Given a string S and a string T, count the number of distinct subsequences of S which equals T.
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).
Example 1:
Input: S ="rabbbit"
, T ="rabbit" Output: 3
Explanation: As shown below, there are 3 ways you can generate "rabbit" from S. (The caret symbol ^ means the chosen letters)rabbbit
^^^^ ^^rabbbit
^^ ^^^^rabbbit
^^^ ^^^
Example 2:
Input: S ="babgbag"
, T ="bag" Output: 5
Explanation: As shown below, there are 5 ways you can generate "bag" from S. (The caret symbol ^ means the chosen letters)babgbag
^^ ^babgbag
^^ ^babgbag
^ ^^babgbag
^ ^^babgbag
^^^
看到有关字符串的子序列或者配准类的问题,首先应该考虑的就是用动态规划 Dynamic Programming 来求解,这个应成为条件反射。而所有 DP 问题的核心就是找出状态转移方程,想这道题就是递推一个二维的 dp 数组,其中 dp[i][j] 表示s中范围是 [0, i] 的子串中能组成t中范围是 [0, j] 的子串的子序列的个数。下面我们从题目中给的例子来分析,这个二维 dp 数组应为:
Ø r a b b b i t Ø 1 1 1 1 1 1 1 1 r 0 1 1 1 1 1 1 1 a 0 0 1 1 1 1 1 1 b 0 0 0 1 2 3 3 3 b 0 0 0 0 1 3 3 3 i 0 0 0 0 0 0 3 3 t 0 0 0 0 0 0 0 3
首先,若原字符串和子序列都为空时,返回1,因为空串也是空串的一个子序列。若原字符串不为空,而子序列为空,也返回1,因为空串也是任意字符串的一个子序列。而当原字符串为空,子序列不为空时,返回0,因为非空字符串不能当空字符串的子序列。理清这些,二维数组 dp 的边缘便可以初始化了,下面只要找出状态转移方程,就可以更新整个 dp 数组了。我们通过观察上面的二维数组可以发现,当更新到 dp[i][j] 时,dp[i][j] >= dp[i][j - 1] 总是成立,再进一步观察发现,当 T[i - 1] == S[j - 1] 时,dp[i][j] = dp[i][j - 1] + dp[i - 1][j - 1],若不等, dp[i][j] = dp[i][j - 1],所以,综合以上,递推式为:
dp[i][j] = dp[i][j - 1] + (T[i - 1] == S[j - 1] ? dp[i - 1][j - 1] : 0)
根据以上分析,可以写出代码如下:
class Solution { public: int numDistinct(string s, string t) { int m = s.size(), n = t.size(); vector<vector<long>> dp(n + 1, vector<long>(m + 1)); for (int j = 0; j <= m; ++j) dp[0][j] = 1; for (int i = 1; i <= n; ++i) { for (int j = 1; j <= m; ++j) { dp[i][j] = dp[i][j - 1] + (t[i - 1] == s[j - 1] ? dp[i - 1][j - 1] : 0); } } return dp[n][m]; } };
Github 同步地址:
https://github.com/grandyang/leetcode/issues/115
参考资料:
https://leetcode.com/problems/distinct-subsequences/
https://leetcode.com/problems/distinct-subsequences/discuss/37327/Easy-to-understand-DP-in-Java