#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 HEAL.Attic;
using HeuristicLab.Analysis;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;

namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
  [StorableType("4318C6BD-E0A1-45FE-AC30-96E7F73B51FB")]
  public class SymbolicRegressionConstraintAnalyzer : SymbolicDataAnalysisAnalyzer, ISymbolicExpressionTreeAnalyzer {
    private const string ConstraintViolationsResultName = "Constraint Violations";
    private const string ProblemDataParameterName = "ProblemData";

    #region parameter properties
    public ILookupParameter<IRegressionProblemData> RegressionProblemDataParameter {
      get { return (ILookupParameter<IRegressionProblemData>) Parameters[ProblemDataParameterName]; }
    }
    #endregion

    public override bool EnabledByDefault => false;

    [StorableConstructor]
    protected SymbolicRegressionConstraintAnalyzer(StorableConstructorFlag _) : base(_) {
    }

    protected SymbolicRegressionConstraintAnalyzer(SymbolicRegressionConstraintAnalyzer original, Cloner cloner) : base(original, cloner) {
    }

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

    public SymbolicRegressionConstraintAnalyzer() : base(){
      Parameters.Add(new LookupParameter<IRegressionProblemData>(ProblemDataParameterName, "The problem data of the symbolic data analysis problem."));
    }

    [StorableHook(HookType.AfterDeserialization)]
    private void AfterDeserialization() {
    }

    public override IOperation Apply() {
      var problemData = RegressionProblemDataParameter.ActualValue;
      var trees = SymbolicExpressionTreeParameter.ActualValue;

      var results = ResultCollectionParameter.ActualValue;
      var constraints = problemData.IntervalConstraints.Constraints.Where(x => x.Enabled);
      var variableRanges = problemData.VariableRanges.VariableIntervals;

      if (!results.ContainsKey(ConstraintViolationsResultName)) {
        var newDataTable = new DataTable(ConstraintViolationsResultName);
          foreach (var constraint in constraints) {
              newDataTable.Rows.Add(new DataRow(constraint.Expression));
        }
        results.Add(new Result(ConstraintViolationsResultName, "Chart displaying the constraint violations.", newDataTable));
      }
      var dataTable = (DataTable)results[ConstraintViolationsResultName].Value;

      var interpreter = new IntervalInterpreter();
      foreach (var constraint in constraints) {
        int violations = 0;
        foreach (var tree in trees) {
          var satisfied = SymbolicRegressionConstraintAnalyzer.ConstraintSatisfied(constraint, interpreter, variableRanges, tree);
          if (!satisfied) violations++;
        }
        dataTable.Rows[constraint.Expression].Values.Add(violations);
      }
      

      return base.Apply();
    }

    public static bool ConstraintSatisfied(IntervalConstraint constraint, IntervalInterpreter intervalInterpreter,
      IDictionary<string, Interval> variableRanges, ISymbolicExpressionTree solution) {

      if (constraint.Variable != null && !variableRanges.ContainsKey(constraint.Variable))
        throw new ArgumentException($"The given variable {constraint.Variable} in the constraint does not exists in the model.", nameof(IntervalConstraintsParser));

      Interval resultInterval;

      if (!constraint.IsDerivation) {
        resultInterval = intervalInterpreter.GetSymbolicExpressionTreeInterval(solution, variableRanges);
      } else {
        var tree = solution;
        for (var i = 0; i < constraint.NumberOfDerivation; ++i) {
          tree = DerivativeCalculator.Derive(tree, constraint.Variable);
        }
        resultInterval = intervalInterpreter.GetSymbolicExpressionTreeInterval(tree, variableRanges);
      }

      var satisfied = constraint.Interval.Contains(resultInterval, constraint.InclusiveLowerBound, constraint.InclusiveUpperBound);
      return satisfied;
    }

    public static bool ConstraintsSatisfied(IEnumerable<IntervalConstraint> constraints, IDictionary<string, Interval> variableRanges, ISymbolicExpressionTree solution) {
      var intervalInterpreter = new IntervalInterpreter();
      foreach (var constraint in constraints) {
        if (constraint.Variable != null && !variableRanges.ContainsKey(constraint.Variable))
          throw new ArgumentException($"The given variable {constraint.Variable} in the constraint does not exists in the model.", nameof(IntervalConstraintsParser));

        var satisfied = ConstraintSatisfied(constraint, intervalInterpreter, variableRanges, solution);
        if (!satisfied) return false;
      }
      return true;
    }
  }
}