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文章目录
- 前言
- [一、力扣187. 重复的DNA序列](#一、力扣187. 重复的DNA序列)
- [二、力扣28. 找出字符串中第一个匹配项的下标](#二、力扣28. 找出字符串中第一个匹配项的下标)
前言
我们不要每次都去一个字符一个字符地比较子串和模式串,而是维护一个滑动窗口,运用滑动哈希算法一边滑动一边计算窗口中字符串的哈希值,拿这个哈希值去和模式串的哈希值比较,这样就可以避免截取子串,从而把匹配算法降低为 O(N),这就是 Rabin-Karp 指纹字符串查找算法的核心逻辑。
一、力扣187. 重复的DNA序列
java
class Solution {
public List<String> findRepeatedDnaSequences(String s) {
List<String> res = new ArrayList<>();
if(s.length() < 10)return res;
Map<String,Integer> map = new HashMap<>();
int left = 0, right = 9;
while(right < s.length()){
String cur = s.substring(left,right+1);
right ++;
map.put(cur,map.getOrDefault(cur,0)+1);
left ++;
}
for(String k : map.keySet()){
if(map.get(k) > 1){
res.add(k);
}
}
return res;
}
}
`在滑动窗口中快速计算窗口中元素的哈希值,叫做滑动哈希技巧`
java
class Solution {
public List<String> findRepeatedDnaSequences(String s) {
int[] nums = new int[s.length()];
for(int i = 0; i < s.length(); i ++){
switch(s.charAt(i)){
case 'A':
nums[i] = 0;break;
case 'C' :
nums[i] = 1;break;
case 'G' :
nums[i] = 2;break;
case 'T':
nums[i] = 3;break;
}
}
HashSet<Integer> seen = new HashSet<>();
HashSet<String> res = new HashSet<>();
int R = 4;//进制
int L = 10;//当前位数
int RL = (int)Math.pow(R,L-1);
int windowHash = 0;
int left = 0, right = 0;
while(right < nums.length){
windowHash = windowHash * R + nums[right];
right ++;
if(right - left == L){
if(seen.contains(windowHash)){
res.add(s.substring(left,right));
}else{
seen.add(windowHash);
}
windowHash = windowHash - nums[left] * RL;
left ++;
}
}
return new LinkedList<>(res);
}
}
二、力扣28. 找出字符串中第一个匹配项的下标
java
class Solution {
public int strStr(String haystack, String needle) {
int L = needle.length();
int R = 256;
long LR = 1;
long Q = 1658598167;
for(int i = 1; i <= L-1; i ++){
LR = (LR * R)%Q;
}
long needleHash = 0;
long windowHash = 0;
for(int i = 0; i < L; i ++){
needleHash = (needleHash * R + needle.charAt(i))%Q ;
}
int left = 0, right = 0;
while(right < haystack.length()){
windowHash = ((windowHash * R)%Q + haystack.charAt(right))%Q;
right ++;
if(right - left == L){
if(windowHash == needleHash){
if(needle.equals(haystack.substring(left,right))){
return left;
}
}
windowHash = (windowHash - (haystack.charAt(left)*LR)%Q+Q)%Q;
left ++;
}
}
return -1;
}
}