{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook was prepared by [Donne Martin](https://github.com/donnemartin). Source and license info is on [GitHub](https://github.com/donnemartin/interactive-coding-challenges)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Solution Notebook" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Problem: Given a list of 2x2 matrices, minimize the cost of matrix multiplication.\n", "\n", "* [Constraints](#Constraints)\n", "* [Test Cases](#Test-Cases)\n", "* [Algorithm](#Algorithm)\n", "* [Code](#Code)\n", "* [Unit Test](#Unit-Test)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Constraints\n", "\n", "* Do we just want to calculate the cost and not list the actual order of operations?\n", " * Yes\n", "* Can we assume the inputs are valid?\n", " * No\n", "* Can we assume this fits memory?\n", " * Yes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Test Cases\n", "\n", "* None -> Exception\n", "* [] -> 0\n", "* [Matrix(2, 3), Matrix(3, 6), Matrix(6, 4), Matrix(4, 5)] -> 124" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Algorithm\n", "\n", "We'll use bottom up dynamic programming to build a table.\n", "\n", "
\n",
    "\n",
    "  0    1    2    3\n",
    "[2,3][3,6][6,4][4,5]\n",
    "\n",
    "Case: 0 * 1\n",
    "2 * 3 * 6 = 36\n",
    "\n",
    "Case: 1 * 2\n",
    "3 * 6 * 4 = 72\n",
    "\n",
    "Case: 2 * 3\n",
    "6 * 4 * 5 = 120\n",
    "\n",
    "Case: 0 * 1 * 2\n",
    "0 * (1 * 2) = 2 * 3 * 4 + 72 = 96\n",
    "(0 * 1) * 2 = 36 + 2 * 6 * 4 = 84\n",
    "min: 84\n",
    "\n",
    "Case: 1 * 2 * 3\n",
    "1 * (2 * 3) = 3 * 6 * 5 + 120 = 210\n",
    "(1 * 2) * 3 = 72 + 3 * 4 * 5 = 132\n",
    "min: 132\n",
    "\n",
    "Case: 0 * 1 * 2 * 3\n",
    "0 * (1 * 2 * 3) = 2 * 3 * 5 + 132 = 162\n",
    "(0 * 1) * (2 * 3) = 36 + 120 + 2 * 6 * 5 = 216\n",
    "(0 * 1 * 2) * 3 = 84 + 2 * 4 * 5 = 124\n",
    "min: 124\n",
    "\n",
    "  ---------------------\n",
    "  | 0 |  1 |  2 |   3 |\n",
    "  ---------------------\n",
    "0 | 0 | 36 | 84 | 124 |\n",
    "1 | x |  0 | 72 | 132 |\n",
    "2 | x |  x |  0 | 120 |\n",
    "3 | x |  x |  x |   0 |\n",
    "  ---------------------\n",
    "\n",
    "min cost = T[0][cols-1] = 124\n",
    "\n",
    "for k in range(i, j):\n",
    "    T[i][j] = minimum of (T[i][k] + T[k+1][j] +\n",
    "                          m[i].first * m[k].second * m[j].second) for all k\n",
    "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Explanation of k" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n",
    "  0    1    2    3\n",
    "[2,3][3,6][6,4][4,5]\n",
    "\n",
    "Fill in the missing cell, where i = 0, j = 3\n",
    "\n",
    "  ---------------------\n",
    "  | 0 |  1 |  2 |   3 |\n",
    "  ---------------------\n",
    "0 | 0 | 36 | 84 | ??? |\n",
    "1 | x |  0 | 72 | 132 |\n",
    "2 | x |  x |  0 | 120 |\n",
    "3 | x |  x |  x |   0 |\n",
    "  ---------------------\n",
    "\n",
    "Case: 0 * (1 * 2 * 3), k = 0\n",
    "i = 0, j = 3\n",
    "\n",
    "0 * (1 * 2 * 3) = 2 * 3 * 5 + 132 = 162\n",
    "T[i][k] + T[k+1][j] + m[i].first * m[k].second * m[j].second\n",
    "T[0][0] + T[1][3] + 2 * 3 * 5\n",
    "0 + 132 + 30 = 162\n",
    "\n",
    "Case: (0 * 1) * (2 * 3), k = 1\n",
    "i = 0, j = 3\n",
    "\n",
    "(0 * 1) * (2 * 3) = 36 + 120 + 2 * 6 * 5 = 216\n",
    "T[i][k] + T[k+1][j] + m[i].first * m[k].second * m[j].second\n",
    "T[0][1] + T[2][3] + 2 * 6 * 5\n",
    "36 + 120 + 60 = 216\n",
    "\n",
    "Case: (0 * 1 * 2) * 3, k = 2\n",
    "i = 0, j = 3\n",
    "\n",
    "(0 * 1 * 2) * 3 = 84 + 2 * 4 * 5 = 124\n",
    "T[i][k] + T[k+1][j] + m[i].first * m[k].second * m[j].second\n",
    "T[0][2] + T[3][3] + 2 * 4 * 5\n",
    "84 + 0 + 40 = 124\n",
    "\n",
    "
\n", "\n", "Complexity:\n", "* Time: O(n^3)\n", "* Space: O(n^2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Code" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "class Matrix(object):\n", "\n", " def __init__(self, first, second):\n", " self.first = first\n", " self.second = second" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import sys\n", "\n", "\n", "class MatrixMultiplicationCost(object):\n", "\n", " def find_min_cost(self, matrices):\n", " if matrices is None:\n", " raise TypeError('matrices cannot be None')\n", " if not matrices:\n", " return 0\n", " size = len(matrices)\n", " T = [[0] * size for _ in range(size)]\n", " for offset in range(1, size):\n", " for i in range(size-offset):\n", " j = i + offset\n", " min_cost = sys.maxsize\n", " for k in range(i, j):\n", " cost = (T[i][k] + T[k+1][j] +\n", " matrices[i].first *\n", " matrices[k].second *\n", " matrices[j].second)\n", " if cost < min_cost:\n", " min_cost = cost\n", " T[i][j] = min_cost\n", " return T[0][size-1]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Unit Test" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Overwriting test_find_min_cost.py\n" ] } ], "source": [ "%%writefile test_find_min_cost.py\n", "import unittest\n", "\n", "\n", "class TestMatrixMultiplicationCost(unittest.TestCase):\n", "\n", " def test_find_min_cost(self):\n", " matrix_mult_cost = MatrixMultiplicationCost()\n", " self.assertRaises(TypeError, matrix_mult_cost.find_min_cost, None)\n", " self.assertEqual(matrix_mult_cost.find_min_cost([]), 0)\n", " matrices = [Matrix(2, 3),\n", " Matrix(3, 6),\n", " Matrix(6, 4),\n", " Matrix(4, 5)]\n", " expected_cost = 124\n", " self.assertEqual(matrix_mult_cost.find_min_cost(matrices), expected_cost)\n", " print('Success: test_find_min_cost')\n", "\n", "\n", "def main():\n", " test = TestMatrixMultiplicationCost()\n", " test.test_find_min_cost()\n", "\n", "\n", "if __name__ == '__main__':\n", " main()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Success: test_find_min_cost\n" ] } ], "source": [ "%run -i test_find_min_cost.py" ] } ], "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": "3.7.2" } }, "nbformat": 4, "nbformat_minor": 1 }