Description
The French author Georges Perec (1936–1982) once wrote a book, La disparition, without the letter 'e'. He was a member of the Oulipo group. A quote from the book:
Tout avait Pair normal, mais tout s’affirmait faux. Tout avait Fair normal, d’abord, puis surgissait l’inhumain, l’affolant. Il aurait voulu savoir où s’articulait l’association qui l’unissait au roman : stir son tapis, assaillant à tout instant son imagination, l’intuition d’un tabou, la vision d’un mal obscur, d’un quoi vacant, d’un non-dit : la vision, l’avision d’un oubli commandant tout, où s’abolissait la raison : tout avait l’air normal mais…
Perec would probably have scored high (or rather, low) in the following contest. People are asked to write a perhaps even meaningful text on some subject with as few occurrences of a given “word” as possible. Our task is to provide the jury with a program that counts these occurrences, in order to obtain a ranking of the competitors. These competitors often write very long texts with nonsense meaning; a sequence of 500,000 consecutive 'T's is not unusual. And they never use spaces.
So we want to quickly find out how often a word, i.e., a given string, occurs in a text. More formally: given the alphabet {'A', 'B', 'C', …, 'Z'} and two finite strings over that alphabet, a word W and a text T, count the number of occurrences of W in T. All the consecutive characters of W must exactly match consecutive characters of T. Occurrences may overlap.
Input
The first line of the input file contains a single number: the number of test cases to follow. Each test case has the following format:
- One line with the word W, a string over {'A', 'B', 'C', …, 'Z'}, with 1 ≤ |W| ≤ 10,000 (here |W| denotes the length of the string W).
- One line with the text T, a string over {'A', 'B', 'C', …, 'Z'}, with |W| ≤ |T| ≤ 1,000,000.
Output
For every test case in the input file, the output should contain a single number, on a single line: the number of occurrences of the word W in the text T.
Sample Input
3 BAPC BAPC AZA AZAZAZA VERDI AVERDXIVYERDIAN
Sample Output
1 3 0
纯KMP算法,KMP确实是神算法。。一开始我还没弄懂就开始敲,居然把长字串给求next值了,KMP其妙是在其求的出现的重复字串的next值,当失配时,只需要回溯到第一个重复字串(后面的都是重复前面的字串)的相应失配位置,再开始匹配就行,不需要从头开始。。这样就把一个嵌套的循环活生生的改成了一个O(n)的时间复杂度。
KMP的实现主要是两步
1.求next数组的值。
我的前提是字串读取为从0开始到len-1位置。
先定义next[0]为0(也有定义为-1的,我的习惯是0)。
从1到len-1循环,
定义i为循环变量,顺便定义j为next数组的循环变量(j=0初始),当s[i]==s[j]时,说明出现重复字串,则j++;
如果不相等,则说明此处失配,但是!!!注意:失配不代表当前next值就为0,需回溯到该失配处对应的上一处重复点,
即while(j>0&&s[i]!=s[j])j=next[j-1];(这里需要着重说明,因为刚刚坑也坑在这里,因为此时j处失配,因此通过next[j-1]回溯到之前,但正好由于数组下标比实际数位小1,因此得到的next[j-1]值正好就是失配点对应的回溯点,不用再+1了,当然如果一直失配下去,j最终为0)
要是比较难理解这个失配点的回溯点是怎么回事,我们看个例子:
ID | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | |
str | a | b | a | b | c | a | b | a | b | a | b | a | b | c | a | b | a | b | |
Next | 0 | 0 | 1 | 2 | 0 | 1 | 2 | 3 | 4 | 3 | 4 | 3 | 4 | 5 | 7 | 7 | 8 | 9 |
我们可以看到,着重注意一下下标为9的点,此时s[i=9]!=s[j=4] 则,找回溯点 j=next[j-1=3]=2,即失配前一个字符对应的回溯点告诉我们 失配点的回溯点的下标为2,则此时 s[j=2]==s[i=9],即匹配成功,说明回溯过去,找到了失配点的一个配对点。但注意,一旦配对成功,(有一种情况是回溯过去,找不到配对点,j直接=0,之后不做处理),但如果配对成功了,说明相对于j=2,该点是j=2之后的又一配对点,所以j++,使得j要=3;故此时next[9]=3;
2.匹配过程
1.匹配是从另一个长串开始循环(定义循环变量为i,长串为ls),另一个循环变量q=0则负责s。
初始i s均为0,若ls[i]==s[q] 则 :q++,i++;
如果不等,则s需要回答其失配点对应的回溯点,当然如果q==0,则没有回溯点可言,故直接i++;否则 q=next[q-1](为什么是q-1和上述相同);
。。。。此处进行很多次循环;
当q==len;说明此时已经匹配完成,ans++;(说明匹配到一个字串) 并且 q=next[q-1](原理相同,将q回到末尾点的回溯点的下一点,与ls[i](此时i已经递增一位)继续进行匹配)。
#include <iostream> #include <cstdio> #include <cstring> using namespace std; char w[10005]; char t[1000005]; int next[10005]; int ans; void kmp_1()//求next数组过程 { next[0]=0; int j=0; for (int i=1; w[i]!='