using System;
using System.Collections.Generic;
using Advanced.Algorithms.DataStructures;
namespace Advanced.Algorithms.Compression;
///
/// A huffman coding implementation using Fibonacci Min Heap.
///
public class HuffmanCoding
{
///
/// Returns a dictionary of chosen encoding bytes for each distinct T.
///
public Dictionary Compress(T[] input)
{
var frequencies = ComputeFrequency(input);
var minHeap = new BHeap();
foreach (var frequency in frequencies)
minHeap.Insert(new FrequencyWrap(
frequency.Key, frequency.Value));
while (minHeap.Count > 1)
{
var a = minHeap.Extract();
var b = minHeap.Extract();
var newNode = new FrequencyWrap(
default, a.Frequency + b.Frequency);
newNode.Left = a;
newNode.Right = b;
minHeap.Insert(newNode);
}
var root = minHeap.Extract();
var result = new Dictionary();
Dfs(root, new List(), result);
return result;
}
///
/// Now gather the codes.
///
private void Dfs(FrequencyWrap currentNode, List pathStack, Dictionary result)
{
if (currentNode.IsLeaf)
{
result.Add(currentNode.Item, pathStack.ToArray());
return;
}
if (currentNode.Left != null)
{
pathStack.Add(0);
Dfs(currentNode.Left, pathStack, result);
pathStack.RemoveAt(pathStack.Count - 1);
}
if (currentNode.Right != null)
{
pathStack.Add(1);
Dfs(currentNode.Right, pathStack, result);
pathStack.RemoveAt(pathStack.Count - 1);
}
}
///
/// Computes frequencies of each of T in given input.
///
private Dictionary ComputeFrequency(T[] input)
{
var result = new Dictionary();
foreach (var item in input)
{
if (!result.ContainsKey(item))
{
result.Add(item, 1);
continue;
}
result[item]++;
}
return result;
}
private class FrequencyWrap : IComparable
{
public FrequencyWrap(T item, int frequency)
{
Item = item;
Frequency = frequency;
}
public T Item { get; }
public int Frequency { get; }
public FrequencyWrap Left { get; set; }
public FrequencyWrap Right { get; set; }
public bool IsLeaf => Left == null && Right == null;
public int CompareTo(object obj)
{
return Frequency.CompareTo(((FrequencyWrap)obj).Frequency);
}
}
}