--- comments: true difficulty: 困难 edit_url: https://github.com/doocs/leetcode/edit/main/solution/0100-0199/0115.Distinct%20Subsequences/README.md tags: - 字符串 - 动态规划 --- <!-- problem:start --> # [115. 不同的子序列](https://leetcode.cn/problems/distinct-subsequences) [English Version](/solution/0100-0199/0115.Distinct%20Subsequences/README_EN.md) ## 题目描述 <!-- description:start --> <p>给你两个字符串 <code>s</code><strong> </strong>和 <code>t</code> ,统计并返回在 <code>s</code> 的 <strong>子序列</strong> 中 <code>t</code> 出现的个数,结果需要对 10<sup>9</sup> + 7 取模。</p> <p> </p> <p><strong>示例 1:</strong></p> <pre> <strong>输入:</strong>s = "rabbbit", t = "rabbit"<code> <strong>输出</strong></code><strong>:</strong><code>3 </code><strong>解释:</strong> 如下所示, 有 3 种可以从 s 中得到 <code>"rabbit" 的方案</code>。 <code><strong><u>rabb</u></strong>b<strong><u>it</u></strong></code> <code><strong><u>ra</u></strong>b<strong><u>bbit</u></strong></code> <code><strong><u>rab</u></strong>b<strong><u>bit</u></strong></code></pre> <p><strong>示例 2:</strong></p> <pre> <strong>输入:</strong>s = "babgbag", t = "bag" <code><strong>输出</strong></code><strong>:</strong><code>5 </code><strong>解释:</strong> 如下所示, 有 5 种可以从 s 中得到 <code>"bag" 的方案</code>。 <code><strong><u>ba</u></strong>b<u><strong>g</strong></u>bag</code> <code><strong><u>ba</u></strong>bgba<strong><u>g</u></strong></code> <code><u><strong>b</strong></u>abgb<strong><u>ag</u></strong></code> <code>ba<u><strong>b</strong></u>gb<u><strong>ag</strong></u></code> <code>babg<strong><u>bag</u></strong></code> </pre> <p> </p> <p><strong>提示:</strong></p> <ul> <li><code>1 <= s.length, t.length <= 1000</code></li> <li><code>s</code> 和 <code>t</code> 由英文字母组成</li> </ul> <!-- description:end --> ## 解法 <!-- solution:start --> ### 方法一:动态规划 我们定义 $f[i][j]$ 表示字符串 $s$ 的前 $i$ 个字符中,子序列构成字符串 $t$ 的前 $j$ 个字符的方案数。初始时 $f[i][0]=1$,其中 $i \in [0,m]$。 当 $i \gt 0$ 时,考虑 $f[i][j]$ 的计算: - 当 $s[i-1] \ne t[j-1]$ 时,不能选取 $s[i-1]$,因此 $f[i][j]=f[i-1][j]$; - 否则,可以选取 $s[i-1]$,此时 $f[i][j]=f[i-1][j-1]$。 因此我们有如下的状态转移方程: $$ f[i][j]=\left\{ \begin{aligned} &f[i-1][j], &s[i-1] \ne t[j-1] \\ &f[i-1][j-1]+f[i-1][j], &s[i-1]=t[j-1] \end{aligned} \right. $$ 最终的答案即为 $f[m][n]$,其中 $m$ 和 $n$ 分别是字符串 $s$ 和 $t$ 的长度。 时间复杂度 $O(m \times n)$,空间复杂度 $O(m \times n)$。 我们注意到 $f[i][j]$ 的计算只和 $f[i-1][..]$ 有关,因此,我们可以优化掉第一维,这样空间复杂度可以降低到 $O(n)$。 <!-- tabs:start --> #### Python3 ```python class Solution: def numDistinct(self, s: str, t: str) -> int: m, n = len(s), len(t) f = [[0] * (n + 1) for _ in range(m + 1)] for i in range(m + 1): f[i][0] = 1 for i, a in enumerate(s, 1): for j, b in enumerate(t, 1): f[i][j] = f[i - 1][j] if a == b: f[i][j] += f[i - 1][j - 1] return f[m][n] ``` #### Java ```java class Solution { public int numDistinct(String s, String t) { int m = s.length(), n = t.length(); int[][] f = new int[m + 1][n + 1]; for (int i = 0; i < m + 1; ++i) { f[i][0] = 1; } for (int i = 1; i < m + 1; ++i) { for (int j = 1; j < n + 1; ++j) { f[i][j] = f[i - 1][j]; if (s.charAt(i - 1) == t.charAt(j - 1)) { f[i][j] += f[i - 1][j - 1]; } } } return f[m][n]; } } ``` #### C++ ```cpp class Solution { public: int numDistinct(string s, string t) { int m = s.size(), n = t.size(); unsigned long long f[m + 1][n + 1]; memset(f, 0, sizeof(f)); for (int i = 0; i < m + 1; ++i) { f[i][0] = 1; } for (int i = 1; i < m + 1; ++i) { for (int j = 1; j < n + 1; ++j) { f[i][j] = f[i - 1][j]; if (s[i - 1] == t[j - 1]) { f[i][j] += f[i - 1][j - 1]; } } } return f[m][n]; } }; ``` #### Go ```go func numDistinct(s string, t string) int { m, n := len(s), len(t) f := make([][]int, m+1) for i := range f { f[i] = make([]int, n+1) } for i := 0; i <= m; i++ { f[i][0] = 1 } for i := 1; i <= m; i++ { for j := 1; j <= n; j++ { f[i][j] = f[i-1][j] if s[i-1] == t[j-1] { f[i][j] += f[i-1][j-1] } } } return f[m][n] } ``` #### TypeScript ```ts function numDistinct(s: string, t: string): number { const m = s.length; const n = t.length; const f: number[][] = new Array(m + 1).fill(0).map(() => new Array(n + 1).fill(0)); for (let i = 0; i <= m; ++i) { f[i][0] = 1; } for (let i = 1; i <= m; ++i) { for (let j = 1; j <= n; ++j) { f[i][j] = f[i - 1][j]; if (s[i - 1] === t[j - 1]) { f[i][j] += f[i - 1][j - 1]; } } } return f[m][n]; } ``` #### Rust ```rust impl Solution { #[allow(dead_code)] pub fn num_distinct(s: String, t: String) -> i32 { let n = s.len(); let m = t.len(); let mut dp: Vec<Vec<u64>> = vec![vec![0; m + 1]; n + 1]; // Initialize the dp vector for i in 0..=n { dp[i][0] = 1; } // Begin the actual dp process for i in 1..=n { for j in 1..=m { dp[i][j] = if s.as_bytes()[i - 1] == t.as_bytes()[j - 1] { dp[i - 1][j] + dp[i - 1][j - 1] } else { dp[i - 1][j] }; } } dp[n][m] as i32 } } ``` <!-- tabs:end --> <!-- solution:end --> <!-- solution:start --> ### 方法二 <!-- tabs:start --> #### Python3 ```python class Solution: def numDistinct(self, s: str, t: str) -> int: n = len(t) f = [1] + [0] * n for a in s: for j in range(n, 0, -1): if a == t[j - 1]: f[j] += f[j - 1] return f[n] ``` #### Java ```java class Solution { public int numDistinct(String s, String t) { int n = t.length(); int[] f = new int[n + 1]; f[0] = 1; for (char a : s.toCharArray()) { for (int j = n; j > 0; --j) { char b = t.charAt(j - 1); if (a == b) { f[j] += f[j - 1]; } } } return f[n]; } } ``` #### C++ ```cpp class Solution { public: int numDistinct(string s, string t) { int n = t.size(); unsigned long long f[n + 1]; memset(f, 0, sizeof(f)); f[0] = 1; for (char& a : s) { for (int j = n; j; --j) { char b = t[j - 1]; if (a == b) { f[j] += f[j - 1]; } } } return f[n]; } }; ``` #### Go ```go func numDistinct(s string, t string) int { n := len(t) f := make([]int, n+1) f[0] = 1 for _, a := range s { for j := n; j > 0; j-- { if b := t[j-1]; byte(a) == b { f[j] += f[j-1] } } } return f[n] } ``` #### TypeScript ```ts function numDistinct(s: string, t: string): number { const n = t.length; const f: number[] = new Array(n + 1).fill(0); f[0] = 1; for (const a of s) { for (let j = n; j; --j) { const b = t[j - 1]; if (a === b) { f[j] += f[j - 1]; } } } return f[n]; } ``` <!-- tabs:end --> <!-- solution:end --> <!-- problem:end -->