02. Linear Algebra.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Linear Algebra\n",
    "A lot of the Data Science methods we will see in this tutorial require some understanding of linear algebra, and in this notebook we will focus on how Julia handles matrices, the types that exist, and how to call basic linear algebra tasks."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# some packages we will use\n",
    "using LinearAlgebra\n",
    "using SparseArrays\n",
    "using Images\n",
    "using MAT"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![title](data/matrix_storage.png)\n",
    "### 🟢Getting started"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will get started with creating a random matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "A = rand(10,10); # created a random matrix of size 10-by-10\n",
    "Atranspose = A' # matrix transpose\n",
    "A = A*Atranspose; # matrix multiplication"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A[11] == A[1, 2] = true\n"
     ]
    }
   ],
   "source": [
    "@show A[11] == A[1,2];"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "norm(A * x - b) = 7.564717849388946e-14\n"
     ]
    }
   ],
   "source": [
    "b = rand(10); #created a random vector of size 10\n",
    "x = A\\b; #x is the solutions to the linear system Ax=b\n",
    "@show norm(A*x-b)\n",
    ";"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A few things that are noteworthy: \n",
    "- `A` is a `Matrix` type, and `b` is a `Vector` type.\n",
    "- The transpose function creates a matrix of type `Adjoint`.\n",
    "- `\\` is always the recommended way to solve a linear system. You almost never want to call the `inv` function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "typeof(A) = Array{Float64,2}\n",
      "typeof(b) = Array{Float64,1}\n",
      "typeof(rand(1, 10)) = Array{Float64,2}\n",
      "typeof(Atranspose) = Adjoint{Float64,Array{Float64,2}}\n"
     ]
    }
   ],
   "source": [
    "@show typeof(A)\n",
    "@show typeof(b)\n",
    "@show typeof(rand(1,10))\n",
    "@show typeof(Atranspose)\n",
    ";"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "true"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Matrix{Float64} == Array{Float64,2}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "true"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Vector{Float64} == Array{Float64,1}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10×10 Adjoint{Float64,Array{Float64,2}}:\n",
       " 0.691112   0.21003    0.441721   0.7048    …  0.410282  0.989499   0.701\n",
       " 0.0900292  0.265803   0.464324   0.241911     0.881453  0.587248   0.825358\n",
       " 0.0440667  0.0484793  0.398946   0.770297     0.680528  0.564222   0.0631149\n",
       " 0.826553   0.0665722  0.881877   0.938612     0.186977  0.0791085  0.920248\n",
       " 0.0848302  0.621067   0.950233   0.732608     0.136986  0.596373   0.647609\n",
       " 0.449024   0.698268   0.182474   0.176015  …  0.28787   0.620021   0.288716\n",
       " 0.597418   0.675114   0.438505   0.105283     0.550881  0.463301   0.460946\n",
       " 0.61592    0.936236   0.805682   0.102351     0.686347  0.58873    0.16106\n",
       " 0.268563   0.373541   0.79847    0.877306     0.538211  0.126789   0.384118\n",
       " 0.400286   0.430963   0.0255386  0.392989     0.637895  0.332142   0.850103"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Atranspose"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`adjoint` in julia is a lazy adjoint -- often, we can easily perform Linear Algebra operations such as `A*A'` without actually transposing the matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "search: \u001b[0m\u001b[1ma\u001b[22m\u001b[0m\u001b[1md\u001b[22m\u001b[0m\u001b[1mj\u001b[22m\u001b[0m\u001b[1mo\u001b[22m\u001b[0m\u001b[1mi\u001b[22m\u001b[0m\u001b[1mn\u001b[22m\u001b[0m\u001b[1mt\u001b[22m \u001b[0m\u001b[1ma\u001b[22m\u001b[0m\u001b[1md\u001b[22m\u001b[0m\u001b[1mj\u001b[22m\u001b[0m\u001b[1mo\u001b[22m\u001b[0m\u001b[1mi\u001b[22m\u001b[0m\u001b[1mn\u001b[22m\u001b[0m\u001b[1mt\u001b[22m! \u001b[0m\u001b[1mA\u001b[22m\u001b[0m\u001b[1md\u001b[22m\u001b[0m\u001b[1mj\u001b[22m\u001b[0m\u001b[1mo\u001b[22m\u001b[0m\u001b[1mi\u001b[22m\u001b[0m\u001b[1mn\u001b[22m\u001b[0m\u001b[1mt\u001b[22m\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/latex": [
       "\\begin{verbatim}\n",
       "adjoint(A)\n",
       "\\end{verbatim}\n",
       "Lazy adjoint (conjugate transposition) (also postfix \\texttt{'}). Note that \\texttt{adjoint} is applied recursively to elements.\n",
       "\n",
       "This operation is intended for linear algebra usage - for general data manipulation see \\href{@ref Base.permutedims}{\\texttt{permutedims}}.\n",
       "\n",
       "\\section{Examples}\n",
       "\\begin{verbatim}\n",
       "julia> A = [3+2im 9+2im; 8+7im  4+6im]\n",
       "2×2 Array{Complex{Int64},2}:\n",
       " 3+2im  9+2im\n",
       " 8+7im  4+6im\n",
       "\n",
       "julia> adjoint(A)\n",
       "2×2 Adjoint{Complex{Int64},Array{Complex{Int64},2}}:\n",
       " 3-2im  8-7im\n",
       " 9-2im  4-6im\n",
       "\\end{verbatim}\n"
      ],
      "text/markdown": [
       "```\n",
       "adjoint(A)\n",
       "```\n",
       "\n",
       "Lazy adjoint (conjugate transposition) (also postfix `'`). Note that `adjoint` is applied recursively to elements.\n",
       "\n",
       "This operation is intended for linear algebra usage - for general data manipulation see [`permutedims`](@ref Base.permutedims).\n",
       "\n",
       "# Examples\n",
       "\n",
       "```jldoctest\n",
       "julia> A = [3+2im 9+2im; 8+7im  4+6im]\n",
       "2×2 Array{Complex{Int64},2}:\n",
       " 3+2im  9+2im\n",
       " 8+7im  4+6im\n",
       "\n",
       "julia> adjoint(A)\n",
       "2×2 Adjoint{Complex{Int64},Array{Complex{Int64},2}}:\n",
       " 3-2im  8-7im\n",
       " 9-2im  4-6im\n",
       "```\n"
      ],
      "text/plain": [
       "\u001b[36m  adjoint(A)\u001b[39m\n",
       "\n",
       "  Lazy adjoint (conjugate transposition) (also postfix \u001b[36m'\u001b[39m). Note that \u001b[36madjoint\u001b[39m\n",
       "  is applied recursively to elements.\n",
       "\n",
       "  This operation is intended for linear algebra usage - for general data\n",
       "  manipulation see \u001b[36mpermutedims\u001b[39m.\n",
       "\n",
       "\u001b[1m  Examples\u001b[22m\n",
       "\u001b[1m  ≡≡≡≡≡≡≡≡≡≡\u001b[22m\n",
       "\n",
       "\u001b[36m  julia> A = [3+2im 9+2im; 8+7im  4+6im]\u001b[39m\n",
       "\u001b[36m  2×2 Array{Complex{Int64},2}:\u001b[39m\n",
       "\u001b[36m   3+2im  9+2im\u001b[39m\n",
       "\u001b[36m   8+7im  4+6im\u001b[39m\n",
       "\u001b[36m  \u001b[39m\n",
       "\u001b[36m  julia> adjoint(A)\u001b[39m\n",
       "\u001b[36m  2×2 Adjoint{Complex{Int64},Array{Complex{Int64},2}}:\u001b[39m\n",
       "\u001b[36m   3-2im  8-7im\u001b[39m\n",
       "\u001b[36m   9-2im  4-6im\u001b[39m"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "?adjoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10×10 Array{Float64,2}:\n",
       " 0.691112  0.0900292  0.0440667  0.826553   …  0.61592    0.268563  0.400286\n",
       " 0.21003   0.265803   0.0484793  0.0665722     0.936236   0.373541  0.430963\n",
       " 0.441721  0.464324   0.398946   0.881877      0.805682   0.79847   0.0255386\n",
       " 0.7048    0.241911   0.770297   0.938612      0.102351   0.877306  0.392989\n",
       " 0.74048   0.482684   0.17164    0.583372      0.0252161  0.43447   0.941488\n",
       " 0.850311  0.587149   0.968115   0.396725   …  0.683235   0.511771  0.541516\n",
       " 0.331551  0.301383   0.982261   0.538301      0.196966   0.568237  0.509913\n",
       " 0.410282  0.881453   0.680528   0.186977      0.686347   0.538211  0.637895\n",
       " 0.989499  0.587248   0.564222   0.0791085     0.58873    0.126789  0.332142\n",
       " 0.701     0.825358   0.0631149  0.920248      0.16106    0.384118  0.850103"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Atranspose.parent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "800"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sizeof(A)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That's because it's an array of Float64's, each is of size 8 bytes, and there are 10*10 numbers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10×10 Array{Float64,2}:\n",
       " 0.691112   0.21003    0.441721   0.7048    …  0.410282  0.989499   0.701\n",
       " 0.0900292  0.265803   0.464324   0.241911     0.881453  0.587248   0.825358\n",
       " 0.0440667  0.0484793  0.398946   0.770297     0.680528  0.564222   0.0631149\n",
       " 0.826553   0.0665722  0.881877   0.938612     0.186977  0.0791085  0.920248\n",
       " 0.0848302  0.621067   0.950233   0.732608     0.136986  0.596373   0.647609\n",
       " 0.449024   0.698268   0.182474   0.176015  …  0.28787   0.620021   0.288716\n",
       " 0.597418   0.675114   0.438505   0.105283     0.550881  0.463301   0.460946\n",
       " 0.61592    0.936236   0.805682   0.102351     0.686347  0.58873    0.16106\n",
       " 0.268563   0.373541   0.79847    0.877306     0.538211  0.126789   0.384118\n",
       " 0.400286   0.430963   0.0255386  0.392989     0.637895  0.332142   0.850103"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# To actually copy the matrix:\n",
    "B = copy(Atranspose)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "800"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sizeof(B)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `\\` operator allows you to solve a system of linear equations, and often uses a suitable matrix factorization to solve the problem. We will cover factorizations next."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "search: \u001b[0m\u001b[1m\\\u001b[22m\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/latex": [
       "\\begin{verbatim}\n",
       "\\(x, y)\n",
       "\\end{verbatim}\n",
       "Left division operator: multiplication of \\texttt{y} by the inverse of \\texttt{x} on the left. Gives floating-point results for integer arguments.\n",
       "\n",
       "\\section{Examples}\n",
       "\\begin{verbatim}\n",
       "julia> 3 \\ 6\n",
       "2.0\n",
       "\n",
       "julia> inv(3) * 6\n",
       "2.0\n",
       "\n",
       "julia> A = [4 3; 2 1]; x = [5, 6];\n",
       "\n",
       "julia> A \\ x\n",
       "2-element Array{Float64,1}:\n",
       "  6.5\n",
       " -7.0\n",
       "\n",
       "julia> inv(A) * x\n",
       "2-element Array{Float64,1}:\n",
       "  6.5\n",
       " -7.0\n",
       "\\end{verbatim}\n",
       "\\rule{\\textwidth}{1pt}\n",
       "\\begin{verbatim}\n",
       "\\(A, B)\n",
       "\\end{verbatim}\n",
       "Matrix division using a polyalgorithm. For input matrices \\texttt{A} and \\texttt{B}, the result \\texttt{X} is such that \\texttt{A*X == B} when \\texttt{A} is square. The solver that is used depends upon the structure of \\texttt{A}.  If \\texttt{A} is upper or lower triangular (or diagonal), no factorization of \\texttt{A} is required and the system is solved with either forward or backward substitution. For non-triangular square matrices, an LU factorization is used.\n",
       "\n",
       "For rectangular \\texttt{A} the result is the minimum-norm least squares solution computed by a pivoted QR factorization of \\texttt{A} and a rank estimate of \\texttt{A} based on the R factor.\n",
       "\n",
       "When \\texttt{A} is sparse, a similar polyalgorithm is used. For indefinite matrices, the \\texttt{LDLt} factorization does not use pivoting during the numerical factorization and therefore the procedure can fail even for invertible matrices.\n",
       "\n",
       "\\section{Examples}\n",
       "\\begin{verbatim}\n",
       "julia> A = [1 0; 1 -2]; B = [32; -4];\n",
       "\n",
       "julia> X = A \\ B\n",
       "2-element Array{Float64,1}:\n",
       " 32.0\n",
       " 18.0\n",
       "\n",
       "julia> A * X == B\n",
       "true\n",
       "\\end{verbatim}\n",
       "\\rule{\\textwidth}{1pt}\n",
       "\\begin{verbatim}\n",
       "(\\)(F::QRSparse, B::StridedVecOrMat)\n",
       "\\end{verbatim}\n",
       "Solve the least squares problem $\\min\\|Ax - b\\|^2$ or the linear system of equations $Ax=b$ when \\texttt{F} is the sparse QR factorization of $A$. A basic solution is returned when the problem is underdetermined.\n",
       "\n",
       "\\section{Examples}\n",
       "\\begin{verbatim}\n",
       "julia> A = sparse([1,2,4], [1,1,1], [1.0,1.0,1.0], 4, 2)\n",
       "4×2 SparseMatrixCSC{Float64,Int64} with 3 stored entries:\n",
       "  [1, 1]  =  1.0\n",
       "  [2, 1]  =  1.0\n",
       "  [4, 1]  =  1.0\n",
       "\n",
       "julia> qr(A)\\fill(1.0, 4)\n",
       "2-element Array{Float64,1}:\n",
       " 1.0\n",
       " 0.0\n",
       "\\end{verbatim}\n"
      ],
      "text/markdown": [
       "```\n",
       "\\(x, y)\n",
       "```\n",
       "\n",
       "Left division operator: multiplication of `y` by the inverse of `x` on the left. Gives floating-point results for integer arguments.\n",
       "\n",
       "# Examples\n",
       "\n",
       "```jldoctest\n",
       "julia> 3 \\ 6\n",
       "2.0\n",
       "\n",
       "julia> inv(3) * 6\n",
       "2.0\n",
       "\n",
       "julia> A = [4 3; 2 1]; x = [5, 6];\n",
       "\n",
       "julia> A \\ x\n",
       "2-element Array{Float64,1}:\n",
       "  6.5\n",
       " -7.0\n",
       "\n",
       "julia> inv(A) * x\n",
       "2-element Array{Float64,1}:\n",
       "  6.5\n",
       " -7.0\n",
       "```\n",
       "\n",
       "---\n",
       "\n",
       "```\n",
       "\\(A, B)\n",
       "```\n",
       "\n",
       "Matrix division using a polyalgorithm. For input matrices `A` and `B`, the result `X` is such that `A*X == B` when `A` is square. The solver that is used depends upon the structure of `A`.  If `A` is upper or lower triangular (or diagonal), no factorization of `A` is required and the system is solved with either forward or backward substitution. For non-triangular square matrices, an LU factorization is used.\n",
       "\n",
       "For rectangular `A` the result is the minimum-norm least squares solution computed by a pivoted QR factorization of `A` and a rank estimate of `A` based on the R factor.\n",
       "\n",
       "When `A` is sparse, a similar polyalgorithm is used. For indefinite matrices, the `LDLt` factorization does not use pivoting during the numerical factorization and therefore the procedure can fail even for invertible matrices.\n",
       "\n",
       "# Examples\n",
       "\n",
       "```jldoctest\n",
       "julia> A = [1 0; 1 -2]; B = [32; -4];\n",
       "\n",
       "julia> X = A \\ B\n",
       "2-element Array{Float64,1}:\n",
       " 32.0\n",
       " 18.0\n",
       "\n",
       "julia> A * X == B\n",
       "true\n",
       "```\n",
       "\n",
       "---\n",
       "\n",
       "```\n",
       "(\\)(F::QRSparse, B::StridedVecOrMat)\n",
       "```\n",
       "\n",
       "Solve the least squares problem $\\min\\|Ax - b\\|^2$ or the linear system of equations $Ax=b$ when `F` is the sparse QR factorization of $A$. A basic solution is returned when the problem is underdetermined.\n",
       "\n",
       "# Examples\n",
       "\n",
       "```jldoctest\n",
       "julia> A = sparse([1,2,4], [1,1,1], [1.0,1.0,1.0], 4, 2)\n",
       "4×2 SparseMatrixCSC{Float64,Int64} with 3 stored entries:\n",
       "  [1, 1]  =  1.0\n",
       "  [2, 1]  =  1.0\n",
       "  [4, 1]  =  1.0\n",
       "\n",
       "julia> qr(A)\\fill(1.0, 4)\n",
       "2-element Array{Float64,1}:\n",
       " 1.0\n",
       " 0.0\n",
       "```\n"
      ],
      "text/plain": [
       "\u001b[36m  \\(x, y)\u001b[39m\n",
       "\n",
       "  Left division operator: multiplication of \u001b[36my\u001b[39m by the inverse of \u001b[36mx\u001b[39m on the left.\n",
       "  Gives floating-point results for integer arguments.\n",
       "\n",
       "\u001b[1m  Examples\u001b[22m\n",
       "\u001b[1m  ≡≡≡≡≡≡≡≡≡≡\u001b[22m\n",
       "\n",
       "\u001b[36m  julia> 3 \\ 6\u001b[39m\n",
       "\u001b[36m  2.0\u001b[39m\n",
       "\u001b[36m  \u001b[39m\n",
       "\u001b[36m  julia> inv(3) * 6\u001b[39m\n",
       "\u001b[36m  2.0\u001b[39m\n",
       "\u001b[36m  \u001b[39m\n",
       "\u001b[36m  julia> A = [4 3; 2 1]; x = [5, 6];\u001b[39m\n",
       "\u001b[36m  \u001b[39m\n",
       "\u001b[36m  julia> A \\ x\u001b[39m\n",
       "\u001b[36m  2-element Array{Float64,1}:\u001b[39m\n",
       "\u001b[36m    6.5\u001b[39m\n",
       "\u001b[36m   -7.0\u001b[39m\n",
       "\u001b[36m  \u001b[39m\n",
       "\u001b[36m  julia> inv(A) * x\u001b[39m\n",
       "\u001b[36m  2-element Array{Float64,1}:\u001b[39m\n",
       "\u001b[36m    6.5\u001b[39m\n",
       "\u001b[36m   -7.0\u001b[39m\n",
       "\n",
       "  ────────────────────────────────────────────────────────────────────────────\n",
       "\n",
       "\u001b[36m  \\(A, B)\u001b[39m\n",
       "\n",
       "  Matrix division using a polyalgorithm. For input matrices \u001b[36mA\u001b[39m and \u001b[36mB\u001b[39m, the\n",
       "  result \u001b[36mX\u001b[39m is such that \u001b[36mA*X == B\u001b[39m when \u001b[36mA\u001b[39m is square. The solver that is used\n",
       "  depends upon the structure of \u001b[36mA\u001b[39m. If \u001b[36mA\u001b[39m is upper or lower triangular (or\n",
       "  diagonal), no factorization of \u001b[36mA\u001b[39m is required and the system is solved with\n",
       "  either forward or backward substitution. For non-triangular square matrices,\n",
       "  an LU factorization is used.\n",
       "\n",
       "  For rectangular \u001b[36mA\u001b[39m the result is the minimum-norm least squares solution\n",
       "  computed by a pivoted QR factorization of \u001b[36mA\u001b[39m and a rank estimate of \u001b[36mA\u001b[39m based\n",
       "  on the R factor.\n",
       "\n",
       "  When \u001b[36mA\u001b[39m is sparse, a similar polyalgorithm is used. For indefinite matrices,\n",
       "  the \u001b[36mLDLt\u001b[39m factorization does not use pivoting during the numerical\n",
       "  factorization and therefore the procedure can fail even for invertible\n",
       "  matrices.\n",
       "\n",
       "\u001b[1m  Examples\u001b[22m\n",
       "\u001b[1m  ≡≡≡≡≡≡≡≡≡≡\u001b[22m\n",
       "\n",
       "\u001b[36m  julia> A = [1 0; 1 -2]; B = [32; -4];\u001b[39m\n",
       "\u001b[36m  \u001b[39m\n",
       "\u001b[36m  julia> X = A \\ B\u001b[39m\n",
       "\u001b[36m  2-element Array{Float64,1}:\u001b[39m\n",
       "\u001b[36m   32.0\u001b[39m\n",
       "\u001b[36m   18.0\u001b[39m\n",
       "\u001b[36m  \u001b[39m\n",
       "\u001b[36m  julia> A * X == B\u001b[39m\n",
       "\u001b[36m  true\u001b[39m\n",
       "\n",
       "  ────────────────────────────────────────────────────────────────────────────\n",
       "\n",
       "\u001b[36m  (\\)(F::QRSparse, B::StridedVecOrMat)\u001b[39m\n",
       "\n",
       "  Solve the least squares problem \u001b[35m\\min\\|Ax - b\\|^2\u001b[39m or the linear system of\n",
       "  equations \u001b[35mAx=b\u001b[39m when \u001b[36mF\u001b[39m is the sparse QR factorization of \u001b[35mA\u001b[39m. A basic solution\n",
       "  is returned when the problem is underdetermined.\n",
       "\n",
       "\u001b[1m  Examples\u001b[22m\n",
       "\u001b[1m  ≡≡≡≡≡≡≡≡≡≡\u001b[22m\n",
       "\n",
       "\u001b[36m  julia> A = sparse([1,2,4], [1,1,1], [1.0,1.0,1.0], 4, 2)\u001b[39m\n",
       "\u001b[36m  4×2 SparseMatrixCSC{Float64,Int64} with 3 stored entries:\u001b[39m\n",
       "\u001b[36m    [1, 1]  =  1.0\u001b[39m\n",
       "\u001b[36m    [2, 1]  =  1.0\u001b[39m\n",
       "\u001b[36m    [4, 1]  =  1.0\u001b[39m\n",
       "\u001b[36m  \u001b[39m\n",
       "\u001b[36m  julia> qr(A)\\fill(1.0, 4)\u001b[39m\n",
       "\u001b[36m  2-element Array{Float64,1}:\u001b[39m\n",
       "\u001b[36m   1.0\u001b[39m\n",
       "\u001b[36m   0.0\u001b[39m"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "?\\"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 🟢Factorizations\n",
    "A common tool used in Linear Algebra is matrix factorizations. These factorizations are often used to solve linear systems like `Ax=b`, and as we will see later in this tutorial... `Ax=b` comes up in a lot of Data Science problems"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### LU factorization\n",
    "L\\*U = P\\*A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LU{Float64,Array{Float64,2}}\n",
       "L factor:\n",
       "10×10 Array{Float64,2}:\n",
       " 1.0        0.0        0.0         0.0        …   0.0         0.0       0.0\n",
       " 0.734489   1.0        0.0         0.0            0.0         0.0       0.0\n",
       " 0.891206   0.273122   1.0         0.0            0.0         0.0       0.0\n",
       " 0.93472   -0.426216   0.0863139   1.0            0.0         0.0       0.0\n",
       " 0.709229   0.0253908  0.294931   -0.627551       0.0         0.0       0.0\n",
       " 0.732411   0.439323   0.275034   -0.276955   …   0.0         0.0       0.0\n",
       " 0.787588  -0.359985   0.969219   -0.660565       0.0         0.0       0.0\n",
       " 0.781098   0.434649   0.204047   -0.24038        1.0         0.0       0.0\n",
       " 0.925357  -0.222352   0.472861    0.0990528     -0.0857109   1.0       0.0\n",
       " 0.933844   0.0504976  0.249237   -0.195707       0.495511   -0.646119  1.0\n",
       "U factor:\n",
       "10×10 Array{Float64,2}:\n",
       " 2.51232  2.38488   2.50875   …   2.61944     2.72894     3.38915\n",
       " 0.0      0.900762  0.528783      0.21848     0.249957   -0.48272\n",
       " 0.0      0.0       1.3832        0.0560333  -0.0286673  -0.0306137\n",
       " 0.0      0.0       0.0          -0.520114   -0.479421   -1.04621\n",
       " 0.0      0.0       0.0           0.152724   -0.0420374  -0.846289\n",
       " 0.0      0.0       0.0       …   0.80822     0.297884    0.15208\n",
       " 0.0      0.0       0.0           0.21491     0.130037    0.22231\n",
       " 0.0      0.0       0.0          -0.44997     0.466345   -0.154157\n",
       " 0.0      0.0       0.0           0.0         0.0461302   0.25068\n",
       " 0.0      0.0       0.0           0.0         0.0         0.141666"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "luA = lu(A)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.6011864169946884e-15"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norm(luA.L*luA.U - luA.P*A)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### QR factorization\n",
    "Q\\*R = A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearAlgebra.QRCompactWY{Float64,Array{Float64,2}}\n",
       "Q factor:\n",
       "10×10 LinearAlgebra.QRCompactWYQ{Float64,Array{Float64,2}}:\n",
       " -0.348214   0.404842    0.37341     …  -0.073193   -0.118657   -0.298112\n",
       " -0.273621  -0.69743     0.122027       -0.302283   -0.157606    0.156396\n",
       " -0.332004  -0.130938   -0.620407        0.364257    0.255984    0.0669681\n",
       " -0.293402   0.341769   -0.522361       -0.357759    0.0800827  -0.189332\n",
       " -0.372533   0.0862223   0.405539        0.152702    0.550826   -0.102608\n",
       " -0.347888   0.0421016   0.137093    …  -0.0618928   0.29985     0.630506\n",
       " -0.264211   0.0418351   0.00774896      0.275706   -0.403252   -0.113255\n",
       " -0.272847  -0.271069   -0.0370552      -0.493239    0.0583428  -0.427171\n",
       " -0.290985  -0.263316    0.0497993       0.533686   -0.194881   -0.277506\n",
       " -0.344726   0.248943   -0.0271919      -0.106417   -0.540209    0.407382\n",
       "R factor:\n",
       "10×10 Array{Float64,2}:\n",
       " -6.74388  -6.67583  -8.42844   …  -7.79502    -7.88581    -8.59364\n",
       "  0.0      -1.18403  -0.352703     -0.716362   -0.751243    0.212051\n",
       "  0.0       0.0      -1.48126      -0.269478   -0.161659   -0.464637\n",
       "  0.0       0.0       0.0          -0.846309   -0.707696   -0.434428\n",
       "  0.0       0.0       0.0           0.0977946   0.116563   -0.876846\n",
       "  0.0       0.0       0.0       …  -0.796552   -0.517442   -0.153218\n",
       "  0.0       0.0       0.0          -0.108224    0.427234    0.105563\n",
       "  0.0       0.0       0.0          -0.230447    0.235769   -0.10437\n",
       "  0.0       0.0       0.0           0.0        -0.0338572  -0.141508\n",
       "  0.0       0.0       0.0           0.0         0.0         0.0893212"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qrA = qr(A)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9.173963038173126e-15"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norm(qrA.Q*qrA.R - A)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Cholesky factorization, note that A needs to be symmetric positive definite\n",
    "L\\*L' = A "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "true"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "isposdef(A)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Cholesky{Float64,Array{Float64,2}}\n",
       "U factor:\n",
       "10×10 UpperTriangular{Float64,Array{Float64,2}}:\n",
       " 1.53242  1.20415  1.46108   …   1.20075    1.28057    1.51707\n",
       "  ⋅       1.09656  0.558169      0.635215   0.649612   0.163956\n",
       "  ⋅        ⋅       1.14766       0.29732    0.207419   0.479145\n",
       "  ⋅        ⋅        ⋅            0.395687   0.437275   0.46458\n",
       "  ⋅        ⋅        ⋅            0.198987   0.11517    0.711988\n",
       "  ⋅        ⋅        ⋅        …   0.805636   0.58622   -0.00426951\n",
       "  ⋅        ⋅        ⋅           -0.107468  -0.423384  -0.253955\n",
       "  ⋅        ⋅        ⋅            0.475051  -0.428835   0.206008\n",
       "  ⋅        ⋅        ⋅             ⋅         0.245258   0.167068\n",
       "  ⋅        ⋅        ⋅             ⋅          ⋅         0.468248"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cholA = cholesky(A)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9.930136612989092e-16"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norm(cholA.L*cholA.U - A)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10×10 LowerTriangular{Float64,Array{Float64,2}}:\n",
       " 1.53242    ⋅             ⋅         …    ⋅         ⋅         ⋅ \n",
       " 1.20415   1.09656        ⋅              ⋅         ⋅         ⋅ \n",
       " 1.46108   0.558169      1.14766         ⋅         ⋅         ⋅ \n",
       " 1.29121  -0.000704639   1.08043         ⋅         ⋅         ⋅ \n",
       " 1.63944   0.374565     -0.0833716       ⋅         ⋅         ⋅ \n",
       " 1.53099   0.391266      0.225625   …    ⋅         ⋅         ⋅ \n",
       " 1.16274   0.286509      0.297886        ⋅         ⋅         ⋅ \n",
       " 1.20075   0.635215      0.29732        0.475051   ⋅         ⋅ \n",
       " 1.28057   0.649612      0.207419      -0.428835  0.245258   ⋅ \n",
       " 1.51707   0.163956      0.479145       0.206008  0.167068  0.468248"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cholA.L"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10×10 UpperTriangular{Float64,Array{Float64,2}}:\n",
       " 1.53242  1.20415  1.46108   …   1.20075    1.28057    1.51707\n",
       "  ⋅       1.09656  0.558169      0.635215   0.649612   0.163956\n",
       "  ⋅        ⋅       1.14766       0.29732    0.207419   0.479145\n",
       "  ⋅        ⋅        ⋅            0.395687   0.437275   0.46458\n",
       "  ⋅        ⋅        ⋅            0.198987   0.11517    0.711988\n",
       "  ⋅        ⋅        ⋅        …   0.805636   0.58622   -0.00426951\n",
       "  ⋅        ⋅        ⋅           -0.107468  -0.423384  -0.253955\n",
       "  ⋅        ⋅        ⋅            0.475051  -0.428835   0.206008\n",
       "  ⋅        ⋅        ⋅             ⋅         0.245258   0.167068\n",
       "  ⋅        ⋅        ⋅             ⋅          ⋅         0.468248"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cholA.U"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Cholesky{Float64,Array{Float64,2}}\n",
       "U factor:\n",
       "10×10 UpperTriangular{Float64,Array{Float64,2}}:\n",
       " 1.53242  1.20415  1.46108   …   1.20075    1.28057    1.51707\n",
       "  ⋅       1.09656  0.558169      0.635215   0.649612   0.163956\n",
       "  ⋅        ⋅       1.14766       0.29732    0.207419   0.479145\n",
       "  ⋅        ⋅        ⋅            0.395687   0.437275   0.46458\n",
       "  ⋅        ⋅        ⋅            0.198987   0.11517    0.711988\n",
       "  ⋅        ⋅        ⋅        …   0.805636   0.58622   -0.00426951\n",
       "  ⋅        ⋅        ⋅           -0.107468  -0.423384  -0.253955\n",
       "  ⋅        ⋅        ⋅            0.475051  -0.428835   0.206008\n",
       "  ⋅        ⋅        ⋅             ⋅         0.245258   0.167068\n",
       "  ⋅        ⋅        ⋅             ⋅          ⋅         0.468248"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "factorize(A)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "search: \u001b[0m\u001b[1mf\u001b[22m\u001b[0m\u001b[1ma\u001b[22m\u001b[0m\u001b[1mc\u001b[22m\u001b[0m\u001b[1mt\u001b[22m\u001b[0m\u001b[1mo\u001b[22m\u001b[0m\u001b[1mr\u001b[22m\u001b[0m\u001b[1mi\u001b[22m\u001b[0m\u001b[1mz\u001b[22m\u001b[0m\u001b[1me\u001b[22m \u001b[0m\u001b[1mF\u001b[22m\u001b[0m\u001b[1ma\u001b[22m\u001b[0m\u001b[1mc\u001b[22m\u001b[0m\u001b[1mt\u001b[22m\u001b[0m\u001b[1mo\u001b[22m\u001b[0m\u001b[1mr\u001b[22m\u001b[0m\u001b[1mi\u001b[22m\u001b[0m\u001b[1mz\u001b[22mation \u001b[0m\u001b[1mf\u001b[22m\u001b[0m\u001b[1ma\u001b[22m\u001b[0m\u001b[1mc\u001b[22m\u001b[0m\u001b[1mt\u001b[22m\u001b[0m\u001b[1mo\u001b[22m\u001b[0m\u001b[1mr\u001b[22m\u001b[0m\u001b[1mi\u001b[22mal\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/latex": [
       "\\begin{verbatim}\n",
       "factorize(A)\n",
       "\\end{verbatim}\n",
       "Compute a convenient factorization of \\texttt{A}, based upon the type of the input matrix. \\texttt{factorize} checks \\texttt{A} to see if it is symmetric/triangular/etc. if \\texttt{A} is passed as a generic matrix. \\texttt{factorize} checks every element of \\texttt{A} to verify/rule out each property. It will short-circuit as soon as it can rule out symmetry/triangular structure. The return value can be reused for efficient solving of multiple systems. For example: \\texttt{A=factorize(A); x=A{\\textbackslash}b; y=A{\\textbackslash}C}.\n",
       "\n",
       "\\begin{tabular}\n",
       "{l | l}\n",
       "Properties of \\texttt{A} & type of factorization \\\\\n",
       "\\hline\n",
       "Positive-definite & Cholesky (see \\href{@ref}{\\texttt{cholesky}}) \\\\\n",
       "Dense Symmetric/Hermitian & Bunch-Kaufman (see \\href{@ref}{\\texttt{bunchkaufman}}) \\\\\n",
       "Sparse Symmetric/Hermitian & LDLt (see \\href{@ref}{\\texttt{ldlt}}) \\\\\n",
       "Triangular & Triangular \\\\\n",
       "Diagonal & Diagonal \\\\\n",
       "Bidiagonal & Bidiagonal \\\\\n",
       "Tridiagonal & LU (see \\href{@ref}{\\texttt{lu}}) \\\\\n",
       "Symmetric real tridiagonal & LDLt (see \\href{@ref}{\\texttt{ldlt}}) \\\\\n",
       "General square & LU (see \\href{@ref}{\\texttt{lu}}) \\\\\n",
       "General non-square & QR (see \\href{@ref}{\\texttt{qr}}) \\\\\n",
       "\\end{tabular}\n",
       "If \\texttt{factorize} is called on a Hermitian positive-definite matrix, for instance, then \\texttt{factorize} will return a Cholesky factorization.\n",
       "\n",
       "\\section{Examples}\n",
       "\\begin{verbatim}\n",
       "julia> A = Array(Bidiagonal(fill(1.0, (5, 5)), :U))\n",
       "5×5 Array{Float64,2}:\n",
       " 1.0  1.0  0.0  0.0  0.0\n",
       " 0.0  1.0  1.0  0.0  0.0\n",
       " 0.0  0.0  1.0  1.0  0.0\n",
       " 0.0  0.0  0.0  1.0  1.0\n",
       " 0.0  0.0  0.0  0.0  1.0\n",
       "\n",
       "julia> factorize(A) # factorize will check to see that A is already factorized\n",
       "5×5 Bidiagonal{Float64,Array{Float64,1}}:\n",
       " 1.0  1.0   ⋅    ⋅    ⋅\n",
       "  ⋅   1.0  1.0   ⋅    ⋅\n",
       "  ⋅    ⋅   1.0  1.0   ⋅\n",
       "  ⋅    ⋅    ⋅   1.0  1.0\n",
       "  ⋅    ⋅    ⋅    ⋅   1.0\n",
       "\\end{verbatim}\n",
       "This returns a \\texttt{5×5 Bidiagonal\\{Float64\\}}, which can now be passed to other linear algebra functions (e.g. eigensolvers) which will use specialized methods for \\texttt{Bidiagonal} types.\n",
       "\n"
      ],
      "text/markdown": [
       "```\n",
       "factorize(A)\n",
       "```\n",
       "\n",
       "Compute a convenient factorization of `A`, based upon the type of the input matrix. `factorize` checks `A` to see if it is symmetric/triangular/etc. if `A` is passed as a generic matrix. `factorize` checks every element of `A` to verify/rule out each property. It will short-circuit as soon as it can rule out symmetry/triangular structure. The return value can be reused for efficient solving of multiple systems. For example: `A=factorize(A); x=A\\b; y=A\\C`.\n",
       "\n",
       "| Properties of `A`          | type of factorization                      |\n",
       "|:-------------------------- |:------------------------------------------ |\n",
       "| Positive-definite          | Cholesky (see [`cholesky`](@ref))          |\n",
       "| Dense Symmetric/Hermitian  | Bunch-Kaufman (see [`bunchkaufman`](@ref)) |\n",
       "| Sparse Symmetric/Hermitian | LDLt (see [`ldlt`](@ref))                  |\n",
       "| Triangular                 | Triangular                                 |\n",
       "| Diagonal                   | Diagonal                                   |\n",
       "| Bidiagonal                 | Bidiagonal                                 |\n",
       "| Tridiagonal                | LU (see [`lu`](@ref))                      |\n",
       "| Symmetric real tridiagonal | LDLt (see [`ldlt`](@ref))                  |\n",
       "| General square             | LU (see [`lu`](@ref))                      |\n",
       "| General non-square         | QR (see [`qr`](@ref))                      |\n",
       "\n",
       "If `factorize` is called on a Hermitian positive-definite matrix, for instance, then `factorize` will return a Cholesky factorization.\n",
       "\n",
       "# Examples\n",
       "\n",
       "```jldoctest\n",
       "julia> A = Array(Bidiagonal(fill(1.0, (5, 5)), :U))\n",
       "5×5 Array{Float64,2}:\n",
       " 1.0  1.0  0.0  0.0  0.0\n",
       " 0.0  1.0  1.0  0.0  0.0\n",
       " 0.0  0.0  1.0  1.0  0.0\n",
       " 0.0  0.0  0.0  1.0  1.0\n",
       " 0.0  0.0  0.0  0.0  1.0\n",
       "\n",
       "julia> factorize(A) # factorize will check to see that A is already factorized\n",
       "5×5 Bidiagonal{Float64,Array{Float64,1}}:\n",
       " 1.0  1.0   ⋅    ⋅    ⋅\n",
       "  ⋅   1.0  1.0   ⋅    ⋅\n",
       "  ⋅    ⋅   1.0  1.0   ⋅\n",
       "  ⋅    ⋅    ⋅   1.0  1.0\n",
       "  ⋅    ⋅    ⋅    ⋅   1.0\n",
       "```\n",
       "\n",
       "This returns a `5×5 Bidiagonal{Float64}`, which can now be passed to other linear algebra functions (e.g. eigensolvers) which will use specialized methods for `Bidiagonal` types.\n"
      ],
      "text/plain": [
       "\u001b[36m  factorize(A)\u001b[39m\n",
       "\n",
       "  Compute a convenient factorization of \u001b[36mA\u001b[39m, based upon the type of the input\n",
       "  matrix. \u001b[36mfactorize\u001b[39m checks \u001b[36mA\u001b[39m to see if it is symmetric/triangular/etc. if \u001b[36mA\u001b[39m is\n",
       "  passed as a generic matrix. \u001b[36mfactorize\u001b[39m checks every element of \u001b[36mA\u001b[39m to\n",
       "  verify/rule out each property. It will short-circuit as soon as it can rule\n",
       "  out symmetry/triangular structure. The return value can be reused for\n",
       "  efficient solving of multiple systems. For example: \u001b[36mA=factorize(A); x=A\\b;\n",
       "  y=A\\C\u001b[39m.\n",
       "\n",
       "  Properties of \u001b[36mA\u001b[39m            type of factorization           \n",
       "  –––––––––––––––––––––––––– ––––––––––––––––––––––––––––––––\n",
       "  Positive-definite          Cholesky (see \u001b[36mcholesky\u001b[39m)         \n",
       "  Dense Symmetric/Hermitian  Bunch-Kaufman (see \u001b[36mbunchkaufman\u001b[39m)\n",
       "  Sparse Symmetric/Hermitian LDLt (see \u001b[36mldlt\u001b[39m)                 \n",
       "  Triangular                 Triangular                      \n",
       "  Diagonal                   Diagonal                        \n",
       "  Bidiagonal                 Bidiagonal                      \n",
       "  Tridiagonal                LU (see \u001b[36mlu\u001b[39m)                     \n",
       "  Symmetric real tridiagonal LDLt (see \u001b[36mldlt\u001b[39m)                 \n",
       "  General square             LU (see \u001b[36mlu\u001b[39m)                     \n",
       "  General non-square         QR (see \u001b[36mqr\u001b[39m)                     \n",
       "\n",
       "  If \u001b[36mfactorize\u001b[39m is called on a Hermitian positive-definite matrix, for\n",
       "  instance, then \u001b[36mfactorize\u001b[39m will return a Cholesky factorization.\n",
       "\n",
       "\u001b[1m  Examples\u001b[22m\n",
       "\u001b[1m  ≡≡≡≡≡≡≡≡≡≡\u001b[22m\n",
       "\n",
       "\u001b[36m  julia> A = Array(Bidiagonal(fill(1.0, (5, 5)), :U))\u001b[39m\n",
       "\u001b[36m  5×5 Array{Float64,2}:\u001b[39m\n",
       "\u001b[36m   1.0  1.0  0.0  0.0  0.0\u001b[39m\n",
       "\u001b[36m   0.0  1.0  1.0  0.0  0.0\u001b[39m\n",
       "\u001b[36m   0.0  0.0  1.0  1.0  0.0\u001b[39m\n",
       "\u001b[36m   0.0  0.0  0.0  1.0  1.0\u001b[39m\n",
       "\u001b[36m   0.0  0.0  0.0  0.0  1.0\u001b[39m\n",
       "\u001b[36m  \u001b[39m\n",
       "\u001b[36m  julia> factorize(A) # factorize will check to see that A is already factorized\u001b[39m\n",
       "\u001b[36m  5×5 Bidiagonal{Float64,Array{Float64,1}}:\u001b[39m\n",
       "\u001b[36m   1.0  1.0   ⋅    ⋅    ⋅\u001b[39m\n",
       "\u001b[36m    ⋅   1.0  1.0   ⋅    ⋅\u001b[39m\n",
       "\u001b[36m    ⋅    ⋅   1.0  1.0   ⋅\u001b[39m\n",
       "\u001b[36m    ⋅    ⋅    ⋅   1.0  1.0\u001b[39m\n",
       "\u001b[36m    ⋅    ⋅    ⋅    ⋅   1.0\u001b[39m\n",
       "\n",
       "  This returns a \u001b[36m5×5 Bidiagonal{Float64}\u001b[39m, which can now be passed to other\n",
       "  linear algebra functions (e.g. eigensolvers) which will use specialized\n",
       "  methods for \u001b[36mBidiagonal\u001b[39m types."
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "?factorize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "search: \u001b[0m\u001b[1md\u001b[22m\u001b[0m\u001b[1mi\u001b[22m\u001b[0m\u001b[1ma\u001b[22m\u001b[0m\u001b[1mg\u001b[22m\u001b[0m\u001b[1mm\u001b[22m sp\u001b[0m\u001b[1md\u001b[22m\u001b[0m\u001b[1mi\u001b[22m\u001b[0m\u001b[1ma\u001b[22m\u001b[0m\u001b[1mg\u001b[22m\u001b[0m\u001b[1mm\u001b[22m \u001b[0m\u001b[1md\u001b[22m\u001b[0m\u001b[1mi\u001b[22m\u001b[0m\u001b[1ma\u001b[22m\u001b[0m\u001b[1mg\u001b[22m \u001b[0m\u001b[1md\u001b[22m\u001b[0m\u001b[1mi\u001b[22m\u001b[0m\u001b[1ma\u001b[22m\u001b[0m\u001b[1mg\u001b[22mind \u001b[0m\u001b[1mD\u001b[22m\u001b[0m\u001b[1mi\u001b[22m\u001b[0m\u001b[1ma\u001b[22m\u001b[0m\u001b[1mg\u001b[22monal is\u001b[0m\u001b[1md\u001b[22m\u001b[0m\u001b[1mi\u001b[22m\u001b[0m\u001b[1ma\u001b[22m\u001b[0m\u001b[1mg\u001b[22m Bi\u001b[0m\u001b[1md\u001b[22m\u001b[0m\u001b[1mi\u001b[22m\u001b[0m\u001b[1ma\u001b[22m\u001b[0m\u001b[1mg\u001b[22monal Tri\u001b[0m\u001b[1md\u001b[22m\u001b[0m\u001b[1mi\u001b[22m\u001b[0m\u001b[1ma\u001b[22m\u001b[0m\u001b[1mg\u001b[22monal\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/latex": [
       "\\begin{verbatim}\n",
       "diagm(kv::Pair{<:Integer,<:AbstractVector}...)\n",
       "diagm(m::Integer, n::Integer, kv::Pair{<:Integer,<:AbstractVector}...)\n",
       "\\end{verbatim}\n",
       "Construct a matrix from \\texttt{Pair}s of diagonals and vectors. Vector \\texttt{kv.second} will be placed on the \\texttt{kv.first} diagonal. By default the matrix is square and its size is inferred from \\texttt{kv}, but a non-square size \\texttt{m}×\\texttt{n} (padded with zeros as needed) can be specified by passing \\texttt{m,n} as the first arguments.\n",
       "\n",
       "\\texttt{diagm} constructs a full matrix; if you want storage-efficient versions with fast arithmetic, see \\href{@ref}{\\texttt{Diagonal}}, \\href{@ref}{\\texttt{Bidiagonal}} \\href{@ref}{\\texttt{Tridiagonal}} and \\href{@ref}{\\texttt{SymTridiagonal}}.\n",
       "\n",
       "\\section{Examples}\n",
       "\\begin{verbatim}\n",
       "julia> diagm(1 => [1,2,3])\n",
       "4×4 Array{Int64,2}:\n",
       " 0  1  0  0\n",
       " 0  0  2  0\n",
       " 0  0  0  3\n",
       " 0  0  0  0\n",
       "\n",
       "julia> diagm(1 => [1,2,3], -1 => [4,5])\n",
       "4×4 Array{Int64,2}:\n",
       " 0  1  0  0\n",
       " 4  0  2  0\n",
       " 0  5  0  3\n",
       " 0  0  0  0\n",
       "\\end{verbatim}\n",
       "\\rule{\\textwidth}{1pt}\n",
       "\\begin{verbatim}\n",
       "diagm(v::AbstractVector)\n",
       "diagm(m::Integer, n::Integer, v::AbstractVector)\n",
       "\\end{verbatim}\n",
       "Construct a matrix with elements of the vector as diagonal elements. By default (if \\texttt{size=nothing}), the matrix is square and its size is given by \\texttt{length(v)}, but a non-square size \\texttt{m}×\\texttt{n} can be specified by passing \\texttt{m,n} as the first arguments.\n",
       "\n",
       "\\section{Examples}\n",
       "\\begin{verbatim}\n",
       "julia> diagm([1,2,3])\n",
       "3×3 Array{Int64,2}:\n",
       " 1  0  0\n",
       " 0  2  0\n",
       " 0  0  3\n",
       "\\end{verbatim}\n"
      ],
      "text/markdown": [
       "```\n",
       "diagm(kv::Pair{<:Integer,<:AbstractVector}...)\n",
       "diagm(m::Integer, n::Integer, kv::Pair{<:Integer,<:AbstractVector}...)\n",
       "```\n",
       "\n",
       "Construct a matrix from `Pair`s of diagonals and vectors. Vector `kv.second` will be placed on the `kv.first` diagonal. By default the matrix is square and its size is inferred from `kv`, but a non-square size `m`×`n` (padded with zeros as needed) can be specified by passing `m,n` as the first arguments.\n",
       "\n",
       "`diagm` constructs a full matrix; if you want storage-efficient versions with fast arithmetic, see [`Diagonal`](@ref), [`Bidiagonal`](@ref) [`Tridiagonal`](@ref) and [`SymTridiagonal`](@ref).\n",
       "\n",
       "# Examples\n",
       "\n",
       "```jldoctest\n",
       "julia> diagm(1 => [1,2,3])\n",
       "4×4 Array{Int64,2}:\n",
       " 0  1  0  0\n",
       " 0  0  2  0\n",
       " 0  0  0  3\n",
       " 0  0  0  0\n",
       "\n",
       "julia> diagm(1 => [1,2,3], -1 => [4,5])\n",
       "4×4 Array{Int64,2}:\n",
       " 0  1  0  0\n",
       " 4  0  2  0\n",
       " 0  5  0  3\n",
       " 0  0  0  0\n",
       "```\n",
       "\n",
       "---\n",
       "\n",
       "```\n",
       "diagm(v::AbstractVector)\n",
       "diagm(m::Integer, n::Integer, v::AbstractVector)\n",
       "```\n",
       "\n",
       "Construct a matrix with elements of the vector as diagonal elements. By default (if `size=nothing`), the matrix is square and its size is given by `length(v)`, but a non-square size `m`×`n` can be specified by passing `m,n` as the first arguments.\n",
       "\n",
       "# Examples\n",
       "\n",
       "```jldoctest\n",
       "julia> diagm([1,2,3])\n",
       "3×3 Array{Int64,2}:\n",
       " 1  0  0\n",
       " 0  2  0\n",
       " 0  0  3\n",
       "```\n"
      ],
      "text/plain": [
       "\u001b[36m  diagm(kv::Pair{<:Integer,<:AbstractVector}...)\u001b[39m\n",
       "\u001b[36m  diagm(m::Integer, n::Integer, kv::Pair{<:Integer,<:AbstractVector}...)\u001b[39m\n",
       "\n",
       "  Construct a matrix from \u001b[36mPair\u001b[39ms of diagonals and vectors. Vector \u001b[36mkv.second\u001b[39m\n",
       "  will be placed on the \u001b[36mkv.first\u001b[39m diagonal. By default the matrix is square and\n",
       "  its size is inferred from \u001b[36mkv\u001b[39m, but a non-square size \u001b[36mm\u001b[39m×\u001b[36mn\u001b[39m (padded with zeros\n",
       "  as needed) can be specified by passing \u001b[36mm,n\u001b[39m as the first arguments.\n",
       "\n",
       "  \u001b[36mdiagm\u001b[39m constructs a full matrix; if you want storage-efficient versions with\n",
       "  fast arithmetic, see \u001b[36mDiagonal\u001b[39m, \u001b[36mBidiagonal\u001b[39m \u001b[36mTridiagonal\u001b[39m and \u001b[36mSymTridiagonal\u001b[39m.\n",
       "\n",
       "\u001b[1m  Examples\u001b[22m\n",
       "\u001b[1m  ≡≡≡≡≡≡≡≡≡≡\u001b[22m\n",
       "\n",
       "\u001b[36m  julia> diagm(1 => [1,2,3])\u001b[39m\n",
       "\u001b[36m  4×4 Array{Int64,2}:\u001b[39m\n",
       "\u001b[36m   0  1  0  0\u001b[39m\n",
       "\u001b[36m   0  0  2  0\u001b[39m\n",
       "\u001b[36m   0  0  0  3\u001b[39m\n",
       "\u001b[36m   0  0  0  0\u001b[39m\n",
       "\u001b[36m  \u001b[39m\n",
       "\u001b[36m  julia> diagm(1 => [1,2,3], -1 => [4,5])\u001b[39m\n",
       "\u001b[36m  4×4 Array{Int64,2}:\u001b[39m\n",
       "\u001b[36m   0  1  0  0\u001b[39m\n",
       "\u001b[36m   4  0  2  0\u001b[39m\n",
       "\u001b[36m   0  5  0  3\u001b[39m\n",
       "\u001b[36m   0  0  0  0\u001b[39m\n",
       "\n",
       "  ────────────────────────────────────────────────────────────────────────────\n",
       "\n",
       "\u001b[36m  diagm(v::AbstractVector)\u001b[39m\n",
       "\u001b[36m  diagm(m::Integer, n::Integer, v::AbstractVector)\u001b[39m\n",
       "\n",
       "  Construct a matrix with elements of the vector as diagonal elements. By\n",
       "  default (if \u001b[36msize=nothing\u001b[39m), the matrix is square and its size is given by\n",
       "  \u001b[36mlength(v)\u001b[39m, but a non-square size \u001b[36mm\u001b[39m×\u001b[36mn\u001b[39m can be specified by passing \u001b[36mm,n\u001b[39m as the\n",
       "  first arguments.\n",
       "\n",
       "\u001b[1m  Examples\u001b[22m\n",
       "\u001b[1m  ≡≡≡≡≡≡≡≡≡≡\u001b[22m\n",
       "\n",
       "\u001b[36m  julia> diagm([1,2,3])\u001b[39m\n",
       "\u001b[36m  3×3 Array{Int64,2}:\u001b[39m\n",
       "\u001b[36m   1  0  0\u001b[39m\n",
       "\u001b[36m   0  2  0\u001b[39m\n",
       "\u001b[36m   0  0  3\u001b[39m"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "?diagm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3×3 Diagonal{Int64,Array{Int64,1}}:\n",
       " 1  ⋅  ⋅\n",
       " ⋅  2  ⋅\n",
       " ⋅  ⋅  3"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert(Diagonal{Int64,Array{Int64,1}},diagm([1,2,3]))\n",
    "Diagonal([1,2,3])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`I` is a function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3×3 Diagonal{Bool,Array{Bool,1}}:\n",
       " 1  ⋅  ⋅\n",
       " ⋅  1  ⋅\n",
       " ⋅  ⋅  1"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "I(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 🟢Sparse Linear Algebra\n",
    "Sparse matrices are stored in Compressed Sparse Column (CSC) form"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5×5 SparseMatrixCSC{Float64,Int64} with 10 stored entries:\n",
       "  [3, 1]  =  0.438031\n",
       "  [4, 1]  =  0.0067164\n",
       "  [2, 2]  =  0.600359\n",
       "  [5, 3]  =  0.384574\n",
       "  [2, 4]  =  0.706176\n",
       "  [3, 4]  =  0.302186\n",
       "  [4, 4]  =  0.352668\n",
       "  [5, 4]  =  0.999347\n",
       "  [1, 5]  =  0.586474\n",
       "  [5, 5]  =  0.618744"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "using SparseArrays\n",
    "S = sprand(5,5,2/5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10-element Array{Int64,1}:\n",
       " 3\n",
       " 4\n",
       " 2\n",
       " 5\n",
       " 2\n",
       " 3\n",
       " 4\n",
       " 5\n",
       " 1\n",
       " 5"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "S.rowval"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5×5 Array{Float64,2}:\n",
       " 0.0        0.0       0.0       0.0       0.586474\n",
       " 0.0        0.600359  0.0       0.706176  0.0\n",
       " 0.438031   0.0       0.0       0.302186  0.0\n",
       " 0.0067164  0.0       0.0       0.352668  0.0\n",
       " 0.0        0.0       0.384574  0.999347  0.618744"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Matrix(S)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6-element Array{Int64,1}:\n",
       "  1\n",
       "  3\n",
       "  4\n",
       "  5\n",
       "  9\n",
       " 11"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "S.colptr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "S.m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 🟢Images as matrices\n",
    "Let's get to the more \"data science-y\" side. We will do so by working with images (which can be viewed as matrices), and we will use the `SVD` decomposition.\n",
    "\n",
    "First let's load an image. I chose this image as it has a lot of details."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: Precompiling QuartzImageIO [dca85d43-d64c-5e67-8c65-017450d5d020]\n",
      "└ @ Base loading.jl:1260\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "283×283 Array{RGBX{N0f8},2} with eltype RGBX{Normed{UInt8,8}}:\n",
       " RGBX{N0f8}(0.149,0.078,0.071)  …  RGBX{N0f8}(0.671,0.663,0.667)\n",
       " RGBX{N0f8}(0.118,0.047,0.039)     RGBX{N0f8}(0.51,0.494,0.498)\n",
       " RGBX{N0f8}(0.129,0.059,0.043)     RGBX{N0f8}(0.624,0.608,0.612)\n",
       " RGBX{N0f8}(0.137,0.071,0.043)     RGBX{N0f8}(0.157,0.137,0.153)\n",
       " RGBX{N0f8}(0.129,0.063,0.031)     RGBX{N0f8}(0.243,0.224,0.239)\n",
       " RGBX{N0f8}(0.125,0.059,0.027)  …  RGBX{N0f8}(0.18,0.161,0.176)\n",
       " RGBX{N0f8}(0.169,0.114,0.071)     RGBX{N0f8}(0.208,0.184,0.2)\n",
       " RGBX{N0f8}(0.482,0.427,0.384)     RGBX{N0f8}(0.153,0.129,0.145)\n",
       " RGBX{N0f8}(0.498,0.451,0.396)     RGBX{N0f8}(0.141,0.106,0.125)\n",
       " RGBX{N0f8}(0.49,0.443,0.388)      RGBX{N0f8}(0.161,0.125,0.137)\n",
       " RGBX{N0f8}(0.49,0.455,0.396)   …  RGBX{N0f8}(0.149,0.114,0.125)\n",
       " RGBX{N0f8}(0.498,0.463,0.404)     RGBX{N0f8}(0.141,0.106,0.118)\n",
       " RGBX{N0f8}(0.478,0.451,0.388)     RGBX{N0f8}(0.145,0.102,0.118)\n",
       " ⋮                              ⋱  \n",
       " RGBX{N0f8}(0.51,0.486,0.486)      RGBX{N0f8}(0.459,0.431,0.463)\n",
       " RGBX{N0f8}(0.49,0.475,0.431)      RGBX{N0f8}(0.443,0.424,0.439)\n",
       " RGBX{N0f8}(0.51,0.494,0.451)      RGBX{N0f8}(0.467,0.443,0.459)\n",
       " RGBX{N0f8}(0.482,0.471,0.435)     RGBX{N0f8}(0.451,0.404,0.42)\n",
       " RGBX{N0f8}(0.463,0.459,0.439)  …  RGBX{N0f8}(0.463,0.404,0.424)\n",
       " RGBX{N0f8}(0.443,0.443,0.435)     RGBX{N0f8}(0.392,0.329,0.341)\n",
       " RGBX{N0f8}(0.471,0.475,0.482)     RGBX{N0f8}(0.4,0.341,0.353)\n",
       " RGBX{N0f8}(0.471,0.486,0.498)     RGBX{N0f8}(0.349,0.31,0.314)\n",
       " RGBX{N0f8}(0.537,0.557,0.573)     RGBX{N0f8}(0.396,0.365,0.365)\n",
       " RGBX{N0f8}(0.529,0.557,0.58)   …  RGBX{N0f8}(0.424,0.4,0.4)\n",
       " RGBX{N0f8}(0.541,0.569,0.6)       RGBX{N0f8}(0.443,0.412,0.412)\n",
       " RGBX{N0f8}(0.541,0.576,0.604)     RGBX{N0f8}(0.459,0.412,0.427)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X1 = load(\"data/khiam-small.jpg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "typeof(X1) = Array{RGBX{Normed{UInt8,8}},2}\n"
     ]
    },
    {
     "data": {
      "image/svg+xml": [
       "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n",
       "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n",
       " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n",
       "<svg xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\"\n",
       "     width=\"25mm\" height=\"25mm\" viewBox=\"0 0 1 1\">\n",
       "    <rect width=\"1\" height=\"1\" fill=\"#261412\" stroke=\"none\"/>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "RGBX{N0f8}(0.149,0.078,0.071)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "@show typeof(X1)\n",
    "X1[1,1] # this is pixel [1,1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can easily convert this image to gray scale."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "283×283 Array{Gray{N0f8},2} with eltype Gray{Normed{UInt8,8}}:\n",
       " Gray{N0f8}(0.098)  Gray{N0f8}(0.063)  …  Gray{N0f8}(0.667)\n",
       " Gray{N0f8}(0.067)  Gray{N0f8}(0.098)     Gray{N0f8}(0.498)\n",
       " Gray{N0f8}(0.078)  Gray{N0f8}(0.086)     Gray{N0f8}(0.612)\n",
       " Gray{N0f8}(0.086)  Gray{N0f8}(0.067)     Gray{N0f8}(0.145)\n",
       " Gray{N0f8}(0.078)  Gray{N0f8}(0.102)     Gray{N0f8}(0.231)\n",
       " Gray{N0f8}(0.075)  Gray{N0f8}(0.075)  …  Gray{N0f8}(0.169)\n",
       " Gray{N0f8}(0.125)  Gray{N0f8}(0.094)     Gray{N0f8}(0.192)\n",
       " Gray{N0f8}(0.439)  Gray{N0f8}(0.447)     Gray{N0f8}(0.137)\n",
       " Gray{N0f8}(0.459)  Gray{N0f8}(0.455)     Gray{N0f8}(0.118)\n",
       " Gray{N0f8}(0.451)  Gray{N0f8}(0.467)     Gray{N0f8}(0.137)\n",
       " Gray{N0f8}(0.459)  Gray{N0f8}(0.459)  …  Gray{N0f8}(0.125)\n",
       " Gray{N0f8}(0.467)  Gray{N0f8}(0.451)     Gray{N0f8}(0.118)\n",
       " Gray{N0f8}(0.451)  Gray{N0f8}(0.451)     Gray{N0f8}(0.118)\n",
       " ⋮                                     ⋱  \n",
       " Gray{N0f8}(0.494)  Gray{N0f8}(0.478)     Gray{N0f8}(0.443)\n",
       " Gray{N0f8}(0.475)  Gray{N0f8}(0.482)     Gray{N0f8}(0.431)\n",
       " Gray{N0f8}(0.494)  Gray{N0f8}(0.502)     Gray{N0f8}(0.451)\n",
       " Gray{N0f8}(0.471)  Gray{N0f8}(0.494)     Gray{N0f8}(0.42)\n",
       " Gray{N0f8}(0.459)  Gray{N0f8}(0.482)  …  Gray{N0f8}(0.424)\n",
       " Gray{N0f8}(0.443)  Gray{N0f8}(0.459)     Gray{N0f8}(0.349)\n",
       " Gray{N0f8}(0.475)  Gray{N0f8}(0.478)     Gray{N0f8}(0.361)\n",
       " Gray{N0f8}(0.482)  Gray{N0f8}(0.478)     Gray{N0f8}(0.322)\n",
       " Gray{N0f8}(0.553)  Gray{N0f8}(0.553)     Gray{N0f8}(0.373)\n",
       " Gray{N0f8}(0.553)  Gray{N0f8}(0.549)  …  Gray{N0f8}(0.408)\n",
       " Gray{N0f8}(0.565)  Gray{N0f8}(0.553)     Gray{N0f8}(0.42)\n",
       " Gray{N0f8}(0.569)  Gray{N0f8}(0.553)     Gray{N0f8}(0.427)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Xgray = Gray.(X1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can easily extract the RGB layers from the image. We will make use of the `reshape` function below to reshape a vector to a matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "R = map(i->X1[i].r,1:length(X1))\n",
    "R = Float64.(reshape(R,size(X1)...))\n",
    "\n",
    "G = map(i->X1[i].g,1:length(X1))\n",
    "G = Float64.(reshape(G,size(X1)...))\n",
    "\n",
    "B = map(i->X1[i].b,1:length(X1))\n",
    "B = Float64.(reshape(B,size(X1)...))\n",
    ";"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "283×283 Array{RGB{Float64},2} with eltype RGB{Float64}:\n",
       " RGB{Float64}(0.0,0.0784314,0.0)  …  RGB{Float64}(0.0,0.662745,0.0)\n",
       " RGB{Float64}(0.0,0.0470588,0.0)     RGB{Float64}(0.0,0.494118,0.0)\n",
       " RGB{Float64}(0.0,0.0588235,0.0)     RGB{Float64}(0.0,0.607843,0.0)\n",
       " RGB{Float64}(0.0,0.0705882,0.0)     RGB{Float64}(0.0,0.137255,0.0)\n",
       " RGB{Float64}(0.0,0.0627451,0.0)     RGB{Float64}(0.0,0.223529,0.0)\n",
       " RGB{Float64}(0.0,0.0588235,0.0)  …  RGB{Float64}(0.0,0.160784,0.0)\n",
       " RGB{Float64}(0.0,0.113725,0.0)      RGB{Float64}(0.0,0.184314,0.0)\n",
       " RGB{Float64}(0.0,0.427451,0.0)      RGB{Float64}(0.0,0.129412,0.0)\n",
       " RGB{Float64}(0.0,0.45098,0.0)       RGB{Float64}(0.0,0.105882,0.0)\n",
       " RGB{Float64}(0.0,0.443137,0.0)      RGB{Float64}(0.0,0.12549,0.0)\n",
       " RGB{Float64}(0.0,0.454902,0.0)   …  RGB{Float64}(0.0,0.113725,0.0)\n",
       " RGB{Float64}(0.0,0.462745,0.0)      RGB{Float64}(0.0,0.105882,0.0)\n",
       " RGB{Float64}(0.0,0.45098,0.0)       RGB{Float64}(0.0,0.101961,0.0)\n",
       " ⋮                                ⋱  \n",
       " RGB{Float64}(0.0,0.486275,0.0)      RGB{Float64}(0.0,0.431373,0.0)\n",
       " RGB{Float64}(0.0,0.47451,0.0)       RGB{Float64}(0.0,0.423529,0.0)\n",
       " RGB{Float64}(0.0,0.494118,0.0)      RGB{Float64}(0.0,0.443137,0.0)\n",
       " RGB{Float64}(0.0,0.470588,0.0)      RGB{Float64}(0.0,0.403922,0.0)\n",
       " RGB{Float64}(0.0,0.458824,0.0)   …  RGB{Float64}(0.0,0.403922,0.0)\n",
       " RGB{Float64}(0.0,0.443137,0.0)      RGB{Float64}(0.0,0.329412,0.0)\n",
       " RGB{Float64}(0.0,0.47451,0.0)       RGB{Float64}(0.0,0.341176,0.0)\n",
       " RGB{Float64}(0.0,0.486275,0.0)      RGB{Float64}(0.0,0.309804,0.0)\n",
       " RGB{Float64}(0.0,0.556863,0.0)      RGB{Float64}(0.0,0.364706,0.0)\n",
       " RGB{Float64}(0.0,0.556863,0.0)   …  RGB{Float64}(0.0,0.4,0.0)\n",
       " RGB{Float64}(0.0,0.568627,0.0)      RGB{Float64}(0.0,0.411765,0.0)\n",
       " RGB{Float64}(0.0,0.576471,0.0)      RGB{Float64}(0.0,0.411765,0.0)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Z = zeros(size(R)...) # just a matrix of all zeros of equal size as the image\n",
    "RGB.(Z,G,Z)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can easily obtain the `Float64` values of the grayscale image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "283×283 Array{Float64,2}:\n",
       " 0.0980392  0.0627451  0.0784314  0.0941176  …  0.509804  0.552941  0.666667\n",
       " 0.0666667  0.0980392  0.0784314  0.054902      0.505882  0.584314  0.498039\n",
       " 0.0784314  0.0862745  0.0784314  0.0901961     0.6       0.701961  0.611765\n",
       " 0.0862745  0.0666667  0.0745098  0.0941176     0.658824  0.705882  0.145098\n",
       " 0.0784314  0.101961   0.0901961  0.0745098     0.713725  0.678431  0.231373\n",
       " 0.0745098  0.0745098  0.0784314  0.0862745  …  0.729412  0.701961  0.168627\n",
       " 0.12549    0.0941176  0.0862745  0.0862745     0.627451  0.466667  0.192157\n",
       " 0.439216   0.447059   0.305882   0.137255      0.231373  0.184314  0.137255\n",
       " 0.458824   0.454902   0.45098    0.454902      0.196078  0.101961  0.117647\n",
       " 0.45098    0.466667   0.458824   0.45098       0.584314  0.121569  0.137255\n",
       " 0.458824   0.458824   0.458824   0.454902   …  0.521569  0.513725  0.12549\n",
       " 0.466667   0.45098    0.458824   0.47451       0.576471  0.741176  0.117647\n",
       " 0.45098    0.45098    0.462745   0.458824      0.560784  0.67451   0.117647\n",
       " ⋮                                           ⋱  ⋮                   \n",
       " 0.494118   0.478431   0.47451    0.462745      0.427451  0.435294  0.443137\n",
       " 0.47451    0.482353   0.470588   0.470588      0.439216  0.431373  0.431373\n",
       " 0.494118   0.501961   0.470588   0.45098       0.447059  0.447059  0.45098\n",
       " 0.470588   0.494118   0.490196   0.482353      0.431373  0.419608  0.419608\n",
       " 0.458824   0.482353   0.47451    0.466667   …  0.454902  0.435294  0.423529\n",
       " 0.443137   0.458824   0.45098    0.45098       0.309804  0.32549   0.34902\n",
       " 0.47451    0.478431   0.462745   0.462745      0.341176  0.345098  0.360784\n",
       " 0.482353   0.478431   0.458824   0.458824      0.419608  0.372549  0.321569\n",
       " 0.552941   0.552941   0.541176   0.533333      0.447059  0.411765  0.372549\n",
       " 0.552941   0.54902    0.576471   0.552941   …  0.435294  0.423529  0.407843\n",
       " 0.564706   0.552941   0.54902    0.505882      0.439216  0.431373  0.419608\n",
       " 0.568627   0.552941   0.521569   0.462745      0.439216  0.431373  0.427451"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Xgrayvalues = Float64.(Xgray)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we will downsample this image using the SVD. First, let's obtain the SVD decomposition."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVD{Float64,Float64,Array{Float64,2}}\n",
       "U factor:\n",
       "283×283 Array{Float64,2}:\n",
       " -0.0635304  -0.131839    -0.11643     …  -0.0117278    0.00738876\n",
       " -0.0626353  -0.150519    -0.112063        0.0180944   -0.0603969\n",
       " -0.0616791  -0.165416    -0.105702       -0.0432192   -0.0192312\n",
       " -0.061823   -0.17487     -0.0962379       0.00404143  -0.00602634\n",
       " -0.0626639  -0.178819    -0.0858857      -0.0547859    0.0348994\n",
       " -0.062426   -0.180596    -0.0776284   …   0.0388114   -0.0493565\n",
       " -0.0617712  -0.18373     -0.06467        -0.0178014    0.016417\n",
       " -0.061205   -0.189956    -0.0439959       0.0611105    0.0618372\n",
       " -0.0600175  -0.193781    -0.0263519      -0.0314437    0.0237265\n",
       " -0.0595613  -0.193258    -0.00823976      0.0042891   -0.0146053\n",
       " -0.0592922  -0.189677     0.0127842   …  -0.00199834  -0.0124865\n",
       " -0.0588676  -0.184172     0.0357173       0.0103637    0.0203563\n",
       " -0.058853   -0.173965     0.0602806      -0.0116031   -0.0832927\n",
       "  ⋮                                    ⋱               \n",
       " -0.0569826  -0.0201465    0.0660973      -0.115984    -0.0585304\n",
       " -0.0568663  -0.0123984    0.0650178      -0.0340802    0.0201757\n",
       " -0.0570423  -0.00961045   0.0710127      -0.0775642    0.106337\n",
       " -0.05692    -0.0223569    0.0807945       0.0886235    0.060707\n",
       " -0.0558864  -0.028646     0.077156    …   0.0147699    0.0543351\n",
       " -0.0556692  -0.0314186    0.0755852       0.0549292   -0.108216\n",
       " -0.0564913  -0.0248891    0.0791656      -0.0162953    0.112085\n",
       " -0.0570511  -0.023051     0.0950692       0.012969    -0.189908\n",
       " -0.0569586  -0.0340126    0.103554       -0.0804813    0.00460067\n",
       " -0.0564649  -0.0406048    0.0920338   …  -0.0324717   -0.0269201\n",
       " -0.0564069  -0.0346054    0.0899593       0.0966035    0.0892608\n",
       " -0.0567346  -0.0285336    0.0840931       0.0354768   -0.0943327\n",
       "singular values:\n",
       "283-element Array{Float64,1}:\n",
       " 118.04189604068874\n",
       "  16.328380424994183\n",
       "  14.476787107972532\n",
       "  12.77496446923333\n",
       "  11.693055439916673\n",
       "   9.210135114015118\n",
       "   8.392820265140037\n",
       "   7.464870080664664\n",
       "   6.548568510752549\n",
       "   5.435071104621175\n",
       "   5.289133576536215\n",
       "   4.828360618188314\n",
       "   4.5783406491255905\n",
       "   ⋮\n",
       "   0.032276231682638046\n",
       "   0.027342581516288815\n",
       "   0.024079818877196933\n",
       "   0.022711973238018816\n",
       "   0.020124147747648178\n",
       "   0.014517257396981436\n",
       "   0.013482121921611594\n",
       "   0.01118652818946172\n",
       "   0.009153430763463408\n",
       "   0.005629053989779064\n",
       "   0.0033624606299640183\n",
       "   0.0014767770562946847\n",
       "Vt factor:\n",
       "283×283 Array{Float64,2}:\n",
       " -0.04237      -0.0427969   -0.0411418   …  -0.06885     -0.0668306\n",
       " -0.0170991    -0.00649451  -0.0198767       0.0209826    0.0629725\n",
       "  0.0466992     0.0331713    0.0305042      -0.0441452   -0.0465419\n",
       " -0.0197308    -0.0382101   -0.0420783      -0.0260171   -0.0131892\n",
       "  0.0445477     0.0249714    0.0174406       0.0521657    0.0696876\n",
       " -0.0524076    -0.0480539   -0.0646097   …   0.0135414   -0.0352727\n",
       "  0.0441811     0.0570927    0.0553505       0.0163962    0.0305056\n",
       " -0.0279442    -0.019959    -0.0205922       0.0562029    0.0330475\n",
       "  0.0786667     0.0864098    0.132677        0.0377532    0.0363607\n",
       "  0.118299      0.134537     0.110292       -0.0528907   -0.0455728\n",
       " -0.0604394    -0.0447648   -0.0357249   …  -0.0480708   -0.0461297\n",
       "  0.116522      0.100197     0.0810574       0.0210671   -0.00637789\n",
       " -0.0152848    -0.0386831   -0.0294735      -0.0314558    0.0562791\n",
       "  ⋮                                      ⋱               \n",
       "  0.0264365    -0.0208248   -0.0362592       0.0730787   -0.0969246\n",
       "  0.0118158     0.0262053   -0.00172901     -0.0604202    0.000470713\n",
       "  0.0701377    -0.0324137    0.108229       -0.0440657    0.0116964\n",
       "  0.0170219     0.113511    -0.0515462      -0.0399928    0.0794217\n",
       " -0.0531091     0.0518792   -0.00551529  …  -0.0164861    0.0116762\n",
       " -0.057445      0.0570675   -0.00888231     -0.0112255   -0.0409418\n",
       " -0.0234717     0.0408859    0.0521775       0.017209    -0.0009115\n",
       " -0.00151444    0.024248    -0.0543359      -0.00113107   0.0127544\n",
       " -0.00258465    0.0394899   -0.131575       -0.0390885    0.0228227\n",
       " -0.0580211     0.151436     0.00912932  …   0.062442    -0.0201693\n",
       " -0.0366921     0.00535911   0.0201197       0.0926434   -0.0821915\n",
       " -0.000239667  -0.00453375  -0.0383345       0.0117324   -0.0706353"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SVD_V = svd(Xgrayvalues)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8.866548274256087e-13"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norm(SVD_V.U*diagm(SVD_V.S)*SVD_V.V' - Xgrayvalues)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "283×283 Array{Float64,2}:\n",
       " 0.296182  0.318408  0.343288  0.3428    …  0.551978  0.572385  0.457663\n",
       " 0.300941  0.320033  0.34921   0.349204     0.537344  0.557327  0.429165\n",
       " 0.304505  0.319618  0.351969  0.352937     0.521884  0.540239  0.401943\n",
       " 0.312917  0.323286  0.357045  0.359396     0.515237  0.530346  0.386081\n",
       " 0.323271  0.329142  0.362818  0.366569     0.515375  0.526637  0.380375\n",
       " 0.326244  0.328384  0.3618    0.366795  …  0.508168  0.516291  0.369826\n",
       " 0.330672  0.327889  0.361238  0.367471     0.494911  0.499066  0.351415\n",
       " 0.341415  0.331471  0.365074  0.372738     0.477811  0.476297  0.325186\n",
       " 0.347501  0.332471  0.36627   0.374449     0.458205  0.452779  0.299349\n",
       " 0.355171  0.33465   0.367304  0.376499     0.445244  0.434844  0.282649\n",
       " 0.364643  0.338368  0.36901   0.379112  …  0.433318  0.417289  0.268441\n",
       " 0.372942  0.339788  0.36773   0.379338     0.419267  0.396395  0.25293\n",
       " 0.38212   0.341701  0.365584  0.378994     0.408862  0.378134  0.243748\n",
       " ⋮                                       ⋱  ⋮                   \n",
       " 0.35427   0.35847   0.352905  0.341237     0.446894  0.438971  0.396952\n",
       " 0.348969  0.353006  0.345455  0.334502     0.447923  0.438963  0.403508\n",
       " 0.351898  0.354103  0.345437  0.334993     0.44691   0.4359    0.402904\n",
       " 0.361119  0.358879  0.352577  0.34305      0.43737   0.423841  0.382016\n",
       " 0.361363  0.364424  0.361038  0.347847  …  0.431377  0.423677  0.373936\n",
       " 0.362403  0.367541  0.365338  0.350729     0.430575  0.42515   0.372044\n",
       " 0.370894  0.380046  0.376858  0.359148     0.439524  0.436767  0.385359\n",
       " 0.379452  0.381638  0.376447  0.361321     0.435349  0.425874  0.377954\n",
       " 0.385723  0.382414  0.378904  0.365772     0.426391  0.413224  0.358858\n",
       " 0.37667   0.373855  0.372202  0.360215  …  0.425272  0.413477  0.355521\n",
       " 0.373652  0.372607  0.369803  0.357196     0.427727  0.416848  0.362864\n",
       " 0.372542  0.37644   0.373043  0.358158     0.436352  0.42918   0.377592"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# use the top 4 singular vectors/values to form a new image\n",
    "u1 = SVD_V.U[:,1]\n",
    "v1 = SVD_V.V[:,1]\n",
    "img1 = SVD_V.S[1]*u1*v1'\n",
    "\n",
    "i = 2\n",
    "u1 = SVD_V.U[:,i]\n",
    "v1 = SVD_V.V[:,i]\n",
    "img1 += SVD_V.S[i]*u1*v1'\n",
    "\n",
    "i = 3\n",
    "u1 = SVD_V.U[:,i]\n",
    "v1 = SVD_V.V[:,i]\n",
    "img1 += SVD_V.S[i]*u1*v1'\n",
    "\n",
    "i = 4\n",
    "u1 = SVD_V.U[:,i]\n",
    "v1 = SVD_V.V[:,i]\n",
    "img1 += SVD_V.S[i]*u1*v1'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "283×283 Array{Gray{Float64},2} with eltype Gray{Float64}:\n",
       " Gray{Float64}(0.296182)  Gray{Float64}(0.318408)  …  Gray{Float64}(0.457663)\n",
       " Gray{Float64}(0.300941)  Gray{Float64}(0.320033)     Gray{Float64}(0.429165)\n",
       " Gray{Float64}(0.304505)  Gray{Float64}(0.319618)     Gray{Float64}(0.401943)\n",
       " Gray{Float64}(0.312917)  Gray{Float64}(0.323286)     Gray{Float64}(0.386081)\n",
       " Gray{Float64}(0.323271)  Gray{Float64}(0.329142)     Gray{Float64}(0.380375)\n",
       " Gray{Float64}(0.326244)  Gray{Float64}(0.328384)  …  Gray{Float64}(0.369826)\n",
       " Gray{Float64}(0.330672)  Gray{Float64}(0.327889)     Gray{Float64}(0.351415)\n",
       " Gray{Float64}(0.341415)  Gray{Float64}(0.331471)     Gray{Float64}(0.325186)\n",
       " Gray{Float64}(0.347501)  Gray{Float64}(0.332471)     Gray{Float64}(0.299349)\n",
       " Gray{Float64}(0.355171)  Gray{Float64}(0.33465)      Gray{Float64}(0.282649)\n",
       " Gray{Float64}(0.364643)  Gray{Float64}(0.338368)  …  Gray{Float64}(0.268441)\n",
       " Gray{Float64}(0.372942)  Gray{Float64}(0.339788)     Gray{Float64}(0.25293)\n",
       " Gray{Float64}(0.38212)   Gray{Float64}(0.341701)     Gray{Float64}(0.243748)\n",
       " ⋮                                                 ⋱  \n",
       " Gray{Float64}(0.35427)   Gray{Float64}(0.35847)      Gray{Float64}(0.396952)\n",
       " Gray{Float64}(0.348969)  Gray{Float64}(0.353006)     Gray{Float64}(0.403508)\n",
       " Gray{Float64}(0.351898)  Gray{Float64}(0.354103)     Gray{Float64}(0.402904)\n",
       " Gray{Float64}(0.361119)  Gray{Float64}(0.358879)     Gray{Float64}(0.382016)\n",
       " Gray{Float64}(0.361363)  Gray{Float64}(0.364424)  …  Gray{Float64}(0.373936)\n",
       " Gray{Float64}(0.362403)  Gray{Float64}(0.367541)     Gray{Float64}(0.372044)\n",
       " Gray{Float64}(0.370894)  Gray{Float64}(0.380046)     Gray{Float64}(0.385359)\n",
       " Gray{Float64}(0.379452)  Gray{Float64}(0.381638)     Gray{Float64}(0.377954)\n",
       " Gray{Float64}(0.385723)  Gray{Float64}(0.382414)     Gray{Float64}(0.358858)\n",
       " Gray{Float64}(0.37667)   Gray{Float64}(0.373855)  …  Gray{Float64}(0.355521)\n",
       " Gray{Float64}(0.373652)  Gray{Float64}(0.372607)     Gray{Float64}(0.362864)\n",
       " Gray{Float64}(0.372542)  Gray{Float64}(0.37644)      Gray{Float64}(0.377592)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Gray.(img1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, it's still far away from the original image. Let's try using 100 singular vectors/values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "283×283 Array{Gray{Float64},2} with eltype Gray{Float64}:\n",
       " Gray{Float64}(0.0977603)  …  Gray{Float64}(0.62991)\n",
       " Gray{Float64}(0.074757)      Gray{Float64}(0.559608)\n",
       " Gray{Float64}(0.0582045)     Gray{Float64}(0.535325)\n",
       " Gray{Float64}(0.0978488)     Gray{Float64}(0.220123)\n",
       " Gray{Float64}(0.104926)      Gray{Float64}(0.210099)\n",
       " Gray{Float64}(0.0673836)  …  Gray{Float64}(0.238482)\n",
       " Gray{Float64}(0.105168)      Gray{Float64}(0.154107)\n",
       " Gray{Float64}(0.438038)      Gray{Float64}(0.129803)\n",
       " Gray{Float64}(0.462261)      Gray{Float64}(0.104301)\n",
       " Gray{Float64}(0.44404)       Gray{Float64}(0.136431)\n",
       " Gray{Float64}(0.458935)   …  Gray{Float64}(0.117797)\n",
       " Gray{Float64}(0.472762)      Gray{Float64}(0.157769)\n",
       " Gray{Float64}(0.437656)      Gray{Float64}(0.126669)\n",
       " ⋮                         ⋱  \n",
       " Gray{Float64}(0.481671)      Gray{Float64}(0.454825)\n",
       " Gray{Float64}(0.47617)       Gray{Float64}(0.485812)\n",
       " Gray{Float64}(0.49531)       Gray{Float64}(0.480303)\n",
       " Gray{Float64}(0.468687)      Gray{Float64}(0.427169)\n",
       " Gray{Float64}(0.471622)   …  Gray{Float64}(0.414139)\n",
       " Gray{Float64}(0.431669)      Gray{Float64}(0.303776)\n",
       " Gray{Float64}(0.479864)      Gray{Float64}(0.342059)\n",
       " Gray{Float64}(0.492655)      Gray{Float64}(0.327173)\n",
       " Gray{Float64}(0.552928)      Gray{Float64}(0.350434)\n",
       " Gray{Float64}(0.524978)   …  Gray{Float64}(0.39918)\n",
       " Gray{Float64}(0.565734)      Gray{Float64}(0.394644)\n",
       " Gray{Float64}(0.586747)      Gray{Float64}(0.429273)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "i = 1:100\n",
    "u1 = SVD_V.U[:,i]\n",
    "v1 = SVD_V.V[:,i]\n",
    "img1 = u1*spdiagm(0=>SVD_V.S[i])*v1'\n",
    "Gray.(img1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This looks almost identical to the original image, even though it's not identical to the original image (and we can see that from the norm difference)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.5263825920952545"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norm(Xgrayvalues-img1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our next problem will still be related to images, but this time we will solve a simple form of the face recognition problem. Let's get the data first."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dict{String,Any} with 1 entry:\n",
       "  \"V2\" => [0.08103 0.0729089 … 0.0529805 0.0594823; 0.089725 0.082329 … 0.05180…"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "M = matread(\"data/face_recog_qr.mat\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Each vector in `M[\"V2\"]` is a fase image. Let's reshape the first one and take a look."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "192×168 Array{Gray{Float64},2} with eltype Gray{Float64}:\n",
       " Gray{Float64}(0.08103)    …  Gray{Float64}(0.0990184)\n",
       " Gray{Float64}(0.089725)      Gray{Float64}(0.0999127)\n",
       " Gray{Float64}(0.0873804)     Gray{Float64}(0.0945833)\n",
       " Gray{Float64}(0.084184)      Gray{Float64}(0.0959911)\n",
       " Gray{Float64}(0.0892354)     Gray{Float64}(0.104112)\n",
       " Gray{Float64}(0.0872113)  …  Gray{Float64}(0.106626)\n",
       " Gray{Float64}(0.0906193)     Gray{Float64}(0.100638)\n",
       " Gray{Float64}(0.0987404)     Gray{Float64}(0.106904)\n",
       " Gray{Float64}(0.0893203)     Gray{Float64}(0.118179)\n",
       " Gray{Float64}(0.0858459)     Gray{Float64}(0.117007)\n",
       " Gray{Float64}(0.0931994)  …  Gray{Float64}(0.115279)\n",
       " Gray{Float64}(0.0892778)     Gray{Float64}(0.108608)\n",
       " Gray{Float64}(0.0994656)     Gray{Float64}(0.110505)\n",
       " ⋮                         ⋱  \n",
       " Gray{Float64}(0.0336083)  …  Gray{Float64}(0.103345)\n",
       " Gray{Float64}(0.0347806)     Gray{Float64}(0.0927523)\n",
       " Gray{Float64}(0.0287924)     Gray{Float64}(0.0846311)\n",
       " Gray{Float64}(0.0254871)     Gray{Float64}(0.0756157)\n",
       " Gray{Float64}(0.0296867)     Gray{Float64}(0.063851)\n",
       " Gray{Float64}(0.0269374)  …  Gray{Float64}(0.0611017)\n",
       " Gray{Float64}(0.0281097)     Gray{Float64}(0.0502313)\n",
       " Gray{Float64}(0.0269799)     Gray{Float64}(0.0347806)\n",
       " Gray{Float64}(0.0250824)     Gray{Float64}(0.0273421)\n",
       " Gray{Float64}(0.0273846)     Gray{Float64}(0.0289615)\n",
       " Gray{Float64}(0.0321579)  …  Gray{Float64}(0.0247619)\n",
       " Gray{Float64}(0.0360131)     Gray{Float64}(0.0270641)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = reshape(M[\"V2\"][:,1],192,168)\n",
    "Gray.(q)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we will go back to the vectorized version of this image, and try to select the images that are most similar to it from the \"dictionary\" matrix. Let's use `b = q[:]` to be the query image. Note that the notation `[:]` vectorizes a matrix column wise."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "32256-element Array{Float64,1}:\n",
       " 0.0810300261581645\n",
       " 0.08972497847335578\n",
       " 0.0873803822279144\n",
       " 0.0841839709221837\n",
       " 0.08923537113064388\n",
       " 0.08721125794763387\n",
       " 0.09061926007535659\n",
       " 0.09874041385097843\n",
       " 0.08932030421406685\n",
       " 0.08584587638761629\n",
       " 0.09319940629980634\n",
       " 0.08927783767235538\n",
       " 0.0994655711726987\n",
       " ⋮\n",
       " 0.10334467325843819\n",
       " 0.09275226549880594\n",
       " 0.0846311117231841\n",
       " 0.07561567634556146\n",
       " 0.06385097046320852\n",
       " 0.06110169995847822\n",
       " 0.05023127567812609\n",
       " 0.03478055114733056\n",
       " 0.027342088151717514\n",
       " 0.028961527075438608\n",
       " 0.024761941927267744\n",
       " 0.027064071630997635"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = q[:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will remove the first image from the dictionary. The goal is to find the solution of the linear system `Ax=b` where `A` is the dictionary of all images. In face recognition problem we really want to minimize the norm differece `norm(Ax-b)` but the `\\` actually solves a least squares problem when the matrix at hand is not invertible."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "192×168 Array{Gray{Float64},2} with eltype Gray{Float64}:\n",
       " Gray{Float64}(0.08103)    …  Gray{Float64}(0.0990184)\n",
       " Gray{Float64}(0.089725)      Gray{Float64}(0.0999127)\n",
       " Gray{Float64}(0.0873804)     Gray{Float64}(0.0945833)\n",
       " Gray{Float64}(0.084184)      Gray{Float64}(0.0959911)\n",
       " Gray{Float64}(0.0892354)     Gray{Float64}(0.104112)\n",
       " Gray{Float64}(0.0872113)  …  Gray{Float64}(0.106626)\n",
       " Gray{Float64}(0.0906193)     Gray{Float64}(0.100638)\n",
       " Gray{Float64}(0.0987404)     Gray{Float64}(0.106904)\n",
       " Gray{Float64}(0.0893203)     Gray{Float64}(0.118179)\n",
       " Gray{Float64}(0.0858459)     Gray{Float64}(0.117007)\n",
       " Gray{Float64}(0.0931994)  …  Gray{Float64}(0.115279)\n",
       " Gray{Float64}(0.0892778)     Gray{Float64}(0.108608)\n",
       " Gray{Float64}(0.0994656)     Gray{Float64}(0.110505)\n",
       " ⋮                         ⋱  \n",
       " Gray{Float64}(0.0336083)  …  Gray{Float64}(0.103345)\n",
       " Gray{Float64}(0.0347806)     Gray{Float64}(0.0927523)\n",
       " Gray{Float64}(0.0287924)     Gray{Float64}(0.0846311)\n",
       " Gray{Float64}(0.0254871)     Gray{Float64}(0.0756157)\n",
       " Gray{Float64}(0.0296867)     Gray{Float64}(0.063851)\n",
       " Gray{Float64}(0.0269374)  …  Gray{Float64}(0.0611017)\n",
       " Gray{Float64}(0.0281097)     Gray{Float64}(0.0502313)\n",
       " Gray{Float64}(0.0269799)     Gray{Float64}(0.0347806)\n",
       " Gray{Float64}(0.0250824)     Gray{Float64}(0.0273421)\n",
       " Gray{Float64}(0.0273846)     Gray{Float64}(0.0289615)\n",
       " Gray{Float64}(0.0321579)  …  Gray{Float64}(0.0247619)\n",
       " Gray{Float64}(0.0360131)     Gray{Float64}(0.0270641)"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A = M[\"V2\"][:,2:end]\n",
    "x = A\\b #Ax=b\n",
    "Gray.(reshape(A*x,192,168))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.4803574387833323e-14"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norm(A*x-b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This was an easy problem. Let's try to make the picture harder to recover. We will add some random error."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "192×168 Array{Gray{Float64},2} with eltype Gray{Float64}:\n",
       " Gray{Float64}(0.260351)   …  Gray{Float64}(0.225117)\n",
       " Gray{Float64}(0.46277)       Gray{Float64}(0.38484)\n",
       " Gray{Float64}(0.0939145)     Gray{Float64}(0.400015)\n",
       " Gray{Float64}(0.191289)      Gray{Float64}(0.111034)\n",
       " Gray{Float64}(0.377208)      Gray{Float64}(0.140466)\n",
       " Gray{Float64}(0.42303)    …  Gray{Float64}(0.516606)\n",
       " Gray{Float64}(0.311579)      Gray{Float64}(0.423216)\n",
       " Gray{Float64}(0.274582)      Gray{Float64}(0.234876)\n",
       " Gray{Float64}(0.221614)      Gray{Float64}(0.36101)\n",
       " Gray{Float64}(0.174896)      Gray{Float64}(0.338019)\n",
       " Gray{Float64}(0.119864)   …  Gray{Float64}(0.296332)\n",
       " Gray{Float64}(0.193724)      Gray{Float64}(0.4877)\n",
       " Gray{Float64}(0.44702)       Gray{Float64}(0.213415)\n",
       " ⋮                         ⋱  \n",
       " Gray{Float64}(0.236826)   …  Gray{Float64}(0.123341)\n",
       " Gray{Float64}(0.341711)      Gray{Float64}(0.263161)\n",
       " Gray{Float64}(0.413403)      Gray{Float64}(0.22294)\n",
       " Gray{Float64}(0.279355)      Gray{Float64}(0.34319)\n",
       " Gray{Float64}(0.4114)        Gray{Float64}(0.177875)\n",
       " Gray{Float64}(0.0675063)  …  Gray{Float64}(0.172777)\n",
       " Gray{Float64}(0.212521)      Gray{Float64}(0.159573)\n",
       " Gray{Float64}(0.394269)      Gray{Float64}(0.420566)\n",
       " Gray{Float64}(0.0863218)     Gray{Float64}(0.200435)\n",
       " Gray{Float64}(0.194825)      Gray{Float64}(0.0432486)\n",
       " Gray{Float64}(0.149955)   …  Gray{Float64}(0.0698718)\n",
       " Gray{Float64}(0.367795)      Gray{Float64}(0.352145)"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qv = q+rand(size(q,1),size(q,2))*0.5\n",
    "qv = qv./maximum(qv)\n",
    "Gray.(qv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = qv[:];"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "22.95190690033657"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = A\\b\n",
    "norm(A*x-b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The error is so much bigger this time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "192×168 Array{Gray{Float64},2} with eltype Gray{Float64}:\n",
       " Gray{Float64}(0.256125)  Gray{Float64}(0.25265)   …  Gray{Float64}(0.279918)\n",
       " Gray{Float64}(0.263324)  Gray{Float64}(0.277312)     Gray{Float64}(0.276782)\n",
       " Gray{Float64}(0.259559)  Gray{Float64}(0.272998)     Gray{Float64}(0.266121)\n",
       " Gray{Float64}(0.271894)  Gray{Float64}(0.278207)     Gray{Float64}(0.260424)\n",
       " Gray{Float64}(0.272656)  Gray{Float64}(0.275102)     Gray{Float64}(0.279246)\n",
       " Gray{Float64}(0.297829)  Gray{Float64}(0.282191)  …  Gray{Float64}(0.285803)\n",
       " Gray{Float64}(0.282838)  Gray{Float64}(0.276605)     Gray{Float64}(0.270912)\n",
       " Gray{Float64}(0.271903)  Gray{Float64}(0.270307)     Gray{Float64}(0.282397)\n",
       " Gray{Float64}(0.289707)  Gray{Float64}(0.280117)     Gray{Float64}(0.285172)\n",
       " Gray{Float64}(0.282173)  Gray{Float64}(0.275989)     Gray{Float64}(0.293157)\n",
       " Gray{Float64}(0.279762)  Gray{Float64}(0.287938)  …  Gray{Float64}(0.291075)\n",
       " Gray{Float64}(0.264797)  Gray{Float64}(0.279654)     Gray{Float64}(0.292453)\n",
       " Gray{Float64}(0.269356)  Gray{Float64}(0.274845)     Gray{Float64}(0.297412)\n",
       " ⋮                                                 ⋱  \n",
       " Gray{Float64}(0.285857)  Gray{Float64}(0.273944)  …  Gray{Float64}(0.306618)\n",
       " Gray{Float64}(0.303435)  Gray{Float64}(0.27368)      Gray{Float64}(0.306095)\n",
       " Gray{Float64}(0.30583)   Gray{Float64}(0.26388)      Gray{Float64}(0.296294)\n",
       " Gray{Float64}(0.266914)  Gray{Float64}(0.254467)     Gray{Float64}(0.294853)\n",
       " Gray{Float64}(0.28758)   Gray{Float64}(0.278109)     Gray{Float64}(0.272472)\n",
       " Gray{Float64}(0.3076)    Gray{Float64}(0.302109)  …  Gray{Float64}(0.286775)\n",
       " Gray{Float64}(0.302859)  Gray{Float64}(0.29447)      Gray{Float64}(0.285699)\n",
       " Gray{Float64}(0.282051)  Gray{Float64}(0.311691)     Gray{Float64}(0.26836)\n",
       " Gray{Float64}(0.284217)  Gray{Float64}(0.29756)      Gray{Float64}(0.271459)\n",
       " Gray{Float64}(0.300035)  Gray{Float64}(0.316095)     Gray{Float64}(0.278572)\n",
       " Gray{Float64}(0.320281)  Gray{Float64}(0.330096)  …  Gray{Float64}(0.257561)\n",
       " Gray{Float64}(0.346234)  Gray{Float64}(0.327669)     Gray{Float64}(0.245737)"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Gray.(reshape(A*x,192,168))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Finally...\n",
    "After finishing this notebook, you should be able to:\n",
    "- [ ] reshape and vectorize a matrix\n",
    "- [ ] apply basic linear algebra operations such as transpose, matrix-matrix product, and solve a linear systerm\n",
    "- [ ] call a linear algebra factorization on your matrix\n",
    "- [ ] use SVD to created a compressed version of an image\n",
    "- [ ] solve the face recognition problem via a least square approach\n",
    "- [ ] create a sparse matrix, and call the components of the Compressed Sparse Column storage\n",
    "- [ ] list a few types of matrices Julia uses (diagonal, upper triangular,...)\n",
    "- [ ] (unrelated to linear algebra): load an image, convert it to grayscale, and extract the RGB layers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 🥳 One cool finding\n",
    "\n",
    "We can solve a simple form of the face recognition problem even when a face image has been distorted with wrong pixels. Example, one of our inputs was this image: <img src=\"data/0201.png\" width=\"100\">\n",
    "\n",
    "And we were able to detect this face to be closest to the input image: <img src=\"data/0202.png\" width=\"100\">"
   ]
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