动态规划及LCS
LCS的python实现：
1 #!/usr/bin/env python 2 #-*- coding: utf-8 -*- 3 import sys 4 5 reload(sys) 6 sys.setdefaultencoding('utf-8') 7 8 9 class LCS(object): 10 """Long Common Subsequence算法 11 """ 12 def __init__(self, str1, str2): 13 self.s1 = str1 14 self.s2 = str2 15 self.lcs = [['' for i in range(len(self.s2) + 1)] for j in range(len(self.s1) + 1)] # 另一种写法 16 17 def get_lcs_len(self): 18 """递归计算lcs的长度 19 """ 20 for i in xrange(len(self.s1) + 1): 21 for j in xrange(len(self.s2) + 1): 22 if i == 0 or j == 0: 23 self.lcs[i, j] = 0 24 elif self.s1[i - 1] == self.s2[j - 1]: 25 self.lcs[i, j] = self.lcs[i - 1][j - 1] + 1 26 else: 27 self.lcs[i, j] = max(self.lcs[i - 1][j], self.lcs[i][j - 1]) 28 return self.lcs[len(self.s1), len(self.s2)] 29 30 def get_lcs(self): 31 """递归计算lcs(直接获取lCS) 32 """ 33 for i in xrange(len(self.s1) + 1): 34 for j in xrange(len(self.s2) + 1): 35 if i == 0 or j == 0: 36 self.lcs[i][j] = '' 37 elif self.s1[i - 1] == self.s2[j - 1]: 38 self.lcs[i][j] = self.lcs[i - 1][j - 1] + self.s1[i - 1] 39 else: 40 self.lcs[i][j] = self.lcs[i - 1][j] if len(self.lcs[i - 1][j]) > \ 41 len(self.lcs[i][j - 1]) else self.lcs[i][j - 1] 42 return self.lcs[len(self.s1)][len(self.s2)] 43 44 45 46 if __name__ == '__main__': 47 s1 = 'abcdefgw' 48 s2 = 'bdfgegwe' 49 model = LCS(s1, s2) 50 print model.get_lcs()
