#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 .
*/
#endregion
using System;
using System.Linq;
using alglib;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using System.Collections.Generic;
namespace HeuristicLab.Problems.DataAnalysis.Operators {
[Item("DynOpEqComparator", "Dynamic Operator Equalization.")]
[StorableClass]
public class DynOpEqComparator : SingleSuccessorOperator, ISubScopesQualityComparator {
public IValueLookupParameter MaximizationParameter {
get { return (IValueLookupParameter)Parameters["Maximization"]; }
}
public ILookupParameter ResultParameter {
get { return (ILookupParameter)Parameters["Result"]; }
}
public ILookupParameter LeftSideParameter {
get { return (ILookupParameter)Parameters["LeftSide"]; }
}
public ILookupParameter> RightSideParameter {
get { return (ILookupParameter>)Parameters["RightSide"]; }
}
public ILookupParameter SymbolicExpressionTreeParameter {
get { return (ILookupParameter)Parameters["SymbolicExpressionTree"]; }
}
public ILookupParameter BestQualityParameter {
get { return (ILookupParameter)Parameters["BestQuality"]; }
}
public IValueLookupParameter BinSizeParameter {
get { return (IValueLookupParameter)Parameters["BinSize"]; }
}
public ILookupParameter> BinCapacityParameter {
get { return (ILookupParameter>)Parameters["BinCapacity"]; }
}
public ILookupParameter>> AcceptedBinQualitiesParameter {
get { return (ILookupParameter>>)Parameters["AcceptedBinQualities"]; }
}
public ILookupParameter> AcceptedCountsParameter {
get { return (ILookupParameter>)Parameters["AcceptedCounts"]; }
}
public ILookupParameter> TotalCountsParameter {
get { return (ILookupParameter>)Parameters["TotalCounts"]; }
}
public DynOpEqComparator()
: base() {
Parameters.Add(new ValueLookupParameter("Maximization", "True if the problem is a maximization problem, false otherwise"));
Parameters.Add(new LookupParameter("Result", "The result of the comparison: True means Quality is better, False means it is worse than parents."));
Parameters.Add(new LookupParameter("LeftSide", "The quality of the child."));
Parameters.Add(new ScopeTreeLookupParameter("RightSide", "The qualities of the parents."));
Parameters.Add(new LookupParameter("SymbolicExpressionTree", "The newly created child."));
Parameters.Add(new LookupParameter("BestQuality"));
Parameters.Add(new ValueLookupParameter("BinSize", new IntValue(5)));
Parameters.Add(new LookupParameter>("BinCapacity"));
Parameters.Add(new LookupParameter>>("AcceptedBinQualities"));
Parameters.Add(new LookupParameter>("AcceptedCounts"));
Parameters.Add(new LookupParameter>("TotalCounts"));
}
public override IOperation Apply() {
if (ResultParameter.ActualValue == null || ResultParameter.ActualValue.Value == true) {
var tree = SymbolicExpressionTreeParameter.ActualValue;
int size = tree.Size;
int bin = GetBinIndexForSize(size);
if (LeftSideParameter.ActualValue == null) {
ItemList totalCounts = TotalCountsParameter.ActualValue;
while (bin >= totalCounts.Count) totalCounts.Add(new IntValue(0));
totalCounts[bin].Value = totalCounts[bin].Value + 1;
if (!Exists(bin)) ResultParameter.ActualValue = new BoolValue(true);
else ResultParameter.ActualValue = new BoolValue(IsNotFull(bin));
} else {
double leftQuality = LeftSideParameter.ActualValue.Value;
ResultParameter.ActualValue = new BoolValue(Accept(size, bin, leftQuality));
}
}
return base.Apply();
}
private int GetBinIndexForSize(int size) {
return (int)Math.Floor((size - 3.0) / BinSizeParameter.ActualValue.Value);
}
private bool Accept(int size, int binIndex, double solutionQuality) {
bool accept = false;
if (Exists(binIndex)) {
if (IsNotFull(binIndex) ||
NewBestOfBin(solutionQuality, binIndex)) {
AddToBin(solutionQuality, binIndex);
accept = true;
}
} else if (NewBestOfRun(solutionQuality)) {
CreateNewBin(binIndex);
AddToBin(solutionQuality, binIndex);
accept = true;
}
return accept;
}
private void AddToBin(double solutionQuality, int binIndex) {
ItemList acceptedBinQualities = AcceptedBinQualitiesParameter.ActualValue[binIndex];
ItemList acceptedCounts = AcceptedCountsParameter.ActualValue;
if (acceptedBinQualities.Count == 0) {
acceptedBinQualities.Add(new DoubleValue(solutionQuality));
acceptedCounts[binIndex].Value = acceptedCounts[binIndex].Value + 1;
} else {
// insert at beginning if it is a new best or add at end
bool maximization = MaximizationParameter.ActualValue.Value;
if ((maximization && solutionQuality > acceptedBinQualities[0].Value) ||
(!maximization && solutionQuality < acceptedBinQualities[0].Value)) {
acceptedBinQualities.Insert(0, new DoubleValue(solutionQuality));
} else {
acceptedBinQualities.Add(new DoubleValue(solutionQuality));
}
acceptedCounts[binIndex].Value = acceptedCounts[binIndex].Value + 1;
}
}
private bool NewBestOfRun(double solutionQuality) {
bool maximization = MaximizationParameter.ActualValue.Value;
double bestQuality = BestQualityParameter.ActualValue.Value;
return maximization ? solutionQuality > bestQuality : solutionQuality < bestQuality;
}
private void CreateNewBin(int binIndex) {
ItemList binCapacities = BinCapacityParameter.ActualValue;
ItemList> acceptedQualities = AcceptedBinQualitiesParameter.ActualValue;
ItemList acceptedCounts = AcceptedCountsParameter.ActualValue;
// create empty bins of capacity one up to the newly created bin
for (int i = binCapacities.Count; i <= binIndex; i++) {
binCapacities.Add(new IntValue(1));
acceptedQualities.Add(new ItemList(10));
acceptedCounts.Add(new IntValue(0));
}
}
private bool NewBestOfBin(double solutionQuality, int binIndex) {
ItemList> acceptedQualities = AcceptedBinQualitiesParameter.ActualValue;
if (acceptedQualities[binIndex].Count == 0) return true;
bool maximization = MaximizationParameter.ActualValue.Value;
IEnumerable binQualities = acceptedQualities[binIndex].Select(x => x.Value);
// binQualities are always sorted so that the best is in bin 0
return maximization ? solutionQuality > binQualities.First() :
solutionQuality < binQualities.First();
}
private bool IsNotFull(int binIndex) {
ItemList binCapacities = BinCapacityParameter.ActualValue;
ItemList> acceptedQualities = AcceptedBinQualitiesParameter.ActualValue;
return acceptedQualities[binIndex].Count < binCapacities[binIndex].Value;
}
private bool Exists(int binIndex) {
// if the bin has a capacity set then it exists
ItemList binCapacities = BinCapacityParameter.ActualValue;
return binIndex < binCapacities.Count;
}
}
}