{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Table of Contents](table_of_contents.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Topic 17. LU Factorization\n",
    "Author: Spencer Ammermon \n",
    "        spencer.ammermon@gmail.com\n",
    "    \n",
    "Engineering Example: Daniel Free, daniel.free816@gmail.com"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  Introduction\n",
    "Many situations arise where an engineer must solve a linear equation of the form $\\textbf{A}\\vec{x}=\\vec{b}$. In some cases, matrix $\\textbf{A}$ is in a special form (such as a Toeplitz, Vandermonde, or Hankel matrix) and $\\vec{x}$ can easily be solved for numerically. When these special forms do not apply to matrix $\\textbf{A}$, one possibility is to factorize $\\textbf{A} = \\textbf{LU}$ where $\\textbf{L}$ is a lower triangular matrix with ones on the diagonal and $\\textbf{U}$ is an upper diagonal matrix. The solution to $\\textbf{A}\\vec{x}=\\vec{b}$ can then be found without explicitly computing $\\textbf{A}^{-1}\\vec{b}$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## LU Factorization in Detail\n",
    "\n",
    "When finding the factorization of an $m x m$ matrix $\\textbf{A}$, we also compute a permutation matrix $\\textbf{P}$ that represents $\\textit{pivoting}$ in the factorization. We pivot in the factorization so that we always divide by large numbers to ensure numerical stability. The factorization then becomes $\\textbf{PA} = \\textbf{LU}$. \n",
    "\n",
    "### Computing P, L, and U\n",
    "\n",
    "To compute matrices $\\textbf{P}$, $\\textbf{L}$, and $\\textbf{U}$, begin with the original matrix $\\textbf{A}$. The goal is to put matrix $\\textbf{A}$ in triangular form while maintaining numerical stability by pivoting to reduce the row with the largest element. Consider Dr. Beard's example matrix:\n",
    "\\begin{equation}\n",
    "\\textbf{A} = \n",
    "\\begin{bmatrix}\n",
    "    1 & -2 & 3\\\\\n",
    "    -4 & 5 & -6\\\\\n",
    "    7 & -8 & 9\n",
    "\\end{bmatrix}\n",
    "\\end{equation}\n",
    "Where we need to swap row 1 and 3 so that the largest element in column 1 is in the 1st position of column 1. To do this, we can compute $\\textbf{P}_{1,3}\\textbf{A}$ where $\\textbf{P}_{1,3}$ is found by swapping $\\textit{columns}$ 1 and 3 of an identity matrix. \n",
    "\n",
    "A function that computes the permutation matrix is as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "First Permutation Matrix:\n",
      " [[0. 0. 1.]\n",
      " [0. 1. 0.]\n",
      " [1. 0. 0.]]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "A = np.array([[1, -2, 3],\n",
    "              [-4, 5, -6],\n",
    "              [7, -8, 9]])\n",
    "\n",
    "def permutationMatrix(n,col,Q): # n is number of rows and cols, Q is a matrix\n",
    "    # look down first column, find the largest value in magnitude\n",
    "    # create a permutation matrix with ones and zeros \n",
    "    P = np.identity(n)\n",
    "    max_index_in_col = np.argmax((np.abs(Q[col:,col:][:,0])))\n",
    "    # swap the col column with the max column\n",
    "    P[:,[col, max_index_in_col+col]] = P[:,[max_index_in_col+col, col]]\n",
    "    return P\n",
    "\n",
    "P_13 = permutationMatrix(3,0,A)\n",
    "\n",
    "print('First Permutation Matrix:\\n',P_13)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\\begin{equation}\n",
    "    \\textbf{P}_{1,3}\\textbf{A}=\n",
    "    \\begin{bmatrix}\n",
    "    0 & 0 & 1\\\\\n",
    "    0 & 1 & 0\\\\\n",
    "    1 & 0 & 0\n",
    "    \\end{bmatrix}\n",
    "    \\begin{bmatrix}\n",
    "    1 & -2 & 3\\\\\n",
    "    -4 & 5 & -6\\\\\n",
    "    7 & -8 & 9\n",
    "    \\end{bmatrix} =\n",
    "    \\begin{bmatrix}\n",
    "    7 & -8 & 9\\\\\n",
    "    -4 & 5 & -6\\\\\n",
    "    1 & -2 & 3\n",
    "    \\end{bmatrix}\n",
    "\\end{equation}\n",
    "The next step is to zero out rows 2 and 3 in column 1 by dividing by the value in $\\textbf{A}[1,1]$. This is done by finding an elementary matrix that is an identity matrix with a first column that will zero out the first column of $\\textbf{P}_{1,3}\\textbf{A}$ when multiplied. To find $\\textbf{E}_1$, start with an identity matrix and then copy the first column of $\\textbf{P}_{1,3}\\textbf{A}$ to the first column of the identity matrix, and then multiply column 1 by $\\dfrac{-1}{\\textbf{P}_{1,3}\\textbf{A}[1,1]}$. This leads to:\n",
    "\\begin{equation}\n",
    "    \\textbf{E}_1\\textbf{P}_{1,3}\\textbf{A} = \n",
    "    \\begin{bmatrix}\n",
    "    1 & 0 & 0\\\\\n",
    "    \\frac{4}{7} & 1 & 0\\\\\n",
    "    \\frac{-1}{7} & 0 & 1\n",
    "    \\end{bmatrix}\n",
    "        \\begin{bmatrix}\n",
    "    0 & 0 & 1\\\\\n",
    "    0 & 1 & 0\\\\\n",
    "    1 & 0 & 0\n",
    "    \\end{bmatrix}\n",
    "    \\begin{bmatrix}\n",
    "    1 & -2 & 3\\\\\n",
    "    -4 & 5 & -6\\\\\n",
    "    7 & -8 & 9\n",
    "    \\end{bmatrix} =\n",
    "    \\begin{bmatrix}\n",
    "    7 & -8 & 9\\\\\n",
    "    0 & 0.4286 & -0.8571\\\\\n",
    "    0 & -0.8571 & 1.7143\n",
    "    \\end{bmatrix}\n",
    "\\end{equation}\n",
    "\n",
    "The elementary matrices can be found with the function \"zeroOutColumn(n,col,Q)\" found below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "E_1:\n",
      " [[ 1.      0.      0.    ]\n",
      " [ 0.5714  1.      0.    ]\n",
      " [-0.1429  0.      1.    ]]\n",
      "E_1@P_13@A:\n",
      " [[ 7.     -8.      9.    ]\n",
      " [-0.      0.4286 -0.8571]\n",
      " [ 0.     -0.8571  1.7143]]\n"
     ]
    }
   ],
   "source": [
    "def zeroOutColumn(n,col,Q):\n",
    "    E = np.identity(n)          # start out with an identity matrix\n",
    "    divisor = -1*Q[col][col]    # divisor is the first element in the matrix\n",
    "    size = len(Q[col:,col:])    \n",
    "    for i in range(size-1):\n",
    "        # E[col:,col:] is a square submatrix of E\n",
    "        # Q[col:,col:] is a square submatrix of the input matrix Q\n",
    "        # Go through the first column and divide all elements after the first \n",
    "        #  by the divisor\n",
    "        E[col:,col:][i+1][0] = Q[col:,col:][i+1][0]/divisor\n",
    "    return E\n",
    "\n",
    "P_13 = permutationMatrix(3,0,A)\n",
    "E_1 = zeroOutColumn(3,0,P_13 @ A)\n",
    "res_1 = E_1 @ P_13 @ A\n",
    "print('E_1:\\n',np.round(E_1,4))\n",
    "print('E_1@P_13@A:\\n',np.round(res_1,4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Utilizing the above code, I chose to solve for the remaining permutation and elementary matrices by looking at submatrices of $\\textbf{A}$.\n",
    "Now that the first column contains a pivot, we can focus on the second column by looking at the submatrix starting at $\\textbf{E}_1\\textbf{P}_{1,3}\\textbf{A}[2,2]$:\n",
    "\\begin{equation}\n",
    "    \\textbf{E}_1\\textbf{P}_{1,3}\\textbf{A}_{[2,2]}=\n",
    "    \\begin{bmatrix}\n",
    "    0.4286 & -0.8571\\\\\n",
    "    -0.8571 & 1.7143\n",
    "    \\end{bmatrix}\n",
    "\\end{equation}\n",
    "and then computing the permutation and elementary matrix in the same manner as $\\textbf{P}_{1,3}$ and $\\textbf{E}_1$. The remaining permutation and elementary matrices will remain $m x m$, not the size of the submatrix. The result should be:\n",
    "\\begin{equation}\n",
    "    \\textbf{E}_2\\textbf{P}_{2,3}\\textbf{E}_1\\textbf{P}_{1,3}\\textbf{A} =\n",
    "    \\begin{bmatrix}\n",
    "        7 & -8 & 9\\\\\n",
    "        0 & -0.8571 & 1.7143\\\\\n",
    "        0 & 0 & 0\n",
    "    \\end{bmatrix} = \\textbf{U}\n",
    "\\end{equation}\n",
    "\n",
    "$\\textbf{L}$ can be computed with an intermediate step by first computing:\n",
    "\\begin{equation}\n",
    "    \\textbf{V} = \\textbf{P}_{1,3}\\textbf{E}^{-1}_1\\textbf{P}_{2,3}\\textbf{E}^{-1}_{2,3}\n",
    "\\end{equation}\n",
    "\\begin{equation}\n",
    "    \\textbf{P}_{2,3}\\textbf{P}_{1,3}\\textbf{V} = \n",
    "    \\begin{bmatrix}\n",
    "        1 & 0 & 0\\\\\n",
    "        0.1429 & 1 & 0\\\\\n",
    "        -0.5714 & -0.5 & 1\n",
    "    \\end{bmatrix} = \\textbf{L}\n",
    "\\end{equation}\n",
    "\n",
    "Finally, $\\textbf{P}$ can be computed as:\n",
    "\\begin{equation}\n",
    "    \\textbf{P}_{2,3}\\textbf{P}_{1,3} =\n",
    "    \\begin{bmatrix}\n",
    "        0 & 0 & 1\\\\\n",
    "        1 & 0 & 0\\\\\n",
    "        0 & 1 & 0\n",
    "    \\end{bmatrix} = \\textbf{P}\n",
    "\\end{equation}\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Homebrew LU Factorization Code\n",
    "We now have all the components necessary to solve an equation of the form $\\textbf{Ax} = \\textbf{b}$ using LU factorization. To put all the code together and create our own LU Factorization: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "myP:\n",
      " [[0. 0. 1.]\n",
      " [1. 0. 0.]\n",
      " [0. 1. 0.]]\n",
      "myL:\n",
      " [[ 1.      0.      0.    ]\n",
      " [ 0.1429  1.      0.    ]\n",
      " [-0.5714 -0.5     1.    ]]\n",
      "myU:\n",
      " [[ 7.     -8.      9.    ]\n",
      " [ 0.     -0.8571  1.7143]\n",
      " [-0.      0.      0.    ]]\n"
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "Created on Tue Oct 27 10:28:34 2020\n",
    "\n",
    "@author: sma\n",
    "\n",
    "LU Factorization \n",
    "\"\"\"\n",
    "import numpy as np\n",
    "\n",
    "A = np.array([[1, -2, 3],\n",
    "              [-4, 5, -6],\n",
    "              [7, -8, 9]])\n",
    "\n",
    "def permutationMatrix(n,col,Q): # n is number of rows and cols, Q is a matrix\n",
    "    # look down first column, find the largest value in magnitude\n",
    "    # create a permutation matrix with ones and zeros \n",
    "    P = np.identity(n)\n",
    "    max_index_in_col = np.argmax((np.abs(Q[col:,col:][:,0])))\n",
    "    # flip the col column with the max column\n",
    "    P[:,[col, max_index_in_col+col]] = P[:,[max_index_in_col+col, col]]\n",
    "    return P\n",
    "\n",
    "def zeroOutColumn(n,col,Q):\n",
    "    E = np.identity(n)          # start out with an identity matrix\n",
    "    divisor = -1*Q[col][col]    # divisor is the first element in the matrix\n",
    "    size = len(Q[col:,col:])    \n",
    "    for i in range(size-1):\n",
    "        # E[col:,col:] is a square submatrix of E\n",
    "        # Q[col:,col:] is a square submatrix of the input matrix Q\n",
    "        # Go through the first column and divide all elements after the first \n",
    "        #  by the divisor\n",
    "        E[col:,col:][i+1][0] = Q[col:,col:][i+1][0]/divisor\n",
    "    return E\n",
    "\n",
    "\n",
    "def myLUFactorization(A):\n",
    "    n = len(A) # all matrices for LU must be n x n\n",
    "    P = []\n",
    "    E = []\n",
    "    U = np.zeros((n,n))\n",
    "    \n",
    "    for i in range(n-1):\n",
    "        P.append(permutationMatrix(n,i,A))      # Save the permutation matrices\n",
    "        E.append(zeroOutColumn(n,i,P[i] @ A))   # Save the zeroing matrices \n",
    "        U = E[i] @ P[i] @ A \n",
    "        A = U\n",
    "      \n",
    "    V_prev = P[0]@np.linalg.inv(E[0])\n",
    "    V = np.zeros((n,n))\n",
    "    \n",
    "    for j in range(len(P)-1): \n",
    "        V = V_prev @ P[j+1] @ np.linalg.inv(E[j+1]) \n",
    "        V_prev = V\n",
    "    \n",
    "    permutation_prev = P[0]\n",
    "    for k in range(len(P)-1): #counting down\n",
    "        permutation = P[k+1] @ permutation_prev \n",
    "        permutation_prev = permutation\n",
    "\n",
    "    L = permutation @ V\n",
    "\n",
    "    return permutation, L, U #P,L,U\n",
    "\n",
    "myP, myL, myU = myLUFactorization(A)\n",
    "print('myP:\\n',np.round(myP,4))\n",
    "print('myL:\\n',np.round(myL,4))\n",
    "print('myU:\\n',np.round(myU,4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simple Numerical Examples\n",
    "\n",
    "We should first check that $\\textbf{PA} = \\textbf{LU}$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 7. -8.  9.]\n",
      " [ 1. -2.  3.]\n",
      " [-4.  5. -6.]]\n",
      "\n",
      "\n",
      "[[ 7. -8.  9.]\n",
      " [ 1. -2.  3.]\n",
      " [-4.  5. -6.]]\n"
     ]
    }
   ],
   "source": [
    "print(myP@A,)\n",
    "print('\\n')\n",
    "print(myL@myU)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Success! We can now solve an equation in the form $\\textbf{A}\\vec{x}=\\vec{b}$. Suppose\n",
    "\\begin{equation}\n",
    "\\vec{b} = \n",
    "\\begin{bmatrix}\n",
    "    10\\\\\n",
    "    11\\\\\n",
    "    12\n",
    "\\end{bmatrix}\n",
    "\\end{equation}\n",
    "\n",
    "We then write\n",
    "\\begin{equation}\n",
    "    \\textbf{A}\\vec{x}=\\vec{b}\n",
    "\\end{equation}\n",
    "as \n",
    "\\begin{equation}\n",
    "    \\textbf{LU}\\vec{x} = \\textbf{P}\\vec{b}\n",
    "\\end{equation}\n",
    "which we can then let $\\textbf{U}\\vec{x} = \\vec{y}$, which leads to the system\n",
    "\\begin{equation}\n",
    "    \\textbf{L}\\vec{y} = \\textbf{P}\\vec{b} = \\vec{c}\n",
    "\\end{equation}\n",
    "\n",
    "Let's start with $\\textbf{L}\\vec{y} = \\textbf{P}\\vec{b}$ by solving for $\\vec{y}$ with \n",
    "\\begin{equation}\n",
    "\\vec{y}=\\textbf{L}^{-1}\\textbf{P}\\vec{b}\n",
    "\\end{equation}\n",
    "Which is easy to solve numerically because $\\textbf{L}$ is lower triangular "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[3.        ]\n",
      " [0.57142857]\n",
      " [4.        ]]\n"
     ]
    }
   ],
   "source": [
    "import scipy.linalg\n",
    "b = np.array([[1],\n",
    "             [2],\n",
    "             [3]])\n",
    "y = np.linalg.pinv(myL) @ myP @ b \n",
    "print(y)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can solve $\\textbf{U}\\vec{x}=\\vec{y}$ for $\\vec{x}$ numerically by using \n",
    "\\begin{equation}\n",
    "\\vec{x}=\\textbf{U}^{-1}\\vec{y}\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x =\n",
      " [[-0.05555556]\n",
      " [-0.11111111]\n",
      " [ 0.27777778]]\n"
     ]
    }
   ],
   "source": [
    "x = np.linalg.pinv(myU) @ y\n",
    "print('x =\\n',x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## An Engineering Application\n",
    "\n",
    "Suppose you are sending data, in this case an image, but it has been encrypted or scrambled in some way. Through other techniques, you have determined the matrix that can help unscramble the image, given in the form $A\\mathbf{x}=\\mathbf{b}$. However, this matrix applies only to a 50x50 grid of pixels at a time (i.e. $\\mathbf{b}$ is the 50x50 matrix of pixel values reshaped into a single vector of length 2500). This means that the matrix $A$ is 2500x2500 and an explicit inverse could be costly. Instead, lets do the LU factorization and use forward and backward substitution to resolve the image. The code below loads in the mixed data and the determined filter, computes the LU factorization, then resolves each 50x50 grid of pixels for each color. Finally, the image is converted to the right data type and displayed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Import libraries necessary to run the code\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import scipy.linalg as alg\n",
    "import scipy.io as sio\n",
    "\n",
    "# Plot the images inline\n",
    "%matplotlib inline\n",
    "\n",
    "# Load the data. Comes with an A matrix and a matrix mx with size (300,150,3) representing rgb values. This is the scrambled image\n",
    "data = sio.loadmat('mixed_img_andFilter.mat')\n",
    "A = data['A']\n",
    "mx = data['mx']\n",
    "\n",
    "# Plot the scrambled image\n",
    "fig1 = plt.imshow(mx)\n",
    "plt.show()\n",
    "\n",
    "# Compute the LU factorization. the scipy.linalg library computes it as A = P*L*U as opposed to Matlab's A = P'*L*U\n",
    "P,L,U = alg.lu(A)\n",
    "# Transpose the permutation matrix P for easier readability later\n",
    "Pt = np.transpose(P)\n",
    "\n",
    "# Loop through the scambled image doing 50x50 grids at a time \n",
    "for i in range(3):\n",
    "    for j in range(0,251,50):\n",
    "        for k in range(0,101,50):\n",
    "            # Extract the current data\n",
    "            temp = mx[j:j+50,k:k+50,i]\n",
    "            tt = np.transpose(temp)\n",
    "            # Reshape the matrix into a vector\n",
    "            b = np.reshape(tt,2500)\n",
    "            Pb = np.dot(Pt,b)\n",
    "            # Solve the first triangular system (Ly = Pb)\n",
    "            y = alg.solve_triangular(L,Pb,lower=True)\n",
    "            # Solve the second triangular system (Ux = y)\n",
    "            x = alg.solve_triangular(U,y,lower = False)\n",
    "            # Reshape the output to be a 50x50 matrix again\n",
    "            mx[j:j+50,k:k+50,i] = np.transpose(np.reshape(x,(50,50)))\n",
    "\n",
    "# Convert the matrix back into unsigned integers for image plotting\n",
    "final = np.uintc(mx)\n",
    "\n",
    "# Show the final image. Merry Christmas!\n",
    "fig2 = plt.imshow(final)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Challenge Problem\n",
    "\n",
    "Add a homework assignment that might take 10 minutes to complete.  Make sure you can work the problem yourself, but you do not need to submit a solution to the problem."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}