05-树9 Huffman Codes(30 分)
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 an non-empty string of no more than 63 ‘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.
Note: The optimal solution is not necessarily generated by Huffman algorithm. Any prefix code with code length being optimal is considered correct.
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 11
Sample Output:
Yes
Yes
No
No
这一题看似复杂实际上要做两件事:
1. 计算出哈夫曼编码WPL
2. 计算学生方案的WPL
3. 比较,不合格就滚,合格再判断是否是前缀码。
我的码一直不太清楚priority_queue
怎么用在建立哈夫曼树上,所以自建了一些轮子,略长:
#include <iostream>
#include <map>
#include <string>
#include <vector>
#include <algorithm>
#include <cstdlib>
//#define LOCAL
//#include <vector>
typedef struct {
int weight;//权重
int parent;//父节点
int lchild;//左孩子
int rchild;//右孩子
}HTNode, *HuffmanTree;
int Min(HuffmanTree HT, int k)
{
int i = 0;
int min; //存weight最小且parent为-1的元素的序号
int min_weight; //存weight最小且parent为-1的元素的weight值
//先将第一个parent为-1的元素的weight值赋给min_weight,留作以后比较用。
//注意,这里不能按照一般的做法,先直接将HT[0].weight赋给min_weight,
//因为如果HT[0].weight的值比较小,那么在第一次构造二叉树时就会被选走,
//而后续的每一轮选择最小权值构造二叉树的比较还是先用HT[0].weight的值来进行判断,
//这样又会再次将其选走,从而产生逻辑上的错误。
while (HT[i].parent != -1)
i++;
min_weight = HT[i].weight;
min = i;
//选出weight最小且parent为-1的元素,并将其序号赋给min
for (;i<k;i++)
{
if (HT[i].weight<min_weight && HT[i].parent == -1)
{
min_weight = HT[i].weight;
min = i;
}
}
//选出weight最小的元素后,将其parent置1,使得下一次比较时将其排除在外。
HT[min].parent = 1;
return min;
}
void select_minium(HuffmanTree HT, int k, int &min1, int &min2)
{
min1 = Min(HT, k);
min2 = Min(HT, k);
}
HuffmanTree Create_tree(int wet[], int n) {
int total = 2 * n - 1;
HuffmanTree ht = (HuffmanTree)malloc(sizeof(HTNode)*(2 * n - 1));
//ht[0]```ht[n-1]存放叶结点
int i;
for (i = 0; i<n; ++i) {
ht[i].parent = -1;
ht[i].lchild = -1;
ht[i].rchild = -1;
ht[i].rchild = -1;
ht[i].weight = *wet++;
}
//n```2n-2为其他
for (;i<total;i++)
{
ht[i].parent = -1;
ht[i].lchild = -1;
ht[i].rchild = -1;
ht[i].weight = 0;
}
int min1, min2;
// priority_queue<int, vector<int>, greater<int> > q;
// for(int i=0; i<n; ++i) {
// q.push(ht[i].weight);
// }
for (int i = n; i<total; ++i) {
select_minium(ht, i, min1, min2);
ht[min1].parent = i;
ht[min2].parent = i;
ht[i].lchild = min1;
ht[i].rchild = min2;
ht[i].weight = ht[min1].weight + ht[min2].weight;
}
return ht;
}
int find_bits(HuffmanTree HT, int n) {
int bits = 0;
for (int i = 0; i<n; ++i) {
int now = i;
while (HT[now].parent != -1) {
now = HT[now].parent;
bits += HT[i].weight;
};
}
return bits;
}
bool isLeagal(std::vector<std::string> v) {
for (auto i = v.cbegin(); i != v.cend(); ++i) {
//std::cout << *i << '\n';
for (auto j = v.cbegin(); j != v.cend(); ++j) {
if (i == j) continue;
if ((*j).find((*i)) == 0) {
//std::cout << *j << " " << *i;
return false;
}
}
}
return true;
}
int main()
{
// #ifdef LOCAL
// freopen("test.txt", "r", stdin);
// #endif
int n, bits;
scanf("%d", &n);
getchar();
std::map<char, int> char_wei;
// char data[n];
//int weight[n];
int* weight = (int *)malloc(sizeof(int)*n);
for (int i = 0; i<n; ++i) {
char tmp1;
int tmp2;
scanf("%c %d", &tmp1, &tmp2);
weight[i] = tmp2;
char_wei[tmp1] = tmp2;
getchar();
}
HuffmanTree tree = Create_tree(weight, n);
bits = find_bits(tree, n);
int m;
scanf("%d", &m);
std::vector<std::string> allCode;
getchar();
while (m--) {
char tmpc;
std::string code;
int sbits = 0;
for (int i = 0; i<n; ++i) {
scanf("%c", &tmpc);
std::cin >> code;
allCode.push_back(code);
sbits += code.length() * char_wei[tmpc];
getchar();
}
/*printf("%d\n", bits);
printf("%d\n", sbits);*/
if (sbits == bits && isLeagal(allCode)) printf("Yes\n");
else printf("No\n");
allCode.resize(0);
}
//for (int i = 0; i < 2*n-1; ++i) {
// printf("%d %d ",i, tree[i].parent);
//}
return 0;
}
第一次没把LOCAL变量删除,所以全错,导致心态爆炸,没继续看了。。。