using System;
using System.Collections.Generic;
using System.Linq;
using HeuristicLab.Algorithms.Bandits;
using HeuristicLab.Algorithms.GrammaticalOptimization;
using HeuristicLab.Algorithms.MonteCarloTreeSearch.Base;
using HeuristicLab.Algorithms.MonteCarloTreeSearch.Simulation;
using HeuristicLab.Common;
using HeuristicLab.Problems.GrammaticalOptimization;

namespace HeuristicLab.Algorithms.MonteCarloTreeSearch
{
    public class MonteCarloTreeSearch : SolverBase
    {
        private readonly int maxLen;
        private readonly IProblem problem;
        private readonly IGrammar grammar;
        private readonly Random random;
        private readonly IBanditPolicy behaviourPolicy;
        private readonly ISimulation simulation;
        private TreeNode rootNode;

        public MonteCarloTreeSearch(IProblem problem, int maxLen, Random random, IBanditPolicy behaviourPolicy, ISimulation simulationPolicy)
        {
            this.problem = problem;
            this.grammar = problem.Grammar;
            this.maxLen = maxLen;
            this.random = random;
            this.behaviourPolicy = behaviourPolicy;
            this.simulation = simulationPolicy;
        }

        public bool StopRequested
        {
            get;
            set;
        }

        public override void Run(int maxIterations)
        {
            Reset();
            for (int i = 0; !StopRequested && i < maxIterations; i++)
            {
                TreeNode currentNode = rootNode;

                while (!currentNode.IsLeaf())
                {
                    int currentActionIndex = behaviourPolicy.SelectAction(random,
                        currentNode.GetChildActionInfos());
                    currentNode = currentNode.children[currentActionIndex];
                }

                string phrase = currentNode.phrase;

                if (!grammar.IsTerminal(phrase))
                {
                    ExpandTreeNode(currentNode);

                    currentNode =
                        currentNode.children[behaviourPolicy.SelectAction(random, currentNode.GetChildActionInfos())];
                }
                double quality = simulation.Simulate(currentNode);
                OnSolutionEvaluated(phrase, quality);

                Propagate(currentNode, quality);
            }
        }

        private void ExpandTreeNode(TreeNode treeNode)
        {
            // create children on the first visit
            if (treeNode.children == null)
            {
                treeNode.children = new List<TreeNode>();

                var phrase = new Sequence(treeNode.phrase);
                // create subnodes for each nt-symbol in phrase
                for (int i = 0; i < phrase.Length; i++)
                {
                    char symbol = phrase[i];
                    if (grammar.IsNonTerminal(symbol))
                    {
                        // create subnode for each alternative of symbol
                        foreach (Sequence alternative in grammar.GetAlternatives(symbol))
                        {
                            Sequence newSequence = new Sequence(phrase);
                            newSequence.ReplaceAt(i, 1, alternative);
                            if (newSequence.Length <= maxLen)
                            {
                                TreeNode childNode = new TreeNode(treeNode, newSequence.ToString());
                                treeNode.children.Add(childNode);
                            }
                        }
                    }
                }
            }
        }

        private void Reset()
        {
            StopRequested = false;
            bestQuality = 0.0;
            rootNode = new TreeNode(null, grammar.SentenceSymbol.ToString());
        }

        private void Propagate(TreeNode node, double quality)
        {
            var currentNode = node;
            do
            {
                currentNode.actionInfo.UpdateReward(quality);
                currentNode = currentNode.parent;
            } while (currentNode != null);
        }

        public void PrintStats()
        {
            //Console.WriteLine("depth: {0,5} tries: {1,5} best phrase {2,50} bestQ {3:F3}", maxSearchDepth, tries, bestPhrase, bestQuality);

            //// use behaviour strategy to generate the currently prefered sentence
            //var policy = behaviourPolicy;

            //var n = rootNode;

            //while (n != null)
            //{
            //    var phrase = n.phrase;
            //    Console.ForegroundColor = ConsoleColor.White;
            //    Console.WriteLine("{0,-30}", phrase);
            //    var children = n.children;
            //    if (children == null || !children.Any()) break;
            //    var values = children.Select(ch => policy.GetValue(ch.phrase));
            //    var maxValue = values.Max();
            //    if (maxValue == 0) maxValue = 1.0;

            //    // write phrases
            //    foreach (var ch in children)
            //    {
            //        SetColorForValue(policy.GetValue(ch.phrase) / maxValue);
            //        Console.Write(" {0,-4}", ch.phrase.Substring(Math.Max(0, ch.phrase.Length - 3), Math.Min(3, ch.phrase.Length)));
            //    }
            //    Console.WriteLine();

            //    // write values
            //    foreach (var ch in children)
            //    {
            //        SetColorForValue(policy.GetValue(ch.phrase) / maxValue);
            //        Console.Write(" {0:F2}", policy.GetValue(ch.phrase) * 10.0);
            //    }
            //    Console.WriteLine();

            //    // write tries
            //    foreach (var ch in children)
            //    {
            //        SetColorForValue(policy.GetValue(ch.phrase) / maxValue);
            //        Console.Write(" {0,4}", policy.GetTries(ch.phrase));
            //    }
            //    Console.WriteLine();
            //    int selectedChildIdx;
            //    if (!policy.TrySelect(random, phrase, children.Select(ch => ch.phrase), out selectedChildIdx))
            //    {
            //        break;
            //    }
            //    n = n.children[selectedChildIdx];
            //}

            //Console.ForegroundColor = ConsoleColor.White;
            //Console.WriteLine("-------------------");
        }

        private void SetColorForValue(double v)
        {
            Console.ForegroundColor = ConsoleEx.ColorForValue(v);
        }
    }
}