04-树6. Huffman Codes (30)
04-树6. Huffman Codes (30)
In 1953, David A. Huffman published his paper "A Method for the Construction of Minimum-Redundancy Codes", and hence printed his name in the history of computer science. As a professor who gives the final exam problem on Huffman codes, I am encountering a big problem: the Huffman codes are NOT unique. For example, given a string "aaaxuaxz", we can observe that the frequencies of the characters 'a', 'x', 'u' and 'z' are 4, 2, 1 and 1, respectively. We may either encode the symbols as {'a'=0, 'x'=10, 'u'=110, 'z'=111}, or in another way as {'a'=1, 'x'=01, 'u'=001, 'z'=000}, both compress the string into 14 bits. Another set of code can be given as {'a'=0, 'x'=11, 'u'=100, 'z'=101}, but {'a'=0, 'x'=01, 'u'=011, 'z'=001} is NOT correct since "aaaxuaxz" and "aazuaxax" can both be decoded from the code 00001011001001. The students are submitting all kinds of codes, and I need a computer program to help me determine which ones are correct and which ones are not.
Input Specification:
Each input file contains one test case. For each case, the first line gives an integer N (2 <= N <= 63), then followed by a line that contains all the N distinct characters and their frequencies in the following format:
c[1] f[1] c[2] f[2] ... c[N] f[N]
where c[i] is a character chosen from {'0' - '9', 'a' - 'z', 'A' - 'Z', '_'}, and f[i] is the frequency of c[i] and is an integer no more than 1000. The next line gives a positive integer M (<=1000), then followed by M student submissions. Each student submission consists of N lines, each in the format:
c[i] code[i]
where c[i] is the i-th character and code[i] is a string of '0's and '1's.
Output Specification:
For each test case, print in each line either “Yes” if the student’s submission is correct, or “No” if not.
Sample Input:7 A 1 B 1 C 1 D 3 E 3 F 6 G 6 4 A 00000 B 00001 C 0001 D 001 E 01 F 10 G 11 A 01010 B 01011 C 0100 D 011 E 10 F 11 G 00 A 000 B 001 C 010 D 011 E 100 F 101 G 110 A 00000 B 00001 C 0001 D 001 E 00 F 10 G 11Sample Output:
Yes Yes No No
#include <stdio.h> #include <stdlib.h> #include <string.h> void percolateDown(int *heap, int parent) { //将位置parent出元素下滤使其满足堆序性 int temp = heap[parent]; int child = 2 * parent; if (child + 1 <= heap[0] && heap[child + 1] < heap[child]) ++child; while (child <= heap[0] && heap[child] < temp) { heap[parent] = heap[child]; parent = child; child = 2 * parent; if (child + 1 <= heap[0] && heap[child + 1] < heap[child]) ++child; } heap[parent] = temp; } void buildMinHeap(int *heap) { //已满足结构性，调整元素位置使满足堆序性 for (int i = heap[0] / 2; i > 0; --i) //所有非叶节点根据堆序性下滤 percolateDown(heap, i); } int deleteMin(int *heap) { //删除并返回堆顶元素，同时调整结构维护堆序性 int minElem = heap[1]; heap[1] = heap[heap[0]--]; //将最后一个元素移到堆顶 percolateDown(heap, 1); //唯一不满足堆序性的堆顶元素下滤 return minElem; } void insertMinHeap(int *heap, int weight) { //堆中插入一个元素 heap[++heap[0]] = weight; //插入到堆末尾 //将插入节点的祖先节点中比他大的节点依次下滤，过程等价于上滤（稍微多一点的开销） for (int i = heap[0] / 2; i > 0 && heap[i] > weight; i /= 2) percolateDown(heap, i); } int calWPL(int *freq) { int heap[100] = {}; //huffman树所用堆，0位置保存元素大小，1位置开始保存权值 int size = 0; for (int i = 0; i < 256; ++i) { //将所有权值放入空堆中，等待建堆（调整使有堆序性） if (freq[i]) { heap[++size] = freq[i]; } } heap[0] = size; //0位置保存堆中元素个数 buildMinHeap(heap); //建堆 //模拟构建huffman树过程：每次从堆中弹出权值最小的两个子树进行合并，合并后的树（权为子树权和）再入堆； //而wpl值 = 两个子树的wpl值（权重在子树内的路径和） + 两个子树的权重和（权重又在父子节点间有1的路径长）； //因此不需要构建huffman树，只需要保存上述两个数值，其中子树的权重和保存在堆中，wpl变量保存子树的wpl值，同时用于累加 int wpl = 0; for (int i = 1; i < size; ++i) { int weight1 = deleteMin(heap); int weight2 = deleteMin(heap); wpl += weight1 + weight2; insertMinHeap(heap, weight1 + weight2); } return wpl; } int isPrefix(char *s1, char *s2) { //判断两个字符串是否属于前缀码关系 while (s1 && s2 && *s1 == *s2) //循环至第一个不相同的字母或结束位置 ++s1, ++s2; if (*s1 == '\0' || *s2 == '\0') //如果此时有一个到达结束位置，说明这个字符串一定是另一个字符串的前缀 return 1; else return 0; } int hasPrefixCode(char s[][200], int n) {//判断n个字符串是否含有前缀码 for (int i = 0; i < n; ++i) for (int j = i + 1; j < n; ++j) if (isPrefix(s[i], s[j])) //两两做对比 return 1; return 0; } int main() { freopen("test.txt", "r", stdin); int n; scanf("%d", &n); int freq[256] = {}; for (int i = 0; i < n; ++i) { char ch; int num; getchar(); scanf("%c%d", &ch, &num); freq[ch] = num; } int wpl = calWPL(freq); //模拟构建huffman树过程计算WPL（加权路径长） int k; //k个测试用例 scanf("%d", &k); while (k--) { char ch[256]; char s[256][200]; int thisWPL = 0; for (int i = 0; i < n; ++i) { scanf("\n%c %s", &ch[i], s[i]); thisWPL += freq[ch[i]] * strlen(s[i]); //根据编码累加加权路径长 } if (thisWPL == wpl && !hasPrefixCode(s, n)) //同时满足加权路径长最短和不含前缀码，则满足huffman编码 printf("Yes\n"); else printf("No\n"); } return 0; }
题目链接：http://www.patest.cn/contests/mooc-ds/04-%E6%A0%916