设计一个c语言代码，基于哈夫曼树的数据压缩算法

下面是一个基于哈夫曼树的数据压缩算法的C语言代码实现：

#include <stdio.h>
#include <stdlib.h>
#include <string.h>

#define MAX_TREE_HT 100

// 哈夫曼树节点结构体
struct HuffmanNode {
    char data;
    int freq;
    struct HuffmanNode *left, *right;
};

// 哈夫曼编码结构体
struct HuffmanCode {
    char data;
    char *code;
};

// 哈夫曼树节点优先队列结构体
struct PriorityQueueNode {
    struct HuffmanNode *node;
    struct PriorityQueueNode *next;
};

// 创建哈夫曼树节点
struct HuffmanNode* createHuffmanNode(char data, int freq) {
    struct HuffmanNode* node = (struct HuffmanNode*) malloc(sizeof(struct HuffmanNode));
    node->data = data;
    node->freq = freq;
    node->left = NULL;
    node->right = NULL;
    return node;
}

// 交换两个哈夫曼树节点
void swap(struct PriorityQueueNode** a, struct PriorityQueueNode** b) {
    struct PriorityQueueNode *t = *a;
    *a = *b;
    *b = t;
}

// 判断队列是否为空
int isEmpty(struct PriorityQueueNode* root) {
    return !root;
}

// 插入哈夫曼树节点优先队列
void insert(struct PriorityQueueNode** root, struct HuffmanNode* node) {
    struct PriorityQueueNode* temp = (struct PriorityQueueNode*) malloc(sizeof(struct PriorityQueueNode));
    temp->node = node;
    temp->next = NULL;

    if (*root == NULL || (*root)->node->freq >= node->freq) {
        temp->next = *root;
        *root = temp;
    } else {
        struct PriorityQueueNode* current = *root;
        while (current->next != NULL && current->next->node->freq < node->freq) {
            current = current->next;
        }
        temp->next = current->next;
        current->next = temp;
    }
}

// 删除哈夫曼树节点优先队列的头节点
struct HuffmanNode* delete(struct PriorityQueueNode** root) {
    struct PriorityQueueNode* temp = *root;
    struct HuffmanNode* node = temp->node;
    *root = (*root)->next;
    free(temp);
    return node;
}

// 建立哈夫曼树
struct HuffmanNode* buildHuffmanTree(char data[], int freq[], int size) {
    struct HuffmanNode *left, *right, *top;
    struct PriorityQueueNode *root = NULL;

    for (int i = 0; i < size; i++) {
        insert(&root, createHuffmanNode(data[i], freq[i]));
    }

    while (!isEmpty(root) && root->next != NULL) {
        left = delete(&root);
        right = delete(&root);
        top = createHuffmanNode('$', left->node->freq + right->node->freq);
        top->left = left->node;
        top->right = right->node;
        insert(&root, top);
    }

    return delete(&root);
}

// 打印哈夫曼编码
void printHuffmanCode(struct HuffmanNode* root, char* code, int top, struct HuffmanCode codes[]) {
    if (root->left) {
        code[top] = '0';
        printHuffmanCode(root->left, code, top + 1, codes);
    }

    if (root->right) {
        code[top] = '1';
        printHuffmanCode(root->right, code, top + 1, codes);
    }

    if (!root->left && !root->right) {
        codes[root->data].data = root->data;
        codes[root->data].code = (char*) malloc(sizeof(char) * (top + 1));
        strncpy(codes[root->data].code, code, top);
        codes[root->data].code[top] = '\0';
    }
}

// 哈夫曼编码
void huffmanEncode(char data[], int freq[], int size, struct HuffmanCode codes[]) {
    struct HuffmanNode* root = buildHuffmanTree(data, freq, size);
    char code[MAX_TREE_HT];
    int top = 0;
    printHuffmanCode(root, code, top, codes);
}

// 压缩数据
void compressData(char data[], struct HuffmanCode codes[], int size) {
    FILE *fp, *fp2;
    fp = fopen("compressed.txt", "w");
    fp2 = fopen("codes.txt", "w");

    for (int i = 0; i < strlen(data); i++) {
        fprintf(fp, "%s", codes[data[i]].code);
    }

    for (int i = 0; i < size; i++) {
        if (codes[i].code != NULL) {
            fprintf(fp2, "%c %s\n", codes[i].data, codes[i].code);
        }
    }

    fclose(fp);
    fclose(fp2);
}

// 解压数据
void decompressData() {
    FILE *fp, *fp2, *fp3;
    fp = fopen("compressed.txt", "r");
    fp2 = fopen("codes.txt", "r");
    fp3 = fopen("decompressed.txt", "w");

    struct HuffmanCode codes[128];
    for (int i = 0; i < 128; i++) {
        codes[i].data = '\0';
        codes[i].code = NULL;
    }

    char d, c[100];
    while (fscanf(fp2, "%c%s\n", &d, c) != EOF) {
        codes[d].data = d;
        codes[d].code = (char*) malloc(sizeof(char) * strlen(c));
        strncpy(codes[d].code, c, strlen(c));
        codes[d].code[strlen(c)] = '\0';
    }

    fseek(fp, 0L, SEEK_END);
    long int size = ftell(fp);
    fseek(fp, 0L, SEEK_SET);

    char* compressedData = (char*) malloc(sizeof(char) * size);
    fgets(compressedData, size, fp);

    char temp[100];
    int j = 0;
    for (int i = 0; i <= strlen(compressedData); i++) {
        if (compressedData[i] == '0' || compressedData[i] == '1') {
            temp[j++] = compressedData[i];
            temp[j] = '\0';
            for (int k = 0; k < 128; k++) {
                if (codes[k].code != NULL && strcmp(temp, codes[k].code) == 0) {
                    fprintf(fp3, "%c", codes[k].data);
                    j = 0;
                    break;
                }
            }
        }
    }

    fclose(fp);
    fclose(fp2);
    fclose(fp3);
}

// 测试
int main() {
    char data[] = {'a', 'b', 'c', 'd', 'e', 'f'};
    int freq[] = {5, 9, 12, 13, 16, 45};
    int size = sizeof(data) / sizeof(data[0]);

    struct HuffmanCode codes[128];
    for (int i = 0; i < 128; i++) {
        codes[i].data = '\0';
        codes[i].code = NULL;
    }

    huffmanEncode(data, freq, size, codes);
    compressData("aaabbbbcccddeeeeffffff", codes, size);
    decompressData();

    return 0;
}

以上代码使用了哈夫曼树的算法对数据进行了压缩，压缩后的数据存储在 `compressed.txt` 文件中，哈夫曼编码存储在 `codes.txt` 文件中，解压缩后的数据存储在 `decompressed.txt` 文件中。