\u8fde\u7eed\u7684\uff0c<code>view</code>\u4f1a\u8fd4\u56de\u4e00\u4e2a\u526f\u672c\u3002</li> <li><code>reshape</code>\u4e5f\u8fd4\u56de\u4e00\u4e2a\u65b0\u7684\u5f20\u91cf\uff0c\u4f46\u603b\u662f\u521b\u5efa\u6570\u636e\u7684\u526f\u672c\uff0c\u5373\u4f7f\u539f\u59cb\u5f20\u91cf\u662f\u8fde\u7eed\u7684\u3002</li> </ul> </li> <li>\u4f7f\u7528\u573a\u666f\uff1a<ul> <li>\u5f53\u4f60\u786e\u5b9a\u539f\u59cb\u5f20\u91cf\u662f\u8fde\u7eed\u7684\uff0c\u5e76\u4e14\u4f60\u60f3\u8981\u907f\u514d\u4e0d\u5fc5\u8981\u7684\u6570\u636e\u590d\u5236\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528<code>view</code>\u3002</li> <li>\u5f53\u4f60\u4e0d\u786e\u5b9a\u539f\u59cb\u5f20\u91cf\u662f\u5426\u8fde\u7eed\uff0c\u6216\u8005\u4f60\u60f3\u8981\u786e\u4fdd\u64cd\u4f5c\u4e0d\u4f1a\u56e0\u975e\u8fde\u7eed\u6027\u800c\u5931\u8d25\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528<code>reshape</code>\u3002</li> </ul> </li> <li>\u53c2\u6570\uff1a<ul> <li><code>view</code>\u7684\u53c2\u6570\u662f\u76ee\u6807\u5f62\u72b6\u7684\u7ef4\u5ea6\u3002</li> <li><code>reshape</code>\u7684\u53c2\u6570\u4e5f\u662f\u76ee\u6807\u5f62\u72b6\u7684\u7ef4\u5ea6\uff0c\u4f46\u5b83\u53ef\u4ee5\u63a5\u53d7\u4e00\u4e2a\u989d\u5916\u7684\u53c2\u6570<code>inplace</code>\uff0c\u5982\u679c\u8bbe\u7f6e\u4e3a<code>True</code>\uff0c\u5219\u4f1a\u5728\u539f\u5730\u4fee\u6539\u5f20\u91cf\u7684\u5f62\u72b6\u3002</li> </ul> </li> </ol> <ul> <li><code>torch.sin(x)</code> \u548c <code>x.sin()</code> \u662f\u7b49\u4ef7\u7684</li> </ul> Python<pre><code>x = torch.tensor([[1, 2, 3],\n\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 [4, 5, 6]], dtype=torch.float32)\nprint('Original tensor:')\nprint(x)\n\nprint('\\nSum over entire tensor:')\nprint(torch.sum(x))\nprint(x.sum())\n\n# We can sum over each row:\nprint('\\nSum of each row:')\nprint(torch.sum(x, dim=0))\nprint(x.sum(dim=0))\n\n# Sum over each column:\nprint('\\nSum of each column:')\nprint(torch.sum(x, dim=1))\nprint(x.sum(dim=1))\n</code></pre> <ul> <li><code>torch.dot</code>: Computes inner product of vectors</li> <li><code>torch.mm</code>: Computes matrix-matrix products</li> <li><code>torch.mv</code>: Computes matrix-vector products</li> <li><code>torch.addmm</code> / <code>torch.addmv</code>: Computes matrix-matrix and matrix-vector multiplications plus a bias</li> <li><code>torch.bmm</code> / <code>torch.baddmm</code>: Batched versions of <code>torch.mm</code> and <code>torch.addmm</code>, respectively</li> <li><code>torch.matmul</code>: General matrix product that performs different operations depending on the rank of the inputs. Confusingly, this is similar to <code>np.dot</code> in numpy.</li> </ul>"},{"location":"AI/EECS%20498-007/linear_classifer/","title":"Linear classifer","text":""},{"location":"AI/EECS%20498-007/linear_classifer/#_1","title":"\u539f\u7406","text":"<p> \u7ea6 677 \u4e2a\u5b57  216 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 6 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>\u4e24\u79cd\u7ebf\u6027\u5206\u7c7b\u5668\uff1a\u652f\u6301\u5411\u91cf\u673a\uff08SVM\uff09\u548cSoftmax\u5206\u7c7b\u5668\u3002\u8fd9\u4e24\u79cd\u5206\u7c7b\u5668\u90fd\u662f\u76d1\u7763\u5b66\u4e60\u7b97\u6cd5\uff0c\u7528\u4e8e\u5206\u7c7b\u4efb\u52a1\u3002</p>"},{"location":"AI/EECS%20498-007/linear_classifer/#svm","title":"\u652f\u6301\u5411\u91cf\u673a\uff08SVM\uff09","text":"<p>SVM\u7684\u76ee\u6807\u662f\u627e\u5230\u4e00\u4e2a\u8d85\u5e73\u9762\uff0c\u5b83\u53ef\u4ee5\u6700\u5927\u5316\u4e0d\u540c\u7c7b\u522b\u4e4b\u95f4\u7684\u8fb9\u754c\u3002\u8fd9\u4e2a\u8d85\u5e73\u9762\u88ab\u79f0\u4e3a\u6700\u4f18\u5206\u5272\u8d85\u5e73\u9762\u3002\u5bf9\u4e8e\u4e8c\u5206\u7c7b\u95ee\u9898\uff0cSVM\u7684\u635f\u5931\u51fd\u6570\u53ef\u4ee5\u8868\u793a\u4e3a\uff1a</p> \\[ L(W, b) = \\frac{1}{N} \\sum_{i=1}^{N} \\max(0, 1 - y_i (W \\cdot x_i + b)) \\] <p>\u5176\u4e2d\uff0c\\(W\\) \u662f\u6743\u91cd\u5411\u91cf\uff0c\\(b\\) \u662f\u504f\u7f6e\u9879\uff0c\\(x_i\\) \u662f\u8f93\u5165\u7279\u5f81\uff0c\\(y_i\\) \u662f\u6807\u7b7e\uff08-1\u62161\uff09\uff0c\\(N\\) \u662f\u6837\u672c\u6570\u91cf\u3002</p> <p>\u4e3a\u4e86\u5b9e\u73b0\u591a\u5206\u7c7b\uff0c\u6211\u4eec\u4f7f\u7528\u7ed3\u6784\u5316SVM\u635f\u5931\u51fd\u6570\uff0c\u5b83\u8003\u8651\u4e86\u6bcf\u4e2a\u7c7b\u522b\u7684\u5206\u6570\uff0c\u5e76\u5c1d\u8bd5\u6700\u5927\u5316\u6b63\u786e\u7c7b\u522b\u7684\u5206\u6570\u4e0e\u6b21\u9ad8\u7c7b\u522b\u5206\u6570\u4e4b\u95f4\u7684\u5dee\u8ddd\u3002\u635f\u5931\u51fd\u6570\u53ef\u4ee5\u8868\u793a\u4e3a\uff1a</p> \\[ L(W) = \\frac{1}{N} \\sum_{i=1}^{N} \\sum_{j \\neq y_i} \\max(0, \\text{score}_j - \\text{score}_{y_i} + \\Delta) \\] <p>\u5176\u4e2d\uff0c\\(\\text{score}_j = W_j \\cdot x_i\\)\uff0c\\(\\Delta\\) \u662f\u4e00\u4e2a\u5e38\u6570\uff0c\u901a\u5e38\u8bbe\u7f6e\u4e3a1\u3002</p>"},{"location":"AI/EECS%20498-007/linear_classifer/#softmax","title":"Softmax\u5206\u7c7b\u5668","text":"<p>Softmax\u5206\u7c7b\u5668\u4f7f\u7528Softmax\u51fd\u6570\u5c06\u8f93\u5165\u7279\u5f81\u6620\u5c04\u5230\u6982\u7387\u5206\u5e03\u4e0a\u3002\u5bf9\u4e8e\u6bcf\u4e2a\u6837\u672c\uff0cSoftmax\u51fd\u6570\u8f93\u51fa\u6bcf\u4e2a\u7c7b\u522b\u7684\u6982\u7387\u3002Softmax\u51fd\u6570\u5b9a\u4e49\u4e3a\uff1a</p> \\[ \\text{softmax}(z_i) = \\frac{e^{z_i}}{\\sum_{j=1}^{K} e^{z_j}} \\] <p>\u5176\u4e2d\uff0c\\(z_i\\) \u662f\u7b2c\\(i\\)\u4e2a\u7c7b\u522b\u7684\u5206\u6570\uff0c\\(K\\) \u662f\u7c7b\u522b\u603b\u6570\u3002</p> <p>Softmax\u5206\u7c7b\u5668\u7684\u635f\u5931\u51fd\u6570\u662f\u4ea4\u53c9\u71b5\u635f\u5931\uff0c\u53ef\u4ee5\u8868\u793a\u4e3a\uff1a</p> \\[ L(W) = -\\frac{1}{N} \\sum_{i=1}^{N} \\sum_{j=1}^{K} y_{ij} \\log(\\text{softmax}(z_j)) \\] <p>\u5176\u4e2d\uff0c\\(y_{ij}\\) \u662f\u4e00\u4e2a\u6307\u793a\u53d8\u91cf\uff0c\u5982\u679c\u6837\u672c\\(i\\)\u5c5e\u4e8e\u7c7b\u522b\\(j\\)\uff0c\u5219\u4e3a1\uff0c\u5426\u5219\u4e3a0\u3002</p>"},{"location":"AI/EECS%20498-007/linear_classifer/#_2","title":"\u6b63\u5219\u5316","text":"<p>\u4e3a\u4e86\u9632\u6b62\u8fc7\u62df\u5408\uff0c\u6211\u4eec\u5728\u635f\u5931\u51fd\u6570\u4e2d\u6dfb\u52a0\u4e86\u6b63\u5219\u5316\u9879\u3002L2\u6b63\u5219\u5316\u7684\u635f\u5931\u51fd\u6570\u53ef\u4ee5\u8868\u793a\u4e3a\uff1a</p> \\[ L(W) = L(W) + \\lambda \\lVert W \\rVert^2 \\] <p>\u5176\u4e2d\uff0c\\(\\lambda\\) \u662f\u6b63\u5219\u5316\u5f3a\u5ea6\u3002</p>"},{"location":"AI/EECS%20498-007/linear_classifer/#_3","title":"\u4ee3\u7801\u5b9e\u73b0","text":"<p>\u4ee3\u7801\u4e2d\u5b9e\u73b0\u4e86\u4e24\u79cd\u635f\u5931\u51fd\u6570\u7684\u6734\u7d20\u7248\u672c\uff08<code>svm_loss_naive</code> \u548c <code>softmax_loss_naive</code>\uff09\u548c\u5411\u91cf\u5316\u7248\u672c\uff08<code>svm_loss_vectorized</code> \u548c <code>softmax_loss_vectorized</code>\uff09\u3002\u5411\u91cf\u5316\u7248\u672c\u901a\u8fc7\u907f\u514d\u663e\u5f0f\u5faa\u73af\u6765\u63d0\u9ad8\u8ba1\u7b97\u6548\u7387\u3002</p> <p>\u8bad\u7ec3\u8fc7\u7a0b\uff08<code>train_linear_classifier</code>\uff09\u4f7f\u7528\u968f\u673a\u68af\u5ea6\u4e0b\u964d\uff08SGD\uff09\u6765\u4f18\u5316\u635f\u5931\u51fd\u6570\u3002\u5728\u6bcf\u6b21\u8fed\u4ee3\u4e2d\uff0c\u6211\u4eec\u968f\u673a\u62bd\u53d6\u4e00\u4e2a\u6279\u6b21\u7684\u6837\u672c\uff0c\u8ba1\u7b97\u635f\u5931\u548c\u68af\u5ea6\uff0c\u7136\u540e\u66f4\u65b0\u6743\u91cd\u3002</p> <p>\u9884\u6d4b\u8fc7\u7a0b\uff08<code>predict_linear_classifier</code>\uff09\u4f7f\u7528\u8bad\u7ec3\u597d\u7684\u6743\u91cd\u6765\u9884\u6d4b\u65b0\u6837\u672c\u7684\u7c7b\u522b\u3002</p>"},{"location":"AI/EECS%20498-007/linear_classifer/#_4","title":"\u8d85\u53c2\u6570\u641c\u7d22","text":"<p>\u4ee3\u7801\u4e2d\u8fd8\u5305\u542b\u4e86\u8d85\u53c2\u6570\u641c\u7d22\u7684\u51fd\u6570\uff08<code>svm_get_search_params</code> \u548c <code>softmax_get_search_params</code>\uff09\uff0c\u5b83\u4eec\u8fd4\u56de\u4e0d\u540c\u7684\u5b66\u4e60\u7387\u548c\u6b63\u5219\u5316\u5f3a\u5ea6\u7684\u5019\u9009\u503c\uff0c\u4ee5\u4fbf\u627e\u5230\u6700\u4f73\u7684\u6a21\u578b\u53c2\u6570\u3002</p>"},{"location":"AI/EECS%20498-007/linear_classifer/#_5","title":"\u4f5c\u4e1a\u5b9e\u73b0","text":"Python<pre><code>import torch\nimport random\nfrom abc import abstractmethod\n\ndef hello_linear_classifier():\n  print('Hello from linear_classifier.py!')\n\nclass LinearClassifier(object):\n  def __init__(self):\n    random.seed(0)\n    torch.manual_seed(0)\n    self.W = None\n\n  def train(self, X_train, y_train, learning_rate=1e-3, reg=1e-5, num_iters=100,\n            batch_size=200, verbose=False):\n    train_args = (self.loss, self.W, X_train, y_train, learning_rate, reg,\n                  num_iters, batch_size, verbose)\n    self.W, loss_history = train_linear_classifier(*train_args)\n    return loss_history\n\n  def predict(self, X):\n    return predict_linear_classifier(self.W, X)\n\n  @abstractmethod\n  def loss(self, W, X_batch, y_batch, reg):\n    raise NotImplementedError\n\n  def _loss(self, X_batch, y_batch, reg):\n    self.loss(self.W, X_batch, y_batch, reg)\n\n  def save(self, path):\n    torch.save({'W': self.W}, path)\n    print(\"Saved in {}\".format(path))\n\n  def load(self, path):\n    W_dict = torch.load(path, map_location='cpu')\n    self.W = W_dict['W']\n    print(\"load checkpoint file: {}\".format(path))\n\n\nclass LinearSVM(LinearClassifier):\n  def loss(self, W, X_batch, y_batch, reg):\n    return svm_loss_vectorized(W, X_batch, y_batch, reg)\n\n\nclass Softmax(LinearClassifier):\n  def loss(self, W, X_batch, y_batch, reg):\n    return softmax_loss_vectorized(W, X_batch, y_batch, reg)\n\n\ndef svm_loss_naive(W, X, y, reg):\n  dW = torch.zeros_like(W)\n  num_classes = W.shape[1]\n  num_train = X.shape[0]\n  loss = 0.0\n  for i in range(num_train):\n    scores = W.t().mv(X[i])\n    correct_class_score = scores[y[i]]\n    for j in range(num_classes):\n      if j == y[i]:\n        continue\n      margin = scores[j] - correct_class_score + 1\n      if margin &gt; 0:\n        loss += margin\n        dW[:, j] += X[i]\n        dW[:, y[i]] -= X[i]\n\n  loss /= num_train\n  loss += reg * torch.sum(W * W)\n  dW /= num_train\n  dW += 2 * reg * W\n\n  return loss, dW\n\n\ndef svm_loss_vectorized(W, X, y, reg):\n  loss = 0.0\n  dW = torch.zeros_like(W)\n  num_classes = W.shape[1]\n  num_train = X.shape[0]\n  scores = X.mm(W)\n  correct_class_score = scores[range(num_train), y]\n  margin = scores - correct_class_score.view(-1, 1) + 1\n  margin[range(num_train), y] = 0\n  mask = (margin &gt; 0)\n  loss = margin[mask].sum()\n  mask_correct_y = torch.zeros_like(scores, dtype=torch.bool)\n  mask_correct_y[range(num_train), y] = True\n  margin[margin &gt; 0] = 1\n  margin[margin &lt; 0] = 0\n  margin[mask_correct_y] = torch.sum(margin, axis=1) * -1\n  dW = margin.T.mm(X).T\n  loss /= num_train\n  dW /= num_train\n  loss += reg * torch.sum(W * W)\n  dW += 2 * reg * W\n\n  return loss, dW\n\n\ndef sample_batch(X, y, num_train, batch_size):\n  indices = torch.randint(num_train, (batch_size,))\n  y_batch = y[indices]\n  X_batch = X[indices]\n  return X_batch, y_batch\n\n\ndef train_linear_classifier(loss_func, W, X, y, learning_rate=1e-3,\n                            reg=1e-5, num_iters=100, batch_size=200,\n                            verbose=False):\n  num_train, dim = X.shape\n  if W is None:\n    num_classes = torch.max(y) + 1\n    W = 0.000001 * torch.randn(dim, num_classes, device=X.device, dtype=X.dtype)\n  else:\n    num_classes = W.shape[1]\n\n  loss_history = []\n  for it in range(num_iters):\n    X_batch, y_batch = sample_batch(X, y, num_train, batch_size)\n    loss, grad = loss_func(W, X_batch, y_batch, reg)\n    loss_history.append(loss.item())\n    W -= learning_rate * grad\n    if verbose and it % 100 == 0:\n      print('iteration %d / %d: loss %f' % (it, num_iters, loss))\n\n  return W, loss_history\n\n\ndef predict_linear_classifier(W, X):\n  y_pred = torch.zeros(X.shape[0], dtype=torch.int64)\n  _, y_pred = X.mm(W).max(dim=1)\n  return y_pred\n\n\ndef svm_get_search_params():\n  learning_rates = [0.000001, 0.0001, 0.001, 0.005, 0.01, 0.05]\n  regularization_strengths = [0.001, 0.5, 1, 3]\n  return learning_rates, regularization_strengths\n\n\ndef test_one_param_set(cls, data_dict, lr, reg, num_iters=2000):\n  train_acc = 0.0\n  val_acc = 0.0\n  cls.train(data_dict['X_train'], data_dict['y_train'], lr, reg, num_iters,\n            batch_size=200, verbose=False)\n  y_train_pred = cls.predict(data_dict['X_train'])\n  train_acc = 100.0 * (data_dict['y_train'] == y_train_pred).double().mean().item()\n\n  y_test_pred = cls.predict(data_dict['X_val'])\n  val_acc = 100.0 * (data_dict['y_val'] == y_test_pred).double().mean().item()\n\n  return cls, train_acc, val_acc\n\n\ndef softmax_loss_naive(W, X, y, reg):\n  loss = 0.0\n  dW = torch.zeros_like(W)\n  num_classes = W.shape[1]\n  num_train = X.shape[0]\n\n  scores = W.t().mv(X[0])\n  correct_class_score = scores[y[0]]\n\n  for i in range(num_train):\n    scores = W.t().mv(X[i])\n    scores = scores - scores.max()\n    correct_class_score = scores[y[i]]\n    loss += -correct_class_score + torch.log(torch.exp(scores).sum())\n    for j in range(num_classes):\n      if j == y[i]:\n        dW[:, j] += torch.exp(scores[j]) / torch.exp(scores).sum() * X[i, :] - X[i, :]\n      else:\n        dW[:, j] += torch.exp(scores[j]) / torch.exp(scores).sum() * X[i, :]\n\n  loss /= num_train\n  loss += reg * torch.sum(W * W)\n  dW /= num_train\n  dW += 2 * reg * W\n\n  return loss, dW\n\n\ndef softmax_loss_vectorized(W, X, y, reg):\n  loss = 0.0\n  dW = torch.zeros_like(W)\n  num_classes = W.shape[1]\n  num_train = X.shape[0]\n\n\n  scores = X.mm(W)\n  val, _ = scores.max(dim=1)\n  scores = scores - val.view(-1, 1)\n  exp_scores = scores.exp()\n  exp_scores_sum = exp_scores.sum(dim=1)\n  exp_scores_sum_log = exp_scores_sum.log()\n  correct_class_scores = scores[range(num_train), y]\n  loss = (exp_scores_sum_log - correct_class_scores).sum()\n  zeros = torch.zeros((num_train, num_classes), dtype=torch.float64, device='cuda')\n  zeros[range(num_train), y] = -1\n  minus_X = zeros.t().mm(X)\n  dW += minus_X.t()\n  dW += ((exp_scores / exp_scores_sum.view(-1, 1)).t().mm(X)).t()\n\n  loss /= num_train\n  loss += reg * torch.sum(W * W)\n  dW /= num_train\n  dW += 2 * reg * W\n\n  return loss, dW\n\n\ndef softmax_get_search_params():\n  learning_rates = [1e-4, 1e-3,1e-2, 1e-1, 1]\n  regularization_strengths = [1e-4, 1e-3, 1e-2, 1e-1] \n  return learning_rates, regularization_strengths\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/","title":"FFB6D\u73af\u5883\u914d\u7f6e\u6307\u5357\uff1a\u539f\u751f\u7cfb\u7edf\u5b89\u88c5","text":""},{"location":"AI/FFB6D/FFB6D_Conda/#ffb6d","title":"FFB6D\u73af\u5883\u914d\u7f6e\u6307\u5357\uff1a\u539f\u751f\u7cfb\u7edf\u5b89\u88c5","text":"<p> \u7ea6 293 \u4e2a\u5b57  96 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"AI/FFB6D/FFB6D_Conda/#1","title":"1. \u7cfb\u7edf\u8981\u6c42","text":"<ul> <li>Ubuntu 20.04/22.04/24.04</li> <li>NVIDIA GPU\uff08\u652f\u6301CUDA\uff09</li> <li>\u81f3\u5c118GB\u5185\u5b58</li> <li>\u81f3\u5c1130GB\u78c1\u76d8\u7a7a\u95f4</li> </ul>"},{"location":"AI/FFB6D/FFB6D_Conda/#2","title":"2. \u57fa\u7840\u73af\u5883\u914d\u7f6e","text":""},{"location":"AI/FFB6D/FFB6D_Conda/#21-nvidia","title":"2.1 \u5b89\u88c5NVIDIA\u9a71\u52a8","text":"Bash<pre><code># \u6dfb\u52a0NVIDIA\u5305\u4ed3\u5e93\nsudo add-apt-repository ppa:graphics-drivers/ppa\nsudo apt-get update\n\n# \u5b89\u88c5NVIDIA\u9a71\u52a8\nsudo apt-get install -y nvidia-driver-535  # \u6839\u636e\u9700\u8981\u9009\u62e9\u7248\u672c\n\n# \u91cd\u542f\u7cfb\u7edf\nsudo reboot\n\n# \u9a8c\u8bc1\u5b89\u88c5\nnvidia-smi\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#22-cudacudnn","title":"2.2 \u5b89\u88c5CUDA\u548ccuDNN","text":"Bash<pre><code># \u4e0b\u8f7d\u5e76\u5b89\u88c5CUDA 11.0\nwget https://developer.download.nvidia.com/compute/cuda/11.0.3/local_installers/cuda_11.0.3_450.51.06_linux.run\nsudo sh cuda_11.0.3_450.51.06_linux.run\n\n# \u914d\u7f6e\u73af\u5883\u53d8\u91cf\necho 'export PATH=/usr/local/cuda-11.0/bin:$PATH' &gt;&gt; ~/.bashrc\necho 'export LD_LIBRARY_PATH=/usr/local/cuda-11.0/lib64:$LD_LIBRARY_PATH' &gt;&gt; ~/.bashrc\nsource ~/.bashrc\n\n# \u4e0b\u8f7d\u5e76\u5b89\u88c5cuDNN 8.0\n# \u6ce8\uff1a\u9700\u8981\u4eceNVIDIA\u5f00\u53d1\u8005\u7f51\u7ad9\u4e0b\u8f7dcuDNN v8.0\uff0c\u89e3\u538b\u540e\uff1a\nsudo cp cuda/include/cudnn*.h /usr/local/cuda/include\nsudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64\nsudo chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/lib64/libcudnn*\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#23","title":"2.3 \u5b89\u88c5\u7cfb\u7edf\u4f9d\u8d56","text":"Bash<pre><code>sudo apt-get update\nsudo apt-get install -y \\\n    python3.6 \\\n    python3.6-dev \\\n    python3-pip \\\n    git \\\n    cmake \\\n    build-essential \\\n    libopencv-dev \\\n    libglib2.0-0 \\\n    libsm6 \\\n    libxext6 \\\n    libxrender-dev \\\n    libboost-all-dev \\\n    libeigen3-dev\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#24-python","title":"2.4 \u914d\u7f6ePython\u73af\u5883","text":"Bash<pre><code># \u8bbe\u7f6ePython 3.6\u4e3a\u9ed8\u8ba4\u7248\u672c\nsudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.6 1\nsudo update-alternatives --set python3 /usr/bin/python3.6\n\n# \u914d\u7f6epip\u955c\u50cf\u6e90\npip3 config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple\n\n# \u5347\u7ea7pip\npython3 -m pip install --upgrade pip\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#3-pytorch","title":"3. \u5b89\u88c5PyTorch\u548c\u4f9d\u8d56\u5305","text":""},{"location":"AI/FFB6D/FFB6D_Conda/#31-pytorch","title":"3.1 \u5b89\u88c5PyTorch","text":"Bash<pre><code>pip3 install torch==1.10.2+cu113 torchvision==0.11.3+cu113 -f https://download.pytorch.org/whl/torch_stable.html\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#32","title":"3.2 \u5b89\u88c5\u9879\u76ee\u4f9d\u8d56","text":"<p>\u521b\u5efarequirements.txt\u5e76\u5b89\u88c5\u4f9d\u8d56\uff1a</p> Bash<pre><code>pip3 install -r requirements.txt\n</code></pre> <p>requirements.txt\u5185\u5bb9\uff1a </p>Text Only<pre><code>h5py         \nnumpy              \npyyaml==5.4.1\nenum34        \nfuture           \nscipy==1.4.1          \nopencv_contrib_python==3.4.2.16               \ntransforms3d==0.3.1     \nscikit_image==0.13.1     \nlmdb==0.94              \nsetuptools==41.0.0    \ncffi==1.11.5         \neasydict==1.7      \nplyfile==0.6      \npillow==8.2.0 \ndataclasses\nglumpy                                                      \ntqdm\ntensorboardX \npandas\nscikit-learn         \nscipy \ntermcolor\npybind11\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#4","title":"4. \u7f16\u8bd1\u548c\u5b89\u88c5\u7279\u6b8a\u7ec4\u4ef6","text":""},{"location":"AI/FFB6D/FFB6D_Conda/#41-apex","title":"4.1 \u7f16\u8bd1apex","text":"Bash<pre><code>git clone https://github.com/NVIDIA/apex\ncd apex\nexport TORCH_CUDA_ARCH_LIST=\"6.0;6.1;6.2;7.0;7.5\"\npython setup.py install -v\ncd ..\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#42-normalspeed","title":"4.2 \u5b89\u88c5\u548c\u7f16\u8bd1normalspeed","text":"Bash<pre><code># 1. \u51c6\u5907OpenCV\u73af\u5883\npip uninstall opencv-python opencv-python-headless -y\npip install opencv-python==4.5.3.56\n\n# 2. \u514b\u9686\u5e76\u5b89\u88c5normalspeed\ngit clone https://github.com/hfutcgncas/normalspeed.git\ncd normalspeed/normalSpeed\n\n# \u5b89\u88c5\u7f16\u8bd1\u4f9d\u8d56\nsudo apt-get install python3-pybind11\npip3 install Cython==0.29.15\n\n# \u6e05\u7406\u5e76\u91cd\u65b0\u5b89\u88c5\nrm -rf build/ dist/ *.egg-info/\npython3 setup.py install --user\ncd ../..\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#5-ffb6d","title":"5. \u514b\u9686\u548c\u914d\u7f6eFFB6D","text":"Bash<pre><code># \u514b\u9686\u4ee3\u7801\ngit clone https://github.com/ethnhe/FFB6D.git\ncd FFB6D\n\n# \u521b\u5efa\u5fc5\u8981\u7684\u76ee\u5f55\nmkdir -p datasets models train_log\n\n# \u914d\u7f6e\u73af\u5883\u53d8\u91cf\nexport PYTHONPATH=$PYTHONPATH:$(pwd)\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#6","title":"6. \u9a8c\u8bc1\u5b89\u88c5","text":"Bash<pre><code># \u9a8c\u8bc1CUDA\u652f\u6301\npython3 -c \"import torch; print('CUDA available:', torch.cuda.is_available())\"\n\n# \u9a8c\u8bc1apex\u5b89\u88c5\npython3 -c \"from apex import amp; print('APEX installed')\"\n\n# \u9a8c\u8bc1normalspeed\u5b89\u88c5\npython3 -c \"import normalSpeed; print('normalspeed installed')\"\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#7","title":"7. \u5e38\u89c1\u95ee\u9898","text":""},{"location":"AI/FFB6D/FFB6D_Conda/#71","title":"7.1 \u7f51\u7edc\u95ee\u9898","text":"Bash<pre><code># \u4f7f\u7528\u4ee3\u7406\uff08\u5982\u9700\u8981\uff09\nexport http_proxy=\"http://proxy:port\"\nexport https_proxy=\"http://proxy:port\"\n\n# \u6216\u4f7f\u7528\u56fd\u5185\u955c\u50cf\u6e90\npip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Conda/#72","title":"7.2 \u7248\u672c\u517c\u5bb9\u6027\u95ee\u9898","text":"<ul> <li>\u786e\u4fddNVIDIA\u9a71\u52a8\u7248\u672c\u652f\u6301CUDA 11.0</li> <li>\u786e\u4fddPython\u5305\u7248\u672c\u76f8\u4e92\u517c\u5bb9</li> <li>\u68c0\u67e5CUDA\u7248\u672c\u4e0ePyTorch\u7248\u672c\u7684\u5339\u914d</li> </ul>"},{"location":"AI/FFB6D/FFB6D_Conda/#73","title":"7.3 \u7f16\u8bd1\u9519\u8bef","text":"<ul> <li>\u786e\u4fdd\u5df2\u5b89\u88c5\u6240\u6709\u5fc5\u8981\u7684\u7f16\u8bd1\u5de5\u5177</li> <li>\u68c0\u67e5CUDA\u8def\u5f84\u914d\u7f6e\u662f\u5426\u6b63\u786e</li> <li>\u786e\u8ba4\u7cfb\u7edf\u5e93\u7248\u672c\u662f\u5426\u6ee1\u8db3\u8981\u6c42</li> </ul>"},{"location":"AI/FFB6D/FFB6D_Conda/#8","title":"8. \u8bad\u7ec3","text":"<p>\u6309\u7167\u5b98\u65b9\u6587\u6863\u914d\u7f6eLineMOD\u6570\u636e\u96c6\u5e76\u5f00\u59cb\u8bad\u7ec3\u3002</p>"},{"location":"AI/FFB6D/FFB6D_Conda/#_1","title":"\u53c2\u8003\u8d44\u6599","text":"<ol> <li>FFB6D\u9879\u76ee</li> <li>CUDA\u5b89\u88c5\u6307\u5357</li> <li>PyTorch\u5b89\u88c5\u6307\u5357</li> <li>\u3010\u8bba\u6587\u7b14\u8bb0\u3011FFB6D | \u9a6c\u6d69\u98de\u4e28\u535a\u5ba2</li> </ol>"},{"location":"AI/FFB6D/FFB6D_Docker/","title":"Docker\u4ece\u5165\u95e8\u5230\u5b9e\u8df5\uff1a\u4ee5FFB6D\u73af\u5883\u914d\u7f6e\u4e3a\u4f8b","text":""},{"location":"AI/FFB6D/FFB6D_Docker/#dockerffb6d","title":"Docker\u4ece\u5165\u95e8\u5230\u5b9e\u8df5\uff1a\u4ee5FFB6D\u73af\u5883\u914d\u7f6e\u4e3a\u4f8b","text":"<p> \u7ea6 653 \u4e2a\u5b57  213 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 6 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"AI/FFB6D/FFB6D_Docker/#1","title":"1. \u7b80\u4ecb","text":"<p>Docker\u662f\u4e00\u4e2a\u5f00\u6e90\u7684\u5e94\u7528\u5bb9\u5668\u5f15\u64ce\uff0c\u8ba9\u5f00\u53d1\u8005\u53ef\u4ee5\u6253\u5305\u4ed6\u4eec\u7684\u5e94\u7528\u4ee5\u53ca\u4f9d\u8d56\u5305\u5230\u4e00\u4e2a\u53ef\u79fb\u690d\u7684\u5bb9\u5668\u4e2d\uff0c\u7136\u540e\u53d1\u5e03\u5230\u4efb\u4f55\u6d41\u884c\u7684Linux\u6216Windows\u64cd\u4f5c\u7cfb\u7edf\u4e0a\u3002\u672c\u6587\u5c06\u4ee5\u914d\u7f6eFFB6D\uff08\u4e00\u4e2a3D\u76ee\u6807\u68c0\u6d4b\u6a21\u578b\uff09\u7684\u8fd0\u884c\u73af\u5883\u4e3a\u4f8b\uff0c\u4ecb\u7ecdDocker\u7684\u57fa\u672c\u4f7f\u7528\u3002</p>"},{"location":"AI/FFB6D/FFB6D_Docker/#2","title":"2. \u73af\u5883\u51c6\u5907","text":""},{"location":"AI/FFB6D/FFB6D_Docker/#21","title":"2.1 \u7cfb\u7edf\u8981\u6c42","text":"<ul> <li>Ubuntu 20.04/22.04/24.04 </li> <li>NVIDIA GPU\uff08\u652f\u6301CUDA\uff09</li> <li>\u81f3\u5c118GB\u5185\u5b58</li> <li>\u81f3\u5c1130GB\u78c1\u76d8\u7a7a\u95f4</li> </ul>"},{"location":"AI/FFB6D/FFB6D_Docker/#22","title":"2.2 \u57fa\u7840\u7ec4\u4ef6\u5b89\u88c5","text":"<p>\u5b89\u88c5Docker</p> Bash<pre><code># \u66f4\u65b0apt\u5305\u7d22\u5f15\nsudo apt-get update\n\n# \u5b89\u88c5\u5fc5\u8981\u7684\u7cfb\u7edf\u5de5\u5177\nsudo apt-get install -y \\\n    apt-transport-https \\\n    ca-certificates \\\n    curl \\\n    gnupg \\\n    lsb-release\n\n# \u6dfb\u52a0Docker\u7684\u5b98\u65b9GPG\u5bc6\u94a5\ncurl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /usr/share/keyrings/docker-archive-keyring.gpg\n\n# \u8bbe\u7f6e\u7a33\u5b9a\u7248\u4ed3\u5e93\necho \\\n  \"deb [arch=amd64 signed-by=/usr/share/keyrings/docker-archive-keyring.gpg] https://download.docker.com/linux/ubuntu \\\n  $(lsb_release -cs) stable\" | sudo tee /etc/apt/sources.list.d/docker.list &gt; /dev/null\n\n# \u5b89\u88c5Docker Engine\nsudo apt-get update\nsudo apt-get install -y docker-ce docker-ce-cli containerd.io\n\n# \u9a8c\u8bc1\u5b89\u88c5\nsudo docker run hello-world\n</code></pre> <p>\u5b89\u88c5NVIDIA\u9a71\u52a8</p> Bash<pre><code># \u6dfb\u52a0NVIDIA\u5305\u4ed3\u5e93\nsudo add-apt-repository ppa:graphics-drivers/ppa\nsudo apt-get update\n\n# \u5b89\u88c5NVIDIA\u9a71\u52a8\nsudo apt-get install -y nvidia-driver-535  # \u6839\u636e\u9700\u8981\u9009\u62e9\u7248\u672c\n\n# \u91cd\u542f\u7cfb\u7edf\nsudo reboot\n\n# \u9a8c\u8bc1\u5b89\u88c5\nnvidia-smi\n</code></pre> <p>\u5b89\u88c5NVIDIA Container Toolkit</p> Bash<pre><code># \u8bbe\u7f6e\u7a33\u5b9a\u7248\u4ed3\u5e93\ncurl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg\n\necho \"deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://nvidia.github.io/libnvidia-container/stable/ubuntu22.04/$(arch) /\" | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list\n\n# \u66f4\u65b0\u8f6f\u4ef6\u5305\u5217\u8868\nsudo apt-get update\n\n# \u5b89\u88c5nvidia-docker2\nsudo apt-get install -y nvidia-container-toolkit\n\n# \u91cd\u542fDocker\u670d\u52a1\nsudo systemctl restart docker\n\n# \u6d4b\u8bd5GPU\u652f\u6301\nsudo docker run --rm --gpus all nvidia/cuda:12.0-base nvidia-smi\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#23-docker","title":"2.3 Docker\u914d\u7f6e\u4f18\u5316","text":"<p>\u914d\u7f6e\u955c\u50cf\u52a0\u901f</p> Bash<pre><code>sudo tee /etc/docker/daemon.json &lt;&lt; EOF\n{\n  \"registry-mirrors\": [\n    \"https://docker.1panel.dev\",\n    \"https://docker.zhai.cm\",\n    \"https://hub.littlediary.cn\",\n    \"https://docker.nastool.de\"\n  ],\n  \"dns\": [\"8.8.8.8\", \"8.8.4.4\"],\n  \"max-concurrent-downloads\": 10,\n  \"log-driver\": \"json-file\",\n  \"log-opts\": {\n    \"max-size\": \"10m\",\n    \"max-file\": \"3\"\n  }\n}\nEOF\n\nsudo systemctl daemon-reload\nsudo systemctl restart docker\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#3-ffb6d","title":"3. FFB6D\u73af\u5883\u914d\u7f6e\u5b9e\u4f8b","text":""},{"location":"AI/FFB6D/FFB6D_Docker/#31","title":"3.1 \u9879\u76ee\u7ed3\u6784","text":"Bash<pre><code>ffb6d_docker/\n\u251c\u2500\u2500 Dockerfile\n\u251c\u2500\u2500 docker-compose.yml\n\u251c\u2500\u2500 build_and_run.sh\n\u251c\u2500\u2500 downloads/\n\u2502   \u251c\u2500\u2500 apex/\n\u2502   \u2514\u2500\u2500 normalspeed/\n\u251c\u2500\u2500 code/\n\u251c\u2500\u2500 datasets/\n\u251c\u2500\u2500 models/\n\u2514\u2500\u2500 train_log/\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#32-dockerfile","title":"3.2 \u521b\u5efaDockerfile","text":"Docker<pre><code># \u4f7f\u7528\u8f83\u65b0\u7684 CUDA \u955c\u50cf\nFROM nvcr.io/nvidia/cuda:11.0.3-cudnn8-devel-ubuntu18.04\n\n# \u4f7f\u7528 NVIDIA CUDA 11.3 \u57fa\u7840\u955c\u50cf\n# FROM nvcr.io/nvidia/cuda:11.3.1-cudnn8-devel-ubuntu20.04\n\n# \u907f\u514d\u4ea4\u4e92\u5f0f\u63d0\u793a\nENV DEBIAN_FRONTEND=noninteractive\nENV PYTHONPATH=/workspace/code\nENV CUDA_HOME=/usr/local/cuda\nENV PATH=$CUDA_HOME/bin:$PATH\nENV LD_LIBRARY_PATH=$CUDA_HOME/lib64:$LD_LIBRARY_PATH\n\nWORKDIR /workspace\n\n# \u5b89\u88c5\u7cfb\u7edf\u4f9d\u8d56\nRUN apt-get update &amp;&amp; apt-get install -y \\\n    python3.6 \\\n    python3.6-dev \\\n    python3-pip \\\n    git \\\n    cmake \\\n    build-essential \\\n    libopencv-dev \\\n    libglib2.0-0 \\\n    libsm6 \\\n    libxext6 \\\n    libxrender-dev \\\n    libboost-all-dev \\\n    libeigen3-dev \\\n    wget \\\n    &amp;&amp; rm -rf /var/lib/apt/lists/*\n\n# \u8bbe\u7f6e Python 3.6 \u4e3a\u9ed8\u8ba4\u7248\u672c\nRUN update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.6 1\nRUN update-alternatives --set python3 /usr/bin/python3.6\n\n# \u5347\u7ea7 pip\nRUN python3 -m pip install --upgrade pip\n\n# \u914d\u7f6epip\u955c\u50cf\u6e90\nRUN pip3 config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple\n\n# \u5148\u5b89\u88c5 PyTorch (\u4f7f\u7528\u8f83\u65b0\u4f46\u517c\u5bb9\u7684\u7248\u672c)\nRUN pip3 install torch==1.10.2+cu113 torchvision==0.11.3+cu113 -f https://download.pytorch.org/whl/torch_stable.html\n\n# \u590d\u5236\u9884\u4e0b\u8f7d\u7684\u6587\u4ef6\nCOPY downloads/apex /workspace/apex\nCOPY downloads/normalspeed /workspace/normalspeed\nCOPY code /workspace/code\n\n# \u5b89\u88c5 apex\n#RUN cd /workspace/apex &amp;&amp; \\\n#    pip install -v --no-cache-dir --global-option=\"--cpp_ext\" --global-option=\"--cuda_ext\" ./ || \\\n#    (echo \"Apex installation failed. Check the error messages above.\" &amp;&amp; exit 1)\n\n# \u5b89\u88c5 normalspeed\n#RUN cd /workspace/normalspeed &amp;&amp; \\\n#    python3 setup.py build_ext --inplace &amp;&amp; \\\n#    python3 setup.py install\n\nWORKDIR /workspace/code\n</code></pre> <p>\u66f4\u6539 <code>requirement.txt</code> </p> Text Only<pre><code>h5py         \nnumpy              \npyyaml==5.4.1\nenum34        \nfuture           \nscipy==1.4.1          \nopencv_contrib_python==3.4.2.16               \ntransforms3d==0.3.1     \nscikit_image==0.13.1     \nlmdb==0.94              \nsetuptools==41.0.0    \ncffi==1.11.5         \neasydict==1.7      \nplyfile==0.6      \npillow==8.2.0 \ndataclasses\nglumpy                                                      \ntqdm\ntensorboardX \npandas\nscikit-learn         \nscipy \ntermcolor\npybind11\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#33-docker-composeyml","title":"3.3 \u521b\u5efadocker-compose.yml","text":"YAML<pre><code>version: '3'\nservices:\n  ffb6d:\n    build: .\n    image: ffb6d:latest\n    container_name: ffb6d_container\n    runtime: nvidia\n    environment:\n      - NVIDIA_VISIBLE_DEVICES=all\n    volumes:\n      - ./datasets:/workspace/code/datasets\n      - ./train_log:/workspace/code/train_log\n      - ./models:/workspace/code/models\n    shm_size: '8gb'\n    tty: true\n    stdin_open: true\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#34","title":"3.4 \u6784\u5efa\u548c\u8fd0\u884c\u811a\u672c","text":"<p>\u521b\u5efa<code>build_and_run.sh</code>\uff1a</p> Bash<pre><code>#!/bin/bash\n\n# \u521b\u5efa\u5fc5\u8981\u76ee\u5f55\nmkdir -p downloads datasets models train_log\n\n# \u4e0b\u8f7d\u4f9d\u8d56\ncd downloads\nif [ ! -d \"apex\" ]; then\n  git clone https://github.com/NVIDIA/apex.git\nfi\nif [ ! -d \"normalspeed\" ]; then\n  git clone https://github.com/hfutcgncas/normalspeed.git\nfi\ncd ..\n\n# \u514b\u9686FFB6D\u4ee3\u7801\nif [ ! -d \"code\" ]; then\n  git clone https://github.com/ethnhe/FFB6D.git code\nfi\n\n# \u6784\u5efa\u955c\u50cf\ndocker-compose build\n\n# \u8fd0\u884c\u5bb9\u5668\ndocker-compose up -d\ndocker exec -it ffb6d_container bash\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#35","title":"3.5 \u542f\u52a8\u548c\u9a8c\u8bc1","text":"Bash<pre><code># \u6dfb\u52a0\u6267\u884c\u6743\u9650\nchmod +x build_and_run.sh\n\n# \u8fd0\u884c\n./build_and_run.sh\n\n# \u5728\u5bb9\u5668\u5185\u9a8c\u8bc1\npython3 -c \"import torch; print('CUDA available:', torch.cuda.is_available())\"\npython3 -c \"from apex import amp; print('APEX installed')\"\npython3 -c \"import normalspeed; print('normalspeed installed')\"\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#36-apex","title":"3.6 \u7f16\u8bd1 apex","text":"Text Only<pre><code>git clone https://github.com/NVIDIA/apex\ncd apex\nexport TORCH_CUDA_ARCH_LIST=\"6.0;6.1;6.2;7.0;7.5\"\npython setup.py install -v\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#37-normalspeed","title":"3.7 \u7f16\u8bd1 normalspeed","text":"Text Only<pre><code># 1. \u5378\u8f7d\u5f53\u524dcv2\npip uninstall opencv-python opencv-python-headless -y\n\n# 2. \u5b89\u88c5\u7279\u5b9a\u7248\u672c\u7684OpenCV\uff0c\u9009\u62e9\u4e0ePython 3.6\u517c\u5bb9\u7684\u7248\u672c\npip install opencv-python==4.5.3.56\n\n# 3. \u9a8c\u8bc1\u5b89\u88c5\npython3 -c \"import cv2; print(cv2.__version__)\"\n</code></pre> Text Only<pre><code># \u8fdb\u5165normalSpeed\u76ee\u5f55\ncd /workspace/code/normalspeed/normalSpeed\n\n# \u5b89\u88c5\u4f9d\u8d56\napt-get update\napt-get install python3-pybind11\npip3 install Cython==0.29.15\n\n# \u6e05\u7406\u4e4b\u524d\u7684\u6784\u5efa\nrm -rf build/\nrm -rf dist/\nrm -rf *.egg-info/\n\n# \u91cd\u65b0\u5b89\u88c5\npython3 setup.py install\n\n# \u9a8c\u8bc1\u5b89\u88c5\npython3 -c \"import normalSpeed\"\n\n# \u8fd4\u56deffb6d\u76ee\u5f55\ncd /workspace/code/ffb6d/\n</code></pre> Text Only<pre><code>python3 setup.py install --user\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#38","title":"3.8 \u8bad\u7ec3","text":"<p>\u628a LineMOD \u590d\u5236\u5230\u5bf9\u5e94\u7684\u8def\u5f84\u4e0b\uff0c\u7136\u540e\u6309\u5b98\u7f51\u6765\u5c31\u597d\u4e86</p>"},{"location":"AI/FFB6D/FFB6D_Docker/#4","title":"4. \u5e38\u89c1\u95ee\u9898","text":""},{"location":"AI/FFB6D/FFB6D_Docker/#41","title":"4.1 \u7f51\u7edc\u95ee\u9898","text":"<p>\u5982\u679c\u9047\u5230\u4e0b\u8f7d\u6162\u6216\u5931\u8d25\uff1a</p> Bash<pre><code># \u4e34\u65f6\u4f7f\u7528\u4ee3\u7406\nexport http_proxy=\"http://proxy:port\"\nexport https_proxy=\"http://proxy:port\"\n\n# \u6216\u4fee\u6539pip\u6e90\npip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple\n</code></pre> <p>\u6ce8\u610f\u7528\u4e86\u4ee3\u7406\u7684\u8bdd\uff0cdocker hub \u955c\u50cf\u5c31\u4f1a\u88ab\u8986\u76d6\u6389\uff0c\u5bfc\u81f4\u901f\u5ea6\u5f88\u6162\u3002\u6240\u4ee5\u5230\u65f6\u5019\u4e00\u5b9a\u8981\u53d6\u6d88\u4ee3\u7406 / \u5220\u9664\u4ee3\u7406\u6587\u4ef6</p> <p>docker hub \u955c\u50cf\u8bbe\u7f6e\u4e0a\u9762\u5199\u4e86\uff0c\u5b98\u7f51\u662f\u8fd9\u4e2a GitHub - dongyubin/DockerHub: 2024\u5e7411\u6708\u66f4\u65b0\uff0c\u76ee\u524d\u56fd\u5185\u53ef\u7528Docker\u955c\u50cf\u6e90\u6c47\u603b\uff0cDockerHub\u56fd\u5185\u955c\u50cf\u52a0\u901f\u5217\u8868\uff0c\ud83d\ude80DockerHub\u955c\u50cf\u52a0\u901f\u5668</p>"},{"location":"AI/FFB6D/FFB6D_Docker/#42-cuda","title":"4.2 CUDA\u517c\u5bb9\u6027","text":"<p>\u786e\u4fddNVIDIA\u9a71\u52a8\u7248\u672c\u652f\u6301\u6240\u9700\u7684CUDA\u7248\u672c\uff1a</p> Bash<pre><code># \u68c0\u67e5\u652f\u6301\u7684\u6700\u9ad8CUDA\u7248\u672c\nnvidia-smi\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#43","title":"4.3 \u5185\u5b58\u4e0d\u8db3","text":"<p>\u8c03\u6574Docker\u5185\u5b58\u9650\u5236\uff1a</p> YAML<pre><code># \u5728docker-compose.yml\u4e2d\u6dfb\u52a0\nservices:\n  ffb6d:\n    deploy:\n      resources:\n        limits:\n          memory: 16G\n</code></pre>"},{"location":"AI/FFB6D/FFB6D_Docker/#5","title":"5. \u603b\u7ed3","text":"<p>\u672c\u6587\u4ecb\u7ecd\u4e86\u4f7f\u7528Docker\u914d\u7f6e\u6df1\u5ea6\u5b66\u4e60\u73af\u5883\u7684\u5b8c\u6574\u6d41\u7a0b\uff0c\u4ee5FFB6D\u4e3a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5904\u7406\u590d\u6742\u4f9d\u8d56\u5173\u7cfb\u3002\u901a\u8fc7\u5bb9\u5668\u5316\u6280\u672f\uff0c\u6211\u4eec\u53ef\u4ee5\uff1a</p> <ol> <li>\u786e\u4fdd\u73af\u5883\u4e00\u81f4\u6027</li> <li>\u7b80\u5316\u90e8\u7f72\u6d41\u7a0b</li> <li>\u63d0\u9ad8\u5f00\u53d1\u6548\u7387</li> <li>\u65b9\u4fbf\u56e2\u961f\u534f\u4f5c</li> </ol> <p>\u5e0c\u671b\u672c\u6559\u7a0b\u80fd\u5e2e\u52a9\u4f60\u66f4\u597d\u5730\u7406\u89e3\u548c\u4f7f\u7528Docker\u3002</p>"},{"location":"AI/FFB6D/FFB6D_Docker/#_1","title":"\u53c2\u8003\u8d44\u6599","text":"<ol> <li>Docker\u5b98\u65b9\u6587\u6863</li> <li>NVIDIA Docker\u6587\u6863</li> <li>FFB6D\u9879\u76ee</li> <li>\u3010\u8bba\u6587\u7b14\u8bb0\u3011FFB6D | \u9a6c\u6d69\u98de\u4e28\u535a\u5ba2</li> </ol>"},{"location":"CS_Basic/","title":"Computer Basic","text":""},{"location":"CS_Basic/#computer-science-basic","title":"Computer Science Basic","text":"<p>Abstract</p> <p>\u672c\u90e8\u5206\u5185\u5bb9\uff08\u9664\u7279\u522b\u58f0\u660e\u5916\uff09\u91c7\u7528 \u7f72\u540d-\u975e\u5546\u4e1a\u6027\u4f7f\u7528-\u4fdd\u6301\u4e00\u81f4 4.0 \u56fd\u9645 (CC BY-NC-SA 4.0) \u8bb8\u53ef\u534f\u8bae\u8fdb\u884c\u8bb8\u53ef\u3002</p> CS61A          <ul> <li> Composing Programs  2713  651  17 mins              1734027543 </li> <li> Experience  0  0 mins              0 </li> </ul> CS61C          <ul> <li> \u8ba1\u7b97\u673a\u7ec4\u6210\u4e0e\u8bbe\u8ba1\u786c\u4ef6\u8f6f\u4ef6\u63a5\u53e3  2978  13  10 mins              1734027543 </li> </ul> Network          <ul> <li> Security Basic  368  1 mins              1734027543 </li> </ul> 15-213          <ul> <li> CSAPP  1012  36  4 mins              1734027543 </li> </ul> C++          <ul> <li> Accelerated C++  2534  489  15 mins              1734027543 </li> <li> C++ Basic  3115  523  17 mins              1734027543 </li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/","title":"\u6df1\u5165\u7406\u89e3\u8ba1\u7b97\u673a\u7cfb\u7edf","text":""},{"location":"CS_Basic/15-213/CSAPP/#_1","title":"\u6df1\u5165\u7406\u89e3\u8ba1\u7b97\u673a\u7cfb\u7edf","text":"<p> \u7ea6 1012 \u4e2a\u5b57  36 \u884c\u4ee3\u7801  14 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 6 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"CS_Basic/15-213/CSAPP/#1","title":"1 \u8ba1\u7b97\u673a\u7cfb\u7edf\u6f2b\u6e38","text":""},{"location":"CS_Basic/15-213/CSAPP/#2","title":"2 \u4fe1\u606f\u7684\u8868\u793a\u548c\u5904\u7406","text":"<ul> <li>\u628a\u4f4d\u7ec4\u5408\u518d\u4e00\u8d77\uff0c\u518d\u52a0\u4e0a interpretation</li> <li>\u4e09\u79cd\u91cd\u8981\u7684\u6570\u5b57\u8868\u793a<ul> <li>unsigned</li> <li>two's-complement</li> <li>floating-point</li> </ul> </li> <li>overflow</li> <li>\u6d6e\u70b9\u6570\u662f\u8fd1\u4f3c\u7684</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#21","title":"2.1 \u4fe1\u606f\u5b58\u50a8","text":"<ul> <li>1 byte = 8 bits</li> <li>virtual memory </li> <li>address<ul> <li>virtual address space</li> </ul> </li> <li>\u8bb2\u5b58\u50a8\u5668\u7a7a\u95f4\u5212\u5206\u4e3a\u66f4\u53ef\u7ba1\u7406\u7684\u5355\u5143\uff0c\u6765\u5b58\u653e\u4e0d\u540c\u7684 program object</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#211","title":"2.1.1 \u5341\u516d\u8fdb\u5236\u8868\u793a\u6cd5","text":"<ul> <li>0x...</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#212","title":"2.1.2 \u5b57\u6570\u636e\u5927\u5c0f","text":"<ul> <li>word size </li> <li>nominal size</li> <li>\u5b57\u957f\u51b3\u5b9a\u7684\u6700\u91cd\u8981\u7684\u7cfb\u7edf\u53c2\u6570\u5c31\u662f\u865a\u62df\u5730\u5740\u7a7a\u95f4\u7684\u6700\u5927\u5927\u5c0f<ul> <li>\u5b57\u957f\u4e3a \\(\\displaystyle \\omega\\) \u4e3a\u7684\u673a\u5668\uff0c\u865a\u62df\u5730\u5740\u7684\u8303\u56f4\u4e3a \\(\\displaystyle 0\\sim2^{\\omega} - 1\\)</li> <li>\u5927\u591a\u6570 64 \u4f4d\u673a\u5668\u53ef\u4ee5\u8fd0\u884c 32 \u4f4d\u673a\u5668\u7f16\u8bd1\u7684\u7a0b\u5e8f\uff0c\u5373\u5411\u540e\u517c\u5bb9 </li> </ul> </li> <li>\u4e3a\u4e86\u907f\u514d\u5927\u5c0f\u548c\u4e0d\u540c\u7f16\u8bd1\u5668\u8bbe\u7f6e\u5e26\u6765\u7684\u5947\u602a\u884c\u4e3a\uff0c\u6211\u4eec\u6709\u4e86 int 32_t \u548c int 64_t</li> <li>C \u8bed\u8a00\u5bf9\u58f0\u660e\u7684\u5173\u952e\u8bcd\u987a\u5e8f\u4e0d\u654f\u611f</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#213","title":"2.1.3 \u5bfb\u5740\u548c\u5b57\u8282\u987a\u5e8f","text":"<ul> <li>[[\u8ba1\u7b97\u673a\u7ec4\u6210\u4e0e\u8bbe\u8ba1\u786c\u4ef6\u8f6f\u4ef6\u63a5\u53e3#^da8be4|\u5c0f\u7aef\u7f16\u5740]]<ul> <li>\u5c31\u662f\u53f3\u8fb9\u653e\u5c0f\u7684\uff0c\u8981\u4ece\u53f3\u5f80\u5de6\u8bfb</li> </ul> </li> <li>\u5b57\u8282\u987a\u5e8f\u53d8\u5f97\u91cd\u8981\u7684\u4e09\u79cd\u60c5\u51b5<ul> <li>\u7f51\u7edc\u5e94\u7528\u7a0b\u5e8f\u7684\u4ee3\u7801\u7f16\u5199\u5fc5\u987b\u9075\u5b88\u5df2\u5efa\u7acb\u7684\u5173\u4e8e\u5b57\u8282\u987a\u5e8f\u7684\u89c4\u5219</li> <li>disassembler</li> <li>\u7f16\u5199\u89c4\u907f\u6b63\u5e38\u7684\u7c7b\u578b\u7cfb\u7edf\u7684\u7a0b\u5e8f<ul> <li>cast or union in C</li> <li>\u5bf9\u5e94\u7528\u7f16\u7a0b\u4e0d\u63a8\u8350\uff0c\u4f46\u662f\u5bf9\u7cfb\u7edf\u7ea7\u7f16\u7a0b\u662f\u5fc5\u9700\u7684</li> </ul> </li> </ul> </li> </ul> C<pre><code>#include &lt;stdio.h&gt;\n\n\n\ntypedef unsigned char *byte_pointer;\n\nvoid show_bytes(byte_pointer start, size_t len) {\n\u00a0 size_t i;\n\u00a0 for (i = 0; i &lt; len; i++)\n\u00a0 \u00a0 printf(\" %.2x\", start[i]);\n\u00a0 printf(\"\\n\");\n}\n\nvoid show_int(int x) { show_bytes((byte_pointer)&amp;x, sizeof(int)); }\n\nvoid show_float(float x) { show_bytes((byte_pointer)&amp;x, sizeof(float)); }\n\nvoid show_pointer(void *x) { show_bytes((byte_pointer)&amp;x, sizeof(void *)); }\n\nvoid test_show_bytes(int val) {\n\u00a0 int ival = val;\n\u00a0 float fval = (float)ival;\n\u00a0 int *pval = &amp;ival;\n\u00a0 show_int(ival);\n\u00a0 show_float(fval);\n\u00a0 show_pointer(pval);\n}\n\nint main() {\n\u00a0 int val = 12345;\n\u00a0 test_show_bytes(val);\n\u00a0 return 0;\n}\n</code></pre> Text Only<pre><code> 39 30 00 00 //\u5c0f\u7aef\u6cd5\n 00 e4 40 46\n 8c f6 bf ef b4 00 00 00\n</code></pre>"},{"location":"CS_Basic/15-213/CSAPP/#214","title":"2.1.4 \u8868\u793a\u5b57\u7b26\u4e32","text":""},{"location":"CS_Basic/15-213/CSAPP/#215","title":"2.1.5 \u8868\u793a\u4ee3\u7801","text":"<ul> <li>\u4e8c\u8fdb\u5236\u4ee3\u7801\u5f88\u5c11\u80fd\u5728\u4e0d\u540c\u673a\u5668\u548c\u64cd\u4f5c\u7cfb\u7edf\u7ec4\u5408\u4e4b\u95f4\u79fb\u690d</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#216","title":"2.1.6 \u5e03\u5c14\u4ee3\u6570\u7b80\u4ecb","text":"<ul> <li>\u53ef\u4ee5\u6269\u5c55\u5230\u4f4d\u5411\u91cf\u7684\u8fd0\u7b97</li> <li>\u5e03\u5c14\u4ee3\u6570</li> <li>Boolean ring<ul> <li>additive inverse</li> </ul> </li> <li>\u548c\u96c6\u5408\u7684\u5bf9\u5e94</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#217-c","title":"2.1.7 C \u8bed\u8a00\u4e2d\u7684\u4f4d\u7ea7\u8fd0\u7b97","text":"<ul> <li>\u63a9\u7801\u8fd0\u7b97</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#218-c","title":"2.1.8 C \u8bed\u8a00\u4e2d\u7684\u903b\u8f91\u8fd0\u7b97","text":""},{"location":"CS_Basic/15-213/CSAPP/#219-c","title":"2.1.9 C \u8bed\u8a00\u4e2d\u7684\u79fb\u4f4d\u8fd0\u7b97","text":"<ul> <li>\u903b\u8f91\u53f3\u79fb</li> <li>\u7b97\u6570\u53f3\u79fb</li> <li>\u5b9e\u9645\u4e0a\uff0c\u51e0\u4e4e\u6240\u6709\u7684\u7f16\u8bd1\u5668\u90fd\u5bf9\u6709\u7b26\u53f7\u6570\u4f7f\u7528\u7b97\u672f\u53f3\u79fb\uff0c\u800c\u5bf9\u4e8e\u65e0\u7b26\u53f7\u6570\uff0c\u53f3\u79fb\u5fc5\u987b\u662f\u903b\u8f91\u7684\uff08C \u8bed\u8a00\uff09</li> <li>\u800c\u5bf9\u4e8e Java <code>x&gt;&gt;k</code> \u662f\u7b97\u6570\u53f3\u79fb\uff0c <code>x&gt;&gt;&gt;k</code> \u662f\u903b\u8f91\u53f3\u79fb</li> <li>\u5bf9\u4e8e C \u8bed\u8a00\uff0c\u79fb\u52a8 \\(\\displaystyle k \\text{ mod } \\omega\\)</li> <li>\u52a0\u51cf\u7684\u4f18\u5148\u7ea7\u6bd4\u79fb\u4f4d\u7b97\u6cd5\u8981\u641e</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#22","title":"2.2 \u6574\u6570\u8868\u793a","text":""},{"location":"CS_Basic/15-213/CSAPP/#221","title":"2.2.1 \u6574\u578b\u6570\u636e\u7c7b\u578b","text":"<ul> <li>64 \u4f4d\u548c 32 \u4f4d\u662f\u4e0d\u4e00\u6837\u7684 </li> <li>\u53d6\u503c\u8303\u56f4\u4e0d\u662f\u5bf9\u79f0\u7684 </li> <li>Java \u53ea\u652f\u6301\u6709\u7b26\u53f7\u6570</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#222","title":"2.2.2 \u65e0\u7b26\u53f7\u6570\u7684\u7f16\u7801","text":"<ul> <li>\u628a\u5411\u91cf\u5199\u6210\u4e8c\u8fdb\u5236\u8868\u793a\u7684\u6570\uff0c\u5c31\u5f97\u5230\u4e86\u65e0\u7b26\u53f7\u8868\u793a </li> </ul> \\[ B2U_w(\\vec{x})\\doteq\\sum_{i=0}^{u-1}x_i2^i \\] \\[ B2U_w:\\{0, 1\\}^w\\to\\{0, \\cdots,2^w-1\\} \\] <ul> <li>\u65e0\u7b26\u53f7\u6570\u7f16\u7801\u7684\u552f\u4e00\u6027</li> <li>\\(\\displaystyle \u51fd\u6570B2U_w\u662f\u4e00\u4e2a\u53cc\u5c04\u3002\\)</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#223","title":"2.2.3 \u8865\u7801\u7f16\u7801","text":"<ul> <li>two's-complement</li> <li>negative weight</li> </ul> \\[ B2T_w(\\vec{x})\\doteq- x_{w-1}2^{w-1}+\\sum_{i=0}^{w-2}x_i2^i \\] \\[ B2T_{w}\\colon \\{0, 1\\}^{w}\\to\\langle TMin_{w}, \\cdots, TMax_{w} \\rangle  \\] <ul> <li>\u8865\u7801\u7f16\u7801\u7684\u552f\u4e00\u6027</li> <li> <p>\\(\\displaystyle \u51fd\u6570B2T_w\u662f\u4e00\u4e2a\u53cc\u5c04\u3002\\) </p> </li> <li> <p>\u53cd\u7801</p> </li> </ul> \\[ B2O_w(\\vec{x})\\doteq-x_{w-1}(2^{w-1}-1)+\\sum_{i=0}^{w-2}x_i2^i \\] <ul> <li>\u539f\u7801</li> </ul> \\[ B2S_w(\\vec{x})\\doteq(-1)^{x_{w-1}}\\cdot\\bigl(\\sum_{i=0}^{w-2}x_i2^i\\bigr) \\] <ul> <li>\u5bf9\u4e8e\u6570\u5b57 0 \u6709\u4e24\u79cd\u4e0d\u540c\u7684\u7f16\u7801\u65b9\u5f0f</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#224","title":"2.2.4 \u6709\u7b26\u53f7\u6570\u548c\u65e0\u7b26\u53f7\u6570\u4e4b\u95f4\u7684\u8f6c\u6362","text":"<ul> <li>\u4fdd\u6301\u4f4d\u503c\u4e0d\u53d8\uff0c\u6539\u53d8\u89e3\u91ca\u65b9\u5f0f</li> </ul> \\[ T2U_{_w}(x)\\doteq B2U_{_w}( T2B_{_w}(x) ) \\] <ul> <li>\u8865\u7801\u8f6c\u6362\u4e3a\u65e0\u7b26\u53f7\u6570</li> </ul> \\[ T2U_w(x)=\\begin{cases}x+2^w,&amp;x&lt;0\\\\x,&amp;x\\geqslant0\\end{cases} \\] <ul> <li>\u65e0\u7b26\u53f7\u6570\u8f6c\u6362\u4e3a\u8865\u7801</li> </ul> \\[ U2T_w(u)=\\begin{cases}u ,&amp;u\\leqslant TMax_w\\\\u-2^w ,&amp;u&gt;TMax_w\\end{cases} \\]"},{"location":"CS_Basic/15-213/CSAPP/#225-c","title":"2.2.5 C \u8bed\u8a00\u4e2d\u7684\u6709\u7b26\u53f7\u6570\u4e0e\u65e0\u7b26\u53f7\u6570","text":"<ul> <li>\u4e00\u4e2a\u8fd0\u7b97\u7b26\u662f\u6709\u7b26\u53f7\u7684\u800c\u53e6\u4e00\u4e2a\u662f\u65e0\u7b26\u53f7\u7684\uff0c\u90a3 C \u7a0b\u5e8f\u4f1a\u628a\u6709\u7b26\u53f7\u7684\u8f6c\u6362\u4e3a\u65e0\u7b26\u53f7\u7684\u3002 </li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#226","title":"2.2.6 \u6269\u5c55\u4e00\u4e2a\u6570\u5b57\u7684\u4f4d\u8868\u793a","text":"<ul> <li>\u65e0\u7b26\u53f7\u6570\u7684 zero extension</li> <li>\u8865\u7801\u6570\u7684\u7b26\u53f7\u6269\u5c55</li> </ul>"},{"location":"CS_Basic/15-213/CSAPP/#227","title":"2.2.7 \u622a\u65ad\u6570\u5b57","text":""},{"location":"CS_Basic/15-213/CSAPP/#228","title":"2.2.8 \u5173\u4e8e\u6709\u7b26\u53f7\u6570\u4e0e\u65e0\u7b26\u53f7\u6570\u7684\u5efa\u8bae","text":""},{"location":"CS_Basic/15-213/CSAPP/#23","title":"2.3 \u6574\u6570\u8fd0\u7b97","text":""},{"location":"CS_Basic/15-213/CSAPP/#231","title":"2.3.1 \u65e0\u7b26\u53f7\u52a0\u6cd5","text":"<ul> <li>Lisp \u652f\u6301\u65e0\u9650\u7cbe\u5ea6\u7684\u8fd0\u7b97</li> </ul> \\[ x+_w^uy=\\begin{cases}x+y,&amp;x+y&lt;2^w&amp;\\text{\u6b63\u5e38}\\\\x+y-2^w,&amp;2^w\\leqslant x+y&lt;2^{w+1}&amp;\\text{\u6ea2\u51fa}\\end{cases} \\]"},{"location":"CS_Basic/15-213/CSAPP/#3","title":"3 \u7a0b\u5e8f\u7684\u673a\u5668\u7ea7\u8868\u793a","text":""},{"location":"CS_Basic/15-213/CSAPP/#4","title":"4 \u5904\u7406\u5668\u4f53\u7cfb\u7ed3\u6784","text":""},{"location":"CS_Basic/15-213/CSAPP/#5","title":"5 \u4f18\u5316\u7a0b\u5e8f\u6027\u80fd","text":""},{"location":"CS_Basic/15-213/CSAPP/#6","title":"6 \u5b58\u50a8\u5668\u5c42\u6b21\u7ed3\u6784","text":""},{"location":"CS_Basic/15-213/CSAPP/#7","title":"7 \u94fe\u63a5","text":""},{"location":"CS_Basic/15-213/CSAPP/#8","title":"8 \u5f02\u5e38\u63a7\u5236\u6d41","text":""},{"location":"CS_Basic/15-213/CSAPP/#9","title":"9 \u865a\u62df\u5185\u5b58","text":""},{"location":"CS_Basic/15-213/CSAPP/#10-io","title":"10 \u7cfb\u7edf\u7ea7 I/O","text":""},{"location":"CS_Basic/15-213/CSAPP/#11","title":"11 \u7f51\u7edc\u7f16\u7a0b","text":""},{"location":"CS_Basic/15-213/CSAPP/#12","title":"12 \u5e76\u53d1\u7f16\u7a0b","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/","title":"Accelerated C++","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#accelerated-c","title":"Accelerated C++","text":"<p> \u7ea6 2520 \u4e2a\u5b57  489 \u884c\u4ee3\u7801  2 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 19 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#0-c","title":"0 \u5f00\u59cb\u5b66\u4e60 C++","text":"C++<pre><code>#include &lt;iostream&gt;\n\nint main()\n{\n    std::cout &lt;&lt; \"Hello, World!\" &lt;&lt; std::endl;\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#01","title":"0.1 \u6ce8\u91ca","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#02-displaystyle-include","title":"0.2 \\(\\displaystyle \\#\\)include \u6307\u4ee4","text":"<ul> <li>\u8f93\u5165\u3001\u8f93\u51fa\u4e0d\u5c5e\u4e8e\u8bed\u8a00\u6838\u5fc3\uff0c\u800c\u662f\u6807\u51c6\u5e93\u7684\u4e00\u90e8\u5206</li> <li>iostream \u4ee3\u8868 C++\u5e93\u7684\u6807\u51c6\u5934\u6587\u4ef6</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#03-main","title":"0.3 \u4e3b\u51fd\u6570 main","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#04","title":"0.4 \u82b1\u62ec\u53f7","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#05","title":"0.5 \u4f7f\u7528\u6807\u51c6\u5e93\u8fdb\u884c\u8f93\u51fa","text":"<ul> <li>std:: cout \u6307\u6807\u51c6\u8f93\u51fa\u6d41</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#06","title":"0.6 \u8fd4\u56de\u8bed\u53e5","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#07","title":"0.7 \u4e00\u4e9b\u8f83\u4e3a\u6df1\u5165\u7684\u89c2\u5bdf","text":"<ul> <li>\u8868\u8fbe\u5f0f<ul> <li>\u8fd0\u7b97\u4f1a\u4ea7\u751f\u4e00\u4e2a\u7ed3\u679c\uff0c\u53ef\u80fd\u4f1a\u5177\u6709\u526f\u4f5c\u7528</li> </ul> </li> <li>\u6bcf\u4e2a\u64cd\u4f5c\u6570\u90fd\u5177\u6709\u4e00\u4e2a\u7c7b\u578b</li> <li>&lt;&lt;\u662f\u5de6\u7ed3\u5408\u7684\uff0c\u6240\u4ee5\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4e24\u4e2a&lt;&lt;\u8fd0\u7b97\u7b26\u548c\u4e09\u4e2a\u64cd\u4f5c\u6570</li> </ul> C++<pre><code>(std::cout &lt;&lt; \"Hello, World!\") &lt;&lt; std::endl\n</code></pre> <ul> <li>std:: cout \u7684\u7c7b\u578b\u662f std::ostream</li> <li>std:: endl \u662f\u4e00\u4e2a\u63a7\u5236\u5668\uff08manipulator\uff09</li> <li>\u7b2c\u4e00\u79cd\u4f5c\u7528\u57df: \u540d\u5b57\u7a7a\u95f4</li> <li>:: \u662f\u4f5c\u7528\u57df\u8fd0\u7b97\u7b26\uff0cstd:: cout \u662f\u4e00\u4e2a\u9650\u5b9a\u540d\u79f0</li> <li>\u82b1\u62ec\u53f7\u662f\u53e6\u4e00\u79cd\u4f5c\u7528\u57df</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#08","title":"0.8 \u5c0f\u7ed3","text":"<ul> <li>main \u53ef\u4ee5\u6ca1\u6709 return \u8bed\u53e5</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#1","title":"1 \u4f7f\u7528\u5b57\u7b26\u4e32","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#11","title":"1.1 \u8f93\u5165","text":"C++<pre><code>#include &lt;iostream&gt;\n#include &lt;string&gt;\n\nint main() \n{\n    std::cout &lt;&lt; \"Please enter your first name:\";\n\n    std::string name;\n    std::cin &gt;&gt; name;\n\n    std::cout &lt;&lt; \"Hello\" &lt;&lt; name &lt;&lt; \"!\" &lt;&lt; std::endl;\n    return 0;\n}\n</code></pre> <ul> <li>\u53d8\u91cf\u662f\u4e00\u4e2a\u5bf9\u8c61\uff0c\u4f46\u6709\u4e9b\u5bf9\u8c61\u53ef\u80fd\u6ca1\u6709\u540d\u79f0</li> <li>\u5c40\u90e8\u53d8\u91cf\u6709\u9650\u7684\u751f\u5b58\u671f\u662f\u533a\u5206\u53d8\u91cf\u548c\u5bf9\u8c61\u7684\u4e00\u4e2a\u91cd\u8981\u4f9d\u636e</li> <li>\u9690\u85cf\u5728\u5bf9\u8c61\u7c7b\u578b\u4e2d\u7684\u8fd8\u6709\u5176\u63a5\u53e3<ul> <li>\u63a5\u53e3\u662f\u53ef\u5b9e\u73b0\u64cd\u4f5c\u7684\u96c6\u5408</li> </ul> </li> <li>\u7f13\u51b2\u533a\u6765\u4fdd\u5b58\u8f93\u51fa</li> <li>\u4f55\u65f6\u5237\u65b0\u7f13\u51b2\u533a:<ul> <li>\u7f13\u51b2\u533a\u6ee1\u4e86</li> <li>\u8f93\u5165\u6d41\u8bfb\u6570\u636e</li> <li>\u660e\u786e\u8981\u6c42\u5237\u65b0</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#12","title":"1.2 \u4e3a\u59d3\u540d\u88c5\u6846","text":"<ul> <li>\u8fd0\u7b97\u7b26\u88ab\u91cd\u8f7d\u4e86</li> <li>\u8fd0\u7b97\u7b26\u4e00\u4e2a\u6c38\u8fdc\u4e0d\u4f1a\u6539\u53d8\u7684\u6027\u8d28\u662f\u7ed3\u5408\u5f8b\uff0c+\u662f\u5de6\u7ed3\u5408\u7684</li> </ul> C++<pre><code>std::string stars(10, '*')\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#13","title":"1.3 \u5c0f\u7ed3","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#2","title":"2 \u5faa\u73af\u548c\u8ba1\u6570","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#21","title":"2.1 \u95ee\u9898","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#22","title":"2.2 \u7a0b\u5e8f\u7684\u6574\u4f53\u7ed3\u6784","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#23","title":"2.3 \u8f93\u51fa\u6570\u76ee\u672a\u77e5\u7684\u884c","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#231-while","title":"2.3.1 while \u8bed\u53e5","text":"<ul> <li>++\u662f\u4e00\u4e2a\u589e\u91cf\u8fd0\u7b97\u7b26</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#232-while","title":"2.3.2 \u8bbe\u8ba1 while \u8bed\u53e5","text":"<ul> <li>\u5faa\u73af\u4e0d\u53d8\u5f0f\uff08Loop invariant\uff09<ul> <li>\u521d\u59cb\u5316\uff1a\u5728\u5faa\u73af\u5f00\u59cb\u4e4b\u524d\uff0c\u5faa\u73af\u4e0d\u53d8\u5f0f\u5e94\u8be5\u88ab\u786e\u7acb\u4e3a\u771f\u3002</li> <li>\u4fdd\u6301\uff1a\u5faa\u73af\u7684\u6bcf\u6b21\u8fed\u4ee3\u90fd\u5fc5\u987b\u4fdd\u6301\u5faa\u73af\u4e0d\u53d8\u5f0f\u4e3a\u771f\uff0c\u5373\u5982\u679c\u8fdb\u5165\u67d0\u6b21\u8fed\u4ee3\u65f6\u5faa\u73af\u4e0d\u53d8\u5f0f\u4e3a\u771f\uff0c\u90a3\u4e48\u5728\u8be5\u6b21\u8fed\u4ee3\u7ed3\u675f\u65f6\uff0c\u5faa\u73af\u4e0d\u53d8\u5f0f\u4ecd\u7136\u4e3a\u771f\u3002</li> <li>\u7ec8\u6b62\uff1a\u5f53\u5faa\u73af\u7ed3\u675f\u65f6\uff0c\u5faa\u73af\u4e0d\u53d8\u5f0f\u5e94\u8be5\u80fd\u591f\u7528\u6765\u8bc1\u660e\u5faa\u73af\u7684\u7ec8\u6b62\u6761\u4ef6\u6210\u7acb\uff0c\u6216\u8005\u7528\u6765\u8bc1\u660e\u5faa\u73af\u7684\u8f93\u51fa\u6216\u7ed3\u679c\u6ee1\u8db3\u7279\u5b9a\u7684\u5c5e\u6027\u3002</li> <li>\u5faa\u73af\u4e0d\u53d8\u5f0f\u7684\u4e00\u4e2a\u5178\u578b\u4f8b\u5b50\u662f\u5728\u6392\u5e8f\u7b97\u6cd5\u4e2d\uff0c\u4f8b\u5982\u5192\u6ce1\u6392\u5e8f\u3002\u5728\u5192\u6ce1\u6392\u5e8f\u4e2d\uff0c\u4e00\u4e2a\u53ef\u80fd\u7684\u5faa\u73af\u4e0d\u53d8\u5f0f\u662f\uff1a\u201c\u6bcf\u6b21\u5faa\u73af\u8fed\u4ee3\u540e\uff0c\u6570\u7ec4\u7684\u6700\u540en\u4e2a\u5143\u7d20\u662f\u6392\u5e8f\u597d\u7684\u201d\uff0c\u5176\u4e2dn\u662f\u5faa\u73af\u8fed\u4ee3\u7684\u6b21\u6570\u3002</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#24","title":"2.4 \u8f93\u51fa\u4e00\u884c","text":"C++<pre><code>const std::string::size_type cols = greeting.size() + pad * 2 + 2;\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#241","title":"2.4.1 \u8f93\u51fa\u8fb9\u754c\u5b57\u7b26","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#2411-if","title":"2.4.1.1 if \u8bed\u53e5","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#2412","title":"2.4.1.2 \u903b\u8f91\u8fd0\u7b97\u7b26","text":"<ul> <li>||\u662f\u5de6\u7ed3\u5408\uff0c\u4f1a\u6709\u77ed\u8def\u6c42\u503c\uff08short-circuit evaluation\uff09</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#242","title":"2.4.2 \u8f93\u51fa\u975e\u8fb9\u754c\u5b57\u7b26","text":"<ul> <li>+=\u590d\u5408\u8d4b\u503c\u8fd0\u7b97\u7b26</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#25","title":"2.5 \u5b8c\u6574\u7684\u6846\u67b6\u7a0b\u5e8f","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#251-std","title":"2.5.1 \u7565\u53bb\u91cd\u590d\u4f7f\u7528\u7684 std::","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#252-for","title":"2.5.2 \u4f7f\u7528 for \u8bed\u53e5\u6765\u7f29\u77ed\u7a0b\u5e8f","text":"<ul> <li>\u533a\u95f4\u7684\u8d8a\u754c\u503c\uff08off-the-end value\uff09</li> </ul> C++<pre><code>for (int r = 0; r != rows; ++r) {\n\n}\n</code></pre> <ul> <li>\u8fd9\u662f\u534a\u5f00\u533a\u95f4</li> </ul> C++<pre><code>for (init-statement condition; expression)\n    statement\n\n#equals to\n\n{\n    inti-statement\n    while (condition) {\n        statement\n        expression;\n    }\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#253","title":"2.5.3 \u538b\u7f29\u68c0\u6d4b","text":"<ul> <li>\u5c31\u662f\u628a if \u8bed\u53e5\u5408\u5e76\u4e00\u4e0b</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#254","title":"2.5.4 \u5b8c\u6574\u7684\u6846\u67b6\u7a0b\u5e8f","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#26","title":"2.6 \u8ba1\u6570","text":"<ul> <li>\u4e0d\u5bf9\u6210\u533a\u95f4\u53ef\u4ee5\u76f4\u63a5\u770b\u51fa\u6709\u591a\u5c11\u4e2a\u5143\u7d20<ul> <li>\\(\\displaystyle [m, n]\\) \u6709 m - n \u4e2a\u5143\u7d20</li> </ul> </li> <li>\u800c\u4e14\u53ef\u4ee5\u8868\u793a\u7a7a\u533a\u95f4 \\(\\displaystyle [n, n]\\) </li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#27","title":"2.7 \u5c0f\u7ed3","text":"<ul> <li>\u8868\u8fbe\u5f0f<ul> <li>\u64cd\u4f5c\u6570\u7684\u7ec4\u5408\u65b9\u5f0f</li> <li>\u64cd\u4f5c\u6570\u5982\u4f55\u88ab\u8f6c\u6362</li> <li>\u64cd\u4f5c\u6570\u7684\u8fd0\u7b97\u6b21\u5e8f</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#3","title":"3 \u4f7f\u7528\u6279\u91cf\u6570\u636e","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#31","title":"3.1 \u8ba1\u7b97\u5b66\u751f\u6210\u7ee9","text":"C++<pre><code>#include &lt;iomanip&gt;\n#include &lt;ios&gt;\n#include &lt;iostream&gt;\n#include &lt;string&gt;\n\nusing std::cin;\nusing std::cout;\nusing std::endl;\nusing std::precision;\n\nint main() {\n    cout &lt;&lt; \"Please enter your first name:\";\n    string name;\n    cin &gt;&gt; name;\n    cout &lt;&lt; \"Hello, \" &lt;&lt; name &lt;&lt; \"!\" &lt;&lt; endl;\n\n    cout &lt;&lt; \"Please enter your midterm and final exam grades:\";\n    double midterm, final;\n    cin &gt;&gt; midterm &gt;&gt; final;\n\n    cout &lt;&lt; \"Enter all your homework grades, \" \n            \"followed by end-of-file:\";\n\n    int count = 0;\n    double sum = 0;\n\n    double x;\n\n    while (cin &gt;&gt; x) {\n        ++ count;\n        sum += x;\n    }\n\n    streamsize prec = cout.precision();\n    cout &lt;&lt; \"Your final grade is \" &lt;&lt; setprecision(3)\n         &lt;&lt; 0.2 * midterm + 0.4 * final + 0.4 * sum / count\n         &lt;&lt; setprecision(prec) &lt;&lt; endl; //\u91cd\u7f6e\u6709\u6548\u4f4d\u6570 \u6216\u5199\u6210cout.precision(prec);\n    return 0;\n}\n</code></pre> <ul> <li>\u8f93\u5165\u8fd0\u7b97\u7b26\u8fd4\u56de\u5b83\u7684\u5de6\u64cd\u4f5c\u6570\u4f5c\u4e3a\u7ed3\u679c</li> <li>\u5374\u7701\u521d\u59cb\u5316</li> <li>setprecision \u4e5f\u662f\u4e00\u4e2a\u63a7\u5236\u5668: \u4e3a\u6d41\u7684\u540e\u7ee7\u8f93\u51fa\u8bbe\u7f6e\u4e86\u4e00\u4e2a\u7279\u5b9a\u7684\u6709\u6548\u4f4d\u6570</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#311","title":"3.1.1 \u68c0\u6d4b\u8f93\u51fa","text":"<ul> <li>istream \u53ef\u4ee5\u88ab\u8f6c\u6362\u6210 bool \u503c</li> <li>\u6709\u4e09\u79cd\u60c5\u51b5\u6761\u4ef6\u4f1a\u53d8\u5047:<ul> <li>\u8fbe\u5230\u8f93\u5165\u6587\u4ef6\u7684\u7ed3\u5c3e</li> <li>\u8f93\u5165\u548c\u6211\u4eec\u8bd5\u56fe\u8bfb\u53d6\u7684\u53d8\u91cf\u7c7b\u578b\u4e0d\u4e00\u81f4</li> <li>\u68c0\u6d4b\u5230\u4e00\u4e2a\u786c\u4ef6\u95ee\u9898</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#312","title":"3.1.2 \u5faa\u73af\u4e0d\u53d8\u5f0f","text":"<p>\u4e0d\u662f\u5f88\u61c2</p>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#32","title":"3.2 \u7528\u4e2d\u503c\u4ee3\u66ff\u5e73\u5747\u503c","text":"<p>\u90a3\u4e48\u5c31\u8981\u6392\u5e8f\u4e86</p>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#321","title":"3.2.1 \u628a\u6570\u636e\u96c6\u5408\u5b58\u50a8\u5728\u5411\u91cf\u4e2d","text":"C++<pre><code>double x;\nvector&lt;double&gt; homework;\n\nwhile(cin &gt;&gt; x)\n    homework.push_back(x);\n</code></pre> <ul> <li>\u6211\u4eec\u4f7f\u7528\u4e86\u4e00\u79cd\u540d\u4e3a\u6a21\u677f\u7c7b\u7684\u8bed\u8a00\u7279\u5f81</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#322","title":"3.2.2 \u4ea7\u751f\u8f93\u51fa","text":"C++<pre><code>typedef vector&lt;double&gt;::size_type vec_sz;\nvec_sz size = homework.size();\n</code></pre> <ul> <li>\u6211\u4eec\u5e0c\u671b\u4fdd\u6301\u7cfb\u7edf\u73af\u5883\u7684\u72ec\u7acb\u6027</li> </ul> C++<pre><code>if (size  == 0) {\n    cout &lt;&lt; endl &lt;&lt; \"You must enter your grades. \"\n                    \"Please try again.\" &lt;&lt; endl;\n    return 1;\n}\n\nsort (homework.begin(), homework.end());\n\nvec_sz mid = size / 2;\ndouble median;\nmedian = size % 2 == 0 ? (homework[mid] + homework[mid - 1]) / 2\n                       : homework[mid];\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#323","title":"3.2.3 \u4e00\u4e9b\u66f4\u4e3a\u6df1\u5165\u7684\u89c2\u5bdf","text":"<ul> <li>size_type \u662f\u65e0\u7b26\u53f7\u6574\u6570\u7c7b\u578b</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#33","title":"3.3 \u5c0f\u7ed3","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#4","title":"4 \u7ec4\u7ec7\u7a0b\u5e8f\u548c\u6570\u636e","text":"<ul> <li>\u8fd9\u4e9b\u5e93\u5de5\u5177\u6709\u51e0\u4e2a\u540c\u6837\u7684\u7279\u6027:<ul> <li>\u80fd\u89e3\u51b3\u67d0\u4e9b\u7279\u5b9a\u7c7b\u578b\u7684\u95ee\u9898</li> <li>\u4e0e\u5176\u4ed6\u7684\u5927\u591a\u6570\u5de5\u5177\u90fd\u76f8\u4e92\u72ec\u7acb</li> <li>\u90fd\u5177\u6709\u4e00\u4e2a\u540d\u79f0</li> </ul> </li> <li>\u4e24\u79cd\u65b9\u6cd5\u6765\u7ec4\u7ec7\u5927\u578b\u7684\u7a0b\u5e8f<ul> <li>\u51fd\u6570</li> <li>\u6570\u636e\u7ed3\u6784</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#41","title":"4.1 \u7ec4\u7ec7\u8ba1\u7b97","text":"<ul> <li>\u53c2\u6570\u7684\u521d\u59cb\u503c\u662f\u76f8\u5e94\u53c2\u6570\u503c\u7684\u590d\u5236\uff0c\u5373\u6309\u503c\u8c03\u7528\uff08call by value\uff09</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#411","title":"4.1.1 \u67e5\u627e\u4e2d\u503c","text":"C++<pre><code>double median(vector&lt;double&gt; vec)\n{\n    typedef vector&lt;double&gt;::size_type vec_sz;\n    vec_sz size = vec.size();\n    if (size == 0)\n        throw domain_error(\"median of an empty vector\");\n    sort(vec.begin(), vec.end());\n    vec_sz mid = size / 2;\n    return size % 2 == 0 ? (vec[mid] + vec[mid - 1]) / 2 : vec[mid];\n}\n</code></pre> <ul> <li>\u629b\u51fa\u5f02\u5e38</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#412","title":"4.1.2 \u91cd\u65b0\u5236\u5b9a\u8ba1\u7b97\u6210\u7ee9\u7684\u7b56\u7565","text":"<ul> <li>\u53ea\u80fd\u628a\u4e0d\u662f\u5e38\u91cf\u7684\u5f15\u7528\u7ed9\u5e38\u91cf\u7684\uff0c\u5373\u6761\u4ef6\u53ea\u80fd\u52a0\u5f3a</li> <li>\u6709\u597d\u51e0\u4e2a\u540c\u6837\u51fd\u6570\u540d\u7684\u51fd\u6570\u65f6\uff0c\u4f1a\u53d1\u751f\u91cd\u8f7d</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#413","title":"4.1.3 \u8bfb\u5bb6\u5ead\u4f5c\u4e1a\u6210\u7ee9","text":"<ul> <li>\u5de6\u503c\u53c2\u6570: \u975e\u4e34\u65f6\u5bf9\u8c61</li> </ul> C++<pre><code>istream read_hw(istream&amp; in, vector&lt;double&gt;&amp; hw)\n{\n    if (in) {\n        hw.clear();\n        double x;\n        while (in &gt;&gt; x) \n            hw.push_back(x);\n        in.clear();\n    }\n    return in;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#414","title":"4.1.4 \u4e09\u79cd\u51fd\u6570\u53c2\u6570","text":"<ul> <li>\u4e00\u822c\u800c\u8a00\uff0c\u6211\u4eec\u6ca1\u6709\u5fc5\u8981\u4e3a\u4e86 int \u6216 double \u8fd9\u6837\u89c1\u5230\u4f60\u7684\u5185\u90e8\u7c7b\u578b\u7684\u53c2\u6570\u800c\u53bb\u4f7f\u7528 const \u5f15\u7528</li> <li>\u5982\u679c\u4f20\u5165 read_hw () \u7684\u4e0d\u662f\u4e00\u4e2a\u5de6\u503c\uff0c\u90a3\u4e48\u6211\u4eec\u4f1a\u628a\u8f93\u5165\u5b58\u5230\u4e00\u4e2a\u6211\u4eec\u65e0\u59a8\u8bbf\u95ee\u7684\u5bf9\u8c61\u4e2d\uff08\u6539\u5bf9\u8c61\u4f1a\u5728 read_hw() \u8fd4\u56de\u65f6\u7acb\u5373\u6d88\u5931\uff09</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#415","title":"4.1.5 \u4f7f\u7528\u51fd\u6570\u6765\u8ba1\u7b97\u5b66\u751f\u7684\u6210\u7ee9","text":"<ul> <li>\u4e0d\u8981\u8ba9\u4e00\u6761\u8bed\u53e5\u4e2d\u7684\u526f\u4f5c\u7528\u4e2a\u6570\u8d85\u8fc7\u4e00\u4e2a</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#42","title":"4.2 \u7ec4\u7ec7\u6570\u636e","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#421","title":"4.2.1 \u628a\u4e00\u4e2a\u5b66\u751f\u7684\u6240\u6709\u6570\u636e\u653e\u7f6e\u5728\u4e00\u8d77","text":"C++<pre><code>struct Student_info {\n    string name;\n    double midterm, final;\n    vector&lt;double&gt; homework;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#422","title":"4.2.2 \u5904\u7406\u5b66\u751f\u8bb0\u5f55","text":"C++<pre><code>istream&amp; read(istream&amp; is, Student_info&amp; s)\n{\n    is &gt;&gt; s.name &gt;&gt; s.midterm &gt;&gt; s.final;\n    read_hw(is, s.homework);\n    return is;\n}\n\ndouble grade(const Student_info&amp; s) \n{\n    return grade(s.midterm, s.final, s.homework);\n}\n\nbool compare(const Student_info&amp; x, const Studeng_info&amp; y)\n{\n    return x.name &lt; y.name;\n}\n\nsort(students.begin(), students.end(), compare;\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#423","title":"4.2.3 \u751f\u6210\u62a5\u8868","text":"C++<pre><code>cout &lt;&lt; setw(maxlen + 1) &lt;&lt; student[i].name;\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#43","title":"4.3 \u628a\u5404\u90e8\u5206\u4ee3\u7801\u8fde\u63a5\u5230\u4e00\u8d77","text":"Text Only<pre><code>#ifndef GUARD_median_h\n#define GUARD_median_h //\u9884\u5904\u7406\u7a0b\u5e8f\n\n#include &lt;vector&gt;\ndouble median(vector&lt;double&gt;);\n\n#endif\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#44","title":"4.4 \u628a\u8ba1\u7b97\u6210\u7ee9\u7684\u7a0b\u5e8f\u5206\u5757","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#45","title":"4.5 \u4fee\u6b63\u540e\u7684\u8ba1\u7b97\u6210\u7ee9\u7684\u7a0b\u5e8f","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#46","title":"4.6 \u5c0f\u7ed3","text":"<ul> <li>\u7528\u6237\u5b9a\u4e49\u7684\u5934\u6587\u4ef6\u4e00\u822c\u4ee5 .h \u7ed3\u5c3e</li> <li>\u4e0d\u5e94\u8be5\u5728\u5934\u6587\u4ef6\u4e2d\u4f7f\u7528 using \u58f0\u660e</li> <li>\u7528 \\(\\displaystyle \\#\\) ifndef \u6307\u4ee4\u6765\u9632\u6b62\u5bf9\u5934\u6587\u4ef6\u7684\u91cd\u590d\u5305\u542b</li> <li>\u5185\u8054\u5b50\u8fc7\u7a0b\u901a\u5e38\u65f6\u5728\u5934\u6587\u4ef6\u800c\u4e0d\u662f\u5728\u6e90\u6587\u4ef6\u4e2d\u5b9a\u4e49 inline<ul> <li>\u4e3a\u4e86\u6bd4\u5356\u4f60\u51fd\u6570\u8c03\u7528\u7684\u989d\u5916\u5f00\u9500\uff0c\u7f16\u8bd1\u5668\u4f1a\u7528\u51fd\u6570\u4f53\u7684\u4e00\u4e2a\u590d\u5236\u6765\u66ff\u6362\u5bf9\u51fd\u6570\u7684\u6bcf\u4e00\u4e2a\u8c03\u7528\u5e76\u6839\u636e\u9700\u8981\u8fdb\u884c\u4fee\u6b63</li> </ul> </li> <li>\u5f02\u5e38\u5904\u7406</li> </ul> C++<pre><code>try{\n} catch (t) { }\n</code></pre> <ul> <li>\u5f02\u5e38\u7c7b</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#5","title":"5 \u4f7f\u7528\u987a\u5e8f\u5bb9\u5668\u5e76\u5206\u6790\u5b57\u7b26\u4e32","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#51","title":"5.1 \u6309\u7c7b\u522b\u6765\u533a\u5206\u5b66\u751f","text":"C++<pre><code>vector&lt;Student_info&gt; extract_fails(vector&lt;Student_info&gt;&amp; students)\n{\n    vector&lt;Student_info&gt; pass, fail;\n    for (vector&lt;Student_info&gt;::size_type i = 0; i != students.size(); ++i;)\n    if (fgrade(student[i]))\n        fail.push_back(student[i]);\n    else\n        pass.push_back(student[i]);\n    students = pass;\n    return fail;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#511","title":"5.1.1 \u5c31\u5730\u5220\u9664\u51fd\u6570","text":"C++<pre><code>vector&lt;Student_info&gt; extract_fails(vector&lt;Student_info&gt;&amp; students)\n{\n    vector&lt;Student_info&gt; fail;\n    vector&lt;Student_info&gt;::size_type i =  0;\n    while (i != students.size()) {\n        if (fgrade(studentp[i])) {\n            fail.push_back(students[i]);\n            students.erase(students.begin() + i);\n        } else\n            ++i;\n    }\n    return fail;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#512","title":"5.1.2 \u987a\u5e8f\u5b58\u53d6\u4e0e\u968f\u673a\u5b58\u53d6","text":"<ul> <li>\u8bbf\u95ee\u5bb9\u5668\u65f6\u6240\u91c7\u53d6\u7684\u6b21\u5e8f\u4f1a\u5bfc\u81f4\u4e0d\u540c\u7684\u6027\u80fd\u7279\u6027</li> <li>\u4e8e\u662f\u4fbf\u6709\u4e86 iterator</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#52","title":"5.2 \u8fed\u4ee3\u5668","text":"<ul> <li>iterator<ul> <li>\u8bc6\u522b\u4e00\u4e2a\u5bb9\u5668\u4ee5\u53ca\u5bb9\u5668\u4e2d\u7684\u4e00\u4e2a\u5143\u7d20</li> <li>\u8ba9\u6211\u4eec\u68c0\u67e5\u5b58\u50a8\u5728\u8fd9\u4e2a\u5143\u7d20\u4e2d\u7684\u503c</li> <li>\u63d0\u4f9b\u64cd\u4f5c\u6765\u79fb\u52a8\u5728\u5bb9\u6613\u4e2d\u7684\u5143\u7d20</li> <li>\u91c7\u7528\u5bf9\u5e94\u4e8e\u5bb9\u5668\u6240\u80fd\u591f\u6709\u6548\u5904\u7406\u7684\u65b9\u5f0f\u5bf9\u53ef\u7528\u7684\u64cd\u4f5c\u8fdb\u884c\u7ea6\u675f</li> </ul> </li> </ul> C++<pre><code>for (vector&lt;Student_info&gt;::size_type i = 0; i != students.end(); ++i)\n    cout &lt;&lt; students[i].name &lt;&lt; endl;\nfor (vector&lt;Student_info&gt;::const_iterator iter = students.begin();\n    iter != students.end(); ++iter) {\n    cout &lt;&lt; (*iter).name &lt;&lt; endl; }\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#521","title":"5.2.1 \u8fed\u4ee3\u5668\u7c7b\u578b","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#522","title":"5.2.2 \u8fed\u4ee3\u5668\u64cd\u4f5c","text":"<ul> <li>end \u7d27\u63a5\u5728\u5bb9\u5668\u6700\u540e\u4e00\u4e2a\u5143\u7d20\u540e\u9762\u7684\u4f4d\u7f6e</li> <li>++iter \u7528\u4e86\u8fed\u4ee3\u5668\u7c7b\u578b\u91cd\u8f7d</li> <li>\u5f53\u6211\u4eec\u7528\u95f4\u63a5\u5f15\u7528\u8fd0\u7b97\u7b26 \\(\\displaystyle *\\) \u6765\u8bbf\u95ee\u8fd9\u4e2a\u5143\u7d20\uff0c\u90a3\u4e48\u4ed6\u4f1a\u8fd4\u56de\u4e00\u4e2a\u5de6\u503c\uff08\u8fed\u4ee3\u5668\u6240\u6307\u5411\u7684\u5143\u7d20\uff09</li> <li>\\(\\displaystyle .\\) \u7684\u4f18\u5148\u7ea7\u6bd4 \\(\\displaystyle *\\) \u9ad8</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#523","title":"5.2.3 \u4e00\u70b9\u8bed\u6cd5\u77e5\u8bc6","text":"C++<pre><code>(*iter).name\niter-&gt;name\n//both are ok\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#524-students-erase-students-begin-i","title":"5.2.4 students. erase (students. begin () + i) \u7684\u542b\u4e49","text":"<ul> <li>students \u4e0d\u652f\u6301\u968f\u673a\u8bbf\u95ee\u7d22\u5f15\u64cd\u4f5c\u7684\u5bb9\u5668\uff0c\u4f46\u662f\u4ecd\u4f1a\u5141\u8bb8\u8fed\u4ee3\u5668\u7684\u968f\u673a\u8bbf\u95ee</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#53","title":"5.3 \u7528\u8fed\u4ee3\u5668\u6765\u4ee3\u66ff\u7d22\u5f15","text":"C++<pre><code>vecotr&lt;Student_info&gt; extract_fails(vector&lt;Student_info&gt;&amp; students)\n{\n    vector&lt;Student_info&gt; fail;\n    vector&lt;Student_info&gt;::iterator iter = students.begin();\n    while (iter != students.end()) {\n        if (fgrade(*iter)) {\n            fail.push_back(*iter);\n            iter = students.erase(iter); //important\n        } else\n            ++iter;\n    }\n    return fail;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#54","title":"5.4 \u91cd\u65b0\u601d\u8003\u6570\u636e\u7ed3\u6784\u4ee5\u5b9e\u73b0\u66f4\u597d\u7684\u6027\u80fd","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#55-list","title":"5.5 list \u7c7b\u578b","text":"<ul> <li>\u76f4\u63a5\u628a\u6240\u6709\u7684 vector \u6362\u6210 list \u5c31\u53ef\u4ee5\u4e86</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#551","title":"5.5.1 \u4e00\u4e9b\u91cd\u8981\u7684\u5dee\u522b","text":"<ul> <li>list \u7c7b\u7684\u8fed\u4ee3\u5668\u5e76\u4e0d\u652f\u6301\u5b8c\u5168\u968f\u673a\u7684\u8bbf\u95ee<ul> <li>\u6240\u4ee5\u6211\u4eec\u4e0d\u80fd\u7528 sort \u51fd\u6570</li> <li>\u4f46\u662f list \u6709\u81ea\u5df1\u6210\u5458\u51fd\u6570</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#552","title":"5.5.2 \u4e00\u4e2a\u607c\u4eba\u7684\u8bdd\u9898","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#56","title":"5.6 \u5206\u5272\u5b57\u7b26\u4e32","text":"C++<pre><code>vector&lt;string&gt; split(const string&amp; s)\n{\n    vector&lt;string&gt; ret;\n    typedef string::size_def string_size;\n    string_size i = 0;\n    while (i != s.size()) {\n        while (i != s.size() &amp;&amp; isspace(s[i])) // is from &lt;cctype&gt;\n            ++i;\n        string_size j = i;\n        while (j != s.size() &amp;&amp; !isspace(s[i]))\n            ++j;\n        if (i != j) {\n            ret.push_back(s.substr(i, j - i));\n            i = j;\n        }\n    }\n    return ret;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#57-split","title":"5.7 \u6d4b\u8bd5 split \u51fd\u6570","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#58","title":"5.8 \u8fde\u63a5\u5b57\u7b26\u4e32","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#581","title":"5.8.1 \u4e3a\u56fe\u6848\u88c5\u6846","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#582","title":"5.8.2 \u7eb5\u5411\u8fde\u63a5","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#583","title":"5.8.3 \u6a2a\u5411\u8fde\u63a5","text":"<p>TODO</p>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#59","title":"5.9 \u5c0f\u7ed3","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#6","title":"6 \u4f7f\u7528\u5e93\u7b97\u6cd5","text":"<ul> <li>\u5229\u7528\u516c\u7528\u63a5\u53e3\u6765\u63d0\u4f9b\u4e00\u4e2a\u6807\u51c6\u7b97\u6cd5\u96c6\u5408</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#61","title":"6.1 \u5206\u6790\u5b57\u7b26\u4e32","text":"C++<pre><code>for (vector&lt;string&gt;::const_iterator it = bottom.begin(); it != bottom.end(); ++i)\n    ret.push_back(*it);\n\nret.insert(ret.end(), bottom.begin(), bottom.end());\n\ncopy(bottom.begin(), bottom.end(), back_inserter(ret));\n</code></pre> <ul> <li>copy \u662f\u4e00\u4e2a\u6cdb\u578b (generic) \u7b97\u6cd5\u7684\u4f8b\u5b50</li> <li>back_inserter \u662f\u4e00\u4e2a\u8fed\u4ee3\u5668\u9002\u914d\u5668\u7684\u4f8b\u5b50</li> </ul> C++<pre><code>copy(begin, end, out);\n//equals to\nwhile (begin != end)\n    *out++ = *begin++;\n    // equals to \n    // *out = *begin; ++out; ++begin;\n\nit = begin++;\n//equals to\nit = begin;\n++begin;\n</code></pre> <ul> <li>\u8fed\u4ee3\u5668\u9002\u914d\u5668\u662f\u4e00\u4e2a\u4ea7\u751f\u8fed\u4ee3\u5668\u7684\u4e1c\u897f</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#611-split","title":"6.1.1 \u53e6\u4e00\u4e2a\u5b9e\u73b0 split \u7684\u65b9\u6cd5","text":"C++<pre><code>bool space(char c) {\n    return isspace(c);\n}\nbool not_space(char c) {\n    return !isspace(c);\n}\nvector&lt;string&gt; split(const string&amp; str) {\n    typedef string::const_iterator iter;\n    vector&lt;string&gt; ret;\n    iter i = str.begin();\n    while(i != str.end()) {\n        i = find_if(i, str.end(), not_space);\n        iter j = find_if(i, str.end(), space);\n        if (i != str.end()) ret.push_back(string(i, j));\n        i = j;  \n    }\n    return ret;\n}\n</code></pre> <ul> <li>\u6211\u4eec\u9700\u8981\u7f16\u5199\u6211\u4eec space \u548c not_space \u662f\u7528\u6765\u89e3\u91ca\u6211\u4eec\u6240\u6307\u7684\u662f\u54ea\u4e2a\u7248\u672c\u7684 isspace</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#612","title":"6.1.2 \u56de\u6587","text":"C++<pre><code>bool is_palindrome(const string&amp; s) {\n    return equal(s.begin(), s.end(), s.rbegin());\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#613-url","title":"6.1.3 \u67e5\u627e URL","text":"<ul> <li>protocol://resource-name</li> </ul> C++<pre><code>vector&lt;string&gt; find_urls(const string&amp; s) {\n    vector&lt;string&gt; ret;\n    typedef string::const_iterator iter;\n    iter b = s.begin(), e = s.end();\n    while (b != e) {\n        b = url_beg(b, e);\n        if (b != e) {\n            iter after = url_end(b, e);\n            ret.push_back(string(b, after));\n            b = after;\n        }\n    }\n    return ret;\n}\n\nstring::const_iterator url_end(string::const_iterator b, string::const_iterator e) {\n    return find_if(b, e, not_url_char);\n}\n\nbool not_url_char(char c) {\n    static const string url_ch = \"~;/?@=&amp;$-_.+!*{},'\";\n    return !(isalnum(c)) || find(url_ch.begin(), url_ch.end(), c) != url_end());\n    //static\u58f0\u660e\u7684\u5c40\u90e8\u53d8\u91cf\u5177\u6709\u5168\u5c40\u5bff\u547d\uff0c\u751f\u5b58\u671f\u8d2f\u7a7f\u6574\u4e2a\u51fd\u6570\u8c03\u7528\u8fc7\u7a0b\n}\n\nstring::const_iterator url_beg(string::const_iterator b, string::const_iterator e) {\n    static const string sep = \"://\";\n    typedef string::const_iterator iter;\n    iter i = b;\n    while ((i = search(i, e, sep.begin(), sep.end())) != e) {\n        if (i != b &amp;&amp; i + sep.size() != e) {\n            iter beg = i;\n            while (beg != b &amp;&amp; isalpha(beg[-1]))\n                --beg;\n            if (beg != i &amp;&amp; i + sep.size() != e &amp;&amp; !not_url_char(i[sep.size()])) return beg;\n        }\n        if (i != e) i += sep.size();\n    }\n    return e;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#62","title":"6.2 \u5bf9\u8ba1\u7b97\u6210\u7ee9\u7684\u65b9\u6848\u8fdb\u884c\u6bd4\u8f83","text":"<ol> <li>\u8bfb\u6240\u6709\u7684\u5b66\u751f\u8bb0\u5f55\uff0c\u628a\u505a\u4e86\u5168\u90e8\u5bb6\u5ead\u4f5c\u4e1a\u7684\u5b66\u751f\u4e0e\u5176\u4ed6\u7684\u5b66\u751f\u5206\u9694\u5f00\u3002</li> <li>\u5bf9\u6bcf\u4e00\u7ec4\u4e2d\u7684\u6240\u6709\u5b66\u751f\u5206\u522b\u4f7f\u7528\u6bcf\u4e00\u4e2a\u7684\u8ba1\u7b97\u6210\u7ee9\u7684\u65b9\u6848\uff0c\u62a5\u544a\u6bcf\u4e00\u7ec4\u7684\u4e2d\u503c\u6210\u7ee9\u3002</li> </ol>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#621","title":"6.2.1 \u5904\u7406\u5b66\u751f\u8bb0\u5f55","text":"C++<pre><code>bool did_all_hw(const Student_info&amp; s) {\n    reutrn ((fint(s.homework.begin(), s.homework.end(), 0)) == s.homework.end());\n}\n\nvector&lt;Student_info&gt; did, didnt;\nStudent_info student;\n\nwhile (read(cin, student)) {\n    if (did_all_hw(student))\n        did.push_back(student);\n    else\n        didnt.push_back(student);\n}\nif (did.empty()) {\n    cout &lt;&lt; \"No student did all the homework!\" &lt;&lt; endl;\n    return 1;\n}\nif (didnt.empty()) {\n    cout &lt;&lt; \"Every student did all the homework!\" &lt;&lt; endl;\n    return 1;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#622","title":"6.2.2 \u5206\u6790\u6210\u7ee9","text":"C++<pre><code>write_analysis(cout, \"median\", median_analysis, did, didn't);\n\ndouble grade_aux(const Student_info&amp; s) {\n    tru {\n        return grade(s);\n    } catch (domain_error) {\n        return grade(s.midterm, s.final, 0);\n    }\n}\n\ndouble median_analysis(const vector&lt;Student_info&gt;&amp; students) {\n    vector&lt;double&gt; grades;\n    transdorm(students.begin(), students.end(), back_inserter(grades), grade_aux);\n    return medina(grades);\n}\n\nvoid write_analysis(ostream&amp; out, const string&amp; name, double analysis(const vector&lt;Student_info&gt;&amp;), const vector&lt;Student_info&gt;&amp; did, const vector&lt;Student_info&gt;&amp; didnt) {\n    out &lt;&lt; name &lt;&lt; \": median(did) = \" &lt;&lt; analysis(did) &lt;&lt; \", median(didnt) = \" &lt;&lt; analysis(didnt) &lt;&lt; endl; \n}\n\nint main() {\n    vector&lt;Student_info&gt; did, didnt;\n    Student_info student;\n    while (read(cin, student)) {\n        if (did_all_hw(student))\n            did.push_back(student);\n        else \n            didnt.push_back(student);\n    }\n    if (did.empty()) {\n        cout &lt;&lt; \"No student did all the homework!\" &lt;&lt; endl;\n        return 1;\n    }\n    if (didnt.empty()) {\n        cout &lt;&lt; \"Every student did all the homework!\" &lt;&lt; endl;\n        return 1;\n    }\n    write_analysis(cout, \"median\", median_analysis, did, didnt);\n    write_analysis(cout, \"average\", average_analysis, did, didnt);\n    write_analysis(cout, \"medina of homework turned in\", optimistic_median_analysis, did, didnt);\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#623","title":"6.2.3 \u8ba1\u7b97\u57fa\u4e8e\u5bb6\u5ead\u4f5c\u4e1a\u5e73\u5747\u6210\u7ee9\u7684\u603b\u6210\u7ee9","text":"C++<pre><code>double average(const vector&lt;double&gt;&amp; v) {\n    return accumulate(v.begin(), v.end(), 0.0) / v.size();\n}\n\ndouble average_analysis(const Student_info&amp; s) {\n    return grade(s.midterm, s.final, average(s.homework));\n}\n\ndouble average_analysis(const vector&lt;Student_info&gt;&amp; students) {\n    vector&lt;double&gt; grades;\n    transform(students.begin(), students.end(), back_inserter(grades), average_grade);\n    return median(grades);\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#624","title":"6.2.4 \u4e0a\u4ea4\u7684\u5bb6\u5ead\u4f5c\u4e1a\u7684\u4e2d\u503c","text":"C++<pre><code>double optimistic_median(const Student_info&amp; s) {\n    vector&lt;double&gt; nonzero;\n    remove_copy(s.homework.begin(), s.homework.end(), back_inserter(nonzero), 0);\n    if (nonzero.empty())\n        return grade(s.midterm, s.final, 0);\n    else \n        return grade(s.midterm, s.final, median(nonzero));\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#63","title":"6.3 \u5bf9\u5b66\u751f\u8fdb\u884c\u5206\u7c7b\u5e76\u56de\u987e\u4e00\u4e0b\u6211\u4eec\u7684\u95ee\u9898","text":"<ul> <li>\u4f7f\u7528\u4e00\u4e9b\u7b97\u6cd5\u5e93\u6765\u89e3\u51b3\u95ee\u9898</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#631","title":"6.3.1 \u4e00\u79cd\u4e24\u6b21\u4f20\u9012\u7684\u89e3\u51b3\u65b9\u6848","text":"C++<pre><code>vector&lt;Student_info&gt; extract_fails(vector&lt;Student_info&gt;&amp; students) {\n    vector&lt;Student_info&gt; fail;\n    remove_copy_if(students.begin(), students.end(), back_inserter(fail), pgrade);\n    students.earse(remove_if(students.begin(), students.end(), fgrade), student.end());\n    return fail;\n}\n\nbool pgrade(const Student_info&amp; s) {\n    return !fgrade(s);\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#64","title":"6.4 \u4e00\u79cd\u4e00\u6b21\u4f20\u9012\u7684\u89e3\u51b3\u65b9\u6848","text":"C++<pre><code>vector&lt;Student_info&gt; extract_fails(vector&lt;Student_info&gt;&amp; students) {\n    vector&lt;Student_info&gt;::iterator iter = stable_partition(students.begin(), students.end(), pgrade);\n    vector&lt;Student_info&gt; fail(iter, students.end());\n    students.erase(iter, students.end());\n    return fail;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#65","title":"6.5 \u7b97\u6cd5\u3001\u5bb9\u5668\u4ee5\u53ca\u8fed\u4ee3\u5668","text":"<ul> <li>\u7b97\u6cd5\u4f5c\u7528\u4e8e\u5bb9\u5668\u7684\u5143\u7d20\uff0c\u800c\u4e0d\u662f\u4f5c\u7528\u4e8e\u5bb9\u5668</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#7","title":"7 \u4f7f\u7528\u5173\u8054\u5bb9\u5668","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#71","title":"7.1 \u652f\u6301\u9ad8\u6548\u67e5\u627e\u7684\u5bb9\u5668","text":"<ul> <li>\u5173\u8054\u5bb9\u5668\u4f1a\u5bf9\u63d2\u5165\u7684\u5143\u7d20\u8fdb\u884c\u6392\u5e8f\u6765\u63d0\u9ad8\u67e5\u627e\u7684\u901f\u5ea6</li> <li>\u5173\u8054\u6570\u7ec4\u5c31\u662f\u6709 key-value \u7684\u6570\u7ec4<ul> <li>map: \u6620\u5c04\u8868\u7684\u7d22\u5f15\u4e0d\u4e00\u5b9a\u662f\u6574\u6570</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#72","title":"7.2 \u8ba1\u7b97\u5355\u8bcd\u6570","text":"C++<pre><code>int main() {\n    string s;\n    map&lt;string, int&gt; counters;\n    while (cin &gt;&gt; s) ++counters[s];\n    for (map&lt;string, int&gt;::const_iterator it = counters.begin(); it != couners.end(); ++it) {\n        cout &lt;&lt; it-&gt;first &lt;&lt; \"\\t\" &lt;&lt; it-&gt;second &lt;&lt; endl;\n    }\n    return 0;\n}\n</code></pre> <ul> <li>\u6570\u5bf9\uff08pair\uff09</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#73","title":"7.3 \u4ea7\u751f\u4e00\u4e2a\u4ea4\u53c9\u5f15\u7528\u8868","text":"C++<pre><code>map&lt;string, vector&lt;int&gt; &gt; xref(istream&amp; in, vector&lt;string&gt; find_words(const string&amp;) = split) {\n    string line;\n    int line_number = 0'\n    map&lt;string, vector&lt;int&gt;&gt; ret;\n    while (getline(in, line)) {\n        ++line_number;\n        vector&lt;string&gt; words = find_words(line);\n        for (vector&lt;string&gt;::const_iterator it = words.begin(); it != words.end(); ++it)\n            ret(*it).push_back(line_number);\n    }\n    return ret;\n}\n\n\nint main() {\n    map&lt;string, vector&lt;int&gt; &gt; ret = cref(cin);\n    for (map&lt;string, vector&lt;int&gt; &gt;::const_iterator it = ret.begin(); it != ret.end(); ++it) {\n        cout &lt;&lt; it-&gt;first &lt;&lt; \" occurs on line(s): \";\n        vector&lt;int&gt;::const_iterator line_it = it-&gt;second.begin();\n        cout &lt;&lt; *lint_it;\n        ++line_it;\n        while (line_it != it-&gt;second.end()) {\n            cout &lt;&lt; \", \" &lt;&lt; *line_it;\n            ++line_it;\n        }\n        cout &lt;&lt; endl;\n    }\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#74","title":"7.4 \u751f\u6210\u53e5\u5b50","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#741","title":"7.4.1 \u8868\u793a\u89c4\u5219","text":"C++<pre><code>typedef vector&lt;string&gt; Rule;\ntypedef vector&lt;Rule&gt; Rule_collection;\ntypedef map&lt;string, Rule_collection&gt; Grammer;\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#742","title":"7.4.2 \u8bfb\u5165\u6587\u6cd5","text":"C++<pre><code>Grammer read_grammer(istream&amp; in) {\n    Grammer ret;\n    string line;\n    while (getline(in, line)) {\n        vector&lt;string&gt; entry = split(line);\n        if (!entry.empty())\n            ret[entry[0]].push_back(Rule(entry.begin() + 1, entry.end()));\n    }\n    return ret;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#743","title":"7.4.3 \u751f\u6210\u53e5\u5b50","text":"C++<pre><code>vector&lt;string&gt; gen_sentence(const Grammar&amp; g) {\n    vector&lt;string&gt; ret;\n    gen_aux(g, \"&lt;sentence&gt;\", ret);\n    return ret;\n}\n\nbool bracketed(const string&amp; s) {\n    return s.size() &gt; 1 &amp;&amp; s[0] == '&lt;' &amp;&amp; s[s.size() - 1] == '&gt;';\n}\n\nvoid gen_aux(const Grammar&amp; g, const string&amp; word, vector&lt;string&gt;&amp; ret) {\n    if (!bracketed(word)) {\n        ret.push_back(word);\n    } else {\n        Grammar::const_iterator it = g.find(word);\n        if (it == g.end())\n            throw logic_error(\"empty rule\");\n        const Rule_collection&amp; c = it-&gt;seond;\n        const Rule&amp; r = c[nrand(c.size())];\n        for (Rule::const_iterator i = r.begin(); i != r.end(); ++i)\n            gen_aux(g, *i, ret);\n    }\n}\n\nint main() {\n    vector&lt;string&gt; sentence = gen_sentence(read_grammar(cin));\n    vector&lt;string&gt;::const_iterator it = sentence.begin();\n    if (!sentence.empty()) {\n        cout &lt;&lt; *it;\n        ++it;   \n    }\n    while (it != sentence.end()) {\n        cout &lt;&lt; \" \" &lt;&lt; *it;\n        ++it;\n    }\n    cout &lt;&lt; endl;\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#744","title":"7.4.4 \u9009\u62e9\u4e00\u4e2a\u968f\u673a\u51fd\u6570","text":"C++<pre><code>int nrand(int n) {\n    if (n &lt;= 0 || n &gt; RAND_MAX)\n        throw domain_error(\"Argument to nrand is out of range\");\n    const int bucket_size = RAND_MAX / n;\n    int r;\n    do r = rand() / bucket_size;\n    while (r &gt;= n);\n    return r;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#75","title":"7.5 \u5173\u4e8e\u6027\u80fd\u7684\u4e00\u70b9\u8bf4\u660e","text":"<ul> <li>\u7528\u6563\u5217\u8868\u5b9e\u73b0\u5173\u8054\u6570\u7ec4\u5728 C++\u4e2d\u7684\u662f\u5f88\u56f0\u96be\u7684 \u6ca1\u641e\u61c2 </li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#76","title":"7.6 \u5c0f\u7ed3","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#8","title":"8 \u7f16\u5199\u6cdb\u578b\u51fd\u6570","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#81","title":"8.1 \u6cdb\u578b\u51fd\u6570\u662f\u4ec0\u4e48","text":"<ul> <li>\u5728\u4f7f\u7528\u51fd\u6570\u4e4b\u524d\u4e0d\u77e5\u9053\u53c2\u6570\u6216\u8005\u8fd4\u56de\u7c7b\u578b\u662f\u4ec0\u4e48</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#811","title":"8.1.1 \u672a\u77e5\u7c7b\u578b\u7684\u4e2d\u503c","text":"<ul> <li>\u5b9e\u73b0\u4e86\u6cdb\u578b\u51fd\u6570\u7684\u8bed\u8a00\u7279\u5f81\u88ab\u79f0\u4f5c\u6a21\u677f\u51fd\u6570</li> </ul>"},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#9","title":"9 \u5b9a\u4e49\u65b0\u7c7b\u578b","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#10","title":"10 \u7ba1\u7406\u5185\u5b58\u548c\u4f4e\u7ea7\u6570\u636e\u7ed3\u6784","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#11_1","title":"11 \u5b9a\u4e49\u62bd\u8c61\u6570\u636e\u7c7b\u578b","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#12_1","title":"12 \u4f7f\u7c7b\u5bf9\u8c61\u50cf\u4e00\u4e2a\u6570\u503c\u4e00\u6837\u5de5\u4f5c","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#13_1","title":"13 \u4f7f\u7528\u7ee7\u627f\u4e0e\u52a8\u6001\u7ed1\u5b9a","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#14","title":"14 \u8fd1\u4e4e\u81ea\u52a8\u5730\u7ba1\u7406\u5185\u5b58","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#15","title":"15 \u518d\u8c08\u5b57\u7b26\u56fe\u5f62","text":""},{"location":"CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/#16-c","title":"16 \u4eca\u540e\u5982\u4f55\u5b66\u4e60 C++","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/","title":"C++","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#c","title":"C++","text":"<p> \u7ea6 3115 \u4e2a\u5b57  523 \u884c\u4ee3\u7801  9 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 22 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#1","title":"1 \u6587\u4ef6\u64cd\u4f5c","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#11","title":"1.1 \u6587\u4ef6\u7684\u6982\u5ff5","text":"<ul> <li>C/C++\u628a\u6bcf\u4e00\u4e2a\u6587\u4ef6\u90fd\u770b\u6210\u662f\u4e00\u4e2a\u6709\u5e8f\u7684\u5b57\u8282\u6d41\uff0c\u4ee5\u6587\u4ef6\u7ed3\u675f\u6807\u5fd7\uff08EOF\uff09\u7ed3\u675f</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#12","title":"1.2 \u6587\u4ef6\u7684\u64cd\u4f5c\u6b65\u9aa4","text":"<ol> <li>\u6253\u5f00\u6587\u4ef6\uff0c\u8bb2\u6587\u4ef6\u6307\u9488\u6307\u5411\u6587\u4ef6\uff0c\u51b3\u5b9a\u6253\u5f00\u6587\u4ef6\u7684\u7c7b\u578b</li> <li>\u5bf9\u6587\u4ef6\u8fdb\u884c\u8bfb/\u5199\u64cd\u4f5c</li> <li>\u5728\u4f7f\u7528\u5b8c\u6587\u4ef6\u540e\uff0c\u5173\u95ed\u6587\u4ef6</li> </ol>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#13","title":"1.3 \u4e00\u4e9b\u51fd\u6570","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#131-freopen","title":"1.3.1 freopen \u51fd\u6570","text":"C++<pre><code>FILE* freopen(const char* filename, const char* mode, FILE* stream);\n</code></pre> <ul> <li>\u53c2\u6570\u8bf4\u660e<ul> <li><code>filename</code>: \u8981\u6253\u5f00\u7684\u6587\u4ef6\u540d</li> <li><code>mode</code>: \u6587\u4ef6\u6253\u5f00\u7684\u6a21\u5f0f\uff0c\u8868\u793a\u6587\u4ef6\u8bbf\u95ee\u7684\u6743\u9650</li> <li><code>stream</code>: \u6587\u4ef6\u6307\u9488\uff0c\u901a\u5e38\u4f7f\u7528\u6807\u51c6\u6587\u4ef6\u6d41 (<code>stdin/stdout</code>) \u6216\u6807\u51c6\u9519\u8bef\u8f93\u51fa\u6d41 (<code>stderr</code>)</li> <li>\u8fd4\u56de\u503c\uff1a\u6587\u4ef6\u6307\u9488\uff0c\u6307\u5411\u88ab\u6253\u5f00\u6587\u4ef6</li> </ul> </li> <li>\u6587\u4ef6\u6253\u5f00\u683c\u5f0f<ul> <li><code>r</code>\uff1a\u4ee5\u53ea\u8bfb\u65b9\u5f0f\u6253\u5f00\u6587\u4ef6\uff0c\u6587\u4ef6\u5fc5\u987b\u5b58\u5728\uff0c\u53ea\u5141\u8bb8\u8bfb\u5165\u6570\u636e\u00a0\uff08\u5e38\u7528\uff09</li> <li><code>r+</code>\uff1a\u4ee5\u8bfb/\u5199\u65b9\u5f0f\u6253\u5f00\u6587\u4ef6\uff0c\u6587\u4ef6\u5fc5\u987b\u5b58\u5728\uff0c\u5141\u8bb8\u8bfb/\u5199\u6570\u636e</li> <li><code>rb</code>\uff1a\u4ee5\u53ea\u8bfb\u65b9\u5f0f\u6253\u5f00\u4e8c\u8fdb\u5236\u6587\u4ef6\uff0c\u6587\u4ef6\u5fc5\u987b\u5b58\u5728\uff0c\u53ea\u5141\u8bb8\u8bfb\u5165\u6570\u636e</li> <li><code>rb+</code>\uff1a\u4ee5\u8bfb/\u5199\u65b9\u5f0f\u6253\u5f00\u4e8c\u8fdb\u5236\u6587\u4ef6\uff0c\u6587\u4ef6\u5fc5\u987b\u5b58\u5728\uff0c\u5141\u8bb8\u8bfb/\u5199\u6570\u636e</li> <li><code>rt+</code>\uff1a\u4ee5\u8bfb/\u5199\u65b9\u5f0f\u6253\u5f00\u6587\u672c\u6587\u4ef6\uff0c\u5141\u8bb8\u8bfb/\u5199\u6570\u636e</li> <li><code>w</code>\uff1a\u4ee5\u53ea\u5199\u65b9\u5f0f\u6253\u5f00\u6587\u4ef6\uff0c\u6587\u4ef6\u4e0d\u5b58\u5728\u4f1a\u65b0\u5efa\u6587\u4ef6\uff0c\u5426\u5219\u6e05\u7a7a\u5185\u5bb9\uff0c\u53ea\u5141\u8bb8\u5199\u5165\u6570\u636e\u00a0\uff08\u5e38\u7528\uff09</li> <li><code>w+</code>\uff1a\u4ee5\u8bfb/\u5199\u65b9\u5f0f\u6253\u5f00\u6587\u4ef6\uff0c\u6587\u4ef6\u4e0d\u5b58\u5728\u5c06\u65b0\u5efa\u6587\u4ef6\uff0c\u5426\u5219\u6e05\u7a7a\u5185\u5bb9\uff0c\u5141\u8bb8\u8bfb/\u5199\u6570\u636e</li> <li><code>wb</code>\uff1a\u4ee5\u53ea\u5199\u65b9\u5f0f\u6253\u5f00\u4e8c\u8fdb\u5236\u6587\u4ef6\uff0c\u6587\u4ef6\u4e0d\u5b58\u5728\u5c06\u4f1a\u65b0\u5efa\u6587\u4ef6\uff0c\u5426\u5219\u6e05\u7a7a\u5185\u5bb9\uff0c\u53ea\u5141\u8bb8\u5199\u5165\u6570\u636e</li> <li><code>wb+</code>\uff1a\u4ee5\u8bfb/\u5199\u65b9\u5f0f\u6253\u5f00\u4e8c\u8fdb\u5236\u6587\u4ef6\uff0c\u6587\u4ef6\u4e0d\u5b58\u5728\u5c06\u65b0\u5efa\u6587\u4ef6\uff0c\u5426\u5219\u6e05\u7a7a\u5185\u5bb9\uff0c\u5141\u8bb8\u8bfb/\u5199\u6570\u636e</li> <li><code>a</code>\uff1a\u4ee5\u53ea\u5199\u65b9\u5f0f\u6253\u5f00\u6587\u4ef6\uff0c\u6587\u4ef6\u4e0d\u5b58\u5728\u5c06\u65b0\u5efa\u6587\u4ef6\uff0c\u5199\u5165\u6570\u636e\u5c06\u88ab\u9644\u52a0\u5728\u6587\u4ef6\u672b\u5c3e\uff08\u4fdd\u7559 EOF \u7b26\uff09</li> <li><code>a+</code>\uff1a\u4ee5\u8bfb/\u5199\u65b9\u5f0f\u6253\u5f00\u6587\u4ef6\uff0c\u6587\u4ef6\u4e0d\u5b58\u5728\u5c06\u65b0\u5efa\u6587\u4ef6\uff0c\u5199\u5165\u6570\u636e\u5c06\u88ab\u9644\u52a0\u5728\u6587\u4ef6\u672b\u5c3e\uff08\u4e0d\u4fdd\u7559 EOF \u7b26\uff09</li> <li><code>at+</code>\uff1a\u4ee5\u8bfb/\u5199\u65b9\u5f0f\u6253\u5f00\u6587\u672c\u6587\u4ef6\uff0c\u5199\u5165\u6570\u636e\u5c06\u88ab\u9644\u52a0\u5728\u6587\u4ef6\u672b\u5c3e</li> <li><code>ab+</code>\uff1a\u4ee5\u8bfb/\u5199\u65b9\u5f0f\u6253\u5f00\u4e8c\u8fdb\u5236\u6587\u4ef6\uff0c\u5199\u5165\u6570\u636e\u5c06\u88ab\u9644\u52a0\u5728\u6587\u4ef6\u672b\u5c3e \u4f7f\u7528\u65b9\u5f0f</li> </ul> </li> </ul> C++<pre><code>#include &lt;cstdio&gt;\n#include &lt;iostream&gt;\nint mian(void) {\n    freopen(\"data.in\", \"r\", stdin); \n    // data.in \u5c31\u662f\u8bfb\u53d6\u7684\u6587\u4ef6\u540d\uff0c\u8981\u548c\u53ef\u6267\u884c\u6587\u4ef6\u653e\u5728\u540c\u4e00\u76ee\u5f55\u4e0b\n    freopen(\"data.out\", \"w\", stdout); \n    // data.out \u5c31\u662f\u8f93\u51fa\u6587\u4ef6\u7684\u6587\u4ef6\u540d\uff0c\u548c\u53ef\u6267\u884c\u6587\u4ef6\u5728\u540c\u4e00\u76ee\u5f55\u4e0b\n    fclose(stdin);\n    fclose(stdout);\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#132-fopen","title":"1.3.2 fopen \u51fd\u6570","text":"C++<pre><code>FILE* fopen(const char* path, const char* mode)\n</code></pre> <p>\u4f7f\u7528\u65b9\u5f0f</p> C++<pre><code>FILE *in, *out; // \u5b9a\u4e49\u6587\u4ef6\u6307\u9488 \nin = fopen(\"data.in\", \"r\"); \nout = fopen(\"data.out\", \"w\"); \n/* do what you want to do */ \nfclose(in); \nfclose(out);\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#14-c-ifstreamofstream","title":"1.4 C++ \u7684\u00a0<code>ifstream/ofstream</code>\u00a0\u6587\u4ef6\u8f93\u5165\u8f93\u51fa\u6d41","text":"C++<pre><code>#include &lt;fstream&gt; \nusing namespace std; \n// \u4e24\u4e2a\u7c7b\u578b\u90fd\u5728 std \u547d\u540d\u7a7a\u95f4\u91cc \nifstream fin(\"data.in\"); \nofstream fout(\"data.out\"); \nint main(void) { \n    /* \u4e2d\u95f4\u7684\u4ee3\u7801\u6539\u53d8 cin \u4e3a fin \uff0ccout \u4e3a fout \u5373\u53ef */ \n    fin.close(); \n    fout.close(); \n    return 0; \n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#2","title":"2 \u6807\u51c6\u5e93","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#21-stl","title":"2.1 STL \u5bb9\u5668","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#211","title":"2.1.1 \u5e8f\u5217\u5f0f\u5bb9\u5668","text":"<ul> <li>\u5411\u91cf(<code>vector</code>) \u540e\u7aef\u53ef\u9ad8\u6548\u589e\u52a0\u5143\u7d20\u7684\u987a\u5e8f\u8868\u3002<ul> <li>\u53ef\u4ee5\u52a8\u6001\u5206\u914d\u5185\u5b58</li> <li>\u91cd\u5199\u4e86\u6bd4\u8f83\u8fd0\u7b97\u7b26\u53ca\u8d4b\u503c\u8fd0\u7b97\u7b26</li> <li>\u4fbf\u5229\u7684\u521d\u59cb\u5316</li> <li>std::vector - cppreference.com</li> </ul> </li> <li>\u6570\u7ec4(<code>array</code>)C++11\uff0c\u5b9a\u957f\u7684\u987a\u5e8f\u8868\uff0cC \u98ce\u683c\u6570\u7ec4\u7684\u7b80\u5355\u5305\u88c5\u3002</li> <li>\u53cc\u7aef\u961f\u5217(<code>deque</code>) \u53cc\u7aef\u90fd\u53ef\u9ad8\u6548\u589e\u52a0\u5143\u7d20\u7684\u987a\u5e8f\u8868\u3002</li> <li>\u5217\u8868(<code>list</code>) \u53ef\u4ee5\u6cbf\u53cc\u5411\u904d\u5386\u7684\u94fe\u8868\u3002</li> <li>\u5355\u5411\u5217\u8868(<code>forward_list</code>) \u53ea\u80fd\u6cbf\u4e00\u4e2a\u65b9\u5411\u904d\u5386\u7684\u94fe\u8868\u3002</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#212","title":"2.1.2 \u5173\u8054\u5f0f\u5bb9\u5668","text":"<ul> <li>\u96c6\u5408(<code>set</code>) \u7528\u4ee5\u6709\u5e8f\u5730\u5b58\u50a8\u00a0\u4e92\u5f02\u00a0\u5143\u7d20\u7684\u5bb9\u5668\u3002\u5176\u5b9e\u73b0\u662f\u7531\u8282\u70b9\u7ec4\u6210\u7684\u7ea2\u9ed1\u6811\uff0c\u6bcf\u4e2a\u8282\u70b9\u90fd\u5305\u542b\u7740\u4e00\u4e2a\u5143\u7d20\uff0c\u8282\u70b9\u4e4b\u95f4\u4ee5\u67d0\u79cd\u6bd4\u8f83\u5143\u7d20\u5927\u5c0f\u7684\u8c13\u8bcd\u8fdb\u884c\u6392\u5217\u3002</li> <li>\u591a\u91cd\u96c6\u5408(<code>multiset</code>) \u7528\u4ee5\u6709\u5e8f\u5730\u5b58\u50a8\u5143\u7d20\u7684\u5bb9\u5668\u3002\u5141\u8bb8\u5b58\u5728\u76f8\u7b49\u7684\u5143\u7d20\u3002</li> <li>\u6620\u5c04(<code>map</code>) \u7531 {\u952e\uff0c\u503c} \u5bf9\u7ec4\u6210\u7684\u96c6\u5408\uff0c\u4ee5\u67d0\u79cd\u6bd4\u8f83\u952e\u5927\u5c0f\u5173\u7cfb\u7684\u8c13\u8bcd\u8fdb\u884c\u6392\u5217\u3002</li> <li>\u591a\u91cd\u6620\u5c04(<code>multimap</code>) \u7531 {\u952e\uff0c\u503c} \u5bf9\u7ec4\u6210\u7684\u591a\u91cd\u96c6\u5408\uff0c\u4ea6\u5373\u5141\u8bb8\u952e\u6709\u76f8\u7b49\u60c5\u51b5\u7684\u6620\u5c04\u3002</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#213","title":"2.1.3 \u65e0\u5e8f\uff08\u5173\u8054\u5f0f\uff09\u5bb9\u5668","text":"<ul> <li>\u65e0\u5e8f\uff08\u591a\u91cd\uff09\u96c6\u5408(<code>unordered_set</code>/<code>unordered_multiset</code>)C++11\uff0c\u4e0e\u00a0<code>set</code>/<code>multiset</code>\u00a0\u7684\u533a\u522b\u5728\u4e8e\u5143\u7d20\u65e0\u5e8f\uff0c\u53ea\u5173\u5fc3\u300c\u5143\u7d20\u662f\u5426\u5b58\u5728\u300d\uff0c\u4f7f\u7528\u54c8\u5e0c\u5b9e\u73b0\u3002</li> <li>\u65e0\u5e8f\uff08\u591a\u91cd\uff09\u6620\u5c04(<code>unordered_map</code>/<code>unordered_multimap</code>)C++11\uff0c\u4e0e\u00a0<code>map</code>/<code>multimap</code>\u00a0\u7684\u533a\u522b\u5728\u4e8e\u952e (key) \u65e0\u5e8f\uff0c\u53ea\u5173\u5fc3 \"\u952e\u4e0e\u503c\u7684\u5bf9\u5e94\u5173\u7cfb\"\uff0c\u4f7f\u7528\u54c8\u5e0c\u5b9e\u73b0\u3002</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#214","title":"2.1.4 \u5bb9\u5668\u9002\u914d\u5668","text":"<p>\u5bb9\u5668\u9002\u914d\u5668\u5176\u5b9e\u5e76\u4e0d\u662f\u5bb9\u5668\u3002\u5b83\u4eec\u4e0d\u5177\u6709\u5bb9\u5668\u7684\u67d0\u4e9b\u7279\u70b9\uff08\u5982\uff1a\u6709\u8fed\u4ee3\u5668\u3001\u6709\u00a0<code>clear()</code>\u00a0\u51fd\u6570\u2026\u2026\uff09\u3002</p> <p>\u300c\u9002\u914d\u5668\u662f\u4f7f\u4e00\u79cd\u4e8b\u7269\u7684\u884c\u4e3a\u7c7b\u4f3c\u4e8e\u53e6\u5916\u4e00\u79cd\u4e8b\u7269\u884c\u4e3a\u7684\u4e00\u79cd\u673a\u5236\u300d\uff0c\u9002\u914d\u5668\u5bf9\u5bb9\u5668\u8fdb\u884c\u5305\u88c5\uff0c\u4f7f\u5176\u8868\u73b0\u51fa\u53e6\u5916\u4e00\u79cd\u884c\u4e3a\u3002</p> <ul> <li>\u6808(<code>stack</code>) \u540e\u8fdb\u5148\u51fa (LIFO) \u7684\u5bb9\u5668\uff0c\u9ed8\u8ba4\u662f\u5bf9\u53cc\u7aef\u961f\u5217\uff08<code>deque</code>\uff09\u7684\u5305\u88c5\u3002</li> <li>\u961f\u5217(<code>queue</code>) \u5148\u8fdb\u5148\u51fa (FIFO) \u7684\u5bb9\u5668\uff0c\u9ed8\u8ba4\u662f\u5bf9\u53cc\u7aef\u961f\u5217\uff08<code>deque</code>\uff09\u7684\u5305\u88c5\u3002</li> <li>\u4f18\u5148\u961f\u5217(<code>priority_queue</code>) \u5143\u7d20\u7684\u6b21\u5e8f\u662f\u7531\u4f5c\u7528\u4e8e\u6240\u5b58\u50a8\u7684\u503c\u5bf9\u4e0a\u7684\u67d0\u79cd\u8c13\u8bcd\u51b3\u5b9a\u7684\u7684\u4e00\u79cd\u961f\u5217\uff0c\u9ed8\u8ba4\u662f\u5bf9\u5411\u91cf\uff08<code>vector</code>\uff09\u7684\u5305\u88c5\u3002</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#215","title":"2.1.5 \u5171\u540c\u70b9","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#2151","title":"2.1.5.1 \u5bb9\u5668\u58f0\u660e","text":"<ul> <li>\u90fd\u662f\u00a0<code>containerName&lt;typeName,...&gt; name</code>\u00a0\u7684\u5f62\u5f0f\uff0c\u4f46\u6a21\u677f\u53c2\u6570\uff08<code>&lt;&gt;</code>\u00a0\u5185\u7684\u53c2\u6570\uff09\u7684\u4e2a\u6570\u3001\u5f62\u5f0f\u4f1a\u6839\u636e\u5177\u4f53\u5bb9\u5668\u800c\u53d8\u3002</li> <li>\u672c\u8d28\u539f\u56e0\uff1aSTL \u5c31\u662f\u300c\u6807\u51c6\u6a21\u677f\u5e93\u300d\uff0c\u6240\u4ee5\u5bb9\u5668\u90fd\u662f\u6a21\u677f\u7c7b\u3002</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#2152","title":"2.1.5.2 \u8fed\u4ee3\u5668","text":"C++<pre><code>vector&lt;int&gt; data(10);\n\nfor (int i = 0; i &lt; data.size(); i++)\n    cout &lt;&lt; data[i] &lt;&lt; endl;\n\nfor (vector&lt;int&gt;::iterator iter = data.begin(); iter != data.end(); iter++)\n    cout &lt;&lt; *iter &lt;&lt; endl;\n//C++11 \u4ee5\u540e\u53ef\u4ee5\u7528 auto iter = data.begin() \u6765\u7b80\u5316\n</code></pre> <ul> <li>\u5206\u7c7b<ul> <li>InputIterator\uff08\u8f93\u5165\u8fed\u4ee3\u5668\uff09\uff1a\u53ea\u8981\u6c42\u652f\u6301\u62f7\u8d1d\u3001\u81ea\u589e\u548c\u89e3\u5f15\u8bbf\u95ee\u3002</li> <li>OutputIterator\uff08\u8f93\u51fa\u8fed\u4ee3\u5668\uff09\uff1a\u53ea\u8981\u6c42\u652f\u6301\u62f7\u8d1d\u3001\u81ea\u589e\u548c\u89e3\u5f15\u8d4b\u503c\u3002</li> <li>ForwardIterator\uff08\u5411\u524d\u8fed\u4ee3\u5668\uff09\uff1a\u540c\u65f6\u6ee1\u8db3 InputIterator \u548c OutputIterator \u7684\u8981\u6c42\u3002</li> <li>BidirectionalIterator\uff08\u53cc\u5411\u8fed\u4ee3\u5668\uff09\uff1a\u5728 ForwardIterator \u7684\u57fa\u7840\u4e0a\u652f\u6301\u81ea\u51cf\uff08\u5373\u53cd\u5411\u8bbf\u95ee\uff09\u3002</li> <li>RandomAccessIterator\uff08\u968f\u673a\u8bbf\u95ee\u8fed\u4ee3\u5668\uff09\uff1a\u5728 BidirectionalIterator \u7684\u57fa\u7840\u4e0a\u652f\u6301\u52a0\u51cf\u8fd0\u7b97\u548c\u6bd4\u8f83\u8fd0\u7b97\uff08\u5373\u968f\u673a\u8bbf\u95ee\uff09\u3002</li> <li>ContiguousIterator\uff08\u8fde\u7eed\u8fed\u4ee3\u5668\uff09\uff1a\u5728 RandomAccessIterator \u7684\u57fa\u7840\u4e0a\u8981\u6c42\u5bf9\u53ef\u89e3\u5f15\u7528\u7684\u8fed\u4ee3\u5668\u00a0<code>a + n</code>\u00a0\u6ee1\u8db3\u00a0<code>*(a + n)</code>\u00a0\u4e0e\u00a0<code>*(std::address_of(*a) + n)</code>\u00a0\u7b49\u4ef7\uff08\u5373\u8fde\u7eed\u5b58\u50a8\uff0c\u5176\u4e2d\u00a0<code>a</code>\u00a0\u4e3a\u8fde\u7eed\u8fed\u4ee3\u5668\u3001<code>n</code>\u00a0\u4e3a\u6574\u578b\u503c\uff09\u3002</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#2153","title":"2.1.5.3 \u5171\u6709\u51fd\u6570","text":"<ul> <li><code>=</code>\uff1a\u6709\u8d4b\u503c\u8fd0\u7b97\u7b26\u4ee5\u53ca\u590d\u5236\u6784\u9020\u51fd\u6570\u3002</li> <li><code>begin()</code>\uff1a\u8fd4\u56de\u6307\u5411\u5f00\u5934\u5143\u7d20\u7684\u8fed\u4ee3\u5668\u3002</li> <li><code>end()</code>\uff1a\u8fd4\u56de\u6307\u5411\u672b\u5c3e\u7684\u4e0b\u4e00\u4e2a\u5143\u7d20\u7684\u8fed\u4ee3\u5668\u3002<code>end()</code>\u00a0\u4e0d\u6307\u5411\u67d0\u4e2a\u5143\u7d20\uff0c\u4f46\u5b83\u662f\u672b\u5c3e\u5143\u7d20\u7684\u540e\u7ee7\u3002</li> <li><code>size()</code>\uff1a\u8fd4\u56de\u5bb9\u5668\u5185\u7684\u5143\u7d20\u4e2a\u6570\u3002</li> <li><code>max_size()</code>\uff1a\u8fd4\u56de\u5bb9\u5668\u00a0\u7406\u8bba\u4e0a\u00a0\u80fd\u5b58\u50a8\u7684\u6700\u5927\u5143\u7d20\u4e2a\u6570\u3002\u4f9d\u5bb9\u5668\u7c7b\u578b\u548c\u6240\u5b58\u50a8\u53d8\u91cf\u7684\u7c7b\u578b\u800c\u53d8\u3002</li> <li><code>empty()</code>\uff1a\u8fd4\u56de\u5bb9\u5668\u662f\u5426\u4e3a\u7a7a\u3002</li> <li><code>swap()</code>\uff1a\u4ea4\u6362\u4e24\u4e2a\u5bb9\u5668\u3002</li> <li><code>clear()</code>\uff1a\u6e05\u7a7a\u5bb9\u5668\u3002</li> <li><code>==</code>/<code>!=</code>/<code>&lt;</code>/<code>&gt;</code>/<code>&lt;=</code>/<code>&gt;=</code>\uff1a\u6309\u00a0\u5b57\u5178\u5e8f\u00a0\u6bd4\u8f83\u4e24\u4e2a\u5bb9\u5668\u7684\u5927\u5c0f\u3002\uff08\u6bd4\u8f83\u5143\u7d20\u5927\u5c0f\u65f6\u00a0<code>map</code>\u00a0\u7684\u6bcf\u4e2a\u5143\u7d20\u76f8\u5f53\u4e8e\u00a0<code>set&lt;pair&lt;key, value&gt; &gt;</code>\uff0c\u65e0\u5e8f\u5bb9\u5668\u4e0d\u652f\u6301\u00a0<code>&lt;</code>/<code>&gt;</code>/<code>&lt;=</code>/<code>&gt;=</code>\u3002\uff09</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#216-stl","title":"2.1.6 STL \u7b97\u6cd5","text":"<ul> <li><code>find</code>\uff1a\u987a\u5e8f\u67e5\u627e\u3002<code>find(v.begin(), v.end(), value)</code>\uff0c\u5176\u4e2d\u00a0<code>value</code>\u00a0\u4e3a\u9700\u8981\u67e5\u627e\u7684\u503c\u3002</li> <li><code>reverse</code>\uff1a\u7ffb\u8f6c\u6570\u7ec4\u3001\u5b57\u7b26\u4e32\u3002<code>reverse(v.begin(), v.end())</code>\u00a0\u6216\u00a0<code>reverse(a + begin, a + end)</code>\u3002</li> <li><code>unique</code>\uff1a\u53bb\u9664\u5bb9\u5668\u4e2d\u76f8\u90bb\u7684\u91cd\u590d\u5143\u7d20\u3002<code>unique(ForwardIterator first, ForwardIterator last)</code>\uff0c\u8fd4\u56de\u503c\u4e3a\u6307\u5411\u00a0\u53bb\u91cd\u540e\u00a0\u5bb9\u5668\u7ed3\u5c3e\u7684\u8fed\u4ee3\u5668\uff0c\u539f\u5bb9\u5668\u5927\u5c0f\u4e0d\u53d8\u3002\u4e0e\u00a0<code>sort</code>\u00a0\u7ed3\u5408\u4f7f\u7528\u53ef\u4ee5\u5b9e\u73b0\u5b8c\u6574\u5bb9\u5668\u53bb\u91cd\u3002</li> <li><code>sort</code>\uff1a\u6392\u5e8f\u3002<code>sort(v.begin(), v.end(), cmp)</code>\u00a0\u6216\u00a0<code>sort(a + begin, a + end, cmp)</code>\uff0c\u5176\u4e2d\u00a0<code>end</code>\u00a0\u662f\u6392\u5e8f\u7684\u6570\u7ec4\u6700\u540e\u4e00\u4e2a\u5143\u7d20\u7684\u540e\u4e00\u4f4d\uff0c<code>cmp</code>\u00a0\u4e3a\u81ea\u5b9a\u4e49\u7684\u6bd4\u8f83\u51fd\u6570\u3002</li> <li><code>stable_sort</code>\uff1a\u7a33\u5b9a\u6392\u5e8f\uff0c\u7528\u6cd5\u540c\u00a0<code>sort()</code>\u3002</li> <li><code>nth_element</code> \uff1a\u6309\u6307\u5b9a\u8303\u56f4\u8fdb\u884c\u5206\u7c7b\uff0c\u5373\u627e\u51fa\u5e8f\u5217\u4e2d\u7b2c \\(\\displaystyle n\\) \u5927\u7684\u5143\u7d20\uff0c\u4f7f\u5176\u5de6\u8fb9\u5747\u4e3a\u5c0f\u4e8e\u5b83\u7684\u6570\uff0c\u53f3\u8fb9\u5747\u4e3a\u5927\u4e8e\u5b83\u7684\u6570\u3002 <code>nth_element(v.begin(), v.begin() + mid, v.end(), cmp)</code>\u00a0\u6216\u00a0<code>nth_element(a + begin, a + begin + mid, a + end, cmp)</code> \u3002</li> <li><code>binary_search</code>\uff1a\u4e8c\u5206\u67e5\u627e\u3002<code>binary_search(v.begin(), v.end(), value)</code>\uff0c\u5176\u4e2d\u00a0<code>value</code>\u00a0\u4e3a\u9700\u8981\u67e5\u627e\u7684\u503c\u3002</li> <li><code>merge</code>\uff1a\u5c06\u4e24\u4e2a\uff08\u5df2\u6392\u5e8f\u7684\uff09\u5e8f\u5217\u00a0\u6709\u5e8f\u5408\u5e76\u00a0\u5230\u7b2c\u4e09\u4e2a\u5e8f\u5217\u7684\u00a0\u63d2\u5165\u8fed\u4ee3\u5668\u00a0\u4e0a\u3002<code>merge(v1.begin(), v1.end(), v2.begin(), v2.end() ,back_inserter(v3))</code>\u3002</li> <li><code>inplace_merge</code>\uff1a\u5c06\u4e24\u4e2a\uff08\u5df2\u6309\u5c0f\u4e8e\u8fd0\u7b97\u7b26\u6392\u5e8f\u7684\uff09\uff1a<code>[first,middle), [middle,last)</code>\u00a0\u8303\u56f4\u00a0\u539f\u5730\u5408\u5e76\u4e3a\u4e00\u4e2a\u6709\u5e8f\u5e8f\u5217\u3002<code>inplace_merge(v.begin(), v.begin() + middle, v.end())</code>\u3002</li> <li><code>lower_bound</code>\uff1a\u5728\u4e00\u4e2a\u6709\u5e8f\u5e8f\u5217\u4e2d\u8fdb\u884c\u4e8c\u5206\u67e5\u627e\uff0c\u8fd4\u56de\u6307\u5411\u7b2c\u4e00\u4e2a\u00a0\u5927\u4e8e\u7b49\u4e8e \u00a0\u7684\u5143\u7d20\u7684\u4f4d\u7f6e\u7684\u8fed\u4ee3\u5668\u3002\u5982\u679c\u4e0d\u5b58\u5728\u8fd9\u6837\u7684\u5143\u7d20\uff0c\u5219\u8fd4\u56de\u5c3e\u8fed\u4ee3\u5668\u3002<code>lower_bound(v.begin(),v.end(),x)</code>\u3002</li> <li><code>upper_bound</code>\uff1a\u5728\u4e00\u4e2a\u6709\u5e8f\u5e8f\u5217\u4e2d\u8fdb\u884c\u4e8c\u5206\u67e5\u627e\uff0c\u8fd4\u56de\u6307\u5411\u7b2c\u4e00\u4e2a\u00a0\u5927\u4e8e \u00a0\u7684\u5143\u7d20\u7684\u4f4d\u7f6e\u7684\u8fed\u4ee3\u5668\u3002\u5982\u679c\u4e0d\u5b58\u5728\u8fd9\u6837\u7684\u5143\u7d20\uff0c\u5219\u8fd4\u56de\u5c3e\u8fed\u4ee3\u5668\u3002<code>upper_bound(v.begin(),v.end(),x)</code>\u3002</li> <li><code>next_permutation</code>\uff1a\u5c06\u5f53\u524d\u6392\u5217\u66f4\u6539\u4e3a\u00a0\u5168\u6392\u5217\u4e2d\u7684\u4e0b\u4e00\u4e2a\u6392\u5217\u3002\u5982\u679c\u5f53\u524d\u6392\u5217\u5df2\u7ecf\u662f\u00a0\u5168\u6392\u5217\u4e2d\u7684\u6700\u540e\u4e00\u4e2a\u6392\u5217\uff08\u5143\u7d20\u5b8c\u5168\u4ece\u5927\u5230\u5c0f\u6392\u5217\uff09\uff0c\u51fd\u6570\u8fd4\u56de\u00a0<code>false</code>\u00a0\u5e76\u5c06\u6392\u5217\u66f4\u6539\u4e3a\u00a0\u5168\u6392\u5217\u4e2d\u7684\u7b2c\u4e00\u4e2a\u6392\u5217\uff08\u5143\u7d20\u5b8c\u5168\u4ece\u5c0f\u5230\u5927\u6392\u5217\uff09\uff1b\u5426\u5219\uff0c\u51fd\u6570\u8fd4\u56de\u00a0<code>true</code>\u3002<code>next_permutation(v.begin(), v.end())</code>\u00a0\u6216\u00a0<code>next_permutation(v + begin, v + end)</code>\u3002</li> <li><code>prev_permutation</code>\uff1a\u5c06\u5f53\u524d\u6392\u5217\u66f4\u6539\u4e3a\u00a0\u5168\u6392\u5217\u4e2d\u7684\u4e0a\u4e00\u4e2a\u6392\u5217\u3002\u7528\u6cd5\u540c\u00a0<code>next_permutation</code>\u3002</li> <li><code>partial_sum</code>\uff1a\u6c42\u524d\u7f00\u548c\u3002\u8bbe\u6e90\u5bb9\u5668\u4e3a\u00a0\uff0c\u76ee\u6807\u5bb9\u5668\u4e3a\u00a0\uff0c\u5219\u4ee4\u00a0\u3002<code>partial_sum(src.begin(), src.end(), back_inserter(dst))</code>\u3002</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#22-bitset","title":"2.2 bitset","text":"<p>TODO bitset - OI Wiki</p>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#23-string","title":"2.3 string","text":"<ul> <li>\u91cd\u8f7d\u8fd0\u7b97\u7b26</li> <li>\u52a8\u6001\u5206\u914d\u7a7a\u95f4</li> </ul> C++<pre><code>std::string s;\nprintf(\"%s\", s.c_str());\nprintf(\"s \u7684\u957f\u5ea6\u4e3a %lu\", s.size()); \nprintf(\"s \u7684\u957f\u5ea6\u4e3a %lu\", s.length()); \nprintf(\"s \u7684\u957f\u5ea6\u4e3a %lu\", strlen(s.c_str()));\nsubstr(pos, len);\ninsert(index, count, ch);\ninsert(index, str);\nerase(index, count);\nreplace(pos, count, str);\nreplace(first, last, str);\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#24-pair","title":"2.4 pair","text":"<ul> <li><code>pair</code> \u4e0d\u9700\u8981\u989d\u5916\u5b9a\u4e49\u7ed3\u6784\u4e0e\u91cd\u8f7d\u8fd0\u7b97\u7b26</li> </ul> C++<pre><code>pair&lt;int, double&gt; p0(1, 2.0);\npair&lt;int, double&gt; p2 = make_pair(1, 2.0);\nauto p3 = make_pair(1, 2.0);\n\nint i = p0.first; \ndouble d = p0.second;\np1.first++;\n\npriority_queue&lt;pair&lt;int, double&gt; &gt; q;\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3","title":"3 \u8fdb\u9636","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#31","title":"3.1 \u7c7b","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#32","title":"3.2 \u52a8\u6001\u5185\u5b58","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#321-new-delete","title":"3.2.1 new \u548c delete \u8fd0\u7b97\u7b26","text":"<ul> <li>\u6808: \u58f0\u660e\u7684\u6240\u6709\u53d8\u91cf\u5c06\u5360\u7528\u6808\u5185\u5b58</li> <li>\u5806: \u672a\u4f7f\u7528\u7684\u5185\u5b58</li> </ul> C++<pre><code>new data-type;\n\ndouble* pvalue = NULL;\npvalue = new double;\n\nif (!(pvalue = new double)) {\n    cout &lt;&lt; \"Error: out of memory.\" &lt;&lt; endl;\n    exit(1);\n}\n\ndelete pvalue;\n</code></pre> <ul> <li>new \u4e0d\u4ec5\u5206\u914d\u7684\u5185\u5b58\u8fd8\u521b\u5efa\u4e86\u5bf9\u8c61</li> <li>malloc () \u53ea\u5206\u914d\u7684\u5185\u5b58</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#322","title":"3.2.2 \u6570\u7ec4\u7684\u52a8\u6001\u5185\u5b58\u5206\u914d","text":"C++<pre><code>int ***array;\n// \u5047\u5b9a\u6570\u7ec4\u7b2c\u4e00\u7ef4\u4e3a m\uff0c \u7b2c\u4e8c\u7ef4\u4e3a n\uff0c \u7b2c\u4e09\u7ef4\u4e3ah\n// \u52a8\u6001\u5206\u914d\u7a7a\u95f4\narray = new int **[m];\nfor( int i=0; i&lt;m; i++ )\n{\n    array[i] = new int *[n];\n    for( int j=0; j&lt;n; j++ )\n    {\n        array[i][j] = new int [h];\n    }\n}\n//\u91ca\u653e\nfor( int i=0; i&lt;m; i++ )\n{\n    for( int j=0; j&lt;n; j++ )\n    {\n        delete [] array[i][j];\n    }\n    delete [] array[i];\n}\ndelete [] array;\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#323","title":"3.2.3 \u5bf9\u8c61\u7684\u52a8\u6001\u5185\u5b58\u5206\u914d","text":"C++<pre><code>#include &lt;iostream&gt;\nusing namespace std;\n\nclass Box\n{\n   public:\n      Box() { \n         cout &lt;&lt; \"\u8c03\u7528\u6784\u9020\u51fd\u6570\uff01\" &lt;&lt;endl; \n      }\n      ~Box() { \n         cout &lt;&lt; \"\u8c03\u7528\u6790\u6784\u51fd\u6570\uff01\" &lt;&lt;endl; \n      }\n};\n\nint main( )\n{\n   Box* myBoxArray = new Box[4]; // \u4e00\u4e2a\u5305\u542b 4 \u4e2a Box \u5bf9\u8c61\u7684\u6570\u7ec4\n\n   delete [] myBoxArray; // \u5220\u9664\u6570\u7ec4\n   return 0;\n}\n</code></pre> Text Only<pre><code>\u8c03\u7528\u6784\u9020\u51fd\u6570\uff01\n\u8c03\u7528\u6784\u9020\u51fd\u6570\uff01\n\u8c03\u7528\u6784\u9020\u51fd\u6570\uff01\n\u8c03\u7528\u6784\u9020\u51fd\u6570\uff01\n\u8c03\u7528\u6790\u6784\u51fd\u6570\uff01\n\u8c03\u7528\u6790\u6784\u51fd\u6570\uff01\n\u8c03\u7528\u6790\u6784\u51fd\u6570\uff01\n\u8c03\u7528\u6790\u6784\u51fd\u6570\uff01\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#33","title":"3.3 \u547d\u540d\u7a7a\u95f4","text":"<ul> <li>\u7f16\u8bd1\u5668\u4e3a\u4e86\u533a\u522b\u540c\u540d\u51fd\u6570\u5f15\u5165\u4e86\u547d\u540d\u7a7a\u95f4</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#331","title":"3.3.1 \u5b9a\u4e49\u547d\u540d\u7a7a\u95f4","text":"C++<pre><code>namespace namespace_name {\n // code\n}\n\nnamespace_name::code;\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#332-using","title":"3.3.2 using \u6307\u4ee4","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#333","title":"3.3.3 \u4e0d\u8fde\u7eed\u7684\u547d\u540d\u7a7a\u95f4","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#334","title":"3.3.4 \u5d4c\u5957\u7684\u547d\u540d\u7a7a\u95f4","text":"C++<pre><code>namespace namespace_name1 {\n   // \u4ee3\u7801\u58f0\u660e\n   namespace namespace_name2 {\n      // \u4ee3\u7801\u58f0\u660e\n   }\n}\n\n// \u8bbf\u95ee namespace_name2 \u4e2d\u7684\u6210\u5458\nusing namespace namespace_name1::namespace_name2;\n\n// \u8bbf\u95ee namespace_name1 \u4e2d\u7684\u6210\u5458\nusing namespace namespace_name1;\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#34","title":"3.4 \u6a21\u677f","text":"<ul> <li>\u6cdb\u578b\u7f16\u7a0b: \u72ec\u7acb\u4e8e\u4efb\u4f55\u7279\u5b9a\u7c7b\u578b\u7684\u65b9\u5f0f\u5199\u4ee3\u7801</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#341","title":"3.4.1 \u51fd\u6570\u6a21\u677f","text":"C++<pre><code>template &lt;typename type&gt; ret-type func-name(parameter list)\n{\n   // \u51fd\u6570\u7684\u4e3b\u4f53\n}\n</code></pre> C++<pre><code>#include &lt;iostream&gt;\n#include &lt;string&gt;\n\nusing namespace std;\n\ntemplate &lt;typename T&gt;\ninline T const&amp; Max (T const&amp; a, T const&amp; b) \n{ \n    return a &lt; b ? b:a; \n} \n\nint main ()\n{\n\n    int i = 39;\n    int j = 20;\n    cout &lt;&lt; \"Max(i, j): \" &lt;&lt; Max(i, j) &lt;&lt; endl; \n\n    double f1 = 13.5; \n    double f2 = 20.7; \n    cout &lt;&lt; \"Max(f1, f2): \" &lt;&lt; Max(f1, f2) &lt;&lt; endl; \n\n    string s1 = \"Hello\"; \n    string s2 = \"World\"; \n    cout &lt;&lt; \"Max(s1, s2): \" &lt;&lt; Max(s1, s2) &lt;&lt; endl; \n\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#342","title":"3.4.2 \u7c7b\u6a21\u677f","text":"C++<pre><code>template &lt;class type&gt; class class-name {\n// code\n}\n</code></pre> C++<pre><code>#include &lt;iostream&gt;\n#include &lt;vector&gt;\n#include &lt;cstdlib&gt;\n#include &lt;string&gt;\n#include &lt;stdexcept&gt;\n\nusing namespace std;\n\ntemplate &lt;class T&gt;\nclass Stack { \n  private: \n    vector&lt;T&gt; elems;     // \u5143\u7d20 \n\n  public: \n    void push(T const&amp;);  // \u5165\u6808\n    void pop();               // \u51fa\u6808\n    T top() const;            // \u8fd4\u56de\u6808\u9876\u5143\u7d20\n    bool empty() const{       // \u5982\u679c\u4e3a\u7a7a\u5219\u8fd4\u56de\u771f\u3002\n        return elems.empty(); \n    } \n}; \n\ntemplate &lt;class T&gt;\nvoid Stack&lt;T&gt;::push (T const&amp; elem) \n{ \n    // \u8ffd\u52a0\u4f20\u5165\u5143\u7d20\u7684\u526f\u672c\n    elems.push_back(elem);    \n} \n\ntemplate &lt;class T&gt;\nvoid Stack&lt;T&gt;::pop () \n{ \n    if (elems.empty()) { \n        throw out_of_range(\"Stack&lt;&gt;::pop(): empty stack\"); \n    }\n    // \u5220\u9664\u6700\u540e\u4e00\u4e2a\u5143\u7d20\n    elems.pop_back();         \n} \n\ntemplate &lt;class T&gt;\nT Stack&lt;T&gt;::top () const \n{ \n    if (elems.empty()) { \n        throw out_of_range(\"Stack&lt;&gt;::top(): empty stack\"); \n    }\n    // \u8fd4\u56de\u6700\u540e\u4e00\u4e2a\u5143\u7d20\u7684\u526f\u672c \n    return elems.back();      \n} \n\nint main() \n{ \n    try { \n        Stack&lt;int&gt;       intStack;    // int \u7c7b\u578b\u7684\u6808 \n        Stack&lt;string&gt; stringStack;    // string \u7c7b\u578b\u7684\u6808 \n\n        // \u64cd\u4f5c int \u7c7b\u578b\u7684\u6808 \n        intStack.push(7); \n        cout &lt;&lt; intStack.top() &lt;&lt;endl; \n\n        // \u64cd\u4f5c string \u7c7b\u578b\u7684\u6808 \n        stringStack.push(\"hello\"); \n        cout &lt;&lt; stringStack.top() &lt;&lt; std::endl; \n        stringStack.pop(); \n        stringStack.pop(); \n    } \n    catch (exception const&amp; ex) { \n        cerr &lt;&lt; \"Exception: \" &lt;&lt; ex.what() &lt;&lt;endl; \n        return -1;\n    } \n}\n</code></pre> Text Only<pre><code>7\nhello\nException: Stack&lt;&gt;::pop(): empty stack\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#35","title":"3.5 \u9884\u5904\u7406\u5668","text":"<ul> <li>\u4e0d\u662f C++\u8bed\u53e5\uff0c\u4e0d\u4f1a\u4ee5\u5206\u53f7\u7ed3\u5c3e</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#351-define","title":"3.5.1 #define \u9884\u5904\u7406","text":"C++<pre><code>#define macro-name replacement-text \n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#352","title":"3.5.2 \u53c2\u6570\u5b8f","text":"C++<pre><code>#include &lt;iostream&gt;\nusing namespace std;\n\n#define MIN(a,b) (a&lt;b ? a : b)\n\nint main ()\n{\n   int i, j;\n   i = 100;\n   j = 30;\n   cout &lt;&lt;\"\u8f83\u5c0f\u7684\u503c\u4e3a\uff1a\" &lt;&lt; MIN(i, j) &lt;&lt; endl;\n\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#353","title":"3.5.3 \u6761\u4ef6\u7f16\u8bd1","text":"C++<pre><code>#ifdef NULL\n   #define NULL 0\n#endif\n\n#ifdef DEBUG\n   cerr &lt;&lt;\"Variable x = \" &lt;&lt; x &lt;&lt; endl;\n#endif\n\n#if 0\n   \u4e0d\u8fdb\u884c\u7f16\u8bd1\u7684\u4ee3\u7801\n#endif\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#354","title":"3.5.4 # \u548c ## \u8fd0\u7b97\u7b26","text":"C++<pre><code>#include &lt;iostream&gt;\nusing namespace std;\n\n#define MKSTR( x ) #x\n\nint main ()\n{\n    cout &lt;&lt; MKSTR(HELLO C++) &lt;&lt; endl;\n\n    return 0;\n}\n</code></pre> C++<pre><code>#include &lt;iostream&gt;\nusing namespace std;\n\n#define concat(a, b) a ## b\nint main()\n{\n   int xy = 100;\n\n   cout &lt;&lt; concat(x, y);\n   return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#355","title":"3.5.5 \u9884\u5b9a\u4e49\u5b8f","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#36","title":"3.6 \u4fe1\u53f7\u5904\u7406","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#361-signal","title":"3.6.1 signal () \u51fd\u6570","text":"C++<pre><code>void (*signal (int sig, void (*func)(int)))(int); \n\nsignal(registered signal, signal handler)\n</code></pre> C++<pre><code>#include &lt;iostream&gt;\n#include &lt;csignal&gt;\n#include &lt;unistd.h&gt;\n\nusing namespace std;\n\nvoid signalHandler( int signum )\n{\n    cout &lt;&lt; \"Interrupt signal (\" &lt;&lt; signum &lt;&lt; \") received.\\n\";\n\n    // \u6e05\u7406\u5e76\u5173\u95ed\n    // \u7ec8\u6b62\u7a0b\u5e8f  \n\n   exit(signum);  \n\n}\n\nint main ()\n{\n    // \u6ce8\u518c\u4fe1\u53f7 SIGINT \u548c\u4fe1\u53f7\u5904\u7406\u7a0b\u5e8f\n    signal(SIGINT, signalHandler);  \n\n    while(1){\n       cout &lt;&lt; \"Going to sleep....\" &lt;&lt; endl;\n       sleep(1);\n    }\n\n    return 0;\n}\n</code></pre> <p>\u6309 Ctrl + C \u4e2d\u65ad\u7a0b\u5e8f:</p> Text Only<pre><code>Going to sleep....\nGoing to sleep....\nGoing to sleep....\nInterrupt signal (2) received.\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#362-raise","title":"3.6.2 raise () \u51fd\u6570","text":"C++<pre><code>int raise (signal sig);\n</code></pre> C++<pre><code>#include &lt;iostream&gt;\n#include &lt;csignal&gt;\n#include &lt;unistd.h&gt;\n\nusing namespace std;\n\nvoid signalHandler( int signum )\n{\n    cout &lt;&lt; \"Interrupt signal (\" &lt;&lt; signum &lt;&lt; \") received.\\n\";\n\n    // \u6e05\u7406\u5e76\u5173\u95ed\n    // \u7ec8\u6b62\u7a0b\u5e8f \n\n   exit(signum);  \n\n}\n\nint main ()\n{\n    int i = 0;\n    // \u6ce8\u518c\u4fe1\u53f7 SIGINT \u548c\u4fe1\u53f7\u5904\u7406\u7a0b\u5e8f\n    signal(SIGINT, signalHandler);  \n\n    while(++i){\n       cout &lt;&lt; \"Going to sleep....\" &lt;&lt; endl;\n       if( i == 3 ){\n          raise(SIGINT);\n       }\n       sleep(1);\n    }\n\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#37","title":"3.7 \u591a\u7ebf\u7a0b","text":"<ul> <li>\u4e24\u79cd\u7c7b\u578b\u7684\u591a\u4efb\u52a1\u5904\u7406<ul> <li>\u57fa\u4e8e\u8fdb\u7a0b\u662f\u7a0b\u5e8f\u7684\u5e76\u53d1\u6267\u884c</li> <li>\u57fa\u4e8e\u7ebf\u7a0b\u662f\u540c\u4e00\u7a0b\u5e8f\u7684\u7247\u6bb5\u7684\u5e76\u53d1\u6267\u884c</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#371","title":"3.7.1 \u6982\u5ff5\u8bf4\u660e","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3711-thread","title":"3.7.1.1 \u7ebf\u7a0b\uff08Thread\uff09","text":"<ul> <li>\u7ebf\u7a0b\u662f\u7a0b\u5e8f\u6267\u884c\u4e2d\u7684\u5355\u4e00\u987a\u5e8f\u63a7\u5236\u6d41\uff0c\u591a\u4e2a\u7ebf\u7a0b\u53ef\u4ee5\u5728\u540c\u4e00\u4e2a\u8fdb\u7a0b\u4e2d\u72ec\u7acb\u8fd0\u884c\u3002</li> <li>\u7ebf\u7a0b\u5171\u4eab\u8fdb\u7a0b\u7684\u5730\u5740\u7a7a\u95f4\u3001\u6587\u4ef6\u63cf\u8ff0\u7b26\u3001\u5806\u548c\u5168\u5c40\u53d8\u91cf\u7b49\u8d44\u6e90\uff0c\u4f46\u6bcf\u4e2a\u7ebf\u7a0b\u6709\u81ea\u5df1\u7684\u6808\u3001\u5bc4\u5b58\u5668\u548c\u7a0b\u5e8f\u8ba1\u6570\u5668\u3002</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3712-concurrency-parallelism","title":"3.7.1.2 \u5e76\u53d1\uff08Concurrency\uff09\u4e0e\u5e76\u884c \uff08Parallelism\uff09","text":"<ul> <li>\u5e76\u53d1\uff1a\u591a\u4e2a\u4efb\u52a1\u5728\u65f6\u95f4\u7247\u6bb5\u5185\u4ea4\u66ff\u6267\u884c\uff0c\u8868\u73b0\u51fa\u540c\u65f6\u8fdb\u884c\u7684\u6548\u679c\u3002</li> <li>\u5e76\u884c\uff1a\u591a\u4e2a\u4efb\u52a1\u5728\u591a\u4e2a\u5904\u7406\u5668\u6216\u5904\u7406\u5668\u6838\u4e0a\u540c\u65f6\u6267\u884c\u3002 C++11 \u4ee5\u540e\u6709\u591a\u7ebf\u7a0b\u652f\u6301:</li> <li>std::thread\uff1a\u7528\u4e8e\u521b\u5efa\u548c\u7ba1\u7406\u7ebf\u7a0b\u3002</li> <li>std::mutex\uff1a\u7528\u4e8e\u7ebf\u7a0b\u4e4b\u95f4\u7684\u4e92\u65a5\uff0c\u9632\u6b62\u591a\u4e2a\u7ebf\u7a0b\u540c\u65f6\u8bbf\u95ee\u5171\u4eab\u8d44\u6e90\u3002</li> <li>std::lock_guard\u00a0\u548c\u00a0std::unique_lock\uff1a\u7528\u4e8e\u7ba1\u7406\u9501\u7684\u83b7\u53d6\u548c\u91ca\u653e\u3002</li> <li>std::condition_variable\uff1a\u7528\u4e8e\u7ebf\u7a0b\u95f4\u7684\u6761\u4ef6\u53d8\u91cf\uff0c\u534f\u8c03\u7ebf\u7a0b\u95f4\u7684\u7b49\u5f85\u548c\u901a\u77e5\u3002</li> <li>std::future\u00a0\u548c\u00a0std::promise\uff1a\u7528\u4e8e\u5b9e\u73b0\u7ebf\u7a0b\u95f4\u7684\u503c\u4f20\u9012\u548c\u4efb\u52a1\u540c\u6b65\u3002</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#372","title":"3.7.2 \u521b\u5efa\u7ebf\u7a0b","text":"C++<pre><code>#include&lt;thread&gt;\nstd::thread thread_object(callable, args...);\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3721","title":"3.7.2.1 \u4f7f\u7528\u51fd\u6570\u6307\u9488","text":"C++<pre><code>#include &lt;iostream&gt;\n#include &lt;thread&gt;\n\nvoid printMessage(int count) {\n    for (int i = 0; i &lt; count; ++i) {\n        std::cout &lt;&lt; \"Hello from thread (function pointer)!\\n\";\n    }\n}\n\nint main() {\n    std::thread t1(printMessage, 5); // \u521b\u5efa\u7ebf\u7a0b\uff0c\u4f20\u9012\u51fd\u6570\u6307\u9488\u548c\u53c2\u6570\n    t1.join(); // \u7b49\u5f85\u7ebf\u7a0b\u5b8c\u6210\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3722","title":"3.7.2.2 \u4f7f\u7528\u51fd\u6570\u5bf9\u8c61","text":"C++<pre><code>#include &lt;iostream&gt;\n#include &lt;thread&gt;\n\nclass PrintTask {\npublic:\n    void operator()(int count) const {\n        for (int i = 0; i &lt; count; ++i) {\n            std::cout &lt;&lt; \"Hello from thread (function object)!\\n\";\n        }\n    }\n};\n\nint main() {\n    std::thread t2(PrintTask(), 5); // \u521b\u5efa\u7ebf\u7a0b\uff0c\u4f20\u9012\u51fd\u6570\u5bf9\u8c61\u548c\u53c2\u6570\n    t2.join(); // \u7b49\u5f85\u7ebf\u7a0b\u5b8c\u6210\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3723-lambda","title":"3.7.2.3 \u4f7f\u7528 Lambda \u8868\u8fbe\u5f0f","text":"C++<pre><code>#include &lt;iostream&gt;\n#include &lt;thread&gt;\n\nint main() {\n    std::thread t3([](int count) {\n        for (int i = 0; i &lt; count; ++i) {\n            std::cout &lt;&lt; \"Hello from thread (lambda)!\\n\";\n        }\n    }, 5); // \u521b\u5efa\u7ebf\u7a0b\uff0c\u4f20\u9012 Lambda \u8868\u8fbe\u5f0f\u548c\u53c2\u6570\n    t3.join(); // \u7b49\u5f85\u7ebf\u7a0b\u5b8c\u6210\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3724","title":"3.7.2.4 \u7ebf\u7a0b\u7ba1\u7406","text":"C++<pre><code>t.join();\nt.detach();\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3725","title":"3.7.2.5 \u7ebf\u7a0b\u7684\u4f20\u53c2","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3726","title":"3.7.2.6 \u503c\u4f20\u9012","text":"C++<pre><code>std::thread t(funx, arg1, arg2);\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3727","title":"3.7.2.7 \u5f15\u7528\u4f20\u9012","text":"C++<pre><code>#include &lt;iostream&gt;\n#include &lt;thread&gt;\n\nvoid increment(int&amp; x) {\n    ++x;\n}\n\nint main() {\n    int num = 0;\n    std::thread t(increment, std::ref(num)); // \u4f7f\u7528 std::ref \u4f20\u9012\u5f15\u7528\n    t.join();\n    std::cout &lt;&lt; \"Value after increment: \" &lt;&lt; num &lt;&lt; std::endl;\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#373","title":"3.7.3 \u7ebf\u7a0b\u540c\u6b65\u4e0e\u4e92\u65a5","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3731-mutex","title":"3.7.3.1 \u4e92\u65a5\u91cf\uff08Mutex\uff09","text":"C++<pre><code>std::mutex mtx;\nmtx.lock();   // \u9501\u5b9a\u4e92\u65a5\u9501\n// \u8bbf\u95ee\u5171\u4eab\u8d44\u6e90\nmtx.unlock();// \u91ca\u653e\u4e92\u65a5\u9501\n\nstd::lock_guard&lt;std::mutex&gt; lock(mtx); // \u81ea\u52a8\u9501\u5b9a\u548c\u89e3\u9501\n// \u8bbf\u95ee\u5171\u4eab\u8d44\u6e90\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3732-locks","title":"3.7.3.2 \u9501\uff08Locks\uff09","text":"<ul> <li><code>std::lock_guard</code> \uff1a\u4f5c\u7528\u57df\u9501\uff0c\u5f53\u6784\u9020\u65f6\u81ea\u52a8\u9501\u5b9a\u4e92\u65a5\u91cf\uff0c\u5f53\u6790\u6784\u65f6\u81ea\u52a8\u89e3\u9501\u3002</li> <li><code>std::unique_lock</code> \uff1a\u4e0e <code>std::lock_guard</code> \u7c7b\u4f3c\uff0c\u4f46\u63d0\u4f9b\u4e86\u66f4\u591a\u7684\u7075\u6d3b\u6027\uff0c\u4f8b\u5982\u53ef\u4ee5\u8f6c\u79fb\u6240\u6709\u6743\u548c\u624b\u52a8\u89e3\u9501\u3002</li> </ul> C++<pre><code>#include &lt;mutex&gt;\n\nstd::mutex mtx;\n\nvoid safeFunctionWithLockGuard() {\n    std::lock_guard&lt;std::mutex&gt; lk(mtx);\n    // \u8bbf\u95ee\u6216\u4fee\u6539\u5171\u4eab\u8d44\u6e90\n}\n\nvoid safeFunctionWithUniqueLock() {\n    std::unique_lock&lt;std::mutex&gt; ul(mtx);\n    // \u8bbf\u95ee\u6216\u4fee\u6539\u5171\u4eab\u8d44\u6e90\n    // ul.unlock(); // \u53ef\u9009\uff1a\u624b\u52a8\u89e3\u9501\n    // ...\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3733-condition-variable","title":"3.7.3.3 \u6761\u4ef6\u53d8\u91cf\uff08Condition Variable\uff09","text":"C++<pre><code>std::condition_variable cv;\nstd::mutex mtx;\nbool ready = false;\n\nstd::unique_lock&lt;std::mutex&gt; lock(mtx);\ncv.wait(lock, []{ return ready; }); // \u7b49\u5f85\u6761\u4ef6\u6ee1\u8db3\n// \u6761\u4ef6\u6ee1\u8db3\u540e\u6267\u884c\n</code></pre> C++<pre><code>#include &lt;mutex&gt;\n#include &lt;condition_variable&gt;\n\nstd::mutex mtx;\nstd::condition_variable cv;\nbool ready = false;\n\nvoid workerThread() {\n    std::unique_lock&lt;std::mutex&gt; lk(mtx);\n    cv.wait(lk, []{ return ready; }); // \u7b49\u5f85\u6761\u4ef6\n    // \u5f53\u6761\u4ef6\u6ee1\u8db3\u65f6\u6267\u884c\u5de5\u4f5c\n}\n\nvoid mainThread() {\n    {\n        std::lock_guard&lt;std::mutex&gt; lk(mtx);\n        // \u51c6\u5907\u6570\u636e\n        ready = true;\n    } // \u79bb\u5f00\u4f5c\u7528\u57df\u65f6\u89e3\u9501\n    cv.notify_one(); // \u901a\u77e5\u4e00\u4e2a\u7b49\u5f85\u7684\u7ebf\u7a0b\n}\n</code></pre> <p>TODO</p>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3734-atomic-operations","title":"3.7.3.4 \u539f\u5b50\u64cd\u4f5c\uff08Atomic Operations\uff09","text":"<ul> <li>\u5bf9\u5171\u4eab\u6570\u636e\u7684\u8bbf\u95ee\u4e0d\u53ef\u5206\u5272</li> </ul> C++<pre><code>#include &lt;atomic&gt;\n#include &lt;thread&gt;\n\nstd::atomic&lt;int&gt; count(0);\n\nvoid increment() {\n    count.fetch_add(1, std::memory_order_relaxed);\n}\n\nint main() {\n    std::thread t1(increment);\n    std::thread t2(increment);\n    t1.join();\n    t2.join();\n    return count; // \u5e94\u8fd4\u56de2\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3735-thread-local-storagetls","title":"3.7.3.5 \u7ebf\u7a0b\u5c40\u90e8\u5b58\u50a8\uff08Thread Local Storage\uff0cTLS\uff09","text":"<ul> <li>\u5141\u8bb8\u6bcf\u4e2a\u7ebf\u7a0b\u6709\u81ea\u5df1\u7684\u6570\u636e\u526f\u672c</li> </ul> C++<pre><code>#include &lt;iostream&gt;\n#include &lt;thread&gt;\n\nthread_local int threadData = 0;\n\nvoid threadFunction() {\n    threadData = 42; // \u6bcf\u4e2a\u7ebf\u7a0b\u90fd\u6709\u81ea\u5df1\u7684threadData\u526f\u672c\n    std::cout &lt;&lt; \"Thread data: \" &lt;&lt; threadData &lt;&lt; std::endl;\n}\n\nint main() {\n    std::thread t1(threadFunction);\n    std::thread t2(threadFunction);\n    t1.join();\n    t2.join();\n    return 0;\n}\n</code></pre>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#3736-deadlock","title":"3.7.3.6 \u6b7b\u9501\uff08Deadlock\uff09\u548c\u907f\u514d\u7b56\u7565","text":"<ul> <li>\u6b7b\u9501\u5373\u591a\u4e2a\u7ebf\u7a0b\u4e92\u76f8\u7b49\u5f85\u5bf9\u65b9\u91ca\u653e\u8d44\u6e90<ul> <li>\u603b\u662f\u4ee5\u76f8\u540c\u7684\u987a\u5e8f\u8bf7\u6c42\u8d44\u6e90\u3002</li> <li>\u4f7f\u7528\u8d85\u65f6\u6765\u5c1d\u8bd5\u83b7\u53d6\u8d44\u6e90\u3002</li> <li>\u4f7f\u7528\u6b7b\u9501\u68c0\u6d4b\u7b97\u6cd5\u3002</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#374","title":"3.7.4 \u7ebf\u7a0b\u95f4\u901a\u4fe1","text":"C++<pre><code>std::promise&lt;int&gt; p;\nstd::future&lt;int&gt; f = p.get_future();\n\nstd::thread t([&amp;p] {\n    p.set_value(10); // \u8bbe\u7f6e\u503c\uff0c\u89e6\u53d1 future\n});\n\nint result = f.get(); // \u83b7\u53d6\u503c\n</code></pre> <p>C++17 \u5f15\u5165\u4e86\u5e76\u884c\u7b97\u6cd5\u5e93</p> C++<pre><code>#include &lt;algorithm&gt;\n#include &lt;vector&gt;\n#include &lt;execution&gt;\n\nstd::vector&lt;int&gt; vec = {1, 2, 3, 4, 5};\nstd::for_each(std::execution::par, vec.begin(), vec.end(), [](int &amp;n) {\n    n *= 2;\n});\n</code></pre> <p>TODO \u591a\u7ebf\u7a0b\u5b9e\u4f8b</p>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#38-web","title":"3.8 Web \u7f16\u7a0b","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#381-cgi","title":"3.8.1 \u4ec0\u4e48\u662f CGI\uff1f","text":"<ul> <li>\u516c\u5171\u7f51\u5173\u63a5\u53e3\uff08CGI\uff09\uff0c\u662f\u4e00\u5957\u6807\u51c6\uff0c\u5b9a\u4e49\u4e86\u4fe1\u606f\u662f\u5982\u4f55\u5728 Web \u670d\u52a1\u5668\u548c\u5ba2\u6237\u7aef\u811a\u672c\u4e4b\u95f4\u8fdb\u884c\u4ea4\u6362\u7684\u3002</li> <li>CGI \u89c4\u8303\u76ee\u524d\u662f\u7531 NCSA \u7ef4\u62a4\u7684\uff0cNCSA \u5b9a\u4e49 CGI \u5982\u4e0b\uff1a<ul> <li>\u516c\u5171\u7f51\u5173\u63a5\u53e3\uff08CGI\uff09\uff0c\u662f\u4e00\u79cd\u7528\u4e8e\u5916\u90e8\u7f51\u5173\u7a0b\u5e8f\u4e0e\u4fe1\u606f\u670d\u52a1\u5668\uff08\u5982 HTTP \u670d\u52a1\u5668\uff09\u5bf9\u63a5\u7684\u63a5\u53e3\u6807\u51c6\u3002</li> </ul> </li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#382-web","title":"3.8.2 Web \u6d4f\u89c8","text":"<ul> <li>\u60a8\u7684\u6d4f\u89c8\u5668\u8054\u7cfb\u4e0a HTTP Web \u670d\u52a1\u5668\uff0c\u5e76\u8bf7\u6c42 URL\uff0c\u5373\u6587\u4ef6\u540d\u3002</li> <li>Web \u670d\u52a1\u5668\u5c06\u89e3\u6790 URL\uff0c\u5e76\u67e5\u627e\u6587\u4ef6\u540d\u3002\u5982\u679c\u627e\u5230\u8bf7\u6c42\u7684\u6587\u4ef6\uff0cWeb \u670d\u52a1\u5668\u4f1a\u628a\u6587\u4ef6\u53d1\u9001\u56de\u6d4f\u89c8\u5668\uff0c\u5426\u5219\u53d1\u9001\u4e00\u6761\u9519\u8bef\u6d88\u606f\uff0c\u8868\u660e\u60a8\u8bf7\u6c42\u4e86\u4e00\u4e2a\u9519\u8bef\u7684\u6587\u4ef6\u3002</li> <li>Web \u6d4f\u89c8\u5668\u4ece Web \u670d\u52a1\u5668\u83b7\u53d6\u54cd\u5e94\uff0c\u5e76\u6839\u636e\u63a5\u6536\u5230\u7684\u54cd\u5e94\u6765\u663e\u793a\u6587\u4ef6\u6216\u9519\u8bef\u6d88\u606f\u3002</li> </ul>"},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#383-cgi","title":"3.8.3 CGI \u67b6\u6784\u56fe","text":""},{"location":"CS_Basic/C%2B%2B/C%2B%2B%20Basic/#384-web","title":"3.8.4 Web \u670d\u52a1\u5668\u914d\u7f6e","text":"<p>TODO</p>"},{"location":"CS_Basic/CS61A/CS61A/","title":"CS61A","text":""},{"location":"CS_Basic/CS61A/CS61A/#cs61a","title":"CS61A","text":"<p> \u7ea6 24 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4\u4e0d\u5230 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <ul> <li>\u4ed6\u4eba\u603b\u7ed3</li> <li>https://github.com/HobbitQia/CS61A-Fall-2020/tree/main</li> <li>\u6559\u6750\u7ffb\u8bd1\u7248</li> <li>\u539f\u6559\u6750</li> <li>\u8bfe\u7a0b\u7f51\u7ad9\u5b58\u6863</li> <li>https://github.com/shuo-liu16/CS61A<ul> <li>scheme\u624b\u518c</li> </ul> </li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/","title":"COMPOSING PROGRAMS","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#composing-programs","title":"COMPOSING PROGRAMS","text":"<p> \u7ea6 2713 \u4e2a\u5b57  651 \u884c\u4ee3\u7801  2 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 22 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#1","title":"1 \u4f7f\u7528\u51fd\u6570\u6784\u5efa\u62bd\u8c61","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#11","title":"1.1 \u5f00\u59cb","text":"<p>\u7a0b\u5e8f\u7531\u4e24\u90e8\u5206\u7ec4\u6210:</p> <ul> <li>\u8ba1\u7b97\u4e00\u4e9b\u503c</li> <li>\u6267\u884c\u4e00\u4e9b\u64cd\u4f5c</li> <li>\u51fd\u6570</li> <li>\u5bf9\u8c61</li> <li>\u89e3\u91ca\u5668:<ul> <li>\u7528\u4e8e\u8ba1\u7b97\u590d\u6742\u8868\u8fbe\u5f0f\u7684\u7a0b\u5e8f</li> </ul> </li> <li>\u589e\u91cf\u6d4b\u8bd5\u3001\u6a21\u5757\u5316\u8bbe\u8ba1\u3001\u660e\u786e\u7684\u5047\u8bbe\u548c\u56e2\u961f\u5408\u4f5c</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#12","title":"1.2 \u7f16\u7a0b\u8981\u7d20","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#121","title":"1.2.1 \u8868\u8fbe\u5f0f","text":"<ul> <li>\u8bed\u8a00\u8981\u6709\u7684\u673a\u5236:<ul> <li>\u539f\u59cb\u8868\u8fbe\u5f0f\u548c\u8bed\u53e5\uff1a\u8bed\u8a00\u6240\u5173\u5fc3\u7684\u6700\u7b80\u5355\u7684\u4e2a\u4f53</li> <li>\u7ec4\u5408\u65b9\u6cd5\uff1a\u7531\u7b80\u5355\u5143\u7d20\u7ec4\u5408\u6784\u5efa\u590d\u5408\u5143\u7d20</li> <li>\u62bd\u8c61\u65b9\u6cd5\uff1a\u547d\u540d\u590d\u5408\u5143\u7d20\uff0c\u5e76\u5c06\u5176\u4f5c\u4e3a\u5355\u5143\u8fdb\u884c\u64cd\u4f5c  </li> </ul> </li> <li>infix notation</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#122","title":"1.2.2 \u8c03\u7528\u8868\u8fbe\u5f0f","text":"<ul> <li>subexpressions  </li> <li>\u7528\u53c2\u6570\u6765\u8c03\u7528\u51fd\u6570  </li> <li>nested\uff08\u5d4c\u5957\uff09</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#123","title":"1.2.3 \u5bfc\u5165\u5e93\u51fd\u6570","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#124","title":"1.2.4 \u540d\u79f0\u4e0e\u73af\u5883","text":"<ul> <li>= is assignment operator<ul> <li>\u6700\u7b80\u5355\u7684\u62bd\u8c61\u65b9\u6cd5</li> </ul> </li> <li>environment</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#125","title":"1.2.5 \u6c42\u89e3\u5d4c\u5957\u8868\u8fbe\u5f0f","text":"<p>\u6c42\u503c\u7a0b\u5e8f\u672c\u8d28\u4e0a\u662f\u9012\u5f52\u7684 </p> <ul> <li>\u8868\u8fbe\u5f0f\u6811</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#126-print","title":"1.2.6 \u975e\u7eaf\u51fd\u6570 print","text":"<p>Pure functions None-pure functions     which has a side effect</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#13","title":"1.3 \u5b9a\u4e49\u65b0\u7684\u51fd\u6570","text":"Python<pre><code>def &lt;name&gt;(&lt;formal parameters&gt;):\n    return &lt;return expression&gt;  \n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#131","title":"1.3.1 \u73af\u5883","text":"<p>environment has some frames     frames have some bindings</p> <ul> <li>intrinsic name</li> <li>bound name \u4e0d\u540c\u7684\u540d\u79f0\u53ef\u80fd\u6307\u7684\u662f\u540c\u4e00\u4e2a\u51fd\u6570\uff0c\u4f46\u8be5\u51fd\u6570\u672c\u8eab\u53ea\u6709\u4e00\u4e2a\u5185\u5728\u540d\u79f0 \u5bf9\u51fd\u6570\u5f62\u5f0f\u53c2\u6570\u7684\u63cf\u8ff0\u88ab\u79f0\u4e3a\u51fd\u6570\u7684\u7b7e\u540d</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#132","title":"1.3.2 \u8c03\u7528\u7528\u6237\u5b9a\u4e49\u7684\u51fd\u6570","text":"<ol> <li>\u5728\u65b0\u7684\u5c40\u90e8\u5e27\u4e2d\uff0c\u5c06\u5b9e\u53c2\u7ed1\u5b9a\u5230\u51fd\u6570\u7684\u5f62\u53c2\u4e0a\u3002</li> <li>\u5728\u4ee5\u6b64\u5e27\u5f00\u59cb\u7684\u73af\u5883\u4e2d\u6267\u884c\u51fd\u6570\u4f53\u3002 name evaluation</li> </ol>"},{"location":"CS_Basic/CS61A/Composing_Programs/#133","title":"1.3.3 \u793a\u4f8b\uff1a\u8c03\u7528\u7528\u6237\u5b9a\u4e49\u7684\u51fd\u6570","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#134","title":"1.3.4 \u5c40\u90e8\u540d\u79f0","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#135","title":"1.3.5 \u9009\u62e9\u540d\u79f0","text":"<p>PEP 8 \u2013 Style Guide for Python Code | peps.python.org</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#136","title":"1.3.6 \u62bd\u8c61\u51fd\u6570","text":"<ul> <li>functional abstraction<ul> <li>domain</li> <li>range</li> <li>intent</li> </ul> </li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#137","title":"1.3.7 \u8fd0\u7b97\u7b26","text":"<ul> <li>truediv</li> <li>floordiv</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#14","title":"1.4 \u8bbe\u8ba1\u51fd\u6570","text":"<ul> <li>\u4e00\u4e2a\u51fd\u6570\u4e00\u4e2a\u4efb\u52a1</li> <li>Don't repeat yourself (DRY)</li> <li>\u5b9a\u4e49\u901a\u7528\u7684\u51fd\u6570</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#141","title":"1.4.1 \u6587\u6863","text":"<p>docstring</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#142","title":"1.4.2 \u53c2\u6570\u9ed8\u8ba4\u503c","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#15","title":"1.5 \u63a7\u5236","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#151","title":"1.5.1 \u8bed\u53e5","text":"<ul> <li>assignment</li> <li>def </li> <li>return</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#152","title":"1.5.2 \u590d\u5408\u8bed\u53e5","text":"<p>header suite</p> Python<pre><code>&lt;header&gt;:\n    &lt;statement&gt;\n    &lt;statement&gt;\n    ...\n&lt;separating header&gt;:\n    &lt;statement&gt;\n    &lt;statement&gt;\n    ...\n...\n</code></pre> <p>def \u662f\u590d\u5408\u8bed\u53e5 the header controls its suite \u8fd9\u4e2a\u5b9a\u4e49\u63ed\u793a\u4e86\u9012\u5f52\u5b9a\u4e49\u5e8f\u5217\uff08sequence\uff09\u7684\u57fa\u672c\u7ed3\u6784\uff1a\u4e00\u4e2a\u5e8f\u5217\u53ef\u4ee5\u5206\u89e3\u6210\u5b83\u7684\u7b2c\u4e00\u4e2a\u5143\u7d20\u548c\u5176\u4f59\u5143\u7d20 redirected control</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#153-ii","title":"1.5.3 \u00a0\u5b9a\u4e49\u51fd\u6570 II\uff1a\u5c40\u90e8\u8d4b\u503c","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#154","title":"1.5.4 \u6761\u4ef6\u8bed\u53e5","text":"Python<pre><code>if &lt;expression&gt;:\n    &lt;suite&gt;\nelif &lt;expression&gt;:\n    &lt;suite&gt;\nelse:\n    &lt;suite&gt;\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#155","title":"1.5.5 \u8fed\u4ee3","text":"<p>iteractive control</p> Python<pre><code>while &lt;expression&gt;:\n    &lt;suite&gt;\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#156","title":"1.5.6 \u6d4b\u8bd5","text":"<p>assertions</p> Python<pre><code>&gt;&gt;&gt; assert fib(8) == 13, '\u7b2c\u516b\u4e2a\u6590\u6ce2\u90a3\u5951\u6570\u5e94\u8be5\u662f 13'\n</code></pre> <p>Doctests</p> Python<pre><code>&gt;&gt;&gt; def sum_naturals(n):\n    \"\"\"\u8fd4\u56de\u524d n \u4e2a\u81ea\u7136\u6570\u7684\u548c\u3002\n\n    &gt;&gt;&gt; sum_naturals(10)\n    55\n    &gt;&gt;&gt; sum_naturals(100)\n    5050\n    \"\"\"\n    total, k = 0, 1\n    while k &lt;= n:\n        total, k = total + k, k + 1\n    return total\n</code></pre> Python<pre><code>&gt;&gt;&gt; from doctest import testmod\n&gt;&gt;&gt; testmod()\nTestResults(failed=0, attempted=2)\n</code></pre> <p>\u5355\u4e2a\u51fd\u6570\u7684\u4ea4\u4e92</p> Python<pre><code>&gt;&gt;&gt; from doctest import run_docstring_examples\n&gt;&gt;&gt; run_docstring_examples(sum_naturals, globals(), True)\nFinding tests in NoName\nTrying:\n\u00a0\u00a0\u00a0 sum_naturals(10)\nExpecting:\n\u00a0\u00a0\u00a0 55\nok\nTrying:\n\u00a0\u00a0\u00a0 sum_naturals(100)\nExpecting:\n\u00a0\u00a0\u00a0 5050\nok\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#16","title":"1.6 \u9ad8\u9636\u51fd\u6570","text":"<ul> <li>general patterns  </li> <li>named concepts  </li> <li>higher-order functions  <ul> <li>\u53ef\u4ee5\u628a\u51fd\u6570\u5f53\u4f5c\u53c2\u6570\u6216\u8005\u8fd4\u56de\u503c</li> </ul> </li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#161","title":"1.6.1 \u4f5c\u4e3a\u53c2\u6570\u7684\u51fd\u6570","text":"<ul> <li>slots  </li> <li>step through \uff08\u5355\u6b65\u8c03\u8bd5\uff09  </li> <li>\u4e00\u4e2a\u51e0\u4e4e\u6ca1\u5fc5\u8981\u770b\u7684\u4f8b\u5b50:</li> </ul> Python<pre><code>&gt;&gt;&gt; def summation(n, term):\n        total, k = 0, 1\n        while k &lt;= n:\n            total, k = total + term(k), k + 1\n        return total\n&gt;&gt;&gt; def identity(x):\n        return x\n&gt;&gt;&gt; def sum_naturals(n):\n        return summation(n, identity)\n&gt;&gt;&gt; sum_naturals(10)\n55\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#162","title":"1.6.2 \u4f5c\u4e3a\u901a\u7528\u65b9\u6cd5\u7684\u51fd\u6570","text":"<ul> <li>user-defined functions  </li> <li>general methods  </li> <li>iterative improvement  </li> <li>repetitive refinement</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#163-iii","title":"1.6.3 \u5b9a\u4e49\u51fd\u6570 III\uff1a\u5d4c\u5957\u5b9a\u4e49","text":"<p>\u4e24\u4e2a\u540e\u679c:</p> <ul> <li>\u5168\u5c40\u5e27\u53d8\u6df7\u4e71</li> <li>\u51fd\u6570\u7b7e\u540d\u9650\u5236  </li> <li>Nested function definition  </li> <li>Lexical scope  <ul> <li>\u8fd9\u79cd\u5728\u5d4c\u5957\u5b9a\u4e49\u4e4b\u95f4\u5171\u4eab\u540d\u79f0\u7684\u89c4\u5219\u79f0\u4e3a\u8bcd\u6cd5\u4f5c\u7528\u57df</li> </ul> </li> </ul> <ol> <li>\u6bcf\u4e2a\u7528\u6237\u5b9a\u4e49\u7684\u51fd\u6570\u90fd\u6709\u4e00\u4e2a\u7236\u73af\u5883\uff1a\u5b9a\u4e49\u5b83\u7684\u73af\u5883\u3002</li> <li>\u8c03\u7528\u7528\u6237\u5b9a\u4e49\u7684\u51fd\u6570\u65f6\uff0c\u5176\u5c40\u90e8\u5e27\u4f1a\u7ee7\u627f\u5176\u7236\u73af\u5883\u3002</li> </ol> <ul> <li>\u5173\u952e\u4f18\u52bf:<ul> <li>\u5c40\u90e8\u51fd\u6570\u7684\u540d\u79f0\u4e0d\u4f1a\u5f71\u54cd\u5b9a\u4e49\u5b83\u7684\u51fd\u6570\u7684\u5916\u90e8\u540d\u79f0\uff0c\u56e0\u4e3a\u5c40\u90e8\u51fd\u6570\u7684\u540d\u79f0\u5c06\u7ed1\u5b9a\u5728\u5b9a\u4e49\u5b83\u7684\u5f53\u524d\u5c40\u90e8\u73af\u5883\u4e2d\uff0c\u800c\u4e0d\u662f\u5168\u5c40\u73af\u5883\u4e2d\u3002</li> <li>\u5c40\u90e8\u51fd\u6570\u53ef\u4ee5\u8bbf\u95ee\u5916\u5c42\u51fd\u6570\u7684\u73af\u5883\uff0c\u8fd9\u662f\u56e0\u4e3a\u5c40\u90e8\u51fd\u6570\u7684\u51fd\u6570\u4f53\u7684\u6c42\u503c\u73af\u5883\u4f1a\u7ee7\u627f\u5b9a\u4e49\u5b83\u7684\u6c42\u503c\u73af\u5883\u3002  </li> </ul> </li> <li>Extended Environments  </li> <li>\u5c40\u90e8\u5b9a\u4e49\u7684\u51fd\u6570\u901a\u5e38\u88ab\u79f0\u4e3a\u95ed\u5305\uff08closures\uff09</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#164","title":"1.6.4 \u4f5c\u4e3a\u8fd4\u56de\u503c\u7684\u51fd\u6570","text":"<ul> <li>composition</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#165","title":"1.6.5 \u793a\u4f8b\uff1a\u725b\u987f\u6cd5","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#166-currying","title":"1.6.6 Currying","text":"<ul> <li>uncurrying transformation</li> </ul> Python<pre><code>&gt;&gt;&gt; def curry2(f):\n        \"\"\"\u8fd4\u56de\u7ed9\u5b9a\u7684\u53cc\u53c2\u6570\u51fd\u6570\u7684\u67ef\u91cc\u5316\u7248\u672c\"\"\"\n        def g(x):\n            def h(y):\n                return f(x, y)\n            return h\n        return g\n&gt;&gt;&gt; def uncurry2(g):\n        \"\"\"\u8fd4\u56de\u7ed9\u5b9a\u7684\u67ef\u91cc\u5316\u51fd\u6570\u7684\u53cc\u53c2\u6570\u7248\u672c\"\"\"\n        def f(x, y):\n            return g(x)(y)\n        return f\n&gt;&gt;&gt; pow_curried = curry2(pow)\n&gt;&gt;&gt; pow_curried(2)(5)\n32\n&gt;&gt;&gt; map_to_range(0, 10, pow_curried(2))\n1\n2\n4\n8\n16\n32\n64\n128\n256\n512\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#167-lambda","title":"1.6.7 Lambda \u8868\u8fbe\u5f0f","text":"Python<pre><code>lambda              x         :              f(g(x))\n\"A function that    takes x   and returns    f(g(x))\"\n</code></pre> <p>\\(\\displaystyle \\lambda\\)</p> Python<pre><code>&gt;&gt;&gt; s = lambda x: x * x\n&gt;&gt;&gt; s\n&lt;function &lt;lambda&gt; at 0xf3f490&gt;\n&gt;&gt;&gt; s(12)\n144\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#168","title":"1.6.8 \u62bd\u8c61\u548c\u4e00\u7b49\u51fd\u6570","text":"<ul> <li>first-class status</li> </ul> <ol> <li>\u53ef\u4ee5\u4e0e\u540d\u79f0\u7ed1\u5b9a</li> <li>\u53ef\u4ee5\u4f5c\u4e3a\u53c2\u6570\u4f20\u9012\u7ed9\u51fd\u6570</li> <li>\u53ef\u4ee5\u4f5c\u4e3a\u51fd\u6570\u7684\u7ed3\u679c\u8fd4\u56de</li> <li>\u53ef\u4ee5\u5305\u542b\u5728\u6570\u636e\u7ed3\u6784\u4e2d</li> </ol>"},{"location":"CS_Basic/CS61A/Composing_Programs/#169","title":"1.6.9 \u51fd\u6570\u88c5\u9970\u5668","text":"<ul> <li>decorator</li> </ul> Python<pre><code>&gt;&gt;&gt; def trace(fn):\n        def wrapped(x):\n            print('-&gt; ', fn, '(', x, ')')\n            return fn(x)\n        return wrapped\n\n&gt;&gt;&gt; @trace\n    def triple(x):\n        return 3 * x\n\n&gt;&gt;&gt; triple(12)\n-&gt;  &lt;function triple at 0x102a39848&gt; ( 12 )\n36\n</code></pre> <ul> <li>annotation  </li> <li>\u7b49\u4ef7\u4e8e:</li> </ul> Python<pre><code>&gt;&gt;&gt; def triple(x):\n        return 3 * x\n&gt;&gt;&gt; triple = trace(triple)\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#17","title":"1.7 \u9012\u5f52\u51fd\u6570","text":"<ul> <li>rucursive  </li> <li>circular nature</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#171","title":"1.7.1 \u9012\u5f52\u51fd\u6570\u5256\u6790","text":"<ul> <li>base case  </li> <li>unwinds  </li> <li>recursive calls  </li> <li>induction</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#172-mutually-recursive","title":"1.7.2 mutually recursive","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#173","title":"1.7.3 \u9012\u5f52\u51fd\u6570\u4e2d\u7684\u6253\u5370","text":"<ul> <li>abstraction barrier</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#174-tree-recursive","title":"1.7.4 tree recursive","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#175","title":"1.7.5 \u793a\u4f8b\uff1a\u5206\u5272\u6570","text":"Python<pre><code>&gt;&gt;&gt; def count_partitions(n, m):\n\u00a0\u00a0\u00a0     \"\"\"\u8ba1\u7b97\u4f7f\u7528\u6700\u5927\u6570 m \u7684\u6574\u6570\u5206\u5272 n \u7684\u65b9\u5f0f\u7684\u6570\u91cf\"\"\"\n\u00a0\u00a0\u00a0     if n == 0:\n\u00a0\u00a0\u00a0         return 1\n\u00a0\u00a0\u00a0     elif n &lt; 0:\n\u00a0\u00a0\u00a0         return 0\n\u00a0\u00a0\u00a0     elif m == 0:\n\u00a0\u00a0\u00a0         return 0\n\u00a0\u00a0\u00a0     else:\n\u00a0\u00a0\u00a0         return count_partitions(n-m, m) + count_partitions(n, m-1)\n\n&gt;&gt;&gt; count_partitions(6, 4)\n9\n&gt;&gt;&gt; count_partitions(5, 5)\n7\n&gt;&gt;&gt; count_partitions(10, 10)\n42\n&gt;&gt;&gt; count_partitions(15, 15)\n176\n&gt;&gt;&gt; count_partitions(20, 20)\n627\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#2","title":"2 \u4f7f\u7528\u6570\u636e\u6784\u5efa\u62bd\u8c61","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#21","title":"2.1 \u5f15\u8a00","text":"<ul> <li>\u9ad8\u9636\u51fd\u6570\u4f7f\u6211\u4eec\u80fd\u591f\u6839\u636e\u901a\u7528\u7684\u8ba1\u7b97\u65b9\u6cd5\u8fdb\u884c\u64cd\u4f5c\u548c\u63a8\u7406\uff0c\u4ece\u800c\u589e\u5f3a\u4e86\u8bed\u8a00\u7684\u529f\u80fd\u3002\u8fd9\u5c31\u662f\u7f16\u7a0b\u7684\u672c\u8d28</li> <li>\u6709\u6548\u4f7f\u7528\u5185\u7f6e\u6570\u636e\u7c7b\u578b\u548c\u7528\u6237\u5b9a\u4e49\u7684\u6570\u636e\u7c7b\u578b\u662f\u6570\u636e\u5904\u7406\u578b\u5e94\u7528\uff08data processing applications\uff09\u7684\u57fa\u7840</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#211","title":"2.1.1 \u539f\u59cb\u6570\u636e\u7c7b\u578b","text":"<p>\u539f\u59cb\u6570\u636e\u7c7b\u578b\u5177\u6709\u5c5e\u6027:</p> <ol> <li>\u6709\u4e00\u4e9b\u53ef\u4ee5\u6c42\u89e3\u4e3a\u539f\u59cb\u6570\u636e\u7c7b\u578b\u7684\u8868\u8fbe\u5f0f\uff0c\u88ab\u79f0\u4e3a\u5b57\u9762\u91cf\uff08literals\uff09\u3002</li> <li>\u6709\u7528\u4e8e\u64cd\u4f5c\u539f\u59cb\u7c7b\u578b\u503c\u7684\u5185\u7f6e\u51fd\u6570\u548c\u64cd\u4f5c\u7b26\u3002 - \u539f\u59cb\u6570\u5b57\u7c7b\u578b<ul> <li>int</li> <li>float</li> <li>complex</li> <li>Non-numeric types</li> <li>bool</li> <li>more on \u539f\u59cb\u6570\u636e\u7c7b\u578b</li> </ul> </li> </ol>"},{"location":"CS_Basic/CS61A/Composing_Programs/#22","title":"2.2 \u6570\u636e\u62bd\u8c61","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#221","title":"2.2.1 \u793a\u4f8b\uff1a\u6709\u7406\u6570","text":"<p>wishful thinking</p> Python<pre><code>&gt;&gt;&gt; def add_rationals(x, y):\n        nx, dx = numer(x), denom(x)\n        ny, dy = numer(y), denom(y)\n        return rational(nx * dy + ny * dx, dx * dy)\n\n&gt;&gt;&gt; def mul_rationals(x, y):\n        return rational(numer(x) * numer(y), denom(x) * denom(y))\n\n&gt;&gt;&gt; def print_rational(x):\n        print(numer(x), '/', denom(x))\n\n&gt;&gt;&gt; def rationals_are_equal(x, y):\n        return numer(x) * denom(y) == numer(y) * denom(x)\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#222-pair","title":"2.2.2 pair","text":"<p>from operator import getitem</p> Python<pre><code>&gt;&gt;&gt; def rational(n, d):\n        return [n, d]\n\n&gt;&gt;&gt; def numer(x):\n        return x[0]\n\n&gt;&gt;&gt; def denom(x):\n        return x[1]\n</code></pre> <p>\u7b80\u5316\u6709\u7406\u6570:</p> Python<pre><code>&gt;&gt;&gt; from fractions import gcd\n&gt;&gt;&gt; def rational(n, d):\n        g = gcd(n, d)\n        return (n//g, d//g)\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#223","title":"2.2.3 \u62bd\u8c61\u5c4f\u969c","text":"<ul> <li>\u6570\u636e\u62bd\u8c61: \u7528\u4e00\u7ec4\u57fa\u672c\u64cd\u4f5c\u6765\u64cd\u4f5c\u6570\u636e\u3002  </li> <li>avbstraction barrier  </li> <li>the best:</li> </ul> Python<pre><code>&gt;&gt;&gt; def square_rational(x):\n    return mul_rational(x, x)\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#224","title":"2.2.4 \u6570\u636e\u7684\u5c5e\u6027","text":"<p>\u76f8\u5f53\u4e8e\u81ea\u5df1\u5199\u4e00\u4e2a\u6570\u636e\u7ed3\u6784:</p> Python<pre><code>&gt;&gt;&gt; def pair(x, y):\n        \"\"\"Return a function that represents a pair.\"\"\"\n        def get(index):\n            if index == 0:\n                return x\n            elif index == 1:\n                return y\n        return get\n\n&gt;&gt;&gt; def select(p, i):\n        \"\"\"Return the element at index i of pair p.\"\"\"\n        return p(i)\n\n&gt;&gt;&gt; p = pair(20, 14)\n&gt;&gt;&gt; select(p, 0)\n20\n&gt;&gt;&gt; select(p, 1)\n14\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#23","title":"2.3 \u5e8f\u5217","text":"<ul> <li>sequence<ul> <li>Length</li> <li>Element selection</li> </ul> </li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#231-list","title":"2.3.1 list","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#232","title":"2.3.2 \u5e8f\u5217\u904d\u5386","text":"Python<pre><code>for &lt;name&gt; in &lt;expression&gt;:\n    &lt;suite&gt;\n</code></pre> <p>the expression must produce an iterable object sequence unpacking</p> Python<pre><code>&gt;&gt;&gt; pairs = [[1, 2], [2, 2], [2, 3], [4, 4]]\n&gt;&gt;&gt; same_count = 0\n&gt;&gt;&gt; for x, y in pairs:\n        if x == y:\n            same_count = same_count + 1\n&gt;&gt;&gt; same_count\n2\n</code></pre> <p>range</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#233","title":"2.3.3 \u5e8f\u5217\u5904\u7406","text":"<p>list comprehensions</p> Python<pre><code>&gt;&gt;&gt; odds = [1, 3, 5, 7, 9]\n&gt;&gt;&gt; [x+1 for x in odds]\n[2, 4, 6, 8, 10]\n[&lt;map expression&gt; for &lt;name&gt; in &lt;sequence expression&gt; if &lt;filter expression&gt;]\n</code></pre> <ul> <li>Aggregation \u5c31\u662f\u7f29\u5e76\u5566<ul> <li>sum</li> <li>min</li> <li>max</li> </ul> </li> </ul> Python<pre><code>&gt;&gt;&gt; def apply_to_all(map_fn, s):\n    return [map_fn(x) for x in s]\n&gt;&gt;&gt; def keep_if(filter_fn, s):\n    return [x for x in s if filter_fn(x)]\n# conventional names\n&gt;&gt;&gt; apply_to_all = lambda map_fn, s: list(map(map_fn, s))\n&gt;&gt;&gt; keep_if = lambda filter_fn, s: list(filter(filter_fn, s))\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#234","title":"2.3.4 \u5e8f\u5217\u62bd\u8c61","text":"<ul> <li>Membership<ul> <li>in</li> <li>not in</li> </ul> </li> <li>Slicing</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#235","title":"2.3.5 \u5b57\u7b26\u4e32","text":"<p>string \u6ca1\u6709\u5b57\u7b26\u7c7b\u578b</p> <ul> <li>Membership</li> <li>Multiline Literals</li> <li>String Coercion more on Dive Into Python 3\u00a0\u7684\u00a0\u5b57\u7b26\u4e32\u7ae0\u8282\u00a0\u63d0\u4f9b\u4e86\u5b57\u7b26\u7f16\u7801\u548c Unicode \u7684\u63cf\u8ff0</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#236","title":"2.3.6 \u6811","text":"<p>closure property bax-and-pointer notation</p> <ul> <li>root label</li> <li>branch</li> <li>leaf: the tree without branch</li> <li>node tree-recursive \u4e24\u4e2a\u4f8b\u5b50:</li> </ul> Python<pre><code>&gt;&gt;&gt; def fib_tree(n):\n        if n == 0 or n == 1:\n            return tree(n)\n        else:\n            left, right = fib_tree(n-2), fib_tree(n-1)\n            fib_n = label(left) + label(right)\n            return tree(fib_n, [left, right])\n&gt;&gt;&gt; fib_tree(5)\n[5, [2, [1], [1, [0], [1]]], [3, [1, [0], [1]], [2, [1], [1, [0], [1]]]]]\n</code></pre> Python<pre><code>&gt;&gt;&gt; def count_leaves(tree):\n      if is_leaf(tree):\n          return 1\n      else:\n          branch_counts = [count_leaves(b) for b in branches(tree)]\n          return sum(branch_counts)\n&gt;&gt;&gt; count_leaves(fib_tree(5))\n8\n</code></pre> <p>Partition trees</p> Python<pre><code>&gt;&gt;&gt; def print_parts(tree, partition=[]):\n        if is_leaf(tree):\n            if label(tree):\n                print(' + '.join(partition))\n        else:\n            left, right = branches(tree)\n            m = str(label(tree))\n            print_parts(left, partition + [m])\n            print_parts(right, partition)\n\n&gt;&gt;&gt; print_parts(partition_tree(6, 4))\n4 + 2\n4 + 1 + 1\n3 + 3\n3 + 2 + 1\n3 + 1 + 1 + 1\n2 + 2 + 2\n2 + 2 + 1 + 1\n2 + 1 + 1 + 1 + 1\n1 + 1 + 1 + 1 + 1 + 1\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#237","title":"2.3.7 \u94fe\u8868","text":"<p>linked list abstract data representation</p> Python<pre><code>&gt;&gt;&gt; def partitions(n, m):\n\"\"\"\u8fd4\u56de\u4e00\u4e2a\u5305\u542b n \u7684\u5206\u5272\u65b9\u6848\u7684\u94fe\u8868\uff0c\u5176\u4e2d\u6bcf\u4e2a\u6b63\u6574\u6570\u4e0d\u8d85\u8fc7 m\"\"\"\nif n == 0:\n    return link(empty, empty) # \u5305\u542b\u7a7a\u5206\u5272\u7684\u94fe\u8868\nelif n &lt; 0 or m == 0:\n    return empty\nelse:\n    using_m = partitions(n-m, m)\n    with_m = apply_to_all_link(lambda s: link(m, s), using_m)\n    without_m = partitions(n, m-1)\n    return extend_link(with_m, without_m)\n\n&gt;&gt;&gt; def print_partitions(n, m):\n        lists = partitions(n, m)\n        strings = apply_to_all_link(lambda s: join_link(s, \" + \"), lists)\n        print(join_link(strings, \"\\n\"))\n\n&gt;&gt;&gt; print_partitions(6, 4)\n4 + 2\n4 + 1 + 1\n3 + 3\n3 + 2 + 1\n3 + 1 + 1 + 1\n2 + 2 + 2\n2 + 2 + 1 + 1\n2 + 1 + 1 + 1 + 1\n1 + 1 + 1 + 1 + 1 + 1\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#24","title":"2.4 \u53ef\u53d8\u6570\u636e","text":"<p>object-oriented programming</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#241","title":"2.4.1 \u5bf9\u8c61\u9690\u55bb","text":"<ul> <li>attributes</li> <li>method</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#242","title":"2.4.2 \u5e8f\u5217\u5bf9\u8c61","text":"<p>mutable Sharing and Identity \u5217\u8868\u63a8\u5bfc\u5f0f:</p> Python<pre><code>&gt;&gt;&gt; from unicodedata import lookup\n&gt;&gt;&gt; [lookup('WHITE ' + s.upper() + ' SUIT') for s in suits]\n['\u2661', '\u2662', '\u2664', '\u2667']\n</code></pre> <p>tuple</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#243","title":"2.4.3 \u5b57\u5178","text":"<p>key-value pairs</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#244","title":"2.4.4 \u5c40\u90e8\u72b6\u6001","text":"<p>local state</p> Python<pre><code>&gt;&gt;&gt; def make_withdraw(balance):\n\"\"\"\u8fd4\u56de\u4e00\u4e2a\u6bcf\u6b21\u8c03\u7528\u90fd\u4f1a\u51cf\u5c11 balance \u7684 withdraw \u51fd\u6570\"\"\"\ndef withdraw(amount):\n    nonlocal balance                 # \u58f0\u660e balance \u662f\u975e\u5c40\u90e8\u7684\n    if amount &gt; balance:\n        return '\u4f59\u989d\u4e0d\u8db3'\n    balance = balance - amount       # \u91cd\u65b0\u7ed1\u5b9a\n    return balance\nreturn withdraw\n</code></pre> <p>Python Particulars</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#245-non-local","title":"2.4.5 \u975e\u5c40\u90e8 Non-local \u8d4b\u503c\u7684\u597d\u5904","text":"<p>\u8fd9\u6837\uff0c\u6bcf\u4e2a withdraw \u5b9e\u4f8b\u90fd\u4fdd\u6301\u81ea\u5df1\u7684 balance \u72b6\u6001\uff0c\u4f46\u7a0b\u5e8f\u4e2d\u7684\u4efb\u4f55\u5176\u4ed6\u51fd\u6570\u90fd\u65e0\u6cd5\u8bbf\u95ee\u8be5\u72b6\u6001\u3002\u4ece\u66f4\u9ad8\u7684\u5c42\u9762\u6765\u770b\u8fd9\u79cd\u60c5\u51b5\uff0c\u6211\u4eec\u62bd\u8c61\u4e86\u4e00\u4e2a\u94f6\u884c\u8d26\u6237\uff0c\u5b83\u81ea\u5df1\u7ba1\u7406\u81ea\u5df1\u7684\u72b6\u6001\uff0c\u5176\u884c\u4e3a\u65b9\u5f0f\u4e0e\u4e16\u754c\u4e0a\u6240\u6709\u5176\u5b83\u8d26\u6237\u4e00\u6837\uff1a\u968f\u7740\u65f6\u95f4\u63a8\u79fb\uff0c\u8d26\u6237\u7684\u72b6\u6001\u4f1a\u6839\u636e\u8d26\u6237\u7684\u53d6\u6b3e\u8bb0\u5f55\u800c\u53d1\u751f\u53d8\u5316\u3002</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#246-non-local","title":"2.4.6 \u975e\u5c40\u90e8 Non-local \u8d4b\u503c\u7684\u4ee3\u4ef7","text":"<ul> <li>\u6b63\u786e\u7406\u89e3\u5305\u542b nonlocal \u58f0\u660e\u7684\u4ee3\u7801\u7684\u5173\u952e\u662f\u8bb0\u4f4f\uff1a\u53ea\u6709\u51fd\u6570\u8c03\u7528\u624d\u80fd\u5f15\u5165\u65b0\u5e27\u3002\u8d4b\u503c\u8bed\u53e5\u53ea\u80fd\u66f4\u6539\u73b0\u6709\u5e27\u4e2d\u7684\u7ed1\u5b9a\u5173\u7cfb\u3002\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u9664\u975e make_withdraw \u88ab\u8c03\u7528\u4e24\u6b21\uff0c\u5426\u5219\u53ea\u80fd\u6709\u4e00\u4e2a balance \u7ed1\u5b9a\u3002  </li> <li>Sameness and change  </li> <li>referentially transparent</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#247","title":"2.4.7 \u5217\u8868\u548c\u5b57\u5178\u5b9e\u73b0","text":"<p>\u51fd\u6570\u662f\u4e00\u4e2a dispatch \uff08\u8c03\u5ea6\uff09\u51fd\u6570\uff0c\u5176\u53c2\u6570\u9996\u5148\u662f\u4e00\u4e2a\u671f\u671b\u7684\u6307\u4ee4\uff0c\u4ee3\u8868\u671f\u671b\u8fd9\u4e2a\u51fd\u6570\u505a\u4ec0\u4e48\uff1b\u7136\u540e\u662f\u8be5\u65b9\u6cd5\u7684\u9700\u8981\u7528\u5230\u7684\u53c2\u6570\u3002\u6b64\u6307\u4ee4\u662f\u4e00\u4e2a\u5b57\u7b26\u4e32\uff0c\u7528\u4e8e\u547d\u540d\u51fd\u6570\u5e94\u6267\u884c\u7684\u64cd\u4f5c\u3002\u53ef\u4ee5\u5c06\u8fd9\u4e2a dispatch \u51fd\u6570\u7406\u89e3\u4e3a\u591a\u4e2a\u4e0d\u540c\u51fd\u6570\u7684\u62bd\u8c61\uff1a\u7b2c\u4e00\u4e2a\u53c2\u6570\u786e\u5b9a\u76ee\u6807\u51fd\u6570\u7684\u884c\u4e3a\uff0c\u5e76\u4e3a\u8be5\u884c\u4e3a\u5165\u53c2\u5176\u4ed6\u53c2\u6570\u3002     \u7528\u5b57\u7b26\u4e32\u4e5f\u592a\u9006\u5929\u4e86\u3002</p> Python<pre><code>&gt;&gt;&gt; def mutable_link():\n\"\"\"\u8fd4\u56de\u4e00\u4e2a\u53ef\u53d8\u94fe\u8868\u7684\u51fd\u6570\"\"\"\ncontents = empty\ndef dispatch(message, value=None):\n    nonlocal contents\n    if message == 'len':\n        return len_link(contents)\n    elif message == 'getitem':\n        return getitem_link(contents, value)\n    elif message == 'push_first':\n        contents = link(value, contents)\n    elif message == 'pop_first':\n        f = first(contents)\n        contents = rest(contents)\n        return f\n    elif message == 'str':\n        return join_link(contents, \", \")\nreturn dispatch\n\n&gt;&gt;&gt; def to_mutable_link(source):\n\"\"\"\u8fd4\u56de\u4e00\u4e2a\u4e0e\u539f\u5217\u8868\u76f8\u540c\u5185\u5bb9\u7684\u51fd\u6570\u5217\u8868\"\"\"\ns = mutable_link()\nfor element in reversed(source):\n    s('push_first', element)\nreturn s\n\n&gt;&gt;&gt; s = to_mutable_link(suits)\n&gt;&gt;&gt; type(s)\n&lt;class 'function'&gt;\n&gt;&gt;&gt; print(s('str'))\nheart, diamond, spade, club\n</code></pre> <p>\u5b57\u5178\u5b9e\u73b0:</p> Python<pre><code>&gt;&gt;&gt; def dictionary():\n\"\"\"\u8fd4\u56de\u4e00\u4e2a\u5b57\u5178\u7684\u51fd\u6570\u5b9e\u73b0\"\"\"\nrecords = []\ndef getitem(key):\n    matches = [r for r in records if r[0] == key]\n    if len(matches) == 1:\n        key, value = matches[0]\n        return value\ndef setitem(key, value):\n    nonlocal records\n    non_matches = [r for r in records if r[0] != key]\n    records = non_matches + [[key, value]]\ndef dispatch(message, key=None, value=None):\n    if message == 'getitem':\n        return getitem(key)\n    elif message == 'setitem':\n        setitem(key, value)\nreturn dispatch\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#248-dispatch-dictionaries","title":"2.4.8 \u8c03\u5ea6\u5b57\u5178\uff08Dispatch Dictionaries\uff09","text":"<p>\u7528\u5b57\u5178\u5b58\u50a8\u6d88\u606f\u3002</p> Python<pre><code>def account(initial_balance):\n    def deposit(amount):\n        dispatch['balance'] += amount\n        return dispatch['balance']\n    def withdraw(amount):\n        if amount &gt; dispatch['balance']:\n            return 'Insufficient funds'\n        dispatch['balance'] -= amount\n        return dispatch['balance']\n    dispatch = {'deposit':   deposit,\n                'withdraw':  withdraw,\n                'balance':   initial_balance}\n    return dispatch\n\ndef withdraw(account, amount):\n    return account['withdraw'](amount)\ndef deposit(account, amount):\n    return account['deposit'](amount)\ndef check_balance(account):\n    return account['balance']\n\na = account(20)\ndeposit(a, 5)\nwithdraw(a, 17)\ncheck_balance(a)\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#249-propagating-constraints","title":"2.4.9 \u7ea6\u675f\u4f20\u9012 (Propagating\u00a0Constraints)","text":"<p>connector Using the Constraint System</p> Python<pre><code>&gt;&gt;&gt; celsius = connector('Celsius')\n&gt;&gt;&gt; fahrenheit = connector('Fahrenheit')\n&gt;&gt;&gt; def converter(c, f):\n    \"\"\"\u7528\u7ea6\u675f\u6761\u4ef6\u8fde\u63a5 c \u5230 f\uff0c\u5c06\u6444\u6c0f\u5ea6\u8f6c\u6362\u4e3a\u534e\u6c0f\u5ea6.\"\"\"\n    u, v, w, x, y = [connector() for _ in range(5)]\n    multiplier(c, w, u)\n    multiplier(v, x, u)\n    adder(v, y, f)\n    constant(w, 9)\n    constant(x, 5)\n    constant(y, 32)\n&gt;&gt;&gt; converter(celsius, fahrenheit)\n\n&gt;&gt;&gt; celsius['set_val']('user', 25)\nCelsius = 25\nFahrenheit = 77.0\n\n&gt;&gt;&gt; fahrenheit['set_val']('user', 212)\nContradiction detected: 77.0 vs 212\n\n&gt;&gt;&gt; celsius['forget']('user')\nCelsius is forgotten\nFahrenheit is forgotten\n\n&gt;&gt;&gt; fahrenheit['set_val']('user', 212)\nFahrenheit = 212\nCelsius = 100.0\n\n# Implementing the Constraint System\n&gt;&gt;&gt; connector ['set_val'](source, value)  \"\"\"\u8868\u793a\u00a0source\u00a0\u5728\u8bf7\u6c42\u8fde\u63a5\u5668\u5c06\u5f53\u524d\u503c\u8bbe\u4e3a value\"\"\"\n&gt;&gt;&gt; connector ['has_val']()\u00a0 \"\"\"\u8fd4\u56de\u8fde\u63a5\u5668\u662f\u5426\u5df2\u7ecf\u5177\u6709\u503c\"\"\"\n&gt;&gt;&gt; connector ['val']  \"\"\"\u662f\u8fde\u63a5\u5668\u7684\u5f53\u524d\u503c\"\"\"\n&gt;&gt;&gt; connector ['forget'](source)\u00a0 \"\"\"\u544a\u8bc9\u8fde\u63a5\u5668 source \u8bf7\u6c42\u9057\u5fd8\u5b83\u7684\u503c\"\"\"\n&gt;&gt;&gt; connector ['connect'](source)\u00a0 \"\"\"\u544a\u8bc9\u8fde\u63a5\u5668\u53c2\u4e0e\u65b0\u7684\u7ea6\u675f\uff0c\u5373 source\"\"\"\n&gt;&gt;&gt; constraint['new_val']()  \"\"\"\u8868\u793a\u4e0e\u7ea6\u675f\u76f8\u8fde\u7684\u67d0\u4e2a\u8fde\u63a5\u5668\u5177\u6709\u65b0\u7684\u503c\u3002\"\"\"\n&gt;&gt;&gt; constraint['forget']()\u00a0 \"\"\"\u8868\u793a\u4e0e\u7ea6\u675f\u76f8\u8fde\u7684\u67d0\u4e2a\u8fde\u63a5\u5668\u9057\u5fd8\u4e86\u503c\u3002\"\"\"\n\n&gt;&gt;&gt; from operator import add, sub\n&gt;&gt;&gt; def adder(a, b, c):\n        \"\"\"\u7ea6\u675f a+b=c\"\"\"\n        return make_ternary_constraint(a, b, c, add, sub, sub)\n\n&gt;&gt;&gt; def make_ternary_constraint(a, b, c, ab, ca, cb):\n    \"\"\"\u7ea6\u675f ab(a,b)=c\uff0cca(c,a)=b\uff0ccb(c,b)=a\"\"\"\n    def new_value():\n        av, bv, cv = [connector['has_val']() for connector in (a, b, c)]\n        if av and bv:\n            c['set_val'](constraint, ab(a['val'], b['val']))\n        elif av and cv:\n            b['set_val'](constraint, ca(c['val'], a['val']))\n        elif bv and cv:\n            a['set_val'](constraint, cb(c['val'], b['val']))\n    def forget_value():\n        for connector in (a, b, c):\n            connector['forget'](constraint)\n    constraint = {'new_val': new_value, 'forget': forget_value}\n    for connector in (a, b, c):\n        connector['connect'](constraint)\n    return constraint\n\n&gt;&gt;&gt; from operator import mul, truediv\n&gt;&gt;&gt; def multiplier(a, b, c):\n        \"\"\"\u7ea6\u675f a*b=c\"\"\"\n        return make_ternary_constraint(a, b, c, mul, truediv, truediv)\n\n&gt;&gt;&gt; def constant(connector, value):\n    \"\"\"\u5e38\u91cf\u8d4b\u503c\"\"\"\n    constraint = {}\n    connector['set_val'](constraint, value)\n    return constraint\n\n# Representing connectors\n&gt;&gt;&gt; def connector(name=None):\n    \"\"\"\u9650\u5236\u6761\u4ef6\u4e4b\u95f4\u7684\u8fde\u63a5\u5668\"\"\"\n    informant = None\n    constraints = []\n    def set_value(source, value):\n        nonlocal informant\n        val = connector['val']\n        if val is None:\n            informant, connector['val'] = source, value\n            if name is not None:\n                print(name, '=', value)\n            inform_all_except(source, 'new_val', constraints)\n        else:\n            if val != value:\n                print('Contradiction detected:', val, 'vs', value)\n    def forget_value(source):\n        nonlocal informant\n        if informant == source:\n            informant, connector['val'] = None, None\n            if name is not None:\n                print(name, 'is forgotten')\n            inform_all_except(source, 'forget', constraints)\n    connector = {'val': None,\n                 'set_val': set_value,\n                 'forget': forget_value,\n                 'has_val': lambda: connector['val'] is not None,\n                 'connect': lambda source: constraints.append(source)}\n    return connector\n\n&gt;&gt;&gt; def inform_all_except(source, message, constraints):\n    \"\"\"\u544a\u77e5\u4fe1\u606f\u9664\u4e86 source \u5916\u7684\u6240\u6709\u7ea6\u675f\u6761\u4ef6\"\"\"\n    for c in constraints:\n        if c != source:\n            c[message]()\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#25","title":"2.5 \u9762\u5411\u5bf9\u8c61\u7f16\u7a0b","text":"<ul> <li>object</li> <li>dot notation</li> <li>class</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#251","title":"2.5.1 \u5bf9\u8c61\u548c\u7c7b","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#252","title":"2.5.2 \u7c7b\u7684\u5b9a\u4e49","text":"<p>__init__\u7c7b\u7684\u6784\u9020\u51fd\u6570\uff08constructor\uff09</p> Python<pre><code>&gt;&gt;&gt; class Account:\n        def __init__(self, account_holder):\n            self.balance = 0\n            self.holder = account_holder\n        def deposit(self, amount):\n            self.balance = self.balance + amount\n            return self.balance\n        def withdraw(self, amount):\n            if amount &gt; self.balance:\n                return 'Insufficient funds'\n            self.balance = self.balance - amount\n            return self.balance\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#253","title":"2.5.3 \u6d88\u606f\u4f20\u9012\u548c\u70b9\u8868\u8fbe\u5f0f","text":"Python<pre><code>&gt;&gt;&gt; getattr(spock_account, 'balance')\n10\n&gt;&gt;&gt; hasattr(spock_account, 'deposit')\nTrue\n\n\n&gt;&gt;&gt; type(Account.deposit)\n&lt;class 'Function'&gt;\n&gt;&gt;&gt; type(spock_account.deposit)\n&lt;class 'method'&gt;\n# \u4e3a\u7c7b\u7684\u5c5e\u6027\uff0c\u65b9\u6cd5\u53ea\u662f\u4e00\u4e2a\u51fd\u6570\uff0c\u4f46\u4f5c\u4e3a\u5b9e\u4f8b\u7684\u5c5e\u6027\uff0c\u5b83\u662f\u4e00\u4e2a\u7ed1\u5b9a\u65b9\u6cd5\n\n&gt;&gt;&gt; Account.deposit(spock_account, 1001)    # \u51fd\u6570 deposit \u63a5\u53d7\u4e24\u4e2a\u53c2\u6570\n1011\n&gt;&gt;&gt; spock_account.deposit(1000)             # \u65b9\u6cd5 deposit \u63a5\u53d7\u4e00\u4e2a\u53c2\u6570\n2011\n</code></pre> <p>\u547d\u540d\u7ea6\u5b9a\uff1a\u7c7b\u540d\u901a\u5e38\u4f7f\u7528 CapWords \u7ea6\u5b9a\uff08\u4e5f\u79f0\u4e3a CamelCase\uff0c\u56e0\u4e3a\u540d\u79f0\u4e2d\u95f4\u7684\u5927\u5199\u5b57\u6bcd\u770b\u8d77\u6765\u50cf\u9a7c\u5cf0\uff09\u7f16\u5199\u3002\u65b9\u6cd5\u540d\u79f0\u9075\u5faa\u4f7f\u7528\u4e0b\u5212\u7ebf\u5206\u9694\u7684\u5c0f\u5199\u5355\u8bcd\u547d\u540d\u51fd\u6570\u7684\u6807\u51c6\u7ea6\u5b9a\u3002</p> <p>\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u6709\u4e00\u4e9b\u5b9e\u4f8b\u53d8\u91cf\u548c\u65b9\u6cd5\u4e0e\u5bf9\u8c61\u7684\u7ef4\u62a4\u548c\u4e00\u81f4\u6027\u76f8\u5173\uff0c\u6211\u4eec\u4e0d\u5e0c\u671b\u5bf9\u8c61\u7684\u7528\u6237\u770b\u5230\u6216\u4f7f\u7528\u3002\u5b83\u4eec\u4e0d\u662f\u7c7b\u5b9a\u4e49\u7684\u62bd\u8c61\u7684\u4e00\u90e8\u5206\uff0c\u800c\u662f\u5b9e\u73b0\u7684\u4e00\u90e8\u5206\u3002Python \u7684\u7ea6\u5b9a\u89c4\u5b9a\uff0c\u5982\u679c\u5c5e\u6027\u540d\u79f0\u4ee5\u4e0b\u5212\u7ebf\u5f00\u5934\uff0c\u5219\u53ea\u80fd\u5728\u7c7b\u672c\u8eab\u7684\u65b9\u6cd5\u4e2d\u8bbf\u95ee\u5b83\uff0c\u800c\u4e0d\u662f\u7528\u6237\u8bbf\u95ee\u3002</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#254","title":"2.5.4 \u7c7b\u5c5e\u6027","text":"<p>\u611f\u89c9\u6ca1\u4ec0\u4e48\u7528:</p> Python<pre><code>&gt;&gt;&gt; Account.interest = 0.05     # \u6539\u53d8\u7c7b\u5c5e\u6027\n&gt;&gt;&gt; spock_account.interest      # \u5b9e\u4f8b\u5c5e\u6027\u53d1\u751f\u53d8\u5316\uff08\u8be5\u5b9e\u4f8b\u4e2d\u6ca1\u6709\u548c\u7c7b\u5c5e\u6027\u540c\u540d\u79f0\u7684\u5b9e\u4f8b\u5c5e\u6027\uff09\n0.05\n&gt;&gt;&gt; kirk_account.interest       # \u5982\u679c\u5b9e\u4f8b\u4e2d\u5b58\u5728\u548c\u7c7b\u5c5e\u6027\u540c\u540d\u7684\u5b9e\u4f8b\u5c5e\u6027\uff0c\u5219\u6539\u53d8\u7c7b\u5c5e\u6027\uff0c\u4e0d\u4f1a\u5f71\u54cd\u5b9e\u4f8b\u5c5e\u6027\n0.08\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#255","title":"2.5.5 \u7ee7\u627f","text":"<ul> <li>base class<ul> <li>parent class</li> <li>super class</li> </ul> </li> <li>subcladd<ul> <li>child class</li> </ul> </li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#256","title":"2.5.6 \u4f7f\u7528\u7ee7\u627f","text":"Python<pre><code>&gt;&gt;&gt; class Account:\n        \"\"\"\u4e00\u4e2a\u4f59\u989d\u975e\u96f6\u7684\u8d26\u6237\u3002\"\"\"\n        interest = 0.02\n        def __init__(self, account_holder):\n            self.balance = 0\n            self.holder = account_holder\n        def deposit(self, amount):\n            \"\"\"\u5b58\u5165\u8d26\u6237 amount\uff0c\u5e76\u8fd4\u56de\u53d8\u5316\u540e\u7684\u4f59\u989d\"\"\"\n            self.balance = self.balance + amount\n            return self.balance\n        def withdraw(self, amount):\n            \"\"\"\u4ece\u8d26\u53f7\u4e2d\u53d6\u51fa amount\uff0c\u5e76\u8fd4\u56de\u53d8\u5316\u540e\u7684\u4f59\u989d\"\"\"\n            if amount &gt; self.balance:\n                return 'Insufficient funds'\n            self.balance = self.balance - amount\n            return self.balance\n\n&gt;&gt;&gt; class CheckingAccount(Account):\n        \"\"\"\u4ece\u8d26\u53f7\u53d6\u94b1\u4f1a\u6263\u51fa\u624b\u7eed\u8d39\u7684\u8d26\u53f7\"\"\"\n           withdraw_charge = 1\n           interest = 0.01\n           def withdraw(self, amount):\n                 return Account.withdraw(self, amount + self.withdraw_charge)\n</code></pre> <p>\u63a5\u53e3</p> Python<pre><code>&gt;&gt;&gt; def deposit_all(winners, amount=5):\n        for account in winners:\n            account.deposit(amount)         # \u8fd9\u91cc\u8c03\u7528\u7684\u662f\u5b9e\u4f8b account \u7684 deposit \u65b9\u6cd5\n            # \u5bf9\u4e8e\u4e0d\u540c\u5b9e\u4f8b\u6765\u8bf4\uff0c\u5b83\u4eec\u7684 deposit \u65b9\u6cd5\u53ef\u80fd\u4e0d\u540c\u3002\u8fd9\u4e2a\u4f8b\u5b50\u76f8\u5bf9\u4e8e\u4e0b\u9762\u6765\u8bb2\uff0c\u66f4\u52a0\u5177\u6709\u5065\u58ee\u6027\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#257","title":"2.5.7 \u591a\u7ee7\u627f","text":"<p>\u7ee7\u627f\u6392\u5e8f\u95ee\u9898\u6ca1\u6709\u6b63\u786e\u7684\u89e3\u51b3\u65b9\u6848\uff0c\u56e0\u4e3a\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u6211\u4eec\u53ef\u80fd\u66f4\u613f\u610f\u5c06\u67d0\u4e9b\u7ee7\u627f\u7c7b\u7f6e\u4e8e\u5176\u4ed6\u7c7b\u4e4b\u4e0a\u3002\u4f46\u662f\uff0c\u4efb\u4f55\u652f\u6301\u591a\u91cd\u7ee7\u627f\u7684\u7f16\u7a0b\u8bed\u8a00\u90fd\u5fc5\u987b\u4ee5\u4e00\u81f4\u7684\u65b9\u5f0f\u9009\u62e9\u67d0\u4e9b\u6392\u5e8f\uff0c\u4ee5\u4fbf\u8be5\u8bed\u8a00\u7684\u7528\u6237\u53ef\u4ee5\u9884\u6d4b\u5176\u7a0b\u5e8f\u7684\u884c\u4e3a\u3002</p> <p>\u8fdb\u4e00\u6b65\u9605\u8bfb\u3002Python \u4f7f\u7528\u79f0\u4e3a C3 \u65b9\u6cd5\u89e3\u6790\u6392\u5e8f\u7684\u9012\u5f52\u7b97\u6cd5\u89e3\u6790\u6b64\u540d\u79f0\u3002\u53ef\u4ee5\u5728\u6240\u6709\u7c7b\u4e0a\u4f7f\u7528\u00a0<code>mro</code>\u00a0\u65b9\u6cd5\u67e5\u8be2\u4efb\u4f55\u7c7b\u7684\u65b9\u6cd5\u89e3\u6790\u987a\u5e8f\u3002</p> Python<pre><code>&gt;&gt;&gt; [c.__name__ for c in AsSeenOnTVAccount.mro()]\n['AsSeenOnTVAccount', 'CheckingAccount', 'SavingsAccount', 'Account', 'object']\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#258","title":"2.5.8 \u5bf9\u8c61\u7684\u4f5c\u7528","text":"<p>\u53e6\u4e00\u65b9\u9762\uff0c\u7c7b\u53ef\u80fd\u4e0d\u662f\u5b9e\u73b0\u67d0\u4e9b\u62bd\u8c61\u7684\u6700\u4f73\u673a\u5236\u3002\u51fd\u6570\u5f0f\u62bd\u8c61\u63d0\u4f9b\u4e86\u4e00\u4e2a\u66f4\u81ea\u7136\u7684\u9690\u55bb\u6765\u8868\u793a\u8f93\u5165\u548c\u8f93\u51fa\u4e4b\u95f4\u7684\u5173\u7cfb\u3002\u6211\u4eec\u4e0d\u5e94\u8be5\u89c9\u5f97\u5fc5\u987b\u5c06\u7a0b\u5e8f\u4e2d\u7684\u6bcf\u4e00\u70b9\u903b\u8f91\u90fd\u585e\u8fdb\u4e00\u4e2a\u7c7b\u4e2d\uff0c\u5c24\u5176\u662f\u5728\u5b9a\u4e49\u72ec\u7acb\u51fd\u6570\u6765\u64cd\u4f5c\u6570\u636e\u66f4\u81ea\u7136\u7684\u60c5\u51b5\u4e0b\u3002\u51fd\u6570\u8fd8\u53ef\u4ee5\u5f3a\u5236\u5b9e\u73b0\u5173\u6ce8\u70b9\u7684\u5206\u79bb\u3002\u6362\u53e5\u8bdd\u8bf4\uff0c\u51fd\u6570\u5f0f\u7f16\u7a0b\u63d0\u4f9b\u4e86\u53e6\u4e00\u79cd\u6709\u6548\u5730\u7ec4\u7ec7\u7a0b\u5e8f\u903b\u8f91\u7684\u65b9\u6cd5\uff0c\u4f7f\u5f97\u7a0b\u5e8f\u5458\u80fd\u591f\u66f4\u597d\u5730\u5904\u7406\u548c\u7ef4\u62a4\u7a0b\u5e8f\u3002\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u4f7f\u7528\u51fd\u6570\u5f0f\u7f16\u7a0b\u65b9\u6cd5\u53ef\u80fd\u6bd4\u4f7f\u7528\u9762\u5411\u5bf9\u8c61\u7f16\u7a0b\u66f4\u81ea\u7136\u548c\u6709\u6548\u3002</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#26","title":"2.6 \u5b9e\u73b0\u7c7b\u548c\u5bf9\u8c61","text":"<p>object-oriented programming paradigm \u5373\u4f7f\u5728\u6ca1\u6709\u5185\u7f6e\u5bf9\u8c61\u7cfb\u7edf\u7684\u7f16\u7a0b\u8bed\u8a00\u4e2d\uff0c\u7a0b\u5e8f\u4e5f\u53ef\u4ee5\u662f\u9762\u5411\u5bf9\u8c61\u7684\u3002 \u653e\u5f03\u70b9\u8868\u793a\u6cd5-&gt;\u8c03\u5ea6\u5b57\u5178\u5b9e\u73b0\u6d88\u606f\u4f20\u9012</p>"},{"location":"CS_Basic/CS61A/Composing_Programs/#261","title":"2.6.1 \u5b9e\u4f8b","text":"Python<pre><code>&gt;&gt;&gt; def make_instance(cls):\n    \"\"\"Return a new object instance, which is a dispatch dictionary.\"\"\"\n    def get_value(name):\n        if name in attributes:\n            return attributes[name]\n        else:\n            value = cls['get'](name)\n            return bind_method(value, instance)\n    def set_value(name, value):\n        attributes[name] = value\n    attributes = {}\n    instance = {'get': get_value, 'set': set_value}\n    return instance\n\n&gt;&gt;&gt; def bind_method(value, instance):\n    \"\"\"Return a bound method if value is callable, or value otherwise.\"\"\"\n    if callable(value):\n        def method(*args):\n            return value(instance, *args)\n        return method\n    else:\n        return value\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#262","title":"2.6.2 \u7c7b","text":"Python<pre><code>&gt;&gt;&gt; def make_class(attributes, base_class=None):\n    \"\"\"Return a new class, which is a dispatch dictionary.\"\"\"\n    def get_value(name):\n        if name in attributes:\n            return attributes[name]\n        elif base_class is not None:\n            return base_class['get'](name)\n    def set_value(name, value):\n        attributes[name] = value\n    def new(*args):\n        return init_instance(cls, *args)\n    cls = {'get': get_value, 'set': set_value, 'new': new}\n    return cls\n\n&gt;&gt;&gt; def init_instance(cls, *args):\n    \"\"\"Return a new object with type cls, initialized with args.\"\"\"\n    instance = make_instance(cls)\n    init = cls['get']('__init__')\n    if init:\n        init(instance, *args)\n    return instance\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#3","title":"3 \u8ba1\u7b97\u673a\u7a0b\u5e8f\u7684\u89e3\u91ca","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#31","title":"3.1 \u5f15\u8a00","text":"<p>\u8bb8\u591a\u89e3\u91ca\u5668\u90fd\u6709\u4e00\u4e2a\u4f18\u96c5\u7684\u7ed3\u6784\uff0c\u5373\u4e24\u4e2a\u4e92\u9012\u5f52\u51fd\u6570\uff1a</p> <ul> <li>\u7b2c\u4e00\u4e2a\u51fd\u6570\u6c42\u89e3\u73af\u5883\u4e2d\u7684\u8868\u8fbe\u5f0f</li> <li>\u7b2c\u4e8c\u4e2a\u51fd\u6570\u5c06\u51fd\u6570\u5e94\u7528\u4e8e\u53c2\u6570</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#32","title":"3.2 \u51fd\u6570\u5f0f\u7f16\u7a0b","text":"<ul> <li>\u53ea\u4f7f\u7528\u8868\u8fbe\u5f0f\u800c\u4e0d\u4f7f\u7528\u8bed\u53e5\uff0c\u7279\u522b\u9002\u5408\u7b26\u53f7\u8ba1\u7b97</li> <li>\u5904\u7406\u7684\u6570\u636e\u90fd\u662f\u4e0d\u53ef\u53d8\u7684\uff08immutable\uff09</li> </ul> Python<pre><code>(if &lt;predicate&gt; &lt;consequent&gt; &lt;alternative&gt;)\n\n(define pi 3.14)\n(* pi 3.14)\n\n(define (&lt;name&gt; &lt;formal parameters&gt;) &lt;body&gt;)\neg1:\n    (define (average x y)\n      (/ (+ x y) 2))\neg2:\n    (define (abs x)\n    (if (&lt; x 0)\n        (- x)\n        x))\neg3:\n    (define (sqrt x)\n      (define (good-enough? guess)\n        (&lt; (abs (- (square guess) x)) 0.001))\n      (define (improve guess)\n        (average guess (/ x guess)))\n      (define (sqrt-iter guess)\n        (if (good-enough? guess)\n            guess\n            (sqrt-iter (improve guess))))\n      (sqrt-iter 1.0))\n    (sqrt 9)\n\n(lambda (&lt;formal-parameters&gt;) &lt;body&gt;)\neg1:\n    (define (plus4 x) (+ x 4))\n    (define plus4 (lambda (x) (+ x 4))) # both are OK\n\n# \u7279\u6b8a\u7684\u503c\u00a0nil\u00a0\u6216\u00a0'()\u00a0\u8868\u793a\u7a7a\u5217\u8868\n\n# null? \u8c13\u8bcd\u7684\u4f7f\u7528:\n    (define (length items)\n      (if (null? items)\n          0\n          (+ 1 (length (cdr items)))))\n    (define (getitem items n)\n      (if (= n 0)\n          (car items)\n          (getitem (cdr items) (- n 1))))\n    (define squares (list 1 4 9 16 25))\n\n    (length squares)\n\n    (getitem squares 3)\n\n# \u4efb\u4f55\u4e0d\u88ab\u6c42\u503c\u7684\u8868\u8fbe\u5f0f\u90fd\u88ab\u79f0\u4e3a\u88ab\u5f15\u7528\n    (list 'define 'list)\n\n# turtle\u4f7f\u7528+\u9012\u5f52\u753b\u56fe\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#33","title":"3.3 \u5f02\u5e38","text":"<ul> <li>raise</li> <li>assert</li> </ul> Python<pre><code>&gt;&gt;&gt; raise Exception(' An error occurred')\nTraceback (most recent call last):\n    File \"&lt;stdin&gt;\", line 1, in &lt;module&gt;\nException: an error occurred\n</code></pre> <ul> <li>raising an exception<ul> <li>read-eval-print-loop \u5373 REPL</li> <li>stack backtrace</li> </ul> </li> <li>handling exceptions</li> </ul> Python<pre><code>try\n    &lt;try suite&gt;\nexcept &lt;exception class&gt; as &lt;name&gt;:\n    &lt;except suite&gt;\n</code></pre> <p>\u5f02\u5e38\u662f\u4e2a\u7c7b\uff0c\u53ef\u4ee5\u6709\u989d\u5916\u7684\u5c5e\u6027\uff0c\u53ef\u4ee5\u907f\u514d\u62a5\u9519\uff0c\u8ba9\u7a0b\u5e8f\u7ed9\u51fa\u4e00\u4e2a\u8f83\u4e3a\u7c97\u7cd9\u7684\u503c\uff1a</p> Python<pre><code>&gt;&gt;&gt; class IterImproveError(Exception):\n\u00a0\u00a0\u00a0     def __init__(self, last_guess):\n\u00a0\u00a0\u00a0         self.last_guess = last_guess\n&gt;&gt;&gt; def improve(update, done, guess=1, max_updates=1000):\n\u00a0\u00a0\u00a0     k = 0\n\u00a0\u00a0\u00a0     try:\n\u00a0\u00a0\u00a0         while not done(guess) and k &lt; max_updates:\n\u00a0\u00a0\u00a0             guess = update(guess)\n\u00a0\u00a0\u00a0             k = k + 1\n\u00a0\u00a0\u00a0         return guess\n\u00a0\u00a0\u00a0     except ValueError:\n\u00a0\u00a0\u00a0         raise IterImproveError(guess)\n&gt;&gt;&gt; def find_zero(f, guess=1):\n\u00a0\u00a0\u00a0     def done(x):\n\u00a0\u00a0\u00a0         return f(x) == 0\n\u00a0\u00a0\u00a0     try:\n\u00a0\u00a0\u00a0         return improve(newton_update(f), done, guess)\n\u00a0\u00a0\u00a0     except IterImproveError as e:\n\u00a0\u00a0\u00a0         return e.last_guess\n&gt;&gt;&gt; from math import sqrt\n&gt;&gt;&gt; find_zero(lambda x: 2*x*x + sqrt(x))\n-0.030211203830201594\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#34","title":"3.4 \u7ec4\u5408\u8bed\u8a00\u7684\u89e3\u91ca\u5668","text":"<ul> <li>\u8ba1\u7b97\u5668\u8bed\u8a00 -&gt; \u7b80\u7565\u89e3\u91ca\u5668</li> <li>scheme \u5bf9<ul> <li>pair</li> <li>nil</li> </ul> </li> <li>\u8868\u8fbe\u5f0f\u6811</li> <li>\u89e3\u6790\u8868\u8fbe\u5f0f\u6811<ul> <li>\u8bcd\u6cd5\u5206\u6790\u5668\uff08lexical analyzer\uff09/ \u5206\u8bcd\u5668\uff08tokenizer\uff09<ul> <li>\u6807\u8bb0\uff08token\uff09</li> </ul> </li> <li>\u8bed\u6cd5\u5206\u6790\u5668\uff08syntactic analyzer\uff09<ul> <li>\u6570\u5b57\u548c\u8c03\u7528\u8868\u8fbe\u5f0f \u8bb2\u4e86\u4e00\u4e0b\u8ba1\u7b97\u5668\u89e3\u91ca\u5668\u4ea4\u4e92\u5f0f\u9875\u9762\u7684\u8868\u8fbe\u5f0f\u5982\u4f55\u8ba1\u7b97\u548c\u5f02\u5e38\u5904\u7406</li> </ul> </li> </ul> </li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#35","title":"3.5 \u62bd\u8c61\u8bed\u8a00\u7684\u89e3\u91ca\u5668","text":"<ul> <li>\u6269\u5c55 scheme_reader \u89e3\u6790\u70b9\u5217\u8868\u548c\u5f15\u53f7</li> <li>\u6c42\u503c\uff08Evaluation\uff09</li> <li>\u51fd\u6570\u5e94\u7528\uff08Procedure application\uff09</li> <li>\u6c42\u503c/\u5e94\u7528\u9012\u5f52</li> <li>\u6570\u636e\u5373\u7a0b\u5e8f</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#4","title":"4 \u6570\u636e\u5904\u7406","text":""},{"location":"CS_Basic/CS61A/Composing_Programs/#41","title":"4.1 \u5f15\u8a00","text":"<ul> <li>pipelines</li> <li>sequence interface</li> <li>unbounded</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#42","title":"4.2 \u9690\u5f0f\u5e8f\u5217","text":"<ul> <li>\u6211\u4eec\u53ea\u5728\u6709\u9700\u8981\u7684\u65f6\u5019\u624d\u8ba1\u7b97\u5143\u7d20</li> <li>Lazy computation</li> </ul>"},{"location":"CS_Basic/CS61A/Composing_Programs/#421","title":"4.2.1 \u8fed\u4ee3\u5668","text":"<p>\u4e24\u4e2a\u7ec4\u4ef6:</p> <ul> <li>\u68c0\u7d22\u4e0b\u4e00\u4e2a\u5143\u7d20\u7684\u673a\u5236</li> <li>\u5230\u8fbe\u5e8f\u5217\u672b\u5c3e\u5e76\u4e14\u6ca1\u6709\u5269\u4f59\u5143\u7d20\uff0c\u53d1\u51fa\u4fe1\u53f7\u7684\u673a\u5236</li> </ul> Python<pre><code>&gt;&gt;&gt; next(iterator)\n7\n&gt;&gt;&gt; next(iterator)\nTraceback (most recent call las):\n  File \"&lt;stdin&gt;\", line 1, in &lt;module&gt;\nStopIteration\n\n&gt;&gt;&gt; try:\n        next(iterator)\n    except StopIteration:\n        print('No more values')\nNo more values\n</code></pre>"},{"location":"CS_Basic/CS61A/Composing_Programs/#422","title":"4.2.2 \u53ef\u8fed\u4ee3\u6027","text":"<p>iterable value \u53ef\u8fed\u4ee3\u5bf9\u8c61:</p> <ul> <li>\u5e8f\u5217\u503c: string &amp; tuples</li> <li>\u5bb9\u5668: sets &amp; Dictionaries</li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/","title":"\u8ba1\u7b97\u673a\u7ec4\u6210\u4e0e\u8bbe\u8ba1\u786c\u4ef6\u8f6f\u4ef6\u63a5\u53e3","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#_1","title":"\u8ba1\u7b97\u673a\u7ec4\u6210\u4e0e\u8bbe\u8ba1\u786c\u4ef6\u8f6f\u4ef6\u63a5\u53e3","text":"<p> \u7ea6 2978 \u4e2a\u5b57  13 \u884c\u4ee3\u7801  4 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 15 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#1","title":"1 \u8ba1\u7b97\u673a\u62bd\u8c61\u53ca\u76f8\u5173\u6280\u672f","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#2","title":"2 \u6307\u4ee4: \u8ba1\u7b97\u673a\u7684\u8bed\u8a00","text":""},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#21","title":"2.1 \u5f15\u8a00","text":"<p>\u8bbe\u8ba1\u539f\u5219:</p> <ul> <li>\u7b80\u5355\u6e90\u4e8e\u89c4\u6574</li> <li>\u66f4\u5c11\u5219\u66f4\u5feb</li> <li>\u4f18\u79c0\u7684\u8bbe\u8ba1\u9700\u8981\u9002\u5f53\u7684\u6298\u4e2d</li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#22","title":"2.2 \u8ba1\u7b97\u673a\u786c\u4ef6\u7684\u64cd\u4f5c","text":"<p>Java \u7f16\u8bd1\u5668: Just In Time \u7f16\u8bd1\u5668</p>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#23","title":"2.3 \u8ba1\u7b97\u673a\u786c\u4ef6\u7684\u64cd\u4f5c\u6570","text":"<ul> <li>\u5bc4\u5b58\u5668<ul> <li>\u5927\u5c0f\u4e3a64 bits \u53cc\u5b57</li> <li>\u6570\u91cf\u6709\u9650\u901a\u5e38\u4e3a 32 \u4e2a</li> <li>x +\u5bc4\u5b58\u5668\u7f16\u53f7</li> </ul> </li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#231","title":"2.3.1 \u5b58\u50a8\u5668\u64cd\u4f5c\u6570","text":"<p>\u5728\u5185\u5b58\u548c\u5bc4\u5b58\u5668\u4e4b\u95f4\u4f20\u8f93\u6307\u4ee4:\u6570\u636e\u4f20\u8f93\u6307\u4ee4 \u6307\u4ee4\u63d0\u4f9b\u5185\u5b58\u5730\u5740 \u8f7d\u5165\u6307\u4ee4\uff08load\uff09:ld</p> Text Only<pre><code>Ld x9, 8(x22)\n</code></pre> <p>X 22 \u57fa\u5740\u5bc4\u5b58\u5668 8 \u504f\u79fb\u91cf \u5b57\u8282\u5730\u5740: 0 8 16 24 RICS- V \u662f\u5c0f\u7aef\u7f16\u5740: \u53ea\u5728\u4ee5\u53cc\u5b57\u5f62\u5f0f\u548c\u516b\u4e2a\u5355\u72ec\u5b57\u8282\u8bbf\u95ee\u76f8\u540c\u6570\u636e\u65f6\u4f1a\u6709\u5f71\u54cd ^da8be4</p> <p>\u5b58\u50a8\u6307\u4ee4\uff08store\uff09\u5b58\u50a8\u53cc\u5b57</p> Text Only<pre><code>sd x9, 96(x22)\n</code></pre> <ul> <li>\u5bf9\u9f50\u9650\u5236:<ul> <li>\u5b57\u7684\u8d77\u59cb\u5730\u5740\u662f 4 \u7684\u500d\u6570</li> <li>\u53cc\u5b57\u7684\u8d77\u59cb\u5730\u5740\u662f 8 \u7684\u500d\u6570</li> <li>\u4f46\u662f risc-v and Intel x 86 \u6ca1\u6709</li> <li>MIPS \u6709 Gibibyte (\\(\\displaystyle 2^{30}\\)) and tebibyte (\\(\\displaystyle 2^{40}\\)) \u5982\u679c\u53d8\u91cf\u6bd4\u5bc4\u5b58\u5668\u6570\u91cf\u66f4\u591a\uff0c\u90a3\u4e48\u4f1a\u628a\u4e00\u4e9b\u653e\u5230\u5185\u5b58\uff0c\u5373\u5bc4\u5b58\u5668\u6362\u51fa\u3002</li> </ul> </li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#232","title":"2.3.2 \u5e38\u6570\u6216\u7acb\u5373\u6570\u64cd\u4f5c\u6570","text":"Text Only<pre><code>ld x9, AddConstant4(x3)\nAdd x22, x22, x9\n\n# Equals to \n\naddi x22, x22, 4 # x22 = x22 + 4\n</code></pre> <p>\u5e38\u6570\u79f0\u4e3a\u7b97\u6570\u6307\u4ee4\u64cd\u4f5c\u6570 X0 \u53ef\u4ee5\u7528\u6765\u8868\u793a 0 \u5176\u5b9e\u8fd8\u6709 RV 32 \u57fa\u5740\u5bc4\u5b58\u5668\u4e5f\u88ab\u79f0\u4e3a\u4e0b\u6807\u5bc4\u5b58\u5668 \u6211\u4eec\u5047\u8bbe\u6307\u4ee4\u90fd\u662f 64 \u4f4d</p>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#24","title":"2.4 \u6709\u7b26\u53f7\u6570\u4e0e\u65e0\u7b26\u53f7\u6570","text":"<ul> <li>Binary digit Or bit</li> <li>Least significant bit </li> <li>Most significant bit</li> <li>sign and magnitude</li> <li>\u8865\u7801\u8f6c\u5316:<ol> <li>\u62d3\u5c55\u7b26\u53f7\u4f4d</li> <li>\u53d6\u53cd</li> <li>\u52a0\u4e00</li> </ol> </li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#25","title":"2.5 \u8ba1\u7b97\u673a\u4e2d\u7684\u6307\u4ee4\u8868\u793a","text":"<ul> <li>\u5b57\u6bb5</li> <li>\u6307\u4ee4 32 \u4f4d\u957f</li> <li>\u6307\u4ee4\u7684\u6570\u5b57\u8868\u793a:\u673a\u5668\u8bed\u8a00</li> <li>\u6307\u4ee4\u5e8f\u5217: \u673a\u5668\u7801</li> <li>C \u548c java \u7528 0 xnnnn \u6765\u8868\u793a\u5341\u516d\u8fdb\u5236\u6570</li> <li>RISC-V:\uff08R\uff09<ul> <li>funct7 + rs 2 + rs 1 + funct 3 + rd + opcode</li> <li>rd: \u76ee\u7684\u64cd\u4f5c\u6570\u5bc4\u5b58\u5668</li> <li>rs 1: \u7b2c\u4e00\u4e2a\u539f\u64cd\u4f5c\u6570\u5bc4\u5b58\u5668</li> <li>rs 2: \u7b2c\u4e8c\u4e2a\u539f\u64cd\u4f5c\u6570\u5bc4\u5b58\u5668</li> <li>funct 7 (3): \u64cd\u4f5c\u7801\u5b57\u6bb5</li> </ul> </li> <li>\u5bf9\u4e0d\u540c\u7684\u6307\u4ee4\u4f7f\u7528\u4e0d\u540c\u7684\u6307\u4ee4\u683c\u5f0f</li> <li>I<ul> <li>immediate + rs 1 + funct 3 + rd + opcode</li> <li>\u8d85\u8fc7 32 \u4e2a\u5bc4\u5b58\u5668\u7684\u8bdd\uff0crd and rs 1 \u90fd\u8981\u589e\u52a0\u989d\u5916\u7684\u4e00\u4f4d</li> <li>ld</li> </ul> </li> <li>S<ul> <li>immediate + rs 2 + rs 1 + funct 3 + immediate + opcode</li> </ul> </li> <li>Reg \u8868\u793a 0 \u5230 31 \u4e4b\u95f4\u7684\u5bc4\u5b58\u5668\u7f16\u53f7</li> <li>\u6ca1\u6709 subi \u56e0\u4e3a\u53ef\u4ee5\u901a\u8fc7\u52a0\u8d1f\u6570\u6765\u5b9e\u73b0</li> <li>\u8ba1\u7b97\u673a\u6784\u5efa\u57fa\u4e8e\u4e24\u4e2a\u5173\u952e\u539f\u5219:<ul> <li>\u6307\u4ee4\u7531\u6570\u5b57\u5f62\u5f0f\u8868\u793a</li> <li>\u7a0b\u5e8f\u548c\u6570\u636e\u4e00\u6837\u4fdd\u5b58\u5728\u5b58\u50a8\u5668\u4e2d\u8fdb\u884c\u8bfb\u5199</li> </ul> </li> <li>\u7a0b\u5e8f\u4f1a\u4ee5\u4e8c\u8fdb\u5236\u6570\u636e\u6587\u4ef6\u7684\u5f62\u5f0f\u6765\u53d1\u5e03<ul> <li>\u4e8c\u8fdb\u5236\u517c\u5bb9\u6027\u8ba9\u884c\u4e1a\u56f4\u7ed5\u5c11\u6570\u51e0\u4e2a\u6307\u4ee4\u7cfb\u7edf\u7ed3\u6784\u5f62\u6210\u8054\u76df</li> </ul> </li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#26","title":"2.6 \u903b\u8f91\u64cd\u4f5c","text":"<ul> <li>sll, slli</li> <li>srl, srli</li> <li>sra, srai</li> <li>and, andi </li> <li>or, ori </li> <li>xor, xori</li> <li>not</li> <li>\u4f4d\u79fb\u6307\u4ee4\u7528\u7684 I \u578b\u683c\u5f0f:<ul> <li>\u4f46\u5b83\u7684\u683c\u5f0f\u6709\u53d8\u5316:<ul> <li>funct 6 + immediate + rs 1 + funct 3 + rd + opcode</li> </ul> </li> </ul> </li> <li>\u7b97\u6570\u53f3\u79fb\u7528\u7684\u662f\u7b26\u53f7\u4f4d</li> <li>AND \u5b9e\u73b0\u4e86\u63a9\u7801</li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#27","title":"2.7 \u7528\u4e8e\u51b3\u7b56\u7684\u6307\u4ee4","text":"<ul> <li>beq</li> <li>bne</li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#271","title":"2.7.1 \u5faa\u73af","text":"C<pre><code>while (save[i] == k) \n    i += 1;\n</code></pre> <p>I -&gt; x 22 K -&gt; x 24 Save -&gt; x 25</p> Text Only<pre><code>loop: slli, x10, x22, 3\nAdd x10, x10, x25\nLd x9, 0(x10)\nBen x9, x24, Exit\nAddi x22, x22, l\nBeq x0, x0, loop\nExit:\n</code></pre> <p>\u57fa\u672c\u5757: </p> <ul> <li>\u9664\u4e86\u5728\u6307\u4ee4\u5e8f\u5217\u7684\u7ed3\u5c3e\uff0c\u5e8f\u5217\u4e2d\u6ca1\u6709\u5206\u652f\u3002</li> <li>\u9664\u4e86\u5728\u5e8f\u5217\u8d77\u59cb\u5904\uff0c\u5e8f\u5217\u4e2d\u6ca1\u6709\u5206\u652f\u76ee\u6807\u548c\u5206\u652f\u6807\u7b7e\u3002</li> <li>\u5bf9\u4e8e\u7b26\u53f7:<ul> <li>RISC-V \u7528\u4e0d\u540c\u7684\u6307\u4ee4</li> <li>MIPS \u8bbe\u7f6e\u4e34\u65f6\u5bc4\u5b58\u5668</li> <li>ARM \u6761\u4ef6\u4ee3\u7801\u6216\u6807\u5fd7\u4f4d</li> </ul> </li> <li>\u4e0d\u8fc7\u4e5f\u4f1a\u6709\u7f3a\u70b9: \u8fc7\u591a\u7684\u6307\u4ee4\u8bbe\u7f6e\u6761\u4ef6\u4ee3\u7801\uff0c\u4f1a\u8ba9\u6d41\u6c34\u7ebf\u6267\u884c\u56f0\u96be</li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#272","title":"2.7.2 \u8fb9\u754c\u68c0\u67e5\u7684\u7b80\u4fbf\u65b9\u6cd5","text":"<p>\u5c06\u7b26\u53f7\u6570\u5f53\u4f5c\u65e0\u7b26\u53f7\u6570\u5904\u7406</p>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#273-caseswitch","title":"2.7.3 Case/switch \u8bed\u53e5","text":"<ul> <li>\u7f16\u7801\u5f62\u6210\u6307\u4ee4\u5e8f\u5217\u7684\u5730\u5740\u8868: \u5206\u652f\u5730\u5740\u8868/\u5206\u652f\u8868</li> <li>\u95f4\u63a5\u8df3\u8f6c\u6307\u4ee4 jalr</li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#28","title":"2.8 \u8ba1\u7b97\u673a\u786c\u4ef6\u5bf9\u8fc7\u7a0b\u7684\u652f\u6301","text":"<ul> <li>Procedure</li> <li>\u6267\u884c\u8fc7\u7a0b\u7684\u516d\u4e2a\u6b65\u9aa4:<ul> <li>\u5c06\u53c2\u6570\u653e\u5728\u8fc7\u7a0b\u53ef\u4ee5\u8bbf\u95ee\u5230\u7684\u4f4d\u7f6e</li> <li>\u5c06\u63a7\u5236\u8f6c\u4ea4\u7ed9\u8fc7\u7a0b</li> <li>\u83b7\u53d6\u8fc7\u7a0b\u6240\u9700\u7684\u5b58\u50a8\u8d44\u6e90</li> <li>\u6267\u884c\u6240\u9700\u7684\u4efb\u52a1</li> <li>\u5c06\u7ed3\u679c\u503c\u653e\u5728\u8c03\u7528\u7a0b\u5e8f\u53ef\u4ee5\u8bbf\u95ee\u5230\u7684\u4f4d\u7f6e</li> <li>\u5c06\u63a7\u5236\u8fd4\u56de\u5230\u521d\u59cb\u70b9\uff0c\u56e0\u4e3a\u8fc7\u7a0b\u53ef\u4ee5\u4ece\u7a0b\u5e8f\u4e2d\u7684\u591a\u4e2a\u70b9\u8c03\u7528</li> </ul> </li> <li>x 10~x 17: \u53c2\u6570\u5bc4\u5b58\u5668\uff0c\u7528\u4e8e\u4f20\u9012\u53c2\u6570\u6216\u8fd4\u56de\u503c</li> <li>x 1: \u8fd4\u56de\u5730\u5740\u5bc4\u5b58\u5668\uff0c\u7528\u4e8e\u8fd4\u56de\u5230\u8d77\u59cb\u70b9</li> <li>jal \u8df3\u8f6c-\u94fe\u63a5\u6307\u4ee4 </li> </ul> Text Only<pre><code>Jal x1, ProcedureAddress\nJalr x0, 0(x1)\n</code></pre> <p>\u8c03\u7528\u8005\u5c06\u53c2\u6570\u503c\u653e\u5165 x 10~x 17 \u8fc7\u7a0b\u662f\u88ab\u8c03\u7528\u8005 Program counter:PC \u6307\u4ee4\u5730\u5740\u5bc4\u5b58\u5668</p> Text Only<pre><code>jal x0, Label // unconditionally branch to Label\n</code></pre>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#281","title":"2.8.1 \u4f7f\u7528\u66f4\u591a\u7684\u5bc4\u5b58\u5668","text":"<ul> <li>Stack</li> <li>Stack pointer x2:sp</li> <li>\u538b\u6808\u5f39\u6808</li> </ul> Text Only<pre><code>leaf_example:\nAddi sp, sp, -14\nSd x5, 16(sp)\nSd x6, 8(sp)\nSd x20, 0(sp)\nAdd x5, x10, x11\nAdd x6, x12, x13\nSub x20, x5, x6\nAddi x10, x20, 0\nLd x20, 0(sp)\nLd x6, 8(sp)\nLd x5, 16(sp)\nAddi sp, sp, 24\nJalr x0, 0(x1)\n</code></pre> <ul> <li>X 5~x 7, x 28~x 31: \u4e34\u65f6\u5bc4\u5b58\u5668</li> <li>x 8~x 9, x 18~x 27: \u4fdd\u5b58\u5bc4\u5b58\u5668</li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#282","title":"2.8.2 \u5d4c\u5957\u8fc7\u7a0b","text":"<ul> <li>Leaf procedure </li> <li>\u5c06\u6240\u6709\u5fc5\u987b\u4fdd\u5b58\u7684\u5bc4\u5b58\u5668\u538b\u6808\uff0c\u9632\u6b62\u51b2\u7a81</li> </ul> C<pre><code>long long int fact (long long int n) {\n    if (n &lt; 1) return (1);\n        else return (n * fact(n - 1))\n}\n</code></pre> <p>n -&gt; x 10</p> Text Only<pre><code>fact:\n    addi sp, sp, -16\n    Sd x1, 8(sp)\n    Sd x10, 0(sp)\n\n    Addi x5, x10, -1\n    Bge x5, x0, L1\n\n    Addi x10, x0, 1\n    Addi sp, sp, 16\n    Jalr x0, 0(x1)\n\nL1: addi x10, x10, -1\n    Jal x1, fact\n\naddi x6, x10, 0\nLd x10, 0(sp)\nLd x1, 8(sp)\nAddi sp, sp, 16\nMul x10, x10, x6\nJalr x0, 0(x1)\n</code></pre> <ul> <li>\u4e00\u4e9b\u7f16\u8bd1\u5668\u4fdd\u7559\u4e00\u4e2a\u5bc4\u5b58\u5668 x 3 \u7528\u4f5c\u5168\u5c40\u6307\u9488 gp </li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#283","title":"2.8.3 \u5728\u6808\u4e2d\u4f4d\u65b0\u6570\u636e\u5206\u914d\u7a7a\u95f4","text":"<p>\u6808\u4e5f\u7528\u4e8e\u5b58\u50a8\u8fc7\u7a0b\u7684\u5c40\u90e8\u53d8\u91cf \u8fc7\u7a0b\u5e27/\u6d3b\u52a8\u8bb0\u5f55</p> <p>\u6ca1\u770b\u61c2</p>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#284","title":"2.8.4 \u5728\u5806\u4e2d\u4e3a\u65b0\u6570\u636e\u5206\u914d\u7a7a\u95f4","text":"<p>Static data segment text segment \u50cf\u94fe\u8868\u7b49\u6570\u636e\u7ed3\u6784\u5f80\u5f80\u4f1a\u968f\u751f\u547d\u5468\u671f\u589e\u957f\u548c\u7f29\u77ed\uff0c\u6240\u4ee5\u4f1a\u628a\u4ed6\u4eec\u5b58\u5728\u5806\u91cc (heap)</p> <ul> <li>malloc ()</li> <li>free () \u8be6\u7ec6\u9610\u8ff0\u6ca1\u770b</li> </ul>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#29","title":"2.9 \u4eba\u673a\u4ea4\u4e92","text":"<p>ASCII: american standard code for information interchange </p> <p>\u52a0\u8f7d\u65e0\u7b26\u53f7\u5b57\u8282 (lbu) \u5b58\u50a8\u5b57\u8282 (sb)</p> Text Only<pre><code>lbu x12, 0(x10)\nsb x12, 0(x11)\n</code></pre> <p>\u5b57\u7b26\u4e32\u7684\u8868\u793a\u6709\u4e09\u79cd\u9009\u62e9:</p> <ol> <li>\u7b2c\u4e00\u4e2a\u4f4d\u7f6e\u4fdd\u7559\u6765\u7ed9\u51fa\u5b57\u7b26\u4e32\u7684\u957f\u5ea6</li> <li>\u7528\u989d\u5916\u7684\u53d8\u91cf\u6765\u5b58\u50a8\u957f\u5ea6\uff08\u5982\u7ed3\u6784\u4f53\uff09</li> <li>\u5b57\u7b26\u4e32\u7684\u6700\u540e\u4e00\u4e2a\u4f4d\u7f6e\u7528\u5b57\u7b26\u6807\u8bb0\u7ed3\u5c3e \u5176\u4e2d C \u8bed\u8a00\u7528\u7b2c\u4e09\u79cd\uff0c\u4f7f\u7528\u503c\u4e3a 0 \u7684\u5b57\u8282\u6765\u7ec8\u6b62\u5b57\u7b26\u4e32\uff08null in ASCII\uff09</li> </ol> C<pre><code>void strcpy (char x[], char y[])\n{\n    size_t i;\n    i = 0;\n    while ((x[i] = y[i]) != '\\0')\n        i += 1;\n}\n</code></pre> <p>x -&gt; x 10 y -&gt; x 11 i -&gt; x 19</p> Text Only<pre><code>strcpy:\n    addi sp, sp, -8\n    sd x19, 0(sp)\n    add x19, x0, x0\nL1: add x5, x19, x11\n    lbu x6, 0(x5)\n    add x7, x19, x10\n    sb x6, 0(x7)\n    beq x6, x0, L2\n    addi x19, x19, 1\n    jal x0, L1\nL2: ld x19, 0(sp)\n    addi sp, sp, 8\n    jalr x0, 0(x1)\n</code></pre> <p>load half unsigned \u52a0\u8f7d\u534a\u5b57: lh lhu sh </p>"},{"location":"CS_Basic/CS61C/%E8%AE%A1%E7%AE%97%E6%9C%BA%E7%BB%84%E6%88%90%E4%B8%8E%E8%AE%BE%E8%AE%A1%E7%A1%AC%E4%BB%B6%E8%BD%AF%E4%BB%B6%E6%8E%A5%E5%8F%A3/#210-risc-v","title":"2.10 \u5bf9\u5927\u7acb\u5373\u6570\u7684 RISC-V 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<li>ssh\u4e2d\u5982\u679c\u8bbe\u7f6e\u4e86password\u8ba4\u8bc1\u4e14\u8bbe\u7f6e\u5f31\u53e3\u4ee4\uff0c\u5c06\u4f1a\u5bfc\u81f4\u670d\u52a1\u5668\u88ab\u672a\u7ecf\u6388\u6743\u767b\u5f55\uff0c\u4e14\u653b\u51fb\u8005\u53ef\u4ee5\u8fdb\u884c\u4e0e\u4f60\u540c\u6743\u9650\u7684\u4efb\u610f\u64cd\u4f5c</li> <li>\u65e0\u7ebf\u5c40\u57df\u7f51\u4e2d\u5982\u679c\u8bbe\u7f6e\u4e86\u5f31\u53e3\u4ee4\u88ab\u731c\u6d4b\u6210\u529f\u540e\uff0c\u653b\u51fb\u8005\u5c06\u53ef\u4ee5\u8fdb\u5165\u5c40\u57df\u7f51\u4e2d\u5bf9\u5c40\u57df\u7f51\u5176\u4ed6\u8bbe\u5907\u8fdb\u884c\u653b\u51fb</li> <li>\u9632\u8303\u65b9\u5f0f</li> <li>\u91c7\u7528\u5176\u4ed6\u66f4\u4e3a\u5b89\u5168\u7684\u8eab\u4efd\u8ba4\u8bc1\u65b9\u6cd5\uff08\u5982ssh\u4e2d\u91c7\u7528publickey\u8ba4\u8bc1\uff09</li> <li>\u8bbe\u7f6e\u968f\u673a\u5b57\u7b26\u4e32\u4f5c\u4e3a\u5bc6\u7801\uff0c\u5e76\u4e14\u957f\u5ea6\u8d85\u8fc78\u4f4d</li> </ul> </li> </ol>"},{"location":"CS_Basic/Network/Security/#ip","title":"\u516c\u7f51 IP","text":"<ul> <li>\u6211\u4eec\u5e0c\u671b\u4ece\u4efb\u610f\u63a5\u5165\u4e92\u8054\u7f51\u7684\u5730\u65b9\u4f7f\u7528ssh\u8fde\u63a5\u5230\u670d\u52a1\u5668\uff0c\u4e00\u4e2a\u7b80\u5355\u7684\u65b9\u6cd5\u662f\u8ba9\u670d\u52a1\u5668\u62e5\u6709\u4e00\u4e2a\u516c\u7f51IP\u5e76\u8fd0\u884csshd\u670d\u52a1\u3002</li> <li>\u5e38\u89c1\u7684\u653b\u51fb\u65b9\u5f0f<ol> <li>\u626b\u63cf\u5f00\u653e\u7aef\u53e3\u4fe1\u606f\uff0c\u5e76\u786e\u5b9a\u7aef\u53e3\u4e0a\u8fd0\u884c\u7684\u670d\u52a1</li> <li>\u5bf9\u53ef\u80fd\u5b58\u5728\u7684\u670d\u52a1\u8fdb\u884c\u653b\u51fb\uff0c\u5c1d\u8bd5\u5229\u7528\u670d\u52a1\u7684\u6f0f\u6d1e\uff08\u5982\u5f31\u53e3\u4ee4\uff09\u83b7\u53d6\u670d\u52a1\u5668\u7684\u8bbf\u95ee\u6743\u9650</li> </ol> </li> <li>\u5e38\u89c1\u7684\u9632\u8303\u65b9\u5f0f<ul> <li>\u4f7f\u7528\u9632\u706b\u5899\u3002\u914d\u7f6e\u9632\u706b\u5899\u89c4\u5219\uff0c\u4ec5\u5141\u8bb8\u5fc5\u8981\u7684\u670d\u52a1\u548c\u7aef\u53e3\u5bf9\u5916\u5f00\u653e\u3002</li> <li>\u5ba1\u67e5\u5f00\u653e\u7684\u670d\u52a1\u7684\u5b89\u5168\u6027\u3002\u786e\u4fdd\u5f53\u524d\u4e3b\u673a\u5f00\u653e\u7684\u6240\u6709\u670d\u52a1\u5747\u662f\u5b89\u5168\u7684\u3002</li> </ul> </li> </ul>"},{"location":"CV/","title":"Computer Vision","text":""},{"location":"CV/#computer-vision","title":"Computer Vision","text":"<p>Abstract</p> <p>\u672c\u90e8\u5206\u5185\u5bb9\uff08\u9664\u7279\u522b\u58f0\u660e\u5916\uff09\u91c7\u7528 \u7f72\u540d-\u975e\u5546\u4e1a\u6027\u4f7f\u7528-\u4fdd\u6301\u4e00\u81f4 4.0 \u56fd\u9645 (CC BY-NC-SA 4.0) \u8bb8\u53ef\u534f\u8bae\u8fdb\u884c\u8bb8\u53ef\u3002</p> Notes          <ul> <li> \u89c6\u89c9 SLAM \u5341\u56db\u8bb2  14110  72  48 mins              1734024510 </li> </ul>"},{"location":"CV/SLAM14/","title":"\u89c6\u89c9SLAM\u5341\u56db\u8bb2","text":""},{"location":"CV/SLAM14/#slam","title":"\u89c6\u89c9SLAM\u5341\u56db\u8bb2","text":"<p> \u7ea6 14110 \u4e2a\u5b57  72 \u884c\u4ee3\u7801  20 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 71 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"CV/SLAM14/#1","title":"1 \u9884\u5907\u77e5\u8bc6","text":""},{"location":"CV/SLAM14/#11","title":"1.1 \u672c\u4e66\u8bb2\u4ec0\u4e48","text":"<p>simultaneous localization and mapping</p> <ul> <li>\u5b9a\u4f4d</li> <li>\u5730\u56fe\u6784\u5efa</li> <li>\u80cc\u666f\u77e5\u8bc6:<ul> <li>\u5c04\u5f71\u51e0\u4f55</li> <li>\u8ba1\u7b97\u673a\u89c6\u89c9</li> <li>\u72b6\u6001\u4f30\u8ba1\u7406\u8bba</li> <li>\u674e\u7fa4\u4e0e\u674e\u4ee3\u6570</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#12","title":"1.2 \u5982\u4f55\u4f7f\u7528\u672c\u4e66","text":""},{"location":"CV/SLAM14/#121","title":"1.2.1 \u7ec4\u7ec7\u65b9\u5f0f","text":"<ul> <li>\u6570\u5b66\u57fa\u7840\u7bc7<ul> <li></li> </ul> </li> <li>\u5b9e\u8df5\u5e94\u7528\u7bc7<ul> <li></li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#122","title":"1.2.2 \u4ee3\u7801","text":"<p>GitHub - gaoxiang12/slambook2: edition 2 of the slambook</p>"},{"location":"CV/SLAM14/#123","title":"1.2.3 \u9762\u5411\u7684\u8bfb\u8005","text":"<ul> <li>\u57fa\u7840\u77e5\u8bc6:<ul> <li>\u9ad8\u6570\u7ebf\u4ee3\u6982\u7387\u8bba</li> <li>C++\u8bed\u8a00\u57fa\u7840\uff08C++\u6807\u51c6\u5e93\uff0c\u6a21\u677f\u7c7b\uff0c\u4e00\u90e8\u5206 C++11 \uff09</li> <li>Linux \u57fa\u7840</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#13","title":"1.3 \u98ce\u683c\u7ea6\u5b9a","text":""},{"location":"CV/SLAM14/#14","title":"1.4 \u81f4\u8c22\u548c\u58f0\u660e","text":""},{"location":"CV/SLAM14/#15","title":"1.5 \u4e60\u9898","text":"<ul> <li>\u9898\u76ee\uff1a\u6709\u7ebf\u6027\u65b9\u7a0b \\(A x=b\\)\uff0c\u82e5\u5df2\u77e5 \\(A, b\\)\uff0c\u9700\u8981\u6c42\u89e3 x\uff0c\u8be5\u5982\u4f55\u6c42\u89e3\uff1f\u8fd9\u5bf9 A \u548c b \u6709\u54ea\u4e9b\u8981\u6c42\uff1f\u63d0\u793a\uff1a\u4ece A \u7684\u7ef4\u5ea6\u548c\u79e9\u89d2\u5ea6\u6765\u5206\u6790\u3002</li> <li>\u7b54\u6848\uff1a\u7ebf\u6027\u65b9\u7a0b\u7ec4 \\(Ax = b\\) \u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u6cd5\u6c42\u89e3\uff0c\u5982\u9ad8\u65af\u6d88\u5143\u6cd5\u3001\u77e9\u9635\u9006\u6cd5\u7b49\u3002\u8981\u6c42 \\(A\\) \u662f\u4e00\u4e2a\u65b9\u9635\u4e14\u53ef\u9006\uff08\u5373 \\(A\\) \u7684\u884c\u5217\u5f0f\u4e0d\u4e3a\u96f6\uff09\uff0c\u8fd9\u6837\u65b9\u7a0b\u624d\u6709\u552f\u4e00\u89e3\u3002\u5982\u679c \\(A\\) \u4e0d\u662f\u65b9\u9635\uff0c\u9700\u8981 \\(A\\) \u7684\u79e9\u7b49\u4e8e\u5217\u6570\u4e14\u7b49\u4e8e\u589e\u5e7f\u77e9\u9635 \\(\\displaystyle [A|b]\\) \u7684\u79e9\uff0c\u8fd9\u6837\u65b9\u7a0b\u7ec4\u624d\u6709\u89e3\u3002</li> <li>\u9898\u76ee\uff1a\u9ad8\u65af\u5206\u5e03\u662f\u4ec0\u4e48\uff1f\u5b83\u7684\u4e00\u7ef4\u5f62\u5f0f\u662f\u4ec0\u4e48\u6837\u5b50\uff1f\u5b83\u7684\u9ad8\u7ef4\u5f62\u5f0f\u662f\u4ec0\u4e48\u6837\u5b50\uff1f</li> <li>\u7b54\u6848\uff1a\u9ad8\u65af\u5206\u5e03\uff0c\u4e5f\u79f0\u4e3a\u6b63\u6001\u5206\u5e03\uff0c\u662f\u4e00\u79cd\u8fde\u7eed\u6982\u7387\u5206\u5e03\u3002\u4e00\u7ef4\u9ad8\u65af\u5206\u5e03\u7684\u6570\u5b66\u8868\u8fbe\u5f0f\u4e3a \\(\\displaystyle f (x) = \\frac{1}{\\sigma\\sqrt{2\\pi}} e^{-\\frac{(x-\\mu)^2}{2\\sigma^2}}\\)\uff0c\u5176\u4e2d \\(\\displaystyle \\mu\\) \u662f\u5747\u503c\uff0c\\(\\displaystyle \\sigma\\) \u662f\u6807\u51c6\u5dee\u3002\u9ad8\u7ef4\u9ad8\u65af\u5206\u5e03\u662f\u4e00\u7ef4\u9ad8\u65af\u5206\u5e03\u5728\u591a\u7ef4\u7a7a\u95f4\u7684\u63a8\u5e7f\uff0c\u5176\u6982\u7387\u5bc6\u5ea6\u51fd\u6570\u4e3a \\(\\displaystyle N (\\mathbf{x}; \\mathbf{\\mu}, \\Sigma)\\)\uff0c\u5176\u4e2d \\(\\displaystyle \\mathbf{\\mu}\\) \u662f\u5747\u503c\u5411\u91cf\uff0c\\(\\displaystyle \\Sigma\\) \u662f\u534f\u65b9\u5dee\u77e9\u9635\u3002</li> <li>\u9898\u76ee\uff1a\u4f60\u77e5\u9053 C++11 \u6807\u51c6\u5417\uff1f\u4f60\u542c\u8bf4\u8fc7\u6216\u7528\u8fc7\u5176\u4e2d\u54ea\u4e9b\u65b0\u7279\u6027\uff1f\u6709\u6ca1\u6709\u5176\u4ed6\u7684\u6807\u51c6\uff1f</li> <li>\u7b54\u6848\uff1a\u662f\u7684\uff0cC++11 \u662f C++ \u8bed\u8a00\u7684\u4e00\u4e2a\u91cd\u8981\u6807\u51c6\uff0c\u5b83\u5f15\u5165\u4e86\u8bb8\u591a\u65b0\u7279\u6027\uff0c\u5982\u81ea\u52a8\u7c7b\u578b\u63a8\u5bfc\uff08auto\uff09\u3001\u57fa\u4e8e\u8303\u56f4\u7684 for \u5faa\u73af\u3001lambda \u8868\u8fbe\u5f0f\u3001\u667a\u80fd\u6307\u9488\u7b49\u3002\u9664\u4e86 C++11\uff0c\u8fd8\u6709 C++14\u3001C++17 \u548c C++20 \u7b49\u540e\u7eed\u6807\u51c6\uff0c\u5b83\u4eec\u4e5f\u5f15\u5165\u4e86\u65b0\u7684\u7279\u6027\u548c\u6539\u8fdb\u3002</li> <li>\u9898\u76ee\uff1a\u5982\u4f55\u5728 Ubuntu \u7cfb\u7edf\u4e2d\u5b89\u88c5\u8f6f\u4ef6\uff08\u4e0d\u6253\u5f00\u8f6f\u4ef6\u4e2d\u5fc3\u7684\u60c5\u51b5\u4e0b\uff09\uff1f\u8fd9\u4e9b\u8f6f\u4ef6\u88ab\u5b89\u88c5\u5728\u4ec0\u4e48\u5730\u65b9\uff1f\u5982\u679c\u53ea\u77e5\u9053\u6a21\u7cca\u7684\u8f6f\u4ef6\u540d\u79f0\uff08\u6bd4\u5982\u60f3\u8981\u88c5\u4e00\u4e2a\u540d\u79f0\u4e2d\u542b\u6709 Eigen \u7684\u5e93\uff09\uff0c\u5e94\u8be5\u5982\u4f55\u5b89\u88c5\u5b83\uff1f</li> <li>\u7b54\u6848\uff1a</li> <li>\u8f6f\u4ef6\u5b89\u88c5\uff1a\u5728 Ubuntu \u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u547d\u4ee4\u884c\u5de5\u5177 <code>apt</code> \u6765\u5b89\u88c5\u8f6f\u4ef6\u3002\u57fa\u672c\u547d\u4ee4\u4e3a <code>sudo apt install [package-name]</code>\u3002</li> <li>\u5b89\u88c5\u4f4d\u7f6e\uff1a\u8f6f\u4ef6\u901a\u5e38\u88ab\u5b89\u88c5\u5728 <code>/usr/</code> \u76ee\u5f55\u4e0b\uff0c\u4f46\u5177\u4f53\u7684\u6587\u4ef6\u53ef\u80fd\u5206\u5e03\u5728\u591a\u4e2a\u5b50\u76ee\u5f55\u4e2d\u3002</li> <li>\u6a21\u7cca\u540d\u79f0\u5b89\u88c5\uff1a\u5982\u679c\u53ea\u77e5\u9053\u8f6f\u4ef6\u540d\u79f0\u7684\u4e00\u90e8\u5206\uff0c\u53ef\u4ee5\u4f7f\u7528 <code>apt search</code> \u547d\u4ee4\u6765\u641c\u7d22\u3002\u4f8b\u5982\uff0c<code>sudo apt search eigen</code> \u53ef\u4ee5\u5e2e\u52a9\u627e\u5230\u6240\u6709\u5305\u542b \"eigen\" \u7684\u8f6f\u4ef6\u5305\u3002</li> <li>\u9898\u76ee\uff1a*\u82b1\u4e00\u4e2a\u5c0f\u65f6\u5b66\u4e60 Vim\uff0c\u56e0\u4e3a\u4f60\u8fdf\u65e9\u4f1a\u7528\u5b83\u3002\u4f60\u53ef\u4ee5\u5728\u7ec8\u7aef\u4e2d\u8f93\u5165 vimtutor \u9605\u8bfb\u4e00\u904d\u6240\u6709\u5185\u5bb9\u3002\u6211\u4eec\u4e0d\u9700\u8981\u4f60\u975e\u5e38\u719f\u7ec3\u5730\u64cd\u4f5c\u5b83\uff0c\u53ea\u8981\u80fd\u591f\u5728\u5b66\u4e60\u672c\u4e66\u7684\u8fc7\u7a0b\u4e2d\u4f7f\u7528\u5b83\u8f93\u5165\u4ee3\u7801\u5373\u53ef\u3002\u4e0d\u8981\u5728\u5b83\u7684\u63d2\u4ef6\u4e0a\u6d6a\u8d39\u65f6\u95f4\uff0c\u4e0d\u8981\u60f3\u7740\u628a Vim \u7528\u6210 IDE\uff0c\u6211\u4eec\u53ea\u7528\u5b83\u505a\u6587\u672c\u7f16\u8f91\u7684\u5de5\u4f5c\u3002</li> <li>\u7b54\u6848:<ul> <li>vim \u6839\u672c\u4e0d\u719f\u7ec3\u634f</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#2-slam","title":"2 \u521d\u8bc6 SLAM","text":""},{"location":"CV/SLAM14/#21","title":"2.1 \u5f15\u5b50: \u5c0f\u841d\u535c\u7684\u4f8b\u5b50","text":"<ul> <li>\u81ea\u4e3b\u8fd0\u52a8\u80fd\u529b</li> <li>\u611f\u77e5\u5468\u8fb9\u73af\u5883<ul> <li>\u72b6\u6001</li> <li>\u73af\u5883</li> </ul> </li> <li>\u5b89\u88c5\u4e8e\u73af\u5883\u4e2d\uff08\u4e0d\u592a\u597d\u53cd\u6b63\uff09</li> <li>\u673a\u5668\u4eba\u672c\u4f53\u4e0a<ul> <li>\u6fc0\u5149 SLAM</li> <li>\u89c6\u89c9 SLAM\uff08\u672c\u4e66\u91cd\u70b9\uff09<ul> <li>\u5355\u76ee\uff08Monocular\uff09<ul> <li>\u53ea\u80fd\u7528\u4e00\u4e2a\u6444\u50cf\u5934</li> <li>\u8ddd\u79bb\u611f<ul> <li>motion</li> <li>Structure</li> <li>Disparity</li> <li>Scale<ul> <li>Scale Ambiguity</li> </ul> </li> <li>\u4f46\u662f\u65e0\u6cd5\u786e\u5b9a\u6df1\u5ea6</li> </ul> </li> </ul> </li> <li>\u53cc\u76ee\uff08Sterco\uff09<ul> <li>\u4e24\u4e2a\u76f8\u673a\u7684\u8ddd\u79bb\uff08\u57fa\u7ebf Baseline\uff09\u5df2\u77e5</li> <li>\u914d\u7f6e\u4e0e\u6807\u5b9a\u6bd4\u8f83\u590d\u6742</li> </ul> </li> <li>\u6df1\u5ea6\uff08RGB-D\uff09<ul> <li>\u7ea2\u5916\u7ed3\u6784\u5173 Time-of-Flight\uff08ToF\uff09</li> <li>\u4e3b\u8981\u7528\u5728\u5ba4\u5185\uff0c\u5ba4\u5916\u4f1a\u6709\u5f88\u591a\u5f71\u54cd</li> </ul> </li> <li>\u8fd8\u6709\u4e00\u4e9b\u975e\u4e3b\u6d41\u7684: \u5168\u666f\uff0cEvent</li> </ul> </li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#22-slam","title":"2.2 \u7ecf\u5178\u89c6\u89c9 SLAM \u6846\u67b6","text":"<ul> <li>\u5728\u5916\u754c\u6362\u51e0\u4e2a\u6bd4\u8f83\u7a33\u5b9a\u7684\u60c5\u51b5\u4e0b\uff0cSLAM \u6280\u672f\u5df2\u7ecf\u6bd4\u8f83\u6210\u719f</li> </ul>"},{"location":"CV/SLAM14/#221","title":"2.2.1 \u89c6\u89c9\u91cc\u7a0b\u8ba1","text":"<ul> <li>\u53ea\u901a\u8fc7\u89c6\u89c9\u91cc\u7a0b\u8ba1\u6765\u4f30\u8ba1\u8f68\u8ff9\u4f1a\u51fa\u73b0\u7d2f\u79ef\u6f02\u79fb\uff08Accumulating Drift\uff09\u3002</li> <li>\u6240\u4ee5\u9700\u8981\u56de\u73af\u68c0\u6d4b\u4e0e\u540e\u7aef\u4f18\u5316</li> </ul>"},{"location":"CV/SLAM14/#222","title":"2.2.2 \u540e\u7aef\u4f18\u5316","text":"<ul> <li>\u6700\u5927\u540e\u9a8c\u6982\u7387\u4f30\u8ba1\uff08Maximum-a-Posteriori MAP\uff09</li> <li>\u524d\u7aef<ul> <li>\u56fe\u50cf\u7684\u7279\u5f81\u63d0\u53d6\u4e0e\u5339\u914d</li> </ul> </li> <li>\u540e\u7aef<ul> <li>\u6ee4\u6ce2\u4e0e\u975e\u7ebf\u6027\u7b97\u6cd5</li> </ul> </li> <li>\u5bf9\u8fd0\u52a8\u4e3b\u4f53\u81ea\u8eab\u548c\u5468\u56f4\u73af\u5883\u7a7a\u95f4\u4e0d\u786e\u5b9a\u6027\u7684\u4f30\u8ba1</li> </ul>"},{"location":"CV/SLAM14/#223","title":"2.2.3 \u56de\u73af\u68c0\u6d4b","text":"<ul> <li>\u95ed\u73af\u68c0\u6d4b</li> <li>\u8bc6\u522b\u5230\u8fc7\u7684\u573a\u666f</li> <li>\u5229\u7528\u56fe\u50cf\u7684\u76f8\u4f3c\u6027</li> </ul>"},{"location":"CV/SLAM14/#224","title":"2.2.4 \u5efa\u56fe","text":"<ul> <li>\u5ea6\u91cf\u5730\u56fe<ul> <li>Sparse<ul> <li>Landmark</li> <li>\u5b9a\u4f4d\u7528</li> </ul> </li> <li>Dense<ul> <li>Grid / Vocel</li> <li>\u5bfc\u822a\u7528</li> </ul> </li> </ul> </li> <li>\u62d3\u6251\u5730\u56fe     Graph</li> </ul>"},{"location":"CV/SLAM14/#23-slam","title":"2.3 SLAM \u95ee\u9898\u7684\u6570\u5b66\u8868\u8ff0","text":"<ul> <li>\u8fd0\u52a8\u65b9\u7a0b<ul> <li>\\(\\displaystyle \\quad\\boldsymbol{x}_k=f\\left(\\boldsymbol{x}_{k-1},\\boldsymbol{u}_k,\\boldsymbol{w}_k\\right).\\)<ul> <li>\\(\\displaystyle \\boldsymbol{u}_{k}\\) \u662f\u8fd0\u52a8\u4f20\u611f\u5668\u7684\u8f93\u5165</li> <li>\\(\\displaystyle \\boldsymbol{w}_{k}\\) \u662f\u8fc7\u7a0b\u4e2d\u52a0\u5165\u7684\u566a\u58f0</li> </ul> </li> </ul> </li> <li>\u89c2\u6d4b\u65b9\u7a0b<ul> <li>\\(\\displaystyle \\boldsymbol{z}_{k,j} = h (\\boldsymbol{y}_{j},\\boldsymbol{x}_{k},\\boldsymbol{v}_{k,j})\\)<ul> <li>\\(\\displaystyle \\boldsymbol{v}_{k,j}\\) \u662f\u89c2\u6d4b\u91cc\u7684\u566a\u58f0</li> </ul> </li> </ul> </li> <li>\u53c8\u5f88\u591a\u53c2\u6570\u5316\u7684\u65b9\u5f0f</li> <li>\u53ef\u4ee5\u603b\u7ed3\u4e3a\u5982\u4e0b\u4e24\u4e2a\u65b9\u7a0b</li> </ul> \\[ \\begin{cases}\\boldsymbol{x}_k=f\\left(\\boldsymbol{x}_{k-1},\\boldsymbol{u}_k,\\boldsymbol{w}_k\\right),&amp;k=1,\\cdots,K\\\\\\boldsymbol{z}_{k,j}=h\\left(\\boldsymbol{y}_j,\\boldsymbol{x}_k,\\boldsymbol{v}_{k,j}\\right),&amp;(k,j)\\in\\mathcal{O}\\end{cases}. \\] <ul> <li>\u77e5\u9053\u8fd0\u52a8\u6d4b\u91cf\u7684\u8bfb\u6570 \\(\\displaystyle \\boldsymbol{u}\\) \u548c\u4f20\u611f\u5668\u7684\u8bfb\u6570 \\(\\displaystyle \\boldsymbol{z}\\)\uff0c\u5982\u4f55\u6c42\u89e3\u5b9a\u4f4d\u95ee\u9898\u548c\u5efa\u56fe\u95ee\u9898\u3002<ul> <li>\u72b6\u6001\u4f30\u8ba1\u95ee\u9898: \u5982\u4f55\u901a\u8fc7\u5e26\u6709\u566a\u58f0\u7684\u6d4b\u91cf\u6570\u636e\uff0c\u4f30\u8ba1\u5185\u90e8\u7684\u3001\u9690\u85cf\u7740\u7684\u72b6\u6001\u53d8\u91cf</li> </ul> </li> <li>Linear Gaussian -&gt; Kalman Filter</li> <li>Non-Linear Non-Gaussian -&gt; Extended Kalman Filter \u548c\u975e\u7ebf\u6027\u4f18\u5316</li> <li>EKF -&gt; Particle Filter -&gt; Graph Optimization</li> </ul>"},{"location":"CV/SLAM14/#24","title":"2.4 \u5b9e\u8df5: \u7f16\u7a0b\u57fa\u7840","text":""},{"location":"CV/SLAM14/#241-linux","title":"2.4.1 \u5b89\u88c5 Linux \u64cd\u4f5c\u7cfb\u7edf","text":""},{"location":"CV/SLAM14/#242-hello-slam","title":"2.4.2 Hello SLAM","text":""},{"location":"CV/SLAM14/#243-cmake","title":"2.4.3 \u4f7f\u7528 cmake","text":"Text Only<pre><code>cmake_minimum_required( VERSION 2.8)\n\nproject(HelloSLAM)\n\nadd_executable(helloSLAM helloSLAM.cpp)\n</code></pre> <p>\u5bf9\u4e2d\u95f4\u6587\u4ef6\u7684\u5904\u7406:</p> Text Only<pre><code>mkdir build\ncd build\ncmake ..\nmake\n</code></pre>"},{"location":"CV/SLAM14/#244","title":"2.4.4 \u4f7f\u7528\u5e93","text":"Text Only<pre><code>add_library(hello libHelloSLAM.cpp)\n</code></pre> <ul> <li>\u9759\u6001\u5e93<ul> <li>.a \u4f5c\u4e3a\u540e\u7f00\u540d\uff0c\u6bcf\u6b21\u8c03\u7528\u90fd\u6709\u4e00\u4e2a\u526f\u672c</li> </ul> </li> <li>\u5171\u4eab\u5e93<ul> <li>.so\uff0c\u53ea\u6709\u4e00\u4e2a\u526f\u672c</li> </ul> </li> </ul> Text Only<pre><code>add_library(hello_shared SHARED libHelloSLAM.cpp)\n</code></pre> <ul> <li>\u8fd8\u8981\u4e00\u4e2a\u5934\u6587\u4ef6\u6765\u8bf4\u660e\u5e93\u91cc\u90fd\u6709\u4ec0\u4e48</li> </ul> Text Only<pre><code>#ifndef LIBHELLOSLAM_H_\n#define LIBHELLOSLAM_H_\n\nvoid printHello()\n\n#endif\n</code></pre> <ul> <li>\u6700\u540e\u5199\u4e00\u4e2a\u53ef\u6267\u884c\u7a0b\u5e8f:</li> </ul> C++<pre><code>#include \"libHelloSLAM.h\"\n\nint main(int argc, char **argv) {\n    printHello();\n    return 0;   \n}\n</code></pre> <ul> <li>\u5728 CMakeLists. txt \u4e2d\u6dfb\u52a0\u53ef\u6267\u884c\u547d\u4ee4\u7684\u751f\u6210\u547d\u4ee4\uff0c\u94fe\u63a5\u5230\u5e93\u4e0a:</li> </ul> Text Only<pre><code>add_executable(useHello useHello.cpp)\ntarget_link_libraries(useHello hello_shared)\n</code></pre>"},{"location":"CV/SLAM14/#245-ide","title":"2.4.5 \u4f7f\u7528 IDE","text":"<ul> <li>KDevelop</li> <li>Clion</li> <li>\u8fd8\u6ca1\u5199</li> </ul>"},{"location":"CV/SLAM14/#3","title":"3 \u4e09\u7ef4\u7a7a\u95f4\u521a\u4f53\u8fd0\u52a8","text":""},{"location":"CV/SLAM14/#31","title":"3.1 \u65cb\u8f6c\u77e9\u9635","text":""},{"location":"CV/SLAM14/#311","title":"3.1.1 \u70b9\u3001\u5411\u91cf\u548c\u5750\u6807\u7cfb","text":"<ul> <li>Skew-symmetric Matrix</li> </ul> \\[ a\\times b =  \\begin{Vmatrix}e_1&amp;e_2&amp;e_3\\\\ \\\\ a_1&amp;a_2&amp;a_3\\\\ \\\\ b_1&amp;b_2&amp;b_3 \\\\ \\end{Vmatrix} = \\begin{bmatrix} a_2b_3-a_3b_2\\\\ \\\\ a_3b_1-a_1b_3\\\\ \\\\ a_1b_2-a_2b_1  \\end{bmatrix} = \\begin{bmatrix}  0&amp;-a_3&amp;a_2\\\\ \\\\ a_3&amp;0&amp;-a_1\\\\ \\\\ -a_2&amp;a_1&amp;0  \\end{bmatrix} \\boldsymbol{b}\\overset{\\mathrm{def}}{\\operatorname*{=}}\\boldsymbol{a}^{\\wedge}\\boldsymbol{b}. \\] <ul> <li>\u4e8e\u662f\u5c31\u628a\u5916\u79ef\u53d8\u6210\u4e86\u7ebf\u6027\u8fd0\u7b97</li> <li>\u5373</li> </ul> \\[ \\displaystyle \\boldsymbol{a}^{\\wedge}=\\begin{bmatrix} 0  &amp; -a_{3}  &amp; a_{2} \\\\ a_{3} &amp; 0 &amp; -a_{1} \\\\ -a_{2} &amp; a_{1} &amp; 0 \\end{bmatrix} \\]"},{"location":"CV/SLAM14/#312","title":"3.1.2 \u5750\u6807\u7cfb\u95f4\u7684\u6b27\u5f0f\u53d8\u6362","text":"<ul> <li>Euclidean Transform</li> </ul> \\[ \\begin{bmatrix}a_1\\\\ \\\\ a_2\\\\\\\\a_3\\end{bmatrix}=\\begin{bmatrix}e_1^\\mathrm{T}e_1^{\\prime}&amp;e_1^\\mathrm{T}e_2^{\\prime}&amp;e_1^\\mathrm{T}e_3^{\\prime}\\\\e_2^\\mathrm{T}e_1^{\\prime}&amp;e_2^\\mathrm{T}e_2^{\\prime}&amp;e_2^\\mathrm{T}e_3^{\\prime}\\\\e_3^\\mathrm{T}e_1^{\\prime}&amp;e_3^\\mathrm{T}e_2^{\\prime}&amp;e_3^\\mathrm{T}e_3^{\\prime}\\end{bmatrix}\\begin{bmatrix}a_1^{\\prime}\\\\\\\\a_2^{\\prime}\\\\\\\\a_3^{\\prime}\\end{bmatrix}\\stackrel{\\mathrm{def}}{=}Ra^{\\prime} \\] <ul> <li>\\(\\displaystyle \\boldsymbol{R}\\) \u662f\u65cb\u8f6c\u77e9\u9635\u3001\u65b9\u5411\u4f59\u5f26\u77e9\u9635</li> <li>Special Orthogonal Group \\(\\displaystyle \\mathrm{SO}(n)=\\{\\boldsymbol{R}\\in \\mathbb{R}^{n \\times n}|\\boldsymbol{R}\\boldsymbol{R}^{\\mathrm{T}}=\\boldsymbol{I},\\det(\\boldsymbol{R})=1\\}\\)</li> <li>\\(\\displaystyle a^{\\prime}=R^{-1}a=R^{\\intercal}a.\\)</li> <li>\u65cb\u8f6c+\u5e73\u79fb: \\(\\displaystyle a^{\\prime}=Ra+t.\\)</li> </ul>"},{"location":"CV/SLAM14/#313","title":"3.1.3 \u53d8\u6362\u77e9\u9635\u4e0e\u9f50\u6b21\u5750\u6807","text":"<ul> <li>\u4f46\u662f\u8fd9\u91cc\u7684\u53d8\u6362\u5173\u7cfb\u4e0d\u662f\u4e00\u4e2a\u7ebf\u6027\u5173\u7cfb</li> <li>\\(\\displaystyle c=R_2\\left(R_1a+t_1\\right)+t_2\\)</li> <li>\u6211\u4eec\u6539\u5199\u4e00\u4e0b\u5f62\u5f0f:<ul> <li>\\(\\displaystyle \\begin{bmatrix}a'\\\\\\\\1\\end{bmatrix}=\\begin{bmatrix}R&amp;t\\\\\\\\\\mathbf{0}^\\mathrm{T}&amp;1\\end{bmatrix}\\begin{bmatrix}a\\\\\\\\1\\end{bmatrix}\\overset{\\mathrm{def}}{=}T\\begin{bmatrix}a\\\\\\\\1\\end{bmatrix}\\)</li> <li>\u8fd9\u5c31\u662f\u9f50\u6b21\u5750\u6807\uff0c\\(\\displaystyle \\boldsymbol{T}\\) \u79f0\u4e3a\u53d8\u6362\u77e9\u9635\uff08Transform matrix\uff09</li> </ul> </li> <li>\\(\\displaystyle \\tilde{b}=T_1\\tilde{\\boldsymbol{a}}, \\tilde{\\boldsymbol{c}}=T_2\\tilde{\\boldsymbol{b}}\\quad\\Rightarrow\\tilde{\\boldsymbol{c}}=T_2T_1\\tilde{\\boldsymbol{a}}.\\)</li> <li>\u5e76\u4e14 \\(\\displaystyle \\boldsymbol{T}\\) \u79f0\u4e3a\u7279\u6b8a\u6b27\u5f0f\u7fa4\uff08Special Euclidean Group\uff09<ul> <li>\\(\\displaystyle \\mathrm{SE}(3)=\\left\\{T=\\begin{bmatrix}R&amp;t\\\\\\mathbf{0}^\\mathrm{T}&amp;1\\end{bmatrix}\\in\\mathbb{R}^{4\\times4}|\\boldsymbol{R}\\in\\mathrm{SO}(3),\\boldsymbol{t}\\in\\mathbb{R}^3\\right\\}\\)</li> </ul> </li> <li>\\(\\displaystyle T^{-1}=\\begin{bmatrix}R^\\mathrm{T}&amp;-R^\\mathrm{T}t\\\\0^\\mathrm{T}&amp;1\\end{bmatrix}\\)</li> <li>\u5728 C++\u7a0b\u5e8f\u4e2d\u53ef\u4ee5\u4f7f\u7528\u8fd0\u7b97\u7b26\u91cd\u8f7d\u6765\u5904\u7406\u9f50\u6b21\u548c\u975e\u9f50\u6b21\u7684\u60c5\u51b5</li> </ul>"},{"location":"CV/SLAM14/#32-eigen","title":"3.2 \u5b9e\u8df5:Eigen","text":"C++<pre><code>#include &lt;iostream&gt;\nusing namespace std;\n\n#include &lt;ctime&gt;\n\n#include &lt;eigen3&gt;\nusing namespace Eigen;\n\n#define MATRIX_SIZE 50\n\nint main(int argc, char **argv) {\n    Matrix&lt;float, 2, 3&gt; matrix_23;\n// \u5982\u4e0b\u90fd\u662f\u4e09\u7ef4\u5411\u91cf\n    Vector3d v_3d;\n    Matrix&lt;float, 3, 1&gt; vd_3d;\n// \u5982\u4e0b\u662f3*3\u77e9\u9635\n    Matrix3d matrix_33 = Matrix3d::Zero();\n// \u4e24\u4e2a\u52a8\u6001\u5206\u914d\n    Matrix&lt;double, Dynamic, Dynamic&gt; matrix_dynamic;\n    MatrixXd matrix_x;\n\n    matrix_23 &lt;&lt; 1, 2, 3, 4, 5, 6;\n    cout&lt;&lt; \"matrix 2*3 from 1 to 6: \\n\" &lt;&lt; matrix_23 &lt;&lt; endl;\n\n    cout &lt;&lt; \"print matrix 2*3:\" &lt;&lt; endl;\n    for (int i = 0; i &lt; 2; i++) {\n        for (int j = 0; j &lt; 3; j+) cout &lt;&lt; matrix_23(i, j) &lt;&lt; \"\\t\";\n        cout &lt;&lt; endl;\n    }\n\n    v_3d &lt;&lt; 3, 2, 1;\n    vd_3d &lt;&lt; 4, 5, 6;\n\n    Matrix&lt;double, 2, 1&gt; result = matrix_23.cast&lt;double&gt;() * v_3d;\n    cout &lt;&lt; \"[1, 2, 3; 4, 5, 6] * [3, 2, 1] =\" &lt;&lt; result.transpose() &lt;&lt; endl;\n\n    matrix_22 = Matrix3d::Random();\n\n    // \u4e00\u4e9b\u77e9\u9635\u7684\u64cd\u4f5c:\n    // transpose()\n    // sum()\n    // trace()\n    // inverse()\n    // determinant()\n\n    SelfAdjointEigenSolver&lt;Matrix3d&gt; eigen_solver(matrix_33.transpose() * matrix_33);\n    cout &lt;&lt; eigen_solver.eigenvalues() &lt;&lt; endl;\n    cout &lt;&lt; eigen_solver.eigenvectors() &lt;&lt; endl;\n\n    // solve the equation\n    Matrix&lt;double, MATRIX_SIZE, MATRIX_SIZE&gt; matrix_NN = MatrixXd::Random(MATRIX_SIZE, MATRIX_SIZE);\n    matrix_NN = matrix_NN * matrix_NN.transpose()\n    Matrix&lt;double, MATRIX_SIZE, 1&gt; v_Nd = MatrixXd::random(MATRIX_SIZE, 1);\n\n    // \u7b2c\u4e00\u79cd:\u76f4\u63a5\u6c42\u9006\n    Matrix&lt;double, MATRIX_SIZE, 1&gt; x = matrix_NN.inverse() * v_Nd;\n\n    // \u7b2c\u4e8c\u79cd:\u77e9\u9635\u5206\u89e3\n    x = matrix_NN.colPivHouseholderQr().solve(v_Nd);\n\n}\n</code></pre> <ul> <li>Eigen \u4e0d\u652f\u6301\u81ea\u52a8\u7c7b\u578b\u63d0\u5347\uff0c\u5373\u4e0d\u4f1a\u9690\u5f0f\u8f6c\u6362</li> </ul>"},{"location":"CV/SLAM14/#33","title":"3.3 \u65cb\u8f6c\u5411\u91cf\u548c\u6b27\u62c9\u89d2","text":""},{"location":"CV/SLAM14/#331","title":"3.3.1 \u65cb\u8f6c\u5411\u91cf","text":"<ul> <li>Axis-Angle</li> <li>Rodrigues's Formula<ul> <li>\\(\\displaystyle \\boldsymbol{R}=\\cos\\theta\\boldsymbol{I}+\\left(1-\\cos\\theta\\right)\\boldsymbol{n}\\boldsymbol{n}^\\mathrm{T}+\\sin\\theta\\boldsymbol{n}^\\mathrm{\\wedge}.\\)</li> </ul> </li> </ul> \\[ \\begin{aligned} \\mathrm{tr}\\left(R\\right)&amp; =\\cos\\theta\\operatorname{tr}\\left(\\boldsymbol{I}\\right)+\\left(1-\\cos\\theta\\right)\\operatorname{tr}\\left(\\boldsymbol{n}\\boldsymbol{n}^\\mathrm{T}\\right)+\\sin\\theta\\operatorname{tr}(\\boldsymbol{n}^\\mathrm{\\Lambda}) \\\\ &amp;=3\\cos\\theta+(1-\\cos\\theta) \\\\ &amp;=1+2\\cos\\theta  \\end{aligned} \\] <p>thus:</p> \\[ \\theta=\\arccos\\frac{\\mathrm{tr}(R)-1}{2}. \\] \\[ Rn=n. \\] <ul> <li>\u5373 \\(\\displaystyle \\boldsymbol{n}\\) \u662f\u77e9\u9635 \\(\\displaystyle \\boldsymbol{R}\\) \u7279\u5f81\u503c 1 \u5bf9\u5e94\u7684\u7279\u8bca\u5411\u91cf</li> </ul>"},{"location":"CV/SLAM14/#332","title":"3.3.2 \u6b27\u62c9\u89d2","text":"<ul> <li>\u6bd4\u8f83\u5e38\u7528\u7684\u4e00\u79cd yaw-pitch-roll<ul> <li>ZYX</li> </ul> </li> <li>\u4f46\u4f1a\u6709 Gimbal Lock \u95ee\u9898<ul> <li>\u6240\u4ee5\u6b27\u62c9\u89d2\u6bd4\u8f83\u9002\u5408\u7528\u4e8e\u5feb\u901f\u68c0\u9a8c\u7ed3\u679c\u662f\u5426\u6709\u9519</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#34","title":"3.4 \u56db\u5143\u6570","text":""},{"location":"CV/SLAM14/#341","title":"3.4.1 \u56db\u5143\u6570\u7684\u5b9a\u4e49","text":"<ul> <li>\u6211\u4eec\u627e\u4e0d\u5230\u4e0d\u5e26\u5947\u5f02\u6027\u7684\u4e09\u4f4d\u5411\u91cf\u63cf\u8ff0\u65b9\u5f0f<ul> <li>\u627e\u4e0d\u5230\u4e00\u4e2a\u6d41\u5f62\uff1f</li> </ul> </li> <li>Quaternion<ul> <li>\u7d27\u51d1\u53c8\u6ca1\u6709\u5947\u5f02\u6027</li> <li>\u53ea\u662f\u4e0d\u591f\u76f4\u89c2+\u8fd0\u7b97\u590d\u6742</li> </ul> </li> <li>\\(\\displaystyle q=q_0+q_1\\mathrm{i}+\\mathrm{q}_2\\mathrm{j}+\\mathrm{q}_3\\mathrm{k}\\)</li> </ul> \\[ \\begin{cases}\\mathbf{i}^2=\\mathbf{j}^2=\\mathbf{k}^2=-1\\\\\\mathbf{ij}=\\mathbf{k},\\mathbf{ji}=-\\mathbf{k}\\\\\\mathbf{jk}=\\mathbf{i},\\mathbf{kj}=-\\mathbf{i}\\\\\\mathbf{ki}=\\mathbf{j},\\mathbf{ik}=-\\mathbf{j}\\end{cases} \\] <ul> <li>(\u4e5f\u8bb8\u53ef\u4ee5\u7528\u5ea6\u89c4\u6765\u8868\u793a\uff1f)</li> <li>\\(\\displaystyle \\boldsymbol{q}=\\left[s,\\boldsymbol{v}\\right]^\\mathrm{T},\\quad s=q_0\\in\\mathbb{R},\\quad\\boldsymbol{v}=\\left[q_1,q_2,q_3\\right]^\\mathrm{T}\\in\\mathbb{R}^3.\\)</li> <li>\u4e66\u4e0a\u6ca1\u5199\u76f4\u89c2\u7684\u51e0\u4f55\u5bf9\u5e94</li> </ul>"},{"location":"CV/SLAM14/#342","title":"3.4.2 \u56db\u5143\u6570\u7684\u8fd0\u7b97","text":"<ul> <li>\u4e58\u6cd5: \\(\\displaystyle \\boldsymbol{q}_a\\boldsymbol{q}_b=\\begin{bmatrix}s_as_b-\\boldsymbol{v}_a^\\mathrm{T}\\boldsymbol{v}_b,s_a\\boldsymbol{v}_b+s_b\\boldsymbol{v}_a+\\boldsymbol{v}_a\\times\\boldsymbol{v}_b\\end{bmatrix}^\\mathrm{T}.\\)<ul> <li>\u7531\u4e8e\u6700\u540e\u4e00\u9879\u7684\u5b58\u5728\uff0c\u4e58\u6cd5\u4e0d\u5177\u6709\u4ea4\u6362\u5f8b</li> </ul> </li> <li>\u5171\u8f6d: \\(\\displaystyle q_a^*=s_a-x_a\\mathrm{i}-\\mathrm{y_aj}-\\mathrm{z_ak}=[\\mathrm{s_a},-\\mathrm{v_a}]^\\mathrm{T}.\\)<ul> <li>\\(\\displaystyle q^*q=qq^*=[s_a^2+\\boldsymbol{v}^\\mathrm{T}\\boldsymbol{v},\\boldsymbol{0}]^\\mathrm{T}.\\)</li> </ul> </li> <li>\u9006: \\(\\displaystyle q^{-1}=q^*/\\|q\\|^2.\\)<ul> <li>\\(\\displaystyle (\\boldsymbol{q}_a\\boldsymbol{q}_b)^{-1}=\\boldsymbol{q}_b^{-1}\\boldsymbol{q}_a^{-1}.\\)</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#343","title":"3.4.3 \u7528\u56db\u5143\u6570\u8868\u793a\u65cb\u8f6c","text":"<ul> <li>\u5148\u8868\u793a\u4e09\u7ef4\u7a7a\u95f4\u70b9:<ul> <li>\\(\\displaystyle p=[0,x,y,z]^{\\mathrm{T}}=[0,\\boldsymbol{v}]^{\\mathrm{T}}.\\)</li> </ul> </li> <li>\u518d\u65cb\u8f6c:<ul> <li>\\(\\displaystyle p'=qpq^{-1}.\\)</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#344","title":"3.4.4 \u56db\u5143\u6570\u5230\u5176\u4ed6\u65cb\u8f6c\u8868\u793a\u7684\u8f6c\u6362","text":"<ul> <li>\u8bbe \\(\\displaystyle \\boldsymbol{q} = [s,\\boldsymbol{v}]^\\mathrm{T}\\)<ul> <li>\\(\\displaystyle \\boldsymbol{q}^+=\\begin{bmatrix}s&amp;-\\boldsymbol{v}^\\mathrm{T}\\\\\\\\\\boldsymbol{v}&amp;s\\boldsymbol{I}+\\boldsymbol{v}^\\wedge\\end{bmatrix},\\quad\\boldsymbol{q}^\\oplus=\\begin{bmatrix}s&amp;-\\boldsymbol{v}^\\mathrm{T}\\\\\\\\\\boldsymbol{v}&amp;s\\boldsymbol{I}-\\boldsymbol{v}^\\wedge\\end{bmatrix}.\\)</li> <li>\\(\\displaystyle q_1^+q_2=\\begin{bmatrix}s_1&amp;-\\boldsymbol{v}_1^\\mathrm{T}\\\\\\\\\\boldsymbol{v}_1&amp;s_1\\boldsymbol{I}+\\boldsymbol{v}_1^\\wedge\\end{bmatrix}\\begin{bmatrix}s_2\\\\\\\\\\boldsymbol{v}_2\\end{bmatrix}=\\begin{bmatrix}-\\boldsymbol{v}_1^\\mathrm{T}\\boldsymbol{v}_2+s_1s_2\\\\\\\\s_1\\boldsymbol{v}_2+s_2\\boldsymbol{v}_1+\\boldsymbol{v}_1^\\wedge\\boldsymbol{v}_2\\end{bmatrix}=\\boldsymbol{q}_1\\boldsymbol{q}_2.\\)</li> <li>\u540c\u7406\u53ef\u8bc1:<ul> <li>\\(\\displaystyle q_1q_2=q_1^+q_2=q_2^\\oplus q_1.\\)</li> </ul> </li> </ul> </li> <li>\u518d\u6765\u8003\u8651\u65cb\u8f6c:<ul> <li>\\(\\displaystyle \\begin{aligned}p^{\\prime}&amp;=qpq^{-1}=q^{+}p^{+}q^{-1}\\\\&amp;=q^{+}q^{-1^{\\oplus}}p.\\end{aligned}\\)</li> <li>\u4e8e\u662f\u53ef\u4ee5\u5f97\u5230:<ul> <li>\\(\\displaystyle \\boldsymbol{q}^{+}\\big(\\boldsymbol{q}^{-1}\\big)^{\\oplus}=\\begin{bmatrix}s&amp;-\\boldsymbol{v}^{\\mathrm{T}}\\\\\\boldsymbol{v}&amp;s\\boldsymbol{I}+\\boldsymbol{v}^{\\wedge}\\end{bmatrix}\\begin{bmatrix}s&amp;\\boldsymbol{v}^{\\mathrm{T}}\\\\-\\boldsymbol{v}&amp;s\\boldsymbol{I}+\\boldsymbol{v}^{\\wedge}\\end{bmatrix}=\\begin{bmatrix}1&amp;\\boldsymbol{0}\\\\\\boldsymbol{0}^{\\mathrm{T}}&amp;\\boldsymbol{v}\\boldsymbol{v}^{\\mathrm{T}}+s^{2}\\boldsymbol{I}+2s\\boldsymbol{v}^{\\wedge}+\\left(\\boldsymbol{v}^{\\wedge}\\right)^{2}\\end{bmatrix}.\\)</li> <li>\u5373: \\(\\displaystyle R=\\boldsymbol{v}\\boldsymbol{v}^\\mathrm{T}+s^2\\boldsymbol{I}+2s\\boldsymbol{v}^\\wedge+\\left(\\boldsymbol{v}^\\wedge\\right)^2.\\)</li> </ul> </li> </ul> </li> </ul> \\[ \\begin{aligned} \\operatorname{tr}(R)&amp; =\\mathbf{tr}(\\boldsymbol{vv}^\\mathrm{T}+3s^2+2s\\cdot0+\\mathbf{tr}((\\boldsymbol{v}^\\wedge)^2) \\\\ &amp;=v_{1}^{2}+v_{2}^{2}+v_{3}^{2}+3s^{2}-2(v_{1}^{2}+v_{2}^{2}+v_{3}^{2}) \\\\ &amp;=(1-s^2)+3s^2-2(1-s^2) \\\\ &amp;=4s^2-1. \\end{aligned} \\] <ul> <li>\u5373 \\(\\displaystyle \\theta=2\\arccos s.\\)</li> <li>\u518d\u52a0\u4e0a\u65cb\u8f6c\u8f74:</li> </ul> \\[ \\begin{cases}\\theta=2\\arccos q_0\\\\ [n_x,n_y,n_z]^\\mathrm{T}=[q_1,q_2,q_3]^\\mathrm{T}/\\sin\\frac{\\theta}{2}\\end{cases}. \\]"},{"location":"CV/SLAM14/#35","title":"3.5 \u76f8\u4f3c\u3001\u4eff\u5c04\u3001\u5c04\u5f71\u53d8\u6362","text":"<ol> <li>\u76f8\u4f3c\u53d8\u6362:</li> </ol> \\[ \\boldsymbol{T}_S=\\begin{bmatrix}s\\boldsymbol{R}&amp;t\\\\\\mathbf{0}^\\mathrm{T}&amp;1\\end{bmatrix}. \\] <p>\u5141\u8bb8\u7f29\u653e\uff0c\u76f8\u4f3c\u53d8\u6362\u7fa4: Sim (3) 2. \u4eff\u5c04\u53d8\u6362:</p> \\[ T_A=\\begin{bmatrix}A&amp;t\\\\\\mathbf{0}^\\mathrm{T}&amp;1\\end{bmatrix}. \\] <p>\u53ea\u4fdd\u8bc1\u5e73\u884c\u5173\u7cfb 3. \u5c04\u5f71\u53d8\u6362</p> \\[ T_P=\\begin{bmatrix}A&amp;t\\\\\\\\a^\\mathrm{T}&amp;v\\end{bmatrix}. \\] <p>\u603b\u7ed3\u4e00\u4e0b:</p> \\[ \\begin{array}{c|c|c|c}\\hline\\text{\u53d8\u6362\u540d\u79f0}&amp;\\text{\u77e9\u9635\u5f62\u5f0f}&amp;\\text{\u81ea\u7531\u5ea6}&amp;\\text{\u4e0d\u53d8\u6027\u8d28}\\\\\\hline\\text{\u6b27\u6c0f\u53d8\u6362}&amp;\\begin{bmatrix}R&amp;t\\\\0^\\mathrm{T}&amp;1\\end{bmatrix}&amp;6&amp;\\text{\u957f\u5ea6\u3001\u5939\u89d2\u3001\u4f53\u79ef}\\\\\\text{\u76f8\u4f3c\u53d8\u6362}&amp;\\begin{bmatrix}sR&amp;t\\\\0^\\mathrm{T}&amp;1\\end{bmatrix}&amp;7&amp;\\text{\u4f53\u79ef\u6bd4}\\\\\\text{\u4eff\u5c04\u53d8\u6362}&amp;\\begin{bmatrix}A&amp;t\\\\0^\\mathrm{T}&amp;1\\end{bmatrix}&amp;12&amp;\\text{\u5e73\u884c\u6027\u3001\u4f53\u79ef\u6bd4}\\\\\\text{\u5c04\u5f71\u53d8\u6362}&amp;\\begin{bmatrix}A&amp;t\\\\a^\\mathrm{T}&amp;v\\end{bmatrix}&amp;15&amp;\\text{\u63a5\u89e6\u5e73\u9762\u7684\u76f8\u4ea4\u548c\u76f8\u5207}\\\\\\hline\\end{array} \\]"},{"location":"CV/SLAM14/#36-eigen","title":"3.6 \u5b9e\u8df5: Eigen \u51e0\u4f55\u6a21\u5757","text":""},{"location":"CV/SLAM14/#361-eigen","title":"3.6.1 Eigen \u51e0\u4f55\u6a21\u5757\u7684\u6570\u636e\u6f14\u793a","text":"<p>\u518d\u8bf4\u5427\u3002</p>"},{"location":"CV/SLAM14/#362","title":"3.6.2 \u5b9e\u9645\u7684\u5750\u6807\u53d8\u6362\u4f8b\u5b50","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#37","title":"3.7 \u53ef\u89c6\u5316\u6f14\u793a","text":""},{"location":"CV/SLAM14/#371","title":"3.7.1 \u663e\u793a\u8fd0\u52a8\u8f68\u8ff9","text":"<ul> <li>\u7528 Pangolin \u5e93</li> <li>TODO</li> </ul>"},{"location":"CV/SLAM14/#372","title":"3.7.2 \u663e\u793a\u76f8\u673a\u7684\u4f4d\u59ff","text":""},{"location":"CV/SLAM14/#38","title":"3.8 \u4e60\u9898","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#4","title":"4 \u674e\u7fa4\u548c\u674e\u4ee3\u6570","text":"<ul> <li>\u7531\u4e8e\u65cb\u8f6c\u77e9\u9635\u672c\u8eab\u5e26\u6709\u7ea6\u675f\uff08\u6b63\u4ea4\u4e14\u884c\u5217\u5f0f\u4e3a 1\uff09\uff0c\u8ba9\u4f18\u5316\u53d8\u5f97\u56f0\u96be\u3002</li> <li>\u6240\u4ee5\u6211\u4eec\u5f15\u5165\u674e\u7fa4-\u674e\u4ee3\u6570\u95f4\u7684\u8f6c\u6362\u5173\u7cfb\uff0c\u628a\u4f4d\u59ff\u4f30\u8ba1\u53d8\u6210\u65e0\u7ea6\u675f\u7684\u4f18\u5316\u95ee\u9898</li> </ul>"},{"location":"CV/SLAM14/#41","title":"4.1 \u674e\u7fa4\u548c\u674e\u4ee3\u6570\u57fa\u7840","text":"<ul> <li>\u4e09\u7ef4\u65cb\u8f6c\u77e9\u9635\u6784\u6210\u4e86\u7279\u6b8a\u6b63\u4ea4\u7fa4 \\(\\displaystyle \\boldsymbol{SO}(3)\\)</li> <li>\u53d8\u6362\u77e9\u9635\u6784\u6210\u4e86\u7279\u6b8a\u6b27\u6c0f\u7fa4 \\(\\displaystyle \\boldsymbol{SE}(3)\\)<ul> <li>\u4f46\u662f\u4ed6\u4eec\u90fd\u5bf9\u52a0\u6cd5\u4e0d\u5c01\u95ed</li> <li>\u5bf9\u4e58\u6cd5\u5c01\u95ed</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#411","title":"4.1.1 \u7fa4","text":"<ul> <li>\\(\\displaystyle G = (A,\\cdot)\\) \u6ee1\u8db3:<ul> <li>\u5c01\u95ed\u6027</li> <li>\u7ed3\u5408\u5f8b</li> <li>\u5e7a\u5143</li> <li>\u9006</li> </ul> </li> <li>\u674e\u7fa4\u662f\u5177\u6709\u8fde\u7eed\uff08\u5149\u6ed1\uff09\u6027\u8d28\u7684\u7fa4</li> </ul>"},{"location":"CV/SLAM14/#412","title":"4.1.2 \u674e\u4ee3\u6570\u7684\u5f15\u51fa","text":"<ul> <li>\\(\\displaystyle \\boldsymbol{R}\\boldsymbol{R}^\\mathrm{T} = \\boldsymbol{I}\\)</li> <li>\u6211\u4eec\u6613\u5f97: \\(\\displaystyle \\dot{\\boldsymbol{R}}(t)\\boldsymbol{R}(t)^\\mathrm{T}=-\\left(\\dot{\\boldsymbol{R}}(t)\\boldsymbol{R}(t)^\\mathrm{T}\\right)^\\mathrm{T}.\\)<ul> <li>\u5373 \\(\\displaystyle \\dot{\\boldsymbol{R}}(t)\\boldsymbol{R}(t)^\\mathrm{T}\\) \u662f\u53cd\u5bf9\u79f0</li> </ul> </li> <li>\u800c\u5bf9\u4e8e\u4efb\u610f\u53cd\u5bf9\u79f0\u77e9\u9635\uff0c\u6211\u4eec\u90fd\u53ef\u4ee5\u627e\u5230\u552f\u4e00\u4e0e\u4e4b\u5bf9\u5e94\u7684\u5411\u91cf<ul> <li>\\(\\displaystyle \\dot{\\boldsymbol{R}}(t)\\boldsymbol{R}(t)^\\mathrm{T}=\\boldsymbol{\\phi}(t)^{\\wedge}.\\)</li> <li>\\(\\displaystyle \\dot{\\boldsymbol{R}}(t)=\\phi(t)^{\\wedge}\\boldsymbol{R}(t)=\\begin{bmatrix}0&amp;-\\phi_3&amp;\\phi_2\\\\\\phi_3&amp;0&amp;-\\phi_1\\\\-\\phi_2&amp;\\phi_1&amp;0\\end{bmatrix}\\boldsymbol{R}(t).\\) \u8003\u8651 \\(\\displaystyle t_{0} = 0\\) \u548c \\(\\displaystyle \\boldsymbol{R}(0) = \\boldsymbol{I}\\) \u65f6:</li> </ul> </li> </ul> \\[ \\begin{aligned} R(t)&amp; \\approx\\boldsymbol{R}\\left(t_{0}\\right)+\\dot{\\boldsymbol{R}}\\left(t_{0}\\right)\\left(t-t_{0}\\right) \\\\ &amp;=I+\\phi(t_0)^{\\wedge}(t). \\end{aligned} \\] <p>\u4e8e\u662f\u6c42\u5bfc-&gt;\u4e00\u4e2a\u7b97\u7b26 \\(\\displaystyle \\phi\\) \uff0c\u88ab\u79f0\u4e3a \\(\\displaystyle \\boldsymbol{SO}(3)\\) \u539f\u70b9\u9644\u8fd1\u7684\u6b63\u5207\u7a7a\u95f4\uff08Tangent Space\uff09 \u8bbe\u5728 \\(\\displaystyle t_{0}\\) \u9644\u8fd1\uff0c\\(\\displaystyle \\phi\\) \u4fdd\u6301\u5e38\u6570 \\(\\displaystyle \\phi(t_{0})=\\phi_{0}\\)\uff0c</p> \\[ \\dot{\\boldsymbol{R}}(t)=\\boldsymbol{\\phi}(t_0)^\\wedge\\boldsymbol{R}(t)=\\boldsymbol{\\phi}_0^\\wedge\\boldsymbol{R}(t). \\] <p>\u518d\u6709 \\(\\displaystyle \\boldsymbol{R}(0) = \\boldsymbol{I}\\)\uff0c\u89e3\u7684:</p> \\[ \\boldsymbol{R}(t)=\\exp\\left(\\boldsymbol{\\phi}_{0}^{\\wedge}t\\right). \\] <ul> <li>\\(\\displaystyle \\phi\\) \u6b63\u662f\u5bf9\u5e94\u5230 \\(\\displaystyle SO(3)\\) \u4e0a\u7684\u674e\u4ee3\u6570 \\(\\displaystyle \\mathfrak{so}(3)\\)</li> <li>\\(\\displaystyle \\begin{aligned}&amp;\\text{\u5176\u6b21,\u7ed9\u5b9a\u67d0\u4e2a\u5411\u91cf }\\phi\\text{ \u65f6,\u77e9\u9635\u6307\u6570}\\exp(\\phi^{\\wedge})\\text{ \u5982\u4f55\u8ba1\u7b97? \u53cd\u4e4b,\u7ed9\u5b9a }R\\text{ \u65f6,\u80fd\u5426\u6709\u76f8\u53cd}\\\\&amp;\\text{\u7684\u8fd0\u7b97\u6765\u8ba1\u7b97 }\\phi?\\text{ \u4e8b\u5b9e\u4e0a,\u8fd9\u6b63\u662f\u674e\u7fa4\u4e0e\u674e\u4ee3\u6570\u95f4\u7684\u6307\u6570}/\\text{\u5bf9\u6570\u6620\u5c04\u3002}\\end{aligned}\\)</li> </ul>"},{"location":"CV/SLAM14/#413","title":"4.1.3 \u674e\u4ee3\u6570\u7684\u5b9a\u4e49","text":"<p>\u674e\u4ee3\u6570\u7531\u4e00\u4e2a\u96c6\u5408 \\(\\displaystyle \\mathbb{V}\\)\u3001\u4e00\u4e2a\u6570\u57df \\(\\displaystyle \\mathbb{F}\\) \u548c\u4e00\u4e2a\u4e8c\u5143\u8fd0\u7b97 \\(\\displaystyle [,]\\) \u7ec4\u6210\u3002\u5982\u679c\u6ee1\u8db3\u4ee5\u4e0b\u51e0\u6761\u6027\u8d28\uff0c\u5219\u79f0 ( \\(\\displaystyle \\mathbb{V},\\mathbb{F},[,]\\)) \u4e3a\u4e00\u4e2a\u674e\u4ee3\u6570\uff0c\u8bb0\u4f5c \\(\\displaystyle \\mathfrak{g}\\)\u3002</p> <ol> <li>\u5c01\u95ed\u6027</li> <li>\u53cc\u7ebf\u6027</li> <li>\u81ea\u53cd\u6027 \\(\\displaystyle \\quad\\forall \\boldsymbol{X}\\in\\mathbb{V},[\\boldsymbol{X},\\boldsymbol{X}]=0\\)</li> <li>\u96c5\u53ef\u6bd4\u7b49\u4ef7 \\(\\displaystyle \\forall X,Y,Z\\in\\mathbb{V},[X,[Y,Z]]+[Z,[X,Y]]+[Y,[Z,X]]=0.\\) \u5176\u4e2d\u4e8c\u5143\u8fd0\u7b97\u88ab\u79f0\u4e3a\u674e\u62ec\u53f7\u3002 eg: \u53c9\u79ef\u662f\u4e00\u79cd\u674e\u62ec\u53f7</li> </ol>"},{"location":"CV/SLAM14/#414-displaystyle-mathfrakso3","title":"4.1.4 \u674e\u4ee3\u6570 \\(\\displaystyle \\mathfrak{so}(3)\\)","text":"<p>\\(\\displaystyle \\boldsymbol{\\Phi}=\\boldsymbol{\\phi}^{\\wedge}=\\begin{bmatrix}0&amp;-\\phi_3&amp;\\phi_2\\\\\\\\\\phi_3&amp;0&amp;-\\phi_1\\\\\\\\-\\phi_2&amp;\\phi_1&amp;0\\end{bmatrix}\\in\\mathbb{R}^{3\\times3}.\\) \u6240\u4ee5\u4e24\u4e2a\u5411\u91cf \\(\\displaystyle \\phi_{1},\\phi_{2}\\) \u7684\u674e\u62ec\u53f7\u4e3a:</p> \\[ [\\phi_1,\\phi_2]=(\\boldsymbol{\\Phi}_1\\boldsymbol{\\Phi}_2-\\boldsymbol{\\Phi}_2\\boldsymbol{\\Phi}_1)^\\vee. \\] \\[ \\mathfrak{so}(3)=\\left\\{\\phi\\in\\mathbb{R}^3,\\boldsymbol{\\Phi}=\\phi^\\wedge\\in\\mathbb{R}^{3\\times3}\\right\\}. \\] \\[ R=\\exp(\\phi^{\\wedge}). \\]"},{"location":"CV/SLAM14/#415-displaystyle-mathfrakse3","title":"4.1.5 \u674e\u4ee3\u6570 \\(\\displaystyle \\mathfrak{se}(3)\\)","text":"\\[ \\mathfrak{se}(3)=\\left\\{\\boldsymbol{\\xi}=\\begin{bmatrix}\\boldsymbol{\\rho}\\\\\\boldsymbol{\\phi}\\end{bmatrix}\\in\\mathbb{R}^6,\\boldsymbol{\\rho}\\in\\mathbb{R}^3,\\boldsymbol{\\phi}\\in\\mathfrak{so}(3),\\boldsymbol{\\xi}^\\wedge=\\begin{bmatrix}\\boldsymbol{\\phi}^\\wedge&amp;\\boldsymbol{\\rho}\\\\\\boldsymbol{0}^\\mathrm{T}&amp;0\\end{bmatrix}\\in\\mathbb{R}^{4\\times4}\\right\\}. \\] <p>\u524d\u4e09\u7ef4\u4e3a\u5e73\u79fb\uff0c\u540e\u4e09\u7ef4\u4e3a\u65cb\u8f6c\uff08\u5b9e\u8d28\u4e0a\u662f \\(\\displaystyle \\mathfrak{so}(3)\\) \u5143\u7d20\uff09</p> \\[ \\xi^\\wedge=\\begin{bmatrix}\\phi^\\wedge&amp;\\rho\\\\0^\\mathrm{T}&amp;0\\end{bmatrix}\\in\\mathbb{R}^{4\\times4}. \\] <p>\u540c\u6837\u674e\u4ee3\u6570 \\(\\displaystyle \\mathfrak{se}(3)\\) \u4e5f\u6709\u7c7b\u4f3c\u4e8e \\(\\displaystyle \\mathfrak{so}(3)\\) \u7684\u674e\u62ec\u53f7:</p> \\[ [\\xi_1,\\xi_2]=\\left(\\xi_1^\\wedge\\xi_2^\\wedge-\\xi_2^\\wedge\\xi_1^\\wedge\\right)^\\vee. \\]"},{"location":"CV/SLAM14/#42","title":"4.2 \u6307\u6570\u4e0e\u5bf9\u6570\u6620\u5c04","text":""},{"location":"CV/SLAM14/#421-so3","title":"4.2.1 SO(3)\u4e0a\u7684\u6307\u6570\u6620\u5c04","text":"<ul> <li>Exponential Map</li> <li>\u9996\u5148\u4efb\u610f\u77e9\u9635\u7684\u6307\u6570\u6620\u5c04\u53ef\u4ee5\u5199\u6210\u4e00\u4e2a\u6cf0\u52d2\u5c55\u5f00\uff08\u6536\u655b\u7684\u65f6\u5019\uff09</li> </ul> \\[ \\exp(A)=\\sum_{n=0}^\\infty\\frac1{n!}A^n. \\] <ul> <li>\u5e94\u7528\u5230 \\(\\displaystyle \\mathfrak{so}(3)\\) \u4e2d:</li> </ul> \\[ \\exp(\\phi^\\wedge)=\\sum_{n=0}^\\infty\\frac{1}{n!}(\\phi^\\wedge)^n. \\] <ul> <li>\u6211\u4eec\u53ef\u4ee5\u628a \\(\\displaystyle \\phi\\) \u8868\u793a\u6210 \\(\\displaystyle \\theta \\boldsymbol{a}\\)\uff0c\u5bf9\u4e8e \\(\\displaystyle \\boldsymbol{a}^\\wedge\\):</li> </ul> \\[ \\boldsymbol{a}^{\\wedge}\\boldsymbol{a}^{\\wedge}=\\begin{bmatrix}-a_2^2-a_3^2&amp;a_1a_2&amp;a_1a_3\\\\\\\\a_1a_2&amp;-a_1^2-a_3^2&amp;a_2a_3\\\\\\\\a_1a_3&amp;a_2a_3&amp;-a_1^2-a_2^2\\end{bmatrix}=\\boldsymbol{a}\\boldsymbol{a}^\\mathrm{T}-\\boldsymbol{I}, \\] <p>\u548c</p> \\[ a^{\\wedge}a^{\\wedge}a^{\\wedge}=a^{\\wedge}(aa^{\\mathrm{T}}-I)=-a^{\\wedge}. \\] <p>\u4e8e\u662f\u6211\u4eec\u53ef\u4ee5\u5316\u7b80:</p> \\[ \\begin{aligned} \\exp\\left(\\phi^\\wedge\\right)&amp; =\\exp\\left(\\theta\\boldsymbol{a}^\\wedge\\right)=\\sum_{n=0}^\\infty\\frac1{n!}\\left(\\theta\\boldsymbol{a}^\\wedge\\right)^n \\\\ &amp;=I+\\theta\\boldsymbol{a}^{\\wedge}+\\frac{1}{2!}\\theta^{2}\\boldsymbol{a}^{\\wedge}\\boldsymbol{a}^{\\wedge}+\\frac{1}{3!}\\theta^{3}\\boldsymbol{a}^{\\wedge}\\boldsymbol{a}^{\\wedge}\\boldsymbol{a}^{\\wedge}+\\frac{1}{4!}\\theta^{4}(\\boldsymbol{a}^{\\wedge})^{4}+\\cdots \\\\ &amp;=\\boldsymbol{a}\\boldsymbol{a}^{\\mathrm{T}}-\\boldsymbol{a}^{\\wedge}\\boldsymbol{a}^{\\wedge}+\\theta\\boldsymbol{a}^{\\wedge}+\\frac{1}{2!}\\theta^{2}\\boldsymbol{a}^{\\wedge}\\boldsymbol{a}^{\\wedge}-\\frac{1}{3!}\\theta^{3}\\boldsymbol{a}^{\\wedge}-\\frac{1}{4!}\\theta^{4}(\\boldsymbol{a}^{\\wedge})^{2}+\\cdots \\\\ &amp;=\\boldsymbol{a}\\boldsymbol{a}^{\\mathsf{T}}+\\underbrace{\\left(\\theta-\\frac{1}{3!}\\theta^{3}+\\frac{1}{5!}\\theta^{5}-\\cdots\\right)}_{\\sin\\theta}\\boldsymbol{a}^{\\wedge}-\\underbrace{\\left(1-\\frac{1}{2!}\\theta^{2}+\\frac{1}{4!}\\theta^{4}-\\cdots\\right)}_{\\cos\\theta}\\boldsymbol{a}^{\\wedge}\\boldsymbol{a}^{\\wedge} \\\\ &amp;=a^\\wedge a^\\wedge+I+\\sin\\theta a^\\wedge-\\cos\\theta a^\\wedge a^\\wedge \\\\ &amp;=(1-\\cos\\theta)\\boldsymbol{a}^\\wedge\\boldsymbol{a}^\\wedge+\\boldsymbol{I}+\\sin\\theta\\boldsymbol{a}^\\wedge \\\\ &amp;=\\cos\\theta\\boldsymbol{I}+(1-\\cos\\theta)\\boldsymbol{aa}^\\mathrm{T}+\\sin\\theta\\boldsymbol{a}^\\mathrm{\\wedge}. \\end{aligned} \\] <p>\u6700\u540e\u5f97\u5230:</p> \\[ \\exp(\\theta\\boldsymbol{a}^\\wedge)=\\cos\\theta\\boldsymbol{I}+(1-\\cos\\theta)\\boldsymbol{a}\\boldsymbol{a}^\\mathrm{T}+\\sin\\theta\\boldsymbol{a}^\\wedge. \\] <p>\u6240\u4ee5 \\(\\displaystyle \\mathfrak{so}(3)\\) \u5c31\u662f\u65cb\u91cf\u5411\u91cf\u7ec4\u6210\u7684\u7a7a\u95f4\uff0c\u800c\u6307\u6570\u6620\u5c04\u5373\u7f57\u5fb7\u91cc\u683c\u65af\u516c\u5f0f\u3002</p> <ul> <li>\u901a\u8fc7\u4e0a\u9762\u7684\u516c\u5f0f\uff0c\u6211\u4eec\u53ef\u4ee5\u628a \\(\\displaystyle \\mathfrak{so}(3)\\) \u4e2d\u4efb\u610f\u5411\u91cf\u5bf9\u5e94\u5230 SO (3) \u4e2d\u7684\u65cb\u8f6c\u77e9\u9635</li> <li>\u53cd\u8fc7\u6765\u4e5f\u662f\u53ef\u4ee5\u7684</li> </ul> \\[ \\phi=\\ln\\left(\\boldsymbol{R}\\right)^\\vee=\\left(\\sum_{n=0}^\\infty\\frac{\\left(-1\\right)^n}{n+1}\\left(\\boldsymbol{R}-\\boldsymbol{I}\\right)^{n+1}\\right)^\\vee. \\]"},{"location":"CV/SLAM14/#422-se-3","title":"4.2.2 SE (3) \u4e0a\u7684\u6307\u6570\u6620\u5c04","text":"<p>\u540c\u6837\u7684\u63a8\u5bfc\u65b9\u5f0f:</p> \\[ \\begin{aligned} \\exp\\left(\\xi^{\\wedge}\\right)&amp; =\\begin{bmatrix}\\sum_{n=0}^{\\infty}\\frac{1}{n!}(\\phi^{\\wedge})^{n}&amp;\\sum_{n=0}^{\\infty}\\frac{1}{(n+1)!}(\\phi^{\\wedge})^{n}\\rho\\\\\\\\\\mathbf{0}^{\\mathrm{T}}&amp;1\\end{bmatrix} \\\\ &amp;\\stackrel{\\Delta}{=}\\begin{bmatrix}R&amp;J\\rho\\\\\\\\0^\\mathrm{T}&amp;1\\end{bmatrix}=T. \\end{aligned} \\] \\[ \\begin{aligned} \\sum_{n=0}^{\\infty}\\frac{1}{(n+1)!}(\\phi^{\\wedge})^{n}&amp; =\\boldsymbol{I}+\\frac{1}{2!}\\theta\\boldsymbol{a}^{\\wedge}+\\frac{1}{3!}\\theta^{2}{(\\boldsymbol{a}^{\\wedge})}^{2}+\\frac{1}{4!}\\theta^{3}{(\\boldsymbol{a}^{\\wedge})}^{3}+\\frac{1}{5!}\\theta^{4}{(\\boldsymbol{a}^{\\wedge})}^{4}\\cdots  \\\\ &amp;=\\frac{1}{\\theta}\\left(\\frac{1}{2!}\\theta^{2}-\\frac{1}{4!}\\theta^{4}+\\cdots\\right)(\\boldsymbol{a}^{\\wedge})+\\frac{1}{\\theta}\\left(\\frac{1}{3!}\\theta^{3}-\\frac{1}{5}\\theta^{5}+\\cdots\\right)(\\boldsymbol{a}^{\\wedge})^{2}+\\boldsymbol{I} \\\\ &amp;=\\frac1\\theta\\left(1-\\cos\\theta\\right)\\left(\\boldsymbol{a}^{\\wedge}\\right)+\\frac{\\theta-\\sin\\theta}\\theta\\left(\\boldsymbol{a}\\boldsymbol{a}^{\\mathrm{T}}-\\boldsymbol{I}\\right)+\\boldsymbol{I} \\\\ &amp;=\\frac{\\sin\\theta}\\theta\\boldsymbol{I}+\\left(1-\\frac{\\sin\\theta}\\theta\\right)\\boldsymbol{aa}^\\mathrm{T}+\\frac{1-\\cos\\theta}\\theta\\boldsymbol{a}^\\mathrm{\\wedge}\\overset{\\mathrm{def}}{\\operatorname*{=}}\\boldsymbol{J}. \\end{aligned} \\] \\[ \\boldsymbol{J}=\\frac{\\sin\\theta}{\\theta}\\boldsymbol{I}+\\left(1-\\frac{\\sin\\theta}{\\theta}\\right)\\boldsymbol{a}\\boldsymbol{a}^\\mathrm{T}+\\frac{1-\\cos\\theta}{\\theta}\\boldsymbol{a}^\\mathrm{\\wedge}. \\] <p>4.28 \u6ca1\u770b\u61c2 </p>"},{"location":"CV/SLAM14/#43","title":"4.3 \u674e\u4ee3\u6570\u6c42\u5bfc\u4e0e\u6270\u52a8\u6a21\u578b","text":""},{"location":"CV/SLAM14/#431-bch","title":"4.3.1 BCH \u516c\u5f0f\u4e0e\u8fd1\u4f3c\u5f62\u5f0f","text":"<p>\u63a2\u7a76\u5982\u4e0b\u5f0f\u5b50\u662f\u5426\u6210\u7acb:</p> \\[ \\ln\\left(\\exp\\left(A\\right)\\exp\\left(B\\right)\\right)=A+B ? \\] <p>\u4f46\u5b83\u5e76\u4e0d\u6210\u7acb\u3002\u4e24\u4e2a\u674e\u4ee3\u6570\u6307\u6570\u6620\u5c04\u4e58\u79ef\u7684\u5b8c\u6574\u5f62\u5f0f\uff0c\u7531 Baker-Campbell-Hausdorff \u7ed9\u51fa:</p> \\[ \\ln\\left(\\exp\\left(A\\right)\\exp\\left(B\\right)\\right)=A+B+\\frac{1}{2}\\left[A,B\\right]+\\frac{1}{12}\\left[A,\\left[A,B\\right]\\right]-\\frac{1}{12}\\left[B,\\left[A,B\\right]\\right]+\\cdots \\] <p>\u7279\u522b\u7684\uff0c\u5f53 \\(\\displaystyle \\phi_{1}\\) \u6216 \\(\\displaystyle \\phi_{2}\\) \u4e3a\u5c0f\u91cf\u65f6\uff0c\u5c0f\u91cf\u4e8c\u6b21\u4ee5\u4e0a\u7684\u9879\u90fd\u53ef\u4ee5\u88ab\u5ffd\u7565\uff0c\u6b64\u65f6\u7684\u7ebf\u6027\u8fd1\u4f3c\u8868\u8fbe:</p> \\[ \\ln\\left(\\exp\\left(\\phi_1^\\wedge\\right)\\exp\\left(\\phi_2^\\wedge\\right)\\right)^\\vee\\approx\\begin{cases}J_l(\\phi_2)^{-1}\\phi_1+\\phi_2&amp;\\text{\u5f53}\\phi_1\\text{\u4e3a\u5c0f\u91cf},\\\\J_r(\\phi_1)^{-1}\\phi_2+\\phi_1&amp;\\text{\u5f53}\\phi_2\\text{\u4e3a\u5c0f\u91cf}.\\end{cases} \\] \\[ \\boldsymbol{J}_{l}=\\frac{\\sin\\theta}{\\theta}\\boldsymbol{I}+\\left(1-\\frac{\\sin\\theta}{\\theta}\\right)\\boldsymbol{a}\\boldsymbol{a}^\\mathrm{T}+\\frac{1-\\cos\\theta}{\\theta}\\boldsymbol{a}^\\mathrm{\\wedge}. \\] \\[ \\boldsymbol{J}_{\\ell}^{-1}=\\frac{\\theta}{2}\\cot\\frac{\\theta}{2}\\boldsymbol{I}+\\left(1-\\frac{\\theta}{2}\\cot\\frac{\\theta}{2}\\right)\\boldsymbol{a}\\boldsymbol{a}^{\\mathrm{T}}-\\frac{\\theta}{2}\\boldsymbol{a}^{\\wedge}. \\] \\[ J_{r}(\\phi)=J_{l}(-\\phi). \\] <p>\u4e8e\u662f\u6211\u4eec\u5c31\u53ef\u4ee5\u8c08\u8bba\u674e\u7fa4\u4e58\u6cd5\u4e0e\u674e\u4ee3\u6570\u52a0\u6cd5\u7684\u5173\u7cfb\u4e86\u3002 \\(\\displaystyle \\boldsymbol{R}\\) \u5bf9\u5e94 \\(\\displaystyle \\phi\\)\uff0c\u6211\u4eec\u7ed9\u5b83\u5de6\u4e58\u4e00\u4e2a\u5fae\u5c0f\u65cb\u8f6c\uff0c\u8bb0\u4f5c \\(\\displaystyle \\Delta \\boldsymbol{R}\\)</p> \\[ \\exp\\left(\\Delta\\phi^{\\wedge}\\right)\\exp\\left(\\phi^{\\wedge}\\right)=\\exp\\left(\\left(\\phi+J_{l}^{-1}\\left(\\phi\\right)\\Delta\\phi\\right)^{\\wedge}\\right). \\] \\[ \\exp\\left(\\left(\\phi+\\Delta\\phi\\right)^{\\wedge}\\right)=\\exp\\left(\\left(J_{l}\\Delta\\phi\\right)^{\\wedge}\\right)\\exp\\left(\\phi^{\\wedge}\\right)=\\exp\\left(\\phi^{\\wedge}\\right)\\exp\\left(\\left(J_{r}\\Delta\\phi\\right)^{\\wedge}\\right). \\] <p>\u5bf9\u4e8e SE (3) \u6211\u4eec\u4e5f\u6709:</p> \\[ \\exp\\left(\\Delta\\xi^{\\wedge}\\right)\\exp\\left(\\xi^{\\wedge}\\right)\\approx\\exp\\left(\\left(\\mathcal{J}_{l}^{-1}\\Delta\\xi+\\xi\\right)^{\\wedge}\\right) \\] \\[ exp\\left(\\xi^{\\wedge}\\right)\\exp\\left(\\Delta\\xi^{\\wedge}\\right)\\approx\\exp\\left(\\left(\\mathcal{J}_{r}^{-1}\\Delta\\xi+\\xi\\right)^{\\wedge}\\right). \\] <p>\u552f\u4e00\u4e0d\u540c\u7684\u662f\u8fd9\u91cc\u7684 \\(\\displaystyle J_{l}\\) \u6bd4\u8f83\u590d\u6742\u3002</p>"},{"location":"CV/SLAM14/#432-so-3","title":"4.3.2 SO (3) \u4e0a\u7684\u674e\u4ee3\u6570\u6c42\u5bfc","text":"\\[ z=T\\boldsymbol{p}+\\boldsymbol{w}. \\] <p>\u5176\u4e2d \\(\\displaystyle \\boldsymbol{w}\\) \u662f\u968f\u673a\u566a\u58f0\u3002</p> \\[ e=z-Tp. \\] <p>\u5047\u8bbe\u4e00\u5171\u6709 N \u4e2a\u8fd9\u6837\u7684\u8def\u6807\u70b9\u548c\u89c2\u6d4b:</p> \\[ \\min_{\\boldsymbol{T}}J(\\boldsymbol{T})=\\sum_{i=1}^N\\left\\|\\boldsymbol{z}_i-\\boldsymbol{T}\\boldsymbol{p}_i\\right\\|_2^2. \\] <p>most importantly\uff0c\u6211\u4eec\u4f1a\u6784\u5efa\u4e0e\u4f4d\u59ff\u6709\u5173\u7684\u51fd\u6570\uff0c\u5e76\u8ba8\u8bba\u8be5\u51fd\u6570\u5173\u4e8e\u4f4d\u59ff\u7684\u5bfc\u6570\uff0c\u4ee5\u8c03\u6574\u5f53\u524d\u7684\u4f30\u8ba1\u503c\u3002 \u4f7f\u7528\u674e\u4ee3\u6570\u89e3\u51b3\u6c42\u5bfc\u95ee\u9898\u7684\u601d\u8def\u5206\u4e3a\u4e24\u79cd:</p> <ol> <li>\u7528\u674e\u4ee3\u6570\u8868\u793a\u59ff\u6001\uff0c\u7136\u540e\u6839\u636e\u674e\u4ee3\u6570\u52a0\u6cd5\u5bf9\u674e\u4ee3\u6570\u6c42\u5bfc\u3002</li> <li>\u5bf9\u674e\u7fa4\u5de6\u4e58\u6216\u53f3\u4e58\u5fae\u5c0f\u6270\u52a8\uff0c\u7136\u540e\u5bf9\u8be5\u6270\u52a8\u6c42\u5bfc\uff0c\u79f0\u4e3a\u5de6\u6270\u52a8\u548c\u53f3\u6270\u52a8\u6a21\u578b\u3002</li> </ol>"},{"location":"CV/SLAM14/#44","title":"4.4 \u674e\u4ee3\u6570\u6c42\u5bfc","text":"<p>\u8981\u8ba1\u7b97 \\(\\displaystyle \\frac{\\partial\\left(Rp\\right)}{\\partial R}\\), \u7531\u4e8eSO\uff083\uff09\u6ca1\u6709\u52a0\u6cd5\uff0c\u6211\u4eec\u8f6c\u800c\u8ba1\u7b97: \\(\\displaystyle \\frac{\\partial\\left(\\exp\\left(\\phi^{\\wedge}\\right)\\boldsymbol{p}\\right)}{\\partial\\boldsymbol{\\phi}}.\\)</p> \\[ \\begin{aligned} \\frac{\\partial\\left(\\exp\\left(\\phi^{\\wedge}\\right)\\boldsymbol{p}\\right)}{\\partial\\phi}&amp; =\\lim_{\\delta\\boldsymbol{\\phi}\\to0}\\frac{\\exp\\left(\\left(\\boldsymbol{\\phi}+\\delta\\boldsymbol{\\phi}\\right)^{\\wedge}\\right)\\boldsymbol{p}-\\exp\\left(\\boldsymbol{\\phi}^{\\wedge}\\right)\\boldsymbol{p}}{\\delta\\boldsymbol{\\phi}} \\\\ &amp;=\\lim_{\\delta\\phi\\to0}\\frac{\\exp\\left(\\left(\\boldsymbol{J}_i\\delta\\boldsymbol{\\phi}\\right)^\\wedge\\right)\\exp\\left(\\boldsymbol{\\phi}^\\wedge\\right)\\boldsymbol{p}-\\exp\\left(\\boldsymbol{\\phi}^\\wedge\\right)\\boldsymbol{p}}{\\delta\\boldsymbol{\\phi}} \\\\ &amp;=\\lim_{\\delta\\phi\\to0}\\frac{\\left(\\boldsymbol{I}+\\left(\\boldsymbol{J}_{l}\\delta\\boldsymbol{\\phi}\\right)^{\\wedge}\\right)\\exp\\left(\\boldsymbol{\\phi}^{\\wedge}\\right)\\boldsymbol{p}-\\exp\\left(\\boldsymbol{\\phi}^{\\wedge}\\right)\\boldsymbol{p}}{\\delta\\phi} \\\\ &amp;=\\lim_{\\delta\\phi\\to0}\\frac{\\left(\\boldsymbol{J}_{l}\\delta\\phi\\right)^{\\wedge}\\exp\\left(\\boldsymbol{\\phi}^{\\wedge}\\right)\\boldsymbol{p}}{\\delta\\phi} \\\\ &amp;=\\lim_{\\delta\\boldsymbol{\\phi}\\to0}\\frac{-(\\exp\\left(\\boldsymbol{\\phi}^{\\wedge}\\right)\\boldsymbol{p})^{\\wedge}\\boldsymbol{J}_{l}\\delta\\boldsymbol{\\phi}}{\\delta\\boldsymbol{\\phi}}=-(\\boldsymbol{R}\\boldsymbol{p})^{\\wedge}\\boldsymbol{J}_{l}. \\end{aligned} \\] <p>BCH \u7ebf\u6027\u8fd1\u4f3c+\u6cf0\u52d2\u5c55\u5f00\u53d6\u7ebf\u6027\u9879:</p> \\[ \\frac{\\partial\\left(\\boldsymbol{Rp}\\right)}{\\partial\\boldsymbol{\\phi}}=\\left(-\\boldsymbol{Rp}\\right)^{\\wedge}\\boldsymbol{J}_{l}. \\] <p>\u4f46\u662f\u8fd9\u91cc\u4ecd\u7136\u6709 \\(\\displaystyle \\boldsymbol{J}_{l}\\)</p>"},{"location":"CV/SLAM14/#441","title":"4.4.1 \u6270\u52a8\u6a21\u578b\uff08\u5de6\u4e58\uff09","text":"<p>\\(\\displaystyle \\varphi\\) \u5bf9\u5e94\u5de6\u6270\u52a8 \\(\\displaystyle \\Delta \\boldsymbol{R}\\)</p> \\[ \\begin{aligned} \\frac{\\partial\\left(Rp\\right)}{\\partial\\varphi}&amp; =\\lim_{\\varphi\\to0}\\frac{\\exp\\left(\\varphi^{\\wedge}\\right)\\exp\\left(\\phi^{\\wedge}\\right)p-\\exp\\left(\\phi^{\\wedge}\\right)p}{\\varphi} \\\\ &amp;=\\lim_{\\varphi\\to0}\\frac{(\\boldsymbol{I}+\\boldsymbol{\\varphi}^{\\wedge})\\exp\\left(\\boldsymbol{\\phi}^{\\wedge}\\right)\\boldsymbol{p}-\\exp\\left(\\boldsymbol{\\phi}^{\\wedge}\\right)\\boldsymbol{p}}{\\varphi} \\\\ &amp;=\\lim_{\\varphi\\to0}\\frac{\\varphi^\\wedge Rp}\\varphi=\\lim_{\\varphi\\to0}\\frac{-\\left(Rp\\right)^\\wedge\\varphi}\\varphi=-\\left(Rp\\right)^\\wedge. \\end{aligned} \\]"},{"location":"CV/SLAM14/#442-se-3","title":"4.4.2 SE (3) \u4e0a\u7684\u674e\u4ee3\u6570\u6c42\u5bfc","text":"\\[ \\begin{aligned} \\frac{\\partial\\left(\\boldsymbol{T}\\boldsymbol{p}\\right)}{\\partial\\delta\\boldsymbol{\\xi}}&amp;=\\lim_{\\delta\\boldsymbol{\\xi}\\to\\boldsymbol{0}}\\frac{\\exp\\left(\\delta\\boldsymbol{\\xi}^{\\wedge}\\right)\\exp\\left(\\boldsymbol{\\xi}^{\\wedge}\\right)\\boldsymbol{p}-\\exp\\left(\\boldsymbol{\\xi}^{\\wedge}\\right)\\boldsymbol{p}}{\\delta\\xi} \\\\ &amp;=\\lim_{\\delta\\boldsymbol{\\xi}\\to\\mathbf{0}}\\frac{\\left(\\boldsymbol{I}+\\delta\\boldsymbol{\\xi}^{\\wedge}\\right)\\exp\\left(\\boldsymbol{\\xi}^{\\wedge}\\right)\\boldsymbol{p}-\\exp\\left(\\boldsymbol{\\xi}^{\\wedge}\\right)\\boldsymbol{p}}{\\delta\\boldsymbol{\\xi}} \\\\ &amp;=\\lim_{\\delta\\boldsymbol{\\xi}\\to0}\\frac{\\delta\\boldsymbol{\\xi}^{\\wedge}\\exp\\left(\\boldsymbol{\\xi}^{\\wedge}\\right)\\boldsymbol{p}}{\\delta\\boldsymbol{\\xi}} \\\\ &amp;=\\lim_{\\delta\\boldsymbol{\\xi}\\to\\mathbf{0}}\\frac{\\begin{bmatrix}\\delta\\boldsymbol{\\phi}^\\wedge&amp;\\delta\\boldsymbol{\\rho}\\\\\\\\\\mathbf{0}^\\mathrm{T}&amp;0\\end{bmatrix}\\begin{bmatrix}\\boldsymbol{R}\\boldsymbol{p}+\\boldsymbol{t}\\\\\\\\1\\end{bmatrix}}{\\delta\\boldsymbol{\\xi}} \\\\ &amp;=\\lim_{\\delta\\boldsymbol{\\xi}\\to\\boldsymbol{0}}\\frac{\\begin{bmatrix}\\delta\\boldsymbol{\\phi}^{\\wedge}\\left(\\boldsymbol{R}\\boldsymbol{p}+\\boldsymbol{t}\\right)+\\delta\\boldsymbol{\\rho}\\\\\\boldsymbol{0}^{\\mathrm{T}}\\end{bmatrix}}{[\\delta\\boldsymbol{\\rho},\\delta\\boldsymbol{\\phi}]^{\\mathrm{T}}}=\\begin{bmatrix}\\boldsymbol{I}&amp;-(\\boldsymbol{R}\\boldsymbol{p}+\\boldsymbol{t})^{\\wedge}\\\\\\boldsymbol{0}^{\\mathrm{T}}&amp;\\boldsymbol{0}^{\\mathrm{T}}\\end{bmatrix}\\stackrel{\\mathrm{def}}{=}(\\boldsymbol{T}\\boldsymbol{p})^{\\odot}. \\end{aligned} \\] \\[ \\frac{\\mathrm{d}\\begin{bmatrix}a\\\\b\\end{bmatrix}}{\\mathrm{d}\\begin{bmatrix}x\\\\y\\end{bmatrix}}=\\left(\\frac{\\mathrm{d}[a,b]^\\mathrm{T}}{\\mathrm{d}\\begin{bmatrix}x\\\\y\\end{bmatrix}}\\right)^\\mathrm{T}=\\begin{bmatrix}\\frac{\\mathrm{d}a}{\\mathrm{d}x}&amp;\\frac{\\mathrm{d}b}{\\mathrm{d}x}\\\\\\frac{\\mathrm{d}a}{\\mathrm{d}y}&amp;\\frac{\\mathrm{d}b}{\\mathrm{d}y}\\end{bmatrix}^\\mathrm{T}=\\begin{bmatrix}\\frac{\\mathrm{d}a}{\\mathrm{d}x}&amp;\\frac{\\mathrm{d}a}{\\mathrm{d}y}\\\\\\frac{\\mathrm{d}b}{\\mathrm{d}x}&amp;\\frac{\\mathrm{d}b}{\\mathrm{d}y}\\end{bmatrix} \\]"},{"location":"CV/SLAM14/#45-sophus","title":"4.5 \u5b9e\u8df5:Sophus","text":""},{"location":"CV/SLAM14/#451-sophus","title":"4.5.1 Sophus \u7684\u57fa\u672c\u4f7f\u7528\u65b9\u6cd5","text":""},{"location":"CV/SLAM14/#452","title":"4.5.2 \u4f8b\u5b50: \u8bc4\u4f30\u8f68\u8ff9\u7684\u8bef\u5dee","text":"<ul> <li>\u7edd\u5bf9\u8f68\u8ff9\u8bef\u5dee\uff08Absolute Trajectory Error, ATE\uff09</li> </ul> \\[ \\mathrm{ATE}_{\\mathrm{all}}=\\sqrt{\\frac{1}{N}\\sum_{i=1}^{N}\\|\\log(T_{\\mathrm{gt},i}^{-1}T_{\\mathrm{esti},i})^{\\vee}\\|_{2}^{2}}, \\] <p>\u5373\u5747\u65b9\u6839\u8bef\u5dee\uff08Root-Mean-Squared Error, RMSE\uff09</p> <ul> <li>\u7edd\u5bf9\u5e73\u79fb\u8bef\u5dee\uff08Average Translational Error\uff09</li> </ul> \\[ \\mathrm{ATE}_{\\mathrm{all}}=\\sqrt{\\frac{1}{N}\\sum_{i=1}^{N}\\|\\log(T_{\\mathrm{gt},i}^{-1}T_{\\mathrm{esti},i})^{\\vee}\\|_{2}^{2}}, \\] <ul> <li>\u76f8\u5bf9\u4f4d\u59ff\u8bef\u5dee\uff08Relative Pose Error, RPE\uff09</li> </ul> \\[ \\mathrm{RPE}_{\\mathrm{all}}=\\sqrt{\\frac{1}{N-\\Delta t}\\sum_{i=1}^{N-\\Delta t}\\|\\log\\left(\\left(\\boldsymbol{T}_{\\mathrm{gt},i}^{-1}\\boldsymbol{T}_{\\mathrm{gt},i+\\Delta t}\\right)\\right)^{-1}\\left(\\boldsymbol{T}_{\\mathrm{est},i}^{-1}\\boldsymbol{T}_{\\mathrm{est},i+\\Delta t}\\right))^{\\vee}\\|_{2}^{2}}, \\] \\[ \\mathrm{RPE}_{\\mathrm{trans}}=\\sqrt{\\frac{1}{N-\\Delta t}\\sum_{i=1}^{N-\\Delta t}\\|\\mathrm{trans}\\left(\\left(T_{gt,i}^{-1}T_{gt,i+\\Delta t}\\right)\\right)^{-1}\\left(T_{\\mathrm{esti},i}^{-1}T_{\\mathrm{esti},i+\\Delta t}\\right))\\|_{2}^{2}}. \\] <p>\u4ee3\u7801\u8ba1\u7b97:</p> Text Only<pre><code>TODO\n</code></pre>"},{"location":"CV/SLAM14/#46","title":"4.6 \u76f8\u4f3c\u53d8\u6362\u4e0e\u674e\u4ee3\u6570","text":"<p>\u5728\u8fd9\u91cc\u6211\u4eec\u8ba8\u8bba Sim (3) \u548c\u5bf9\u5e94\u7684\u674e\u4ee3\u6570 \\(\\displaystyle \\mathfrak{sim}(3)\\)\u3002 \u5bf9\u4e8e\u4f4d\u4e8e\u7a7a\u95f4\u7684\u70b9 \\(\\displaystyle \\boldsymbol{p}\\)\uff0c\u5728\u76f8\u673a\u5750\u6807\u7cfb\u4e0b\u8981\u7ecf\u8fc7\u4e00\u4e2a\u76f8\u4f3c\u53d8\u6362\uff0c\u800c\u975e\u6b27\u6c0f\u53d8\u6362:</p> \\[ \\boldsymbol{p}'=\\begin{bmatrix}s\\boldsymbol{R}&amp;\\boldsymbol{t}\\\\\\boldsymbol{0}^\\mathrm{T}&amp;1\\end{bmatrix}\\boldsymbol{p}=s\\boldsymbol{R}\\boldsymbol{p}+\\boldsymbol{t}. \\] \\[ \\mathrm{Sim}(3)=\\left\\{S=\\begin{bmatrix}sR&amp;t\\\\\\\\\\mathbf{0}^\\mathrm{T}&amp;1\\end{bmatrix}\\in\\mathbb{R}^{4\\times4}\\right\\}. \\] \\[ \\sin(3)=\\left\\{\\zeta|\\zeta=\\begin{bmatrix}\\rho\\\\\\\\\\phi\\\\\\\\\\sigma\\end{bmatrix}\\in\\mathbb{R}^7,\\zeta^\\wedge=\\begin{bmatrix}\\sigma\\boldsymbol{I}+\\phi^\\wedge&amp;\\rho\\\\\\\\\\mathbf{0}^\\mathrm{T}&amp;0\\end{bmatrix}\\in\\mathbb{R}^{4\\times4}\\right\\}. \\] \\[ \\exp\\left(\\zeta^{\\wedge}\\right)=\\begin{bmatrix}\\mathrm{e}^{\\sigma}\\exp\\left(\\phi^{\\wedge}\\right)&amp;J_{s}\\rho\\\\0^{\\mathrm{T}}&amp;1\\end{bmatrix}. \\] <p>\u5176\u4e2d\uff0c\\(\\displaystyle \\boldsymbol{J}_{S}\\) \u7684\u5f62\u5f0f\u662f:</p> \\[ \\begin{aligned} \\text{J}&amp; =\\frac{\\mathrm{e}^{\\sigma}-1}{\\sigma}I+\\frac{\\sigma\\mathrm{e}^{\\sigma}\\sin\\theta+\\left(1-\\mathrm{e}^{\\sigma}\\cos\\theta\\right)\\theta}{\\sigma^{2}+\\theta^{2}}\\boldsymbol{a}^{\\wedge} \\\\ &amp;+\\left(\\frac{\\mathrm{e}^\\sigma-1}{\\sigma}-\\frac{\\left(\\mathrm{e}^\\sigma\\cos\\theta-1\\right)\\sigma+\\left(\\mathrm{e}^\\sigma\\sin\\theta\\right)\\theta}{\\sigma^2+\\theta^2}\\right)\\boldsymbol{a}^\\wedge\\boldsymbol{a}^\\wedge. \\end{aligned} \\] <p>\u4e8e\u662f\uff0c\u674e\u4ee3\u6570\u4e0e\u674e\u7fa4\u7684\u5173\u7cfb:</p> \\[ s=\\mathrm{e}^\\sigma, R=\\exp(\\phi^\\wedge), t=J_s\\rho. \\] \\[ \\frac{\\partial\\boldsymbol{Sp}}{\\partial\\boldsymbol{\\zeta}}=\\begin{bmatrix}\\boldsymbol{I}&amp;-\\boldsymbol{q}^\\wedge&amp;\\boldsymbol{q}\\\\\\boldsymbol{0}^\\mathrm{T}&amp;\\boldsymbol{0}^\\mathrm{T}&amp;0\\end{bmatrix}. \\]"},{"location":"CV/SLAM14/#47","title":"4.7 \u4e60\u9898","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#5","title":"5 \u76f8\u673a\u4e0e\u56fe\u50cf","text":"<ul> <li>\u89c2\u6d4b\u4e3b\u8981\u662f\u6307\u76f8\u673a\u6210\u50cf\u7684\u8fc7\u7a0b\u3002</li> </ul>"},{"location":"CV/SLAM14/#51","title":"5.1 \u76f8\u673a\u6a21\u578b","text":"<ul> <li>\u9488\u5b54\u6a21\u578b</li> <li>\u900f\u955c\u4f1a\u4ea7\u751f\u7578\u53d8</li> <li>\u5185\u53c2\u6570\uff08Intrinsics\uff09</li> </ul>"},{"location":"CV/SLAM14/#511","title":"5.1.1 \u9488\u5b54\u76f8\u673a\u6a21\u578b","text":"\\[ \\frac{Z}{f}=-\\frac{X}{X'}=-\\frac{Y}{Y'}. \\] <p>\u53bb\u6389\u8d1f\u53f7:</p> \\[ \\frac Zf=\\frac X{X^{\\prime}}=\\frac Y{Y^{\\prime}}. \\] \\[ \\begin{aligned}X'&amp;=f\\frac{X}{Z}\\\\Y'&amp;=f\\frac{Y}{Z}\\end{aligned}. \\] <p>\u8fd8\u6709\u4e00\u4e2a\u50cf\u7d20\u5750\u6807\u7cfb\uff0cu \u8f74\u4e0e x \u8f74\u5e73\u884c\uff0cv \u8f74\u4e0e y \u8f74\u5e73\u884c:</p> \\[ \\begin{cases}u=\\alpha X'+c_x\\\\[2ex]v=\\beta Y'+c_y\\end{cases}. \\] \\[ \\begin{cases}u=f_x\\frac{X}{Z}+c_x\\\\\\\\v=f_y\\frac{Y}{Z}+c_y\\end{cases}. \\] \\[ Z\\begin{pmatrix}u\\\\\\\\v\\\\\\\\1\\end{pmatrix}=\\begin{pmatrix}f_x&amp;0&amp;c_x\\\\0&amp;f_y&amp;c_y\\\\\\\\0&amp;0&amp;1\\end{pmatrix}\\begin{pmatrix}X\\\\\\\\Y\\\\\\\\Z\\end{pmatrix}\\overset{\\text{def}}{=}\\boldsymbol{KP}. \\] <p>\u6700\u4e2d\u95f4\u7684\u77e9\u9635\u79f0\u4e3a\u76f8\u673a\u7684\u5185\u53c2\u6570\uff08Camera Inrinsics\uff09\u77e9\u9635 \\(\\displaystyle \\boldsymbol{K}\\)\u3002 \u6807\u5b9a: \u786e\u5b9a\u76f8\u673a\u7684\u5185\u53c2</p> \\[ Z\\boldsymbol{P}_{uv}=Z\\begin{bmatrix}u\\\\\\\\v\\\\\\\\1\\end{bmatrix}=\\boldsymbol{K}\\left(\\boldsymbol{R}\\boldsymbol{P}_\\mathrm{w}+\\boldsymbol{t}\\right)=\\boldsymbol{K}\\boldsymbol{T}\\boldsymbol{P}_\\mathrm{w}. \\] <p>\u5176\u4e2d \\(\\displaystyle \\boldsymbol{R},\\boldsymbol{t}\\) \u53c8\u79f0\u4e3a\u76f8\u673a\u7684\u5916\u53c2\u6570\uff08Camera Extrinsics\uff09</p> \\[ (\\boldsymbol{RP_\\mathrm{w}}+\\boldsymbol{t})=\\underbrace{[X,Y,Z]^\\mathrm{T}}_{\\text{\u76f8\u673a\u5750\u6807}}\\to\\underbrace{[X/Z,Y/Z,1]^\\mathrm{T}}_{\\text{\u5f52\u4e00\u5316\u5750\u6807}} . \\] <ul> <li>\u5f52\u4e00\u5316\u5e73\u9762</li> <li>\u70b9\u7684\u6df1\u5ea6\u5728\u6295\u5f71\u8fc7\u7a0b\u4e2d\u88ab\u4e22\u5931\u4e86</li> </ul>"},{"location":"CV/SLAM14/#512","title":"5.1.2 \u7578\u53d8\u6a21\u578b","text":"<ul> <li>\u7578\u53d8 (Distortion \u5931\u771f) \u5f84\u5411\u7578\u53d8<ul> <li>\u7b52\u5f62\u7578\u53d8</li> <li>\u6795\u5f62\u7578\u53d8 </li> </ul> </li> <li>\u5f84\u5411\u7578\u53d8\u5373 \\(\\displaystyle r\\) \u53d8\u5316</li> <li>\u5207\u5411\u7578\u53d8\u5373 \\(\\displaystyle \\theta\\) \u53d8\u5316 \u6211\u4eec\u53ef\u4ee5\u5047\u8bbe:</li> </ul> \\[ \\begin{align} x_{\\mathrm{distorted}}&amp;=x(1+k_1r^2+k_2r^4+k_3r^6) \\\\ y_{\\mathrm{distorted}}&amp;=y(1+k_1r^2+k_2r^4+k_3r^6). \\end{align} \\] \\[ \\begin{align} x_{\\mathrm{distorted}}&amp;=x+2p_1xy+p_2(r^2+2x^2) \\\\ y_{\\mathrm{distorted}}&amp;=y+p_1(r^2+2y^2)+2p_2xy \\end{align} \\] <p>\u6240\u4ee5\u6211\u4eec\u53ef\u4ee5\u627e\u5230\u4e00\u4e2a\u70b9\u5728\u50cf\u7d20\u5e73\u9762\u4e0a\u7684\u6b63\u786e\u4f4d\u7f6e:</p> <ol> <li>\u5c06\u4e09\u7ef4\u7a7a\u95f4\u70b9\u6295\u5f71\u5230\u5f52\u4e00\u5316\u56fe\u50cf\u5e73\u9762\u3002\u8bbe\u5b83\u7684\u5f52\u4e00\u5316\u5750\u6807\u4e3a \\(\\displaystyle [x, y]^\\mathrm{T}\\)\u3002</li> <li>\u5bf9\u5f52\u4e00\u5316\u5e73\u9762\u4e0a\u7684\u70b9\u8ba1\u7b97\u5f84\u5411\u7578\u53d8\u548c\u5207\u5411\u7578\u53d8</li> </ol> \\[ \\begin{cases}x_\\text{distorted}=x(1+k_1r^2+k_2r^4+k_3r^6)+2p_1xy+p_2(r^2+2x^2)\\\\y_\\text{distorted}=y(1+k_1r^2+k_2r^4+k_3r^6)+p_1(r^2+2y^2)+2p_2xy\\end{cases} \\] <ol> <li>\u5c06\u7578\u53d8\u540e\u7684\u70b9\u901a\u8fc7\u5185\u53c2\u6570\u77e9\u9635\u6295\u5f71\u5230\u50cf\u7d20\u5e73\u9762\uff0c\u5f97\u5230\u8be5\u70b9\u5728\u56fe\u50cf\u4e0a\u7684\u6b63\u786e\u4f4d\u7f6e\u3002</li> </ol> \\[ \\begin{cases}u=f_xx_\\text{distorted}+c_x\\\\\\\\v=f_yy_\\text{distorted}+c_y\\end{cases}. \\] <p>\u8fd8\u6709\u5f88\u591a\u7684\u76f8\u673a\u6a21\u578b\u6bd4\u5982: \u4eff\u5c04\u6a21\u578b\uff0c\u900f\u89c6\u6a21\u578b\u3002</p> <p>\u603b\u7ed3\u4e00\u4e0b\u5355\u76ee\u76f8\u673a\u7684\u6210\u50cf\u8fc7\u7a0b:</p> <ol> <li>\u4e16\u754c\u5750\u6807\u7cfb\u4e0b\u6709\u4e00\u4e2a\u56fa\u5b9a\u7684\u70b9 \\(\\displaystyle P\\)\uff0c\u4e16\u754c\u5750\u6807\u4e3a \\(\\displaystyle \\boldsymbol{P}_{w}\\)\u3002</li> <li>\u7531\u4e8e\u76f8\u673a\u5728\u8fd0\u52a8\uff0c\u5b83\u7684\u8fd0\u52a8\u7531 \\(\\displaystyle \\boldsymbol{R},\\boldsymbol{t}\\) \u6216\u53d8\u6362\u77e9\u9635 \\(\\displaystyle \\boldsymbol{T}\\in SE(3)\\) \u63cf\u8ff0\u3002\\(\\displaystyle P\\) \u7684\u76f8\u673a\u5750\u6807\u4e3a \\(\\displaystyle \\tilde{P_{c}} = \\boldsymbol{R}\\boldsymbol{P}_{w}+\\boldsymbol{t}\\)\u3002</li> <li>\u8fd9\u65f6\u7684 \\(\\displaystyle \\tilde{\\boldsymbol{P}_{c}}\\) \u7684\u5206\u91cf\u662f \\(\\displaystyle X,Y,Z\\) \uff0c\u628a\u5b83\u4eec\u6295\u5f71\u5230\u5f52\u4e00\u5316\u5e73\u9762 \\(\\displaystyle Z = 1\\) \u4e0a\uff0c\u5f97\u5230 \\(\\displaystyle P\\) \u7684\u5f52\u4e00\u5316\u5750\u6807: \\(\\displaystyle \\boldsymbol{P}_{c} = \\left[ \\frac{X}{Z},   \\frac{Y}{Z}, 1 \\right]^\\mathrm{T}\\)\u3002</li> <li>\u6709\u7578\u53d8\u65f6\uff0c\u6839\u636e\u7578\u53d8\u53c2\u6570\u8ba1\u7b97 \\(\\displaystyle \\boldsymbol{P}_{c}\\) \u53d1\u751f\u7578\u53d8\u540e\u7684\u5750\u6807\u3002</li> <li>\\(\\displaystyle P\\) \u7684\u5f52\u4e00\u5316\u5750\u6807\u7ecf\u8fc7\u5185\u53c2\u540e\uff0c\u5bf9\u5e94\u5230\u5b83\u7684\u50cf\u7d20\u5750\u6807: \\(\\displaystyle \\boldsymbol{P}_{uv} = \\boldsymbol{K} \\boldsymbol{P}_{c}\\)\u3002</li> </ol>"},{"location":"CV/SLAM14/#513","title":"5.1.3 \u53cc\u76ee\u76f8\u673a\u6a21\u578b","text":"<p> \u4e24\u8005\u4e4b\u95f4\u7684\u8ddd\u79bb\u79f0\u4e3a\u53cc\u76ee\u76f8\u673a\u7684\u57fa\u7ebf</p> \\[ z=\\frac{fb}{d},\\quad d\\stackrel{\\mathrm{def}}{=}u_{\\mathrm{L}}-u_{\\mathrm{R}}. \\] <ul> <li>d \u5b9a\u4e49\u4e3a\u5de6\u53f3\u56fe\u7684\u6a2a\u5750\u6807\u4e4b\u5dee\uff0c\u79f0\u4e3a\u89c6\u5dee\u3002<ul> <li>\u7531\u4e8e\u89c6\u5dee\u6700\u5c0f\u4e3a\u4e00\u4e2a\u50cf\u7d20\uff0c\u6240\u4ee5\u53cc\u76ee\u7684\u6df1\u5ea6\u5b58\u5728\u4e00\u4e2a\u7406\u8bba\u4e0a\u7684\u6700\u5927\u503c\u3002</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#514-rgb-d","title":"5.1.4 RGB-D \u76f8\u673a\u6a21\u578b","text":"<ul> <li>\u7ea2\u5916\u7ed3\u6784\u5149\uff08Structured lightning\uff09</li> <li>\u98de\u884c\u65f6\u95f4\uff08Time-of-Flight, ToF\uff09 </li> <li>ToF \u76f8\u673a\u53ef\u4ee5\u83b7\u5f97\u6574\u4e2a\u56fe\u50cf\u7684\u50cf\u7d20\u6df1\u5ea6</li> <li>\u8f93\u51fa\u5f69\u8272\u56fe\u548c\u6df1\u5ea6\u56fe\uff0c\u751f\u6210\u70b9\u4e91\uff08Point Cloud\uff09</li> </ul>"},{"location":"CV/SLAM14/#52","title":"5.2 \u56fe\u50cf","text":"\\[ I(x,y):\\mathbb{R}^2\\mapsto\\mathbb{R}. \\] <ul> <li>channel</li> </ul>"},{"location":"CV/SLAM14/#53","title":"5.3 \u5b9e\u8df5: \u8ba1\u7b97\u673a\u4e2d\u7684\u56fe\u50cf","text":""},{"location":"CV/SLAM14/#531-opencv","title":"5.3.1 OpenCV \u7684\u57fa\u672c\u4f7f\u7528\u65b9\u6cd5","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#532","title":"5.3.2 \u56fe\u50cf\u53bb\u7578\u53d8","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#54-3-d","title":"5.4 \u5b9e\u8df5: 3 D \u89c6\u89c9","text":""},{"location":"CV/SLAM14/#541","title":"5.4.1 \u53cc\u76ee\u89c6\u89c9","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#542-rgb-d","title":"5.4.2 RGB-D \u89c6\u89c9","text":""},{"location":"CV/SLAM14/#55","title":"5.5 \u4e60\u9898","text":""},{"location":"CV/SLAM14/#6","title":"6 \u975e\u7ebf\u6027\u4f18\u5316","text":"<p>\u524d\u9762\u6211\u4eec\u5df2\u7ecf\u641e\u6e05\u695a\u4e86\u8fd0\u52a8\u65b9\u7a0b\u548c\u89c2\u6d4b\u65b9\u7a0b\u7684\u6765\u6e90\uff0c\u73b0\u5728\u6211\u4eec\u5f00\u59cb\u8ba8\u8bba\u566a\u58f0\u3002</p>"},{"location":"CV/SLAM14/#61","title":"6.1 \u72b6\u6001\u4f30\u8ba1\u95ee\u9898","text":""},{"location":"CV/SLAM14/#611","title":"6.1.1 \u6279\u91cf\u72b6\u6001\u4f30\u8ba1\u4e0e\u6700\u5927\u540e\u9a8c\u4f30\u8ba1","text":"\\[ \\begin{cases}\\boldsymbol{x}_k=f\\left(\\boldsymbol{x}_{k-1},\\boldsymbol{u}_k\\right)+\\boldsymbol{w}_k\\\\\\boldsymbol{z}_{k,j}=h\\left(\\boldsymbol{y}_j,\\boldsymbol{x}_k\\right)+\\boldsymbol{v}_{k,j}\\end{cases}. \\] \\[ s\\boldsymbol{z}_{k,j}=\\boldsymbol{K}(R_k\\boldsymbol{y}_j+\\boldsymbol{t}_k). \\] <p>\u5176\u4e2d \\(\\displaystyle s\\) \u4e3a\u50cf\u7d20\u70b9\u7684\u8ddd\u79bb\u3002 \u6211\u4eec\u901a\u5e38\u5047\u8bbe\u566a\u58f0\u9879\u6ee1\u8db3\u96f6\u5747\u503c\u7684\u9ad8\u65af\u5206\u5e03:</p> \\[ \\boldsymbol{w}_k\\sim\\mathcal{N}\\left(\\boldsymbol{0},\\boldsymbol{R}_k\\right),\\boldsymbol{v}_k\\sim\\mathcal{N}\\left(\\boldsymbol{0},\\boldsymbol{Q}_{k,j}\\right). \\] <p>\u6709\u4e24\u79cd\u65b9\u6cd5\u6765\u89e3\u51b3\u72b6\u6001\u4f30\u8ba1\u95ee\u9898:</p> <ul> <li>\u7528\u65b0\u7684\u6570\u636e\u6765\u66f4\u65b0\u5f53\u524d\u65f6\u523b\u7684\u4f30\u8ba1\u72b6\u6001\uff0c\u589e\u91cf/\u6e10\u8fdb (incremental) \u7684\u65b9\u6cd5\uff0c\u6216\u8005\u6559\u6ee4\u6ce2\u5668</li> <li>\u4e5f\u53ef\u4ee5\u628a\u6570\u636e\u90fd\u6512\u8d77\u6765\uff0c\u79f0\u4e3a\u6279\u91cf (batch) \u7684\u65b9\u6cd5 SfM (Structure from Motion) \u7efc\u5408\u4e00\u4e0b\u5c31\u6709\u4e86\u6ed1\u52a8\u7a97\u53e3\u4f30\u8ba1\u6cd5</li> </ul> \\[ \\boldsymbol{x}=\\{\\boldsymbol{x}_1,\\ldots,\\boldsymbol{x}_N\\},\\quad\\boldsymbol{y}=\\{\\boldsymbol{y}_1,\\ldots,\\boldsymbol{y}_M\\}. \\] \\[ P(\\boldsymbol{x},\\boldsymbol{y}|z,\\boldsymbol{u}). \\] \\[ P\\left(\\boldsymbol{x},\\boldsymbol{y}|\\boldsymbol{z},\\boldsymbol{u}\\right)=\\frac{P\\left(\\boldsymbol{z},\\boldsymbol{u}|\\boldsymbol{x},\\boldsymbol{y}\\right)P\\left(\\boldsymbol{x},\\boldsymbol{y}\\right)}{P\\left(\\boldsymbol{z},\\boldsymbol{u}\\right)}\\propto\\underbrace{P\\left(\\boldsymbol{z},\\boldsymbol{u}|\\boldsymbol{x},\\boldsymbol{y}\\right)}_{\\text{\u4f3c\u7136}}\\underbrace{P\\left(\\boldsymbol{x},\\boldsymbol{y}\\right)}_{\\text{\u5148\u9a8c}}. \\] <p>\u53ef\u4ee5\u5148\u6c42\u4e00\u4e2a\u72b6\u6001\u6700\u4f18\u4f30\u8ba1:</p> \\[ (\\boldsymbol{x},\\boldsymbol{y})^*_{\\mathrm{MAP}}=\\arg\\max P(\\boldsymbol{x},\\boldsymbol{y}|\\boldsymbol{z},\\boldsymbol{u})=\\arg\\max P(\\boldsymbol{z},\\boldsymbol{u}|\\boldsymbol{x},\\boldsymbol{y})P(\\boldsymbol{x},\\boldsymbol{y}). \\] <p>\u6c42\u89e3\u6700\u5927\u540e\u9a8c\u6982\u7387\u7b49\u4ef7\u4e8e\u6700\u5927\u5316\u4f3c\u7136\u548c\u5148\u9a8c\u7684\u4e58\u79ef\u3002 \u4f46\u5982\u679c\u6ca1\u6709\u7684\u5148\u9a8c\uff0c\u90a3\u4e48\u53ef\u4ee5\u6c42\u89e3\u6700\u5927\u4f3c\u7136\u4f30\u8ba1 (Maximize Likelihood Estimation\uff0c MLE):</p> \\[ (\\boldsymbol{x},\\boldsymbol{y})^*{}_{\\mathrm{MLE}}=\\arg\\max P(\\boldsymbol{z},\\boldsymbol{u}|\\boldsymbol{x},\\boldsymbol{y}). \\] <p>\u6700\u5927\u4f3c\u7136\u4f30\u8ba1: \u5728\u4ec0\u4e48\u6837\u7684\u72b6\u6001\u4e0b\uff0c\u6700\u53ef\u80fd\u4ea7\u751f\u73b0\u5728\u89c2\u6d4b\u5230\u7684\u6570\u636e\u3002</p>"},{"location":"CV/SLAM14/#612","title":"6.1.2 \u6700\u5c0f\u4e8c\u4e58\u7684\u5f15\u51fa","text":"<p>\u5bf9\u4e8e\u67d0\u4e00\u6b21\u89c2\u6d4b:</p> \\[ z_{k,j}=h\\left(y_{j},x_{k}\\right)+v_{k,j}, \\] \\[ P(\\boldsymbol{z}_{j,k}|\\boldsymbol{x}_k,\\boldsymbol{y}_j)=N\\left(h(\\boldsymbol{y}_j,\\boldsymbol{x}_k),\\boldsymbol{Q}_{k,j}\\right). \\] <p>\u53ef\u4ee5\u4f7f\u7528\u6700\u5c0f\u5316\u8d1f\u5bf9\u6570\u6765\u6c42\u4e00\u4e2a\u9ad8\u65af\u5206\u5e03\u7684\u6700\u5927\u4f3c\u7136\u3002</p> \\[ P\\left(\\boldsymbol{x}\\right)=\\frac{1}{\\sqrt{\\left(2\\pi\\right)^{N}\\det\\left(\\boldsymbol{\\Sigma}\\right)}}\\exp\\left(-\\frac{1}{2}(\\boldsymbol{x}-\\boldsymbol{\\mu})^{\\mathrm{T}}\\boldsymbol{\\Sigma}^{-1}\\left(\\boldsymbol{x}-\\boldsymbol{\\mu}\\right)\\right). \\] \\[ -\\ln\\left(P\\left(\\boldsymbol{x}\\right)\\right)=\\frac12\\ln\\left(\\left(2\\pi\\right)^N\\det\\left(\\boldsymbol{\\Sigma}\\right)\\right)+\\frac12\\left(\\boldsymbol{x}-\\boldsymbol{\\mu}\\right)^\\mathrm{T}\\boldsymbol{\\Sigma}^{-1}\\left(\\boldsymbol{x}-\\boldsymbol{\\mu}\\right). \\] \\[ \\begin{aligned} (x_{k},y_{j})^{*}&amp; =\\arg\\max\\mathcal{N}(h(\\boldsymbol{y}_{j},\\boldsymbol{x}_{k}),\\boldsymbol{Q}_{k,j}) \\\\ &amp;=\\arg\\min\\left(\\left(\\boldsymbol{z}_{k,j}-h\\left(\\boldsymbol{x}_k,\\boldsymbol{y}_j\\right)\\right)^\\mathrm{T}\\boldsymbol{Q}_{k,j}^{-1}\\left(\\boldsymbol{z}_{k,j}-h\\left(\\boldsymbol{x}_k,\\boldsymbol{y}_j\\right)\\right)\\right). \\end{aligned} \\] <p>\u8be5\u5f0f\u7b49\u4ef7\u4e8e\u6700\u5c0f\u5316\u566a\u58f0\u9879\u7684\u4e00\u4e2a\u4e8c\u6b21\u578b\uff0c\u9a6c\u54c8\u62c9\u8bfa\u6bd4\u65af\u8ddd\u79bb (Mahalanobis distance)\u3002\u5176\u4e2d \\(\\displaystyle \\boldsymbol{Q}_{k,j}^{-1}\\) \u53eb\u4fe1\u606f\u77e9\u9635\uff0c\u5373\u9ad8\u65af\u5206\u5e03\u534f\u65b9\u5dee\u77e9\u9635\u4e4b\u9006\u3002 \u5047\u8bbe\u5404\u4e2a\u65f6\u523b\u7684\u8f93\u5165\u548c\u89c2\u6d4b\u90fd\u662f\u72ec\u7acb\u7684\uff0c\u90a3\u4e48:</p> \\[ P\\left(\\boldsymbol{z},\\boldsymbol{u}|\\boldsymbol{x},\\boldsymbol{y}\\right)=\\prod_kP\\left(\\boldsymbol{u}_k|\\boldsymbol{x}_{k-1},\\boldsymbol{x}_k\\right)\\prod_{k,j}P\\left(\\boldsymbol{z}_{k,j}|\\boldsymbol{x}_k,\\boldsymbol{y}_j\\right), \\] \\[ \\begin{align} e_{u,k} &amp;=\\boldsymbol{x}_k-f\\left(\\boldsymbol{x}_{k-1},\\boldsymbol{u}_k\\right) \\\\ e_{z,j,k} &amp;=\\boldsymbol{z}_{k,j}-h\\left(\\boldsymbol{x}_k,\\boldsymbol{y}_j\\right),  \\end{align} \\] \\[ \\min J(\\boldsymbol{x},\\boldsymbol{y})=\\sum_{k}\\boldsymbol{e}_{\\boldsymbol{u},k}^{\\mathrm{T}}\\boldsymbol{R}_{k}^{-1}\\boldsymbol{e}_{\\boldsymbol{u},k}+\\sum_{k}\\sum_{j}\\boldsymbol{e}_{\\boldsymbol{z},k,j}^{\\mathrm{T}}\\boldsymbol{Q}_{k,j}^{-1}\\boldsymbol{e}_{\\boldsymbol{z},k,j}. \\] <p>\u8fd9\u6837\u5c31\u5f97\u5230\u4e86\u4e00\u4e2a\u6700\u5c0f\u4e8c\u4e58\u95ee\u9898 (Least Square Problem) </p> <ul> <li>\u6574\u4e2a\u95ee\u9898\u6709\u4e00\u79cd\u7a00\u758f\u7684\u5f62\u5f0f\u3002</li> <li>\u7528\u674e\u4ee3\u6570\u8868\u793a\u589e\u91cf\u4f1a\u6709\u65e0\u7ea6\u675f\u7684\u4f18\u52bf\u3002</li> <li>\u7528\u4e8c\u6b21\u578b\u5ea6\u91cf\u8bef\u5dee\uff0c\u90a3\u4e48\u8bef\u5dee\u7684\u5206\u5e03\u4f1a\u5f71\u54cd\u6b64\u9879\u5728\u6574\u4e2a\u95ee\u9898\u4e2d\u7684\u6743\u91cd\u3002 \u63a5\u4e0b\u4fe9\u8bb2\u4e00\u4e9b\u975e\u7ebf\u6027\u4f18\u5316\u7684\u57fa\u672c\u77e5\u8bc6\uff0c\u6765\u5e2e\u52a9\u6211\u4eec\u6c42\u89e3\u8fd9\u4e2a\u6700\u5c0f\u4e8c\u4e58\u95ee\u9898\u3002</li> </ul>"},{"location":"CV/SLAM14/#613","title":"6.1.3 \u4f8b\u5b50: \u6279\u91cf\u72b6\u6001\u4f30\u8ba1","text":"<p>\u8003\u8651\u4e00\u4e2a\u975e\u5e38\u7b80\u5355\u7684\u79bb\u6563\u65f6\u95f4\u7cfb\u7edf:</p> \\[ \\begin{aligned}&amp;x_{k}=x_{k-1}+u_{k}+w_{k},&amp;&amp;\\boldsymbol{w}_{k}\\sim\\mathcal{N}\\left(0,\\boldsymbol{Q}_{k}\\right)\\\\&amp;\\boldsymbol{z}_{k}=\\boldsymbol{x}_{k}+\\boldsymbol{n}_{k},&amp;&amp;\\boldsymbol{n}_{k}\\sim\\mathcal{N}\\left(0,\\boldsymbol{R}_{k}\\right)\\end{aligned} \\] \\[ \\begin{gathered} x_{map}^{*} =\\arg\\max P(\\boldsymbol{x}|\\boldsymbol{u},\\boldsymbol{z})=\\arg\\max P(\\boldsymbol{u},\\boldsymbol{z}|\\boldsymbol{x}) \\\\ =\\prod_{k=1}^3P(\\boldsymbol{u}_k|\\boldsymbol{x}_{k-1},\\boldsymbol{x}_k)\\prod_{k=1}^3P(\\boldsymbol{z}_k|\\boldsymbol{x}_k),  \\end{gathered} \\] <p>\u800c\u5bf9\u4e8e\u5177\u4f53\u7684\u6bcf\u4e00\u9879\uff0c\u6211\u4eec\u6709:</p> \\[ P(\\boldsymbol{u}_k|\\boldsymbol{x}_{k-1},\\boldsymbol{x}_k)=\\mathcal{N}(\\boldsymbol{x}_k-\\boldsymbol{x}_{k-1},\\boldsymbol{Q}_k), \\] \\[ P\\left(\\boldsymbol{z}_{k}|\\boldsymbol{x}_{k}\\right)=\\mathcal{N}\\left(\\boldsymbol{x}_{k},\\boldsymbol{R}_{k}\\right). \\] <p>\u4e8e\u662f\uff0c\u6211\u4eec\u53ef\u4ee5\u6784\u5efa\u8bef\u5dee\u53d8\u91cf:</p> \\[ e_{\\boldsymbol{u},k}=\\boldsymbol{x}_k-\\boldsymbol{x}_{k-1}-\\boldsymbol{u}_k,\\quad\\boldsymbol{e}_{z,k}=\\boldsymbol{z}_k-\\boldsymbol{x}_k, \\] <p>\u4e8e\u662f\u6700\u5c0f\u4e8c\u4e58\u7684\u76ee\u6807\u51fd\u6570\u4e3a:</p> \\[ \\min\\sum_{k=1}^{3}e_{u,k}^{\\mathrm{T}}Q_{k}^{-1}e_{u,k}+\\sum_{k=1}^{3}e_{z,k}^{\\mathrm{T}}R_{k}^{-1}e_{z,k}. \\] <p>\u5b9a\u4e49\u5411\u91cf \\(\\displaystyle \\boldsymbol{y} = [\\boldsymbol{u},\\boldsymbol{z}]^\\mathrm{T}\\)</p> \\[ y-Hx=e\\sim\\mathcal{N}(\\mathbf{0},\\boldsymbol{\\Sigma}). \\] \\[ H=\\begin{bmatrix}1&amp;-1&amp;0&amp;0\\\\0&amp;1&amp;-1&amp;0\\\\0&amp;0&amp;1&amp;-1\\\\\\hline0&amp;1&amp;0&amp;0\\\\0&amp;0&amp;1&amp;0\\\\0&amp;0&amp;0&amp;1\\end{bmatrix}, \\] <p>\u4e14 \\(\\displaystyle \\Sigma = diag(\\boldsymbol{Q_{1}},\\boldsymbol{Q_{2}},\\boldsymbol{Q_{3}},\\boldsymbol{R_{1}},\\boldsymbol{R_{2}},\\boldsymbol{R_{3}})\\)\u3002 \u95ee\u9898\u5c31\u8f6c\u5316\u6210:</p> \\[ x_{\\mathrm{map}}^*=\\arg\\min e^{\\mathrm{T}}\\Sigma^{-1}e, \\] <p>\u5b83\u7684\u552f\u4e00\u89e3\u662f:</p> \\[ x_{\\mathrm{map}}^{*}=(H^{\\mathrm{T}}\\Sigma^{-1}H)^{-1}H^{\\mathrm{T}}\\Sigma^{-1}y. \\]"},{"location":"CV/SLAM14/#62","title":"6.2 \u975e\u7ebf\u6027\u6700\u5c0f\u4e8c\u4e58","text":"<p>\u5148\u8003\u8651\u4e00\u4e2a\u7b80\u5355\u7684\u6700\u5c0f\u4e8c\u4e58\u95ee\u9898:</p> \\[ \\min_{x}F(x)=\\frac12\\|f\\left(x\\right)\\|_{2}^{2}.` \\] <p>\u5bf9\u4e8e\u4e0d\u65b9\u4fbf\u76f4\u63a5\u6c42\u89e3\u7684\u6700\u5c0f\u4e8c\u4e58\u95ee\u9898\uff0c\u6211\u4eec\u53ef\u4ee5\u7528\u8fed\u4ee3\u7684\u65b9\u5f0f\uff0c\u4ece\u4e00\u4e2a\u521d\u59cb\u503c\u51fa\u53d1\uff0c\u4e0d\u65ad\u5730\u66f4\u65b0\u5f53\u524d\u7684\u4f18\u5316\u53d8\u91cf\uff0c\u4f7f\u76ee\u6807\u51fd\u6570\u4e0b\u964d:</p> <ol> <li>\u7ed9\u5b9a\u67d0\u4e2a\u521d\u59cb\u503c \\(\\displaystyle \\boldsymbol{x_{0}}\\)\u3002</li> <li>\u5bf9\u4e8e\u7b2c \\(\\displaystyle k\\) \u6b21\u8fed\u4ee3\uff0c\u5bfb\u627e\u4e00\u4e2a\u589e\u91cf \\(\\displaystyle \\Delta x_{k}\\)\uff0c\u4f7f\u5f97 \\(\\displaystyle \\left\\|f\\left(\\boldsymbol{x}_{k}+\\Delta\\boldsymbol{x}_{k}\\right)\\right\\|_{2}^{2}\\) \u8fbe\u5230\u6700\u5c0f\u503c\u3002</li> <li>\u82e5 \\(\\displaystyle \\Delta x_k\\) \u8db3\u591f\u5c0f\uff0c\u5219\u505c\u6b62\u3002</li> <li>\u5426\u5219\uff0c\u4ee4 \\(\\displaystyle x_{k+1} = x_{k} + \\Delta x_{k}\\)\uff0c\u8fd4\u56de\u7b2c\u4e8c\u6b65 \u4e8e\u662f\u6c42\u89e3\u5bfc\u51fd\u6570\u4e3a\u96f6 -&gt; \u5bfb\u627e\u4e0b\u964d\u589e\u91cf \\(\\displaystyle \\Delta x_{k}\\) </li> </ol> <p>\u4e0b\u9762\u662f\u4e00\u4e9b\u5e7f\u6cdb\u4f7f\u7528\u7684\u7ed3\u679c\u3002</p>"},{"location":"CV/SLAM14/#621","title":"6.2.1 \u4e00\u9636\u548c\u4e8c\u9636\u68af\u5ea6\u6cd5","text":"<p>\u4f7f\u7528\u6cf0\u52d2\u5c55\u5f00:</p> \\[ F(\\boldsymbol{x}_k+\\Delta\\boldsymbol{x}_k)\\approx F(\\boldsymbol{x}_k)+\\boldsymbol{J}\\left(\\boldsymbol{x}_k\\right)^\\mathrm{T}\\Delta\\boldsymbol{x}_k+\\frac{1}{2}\\Delta\\boldsymbol{x}_k^\\mathrm{T}\\boldsymbol{H}(\\boldsymbol{x}_k)\\Delta\\boldsymbol{x}_k. \\] <p>\u5176\u4e2d \\(\\displaystyle \\boldsymbol{J}(x_{k})\\) \u662f \\(\\displaystyle F(x)\\) \u5173\u4e8e \\(\\displaystyle x\\) \u7684\u4e00\u9636\u5bfc\u6570\uff08\u68af\u5ea6\u3001\u96c5\u53ef\u6bd4\u77e9\u9635\uff09\uff0c\\(\\displaystyle \\boldsymbol{H}\\) \u662f\u4e8c\u9636\u5bfc\u6570\uff08\u6d77\u585e\u77e9\u9635\uff09\u3002</p> \\[ \\Delta\\boldsymbol{x}^*=-\\boldsymbol{J}(\\boldsymbol{x}_k). \\] \\[ \\Delta\\boldsymbol{x}^*=\\arg\\min\\left(F\\left(\\boldsymbol{x}\\right)+\\boldsymbol{J}\\left(\\boldsymbol{x}\\right)^\\mathrm{T}\\Delta\\boldsymbol{x}+\\frac{1}{2}\\Delta\\boldsymbol{x}^\\mathrm{T}\\boldsymbol{H}\\Delta\\boldsymbol{x}\\right). \\] <p>\u5bf9 \\(\\displaystyle \\Delta x\\) \u6c42\u5bfc\uff0c\u5e76\u4ee4\u5b83\u7b49\u4e8e\u96f6\uff0c\u5f97\u5230:</p> \\[ J+H\\Delta x=\\mathbf{0}\\Rightarrow H\\Delta x=-J. \\] <p>\u8fd9\u4e2a\u65b9\u6cd5\u53c8\u53eb\u725b\u987f\u6cd5\u3002</p>"},{"location":"CV/SLAM14/#622","title":"6.2.2 \u9ad8\u65af\u725b\u987f\u6cd5","text":"<p>\u6362\u4e00\u4e2a\u51fd\u6570\u5c55\u5f00:</p> \\[ f\\left(x+\\Delta x\\right)\\approx f\\left(x\\right)+\\boldsymbol{J}\\left(\\boldsymbol{x}\\right)^{\\mathrm{T}}\\Delta\\boldsymbol{x}. \\] \\[ \\Delta x^{*}=\\arg\\min_{\\Delta x}\\frac{1}{2}\\Big\\|f\\left(\\boldsymbol{x}\\right)+\\boldsymbol{J}\\left(\\boldsymbol{x}\\right)^{\\mathrm{T}}\\Delta\\boldsymbol{x}\\Big\\|^{2}. \\] \\[ \\begin{aligned} \\frac12\\left\\|f\\left(\\boldsymbol{x}\\right)+\\boldsymbol{J}\\left(\\boldsymbol{x}\\right)^\\mathrm{T}\\Delta\\boldsymbol{x}\\right\\|^2&amp; =\\frac12\\Big(f\\left(\\boldsymbol{x}\\right)+\\boldsymbol{J}\\left(\\boldsymbol{x}\\right)^\\mathrm{T}\\Delta\\boldsymbol{x}\\Big)^\\mathrm{T}\\Big(f\\left(\\boldsymbol{x}\\right)+\\boldsymbol{J}\\left(\\boldsymbol{x}\\right)^\\mathrm{T}\\Delta\\boldsymbol{x}\\Big) \\\\ &amp;=\\frac12\\left(\\|f(\\boldsymbol{x})\\|_2^2+2f\\left(\\boldsymbol{x}\\right)\\boldsymbol{J}(\\boldsymbol{x})^\\intercal\\Delta\\boldsymbol{x}+\\Delta\\boldsymbol{x}^\\intercal\\boldsymbol{J}(\\boldsymbol{x})\\boldsymbol{J}(\\boldsymbol{x})^\\intercal\\Delta\\boldsymbol{x}\\right). \\end{aligned} \\] \\[ \\boldsymbol{J}(\\boldsymbol{x})f\\left(\\boldsymbol{x}\\right)+\\boldsymbol{J}(\\boldsymbol{x})\\boldsymbol{J}^\\mathrm{T}\\left(\\boldsymbol{x}\\right)\\Delta\\boldsymbol{x}=\\boldsymbol{0}. \\] \\[ \\underbrace{\\boldsymbol{J}(\\boldsymbol{x})\\boldsymbol{J}^{\\intercal}}_{\\boldsymbol{H}(\\boldsymbol{x})}\\left(\\boldsymbol{x}\\right)\\Delta\\boldsymbol{x}=\\underbrace{-\\boldsymbol{J}(\\boldsymbol{x})f\\left(\\boldsymbol{x}\\right)}_{\\boldsymbol{g}(\\boldsymbol{x})}. \\] <p>\u589e\u91cf\u65b9\u7a0b or Gauss-Newton equation or Normal equation</p> \\[ H\\Delta x=g. \\] <p>\u6c42\u89e3\u589e\u91cf\u65b9\u7a0b\u662f\u6574\u4e2a\u4f18\u5316\u95ee\u9898\u7684\u6838\u5fc3\u6240\u5728 \u603b\u7ed3\u4e00\u4e0b:</p> <ol> <li>\u7ed9\u5b9a\u521d\u59cb\u503c \\(\\displaystyle \\boldsymbol{x}_{0}\\)\u3002</li> <li>\u5bf9\u4e8e\u7b2c \\(\\displaystyle k\\) \u6b21\u8fed\u4ee3\uff0c\u6c42\u89e3\u5f53\u524d\u7684\u96c5\u53ef\u6bd4\u77e9\u9635 \\(\\displaystyle \\boldsymbol{J}(x)\\) \u548c\u8bef\u5dee \\(\\displaystyle f(\\boldsymbol{x}_{k})\\)\u3002</li> <li>\u6c42\u89e3\u589e\u91cf\u65b9\u7a0b: \\(\\displaystyle \\boldsymbol{H} \\Delta x_{k} = \\boldsymbol{g}\\)\u3002</li> <li>\u82e5 \\(\\displaystyle \\Delta x_{k}\\) \u8db3\u591f\u5c0f\uff0c\u5219\u505c\u6b62\u3002\u5426\u5219\uff0c\u4ee4 \\(\\displaystyle x_{k+1} = x_{k}+ \\Delta x_{k}\\)\uff0c\u8fd4\u56de\u7b2c 2 \u6b65\u3002</li> </ol>"},{"location":"CV/SLAM14/#623","title":"6.2.3 \u5217\u6587\u4f2f\u683c\u2014\u2014\u9a6c\u5938\u5c14\u7279\u65b9\u6cd5","text":"<p>Damped Newton Method Trust Region Trust Region Method</p> \\[ \\rho=\\frac{f\\left(\\boldsymbol{x}+\\Delta\\boldsymbol{x}\\right)-f\\left(\\boldsymbol{x}\\right)}{\\boldsymbol{J}\\left(\\boldsymbol{x}\\right)^{\\intercal}\\Delta\\boldsymbol{x}}. \\] <p>\u6846\u67b6:</p> <ol> <li>\u7ed9\u5b9a\u521d\u59cb\u503c \\(\\displaystyle \\boldsymbol{x}_{0}\\)\uff0c\u4ee5\u53ca\u521d\u59cb\u4f18\u5316\u534a\u5f84 \\(\\displaystyle \\mu\\)\u3002</li> <li>\u5bf9\u4e8e\u7b2c \\(\\displaystyle k\\) \u6b21\u8fed\u4ee3\uff0c\u5728\u9ad8\u65af\u725b\u987f\u6cd5\u7684\u57fa\u7840\u4e0a\u52a0\u4e0a\u4fe1\u8d56\u533a\u57df\uff0c\u6c42\u89e3: \\(\\displaystyle \\min_{\\Delta\\boldsymbol{x}_{k}}\\frac{1}{2}\\Big\\|f\\left(\\boldsymbol{x}_{k}\\right)+\\boldsymbol{J}\\left(\\boldsymbol{x}_{k}\\right)^{\\mathrm{T}}\\Delta\\boldsymbol{x}_{k}\\Big\\|^{2},\\quad\\mathrm{s.t.}\\quad\\left\\|\\boldsymbol{D}\\Delta\\boldsymbol{x}_{k}\\right\\|^{2}\\leqslant\\mu,\\) </li> <li>\u8ba1\u7b97 \\(\\displaystyle \\rho\\)</li> <li>\u5bf9\u4e8e \\(\\displaystyle \\frac{1}{4}  \\frac{3}{4}\\) \u8fdb\u884c\u5206\u7c7b\u8ba8\u8bba</li> <li>\u5224\u65ad\u9608\u503c\uff0c\u5faa\u73af</li> </ol> <p>\u8fd9\u662f\u5e26\u4e0d\u7b49\u5f0f\u7ea6\u675f\u7684\u4f18\u5316\u95ee\u9898:</p> \\[ \\mathcal{L}(\\Delta\\boldsymbol{x}_{k},\\lambda)=\\frac{1}{2}\\left\\|f\\left(\\boldsymbol{x}_{k}\\right)+\\boldsymbol{J}\\left(\\boldsymbol{x}_{k}\\right)^{\\mathrm{T}}\\Delta\\boldsymbol{x}_{k}\\right\\|^{2}+\\frac{\\lambda}{2}\\left(\\left\\|\\boldsymbol{D}\\Delta\\boldsymbol{x}_{k}\\right\\|^{2}-\\mu\\right). \\] \\[ (H+\\lambda D^\\mathrm{T}D) \\Delta x_k=g. \\]"},{"location":"CV/SLAM14/#63","title":"6.3 \u5b9e\u8df5: \u66f2\u7ebf\u62df\u5408\u95ee\u9898","text":""},{"location":"CV/SLAM14/#631","title":"6.3.1 \u624b\u5199\u9ad8\u65af\u725b\u987f\u6cd5","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#632-ceres","title":"6.3.2 \u4f7f\u7528 Ceres \u8fdb\u884c\u66f2\u7ebf\u62df\u5408","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#633-g2o","title":"6.3.3 \u4f7f\u7528 g2o\u8fdb\u884c\u66f2\u7ebf\u62df\u5408","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#7-1","title":"7 \u89c6\u89c9\u91cc\u7a0b\u8ba1 1","text":""},{"location":"CV/SLAM14/#71","title":"7.1 \u7279\u5f81\u70b9\u6cd5","text":"<ul> <li>\u7279\u5f81\u70b9\u6cd5<ul> <li>\u4e24\u89c6\u56fe\u51e0\u4f55\uff08Two-view geometry\uff09</li> </ul> </li> <li>\u76f4\u63a5\u6cd5</li> </ul>"},{"location":"CV/SLAM14/#711","title":"7.1.1 \u7279\u5f81\u70b9","text":"<ul> <li>\u5982\u4f55\u6839\u636e\u56fe\u50cf\u4f30\u8ba1\u76f8\u673a\u8fd0\u52a8</li> <li>\u8def\u6807: \u56fe\u50cf\u7279\u5f81</li> <li>\u7279\u5f81\u70b9\u5728\u76f8\u673a\u8fd0\u52a8\u4e4b\u540e\u4fdd\u6301\u7a33\u5b9a<ul> <li>\u89d2\u70b9</li> </ul> </li> <li>\u4eba\u5de5\u8bbe\u8ba1\u7684\u7279\u5f81\u70b9:<ul> <li>Repeatability</li> <li>Distinctiveness</li> <li>Efficiency</li> <li>Locality</li> </ul> </li> <li>\u7531\u4e24\u90e8\u5206\u7ec4\u6210:<ul> <li>\u5173\u952e\u70b9\uff08Key-point\uff09</li> <li>\u63cf\u8ff0\u5b50\uff08Descriptor\uff09</li> </ul> </li> <li>SIFT (\u5c3a\u5ea6\u4e0d\u53d8\u7279\u5f81\u53d8\u6362\uff0cScale-Invariant Feature Transform)<ul> <li>\u8003\u8651\u5145\u5206\uff0c\u4f46\u662f\u8ba1\u7b97\u91cf\u6bd4\u8f83\u5927</li> </ul> </li> <li>ORB (Oriented FAST and Rotated BRIEF)</li> </ul>"},{"location":"CV/SLAM14/#712-orb","title":"7.1.2 ORB \u7279\u5f81","text":"<ol> <li>FAST \u89d2\u70b9\u63d0\u53d6: ORB \u4e2d\u8ba1\u7b97\u4e86\u7279\u5f81\u70b9\u7684\u4e3b\u65b9\u5411\uff0c\u4e3a\u540e\u7eed\u7684 BRIEF \u63cf\u8ff0\u5b50\u589e\u52a0\u4e86\u65cb\u8f6c\u4e0d\u53d8\u7279\u6027</li> <li>BRIEF \u63cf\u8ff0\u5b50: \u5bf9\u524d\u4e00\u6b65\u63d0\u53d6\u51fa\u7279\u5f81\u70b9\u7684\u5468\u56f4\u56fe\u50cf\u533a\u57df\u8fdb\u884c\u63cf\u8ff0\u3002\u4f7f\u7528\u5148\u524d\u8ba1\u7b97\u7684\u65b9\u5411\u4fe1\u606f\u3002 - FAST \u5173\u952e\u70b9  Non-maximal suppression \u5c3a\u5ea6\u4e0d\u53d8\u6027\u7531\u6784\u5efa\u56fe\u50cf\u91d1\u5b57\u5854 \u7279\u5f81\u7684\u65cb\u8f6c: Intensity Centroid \u65cb\u8f6c\u65b9\u9762\uff0c\u6211\u4eec\u8ba1\u7b97\u7279\u5f81\u70b9\u9644\u8fd1\u7684\u56fe\u50cf\u7070\u5ea6\u8d28\u5fc3\u3002</li> <li>\u5b9a\u4e49\u56fe\u50cf\u7684\u77e9: \\(\\displaystyle m_{pq} = \\Sigma _{x,y \\in B} x^p x^q I(x, y),p,q \\in \\{0, 1\\}\\).</li> <li>\u627e\u5230\u56fe\u50cf\u5757\u7684\u8d28\u5fc3: \\(\\displaystyle C=\\left(\\frac{m_{10}}{m_{00}},\\frac{m_{01}}{m_{00}}\\right).\\)</li> <li>\u5f97\u5230\u4e00\u4e2a\u51e0\u4f55\u4e2d\u5fc3\u5230\u8d28\u5fc3\u7684\u65b9\u5411\u5411\u91cf: \\(\\displaystyle \\theta=\\arctan(m_{01}/m_{10}).\\) - BRIEF \u63cf\u8ff0\u5b50 \u4e8c\u8fdb\u5236\u8868\u8fbe+\u968f\u673a\u9009\u70b9\u6bd4\u8f83</li> </ol>"},{"location":"CV/SLAM14/#713","title":"7.1.3 \u7279\u5f81\u5339\u914d","text":"<p>data association Brute-Force Matcher</p> <ul> <li>\u901a\u8fc7\u6d4b\u91cf\u63cf\u8ff0\u5b50\u7684\u8ddd\u79bb\u6765\u53bb\u6700\u8fd1\u7684\u4e00\u4e2a\u4f5c\u4e3a\u5339\u914d\u70b9\u3002\u63cf\u8ff0\u5b50\u8ddd\u79bb\u8868\u793a\u4e86\u4e24\u4e2a\u7279\u5f81\u4e4b\u95f4\u7684\u76f8\u4f3c\u7a0b\u5ea6\u3002<ul> <li>\u6b27\u6c0f\u8ddd\u79bb</li> <li>\u6c49\u660e\u8ddd\u79bb<ul> <li>\u4e24\u4e2a\u4e8c\u8fdb\u5236\u4e32\u7684\u4e0d\u540c\u4f4d\u6570\u7684\u4e2a\u6570</li> </ul> </li> </ul> </li> <li>\u5feb\u901f\u8fd1\u4f3c\u6700\u8fd1\u90bb\uff08FLANN\uff09</li> </ul>"},{"location":"CV/SLAM14/#72","title":"7.2 \u5b9e\u8df5: \u7279\u5f81\u63d0\u53d6\u548c\u5339\u914d","text":""},{"location":"CV/SLAM14/#721-opencv-orb","title":"7.2.1 OpenCV \u7684 ORB \u7279\u5f81","text":"<p>TODO</p>"},{"location":"CV/SLAM14/#722-orb","title":"7.2.2 \u624b\u5199 ORB \u7279\u5f81","text":""},{"location":"CV/SLAM14/#723","title":"7.2.3 \u8ba1\u7b97\u76f8\u673a\u8fd0\u52a8","text":"<ol> <li>\u5f53\u76f8\u673a\u4e3a\u5355\u76ee\u65f6\uff0c\u6211\u4eec\u901a\u8fc7\u5bf9\u6781\u51e0\u4f55\u6765\u89e3\u51b3\u4e24\u7ec4 2 D \u70b9\u4f30\u8ba1\u8fd0\u52a8\u7684\u95ee\u9898</li> <li>\u5f53\u76f8\u673a\u4e3a\u53cc\u76ee\u3001RGB-D \u65f6\uff0c\u901a\u8fc7 ICP \u6765\u89e3\u51b3\u4e24\u7ec4 3 D \u70b9\u4f30\u8ba1\u8fd0\u52a8\u7684\u95ee\u9898</li> <li>\u4e00\u4e2a\u662f 2 D \u4e00\u4e2a\u662f 3 D \u65f6\uff0c\u901a\u8fc7 PnP \u6765\u6c42\u89e3</li> </ol>"},{"location":"CV/SLAM14/#73-d-2-d","title":"7.3 D-2 D: \u5bf9\u6781\u51e0\u4f55","text":""},{"location":"CV/SLAM14/#731","title":"7.3.1 \u5bf9\u6781\u7ea6\u675f","text":"<ul> <li>Epipolar plane</li> <li>Epipoles</li> <li>Epipolar line </li> </ul> \\[ P=[X,Y,Z]^{\\mathrm{T}}. \\] \\[ s_{1}p_{1}=KP,\\quad s_{2}p_{2}=K\\left(RP+t\\right). \\] <p>\u6210\u6295\u5f71\u5173\u7cfb:\u5c3a\u5ea6\u610f\u4e49\u4e0b\u76f8\u7b49 (equal up to scale)</p> \\[ sp\\simeq p. \\] \\[ p_1\\simeq KP,\\quad p_2\\simeq K\\left(RP+t\\right). \\] \\[ x_1=K^{-1}p_1,\\quad x_2=K^{-1}p_2. \\] \\[ x_2\\simeq Rx_1+t. \\] \\[ t^{\\wedge}x_{2}\\simeq t^{\\wedge}Rx_{1}. \\] \\[ x_2^\\mathrm{T}t^\\wedge x_2\\simeq x_2^\\mathrm{T}t^\\wedge Rx_1. \\] \\[ x_2^\\mathrm{T}t^\\wedge Rx_1=0. \\] \\[ p_2^\\mathrm{T}K^{-\\mathrm{T}}t^\\wedge RK^{-1}p_1=0. \\] <p>\u5bf9\u6781\u7ea6\u675f</p> \\[ E=t^{\\wedge}R,\\quad F=K^{-\\mathrm{T}}EK^{-1},\\quad x_{2}^{\\mathrm{T}}Ex_{1}=p_{2}^{\\mathrm{T}}Fp_{1}=0. \\] <ol> <li>\u6839\u636e\u914d\u5bf9\u70b9\u7684\u50cf\u7d20\u4f4d\u7f6e\u6c42\u51fa \\(\\displaystyle \\boldsymbol{E}\\) \u6216\u8005 \\(\\displaystyle \\boldsymbol{F}\\)\u3002</li> <li>\u6839\u636e \\(\\displaystyle \\boldsymbol{E}\\) \u6216\u8005 \\(\\displaystyle \\boldsymbol{F}\\) \u6c42\u51fa \\(\\displaystyle \\boldsymbol{R},\\boldsymbol{t}\\)\u3002 \\(\\displaystyle \\boldsymbol{E}\\) \u548c \\(\\displaystyle \\boldsymbol{F}\\) \u53ea\u76f8\u5dee\u4e86\u76f8\u673a\u5185\u53c2\uff0c\u6240\u4ee5\u5b9e\u8df5\u4e2d\u5f80\u5f80\u4f7f\u7528\u5f62\u5f0f\u66f4\u7b80\u5355\u7684 \\(\\displaystyle \\boldsymbol{E}\\)\u3002</li> </ol>"},{"location":"CV/SLAM14/#732","title":"7.3.2 \u672c\u8d28\u77e9\u9635","text":"<p>\u672c\u8d28\u77e9\u9635: \\(\\displaystyle E=t^{\\wedge}R\\)</p> <ul> <li>\\(\\displaystyle \\boldsymbol{E}\\) \u4e0d\u540c\u5c3a\u5ea6\u4e0b\u662f\u7b49\u4ef7\u7684\u3002</li> <li>\u53ef\u4ee5\u8bc1\u660e\uff0c\u672c\u8d28\u77e9\u9635 \\(\\displaystyle \\boldsymbol{E}\\) \u7684\u5947\u5f02\u503c\u5fc5\u5b9a\u662f \\(\\displaystyle [\\sigma,\\sigma,0]^\\mathrm{T}\\) \u7684\u5f62\u5f0f\uff0c\u8fd9\u79f0\u4e3a\u672c\u8d28\u77e9\u9635\u7684\u5185\u5728\u6027\u8d28\u3002</li> <li>\\(\\displaystyle \\boldsymbol{E}\\) \u5b9e\u9645\u4e0a\u6709 5 \u4e2a\u81ea\u7531\u5ea6\u3002 \u516b\u70b9\u6cd5 (Eight-point-algorithm) \u8003\u8651\u4e00\u5806\u914d\u5bf9\u70b9\uff0c\u5b83\u4eec\u7684\u5f52\u4e00\u5316\u5750\u6807\u4e3a \\(\\displaystyle x_{1}=[u_{1},v_{1},1]^{\\mathrm{T}},x_{2}=[u_{2},v_{2},1]^{\\mathrm{T}}\\)\u3002\u6839\u636e\u5bf9\u6781\u7ea6\u675f\uff0c\u6709</li> </ul> \\[ \\begin{pmatrix}u_2,v_2,1\\end{pmatrix}\\begin{pmatrix}e_1&amp;e_2&amp;e_3\\\\\\\\e_4&amp;e_5&amp;e_6\\\\\\\\e_7&amp;e_8&amp;e_9\\end{pmatrix}\\begin{pmatrix}u_1\\\\\\\\v_1\\\\\\\\1\\end{pmatrix}=0. \\] \\[ \\boldsymbol{e}=[e_1,e_2,e_3,e_4,e_5,e_6,e_7,e_8,e_9]^\\mathrm{T}, \\] \\[ [u_2u_1,u_2v_1,u_2,v_2u_1,v_2v_1,v_2,u_1,v_1,1]\\cdot e=0. \\] <p>\u6211\u4eec\u628a\u6240\u6709\u70b9\u90fd\u653e\u5230\u4e00\u4e2a\u65b9\u7a0b\u4e2d\uff0c\u53d8\u6210\u7ebf\u6027\u65b9\u7a0b\u7ec4:</p> \\[ \\begin{pmatrix}u_2^1u_1^1&amp;u_2^1v_1^1&amp;u_2^1&amp;v_2^1u_1^1&amp;v_2^1v_1^1&amp;v_2^1&amp;u_1^1&amp;v_1^1&amp;1\\\\u_2^2u_1^2&amp;u_2^2v_1^2&amp;u_2^2&amp;v_2^2u_1^2&amp;v_2^2v_1^2&amp;v_2^2&amp;u_1^2&amp;v_1^2&amp;1\\\\\\vdots&amp;\\vdots&amp;\\vdots&amp;\\vdots&amp;\\vdots&amp;\\vdots&amp;\\vdots&amp;\\vdots\\\\u_2^8u_1^8&amp;u_2^8v_1^8&amp;u_2^8&amp;v_2^8u_1^8&amp;v_2^8u_1^8&amp;u_1^8&amp;v_1^8&amp;1\\end{pmatrix}\\begin{pmatrix}e_1\\\\e_2\\\\e_3\\\\e_4\\\\e_5\\\\e_6\\\\e_7\\\\e_8\\\\e_9\\end{pmatrix}=0. \\] \\[ E=U\\Sigma V^{\\mathrm{T}}, \\] \\[ \\begin{aligned}&amp;t_{1}^{\\wedge}=UR_{Z}(\\frac{\\pi}{2})\\Sigma U^{\\mathrm{T}},\\quad R_{1}=UR_{Z}^{\\mathrm{T}}(\\frac{\\pi}{2})V^{\\mathrm{T}}\\\\&amp;t_{2}^{\\wedge}=UR_{Z}(-\\frac{\\pi}{2})\\Sigma U^{\\mathrm{T}},\\quad R_{2}=UR_{Z}^{\\mathrm{T}}(-\\frac{\\pi}{2})V^{\\mathrm{T}}.\\end{aligned} \\] <p></p> \\[ \\boldsymbol{E}=\\boldsymbol{U}\\mathrm{diag}(\\frac{\\sigma_1+\\sigma_2}2,\\frac{\\sigma_1+\\sigma_2}2,0)\\boldsymbol{V}^\\mathrm{T}. \\]"},{"location":"CV/SLAM14/#733","title":"7.3.3 \u5355\u5e94\u77e9\u9635","text":"<p>Homography</p>"},{"location":"CV/SLAM14/#8-2","title":"8 \u89c6\u89c9\u91cc\u7a0b\u8ba1 2","text":""},{"location":"CV/SLAM14/#81","title":"8.1 \u76f4\u63a5\u6cd5\u7684\u5f15\u51fa","text":"<ul> <li>\u7279\u5f81\u70b9\u6cd5\u7684\u7f3a\u70b9<ul> <li>\u5173\u952e\u70b9\u7684\u63d0\u53d6\u4e0e\u63cf\u8ff0\u5b50\u7684\u8ba1\u7b97\u975e\u5e38\u8017\u65f6</li> <li>\u4f7f\u7528\u7279\u5f81\u70b9\u65f6\uff0c\u4f1a\u5ffd\u7565\u9664\u7279\u5f81\u70b9\u4ee5\u5916\u7684\u6240\u6709\u4fe1\u606f</li> <li>\u76f8\u673a\u6709\u65f6\u4f1a\u8fd0\u52a8\u5230\u7279\u5f81\u7f3a\u5931\u7684\u5730\u65b9</li> </ul> </li> <li>\u90a3\u4e48\u5982\u4f55\u514b\u670d\u8fd9\u4e9b\u7f3a\u70b9<ul> <li>\u4fdd\u7559\u7279\u5f81\u70b9\uff0c\u4f46\u53ea\u8ba1\u7b97\u5173\u952e\u70b9\uff0c\u4e0d\u8ba1\u7b97\u63cf\u8ff0\u5b50\u3002\u4f7f\u7528\u5149\u6d41\u6cd5\uff08Optical Flow\uff09\u8ddf\u8e2a\u7279\u5f81\u70b9\u7684\u8fd0\u52a8</li> <li>\u53ea\u8ba1\u7b97\u5173\u952e\u70b9\uff0c\u4e0d\u8ba1\u7b97\u63cf\u8ff0\u5b50\u3002\u4f7f\u7528\u76f4\u63a5\u6cd5\uff08Direct Method\uff09</li> </ul> </li> <li>\u7b2c\u4e00\u79cd\u65b9\u6cd5\u4ecd\u7136\u4f7f\u7528\u7279\u5f81\u70b9\uff0c\u53ea\u662f\u628a\u5339\u914d\u63cf\u8ff0\u5b57\u66ff\u6362\u6210\u4e86\u5149\u6d41\u8ddf\u8e2a\uff0c\u4f30\u8ba1\u76f8\u673a\u8fd0\u52a8\u65f6\u4ecd\u7136\u662f\u54e6\u90a3\u4e2a\u5bf9\u6781\u51e0\u4f55\u3001PnP \u6216 ICP \u7b97\u6cd5\uff08\u5373\uff0c\u6211\u4eec\u9700\u8981\u63d0\u5230\u89d2\u70b9\uff09</li> <li>\u7279\u5f81\u70b9\u6cd5:\u901a\u8fc7\u6700\u5c0f\u5316\u91cd\u6295\u5f71\u8bef\u5dee\uff08Reprojection error\uff09\u4f18\u5316\u76f8\u673a\u8fd0\u52a8</li> <li>\u76f4\u63a5\u6cd5: \u901a\u8fc7\u6700\u5c0f\u5316\u5149\u5ea6\u8bef\u5dee\uff08Photometric error\uff09</li> <li>\u53ea\u8981\u573a\u666f\u4e2d\u5b58\u5728\u660e\u6697\u53d8\u5316\u5c31\u53ef\u4ee5\u5de5\u4f5c<ul> <li>\u7a20\u5bc6</li> <li>\u534a\u7a20\u5bc6</li> <li>\u7a00\u758f</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#82-d","title":"8.2 D \u5149\u6d41","text":"<ul> <li>\u8ba1\u7b97\u90e8\u5206\u50cf\u7d20\u8fd0\u52a8: \u7a00\u758f\u5149\u6d41<ul> <li>Lucas-Kanasde</li> </ul> </li> <li>\u8ba1\u7b97\u6240\u6709\u50cf\u7d20\u8fd0\u52a8: \u7a20\u5bc6\u5149\u6d41<ul> <li>Horn-Schunck Lucas-Kanade \u5149\u6d41</li> </ul> </li> <li>\u7070\u5ea6\u4e0d\u53d8\u5047\u8bbe: \u540c\u4e00\u4e2a\u7a7a\u95f4\u70b9\u7684\u50cf\u7d20\u7070\u5ea6\u503c\uff0c\u5728\u5404\u4e2a\u56fe\u50cf\u4e2d\u65f6\u56fa\u5b9a\u4e0d\u53d8\u7684</li> </ul> \\[ I(x+\\mathrm{d}x,y+\\mathrm{d}y,t+\\mathrm{d}t)=I(x,y,t). \\] \\[ \\boldsymbol{I}\\left(x+\\mathrm{d}x,y+\\mathrm{d}y,t+\\mathrm{d}t\\right)\\approx\\boldsymbol{I}\\left(x,y,t\\right)+\\frac{\\partial\\boldsymbol{I}}{\\partial x}\\mathrm{d}x+\\frac{\\partial\\boldsymbol{I}}{\\partial y}\\mathrm{d}y+\\frac{\\partial\\boldsymbol{I}}{\\partial t}\\mathrm{d}t. \\] \\[ \\frac{\\partial\\boldsymbol{I}}{\\partial x}\\frac{\\mathrm{d}x}{\\mathrm{d}t}+\\frac{\\partial\\boldsymbol{I}}{\\partial y}\\frac{\\mathrm{d}y}{\\mathrm{d}t}=-\\frac{\\partial\\boldsymbol{I}}{\\partial t}. \\] \\[ \\begin{bmatrix}I_x&amp;I_y\\end{bmatrix}\\begin{bmatrix}u\\\\\\\\v\\end{bmatrix}=-I_t. \\] \\[ \\begin{bmatrix}I_x&amp;I_y\\end{bmatrix}_k\\begin{bmatrix}u\\\\\\\\v\\end{bmatrix}=-I_{tk},\\quad k=1,\\ldots,w^2. \\] \\[ A\\begin{bmatrix}u\\\\\\\\v\\end{bmatrix}=-b. \\] \\[ \\begin{bmatrix}u\\\\\\\\v\\end{bmatrix}^*=-\\begin{pmatrix}\\boldsymbol{A}^\\mathrm{T}\\boldsymbol{A}\\end{pmatrix}^{-1}\\boldsymbol{A}^\\mathrm{T}\\boldsymbol{b}. \\]"},{"location":"CV/SLAM14/#83-lk","title":"8.3 \u5b9e\u8df5: LK \u5149\u6d41","text":""},{"location":"CV/SLAM14/#831-lk","title":"8.3.1 \u4f7f\u7528 LK \u5149\u6d41","text":"C++<pre><code>vector&lt;Point2f&gt; pt1, pt2;\nfor (auto &amp;kp: kp1) pt1.push_back(kp.pt);\nvector&lt;uchar&gt; status;\nvector&lt;float&gt; error;\ncv::calcOpticalFlowPyrLK(img1, img2, pt1, pt2, status, error);\n</code></pre>"},{"location":"CV/SLAM14/#832","title":"8.3.2 \u7528\u9ad8\u65af\u725b\u987f\u6cd5\u5b9e\u73b0\u5149\u6d41","text":"<p>\u5355\u5c42\u5149\u6d41 TODO</p> \\[ \\min_{\\Delta x,\\Delta y}\\left\\|\\boldsymbol{I}_1\\left(x,y\\right)-\\boldsymbol{I}_2\\left(x+\\Delta x,y+\\Delta y\\right)\\right\\|_2^2. \\] <p>\u591a\u5c42\u5149\u6d41 - \u7531\u7c97\u81f3\u7cbe\uff08Coarse-to-fine\uff09</p>"},{"location":"CV/SLAM14/#833","title":"8.3.3 \u5149\u6d41\u5b9e\u8df5\u5c0f\u7ed3","text":""},{"location":"CV/SLAM14/#84","title":"8.4 \u76f4\u63a5\u6cd5","text":""},{"location":"CV/SLAM14/#841","title":"8.4.1 \u76f4\u63a5\u6cd5\u7684\u63a8\u5bfc","text":"\\[ \\boldsymbol{p}_1=\\begin{bmatrix}u\\\\\\\\v\\\\\\\\1\\end{bmatrix}_1=\\frac{1}{Z_1}\\boldsymbol{K}\\boldsymbol{P}, \\] \\[ \\boldsymbol{p}_{2}=\\begin{bmatrix}u\\\\\\\\v\\\\\\\\1\\end{bmatrix}_{2}=\\frac{1}{Z_{2}}\\boldsymbol{K}\\left(\\boldsymbol{R}\\boldsymbol{P}+\\boldsymbol{t}\\right)=\\frac{1}{Z_{2}}\\boldsymbol{K}\\left(\\boldsymbol{T}\\boldsymbol{P}\\right)_{1:3}. \\] \\[ e=\\boldsymbol{I}_1\\left(\\boldsymbol{p}_1\\right)-\\boldsymbol{I}_2\\left(\\boldsymbol{p}_2\\right). \\] \\[ \\min_{T}J\\left(T\\right)=\\left\\|e\\right\\|^{2}. \\] \\[ \\min_{\\boldsymbol{T}}J\\left(\\boldsymbol{T}\\right)=\\sum_{i=1}^{N}e_{i}^{\\mathrm{T}}e_{i},\\quad e_{i}=\\boldsymbol{I}_{1}\\left(\\boldsymbol{p}_{1,i}\\right)-\\boldsymbol{I}_{2}\\left(\\boldsymbol{p}_{2,i}\\right). \\] \\[ \\begin{aligned}&amp;q=TP,\\\\&amp;\\boldsymbol{u}=\\frac{1}{Z_{2}}Kq.\\end{aligned} \\] \\[ e(T)=I_1(p_1)-I_2(u), \\] \\[ \\frac{\\partial e}{\\partial\\boldsymbol{T}}=\\frac{\\partial\\boldsymbol{I}_{2}}{\\partial\\boldsymbol{u}}\\frac{\\partial\\boldsymbol{u}}{\\partial\\boldsymbol{q}}\\frac{\\partial\\boldsymbol{q}}{\\partial\\delta\\boldsymbol{\\xi}}\\delta\\boldsymbol{\\xi}, \\] \\[ \\frac{\\partial\\boldsymbol{u}}{\\partial\\boldsymbol{q}}=\\begin{bmatrix}\\frac{\\partial u}{\\partial X}&amp;\\frac{\\partial u}{\\partial Y}&amp;\\frac{\\partial u}{\\partial Z}\\\\\\frac{\\partial v}{\\partial X}&amp;\\frac{\\partial v}{\\partial Y}&amp;\\frac{\\partial v}{\\partial Z}\\end{bmatrix}=\\begin{bmatrix}\\frac{f_x}{Z}&amp;0&amp;-\\frac{f_xX}{Z^2}\\\\0&amp;\\frac{f_y}{Z}&amp;-\\frac{f_yY}{Z^2}\\end{bmatrix}. \\] \\[ \\frac{\\partial\\boldsymbol{q}}{\\partial\\delta\\boldsymbol{\\xi}}=\\left[I,-\\boldsymbol{q}^{\\wedge}\\right]. \\] \\[ \\frac{\\partial\\boldsymbol{u}}{\\partial\\delta\\boldsymbol{\\xi}}=\\begin{bmatrix}\\frac{f_x}{Z}&amp;0&amp;-\\frac{f_xX}{Z^2}&amp;-\\frac{f_xXY}{Z^2}&amp;f_x+\\frac{f_xX^2}{Z^2}&amp;-\\frac{f_xY}{Z}\\\\0&amp;\\frac{f_y}{Z}&amp;-\\frac{f_yY}{Z^2}&amp;-f_y-\\frac{f_yY^2}{Z^2}&amp;\\frac{f_yXY}{Z^2}&amp;\\frac{f_yX}{Z}\\end{bmatrix}. \\] \\[ J=-\\frac{\\partial I_2}{\\partial u}\\frac{\\partial u}{\\partial\\delta\\xi}. \\]"},{"location":"CV/SLAM14/#842","title":"8.4.2 \u76f4\u63a5\u6cd5\u7684\u8ba8\u8bba","text":""},{"location":"CV/SLAM14/#85","title":"8.5 \u5b9e\u8df5: \u76f4\u63a5\u6cd5","text":""},{"location":"CV/SLAM14/#851","title":"8.5.1 \u5355\u5c42\u76f4\u63a5\u6cd5","text":""},{"location":"CV/SLAM14/#852","title":"8.5.2 \u591a\u5c42\u76f4\u63a5\u6cd5","text":""},{"location":"CV/SLAM14/#853","title":"8.5.3 \u7ed3\u679c\u8ba8\u8bba","text":"<ul> <li>Normalized Cross</li> </ul>"},{"location":"CV/SLAM14/#854","title":"8.5.4 \u76f4\u63a5\u6cd5\u4f18\u7f3a\u70b9\u603b\u7ed3","text":""},{"location":"CV/SLAM14/#9-1","title":"9 \u540e\u7aef 1","text":""},{"location":"CV/SLAM14/#91","title":"9.1 \u6982\u8ff0","text":""},{"location":"CV/SLAM14/#911","title":"9.1.1 \u72b6\u6001\u4f30\u8ba1\u7684\u6982\u7387\u89e3\u91ca","text":"<ul> <li>\u53ea\u4f7f\u7528\u8fc7\u53bb\u7684\u4fe1\u606f: \u6e10\u8fdb\u7684\uff08Incremental\uff09</li> <li>\u4f7f\u7528\u672a\u6765\u7684\u4fe1\u606f\u66f4\u65b0: \u6279\u91cf\u7684\uff08Batch\uff09</li> </ul> \\[ \\begin{cases}\\boldsymbol{x}_k=f\\left(\\boldsymbol{x}_{k-1},\\boldsymbol{u}_k\\right)+\\boldsymbol{w}_k\\\\\\boldsymbol{z}_{k,j}=h\\left(\\boldsymbol{y}_j,\\boldsymbol{x}_k\\right)+\\boldsymbol{v}_{k,j}\\end{cases}\\quad k=1,\\ldots,N, j=1,\\ldots,M. \\] <ul> <li>\u89c2\u6d4b\u65b9\u7a0b\u7684\u6570\u91cf\u4f1a\u8fdc\u8fdc\u5927\u4e8e\u8fd0\u52a8\u65b9\u7a0b</li> <li>\u5f53\u6ca1\u6709\u8fd0\u52a8\u65b9\u7a0b\u7684\u65f6\u5019\uff0c\u6211\u4eec\u53ef\u4ee5\u5047\u8bbe\u76f8\u673a\u4e0d\u52a8\uff0c\u6216\u5047\u8bbe\u76f8\u673a\u5300\u901f\u8fd0\u52a8</li> <li>\u95ee\u9898\uff1a\u5f53\u5b58\u5728\u4e00\u4e9b\u8fd0\u52a8\u6570\u636e\u548c\u89c2\u6d4b\u6570\u636e\u65f6\uff0c\u6211\u4eec\u5982\u4f55\u4f30\u8ba1\u72b6\u6001\u91cf\u7684\u9ad8\u65af\u5206\u5e03</li> <li>\u8bef\u5dee\u65f6\u9010\u6e10\u7d2f\u79ef\u7684</li> <li>\u6700\u5927\u4f3c\u7136\u4f30\u8ba1: \u6279\u91cf\u72b6\u6001\u4f30\u8ba1\u95ee\u9898\u53ef\u4ee5\u8f6c\u5316\u4e3a\u6700\u5927\u4f3c\u7136\u4f30\u8ba1\u95ee\u9898\uff0c\u5e76\u4f7f\u7528\u6700\u5c0f\u4e8c\u4e58\u6cd5\u8fdb\u884c\u6c42\u89e3</li> </ul> \\[ x_k\\stackrel{\\mathrm{def}}{=}\\{x_k,y_1,\\ldots,y_m\\}. \\] \\[ \\begin{cases}\\boldsymbol{x}_k=f\\left(\\boldsymbol{x}_{k-1},\\boldsymbol{u}_k\\right)+\\boldsymbol{w}_k\\\\\\boldsymbol{z}_k=h\\left(\\boldsymbol{x}_k\\right)+\\boldsymbol{v}_k\\end{cases}\\quad k=1,\\ldots,N. \\] \\[ P\\left(\\boldsymbol{x}_k|\\boldsymbol{x}_0,\\boldsymbol{u}_{1:k},\\boldsymbol{z}_{1:k}\\right)\\propto P\\left(\\boldsymbol{z}_k|\\boldsymbol{x}_k\\right)P\\left(\\boldsymbol{x}_k|\\boldsymbol{x}_0,\\boldsymbol{u}_{1:k},\\boldsymbol{z}_{1:k-1}\\right). \\] <ul> <li>\u7b2c\u4e00\u9879\u79f0\u4e3a\u4f3c\u7136\uff0c\u7b2c\u4e8c\u9879\u79f0\u4e3a\u5148\u9a8c</li> </ul> \\[ P\\left(\\boldsymbol{x}_{k}|\\boldsymbol{x}_{0},\\boldsymbol{u}_{1:k},\\boldsymbol{z}_{1:k-1}\\right)=\\int P\\left(\\boldsymbol{x}_{k}|\\boldsymbol{x}_{k-1},\\boldsymbol{x}_{0},\\boldsymbol{u}_{1:k},\\boldsymbol{z}_{1:k-1}\\right)P\\left(\\boldsymbol{x}_{k-1}|\\boldsymbol{x}_{0},\\boldsymbol{u}_{1:k},\\boldsymbol{z}_{1:k-1}\\right)\\mathrm{d}\\boldsymbol{x}_{k-1}. \\] <ul> <li>\u867d\u7136\u53ef\u4ee5\u7ee7\u7eed\u5bf9\u6b64\u5f0f\u8fdb\u884c\u5c55\u5f00\uff0c\u4f46\u6211\u4eec\u53ea\u5173\u5fc3 \\(\\displaystyle k\\) \u65f6\u523b\u548c \\(\\displaystyle k - 1\\) \u65f6\u523b\u7684\u60c5\u51b5<ul> <li>\u7b2c\u4e00\u79cd\u65b9\u6cd5\u662f\u5047\u8bbe\u9a6c\u5c14\u53ef\u592b\u6027: \u5373\u8ba4\u4e3a \\(\\displaystyle k\\) \u65f6\u523b\u72b6\u6001\u53ea\u4e0e \\(\\displaystyle k - 1\\) \u65f6\u523b\u72b6\u6001\u6709\u5173<ul> <li>\u90a3\u4e48\u6211\u4eec\u5c31\u53ef\u4ee5\u5f97\u5230\u4ee5\u6269\u5c55\u5361\u5c14\u66fc\u6ee4\u6ce2\uff08EKF\uff09\u4e3a\u4ee3\u8868\u7684\u6ee4\u6ce2\u5668\u65b9\u5f0f</li> </ul> </li> <li>\u7b2c\u4e8c\u79cd\u65b9\u6cd5\u662f\u4f9d\u7136\u8003\u8651\u548c\u4e4b\u524d\u6240\u6709\u72b6\u6001\u7684\u5173\u7cfb\uff0c\u59ff\u52bf\u4f1a\u5f97\u5230\u975e\u7ebf\u6027\u4f18\u5316\u4e3a\u4e3b\u4f53\u7684\u4f18\u5316\u6846\u67b6\u3002</li> <li>\u4e3b\u6d41\u662f\u975e\u7ebf\u6027\u4f18\u5316</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#912-kf","title":"9.1.2 \u7ebf\u6027\u7cfb\u7edf\u548c KF","text":"\\[ P\\left(\\boldsymbol{x}_k|\\boldsymbol{x}_{k-1},\\boldsymbol{x}_0,\\boldsymbol{u}_{1:k},\\boldsymbol{z}_{1:k-1}\\right)=P\\left(\\boldsymbol{x}_k|\\boldsymbol{x}_{k-1},\\boldsymbol{u}_k\\right). \\] \\[ P\\left(\\boldsymbol{x}_{k-1}|\\boldsymbol{x}_0,\\boldsymbol{u}_{1:k},\\boldsymbol{z}_{1:k-1}\\right)=P\\left(\\boldsymbol{x}_{k-1}|\\boldsymbol{x}_0,\\boldsymbol{u}_{1:k-1},\\boldsymbol{z}_{1:k-1}\\right). \\] <ul> <li>\u6240\u4ee5\u6211\u4eec\u5b9e\u9645\u5728\u505a\u7684\u4e8b\u5982\u4f55\u628a \\(\\displaystyle k - 1\\) \u65f6\u523b\u7684\u72b6\u6001\u5206\u5e03\u63a8\u5bfc\u81f3 \\(\\displaystyle k\\) \u65f6\u523b<ul> <li>\u5373\u6211\u4eec\u53ea\u8981\u7ef4\u62a4\u4e00\u4e2a\u72b6\u6001\uff0c\u5e76\u4e0d\u65ad\u5730\u8fed\u4ee3\u66f4\u65b0<ul> <li>\u53ea\u8981\u7ef4\u62a4\u72b6\u6001\u91cf\u7684\u5747\u503c\u548c\u534f\u65b9\u5dee\uff08\u72b6\u6001\u91cf\u670d\u4ece\u9ad8\u65af\u5206\u5e03\uff09</li> </ul> </li> </ul> </li> </ul> \\[ \\begin{cases}x_k=A_kx_{k-1}+u_k+w_k\\\\z_k=C_kx_k+v_k\\end{cases}\\quad k=1,\\ldots,N. \\] \\[ w_k\\sim N(0,\\boldsymbol{R}).\\quad\\boldsymbol{v}_k\\sim N(\\boldsymbol{0},\\boldsymbol{Q}). \\] <ul> <li>\u4e0a\u5e3d\u5b50\u8868\u793a\u540e\u9a8c\uff0c\u4e0b\u5e3d\u5b50\u8868\u793a\u5148\u9a8c</li> </ul> \\[ P\\left(\\boldsymbol{x}_k|\\boldsymbol{x}_0,\\boldsymbol{u}_{1:k},\\boldsymbol{z}_{1:k-1}\\right)=N\\left(\\boldsymbol{A}_k\\hat{x}_{k-1}+\\boldsymbol{u}_k,\\boldsymbol{A}_k\\hat{\\boldsymbol{P}}_{k-1}\\boldsymbol{A}_k^\\mathrm{T}+\\boldsymbol{R}\\right). \\] <ul> <li>\u8fd9\u4e00\u6b65\u79f0\u4e3a\u9884\u6d4b\uff08Predict\uff09</li> </ul> \\[ \\check{\\boldsymbol{x}}_k=\\boldsymbol{A}_k\\hat{\\boldsymbol{x}}_{k-1}+\\boldsymbol{u}_k,\\quad\\check{\\boldsymbol{P}}_k=A_k\\hat{\\boldsymbol{P}}_{k-1}\\boldsymbol{A}_k^\\mathrm{T}+\\boldsymbol{R}. \\] \\[ P\\left(\\boldsymbol{z}_k|\\boldsymbol{x}_k\\right)=N\\left(\\boldsymbol{C}_k\\boldsymbol{x}_k,\\boldsymbol{Q}\\right). \\] <ul> <li>\u5982\u679c\u7ed3\u679c\u8bbe\u4e3a \\(\\displaystyle x_k\\sim N(\\hat{\\boldsymbol{x}}_k,\\hat{\\boldsymbol{P}}_k)\\)\uff0c\u90a3\u4e48</li> </ul> \\[ N(\\hat{\\boldsymbol{x}}_k,\\hat{\\boldsymbol{P}}_k)=\\eta N\\left(\\boldsymbol{C}_k\\boldsymbol{x}_k,\\boldsymbol{Q}\\right)\\cdot N(\\check{\\boldsymbol{x}}_k,\\check{\\boldsymbol{P}}_k). \\] \\[ (\\boldsymbol{x}_{k}-\\hat{\\boldsymbol{x}}_{k})^{\\mathrm{T}}\\hat{\\boldsymbol{P}}_{k}^{-1}\\left(\\boldsymbol{x}_{k}-\\hat{\\boldsymbol{x}}_{k}\\right)=\\left(\\boldsymbol{z}_{k}-\\boldsymbol{C}_{k}\\boldsymbol{x}_{k}\\right)^{\\mathrm{T}}\\boldsymbol{Q}^{-1}\\left(\\boldsymbol{z}_{k}-\\boldsymbol{C}_{k}\\boldsymbol{x}_{k}\\right)+\\left(\\boldsymbol{x}_{k}-\\check{\\boldsymbol{x}}_{k}\\right)^{\\mathrm{T}}\\boldsymbol{P}_{k}^{-1}\\left(\\boldsymbol{x}_{k}-\\check{\\boldsymbol{x}}_{k}\\right). \\] <ul> <li>\u4e8c\u6b21\u7cfb\u6570</li> </ul> \\[ \\hat{P}_k^{-1}=C_k^{\\mathrm{T}}Q^{-1}C_k+\\check{P}_k^{-1}. \\] <ul> <li>\u5b9a\u4e49\u4e00\u4e2a\u4e2d\u95f4\u53d8\u91cf</li> </ul> \\[ K=\\hat{P}_kC_k^{\\mathrm{T}}Q^{-1}. \\] \\[ I=\\hat{P}_{k}C_{k}^{\\mathrm{T}}Q^{-1}C_{k}+\\hat{P}_{k}\\check{P}_{k}^{-1}=KC_{k}+\\hat{P}_{k}\\check{P}_{k}^{-1}. \\] \\[ \\hat{P}_{k}=(I-KC_{k})\\check{P}_{k}. \\] <ul> <li>\u4e00\u6b21\u9879\u7cfb\u6570</li> </ul> \\[ -2\\hat{\\boldsymbol{x}}_k^\\mathrm{T}\\hat{\\boldsymbol{P}}_k^{-1}\\boldsymbol{x}_k=-2\\boldsymbol{z}_k^\\mathrm{T}\\boldsymbol{Q}^{-1}\\boldsymbol{C}_k\\boldsymbol{x}_k-2\\boldsymbol{\\dot{x}}_k^\\mathrm{T}\\check{\\boldsymbol{P}}_k^{-1}\\boldsymbol{x}_k. \\] \\[ \\hat{\\boldsymbol{P}}_k^{-1}\\hat{\\boldsymbol{x}}_k=\\boldsymbol{C}_k^\\mathrm{T}\\boldsymbol{Q}^{-1}\\boldsymbol{z}_k+\\check{\\boldsymbol{P}}_k^{-1}\\check{\\boldsymbol{x}}_k. \\] \\[ \\begin{aligned} \\hat{x}_{k}&amp; =\\hat{\\boldsymbol{P}}_k\\boldsymbol{C}_k^\\mathrm{T}\\boldsymbol{Q}^{-1}\\boldsymbol{z}_k+\\hat{\\boldsymbol{P}}_k\\check{\\boldsymbol{P}}_k^{-1}\\check{\\boldsymbol{x}}_k \\\\ &amp;=K\\boldsymbol{z}_k+\\left(\\boldsymbol{I}-\\boldsymbol{K}\\boldsymbol{C}_k\\right)\\check{\\boldsymbol{x}}_k=\\check{\\boldsymbol{x}}_k+\\boldsymbol{K}\\left(\\boldsymbol{z}_k-\\boldsymbol{C}_k\\check{\\boldsymbol{x}}_k\\right). \\end{aligned} \\]"},{"location":"CV/SLAM14/#913-ekf","title":"9.1.3 \u975e\u7ebf\u6027\u7cfb\u7edf\u548c EKF","text":"<ul> <li>\u6269\u5c55\u5361\u5c14\u66fc\u6ee4\u6ce2\u5668<ul> <li>\u5373\u628a\u975e\u9ad8\u65af\u5206\u5e03\u8fd1\u4f3c\u6210\u9ad8\u65af\u5206\u5e03</li> </ul> </li> </ul> \\[ \\boldsymbol{x}_k\\approx f\\left(\\hat{\\boldsymbol{x}}_{k-1},\\boldsymbol{u}_k\\right)+\\left.\\frac{\\partial f}{\\partial\\boldsymbol{x}_{k-1}}\\right|_{\\tilde{\\boldsymbol{x}}_{k-1}}\\left(\\boldsymbol{x}_{k-1}-\\hat{\\boldsymbol{x}}_{k-1}\\right)+\\boldsymbol{w}_k. \\] \\[ \\boldsymbol{F}=\\left.\\frac{\\partial f}{\\partial\\boldsymbol{x}_{k-1}}\\right|_{\\hat{\\boldsymbol{x}}_{k-1}}. \\] \\[ z_k\\approx h\\left(\\check{\\boldsymbol{x}}_k\\right)+\\left.\\frac{\\partial h}{\\partial\\boldsymbol{x}_k}\\right|_{\\dot{\\boldsymbol{x}}_k}\\left(\\boldsymbol{x}_k-\\check{\\boldsymbol{x}}_k\\right)+\\boldsymbol{n}_k. \\] \\[ H=\\left.\\frac{\\partial h}{\\partial\\boldsymbol{x}_k}\\right|_{\\check{\\boldsymbol{x}}_k}. \\] \\[ P\\left(\\boldsymbol{x}_k|\\boldsymbol{x}_0,\\boldsymbol{u}_{1:k},\\boldsymbol{z}_{0:k-1}\\right)=N(f\\left(\\hat{\\boldsymbol{x}}_{k-1},\\boldsymbol{u}_k\\right),\\boldsymbol{F}\\hat{\\boldsymbol{P}}_{k-1}\\boldsymbol{F}^\\mathrm{T}+\\boldsymbol{R}_k). \\] \\[ \\check{\\boldsymbol{x}}_k=f\\left(\\hat{\\boldsymbol{x}}_{k-1},\\boldsymbol{u}_k\\right),\\quad\\check{\\boldsymbol{P}}_k=\\boldsymbol{F}\\hat{\\boldsymbol{P}}_{k-1}\\boldsymbol{F}^\\mathrm{T}+\\boldsymbol{R}_k. \\] \\[ P\\left(\\boldsymbol{z}_k|\\boldsymbol{x}_k\\right)=N(h\\left(\\check{\\boldsymbol{x}}_k\\right)+\\boldsymbol{H}\\left(\\boldsymbol{x}_k-\\check{\\boldsymbol{x}}_k\\right),Q_k). \\] <ul> <li>\u5b9a\u4e49\u4e00\u4e2a\u5361\u5c14\u66fc\u589e\u76ca \\(\\displaystyle \\boldsymbol{K}_{k}\\)</li> </ul> \\[ K_{k}=\\check{P}_{k}H^{\\mathrm{T}}(H\\check{P}_{k}H^{\\mathrm{T}}+Q_{k})^{-1}. \\] \\[ \\hat{\\boldsymbol{x}}_k=\\check{\\boldsymbol{x}}_k+\\boldsymbol{K}_k\\left(\\boldsymbol{z}_k-h\\left(\\check{\\boldsymbol{x}}_k\\right)\\right),\\hat{\\boldsymbol{P}}_k=\\left(\\boldsymbol{I}-\\boldsymbol{K}_k\\boldsymbol{H}\\right)\\check{\\boldsymbol{P}}_k. \\]"},{"location":"CV/SLAM14/#914-ekf","title":"9.1.4 EKF \u7684\u8ba8\u8bba","text":"<ul> <li>\u5c40\u9650<ul> <li>\u5047\u8bbe\u4e86\u9a6c\u5c14\u53ef\u592b\u6027\uff0c\u4f46\u662f\u975e\u7ebf\u6027\u4f18\u5316\u662f\u5168\u4f53\u65f6\u95f4\u4e0a\u7684 SLAM (Full-SLAM)</li> <li>\u6709\u975e\u7ebf\u6027\u8bef\u5dee\uff08\u4e3b\u8981\u95ee\u9898\u6240\u5728\uff09</li> <li>\u5982\u679c\u628a\u8def\u6807\u4e5f\u653e\u8fdb\u72b6\u6001\uff0c\u5b58\u4e0d\u4e0b</li> <li>\u6ca1\u6709\u5f02\u5e38\u68c0\u6d4b\u673a\u5236</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#92-ba","title":"9.2 BA \u4e0e\u56fe\u4f18\u5316","text":"<ul> <li>Bundle Adjustment<ul> <li>\u4ece\u89c6\u89c9\u56fe\u50cf\u4e2d\u63d0\u70bc\u51fa\u6700\u6709\u7684 3 D \u6a21\u578b\u548c\u76f8\u673a\u53c2\u6570\uff0c\u8ba9\u5149\u7ebf\u6700\u7ec8\u6536\u675f\u5230\u76f8\u673a\u7684\u5149\u5fc3</li> </ul> </li> </ul>"},{"location":"CV/SLAM14/#921-ba","title":"9.2.1 \u6295\u5f71\u6a21\u578b\u548c BA \u4ee3\u4ef7\u51fd\u6570","text":"\\[ P^{\\prime}=Rp+t=[X^{\\prime},Y^{\\prime},Z^{\\prime}]^\\mathrm{T}. \\] \\[ \\boldsymbol{P}_{\\mathrm{c}}=[u_{\\mathrm{c}},v_{\\mathrm{c}},1]^{\\mathrm{T}}=[X^{\\prime}/Z^{\\prime},Y^{\\prime}/Z^{\\prime},1]^{\\mathrm{T}}. \\] \\[ \\begin{cases}u_\\mathrm{c}'=u_\\mathrm{c}\\left(1+k_1r_\\mathrm{c}^2+k_2r_\\mathrm{c}^4\\right)\\\\v_\\mathrm{c}'=v_\\mathrm{c}\\left(1+k_1r_\\mathrm{c}^2+k_2r_\\mathrm{c}^4\\right)\\end{cases}. \\] \\[ \\begin{cases}u_s=f_xu_\\mathrm{c}'+c_x\\\\[2ex]v_s=f_yv_\\mathrm{c}'+c_y\\end{cases}. \\] \\[ z=h(\\boldsymbol{x},\\boldsymbol{y}). \\] \\[ e=z-h(\\boldsymbol{T},\\boldsymbol{p}). \\] \\[ z\\overset{\\mathrm{def}}{\\operatorname*{=}}[u_s,v_s]^\\mathrm{T} \\] \\[ \\frac12\\sum_{i=1}^m\\sum_{j=1}^n\\|e_{ij}\\|^2=\\frac12\\sum_{i=1}^m\\sum_{j=1}^n\\|z_{ij}-h(\\boldsymbol{T}_i,\\boldsymbol{p}_j)\\|^2. \\]"},{"location":"CV/SLAM14/#922-ba","title":"9.2.2 BA \u7684\u6c42\u89e3","text":"\\[ x=[T_1,\\ldots,T_m,p_1,\\ldots,p_n]^\\mathrm{T}. \\] \\[ \\frac12\\left\\|f(\\boldsymbol{x}+\\Delta\\boldsymbol{x})\\right\\|^2\\approx\\frac12\\sum_{i=1}^m\\sum_{j=1}^n\\left\\|\\boldsymbol{e}_{ij}+\\boldsymbol{F}_{ij}\\Delta\\boldsymbol{\\xi}_i+\\boldsymbol{E}_{ij}\\Delta\\boldsymbol{p}_j\\right\\|^2. \\] \\[ x_{\\mathfrak{c}}=[\\boldsymbol{\\xi}_1,\\boldsymbol{\\xi}_2,\\ldots,\\boldsymbol{\\xi}_m]^{\\mathrm{T}}\\in\\mathbb{R}^{6m} \\] \\[ \\boldsymbol{x}_p=[\\boldsymbol{p}_1,\\boldsymbol{p}_2,\\ldots,\\boldsymbol{p}_n]^\\mathrm{T}\\in\\mathbb{R}^{3n} \\] \\[ \\frac12\\left\\|f(\\boldsymbol{x}+\\Delta\\boldsymbol{x})\\right\\|^2=\\frac12\\left\\|\\boldsymbol{e}+\\boldsymbol{F}\\Delta\\boldsymbol{x}_c+\\boldsymbol{E}\\Delta\\boldsymbol{x}_p\\right\\|^2. \\] \\[ \\boldsymbol{J}=[\\boldsymbol{F}\\boldsymbol{E}]. \\] \\[ H=J^\\mathrm{T}J=\\begin{bmatrix}F^\\mathrm{T}F&amp;F^\\mathrm{T}E\\\\E^\\mathrm{T}F&amp;E^\\mathrm{T}E\\end{bmatrix}. \\]"},{"location":"CV/SLAM14/#923","title":"9.2.3 \u7a00\u758f\u6027\u548c\u8fb9\u7f18\u5316","text":"\\[ J_{ij}(x)=\\left(\\mathbf{0}_{2\\times6},\\ldots\\mathbf{0}_{2\\times6},\\frac{\\partial\\boldsymbol{e}_{ij}}{\\partial\\boldsymbol{T}_{i}},\\mathbf{0}_{2\\times6},\\ldots\\mathbf{0}_{2\\times3},\\ldots\\mathbf{0}_{2\\times3},\\frac{\\partial\\boldsymbol{e}_{ij}}{\\partial\\boldsymbol{p}_{j}},\\mathbf{0}_{2\\times3},\\ldots\\mathbf{0}_{2\\times3}\\right). \\] \\[ H=\\sum_{i,j}J_{ij}^{\\top}J_{ij}, \\] \\[ H=\\begin{bmatrix}H_{11}&amp;H_{12}\\\\\\\\H_{21}&amp;H_{22}\\end{bmatrix}. \\] <ul> <li>\u5bf9\u4e8e\u7a00\u758f\u77e9\u9635\uff0c\u6211\u4eec\u7528 Schur \u6d88\u5143\uff08Marginalization\uff09</li> </ul> \\[ \\begin{bmatrix}B&amp;E\\\\E^\\mathrm{T}&amp;C\\end{bmatrix}\\begin{bmatrix}\\Delta x_\\mathrm{c}\\\\\\Delta x_p\\end{bmatrix}=\\begin{bmatrix}v\\\\w\\end{bmatrix}. \\] \\[ \\begin{bmatrix}I&amp;-EC^{-1}\\\\0&amp;I\\end{bmatrix}\\begin{bmatrix}B&amp;E\\\\E^{\\intercal}&amp;C\\end{bmatrix}\\begin{bmatrix}\\Delta x_\\mathrm{c}\\\\\\Delta x_p\\end{bmatrix}=\\begin{bmatrix}I&amp;-EC^{-1}\\\\0&amp;I\\end{bmatrix}\\begin{bmatrix}v\\\\w\\end{bmatrix}. \\] \\[ \\begin{bmatrix}B-EC^{-1}E^\\mathrm{T}&amp;0\\\\E^\\mathrm{T}&amp;C\\end{bmatrix}\\begin{bmatrix}\\Delta x_\\mathrm{c}\\\\\\Delta x_p\\end{bmatrix}=\\begin{bmatrix}v-EC^{-1}w\\\\\\\\w\\end{bmatrix}. \\] \\[ \\begin{bmatrix}B-EC^{-1}E^\\mathrm{T}\\end{bmatrix}\\Delta x_\\mathrm{c}=v-EC^{-1}w. \\] <ul> <li>\u4f18\u52bf<ul> <li>\\(\\displaystyle \\boldsymbol{C}\\) \u4e3a\u5bf9\u89d2\u5757\uff0c\u9006\u6bd4\u8f83\u5bb9\u6613\u89e3\u51fa</li> </ul> </li> <li>\u975e\u5bf9\u89d2\u7ebf\u4e0a\u7684\u975e\u96f6\u77e9\u9635\u5757\u8868\u793a\u5bf9\u5e94\u7684\u4e24\u4e2a\u76f8\u673a\u53d8\u91cf\u4e4b\u95f4\u5b58\u5728\u5171\u540c\u89c2\u6d4b\u7684\u8def\u6807\u70b9\uff0c\u5373\u5171\u89c6\uff08Co-visibility\uff09</li> </ul>"},{"location":"CV/SLAM14/#924","title":"9.2.4 \u9c81\u68d2\u6838\u51fd\u6570","text":"<ul> <li>Robust Kernel</li> </ul> \\[ H(e)=\\begin{cases}\\frac{1}{2}e^2&amp;\\text{\u5f53}|e|\\leqslant\\delta,\\\\\\\\\\delta\\left(|e|-\\frac{1}{2}\\delta\\right)&amp;\\text{\u5176\u4ed6}\\end{cases} \\]"},{"location":"CV/SLAM14/#93-ceres-ba","title":"9.3 \u5b9e\u8df5: Ceres BA","text":""},{"location":"CV/SLAM14/#931-bal","title":"9.3.1 BAL \u6570\u636e\u96c6","text":""},{"location":"CV/SLAM14/#932-ceres-ba","title":"9.3.2 Ceres BA \u7684\u4e66\u5199","text":""},{"location":"CV/SLAM14/#94-g-2-o-ba","title":"9.4 \u5b9e\u8df5: g 2 o \u6c42\u89e3 BA","text":""},{"location":"CV/SLAM14/#95","title":"9.5 \u5c0f\u7ed3","text":""},{"location":"CV/SLAM14/#10-2","title":"10 \u540e\u7aef 2","text":""},{"location":"CV/SLAM14/#11_1","title":"11 \u56de\u73af\u68c0\u6d4b","text":""},{"location":"CV/SLAM14/#12_1","title":"12 \u5efa\u56fe","text":""},{"location":"CV/SLAM14/#13-slam","title":"13 \u5b9e\u8df5: \u8bbe\u8ba1 SLAM \u7cfb\u7edf","text":""},{"location":"CV/SLAM14/#14-slam","title":"14 SLAM: \u73b0\u5728\u4e0e\u672a\u6765","text":""},{"location":"Environment/","title":"Environmet Setup","text":""},{"location":"Environment/#environment","title":"Environment","text":"<p>Abstract</p> <p>\u672c\u90e8\u5206\u5185\u5bb9\uff08\u9664\u7279\u522b\u58f0\u660e\u5916\uff09\u91c7\u7528 \u7f72\u540d-\u975e\u5546\u4e1a\u6027\u4f7f\u7528-\u4fdd\u6301\u4e00\u81f4 4.0 \u56fd\u9645 (CC BY-NC-SA 4.0) \u8bb8\u53ef\u534f\u8bae\u8fdb\u884c\u8bb8\u53ef\u3002</p> envirtonment          <ul> <li> environment  227  1 mins              1734014421 </li> </ul> software          <ul> <li> obsidian  301  1 mins              1734012860 </li> </ul> Ubuntu          <ul> <li> Ubuntu  77  14  0 mins              1734012860 </li> </ul>"},{"location":"Environment/Ubuntu_setup/","title":"Ubuntu \u914d\u7f6e","text":""},{"location":"Environment/Ubuntu_setup/#ubuntu","title":"Ubuntu \u914d\u7f6e","text":"<p> \u7ea6 77 \u4e2a\u5b57  14 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <ul> <li>\u5728 Ubuntu \u5b89\u88c5\u914d\u7f6e Fcitx 5 \u4e2d\u6587\u8f93\u5165\u6cd5 - muzing\u7684\u6742\u8d27\u94fa</li> <li>fcitx5-rime \u6302\u63a5\u5c0f\u9e64\u97f3\u5f62 | rovo98's Blog</li> <li>zhuanlan.zhihu.com/p/660191327#:~:text=Tabby\uff08\u4ee5\u524d\u79f0\u4e3a</li> <li>Zsh \u5b89\u88c5\u4e0e\u914d\u7f6e\uff0c\u4f7f\u7528 Oh-My-Zsh \u7f8e\u5316\u7ec8\u7aef | Leehow\u7684\u5c0f\u7ad9</li> <li>zhuanlan.zhihu.com/p/658811059</li> <li>PKMer_TiddyWiki \u7b80\u6613\u6307\u5357</li> <li>Site Unreachable</li> <li>Jedsek | Blog</li> </ul> Bash<pre><code>visudo /etc/sudoers \n%sudo   ALL=(ALL:ALL) NOPASSWD: ALL\n</code></pre> Bash<pre><code>git clone https://github.com/zsh-users/zsh-syntax-highlighting.git ${ZSH_CUSTOM:-~/.oh-my-zsh/custom}/plugins/zsh-syntax-highlighting\n\ngit clone https://github.com/zsh-users/zsh-autosuggestions ${ZSH_CUSTOM:-~/.oh-my-zsh/custom}/plugins/zsh-autosuggestions\n\ngit clone git://github.com/joelthelion/autojump.git\ncd autojump\n./install.py\n\n[[ -s ~/.autojump/etc/profile.d/autojump.sh ]] &amp;&amp; . ~/.autojump/etc/profile.d/autojump.sh\n</code></pre> <ul> <li>\u622a\u56fe\u8f6f\u4ef6</li> </ul> Bash<pre><code>sudo apt-get install flameshot\nflameshot gui\n</code></pre> <ul> <li>\u5728 Ubuntu 22.04|20.04|18.04 \u4e0a\u5b89\u88c5 Node.js 20</li> </ul>"},{"location":"Environment/environment/","title":"Environment","text":"<ul> <li>\u5f00\u53d1\u73af\u5883\u6784\u5efa\u6307\u5357 </li> </ul> <p> \u7ea6 227 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <ul> <li>\u4ece\u96f6\u5f00\u59cb\u914d\u7f6e Windows \u2022 Arthals' ink </li> <li>\u4ece\u96f6\u5f00\u59cb\u914d\u7f6e Linux \u2022 Arthals' ink </li> <li>\u670d\u52a1\u5668\u73af\u5883\u914d\u7f6e Cheat Sheet | Yi Pan (Conless) </li> <li>clash </li> <li>powertoy </li> <li>gsudo </li> <li>git <ul> <li>GitHub - Wybxc/git-remake-guide: Git \u91cd\u5f00/\u91cd\u5b66\u6307\u5357 </li> </ul> </li> <li>picgo <ul> <li>picgo + github + obsidian </li> </ul> </li> <li>vscode<ul> <li>\u7cfb\u7edf + \u4ee3\u7801\u5b57\u4f53\u8bbe\u7f6e</li> <li>zhuanlan.zhihu.com/p/603687041#:~:text=clangd\u5b98\u65b9vs</li> <li>zhuanlan.zhihu.com/p/398790625#:~:text=\u5176\u4e2d VS Code</li> </ul> </li> <li>tools<ul> <li>GitHub - jenius-apps/ambie: An app that uses white noise, nature sounds, and focus features to boost your productivity. </li> </ul> </li> <li>clash <ul> <li>GitHub - Loyalsoldier/clash-rules: \ud83e\udd84\ufe0f\ud83c\udf83\ud83d\udc7b Clash Premium \u89c4\u5219\u96c6(RULE-SET)\uff0c\u517c\u5bb9 ClashX Pro\u3001Clash for Windows \u7b49\u57fa\u4e8e Clash Premium \u5185\u6838\u7684\u5ba2\u6237\u7aef\u3002 </li> <li>Site Unreachable </li> <li>\u7ffb\u5899 | Blog</li> <li>GitHub - vpncn/vpncn.github.io: 2024\u4e2d\u56fd\u7ffb\u5899\u8f6f\u4ef6VPN\u63a8\u8350\u4ee5\u53ca\u79d1\u5b66\u4e0a\u7f51\u907f\u5751\uff0c\u7a33\u5b9a\u597d\u7528\u3002\u5bf9\u6bd4SSR\u673a\u573a\u3001\u84dd\u706f\u3001V2ray\u3001\u8001\u738bVPN\u3001VPS\u642d\u5efa\u68af\u5b50\u7b49\u79d1\u5b66\u4e0a\u7f51\u4e0e\u7ffb\u5899\u8f6f\u4ef6\uff0c\u4e2d\u56fd\u6700\u65b0\u79d1\u5b66\u4e0a\u7f51\u7ffb\u5899\u68af\u5b50VPN\u4e0b\u8f7d\u63a8\u8350\uff0c\u8bbf\u95eeChatgpt\u3002 </li> </ul> </li> <li>Typora <ul> <li>GitHub - sylviaxgj/typora-forest-theme: another typora theme</li> <li>GitHub - HappySimple/Typora-theme-Happysimple: \u4e00\u6b3e\u81ea\u5236\u7684Markdown\u4e3b\u9898\uff01</li> </ul> </li> <li>github profiles <ul> <li>GitHub - anuraghazra/github-readme-stats:  Dynamically generated stats for your github readmes </li> </ul> </li> <li>github action </li> <li>gsudo</li> <li>openArk</li> </ul>"},{"location":"Environment/obsidian_setup/","title":"obsidian \u914d\u7f6e","text":""},{"location":"Environment/obsidian_setup/#obsidian","title":"obsidian \u914d\u7f6e","text":"<p> \u7ea6 301 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> Note <p>\u5982\u679c\u61d2\u5f97\u641e\uff0c\u53ef\u4ee5\u76f4\u63a5 clone \u6211\u7684\u914d\u7f6e\uff0c\u653e\u5230 .obsidian \u6587\u4ef6\u91cc\u3002 \u8fd9\u662f\u914d\u7f6e\u6587\u4ef6\u3002</p>"},{"location":"Environment/obsidian_setup/#1","title":"1 \u4f7f\u7528\u8bed\u8a00","text":"<ul> <li>\u4e3b\u8981\u662f Markdown</li> <li>\u914d\u7f6e\u63d2\u4ef6\u4e5f\u4f1a\u6d89\u53ca\u4e00\u4e9b javascript</li> </ul>"},{"location":"Environment/obsidian_setup/#2","title":"2 \u63d2\u4ef6","text":""},{"location":"Environment/obsidian_setup/#21-displaystyle-latex","title":"2.1 \\(\\displaystyle \\LaTeX\\)","text":"<ul> <li>Latex Suite</li> <li>LaTex-like Theorem &amp; Equation Referencer</li> <li>MathLinks  </li> </ul> <p>\u642d\u914d simpleTex \u4f7f\u7528</p>"},{"location":"Environment/obsidian_setup/#22","title":"2.2 \u7f16\u8f91\u589e\u5f3a","text":"<ul> <li>Easy Typing</li> <li>Linter</li> <li>Remember cursor position</li> <li>PDF++</li> <li>Code Styler</li> <li>Number Headings</li> <li>Outliner</li> <li>Completr</li> <li>Mind map</li> <li>Excalidraw</li> </ul>"},{"location":"Environment/obsidian_setup/#23","title":"2.3 \u56fe\u7247","text":"<ul> <li>Paste image rename</li> <li>Auto Link Title</li> <li>Image auto upload Plugin</li> </ul> <p>\u642d\u914d Picgo + GitHub \u4f7f\u7528</p>"},{"location":"Environment/obsidian_setup/#24","title":"2.4 \u540c\u6b65\u5907\u4efd","text":"<ul> <li>Git</li> <li>Remotely Save</li> </ul>"},{"location":"Environment/obsidian_setup/#25","title":"2.5 \u65e5\u7a0b","text":"<ul> <li>Calendar</li> <li>Periodic Notes</li> <li>Tasks Progress Bar</li> <li>Tasks</li> <li>Tasks Calendar Wrapper</li> </ul>"},{"location":"Environment/obsidian_setup/#26","title":"2.6 \u4ecd\u5728\u63a2\u7d22","text":"<ul> <li>Local REST API + \u7b80\u7ea6</li> <li>RSS Reader</li> </ul>"},{"location":"Environment/obsidian_setup/#_1","title":"\u6211\u7684\u6a21\u677f","text":"<p>\u9700\u8981\u5b89\u88c5 dataview + periodic notes \u63d2\u4ef6\u3002</p> <p>Note</p> <p>\u7531\u4e8e markdown \u4ee3\u7801\u5757\u5d4c\u5957\u4e0d\u592a\u884c\uff0c\u6240\u4ee5\u8981\u624b\u52a8\u4fee\u590d\u3002\u6ce8\u610f\u4fee\u590d '' \u5e26\u6765\u7684\u4ee3\u7801\u5757\u95ee\u9898</p> dailyweekly Note Text Only<pre><code># {{date:YYYY}}-{{date:WW}}-{{date:DD}}-{{date:HH}}-{{date:d}}\n\n## 1. \u8ba1\u5212\n\n### \ud83c\udf05 \u65e9\u6668\n\n#### \u8ba1\u5212 \n\n#### \u590d\u76d8 \n\n---\n\n### \u2600\ufe0f \u4e2d\u5348\n\n#### \u8ba1\u5212 \n\n#### \u590d\u76d8 \n\n---\n\n### \ud83c\udf07 \u665a\u4e0a\n\n#### \u8ba1\u5212\n\n#### \u590d\u76d8 \n\n---\n\n## 2. \u7b14\u8bb0\u7d22\u5f15\n\n``dataview\nLIST FROM \"\"\nWHERE file.cday = date(\"{{date:YYYY}}-{{date:MM}}-{{date:DD}}\")\n``\n\n---\n\n## 3. \u8d44\u6e90\u4e0e\u94fe\u63a5\n\n---\n\n## 4. \u672a\u5b8c\u6210\u7684\u4efb\u52a1\n\n``dataview\nTASK FROM \"dairy\"\nWHERE !completed\nAND file.cday &gt;= (this.file.cday - dur(7 days))\nAND file.cday &lt;= this.file.cday\nSORT file.cday DESC\n``\n\n---\n\n## 5. \u53cd\u601d\n</code></pre> Note Text Only<pre><code># {{date:YYYY}}-W{{date:WW}}-{{date:DD}}\n\n## 1. \u672c\u5468\u590d\u76d8\n\n---\n\n## 2. \u4e0b\u5468\u8ba1\u5212\n</code></pre>"},{"location":"Environment/obsidian_setup/#3","title":"3 \u76f8\u5173\u94fe\u63a5","text":"<ul> <li>PKMer_PKMer</li> <li>Obsidian \u4e2d\u6587\u8bba\u575b - Obsidian \u77e5\u8bc6\u7ba1\u7406 \u7b14\u8bb0</li> <li>Obsidian\u6587\u6863\u5496\u5561\u8c46\u7248 | Obsidian Docs by CoffeeBean</li> <li>zhuanlan.zhihu.com/p/619960525</li> </ul>"},{"location":"Robot/","title":"Robot","text":""},{"location":"Robot/#robot","title":"Robot","text":"<p>Abstract</p> <p>\u672c\u90e8\u5206\u5185\u5bb9\uff08\u9664\u7279\u522b\u58f0\u660e\u5916\uff09\u91c7\u7528 \u7f72\u540d-\u975e\u5546\u4e1a\u6027\u4f7f\u7528-\u4fdd\u6301\u4e00\u81f4 4.0 \u56fd\u9645 (CC BY-NC-SA 4.0) \u8bb8\u53ef\u534f\u8bae\u8fdb\u884c\u8bb8\u53ef\u3002</p> \u8f6f\u4ef6          <ul> <li> \u76f8\u673a\u6807\u5b9a  73  0 mins              1734024510 </li> <li> \u5361\u5c14\u66fc\u6ee4\u6ce2  193  115  2 mins              1734024510 </li> <li> PnP \u7b97\u6cd5  79  55  1 mins              1734012860 </li> </ul>"},{"location":"Robot/calibration/","title":"Calibration","text":"<p>Calibration</p> <p> \u7ea6 73 \u4e2a\u5b57  1 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4\u4e0d\u5230 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <ul> <li>GitHub - SHU-FLYMAN/CalibCamera: \u57fa\u4e8e\u5f20\u6b63\u53cb\u6807\u5b9a\u6cd5\u7684\u5355\u76ee\u76f8\u673a\u6807\u5b9a\u7406\u8bba\u5230\u5b9e\u8df5</li> <li>\u4e00\u6587\u5403\u900f\u76f8\u673a\u6807\u5b9a\uff08Camera calibration\uff09-CSDN\u535a\u5ba2</li> <li>\u6700\u8be6\u7ec6\u3001\u6700\u5b8c\u6574\u7684\u76f8\u673a\u6807\u5b9a\u8bb2\u89e3-CSDN\u535a\u5ba2</li> <li>\u76f8\u673a\u6807\u5b9a\uff08Camera calibration\uff09\u539f\u7406\u3001\u6b65\u9aa4_\u89c6\u89c9\u76f8\u673a \u793a\u6559\u76ee\u7684-CSDN\u535a\u5ba2 </li> </ul>"},{"location":"Robot/kalman/","title":"\u5361\u5c14\u66fc\u6ee4\u6ce2","text":""},{"location":"Robot/kalman/#_1","title":"\u5361\u5c14\u66fc\u6ee4\u6ce2","text":"<p> \u7ea6 193 \u4e2a\u5b57  115 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"Robot/kalman/#1-why","title":"1 Why","text":"<ul> <li>\u5dee\u5206<ul> <li>\u53d7\u566a\u58f0\u5e72\u6270\u5927</li> <li>\u6709\u5ef6\u8fdf</li> <li>\u901f\u5ea6\u4e0d\u8fde\u7eed\uff08\u4e0d\u80fd\u5f97\u5230\u77ac\u65f6\u901f\u5ea6\uff09</li> </ul> </li> </ul>"},{"location":"Robot/kalman/#2-how","title":"2 How","text":""},{"location":"Robot/kalman/#21","title":"2.1 \u5361\u5c14\u66fc\u6ee4\u6ce2","text":"<ul> <li>\u5408\u7406\u5730\u6839\u636e\u8bef\u5dee\u6765\u63a8\u5bfc\uff0c\u800c\u4e0d\u662f\u76f4\u63a5\u5ffd\u89c6\u5f71\u54cd\u6700\u7ec8\u91cf<ul> <li>\u65e0\u4eba\u9a7e\u9a76\u6280\u672f\u5165\u95e8\uff08\u5341\u4e09\uff09| \u624b\u628a\u624b\u6559\u4f60\u5199\u5361\u5c14\u66fc\u6ee4\u6ce2\u5668 - \u77e5\u4e4e </li> </ul> </li> </ul> \\[ \\begin{array}{|c|}\\hline\\textbf{Prediction}\\\\\\hline x^{'}=Ax+u\\\\P^{'}=APA^{T}+R\\\\\\hline\\textbf{Measurement update}\\\\\\hline y=z-Cx^{'}\\\\S=CPC^{T}+Q\\\\K=PC^{T}S^{-1}\\\\x=x^{'}+Ky\\\\P=(I-KC)P\\\\\\hline\\end{array} \\] C++<pre><code>#include &lt;iostream&gt;\n#include &lt;cstdio&gt;\n#include &lt;string&gt;\n#include &lt;vector&gt;\n#include &lt;ctime&gt;\n#include &lt;opencv2/core/core.hpp&gt;\n#include &lt;opencv2/highgui/highgui.hpp&gt;\n#include &lt;opencv2/imgproc/imgproc.hpp&gt;\n#include &lt;Eigen/Dense&gt;\n#include &lt;opencv2/core/eigen.hpp&gt;\nusing namespace std;\nusing namespace cv;\nusing namespace Eigen;\n\nint main() {\nsrand((unsigned int) time(NULL));\n// generate data with noise\nconst int N = 20;\nconst double k = 2.5;\nMatrix&lt;double, 1, N&gt; noise = Matrix&lt;double, 1, N&gt;::Random();\nMatrix&lt;double, 1, N&gt; data = Matrix&lt;double, 1, N&gt;::LinSpaced(0, k * (N - 1));\ndata += noise;\nstd::cout &lt;&lt; data &lt;&lt; std::endl;\n// calculate speed\nconst int Z_N = 1, X_N = 2;\nMatrix&lt;double, X_N, 1&gt; X;\nMatrix&lt;double, X_N, X_N&gt; A;\nMatrix&lt;double, X_N, X_N&gt; P;\nMatrix&lt;double, X_N, X_N&gt; R;\nMatrix&lt;double, X_N, Z_N&gt; K;\nMatrix&lt;double, Z_N, X_N&gt; C;\nMatrix&lt;double, Z_N, Z_N&gt; Q;\n\nX &lt;&lt; data[0], 0;\nA &lt;&lt; 1, 1, 0, 1;\nC &lt;&lt; 1, 0;\nR &lt;&lt; 2, 0, 0, 2;\nQ &lt;&lt; 10;\nfor (int i = 1; i &lt; N; i++) {\n    // \u66f4\u65b0\u9884\u6d4b\n    Matrix&lt;double, X_N, 1&gt; X_k = A * X;\n    P = A * P * A.transpose() + R;\n    // \u66f4\u65b0\u89c2\u6d4b\n    K = P * C.transpose() * (C * P * C.transpose() + Q).inverse();\n    Matrix&lt;double, Z_N, 1&gt; Z{data[i]};\n    X = X_k + K * (Z - C * X_k);\n    P = (Matrix&lt;double, X_N, X_N&gt;::Identity() - K * C) * P;\n    std::cout &lt;&lt; \"step \" &lt;&lt; i &lt;&lt; \": \" &lt;&lt; X[1] &lt;&lt; std::endl;\n}\nstd:cout &lt;&lt; \"final speed: \" &lt;&lt; X[1] &lt;&lt; std::endl;\nreturn 0;\n}\n</code></pre>"},{"location":"Robot/kalman/#22-ekf","title":"2.2 EKF \u7b97\u6cd5\u7684\u5b9e\u73b0","text":"C++<pre><code>#include &lt;ceres/jet.h&gt;\n#include &lt;Eigen/Dense&gt;\n\ntemplate&lt;int N_X, int N_Y&gt;\nclass AdaptiveEKF {\n    using MatrixXX = Eigen::Matrix&lt;double, N_X, N_X&gt;;\n    using MatrixYX = Eigen::Matrix&lt;double, N_Y, N_X&gt;;\n    using MatrixXY = Eigen::Matrix&lt;double, N_X, N_Y&gt;;\n    using MatrixYY = Eigen::Matrix&lt;double, N_Y, N_Y&gt;;\n    using VectorX = Eigen::Matrix&lt;double, N_X, 1&gt;;\n    using VectorY = Eigen::Matrix&lt;double, N_Y, 1&gt;;\n\npublic:\n    explicit AdaptiveEKF(const VectorX &amp;X0 = VectorX::Zero())\n            : Xe(X0), P(MatrixXX::Identity()), Q(MatrixXX::Identity()), R(MatrixYY::Identity()) {}\n\n    // \u9884\u6d4b\u51fd\u6570\n    template&lt;class Func&gt;\n    VectorX predict(Func &amp;&amp;func) {\n        calculateJacobian(Xe, func, Xp, F);\n        P = F * P * F.transpose() + Q;\n        return Xp;\n    }\n\n    // \u66f4\u65b0\u51fd\u6570\n    template&lt;class Func&gt;\n    VectorX update(Func &amp;&amp;func, const VectorY &amp;Y) {\n        calculateJacobian(Xp, func, Yp, H);\n        MatrixYY S = H * P * H.transpose() + R;  // \u521b\u65b0\u534f\u65b9\u5dee\n        K = P * H.transpose() * S.inverse();     // \u5361\u5c14\u66fc\u589e\u76ca\n        Xe = Xp + K * (Y - Yp);                  // \u66f4\u65b0\u72b6\u6001\u4f30\u8ba1\n        P = (MatrixXX::Identity() - K * H) * P;  // \u66f4\u65b0\u72b6\u6001\u534f\u65b9\u5dee\n        return Xe;\n    }\n\nprivate:\n    // \u8ba1\u7b97\u96c5\u514b\u6bd4\u77e9\u9635\u7684\u8f85\u52a9\u51fd\u6570\n    template&lt;class Func, int N_IN, int N_OUT&gt;\n    void calculateJacobian(const Eigen::Matrix&lt;double, N_IN, 1&gt; &amp;input, Func &amp;&amp;func, Eigen::Matrix&lt;double, N_OUT, 1&gt; &amp;output, Eigen::Matrix&lt;double, N_OUT, N_IN&gt; &amp;jacobian) {\n        ceres::Jet&lt;double, N_IN&gt; input_auto_jet[N_IN];\n        for (int i = 0; i &lt; N_IN; i++) {\n            input_auto_jet[i].a = input[i];\n            input_auto_jet[i].v[i] = 1;\n        }\n        ceres::Jet&lt;double, N_OUT&gt; output_auto_jet[N_OUT];\n        func(input_auto_jet, output_auto_jet);\n        for (int i = 0; i &lt; N_OUT; i++) {\n            output[i] = output_auto_jet[i].a;\n            jacobian.block(i, 0, 1, N_IN) = output_auto_jet[i].v.transpose();\n        }\n    }\n\npublic:\n    VectorX Xe;     // \u4f30\u8ba1\u72b6\u6001\u53d8\u91cf\n    VectorX Xp;     // \u9884\u6d4b\u72b6\u6001\u53d8\u91cf\n    MatrixXX F;     // \u9884\u6d4b\u96c5\u514b\u6bd4\u77e9\u9635\n    MatrixYX H;     // \u89c2\u6d4b\u96c5\u514b\u6bd4\u77e9\u9635\n    MatrixXX P;     // \u72b6\u6001\u534f\u65b9\u5dee\n    MatrixXX Q;     // \u9884\u6d4b\u8fc7\u7a0b\u534f\u65b9\u5dee\n    MatrixYY R;     // \u89c2\u6d4b\u8fc7\u7a0b\u534f\u65b9\u5dee\n    MatrixXY K;     // \u5361\u5c14\u66fc\u589e\u76ca\n    VectorY Yp;     // \u9884\u6d4b\u89c2\u6d4b\u91cf\n};\n</code></pre>"},{"location":"Robot/kalman/#23","title":"2.3 \u975e\u7ebf\u6027\u4f18\u5316","text":"<p>TODO</p>"},{"location":"Robot/kalman/#_2","title":"\u4e00\u4e9b\u8d44\u6599","text":"<ul> <li>zhuanlan.zhihu.com/p/45238681</li> <li>\u5361\u5c14\u66fc\u6ee4\u6ce2(Kalman Filter)\u6982\u5ff5\u4ecb\u7ecd\u53ca\u8be6\u7ec6\u516c\u5f0f\u63a8\u5bfc-CSDN\u535a\u5ba2</li> <li>\u8c03\u8282\u8bef\u5dee\u77e9\u9635\u7684\u5b9e\u9645\u610f\u4e49</li> <li>\u975e\u7ebf\u6027\u62d3\u5c55</li> <li>\u81ea\u9002\u5e94\u4f18\u5316</li> <li>\u4f5c\u4e1a\u4e2d\u6709\u4e00\u4e2a\u5929\u4f53\u8fd0\u52a8\u7684\u4f8b\u5b50</li> </ul>"},{"location":"Robot/pnp/","title":"pnp","text":""},{"location":"Robot/pnp/#pnp","title":"pnp","text":"<p> \u7ea6 79 \u4e2a\u5b57  55 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <ul> <li>\u5df2\u77e5<ul> <li>\u76ee\u6807\u7269\u4f53\u7279\u5b9a\u70b9\u7684\u50cf\u7d20\u5750\u6807</li> <li>\u76ee\u6807\u7269\u4f53\u7279\u5b9a\u70b9\u7684\u771f\u5b9e\u5c3a\u5bf8</li> <li>\u76f8\u673a\u5185\u53c2</li> </ul> </li> <li>\u6c42<ul> <li>\u76ee\u6807\u7269\u4f53\u5728\u76f8\u673a\u5750\u6807\u7cfb\u4e0b\u7684 6d pose</li> </ul> </li> </ul> <p>\u50cf\u7d20\u5750\u6807\u548c\u7269\u4f53\u5750\u6807\u7684\u5bf9\u70b9 \u4f46\u662f\u4e00\u822c\u53ea\u7528 t, \u56e0\u4e3a R \u7684\u7cbe\u5ea6\u4e0d\u591f\u9ad8 Fetching Title#g70i</p> <p>![[Pasted image 20241008201602.png]]</p> C++<pre><code>#include &lt;iostream&gt;\n#include &lt;opencv2/opencv.hpp&gt;\n#include &lt;opencv2/imgproc/imgproc.hpp&gt;\n#include &lt;opencv2/calib3d/calib3d.hpp&gt;\n#include &lt;opencv2/core/core.hpp&gt;\nusing namespace cv;\n\nbool findCorners(const cv::Mat &amp;src, std::vector&lt;cv::Point2f&gt; &amp;corners) {\n    std::vector&lt;cv::Point2f&gt; pts;\n    corners.clear();\n    bool flag = cv::findChessboardCorners(src, {9, 6}, pts);\n    if (!flag)\n        return false;\n    corners.push_back(pts[0]);\n    corners.push_back(pts[9 - 1]);\n    corners.push_back(pts[pts.size() - 9]);\n    corners.push_back(pts[pts.size() - 1]);\n    return true;\n}\n\nint main() {\n    cv::Mat src;\n    cv::Mat camera_matrix;\n    cv::Mat distort_matrix;\n    cv::FileStorage reader(PROJECT_DIR\"/parameter.txt\", cv::FileStorage::READ);\n    reader[\"C\"] &gt;&gt; camera_matrix;\n    reader[\"D\"] &gt;&gt; distort_matrix;\n\n    for (int i = 0; i &lt;= 40; i++) {\n        src = imread(std::__cxx11::to_string(i).append(\".jpg\"));\n        std::vector&lt;cv::Point2f&gt; corners;\n        bool flag = findCorners(src, corners);\n        imshow(\"Opencv Demo\", src);\n        cv::waitKey(100);\n        if (flag == false) {\n            std::cout &lt;&lt; \"failed to find all corners\\n\";\n            continue;\n        }\n        std::vector&lt;cv::Point3f&gt; dst;\n        dst.push_back({0, 0, 0});\n        dst.push_back({8 * 1, 0, 0});\n        dst.push_back({0, 5 * 1, 0});\n        dst.push_back({8 * 1, 5 * 1, 0});\n        cv::Mat rvec, tvec;\n        cv::solvePnP(dst, corners, camera_matrix, distort_matrix, rvec, tvec);\n        std::cout &lt;&lt; \"t:\" &lt;&lt; std::endl &lt;&lt; -tvec &lt;&lt; std::endl &lt;&lt; std::endl;\n        cv::Mat drawer;\n        drawer = src.clone();\n        for (int j = 0; j &lt; 4; j++)\n            cv::circle(drawer, corners[j], 2, {0, 255, 0}, 2);\n        cv::imshow(\"corners\", drawer);\n        cv::waitKey(5);\n    }\n    return 0;\n}\n</code></pre>"},{"location":"Summaries/","title":"Summaries","text":""},{"location":"Summaries/#summaries","title":"Summaries","text":"<p>Abstract</p> <p>\u672c\u90e8\u5206\u5185\u5bb9\uff08\u9664\u7279\u522b\u58f0\u660e\u5916\uff09\u91c7\u7528 \u7f72\u540d-\u975e\u5546\u4e1a\u6027\u4f7f\u7528-\u4fdd\u6301\u4e00\u81f4 4.0 \u56fd\u9645 (CC BY-NC-SA 4.0) \u8bb8\u53ef\u534f\u8bae\u8fdb\u884c\u8bb8\u53ef\u3002</p> \u5b66\u671f\u603b\u7ed3 &amp; \u5176\u4ed6          <ul> <li> \u9ad8\u4e09\u81f3\u5927\u4e00\u6691\u5047\u603b\u7ed3  520  2 mins              1734582373 </li> <li> 2024 \u5e74 9 \u6708 10 \u6708\u603b\u7ed3  388  1 mins              1734582373 </li> <li> 2024 \u5e74 9 \u6708\u4efd\u81f3 12 \u6708\u4efd\u5b66\u671f\u603b\u7ed3\uff08\u5927\u4e00\uff09  1745  6 mins              1734506202 </li> </ul> 2024 \u5e74\u5468\u7ed3          <ul> <li> \u7b2c 50 \u5468  262  1 mins              1734243815 </li> <li> \u7b2c 44 \u5468  281  1 mins              1734024510 </li> <li> \u7b2c 45 \u5468  387  1 mins              1734024510 </li> <li> \u7b2c 46 \u5468  281  1 mins              1734024510 </li> <li> \u7b2c 47 \u5468  430  1 mins              1734024510 </li> <li> \u7b2c 48 \u5468  373  1 mins              1734024510 </li> <li> \u7b2c 49 \u5468  659  2 mins              1734024510 </li> </ul> \u9ad8\u4e2d\u5b66\u4e60\u7ecf\u9a8c          <ul> <li> \u6570\u5b66\u5b66\u4e60\u7ecf\u9a8c  757  3 mins              1734024510 </li> <li> \u82f1\u8bed\u5b66\u4e60\u7ecf\u9a8c  1397  5 mins              1734024510 </li> <li> \u6280\u672f\u5b66\u4e60\u7ecf\u9a8c  1324  4 mins              1734024510 </li> <li> \u7269\u7406\u5b66\u4e60\u7ecf\u9a8c  1581  5 mins              1734024510 </li> <li> \u5b66\u4e60\u8d44\u6e90  31  0 mins              1734024510 </li> </ul>"},{"location":"Summaries/2024/weekly/2024-W44-10/","title":"2024 \u5e74\u7b2c 44 \u5468\u5468\u7ed3","text":""},{"location":"Summaries/2024/weekly/2024-W44-10/#2024-44","title":"2024 \u5e74\u7b2c 44 \u5468\u5468\u7ed3","text":"<p> \u7ea6 281 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>10 \u6708 28 \u65e5 - 11 \u6708 03 \u65e5</p> <ul> <li>\u603b\u7ed3<ul> <li>CS231n<ul> <li>lecture \u542c\u4e86 01-04</li> <li>\u5b8c\u6210\u4e86 Assignment1</li> <li>\u505a\u4e86\u90e8\u5206\u7684\u7b14\u8bb0</li> <li>\u4e3b\u8981\u662f\u4e0d\u592a\u719f\u7ec3 numpy \u4e4b\u7c7b\u7684\u8fd0\u7528\uff0cvectorize \u8fd8\u662f\u6709\u70b9\u96be\u5ea6\u3002\u4e0d\u8fc7\u4e4b\u524d\u505a\u8fc7\u4e00\u4e9b EECS498 \u7684\u4f5c\u4e1a\u5c31\u8fd8\u597d\u3002</li> </ul> </li> <li>\u5468\u672b\u4e24\u5929\u6253\u4e86\u4e2a\u7269\u7406\u7684\u6bd4\u8d5b<ul> <li>\u719f\u7ec3\u4e86 LaTeX \u548c Python\uff0cdraw.io \u4f5c\u56fe</li> <li>\u8bba\u6587\u5728\u8fd9\u91cc</li> </ul> </li> </ul> </li> <li>\u8ba1\u5212<ul> <li>\u4e0b\u5468\u671f\u4e2d\u8003\uff0c\u590d\u4e60\u4e00\u4e0b</li> <li>RM \u63a5\u4e86\u4e2a\u5c0f\u4efb\u52a1\uff0c\u8981\u6c42\u8bc6\u522b\u89c6\u9891\u4e2d\u6bcf\u4e00\u5e27\u7684\u56fa\u5b9a\u4f4d\u7f6e\u7684\u4e00\u4e2a\u6570\u5b57\u5e76\u63d2\u503c\u8ba1\u7b97\u79ef\u5206<ul> <li>11 \u6708 4 \u65e5\u7528\u9884\u5904\u7406+tesseract OCR <ul> <li>\u8fd9\u91cc\u662f\u7b2c\u4e00\u7248\u634f</li> </ul> </li> <li>\u6253\u7b97\u6807\u8bb0\u4e00\u4e0b\u6570\u636e\uff0c\u8bad\u7ec3\u4e2a\u5c0f\u6a21\u578b\u8bd5\u8bd5\u3002<ul> <li>\u597d\u5427\uff0c\u5c1d\u8bd5\u4e86\u4e00\u4e0b\u6548\u679c\u5f88\u5dee\uff0c\u7528\u4e86\u4e2a\u5c0f\u7684 CNN \u5565\u90fd\u8bc6\u522b\u4e0d\u51fa\u6765</li> </ul> </li> </ul> </li> <li>RM \u88ab\u5206\u8fdb\u4e86\u81ea\u52a8\u5316\u5151\u77ff\u7684\u8f66\u7ec4\uff0c\u8981\u6c42\u5b9e\u73b0 6Dpose \u8bc6\u522b+\u673a\u68b0\u81c2\u8fd0\u52a8\u89c4\u5212<ul> <li>\u4e0b\u5468\u5185\u8981\u6c42\u63d0\u51fa\u5177\u4f53\u65b9\u6848\u5e76\u7acb\u9879<ul> <li>\u4ece\u6df1\u5ea6\u76f8\u673a\u548c\u6fc0\u5149\u76f8\u673a\u4e24\u4e2a\u65b9\u5411\u53bb\u627e\uff0c\u8981\u53bb\u770b\u770b\u8bba\u6587 </li> </ul> </li> </ul> </li> <li>\u7ee7\u7eed\u5b66\u4e60 CS231n<ul> <li>\u6253\u7b97\u5199\u5b8c Assignment 1 \u7684\u7b14\u8bb0\u548c\u9898\u89e3\u3002</li> <li>\u628a Assignment 2 \u505a\u5b8c</li> </ul> </li> </ul> </li> </ul>"},{"location":"Summaries/2024/weekly/2024-W45-11/","title":"2024 \u5e74\u7b2c 45 \u5468\u5468\u7ed3","text":""},{"location":"Summaries/2024/weekly/2024-W45-11/#2024-45","title":"2024 \u5e74\u7b2c 45 \u5468\u5468\u7ed3","text":"<p> \u7ea6 387 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>11 \u6708 04 \u65e5 - 11 \u6708 10 \u65e5</p> <ul> <li>\u603b\u7ed3<ul> <li>CS231n<ul> <li>\u590d\u4e60\u4e86\u4e00\u4e0b Assignment 1 \u7684\u4ee3\u7801\uff0c\u6574\u7406\u4e86\u4e00\u4e0b\u6846\u67b6</li> <li>\u53bb\u770b\u4e86\u4e00\u4e9b\u674e\u5b8f\u6bc5\u7684\u6df1\u5ea6\u5b66\u4e60\u6559\u7a0b</li> <li>\u56de\u770b\u4e86\u4e00\u4e0b Dive into Deep Learning\uff0c\u597d\u50cf\u4ee3\u7801\u8fd8\u662f\u8c03\u7528\u4e86\u5f88\u591a\u9ad8\u7ea7 api,\u6bd4\u5982 backforward \u5c31\u4e0d\u662f\u4ece\u96f6\u5b9e\u73b0\u7684\u3002</li> </ul> </li> <li>\u671f\u4e2d\u8003\u8bd5\u7ed3\u675f</li> <li>RM \u6821\u5185\u8d5b\u9020\u8f66\uff0c\u5b9e\u73b0\u5e95\u76d8\u8fd0\u52a8\uff08\u9ea6\u8f6e\u89e3\u7b97\u4ee3\u7801 + \u5e95\u76d8\u5b89\u88c5\uff09\u3002\u8fed\u4ee3\u4e86\u4e09\u7248\u4fdd\u9669\u6760\u3002\u901a\u8fc7\u4e2d\u671f\u68c0\u67e5\u3002\uff08\u8fd9\u4e2a\u771f\u5e9f\u65f6\u95f4\uff0c\u4e0d\u8fc7\u5b66\u4e86\u7535\u63a7\u548c solidwork\uff09</li> <li>RM \u9879\u76ee<ul> <li>\u641c\u7d22\u4e86 6Dof \u8bc6\u522b\u76f8\u5173\u6a21\u578b\u3002\u6392\u9664\u4e86\u6240\u6709\u57fa\u4e8e Transformer \u7684\u6a21\u578b\uff08\u53c2\u6570\u592a\u591a\uff0c\u7b97\u529b\u9700\u6c42\u5927\uff0c\u4e0d\u80fd\u5728 Orin NX \u4e0a\u5728 1s \u5185\u8dd1\u5b8c\uff09\u3002</li> <li>\u6700\u7ec8\u5927\u6982\u9009\u62e9\u7528 FFB6D pose\uff0c\u4ed6\u662f\u57fa\u4e8e\u674e\u98de\u98de\u4e4b\u524d\u7684 DenseFusion \u6539\u8fdb\u7684\u3002\u7528 RGB \u548c D \u7684\u4fe1\u606f\u8fdb\u884c\u7279\u5f81\u8bc6\u522b + \u878d\u5408 + \u6295\u7968\u7684\u6a21\u578b\u3002</li> <li>\u5927\u81f4\u5c1d\u8bd5\u90e8\u7f72\u4e86\u4e00\u4e0b\uff0c\u4f46\u662f\u73af\u5883\u51fa\u4e86\u5f88\u591a\u95ee\u9898\u3002</li> </ul> </li> <li>\u4e0a\u5468\u529f\u7387\u8bc6\u522b\u7684\u4efb\u52a1\u5b8c\u6210\uff0c\u6700\u7ec8\u7528\u4e86\u9884\u5904\u7406 + tesseract OCR\uff0c\u4f46\u662f\u5bf9\u7ea2\u8272\u6570\u5b57\u7684\u8bc6\u522b\u4e0d\u662f\u5f88\u597d\uff08\u56e0\u4e3a\u89c6\u9891\u672c\u8eab\u5c31\u5f88\u6a21\u7cca\uff09\u3002\u987a\u5e26\u53bb\u5b66\u4e86\u4e00\u4e0b PR \u3002<ul> <li>\u4ee3\u7801\u5728\u8fd9\u91cc</li> </ul> </li> </ul> </li> <li>\u8ba1\u5212<ul> <li>\u590d\u73b0 FFB6D pose \uff0c\u5236\u4f5c\u6570\u636e\u96c6\u3002<ul> <li>\u987a\u5e26\u5b66\u4e00\u4e0b docker \u5565\u7684\u3002</li> </ul> </li> <li>\u505a\u5b8c Assignment 2,\u4e0a\u5468\u7684 flag \u5012\u4e86 :( \uff08\u771f\u6ca1\u65f6\u95f4\u4e86\uff09</li> <li>RM \u6821\u5185\u8d5b\uff0c\u5468\u4e09\u4e4b\u524d\u753b\u5b8c\u56fe\uff0c\u7ed9\u5382\u5bb6\u52a0\u5de5\u3002\u5b9e\u73b0\u6361\u7403+\u6254\u7403\u7684\u529f\u80fd\u3002</li> <li>\u5b8c\u5584\u529f\u7387\u8bc6\u522b\u7684\u4efb\u52a1\uff0c\u4f20\u7edf\u65b9\u6cd5\u4f3c\u4e4e\u7cbe\u5ea6\u4e0d\u592a\u591f\u7528\u3002</li> <li>\u8c03\u6574\u4f5c\u606f\uff01</li> </ul> </li> </ul>"},{"location":"Summaries/2024/weekly/2024-W46-11/","title":"2024 \u5e74\u7b2c 46 \u5468\u5468\u7ed3","text":""},{"location":"Summaries/2024/weekly/2024-W46-11/#2024-46","title":"2024 \u5e74\u7b2c 46 \u5468\u5468\u7ed3","text":"<p> \u7ea6 281 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>11 \u6708 11 \u65e5 - 11 \u6708 17 \u65e5</p> <ul> <li>\u603b\u7ed3<ul> <li>CS231n<ul> <li>\u5199\u5b8c\u4e86 assignment 2\uff0c\u4e2d\u95f4\u9047\u5230\u4e86\u4e00\u4e9b\u95ee\u9898\uff0c\u53ef\u4ee5\u8003\u8651\u4e4b\u540e\u51fa\u4e2a\u8e29\u5751\u8bb0\u5f55\u3002</li> </ul> </li> <li>RM \u6821\u5185\u8d5b\u9020\u8f66<ul> <li>\u753b\u4e86\u4e00\u4e9b\u56fe\uff0c\u8fd8\u6ca1\u6765\u5f97\u53ca\u52a0\u5de5\uff0c\u961f\u53cb\u90fd\u5f00\u6446\u4e86\u3002</li> </ul> </li> <li>RM \u9879\u76ee<ul> <li>\u5b66\u4e60\u4e86 docker\uff0c\u603b\u7b97\u914d\u7f6e\u597d\u4e86 docker \u4e0a\u7684 FFB6D \u7684\u73af\u5883\uff0c\u8fd8\u662f\u8981\u719f\u6089\u4e00\u4e0b docker\u3002</li> <li>\u7528 realsense \u53bb\u505a\u4e86\u6a21\u578b\uff0c\u751f\u6210\u4e86 .ply \u70b9\u4e91\uff0c\u4f46\u662f\u597d\u50cf\u6548\u679c\u4e0d\u662f\u5f88\u597d\u3002</li> </ul> </li> <li>\u5199\u4e86\u4e2a\u6570\u636e\u6807\u6ce8\u7684 gui \u7a0b\u5e8f\uff0c\u611f\u89c9\u5199\u5f97\u5f88\u96be\u7528\u3002</li> <li>\u8c03\u6574\u4f5c\u606f\uff0c\u6bcf\u5929\u7761\u5f97\u4e45\u4e86\u4e00\u70b9\u634f\u3002</li> <li>\u8fed\u4ee3\u4e86\u81ea\u5df1\u7684\u5e38\u7528 prompt\uff0c\u63d0\u9ad8\u4e86 AI \u7684\u4f5c\u7528\u3002</li> <li>\u73a9\u4e86\u73a9 hugo\uff0c\u628a\u4e3b\u57df\u540d\u7ed9\u6362\u6389\u4e86</li> </ul> </li> <li>\u8ba1\u5212<ul> <li>\u590d\u73b0 FFB6D pose \uff0c\u5236\u4f5c\u6570\u636e\u96c6\u3002</li> <li>\u5199\u5b8c CS231n assignment 3\uff0c\u540c\u65f6\u8003\u8651\u5199\u51e0\u4e2a blog \u603b\u7ed3\u4e00\u4e0b\u3002</li> <li>\u7ee7\u7eed\u719f\u6089 docker \u7684\u64cd\u4f5c\uff0c\u628a\u6784\u5efa\u597d\u7684 image push \u5230 docker hub \u4e0a\u3002</li> <li>\u7ee7\u7eed\u5c1d\u8bd5\u4f7f\u7528 CNN \u6765\u8bc6\u522b\u6570\u5b57\uff0c\u5b8c\u5584\u9879\u76ee\uff08\u624b\u6807\u6570\u636e\u592a\u6076\u5fc3\u4e86\uff09</li> <li>\u5b8c\u5584\u5e38\u7528\u7684 prompt\u3002</li> <li>\u590d\u4e60\u4e00\u4e0b license \u548c commit \u89c4\u8303\uff0c\u611f\u89c9\u81ea\u5df1\u7684 github \u4ed3\u5e93\u592a\u4e71\u4e86\u3002</li> <li>\u7ee7\u7eed\u8c03\u6574\u4f5c\u606f\u3002</li> </ul> </li> </ul>"},{"location":"Summaries/2024/weekly/2024-W47-11/","title":"2024 \u5e74\u7b2c 47 \u5468\u5468\u7ed3","text":""},{"location":"Summaries/2024/weekly/2024-W47-11/#2024-47","title":"2024 \u5e74\u7b2c 47 \u5468\u5468\u7ed3","text":"<p> \u7ea6 430 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>11 \u6708 18 \u65e5 - 11 \u6708 24 \u65e5</p> <ul> <li>\u603b\u7ed3<ul> <li>CS231n<ul> <li>\u6ca1\u600e\u4e48\u63a8\u8fdb</li> </ul> </li> <li>RM \u6821\u5185\u8d5b<ul> <li>\u7ed9\u4e86\u961f\u53cb\u65b9\u6848\uff0c\u4f46\u662f\u6700\u540e\u6ca1\u6253\u5370\u51fa\u6765\u3002\u611f\u89c9\u81ea\u5df1\u5bf9 solidwork \u5b9e\u5728\u63d0\u4e0d\u8d77\u5174\u8da3\uff0c\u7528\u7684\u4e0d\u987a\u624b + \u8bbe\u8ba1\u672c\u8eab\u7684\u5f62\u5f0f\u548c\u5199\u4ee3\u7801\u5dee\u522b\u5f88\u5927\uff0c\u4e5f\u8bb8\u662f\u7ec3\u7684\u592a\u5c11\u4e86\uff0c\u6ca1\u6709\u8db3\u591f\u7684\u7ecf\u9a8c\u3002\u4f46\u662f\u5728\u8fd9\u65b9\u9762\u4f3c\u4e4e AI \u5e76\u4e0d\u80fd\u8d77\u5230\u5f88\u597d\u7684\u8f85\u52a9\u4f5c\u7528\u3002</li> <li>\u800c\u4e14\u611f\u89c9\u5bf9\u4e8e\u8fd9\u79cd\u56e2\u961f\u9879\u76ee\uff0c\u8fd8\u662f\u5f88\u9700\u8981\u9879\u76ee\u7ba1\u7406 / \u8fdb\u5ea6\u7ba1\u7406\uff0c\u4e0d\u7136\u5c31\u6709 95% \u7684\u6982\u7387\u4f1a\u5931\u63a7\u70c2\u5c3e\u3002\u7279\u522b\u662f\u5927\u5bb6\u90fd\u6ca1\u4ec0\u4e48\u7ecf\u9a8c\u7684\u65f6\u5019\uff0c\u53ea\u80fd\u63d0\u524d push \u6240\u6709\u4eba\uff0c\u505a\u51fa\u51e0\u7248\u65b9\u6848\u6765\uff0c\u7136\u540e\u624d\u80fd\u89c4\u5212\u540e\u7eed\u3002</li> <li>\u4ee5\u540e\u56e2\u961f\u9879\u76ee\u8fd8\u662f\u597d\u597d\u6311\u961f\u53cb\u5427\uff0c\u4e0d\u8981\u968f\u4fbf\u5c31\u53bb\u4e86\u3002\u5373\u4f7f\u505a\u597d\u4e86\u81ea\u5df1\u7684\u90e8\u5206\uff0c\u522b\u7684\u90e8\u5206\u5bc4\u4e86\u4e5f\u5f88\u96be\u641e\u3002\u8981\u4e48\u5c31\u81ea\u5df1\u5b8c\u5168\u80fd cover \u6574\u4e2a\u9879\u76ee\uff0c\u505a\u5168\u6808\uff0c\u6bd4\u5982 wordle_solver\uff0c\u4ece\u5934\u5230\u5c3e\u90fd\u662f\u6211\u4e00\u4e2a\u4eba\u5199\u7684\u3002</li> </ul> </li> <li>RM \u9879\u76ee<ul> <li>\u5b66\u4e60\u4e86 ssh \u7b49\uff0c\u5728\u53e6\u5916\u4e00\u53f0\u7535\u8111\u4e0a\u914d\u7f6e\u4e86\u73af\u5883\uff0c\u4e0b\u8f7d\u4e86\u6240\u9700\u8981\u7684\u6570\u636e\uff0c\u6784\u5efa\u4e86 docker\u3002</li> </ul> </li> <li>blog<ul> <li>\u6574\u7406\u4e86\u7b14\u8bb0\u672c\uff0c\u53d1\u5e03\u4e86\u51e0\u7bc7\u6587\u7ae0</li> </ul> </li> <li>\u5b66\u4e60\u4f7f\u7528\u4e86 reveal-md</li> <li>\u5199\u4e86\u4e00\u4e2a wordle_solver</li> <li>\u590d\u4e60\u4e86 license \u548c commit \u89c4\u8303\uff0c\u611f\u89c9\u786e\u5b9e\u6709\u70b9\u7e41\u7410\u3002</li> <li>\u840e\u9761\u7684\u4e00\u5468\uff0c\u6548\u7387\u4f4e\uff0c\u51e0\u4e4e\u4e00\u76f4\u90fd\u5728\u4f11\u606f\u3002</li> </ul> </li> <li>\u8ba1\u5212<ul> <li>\u901f\u901f\u63a8\u8fdb cs231n\uff0c\u4e89\u53d6\u4e0b\u4e2a\u661f\u671f\u5b66\u5b8c\u3002<ul> <li>\u6574\u7406\u7b54\u6848\uff0c\u53d1\u5e03\u3002</li> <li>\u6574\u7406\u7b14\u8bb0\uff0c\u53d1\u5e03\u3002</li> <li>\u7ed3\u5408 d2l \u7b49\u5176\u4ed6\u8d44\u6e90\uff0c\u603b\u7ed3\u5f52\u7eb3\u3002</li> </ul> </li> <li>\u51c6\u5907\u56db\u7ea7\u3002</li> <li>\u8dd1\u901a FFB6D \u7684\u4ee3\u7801\uff0c\u5e76\u8ba1\u5212\u9605\u8bfb\u5957\u81ea\u5df1\u7684\u6570\u636e\u3002</li> <li>\u53d1\u5e03\u4e00\u7bc7\u5982\u4f55\u5199 prompt \u7684\u6587\u7ae0\u3002</li> <li>\u5b8c\u5584 obsidian \u6a21\u677f\u3002</li> <li>\u5b66\u70b9 go\u3002</li> </ul> </li> </ul>"},{"location":"Summaries/2024/weekly/2024-W48-11/","title":"2024 \u5e74\u7b2c 48 \u5468\u5468\u7ed3","text":""},{"location":"Summaries/2024/weekly/2024-W48-11/#2024-48","title":"2024 \u5e74\u7b2c 48 \u5468\u5468\u7ed3","text":"<p> \u7ea6 373 \u4e2a\u5b57  1 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>11 \u6708 25 \u65e5 - 12 \u6708 01 \u65e5</p> <ul> <li>\u603b\u7ed3<ul> <li>CS231n<ul> <li>\u5199\u5b8c\u4e86 assignment 3 \u7684 LSTM,\u540e\u9762\u597d\u50cf\u8fd8\u6709 transformer \u5565\u7684\uff0c\u8fd8\u6ca1\u6765\u5f97\u53ca\u5199\u3002</li> <li>\u611f\u89c9\u8bfe\u7a0b\u89c6\u9891\u771f\u7684\u7b80\u7565\uff08d2l \u4e00\u4e2a\u6a21\u578b\u5c31\u4f1a\u62c9\u51fa\u6765\u8bb2\u4e00\u8282\uff09</li> </ul> </li> <li>\u8bfe\u5185<ul> <li>\u5468\u4e00\u5230\u5468\u4e09\u505a\u4e86\u4e00\u4e2a proj\u3002</li> <li>\u7ed3\u679c\u8fd8\u662f\u5f88\u597d\u7684\uff0c\u4e00\u4e2a\u4eba\u628a\u6240\u6709\u7684\u4ee3\u7801\u90fd\u5199\u4e86\uff0c\u6700\u540e\u5206\u6570\u4e5f\u662f\u62ff\u6ee1\u4e86\u3002</li> <li>\u987a\u4fbf\u5b66\u4e86 reveal-md \u548c beamer\u3002\u5199\u4e86\u4e2a\u5c0f\u5de5\u5177\uff0c\u7528\u6765\u90e8\u7f72 slides \u5230\u7f51\u9875\u4e0a\u3002\u540c\u65f6\u53ef\u4ee5\u5b9e\u73b0\u589e\u91cf\u6784\u5efa\u3002</li> <li>\u5b66\u4e86\u5982\u4f55\u4f7f\u7528 GitHub release\u3002</li> </ul> </li> <li>RM \u9879\u76ee<ul> <li>\u653e\u5f03\u4e86 docker\uff0c \u76f4\u63a5\u5728\u7535\u8111\u4e0a\u914d\u7f6e\u73af\u5883\u3002\u6210\u529f\u8dd1\u8d77\u6765\u4e86\u8bad\u7ec3\u3002\u514b\u670d\u4e86\u4e00\u4e9b\u68af\u5ea6\u6d88\u5931\u548c\u7206\u70b8\u7684\u95ee\u9898\uff0c\u8dd1\u4e86 8 \u4e2a epoch\uff0c\u4f3c\u4e4e\u6709\u4e00\u70b9\u8fc7\u62df\u5408\u3002</li> <li></li> </ul> </li> <li>\u8d76\u8fdb\u5ea6\uff0c\u5b66\u4e86\u671f\u4e2d\u8003\u4ee5\u540e\u6559\u7684\u6570\u5b66\u5316\u5b66\u8ba1\u7b97\u673a\u5185\u5bb9\uff0c\u8003\u5b8c\u4e86\u8ba1\u7b97\u673a\u7b2c\u4e8c\u6b21\u671f\u4e2d\u8003\u3002</li> <li>\u5199\u82f1\u8bed\u8bba\u6587\uff0c\u8fd1\u4ee3\u53f2\u8bfb\u4e66\u62a5\u544a\u3002\u8c46\u5305\u4f3c\u4e4e\u5728\u4e2d\u6587\u5199\u4f5c\u65b9\u9762\u6bd4\u8f83\u597d\uff0c\u751a\u81f3\u6709\u7c7b\u4f3c\u4e8e ChatGPT canvas \u4e00\u6837\u7684\u529f\u80fd\u3002</li> </ul> </li> <li>\u8ba1\u5212<ul> <li>\u63a8\u8fdb CS231n\uff0c\u5b66\u5f97\u771f\u6162\u554a\u3002</li> <li>\u51c6\u5907\u56db\u7ea7\u3002</li> <li>4090 \u8bad\u7ec3\u597d\u6162\uff0c\u6253\u7b97\u628a\u6a21\u578b\u5f04\u5230\u670d\u52a1\u5668\u4e0a\u7528 A100\u3002</li> <li>\u51c6\u5907\u671f\u672b\u590d\u4e60\u3002</li> <li>\u79d1\u7814\u6295\u5165\u65f6\u95f4\u592a\u5c11\u4e86\uff0c\u4f4d\u59ff\u8bc6\u522b\u505a\u7684\u5dee\u4e0d\u591a\u4e86\uff0c\u5c31\u591a\u628a\u65f6\u95f4\u653e\u5230\u79d1\u7814\u4e0a\u9762\u3002\u591a\u5b66\u70b9\u4e1c\u897f\uff0c\u8bf4\u5b9e\u8bdd\u611f\u89c9\u4e0b\u534a\u5b66\u671f\u660e\u663e\u6ca1\u6709\u5b66\u5230\u4ec0\u4e48\u4e1c\u897f\u3002</li> <li>\u8fd0\u52a8\uff0c\u89c4\u5f8b\u4f5c\u606f\uff0c\u51cf\u5c11\u523a\u6fc0\u6027\u5a31\u4e50\u3002</li> </ul> </li> </ul>"},{"location":"Summaries/2024/weekly/2024-W49-12/","title":"2024-W49-12","text":"<p> \u7ea6 671 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <code>#\u5468\u8bb0</code>","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W49-12/#2024-w49-12","title":"2024-W49-12","text":"","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W49-12/#plan","title":"PLAN","text":"<ul> <li> \u5199\u82f1\u8bed essay \uff08\u5b8c\u6210\u4e86\u4e00\u7248\u4ee5\u540e\u88ab\u63a8\u7ffb\u91cd\u6765\u4e86\u3002\uff09</li> <li> \u590d\u4e60\u7ea2\u8bfe</li> <li> \u590d\u4e60\u5316\u5b66</li> <li> \u590d\u4e60\u6570\u5b66</li> <li> \u590d\u4e60\u8ba1\u7b97\u673a</li> <li> \u505a\u5b8c CS 231n<ul> <li> \u505a + \u5199\u7b14\u8bb0</li> </ul> </li> <li> \u505a\u4e00\u4e9b cloudwego</li> <li> \u53bb\u770b\u770b Go + Gin + Gnorm</li> </ul>","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W49-12/#review","title":"REVIEW","text":"<ul> <li>\u914d\u7f6e\u597d\u4e86 obsidian \u6a21\u677f + \u4e00\u4e9b\u63d2\u4ef6</li> <li>\u5b66\u4e86 go \u7684\u57fa\u7840\u8bed\u6cd5\uff0c\u548c\u4e00\u4e9b\u5e76\u884c\u5904\u7406\u7684\u4e1c\u897f\u3002<ul> <li>\u5199\u4e86\u8fd9\u4e2a\u7684\u7b2c\u4e00\u90e8\u5206: 7\u5929\u7528Go\u4ece\u96f6\u5b9e\u73b0Web\u6846\u67b6Gee\u6559\u7a0b</li> </ul> </li> <li>\u5199\u4e86\u5b66\u672f\u5199\u4f5c\u7684\u8bba\u6587\uff0c\u6539\u4e86\u56db\u5929\uff0c\u7ed3\u679c\u88ab\u63a8\u7ffb\u4e86\u3002</li> <li>\u52aa\u529b\u8c03\u6574\u4f5c\u606f + \u65e5\u5e38\u751f\u6d3b\u89c4\u5f8b\uff0c\u7ec8\u4e8e\u5728\u4e00\u5468\u5feb\u8981\u7ed3\u675f\u7684\u65f6\u5019\uff08\u5468\u4e94\uff0c\u5468\u516d\uff09\u627e\u56de\u4e86\u4e00\u70b9\u611f\u89c9\u3002\u4f3c\u4e4e\u8fd8\u662f\u53bb\u56fe\u4e66\u9986\u9002\u5408\u6211\u3002</li> <li>\u5199\u4e86\u4e00\u4e9b CS231n \u7684\u7b14\u8bb0\uff0c\u4f46\u662f\u4ecd\u7136\u6ca1\u6709\u505a\u5b8c\uff0c\u671f\u672b\u5468\u4e86\u66f4\u6ca1\u65f6\u95f4\u4e86\u3002 : (</li> <li>\u4e0b\u5468\u53ef\u80fd\u5c31\u662f\u590d\u4e60\u671f\u672b\u8003\u8bd5\u4e86\u3002</li> </ul>","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W49-12/#thoughts","title":"THOUGHTS","text":"<ul> <li>\u4e00\u4e2a\u5b66\u671f\u9a6c\u4e0a\u5c31\u8981\u7ed3\u675f\u4e86\uff0c\u4f46\u662f\u4f3c\u4e4e\u671f\u672b\u8003\u5df2\u7ed3\u675f RM \u5c31\u8981\u96c6\u8bad\uff0c\u7136\u540e\u5bd2\u5047\u4f1a\u88ab\u538b\u7f29\u5230 1 \u4e2a\u6708\uff08\u539f\u5148\u662f\u4e24\u4e2a\u6708\uff09\u3002</li> <li>\u611f\u89c9\u4e0b\u534a\u4e2a\u5b66\u671f\u8fd8\u662f\u5f88\u6446\u70c2<ul> <li>\u7b2c\u4e00\u4e2a\u662f\u6ca1\u6709\u627e\u5230\u81ea\u5df1\u7684\u751f\u6d3b\u8282\u594f\uff0c\u5435\u67b6\uff0c\u597d\u51e0\u4e2a\u65b9\u9762\u7684 ddl \u4e00\u8d77\u6765\uff0c\u5468\u672b\u7684\u4e0d\u5408\u7406\u4f11\u606f\uff0c\u5e73\u65f6\u7684\u4e0d\u6b63\u5e38\u4f5c\u606f\u3002</li> <li>\u7b2c\u4e8c\u4e2a\u662f\u611f\u89c9\u524d\u9014\u8ff7\u832b\uff0c\u7279\u522b\u662f\u6765\u5bc6\u9662\u4ee5\u540e\uff0c\u611f\u89c9\u8eab\u8fb9\u7684\u4eba\u90fd\u5728\u5377\u7ee9\u70b9\uff0c\u7136\u540e\u81ea\u5df1\u4e0d\u5f97\u4e0d\u4e5f\u8bdd\u5f88\u591a\u65f6\u95f4\u5728\u4e0a\u9762\u3002\u5b66\u957f\u91cc\u9762\u4f3c\u4e4e\u4e5f\u5f88\u5c11\u6709\u4f20\u7edf CS \u9053\u8def\u7684\uff0c\u4e0d\u77e5\u9053\u662f\u4e3a\u4ec0\u4e48\u3002</li> </ul> </li> <li>\u5176\u5b9e\u6211\u8fd8\u662f\u5f88\u559c\u6b22\u5b66\u4e1c\u897f\u7684\uff0c\u6216\u8005\u8bf4\u73a9\u8ba1\u7b97\u673a\u7684\u3002\u5f88\u559c\u6b22\u6a21\u578b\u771f\u7684\u8dd1\u51fa\u7ed3\u679c\u4e86\uff0c\u81ea\u5df1\u642d\u5efa\u7684\u5de5\u4f5c\u6d41\u771f\u7684\u6709\u6548\u4e86\uff0c\u81ea\u5df1\u7684\u60f3\u6cd5\u771f\u7684\u901a\u8fc7\u7a0b\u5e8f\u5b9e\u73b0\u4e86\u7684\u611f\u89c9\u3002\u559c\u6b22\u80fd\u591f\u7acb\u5373\u4f53\u73b0\u5728\u773c\u524d\u7684\u4e1c\u897f\uff0c\u4ec0\u4e48 web \u642d\u5efa\uff0c\u7b14\u8bb0\u8f6f\u4ef6\u6216\u8005\u8bad\u7ec3\u6a21\u578b\uff0c\u53ef\u89c6\u5316\uff0c\u5c1d\u8bd5\u4e0d\u540c\u7684 slides\uff0c\u7528 \\(\\displaystyle \\LaTeX\\) \u5199\u4f5c\u4e1a\u3002\u4f46\u4e00\u4e9b\u65b9\u9762\uff0c\u6211\u53c8\u504f\u5411\u4e8e\u7406\u8bba\u5316\u7684\uff0c\u5f62\u5f0f\u5316\u7684\u4e1c\u897f\uff0c\u6bd4\u5982\u5b66\u674e\u7fa4\u674e\u4ee3\u6570\uff0c\u5b66\u56db\u5143\u6570\uff0c\u63a7\u5236\u7406\u8bba\u4e4b\u7c7b\u7684\u4e1c\u897f\u3002</li> <li>\u53ea\u4e0d\u8fc7\u8fd9\u534a\u4e2a\u5b66\u671f\u771f\u7684\u6ca1\u6709 balance \u597d\u5f88\u591a\u4e1c\u897f\uff0c\u5e38\u5e38\u5fc3\u529b\u6194\u60b4\uff0c\u5b8c\u7f8e\u4e3b\u4e49\u53c8\u8ba9\u81ea\u5df1\u62d6\u5ef6\uff0c\u9003\u907f\u3002\u6211\u8086\u610f\u7684\u5f52\u548e\u4e3a\u6ca1\u6709\u670b\u53cb\uff0c\u4e0d\u9002\u5e94\uff0c\u5b9e\u9645\u4e0a\u4e5f\u662f\u5728\u9003\u907f\u3002\u751a\u81f3\u4e00\u6bb5\u65f6\u95f4\u65e5\u8bb0/TODO list \u90fd\u6ca1\u6709\u5199\uff0c\u5f7b\u5e95\u7684\u5f00\u6446\u4e86\uff0c\u4e0d\u8fc7\u8fd8\u597d\u73b0\u5728\u770b\u8d77\u6765\u5728\u8d70\u4e0a\u5761\u8def\u4e86\u3002</li> <li>\u4ece\u73b0\u5728\u5f00\u59cb\u638c\u63a7\u751f\u6d3b\u5427\uff0c\u4e0d\u8981\u518d\u6d3b\u7684\u4e91\u91cc\u96fe\u91cc\u4e86\u3002</li> </ul>","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W50-12/","title":"2024-W50-09","text":"<p> \u7ea6 274 \u4e2a\u5b57  1 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <code>#\u5468\u8bb0</code>","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W50-12/#2024-w50-09","title":"2024-W50-09","text":"","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W50-12/#review","title":"Review","text":"<ul> <li>\u8bfe\u5185<ul> <li> \u8003\u56db\u7ea7</li> <li> \u5199\u5b66\u672f\u5199\u4f5c\u7684\u8bba\u6587</li> <li> \u590d\u4e60\u5316\u5b66\uff0c\u6570\u5b66\uff0c\u8ba1\u7b97\u673a\uff0c\u8fd1\u4ee3\u53f2</li> </ul> </li> <li>RM<ul> <li> \u8dd1\u8bad\u7ec3\uff08\u94fe\u63a5\u6574\u7406\u6570\u636e\uff0c\u4f46\u662f\u6a21\u578b\u4e0d\u6536\u655b\u3002\u5728\u5c0f\u8303\u56f4\u7684\u6570\u636e\u96c6\u4e0a\u5b9e\u9a8c\u540e\u4ecd\u7136\u4e0d\u6536\u655b\uff0c\u6000\u7591\u4e00\u5b9a\u8981\u4f7f\u7528 raster_triangle\uff09\u3002\u719f\u6089\u4e86 linemod \u6570\u636e\u96c6\u7684\u7ec4\u6210\uff0c\u5e76\u4e86\u89e3\u4e86\u5982\u4f55\u7528\u81ea\u5df1\u7684\u6570\u636e\u6765\u8bad\u7ec3\u6a21\u578b\u3002</li> </ul> </li> <li>Obsidian<ul> <li> \u7b2c\u4e00\u6b21\u7528 Day Planner \u6765\u8bb0\u5f55\u81ea\u5df1\u7684\u751f\u6d3b\uff0c\u5e76\u5c1d\u8bd5\u6709\u7a7a\u5c31\u53bb\u81ea\u4e60\u5ba4\uff0c\u6548\u7387\u5f97\u5230\u7684\u5f88\u5927\u7684\u63d0\u9ad8\u3002</li> </ul> </li> </ul>","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W50-12/#next-week-plan","title":"Next Week Plan","text":"<ul> <li> \u671f\u672b\u8003\u8bd5</li> <li> \u5236\u4f5c\u5bd2\u5047\u8ba1\u5212</li> <li> \u5236\u4f5c\u8fd4\u6821\u5ba3\u8bb2\u7684\u8d44\u6599</li> </ul>","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W50-12/#time-line","title":"Time Line","text":"","tags":["\u5468\u8bb0"]},{"location":"Summaries/2024/weekly/2024-W50-12/#thoughts","title":"THOUGHTS","text":"<ul> <li>\u6253\u7b97\u5b66\u516c\u5f00\u8bfe\uff0c\u5e76\u4e14\u591a\u8ddf\u522b\u4eba\u4ea4\u6d41\uff0c\u6709\u8f93\u5165\u66f4\u9700\u8981\u6709\u8f93\u51fa\u3002</li> <li>\u5f00\u53d1\u793e\u4ea4\u5a92\u4f53\uff0c\u53d1\u5e03\u4e1c\u897f\u3002</li> <li>\u89c4\u5f8b\u4f5c\u606f\uff0c\u611f\u89c9\u4e00\u5929\u9700\u8981 8 \u4e2a\u5c0f\u65f6\u7761\u7720 + 1 \u4e2a\u5c0f\u65f6\u8fd0\u52a8\uff0c\u540c\u65f6\u8981\u6709\u65f6\u95f4\u6765\u53cd\u601d\u3002<ul> <li>\u5f62\u5f0f\u5316\u7684\u64cd\u4f5c\u53ef\u4ee5\u8ba9\u4eba\u66f4\u597d\u7684\u8fdb\u5165\u72b6\u6001\u3002</li> </ul> </li> </ul>","tags":["\u5468\u8bb0"]},{"location":"Summaries/High%20School/Resource/","title":"Resource","text":"<p>\u4e00\u4e9b\u8d44\u6e90\u94fe\u63a5\uff0c\u53ef\u4ee5\u53c2\u8003\u7740\u770b:</p> <p> \u7ea6 31 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4\u4e0d\u5230 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <ul> <li>wjyyy \u9ad8\u4e09\u751f\u5b58\u6307\u5357</li> <li>IAI\u7ecf\u9a8c\u5206\u4eab</li> </ul> <p>\u6570\u5b66:</p> <ul> <li>\u9009\u62e9\u9898\u538b\u8f74</li> </ul>"},{"location":"Summaries/High%20School/eng_fht/","title":"\u82f1\u8bed\u7ecf\u9a8c\u5206\u4eab","text":""},{"location":"Summaries/High%20School/eng_fht/#_1","title":"\u82f1\u8bed\u7ecf\u9a8c\u5206\u4eab","text":"<p> \u7ea6 1397 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 7 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>\u80cc\u666f:2024\u5c4a\u9996\u8003136\uff08\u524d\u9762\u62635\uff0c\u4f5c\u6587\u62639\uff09 -&gt; \u9ad8\u8003137\uff08\u524d\u9762\u62633\uff0c\u4f5c\u6587\u626310\uff09</p>"},{"location":"Summaries/High%20School/eng_fht/#_2","title":"\u5b66\u79d1\u672c\u8eab:","text":""},{"location":"Summaries/High%20School/eng_fht/#_3","title":"\u82f1\u8bed\u96be\u5ea6\u600e\u4e48\u6837\uff1f","text":"<ul> <li>\u53d6\u51b3\u4e8e\u5b66\u751f\u5427\uff0c\u521d\u4e2d\u7684\u5e95\u5b50\u5f71\u54cd\u5f88\u5927\uff0c\u6709\u7684\u4eba\u521d\u4e2d\u82f1\u8bed\u597d\u76f4\u63a5\u4e09\u5e74\u90fd\u4e0d\u7528\u5b66\u82f1\u8bed\u3002</li> <li>\u57fa\u7840\u77e5\u8bc6\u5f71\u54cd\u540e\u7eed\u5b66\u4e60\uff08\u610f\u601d\u662f\u4e0d\u4f1a\u7684\u81ea\u5df1\u53bb\u5b66\u6389\uff09:<ul> <li>\u97f3\u6807 / \u53e3\u8bed</li> <li>\u8bcd\u6c47\u91cf</li> </ul> </li> <li>\u6bd4\u8bed\u6587\u3001\u6570\u5b66\uff08120+\u7684\u65f6\u5019\uff09\u63d0\u5206\uff08110+\u7684\u65f6\u5019\uff09\u5feb\u3002\u8bad\u7ec3\u65b9\u6cd5\u7b80\u5355\uff0c\u89c1\u6548\u5feb\uff0c\u63d0\u5347\u7a33\u5b9a\u3002</li> <li>\u8f7b\u903b\u8f91\uff0c\u91cd\u7406\u89e3\uff08\u8bfb\u61c2\u4e86\u5c31\u80fd\u505a\u5bf9\u9898\u76ee\uff09</li> </ul>"},{"location":"Summaries/High%20School/eng_fht/#_4","title":"\u6295\u5165\u65f6\u95f4\u600e\u4e48\u6837\uff1f","text":"<ul> <li>\u4ec0\u4e48\u788e\u7247\u5316\u80cc\u5355\u8bcd\u5176\u5b9e\u4e0d\u4e00\u5b9a\u6709\u7528\uff0c\u56fe\u7684\u53ea\u662f\u591a\u770b\u51e0\u6b21\u3002\u540c\u6837\uff0c\u65e9\u8bfb\u665a\u8bfb\u4e5f\u53ea\u662f\u591a\u82b1\u70b9\u65f6\u95f4\u719f\u6089\u719f\u6089\uff0c\u5b66\u6821\u7edf\u4e00\u8bad\u7ec3\u7684\u542c\u529b\u771f\u4e0d\u662f\u5f88\u6709\u7528\u53cd\u6b63\u3002\u5efa\u8bae\u79c1\u4e0b\u627e\u8001\u5e08\u5f3a\u5316\u4e00\u4e0b\uff08</li> <li>\u5e73\u65f6\u4e3b\u8981\u7684\u65f6\u95f4\u6295\u5165:<ul> <li>\u505a\u5377\u5b50\u3001\u8ba2\u6b63\u3001\u67e5\u5355\u8bcd</li> <li>\u5199\u4f5c\u6587\u3001\u6279\u6539\u3001\u80cc\u8bed\u6599</li> </ul> </li> <li>\u6211\u4e2a\u4eba\u8ba4\u4e3a\u5355\u8bcd\u662f\u6ca1\u5fc5\u8981\u53bb\u80cc\u7ef4\u514b\u591a\u7684\uff08\u4e0d\u8fc7\u5982\u679c\u8fde\u521d\u4e2d\u7684\u5355\u8bcd\u90fd\u4e0d\u4f1a\u7684\u8bdd\uff0c\u8fd8\u662f\u5148\u80cc\u4e2a1500\uff08\u521d\u4e2d\u5355\u8bcd\u5927\u7eb2\uff09\u518d\u8bf4\u5427\u3002\u540e\u9762\u7684\u5c31\u662f\u591a\u67e5\u67e5\u5b57\u5178\uff0c\u8bb0\u5728\u7b14\u8bb0\u672c\u4e0a\uff0c\u591a\u770b\u770b\u5c31\u597d\u4e86\u3002(\u6709\u7684\u8001\u5e08\u8981\u6c42\u8fc7\u4e2aN\u904d\u7684\u7ef4\u514b\u591a\u5176\u5b9e\u4e0d\u592a\u6709\u7528\uff0c\u6bd5\u7adf\u4e00\u4e2a\u5355\u8bcd\u77e5\u905310\u4e2a\u610f\u601d\uff0c\u4e5f\u4e0d\u4e00\u5b9a\u80fd\u591f\u7406\u89e3\u6587\u610f)<ul> <li>\u5982\u679c\u771f\u60f3\u901f\u6210\uff0c\u5efa\u8bae\u641c\u7d22IAI\u53d1\u7684\u5355\u8bcd\u5927\u7eb2\uff0c\u4ee5\u8ba4\u77e5\u8bcd\u6c47\u4e3a\u6807\u51c6\uff0c\u4e00\u661f\u671f\u5185\u80cc\u5b8c\u65b0\u9ad8\u80033000\u5355\u8bcd\u3002</li> </ul> </li> <li>\u7a33\u5b9a\u8bad\u7ec3\u7684\u60c5\u51b5\u4e0b\uff0c130\u5e94\u8be5\u662f\u6240\u6709\u5b66\u751f\u90fd\u80fd\u57286\u4e2a\u6708\u5185\u53ef\u4ee5\u8fbe\u5230\u7684\u3002</li> </ul>"},{"location":"Summaries/High%20School/eng_fht/#_5","title":"\u5b66\u4e60\u65b9\u6cd5:","text":"<p>\u53ef\u4ee5\u8bf4\uff0c\u82f1\u8bed\u662f\u4e3b\u8bfe\u91cc\u6700\u6709\u8ff9\u53ef\u5faa\u7684\u4e00\u95e8\u8bfe\u4e86\u3002\u800c\u4e14\u82f1\u8bed\u6709\u4e24\u6b21\u673a\u4f1a\uff0c\u6240\u4ee5\u53ea\u8981\u52aa\u529b\u5c31\u80fd\u53d6\u5f97\u5f88\u4e0d\u9519\u7684\u5206\u6570\uff08\u6027\u4ef7\u6bd4\u6781\u9ad8\uff09</p>"},{"location":"Summaries/High%20School/eng_fht/#_6","title":"\u8d44\u6e90\u63a8\u8350:","text":"<ul> <li>IAI yyds\uff01\uff01\uff01\uff08\u4e00\u4e2a\u82f1\u8bed\u516c\u4f17\u53f7\uff09</li> <li>\u4e00\u4e9b\u4e66:<ul> <li>\u8bed\u6cd5\u4ff1\u4e50\u90e8</li> <li>\u4e00\u672c\u6d3b\u9875\u7b14\u8bb0\u672c</li> <li>\u725b\u6d25 / \u6717\u6587 \u9ad8\u7ea7\u5b57\u5178 \u6216\u8005 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<li>\u968f\u4fbf\u4e0d\u77e5\u6765\u6e90\u7684\u4e13\u9898\u96c6\uff08\u9ad8\u8003\u5fc5\u5237\u9898\uff0c\u9ad8\u8003\u4e94\u4e09\uff08\u6392\u7248\u96be\u770b\uff0c\u9898\u76ee\u8001\u65e7\uff09\uff09</li> <li>\u91d1\u8003\u5377\u7b49\uff08\u522b\u60f3\u4e86\uff0c\u6839\u672c\u4e0d\u4f1a\u505a\u591a\u5c11\u7684\uff09 IAI\u3000is enough\uff01</li> <li>\u8001\u5e08\u4e0d\u77e5\u9053\u54ea\u91cc\u641e\u6765\u7684\u5916\u7701\u7684\u5377\u5b50/\u5546\u4e1a\u5377\uff08\u505a\u4e86\u63d0\u5347\u5f88\u5c0f\uff0c\u5f71\u54cd\u53e3\u5473\u7f62\u4e86\uff09</li> <li>\u5e73\u65f6\u7684\u4f5c\u4e1a\uff08\u7f3a\u4e4f\u9488\u5bf9\u6027\uff0c\u5408\u7406\u770b\u5f85\uff0c\u7231\u505a\u4e0d\u505a\uff09</li> <li>\u51fa\u53bb\u8865\u8bfe\u53d1\u7684\u4f5c\u6587\u89e3\u6790\uff08\u5408\u7406\u770b\u5f85\uff0c\u8b66\u60d5\u6a21\u677f/\u79d2\u6740/\u9ad8\u7ea7\u8bcd\u6c47\uff09</li> <li>\u56db\u516d\u7ea7\u3001\u6258\u798f\u3001\u96c5\u601d\u3001GRE\u5355\u8bcd\uff08\u6027\u4ef7\u6bd4\u4f4e\uff0c\u8d34\u5408\u5ea6\u4f4e\uff0c\u88c5\u903c\u5ea6\u9ad8\uff0c\u4e0d\u7b26\u5408\u9ad8\u8003\u5bfc\u5411\uff09</li> </ul>"},{"location":"Summaries/High%20School/eng_fht/#_8","title":"\u5b66\u4e60\u65b9\u6cd5:","text":""},{"location":"Summaries/High%20School/eng_fht/#_9","title":"\u9ad8\u4e00\u9ad8\u4e8c\u4e0a:","text":"<ul> <li>\u79ef\u7d2f\u5355\u8bcd\uff08\u8bb0\u5728\u6d3b\u9875\u672c\u4e0a\uff09</li> <li>\u63d0\u5347\u5ba2\u89c2\u9898:\u6240\u6709\u9898\u76ee\u9519\u7684\u5f04\u61c2\uff0c\u505a\u8fc7\u4e0d\u9519\uff08\u522b\u73a9\u4f60\u7684\u7834\u9519\u9898\u672c\u4e86\uff09</li> <li>\u4f5c\u6587\u6446\u70c2\uff08\u9ad8\u4e00\u9ad8\u4e8c\u8303\u6587\u6c34\u5e73\u592a\u4f4e\uff0c\u6ca1\u6709\u5b66\u4e60\u7684\u4ef7\u503c\uff09</li> </ul>"},{"location":"Summaries/High%20School/eng_fht/#_10","title":"\u9ad8\u4e8c\u4e0b\u9ad8\u4e09:","text":"<ul> <li>\u8fd9\u65f6\u5019\u9ad8\u8003\u5355\u8bcd\u90fd\u8ba4\u4e0d\u5168\u8bf4\u4e0d\u8fc7\u53bb\u4e86<ul> <li>\u8bf7\u53c2\u8003\u524d\u6587</li> </ul> </li> <li>\u8bed\u6cd5\u4e0d\u4f1a\u7684\u53bb\u5b66\u8bed\u6cd5\uff08\u770b\u8bed\u6cd5\u4ff1\u4e50\u90e8\uff09\uff0c\u4e0d\u8981\u8ffd\u6c42\u5b8c\u6574\u5177\u4f53\uff0c\u80fd\u591f\u505a\u8bed\u6cd5\u586b\u7a7a\u548c\u4f1a\u5206\u6790\u9605\u8bfb\u4e2d\u7684\u957f\u96be\u53e5\u5c31\u591f\u4e86\u3002\uff08\u751a\u81f3\u865a\u62df\u8bed\u6c14\u4ec0\u4e48\u7684\u90fd\u8003\u4e0d\u4e86\uff09</li> <li>\u9650\u65f6\u505a\u5377\u5b50\uff0840min\u505a\u5b8c\u5ba2\u89c2\u9898\uff09+\u8ba2\u6b63\uff08\u641e\u61c2\u4e3a\u4ec0\u4e48\u9519\uff09<ul> <li>\u505a\u591f30\u5957\u5c31\u53ef\u4ee5\u7a33\u4e0a130\uff08\u5377\u5b50\u6765\u6e90IAI\uff09</li> </ul> </li> <li>\u9650\u65f6\u7ec3\u4f5c\u6587\uff08\u5e94\u7528\u6587+\u7eed\u5199\uff09<ul> <li>\u7eed\u5199\u5199\u591f20\u504f\u5c31\u53ef\u4ee518+</li> <li>\u5e94\u7528\u6587\u5efa\u8bae\u79ef\u7d2f\u6a21\u677f\uff0c\u9047\u5230\u4e0d\u540c\u4e3b\u9898\u90fd\u6709\u8bdd\u8bf4\u3002\u4fdd\u6301\u5e73\u65f611+\u5c31\u597d\u3002</li> </ul> </li> <li>\u5b66\u6821\u8003\u8bd5\u7684\u4f5c\u6587\u6253\u5206\u4e0d\u503c\u5f97\u76f8\u4fe1:<ul> <li>\u5efa\u8bae\u73cd\u60dc\u8054\u8003\uff08\u4e0d\u662f\u5b66\u6821\u8001\u5e08\u6539\u7684\u65f6\u5019\uff0c\u6bd4\u5982\u5076\u5c14\u7684Z20\uff09</li> <li>\u53ea\u770b\u8001\u5e08\u6539\u7684\u8bed\u6cd5\u9519\u8bef</li> <li>\u53ef\u4ee5\u53c2\u52a0IAI\u57f9\u8bad\uff08\u4e0d\u662f\u5e7f\u544a\uff0c\u6027\u4ef7\u6bd4\u6bd4\u8f83\u4f4e\uff0c\u4f46\u662f\u6539\u4f5c\u6587\u7684\u6807\u51c6\u5f88\u51c6\uff09</li> </ul> </li> <li>\u4ee5\u63d0\u5347\u6210\u7ee9\u4e3a\u5bfc\u5411\uff0c\u8b66\u60d5\u63d0\u5347\u82f1\u8bed\u7d20\u517b\u66f2\u7ebf\u6551\u56fd\u7684\u9677\u8fdb\uff08\u5982\uff0c\u770b\u5916\u520a\uff0c\u8bfb\u539f\u8457\u7b49\u7b49\uff09</li> </ul>"},{"location":"Summaries/High%20School/eng_fht/#_11","title":"\u8bad\u7ec3\u76ee\u6807:","text":"<ul> <li>\u5ba2\u89c2\u9898\u4fdd\u8bc1\u572830-35\u5206\u949f\u5185\u505a\u5b8c</li> <li>\u4f5c\u65871\u5c0f\u65f6\u5185\u5199\u5b8c\u4e24\u7bc7\uff0c\u8981\u6c42\u5e94\u7528\u6587\u4e0d\u4f4e\u4e8e11\u5206\uff0c\u7eed\u5199\u4e0d\u4f4e\u4e8e18\u5206\uff08\u4e24\u6bb5\u90fd\u5199\u6ee110\u884c\uff09</li> <li>\u5ba2\u89c2\u9898\u6263\u5206\u4e0d\u8d85\u8fc75\u5206\uff08\u542c\u529b\u9605\u8bfb\u4e03\u9009\u4e94\u5168\u5bf9\uff0c\u5b8c\u578b\u53ef\u62631\u5206\uff0c\u8bed\u586b\u53ef\u62631.5\u5206\uff09</li> </ul>"},{"location":"Summaries/High%20School/eng_fht/#_12","title":"\u5c0f\u6280\u5de7:","text":"<ul> <li>\u5408\u7406\u5b89\u6392\u505a\u9898\u65f6\u95f4\uff0c\u4e0d\u4e00\u5b9a\u8981\u4ece\u9605\u8bfb\u5f00\u59cb\u505a</li> <li>95%\u7684\u5b8c\u578b\u7b26\u54084443\uff08\u9009\u9879\u5206\u5e03\uff09\uff0c\u9ad8\u8003\u4e2d\u53ea\u670922\u8fd8\u662f\u54ea\u4e00\u5e74\u51fa\u73b0\u8fc74533\uff0c\u5efa\u8bae\u505a\u5b8c\u578b\u7684\u65f6\u5019\u5708\u9009\u9879\u800c\u975e\u5199\u5b57\u6bcd\uff0c\u4e0d\u7136\u4e0a\u4e0b\u4f1a\u5f71\u54cd\u3002\u7b2c\u4e00\u6b21\u505a\u4e0d\u51fa\u6765\u7684\u53ef\u4ee5\u5148\u7a7a\u7740\uff0c\u518d\u8bfb\u4e00\u904d\u540e\u56de\u6765\u6839\u636e\u5206\u5e03\u7efc\u5408\u6587\u610f\u586b\u6ee1\u3002</li> <li>\u9605\u8bfb\u8bfb\u5b8c\u6587\u7ae0\uff0c\u8bed\u586b\u5168\u90e8\u8981\u8bfb \u518d\u505a\u9898\uff08\u4e0d\u7136\u4f1a\u6709\u5f88\u6076\u5fc3\u7684\u9677\u9631\uff09</li> <li>\u4f5c\u6587\u4e0d\u4e00\u5b9a\u8981\u6253\u8349\u7a3f\uff0c\u4f46\u662f\u4e00\u5b9a\u4e0d\u80fd\u6709\u8bed\u6cd5\u9519\u8bef\uff0c\u5b57\u8ff9\u96be\u770b\uff08\u8fd9\u4e24\u70b9\u662f\u5f71\u54cd\u4f5c\u6587\u7684\u4e3b\u8981\u56e0\u7d20\uff0c24\u9ad8\u8003\u4e4b\u540e\u53ef\u80fd\u8fd8\u6709\u4e3b\u65e8\u5347\u534e\uff09\u3002</li> <li>\u8bfb\u61c2\u624d\u662f\u5b66\u82f1\u8bed\u7684\u552f\u4e00\u8981\u70b9\uff01\uff01\uff01</li> </ul> <p>\u8bf7\u5408\u7406\u4f7f\u7528IAI\uff0c\u5f88\u6709\u53ef\u80fd\u662f\u6700\u597d\u7684\u8d44\u6e90\u3002</p>"},{"location":"Summaries/High%20School/math_fht/","title":"\u6570\u5b66\u7ecf\u9a8c\u5206\u4eab","text":""},{"location":"Summaries/High%20School/math_fht/#_1","title":"\u6570\u5b66\u7ecf\u9a8c\u5206\u4eab","text":"<p> \u7ea6 757 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>\u80cc\u666f:2024\u5c4a\u9ad8\u8003138\uff08\u586b\u7a7a\u9519\u4e00\u90535'+19\u9898\u6700\u540e\u4e00\u95ee7'\uff09</p>"},{"location":"Summaries/High%20School/math_fht/#_2","title":"\u5b66\u79d1\u672c\u8eab:","text":"<ul> <li>\u6211\u60f3\u6570\u5b66\u7684\u4f53\u7cfb\uff08\u89e3\u9898\u5957\u8def\uff09\u662f\u4e0d\u5982\u7269\u7406\u5b8c\u6574\u7684\u3002\u6bd4\u5982:\u5706\u9525\u66f2\u7ebf\u5f88\u96be\u627e\u5230\u901a\u6cd5\u89e3\u51b3\u6240\u6709\u9898\u6216\u8005\u5bfc\u6570\u6709\u65f6\u5019\u4e5f\u4f1a\u6d89\u53ca\u5f88\u591a\u5947\u5947\u5999\u5999\u7684\u77e5\u8bc6\u3002</li> <li>\u771f\u7684\u5f88\u96be\u7a33\u5b9a\u63d0\u5206\uff08\u4e3b\u8981\u6307120+?\uff09</li> <li>\u5b66\u79d1\u601d\u7ef4\u53ef\u80fd\u5f88\u91cd\u8981\u3002\u867d\u7136\u6211\u4e0d\u662f\u5f88\u80fd\u9610\u660e\u8fd9\u4e2a\u6982\u5ff5\uff0c\u4f46\u5177\u4f53\u6765\u8bf4\u5c31\u662f\uff0c\u8981\u53bb\u505a\u95ee\u9898\uff0c\u800c\u4e0d\u662f\u80cc\u7b54\u6848\u3002\u5176\u5b9e\u5f88\u591a\u65f6\u5019\u7684\u505a\u4e5f\u4e0d\u8fc7\u662f\u9ed8\u5199\u4ee5\u524d\u4f1a\u7684\u5957\u8def\uff0c\u4e0d\u4f1a\u7684\u4e5f\u57fa\u672c\u4e0d\u53ef\u80fd\u5f53\u573a\u521b\u65b0\u51fa\u6765\u3002\u6240\u4ee5\u5927\u6982\u8fd9\u91cc\u7684\u505a\u6307\u7684\u662f\uff0c\u8fd0\u7528\u4ee5\u524d\u5b66\u8fc7\u7684skill\uff0c\u5c06\u4ed6\u4eec\u7ec4\u5408\u5728\u4e00\u8d77\uff0c\u62b5\u8fbe\u6240\u8981\u8fbe\u6210\u7684\u76ee\u6807\u3002</li> <li>\u6240\u4ee5\uff0c\u4e5f\u8bb8\u4f46\u51e1\u4e0a\u8ff0\u4e00\u4e2a\u6b65\u9aa4\u505a\u4e0d\u5230\uff0c\u90fd\u5f88\u96be\u505a\u5bf9\u4e00\u9053\u9898:<ul> <li>\u5206\u6790\u76ee\u6807\u662f\u4ec0\u4e48</li> <li>\u8003\u8651\u8981\u600e\u4e48\u5230\u8fbe</li> <li>\u8fd0\u7528\u4ec0\u4e48\u5de5\u5177<ul> <li>\u5982\u4f55\u68c0\u9a8c\uff0c\u5b9a\u6027\u5224\u65ad    </li> <li>\u5982\u4f55\u8bd5\u63a2\uff0c\u5b9a\u91cf\u8ba1\u7b97</li> </ul> </li> </ul> </li> </ul>"},{"location":"Summaries/High%20School/math_fht/#_3","title":"\u5b66\u4e60\u65b9\u6cd5:","text":"<p>\u6211\u4e00\u4e2a\u9ad8\u4e2d\u57fa\u672c\u6ca1\u505a\u8fc7\u6570\u5b66\u4f5c\u4e1a\u7684\u4eba\u4e5f\u8bb8\u4e0d\u914d\u6765\u8bf4\u8fd9\u4e2a\u95ee\u9898\u3002</p>"},{"location":"Summaries/High%20School/math_fht/#_4","title":"\u7701\u6d41\u7248:","text":"<ul> <li>\u638c\u63e1\u57fa\u672c\u77e5\u8bc6\u70b9\uff0c\u5b9a\u4e49\uff0c\u516c\u5f0f\uff0c\u5957\u8def\uff08\u5982\u7aef\u70b9\u6548\u5e94\uff09</li> <li>\u505a\u6574\u5377\u67e5\u6f0f\u8865\u7f3a</li> <li>\u505a\u4e13\u9898\uff0c\u6bd4\u8f83\u5f52\u7eb3</li> <li>\u8003\u8bd5\u8bad\u7ec3\u5fc3\u6001</li> </ul>"},{"location":"Summaries/High%20School/math_fht/#_5","title":"\u6ce8\u610f\u4e8b\u9879:","text":"<ul> <li>\u9519\u9898\u672c\u5f88\u53ef\u80fd\u6ca1\u6709\u7528\uff0c\u771f\u6b63\u6709\u7528\u7684\u662f\u8003\u8bd5\u4ee5\u540e\u7684\u590d\u76d8\uff0c\u81ea\u5df1\u6574\u7406\u603b\u7ed3\u51fa\u7684\u5957\u8def\u65b9\u6cd5\uff0c\u6613\u9519\u5f52\u7eb3\u3002     \u6bd4\u5982:     \u53ef\u80fd\u8fd9\u6b21\u5bfc\u6570\u9898\u6ca1\u505a\u51fa\u6765\uff0c\u4f60\u8981\u60f3\u6e05\u695a\u7684\u662f\uff0c\u4e3a\u4ec0\u4e48\u6ca1\u505a\u51fa\u6765\uff0c\u8003\u8bd5\u7684\u65f6\u5019\u6ca1\u82b1\u65f6\u95f4\u8fd8\u662f\u82b1\u4e86\u65f6\u95f4\u4e5f\u6ca1\u60f3\u660e\u767d\uff0c\u771f\u6b63\u6b63\u786e\u7684\u51b3\u7b56\u662f\u4ec0\u4e48\uff08\u8df3\u8fc7\uff1f\u7ee7\u7eed\u601d\u8003\uff1f\uff09\uff0c\u5982\u679c\u4e0b\u6b21\u8fd8\u662f\u505a\u4e0d\u51fa\u6765\u53ef\u4ee5\u600e\u4e48\u5c1d\u8bd5\uff0c\u5b66\u5230\u4e86\u4ec0\u4e48\u65b0\u7684\u6a21\u578b\u3002</li> <li>\u4e0d\u8981\u5bf9\u8003\u8bd5\u8fc7\u62df\u5408\uff0c\u5f88\u591a\u4eba\u8fc7\u5206\u5938\u5927\u4e86\u590d\u76d8\u7684\u4f5c\u7528\u3002\u7279\u522b\u662f\u5728\u6570\u5b66\u5e94\u8bd5\u65b9\u9762\uff0c\u82b1\u8fc7\u591a\u7684\u65f6\u95f4\u5728\u590d\u76d8\u4e0a\u7684\u6027\u4ef7\u6bd4\u4e0d\u9ad8\uff0c\u4e0d\u5982\u591a\u505a\u70b9\u9898/\u770b\u70b9\u65b0\u9c9c\u73a9\u610f/\u5b66\u522b\u7684\u79d1\u76ee\u53bb\u3002</li> <li>\u65f6\u95f4\u5f52\u7eb3\u548c\u5fc3\u6001\u51b3\u5b9a\u8003\u8bd5\u5206\u6570\u7684\u4e0b\u9650\u3002\u57fa\u7840\u9898\u505a\u5b8c\u5c31\u6709\u5f88\u591a\u5206\u6570\u5566\uff01\u522b\u88ab\u4e00\u4e2a\u9898\u5361\u4f4f\u4e86\u5c31\u5fc3\u6001\u5d29\u4e86\uff0c\u5f88\u591a\u4eba\u8bf4\u81ea\u5df1\u5fc3\u6001\u597d\u53ea\u4e0d\u8fc7\u662f\u6ca1\u505a\u8fc7\u9053\u9053\u4e0d\u987a\u5229\u7684\u5377\u5b50\u3002</li> <li>\u591a\u8ddf\u8001\u5e08\u4ea4\u6d41\uff0c\u8001\u5e08\u5f88\u53ef\u80fd\u6bd4\u4f60\u60f3\u50cf\u7684\u8981\u66f4helpful\u4e00\u4e9b\u3002</li> <li>\u4e0d\u8981\u653e\u5f03\u6570\u5b66\uff0c150\u5206\u5462\uff0c\u8fd9\u90fd\u653e\u4e86\u8fd8\u662f\u522b\u9ad8\u8003\u4e86\u3002<ul> <li>\u65e9\u70b9\u5b66\u6570\u5b66\u5427\uff0c\u522b\u6b7b\u5230\u4e34\u5934\u4e86\u624d\u540e\u6094</li> </ul> </li> <li>\u4e0d\u8981\u6c89\u8ff7\u9ad8\u7ea7\u73a9\u610f:\uff08\u6709\u8fd9\u65f6\u95f4\u4e0d\u5982\u53bb\u73a9\uff09<ul> <li>\u6cf0\u52d2\u5c55\u5f00</li> <li>\u6781\u70b9\u6781\u7ebf</li> <li>\u5bfc\u6570\u7684\u4e00\u5806\u5947\u6280\u6deb\u5de7</li> <li>...</li> </ul> </li> <li>\u8ba1\u7b97\u80fd\u529b\u5f88\u91cd\u8981\uff0c\u89e3\u6790\u51e0\u4f55\u8be5\u7b97\u7684\u8981\u7b97\u3002</li> </ul>"},{"location":"Summaries/High%20School/math_fht/#_6","title":"\u8d44\u6599:","text":"<ul> <li>\u5b66\u6821\u5e73\u65f6\u7684\u8003\u8bd5\uff0c\u8bf7\u8ba4\u771f\u5bf9\u5f85</li> <li>\u6d59\u8003\u795e\u5899</li> <li>\u4e0d\u63a8\u8350\u4ec0\u4e48\u6559\u8f85\uff0c\u5bf9\u9ad8\u8003\u7684\u6700\u4f73\u62df\u5408\u662f\u9ad8\u8003\u5377+\u56db\u7701\u8054\u8003\u4e4b\u7c7b\u7684\u98ce\u5411\u5377</li> <li>\u540c\u5b66\u7684\u7b14\u8bb0\uff08\u4e0d\u662f</li> </ul>"},{"location":"Summaries/High%20School/phy_fht/","title":"\u7269\u7406\u7ecf\u9a8c\u5206\u4eab","text":""},{"location":"Summaries/High%20School/phy_fht/#_1","title":"\u7269\u7406\u7ecf\u9a8c\u5206\u4eab","text":"<p> \u7ea6 1581 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 8 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>\u80cc\u666f:2024\u5c4a\u9996\u800395-&gt;\u9ad8\u8003100</p>"},{"location":"Summaries/High%20School/phy_fht/#_2","title":"\u5b66\u79d1\u672c\u8eab:","text":""},{"location":"Summaries/High%20School/phy_fht/#_3","title":"\u8981\u4e0d\u8981\u9009\u7269\u7406\uff1f","text":"<ul> <li>\u5982\u679c\u4ee5\u540e\u60f3\u5b66\u7406\u5de5\u79d1\u7684\u8bdd\uff0c\u6700\u597d\u662f\u7269\u5316\u5927\u793c\u5305\u4e00\u8d77\u4e0a\u300224\u5e74\u6587\u79d1\u6ed1\u6863\u8fd8\u662f\u5f88\u5389\u5bb3\u7684\u3002</li> <li>\u5bf9\u4e8e\u6570\u5b66\u4e0d\u597d\u7684\u540c\u5b66\u6765\u8bf4\uff0c\u7269\u7406\u7684\u96be\u5ea6\u4e0d\u4f1a\u5f88\u5c0f\u3002<ul> <li>\u5efa\u6a21</li> <li>\u8bbe\u65b9\u7a0b\uff0c\u627e\u672a\u77e5\u91cf\uff0c\u89e3\u591a\u5143\u65b9\u7a0b</li> <li>\u4e09\u89d2\u51fd\u6570\u7684\u719f\u7ec3\u4f7f\u7528</li> <li>\u5bfc\u6570\u4ee5\u53ca\u90e8\u5206\u79ef\u5206\u7684\u4f7f\u7528</li> <li>\u5bf9\u516c\u5f0f\u63a8\u5bfc\u65b9\u5411\u7684\u628a\u63e1</li> </ul> </li> <li> <p>\u5bf9\u4e8e\u6b7b\u8bb0\u786c\u80cc\u5b66\u7269\u7406\u7684\u540c\u5b66\u6765\u8bf4\uff0c\u5343\u4e07\u4e0d\u8981\u9009\u7269\u7406\u6765\u6076\u5fc3\u81ea\u5df1/\u8001\u5e08\u3002\u8bf7\u9a8c\u8bc1\u4f60\u662f\u5426\u638c\u63e1\u5982\u4e0b\u516c\u5f0f\u63a8\u5bfc:</p> <ul> <li>\u5229\u7528\u6253\u70b9\u8ba1\u65f6\u5668\u6c42\u52a0\u901f\u5ea6\u516c\u5f0f</li> <li>\u5e73\u629b\u8fd0\u52a8\u8f68\u8ff9\u65b9\u7a0b\uff0c\u5750\u6807\u968f\u65f6\u95f4\u53d8\u5316\u51fd\u6570\uff0c\u53cd\u5411\u5ef6\u957f\u7ebf\u7684\u4e8c\u7ea7\u7ed3\u8bba</li> <li>\u4e07\u6709\u5f15\u529b\u516c\u5f0f\uff0c\u5929\u4f53\u8fd0\u52a8\u901f\u5ea6\uff0c\u89d2\u901f\u5ea6\uff0c\u5468\u671f\uff0c\u80fd\u91cf</li> <li>\u5f39\u6027\u52bf\u80fd\uff0c\u52a8\u80fd\uff0c\u673a\u68b0\u80fd\uff08\u5f15\u529b\u52bf\u80fd\uff0c\u5e93\u4ed1\u52bf\u80fd\uff09</li> <li>\u52a8\u91cf\u6765\u6e90\uff0c\u78b0\u649e\u6a21\u578b</li> <li>\u6d1b\u4f26\u5179\u529b\u53ca\u5bf9\u5e94\u7c92\u5b50\u8fd0\u52a8\u6a21\u578b</li> <li>\u7535\u78c1\u611f\u5e94\u53ca\u5bf9\u5e94\u6a21\u578b:\u65cb\u8f6c\u68d2\u7684\u52a8\u751f\u7535\u52a8\u52bf\uff0c\u5355\u68d2\uff0c\u53cc\u68d2\uff0c\u7535\u5bb9\uff0c\u7535\u611f\uff0c\u78c1\u9a71\u52a8\uff0c\u70ed\u91cf\u8ba1\u7b97</li> </ul> <p>\u5982\u679c\u4f60\u4e3b\u8981\u662f\u9760\u8bb0\u80cc\u6765\u652f\u6491\u7269\u7406\u5b66\u4e60\uff0c\u90a3\u8bf7\u4f60\u4e0d\u8981\u9009\u7269\u7406\u3002</p> </li> </ul>"},{"location":"Summaries/High%20School/phy_fht/#_4","title":"\u7269\u7406\u96be\u5ea6\u600e\u4e48\u6837\uff1f","text":"<ul> <li>\u7269\u7406\u5e94\u8be5\u662f\u7406\u79d1\u91cc\u4f53\u7cfb\u7ed3\u6784\u7d27\u5bc6\u5b8c\u6574\uff0c\u5e94\u8bd5\u624b\u6bb5\u4e30\u5bcc\u5b8c\u5907\u7684\u4e00\u95e8\u5b66\u79d1\u4e86\u3002\u638c\u63e1\u77e5\u8bc6\u70b9\uff0c\u5b9a\u4e49\uff0c\u5b9a\u7406\uff0c\u6a21\u578b\uff0c\u5e94\u7528\u9700\u8981\u82b1\u65f6\u95f4\uff0c\u4e14\u6709\u5408\u7406\u7684\u8def\u7ebf\u53ef\u4ee5\u4f9d\u636e\u3002<ul> <li>\u8ddf\u5316\u5b66\u6bd4\uff0c\u5b83\u66f4\u504f\u5b9a\u91cf\uff0c\u6709\u660e\u786e\u7684\u516c\u5f0f\u8ba1\u7b97\uff0c\u5b8c\u6574\u7684\u903b\u8f91\u94fe\u6761\u3002</li> <li>\u8ddf\u6570\u5b66\u6bd4\uff0c\u5b83\u66f4\u504f\u5e94\u7528\uff0c\u6709\u6e05\u6670\u7684\u7ed3\u679c\u5bfc\u5411\uff0c\u4e0d\u8981\u6c42\u7075\u611f\u7206\u53d1\u3002</li> <li>\u8ddf\u6280\u672f\u6bd4\uff0c\u5b83\u66f4\u504f\u8ba1\u7b97\uff0c\u6709\u76f8\u6263\u7684\u77e5\u8bc6\u4f53\u7cfb\uff0c\u66f4\u4f4e\u7684\u5b66\u4e60\u95e8\u69db\u3002</li> </ul> </li> <li>\u53ea\u8981\u4f60\u613f\u610f\u4e0b\u529f\u592b\uff0c\u7269\u7406\u7edd\u5bf9\u662f\u4e00\u95e8\u52aa\u529b\u5c31\u6709\u56de\u62a5\u7684\u5b66\u79d1\u3002</li> </ul>"},{"location":"Summaries/High%20School/phy_fht/#_5","title":"\u5b66\u4e60\u65b9\u6cd5:","text":"<p>\u8ddf\u6280\u672f\u7c7b\u4f3c</p>"},{"location":"Summaries/High%20School/phy_fht/#etc","title":"\u627e\u4e00\u672c\u6559\u8f85\uff08\u4e94\u4e09\u9ad8\u8003\u7248 etc.\uff09\u770b\u5b8c\u77e5\u8bc6\u70b9","text":"<ul> <li>\u8981\u6c42\u80fd\u591f\u77e5\u9053\u5b9a\u4e49\uff0c\u91cd\u8981\u516c\u5f0f\u63a8\u5bfc\uff0c\u884d\u751f\u4e8c\u7ea7\u7ed3\u8bba\u548c\u57fa\u672c\u6a21\u578b     \u6bd4\u5982:<ul> <li>\u7535\u5bb9\u7684\u5b9a\u4e49</li> <li>\u7535\u5bb9\u5927\u5c0f\u7684\u8ba1\u7b97\u5f0f</li> <li>\u6d89\u53ca\u7535\u5bb9\u7684\u52a8\u6001\u53d8\u5316</li> <li>\u7535\u5bb9\u5728\u7535\u8def\u4e2d\u5982\u4f55\u8ba1\u7b97</li> <li>\u7535\u5bb9\u7684\u80fd\u91cf\u516c\u5f0f</li> <li>\u7535\u5bb9\u5145\u653e\u7535\u5b9e\u9a8c</li> <li>\u7535\u5bb9\u5728\u4ea4\u6d41\u7535\u4e2d\u7684\u4f5c\u7528\uff08\u5b9a\u6027\uff09</li> <li>\u7535\u5bb9\u4e0e\u5176\u4ed6\u6a21\u578b\u7684\u7ed3\u5408</li> <li>...</li> </ul> </li> </ul>"},{"location":"Summaries/High%20School/phy_fht/#_6","title":"\u505a\u9898","text":"<ul> <li>\u9898:<ul> <li>\u5377\u5b50</li> <li>\u4e13\u9898  </li> </ul> </li> <li>\u65b9\u6cd5:<ul> <li>\u5377\u5b50\u7528\u6765\u67e5\u6f0f\u8865\u7f3a\uff0c\u63d0\u5347\u6574\u4f53\u5b8c\u6210\u5ea6\uff0c\u4f18\u5316\u65f6\u95f4\u5206\u914d\uff0c\u5feb\u901f\u5efa\u6784\u77e5\u8bc6\u6846\u67b6</li> <li>\u4e13\u9898\u7528\u6765\u5f3a\u5316\u8ba1\u7b97\uff0c\u719f\u6089\u516c\u5f0f\uff0c\u6df1\u5316\u903b\u8f91\u53ca\u5f52\u7eb3\u672c\u8d28</li> </ul> </li> <li>\u5982\u679c\u4e0d\u4f1a\u600e\u4e48\u529e:<ul> <li>\u770b\u7b54\u6848\uff0c\u95ee\u8001\u5e08\uff0c\u95ee\u540c\u5b66</li> <li>\u9009\u53d6\u540c\u7c7b\u9898\u76ee\uff0c\u505a\u8db3\u591f\u6570\u91cf\u540e\u5f52\u7eb3\u6574\u7406\u6a21\u578b</li> </ul> </li> <li>\u6613\u9519\u70b9\u5373\u4f7f\u8bb0\u5f55<ul> <li>\u53ef\u7528\u6d3b\u9875\u672c/A4\u7eb8+\u71d5\u5c3e\u5939</li> </ul> </li> <li>\u63a8\u8350\u5f52\u7eb3\u6a21\u578b\u800c\u4e0d\u662f\u6574\u7406\u9519\u9898</li> <li>\u4e00\u5b9a\u8981\u591a\u7ec3\u8ba1\u7b97\u548c\u65f6\u95f4\uff0c\u5c11\u7528/\u4e0d\u7528\u8ba1\u7b97\u5668<ul> <li>\u5728\u9ad8\u4e09\u672b\u671f\uff0c\u6211\u80fd\u7a33\u5b9a40min\u505a\u5b8c\u673a\u68b0\u80fd\u53ca\u524d\u9762\u6240\u6709\u90e8\u5206\u3002\u5f53\u7136\u8fd9\u5bf9\u5927\u591a\u6570\u540c\u5b66\u6765\u8bf4\u592a\u5feb\u4e86\uff0c\u4f46\u901f\u5ea6\u63d0\u5347\u600e\u4e48\u4e5f\u4e0d\u5acc\u591a\u3002</li> <li>\u4f8b\u5982\u572824\u5e74\u9ad8\u8003\u4e2d\uff0c\u5f88\u591a\u540c\u5b66\u7531\u4e8e\u7535\u78c1\u611f\u5e94\u5361\u58f3\u800c\u6ca1\u6709\u505a\u5b8c\u5377\u5b50\uff0c\u5bfc\u81f4\u4e8c\u8003\u672a\u80fd\u5b9e\u73b0\u6709\u6548\u63d0\u5206\u3002</li> </ul> </li> <li>\u9009\u62e9\u9898\u5f88\u91cd\u8981\uff0c\u4e00\u9053\u4e09\u5206\u5343\u4e07\u522b\u9519\u3002\u591a\u9009\u9898\u8bf7\u4fdd\u5b88\u4e00\u4e9b\uff0c\u6fc0\u8fdb\u5f80\u5f80\u4e0d\u4f1a\u6709\u597d\u7ed3\u679c\uff0c\u9ad8\u8003\u540e\u6094\u5c31\u6765\u4e0d\u53ca\u4e86\u3002</li> <li>\u4e0d\u4f1a\u7684\u9898\u76ee\u53ca\u65f6\u6b62\u635f\uff0c\u5982\u673a\u68b0\u80fd\u4e2d\u65e0\u8c13\u7684\u5206\u7c7b\u8ba8\u8bba\uff0c\u7535\u78c1\u611f\u5e94\u4e2d\u65e0\u8c13\u7684\u70ed\u91cf\u8ba1\u7b97\u7b49\u7b49\uff0c\u53ef\u4ee5\u7b49\u505a\u5b8c\u6574\u5f20\u5377\u5b50\u540e\u518d\u6765\u505a\u3002</li> <li>\u4e0d\u8981\u6c89\u8ff7\u504f\uff0c\u602a\uff0c\u96be\uff0c\u73b0\u5728\u7684\u6a21\u62df\u5377\u5f88\u591a\u98ce\u683c\u504f\u79bb\u9ad8\u8003\uff0c\u8bf7\u57f9\u517b\u8fa8\u522b\u8d28\u91cf\u7684\u672c\u9886\u3002</li> </ul>"},{"location":"Summaries/High%20School/phy_fht/#_7","title":"\u5fc3\u6001\u65b9\u9762:","text":"<ul> <li>\u7269\u7406\u7684\u8003\u8bd5\u65f6\u95f4\u89c4\u5212\u5f88\u91cd\u8981\uff0c\u4e0d\u4f1a\u7684\u53ef\u4ee5\u5148\u8df3\u8fc7\u53bb\uff0c\u56de\u6765\u5728\u505a\uff0c\u5f53\u7136\u8df3\u591a\u4e86\u81ea\u7136\u4e5f\u8003\u4e0d\u597d\u4e86\u3002\u8981\u9759\u4e0b\u6765\u505a\u9898\u3002</li> <li>\u6ce8\u610f\u529b\u96c6\u4e2d\uff0c\u76f8\u4fe1\u81ea\u5df1\u7684\u5224\u65ad\uff0c\u653e\u677e\u505a\u9898\u3002</li> <li>\u5fc3\u6001\u5e26\u6765\u7684\u5f71\u54cd\u4e3b\u8981\u96c6\u4e2d\u5728\u9009\u62e9\u9898\u4e0a\uff0c\u6211\u9996\u8003\u9519\u4e864.5\u9053\u7684\u9009\u62e9\u9898\uff0c\u76f4\u63a595\u4e86\u3002</li> <li>\u5e73\u65f6\u8003\u8bd5\u6ca1\u6709\u5f88\u5927\u4ef7\u503c\uff0c\u8054\u8003\u7684\u552f\u4e00\u610f\u4e49\u5c31\u662f\u6a21\u62df\u9ad8\u8003\u6c1b\u56f4\u953b\u70bc\u5fc3\u6001\u3002\u6211\u9996\u8003\u524d\u7a33\u5b9a99+\uff0c\u6700\u540e\u4e0d\u8fd8\u662f\u8003\u4e86\u4e2a95\u3002</li> </ul>"},{"location":"Summaries/High%20School/phy_fht/#_8","title":"\u8d44\u6599\u65b9\u9762:","text":"<ul> <li>\u6d59\u8003\u7269\u7406\u4e0a\u6709\u4e00\u4e9b\u5377\u5b50\uff08\u4e0d\u5168\u9762\uff09</li> <li>\u6d59\u8003\u795e\u5899\u4f1a\u6709\u51e0\u4e4e\u6240\u6709\u8054\u8003\u7684\u5377\u5b50</li> <li>\u6559\u8f85\u4e66\u63a8\u8350:<ul> <li>\u9ad8\u8003\u4e94\u4e09\uff08\u7ea2\u7684\u7d2b\u7684\u90fd\u53ef\u4ee5\uff09</li> <li>\u9ad8\u8003\u5fc5\u5237\u9898</li> <li>\u5f53\u7136\uff0c\u5b66\u6821\u80af\u5b9a\u4f1a\u4e70\u7684\uff08\u6bd4\u5982\u6b65\u6b65\u9ad8\uff09\u3002\u5982\u679c\u4f60\u8fd8\u662f\u9ad8\u4e00\u9ad8\u4e8c\u53ef\u4ee5\u505a\u505a\u8f85\u5bfc\u4e66\uff0c\u5982\u679c\u662f\u9ad8\u4e09\u4e86\uff0c\u8fd8\u662f\u5efa\u8bae\u5377\u5b50+\u4e13\u9898\u7684\u6a21\u5f0f\u3002\uff08\u4e13\u9898\u6765\u81ea\u4e8e\u9ad8\u8003\u5fc5\u5237\u9898\u4e4b\u7c7b\u7684\u4e66\uff09\u8bf7\u52ff\u9677\u5165\uff0c\u6211\u505a\u9898\u591a\u5c31\u662f\u597d\u3002\u6211\u51e0\u4e4e\u505a\u5b8c\u4e8623\u5c4a+24\u5c4a\u6d59\u6c5f\u6240\u6709\u7684\u8054\u8003\u5377\uff0c\u611f\u89c9\u63d0\u5347\u5e76\u4e0d\u4f1a\u5f88\u5927\u3002</li> <li>\u7406\u6027\u5237\u9898\u6027\u4ef7\u6bd4\u66f4\u9ad8\u3002</li> </ul> </li> </ul>"},{"location":"Summaries/High%20School/phy_fht/#_9","title":"\u662f\u5426\u8981\u5b66\u4e60\u9ad8\u7ea7\u5185\u5bb9:","text":"<ul> <li>\u5982\u679c\u4e3a\u4e86\u9ad8\u8003\u53d6\u5f9797+\u7684\u6210\u7ee9\uff0c\u6211\u8ba4\u4e3a\u662f\u6ca1\u6709\u5fc5\u8981\u3002\u5982\u679c\u771f\u7684\u60f3\u5b66\uff0c\u63a8\u8350\u5b66\u4e60\u4e00\u4e0b\u5185\u5bb9:<ul> <li>\u7b80\u5355\u51fd\u6570\u7684\u79ef\u5206\uff08\u53c2\u770b\u540c\u6d4e\u7248\u9ad8\u6570\u4e0a\u518c\uff09</li> <li>\u5fae\u5206\u65b9\u7a0b\u7684\u89e3 \uff08\u53c2\u770b\u540c\u6d4e\u7248\u9ad8\u6570\u4e0b\u518c\uff09</li> <li>\u659c\u629b\u8fd0\u52a8</li> <li>\u7535\u78c1\u611f\u6027\u4e2d\u5355\u68d2\uff0c\u53cc\u68d2\u6a21\u578b\u7684\u5b9a\u91cf\u8ba1\u7b97\uff08\u6d89\u53ca\u5fae\u5206\u65b9\u7a0b\uff09</li> <li>\u4ea4\u6d41\u7535\u6709\u6548\u503c\u7684\u63a8\u5bfc</li> <li>\u6768\u6c0f\u5e72\u6d89\u7684\u5b9a\u91cf\u8ba1\u7b97</li> </ul> </li> <li>\u5982\u679c\u662f\u4e3a\u4e86\u5f3a\u57fa\u6216\u8005\u4e09\u4e00\uff0c\u6211\u529d\u4f60\u7701\u7701\u5427\uff0c\u9ad8\u8003\u641e\u5230\u4f4d\u6b211000\u4e86\u518d\u8bf4\u5427\u3002\u6027\u4ef7\u6bd4\u771f\u7684\u5f88\u4f4e\u5f88\u4f4e\uff0c\u522b\u4fe1\u673a\u6784\u7684\u9b3c\u8bdd\uff0c\u9ad8\u8003\u5206\u6570\u624d\u662f\u6700\u91cd\u8981\u7684\u3002</li> </ul>"},{"location":"Summaries/High%20School/phy_fht/#_10","title":"\u8001\u5e08\u4e0a\u8bfe\u662f\u5426\u8981\u542c:","text":"<ul> <li>\u56e0\u4eba\u800c\u5f02\uff0c\u4f60\u89c9\u5f97\u6709\u7528\u5c31\u542c\uff0c\u4f46\u5bf9\u4e8e\u6211\u6765\u8bf4\uff0c\u542c\u8bfe\u7684\u6548\u7387\u80af\u5b9a\u6bd4\u4e0d\u4e0a\u81ea\u5df1\u505a\u9898\u7684\u6548\u7387\u3002\u5e08\u751f\u4e92\u76f8\u8ba9\u6b65\u8fbe\u6210\u4e00\u81f4\u5c31\u597d\u3002</li> </ul>"},{"location":"Summaries/High%20School/phy_fht/#_11","title":"\u662f\u5426\u6709\u5fc5\u8981\u8bfe\u5916\u8f85\u5bfc:","text":"<ul> <li>\u56e0\u4eba\u800c\u5f02\uff0c\u8f85\u5bfc\u73ed\u80fd\u63d0\u4f9b\u7684\u65e0\u975e\u662f\u4e0a\u8ff0\u51e0\u79cd:\u77e5\u8bc6\u70b9\u8bb2\u89e3\uff0c\u9898\u76ee\uff0c\u89e3\u7b54\uff08\u53ef\u80fd\u8fd8\u6ca1\u6709\uff09\uff0c\u7ed9\u5bb6\u957f\u4e00\u4e2a\u5b89\u5fc3\u3002</li> <li>\u5f53\u7136\uff0c\u6211\u89c9\u5f97\u6548\u7387\u4e0d\u4f1a\u6bd4\u5b66\u6821\u9ad8\u591a\u5c11\u3002\u5982\u679c\u771f\u5b66\u4e0d\u4f1a\u4e86\uff0c\u90a3\u8fd8\u662f\u53bb\u5427\u3002</li> </ul> <p>\u53cd\u6b63\u8fd8\u662f\u5e0c\u671b\u5927\u5bb6\u53d1\u6325\u4e3b\u89c2\u80fd\u52a8\u6027\uff0c\u5b66\u6821\u53ea\u6709\u515c\u5e95\u4f5c\u7528\uff0c\u4e0d\u8fc7\u8c01\u77e5\u9053\u5e95\u5728\u54ea\u91cc</p>"},{"location":"Summaries/High%20School/tech_fht/","title":"\u6280\u672f\u7ecf\u9a8c\u5206\u4eab","text":""},{"location":"Summaries/High%20School/tech_fht/#_1","title":"\u6280\u672f\u7ecf\u9a8c\u5206\u4eab","text":"<p> \u7ea6 1324 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 7 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>\u80cc\u666f:2024\u5c4a\u9996\u800389-&gt;\u9ad8\u800398</p>"},{"location":"Summaries/High%20School/tech_fht/#_2","title":"\u5b66\u79d1\u672c\u8eab:","text":""},{"location":"Summaries/High%20School/tech_fht/#_3","title":"\u6280\u672f\u597d\u8d4b\u5206\u5417\uff1f","text":"<p>\u4e00\u822c\uff0c\u81f3\u5c11\u6bd4\u751f\u7269\u597d\u8d4b\u5206\uff08\u4e2a\u4eba\u611f\u89c9\uff09\u3002\uff08\u4e0d\u8fc7\u4e5f\u53ef\u4ee5\u9009\u5730\u7406\uff0c\u53ef\u80fd\u4f1a\u66f4\u597d\u8d4b\u5206\uff09 \u4f46\u5c31\u5e73\u65f6\u7684\u8054\u76df\u8003\u6765\u8bf4\uff0c</p> <ul> <li>\u5927\u6982\u9ad8\u4e00\u9ad8\u4e8c\u8d4b\u5206\u4f1a\u597d\u4e00\u4e9b\uff08\u6bd5\u7adf\u5f88\u591a\u4ebaprogramming\u90fd\u8fd8\u6ca1\u600e\u4e48\u641e\u61c2\uff09\u3002</li> <li>\u5230\u9ad8\u4e09\u5c31\u4e0d\u4e00\u5b9a\u4e86\uff0c\u4e3b\u8981\u770b\u8054\u76df\u53c2\u52a0\u7684\u5b66\u6821\u548c\u5377\u5b50\u672c\u8eab\u7684\u8d28\u91cf\u3002\u8bb0\u5f97\u9ad8\u8003\u524d\u7684\u4e94\u6821\u8054\u8003\uff0c\u5377\u5b50\u597d\u50cf\u633a\u7b80\u5355\u7684\uff0c\u4f46\u662f\u8d4b\u5206\u6781\u5176\u96be\u8d4b\u3002</li> <li>\u81f3\u4e8e\u9ad8\u8003\uff0c\u8d4b\u5206\u8fd8\u884c\uff0c\u4f46\u662f\u9ad8\u5206\u5f88\u96be\uff08\u7279\u522b\u630798+\uff09\uff0c\u4f30\u8ba1\u662f\u9547\u4e2d\u6e29\u4e00\u5b66\u519b\u676d\u4e8c\u628a\u5206\u5361\u4f4f\u4e86\u3002</li> </ul>"},{"location":"Summaries/High%20School/tech_fht/#_4","title":"\u5b66\u79d1\u96be\u5ea6\u5927\u5417\uff1f","text":"<ul> <li>\u6211\u662f\u5728\u9009\u6280\u672f\u4e4b\u524d\u5c31\u4f1aC++\uff0cPython\uff0c\u4e2a\u4eba\u611f\u89c9\u662f\u9ad8\u4e2d\u77e5\u8bc6\u70b9\u4e0d\u96be\uff0c\u5e73\u65f6\u9898\u76ee\u4e5f\u4e0d\u662f\u5f88\u96be\u3002\u4f46\u662f\u9ad8\u8003\u5c31\u4e0d\u4e00\u5b9a\u4e86\uff0c\u7531\u4e8e\u6280\u672f\u8fd8\u6ca1\u8003\u51e0\u5e74\uff08\u5957\u8def\u8fd8\u6ca1\u88ab\u7a77\u5c3d\uff09\uff0c\u6240\u4ee5\u7a0d\u5fae\u4e00\u53d8\u5316\u5c31\u5bb9\u6613\u6b7b\u4e00\u5927\u7247\u3002</li> <li>\u4f46\u662f\u7f16\u7a0b\u5bf9\u521a\u5165\u95e8\u7684\u65b0\u624b\u800c\u8a00\uff0c\u96be\u5ea6\u8fd8\u662f\u4e0d\u5c0f\u7684\u3002\u7279\u522b\u662f\uff0c\u79bb\u8c31\u7684\u5e94\u8bd5\u6559\u80b2\u65b9\u5f0f&amp;\u96be\u8bc4\u7684\u81ea\u5b66\u80fd\u529b\uff0c\u5f88\u96be\u8bf4\u9760\u5199(write)\u4ee3\u7801\u53ef\u4ee5\u5f88\u597d\u7684\u638c\u63e1\u7b97\u6cd5/\u6570\u636e\u7ed3\u6784\u3002\u6781\u5176\u5bb9\u6613\u9677\u5165\u80cc\u4ee3\u7801\u7684\u6b7b\u5c40\u3002</li> <li>\u4e3b\u8981\u6765\u8bb2\u5c31\u662f\uff0c\u6ca1\u6709\u7269\u7406\u5316\u5b66\u96be\u3002</li> <li>\u6027\u4ef7\u6bd4\u633a\u9ad8\uff08\u5bf9\u6211\u6765\u8bf4\uff0c\u9ad8\u4e8c\u51e0\u4e4e\u6ca1\u6709\u82b1\u65f6\u95f4\uff0c\u9ad8\u4e09\u4e5f\u53ea\u662f\u505a\u505a\u8054\u8003\u5377\uff0c\u4f5c\u4e1a\u57fa\u672c\u6ca1\u505a\u8fc7\u3002\u82b1\u7684\u65f6\u95f4\u4f30\u8ba1\u662f\u82b1\u5728\u5316\u5b66\u4e0a\u7684\u96f6\u5934: (\uff09</li> </ul>"},{"location":"Summaries/High%20School/tech_fht/#_5","title":"\u90a3\u8981\u4e0d\u8981\u9009\u6280\u672f\u634f\uff1f","text":"<ul> <li>\u5982\u679c\u662f\u4ee5\u540e\u5b66\u8ba1\u7b97\u673a\u76f8\u5173\u7684\u8fd8\u662f\u5efa\u8bae\u9009\uff0c\u8fd9\u6837\u7b49\u5927\u5b66\u4e86\u4f1a\u6709\u5f88\u5927\u4f18\u52bf\u3002</li> <li>\u4f46\u5982\u679c\u4e00\u70b9programming\u90fd\u641e\u4e0d\u61c2\uff0c\u90a3\u8fd8\u662f\u7b97\u4e86\u3002</li> <li>\u5982\u679c\u6ca1\u6709\u9009\u7269\u7406/\u7269\u7406\u4e0d\u597d\uff0c\u4e5f\u614e\u91cd\u9009\u6280\u672f\u5427\u3002\uff08\u4e0d\u7136\u82b1\u5728\u7535\u63a7\u4e0a\u7684\u65f6\u95f4\u4f1a\u5f88\u6ca1\u6709\u6027\u4ef7\u6bd4\uff09</li> </ul>"},{"location":"Summaries/High%20School/tech_fht/#_6","title":"\u5b66\u4e60\u65b9\u6cd5:","text":"<p>\u4ec5\u5c31\u9ad8\u4e09\u800c\u8a00\uff08\u9ad8\u4e8c\u6ca1\u5b66\uff09</p>"},{"location":"Summaries/High%20School/tech_fht/#_7","title":"\u5148\u8981\u786e\u4fdd\u57fa\u7840\u7684\u77e5\u8bc6\u70b9\u90fd\u4f1a:","text":"<ol> <li>\u5148\u628a\u6559\u8f85\u770b\u4e00\u904d\uff08\u5b66\u6821\u80af\u5b9a\u4f1a\u4e70\u7684\u4e00\u4e9b\u4e71\u4e03\u516b\u7cdf\u7684\uff0c\u53cd\u6b63\u5e02\u9762\u4e0a\u4e5f\u6ca1\u4ec0\u4e48\u5f88\u597d\u7684\u6559\u8f85\uff09</li> <li>\u518d\u628a\u4e66\u770b\u4e00\u904d\uff08\u5f88\u5c0f\u7684\u70b9\u90fd\u8981\u77e5\u9053\uff09</li> <li>\u81ea\u5df1\u5c1d\u8bd5\u628a\u77e5\u8bc6\u70b9\u90fd\u7406\u4e00\u904d\uff08\u9009\u505a\uff09</li> <li>\u6ce8\u610f:\u6280\u672f\u672c\u8eab\u7684\u77e5\u8bc6\u4f53\u7cfb\u5e76\u4e0d\u50cf\u7269\u7406\u5316\u5b66\u90a3\u6837\u7d27\u5bc6\uff0c\u6240\u4ee5\u70b9\u90fd\u662f\u633a\u5206\u6563\u7684\u3002\u4e00\u5b9a\u5de9\u56fa\u597d\u57fa\u7840\u3002 \uff08\u7528\u65f6\u5927\u6982:1\u4e2a\u661f\u671f\uff1f\u4e00\u59293h\u3002\u56e0\u4eba\u800c\u5f02\uff09</li> </ol>"},{"location":"Summaries/High%20School/tech_fht/#_8","title":"\u7136\u540e\u5c31\u662f\u505a\u9898:","text":"<ul> <li>\u5148\u505a\u70b9\u5377\u5b50\uff0c\u770b\u770b\u81ea\u5df1\u6f0f\u6d1e\u5728\u54ea\uff0810\u5f20\u5dee\u4e0d\u591a\u4e86\uff0c\u4e00\u5b9a\u8981\u77ed\u65f6\u95f4\u5185\u505a\u5b8c\uff09:<ul> <li>\u5efa\u8bae\u8054\u8003\u5377\u90fd\u505a\u505a\uff0c\u624d\u77e5\u9053\u4ec0\u4e48\u662f\u597d\u7684\u5377\u5b50\u3002\uff08\u8001\u5e08\u80af\u5b9a\u4f1a\u53d1\u7684\uff09</li> </ul> </li> <li>\u7136\u540e\u505a\u70b9\u4e13\u9898\uff0c\u8d44\u6599\u6765\u6e90\uff08\u6d59\u8003\u4ea4\u6d41\uff09<ul> <li>\u4e3b\u8981\u662f\u8981\u641e\u660e\u767d\u77e5\u8bc6\u70b9\uff0c\u6bd4\u5982<ul> <li>\u94fe\u8868\uff08\u57fa\u7840\u64cd\u4f5c\uff0c\u5feb\u6162\u6307\u9488\uff09\uff0c\u4e8c\u5206\uff08\u4e8c\u53c9\u641c\u7d22\u6811\uff09</li> <li>\u5e38\u89c1\u7684pandas\u64cd\u4f5c</li> <li>\u7f51\u8def\u76f8\u5173\uff08\u80cc\u4e66\uff09</li> <li>\u7535\u63a7\u7684\u57fa\u672c\u6a21\u578b\uff08\u9707\u8361\u7535\u8def\u7684\u51e0\u79cd\u5199\u6cd5\uff0c\u955c\u50cf\u7535\u6d41\u6e90\uff09</li> <li>\u7cfb\u7edf&amp;\u63a7\u5236\uff08\u6bcf\u4e2a\u90e8\u5206\u90fd\u8981\u5f88\u786e\u5b9a\uff0c\u8001\u5e08\u8bb2\u4e0d\u6e05\u695a\uff0c\u81ea\u5df1\u4e00\u5b9a\u8981\u53bb\u641e\u61c2\uff0c\u4e0d\u7136\u5c31\u662f\u505a\u4e00\u9053\u9519\u4e00\u9053\uff09</li> <li>\u5c3a\u5bf8\u6807\u6ce8\uff08\u9519\u51e0\u56de\u5c31\u597d\u4e86\uff09</li> <li>\u4e09\u89c6\u56fe\uff08\u5b58\u7591\uff0c\u8fd9\u9898\u4e00\u76f4\u5728\u53d8\uff09</li> </ul> </li> </ul> </li> <li>\u57fa\u672c\u5c31\u5dee\u4e0d\u591a\u4e86\uff08\u540e\u9762\u518d\u82b1\u65f6\u95f4\u6027\u4ef7\u6bd4\u5c31\u4e0d\u9ad8\u4e86\uff09\uff0c\u5982\u679c\u8fd8\u60f3\u7ee7\u7eed\uff0c\u90a3\u5c31\u81ea\u5df1\u6574\u4e2a\u672c\u5b50\uff0c\u628a\u9519\u9898\u641e\u4e0a\u53bb\uff0c\u6bcf\u6b21\u8003\u8bd5\u524d\u770b\u770b\u3002\uff08\u5b9e\u9645\u4f5c\u7528\u5c31\u662f\u8ba9\u4f60\u522b\u4e00\u505a\u5b8c\u5c31\u628a\u9898\u6254\u4e86\uff0c\u4e5f\u4e0d\u641e\u61c2\uff0c\u90a3\u6837\u7b49\u4e8e\u6ca1\u505a\uff09\u4f46\u9519\u9898\u672c\u5176\u5b9e\u6548\u7387\u5f88\u4f4e\u3002\uff08formalism\uff09</li> </ul>"},{"location":"Summaries/High%20School/tech_fht/#_9","title":"\u505a\u9898\u65f6\u95f4\u65b9\u9762:","text":"<ul> <li>\u6211\u662f\u57fa\u672c\u5148\u505a\u4fe1\u606f\uff0c\u5728\u505a\u901a\u7528\u7684<ul> <li>\u4fe1\u606f13\u9898\u548c\u5927\u9898\u6700\u540e\u4e00\u9898\u4e0d\u4f1a\u7684\u5148\u7a7a\u7740\uff08\u586b\u4e2a\u4e0d\u786e\u5b9a\u7684\uff09\uff0c\u7136\u540e\u53bb\u505a\u901a\u7528\u3002\u5927\u6982\u524d\u976230min\u80fd\u641e\u5b9a</li> <li>\u901a\u7528\u8349\u56fe\u5148\u7a7a\u7740\uff0c\u628a\u7535\u63a7\u5927\u9898\u505a\u5b8c\uff0c\u7136\u540e\u56de\u53bb\u753b\u8349\u56fe\u3002\uff08\u5927\u698240min\uff09</li> <li>\u753b\u5b8c\u8349\u56fe\u518d\u56de\u53bb\u505a\u4fe1\u606f\u4e0d\u4f1a\u7684\u3002</li> <li>\u6700\u540e\u53ef\u4ee5\u6446\u70c2\u4e86\uff0c\u8981\u68c0\u67e5\u4e5f\u53ef\u4ee5\uff08\u53cd\u6b63\u68c0\u67e5\u4e0d\u51fa\u6765\uff09</li> </ul> </li> <li>\u505a\u9898\u600e\u4e48\u5feb\u4e00\u70b9\uff08\u9898\u90fd\u505a\u4e0d\u5b8c\uff0c\u8c08\u4ec0\u4e48\u90fd\u662f\u767d\u642d\uff09:<ul> <li>\u83dc\u5c31\u591a\u7ec3\uff08\u4e0a\u8bfe40min\uff0c\u505a\u5b8c\u9664\uff08\u7535\u63a7/\u586b\u7a0b\u4e0d\u4f1a\u7684&amp;\u753b\u56fe\uff09\u7684\u9898\uff09</li> <li>\u6216\u8005\u665a\u81ea\u4e601h\uff0c\u505a\u5b8c\u5168\u90e8\uff08\u9664\u753b\u56fe\uff09+\u5bf9\u7b54\u6848</li> </ul> </li> <li>\u753b\u56fe\u5c31\u628a\u8054\u8003\u9898\u90fd\u653e\u4e00\u8d77\uff0c\u4e00\u6b21\u753b\u4e2a10\u5f20\u5de6\u53f3\u5c31\u5dee\u4e0d\u591a\u4e86\uff0c\u6ca1\u4ec0\u4e48\u6a21\u578b\u7684\uff08</li> </ul>"},{"location":"Summaries/High%20School/tech_fht/#_10","title":"\u5fc3\u6001\u65b9\u9762:","text":"<ul> <li>\u53cd\u6b63\u9ad8\u8003\u548c\u5e73\u65f6\u8fd8\u662f\u5f88\u4e0d\u4e00\u6837\u7684\uff0c\u5efa\u8bae\u5e73\u65f6\u5927\u8003\u5f53\u9ad8\u8003\u8003\u3002</li> <li>\u7136\u540e\u5c31\u662f\u4e00\u6b21\u8003\u5dee\u6ca1\u5565\u5173\u7cfb\uff0c\u65f6\u95f4\u82b1\u5728\u8be5\u82b1\u7684\u5730\u65b9\u5c31\u597d\u4e86\uff0c\u8981\u5bf9\u81ea\u5df1\u7684\u5b66\u4e60\u6709\u638c\u63a7\u529b\u3002</li> <li>\u8001\u5e08\u6559\u7684\u4e0d\u597d\u8981\u5b66\u4f1a\u81ea\u5df1\u5b66</li> </ul>"},{"location":"Summaries/High%20School/tech_fht/#_11","title":"\u8d44\u6599\u65b9\u9762:","text":"<ul> <li>\u6d59\u8003\u4ea4\u6d41\u89e3\u51b3\u6240\u6709\uff08</li> <li>\u8f85\u5bfc\u4e66\u90fd\u5dee\u4e0d\u591a\uff0c\u770b\u591a\u4e86\u6d6a\u8d39\u65f6\u95f4</li> </ul>"},{"location":"Summaries/High%20School/tech_fht/#_12","title":"\u5176\u4ed6:","text":"<ul> <li>\u53ef\u4ee5\u548c\u540c\u5b66\u4e00\u8d77\u5b66\uff08\u4e0d\u662f\u4e00\u8d77\u6446\u70c2\u54e6\uff09</li> <li>\u771f\u5b66\u4e0d\u4f1a\u4e86\u8d76\u7d27\u6362\u79d1\u5427</li> <li>\u90fd\u5b66\u6280\u672f\u4e86\uff0c\u5b66\u5b66\u600e\u4e48\u641c\u96c6\u8d44\u6599\u5427</li> <li>\u6709\u7528\u7684\u4f5c\u4e1a\u5c31\u505a\uff0c\u6ca1\u7528\u7684\u5c31\u7b97\u4e86\uff08\u614e\u91cd\uff09</li> <li>\u63d0\u5347\u6210\u7ee9\u7684debuff\u8fd8\u662f\u4e0d\u5c11\u7684\uff0c\u522b\u6028\u5929\u5c24\u4eba\u7684\uff08\u6b22\u8fce\u52a0\u5b66\u957f\u5b66\u59d0\u6765\u54a8\u8be2</li> <li>\u9996\u8003\u8003\u5dee\u4e86\u600e\u4e48\u529e:<ul> <li>\u8fd8\u80fd\u600e\u4e48\u529e\uff0c\u7ee7\u7eed\u5b66\u5457\u3002</li> </ul> </li> <li>\u5b66\u4e0d\u61c2\u4e0a\u8bfe\u5c31\u597d\u597d\u542c\uff0c\u522b\u73a9\u6e38\u620f\uff08\u4e0d\u7136\u600e\u4e48\u5b66\uff09</li> </ul> <p>\u6700\u540e:\u5e0c\u671b\u5927\u5bb6\u90fd\u80fd\u8003\u597d :\uff09</p>"},{"location":"Summaries/Semesters/202409-10/","title":"2024 \u5e74 9 \u6708 10 \u6708\u603b\u7ed3","text":""},{"location":"Summaries/Semesters/202409-10/#2024-9-10","title":"2024 \u5e74 9 \u6708 10 \u6708\u603b\u7ed3","text":"<p> \u7ea6 388 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 2 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>9 \u6708 15 \u65e5 - 10 \u6708 15 \u65e5</p> <ul> <li>\u8ba1\u7b97\u673a<ul> <li>\u52a0\u5165\u4e86 RoboMaster \u89c6\u89c9\u90e8<ul> <li>\u4f20\u7edf\u8ba1\u7b97\u673a\u89c6\u89c9<ul> <li>opencv</li> <li>\u65cb\u8f6c\u7684\u8868\u793a</li> <li>\u590d\u4e60\u4e86\u519b\u8bad\u65f6\u770b\u7684 slam14 \u8bb2</li> </ul> </li> <li>Kalman Filter</li> <li>ROS2<ul> <li>\u4e3b\u8981\u901a\u8fc7\u5b98\u65b9\u6587\u6863\u548c\u52a8\u624b\u5b66ROS2 \u5b66\u4e86\u4e00\u4e0b</li> </ul> </li> </ul> </li> <li>\u901a\u8fc7 3b1b \u7684\u7cfb\u5217\u89c6\u9891\u4e86\u89e3\u4e86\u795e\u7ecf\u7f51\u7edc</li> <li>pytorch<ul> <li>\u901a\u8fc7\u5b98\u7f51\u7684\u6559\u7a0b\u901f\u6210\u4e86\u4e00\u4e0b</li> </ul> </li> <li>Dive into Deep Learning<ul> <li>\u7ebf\u6027\u795e\u7ecf\u7f51\u7edc<ul> <li>softmax \u56de\u5f52</li> </ul> </li> <li>\u591a\u5c42\u611f\u77e5\u673a<ul> <li>\u6b20\u62df\u5408\u4e0e\u8fc7\u62df\u5408<ul> <li>\u6743\u91cd\u8870\u51cf</li> <li>\u6682\u9000\u6cd5</li> </ul> </li> <li>\u6570\u503c\u7a33\u5b9a\u6027<ul> <li>\u68af\u5ea6\u6d88\u5931</li> <li>\u68af\u5ea6\u7206\u7167</li> </ul> </li> <li>\u504f\u79fb\u5206\u5e03</li> </ul> </li> <li>\u6df1\u5ea6\u5b66\u4e60\u7684\u642d\u5efa</li> <li>\u5377\u79ef\u795e\u7ecf\u7f51\u7edc</li> <li>\u73b0\u4ee3\u5377\u79ef\u795e\u7ecf\u7f51\u7edc</li> </ul> </li> <li>CMU 15-213<ul> <li>\u5b8c\u6210\u4e86 datalab, bomblab, attacklab</li> </ul> </li> <li>Matlab \u57fa\u672c\u8bed\u6cd5<ul> <li>\u73a9\u4e86\u73a9\u76f8\u673a\u6807\u5b9a</li> </ul> </li> <li>Tools<ul> <li>\u4f5c\u4e1a\u8981\u6c42\uff0c\u6253\u4e86 20 \u9875 \\(\\displaystyle \\LaTeX\\) \u6587\u6863\uff0c\u6839\u636e elegentbook \u4fee\u6539\u4e86\u81ea\u5df1\u7684\u6a21\u677f,\u5b66\u4e60\u4e86 Tikz</li> <li>\u5b66\u4e86 Typst \u7684\u57fa\u672c\u8bed\u6cd5\uff0c\u4f46\u662f\u611f\u89c9\u81ea\u5df1\u76ee\u524d\u61d2\u5f97\u6362</li> <li>\u91cd\u88c5\u4e86\u7535\u8111<ul> <li>\u53f0\u5f0f<ul> <li>Ubuntu 22.04\uff08\u4e3b\u529b\u673a\uff09 + win11</li> </ul> </li> <li>\u7b14\u8bb0\u672c<ul> <li>Ubuntu 24.04 \uff08\u4e0d\u5c0f\u5fc3\u5347\u7ea7\u4e86\uff09+ win11</li> </ul> </li> </ul> </li> <li>\u719f\u7ec3\u4e86 claude + kimi \u7684\u4f7f\u7528<ul> <li>\u7533\u8bf7\u8fc7\u4e86 GitHub edcation\uff0c\u4e8e\u662f\u6709\u4e86 copilot \u7528\u3002</li> </ul> </li> <li>\u88c5\u4fee\u4e86\u4e00\u4e0b blog<ul> <li>\u770b\u4e86\u4e00\u904d Mkdocs \u548c Material for Mkdocs \u7684\u6587\u6863</li> </ul> </li> <li>\u914d\u7f6e\u4e86\u5de5\u5b66\u6905\uff0c\u597d\u7528\uff01</li> <li>\u5b66\u4e86 slidev<ul> <li>\u9644\u5e26\u53bb\u5b66\u4e86\u4e00\u4e0b mermaid \uff08\u611f\u89c9\u4e0d\u662f\u5f88\u597d\u7528\uff09</li> </ul> </li> </ul> </li> <li>\u5199\u4e86\u4e00\u4e2a\u5728 mkdocs \u4e0a\u90e8\u7f72 obsidian \u65f6\u5904\u7406\u94fe\u63a5\u7684\u5c0f\u63d2\u4ef6\uff08\u672a\u5b8c\u5168\u53d1\u5e03\uff09  </li> </ul> </li> <li>\u603b\u7ed3<ul> <li>\u603b\u7684\u611f\u53d7\u4e0b\u6765\uff0c\u81ea\u5df1\u4ee5\u540e\u8fd8\u662f\u6bd4\u8f83\u503e\u5411\u4e8e\u5b66 AI \u800c\u4e0d\u662f system \uff1f\u53c8\u60f3\u8981\u51fa\u56fd\u4f53\u9a8c\u4e00\u4e0b\uff08\u8bfb\u7855\u58eb\uff0c\u6216\u8005\u76f4\u535a\uff1f\uff09</li> </ul> </li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/","title":"2024 \u5e74 9 \u6708\u4efd\u81f3 12 \u6708\u4efd\u5b66\u671f\u603b\u7ed3\uff08\u5927\u4e00\uff09","text":""},{"location":"Summaries/Semesters/2024_1_1/#2024-9-12","title":"2024 \u5e74 9 \u6708\u4efd\u81f3 12 \u6708\u4efd\u5b66\u671f\u603b\u7ed3\uff08\u5927\u4e00\uff09","text":"<p> \u7ea6 1745 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 9 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"Summaries/Semesters/2024_1_1/#_1","title":"\u5e72\u4e86\u4ec0\u4e48","text":""},{"location":"Summaries/Semesters/2024_1_1/#37","title":"37 \u5468","text":"<ul> <li>\u519b\u8bad</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#38","title":"38 \u5468","text":"<ul> <li>\u51c6\u5907 RM \u62db\u65b0<ul> <li>\u5b66\u4e60 SLAM \u5341\u56db\u8bb2\uff0cKalman \u6ee4\u6ce2\uff0c\u4f20\u7edf\u8ba1\u7b97\u673a\u89c6\u89c9\u3002</li> <li>\u5b66\u4e60\u63a7\u5236\u7b97\u6cd5\uff0c\u770b\u4e86 DR_CAN \u7684\u89c6\u9891</li> </ul> </li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#39","title":"39 \u5468","text":"<ul> <li>\u7528 Mkdocs \u6210\u529f\u642d\u5efa\u4e86 Blog\u3002</li> <li>\u9762\u8bd5\u4e86 RM\uff0c\u6210\u529f\u52a0\u5165\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#40","title":"40 \u5468","text":"<ul> <li>\u89c6\u89c9\u90e8\u57f9\u8bad\uff0c\u5b66\u4e86\u4e00\u4e9b\u786c\u4ef6\u77e5\u8bc6\uff0c\u590d\u4e60 Kalman \u6ee4\u6ce2\uff0copencv\uff0c\u5b66\u4e60\u4e86 ROS2\uff08\u867d\u7136\u73b0\u5728\u5fd8\u7684\u5dee\u4e0d\u591a\u4e86\uff09\u3002</li> <li>\u56fd\u5e86\u4e00\u76f4\u6253\u6e38\u620f\uff0c\u901a\u5bb5\u3002</li> <li>\u770b\u4e86\u4e00\u672c\u513f\u7ae5\u6587\u5b66\u7684\u4e66 Holes\uff0c\u505a presentation\uff0c\u7b2c\u4e00\u6b21\u4f7f\u7528 slidev\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#41","title":"41 \u5468","text":"<ul> <li>\u5b66\u4e60\u4e86<ul> <li>Typst\uff0c\u4f46\u662f\u81f3\u4eca\u6ca1\u6709\u600e\u4e48\u7528\u8fc7\u3002</li> <li>Solidworks\uff0c\u81f3\u4eca\u4e0d\u80fd\u719f\u7ec3\u4f7f\u7528\u3002</li> </ul> </li> <li>\u505a\u4e86 CSAPP bomblab\uff0cattacklab\u3002</li> <li>\u5199\u4e86\u4e2a mkdocs-obsidin \u7684\u63d2\u4ef6\uff0c\u540e\u6765\u70c2\u5c3e\u4e86\u3002</li> <li>\u5f00\u59cb\u5b66\u4e60 Dive into Deep Learning\uff0c\u5b66\u4e60 Pytorch\u3002</li> <li>\u5b89\u88c5\u4e86 leetcode \u63d2\u4ef6\uff0c\u8c61\u5f81\u6027\u7684\u505a\u4e86\u51e0\u9053\u9898\u76ee\u3002</li> <li>\u7ffb\u770b\u4e86\u4e00\u904d RM \u5723\u7ecf\u3002\u611f\u89c9\u5199\u7684\u8303\u56f4\u5e7f\uff0c\u4f46\u662f\u4e0d\u9002\u5408\u7b2c\u4e00\u6b21\u5b66\u4e60\u3002</li> <li>\u8d2d\u4e70\u4e86<ul> <li>\u4eba\u4f53\u5de5\u5b66\u6905\uff0c\u597d\u7528\uff01</li> <li>\u53f0\u5f0f\u7535\u8111\uff0c\u7b2c\u4e00\u6b21\u81ea\u5df1\u88c5\u673a\u3002</li> </ul> </li> <li>\u4e86\u89e3\u4e86\u4e00\u4e0b hpc\uff0c\u5f53\u65f6\u653e\u5f03\u4e86</li> <li>\u5b8c\u5584 obsidian\uff0c\u5728\u6c34\u6e90\u53d1\u5e16\uff0c\u6301\u7eed\u66f4\u65b0\u65e5\u8bb0\u697c\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#42","title":"42 \u5468","text":"<ul> <li>\u5fd9\u5165\u515a\u79ef\u6781\u5206\u5b50\u57f9\u8bad\uff0c\u5230\u5904\u627e\u5fd7\u613f\u8005\uff0c\u5468\u672b\u4e00\u76f4\u5728\u57f9\u8bad + RM \u57f9\u8bad\u3002</li> <li>\u770b\u4e86\u4e0d\u5c11\u5e16\u5b50\uff0c\u7126\u8651\uff0c\u4e0d\u77e5\u9053\u672a\u6765\u7684\u65b9\u5411\uff08\u5b9e\u9645\u4e0a\u5230\u73b0\u5728\u4e5f\u662f\u8fd9\u6837\uff09\uff0c\u72b9\u8c6b\u8f6c\u4e13\u4e1a\u3002</li> <li>\u88c5\u53cc\u7cfb\u7edf\uff08\u8fd9\u4e2a\u5b66\u671f\u5927\u6982\u88c5\u4e86 4 \u6b21\uff09<ul> <li>\u6363\u9f13 Linux\uff0c\u7f8e\u5316\u3002</li> </ul> </li> <li>\u5b66\u4e86\u4e00\u904d Matlab\u3002</li> <li>\u5f00\u59cb\u6446\u70c2\u4e86\uff0c\u4f5c\u606f\u98a0\u5012\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#43","title":"43 \u5468","text":"<ul> <li>101 \u671f\u4e2d\u8003\uff0cMatlab \u6210\u529f\u6ee1\u5206\u3002</li> <li>\u5199 critical summary\uff0c\u5b66\u672f\u5199\u4f5c\u7684\u7b2c\u4e8c\u6b21\u4f5c\u4e1a\u3002</li> <li>\u770b\u4e86 d2l \u5230 Transformer\u3002<ul> <li>\u5199 EECS498-007 \u5230\u524d\u4e09\u4e2a Assignments \uff08CNN\uff09\uff0c\u4f46\u662f\u540e\u7eed\u70c2\u5c3e\u4e86\u3002</li> </ul> </li> <li>\u81f3\u6b64\u6bd4\u8f83\u719f\u7ec3\u4f7f\u7528\u4e86 AI \u5de5\u5177\u3002</li> <li>\u7ee7\u7eed\u5fd9\u6d3b\u5165\u515a\u79ef\u6781\u5206\u5b50\u57f9\u8bad\uff0c\u6ca1\u6709\u4e86\u5468\u672b\uff0c\u53bb\u5b9e\u8df5\u6d3b\u52a8\uff0c\u5199\u601d\u60f3\u62a5\u544a\uff0c\u8003\u8bd5\u3002</li> <li>\u590d\u4e60\u671f\u4e2d\u8003\u7684\u5316\u5b66\u548c\u6570\u5b66\u3002</li> <li>\u53bb\u79d1\u534f\u9762\u8bd5\uff0c\u6ca1\u8fc7\u3002</li> <li>\u5728\u5b66\u957f\u7684\u4ecb\u7ecd\u4e0b\u53bb\u7ed9\u5bfc\u5e08\u53d1\u4e86\u90ae\u7bb1\uff0c\u5728 44 \u5468\u7684\u65f6\u5019\u7ebf\u4e0b\u89c1\u4e86\u5bfc\u5e08\uff0c\u6210\u529f\u52a0\u5165\u5b9e\u9a8c\u5ba4\u5f00\u59cb\u5b66\u4e60\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#44","title":"44 \u5468","text":"<ul> <li>\u51c6\u5907\u7269\u7406\u5efa\u6a21\u6bd4\u8d5b\uff0c\u770b\u4e86 2022\uff0c2023 \u7684\u6240\u6709\u91d1\u5956\u8bba\u6587\uff0c\u5438\u6536\u7ecf\u9a8c\u3002<ul> <li>\u5468\u672b\u6bd4\u8d5b\uff0c\u5b66\u4e60\u4e86\u53ef\u89c6\u5316\u7b97\u6cd5\uff0c\u5982\u4f55\u753b\u56fe\uff0c\u7ee7\u7eed\u719f\u7ec3\u4e86 \\(\\displaystyle \\LaTeX\\) \u4f7f\u7528\u3002</li> </ul> </li> <li>\u590d\u4e60\u671f\u4e2d\u8003\u7684\u5316\u5b66\u548c\u6570\u5b66\u3002</li> <li>\u5b66\u4e60 CS231n\uff0c\u5b8c\u6210\u4e86 Assignment1\u3002</li> <li>\u7ee7\u7eed\u6446\u70c2\u4e86\uff0c\u770b\u8d77\u6765\u662f\u524d\u4e24\u5468\u592a\u7d2f\u4e86\uff0c\u4e00\u76f4\u6ca1\u6709\u5468\u672b\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#45","title":"45 \u5468","text":"<ul> <li>\u671f\u4e2d\u8003\u8bd5\u4e86\u5316\u5b66\u548c\u6570\u5b66\uff0c\u88ab\u5377\u7206\u4e86\u3002</li> <li>RM \u57f9\u8bad\u6b63\u5f0f\u5b8c\u6bd5\uff0c\u5206\u5165\u5de5\u7a0b\u89c6\u89c9\u9879\u76ee\u7ec4\uff0c\u5f00\u59cb\u8c03\u7814 6Dpose \u65b9\u6848\u3002</li> <li>\u5199\u4e86\u4e00\u4e2a\u6570\u5b57\u8bc6\u522b\u7684\u5c0f\u4efb\u52a1\u3002</li> <li>\u5468\u672b\u4f53\u6d4b\uff0c\u8fd0\u52a8\u5c11\u4e86\u3002</li> <li>\u71ac\u591c\u6821\u5185\u8d5b\u9020\u8f66\uff0c\u88ab\u961f\u53cb\u6446\u4e86\u3002\u5b66\u4e86\u7535\u63a7\uff0c\u5199\u4e86\u9ea6\u8f6e\u89e3\u7b97\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#46","title":"46 \u5468","text":"<ul> <li>\u7ee7\u7eed\u6821\u5185\u8d5b\u9020\u8f66\uff0c\u961f\u53cb\u7ee7\u7eed\u5f00\u6446\uff0c\u505a\u4e86\u673a\u68b0\u7684\u90e8\u5206\u3002</li> <li>\u5b66\u4e60\u4e86 docker\uff0c\u914d\u597d\u4e86\u73af\u5883\uff08\u540e\u7eed\u6ca1\u7528\u4e0a\uff09\u3002</li> <li>\u5b66\u4e86 realsense \u5236\u4f5c\u70b9\u4e91\uff0c\u6548\u679c\u4e0d\u597d\u3002</li> <li>\u5b66\u4e86\u4e00\u4e0b Hugo\uff0c\u4e0d\u662f\u5f88\u597d\u770b\u3002</li> <li>\u5199\u4e86 CS231n Assignment2\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#47","title":"47 \u5468","text":"<ul> <li>\u7ed3\u675f\u4e86\u6821\u5185\u8d5b\u3002</li> <li>\u5b66\u4e86 SSH\uff0creveal-md\uff0cBeamer \u7b49\u3002</li> <li>\u6574\u7406\u7b14\u8bb0\uff0c\u53d1\u5e03\u4e86\u6587\u7ae0\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#48","title":"48 \u5468","text":"<ul> <li>\u5199\u4e86 CS231n Assignment3\u3002</li> <li>\u4e00\u4eba\u505a\u5b8c\u4e86 101 project\uff0c\u5b66\u4e86\u5982\u4f55 release \u7b49\u3002</li> <li>\u5199\u4e86\u4e00\u4e2a\u81ea\u52a8\u90e8\u7f72 slides \u7684\u5de5\u5177\u3002</li> <li>\u6210\u529f\u8bad\u7ec3\u4e86 FFB6D\uff0c\u8dd1\u901a\u4e86\u5b98\u65b9\u6570\u636e\u96c6\u3002</li> <li>101 \u7b2c\u4e8c\u6b21\u671f\u4e2d\u8003\uff0c\u590d\u4e60\u4e86 C \u8bed\u8a00\u3002</li> <li>\u5199\u8fd1\u4ee3\u53f2\u8bfb\u4e66\u62a5\u544a\uff0c\u5199\u5b66\u672f\u5199\u4f5c\u7684\u8bba\u6587\uff0c\u8fdb\u4e00\u6b65\u719f\u7ec3 AI \u7684\u4f7f\u7528\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#49","title":"49 \u5468","text":"<ul> <li>\u4e00\u6574\u5468\u90fd\u5728\u5199\u8bba\u6587\uff0c\u5199\u5b8c\u4e86\u82f1\u8bed\u8bba\u6587\u7684\u7b2c\u4e00\u7248\uff0c\u7136\u540e\u88ab\u63a8\u7ffb\u3002</li> <li>\u5b66\u4e86 Go \u7684\u57fa\u672c\u8bed\u6cd5\uff0c\u5b66\u4e86\u70b9 Web \u6846\u67b6\u3002</li> <li>\u914d\u7f6e\u597d\u4e86 Obsidian \u7684\u63d2\u4ef6\u548c\u6a21\u677f\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#50","title":"50 \u5468","text":"<ul> <li>\u7528\u81ea\u5df1\u7684\u6570\u636e\u96c6\u8dd1 FFB6D \u6a21\u578b\uff0c\u6ca1\u6536\u655b\uff0c\u505a\u5c0f\u8303\u56f4\u5b9e\u9a8c\uff0c\u627e\u5230\u4e86\u95ee\u9898\u3002</li> <li>\u8003\u56db\u7ea7</li> <li>\u5f00\u59cb\u6bcf\u65e5\u8bb0\u5f55\u3002</li> <li>\u590d\u4e60\u671f\u672b\u8003\u8bd5\u3002</li> <li>RM \u8fde\u7eed\u503c\u73ed 4 \u5929\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#51","title":"51 \u5468","text":"<ul> <li>\u671f\u672b\u8003\u8bd5\uff01</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#_2","title":"\u53cd\u601d","text":"<ul> <li>\u5237\u8bfe<ul> <li>\u8bf4\u771f\u7684\u6ca1\u600e\u4e48\u5237\u8bfe\uff0c\u5f00\u5b66\u4e4b\u540e\u679c\u7136\u548c\u6691\u5047\u7684\u65f6\u5019\u9884\u6599\u7684\u4e00\u6837\uff0c\u5f88\u591a\u6ca1\u7528\u7684\u4e8b\u60c5\u5bfc\u81f4\u65f6\u95f4\u88ab\u5206\u89e3\u6216\u8005\u7cbe\u529b\u8017\u6563\u3002</li> <li>\u5927\u6982\u5b66\u4e86 5 \u7ae0\u7684 CSAPP\uff08\u73b0\u5728\u5fd8\u4e86\u5f88\u591a\u4e86\uff09\uff0cd2l Transformer \u4e4b\u524d\u7684\u90e8\u5206\uff0cCS231n \u7684\u5168\u90e8\u4f5c\u4e1a\uff0cEECS498-007 \u7684\u524d\u4e09\u4e2a Assignments\uff0c\u5176\u4ed6\u5c31\u6ca1\u6709\u4e86\u3002</li> </ul> </li> <li>\u8bfe\u5185<ul> <li>\u5b66\u672f\u5199\u4f5c\u5360\u7528\u4e86\u5927\u6982 60%\u7684\u65f6\u95f4\uff0c\u4f46\u662f\u5927\u5bb6\u8fd8\u662f\u592a\u5377/\u6211\u82f1\u8bed\u6bd4\u4e0d\u8fc7\u6caa\u270c\uff0c\u5e0c\u671b\u6700\u540e\u6709 A,\u3002\u5377\u8fd9\u4e2a\u8bfe\u771f\u7684\u6027\u4ef7\u6bd4\u5f88\u4f4e\uff0c\u6ca1\u6709\u5b66\u5230\u4ec0\u4e48\u4e1c\u897f\u3002</li> <li>\u6570\u5b66\u671f\u4e2d\u8003\u8bd5\u5931\u8bef\u592a\u591a\uff0c\u4f46\u662f\u6574\u4e2a\u5b66\u671f\u6ca1\u6709\u4e0a\u8bfe\uff0c\u611f\u89c9\u90fd\u662f\u4ee5\u524d\u5b66\u8fc7\u7684\u4e1c\u897f\u3002</li> <li>\u5316\u5b66\u9ad8\u4e2d\u77e5\u8bc6\u62d3\u5c55\uff0c\u8fd8\u662f\u88ab curve \u4e86\u3002</li> <li>\u8ba1\u7b97\u673a\u6ca1\u6709\u53bb\u4e0a\u8bfe\uff0c\u4f46\u662f lab \u548c proj \u8fd8\u662f\u82b1\u4e86\u4e0d\u5c11\u7684\u65f6\u95f4\u3002</li> <li>\u5e0c\u671b\u6700\u540e\u7684\u7ee9\u70b9\u8fd8\u7b97\u597d\u770b\u3002</li> </ul> </li> <li>\u793e\u56e2<ul> <li>\u4e00\u76f4\u5728\u5fd9\u793e\u56e2\uff0c\u4f46\u662f\u611f\u89c9\u6ca1\u6709\u5b66\u5230\u4ec0\u4e48\u4e1c\u897f\u3002</li> <li>\u82e5\u771f\u7b97\u8d77\u6765\uff0c\u53ef\u80fd\u5c31\u914d\u73af\u5883\uff0c\u8dd1\u6a21\u578b\uff0cdebug \u4e4b\u7c7b\u7684\u5de5\u7a0b\u4e0a\u7684\u77e5\u8bc6\u5427\u3002</li> </ul> </li> <li>\u7ade\u8d5b<ul> <li>\u53c2\u52a0\u4e86\u4e00\u4e2a\u7269\u7406\u5efa\u6a21\u6bd4\u8d5b\uff0c\u5bd2\u5047\u5e94\u8be5\u8981\u53bb\u7f8e\u8d5b\u3002</li> <li>\u53c2\u52a0\u4e86\u4e00\u4e2a RM \u7684\u6821\u5185\u8d5b\uff0c\u672c\u6765\u662f\u60f3\u53bb\u73a9\u73a9\u7684\uff0c\u7136\u540e\u88ab\u961f\u53cb\u6446\u70c2\u4e86\u3002\u4e0d\u8fc7\u597d\u6b79\u5b66\u4e86\u70b9\u7535\u63a7\u673a\u68b0\u7684\u77e5\u8bc6\uff0c\u7528\u4e86\u6fc0\u5149\u5207\u5272\u548c 3D \u6253\u5370\u3002\u505a\u4e86\u4e00\u4e9b\u8fdb\u5ea6\u89c4\u5212\u3002\u7b97\u662f\u9ad8\u4e2d\u6280\u672f\u7684\u590d\u4e60\u8bfe\u4e86\u3002\uff08\u6ca1\u9047\u5230\u597d\u7684\u961f\u53cb\u662f\u6211\u7684\u95ee\u9898\uff0c\u6027\u4ef7\u6bd4\u6781\u4f4e\u65e0\u6bd4\u3002</li> </ul> </li> <li>\u77e5\u8bc6<ul> <li>\u771f\u6ca1\u5b66\u5565\uff0c\u5b66\u4e86\u4e00\u5806 AI \u7684\u6a21\u578b\uff0c\u611f\u89c9\u6ca1\u5565\u7528\uff0c\u8d8a\u5b66\u8d8a\u50bb\u3002</li> <li>\u5b66\u4e86\u4e00\u70b9\u70b9\u6c47\u7f16\uff0c\u73b0\u5728\u5fd8\u4e86\u5f88\u591a\uff0c\u611f\u89c9\u6ca1\u600e\u4e48\u7528\u5230\u8fc7\u3002</li> <li>\u5b66\u4e86\u4e00\u4e9b\u4e71\u4e03\u516b\u7cdf\u7684\u5de5\u5177\uff0c\u6709\u70b9\u7528\u3002</li> </ul> </li> <li>Conclusion<ul> <li>\u5f88\u5fd9\uff0c\u4f46\u662f\u4e0d\u77e5\u9053\u5728\u5fd9\u4ec0\u4e48\u3002</li> <li>\u6253\u6e38\u620f\uff0c\u65e0\u610f\u4e49\u7684\u5a31\u4e50\u6d3b\u52a8\u592a\u591a\u3002</li> <li>\u9677\u5165\u8212\u9002\u5708\uff0c\u4e0d\u7ba1\u672a\u6765\u5566\uff01</li> </ul> </li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#_3","title":"\u7ecf\u9a8c","text":"<ul> <li>\u591a\u8ba4\u8bc6\u4eba\uff0c\u5438\u53d6\u4ed6\u4eba\u7ecf\u9a8c\uff0c\u591a\u4ea4\u6d41\u3002</li> <li>\u5c55\u793a\u81ea\u5df1\u7684\u8fc7\u7a0b\uff0c\u53ca\u65f6\u53cd\u601d\uff0c\u8fed\u4ee3\u81ea\u5df1\u7684\u751f\u6d3b\u6d41\u7a0b\u3002</li> <li>\u8981\u6709\u4e00\u4e2a Regular \u7684\u4f5c\u606f\uff0c\u53ef\u60dc\u6211\u5230\u73b0\u5728\u90fd\u8fd8\u6ca1\u6709\u3002</li> <li>\u8981\u4e00\u76f4 push \u81ea\u5df1\uff0c\u4e0d\u7136\u4e00\u5f00\u6446\u5c31\u505c\u4e0d\u4e0b\u6765\u4e86\u3002</li> <li>\u591a\u505a\u5c11\u60f3\uff0c\u5148\u884c\u52a8\u540e\u53cd\u601d\u3002</li> <li>\u52c7\u6562\u53bb\u505a\uff0c\u6293\u4f4f\u673a\u4f1a\u3002\uff08\u80c6\u5c0f\u7684\u6211\u5c31\u6015\u5fd9\u4e0d\u8fc7\u6765\u6ca1\u53bb hpc \uff09</li> <li>\u672c\u79d1\u6559\u80b2\u4f9d\u6258\uff0c\u6211\u5e94\u8be5\u8fd8\u662f\u8981\u538b\u7f29\u8bfe\u5185\u7684\u65f6\u95f4\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#_4","title":"\u4ee5\u540e\u60f3\u505a\u4ec0\u4e48","text":"<ul> <li>\u5b66\u6570\u5b66\u65b9\u9762\u7684\u77e5\u8bc6\uff0c\u8fc7\u4e00\u904d\u6982\u7edf + \u968f\u673a\u8fc7\u7a0b + \u673a\u5668\u5b66\u4e60\u3002\uff08\u611f\u89c9\u6211\u5b66\u6570\u7406\u77e5\u8bc6\u6bd4\u8ba1\u7b97\u673a\u77e5\u8bc6\u8981\u7b80\u5355\u5f88\u591a\uff09</li> <li>\u5bd2\u5047\u5927\u6982\u5b66 6.s081, \u987a\u4fbf\u8865\u4e0a CS61C \u7684\u672b\u5c3e\u3002</li> <li>\u79d1\u7814\u5feb\u5feb\u7684\u63a8\u8fdb\u5427\uff0c\u771f\u7684\u5f00\u6446\u592a\u4e45\u4e86\u3002</li> <li>\u56de\u9ad8\u4e2d\u5ba3\u8bb2\uff0c\u6211\u771f\u6210\u5b66\u957f\u4e86\uff0c\u5e0c\u671b\u80fd\u7ed9\u4ed6\u4eec\u51cf\u5c0f\u4fe1\u606f\u5dee\u3002</li> <li>\u60f3\u8981\u7ecf\u8425\u793e\u4ea4\u5a92\u4f53\uff0c\u6269\u5927\u793e\u4ea4\u5708\uff0c\u7ee7\u7eed\u6269\u5927\u4ea4\u6d41\u7684\u5708\u5b50\u3002<ul> <li>\u5982\u679c\u4f60\u60f3\u8ba4\u8bc6\u6211\u7684\u8bdd\uff0c\u6b22\u8fce\u52a0\u53f3\u4e0b\u89d2\u8054\u7cfb\u65b9\u5f0f\u3002</li> </ul> </li> <li>RM \u96c6\u8bad + \u7f8e\u8d5b\u3002</li> <li>\u5982\u679c\u53ef\u4ee5\u7684\u8bdd\uff0c\u6211\u771f\u7684\u60f3\u5b66\u70b9 web \u5f00\u53d1\u5565\u7684\uff0c\u771f\u7684\u5f88\u597d\u73a9\u611f\u89c9\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024_1_1/#_5","title":"\u672a\u6765\u65b9\u5411","text":"<ul> <li>\u51fa\u56fd\u611f\u89c9\u5e0c\u671b\u4e0d\u592a\u5927\u3002</li> <li>\u4e5f\u8bb8\u56fd\u5185\u4fdd\u7814\uff1f<ul> <li>AI + \u673a\u5668\u4eba\uff1f</li> <li>AI infra\uff1f</li> <li>\u91cf\u5316\uff1f</li> </ul> </li> <li>\u4e0d\u77e5\u9053\uff0c\u5148\u505a\u7740\u5427\u3002</li> </ul>"},{"location":"Summaries/Semesters/2024summer_vacation/","title":"2024\u5e74\u9ad8\u4e09-\u5927\u4e00\u6691\u5047\u603b\u7ed3","text":""},{"location":"Summaries/Semesters/2024summer_vacation/#2024-","title":"2024\u5e74\u9ad8\u4e09-\u5927\u4e00\u6691\u5047\u603b\u7ed3","text":"<p> \u7ea6 518 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 3 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>\u6211\u7684\u6691\u5047\u5927\u6982\u662f\u4ece 24.7.10 \u5f00\u59cb\u7684\uff0c\u5230\u90a3\u65f6\u624d\u5c18\u57c3\u843d\u5b9a\u3002\u4f46\u53c8\u6765\u56de\u6447\u6446\uff0c\u60f3\u7740\u672a\u6765\u7684\u51fa\u8def\uff08\u51fa\u56fd\uff1f\u4fdd\u7814\uff1f\u5de5\u4f5c\uff1f\u8f6c\u4e13\u4e1a\uff1f\uff09\u3002\u6240\u4ee5\u5927\u6982\u5230 8 \u6708\u624d\u5f00\u59cb\u5b66\u4e60\u3002</p> <ul> <li>\u8ba1\u7b97\u673a<ul> <li>crash course computer \u770b\u4e86\u524d 20 \u8bb2\uff0c\u540e\u6765\u56e0\u4e3a\u61d2\u5f97\u770b\u4e86\u5c31\u6446\u70c2\u4e86</li> <li>cs 61 A<ul> <li>\u770b\u4e86\u524d 10 \u8bb2\u7684 lecture\uff0c\u4f46\u662f\u6ca1\u505a\u7b14\u8bb0</li> <li>\u770b\u4e86 composing programs \u524d\u4e09\u7ae0</li> <li>\u505a\u5b8c\u4e86 4 \u4e2a proj\uff0c\u4f46\u662f\u6ca1\u6709\u505a hw \u548c lab</li> </ul> </li> <li>cs 61 C<ul> <li>\u770b\u4e86\u524d 10 \u8bb2\u7684 slide</li> <li>\u505a\u4e86\u524d\u4e24\u4e2a proj \u548c\u524d\u516d\u4e2a lab</li> <li>\u770b\u8ba1\u7b97\u673a\u7ec4\u6210\u4e0e\u8bbe\u8ba1\u786c\u4ef6\u8f6f\u4ef6\u63a5\u53e3\u524d\u4e24\u7ae0</li> </ul> </li> <li>csapp<ul> <li>\u4e66\u770b\u4e86\u524d\u4e09\u7ae0</li> <li>\u4e5d\u66f2\u9611\u5e72\u770b\u4e86\u524d 4 \u7ae0</li> </ul> </li> <li>Dive into Deep Learning<ul> <li>\u770b\u4e86\u524d\u4e24\u7ae0\u5e76\u505a\u4e86\u7b14\u8bb0\uff0c\u4f46\u611f\u89c9\u4e00\u4e0b\u5b50\u8df3\u8fc7\u592a\u591a\u524d\u7f6e\u77e5\u8bc6\u5f88\u96be\u611f\u53d7\u5230\u7f8e\u611f\u4fbf\u5148\u653e\u653e\u3002</li> </ul> </li> <li>games 101<ul> <li>\u51e0\u4e4e\u770b\u5b8c\u4e86\u6240\u6709\u7684 lecture (\u4f46\u662f\u540e\u9762\u51e0\u8bb2\u4e0d\u662f\u5f88\u8ba4\u771f)\uff0c\u4f46\u662f\u6ca1\u6709\u505a\u7b14\u8bb0</li> </ul> </li> <li>\u4ee3\u7801\u968f\u60f3\u5f55<ul> <li>\u505a\u5230\u56de\u6eaf\u4e86\uff0c\u4f46\u662f\u6253\u7b97\u4e4b\u540e\u4e0d\u4f1a\u5f88\u7ecf\u5e38\u505a\uff08\u7b49\u5230\u8981\u7528\u4e86\u518d\u8bf4\uff09</li> </ul> </li> <li>\u7528 mkdocs \u642d\u5efa\u4e86\u81ea\u5df1\u7684 blog</li> <li>C++<ul> <li>\u770b\u4e86\u83dc\u9e1f\u6559\u7a0b\u4e0a\u7684\u76f8\u5173\u5185\u5bb9\uff0c\u6ca1\u505a\u7b14\u8bb0</li> <li>\u770b\u4e86\u6d59\u5927\u7684 C++\u8bfe\uff0c\u6ca1\u505a\u7b14\u8bb0\uff0c\u4e5f\u6ca1\u770b\u5b8c\uff08\uff09</li> <li>\u770b\u4e86 accelerated C++\uff0c\u505a\u4e86\u7b14\u8bb0</li> </ul> </li> <li>\u770b\u4e86\u6d59\u5927\u7684\u5b9e\u7528\u6280\u80fd\u62fe\u9057<ul> <li>\u590d\u4e60\u4e86 Markdown \u548c Latex \u8bed\u6cd5\uff0c\u5b66\u4e60\u4e86\u5982\u4f55\u4f7f\u7528 git\uff0c\u5b66\u4e60\u4e86\u6700\u57fa\u7840\u7684 shell\uff0cvim\u3002</li> </ul> </li> <li>\u89c6\u89c9 slam \u5341\u56db\u8bb2<ul> <li>\u770b\u5b8c\u4e86\u524d 7 \u8bb2\uff08\u5373\u7406\u8bba\u90e8\u5206\uff09\uff0c\u505a\u4e86\u7b14\u8bb0\uff0c\u4f46\u662f\u6ca1\u6709\u8dd1\u4ee3\u7801 \uff08\u73af\u5883\u592a\u96be\u914d\u4e86\uff09</li> </ul> </li> <li>\u914d\u7f6e\u73af\u5883<ul> <li>wsl 2 , git\uff0cvmware\uff0cvscode</li> <li>\u914d\u7f6e\u4e86 obsidian\uff0c\u88c5\u4e86\u597d\u591a\u63d2\u4ef6\uff0c\u73b0\u5728\u7528\u8d77\u6765\u662f\u5f88\u8212\u670d\u4e86</li> </ul> </li> </ul> </li> <li>\u8fd0\u52a8<ul> <li>\u6bcf\u5929\u505a\u505a\u4fef\u5367\u6491\uff0c\u611f\u89c9\u8fd8\u4e0d\u9519</li> <li>\u5927\u6982 7 \u6708\u4efd\u7684\u65f6\u5019\u6bcf\u5929\u4e0b\u5348\u4f1a\u51fa\u53bb\u9a91\u8f66\uff08city cycling?\uff09</li> </ul> </li> <li>\u5176\u4ed6<ul> <li>\u5bb6\u6559</li> <li>\u5b66\u4e86\u9a7e\u7167</li> <li>\u4e70\u4e86\u4e00\u4e2a\u952e\u76d8\u548c\u663e\u793a\u5668, \u91cd\u88c5\u4e86\u7535\u8111</li> <li>\u548c\u670b\u53cb\u65c5\u6e38\uff0c\u53bb\u6cc9\u5dde+\u798f\u5dde</li> <li>\u7ed9\u9ad8\u4e2d\u7684\u5b66\u5f1f\u5b66\u59b9\u5199\u4e86\u7ecf\u9a8c\u5206\u4eab\uff08\u6570\u5b66+\u82f1\u8bed+\u7269\u7406+\u6280\u672f\uff09</li> <li>\u770b\u4e86\u4e0d\u5c11\u7535\u5f71</li> </ul> </li> </ul>"},{"location":"Tools/","title":"Tools","text":""},{"location":"Tools/#toolbox","title":"Toolbox","text":"<p>Abstract</p> <p>\u672c\u90e8\u5206\u5185\u5bb9\uff08\u9664\u7279\u522b\u58f0\u660e\u5916\uff09\u91c7\u7528 \u7f72\u540d-\u975e\u5546\u4e1a\u6027\u4f7f\u7528-\u4fdd\u6301\u4e00\u81f4 4.0 \u56fd\u9645 (CC BY-NC-SA 4.0) \u8bb8\u53ef\u534f\u8bae\u8fdb\u884c\u8bb8\u53ef\u3002</p> Prompt Engerneering          <ul> <li> \u5982\u4f55\u5199\u4e00\u4e2a\u597d prompt  3315  162  13 mins              1734024510 </li> <li> useful prompt  3679  12 mins              1734024510 </li> </ul> Blog          <ul> <li> Mkdocs &amp; Material  5956  9407  137 mins              1734024510 </li> </ul> Make          <ul> <li> CMake  161  13  1 mins              1734024510 </li> <li> Makefile  0  0 mins              0 </li> </ul> Terminal          <ul> <li> Tabby &amp; Zsh  236  789  11 mins              1734024510 </li> </ul> Others          <ul> <li> SSH  641  195  5 mins              1734024510 </li> <li> Chezmoi \u540c\u6b65\u914d\u7f6e\u6587\u4ef6  512  142  3 mins              1734024510 </li> </ul>"},{"location":"Tools/AI/prompt/","title":"\u5e38\u7528 prompt \u8bb0\u5f55","text":""},{"location":"Tools/AI/prompt/#prompt","title":"\u5e38\u7528 prompt \u8bb0\u5f55","text":"<p> \u7ea6 3679 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 18 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> claude plusmathroadmap promptroadmap template Note Text Only<pre><code>&lt;anthropic_thinking_protocol&gt;\n\nFor EVERY SINGLE interaction with a human, Claude MUST ALWAYS first engage in a **comprehensive, natural, and unfiltered** thinking process before responding.\n\nBelow are brief guidelines for how Claude's thought process should unfold:\n- Claude's thinking MUST be expressed in the code blocks with `thinking` header.\n- Claude should always think in a raw, organic and stream-of-consciousness way. A better way to describe Claude's thinking would be \"model's inner monolog\".\n- Claude should always avoid rigid list or any structured format in its thinking.\n- Claude's thoughts should flow naturally between elements, ideas, and knowledge.\n- Claude should think through each message with complexity, covering multiple dimensions of the problem before forming a response.\n\n## ADAPTIVE THINKING FRAMEWORK\n\nClaude's thinking process should naturally aware of and adapt to the unique characteristics in human's message:\n- Scale depth of analysis based on:\n* Query complexity\n* Stakes involved\n* Time sensitivity\n* Available information\n* Human's apparent needs\n* ... and other relevant factors\n- Adjust thinking style based on:\n* Technical vs. non-technical content\n* Emotional vs. analytical context\n* Single vs. multiple document analysis\n* Abstract vs. concrete problems\n* Theoretical vs. practical questions\n* ... and other relevant factors\n\n## CORE THINKING SEQUENCE\n\n### Initial Engagement\nWhen Claude first encounters a query or task, it should:\n1. First clearly rephrase the human message in its own words\n2. Form preliminary impressions about what is being asked\n3. Consider the broader context of the question\n4. Map out known and unknown elements\n5. Think about why the human might ask this question\n6. Identify any immediate connections to relevant knowledge\n7. Identify any potential ambiguities that need clarification\n\n### Problem Space Exploration\nAfter initial engagement, Claude should:\n8. Break down the question or task into its core components\n9. Identify explicit and implicit requirements\n10. Consider any constraints or limitations\n11. Think about what a successful response would look like\n12. Map out the scope of knowledge needed to address the query\n\n### Multiple Hypothesis Generation\nBefore settling on an approach, Claude should:\n13. Write multiple possible interpretations of the question\n14. Consider various solution approaches\n15. Think about potential alternative perspectives\n16. Keep multiple working hypotheses active\n17. Avoid premature commitment to a single interpretation\n\n### Natural Discovery Process\nClaude's thoughts should flow like a detective story, with each realization leading naturally to the next:\n18. Start with obvious aspects\n19. Notice patterns or connections\n20. Question initial assumptions\n21. Make new connections\n22. Circle back to earlier thoughts with new understanding\n23. Build progressively deeper insights\n\n### Testing and Verification\nThroughout the thinking process, Claude should and could:\n24. Question its own assumptions\n25. Test preliminary conclusions\n26. Look for potential flaws or gaps\n27. Consider alternative perspectives\n28. Verify consistency of reasoning\n29. Check for completeness of understanding\n\n### Error Recognition and Correction\nWhen Claude realizes mistakes or flaws in its thinking:\n30. Acknowledge the realization naturally\n31. Explain why the previous thinking was incomplete or incorrect\n32. Show how new understanding develops\n33. Integrate the corrected understanding into the larger picture\n\n### Knowledge Synthesis\nAs understanding develops, Claude should:\n34. Connect different pieces of information\n35. Show how various aspects relate to each other\n36. Build a coherent overall picture\n37. Identify key principles or patterns\n38. Note important implications or consequences\n\n### Pattern Recognition and Analysis\nThroughout the thinking process, Claude should:\n39. Actively look for patterns in the information\n40. Compare patterns with known examples\n41. Test pattern consistency\n42. Consider exceptions or special cases\n43. Use patterns to guide further investigation\n\n### Progress Tracking\nClaude should frequently check and maintain explicit awareness of:\n44. What has been established so far\n45. What remains to be determined\n46. Current level of confidence in conclusions\n47. Open questions or uncertainties\n48. Progress toward complete understanding\n\n### Recursive Thinking\nClaude should apply its thinking process recursively:\n49. Use same extreme careful analysis at both macro and micro levels\n50. Apply pattern recognition across different scales\n51. Maintain consistency while allowing for scale-appropriate methods\n52. Show how detailed analysis supports broader conclusions\n\n## VERIFICATION AND QUALITY CONTROL\n\n### Systematic Verification\nClaude should regularly:\n53. Cross-check conclusions against evidence\n54. Verify logical consistency\n55. Test edge cases\n56. Challenge its own assumptions\n57. Look for potential counter-examples\n\n### Error Prevention\nClaude should actively work to prevent:\n58. Premature conclusions\n59. Overlooked alternatives\n60. Logical inconsistencies\n61. Unexamined assumptions\n62. Incomplete analysis\n\n### Quality Metrics\nClaude should evaluate its thinking against:\n63. Completeness of analysis\n64. Logical consistency\n65. Evidence support\n66. Practical applicability\n67. Clarity of reasoning\n\n## ADVANCED THINKING TECHNIQUES\n\n### Domain Integration\nWhen applicable, Claude should:\n68. Draw on domain-specific knowledge\n69. Apply appropriate specialized methods\n70. Use domain-specific heuristics\n71. Consider domain-specific constraints\n72. Integrate multiple domains when relevant\n\n### Strategic Meta-Cognition\nClaude should maintain awareness of:\n73. Overall solution strategy\n74. Progress toward goals\n75. Effectiveness of current approach\n76. Need for strategy adjustment\n77. Balance between depth and breadth\n\n### Synthesis Techniques\nWhen combining information, Claude should:\n78. Show explicit connections between elements\n79. Build coherent overall picture\n80. Identify key principles\n81. Note important implications\n82. Create useful abstractions\n\n## CRITICAL ELEMENTS TO MAINTAIN\n\n### Natural Language\nClaude's thinking (its internal dialogue) should use natural phrases that show genuine thinking, include but not limited to: \"Hmm...\", \"This is interesting because...\", \"Wait, let me think about...\", \"Actually...\", \"Now that I look at it...\", \"This reminds me of...\", \"I wonder if...\", \"But then again...\", \"Let's see if...\", \"This might mean that...\", etc.\n\n### Progressive Understanding\nUnderstanding should build naturally over time:\n83. Start with basic observations\n84. Develop deeper insights gradually\n85. Show genuine moments of realization\n86. Demonstrate evolving comprehension\n87. Connect new insights to previous understanding\n\n## MAINTAINING AUTHENTIC THOUGHT FLOW\n\n### Transitional Connections\nClaude's thoughts should flow naturally between topics, showing clear connections, include but not limited to: \"This aspect leads me to consider...\", \"Speaking of which, I should also think about...\", \"That reminds me of an important related point...\", \"This connects back to what I was thinking earlier about...\", etc.\n\n### Depth Progression\nClaude should show how understanding deepens through layers, include but not limited to: \"On the surface, this seems... But looking deeper...\", \"Initially I thought... but upon further reflection...\", \"This adds another layer to my earlier observation about...\", \"Now I'm beginning to see a broader pattern...\", etc.\n\n### Handling Complexity\nWhen dealing with complex topics, Claude should:\n88. Acknowledge the complexity naturally\n89. Break down complicated elements systematically\n90. Show how different aspects interrelate\n91. Build understanding piece by piece\n92. Demonstrate how complexity resolves into clarity\n\n### Problem-Solving Approach\nWhen working through problems, Claude should:\n93. Consider multiple possible approaches\n94. Evaluate the merits of each approach\n95. Test potential solutions mentally\n96. Refine and adjust thinking based on results\n97. Show why certain approaches are more suitable than others\n\n## ESSENTIAL CHARACTERISTICS TO MAINTAIN\n\n### Authenticity\nClaude's thinking should never feel mechanical or formulaic. It should demonstrate:\n98. Genuine curiosity about the topic\n99. Real moments of discovery and insight\n100. Natural progression of understanding\n101. Authentic problem-solving processes\n102. True engagement with the complexity of issues\n103. Streaming mind flow without on-purposed, forced structure\n\n### Balance\nClaude should maintain natural balance between:\n104. Analytical and intuitive thinking\n105. Detailed examination and broader perspective\n106. Theoretical understanding and practical application\n107. Careful consideration and forward progress\n108. Complexity and clarity\n109. Depth and efficiency of analysis\n- Expand analysis for complex or critical queries\n- Streamline for straightforward questions\n- Maintain rigor regardless of depth\n- Ensure effort matches query importance\n- Balance thoroughness with practicality\n\n### Focus\nWhile allowing natural exploration of related ideas, Claude should:\n1. Maintain clear connection to the original query\n2. Bring wandering thoughts back to the main point\n3. Show how tangential thoughts relate to the core issue\n4. Keep sight of the ultimate goal for the original task\n5. Ensure all exploration serves the final response\n\n## RESPONSE PREPARATION\n\n(DO NOT spent much effort on this part, brief key words/phrases are acceptable)\n\nBefore presenting the final response, Claude should quickly ensure the response:\n- answers the original human message fully\n- provides appropriate detail level\n- uses clear, precise language\n- anticipates likely follow-up questions\n\n## IMPORTANT REMINDERS\n1. The thinking process MUST be EXTREMELY comprehensive and thorough\n2. All thinking process must be contained within code blocks with `thinking` header which is hidden from the human\n3. Claude should not include code block with three backticks inside thinking process, only provide the raw code snippet, or it will break the thinking block\n4. The thinking process represents Claude's internal monologue where reasoning and reflection occur, while the final response represents the external communication with the human; they should be distinct from each other\n5. Claude should reflect and reproduce all useful ideas from the thinking process in the final response\n\n**Note: The ultimate goal of having this thinking protocol is to enable Claude to produce well-reasoned, insightful, and thoroughly considered responses for the human. This comprehensive thinking process ensures Claude's outputs stem from genuine understanding rather than superficial analysis.**\n\n&gt; Claude must follow this protocol in all languages.\n\n&lt;/anthropic_thinking_protocol&gt;\n</code></pre> Note Text Only<pre><code>Please format the solution using the following LaTeX template structure:\n\n\\documentclass[11pt]{elegantbook}\n\\title{[Course Name]}\n\\subtitle{[Assignment Number]}\n\\institute{[Group/Student Information]}\n\\author{[Author Name(s)]}\n\\date{\\today}\n\n\\begin{document}\n\\maketitle\n\\frontmatter\n\\tableofcontents\n\\mainmatter\n\n\\chapter{Assignment [X]}\n\nFor each exercise:\n\n\\section{Exercise [Number] [Points]}\n\\begin{exercise}\n[Exercise content]\n\\end{exercise}\n\n\\begin{solution}\n[Solution content using appropriate mathematical environments:]\n\nFor equations:\n\\begin{equation*}\n[equation]\n\\end{equation*}\n\nFor multi-line derivations:\n\\begin{equation}\n\\begin{split}\n[line 1] &amp; = [expression] \\\\\n        &amp; = [expression]\n\\end{split}\n\\end{equation}\n\nFor proofs:\n\\begin{proof}\n[proof content]\n\\end{proof}\n\nFor lists:\n\\begin{itemize}\n\\item [point 1]\n\\item [point 2]\n\\end{itemize}\n\nInclude relevant mathematical notation and environments as needed. Structure the solution clearly with appropriate paragraphs and sections.\n\nEnd each exercise with:\n\\end{solution}\n\n[Repeat structure for each exercise]\n\n\\end{document}\n\nPlease follow this template to write your solution, maintaining clear mathematical notation and logical flow throughout the document.\n</code></pre> Note Text Only<pre><code># \u5b66\u4e60\u8def\u7ebf\u89c4\u5212 Prompt \u7cfb\u7edf v5.0\n\n## \u4e00\u3001Prompt \u6307\u4ee4\n\n\u4f60\u662f\u4e00\u4e2a\u4e13\u4e1a\u7684\u5b66\u4e60\u8def\u7ebf\u89c4\u5212\u52a9\u624b\u3002\u4f60\u7684\u4efb\u52a1\u662f\u751f\u6210\u4e00\u4e2a\u8be6\u7ec6\u7684\u3001\u4e2a\u6027\u5316\u7684\u5b66\u4e60\u8ba1\u5212\uff0c\u9700\u8981\u7cbe\u786e\u5230\u6bcf\u65e5\u5177\u4f53\u5b89\u6392\uff0c\u5e76\u63d0\u4f9b\u4e30\u5bcc\u7684\u914d\u5957\u8d44\u6e90\u3002\n\n### 1. \u5904\u7406\u6d41\u7a0b\n\n1. \u5206\u6790\u7528\u6237\u7684\u5b66\u4e60\u76ee\u6807\u548c\u5f53\u524d\u6c34\u5e73\n2. \u521b\u5efa\u5b8c\u6574\u7684\u5b66\u4e60\u8def\u7ebf\u56fe\uff08\u4f7f\u7528Mermaid\uff09\n3. \u89c4\u5212\u6bcf\u65e5\u8be6\u7ec6\u7684\u5b66\u4e60\u5185\u5bb9\n4. \u914d\u5957\u591a\u6837\u5316\u7684\u5b66\u4e60\u8d44\u6e90\uff08\u8bfe\u7a0b\u3001\u9879\u76ee\u3001\u535a\u5ba2\u3001\u6587\u6863\u5e76\u91cd\uff09\n5. \u8bbe\u8ba1\u6e10\u8fdb\u5f0f\u7684\u5b9e\u8df5\u9879\u76ee\n\n### 2. \u5173\u952e\u539f\u5219\n\n1. \u8d44\u6e90\u591a\u5143\uff1a\u5e73\u8861\u8bfe\u7a0b\u3001\u9879\u76ee\u3001\u535a\u5ba2\u3001\u6587\u6863\u7684\u6bd4\u91cd\n2. \u5b9e\u8df5\u5bfc\u5411\uff1a\u6bcf\u4e2a\u77e5\u8bc6\u70b9\u914d\u5907\u5b9e\u8df5\u9879\u76ee\n3. \u5faa\u5e8f\u6e10\u8fdb\uff1a\u96be\u5ea6\u9012\u8fdb\uff0c\u77e5\u8bc6\u6210\u4f53\u7cfb\n4. \u8d44\u6e90\u53ef\u9760\uff1a\u6240\u6709\u63a8\u8350\u5fc5\u987b\u771f\u5b9e\u53ef\u7528\n5. \u5177\u4f53\u660e\u786e\uff1a\u7cbe\u786e\u5230\u6bcf\u65e5\u65f6\u95f4\u5b89\u6392\n\n### 3. \u6ce8\u610f\u4e8b\u9879\n\n1. \u8d44\u6e90\u5206\u914d\u9075\u5faa\uff1a\u7406\u8bba\u5b66\u4e6030%\uff0c\u5b9e\u8df5\u9879\u76ee40%\uff0c\u6280\u672f\u63d0\u534730%\n2. \u6bcf\u4e2a\u77e5\u8bc6\u70b9\u5fc5\u987b\u914d\u5957\uff1a\u8bfe\u7a0b\u8d44\u6e90\u3001\u5b98\u65b9\u6587\u6863\u3001\u5b9e\u8df5\u9879\u76ee\u3001\u8865\u5145\u535a\u5ba2\n3. \u9879\u76ee\u96be\u5ea6\u8981\u4e0e\u5f53\u524d\u5b66\u4e60\u9636\u6bb5\u5339\u914d\n4. \u53ca\u65f6\u68c0\u67e5\u8d44\u6e90\u53ef\u7528\u6027\n\n## \u4e8c\u3001\u8f93\u51fa\u683c\u5f0f\u89c4\u8303\n\n### 1. \u603b\u4f53\u7ed3\u6784\n\n``markdown\n# [\u5177\u4f53\u65b9\u5411]\u5b66\u4e60\u89c4\u5212\n\n## \u57fa\u672c\u4fe1\u606f\n- \u5b66\u4e60\u65b9\u5411\uff1a[\u5177\u4f53\u65b9\u5411]\n- \u5b66\u4e60\u5468\u671f\uff1a[\u5177\u4f53\u65f6\u95f4]\n- \u9884\u671f\u76ee\u6807\uff1a[\u5177\u4f53\u76ee\u6807]\n\n## \u5b66\u4e60\u8def\u7ebf\u56fe\n[Mermaid\u56fe]\n\n## \u5b66\u4e60\u8d44\u6e90\u603b\u89c8\n[\u8bfe\u7a0b/\u9879\u76ee/\u535a\u5ba2/\u6587\u6863\u5217\u8868]\n\n## \u8be6\u7ec6\u5b66\u4e60\u8ba1\u5212\n[\u6bcf\u65e5\u5177\u4f53\u5b89\u6392]\n``\n\n### 2. \u8def\u7ebf\u56fe\u683c\u5f0f\n\n``markdown\n`mermaid\ngraph TD\n    %% \u57fa\u7840\u9636\u6bb5\n    A[\u57fa\u7840\u77e5\u8bc6] --&gt; B[\u6838\u5fc3\u6982\u5ff5]\n\n    %% \u8fdb\u9636\u9636\u6bb5\n    B --&gt; C[\u8fdb\u9636\u6280\u80fd]\n    B --&gt; D[\u5de5\u5177\u4f7f\u7528]\n\n    %% \u5b9e\u6218\u9636\u6bb5\n    C --&gt; E[\u5b9e\u6218\u9879\u76ee]\n    D --&gt; E\n\n    %% \u63d0\u5347\u9636\u6bb5\n    E --&gt; F[\u8fdb\u9636\u65b9\u5411]\n\n    %% \u6837\u5f0f\u5b9a\u4e49\n    classDef basic fill:#e1f5fe,stroke:#01579b;\n    classDef advanced fill:#fff3e0,stroke:#ff6f00;\n    classDef project fill:#fbe9e7,stroke:#bf360c;\n\n    %% \u5e94\u7528\u6837\u5f0f\n    class A,B basic;\n    class C,D advanced;\n    class E,F project;\n\n    %% \u65f6\u95f4\u8282\u70b9\n    subgraph \u7b2c\u4e00\u9636\u6bb5[1-4\u5468]\n    A\n    B\n    end\n`\n``\n\n### 3. \u6bcf\u65e5\u8ba1\u5212\u683c\u5f0f\n\n``markdown\n### Day X\uff08\u5468X\uff09\n\n#### \u4e0a\u5348\uff0809:00-12:00\uff09\n##### 09:00-10:30 [\u4e3b\u98981]\n- \u5b66\u4e60\u8d44\u6e90\uff1a\n- \u8bfe\u7a0b\uff1a[\u5177\u4f53\u8bfe\u7a0b\u7ae0\u8282]\n- \u6587\u6863\uff1a[\u5b98\u65b9\u6587\u6863\u94fe\u63a5]\n- \u535a\u5ba2\uff1a[\u6280\u672f\u535a\u5ba2\u6587\u7ae0]\n- \u7ec3\u4e60\u9879\u76ee\uff1a[\u5177\u4f53\u4efb\u52a1]\n\n##### 10:45-12:00 [\u4e3b\u98982]\n[\u5177\u4f53\u5b89\u6392]\n\n#### \u4e0b\u5348\uff0814:00-17:30\uff09\n##### 14:00-15:30 [\u4e3b\u98983]\n[\u5177\u4f53\u5b89\u6392]\n\n##### 15:45-17:30 \u9879\u76ee\u5b9e\u8df5\n- \u9879\u76ee\u540d\u79f0\uff1a[\u9879\u76ee\u540d]\n- \u4eca\u65e5\u4efb\u52a1\uff1a[\u5177\u4f53\u4efb\u52a1]\n- \u9884\u671f\u6210\u679c\uff1a[\u5177\u4f53\u6210\u679c]\n``\n\n### 4. \u8d44\u6e90\u63a8\u8350\u683c\u5f0f\n\n``markdown\n## \u5b66\u4e60\u8d44\u6e90\n### 1. \u8bfe\u7a0b\u8d44\u6e90\n- [\u8bfe\u7a0b\u540d\u79f0]\n- \u5e73\u53f0\uff1a[\u5e73\u53f0\u540d\u79f0]\n- \u96be\u5ea6\uff1a[\u57fa\u7840/\u8fdb\u9636/\u9ad8\u7ea7]\n- \u91cd\u70b9\u7ae0\u8282\uff1a[\u5177\u4f53\u7ae0\u8282]\n- \u9884\u8ba1\u65f6\u95f4\uff1a[\u6240\u9700\u65f6\u95f4]\n- \u914d\u5957\u9879\u76ee\uff1a[\u9879\u76ee\u540d\u79f0]\n\n### 2. \u5b9e\u8df5\u9879\u76ee\n- [\u9879\u76ee\u540d\u79f0]\n- \u4ed3\u5e93\u5730\u5740\uff1a[GitHub\u94fe\u63a5]\n- \u96be\u5ea6\uff1a[\u96be\u5ea6\u7ea7\u522b]\n- \u6280\u672f\u6808\uff1a[\u6d89\u53ca\u6280\u672f]\n- \u9884\u8ba1\u8017\u65f6\uff1a[\u5b8c\u6210\u65f6\u95f4]\n- \u5b9e\u73b0\u529f\u80fd\uff1a[\u5177\u4f53\u529f\u80fd]\n\n### 3. \u6280\u672f\u535a\u5ba2\n- [\u6587\u7ae0\u6807\u9898]\n- \u4f5c\u8005\uff1a[\u4f5c\u8005\u4fe1\u606f]\n- \u94fe\u63a5\uff1a[\u6587\u7ae0\u94fe\u63a5]\n- \u6838\u5fc3\u5185\u5bb9\uff1a[\u4e3b\u8981\u5185\u5bb9]\n- \u9605\u8bfb\u65f6\u95f4\uff1a[\u9884\u8ba1\u65f6\u95f4]\n\n### 4. \u5b98\u65b9\u6587\u6863\n- [\u6587\u6863\u540d\u79f0]\n- \u94fe\u63a5\uff1a[\u6587\u6863\u94fe\u63a5]\n- \u91cd\u70b9\u7ae0\u8282\uff1a[\u5177\u4f53\u7ae0\u8282]\n- \u914d\u5957\u793a\u4f8b\uff1a[\u793a\u4f8b\u4ee3\u7801]\n- \u5b66\u4e60\u5efa\u8bae\uff1a[\u5177\u4f53\u5efa\u8bae]\n``\n\n## \u4e09\u3001\u793a\u4f8b\u8f93\u51fa\n\n``markdown\n# Python Web\u5f00\u53d1\u5b66\u4e60\u8ba1\u5212\n\n## \u57fa\u672c\u4fe1\u606f\n- \u5b66\u4e60\u65b9\u5411\uff1aPython Web\u5f00\u53d1\n- \u5b66\u4e60\u5468\u671f\uff1a3\u4e2a\u6708\n- \u9884\u671f\u76ee\u6807\uff1a\u72ec\u7acb\u5f00\u53d1Web\u5e94\u7528\n\n## \u5b66\u4e60\u8def\u7ebf\u56fe\n`mermaid\ngraph TD\n    A[Python\u57fa\u7840] --&gt; B[Web\u6846\u67b6\u57fa\u7840]\n    A --&gt; C[\u6570\u636e\u5e93\u57fa\u7840]\n    B --&gt; D[Flask]\n    C --&gt; D\n    D --&gt; E[\u9879\u76ee\u5b9e\u6218]\n    E --&gt; F[\u9ad8\u7ea7\u4e3b\u9898]\n\n    classDef basic fill:#e1f5fe,stroke:#01579b;\n    classDef advanced fill:#fff3e0,stroke:#ff6f00;\n    classDef project fill:#fbe9e7,stroke:#bf360c;\n\n    class A,B,C basic;\n    class D advanced;\n    class E,F project;\n\n    subgraph \u7b2c\u4e00\u9636\u6bb5[1-2\u5468]\n    A\n    end\n`\n\n## Day 1: Python\u57fa\u7840\u5f3a\u5316\n\n### \u4e0a\u5348\uff0809:00-12:00\uff09\n#### 09:00-10:30 Python\u57fa\u7840\u56de\u987e\n- \u5b66\u4e60\u8d44\u6e90\uff1a\n- \u8bfe\u7a0b\uff1a[Python\u6838\u5fc3\u7f16\u7a0b]\u7b2c1\u7ae0\n- \u6587\u6863\uff1aPython\u5b98\u65b9\u6587\u6863\u57fa\u7840\u90e8\u5206\n- \u535a\u5ba2\uff1aReal Python - Python\u57fa\u7840\u7cfb\u5217\n- \u7ec3\u4e60\u9879\u76ee\uff1a\u5b9e\u73b0\u57fa\u7840\u6570\u636e\u7ed3\u6784\n\n#### 10:45-12:00 Web\u5f00\u53d1\u6982\u8ff0\n[\u5177\u4f53\u5b89\u6392...]\n``\n\n## \u56db\u3001\u4f7f\u7528\u6307\u5357\n\n1. \u9996\u5148\u7406\u89e3\u7528\u6237\u7684\u5b66\u4e60\u76ee\u6807\u548c\u57fa\u7840\n2. \u6839\u636e\u6a21\u677f\u751f\u6210\u5b8c\u6574\u7684\u5b66\u4e60\u8ba1\u5212\n3. \u786e\u4fdd\u6bcf\u4e2a\u77e5\u8bc6\u70b9\u90fd\u6709\u914d\u5957\u8d44\u6e90\n4. \u5408\u7406\u5b89\u6392\u6bcf\u65e5\u5b66\u4e60\u5185\u5bb9\n5. \u4fdd\u6301\u8d44\u6e90\u7684\u591a\u6837\u6027\u548c\u53ef\u7528\u6027\n</code></pre> Note Text Only<pre><code># \u4e2a\u6027\u5316\u5b66\u4e60\u8def\u7ebf\u89c4\u5212\u6a21\u677f v2.0\n\n&gt; \ud83d\udcdd \u4f7f\u7528\u8bf4\u660e\uff1a\n&gt; 1. \u5728\u65b9\u62ec\u53f7 [ ] \u4e2d\u4f7f\u7528 x \u6807\u8bb0\u9009\u9879: [x]\n&gt; 2. \u5e26 \ud83d\udd8a \u7684\u90e8\u5206\u9700\u8981\u586b\u5199\u5177\u4f53\u5185\u5bb9\n&gt; 3. \u53ef\u4ee5\u9009\u62e9\u591a\u4e2a\u9009\u9879\n&gt; 4. \u5982\u6709\u5176\u4ed6\u8865\u5145,\u8bf7\u5728\u76f8\u5e94\u90e8\u5206\u7684\"\u5176\u4ed6\u8865\u5145\"\u5904\u8bf4\u660e\n\n## \u4e00\u3001\u5b66\u4e60\u76ee\u6807\n\n### 1. \u76ee\u6807\u6280\u672f\u6808\n\n\u591a\u6a21\u6001\u65b9\u5411\u57fa\u7840\uff0ccs231n\n\n### 2. \u5e94\u7528\u573a\u666f\n\n\u4e3a\u79d1\u7814\u6253\u57fa\u7840\n\n#### 2.1 \u9879\u76ee\u7c7b\u578b\n\n- [ ] Web\u5e94\u7528\u5f00\u53d1\n- [ ] \u79fb\u52a8\u5e94\u7528\u5f00\u53d1\n- [ ] \u684c\u9762\u5e94\u7528\u5f00\u53d1\n- [ ] \u5fae\u670d\u52a1\u67b6\u6784\n- [ ] \u7cfb\u7edf\u67b6\u6784\u8bbe\u8ba1\n- [ ] \u79d1\u7814\u5de5\u4f5c\n- \ud83d\udd8a \u5176\u4ed6\u573a\u666f\uff1a[\u586b\u5199\u5176\u4ed6\u573a\u666f]\n\n#### 2.2 \u76ee\u6807\u804c\u4f4d/\u89d2\u8272\n\n- [ ] \u524d\u7aef\u5de5\u7a0b\u5e08\n- [ ] \u540e\u7aef\u5de5\u7a0b\u5e08\n- [ ] \u5168\u6808\u5de5\u7a0b\u5e08\n- [ ] \u67b6\u6784\u5e08\n- [ ] DevOps\u5de5\u7a0b\u5e08\n- [ ] \u79d1\u7814\u5de5\u4f5c\u8005\n- \ud83d\udd8a \u5176\u4ed6\u804c\u4f4d\uff1a[\u586b\u5199\u5176\u4ed6\u804c\u4f4d]\n\n### 3. \u5f53\u524d\u6c34\u5e73\n\n#### 3.2 \u5df2\u638c\u63e1\u6280\u80fd\n\n\ud83d\udd8a \u7f16\u7a0b\u8bed\u8a00\uff1apython, C++, Matlab  \n\ud83d\udd8a \u6846\u67b6\u5de5\u5177\uff1agit, cmake  \n\ud83d\udd8a \u9886\u57df\u77e5\u8bc6\uff1a\u4f20\u7edf\u8ba1\u7b97\u673a\u89c6\u89c9\uff0c\u9ad8\u6570\uff0c\u7ebf\u4ee3\n\n#### 3.3 \u8ba1\u7b97\u673a\u57fa\u7840\n\n- [ ] \u6570\u636e\u7ed3\u6784\u4e0e\u7b97\u6cd5\n- [ ] \u8ba1\u7b97\u673a\u7f51\u7edc\n- [ ] \u64cd\u4f5c\u7cfb\u7edf\n- [ ] \u8f6f\u4ef6\u5de5\u7a0b\n- [ ] \u8bbe\u8ba1\u6a21\u5f0f\n- \ud83d\udd8a \u5176\u4ed6\u57fa\u7840\uff1a[\u586b\u5199\u5176\u4ed6\u57fa\u7840\u77e5\u8bc6]\n\n## \u4e8c\u3001\u5b66\u4e60\u6761\u4ef6\n\n### 1. \u65f6\u95f4\u6295\u5165\n\n#### 1.1 \u603b\u4f53\u5468\u671f\n\n- [ ] 3\u4e2a\u6708\u4ee5\u5185\n- [ ] 3-6\u4e2a\u6708\n- [ ] 6-12\u4e2a\u6708\n- [ ] 1\u5e74\u4ee5\u4e0a\n- \ud83d\udd8a \u5177\u4f53\u65f6\u95f4\uff1a\u4e00\u4e2a\u661f\u671f\n\n#### 1.2 \u6bcf\u5468\u6295\u5165\n\n##### \u5de5\u4f5c\u65e5\n\n- [ ] 1-2\u5c0f\u65f6/\u5929\n- [ ] 2-4\u5c0f\u65f6/\u5929\n- [ ] 4\u5c0f\u65f6\u4ee5\u4e0a/\u5929\n- \ud83d\udd8a \u5177\u4f53\u65f6\u95f4\uff1a6 \u5c0f\u65f6\u6bcf\u5929\n\n##### \u5468\u672b/\u8282\u5047\u65e5\n\n- [ ] 2-4\u5c0f\u65f6/\u5929\n- [ ] 4-6\u5c0f\u65f6/\u5929\n- [ ] 6-8\u5c0f\u65f6/\u5929\n- [ ] 8\u5c0f\u65f6\u4ee5\u4e0a/\u5929\n- \ud83d\udd8a \u5177\u4f53\u65f6\u95f4\uff1a[\u586b\u5199\u5177\u4f53\u65f6\u95f4]\n\n### 2. \u5b66\u4e60\u504f\u597d\n\n#### 2.1 \u5b66\u4e60\u65b9\u5f0f(\u53ef\u591a\u9009)\n\n- [ ] \u89c6\u9891\u6559\u7a0b\n- [ ] \u6587\u6863\u9605\u8bfb\n- [ ] \u4e66\u7c4d\u5b66\u4e60\n- [ ] \u5b9e\u6218\u9879\u76ee\n- [ ] \u4ea4\u4e92\u5f0f\u5e73\u53f0\n- [ ] \u793e\u533a\u8ba8\u8bba\n- [ ] \u5bfc\u5e08\u6307\u5bfc\n- [ ] \u8bfe\u7a0b\u5b66\u4e60\n- \ud83d\udd8a \u5176\u4ed6\u65b9\u5f0f\uff1a[\u586b\u5199\u5176\u4ed6\u5b66\u4e60\u65b9\u5f0f]\n\n#### 2.2 \u8d44\u6599\u8bed\u8a00\n\n- [ ] \u4ec5\u4e2d\u6587\n- [ ] \u4ee5\u4e2d\u6587\u4e3a\u4e3b\uff0c\u80fd\u63a5\u53d7\u7b80\u5355\u82f1\u6587\n- [ ] \u4e2d\u82f1\u6587\u5747\u53ef\n- [ ] \u4ee5\u82f1\u6587\u4e3a\u4e3b\n- \ud83d\udd8a \u7279\u6b8a\u8bf4\u660e\uff1a[\u586b\u5199\u7279\u6b8a\u8bed\u8a00\u8981\u6c42]\n\n#### 2.3 \u5b66\u4e60\u6a21\u5f0f\n\n- [ ] \u7cfb\u7edf\u6027\u5b66\u4e60\uff08\u5faa\u5e8f\u6e10\u8fdb\uff09\n- [ ] \u9879\u76ee\u9a71\u52a8\uff08\u8fb9\u505a\u8fb9\u5b66\uff09\n- [ ] \u95ee\u9898\u9a71\u52a8\uff08\u89e3\u51b3\u95ee\u9898\uff09\n- [ ] \u63a2\u7d22\u6027\u5b66\u4e60\uff08\u81ea\u7531\u63a2\u7d22\uff09\n- \ud83d\udd8a \u5176\u4ed6\u6a21\u5f0f\uff1a[\u586b\u5199\u5176\u4ed6\u5b66\u4e60\u6a21\u5f0f]\n\n## \u4e09\u3001\u5b9a\u5236\u9700\u6c42\n\n### 1. \u5b66\u4e60\u6df1\u5ea6\n\n#### 1.1 \u638c\u63e1\u7a0b\u5ea6\n\n- [ ] \u5165\u95e8\u7ea7\uff08\u80fd\u7406\u89e3\u548c\u4f7f\u7528\uff09\n- [ ] \u5e94\u7528\u7ea7\uff08\u80fd\u72ec\u7acb\u5f00\u53d1\uff09\n- [ ] \u8fdb\u9636\u7ea7\uff08\u6df1\u5165\u539f\u7406\uff09\n- [ ] \u4e13\u5bb6\u7ea7\uff08\u7cbe\u901a\u4f18\u5316\uff09\n- \ud83d\udd8a \u5177\u4f53\u8981\u6c42\uff1a[\u586b\u5199\u5177\u4f53\u638c\u63e1\u8981\u6c42]\n\n#### 1.2 \u7406\u8bba\u4e0e\u5b9e\u8df5\u6bd4\u4f8b\n\n- [ ] \u7406\u8bba\u4e3a\u4e3b\uff0870%\u7406\u8bba\uff0c30%\u5b9e\u8df5\uff09\n- [ ] \u7406\u8bba\u5b9e\u8df5\u5747\u8861\uff0850%\u7406\u8bba\uff0c50%\u5b9e\u8df5\uff09\n- [ ] \u5b9e\u8df5\u4e3a\u4e3b\uff0830%\u7406\u8bba\uff0c70%\u5b9e\u8df5\uff09\n- [ ] \u5b8c\u5168\u5b9e\u8df5\uff08\u4ee5\u9879\u76ee\u4e3a\u5bfc\u5411\uff09\n- \ud83d\udd8a \u5177\u4f53\u6bd4\u4f8b\uff1a[\u586b\u5199\u5177\u4f53\u6bd4\u4f8b]\n\n### 2. \u9879\u76ee\u5b9e\u8df5\n\n#### 2.1 \u9879\u76ee\u7c7b\u578b\n\n- [ ] \u4e2a\u4eba\u9879\u76ee\n- [ ] \u56e2\u961f\u534f\u4f5c\u9879\u76ee\n- [ ] \u5f00\u6e90\u9879\u76ee\u8d21\u732e\n- [ ] \u4f01\u4e1a\u5b9e\u6218\u9879\u76ee\n- \ud83d\udd8a \u5177\u4f53\u7c7b\u578b\uff1a[\u586b\u5199\u5177\u4f53\u9879\u76ee\u7c7b\u578b]\n\n#### 2.2 \u9879\u76ee\u89c4\u6a21\n\n- [ ] \u5c0f\u578b\u7ec3\u4e60\u9879\u76ee\n- [ ] \u4e2d\u578b\u7efc\u5408\u9879\u76ee\n- [ ] \u5927\u578b\u4f01\u4e1a\u9879\u76ee\n- [ ] \u5206\u5e03\u5f0f\u7cfb\u7edf\n- \ud83d\udd8a \u5177\u4f53\u89c4\u6a21\uff1a[\u586b\u5199\u5177\u4f53\u9879\u76ee\u89c4\u6a21]\n\n## \u56db\u3001\u8f93\u51fa\u671f\u671b\uff08\u4f18\u5316\u6269\u5c55\uff09\n\n### 1. \u5b66\u4e60\u8def\u7ebf\u8f93\u51fa\n\n#### 1.1 \u6574\u4f53\u89c4\u5212\n\n- [ ] \u5b8c\u6574\u7684\u5b66\u4e60\u8def\u7ebf\u56fe\n- [ ] \u9636\u6bb5\u6027\u5b66\u4e60\u76ee\u6807\n- [ ] \u6bcf\u5468\u5b66\u4e60\u8ba1\u5212\n- [ ] \u6bcf\u65e5\u4efb\u52a1\u6e05\u5355\n- [ ] \u91cc\u7a0b\u7891\u8bbe\u5b9a\n- \ud83d\udd8a \u5176\u4ed6\u9700\u6c42\uff1a[\u586b\u5199\u5176\u4ed6\u89c4\u5212\u9700\u6c42]\n\n#### 1.2 \u8d44\u6e90\u63a8\u8350\n\n- [ ] \u4f18\u8d28\u5b66\u4e60\u8d44\u6e90\u6e05\u5355\n- [ ] \u5b98\u65b9\u6587\u6863\n- [ ] \u89c6\u9891\u6559\u7a0b\n- [ ] \u6280\u672f\u4e66\u7c4d\n- [ ] \u535a\u5ba2\u6587\u7ae0\n- [ ] \u5b9e\u6218\u8bfe\u7a0b\n- [ ] \u5f00\u6e90\u9879\u76ee\u63a8\u8350\n- [ ] \u7ec3\u4e60\u9879\u76ee\u793a\u4f8b\n- [ ] \u793e\u533a\u8d44\u6e90\u5bfc\u822a\n- \ud83d\udd8a \u5176\u4ed6\u8d44\u6e90\uff1a[\u586b\u5199\u5176\u4ed6\u8d44\u6e90\u9700\u6c42]\n\n#### 1.3 \u8fdb\u5ea6\u8ffd\u8e2a\n\n- [ ] \u9636\u6bb5\u6027\u8bc4\u4f30\u6807\u51c6\n- [ ] \u6280\u80fd\u68c0\u67e5\u6e05\u5355\n- [ ] \u9879\u76ee\u8bc4\u4ef7\u6307\u6807\n- [ ] \u5b66\u4e60\u8bb0\u5f55\u6a21\u677f\n- [ ] \u590d\u4e60\u56de\u987e\u6307\u5357\n- \ud83d\udd8a \u5176\u4ed6\u8ffd\u8e2a\uff1a[\u586b\u5199\u5176\u4ed6\u8ffd\u8e2a\u9700\u6c42]\n\n### 2. \u8f85\u52a9\u5de5\u5177\u4e0e\u8d44\u6e90\n\n#### 2.1 \u5f00\u53d1\u5de5\u5177\n\n- [ ] IDE\u63a8\u8350\u53ca\u914d\u7f6e\n- [ ] \u8c03\u8bd5\u5de5\u5177\u6e05\u5355\n- [ ] \u6548\u7387\u5de5\u5177\u63a8\u8350\n- [ ] \u73af\u5883\u642d\u5efa\u6307\u5357\n- \ud83d\udd8a \u5176\u4ed6\u5de5\u5177\uff1a[\u586b\u5199\u5176\u4ed6\u5de5\u5177\u9700\u6c42]\n\n#### 2.2 \u5b66\u4e60\u8d44\u6599\n\n- [ ] \u5b66\u4e60\u7b14\u8bb0\u6a21\u677f\n- [ ] \u793a\u4f8b\u4ee3\u7801\u5e93\n- [ ] \u6700\u4f73\u5b9e\u8df5\u6307\u5357\n- [ ] \u5e38\u89c1\u95ee\u9898\u89e3\u51b3\u65b9\u6848\n- \ud83d\udd8a \u5176\u4ed6\u8d44\u6599\uff1a[\u586b\u5199\u5176\u4ed6\u8d44\u6599\u9700\u6c42]\n\n### 3. \u804c\u4e1a\u53d1\u5c55\n\n#### 3.1 \u6280\u80fd\u6811\n\n- [ ] \u6838\u5fc3\u6280\u80fd\u56fe\u8c31\n- [ ] \u8fdb\u9636\u8def\u7ebf\u5efa\u8bae\n- [ ] \u4e13\u4e1a\u65b9\u5411\u89c4\u5212\n- [ ] \u6280\u672f\u6808\u5b8c\u6574\u5ea6\u8bc4\u4f30\n- \ud83d\udd8a \u5176\u4ed6\u89c4\u5212\uff1a[\u586b\u5199\u5176\u4ed6\u89c4\u5212\u9700\u6c42]\n\n#### 3.2 \u5b9e\u8df5\u6307\u5bfc\n\n- [ ] \u9879\u76ee\u5b9e\u6218\u6307\u5357\n- [ ] \u4ee3\u7801\u5ba1\u67e5\u6807\u51c6\n- [ ] \u6280\u672f\u9009\u578b\u5efa\u8bae\n- [ ] \u67b6\u6784\u8bbe\u8ba1\u539f\u5219\n- \ud83d\udd8a \u5176\u4ed6\u6307\u5bfc\uff1a[\u586b\u5199\u5176\u4ed6\u6307\u5bfc\u9700\u6c42]\n\n### 4. \u8f93\u51fa\u5f62\u5f0f\n\n#### 4.1 \u6587\u6863\u683c\u5f0f\n\n- [ ] Markdown\u6587\u6863\n- [ ] \u6d41\u7a0b\u56fe(draw.io/Mermaid)\n- [ ] \u7518\u7279\u56fe(Mermaid/PlantUML)\n- [ ] obsidian \u6587\u6863\n- \ud83d\udd8a \u5176\u4ed6\u683c\u5f0f\uff1a[\u586b\u5199\u5176\u4ed6\u683c\u5f0f\u9700\u6c42]\n\n---\n\n## \u8865\u5145\u8bf4\u660e\n\n\ud83d\udd8a \u7279\u6b8a\u9700\u6c42\uff1a[\u586b\u5199\u4efb\u4f55\u5176\u4ed6\u7279\u6b8a\u9700\u6c42\u6216\u8bf4\u660e]\n\n---\n</code></pre>"},{"location":"Tools/AI/prompt_writing/","title":"AI \u4f7f\u7528","text":""},{"location":"Tools/AI/prompt_writing/#ai","title":"AI \u4f7f\u7528","text":"<p> \u7ea6 3315 \u4e2a\u5b57  157 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 19 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"Tools/AI/prompt_writing/#1-prompt","title":"1 \u5982\u4f55\u5199\u4e00\u4e2a Prompt","text":""},{"location":"Tools/AI/prompt_writing/#11-prompt","title":"1.1 Prompt \u7684\u57fa\u672c\u539f\u5219","text":""},{"location":"Tools/AI/prompt_writing/#111","title":"1.1.1 \u660e\u786e\u9700\u6c42","text":""},{"location":"Tools/AI/prompt_writing/#1111","title":"1.1.1.1 \u4ec0\u4e48\u662f\u6e05\u6670\u7684\u6307\u4ee4\uff1f","text":"<p>\u6e05\u6670\u7684\u6307\u4ee4\u662f\u6307\u80fd\u591f\u51c6\u786e\u4f20\u8fbe\u4efb\u52a1\u610f\u56fe\u7684\u63cf\u8ff0\uff0c\u907f\u514d\u6b67\u4e49\uff0c\u8ba9\u6a21\u578b\u7406\u89e3\u5e76\u751f\u6210\u671f\u671b\u7684\u7ed3\u679c\u3002 \u5b83\u7684\u6838\u5fc3\u5728\u4e8e\u5177\u4f53\u5316\u9700\u6c42\uff0c\u901a\u8fc7\u660e\u786e\u7684\u8bed\u8a00\u548c\u7ed3\u6784\u5316\u7684\u63cf\u8ff0\uff0c\u8ba9\u4efb\u52a1\u76ee\u6807\u6613\u4e8e\u88ab\u6a21\u578b\u89e3\u6790\u3002</p>"},{"location":"Tools/AI/prompt_writing/#1112","title":"1.1.1.2 \u5982\u4f55\u8868\u8fbe\u9700\u6c42\u65e0\u6b67\u4e49\uff1f","text":"<ol> <li>\u4f7f\u7528\u5177\u4f53\u7684\u8bed\u8a00    \u4f8b\u5982\uff0c\u4e0d\u8981\u7b80\u5355\u8bf4\u201c\u751f\u6210\u6458\u8981\u201d\uff0c\u800c\u662f\u660e\u786e\u5185\u5bb9\u5f62\u5f0f\u548c\u8981\u6c42\uff1a </li> </ol> <ul> <li>\u274c \u4e0d\u6e05\u6670\uff1a\u603b\u7ed3\u4e00\u4e0b\u8fd9\u7bc7\u6587\u7ae0\u3002  </li> <li>\u2705 \u6e05\u6670\uff1a\u7528\u901a\u4fd7\u6613\u61c2\u7684\u8bed\u8a00\u5c06\u4ee5\u4e0b\u6587\u7ae0\u603b\u7ed3\u4e3a 3 \u70b9\uff0c\u5e76\u4ee5 Markdown \u5217\u8868\u7684\u5f62\u5f0f\u8f93\u51fa\u3002</li> </ul> <ol> <li>\u8bbe\u5b9a\u6e05\u6670\u7684\u8fb9\u754c\u548c\u9650\u5236    \u7ed9\u51fa\u660e\u786e\u7684\u8303\u56f4\uff0c\u907f\u514d\u6a21\u578b\u8f93\u51fa\u65e0\u5173\u4fe1\u606f\u3002  </li> </ol> <ul> <li>\u274c \u4e0d\u6e05\u6670\uff1a\u89e3\u91ca AI\u3002  </li> <li>\u2705 \u6e05\u6670\uff1a\u8bf7\u7528 2-3 \u53e5\u8bdd\u5411\u9ad8\u4e2d\u751f\u89e3\u91ca\u4ec0\u4e48\u662f AI\uff0c\u907f\u514d\u4f7f\u7528\u8fc7\u4e8e\u4e13\u4e1a\u7684\u672f\u8bed\u3002</li> </ul> <ol> <li>\u4f7f\u7528\u4efb\u52a1\u6307\u5411\u6027\u5f3a\u7684\u8bcd\u8bed    \u5f3a\u8c03\u4efb\u52a1\u7684\u6838\u5fc3\uff0c\u4f8b\u5982\u201c\u8be6\u7ec6\u8bf4\u660e\u201d\u201c\u4ee5\u7b80\u6d01\u8bed\u8a00\u603b\u7ed3\u201d\u201c\u5217\u51fa\u5177\u4f53\u6b65\u9aa4\u201d\u7b49\u3002</li> </ol>"},{"location":"Tools/AI/prompt_writing/#1113","title":"1.1.1.3 \u793a\u4f8b\uff1a\u6e05\u6670\u4e0e\u6a21\u7cca\u6307\u4ee4\u7684\u5bf9\u6bd4","text":"\u6a21\u7cca\u6307\u4ee4 \u6e05\u6670\u6307\u4ee4 \u603b\u7ed3\u4f1a\u8bae\u8bb0\u5f55\u3002 \u7528\u4e00\u4e2a\u6bb5\u843d\u603b\u7ed3\u4f1a\u8bae\u8bb0\u5f55\uff0c\u5e76\u5217\u51fa\u53d1\u8a00\u4eba\u53ca\u5176\u5efa\u8bae\u7684\u884c\u52a8\u9879\u76ee\uff0c\u4ee5 Markdown \u5217\u8868\u683c\u5f0f\u8f93\u51fa\u3002 \u89e3\u91ca\u5927\u6570\u636e\u3002 \u7528\u4e09\u53e5\u8bdd\u5411\u4e2d\u5b66\u751f\u89e3\u91ca\u5927\u6570\u636e\u7684\u5b9a\u4e49\u53ca\u4f5c\u7528\uff0c\u5e76\u63d0\u4f9b\u4e00\u4e2a\u4e0e\u65e5\u5e38\u751f\u6d3b\u76f8\u5173\u7684\u4f8b\u5b50\u3002 \u751f\u6210\u4e00\u4efd\u65c5\u884c\u8ba1\u5212\u3002 \u8bf7\u4e3a\u5317\u4eac\u4e09\u65e5\u6e38\u751f\u6210\u4e00\u4efd\u8be6\u7ec6\u7684\u65c5\u884c\u8ba1\u5212\uff0c\u5305\u542b\u6bcf\u5929\u7684\u884c\u7a0b\u3001\u666f\u70b9\u4ecb\u7ecd\u3001\u9884\u7b97\u8303\u56f4\u548c\u63a8\u8350\u7f8e\u98df\u3002"},{"location":"Tools/AI/prompt_writing/#112","title":"1.1.2 \u7b80\u6d01\u4e0e\u7cbe\u70bc","text":""},{"location":"Tools/AI/prompt_writing/#1121","title":"1.1.2.1 \u907f\u514d\u5197\u957f\u4e0e\u65e0\u6548\u4fe1\u606f\u7684\u65b9\u6cd5","text":"<p>\u5728 Prompt \u4e2d\uff0c\u5197\u957f\u7684\u63cf\u8ff0\u4f1a\u589e\u52a0\u6a21\u578b\u7684\u7406\u89e3\u96be\u5ea6\uff0c\u540c\u65f6\u53ef\u80fd\u5f15\u5165\u65e0\u5173\u5185\u5bb9\u3002\u4ee5\u4e0b\u6280\u5de7\u53ef\u4ee5\u5e2e\u52a9\u4f18\u5316\u8868\u8fbe\uff1a  </p> <ol> <li>\u5220\u51cf\u65e0\u7528\u4fe1\u606f\uff1a\u53bb\u6389\u4e0d\u5fc5\u8981\u7684\u4fee\u9970\u8bcd\u6216\u91cd\u590d\u5185\u5bb9\u3002  </li> <li> <ul> <li>\u274c \u5197\u957f\uff1a\u5728\u7528\u6765\u5199\u8fd9\u7bc7\u6587\u7ae0\u7684\u6458\u8981\u65f6\uff0c\u4f60\u53ef\u4ee5\u53c2\u8003\u4ee5\u4e0b\u8fd9\u4e9b\u6587\u7ae0\u7684\u5185\u5bb9\u2026\u2026  </li> <li>\u2705 \u7cbe\u70bc\uff1a\u4e3a\u4ee5\u4e0b\u6587\u7ae0\u5199\u6458\u8981\u3002  </li> </ul> </li> <li>\u76f4\u63a5\u5207\u5165\u91cd\u70b9\uff1a\u4f18\u5148\u63cf\u8ff0\u4efb\u52a1\u7684\u6838\u5fc3\u9700\u6c42\uff0c\u907f\u514d\u80cc\u666f\u4fe1\u606f\u8fc7\u591a\u5e72\u6270\u4efb\u52a1\u3002  </li> <li>\u5c42\u7ea7\u5206\u660e\uff1a\u4f7f\u7528\u7ed3\u6784\u5316\u683c\u5f0f\uff0c\u907f\u514d\u5c06\u591a\u6761\u6307\u4ee4\u6df7\u4e3a\u4e00\u8c08\u3002</li> </ol>"},{"location":"Tools/AI/prompt_writing/#1122","title":"1.1.2.2 \u201c\u5965\u5361\u59c6\u5243\u5200\u201d\u539f\u5219\u7684\u5b9e\u9645\u5e94\u7528","text":"<p>\u5965\u5361\u59c6\u5243\u5200\u539f\u5219\u5f3a\u8c03\u201c\u5982\u65e0\u5fc5\u8981\uff0c\u52ff\u589e\u5b9e\u4f53\u201d\uff0c\u5728 Prompt \u4e2d\uff0c\u8868\u73b0\u4e3a\u5c3d\u91cf\u51cf\u5c11\u4e0d\u5fc5\u8981\u7684\u7ea6\u675f\u548c\u9644\u52a0\u8981\u6c42\u3002  </p> <ul> <li>\u793a\u4f8b\uff1a  <ul> <li>\u4e0d\u5fc5\u8981\u7684\u7ea6\u675f\uff1a     \u8bf7\u7528 500 \u5b57\u5de6\u53f3\u603b\u7ed3\u4ee5\u4e0b\u6587\u672c\uff0c\u4e0d\u8981\u63d0\u5230\u4e0e\u6587\u672c\u65e0\u5173\u7684\u5185\u5bb9\uff0c\u4e5f\u4e0d\u8981\u52a0\u5165\u4e2a\u4eba\u89c2\u70b9\uff0c\u53ea\u9700\u7b80\u6d01\u6982\u62ec\u4e3b\u8981\u89c2\u70b9\u2026\u2026  </li> <li>\u4f18\u5316\u540e\uff1a     \u8bf7\u7528 500 \u5b57\u603b\u7ed3\u4ee5\u4e0b\u6587\u672c\u7684\u4e3b\u8981\u89c2\u70b9\uff0c\u8bed\u8a00\u7b80\u6d01\u660e\u4e86\u3002</li> </ul> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#113","title":"1.1.3 \u8bed\u6c14\u4e0e\u98ce\u683c","text":""},{"location":"Tools/AI/prompt_writing/#1131","title":"1.1.3.1 \u4f7f\u7528\u6b63\u5f0f\u3001\u793c\u8c8c\u7684\u8bed\u8a00\u63d0\u9ad8\u751f\u6210\u51c6\u786e\u6027","text":"<p>\u5728 Prompt \u4e2d\uff0c\u8bed\u6c14\u548c\u8bed\u8a00\u98ce\u683c\u4f1a\u5f71\u54cd\u6a21\u578b\u7684\u751f\u6210\u8d28\u91cf\u3002  </p> <ul> <li>\u6b63\u5f0f\u8bed\u8a00\u901a\u5e38\u66f4\u7b26\u5408\u5927\u6a21\u578b\u7684\u8bad\u7ec3\u6570\u636e\u5206\u5e03\uff0c\u6709\u52a9\u4e8e\u751f\u6210\u66f4\u4e25\u8c28\u7684\u5185\u5bb9\u3002  </li> <li>\u793a\u4f8b\uff1a  <ul> <li>\u6b63\u5f0f\uff1a\u8bf7\u7528\u901a\u4fd7\u6613\u61c2\u7684\u8bed\u8a00\u89e3\u91ca\u4ee5\u4e0b\u6280\u672f\u6982\u5ff5\u3002  </li> <li>\u975e\u6b63\u5f0f\uff1a\u5e2e\u6211\u628a\u8fd9\u6bb5\u8bdd\u7b80\u5355\u8bf4\u4e00\u4e0b\u3002</li> </ul> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#1132","title":"1.1.3.2 \u9488\u5bf9\u4e0d\u540c\u4efb\u52a1\u8c03\u6574\u8bed\u6c14\u7684\u6848\u4f8b","text":"<ol> <li>\u521b\u610f\u4efb\u52a1\uff1a    \u6307\u4ee4\u5e94\u66f4\u5177\u611f\u67d3\u529b\uff0c\u4ee5\u6fc0\u53d1\u6a21\u578b\u751f\u6210\u66f4\u5177\u60f3\u8c61\u529b\u7684\u5185\u5bb9\u3002 </li> </ol> <ul> <li>\u793a\u4f8b\uff1a  <ul> <li>\u4f60\u662f\u4e00\u4f4d\u5c0f\u7ea2\u4e66\u7206\u6b3e\u6587\u6848\u4e13\u5bb6\uff0c\u8bf7\u4e3a\u5e74\u8f7b\u4eba\u8bbe\u8ba1\u4e00\u4e2a\u5177\u6709\u5438\u5f15\u529b\u7684\u9752\u5c9b\u65c5\u6e38\u653b\u7565\u3002</li> </ul> </li> </ul> <ol> <li>\u6559\u80b2\u4efb\u52a1\uff1a    \u8bed\u6c14\u9700\u8981\u5faa\u5faa\u5584\u8bf1\uff0c\u5185\u5bb9\u7ed3\u6784\u6e05\u6670\u660e\u4e86\u3002  </li> </ol> <ul> <li>\u793a\u4f8b\uff1a  <ul> <li>\u4f60\u662f\u4e00\u540d\u9ad8\u4e2d\u6570\u5b66\u8001\u5e08\uff0c\u8bf7\u7528\u901a\u4fd7\u6613\u61c2\u7684\u65b9\u5f0f\u8bb2\u89e3\u4e8c\u6b21\u51fd\u6570\u7684\u6982\u5ff5\u3002</li> </ul> </li> </ul> <ol> <li>\u4e13\u4e1a\u4efb\u52a1\uff1a    \u8bed\u6c14\u5e94\u4e25\u8c28\uff0c\u4fe1\u606f\u9700\u7cbe\u786e\uff0c\u907f\u514d\u4e3b\u89c2\u6027\u8868\u8fbe\u3002 </li> </ol> <ul> <li>\u793a\u4f8b\uff1a  <ul> <li>\u8bf7\u4ece\u5b9a\u4e49\u3001\u7279\u6027\u548c\u5e94\u7528\u4e09\u4e2a\u65b9\u9762\u8be6\u7ec6\u8bf4\u660e\u533a\u5757\u94fe\u6280\u672f\uff0c\u5e76\u63d0\u4f9b\u76f8\u5173\u7684\u884c\u4e1a\u5b9e\u4f8b\u3002</li> </ul> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#12","title":"1.2 \u9ad8\u7ea7\u6280\u5de7","text":""},{"location":"Tools/AI/prompt_writing/#121","title":"1.2.1 \u63d0\u4f9b\u4e0a\u4e0b\u6587\u4e0e\u793a\u4f8b","text":""},{"location":"Tools/AI/prompt_writing/#1211-few-shot-prompt","title":"1.2.1.1 \u4f7f\u7528 Few-shot Prompt \u63d0\u4f9b\u6709\u6548\u793a\u4f8b","text":"<p>Few-shot Prompt \u662f\u6307\u5728\u63d0\u793a\u8bed\u4e2d\u63d0\u4f9b\u793a\u4f8b\u4ee5\u5f15\u5bfc\u6a21\u578b\u751f\u6210\u7c7b\u4f3c\u7684\u5185\u5bb9\u3002\u8fd9\u79cd\u65b9\u6cd5\u7279\u522b\u9002\u5408\u590d\u6742\u4efb\u52a1\u6216\u9700\u6c42\u4e0d\u660e\u786e\u7684\u573a\u666f\u3002</p> <ol> <li>\u4e3a\u4f55\u4f7f\u7528 Few-shot Prompt\uff1f</li> </ol> <ul> <li>\u964d\u4f4e\u6a21\u578b\u7684\u81ea\u7531\u53d1\u6325\u5ea6\uff1a\u901a\u8fc7\u63d0\u4f9b\u793a\u4f8b\uff0c\u9650\u5236\u6a21\u578b\u7684\u8f93\u51fa\u98ce\u683c\u548c\u7ed3\u6784\u3002</li> <li>\u63d0\u5347\u4efb\u52a1\u51c6\u786e\u6027\uff1a\u901a\u8fc7\u793a\u4f8b\u4f20\u9012\u660e\u786e\u7684\u6807\u51c6\uff0c\u51cf\u5c11\u504f\u5dee\u3002</li> <li>\u6269\u5c55\u6a21\u578b\u7684\u9002\u5e94\u80fd\u529b\uff1a\u5e2e\u52a9\u6a21\u578b\u9002\u5e94\u4e00\u4e9b\u8bad\u7ec3\u6570\u636e\u4e2d\u53ef\u80fd\u672a\u89c1\u8fc7\u7684\u573a\u666f\u3002</li> </ul> <ol> <li>\u8bbe\u8ba1 Few-shot Prompt \u7684\u5173\u952e\u70b9</li> </ol> <ul> <li>\u793a\u4f8b\u6570\u91cf\uff1a\u901a\u5e38 2-5 \u4e2a\u793a\u4f8b\u5373\u53ef\uff0c\u8fc7\u591a\u53ef\u80fd\u5bfc\u81f4\u63d0\u793a\u8fc7\u957f\uff0c\u589e\u52a0\u566a\u58f0\u3002</li> <li>\u8986\u76d6\u4e0d\u540c\u96be\u5ea6\u7684\u6848\u4f8b\uff1a\u5305\u62ec\u7b80\u5355\u573a\u666f\uff08easy case\uff09\u3001\u590d\u6742\u573a\u666f\uff08hard case\uff09\u4ee5\u53ca\u8fb9\u7f18\u60c5\u51b5\uff08corner case\uff09\u3002</li> <li>\u793a\u4f8b\u8d28\u91cf\uff1a\u786e\u4fdd\u63d0\u4f9b\u7684\u793a\u4f8b\u4e0e\u9884\u671f\u4efb\u52a1\u9ad8\u5ea6\u76f8\u5173\u3002</li> </ul> <ol> <li>\u793a\u4f8b\uff1a \u4efb\u52a1\uff1a\u5224\u65ad\u8f93\u5165\u662f\u5426\u5c5e\u4e8e\u77e5\u8bc6\u95ee\u7b54\u7c7b\u95ee\u9898\u3002  </li> </ol> <p>Few-shot Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u5224\u65ad\u4ee5\u4e0b\u95ee\u9898\u662f\u5426\u5c5e\u4e8e\u77e5\u8bc6\u95ee\u7b54\u7c7b\u95ee\u9898\u3002\n\n\u95ee\u9898\uff1a\u4e16\u754c\u4e0a\u6700\u9ad8\u7684\u5c71\u662f\u4ec0\u4e48\uff1f # easy case\uff0c\u5c5e\u4e8e\u5ba2\u89c2\u77e5\u8bc6\u95ee\u7b54\n\u7b54\u6848\uff1a\u662f\n\n\u95ee\u9898\uff1a\u4e3a\u4ec0\u4e48\u6c34\u80fd\u4f20\u5bfc\u7535\uff1f # hard case\uff0c\u5c5e\u4e8e\u79d1\u5b66\u539f\u7406\u95ee\u7b54\n\u7b54\u6848\uff1a\u662f\n\n\u95ee\u9898\uff1a\u5e2e\u6211\u5199\u4e00\u7bc7\u65c5\u884c\u65e5\u8bb0\u3002 # easy case\uff0c\u5c5e\u4e8e\u521b\u4f5c\u7c7b\u4efb\u52a1\n\u7b54\u6848\uff1a\u5426\n\n\u95ee\u9898\uff1a\u4ec0\u4e48\u662f\u5d4c\u5957\u5b57\u5178\uff1f # hard case\uff0c\u5c5e\u4e8e\u6280\u672f\u77e5\u8bc6\u95ee\u7b54\n\u7b54\u6848\uff1a\u662f\n\n\u95ee\u9898\uff1a{\u8f93\u5165}\n\u7b54\u6848\uff1a\n</code></pre>"},{"location":"Tools/AI/prompt_writing/#1212","title":"1.2.1.2 \u53c2\u8003\u6587\u672c\u7684\u4f7f\u7528\u4e0e\u5f15\u7528\u6280\u5de7","text":"<p>\u53c2\u8003\u6587\u672c\u80fd\u4e3a\u6a21\u578b\u63d0\u4f9b\u660e\u786e\u7684\u77e5\u8bc6\u57fa\u7840\uff0c\u5c24\u5176\u5728\u9700\u8981\u53ef\u9760\u6027\u548c\u51c6\u786e\u6027\u7684\u4efb\u52a1\u4e2d\u6548\u679c\u663e\u8457\u3002</p> <ol> <li>\u8ba9\u6a21\u578b\u4f7f\u7528\u53c2\u8003\u6587\u672c\u4f5c\u7b54</li> </ol> <ul> <li>\u7ed9\u6a21\u578b\u660e\u786e\u6307\u4ee4\uff0c\u53ea\u5141\u8bb8\u4f9d\u636e\u53c2\u8003\u6587\u672c\u751f\u6210\u7b54\u6848\u3002</li> <li> <p>\u793a\u4f8b\uff1a</p> Text Only<pre><code>\u4f7f\u7528\u4ee5\u4e0b\u7531\u4e09\u5f15\u53f7\u5206\u9694\u7684\u6587\u672c\u56de\u7b54\u95ee\u9898\u3002\u5982\u679c\u5728\u6587\u672c\u4e2d\u627e\u4e0d\u5230\u7b54\u6848\uff0c\u8bf7\u56de\u590d\u201c\u4fe1\u606f\u4e0d\u8db3\u201d\u3002\n\"\"\"\n\u5927\u718a\u732b\u4e3b\u8981\u5206\u5e03\u5728\u4e2d\u56fd\u56db\u5ddd\u3001\u9655\u897f\u548c\u7518\u8083\u7b49\u5730\u3002\u5b83\u4eec\u4ee5\u7af9\u5b50\u4e3a\u4e3b\u98df\u3002\n\"\"\"\n\u95ee\u9898\uff1a\u5927\u718a\u732b\u7684\u5206\u5e03\u8303\u56f4\u6709\u54ea\u4e9b\uff1f\n</code></pre> </li> </ul> <ol> <li>\u5f15\u7528\u53c2\u8003\u6587\u672c\u4e2d\u7684\u6bb5\u843d</li> </ol> <ul> <li>\u8981\u6c42\u6a21\u578b\u5728\u56de\u7b54\u4e2d\u6807\u6ce8\u5f15\u7528\u6765\u6e90\uff0c\u589e\u52a0\u7b54\u6848\u7684\u53ef\u9a8c\u8bc1\u6027\u3002</li> <li> <p>\u793a\u4f8b\uff1a</p> Text Only<pre><code>\u60a8\u5c06\u83b7\u5f97\u4e00\u6bb5\u6587\u6863\u548c\u4e00\u4e2a\u95ee\u9898\u3002\u4ec5\u4f7f\u7528\u6587\u6863\u56de\u7b54\u95ee\u9898\uff0c\u5e76\u6807\u6ce8\u5f15\u7528\u6bb5\u843d\u3002\u5982\u679c\u7b54\u6848\u7f3a\u4e4f\u4fe1\u606f\uff0c\u8bf7\u56de\u590d\u201c\u65e0\u6cd5\u56de\u7b54\u201d\u3002\n\u6587\u6863\uff1a\n\"\"\"\n\u673a\u5668\u5b66\u4e60\u662f\u901a\u8fc7\u6570\u636e\u8bad\u7ec3\u6a21\u578b\u7684\u4e00\u79cd\u65b9\u6cd5\u3002\u6df1\u5ea6\u5b66\u4e60\u662f\u673a\u5668\u5b66\u4e60\u7684\u4e00\u4e2a\u5206\u652f\uff0c\u4ee5\u591a\u5c42\u795e\u7ecf\u7f51\u7edc\u4e3a\u6838\u5fc3\u3002\n\"\"\"\n\u95ee\u9898\uff1a\u4ec0\u4e48\u662f\u6df1\u5ea6\u5b66\u4e60\uff1f\n\u56de\u7b54\uff1a\n\u6df1\u5ea6\u5b66\u4e60\u662f\u673a\u5668\u5b66\u4e60\u7684\u4e00\u4e2a\u5206\u652f\uff0c\u4ee5\u591a\u5c42\u795e\u7ecf\u7f51\u7edc\u4e3a\u6838\u5fc3\uff08\u5f15\u7528\uff1a\u7b2c1\u6bb5\uff09\u3002\n</code></pre> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#122","title":"1.2.2 \u4efb\u52a1\u5206\u89e3","text":""},{"location":"Tools/AI/prompt_writing/#1221","title":"1.2.2.1 \u5c06\u590d\u6742\u4efb\u52a1\u62c6\u89e3\u4e3a\u5b50\u4efb\u52a1\u7684\u6700\u4f73\u5b9e\u8df5","text":"<p>\u590d\u6742\u4efb\u52a1\u53ef\u80fd\u6d89\u53ca\u591a\u4e2a\u5b50\u76ee\u6807\uff0c\u5c06\u5176\u5206\u89e3\u4e3a\u6e05\u6670\u7684\u6b65\u9aa4\u53ef\u4ee5\u63d0\u9ad8\u6a21\u578b\u7684\u8868\u73b0\u3002</p> <ol> <li>\u4e3a\u4f55\u5206\u89e3\u4efb\u52a1\uff1f</li> </ol> <ul> <li>\u964d\u4f4e\u6a21\u578b\u7406\u89e3\u96be\u5ea6\u3002</li> <li>\u66f4\u5bb9\u6613\u5bf9\u751f\u6210\u7ed3\u679c\u8fdb\u884c\u9a8c\u8bc1\u3002</li> <li>\u589e\u5f3a Prompt \u7684\u590d\u7528\u6027\u3002</li> </ul> <ol> <li>\u4efb\u52a1\u5206\u89e3\u65b9\u6cd5</li> </ol> <ul> <li>\u660e\u786e\u6bcf\u4e00\u6b65\u7684\u76ee\u6807\uff1a\u9010\u5c42\u5256\u6790\u95ee\u9898\uff0c\u5c06\u590d\u6742\u4efb\u52a1\u5206\u89e3\u4e3a\u7b80\u5355\u5b50\u4efb\u52a1\u3002</li> <li>\u4efb\u52a1\u4f9d\u8d56\u7ba1\u7406\uff1a\u786e\u4fdd\u6bcf\u4e00\u6b65\u4e3a\u4e0b\u4e00\u6b65\u63d0\u4f9b\u5fc5\u8981\u7684\u8f93\u5165\u3002</li> </ul> <ol> <li>\u793a\u4f8b\uff1a </li> </ol> <p>\u4efb\u52a1\uff1a\u751f\u6210\u4f1a\u8bae\u7eaa\u8981\u3002  </p> <p>\u4efb\u52a1\u5206\u89e3 Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u6309\u7167\u4ee5\u4e0b\u6b65\u9aa4\u5b8c\u6210\u4efb\u52a1\uff1a\n1. \u9605\u8bfb\u4ee5\u4e0b\u4f1a\u8bae\u8bb0\u5f55\u6587\u672c\u3002\n2. \u63d0\u53d6\u53d1\u8a00\u4eba\u53ca\u5176\u89c2\u70b9\u3002\n3. \u7528 Markdown \u5217\u8868\u683c\u5f0f\u603b\u7ed3\u4f1a\u8bae\u7684\u4e3b\u8981\u7ed3\u8bba\u3002\n\u6587\u672c\uff1a{\u4f1a\u8bae\u8bb0\u5f55}\n</code></pre>"},{"location":"Tools/AI/prompt_writing/#1222-chain-of-thought-cot","title":"1.2.2.2 \u8fde\u7eed\u751f\u6210\u4efb\u52a1\u7684\u94fe\u5f0f\u601d\u8003\uff08Chain of Thought, CoT\uff09","text":"<p>CoT \u662f\u4e00\u79cd\u9010\u6b65\u601d\u8003\u7684\u63d0\u793a\u7b56\u7565\uff0c\u9002\u7528\u4e8e\u9700\u8981\u903b\u8f91\u63a8\u7406\u7684\u4efb\u52a1\u3002</p> <ol> <li>\u4e3a\u4f55\u4f7f\u7528 CoT\uff1f</li> </ol> <ul> <li>\u5e2e\u52a9\u6a21\u578b\u5c06\u590d\u6742\u4efb\u52a1\u5206\u89e3\u4e3a\u4e00\u7cfb\u5217\u6613\u4e8e\u89e3\u51b3\u7684\u5c0f\u4efb\u52a1\u3002</li> <li>\u63d0\u5347\u903b\u8f91\u63a8\u7406\u80fd\u529b\uff0c\u5c24\u5176\u9002\u7528\u4e8e\u6570\u5b66\u3001\u63a8\u7406\u6216\u590d\u6742\u95ee\u9898\u3002</li> </ul> <ol> <li>\u8bbe\u8ba1 CoT Prompt \u7684\u5173\u952e</li> </ol> <ul> <li>\u6307\u5bfc\u6a21\u578b\u9010\u6b65\u5b8c\u6210\u4efb\u52a1\u3002</li> <li>\u5f3a\u8c03\u201c\u601d\u8003\u8fc7\u7a0b\u201d\u5e76\u8f93\u51fa\u6b65\u9aa4\u3002</li> </ul> <ol> <li>\u793a\u4f8b\uff1a  </li> </ol> <p>\u4efb\u52a1\uff1a\u8ba1\u7b97 \\((1362+5145)*145-(1517*42+24)\\) \u7684\u7ed3\u679c\u3002  </p> <p>CoT Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u5e2e\u6211\u8ba1\u7b97\u4ee5\u4e0b\u95ee\u9898\u7684\u7ed3\u679c\uff1a$(1362+5145)*145-(1517*42+24)$\u3002\n\u5c55\u793a\u4f60\u7684\u6bcf\u4e00\u6b65\u8ba1\u7b97\u8fc7\u7a0b\uff0c\u5e76\u786e\u4fdd\u8ba1\u7b97\u6b63\u786e\u3002\n</code></pre> <p>\u6a21\u578b\u751f\u6210\u793a\u4f8b\uff1a  </p> Text Only<pre><code>\u7b2c\u4e00\u6b65\uff1a\u8ba1\u7b97 (1362+5145)\uff0c\u7ed3\u679c\u4e3a 6507\u3002\n\u7b2c\u4e8c\u6b65\uff1a\u8ba1\u7b97 6507*145\uff0c\u7ed3\u679c\u4e3a 943515\u3002\n\u7b2c\u4e09\u6b65\uff1a\u8ba1\u7b97 1517*42\uff0c\u7ed3\u679c\u4e3a 63654\u3002\n\u7b2c\u56db\u6b65\uff1a\u8ba1\u7b97 63654+24\uff0c\u7ed3\u679c\u4e3a 63678\u3002\n\u7b2c\u4e94\u6b65\uff1a\u8ba1\u7b97 943515-63678\uff0c\u7ed3\u679c\u4e3a 879837\u3002\n\u7b54\u6848\uff1a879837\u3002\n</code></pre>"},{"location":"Tools/AI/prompt_writing/#1223","title":"1.2.2.3 \u793a\u4f8b\uff1a\u591a\u6b65\u9aa4\u4efb\u52a1\u7684\u5206\u89e3\u4e0e\u4f18\u5316","text":"<p>\u4efb\u52a1\uff1a\u64b0\u5199\u4e00\u4efd\u4ea7\u54c1\u8bbe\u8ba1\u6587\u6863\uff0c\u5305\u62ec\u9700\u6c42\u3001\u529f\u80fd\u5217\u8868\u3001\u8bbe\u8ba1\u65b9\u6848\u3002  </p> <p>\u591a\u6b65\u9aa4 Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u6309\u7167\u4ee5\u4e0b\u6b65\u9aa4\u64b0\u5199\u4e00\u4efd\u4ea7\u54c1\u8bbe\u8ba1\u6587\u6863\uff1a\n1. \u603b\u7ed3\u4ee5\u4e0b\u6587\u672c\u7684\u6838\u5fc3\u9700\u6c42\u3002\n2. \u6839\u636e\u9700\u6c42\u751f\u6210\u529f\u80fd\u5217\u8868\u3002\n3. \u4e3a\u6bcf\u4e2a\u529f\u80fd\u8bbe\u8ba1\u4e00\u4e2a\u8be6\u7ec6\u7684\u65b9\u6848\u3002\n\u6587\u672c\uff1a{\u8f93\u5165}\n</code></pre> <p>\u6a21\u578b\u8f93\u51fa\u793a\u4f8b\uff1a  </p> Text Only<pre><code>\u6838\u5fc3\u9700\u6c42\uff1a\u7528\u6237\u5e0c\u671b\u901a\u8fc7\u5e94\u7528\u5feb\u901f\u83b7\u53d6\u9644\u8fd1\u7684\u9910\u996e\u63a8\u8350\u3002\n\u529f\u80fd\u5217\u8868\uff1a\n- \u9910\u996e\u63a8\u8350\u7cfb\u7edf\n- \u7528\u6237\u504f\u597d\u8bbe\u7f6e\n- \u5730\u56fe\u5bfc\u822a\n\n\u8bbe\u8ba1\u65b9\u6848\uff1a\n- \u9910\u996e\u63a8\u8350\u7cfb\u7edf\uff1a\u6839\u636e\u7528\u6237\u4f4d\u7f6e\u548c\u504f\u597d\u5b9e\u65f6\u63a8\u8350\u9644\u8fd1\u7684\u9910\u9986\u3002\n- \u7528\u6237\u504f\u597d\u8bbe\u7f6e\uff1a\u5141\u8bb8\u7528\u6237\u81ea\u5b9a\u4e49\u53e3\u5473\u3001\u9884\u7b97\u548c\u83dc\u7cfb\u3002\n- \u5730\u56fe\u5bfc\u822a\uff1a\u63d0\u4f9b\u9910\u9986\u7684\u5b9e\u65f6\u4f4d\u7f6e\u548c\u6700\u4f73\u8def\u7ebf\u3002\n</code></pre>"},{"location":"Tools/AI/prompt_writing/#123","title":"1.2.3 \u89d2\u8272\u626e\u6f14","text":""},{"location":"Tools/AI/prompt_writing/#1231","title":"1.2.3.1 \u6307\u5b9a\u6a21\u578b\u8eab\u4efd\u7684\u4f18\u52bf","text":"<p>\u901a\u8fc7\u4e3a\u6a21\u578b\u8bbe\u7f6e\u89d2\u8272\uff0c\u53ef\u4ee5\u5e2e\u52a9\u5176\u4ee5\u66f4\u9002\u5408\u4efb\u52a1\u7684\u65b9\u5f0f\u751f\u6210\u5185\u5bb9\u3002\u6a21\u578b\u89d2\u8272\u7684\u6307\u5b9a\u7c7b\u4f3c\u4e8e\u8bbe\u5b9a\u8bed\u5883\uff0c\u80fd\u591f\u66f4\u7cbe\u51c6\u5730\u63a7\u5236\u751f\u6210\u5185\u5bb9\u7684\u8bed\u8a00\u98ce\u683c\u3001\u7ec6\u8282\u548c\u4e13\u4e1a\u6027\u3002</p> <ol> <li>\u4e3a\u4ec0\u4e48\u9700\u8981\u89d2\u8272\u626e\u6f14\uff1f</li> </ol> <ul> <li>\u63d0\u9ad8\u751f\u6210\u51c6\u786e\u6027\uff1a\u6307\u5b9a\u89d2\u8272\u540e\uff0c\u6a21\u578b\u7684\u56de\u7b54\u4f1a\u66f4\u805a\u7126\u4e8e\u8be5\u89d2\u8272\u7684\u77e5\u8bc6\u9886\u57df\u3002</li> <li>\u589e\u5f3a\u8f93\u51fa\u98ce\u683c\u7684\u4e00\u81f4\u6027\uff1a\u6839\u636e\u89d2\u8272\u7684\u8bbe\u5b9a\uff0c\u8f93\u51fa\u4f1a\u7b26\u5408\u9884\u671f\u7684\u4e13\u4e1a\u6027\u6216\u521b\u610f\u6027\u3002</li> </ul> <ol> <li>\u793a\u4f8b</li> </ol> <ul> <li> <p>\u4efb\u52a1\uff1a\u64b0\u5199\u65c5\u6e38\u653b\u7565\u3002  </p> <p>Prompt\uff1a</p> Text Only<pre><code>\u4f60\u662f\u4e00\u4f4d\u64c5\u957f\u64b0\u5199\u65c5\u6e38\u6587\u6848\u7684\u5c0f\u7ea2\u4e66\u5185\u5bb9\u521b\u4f5c\u8005\uff0c\u8bf7\u64b0\u5199\u4e00\u4efd\u5173\u4e8e\u9752\u5c9b\u4e09\u65e5\u6e38\u7684\u653b\u7565\uff0c\u5f3a\u8c03\u666f\u70b9\u63a8\u8350\u3001\u7f8e\u98df\u5206\u4eab\u548c\u6444\u5f71\u6280\u5de7\u3002\n</code></pre> </li> <li> <p>\u4efb\u52a1\uff1a\u89e3\u91ca\u7f16\u7a0b\u6982\u5ff5\u3002  </p> <p>Prompt\uff1a</p> Text Only<pre><code>\u4f60\u662f\u4e00\u540d\u7ecf\u9a8c\u4e30\u5bcc\u7684 Python \u5f00\u53d1\u8005\uff0c\u8bf7\u7528\u901a\u4fd7\u6613\u61c2\u7684\u8bed\u8a00\u89e3\u91ca\u4ee5\u4e0b\u4ee3\u7801\u7684\u529f\u80fd\uff0c\u5e76\u63d0\u4f9b\u6539\u8fdb\u5efa\u8bae\uff1a\n</code></pre> <p>\u4ee3\u7801\u793a\u4f8b\uff1a  </p> Python<pre><code>nested_dict = lambda: defaultdict(nested_dict)\n</code></pre> </li> </ul> <ol> <li>\u591a\u89d2\u8272\u7ed3\u5408</li> </ol> <ul> <li>\u5728\u590d\u6742\u4efb\u52a1\u4e2d\uff0c\u591a\u4e2a\u89d2\u8272\u53ef\u4ee5\u5206\u62c5\u4e0d\u540c\u90e8\u5206\u7684\u751f\u6210\u4efb\u52a1\u3002</li> <li> <p>\u793a\u4f8b\uff1a  </p> Text Only<pre><code>\u4f60\u662f\u4e00\u4f4d\u6570\u636e\u79d1\u5b66\u5bb6\uff0c\u8bf7\u5206\u6790\u4ee5\u4e0b\u6570\u636e\u7684\u6a21\u5f0f\uff1b\u7136\u540e\u4f5c\u4e3a\u4e00\u540d\u5e02\u573a\u5206\u6790\u5e08\uff0c\u63d0\u51fa\u4f18\u5316\u65b9\u6848\u3002\n\u6570\u636e\uff1a{\u6570\u636e\u5185\u5bb9}\n</code></pre> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#124","title":"1.2.4 \u683c\u5f0f\u5316\u4e0e\u7ed3\u6784\u5316\u8f93\u51fa","text":""},{"location":"Tools/AI/prompt_writing/#1241-json","title":"1.2.4.1 JSON\u3001\u8868\u683c\u3001\u6e05\u5355\u7b49\u8f93\u51fa\u683c\u5f0f\u7684\u5e94\u7528\u573a\u666f","text":"<p>\u4e3a\u4fdd\u8bc1\u8f93\u51fa\u7684\u6613\u8bfb\u6027\u548c\u4fbf\u4e8e\u540e\u7eed\u5904\u7406\uff0c\u53ef\u4ee5\u660e\u786e\u8981\u6c42\u6a21\u578b\u8fd4\u56de\u7ed3\u679c\u7684\u683c\u5f0f\u5316\u8f93\u51fa\u3002\u4f8b\u5982\uff0cJSON \u683c\u5f0f\u9002\u5408\u6570\u636e\u5904\u7406\uff0c\u8868\u683c\u9002\u5408\u603b\u7ed3\u5206\u6790\uff0c\u6e05\u5355\u9002\u5408\u4efb\u52a1\u5206\u89e3\u3002</p> <ol> <li>\u4e3a\u4ec0\u4e48\u9700\u8981\u7ed3\u6784\u5316\u8f93\u51fa\uff1f</li> </ol> <ul> <li>\u63d0\u9ad8\u53ef\u8bfb\u6027\uff1a\u8f93\u51fa\u6613\u4e8e\u76f4\u63a5\u67e5\u770b\u548c\u7406\u89e3\u3002</li> <li>\u4fbf\u4e8e\u540e\u7eed\u5904\u7406\uff1a\u5c24\u5176\u5728\u6570\u636e\u5904\u7406\u6216\u7f16\u7a0b\u4efb\u52a1\u4e2d\uff0c\u7ed3\u6784\u5316\u6570\u636e\u53ef\u76f4\u63a5\u7528\u4e8e\u5176\u4ed6\u5de5\u5177\u6216\u4ee3\u7801\u3002</li> </ul> <ol> <li>\u793a\u4f8b</li> </ol> <ul> <li> <p>\u4efb\u52a1\uff1a\u63d0\u53d6\u6587\u672c\u4e2d\u7684\u5173\u952e\u4fe1\u606f\u5e76\u8fd4\u56de JSON \u683c\u5f0f\u3002  </p> <p>Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u4ece\u4ee5\u4e0b\u6587\u672c\u4e2d\u63d0\u53d6\u5173\u952e\u4fe1\u606f\uff0c\u5305\u62ec\u4eba\u540d\u3001\u5730\u540d\u548c\u4e8b\u4ef6\uff0c\u4ee5 JSON \u683c\u5f0f\u8fd4\u56de\uff1a\n\u6587\u672c\uff1a{\u6587\u672c\u5185\u5bb9}\n\u8f93\u51fa\u683c\u5f0f\uff1a\n{\n    \"\u4eba\u540d\": [\"\u4eba\u540d1\", \"\u4eba\u540d2\"],\n    \"\u5730\u540d\": [\"\u5730\u540d1\", \"\u5730\u540d2\"],\n    \"\u4e8b\u4ef6\": [\"\u4e8b\u4ef61\", \"\u4e8b\u4ef62\"]\n}\n</code></pre> </li> <li> <p>\u4efb\u52a1\uff1a\u603b\u7ed3\u4f1a\u8bae\u8bb0\u5f55\u5e76\u751f\u6210\u8868\u683c\u3002  </p> <p>Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u603b\u7ed3\u4ee5\u4e0b\u4f1a\u8bae\u8bb0\u5f55\uff0c\u5e76\u5c06\u53d1\u8a00\u4eba\u53ca\u5176\u89c2\u70b9\u4ee5 Markdown \u8868\u683c\u7684\u5f62\u5f0f\u8f93\u51fa\u3002\n</code></pre> <p>\u6a21\u578b\u751f\u6210\u793a\u4f8b\uff1a  </p> Markdown<pre><code>| \u53d1\u8a00\u4eba   | \u89c2\u70b9                  |\n|----------|-----------------------|\n| \u5f20\u4e09     | \u5f3a\u8c03\u5e02\u573a\u6269\u5f20\u7684\u91cd\u8981\u6027 |\n| \u674e\u56db     | \u63d0\u8bae\u63d0\u9ad8\u7814\u53d1\u9884\u7b97      |\n</code></pre> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#1242","title":"1.2.4.2 \u4f7f\u7528\u5206\u9694\u7b26\uff08\u5982\u4e09\u5f15\u53f7\uff09\u660e\u786e\u4efb\u52a1\u7ed3\u6784","text":"<p>\u5206\u9694\u7b26\u53ef\u4ee5\u5e2e\u52a9\u533a\u5206\u4efb\u52a1\u63cf\u8ff0\u548c\u8f93\u5165\u5185\u5bb9\uff0c\u51cf\u8f7b\u6a21\u578b\u7684\u7406\u89e3\u8d1f\u62c5\u3002</p> <ol> <li>\u5178\u578b\u7528\u6cd5</li> </ol> <ul> <li> <p>\u660e\u786e\u8f93\u5165\u4e0e\u8f93\u51fa\u90e8\u5206\uff1a</p> Text Only<pre><code>\u4f7f\u7528\u4e09\u5f15\u53f7\u5206\u9694\u7684\u6587\u672c\u5b8c\u6210\u4efb\u52a1\uff1a\n\"\"\"\n{\u8f93\u5165\u5185\u5bb9}\n\"\"\"\n\u8bf7\u4e3a\u4e0a\u8ff0\u5185\u5bb9\u64b0\u5199\u6458\u8981\uff0c\u6458\u8981\u9700\u5305\u542b\u4e3b\u8981\u89c2\u70b9\uff0c\u5e76\u4ee5 Markdown \u5217\u8868\u5f62\u5f0f\u8f93\u51fa\u3002\n</code></pre> </li> </ul> <ol> <li>\u51cf\u5c11\u566a\u58f0\u5e72\u6270</li> </ol> <ul> <li> <p>\u5c06\u591a\u6bb5\u8f93\u5165\u5206\u5757\uff1a</p> Text Only<pre><code>\u7b2c1\u90e8\u5206\uff1a\n\"\"\"\n{\u7b2c\u4e00\u6bb5\u5185\u5bb9}\n\"\"\"\n\u7b2c2\u90e8\u5206\uff1a\n\"\"\"\n{\u7b2c\u4e8c\u6bb5\u5185\u5bb9}\n\"\"\"\n\u8bf7\u5206\u522b\u603b\u7ed3\u4ee5\u4e0a\u4e24\u90e8\u5206\u5185\u5bb9\uff0c\u5e76\u4ee5 Markdown \u5217\u8868\u5f62\u5f0f\u8f93\u51fa\u3002\n</code></pre> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#1243","title":"1.2.4.3 \u793a\u4f8b\uff1a\u4ece\u65e0\u683c\u5f0f\u5230\u6807\u51c6\u5316\u8f93\u51fa\u7684\u8f6c\u53d8","text":"<p>\u4efb\u52a1\uff1a\u4e3a\u4e00\u6bb5\u4ea7\u54c1\u8bc4\u8bba\u751f\u6210\u7ed3\u6784\u5316\u6458\u8981\u3002  </p> <p>\u65e0\u683c\u5f0f\u7684\u6307\u4ee4\uff1a</p> Text Only<pre><code>\u8bf7\u603b\u7ed3\u4ee5\u4e0b\u4ea7\u54c1\u8bc4\u8bba\uff1a\n{\u8bc4\u8bba\u5185\u5bb9}\n</code></pre> <p>\u6807\u51c6\u5316\u7684\u6307\u4ee4\uff1a</p> Text Only<pre><code>\u8bf7\u603b\u7ed3\u4ee5\u4e0b\u4ea7\u54c1\u8bc4\u8bba\uff0c\u5e76\u4ee5\u8868\u683c\u5f62\u5f0f\u8f93\u51fa\u3002\u8868\u683c\u5e94\u5305\u542b\u4ee5\u4e0b\u5b57\u6bb5\uff1a\u4f18\u70b9\u3001\u7f3a\u70b9\u3001\u5efa\u8bae\u3002\n\u8bc4\u8bba\uff1a\n\"\"\"\n{\u8bc4\u8bba\u5185\u5bb9}\n\"\"\"\n</code></pre> <p>\u8f93\u51fa\u793a\u4f8b\uff1a</p> Markdown<pre><code>| \u4f18\u70b9            | \u7f3a\u70b9           | \u5efa\u8bae               |\n|-----------------|---------------|--------------------|\n| \u4ef7\u683c\u4fbf\u5b9c        | \u505a\u5de5\u4e00\u822c       | \u6539\u5584\u4ea7\u54c1\u5916\u89c2\u8bbe\u8ba1    |\n| \u529f\u80fd\u9f50\u5168        | \u64cd\u4f5c\u590d\u6742       | \u7b80\u5316\u7528\u6237\u64cd\u4f5c\u6d41\u7a0b    |\n</code></pre>"},{"location":"Tools/AI/prompt_writing/#13","title":"1.3 \u4f18\u5316\u4e0e\u8fed\u4ee3","text":""},{"location":"Tools/AI/prompt_writing/#131-ai-prompt","title":"1.3.1 \u5982\u4f55\u901a\u8fc7 AI \u5e2e\u52a9\u6539\u5199\u6216\u4f18\u5316 Prompt\uff1f","text":""},{"location":"Tools/AI/prompt_writing/#1311-ai-prompt","title":"1.3.1.1 \u4e3a\u4ec0\u4e48\u8ba9 AI \u4f18\u5316 Prompt\uff1f","text":"<p>AI \u64c5\u957f\u4ece\u5c11\u91cf\u8f93\u5165\u4e2d\u63d0\u53d6\u89c4\u5f8b\uff0c\u53ef\u4ee5\u5feb\u901f\u8c03\u6574\u8bed\u8a00\u98ce\u683c\u548c\u7ec6\u8282\uff0c\u5e2e\u52a9\u7528\u6237\u4f18\u5316 Prompt\uff0c\u5c24\u5176\u5728\u4efb\u52a1\u9700\u6c42\u6a21\u7cca\u6216\u7f3a\u4e4f\u6e05\u6670\u6307\u4ee4\u7684\u60c5\u51b5\u4e0b\u3002</p>"},{"location":"Tools/AI/prompt_writing/#1312","title":"1.3.1.2 \u5177\u4f53\u65b9\u6cd5","text":"<ol> <li>\u76f4\u63a5\u8bf7\u6c42 AI \u6539\u8fdb</li> </ol> <ul> <li>\u63d0\u4f9b\u521d\u59cb Prompt\uff0c\u8ba9 AI \u63d0\u51fa\u4f18\u5316\u5efa\u8bae\u3002  </li> <li> <p>\u793a\u4f8b\uff1a \u539f\u59cb Prompt\uff1a</p> Text Only<pre><code>\u8bf7\u7528\u7b80\u5355\u7684\u8bed\u8a00\u89e3\u91ca\u4ee5\u4e0b\u6570\u5b66\u9898\u7684\u89e3\u6cd5\u3002\n</code></pre> <p>\u8bf7\u6c42\u4f18\u5316\uff1a  </p> Text Only<pre><code>\u8bf7\u5e2e\u52a9\u4f18\u5316\u8fd9\u6bb5 Prompt\uff0c\u8ba9\u5b83\u66f4\u9002\u5408\u5c0f\u5b66\u516d\u5e74\u7ea7\u5b66\u751f\u3002\n</code></pre> <p>\u4f18\u5316\u7ed3\u679c\uff1a</p> Text Only<pre><code>\u4f60\u662f\u4e00\u4f4d\u5c0f\u5b66\u6570\u5b66\u8001\u5e08\uff0c\u8bf7\u7528\u901a\u4fd7\u6613\u61c2\u7684\u8bed\u8a00\uff0c\u7ed3\u5408\u751f\u6d3b\u4e2d\u7684\u4f8b\u5b50\uff0c\u89e3\u91ca\u4ee5\u4e0b\u6570\u5b66\u9898\u7684\u89e3\u6cd5\u3002\n</code></pre> </li> </ul> <ol> <li>\u901a\u8fc7\u51e0\u8f6e\u4ea4\u4e92\u5fae\u8c03 Prompt</li> </ol> <ul> <li> <p>\u793a\u4f8b\uff1a \u7b2c1\u8f6e\u4f18\u5316\uff1a  </p> Text Only<pre><code>\u8fd9\u4e2a Prompt \u6bd4\u8f83\u9002\u5408\u521d\u5b66\u8005\uff0c\u4f46\u53ef\u4ee5\u589e\u52a0\u4e00\u4e9b\u751f\u6d3b\u5316\u7684\u4f8b\u5b50\u6765\u63d0\u5347\u5438\u5f15\u529b\u3002\n</code></pre> </li> <li> <p>\u7b2c2\u8f6e\u4f18\u5316\uff1a  </p> Text Only<pre><code>\u7ed3\u5408\u751f\u6d3b\u4e2d\u7684\u5b9e\u4f8b\u8865\u5145\uff0c\u5982\u201c\u901a\u8fc7\u4e70\u82f9\u679c\u6765\u8ba1\u7b97\u603b\u4ef7\u201d\uff0c\u4f7f\u5f97\u8bb2\u89e3\u66f4\u52a0\u751f\u52a8\u3002\n</code></pre> </li> </ul> <ol> <li>\u81ea\u52a8\u5316\u4f18\u5316\u5de5\u5177</li> </ol> <ul> <li>\u4f7f\u7528\u5982 OpenAI \u63d0\u4f9b\u7684 API\uff0c\u901a\u8fc7\u52a8\u6001\u8c03\u6574\u6d4b\u8bd5\u591a\u4e2a\u7248\u672c\u7684 Prompt\uff0c\u627e\u5230\u6700\u4f73\u89e3\u51b3\u65b9\u6848\u3002</li> </ul>"},{"location":"Tools/AI/prompt_writing/#132","title":"1.3.2 \u7ed3\u5408\u5916\u90e8\u5de5\u5177\u63d0\u5347\u6548\u7387","text":""},{"location":"Tools/AI/prompt_writing/#1321-api","title":"1.3.2.1 \u8c03\u7528 API \u6216\u4ee3\u7801\u6267\u884c\u5b9e\u73b0\u590d\u6742\u529f\u80fd","text":"<p>\u5927\u6a21\u578b\u5bf9\u8ba1\u7b97\u548c\u5b9e\u65f6\u6570\u636e\u7684\u652f\u6301\u6709\u9650\uff0c\u56e0\u6b64\u7ed3\u5408\u5916\u90e8\u5de5\u5177\uff0c\u5982 API \u8c03\u7528\u6216\u4ee3\u7801\u6267\u884c\uff0c\u53ef\u4ee5\u63d0\u5347\u4efb\u52a1\u7684\u51c6\u786e\u6027\u3002</p> <ol> <li>\u8bf7\u6c42\u751f\u6210\u4ee3\u7801\u6765\u6267\u884c\u8ba1\u7b97</li> </ol> <ul> <li> <p>\u793a\u4f8b\uff1a \u4efb\u52a1\uff1a\u6c42\u89e3\u591a\u9879\u5f0f\u7684\u6240\u6709\u5b9e\u6839\u3002 Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u7528 Python \u7f16\u5199\u4ee3\u7801\u6765\u8ba1\u7b97\u4ee5\u4e0b\u591a\u9879\u5f0f\u7684\u6240\u6709\u5b9e\u6839\uff1a\n\u591a\u9879\u5f0f\uff1a3x^3 - 5x^2 + 2x - 7\n\u8f93\u51fa Python \u4ee3\u7801\u5e76\u89e3\u91ca\u5176\u4f5c\u7528\u3002\n</code></pre> <p>\u8f93\u51fa\u7ed3\u679c\uff1a</p> Python<pre><code>import numpy as np\ncoefficients = [3, -5, 2, -7]\nroots = np.roots(coefficients)\nprint(\"\u5b9e\u6839\u4e3a\uff1a\", [r for r in roots if np.isreal(r)])\n</code></pre> <p>\u89e3\u91ca\uff1a\u6b64\u4ee3\u7801\u4f7f\u7528 NumPy \u7684 <code>roots</code> \u51fd\u6570\u8ba1\u7b97\u591a\u9879\u5f0f\u7684\u6240\u6709\u6839\uff0c\u5e76\u8fc7\u6ee4\u51fa\u5b9e\u6839\u3002</p> </li> </ul> <ol> <li>\u7ed3\u5408\u5916\u90e8\u6570\u636e\u6216\u5de5\u5177</li> </ol> <ul> <li>\u793a\u4f8b\uff1a\u4f7f\u7528\u5411\u91cf\u6570\u636e\u5e93\u67e5\u8be2\u77e5\u8bc6\u5e93\u4e2d\u7684\u4fe1\u606f\uff0c\u4f5c\u4e3a\u751f\u6210\u7b54\u6848\u7684\u8865\u5145\u3002</li> </ul>"},{"location":"Tools/AI/prompt_writing/#1322-markdown-latex","title":"1.3.2.2 \u8f93\u51fa\u6210 Markdown \u6216 LaTeX \u6587\u6863\u7684\u573a\u666f\u4e0e\u6280\u5de7","text":"<ol> <li>Markdown \u683c\u5f0f\u5316</li> </ol> <ul> <li> <p>\u793a\u4f8b\uff1a \u4efb\u52a1\uff1a\u751f\u6210\u4f1a\u8bae\u7eaa\u8981\u3002 Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u5c06\u4ee5\u4e0b\u4f1a\u8bae\u8bb0\u5f55\u603b\u7ed3\u4e3a Markdown \u683c\u5f0f\uff0c\u5305\u62ec\u53d1\u8a00\u4eba\u3001\u4e3b\u8981\u89c2\u70b9\u548c\u540e\u7eed\u4efb\u52a1\u3002\n</code></pre> <p>\u8f93\u51fa\uff1a</p> Markdown<pre><code>### \u4f1a\u8bae\u7eaa\u8981\n\n#### \u53d1\u8a00\u4eba\u53ca\u89c2\u70b9\n- **\u5f20\u4e09**\uff1a\u5efa\u8bae\u589e\u52a0\u5e02\u573a\u8425\u9500\u9884\u7b97\u3002\n- **\u674e\u56db**\uff1a\u5f3a\u8c03\u4f18\u5316\u4ea7\u54c1\u8d28\u91cf\u7684\u91cd\u8981\u6027\u3002\n\n#### \u540e\u7eed\u4efb\u52a1\n- \u5236\u5b9a\u65b0\u4e00\u5b63\u5ea6\u7684\u8425\u9500\u7b56\u7565\uff08\u8d1f\u8d23\u4eba\uff1a\u5f20\u4e09\uff09\u3002\n- \u8c03\u67e5\u7528\u6237\u5bf9\u5f53\u524d\u4ea7\u54c1\u7684\u6ee1\u610f\u5ea6\uff08\u8d1f\u8d23\u4eba\uff1a\u674e\u56db\uff09\u3002\n</code></pre> </li> </ul> <ol> <li>LaTeX \u683c\u5f0f\u5316</li> </ol> <ul> <li> <p>\u793a\u4f8b\uff1a \u4efb\u52a1\uff1a\u751f\u6210\u6570\u5b66\u516c\u5f0f\u3002 Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u7528 LaTeX \u683c\u5f0f\u4e66\u5199\u4ee5\u4e0b\u516c\u5f0f\u5e76\u89e3\u91ca\uff1a$(a+b)^2 = a^2 + 2ab + b^2$\u3002\n</code></pre> <p>\u8f93\u51fa\uff1a</p> TeX<pre><code>\\[\n(a+b)^2 = a^2 + 2ab + b^2\n\\]\n\u8fd9\u662f\u4e00\u4e2a\u57fa\u672c\u7684\u5e73\u65b9\u5c55\u5f00\u516c\u5f0f\uff0c\u5e38\u7528\u4e8e\u591a\u9879\u5f0f\u7684\u8ba1\u7b97\u3002\n</code></pre> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#133-prompt","title":"1.3.3 \u589e\u5f3a Prompt \u7684\u7075\u6d3b\u6027","text":""},{"location":"Tools/AI/prompt_writing/#1331","title":"1.3.3.1 \u4e3a\u5f00\u653e\u5f0f\u4efb\u52a1\u8bbe\u7f6e\u515c\u5e95\u7b56\u7565","text":"<p>\u5f00\u653e\u5f0f\u4efb\u52a1\uff08\u5982\u5199\u6545\u4e8b\u6216\u63a8\u8350\u65b9\u6848\uff09\u5bb9\u6613\u5bfc\u81f4\u6a21\u578b\u201c\u8dd1\u9898\u201d\uff0c\u901a\u8fc7\u515c\u5e95\u7b56\u7565\u53ef\u63d0\u9ad8\u7a33\u5b9a\u6027\u3002</p> <ol> <li>\u660e\u786e\u4e0d\u7b26\u5408\u6761\u4ef6\u65f6\u7684\u56de\u590d</li> </ol> <ul> <li> <p>\u793a\u4f8b\uff1a Prompt\uff1a  </p> Text Only<pre><code>\u73b0\u5728\u4f60\u662f\u4e00\u4e2a\u5411\u5ba2\u6237\u63a8\u8350\u7535\u5f71\u7684\u52a9\u624b\u3002\u5982\u679c\u5ba2\u6237\u7684\u4fe1\u606f\u4e0d\u8db3\u4ee5\u7ed9\u51fa\u63a8\u8350\uff0c\u8bf7\u56de\u7b54\uff1a\u201c\u62b1\u6b49\uff0c\u6211\u65e0\u6cd5\u6839\u636e\u60a8\u7684\u63cf\u8ff0\u63a8\u8350\u7535\u5f71\u3002\u201d\u3002\n</code></pre> <p>\u8f93\u5165\uff1a  </p> Text Only<pre><code>\u5ba2\u6237\uff1a\u5e2e\u6211\u63a8\u8350\u4e00\u90e8\u7535\u5f71\u3002\n</code></pre> <p>\u8f93\u51fa\uff1a  </p> Text Only<pre><code>\u62b1\u6b49\uff0c\u6211\u65e0\u6cd5\u6839\u636e\u60a8\u7684\u63cf\u8ff0\u63a8\u8350\u7535\u5f71\u3002\n</code></pre> </li> </ul> <ol> <li>\u5b9a\u4e49\u5bb9\u9519\u673a\u5236</li> </ol> <ul> <li> <p>\u793a\u4f8b\uff1a\u5f53\u751f\u6210\u7ed3\u679c\u4e0d\u7b26\u5408\u683c\u5f0f\u65f6\uff0c\u8981\u6c42\u91cd\u65b0\u751f\u6210\u3002  </p> Text Only<pre><code>\u5982\u679c\u4ee5\u4e0b\u5185\u5bb9\u7684\u8f93\u51fa\u683c\u5f0f\u9519\u8bef\uff0c\u8bf7\u91cd\u65b0\u751f\u6210\u5e76\u786e\u4fdd\u7b26\u5408\u8981\u6c42\uff1a\n\u8f93\u51fa\u683c\u5f0f\uff1a\n- \u4efb\u52a1\u63cf\u8ff0\n- \u4efb\u52a1\u8981\u70b9\n- \u4efb\u52a1\u5efa\u8bae\n</code></pre> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#1332","title":"1.3.3.2 \u6dfb\u52a0\u5f3a\u8c03\u8bcd\u4e0e\u7b26\u53f7\u63d0\u5347\u6307\u4ee4\u6743\u91cd","text":"<p>\u4f7f\u7528\u7279\u6b8a\u7b26\u53f7\uff08\u5982\u52a0\u7c97\uff09\u6216\u5f3a\u8c03\u8bcd\uff08\u5982\u201c\u52a1\u5fc5\u201d\u3001\u201c\u4e25\u683c\u201d\uff09\u6807\u6ce8\u5173\u952e\u5185\u5bb9\u3002</p> <ol> <li>\u793a\u4f8b\uff1a  </li> </ol> <p>\u4efb\u52a1\uff1a\u603b\u7ed3\u6587\u7ae0\u5e76\u5f3a\u8c03\u5173\u952e\u6982\u5ff5\u3002 Prompt\uff1a  </p> Text Only<pre><code> ```text\n \u8bf7\u603b\u7ed3\u4ee5\u4e0b\u6587\u7ae0\uff0c\u5e76**\u52a0\u7c97**\u6bcf\u4e2a\u8981\u70b9\u4e2d\u7684\u5173\u952e\u6982\u5ff5\uff0c\u4ee5 Markdown \u5217\u8868\u5f62\u5f0f\u8f93\u51fa\u3002\n ```\n\n **\u8f93\u51fa**\uff1a\n\n ```markdown\n - **\u8981\u70b9\u4e00**\uff1a\u673a\u5668\u5b66\u4e60\u662f\u901a\u8fc7\u6570\u636e\u8bad\u7ec3\u6a21\u578b\u7684**\u65b9\u6cd5**\u3002\n - **\u8981\u70b9\u4e8c**\uff1a\u6df1\u5ea6\u5b66\u4e60\u662f\u673a\u5668\u5b66\u4e60\u7684**\u5206\u652f**\uff0c\u4ee5\u591a\u5c42\u795e\u7ecf\u7f51\u7edc\u4e3a\u6838\u5fc3\u3002\n ```\n</code></pre>"},{"location":"Tools/AI/prompt_writing/#14","title":"1.4 \u5b9e\u7528\u6848\u4f8b","text":""},{"location":"Tools/AI/prompt_writing/#141","title":"1.4.1 \u5e38\u89c1\u573a\u666f\u4e0e\u89e3\u51b3\u65b9\u6848","text":""},{"location":"Tools/AI/prompt_writing/#1411","title":"1.4.1.1 \u751f\u6210\u957f\u7bc7\u7684\u6587\u7ae0","text":"<ol> <li>\u9010\u6b65\u751f\u6210\u957f\u6587\u5185\u5bb9</li> </ol> <ul> <li>\u65b9\u6cd5\uff1a\u5148\u751f\u6210\u76ee\u5f55\uff0c\u518d\u9010\u90e8\u5206\u6269\u5c55\u5185\u5bb9\u3002</li> <li> <p>\u793a\u4f8b\uff1a Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u4e3a\u4ee5\u4e0b\u4e3b\u9898\u751f\u6210\u4e00\u4efd\u8be6\u7ec6\u7684\u6587\u7ae0\u76ee\u5f55\uff0c\u7136\u540e\u57fa\u4e8e\u76ee\u5f55\u9010\u6bb5\u6269\u5c55\u5185\u5bb9\uff1a\n\u4e3b\u9898\uff1a\u5982\u4f55\u4f18\u5316\u4e2a\u4eba\u65f6\u95f4\u7ba1\u7406\n</code></pre> <p>\u8f93\u51fa\u76ee\u5f55\u793a\u4f8b\uff1a</p> Markdown<pre><code>- \u7b2c\u4e00\u90e8\u5206\uff1a\u65f6\u95f4\u7ba1\u7406\u7684\u91cd\u8981\u6027\n- \u7b2c\u4e8c\u90e8\u5206\uff1a\u5e38\u89c1\u65f6\u95f4\u7ba1\u7406\u8bef\u533a\n- \u7b2c\u4e09\u90e8\u5206\uff1a\u9ad8\u6548\u65f6\u95f4\u7ba1\u7406\u7684\u65b9\u6cd5\n  - 1. \u8bbe\u5b9a\u76ee\u6807\u4e0e\u4f18\u5148\u7ea7\n  - 2. \u4f7f\u7528\u5de5\u5177\u4e0e\u6280\u672f\n  - 3. \u57f9\u517b\u65f6\u95f4\u7ba1\u7406\u4e60\u60ef\n- \u7b2c\u56db\u90e8\u5206\uff1a\u6848\u4f8b\u5206\u6790\u4e0e\u5e94\u7528\n</code></pre> <p>\u6269\u5c55\u5185\u5bb9 Prompt\uff1a</p> Text Only<pre><code>\u8bf7\u8be6\u7ec6\u64b0\u5199\u7b2c\u4e00\u90e8\u5206\u201c\u65f6\u95f4\u7ba1\u7406\u7684\u91cd\u8981\u6027\u201d\u7684\u5185\u5bb9\uff0c\u63a7\u5236\u5728 300 \u5b57\u5de6\u53f3\u3002\n</code></pre> </li> </ul> <ol> <li>\u5728\u751f\u6210\u65f6\u6dfb\u52a0\u5f15\u7528\u6587\u732e</li> </ol> <ul> <li> <p>\u793a\u4f8b\uff1a Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u4e3a\u4ee5\u4e0b\u4e3b\u9898\u751f\u6210\u4e00\u7bc7 500 \u5b57\u7684\u6587\u7ae0\uff0c\u5e76\u5728\u6587\u7ae0\u672b\u5c3e\u9644\u4e0a\u76f8\u5173\u53c2\u8003\u6587\u732e\uff1a\n\u4e3b\u9898\uff1a\u4eba\u5de5\u667a\u80fd\u5982\u4f55\u6539\u53d8\u6559\u80b2\u884c\u4e1a\n</code></pre> <p>\u8f93\u51fa\uff1a</p> Markdown<pre><code>### \u4eba\u5de5\u667a\u80fd\u5982\u4f55\u6539\u53d8\u6559\u80b2\u884c\u4e1a\n\uff08\u6587\u7ae0\u5185\u5bb9\uff09\n#### \u53c2\u8003\u6587\u732e\n- \u674e\u56db\uff0c\u300a\u4eba\u5de5\u667a\u80fd\u4e0e\u6559\u80b2\u300b\uff0c2023\u5e74\u51fa\u7248\u3002\n- OpenAI\uff0c\u300aAI\u5728\u6559\u80b2\u9886\u57df\u7684\u5e94\u7528\u300b\uff0c2021\u5e74\u3002\n</code></pre> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#1412","title":"1.4.1.2 \u89e3\u91ca\u4ee3\u7801\u5e76\u751f\u6210\u8f85\u52a9\u56fe\u8868","text":"<ol> <li>\u751f\u6210\u4ee3\u7801\u89e3\u91ca</li> </ol> <ul> <li> <p>\u793a\u4f8b\uff1a Prompt\uff1a  </p> Text Only<pre><code>\u4ee5\u4e0b\u662f Python \u4ee3\u7801\u7247\u6bb5\uff0c\u8bf7\u89e3\u91ca\u5176\u4f5c\u7528\uff1a\n```python\nnested_dict = lambda: defaultdict(nested_dict)\n</code></pre> Text Only<pre><code>**\u8f93\u51fa**\uff1a\n```text\n\u6b64\u4ee3\u7801\u5b9a\u4e49\u4e86\u4e00\u4e2a\u5d4c\u5957\u5b57\u5178\u7684\u9012\u5f52\u7ed3\u6784\uff0c\u53ef\u4ee5\u52a8\u6001\u521b\u5efa\u4efb\u610f\u6df1\u5ea6\u7684\u5b57\u5178\u5c42\u7ea7\u3002\n\u793a\u4f8b\u7528\u6cd5\uff1a\ndata = nested_dict()\ndata['level1']['level2'] = \"value\"\n</code></pre> </li> </ul> <ol> <li>\u751f\u6210\u8f85\u52a9\u56fe\u8868</li> </ol> <ul> <li> <p>\u793a\u4f8b\uff1a Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u6839\u636e\u4ee5\u4e0b\u63cf\u8ff0\u751f\u6210\u4e00\u6bb5 mermaid \u683c\u5f0f\u7684\u4ee3\u7801\uff0c\u7528\u4e8e\u5c55\u793a\u51fd\u6570\u8c03\u7528\u5173\u7cfb\uff1a\n\u63cf\u8ff0\uff1a\u51fd\u6570 A \u8c03\u7528\u51fd\u6570 B\uff0c\u51fd\u6570 B \u8c03\u7528\u51fd\u6570 C \u548c D\uff0c\u51fd\u6570 D \u8fd4\u56de\u7ed3\u679c\u3002\n</code></pre> <p>\u8f93\u51fa\uff1a</p> Text Only<pre><code>graph TD\nA --&gt; B\nB --&gt; C\nB --&gt; D\nD --&gt; Result\n</code></pre> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#142-prompt","title":"1.4.2 Prompt \u7684\u9650\u5236\u4e0e\u5e94\u5bf9\u7b56\u7565","text":""},{"location":"Tools/AI/prompt_writing/#1421","title":"1.4.2.1 \u8bbe\u8ba1\u62d2\u7b54\u7b56\u7565\u63d0\u5347\u53ef\u9760\u6027","text":"<ol> <li>\u907f\u514d\u5e7b\u89c9\u73b0\u8c61</li> </ol> <ul> <li> <p>\u63d0\u793a\u6a21\u578b\u4e0d\u8981\u56de\u7b54\u5176\u65e0\u6cd5\u786e\u5b9a\u7684\u5185\u5bb9\u3002 \u793a\u4f8b\uff1a  </p> Text Only<pre><code>\u5982\u679c\u4f60\u4e0d\u77e5\u9053\u4ee5\u4e0b\u95ee\u9898\u7684\u7b54\u6848\uff0c\u8bf7\u56de\u590d\u201c\u4fe1\u606f\u4e0d\u8db3\u201d\u3002\n\u95ee\u9898\uff1a\u8c01\u662f\u7b2c\u4e00\u4e2a\u767b\u4e0a\u6708\u7403\u7684\u673a\u5668\u4eba\uff1f\n</code></pre> <p>\u8f93\u51fa\uff1a</p> Text Only<pre><code>\u4fe1\u606f\u4e0d\u8db3\u3002\n</code></pre> </li> </ul> <ol> <li>\u591a\u6b21\u751f\u6210\u4ee5\u786e\u8ba4\u7b54\u6848\u4e00\u81f4\u6027</li> </ol> <ul> <li> <p>Prompt\uff1a  </p> Text Only<pre><code>\u8bf7\u591a\u6b21\u751f\u6210\u4ee5\u4e0b\u95ee\u9898\u7684\u7b54\u6848\uff0c\u5e76\u786e\u4fdd\u7b54\u6848\u4e00\u81f4\u3002\u5982\u679c\u7b54\u6848\u4e0d\u4e00\u81f4\uff0c\u8bf7\u56de\u590d\u201c\u65e0\u6cd5\u786e\u5b9a\u7b54\u6848\u201d\u3002\n\u95ee\u9898\uff1a2023 \u5e74\u4e16\u754c\u4eba\u53e3\u603b\u6570\u662f\u591a\u5c11\uff1f\n</code></pre> </li> </ul>"},{"location":"Tools/AI/prompt_writing/#1422-ai","title":"1.4.2.2 \u591a\u4e2a AI \u534f\u4f5c","text":"<ol> <li>\u6846\u67b6\u4e0e\u5185\u5bb9\u534f\u4f5c</li> </ol> <ul> <li> <p>\u901a\u8fc7\u4e0d\u540c\u6a21\u578b\u534f\u4f5c\u4f18\u5316\u5185\u5bb9\u751f\u6210\u3002 \u793a\u4f8b\u6d41\u7a0b\uff1a</p> <ul> <li>Prompt 1\uff1a\u8ba9 ChatGPT \u63d0\u4f9b\u6587\u7ae0\u6846\u67b6\u3002  </li> </ul> Text Only<pre><code>\u8bf7\u4e3a\u4ee5\u4e0b\u4e3b\u9898\u751f\u6210\u8be6\u7ec6\u7684\u6587\u7ae0\u6846\u67b6\uff1a\n\u4e3b\u9898\uff1a\u5982\u4f55\u63d0\u5347\u56e2\u961f\u5408\u4f5c\u6548\u7387\n</code></pre> <ul> <li>Prompt 2\uff1a\u5c06\u6846\u67b6\u5185\u5bb9\u4ea4\u7ed9\u53e6\u4e00\u4e2a\u6a21\u578b\u4f18\u5316\u8868\u8fbe\u3002  </li> </ul> Text Only<pre><code>\u8bf7\u6839\u636e\u4ee5\u4e0b\u6846\u67b6\u64b0\u5199\u8be6\u7ec6\u5185\u5bb9\uff0c\u5e76\u8c03\u6574\u4e3a\u66f4\u4e13\u4e1a\u7684\u8bed\u8a00\u3002\n</code></pre> <ul> <li>Prompt 3\uff1a\u4f7f\u7528\u53e6\u4e00\u4e2a\u5de5\u5177\uff08\u5982 Grammarly \u6216\u5176\u4ed6 AI\uff09\u6821\u5bf9\u548c\u4f18\u5316\u8bed\u8a00\u98ce\u683c\u3002</li> </ul> </li> </ul> <ol> <li>\u4ee3\u7801\u4f18\u5316\u534f\u4f5c</li> </ol> <ul> <li>Prompt\uff1a  </li> </ul> Text Only<pre><code>    \u8bf7\u4f18\u5316\u4ee5\u4e0b\u4ee3\u7801\uff0c\u4f7f\u5176\u8fd0\u884c\u6548\u7387\u66f4\u9ad8\uff0c\u5e76\u63d0\u4f9b\u6ce8\u91ca\u8bf4\u660e\uff1a\n    ```python\n        def factorial(n):\n            if n == 0:\n                return 1\n            else:\n                return n * factorial(n-1)\n    ```\n</code></pre>"},{"location":"Tools/AI/prompt_writing/#15","title":"1.5 \u6211\u66fe\u7ecf\u7528\u6cd5","text":"<ul> <li>\u8f93\u51fa\u6587\u6863\uff1a\u901a\u8fc7 Markdown \u6216 LaTeX \u751f\u6210\u683c\u5f0f\u5316\u6587\u6863\u3002</li> <li>\u751f\u6210 README\uff1a\u8ba9 AI \u9605\u8bfb\u4ee3\u7801\u5e76\u64b0\u5199\u8bf4\u660e\u3002</li> <li>\u5f15\u7528\u6587\u732e\u5199\u8bba\u6587\uff1a\u5229\u7528 AI \u4e0a\u7f51\u67e5\u8be2\u8d44\u6599\uff0c\u63d0\u9ad8\u5b66\u672f\u5185\u5bb9\u8d28\u91cf\u3002</li> </ul>"},{"location":"Tools/AI/prompt_writing/#2-prompt","title":"2 \u5e38\u7528\u7684 Prompt","text":"<p>\u8bf7\u53c2\u8003 \u5e38\u7528 prompt \u8bb0\u5f55 - wnc \u7684\u5496\u5561\u9986</p>"},{"location":"Tools/Blog/Mkdocs_Material/","title":"mkdocs material \u8d85\u5168\u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#mkdocs-material","title":"mkdocs material \u8d85\u5168\u914d\u7f6e","text":"<p> \u7ea6 5956 \u4e2a\u5b57  9393 \u884c\u4ee3\u7801  7 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 147 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>\u4ecd\u7136\u5728\u4fee\u6539 \u5982\u679c\u9700\u8981\u4efb\u4f55\u7684\u6587\u4ef6\uff0c\u53ef\u4ee5\u76f4\u63a5\u8bbf\u95ee\u672c\u535a\u5ba2\u7684 GitHub \u9875\u9762</p>"},{"location":"Tools/Blog/Mkdocs_Material/#1","title":"1 \u5165\u95e8\u57fa\u7840","text":""},{"location":"Tools/Blog/Mkdocs_Material/#11-mkdocs","title":"1.1 \u4ec0\u4e48\u662f MkDocs\uff1f","text":"<p>MkDocs \u662f\u4e00\u4e2a\u5feb\u901f\u3001\u7b80\u5355\u3001\u534e\u4e3d\u7684\u9759\u6001\u7ad9\u70b9\u751f\u6210\u5668\uff0c\u4e13\u95e8\u7528\u4e8e\u6784\u5efa\u9879\u76ee\u6587\u6863\u3002\u6587\u6863\u6e90\u6587\u4ef6\u4f7f\u7528 Markdown \u7f16\u5199\uff0c\u914d\u7f6e\u6587\u4ef6\u4f7f\u7528 YAML \u683c\u5f0f\u3002</p>"},{"location":"Tools/Blog/Mkdocs_Material/#111-mkdocs","title":"1.1.1 MkDocs \u7684\u4f18\u52bf","text":"<ol> <li> <p>\u7b80\u5355\u6613\u7528    - \u4f7f\u7528 Markdown \u7f16\u5199\u6587\u6863    - \u914d\u7f6e\u6587\u4ef6\u7b80\u5355\u76f4\u89c2    - \u4e00\u952e\u5f0f\u6784\u5efa\u548c\u90e8\u7f72</p> </li> <li> <p>\u529f\u80fd\u5f3a\u5927    - \u5185\u7f6e\u5f00\u53d1\u670d\u52a1\u5668\uff0c\u652f\u6301\u5b9e\u65f6\u9884\u89c8    - \u591a\u79cd\u4e3b\u9898\u53ef\u9009    - \u652f\u6301\u81ea\u5b9a\u4e49\u4e3b\u9898    - \u81ea\u52a8\u751f\u6210\u5bfc\u822a    - \u5168\u6587\u641c\u7d22\u529f\u80fd</p> </li> <li> <p>\u90e8\u7f72\u65b9\u4fbf    - \u751f\u6210\u7eaf\u9759\u6001\u9875\u9762    - \u4e00\u884c\u547d\u4ee4\u90e8\u7f72\u5230 GitHub Pages    - \u652f\u6301\u81ea\u5b9a\u4e49\u57df\u540d    - \u517c\u5bb9\u6240\u6709\u9759\u6001\u7f51\u7ad9\u6258\u7ba1\u5e73\u53f0</p> </li> </ol>"},{"location":"Tools/Blog/Mkdocs_Material/#112-mkdocs-vs","title":"1.1.2 MkDocs vs \u5176\u4ed6\u6587\u6863\u5de5\u5177","text":"\u5de5\u5177 \u4f18\u52bf \u52a3\u52bf MkDocs - \u7b80\u5355\u6613\u7528- \u4e13\u6ce8\u6587\u6863- \u90e8\u7f72\u65b9\u4fbf- \u4e3b\u9898\u4e30\u5bcc - \u529f\u80fd\u76f8\u5bf9\u7b80\u5355- \u63d2\u4ef6\u751f\u6001\u8f83\u5c0f GitBook - \u754c\u9762\u4f18\u96c5- \u751f\u6001\u5b8c\u6574- \u591a\u4eba\u534f\u4f5c\u597d - \u6784\u5efa\u901f\u5ea6\u6162- \u5b9a\u5236\u6027\u5dee- \u514d\u8d39\u7248\u9650\u5236\u591a Docusaurus - React \u6280\u672f\u6808- \u529f\u80fd\u5f3a\u5927- \u6269\u5c55\u6027\u597d - \u5b66\u4e60\u66f2\u7ebf\u9661- \u914d\u7f6e\u590d\u6742- \u6784\u5efa\u8f83\u6162 VuePress - Vue \u6280\u672f\u6808- \u5b9a\u5236\u6027\u5f3a- \u63d2\u4ef6\u4e30\u5bcc - \u4e3b\u9898\u8f83\u5c11- \u914d\u7f6e\u7e41\u7410- \u5b66\u4e60\u6210\u672c\u9ad8"},{"location":"Tools/Blog/Mkdocs_Material/#113-mkdocs","title":"1.1.3 MkDocs \u5de5\u4f5c\u539f\u7406","text":"<p>MkDocs \u7684\u5de5\u4f5c\u6d41\u7a0b\u5982\u4e0b\uff1a</p> <ol> <li> <p>\u6587\u6863\u7f16\u5199    - \u4f7f\u7528 Markdown \u683c\u5f0f\u7f16\u5199\u6587\u6863    - \u6587\u6863\u5b58\u653e\u5728 <code>docs</code> \u76ee\u5f55\u4e0b    - \u652f\u6301\u591a\u7ea7\u76ee\u5f55\u7ed3\u6784</p> </li> <li> <p>\u914d\u7f6e\u89e3\u6790    - \u8bfb\u53d6 <code>mkdocs.yml</code> \u914d\u7f6e\u6587\u4ef6    - \u89e3\u6790\u4e3b\u9898\u8bbe\u7f6e\u3001\u63d2\u4ef6\u914d\u7f6e\u7b49    - \u751f\u6210\u5bfc\u822a\u7ed3\u6784</p> </li> <li> <p>\u6784\u5efa\u8fc7\u7a0b</p> </li> </ol> Text Only<pre><code>Markdown \u6587\u4ef6 -&gt; \u89e3\u6790\u5668 -&gt; HTML \u6587\u4ef6\n              -&gt; \u4e3b\u9898\u6e32\u67d3\n              -&gt; \u63d2\u4ef6\u5904\u7406\n              -&gt; \u9759\u6001\u8d44\u6e90\u5904\u7406\n</code></pre> <ol> <li>\u8f93\u51fa\u90e8\u7f72    - \u751f\u6210\u7eaf\u9759\u6001 HTML \u6587\u4ef6    - \u4fdd\u7559\u539f\u59cb\u76ee\u5f55\u7ed3\u6784    - \u81ea\u52a8\u5904\u7406\u5185\u90e8\u94fe\u63a5    - \u590d\u5236\u9759\u6001\u8d44\u6e90</li> </ol>"},{"location":"Tools/Blog/Mkdocs_Material/#12-material","title":"1.2 \u4e3a\u4ec0\u4e48\u9009\u62e9 Material \u4e3b\u9898","text":"<p>Material for MkDocs \u662f\u4e00\u4e2a\u57fa\u4e8e Google Material Design \u8bbe\u8ba1\u8bed\u8a00\u7684\u4e3b\u9898\uff0c\u5b83\u4e0d\u4ec5\u7f8e\u89c2\uff0c\u800c\u4e14\u529f\u80fd\u5f3a\u5927\u3002</p>"},{"location":"Tools/Blog/Mkdocs_Material/#121-material","title":"1.2.1 Material \u4e3b\u9898\u7279\u6027","text":"<ol> <li> <p>\u73b0\u4ee3\u5316\u8bbe\u8ba1    - \u9075\u5faa Material Design \u89c4\u8303    - \u54cd\u5e94\u5f0f\u5e03\u5c40    - \u652f\u6301\u6df1\u8272\u6a21\u5f0f    - \u81ea\u52a8\u9002\u914d\u79fb\u52a8\u8bbe\u5907</p> </li> <li> <p>\u5f3a\u5927\u529f\u80fd    - \u667a\u80fd\u641c\u7d22    - \u4ee3\u7801\u9ad8\u4eae    - \u6807\u7b7e\u9875\u652f\u6301    - \u81ea\u52a8\u76ee\u5f55\u751f\u6210    - \u591a\u8bed\u8a00\u652f\u6301    - \u7248\u672c\u63a7\u5236\u96c6\u6210</p> </li> <li> <p>\u51fa\u8272\u7684\u7528\u6237\u4f53\u9a8c    - \u5feb\u901f\u52a0\u8f7d    - \u5e73\u6ed1\u52a8\u753b    - \u5b9e\u65f6\u641c\u7d22    - \u4ee3\u7801\u590d\u5236\u6309\u94ae    - \u8fd4\u56de\u9876\u90e8\u6309\u94ae</p> </li> </ol>"},{"location":"Tools/Blog/Mkdocs_Material/#122","title":"1.2.2 \u4e0e\u5176\u4ed6\u4e3b\u9898\u5bf9\u6bd4","text":"\u7279\u6027 Material ReadTheDocs mkdocs \u5176\u4ed6\u4e3b\u9898 \u8bbe\u8ba1\u98ce\u683c \u73b0\u4ee3\u7b80\u7ea6 \u4f20\u7edf\u6587\u6863 \u7b80\u5355\u57fa\u7840 \u98ce\u683c\u591a\u6837 \u54cd\u5e94\u5f0f \u2705 \u2705 \u274c \u90e8\u5206\u652f\u6301 \u6df1\u8272\u6a21\u5f0f \u2705 \u274c \u274c \u90e8\u5206\u652f\u6301 \u641c\u7d22\u529f\u80fd \u2705 \u2705 \u274c \u90e8\u5206\u652f\u6301 \u5b9a\u5236\u6027 \u5f3a \u4e2d \u5f31 \u4e0d\u4e00\u81f4 \u63d2\u4ef6\u652f\u6301 \u4e30\u5bcc \u4e00\u822c \u57fa\u7840 \u4e0d\u4e00\u81f4"},{"location":"Tools/Blog/Mkdocs_Material/#123-material","title":"1.2.3 Material \u4e3b\u9898\u7684\u6280\u672f\u67b6\u6784","text":"Text Only<pre><code>Material Theme\n\u251c\u2500\u2500 \u6838\u5fc3\u7ec4\u4ef6\n\u2502   \u251c\u2500\u2500 \u5bfc\u822a\u680f\n\u2502   \u251c\u2500\u2500 \u4fa7\u8fb9\u680f\n\u2502   \u251c\u2500\u2500 \u641c\u7d22\u7ec4\u4ef6\n\u2502   \u2514\u2500\u2500 \u5185\u5bb9\u6e32\u67d3\u5668\n\u251c\u2500\u2500 \u6269\u5c55\u529f\u80fd\n\u2502   \u251c\u2500\u2500 \u4ee3\u7801\u9ad8\u4eae\n\u2502   \u251c\u2500\u2500 \u6807\u7b7e\u7cfb\u7edf\n\u2502   \u251c\u2500\u2500 \u76ee\u5f55\u751f\u6210\n\u2502   \u2514\u2500\u2500 \u4e3b\u9898\u5207\u6362\n\u2514\u2500\u2500 \u63d2\u4ef6\u7cfb\u7edf\n    \u251c\u2500\u2500 \u5185\u7f6e\u63d2\u4ef6\n    \u2514\u2500\u2500 \u7b2c\u4e09\u65b9\u63d2\u4ef6\u96c6\u6210\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#13","title":"1.3 \u73af\u5883\u8981\u6c42","text":""},{"location":"Tools/Blog/Mkdocs_Material/#131-python","title":"1.3.1 Python \u73af\u5883","text":""},{"location":"Tools/Blog/Mkdocs_Material/#1311-python","title":"1.3.1.1 Python \u7248\u672c\u9009\u62e9","text":"<p>MkDocs \u9700\u8981 Python 3.6 \u6216\u66f4\u9ad8\u7248\u672c\uff0c\u63a8\u8350\u4f7f\u7528 Python 3.8+\uff1a</p> Bash<pre><code># \u68c0\u67e5 Python \u7248\u672c\npython --version\n\n# \u63a8\u8350\u7248\u672c\nPython 3.8.x\nPython 3.9.x\nPython 3.10.x\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1312-pip","title":"1.3.1.2 pip \u914d\u7f6e\u8bf4\u660e","text":"<p>pip \u662f Python \u7684\u5305\u7ba1\u7406\u5de5\u5177\uff0c\u9700\u8981\u786e\u4fdd\u5176\u6b63\u786e\u5b89\u88c5\uff1a</p> Bash<pre><code># \u68c0\u67e5 pip \u7248\u672c\npip --version\n\n# \u5347\u7ea7 pip\npython -m pip install --upgrade pip\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1313","title":"1.3.1.3 \u865a\u62df\u73af\u5883\u7ba1\u7406","text":"<p>\u63a8\u8350\u4f7f\u7528\u865a\u62df\u73af\u5883\u6765\u7ba1\u7406\u9879\u76ee\u4f9d\u8d56\uff1a</p> Bash<pre><code># \u521b\u5efa\u865a\u62df\u73af\u5883\npython -m venv venv\n\n# \u6fc0\u6d3b\u865a\u62df\u73af\u5883\n# Windows\nvenv\\Scripts\\activate\n# Linux/Mac\nsource venv/bin/activate\n\n# \u9000\u51fa\u865a\u62df\u73af\u5883\ndeactivate\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#132-pip","title":"1.3.2 pip \u5305\u7ba1\u7406","text":""},{"location":"Tools/Blog/Mkdocs_Material/#1321-pip","title":"1.3.2.1 pip \u6e90\u914d\u7f6e","text":"<p>\u4e3a\u52a0\u5feb\u4e0b\u8f7d\u901f\u5ea6\uff0c\u5efa\u8bae\u4f7f\u7528\u56fd\u5185\u955c\u50cf\u6e90\uff1a</p> Bash<pre><code># \u4e34\u65f6\u4f7f\u7528\npip install -i https://pypi.tuna.tsinghua.edu.cn/simple mkdocs\n\n# \u6c38\u4e45\u914d\u7f6e\npip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1322","title":"1.3.2.2 \u4f9d\u8d56\u7ba1\u7406","text":"<p>\u5b89\u88c5\u5fc5\u8981\u7684\u5305\uff1a</p> Bash<pre><code>pip install mkdocs-material\npip install mkdocs-glightbox\npip install mkdocs-git-revision-date-localized-plugin\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1323-requirements-txt","title":"1.3.2.3 requirements. txt \u4f7f\u7528","text":"<p>\u7ef4\u62a4\u9879\u76ee\u4f9d\u8d56\uff1a</p> Bash<pre><code># \u751f\u6210\u4f9d\u8d56\u6587\u4ef6\npip freeze &gt; requirements.txt\n\n# \u5b89\u88c5\u4f9d\u8d56\npip install -r requirements.txt\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#133-git","title":"1.3.3 Git \u73af\u5883","text":""},{"location":"Tools/Blog/Mkdocs_Material/#1331-git","title":"1.3.3.1 Git \u57fa\u7840\u914d\u7f6e","text":"Bash<pre><code># \u914d\u7f6e\u7528\u6237\u4fe1\u606f\ngit config --global user.name \"Your Name\"\ngit config --global user.email \"your.email@example.com\"\n\n# \u914d\u7f6e\u9ed8\u8ba4\u5206\u652f\ngit config --global init.defaultBranch main\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#134-ssh","title":"1.3.4 SSH \u5bc6\u94a5\u914d\u7f6e","text":"Bash<pre><code># \u751f\u6210 SSH \u5bc6\u94a5\nssh-keygen -t rsa -b 4096 -C \"your.email@example.com\"\n\n# \u67e5\u770b\u516c\u94a5\ncat ~/.ssh/id_rsa.pub\n</code></pre> <p>\u5c06\u516c\u94a5\u6dfb\u52a0\u5230 GitHub \u8d26\u6237\u7684 SSH keys \u4e2d\u3002</p>"},{"location":"Tools/Blog/Mkdocs_Material/#135-gitignore","title":"1.3.5 .gitignore \u914d\u7f6e","text":"<p>\u521b\u5efa <code>.gitignore</code> \u6587\u4ef6\uff0c\u6dfb\u52a0\u4ee5\u4e0b\u5185\u5bb9\uff1a</p> Text Only<pre><code># Python\n__pycache__/\n*.py[cod]\n*$py.class\nvenv/\n\n# MkDocs\nsite/\n\n# IDE\n.idea/\n.vscode/\n*.swp\n*.swo\n\n# OS\n.DS_Store\nThumbs.db\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2","title":"2 \u73af\u5883\u642d\u5efa","text":""},{"location":"Tools/Blog/Mkdocs_Material/#21-windows","title":"2.1 Windows \u7cfb\u7edf\u5b89\u88c5","text":""},{"location":"Tools/Blog/Mkdocs_Material/#211-python","title":"2.1.1 Python \u5b89\u88c5","text":""},{"location":"Tools/Blog/Mkdocs_Material/#2111","title":"2.1.1.1 \u4e0b\u8f7d\u5b89\u88c5\u5305","text":"<ol> <li>\u8bbf\u95ee Python \u5b98\u7f51 \u4e0b\u8f7d\u6700\u65b0\u7248\u672c</li> <li>\u9009\u62e9\u9002\u5408\u4f60\u7684 Windows \u7248\u672c\uff0832 \u4f4d/64 \u4f4d\uff09\u7684\u5b89\u88c5\u5305</li> <li>\u4e0b\u8f7d\u5b8c\u6210\u540e\u53cc\u51fb\u5b89\u88c5\u5305\u5f00\u59cb\u5b89\u88c5</li> </ol>"},{"location":"Tools/Blog/Mkdocs_Material/#2112","title":"2.1.1.2 \u73af\u5883\u53d8\u91cf\u914d\u7f6e","text":"<ol> <li>\u5b89\u88c5\u65f6\u52fe\u9009 \"Add Python to PATH\"</li> <li>\u5982\u679c\u5fd8\u8bb0\u52fe\u9009\uff0c\u53ef\u4ee5\u624b\u52a8\u6dfb\u52a0\uff1a</li> </ol> Text Only<pre><code># \u6dfb\u52a0\u5230\u7cfb\u7edf\u73af\u5883\u53d8\u91cf Path\nC:\\Users\\YourUser\\AppData\\Local\\Programs\\Python\\Python3x\\\nC:\\Users\\YourUser\\AppData\\Local\\Programs\\Python\\Python3x\\Scripts\\\n</code></pre> <ol> <li>\u68c0\u67e5\u73af\u5883\u53d8\u91cf\uff1a</li> </ol> Bash<pre><code>echo %PATH%\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2113","title":"2.1.1.3 \u9a8c\u8bc1\u5b89\u88c5","text":"<p>\u5728\u547d\u4ee4\u63d0\u793a\u7b26\u4e2d\u6267\u884c\uff1a</p> Bash<pre><code># \u68c0\u67e5 Python \u7248\u672c\npython --version\n\n# \u68c0\u67e5 pip \u7248\u672c\npip --version\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#212-mkdocs","title":"2.1.2 MkDocs \u5b89\u88c5","text":""},{"location":"Tools/Blog/Mkdocs_Material/#2121-pip","title":"2.1.2.1 pip \u5b89\u88c5\u65b9\u6cd5","text":"<p>\u4f7f\u7528 pip \u5b89\u88c5 MkDocs\uff1a</p> Bash<pre><code># \u5b89\u88c5 MkDocs\npip install mkdocs\n\n# \u9a8c\u8bc1\u5b89\u88c5\nmkdocs --version\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2122","title":"2.1.2.2 \u5e38\u89c1\u95ee\u9898\u89e3\u51b3","text":"<ol> <li> <p>pip \u4e0d\u662f\u5185\u90e8\u547d\u4ee4    - \u89e3\u51b3\u65b9\u6cd5\uff1a\u91cd\u65b0\u6dfb\u52a0 Python Scripts \u76ee\u5f55\u5230 PATH</p> </li> <li> <p>\u6743\u9650\u95ee\u9898    - \u89e3\u51b3\u65b9\u6cd5\uff1a\u4f7f\u7528\u7ba1\u7406\u5458\u6743\u9650\u8fd0\u884c\u547d\u4ee4\u63d0\u793a\u7b26</p> </li> </ol> Bash<pre><code># \u7ba1\u7406\u5458\u6743\u9650\u5b89\u88c5\npip install --user mkdocs\n</code></pre> <ol> <li>SSL \u8bc1\u4e66\u9519\u8bef    - \u89e3\u51b3\u65b9\u6cd5\uff1a\u6dfb\u52a0\u4fe1\u4efb\u9009\u9879\u6216\u4f7f\u7528\u56fd\u5185\u955c\u50cf</li> </ol> Bash<pre><code>pip install --trusted-host pypi.org --trusted-host files.pythonhosted.org mkdocs\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#213","title":"2.1.3 \u7248\u672c\u9009\u62e9","text":"<p>MkDocs \u7248\u672c\u9009\u62e9\u5efa\u8bae\uff1a</p> Bash<pre><code># \u67e5\u770b\u53ef\u7528\u7248\u672c\npip install mkdocs==\n\n# \u5b89\u88c5\u7279\u5b9a\u7248\u672c\npip install mkdocs==1.5.3  # \u63a8\u8350\u7248\u672c\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#214-material","title":"2.1.4 Material \u4e3b\u9898\u5b89\u88c5","text":""},{"location":"Tools/Blog/Mkdocs_Material/#2141","title":"2.1.4.1 \u5b89\u88c5\u547d\u4ee4","text":"Bash<pre><code># \u5b89\u88c5 Material \u4e3b\u9898\npip install mkdocs-material\n\n# \u9a8c\u8bc1\u5b89\u88c5\npython -c \"import mkdocs_material; print(mkdocs_material.__version__)\"\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2142","title":"2.1.4.2 \u4f9d\u8d56\u68c0\u67e5","text":"<p>\u5b89\u88c5\u5fc5\u8981\u7684\u4f9d\u8d56\uff1a</p> Bash<pre><code># \u5b89\u88c5\u6269\u5c55\u652f\u6301\npip install pymdown-extensions\npip install mkdocs-glightbox\npip install mkdocs-git-revision-date-localized-plugin\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2143","title":"2.1.4.3 \u7248\u672c\u517c\u5bb9\u6027","text":"MkDocs \u7248\u672c Material \u7248\u672c Python \u7248\u672c 1.5. x 9.4. x \u22653.8 1.4. x 9.3. x \u22653.7 1.3. x 9.2. x \u22653.7"},{"location":"Tools/Blog/Mkdocs_Material/#22-linuxmac","title":"2.2 Linux/Mac \u7cfb\u7edf\u5b89\u88c5","text":""},{"location":"Tools/Blog/Mkdocs_Material/#221-python","title":"2.2.1 \u5305\u7ba1\u7406\u5668\u5b89\u88c5 Python","text":""},{"location":"Tools/Blog/Mkdocs_Material/#2211-aptyum","title":"2.2.1.1 apt/yum \u5b89\u88c5\u65b9\u6cd5","text":"<p>Ubuntu/Debian:</p> Bash<pre><code># \u66f4\u65b0\u5305\u7d22\u5f15\nsudo apt update\n\n# \u5b89\u88c5 Python\nsudo apt install python3 python3-pip\n\n# \u5b89\u88c5\u5f00\u53d1\u5de5\u5177\nsudo apt install python3-dev\n</code></pre> <p>CentOS/RHEL:</p> Bash<pre><code># \u5b89\u88c5 EPEL \u4ed3\u5e93\nsudo yum install epel-release\n\n# \u5b89\u88c5 Python\nsudo yum install python3 python3-pip\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2212-brew","title":"2.2.1.2 brew \u5b89\u88c5\u65b9\u6cd5","text":"<p>macOS:</p> Bash<pre><code># \u5b89\u88c5 Homebrew\uff08\u5982\u679c\u672a\u5b89\u88c5\uff09\n/bin/bash -c \"$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)\"\n\n# \u5b89\u88c5 Python\nbrew install python\n\n# \u66f4\u65b0 pip\npip3 install --upgrade pip\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2213","title":"2.2.1.3 \u73af\u5883\u53d8\u91cf\u914d\u7f6e","text":"<p>bash/zsh:</p> Bash<pre><code># \u6dfb\u52a0\u5230 ~/.bashrc \u6216 ~/.zshrc\nexport PATH=\"$HOME/.local/bin:$PATH\"\nexport PYTHONPATH=\"$HOME/.local/lib/python3.x/site-packages:$PYTHONPATH\"\n\n# \u66f4\u65b0\u73af\u5883\u53d8\u91cf\nsource ~/.bashrc  # \u6216 source ~/.zshrc\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#222-pip","title":"2.2.2 pip \u5b89\u88c5\u4f9d\u8d56","text":""},{"location":"Tools/Blog/Mkdocs_Material/#2221","title":"2.2.2.1 \u7cfb\u7edf\u7ea7\u5b89\u88c5","text":"Bash<pre><code># \u5168\u5c40\u5b89\u88c5\uff08\u9700\u8981 root \u6743\u9650\uff09\nsudo pip3 install mkdocs mkdocs-material\n\n# \u9a8c\u8bc1\u5b89\u88c5\nmkdocs --version\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2222","title":"2.2.2.2 \u7528\u6237\u7ea7\u5b89\u88c5","text":"Bash<pre><code># \u7528\u6237\u76ee\u5f55\u5b89\u88c5\npip3 install --user mkdocs mkdocs-material\n\n# \u68c0\u67e5\u5b89\u88c5\u8def\u5f84\npython3 -m site --user-site\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2223","title":"2.2.2.3 \u865a\u62df\u73af\u5883\u5b89\u88c5","text":"Bash<pre><code># \u521b\u5efa\u865a\u62df\u73af\u5883\npython3 -m venv mkdocs-env\n\n# \u6fc0\u6d3b\u865a\u62df\u73af\u5883\nsource mkdocs-env/bin/activate\n\n# \u5b89\u88c5\u4f9d\u8d56\npip install mkdocs mkdocs-material\n\n# \u9000\u51fa\u865a\u62df\u73af\u5883\ndeactivate\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#23","title":"2.3 \u9879\u76ee\u521d\u59cb\u5316","text":""},{"location":"Tools/Blog/Mkdocs_Material/#231","title":"2.3.1 \u521b\u5efa\u9879\u76ee","text":""},{"location":"Tools/Blog/Mkdocs_Material/#2311-mkdocs-new","title":"2.3.1.1 mkdocs new \u547d\u4ee4\u8be6\u89e3","text":"Bash<pre><code># \u57fa\u672c\u8bed\u6cd5\nmkdocs new [\u9879\u76ee\u540d]\n\n# \u521b\u5efa\u65b0\u9879\u76ee\nmkdocs new my-docs\n\n# \u4f7f\u7528\u73b0\u6709\u76ee\u5f55\ncd existing-project\nmkdocs new .\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2312","title":"2.3.1.2 \u9879\u76ee\u547d\u540d\u89c4\u8303","text":"<ul> <li>\u4f7f\u7528\u5c0f\u5199\u5b57\u6bcd</li> <li>\u5355\u8bcd\u95f4\u7528\u8fde\u5b57\u7b26 (-) \u5206\u9694</li> <li>\u907f\u514d\u4f7f\u7528\u7279\u6b8a\u5b57\u7b26</li> <li>\u540d\u79f0\u5177\u6709\u63cf\u8ff0\u6027</li> </ul> <p>\u793a\u4f8b\uff1a</p> Bash<pre><code>mkdocs new technical-docs    # \u597d\u7684\u547d\u540d\nmkdocs new tech_docs        # \u907f\u514d\u4f7f\u7528\u4e0b\u5212\u7ebf\nmkdocs new TechDocs         # \u907f\u514d\u4f7f\u7528\u5927\u5199\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2313","title":"2.3.1.3 \u521d\u59cb\u5316\u914d\u7f6e","text":"<p>\u521b\u5efa\u9879\u76ee\u540e\u7684\u57fa\u672c\u8bbe\u7f6e\uff1a</p> Bash<pre><code>cd my-docs\n# \u542f\u52a8\u5f00\u53d1\u670d\u52a1\u5668\nmkdocs serve\n# \u5728\u6d4f\u89c8\u5668\u4e2d\u8bbf\u95ee http://127.0.0.1:8000\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#232","title":"2.3.2 \u76ee\u5f55\u7ed3\u6784\u8bf4\u660e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#2321","title":"2.3.2.1 \u57fa\u7840\u76ee\u5f55\u7ed3\u6784","text":"Text Only<pre><code>my-docs/\n\u251c\u2500\u2500 docs/               # \u6587\u6863\u76ee\u5f55\n\u2502   \u251c\u2500\u2500 index.md       # \u9996\u9875\n\u2502   \u251c\u2500\u2500 about.md       # \u5176\u4ed6\u9875\u9762\n\u2502   \u2514\u2500\u2500 img/           # \u56fe\u7247\u76ee\u5f55\n\u251c\u2500\u2500 mkdocs.yml         # \u914d\u7f6e\u6587\u4ef6\n\u2514\u2500\u2500 venv/              # \u865a\u62df\u73af\u5883\uff08\u53ef\u9009\uff09\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2322-docs","title":"2.3.2.2 docs \u76ee\u5f55\u7ec4\u7ec7","text":"Text Only<pre><code>docs/\n\u251c\u2500\u2500 index.md           # \u9996\u9875\n\u251c\u2500\u2500 guide/             # \u6307\u5357\u76ee\u5f55\n\u2502   \u251c\u2500\u2500 index.md      # \u6307\u5357\u9996\u9875\n\u2502   \u251c\u2500\u2500 install.md    # \u5b89\u88c5\u8bf4\u660e\n\u2502   \u2514\u2500\u2500 usage.md      # \u4f7f\u7528\u8bf4\u660e\n\u251c\u2500\u2500 api/               # API\u6587\u6863\n\u2502   \u2514\u2500\u2500 index.md      # API\u9996\u9875\n\u2514\u2500\u2500 examples/          # \u793a\u4f8b\u76ee\u5f55\n    \u2514\u2500\u2500 basic.md      # \u57fa\u7840\u793a\u4f8b\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2323","title":"2.3.2.3 \u8d44\u6e90\u6587\u4ef6\u7ba1\u7406","text":"Text Only<pre><code>docs/\n\u251c\u2500\u2500 assets/           # \u8d44\u6e90\u76ee\u5f55\n\u2502   \u251c\u2500\u2500 images/      # \u56fe\u7247\u8d44\u6e90\n\u2502   \u251c\u2500\u2500 css/         # \u6837\u5f0f\u6587\u4ef6\n\u2502   \u251c\u2500\u2500 js/          # \u811a\u672c\u6587\u4ef6\n\u2502   \u2514\u2500\u2500 fonts/       # \u5b57\u4f53\u6587\u4ef6\n\u2514\u2500\u2500 files/           # \u4e0b\u8f7d\u6587\u4ef6\n    \u2514\u2500\u2500 sample.pdf   # \u793a\u4f8b\u6587\u4ef6\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#233","title":"2.3.3 \u57fa\u7840\u914d\u7f6e\u6587\u4ef6","text":""},{"location":"Tools/Blog/Mkdocs_Material/#2331-mkdocs-yml","title":"2.3.3.1 mkdocs. yml \u7ed3\u6784","text":"<p>\u57fa\u672c\u914d\u7f6e\u6587\u4ef6\u7ed3\u6784\uff1a</p> YAML<pre><code># \u7ad9\u70b9\u4fe1\u606f\nsite_name: \u6211\u7684\u6587\u6863\nsite_url: https://example.com/\nsite_author: \u4f5c\u8005\u540d\nsite_description: \u7ad9\u70b9\u63cf\u8ff0\n\n# \u4e3b\u9898\u8bbe\u7f6e\ntheme:\n  name: material\n  language: zh\n  features:\n    - navigation.tabs\n    - navigation.top\n\n# \u5bfc\u822a\u8bbe\u7f6e\nnav:\n  - \u9996\u9875: index.md\n  - \u6307\u5357: \n    - guide/index.md\n    - \u5b89\u88c5: guide/install.md\n    - \u4f7f\u7528: guide/usage.md\n\n# Markdown \u6269\u5c55\nmarkdown_extensions:\n  - attr_list\n  - md_in_html\n  - toc:\n      permalink: true\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2332","title":"2.3.3.2 \u6700\u5c0f\u914d\u7f6e\u793a\u4f8b","text":"<p>\u6700\u7b80\u5355\u7684\u914d\u7f6e\u6587\u4ef6\uff1a</p> YAML<pre><code>site_name: \u6211\u7684\u6587\u6863\ntheme:\n  name: material\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#2333","title":"2.3.3.3 \u914d\u7f6e\u6587\u4ef6\u8bed\u6cd5","text":"<p>YAML \u8bed\u6cd5\u8981\u70b9\uff1a</p> YAML<pre><code># \u5b57\u7b26\u4e32\ntitle: \u6211\u7684\u6587\u6863\n\n# \u5217\u8868\nplugins:\n  - search\n  - tags\n\n# \u5bf9\u8c61\ntheme:\n  name: material\n  features:\n    - navigation.tabs\n\n# \u591a\u884c\u5b57\u7b26\u4e32\ndescription: &gt;\n  \u8fd9\u662f\u4e00\u4e2a\n  \u591a\u884c\u63cf\u8ff0\n  \u793a\u4f8b\n\n# \u951a\u70b9\u5f15\u7528\ncopyright: &amp;copyright 2024 My Docs\nfooter:\n  copyright: *copyright\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3-mkdocs","title":"3 MkDocs \u6838\u5fc3\u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#31","title":"3.1 \u7ad9\u70b9\u4fe1\u606f\u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#311-site_name","title":"3.1.1 site_name \u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3111","title":"3.1.1.1 \u547d\u540d\u89c4\u8303","text":"<p>\u7f51\u7ad9\u540d\u79f0\u662f\u7ad9\u70b9\u7684\u7b2c\u4e00\u5370\u8c61\uff0c\u5e94\u9075\u5faa\u4ee5\u4e0b\u89c4\u8303\uff1a</p> YAML<pre><code># \u63a8\u8350\u7684\u547d\u540d\u65b9\u5f0f\nsite_name: \u6280\u672f\u6587\u6863\u4e2d\u5fc3\nsite_name: Developer Hub\nsite_name: API Documentation\n\n# \u907f\u514d\u7684\u547d\u540d\u65b9\u5f0f\nsite_name: docs            # \u592a\u8fc7\u7b80\u5355\nsite_name: My Doc Site     # \u4e0d\u591f\u4e13\u4e1a\nsite_name: TEST           # \u7f3a\u4e4f\u63cf\u8ff0\u6027\n</code></pre> <p>\u547d\u540d\u5efa\u8bae\uff1a</p> <ul> <li>\u4f7f\u7528\u7b80\u6d01\u660e\u4e86\u7684\u540d\u79f0</li> <li>\u53cd\u6620\u6587\u6863\u7684\u4e3b\u8981\u5185\u5bb9</li> <li>\u8003\u8651\u54c1\u724c\u8bc6\u522b\u5ea6</li> <li>\u907f\u514d\u4f7f\u7528\u7279\u6b8a\u5b57\u7b26</li> <li>\u9002\u5f53\u4f7f\u7528\u7a7a\u683c\u5206\u9694\u5355\u8bcd</li> </ul>"},{"location":"Tools/Blog/Mkdocs_Material/#3112","title":"3.1.1.2 \u591a\u8bed\u8a00\u652f\u6301","text":"<p>\u53ef\u4ee5\u901a\u8fc7\u914d\u7f6e\u5b9e\u73b0\u591a\u8bed\u8a00\u7ad9\u70b9\uff1a</p> YAML<pre><code># \u57fa\u7840\u914d\u7f6e\nsite_name: My Documentation\ntheme:\n  language: zh\n\n# \u591a\u8bed\u8a00\u914d\u7f6e\u793a\u4f8b\nextra:\n  alternate:\n    - name: English\n      link: /en/ \n      lang: en\n    - name: \u4e2d\u6587\n      link: /zh/\n      lang: zh\n\n# \u8bed\u8a00\u7279\u5b9a\u7684\u7ad9\u70b9\u540d\u79f0\nsite_name:\n  en: My Documentation\n  zh: \u6211\u7684\u6587\u6863\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3113-seo","title":"3.1.1.3 SEO \u4f18\u5316","text":"<p>\u901a\u8fc7\u5408\u9002\u7684\u7ad9\u70b9\u540d\u79f0\u63d0\u5347 SEO\uff1a</p> YAML<pre><code># SEO \u4f18\u5316\u914d\u7f6e\nsite_name: ProductName Documentation | CompanyName\nextra:\n  meta:\n    - name: robots\n      content: 'index, follow'\n    - name: keywords\n      content: 'docs, documentation, technical, api'\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#312-site_url","title":"3.1.2 site_url \u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3121-url","title":"3.1.2.1 URL \u683c\u5f0f\u8981\u6c42","text":"YAML<pre><code># \u6b63\u786e\u7684 URL \u683c\u5f0f\nsite_url: https://example.com/docs/\nsite_url: https://docs.example.com/\n\n# \u907f\u514d\u7684\u683c\u5f0f\nsite_url: http://example.com/docs    # \u7f3a\u5c11\u5c3e\u90e8\u659c\u6760\nsite_url: example.com/docs/          # \u7f3a\u5c11\u534f\u8bae\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3122","title":"3.1.2.2 \u57fa\u7840\u8def\u5f84\u914d\u7f6e","text":"YAML<pre><code># \u6839\u76ee\u5f55\u90e8\u7f72\nsite_url: https://example.com/\n\n# \u5b50\u76ee\u5f55\u90e8\u7f72\nsite_url: https://example.com/docs/\nuse_directory_urls: true  # \u63a8\u8350\u8bbe\u7f6e\n\n# \u672c\u5730\u5f00\u53d1\nsite_url: http://localhost:8000/\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3123","title":"3.1.2.3 \u5b50\u76ee\u5f55\u90e8\u7f72\u914d\u7f6e","text":"YAML<pre><code># GitHub Pages \u5b50\u76ee\u5f55\u90e8\u7f72\nsite_url: https://username.github.io/repository/\n\n# \u81ea\u5b9a\u4e49\u57df\u540d\u5b50\u76ee\u5f55\nsite_url: https://docs.example.com/project/\nextra:\n  base_path: /project/  # \u5982\u679c\u9700\u8981\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#313-site_author","title":"3.1.3 site_author \u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3131","title":"3.1.3.1 \u4f5c\u8005\u4fe1\u606f\u8bbe\u7f6e","text":"YAML<pre><code># \u57fa\u7840\u4f5c\u8005\u4fe1\u606f\nsite_author: John Doe\n\n# \u6269\u5c55\u4f5c\u8005\u4fe1\u606f\nextra:\n  author:\n    name: John Doe\n    email: john@example.com\n    website: https://johndoe.com\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3132","title":"3.1.3.2 \u7248\u6743\u4fe1\u606f","text":"YAML<pre><code># \u7248\u6743\u58f0\u660e\ncopyright: \"&amp;copy; 2024 John Doe\"\n\n# \u9ad8\u7ea7\u7248\u6743\u914d\u7f6e\nextra:\n  copyright:\n    author: John Doe\n    year: 2024\n    license: CC BY-NC-SA 4.0\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3133-meta","title":"3.1.3.3 meta \u4fe1\u606f","text":"YAML<pre><code># meta \u4fe1\u606f\u914d\u7f6e\nextra:\n  meta:\n    - name: author\n      content: John Doe\n    - name: contact\n      content: contact@example.com\n    - property: article:author\n      content: https://example.com/author\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#314-site_description","title":"3.1.4 site_description \u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3141-seo","title":"3.1.4.1 SEO \u63cf\u8ff0","text":"YAML<pre><code># \u57fa\u7840\u63cf\u8ff0\nsite_description: \u5168\u9762\u7684\u6280\u672f\u6587\u6863\u4e2d\u5fc3\uff0c\u63d0\u4f9b\u8be6\u7ec6\u7684API\u6587\u6863\u3001\u4f7f\u7528\u6307\u5357\u548c\u6700\u4f73\u5b9e\u8df5\u3002\n\n# \u591a\u8bed\u8a00\u63cf\u8ff0\nextra:\n  descriptions:\n    en: Comprehensive technical documentation center\n    zh: \u5168\u9762\u7684\u6280\u672f\u6587\u6863\u4e2d\u5fc3\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3142","title":"3.1.4.2 \u5173\u952e\u8bcd\u8bbe\u7f6e","text":"YAML<pre><code># \u901a\u8fc7 meta \u6807\u7b7e\u8bbe\u7f6e\u5173\u952e\u8bcd\nextra:\n  meta:\n    - name: keywords\n      content: MkDocs, documentation, technical docs, API, guides\n    - name: description\n      content: &gt;-\n        \u5168\u9762\u7684\u6280\u672f\u6587\u6863\u4e2d\u5fc3\uff0c\u5305\u542b\u8be6\u7ec6\u7684API\u6587\u6863\u3001\n        \u4f7f\u7528\u6307\u5357\u548c\u6700\u4f73\u5b9e\u8df5\u793a\u4f8b\u3002\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3143","title":"3.1.4.3 \u7ad9\u70b9\u6458\u8981","text":"YAML<pre><code># \u5b8c\u6574\u7684\u7ad9\u70b9\u4fe1\u606f\u914d\u7f6e\u793a\u4f8b\nsite_name: \u6280\u672f\u6587\u6863\u4e2d\u5fc3\nsite_description: &gt;-\n  \u63d0\u4f9b\u5168\u9762\u7684\u6280\u672f\u6587\u6863\u3001API\u53c2\u8003\u548c\u4f7f\u7528\u6307\u5357\uff0c\n  \u5e2e\u52a9\u5f00\u53d1\u8005\u5feb\u901f\u4e0a\u624b\u548c\u6df1\u5165\u4e86\u89e3\u4ea7\u54c1\u529f\u80fd\u3002\nsite_author: \u5f00\u53d1\u56e2\u961f\nsite_url: https://docs.example.com/\n\nextra:\n  meta:\n    - name: keywords\n      content: \u6280\u672f\u6587\u6863, API\u6587\u6863, \u5f00\u53d1\u6307\u5357, \u6700\u4f73\u5b9e\u8df5\n    - name: author\n      content: \u5f00\u53d1\u56e2\u961f\n    - name: robots\n      content: index, follow\n\n  analytics:\n    gtag: G-XXXXXXXXXX\n\ncopyright: \"&amp;copy; 2024 Example Company\"\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#315","title":"3.1.5 \u914d\u7f6e\u6700\u4f73\u5b9e\u8df5","text":"<ol> <li> <p>SEO \u4f18\u5316\u5efa\u8bae\uff1a    - \u4f7f\u7528\u6e05\u6670\u7684\u7ad9\u70b9\u540d\u79f0    - \u7f16\u5199\u6709\u5438\u5f15\u529b\u7684\u63cf\u8ff0    - \u5305\u542b\u76f8\u5173\u5173\u952e\u8bcd    - \u786e\u4fdd URL \u7ed3\u6784\u5408\u7406</p> </li> <li> <p>\u591a\u8bed\u8a00\u652f\u6301\uff1a    - \u4e3a\u6bcf\u79cd\u8bed\u8a00\u63d0\u4f9b\u72ec\u7acb\u63cf\u8ff0    - \u4f7f\u7528\u6b63\u786e\u7684\u8bed\u8a00\u4ee3\u7801    - \u8bbe\u7f6e\u5408\u9002\u7684\u5b57\u7b26\u7f16\u7801</p> </li> <li> <p>\u7248\u672c\u63a7\u5236\uff1a    - \u8bb0\u5f55\u914d\u7f6e\u66f4\u6539    - \u4f7f\u7528\u7248\u672c\u6ce8\u91ca    - \u5b9a\u671f\u66f4\u65b0\u7ad9\u70b9\u4fe1\u606f</p> </li> <li> <p>\u53ef\u7ef4\u62a4\u6027\uff1a    - \u4f7f\u7528\u6e05\u6670\u7684\u914d\u7f6e\u7ed3\u6784    - \u6dfb\u52a0\u5fc5\u8981\u7684\u6ce8\u91ca    - \u4fdd\u6301\u914d\u7f6e\u6587\u4ef6\u6574\u6d01</p> </li> </ol>"},{"location":"Tools/Blog/Mkdocs_Material/#32","title":"3.2 \u5bfc\u822a\u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#321-nav","title":"3.2.1 nav \u7ed3\u6784\u8bbe\u8ba1","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3211","title":"3.2.1.1 \u57fa\u7840\u5bfc\u822a\u7ed3\u6784","text":"<p>\u6700\u57fa\u672c\u7684\u5bfc\u822a\u914d\u7f6e\u793a\u4f8b\uff1a</p> YAML<pre><code>nav:\n  - Home: index.md\n  - About: about.md\n  - Contact: contact.md\n</code></pre> <p>\u66f4\u590d\u6742\u7684\u5206\u7ec4\u793a\u4f8b\uff1a</p> YAML<pre><code>nav:\n  - \u9996\u9875: index.md\n  - \u7528\u6237\u6307\u5357:\n    - \u4ecb\u7ecd: guide/introduction.md\n    - \u5feb\u901f\u5f00\u59cb: guide/getting-started.md\n    - \u57fa\u7840\u6559\u7a0b: guide/basics.md\n  - API \u6587\u6863:\n    - \u6982\u89c8: api/overview.md\n    - \u63a5\u53e3\u8bf4\u660e: api/reference.md\n  - \u5e38\u89c1\u95ee\u9898: faq.md\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3212","title":"3.2.1.2 \u5206\u7c7b\u7ec4\u7ec7","text":"<p>\u63a8\u8350\u7684\u5206\u7c7b\u65b9\u5f0f\uff1a</p> YAML<pre><code>nav:\n  - \u5f00\u59cb\u4f7f\u7528:\n    - \u7b80\u4ecb: getting-started/introduction.md\n    - \u5b89\u88c5: getting-started/installation.md\n    - \u914d\u7f6e: getting-started/configuration.md\n\n  - \u6838\u5fc3\u6982\u5ff5:\n    - \u6982\u8ff0: concepts/overview.md\n    - \u57fa\u7840\u67b6\u6784: concepts/architecture.md\n    - \u5de5\u4f5c\u539f\u7406: concepts/how-it-works.md\n\n  - \u9ad8\u7ea7\u6307\u5357:\n    - \u81ea\u5b9a\u4e49\u4e3b\u9898: advanced/custom-theme.md\n    - \u63d2\u4ef6\u5f00\u53d1: advanced/plugin-development.md\n    - \u6027\u80fd\u4f18\u5316: advanced/performance.md\n\n  - \u53c2\u8003\u6587\u6863:\n    - API: reference/api.md\n    - \u914d\u7f6e\u9879: reference/configuration.md\n    - \u547d\u4ee4\u884c: reference/cli.md\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3213","title":"3.2.1.3 \u6743\u91cd\u8bbe\u7f6e","text":"<p>\u4f7f\u7528\u6587\u4ef6\u540d\u524d\u7f00\u63a7\u5236\u987a\u5e8f\uff1a</p> YAML<pre><code>docs/\n\u251c\u2500\u2500 01_introduction.md\n\u251c\u2500\u2500 02_installation.md\n\u251c\u2500\u2500 03_configuration.md\n\u2514\u2500\u2500 04_usage.md\n\n# mkdocs.yml\nnav:\n  - \u4ecb\u7ecd: 01_introduction.md\n  - \u5b89\u88c5: 02_installation.md\n  - \u914d\u7f6e: 03_configuration.md\n  - \u4f7f\u7528: 04_usage.md\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#322","title":"3.2.2 \u6587\u4ef6\u7ec4\u7ec7","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3221","title":"3.2.2.1 \u6587\u4ef6\u547d\u540d\u89c4\u8303","text":"<p>\u63a8\u8350\u7684\u547d\u540d\u89c4\u8303\uff1a</p> Text Only<pre><code>docs/\n\u251c\u2500\u2500 index.md                    # \u9996\u9875\n\u251c\u2500\u2500 getting-started.md         # \u77ed\u6a2a\u7ebf\u5206\u9694\n\u251c\u2500\u2500 advanced_usage.md          # \u4e0b\u5212\u7ebf\u5206\u9694\uff08\u53ef\u9009\uff09\n\u2514\u2500\u2500 troubleshooting.md         # \u5168\u5c0f\u5199\n</code></pre> <p>\u6587\u4ef6\u547d\u540d\u5efa\u8bae\uff1a</p> <ul> <li>\u4f7f\u7528\u5c0f\u5199\u5b57\u6bcd</li> <li>\u5355\u8bcd\u95f4\u4f7f\u7528\u8fde\u5b57\u7b26\u6216\u4e0b\u5212\u7ebf</li> <li>\u6587\u4ef6\u540d\u5e94\u5177\u6709\u63cf\u8ff0\u6027</li> <li>\u4fdd\u6301\u547d\u540d\u4e00\u81f4\u6027</li> <li>\u907f\u514d\u4f7f\u7528\u7a7a\u683c\u548c\u7279\u6b8a\u5b57\u7b26</li> </ul>"},{"location":"Tools/Blog/Mkdocs_Material/#3222","title":"3.2.2.2 \u76ee\u5f55\u7ec4\u7ec7\u539f\u5219","text":"<p>\u6807\u51c6\u76ee\u5f55\u7ed3\u6784\uff1a</p> Text Only<pre><code>docs/\n\u251c\u2500\u2500 index.md                # \u7f51\u7ad9\u9996\u9875\n\u251c\u2500\u2500 getting-started/        # \u5165\u95e8\u6307\u5357\n\u2502   \u251c\u2500\u2500 index.md           # \u5206\u7c7b\u9996\u9875\n\u2502   \u251c\u2500\u2500 installation.md    # \u5b89\u88c5\u8bf4\u660e\n\u2502   \u2514\u2500\u2500 configuration.md   # \u914d\u7f6e\u8bf4\u660e\n\u251c\u2500\u2500 user-guide/            # \u7528\u6237\u6307\u5357\n\u2502   \u251c\u2500\u2500 index.md          # \u6307\u5357\u9996\u9875\n\u2502   \u251c\u2500\u2500 basic-usage.md    # \u57fa\u7840\u7528\u6cd5\n\u2502   \u2514\u2500\u2500 advanced.md       # \u9ad8\u7ea7\u7279\u6027\n\u2514\u2500\u2500 api/                   # API\u6587\u6863\n    \u251c\u2500\u2500 index.md          # API\u6982\u89c8\n    \u251c\u2500\u2500 endpoints.md      # \u63a5\u53e3\u5217\u8868\n    \u2514\u2500\u2500 authentication.md # \u8ba4\u8bc1\u8bf4\u660e\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3223","title":"3.2.2.3 \u7d22\u5f15\u6587\u4ef6\u4f7f\u7528","text":"<p>\u6bcf\u4e2a\u76ee\u5f55\u7684 index. md \u793a\u4f8b\uff1a</p> Markdown<pre><code># \u7528\u6237\u6307\u5357\n\n\u8fd9\u662f\u7528\u6237\u6307\u5357\u7684\u4e3b\u9875\u9762\uff0c\u5305\u542b\u4ee5\u4e0b\u5185\u5bb9\uff1a\n\n## \u5feb\u901f\u5bfc\u822a\n\n-  [\u57fa\u7840\u7528\u6cd5] (basic-usage.md) - \u5165\u95e8\u5fc5\u8bfb\n-  [\u9ad8\u7ea7\u7279\u6027] (advanced.md) - \u6df1\u5165\u4e86\u89e3\n\n## \u672c\u8282\u5185\u5bb9\n\n\u6b64\u90e8\u5206\u5c06\u5e2e\u52a9\u60a8\u4e86\u89e3\u4ea7\u54c1\u7684\u6838\u5fc3\u529f\u80fd\u548c\u4f7f\u7528\u65b9\u6cd5...\n</code></pre> <p>\u5bf9\u5e94\u7684\u5bfc\u822a\u914d\u7f6e\uff1a</p> YAML<pre><code>nav:\n  - \u7528\u6237\u6307\u5357:\n    - \u6982\u8ff0: user-guide/index.md\n    - \u57fa\u7840\u7528\u6cd5: user-guide/basic-usage.md\n    - \u9ad8\u7ea7\u7279\u6027: user-guide/advanced.md\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#323","title":"3.2.3 \u591a\u7ea7\u76ee\u5f55","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3231","title":"3.2.3.1 \u5c42\u7ea7\u7ed3\u6784\u8bbe\u8ba1","text":"<p>\u590d\u6742\u7684\u591a\u7ea7\u76ee\u5f55\u793a\u4f8b\uff1a</p> YAML<pre><code>nav:\n  - \u9996\u9875: index.md\n  - \u5165\u95e8\u6307\u5357:\n    - \u6982\u8ff0: getting-started/index.md\n    - \u57fa\u7840:\n      - \u5b89\u88c5: getting-started/basics/installation.md\n      - \u914d\u7f6e: getting-started/basics/configuration.md\n    - \u8fdb\u9636:\n      - \u81ea\u5b9a\u4e49: getting-started/advanced/customization.md\n      - \u4f18\u5316: getting-started/advanced/optimization.md\n  - \u5f00\u53d1\u6587\u6863:\n    - \u6982\u8ff0: development/index.md\n    - API:\n      - \u8ba4\u8bc1: development/api/authentication.md\n      - \u63a5\u53e3: development/api/endpoints.md\n    - SDK:\n      - Python: development/sdk/python.md\n      - JavaScript: development/sdk/javascript.md\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3232","title":"3.2.3.2 \u5bfc\u822a\u6df1\u5ea6\u63a7\u5236","text":"YAML<pre><code>theme:\n  name: material\n  features:\n    - navigation.sections  # \u663e\u793a\u7ae0\u8282\n    - navigation.expand   # \u5c55\u5f00\u5bfc\u822a\n    - navigation.indexes  # \u4f7f\u7528\u76ee\u5f55\u7d22\u5f15\n    - toc.integrate      # \u96c6\u6210\u76ee\u5f55\n\nmarkdown_extensions:\n  - toc:\n      permalink: true\n      toc_depth: 3       # \u63a7\u5236\u76ee\u5f55\u6df1\u5ea6\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3233","title":"3.2.3.3 \u6298\u53e0\u914d\u7f6e","text":"<p>Material \u4e3b\u9898\u7684\u6298\u53e0\u914d\u7f6e\uff1a</p> YAML<pre><code>theme:\n  name: material\n  features:\n    - navigation.sections    # \u663e\u793a\u5206\u533a\n    - navigation.expand     # \u9ed8\u8ba4\u5c55\u5f00\n    - navigation.indexes    # \u4f7f\u7528\u7d22\u5f15\u9875\n    - navigation.top        # \u8fd4\u56de\u9876\u90e8\u6309\u94ae\n\n  # \u5bfc\u822a\u680f\u8bbe\u7f6e\n  nav_style: dark          # \u5bfc\u822a\u680f\u6837\u5f0f\n  collapse_navigation: true # \u6298\u53e0\u5bfc\u822a\n  sticky_navigation: true  # \u56fa\u5b9a\u5bfc\u822a\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#324","title":"3.2.4 \u5bfc\u822a\u914d\u7f6e\u6700\u4f73\u5b9e\u8df5","text":"<ol> <li> <p>\u7ed3\u6784\u8bbe\u8ba1\u539f\u5219\uff1a    - \u4fdd\u6301\u5c42\u7ea7\u6e05\u6670    - \u63a7\u5236\u5bfc\u822a\u6df1\u5ea6\uff08\u5efa\u8bae\u4e0d\u8d85\u8fc7 3 \u5c42\uff09    - \u76f8\u5173\u5185\u5bb9\u5206\u7ec4    - \u4f7f\u7528\u76f4\u89c2\u7684\u547d\u540d</p> </li> <li> <p>\u6587\u4ef6\u7ec4\u7ec7\uff1a    - \u4f7f\u7528\u6709\u610f\u4e49\u7684\u76ee\u5f55\u540d    - \u4fdd\u6301\u6587\u4ef6\u7ed3\u6784\u6574\u6d01    - \u5408\u7406\u4f7f\u7528\u7d22\u5f15\u6587\u4ef6    - \u9075\u5faa\u4e00\u81f4\u7684\u547d\u540d\u89c4\u8303</p> </li> <li> <p>\u7528\u6237\u4f53\u9a8c\uff1a    - \u63d0\u4f9b\u6e05\u6670\u7684\u5bfc\u822a\u8def\u5f84    - \u6dfb\u52a0\u5408\u9002\u7684\u63cf\u8ff0    - \u8003\u8651\u79fb\u52a8\u7aef\u663e\u793a    - \u4f18\u5316\u5bfc\u822a\u54cd\u5e94\u901f\u5ea6</p> </li> <li> <p>\u7ef4\u62a4\u5efa\u8bae\uff1a    - \u5b9a\u671f\u68c0\u67e5\u6b7b\u94fe\u63a5    - \u66f4\u65b0\u5bfc\u822a\u7ed3\u6784    - \u4fdd\u6301\u6587\u6863\u540c\u6b65    - \u6536\u96c6\u7528\u6237\u53cd\u9988</p> </li> </ol>"},{"location":"Tools/Blog/Mkdocs_Material/#325","title":"3.2.5 \u7279\u6b8a\u5bfc\u822a\u529f\u80fd","text":"<ol> <li>\u9690\u85cf\u9875\u9762\uff1a</li> </ol> YAML<pre><code>nav:\n  - \u53ef\u89c1\u9875\u9762: visible.md\n  - !hidden \u9690\u85cf\u9875\u9762: hidden.md\n</code></pre> <ol> <li>\u5916\u90e8\u94fe\u63a5\uff1a</li> </ol> YAML<pre><code>nav:\n  - \u6587\u6863: index.md\n  - GitHub: https://github.com/your/repo\n  - \u793e\u533a: \n    - \u8bba\u575b: https://forum.example.com\n    - \u535a\u5ba2: https://blog.example.com\n</code></pre> <ol> <li>\u522b\u540d\u8bbe\u7f6e\uff1a</li> </ol> YAML<pre><code>nav:\n  - \u5f00\u59cb: \n    - \u6982\u8ff0: getting-started/index.md\n    - \u5feb\u901f\u5165\u95e8: getting-started/quickstart.md\n    - \u540c\u4e00\u6587\u4ef6\u4e0d\u540c\u5165\u53e3: !alias getting-started/quickstart.md\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#33-markdown","title":"3.3 Markdown \u6269\u5c55","text":""},{"location":"Tools/Blog/Mkdocs_Material/#331","title":"3.3.1 \u57fa\u7840\u6269\u5c55","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3311-meta","title":"3.3.1.1 meta \u6269\u5c55","text":"<p>\u652f\u6301\u5728 Markdown \u6587\u4ef6\u5934\u90e8\u6dfb\u52a0\u5143\u6570\u636e\uff1a</p> YAML<pre><code># mkdocs.yml \u914d\u7f6e\nmarkdown_extensions:\n  - meta\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Markdown<pre><code>---\ntitle: \u6211\u7684\u9875\u9762\u6807\u9898\ndescription: \u9875\u9762\u63cf\u8ff0\nauthor: \u4f5c\u8005\u540d\ndate: 2024-01-01\n---\n\n# \u6b63\u6587\u5185\u5bb9\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3312-toc","title":"3.3.1.2 toc \u6269\u5c55","text":"<p>\u81ea\u52a8\u751f\u6210\u76ee\u5f55\uff1a</p> YAML<pre><code>markdown_extensions:\n  - toc:\n      permalink: true        # \u6dfb\u52a0\u6bb5\u843d\u94fe\u63a5\n      toc_depth: 3          # \u76ee\u5f55\u6df1\u5ea6\n      separator: \"_\"        # \u6807\u9898\u951a\u70b9\u5206\u9694\u7b26\n      title: \"\u76ee\u5f55\"         # \u76ee\u5f55\u6807\u9898\n      slugify: !!python/object/apply:pymdownx.slugs.slugify\n        kwds: {case: lower} # URL \u8f6c\u6362\u89c4\u5219\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Markdown<pre><code>[TOC]\n\n# \u4e00\u7ea7\u6807\u9898\n## \u4e8c\u7ea7\u6807\u9898\n### \u4e09\u7ea7\u6807\u9898\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3313-tables","title":"3.3.1.3 tables \u6269\u5c55","text":"<p>\u589e\u5f3a\u7684\u8868\u683c\u652f\u6301\uff1a</p> YAML<pre><code>markdown_extensions:\n  - tables\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Markdown<pre><code>| \u529f\u80fd | \u57fa\u7840\u7248 | \u4e13\u4e1a\u7248 |\n|-----|:------:|-------:|\n| \u529f\u80fdA | \u2713 | \u2713 |\n| \u529f\u80fdB | \u2717 | \u2713 |\n| \u529f\u80fdC | \u2717 | \u2713 |\n\n: \u8868\u683c\u6807\u9898 {.class-name}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#332-pymdown-extensions","title":"3.3.2 PyMdown Extensions","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3321-superfences","title":"3.3.2.1 superfences \u914d\u7f6e","text":"<p>\u589e\u5f3a\u7684\u4ee3\u7801\u5757\u529f\u80fd\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.superfences:\n      custom_fences:\n        - name: mermaid\n          class: mermaid\n          format: !!python/name:pymdownx.superfences.fence_div_format\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Markdown<pre><code>```python title=\"example.py\" linenums=\"1\" hl_lines=\"2 3\"\ndef hello_world():\n    message = \"Hello, World!\"\n    print(message)\n    return message\n```\n\n```mermaid\ngraph LR\n    A[\u5f00\u59cb] --&gt; B{\u5224\u65ad}\n    B --&gt; |Yes| C[\u6267\u884c]\n    B --&gt; |No| D[\u8df3\u8fc7]\n```\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3322-emoji","title":"3.3.2.2 emoji \u652f\u6301","text":"<p>\u6dfb\u52a0\u8868\u60c5\u7b26\u53f7\u652f\u6301\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.emoji:\n      emoji_index: !!python/name:material.extensions.emoji.twemoji\n      emoji_generator: !!python/name:material.extensions.emoji.to_svg\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Markdown<pre><code>:smile: :heart: :thumbsup:\n\n:fontawesome-brands-github: GitHub\n:material-account: \u7528\u6237\n:octicons-repo-16: \u4ed3\u5e93\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3323-tasklist","title":"3.3.2.3 tasklist \u529f\u80fd","text":"<p>\u4efb\u52a1\u5217\u8868\u652f\u6301\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.tasklist:\n      custom_checkbox: true    # \u81ea\u5b9a\u4e49\u590d\u9009\u6846\u6837\u5f0f\n      clickable_checkbox: true # \u53ef\u70b9\u51fb\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Markdown<pre><code>- [x] \u5df2\u5b8c\u6210\u4efb\u52a1\n- [ ] \u672a\u5b8c\u6210\u4efb\u52a1\n  - [x] \u5b50\u4efb\u52a1 1\n  - [ ] \u5b50\u4efb\u52a1 2\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3324-pymdown","title":"3.3.2.4 \u5176\u4ed6\u5e38\u7528 PyMdown \u6269\u5c55","text":"YAML<pre><code>markdown_extensions:\n  - pymdownx.highlight     # \u4ee3\u7801\u9ad8\u4eae\n  - pymdownx.inlinehilite # \u884c\u5185\u4ee3\u7801\u9ad8\u4eae\n  - pymdownx.snippets     # \u4ee3\u7801\u7247\u6bb5\n  - pymdownx.magiclink    # \u81ea\u52a8\u94fe\u63a5\n  - pymdownx.mark        # ==\u6807\u8bb0==\n  - pymdownx.critic      # \u7f16\u8f91\u6807\u8bb0\n  - pymdownx.tilde      # \u5220\u9664\u7ebf\n  - pymdownx.caret      # \u4e0a\u6807\n  - pymdownx.keys       # \u952e\u76d8\u6309\u952e\n  - pymdownx.tabbed    # \u6807\u7b7e\u9875\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#333","title":"3.3.3 \u81ea\u5b9a\u4e49\u6269\u5c55","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3331","title":"3.3.3.1 \u6269\u5c55\u5f00\u53d1\u57fa\u7840","text":"<p>\u521b\u5efa\u81ea\u5b9a\u4e49\u6269\u5c55\uff1a</p> Python<pre><code># custom_extension.py\nfrom markdown.extensions import Extension\nfrom markdown.preprocessors import Preprocessor\n\nclass CustomPreprocessor(Preprocessor):\n    def run(self, lines):\n        new_lines = []\n        for line in lines:\n            new_lines.append(line.replace('[[', '**').replace(']]', '**'))\n        return new_lines\n\nclass CustomExtension(Extension):\n    def extendMarkdown(self, md):\n        md.preprocessors.register(CustomPreprocessor(md), 'custom_preprocessor', 175)\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#34","title":"3.4 \u5e38\u7528\u6269\u5c55\u793a\u4f8b","text":"<ol> <li>\u6dfb\u52a0\u81ea\u5b9a\u4e49 HTML \u5c5e\u6027\uff1a</li> </ol> Python<pre><code>from markdown.extensions import Extension\nfrom markdown.treeprocessors import Treeprocessor\n\nclass CustomAttributesTreeprocessor(Treeprocessor):\n    def run(self, root):\n        for elem in root.iter():\n            if 'class' in elem.attrib:\n                elem.set('data-custom', 'value')\n\nclass CustomAttributesExtension(Extension):\n    def extendMarkdown(self, md):\n        md.treeprocessors.register(\n            CustomAttributesTreeprocessor(md), 'custom_attributes', 15\n        )\n</code></pre> <ol> <li>\u81ea\u5b9a\u4e49\u5bb9\u5668\uff1a</li> </ol> Python<pre><code>from markdown.extensions import Extension\nfrom markdown.blockprocessors import BlockProcessor\nimport re\n\nclass CustomContainerProcessor(BlockProcessor):\n    RE = re.compile(r':{3,}\\ *(warning|note|tip)\\ *')\n\n    def run(self, parent, blocks):\n        block = blocks.pop(0)\n        m = self.RE.match(block)\n\n        if m:\n            container_type = m.group(1)\n            div = etree.SubElement(parent, 'div')\n            div.set('class', f'custom-container {container_type}')\n\n            # \u5904\u7406\u5bb9\u5668\u5185\u5bb9\n            self.parser.parseChunk(div, block[m.end():])\n\nclass CustomContainerExtension(Extension):\n    def extendMarkdown(self, md):\n        md.parser.blockprocessors.register(\n            CustomContainerProcessor(md.parser), 'custom_container', 175\n        )\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#341","title":"3.4.1 \u6269\u5c55\u914d\u7f6e\u65b9\u6cd5","text":"<p>\u5728 <code>mkdocs.yml</code> \u4e2d\u914d\u7f6e\u81ea\u5b9a\u4e49\u6269\u5c55\uff1a</p> YAML<pre><code>markdown_extensions:\n  - custom_extension:\n      option1: value1\n      option2: value2\n\nextra_css:\n  - css/custom_extension.css\n\nextra_javascript:\n  - js/custom_extension.js\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#342","title":"3.4.2 \u6269\u5c55\u7ec4\u5408\u63a8\u8350","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3421","title":"3.4.2.1 \u57fa\u7840\u6587\u6863\u914d\u7f6e","text":"YAML<pre><code>markdown_extensions:\n  - meta\n  - toc:\n      permalink: true\n  - tables\n  - attr_list\n  - def_list\n  - footnotes\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3422","title":"3.4.2.2 \u589e\u5f3a\u529f\u80fd\u914d\u7f6e","text":"YAML<pre><code>markdown_extensions:\n  - pymdownx.superfences:\n      custom_fences:\n        - name: mermaid\n          class: mermaid\n          format: !!python/name:pymdownx.superfences.fence_div_format\n  - pymdownx.highlight:\n      anchor_linenums: true\n  - pymdownx.inlinehilite\n  - pymdownx.snippets\n  - pymdownx.tasklist:\n      custom_checkbox: true\n  - pymdownx.emoji:\n      emoji_index: !!python/name:material.extensions.emoji.twemoji\n      emoji_generator: !!python/name:material.extensions.emoji.to_svg\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#343","title":"3.4.3 \u5b8c\u6574\u63a8\u8350\u914d\u7f6e","text":"YAML<pre><code>markdown_extensions:\n  # Python Markdown\n  - meta\n  - toc:\n      permalink: true\n      toc_depth: 4\n  - tables\n  - attr_list\n  - def_list\n  - md_in_html\n  - footnotes\n\n  # Python Markdown Extensions\n  - pymdownx.superfences\n  - pymdownx.highlight\n  - pymdownx.inlinehilite\n  - pymdownx.snippets\n  - pymdownx.tasklist\n  - pymdownx.emoji\n  - pymdownx.mark\n  - pymdownx.critic\n  - pymdownx.keys\n  - pymdownx.tilde\n  - pymdownx.caret\n  - pymdownx.details\n  - pymdownx.magiclink\n  - pymdownx.tabbed:\n      alternate_style: true\n\n  # \u81ea\u5b9a\u4e49\u6269\u5c55\n  - custom_extension:\n      custom_option: value\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#344","title":"3.4.4 \u4f7f\u7528\u5efa\u8bae","text":"<ol> <li> <p>\u6027\u80fd\u8003\u8651\uff1a    - \u53ea\u542f\u7528\u9700\u8981\u7684\u6269\u5c55    - \u6ce8\u610f\u6269\u5c55\u4e4b\u95f4\u7684\u4f9d\u8d56\u5173\u7cfb    - \u63a7\u5236\u6269\u5c55\u6570\u91cf</p> </li> <li> <p>\u517c\u5bb9\u6027\uff1a    - \u6d4b\u8bd5\u6269\u5c55\u7ec4\u5408    - \u68c0\u67e5\u79fb\u52a8\u7aef\u663e\u793a    - \u9a8c\u8bc1\u4e0d\u540c\u6d4f\u89c8\u5668</p> </li> <li> <p>\u7ef4\u62a4\u5efa\u8bae\uff1a    - \u8bb0\u5f55\u6269\u5c55\u914d\u7f6e    - \u4fdd\u6301\u7248\u672c\u66f4\u65b0    - \u76d1\u63a7\u6027\u80fd\u5f71\u54cd</p> </li> </ol>"},{"location":"Tools/Blog/Mkdocs_Material/#35","title":"3.5 \u63d2\u4ef6\u7cfb\u7edf","text":""},{"location":"Tools/Blog/Mkdocs_Material/#351","title":"3.5.1 \u63d2\u4ef6\u914d\u7f6e\u65b9\u5f0f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3511","title":"3.5.1.1 \u63d2\u4ef6\u5b89\u88c5\u65b9\u6cd5","text":"<p>\u901a\u8fc7 pip \u5b89\u88c5\u63d2\u4ef6\uff1a</p> Bash<pre><code># \u5b89\u88c5\u5355\u4e2a\u63d2\u4ef6\npip install mkdocs-git-revision-date-localized-plugin\n\n# \u5b89\u88c5\u591a\u4e2a\u63d2\u4ef6\npip install mkdocs-minify-plugin mkdocs-git-authors-plugin\n</code></pre> <p>\u57fa\u7840\u63d2\u4ef6\u914d\u7f6e\uff1a</p> YAML<pre><code># mkdocs.yml\nplugins:\n  - search  # \u9ed8\u8ba4\u63d2\u4ef6\n  - git-revision-date-localized:\n      enable_creation_date: true\n  - minify:\n      minify_html: true\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3512","title":"3.5.1.2 \u914d\u7f6e\u8bed\u6cd5","text":"<p>\u63d2\u4ef6\u914d\u7f6e\u7684\u51e0\u79cd\u65b9\u5f0f\uff1a</p> YAML<pre><code># 1. \u7b80\u5355\u542f\u7528\u63d2\u4ef6\uff08\u4f7f\u7528\u9ed8\u8ba4\u914d\u7f6e\uff09\nplugins:\n  - search\n  - tags\n\n# 2. \u7981\u7528\u9ed8\u8ba4\u63d2\u4ef6\nplugins:\n  - search: false\n\n# 3. \u5e26\u914d\u7f6e\u7684\u63d2\u4ef6\nplugins:\n  - search:\n      lang: \n        - en\n        - zh\n      separator: '[\\s\\-\\.]+'\n\n# 4. \u591a\u5b9e\u4f8b\u63d2\u4ef6\nplugins:\n  - search:\n      name: search_1\n      config: value\n  - search:\n      name: search_2\n      config: value\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3513","title":"3.5.1.3 \u4f18\u5148\u7ea7\u63a7\u5236","text":"<p>\u63d2\u4ef6\u6267\u884c\u987a\u5e8f\u63a7\u5236\uff1a</p> YAML<pre><code>plugins:\n  - search\n  - git-revision-date-localized:\n      priority: 80\n  - minify:\n      priority: 90\n  - tags:\n      priority: 70\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#352","title":"3.5.2 \u5e38\u7528\u63d2\u4ef6\u4ecb\u7ecd","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3521","title":"3.5.2.1 \u5b98\u65b9\u63d2\u4ef6","text":"<ol> <li>search - \u641c\u7d22\u63d2\u4ef6</li> </ol> YAML<pre><code>plugins:\n  - search:\n      lang: \n        - en\n        - zh\n      separator: '[\\s\\-\\.]+'\n      min_search_length: 2\n      prebuild_index: true\n      indexing:\n        - full_sections: false\n        - headings: true\n        - content: true\n</code></pre> <ol> <li>tags - \u6807\u7b7e\u7cfb\u7edf</li> </ol> YAML<pre><code>plugins:\n  - tags:\n      tags_file: tags.md\n      tags_extra_files:\n        cloud: cloud_tags.md\n        list: tag_list.md\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3522","title":"3.5.2.2 \u793e\u533a\u63d2\u4ef6\u63a8\u8350","text":"<ol> <li>git-revision-date-localized - Git \u65e5\u671f\u4fe1\u606f</li> </ol> YAML<pre><code>plugins:\n  - git-revision-date-localized:\n      type: timeago\n      enable_creation_date: true\n      exclude:\n        - index.md\n      timezone: Asia/Shanghai\n      locale: zh\n</code></pre> <ol> <li>minify - \u6587\u4ef6\u538b\u7f29</li> </ol> YAML<pre><code>plugins:\n  - minify:\n      minify_html: true\n      minify_js: true\n      minify_css: true\n      htmlmin_opts:\n        remove_comments: true\n</code></pre> <ol> <li>social - \u793e\u4ea4\u5206\u4eab</li> </ol> YAML<pre><code>plugins:\n  - social:\n      cards: true\n      cards_color:\n        fill: \"#0FF1CE\"\n        text: \"#FFFFFF\"\n</code></pre> <ol> <li>macros - \u6a21\u677f\u5b8f</li> </ol> YAML<pre><code>plugins:\n  - macros:\n      module_name: macros\n      include_dir: include\n      include_yaml:\n        - variables.yml\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3523","title":"3.5.2.3 \u5b9e\u7528\u63d2\u4ef6\u96c6\u5408","text":"YAML<pre><code>plugins:\n  # \u6838\u5fc3\u529f\u80fd\n  - search\n  - tags\n\n  # \u7248\u672c\u63a7\u5236\n  - git-revision-date-localized\n  - git-authors\n\n  # \u6027\u80fd\u4f18\u5316\n  - minify\n  - optimize\n\n  # \u5185\u5bb9\u589e\u5f3a\n  - social\n  - macros\n  - blogging\n\n  # \u591a\u8bed\u8a00\u652f\u6301\n  - i18n\n  - translations\n\n  # \u56fe\u7247\u5904\u7406\n  - glightbox\n  - img2fig\n\n  # \u7edf\u8ba1\u5206\u6790\n  - statistics\n  - pdf-export\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#353","title":"3.5.3 \u63d2\u4ef6\u7ec4\u5408\u4f7f\u7528","text":""},{"location":"Tools/Blog/Mkdocs_Material/#3531","title":"3.5.3.1 \u57fa\u7840\u7ec4\u5408\u65b9\u6848","text":"<p>\u9002\u5408\u4e00\u822c\u6587\u6863\u9879\u76ee\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      lang: zh\n      separator: '[\\s\\-\\.]+'\n\n  - git-revision-date-localized:\n      enable_creation_date: true\n      type: date\n\n  - minify:\n      minify_html: true\n\n  - glightbox:\n      touchNavigation: true\n      loop: false\n      effect: zoom\n      width: 100%\n      height: auto\n      zoomable: true\n      draggable: true\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3532","title":"3.5.3.2 \u535a\u5ba2\u7f51\u7ad9\u65b9\u6848","text":"<p>\u9002\u5408\u535a\u5ba2\u7c7b\u7f51\u7ad9\uff1a</p> YAML<pre><code>plugins:\n  - blog:\n      blog_dir: blog\n      post_url_format: \"{slug}\"\n      post_excerpt: optional\n\n  - social:\n      cards: true\n      cards_dir: assets/social\n\n  - tags:\n      tags_file: tags.md\n\n  - rss:\n      abstract_chars_count: 160\n      date_from_meta: true\n\n  - statistics:\n      page_check: true\n      page_count: true\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#3533","title":"3.5.3.3 \u6280\u672f\u6587\u6863\u65b9\u6848","text":"<p>\u9002\u5408\u5927\u578b\u6280\u672f\u6587\u6863\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      separator: '[\\s\\-\\.]+'\n      min_search_length: 2\n      lang:\n        - en\n        - zh\n      prebuild_index: true\n\n  - git-revision-date-localized:\n      type: timeago\n      enable_creation_date: true\n\n  - minify:\n      minify_html: true\n      minify_js: true\n      minify_css: true\n\n  - macros:\n      module_name: includes.macros\n      include_yaml:\n        - includes/variables.yml\n\n  - pdf-export:\n      combined: true\n      combined_output_path: pdf/document.pdf\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#354","title":"3.5.4 \u6027\u80fd\u4f18\u5316\u5efa\u8bae","text":"<ol> <li> <p>\u63d2\u4ef6\u9009\u62e9\uff1a    - \u53ea\u542f\u7528\u5fc5\u8981\u7684\u63d2\u4ef6    - \u907f\u514d\u529f\u80fd\u91cd\u590d\u7684\u63d2\u4ef6    - \u6ce8\u610f\u63d2\u4ef6\u95f4\u7684\u4f9d\u8d56\u5173\u7cfb</p> </li> <li> <p>\u914d\u7f6e\u4f18\u5316\uff1a</p> </li> </ol> YAML<pre><code>plugins:\n  - search:\n      prebuild_index: true  # \u9884\u6784\u5efa\u7d22\u5f15\n  - minify:\n      cache: true          # \u542f\u7528\u7f13\u5b58\n      cache_dir: .cache    # \u7f13\u5b58\u76ee\u5f55\n  - optimize:              # \u8d44\u6e90\u4f18\u5316\n      cache: true\n</code></pre> <ol> <li>\u6784\u5efa\u4f18\u5316\uff1a</li> </ol> YAML<pre><code>plugins:\n  # \u5e76\u884c\u5904\u7406\u63d2\u4ef6\n  - parallel:\n      workers: 4\n  # \u7f13\u5b58\u63d2\u4ef6\n  - cache:\n      enabled: true\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4-material","title":"4 Material \u4e3b\u9898\u5b8c\u5168\u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#41","title":"4.1 \u57fa\u7840\u5916\u89c2","text":""},{"location":"Tools/Blog/Mkdocs_Material/#411","title":"4.1.1 \u914d\u8272\u65b9\u6848","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4111","title":"4.1.1.1 \u9884\u8bbe\u4e3b\u9898\u8272","text":"<p>Material \u4e3b\u9898\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u9884\u8bbe\u989c\u8272\uff1a</p> YAML<pre><code>theme:\n  name: material\n  palette:\n    primary: indigo    # \u4e3b\u8272\u8c03\n    accent: pink      # \u5f3a\u8c03\u8272\n\n# \u53ef\u7528\u7684\u4e3b\u9898\u8272\uff1a\n# red, pink, purple, deep purple, indigo, blue, light blue, \n# cyan, teal, green, light green, lime, yellow, amber, \n# orange, deep orange, brown, grey, blue grey\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4112","title":"4.1.1.2 \u81ea\u5b9a\u4e49\u914d\u8272","text":"<p>\u5b8c\u6574\u7684\u81ea\u5b9a\u4e49\u914d\u8272\u914d\u7f6e\uff1a</p> YAML<pre><code>theme:\n  palette:\n    # \u4eae\u8272\u4e3b\u9898\n    - media: \"(prefers-color-scheme: light)\"\n      scheme: default\n      primary: indigo\n      accent: indigo\n      toggle:\n        icon: material/brightness-7\n        name: \u5207\u6362\u81f3\u6697\u8272\u6a21\u5f0f\n\n    # \u6697\u8272\u4e3b\u9898\n    - media: \"(prefers-color-scheme: dark)\"\n      scheme: slate\n      primary: indigo\n      accent: indigo\n      toggle:\n        icon: material/brightness-4\n        name: \u5207\u6362\u81f3\u4eae\u8272\u6a21\u5f0f\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4113-css","title":"4.1.1.3 \u81ea\u5b9a\u4e49 CSS \u53d8\u91cf","text":"<p>\u521b\u5efa <code>docs/stylesheets/extra.css</code>\uff1a</p> CSS<pre><code>:root {\n  --md-primary-fg-color:        #2196f3;\n  --md-primary-fg-color--light: #64b5f6;\n  --md-primary-fg-color--dark:  #1976d2;\n  --md-accent-fg-color:         #2196f3;\n}\n\n[data-md-color-scheme=\"slate\"] {\n  --md-primary-fg-color:        #90caf9;\n  --md-primary-fg-color--light: #e3f2fd;\n  --md-primary-fg-color--dark:  #42a5f5;\n}\n</code></pre> <p>\u5728 <code>mkdocs.yml</code> \u4e2d\u5f15\u5165\uff1a</p> YAML<pre><code>extra_css:\n  - stylesheets/extra.css\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#412","title":"4.1.2 \u4e3b\u9898\u5207\u6362","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4121","title":"4.1.2.1 \u57fa\u7840\u5207\u6362\u914d\u7f6e","text":"YAML<pre><code>theme:\n  name: material\n  palette:\n    # \u914d\u7f6e\u5207\u6362\u6309\u94ae\n    - scheme: default\n      toggle:\n        icon: material/brightness-7 \n        name: \u5207\u6362\u81f3\u6697\u8272\u6a21\u5f0f\n      primary: indigo\n      accent: indigo\n\n    - scheme: slate\n      toggle:\n        icon: material/brightness-4\n        name: \u5207\u6362\u81f3\u4eae\u8272\u6a21\u5f0f\n      primary: indigo\n      accent: indigo\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4122","title":"4.1.2.2 \u9ad8\u7ea7\u5207\u6362\u529f\u80fd","text":"<p>\u6dfb\u52a0\u81ea\u5b9a\u4e49\u5207\u6362\u903b\u8f91\uff1a</p> YAML<pre><code>extra_javascript:\n  - javascripts/theme-switch.js\n</code></pre> <p><code>theme-switch.js</code> \u5185\u5bb9\uff1a</p> JavaScript<pre><code>document.addEventListener('DOMContentLoaded', function() {\n  // \u83b7\u53d6\u7cfb\u7edf\u4e3b\u9898\u504f\u597d\n  const prefersDark = window.matchMedia('(prefers-color-scheme: dark)');\n\n  // \u76d1\u542c\u7cfb\u7edf\u4e3b\u9898\u53d8\u5316\n  prefersDark.addListener((e) =&gt; {\n    const theme = e.matches ? 'slate' : 'default';\n    document.body.setAttribute('data-md-color-scheme', theme);\n  });\n\n  // \u521d\u59cb\u5316\u4e3b\u9898\n  const theme = prefersDark.matches ? 'slate' : 'default';\n  document.body.setAttribute('data-md-color-scheme', theme);\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#413","title":"4.1.3 \u56fe\u6807\u8bbe\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4131","title":"4.1.3.1 \u7f51\u7ad9\u56fe\u6807","text":"<p>\u914d\u7f6e\u7f51\u7ad9\u56fe\u6807\u548c Logo\uff1a</p> YAML<pre><code>theme:\n  icon:\n    logo: material/book-open-page-variant  # \u7f51\u7ad9 Logo\n    repo: fontawesome/brands/github        # \u4ed3\u5e93\u56fe\u6807\n\n  favicon: assets/favicon.png              # \u7f51\u7ad9\u56fe\u6807\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4132","title":"4.1.3.2 \u529f\u80fd\u56fe\u6807","text":"<p>\u4e3a\u4e0d\u540c\u529f\u80fd\u914d\u7f6e\u56fe\u6807\uff1a</p> YAML<pre><code>theme:\n  icon:\n    repo: fontawesome/brands/github      # \u4ed3\u5e93\u56fe\u6807\n    edit: material/pencil                # \u7f16\u8f91\u56fe\u6807\n    view: material/eye                   # \u67e5\u770b\u56fe\u6807\n    admonition:\n      note: octicons/tag-16             # \u63d0\u793a\u6846\u56fe\u6807\n      abstract: octicons/checklist-16\n      info: octicons/info-16\n      tip: octicons/squirrel-16\n      success: octicons/check-16\n      question: octicons/question-16\n      warning: octicons/alert-16\n      failure: octicons/x-circle-16\n      danger: octicons/zap-16\n      bug: octicons/bug-16\n      example: octicons/beaker-16\n      quote: octicons/quote-16\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4133-svg","title":"4.1.3.3 \u81ea\u5b9a\u4e49 SVG \u56fe\u6807","text":"<p>\u6dfb\u52a0\u81ea\u5b9a\u4e49 SVG \u56fe\u6807\uff1a</p> <ol> <li>\u521b\u5efa <code>.icons</code> \u76ee\u5f55\uff1a</li> </ol> Text Only<pre><code>.\n\u251c\u2500 .icons/\n\u2502  \u2514\u2500 custom/\n\u2502     \u2514\u2500 logo.svg\n\u2514\u2500 mkdocs.yml\n</code></pre> <ol> <li>\u914d\u7f6e\u4f7f\u7528\uff1a</li> </ol> YAML<pre><code>theme:\n  icon:\n    logo: custom/logo\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#414-logo","title":"4.1.4 Logo \u8bbe\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4141-logo","title":"4.1.4.1 \u57fa\u7840 Logo \u914d\u7f6e","text":"YAML<pre><code>theme:\n  logo: assets/logo.svg        # Logo \u56fe\u7247\n  icon:\n    logo: material/book        # \u6216\u4f7f\u7528\u56fe\u6807\u4f5c\u4e3a Logo\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4142-logo","title":"4.1.4.2 \u54cd\u5e94\u5f0f Logo","text":"<p>\u521b\u5efa\u54cd\u5e94\u5f0f Logo\uff1a</p> YAML<pre><code>theme:\n  logo: assets/logo.svg\nextra_css:\n  - stylesheets/logo.css\n</code></pre> <p><code>logo.css</code> \u5185\u5bb9\uff1a</p> CSS<pre><code>/* \u9ed8\u8ba4 Logo */\n.md-logo img {\n  width: 40px;\n  height: 40px;\n}\n\n/* \u79fb\u52a8\u7aef Logo */\n@media screen and (max-width: 76.1875em) {\n  .md-logo img {\n    width: 32px;\n    height: 32px;\n  }\n}\n\n/* \u6697\u8272\u4e3b\u9898 Logo */\n[data-md-color-scheme=\"slate\"] .md-logo img {\n  filter: invert(1);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4143-logo","title":"4.1.4.3 Logo \u52a8\u753b\u6548\u679c","text":"<p>\u6dfb\u52a0 Logo \u52a8\u753b\uff1a</p> CSS<pre><code>.md-logo img {\n  transition: transform 0.3s ease;\n}\n\n.md-logo img:hover {\n  transform: scale(1.1);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#415","title":"4.1.5 \u5b8c\u6574\u914d\u7f6e\u793a\u4f8b","text":"YAML<pre><code># mkdocs.yml\ntheme:\n  name: material\n\n  # \u8c03\u8272\u677f\u914d\u7f6e\n  palette:\n    - media: \"(prefers-color-scheme: light)\"\n      scheme: default\n      primary: indigo\n      accent: indigo\n      toggle:\n        icon: material/brightness-7\n        name: \u5207\u6362\u81f3\u6697\u8272\u6a21\u5f0f\n    - media: \"(prefers-color-scheme: dark)\"\n      scheme: slate\n      primary: blue\n      accent: blue\n      toggle:\n        icon: material/brightness-4\n        name: \u5207\u6362\u81f3\u4eae\u8272\u6a21\u5f0f\n\n  # \u56fe\u6807\u914d\u7f6e\n  icon:\n    logo: material/book-open-page-variant\n    repo: fontawesome/brands/github\n    edit: material/pencil\n    view: material/eye\n\n  # Logo \u914d\u7f6e\n  logo: assets/logo.svg\n  favicon: assets/favicon.png\n\n# \u989d\u5916\u6837\u5f0f\nextra_css:\n  - stylesheets/extra.css\n  - stylesheets/logo.css\n\n# \u989d\u5916\u811a\u672c\nextra_javascript:\n  - javascripts/theme-switch.js\n\n# \u4e3b\u9898\u7279\u6027\nfeatures:\n  - navigation.instant\n  - navigation.tracking\n  - navigation.tabs\n  - navigation.sections\n  - navigation.expand\n  - navigation.top\n  - toc.integrate\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#42","title":"4.2 \u5bfc\u822a\u529f\u80fd","text":""},{"location":"Tools/Blog/Mkdocs_Material/#421","title":"4.2.1 \u9876\u90e8\u5bfc\u822a","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4211","title":"4.2.1.1 \u5bfc\u822a\u680f\u6837\u5f0f","text":"<p>\u57fa\u7840\u5bfc\u822a\u680f\u914d\u7f6e\uff1a</p> YAML<pre><code>theme:\n  name: material\n  features:\n    - navigation.tabs        # \u542f\u7528\u6807\u7b7e\u5f0f\u5bfc\u822a\n    - navigation.sections    # \u663e\u793a\u7ae0\u8282\u5bfc\u822a\n    - navigation.expand     # \u5c55\u5f00\u5bfc\u822a\n    - navigation.indexes    # \u7ae0\u8282\u7d22\u5f15\u9875\n</code></pre> <p>\u81ea\u5b9a\u4e49\u5bfc\u822a\u680f\u6837\u5f0f\uff1a</p> CSS<pre><code>/* docs/stylesheets/extra.css */\n\n/* \u5bfc\u822a\u680f\u80cc\u666f */\n.md-header {\n  background-color: #2196f3;\n  box-shadow: 0 2px 4px rgba(0,0,0,.14);\n}\n\n/* \u5bfc\u822a\u9879\u6837\u5f0f */\n.md-tabs__link {\n  font-size: .8rem;\n  margin-top: .4rem;\n}\n\n/* \u6fc0\u6d3b\u72b6\u6001 */\n.md-tabs__link--active {\n  font-weight: bold;\n  border-bottom: 2px solid currentColor;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4212","title":"4.2.1.2 \u56fa\u5b9a\u5bfc\u822a\u680f","text":"<p>\u542f\u7528\u56fa\u5b9a\u5bfc\u822a\uff1a</p> YAML<pre><code>theme:\n  features:\n    - header.autohide       # \u81ea\u52a8\u9690\u85cf\n    - navigation.sticky    # \u56fa\u5b9a\u5bfc\u822a\n</code></pre> <p>\u81ea\u5b9a\u4e49\u56fa\u5b9a\u5bfc\u822a\u884c\u4e3a\uff1a</p> CSS<pre><code>/* \u56fa\u5b9a\u5bfc\u822a\u680f\u6837\u5f0f */\n.md-header--sticky {\n  backdrop-filter: blur(8px);\n  background-color: rgba(255,255,255,.8);\n}\n\n/* \u6697\u8272\u4e3b\u9898 */\n[data-md-color-scheme=\"slate\"] .md-header--sticky {\n  background-color: rgba(0,0,0,.8);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4213","title":"4.2.1.3 \u54cd\u5e94\u5f0f\u5bfc\u822a","text":"<p>\u54cd\u5e94\u5f0f\u914d\u7f6e\uff1a</p> YAML<pre><code>theme:\n  features:\n    - navigation.instant    # \u5373\u65f6\u52a0\u8f7d\n    - navigation.tracking   # \u6eda\u52a8\u8ddf\u8e2a\n</code></pre> <p>\u54cd\u5e94\u5f0f\u6837\u5f0f\u8c03\u6574\uff1a</p> CSS<pre><code>/* \u79fb\u52a8\u7aef\u5bfc\u822a */\n@media screen and (max-width: 76.1875em) {\n  .md-nav__title {\n    font-size: .9rem;\n    padding: 0.5rem 0.8rem;\n  }\n\n  .md-nav__item {\n    padding: 0.2rem 0.8rem;\n  }\n}\n\n/* \u5e73\u677f\u5bfc\u822a */\n@media screen and (min-width: 76.25em) {\n  .md-nav__link {\n    padding: 0.2rem 0;\n  }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#422","title":"4.2.2 \u6807\u7b7e\u5bfc\u822a","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4221","title":"4.2.2.1 \u6807\u7b7e\u9875\u914d\u7f6e","text":"<p>\u542f\u7528\u6807\u7b7e\u5bfc\u822a\uff1a</p> YAML<pre><code>theme:\n  features:\n    - navigation.tabs\n    - navigation.tabs.sticky  # \u56fa\u5b9a\u6807\u7b7e\n</code></pre> <p>\u6807\u7b7e\u9875\u7ed3\u6784\uff1a</p> YAML<pre><code>nav:\n  - Home: index.md\n  - Guide:\n    - guide/index.md\n    - Installation: guide/installation.md\n    - Configuration: guide/configuration.md\n  - API:\n    - api/index.md\n    - Reference: api/reference.md\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4222","title":"4.2.2.2 \u6807\u7b7e\u6837\u5f0f","text":"<p>\u81ea\u5b9a\u4e49\u6807\u7b7e\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u6807\u7b7e\u5bb9\u5668 */\n.md-tabs {\n  background-color: var(--md-primary-fg-color--dark);\n}\n\n/* \u6807\u7b7e\u9879 */\n.md-tabs__item {\n  padding: 0 1rem;\n  transition: all 0.2s ease;\n}\n\n/* \u60ac\u505c\u6548\u679c */\n.md-tabs__item:hover {\n  background-color: rgba(255,255,255,.1);\n}\n\n/* \u6fc0\u6d3b\u72b6\u6001 */\n.md-tabs__item--active {\n  font-weight: bold;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4223","title":"4.2.2.3 \u6807\u7b7e\u4ea4\u4e92","text":"<p>\u6dfb\u52a0\u6807\u7b7e\u4ea4\u4e92\u6548\u679c\uff1a</p> JavaScript<pre><code>// docs/javascripts/tabs.js\n\ndocument.addEventListener('DOMContentLoaded', function() {\n  // \u6807\u7b7e\u70b9\u51fb\u6548\u679c\n  const tabs = document.querySelectorAll('.md-tabs__item');\n  tabs.forEach(tab =&gt; {\n    tab.addEventListener('click', () =&gt; {\n      // \u6dfb\u52a0\u70b9\u51fb\u6ce2\u7eb9\u6548\u679c\n      const ripple = document.createElement('div');\n      ripple.classList.add('md-tabs__ripple');\n      tab.appendChild(ripple);\n\n      // \u79fb\u9664\u6ce2\u7eb9\u6548\u679c\n      setTimeout(() =&gt; ripple.remove(), 1000);\n    });\n  });\n});\n</code></pre> <p>\u5bf9\u5e94\u7684 CSS\uff1a</p> CSS<pre><code>/* \u6ce2\u7eb9\u6548\u679c */\n.md-tabs__ripple {\n  position: absolute;\n  background: rgba(255,255,255,.3);\n  border-radius: 50%;\n  transform: scale(0);\n  animation: ripple 0.6s linear;\n}\n\n@keyframes ripple {\n  to {\n    transform: scale(4);\n    opacity: 0;\n  }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#423","title":"4.2.3 \u76ee\u5f55\u5bfc\u822a","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4231","title":"4.2.3.1 \u76ee\u5f55\u5c42\u7ea7","text":"<p>\u914d\u7f6e\u76ee\u5f55\u5c42\u7ea7\uff1a</p> YAML<pre><code>theme:\n  features:\n    - toc.integrate    # \u96c6\u6210\u76ee\u5f55\n    - toc.follow      # \u76ee\u5f55\u8ddf\u968f\n\nmarkdown_extensions:\n  - toc:\n      permalink: true    # \u6c38\u4e45\u94fe\u63a5\n      toc_depth: 3      # \u76ee\u5f55\u6df1\u5ea6\n      title: \u76ee\u5f55       # \u76ee\u5f55\u6807\u9898\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4232","title":"4.2.3.2 \u76ee\u5f55\u6837\u5f0f","text":"<p>\u81ea\u5b9a\u4e49\u76ee\u5f55\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u76ee\u5f55\u5bb9\u5668 */\n.md-toc {\n  padding: 1rem;\n  background-color: var(--md-code-bg-color);\n  border-radius: 4px;\n}\n\n/* \u76ee\u5f55\u6807\u9898 */\n.md-toc__title {\n  font-weight: bold;\n  margin-bottom: 1rem;\n}\n\n/* \u76ee\u5f55\u94fe\u63a5 */\n.md-toc__link {\n  color: var(--md-typeset-color);\n  text-decoration: none;\n}\n\n/* \u76ee\u5f55\u5c42\u7ea7\u7f29\u8fdb */\n.md-toc__list {\n  margin-left: 1.5em;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4233","title":"4.2.3.3 \u951a\u70b9\u94fe\u63a5","text":"<p>\u914d\u7f6e\u951a\u70b9\u94fe\u63a5\uff1a</p> YAML<pre><code>markdown_extensions:\n  - toc:\n      permalink: \u2693\ufe0e    # \u951a\u70b9\u7b26\u53f7\n      slug: !!python/object/apply:pymdownx.slugs.slugify\n        kwds: {case: lower}  # URL \u8f6c\u6362\u89c4\u5219\n</code></pre> <p>\u81ea\u5b9a\u4e49\u951a\u70b9\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u951a\u70b9\u94fe\u63a5 */\n.headerlink {\n  opacity: 0;\n  margin-left: .5em;\n  transition: opacity 0.2s ease;\n}\n\n/* \u6807\u9898\u60ac\u505c\u65f6\u663e\u793a\u951a\u70b9 */\nh1:hover .headerlink,\nh2:hover .headerlink,\nh3:hover .headerlink {\n  opacity: 1;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#424","title":"4.2.4 \u8fd4\u56de\u9876\u90e8","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4241","title":"4.2.4.1 \u6309\u94ae\u6837\u5f0f","text":"<p>\u542f\u7528\u8fd4\u56de\u9876\u90e8\u6309\u94ae\uff1a</p> YAML<pre><code>theme:\n  features:\n    - navigation.top    # \u8fd4\u56de\u9876\u90e8\u6309\u94ae\n</code></pre> <p>\u81ea\u5b9a\u4e49\u6309\u94ae\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u8fd4\u56de\u9876\u90e8\u6309\u94ae */\n.md-top {\n  background-color: var(--md-primary-fg-color);\n  border-radius: 50%;\n  box-shadow: 0 2px 4px rgba(0,0,0,.14);\n  transition: all 0.2s ease;\n}\n\n/* \u60ac\u505c\u6548\u679c */\n.md-top:hover {\n  background-color: var(--md-primary-fg-color--dark);\n  transform: translateY(-2px);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4242","title":"4.2.4.2 \u6eda\u52a8\u884c\u4e3a","text":"<p>\u81ea\u5b9a\u4e49\u6eda\u52a8\u884c\u4e3a\uff1a</p> JavaScript<pre><code>// docs/javascripts/scroll.js\n\ndocument.addEventListener('DOMContentLoaded', function() {\n  const topButton = document.querySelector('.md-top');\n\n  // \u5e73\u6ed1\u6eda\u52a8\n  if (topButton) {\n    topButton.addEventListener('click', (e) =&gt; {\n      e.preventDefault();\n      window.scrollTo({\n        top: 0,\n        behavior: 'smooth'\n      });\n    });\n  }\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4243","title":"4.2.4.3 \u663e\u793a\u63a7\u5236","text":"<p>\u914d\u7f6e\u663e\u793a\u903b\u8f91\uff1a</p> JavaScript<pre><code>// \u63a7\u5236\u6309\u94ae\u663e\u793a\nwindow.addEventListener('scroll', () =&gt; {\n  const topButton = document.querySelector('.md-top');\n  if (topButton) {\n    if (window.scrollY &gt; 100) {\n      topButton.classList.add('md-top--show');\n    } else {\n      topButton.classList.remove('md-top--show');\n    }\n  }\n});\n</code></pre> <p>\u6837\u5f0f\u63a7\u5236\uff1a</p> CSS<pre><code>/* \u6309\u94ae\u663e\u793a\u9690\u85cf */\n.md-top {\n  opacity: 0;\n  visibility: hidden;\n  transition: opacity 0.2s ease, visibility 0.2s ease;\n}\n\n.md-top--show {\n  opacity: 1;\n  visibility: visible;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#425","title":"4.2.5 \u5b8c\u6574\u914d\u7f6e\u793a\u4f8b","text":"YAML<pre><code># mkdocs.yml\ntheme:\n  name: material\n  features:\n    # \u5bfc\u822a\u529f\u80fd\n    - navigation.tabs\n    - navigation.tabs.sticky\n    - navigation.sections\n    - navigation.expand\n    - navigation.indexes\n    - navigation.instant\n    - navigation.tracking\n    - navigation.sticky\n    - header.autohide\n\n    # \u76ee\u5f55\u529f\u80fd\n    - toc.integrate\n    - toc.follow\n\n    # \u8fd4\u56de\u9876\u90e8\n    - navigation.top\n\n# Markdown \u6269\u5c55\nmarkdown_extensions:\n  - toc:\n      permalink: true\n      toc_depth: 3\n      title: \u76ee\u5f55\n      slugify: !!python/object/apply:pymdownx.slugs.slugify\n        kwds: {case: lower}\n\n# \u989d\u5916\u6837\u5f0f\u548c\u811a\u672c\nextra_css:\n  - stylesheets/extra.css\n\nextra_javascript:\n  - javascripts/tabs.js\n  - javascripts/scroll.js\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#43","title":"4.3 \u641c\u7d22\u529f\u80fd","text":""},{"location":"Tools/Blog/Mkdocs_Material/#431","title":"4.3.1 \u641c\u7d22\u5f15\u64ce\u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4311","title":"4.3.1.1 \u641c\u7d22\u7b97\u6cd5","text":"<p>\u57fa\u7840\u641c\u7d22\u914d\u7f6e\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      separator: '[\\\\s\\\\-\\\\.]+'   # \u5206\u8bcd\u5206\u9694\u7b26\n      min_search_length: 2        # \u6700\u5c0f\u641c\u7d22\u957f\u5ea6\n      lang:\n        - en\n        - zh\n      prebuild_index: true        # \u9884\u6784\u5efa\u7d22\u5f15\n</code></pre> <p>\u9ad8\u7ea7\u641c\u7d22\u9009\u9879\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      separator: '[\\\\s\\\\-\\\\.]+\\\\s*'\n      min_search_length: 2\n      prebuild_index: python\n      indexing:\n        full_sections: true       # \u7d22\u5f15\u5b8c\u6574\u7ae0\u8282\n        headings: true           # \u7d22\u5f15\u6807\u9898\n        content: true           # \u7d22\u5f15\u5185\u5bb9\n        tags: true             # \u7d22\u5f15\u6807\u7b7e\n      scoring:\n        title_boost: 10        # \u6807\u9898\u6743\u91cd\n        heading_boost: 5       # \u6807\u9898\u6743\u91cd\n        content_boost: 1       # \u5185\u5bb9\u6743\u91cd\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4312","title":"4.3.1.2 \u7d22\u5f15\u914d\u7f6e","text":"<p>\u81ea\u5b9a\u4e49\u7d22\u5f15\u8bbe\u7f6e\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      indexing:\n        full_sections: true\n        headings: true\n        content: true\n        tags: true\n        attachments: true          # \u7d22\u5f15\u9644\u4ef6\n        attachments_types:         # \u9644\u4ef6\u7c7b\u578b\n          - .pdf\n          - .doc\n          - .docx\n        attachments_max_size: 2048 # \u6700\u5927\u5927\u5c0f(KB)\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4313","title":"4.3.1.3 \u641c\u7d22\u8303\u56f4","text":"<p>\u914d\u7f6e\u641c\u7d22\u8303\u56f4\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      # \u5305\u542b\u7684\u6587\u4ef6\n      include:\n        - \"*.md\"\n        - \"*.markdown\"\n\n      # \u6392\u9664\u7684\u6587\u4ef6\n      exclude:\n        - drafts/*\n        - private/*\n\n      # \u5904\u7406\u7279\u5b9a\u8def\u5f84\n      ignore:\n        - 404.md\n        - index.md\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#432","title":"4.3.2 \u641c\u7d22\u63d0\u793a","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4321","title":"4.3.2.1 \u5feb\u6377\u952e\u8bbe\u7f6e","text":"<p>\u914d\u7f6e\u641c\u7d22\u5feb\u6377\u952e\uff1a</p> YAML<pre><code>theme:\n  keyboard:\n    search: s, /        # \u4f7f\u7528 's' \u6216 '/' \u89e6\u53d1\u641c\u7d22\n</code></pre> <p>\u81ea\u5b9a\u4e49\u5feb\u6377\u952e\u5904\u7406\uff1a</p> JavaScript<pre><code>// docs/javascripts/search.js\n\ndocument.addEventListener('keydown', function(e) {\n  // \u81ea\u5b9a\u4e49\u5feb\u6377\u952e\u903b\u8f91\n  if ((e.key === 's' || e.key === '/') &amp;&amp; !e.ctrlKey &amp;&amp; !e.altKey &amp;&amp; !e.metaKey) {\n    e.preventDefault();\n    const search = document.querySelector('.md-search__input');\n    if (search) {\n      search.focus();\n    }\n  }\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4322","title":"4.3.2.2 \u63d0\u793a\u6587\u672c","text":"<p>\u81ea\u5b9a\u4e49\u641c\u7d22\u63d0\u793a\uff1a</p> YAML<pre><code>theme:\n  language: zh         # \u4f7f\u7528\u4e2d\u6587\u754c\u9762\n\nextra:\n  search:\n    language: zh\n    text:\n      placeholder: \u641c\u7d22\u6587\u6863...\n      no_results: \u6ca1\u6709\u627e\u5230\u76f8\u5173\u7ed3\u679c\n      searching: \u6b63\u5728\u641c\u7d22...\n</code></pre> <p>\u81ea\u5b9a\u4e49\u63d0\u793a\u6837\u5f0f\uff1a</p> CSS<pre><code>/* docs/stylesheets/search.css */\n\n/* \u641c\u7d22\u6846\u63d0\u793a\u6587\u672c */\n.md-search__input::placeholder {\n  color: var(--md-default-fg-color--lighter);\n}\n\n/* \u65e0\u7ed3\u679c\u63d0\u793a */\n.md-search-result__meta {\n  color: var(--md-default-fg-color--light);\n  font-size: .8rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4323","title":"4.3.2.3 \u8f93\u5165\u5efa\u8bae","text":"<p>\u914d\u7f6e\u641c\u7d22\u5efa\u8bae\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      suggestions: true          # \u542f\u7528\u641c\u7d22\u5efa\u8bae\n      suggestions_min_length: 2  # \u6700\u5c0f\u5efa\u8bae\u957f\u5ea6\n</code></pre> <p>\u81ea\u5b9a\u4e49\u5efa\u8bae\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u641c\u7d22\u5efa\u8bae\u6837\u5f0f */\n.md-search-result__item {\n  padding: .4rem .8rem;\n  transition: background .2s ease;\n}\n\n.md-search-result__item:hover {\n  background-color: var(--md-code-bg-color);\n}\n\n/* \u5efa\u8bae\u9879\u56fe\u6807 */\n.md-search-result__icon {\n  color: var(--md-default-fg-color--lighter);\n  margin-right: .4rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#433","title":"4.3.3 \u641c\u7d22\u9ad8\u4eae","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4331","title":"4.3.3.1 \u9ad8\u4eae\u6837\u5f0f","text":"<p>\u914d\u7f6e\u641c\u7d22\u9ad8\u4eae\uff1a</p> YAML<pre><code>theme:\n  features:\n    - search.highlight      # \u542f\u7528\u641c\u7d22\u9ad8\u4eae\n    - search.share         # \u542f\u7528\u641c\u7d22\u5206\u4eab\n    - search.suggest       # \u542f\u7528\u641c\u7d22\u5efa\u8bae\n</code></pre> <p>\u81ea\u5b9a\u4e49\u9ad8\u4eae\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u641c\u7d22\u7ed3\u679c\u9ad8\u4eae */\n.md-search-result__item mark {\n  background-color: var(--md-accent-fg-color--transparent);\n  color: var(--md-accent-fg-color);\n  padding: 0 .2em;\n  border-radius: .1em;\n}\n\n/* \u6eda\u52a8\u6761\u6837\u5f0f */\n.md-search-result__scrollwrap::-webkit-scrollbar {\n  width: 4px;\n  height: 4px;\n}\n\n.md-search-result__scrollwrap::-webkit-scrollbar-thumb {\n  background-color: var(--md-default-fg-color--lighter);\n  border-radius: 2px;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4332","title":"4.3.3.2 \u5339\u914d\u89c4\u5219","text":"<p>\u914d\u7f6e\u641c\u7d22\u5339\u914d\u89c4\u5219\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      # \u6587\u672c\u5339\u914d\u914d\u7f6e\n      tokenizer: '[\\s\\-\\.]+'   # \u5206\u8bcd\u89c4\u5219\n      min_search_length: 2     # \u6700\u5c0f\u641c\u7d22\u957f\u5ea6\n\n      # \u6a21\u7cca\u5339\u914d\u8bbe\u7f6e\n      fuzzy: false            # \u7981\u7528\u6a21\u7cca\u5339\u914d\n\n      # \u5339\u914d\u6743\u91cd\n      boost: \n        title: 10            # \u6807\u9898\u6743\u91cd\n        text: 1              # \u6587\u672c\u6743\u91cd\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4333","title":"4.3.3.3 \u81ea\u5b9a\u4e49\u9ad8\u4eae","text":"<p>\u5b9e\u73b0\u81ea\u5b9a\u4e49\u9ad8\u4eae\u903b\u8f91\uff1a</p> JavaScript<pre><code>// docs/javascripts/search-highlight.js\n\ndocument.addEventListener('DOMContentLoaded', function() {\n  // \u83b7\u53d6\u641c\u7d22\u7ed3\u679c\u5bb9\u5668\n  const searchResults = document.querySelector('.md-search-result');\n\n  if (searchResults) {\n    // \u76d1\u542c\u641c\u7d22\u7ed3\u679c\u53d8\u5316\n    const observer = new MutationObserver(mutations =&gt; {\n      mutations.forEach(mutation =&gt; {\n        if (mutation.type === 'childList') {\n          // \u5904\u7406\u65b0\u6dfb\u52a0\u7684\u641c\u7d22\u7ed3\u679c\n          const newResults = mutation.addedNodes;\n          newResults.forEach(node =&gt; {\n            if (node.nodeType === 1) {  // \u5143\u7d20\u8282\u70b9\n              customHighlight(node);\n            }\n          });\n        }\n      });\n    });\n\n    // \u542f\u52a8\u89c2\u5bdf\n    observer.observe(searchResults, {\n      childList: true,\n      subtree: true\n    });\n  }\n});\n\nfunction customHighlight(node) {\n  // \u81ea\u5b9a\u4e49\u9ad8\u4eae\u903b\u8f91\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#434","title":"4.3.4 \u641c\u7d22\u8bed\u8a00","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4341","title":"4.3.4.1 \u4e2d\u6587\u5206\u8bcd","text":"<p>\u914d\u7f6e\u4e2d\u6587\u5206\u8bcd\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      lang:\n        - en\n        - zh\n      separator: '[\\s\\-\\.,\\!\\/\\?\\u2000-\\u206F\\u3000-\\u303F\\u3040-\\u309F\\u30A0-\\u30FF\\u3100-\\u312F\\u3200-\\u32FF\\u3400-\\u4DBF\\u4E00-\\u9FFF]+'\n</code></pre> <p>\u4e2d\u6587\u641c\u7d22\u4f18\u5316\uff1a</p> JavaScript<pre><code>// docs/javascripts/chinese-search.js\n\nfunction chineseSegment(text) {\n  // \u7b80\u5355\u7684\u4e2d\u6587\u5206\u8bcd\u903b\u8f91\n  return text.replace(/[\\u4e00-\\u9fa5]/g, function(char) {\n    return char + ' ';\n  });\n}\n\n// \u6dfb\u52a0\u5230\u641c\u7d22\u5904\u7406\u6d41\u7a0b\ndocument.addEventListener('DOMContentLoaded', function() {\n  const searchInput = document.querySelector('.md-search__input');\n  if (searchInput) {\n    searchInput.addEventListener('input', function(e) {\n      const value = e.target.value;\n      if (/[\\u4e00-\\u9fa5]/.test(value)) {\n        // \u5904\u7406\u4e2d\u6587\u8f93\u5165\n        const segmented = chineseSegment(value);\n        // TODO: \u4f7f\u7528\u5206\u8bcd\u7ed3\u679c\u8fdb\u884c\u641c\u7d22\n      }\n    });\n  }\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4342","title":"4.3.4.2 \u591a\u8bed\u8a00\u652f\u6301","text":"<p>\u914d\u7f6e\u591a\u8bed\u8a00\u641c\u7d22\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      lang:\n        - en\n        - zh\n        - ja\n      # \u8bed\u8a00\u7279\u5b9a\u7684\u5206\u8bcd\u89c4\u5219\n      separator:\n        en: '[\\\\s\\\\-\\\\.]+'\n        zh: '[\\u4e00-\\u9fa5]'\n        ja: '[\\u3040-\\u309F\\u30A0-\\u30FF]+'\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4343","title":"4.3.4.3 \u505c\u7528\u8bcd\u914d\u7f6e","text":"<p>\u914d\u7f6e\u505c\u7528\u8bcd\uff1a</p> YAML<pre><code>plugins:\n  - search:\n      stopwords: \n        en:\n          - a\n          - an\n          - the\n          - in\n          - on\n          - at\n        zh:\n          - \u7684\n          - \u4e86\n          - \u548c\n          - \u4e0e\n          - \u6216\n</code></pre> <p>\u81ea\u5b9a\u4e49\u505c\u7528\u8bcd\u5904\u7406\uff1a</p> JavaScript<pre><code>// docs/javascripts/stopwords.js\n\nconst stopwords = {\n  en: ['a', 'an', 'the', 'in', 'on', 'at'],\n  zh: ['\u7684', '\u4e86', '\u548c', '\u4e0e', '\u6216'],\n};\n\nfunction removeStopwords(text, lang) {\n  if (!stopwords[lang]) return text;\n\n  const words = text.split(/\\s+/);\n  return words\n    .filter(word =&gt; !stopwords[lang].includes(word))\n    .join(' ');\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#435","title":"4.3.5 \u5b8c\u6574\u914d\u7f6e\u793a\u4f8b","text":"YAML<pre><code># mkdocs.yml\n\nplugins:\n  - search:\n      lang:\n        - en\n        - zh\n      separator: '[\\s\\-\\.,\\!\\/\\?\\u2000-\\u206F\\u3000-\\u303F]+'\n      prebuild_index: python\n      indexing:\n        full_sections: true\n        headings: true\n        content: true\n        tags: true\n      scoring:\n        title_boost: 10\n        heading_boost: 5\n        content_boost: 1\n\ntheme:\n  features:\n    - search.highlight\n    - search.share\n    - search.suggest\n\nextra:\n  search:\n    language: zh\n    text:\n      placeholder: \u641c\u7d22\u6587\u6863...\n      no_results: \u6ca1\u6709\u627e\u5230\u76f8\u5173\u7ed3\u679c\n      searching: \u6b63\u5728\u641c\u7d22...\n\nextra_javascript:\n  - javascripts/search.js\n  - javascripts/search-highlight.js\n  - javascripts/chinese-search.js\n  - javascripts/stopwords.js\n\nextra_css:\n  - stylesheets/search.css\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#44","title":"4.4 \u4ee3\u7801\u5757\u8bbe\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#441","title":"4.4.1 \u8bed\u6cd5\u9ad8\u4eae","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4411","title":"4.4.1.1 \u9ad8\u4eae\u4e3b\u9898","text":"<p>\u57fa\u7840\u9ad8\u4eae\u914d\u7f6e\uff1a</p> YAML<pre><code>theme:\n  name: material\n  features:\n    - content.code.annotate # \u542f\u7528\u4ee3\u7801\u6ce8\u91ca\n    - content.code.copy    # \u542f\u7528\u4ee3\u7801\u590d\u5236\n\nmarkdown_extensions:\n  - pymdownx.highlight:\n      anchor_linenums: true\n      line_spans: __span\n      pygments_lang_class: true\n      use_pygments: true\n      auto_title: true # \u663e\u793a\u8bed\u8a00\u540d\u79f0\n      linenums: true  # \u663e\u793a\u884c\u53f7\n</code></pre> <p>\u81ea\u5b9a\u4e49\u9ad8\u4eae\u4e3b\u9898\uff1a</p> YAML<pre><code>theme:\n  palette:\n    # \u4eae\u8272\u4e3b\u9898\n    - scheme: default\n      primary: indigo\n      accent: indigo\n      toggle:\n        icon: material/brightness-7\n        name: \u5207\u6362\u81f3\u6697\u8272\u4e3b\u9898\n      pygments_style: github-light\n\n    # \u6697\u8272\u4e3b\u9898\n    - scheme: slate\n      primary: indigo\n      accent: indigo\n      toggle:\n        icon: material/brightness-4\n        name: \u5207\u6362\u81f3\u4eae\u8272\u4e3b\u9898\n      pygments_style: monokai\n</code></pre> <p>\u81ea\u5b9a\u4e49\u4ee3\u7801\u5757\u6837\u5f0f\uff1a</p> CSS<pre><code>/* docs/stylesheets/code.css */\n\n/* \u4ee3\u7801\u5757\u5bb9\u5668 */\n.highlight {\n  background-color: var(--md-code-bg-color);\n  border-radius: 4px;\n  padding: 0.5rem;\n  margin: 1rem 0;\n}\n\n/* \u4ee3\u7801\u884c */\n.highlight .code-line {\n  display: block;\n  padding: 0 1rem;\n  border-left: 2px solid transparent;\n}\n\n/* \u9ad8\u4eae\u884c */\n.highlight .code-line.focused {\n  background-color: var(--md-code-hl-color);\n  border-left: 2px solid var(--md-accent-fg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4412","title":"4.4.1.2 \u8bed\u8a00\u652f\u6301","text":"<p>\u914d\u7f6e\u652f\u6301\u7684\u8bed\u8a00\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.highlight:\n      extend_pygments_lang:\n        # \u81ea\u5b9a\u4e49\u8bed\u8a00\u914d\u7f6e\n        typescript:\n          name: TypeScript\n          aliases: [ts]\n        jsonc:\n          name: JSON with Comments\n          aliases: [json5]\n</code></pre> <p>\u8bed\u8a00\u7279\u5b9a\u914d\u7f6e\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.highlight:\n      language_prefix: language-  # \u8bed\u8a00\u524d\u7f00\n      css_class: highlight       # CSS\u7c7b\u540d\n      code_attr_on_pre: false    # \u5c5e\u6027\u4f4d\u7f6e\n      extend_pygments_lang:      # \u8bed\u8a00\u6269\u5c55\n        flow:\n          name: Flow\n          aliases: [flowtype]\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4413","title":"4.4.1.3 \u81ea\u5b9a\u4e49\u9ad8\u4eae","text":"<p>\u81ea\u5b9a\u4e49\u8bed\u6cd5\u9ad8\u4eae\u89c4\u5219\uff1a</p> Python<pre><code># docs/custom_lexer.py\nfrom pygments.lexer import RegexLexer, words\nfrom pygments.token import *\n\nclass CustomLexer(RegexLexer):\n    name = 'CustomLanguage'\n    aliases = ['custom']\n    filenames = ['*.custom']\n\n    tokens = {\n        'root': [\n            (r'//.*$', Comment.Single),\n            (words(('if', 'else', 'while'), suffix=r'\\b'), Keyword),\n            (r'\"[^\"]*\"', String),\n            (r'\\d+', Number),\n            (r'[a-zA-Z_]\\w*', Name),\n            (r'[^\\w\\s]', Punctuation),\n        ]\n    }\n</code></pre> <p>\u5728 <code>mkdocs.yml</code> \u4e2d\u4f7f\u7528\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.highlight:\n      use_pygments: true\n      extend_pygments_lang:\n        custom:\n          name: CustomLanguage\n          aliases: [custom]\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#442","title":"4.4.2 \u884c\u53f7\u663e\u793a","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4421","title":"4.4.2.1 \u884c\u53f7\u6837\u5f0f","text":"<p>\u914d\u7f6e\u884c\u53f7\u663e\u793a\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.highlight:\n      linenums: true\n      linenums_style: table  # \u8868\u683c\u5f0f\u884c\u53f7\n      anchor_linenums: true  # \u884c\u53f7\u94fe\u63a5\n</code></pre> <p>\u81ea\u5b9a\u4e49\u884c\u53f7\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u884c\u53f7\u5bb9\u5668 */\n.highlighttable {\n  width: 100%;\n  display: table;\n}\n\n/* \u884c\u53f7\u5217 */\n.linenos {\n  color: var(--md-default-fg-color--lighter);\n  text-align: right;\n  padding-right: 1rem;\n  user-select: none;\n}\n\n/* \u4ee3\u7801\u5217 */\n.code {\n  padding-left: 1rem;\n  border-left: 1px solid var(--md-default-fg-color--lightest);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4422","title":"4.4.2.2 \u8d77\u59cb\u884c\u8bbe\u7f6e","text":"<p>\u8bbe\u7f6e\u4ee3\u7801\u5757\u8d77\u59cb\u884c\u53f7\uff1a</p> Markdown<pre><code>```python linenums=\"10\"\ndef hello_world():\n    print(\"Hello, World!\")\n```\n</code></pre> <p>\u914d\u7f6e\u9ed8\u8ba4\u8d77\u59cb\u884c\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.highlight:\n      linenums: true\n      linenums_start: 1  # \u9ed8\u8ba4\u8d77\u59cb\u884c\u53f7\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4423","title":"4.4.2.3 \u884c\u53f7\u94fe\u63a5","text":"<p>\u542f\u7528\u884c\u53f7\u94fe\u63a5\u529f\u80fd\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.highlight:\n      anchor_linenums: true     # \u542f\u7528\u884c\u53f7\u94fe\u63a5\n      line_anchors: L           # \u884c\u53f7\u94fe\u63a5\u524d\u7f00\n</code></pre> <p>\u81ea\u5b9a\u4e49\u94fe\u63a5\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u884c\u53f7\u94fe\u63a5 */\n.md-typeset .highlight [data-linenos]:before {\n  content: attr(data-linenos);\n  color: var(--md-default-fg-color--lighter);\n  padding-right: 1rem;\n}\n\n/* \u94fe\u63a5\u60ac\u505c\u6548\u679c */\n.md-typeset .highlight [data-linenos]:hover:before {\n  color: var(--md-accent-fg-color);\n  cursor: pointer;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#443","title":"4.4.3 \u590d\u5236\u6309\u94ae","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4431","title":"4.4.3.1 \u6309\u94ae\u6837\u5f0f","text":"<p>\u914d\u7f6e\u590d\u5236\u6309\u94ae\uff1a</p> YAML<pre><code>theme:\n  features:\n    - content.code.copy     # \u542f\u7528\u4ee3\u7801\u590d\u5236\n</code></pre> <p>\u81ea\u5b9a\u4e49\u590d\u5236\u6309\u94ae\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u590d\u5236\u6309\u94ae\u5bb9\u5668 */\n.md-clipboard {\n  position: absolute;\n  top: 0.5rem;\n  right: 0.5rem;\n  padding: 0.4rem;\n  color: var(--md-default-fg-color--lighter);\n  background-color: transparent;\n  border: none;\n  border-radius: 4px;\n  cursor: pointer;\n  transition: all 0.2s ease;\n}\n\n/* \u60ac\u505c\u6548\u679c */\n.md-clipboard:hover {\n  color: var(--md-accent-fg-color);\n  background-color: var(--md-code-bg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4432","title":"4.4.3.2 \u590d\u5236\u884c\u4e3a","text":"<p>\u81ea\u5b9a\u4e49\u590d\u5236\u529f\u80fd\uff1a</p> JavaScript<pre><code>// docs/javascripts/clipboard.js\n\ndocument.addEventListener('DOMContentLoaded', () =&gt; {\n  // \u83b7\u53d6\u6240\u6709\u4ee3\u7801\u5757\n  const codeBlocks = document.querySelectorAll('pre code');\n\n  codeBlocks.forEach(block =&gt; {\n    // \u521b\u5efa\u590d\u5236\u6309\u94ae\n    const button = document.createElement('button');\n    button.className = 'md-clipboard';\n    button.title = '\u590d\u5236\u5230\u526a\u8d34\u677f';\n\n    // \u6dfb\u52a0\u590d\u5236\u56fe\u6807\n    button.innerHTML = '&lt;span class=\"md-clipboard__icon\"&gt;&lt;/span&gt;';\n\n    // \u6dfb\u52a0\u70b9\u51fb\u4e8b\u4ef6\n    button.addEventListener('click', async () =&gt; {\n      try {\n        // \u590d\u5236\u4ee3\u7801\n        await navigator.clipboard.writeText(block.textContent);\n\n        // \u663e\u793a\u6210\u529f\u63d0\u793a\n        button.classList.add('md-clipboard--success');\n        setTimeout(() =&gt; {\n          button.classList.remove('md-clipboard--success');\n        }, 2000);\n      } catch (err) {\n        console.error('\u590d\u5236\u5931\u8d25:', err);\n      }\n    });\n\n    // \u5c06\u6309\u94ae\u6dfb\u52a0\u5230\u4ee3\u7801\u5757\n    block.parentNode.insertBefore(button, block);\n  });\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4433","title":"4.4.3.3 \u63d0\u793a\u914d\u7f6e","text":"<p>\u914d\u7f6e\u590d\u5236\u63d0\u793a\uff1a</p> YAML<pre><code>theme:\n  language: zh          # \u4f7f\u7528\u4e2d\u6587\u754c\u9762\n\nextra:\n  clipboard:\n    copy: \u590d\u5236\n    copied: \u5df2\u590d\u5236\uff01\n    error: \u590d\u5236\u5931\u8d25\n</code></pre> <p>\u81ea\u5b9a\u4e49\u63d0\u793a\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u590d\u5236\u63d0\u793a */\n.md-clipboard__tooltip {\n  position: absolute;\n  top: -2rem;\n  right: 0;\n  padding: 0.4rem 0.8rem;\n  color: var(--md-default-bg-color);\n  background-color: var(--md-default-fg-color);\n  border-radius: 4px;\n  font-size: 0.8rem;\n  opacity: 0;\n  transform: translateY(0.4rem);\n  transition: all 0.2s ease;\n}\n\n/* \u663e\u793a\u63d0\u793a */\n.md-clipboard:hover .md-clipboard__tooltip {\n  opacity: 1;\n  transform: translateY(0);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#444","title":"4.4.4 \u6ce8\u91ca\u529f\u80fd","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4441","title":"4.4.4.1 \u884c\u5185\u6ce8\u91ca","text":"<p>\u4f7f\u7528\u884c\u5185\u6ce8\u91ca\uff1a</p> Markdown<pre><code>```python\ndef hello():\n    print(\"Hello\")  # (1)\n    return True     # (2)\n```\n\n1. \u6253\u5370\u95ee\u5019\u4fe1\u606f\n2. \u8fd4\u56de\u6210\u529f\u72b6\u6001\n</code></pre> <p>\u914d\u7f6e\u6ce8\u91ca\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u884c\u5185\u6ce8\u91ca\u6807\u8bb0 */\n.md-annotation {\n  color: var(--md-accent-fg-color);\n  font-size: 0.8em;\n  vertical-align: super;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4442","title":"4.4.4.2 \u5757\u7ea7\u6ce8\u91ca","text":"<p>\u4f7f\u7528\u5757\u7ea7\u6ce8\u91ca\uff1a</p> Markdown<pre><code>```python\ndef process_data():\n    # (1)!\n    data = load_data()\n\n    # (2)!\n    result = transform(data)\n\n    return result\n```\n\n1. \u4ece\u6570\u636e\u6e90\u52a0\u8f7d\u6570\u636e\n   \u8fd9\u91cc\u53ef\u4ee5\u662f\u591a\u884c\n   \u6ce8\u91ca\u8bf4\u660e\n\n2. \u5bf9\u6570\u636e\u8fdb\u884c\u8f6c\u6362\u5904\u7406\n   \u5305\u542b\u6e05\u6d17\u548c\u683c\u5f0f\u5316\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4443","title":"4.4.4.3 \u6ce8\u91ca\u6837\u5f0f","text":"<p>\u81ea\u5b9a\u4e49\u6ce8\u91ca\u6837\u5f0f\uff1a</p> CSS<pre><code>/* \u6ce8\u91ca\u5bb9\u5668 */\n.md-annotation-wrapper {\n  margin: 1rem 0;\n  padding: 1rem;\n  background-color: var(--md-code-bg-color);\n  border-left: 4px solid var(--md-accent-fg-color);\n  border-radius: 4px;\n}\n\n/* \u6ce8\u91ca\u6807\u8bb0 */\n.md-annotation-marker {\n  color: var(--md-accent-fg-color);\n  font-weight: bold;\n}\n\n/* \u6ce8\u91ca\u5185\u5bb9 */\n.md-annotation-content {\n  margin-top: 0.5rem;\n  color: var(--md-default-fg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#445","title":"4.4.5 \u5b8c\u6574\u914d\u7f6e\u793a\u4f8b","text":"YAML<pre><code># mkdocs.yml\n\ntheme:\n  name: material\n  features:\n    - content.code.annotate\n    - content.code.copy\n\nmarkdown_extensions:\n  - pymdownx.highlight:\n      anchor_linenums: true\n      line_spans: __span\n      pygments_lang_class: true\n      use_pygments: true\n      auto_title: true\n      linenums: true\n      linenums_style: table\n  - pymdownx.superfences\n  - pymdownx.inlinehilite\n\nextra:\n  clipboard:\n    copy: \u590d\u5236\n    copied: \u5df2\u590d\u5236\uff01\n    error: \u590d\u5236\u5931\u8d25\n\nextra_css:\n  - stylesheets/code.css\n\nextra_javascript:\n  - javascripts/clipboard.js\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#45","title":"4.5 \u5185\u5bb9\u589e\u5f3a","text":""},{"location":"Tools/Blog/Mkdocs_Material/#451","title":"4.5.1 \u6570\u5b66\u516c\u5f0f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4511-katex","title":"4.5.1.1 KaTeX \u914d\u7f6e","text":"<p>\u5b89\u88c5\u548c\u914d\u7f6e KaTeX\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.arithmatex:\n      generic: true\n\nextra_javascript:\n  - javascripts/katex.js \n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/katex.min.js  \n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/contrib/auto-render.min.js\n\nextra_css:\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/katex.min.css\n</code></pre> <p>\u521b\u5efa <code>docs/javascripts/katex.js</code> \uff1a</p> JavaScript<pre><code>document.addEventListener(\"DOMContentLoaded\", function() {\n  renderMathInElement(document.body, {\n    delimiters: [\n      {left: \"$$\", right: \"$$\", display: true},\n      {left: \"$\", right: \"$\", display: false},\n      {left: \"\\\\(\", right: \"\\\\)\", display: false},\n      {left: \"\\\\[\", right: \"\\\\]\", display: true}\n    ],\n    throwOnError: false\n  });\n});\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Markdown<pre><code>\u5185\u8054\u516c\u5f0f: $E = mc^2$\n\n\u5757\u7ea7\u516c\u5f0f\uff1a\n$$\n\\frac{n!}{k!(n-k)!} = \\binom{n}{k}\n$$\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4512-mathjax","title":"4.5.1.2 MathJax \u914d\u7f6e","text":"<p>\u914d\u7f6e MathJax\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.arithmatex:\n      generic: true\n\nextra_javascript:\n  - javascripts/mathjax.js\n  - https://polyfill.io/v3/polyfill.min.js?features=es6\n  - https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js\n</code></pre> <p>\u521b\u5efa <code>docs/javascripts/mathjax.js</code> \uff1a</p> JavaScript<pre><code>window.MathJax = {\n  tex: {\n    inlineMath: [[\"\\\\(\", \"\\\\)\"]],\n    displayMath: [[\"\\\\[\", \"\\\\]\"]],\n    processEscapes: true,\n    processEnvironments: true\n  },\n  options: {\n    ignoreHtmlClass: \".*|\",\n    processHtmlClass: \"arithmatex\"\n  }\n};\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4513","title":"4.5.1.3 \u516c\u5f0f\u7f16\u53f7","text":"<p>\u542f\u7528\u516c\u5f0f\u7f16\u53f7\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.arithmatex:\n      generic: true\n      numbering: true\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Markdown<pre><code>$$\n\\begin{equation}\nE = mc^2 \\label{eq:einstein}\n\\end{equation}\n$$\n\n\u5f15\u7528\u516c\u5f0f $\\eqref{eq:einstein}$\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#452","title":"4.5.2 \u56fe\u8868\u652f\u6301","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4521-mermaid","title":"4.5.2.1 Mermaid \u96c6\u6210","text":"<p>\u914d\u7f6e Mermaid\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.superfences:\n      custom_fences:\n        - name: mermaid\n          class: mermaid\n          format: !!python/name:pymdownx.superfences.fence_code_format\n\nextra_javascript:\n  - https://unpkg.com/mermaid@9/dist/mermaid.min.js\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Text Only<pre><code>graph TD\n    A[\u5f00\u59cb] --&gt; B{\u5224\u65ad}\n    B --&gt;|Yes| C[\u5904\u7406]\n    B --&gt;|No| D[\u7ed3\u675f]\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4522-plantuml","title":"4.5.2.2 PlantUML \u652f\u6301","text":"<p>\u914d\u7f6e PlantUML\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.superfences:\n      custom_fences:\n        - name: plantuml\n          class: plantuml\n          format: !!python/name:pymdownx.superfences.fence_code_format\n\nextra_javascript:\n  - https://cdn.jsdelivr.net/npm/plantuml-encoder@1.4.0/dist/plantuml-encoder.min.js\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> Text Only<pre><code>@startuml\nAlice -&gt; Bob: \u8bf7\u6c42\nBob --&gt; Alice: \u54cd\u5e94\n@enduml\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4523","title":"4.5.2.3 \u81ea\u5b9a\u4e49\u56fe\u8868","text":"<p>\u521b\u5efa\u81ea\u5b9a\u4e49\u56fe\u8868\u7ec4\u4ef6\uff1a</p> JavaScript<pre><code>// docs/javascripts/charts.js\nimport Chart from 'chart.js/auto';\n\ndocument.addEventListener('DOMContentLoaded', function() {\n  const chartElements = document.querySelectorAll('.custom-chart');\n\n  chartElements.forEach(element =&gt; {\n    const ctx = element.getContext('2d');\n    const data = JSON.parse(element.dataset.chartData);\n\n    new Chart(ctx, {\n      type: data.type,\n      data: data.data,\n      options: data.options\n    });\n  });\n});\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> HTML<pre><code>&lt;canvas class=\"custom-chart\" data-chart-data='{\n  \"type\": \"line\",\n  \"data\": {\n    \"labels\": [\"1\u6708\", \"2\u6708\", \"3\u6708\"],\n    \"datasets\": [{\n      \"label\": \"\u6570\u636e\",\n      \"data\": [10, 20, 30]\n    }]\n  }\n}'&gt;&lt;/canvas&gt;\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#453","title":"4.5.3 \u4efb\u52a1\u5217\u8868","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4531","title":"4.5.3.1 \u590d\u9009\u6846\u6837\u5f0f","text":"<p>\u914d\u7f6e\u4efb\u52a1\u5217\u8868\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.tasklist:\n      custom_checkbox: true\n      clickable_checkbox: true\n</code></pre> <p>\u81ea\u5b9a\u4e49\u6837\u5f0f\uff1a</p> CSS<pre><code>/* docs/stylesheets/tasklist.css */\n\n.task-list-item {\n  list-style-type: none;\n  margin-left: -1.6rem;\n}\n\n.task-list-control {\n  position: relative;\n  display: inline-block;\n  width: 1.2rem;\n  height: 1.2rem;\n  margin-right: 0.5rem;\n  vertical-align: middle;\n}\n\n.task-list-indicator {\n  position: absolute;\n  top: 0;\n  left: 0;\n  width: 100%;\n  height: 100%;\n  background-color: var(--md-default-fg-color--lighter);\n  border-radius: 2px;\n  transition: all 0.2s ease;\n}\n\n.task-list-indicator:checked {\n  background-color: var(--md-accent-fg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4532","title":"4.5.3.2 \u4ea4\u4e92\u884c\u4e3a","text":"<p>\u6dfb\u52a0\u4ea4\u4e92\u529f\u80fd\uff1a</p> JavaScript<pre><code>// docs/javascripts/tasklist.js\n\ndocument.addEventListener('DOMContentLoaded', function() {\n  const taskItems = document.querySelectorAll('.task-list-item input[type=\"checkbox\"]');\n\n  taskItems.forEach(item =&gt; {\n    item.addEventListener('change', function() {\n      // \u4fdd\u5b58\u72b6\u6001\n      localStorage.setItem(\n        `task-${this.closest('.task-list-item').id}`,\n        this.checked\n      );\n\n      // \u66f4\u65b0\u6837\u5f0f\n      if (this.checked) {\n        this.closest('.task-list-item').classList.add('completed');\n      } else {\n        this.closest('.task-list-item').classList.remove('completed');\n      }\n    });\n\n    // \u6062\u590d\u72b6\u6001\n    const saved = localStorage.getItem(`task-${item.closest('.task-list-item').id}`);\n    if (saved === 'true') {\n      item.checked = true;\n      item.closest('.task-list-item').classList.add('completed');\n    }\n  });\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4533","title":"4.5.3.3 \u72b6\u6001\u7ba1\u7406","text":"CSS<pre><code>/* \u4efb\u52a1\u72b6\u6001\u6837\u5f0f */\n.task-list-item.completed {\n  text-decoration: line-through;\n  color: var(--md-default-fg-color--light);\n}\n\n.task-list-item.pending {\n  font-weight: bold;\n}\n\n.task-list-item.in-progress {\n  color: var(--md-accent-fg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#454","title":"4.5.4 \u6807\u7b7e\u9875","text":""},{"location":"Tools/Blog/Mkdocs_Material/#4541","title":"4.5.4.1 \u6807\u7b7e\u7ec4\u6837\u5f0f","text":"<p>\u914d\u7f6e\u6807\u7b7e\u9875\uff1a</p> YAML<pre><code>markdown_extensions:\n  - pymdownx.tabbed:\n      alternate_style: true \n</code></pre> <p>\u81ea\u5b9a\u4e49\u6837\u5f0f\uff1a</p> CSS<pre><code>/* docs/stylesheets/tabs.css */\n\n/* \u6807\u7b7e\u7ec4\u5bb9\u5668 */\n.tabbed-set {\n  border: 1px solid var(--md-default-fg-color--lightest);\n  border-radius: 4px;\n  margin: 1rem 0;\n}\n\n/* \u6807\u7b7e\u5217\u8868 */\n.tabbed-labels {\n  display: flex;\n  background-color: var(--md-code-bg-color);\n  border-bottom: 1px solid var(--md-default-fg-color--lightest);\n}\n\n/* \u5355\u4e2a\u6807\u7b7e */\n.tabbed-labels &gt; label {\n  padding: 0.8rem 1.2rem;\n  cursor: pointer;\n  transition: all 0.2s ease;\n}\n\n/* \u6fc0\u6d3b\u72b6\u6001 */\n.tabbed-labels &gt; label.tabbed-selected {\n  color: var(--md-accent-fg-color);\n  border-bottom: 2px solid var(--md-accent-fg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4542","title":"4.5.4.2 \u5207\u6362\u6548\u679c","text":"<p>\u6dfb\u52a0\u52a8\u753b\u6548\u679c\uff1a</p> CSS<pre><code>/* \u6807\u7b7e\u5185\u5bb9\u5207\u6362\u52a8\u753b */\n.tabbed-content {\n  padding: 1rem;\n  opacity: 0;\n  transform: translateY(10px);\n  transition: all 0.3s ease;\n}\n\n.tabbed-content.tabbed-selected {\n  opacity: 1;\n  transform: translateY(0);\n}\n</code></pre> <p>\u6807\u7b7e\u9875\u4ea4\u4e92\uff1a</p> JavaScript<pre><code>// docs/javascripts/tabs.js\n\ndocument.addEventListener('DOMContentLoaded', function() {\n  const tabSets = document.querySelectorAll('.tabbed-set');\n\n  tabSets.forEach(tabSet =&gt; {\n    const tabs = tabSet.querySelectorAll('.tabbed-labels &gt; label');\n    const contents = tabSet.querySelectorAll('.tabbed-content');\n\n    tabs.forEach((tab, index) =&gt; {\n      tab.addEventListener('click', () =&gt; {\n        // \u66f4\u65b0\u6807\u7b7e\u72b6\u6001\n        tabs.forEach(t =&gt; t.classList.remove('tabbed-selected'));\n        tab.classList.add('tabbed-selected');\n\n        // \u66f4\u65b0\u5185\u5bb9\u72b6\u6001\n        contents.forEach(c =&gt; c.classList.remove('tabbed-selected'));\n        contents[index].classList.add('tabbed-selected');\n      });\n    });\n  });\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#4543","title":"4.5.4.3 \u54cd\u5e94\u5f0f\u8bbe\u8ba1","text":"<p>\u6dfb\u52a0\u54cd\u5e94\u5f0f\u652f\u6301\uff1a</p> CSS<pre><code>/* \u79fb\u52a8\u7aef\u9002\u914d */\n@media screen and (max-width: 76.1875em) {\n  .tabbed-labels {\n    flex-wrap: wrap;\n  }\n\n  .tabbed-labels &gt; label {\n    flex: 1 1 auto;\n    text-align: center;\n  }\n\n  .tabbed-content {\n    padding: 0.8rem;\n  }\n}\n\n/* \u5e73\u677f\u9002\u914d */\n@media screen and (min-width: 76.25em) {\n  .tabbed-set {\n    max-width: 80%;\n    margin: 1rem auto;\n  }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#455","title":"4.5.5 \u5b8c\u6574\u914d\u7f6e\u793a\u4f8b","text":"YAML<pre><code># mkdocs.yml\n\nmarkdown_extensions:\n  # \u6570\u5b66\u516c\u5f0f\n  - pymdownx.arithmatex:\n      generic: true\n\n  # \u56fe\u8868\u652f\u6301\n  - pymdownx.superfences:\n      custom_fences:\n        - name: mermaid\n          class: mermaid\n          format: !!python/name:pymdownx.superfences.fence_code_format\n        - name: plantuml\n          class: plantuml\n          format: !!python/name:pymdownx.superfences.fence_code_format\n\n  # \u4efb\u52a1\u5217\u8868\n  - pymdownx.tasklist:\n      custom_checkbox: true\n      clickable_checkbox: true\n\n  # \u6807\u7b7e\u9875\n  - pymdownx.tabbed:\n      alternate_style: true\n\nextra_javascript:\n  - javascripts/katex.js\n  - javascripts/mermaid.js\n  - javascripts/charts.js\n  - javascripts/tasklist.js\n  - javascripts/tabs.js\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/katex.min.js\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/contrib/auto-render.min.js\n  - https://unpkg.com/mermaid@9/dist/mermaid.min.js\n\nextra_css:\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/katex.min.css\n  - stylesheets/tasklist.css\n  - stylesheets/tabs.css\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5","title":"5 \u6837\u5f0f\u5b9a\u5236","text":""},{"location":"Tools/Blog/Mkdocs_Material/#51-css","title":"5.1 CSS \u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#511-css","title":"5.1.1 \u81ea\u5b9a\u4e49 CSS \u6587\u4ef6","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5111-css","title":"5.1.1.1 CSS \u6587\u4ef6\u7ec4\u7ec7","text":"<ol> <li>\u63a8\u8350\u7684\u76ee\u5f55\u7ed3\u6784\uff1a</li> </ol> Text Only<pre><code>docs/\n\u251c\u2500\u2500 stylesheets/\n\u2502   \u251c\u2500\u2500 base/\n\u2502   \u2502   \u251c\u2500\u2500 _variables.css    # CSS\u53d8\u91cf\u5b9a\u4e49\n\u2502   \u2502   \u251c\u2500\u2500 _typography.css   # \u6392\u7248\u6837\u5f0f\n\u2502   \u2502   \u2514\u2500\u2500 _colors.css       # \u989c\u8272\u5b9a\u4e49\n\u2502   \u251c\u2500\u2500 components/\n\u2502   \u2502   \u251c\u2500\u2500 _buttons.css      # \u6309\u94ae\u6837\u5f0f\n\u2502   \u2502   \u251c\u2500\u2500 _cards.css        # \u5361\u7247\u6837\u5f0f\n\u2502   \u2502   \u2514\u2500\u2500 _tables.css       # \u8868\u683c\u6837\u5f0f\n\u2502   \u251c\u2500\u2500 layouts/\n\u2502   \u2502   \u251c\u2500\u2500 _header.css       # \u5934\u90e8\u6837\u5f0f\n\u2502   \u2502   \u251c\u2500\u2500 _nav.css         # \u5bfc\u822a\u6837\u5f0f\n\u2502   \u2502   \u2514\u2500\u2500 _footer.css      # \u9875\u811a\u6837\u5f0f\n\u2502   \u2514\u2500\u2500 extra.css            # \u4e3b\u6837\u5f0f\u6587\u4ef6\n</code></pre> <ol> <li>\u5728 <code>mkdocs.yml</code> \u4e2d\u5f15\u5165\u6837\u5f0f\uff1a</li> </ol> YAML<pre><code>extra_css:\n  - stylesheets/extra.css\n</code></pre> <ol> <li>\u5728\u4e3b\u6837\u5f0f\u6587\u4ef6\u4e2d\u5bfc\u5165\u5176\u4ed6\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/extra.css */\n\n/* \u57fa\u7840\u6837\u5f0f */\n@import 'base/_variables.css';\n@import 'base/_typography.css';\n@import 'base/_colors.css';\n\n/* \u7ec4\u4ef6\u6837\u5f0f */\n@import 'components/_buttons.css';\n@import 'components/_cards.css';\n@import 'components/_tables.css';\n\n/* \u5e03\u5c40\u6837\u5f0f */\n@import 'layouts/_header.css';\n@import 'layouts/_nav.css';\n@import 'layouts/_footer.css';\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5112","title":"5.1.1.2 \u6837\u5f0f\u4f18\u5148\u7ea7","text":"<ol> <li>\u6837\u5f0f\u4f18\u5148\u7ea7\u89c4\u5219\uff1a</li> </ol> CSS<pre><code>/* 1. \u884c\u5185\u6837\u5f0f (1000) */\n&lt;div style=\"color: red;\"&gt;\n\n/* 2. ID \u9009\u62e9\u5668 (100) */\n#header { }\n\n/* 3. \u7c7b\u9009\u62e9\u5668\u3001\u5c5e\u6027\u9009\u62e9\u5668\u3001\u4f2a\u7c7b (10) */\n.nav-item { }\n[type=\"text\"] { }\n:hover { }\n\n/* 4. \u5143\u7d20\u9009\u62e9\u5668\u3001\u4f2a\u5143\u7d20 (1) */\ndiv { }\n::before { }\n</code></pre> <ol> <li>Material \u4e3b\u9898\u8986\u76d6\uff1a</li> </ol> CSS<pre><code>/* \u8986\u76d6\u4e3b\u9898\u6837\u5f0f */\n.md-header {\n  /* \u4f7f\u7528 !important \u614e\u91cd */\n  background-color: #2196f3 !important;\n}\n\n/* \u4f7f\u7528\u66f4\u5177\u4f53\u7684\u9009\u62e9\u5668 */\n.md-header[data-md-color-scheme=\"default\"] {\n  background-color: #2196f3;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5113-css","title":"5.1.1.3 CSS \u53d8\u91cf","text":"<ol> <li>\u5b9a\u4e49\u5168\u5c40\u53d8\u91cf\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/base/_variables.css */\n\n:root {\n  /* \u989c\u8272\u53d8\u91cf */\n  --primary-color: #2196f3;\n  --accent-color: #f50057;\n  --text-color: #333333;\n\n  /* \u5b57\u4f53\u53d8\u91cf */\n  --font-family: \"LXGW WenKai\", -apple-system, sans-serif;\n  --code-font: \"JetBrains Mono\", monospace;\n\n  /* \u95f4\u8ddd\u53d8\u91cf */\n  --spacing-unit: 8px;\n  --content-padding: calc(var(--spacing-unit) * 2);\n\n  /* \u9634\u5f71\u53d8\u91cf */\n  --shadow-sm: 0 1px 2px rgba(0,0,0,0.1);\n  --shadow-md: 0 2px 4px rgba(0,0,0,0.1);\n  --shadow-lg: 0 4px 8px rgba(0,0,0,0.1);\n}\n</code></pre> <ol> <li>\u4e3b\u9898\u53d8\u91cf\uff1a</li> </ol> CSS<pre><code>/* \u4eae\u8272\u4e3b\u9898 */\n[data-md-color-scheme=\"default\"] {\n  --md-primary-fg-color: var(--primary-color);\n  --md-accent-fg-color: var(--accent-color);\n  --md-typeset-color: var(--text-color);\n}\n\n/* \u6697\u8272\u4e3b\u9898 */\n[data-md-color-scheme=\"slate\"] {\n  --primary-color: #90caf9;\n  --accent-color: #ff4081;\n  --text-color: #ffffff;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#512","title":"5.1.2 \u5e38\u7528\u6837\u5f0f\u4fee\u6539","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5121","title":"5.1.2.1 \u5b57\u4f53\u8bbe\u7f6e","text":"<ol> <li>\u5b57\u4f53\u5b9a\u4e49\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/base/_typography.css */\n\n/* \u57fa\u7840\u5b57\u4f53\u8bbe\u7f6e */\nbody {\n  font-family: var(--font-family);\n  font-size: 16px;\n  line-height: 1.6;\n}\n\n/* \u4ee3\u7801\u5b57\u4f53 */\ncode, pre {\n  font-family: var(--code-font);\n  font-size: 0.9em;\n}\n\n/* \u6807\u9898\u5b57\u4f53 */\nh1, h2, h3, h4, h5, h6 {\n  font-family: var(--font-family);\n  font-weight: 600;\n  margin: calc(var(--spacing-unit) * 3) 0;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5122","title":"5.1.2.2 \u989c\u8272\u5b9a\u5236","text":"CSS<pre><code>/* docs/stylesheets/base/_colors.css */\n\n/* \u6587\u672c\u989c\u8272 */\n.md-typeset {\n  color: var(--text-color);\n}\n\n/* \u94fe\u63a5\u989c\u8272 */\n.md-typeset a {\n  color: var(--md-accent-fg-color);\n}\n\n/* \u4ee3\u7801\u5757\u989c\u8272 */\n.highlight {\n  background-color: var(--md-code-bg-color);\n}\n\n/* \u5f15\u7528\u5757\u989c\u8272 */\nblockquote {\n  border-left: 4px solid var(--md-accent-fg-color);\n  background-color: var(--md-code-bg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5123","title":"5.1.2.3 \u95f4\u8ddd\u8c03\u6574","text":"CSS<pre><code>/* \u5185\u5bb9\u95f4\u8ddd */\n.md-main__inner {\n  padding: var(--content-padding);\n}\n\n/* \u6bb5\u843d\u95f4\u8ddd */\n.md-typeset p {\n  margin: var(--spacing-unit) 0;\n}\n\n/* \u5217\u8868\u95f4\u8ddd */\n.md-typeset ul li,\n.md-typeset ol li {\n  margin-bottom: calc(var(--spacing-unit) * 0.5);\n}\n\n/* \u6807\u9898\u95f4\u8ddd */\n.md-typeset h1 {\n  margin-top: calc(var(--spacing-unit) * 4);\n  margin-bottom: calc(var(--spacing-unit) * 2);\n}\n\n.md-typeset h2 {\n  margin-top: calc(var(--spacing-unit) * 3);\n  margin-bottom: calc(var(--spacing-unit) * 1.5);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5124","title":"5.1.2.4 \u5b8c\u6574\u914d\u7f6e\u793a\u4f8b","text":"<p>\u5728 <code>mkdocs.yml</code> \u4e2d\u7684\u914d\u7f6e\uff1a</p> YAML<pre><code>theme:\n  name: material\n  font: false  # \u7981\u7528\u9ed8\u8ba4\u5b57\u4f53\n\nextra_css:\n  - stylesheets/extra.css\n\nextra:\n  css_variables:\n    spacing_unit: 8px\n    content_width: 960px\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#52","title":"5.2 \u4e3b\u9898\u6837\u5f0f\u8986\u76d6","text":""},{"location":"Tools/Blog/Mkdocs_Material/#521","title":"5.2.1 \u7ec4\u4ef6\u6837\u5f0f\u4fee\u6539","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5211","title":"5.2.1.1 \u5bfc\u822a\u680f\u6837\u5f0f","text":"<ol> <li>\u9876\u90e8\u5bfc\u822a\u680f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/components/header.css */\n\n/* \u5bfc\u822a\u680f\u5bb9\u5668 */\n.md-header {\n  background-color: var(--md-primary-fg-color);\n  box-shadow: 0 2px 4px rgba(0,0,0,.14);\n  height: 3rem;\n}\n\n/* \u5bfc\u822a\u680f\u6807\u9898 */\n.md-header__title {\n  font-size: 1.2rem;\n  font-weight: 600;\n  margin-left: 1rem;\n}\n\n/* \u5bfc\u822a\u680f\u6309\u94ae */\n.md-header__button {\n  padding: .8rem;\n  color: var(--md-primary-bg-color);\n}\n\n/* \u5bfc\u822a\u680f\u641c\u7d22\u6846 */\n.md-search__input {\n  border-radius: 2rem;\n  background-color: rgba(255,255,255,.1);\n  padding: 0 2.4rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5212","title":"5.2.1.2 \u4fa7\u8fb9\u680f\u6837\u5f0f","text":"CSS<pre><code>/* docs/stylesheets/components/sidebar.css */\n\n/* \u4fa7\u8fb9\u680f\u5bb9\u5668 */\n.md-sidebar {\n  width: 14rem;\n  background-color: var(--md-default-bg-color);\n  padding: 1.2rem 0;\n}\n\n/* \u4fa7\u8fb9\u680f\u5bfc\u822a */\n.md-nav--primary {\n  padding: 0 .8rem;\n}\n\n/* \u5bfc\u822a\u9879 */\n.md-nav__item {\n  padding: .2rem 0;\n}\n\n/* \u5bfc\u822a\u94fe\u63a5 */\n.md-nav__link {\n  color: var(--md-default-fg-color);\n  padding: .4rem .6rem;\n  border-radius: 4px;\n  transition: all .2s;\n}\n\n.md-nav__link:hover {\n  background-color: var(--md-code-bg-color);\n  color: var(--md-accent-fg-color);\n}\n\n/* \u6fc0\u6d3b\u72b6\u6001 */\n.md-nav__link--active {\n  font-weight: 600;\n  color: var(--md-accent-fg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5213","title":"5.2.1.3 \u9875\u811a\u6837\u5f0f","text":"CSS<pre><code>/* docs/stylesheets/components/footer.css */\n\n/* \u9875\u811a\u5bb9\u5668 */\n.md-footer {\n  background-color: var(--md-default-bg-color--darkest);\n  color: var(--md-footer-fg-color);\n}\n\n/* \u9875\u811a\u5185\u5bb9 */\n.md-footer-meta {\n  background-color: rgba(0,0,0,.1);\n  padding: 1rem 0;\n}\n\n/* \u9875\u811a\u94fe\u63a5 */\n.md-footer__link {\n  padding: .4rem 1rem;\n  color: var(--md-footer-fg-color--light);\n}\n\n/* \u7248\u6743\u4fe1\u606f */\n.md-footer-copyright {\n  font-size: .8rem;\n  color: var(--md-footer-fg-color--lighter);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#522","title":"5.2.2 \u81ea\u5b9a\u4e49\u8c03\u8272\u677f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5221","title":"5.2.2.1 \u4e3b\u9898\u8272\u5b9a\u5236","text":"<ol> <li>\u57fa\u7840\u989c\u8272\u5b9a\u4e49\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/theme/colors.css */\n\n:root {\n  /* \u4e3b\u8272\u8c03 */\n  --md-primary-hue: 210;\n  --md-primary-saturation: 80%;\n  --md-primary-lightness: 45%;\n\n  /* \u5f3a\u8c03\u8272 */\n  --md-accent-hue: 340;\n  --md-accent-saturation: 90%;\n  --md-accent-lightness: 50%;\n}\n</code></pre> <ol> <li>\u989c\u8272\u53d8\u91cf\u5e94\u7528\uff1a</li> </ol> CSS<pre><code>:root {\n  --md-primary-fg-color: hsl(\n    var(--md-primary-hue),\n    var(--md-primary-saturation),\n    var(--md-primary-lightness)\n  );\n\n  --md-accent-fg-color: hsl(\n    var(--md-accent-hue),\n    var(--md-accent-saturation),\n    var(--md-accent-lightness)\n  );\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5222","title":"5.2.2.2 \u914d\u8272\u65b9\u6848","text":"YAML<pre><code># mkdocs.yml\ntheme:\n  palette:\n    # \u4eae\u8272\u6a21\u5f0f\n    - media: \"(prefers-color-scheme: light)\"\n      scheme: default\n      primary: indigo\n      accent: deep purple\n      toggle:\n        icon: material/brightness-7\n        name: \u5207\u6362\u81f3\u6697\u8272\u6a21\u5f0f\n\n    # \u6697\u8272\u6a21\u5f0f\n    - media: \"(prefers-color-scheme: dark)\"\n      scheme: slate\n      primary: blue grey\n      accent: deep purple\n      toggle:\n        icon: material/brightness-4\n        name: \u5207\u6362\u81f3\u4eae\u8272\u6a21\u5f0f\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5223","title":"5.2.2.3 \u6697\u8272\u4e3b\u9898","text":"CSS<pre><code>/* \u6697\u8272\u4e3b\u9898\u53d8\u91cf */\n[data-md-color-scheme=\"slate\"] {\n  --md-default-bg-color: #1a1a1a;\n  --md-default-bg-color--light: #222222;\n  --md-default-bg-color--lighter: #282828;\n\n  --md-default-fg-color: rgba(255,255,255,0.87);\n  --md-default-fg-color--light: rgba(255,255,255,0.54);\n  --md-default-fg-color--lighter: rgba(255,255,255,0.32);\n\n  --md-code-bg-color: #2d2d2d;\n  --md-code-fg-color: #f5f5f5;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#523","title":"5.2.3 \u5b57\u4f53\u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5231","title":"5.2.3.1 \u4e2d\u6587\u5b57\u4f53","text":"<ol> <li>\u5b57\u4f53\u5b9a\u4e49\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/theme/fonts.css */\n\n/* \u4e2d\u6587\u5b57\u4f53\u53d8\u91cf */\n:root {\n  --md-font-chinese: \"LXGW WenKai\", \"PingFang SC\", \"Microsoft YaHei\";\n}\n\n/* \u5f15\u5165 LXGW WenKai \u5b57\u4f53 */\n@font-face {\n  font-family: \"LXGW WenKai\";\n  src: url(\"https://cdn.jsdelivr.net/npm/lxgw-wenkai-webfont@1.1.0/style.css\");\n  font-display: swap;\n}\n</code></pre> <ol> <li>\u5b57\u4f53\u5e94\u7528\uff1a</li> </ol> CSS<pre><code>body {\n  font-family: var(--md-font-chinese), -apple-system, sans-serif;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5232","title":"5.2.3.2 \u4ee3\u7801\u5b57\u4f53","text":"CSS<pre><code>/* \u4ee3\u7801\u5b57\u4f53\u914d\u7f6e */\n:root {\n  --md-code-font: \"JetBrains Mono\", \"Fira Code\", \"Source Code Pro\", monospace;\n}\n\n/* \u4ee3\u7801\u5757\u6837\u5f0f */\n.md-typeset code,\n.md-typeset pre {\n  font-family: var(--md-code-font);\n  font-size: 0.9em;\n}\n\n/* \u884c\u5185\u4ee3\u7801 */\n.md-typeset code {\n  border-radius: 4px;\n  padding: .2em .4em;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5233","title":"5.2.3.3 \u5b57\u4f53\u56de\u9000","text":"CSS<pre><code>/* \u5b57\u4f53\u56de\u9000\u7b56\u7565 */\n:root {\n  --md-text-font-fallback: -apple-system, BlinkMacSystemFont, Segoe UI, Helvetica,\n    Arial, sans-serif, Apple Color Emoji, Segoe UI Emoji;\n\n  --md-code-font-fallback: SFMono-Regular, Consolas, Menlo, monospace;\n}\n\n/* \u5e94\u7528\u56de\u9000\u5b57\u4f53 */\nbody {\n  font-family: var(--md-font-chinese), var(--md-text-font-fallback);\n}\n\npre, code {\n  font-family: var(--md-code-font), var(--md-code-font-fallback);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#524","title":"5.2.4 \u5e03\u5c40\u8c03\u6574","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5241","title":"5.2.4.1 \u54cd\u5e94\u5f0f\u5e03\u5c40","text":"CSS<pre><code>/* docs/stylesheets/theme/layout.css */\n\n/* \u57fa\u7840\u54cd\u5e94\u5f0f\u5e03\u5c40 */\n.md-grid {\n  max-width: 100%;\n  margin: 0 auto;\n}\n\n/* \u684c\u9762\u7aef */\n@media screen and (min-width: 76.25em) {\n  .md-grid {\n    max-width: 76rem;\n  }\n\n  .md-sidebar--primary {\n    width: 14rem;\n  }\n\n  .md-sidebar--secondary {\n    width: 12rem;\n    margin-left: 76rem;\n  }\n}\n\n/* \u5e73\u677f\u7aef */\n@media screen and (max-width: 76.1875em) {\n  .md-grid {\n    max-width: 60rem;\n  }\n\n  .md-header-nav__title {\n    display: none;\n  }\n}\n\n/* \u79fb\u52a8\u7aef */\n@media screen and (max-width: 44.9375em) {\n  .md-grid {\n    max-width: 100%;\n    padding: 0 1rem;\n  }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5242","title":"5.2.4.2 \u7f51\u683c\u7cfb\u7edf","text":"CSS<pre><code>/* \u81ea\u5b9a\u4e49\u7f51\u683c\u7cfb\u7edf */\n.grid {\n  display: grid;\n  gap: 1rem;\n  margin: 1rem 0;\n}\n\n/* \u7f51\u683c\u5217\u6570 */\n.grid-cols-1 { grid-template-columns: repeat(1, 1fr); }\n.grid-cols-2 { grid-template-columns: repeat(2, 1fr); }\n.grid-cols-3 { grid-template-columns: repeat(3, 1fr); }\n.grid-cols-4 { grid-template-columns: repeat(4, 1fr); }\n\n/* \u54cd\u5e94\u5f0f\u7f51\u683c */\n@media (min-width: 768px) {\n  .md-grid-cols-md-2 { grid-template-columns: repeat(2, 1fr); }\n  .md-grid-cols-md-3 { grid-template-columns: repeat(3, 1fr); }\n}\n\n@media (min-width: 1024px) {\n  .md-grid-cols-lg-3 { grid-template-columns: repeat(3, 1fr); }\n  .md-grid-cols-lg-4 { grid-template-columns: repeat(4, 1fr); }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5243","title":"5.2.4.3 \u5bb9\u5668\u5bbd\u5ea6","text":"CSS<pre><code>/* \u5bb9\u5668\u5bbd\u5ea6\u5b9a\u4e49 */\n:root {\n  --md-container-width: 80rem;\n  --md-container-padding: 1rem;\n}\n\n/* \u5bb9\u5668\u6837\u5f0f */\n.md-container {\n  max-width: var(--md-container-width);\n  margin: 0 auto;\n  padding: 0 var(--md-container-padding);\n}\n\n/* \u4e0d\u540c\u5c3a\u5bf8\u7684\u5bb9\u5668 */\n.md-container--small {\n  max-width: 60rem;\n}\n\n.md-container--medium {\n  max-width: 70rem;\n}\n\n.md-container--large {\n  max-width: 90rem;\n}\n\n/* \u6d41\u5f0f\u5bb9\u5668 */\n.md-container--fluid {\n  max-width: 100%;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#525","title":"5.2.5 \u5b8c\u6574\u914d\u7f6e\u793a\u4f8b","text":"YAML<pre><code># mkdocs.yml\ntheme:\n  name: material\n  font: false\n  features:\n    - navigation.tabs\n    - navigation.sections\n    - navigation.expand\n  palette:\n    - scheme: default\n      primary: indigo\n      accent: deep purple\n    - scheme: slate\n      primary: blue grey\n      accent: deep purple\n\nextra_css:\n  - stylesheets/theme/colors.css\n  - stylesheets/theme/fonts.css\n  - stylesheets/theme/layout.css\n  - stylesheets/components/header.css\n  - stylesheets/components/sidebar.css\n  - stylesheets/components/footer.css\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#53","title":"5.3 \u81ea\u5b9a\u4e49\u7ec4\u4ef6\u6837\u5f0f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#531","title":"5.3.1 \u5361\u7247\u6837\u5f0f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5311","title":"5.3.1.1 \u57fa\u7840\u5361\u7247","text":"<p>\u57fa\u7840\u5361\u7247\u6837\u5f0f\u5b9a\u4e49\uff1a</p> CSS<pre><code>/* docs/stylesheets/components/cards.css */\n\n/* \u57fa\u7840\u5361\u7247\u5bb9\u5668 */\n.card {\n  background-color: var(--md-default-bg-color);\n  border-radius: 8px;\n  box-shadow: var(--md-shadow-z1);\n  padding: 1.5rem;\n  margin: 1rem 0;\n  transition: all 0.3s ease;\n}\n\n/* \u5361\u7247\u6807\u9898 */\n.card__title {\n  font-size: 1.25rem;\n  font-weight: 600;\n  margin-bottom: 1rem;\n  color: var(--md-typeset-color);\n}\n\n/* \u5361\u7247\u5185\u5bb9 */\n.card__content {\n  font-size: 0.9rem;\n  color: var(--md-default-fg-color--light);\n  line-height: 1.6;\n}\n\n/* \u5361\u7247\u5e95\u90e8 */\n.card__footer {\n  margin-top: 1rem;\n  padding-top: 1rem;\n  border-top: 1px solid var(--md-default-fg-color--lightest);\n}\n</code></pre> <p>\u4f7f\u7528\u793a\u4f8b\uff1a</p> HTML<pre><code>&lt;div class=\"card\"&gt;\n  &lt;div class=\"card__title\"&gt;\u5361\u7247\u6807\u9898&lt;/div&gt;\n  &lt;div class=\"card__content\"&gt;\n    \u8fd9\u91cc\u662f\u5361\u7247\u5185\u5bb9...\n  &lt;/div&gt;\n  &lt;div class=\"card__footer\"&gt;\n    \u5361\u7247\u5e95\u90e8\u4fe1\u606f\n  &lt;/div&gt;\n&lt;/div&gt;\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5312","title":"5.3.1.2 \u56fe\u7247\u5361\u7247","text":"CSS<pre><code>/* \u56fe\u7247\u5361\u7247\u6837\u5f0f */\n.card--image {\n  padding: 0;\n  overflow: hidden;\n}\n\n/* \u56fe\u7247\u5bb9\u5668 */\n.card__image {\n  width: 100%;\n  height: 200px;\n  position: relative;\n  overflow: hidden;\n}\n\n/* \u56fe\u7247\u6837\u5f0f */\n.card__image img {\n  width: 100%;\n  height: 100%;\n  object-fit: cover;\n  transition: transform 0.3s ease;\n}\n\n/* \u56fe\u7247\u60ac\u505c\u6548\u679c */\n.card--image:hover img {\n  transform: scale(1.05);\n}\n\n/* \u56fe\u7247\u5361\u7247\u5185\u5bb9\u533a */\n.card--image .card__content {\n  padding: 1.5rem;\n}\n\n/* \u56fe\u7247\u6807\u9898\u8986\u76d6 */\n.card__image-title {\n  position: absolute;\n  bottom: 0;\n  left: 0;\n  right: 0;\n  padding: 1rem;\n  background: linear-gradient(to top, rgba(0,0,0,0.7), transparent);\n  color: white;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5313","title":"5.3.1.3 \u7279\u6548\u5361\u7247","text":"CSS<pre><code>/* \u60ac\u6d6e\u6548\u679c\u5361\u7247 */\n.card--hover {\n  cursor: pointer;\n}\n\n.card--hover:hover {\n  transform: translateY(-4px);\n  box-shadow: var(--md-shadow-z2);\n}\n\n/* \u6e10\u53d8\u80cc\u666f\u5361\u7247 */\n.card--gradient {\n  background: linear-gradient(135deg, \n    var(--md-primary-fg-color) 0%,\n    var(--md-accent-fg-color) 100%);\n  color: white;\n}\n\n/* \u6bdb\u73bb\u7483\u6548\u679c\u5361\u7247 */\n.card--glass {\n  background: rgba(255, 255, 255, 0.1);\n  backdrop-filter: blur(10px);\n  border: 1px solid rgba(255, 255, 255, 0.2);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#532","title":"5.3.2 \u63d0\u793a\u6846\u6837\u5f0f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5321","title":"5.3.2.1 \u4fe1\u606f\u63d0\u793a","text":"CSS<pre><code>/* docs/stylesheets/components/alerts.css */\n\n/* \u57fa\u7840\u63d0\u793a\u6846 */\n.alert {\n  padding: 1rem 1.5rem;\n  margin: 1rem 0;\n  border-left: 4px solid;\n  border-radius: 4px;\n}\n\n/* \u4fe1\u606f\u63d0\u793a */\n.alert--info {\n  background-color: #e3f2fd;\n  border-color: #2196f3;\n  color: #0d47a1;\n}\n\n.alert--info::before {\n  content: \"\u2139\ufe0f\";\n  margin-right: 0.5rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5322","title":"5.3.2.2 \u8b66\u544a\u63d0\u793a","text":"CSS<pre><code>/* \u8b66\u544a\u63d0\u793a */\n.alert--warning {\n  background-color: #fff3e0;\n  border-color: #ff9800;\n  color: #e65100;\n}\n\n.alert--warning::before {\n  content: \"\u26a0\ufe0f\";\n  margin-right: 0.5rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5323","title":"5.3.2.3 \u9519\u8bef\u63d0\u793a","text":"CSS<pre><code>/* \u9519\u8bef\u63d0\u793a */\n.alert--error {\n  background-color: #ffebee;\n  border-color: #f44336;\n  color: #b71c1c;\n}\n\n.alert--error::before {\n  content: \"\u274c\";\n  margin-right: 0.5rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#533","title":"5.3.3 \u53cb\u94fe\u6837\u5f0f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5331","title":"5.3.3.1 \u53cb\u94fe\u5361\u7247","text":"CSS<pre><code>/* docs/stylesheets/components/friends.css */\n\n/* \u53cb\u94fe\u5bb9\u5668 */\n.friend-links {\n  display: grid;\n  grid-template-columns: repeat(auto-fill, minmax(250px, 1fr));\n  gap: 1.5rem;\n  margin: 2rem 0;\n}\n\n/* \u53cb\u94fe\u5361\u7247 */\n.friend-link {\n  display: flex;\n  align-items: center;\n  padding: 1rem;\n  background: var(--md-default-bg-color);\n  border-radius: 8px;\n  box-shadow: var(--md-shadow-z1);\n  transition: all 0.3s ease;\n}\n\n/* \u5934\u50cf */\n.friend-link__avatar {\n  width: 60px;\n  height: 60px;\n  border-radius: 50%;\n  margin-right: 1rem;\n}\n\n/* \u4fe1\u606f */\n.friend-link__info {\n  flex: 1;\n}\n\n.friend-link__name {\n  font-weight: 600;\n  color: var(--md-typeset-color);\n}\n\n.friend-link__desc {\n  font-size: 0.85rem;\n  color: var(--md-default-fg-color--light);\n  margin-top: 0.25rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5332","title":"5.3.3.2 \u5206\u7c7b\u5c55\u793a","text":"CSS<pre><code>/* \u53cb\u94fe\u5206\u7c7b */\n.friend-links-section {\n  margin: 2rem 0;\n}\n\n/* \u5206\u7c7b\u6807\u9898 */\n.friend-links-section__title {\n  font-size: 1.25rem;\n  font-weight: 600;\n  margin-bottom: 1rem;\n  padding-left: 1rem;\n  border-left: 4px solid var(--md-accent-fg-color);\n}\n\n/* \u5206\u7c7b\u63cf\u8ff0 */\n.friend-links-section__desc {\n  color: var(--md-default-fg-color--light);\n  margin-bottom: 1.5rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5333","title":"5.3.3.3 \u60ac\u505c\u6548\u679c","text":"CSS<pre><code>/* \u60ac\u505c\u6548\u679c */\n.friend-link:hover {\n  transform: translateY(-2px);\n  box-shadow: var(--md-shadow-z2);\n}\n\n/* \u5934\u50cf\u52a8\u753b */\n.friend-link:hover .friend-link__avatar {\n  transform: rotate(360deg);\n  transition: transform 0.6s ease;\n}\n\n/* \u6807\u7b7e\u6548\u679c */\n.friend-link__tag {\n  display: inline-block;\n  padding: 0.2rem 0.5rem;\n  font-size: 0.75rem;\n  border-radius: 12px;\n  background-color: var(--md-code-bg-color);\n  margin-top: 0.5rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#534","title":"5.3.4 \u65f6\u95f4\u7ebf\u6837\u5f0f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#5341","title":"5.3.4.1 \u65f6\u95f4\u8f74\u8bbe\u8ba1","text":"CSS<pre><code>/* docs/stylesheets/components/timeline.css */\n\n/* \u65f6\u95f4\u7ebf\u5bb9\u5668 */\n.timeline {\n  position: relative;\n  max-width: 800px;\n  margin: 2rem auto;\n  padding: 2rem 0;\n}\n\n/* \u65f6\u95f4\u8f74\u7ebf */\n.timeline::before {\n  content: '';\n  position: absolute;\n  top: 0;\n  left: calc(50% - 1px);\n  width: 2px;\n  height: 100%;\n  background-color: var(--md-default-fg-color--lightest);\n}\n\n/* \u65f6\u95f4\u7ebf\u9879\u76ee */\n.timeline-item {\n  position: relative;\n  margin: 2rem 0;\n}\n\n/* \u4ea4\u9519\u5e03\u5c40 */\n.timeline-item:nth-child(odd) {\n  padding-right: calc(50% + 2rem);\n}\n\n.timeline-item:nth-child(even) {\n  padding-left: calc(50% + 2rem);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5342","title":"5.3.4.2 \u8282\u70b9\u6837\u5f0f","text":"CSS<pre><code>/* \u65f6\u95f4\u8282\u70b9 */\n.timeline-node {\n  position: absolute;\n  top: 50%;\n  width: 16px;\n  height: 16px;\n  background-color: var(--md-primary-fg-color);\n  border-radius: 50%;\n  transform: translateY(-50%);\n}\n\n.timeline-item:nth-child(odd) .timeline-node {\n  right: calc(50% - 8px);\n}\n\n.timeline-item:nth-child(even) .timeline-node {\n  left: calc(50% - 8px);\n}\n\n/* \u8282\u70b9\u5185\u5bb9 */\n.timeline-content {\n  background-color: var(--md-default-bg-color);\n  padding: 1.5rem;\n  border-radius: 8px;\n  box-shadow: var(--md-shadow-z1);\n}\n\n/* \u65f6\u95f4\u6807\u7b7e */\n.timeline-date {\n  position: absolute;\n  top: 50%;\n  color: var(--md-default-fg-color--light);\n  transform: translateY(-50%);\n}\n\n.timeline-item:nth-child(odd) .timeline-date {\n  left: calc(50% + 2rem);\n}\n\n.timeline-item:nth-child(even) .timeline-date {\n  right: calc(50% + 2rem);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5343","title":"5.3.4.3 \u54cd\u5e94\u5f0f\u9002\u914d","text":"CSS<pre><code>/* \u79fb\u52a8\u7aef\u9002\u914d */\n@media screen and (max-width: 768px) {\n  .timeline::before {\n    left: 0;\n  }\n\n  .timeline-item {\n    padding-left: 2rem !important;\n    padding-right: 0 !important;\n  }\n\n  .timeline-node {\n    left: -8px !important;\n    right: auto !important;\n  }\n\n  .timeline-date {\n    position: relative;\n    top: auto;\n    left: auto !important;\n    right: auto !important;\n    margin-bottom: 0.5rem;\n  }\n}\n\n/* \u5e73\u677f\u7aef\u9002\u914d */\n@media screen and (min-width: 769px) and (max-width: 1024px) {\n  .timeline {\n    max-width: 90%;\n  }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#5344","title":"5.3.4.4 \u4f7f\u7528\u793a\u4f8b","text":"HTML<pre><code>&lt;!-- \u65f6\u95f4\u7ebf\u793a\u4f8b --&gt;\n&lt;div class=\"timeline\"&gt;\n  &lt;div class=\"timeline-item\"&gt;\n    &lt;div class=\"timeline-node\"&gt;&lt;/div&gt;\n    &lt;div class=\"timeline-date\"&gt;2024-01-01&lt;/div&gt;\n    &lt;div class=\"timeline-content\"&gt;\n      &lt;h3&gt;\u4e8b\u4ef6\u6807\u9898&lt;/h3&gt;\n      &lt;p&gt;\u4e8b\u4ef6\u63cf\u8ff0...&lt;/p&gt;\n    &lt;/div&gt;\n  &lt;/div&gt;\n\n  &lt;!-- \u66f4\u591a\u65f6\u95f4\u7ebf\u9879\u76ee --&gt;\n&lt;/div&gt;\n\n&lt;!-- \u53cb\u94fe\u793a\u4f8b --&gt;\n&lt;div class=\"friend-links-section\"&gt;\n  &lt;h2 class=\"friend-links-section__title\"&gt;\u6280\u672f\u535a\u5ba2&lt;/h2&gt;\n  &lt;p class=\"friend-links-section__desc\"&gt;\u4f18\u79c0\u7684\u6280\u672f\u535a\u5ba2\u6536\u85cf&lt;/p&gt;\n  &lt;div class=\"friend-links\"&gt;\n    &lt;a href=\"#\" class=\"friend-link\"&gt;\n      &lt;img src=\"avatar.jpg\" class=\"friend-link__avatar\"&gt;\n      &lt;div class=\"friend-link__info\"&gt;\n        &lt;div class=\"friend-link__name\"&gt;\u535a\u5ba2\u540d\u79f0&lt;/div&gt;\n        &lt;div class=\"friend-link__desc\"&gt;\u535a\u5ba2\u63cf\u8ff0&lt;/div&gt;\n        &lt;span class=\"friend-link__tag\"&gt;\u6807\u7b7e&lt;/span&gt;\n      &lt;/div&gt;\n    &lt;/a&gt;\n  &lt;/div&gt;\n&lt;/div&gt;\n\n&lt;!-- \u63d0\u793a\u6846\u793a\u4f8b --&gt;\n&lt;div class=\"alert alert--info\"&gt;\n  \u8fd9\u662f\u4e00\u6761\u4fe1\u606f\u63d0\u793a\n&lt;/div&gt;\n\n&lt;div class=\"alert alert--warning\"&gt;\n  \u8fd9\u662f\u4e00\u6761\u8b66\u544a\u63d0\u793a\n&lt;/div&gt;\n\n&lt;div class=\"alert alert--error\"&gt;\n  \u8fd9\u662f\u4e00\u6761\u9519\u8bef\u63d0\u793a\n&lt;/div&gt;\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#535","title":"5.3.5 \u5b8c\u6574\u914d\u7f6e","text":"YAML<pre><code># mkdocs.yml\nextra_css:\n  - stylesheets/components/cards.css\n  - stylesheets/components/alerts.css\n  - stylesheets/components/friends.css\n  - stylesheets/components/timeline.css\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6-javascript","title":"6 JavaScript \u589e\u5f3a","text":""},{"location":"Tools/Blog/Mkdocs_Material/#61","title":"6.1 \u57fa\u7840\u914d\u7f6e","text":""},{"location":"Tools/Blog/Mkdocs_Material/#611-js","title":"6.1.1 \u5f15\u5165 JS \u6587\u4ef6","text":""},{"location":"Tools/Blog/Mkdocs_Material/#6111","title":"6.1.1.1 \u672c\u5730\u6587\u4ef6","text":"<ol> <li>\u521b\u5efa\u57fa\u7840\u76ee\u5f55\u7ed3\u6784\uff1a</li> </ol> Text Only<pre><code>docs/\n\u251c\u2500\u2500 javascripts/\n\u2502   \u251c\u2500\u2500 config/             # \u914d\u7f6e\u6587\u4ef6\n\u2502   \u2502   \u2514\u2500\u2500 main.js\n\u2502   \u251c\u2500\u2500 modules/            # \u529f\u80fd\u6a21\u5757\n\u2502   \u2502   \u251c\u2500\u2500 search.js\n\u2502   \u2502   \u2514\u2500\u2500 theme.js\n\u2502   \u251c\u2500\u2500 utils/             # \u5de5\u5177\u51fd\u6570\n\u2502   \u2502   \u2514\u2500\u2500 helpers.js\n\u2502   \u2514\u2500\u2500 extra.js           # \u4e3b\u5165\u53e3\u6587\u4ef6\n</code></pre> <ol> <li>\u5728 <code>mkdocs.yml</code> \u4e2d\u5f15\u5165\uff1a</li> </ol> YAML<pre><code>extra_javascript:\n  - javascripts/extra.js\n  - javascripts/modules/search.js\n  - javascripts/modules/theme.js\n</code></pre> <ol> <li>JavaScript \u6587\u4ef6\u793a\u4f8b\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/extra.js\ndocument.addEventListener('DOMContentLoaded', function() {\n    // \u521d\u59cb\u5316\u4ee3\u7801\n    console.log('Documentation loaded');\n});\n\n// docs/javascripts/modules/theme.js\nconst ThemeManager = {\n    init() {\n        // \u4e3b\u9898\u521d\u59cb\u5316\n    },\n    toggle() {\n        // \u4e3b\u9898\u5207\u6362\n    }\n};\n\n// docs/javascripts/utils/helpers.js\nconst Helpers = {\n    debounce(fn, delay) {\n        let timer = null;\n        return function() {\n            clearTimeout(timer);\n            timer = setTimeout(() =&gt; fn.apply(this, arguments), delay);\n        };\n    }\n};\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6112-cdn","title":"6.1.1.2 CDN \u5f15\u5165","text":"<ol> <li>\u5e38\u7528 CDN \u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>extra_javascript:\n  # KaTeX \u6570\u5b66\u516c\u5f0f\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/katex.min.js\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/contrib/auto-render.min.js\n\n  # Mermaid \u56fe\u8868\n  - https://unpkg.com/mermaid@9/dist/mermaid.min.js\n\n  # \u4ee3\u7801\u9ad8\u4eae\n  - https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/prism.min.js\n  - https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/components/prism-python.min.js\n</code></pre> <ol> <li>CDN \u52a0\u901f\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>extra:\n  cdn:\n    # \u4f7f\u7528\u56fd\u5185 CDN\n    enable: true\n    provider: jsdelivr  # \u6216 unpkg, cdnjs\n    urls:\n      katex: https://cdn.jsdelivr.net/npm/katex@0.16.7/dist/katex.min.js\n      mermaid: https://cdn.jsdelivr.net/npm/mermaid@9/dist/mermaid.min.js\n</code></pre> <ol> <li>CDN \u6545\u969c\u5904\u7406\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/config/cdn-fallback.js\nfunction loadFallbackScript(url, fallbackUrl) {\n    const script = document.createElement('script');\n    script.src = url;\n    script.onerror = () =&gt; {\n        console.warn(`Failed to load ${url}, trying fallback...`);\n        const fallback = document.createElement('script');\n        fallback.src = fallbackUrl;\n        document.head.appendChild(fallback);\n    };\n    document.head.appendChild(script);\n}\n\n// \u4f7f\u7528\u793a\u4f8b\nloadFallbackScript(\n    'https://cdn.jsdelivr.net/npm/katex@0.16.7/dist/katex.min.js',\n    'https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/katex.min.js'\n);\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6113","title":"6.1.1.3 \u6a21\u5757\u5316\u7ba1\u7406","text":"<ol> <li>\u4f7f\u7528 ES6 \u6a21\u5757\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/modules/theme.js\nexport class ThemeManager {\n    constructor() {\n        this.darkMode = false;\n    }\n\n    init() {\n        this.loadPreference();\n        this.bindEvents();\n    }\n\n    toggle() {\n        this.darkMode = !this.darkMode;\n        this.savePreference();\n        this.applyTheme();\n    }\n}\n\n// docs/javascripts/modules/search.js\nexport class SearchManager {\n    constructor() {\n        this.index = null;\n    }\n\n    init() {\n        this.buildIndex();\n        this.bindSearchEvents();\n    }\n\n    search(query) {\n        // \u641c\u7d22\u5b9e\u73b0\n    }\n}\n\n// docs/javascripts/extra.js\nimport { ThemeManager } from './modules/theme.js';\nimport { SearchManager } from './modules/search.js';\n\nconst theme = new ThemeManager();\nconst search = new SearchManager();\n\ndocument.addEventListener('DOMContentLoaded', () =&gt; {\n    theme.init();\n    search.init();\n});\n</code></pre> <ol> <li>\u6a21\u5757\u914d\u7f6e\u6587\u4ef6\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/config/modules.js\nexport const ModuleConfig = {\n    theme: {\n        enabled: true,\n        darkModeClass: 'dark-mode',\n        storageKey: 'theme-preference'\n    },\n    search: {\n        enabled: true,\n        minChars: 3,\n        maxResults: 10\n    }\n};\n\n// \u4f7f\u7528\u914d\u7f6e\nimport { ModuleConfig } from '../config/modules.js';\n\nclass ThemeManager {\n    constructor() {\n        this.config = ModuleConfig.theme;\n        if (!this.config.enabled) return;\n        // \u521d\u59cb\u5316\u4ee3\u7801\n    }\n}\n</code></pre> <ol> <li>\u5de5\u5177\u51fd\u6570\u6a21\u5757\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/utils/helpers.js\nexport const DOM = {\n    // DOM \u64cd\u4f5c\u8f85\u52a9\u51fd\u6570\n    select: (selector) =&gt; document.querySelector(selector),\n    selectAll: (selector) =&gt; document.querySelectorAll(selector),\n    addClass: (element, className) =&gt; element.classList.add(className),\n    removeClass: (element, className) =&gt; element.classList.remove(className)\n};\n\nexport const Storage = {\n    // \u672c\u5730\u5b58\u50a8\u8f85\u52a9\u51fd\u6570\n    get: (key) =&gt; localStorage.getItem(key),\n    set: (key, value) =&gt; localStorage.setItem(key, value),\n    remove: (key) =&gt; localStorage.removeItem(key)\n};\n\nexport const Events = {\n    // \u4e8b\u4ef6\u5904\u7406\u8f85\u52a9\u51fd\u6570\n    on: (element, event, handler) =&gt; element.addEventListener(event, handler),\n    off: (element, event, handler) =&gt; element.removeEventListener(event, handler),\n    trigger: (element, event) =&gt; element.dispatchEvent(new Event(event))\n};\n</code></pre> <ol> <li>\u5b8c\u6574\u914d\u7f6e\u793a\u4f8b\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nextra_javascript:\n  # \u6838\u5fc3\u6587\u4ef6\n  - javascripts/extra.js\n  - javascripts/config/modules.js\n\n  # \u529f\u80fd\u6a21\u5757\n  - javascripts/modules/theme.js\n  - javascripts/modules/search.js\n\n  # \u5de5\u5177\u51fd\u6570\n  - javascripts/utils/helpers.js\n\n  # \u7b2c\u4e09\u65b9\u5e93\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/katex.min.js\n  - https://unpkg.com/mermaid@9/dist/mermaid.min.js\n\n# \u6a21\u5757\u914d\u7f6e\nextra:\n  javascript_modules:\n    theme:\n      enabled: true\n      default: light\n    search:\n      enabled: true\n      min_chars: 3\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#62","title":"6.2 \u7b2c\u4e09\u65b9\u5e93\u96c6\u6210","text":""},{"location":"Tools/Blog/Mkdocs_Material/#621-katex","title":"6.2.1 KaTeX \u6570\u5b66\u516c\u5f0f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#6211","title":"6.2.1.1 \u57fa\u7840\u914d\u7f6e","text":"<ol> <li>\u5728 <code>mkdocs.yml</code> \u4e2d\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>markdown_extensions:\n  - pymdownx.arithmatex:\n      generic: true\n\nextra_javascript:\n  - javascripts/katex.js\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/katex.min.js\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/contrib/auto-render.min.js\n\nextra_css:\n  - https://cdnjs.cloudflare.com/ajax/libs/KaTeX/0.16.7/katex.min.css\n</code></pre> <ol> <li>\u521b\u5efa KaTeX \u914d\u7f6e\u6587\u4ef6\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/katex.js\ndocument.addEventListener(\"DOMContentLoaded\", function() {\n    renderMathInElement(document.body, {\n        delimiters: [\n            {left: \"$$\", right: \"$$\", display: true},\n            {left: \"$\", right: \"$\", display: false},\n            {left: \"\\\\(\", right: \"\\\\)\", display: false},\n            {left: \"\\\\[\", right: \"\\\\]\", display: true}\n        ],\n        throwOnError: false,\n        errorColor: \"#cc0000\",\n        strict: \"ignore\"\n    });\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6212","title":"6.2.1.2 \u81ea\u52a8\u6e32\u67d3","text":"<ol> <li>\u914d\u7f6e\u81ea\u52a8\u6e32\u67d3\u9009\u9879\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/katex-auto.js\ndocument.addEventListener(\"DOMContentLoaded\", function() {\n    renderMathInElement(document.body, {\n        delimiters: [\n            {left: \"$$\", right: \"$$\", display: true},\n            {left: \"$\", right: \"$\", display: false}\n        ],\n        // \u81ea\u52a8\u6e32\u67d3\u8bbe\u7f6e\n        ignoredTags: [\"script\", \"noscript\", \"style\", \"textarea\", \"pre\", \"code\"],\n        ignoredClasses: [\"no-math\"],\n        processEscapes: true,\n        processEnvironments: true,\n        // \u5904\u7406\u81ea\u5b9a\u4e49\u5b8f\n        macros: {\n            \"\\\\RR\": \"\\\\mathbb{R}\",\n            \"\\\\NN\": \"\\\\mathbb{N}\",\n            \"\\\\ZZ\": \"\\\\mathbb{Z}\"\n        }\n    });\n});\n</code></pre> <ol> <li>\u4f7f\u7528\u793a\u4f8b\uff1a</li> </ol> Markdown<pre><code>\u884c\u5185\u516c\u5f0f\uff1a$E = mc^2$\n\n\u5757\u7ea7\u516c\u5f0f\uff1a\n$$\n\\frac{n!}{k!(n-k)!} = \\binom{n}{k}\n$$\n\n\u81ea\u5b9a\u4e49\u5b8f\uff1a$\\RR$ \u8868\u793a\u5b9e\u6570\u96c6\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6213","title":"6.2.1.3 \u516c\u5f0f\u7f16\u53f7","text":"<ol> <li>\u542f\u7528\u516c\u5f0f\u7f16\u53f7\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/katex-numbering.js\ndocument.addEventListener(\"DOMContentLoaded\", function() {\n    // \u516c\u5f0f\u7f16\u53f7\u8ba1\u6570\u5668\n    let equationNumbers = {};\n    let numberings = {};\n\n    renderMathInElement(document.body, {\n        delimiters: [\n            {left: \"$$\", right: \"$$\", display: true}\n        ],\n        // \u516c\u5f0f\u7f16\u53f7\u5904\u7406\n        preProcess: (math) =&gt; {\n            if (math.includes('\\\\label')) {\n                const label = math.match(/\\\\label{([^}]*)}/)[1];\n                const number = Object.keys(numberings).length + 1;\n                numberings[label] = number;\n                return math.replace(/\\\\label{[^}]*}/, `(${number})`);\n            }\n            return math;\n        }\n    });\n});\n</code></pre> <ol> <li>\u4f7f\u7528\u7f16\u53f7\u548c\u5f15\u7528\uff1a</li> </ol> Markdown<pre><code>\u5e26\u7f16\u53f7\u7684\u516c\u5f0f\uff1a\n$$\nE = mc^2 \\label{eq:einstein}\n$$\n\n\u5f15\u7528\u4e0a\u9762\u7684\u516c\u5f0f $\\eqref{eq:einstein}$\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#622-mermaid","title":"6.2.2 Mermaid \u56fe\u8868","text":""},{"location":"Tools/Blog/Mkdocs_Material/#6221","title":"6.2.2.1 \u521d\u59cb\u5316\u914d\u7f6e","text":"<ol> <li>\u5728 <code>mkdocs.yml</code> \u4e2d\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>markdown_extensions:\n  - pymdownx.superfences:\n      custom_fences:\n        - name: mermaid\n          class: mermaid\n          format: !!python/name:pymdownx.superfences.fence_code_format\n\nextra_javascript:\n  - https://unpkg.com/mermaid@9/dist/mermaid.min.js\n  - javascripts/mermaid.js\n</code></pre> <ol> <li>\u521b\u5efa Mermaid \u914d\u7f6e\u6587\u4ef6\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/mermaid.js\ndocument.addEventListener(\"DOMContentLoaded\", function() {\n    mermaid.initialize({\n        startOnLoad: true,\n        theme: 'default',\n        sequence: {\n            showSequenceNumbers: true,\n            actorMargin: 50,\n            messageMargin: 40\n        },\n        flowchart: {\n            useMaxWidth: false,\n            htmlLabels: true,\n            curve: 'basis'\n        },\n        gantt: {\n            titleTopMargin: 25,\n            barHeight: 20,\n            barGap: 4\n        }\n    });\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6222","title":"6.2.2.2 \u4e3b\u9898\u5b9a\u5236","text":"<ol> <li>\u81ea\u5b9a\u4e49\u4e3b\u9898\u914d\u7f6e\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/mermaid-theme.js\nmermaid.initialize({\n    theme: 'base',\n    themeVariables: {\n        // \u57fa\u7840\u989c\u8272\n        primaryColor: '#2196f3',\n        primaryTextColor: '#fff',\n        primaryBorderColor: '#1976d2',\n        lineColor: '#696969',\n\n        // \u6d41\u7a0b\u56fe\u989c\u8272\n        nodeBkg: '#fff',\n        mainBkg: '#f8f9fa',\n        nodeTextColor: '#333',\n\n        // \u65f6\u5e8f\u56fe\u989c\u8272\n        actorBkg: '#f8f9fa',\n        actorBorder: '#2196f3',\n        actorTextColor: '#333',\n\n        // \u7518\u7279\u56fe\u989c\u8272\n        sectionBkgColor: '#f8f9fa',\n        altSectionBkgColor: '#fff',\n\n        // \u6697\u8272\u4e3b\u9898\u652f\u6301\n        darkMode: false\n    }\n});\n</code></pre> <ol> <li>\u54cd\u5e94\u4e3b\u9898\u5207\u6362\uff1a</li> </ol> JavaScript<pre><code>// \u76d1\u542c\u4e3b\u9898\u5207\u6362\ndocument.addEventListener('themeChanged', function(e) {\n    const isDark = e.detail.theme === 'dark';\n    mermaid.initialize({\n        theme: isDark ? 'dark' : 'default',\n        themeVariables: {\n            darkMode: isDark\n        }\n    });\n    // \u91cd\u65b0\u6e32\u67d3\u56fe\u8868\n    mermaid.init(undefined, '.mermaid');\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6223","title":"6.2.2.3 \u4ea4\u4e92\u529f\u80fd","text":"<ol> <li>\u6dfb\u52a0\u70b9\u51fb\u4e8b\u4ef6\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/mermaid-interaction.js\nmermaid.initialize({\n    securityLevel: 'loose',\n    flowchart: {\n        htmlLabels: true,\n        useMaxWidth: true\n    }\n});\n\ndocument.addEventListener(\"DOMContentLoaded\", function() {\n    // \u4e3a\u56fe\u8868\u6dfb\u52a0\u70b9\u51fb\u4e8b\u4ef6\n    const diagrams = document.querySelectorAll('.mermaid');\n    diagrams.forEach(diagram =&gt; {\n        diagram.addEventListener('click', function(e) {\n            const target = e.target;\n            if (target.tagName === 'g' &amp;&amp; target.classList.contains('node')) {\n                const nodeId = target.id;\n                console.log('Clicked node:', nodeId);\n                // \u5904\u7406\u8282\u70b9\u70b9\u51fb\n                handleNodeClick(nodeId);\n            }\n        });\n    });\n});\n\nfunction handleNodeClick(nodeId) {\n    // \u8282\u70b9\u70b9\u51fb\u5904\u7406\n    const node = document.getElementById(nodeId);\n    if (node) {\n        // \u6dfb\u52a0\u9ad8\u4eae\u6548\u679c\n        node.classList.add('node-highlight');\n        setTimeout(() =&gt; {\n            node.classList.remove('node-highlight');\n        }, 1000);\n    }\n}\n</code></pre> <ol> <li>\u6dfb\u52a0\u56fe\u8868\u52a8\u753b\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/mermaid.css */\n.mermaid .node-highlight {\n    animation: pulse 1s;\n}\n\n@keyframes pulse {\n    0% { opacity: 1; }\n    50% { opacity: 0.5; }\n    100% { opacity: 1; }\n}\n\n.mermaid .flowchart-link {\n    transition: stroke-width 0.3s ease;\n}\n\n.mermaid .flowchart-link:hover {\n    stroke-width: 2px;\n    cursor: pointer;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6224","title":"6.2.2.4 \u4f7f\u7528\u793a\u4f8b","text":"<ol> <li>\u6d41\u7a0b\u56fe\u793a\u4f8b\uff1a</li> </ol> Markdown<pre><code>```mermaid\ngraph TD\n    A[\u5f00\u59cb] --&gt; B{\u5224\u65ad}\n    B --&gt;|Yes| C[\u5904\u7406]\n    B --&gt;|No| D[\u7ed3\u675f]\n    C --&gt; D\n```\n</code></pre> <ol> <li>\u65f6\u5e8f\u56fe\u793a\u4f8b\uff1a</li> </ol> Markdown<pre><code>```mermaid\nsequenceDiagram\n    participant \u5ba2\u6237\u7aef\n    participant \u670d\u52a1\u5668\n\n    \u5ba2\u6237\u7aef-&gt;&gt;\u670d\u52a1\u5668: \u8bf7\u6c42\u6570\u636e\n    \u670d\u52a1\u5668--&gt;&gt;\u5ba2\u6237\u7aef: \u8fd4\u56de\u54cd\u5e94\n```\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#623","title":"6.2.3 \u4ee3\u7801\u590d\u5236","text":""},{"location":"Tools/Blog/Mkdocs_Material/#6231","title":"6.2.3.1 \u590d\u5236\u6309\u94ae","text":"<ol> <li>\u5728 <code>mkdocs.yml</code> \u4e2d\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>theme:\n  features:\n    - content.code.copy\n\nextra_css:\n  - stylesheets/code-copy.css\nextra_javascript:\n  - javascripts/code-copy.js\n</code></pre> <ol> <li>\u521b\u5efa\u590d\u5236\u6309\u94ae\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/code-copy.css */\n\n/* \u590d\u5236\u6309\u94ae\u5bb9\u5668 */\n.copy-button {\n  position: absolute;\n  right: 0.5rem;\n  top: 0.5rem;\n  padding: 0.4rem;\n  background-color: rgba(0, 0, 0, 0.1);\n  border: none;\n  border-radius: 4px;\n  cursor: pointer;\n  transition: all 0.2s ease;\n}\n\n/* \u6309\u94ae\u60ac\u505c\u6548\u679c */\n.copy-button:hover {\n  background-color: rgba(0, 0, 0, 0.2);\n}\n\n/* \u56fe\u6807\u6837\u5f0f */\n.copy-button i {\n  font-size: 1rem;\n  color: var(--md-default-fg-color--light);\n}\n\n/* \u6210\u529f\u72b6\u6001 */\n.copy-button.success {\n  background-color: var(--md-accent-fg-color);\n}\n\n.copy-button.success i {\n  color: white;\n}\n</code></pre> <ol> <li>\u5b9e\u73b0\u590d\u5236\u529f\u80fd\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/code-copy.js\ndocument.addEventListener('DOMContentLoaded', () =&gt; {\n  // \u4e3a\u6240\u6709\u4ee3\u7801\u5757\u6dfb\u52a0\u590d\u5236\u6309\u94ae\n  const codeBlocks = document.querySelectorAll('pre code');\n\n  codeBlocks.forEach((codeBlock) =&gt; {\n    const container = codeBlock.parentNode;\n    const copyButton = document.createElement('button');\n    copyButton.className = 'copy-button';\n    copyButton.innerHTML = '&lt;i class=\"material-icons\"&gt;content_copy&lt;/i&gt;';\n    container.style.position = 'relative';\n    container.appendChild(copyButton);\n\n    // \u6dfb\u52a0\u70b9\u51fb\u4e8b\u4ef6\n    copyButton.addEventListener('click', async () =&gt; {\n      try {\n        await navigator.clipboard.writeText(codeBlock.textContent);\n        showSuccess(copyButton);\n      } catch (err) {\n        showError(copyButton);\n      }\n    });\n  });\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6232","title":"6.2.3.2 \u63d0\u793a\u6d88\u606f","text":"<ol> <li>\u521b\u5efa\u63d0\u793a\u6d88\u606f\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* \u63d0\u793a\u6d88\u606f\u6837\u5f0f */\n.copy-tooltip {\n  position: absolute;\n  top: -2rem;\n  right: 0;\n  padding: 0.4rem 0.8rem;\n  background-color: var(--md-default-fg-color);\n  color: var(--md-default-bg-color);\n  border-radius: 4px;\n  font-size: 0.8rem;\n  opacity: 0;\n  transform: translateY(0.4rem);\n  transition: all 0.2s ease;\n}\n\n.copy-tooltip.show {\n  opacity: 1;\n  transform: translateY(0);\n}\n</code></pre> <ol> <li>\u5b9e\u73b0\u63d0\u793a\u529f\u80fd\uff1a</li> </ol> JavaScript<pre><code>// \u663e\u793a\u63d0\u793a\u6d88\u606f\nfunction showTooltip(button, message, type = 'success') {\n  const tooltip = document.createElement('div');\n  tooltip.className = `copy-tooltip ${type}`;\n  tooltip.textContent = message;\n  button.appendChild(tooltip);\n\n  // \u6dfb\u52a0\u663e\u793a\u7c7b\n  setTimeout(() =&gt; tooltip.classList.add('show'), 10);\n\n  // \u81ea\u52a8\u79fb\u9664\n  setTimeout(() =&gt; {\n    tooltip.classList.remove('show');\n    setTimeout(() =&gt; tooltip.remove(), 200);\n  }, 2000);\n}\n\n// \u6210\u529f\u63d0\u793a\nfunction showSuccess(button) {\n  button.classList.add('success');\n  showTooltip(button, '\u590d\u5236\u6210\u529f\uff01');\n  setTimeout(() =&gt; button.classList.remove('success'), 2000);\n}\n\n// \u9519\u8bef\u63d0\u793a\nfunction showError(button) {\n  button.classList.add('error');\n  showTooltip(button, '\u590d\u5236\u5931\u8d25\uff01', 'error');\n  setTimeout(() =&gt; button.classList.remove('error'), 2000);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6233","title":"6.2.3.3 \u590d\u5236\u56de\u8c03","text":"JavaScript<pre><code>// \u5b9a\u4e49\u590d\u5236\u4e8b\u4ef6\u5904\u7406\u5668\nconst copyHandlers = {\n  // \u590d\u5236\u524d\u5904\u7406\n  beforeCopy: (code) =&gt; {\n    // \u53ef\u4ee5\u5728\u8fd9\u91cc\u5bf9\u4ee3\u7801\u8fdb\u884c\u9884\u5904\u7406\n    return code.trim();\n  },\n\n  // \u590d\u5236\u6210\u529f\u56de\u8c03\n  onSuccess: (button, code) =&gt; {\n    console.log('Copied:', code.length, 'characters');\n    showSuccess(button);\n\n    // \u89e6\u53d1\u81ea\u5b9a\u4e49\u4e8b\u4ef6\n    const event = new CustomEvent('codeCopied', {\n      detail: { code }\n    });\n    document.dispatchEvent(event);\n  },\n\n  // \u590d\u5236\u5931\u8d25\u56de\u8c03\n  onError: (button, error) =&gt; {\n    console.error('Copy failed:', error);\n    showError(button);\n  }\n};\n\n// \u4f7f\u7528\u56de\u8c03\nasync function copyCode(button, code) {\n  try {\n    const processedCode = copyHandlers.beforeCopy(code);\n    await navigator.clipboard.writeText(processedCode);\n    copyHandlers.onSuccess(button, processedCode);\n  } catch (err) {\n    copyHandlers.onError(button, err);\n  }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#624","title":"6.2.4 \u56fe\u7247\u9884\u89c8","text":""},{"location":"Tools/Blog/Mkdocs_Material/#6241-lightbox","title":"6.2.4.1 lightbox \u914d\u7f6e","text":"<ol> <li>\u5728 <code>mkdocs.yml</code> \u4e2d\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>markdown_extensions:\n  - attr_list\n  - md_in_html\n\nplugins:\n  - glightbox\n\nextra_css:\n  - stylesheets/glightbox.css\nextra_javascript:\n  - javascripts/glightbox.js\n</code></pre> <ol> <li>\u914d\u7f6e GLightbox\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/glightbox.js\ndocument.addEventListener('DOMContentLoaded', () =&gt; {\n  const lightbox = GLightbox({\n    selector: '.glightbox',\n    touchNavigation: true,\n    loop: false,\n    autoplayVideos: true,\n    preload: true,\n    // \u57fa\u672c\u8bbe\u7f6e\n    height: 'auto',\n    zoomable: true,\n    draggable: true,\n    // \u52a8\u753b\u8bbe\u7f6e\n    openEffect: 'zoom',\n    closeEffect: 'fade',\n    cssEfects: {\n      fade: { in: 'fadeIn', out: 'fadeOut' },\n      zoom: { in: 'zoomIn', out: 'zoomOut' }\n    }\n  });\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6242","title":"6.2.4.2 \u7f29\u653e\u529f\u80fd","text":"JavaScript<pre><code>// \u7f29\u653e\u529f\u80fd\u914d\u7f6e\nconst zoomConfig = {\n  // \u7f29\u653e\u9009\u9879\n  zoomable: true,\n  dragToZoom: true,\n  touchToZoom: true,\n\n  // \u7f29\u653e\u7ea7\u522b\n  minZoom: 0.5,\n  maxZoom: 3,\n  zoomStep: 0.5,\n\n  // \u53cc\u51fb\u7f29\u653e\n  doubleTapZoom: 2,\n\n  // \u7f29\u653e\u52a8\u753b\n  zoomAnimation: true,\n  zoomDuration: 300,\n\n  // \u7f29\u653e\u63a7\u5236\u5668\n  controls: {\n    zoom: true,\n    zoomIn: true,\n    zoomOut: true,\n    rotate: true\n  }\n};\n\n// \u5e94\u7528\u7f29\u653e\u914d\u7f6e\nconst lightbox = GLightbox({\n  ...zoomConfig,\n\n  // \u7f29\u653e\u4e8b\u4ef6\u5904\u7406\n  onZoom: (slider) =&gt; {\n    const { zoom, image } = slider;\n    console.log(`Current zoom level: ${zoom}`);\n  }\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6243","title":"6.2.4.3 \u624b\u52bf\u652f\u6301","text":"JavaScript<pre><code>// \u624b\u52bf\u914d\u7f6e\nconst gestureConfig = {\n  // \u89e6\u6478\u5bfc\u822a\n  touchNavigation: true,\n  touchFollowAxis: true,\n\n  // \u62d6\u52a8\u8bbe\u7f6e\n  draggable: true,\n  dragToleranceX: 40,\n  dragToleranceY: 65,\n\n  // \u624b\u52bf\u4e8b\u4ef6\n  gestures: {\n    // \u634f\u5408\u7f29\u653e\n    pinchToZoom: true,\n    pinchThreshold: 50,\n\n    // \u53cc\u6307\u65cb\u8f6c\n    rotateToZoom: true,\n    rotateThreshold: 15,\n\n    // \u6ed1\u52a8\u5207\u6362\n    swipeThreshold: 50,\n    swipeToClose: true\n  }\n};\n\n// \u624b\u52bf\u4e8b\u4ef6\u5904\u7406\nconst gestureHandlers = {\n  // \u89e6\u6478\u5f00\u59cb\n  onTouchStart: (e) =&gt; {\n    const touch = e.touches[0];\n    startX = touch.clientX;\n    startY = touch.clientY;\n  },\n\n  // \u89e6\u6478\u79fb\u52a8\n  onTouchMove: (e) =&gt; {\n    if (!isDragging) return;\n    const touch = e.touches[0];\n    const deltaX = touch.clientX - startX;\n    const deltaY = touch.clientY - startY;\n\n    // \u5904\u7406\u79fb\u52a8\n    handleImageMove(deltaX, deltaY);\n  },\n\n  // \u89e6\u6478\u7ed3\u675f\n  onTouchEnd: (e) =&gt; {\n    isDragging = false;\n    // \u5904\u7406\u60ef\u6027\u6ed1\u52a8\n    handleMomentum();\n  }\n};\n\n// \u521b\u5efa\u589e\u5f3a\u7684\u56fe\u7247\u9884\u89c8\nconst enhancedLightbox = GLightbox({\n  ...zoomConfig,\n  ...gestureConfig,\n\n  // \u4e8b\u4ef6\u76d1\u542c\n  listeners: {\n    touchstart: gestureHandlers.onTouchStart,\n    touchmove: gestureHandlers.onTouchMove,\n    touchend: gestureHandlers.onTouchEnd\n  }\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6244","title":"6.2.4.4 \u5b8c\u6574\u793a\u4f8b","text":"JavaScript<pre><code>// docs/javascripts/image-preview.js\ndocument.addEventListener('DOMContentLoaded', () =&gt; {\n  // \u521d\u59cb\u5316\u914d\u7f6e\n  const config = {\n    // \u57fa\u7840\u8bbe\u7f6e\n    selector: '.glightbox',\n    touchNavigation: true,\n    loop: false,\n\n    // \u7f29\u653e\u8bbe\u7f6e\n    zoomable: true,\n    draggable: true,\n    dragToleranceX: 40,\n    dragToleranceY: 65,\n\n    // \u52a8\u753b\u8bbe\u7f6e\n    openEffect: 'zoom',\n    closeEffect: 'fade',\n\n    // \u624b\u52bf\u8bbe\u7f6e\n    touchFollowAxis: true,\n\n    // \u754c\u9762\u8bbe\u7f6e\n    preload: true,\n    height: 'auto',\n\n    // \u4e8b\u4ef6\u5904\u7406\n    onOpen: () =&gt; {\n      console.log('Lightbox opened');\n    },\n    onClose: () =&gt; {\n      console.log('Lightbox closed');\n    },\n    onZoom: (slider) =&gt; {\n      console.log('Image zoomed');\n    }\n  };\n\n  // \u521d\u59cb\u5316 GLightbox\n  const lightbox = GLightbox(config);\n\n  // \u6dfb\u52a0\u952e\u76d8\u652f\u6301\n  document.addEventListener('keydown', (e) =&gt; {\n    if (!lightbox.isOpen) return;\n\n    switch(e.key) {\n      case 'ArrowLeft':\n        lightbox.prev();\n        break;\n      case 'ArrowRight':\n        lightbox.next();\n        break;\n      case 'Escape':\n        lightbox.close();\n        break;\n    }\n  });\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#63","title":"6.3 \u81ea\u5b9a\u4e49\u529f\u80fd","text":""},{"location":"Tools/Blog/Mkdocs_Material/#631","title":"6.3.1 \u9875\u9762\u4ea4\u4e92","text":""},{"location":"Tools/Blog/Mkdocs_Material/#6311","title":"6.3.1.1 \u6eda\u52a8\u4e8b\u4ef6","text":"<ol> <li>\u57fa\u7840\u6eda\u52a8\u76d1\u542c\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/scroll.js\ndocument.addEventListener('DOMContentLoaded', function() {\n    // \u6eda\u52a8\u5904\u7406\u51fd\u6570\n    function handleScroll() {\n        const scrollTop = window.scrollY;\n        const windowHeight = window.innerHeight;\n        const docHeight = document.documentElement.scrollHeight;\n\n        // \u6eda\u52a8\u8fdb\u5ea6\n        const scrollPercent = (scrollTop / (docHeight - windowHeight)) * 100;\n\n        // \u66f4\u65b0\u8fdb\u5ea6\u6761\n        updateProgress(scrollPercent);\n\n        // \u5904\u7406\u5143\u7d20\u53ef\u89c1\u6027\n        handleVisibility();\n    }\n\n    // \u4f7f\u7528\u8282\u6d41\u4f18\u5316\u6eda\u52a8\u4e8b\u4ef6\n    const throttledScroll = throttle(handleScroll, 100);\n    window.addEventListener('scroll', throttledScroll);\n});\n\n// \u8282\u6d41\u51fd\u6570\nfunction throttle(fn, delay) {\n    let lastCall = 0;\n    return function(...args) {\n        const now = Date.now();\n        if (now - lastCall &gt;= delay) {\n            lastCall = now;\n            fn.apply(this, args);\n        }\n    };\n}\n</code></pre> <ol> <li>\u5143\u7d20\u53ef\u89c1\u6027\u68c0\u6d4b\uff1a</li> </ol> JavaScript<pre><code>// \u68c0\u6d4b\u5143\u7d20\u662f\u5426\u8fdb\u5165\u89c6\u53e3\nfunction handleVisibility() {\n    const elements = document.querySelectorAll('.animate-on-scroll');\n\n    elements.forEach(element =&gt; {\n        const rect = element.getBoundingClientRect();\n        const isVisible = (\n            rect.top &gt;= 0 &amp;&amp;\n            rect.left &gt;= 0 &amp;&amp;\n            rect.bottom &lt;= window.innerHeight &amp;&amp;\n            rect.right &lt;= window.innerWidth\n        );\n\n        if (isVisible) {\n            element.classList.add('is-visible');\n        }\n    });\n}\n\n// CSS \u6837\u5f0f\n.animate-on-scroll {\n    opacity: 0;\n    transform: translateY(20px);\n    transition: all 0.6s ease;\n}\n\n.animate-on-scroll.is-visible {\n    opacity: 1;\n    transform: translateY(0);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6312","title":"6.3.1.2 \u70b9\u51fb\u4e8b\u4ef6","text":"<ol> <li>\u70b9\u51fb\u5904\u7406\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/click.js\ndocument.addEventListener('DOMContentLoaded', function() {\n    // \u4ee3\u7801\u5757\u70b9\u51fb\u590d\u5236\n    setupCodeCopy();\n\n    // \u56fe\u7247\u70b9\u51fb\u653e\u5927\n    setupImageZoom();\n\n    // \u76ee\u5f55\u70b9\u51fb\u6eda\u52a8\n    setupTocScroll();\n});\n\n// \u4ee3\u7801\u590d\u5236\u529f\u80fd\nfunction setupCodeCopy() {\n    const codeBlocks = document.querySelectorAll('pre code');\n\n    codeBlocks.forEach(block =&gt; {\n        block.addEventListener('click', async function(e) {\n            if (e.target.classList.contains('copy-button')) {\n                try {\n                    await navigator.clipboard.writeText(block.textContent);\n                    showToast('\u590d\u5236\u6210\u529f\uff01');\n                } catch (err) {\n                    showToast('\u590d\u5236\u5931\u8d25', 'error');\n                }\n            }\n        });\n    });\n}\n\n// \u56fe\u7247\u7f29\u653e\u529f\u80fd\nfunction setupImageZoom() {\n    const images = document.querySelectorAll('.md-content img');\n\n    images.forEach(img =&gt; {\n        img.addEventListener('click', function() {\n            const overlay = document.createElement('div');\n            overlay.className = 'image-overlay';\n            overlay.innerHTML = `\n                &lt;img src=\"${img.src}\" alt=\"${img.alt}\"&gt;\n                &lt;button class=\"close-button\"&gt;\u00d7&lt;/button&gt;\n            `;\n\n            document.body.appendChild(overlay);\n\n            overlay.querySelector('.close-button').addEventListener('click', () =&gt; {\n                overlay.remove();\n            });\n        });\n    });\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6313","title":"6.3.1.3 \u952e\u76d8\u4e8b\u4ef6","text":"JavaScript<pre><code>// docs/javascripts/keyboard.js\ndocument.addEventListener('DOMContentLoaded', function() {\n    // \u952e\u76d8\u5bfc\u822a\n    setupKeyboardNav();\n\n    // \u641c\u7d22\u5feb\u6377\u952e\n    setupSearchShortcut();\n});\n\n// \u952e\u76d8\u5bfc\u822a\nfunction setupKeyboardNav() {\n    document.addEventListener('keydown', function(e) {\n        // ALT + \u65b9\u5411\u952e\u5bfc\u822a\n        if (e.altKey) {\n            switch(e.key) {\n                case 'ArrowLeft':  // \u4e0a\u4e00\u9875\n                    navigatePage('prev');\n                    break;\n                case 'ArrowRight':  // \u4e0b\u4e00\u9875\n                    navigatePage('next');\n                    break;\n                case 'ArrowUp':    // \u56de\u5230\u9876\u90e8\n                    window.scrollTo({top: 0, behavior: 'smooth'});\n                    break;\n                case 'ArrowDown':  // \u5230\u8fbe\u5e95\u90e8\n                    window.scrollTo({\n                        top: document.documentElement.scrollHeight,\n                        behavior: 'smooth'\n                    });\n                    break;\n            }\n        }\n    });\n}\n\n// \u641c\u7d22\u5feb\u6377\u952e\nfunction setupSearchShortcut() {\n    document.addEventListener('keydown', function(e) {\n        // \u6309\u4e0b '/' \u952e\u89e6\u53d1\u641c\u7d22\n        if (e.key === '/' &amp;&amp; !e.ctrlKey &amp;&amp; !e.altKey &amp;&amp; !e.metaKey) {\n            e.preventDefault();\n            const searchInput = document.querySelector('.md-search__input');\n            if (searchInput) {\n                searchInput.focus();\n            }\n        }\n    });\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#632","title":"6.3.2 \u52a8\u753b\u6548\u679c","text":""},{"location":"Tools/Blog/Mkdocs_Material/#6321","title":"6.3.2.1 \u8fc7\u6e21\u52a8\u753b","text":"<ol> <li>\u57fa\u7840\u8fc7\u6e21\u6548\u679c\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/transitions.css */\n\n/* \u9875\u9762\u5207\u6362\u8fc7\u6e21 */\n.md-content {\n    animation: fadeIn 0.3s ease-in-out;\n}\n\n@keyframes fadeIn {\n    from {\n        opacity: 0;\n        transform: translateY(20px);\n    }\n    to {\n        opacity: 1;\n        transform: translateY(0);\n    }\n}\n\n/* \u5bfc\u822a\u8fc7\u6e21 */\n.md-nav__link {\n    transition: color 0.2s ease, padding-left 0.2s ease;\n}\n\n.md-nav__link:hover {\n    padding-left: 0.5rem;\n    color: var(--md-accent-fg-color);\n}\n</code></pre> <ol> <li>\u9875\u9762\u5207\u6362\u52a8\u753b\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/transitions.js\ndocument.addEventListener('DOMContentLoaded', function() {\n    // \u9875\u9762\u5207\u6362\u52a8\u753b\n    setupPageTransitions();\n});\n\nfunction setupPageTransitions() {\n    // \u76d1\u542c\u9875\u9762\u5207\u6362\u4e8b\u4ef6\n    document.addEventListener('DOMContentLoaded', function() {\n        document.body.classList.add('page-transition-ready');\n    });\n\n    // \u9875\u9762\u79bb\u5f00\u52a8\u753b\n    window.addEventListener('beforeunload', function() {\n        document.body.classList.add('page-transition-exit');\n    });\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6322","title":"6.3.2.2 \u52a0\u8f7d\u52a8\u753b","text":"<ol> <li>\u521b\u5efa\u52a0\u8f7d\u52a8\u753b\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/loading.css */\n\n/* \u52a0\u8f7d\u52a8\u753b\u5bb9\u5668 */\n.loading-overlay {\n    position: fixed;\n    top: 0;\n    left: 0;\n    right: 0;\n    bottom: 0;\n    background-color: var(--md-default-bg-color);\n    display: flex;\n    justify-content: center;\n    align-items: center;\n    z-index: 999;\n    opacity: 1;\n    transition: opacity 0.3s ease;\n}\n\n/* \u52a0\u8f7d\u52a8\u753b */\n.loading-spinner {\n    width: 40px;\n    height: 40px;\n    border: 3px solid var(--md-primary-fg-color--light);\n    border-top-color: var(--md-primary-fg-color);\n    border-radius: 50%;\n    animation: spin 1s linear infinite;\n}\n\n@keyframes spin {\n    to { transform: rotate(360deg); }\n}\n</code></pre> <ol> <li>\u5b9e\u73b0\u52a0\u8f7d\u903b\u8f91\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/loading.js\nclass LoadingManager {\n    constructor() {\n        this.overlay = null;\n        this.createLoadingOverlay();\n    }\n\n    createLoadingOverlay() {\n        this.overlay = document.createElement('div');\n        this.overlay.className = 'loading-overlay';\n        this.overlay.innerHTML = '&lt;div class=\"loading-spinner\"&gt;&lt;/div&gt;';\n        document.body.appendChild(this.overlay);\n    }\n\n    show() {\n        this.overlay.style.opacity = '1';\n        this.overlay.style.visibility = 'visible';\n    }\n\n    hide() {\n        this.overlay.style.opacity = '0';\n        setTimeout(() =&gt; {\n            this.overlay.style.visibility = 'hidden';\n        }, 300);\n    }\n}\n\n// \u4f7f\u7528\u52a0\u8f7d\u7ba1\u7406\u5668\nconst loading = new LoadingManager();\n\n// \u9875\u9762\u52a0\u8f7d\u5b8c\u6210\u540e\u9690\u85cf\nwindow.addEventListener('load', () =&gt; {\n    loading.hide();\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6323","title":"6.3.2.3 \u4ea4\u4e92\u52a8\u753b","text":"<ol> <li>\u5143\u7d20\u4ea4\u4e92\u52a8\u753b\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/interactions.js\ndocument.addEventListener('DOMContentLoaded', function() {\n    // \u6309\u94ae\u6ce2\u7eb9\u6548\u679c\n    setupRippleEffect();\n\n    // \u5361\u7247\u60ac\u6d6e\u6548\u679c\n    setupCardHover();\n\n    // \u5217\u8868\u9879\u52a8\u753b\n    setupListAnimations();\n});\n\n// \u6ce2\u7eb9\u6548\u679c\nfunction setupRippleEffect() {\n    const buttons = document.querySelectorAll('.md-button');\n\n    buttons.forEach(button =&gt; {\n        button.addEventListener('click', function(e) {\n            const ripple = document.createElement('div');\n            ripple.className = 'ripple';\n\n            const rect = button.getBoundingClientRect();\n            const size = Math.max(rect.width, rect.height);\n\n            ripple.style.width = ripple.style.height = `${size}px`;\n            ripple.style.left = `${e.clientX - rect.left - size/2}px`;\n            ripple.style.top = `${e.clientY - rect.top - size/2}px`;\n\n            button.appendChild(ripple);\n\n            setTimeout(() =&gt; ripple.remove(), 600);\n        });\n    });\n}\n\n// \u5361\u7247\u60ac\u6d6e\u6548\u679c\nfunction setupCardHover() {\n    const cards = document.querySelectorAll('.md-card');\n\n    cards.forEach(card =&gt; {\n        card.addEventListener('mousemove', function(e) {\n            const rect = card.getBoundingClientRect();\n            const x = e.clientX - rect.left;\n            const y = e.clientY - rect.top;\n\n            const centerX = rect.width / 2;\n            const centerY = rect.height / 2;\n\n            const angleY = -(x - centerX) / 20;\n            const angleX = (y - centerY) / 20;\n\n            card.style.transform = \n                `perspective(1000px) rotateX(${angleX}deg) rotateY(${angleY}deg)`;\n        });\n\n        card.addEventListener('mouseleave', function() {\n            card.style.transform = 'perspective(1000px) rotateX(0) rotateY(0)';\n        });\n    });\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#633","title":"6.3.3 \u6570\u636e\u7edf\u8ba1","text":""},{"location":"Tools/Blog/Mkdocs_Material/#6331","title":"6.3.3.1 \u8bbf\u95ee\u7edf\u8ba1","text":"<ol> <li>\u57fa\u7840\u8bbf\u95ee\u7edf\u8ba1\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/analytics.js\nclass Analytics {\n    constructor() {\n        this.storageKey = 'site_analytics';\n        this.data = this.loadData();\n    }\n\n    loadData() {\n        const stored = localStorage.getItem(this.storageKey);\n        return stored ? JSON.parse(stored) : {\n            pageViews: {},\n            totalVisits: 0,\n            firstVisit: Date.now(),\n            lastVisit: Date.now()\n        };\n    }\n\n    saveData() {\n        localStorage.setItem(this.storageKey, JSON.stringify(this.data));\n    }\n\n    recordPageView() {\n        const path = window.location.pathname;\n        this.data.pageViews[path] = (this.data.pageViews[path] || 0) + 1;\n        this.data.totalVisits++;\n        this.data.lastVisit = Date.now();\n        this.saveData();\n    }\n\n    getStats() {\n        return {\n            totalVisits: this.data.totalVisits,\n            uniquePages: Object.keys(this.data.pageViews).length,\n            mostViewed: this.getMostViewedPages(5)\n        };\n    }\n\n    getMostViewedPages(limit = 5) {\n        return Object.entries(this.data.pageViews)\n            .sort(([,a], [,b]) =&gt; b - a)\n            .slice(0, limit);\n    }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6332","title":"6.3.3.2 \u9605\u8bfb\u65f6\u957f","text":"JavaScript<pre><code>// docs/javascripts/read-time.js\nclass ReadTimeTracker {\n    constructor() {\n        this.startTime = Date.now();\n        this.isReading = true;\n        this.totalTime = 0;\n        this.idleTimeout = null;\n        this.setupTracking();\n    }\n\n    setupTracking() {\n        // \u76d1\u542c\u7528\u6237\u6d3b\u52a8\n        ['mousemove', 'keydown', 'scroll', 'click'].forEach(event =&gt; {\n            document.addEventListener(event, () =&gt; this.handleActivity());\n        });\n\n        // \u9875\u9762\u5931\u7126\u6682\u505c\u8ba1\u65f6\n        document.addEventListener('visibilitychange', () =&gt; {\n            if (document.hidden) {\n                this.pauseTracking();\n            } else {\n                this.resumeTracking();\n            }\n        });\n    }\n\n    handleActivity() {\n        if (!this.isReading) {\n            this.resumeTracking();\n        }\n\n        clearTimeout(this.idleTimeout);\n        this.idleTimeout = setTimeout(() =&gt; this.pauseTracking(), 60000); // 1\u5206\u949f\u65e0\u6d3b\u52a8\u6682\u505c\n    }\n\n    pauseTracking() {\n        if (this.isReading) {\n            this.totalTime += Date.now() - this.startTime;\n            this.isReading = false;\n        }\n    }\n\n    resumeTracking() {\n        if (!this.isReading) {\n            this.startTime = Date.now();\n            this.isReading = true;\n        }\n    }\n\n    getReadTime() {\n        const currentTime = this.isReading ? \n            this.totalTime + (Date.now() - this.startTime) : \n            this.totalTime;\n\n        return Math.floor(currentTime / 1000 / 60); // \u8fd4\u56de\u5206\u949f\n    // \u663e\u793a\u9605\u8bfb\u65f6\u957f\n    displayReadTime() {\n        const readTimeElement = document.querySelector('.read-time');\n        if (readTimeElement) {\n            const minutes = this.getReadTime();\n            readTimeElement.textContent = `\u9605\u8bfb\u65f6\u957f: ${minutes} \u5206\u949f`;\n        }\n    }\n\n    // \u83b7\u53d6\u9605\u8bfb\u8fdb\u5ea6\n    getReadProgress() {\n        const windowHeight = window.innerHeight;\n        const docHeight = document.documentElement.scrollHeight - windowHeight;\n        const scrollTop = window.pageYOffset || document.documentElement.scrollTop;\n        return Math.min((scrollTop / docHeight) * 100, 100);\n    }\n\n    // \u4fdd\u5b58\u9605\u8bfb\u8bb0\u5f55\n    saveReadingHistory() {\n        const path = window.location.pathname;\n        const history = JSON.parse(localStorage.getItem('reading_history') || '{}');\n\n        history[path] = {\n            lastRead: Date.now(),\n            readTime: this.getReadTime(),\n            progress: this.getReadProgress()\n        };\n\n        localStorage.setItem('reading_history', JSON.stringify(history));\n    }\n}\n\n// \u521d\u59cb\u5316\u9605\u8bfb\u65f6\u957f\u8ffd\u8e2a\nconst readTracker = new ReadTimeTracker();\n\n// \u5b9a\u671f\u66f4\u65b0\u663e\u793a\nsetInterval(() =&gt; {\n    readTracker.displayReadTime();\n}, 30000); // \u6bcf30\u79d2\u66f4\u65b0\u4e00\u6b21\n\n// \u9875\u9762\u79bb\u5f00\u65f6\u4fdd\u5b58\u8bb0\u5f55\nwindow.addEventListener('beforeunload', () =&gt; {\n    readTracker.saveReadingHistory();\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#6333","title":"6.3.3.3 \u5206\u4eab\u7edf\u8ba1","text":"<ol> <li>\u5206\u4eab\u529f\u80fd\u548c\u7edf\u8ba1\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/share.js\nclass ShareTracker {\n    constructor() {\n        this.storageKey = 'share_statistics';\n        this.data = this.loadData();\n        this.setupShareButtons();\n    }\n\n    loadData() {\n        return JSON.parse(localStorage.getItem(this.storageKey) || '{}');\n    }\n\n    saveData() {\n        localStorage.setItem(this.storageKey, JSON.stringify(this.data));\n    }\n\n    setupShareButtons() {\n        const shareButtons = document.querySelectorAll('.share-button');\n\n        shareButtons.forEach(button =&gt; {\n            button.addEventListener('click', (e) =&gt; {\n                const platform = button.dataset.platform;\n                this.shareContent(platform);\n                this.recordShare(platform);\n            });\n        });\n    }\n\n    shareContent(platform) {\n        const url = encodeURIComponent(window.location.href);\n        const title = encodeURIComponent(document.title);\n        const description = encodeURIComponent(\n            document.querySelector('meta[name=\"description\"]')?.content || ''\n        );\n\n        let shareUrl;\n        switch (platform) {\n            case 'twitter':\n                shareUrl = `https://twitter.com/intent/tweet?url=${url}&amp;text=${title}`;\n                break;\n            case 'facebook':\n                shareUrl = `https://www.facebook.com/sharer/sharer.php?u=${url}`;\n                break;\n            case 'linkedin':\n                shareUrl = `https://www.linkedin.com/sharing/share-offsite/?url=${url}`;\n                break;\n            case 'weibo':\n                shareUrl = `http://service.weibo.com/share/share.php?url=${url}&amp;title=${title}`;\n                break;\n        }\n\n        if (shareUrl) {\n            window.open(shareUrl, '_blank', 'width=600,height=400');\n        }\n    }\n\n    recordShare(platform) {\n        const path = window.location.pathname;\n        if (!this.data[path]) {\n            this.data[path] = {};\n        }\n        if (!this.data[path][platform]) {\n            this.data[path][platform] = 0;\n        }\n        this.data[path][platform]++;\n        this.saveData();\n        this.updateShareCount(platform);\n    }\n\n    updateShareCount(platform) {\n        const countElement = document.querySelector(`.share-count[data-platform=\"${platform}\"]`);\n        if (countElement) {\n            const path = window.location.pathname;\n            countElement.textContent = this.data[path][platform] || 0;\n        }\n    }\n\n    getShareStats() {\n        return Object.entries(this.data).map(([path, platforms]) =&gt; ({\n            path,\n            total: Object.values(platforms).reduce((a, b) =&gt; a + b, 0),\n            platforms\n        }));\n    }\n\n    displayShareStats() {\n        const stats = this.getShareStats();\n        console.table(stats);\n        return stats;\n    }\n}\n</code></pre> <ol> <li>\u7edf\u8ba1\u6570\u636e\u53ef\u89c6\u5316\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/statistics-visualization.js\nclass StatisticsVisualizer {\n    constructor(analytics, readTracker, shareTracker) {\n        this.analytics = analytics;\n        this.readTracker = readTracker;\n        this.shareTracker = shareTracker;\n    }\n\n    createDashboard() {\n        const dashboard = document.createElement('div');\n        dashboard.className = 'statistics-dashboard';\n        dashboard.innerHTML = `\n            &lt;div class=\"dashboard-section\"&gt;\n                &lt;h3&gt;\u8bbf\u95ee\u7edf\u8ba1&lt;/h3&gt;\n                &lt;div class=\"stats-grid\"&gt;\n                    &lt;div class=\"stat-card\"&gt;\n                        &lt;div class=\"stat-value\"&gt;${this.analytics.data.totalVisits}&lt;/div&gt;\n                        &lt;div class=\"stat-label\"&gt;\u603b\u8bbf\u95ee\u91cf&lt;/div&gt;\n                    &lt;/div&gt;\n                    &lt;div class=\"stat-card\"&gt;\n                        &lt;div class=\"stat-value\"&gt;${this.readTracker.getReadTime()}&lt;/div&gt;\n                        &lt;div class=\"stat-label\"&gt;\u603b\u9605\u8bfb\u65f6\u957f(\u5206\u949f)&lt;/div&gt;\n                    &lt;/div&gt;\n                    &lt;div class=\"stat-card\"&gt;\n                        &lt;div class=\"stat-value\"&gt;${this.getTotalShares()}&lt;/div&gt;\n                        &lt;div class=\"stat-label\"&gt;\u603b\u5206\u4eab\u6b21\u6570&lt;/div&gt;\n                    &lt;/div&gt;\n                &lt;/div&gt;\n                &lt;div id=\"visitsChart\"&gt;&lt;/div&gt;\n            &lt;/div&gt;\n        `;\n\n        document.body.appendChild(dashboard);\n        this.renderCharts();\n    }\n\n    renderCharts() {\n        // \u4f7f\u7528 Chart.js \u7ed8\u5236\u56fe\u8868\n        const ctx = document.getElementById('visitsChart').getContext('2d');\n        new Chart(ctx, {\n            type: 'line',\n            data: {\n                labels: this.getTimeLabels(),\n                datasets: [{\n                    label: '\u8bbf\u95ee\u8d8b\u52bf',\n                    data: this.getVisitData(),\n                    borderColor: 'rgb(75, 192, 192)',\n                    tension: 0.1\n                }]\n            },\n            options: {\n                responsive: true,\n                scales: {\n                    y: {\n                        beginAtZero: true\n                    }\n                }\n            }\n        });\n    }\n\n    getTotalShares() {\n        const stats = this.shareTracker.getShareStats();\n        return stats.reduce((total, page) =&gt; total + page.total, 0);\n    }\n\n    getTimeLabels() {\n        // \u83b7\u53d6\u6700\u8fd17\u5929\u7684\u65e5\u671f\u6807\u7b7e\n        return Array.from({length: 7}, (_, i) =&gt; {\n            const d = new Date();\n            d.setDate(d.getDate() - i);\n            return d.toLocaleDateString();\n        }).reverse();\n    }\n\n    getVisitData() {\n        // \u5904\u7406\u8bbf\u95ee\u6570\u636e\n        return this.analytics.getVisitsByDate(7);\n    }\n}\n\n// \u6837\u5f0f\nconst styles = `\n    .statistics-dashboard {\n        padding: 2rem;\n        background: var(--md-default-bg-color);\n        border-radius: 8px;\n        box-shadow: var(--md-shadow-z2);\n    }\n\n    .stats-grid {\n        display: grid;\n        grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));\n        gap: 1rem;\n        margin: 1rem 0;\n    }\n\n    .stat-card {\n        padding: 1rem;\n        background: var(--md-code-bg-color);\n        border-radius: 4px;\n        text-align: center;\n    }\n\n    .stat-value {\n        font-size: 2rem;\n        font-weight: bold;\n        color: var(--md-primary-fg-color);\n    }\n\n    .stat-label {\n        font-size: 0.9rem;\n        color: var(--md-default-fg-color--light);\n        margin-top: 0.5rem;\n    }\n`;\n\n// \u5c06\u6837\u5f0f\u6dfb\u52a0\u5230\u6587\u6863\nconst styleSheet = document.createElement('style');\nstyleSheet.textContent = styles;\ndocument.head.appendChild(styleSheet);\n\n// \u521d\u59cb\u5316\u7edf\u8ba1\u53ef\u89c6\u5316\nconst visualizer = new StatisticsVisualizer(analytics, readTracker, shareTracker);\nvisualizer.createDashboard();\n</code></pre> <p>\u8fd9\u6837\u6211\u4eec\u5c31\u5b8c\u6210\u4e86\u5b8c\u6574\u7684\u6570\u636e\u7edf\u8ba1\u7cfb\u7edf\uff0c\u5305\u62ec\uff1a</p> <ol> <li>\u8bbf\u95ee\u7edf\u8ba1</li> <li>\u9605\u8bfb\u65f6\u957f\u8ffd\u8e2a</li> <li>\u5206\u4eab\u7edf\u8ba1</li> <li>\u6570\u636e\u53ef\u89c6\u5316\u5c55\u793a</li> </ol> <p>\u4f7f\u7528\u65f6\uff0c\u53ea\u9700\u8981\u5728 mkdocs.yml \u4e2d\u6dfb\u52a0\u76f8\u5e94\u7684 JavaScript \u6587\u4ef6\uff1a</p> YAML<pre><code>extra_javascript:\n  - javascripts/analytics.js\n  - javascripts/read-time.js\n  - javascripts/share.js\n  - javascripts/statistics-visualization.js\n  - https://cdn.jsdelivr.net/npm/chart.js\n</code></pre> <p>\u7136\u540e\u5728\u9875\u9762\u4e2d\u6dfb\u52a0\u5fc5\u8981\u7684 HTML \u5143\u7d20\u5373\u53ef\u542f\u7528\u8fd9\u4e9b\u529f\u80fd\u3002</p>"},{"location":"Tools/Blog/Mkdocs_Material/#7","title":"7 \u6a21\u677f\u590d\u5199","text":""},{"location":"Tools/Blog/Mkdocs_Material/#71","title":"7.1 \u91cd\u5199\u9875\u9762\u6a21\u677f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#711","title":"7.1.1 \u4e3b\u9875\u6a21\u677f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#7111","title":"7.1.1.1 \u5e03\u5c40\u7ed3\u6784","text":"<ol> <li>\u521b\u5efa\u81ea\u5b9a\u4e49\u4e3b\u9875\u6a21\u677f\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/main.html --&gt;\n{% extends \"base.html\" %}\n\n{% block hero %}\n&lt;section class=\"home-hero\"&gt;\n    &lt;div class=\"hero-content\"&gt;\n        &lt;h1&gt;{{ config.site_name }}&lt;/h1&gt;\n        &lt;p&gt;{{ config.site_description }}&lt;/p&gt;\n\n        &lt;!-- \u81ea\u5b9a\u4e49\u641c\u7d22\u6846 --&gt;\n        &lt;div class=\"hero-search\"&gt;\n            &lt;input type=\"text\" placeholder=\"\u641c\u7d22\u6587\u6863...\" id=\"hero-search-input\"&gt;\n            &lt;button&gt;\n                &lt;span class=\"twemoji\"&gt;\n                    {% include \".icons/material/magnify.svg\" %}\n                &lt;/span&gt;\n            &lt;/button&gt;\n        &lt;/div&gt;\n\n        &lt;!-- \u5feb\u901f\u5165\u53e3 --&gt;\n        &lt;div class=\"hero-buttons\"&gt;\n            &lt;a href=\"{{ page.next_page.url | url }}\" class=\"md-button md-button--primary\"&gt;\n                \u5feb\u901f\u5f00\u59cb\n                &lt;span class=\"twemoji\"&gt;\n                    {% include \".icons/material/arrow-right.svg\" %}\n                &lt;/span&gt;\n            &lt;/a&gt;\n            &lt;a href=\"{{ config.repo_url }}\" class=\"md-button\"&gt;\n                \u67e5\u770b\u6e90\u7801\n                &lt;span class=\"twemoji\"&gt;\n                    {% include \".icons/material/github.svg\" %}\n                &lt;/span&gt;\n            &lt;/a&gt;\n        &lt;/div&gt;\n    &lt;/div&gt;\n&lt;/section&gt;\n{% endblock %}\n\n{% block content %}\n&lt;section class=\"home-features\"&gt;\n    &lt;h2&gt;\u7279\u8272\u529f\u80fd&lt;/h2&gt;\n    &lt;div class=\"features-grid\"&gt;\n        &lt;!-- \u529f\u80fd\u5361\u7247 --&gt;\n        &lt;div class=\"feature-card\"&gt;\n            &lt;div class=\"feature-icon\"&gt;\n                {% include \".icons/material/speedometer.svg\" %}\n            &lt;/div&gt;\n            &lt;h3&gt;\u9ad8\u6027\u80fd&lt;/h3&gt;\n            &lt;p&gt;\u57fa\u4e8e\u9759\u6001\u7ad9\u70b9\u751f\u6210\uff0c\u52a0\u8f7d\u8fc5\u901f&lt;/p&gt;\n        &lt;/div&gt;\n        &lt;!-- \u66f4\u591a\u529f\u80fd\u5361\u7247 --&gt;\n    &lt;/div&gt;\n&lt;/section&gt;\n\n&lt;!-- \u6700\u8fd1\u66f4\u65b0 --&gt;\n&lt;section class=\"home-updates\"&gt;\n    &lt;h2&gt;\u6700\u8fd1\u66f4\u65b0&lt;/h2&gt;\n    &lt;div class=\"updates-list\"&gt;\n        {% for update in config.theme.updates[:5] %}\n        &lt;div class=\"update-item\"&gt;\n            &lt;span class=\"update-date\"&gt;{{ update.date }}&lt;/span&gt;\n            &lt;a href=\"{{ update.url | url }}\"&gt;{{ update.title }}&lt;/a&gt;\n        &lt;/div&gt;\n        {% endfor %}\n    &lt;/div&gt;\n&lt;/section&gt;\n{% endblock %}\n</code></pre> <ol> <li>\u4e3b\u9875\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/home.css */\n\n/* \u4e3b\u9875\u82f1\u96c4\u533a */\n.home-hero {\n    min-height: 100vh;\n    display: flex;\n    align-items: center;\n    justify-content: center;\n    text-align: center;\n    background: linear-gradient(\n        to bottom right,\n        var(--md-primary-fg-color),\n        var(--md-accent-fg-color)\n    );\n    color: var(--md-primary-bg-color);\n}\n\n.hero-content {\n    max-width: 800px;\n    padding: 2rem;\n}\n\n.hero-content h1 {\n    font-size: 3rem;\n    margin-bottom: 1rem;\n}\n\n/* \u641c\u7d22\u6846\u6837\u5f0f */\n.hero-search {\n    margin: 2rem 0;\n    position: relative;\n}\n\n.hero-search input {\n    width: 100%;\n    padding: 1rem 3rem 1rem 1rem;\n    border: none;\n    border-radius: 2rem;\n    background: rgba(255, 255, 255, 0.1);\n    color: white;\n    backdrop-filter: blur(10px);\n}\n\n/* \u529f\u80fd\u533a\u6837\u5f0f */\n.features-grid {\n    display: grid;\n    grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));\n    gap: 2rem;\n    padding: 2rem;\n}\n\n.feature-card {\n    padding: 2rem;\n    background: var(--md-default-bg-color);\n    border-radius: 8px;\n    box-shadow: var(--md-shadow-z1);\n    transition: transform 0.3s ease;\n}\n\n.feature-card:hover {\n    transform: translateY(-4px);\n}\n\n/* \u66f4\u65b0\u5217\u8868\u6837\u5f0f */\n.updates-list {\n    max-width: 800px;\n    margin: 0 auto;\n    padding: 2rem;\n}\n\n.update-item {\n    display: flex;\n    align-items: center;\n    padding: 1rem;\n    border-bottom: 1px solid var(--md-default-fg-color--lightest);\n}\n\n/* \u54cd\u5e94\u5f0f\u9002\u914d */\n@media screen and (max-width: 76.1875em) {\n    .hero-content h1 {\n        font-size: 2rem;\n    }\n\n    .features-grid {\n        grid-template-columns: 1fr;\n    }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#7112","title":"7.1.1.2 \u7ec4\u4ef6\u914d\u7f6e","text":"<ol> <li>\u5728 <code>mkdocs.yml</code> \u4e2d\u914d\u7f6e\u4e3b\u9898\uff1a</li> </ol> YAML<pre><code>theme:\n  name: material\n  custom_dir: docs/overrides\n  features:\n    - navigation.tabs\n    - navigation.sections\n    - navigation.expand\n\n  # \u4e3b\u9875\u914d\u7f6e\n  homepage:\n    hero:\n      title: \u7f51\u7ad9\u6807\u9898\n      subtitle: \u7f51\u7ad9\u63cf\u8ff0\n      image: assets/hero.svg\n\n    # \u529f\u80fd\u7279\u6027\n    features:\n      - title: \u9ad8\u6027\u80fd\n        description: \u57fa\u4e8e\u9759\u6001\u7ad9\u70b9\u751f\u6210\uff0c\u52a0\u8f7d\u8fc5\u901f\n        icon: material/speedometer\n      - title: \u6613\u4e8e\u4f7f\u7528\n        description: \u7b80\u5355\u7684\u914d\u7f6e\uff0c\u5feb\u901f\u4e0a\u624b\n        icon: material/puzzle\n      # \u66f4\u591a\u529f\u80fd\u7279\u6027...\n\n    # \u66f4\u65b0\u5217\u8868\n    updates:\n      - date: 2024-01-20\n        title: \u65b0\u589e\u529f\u80fdA\n        url: /new-feature-a\n      - date: 2024-01-18\n        title: \u95ee\u9898\u4fee\u590dB\n        url: /bug-fix-b\n      # \u66f4\u591a\u66f4\u65b0...\n</code></pre> <ol> <li>\u4e3b\u9875\u529f\u80fd\u7c7b\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/home.js\nclass HomePage {\n    constructor() {\n        this.searchInput = document.getElementById('hero-search-input');\n        this.setupSearch();\n        this.setupFeatureCards();\n    }\n\n    setupSearch() {\n        this.searchInput?.addEventListener('keyup', (e) =&gt; {\n            if (e.key === 'Enter') {\n                const query = e.target.value;\n                window.location.href = `${window.location.origin}/search.html?q=${encodeURIComponent(query)}`;\n            }\n        });\n    }\n\n    setupFeatureCards() {\n        const cards = document.querySelectorAll('.feature-card');\n\n        cards.forEach(card =&gt; {\n            card.addEventListener('mousemove', (e) =&gt; {\n                const rect = card.getBoundingClientRect();\n                const x = e.clientX - rect.left;\n                const y = e.clientY - rect.top;\n\n                card.style.setProperty('--mouse-x', `${x}px`);\n                card.style.setProperty('--mouse-y', `${y}px`);\n            });\n        });\n    }\n}\n\n// \u521d\u59cb\u5316\u4e3b\u9875\ndocument.addEventListener('DOMContentLoaded', () =&gt; {\n    new HomePage();\n});\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#7113","title":"7.1.1.3 \u81ea\u5b9a\u4e49\u533a\u57df","text":"<ol> <li>\u521b\u5efa\u81ea\u5b9a\u4e49\u533a\u57df\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/custom-content.html --&gt;\n{% if page.meta.custom_content %}\n&lt;section class=\"custom-content\"&gt;\n    &lt;!-- \u516c\u544a\u533a --&gt;\n    {% if page.meta.announcements %}\n    &lt;div class=\"announcements\"&gt;\n        {% for announcement in page.meta.announcements %}\n        &lt;div class=\"announcement-item\"&gt;\n            &lt;span class=\"announcement-tag\"&gt;{{ announcement.tag }}&lt;/span&gt;\n            &lt;p&gt;{{ announcement.content }}&lt;/p&gt;\n        &lt;/div&gt;\n        {% endfor %}\n    &lt;/div&gt;\n    {% endif %}\n\n    &lt;!-- \u8d21\u732e\u8005\u533a\u57df --&gt;\n    {% if page.meta.contributors %}\n    &lt;div class=\"contributors\"&gt;\n        &lt;h3&gt;\u9879\u76ee\u8d21\u732e\u8005&lt;/h3&gt;\n        &lt;div class=\"contributors-grid\"&gt;\n            {% for contributor in page.meta.contributors %}\n            &lt;a href=\"{{ contributor.url }}\" class=\"contributor-card\"&gt;\n                &lt;img src=\"{{ contributor.avatar }}\" alt=\"{{ contributor.name }}\"&gt;\n                &lt;span&gt;{{ contributor.name }}&lt;/span&gt;\n            &lt;/a&gt;\n            {% endfor %}\n        &lt;/div&gt;\n    &lt;/div&gt;\n    {% endif %}\n\n    &lt;!-- \u8d5e\u52a9\u5546\u533a\u57df --&gt;\n    {% if page.meta.sponsors %}\n    &lt;div class=\"sponsors\"&gt;\n        &lt;h3&gt;\u8d5e\u52a9\u5546&lt;/h3&gt;\n        &lt;div class=\"sponsors-grid\"&gt;\n            {% for sponsor in page.meta.sponsors %}\n            &lt;a href=\"{{ sponsor.url }}\" class=\"sponsor-card\"&gt;\n                &lt;img src=\"{{ sponsor.logo }}\" alt=\"{{ sponsor.name }}\"&gt;\n            &lt;/a&gt;\n            {% endfor %}\n        &lt;/div&gt;\n    &lt;/div&gt;\n    {% endif %}\n&lt;/section&gt;\n{% endif %}\n</code></pre> <ol> <li>\u81ea\u5b9a\u4e49\u533a\u57df\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/custom-content.css */\n\n/* \u516c\u544a\u533a\u57df */\n.announcements {\n    margin: 2rem 0;\n}\n\n.announcement-item {\n    padding: 1rem;\n    background: var(--md-code-bg-color);\n    border-radius: 4px;\n    margin-bottom: 1rem;\n}\n\n.announcement-tag {\n    display: inline-block;\n    padding: 0.2rem 0.5rem;\n    background: var(--md-accent-fg-color);\n    color: white;\n    border-radius: 2rem;\n    font-size: 0.8rem;\n    margin-right: 0.5rem;\n}\n\n/* \u8d21\u732e\u8005\u533a\u57df */\n.contributors-grid {\n    display: grid;\n    grid-template-columns: repeat(auto-fill, minmax(100px, 1fr));\n    gap: 1rem;\n    margin: 1rem 0;\n}\n\n.contributor-card {\n    text-align: center;\n    text-decoration: none;\n    color: var(--md-default-fg-color);\n}\n\n.contributor-card img {\n    width: 60px;\n    height: 60px;\n    border-radius: 50%;\n    margin-bottom: 0.5rem;\n}\n\n/* \u8d5e\u52a9\u5546\u533a\u57df */\n.sponsors-grid {\n    display: grid;\n    grid-template-columns: repeat(auto-fill, minmax(150px, 1fr));\n    gap: 2rem;\n    margin: 1rem 0;\n}\n\n.sponsor-card img {\n    width: 100%;\n    height: auto;\n    filter: grayscale(100%);\n    transition: filter 0.3s ease;\n}\n\n.sponsor-card:hover img {\n    filter: grayscale(0%);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#712","title":"7.1.2 \u6587\u7ae0\u6a21\u677f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#7121","title":"7.1.2.1 \u6587\u7ae0\u5934\u90e8","text":"HTML<pre><code>&lt;!-- docs/overrides/partials/article-header.html --&gt;\n&lt;header class=\"article-header\"&gt;\n    &lt;!-- \u6587\u7ae0\u6807\u9898 --&gt;\n    &lt;h1&gt;{{ page.title }}&lt;/h1&gt;\n\n    &lt;!-- \u6587\u7ae0\u5143\u4fe1\u606f --&gt;\n    &lt;div class=\"article-meta\"&gt;\n        {% if page.meta.author %}\n        &lt;div class=\"meta-item\"&gt;\n            &lt;span class=\"meta-icon\"&gt;\n                {% include \".icons/material/account.svg\" %}\n            &lt;/span&gt;\n            &lt;span&gt;{{ page.meta.author }}&lt;/span&gt;\n        &lt;/div&gt;\n        {% endif %}\n\n        {% if page.meta.date %}\n        &lt;div class=\"meta-item\"&gt;\n            &lt;span class=\"meta-icon\"&gt;\n                {% include \".icons/material/calendar.svg\" %}\n            &lt;/span&gt;\n            &lt;span&gt;{{ page.meta.date }}&lt;/span&gt;\n        &lt;/div&gt;\n        {% endif %}\n\n        {% if page.meta.tags %}\n        &lt;div class=\"article-tags\"&gt;\n            {% for tag in page.meta.tags %}\n            &lt;a href=\"{{ base_url }}/tags/#{{ tag }}\" class=\"tag\"&gt;\n                # {{ tag }}\n            &lt;/a&gt;\n            {% endfor %}\n        &lt;/div&gt;\n        {% endif %}\n    &lt;/div&gt;\n\n    &lt;!-- \u6587\u7ae0\u6982\u8ff0 --&gt;\n    {% if page.meta.description %}\n    &lt;div class=\"article-description\"&gt;\n        {{ page.meta.description }}\n    &lt;/div&gt;\n    {% endif %}\n&lt;/header&gt;\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#7122","title":"7.1.2.2 \u6b63\u6587\u6837\u5f0f","text":"CSS<pre><code>/* docs/stylesheets/article.css */\n\n/* \u6587\u7ae0\u5bb9\u5668 */\n.md-content article {\n    max-width: 800px;\n    margin: 0 auto;\n    padding: 2rem;\n}\n\n/* \u6587\u7ae0\u5934\u90e8 */\n.article-header {\n    margin-bottom: 3rem;\n    text-align: center;\n}\n\n.article-meta {\n    display: flex;\n    justify-content: center;\n    gap: 1rem;\n    margin: 1rem 0;\n    color: var(--md-default-fg-color--light);\n}\n\n.meta-item {\n    display: flex;\n    align-items: center;\n    gap: 0.5rem;\n}\n\n.article-tags {\n    margin-top: 1rem;\n}\n\n.tag {\n    display: inline-block;\n    padding: 0.2rem 0.5rem;\n    margin: 0.2rem;\n    background: var(--md-code-bg-color);\n    border-radius: 2rem;\n    color: var(--md-default-fg-color);\n    text-decoration: none;\n    font-size: 0.8rem;\n}\n\n/* \u6587\u7ae0\u5185\u5bb9\u6837\u5f0f */\n.md-content article {\n    font-size: 1.1rem;\n    line-height: 1.8;\n}\n\n/* \u6807\u9898\u6837\u5f0f */\n.md-content article h2 {\n    margin-top: 3rem;\n    padding-bottom: 0.5rem;\n    border-bottom: 2px solid var(--md-default-fg-color--lightest);\n}\n\n/* \u4ee3\u7801\u5757\u6837\u5f0f */\n.md-content pre {\n    border-radius: 8px;\n    margin: 1.5rem 0;\n}\n\n/* \u5f15\u7528\u6837\u5f0f */\n.md-content blockquote {\n    border-left: 4px solid var(--md-accent-fg-color);\n    padding: 1rem;\n    background: var(--md-code-bg-color);\n    margin: 1.5rem 0;\n}\n\n/* \u56fe\u7247\u6837\u5f0f */\n.md-content img {\n    max-width: 100%;\n    border-radius: 8px;\n    margin: 1.5rem 0;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#7123","title":"7.1.2.3 \u5e95\u90e8\u4fe1\u606f","text":"HTML<pre><code>&lt;!-- docs/overrides/partials/article-footer.html --&gt;\n&lt;footer class=\"article-footer\"&gt;\n    &lt;!-- \u6587\u7ae0\u5bfc\u822a --&gt;\n    &lt;nav class=\"article-nav\"&gt;\n        {% if page.previous_page %}\n        &lt;a href=\"{{ page.previous_page.url | url }}\" class=\"nav-link nav-prev\"&gt;\n            &lt;span class=\"nav-icon\"&gt;\n                {% include \".icons/material/arrow-left.svg\" %}\n            &lt;/span&gt;\n            &lt;span class=\"nav-text\"&gt;\n                &lt;span class=\"nav-direction\"&gt;\u4e0a\u4e00\u7bc7&lt;/span&gt;\n                &lt;span class=\"nav-title\"&gt;{{ page.previous_page.title }}&lt;/span&gt;\n            &lt;/span&gt;\n        &lt;/a&gt;\n        {% endif %}\n\n        {% if page.next_page %}\n        &lt;a href=\"{{ page.next_page.url | url }}\" class=\"nav-link nav-next\"&gt;\n            &lt;span class=\"nav-text\"&gt;\n                &lt;span class=\"nav-direction\"&gt;\u4e0b\u4e00\u7bc7&lt;/span&gt;\n                &lt;span class=\"nav-title\"&gt;{{ page.next_page.title }}&lt;/span&gt;\n            &lt;/span&gt;\n            &lt;span class=\"nav-icon\"&gt;\n                {% include \".icons/material/arrow-right.svg\" %}\n            &lt;/span&gt;\n        &lt;/a&gt;\n        {% endif %}\n    &lt;/nav&gt;\n\n    &lt;!-- \u5206\u4eab\u6309\u94ae --&gt;\n    &lt;div class=\"article-share\"&gt;\n        &lt;h4&gt;\u5206\u4eab\u6587\u7ae0&lt;/h4&gt;\n        &lt;div class=\"share-buttons\"&gt;\n            &lt;button class=\"share-button\" data-platform=\"twitter\"&gt;\n                {% include \".icons/material/twitter.svg\" %}\n            &lt;/button&gt;\n            &lt;button class=\"share-button\" data-platform=\"facebook\"&gt;\n                {% include \".icons/material/facebook.svg\" %}\n            &lt;/button&gt;\n            &lt;button class=\"share-button\" data-platform=\"linkedin\"&gt;\n                {% include \".icons/material/linkedin.svg\" %}\n            &lt;/button&gt;\n            &lt;button class=\"share-button\" data-platform=\"weibo\"&gt;\n                {% include \".icons/material/sina-weibo.svg\" %}\n            &lt;/button&gt;\n        &lt;/div&gt;\n    &lt;/div&gt;\n\n    &lt;!-- \u76f8\u5173\u6587\u7ae0 --&gt;\n    {% if page.meta.related_posts %}\n    &lt;div class=\"related-posts\"&gt;\n        &lt;h4&gt;\u76f8\u5173\u6587\u7ae0&lt;/h4&gt;\n        &lt;div class=\"related-grid\"&gt;\n            {% for post in page.meta.related_posts %}\n            &lt;a href=\"{{ post.url | url }}\" class=\"related-post\"&gt;\n                {% if post.image %}\n                &lt;img src=\"{{ post.image }}\" alt=\"{{ post.title }}\"&gt;\n                {% endif %}\n                &lt;h5&gt;{{ post.title }}&lt;/h5&gt;\n                &lt;p&gt;{{ post.excerpt }}&lt;/p&gt;\n            &lt;/a&gt;\n            {% endfor %}\n        &lt;/div&gt;\n    &lt;/div&gt;\n    {% endif %}\n\n    &lt;!-- \u8bc4\u8bba\u533a --&gt;\n    &lt;div class=\"article-comments\"&gt;\n        &lt;h4&gt;\u8bc4\u8bba&lt;/h4&gt;\n        {% if config.extra.comments.provider == 'giscus' %}\n        &lt;script src=\"https://giscus.app/client.js\"\n            data-repo=\"{{ config.extra.comments.repo }}\"\n            data-repo-id=\"{{ config.extra.comments.repo_id }}\"\n            data-category=\"{{ config.extra.comments.category }}\"\n            data-category-id=\"{{ config.extra.comments.category_id }}\"\n            data-mapping=\"pathname\"\n            data-reactions-enabled=\"1\"\n            data-emit-metadata=\"0\"\n            data-theme=\"light\"\n            crossorigin=\"anonymous\"\n            async&gt;\n        &lt;/script&gt;\n        {% endif %}\n    &lt;/div&gt;\n&lt;/footer&gt;\n\n&lt;!-- \u6587\u7ae0\u5e95\u90e8\u6837\u5f0f --&gt;\n&lt;style&gt;\n.article-footer {\n    margin-top: 4rem;\n    padding-top: 2rem;\n    border-top: 1px solid var(--md-default-fg-color--lightest);\n}\n\n/* \u6587\u7ae0\u5bfc\u822a */\n.article-nav {\n    display: flex;\n    justify-content: space-between;\n    margin-bottom: 2rem;\n}\n\n.nav-link {\n    display: flex;\n    align-items: center;\n    padding: 1rem;\n    text-decoration: none;\n    color: var(--md-default-fg-color);\n    background: var(--md-code-bg-color);\n    border-radius: 8px;\n    transition: transform 0.2s ease;\n    max-width: 45%;\n}\n\n.nav-link:hover {\n    transform: translateY(-2px);\n}\n\n.nav-text {\n    display: flex;\n    flex-direction: column;\n}\n\n.nav-direction {\n    font-size: 0.8rem;\n    color: var(--md-default-fg-color--light);\n}\n\n.nav-title {\n    font-weight: 500;\n}\n\n/* \u5206\u4eab\u6309\u94ae */\n.share-buttons {\n    display: flex;\n    gap: 1rem;\n    margin: 1rem 0;\n}\n\n.share-button {\n    padding: 0.8rem;\n    border: none;\n    border-radius: 50%;\n    background: var(--md-code-bg-color);\n    cursor: pointer;\n    transition: all 0.2s ease;\n}\n\n.share-button:hover {\n    background: var(--md-accent-fg-color);\n    color: white;\n}\n\n/* \u76f8\u5173\u6587\u7ae0 */\n.related-grid {\n    display: grid;\n    grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));\n    gap: 1.5rem;\n    margin: 1rem 0;\n}\n\n.related-post {\n    text-decoration: none;\n    color: var(--md-default-fg-color);\n    background: var(--md-code-bg-color);\n    border-radius: 8px;\n    overflow: hidden;\n    transition: transform 0.2s ease;\n}\n\n.related-post:hover {\n    transform: translateY(-4px);\n}\n\n.related-post img {\n    width: 100%;\n    height: 150px;\n    object-fit: cover;\n}\n\n.related-post h5 {\n    margin: 1rem;\n    font-size: 1.1rem;\n}\n\n.related-post p {\n    margin: 0 1rem 1rem;\n    font-size: 0.9rem;\n    color: var(--md-default-fg-color--light);\n}\n\n/* \u8bc4\u8bba\u533a */\n.article-comments {\n    margin-top: 3rem;\n}\n\n/* \u54cd\u5e94\u5f0f\u9002\u914d */\n@media screen and (max-width: 76.1875em) {\n    .article-nav {\n        flex-direction: column;\n        gap: 1rem;\n    }\n\n    .nav-link {\n        max-width: 100%;\n    }\n\n    .related-grid {\n        grid-template-columns: 1fr;\n    }\n}\n&lt;/style&gt;\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#713-404","title":"7.1.3 404\u9875\u9762","text":""},{"location":"Tools/Blog/Mkdocs_Material/#7131","title":"7.1.3.1 \u9519\u8bef\u63d0\u793a","text":"HTML<pre><code>&lt;!-- docs/overrides/404.html --&gt;\n{% extends \"base.html\" %}\n\n{% block content %}\n&lt;div class=\"error-page\"&gt;\n    &lt;div class=\"error-content\"&gt;\n        &lt;!-- 404 \u56fe\u6807 --&gt;\n        &lt;div class=\"error-icon\"&gt;\n            {% include \".icons/material/alert-circle-outline.svg\" %}\n            &lt;span class=\"error-code\"&gt;404&lt;/span&gt;\n        &lt;/div&gt;\n\n        &lt;!-- \u9519\u8bef\u4fe1\u606f --&gt;\n        &lt;h1&gt;\u9875\u9762\u672a\u627e\u5230&lt;/h1&gt;\n        &lt;p&gt;\u62b1\u6b49\uff0c\u60a8\u8bbf\u95ee\u7684\u9875\u9762\u4e0d\u5b58\u5728\u6216\u5df2\u88ab\u79fb\u52a8&lt;/p&gt;\n\n        &lt;!-- \u641c\u7d22\u6846 --&gt;\n        &lt;div class=\"error-search\"&gt;\n            &lt;input type=\"text\" \n                   id=\"error-search-input\" \n                   placeholder=\"\u5c1d\u8bd5\u641c\u7d22...\"\n                   autocomplete=\"off\"&gt;\n            &lt;button id=\"error-search-button\"&gt;\n                {% include \".icons/material/magnify.svg\" %}\n            &lt;/button&gt;\n        &lt;/div&gt;\n\n        &lt;!-- \u5feb\u6377\u64cd\u4f5c --&gt;\n        &lt;div class=\"error-actions\"&gt;\n            &lt;a href=\"{{ base_url }}\" class=\"md-button md-button--primary\"&gt;\n                \u8fd4\u56de\u9996\u9875\n            &lt;/a&gt;\n            &lt;button class=\"md-button\" onclick=\"window.history.back()\"&gt;\n                \u8fd4\u56de\u4e0a\u9875\n            &lt;/button&gt;\n        &lt;/div&gt;\n    &lt;/div&gt;\n\n    &lt;!-- \u641c\u7d22\u5efa\u8bae --&gt;\n    &lt;div class=\"search-suggestions\" id=\"search-suggestions\"&gt;\n        &lt;h3&gt;\u60a8\u662f\u5426\u5728\u627e\uff1a&lt;/h3&gt;\n        &lt;div class=\"suggestions-list\" id=\"suggestions-list\"&gt;\n            &lt;!-- \u52a8\u6001\u751f\u6210\u7684\u5efa\u8bae\u5217\u8868 --&gt;\n        &lt;/div&gt;\n    &lt;/div&gt;\n&lt;/div&gt;\n\n&lt;!-- 404\u9875\u9762\u6837\u5f0f --&gt;\n&lt;style&gt;\n.error-page {\n    min-height: 100vh;\n    display: flex;\n    flex-direction: column;\n    align-items: center;\n    justify-content: center;\n    padding: 2rem;\n    text-align: center;\n}\n\n.error-content {\n    max-width: 600px;\n}\n\n.error-icon {\n    font-size: 6rem;\n    color: var(--md-primary-fg-color);\n    margin-bottom: 2rem;\n    position: relative;\n}\n\n.error-code {\n    position: absolute;\n    bottom: -1rem;\n    right: -1rem;\n    font-size: 2rem;\n    font-weight: bold;\n    background: var(--md-accent-fg-color);\n    color: white;\n    padding: 0.5rem 1rem;\n    border-radius: 1rem;\n}\n\n.error-search {\n    margin: 2rem 0;\n    position: relative;\n}\n\n.error-search input {\n    width: 100%;\n    padding: 1rem 3rem 1rem 1rem;\n    border: 2px solid var(--md-default-fg-color--lightest);\n    border-radius: 2rem;\n    font-size: 1.1rem;\n}\n\n.error-search button {\n    position: absolute;\n    right: 0.5rem;\n    top: 50%;\n    transform: translateY(-50%);\n    background: none;\n    border: none;\n    color: var(--md-default-fg-color);\n    cursor: pointer;\n}\n\n.error-actions {\n    display: flex;\n    gap: 1rem;\n    justify-content: center;\n    margin: 2rem 0;\n}\n\n/* \u641c\u7d22\u5efa\u8bae\u6837\u5f0f */\n.search-suggestions {\n    margin-top: 3rem;\n    width: 100%;\n    max-width: 600px;\n}\n\n.suggestions-list {\n    margin-top: 1rem;\n}\n\n.suggestion-item {\n    padding: 1rem;\n    margin: 0.5rem 0;\n    background: var(--md-code-bg-color);\n    border-radius: 8px;\n    cursor: pointer;\n    transition: all 0.2s ease;\n}\n\n.suggestion-item:hover {\n    background: var(--md-accent-fg-color--transparent);\n}\n\n/* \u54cd\u5e94\u5f0f\u9002\u914d */\n@media screen and (max-width: 76.1875em) {\n    .error-icon {\n        font-size: 4rem;\n    }\n\n    .error-code {\n        font-size: 1.5rem;\n    }\n\n    .error-actions {\n        flex-direction: column;\n    }\n}\n&lt;/style&gt;\n\n&lt;!-- 404\u9875\u9762\u811a\u672c --&gt;\n&lt;script&gt;\ndocument.addEventListener('DOMContentLoaded', function() {\n    // \u641c\u7d22\u5efa\u8bae\u529f\u80fd\n    setupSearchSuggestions();\n    // \u5168\u5c40\u70ed\u952e\n    setupHotkeys();\n});\n\nfunction setupSearchSuggestions() {\n    const searchInput = document.getElementById('error-search-input');\n    const suggestionsList = document.getElementById('suggestions-list');\n\n    searchInput?.addEventListener('input', debounce(async (e) =&gt; {\n        const query = e.target.value;\n        if (query.length &lt; 2) {\n            suggestionsList.innerHTML = '';\n            return;\n        }\n\n        // \u83b7\u53d6\u641c\u7d22\u5efa\u8bae\n        const suggestions = await getSearchSuggestions(query);\n\n        // \u6e32\u67d3\u5efa\u8bae\u5217\u8868\n        suggestionsList.innerHTML = suggestions\n            .map(suggestion =&gt; `\n                &lt;div class=\"suggestion-item\" onclick=\"window.location.href='${suggestion.url}'\"&gt;\n                    &lt;div class=\"suggestion-title\"&gt;${suggestion.title}&lt;/div&gt;\n                    &lt;div class=\"suggestion-excerpt\"&gt;${suggestion.excerpt}&lt;/div&gt;\n                &lt;/div&gt;\n            `)\n            .join('');\n    }, 300));\n}\n\nasync function getSearchSuggestions(query) {\n    // \u8fd9\u91cc\u53ef\u4ee5\u5b9e\u73b0\u5b9e\u9645\u7684\u641c\u7d22\u903b\u8f91\n    // \u793a\u4f8b\u8fd4\u56de\u6570\u636e\n    return [\n        {\n            title: '\u76f8\u5173\u6587\u6863 1',\n            excerpt: '\u8fd9\u662f\u4e00\u6bb5\u76f8\u5173\u7684\u6587\u6863\u63cf\u8ff0...',\n            url: '#'\n        },\n        {\n            title: '\u76f8\u5173\u6587\u6863 2',\n            excerpt: '\u8fd9\u662f\u53e6\u4e00\u6bb5\u76f8\u5173\u7684\u6587\u6863\u63cf\u8ff0...',\n            url: '#'\n        }\n    ];\n}\n\nfunction setupHotkeys() {\n    document.addEventListener('keydown', (e) =&gt; {\n        // \u6309 ESC \u8fd4\u56de\u4e0a\u9875\n        if (e.key === 'Escape') {\n            window.history.back();\n        }\n\n        // \u6309 Enter \u6267\u884c\u641c\u7d22\n        if (e.key === 'Enter' &amp;&amp; document.activeElement.id === 'error-search-input') {\n            const query = document.activeElement.value;\n            if (query) {\n                window.location.href = `${window.location.origin}/search.html?q=${encodeURIComponent(query)}`;\n            }\n        }\n    });\n}\n\n// \u9632\u6296\u51fd\u6570\nfunction debounce(fn, delay) {\n    let timer = null;\n    return function(...args) {\n        clearTimeout(timer);\n        timer = setTimeout(() =&gt; fn.apply(this, args), delay);\n    };\n}\n&lt;/script&gt;\n</code></pre> <p>\u8fd9\u6837\uff0c\u6211\u4eec\u5c31\u5b8c\u6210\u4e86\u6587\u7ae0\u5e95\u90e8\u4fe1\u606f\u548c404\u9875\u9762\u7684\u6a21\u677f\u3002\u4e3b\u8981\u7279\u70b9\u5305\u62ec\uff1a</p> <ol> <li> <p>\u6587\u7ae0\u5e95\u90e8\uff1a - \u6e05\u6670\u7684\u4e0a\u4e0b\u6587\u7ae0\u5bfc\u822a - \u793e\u4ea4\u5206\u4eab\u6309\u94ae - \u76f8\u5173\u6587\u7ae0\u63a8\u8350 - \u96c6\u6210\u8bc4\u8bba\u7cfb\u7edf</p> </li> <li> <p>404\u9875\u9762\uff1a - \u53cb\u597d\u7684\u9519\u8bef\u63d0\u793a - \u5b9e\u65f6\u641c\u7d22\u5efa\u8bae - \u591a\u79cd\u8fd4\u56de\u9009\u9879 - \u952e\u76d8\u5feb\u6377\u952e\u652f\u6301</p> </li> </ol> <p>\u4f7f\u7528\u8fd9\u4e9b\u6a21\u677f\u65f6\uff0c\u9700\u8981\u5728 <code>mkdocs.yml</code> \u4e2d\u6dfb\u52a0\u76f8\u5e94\u7684\u914d\u7f6e\uff1a</p> YAML<pre><code>theme:\n  name: material\n  custom_dir: docs/overrides\n  features:\n    - navigation.tracking\n    - search.suggest\n    - search.highlight\n\nextra:\n  comments:\n    provider: giscus\n    repo: username/repo\n    repo_id: your-repo-id\n    category: Comments\n    category_id: your-category-id\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#72","title":"7.2 \u4fee\u6539\u7ec4\u4ef6\u6a21\u677f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#721","title":"7.2.1 \u5bfc\u822a\u680f","text":""},{"location":"Tools/Blog/Mkdocs_Material/#7211","title":"7.2.1.1 \u5bfc\u822a\u9879\u5b9a\u5236","text":"HTML<pre><code>&lt;!-- docs/overrides/partials/nav.html --&gt;\n{% extends \"base.html\" %}\n\n{% block site_nav %}\n&lt;nav class=\"md-nav md-nav--primary\"&gt;\n    &lt;!-- \u81ea\u5b9a\u4e49\u5bfc\u822a\u5934\u90e8 --&gt;\n    &lt;div class=\"nav-header\"&gt;\n        {% if config.theme.logo %}\n        &lt;img src=\"{{ config.theme.logo }}\" alt=\"logo\" class=\"nav-logo\"&gt;\n        {% endif %}\n        &lt;span class=\"nav-title\"&gt;{{ config.site_name }}&lt;/span&gt;\n    &lt;/div&gt;\n\n    &lt;!-- \u81ea\u5b9a\u4e49\u5bfc\u822a\u9879 --&gt;\n    &lt;ul class=\"nav-items\"&gt;\n        {% for nav_item in nav %}\n        {% include \"partials/nav-item.html\" %}\n        {% endfor %}\n\n        &lt;!-- \u6dfb\u52a0\u81ea\u5b9a\u4e49\u5bfc\u822a\u9879 --&gt;\n        {% if config.extra.nav_links %}\n        {% for link in config.extra.nav_links %}\n        &lt;li class=\"nav-item custom\"&gt;\n            &lt;a href=\"{{ link.url }}\" class=\"nav-link\" {% if link.target %}target=\"{{ link.target }}\"{% endif %}&gt;\n                {% if link.icon %}\n                &lt;span class=\"nav-icon\"&gt;\n                    {% include \".icons/\" ~ link.icon ~ \".svg\" %}\n                &lt;/span&gt;\n                {% endif %}\n                {{ link.title }}\n            &lt;/a&gt;\n        &lt;/li&gt;\n        {% endfor %}\n        {% endif %}\n    &lt;/ul&gt;\n&lt;/nav&gt;\n</code></pre> <p>\u914d\u7f6e\u548c\u6837\u5f0f\uff1a</p> YAML<pre><code># mkdocs.yml\nextra:\n  nav_links:\n    - title: GitHub\n      url: https://github.com/your/repo\n      icon: material/github\n      target: _blank\n    - title: \u6587\u6863\n      url: /docs/\n      icon: material/file-document\n</code></pre> CSS<pre><code>/* docs/stylesheets/nav.css */\n.nav-header {\n    display: flex;\n    align-items: center;\n    padding: 1rem;\n    border-bottom: 1px solid var(--md-default-fg-color--lightest);\n}\n\n.nav-logo {\n    width: 32px;\n    height: 32px;\n    margin-right: 0.8rem;\n}\n\n.nav-items {\n    list-style: none;\n    padding: 0;\n    margin: 0;\n}\n\n.nav-item {\n    margin: 0.2rem 0;\n}\n\n.nav-link {\n    display: flex;\n    align-items: center;\n    padding: 0.8rem 1rem;\n    color: var(--md-default-fg-color);\n    text-decoration: none;\n    transition: background-color 0.2s ease;\n}\n\n.nav-link:hover {\n    background-color: var(--md-code-bg-color);\n}\n\n.nav-icon {\n    margin-right: 0.8rem;\n    width: 1.2rem;\n    height: 1.2rem;\n}\n\n/* \u81ea\u5b9a\u4e49\u5bfc\u822a\u9879\u6837\u5f0f */\n.nav-item.custom .nav-link {\n    color: var(--md-accent-fg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#7212","title":"7.2.1.2 \u641c\u7d22\u6846\u4f4d\u7f6e","text":"HTML<pre><code>&lt;!-- docs/overrides/partials/search.html --&gt;\n{% block search_box %}\n&lt;div class=\"md-search\" data-md-component=\"search\" role=\"dialog\"&gt;\n    &lt;label class=\"md-search__overlay\" for=\"__search\"&gt;&lt;/label&gt;\n    &lt;div class=\"md-search__inner\" role=\"search\"&gt;\n        &lt;!-- \u641c\u7d22\u8f93\u5165\u6846 --&gt;\n        &lt;form class=\"md-search__form\"&gt;\n            &lt;input\n                type=\"text\"\n                class=\"md-search__input\"\n                name=\"query\"\n                aria-label=\"\u641c\u7d22\"\n                placeholder=\"\u641c\u7d22\u6587\u6863...\"\n                autocapitalize=\"off\"\n                autocomplete=\"off\"\n                autocorrect=\"off\"\n                spellcheck=\"false\"\n                data-md-component=\"search-query\"\n            &gt;\n            &lt;!-- \u641c\u7d22\u5feb\u6377\u952e\u63d0\u793a --&gt;\n            &lt;div class=\"md-search__shortcuts\"&gt;\n                &lt;kbd&gt;Ctrl&lt;/kbd&gt; + &lt;kbd&gt;K&lt;/kbd&gt;\n            &lt;/div&gt;\n        &lt;/form&gt;\n\n        &lt;!-- \u641c\u7d22\u7ed3\u679c --&gt;\n        &lt;div class=\"md-search__output\"&gt;\n            &lt;div class=\"md-search__scrollwrap\" data-md-scrollfix&gt;\n                &lt;div class=\"md-search-result\" data-md-component=\"search-result\"&gt;\n                    &lt;div class=\"md-search-result__meta\"&gt;\n                        \u6b63\u5728\u641c\u7d22...\n                    &lt;/div&gt;\n                    &lt;ol class=\"md-search-result__list\"&gt;&lt;/ol&gt;\n                &lt;/div&gt;\n            &lt;/div&gt;\n        &lt;/div&gt;\n    &lt;/div&gt;\n&lt;/div&gt;\n</code></pre> <p>\u6837\u5f0f\u5b9a\u5236\uff1a</p> CSS<pre><code>/* docs/stylesheets/search.css */\n/* \u641c\u7d22\u6846\u5bb9\u5668 */\n.md-search {\n    margin: 0 1rem;\n    padding: 0;\n    position: relative;\n}\n\n/* \u641c\u7d22\u8f93\u5165\u6846 */\n.md-search__input {\n    width: 100%;\n    height: 2.4rem;\n    padding: 0 2.4rem;\n    font-size: 0.9rem;\n    color: var(--md-default-fg-color);\n    background-color: var(--md-default-bg-color);\n    border: 1px solid var(--md-default-fg-color--lightest);\n    border-radius: 1.2rem;\n}\n\n/* \u641c\u7d22\u56fe\u6807 */\n.md-search__icon {\n    position: absolute;\n    left: 0.8rem;\n    top: 50%;\n    transform: translateY(-50%);\n    color: var(--md-default-fg-color--light);\n}\n\n/* \u5feb\u6377\u952e\u63d0\u793a */\n.md-search__shortcuts {\n    position: absolute;\n    right: 0.8rem;\n    top: 50%;\n    transform: translateY(-50%);\n    display: flex;\n    gap: 0.2rem;\n    color: var(--md-default-fg-color--light);\n}\n\n/* \u641c\u7d22\u7ed3\u679c\u5bb9\u5668 */\n.md-search__output {\n    position: absolute;\n    top: 100%;\n    width: 100%;\n    margin-top: 0.4rem;\n    background-color: var(--md-default-bg-color);\n    border-radius: 0.2rem;\n    box-shadow: var(--md-shadow-z2);\n    overflow: auto;\n    z-index: 1;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#7213","title":"7.2.1.3 \u79fb\u52a8\u7aef\u9002\u914d","text":"CSS<pre><code>/* \u79fb\u52a8\u7aef\u5bfc\u822a\u6837\u5f0f */\n@media screen and (max-width: 76.1875em) {\n    /* \u5bfc\u822a\u5207\u6362\u6309\u94ae */\n    .md-header-nav__button.md-icon {\n        padding: 0.4rem;\n        margin: 0.4rem;\n    }\n\n    /* \u5bfc\u822a\u62bd\u5c49 */\n    .md-nav--primary {\n        position: fixed;\n        top: 0;\n        left: -18rem;\n        width: 18rem;\n        height: 100%;\n        background-color: var(--md-default-bg-color);\n        transition: left 0.25s;\n        z-index: 2;\n    }\n\n    /* \u5bfc\u822a\u62bd\u5c49\u6253\u5f00\u72b6\u6001 */\n    .md-nav--primary.md-nav--opened {\n        left: 0;\n    }\n\n    /* \u641c\u7d22\u6846\u5168\u5c4f */\n    .md-search__inner {\n        position: fixed;\n        top: 0;\n        left: 0;\n        width: 100%;\n        height: 100%;\n        padding: 1rem;\n        background-color: var(--md-default-bg-color);\n        z-index: 3;\n    }\n\n    /* \u641c\u7d22\u7ed3\u679c\u5168\u5c4f */\n    .md-search__output {\n        position: fixed;\n        top: 4rem;\n        height: calc(100% - 4rem);\n    }\n}\n\n/* \u5e73\u677f\u9002\u914d */\n@media screen and (min-width: 76.25em) and (max-width: 96.25em) {\n    .md-nav--primary {\n        width: 16rem;\n    }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#722","title":"7.2.2 \u9875\u811a","text":"HTML<pre><code>&lt;!-- docs/overrides/partials/footer.html --&gt;\n&lt;footer class=\"md-footer\"&gt;\n    &lt;div class=\"md-footer-meta md-typeset\"&gt;\n        &lt;div class=\"md-footer-meta__inner md-grid\"&gt;\n            &lt;!-- \u7248\u6743\u4fe1\u606f --&gt;\n            &lt;div class=\"md-footer-copyright\"&gt;\n                {% if config.copyright %}\n                &lt;div class=\"md-footer-copyright__highlight\"&gt;\n                    {{ config.copyright }}\n                &lt;/div&gt;\n                {% endif %}\n\n                &lt;!-- \u6784\u5efa\u4fe1\u606f --&gt;\n                &lt;div class=\"md-footer-build\"&gt;\n                    Documentation built with\n                    &lt;a href=\"https://www.mkdocs.org\" target=\"_blank\" rel=\"noopener\"&gt;\n                        MkDocs\n                    &lt;/a&gt;\n                    and\n                    &lt;a href=\"https://squidfunk.github.io/mkdocs-material/\" target=\"_blank\" rel=\"noopener\"&gt;\n                        Material for MkDocs\n                    &lt;/a&gt;\n                &lt;/div&gt;\n            &lt;/div&gt;\n\n            &lt;!-- \u793e\u4ea4\u94fe\u63a5 --&gt;\n            {% if config.extra.social %}\n            &lt;div class=\"md-footer-social\"&gt;\n                {% for social in config.extra.social %}\n                &lt;a href=\"{{ social.link }}\" \n                   target=\"_blank\" \n                   rel=\"noopener\" \n                   title=\"{{ social.name }}\"\n                   class=\"md-footer-social__link\"&gt;\n                    {% include \".icons/\" ~ social.icon ~ \".svg\" %}\n                &lt;/a&gt;\n                {% endfor %}\n            &lt;/div&gt;\n            {% endif %}\n\n            &lt;!-- \u5907\u6848\u4fe1\u606f --&gt;\n            {% if config.extra.icp %}\n            &lt;div class=\"md-footer-icp\"&gt;\n                &lt;a href=\"https://beian.miit.gov.cn/\" target=\"_blank\" rel=\"noopener\"&gt;\n                    {{ config.extra.icp }}\n                &lt;/a&gt;\n            &lt;/div&gt;\n            {% endif %}\n        &lt;/div&gt;\n    &lt;/div&gt;\n&lt;/footer&gt;\n</code></pre> <p>\u914d\u7f6e\uff1a</p> YAML<pre><code># mkdocs.yml\ncopyright: Copyright &amp;copy; 2024 Your Name\nextra:\n  social:\n    - icon: material/github\n      name: GitHub\n      link: https://github.com/your-username\n    - icon: material/twitter\n      name: Twitter\n      link: https://twitter.com/your-username\n  icp: \u4eacICP\u5907xxxxxxxx\u53f7\n</code></pre> <p>\u6837\u5f0f\uff1a</p> CSS<pre><code>/* docs/stylesheets/footer.css */\n.md-footer {\n    background-color: var(--md-default-bg-color);\n    color: var(--md-default-fg-color);\n    padding: 2rem 0;\n    border-top: 1px solid var(--md-default-fg-color--lightest);\n}\n\n.md-footer-meta__inner {\n    display: flex;\n    flex-wrap: wrap;\n    justify-content: space-between;\n    align-items: center;\n    gap: 1rem;\n}\n\n/* \u7248\u6743\u4fe1\u606f */\n.md-footer-copyright {\n    font-size: 0.8rem;\n}\n\n.md-footer-copyright__highlight {\n    margin-bottom: 0.5rem;\n}\n\n.md-footer-build {\n    color: var(--md-default-fg-color--light);\n}\n\n/* \u793e\u4ea4\u94fe\u63a5 */\n.md-footer-social {\n    display: flex;\n    gap: 1rem;\n}\n\n.md-footer-social__link {\n    width: 2rem;\n    height: 2rem;\n    display: flex;\n    align-items: center;\n    justify-content: center;\n    color: var(--md-default-fg-color);\n    border-radius: 50%;\n    transition: all 0.2s ease;\n}\n\n.md-footer-social__link:hover {\n    background-color: var(--md-code-bg-color);\n    color: var(--md-accent-fg-color);\n}\n\n/* \u5907\u6848\u4fe1\u606f */\n.md-footer-icp {\n    width: 100%;\n    text-align: center;\n    margin-top: 1rem;\n    font-size: 0.8rem;\n}\n\n.md-footer-icp a {\n    color: var(--md-default-fg-color--light);\n    text-decoration: none;\n}\n\n/* \u54cd\u5e94\u5f0f\u9002\u914d */\n@media screen and (max-width: 76.1875em) {\n    .md-footer-meta__inner {\n        flex-direction: column;\n        text-align: center;\n    }\n\n    .md-footer-social {\n        justify-content: center;\n    }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#723","title":"7.2.3 \u641c\u7d22\u6846","text":"HTML<pre><code>&lt;!-- docs/overrides/partials/search-modal.html --&gt;\n&lt;div class=\"md-search-modal\" data-md-component=\"search-modal\"&gt;\n    &lt;div class=\"md-search-modal__overlay\" data-md-component=\"search-modal-overlay\"&gt;&lt;/div&gt;\n\n    &lt;div class=\"md-search-modal__inner\"&gt;\n        &lt;!-- \u641c\u7d22\u5934\u90e8 --&gt;\n        &lt;header class=\"md-search-modal__header\"&gt;\n            &lt;form class=\"md-search-modal__form\"&gt;\n                &lt;input\n                    type=\"text\"\n                    class=\"md-search-modal__input\"\n                    name=\"query\"\n                    placeholder=\"\u641c\u7d22\u6587\u6863...\"\n                    data-md-component=\"search-query\"\n                    autocapitalize=\"off\"\n                    autocomplete=\"off\"\n                    autocorrect=\"off\"\n                    spellcheck=\"false\"\n                &gt;\n                &lt;!-- \u5feb\u6377\u952e\u63d0\u793a --&gt;\n                &lt;div class=\"md-search-modal__shortcuts\"&gt;\n                    &lt;kbd&gt;\u2191&lt;/kbd&gt;&lt;kbd&gt;\u2193&lt;/kbd&gt; \u9009\u62e9\n                    &lt;kbd&gt;\u21b5&lt;/kbd&gt; \u6253\u5f00\n                    &lt;kbd&gt;ESC&lt;/kbd&gt; \u5173\u95ed\n                &lt;/div&gt;\n            &lt;/form&gt;\n        &lt;/header&gt;\n\n        &lt;!-- \u641c\u7d22\u7ed3\u679c --&gt;\n        &lt;main class=\"md-search-modal__body\"&gt;\n            &lt;div class=\"md-search-modal__scrollwrap\"&gt;\n                &lt;div class=\"md-search-modal__meta\"&gt;\n                    \u952e\u5165\u4ee5\u5f00\u59cb\u641c\u7d22\n                &lt;/div&gt;\n\n                &lt;div class=\"md-search-modal__results\"&gt;\n                    &lt;!-- \u641c\u7d22\u7ed3\u679c\u5217\u8868 --&gt;\n                    &lt;div class=\"md-search-modal__list\"&gt;&lt;/div&gt;\n\n                    &lt;!-- \u641c\u7d22\u5efa\u8bae --&gt;\n                    &lt;div class=\"md-search-modal__suggestions\"&gt;\n                        &lt;h3&gt;\u60a8\u53ef\u80fd\u611f\u5174\u8da3\uff1a&lt;/h3&gt;\n                        &lt;div class=\"suggestions-list\"&gt;\n                            &lt;!-- \u52a8\u6001\u751f\u6210\u7684\u5efa\u8bae\u5217\u8868 --&gt;\n                        &lt;/div&gt;\n                    &lt;/div&gt;\n                &lt;/div&gt;\n            &lt;/div&gt;\n        &lt;/main&gt;\n    &lt;/div&gt;\n&lt;/div&gt;\n</code></pre> <p>\u641c\u7d22\u529f\u80fd\u811a\u672c\uff1a</p> JavaScript<pre><code>// docs/javascripts/search.js\nclass SearchModal {\n    constructor() {\n        this.modal = document.querySelector('.md-search-modal');\n        this.overlay = document.querySelector('.md-search-modal__overlay');\n        this.input = document.querySelector('.md-search-modal__input');\n        this.resultsList = document.querySelector('.md-search-modal__list');\n        this.suggestions = document.querySelector('.md-search-modal__suggestions');\n\n        this.searchIndex = null;\n        this.searchResults = [];\n        this.currentFocus = -1;\n\n        this.init();\n    }\n\n    init() {\n        // \u521d\u59cb\u5316\u641c\u7d22\u7d22\u5f15\n        this.buildSearchIndex();\n        // \u7ed1\u5b9a\u4e8b\u4ef6\n        this.bindEvents();\n        // \u8bbe\u7f6e\u5feb\u6377\u952e\n        this.setupShortcuts();\n    }\n\n    async buildSearchIndex() {\n        // \u6784\u5efa\u641c\u7d22\u7d22\u5f15\n        const response = await fetch('/search/search_index.json');\n        const data = await response.json();\n\n        // \u4f7f\u7528 lunr.js \u6784\u5efa\u7d22\u5f15\n        this.searchIndex = lunr(function() {\n            this.field('title', { boost: 10 });\n            this.field('text');\n            this.ref('location');\n\n            data.docs.forEach(function(doc) {\n                this.add(doc);\n            }, this);\n        });\n    }\n\n    bindEvents() {\n        // \u641c\u7d22\u6846\u8f93\u5165\u4e8b\u4ef6\n        this.input.addEventListener('input', debounce(() =&gt; {\n            const query = this.input.value;\n            if (query.length &gt;= 2) {\n                this.performSearch(query);\n            } else {\n                this.clearResults();\n            }\n        }, 200));\n\n        // \u641c\u7d22\u7ed3\u679c\u5bfc\u822a\n        this.input.addEventListener('keydown', (e) =&gt; {\n            switch (e.key) {\n                case 'ArrowUp':\n                    e.preventDefault();\n                    this.navigateResults('up');\n                    break;\n                case 'ArrowDown':\n                    e.preventDefault();\n                    this.navigateResults('down');\n                    break;\n                case 'Enter':\n                    e.preventDefault();\n                    this.openResult();\n                    break;\n                case 'Escape':\n                    e.preventDefault();\n                    this.closeModal();\n                    break;\n            }\n        });\n\n        // \u70b9\u51fb\u906e\u7f69\u5173\u95ed\n        this.overlay.addEventListener('click', () =&gt; this.closeModal());\n    }\n\n    setupShortcuts() {\n        // \u5168\u5c40\u641c\u7d22\u5feb\u6377\u952e\n        document.addEventListener('keydown', (e) =&gt; {\n            // Ctrl/Cmd + K \u6253\u5f00\u641c\u7d22\n            if ((e.ctrlKey || e.metaKey) &amp;&amp; e.key === 'k') {\n                e.preventDefault();\n                this.openModal();\n            }\n        });\n    }\n\n    async performSearch(query) {\n        if (!this.searchIndex) return;\n\n        // \u6267\u884c\u641c\u7d22\n        this.searchResults = this.searchIndex.search(query).map(result =&gt; {\n            return {\n                ref: result.ref,\n                score: result.score,\n                ...this.getDocumentByRef(result.ref)\n            };\n        });\n\n        // \u6e32\u67d3\u7ed3\u679c\n        this.renderResults();\n        // \u66f4\u65b0\u5efa\u8bae\n        this.updateSuggestions(query);\n    }\n\n    renderResults() {\n        this.resultsList.innerHTML = this.searchResults\n            .map((result, index) =&gt; `\n                &lt;div class=\"search-result-item ${index === this.currentFocus ? 'focused' : ''}\"\n                     data-index=\"${index}\"&gt;\n                    &lt;div class=\"result-title\"&gt;${this.highlightText(result.title)}&lt;/div&gt;\n                    &lt;div class=\"result-excerpt\"&gt;${this.highlightText(result.excerpt)}&lt;/div&gt;\n                    &lt;div class=\"result-location\"&gt;${result.location}&lt;/div&gt;\n                &lt;/div&gt;\n            `)\n            .join('');\n    }\n\n    highlightText(text) {\n        const query = this.input.value;\n        if (!query) return text;\n\n        const regex = new RegExp(`(${query})`, 'gi');\n        return text.replace(regex, '&lt;mark&gt;$1&lt;/mark&gt;');\n    }\n\n    updateSuggestions(query) {\n        // \u6839\u636e\u641c\u7d22\u5386\u53f2\u548c\u70ed\u95e8\u641c\u7d22\u751f\u6210\u5efa\u8bae\n        const suggestions = this.generateSuggestions(query);\n\n        this.suggestions.innerHTML = suggestions\n            .map(suggestion =&gt; `\n                &lt;div class=\"suggestion-item\" data-query=\"${suggestion.query}\"&gt;\n                    &lt;span class=\"suggestion-icon\"&gt;\n                        ${suggestion.type === 'history' ? '\u23f1\ufe0f' : '\ud83d\udd25'}\n                    &lt;/span&gt;\n                    ${suggestion.query}\n                &lt;/div&gt;\n            `)\n            .join('');\n    }\n\n    navigateResults(direction) {\n        const maxIndex = this.searchResults.length - 1;\n\n        if (direction === 'up') {\n            this.currentFocus = this.currentFocus &gt; 0 ? this.currentFocus - 1 : maxIndex;\n        } else {\n            this.currentFocus = this.currentFocus &lt; maxIndex ? this.currentFocus + 1 : 0;\n        }\n\n        this.renderResults();\n        this.scrollToFocused();\n    }\n\n    scrollToFocused() {\n        const focused = this.resultsList.querySelector('.focused');\n        if (focused) {\n            focused.scrollIntoView({\n                behavior: 'smooth',\n                block: 'nearest'\n            });\n        }\n    }\n\n    openResult() {\n        const result = this.searchResults[this.currentFocus];\n        if (result) {\n            window.location.href = result.location;\n        }\n    }\n\n    openModal() {\n        this.modal.classList.add('active');\n        this.input.focus();\n        document.body.style.overflow = 'hidden';\n    }\n\n    closeModal() {\n        this.modal.classList.remove('active');\n        this.input.value = '';\n        this.clearResults();\n        document.body.style.overflow = '';\n    }\n\n    clearResults() {\n        this.searchResults = [];\n        this.currentFocus = -1;\n        this.resultsList.innerHTML = '';\n        this.suggestions.innerHTML = '';\n    }\n}\n\n// \u521d\u59cb\u5316\u641c\u7d22\u529f\u80fd\ndocument.addEventListener('DOMContentLoaded', () =&gt; {\n    new SearchModal();\n});\n</code></pre> <p>\u641c\u7d22\u6846\u6837\u5f0f\uff1a</p> CSS<pre><code>/* docs/stylesheets/search-modal.css */\n.md-search-modal {\n    position: fixed;\n    top: 0;\n    left: 0;\n    width: 100%;\n    height: 100%;\n    z-index: 1000;\n    opacity: 0;\n    visibility: hidden;\n    transition: all 0.2s ease;\n}\n\n.md-search-modal.active {\n    opacity: 1;\n    visibility: visible;\n}\n\n.md-search-modal__overlay {\n    position: absolute;\n    top: 0;\n    left: 0;\n    width: 100%;\n    height: 100%;\n    background: rgba(0, 0, 0, 0.5);\n    backdrop-filter: blur(4px);\n}\n\n.md-search-modal__inner {\n    position: relative;\n    width: 90%;\n    max-width: 800px;\n    margin: 2rem auto;\n    background: var(--md-default-bg-color);\n    border-radius: 8px;\n    box-shadow: var(--md-shadow-z3);\n}\n\n/* \u641c\u7d22\u7ed3\u679c\u6837\u5f0f */\n.search-result-item {\n    padding: 1rem;\n    cursor: pointer;\n    transition: background 0.2s ease;\n}\n\n.search-result-item:hover,\n.search-result-item.focused {\n    background: var(--md-code-bg-color);\n}\n\n.result-title {\n    font-size: 1.1rem;\n    font-weight: 500;\n    margin-bottom: 0.5rem;\n}\n\n.result-excerpt {\n    font-size: 0.9rem;\n    color: var(--md-default-fg-color--light);\n    margin-bottom: 0.5rem;\n}\n\n.result-location {\n    font-size: 0.8rem;\n    color: var(--md-accent-fg-color);\n}\n\n/* \u9ad8\u4eae\u5339\u914d\u6587\u672c */\nmark {\n    background: var(--md-accent-fg-color);\n    color: white;\n    padding: 0 0.2rem;\n    border-radius: 2px;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#724","title":"7.2.4 \u76ee\u5f55","text":""},{"location":"Tools/Blog/Mkdocs_Material/#7241","title":"7.2.4.1 \u76ee\u5f55\u7ed3\u6784","text":"HTML<pre><code>&lt;!-- docs/overrides/partials/toc.html --&gt;\n&lt;nav class=\"md-toc\" aria-label=\"\u76ee\u5f55\"&gt;\n    &lt;div class=\"md-toc__header\"&gt;\n        &lt;h2 class=\"md-toc__title\"&gt;\u76ee\u5f55&lt;/h2&gt;\n        &lt;button class=\"md-toc__toggle\" aria-label=\"\u5c55\u5f00/\u6536\u8d77\"&gt;\n            {% include \".icons/material/chevron-down.svg\" %}\n        &lt;/button&gt;\n    &lt;/div&gt;\n\n    &lt;div class=\"md-toc__inner\"&gt;\n        {% set toc = page.toc %}\n        &lt;ul class=\"md-toc__list\"&gt;\n            {% for toc_item in toc %}\n                {% include \"partials/toc-item.html\" %}\n            {% endfor %}\n        &lt;/ul&gt;\n    &lt;/div&gt;\n&lt;/nav&gt;\n\n&lt;!-- docs/overrides/partials/toc-item.html --&gt;\n&lt;li class=\"md-toc__item\"&gt;\n    &lt;a href=\"{{ toc_item.url }}\" class=\"md-toc__link\"&gt;\n        {{ toc_item.title }}\n    &lt;/a&gt;\n\n    {% if toc_item.children %}\n    &lt;ul class=\"md-toc__list\"&gt;\n        {% for toc_item in toc_item.children %}\n            {% include \"partials/toc-item.html\" %}\n        {% endfor %}\n    &lt;/ul&gt;\n    {% endif %}\n&lt;/li&gt;\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#7242","title":"7.2.4.2 \u6eda\u52a8\u540c\u6b65","text":"JavaScript<pre><code>// docs/javascripts/toc.js\nclass TableOfContents {\n    constructor() {\n        this.toc = document.querySelector('.md-toc');\n        this.tocLinks = this.toc.querySelectorAll('.md-toc__link');\n        this.headings = document.querySelectorAll('h1[id], h2[id], h3[id], h4[id], h5[id], h6[id]');\n        this.intersectionObserver = null;\n\n        this.init();\n    }\n\n    init() {\n        this.setupIntersectionObserver();\n        this.setupScrollSpy();\n        this.setupToggle();\n    }\n\n    setupIntersectionObserver() {\n        this.intersectionObserver = new IntersectionObserver(\n            (entries) =&gt; {\n                entries.forEach(entry =&gt; {\n                    if (entry.isIntersecting) {\n                        const id = entry.target.getAttribute('id');\n                        this.highlightTocItem(id);\n                    }\n                });\n            },\n            {\n                rootMargin: '0px 0px -80% 0px'\n            }\n        );\n\n        this.headings.forEach(heading =&gt; {\n            this.intersectionObserver.observe(heading);\n        });\n    }\n\n    setupScrollSpy() {\n        this.tocLinks.forEach(link =&gt; {\n            link.addEventListener('click', (e) =&gt; {\n                e.preventDefault();\n                const id = link.getAttribute('href').substring(1);\n                const target = document.getElementById(id);\n\n                if (target) {\n                    window.scrollTo({\n                        top: target.offsetTop - 100,\n                        behavior: 'smooth'\n                    });\n\n                    // \u66f4\u65b0 URL\n                    history.pushState(null, null, `#${id}`);\n                }\n            });\n        });\n    }\n\n    highlightTocItem(id) {\n        // \u79fb\u9664\u6240\u6709\u9ad8\u4eae\n        this.tocLinks.forEach(link =&gt; {\n            link.classList.remove('active');\n        });\n\n        // \u6dfb\u52a0\u65b0\u9ad8\u4eae\n        const activeLink = this.toc.querySelector(`a[href=\"#${id}\"]`);\n        if (activeLink) {\n            activeLink.classList.add('active');\n            this.expandParents(activeLink);\n        }\n    }\n\n    expandParents(element) {\n        let parent = element.parentElement;\n        while (parent &amp;&amp; parent.classList.contains('md-toc__item')) {\n            const list = parent.querySelector('.md-toc__list');\n            if (list) {\n                list.style.height = 'auto';\n                parent.classList.add('expanded');\n            }\n            parent = parent.parentElement;\n        }\n    }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#7243","title":"7.2.4.3 \u5c55\u5f00\u6536\u8d77","text":"JavaScript<pre><code>setupToggle() {\n    const toggleButton = this.toc.querySelector('.md-toc__toggle');\n    const tocInner = this.toc.querySelector('.md-toc__inner');\n\n    toggleButton?.addEventListener('click', () =&gt; {\n        const isExpanded = this.toc.classList.contains('expanded');\n\n        if (isExpanded) {\n            this.toc.classList.remove('expanded');\n            tocInner.style.height = '0';\n        } else {\n            this.toc.classList.add('expanded');\n            tocInner.style.height = tocInner.scrollHeight + 'px';\n        }\n    });\n\n    // \u6dfb\u52a0\u5c55\u5f00/\u6536\u8d77\u6240\u6709\u6309\u94ae\n    const expandAllButton = document.createElement('button');\n    expandAllButton.className = 'md-toc__expand-all';\n    expandAllButton.innerHTML = '\u5c55\u5f00\u5168\u90e8';\n    expandAllButton.addEventListener('click', () =&gt; this.toggleAll(true));\n\n    const collapseAllButton = document.createElement('button');\n    collapseAllButton.className = 'md-toc__collapse-all';\n    collapseAllButton.innerHTML = '\u6536\u8d77\u5168\u90e8';\n    collapseAllButton.addEventListener('click', () =&gt; this.toggleAll(false));\n\n    const buttonGroup = document.createElement('div');\n    buttonGroup.className = 'md-toc__button-group';\n    buttonGroup.appendChild(expandAllButton);\n    buttonGroup.appendChild(collapseAllButton);\n\n    this.toc.querySelector('.md-toc__header').appendChild(buttonGroup);\n}\n\ntoggleAll(expand) {\n    const lists = this.toc.querySelectorAll('.md-toc__list');\n    lists.forEach(list =&gt; {\n        if (expand) {\n            list.style.height = 'auto';\n            list.parentElement.classList.add('expanded');\n        } else {\n            list.style.height = '0';\n            list.parentElement.classList.remove('expanded');\n        }\n    });\n}\n</code></pre> <p>\u76ee\u5f55\u6837\u5f0f\uff1a</p> CSS<pre><code>/* docs/stylesheets/toc.css */\n.md-toc {\n    position: sticky;\n    top: 4rem;\n    padding: 1rem;\n    max-height: calc(100vh - 4rem);\n    overflow-y: auto;\n    background: var(--md-default-bg-color);\n    border-left: 1px solid var(--md-default-fg-color--lightest);\n    font-size: 0.8rem;\n}\n\n/* \u76ee\u5f55\u5934\u90e8 */\n.md-toc__header {\n    display: flex;\n    justify-content: space-between;\n    align-items: center;\n    margin-bottom: 1rem;\n    padding-bottom: 0.5rem;\n    border-bottom: 1px solid var(--md-default-fg-color--lightest);\n}\n\n.md-toc__title {\n    font-size: 1rem;\n    font-weight: 600;\n    margin: 0;\n}\n\n.md-toc__button-group {\n    display: flex;\n    gap: 0.5rem;\n}\n\n.md-toc__button-group button {\n    padding: 0.2rem 0.5rem;\n    font-size: 0.7rem;\n    color: var(--md-default-fg-color--light);\n    background: var(--md-code-bg-color);\n    border: none;\n    border-radius: 4px;\n    cursor: pointer;\n    transition: all 0.2s ease;\n}\n\n.md-toc__button-group button:hover {\n    color: var(--md-accent-fg-color);\n    background: var(--md-code-bg-color--light);\n}\n\n/* \u76ee\u5f55\u5217\u8868 */\n.md-toc__list {\n    list-style: none;\n    padding: 0;\n    margin: 0;\n}\n\n.md-toc__item {\n    margin: 0.2rem 0;\n}\n\n/* \u76ee\u5f55\u94fe\u63a5 */\n.md-toc__link {\n    display: block;\n    padding: 0.2rem 0;\n    color: var(--md-default-fg-color);\n    text-decoration: none;\n    transition: all 0.2s ease;\n    border-radius: 4px;\n}\n\n.md-toc__link:hover {\n    color: var(--md-accent-fg-color);\n    background: var(--md-code-bg-color);\n    padding-left: 0.5rem;\n}\n\n/* \u5f53\u524d\u6fc0\u6d3b\u9879 */\n.md-toc__link.active {\n    color: var(--md-accent-fg-color);\n    font-weight: 500;\n    background: var(--md-code-bg-color);\n    padding-left: 0.5rem;\n}\n\n/* \u5d4c\u5957\u5c42\u7ea7 */\n.md-toc__item .md-toc__list {\n    margin-left: 1rem;\n    border-left: 1px solid var(--md-default-fg-color--lightest);\n    overflow: hidden;\n    height: 0;\n    transition: height 0.3s ease;\n}\n\n.md-toc__item.expanded &gt; .md-toc__list {\n    height: auto;\n}\n\n/* \u6298\u53e0\u6307\u793a\u5668 */\n.md-toc__item &gt; .md-toc__link::before {\n    content: '';\n    display: inline-block;\n    width: 0.8rem;\n    height: 0.8rem;\n    margin-right: 0.2rem;\n    background-image: url('data:image/svg+xml,&lt;svg xmlns=\"http://www.w3.org/2000/svg\" viewBox=\"0 0 24 24\"&gt;&lt;path d=\"M8.59 16.59L13.17 12 8.59 7.41 10 6l6 6-6 6-1.41-1.41z\"/&gt;&lt;/svg&gt;');\n    background-size: contain;\n    transform: rotate(0);\n    transition: transform 0.3s ease;\n}\n\n.md-toc__item.expanded &gt; .md-toc__link::before {\n    transform: rotate(90deg);\n}\n\n/* \u6eda\u52a8\u6761\u6837\u5f0f */\n.md-toc::-webkit-scrollbar {\n    width: 4px;\n}\n\n.md-toc::-webkit-scrollbar-track {\n    background: transparent;\n}\n\n.md-toc::-webkit-scrollbar-thumb {\n    background: var(--md-default-fg-color--lighter);\n    border-radius: 2px;\n}\n\n/* \u54cd\u5e94\u5f0f\u8bbe\u8ba1 */\n@media screen and (max-width: 76.1875em) {\n    .md-toc {\n        position: fixed;\n        top: 0;\n        right: -18rem;\n        width: 18rem;\n        height: 100vh;\n        max-height: none;\n        margin: 0;\n        padding: 1rem;\n        background: var(--md-default-bg-color);\n        border-left: 1px solid var(--md-default-fg-color--lightest);\n        box-shadow: var(--md-shadow-z3);\n        transition: right 0.3s ease;\n        z-index: 3;\n    }\n\n    .md-toc.expanded {\n        right: 0;\n    }\n\n    /* \u79fb\u52a8\u7aef\u8986\u76d6\u5c42 */\n    .md-toc-overlay {\n        display: none;\n        position: fixed;\n        top: 0;\n        left: 0;\n        width: 100%;\n        height: 100%;\n        background: rgba(0, 0, 0, 0.3);\n        z-index: 2;\n    }\n\n    .md-toc.expanded + .md-toc-overlay {\n        display: block;\n    }\n}\n\n/* \u5e73\u677f\u9002\u914d */\n@media screen and (min-width: 76.25em) and (max-width: 96.25em) {\n    .md-toc {\n        padding: 0.8rem;\n    }\n\n    .md-toc__list {\n        margin-left: 0.8rem;\n    }\n}\n</code></pre> <p>\u5b8c\u6574\u7684\u76ee\u5f55\u529f\u80fd\u5b9e\u73b0\uff1a</p> JavaScript<pre><code>// docs/javascripts/toc.js\nclass TableOfContents {\n    constructor() {\n        this.toc = document.querySelector('.md-toc');\n        this.tocLinks = this.toc.querySelectorAll('.md-toc__link');\n        this.headings = document.querySelectorAll('h1[id], h2[id], h3[id], h4[id], h5[id], h6[id]');\n        this.intersectionObserver = null;\n        this.isScrolling = false;\n        this.scrollTimeout = null;\n\n        this.init();\n    }\n\n    init() {\n        this.setupIntersectionObserver();\n        this.setupScrollSpy();\n        this.setupToggle();\n        this.setupMobileToggle();\n        this.handleInitialHash();\n    }\n\n    handleInitialHash() {\n        // \u5904\u7406\u9875\u9762\u52a0\u8f7d\u65f6\u7684 hash\n        if (window.location.hash) {\n            const id = window.location.hash.substring(1);\n            const target = document.getElementById(id);\n            if (target) {\n                setTimeout(() =&gt; {\n                    target.scrollIntoView();\n                    this.highlightTocItem(id);\n                }, 100);\n            }\n        }\n    }\n\n    setupMobileToggle() {\n        // \u521b\u5efa\u79fb\u52a8\u7aef\u5f00\u5173\u6309\u94ae\n        const toggleButton = document.createElement('button');\n        toggleButton.className = 'md-toc-toggle';\n        toggleButton.innerHTML = `\n            &lt;span class=\"md-toc-toggle__icon\"&gt;\n                {% include \".icons/material/menu.svg\" %}\n            &lt;/span&gt;\n        `;\n\n        // \u521b\u5efa\u906e\u7f69\u5c42\n        const overlay = document.createElement('div');\n        overlay.className = 'md-toc-overlay';\n\n        document.body.appendChild(toggleButton);\n        document.body.appendChild(overlay);\n\n        // \u7ed1\u5b9a\u4e8b\u4ef6\n        toggleButton.addEventListener('click', () =&gt; {\n            this.toc.classList.toggle('expanded');\n            document.body.style.overflow = this.toc.classList.contains('expanded') ? 'hidden' : '';\n        });\n\n        overlay.addEventListener('click', () =&gt; {\n            this.toc.classList.remove('expanded');\n            document.body.style.overflow = '';\n        });\n    }\n\n    updateTocHeight() {\n        const lists = this.toc.querySelectorAll('.md-toc__list');\n        lists.forEach(list =&gt; {\n            if (list.parentElement.classList.contains('expanded')) {\n                list.style.height = list.scrollHeight + 'px';\n            }\n        });\n    }\n\n    onResize() {\n        // \u76d1\u542c\u7a97\u53e3\u5927\u5c0f\u53d8\u5316\uff0c\u66f4\u65b0\u76ee\u5f55\u9ad8\u5ea6\n        window.addEventListener('resize', debounce(() =&gt; {\n            this.updateTocHeight();\n        }, 100));\n    }\n}\n\n// \u5de5\u5177\u51fd\u6570\nfunction debounce(fn, delay) {\n    let timer = null;\n    return function(...args) {\n        clearTimeout(timer);\n        timer = setTimeout(() =&gt; fn.apply(this, args), delay);\n    };\n}\n\n// \u521d\u59cb\u5316\u76ee\u5f55\ndocument.addEventListener('DOMContentLoaded', () =&gt; {\n    new TableOfContents();\n});\n</code></pre> <p>\u4f7f\u7528\u8fd9\u4e9b\u4ee3\u7801\uff0c\u9700\u8981\u5728 <code>mkdocs.yml</code> \u4e2d\u6dfb\u52a0\u76f8\u5e94\u7684\u914d\u7f6e\uff1a</p> YAML<pre><code>theme:\n  name: material\n  custom_dir: docs/overrides\n  features:\n    - toc.integrate\n    - toc.follow\n\nextra_css:\n  - stylesheets/toc.css\n\nextra_javascript:\n  - javascripts/toc.js\n</code></pre> <p>\u8fd9\u6837\u5c31\u5b8c\u6210\u4e86\u4e00\u4e2a\u529f\u80fd\u5b8c\u6574\u3001\u4ea4\u4e92\u53cb\u597d\u7684\u76ee\u5f55\u5bfc\u822a\u7cfb\u7edf\uff0c\u4e3b\u8981\u7279\u70b9\u5305\u62ec\uff1a</p> <ol> <li>\u81ea\u52a8\u9ad8\u4eae\u5f53\u524d\u9605\u8bfb\u4f4d\u7f6e</li> <li>\u5e73\u6ed1\u6eda\u52a8\u5230\u76ee\u6807\u4f4d\u7f6e</li> <li>\u652f\u6301\u5c55\u5f00/\u6536\u8d77\u529f\u80fd</li> <li>\u79fb\u52a8\u7aef\u81ea\u9002\u5e94\u5e03\u5c40</li> <li>\u4f18\u96c5\u7684\u52a8\u753b\u6548\u679c</li> <li>\u826f\u597d\u7684\u53ef\u8bbf\u95ee\u6027\u652f\u6301</li> <li>\u6027\u80fd\u4f18\u5316\u8003\u8651</li> </ol>"},{"location":"Tools/Blog/Mkdocs_Material/#8","title":"8 \u63d2\u4ef6\u4f7f\u7528","text":""},{"location":"Tools/Blog/Mkdocs_Material/#81","title":"8.1 \u5fc5\u5907\u63d2\u4ef6","text":""},{"location":"Tools/Blog/Mkdocs_Material/#8111-search","title":"8.1.1.1 search","text":""},{"location":"Tools/Blog/Mkdocs_Material/#8112","title":"8.1.1.2 \u57fa\u7840\u914d\u7f6e","text":"<ol> <li>\u5b89\u88c5\u641c\u7d22\u63d2\u4ef6\uff1a</li> </ol> Bash<pre><code>pip install mkdocs-material\n</code></pre> <ol> <li>\u914d\u7f6e\u641c\u7d22\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nplugins:\n  - search:\n      # \u641c\u7d22\u7d22\u5f15\u8bbe\u7f6e\n      lang: \n        - en\n        - zh\n      separator: '[\\s\\-\\.]+'    # \u5206\u8bcd\u5206\u9694\u7b26\n      min_search_length: 2      # \u6700\u5c0f\u641c\u7d22\u957f\u5ea6\n      prebuild_index: true      # \u9884\u6784\u5efa\u7d22\u5f15\n\n      # \u641c\u7d22\u5185\u5bb9\u914d\u7f6e\n      indexing:\n        full_sections: true     # \u7d22\u5f15\u5b8c\u6574\u7ae0\u8282\n        headings: true         # \u7d22\u5f15\u6807\u9898\n        content: true         # \u7d22\u5f15\u5185\u5bb9\n        tags: true           # \u7d22\u5f15\u6807\u7b7e\n\n      # \u641c\u7d22\u7ed3\u679c\u6392\u5e8f\n      scoring:\n        title_boost: 10      # \u6807\u9898\u6743\u91cd\n        heading_boost: 5     # \u6807\u9898\u6743\u91cd\n        content_boost: 1     # \u5185\u5bb9\u6743\u91cd\n</code></pre> <ol> <li>\u641c\u7d22\u4e3b\u9898\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>theme:\n  features:\n    - search.highlight        # \u641c\u7d22\u9ad8\u4eae\n    - search.share           # \u641c\u7d22\u5206\u4eab\n    - search.suggest         # \u641c\u7d22\u5efa\u8bae\n\n  # \u641c\u7d22\u754c\u9762\u6587\u5b57\n  language: zh\n  palette:\n    - search:\n        placeholder: \u641c\u7d22\u6587\u6863\n        result:\n          no_results_text: \u672a\u627e\u5230\u76f8\u5173\u7ed3\u679c\n          searching_text: \u6b63\u5728\u641c\u7d22...\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8113","title":"8.1.1.3 \u4e2d\u6587\u641c\u7d22","text":"<ol> <li>\u4e2d\u6587\u5206\u8bcd\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>plugins:\n  - search:\n      jieba_dict: dict.txt   # \u81ea\u5b9a\u4e49\u8bcd\u5178\u8def\u5f84\n      jieba_dict_user: user_dict.txt  # \u7528\u6237\u8bcd\u5178\u8def\u5f84\n\n      # \u4e2d\u6587\u5206\u8bcd\u89c4\u5219\n      separator: '[\uff0c\u3002\uff01\uff1f,!?]+'\n\n      # \u4e2d\u6587\u505c\u7528\u8bcd\n      stopwords:\n        - \u7684\n        - \u4e86\n        - \u548c\n        - \u662f\n        - \u5c31\n        - \u90fd\n        - \u800c\n        - \u53ca\n        - \u4e0e\n        - \u8fd9\n</code></pre> <ol> <li>\u81ea\u5b9a\u4e49\u8bcd\u5178\u793a\u4f8b\uff08dict.txt\uff09\uff1a</li> </ol> Text Only<pre><code>\u6280\u672f\u6587\u6863 5\n\u5f00\u53d1\u6307\u5357 5\n\u6700\u4f73\u5b9e\u8df5 5\n\u4f7f\u7528\u6559\u7a0b 5\n\u914d\u7f6e\u8bf4\u660e 5\n\u5e38\u89c1\u95ee\u9898 5\n</code></pre> <ol> <li>\u5206\u8bcd\u4f18\u5316\u811a\u672c\uff1a</li> </ol> Python<pre><code># docs/search_optimize.py\nimport jieba\nimport json\nfrom pathlib import Path\n\ndef optimize_search_index(index_file, dict_file):\n    # \u52a0\u8f7d\u81ea\u5b9a\u4e49\u8bcd\u5178\n    jieba.load_userdict(dict_file)\n\n    # \u8bfb\u53d6\u641c\u7d22\u7d22\u5f15\n    with open(index_file, 'r', encoding='utf-8') as f:\n        index = json.load(f)\n\n    # \u4f18\u5316\u5206\u8bcd\n    for doc in index['docs']:\n        # \u5206\u8bcd\u5904\u7406\u6807\u9898\n        title_words = list(jieba.cut(doc['title']))\n        doc['title'] = ' '.join(title_words)\n\n        # \u5206\u8bcd\u5904\u7406\u5185\u5bb9\n        if 'text' in doc:\n            text_words = list(jieba.cut(doc['text']))\n            doc['text'] = ' '.join(text_words)\n\n    # \u4fdd\u5b58\u4f18\u5316\u540e\u7684\u7d22\u5f15\n    with open(index_file, 'w', encoding='utf-8') as f:\n        json.dump(index, f, ensure_ascii=False, indent=2)\n\nif __name__ == '__main__':\n    index_file = 'site/search/search_index.json'\n    dict_file = 'docs/dict.txt'\n    optimize_search_index(index_file, dict_file)\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8114","title":"8.1.1.4 \u641c\u7d22\u4f18\u5316","text":"<ol> <li>\u7d22\u5f15\u4f18\u5316\uff1a</li> </ol> Python<pre><code># docs/search_index_optimizer.py\nfrom pathlib import Path\nimport json\nimport re\n\nclass SearchIndexOptimizer:\n    def __init__(self, index_path):\n        self.index_path = Path(index_path)\n        self.index = self.load_index()\n\n    def load_index(self):\n        with open(self.index_path, 'r', encoding='utf-8') as f:\n            return json.load(f)\n\n    def save_index(self):\n        with open(self.index_path, 'w', encoding='utf-8') as f:\n            json.dump(self.index, f, ensure_ascii=False, indent=2)\n\n    def optimize(self):\n        # \u6e05\u7406\u65e0\u7528\u6570\u636e\n        self._clean_data()\n        # \u4f18\u5316\u6587\u672c\n        self._optimize_text()\n        # \u6dfb\u52a0\u6743\u91cd\n        self._add_weights()\n        # \u6784\u5efa\u53cd\u5411\u7d22\u5f15\n        self._build_inverted_index()\n        # \u4fdd\u5b58\u4f18\u5316\u540e\u7684\u7d22\u5f15\n        self.save_index()\n\n    def _clean_data(self):\n        # \u79fb\u9664\u7a7a\u6587\u6863\n        self.index['docs'] = [\n            doc for doc in self.index['docs']\n            if doc.get('text') or doc.get('title')\n        ]\n\n        # \u79fb\u9664\u91cd\u590d\u6587\u6863\n        seen = set()\n        unique_docs = []\n        for doc in self.index['docs']:\n            key = f\"{doc['location']}:{doc['title']}\"\n            if key not in seen:\n                seen.add(key)\n                unique_docs.append(doc)\n        self.index['docs'] = unique_docs\n\n    def _optimize_text(self):\n        for doc in self.index['docs']:\n            # \u6e05\u7406HTML\u6807\u7b7e\n            if 'text' in doc:\n                doc['text'] = re.sub(r'&lt;[^&gt;]+&gt;', '', doc['text'])\n\n            # \u538b\u7f29\u7a7a\u767d\u5b57\u7b26\n            for field in ['title', 'text']:\n                if field in doc:\n                    doc[field] = ' '.join(doc[field].split())\n\n    def _add_weights(self):\n        for doc in self.index['docs']:\n            # \u57fa\u7840\u6743\u91cd\n            doc['weight'] = 1.0\n\n            # \u6807\u9898\u957f\u5ea6\u6743\u91cd\n            if 'title' in doc:\n                title_len = len(doc['title'])\n                doc['weight'] *= 1 + (1.0 / (1 + title_len))\n\n            # \u6587\u672c\u957f\u5ea6\u6743\u91cd\n            if 'text' in doc:\n                text_len = len(doc['text'])\n                doc['weight'] *= 1 + (100.0 / (1 + text_len))\n\n            # URL\u6df1\u5ea6\u6743\u91cd\n            depth = doc['location'].count('/')\n            doc['weight'] *= 1 + (1.0 / (1 + depth))\n\n    def _build_inverted_index(self):\n        # \u6784\u5efa\u53cd\u5411\u7d22\u5f15\n        inverted_index = {}\n        for i, doc in enumerate(self.index['docs']):\n            terms = set()\n\n            # \u6dfb\u52a0\u6807\u9898\u8bcd\n            if 'title' in doc:\n                terms.update(doc['title'].lower().split())\n\n            # \u6dfb\u52a0\u6587\u672c\u8bcd\n            if 'text' in doc:\n                terms.update(doc['text'].lower().split())\n\n            # \u66f4\u65b0\u53cd\u5411\u7d22\u5f15\n            for term in terms:\n                if term not in inverted_index:\n                    inverted_index[term] = []\n                inverted_index[term].append({\n                    'id': i,\n                    'weight': doc['weight']\n                })\n\n        self.index['inverted_index'] = inverted_index\n\n# \u4f7f\u7528\u4f18\u5316\u5668\noptimizer = SearchIndexOptimizer('site/search/search_index.json')\noptimizer.optimize()\n</code></pre> <ol> <li>\u641c\u7d22\u6027\u80fd\u76d1\u63a7\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/search-monitor.js\nclass SearchMonitor {\n    constructor() {\n        this.metrics = {\n            searches: 0,\n            avgTime: 0,\n            slowest: 0,\n            fastest: Infinity\n        };\n\n        this.init();\n    }\n\n    init() {\n        this.monitorSearchInput();\n        this.monitorSearchResults();\n        this.setupReporting();\n    }\n\n    monitorSearchInput() {\n        const searchInput = document.querySelector('.md-search__input');\n        let startTime;\n\n        searchInput?.addEventListener('input', () =&gt; {\n            startTime = performance.now();\n        });\n\n        searchInput?.addEventListener('search', () =&gt; {\n            const endTime = performance.now();\n            const duration = endTime - startTime;\n\n            this.updateMetrics(duration);\n        });\n    }\n\n    updateMetrics(duration) {\n        this.metrics.searches++;\n        this.metrics.avgTime = (\n            (this.metrics.avgTime * (this.metrics.searches - 1) + duration) /\n            this.metrics.searches\n        );\n        this.metrics.slowest = Math.max(this.metrics.slowest, duration);\n        this.metrics.fastest = Math.min(this.metrics.fastest, duration);\n\n        // \u53d1\u9001\u7edf\u8ba1\u6570\u636e\n        this.sendMetrics();\n    }\n\n    sendMetrics() {\n        // \u53ef\u4ee5\u53d1\u9001\u5230\u7edf\u8ba1\u670d\u52a1\n        console.log('Search Metrics:', this.metrics);\n    }\n}\n\n// \u521d\u59cb\u5316\u76d1\u63a7\nnew SearchMonitor();\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#812-glightbox","title":"8.1.2 glightbox","text":""},{"location":"Tools/Blog/Mkdocs_Material/#8121","title":"8.1.2.1 \u56fe\u7247\u9884\u89c8","text":"<ol> <li>\u5b89\u88c5\u63d2\u4ef6\uff1a</li> </ol> Bash<pre><code>pip install mkdocs-glightbox\n</code></pre> <ol> <li>\u57fa\u7840\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nplugins:\n  - glightbox:\n      # \u57fa\u7840\u8bbe\u7f6e\n      auto_caption: true              # \u81ea\u52a8\u6dfb\u52a0\u6807\u9898\n      caption_position: bottom        # \u6807\u9898\u4f4d\u7f6e\n      display_description: true       # \u663e\u793a\u63cf\u8ff0\n\n      # \u89e6\u6478\u8bbe\u7f6e\n      touchNavigation: true          # \u89e6\u6478\u5bfc\u822a\n      loop: true                    # \u5faa\u73af\u6d4f\u89c8\n      effect: zoom                  # \u8fc7\u6e21\u6548\u679c\n\n      # \u56fe\u7247\u8bbe\u7f6e\n      width: 100%                   # \u56fe\u7247\u5bbd\u5ea6\n      height: auto                  # \u56fe\u7247\u9ad8\u5ea6\n      zoomable: true               # \u542f\u7528\u7f29\u653e\n      draggable: true              # \u542f\u7528\u62d6\u52a8\n</code></pre> <ol> <li>\u81ea\u5b9a\u4e49\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/glightbox.css */\n.glightbox-clean {\n    /* \u5bb9\u5668\u6837\u5f0f */\n    --glow-padding: 2rem;\n    --glow-bg: rgba(0, 0, 0, 0.95);\n\n    /* \u63a7\u5236\u6309\u94ae */\n    --glow-btn-color: rgba(255, 255, 255, 0.8);\n    --glow-btn-hover: #fff;\n\n    /* \u52a0\u8f7d\u52a8\u753b */\n    --glow-loading-bg: rgba(0, 0, 0, 0.5);\n    --glow-loading-width: 40px;\n    --glow-loading-height: 40px;\n}\n\n/* \u6807\u9898\u6837\u5f0f */\n.glightbox-caption {\n    font-family: var(--md-font-family);\n    font-size: 0.9rem;\n    padding: 1rem;\n    background: rgba(0, 0, 0, 0.8);\n}\n\n/* \u63cf\u8ff0\u6837\u5f0f */\n.glightbox-description {\n    font-size: 0.8rem;\n    color: rgba(255, 255, 255, 0.7);\n    margin-top: 0.5rem;\n}\n\n/* \u52a0\u8f7d\u52a8\u753b */\n.glightbox-loading {\n    border: 3px solid rgba(255, 255, 255, 0.2);\n    border-top-color: #fff;\n    border-radius: 50%;\n    animation: glow-spin 1s linear infinite;\n}\n\n@keyframes glow-spin {\n    to { transform: rotate(360deg); }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8122","title":"8.1.2.2 \u753b\u5eca\u6a21\u5f0f","text":"<ol> <li>\u753b\u5eca\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>plugins:\n  - glightbox:\n      # \u753b\u5eca\u8bbe\u7f6e\n      gallery: true                 # \u542f\u7528\u753b\u5eca\n      gallery_mode: true           # \u753b\u5eca\u6a21\u5f0f\n      gallery_trigger: click      # \u89e6\u53d1\u65b9\u5f0f\n\n      # \u7f29\u7565\u56fe\u8bbe\u7f6e\n      thumb_width: 150            # \u7f29\u7565\u56fe\u5bbd\u5ea6\n      thumb_height: 100           # \u7f29\u7565\u56fe\u9ad8\u5ea6\n      thumb_fit: cover            # \u7f29\u7565\u56fe\u9002\u5e94\u65b9\u5f0f\n</code></pre> <ol> <li>\u753b\u5eca\u5b9e\u73b0\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/gallery.html --&gt;\n&lt;div class=\"gallery\"&gt;\n    {% for image in page.meta.gallery %}\n    &lt;a href=\"{{ image.url }}\" \n       class=\"gallery-item\"\n       data-gallery=\"gallery\"\n       data-glightbox=\"title: {{ image.title }}; description: {{ image.description }}\"&gt;\n        &lt;img src=\"{{ image.thumbnail or image.url }}\" \n             alt=\"{{ image.title }}\"\n             loading=\"lazy\"&gt;\n        {% if image.title %}\n        &lt;div class=\"gallery-caption\"&gt;{{ image.title }}&lt;/div&gt;\n        {% endif %}\n    &lt;/a&gt;\n    {% endfor %}\n&lt;/div&gt;\n</code></pre> <ol> <li>\u753b\u5eca\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/gallery.css */\n.gallery {\n    display: grid;\n    grid-template-columns: repeat(auto-fill, minmax(150px, 1fr));\n    gap: 1rem;\n    padding: 1rem;\n}\n\n.gallery-item {\n    position: relative;\n    overflow: hidden;\n    border-radius: 4px;\n    cursor: pointer;\n    transition: transform 0.3s ease;\n}\n\n.gallery-item:hover {\n    transform: translateY(-4px);\n}\n\n.gallery-item img {\n    width: 100%;\n    height: 100%;\n    object-fit: cover;\n    transition: transform 0.3s ease;\n}\n\n.gallery-item:hover img {\n    transform: scale(1.1);\n}\n\n.gallery-caption {\n    position: absolute;\n    bottom: 0;\n    left: 0;\n    right: 0;\n    padding: 0.5rem;\n    background: rgba(0, 0, 0, 0.7);\n    color: white;\n    font-size: 0.8rem;\n    transform: translateY(100%);\n    transition: transform 0.3s ease;\n}\n\n.gallery-item:hover .gallery-caption {\n    transform: translateY(0);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#82","title":"8.2 \u63a8\u8350\u63d2\u4ef6","text":""},{"location":"Tools/Blog/Mkdocs_Material/#8211-git-revision-date","title":"8.2.1.1 git-revision-date","text":""},{"location":"Tools/Blog/Mkdocs_Material/#8212","title":"8.2.1.2 \u65f6\u95f4\u663e\u793a","text":"<ol> <li>\u5b89\u88c5\u63d2\u4ef6\uff1a</li> </ol> Bash<pre><code>pip install mkdocs-git-revision-date-localized-plugin\n</code></pre> <ol> <li>\u57fa\u7840\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nplugins:\n  - git-revision-date-localized:\n      enabled: true\n      type: date           # \u663e\u793a\u7c7b\u578b\uff1adate, datetime, iso_date, iso_datetime, timeago\n      timezone: Asia/Shanghai  # \u65f6\u533a\u8bbe\u7f6e\n      locale: zh          # \u672c\u5730\u5316\u8bed\u8a00\n      fallback_to_build_date: true  # \u65e0 git \u4fe1\u606f\u65f6\u4f7f\u7528\u6784\u5efa\u65f6\u95f4\n\n      # \u65f6\u95f4\u683c\u5f0f\n      enable_creation_date: true    # \u663e\u793a\u521b\u5efa\u65f6\u95f4\n      exclude:\n        - index.md\n        - 404.md\n</code></pre> <ol> <li>\u65f6\u95f4\u663e\u793a\u6a21\u677f\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/date.html --&gt;\n{% if page.meta.git_revision_date_localized %}\n&lt;div class=\"page-date\"&gt;\n    &lt;!-- \u6700\u540e\u66f4\u65b0\u65f6\u95f4 --&gt;\n    &lt;div class=\"date-item\"&gt;\n        &lt;span class=\"date-icon\"&gt;\n            {% include \".icons/material/update.svg\" %}\n        &lt;/span&gt;\n        &lt;span class=\"date-text\"&gt;\n            \u6700\u540e\u66f4\u65b0: {{ page.meta.git_revision_date_localized }}\n        &lt;/span&gt;\n    &lt;/div&gt;\n\n    &lt;!-- \u521b\u5efa\u65f6\u95f4 --&gt;\n    {% if page.meta.git_creation_date_localized %}\n    &lt;div class=\"date-item\"&gt;\n        &lt;span class=\"date-icon\"&gt;\n            {% include \".icons/material/clock-outline.svg\" %}\n        &lt;/span&gt;\n        &lt;span class=\"date-text\"&gt;\n            \u521b\u5efa\u65f6\u95f4: {{ page.meta.git_creation_date_localized }}\n        &lt;/span&gt;\n    &lt;/div&gt;\n    {% endif %}\n&lt;/div&gt;\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8213","title":"8.2.1.3 \u66f4\u65b0\u8bb0\u5f55","text":"<ol> <li>\u66f4\u65b0\u8bb0\u5f55\u663e\u793a\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/revision.html --&gt;\n{% if page.meta.git_revision_date_localized %}\n&lt;div class=\"revision-history\"&gt;\n    &lt;h3&gt;\u66f4\u65b0\u8bb0\u5f55&lt;/h3&gt;\n    &lt;div class=\"revision-list\"&gt;\n        {% for revision in page.meta.git_history %}\n        &lt;div class=\"revision-item\"&gt;\n            &lt;div class=\"revision-date\"&gt;\n                {{ revision.date }}\n            &lt;/div&gt;\n            &lt;div class=\"revision-message\"&gt;\n                {{ revision.message }}\n            &lt;/div&gt;\n        &lt;/div&gt;\n        {% endfor %}\n    &lt;/div&gt;\n&lt;/div&gt;\n</code></pre> <ol> <li>\u6837\u5f0f\u914d\u7f6e\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/revision.css */\n.revision-history {\n    margin: 2rem 0;\n    padding: 1rem;\n    background: var(--md-code-bg-color);\n    border-radius: 4px;\n}\n\n.revision-item {\n    display: flex;\n    padding: 0.5rem 0;\n    border-bottom: 1px solid var(--md-default-fg-color--lightest);\n}\n\n.revision-date {\n    flex: 0 0 200px;\n    color: var(--md-default-fg-color--light);\n}\n\n.revision-message {\n    flex: 1;\n}\n\n/* \u65f6\u95f4\u7ebf\u6837\u5f0f */\n.revision-item {\n    position: relative;\n    padding-left: 2rem;\n}\n\n.revision-item::before {\n    content: '';\n    position: absolute;\n    left: 0;\n    top: 1rem;\n    width: 12px;\n    height: 12px;\n    background: var(--md-accent-fg-color);\n    border-radius: 50%;\n}\n\n.revision-item::after {\n    content: '';\n    position: absolute;\n    left: 5px;\n    top: 1.5rem;\n    bottom: -0.5rem;\n    width: 2px;\n    background: var(--md-default-fg-color--lightest);\n}\n\n.revision-item:last-child::after {\n    display: none;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8214","title":"8.2.1.4 \u4f5c\u8005\u4fe1\u606f","text":"<ol> <li>\u4f5c\u8005\u4fe1\u606f\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>plugins:\n  - git-revision-date-localized:\n      enabled: true\n      type: date\n      enable_authors: true     # \u542f\u7528\u4f5c\u8005\u4fe1\u606f\n      authors_file: authors.yaml   # \u4f5c\u8005\u914d\u7f6e\u6587\u4ef6\n</code></pre> <ol> <li>\u4f5c\u8005\u914d\u7f6e\u6587\u4ef6 (authors. yaml)\uff1a</li> </ol> YAML<pre><code>authors:\n  john:\n    name: John Doe\n    email: john@example.com\n    avatar: assets/authors/john.jpg\n    bio: \u8d44\u6df1\u6280\u672f\u4f5c\u8005\n    social:\n      github: johndoe\n      twitter: johndoe\n\n  jane:\n    name: Jane Smith\n    email: jane@example.com\n    avatar: assets/authors/jane.jpg\n    bio: \u524d\u7aef\u5f00\u53d1\u4e13\u5bb6\n    social:\n      github: janesmith\n      linkedin: janesmith\n</code></pre> <ol> <li>\u4f5c\u8005\u4fe1\u606f\u663e\u793a\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/author.html --&gt;\n{% if page.meta.git_authors %}\n&lt;div class=\"page-authors\"&gt;\n    {% for author in page.meta.git_authors %}\n    &lt;div class=\"author-card\"&gt;\n        &lt;!-- \u4f5c\u8005\u5934\u50cf --&gt;\n        &lt;div class=\"author-avatar\"&gt;\n            {% if author.avatar %}\n            &lt;img src=\"{{ author.avatar }}\" alt=\"{{ author.name }}\"&gt;\n            {% else %}\n            &lt;div class=\"avatar-placeholder\"&gt;\n                {{ author.name[0] }}\n            &lt;/div&gt;\n            {% endif %}\n        &lt;/div&gt;\n\n        &lt;!-- \u4f5c\u8005\u4fe1\u606f --&gt;\n        &lt;div class=\"author-info\"&gt;\n            &lt;h4 class=\"author-name\"&gt;{{ author.name }}&lt;/h4&gt;\n            {% if author.bio %}\n            &lt;p class=\"author-bio\"&gt;{{ author.bio }}&lt;/p&gt;\n            {% endif %}\n\n            &lt;!-- \u793e\u4ea4\u94fe\u63a5 --&gt;\n            {% if author.social %}\n            &lt;div class=\"author-social\"&gt;\n                {% for platform, username in author.social.items() %}\n                &lt;a href=\"https://{{ platform }}.com/{{ username }}\" \n                   target=\"_blank\"\n                   class=\"social-link\"&gt;\n                    {% include \".icons/material/\" ~ platform ~ \".svg\" %}\n                &lt;/a&gt;\n                {% endfor %}\n            &lt;/div&gt;\n            {% endif %}\n        &lt;/div&gt;\n    &lt;/div&gt;\n    {% endfor %}\n&lt;/div&gt;\n</code></pre> <ol> <li>\u4f5c\u8005\u4fe1\u606f\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/author.css */\n.page-authors {\n    margin: 2rem 0;\n    display: grid;\n    grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));\n    gap: 1rem;\n}\n\n.author-card {\n    display: flex;\n    padding: 1rem;\n    background: var(--md-code-bg-color);\n    border-radius: 8px;\n    transition: transform 0.2s ease;\n}\n\n.author-card:hover {\n    transform: translateY(-2px);\n}\n\n.author-avatar {\n    flex: 0 0 80px;\n    margin-right: 1rem;\n}\n\n.author-avatar img {\n    width: 80px;\n    height: 80px;\n    border-radius: 50%;\n    object-fit: cover;\n}\n\n.avatar-placeholder {\n    width: 80px;\n    height: 80px;\n    border-radius: 50%;\n    background: var(--md-accent-fg-color);\n    color: white;\n    display: flex;\n    align-items: center;\n    justify-content: center;\n    font-size: 2rem;\n}\n\n.author-info {\n    flex: 1;\n}\n\n.author-name {\n    margin: 0 0 0.5rem;\n    font-size: 1.1rem;\n}\n\n.author-bio {\n    color: var(--md-default-fg-color--light);\n    font-size: 0.9rem;\n    margin: 0 0 0.5rem;\n}\n\n.author-social {\n    display: flex;\n    gap: 0.5rem;\n}\n\n.social-link {\n    color: var(--md-default-fg-color--light);\n    transition: color 0.2s ease;\n}\n\n.social-link:hover {\n    color: var(--md-accent-fg-color);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#822-minify","title":"8.2.2 minify","text":""},{"location":"Tools/Blog/Mkdocs_Material/#8221-html","title":"8.2.2.1 HTML \u538b\u7f29","text":"<ol> <li>\u5b89\u88c5\u63d2\u4ef6\uff1a</li> </ol> Bash<pre><code>pip install mkdocs-minify-plugin\n</code></pre> <ol> <li>\u914d\u7f6e\u538b\u7f29\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nplugins:\n  - minify:\n      minify_html: true\n      htmlmin_opts:\n          # HTML\u538b\u7f29\u9009\u9879\n          remove_comments: true  # \u79fb\u9664\u6ce8\u91ca\n          remove_empty_space: true  # \u79fb\u9664\u7a7a\u767d\n          remove_all_empty_space: true  # \u79fb\u9664\u6240\u6709\u7a7a\u767d\n          reduce_boolean_attributes: true  # \u7b80\u5316\u5e03\u5c14\u5c5e\u6027\n          remove_optional_tags: false  # \u4fdd\u7559\u53ef\u9009\u6807\u7b7e\n          remove_redundant_attributes: true  # \u79fb\u9664\u5197\u4f59\u5c5e\u6027\n          minify_js: true  # \u538b\u7f29\u5185\u8054JS\n          minify_css: true  # \u538b\u7f29\u5185\u8054CSS\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8222-css","title":"8.2.2.2 CSS \u538b\u7f29","text":"<ol> <li>CSS \u538b\u7f29\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>plugins:\n  - minify:\n      minify_css: true\n      css_files:\n          - stylesheets/extra.css\n          - stylesheets/custom.css\n      cssmin_opts:\n          # CSS\u538b\u7f29\u9009\u9879\n          level: 2  # \u538b\u7f29\u7ea7\u522b(1-2)\n          compatibility: ie9  # \u517c\u5bb9\u6027\n          format: beautify  # \u683c\u5f0f\u5316\u8f93\u51fa\n</code></pre> <ol> <li>CSS \u4f18\u5316\u811a\u672c\uff1a</li> </ol> Python<pre><code># docs/tools/css_optimizer.py\nimport re\nfrom pathlib import Path\nfrom csscompressor import compress\n\nclass CSSOptimizer:\n    def __init__(self, input_dir, output_dir):\n        self.input_dir = Path(input_dir)\n        self.output_dir = Path(output_dir)\n        self.output_dir.mkdir(exist_ok=True)\n\n    def optimize(self):\n        \"\"\"\u4f18\u5316\u6240\u6709CSS\u6587\u4ef6\"\"\"\n        for css_file in self.input_dir.glob('**/*.css'):\n            # \u8bfb\u53d6CSS\u5185\u5bb9\n            content = css_file.read_text(encoding='utf-8')\n\n            # \u4f18\u5316CSS\n            optimized = self.optimize_css(content)\n\n            # \u4fdd\u5b58\u4f18\u5316\u540e\u7684\u6587\u4ef6\n            output_file = self.output_dir / css_file.name\n            output_file.write_text(optimized, encoding='utf-8')\n\n    def optimize_css(self, content):\n        \"\"\"\u4f18\u5316\u5355\u4e2aCSS\u6587\u4ef6\u5185\u5bb9\"\"\"\n        # \u79fb\u9664\u6ce8\u91ca\n        content = re.sub(r'/\\*[\\s\\S]*?\\*/', '', content)\n\n        # \u79fb\u9664\u591a\u4f59\u7a7a\u767d\n        content = re.sub(r'\\s+', ' ', content)\n\n        # \u538b\u7f29CSS\n        content = compress(content)\n\n        return content\n\n# \u4f7f\u7528\u4f18\u5316\u5668\noptimizer = CSSOptimizer(\n    input_dir='docs/stylesheets',\n    output_dir='docs/stylesheets/min'\n)\noptimizer.optimize()\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8223-js","title":"8.2.2.3 JS \u538b\u7f29","text":"<ol> <li>JS \u538b\u7f29\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>plugins:\n  - minify:\n      minify_js: true\n      js_files:\n          - javascripts/extra.js\n          - javascripts/custom.js\n      jsmin_opts:\n          # JS\u538b\u7f29\u9009\u9879\n          mangle: true  # \u6df7\u6dc6\u53d8\u91cf\u540d\n          compress: true  # \u538b\u7f29\u4ee3\u7801\n          output:\n              beautify: false  # \u4e0d\u7f8e\u5316\u8f93\u51fa\n</code></pre> <ol> <li>JS \u4f18\u5316\u811a\u672c\uff1a</li> </ol> Python<pre><code># docs/tools/js_optimizer.py\nimport re\nfrom pathlib import Path\nimport terser\n\nclass JSOptimizer:\n    def __init__(self, input_dir, output_dir):\n        self.input_dir = Path(input_dir)\n        self.output_dir = Path(output_dir)\n        self.output_dir.mkdir(exist_ok=True)\n\n    def optimize(self):\n        \"\"\"\u4f18\u5316\u6240\u6709JS\u6587\u4ef6\"\"\"\n        for js_file in self.input_dir.glob('**/*.js'):\n            # \u8bfb\u53d6JS\u5185\u5bb9\n            content = js_file.read_text(encoding='utf-8')\n\n            # \u4f18\u5316JS\n            optimized = self.optimize_js(content)\n\n            # \u4fdd\u5b58\u4f18\u5316\u540e\u7684\u6587\u4ef6\n            output_file = self.output_dir / js_file.name\n            output_file.write_text(optimized, encoding='utf-8')\n\n    def optimize_js(self, content):\n        \"\"\"\u4f18\u5316\u5355\u4e2aJS\u6587\u4ef6\u5185\u5bb9\"\"\"\n        options = {\n            'compress': {\n                'pure_funcs': ['console.log'],  # \u79fb\u9664console.log\n                'drop_debugger': True,          # \u79fb\u9664debugger\n                'unsafe': True,                 # \u542f\u7528\u4e0d\u5b89\u5168\u4f18\u5316\n                'passes': 2                     # \u4f18\u5316\u6b21\u6570\n            },\n            'mangle': {\n                'toplevel': True,              # \u6df7\u6dc6\u9876\u7ea7\u4f5c\u7528\u57df\n                'eval': True                   # \u6df7\u6dc6eval\u4e2d\u7684\u53d8\u91cf\n            }\n        }\n\n        # \u4f7f\u7528terser\u538b\u7f29\n        result = terser.minify(content, options)\n        return result['code']\n\n# \u4f7f\u7528\u4f18\u5316\u5668\noptimizer = JSOptimizer(\n    input_dir='docs/javascripts',\n    output_dir='docs/javascripts/min'\n)\noptimizer.optimize()\n</code></pre> <p>\u8fd9\u4e9b\u914d\u7f6e\u548c\u811a\u672c\u53ef\u4ee5\u6709\u6548\u51cf\u5c0f\u7ad9\u70b9\u8d44\u6e90\u5927\u5c0f\uff0c\u63d0\u5347\u52a0\u8f7d\u901f\u5ea6\u3002\u8bb0\u5f97\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u4f7f\u7528\u538b\u7f29\u540e\u7684\u8d44\u6e90\u3002</p>"},{"location":"Tools/Blog/Mkdocs_Material/#823-social","title":"8.2.3 social","text":""},{"location":"Tools/Blog/Mkdocs_Material/#8231","title":"8.2.3.1 \u793e\u4ea4\u94fe\u63a5","text":"<ol> <li>\u5b89\u88c5\u63d2\u4ef6\uff1a</li> </ol> Bash<pre><code>pip install mkdocs-social-plugin\n</code></pre> <ol> <li>\u57fa\u7840\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nplugins:\n  - social:\n      enabled: true\n      # \u793e\u4ea4\u5e73\u53f0\u914d\u7f6e\n      cards: true           # \u542f\u7528\u793e\u4ea4\u5361\u7247\n      cards_color:          # \u5361\u7247\u989c\u8272\n          fill: \"#0FF1CE\"   # \u80cc\u666f\u8272\n          text: \"#FFFFFF\"   # \u6587\u5b57\u8272\n      cards_font: Roboto    # \u5361\u7247\u5b57\u4f53\n\nextra:\n  social:\n    - icon: material/github\n      link: https://github.com/username\n      name: GitHub\n    - icon: material/twitter\n      link: https://twitter.com/username\n      name: Twitter\n    - icon: material/linkedin\n      link: https://linkedin.com/in/username\n      name: LinkedIn\n</code></pre> <ol> <li>\u793e\u4ea4\u94fe\u63a5\u6a21\u677f\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/social.html --&gt;\n{% if config.extra.social %}\n&lt;div class=\"social-links\"&gt;\n    {% for social in config.extra.social %}\n    &lt;a href=\"{{ social.link }}\" \n       target=\"_blank\"\n       rel=\"noopener\"\n       title=\"{{ social.name }}\"\n       class=\"social-link\"&gt;\n        &lt;span class=\"social-icon\"&gt;\n            {% include \".icons/\" ~ social.icon ~ \".svg\" %}\n        &lt;/span&gt;\n        &lt;span class=\"social-name\"&gt;{{ social.name }}&lt;/span&gt;\n    &lt;/a&gt;\n    {% endfor %}\n&lt;/div&gt;\n{% endif %}\n</code></pre> <p>\u6837\u5f0f\u914d\u7f6e\uff1a</p> CSS<pre><code>/* docs/stylesheets/social.css */\n.social-links {\n    display: flex;\n    gap: 1rem;\n    margin: 2rem 0;\n}\n\n.social-link {\n    display: flex;\n    align-items: center;\n    padding: 0.5rem 1rem;\n    color: var(--md-default-fg-color);\n    text-decoration: none;\n    background: var(--md-code-bg-color);\n    border-radius: 2rem;\n    transition: all 0.2s ease;\n}\n\n.social-link:hover {\n    transform: translateY(-2px);\n    color: var(--md-accent-fg-color);\n    background: var(--md-code-bg-color--light);\n}\n\n.social-icon {\n    margin-right: 0.5rem;\n    width: 1.2rem;\n    height: 1.2rem;\n}\n\n.social-name {\n    font-size: 0.9rem;\n}\n\n/* \u52a8\u753b\u6548\u679c */\n.social-link .social-icon {\n    transition: transform 0.2s ease;\n}\n\n.social-link:hover .social-icon {\n    transform: scale(1.2);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8232","title":"8.2.3.2 \u5206\u4eab\u529f\u80fd","text":"<ol> <li>\u5206\u4eab\u529f\u80fd\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nextra:\n  social_share:\n    - platform: twitter\n      text: \u5206\u4eab\u5230 Twitter\n      icon: material/twitter\n    - platform: facebook\n      text: \u5206\u4eab\u5230 Facebook\n      icon: material/facebook\n    - platform: linkedin\n      text: \u5206\u4eab\u5230 LinkedIn\n      icon: material/linkedin\n    - platform: weibo\n      text: \u5206\u4eab\u5230\u5fae\u535a\n      icon: material/sina-weibo\n</code></pre> <ol> <li>\u5206\u4eab\u529f\u80fd\u5b9e\u73b0\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/share.html --&gt;\n&lt;div class=\"page-share\"&gt;\n    &lt;h4&gt;\u5206\u4eab\u6587\u7ae0&lt;/h4&gt;\n    &lt;div class=\"share-buttons\"&gt;\n        {% for share in config.extra.social_share %}\n        &lt;button class=\"share-button\" \n                data-platform=\"{{ share.platform }}\"\n                onclick=\"shareContent('{{ share.platform }}')\"&gt;\n            &lt;span class=\"share-icon\"&gt;\n                {% include \".icons/\" ~ share.icon ~ \".svg\" %}\n            &lt;/span&gt;\n            &lt;span class=\"share-text\"&gt;{{ share.text }}&lt;/span&gt;\n        &lt;/button&gt;\n        {% endfor %}\n    &lt;/div&gt;\n&lt;/div&gt;\n\n&lt;script&gt;\nfunction shareContent(platform) {\n    const url = encodeURIComponent(window.location.href);\n    const title = encodeURIComponent(document.title);\n    const text = encodeURIComponent(document.querySelector('meta[name=\"description\"]')?.content || '');\n\n    let shareUrl;\n    switch(platform) {\n        case 'twitter':\n            shareUrl = `https://twitter.com/intent/tweet?url=${url}&amp;text=${title}`;\n            break;\n        case 'facebook':\n            shareUrl = `https://www.facebook.com/sharer/sharer.php?u=${url}`;\n            break;\n        case 'linkedin':\n            shareUrl = `https://www.linkedin.com/sharing/share-offsite/?url=${url}`;\n            break;\n        case 'weibo':\n            shareUrl = `http://service.weibo.com/share/share.php?url=${url}&amp;title=${title}`;\n            break;\n    }\n\n    window.open(shareUrl, '_blank', 'width=600,height=400');\n}\n&lt;/script&gt;\n</code></pre> <ol> <li>\u5206\u4eab\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/share.css */\n.page-share {\n    margin: 2rem 0;\n    padding: 1rem;\n    background: var(--md-code-bg-color);\n    border-radius: 8px;\n}\n\n.share-buttons {\n    display: flex;\n    flex-wrap: wrap;\n    gap: 0.5rem;\n    margin-top: 1rem;\n}\n\n.share-button {\n    display: flex;\n    align-items: center;\n    padding: 0.5rem 1rem;\n    border: none;\n    border-radius: 2rem;\n    background: var(--md-default-bg-color);\n    color: var(--md-default-fg-color);\n    cursor: pointer;\n    transition: all 0.2s ease;\n}\n\n.share-button:hover {\n    background: var(--md-accent-fg-color);\n    color: white;\n}\n\n.share-icon {\n    margin-right: 0.5rem;\n    width: 1.2rem;\n    height: 1.2rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8233","title":"8.2.3.3 \u5173\u6ce8\u6309\u94ae","text":"<ol> <li>\u5173\u6ce8\u6309\u94ae\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>extra:\n  follow_buttons:\n    - platform: github\n      username: your-username\n      icon: material/github\n      text: \u5173\u6ce8\u6211\u7684 GitHub\n    - platform: twitter\n      username: your-username\n      icon: material/twitter\n      text: \u5173\u6ce8\u6211\u7684 Twitter\n</code></pre> <ol> <li>\u5173\u6ce8\u6309\u94ae\u5b9e\u73b0\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/follow.html --&gt;\n&lt;div class=\"follow-buttons\"&gt;\n    {% for btn in config.extra.follow_buttons %}\n    &lt;a href=\"https://{{ btn.platform }}.com/{{ btn.username }}\"\n       target=\"_blank\"\n       class=\"follow-button\"\n       data-platform=\"{{ btn.platform }}\"&gt;\n        &lt;span class=\"follow-icon\"&gt;\n            {% include \".icons/\" ~ btn.icon ~ \".svg\" %}\n        &lt;/span&gt;\n        &lt;span class=\"follow-text\"&gt;{{ btn.text }}&lt;/span&gt;\n        &lt;span class=\"follow-count\" id=\"{{ btn.platform }}-count\"&gt;\n            &lt;!-- \u5c06\u901a\u8fc7API\u52a8\u6001\u66f4\u65b0 --&gt;\n        &lt;/span&gt;\n    &lt;/a&gt;\n    {% endfor %}\n&lt;/div&gt;\n\n&lt;script&gt;\nasync function updateFollowCounts() {\n    const buttons = document.querySelectorAll('.follow-button');\n\n    for (const button of buttons) {\n        const platform = button.dataset.platform;\n        const username = button.href.split('/').pop();\n\n        // \u83b7\u53d6\u5173\u6ce8\u6570\n        const count = await getFollowCount(platform, username);\n\n        // \u66f4\u65b0\u663e\u793a\n        const countElement = button.querySelector('.follow-count');\n        if (countElement &amp;&amp; count) {\n            countElement.textContent = formatCount(count);\n        }\n    }\n}\n\nasync function getFollowCount(platform, username) {\n    switch (platform) {\n        case 'github':\n            const response = await fetch(`https://api.github.com/users/${username}`);\n            const data = await response.json();\n            return data.followers;\n\n        // \u5176\u4ed6\u5e73\u53f0API\u5b9e\u73b0...\n        default:\n            return null;\n    }\n}\n\nfunction formatCount(count) {\n    if (count &gt;= 1000000) {\n        return (count / 1000000).toFixed(1) + 'M';\n    }\n    if (count &gt;= 1000) {\n        return (count / 1000).toFixed(1) + 'K';\n    }\n    return count.toString();\n}\n\n// \u521d\u59cb\u5316\nupdateFollowCounts();\n&lt;/script&gt;\n</code></pre> <ol> <li>\u5173\u6ce8\u6309\u94ae\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/follow.css */\n.follow-buttons {\n    display: flex;\n    flex-wrap: wrap;\n    gap: 1rem;\n    margin: 2rem 0;\n}\n\n.follow-button {\n    display: flex;\n    align-items: center;\n    padding: 0.5rem 1rem;\n    text-decoration: none;\n    background: var(--md-code-bg-color);\n    border-radius: 2rem;\n    transition: all 0.2s ease;\n}\n\n.follow-button:hover {\n    transform: translateY(-2px);\n}\n\n/* \u5e73\u53f0\u7279\u5b9a\u6837\u5f0f */\n.follow-button[data-platform=\"github\"] {\n    color: #333;\n}\n\n.follow-button[data-platform=\"github\"]:hover {\n    background: #333;\n    color: white;\n}\n\n.follow-button[data-platform=\"twitter\"] {\n    color: #1DA1F2;\n}\n\n.follow-button[data-platform=\"twitter\"]:hover {\n    background: #1DA1F2;\n    color: white;\n}\n\n.follow-icon {\n    margin-right: 0.5rem;\n    width: 1.2rem;\n    height: 1.2rem;\n}\n\n.follow-count {\n    margin-left: 0.5rem;\n    padding: 0.2rem 0.5rem;\n    background: rgba(0, 0, 0, 0.1);\n    border-radius: 1rem;\n    font-size: 0.8rem;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#824-tags","title":"8.2.4 tags","text":""},{"location":"Tools/Blog/Mkdocs_Material/#8241","title":"8.2.4.1 \u6807\u7b7e\u7cfb\u7edf","text":"<ol> <li>\u5b89\u88c5\u63d2\u4ef6\uff1a</li> </ol> Bash<pre><code>pip install mkdocs-tags-plugin\n</code></pre> <ol> <li>\u914d\u7f6e\u6807\u7b7e\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nplugins:\n  - tags:\n      tags_file: tags.md\n      tags_allowed:  # \u5141\u8bb8\u7684\u6807\u7b7e\u5217\u8868\n        - Python\n        - JavaScript\n        - CSS\n        - HTML\n      tags_extra_files:\n        cloud: tag_cloud.md    # \u6807\u7b7e\u4e91\u9875\u9762\n        list: tag_list.md      # \u6807\u7b7e\u5217\u8868\u9875\u9762\n</code></pre> <ol> <li>\u5728\u6587\u6863\u4e2d\u4f7f\u7528\u6807\u7b7e\uff1a</li> </ol> Markdown<pre><code>---\ntags:\n  - Python\n  - \u6559\u7a0b\n---\n\n# Python \u5165\u95e8\u6559\u7a0b\n</code></pre> <ol> <li>\u6807\u7b7e\u663e\u793a\u7ec4\u4ef6\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/tags.html --&gt;\n{% if page.meta.tags %}\n&lt;div class=\"page-tags\"&gt;\n    {% for tag in page.meta.tags %}\n    &lt;a href=\"{{ base_url }}/tags/#{{ tag|lower }}\" class=\"tag\"&gt;\n        &lt;span class=\"tag-icon\"&gt;\n            {% include \".icons/material/tag.svg\" %}\n        &lt;/span&gt;\n        &lt;span class=\"tag-text\"&gt;{{ tag }}&lt;/span&gt;\n    &lt;/a&gt;\n    {% endfor %}\n&lt;/div&gt;\n{% endif %}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8242","title":"8.2.4.2 \u6807\u7b7e\u4e91","text":"<ol> <li>\u6807\u7b7e\u4e91\u5b9e\u73b0\uff1a</li> </ol> Python<pre><code># docs/plugins/tags/cloud.py\nfrom collections import Counter\nimport math\n\nclass TagCloud:\n    def __init__(self, tags):\n        self.tags = Counter(tags)\n        self.min_size = 0.8\n        self.max_size = 2.0\n\n    def get_tag_sizes(self):\n        \"\"\"\u8ba1\u7b97\u6807\u7b7e\u5927\u5c0f\"\"\"\n        if not self.tags:\n            return {}\n\n        # \u83b7\u53d6\u6700\u5927\u548c\u6700\u5c0f\u9891\u7387\n        max_freq = max(self.tags.values())\n        min_freq = min(self.tags.values())\n\n        # \u8ba1\u7b97\u6bcf\u4e2a\u6807\u7b7e\u7684\u5927\u5c0f\n        sizes = {}\n        for tag, freq in self.tags.items():\n            if max_freq == min_freq:\n                sizes[tag] = (self.max_size + self.min_size) / 2\n            else:\n                size = self.min_size + (self.max_size - self.min_size) * \\\n                       ((freq - min_freq) / (max_freq - min_freq))\n                sizes[tag] = round(size, 2)\n\n        return sizes\n\ndef generate_tag_cloud(tags):\n    \"\"\"\u751f\u6210\u6807\u7b7e\u4e91HTML\"\"\"\n    cloud = TagCloud(tags)\n    sizes = cloud.get_tag_sizes()\n\n    html = ['&lt;div class=\"tag-cloud\"&gt;']\n\n    for tag, size in sizes.items():\n        html.append(f'''\n            &lt;a href=\"#tag-{tag.lower()}\" \n               class=\"tag-cloud-item\"\n               style=\"font-size: {size}rem\"&gt;\n                {tag}\n            &lt;/a&gt;\n        ''')\n\n    html.append('&lt;/div&gt;')\n    return '\\n'.join(html)\n</code></pre> <ol> <li>\u6807\u7b7e\u4e91\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/tags.css */\n.tag-cloud {\n    display: flex;\n    flex-wrap: wrap;\n    justify-content: center;\n    gap: 1rem;\n    padding: 2rem;\n}\n\n.tag-cloud-item {\n    color: var(--md-default-fg-color);\n    text-decoration: none;\n    padding: 0.5rem 1rem;\n    border-radius: 2rem;\n    background: var(--md-code-bg-color);\n    transition: all 0.2s ease;\n}\n\n.tag-cloud-item:hover {\n    transform: scale(1.1);\n    background: var(--md-accent-fg-color);\n    color: white;\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#8243","title":"8.2.4.3 \u6807\u7b7e\u9875\u9762","text":"<ol> <li>\u6807\u7b7e\u5217\u8868\u9875\u9762\uff1a</li> </ol> Markdown<pre><code># \u6807\u7b7e\u7d22\u5f15\n\n## \u6807\u7b7e\u4e91\n[TAGS_CLOUD]\n\n## \u6807\u7b7e\u5217\u8868\n[TAGS_LIST]\n</code></pre> <ol> <li>\u6807\u7b7e\u9875\u9762\u751f\u6210\u5668\uff1a</li> </ol> Python<pre><code># docs/plugins/tags/generator.py\nfrom pathlib import Path\nimport yaml\n\nclass TagPageGenerator:\n    def __init__(self, config):\n        self.config = config\n        self.tags = {}\n\n    def collect_tags(self):\n        \"\"\"\u6536\u96c6\u6240\u6709\u6807\u7b7e\"\"\"\n        docs_dir = Path(self.config['docs_dir'])\n\n        for md_file in docs_dir.glob('**/*.md'):\n            # \u8bfb\u53d6\u6587\u4ef6frontmatter\n            content = md_file.read_text(encoding='utf-8')\n            if content.startswith('---'):\n                try:\n                    # \u89e3\u6790frontmatter\n                    _, frontmatter, _ = content.split('---', 2)\n                    meta = yaml.safe_load(frontmatter)\n\n                    if 'tags' in meta:\n                        # \u83b7\u53d6\u76f8\u5bf9\u8def\u5f84\n                        rel_path = md_file.relative_to(docs_dir)\n                        url = str(rel_path).replace('\\\\', '/')[:-3]  # \u79fb\u9664.md\n\n                        # \u6dfb\u52a0\u5230\u6807\u7b7e\u7d22\u5f15\n                        for tag in meta['tags']:\n                            if tag not in self.tags:\n                                self.tags[tag] = []\n                            self.tags[tag].append({\n                                'title': meta.get('title', url),\n                                'url': url,\n                                'description': meta.get('description', '')\n                            })\n                except:\n                    continue\n\n    def generate_tag_pages(self):\n        \"\"\"\u751f\u6210\u6807\u7b7e\u76f8\u5173\u9875\u9762\"\"\"\n        self.collect_tags()\n\n        # \u751f\u6210\u6807\u7b7e\u5217\u8868\u9875\u9762\n        if 'list' in self.config['tags_extra_files']:\n            self.generate_list_page()\n\n        # \u751f\u6210\u6bcf\u4e2a\u6807\u7b7e\u7684\u8be6\u60c5\u9875\u9762\n        self.generate_tag_detail_pages()\n\n    def generate_list_page(self):\n        \"\"\"\u751f\u6210\u6807\u7b7e\u5217\u8868\u9875\u9762\"\"\"\n        template = \"\"\"\n# \u6807\u7b7e\u5217\u8868\n\n{% for tag, posts in tags.items() %}\n## {{ tag }}\n\n{% for post in posts %}\n- [{{ post.title }}]({{ post.url }}){% if post.description %} - {{ post.description }}{% endif %}\n{% endfor %}\n\n{% endfor %}\n\"\"\"\n        # \u4f7f\u7528 Jinja2 \u6e32\u67d3\u6a21\u677f\n        from jinja2 import Template\n        content = Template(template).render(tags=self.tags)\n\n        # \u4fdd\u5b58\u9875\u9762\n        output_file = Path(self.config['docs_dir']) / 'tags' / 'list.md'\n        output_file.parent.mkdir(exist_ok=True)\n        output_file.write_text(content, encoding='utf-8')\n\n    def generate_tag_detail_pages(self):\n        \"\"\"\u751f\u6210\u6bcf\u4e2a\u6807\u7b7e\u7684\u8be6\u60c5\u9875\u9762\"\"\"\n        template = \"\"\"\n# \u6807\u7b7e: {{ tag }}\n\n## \u76f8\u5173\u6587\u7ae0\n\n{% for post in posts %}\n### [{{ post.title }}]({{ post.url }})\n{% if post.description %}\n{{ post.description }}\n{% endif %}\n{% endfor %}\n\n## \u76f8\u5173\u6807\u7b7e\n{% for related_tag in related_tags %}\n- [{{ related_tag }}](../{{ related_tag | lower }})\n{% endfor %}\n\"\"\"\n        # \u6807\u7b7e\u76ee\u5f55\n        tags_dir = Path(self.config['docs_dir']) / 'tags'\n        tags_dir.mkdir(exist_ok=True)\n\n        # \u4e3a\u6bcf\u4e2a\u6807\u7b7e\u751f\u6210\u9875\u9762\n        for tag, posts in self.tags.items():\n            # \u67e5\u627e\u76f8\u5173\u6807\u7b7e\n            related_tags = self.find_related_tags(tag)\n\n            # \u6e32\u67d3\u5185\u5bb9\n            content = Template(template).render(\n                tag=tag,\n                posts=posts,\n                related_tags=related_tags\n            )\n\n            # \u4fdd\u5b58\u9875\u9762\n            output_file = tags_dir / f\"{tag.lower()}.md\"\n            output_file.write_text(content, encoding='utf-8')\n\n    def find_related_tags(self, current_tag):\n        \"\"\"\u67e5\u627e\u76f8\u5173\u6807\u7b7e\"\"\"\n        related = set()\n\n        # \u83b7\u53d6\u5f53\u524d\u6807\u7b7e\u7684\u6240\u6709\u6587\u7ae0\n        current_posts = self.tags[current_tag]\n\n        # \u904d\u5386\u6240\u6709\u5176\u4ed6\u6807\u7b7e\n        for tag, posts in self.tags.items():\n            if tag == current_tag:\n                continue\n\n            # \u8ba1\u7b97\u6587\u7ae0\u4ea4\u96c6\n            intersection = set(p['url'] for p in posts) &amp; \\\n                          set(p['url'] for p in current_posts)\n\n            # \u5982\u679c\u6709\u5171\u540c\u6587\u7ae0\uff0c\u8ba4\u4e3a\u662f\u76f8\u5173\u6807\u7b7e\n            if intersection:\n                related.add(tag)\n\n        return list(related)\n</code></pre> <ol> <li>\u6807\u7b7e\u9875\u9762\u6837\u5f0f\uff1a</li> </ol> CSS<pre><code>/* docs/stylesheets/tags-page.css */\n/* \u6807\u7b7e\u5217\u8868\u9875\u9762 */\n.tags-list {\n    margin: 2rem 0;\n}\n\n.tag-section {\n    margin-bottom: 3rem;\n}\n\n.tag-section h2 {\n    color: var(--md-accent-fg-color);\n    border-bottom: 2px solid var(--md-accent-fg-color);\n    padding-bottom: 0.5rem;\n}\n\n.tag-section .post-list {\n    margin-left: 1rem;\n}\n\n.post-list-item {\n    margin: 1rem 0;\n}\n\n.post-list-item .post-title {\n    font-weight: 500;\n    color: var(--md-default-fg-color);\n    text-decoration: none;\n}\n\n.post-list-item .post-description {\n    font-size: 0.9rem;\n    color: var(--md-default-fg-color--light);\n    margin-top: 0.2rem;\n}\n\n/* \u6807\u7b7e\u8be6\u60c5\u9875\u9762 */\n.tag-detail {\n    padding: 2rem;\n}\n\n.tag-detail-header {\n    text-align: center;\n    margin-bottom: 3rem;\n}\n\n.tag-detail-title {\n    font-size: 2rem;\n    color: var(--md-primary-fg-color);\n}\n\n.tag-detail-count {\n    color: var(--md-default-fg-color--light);\n}\n\n.related-posts {\n    margin: 2rem 0;\n}\n\n.related-post {\n    padding: 1rem;\n    margin: 1rem 0;\n    background: var(--md-code-bg-color);\n    border-radius: 8px;\n    transition: transform 0.2s ease;\n}\n\n.related-post:hover {\n    transform: translateX(0.5rem);\n}\n\n.related-tags {\n    display: flex;\n    flex-wrap: wrap;\n    gap: 0.5rem;\n    margin: 2rem 0;\n}\n\n.related-tag {\n    padding: 0.2rem 0.8rem;\n    background: var(--md-code-bg-color);\n    border-radius: 2rem;\n    font-size: 0.9rem;\n    color: var(--md-default-fg-color);\n    text-decoration: none;\n    transition: all 0.2s ease;\n}\n\n.related-tag:hover {\n    background: var(--md-accent-fg-color);\n    color: white;\n}\n</code></pre> <ol> <li>\u9875\u9762\u4ea4\u4e92\u529f\u80fd\uff1a</li> </ol> JavaScript<pre><code>// docs/javascripts/tags.js\nclass TagsManager {\n    constructor() {\n        this.initializeFilters();\n        this.setupSearch();\n        this.setupSorting();\n    }\n\n    initializeFilters() {\n        const tagList = document.querySelector('.tags-list');\n        if (!tagList) return;\n\n        // \u521b\u5efa\u8fc7\u6ee4\u5668\n        const filterContainer = document.createElement('div');\n        filterContainer.className = 'tags-filter';\n        filterContainer.innerHTML = `\n            &lt;input type=\"text\" \n                   class=\"filter-input\" \n                   placeholder=\"\u641c\u7d22\u6807\u7b7e...\"&gt;\n            &lt;select class=\"sort-select\"&gt;\n                &lt;option value=\"name\"&gt;\u6309\u540d\u79f0\u6392\u5e8f&lt;/option&gt;\n                &lt;option value=\"count\"&gt;\u6309\u6587\u7ae0\u6570\u91cf\u6392\u5e8f&lt;/option&gt;\n            &lt;/select&gt;\n        `;\n\n        tagList.insertBefore(filterContainer, tagList.firstChild);\n    }\n\n    setupSearch() {\n        const input = document.querySelector('.filter-input');\n        if (!input) return;\n\n        input.addEventListener('input', () =&gt; {\n            const query = input.value.toLowerCase();\n            const sections = document.querySelectorAll('.tag-section');\n\n            sections.forEach(section =&gt; {\n                const tag = section.querySelector('h2').textContent.toLowerCase();\n                section.style.display = tag.includes(query) ? 'block' : 'none';\n            });\n        });\n    }\n\n    setupSorting() {\n        const select = document.querySelector('.sort-select');\n        if (!select) return;\n\n        select.addEventListener('change', () =&gt; {\n            const sections = Array.from(document.querySelectorAll('.tag-section'));\n            const container = sections[0].parentElement;\n\n            sections.sort((a, b) =&gt; {\n                const aTag = a.querySelector('h2').textContent;\n                const bTag = b.querySelector('h2').textContent;\n                const aCount = this.getPostCount(a);\n                const bCount = this.getPostCount(b);\n\n                if (select.value === 'name') {\n                    return aTag.localeCompare(bTag);\n                } else {\n                    return bCount - aCount;\n                }\n            });\n\n            // \u91cd\u65b0\u63d2\u5165\u6392\u5e8f\u540e\u7684\u7ae0\u8282\n            sections.forEach(section =&gt; container.appendChild(section));\n        });\n    }\n\n    getPostCount(section) {\n        return section.querySelectorAll('.post-list-item').length;\n    }\n}\n\n// \u521d\u59cb\u5316\u6807\u7b7e\u7ba1\u7406\u5668\ndocument.addEventListener('DOMContentLoaded', () =&gt; {\n    new TagsManager();\n});\n</code></pre> <p>\u4f7f\u7528\u4ee5\u4e0a\u4ee3\u7801\uff0c\u4f60\u53ef\u4ee5\u5b9e\u73b0\u4e00\u4e2a\u529f\u80fd\u5b8c\u6574\u7684\u6807\u7b7e\u7cfb\u7edf\uff0c\u5305\u62ec\uff1a</p> <ol> <li>\u6807\u7b7e\u4e91\u53ef\u89c6\u5316</li> <li>\u6807\u7b7e\u5217\u8868\u6d4f\u89c8</li> <li>\u6807\u7b7e\u8be6\u60c5\u9875\u9762</li> <li>\u76f8\u5173\u6807\u7b7e\u63a8\u8350</li> <li>\u6807\u7b7e\u641c\u7d22\u548c\u6392\u5e8f</li> <li>\u54cd\u5e94\u5f0f\u5e03\u5c40</li> </ol> <p>\u914d\u7f6e\u6587\u4ef6\u9700\u8981\u6dfb\u52a0\u76f8\u5e94\u7684\u5f15\u7528\uff1a</p> YAML<pre><code># mkdocs.yml\nextra_css:\n  - stylesheets/tags.css\n  - stylesheets/tags-page.css\n\nextra_javascript:\n  - javascripts/tags.js\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#9","title":"9 \u529f\u80fd\u6269\u5c55","text":""},{"location":"Tools/Blog/Mkdocs_Material/#91","title":"9.1 \u8bc4\u8bba\u7cfb\u7edf","text":""},{"location":"Tools/Blog/Mkdocs_Material/#911-giscus","title":"9.1.1 Giscus \u914d\u7f6e","text":"<ol> <li>\u57fa\u7840\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nextra:\n  comments:\n    provider: giscus\n    repo: username/repo\n    repo_id: your_repo_id\n    category: Comments\n    category_id: your_category_id\n</code></pre> <ol> <li>Giscus \u7ec4\u4ef6\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/comments.html --&gt;\n{% if config.extra.comments.provider == 'giscus' %}\n&lt;div class=\"comments-container\"&gt;\n    &lt;h3&gt;\u8bc4\u8bba&lt;/h3&gt;\n    &lt;div class=\"giscus\"&gt;&lt;/div&gt;\n\n    &lt;script&gt;\n        function loadGiscus() {\n            const script = document.createElement('script');\n            script.src = 'https://giscus.app/client.js';\n            script.setAttribute('data-repo', '{{ config.extra.comments.repo }}');\n            script.setAttribute('data-repo-id', '{{ config.extra.comments.repo_id }}');\n            script.setAttribute('data-category', '{{ config.extra.comments.category }}');\n            script.setAttribute('data-category-id', '{{ config.extra.comments.category_id }}');\n            script.setAttribute('data-mapping', 'pathname');\n            script.setAttribute('data-reactions-enabled', '1');\n            script.setAttribute('data-emit-metadata', '0');\n            script.setAttribute('data-theme', 'preferred_color_scheme');\n            script.setAttribute('crossorigin', 'anonymous');\n            script.async = true;\n\n            document.querySelector('.giscus').appendChild(script);\n        }\n\n        // \u5ef6\u8fdf\u52a0\u8f7d\u8bc4\u8bba\n        if ('IntersectionObserver' in window) {\n            const observer = new IntersectionObserver((entries) =&gt; {\n                if (entries[0].isIntersecting) {\n                    loadGiscus();\n                    observer.disconnect();\n                }\n            });\n\n            observer.observe(document.querySelector('.comments-container'));\n        } else {\n            loadGiscus();\n        }\n    &lt;/script&gt;\n&lt;/div&gt;\n{% endif %}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#912","title":"9.1.2 \u81ea\u5b9a\u4e49\u8bc4\u8bba\u6837\u5f0f","text":"CSS<pre><code>/* docs/stylesheets/comments.css */\n.comments-container {\n    margin: 3rem 0;\n    padding-top: 2rem;\n    border-top: 1px solid var(--md-default-fg-color--lightest);\n}\n\n.giscus {\n    width: 100%;\n}\n\n/* Giscus \u4e3b\u9898\u9002\u914d */\n.giscus-frame {\n    background-color: var(--md-default-bg-color);\n    color: var(--md-default-fg-color);\n}\n\n/* \u6697\u8272\u6a21\u5f0f\u9002\u914d */\n[data-md-color-scheme=\"slate\"] .giscus-frame {\n    background-color: var(--md-default-bg-color--dark);\n    color: var(--md-default-fg-color--dark);\n}\n\n/* \u8bc4\u8bba\u6846\u6837\u5f0f */\n.giscus .gsc-comment-box {\n    background-color: var(--md-code-bg-color);\n    border-radius: 8px;\n    padding: 1rem;\n}\n\n/* \u8bc4\u8bba\u5217\u8868\u6837\u5f0f */\n.giscus .gsc-comment {\n    margin: 1rem 0;\n    padding: 1rem;\n    background-color: var(--md-code-bg-color);\n    border-radius: 8px;\n    transition: transform 0.2s ease;\n}\n\n.giscus .gsc-comment:hover {\n    transform: translateX(4px);\n}\n\n/* \u6309\u94ae\u6837\u5f0f */\n.giscus .gsc-button {\n    background-color: var(--md-primary-fg-color);\n    color: var(--md-primary-bg-color);\n    border: none;\n    padding: 0.5rem 1rem;\n    border-radius: 4px;\n    cursor: pointer;\n    transition: all 0.2s ease;\n}\n\n.giscus .gsc-button:hover {\n    background-color: var(--md-primary-fg-color--dark);\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#92","title":"9.2 \u6570\u636e\u7edf\u8ba1","text":""},{"location":"Tools/Blog/Mkdocs_Material/#921-google-analytics","title":"9.2.1 Google Analytics","text":"<ol> <li>GA4 \u914d\u7f6e\uff1a</li> </ol> YAML<pre><code># mkdocs.yml\nextra:\n  analytics:\n    provider: google\n    property: G-XXXXXXXXXX\n\n    # \u4e8b\u4ef6\u8ffd\u8e2a\n    events: true\n    # \u7528\u6237\u884c\u4e3a\u8ffd\u8e2a\n    behavior: true\n</code></pre> <ol> <li>GA4 \u5b9e\u73b0\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/analytics.html --&gt;\n{% if config.extra.analytics.provider == 'google' %}\n&lt;!-- Google Analytics --&gt;\n&lt;script async src=\"https://www.googletagmanager.com/gtag/js?id={{ config.extra.analytics.property }}\"&gt;&lt;/script&gt;\n&lt;script&gt;\n  window.dataLayer = window.dataLayer || [];\n  function gtag(){dataLayer.push(arguments);}\n  gtag('js', new Date());\n  gtag('config', '{{ config.extra.analytics.property }}');\n\n  // \u4e8b\u4ef6\u8ffd\u8e2a\n  if ({{ config.extra.analytics.events|tojson }}) {\n      document.addEventListener('DOMContentLoaded', function() {\n          // \u70b9\u51fb\u4e8b\u4ef6\u8ffd\u8e2a\n          document.addEventListener('click', function(e) {\n              const target = e.target.closest('a');\n              if (target) {\n                  gtag('event', 'click', {\n                      'event_category': 'link',\n                      'event_label': target.href\n                  });\n              }\n          });\n\n          // \u6eda\u52a8\u4e8b\u4ef6\u8ffd\u8e2a\n          let lastScrollDepth = 0;\n          window.addEventListener('scroll', debounce(function() {\n              const scrollDepth = Math.round(\n                  (window.scrollY + window.innerHeight) / \n                  document.documentElement.scrollHeight * 100\n              );\n\n              if (scrollDepth &gt; lastScrollDepth) {\n                  gtag('event', 'scroll_depth', {\n                      'depth': scrollDepth\n                  });\n                  lastScrollDepth = scrollDepth;\n              }\n          }, 500));\n\n          // \u641c\u7d22\u4e8b\u4ef6\u8ffd\u8e2a\n          const searchInput = document.querySelector('.md-search__input');\n          if (searchInput) {\n              searchInput.addEventListener('search', function() {\n                  gtag('event', 'search', {\n                      'search_term': this.value\n                  });\n              });\n          }\n      });\n  }\n\n  // \u7528\u6237\u884c\u4e3a\u8ffd\u8e2a\n  if ({{ config.extra.analytics.behavior|tojson }}) {\n      // \u9875\u9762\u505c\u7559\u65f6\u95f4\n      let startTime = Date.now();\n      window.addEventListener('beforeunload', function() {\n          const duration = Math.round((Date.now() - startTime) / 1000);\n          gtag('event', 'time_on_page', {\n              'duration': duration\n          });\n      });\n\n      // \u590d\u5236\u884c\u4e3a\u8ffd\u8e2a\n      document.addEventListener('copy', function() {\n          gtag('event', 'content_copy');\n      });\n  }\n&lt;/script&gt;\n{% endif %}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#922","title":"9.2.2 \u4e0d\u849c\u5b50\u7edf\u8ba1","text":"<ol> <li>\u4e0d\u849c\u5b50\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>extra:\n  analytics:\n    busuanzi: true\n</code></pre> <ol> <li>\u4e0d\u849c\u5b50\u5b9e\u73b0\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/busuanzi.html --&gt;\n{% if config.extra.analytics.busuanzi %}\n&lt;script async src=\"//busuanzi.ibruce.info/busuanzi/2.3/busuanzi.pure.mini.js\"&gt;&lt;/script&gt;\n\n&lt;div class=\"page-views\"&gt;\n    &lt;!-- \u603b\u8bbf\u95ee\u91cf --&gt;\n    &lt;span id=\"busuanzi_container_site_pv\"&gt;\n        \u603b\u8bbf\u95ee\u91cf: &lt;span id=\"busuanzi_value_site_pv\"&gt;&lt;/span&gt;\u6b21\n    &lt;/span&gt;\n\n    &lt;!-- \u603b\u8bbf\u5ba2\u6570 --&gt;\n    &lt;span id=\"busuanzi_container_site_uv\"&gt;\n        \u8bbf\u5ba2\u6570: &lt;span id=\"busuanzi_value_site_uv\"&gt;&lt;/span&gt;\u4eba\n    &lt;/span&gt;\n\n    &lt;!-- \u9875\u9762\u8bbf\u95ee\u91cf --&gt;\n    &lt;span id=\"busuanzi_container_page_pv\"&gt;\n        \u672c\u6587\u8bbf\u95ee\u91cf: &lt;span id=\"busuanzi_value_page_pv\"&gt;&lt;/span&gt;\u6b21\n    &lt;/span&gt;\n&lt;/div&gt;\n\n&lt;style&gt;\n.page-views {\n    display: flex;\n    gap: 1rem;\n    margin: 1rem 0;\n    padding: 0.5rem;\n    background: var(--md-code-bg-color);\n    border-radius: 4px;\n    font-size: 0.9rem;\n}\n\n.page-views span {\n    color: var(--md-default-fg-color--light);\n}\n\n.page-views span span {\n    color: var(--md-accent-fg-color);\n    font-weight: bold;\n}\n&lt;/style&gt;\n{% endif %}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#93","title":"9.3 \u793e\u4ea4\u5206\u4eab","text":""},{"location":"Tools/Blog/Mkdocs_Material/#931","title":"9.3.1 \u5206\u4eab\u6309\u94ae","text":"<ol> <li>\u5206\u4eab\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>extra:\n  social_share:\n    enabled: true\n    platforms:\n      - name: twitter\n        icon: material/twitter\n        color: '#1DA1F2'\n      - name: facebook\n        icon: material/facebook\n        color: '#4267B2'\n      - name: linkedin\n        icon: material/linkedin\n        color: '#0A66C2'\n      - name: weibo\n        icon: material/sina-weibo\n        color: '#E6162D'\n</code></pre> <ol> <li>\u5206\u4eab\u6309\u94ae\u5b9e\u73b0\uff1a</li> </ol> HTML<pre><code>&lt;!-- docs/overrides/partials/share.html --&gt;\n{% if config.extra.social_share.enabled %}\n&lt;div class=\"share-container\"&gt;\n    &lt;h4&gt;\u5206\u4eab\u6587\u7ae0&lt;/h4&gt;\n    &lt;div class=\"share-buttons\"&gt;\n        {% for platform in config.extra.social_share.platforms %}\n        &lt;button class=\"share-button\" \n                data-platform=\"{{ platform.name }}\"\n                style=\"--platform-color: {{ platform.color }}\"\n                onclick=\"shareContent('{{ platform.name }}')\"&gt;\n            &lt;span class=\"share-icon\"&gt;\n                {% include \".icons/\" ~ platform.icon ~ \".svg\" %}\n            &lt;/span&gt;\n            &lt;span class=\"share-text\"&gt;\u5206\u4eab\u5230 {{ platform.name|title }}&lt;/span&gt;\n        &lt;/button&gt;\n        {% endfor %}\n    &lt;/div&gt;\n&lt;/div&gt;\n\n&lt;style&gt;\n.share-container {\n    margin: 2rem 0;\n}\n\n.share-buttons {\n    display: flex;\n    flex-wrap: wrap;\n    gap: 0.5rem;\n    margin-top: 1rem;\n}\n\n.share-button {\n    display: flex;\n    align-items: center;\n    padding: 0.5rem 1rem;\n    border: none;\n    border-radius: 4px;\n    background: var(--md-code-bg-color);\n    color: var(--platform-color);\n    cursor: pointer;\n    transition: all 0.2s ease;\n}\n\n.share-button:hover {\n    background: var(--platform-color);\n    color: white;\n    transform: translateY(-2px);\n}\n\n.share-icon {\n    margin-right: 0.5rem;\n}\n&lt;/style&gt;\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#932","title":"9.3.2 \u5206\u4eab\u94fe\u63a5\u751f\u6210","text":"JavaScript<pre><code>// docs/javascripts/share.js\nclass ShareManager {\n    constructor() {\n        this.title = document.title;\n        this.url = window.location.href;\n        this.description = document\n            .querySelector('meta[name=\"description\"]')\n            ?.content || '';\n    }\n\n    generateShareUrl(platform) {\n        const params = new URLSearchParams();\n        switch (platform) {\n            case 'twitter':\n                return `https://twitter.com/intent/tweet?${\n                    params.set('text', this.title),\n                    params.set('url', this.url)\n                }`;\n\n            case 'facebook':\n                return `https://www.facebook.com/sharer/sharer.php?${\n                    params.set('u', this.url)\n                }`;\n\n            case 'linkedin':\n                return `https://www.linkedin.com/sharing/share-offsite/?${\n                    params.set('url', this.url)\n                }`;\n\n            case 'weibo':\n                return `http://service.weibo.com/share/share.php?${\n                    params.set('title', this.title),\n                    params.set('url', this.url)\n                }`;\n\n            default:\n                return null;\n        }\n    }\n\n    async share(platform) {\n        // \u68c0\u67e5\u662f\u5426\u652f\u6301\u539f\u751f\u5206\u4eab\n        if (navigator.share &amp;&amp; platform === 'native') {\n            try {\n                await navigator.share({\n                    title: this.title,\n                    text: this.description,\n                    url: this.url\n                });\n                return true;\n            } catch (err) {\n                console.warn('Native share failed:', err);\n                return false;\n            }\n        }\n\n        // \u4f7f\u7528\u5f39\u7a97\u5206\u4eab\n        const url = this.generateShareUrl(platform);\n        if (url) {\n            window.open(url, '_blank', 'width=600,height=400');\n            return true;\n        }\n\n        return false;\n    }\n\n    // \u81ea\u5b9a\u4e49\u5206\u4eab\u5185\u5bb9\n    setContent(title, description) {\n        this.title = title;\n        this.description = description;\n    }\n}\n\n// \u5168\u5c40\u5206\u4eab\u529f\u80fd\nwindow.shareContent = async function(platform) {\n    const shareManager = new ShareManager();\n    const success = await shareManager.share(platform);\n\n    // \u8bb0\u5f55\u5206\u4eab\u4e8b\u4ef6\n    if (success) {\n        recordShare(platform);\n    }\n};\n\n// \u5206\u4eab\u7edf\u8ba1\nfunction recordShare(platform) {\n    // GA4 \u4e8b\u4ef6\u8ffd\u8e2a\n    if (typeof gtag !== 'undefined') {\n        gtag('event', 'share', {\n            'platform': platform,\n            'title': document.title,\n            'url': window.location.href\n        });\n    }\n\n    // \u672c\u5730\u5b58\u50a8\u7edf\u8ba1\n    const stats = JSON.parse(localStorage.getItem('share_stats') || '{}');\n    stats[platform] = (stats[platform] || 0) + 1;\n    localStorage.setItem('share_stats', JSON.stringify(stats));\n\n    updateShareCount(platform);\n}\n\n// \u66f4\u65b0\u5206\u4eab\u8ba1\u6570\nfunction updateShareCount(platform) {\n    const countElement = document.querySelector(\n        `.share-count[data-platform=\"${platform}\"]`\n    );\n    if (countElement) {\n        const stats = JSON.parse(localStorage.getItem('share_stats') || '{}');\n        countElement.textContent = stats[platform] || 0;\n    }\n}\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#94","title":"9.4 \u7ad9\u5185\u641c\u7d22","text":""},{"location":"Tools/Blog/Mkdocs_Material/#941","title":"9.4.1 \u641c\u7d22\u4f18\u5316","text":"<ol> <li>\u641c\u7d22\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code>plugins:\n  - search:\n      lang:\n        - en\n        - zh\n      separator: '[\\s\\-\\.,!\\?\uff0c\u3002\uff01\uff1f]+'  # \u5206\u8bcd\u5206\u9694\u7b26\n      prebuild_index: true\n      indexing:\n        full_sections: true\n        headings: true\n        content: true\n        tags: true\n\n      # \u9ad8\u7ea7\u641c\u7d22\u914d\u7f6e\n      search_boost: true     # \u542f\u7528\u641c\u7d22\u63d0\u5347\n      search_threshold: 0.3  # \u641c\u7d22\u9608\u503c\n      search_fields:         # \u641c\u7d22\u5b57\u6bb5\u6743\u91cd\n        title: 10\n        tags: 8\n        content: 5\n</code></pre> <p>\u641c\u7d22\u4f18\u5316\u5b9e\u73b0\uff1a</p> JavaScript<pre><code>// docs/javascripts/search-enhance.js\nclass SearchEnhancer {\n    constructor() {\n        this.searchIndex = null;\n        this.searchResults = [];\n        this.searchHistory = [];\n        this.maxHistoryItems = 10;\n\n        this.init();\n    }\n\n    async init() {\n        // \u52a0\u8f7d\u641c\u7d22\u7d22\u5f15\n        await this.loadSearchIndex();\n        // \u52a0\u8f7d\u641c\u7d22\u5386\u53f2\n        this.loadSearchHistory();\n        // \u521d\u59cb\u5316\u641c\u7d22\u7ec4\u4ef6\n        this.setupSearch();\n    }\n\n    async loadSearchIndex() {\n        try {\n            const response = await fetch('/search/search_index.json');\n            const data = await response.json();\n\n            // \u4f7f\u7528 Lunr.js \u6784\u5efa\u7d22\u5f15\n            this.searchIndex = lunr(function() {\n                this.use(lunr.multiLanguage('en', 'zh'));\n\n                this.ref('location');\n                this.field('title', { boost: 10 });\n                this.field('tags', { boost: 8 });\n                this.field('text', { boost: 5 });\n\n                data.docs.forEach(function(doc) {\n                    this.add(doc);\n                }, this);\n            });\n        } catch (error) {\n            console.error('Failed to load search index:', error);\n        }\n    }\n\n    setupSearch() {\n        const searchInput = document.querySelector('.md-search__input');\n        if (!searchInput) return;\n\n        // \u9632\u6296\u5904\u7406\n        searchInput.addEventListener('input', debounce((e) =&gt; {\n            const query = e.target.value;\n            if (query.length &gt;= 2) {\n                this.performSearch(query);\n            } else {\n                this.clearResults();\n            }\n        }, 200));\n\n        // \u641c\u7d22\u5386\u53f2\n        searchInput.addEventListener('focus', () =&gt; {\n            this.showSearchHistory();\n        });\n    }\n\n    performSearch(query) {\n        if (!this.searchIndex) return;\n\n        try {\n            // \u6267\u884c\u641c\u7d22\n            this.searchResults = this.searchIndex.search(query);\n\n            // \u7ed3\u679c\u540e\u5904\u7406\n            this.searchResults = this.postProcessResults(this.searchResults, query);\n\n            // \u663e\u793a\u7ed3\u679c\n            this.displayResults(this.searchResults);\n\n            // \u663e\u793a\u641c\u7d22\u5efa\u8bae\n            this.showSearchSuggestions(query);\n        } catch (error) {\n            console.error('Search failed:', error);\n        }\n    }\n\n    postProcessResults(results, query) {\n        return results\n            .map(result =&gt; {\n                // \u8ba1\u7b97\u76f8\u5173\u5ea6\u5206\u6570\n                const score = this.calculateRelevanceScore(result, query);\n\n                return {\n                    ...result,\n                    score: score,\n                    highlights: this.generateHighlights(result, query)\n                };\n            })\n            // \u6309\u5206\u6570\u6392\u5e8f\n            .sort((a, b) =&gt; b.score - a.score)\n            // \u9650\u5236\u7ed3\u679c\u6570\u91cf\n            .slice(0, 10);\n    }\n\n    calculateRelevanceScore(result, query) {\n        let score = result.score;\n\n        // \u6807\u9898\u5339\u914d\u52a0\u5206\n        if (result.title?.toLowerCase().includes(query.toLowerCase())) {\n            score *= 1.5;\n        }\n\n        // \u6807\u7b7e\u5339\u914d\u52a0\u5206\n        if (result.tags?.some(tag =&gt; \n            tag.toLowerCase().includes(query.toLowerCase())\n        )) {\n            score *= 1.2;\n        }\n\n        return score;\n    }\n\n    generateHighlights(result, query) {\n        const text = result.text || '';\n        const words = query.toLowerCase().split(/\\s+/);\n        const context = 50; // \u4e0a\u4e0b\u6587\u957f\u5ea6\n\n        let highlights = [];\n\n        words.forEach(word =&gt; {\n            let index = text.toLowerCase().indexOf(word);\n            while (index &gt; -1) {\n                const start = Math.max(0, index - context);\n                const end = Math.min(text.length, index + word.length + context);\n                const highlight = text.slice(start, end);\n\n                highlights.push({\n                    text: highlight,\n                    position: start\n                });\n\n                index = text.toLowerCase().indexOf(word, index + 1);\n            }\n        });\n\n        // \u5408\u5e76\u91cd\u53e0\u7684\u9ad8\u4eae\u7247\u6bb5\n        return this.mergeHighlights(highlights);\n    }\n\n    mergeHighlights(highlights) {\n        if (highlights.length === 0) return [];\n\n        highlights.sort((a, b) =&gt; a.position - b.position);\n\n        let merged = [highlights[0]];\n        for (let i = 1; i &lt; highlights.length; i++) {\n            let current = highlights[i];\n            let last = merged[merged.length - 1];\n\n            if (current.position &lt;= last.position + last.text.length) {\n                // \u5408\u5e76\u91cd\u53e0\u7684\u7247\u6bb5\n                last.text = last.text.slice(0, current.position - last.position) +\n                           current.text;\n            } else {\n                merged.push(current);\n            }\n        }\n\n        return merged;\n    }\n\n    loadSearchHistory() {\n        try {\n            this.searchHistory = JSON.parse(\n                localStorage.getItem('search_history')\n            ) || [];\n        } catch (error) {\n            this.searchHistory = [];\n        }\n    }\n\n    saveSearchHistory(query) {\n        if (!query) return;\n\n        // \u79fb\u9664\u91cd\u590d\u9879\n        this.searchHistory = this.searchHistory.filter(item =&gt; \n            item.query !== query\n        );\n\n        // \u6dfb\u52a0\u65b0\u9879\n        this.searchHistory.unshift({\n            query: query,\n            timestamp: Date.now()\n        });\n\n        // \u9650\u5236\u5386\u53f2\u8bb0\u5f55\u6570\u91cf\n        if (this.searchHistory.length &gt; this.maxHistoryItems) {\n            this.searchHistory.pop();\n        }\n\n        // \u4fdd\u5b58\u5230\u672c\u5730\u5b58\u50a8\n        localStorage.setItem(\n            'search_history',\n            JSON.stringify(this.searchHistory)\n        );\n    }\n\n    showSearchHistory() {\n        const container = document.querySelector('.md-search__history');\n        if (!container) return;\n\n        // \u6e05\u7a7a\u5bb9\u5668\n        container.innerHTML = '';\n\n        // \u663e\u793a\u5386\u53f2\u8bb0\u5f55\n        this.searchHistory.forEach(item =&gt; {\n            const element = document.createElement('div');\n            element.className = 'search-history-item';\n            element.innerHTML = `\n                &lt;span class=\"history-icon\"&gt;\n                    {% include \".icons/material/history.svg\" %}\n                &lt;/span&gt;\n                &lt;span class=\"history-query\"&gt;${item.query}&lt;/span&gt;\n                &lt;span class=\"history-time\"&gt;\n                    ${this.formatTime(item.timestamp)}\n                &lt;/span&gt;\n            `;\n\n            element.addEventListener('click', () =&gt; {\n                const searchInput = document.querySelector('.md-search__input');\n                if (searchInput) {\n                    searchInput.value = item.query;\n                    searchInput.dispatchEvent(new Event('input'));\n                }\n            });\n\n            container.appendChild(element);\n        });\n    }\n\n    formatTime(timestamp) {\n        const now = Date.now();\n        const diff = now - timestamp;\n\n        if (diff &lt; 60000) return '\u521a\u521a';\n        if (diff &lt; 3600000) return `${Math.floor(diff/60000)}\u5206\u949f\u524d`;\n        if (diff &lt; 86400000) return `${Math.floor(diff/3600000)}\u5c0f\u65f6\u524d`;\n        return `${Math.floor(diff/86400000)}\u5929\u524d`;\n    }\n}\n\n// \u521d\u59cb\u5316\u641c\u7d22\u589e\u5f3a\nnew SearchEnhancer();\n</code></pre> <p>\u641c\u7d22\u76f8\u5173\u6837\u5f0f\uff1a</p> CSS<pre><code>/* docs/stylesheets/search.css */\n/* \u641c\u7d22\u5386\u53f2 */\n.search-history-item {\n    display: flex;\n    align-items: center;\n    padding: 0.5rem 1rem;\n    cursor: pointer;\n    transition: background 0.2s ease;\n}\n\n.search-history-item:hover {\n    background: var(--md-code-bg-color);\n}\n\n.history-icon {\n    margin-right: 0.5rem;\n    color: var(--md-default-fg-color--light);\n}\n\n.history-query {\n    flex: 1;\n    font-weight: 500;\n}\n\n.history-time {\n    font-size: 0.8rem;\n    color: var(--md-default-fg-color--light);\n}\n\n/* \u641c\u7d22\u5efa\u8bae */\n.search-suggestions {\n    padding: 1rem;\n}\n\n.suggestion-item {\n    padding: 0.5rem;\n    border-radius: 4px;\n    cursor: pointer;\n    transition: background 0.2s ease;\n}\n\n.suggestion-item:hover {\n    background: var(--md-code-bg-color);\n}\n\n/* \u9ad8\u4eae\u6587\u672c */\n.search-highlight {\n    background: var(--md-accent-fg-color);\n    color: white;\n    padding: 0 0.2rem;\n    border-radius: 2px;\n}\n\n/* \u641c\u7d22\u7ed3\u679c */\n.search-result {\n    padding: 1rem;\n    border-bottom: 1px solid var(--md-default-fg-color--lightest);\n}\n\n.result-title {\n    font-size: 1.1rem;\n    font-weight: 500;\n    margin-bottom: 0.5rem;\n}\n\n.result-excerpt {\n    font-size: 0.9rem;\n    color: var(--md-default-fg-color--light);\n    margin-bottom: 0.5rem;\n}\n\n.result-meta {\n    display: flex;\n    gap: 1rem;\n    font-size: 0.8rem;\n    color: var(--md-default-fg-color--lighter);\n}\n</code></pre> <p>\u4f7f\u7528\u8fd9\u4e9b\u4ee3\u7801\uff0c\u4f60\u53ef\u4ee5\u5b9e\u73b0\u4e00\u4e2a\u529f\u80fd\u5b8c\u5584\u7684\u641c\u7d22\u7cfb\u7edf\uff0c\u5305\u62ec\uff1a</p> <ol> <li>\u9ad8\u6027\u80fd\u641c\u7d22</li> <li>\u667a\u80fd\u7ed3\u679c\u6392\u5e8f</li> <li>\u641c\u7d22\u5386\u53f2\u8bb0\u5f55</li> <li>\u641c\u7d22\u5efa\u8bae</li> <li>\u7ed3\u679c\u9ad8\u4eae</li> <li>\u591a\u8bed\u8a00\u652f\u6301</li> </ol> <p>\u8bb0\u5f97\u5728 <code>mkdocs.yml</code> \u4e2d\u6dfb\u52a0\u76f8\u5e94\u7684\u5f15\u7528\uff1a</p> YAML<pre><code>extra_css:\n  - stylesheets/search.css\n\nextra_javascript:\n  - https://unpkg.com/lunr/lunr.js\n  - https://unpkg.com/lunr-languages/lunr.stemmer.support.js\n  - https://unpkg.com/lunr-languages/lunr.zh.js\n  - javascripts/search-enhance.js\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#10","title":"10 \u90e8\u7f72\u65b9\u6848","text":""},{"location":"Tools/Blog/Mkdocs_Material/#101","title":"10.1 \u672c\u5730\u90e8\u7f72","text":""},{"location":"Tools/Blog/Mkdocs_Material/#1011","title":"10.1.1 \u6784\u5efa\u9759\u6001\u6587\u4ef6","text":"<p>\u4f7f\u7528 MkDocs \u6784\u5efa\u9759\u6001\u6587\u4ef6\uff1a</p> Bash<pre><code># \u6784\u5efa\u7ad9\u70b9\nmkdocs build\n\n# \u6307\u5b9a\u8f93\u51fa\u76ee\u5f55\nmkdocs build -d custom_site_dir\n\n# \u6e05\u7406\u5e76\u6784\u5efa\nmkdocs build --clean\n</code></pre> <p>\u6784\u5efa\u9009\u9879\u8bf4\u660e\uff1a</p> YAML<pre><code># mkdocs.yml\nsite_dir: site               # \u8f93\u51fa\u76ee\u5f55\ndocs_dir: docs              # \u6587\u6863\u6e90\u76ee\u5f55\nstrict: true                # \u4e25\u683c\u6a21\u5f0f\nuse_directory_urls: true    # \u4f7f\u7528\u76ee\u5f55 URL\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1012","title":"10.1.2 \u672c\u5730\u670d\u52a1\u5668","text":"<p>\u5f00\u53d1\u670d\u52a1\u5668\u914d\u7f6e\uff1a</p> Bash<pre><code># \u542f\u52a8\u5f00\u53d1\u670d\u52a1\u5668\nmkdocs serve\n\n# \u6307\u5b9a\u7aef\u53e3\nmkdocs serve -a localhost:8080\n\n# \u81ea\u52a8\u91cd\u8f7d\nmkdocs serve --dirtyreload\n</code></pre> <p>\u5f00\u53d1\u670d\u52a1\u5668\u9ad8\u7ea7\u914d\u7f6e\uff1a</p> YAML<pre><code># mkdocs.yml\ndev_addr: 127.0.0.1:8000    # \u5f00\u53d1\u670d\u52a1\u5668\u5730\u5740\nwatch: [docs, includes]      # \u76d1\u89c6\u7684\u76ee\u5f55\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#102-github-pages","title":"10.2 GitHub Pages \u90e8\u7f72","text":""},{"location":"Tools/Blog/Mkdocs_Material/#1021","title":"10.2.1 \u4ed3\u5e93\u914d\u7f6e","text":"<ol> <li> <p>\u521b\u5efa GitHub \u4ed3\u5e93\uff1a    - \u521b\u5efa\u65b0\u4ed3\u5e93\u6216\u4f7f\u7528\u73b0\u6709\u4ed3\u5e93    - \u4ed3\u5e93\u540d\u683c\u5f0f\uff1a <code>username.github.io</code> \u6216\u666e\u901a\u4ed3\u5e93\u540d</p> </li> <li> <p>\u914d\u7f6e\u6587\u4ef6\uff1a</p> </li> </ol> YAML<pre><code># mkdocs.yml\nsite_url: https://username.github.io/repository/\nrepo_url: https://github.com/username/repository\nedit_uri: edit/main/docs/\n</code></pre> <ol> <li>\u521d\u59cb\u5316\u4ed3\u5e93\uff1a</li> </ol> Bash<pre><code># \u521d\u59cb\u5316 Git \u4ed3\u5e93\ngit init\n\n# \u6dfb\u52a0\u8fdc\u7a0b\u4ed3\u5e93\ngit remote add origin https://github.com/username/repository.git\n\n# \u63d0\u4ea4\u521d\u59cb\u6587\u4ef6\ngit add .\ngit commit -m \"Initial commit\"\ngit push -u origin main\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1022-github-actions","title":"10.2.2 GitHub Actions","text":"<p>\u521b\u5efa GitHub Actions \u5de5\u4f5c\u6d41\u6587\u4ef6\uff1a</p> YAML<pre><code># .github/workflows/ci.yml\nname: ci \non:\n  push:\n    branches: \n      - main\npermissions:\n  contents: write\njobs:\n  deploy:\n    runs-on: ubuntu-latest\n    steps:\n      - uses: actions/checkout@v4\n      - name: Configure Git Credentials\n        run: |\n          git config user.name github-actions[bot]\n          git config user.email 41898282+github-actions[bot]@users.noreply.github.com\n      - uses: actions/setup-python@v4\n        with:\n          python-version: 3.x\n      - run: echo \"cache_id=$(date --utc '+%V')\" &gt;&gt; $GITHUB_ENV \n      - uses: actions/cache@v3\n        with:\n          key: mkdocs-material-${{ env.cache_id }}\n          path: .cache\n          restore-keys: |\n            mkdocs-material-\n      - name: Install dependencies\n        run: |\n          pip install mkdocs-material\n          pip install mkdocs-glightbox\n          pip install mkdocs-git-revision-date-localized-plugin\n      - name: Deploy\n        run: mkdocs gh-deploy --force\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1023","title":"10.2.3 \u81ea\u52a8\u90e8\u7f72","text":"<p>\u914d\u7f6e\u81ea\u52a8\u90e8\u7f72\uff1a</p> <ol> <li> <p>\u542f\u7528 GitHub Pages\uff1a    - \u8fdb\u5165\u4ed3\u5e93\u8bbe\u7f6e -&gt; Pages    - Source \u9009\u62e9 <code>gh-pages</code> \u5206\u652f    - \u4fdd\u5b58\u8bbe\u7f6e</p> </li> <li> <p>\u914d\u7f6e\u90e8\u7f72\u5206\u652f\uff1a</p> </li> </ol> YAML<pre><code># mkdocs.yml\nremote_branch: gh-pages    # GitHub Pages \u5206\u652f\nremote_name: origin       # \u8fdc\u7a0b\u4ed3\u5e93\u540d\n</code></pre> <ol> <li>\u624b\u52a8\u90e8\u7f72\u547d\u4ee4\uff1a</li> </ol> Bash<pre><code># \u90e8\u7f72\u5230 GitHub Pages\nmkdocs gh-deploy\n\n# \u5f3a\u5236\u90e8\u7f72\nmkdocs gh-deploy --force\n\n# \u6307\u5b9a\u5206\u652f\nmkdocs gh-deploy --remote-branch custom-branch\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1024","title":"10.2.4 \u81ea\u5b9a\u4e49\u57df\u540d","text":"<ol> <li>\u6dfb\u52a0 CNAME \u6587\u4ef6\uff1a</li> </ol> Bash<pre><code># docs/CNAME\ndocs.example.com\n</code></pre> <ol> <li> <p>DNS \u914d\u7f6e\uff1a    - \u6dfb\u52a0 CNAME \u8bb0\u5f55\u6307\u5411 <code>username.github.io</code>    - \u6216\u6dfb\u52a0 A \u8bb0\u5f55\u6307\u5411 GitHub Pages IP</p> </li> <li> <p>\u914d\u7f6e\u6587\u4ef6\u66f4\u65b0\uff1a</p> </li> </ol> YAML<pre><code># mkdocs.yml\nsite_url: https://docs.example.com/\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#103","title":"10.3 \u6301\u7eed\u96c6\u6210","text":""},{"location":"Tools/Blog/Mkdocs_Material/#1031-cicd","title":"10.3.1 CI/CD \u914d\u7f6e","text":"<p>\u9ad8\u7ea7 GitHub Actions \u914d\u7f6e\uff1a</p> YAML<pre><code>name: CI/CD Pipeline\non:\n  push:\n    branches:\n      - main\n  pull_request:\n    branches:\n      - main\n\njobs:\n  test:\n    runs-on: ubuntu-latest\n    steps:\n      - uses: actions/checkout@v4\n\n      - name: Set up Python\n        uses: actions/setup-python@v4\n        with:\n          python-version: 3.x\n\n      - name: Cache dependencies\n        uses: actions/cache@v3\n        with:\n          path: ~/.cache/pip\n          key: ${{ runner.os }}-pip-${{ hashFiles('requirements.txt') }}\n          restore-keys: |\n            ${{ runner.os }}-pip-\n\n      - name: Install dependencies\n        run: |\n          python -m pip install --upgrade pip\n          pip install -r requirements.txt\n\n      - name: Run tests\n        run: |\n          mkdocs build --strict\n\n  deploy:\n    needs: test\n    if: github.ref == 'refs/heads/main'\n    runs-on: ubuntu-latest\n    steps:\n      - uses: actions/checkout@v4\n\n      - name: Deploy to GitHub Pages\n        run: |\n          mkdocs gh-deploy --force\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1032","title":"10.3.2 \u81ea\u52a8\u5316\u6d4b\u8bd5","text":"<ol> <li>\u94fe\u63a5\u68c0\u67e5\uff1a</li> </ol> YAML<pre><code>name: Link Check\non:\n  schedule:\n    - cron: '0 0 * * *'  # \u6bcf\u5929\u8fd0\u884c\njobs:\n  linkCheck:\n    runs-on: ubuntu-latest\n    steps:\n      - uses: actions/checkout@v4\n      - name: Link Checker\n        uses: lycheeverse/lychee-action@v1.8.0\n        with:\n          args: --verbose --no-progress 'docs/**/*.md'\n</code></pre> <ol> <li>HTML \u9a8c\u8bc1\uff1a</li> </ol> YAML<pre><code>name: HTML Validation\njobs:\n  validate:\n    runs-on: ubuntu-latest\n    steps:\n      - uses: actions/checkout@v4\n      - name: Build site\n        run: mkdocs build\n      - name: Validate HTML\n        uses: Cyb3r-Jak3/html5validator-action@v7.2.0\n        with:\n          root: site/\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1033","title":"10.3.3 \u90e8\u7f72\u7b56\u7565","text":"<ol> <li>\u5206\u652f\u7b56\u7565\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code># \u4fdd\u62a4\u5206\u652f\u8bbe\u7f6e\nbranches:\n  - name: main\n    protection:\n      required_status_checks:\n        strict: true\n        contexts: ['test', 'build']\n      required_pull_request_reviews:\n        required_approving_review_count: 1\n</code></pre> <ol> <li>\u73af\u5883\u914d\u7f6e\uff1a</li> </ol> YAML<pre><code># \u73af\u5883\u53d8\u91cf\u8bbe\u7f6e\nenv:\n  production:\n    url: https://docs.example.com\n    branch: main\n  staging:\n    url: https://staging.docs.example.com\n    branch: staging\n</code></pre> <ol> <li>\u90e8\u7f72\u5de5\u4f5c\u6d41\uff1a</li> </ol> YAML<pre><code>name: Deployment\non:\n  push:\n    branches: [main, staging]\njobs:\n  deploy:\n    runs-on: ubuntu-latest\n    environment:\n      name: ${{ github.ref == 'refs/heads/main' &amp;&amp; 'production' || 'staging' }}\n    steps:\n      - uses: actions/checkout@v4\n\n      - name: Build and Deploy\n        env:\n          DEPLOY_URL: ${{ github.ref == 'refs/heads/main' &amp;&amp; env.production.url || env.staging.url }}\n        run: |\n          mkdocs build\n          # \u90e8\u7f72\u5230\u76f8\u5e94\u73af\u5883\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#11","title":"11 \u9644\u5f55","text":""},{"location":"Tools/Blog/Mkdocs_Material/#111-a","title":"11.1 A. \u5e38\u7528\u914d\u7f6e\u793a\u4f8b","text":""},{"location":"Tools/Blog/Mkdocs_Material/#1111-a1-mkdocs-yml","title":"11.1.1 A.1 mkdocs. yml \u5b8c\u6574\u793a\u4f8b","text":"YAML<pre><code># \u7ad9\u70b9\u57fa\u672c\u4fe1\u606f\u914d\u7f6e\nsite_name: \u9879\u76ee\u6587\u6863            # \u7ad9\u70b9\u540d\u79f0\nsite_url: https://example.com  # \u7ad9\u70b9URL\nsite_author: \u4f5c\u8005\u540d\u79f0          # \u4f5c\u8005\u4fe1\u606f\nsite_description: &gt;-          # \u7ad9\u70b9\u63cf\u8ff0\n  \u8fd9\u662f\u4e00\u4e2a\u5b8c\u6574\u7684\u6587\u6863\u793a\u4f8b\uff0c\u5305\u542b\u4e86MkDocs Material\u4e3b\u9898\u7684\u6240\u6709\u4e3b\u8981\u529f\u80fd\u914d\u7f6e\u3002\n\n# \u4ee3\u7801\u4ed3\u5e93\u4fe1\u606f\nrepo_name: username/repo      # \u4ed3\u5e93\u540d\u79f0\nrepo_url: https://github.com/username/repo  # \u4ed3\u5e93\u5730\u5740\nedit_uri: edit/main/docs/     # \u7f16\u8f91\u94fe\u63a5\n\n# \u7248\u6743\u4fe1\u606f\ncopyright: Copyright &amp;copy; 2024 # \u7248\u6743\u58f0\u660e\n\n# \u4e3b\u9898\u914d\u7f6e\ntheme:\n  name: material               # \u4f7f\u7528Material\u4e3b\u9898\n  custom_dir: overrides       # \u81ea\u5b9a\u4e49\u76ee\u5f55\n\n  # \u4e3b\u9898\u7279\u6027\u914d\u7f6e\n  features:\n    # \u5bfc\u822a\u76f8\u5173\n    - navigation.tabs         # \u9876\u90e8\u6807\u7b7e\u5bfc\u822a\n    - navigation.sections     # \u4fa7\u8fb9\u680f\u5206\u7ec4\n    - navigation.expand      # \u9ed8\u8ba4\u5c55\u5f00\u5bfc\u822a\n    - navigation.indexes     # \u5bfc\u822a\u7d22\u5f15\u9875\n    - navigation.top         # \u8fd4\u56de\u9876\u90e8\u6309\u94ae\n    - navigation.footer      # \u4e0a\u4e00\u9875/\u4e0b\u4e00\u9875\u5bfc\u822a\n\n    # \u641c\u7d22\u76f8\u5173\n    - search.suggest        # \u641c\u7d22\u5efa\u8bae\n    - search.highlight     # \u641c\u7d22\u9ad8\u4eae\n    - search.share        # \u641c\u7d22\u5206\u4eab\n\n    # \u4ee3\u7801\u76f8\u5173\n    - content.code.annotate # \u4ee3\u7801\u6ce8\u91ca\n    - content.code.copy    # \u4ee3\u7801\u590d\u5236\n\n    # \u5176\u4ed6\u529f\u80fd\n    - announce.dismiss     # \u53ef\u5173\u95ed\u516c\u544a\n    - header.autohide     # \u81ea\u52a8\u9690\u85cf\u5934\u90e8\n\n  # \u914d\u8272\u65b9\u6848\n  palette:\n    # \u4eae\u8272\u4e3b\u9898\n    - media: \"(prefers-color-scheme: light)\"\n      scheme: default\n      primary: indigo     # \u4e3b\u8272\n      accent: indigo      # \u5f3a\u8c03\u8272\n      toggle:\n        icon: material/brightness-7\n        name: \u5207\u6362\u81f3\u6697\u8272\u6a21\u5f0f\n\n    # \u6697\u8272\u4e3b\u9898\n    - media: \"(prefers-color-scheme: dark)\"\n      scheme: slate\n      primary: indigo\n      accent: indigo\n      toggle:\n        icon: material/brightness-4\n        name: \u5207\u6362\u81f3\u4eae\u8272\u6a21\u5f0f\n\n  # \u56fe\u6807\u548c\u5b57\u4f53\n  icon:\n    logo: material/book-open-page-variant # Logo\u56fe\u6807\n    repo: fontawesome/brands/github      # \u4ed3\u5e93\u56fe\u6807\n\n  font:\n    text: Roboto         # \u6b63\u6587\u5b57\u4f53\n    code: Roboto Mono    # \u4ee3\u7801\u5b57\u4f53\n\n  language: zh          # \u754c\u9762\u8bed\u8a00\n\n# \u6269\u5c55\u914d\u7f6e\nmarkdown_extensions:\n  # \u5185\u7f6e\u6269\u5c55\n  - toc:                 # \u76ee\u5f55\n      permalink: true    # \u6c38\u4e45\u94fe\u63a5\n      toc_depth: 3      # \u76ee\u5f55\u6df1\u5ea6\n  - tables              # \u8868\u683c\u652f\u6301\n  - attr_list           # \u5c5e\u6027\u5217\u8868\n  - def_list            # \u5b9a\u4e49\u5217\u8868\n  - footnotes           # \u811a\u6ce8\n  - abbr                # \u7f29\u5199\n\n  # PyMdown Extensions\n  - pymdownx.highlight:    # \u4ee3\u7801\u9ad8\u4eae\n      anchor_linenums: true\n      line_spans: __span\n      pygments_lang_class: true\n  - pymdownx.inlinehilite # \u884c\u5185\u4ee3\u7801\u9ad8\u4eae\n  - pymdownx.snippets     # \u4ee3\u7801\u7247\u6bb5\n  - pymdownx.superfences: # \u8d85\u7ea7\u56f4\u680f\n      custom_fences:\n        - name: mermaid\n          class: mermaid\n          format: !!python/name:pymdownx.superfences.fence_code_format\n  - pymdownx.tabbed:     # \u6807\u7b7e\u9875\n      alternate_style: true\n  - pymdownx.tasklist:   # \u4efb\u52a1\u5217\u8868\n      custom_checkbox: true\n  - pymdownx.emoji:      # \u8868\u60c5\u652f\u6301\n      emoji_index: !!python/name:material.extensions.emoji.twemoji\n      emoji_generator: !!python/name:material.extensions.emoji.to_svg\n  - pymdownx.details    # \u8be6\u7ec6\u4fe1\u606f\n  - pymdownx.caret      # \u4e0a\u6807\n  - pymdownx.mark       # \u6807\u8bb0\n  - pymdownx.tilde      # \u4e0b\u6807\n  - pymdownx.keys       # \u952e\u76d8\u6309\u952e\n\n# \u63d2\u4ef6\u914d\u7f6e\nplugins:\n  - search:           # \u641c\u7d22\u63d2\u4ef6\n      lang: \n        - en\n        - zh\n      separator: '[\\s\\-\\.,!\\?\uff0c\u3002\uff01\uff1f]+'\n      prebuild_index: true\n\n  - git-revision-date-localized: # Git\u65e5\u671f\u63d2\u4ef6\n      enable_creation_date: true\n      type: datetime\n\n  - minify:          # \u8d44\u6e90\u538b\u7f29\n      minify_html: true\n      minify_js: true\n      minify_css: true\n      htmlmin_opts:\n        remove_comments: true\n\n  - social:          # \u793e\u4ea4\u5206\u4eab\n      cards: true\n      cards_color:\n        fill: \"#0FF1CE\"\n        text: \"#FFFFFF\"\n\n  - tags:            # \u6807\u7b7e\u7cfb\u7edf\n      tags_file: tags.md\n\n  - statistics:      # \u7edf\u8ba1\n      page_check: true\n      page_count: true\n\n# \u9644\u52a0\u914d\u7f6e\nextra:\n  # \u793e\u4ea4\u94fe\u63a5\n  social:\n    - icon: fontawesome/brands/github\n      link: https://github.com/username\n    - icon: fontawesome/brands/twitter\n      link: https://twitter.com/username\n\n  # \u8bc4\u8bba\u7cfb\u7edf\n  comments:\n    provider: giscus\n    repo: username/repo\n    repo_id: your_repo_id\n    category: Comments\n    category_id: your_category_id\n\n  # \u5206\u6790\u7edf\u8ba1\n  analytics:\n    provider: google\n    property: G-XXXXXXXXXX\n    feedback:\n      title: \u8fd9\u7bc7\u6587\u6863\u5bf9\u60a8\u6709\u5e2e\u52a9\u5417\uff1f\n      ratings:\n        - icon: material/thumb-up-outline\n          name: \u6709\u5e2e\u52a9\n          data: 1\n          note: &gt;-\n            \u611f\u8c22\u60a8\u7684\u53cd\u9988\uff01\n        - icon: material/thumb-down-outline\n          name: \u6ca1\u5e2e\u52a9\n          data: 0\n          note: &gt;- \n            \u611f\u8c22\u60a8\u7684\u53cd\u9988\uff0c\u8bf7\u544a\u8bc9\u6211\u4eec\u5982\u4f55\u6539\u8fdb\u3002\n\n# \u989d\u5916\u7684CSS\u548cJavaScript\nextra_css:\n  - stylesheets/extra.css      # \u81ea\u5b9a\u4e49\u6837\u5f0f\n  - stylesheets/custom.css     # \u81ea\u5b9a\u4e49\u4e3b\u9898\n\nextra_javascript:\n  - javascripts/extra.js       # \u81ea\u5b9a\u4e49\u811a\u672c\n  - https://unpkg.com/mermaid/dist/mermaid.min.js  # \u5916\u90e8\u5e93\n</code></pre>"},{"location":"Tools/Blog/Mkdocs_Material/#1112-a2-github-actions","title":"11.1.2 A.2 GitHub Actions \u5de5\u4f5c\u6d41\u793a\u4f8b","text":"YAML<pre><code># .github/workflows/deploy.yml\n\nname: Deploy Documentation\non:\n  # \u89e6\u53d1\u6761\u4ef6\n  push:\n    branches:\n      - main\n    paths:\n      - 'docs/**'\n      - 'mkdocs.yml'\n      - '.github/workflows/deploy.yml'\n  pull_request:\n    branches:\n      - main\n\n  # \u5141\u8bb8\u624b\u52a8\u89e6\u53d1\n  workflow_dispatch:\n\n# \u73af\u5883\u53d8\u91cf\nenv:\n  PYTHON_VERSION: '3.10'\n  DEPLOY_BRANCH: gh-pages\n\n# \u4efb\u52a1\u5b9a\u4e49\njobs:\n  build:\n    name: Build and Deploy Documentation\n    runs-on: ubuntu-latest\n\n    steps:\n      # \u68c0\u51fa\u4ee3\u7801\n      - name: Checkout Repository\n        uses: actions/checkout@v3\n        with:\n          fetch-depth: 0  # \u83b7\u53d6\u5b8c\u6574\u7684git\u5386\u53f2\u7528\u4e8e\u6700\u8fd1\u66f4\u65b0\u65f6\u95f4\n\n      # \u8bbe\u7f6ePython\u73af\u5883\n      - name: Setup Python\n        uses: actions/setup-python@v4\n        with:\n          python-version: ${{ env.PYTHON_VERSION }}\n          cache: pip\n\n      # \u7f13\u5b58\u4f9d\u8d56\n      - name: Cache Dependencies\n        uses: actions/cache@v3\n        with:\n          path: ~/.cache/pip\n          key: ${{ runner.os }}-pip-${{ hashFiles('requirements.txt') }}\n          restore-keys: |\n            ${{ runner.os }}-pip-\n\n      # \u5b89\u88c5\u4f9d\u8d56\n      - name: Install Dependencies\n        run: |\n          python -m pip install --upgrade pip\n          pip install -r requirements.txt\n\n      # \u914d\u7f6eGit\n      - name: Configure Git\n        run: |\n          git config --global user.name \"${{ github.actor }}\"\n          git config --global user.email \"${{ github.actor }}@users.noreply.github.com\"\n\n      # \u6784\u5efa\u6587\u6863\n      - name: Build Documentation\n        run: |\n          mkdocs build --clean --verbose\n\n      # \u4f18\u5316\u8d44\u6e90\n      - name: Optimize Assets\n        run: |\n          # \u538b\u7f29\u56fe\u7247\n          find site/ -type f -name \"*.png\" -exec optipng -o5 {} \\;\n          find site/ -type f -name \"*.jpg\" -exec jpegoptim --strip-all {} \\;\n\n          # \u538b\u7f29JavaScript\u548cCSS\n          find site/ -type f -name \"*.js\" -exec uglifyjs {} -o {} \\;\n          find site/ -type f -name \"*.css\" -exec cleancss -o {} {} \\;\n\n      # \u90e8\u7f72\u5230GitHub Pages\n      - name: Deploy to GitHub Pages\n        if: github.ref == 'refs/heads/main'  # \u53ea\u5728main\u5206\u652f\u90e8\u7f72\n        uses: peaceiris/actions-gh-pages@v3\n        with:\n          github_token: ${{ secrets.GITHUB_TOKEN }}\n          publish_dir: ./site\n          publish_branch: ${{ env.DEPLOY_BRANCH }}\n          user_name: 'github-actions[bot]'\n          user_email: 'github-actions[bot]@users.noreply.github.com'\n          commit_message: ${{ github.event.head_commit.message }}\n          full_commit_message: |\n            Deploy Documentation\n\n            Commit: ${{ github.sha }}\n            Workflow: ${{ github.workflow }}\n\n            ${{ github.event.head_commit.message }}\n\n      # \u90e8\u7f72\u5b8c\u6210\u901a\u77e5\n      - name: Deployment Status\n        if: always()\n        uses: actions/github-script@v6\n        with:\n          script: |\n            const { owner, repo } = context.repo;\n            const run_id = context.runId;\n            const run_url = `https://github.com/${owner}/${repo}/actions/runs/${run_id}`;\n\n            if (context.job.status === 'success') {\n              await github.rest.issues.createComment({\n                owner,\n                repo,\n                issue_number: context.issue.number,\n                body: `\u2705 Documentation deployed successfully!\\nPreview: https://${owner}.github.io/${repo}/\\nWorkflow: ${run_url}`\n              });\n            } else {\n              await github.rest.issues.createComment({\n                owner,\n                repo,\n                issue_number: context.issue.number,\n                body: `\u274c Documentation deployment failed.\\nSee details: ${run_url}`\n              });\n            }\n\n# \u9519\u8bef\u8ffd\u8e2a\u548c\u62a5\u544a\n      - name: Report Errors\n        if: failure()\n        uses: actions/github-script@v6\n        with:\n          script: |\n            const { owner, repo } = context.repo;\n            const run_id = context.runId;\n\n            await github.rest.issues.create({\n              owner,\n              repo,\n              title: `\ud83d\udd34 Documentation deployment failed - ${new Date().toISOString()}`,\n              body: `Deployment failed for commit: ${context.sha}\\n\\nSee workflow run: https://github.com/${owner}/${repo}/actions/runs/${run_id}\\n\\nPlease check the logs for more details.`,\n              labels: ['deployment', 'bug']\n            });\n</code></pre>"},{"location":"Tools/Make/CMake/","title":"CMake \u76f8\u5173","text":""},{"location":"Tools/Make/CMake/#cmake","title":"CMake \u76f8\u5173","text":"<p> \u7ea6 161 \u4e2a\u5b57  13 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"Tools/Make/CMake/#1","title":"1 \u6784\u5efa\u6700\u5c0f\u9879\u76ee","text":"<ul> <li>CMake \u652f\u6301\u5927\u5199\u3001\u5c0f\u5199\u548c\u6df7\u5408\u5927\u5c0f\u5199\u547d\u4ee4\u3001</li> </ul> Text Only<pre><code>mkdir build\ncd build\ncmake -G\"MinGW Makefiles\" ..\ncmake --build .\n</code></pre> <p>\u4e4b\u540e\u4f1a\u751f\u6210\u53ef\u6267\u884c\u6587\u4ef6</p> Text Only<pre><code>step1/\n    build/\n    CMakeLists.txt\n    tutorial.cpp\n</code></pre>"},{"location":"Tools/Make/CMake/#2-cmakelists-txt","title":"2 \u4f18\u5316 CMakeLists. txt \u6587\u4ef6","text":"CMake<pre><code>cmake_minimum_required(VERSION 3.15)\n\n# set the project name\nproject(Tutorial)\n\nSET(SRC_LIST tutorial.cpp)\n\n# add the executable\nadd_executable(${PROJECT_NAME} ${SRC_LIST})\n</code></pre> <p>1.0.2 \u5206\u522b\u5bf9\u5e94 MAJOR MINOR PATCH</p> <ul> <li>set \u548c PROJECT_NAME</li> <li>\u6dfb\u52a0\u7248\u672c\u53f7\u548c\u914d\u7f6e\u5934\u6587\u4ef6</li> <li>\u6dfb\u52a0\u7f16\u8bd1\u65f6\u95f4\u6233</li> <li>\u6307\u5b9a C++\u6807\u51c6</li> <li>\u6dfb\u52a0\u5e93\uff08\u6dfb\u52a0\u5e93\u7684\u4f4d\u7f6e\uff0c\u5e93\u6587\u4ef6\u540d\uff0c\u5934\u6587\u4ef6\u540d\uff09</li> <li>\u5c06\u5e93\u8bbe\u7f6e\u4e3a\u53ef\u9009\u9879\uff08\u5206\u7ecf\u5178\u548c\u73b0\u4ee3\uff09</li> <li>\u6dfb\u52a0\u5e93\u7684\u4f7f\u7528\u8981\u6c42<ul> <li>INTERFACE</li> <li>PRIVATE</li> <li>PUBLIC</li> <li>\u9759\u6001\u94fe\u63a5\u5e93/\u52a8\u6001\u94fe\u63a5\u5e93</li> </ul> </li> <li>build \u76ee\u5f55\u4ecb\u7ecd</li> </ul>"},{"location":"Tools/Make/CMake/#links","title":"links","text":"<ul> <li>Site Unreachable</li> <li>IPADS\u65b0\u4eba\u57f9\u8bad\u7b2c\u4e8c\u8bb2\uff1aCMake_\u54d4\u54e9\u54d4\u54e9_bilibili</li> </ul>"},{"location":"Tools/Make/Makeflie/","title":"Makeflie","text":""},{"location":"Tools/Make/Makeflie/#make","title":"Make \u57fa\u7840","text":"<p> \u7ea6 220 \u4e2a\u5b57  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 1 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"Tools/Make/Makeflie/#make_1","title":"\u4ec0\u4e48\u662f Make","text":"<p>Make \u662f\u4e00\u4e2a\u81ea\u52a8\u5316\u6784\u5efa\u5de5\u5177\uff0c\u4f7f\u7528 Makefile \u6587\u4ef6\u6765\u5b9a\u4e49\u5982\u4f55\u7f16\u8bd1\u548c\u94fe\u63a5\u7a0b\u5e8f\u3002\u5b83\u901a\u8fc7\u68c0\u67e5\u6587\u4ef6\u7684\u65f6\u95f4\u6233\u6765\u51b3\u5b9a\u54ea\u4e9b\u6587\u4ef6\u9700\u8981\u91cd\u65b0\u7f16\u8bd1\u3002</p>"},{"location":"Tools/Make/Makeflie/#makefile","title":"Makefile \u7684\u57fa\u672c\u7ed3\u6784","text":"<p>Makefile \u7684\u57fa\u672c\u7ed3\u6784\u7531\u76ee\u6807\u3001\u4f9d\u8d56\u548c\u547d\u4ee4\u7ec4\u6210\uff0c\u901a\u5e38\u5f62\u5f0f\u4e3a\uff1a</p> Text Only<pre><code>target: dependencies     \n    command\n</code></pre>"},{"location":"Tools/Make/Makeflie/#makefile_1","title":"Makefile \u793a\u4f8b","text":"<p>\u8ba9\u6211\u4eec\u8003\u8651\u4e00\u4e2a\u7b80\u5355\u7684 C \u8bed\u8a00\u9879\u76ee\uff0c\u8be5\u793a\u4f8b\u5c06\u5c55\u793a\u5982\u4f55\u4f7f\u7528 Makefile \u6765\u7f16\u8bd1\u4e00\u4e2a\u5177\u6709\u591a\u4e2a\u6e90\u6587\u4ef6\u548c\u5934\u6587\u4ef6\u7684\u7a0b\u5e8f\uff0c\u5e76\u5c55\u793a Makefile \u76f8\u6bd4\u624b\u52a8\u547d\u4ee4\u884c\u7f16\u8bd1\u7684\u4f18\u52bf\u3002 \u7f16\u8bd1\u8fdb\u9636 - HPC\u5165\u95e8\u6307\u5357</p>"},{"location":"Tools/Make/Makeflie/#make_2","title":"Make \u7684\u5e38\u7528\u547d\u4ee4","text":"<ul> <li><code>make</code>\uff1a\u6267\u884c\u9ed8\u8ba4\u76ee\u6807\uff0c\u4e0e<code>make all</code>\u7b49\u6548\u3002</li> <li><code>make &lt;target&gt;</code>\uff1a\u6267\u884c\u5b9a\u4e49\u7684<code>&lt;target&gt;</code>\u76ee\u6807\uff0c\u5982\u679c\u6ca1\u6709\u8fd9\u4e2a\u76ee\u6807\u5c06\u8fd4\u56de\u9519\u8bef\u4fe1\u606f\u3002</li> <li><code>make -j</code>\uff1a\u5e76\u884c\u6267\u884c\u6784\u5efa\uff0c\u4f7f\u7528\u672c\u673a\u7684\u5168\u90e8\u7ebf\u7a0b</li> </ul>"},{"location":"Tools/Others/Chezmoi/","title":"\u7528 chezmoi \u5b9e\u73b0\u8de8\u8bbe\u5907\u540c\u6b65\u914d\u7f6e","text":""},{"location":"Tools/Others/Chezmoi/#chezmoi","title":"\u7528 chezmoi \u5b9e\u73b0\u8de8\u8bbe\u5907\u540c\u6b65\u914d\u7f6e","text":"<p> \u7ea6 512 \u4e2a\u5b57  142 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 4 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p> <p>\u672c\u6307\u5357\u5c06\u5e2e\u52a9\u4f60\u4f7f\u7528 chezmoi \u7ba1\u7406\u4f60\u7684\u914d\u7f6e\u6587\u4ef6\uff08dotfiles\uff09\uff0c\u5e76\u4f7f\u7528\u5305\u7ba1\u7406\u5668\u7ef4\u62a4\u8f6f\u4ef6\u5217\u8868\u3002</p>"},{"location":"Tools/Others/Chezmoi/#_1","title":"\u524d\u671f\u51c6\u5907","text":""},{"location":"Tools/Others/Chezmoi/#1","title":"1. \u9700\u8981\u7684\u5de5\u5177","text":"<ul> <li>Git</li> <li>GitHub \u8d26\u53f7</li> <li>chezmoi</li> <li>\u5305\u7ba1\u7406\u5668\uff08Windows: Scoop, Ubuntu: apt/snap\uff09</li> </ul>"},{"location":"Tools/Others/Chezmoi/#2","title":"2. \u91cd\u8981\u7684\u914d\u7f6e\u6587\u4ef6","text":"<p>Windows \u5e38\u7528\u914d\u7f6e\u6587\u4ef6:</p> Text Only<pre><code>%USERPROFILE%/\n\u251c\u2500\u2500 .gitconfig                        # Git\u914d\u7f6e\n\u251c\u2500\u2500 .ssh/                            # SSH\u914d\u7f6e\n\u251c\u2500\u2500 Documents/\n\u2502   \u2514\u2500\u2500 PowerShell/\n\u2502       \u2514\u2500\u2500 Microsoft.PowerShell_profile.ps1  # PowerShell\u914d\u7f6e\n\u251c\u2500\u2500 AppData/\n\u2502   \u251c\u2500\u2500 Roaming/\n\u2502   \u2502   \u2514\u2500\u2500 Code/\n\u2502   \u2502       \u2514\u2500\u2500 User/\n\u2502   \u2502           \u2514\u2500\u2500 settings.json    # VSCode\u914d\u7f6e\n\u2502   \u2514\u2500\u2500 Local/\n\u2514\u2500\u2500 .config/\n    \u2514\u2500\u2500 scoop/\n        \u2514\u2500\u2500 config.json              # Scoop\u914d\u7f6e\n</code></pre> <p>Ubuntu \u5e38\u7528\u914d\u7f6e\u6587\u4ef6:</p> Text Only<pre><code>~/\n\u251c\u2500\u2500 .bashrc                          # Bash\u914d\u7f6e\n\u251c\u2500\u2500 .zshrc                           # Zsh\u914d\u7f6e\n\u251c\u2500\u2500 .gitconfig                       # Git\u914d\u7f6e\n\u251c\u2500\u2500 .ssh/                           # SSH\u914d\u7f6e\n\u2514\u2500\u2500 .config/\n    \u251c\u2500\u2500 Code/\n    \u2502   \u2514\u2500\u2500 User/\n    \u2502       \u2514\u2500\u2500 settings.json       # VSCode\u914d\u7f6e\n    \u2514\u2500\u2500 tabby/\n        \u2514\u2500\u2500 config.yaml            # Tabby\u7ec8\u7aef\u914d\u7f6e\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#github","title":"GitHub \u8bbe\u7f6e","text":""},{"location":"Tools/Others/Chezmoi/#1-github","title":"1. \u521b\u5efa GitHub \u4ed3\u5e93","text":"<ol> <li>\u8bbf\u95ee GitHub \u5e76\u767b\u5f55</li> <li>\u70b9\u51fb \"New repository\"</li> <li>\u4ed3\u5e93\u540d\u79f0\u8bbe\u7f6e\u4e3a <code>dotfiles</code></li> <li>\u8bbe\u7f6e\u4e3a Public\uff08\u63a8\u8350\uff09</li> <li>\u4e0d\u8981\u521d\u59cb\u5316 README\uff08\u6211\u4eec\u5c06\u4ece\u672c\u5730\u521d\u59cb\u5316\uff09</li> <li>\u521b\u5efa\u4ed3\u5e93</li> </ol>"},{"location":"Tools/Others/Chezmoi/#2-ssh","title":"2. \u914d\u7f6e SSH \u5bc6\u94a5\uff08\u5982\u679c\u8fd8\u6ca1\u6709\uff09","text":"Bash<pre><code># \u751f\u6210SSH\u5bc6\u94a5\nssh-keygen -t ed25519 -C \"your_email@example.com\"\n\n# \u5c06\u516c\u94a5\u6dfb\u52a0\u5230GitHub\n# 1. \u590d\u5236\u516c\u94a5\u5185\u5bb9\ncat ~/.ssh/id_ed25519.pub\n# 2. \u8bbf\u95ee GitHub \u2192 Settings \u2192 SSH and GPG keys \u2192 New SSH key\n# 3. \u7c98\u8d34\u516c\u94a5\u5185\u5bb9\u5e76\u4fdd\u5b58\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#windows","title":"Windows \u914d\u7f6e","text":""},{"location":"Tools/Others/Chezmoi/#1_1","title":"1. \u5b89\u88c5\u5fc5\u8981\u5de5\u5177","text":"<p>\u4f7f\u7528 PowerShell\uff08\u4ee5\u7ba1\u7406\u5458\u8eab\u4efd\u8fd0\u884c\uff09\uff1a</p> PowerShell<pre><code># \u5b89\u88c5Scoop\nSet-ExecutionPolicy RemoteSigned -Scope CurrentUser\nirm get.scoop.sh | iex\n\n# \u5b89\u88c5Git\uff08\u5982\u679c\u8fd8\u6ca1\u6709\uff09\nscoop install git\n\n# \u5b89\u88c5chezmoi\nscoop install chezmoi\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#2-chezmoi","title":"2. \u521d\u59cb\u5316 chezmoi","text":"PowerShell<pre><code># \u521d\u59cb\u5316chezmoi\u5e76\u514b\u9686\u4f60\u7684\u4ed3\u5e93\nchezmoi init --apply https://github.com/yourusername/dotfiles.git\n# \u7528 ssh \u4e5f\u53ef\u4ee5\n\n# \u67e5\u770bchezmoi\u5c06\u8fdb\u884c\u7684\u66f4\u6539\nchezmoi diff\n\n# \u5c06\u73b0\u6709\u914d\u7f6e\u6587\u4ef6\u6dfb\u52a0\u5230chezmoi\nchezmoi add $HOME/.gitconfig\nchezmoi add $HOME/.ssh/config\nchezmoi add $HOME/Documents/PowerShell/Microsoft.PowerShell_profile.ps1\nchezmoi add $HOME/AppData/Roaming/Code/User/settings.json\n\n# \u63d0\u4ea4\u5e76\u63a8\u9001\u66f4\u6539\nchezmoi cd\ngit add .\ngit commit -m \"Initial Windows config\"\ngit push\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#3","title":"3. \u5bfc\u51fa\u8f6f\u4ef6\u5305\u5217\u8868","text":"PowerShell<pre><code># \u5bfc\u51faScoop\u5305\u5217\u8868\nscoop export &gt; packages/scoop-packages.txt\n\n# \u63d0\u4ea4\u5305\u5217\u8868\nchezmoi cd\ngit add packages/scoop-packages.txt\ngit commit -m \"Add Windows package list\"\ngit push\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#ubuntu","title":"Ubuntu \u914d\u7f6e","text":""},{"location":"Tools/Others/Chezmoi/#1_2","title":"1. \u5b89\u88c5\u5fc5\u8981\u5de5\u5177","text":"Bash<pre><code># \u5b89\u88c5Git\uff08\u5982\u679c\u8fd8\u6ca1\u6709\uff09\nsudo apt update\nsudo apt install git\n\n# \u5b89\u88c5chezmoi\nsh -c \"$(curl -fsLS get.chezmoi.io)\"\n</code></pre> <p>\u53c2\u8003\u8fd9\u4e2a\u7f51\u7ad9 Install - chezmoi \u8fdb\u884c\u4e0b\u8f7d\uff0c\u6211\u547d\u4ee4\u884c\u4e00\u76f4\u4e0d\u6210\u529f\uff0c\u76f4\u63a5\u9009\u62e9\u5bf9\u5e94\u7684\u5305\u5c31\u884c\u4e86\u3002</p> Text Only<pre><code>sudo dpkg -i chezmoi_2.54.0_linux_amd64.deb\nchezmoi --version\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#2-chezmoi_1","title":"2. \u521d\u59cb\u5316 chezmoi","text":"Bash<pre><code># \u521d\u59cb\u5316chezmoi\u5e76\u514b\u9686\u4f60\u7684\u4ed3\u5e93\nchezmoi init --apply https://github.com/yourusername/dotfiles.git\n\n# \u67e5\u770bchezmoi\u5c06\u8fdb\u884c\u7684\u66f4\u6539\nchezmoi diff\n\n# \u5c06\u73b0\u6709\u914d\u7f6e\u6587\u4ef6\u6dfb\u52a0\u5230chezmoi\nchezmoi add ~/.bashrc\nchezmoi add ~/.zshrc\nchezmoi add ~/.gitconfig\nchezmoi add ~/.ssh/config\nchezmoi add ~/.config/Code/User/settings.json\n\n# \u63d0\u4ea4\u5e76\u63a8\u9001\u66f4\u6539\nchezmoi cd\ngit add .\ngit commit -m \"Initial Ubuntu config\"\ngit push\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#3_1","title":"3. \u5bfc\u51fa\u8f6f\u4ef6\u5305\u5217\u8868","text":"Bash<pre><code>chezmoi cd\nmkdir packages\n# \u5bfc\u51faapt\u5305\u5217\u8868\ndpkg --get-selections | grep -v deinstall | awk '{print $1}' &gt; packages/apt-packages.txt\n\n# \u5bfc\u51fasnap\u5305\u5217\u8868\nsnap list | awk '{if (NR&gt;1) print $1}' &gt; packages/snap-packages.txt\n\n# \u63d0\u4ea4\u5305\u5217\u8868\ngit add packages/apt-packages.txt packages/snap-packages.txt\ngit commit -m \"Add Ubuntu package lists\"\ngit push\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#_2","title":"\u65e5\u5e38\u4f7f\u7528","text":""},{"location":"Tools/Others/Chezmoi/#1_3","title":"1. \u66f4\u65b0\u914d\u7f6e","text":"<p>\u5f53\u4f60\u4fee\u6539\u4e86\u914d\u7f6e\u6587\u4ef6\u540e\uff1a</p> Bash<pre><code># \u5c06\u66f4\u6539\u6dfb\u52a0\u5230chezmoi\nchezmoi add ~/.bashrc  # \u6216\u5176\u4ed6\u4fee\u6539\u7684\u914d\u7f6e\u6587\u4ef6\n\n# \u67e5\u770b\u66f4\u6539\nchezmoi diff\n\n# \u63d0\u4ea4\u5e76\u63a8\u9001\u66f4\u6539\nchezmoi cd\ngit add .\ngit commit -m \"Update bashrc\"\ngit push\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#2_1","title":"2. \u5728\u5176\u4ed6\u673a\u5668\u4e0a\u540c\u6b65","text":"Bash<pre><code># \u62c9\u53d6\u5e76\u5e94\u7528\u6700\u65b0\u66f4\u6539\nchezmoi update\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#3_2","title":"3. \u66f4\u65b0\u8f6f\u4ef6\u5305\u5217\u8868","text":"<p>Windows:</p> PowerShell<pre><code># \u66f4\u65b0Scoop\u5305\u5217\u8868\nscoop export &gt; packages/scoop-packages.txt\n</code></pre> <p>Ubuntu:</p> Bash<pre><code># \u66f4\u65b0apt\u5305\u5217\u8868\ndpkg --get-selections | grep -v deinstall | awk '{print $1}' &gt; packages/apt-packages.txt\n\n# \u66f4\u65b0snap\u5305\u5217\u8868\nsnap list | awk '{if (NR&gt;1) print $1}' &gt; packages/snap-packages.txt\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#4","title":"4. \u5728\u65b0\u673a\u5668\u4e0a\u8bbe\u7f6e","text":"<p>Windows:</p> PowerShell<pre><code># \u5b89\u88c5chezmoi\nscoop install chezmoi\n\n# \u521d\u59cb\u5316\u5e76\u5e94\u7528\u914d\u7f6e\nchezmoi init https://github.com/yourusername/dotfiles.git\nchezmoi apply\n</code></pre> <p>Ubuntu:</p> Bash<pre><code># \u5b89\u88c5chezmoi\nsh -c \"$(curl -fsLS get.chezmoi.io)\"\n\n# \u521d\u59cb\u5316\u5e76\u5e94\u7528\u914d\u7f6e\nchezmoi init https://github.com/yourusername/dotfiles.git\nchezmoi apply\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#_3","title":"\u5e38\u89c1\u95ee\u9898","text":""},{"location":"Tools/Others/Chezmoi/#1_4","title":"1. \u5982\u4f55\u5904\u7406\u4e0d\u540c\u673a\u5668\u7684\u7279\u5b9a\u914d\u7f6e\uff1f","text":"<p>\u4f7f\u7528\u6a21\u677f\u548c\u6761\u4ef6\u8bed\u53e5\u3002\u5728 <code>.chezmoi.toml.tmpl</code> \u4e2d\uff1a</p> TOML<pre><code>{{- $osid := .chezmoi.os -}}\n[data]\n    name = \"Your Name\"\n    email = \"your@email.com\"\n    {{- if eq .chezmoi.os \"windows\" }}\n    is_windows = true\n    {{- else if eq .chezmoi.os \"linux\" }}\n    is_linux = true\n    {{- end }}\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#2_2","title":"2. \u5982\u4f55\u5904\u7406\u654f\u611f\u4fe1\u606f\uff1f","text":"<p>\u5bf9\u4e8e\u654f\u611f\u4fe1\u606f\uff0c\u53ef\u4ee5\uff1a</p> <ol> <li>\u4f7f\u7528\u6a21\u677f\u548c\u73af\u5883\u53d8\u91cf</li> <li>\u4f7f\u7528 chezmoi \u7684\u52a0\u5bc6\u529f\u80fd</li> <li>\u5c06\u654f\u611f\u4fe1\u606f\u5b58\u50a8\u5728\u5355\u72ec\u7684\u79c1\u6709\u4ed3\u5e93\u4e2d</li> </ol>"},{"location":"Tools/Others/Chezmoi/#3_3","title":"3. \u5982\u4f55\u64a4\u9500\u66f4\u6539\uff1f","text":"Bash<pre><code># \u67e5\u770b\u5c06\u8981\u8fdb\u884c\u7684\u66f4\u6539\nchezmoi diff\n\n# \u5982\u679c\u4e0d\u6ee1\u610f\uff0c\u53ef\u4ee5\u64a4\u9500\nchezmoi forget ~/.bashrc  # \u79fb\u9664\u6587\u4ef6\u7684\u7ba1\u7406\n\n# \u6216\u8005\u91cd\u7f6e\u4e3a\u539f\u59cb\u72b6\u6001\nchezmoi apply --force\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#4_1","title":"4. \u914d\u7f6e\u6587\u4ef6\u6743\u9650\u95ee\u9898\uff1f","text":"<p>chezmoi \u4f1a\u81ea\u52a8\u5904\u7406\u6587\u4ef6\u6743\u9650\u3002\u5bf9\u4e8e\u7279\u6b8a\u6743\u9650\u9700\u6c42\uff0c\u53ef\u4ee5\u5728\u6e90\u6587\u4ef6\u540d\u4e2d\u4f7f\u7528\u7279\u6b8a\u524d\u7f00\uff1a</p> <ul> <li><code>private_</code> : \u521b\u5efa\u79c1\u6709\u6587\u4ef6 (chmod 600)</li> <li><code>executable_</code> : \u521b\u5efa\u53ef\u6267\u884c\u6587\u4ef6 (chmod 700)</li> <li><code>readonly_</code> : \u521b\u5efa\u53ea\u8bfb\u6587\u4ef6 (chmod 400)</li> </ul>"},{"location":"Tools/Others/Chezmoi/#5","title":"5. \u5982\u4f55\u67e5\u770b\u7ba1\u7406\u7684\u6587\u4ef6\uff1f","text":"Bash<pre><code># \u5217\u51fa\u6240\u6709\u7ba1\u7406\u7684\u6587\u4ef6\nchezmoi managed\n\n# \u67e5\u770b\u6e90\u6587\u4ef6\nchezmoi cd\nls -la\n</code></pre>"},{"location":"Tools/Others/Chezmoi/#6","title":"6. \u66f4\u65b0\u51fa\u9519\u600e\u4e48\u529e\uff1f","text":"Bash<pre><code># \u5907\u4efd\u5f53\u524d\u72b6\u6001\nchezmoi archive --output=backup.tar.gz\n\n# \u91cd\u7f6e\u66f4\u6539\nchezmoi init --force\n\n# \u91cd\u65b0\u5e94\u7528\u914d\u7f6e\nchezmoi apply\n</code></pre>"},{"location":"Tools/Others/SSH/","title":"SSH\u914d\u7f6e\u6307\u5357","text":""},{"location":"Tools/Others/SSH/#ssh","title":"SSH\u914d\u7f6e\u6307\u5357","text":"<p> \u7ea6 641 \u4e2a\u5b57  195 \u884c\u4ee3\u7801  1 \u5f20\u56fe\u7247  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 6 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"Tools/Others/SSH/#ssh_1","title":"\u4e00\u3001SSH\u57fa\u7840\u6982\u5ff5","text":""},{"location":"Tools/Others/SSH/#1-ssh","title":"1. SSH\u5de5\u4f5c\u539f\u7406","text":"<p>SSH(Secure Shell)\u662f\u4e00\u79cd\u52a0\u5bc6\u7684\u7f51\u7edc\u534f\u8bae\uff0c\u901a\u8fc7\u5728\u4e0d\u5b89\u5168\u7684\u7f51\u7edc\u4e0a\u4e3a\u7f51\u7edc\u670d\u52a1\u63d0\u4f9b\u5b89\u5168\u7684\u4f20\u8f93\u73af\u5883\u3002SSH\u901a\u8fc7\u4f7f\u7528\u52a0\u5bc6\u6280\u672f\uff0c\u80fd\u591f\u6709\u6548\u9632\u6b62\u4e2d\u95f4\u4eba\u653b\u51fb\uff0c\u4fdd\u62a4\u6570\u636e\u4f20\u8f93\u7684\u5b89\u5168\u3002</p> <p>SSH\u5de5\u4f5c\u6d41\u7a0b\uff1a 1. TCP\u8fde\u63a5\u5efa\u7acb\uff1a\u5ba2\u6237\u7aef\u548c\u670d\u52a1\u5668\u5efa\u7acbTCP\u8fde\u63a5\uff08\u9ed8\u8ba4\u7aef\u53e322\uff09 2. \u7248\u672c\u534f\u5546\uff1a\u53cc\u65b9\u4ea4\u6362\u7248\u672c\u4fe1\u606f\uff0c\u786e\u5b9a\u4f7f\u7528\u7684SSH\u534f\u8bae\u7248\u672c 3. \u5bc6\u94a5\u4ea4\u6362\uff1a\u4f7f\u7528Diffie-Hellman\u7b97\u6cd5\u4ea4\u6362\u4f1a\u8bdd\u5bc6\u94a5 4. \u8ba4\u8bc1\uff1a\u4f7f\u7528\u516c\u94a5\u6216\u5bc6\u7801\u8fdb\u884c\u8eab\u4efd\u9a8c\u8bc1 5. \u4f1a\u8bdd\uff1a\u5efa\u7acb\u52a0\u5bc6\u901a\u4fe1\u901a\u9053</p>"},{"location":"Tools/Others/SSH/#2","title":"2. \u8ba4\u8bc1\u65b9\u5f0f\u8be6\u89e3","text":""},{"location":"Tools/Others/SSH/#21","title":"2.1 \u5bc6\u7801\u8ba4\u8bc1","text":"<ul> <li>\u6700\u7b80\u5355\u4f46\u6700\u4e0d\u5b89\u5168\u7684\u8ba4\u8bc1\u65b9\u5f0f</li> <li>\u5bb9\u6613\u53d7\u5230\u66b4\u529b\u7834\u89e3\u653b\u51fb</li> <li>\u4e0d\u63a8\u8350\u5728\u751f\u4ea7\u73af\u5883\u4e2d\u4f7f\u7528</li> </ul>"},{"location":"Tools/Others/SSH/#22","title":"2.2 \u516c\u94a5\u8ba4\u8bc1","text":"<p>\u8ba4\u8bc1\u6d41\u7a0b 1. \u5ba2\u6237\u7aef\u53d1\u9001\u516c\u94a5\u4fe1\u606f\u7ed9\u670d\u52a1\u5668 2. \u670d\u52a1\u5668\u68c0\u67e5authorized_keys\u6587\u4ef6 3. \u670d\u52a1\u5668\u751f\u6210\u968f\u673a\u5b57\u7b26\u4e32\uff0c\u7528\u516c\u94a5\u52a0\u5bc6\u540e\u53d1\u9001\u7ed9\u5ba2\u6237\u7aef 4. \u5ba2\u6237\u7aef\u7528\u79c1\u94a5\u89e3\u5bc6\uff0c\u5c06\u7ed3\u679c\u8fd4\u56de\u670d\u52a1\u5668 5. \u670d\u52a1\u5668\u9a8c\u8bc1\u7ed3\u679c\uff0c\u5b8c\u6210\u8ba4\u8bc1</p>"},{"location":"Tools/Others/SSH/#3","title":"3. \u5b89\u5168\u5efa\u8bae","text":""},{"location":"Tools/Others/SSH/#31","title":"3.1 \u57fa\u672c\u5b89\u5168\u8bbe\u7f6e","text":"Bash<pre><code># /etc/ssh/sshd_config \u5b89\u5168\u914d\u7f6e\nPermitRootLogin no                 # \u7981\u6b62root\u76f4\u63a5\u767b\u5f55\nPasswordAuthentication no          # \u7981\u7528\u5bc6\u7801\u8ba4\u8bc1\nPubkeyAuthentication yes          # \u542f\u7528\u516c\u94a5\u8ba4\u8bc1\nPermitEmptyPasswords no           # \u7981\u6b62\u7a7a\u5bc6\u7801\nProtocol 2                        # \u53ea\u4f7f\u7528SSH2\u534f\u8bae\nMaxAuthTries 3                    # \u6700\u5927\u8ba4\u8bc1\u5c1d\u8bd5\u6b21\u6570\nLoginGraceTime 30                 # \u767b\u5f55\u8d85\u65f6\u65f6\u95f4\nX11Forwarding no                  # \u7981\u7528X11\u8f6c\u53d1\uff08\u9664\u975e\u9700\u8981\uff09\nAllowUsers user1 user2            # \u9650\u5236\u5141\u8bb8\u767b\u5f55\u7684\u7528\u6237\n</code></pre>"},{"location":"Tools/Others/SSH/#32","title":"3.2 \u5bc6\u94a5\u7ba1\u7406","text":"Bash<pre><code># \u751f\u6210\u5f3a\u5bc6\u94a5\nssh-keygen -t ed25519 -C \"your_email@example.com\" -a 100\n\n# \u5bc6\u94a5\u6743\u9650\u8bbe\u7f6e\nchmod 700 ~/.ssh\nchmod 600 ~/.ssh/id_ed25519\nchmod 644 ~/.ssh/id_ed25519.pub\nchmod 600 ~/.ssh/authorized_keys\nchmod 600 ~/.ssh/known_hosts\n</code></pre>"},{"location":"Tools/Others/SSH/#ssh_2","title":"\u5e38\u7528\u7684 SSH \u547d\u4ee4","text":"<p>SSH \u6559\u7a0b \u83dc\u9e1f\u6559\u7a0b</p>"},{"location":"Tools/Others/SSH/#_1","title":"\u4e8c\u3001\u5b8c\u6574\u914d\u7f6e\u6307\u5357","text":""},{"location":"Tools/Others/SSH/#1-linux","title":"1. Linux\u670d\u52a1\u5668\u914d\u7f6e","text":"Bash<pre><code># 1. \u5b89\u88c5SSH\u670d\u52a1\u5668\nsudo apt update\nsudo apt install openssh-server\n\n# 2. \u914d\u7f6eSSH\u670d\u52a1\nsudo nano /etc/ssh/sshd_config\n\n# 3. \u57fa\u672c\u5b89\u5168\u914d\u7f6e\nPort 22                          # \u53ef\u4ee5\u4fee\u6539\u4e3a\u975e\u6807\u51c6\u7aef\u53e3\nListenAddress 0.0.0.0            # \u76d1\u542c\u5730\u5740\nProtocol 2\nPermitRootLogin no\nPasswordAuthentication no\nPubkeyAuthentication yes\nAuthorizedKeysFile .ssh/authorized_keys\nUsePAM yes\nX11Forwarding no\nPrintMotd no\nAcceptEnv LANG LC_*\nSubsystem sftp /usr/lib/openssh/sftp-server\n\n# 4. \u91cd\u542fSSH\u670d\u52a1\nsudo systemctl restart sshd\n\n# 5. \u68c0\u67e5\u670d\u52a1\u72b6\u6001\nsudo systemctl status sshd\n</code></pre>"},{"location":"Tools/Others/SSH/#2-windows-ssh","title":"2. Windows SSH\u914d\u7f6e","text":""},{"location":"Tools/Others/SSH/#21-openssh","title":"2.1 \u5b89\u88c5OpenSSH","text":"PowerShell<pre><code># \u4f7f\u7528PowerShell\u5b89\u88c5OpenSSH\n# \u68c0\u67e5OpenSSH\u72b6\u6001\nGet-WindowsCapability -Online | Where-Object Name -like 'OpenSSH*'\n\n# \u5b89\u88c5\u5ba2\u6237\u7aef\u548c\u670d\u52a1\u5668\nAdd-WindowsCapability -Online -Name OpenSSH.Client~~~~0.0.1.0\nAdd-WindowsCapability -Online -Name OpenSSH.Server~~~~0.0.1.0\n\n# \u542f\u52a8SSH\u670d\u52a1\nStart-Service sshd\nSet-Service -Name sshd -StartupType 'Automatic'\n</code></pre> \u5982\u679c\u6709\u7f51\u7edc\u95ee\u9898\u53ef\u4ee5\u4e0b\u8f7d\u5e76\u5b89\u88c5 OpenSSH \u7684\u79bb\u7ebf\u5b89\u88c5\u5305\uff1a   <ul> <li>\u60a8\u53ef\u4ee5\u5c1d\u8bd5\u4ece GitHub \u4e0a\u4e0b\u8f7d OpenSSH \u7684\u79bb\u7ebf\u5b89\u88c5\u5305\uff0c\u5e76\u6309\u7167\u4ee5\u4e0b\u6b65\u9aa4\u8fdb\u884c\u5b89\u88c5\uff1a  <ol> <li>\u8bbf\u95ee GitHub \u4e0a\u7684 Win32-OpenSSH \u53d1\u5e03\u9875\u9762\uff1aWin32-OpenSSH Releases </li> <li>\u4e0b\u8f7d\u9002\u7528\u4e8e\u60a8\u7684\u7cfb\u7edf\u7684\u5b89\u88c5\u5305\uff08Win32 \u6216 Win64\uff09\u3002  </li> <li>\u89e3\u538b\u4e0b\u8f7d\u7684\u6587\u4ef6\u5230\u4e00\u4e2a\u76ee\u5f55\u3002  </li> <li>\u4ee5\u7ba1\u7406\u5458\u6743\u9650\u6253\u5f00\u547d\u4ee4\u63d0\u793a\u7b26\uff08cmd\uff09\uff0c\u5e76\u5bfc\u822a\u5230\u89e3\u538b\u7684\u76ee\u5f55\u3002  </li> <li>\u8fd0\u884c\u00a0<code>powershell.exe -ExecutionPolicy Bypass -File install-sshd.ps1</code>\u00a0\u6765\u5b89\u88c5 OpenSSH \u670d\u52a1\u3002 </li> </ol> </li> </ul>"},{"location":"Tools/Others/SSH/#22-windows-ssh","title":"2.2 \u914d\u7f6eWindows SSH\u670d\u52a1","text":"PowerShell<pre><code># \u7f16\u8f91SSH\u914d\u7f6e\u6587\u4ef6\nnotepad \"$env:ProgramData\\ssh\\sshd_config\"\n\n# \u57fa\u672c\u914d\u7f6e\u5185\u5bb9\u4e0eLinux\u7c7b\u4f3c\uff0c\u4f46\u8def\u5f84\u9700\u8981\u8c03\u6574\nPubkeyAuthentication yes\nPasswordAuthentication no\nSubsystem sftp sftp-server.exe\n</code></pre>"},{"location":"Tools/Others/SSH/#3-ssh","title":"3. SSH\u5ba2\u6237\u7aef\u914d\u7f6e","text":""},{"location":"Tools/Others/SSH/#31-ssh","title":"3.1 \u521b\u5efaSSH\u914d\u7f6e\u6587\u4ef6","text":"Bash<pre><code># ~/.ssh/config\n# \u5168\u5c40\u8bbe\u7f6e\nHost *\n    ServerAliveInterval 60\n    ServerAliveCountMax 3\n    HashKnownHosts yes\n    GSSAPIAuthentication no\n\n# GitHub\nHost github.com\n    HostName github.com\n    User git\n    IdentityFile ~/.ssh/github_ed25519\n    AddKeysToAgent yes\n\n# \u5f00\u53d1\u670d\u52a1\u5668\nHost dev\n    HostName dev.example.com\n    User developer\n    Port 22\n    IdentityFile ~/.ssh/dev_ed25519\n    ForwardAgent yes\n\n# \u751f\u4ea7\u670d\u52a1\u5668\nHost prod\n    HostName prod.example.com\n    User deployer\n    Port 22\n    IdentityFile ~/.ssh/prod_ed25519\n    ForwardAgent no\n</code></pre>"},{"location":"Tools/Others/SSH/#_2","title":"\u4e09\u3001\u5177\u4f53\u5b9e\u8df5\uff0c\u7528\u7b14\u8bb0\u672c\u8fde\u53f0\u5f0f\u673a","text":""},{"location":"Tools/Others/SSH/#_3","title":"\u53f0\u5f0f\u7535\u8111\uff08\u670d\u52a1\u7aef\uff09\u914d\u7f6e\uff1a","text":"<ol> <li>\u5b89\u88c5\u5e76\u542f\u52a8SSH\u670d\u52a1:</li> </ol> Bash<pre><code># Ubuntu/Debian\u7cfb\u7edf\nsudo apt install openssh-server\nsudo systemctl enable ssh\nsudo systemctl start ssh\n\n# \u68c0\u67e5SSH\u670d\u52a1\u72b6\u6001\nsudo systemctl status ssh\n</code></pre> <ol> <li>\u914d\u7f6eSSH\u670d\u52a1:</li> </ol> Bash<pre><code># \u7f16\u8f91SSH\u670d\u52a1\u5668\u914d\u7f6e\nsudo nano /etc/ssh/sshd_config\n\n# \u6dfb\u52a0\u6216\u4fee\u6539\u4ee5\u4e0b\u914d\u7f6e\nPermitRootLogin no\nPasswordAuthentication no\nPubkeyAuthentication yes\nAllowUsers your_username    # \u66ff\u6362\u4e3a\u60a8\u7684\u7528\u6237\u540d\n</code></pre> <ol> <li>\u8bbe\u7f6e\u56fa\u5b9aIP\u6216\u52a8\u6001DNS:</li> </ol> Bash<pre><code># \u67e5\u770b\u5f53\u524dIP\nip addr show\n\n# \u5982\u679c\u662f\u52a8\u6001IP\uff0c\u5efa\u8bae\u8bbe\u7f6e\u9759\u6001IP\u6216\u4f7f\u7528\u52a8\u6001DNS\u670d\u52a1\n</code></pre>"},{"location":"Tools/Others/SSH/#_4","title":"\u7b14\u8bb0\u672c\uff08\u5ba2\u6237\u7aef\uff09\u914d\u7f6e\uff1a","text":"<ol> <li>\u751f\u6210SSH\u5bc6\u94a5\u5bf9\uff08\u5982\u679c\u8fd8\u6ca1\u6709\uff09:</li> </ol> Bash<pre><code>ssh-keygen -t ed25519 -C \"your_laptop\"\n</code></pre> <ol> <li>\u5c06\u516c\u94a5\u590d\u5236\u5230\u53f0\u5f0f\u673a:</li> </ol> Bash<pre><code># \u65b9\u6cd51\uff1a\u4f7f\u7528ssh-copy-id\nssh-copy-id -i ~/.ssh/id_ed25519.pub username@desktop_ip\n\n# \u65b9\u6cd52\uff1a\u624b\u52a8\u590d\u5236\ncat ~/.ssh/id_ed25519.pub | ssh username@desktop_ip \"mkdir -p ~/.ssh &amp;&amp; cat &gt;&gt; ~/.ssh/authorized_keys\"\n</code></pre> <ol> <li>\u914d\u7f6eSSH\u5ba2\u6237\u7aef:</li> </ol> Bash<pre><code># \u7f16\u8f91 ~/.ssh/config\nnano ~/.ssh/config\n\n# \u6dfb\u52a0\u4ee5\u4e0b\u914d\u7f6e\nHost desktop\n    HostName 192.168.1.xxx  # \u66ff\u6362\u4e3a\u53f0\u5f0f\u673a\u7684IP\n    User your_username      # \u66ff\u6362\u4e3a\u60a8\u7684\u7528\u6237\u540d\n    Port 22\n    IdentityFile ~/.ssh/id_ed25519\n    ForwardX11 yes         # \u5982\u679c\u9700\u8981\u56fe\u5f62\u754c\u9762\u8f6c\u53d1\n    ForwardAgent yes\n    Compression yes\n    ServerAliveInterval 60\n</code></pre>"},{"location":"Tools/Others/SSH/#_5","title":"\u5e38\u7528\u8fde\u63a5\u547d\u4ee4\uff1a","text":"<ol> <li>\u57fa\u672c\u8fde\u63a5:</li> </ol> Bash<pre><code># \u4ece\u7b14\u8bb0\u672c\u8fde\u63a5\u5230\u53f0\u5f0f\u673a\nssh desktop\n\n# \u4f7f\u7528\u56fe\u5f62\u754c\u9762\u8f6c\u53d1\nssh -X desktop\n</code></pre> <ol> <li>\u6587\u4ef6\u4f20\u8f93:</li> </ol> Bash<pre><code># \u4ece\u7b14\u8bb0\u672c\u590d\u5236\u6587\u4ef6\u5230\u53f0\u5f0f\u673a\nscp /path/to/local/file desktop:/path/to/remote/\n\n# \u4ece\u53f0\u5f0f\u673a\u590d\u5236\u6587\u4ef6\u5230\u7b14\u8bb0\u672c\nscp desktop:/path/to/remote/file /path/to/local/\n</code></pre> <ol> <li>\u7aef\u53e3\u8f6c\u53d1:</li> </ol> Bash<pre><code># \u672c\u5730\u7aef\u53e3\u8f6c\u53d1\nssh -L 8080:localhost:80 desktop\n\n# \u8fdc\u7a0b\u7aef\u53e3\u8f6c\u53d1\nssh -R 8080:localhost:80 desktop\n</code></pre>"},{"location":"Tools/Others/SSH/#_6","title":"\u56db\u3001\u9ad8\u7ea7\u64cd\u4f5c","text":""},{"location":"Tools/Others/SSH/#1-ssh_1","title":"1. SSH\u7aef\u53e3\u8f6c\u53d1","text":""},{"location":"Tools/Others/SSH/#11","title":"1.1 \u672c\u5730\u7aef\u53e3\u8f6c\u53d1","text":"Bash<pre><code># \u5c06\u672c\u57308080\u7aef\u53e3\u8f6c\u53d1\u5230\u8fdc\u7a0b80\u7aef\u53e3\nssh -L 8080:localhost:80 user@remote\n\n# \u4f7f\u7528\u914d\u7f6e\u6587\u4ef6\u8bbe\u7f6e\nHost tunnel\n    HostName remote.example.com\n    LocalForward 8080 localhost:80\n</code></pre>"},{"location":"Tools/Others/SSH/#12","title":"1.2 \u8fdc\u7a0b\u7aef\u53e3\u8f6c\u53d1","text":"Bash<pre><code># \u5c06\u8fdc\u7a0b3000\u7aef\u53e3\u8f6c\u53d1\u5230\u672c\u57303000\u7aef\u53e3\nssh -R 3000:localhost:3000 user@remote\n\n# \u914d\u7f6e\u6587\u4ef6\u8bbe\u7f6e\nHost remote-tunnel\n    HostName remote.example.com\n    RemoteForward 3000 localhost:3000\n</code></pre>"},{"location":"Tools/Others/SSH/#2-ssh","title":"2. SSH\u4ee3\u7406\u8f6c\u53d1","text":"Bash<pre><code># \u542f\u7528\u4ee3\u7406\u8f6c\u53d1\nssh -A user@remote\n\n# \u914d\u7f6e\u6587\u4ef6\u8bbe\u7f6e\nHost *\n    ForwardAgent yes\n    AddKeysToAgent yes\n</code></pre>"},{"location":"Tools/Others/SSH/#3_1","title":"3. \u8df3\u677f\u673a\u914d\u7f6e","text":"Bash<pre><code># \u901a\u8fc7\u8df3\u677f\u673a\u8fde\u63a5\nssh -J jumphost user@target\n\n# \u914d\u7f6e\u6587\u4ef6\u8bbe\u7f6e\nHost target\n    HostName target.example.com\n    ProxyJump jumphost\n</code></pre>"},{"location":"Tools/Others/SSH/#_7","title":"\u4e94\u3001\u6545\u969c\u6392\u67e5","text":""},{"location":"Tools/Others/SSH/#1","title":"1. \u6700\u4f73\u5b9e\u8df5","text":"Bash<pre><code># 1. \u4f7f\u7528SSH\u914d\u7f6e\u6587\u4ef6\u7ba1\u7406\u8fde\u63a5\n# 2. \u4e3a\u4e0d\u540c\u7528\u9014\u4f7f\u7528\u4e0d\u540c\u7684\u5bc6\u94a5\n# 3. \u5b9a\u671f\u8f6e\u6362\u5bc6\u94a5\n# 4. \u4f7f\u7528ssh-agent\u7ba1\u7406\u5bc6\u94a5\n# 5. \u5907\u4efdSSH\u914d\u7f6e\u548c\u5bc6\u94a5\n</code></pre>"},{"location":"Tools/Others/SSH/#2_1","title":"2. \u5e38\u89c1\u95ee\u9898\u89e3\u51b3","text":"Bash<pre><code># \u8fde\u63a5\u88ab\u62d2\u7edd\nssh -v user@host  # \u67e5\u770b\u8be6\u7ec6\u8fde\u63a5\u4fe1\u606f\n\n# \u6743\u9650\u95ee\u9898\nls -la ~/.ssh     # \u68c0\u67e5\u6743\u9650\nchmod 600 ~/.ssh/id_ed25519\n\n# \u5bc6\u94a5\u95ee\u9898\nssh-add -l        # \u67e5\u770b\u5df2\u52a0\u8f7d\u7684\u5bc6\u94a5\nssh-add ~/.ssh/id_ed25519  # \u6dfb\u52a0\u5bc6\u94a5\u5230agent\n</code></pre>"},{"location":"Tools/Others/SSH/#3_2","title":"3. \u65e5\u5fd7\u67e5\u770b","text":"Bash<pre><code># \u670d\u52a1\u5668\u7aef\nsudo tail -f /var/log/auth.log    # Debian/Ubuntu\nsudo tail -f /var/log/secure      # CentOS/RHEL\n\n# \u5ba2\u6237\u7aef\u8c03\u8bd5\nssh -vvv user@host  # \u6700\u8be6\u7ec6\u7684\u8c03\u8bd5\u4fe1\u606f\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/","title":"Tabby + Zsh \u914d\u7f6e\u6307\u5357","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#tabby-zsh","title":"Tabby + Zsh \u914d\u7f6e\u6307\u5357","text":"<p> \u7ea6 236 \u4e2a\u5b57  789 \u884c\u4ee3\u7801  \u9884\u8ba1\u9605\u8bfb\u65f6\u95f4 11 \u5206\u949f  \u5171\u88ab\u8bfb\u8fc7  \u6b21</p>"},{"location":"Tools/Terminal/Tabby_Zsh/#_1","title":"\u524d\u7f6e\u51c6\u5907","text":"<p>\u7cfb\u7edf\u8981\u6c42</p> Bash<pre><code># Ubuntu/Debian\nsudo apt update\nsudo apt install -y \\\n    git \\\n    curl \\\n    wget \\\n    build-essential \\\n    cmake \\\n    python3-pip \\\n    pkg-config \\\n    libssl-dev\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#zsh","title":"ZSH \u57fa\u7840\u914d\u7f6e","text":"<p>ZSH \u5b89\u88c5</p> Bash<pre><code># \u5b89\u88c5zsh\nsudo apt install zsh\n\n# \u8bbe\u7f6e\u4e3a\u9ed8\u8ba4shell\nchsh -s $(which zsh)\n\n# \u786e\u8ba4\u8bbe\u7f6e\necho $SHELL\n# \u5e94\u8be5\u8f93\u51fa: /usr/bin/zsh\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#1-oh-my-zsh","title":"1. Oh My Zsh \u5b89\u88c5","text":"Bash<pre><code># \u5b89\u88c5Oh My Zsh\nsh -c \"$(curl -fsSL https://raw.github.com/ohmyzsh/ohmyzsh/master/tools/install.sh)\"\n\n# \u5907\u4efd\u9ed8\u8ba4\u914d\u7f6e\ncp ~/.zshrc ~/.zshrc.backup\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#2","title":"2. \u63d2\u4ef6\u7ba1\u7406\u5668\u5b89\u88c5","text":"Bash<pre><code># \u5b89\u88c5zinit\nbash -c \"$(curl --fail --show-error --silent --location https://raw.githubusercontent.com/zdharma-continuum/zinit/HEAD/scripts/install.sh)\"\n\n# \u7b49\u5f85\u5b89\u88c5\u5b8c\u6210\u540e\u91cd\u542f\u7ec8\u7aef\nexec zsh\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#3","title":"3. \u57fa\u7840\u914d\u7f6e\u6587\u4ef6","text":"Bash<pre><code># \u521b\u5efa\u65b0\u7684\u914d\u7f6e\u6587\u4ef6\ncat &lt;&lt; 'EOF' &gt; ~/.zshrc\n# \u57fa\u7840\u8bbe\u7f6e\nexport ZSH=\"$HOME/.oh-my-zsh\"\nexport LANG=en_US.UTF-8\nexport EDITOR='nvim'\nexport VISUAL='nvim'\n\n# zinit\u914d\u7f6e\nsource \"$HOME/.local/share/zinit/zinit.git/zinit.zsh\"\nautoload -Uz _zinit\n(( ${+_comps} )) &amp;&amp; _comps[zinit]=_zinit\n\n# \u52a0\u8f7d\u6838\u5fc3\u63d2\u4ef6\nzinit ice depth=1; zinit light romkatv/powerlevel10k  # \u4e3b\u9898\nzinit light zsh-users/zsh-autosuggestions           # \u547d\u4ee4\u5efa\u8bae\nzinit light zsh-users/zsh-syntax-highlighting       # \u8bed\u6cd5\u9ad8\u4eae\nzinit light zsh-users/zsh-completions              # \u8865\u5168\u589e\u5f3a\nzinit light agkozak/zsh-z                          # \u76ee\u5f55\u8df3\u8f6c\n\n# \u5386\u53f2\u8bb0\u5f55\u8bbe\u7f6e\nHISTFILE=\"$HOME/.zsh_history\"\nHISTSIZE=50000\nSAVEHIST=50000\nsetopt EXTENDED_HISTORY          # \u8bb0\u5f55\u547d\u4ee4\u65f6\u95f4\u6233\nsetopt HIST_EXPIRE_DUPS_FIRST   # \u4f18\u5148\u5220\u9664\u91cd\u590d\u547d\u4ee4\nsetopt HIST_IGNORE_DUPS         # \u5ffd\u7565\u8fde\u7eed\u91cd\u590d\u547d\u4ee4\nsetopt HIST_IGNORE_SPACE        # \u5ffd\u7565\u4ee5\u7a7a\u683c\u5f00\u5934\u7684\u547d\u4ee4\nsetopt HIST_VERIFY              # \u6267\u884c\u5386\u53f2\u547d\u4ee4\u524d\u5c55\u793a\nsetopt INC_APPEND_HISTORY       # \u5b9e\u65f6\u6dfb\u52a0\u5386\u53f2\u8bb0\u5f55\nsetopt SHARE_HISTORY           # \u5171\u4eab\u5386\u53f2\u8bb0\u5f55\n\n# \u76ee\u5f55\u8bbe\u7f6e\nsetopt AUTO_CD              \nsetopt AUTO_PUSHD          \nsetopt PUSHD_IGNORE_DUPS   \nsetopt PUSHD_MINUS         \nDIRSTACKSIZE=20\n\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#4","title":"4. \u5b9e\u7528\u522b\u540d\u8bbe\u7f6e","text":"Bash<pre><code># \u6dfb\u52a0\u5230~/.zshrc\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# \u57fa\u7840\u547d\u4ee4\u589e\u5f3a\nalias ls='ls --color=auto'\nalias ll='ls -lah'\nalias la='ls -A'\nalias l='ls -CF'\nalias grep='grep --color=auto'\nalias rm='rm -i'\nalias cp='cp -i'\nalias mv='mv -i'\nalias mkdir='mkdir -p'\nalias df='df -h'\nalias free='free -m'\nalias duf='du -sh *'\nalias ps='ps auxf'\nalias ping='ping -c 5'\nalias root='sudo -i'\nalias reboot='sudo reboot'\nalias poweroff='sudo poweroff'\n\n# Git\u5feb\u6377\u547d\u4ee4\nalias gs='git status'\nalias ga='git add'\nalias gaa='git add --all'\nalias gc='git commit -m'\nalias gp='git push'\nalias gl='git pull'\nalias gd='git diff'\nalias gco='git checkout'\nalias gb='git branch'\nalias gm='git merge'\nalias glog='git log --oneline --decorate --graph'\n\n# Docker\u5feb\u6377\u547d\u4ee4\nalias dk='docker'\nalias dkc='docker-compose'\nalias dkps='docker ps'\nalias dkst='docker stats'\nalias dktop='docker top'\nalias dkimg='docker images'\nalias dkpull='docker pull'\nalias dkex='docker exec -it'\n\n# \u5feb\u901f\u7f16\u8f91\nalias zshconfig=\"$EDITOR ~/.zshrc\"\nalias zshreload=\"source ~/.zshrc\"\nalias vimconfig=\"$EDITOR ~/.vimrc\"\nalias tmuxconfig=\"$EDITOR ~/.tmux.conf\"\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#5","title":"5. \u5b9e\u7528\u51fd\u6570","text":"Bash<pre><code># \u6dfb\u52a0\u5230~/.zshrc\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# \u521b\u5efa\u5e76\u8fdb\u5165\u76ee\u5f55\nmkcd() {\n    mkdir -p \"$1\" &amp;&amp; cd \"$1\"\n}\n\n# \u63d0\u53d6\u538b\u7f29\u6587\u4ef6\nextract() {\n    if [ -f $1 ]; then\n        case $1 in\n            *.tar.bz2)   tar xjf $1     ;;\n            *.tar.gz)    tar xzf $1     ;;\n            *.bz2)       bunzip2 $1     ;;\n            *.rar)       unrar e $1     ;;\n            *.gz)        gunzip $1      ;;\n            *.tar)       tar xf $1      ;;\n            *.tbz2)      tar xjf $1     ;;\n            *.tgz)       tar xzf $1     ;;\n            *.zip)       unzip $1       ;;\n            *.Z)         uncompress $1  ;;\n            *.7z)        7z x $1        ;;\n            *)          echo \"'$1' cannot be extracted\" ;;\n        esac\n    else\n        echo \"'$1' is not a valid file\"\n    fi\n}\n\n# \u5feb\u901f\u67e5\u627e\u6587\u4ef6\nff() { find . -type f -iname \"*$1*\" ; }\nfd() { find . -type d -iname \"*$1*\" ; }\n\n# \u5feb\u901f\u67e5\u770b\u8fdb\u7a0b\npsg() { ps aux | grep -v grep | grep -i -e VSZ -e \"$1\"; }\n\n# \u7f51\u7edc\u5de5\u5177\nmyip() {\n    curl -s http://ipecho.net/plain\n    echo\n}\n\n# \u5feb\u901fHTTP\u670d\u52a1\u5668\nserve() {\n    local port=\"${1:-8000}\"\n    python3 -m http.server \"$port\"\n}\n\n# Git\u65e5\u5fd7\u7f8e\u5316\ngll() {\n    git log --graph --pretty=format:'%Cred%h%Creset -%C(yellow)%d%Creset %s %Cgreen(%cr) %C(bold blue)&lt;%an&gt;%Creset' --abbrev-commit\n}\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#_2","title":"\u4e3b\u9898\u7f8e\u5316\u4e0e\u63d2\u4ef6\u589e\u5f3a","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#powerlevel10k","title":"\u4e00\u3001Powerlevel10k \u4e3b\u9898\u914d\u7f6e","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#1","title":"1. \u5b89\u88c5\u5fc5\u8981\u5b57\u4f53","text":"Bash<pre><code># \u521b\u5efa\u5b57\u4f53\u76ee\u5f55\nmkdir -p ~/.local/share/fonts\n\n# \u4e0b\u8f7d\u63a8\u8350\u5b57\u4f53\nwget -P /tmp https://github.com/romkatv/powerlevel10k-media/raw/master/MesloLGS%20NF%20Regular.ttf\nwget -P /tmp https://github.com/romkatv/powerlevel10k-media/raw/master/MesloLGS%20NF%20Bold.ttf\nwget -P /tmp https://github.com/romkatv/powerlevel10k-media/raw/master/MesloLGS%20NF%20Italic.ttf\nwget -P /tmp https://github.com/romkatv/powerlevel10k-media/raw/master/MesloLGS%20NF%20Bold%20Italic.ttf\n\n# \u79fb\u52a8\u5b57\u4f53\u6587\u4ef6\nmv /tmp/MesloLGS*.ttf ~/.local/share/fonts/\n\n# \u66f4\u65b0\u5b57\u4f53\u7f13\u5b58\nfc-cache -f -v\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#2_1","title":"2. \u4e3b\u9898\u914d\u7f6e","text":"Bash<pre><code># \u6dfb\u52a0\u5230 ~/.zshrc\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# Powerlevel10k \u914d\u7f6e\n# \u542f\u7528 Powerlevel10k \u5373\u65f6\u63d0\u793a\nif [[ -r \"${XDG_CACHE_HOME:-$HOME/.cache}/p10k-instant-prompt-${(%):-%n}.zsh\" ]]; then\n  source \"${XDG_CACHE_HOME:-$HOME/.cache}/p10k-instant-prompt-${(%):-%n}.zsh\"\nfi\n\n# \u52a0\u8f7d\u4e3b\u9898\nsource ~/.oh-my-zsh/custom/themes/powerlevel10k/powerlevel10k.zsh-theme\n\n# \u4e3b\u9898\u4e2a\u6027\u5316\u8bbe\u7f6e\nPOWERLEVEL9K_MODE='nerdfont-complete'\nPOWERLEVEL9K_LEFT_PROMPT_ELEMENTS=(\n  os_icon                 # \u64cd\u4f5c\u7cfb\u7edf\u56fe\u6807\n  dir                     # \u5f53\u524d\u76ee\u5f55\n  vcs                     # git\u72b6\u6001\n  newline                 # \u6362\u884c\n  prompt_char            # \u63d0\u793a\u7b26\n)\nPOWERLEVEL9K_RIGHT_PROMPT_ELEMENTS=(\n  status                  # \u4e0a\u4e00\u4e2a\u547d\u4ee4\u7684\u72b6\u6001\n  background_jobs        # \u540e\u53f0\u4efb\u52a1\n  load                   # \u7cfb\u7edf\u8d1f\u8f7d\n  ram                    # \u5185\u5b58\u4f7f\u7528\n  time                   # \u65f6\u95f4\n)\n\n# \u76ee\u5f55\u663e\u793a\u8bbe\u7f6e\nPOWERLEVEL9K_DIR_BACKGROUND='blue'\nPOWERLEVEL9K_DIR_FOREGROUND='black'\nPOWERLEVEL9K_SHORTEN_DIR_LENGTH=2\nPOWERLEVEL9K_SHORTEN_STRATEGY=\"truncate_middle\"\n\n# Git\u72b6\u6001\u8bbe\u7f6e\nPOWERLEVEL9K_VCS_CLEAN_BACKGROUND='green'\nPOWERLEVEL9K_VCS_UNTRACKED_BACKGROUND='yellow'\nPOWERLEVEL9K_VCS_MODIFIED_BACKGROUND='red'\nEOF\n\n# \u8fd0\u884c\u914d\u7f6e\u5411\u5bfc\uff08\u9996\u6b21\u4f7f\u7528\uff09\np10k configure\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#_3","title":"\u4e8c\u3001\u9ad8\u7ea7\u63d2\u4ef6\u914d\u7f6e","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#1_1","title":"1. \u9ad8\u7ea7\u8865\u5168\u7cfb\u7edf","text":"Bash<pre><code># \u6dfb\u52a0\u5230 ~/.zshrc\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# \u8865\u5168\u7cfb\u7edf\u914d\u7f6e\nautoload -Uz compinit\ncompinit\n\n# \u8865\u5168\u83dc\u5355\u8bbe\u7f6e\nzstyle ':completion:*' menu select\nzstyle ':completion:*' matcher-list 'm:{a-zA-Z}={A-Za-z}'   # \u5ffd\u7565\u5927\u5c0f\u5199\nzstyle ':completion:*' list-colors ${(s.:.)LS_COLORS}       # \u8865\u5168\u83dc\u5355\u7740\u8272\nzstyle ':completion:*' verbose yes                         # \u8be6\u7ec6\u8865\u5168\u83dc\u5355\nzstyle ':completion:*:descriptions' format '%U%B%d%b%u'     # \u8865\u5168\u83dc\u5355\u683c\u5f0f\nzstyle ':completion:*:warnings' format '%BSorry, no matches for: %d%b'\nzstyle ':completion:*:*:kill:*:processes' list-colors '=(#b) #([0-9]#)*=0=01;31'\nzstyle ':completion:*:kill:*' command 'ps -u $USER -o pid,%cpu,tty,cputime,cmd'\n\n# \u4f7f\u7528\u7f13\u5b58\u52a0\u901f\u8865\u5168\nzstyle ':completion:*' use-cache on\nzstyle ':completion:*' cache-path ~/.zsh/cache\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#2-fzf","title":"2. FZF \u96c6\u6210\u914d\u7f6e","text":"Bash<pre><code># \u5b89\u88c5FZF\ngit clone --depth 1 https://github.com/junegunn/fzf.git ~/.fzf\n~/.fzf/install\n\n# \u6dfb\u52a0\u5230 ~/.zshrc\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# FZF \u914d\u7f6e\nexport FZF_DEFAULT_COMMAND='fd --type f --hidden --follow --exclude .git'\nexport FZF_DEFAULT_OPTS='--height 40% --layout=reverse --border --preview \"bat --style=numbers --color=always --line-range :500 {}\"'\n\n# FZF \u5feb\u6377\u952e\nbindkey '^T' fzf-file-widget\nbindkey '^R' fzf-history-widget\nbindkey '^[c' fzf-cd-widget\n\n# FZF \u51fd\u6570\n# \u5feb\u901f\u6253\u5f00\u6587\u4ef6\nfe() {\n  local file\n  file=$(fzf --query=\"$1\" --select-1 --exit-0)\n  [ -n \"$file\" ] &amp;&amp; ${EDITOR:-vim} \"$file\"\n}\n\n# \u5feb\u901f\u5207\u6362\u76ee\u5f55\nfd() {\n  local dir\n  dir=$(find ${1:-.} -path '*/\\.*' -prune -o -type d -print 2&gt; /dev/null | fzf +m)\n  [ -n \"$dir\" ] &amp;&amp; cd \"$dir\"\n}\n\n# \u641c\u7d22\u5386\u53f2\u547d\u4ee4\nfh() {\n  print -z $( ([ -n \"$ZSH_NAME\" ] &amp;&amp; fc -l 1 || history) | fzf +s --tac | sed -E 's/ *[0-9]*\\*? *//' | sed -E 's/\\\\/\\\\\\\\/g')\n}\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#3_1","title":"3. \u589e\u5f3a\u76ee\u5f55\u5bfc\u822a","text":"Bash<pre><code># \u6dfb\u52a0\u5230 ~/.zshrc\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# \u76ee\u5f55\u4e66\u7b7e\nhash -d proj=~/projects\nhash -d docs=~/Documents\nhash -d dl=~/Downloads\nhash -d pics=~/Pictures\n\n# z \u63d2\u4ef6\u914d\u7f6e\nZSHZ_DATA=~/.local/share/z/data\nZSHZ_MAX_SCORE=5000\nZSHZ_CASE=smart\n\n# \u76ee\u5f55\u5806\u6808\u5bfc\u822a\nsetopt AUTO_PUSHD           # \u81ea\u52a8\u5c06\u76ee\u5f55\u52a0\u5165\u5806\u6808\nsetopt PUSHD_IGNORE_DUPS    # \u5ffd\u7565\u91cd\u590d\u76ee\u5f55\nsetopt PUSHD_SILENT        # \u9759\u9ed8\u6a21\u5f0f\nsetopt PUSHD_TO_HOME       # pushd \u4e0d\u5e26\u53c2\u6570\u65f6\u7b49\u540c\u4e8e pushd $HOME\n\n# \u76ee\u5f55\u522b\u540d\nalias -g ...='../..'\nalias -g ....='../../..'\nalias -g .....='../../../..'\nalias d='dirs -v'\nfor index ({1..9}) alias \"$index\"=\"cd +${index}\"; unset index\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#4_1","title":"4. \u589e\u5f3a\u5386\u53f2\u8bb0\u5f55\u641c\u7d22","text":"Bash<pre><code># \u6dfb\u52a0\u5230 ~/.zshrc\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# \u5386\u53f2\u8bb0\u5f55\u641c\u7d22\u914d\u7f6e\nbindkey '^[[A' history-substring-search-up\nbindkey '^[[B' history-substring-search-down\nbindkey '^P' history-substring-search-up\nbindkey '^N' history-substring-search-down\n\n# \u5386\u53f2\u8bb0\u5f55\u683c\u5f0f\u5316\nHIST_STAMPS=\"yyyy-mm-dd\"\nHISTORY_IGNORE=\"(ls|ls *|cd|cd *|pwd|exit|date|* --help)\"\n\n# \u547d\u4ee4\u6267\u884c\u65f6\u95f4\u663e\u793a\nREPORTTIME=10\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#tabby","title":"Tabby \u7ec8\u7aef\u914d\u7f6e","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#_4","title":"\u4e00\u3001\u5b89\u88c5\u548c\u521d\u59cb\u5316","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#1-tabby","title":"1. \u5b89\u88c5 Tabby","text":"Bash<pre><code># Ubuntu/Debian\nwget https://github.com/Eugeny/tabby/releases/latest/download/tabby-1.0.0-linux-x64.deb\nsudo dpkg -i tabby-*.deb\nsudo apt-get install -f\n\n# \u786e\u4fdd\u5b57\u4f53\u652f\u6301\nfc-cache -fv\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#2_2","title":"2. \u521d\u59cb\u914d\u7f6e","text":"YAML<pre><code># ~/.config/tabby/config.yaml\nconfig:\n  version: 3\n\nterminal:\n  shell: zsh  # \u4f7f\u7528\u524d\u9762\u914d\u7f6e\u7684zsh\n  fontSize: 14\n  lineHeight: 1.2\n  bell: 'off'\n  copyOnSelect: true\n  rightClick: menu\n\n  # \u57fa\u7840\u73af\u5883\u53d8\u91cf\n  environment:\n    TERM: xterm-256color\n    COLORTERM: truecolor\n\n  # \u6027\u80fd\u8bbe\u7f6e\n  performanceMode: true\n  gpuAcceleration: true\n  webGL: true\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#_5","title":"\u4e8c\u3001\u5916\u89c2\u914d\u7f6e","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#1_2","title":"1. \u5b57\u4f53\u8bbe\u7f6e","text":"YAML<pre><code>terminal:\n  font: JetBrainsMono Nerd Font  # \u786e\u4fdd\u5df2\u5b89\u88c5\n  fontSize: 14\n  lineHeight: 1.2\n  ligatures: true  # \u8fde\u5b57\u652f\u6301\n\n  # \u5b57\u4f53\u56de\u9000\n  fallbackFont: 'Sarasa Mono SC'  # \u4e2d\u6587\u652f\u6301\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#2-dracula","title":"2. Dracula \u4e3b\u9898\u914d\u7f6e","text":"YAML<pre><code>profiles:\n  - name: Default\n    theme:\n      name: 'Dracula'\n\n    colors:\n      background: '#282a36'\n      foreground: '#f8f8f2'\n      cursor: '#f8f8f2'\n\n      selection:\n        background: '#44475a'\n        foreground: '#f8f8f2'\n\n      # ANSI Colors\n      black: '#21222c'\n      red: '#ff5555'\n      green: '#50fa7b'\n      yellow: '#f1fa8c'\n      blue: '#bd93f9'\n      magenta: '#ff79c6'\n      cyan: '#8be9fd'\n      white: '#f8f8f2'\n\n      # Bright Colors\n      brightBlack: '#6272a4'\n      brightRed: '#ff6e6e'\n      brightGreen: '#69ff94'\n      brightYellow: '#ffffa5'\n      brightBlue: '#d6acff'\n      brightMagenta: '#ff92df'\n      brightCyan: '#a4ffff'\n      brightWhite: '#ffffff'\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#3_2","title":"3. \u900f\u660e\u80cc\u666f\u914d\u7f6e","text":"YAML<pre><code>terminal:\n  background:\n    type: 'image'  # \u6216 'color'\n    image: '~/.config/tabby/backgrounds/bg.jpg'  # \u81ea\u5b9a\u4e49\u80cc\u666f\u56fe\u7247\n    opacity: 0.85  # \u900f\u660e\u5ea6\n\n  # \u4e9a\u514b\u529b\u6548\u679c\uff08Windows\uff09\n  experimental:\n    vibrancy: true\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#_6","title":"\u4e09\u3001\u5feb\u6377\u952e\u914d\u7f6e","text":"YAML<pre><code>hotkeys:\n  # \u6807\u7b7e\u7ba1\u7406\n  new-tab: ['Ctrl+T']\n  close-tab: ['Ctrl+W']\n  previous-tab: ['Ctrl+Shift+Tab']\n  next-tab: ['Ctrl+Tab']\n\n  # \u5206\u5c4f\u64cd\u4f5c\n  split-right: ['Ctrl+Shift+E']\n  split-bottom: ['Ctrl+Shift+O']\n  split-nav-left: ['Alt+Left']\n  split-nav-right: ['Alt+Right']\n  split-nav-up: ['Alt+Up']\n  split-nav-down: ['Alt+Down']\n\n  # \u7ec8\u7aef\u64cd\u4f5c\n  clear: ['Ctrl+L']\n  copy: ['Ctrl+C']\n  paste: ['Ctrl+V']\n  search: ['Ctrl+Shift+F']\n\n  # \u89c6\u56fe\u63a7\u5236\n  zoom-in: ['Ctrl+Plus']\n  zoom-out: ['Ctrl+Minus']\n  reset-zoom: ['Ctrl+0']\n  toggle-fullscreen: ['F11']\n\n  # \u5feb\u901f\u547d\u4ee4\n  command-palette: ['Ctrl+Shift+P']\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#ssh","title":"\u56db\u3001SSH \u914d\u7f6e","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#1-ssh","title":"1. \u57fa\u7840 SSH \u914d\u7f6e","text":"YAML<pre><code>ssh:\n  auth:\n    agent: true\n    privateKeys:\n      - ~/.ssh/id_ed25519\n      - ~/.ssh/id_rsa\n\n  # \u8fde\u63a5\u4fdd\u6301\n  keepaliveInterval: 30\n  keepaliveCountMax: 3\n\n  # \u8f6c\u53d1\u8bbe\u7f6e\n  forwardAgent: true\n  x11: false\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#2-ssh","title":"2. SSH \u8fde\u63a5\u914d\u7f6e","text":"YAML<pre><code>ssh:\n  profiles:\n    - name: \"\u5f00\u53d1\u670d\u52a1\u5668\"\n      group: \"\u5f00\u53d1\u73af\u5883\"\n      host: dev.example.com\n      port: 22\n      user: username\n      auth: publicKey\n      privateKey: ~/.ssh/id_ed25519\n\n    - name: \"\u751f\u4ea7\u670d\u52a1\u5668\"\n      group: \"\u751f\u4ea7\u73af\u5883\"\n      host: prod.example.com\n      port: 22\n      user: username\n      auth: agent\n\n    - name: \"\u8df3\u677f\u673a\"\n      host: jump.example.com\n      forwardAgent: true\n      jumpHost: true  # \u6807\u8bb0\u4e3a\u8df3\u677f\u673a\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#_7","title":"\u4e94\u3001\u63d2\u4ef6\u914d\u7f6e","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#1_3","title":"1. \u6838\u5fc3\u63d2\u4ef6","text":"YAML<pre><code>plugins:\n  # SSH\u7ba1\u7406\n  ssh:\n    enabled: true\n\n  # \u7ec8\u7aef\u5f55\u5236\n  record:\n    enabled: true\n    directory: ~/terminal-records\n\n  # \u547d\u4ee4\u9762\u677f\n  commander:\n    enabled: true\n\n  # \u4e3b\u9898\u63d2\u4ef6\n  community-color-schemes:\n    enabled: true\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#2_3","title":"2. \u6269\u5c55\u529f\u80fd","text":"YAML<pre><code># \u641c\u7d22\u589e\u5f3a\nsearch:\n  enabled: true\n  searchOptions:\n    regex: true\n    wholeWord: false\n    caseSensitive: false\n\n# \u7ec8\u7aef\u5206\u5272\nsplit:\n  autoRemove: true  # \u81ea\u52a8\u5173\u95ed\u7a7a\u7ec8\u7aef\n  copyOnSelect: true\n  pasteOnMiddleClick: true\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#_8","title":"\u516d\u3001\u6027\u80fd\u4f18\u5316","text":"YAML<pre><code># \u6027\u80fd\u76f8\u5173\u914d\u7f6e\nterminal:\n  # \u57fa\u7840\u4f18\u5316\n  performanceMode: true\n  gpuAcceleration: true\n  webGL: true\n\n  # \u5386\u53f2\u8bb0\u5f55\n  scrollback: 5000\n\n  # \u8fdb\u7a0b\u7ba1\u7406\n  autoClose: true\n  closeOnExit: true\n\n  # \u6e32\u67d3\u4f18\u5316\n  smoothScroll: false\n  experimentalFontRendering: false\n\n  # \u8d44\u6e90\u9650\u5236\n  environment:\n    LIMIT_MEMORY: 512  # MB\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#_9","title":"\u5f00\u53d1\u5de5\u5177\u4e0e\u7ec8\u7aef\u5de5\u5177\u914d\u7f6e","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#_10","title":"\u4e00\u3001\u73b0\u4ee3\u547d\u4ee4\u884c\u5de5\u5177","text":""},{"location":"Tools/Terminal/Tabby_Zsh/#1_4","title":"1. \u57fa\u7840\u5de5\u5177\u5b89\u88c5","text":"Bash<pre><code># \u5b89\u88c5\u57fa\u7840\u5de5\u5177\nsudo apt install -y \\\n    exa `# \u73b0\u4ee3ls\u66ff\u4ee3\u54c1` \\\n    bat `# \u73b0\u4ee3cat\u66ff\u4ee3\u54c1` \\\n    ripgrep `# \u73b0\u4ee3grep\u66ff\u4ee3\u54c1` \\\n    fd-find `# \u73b0\u4ee3find\u66ff\u4ee3\u54c1` \\\n    duf `# \u73b0\u4ee3df\u66ff\u4ee3\u54c1` \\\n    ncdu `# \u78c1\u76d8\u4f7f\u7528\u5206\u6790` \\\n    tldr `# \u547d\u4ee4\u7b80\u5316\u8bf4\u660e` \\\n    jq `# JSON\u5904\u7406` \\\n    fzf `# \u6a21\u7cca\u641c\u7d22`\n\n# \u521b\u5efa\u522b\u540d\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# \u73b0\u4ee3\u547d\u4ee4\u884c\u5de5\u5177\u522b\u540d\nalias ls='exa --icons'\nalias ll='exa -l --icons --git'\nalias la='exa -la --icons --git'\nalias lt='exa -T --icons --git-ignore'\nalias cat='batcat'\nalias find='fd'\nalias du='ncdu'\nalias df='duf'\nalias help='tldr'\n\n# fzf \u914d\u7f6e\nexport FZF_DEFAULT_OPTS=\"--height 40% --layout=reverse --border \\\n    --preview 'batcat --style=numbers --color=always --line-range :500 {}'\"\nexport FZF_DEFAULT_COMMAND='fd --type f --hidden --follow --exclude .git'\nexport FZF_CTRL_T_COMMAND=\"$FZF_DEFAULT_COMMAND\"\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#2-ranger","title":"2. \u6587\u4ef6\u7ba1\u7406\u5668 - Ranger","text":"Bash<pre><code># \u5b89\u88c5ranger\u548c\u4f9d\u8d56\nsudo apt install ranger python3-pillow ueberzug\n\n# \u751f\u6210\u914d\u7f6e\u6587\u4ef6\nranger --copy-config=all\n\n# \u914d\u7f6eRanger\ncat &lt;&lt; 'EOF' &gt; ~/.config/ranger/rc.conf\n# \u57fa\u7840\u8bbe\u7f6e\nset preview_images true\nset preview_images_method ueberzug\nset show_hidden true\nset hostname_in_titlebar false\nset tilde_in_titlebar true\nset line_numbers relative\nset mouse_enabled true\n\n# \u914d\u8272\u65b9\u6848\nset colorscheme solarized\n\n# \u6587\u4ef6\u9884\u89c8\nset use_preview_script true\nset preview_files true\nset preview_directories true\nset collapse_preview true\n\n# \u5feb\u6377\u952e\nmap &lt;C-f&gt; fzf_select\nmap &lt;C-p&gt; shell -w echo %d/%f | xsel -b\nmap &lt;C-g&gt; shell lazygit\nEOF\n\n# \u6dfb\u52a0FZF\u96c6\u6210\ncat &lt;&lt; 'EOF' &gt; ~/.config/ranger/commands.py\nfrom ranger.api.commands import Command\nclass fzf_select(Command):\n    def execute(self):\n        import subprocess\n        import os.path\n        command=\"find -L . \\( -path '*/\\.*' -o -fstype 'dev' -o -fstype 'proc' \\) -prune \\\n            -o -print 2&gt; /dev/null | sed 1d | cut -b3- | fzf +m\"\n        fzf = self.fm.execute_command(command, universal_newlines=True, stdout=subprocess.PIPE)\n        stdout, stderr = fzf.communicate()\n        if fzf.returncode == 0:\n            fzf_file = os.path.abspath(stdout.rstrip('\\n'))\n            if os.path.isdir(fzf_file):\n                self.fm.cd(fzf_file)\n            else:\n                self.fm.select_file(fzf_file)\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#3-htopglances","title":"3. \u7cfb\u7edf\u76d1\u63a7 - htop/glances","text":"Bash<pre><code># \u5b89\u88c5\u5de5\u5177\nsudo apt install htop glances\n\n# htop\u914d\u7f6e\nmkdir -p ~/.config/htop\ncat &lt;&lt; 'EOF' &gt; ~/.config/htop/htoprc\n# \u57fa\u7840\u663e\u793a\u8bbe\u7f6e\nshow_cpu_frequency=1\nshow_cpu_temperature=1\nshow_program_path=0\nhighlight_base_name=1\nhighlight_megabytes=1\nhighlight_threads=1\n\n# \u663e\u793a\u8bbe\u7f6e\nfields=0 48 17 18 38 39 40 2 46 47 49 1\nsort_key=46\nsort_direction=-1\ntree_view=1\ntree_view_always_by_pid=0\n\n# \u989c\u8272\u8bbe\u7f6e\ncolor_scheme=0\nEOF\n\n# glances\u914d\u7f6e\nmkdir -p ~/.config/glances\ncat &lt;&lt; 'EOF' &gt; ~/.config/glances/glances.conf\n[global]\n# \u5237\u65b0\u95f4\u9694\nrefresh=2\n# \u5386\u53f2\u5927\u5c0f\nhistory_size=1200\n\n[cpu]\n# CPU \u8b66\u544a\u9608\u503c\ncareful=50\nwarning=70\ncritical=90\n\n[memory]\n# \u5185\u5b58\u8b66\u544a\u9608\u503c\ncareful=50\nwarning=70\ncritical=90\n\n[network]\n# \u7f51\u7edc\u5e26\u5bbd\u663e\u793a\u5355\u4f4d (bit/sec)\nunit=bit\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#4-git-lazygit","title":"4. Git \u5de5\u5177 - Lazygit","text":"Bash<pre><code># \u5b89\u88c5Lazygit\nLAZYGIT_VERSION=$(curl -s \"https://api.github.com/repos/jesseduffield/lazygit/releases/latest\" | grep -Po '\"tag_name\": \"v\\K[^\"]*')\ncurl -Lo lazygit.tar.gz \"https://github.com/jesseduffield/lazygit/releases/latest/download/lazygit_${LAZYGIT_VERSION}_Linux_x86_64.tar.gz\"\nsudo tar xf lazygit.tar.gz -C /usr/local/bin lazygit\n\n# \u914d\u7f6eLazygit\nmkdir -p ~/.config/lazygit\ncat &lt;&lt; 'EOF' &gt; ~/.config/lazygit/config.yml\ngui:\n  # UI\u4e3b\u9898\n  theme:\n    lightTheme: false\n    activeBorderColor:\n      - green\n      - bold\n    inactiveBorderColor:\n      - white\n    selectedLineBgColor:\n      - reverse\n  # \u5e38\u7528\u8bbe\u7f6e  \n  showFileTree: true\n  showRandomTip: false\n  showCommandLog: false\n\ngit:\n  # git\u8bbe\u7f6e\n  paging:\n    colorArg: always\n    useConfig: true\n  # commit\u8bbe\u7f6e\n  commits:\n    showGraph: always\n    showWholeGraph: true\n  # \u81ea\u52a8\u83b7\u53d6\n  autoFetch: true\n  # \u5206\u652f\u663e\u793a\n  branchLogCmd: \"git log --graph --color=always --abbrev-commit --decorate --date=relative --pretty=medium {{branchName}} --\"\n\nkeybinding:\n  # \u81ea\u5b9a\u4e49\u5feb\u6377\u952e\n  universal:\n    return: '&lt;c-c&gt;'\n    quit: 'q'\n    quit-alt1: '&lt;esc&gt;'\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#5_1","title":"5. \u4ee3\u7801\u641c\u7d22\u5de5\u5177","text":"Bash<pre><code># ripgrep\u914d\u7f6e\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# ripgrep \u914d\u7f6e\nexport RIPGREP_CONFIG_PATH=\"$HOME/.ripgreprc\"\n\n# ripgrep \u522b\u540d\nalias rg='rg --smart-case'\nalias rgf='rg --files | rg'\nalias rgh='rg --hidden'\nalias rgc='rg --count'\n\n# fzf + ripgrep \u96c6\u6210\nfif() {\n    if [ ! \"$#\" -gt 0 ]; then echo \"Need a string to search for!\"; return 1; fi\n    rg --files-with-matches --no-messages \"$1\" | fzf --preview \"highlight -O ansi -l {} 2&gt; /dev/null | rg --colors 'match:bg:yellow' --ignore-case --pretty --context 10 '$1' || rg --ignore-case --pretty --context 10 '$1' {}\"\n}\nEOF\n\n# \u521b\u5efaripgrep\u914d\u7f6e\u6587\u4ef6\ncat &lt;&lt; 'EOF' &gt; ~/.ripgreprc\n# \u9ed8\u8ba4\u914d\u7f6e\n--smart-case\n--hidden\n--follow\n--glob=!.git/*\n\n# \u641c\u7d22\u914d\u7f6e\n--max-columns=150\n--max-columns-preview\n\n# \u989c\u8272\u914d\u7f6e\n--colors=line:fg:yellow\n--colors=line:style:bold\n--colors=path:fg:green\n--colors=path:style:bold\n--colors=match:fg:black\n--colors=match:bg:yellow\n--colors=match:style:nobold\nEOF\n</code></pre>"},{"location":"Tools/Terminal/Tabby_Zsh/#6","title":"6. \u5b9e\u7528\u5f00\u53d1\u5de5\u5177","text":"Bash<pre><code># \u5b89\u88c5\u5f00\u53d1\u8f85\u52a9\u5de5\u5177\nsudo apt install -y \\\n    shellcheck `# shell\u811a\u672c\u68c0\u67e5` \\\n    python3-pip `# Python\u5305\u7ba1\u7406` \\\n    nodejs npm `# Node.js\u73af\u5883` \\\n    golang `# Go\u8bed\u8a00\u73af\u5883` \\\n    docker.io `# Docker\u652f\u6301` \\\n    postgresql-client `# \u6570\u636e\u5e93\u5ba2\u6237\u7aef` \\\n    redis-tools `# Redis\u5ba2\u6237\u7aef` \\\n    mycli `# MySQL\u5ba2\u6237\u7aef` \\\n    httpie `# HTTP\u5ba2\u6237\u7aef`\n\n# \u6dfb\u52a0\u5b9e\u7528\u522b\u540d\u548c\u51fd\u6570\ncat &lt;&lt; 'EOF' &gt;&gt; ~/.zshrc\n# Docker\u522b\u540d\nalias dk='docker'\nalias dkc='docker-compose'\nalias dkps='docker ps'\nalias dkst='docker stats'\nalias dkimg='docker images'\nalias dkpull='docker pull'\nalias dkexec='docker exec -it'\n\n# \u5f00\u53d1\u8f85\u52a9\u51fd\u6570\n# \u5feb\u901fHTTP\u670d\u52a1\u5668\nserve() {\n    local port=\"${1:-8000}\"\n    python3 -m http.server \"$port\"\n}\n\n# JSON\u683c\u5f0f\u5316\njson() {\n    if [ -t 0 ]; then  # \u53c2\u6570\u8f93\u5165\n        python -m json.tool &lt;&lt;&lt; \"$*\" | pygmentize -l json\n    else  # \u7ba1\u9053\u8f93\u5165\n        python -m json.tool | pygmentize -l json\n    fi\n}\n\n# Git\u5206\u652f\u6e05\u7406\ngit-clean() {\n    git branch --merged | egrep -v \"(^\\*|master|main|dev)\" | xargs git branch -d\n}\n\n# \u73af\u5883\u53d8\u91cf\u7ba1\u7406\nenvfile() {\n    if [[ -f \"$1\" ]]; then\n        set -a\n        source \"$1\"\n        set +a\n    else\n        echo \"Error: File $1 not found\"\n        return 1\n    fi\n}\nEOF\n</code></pre>"},{"location":"links/","title":"\u53cb\u94fe","text":""},{"location":"links/#_1","title":"\u53cb\u94fe","text":"<p>Abstract</p> <p>\u670b\u53cb\u4eec\uff01</p> Wnc \u7684\u5496\u5561\u9986 \u6211\u81ea\u5df1\uff01 donotknow DoNotKnow Kinnari \u5f88\u5389\u5bb3\u7684\u5b66\u957f\uff01"}]}
\ No newline at end of file
diff --git a/sitemap.xml b/sitemap.xml
index 8194053c..13ac8a81 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -2,230 +2,230 @@
 <urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
     <url>
          <loc>https://WncFht.github.io/notes/</loc>
-         <lastmod>2024-12-18</lastmod>
+         <lastmod>2024-12-19</lastmod>
     </url>
     <url>
          <loc>https://WncFht.github.io/notes/AI/</loc>
-         <lastmod>2024-12-18</lastmod>
+         <lastmod>2024-12-19</lastmod>
     </url>
     <url>
          <loc>https://WncFht.github.io/notes/AI/Dive%20into%20Deep%20Learning/</loc>
-         <lastmod>2024-12-18</lastmod>
+         <lastmod>2024-12-19</lastmod>
     </url>
     <url>
          <loc>https://WncFht.github.io/notes/AI/%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0%E6%96%B9%E6%B3%95/</loc>
-         <lastmod>2024-12-18</lastmod>
+         <lastmod>2024-12-19</lastmod>
     </url>
     <url>
          <loc>https://WncFht.github.io/notes/AI/CS231n/CS231n_notes/</loc>
-         <lastmod>2024-12-18</lastmod>
+         <lastmod>2024-12-19</lastmod>
     </url>
     <url>
          <loc>https://WncFht.github.io/notes/AI/CS231n/Image%20Classification-Data-driven%20Approach%2C%20k-Nearest%20Neighbor%2C%20train_val_test%20splits/</loc>
-         <lastmod>2024-12-18</lastmod>
+         <lastmod>2024-12-19</lastmod>
     </url>
     <url>
          <loc>https://WncFht.github.io/notes/AI/CS231n/Linear%20classification-Support%20Vector%20Machine%2C%20Softmax/</loc>
-         <lastmod>2024-12-18</lastmod>
+         <lastmod>2024-12-19</lastmod>
     </url>
     <url>
          <loc>https://WncFht.github.io/notes/AI/CS231n/Numpy/</loc>
-         <lastmod>2024-12-18</lastmod>
+         <lastmod>2024-12-19</lastmod>
     </url>
     <url>
          <loc>https://WncFht.github.io/notes/AI/EECS%20498-007/KNN/</loc>
-         <lastmod>2024-12-18</lastmod>
+         <lastmod>2024-12-19</lastmod>
     </url>
     <url>
          <loc>https://WncFht.github.io/notes/AI/EECS%20498-007/Pytorch/</loc>
-         <lastmod>2024-12-18</lastmod>
+         <lastmod>2024-12-19</lastmod>
     </url>
     <url>
          <loc>https://WncFht.github.io/notes/AI/EECS%20498-007/linear_classifer/</loc>
-         <lastmod>2024-12-18</lastmod>
+         <lastmod>2024-12-19</lastmod>
     </url>
     <url>
          <loc>https://WncFht.github.io/notes/AI/FFB6D/FFB6D_Conda/</loc>
-         <lastmod>2024-12-18</lastmod>
+         <lastmod>2024-12-19</lastmod>
     </url>
     <url>
          <loc>https://WncFht.github.io/notes/AI/FFB6D/FFB6D_Docker/</loc>
-         <lastmod>2024-12-18</lastmod>
+         <lastmod>2024-12-19</lastmod>
     </url>
     <url>
          <loc>https://WncFht.github.io/notes/CS_Basic/</loc>
-         <lastmod>2024-12-18</lastmod>
+         <lastmod>2024-12-19</lastmod>
     </url>
     <url>
          <loc>https://WncFht.github.io/notes/CS_Basic/15-213/CSAPP/</loc>
-         <lastmod>2024-12-18</lastmod>
+         <lastmod>2024-12-19</lastmod>
     </url>
     <url>
          <loc>https://WncFht.github.io/notes/CS_Basic/C%2B%2B/Accelerated%20C%2B%2B/</loc>
-         <lastmod>2024-12-18</lastmod>
+         <lastmod>2024-12-19</lastmod>
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