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851 lines
30 KiB
851 lines
30 KiB
1 year ago
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---
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comments: true
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---
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# 14.6 编辑距离问题
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编辑距离,也被称为 Levenshtein 距离,指两个字符串之间互相转换的最小修改次数,通常用于在信息检索和自然语言处理中度量两个序列的相似度。
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!!! question
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输入两个字符串 $s$ 和 $t$ ,返回将 $s$ 转换为 $t$ 所需的最少编辑步数。
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你可以在一个字符串中进行三种编辑操作:插入一个字符、删除一个字符、替换字符为任意一个字符。
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如图 14-27 所示,将 `kitten` 转换为 `sitting` 需要编辑 3 步,包括 2 次替换操作与 1 次添加操作;将 `hello` 转换为 `algo` 需要 3 步,包括 2 次替换操作和 1 次删除操作。
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![编辑距离的示例数据](edit_distance_problem.assets/edit_distance_example.png)
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<p align="center"> 图 14-27 编辑距离的示例数据 </p>
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**编辑距离问题可以很自然地用决策树模型来解释**。字符串对应树节点,一轮决策(一次编辑操作)对应树的一条边。
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如图 14-28 所示,在不限制操作的情况下,每个节点都可以派生出许多条边,每条边对应一种操作,这意味着从 `hello` 转换到 `algo` 有许多种可能的路径。
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从决策树的角度看,本题的目标是求解节点 `hello` 和节点 `algo` 之间的最短路径。
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![基于决策树模型表示编辑距离问题](edit_distance_problem.assets/edit_distance_decision_tree.png)
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<p align="center"> 图 14-28 基于决策树模型表示编辑距离问题 </p>
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### 1. 动态规划思路
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**第一步:思考每轮的决策,定义状态,从而得到 $dp$ 表**
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每一轮的决策是对字符串 $s$ 进行一次编辑操作。
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我们希望在编辑操作的过程中,问题的规模逐渐缩小,这样才能构建子问题。设字符串 $s$ 和 $t$ 的长度分别为 $n$ 和 $m$ ,我们先考虑两字符串尾部的字符 $s[n-1]$ 和 $t[m-1]$ 。
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- 若 $s[n-1]$ 和 $t[m-1]$ 相同,我们可以跳过它们,直接考虑 $s[n-2]$ 和 $t[m-2]$ 。
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- 若 $s[n-1]$ 和 $t[m-1]$ 不同,我们需要对 $s$ 进行一次编辑(插入、删除、替换),使得两字符串尾部的字符相同,从而可以跳过它们,考虑规模更小的问题。
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也就是说,我们在字符串 $s$ 中进行的每一轮决策(编辑操作),都会使得 $s$ 和 $t$ 中剩余的待匹配字符发生变化。因此,状态为当前在 $s$ 和 $t$ 中考虑的第 $i$ 和 $j$ 个字符,记为 $[i, j]$ 。
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状态 $[i, j]$ 对应的子问题:**将 $s$ 的前 $i$ 个字符更改为 $t$ 的前 $j$ 个字符所需的最少编辑步数**。
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至此,得到一个尺寸为 $(i+1) \times (j+1)$ 的二维 $dp$ 表。
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**第二步:找出最优子结构,进而推导出状态转移方程**
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考虑子问题 $dp[i, j]$ ,其对应的两个字符串的尾部字符为 $s[i-1]$ 和 $t[j-1]$ ,可根据不同编辑操作分为图 14-29 所示的三种情况。
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1. 在 $s[i-1]$ 之后添加 $t[j-1]$ ,则剩余子问题 $dp[i, j-1]$ 。
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2. 删除 $s[i-1]$ ,则剩余子问题 $dp[i-1, j]$ 。
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3. 将 $s[i-1]$ 替换为 $t[j-1]$ ,则剩余子问题 $dp[i-1, j-1]$ 。
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![编辑距离的状态转移](edit_distance_problem.assets/edit_distance_state_transfer.png)
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<p align="center"> 图 14-29 编辑距离的状态转移 </p>
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根据以上分析,可得最优子结构:$dp[i, j]$ 的最少编辑步数等于 $dp[i, j-1]$、$dp[i-1, j]$、$dp[i-1, j-1]$ 三者中的最少编辑步数,再加上本次的编辑步数 $1$ 。对应的状态转移方程为:
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$$
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dp[i, j] = \min(dp[i, j-1], dp[i-1, j], dp[i-1, j-1]) + 1
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$$
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请注意,**当 $s[i-1]$ 和 $t[j-1]$ 相同时,无须编辑当前字符**,这种情况下的状态转移方程为:
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$$
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dp[i, j] = dp[i-1, j-1]
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$$
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**第三步:确定边界条件和状态转移顺序**
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当两字符串都为空时,编辑步数为 $0$ ,即 $dp[0, 0] = 0$ 。当 $s$ 为空但 $t$ 不为空时,最少编辑步数等于 $t$ 的长度,即首行 $dp[0, j] = j$ 。当 $s$ 不为空但 $t$ 为空时,等于 $s$ 的长度,即首列 $dp[i, 0] = i$ 。
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观察状态转移方程,解 $dp[i, j]$ 依赖左方、上方、左上方的解,因此通过两层循环正序遍历整个 $dp$ 表即可。
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### 2. 代码实现
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=== "Python"
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```python title="edit_distance.py"
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def edit_distance_dp(s: str, t: str) -> int:
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"""编辑距离:动态规划"""
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n, m = len(s), len(t)
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dp = [[0] * (m + 1) for _ in range(n + 1)]
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# 状态转移:首行首列
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for i in range(1, n + 1):
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dp[i][0] = i
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for j in range(1, m + 1):
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dp[0][j] = j
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# 状态转移:其余行列
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for i in range(1, n + 1):
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for j in range(1, m + 1):
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if s[i - 1] == t[j - 1]:
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# 若两字符相等,则直接跳过此两字符
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dp[i][j] = dp[i - 1][j - 1]
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else:
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# 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
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dp[i][j] = min(dp[i][j - 1], dp[i - 1][j], dp[i - 1][j - 1]) + 1
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return dp[n][m]
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1 year ago
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```
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=== "C++"
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```cpp title="edit_distance.cpp"
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/* 编辑距离:动态规划 */
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int editDistanceDP(string s, string t) {
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int n = s.length(), m = t.length();
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vector<vector<int>> dp(n + 1, vector<int>(m + 1, 0));
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// 状态转移:首行首列
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for (int i = 1; i <= n; i++) {
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dp[i][0] = i;
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}
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for (int j = 1; j <= m; j++) {
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dp[0][j] = j;
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}
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// 状态转移:其余行列
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for (int i = 1; i <= n; i++) {
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for (int j = 1; j <= m; j++) {
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if (s[i - 1] == t[j - 1]) {
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// 若两字符相等,则直接跳过此两字符
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dp[i][j] = dp[i - 1][j - 1];
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} else {
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// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
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dp[i][j] = min(min(dp[i][j - 1], dp[i - 1][j]), dp[i - 1][j - 1]) + 1;
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}
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}
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}
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return dp[n][m];
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}
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1 year ago
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```
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=== "Java"
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```java title="edit_distance.java"
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/* 编辑距离:动态规划 */
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int editDistanceDP(String s, String t) {
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int n = s.length(), m = t.length();
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int[][] dp = new int[n + 1][m + 1];
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// 状态转移:首行首列
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for (int i = 1; i <= n; i++) {
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dp[i][0] = i;
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}
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for (int j = 1; j <= m; j++) {
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dp[0][j] = j;
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}
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// 状态转移:其余行列
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for (int i = 1; i <= n; i++) {
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for (int j = 1; j <= m; j++) {
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if (s.charAt(i - 1) == t.charAt(j - 1)) {
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// 若两字符相等,则直接跳过此两字符
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dp[i][j] = dp[i - 1][j - 1];
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} else {
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// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
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dp[i][j] = Math.min(Math.min(dp[i][j - 1], dp[i - 1][j]), dp[i - 1][j - 1]) + 1;
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}
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}
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}
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return dp[n][m];
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}
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1 year ago
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```
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=== "C#"
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```csharp title="edit_distance.cs"
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/* 编辑距离:动态规划 */
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int EditDistanceDP(string s, string t) {
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int n = s.Length, m = t.Length;
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int[,] dp = new int[n + 1, m + 1];
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// 状态转移:首行首列
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for (int i = 1; i <= n; i++) {
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dp[i, 0] = i;
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}
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for (int j = 1; j <= m; j++) {
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dp[0, j] = j;
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}
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// 状态转移:其余行列
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for (int i = 1; i <= n; i++) {
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for (int j = 1; j <= m; j++) {
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if (s[i - 1] == t[j - 1]) {
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// 若两字符相等,则直接跳过此两字符
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dp[i, j] = dp[i - 1, j - 1];
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} else {
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// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
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dp[i, j] = Math.Min(Math.Min(dp[i, j - 1], dp[i - 1, j]), dp[i - 1, j - 1]) + 1;
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}
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}
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}
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return dp[n, m];
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}
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1 year ago
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```
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=== "Go"
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```go title="edit_distance.go"
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/* 编辑距离:动态规划 */
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func editDistanceDP(s string, t string) int {
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n := len(s)
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m := len(t)
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dp := make([][]int, n+1)
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for i := 0; i <= n; i++ {
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dp[i] = make([]int, m+1)
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}
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// 状态转移:首行首列
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for i := 1; i <= n; i++ {
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dp[i][0] = i
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}
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for j := 1; j <= m; j++ {
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dp[0][j] = j
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}
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// 状态转移:其余行列
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for i := 1; i <= n; i++ {
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for j := 1; j <= m; j++ {
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if s[i-1] == t[j-1] {
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// 若两字符相等,则直接跳过此两字符
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dp[i][j] = dp[i-1][j-1]
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} else {
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// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
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dp[i][j] = MinInt(MinInt(dp[i][j-1], dp[i-1][j]), dp[i-1][j-1]) + 1
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}
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}
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}
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return dp[n][m]
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}
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1 year ago
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```
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=== "Swift"
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```swift title="edit_distance.swift"
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/* 编辑距离:动态规划 */
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func editDistanceDP(s: String, t: String) -> Int {
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let n = s.utf8CString.count
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let m = t.utf8CString.count
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var dp = Array(repeating: Array(repeating: 0, count: m + 1), count: n + 1)
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// 状态转移:首行首列
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for i in stride(from: 1, through: n, by: 1) {
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dp[i][0] = i
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}
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for j in stride(from: 1, through: m, by: 1) {
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dp[0][j] = j
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}
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// 状态转移:其余行列
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for i in stride(from: 1, through: n, by: 1) {
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for j in stride(from: 1, through: m, by: 1) {
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if s.utf8CString[i - 1] == t.utf8CString[j - 1] {
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// 若两字符相等,则直接跳过此两字符
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dp[i][j] = dp[i - 1][j - 1]
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} else {
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// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
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dp[i][j] = min(min(dp[i][j - 1], dp[i - 1][j]), dp[i - 1][j - 1]) + 1
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}
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}
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}
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return dp[n][m]
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}
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1 year ago
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```
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=== "JS"
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```javascript title="edit_distance.js"
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/* 编辑距离:动态规划 */
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function editDistanceDP(s, t) {
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const n = s.length,
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m = t.length;
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const dp = Array.from({ length: n + 1 }, () => new Array(m + 1).fill(0));
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// 状态转移:首行首列
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for (let i = 1; i <= n; i++) {
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dp[i][0] = i;
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}
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for (let j = 1; j <= m; j++) {
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dp[0][j] = j;
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}
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// 状态转移:其余行列
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for (let i = 1; i <= n; i++) {
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for (let j = 1; j <= m; j++) {
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if (s.charAt(i - 1) === t.charAt(j - 1)) {
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// 若两字符相等,则直接跳过此两字符
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dp[i][j] = dp[i - 1][j - 1];
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} else {
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// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
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dp[i][j] =
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Math.min(
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Math.min(dp[i][j - 1], dp[i - 1][j]),
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dp[i - 1][j - 1]
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) + 1;
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}
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}
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}
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return dp[n][m];
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}
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1 year ago
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```
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=== "TS"
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```typescript title="edit_distance.ts"
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/* 编辑距离:动态规划 */
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function editDistanceDP(s: string, t: string): number {
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const n = s.length,
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m = t.length;
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const dp = Array.from({ length: n + 1 }, () =>
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Array.from({ length: m + 1 }, () => 0)
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);
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// 状态转移:首行首列
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for (let i = 1; i <= n; i++) {
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dp[i][0] = i;
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}
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for (let j = 1; j <= m; j++) {
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dp[0][j] = j;
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}
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// 状态转移:其余行列
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for (let i = 1; i <= n; i++) {
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for (let j = 1; j <= m; j++) {
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if (s.charAt(i - 1) === t.charAt(j - 1)) {
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||
|
// 若两字符相等,则直接跳过此两字符
|
||
|
dp[i][j] = dp[i - 1][j - 1];
|
||
|
} else {
|
||
|
// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
|
||
|
dp[i][j] =
|
||
|
Math.min(
|
||
|
Math.min(dp[i][j - 1], dp[i - 1][j]),
|
||
|
dp[i - 1][j - 1]
|
||
|
) + 1;
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
return dp[n][m];
|
||
|
}
|
||
1 year ago
|
```
|
||
|
|
||
|
=== "Dart"
|
||
|
|
||
|
```dart title="edit_distance.dart"
|
||
1 year ago
|
/* 编辑距离:动态规划 */
|
||
|
int editDistanceDP(String s, String t) {
|
||
|
int n = s.length, m = t.length;
|
||
|
List<List<int>> dp = List.generate(n + 1, (_) => List.filled(m + 1, 0));
|
||
|
// 状态转移:首行首列
|
||
|
for (int i = 1; i <= n; i++) {
|
||
|
dp[i][0] = i;
|
||
|
}
|
||
|
for (int j = 1; j <= m; j++) {
|
||
|
dp[0][j] = j;
|
||
|
}
|
||
|
// 状态转移:其余行列
|
||
|
for (int i = 1; i <= n; i++) {
|
||
|
for (int j = 1; j <= m; j++) {
|
||
|
if (s[i - 1] == t[j - 1]) {
|
||
|
// 若两字符相等,则直接跳过此两字符
|
||
|
dp[i][j] = dp[i - 1][j - 1];
|
||
|
} else {
|
||
|
// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
|
||
|
dp[i][j] = min(min(dp[i][j - 1], dp[i - 1][j]), dp[i - 1][j - 1]) + 1;
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
return dp[n][m];
|
||
|
}
|
||
1 year ago
|
```
|
||
|
|
||
|
=== "Rust"
|
||
|
|
||
|
```rust title="edit_distance.rs"
|
||
1 year ago
|
/* 编辑距离:动态规划 */
|
||
|
fn edit_distance_dp(s: &str, t: &str) -> i32 {
|
||
|
let (n, m) = (s.len(), t.len());
|
||
|
let mut dp = vec![vec![0; m + 1]; n + 1];
|
||
|
// 状态转移:首行首列
|
||
|
for i in 1..= n {
|
||
|
dp[i][0] = i as i32;
|
||
|
}
|
||
|
for j in 1..m {
|
||
|
dp[0][j] = j as i32;
|
||
|
}
|
||
|
// 状态转移:其余行列
|
||
|
for i in 1..=n {
|
||
|
for j in 1..=m {
|
||
|
if s.chars().nth(i - 1) == t.chars().nth(j - 1) {
|
||
|
// 若两字符相等,则直接跳过此两字符
|
||
|
dp[i][j] = dp[i - 1][j - 1];
|
||
|
} else {
|
||
|
// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
|
||
|
dp[i][j] = std::cmp::min(std::cmp::min(dp[i][j - 1], dp[i - 1][j]), dp[i - 1][j - 1]) + 1;
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
dp[n][m]
|
||
|
}
|
||
1 year ago
|
```
|
||
|
|
||
|
=== "C"
|
||
|
|
||
|
```c title="edit_distance.c"
|
||
|
[class]{}-[func]{editDistanceDP}
|
||
|
```
|
||
|
|
||
|
=== "Zig"
|
||
|
|
||
|
```zig title="edit_distance.zig"
|
||
1 year ago
|
// 编辑距离:动态规划
|
||
|
fn editDistanceDP(comptime s: []const u8, comptime t: []const u8) i32 {
|
||
|
comptime var n = s.len;
|
||
|
comptime var m = t.len;
|
||
|
var dp = [_][m + 1]i32{[_]i32{0} ** (m + 1)} ** (n + 1);
|
||
|
// 状态转移:首行首列
|
||
|
for (1..n + 1) |i| {
|
||
|
dp[i][0] = @intCast(i);
|
||
|
}
|
||
|
for (1..m + 1) |j| {
|
||
|
dp[0][j] = @intCast(j);
|
||
|
}
|
||
|
// 状态转移:其余行列
|
||
|
for (1..n + 1) |i| {
|
||
|
for (1..m + 1) |j| {
|
||
|
if (s[i - 1] == t[j - 1]) {
|
||
|
// 若两字符相等,则直接跳过此两字符
|
||
|
dp[i][j] = dp[i - 1][j - 1];
|
||
|
} else {
|
||
|
// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
|
||
|
dp[i][j] = @min(@min(dp[i][j - 1], dp[i - 1][j]), dp[i - 1][j - 1]) + 1;
|
||
|
}
|
||
|
}
|
||
|
}
|
||
|
return dp[n][m];
|
||
|
}
|
||
1 year ago
|
```
|
||
|
|
||
|
如图 14-30 所示,编辑距离问题的状态转移过程与背包问题非常类似,都可以看作是填写一个二维网格的过程。
|
||
|
|
||
|
=== "<1>"
|
||
|
![编辑距离的动态规划过程](edit_distance_problem.assets/edit_distance_dp_step1.png)
|
||
|
|
||
|
=== "<2>"
|
||
|
![edit_distance_dp_step2](edit_distance_problem.assets/edit_distance_dp_step2.png)
|
||
|
|
||
|
=== "<3>"
|
||
|
![edit_distance_dp_step3](edit_distance_problem.assets/edit_distance_dp_step3.png)
|
||
|
|
||
|
=== "<4>"
|
||
|
![edit_distance_dp_step4](edit_distance_problem.assets/edit_distance_dp_step4.png)
|
||
|
|
||
|
=== "<5>"
|
||
|
![edit_distance_dp_step5](edit_distance_problem.assets/edit_distance_dp_step5.png)
|
||
|
|
||
|
=== "<6>"
|
||
|
![edit_distance_dp_step6](edit_distance_problem.assets/edit_distance_dp_step6.png)
|
||
|
|
||
|
=== "<7>"
|
||
|
![edit_distance_dp_step7](edit_distance_problem.assets/edit_distance_dp_step7.png)
|
||
|
|
||
|
=== "<8>"
|
||
|
![edit_distance_dp_step8](edit_distance_problem.assets/edit_distance_dp_step8.png)
|
||
|
|
||
|
=== "<9>"
|
||
|
![edit_distance_dp_step9](edit_distance_problem.assets/edit_distance_dp_step9.png)
|
||
|
|
||
|
=== "<10>"
|
||
|
![edit_distance_dp_step10](edit_distance_problem.assets/edit_distance_dp_step10.png)
|
||
|
|
||
|
=== "<11>"
|
||
|
![edit_distance_dp_step11](edit_distance_problem.assets/edit_distance_dp_step11.png)
|
||
|
|
||
|
=== "<12>"
|
||
|
![edit_distance_dp_step12](edit_distance_problem.assets/edit_distance_dp_step12.png)
|
||
|
|
||
|
=== "<13>"
|
||
|
![edit_distance_dp_step13](edit_distance_problem.assets/edit_distance_dp_step13.png)
|
||
|
|
||
|
=== "<14>"
|
||
|
![edit_distance_dp_step14](edit_distance_problem.assets/edit_distance_dp_step14.png)
|
||
|
|
||
|
=== "<15>"
|
||
|
![edit_distance_dp_step15](edit_distance_problem.assets/edit_distance_dp_step15.png)
|
||
|
|
||
|
<p align="center"> 图 14-30 编辑距离的动态规划过程 </p>
|
||
|
|
||
|
### 3. 空间优化
|
||
|
|
||
|
由于 $dp[i,j]$ 是由上方 $dp[i-1, j]$、左方 $dp[i, j-1]$、左上方状态 $dp[i-1, j-1]$ 转移而来,而正序遍历会丢失左上方 $dp[i-1, j-1]$ ,倒序遍历无法提前构建 $dp[i, j-1]$ ,因此两种遍历顺序都不可取。
|
||
|
|
||
|
为此,我们可以使用一个变量 `leftup` 来暂存左上方的解 $dp[i-1, j-1]$ ,从而只需考虑左方和上方的解。此时的情况与完全背包问题相同,可使用正序遍历。
|
||
|
|
||
|
=== "Python"
|
||
|
|
||
|
```python title="edit_distance.py"
|
||
1 year ago
|
def edit_distance_dp_comp(s: str, t: str) -> int:
|
||
|
"""编辑距离:空间优化后的动态规划"""
|
||
|
n, m = len(s), len(t)
|
||
|
dp = [0] * (m + 1)
|
||
|
# 状态转移:首行
|
||
|
for j in range(1, m + 1):
|
||
|
dp[j] = j
|
||
|
# 状态转移:其余行
|
||
|
for i in range(1, n + 1):
|
||
|
# 状态转移:首列
|
||
|
leftup = dp[0] # 暂存 dp[i-1, j-1]
|
||
|
dp[0] += 1
|
||
|
# 状态转移:其余列
|
||
|
for j in range(1, m + 1):
|
||
|
temp = dp[j]
|
||
|
if s[i - 1] == t[j - 1]:
|
||
|
# 若两字符相等,则直接跳过此两字符
|
||
|
dp[j] = leftup
|
||
|
else:
|
||
|
# 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
|
||
|
dp[j] = min(dp[j - 1], dp[j], leftup) + 1
|
||
|
leftup = temp # 更新为下一轮的 dp[i-1, j-1]
|
||
|
return dp[m]
|
||
1 year ago
|
```
|
||
|
|
||
|
=== "C++"
|
||
|
|
||
|
```cpp title="edit_distance.cpp"
|
||
1 year ago
|
/* 编辑距离:空间优化后的动态规划 */
|
||
|
int editDistanceDPComp(string s, string t) {
|
||
|
int n = s.length(), m = t.length();
|
||
|
vector<int> dp(m + 1, 0);
|
||
|
// 状态转移:首行
|
||
|
for (int j = 1; j <= m; j++) {
|
||
|
dp[j] = j;
|
||
|
}
|
||
|
// 状态转移:其余行
|
||
|
for (int i = 1; i <= n; i++) {
|
||
|
// 状态转移:首列
|
||
|
int leftup = dp[0]; // 暂存 dp[i-1, j-1]
|
||
|
dp[0] = i;
|
||
|
// 状态转移:其余列
|
||
|
for (int j = 1; j <= m; j++) {
|
||
|
int temp = dp[j];
|
||
|
if (s[i - 1] == t[j - 1]) {
|
||
|
// 若两字符相等,则直接跳过此两字符
|
||
|
dp[j] = leftup;
|
||
|
} else {
|
||
|
// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
|
||
|
dp[j] = min(min(dp[j - 1], dp[j]), leftup) + 1;
|
||
|
}
|
||
|
leftup = temp; // 更新为下一轮的 dp[i-1, j-1]
|
||
|
}
|
||
|
}
|
||
|
return dp[m];
|
||
|
}
|
||
1 year ago
|
```
|
||
|
|
||
|
=== "Java"
|
||
|
|
||
|
```java title="edit_distance.java"
|
||
1 year ago
|
/* 编辑距离:空间优化后的动态规划 */
|
||
|
int editDistanceDPComp(String s, String t) {
|
||
|
int n = s.length(), m = t.length();
|
||
|
int[] dp = new int[m + 1];
|
||
|
// 状态转移:首行
|
||
|
for (int j = 1; j <= m; j++) {
|
||
|
dp[j] = j;
|
||
|
}
|
||
|
// 状态转移:其余行
|
||
|
for (int i = 1; i <= n; i++) {
|
||
|
// 状态转移:首列
|
||
|
int leftup = dp[0]; // 暂存 dp[i-1, j-1]
|
||
|
dp[0] = i;
|
||
|
// 状态转移:其余列
|
||
|
for (int j = 1; j <= m; j++) {
|
||
|
int temp = dp[j];
|
||
|
if (s.charAt(i - 1) == t.charAt(j - 1)) {
|
||
|
// 若两字符相等,则直接跳过此两字符
|
||
|
dp[j] = leftup;
|
||
|
} else {
|
||
|
// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
|
||
|
dp[j] = Math.min(Math.min(dp[j - 1], dp[j]), leftup) + 1;
|
||
|
}
|
||
|
leftup = temp; // 更新为下一轮的 dp[i-1, j-1]
|
||
|
}
|
||
|
}
|
||
|
return dp[m];
|
||
|
}
|
||
1 year ago
|
```
|
||
|
|
||
|
=== "C#"
|
||
|
|
||
|
```csharp title="edit_distance.cs"
|
||
1 year ago
|
/* 编辑距离:空间优化后的动态规划 */
|
||
1 year ago
|
int EditDistanceDPComp(string s, string t) {
|
||
1 year ago
|
int n = s.Length, m = t.Length;
|
||
|
int[] dp = new int[m + 1];
|
||
|
// 状态转移:首行
|
||
|
for (int j = 1; j <= m; j++) {
|
||
|
dp[j] = j;
|
||
|
}
|
||
|
// 状态转移:其余行
|
||
|
for (int i = 1; i <= n; i++) {
|
||
|
// 状态转移:首列
|
||
|
int leftup = dp[0]; // 暂存 dp[i-1, j-1]
|
||
|
dp[0] = i;
|
||
|
// 状态转移:其余列
|
||
|
for (int j = 1; j <= m; j++) {
|
||
|
int temp = dp[j];
|
||
|
if (s[i - 1] == t[j - 1]) {
|
||
|
// 若两字符相等,则直接跳过此两字符
|
||
|
dp[j] = leftup;
|
||
|
} else {
|
||
|
// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
|
||
|
dp[j] = Math.Min(Math.Min(dp[j - 1], dp[j]), leftup) + 1;
|
||
|
}
|
||
|
leftup = temp; // 更新为下一轮的 dp[i-1, j-1]
|
||
|
}
|
||
|
}
|
||
|
return dp[m];
|
||
|
}
|
||
1 year ago
|
```
|
||
|
|
||
|
=== "Go"
|
||
|
|
||
|
```go title="edit_distance.go"
|
||
1 year ago
|
/* 编辑距离:空间优化后的动态规划 */
|
||
|
func editDistanceDPComp(s string, t string) int {
|
||
|
n := len(s)
|
||
|
m := len(t)
|
||
|
dp := make([]int, m+1)
|
||
|
// 状态转移:首行
|
||
|
for j := 1; j <= m; j++ {
|
||
|
dp[j] = j
|
||
|
}
|
||
|
// 状态转移:其余行
|
||
|
for i := 1; i <= n; i++ {
|
||
|
// 状态转移:首列
|
||
|
leftUp := dp[0] // 暂存 dp[i-1, j-1]
|
||
|
dp[0] = i
|
||
|
// 状态转移:其余列
|
||
|
for j := 1; j <= m; j++ {
|
||
|
temp := dp[j]
|
||
|
if s[i-1] == t[j-1] {
|
||
|
// 若两字符相等,则直接跳过此两字符
|
||
|
dp[j] = leftUp
|
||
|
} else {
|
||
|
// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
|
||
|
dp[j] = MinInt(MinInt(dp[j-1], dp[j]), leftUp) + 1
|
||
|
}
|
||
|
leftUp = temp // 更新为下一轮的 dp[i-1, j-1]
|
||
|
}
|
||
|
}
|
||
|
return dp[m]
|
||
|
}
|
||
1 year ago
|
```
|
||
|
|
||
|
=== "Swift"
|
||
|
|
||
|
```swift title="edit_distance.swift"
|
||
1 year ago
|
/* 编辑距离:空间优化后的动态规划 */
|
||
|
func editDistanceDPComp(s: String, t: String) -> Int {
|
||
|
let n = s.utf8CString.count
|
||
|
let m = t.utf8CString.count
|
||
|
var dp = Array(repeating: 0, count: m + 1)
|
||
|
// 状态转移:首行
|
||
|
for j in stride(from: 1, through: m, by: 1) {
|
||
|
dp[j] = j
|
||
|
}
|
||
|
// 状态转移:其余行
|
||
|
for i in stride(from: 1, through: n, by: 1) {
|
||
|
// 状态转移:首列
|
||
|
var leftup = dp[0] // 暂存 dp[i-1, j-1]
|
||
|
dp[0] = i
|
||
|
// 状态转移:其余列
|
||
|
for j in stride(from: 1, through: m, by: 1) {
|
||
|
let temp = dp[j]
|
||
|
if s.utf8CString[i - 1] == t.utf8CString[j - 1] {
|
||
|
// 若两字符相等,则直接跳过此两字符
|
||
|
dp[j] = leftup
|
||
|
} else {
|
||
|
// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
|
||
|
dp[j] = min(min(dp[j - 1], dp[j]), leftup) + 1
|
||
|
}
|
||
|
leftup = temp // 更新为下一轮的 dp[i-1, j-1]
|
||
|
}
|
||
|
}
|
||
|
return dp[m]
|
||
|
}
|
||
1 year ago
|
```
|
||
|
|
||
|
=== "JS"
|
||
|
|
||
|
```javascript title="edit_distance.js"
|
||
1 year ago
|
/* 编辑距离:状态压缩后的动态规划 */
|
||
|
function editDistanceDPComp(s, t) {
|
||
|
const n = s.length,
|
||
|
m = t.length;
|
||
|
const dp = new Array(m + 1).fill(0);
|
||
|
// 状态转移:首行
|
||
|
for (let j = 1; j <= m; j++) {
|
||
|
dp[j] = j;
|
||
|
}
|
||
|
// 状态转移:其余行
|
||
|
for (let i = 1; i <= n; i++) {
|
||
|
// 状态转移:首列
|
||
|
let leftup = dp[0]; // 暂存 dp[i-1, j-1]
|
||
|
dp[0] = i;
|
||
|
// 状态转移:其余列
|
||
|
for (let j = 1; j <= m; j++) {
|
||
|
const temp = dp[j];
|
||
|
if (s.charAt(i - 1) === t.charAt(j - 1)) {
|
||
|
// 若两字符相等,则直接跳过此两字符
|
||
|
dp[j] = leftup;
|
||
|
} else {
|
||
|
// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
|
||
|
dp[j] = Math.min(Math.min(dp[j - 1], dp[j]), leftup) + 1;
|
||
|
}
|
||
|
leftup = temp; // 更新为下一轮的 dp[i-1, j-1]
|
||
|
}
|
||
|
}
|
||
|
return dp[m];
|
||
|
}
|
||
1 year ago
|
```
|
||
|
|
||
|
=== "TS"
|
||
|
|
||
|
```typescript title="edit_distance.ts"
|
||
1 year ago
|
/* 编辑距离:状态压缩后的动态规划 */
|
||
|
function editDistanceDPComp(s: string, t: string): number {
|
||
|
const n = s.length,
|
||
|
m = t.length;
|
||
|
const dp = new Array(m + 1).fill(0);
|
||
|
// 状态转移:首行
|
||
|
for (let j = 1; j <= m; j++) {
|
||
|
dp[j] = j;
|
||
|
}
|
||
|
// 状态转移:其余行
|
||
|
for (let i = 1; i <= n; i++) {
|
||
|
// 状态转移:首列
|
||
|
let leftup = dp[0]; // 暂存 dp[i-1, j-1]
|
||
|
dp[0] = i;
|
||
|
// 状态转移:其余列
|
||
|
for (let j = 1; j <= m; j++) {
|
||
|
const temp = dp[j];
|
||
|
if (s.charAt(i - 1) === t.charAt(j - 1)) {
|
||
|
// 若两字符相等,则直接跳过此两字符
|
||
|
dp[j] = leftup;
|
||
|
} else {
|
||
|
// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
|
||
|
dp[j] = Math.min(Math.min(dp[j - 1], dp[j]), leftup) + 1;
|
||
|
}
|
||
|
leftup = temp; // 更新为下一轮的 dp[i-1, j-1]
|
||
|
}
|
||
|
}
|
||
|
return dp[m];
|
||
|
}
|
||
1 year ago
|
```
|
||
|
|
||
|
=== "Dart"
|
||
|
|
||
|
```dart title="edit_distance.dart"
|
||
1 year ago
|
/* 编辑距离:空间优化后的动态规划 */
|
||
|
int editDistanceDPComp(String s, String t) {
|
||
|
int n = s.length, m = t.length;
|
||
|
List<int> dp = List.filled(m + 1, 0);
|
||
|
// 状态转移:首行
|
||
|
for (int j = 1; j <= m; j++) {
|
||
|
dp[j] = j;
|
||
|
}
|
||
|
// 状态转移:其余行
|
||
|
for (int i = 1; i <= n; i++) {
|
||
|
// 状态转移:首列
|
||
|
int leftup = dp[0]; // 暂存 dp[i-1, j-1]
|
||
|
dp[0] = i;
|
||
|
// 状态转移:其余列
|
||
|
for (int j = 1; j <= m; j++) {
|
||
|
int temp = dp[j];
|
||
|
if (s[i - 1] == t[j - 1]) {
|
||
|
// 若两字符相等,则直接跳过此两字符
|
||
|
dp[j] = leftup;
|
||
|
} else {
|
||
|
// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
|
||
|
dp[j] = min(min(dp[j - 1], dp[j]), leftup) + 1;
|
||
|
}
|
||
|
leftup = temp; // 更新为下一轮的 dp[i-1, j-1]
|
||
|
}
|
||
|
}
|
||
|
return dp[m];
|
||
|
}
|
||
1 year ago
|
```
|
||
|
|
||
|
=== "Rust"
|
||
|
|
||
|
```rust title="edit_distance.rs"
|
||
1 year ago
|
/* 编辑距离:空间优化后的动态规划 */
|
||
|
fn edit_distance_dp_comp(s: &str, t: &str) -> i32 {
|
||
|
let (n, m) = (s.len(), t.len());
|
||
|
let mut dp = vec![0; m + 1];
|
||
|
// 状态转移:首行
|
||
|
for j in 1..m {
|
||
|
dp[j] = j as i32;
|
||
|
}
|
||
|
// 状态转移:其余行
|
||
|
for i in 1..=n {
|
||
|
// 状态转移:首列
|
||
|
let mut leftup = dp[0]; // 暂存 dp[i-1, j-1]
|
||
|
dp[0] = i as i32;
|
||
|
// 状态转移:其余列
|
||
|
for j in 1..=m {
|
||
|
let temp = dp[j];
|
||
|
if s.chars().nth(i - 1) == t.chars().nth(j - 1) {
|
||
|
// 若两字符相等,则直接跳过此两字符
|
||
|
dp[j] = leftup;
|
||
|
} else {
|
||
|
// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
|
||
|
dp[j] = std::cmp::min(std::cmp::min(dp[j - 1], dp[j]), leftup) + 1;
|
||
|
}
|
||
|
leftup = temp; // 更新为下一轮的 dp[i-1, j-1]
|
||
|
}
|
||
|
}
|
||
|
dp[m]
|
||
|
}
|
||
1 year ago
|
```
|
||
|
|
||
|
=== "C"
|
||
|
|
||
|
```c title="edit_distance.c"
|
||
|
[class]{}-[func]{editDistanceDPComp}
|
||
|
```
|
||
|
|
||
|
=== "Zig"
|
||
|
|
||
|
```zig title="edit_distance.zig"
|
||
1 year ago
|
// 编辑距离:空间优化后的动态规划
|
||
|
fn editDistanceDPComp(comptime s: []const u8, comptime t: []const u8) i32 {
|
||
|
comptime var n = s.len;
|
||
|
comptime var m = t.len;
|
||
|
var dp = [_]i32{0} ** (m + 1);
|
||
|
// 状态转移:首行
|
||
|
for (1..m + 1) |j| {
|
||
|
dp[j] = @intCast(j);
|
||
|
}
|
||
|
// 状态转移:其余行
|
||
|
for (1..n + 1) |i| {
|
||
|
// 状态转移:首列
|
||
|
var leftup = dp[0]; // 暂存 dp[i-1, j-1]
|
||
|
dp[0] = @intCast(i);
|
||
|
// 状态转移:其余列
|
||
|
for (1..m + 1) |j| {
|
||
|
var temp = dp[j];
|
||
|
if (s[i - 1] == t[j - 1]) {
|
||
|
// 若两字符相等,则直接跳过此两字符
|
||
|
dp[j] = leftup;
|
||
|
} else {
|
||
|
// 最少编辑步数 = 插入、删除、替换这三种操作的最少编辑步数 + 1
|
||
|
dp[j] = @min(@min(dp[j - 1], dp[j]), leftup) + 1;
|
||
|
}
|
||
|
leftup = temp; // 更新为下一轮的 dp[i-1, j-1]
|
||
|
}
|
||
|
}
|
||
|
return dp[m];
|
||
|
}
|
||
1 year ago
|
```
|