问题
My Huffman tree which I had asked about earlier has another problem! Here is the code:
package huffman;
import java.io.FileNotFoundException;
import java.io.FileReader;
import java.util.ArrayList;
import java.util.PriorityQueue;
import java.util.Scanner;
public class Huffman {
public ArrayList<Frequency> fileReader(String file)
{
ArrayList<Frequency> al = new ArrayList<Frequency>();
Scanner s;
try {
s = new Scanner(new FileReader(file)).useDelimiter("");
while (s.hasNext())
{
boolean found = false;
int i = 0;
String temp = s.next();
while(!found)
{
if(al.size() == i && !found)
{
found = true;
al.add(new Frequency(temp, 1));
}
else if(temp.equals(al.get(i).getString()))
{
int tempNum = al.get(i).getFreq() + 1;
al.get(i).setFreq(tempNum);
found = true;
}
i++;
}
}
} catch (FileNotFoundException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
return al;
}
public Frequency buildTree(ArrayList<Frequency> al)
{
Frequency r = al.get(1);
PriorityQueue<Frequency> pq = new PriorityQueue<Frequency>();
for(int i = 0; i < al.size(); i++)
{
pq.add(al.get(i));
}
/*while(pq.size() > 0)
{
System.out.println(pq.remove().getString());
}*/
for(int i = 0; i < al.size() - 1; i++)
{
Frequency p = pq.remove();
Frequency q = pq.remove();
int temp = p.getFreq() + q.getFreq();
r = new Frequency(null, temp);
r.left = p;
r.right = q;
pq.add(r); // put in the correct place in the priority queue
}
pq.remove(); // leave the priority queue empty
return(r); // this is the root of the tree built
}
public void inOrder(Frequency top)
{
if(top == null)
{
return;
}
else
{
inOrder(top.left);
System.out.print(top.getString() +", ");
inOrder(top.right);
return;
}
}
public void printFreq(ArrayList<Frequency> al)
{
for(int i = 0; i < al.size(); i++)
{
System.out.println(al.get(i).getString() + "; " + al.get(i).getFreq());
}
}
}
What needs to be done now is I need to create a method that will search through the tree to find the binary code (011001 etc) to the specific character. What is the best way to do this? I thought maybe I would do a normal search through the tree as if it were an AVL tree going to the right if its bigger or left if it's smaller.
But because the nodes don't use ints doubles etc. but only using objects that contain characters as strings or null to signify its not a leaf but only a root. The other option would be to do an in-order run through to find the leaf that I'm looking for but at the same time how would I determine if I went right so many times or left so many times to get the character.
package huffman;
public class Frequency implements Comparable {
private String s;
private int n;
public Frequency left;
public Frequency right;
Frequency(String s, int n)
{
this.s = s;
this.n = n;
}
public String getString()
{
return s;
}
public int getFreq()
{
return n;
}
public void setFreq(int n)
{
this.n = n;
}
@Override
public int compareTo(Object arg0) {
Frequency other = (Frequency)arg0;
return n < other.n ? -1 : (n == other.n ? 0 : 1);
}
}
What I'm trying to do is find the binary code to actually get to each character. So if I were trying to encode aabbbcccc how would I create a string holding the binary code for a going left is 0 and going right is 1.
What has me confused is because you can't determine where anything is because the tree is obviously unbalanced and there is no determining if a character is right or left of where you are. So you have to search through the whole tree but if you get to a node that isn't what you are looking for, you have backtrack to another root to get to the other leaves.
回答1:
Traverse through the huffman tree nodes to get a map like {'a': "1001", 'b': "10001"} etc. You can use this map to get the binary code to a specific character.
If you need to do in reverse, just handle it as a state machine:
state = huffman_root
for each bit
if (state.type == 'leaf')
output(state.data);
state = huffman_root
state = state.leaves[bit]
Honestly said, I didn't look into your code. It ought be pretty obvious what to do with the fancy tree.
回答2:
Remember, if you have 1001, you will never have a 10010 or 10011. So your basic method looks like this (in pseudocode):
if(input == thisNode.key) return thisNode.value
if(input.endsWith(1)) return search(thisNode.left)
else return search(thisNode.right)
I didn't read your program to figure out how to integrate it, but that's a key element of huffman encoding in a nutshell
Try something like this - you're trying to find token. So if you wanted to find the String for "10010", you'd do search(root,"10010")
String search(Frequency top, String token) {
return search(top,token,0);
}
// depending on your tree, you may have to switch top.left and top.right
String search(Frequency top, String token, int depth) {
if(token.length() == depth) return "NOT FOUND";
if(token.length() == depth - 1) return top.getString();
if(token.charAt(depth) == '0') return search(top.left,token,depth+1);
else return search(top.right,token,depth+1);
}
回答3:
I considered two options when I was having a go at Huffman coding encoding tree.
option 1: use pointer based binary tree. I coded most of this and then felt that, to trace up the tree from the leaf to find an encoding, I needed parent pointers. other wise, like mentioned in this post, you do a search of the tree which is not a solution to finding the encoding straight away. The disadvantage of the pointer based tree is that, I have to have 3 pointers for every node in the tree which I thought was too much. The code to follow the pointers is simple but more complicated that in option 2.
option 2: use an array based tree to represent the encoding tree that you will use on the run to encode and decode. so if you want the encoding of a character, you find the character in the array. Pretty straight forward, I use a table so smack right and there I get the leaf. now I trace up to the root which is at index 1 in the array. I do a (current_index / 2) for the parent. if child index is parent /2 it is a left and otherwise right.
option 2 was pretty easy to code up and although the array can have a empty spaces. I thought it was better in performance than a pointer based tree. Besides identifying the root and leaf now is a matter of indices rather than object type. ;) This will also be very usefull if you have to send your tree!?
also, you dont search (root, 10110) while decoding the Huffman code. You just walk the tree through the stream of encoded bitstream, take a left or right based on your bit and when you reach the leaf, you output the character.
Hope this was helpful.
Harisankar Krishna Swamy (example)
回答4:
I guess your homework is either done or very late by now, but maybe this will help someone else.
It's actually pretty simple. You create a tree where 0 goes right and 1 goes left. Reading the stream will navigate you through the tree. When you hit a leaf, you found a letter and start over from the beginning. Like glowcoder said, you will never have a letter on a non-leaf node. The tree also covers every possible sequence of bits. So navigating in this way always works no matter the encoded input.
I had an assignment to write an huffman encoder/decoder just like you a while ago and I wrote a blog post with the code in Java and a longer explanation : http://www.byteauthor.com/2010/09/huffman-coding-in-java/
PS. Most of the explanation is on serializing the huffman tree with the least possible number of bits but the encoding/decoding algorithms are pretty straightforward in the sources.
回答5:
Here's a Scala implementation: http://blog.flotsam.nl/2011/10/huffman-coding-done-in-scala.html
来源：https://stackoverflow.com/questions/3311432/huffman-tree-encoding