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  • Leetcode: Find All Anagrams in a String

    Given a string s and a non-empty string p, find all the start indices of p's anagrams in s.
    
    Strings consists of lowercase English letters only and the length of both strings s and p will not be larger than 20,100.
    
    The order of output does not matter.
    
    Example 1:
    
    Input:
    s: "cbaebabacd" p: "abc"
    
    Output:
    [0, 6]
    
    Explanation:
    The substring with start index = 0 is "cba", which is an anagram of "abc".
    The substring with start index = 6 is "bac", which is an anagram of "abc".
    Example 2:
    
    Input:
    s: "abab" p: "ab"
    
    Output:
    [0, 1, 2]
    
    Explanation:
    The substring with start index = 0 is "ab", which is an anagram of "ab".
    The substring with start index = 1 is "ba", which is an anagram of "ab".
    The substring with start index = 2 is "ab", which is an anagram of "ab".

    Time Complexity will be O(n) because the "start" and "end" points will only move from left to right once.

    Sliding Window: Use a count to denote the difference between current sliding window and p, if count == 0, means the current sliding window is the same with p, add start to the result

    refer to https://discuss.leetcode.com/topic/64434/shortest-concise-java-o-n-sliding-window-solution/2

     1 public class Solution {
     2     public List<Integer> findAnagrams(String s, String p) {
     3         List<Integer> list = new ArrayList<>();
     4     if (s == null || s.length() == 0 || p == null || p.length() == 0) return list;
     5     
     6     int[] hash = new int[256]; //character hash
     7     
     8     //record each character in p to hash
     9     for (char c : p.toCharArray()) {
    10         hash[c]++;
    11     }
    12     //two points, initialize count to p's length
    13     int left = 0, right = 0, count = p.length();
    14     
    15     while (right < s.length()) {
    16         //move right everytime, if the character exists in p's hash, decrease the count
    17         //current hash value >= 1 means the character is existing in p
    18         if (hash[s.charAt(right)] >= 1) { //char at right is in p, so is needed to make an anagram of p, so if we shift our window to
    19             count--;             // include right, the difference between our window and p will decrease by 1, so count-1
    20         }
    21         hash[s.charAt(right)]--;      //Other case if hash[s.charAt(right)] right now == 0, which means we do not need it, we do not decrease count
    22         right++;                // hash[s.charAt(right)] will be -1, if window contains some char that p do not need, count will never reach 0
    23                              // whereas some hash[somewhere] will be negative, some hash[somewhereelse] will be positive
    24         //when the count is down to 0, means we found the right anagram
    25         //then add window's left to result list
    26         if (count == 0) {          // this is only when p's chars and window's chars are all the same
    27             list.add(left);
    28         }
    29         //if we find the window's size equals to p, then we have to move left (narrow the window) to find the new match window
    30         //++ to reset the hash because we kicked out the left
    31         //only increase the count if the character is in p
    32         //the count >= 0 indicate it was original in the hash, cuz it won't go below 0
    33         if (right - left == p.length() ) {
    34            
    35             if (hash[s.charAt(left)] >= 0) {
    36                 count++;
    37             }
    38             hash[s.charAt(left)]++;
    39             left++;
    40         
    41         }
    42 
    43         
    44     }
    45         return list;
    46     }
    47 }
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  • 原文地址:https://www.cnblogs.com/EdwardLiu/p/6128474.html
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