Design, analyze and implement the algorithm of computing Huffman code. Input: 26
ID: 3762988 • Letter: D
Question
Design, analyze and implement the algorithm of computing Huffman code. Input: 26 English characters (your can add some other characters, such as space, ",", ",") and their frequencies (the sum of the frequencies is 100). Output: Huffman codewords of each character. Build Huffman code tree In-order transversal the tree to get the codewords First encoding, and then, decoding a text file using the Huffman codewords (the output of the Task 1). Input: a text file consists of the characters in Task 1 Output: Encoded the text file and decoded it back. Requirements Design the algorithms for Task 1 and Task 2. Two data structures have to be used in the algorithm for Task 1. One is a priority queue Q. Each node in Q is the root of a binary tree which keeps Huffman codewords. Analyze the time complexity of each algorithm using O-notation. Note that the time complexity depends on the implementation of the data structures. Implement the algorithms using C#. A simple user interface has to be contained. That is, the user can input the set of characters and their frequencies, and output the Huffman code of each character. Also, they can encode and decode a text file. Submission Project description. Algorithms. Algorithm analysis. Experiment output. Code.Explanation / Answer
#include <stdio.h>
#include <stdlib.h>
// This constant can be avoided by explicitly calculating height of Huffman Tree
#define MAX_TREE_HT 100
// A Huffman tree node
struct MinHeapNode
{
char data; // One of the input characters
unsigned freq; // Frequency of the character
struct MinHeapNode *left, *right; // Left and right child of this node
};
// A Min Heap: Collection of min heap (or Hufmman tree) nodes
struct MinHeap
{
unsigned size; // Current size of min heap
unsigned capacity; // capacity of min heap
struct MinHeapNode **array; // Attay of minheap node pointers
};
// 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));
minHeap->size = 0; // current size is 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 funvtion 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)
printf("%d", arr[i]);
printf(" ");
}
// 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))
{
printf("%c: ", 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 program to test above functions
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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