source: branches/2971_named_intervals/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionConstraintAnalyzer.cs @ 16755

#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.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, ISymbolicDataAnalysisInterpreterOperator, ISymbolicExpressionTreeAnalyzer {
    private const string ConstraintViolationsResultName = "Constraint Violations";

    private const string ProblemDataParameterName = "ProblemData";
    private const string SymbolicDataAnalysisTreeInterpreterParameterName = "SymbolicDataAnalysisTreeInterpreter";

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

    public RegressionProblemData RegressionProblemData {
      get { return RegressionProblemDataParameter.ActualValue; }
    }

    public ISymbolicDataAnalysisExpressionTreeInterpreter Interpreter {
      get { return SymbolicDataAnalysisTreeInterpreterParameter.ActualValue; }
    }
    #endregion

    public virtual bool EnabledByDefault {
      get { return 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() {
      Parameters.Add(new LookupParameter<RegressionProblemData>(ProblemDataParameterName, "The problem data of the symbolic data analysis problem."));
      Parameters.Add(new LookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(SymbolicDataAnalysisTreeInterpreterParameterName, "The interpreter for symbolic data analysis expression trees."));
    }

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

    static Dictionary<IntervalConstraint, bool> CheckConstraints(ISymbolicExpressionTree model,
      IRegressionProblemData problemData) {
      var constraints = IntervalConstraintsParser.Parse(((RegressionProblemData)problemData).IntervalConstraints.Value);
      var constraintViolations = new Dictionary<IntervalConstraint, bool>();
      var variableRanges = ((RegressionProblemData)problemData).VariableRanges.VariableIntervals;

      foreach (var constraint in constraints) {
        if (!constraintViolations.ContainsKey(constraint)) {
          constraintViolations.Add(constraint, CheckConstraint(model, variableRanges, constraint));
        }
      }

      return constraintViolations;
    }

    static Dictionary<IntervalConstraint, bool> CheckConstraints(ISymbolicRegressionModel model,
      IRegressionProblemData problemData) {
      return CheckConstraints(model.SymbolicExpressionTree, problemData);
    }

    static bool CheckConstraint(ISymbolicExpressionTree model, Dictionary<string, Interval> variableRanges,
      IntervalConstraint constraint) {
      var intervalInterpreter = new IntervalInterpreter();
      if (constraint.Variable != null) {
        if (!constraint.IsDerivation) {
          var res = intervalInterpreter.GetSymbolicExpressionTreeInterval(model,
            variableRanges);
          if (!constraint.Interval.Contains(res, constraint.InclusiveLowerBound,
            constraint.InclusiveUpperBound)) {
            return false;
          }
        } else {
          var dTree = model;
          for (var i = 0; i < constraint.NumberOfDerivation; ++i) {
            dTree = DerivativeCalculator.Derive(dTree, constraint.Variable);
          }
          var res = intervalInterpreter.GetSymbolicExpressionTreeInterval(dTree,
            variableRanges);
          if (!constraint.Interval.Contains(res, constraint.InclusiveLowerBound,
            constraint.InclusiveUpperBound)) {
            return false;
          }
        }
      }
      return true;
    }

    static bool CheckConstraint(ISymbolicRegressionModel model, Dictionary<string, Interval> variableRanges, IntervalConstraint constraint) {
      return CheckConstraint(model.SymbolicExpressionTree, variableRanges, constraint);
    }

    public override IOperation Apply() {
      var results = ResultCollectionParameter.ActualValue;
      if (!results.ContainsKey(ConstraintViolationsResultName)) {
        var newDataTable = new DataTable(ConstraintViolationsResultName);
        results.Add(new Result(ConstraintViolationsResultName, "Chart displaying the constraint violations.",
          newDataTable));
      }
      var dataTable = (DataTable)results[ConstraintViolationsResultName].Value;
      var problemData = RegressionProblemData;
      var constraintViolations = new Dictionary<string, int>();

      var constraints = IntervalConstraintsParser.Parse(problemData.IntervalConstraints.Value);

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

      foreach (var constraint in constraints) {
        constraintViolations.Add(constraint.Expression, 0);
      }

      foreach (var tree in this.SymbolicExpressionTree) {
        var checkedConstraints = CheckConstraints(tree, problemData);

        foreach (var kvp in checkedConstraints) {
          if (!kvp.Value)
            constraintViolations[kvp.Key.Expression]++;
        }
      }

      foreach (var kvp in constraintViolations) {
        dataTable.Rows[kvp.Key].Values.Add(kvp.Value);
      }
      return base.Apply();
    }
  }
}