#region License Information
/* HeuristicLab
* Copyright (C) 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 .
*/
#endregion
using System;
using System.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HEAL.Attic;
using HeuristicLab.Random;
namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
///
/// Abstract base class for symbolic data analysis analyzers that validate a solution on a separate data partition using the evaluator.
///
[StorableType("B1A1F3CC-5C21-42F4-BED0-831E0D4AD1F6")]
public abstract class SymbolicDataAnalysisSingleObjectiveValidationAnalyzer : SymbolicDataAnalysisSingleObjectiveAnalyzer,
ISymbolicDataAnalysisValidationAnalyzer, IStochasticOperator
where T : class, ISymbolicDataAnalysisSingleObjectiveEvaluator
where U : class, IDataAnalysisProblemData {
private const string RandomParameterName = "Random";
private const string ProblemDataParameterName = "ProblemData";
private const string EvaluatorParameterName = "Evaluator";
private const string SymbolicDataAnalysisTreeInterpreterParameterName = "SymbolicDataAnalysisTreeInterpreter";
private const string ValidationPartitionParameterName = "ValidationPartition";
private const string RelativeNumberOfEvaluatedSamplesParameterName = "RelativeNumberOfEvaluatedSamples";
private const string PercentageOfBestSolutionsParameterName = "PercentageOfBestSolutions";
#region parameter properties
public ILookupParameter RandomParameter {
get { return (ILookupParameter)Parameters[RandomParameterName]; }
}
public ILookupParameter ProblemDataParameter {
get { return (ILookupParameter)Parameters[ProblemDataParameterName]; }
}
public ILookupParameter EvaluatorParameter {
get { return (ILookupParameter)Parameters[EvaluatorParameterName]; }
}
public ILookupParameter SymbolicDataAnalysisTreeInterpreterParameter {
get { return (ILookupParameter)Parameters[SymbolicDataAnalysisTreeInterpreterParameterName]; }
}
public IValueLookupParameter ValidationPartitionParameter {
get { return (IValueLookupParameter)Parameters[ValidationPartitionParameterName]; }
}
public IValueLookupParameter RelativeNumberOfEvaluatedSamplesParameter {
get { return (IValueLookupParameter)Parameters[RelativeNumberOfEvaluatedSamplesParameterName]; }
}
public IValueLookupParameter PercentageOfBestSolutionsParameter {
get { return (IValueLookupParameter)Parameters[PercentageOfBestSolutionsParameterName]; }
}
#endregion
[StorableConstructor]
protected SymbolicDataAnalysisSingleObjectiveValidationAnalyzer(StorableConstructorFlag _) : base(_) { }
protected SymbolicDataAnalysisSingleObjectiveValidationAnalyzer(SymbolicDataAnalysisSingleObjectiveValidationAnalyzer original, Cloner cloner)
: base(original, cloner) {
}
protected SymbolicDataAnalysisSingleObjectiveValidationAnalyzer(): base() {
Parameters.Add(new LookupParameter(RandomParameterName, "The random generator."));
Parameters.Add(new LookupParameter(ProblemDataParameterName, "The problem data of the symbolic data analysis problem."));
Parameters.Add(new LookupParameter(EvaluatorParameterName, "The operator to use for fitness evaluation on the validation partition."));
Parameters.Add(new LookupParameter(SymbolicDataAnalysisTreeInterpreterParameterName, "The interpreter for symbolic data analysis expression trees."));
Parameters.Add(new ValueLookupParameter(ValidationPartitionParameterName, "The validation partition."));
Parameters.Add(new ValueLookupParameter(RelativeNumberOfEvaluatedSamplesParameterName, "The relative number of samples of the dataset partition, which should be randomly chosen for evaluation between the start and end index."));
Parameters.Add(new ValueLookupParameter(PercentageOfBestSolutionsParameterName,
"The percentage of the top solutions which should be analyzed.", new PercentValue(0.1)));
}
[StorableHook(HookType.AfterDeserialization)]
private void AfterDeserialization() {
if (!Parameters.ContainsKey(PercentageOfBestSolutionsParameterName))
Parameters.Add(new ValueLookupParameter(PercentageOfBestSolutionsParameterName,
"The percentage of the top solutions which should be analyzed.", new PercentValue(1)));
}
protected IEnumerable GenerateRowsToEvaluate() {
int seed = RandomParameter.ActualValue.Next();
int samplesStart = ValidationPartitionParameter.ActualValue.Start;
int samplesEnd = ValidationPartitionParameter.ActualValue.End;
int testPartitionStart = ProblemDataParameter.ActualValue.TestPartition.Start;
int testPartitionEnd = ProblemDataParameter.ActualValue.TestPartition.End;
if (samplesEnd < samplesStart) throw new ArgumentException("Start value is larger than end value.");
int count = (int)((samplesEnd - samplesStart) * RelativeNumberOfEvaluatedSamplesParameter.ActualValue.Value);
if (count == 0) count = 1;
return RandomEnumerable.SampleRandomNumbers(seed, samplesStart, samplesEnd, count)
.Where(i => i < testPartitionStart || testPartitionEnd <= i);
}
}
}