原题地址:https://oj.leetcode.com/problems/distinct-subsequences/
题意:
Given a string S and a string T, count the number of distinct subsequences of T in S.
A subsequence of a string is a new string which is formed from the original string by deleting some (can be none) of the characters without disturbing the relative positions of the remaining characters. (ie, "ACE"
is a subsequence of "ABCDE"
while "AEC"
is not).
Here is an example:
S = "rabbbit"
, T = "rabbit"
Return 3
.
解题思路:这道题使用动态规划来解决。题的意思是:S的所有子串中,有多少子串是T。下面来看看状态转移方程。dp[i][j]表示S[0...i-1]中有多少子串是T[0...j-1]。
当S[i-1]=T[j-1]时:dp[i][j]=dp[i-1][j-1]+dp[i-1][j];
S[0...i-1]中有多少子串是T[0...j-1]包含:{S[0...i-2]中有多少子串是T[0...j-2]}+{S[0...i-2]中有多少子串是T[0...j-1]}
当S[i-1]!=T[j-1]时:dp[i][j]=dp[i-1][j-1]
初始化状态如何确定呢:
dp[0][j]=0;因为:S是空串,则无论如何都不能包含非空的子串。这个初始状态在初始化矩阵dp的时候就顺带包括了
dp[i][0]=1;因为:S[0...i-1]只有一个子串是空串。
代码:
class Solution: # @return an integer def numDistinct(self, S, T): dp = [ [0 for j in range(len(T) + 1)] for i in range(len(S) + 1) ] for i in range(len(S) + 1): dp[i][0] = 1 for i in range(1, len(S) + 1): for j in range(1, len(T) + 1): if S[i - 1] == T[j - 1]: dp[i][j] = dp[i-1][j-1] + dp[i-1][j] else: dp[i][j] = dp[i-1][j] return dp[len(S)][len(T)]