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
^^^ ^^^
给出一个S字符串,一个T字符串,问S可以有多少种方法变成T,只允许删除S中的字符而不能改变顺序
如上例子,S = “rabbbit”, T = “rabbit”
可以通过删除S第一,第二,第三个“b“这3种方式来得到T
思路:
S中的每个字符都可以有保留和删除两种操作
保留第 j 位字符的时候是一种匹配,删除 j 位字符的时候是一种匹配,要把这两种情况加起来
用dynamic programming来解决,二维dp
这里用x轴用来表示S, dp[0][0]表示的是S和T都是空字符串,这时S和T完全匹配
所以dp[0][0] = 1
对于第0行的j > 0的所有列,表示T=“”,S不是空,这时候S只有一种方法转换成T,就是删除S的所有字符,所以第一行都是1
对于第1列的 i > 0的所有行,表示T不是空,但是S是空,所以S无法转换成T,所以都是0
y轴表示T
T S: "" r a b b b i t ( j )
"" 1 1 1 1 1 1 1 1
r 0
a 0
b 0
b 0
i 0
t 0
( i )
接下来是 i > 0 和 j > 0的部分
比如i = 1,j = 1, 这时候S=“r“, T=”r“, (为方便,i,j为1开始的index)
选择保留S[ j ]:就要看S和T的前一位有多少种方式,前一位是S,T都为空,所以看dp[0][0]
选择删除S[ j ]:就要看S的前一位和T有多少种方式,S前一位是空,T当前是"r",所以看dp[1][0]
这两种方式加起来是dp[0][0] + dp[1][0]
即S[j] == T[i]时:dp[i][j] = dp[i - 1][j - 1] + dp[i][j - 1]
S[j] != T[i]时,比如i = 1, j= 2, 即S=“ra”, T=“r” (为方便,i,j为1开始的index)
S[2] != T[1], 这时应该删除"a", 看S前一位和T是否匹配,即看S="r"和T=“r”
也就是dp[1][1]
即S[j] != T[i]时:dp[i][j] = dp[i][j - 1]
最后返回dp[s.length()][t.length()]
public int numDistinct(String s, String t) {
if (s.length() < t.length()) {
return 0;
}
if (s == null || t == null) {
return 1;
}
int[][] dp = new int[t.length() + 1][s.length() + 1];
dp[0][0] = 1;
//s="" and t.length>0, no match..
for (int i = 1; i <= t.length(); i++) {
dp[i][0] = 0;
}
//t="" and s.length>0, then only one way to get t is to delete all chars in s..
for (int j = 1; j <= s.length(); j++) {
dp[0][j] = 1;
}
for (int i = 1; i <= t.length(); i++) {
for (int j = 1; j <= s.length(); j++) {
if (s.charAt(j - 1) == t.charAt(i - 1)) {
//use s[j] or delete s[j]..
dp[i][j] = dp[i - 1][j - 1] + dp[i][j - 1];
} else {
//delete s[j]..
dp[i][j] = dp[i][j - 1];
}
}
}
return dp[t.length()][s.length()];
}