source: branches/2971_named_intervals/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionConstraintAnalyzer.cs @ 16590

#region License Information

/* HeuristicLab
 * Copyright (C) 2002-2018 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.Linq;
using HeuristicLab.Analysis;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
  [StorableClass]
  public class SymbolicRegressionConstraintAnalyzer : SingleSuccessorOperator, IAnalyzer {
    private const string ResultCollectionParameterName = "Results";
    private const string RegressionSolutionQualitiesResultName = "Constraint Violations";


    public ILookupParameter<ResultCollection> ResultCollectionParameter {
      get { return (ILookupParameter<ResultCollection>)Parameters[ResultCollectionParameterName]; }
    }


    public virtual bool EnabledByDefault {
      get { return false; }
    }

    [StorableConstructor]
    protected SymbolicRegressionConstraintAnalyzer(bool deserializing) : base(deserializing) {
    }

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

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

    public SymbolicRegressionConstraintAnalyzer() {
      Parameters.Add(new LookupParameter<ResultCollection>(ResultCollectionParameterName,
        "The result collection to store the analysis results."));

    }

    [StorableHook(HookType.AfterDeserialization)]
    private void AfterDeserialization() {
      // BackwardsCompatibility3.3
    }

    public override IOperation Apply() {
      var results = ResultCollectionParameter.ActualValue;
      IntervalConstraintsParser parser = new IntervalConstraintsParser();
      var intervalInterpreter = new IntervalInterpreter();
      if (!results.ContainsKey(RegressionSolutionQualitiesResultName)) {
        var newDataTable = new DataTable(RegressionSolutionQualitiesResultName);
        results.Add(new Result(RegressionSolutionQualitiesResultName, "Chart displaying the constraint violatoins.",
          newDataTable));
      }

      var dataTable = (DataTable)results[RegressionSolutionQualitiesResultName].Value;

      foreach (var result in results.Where(r => r.Value is IRegressionSolution)) {
        var solution = (ISymbolicRegressionSolution)result.Value;
        var constraints =
          parser.Parse(((RegressionProblemData)solution.ProblemData).IntervalConstraintsParameter.Value.Value);
        var variableRanges = ((RegressionProblemData)solution.ProblemData).VariableRangesParameter.Value
          .VariableIntervals;

        if (dataTable.Rows.Count == 0) {
          foreach (var constraint in constraints) {
            if (!dataTable.Rows.ContainsKey(constraint.Derivaiton)) {
              dataTable.Rows.Add(new DataRow(constraint.Derivaiton));
            }
          }
        }

        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 numberOfViolations = dataTable.Rows[constraint.Derivaiton].Values.Count > 0
            ? dataTable.Rows[constraint.Derivaiton].Values.Last()
            : 0;
          if (!constraint.IsDerivation) {
            var res = intervalInterpreter.GetSymbolicExressionTreeInterval(solution.Model.SymbolicExpressionTree,
              variableRanges);
            if (!IntervalInBoundaries(constraint.Interval, res, constraint.InclusiveLowerBound,
              constraint.InclusiveUpperBound)) {
              dataTable.Rows[constraint.Derivaiton].Values.Add(numberOfViolations + 1);
            } else {
              dataTable.Rows[constraint.Derivaiton].Values.Add(numberOfViolations);
            }
          } else {
            var tree = solution.Model.SymbolicExpressionTree;
            for (var i = 0; i < constraint.NumberOfDerivation; ++i) {
              tree = DerivativeCalculator.Derive(tree, constraint.Variable);
            }

            var res = intervalInterpreter.GetSymbolicExressionTreeInterval(solution.Model.SymbolicExpressionTree,
              variableRanges);
            if (!IntervalInBoundaries(constraint.Interval, res, constraint.InclusiveLowerBound,
              constraint.InclusiveUpperBound)) {
              dataTable.Rows[constraint.Derivaiton].Values.Add(numberOfViolations + 1);
            } else {
              dataTable.Rows[constraint.Derivaiton].Values.Add(numberOfViolations);
            }
          }
        }

      }
      return base.Apply();
    }

    private static bool IntervalInBoundaries(Interval i1, Interval i2, bool inclusiveLower, bool inclusiveUpper) {
      if (double.IsNegativeInfinity(i1.LowerBound) && double.IsPositiveInfinity(i1.UpperBound))
        return true;
      //Left-unbounded and right-bounded:
      if (double.IsNegativeInfinity(i1.LowerBound)) {
        if (inclusiveUpper)
          return i2.LowerBound <= i1.UpperBound && i2.UpperBound <= i1.UpperBound;
        return i2.LowerBound < i1.UpperBound && i2.UpperBound < i1.UpperBound;
      }

      //Left-bounded and right-unbounded:
      if (double.IsPositiveInfinity(i1.UpperBound)) {
        if (inclusiveLower)
          return i2.LowerBound >= i1.LowerBound && i2.UpperBound >= i1.LowerBound;
        return i2.LowerBound > i1.LowerBound && i2.UpperBound > i1.LowerBound;
      }

      //Proper and bounded:
      //Closed:
      if (inclusiveLower && inclusiveUpper) {
        return i1.LowerBound <= i2.LowerBound && i2.UpperBound <= i1.UpperBound;
      }

      //Open:
      if (!inclusiveLower && !inclusiveUpper) {
        return i1.LowerBound < i2.LowerBound && i2.UpperBound < i1.UpperBound;
      }

      //Left-closed, right-open:
      if (inclusiveLower) {
        return i1.LowerBound <= i2.LowerBound && i2.UpperBound < i1.UpperBound;
      }

      //Left-open, right-closed:
      return i1.LowerBound < i2.LowerBound && i2.UpperBound <= i1.UpperBound;
    }
  }
}