HuffmanCoding.java

import java.util.PriorityQueue; 
import java.util.Scanner; 
import java.util.Comparator; 

// Implementation of Hoffman Coding algoritms.
class HuffmanNode { 

	int data; 
	char c;
	HuffmanNode left; 
	HuffmanNode right; 
} 

// comparator class helps to compare the node 
// on the basis of one of its attribute. 
// Here we will be compared 
// on the basis of data values of the nodes. 
class MyComparator implements Comparator<HuffmanNode> { 
	public int compare(HuffmanNode x, HuffmanNode y) 
	{ 

		return x.data - y.data; 
	} 
} 

public class Huffman { 

	// recursive function to print the 
	// huffman-code through the tree traversal. 
	// Here s is the huffman - code generated. 
	public static void printCode(HuffmanNode root, String s) 
	{ 

		// base case; if the left and right are null 
		// then its a leaf node and we print 
		// the code s generated by traversing the tree. 
		if (root.left == null && root.right == null && Character.isLetter(root.c)) { 
			// c is the character in the node 
			System.out.println(root.c + ":" + s); 
			return; 
		} 

		// if we go to left then add "0" to the code. 
		// if we go to the right add"1" to the code. 

		// recursive calls for left and 
		// right sub-tree of the generated tree. 
		printCode(root.left, s + "0"); 
		printCode(root.right, s + "1"); 
	} 

	// main function 
	public static void main(String[] args) 
	{ 

		Scanner s = new Scanner(System.in);
		// number of characters. 
		int n = 6; 
		char[] charArray = { 'a', 'b', 'c', 'd', 'e', 'f' }; 
		int[] charfreq = { 5, 9, 12, 13, 16, 45 }; 

		// creating a priority queue q. 
		// makes a min-priority queue(min-heap). 
		PriorityQueue<HuffmanNode> q 
			= new PriorityQueue<HuffmanNode>(n, new MyComparator()); 

		for (int i = 0; i < n; i++) { 

			// creating a huffman node object 
			// and adding it to the priority-queue. 
			HuffmanNode hn = new HuffmanNode(); 

			hn.c = charArray[i]; 
			hn.data = charfreq[i]; 

			hn.left = null; 
			hn.right = null; 

			// add functions adds 
			// the huffman node to the queue. 
			q.add(hn); 
		} 

		// create a root node 
		HuffmanNode root = null; 

		// Here we will extract the two minimum value 
		// from the heap each time until 
		// its size reduces to 1, extract until 
		// all the nodes are extracted. 
		while (q.size() > 1) { 

			// first min extract. 
			HuffmanNode x = q.peek(); 
			q.poll(); 

			// second min extarct. 
			HuffmanNode y = q.peek(); 
			q.poll(); 

			// new node f which is equal 
			HuffmanNode f = new HuffmanNode(); 

			// to the sum of the frequency of the two nodes 
			// assigning values to the f node. 
			f.data = x.data + y.data; 
			f.c = '-'; 

			// first extracted node as left child. 
			f.left = x; 

			// second extracted node as the right child. 
			f.right = y; 

			// marking the f node as the root node. 
			root = f; 

			// add this node to the priority-queue. 
			q.add(f); 
		} 

		// print the codes by traversing the tree 
		printCode(root, ""); 
	} 
}