Add Huffman Compression (#2753)
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135
Others/Huffman.java
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135
Others/Huffman.java
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import java.util.PriorityQueue;
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import java.util.Scanner;
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import java.util.Comparator;
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// node class is the basic structure
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// of each node present in the Huffman - tree.
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class HuffmanNode {
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int data;
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char c;
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HuffmanNode left;
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HuffmanNode right;
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}
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// comparator class helps to compare the node
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// on the basis of one of its attribute.
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// Here we will be compared
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// on the basis of data values of the nodes.
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class MyComparator implements Comparator<HuffmanNode> {
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public int compare(HuffmanNode x, HuffmanNode y)
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{
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return x.data - y.data;
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}
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}
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public class Huffman {
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// recursive function to print the
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// huffman-code through the tree traversal.
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// Here s is the huffman - code generated.
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public static void printCode(HuffmanNode root, String s)
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{
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// base case; if the left and right are null
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// then its a leaf node and we print
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// the code s generated by traversing the tree.
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if (root.left
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== null
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&& root.right
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== null
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&& Character.isLetter(root.c)) {
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// c is the character in the node
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System.out.println(root.c + ":" + s);
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return;
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}
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// if we go to left then add "0" to the code.
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// if we go to the right add"1" to the code.
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// recursive calls for left and
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// right sub-tree of the generated tree.
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printCode(root.left, s + "0");
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printCode(root.right, s + "1");
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}
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// main function
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public static void main(String[] args)
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{
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Scanner s = new Scanner(System.in);
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// number of characters.
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int n = 6;
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char[] charArray = { 'a', 'b', 'c', 'd', 'e', 'f' };
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int[] charfreq = { 5, 9, 12, 13, 16, 45 };
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// creating a priority queue q.
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// makes a min-priority queue(min-heap).
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PriorityQueue<HuffmanNode> q
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= new PriorityQueue<HuffmanNode>(n, new MyComparator());
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for (int i = 0; i < n; i++) {
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// creating a Huffman node object
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// and add it to the priority queue.
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HuffmanNode hn = new HuffmanNode();
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hn.c = charArray[i];
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hn.data = charfreq[i];
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hn.left = null;
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hn.right = null;
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// add functions adds
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// the huffman node to the queue.
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q.add(hn);
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}
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// create a root node
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HuffmanNode root = null;
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// Here we will extract the two minimum value
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// from the heap each time until
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// its size reduces to 1, extract until
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// all the nodes are extracted.
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while (q.size() > 1) {
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// first min extract.
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HuffmanNode x = q.peek();
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q.poll();
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// second min extarct.
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HuffmanNode y = q.peek();
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q.poll();
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// new node f which is equal
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HuffmanNode f = new HuffmanNode();
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// to the sum of the frequency of the two nodes
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// assigning values to the f node.
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f.data = x.data + y.data;
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f.c = '-';
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// first extracted node as left child.
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f.left = x;
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// second extracted node as the right child.
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f.right = y;
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// marking the f node as the root node.
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root = f;
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// add this node to the priority-queue.
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q.add(f);
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}
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// print the codes by traversing the tree
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printCode(root, "");
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}
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}
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