{ "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 stock prices on each consecutive day, determine the max profits with k transactions.\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", "* Is k the number of sell transactions?\n", " * Yes\n", "* Can we assume the prices input is an array of ints?\n", " * Yes\n", "* Can we assume the inputs are valid?\n", " * No\n", "* If the prices are all decreasing and there is no opportunity to make a profit, do we just return 0?\n", " * Yes\n", "* Should the output be the max profit and days to buy and sell?\n", " * Yes\n", "* Can we assume this fits memory?\n", " * Yes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Test Cases\n", "\n", "
\n", "* Prices: None or k: None -> None\n", "* Prices: [] or k <= 0 -> []\n", "* Prices: [0, -1, -2, -3, -4, -5]\n", " * (max profit, list of transactions)\n", " * (0, [])\n", "* Prices: [2, 5, 7, 1, 4, 3, 1, 3] k: 3\n", " * (max profit, list of transactions)\n", " * (10, [Type.SELL day: 7 price: 3, \n", " Type.BUY day: 6 price: 1, \n", " Type.SELL day: 4 price: 4, \n", " Type.BUY day: 3 price: 1, \n", " Type.SELL day: 2 price: 7, \n", " Type.BUY day: 0 price: 2])\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Algorithm\n", "\n", "We'll use bottom up dynamic programming to build a table.\n", "\n", "
\n", "\n", "The rows (i) represent the prices.\n", "The columns (j) represent the number of transactions (k).\n", "\n", "T[i][j] = max(T[i][j - 1],\n", " prices[j] - price[m] + T[i - 1][m])\n", "\n", "m = 0...j-1\n", "\n", " 0 1 2 3 4 5 6 7\n", "--------------------------------------\n", "| | 2 | 5 | 7 | 1 | 4 | 3 | 1 | 3 |\n", "--------------------------------------\n", "| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n", "| 1 | 0 | 3 | 5 | 5 | 5 | 5 | 5 | 5 |\n", "| 2 | 0 | 3 | 5 | 5 | 8 | 8 | 8 | 8 |\n", "| 3 | 0 | 3 | 5 | 5 | 8 | 8 | 8 | 10 |\n", "--------------------------------------\n", "\n", "Optimization:\n", "\n", "max_diff = max(max_diff,\n", " T[i - 1][j - 1] - prices[j - 1])\n", "\n", "T[i][j] = max(T[i][j - 1],\n", " prices[j] + max_diff)\n", "\n", "\n", "\n", "Complexity:\n", "* Time: O(n * k)\n", "* Space: O(n * k)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Code" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from enum import Enum # Python 2 users: Run pip install enum34\n", "\n", "\n", "class Type(Enum):\n", " SELL = 0\n", " BUY = 1\n", "\n", "\n", "class Transaction(object):\n", "\n", " def __init__(self, type, day, price):\n", " self.type = type\n", " self.day = day\n", " self.price = price\n", "\n", " def __eq__(self, other):\n", " return self.type == other.type and \\\n", " self.day == other.day and \\\n", " self.price == other.price\n", "\n", " def __repr__(self):\n", " return str(self.type) + ' day: ' + \\\n", " str(self.day) + ' price: ' + \\\n", " str(self.price)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import sys\n", "\n", "\n", "class StockTrader(object):\n", "\n", " def find_max_profit(self, prices, k):\n", " if prices is None or k is None:\n", " raise TypeError('prices or k cannot be None')\n", " if not prices or k <= 0:\n", " return []\n", " num_rows = k + 1 # 0th transaction for dp table\n", " num_cols = len(prices)\n", " T = [[None] * num_cols for _ in range(num_rows)]\n", " for i in range(num_rows):\n", " for j in range(num_cols):\n", " if i == 0 or j == 0:\n", " T[i][j] = 0\n", " continue\n", " max_profit = -sys.maxsize\n", " for m in range(j):\n", " profit = prices[j] - prices[m] + T[i - 1][m]\n", " if profit > max_profit:\n", " max_profit = profit\n", " T[i][j] = max(T[i][j - 1], max_profit)\n", " return self._find_max_profit_transactions(T, prices)\n", "\n", " def find_max_profit_optimized(self, prices, k):\n", " if prices is None or k is None:\n", " raise TypeError('prices or k cannot be None')\n", " if not prices or k <= 0:\n", " return []\n", " num_rows = k + 1\n", " num_cols = len(prices)\n", " T = [[None] * num_cols for _ in range(num_rows)]\n", " for i in range(num_rows):\n", " max_diff = prices[0] * -1\n", " for j in range(num_cols):\n", " if i == 0 or j == 0:\n", " T[i][j] = 0\n", " continue\n", " max_diff = max(\n", " max_diff,\n", " T[i - 1][j - 1] - prices[j - 1])\n", " T[i][j] = max(\n", " T[i][j - 1],\n", " prices[j] + max_diff)\n", " return self._find_max_profit_transactions(T, prices)\n", "\n", " def _find_max_profit_transactions(self, T, prices):\n", " results = []\n", " i = len(T) - 1\n", " j = len(T[0]) - 1\n", " max_profit = T[i][j]\n", " while i != 0 and j != 0:\n", " if T[i][j] == T[i][j - 1]:\n", " j -= 1\n", " else:\n", " sell_price = prices[j]\n", " results.append(Transaction(Type.SELL, j, sell_price))\n", " profit = T[i][j] - T[i - 1][j - 1]\n", " i -= 1\n", " j -= 1\n", " for m in range(j + 1)[::-1]:\n", " if sell_price - prices[m] == profit:\n", " results.append(Transaction(Type.BUY, m, prices[m]))\n", " break\n", " return (max_profit, results)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Unit Test" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Overwriting test_max_profit.py\n" ] } ], "source": [ "%%writefile test_max_profit.py\n", "from nose.tools import assert_equal\n", "from nose.tools import assert_raises\n", "from nose.tools import assert_true\n", "\n", "\n", "class TestMaxProfit(object):\n", "\n", " def test_max_profit(self):\n", " stock_trader = StockTrader()\n", " assert_raises(TypeError, stock_trader.find_max_profit, None, None)\n", " assert_equal(stock_trader.find_max_profit(prices=[], k=0), [])\n", " prices = [5, 4, 3, 2, 1]\n", " k = 3\n", " assert_equal(stock_trader.find_max_profit(prices, k), (0, []))\n", " prices = [2, 5, 7, 1, 4, 3, 1, 3]\n", " profit, transactions = stock_trader.find_max_profit(prices, k)\n", " assert_equal(profit, 10)\n", " assert_true(Transaction(Type.SELL,\n", " day=7,\n", " price=3) in transactions)\n", " assert_true(Transaction(Type.BUY,\n", " day=6,\n", " price=1) in transactions)\n", " assert_true(Transaction(Type.SELL,\n", " day=4,\n", " price=4) in transactions)\n", " assert_true(Transaction(Type.BUY,\n", " day=3,\n", " price=1) in transactions)\n", " assert_true(Transaction(Type.SELL,\n", " day=2,\n", " price=7) in transactions)\n", " assert_true(Transaction(Type.BUY,\n", " day=0,\n", " price=2) in transactions)\n", " print('Success: test_max_profit')\n", "\n", "\n", "def main():\n", " test = TestMaxProfit()\n", " test.test_max_profit()\n", "\n", "\n", "if __name__ == '__main__':\n", " main()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Success: test_max_profit\n" ] } ], "source": [ "%run -i test_max_profit.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": "3.4.3" } }, "nbformat": 4, "nbformat_minor": 0 }