source: branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/Evaluators/SymbolicTimeSeriesPrognosisNormalizedMseEvaluator.cs @ 5955

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2010 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.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Problems.DataAnalysis.SupportVectorMachine;
using HeuristicLab.Problems.DataAnalysis;
using HeuristicLab.Problems.DataAnalysis.Evaluators;
using HeuristicLab.Parameters;
using HeuristicLab.Optimization;
using HeuristicLab.Operators;
using HeuristicLab.Problems.DataAnalysis.Regression.Symbolic;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using System.Collections.Generic;
using HeuristicLab.Problems.DataAnalysis.Regression;
using HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis.Symbolic.Interfaces;

namespace HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis.Symbolic.Evaluators {
  [Item("SymbolicTimeSeriesPrognosisNormalizedMseEvaluator", "")]
  [StorableClass]
  public class SymbolicTimeSeriesPrognosisNormalizedMseEvaluator : SymbolicTimeSeriesPrognosisEvaluator {

    [StorableConstructor]
    protected SymbolicTimeSeriesPrognosisNormalizedMseEvaluator(bool deserializing) : base(deserializing) { }
    protected SymbolicTimeSeriesPrognosisNormalizedMseEvaluator(SymbolicTimeSeriesPrognosisNormalizedMseEvaluator original, Cloner cloner)
      : base(original, cloner) {
    }
    public SymbolicTimeSeriesPrognosisNormalizedMseEvaluator()
      : base() {
    }

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

    public override double Evaluate(SymbolicExpressionTree tree, MultiVariateDataAnalysisProblemData problemData, ISymbolicTimeSeriesExpressionInterpreter interpreter, IEnumerable<int> rows, int predictionHorizon, DoubleArray lowerEstimationLimit, DoubleArray upperEstimationLimit) {
      return Calculate(tree, problemData, interpreter, rows, predictionHorizon, lowerEstimationLimit, upperEstimationLimit);
    }

    public static double Calculate(SymbolicExpressionTree tree, MultiVariateDataAnalysisProblemData problemData,
      ISymbolicTimeSeriesExpressionInterpreter interpreter, 
      IEnumerable<int> rows, int predictionHorizon, DoubleArray lowerEstimationLimit, DoubleArray upperEstimationLimit) {
      double[] zeros = new double[problemData.TargetVariables.CheckedItems.Count()];
      double[] ones = Enumerable.Repeat(1.0, zeros.Length).ToArray();
      return SymbolicTimeSeriesPrognosisScaledNormalizedMseEvaluator.CalculateWithScaling(tree, problemData, interpreter, rows,
        predictionHorizon, lowerEstimationLimit, upperEstimationLimit, ones, zeros);
    }
  }
}