• LeetCode: Distinct Subsequences 解题报告


    Distinct Subsequences

    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.

    SOLUTION 1(AC):

    现在这种DP题目基本都是5分钟AC咯。主页君引一下别人的解释咯:

    http://blog.csdn.net/fightforyourdream/article/details/17346385?reload#comments

    http://blog.csdn.net/abcbc/article/details/8978146

    引自以上的解释:

     遇到这种两个串的问题,很容易想到DP。但是这道题的递推关系不明显。可以先尝试做一个二维的表int[][] dp,用来记录匹配子序列的个数(以S ="rabbbit",T = "rabbit"为例):

        r a b b b i t

      1 1 1 1 1 1 1 1

    0 1 1 1 1 1 1 1

    a 0 1 1 1 1 1 1

    b 0 0 2 3 3 3

    b 0 0 0 0 3 3 3

    i 0 0 0 0 0 0 3 3

    t 0 0 0 0 0 0 0 3  

    从这个表可以看出,无论T的字符与S的字符是否匹配,dp[i][j] = dp[i][j - 1].就是说,假设S已经匹配了j - 1个字符,得到匹配个数为dp[i][j - 1].现在无论S[j]是不是和T[i]匹配,匹配的个数至少是dp[i][j - 1]。除此之外,当S[j]和T[i]相等时,我们可以让S[j]和T[i]匹配,然后让S[j - 1]和T[i - 1]去匹配。所以递推关系为:

    dp[0][0] = 1; // T和S都是空串.

    dp[0][1 ... S.length() - 1] = 1; // T是空串,S只有一种子序列匹配。

    dp[1 ... T.length() - 1][0] = 0; // S是空串,T不是空串,S没有子序列匹配。

    dp[i][j] = dp[i][j - 1] + (T[i - 1] == S[j - 1] ? dp[i - 1][j - 1] : 0).1 <= i <= T.length(), 1 <= j <= S.length()


    这道题可以作为两个字符串DP的典型:

    两个字符串:

    先创建二维数组存放答案,如解法数量。注意二维数组的长度要比原来字符串长度+1,因为要考虑第一个位置是空字符串。

    然后考虑dp[i][j]和dp[i-1][j],dp[i][j-1],dp[i-1][j-1]的关系,如何通过判断S.charAt(i)和T.charAt(j)的是否相等来看看如果移除了最后两个字符,能不能把问题转化到子问题。

    最后问题的答案就是dp[S.length()][T.length()]

    还有就是要注意通过填表来找规律。

    注意:循环的时候,一定要注意i的取值要到len,这个出好几次错了。

     1 public class Solution {
     2     public int numDistinct(String S, String T) {
     3         if (S == null || T == null) {
     4             return 0;
     5         }
     6         
     7         int lenS = S.length();
     8         int lenT = T.length();
     9         
    10         if (lenS < lenT) {
    11             return 0;
    12         }
    13         
    14         int[][] D = new int[lenS + 1][lenT + 1];
    15         
    16         // BUG 1: forget to use <= instead of <....
    17         for (int i = 0; i <= lenS; i++) {
    18             for (int j = 0; j <= lenT; j++) {
    19                 // both are empty.
    20                 if (i == 0 && j == 0) {
    21                     D[i][j] = 1;
    22                 } else if (i == 0) {
    23                     // S is empty, can't form a non-empty string.
    24                     D[i][j] = 0;
    25                 } else if (j == 0) {
    26                     // T is empty. S is not empty.
    27                     D[i][j] = 1;
    28                 } else {
    29                     D[i][j] = 0;
    30                     // keep the last character of S.
    31                     if (S.charAt(i - 1) == T.charAt(j - 1)) {
    32                         D[i][j] += D[i - 1][j - 1];
    33                     }
    34                     
    35                     // discard the last character of S.
    36                     D[i][j] += D[i - 1][j];
    37                 }
    38             }
    39         }
    40         
    41         return D[lenS][lenT];
    42     }
    43 }
    View Code

    运行时间:

    Submit TimeStatusRun TimeLanguage
    13 minutes ago Accepted 432 ms java

    SOLUTION 2:

    递归解法也写一下,蛮简单的:

    但是这个解法过不了,TLE了。

     1 // SOLUTION 2: recursion version.
     2     public int numDistinct(String S, String T) {
     3         if (S == null || T == null) {
     4             return 0;
     5         }
     6         
     7         return rec(S, T, 0, 0);
     8     }
     9     
    10     public int rec(String S, String T, int indexS, int indexT) {
    11         int lenS = S.length();
    12         int lenT = T.length();
    13         
    14         // base case:
    15         if (indexT >= lenT) {
    16             // T is empty.
    17             return 1;
    18         }
    19         
    20         if (indexS >= lenS) {
    21             // S is empty but T is not empty.
    22             return 0;
    23         }
    24         
    25         int sum = 0;
    26         // use the first character in S.
    27         if (S.charAt(indexS) == T.charAt(indexT)) {
    28             sum += rec(S, T, indexS + 1, indexT + 1);
    29         }
    30         
    31         // Don't use the first character in S.
    32         sum += rec(S, T, indexS + 1, indexT);
    33         
    34         return sum;
    35     }
    View Code

    SOLUTION 3:

    递归加上memory记忆之后,StackOverflowError. 可能还是不够优化。确实递归层次太多。

    Runtime Error Message: Line 125: java.lang.StackOverflowError
    Last executed input: "zzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzzz
     1 // SOLUTION 3: recursion version with memory.
     2     public int numDistinct(String S, String T) {
     3         if (S == null || T == null) {
     4             return 0;
     5         }
     6         
     7         int lenS = S.length();
     8         int lenT = T.length();
     9         
    10         int[][] memory = new int[lenS + 1][lenT + 1];
    11         for (int i = 0; i <= lenS; i++) {
    12             for (int j = 0; j <= lenT; j++) {
    13                 memory[i][j] = -1;
    14             }
    15         }
    16         
    17         return rec(S, T, 0, 0, memory);
    18     }
    19     
    20     public int rec(String S, String T, int indexS, int indexT, int[][] memory) {
    21         int lenS = S.length();
    22         int lenT = T.length();
    23         
    24         // base case:
    25         if (indexT >= lenT) {
    26             // T is empty.
    27             return 1;
    28         }
    29         
    30         if (indexS >= lenS) {
    31             // S is empty but T is not empty.
    32             return 0;
    33         }
    34         
    35         if (memory[indexS][indexT] != -1) {
    36             return memory[indexS][indexT];
    37         }
    38         
    39         int sum = 0;
    40         // use the first character in S.
    41         if (S.charAt(indexS) == T.charAt(indexT)) {
    42             sum += rec(S, T, indexS + 1, indexT + 1);
    43         }
    44         
    45         // Don't use the first character in S.
    46         sum += rec(S, T, indexS + 1, indexT);
    47         
    48         // record the solution.
    49         memory[indexS][indexT] = sum;
    50         return sum;
    51     }
    View Code

    SOLUTION 4 (AC):

    参考了http://blog.csdn.net/fightforyourdream/article/details/17346385?reload#comments的代码后,发现递归过程找解的过程可以优化。我们不需要沿用DP的思路

    而应该与permutation之类差不多,把当前可能可以取的解都去尝试一次。就是在S中找到T的首字母,再进一步递归。

    Submit TimeStatusRun TimeLanguage
    0 minutes ago Accepted 500 ms java
     1 // SOLUTION 4: improved recursion version
     2     public int numDistinct(String S, String T) {
     3         if (S == null || T == null) {
     4             return 0;
     5         }
     6         
     7         int lenS = S.length();
     8         int lenT = T.length();
     9         
    10         int[][] memory = new int[lenS + 1][lenT + 1];
    11         for (int i = 0; i <= lenS; i++) {
    12             for (int j = 0; j <= lenT; j++) {
    13                 memory[i][j] = -1;
    14             }
    15         }
    16         
    17         return rec4(S, T, 0, 0, memory);
    18     }
    19     
    20     public int rec4(String S, String T, int indexS, int indexT, int[][] memory) {
    21         int lenS = S.length();
    22         int lenT = T.length();
    23         
    24         // base case:
    25         if (indexT >= lenT) {
    26             // T is empty.
    27             return 1;
    28         }
    29         
    30         if (indexS >= lenS) {
    31             // S is empty but T is not empty.
    32             return 0;
    33         }
    34         
    35         if (memory[indexS][indexT] != -1) {
    36             return memory[indexS][indexT];
    37         }
    38         
    39         int sum = 0;
    40         for (int i = indexS; i < lenS; i++) {
    41             // choose which character in S to choose as the first character of T.
    42             if (S.charAt(i) == T.charAt(indexT)) {
    43                 sum += rec4(S, T, i + 1, indexT + 1, memory);
    44             }
    45         }
    46         
    47         // record the solution.
    48         memory[indexS][indexT] = sum;
    49         return sum;
    50     }
    View Code

    SOLUTION 5:

    在SOLUTION 4的基础之上,把记忆体去掉之后,仍然是TLE

    Last executed input: "daacaedaceacabbaabdccdaaeaebacddadcaeaacadbceaecddecdeedcebcdacdaebccdeebcbdeaccabcecbeeaadbccbaeccbbdaeadecabbbedceaddcdeabbcdaeadcddedddcececbeeabcbecaeadddeddccbdbcdcbceabcacddbbcedebbcaccac", "ceadbaa"
     1 // SOLUTION 5: improved recursion version without memory.
     2     public int numDistinct(String S, String T) {
     3         if (S == null || T == null) {
     4             return 0;
     5         }
     6 
     7         return rec5(S, T, 0, 0);
     8     }
     9     
    10     public int rec5(String S, String T, int indexS, int indexT) {
    11         int lenS = S.length();
    12         int lenT = T.length();
    13         
    14         // base case:
    15         if (indexT >= lenT) {
    16             // T is empty.
    17             return 1;
    18         }
    19         
    20         if (indexS >= lenS) {
    21             // S is empty but T is not empty.
    22             return 0;
    23         }
    24         
    25         int sum = 0;
    26         for (int i = indexS; i < lenS; i++) {
    27             // choose which character in S to choose as the first character of T.
    28             if (S.charAt(i) == T.charAt(indexT)) {
    29                 sum += rec5(S, T, i + 1, indexT + 1);
    30             }
    31         }
    32         
    33         return sum;
    34     }
    View Code

    总结:

    大家可以在SOLUTION 1和SOLUTION 4两个选择里用一个就好啦。

    http://blog.csdn.net/fightforyourdream/article/details/17346385?reload#comments

    这道题可以作为两个字符串DP的典型:

    两个字符串:

    先创建二维数组存放答案,如解法数量。注意二维数组的长度要比原来字符串长度+1,因为要考虑第一个位置是空字符串。

    然后考虑dp[i][j]和dp[i-1][j],dp[i][j-1],dp[i-1][j-1]的关系,如何通过判断S.charAt(i)和T.charAt(j)的是否相等来看看如果移除了最后两个字符,能不能把问题转化到子问题。

    最后问题的答案就是dp[S.length()][T.length()]

    还有就是要注意通过填表来找规律。

    GITHUB:

    https://github.com/yuzhangcmu/LeetCode_algorithm/blob/master/dp/NumDistinct.java

  • 相关阅读:
    济群法师:《大乘百法明门论》讲记·视频·音频·MP3
    dict.cn海词:划词助手划遍天下网
    求解:nunit如何测试ConfigurationManager呢?
    spring.net快速入门
    好书推荐:《数学与知识的探求》
    《货币战争》的一点感想
    买了《精通spring 2.0》
    《spring 2.0技术手册》的技术写作方式值得学习!
    关于Erlang语言
    rss阅读器最重要的几项功能
  • 原文地址:https://www.cnblogs.com/yuzhangcmu/p/4196373.html
Copyright © 2020-2023  润新知