76. Minimum Window Substring 76.最小窗口子字符串BANC
Given a string S and a string T, find the minimum window in S which will contain all the characters in T in complexity O(n).
Example:
Input: S = "ADOBECODEBANC", T = "ABC" Output: "BANC"
一句话概括思路:用map保证覆盖了t中所有的字母。
count = 0时,t全部找到,可以往前移。利用原来map的key,增加map,begin++
比如ABC全部找到,ABC得value减少为0.
此时再增加原来key的value,就ABC,因为这里就是曾经的end。end再从map中减去。
end - begin,在这个窗口的范围内覆盖了t的所有字母
map.containsKey(c) ){ //首先应该判断是否有这个key,然后才是 .get > 1
counter++; //counter重建了,所以需要数量++
begin++; //更新完了head = begin才加
class Solution {
public String minWindow(String s, String t) {
//cc
if (s.length() < t.length())
return "";
//定义map
HashMap<Character, Integer> map = new HashMap<>();
int start = 0, end = 0, head = 0, len = Integer.MAX_VALUE;
//定义counter
for (char c : t.toCharArray()) {
map.put(c, map.getOrDefault(c, 0) + 1);
}
int count = map.size();
//while循环
//end的减少
while (end < s.length()) {
char charAtEnd = s.charAt(end);
if (map.containsKey(charAtEnd)) {
map.put(charAtEnd, map.get(charAtEnd) - 1);
if (map.get(charAtEnd) == 0)
count--;
}
end++;
while (count == 0) {
char charAtStart = s.charAt(start);
if (map.containsKey(charAtStart)) {
map.put(charAtStart, map.get(charAtStart) + 1);
if (map.get(charAtStart) > 0)
count++;
}
//更新head
if (end - start < len) {
len = end - start;
head = start;
}
//start往前移
start++;
}
}
//返回
if (len == Integer.MAX_VALUE) return "";
else return s.substring(head, head + len);
}
}