{ "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: Create a class with an insert method to insert an int to a list. It should also support calculating the max, min, mean, and mode in O(1).\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", "* Can we assume the inputs are valid?\n", " * No\n", "* Is there a range of inputs?\n", " * 0 <= item <= 100\n", "* Should mean return a float?\n", " * Yes\n", "* Should the other results return an int?\n", " * Yes\n", "* If there are multiple modes, what do we return?\n", " * Any of the modes\n", "* Can we assume this fits memory?\n", " * Yes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Test Cases\n", "\n", "* None -> TypeError\n", "* [] -> ValueError\n", "* [5, 2, 7, 9, 9, 2, 9, 4, 3, 3, 2]\n", " * max: 9\n", " * min: 2\n", " * mean: 55\n", " * mode: 9 or 2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Algorithm\n", "\n", "Return the input, val\n", "\n", "Complexity:\n", "* Time: O(1)\n", "* Space: O(1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Code" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from __future__ import division\n", "\n", "\n", "class Solution(object):\n", "\n", " def __init__(self, upper_limit=100):\n", " self.max = None\n", " self.min = None\n", " # Mean\n", " self.num_items = 0\n", " self.running_sum = 0\n", " self.mean = None\n", " # Mode\n", " self.array = [0] * (upper_limit+1)\n", " self.mode_ocurrences = 0\n", " self.mode = None\n", "\n", " def insert(self, val):\n", " if val is None:\n", " raise TypeError('val cannot be None')\n", " if self.max is None or val > self.max:\n", " self.max = val\n", " if self.min is None or val < self.min:\n", " self.min = val\n", " # Calculate the mean\n", " self.num_items += 1\n", " self.running_sum += val\n", " self.mean = self.running_sum / self.num_items\n", " # Calculate the mode\n", " self.array[val] += 1\n", " if self.array[val] > self.mode_ocurrences:\n", " self.mode_ocurrences = self.array[val]\n", " self.mode = val" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Unit Test" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Overwriting test_math_ops.py\n" ] } ], "source": [ "%%writefile test_math_ops.py\n", "import unittest\n", "\n", "\n", "class TestMathOps(unittest.TestCase):\n", "\n", " def test_math_ops(self):\n", " solution = Solution()\n", " self.assertRaises(TypeError, solution.insert, None)\n", " solution.insert(5)\n", " solution.insert(2)\n", " solution.insert(7)\n", " solution.insert(9)\n", " solution.insert(9)\n", " solution.insert(2)\n", " solution.insert(9)\n", " solution.insert(4)\n", " solution.insert(3)\n", " solution.insert(3)\n", " solution.insert(2)\n", " self.assertEqual(solution.max, 9)\n", " self.assertEqual(solution.min, 2)\n", " self.assertEqual(solution.mean, 5)\n", " self.assertTrue(solution.mode in (2, 9))\n", " print('Success: test_math_ops')\n", "\n", "\n", "def main():\n", " test = TestMathOps()\n", " test.test_math_ops()\n", "\n", "\n", "if __name__ == '__main__':\n", " main()" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Success: test_math_ops\n" ] } ], "source": [ "%run -i test_math_ops.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 }