组别:入门级
难度:4
哈夫曼树又称最优树,给定N个权值作为N个叶子结点,构造一棵二叉树,若该树的带权路径长度达到最小,称这样的二叉树为最优二叉树,也称为哈夫曼树(Huffman Tree)。哈夫曼树是带权路径长度最短的树,权值较大的结点离根较近。
哈夫曼编码
哈夫曼编码是一种压缩编码的编码算法,是基于哈夫曼树的一种编码方式。哈夫曼树又称为带权路径长度最短的二叉树。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 | // C++ program for Huffman Coding #include <cstdlib> #include <iostream> using namespace std; // This constant can be avoided by explicitly // calculating height of Huffman Tree #define MAX_TREE_HT 100 // A Huffman tree node struct MinHeapNode { // One of the input characters char data; // Frequency of the character unsigned freq; // Left and right child of this node struct MinHeapNode *left, *right; }; // A Min Heap: Collection of min-heap (or Huffman tree) nodes struct MinHeap { // Current size of min heap unsigned size; // capacity of min heap unsigned capacity; // Array of minheap node pointers struct MinHeapNode** array; }; // A utility function allocate a new // min heap node with given character // and frequency of the character 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; } // A utility function to create // a min heap of given capacity struct MinHeap* createMinHeap(unsigned capacity){ struct MinHeap* minHeap = (struct MinHeap*)malloc(sizeof(struct MinHeap)); // current size is 0 minHeap->size = 0; minHeap->capacity = capacity; minHeap->array = (struct MinHeapNode**)malloc( minHeap->capacity * sizeof(struct MinHeapNode*)); return minHeap; } // A utility function to swap two min heap nodes void swapMinHeapNode(struct MinHeapNode** a,struct MinHeapNode** b){ struct MinHeapNode* t = *a; *a = *b; *b = t; } // The standard minHeapify function. 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); } } // A utility function to check if size of heap is 1 or not int isSizeOne(struct MinHeap* minHeap){ return (minHeap->size == 1); } // A standard function to extract minimum value node from heap 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; } // A utility function to insert a new node to Min Heap 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; } // A standard function to build min heap void buildMinHeap(struct MinHeap* minHeap){ int n = minHeap->size - 1; int i; for (i = (n - 1) / 2; i >= 0; --i) minHeapify(minHeap, i); } // A utility function to print an array of size n void printArr(int arr[], int n){ int i; for (i = 0; i < n; ++i) cout << arr[i]; cout << "\n"; } // Utility function to check if this node is leaf int isLeaf(struct MinHeapNode* root){ return !(root->left) && !(root->right); } // Creates a min heap of capacity // equal to size and inserts all character of // data[] in min heap. Initially size of // min heap is equal to capacity 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; buildMinHeap(minHeap); return minHeap; } // The main function that builds Huffman tree struct MinHeapNode* buildHuffmanTree(char data[],int freq[], int size){ struct MinHeapNode *left, *right, *top; // Step 1: Create a min heap of capacity // equal to size. Initially, there are // modes equal to size. struct MinHeap* minHeap= createAndBuildMinHeap(data, freq, size); // Iterate while size of heap doesn't become 1 while (!isSizeOne(minHeap)) { // Step 2: Extract the two minimum // freq items from min heap left = extractMin(minHeap); right = extractMin(minHeap); // Step 3: Create a new internal // node with frequency equal to the // sum of the two nodes frequencies. // Make the two extracted node as // left and right children of this new node. // Add this node to the min heap // '$' is a special value for internal nodes, not // used top = newNode('$', left->freq + right->freq); top->left = left; top->right = right; insertMinHeap(minHeap, top); } // Step 4: The remaining node is the // root node and the tree is complete. return extractMin(minHeap); } // Prints huffman codes from the root of Huffman Tree. // It uses arr[] to store codes void printCodes(struct MinHeapNode* root, int arr[],int top){ // Assign 0 to left edge and recur if (root->left) { arr[top] = 0; printCodes(root->left, arr, top + 1); } // Assign 1 to right edge and recur if (root->right) { arr[top] = 1; printCodes(root->right, arr, top + 1); } // If this is a leaf node, then // it contains one of the input // characters, print the character // and its code from arr[] if (isLeaf(root)) { cout << root->data << ": "; printArr(arr, top); } } // The main function that builds a // Huffman Tree and print codes by traversing // the built Huffman Tree void HuffmanCodes(char data[], int freq[], int size){ // Construct Huffman Tree struct MinHeapNode* root = buildHuffmanTree(data, freq, size); // Print Huffman codes using // the Huffman tree built above int arr[MAX_TREE_HT], top = 0; printCodes(root, arr, top); } // Driver code 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; } |
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