{ "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": [ "# Challenge Notebook" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Problem: Find the lowest common ancestor in a binary tree.\n", "\n", "* [Constraints](#Constraints)\n", "* [Test Cases](#Test-Cases)\n", "* [Algorithm](#Algorithm)\n", "* [Code](#Code)\n", "* [Unit Test](#Unit-Test)\n", "* [Solution Notebook](#Solution-Notebook)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Constraints\n", "\n", "* Is this a binary search tree?\n", " * No\n", "* Can we assume the two nodes are in the tree?\n", " * No\n", "* Can we assume this fits memory?\n", " * Yes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Test Cases\n", "\n", "
\n", " _10_\n", " / \\\n", " 5 9\n", " / \\ / \\\n", " 12 3 18 20\n", " / \\ /\n", " 1 8 40\n", "\n", "\n", "* 0, 5 -> None\n", "* 5, 0 -> None\n", "* 1, 8 -> 3\n", "* 12, 8 -> 5\n", "* 12, 40 -> 10\n", "* 9, 20 -> 9\n", "* 3, 5 -> 5" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Algorithm\n", "\n", "Refer to the [Solution Notebook](http://nbviewer.jupyter.org/github/donnemartin/interactive-coding-challenges/blob/master/graphs_trees/tree_lca/tree_lca_solution.ipynb). If you are stuck and need a hint, the solution notebook's algorithm discussion might be a good place to start." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Code" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "class Node(object):\n", "\n", " def __init__(self, key, left=None, right=None):\n", " self.key = key\n", " self.left = left\n", " self.right = right\n", "\n", " def __repr__(self):\n", " return str(self.key)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "class BinaryTree(object):\n", "\n", " def lca(self, root, node1, node2):\n", " # TODO: Implement me\n", " pass" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Unit Test" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**The following unit test is expected to fail until you solve the challenge.**" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# %load test_lca.py\n", "from nose.tools import assert_equal\n", "\n", "\n", "class TestLowestCommonAncestor(object):\n", "\n", " def test_lca(self):\n", " node10 = Node(10)\n", " node5 = Node(5)\n", " node12 = Node(12)\n", " node3 = Node(3)\n", " node1 = Node(1)\n", " node8 = Node(8)\n", " node9 = Node(9)\n", " node18 = Node(18)\n", " node20 = Node(20)\n", " node40 = Node(40)\n", " node3.left = node1\n", " node3.right = node8\n", " node5.left = node12\n", " node5.right = node3\n", " node20.left = node40\n", " node9.left = node18\n", " node9.right = node20\n", " node10.left = node5\n", " node10.right = node9\n", " root = node10\n", " node0 = Node(0)\n", " binary_tree = BinaryTree()\n", " assert_equal(binary_tree.lca(root, node0, node5), None)\n", " assert_equal(binary_tree.lca(root, node5, node0), None)\n", " assert_equal(binary_tree.lca(root, node1, node8), node3)\n", " assert_equal(binary_tree.lca(root, node12, node8), node5)\n", " assert_equal(binary_tree.lca(root, node12, node40), node10)\n", " assert_equal(binary_tree.lca(root, node9, node20), node9)\n", " assert_equal(binary_tree.lca(root, node3, node5), node5)\n", " print('Success: test_lca')\n", "\n", "\n", "def main():\n", " test = TestLowestCommonAncestor()\n", " test.test_lca()\n", "\n", "\n", "if __name__ == '__main__':\n", " main()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Solution Notebook\n", "\n", "Review the [Solution Notebook]() for a discussion on algorithms and code solutions." ] } ], "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": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 1 }