c语言哈夫曼编码译码

哈夫曼编码是一种用于压缩数据的技术，它的基本思想是根据数据出现的频率构建一棵二叉树，并将出现频率较高的字符编码为较短的二进制码，出现频率较低的字符编码为较长的二进制码，从而达到压缩数据的目的。哈夫曼编码的解码过程就是根据构建的二叉树进行反向遍历，将二进制码转换为原来的字符。

哈夫曼编码的具体步骤如下：
1. 统计待压缩数据中每个字符出现的频率，将其保存在一个字符频率表中。
2. 将字符频率表中的每个字符作为叶子节点，构建哈夫曼树。构建哈夫曼树的过程可以采用贪心算法，每次选取频率最小的两个节点合并。
3. 对哈夫曼树进行编码，从根节点开始遍历哈夫曼树，遇到左子节点为0，遇到右子节点为1。将每个字符的编码保存在一个编码表中。
4. 将待压缩数据中的每个字符转换为其对应的哈夫曼编码，并将所有编码拼接起来，形成压缩后的数据。

哈夫曼解码的具体步骤如下：
1. 读取压缩后的数据，并从根节点开始遍历哈夫曼树。
2. 遇到0则遍历左子节点，遇到1则遍历右子节点，直到遍历到叶子节点。
3. 根据叶子节点对应的字符进行解码，并将解码后的字符保存起来，直到所有编码都被解码完毕。

相关问题

c语言哈夫曼编码译码器课设,数据结构课程设计哈夫曼编码译码器

哈夫曼编码是一种压缩算法，它通过对原始数据进行编码，可以把数据压缩为更小的体积，从而减少存储空间和传输带宽的占用。C语言实现哈夫曼编码译码器的关键在于，需要用哈夫曼树来生成编码表，然后利用编码表来对数据进行编码和解码。

以下是一个简单的C语言实现哈夫曼编码译码器的示例代码：

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

#define MAX_TREE_HT 100

struct MinHeapNode {
    char data;
    unsigned freq;
    struct MinHeapNode *left, *right;
};

struct MinHeap {
    unsigned size;
    unsigned capacity;
    struct MinHeapNode **array;
};

struct MinHeapNode *newNode(char data, unsigned freq) {
    struct MinHeapNode *temp = (struct MinHeapNode *)malloc(sizeof(struct MinHeapNode));
    temp->left = temp->right = NULL;
    temp->data = data;
    temp->freq = freq;
    return temp;
}

struct MinHeap *createMinHeap(unsigned capacity) {
    struct MinHeap *minHeap = (struct MinHeap *)malloc(sizeof(struct MinHeap));
    minHeap->size = 0;
    minHeap->capacity = capacity;
    minHeap->array = (struct MinHeapNode **)malloc(minHeap->capacity * sizeof(struct MinHeapNode *));
    return minHeap;
}

void swapMinHeapNode(struct MinHeapNode **a, struct MinHeapNode **b) {
    struct MinHeapNode *t = *a;
    *a = *b;
    *b = t;
}

void minHeapify(struct MinHeap *minHeap, int idx) {
    int smallest = idx;
    int left = 2 * idx + 1;
    int right = 2 * idx + 2;
    if (left < minHeap->size && minHeap->array[left]->freq < minHeap->array[smallest]->freq)
        smallest = left;
    if (right < minHeap->size && minHeap->array[right]->freq < minHeap->array[smallest]->freq)
        smallest = right;
    if (smallest != idx) {
        swapMinHeapNode(&minHeap->array[smallest], &minHeap->array[idx]);
        minHeapify(minHeap, smallest);
    }
}

int isSizeOne(struct MinHeap *minHeap) {
    return (minHeap->size == 1);
}

struct MinHeapNode *extractMin(struct MinHeap *minHeap) {
    struct MinHeapNode *temp = minHeap->array[0];
    minHeap->array[0] = minHeap->array[minHeap->size - 1];
    --minHeap->size;
    minHeapify(minHeap, 0);
    return temp;
}

void insertMinHeap(struct MinHeap *minHeap, struct MinHeapNode *minHeapNode) {
    ++minHeap->size;
    int i = minHeap->size - 1;
    while (i && minHeapNode->freq < minHeap->array[(i - 1) / 2]->freq) {
        minHeap->array[i] = minHeap->array[(i - 1) / 2];
        i = (i - 1) / 2;
    }
    minHeap->array[i] = minHeapNode;
}

void buildMinHeap(struct MinHeap *minHeap) {
    int n = minHeap->size - 1;
    int i;
    for (i = (n - 1) / 2; i >= 0; --i)
        minHeapify(minHeap, i);
}

void printArr(int arr[], int n) {
    int i;
    for (i = 0; i < n; ++i)
        printf("%d", arr[i]);
    printf("\n");
}

int isLeaf(struct MinHeapNode *root) {
    return !(root->left) && !(root->right);
}

struct MinHeap *createAndBuildMinHeap(char data[], int freq[], int size) {
    struct MinHeap *minHeap = createMinHeap(size);
    int i;
    for (i = 0; i < size; ++i)
        minHeap->array[i] = newNode(data[i], freq[i]);
    minHeap->size = size;
    buildMinHeap(minHeap);
    return minHeap;
}

struct MinHeapNode *buildHuffmanTree(char data[], int freq[], int size) {
    struct MinHeapNode *left, *right, *top;
    struct MinHeap *minHeap = createAndBuildMinHeap(data, freq, size);
    while (!isSizeOne(minHeap)) {
        left = extractMin(minHeap);
        right = extractMin(minHeap);
        top = newNode('$', left->freq + right->freq);
        top->left = left;
        top->right = right;
        insertMinHeap(minHeap, top);
    }
    return extractMin(minHeap);
}

void printCodes(struct MinHeapNode *root, int arr[], int top) {
    if (root->left) {
        arr[top] = 0;
        printCodes(root->left, arr, top + 1);
    }
    if (root->right) {
        arr[top] = 1;
        printCodes(root->right, arr, top + 1);
    }
    if (isLeaf(root)) {
        printf("%c: ", root->data);
        printArr(arr, top);
    }
}

void HuffmanCodes(char data[], int freq[], int size) {
    struct MinHeapNode *root = buildHuffmanTree(data, freq, size);
    int arr[MAX_TREE_HT], top = 0;
    printCodes(root, arr, top);
}

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

这段代码定义了一个`MinHeapNode`结构体表示哈夫曼树的节点，`MinHeap`结构体表示最小堆，其中`array`数组存储了指向哈夫曼树节点的指针。`newNode`函数用于创建一个新的哈夫曼树节点，`createMinHeap`函数用于创建一个最小堆，`swapMinHeapNode`函数用于交换两个最小堆节点的位置，`minHeapify`函数用于维护最小堆的性质，`isSizeOne`函数用于判断最小堆的大小是否为1，`extractMin`函数用于取出最小堆的根节点，`insertMinHeap`函数用于插入一个新的节点到最小堆中，`buildMinHeap`函数用于构建最小堆，`printArr`函数用于打印一个整型数组，`isLeaf`函数用于判断一个节点是否为叶子节点，`createAndBuildMinHeap`函数用于创建并构建一个最小堆，`buildHuffmanTree`函数用于构建哈夫曼树，`printCodes`函数用于打印哈夫曼编码，`HuffmanCodes`函数用于生成哈夫曼编码。

你可以根据自己的需要对这段代码进行修改和补充，以实现一个完整的哈夫曼编码译码器。

用c语言哈夫曼编码和译码

以下是使用C语言实现哈夫曼编码和译码的示例代码，其中包含注释说明：

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

#define MAX_TREE_HT 100

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

// 哈夫曼树结构体
struct MinHeap {
    unsigned size;
    unsigned capacity;
    struct MinHeapNode **array;
};

// 创建一个新的哈夫曼树节点
struct MinHeapNode* newNode(char data, unsigned freq) {
    struct MinHeapNode* temp = (struct MinHeapNode*)malloc(sizeof(struct MinHeapNode));
    temp->left = temp->right = NULL;
    temp->data = data;
    temp->freq = freq;
    return temp;
}

// 创建一个新的哈夫曼树
struct MinHeap* createMinHeap(unsigned capacity) {
    struct MinHeap* minHeap = (struct MinHeap*)malloc(sizeof(struct MinHeap));
    minHeap->size = 0;
    minHeap->capacity = capacity;
    minHeap->array = (struct MinHeapNode**)malloc(minHeap->capacity * sizeof(struct MinHeapNode*));
    return minHeap;
}

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

// 维护最小堆的性质
void minHeapify(struct MinHeap* minHeap, int idx) {
    int smallest = idx;
    int left = 2 * idx + 1;
    int right = 2 * idx + 2;
    if (left < minHeap->size && minHeap->array[left]->freq < minHeap->array[smallest]->freq)
        smallest = left;
    if (right < minHeap->size && minHeap->array[right]->freq < minHeap->array[smallest]->freq)
        smallest = right;
    if (smallest != idx) {
        swapMinHeapNode(&minHeap->array[smallest], &minHeap->array[idx]);
        minHeapify(minHeap, smallest);
    }
}

// 判断堆是否只有一个节点
int isSizeOne(struct MinHeap* minHeap) {
    return (minHeap->size == 1);
}

// 从堆中取出最小的节点
struct MinHeapNode* extractMin(struct MinHeap* minHeap) {
    struct MinHeapNode* temp = minHeap->array[0];
    minHeap->array[0] = minHeap->array[minHeap->size - 1];
    --minHeap->size;
    minHeapify(minHeap, 0);
    return temp;}

// 插入一个新的节点到堆中
void insertMinHeap(struct MinHeap* minHeap, struct MinHeapNode* minHeapNode) {
    ++minHeap->size;
    int i = minHeap->size - 1;
    while (i && minHeapNode->freq < minHeap->array[(i - 1) / 2]->freq) {
        minHeap->array[i] = minHeap->array[(i - 1) / 2];
        i = (i - 1) / 2;
    }
    minHeap->array[i] = minHeapNode;
}

// 判断节点是否是叶子节点
int isLeaf(struct MinHeapNode* root) {
    return !(root->left) && !(root->right);
}

// 创建一个新的哈夫曼树
struct MinHeap* createAndBuildMinHeap(char data[], int freq[], int size) {
    struct MinHeap* minHeap = createMinHeap(size);
    for (int i = 0; i < size; ++i)
        minHeap->array[i] = newNode(data[i], freq[i]);
    minHeap->size = size;
    for (int i = (minHeap->size - 1) / 2; i >= 0; --i)
        minHeapify(minHeap, i);
    return minHeap;
}

// 构建哈夫曼树
struct MinHeapNode* buildHuffmanTree(char data[], int freq[], int size) {
    struct MinHeapNode *left, *right, *top;
    struct MinHeap* minHeap = createAndBuildMinHeap(data, freq, size);
    while (!isSizeOne(minHeap)) {
        left = extractMin(minHeap);
        right = extractMin(minHeap);
        top = newNode('$', left->freq + right->freq);
        top->left = left;
        top->right = right;
        insertMinHeap(minHeap, top);
    }
    return extractMin(minHeap);
}

// 打印哈夫曼编码
void printCodes(struct MinHeapNode* root, int arr[], int top) {
    if (root->left) {
        arr[top] = 0;
        printCodes(root->left, arr, top + 1);
    }
    if (root->right) {
        arr[top] = 1;
        printCodes(root->right, arr, top + 1);
    }
    if (isLeaf(root)) {
        printf("%c: ", root->data);
        for (int i = 0; i < top; ++i)
            printf("%d", arr[i]);
        printf("\n");
    }
}

// 哈夫曼编码主函数
void HuffmanCodes(char data[], int freq[], int size) {
    struct MinHeapNode* root = buildHuffmanTree(data, freq, size);
    int arr[MAX_TREE_HT], top = 0;
    printCodes(root, arr, top);
}

// 哈夫曼译码主函数
void decodeHuffman(struct MinHeapNode* root, char* s) {
    struct MinHeapNode* curr = root;
    while (*s) {
        if (*s == '0')
            curr = curr->left;
        else
            curr = curr->right;
        if (isLeaf(curr)) {
            printf("%c", curr->data);
            curr = root;
        }
        ++s;
    }
}

// 计算信源熵
float calculateEntropy(int freq[], int size) {
    float entropy = 0.0;
    int total = 0;
    for (int i = 0; i < size; ++i)
        total += freq[i];
    for (int i = 0; i < size; ++i) {
        float p = (float)freq[i] / total;
        entropy -= p * log2(p);
    }
    return entropy;
}

// 计算平均编码长度
float calculateAvgCodeLength(int freq[], int size, int codes[][MAX_TREE_HT]) {
    float avgCodeLength = 0.0;
    int total = 0;
    for (int i = 0; i < size; ++i)
        total += freq[i];
    for (int i = 0; i < size; ++i) {
        float p = (float)freq[i] / total;
        int len = strlen((char*)codes[i]);
        avgCodeLength += p * len;
    }
    return avgCodeLength;
}

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]);
    printf("Huffman Codes:\n");
    HuffmanCodes(data, freq, size);
    printf("\n");
    char str[] = "101010000111110101011100";
    printf("Decoded Huffman data: ");
    decodeHuffman(buildHuffmanTree(data, freq, size), str);
    printf("\n");
    printf("Entropy: %f\n", calculateEntropy(freq, size));
    int codes[size][MAX_TREE_HT];
    for (int i = 0; i < size; ++i)
        memset(codes[i], 0, sizeof(codes[i]));
    int arr[MAX_TREE_HT], top = 0;
    printCodes(buildHuffmanTree(data, freq, size), arr, top);
    printf("Average Code Length: %f\n", calculateAvgCodeLength(freq, size, codes));
    return 0;
}