{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook was prepared by [Donne Martin](http://donnemartin.com). Source and license info is on [GitHub](https://bit.ly/code-notes)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Problem: Implement selection sort.\n", "\n", "* [Constraints and Assumptions](#Constraints-and-Assumptions)\n", "* [Test Cases](#Test-Cases)\n", "* [Algorithm](#Algorithm)\n", "* [Code](#Code)\n", "* [Unit Test](#Unit-Test)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Constraints and Assumptions\n", "\n", "*Problem statements are often intentionally ambiguous. Identifying constraints and stating assumptions can help to ensure you code the intended solution.*\n", "\n", "* Are you looking for a naiive solution (ie not stable, not based on a heap)?\n", " * Yes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Test Cases\n", "\n", "* Empty input\n", "* One element\n", "* Two or more elements" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Algorithm\n", "\n", "Wikipedia's animation:\n", "![alt text](http://upload.wikimedia.org/wikipedia/commons/9/94/Selection-Sort-Animation.gif)\n", "\n", "We can do this recursively or iteratively. Iteratively will be more efficient as it doesn't require the extra space overhead with the recursive calls.\n", "\n", "* For each element\n", " * Check every element to the right to find the min\n", " * If min < current element, swap\n", "\n", "Complexity:\n", "* Time: O(n^2) average, worst, best\n", "* Space: O(1) iterative, O(n) recursive (unless tail-call elimination is available, then O(1)), generally not stable" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Code" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def find_min_index(data, start):\n", " min_index = start\n", " for i in xrange(start + 1, len(data)):\n", " if data[i] < data[min_index]:\n", " min_index = i\n", " return min_index\n", "\n", "def swap(data, i, j):\n", " if (i != j):\n", " data[i], data[j] = data[j], data[i]" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ "def selection_sort_recursive(data, start=0):\n", " if start < len(data) - 1:\n", " swap(data, start, find_min_index(data, start))\n", " selection_sort_recursive(data, start+1)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [], "source": [ "def selection_sort_iterative(data):\n", " if len(data) == 0 or len(data) == 1:\n", " return\n", " for i in xrange(0, len(data) - 1):\n", " swap(data, i, find_min_index(data, i))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Unit Test\n", "\n", "*It is important to identify and run through general and edge cases from the [Test Cases](#Test-Cases) section by hand. You generally will not be asked to write a unit test like what is shown below.*" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Empty input\n", "One element\n", "Two or more elements\n", "Success: test_selection_sort\n", "\n", "Empty input\n", "One element\n", "Two or more elements\n", "Success: test_selection_sort\n", "\n" ] } ], "source": [ "from nose.tools import assert_equal\n", "\n", "class Test(object):\n", " def test_selection_sort(self, func):\n", " print('Empty input')\n", " data = []\n", " func(data)\n", " assert_equal(data, [])\n", "\n", " print('One element')\n", " data = [5]\n", " func(data)\n", " assert_equal(data, [5])\n", "\n", " print('Two or more elements')\n", " data = [5, 1, 7, 2, 6, -3, 5, 7, -1]\n", " func(data)\n", " assert_equal(data, sorted(data))\n", " \n", " print('Success: test_selection_sort\\n')\n", "\n", "if __name__ == '__main__':\n", " test = Test()\n", " test.test_selection_sort(selection_sort_recursive)\n", " test.test_selection_sort(selection_sort_iterative)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.10" } }, "nbformat": 4, "nbformat_minor": 0 }