{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "def z(s):\n", " ''' Use Z-algorithm to preprocess given string. See\n", " Gusfield for complete description of algorithm. '''\n", " \n", " Z = [len(s)] + [0] * len(s)\n", " assert len(s) > 1\n", " \n", " # Initial comparison of s[1:] with prefix\n", " for i in range(1, len(s)):\n", " if s[i] == s[i-1]:\n", " Z[1] += 1\n", " else:\n", " break\n", " \n", " r, l = 0, 0\n", " if Z[1] > 0:\n", " r, l = Z[1], 1\n", " \n", " for k in range(2, len(s)):\n", " assert Z[k] == 0\n", " if k > r:\n", " # Case 1\n", " for i in range(k, len(s)):\n", " if s[i] == s[i-k]:\n", " Z[k] += 1\n", " else:\n", " break\n", " r, l = k + Z[k] - 1, k\n", " else:\n", " # Case 2\n", " # Calculate length of beta\n", " nbeta = r - k + 1\n", " Zkp = Z[k - l]\n", " if nbeta > Zkp:\n", " # Case 2a: Zkp wins\n", " Z[k] = Zkp\n", " else:\n", " # Case 2b: Compare characters just past r\n", " nmatch = 0\n", " for i in range(r+1, len(s)):\n", " if s[i] == s[i - k]:\n", " nmatch += 1\n", " else:\n", " break\n", " l, r = k, r + nmatch\n", " Z[k] = r - k + 1\n", " return Z" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[11, 0, 0, 1, 0, 1, 0, 4, 0, 0, 1, 0]" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "z('abracadabra')\n", "# abracadabra (11)\n", "# a (1)\n", "# a (1)\n", "# abra (4)\n", "# a (1)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[5, 4, 3, 2, 1, 0]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "z('aaaaa')" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "def zMatch(p, t):\n", " s = p + \"$\" + t\n", " Z = z(s)\n", " occurrences = []\n", " for i in range(len(p) + 1, len(s)):\n", " if Z[i] >= len(p):\n", " occurrences.append(i - (len(p) + 1))\n", " return occurrences" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[9]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "zMatch('needle', 'haystack needle haystack')\n", "# 012345678901234567890123\n", "# 1 2" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[9, 16]" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "zMatch('needle', 'haystack needle needle')\n", "# 0123456789012345678901\n", "# 1 2" ] } ], "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": "3.6.2" } }, "nbformat": 4, "nbformat_minor": 1 }