{ "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: Search a sorted matrix for an item.\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", "* Are items in each row sorted?\n", " * Yes\n", "* Are items in each column sorted?\n", " * Yes\n", "* Is the sorting in ascending or descending order?\n", " * Ascending\n", "* Is the matrix a rectangle? Not jagged?\n", " * Yes\n", "* Is the matrix square?\n", " * Not necessarily\n", "* Is the output a tuple (row, col)?\n", " * Yes\n", "* Is the item you are searching for always in the matrix?\n", " * No\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", "* General case\n", " * Item found -> (row, col)\n", " * Item not found -> None" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Algorithm\n", "\n", "
\n",
    "\n",
    "Find 60 (val = 60)\n",
    "\n",
    " 20  40  63   80\n",
    " 30  50  80   90\n",
    " 40  60  100 110\n",
    " 50  65  105 150\n",
    "\n",
    "* If the start of a col > val, look left\n",
    "* If the end of a col < val, look right\n",
    "* If the start of row > val, look up\n",
    "* If the end of a row < val, look down\n",
    "\n",
    "If we start at the upper right corner, we just need to use these cases:\n",
    "\n",
    "* If the start of a col > val, look left\n",
    "* If the end of a row < val, look down\n",
    "\n",
    "
\n", "\n", "Complexity:\n", "* Time: O(n + m), where n and m are the matrix dimensions\n", "* Space: O(1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Code" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "class SortedMatrix(object):\n", "\n", " def find_val(self, matrix, val):\n", " if matrix is None or val is None:\n", " raise TypeError('matrix and val cannot be None')\n", " row = 0\n", " col = len(matrix[0]) - 1\n", " while row < len(matrix) and col >= 0:\n", " if matrix[row][col] == val:\n", " return (row, col)\n", " elif matrix[row][col] > val:\n", " col -= 1\n", " else:\n", " row += 1\n", " return None" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Unit Test" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Overwriting test_search_sorted_matrix.py\n" ] } ], "source": [ "%%writefile test_search_sorted_matrix.py\n", "import unittest\n", "\n", "\n", "class TestSortedMatrix(unittest.TestCase):\n", "\n", " def test_find_val(self):\n", " matrix = [[20, 40, 63, 80],\n", " [30, 50, 80, 90],\n", " [40, 60, 110, 110],\n", " [50, 65, 105, 150]]\n", " sorted_matrix = SortedMatrix()\n", " self.assertRaises(TypeError, sorted_matrix.find_val, None, None)\n", " self.assertEqual(sorted_matrix.find_val(matrix, 1000), None)\n", " self.assertEqual(sorted_matrix.find_val(matrix, 60), (2, 1))\n", " print('Success: test_find_val')\n", "\n", "\n", "def main():\n", " test = TestSortedMatrix()\n", " test.test_find_val()\n", "\n", "\n", "if __name__ == '__main__':\n", " main()" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Success: test_find_val\n" ] } ], "source": [ "%run -i test_search_sorted_matrix.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 }