#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2019 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
 *
 * This file is part of HeuristicLab.
 *
 * HeuristicLab is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * HeuristicLab is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
 */
#endregion

using System;
using System.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using HEAL.Attic;
using HeuristicLab.Parameters;

namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
  [StorableType("DE6C1E1E-D7C1-4070-847E-63B68562B10C")]
  [Item("IntervalInterpreter", "Intperter for calculation of intervals of symbolic models.")]
  public sealed class IntervalInterpreter : ParameterizedNamedItem, IStatefulItem {

    private const string EvaluatedSolutionsParameterName = "EvaluatedSolutions";

    public IFixedValueParameter<IntValue> EvaluatedSolutionsParameter {
      get { return (IFixedValueParameter<IntValue>)Parameters[EvaluatedSolutionsParameterName]; }
    }

    public int EvaluatedSolutions {
      get { return EvaluatedSolutionsParameter.Value.Value; }
      set { EvaluatedSolutionsParameter.Value.Value = value; }
    }

    [StorableConstructor]
    private IntervalInterpreter(StorableConstructorFlag _) : base(_) { }
    private IntervalInterpreter(IntervalInterpreter original, Cloner cloner)
        : base(original, cloner) { }

    public IntervalInterpreter()
        : base("IntervalInterpreter", "Intperter for calculation of intervals of symbolic models.") {
      Parameters.Add(new FixedValueParameter<IntValue>(EvaluatedSolutionsParameterName, "A counter for the total number of solutions the interpreter has evaluated", new IntValue(0)));
    }

    public override IDeepCloneable Clone(Cloner cloner) {
      return new IntervalInterpreter(this, cloner);
    }

    private readonly object syncRoot = new object();

    #region IStatefulItem Members
    public void InitializeState() {
      EvaluatedSolutions = 0;
    }
    public void ClearState() { }
    #endregion

    public Interval GetSymbolicExressionTreeInterval(ISymbolicExpressionTree tree, IDataset dataset, IEnumerable<int> rows = null) {
      var variableRanges = DatasetUtil.GetVariableRanges(dataset, rows);
      return GetSymbolicExressionTreeInterval(tree, variableRanges);
    }

    public Interval GetSymbolicExressionTreeIntervals(ISymbolicExpressionTree tree, IDataset dataset,
      out Dictionary<ISymbolicExpressionTreeNode, Interval> nodeIntervals, IEnumerable<int> rows = null) {
      var variableRanges = DatasetUtil.GetVariableRanges(dataset, rows);
      return GetSymbolicExressionTreeIntervals(tree, variableRanges, out nodeIntervals);
    }

    public Interval GetSymbolicExressionTreeInterval(ISymbolicExpressionTree tree, Dictionary<string, Interval> variableRanges) {
      lock (syncRoot) {
        EvaluatedSolutions++;
      }
      int instructionCount = 0;
      var instructions = PrepareInterpreterState(tree, variableRanges);
      var outputInterval = Evaluate(instructions, ref instructionCount);

      // because of numerical errors the bounds might be incorrect
      if (outputInterval.LowerBound <= outputInterval.UpperBound)
        return outputInterval;
      else
        return new Interval(outputInterval.UpperBound, outputInterval.LowerBound);
    }


    public Interval GetSymbolicExressionTreeIntervals(ISymbolicExpressionTree tree,
      Dictionary<string, Interval> variableRanges, out Dictionary<ISymbolicExpressionTreeNode, Interval> nodeIntervals) {
      lock (syncRoot) {
        EvaluatedSolutions++;
      }
      int instructionCount = 0;
      var intervals = new Dictionary<ISymbolicExpressionTreeNode, Interval>();
      var instructions = PrepareInterpreterState(tree, variableRanges);
      var outputInterval = Evaluate(instructions, ref instructionCount, intervals);

      // fix incorrect intervals if necessary (could occur because of numerical errors)
      nodeIntervals = new Dictionary<ISymbolicExpressionTreeNode, Interval>();
      foreach(var kvp in intervals) {
        var interval = kvp.Value;
        if (interval.IsInfiniteOrUndefined || interval.LowerBound <= interval.UpperBound)
          nodeIntervals.Add(kvp.Key, interval);
        else
          nodeIntervals.Add(kvp.Key, new Interval(interval.UpperBound, interval.LowerBound));
      }

      // because of numerical errors the bounds might be incorrect
      if (outputInterval.IsInfiniteOrUndefined || outputInterval.LowerBound <= outputInterval.UpperBound)
        return outputInterval;
      else
        return new Interval(outputInterval.UpperBound, outputInterval.LowerBound);
    }


    private static Instruction[] PrepareInterpreterState(ISymbolicExpressionTree tree, Dictionary<string, Interval> variableRanges) {
      if (variableRanges == null)
        throw new ArgumentNullException("No variablew ranges are present!", nameof(variableRanges));

      //Check if all variables used in the tree are present in the dataset
      foreach (var variable in tree.IterateNodesPrefix().OfType<VariableTreeNode>().Select(n => n.VariableName).Distinct()) {
        if (!variableRanges.ContainsKey(variable)) throw new InvalidOperationException($"No ranges for variable {variable} is present");
      }

      Instruction[] code = SymbolicExpressionTreeCompiler.Compile(tree, OpCodes.MapSymbolToOpCode);
      foreach (Instruction instr in code.Where(i => i.opCode == OpCodes.Variable)) {
        var variableTreeNode = (VariableTreeNode)instr.dynamicNode;
        instr.data = variableRanges[variableTreeNode.VariableName];
      }
      return code;
    }

    private Interval Evaluate(Instruction[] instructions, ref int instructionCounter, Dictionary<ISymbolicExpressionTreeNode, Interval> nodeIntervals = null) {
      Instruction currentInstr = instructions[instructionCounter];
      //Use ref parameter, because the tree will be iterated through recursively from the left-side branch to the right side
      //Update instructionCounter, whenever Evaluate is called
      instructionCounter++;
      Interval result = null;

      switch (currentInstr.opCode) {
        //Variables, Constants, ...
        case OpCodes.Variable: {
            var variableTreeNode = (VariableTreeNode)currentInstr.dynamicNode;
            var weightInterval = new Interval(variableTreeNode.Weight, variableTreeNode.Weight);
            var variableInterval = (Interval)currentInstr.data;

            result = Interval.Multiply(variableInterval, weightInterval);
            break;
          }
        case OpCodes.Constant: {
            var constTreeNode = (ConstantTreeNode)currentInstr.dynamicNode;
            result = new Interval(constTreeNode.Value, constTreeNode.Value);
            break;
          }
        //Elementary arithmetic rules
        case OpCodes.Add: {
            result = Evaluate(instructions, ref instructionCounter, nodeIntervals);
            for (int i = 1; i < currentInstr.nArguments; i++) {
              var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
              result = Interval.Add(result, argumentInterval);
            }
            break;
          }
        case OpCodes.Sub: {
            result = Evaluate(instructions, ref instructionCounter, nodeIntervals);
            if (currentInstr.nArguments == 1)
              result = Interval.Multiply(new Interval(-1, -1), result);

            for (int i = 1; i < currentInstr.nArguments; i++) {
              var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
              result = Interval.Subtract(result, argumentInterval);
            }
            break;
          }
        case OpCodes.Mul: {
            result = Evaluate(instructions, ref instructionCounter, nodeIntervals);
            for (int i = 1; i < currentInstr.nArguments; i++) {
              var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
              result = Interval.Multiply(result, argumentInterval);
            }
            break;
          }
        case OpCodes.Div: {
            result = Evaluate(instructions, ref instructionCounter, nodeIntervals);
            if (currentInstr.nArguments == 1)
              result = Interval.Divide(new Interval(1, 1), result);

            for (int i = 1; i < currentInstr.nArguments; i++) {
              var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
              result = Interval.Divide(result, argumentInterval);
            }
            break;
          }
        //Trigonometric functions
        case OpCodes.Sin: {
            var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
            result = Interval.Sine(argumentInterval);
            break;
          }
        case OpCodes.Cos: {
            var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
            result = Interval.Cosine(argumentInterval);
            break;
          }
        case OpCodes.Tan: {
            var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
            result = Interval.Tangens(argumentInterval);
            break;
          }
        //Exponential functions
        case OpCodes.Log: {
            var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
            result = Interval.Logarithm(argumentInterval);
            break;
          }
        case OpCodes.Exp: {
            var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
            result = Interval.Exponential(argumentInterval);
            break;
          }
        case OpCodes.Power: {
            result = Evaluate(instructions, ref instructionCounter, nodeIntervals);
            for (int i = 1; i < currentInstr.nArguments; i++) {
              var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
              result = Interval.Power(result, argumentInterval);
            }
            break;
          }
        case OpCodes.Square: {
            var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
            result = Interval.Square(argumentInterval);
            break;
          }
        case OpCodes.Root: {
            result = Evaluate(instructions, ref instructionCounter, nodeIntervals);
            for (int i = 1; i < currentInstr.nArguments; i++) {
              var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
              result = Interval.Root(result, argumentInterval);
            }
            break;
          }
        case OpCodes.SquareRoot: {
            var argumentInterval = Evaluate(instructions, ref instructionCounter, nodeIntervals);
            result = Interval.SquareRoot(argumentInterval);
            break;
          }
        default:
          throw new NotSupportedException($"The tree contains the unknown symbol {currentInstr.dynamicNode.Symbol}");
      }

      if (nodeIntervals != null)
        nodeIntervals.Add(currentInstr.dynamicNode, result);

      return result;
    }

    public static bool IsCompatible(ISymbolicExpressionTree tree) {
      var containsUnknownSyumbol = (
        from n in tree.Root.GetSubtree(0).IterateNodesPrefix()
        where
          !(n.Symbol is StartSymbol) &&
          !(n.Symbol is Addition) &&
          !(n.Symbol is Subtraction) &&
          !(n.Symbol is Multiplication) &&
          !(n.Symbol is Division) &&
          !(n.Symbol is Sine) &&
          !(n.Symbol is Cosine) &&
          !(n.Symbol is Tangent) &&
          !(n.Symbol is Logarithm) &&
          !(n.Symbol is Exponential) &&
          !(n.Symbol is Power) &&
          !(n.Symbol is Square) &&
          !(n.Symbol is Root) &&
          !(n.Symbol is SquareRoot) &&
          !(n.Symbol is Problems.DataAnalysis.Symbolic.Variable) &&
          !(n.Symbol is Constant)
        select n).Any();
      return !containsUnknownSyumbol;
    }
  }
}