滑动窗口-Substring Search Problem
2018-07-18 11:19:19
一、Minimum Window Substring
问题描述:

问题求解:
public String minWindow(String s, String t) {
String res = "";
if (t.length() > s.length()) return res;
Map<Character, Integer> map = new HashMap<>();
for (int i = 0; i < t.length(); i++) {
map.put(t.charAt(i), map.getOrDefault(t.charAt(i), 0) + 1);
}
int begin, end, count;
begin = 0;
end = 0;
count = map.size();
int minLen = Integer.MAX_VALUE;
for (; end < s.length(); end++) {
char c = s.charAt(end);
if (map.containsKey(c)) {
map.put(c, map.get(c) - 1);
if (map.get(c) == 0) count--;
}
while (count == 0) {
if (end - begin + 1 < minLen) {
res = s.substring(begin, end);
minLen = end - begin + 1;
}
char temp = s.charAt(begin);
if (map.containsKey(temp)) {
if (map.get(temp) == 0) count++;
map.put(temp, map.get(temp) + 1);
}
begin++;
}
}
return res;
}
二、Longest Substring Without Repeating Characters
问题描述:

问题求解:
public int lengthOfLongestSubstring(String s) {
int[] map = new int[256];
int res = 0;
int begin = 0;
for (int end = 0; end < s.length(); end++) {
char c = s.charAt(end);
map[c]++;
while (map[c] > 1) {
map[s.charAt(begin)]--;
begin++;
}
res = Math.max(res, end - begin + 1);
}
return res;
}
三、Substring with Concatenation of All Words
问题描述:

问题求解:
本题其实是一道拓展题,这里题目中给出了所有单词的长度相同,也就意味着可以将所有的单词看作单个字母来进行处理,如果是这样的话,那么外层循环很显然就是word length了。之后通过两个Map对单词进行计数就可以进行解决。
public List<Integer> findSubstring(String s, String[] words) {
List<Integer> res = new ArrayList<>();
if (s == null || s.length() == 0 || words.length == 0) return res;
Map<String, Integer> map = new HashMap<>();
int wl = words[0].length();
int num = words.length;
int n = s.length();
if (n < num * wl) return res;
for (int i = 0; i < num; i++)
map.put(words[i], map.getOrDefault(words[i], 0) + 1);
for (int i = 0; i < wl; i++) {
int begin, end, cnt;
Map<String, Integer> seen = new HashMap<>();
begin = i;
cnt = 0;
for (end = begin; end <= n - wl; end += wl) {
String str = s.substring(end, end + wl);
// 匹配成功
if (map.containsKey(str)) {
seen.put(str, seen.getOrDefault(str, 0) + 1);
cnt++;
// 若计数个数超过map, 则需要对窗口大小进行调整
while (seen.get(str) > map.get(str)) {
String temp = s.substring(begin, begin + wl);
seen.put(temp, seen.get(temp) - 1);
begin = begin + wl;
cnt--;
}
// 如果所有单词都匹配完成, 则向res中添加答案,同时将窗口大小向前挪动一步
if (cnt == num) {
res.add(begin);
String temp = s.substring(begin, begin + wl);
seen.put(temp, seen.get(temp) - 1);
begin = begin + wl;
cnt--;
}
}
// 当前匹配失败,则begin要从下一个开始,且所有的计数都要初始化
else {
seen.clear();
begin = end + wl;
cnt = 0;
}
}
}
return res;
}
四、Longest Substring with At Least K Repeating Characters
问题描述:

问题求解:
单纯的使用滑动窗口在修改窗口大小的时候会出现难以判断的情况,可以引入uniqueNum这个变量,来表征K个不同的字母,这样就可以大大降低问题的复杂度。
public int longestSubstring(String s, int k) {
int res = 0;
char[] chs = s.toCharArray();
for (int i = 1; i <= 26; i++) {
res = Math.max(res, helper(chs, k, i));
}
return res;
}
private int helper(char[] chs, int k, int uniqueNum) {
int res = 0;
int[] cnt = new int[256];
int begin = 0;
int nolessthank = 0;
int curUnique = 0;
for (int end = 0; end < chs.length; end++) {
if (cnt[chs[end]] == 0) curUnique++;
if (cnt[chs[end]] == k - 1) nolessthank++;
cnt[chs[end]]++;
while (curUnique > uniqueNum) {
if (cnt[chs[begin]] == k) nolessthank--;
if (cnt[chs[begin]] == 1) curUnique--;
cnt[chs[begin]]--;
begin++;
}
if (curUnique == uniqueNum && nolessthank == curUnique)
res = Math.max(res, end - begin + 1);
}
return res;
}
五、Max Consecutive Ones III
问题描述:

问题求解:
这种问题一般要么dp,要么滑动窗口,这种敏感性要有。
本题就是使用滑动窗口来进行解决的问题。实质上就是求解最长的substring其中至多包含k个0。
public int longestOnes(int[] A, int K) {
int res = 0;
int begin = 0;
int cnt = 0;
for (int end = 0; end < A.length; end++) {
if (A[end] == 0) cnt+= 1;
while (cnt > K) {
if (A[begin] == 0) cnt -= 1;
begin++;
}
res = Math.max(res, end - begin + 1);
}
return res;
}

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