using Esiur.Analysis.Units;
using Esiur.Data;
using System;
using System.Collections;
using System.Collections.Generic;
using System.Globalization;
using System.Linq;
using System.Text;
using System.Xml.Linq;

namespace Esiur.Analysis.Coding
{
    public class Huffman : ICodec
    {

        public class Node<TKey, TValue, TFrequency>
        {
            public TKey Key { get; set; } // decision maker (bit)


            public TValue Value { get; set; } // node value
            public TFrequency Frequency { get; set; } // node / subnodes frequency

            public Dictionary<TKey, Node<TKey, TValue, TFrequency>> Branches { get; set; }


            public Node<TKey, TValue, TFrequency> Parent { get; set; }


            public override string ToString()
            {
                if (Sequence != null)
                    return $"{Key} => {Value} [{Frequency}] | {string.Join("->", Sequence)}";
                else
                    return $"{Key} => {Value} [{Frequency}]";
            }


            public TKey[]? Sequence { get; internal set; }

            public void UpdateDecisionSequence()
            {
                var parent = Parent;

                var seq = new List<TKey>() { Key };

                while (parent != null)
                {
                    seq.Add(parent.Key);
                    parent = parent.Parent;
                }

                seq.Reverse();

                Sequence = seq.ToArray();
            }
        }


        public class Tree<TKey, TValue, TFrequency>
        {

            public (uint, TValue) Decide(TKey[] sequence, uint offset)
            {
                var oOffset = offset;

                var node = Branches[sequence[offset++]];

                while (node != null && node.Branches != null && node.Branches.Count > 0)
                {
                    node = node.Branches[sequence[offset++]];
                }

                return (offset - oOffset, node.Value);
            }

            public Dictionary<TKey, Node<TKey, TValue, TFrequency>> Branches { get; }
            public Dictionary<TValue, Node<TKey, TValue, TFrequency>> Leafs { get; set; }

            public Tree(Node<TKey, TValue, TFrequency> rootNode)
            {
                Branches = rootNode.Branches;

                var leafs = new List<Node<TKey, TValue, TFrequency>>();

                GetLeafs(rootNode, leafs, new TKey[0]);

                Leafs = leafs.ToDictionary(x => x.Value, x => x);
            }

            void GetLeafs(Node<TKey, TValue, TFrequency> node, List<Node<TKey, TValue, TFrequency>> leafs, TKey[] sequence)
            {
                foreach (var branch in node.Branches)
                    if (branch.Value.Branches == null || branch.Value.Branches.Count == 0)
                    {
                        leafs.Add(branch.Value);
                        branch.Value.Sequence = sequence.Append(branch.Key).ToArray();
                    }
                    else
                    {
                        GetLeafs(branch.Value, leafs, sequence.Append(branch.Key).ToArray());
                    }
            }
        }

        public class HuffmanTable
        {
            public Dictionary<byte, BitArray> ForwardMap { get; set; } = new Dictionary<byte, BitArray>();
            public Dictionary<BitArray, byte> BackwardMap { get; set; } = new Dictionary<BitArray, byte>();
        }


        public Tree<bool, byte, int> DecisionTree { get; set; }

        public Huffman(byte[] source, uint offset, uint length)
        {
            //var freq = new int[byte.MaxValue + 1];

            var freq = new Dictionary<byte, int>();

            // var root = new Branch<bool, KeyValuePair<byte, int>>();

            // calculate probabilities
            var end = offset + length;
            for (var i = offset; i < end; i++)
                if (freq.ContainsKey(source[i]))
                    freq[source[i]]++;
                else
                    freq.Add(source[i], 1);

            var nodes = freq.OrderBy(x => x.Value).Select(x => new Node<bool, byte, int>()
            { Frequency = x.Value, Key = false, Value = x.Key }).ToList();


            //var leafs = nodes.ToList();

            while (nodes.Count() > 1)
            {
                var decision = nodes.Take(2).ToList();

                decision[1].Key = true;

                var branch = new Node<bool, byte, int>
                {
                    Branches = new Dictionary<bool, Node<bool, byte, int>>()
                    {
                        [decision[0].Key] = decision[0],
                        [decision[1].Key] = decision[1]
                    },
                    Key = false,
                    Frequency = decision[0].Frequency + decision[1].Frequency
                };

                decision[0].Parent = branch;
                decision[1].Parent = branch;

                nodes = nodes.Skip(2).Append(branch).OrderBy(x => x.Frequency).ToList();
            }

            // create tree

            DecisionTree = new Tree<bool, byte, int>(nodes[0]);

            Console.WriteLine();

        }

        public byte[] Encode(byte[] source, uint offset, uint length)
        {
            var end = offset + length;

            var seq = new List<bool>();
            for (var i = offset; i < end; i++)
            {
                seq.AddRange(DecisionTree.Leafs[source[i]].Sequence);
            }


            var str = (String.Join("", seq.Select(x => x ? "1" : "0")));

            // convert sequence to bytes
            //var bits = new BitArray(seq.ToArray());


            var rt = new byte[(seq.Count - 1) / 8 + 1];
            var dst = 0;

            for (var i = 0; i < rt.Length; i++)
            {
                for (var j = 7; j >= 0; j--)
                {
                    if (dst >= seq.Count)
                        break;

                    if (seq[dst++])
                        rt[i] |= (byte)(0x1 << j);
                }
            }

           // bits.CopyTo(rt, 0);
            return rt;
        }

        public byte[] Decode(byte[] source, uint offset, uint length)
        {

            var rt = new List<byte>();

            var bits = new bool[length * 8];
            var end = offset + length;

            

            var dst = 0;
            for (var i = offset; i < end; i++)
            {
                for (var j = 7; j >= 0; j--)
                {
                    bits[dst++] = ((source[i] >> j) & 0x1) > 0 ? true : false;
                }
            }

            uint b = 0;
            while (b < bits.Length)
            {
                var (len, value) = DecisionTree.Decide(bits, b);
                rt.Add(value);
                b += len;
            }

            return rt.ToArray();
        }
    }
}