Early_Classification.ipynb

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  "metadata": {
    "colab": {
      "name": "Early Classification.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyO/W8WjFEtux3xRQNvLLXxg",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ashishpatel26/Shapelet-time-Series-Classification/blob/main/Early_Classification.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oRUAPKq8uqOh",
        "outputId": "a66f31de-487e-4da6-dc14-79fa10c2d934"
      },
      "source": [
        "pip install tslearn"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting tslearn\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/95/98/9a67e2869a8b1416eb6e6fd5e69c56f86869980403b18f30bdb5783ade9d/tslearn-0.5.0.5-cp37-cp37m-manylinux2010_x86_64.whl (790kB)\n",
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            "\u001b[?25hRequirement already satisfied: scipy in /usr/local/lib/python3.7/dist-packages (from tslearn) (1.4.1)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from tslearn) (1.19.5)\n",
            "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.7/dist-packages (from tslearn) (0.22.2.post1)\n",
            "Requirement already satisfied: numba in /usr/local/lib/python3.7/dist-packages (from tslearn) (0.51.2)\n",
            "Requirement already satisfied: Cython in /usr/local/lib/python3.7/dist-packages (from tslearn) (0.29.22)\n",
            "Requirement already satisfied: joblib in /usr/local/lib/python3.7/dist-packages (from tslearn) (1.0.1)\n",
            "Requirement already satisfied: llvmlite<0.35,>=0.34.0.dev0 in /usr/local/lib/python3.7/dist-packages (from numba->tslearn) (0.34.0)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (from numba->tslearn) (56.1.0)\n",
            "Installing collected packages: tslearn\n",
            "Successfully installed tslearn-0.5.0.5\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YqXIM3j3udTg",
        "outputId": "772492ca-8a9e-41b6-eb65-ea21ff0e216b"
      },
      "source": [
        "import numpy\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "from tslearn.preprocessing import TimeSeriesScalerMeanVariance\n",
        "from tslearn.early_classification import NonMyopicEarlyClassifier\n",
        "from tslearn.datasets import UCR_UEA_datasets"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/tslearn/clustering/kmeans.py:17: UserWarning: Scikit-learn <0.24 will be deprecated in a future release of tslearn\n",
            "  \"Scikit-learn <0.24 will be deprecated in a \"\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V0_5UHQCumJl"
      },
      "source": [
        "def plot_partial(time_series, t, y_true=0, y_pred=0, color=\"k\"):\n",
        "    plt.plot(time_series[:t+1].ravel(), color=color, linewidth=1.5)\n",
        "    plt.plot(numpy.arange(t+1, time_series.shape[0]),\n",
        "             time_series[t+1:].ravel(),\n",
        "             linestyle=\"dashed\", color=color, linewidth=1.5)\n",
        "    plt.axvline(x=t, color=color, linewidth=1.5)\n",
        "    plt.text(x=t - 20, y=time_series.max() - .25, s=\"Prediction time\")\n",
        "    plt.title(\n",
        "        \"Sample of class {} predicted as class {}\".format(y_true, y_pred)\n",
        "    )\n",
        "    plt.xlim(0, time_series.shape[0] - 1)"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "z3yRsEOtuyTw"
      },
      "source": [
        "numpy.random.seed(0)"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tzhTBPbwu1xT"
      },
      "source": [
        "X_train, y_train, X_test, y_test = UCR_UEA_datasets().load_dataset(\"ECG200\")"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 439
        },
        "id": "ZF4B5NQ4u6Ex",
        "outputId": "a9fad7e7-0b8c-4d18-a51b-d0efe8dd426c"
      },
      "source": [
        "pd.DataFrame(X_train[:,:,0])"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
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              "      <td>-1.714279</td>\n",
              "      <td>-1.649858</td>\n",
              "      <td>-1.032699</td>\n",
              "      <td>-1.423918</td>\n",
              "      <td>-1.782433</td>\n",
              "      <td>-1.025126</td>\n",
              "      <td>-1.798909</td>\n",
              "      <td>-1.793614</td>\n",
              "      <td>-1.085478</td>\n",
              "      <td>-1.574390</td>\n",
              "      <td>-1.036059</td>\n",
              "      <td>-2.130021</td>\n",
              "      <td>-2.038621</td>\n",
              "      <td>-0.055013</td>\n",
              "      <td>-1.140195</td>\n",
              "      <td>-0.704275</td>\n",
              "      <td>0.048723</td>\n",
              "      <td>-0.475854</td>\n",
              "      <td>0.525865</td>\n",
              "      <td>0.244778</td>\n",
              "      <td>0.679932</td>\n",
              "      <td>0.928601</td>\n",
              "      <td>0.573041</td>\n",
              "      <td>1.231607</td>\n",
              "      <td>1.043324</td>\n",
              "      <td>1.580228</td>\n",
              "      <td>...</td>\n",
              "      <td>0.631120</td>\n",
              "      <td>0.694075</td>\n",
              "      <td>0.515071</td>\n",
              "      <td>0.559229</td>\n",
              "      <td>0.555712</td>\n",
              "      <td>0.469694</td>\n",
              "      <td>0.388821</td>\n",
              "      <td>0.343129</td>\n",
              "      <td>0.535598</td>\n",
              "      <td>0.900708</td>\n",
              "      <td>0.656846</td>\n",
              "      <td>0.690033</td>\n",
              "      <td>0.952596</td>\n",
              "      <td>0.547770</td>\n",
              "      <td>-0.167693</td>\n",
              "      <td>0.011532</td>\n",
              "      <td>-0.176488</td>\n",
              "      <td>-0.277706</td>\n",
              "      <td>-0.224836</td>\n",
              "      <td>-0.910723</td>\n",
              "      <td>-0.037932</td>\n",
              "      <td>0.071668</td>\n",
              "      <td>-1.048920</td>\n",
              "      <td>-0.636218</td>\n",
              "      <td>-0.386637</td>\n",
              "      <td>-0.507512</td>\n",
              "      <td>-0.716656</td>\n",
              "      <td>-0.463758</td>\n",
              "      <td>-0.460442</td>\n",
              "      <td>-0.770792</td>\n",
              "      <td>-0.533503</td>\n",
              "      <td>-0.400228</td>\n",
              "      <td>0.176084</td>\n",
              "      <td>1.111768</td>\n",
              "      <td>2.438428</td>\n",
              "      <td>2.734889</td>\n",
              "      <td>1.736054</td>\n",
              "      <td>0.036857</td>\n",
              "      <td>-1.265074</td>\n",
              "      <td>-0.208024</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.316646</td>\n",
              "      <td>0.243199</td>\n",
              "      <td>0.370471</td>\n",
              "      <td>1.063738</td>\n",
              "      <td>1.678187</td>\n",
              "      <td>1.759558</td>\n",
              "      <td>1.697717</td>\n",
              "      <td>1.612159</td>\n",
              "      <td>1.168188</td>\n",
              "      <td>0.499957</td>\n",
              "      <td>-0.022363</td>\n",
              "      <td>-0.235318</td>\n",
              "      <td>-0.118273</td>\n",
              "      <td>-0.071027</td>\n",
              "      <td>-0.322986</td>\n",
              "      <td>-0.433562</td>\n",
              "      <td>-0.318660</td>\n",
              "      <td>-0.295655</td>\n",
              "      <td>-0.417733</td>\n",
              "      <td>-0.682480</td>\n",
              "      <td>-0.881840</td>\n",
              "      <td>-0.843320</td>\n",
              "      <td>-0.883652</td>\n",
              "      <td>-1.030018</td>\n",
              "      <td>-1.055265</td>\n",
              "      <td>-1.168637</td>\n",
              "      <td>-1.363991</td>\n",
              "      <td>-1.337611</td>\n",
              "      <td>-1.261294</td>\n",
              "      <td>-1.409782</td>\n",
              "      <td>-1.634504</td>\n",
              "      <td>-1.703238</td>\n",
              "      <td>-1.677025</td>\n",
              "      <td>-1.782628</td>\n",
              "      <td>-1.996872</td>\n",
              "      <td>-2.056372</td>\n",
              "      <td>-1.937881</td>\n",
              "      <td>-1.879412</td>\n",
              "      <td>-1.915427</td>\n",
              "      <td>-1.845507</td>\n",
              "      <td>...</td>\n",
              "      <td>0.675666</td>\n",
              "      <td>0.699885</td>\n",
              "      <td>0.732561</td>\n",
              "      <td>0.771665</td>\n",
              "      <td>0.738129</td>\n",
              "      <td>0.723700</td>\n",
              "      <td>0.806876</td>\n",
              "      <td>0.878984</td>\n",
              "      <td>0.855791</td>\n",
              "      <td>0.806384</td>\n",
              "      <td>0.792501</td>\n",
              "      <td>0.803814</td>\n",
              "      <td>0.781938</td>\n",
              "      <td>0.700439</td>\n",
              "      <td>0.735960</td>\n",
              "      <td>0.864162</td>\n",
              "      <td>0.707670</td>\n",
              "      <td>0.458756</td>\n",
              "      <td>0.600146</td>\n",
              "      <td>0.825136</td>\n",
              "      <td>0.800034</td>\n",
              "      <td>0.762821</td>\n",
              "      <td>0.755443</td>\n",
              "      <td>0.653766</td>\n",
              "      <td>0.526441</td>\n",
              "      <td>0.477339</td>\n",
              "      <td>0.574946</td>\n",
              "      <td>0.698425</td>\n",
              "      <td>0.722414</td>\n",
              "      <td>0.771598</td>\n",
              "      <td>0.764229</td>\n",
              "      <td>0.610621</td>\n",
              "      <td>0.552900</td>\n",
              "      <td>0.566786</td>\n",
              "      <td>0.604002</td>\n",
              "      <td>0.777068</td>\n",
              "      <td>0.812345</td>\n",
              "      <td>0.748848</td>\n",
              "      <td>0.818042</td>\n",
              "      <td>0.539347</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1.168874</td>\n",
              "      <td>2.075901</td>\n",
              "      <td>1.760141</td>\n",
              "      <td>1.606446</td>\n",
              "      <td>1.949046</td>\n",
              "      <td>1.302842</td>\n",
              "      <td>0.459332</td>\n",
              "      <td>0.516412</td>\n",
              "      <td>0.852180</td>\n",
              "      <td>0.989227</td>\n",
              "      <td>0.821253</td>\n",
              "      <td>0.576448</td>\n",
              "      <td>0.743089</td>\n",
              "      <td>0.852970</td>\n",
              "      <td>0.307458</td>\n",
              "      <td>-0.130391</td>\n",
              "      <td>-0.062200</td>\n",
              "      <td>-0.100727</td>\n",
              "      <td>-0.232818</td>\n",
              "      <td>-0.234465</td>\n",
              "      <td>-0.214756</td>\n",
              "      <td>-0.230413</td>\n",
              "      <td>-0.227551</td>\n",
              "      <td>-0.231002</td>\n",
              "      <td>-0.463479</td>\n",
              "      <td>-0.724215</td>\n",
              "      <td>-0.787885</td>\n",
              "      <td>-0.986687</td>\n",
              "      <td>-1.224672</td>\n",
              "      <td>-1.288142</td>\n",
              "      <td>-1.364148</td>\n",
              "      <td>-1.428221</td>\n",
              "      <td>-1.501767</td>\n",
              "      <td>-1.648084</td>\n",
              "      <td>-1.705836</td>\n",
              "      <td>-1.686791</td>\n",
              "      <td>-1.705719</td>\n",
              "      <td>-1.777683</td>\n",
              "      <td>-1.869313</td>\n",
              "      <td>-1.858376</td>\n",
              "      <td>...</td>\n",
              "      <td>0.405055</td>\n",
              "      <td>0.464974</td>\n",
              "      <td>0.434163</td>\n",
              "      <td>0.486807</td>\n",
              "      <td>0.439388</td>\n",
              "      <td>0.369611</td>\n",
              "      <td>0.413149</td>\n",
              "      <td>0.397895</td>\n",
              "      <td>0.318764</td>\n",
              "      <td>0.263717</td>\n",
              "      <td>0.288863</td>\n",
              "      <td>0.358244</td>\n",
              "      <td>0.326737</td>\n",
              "      <td>0.229215</td>\n",
              "      <td>0.204418</td>\n",
              "      <td>0.244386</td>\n",
              "      <td>0.262632</td>\n",
              "      <td>0.243885</td>\n",
              "      <td>0.227502</td>\n",
              "      <td>0.245785</td>\n",
              "      <td>0.232959</td>\n",
              "      <td>0.164611</td>\n",
              "      <td>0.171538</td>\n",
              "      <td>0.166690</td>\n",
              "      <td>0.099141</td>\n",
              "      <td>0.146937</td>\n",
              "      <td>0.133414</td>\n",
              "      <td>0.125294</td>\n",
              "      <td>0.202713</td>\n",
              "      <td>0.186409</td>\n",
              "      <td>0.419006</td>\n",
              "      <td>0.723888</td>\n",
              "      <td>1.323947</td>\n",
              "      <td>2.136488</td>\n",
              "      <td>1.746597</td>\n",
              "      <td>1.470220</td>\n",
              "      <td>1.893512</td>\n",
              "      <td>1.256949</td>\n",
              "      <td>0.800407</td>\n",
              "      <td>0.731540</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.648658</td>\n",
              "      <td>0.752026</td>\n",
              "      <td>2.636231</td>\n",
              "      <td>3.455716</td>\n",
              "      <td>2.118157</td>\n",
              "      <td>0.520620</td>\n",
              "      <td>-0.188627</td>\n",
              "      <td>0.780818</td>\n",
              "      <td>0.933775</td>\n",
              "      <td>0.701402</td>\n",
              "      <td>1.006133</td>\n",
              "      <td>0.395784</td>\n",
              "      <td>-0.369703</td>\n",
              "      <td>-0.738202</td>\n",
              "      <td>-0.729084</td>\n",
              "      <td>-0.906940</td>\n",
              "      <td>-0.870962</td>\n",
              "      <td>-1.060217</td>\n",
              "      <td>-1.197958</td>\n",
              "      <td>-0.981602</td>\n",
              "      <td>-1.272497</td>\n",
              "      <td>-1.287380</td>\n",
              "      <td>-1.276698</td>\n",
              "      <td>-1.539702</td>\n",
              "      <td>-1.346610</td>\n",
              "      <td>-1.535217</td>\n",
              "      <td>-1.763418</td>\n",
              "      <td>-1.688821</td>\n",
              "      <td>-1.809368</td>\n",
              "      <td>-1.863891</td>\n",
              "      <td>-1.994453</td>\n",
              "      <td>-1.889810</td>\n",
              "      <td>-1.925713</td>\n",
              "      <td>-1.833629</td>\n",
              "      <td>-1.661830</td>\n",
              "      <td>-1.342510</td>\n",
              "      <td>-1.011317</td>\n",
              "      <td>-0.672717</td>\n",
              "      <td>-0.216157</td>\n",
              "      <td>0.052872</td>\n",
              "      <td>...</td>\n",
              "      <td>0.543004</td>\n",
              "      <td>0.453148</td>\n",
              "      <td>0.485785</td>\n",
              "      <td>0.440679</td>\n",
              "      <td>0.539153</td>\n",
              "      <td>0.369571</td>\n",
              "      <td>0.377316</td>\n",
              "      <td>0.470113</td>\n",
              "      <td>0.321448</td>\n",
              "      <td>0.325513</td>\n",
              "      <td>0.251259</td>\n",
              "      <td>0.270571</td>\n",
              "      <td>0.277161</td>\n",
              "      <td>0.155171</td>\n",
              "      <td>0.120954</td>\n",
              "      <td>0.326395</td>\n",
              "      <td>0.473952</td>\n",
              "      <td>0.594736</td>\n",
              "      <td>0.698199</td>\n",
              "      <td>0.826781</td>\n",
              "      <td>0.575166</td>\n",
              "      <td>0.401196</td>\n",
              "      <td>0.349966</td>\n",
              "      <td>0.148053</td>\n",
              "      <td>-0.033206</td>\n",
              "      <td>-0.114266</td>\n",
              "      <td>0.120345</td>\n",
              "      <td>-0.220102</td>\n",
              "      <td>-0.151226</td>\n",
              "      <td>-0.077445</td>\n",
              "      <td>-0.097869</td>\n",
              "      <td>-0.136787</td>\n",
              "      <td>-0.340237</td>\n",
              "      <td>-0.089441</td>\n",
              "      <td>-0.080297</td>\n",
              "      <td>-0.192584</td>\n",
              "      <td>-0.304704</td>\n",
              "      <td>-0.454556</td>\n",
              "      <td>0.314590</td>\n",
              "      <td>0.582190</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>95</th>\n",
              "      <td>0.581277</td>\n",
              "      <td>0.876188</td>\n",
              "      <td>1.042767</td>\n",
              "      <td>1.796120</td>\n",
              "      <td>2.541399</td>\n",
              "      <td>2.246653</td>\n",
              "      <td>1.500387</td>\n",
              "      <td>1.031521</td>\n",
              "      <td>0.382672</td>\n",
              "      <td>-0.197561</td>\n",
              "      <td>-0.169938</td>\n",
              "      <td>0.011444</td>\n",
              "      <td>-0.014047</td>\n",
              "      <td>-0.076611</td>\n",
              "      <td>-0.060981</td>\n",
              "      <td>0.091620</td>\n",
              "      <td>0.224723</td>\n",
              "      <td>-0.013561</td>\n",
              "      <td>-0.476781</td>\n",
              "      <td>-0.658850</td>\n",
              "      <td>-0.674972</td>\n",
              "      <td>-0.832898</td>\n",
              "      <td>-0.850541</td>\n",
              "      <td>-0.737077</td>\n",
              "      <td>-0.808637</td>\n",
              "      <td>-0.870819</td>\n",
              "      <td>-0.893871</td>\n",
              "      <td>-1.053572</td>\n",
              "      <td>-1.164487</td>\n",
              "      <td>-1.186889</td>\n",
              "      <td>-1.171606</td>\n",
              "      <td>-1.130290</td>\n",
              "      <td>-1.280472</td>\n",
              "      <td>-1.457825</td>\n",
              "      <td>-1.453798</td>\n",
              "      <td>-1.560752</td>\n",
              "      <td>-1.714101</td>\n",
              "      <td>-1.740958</td>\n",
              "      <td>-1.876972</td>\n",
              "      <td>-1.975246</td>\n",
              "      <td>...</td>\n",
              "      <td>0.623532</td>\n",
              "      <td>0.512156</td>\n",
              "      <td>0.688791</td>\n",
              "      <td>0.947720</td>\n",
              "      <td>0.827412</td>\n",
              "      <td>0.729604</td>\n",
              "      <td>0.711200</td>\n",
              "      <td>0.570643</td>\n",
              "      <td>0.598944</td>\n",
              "      <td>0.764949</td>\n",
              "      <td>0.719343</td>\n",
              "      <td>0.563323</td>\n",
              "      <td>0.517305</td>\n",
              "      <td>0.498195</td>\n",
              "      <td>0.504544</td>\n",
              "      <td>0.591249</td>\n",
              "      <td>0.562379</td>\n",
              "      <td>0.447038</td>\n",
              "      <td>0.452398</td>\n",
              "      <td>0.440700</td>\n",
              "      <td>0.449134</td>\n",
              "      <td>0.657936</td>\n",
              "      <td>0.771284</td>\n",
              "      <td>0.688320</td>\n",
              "      <td>0.760576</td>\n",
              "      <td>0.951067</td>\n",
              "      <td>0.951675</td>\n",
              "      <td>0.869962</td>\n",
              "      <td>0.960210</td>\n",
              "      <td>1.070311</td>\n",
              "      <td>1.002770</td>\n",
              "      <td>0.907869</td>\n",
              "      <td>0.916457</td>\n",
              "      <td>0.923975</td>\n",
              "      <td>0.767357</td>\n",
              "      <td>0.656223</td>\n",
              "      <td>0.762357</td>\n",
              "      <td>0.501373</td>\n",
              "      <td>-0.333336</td>\n",
              "      <td>-0.524546</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>96</th>\n",
              "      <td>2.689017</td>\n",
              "      <td>2.708703</td>\n",
              "      <td>2.008381</td>\n",
              "      <td>2.235800</td>\n",
              "      <td>1.516982</td>\n",
              "      <td>0.029916</td>\n",
              "      <td>-0.561346</td>\n",
              "      <td>-0.793702</td>\n",
              "      <td>-0.979371</td>\n",
              "      <td>-1.288162</td>\n",
              "      <td>-1.178131</td>\n",
              "      <td>-1.389989</td>\n",
              "      <td>-1.384316</td>\n",
              "      <td>-1.479919</td>\n",
              "      <td>-1.617465</td>\n",
              "      <td>-1.606800</td>\n",
              "      <td>-1.707307</td>\n",
              "      <td>-1.833382</td>\n",
              "      <td>-1.751167</td>\n",
              "      <td>-1.883754</td>\n",
              "      <td>-1.913390</td>\n",
              "      <td>-1.998631</td>\n",
              "      <td>-1.843806</td>\n",
              "      <td>-1.930836</td>\n",
              "      <td>-1.733986</td>\n",
              "      <td>-1.578720</td>\n",
              "      <td>-1.368667</td>\n",
              "      <td>-1.066986</td>\n",
              "      <td>-0.686882</td>\n",
              "      <td>-0.382549</td>\n",
              "      <td>0.005838</td>\n",
              "      <td>0.286448</td>\n",
              "      <td>0.564348</td>\n",
              "      <td>0.763883</td>\n",
              "      <td>0.924309</td>\n",
              "      <td>1.176783</td>\n",
              "      <td>1.019592</td>\n",
              "      <td>1.056547</td>\n",
              "      <td>0.974529</td>\n",
              "      <td>0.972086</td>\n",
              "      <td>...</td>\n",
              "      <td>0.257770</td>\n",
              "      <td>0.387559</td>\n",
              "      <td>0.250755</td>\n",
              "      <td>0.260461</td>\n",
              "      <td>0.117192</td>\n",
              "      <td>0.130050</td>\n",
              "      <td>0.306629</td>\n",
              "      <td>0.093103</td>\n",
              "      <td>0.093169</td>\n",
              "      <td>0.069559</td>\n",
              "      <td>0.217294</td>\n",
              "      <td>0.064019</td>\n",
              "      <td>0.191030</td>\n",
              "      <td>0.080115</td>\n",
              "      <td>0.123765</td>\n",
              "      <td>0.164131</td>\n",
              "      <td>0.245517</td>\n",
              "      <td>0.598562</td>\n",
              "      <td>0.785952</td>\n",
              "      <td>0.632892</td>\n",
              "      <td>0.601114</td>\n",
              "      <td>0.396554</td>\n",
              "      <td>0.184871</td>\n",
              "      <td>0.239439</td>\n",
              "      <td>0.048780</td>\n",
              "      <td>0.014701</td>\n",
              "      <td>0.056774</td>\n",
              "      <td>-0.159521</td>\n",
              "      <td>-0.022906</td>\n",
              "      <td>-0.137400</td>\n",
              "      <td>-0.136610</td>\n",
              "      <td>-0.072176</td>\n",
              "      <td>-0.082738</td>\n",
              "      <td>-0.138468</td>\n",
              "      <td>-0.120396</td>\n",
              "      <td>-0.089411</td>\n",
              "      <td>-0.243141</td>\n",
              "      <td>-0.119710</td>\n",
              "      <td>0.124042</td>\n",
              "      <td>0.273463</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>97</th>\n",
              "      <td>0.197677</td>\n",
              "      <td>0.455417</td>\n",
              "      <td>0.973110</td>\n",
              "      <td>1.935956</td>\n",
              "      <td>2.259463</td>\n",
              "      <td>1.741341</td>\n",
              "      <td>1.158296</td>\n",
              "      <td>0.418241</td>\n",
              "      <td>-0.071605</td>\n",
              "      <td>-0.241250</td>\n",
              "      <td>-0.243478</td>\n",
              "      <td>-0.263902</td>\n",
              "      <td>-0.621656</td>\n",
              "      <td>-0.418716</td>\n",
              "      <td>-0.188502</td>\n",
              "      <td>-0.623142</td>\n",
              "      <td>-0.935790</td>\n",
              "      <td>-1.117823</td>\n",
              "      <td>-1.245035</td>\n",
              "      <td>-1.327768</td>\n",
              "      <td>-1.354321</td>\n",
              "      <td>-1.261860</td>\n",
              "      <td>-1.280882</td>\n",
              "      <td>-1.367876</td>\n",
              "      <td>-1.509392</td>\n",
              "      <td>-1.748995</td>\n",
              "      <td>-1.691137</td>\n",
              "      <td>-1.575437</td>\n",
              "      <td>-1.834501</td>\n",
              "      <td>-1.847968</td>\n",
              "      <td>-1.774686</td>\n",
              "      <td>-2.059572</td>\n",
              "      <td>-2.179838</td>\n",
              "      <td>-2.021338</td>\n",
              "      <td>-1.799725</td>\n",
              "      <td>-1.589470</td>\n",
              "      <td>-1.450670</td>\n",
              "      <td>-1.292907</td>\n",
              "      <td>-1.036169</td>\n",
              "      <td>-0.729064</td>\n",
              "      <td>...</td>\n",
              "      <td>0.466186</td>\n",
              "      <td>0.484099</td>\n",
              "      <td>0.468112</td>\n",
              "      <td>0.434148</td>\n",
              "      <td>0.434440</td>\n",
              "      <td>0.468845</td>\n",
              "      <td>0.437875</td>\n",
              "      <td>0.464744</td>\n",
              "      <td>0.529423</td>\n",
              "      <td>0.505021</td>\n",
              "      <td>0.595805</td>\n",
              "      <td>0.606654</td>\n",
              "      <td>0.578332</td>\n",
              "      <td>0.657457</td>\n",
              "      <td>0.660664</td>\n",
              "      <td>0.804206</td>\n",
              "      <td>0.950174</td>\n",
              "      <td>0.866321</td>\n",
              "      <td>1.001497</td>\n",
              "      <td>1.266776</td>\n",
              "      <td>1.261269</td>\n",
              "      <td>1.262186</td>\n",
              "      <td>1.199633</td>\n",
              "      <td>0.943059</td>\n",
              "      <td>0.833524</td>\n",
              "      <td>0.691573</td>\n",
              "      <td>0.418308</td>\n",
              "      <td>0.426017</td>\n",
              "      <td>0.578058</td>\n",
              "      <td>0.580230</td>\n",
              "      <td>0.482452</td>\n",
              "      <td>0.325569</td>\n",
              "      <td>0.247991</td>\n",
              "      <td>0.184127</td>\n",
              "      <td>0.050358</td>\n",
              "      <td>0.241988</td>\n",
              "      <td>0.331451</td>\n",
              "      <td>-0.120006</td>\n",
              "      <td>0.042423</td>\n",
              "      <td>0.343293</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98</th>\n",
              "      <td>0.179500</td>\n",
              "      <td>1.038409</td>\n",
              "      <td>1.946421</td>\n",
              "      <td>2.705141</td>\n",
              "      <td>1.670706</td>\n",
              "      <td>-0.101167</td>\n",
              "      <td>-1.578876</td>\n",
              "      <td>-0.750906</td>\n",
              "      <td>0.175310</td>\n",
              "      <td>0.064901</td>\n",
              "      <td>0.443132</td>\n",
              "      <td>0.034639</td>\n",
              "      <td>0.009543</td>\n",
              "      <td>-0.539524</td>\n",
              "      <td>-0.770374</td>\n",
              "      <td>-0.864598</td>\n",
              "      <td>-1.216904</td>\n",
              "      <td>-1.122070</td>\n",
              "      <td>-1.297051</td>\n",
              "      <td>-1.056245</td>\n",
              "      <td>-1.268446</td>\n",
              "      <td>-1.492731</td>\n",
              "      <td>-1.499857</td>\n",
              "      <td>-1.642974</td>\n",
              "      <td>-1.511123</td>\n",
              "      <td>-1.840932</td>\n",
              "      <td>-1.592642</td>\n",
              "      <td>-1.765328</td>\n",
              "      <td>-2.078231</td>\n",
              "      <td>-1.801961</td>\n",
              "      <td>-2.029962</td>\n",
              "      <td>-2.019809</td>\n",
              "      <td>-1.985586</td>\n",
              "      <td>-1.724461</td>\n",
              "      <td>-1.656407</td>\n",
              "      <td>-1.542250</td>\n",
              "      <td>-1.110030</td>\n",
              "      <td>-0.718238</td>\n",
              "      <td>-0.300933</td>\n",
              "      <td>-0.232943</td>\n",
              "      <td>...</td>\n",
              "      <td>0.466719</td>\n",
              "      <td>0.617062</td>\n",
              "      <td>0.684901</td>\n",
              "      <td>0.461434</td>\n",
              "      <td>0.507010</td>\n",
              "      <td>0.542802</td>\n",
              "      <td>0.531181</td>\n",
              "      <td>0.730128</td>\n",
              "      <td>0.774075</td>\n",
              "      <td>0.551152</td>\n",
              "      <td>0.417327</td>\n",
              "      <td>0.581276</td>\n",
              "      <td>0.494547</td>\n",
              "      <td>0.492442</td>\n",
              "      <td>0.487352</td>\n",
              "      <td>0.461255</td>\n",
              "      <td>0.648460</td>\n",
              "      <td>0.998792</td>\n",
              "      <td>0.962698</td>\n",
              "      <td>1.042193</td>\n",
              "      <td>0.758785</td>\n",
              "      <td>0.613773</td>\n",
              "      <td>0.739696</td>\n",
              "      <td>0.419647</td>\n",
              "      <td>0.586495</td>\n",
              "      <td>0.344659</td>\n",
              "      <td>0.207503</td>\n",
              "      <td>0.526980</td>\n",
              "      <td>0.272584</td>\n",
              "      <td>0.348410</td>\n",
              "      <td>0.324323</td>\n",
              "      <td>0.330489</td>\n",
              "      <td>0.111953</td>\n",
              "      <td>0.448948</td>\n",
              "      <td>0.567132</td>\n",
              "      <td>0.136757</td>\n",
              "      <td>0.444768</td>\n",
              "      <td>0.151050</td>\n",
              "      <td>0.193378</td>\n",
              "      <td>0.451709</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99</th>\n",
              "      <td>0.073124</td>\n",
              "      <td>0.776054</td>\n",
              "      <td>2.181336</td>\n",
              "      <td>3.440325</td>\n",
              "      <td>2.168475</td>\n",
              "      <td>0.497315</td>\n",
              "      <td>-0.924284</td>\n",
              "      <td>-1.499227</td>\n",
              "      <td>-0.679328</td>\n",
              "      <td>-0.549892</td>\n",
              "      <td>-0.787257</td>\n",
              "      <td>-0.865248</td>\n",
              "      <td>-0.672813</td>\n",
              "      <td>-0.438372</td>\n",
              "      <td>-0.759575</td>\n",
              "      <td>-1.247079</td>\n",
              "      <td>-0.767535</td>\n",
              "      <td>-0.903549</td>\n",
              "      <td>-1.194720</td>\n",
              "      <td>-1.121947</td>\n",
              "      <td>-0.983558</td>\n",
              "      <td>-1.243915</td>\n",
              "      <td>-1.422845</td>\n",
              "      <td>-1.247005</td>\n",
              "      <td>-1.561146</td>\n",
              "      <td>-1.488745</td>\n",
              "      <td>-1.242094</td>\n",
              "      <td>-1.522450</td>\n",
              "      <td>-1.951195</td>\n",
              "      <td>-1.881457</td>\n",
              "      <td>-1.751462</td>\n",
              "      <td>-1.819755</td>\n",
              "      <td>-1.562987</td>\n",
              "      <td>-1.438170</td>\n",
              "      <td>-1.359779</td>\n",
              "      <td>-0.816034</td>\n",
              "      <td>-0.619600</td>\n",
              "      <td>-0.489861</td>\n",
              "      <td>-0.155670</td>\n",
              "      <td>0.112853</td>\n",
              "      <td>...</td>\n",
              "      <td>0.796519</td>\n",
              "      <td>0.839543</td>\n",
              "      <td>0.761567</td>\n",
              "      <td>0.629959</td>\n",
              "      <td>0.941793</td>\n",
              "      <td>0.514841</td>\n",
              "      <td>0.571688</td>\n",
              "      <td>0.840112</td>\n",
              "      <td>0.573670</td>\n",
              "      <td>0.717316</td>\n",
              "      <td>0.811504</td>\n",
              "      <td>0.637318</td>\n",
              "      <td>0.220638</td>\n",
              "      <td>0.685226</td>\n",
              "      <td>0.526078</td>\n",
              "      <td>0.441061</td>\n",
              "      <td>0.329281</td>\n",
              "      <td>0.605221</td>\n",
              "      <td>0.993767</td>\n",
              "      <td>0.833439</td>\n",
              "      <td>0.740540</td>\n",
              "      <td>0.618121</td>\n",
              "      <td>0.625788</td>\n",
              "      <td>0.468646</td>\n",
              "      <td>0.059755</td>\n",
              "      <td>0.096982</td>\n",
              "      <td>0.196858</td>\n",
              "      <td>-0.002127</td>\n",
              "      <td>-0.094384</td>\n",
              "      <td>-0.253487</td>\n",
              "      <td>-0.058935</td>\n",
              "      <td>-0.130638</td>\n",
              "      <td>-0.347235</td>\n",
              "      <td>-0.177933</td>\n",
              "      <td>-0.060332</td>\n",
              "      <td>-0.347634</td>\n",
              "      <td>-0.447443</td>\n",
              "      <td>-0.066689</td>\n",
              "      <td>-0.178448</td>\n",
              "      <td>-0.256052</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>100 rows × 96 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          0         1         2   ...        93        94        95\n",
              "0   0.502055  0.542163  0.722383  ...  0.705011  0.713815  0.433765\n",
              "1   0.147647  0.804668  0.367771  ...  0.036857 -1.265074 -0.208024\n",
              "2   0.316646  0.243199  0.370471  ...  0.748848  0.818042  0.539347\n",
              "3   1.168874  2.075901  1.760141  ...  1.256949  0.800407  0.731540\n",
              "4   0.648658  0.752026  2.636231  ... -0.454556  0.314590  0.582190\n",
              "..       ...       ...       ...  ...       ...       ...       ...\n",
              "95  0.581277  0.876188  1.042767  ...  0.501373 -0.333336 -0.524546\n",
              "96  2.689017  2.708703  2.008381  ... -0.119710  0.124042  0.273463\n",
              "97  0.197677  0.455417  0.973110  ... -0.120006  0.042423  0.343293\n",
              "98  0.179500  1.038409  1.946421  ...  0.151050  0.193378  0.451709\n",
              "99  0.073124  0.776054  2.181336  ... -0.066689 -0.178448 -0.256052\n",
              "\n",
              "[100 rows x 96 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 439
        },
        "id": "PBlOMeTwu8FU",
        "outputId": "646590d5-1844-46ec-9906-2c8d0d20f4f3"
      },
      "source": [
        "pd.DataFrame(X_test[:,:,0])"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "      <th>5</th>\n",
              "      <th>6</th>\n",
              "      <th>7</th>\n",
              "      <th>8</th>\n",
              "      <th>9</th>\n",
              "      <th>10</th>\n",
              "      <th>11</th>\n",
              "      <th>12</th>\n",
              "      <th>13</th>\n",
              "      <th>14</th>\n",
              "      <th>15</th>\n",
              "      <th>16</th>\n",
              "      <th>17</th>\n",
              "      <th>18</th>\n",
              "      <th>19</th>\n",
              "      <th>20</th>\n",
              "      <th>21</th>\n",
              "      <th>22</th>\n",
              "      <th>23</th>\n",
              "      <th>24</th>\n",
              "      <th>25</th>\n",
              "      <th>26</th>\n",
              "      <th>27</th>\n",
              "      <th>28</th>\n",
              "      <th>29</th>\n",
              "      <th>30</th>\n",
              "      <th>31</th>\n",
              "      <th>32</th>\n",
              "      <th>33</th>\n",
              "      <th>34</th>\n",
              "      <th>35</th>\n",
              "      <th>36</th>\n",
              "      <th>37</th>\n",
              "      <th>38</th>\n",
              "      <th>39</th>\n",
              "      <th>...</th>\n",
              "      <th>56</th>\n",
              "      <th>57</th>\n",
              "      <th>58</th>\n",
              "      <th>59</th>\n",
              "      <th>60</th>\n",
              "      <th>61</th>\n",
              "      <th>62</th>\n",
              "      <th>63</th>\n",
              "      <th>64</th>\n",
              "      <th>65</th>\n",
              "      <th>66</th>\n",
              "      <th>67</th>\n",
              "      <th>68</th>\n",
              "      <th>69</th>\n",
              "      <th>70</th>\n",
              "      <th>71</th>\n",
              "      <th>72</th>\n",
              "      <th>73</th>\n",
              "      <th>74</th>\n",
              "      <th>75</th>\n",
              "      <th>76</th>\n",
              "      <th>77</th>\n",
              "      <th>78</th>\n",
              "      <th>79</th>\n",
              "      <th>80</th>\n",
              "      <th>81</th>\n",
              "      <th>82</th>\n",
              "      <th>83</th>\n",
              "      <th>84</th>\n",
              "      <th>85</th>\n",
              "      <th>86</th>\n",
              "      <th>87</th>\n",
              "      <th>88</th>\n",
              "      <th>89</th>\n",
              "      <th>90</th>\n",
              "      <th>91</th>\n",
              "      <th>92</th>\n",
              "      <th>93</th>\n",
              "      <th>94</th>\n",
              "      <th>95</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.425189</td>\n",
              "      <td>1.418599</td>\n",
              "      <td>2.668791</td>\n",
              "      <td>3.298629</td>\n",
              "      <td>2.264554</td>\n",
              "      <td>0.165179</td>\n",
              "      <td>-0.959727</td>\n",
              "      <td>0.282668</td>\n",
              "      <td>0.842850</td>\n",
              "      <td>0.683458</td>\n",
              "      <td>1.082088</td>\n",
              "      <td>0.722577</td>\n",
              "      <td>0.109811</td>\n",
              "      <td>-0.696609</td>\n",
              "      <td>-0.662268</td>\n",
              "      <td>-0.839985</td>\n",
              "      <td>-0.935297</td>\n",
              "      <td>-0.895362</td>\n",
              "      <td>-0.924266</td>\n",
              "      <td>-1.088177</td>\n",
              "      <td>-1.113585</td>\n",
              "      <td>-1.130681</td>\n",
              "      <td>-1.201895</td>\n",
              "      <td>-1.539509</td>\n",
              "      <td>-1.535227</td>\n",
              "      <td>-1.468417</td>\n",
              "      <td>-2.078012</td>\n",
              "      <td>-1.856547</td>\n",
              "      <td>-1.982868</td>\n",
              "      <td>-2.041212</td>\n",
              "      <td>-1.793860</td>\n",
              "      <td>-1.986162</td>\n",
              "      <td>-1.946903</td>\n",
              "      <td>-1.706593</td>\n",
              "      <td>-1.325142</td>\n",
              "      <td>-1.147066</td>\n",
              "      <td>-0.863629</td>\n",
              "      <td>-0.356015</td>\n",
              "      <td>-0.204890</td>\n",
              "      <td>0.183010</td>\n",
              "      <td>...</td>\n",
              "      <td>0.463712</td>\n",
              "      <td>0.585878</td>\n",
              "      <td>0.622586</td>\n",
              "      <td>0.314033</td>\n",
              "      <td>0.421676</td>\n",
              "      <td>0.639392</td>\n",
              "      <td>0.470756</td>\n",
              "      <td>0.299982</td>\n",
              "      <td>0.247447</td>\n",
              "      <td>0.319957</td>\n",
              "      <td>0.299768</td>\n",
              "      <td>0.200925</td>\n",
              "      <td>0.152368</td>\n",
              "      <td>0.069307</td>\n",
              "      <td>0.290626</td>\n",
              "      <td>0.096217</td>\n",
              "      <td>0.379715</td>\n",
              "      <td>0.791631</td>\n",
              "      <td>0.606662</td>\n",
              "      <td>0.801544</td>\n",
              "      <td>0.696313</td>\n",
              "      <td>0.204389</td>\n",
              "      <td>0.205122</td>\n",
              "      <td>-0.045159</td>\n",
              "      <td>-0.184017</td>\n",
              "      <td>0.115775</td>\n",
              "      <td>-0.098132</td>\n",
              "      <td>-0.178360</td>\n",
              "      <td>-0.107120</td>\n",
              "      <td>-0.193491</td>\n",
              "      <td>-0.018196</td>\n",
              "      <td>-0.220493</td>\n",
              "      <td>-0.152557</td>\n",
              "      <td>-0.117011</td>\n",
              "      <td>-0.145160</td>\n",
              "      <td>-0.116668</td>\n",
              "      <td>-0.199262</td>\n",
              "      <td>-0.109837</td>\n",
              "      <td>-0.142488</td>\n",
              "      <td>0.098758</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.653929</td>\n",
              "      <td>2.177290</td>\n",
              "      <td>3.644783</td>\n",
              "      <td>2.279203</td>\n",
              "      <td>0.978367</td>\n",
              "      <td>-0.388296</td>\n",
              "      <td>-0.911911</td>\n",
              "      <td>-0.148330</td>\n",
              "      <td>0.305439</td>\n",
              "      <td>-0.230098</td>\n",
              "      <td>-0.451530</td>\n",
              "      <td>0.224113</td>\n",
              "      <td>-0.550054</td>\n",
              "      <td>-0.933977</td>\n",
              "      <td>-0.841629</td>\n",
              "      <td>-0.763727</td>\n",
              "      <td>-1.390977</td>\n",
              "      <td>-0.668909</td>\n",
              "      <td>-1.180268</td>\n",
              "      <td>-1.366029</td>\n",
              "      <td>-1.003644</td>\n",
              "      <td>-1.486201</td>\n",
              "      <td>-1.423197</td>\n",
              "      <td>-1.497927</td>\n",
              "      <td>-1.530533</td>\n",
              "      <td>-1.814270</td>\n",
              "      <td>-1.964060</td>\n",
              "      <td>-1.956103</td>\n",
              "      <td>-1.934264</td>\n",
              "      <td>-1.920925</td>\n",
              "      <td>-1.984635</td>\n",
              "      <td>-1.796928</td>\n",
              "      <td>-1.717051</td>\n",
              "      <td>-1.741488</td>\n",
              "      <td>-0.676497</td>\n",
              "      <td>-0.603892</td>\n",
              "      <td>-0.594680</td>\n",
              "      <td>0.071467</td>\n",
              "      <td>0.047549</td>\n",
              "      <td>0.617081</td>\n",
              "      <td>...</td>\n",
              "      <td>0.688933</td>\n",
              "      <td>0.406544</td>\n",
              "      <td>0.319476</td>\n",
              "      <td>0.725306</td>\n",
              "      <td>0.298402</td>\n",
              "      <td>0.504723</td>\n",
              "      <td>0.395827</td>\n",
              "      <td>0.399075</td>\n",
              "      <td>0.554689</td>\n",
              "      <td>0.183927</td>\n",
              "      <td>0.461040</td>\n",
              "      <td>0.106824</td>\n",
              "      <td>0.631238</td>\n",
              "      <td>0.671494</td>\n",
              "      <td>-0.106819</td>\n",
              "      <td>0.392942</td>\n",
              "      <td>0.611029</td>\n",
              "      <td>0.494914</td>\n",
              "      <td>1.028177</td>\n",
              "      <td>0.812667</td>\n",
              "      <td>0.500167</td>\n",
              "      <td>0.476564</td>\n",
              "      <td>0.432609</td>\n",
              "      <td>0.491859</td>\n",
              "      <td>0.015041</td>\n",
              "      <td>-0.098010</td>\n",
              "      <td>0.027623</td>\n",
              "      <td>-0.117590</td>\n",
              "      <td>0.106466</td>\n",
              "      <td>-0.064095</td>\n",
              "      <td>0.099883</td>\n",
              "      <td>0.141395</td>\n",
              "      <td>-0.239092</td>\n",
              "      <td>0.247424</td>\n",
              "      <td>-0.085150</td>\n",
              "      <td>0.007800</td>\n",
              "      <td>0.407868</td>\n",
              "      <td>-0.194915</td>\n",
              "      <td>0.171107</td>\n",
              "      <td>0.197027</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.404953</td>\n",
              "      <td>0.553996</td>\n",
              "      <td>0.724097</td>\n",
              "      <td>1.449039</td>\n",
              "      <td>2.012616</td>\n",
              "      <td>1.624477</td>\n",
              "      <td>1.204726</td>\n",
              "      <td>1.117511</td>\n",
              "      <td>0.562099</td>\n",
              "      <td>-0.011556</td>\n",
              "      <td>-0.151060</td>\n",
              "      <td>-0.165723</td>\n",
              "      <td>-0.149703</td>\n",
              "      <td>-0.303985</td>\n",
              "      <td>-0.439550</td>\n",
              "      <td>-0.251222</td>\n",
              "      <td>-0.226462</td>\n",
              "      <td>-0.491236</td>\n",
              "      <td>-0.718471</td>\n",
              "      <td>-0.819033</td>\n",
              "      <td>-0.742902</td>\n",
              "      <td>-0.794862</td>\n",
              "      <td>-1.005411</td>\n",
              "      <td>-0.854667</td>\n",
              "      <td>-0.664719</td>\n",
              "      <td>-0.966059</td>\n",
              "      <td>-1.250551</td>\n",
              "      <td>-1.148753</td>\n",
              "      <td>-1.081805</td>\n",
              "      <td>-1.229859</td>\n",
              "      <td>-1.329428</td>\n",
              "      <td>-1.343500</td>\n",
              "      <td>-1.388611</td>\n",
              "      <td>-1.469790</td>\n",
              "      <td>-1.529446</td>\n",
              "      <td>-1.452891</td>\n",
              "      <td>-1.438498</td>\n",
              "      <td>-1.637808</td>\n",
              "      <td>-1.637643</td>\n",
              "      <td>-1.516326</td>\n",
              "      <td>...</td>\n",
              "      <td>0.361909</td>\n",
              "      <td>0.523365</td>\n",
              "      <td>0.312846</td>\n",
              "      <td>0.290468</td>\n",
              "      <td>0.497942</td>\n",
              "      <td>0.504409</td>\n",
              "      <td>0.418277</td>\n",
              "      <td>0.422805</td>\n",
              "      <td>0.391918</td>\n",
              "      <td>0.386068</td>\n",
              "      <td>0.468577</td>\n",
              "      <td>0.411592</td>\n",
              "      <td>0.260108</td>\n",
              "      <td>0.341633</td>\n",
              "      <td>0.550400</td>\n",
              "      <td>0.604816</td>\n",
              "      <td>0.494183</td>\n",
              "      <td>0.386066</td>\n",
              "      <td>0.502098</td>\n",
              "      <td>0.591109</td>\n",
              "      <td>0.476200</td>\n",
              "      <td>0.660107</td>\n",
              "      <td>0.928723</td>\n",
              "      <td>0.801658</td>\n",
              "      <td>0.780144</td>\n",
              "      <td>0.934836</td>\n",
              "      <td>0.981024</td>\n",
              "      <td>1.092867</td>\n",
              "      <td>1.151628</td>\n",
              "      <td>1.203222</td>\n",
              "      <td>1.297938</td>\n",
              "      <td>1.243332</td>\n",
              "      <td>1.463616</td>\n",
              "      <td>1.694916</td>\n",
              "      <td>1.456115</td>\n",
              "      <td>1.570372</td>\n",
              "      <td>1.934584</td>\n",
              "      <td>1.497556</td>\n",
              "      <td>0.812570</td>\n",
              "      <td>0.390639</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1.088088</td>\n",
              "      <td>2.011949</td>\n",
              "      <td>2.301733</td>\n",
              "      <td>1.630199</td>\n",
              "      <td>0.636768</td>\n",
              "      <td>-0.140502</td>\n",
              "      <td>0.547954</td>\n",
              "      <td>1.075071</td>\n",
              "      <td>0.896861</td>\n",
              "      <td>1.137943</td>\n",
              "      <td>1.046725</td>\n",
              "      <td>0.390159</td>\n",
              "      <td>-0.463177</td>\n",
              "      <td>-0.516452</td>\n",
              "      <td>-0.748172</td>\n",
              "      <td>-0.870152</td>\n",
              "      <td>-0.839930</td>\n",
              "      <td>-0.972055</td>\n",
              "      <td>-1.087207</td>\n",
              "      <td>-1.066441</td>\n",
              "      <td>-1.278173</td>\n",
              "      <td>-1.391932</td>\n",
              "      <td>-1.527656</td>\n",
              "      <td>-1.722810</td>\n",
              "      <td>-1.801991</td>\n",
              "      <td>-2.109684</td>\n",
              "      <td>-2.231006</td>\n",
              "      <td>-2.357204</td>\n",
              "      <td>-2.432272</td>\n",
              "      <td>-2.444519</td>\n",
              "      <td>-2.442007</td>\n",
              "      <td>-2.176233</td>\n",
              "      <td>-1.942050</td>\n",
              "      <td>-1.663546</td>\n",
              "      <td>-1.124193</td>\n",
              "      <td>-0.796676</td>\n",
              "      <td>-0.546558</td>\n",
              "      <td>-0.140208</td>\n",
              "      <td>0.145777</td>\n",
              "      <td>0.287973</td>\n",
              "      <td>...</td>\n",
              "      <td>0.573265</td>\n",
              "      <td>0.629044</td>\n",
              "      <td>0.670985</td>\n",
              "      <td>0.613061</td>\n",
              "      <td>0.524032</td>\n",
              "      <td>0.602005</td>\n",
              "      <td>0.547952</td>\n",
              "      <td>0.499085</td>\n",
              "      <td>0.473772</td>\n",
              "      <td>0.444688</td>\n",
              "      <td>0.515292</td>\n",
              "      <td>0.383676</td>\n",
              "      <td>0.405070</td>\n",
              "      <td>0.392573</td>\n",
              "      <td>0.385344</td>\n",
              "      <td>0.359873</td>\n",
              "      <td>0.533237</td>\n",
              "      <td>0.644077</td>\n",
              "      <td>0.760671</td>\n",
              "      <td>0.660656</td>\n",
              "      <td>0.434464</td>\n",
              "      <td>0.399898</td>\n",
              "      <td>0.319325</td>\n",
              "      <td>0.233626</td>\n",
              "      <td>0.142697</td>\n",
              "      <td>0.174776</td>\n",
              "      <td>0.134232</td>\n",
              "      <td>0.055882</td>\n",
              "      <td>0.141421</td>\n",
              "      <td>0.173346</td>\n",
              "      <td>0.125239</td>\n",
              "      <td>0.071349</td>\n",
              "      <td>0.138197</td>\n",
              "      <td>0.116399</td>\n",
              "      <td>0.131198</td>\n",
              "      <td>0.119412</td>\n",
              "      <td>0.082968</td>\n",
              "      <td>0.151348</td>\n",
              "      <td>0.273915</td>\n",
              "      <td>0.349405</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.443621</td>\n",
              "      <td>0.947285</td>\n",
              "      <td>1.924084</td>\n",
              "      <td>2.159790</td>\n",
              "      <td>1.499447</td>\n",
              "      <td>0.964508</td>\n",
              "      <td>0.223256</td>\n",
              "      <td>-0.424946</td>\n",
              "      <td>0.121279</td>\n",
              "      <td>0.830197</td>\n",
              "      <td>0.727048</td>\n",
              "      <td>0.648830</td>\n",
              "      <td>0.787877</td>\n",
              "      <td>0.643346</td>\n",
              "      <td>0.467292</td>\n",
              "      <td>0.319482</td>\n",
              "      <td>-0.178127</td>\n",
              "      <td>-0.589164</td>\n",
              "      <td>-0.582264</td>\n",
              "      <td>-0.656677</td>\n",
              "      <td>-0.790563</td>\n",
              "      <td>-0.786609</td>\n",
              "      <td>-0.846742</td>\n",
              "      <td>-0.872577</td>\n",
              "      <td>-0.822020</td>\n",
              "      <td>-0.863381</td>\n",
              "      <td>-0.938879</td>\n",
              "      <td>-0.986204</td>\n",
              "      <td>-1.014380</td>\n",
              "      <td>-1.044480</td>\n",
              "      <td>-1.134152</td>\n",
              "      <td>-1.234278</td>\n",
              "      <td>-1.250723</td>\n",
              "      <td>-1.220270</td>\n",
              "      <td>-1.228189</td>\n",
              "      <td>-1.255540</td>\n",
              "      <td>-1.289033</td>\n",
              "      <td>-1.349891</td>\n",
              "      <td>-1.390175</td>\n",
              "      <td>-1.429303</td>\n",
              "      <td>...</td>\n",
              "      <td>0.099233</td>\n",
              "      <td>0.217777</td>\n",
              "      <td>0.238587</td>\n",
              "      <td>0.290855</td>\n",
              "      <td>0.377898</td>\n",
              "      <td>0.434383</td>\n",
              "      <td>0.472361</td>\n",
              "      <td>0.466453</td>\n",
              "      <td>0.427637</td>\n",
              "      <td>0.416249</td>\n",
              "      <td>0.398286</td>\n",
              "      <td>0.376364</td>\n",
              "      <td>0.343084</td>\n",
              "      <td>0.271855</td>\n",
              "      <td>0.253910</td>\n",
              "      <td>0.250182</td>\n",
              "      <td>0.202643</td>\n",
              "      <td>0.246176</td>\n",
              "      <td>0.300655</td>\n",
              "      <td>0.216936</td>\n",
              "      <td>0.162536</td>\n",
              "      <td>0.219100</td>\n",
              "      <td>0.233445</td>\n",
              "      <td>0.210880</td>\n",
              "      <td>0.260673</td>\n",
              "      <td>0.280664</td>\n",
              "      <td>0.280145</td>\n",
              "      <td>0.322233</td>\n",
              "      <td>0.315104</td>\n",
              "      <td>0.539736</td>\n",
              "      <td>0.900511</td>\n",
              "      <td>1.278688</td>\n",
              "      <td>2.317878</td>\n",
              "      <td>2.916254</td>\n",
              "      <td>2.211947</td>\n",
              "      <td>2.034753</td>\n",
              "      <td>2.071302</td>\n",
              "      <td>1.254178</td>\n",
              "      <td>1.037879</td>\n",
              "      <td>1.009615</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>95</th>\n",
              "      <td>0.843834</td>\n",
              "      <td>2.564764</td>\n",
              "      <td>3.343127</td>\n",
              "      <td>2.591811</td>\n",
              "      <td>1.989914</td>\n",
              "      <td>0.441743</td>\n",
              "      <td>0.356408</td>\n",
              "      <td>1.283447</td>\n",
              "      <td>0.820812</td>\n",
              "      <td>0.565674</td>\n",
              "      <td>0.319388</td>\n",
              "      <td>0.015538</td>\n",
              "      <td>-0.140170</td>\n",
              "      <td>-0.160333</td>\n",
              "      <td>-0.214422</td>\n",
              "      <td>-0.343228</td>\n",
              "      <td>-0.641436</td>\n",
              "      <td>-0.774836</td>\n",
              "      <td>-0.754361</td>\n",
              "      <td>-1.001433</td>\n",
              "      <td>-1.248467</td>\n",
              "      <td>-1.207493</td>\n",
              "      <td>-1.394460</td>\n",
              "      <td>-1.570863</td>\n",
              "      <td>-1.550313</td>\n",
              "      <td>-1.702578</td>\n",
              "      <td>-1.761711</td>\n",
              "      <td>-1.906302</td>\n",
              "      <td>-2.025120</td>\n",
              "      <td>-1.989133</td>\n",
              "      <td>-2.175049</td>\n",
              "      <td>-2.174753</td>\n",
              "      <td>-1.909535</td>\n",
              "      <td>-1.757096</td>\n",
              "      <td>-1.471098</td>\n",
              "      <td>-1.137170</td>\n",
              "      <td>-0.728904</td>\n",
              "      <td>-0.181200</td>\n",
              "      <td>0.143046</td>\n",
              "      <td>0.430733</td>\n",
              "      <td>...</td>\n",
              "      <td>0.327132</td>\n",
              "      <td>0.450974</td>\n",
              "      <td>0.459082</td>\n",
              "      <td>0.320024</td>\n",
              "      <td>0.348397</td>\n",
              "      <td>0.408187</td>\n",
              "      <td>0.314442</td>\n",
              "      <td>0.253704</td>\n",
              "      <td>0.407332</td>\n",
              "      <td>0.351954</td>\n",
              "      <td>0.205625</td>\n",
              "      <td>0.298598</td>\n",
              "      <td>0.247829</td>\n",
              "      <td>0.247081</td>\n",
              "      <td>0.230612</td>\n",
              "      <td>0.124415</td>\n",
              "      <td>0.412994</td>\n",
              "      <td>0.492565</td>\n",
              "      <td>0.486995</td>\n",
              "      <td>0.649423</td>\n",
              "      <td>0.381061</td>\n",
              "      <td>0.250059</td>\n",
              "      <td>0.161767</td>\n",
              "      <td>-0.078093</td>\n",
              "      <td>-0.099281</td>\n",
              "      <td>-0.167191</td>\n",
              "      <td>-0.226600</td>\n",
              "      <td>-0.359111</td>\n",
              "      <td>-0.226478</td>\n",
              "      <td>-0.154037</td>\n",
              "      <td>-0.243969</td>\n",
              "      <td>-0.242760</td>\n",
              "      <td>-0.356488</td>\n",
              "      <td>-0.245672</td>\n",
              "      <td>-0.184878</td>\n",
              "      <td>-0.277344</td>\n",
              "      <td>-0.105103</td>\n",
              "      <td>-0.169774</td>\n",
              "      <td>-0.023764</td>\n",
              "      <td>0.258732</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>96</th>\n",
              "      <td>1.398472</td>\n",
              "      <td>2.874771</td>\n",
              "      <td>3.453428</td>\n",
              "      <td>2.897919</td>\n",
              "      <td>1.260043</td>\n",
              "      <td>0.173332</td>\n",
              "      <td>1.289293</td>\n",
              "      <td>1.470054</td>\n",
              "      <td>1.028398</td>\n",
              "      <td>1.333152</td>\n",
              "      <td>0.877758</td>\n",
              "      <td>0.137694</td>\n",
              "      <td>-0.537904</td>\n",
              "      <td>-0.538739</td>\n",
              "      <td>-0.752478</td>\n",
              "      <td>-0.851250</td>\n",
              "      <td>-0.874064</td>\n",
              "      <td>-0.985425</td>\n",
              "      <td>-0.924813</td>\n",
              "      <td>-1.142311</td>\n",
              "      <td>-1.198901</td>\n",
              "      <td>-1.327447</td>\n",
              "      <td>-1.325352</td>\n",
              "      <td>-1.311842</td>\n",
              "      <td>-1.615285</td>\n",
              "      <td>-1.489392</td>\n",
              "      <td>-1.519243</td>\n",
              "      <td>-1.643568</td>\n",
              "      <td>-1.765136</td>\n",
              "      <td>-1.780863</td>\n",
              "      <td>-1.769368</td>\n",
              "      <td>-1.703646</td>\n",
              "      <td>-1.580838</td>\n",
              "      <td>-1.514497</td>\n",
              "      <td>-1.256232</td>\n",
              "      <td>-0.844510</td>\n",
              "      <td>-0.584716</td>\n",
              "      <td>-0.254974</td>\n",
              "      <td>0.094085</td>\n",
              "      <td>0.324336</td>\n",
              "      <td>...</td>\n",
              "      <td>0.596371</td>\n",
              "      <td>0.517303</td>\n",
              "      <td>0.424453</td>\n",
              "      <td>0.380032</td>\n",
              "      <td>0.466349</td>\n",
              "      <td>0.495478</td>\n",
              "      <td>0.349175</td>\n",
              "      <td>0.288753</td>\n",
              "      <td>0.391522</td>\n",
              "      <td>0.267060</td>\n",
              "      <td>0.130092</td>\n",
              "      <td>0.135472</td>\n",
              "      <td>0.146902</td>\n",
              "      <td>0.219927</td>\n",
              "      <td>0.058654</td>\n",
              "      <td>0.056372</td>\n",
              "      <td>0.086485</td>\n",
              "      <td>0.081060</td>\n",
              "      <td>0.368146</td>\n",
              "      <td>0.422254</td>\n",
              "      <td>0.328152</td>\n",
              "      <td>0.097205</td>\n",
              "      <td>0.093596</td>\n",
              "      <td>0.171224</td>\n",
              "      <td>-0.075631</td>\n",
              "      <td>-0.220097</td>\n",
              "      <td>-0.384314</td>\n",
              "      <td>-0.114521</td>\n",
              "      <td>-0.317208</td>\n",
              "      <td>-0.511616</td>\n",
              "      <td>-0.406242</td>\n",
              "      <td>-0.525755</td>\n",
              "      <td>-0.439422</td>\n",
              "      <td>-0.398495</td>\n",
              "      <td>-0.366739</td>\n",
              "      <td>-0.399198</td>\n",
              "      <td>-0.401109</td>\n",
              "      <td>-0.371077</td>\n",
              "      <td>-0.451180</td>\n",
              "      <td>-0.100215</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>97</th>\n",
              "      <td>1.113685</td>\n",
              "      <td>1.275951</td>\n",
              "      <td>1.171770</td>\n",
              "      <td>1.554551</td>\n",
              "      <td>2.280557</td>\n",
              "      <td>2.636614</td>\n",
              "      <td>2.514625</td>\n",
              "      <td>2.363170</td>\n",
              "      <td>2.290844</td>\n",
              "      <td>1.997703</td>\n",
              "      <td>1.446090</td>\n",
              "      <td>0.899585</td>\n",
              "      <td>0.485640</td>\n",
              "      <td>0.263133</td>\n",
              "      <td>0.294065</td>\n",
              "      <td>0.343763</td>\n",
              "      <td>0.129681</td>\n",
              "      <td>-0.137114</td>\n",
              "      <td>-0.132807</td>\n",
              "      <td>-0.000212</td>\n",
              "      <td>0.009882</td>\n",
              "      <td>-0.096064</td>\n",
              "      <td>-0.257354</td>\n",
              "      <td>-0.432367</td>\n",
              "      <td>-0.513272</td>\n",
              "      <td>-0.496645</td>\n",
              "      <td>-0.526507</td>\n",
              "      <td>-0.629881</td>\n",
              "      <td>-0.719089</td>\n",
              "      <td>-0.799052</td>\n",
              "      <td>-0.927877</td>\n",
              "      <td>-1.034161</td>\n",
              "      <td>-1.010181</td>\n",
              "      <td>-0.956941</td>\n",
              "      <td>-1.062470</td>\n",
              "      <td>-1.250001</td>\n",
              "      <td>-1.319562</td>\n",
              "      <td>-1.340979</td>\n",
              "      <td>-1.470328</td>\n",
              "      <td>-1.599300</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.186545</td>\n",
              "      <td>-0.053824</td>\n",
              "      <td>0.073488</td>\n",
              "      <td>0.150926</td>\n",
              "      <td>0.189145</td>\n",
              "      <td>0.251839</td>\n",
              "      <td>0.285380</td>\n",
              "      <td>0.248131</td>\n",
              "      <td>0.289882</td>\n",
              "      <td>0.440704</td>\n",
              "      <td>0.471028</td>\n",
              "      <td>0.386137</td>\n",
              "      <td>0.422303</td>\n",
              "      <td>0.495732</td>\n",
              "      <td>0.436391</td>\n",
              "      <td>0.414577</td>\n",
              "      <td>0.467959</td>\n",
              "      <td>0.341471</td>\n",
              "      <td>0.143517</td>\n",
              "      <td>0.205160</td>\n",
              "      <td>0.381566</td>\n",
              "      <td>0.397318</td>\n",
              "      <td>0.386255</td>\n",
              "      <td>0.488756</td>\n",
              "      <td>0.593788</td>\n",
              "      <td>0.641349</td>\n",
              "      <td>0.610417</td>\n",
              "      <td>0.434168</td>\n",
              "      <td>0.250755</td>\n",
              "      <td>0.302079</td>\n",
              "      <td>0.484357</td>\n",
              "      <td>0.474087</td>\n",
              "      <td>0.323893</td>\n",
              "      <td>0.387200</td>\n",
              "      <td>0.575901</td>\n",
              "      <td>0.426197</td>\n",
              "      <td>0.077527</td>\n",
              "      <td>0.148549</td>\n",
              "      <td>0.479638</td>\n",
              "      <td>0.358700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98</th>\n",
              "      <td>2.318208</td>\n",
              "      <td>2.139772</td>\n",
              "      <td>1.794243</td>\n",
              "      <td>2.344508</td>\n",
              "      <td>1.724400</td>\n",
              "      <td>0.431501</td>\n",
              "      <td>-0.464933</td>\n",
              "      <td>-0.542414</td>\n",
              "      <td>-0.830620</td>\n",
              "      <td>-1.030462</td>\n",
              "      <td>-1.008537</td>\n",
              "      <td>-1.102180</td>\n",
              "      <td>-1.218044</td>\n",
              "      <td>-1.401442</td>\n",
              "      <td>-1.413984</td>\n",
              "      <td>-1.597216</td>\n",
              "      <td>-1.595156</td>\n",
              "      <td>-1.662081</td>\n",
              "      <td>-1.752268</td>\n",
              "      <td>-1.773032</td>\n",
              "      <td>-1.893021</td>\n",
              "      <td>-1.996400</td>\n",
              "      <td>-2.015084</td>\n",
              "      <td>-1.954397</td>\n",
              "      <td>-1.991718</td>\n",
              "      <td>-1.774352</td>\n",
              "      <td>-1.685402</td>\n",
              "      <td>-1.590773</td>\n",
              "      <td>-1.245291</td>\n",
              "      <td>-0.836889</td>\n",
              "      <td>-0.500863</td>\n",
              "      <td>-0.176398</td>\n",
              "      <td>0.295740</td>\n",
              "      <td>0.437348</td>\n",
              "      <td>0.683109</td>\n",
              "      <td>0.944120</td>\n",
              "      <td>1.014931</td>\n",
              "      <td>1.178716</td>\n",
              "      <td>1.030768</td>\n",
              "      <td>1.134016</td>\n",
              "      <td>...</td>\n",
              "      <td>0.335282</td>\n",
              "      <td>0.461332</td>\n",
              "      <td>0.338808</td>\n",
              "      <td>0.273712</td>\n",
              "      <td>0.338584</td>\n",
              "      <td>0.402073</td>\n",
              "      <td>0.251747</td>\n",
              "      <td>0.339421</td>\n",
              "      <td>0.166366</td>\n",
              "      <td>0.123886</td>\n",
              "      <td>0.285120</td>\n",
              "      <td>0.061394</td>\n",
              "      <td>0.236491</td>\n",
              "      <td>0.478221</td>\n",
              "      <td>0.513242</td>\n",
              "      <td>0.711277</td>\n",
              "      <td>0.646041</td>\n",
              "      <td>0.516391</td>\n",
              "      <td>0.433842</td>\n",
              "      <td>0.140320</td>\n",
              "      <td>0.043501</td>\n",
              "      <td>0.125255</td>\n",
              "      <td>-0.042819</td>\n",
              "      <td>-0.261193</td>\n",
              "      <td>-0.038990</td>\n",
              "      <td>0.005607</td>\n",
              "      <td>-0.065313</td>\n",
              "      <td>-0.103264</td>\n",
              "      <td>-0.208586</td>\n",
              "      <td>-0.107174</td>\n",
              "      <td>-0.099292</td>\n",
              "      <td>-0.239948</td>\n",
              "      <td>-0.065850</td>\n",
              "      <td>-0.090294</td>\n",
              "      <td>-0.234900</td>\n",
              "      <td>-0.032727</td>\n",
              "      <td>-0.102668</td>\n",
              "      <td>-0.064539</td>\n",
              "      <td>0.285008</td>\n",
              "      <td>0.470914</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99</th>\n",
              "      <td>2.395329</td>\n",
              "      <td>3.283697</td>\n",
              "      <td>2.918598</td>\n",
              "      <td>2.279072</td>\n",
              "      <td>1.393210</td>\n",
              "      <td>0.592044</td>\n",
              "      <td>0.044003</td>\n",
              "      <td>0.110276</td>\n",
              "      <td>0.198213</td>\n",
              "      <td>-0.011564</td>\n",
              "      <td>0.023424</td>\n",
              "      <td>0.230739</td>\n",
              "      <td>0.265538</td>\n",
              "      <td>-0.012758</td>\n",
              "      <td>-0.545098</td>\n",
              "      <td>-0.679876</td>\n",
              "      <td>-0.688349</td>\n",
              "      <td>-0.885966</td>\n",
              "      <td>-0.765142</td>\n",
              "      <td>-0.742030</td>\n",
              "      <td>-0.894231</td>\n",
              "      <td>-0.840967</td>\n",
              "      <td>-0.944645</td>\n",
              "      <td>-1.027777</td>\n",
              "      <td>-0.876301</td>\n",
              "      <td>-0.943380</td>\n",
              "      <td>-1.144614</td>\n",
              "      <td>-1.212391</td>\n",
              "      <td>-1.365604</td>\n",
              "      <td>-1.473826</td>\n",
              "      <td>-1.437622</td>\n",
              "      <td>-1.615067</td>\n",
              "      <td>-1.757910</td>\n",
              "      <td>-1.803779</td>\n",
              "      <td>-1.886200</td>\n",
              "      <td>-1.715758</td>\n",
              "      <td>-1.662275</td>\n",
              "      <td>-1.755992</td>\n",
              "      <td>-1.545277</td>\n",
              "      <td>-1.349528</td>\n",
              "      <td>...</td>\n",
              "      <td>0.471901</td>\n",
              "      <td>0.297977</td>\n",
              "      <td>0.653269</td>\n",
              "      <td>0.171035</td>\n",
              "      <td>-0.067739</td>\n",
              "      <td>0.367762</td>\n",
              "      <td>0.415151</td>\n",
              "      <td>0.279549</td>\n",
              "      <td>0.319230</td>\n",
              "      <td>0.389731</td>\n",
              "      <td>0.368620</td>\n",
              "      <td>0.446627</td>\n",
              "      <td>0.624306</td>\n",
              "      <td>0.631960</td>\n",
              "      <td>0.768937</td>\n",
              "      <td>1.058238</td>\n",
              "      <td>1.076122</td>\n",
              "      <td>1.121251</td>\n",
              "      <td>1.344252</td>\n",
              "      <td>1.249993</td>\n",
              "      <td>1.046635</td>\n",
              "      <td>1.093166</td>\n",
              "      <td>0.915985</td>\n",
              "      <td>0.535240</td>\n",
              "      <td>0.533678</td>\n",
              "      <td>0.494146</td>\n",
              "      <td>0.023635</td>\n",
              "      <td>-0.074234</td>\n",
              "      <td>0.291274</td>\n",
              "      <td>0.249666</td>\n",
              "      <td>-0.049051</td>\n",
              "      <td>-0.099085</td>\n",
              "      <td>0.027991</td>\n",
              "      <td>0.141353</td>\n",
              "      <td>0.085650</td>\n",
              "      <td>0.005304</td>\n",
              "      <td>0.149875</td>\n",
              "      <td>0.103510</td>\n",
              "      <td>0.072660</td>\n",
              "      <td>0.215942</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>100 rows × 96 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          0         1         2   ...        93        94        95\n",
              "0   0.425189  1.418599  2.668791  ... -0.109837 -0.142488  0.098758\n",
              "1   0.653929  2.177290  3.644783  ... -0.194915  0.171107  0.197027\n",
              "2   0.404953  0.553996  0.724097  ...  1.497556  0.812570  0.390639\n",
              "3   1.088088  2.011949  2.301733  ...  0.151348  0.273915  0.349405\n",
              "4   0.443621  0.947285  1.924084  ...  1.254178  1.037879  1.009615\n",
              "..       ...       ...       ...  ...       ...       ...       ...\n",
              "95  0.843834  2.564764  3.343127  ... -0.169774 -0.023764  0.258732\n",
              "96  1.398472  2.874771  3.453428  ... -0.371077 -0.451180 -0.100215\n",
              "97  1.113685  1.275951  1.171770  ...  0.148549  0.479638  0.358700\n",
              "98  2.318208  2.139772  1.794243  ... -0.064539  0.285008  0.470914\n",
              "99  2.395329  3.283697  2.918598  ...  0.103510  0.072660  0.215942\n",
              "\n",
              "[100 rows x 96 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "u1KCv37YvZen",
        "outputId": "a9231288-4666-483a-ba78-2a987079eb0e"
      },
      "source": [
        "pd.Series(y_train).value_counts()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              " 1    69\n",
              "-1    31\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i_y3ekx0vf2_",
        "outputId": "a0787606-eb64-4365-afb5-5e8e2fe4b800"
      },
      "source": [
        "pd.Series(y_test).value_counts()"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              " 1    64\n",
              "-1    36\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4Xc9kAYKvmxm"
      },
      "source": [
        "# Scale time series\n",
        "X_train = TimeSeriesScalerMeanVariance().fit_transform(X_train)\n",
        "X_test = TimeSeriesScalerMeanVariance().fit_transform(X_test)"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QZz7hZJawQtO"
      },
      "source": [
        "size = X_train.shape[1]\n",
        "n_classes = len(set(y_train))"
      ],
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 356
        },
        "id": "N1eE_BtSwVRB",
        "outputId": "dd37f196-5aad-452c-eef5-4ac0f370fda6"
      },
      "source": [
        "plt.figure(figsize=(14,5))\n",
        "for i, cl in enumerate(set(y_train)):\n",
        "    plt.subplot(n_classes, 1, i + 1)\n",
        "    for ts in X_train[y_train == cl]:\n",
        "        plt.plot(ts.ravel(), color=\"orange\" if cl > 0 else \"blue\", alpha=.3)\n",
        "    plt.xlim(0, size - 1)\n",
        "plt.suptitle(\"Training time series\")\n",
        "plt.show()"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1008x360 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Fp3QfpsNwaZk"
      },
      "source": [
        "early_clf = NonMyopicEarlyClassifier(n_clusters=3, cost_time_parameter=1e-3,lamb=1e2,random_state=0)"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZBKmqPzpxH-3",
        "outputId": "8edbc1e7-d6c3-4075-c55d-ab7d36c9079c"
      },
      "source": [
        "early_clf.fit(X_train, y_train)"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "NonMyopicEarlyClassifier(base_classifier=None, cost_time_parameter=0.001,\n",
              "                         lamb=100.0, min_t=1, n_clusters=3, random_state=0)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tiv2Yf7RxP0d"
      },
      "source": [
        "preds, times = early_clf.predict_class_and_earliness(X_test)"
      ],
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 369
        },
        "id": "MDDS751ZxViS",
        "outputId": "d39b368a-5d5e-49d6-e369-6f8884db9c50"
      },
      "source": [
        "plt.figure(figsize=(14,5))\n",
        "plt.subplot(2, 1, 1)\n",
        "ts_idx = 0\n",
        "t = times[ts_idx]\n",
        "plot_partial(X_test[ts_idx], t, y_test[ts_idx], preds[ts_idx], color=\"orange\")\n",
        "\n",
        "\n",
        "plt.subplot(2, 1, 2)\n",
        "ts_idx = 9\n",
        "t = times[ts_idx]\n",
        "plot_partial(X_test[ts_idx], t, y_test[ts_idx], preds[ts_idx], color=\"blue\")\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1008x360 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 460
        },
        "id": "aD97h1LzxZz-",
        "outputId": "672148c9-3386-4367-f263-292b31a9d686"
      },
      "source": [
        "plt.figure(figsize=(14,7))\n",
        "hatches = [\"///\", \"\\\\\\\\\\\\\", \"*\"]\n",
        "for i, cost_t in enumerate([1e-4, 1e-3, 1e-2]):\n",
        "    early_clf.set_params(cost_time_parameter=cost_t)\n",
        "    early_clf.fit(X_train, y_train)\n",
        "    preds, times = early_clf.predict_class_and_earliness(X_test)\n",
        "    plt.hist(times,\n",
        "             alpha=.5, hatch=hatches[i],\n",
        "             density=True,\n",
        "             label=\"$\\\\alpha={}$\".format(cost_t),\n",
        "             bins=numpy.arange(0, size, 5))\n",
        "plt.legend(loc=\"upper right\")\n",
        "plt.xlim(0, size - 1)\n",
        "plt.xlabel(\"Prediction times\")\n",
        "plt.title(\"Impact of cost_time_parameter ($\\\\alpha$)\")\n",
        "plt.show()"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1008x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}