标签:hash 选择 窗口 turn list lis 超过 一个 put
所有的循环只为寻找答案, 所有的判断只为选择正确答案
public List<Integer> findSubstring(String s, String[] words) { List<Integer> res = new LinkedList<Integer>(); if(words == null || words.length == 0 || s == null || s.equals("")) return res; HashMap<String, Integer> freq = new HashMap<String, Integer>(); // 统计数组中每个词出现的次数,放入哈希表中待用 for(String word : words){ freq.put(word, freq.containsKey(word) ? freq.get(word) + 1 : 1); } // 得到每个词的长度 int len = words[0].length(); // 错开位来统计 for(int i = 0; i < len; i++){ // 因为要一单词长度递增, 因此i < len
// 建一个新的哈希表,记录本轮搜索中窗口内单词出现次数 HashMap<String, Integer> currFreq = new HashMap<String, Integer>(); // start是窗口的开始,count表明窗口内有多少词 int start = i, count = 0; for(int j = i; j <= s.length() - len; j += len){ String sub = s.substring(j, j + len); // 看下一个词是否是给定数组中的 if(freq.containsKey(sub)){ // 窗口中单词出现次数加1 currFreq.put(sub, currFreq.containsKey(sub) ? currFreq.get(sub) + 1 : 1); count++; // 如果该单词出现次数已经超过给定数组中的次数了,说明多来了一个该单词,所以要把窗口中该单词上次出现的位置及之前所有单词给去掉 while(currFreq.get(sub) > freq.get(sub)){ String leftMost = s.substring(start, start + len); currFreq.put(leftMost, currFreq.get(leftMost) - 1); start = start + len; count--; } // 如果窗口内单词数和总单词数一样,则找到结果 if(count == words.length){ String leftMost = s.substring(start, start + len); currFreq.put(leftMost, currFreq.get(leftMost) - 1); res.add(start); start = start + len; count--; } // 如果截出来的单词都不在数组中,前功尽弃,重新开始 } else { currFreq.clear(); start = j + len; count = 0; } } } return res; }
30. Substring with Concatenation of All Words
标签:hash 选择 窗口 turn list lis 超过 一个 put
原文地址:http://www.cnblogs.com/apanda009/p/7122674.html