public ParetoSolver(SolutionSet solutions)
{
_solutions = solutions;
var size = _solutions.GetObjectives().GetUpperBound(0) + 1;
var ocount = _solutions.GetObjectives()[0].Length;
var objectives = _solutions.GetObjectives();
var f1 = new double[size];
var f2 = new double[size];
var f3 = new double[] { };
if (ocount == 3)
{
f3 = new double[size];
}
for (var i = 0; i < size; i++)
{
f1[i] = objectives[i][0];
if (ocount > 1)
{
f2[i] = objectives[i][1];
}
if (ocount > 2)
{
f3[i] = objectives[i][2];
}
}
var f1min = f1.Min();
var f1max = f1.Max();
var f2min = f2.Min();
var f2max = f2.Max();
double f3min = 0;
double f3max = 0;
if (ocount == 3)
{
f3min = f3.Min();
f3max = f3.Max();
}
_f1Scaled = new double[size];
_f2Scaled = new double[size];
_f3Scaled = new double[size];
for (var i = 0; i < size; i++)
{
_f1Scaled[i] = FMScaling.ScaleFromTo(f1min, f1max, 0, 1, f1[i]);
if (ocount > 1)
{
_f2Scaled[i] = FMScaling.ScaleFromTo(f2min, f2max, 0, 1, f2[i]);
}
if (ocount == 3)
{
_f3Scaled[i] = FMScaling.ScaleFromTo(f3min, f3max, 0, 1, f3[i]);
}
}
}
public override void Evaluate(Solution solution)
{
var s = (IntergenSolution)solution;
var doubleVal = new double[Model.Setting.NumberOfFeatures];
var interacVal = new double[Model.Setting.NumberOfInteractions];
var values = new XReal(solution);
for (var i = 0; i < Model.Setting.NumberOfFeatures; i++)
{
doubleVal[i] = values.GetValue(i);
}
for (var i = 0; i < Model.Setting.NumberOfInteractions; i++)
{
interacVal[i] = values.GetValue(i + Model.Setting.NumberOfFeatures);
}
//the distribution from the NSGA2
var nsgaFv = new Distribution(doubleVal);
var interacDist = new Distribution(interacVal);
var multiplicationTime = new Stopwatch(); multiplicationTime.Start();
var variantValuesWithoutInteraction = FeatureMatrix.Dot(doubleVal);
var interacVals = InteractionMatrix.Dot(interacVal);
var variantResults = variantValuesWithoutInteraction.Add(interacVals);
multiplicationTime.Stop();
FitnessTracker.AddMultiplicationTime(multiplicationTime.ElapsedMilliseconds);
var variantResult = new Distribution(variantResults);
var localScaledVariants = new double[VariantTarget.Values.Length];
Array.Copy(VariantTarget.Values, localScaledVariants, VariantTarget.Values.Length);
var localVariantTarget = new Distribution(localScaledVariants);
localVariantTarget = FMScaling.InteractionToScale(localVariantTarget, variantResults.Min(),
variantResults.Max());
var fc = new FitnessCalculator(Model, s.FoundAtEval);
var fitnessValues = fc.Calculate(variantResult, localVariantTarget, nsgaFv, FeatureTarget, interacDist, InteractionTarget);
solution.Objective[0] = fitnessValues.FeatureVal;
solution.Objective[1] = fitnessValues.InteracVal;
solution.Objective[2] = fitnessValues.VariantVal;
FitnessTracker.AddCalcTime(fc.GetFitnessTime());
FitnessTracker.Add(s.FoundAtEval, fitnessValues.FeatureVal, fitnessValues.InteracVal, fitnessValues.VariantVal);
}
public override void Evaluate(Solution solution)
{
var s = (IntergenSolution)solution;
var doubleVal = new double[Model.Setting.NumberOfFeatures];
var values = new XReal(solution);
for (var i = 0; i < Model.Setting.NumberOfFeatures; i++)
{
doubleVal[i] = values.GetValue(i);
}
//the distribution from the NSGA2
var nsgaFv = new Distribution(doubleVal);
var variantResults = FeatureMatrix.Dot(doubleVal);
var variantResult = new Distribution(variantResults);
var localScaledVariants = new double[VariantTarget.Values.Length];
Array.Copy(VariantTarget.Values, localScaledVariants, VariantTarget.Values.Length);
var localVariantTarget = new Distribution(localScaledVariants);
localVariantTarget = FMScaling.InteractionToScale(localVariantTarget, variantResults.Min(),
variantResults.Max());
var fc = new FitnessCalculator(Model, s.FoundAtEval);
var fitnessValues = fc.Calculate(variantResult, localVariantTarget, nsgaFv, FeatureTarget, null, null);
solution.Objective[0] = fitnessValues.FeatureVal;
solution.Objective[1] = fitnessValues.VariantVal;
FitnessTracker.AddFeatVar(s.FoundAtEval, fitnessValues.FeatureVal, fitnessValues.VariantVal);
}
public override void Evaluate(Solution solution)
{
#if DEBUG
if (_counter == 0)
{
if (Model.Setting.Logging)
{
LogArrayValues(FeatureTarget.Values, "targetFeatures");
if (Model.Setting.NumberOfInteractions > 0)
{
LogArrayValues(InteractionTarget.Values, "targetInteraction");
}
}
}
_counter++;
#endif
Console.WriteLine(_counter);
Distribution variantTarget = null;
if (!Model.Setting.NoVariantCalculation)
{
var localScaledVariants = new double[ScaledVariantTarget.Values.Length];
Array.Copy(ScaledVariantTarget.Values, localScaledVariants, ScaledVariantTarget.Values.Length);
variantTarget = new Distribution(localScaledVariants);
}
var doubleVal = new double[Model.Setting.NumberOfFeatures];
var interacVal = new double[Model.Setting.NumberOfInteractions];
var values = new XReal(solution);
for (var i = 0; i < Model.Setting.NumberOfFeatures; i++)
{
doubleVal[i] = values.GetValue(i);
}
for (var i = 0; i < Model.Setting.NumberOfInteractions; i++)
{
interacVal[i] = values.GetValue(i + Model.Setting.NumberOfFeatures);
}
//the distribution from the NSGA2
var nsgaFv = new Distribution(doubleVal);
var interacDist = new Distribution(interacVal);
var watch = Stopwatch.StartNew();
//calculate the variant values
Distribution variantResult = null;
if (_counter > 9500)
{
var variantValuesWithoutInteraction = FeatureMatrix.Dot(doubleVal);
if (Model.Setting.NumberOfInteractions > 0)
{
var interacVals = InteractionMatrix.Dot(interacVal);
var variantResults = variantValuesWithoutInteraction.Add(interacVals);
variantResult = new Distribution(variantResults);
}
else
{
variantResult = new Distribution(variantValuesWithoutInteraction);
}
}
watch.Stop();
calcTime += watch.ElapsedMilliseconds;
//scale the variant target distribution to the size of the calculated variant distribution
var scaleWatch = Stopwatch.StartNew();
FMScaling fms = new FMScaling(Model);
if (Model.Setting.ScaleToGlobalMinMax)
{
var change = false;
if (currentMin > variantResult.Values.Min())
{
currentMin = variantResult.Values.Min();
change = true;
}
if (currentMax < variantResult.Values.Max())
{
currentMax = variantResult.Values.Max();
change = true;
}
if (change)
{
ScaledVariantTarget = FMScaling.InteractionToScale(ScaledVariantTarget, currentMin, currentMax);
}
}
else
{
if (!Model.Setting.NoVariantCalculation)
{
variantTarget = FMScaling.InteractionToScale(variantTarget, variantResult.Values.Min(),
variantResult.Values.Max());
}
}
scaleWatch.Stop();
scaleTime += scaleWatch.ElapsedMilliseconds;
IntergenSolution s = (IntergenSolution)solution;
s.FoundAtEval = _counter;
var testWatch = Stopwatch.StartNew();
//calculate the fitness values for features and variants
var fc = new FitnessCalculator(Model, _counter);
var fitnessValues = fc.Calculate(variantResult, variantTarget, nsgaFv, FeatureTarget, interacDist, InteractionTarget);
solution.Objective[0] = fitnessValues.FeatureVal;
if (Model.Setting.NoVariantCalculation)
{
if (Model.Setting.NumberOfInteractions > 0)
{
solution.Objective[1] = fitnessValues.InteracVal;
}
}
else
{
//interacs and variants
if (Model.Setting.NumberOfInteractions > 0)
{
solution.Objective[1] = fitnessValues.InteracVal;
solution.Objective[2] = fitnessValues.VariantVal;
}
else
{
solution.Objective[1] = fitnessValues.VariantVal;
}
}
/* if (Model.Setting.UseKs)
* {
* PerfomKs(variantResult, variantTarget, nsgaFv, FeatureTarget, solution);
*
* }
* else if (Model.Setting.UseCmv)
* {
* PerformCmv(variantResult, variantTarget, nsgaFv, FeatureTarget, InteractionTarget, interacDist, solution);
* }
* else if (Model.Setting.UseEuclidean) {
* var bd = new BinnedDistance(variantTarget, variantResult, Model.VariantDynamicHist, _counter);
* var bd2 = new BinnedDistance(nsgaFv, FeatureTarget, Model.FeaturesDynamicHist, _counter);
*
* solution.Objective[0] = bd2.EuclidianDist();
* solution.Objective[1] = bd.EuclidianDist();
* if (Model.Setting.NumberOfInteractions > 0)
* {
* var interac = new BinnedDistance(interacDist, InteractionTarget, Model.InteracDynamicHist, _counter);
* solution.Objective[2] = interac.EuclidianDist();
* }
* }
* else if (Model.Setting.UseChiSquared)
* {
* var bd = new BinnedDistance(variantTarget, variantResult, Model.VariantDynamicHist,
* _counter);
* var bd2 = new BinnedDistance(nsgaFv, FeatureTarget, Model.FeaturesDynamicHist, _counter);
*
*
* solution.Objective[0] = bd2.ChiSquaredDist();
* solution.Objective[1] = bd.ChiSquaredDist();
* if (Model.Setting.NumberOfInteractions > 0)
* {
* var interac = new BinnedDistance(interacDist, InteractionTarget, Model.InteracDynamicHist, _counter);
* solution.Objective[2] = interac.ChiSquaredDist();
* }
* }
* else if (Model.Setting.EuclAndCmv)
* {
* PerformCmv(variantTarget, variantResult, nsgaFv, FeatureTarget, InteractionTarget, interacDist, solution);
*
* var variant = new BinnedDistance(variantTarget, variantResult, Model.VariantDynamicHist, _counter);
* var feat = new BinnedDistance(nsgaFv, FeatureTarget, Model.FeaturesDynamicHist, _counter);
* var interac = new BinnedDistance(interacDist, InteractionTarget, Model.InteracDynamicHist, _counter);
*
* solution.Objective[3] = feat.EuclidianDist();
* solution.Objective[4] = variant.EuclidianDist();
* solution.Objective[5] = interac.EuclidianDist();
* }
* else if (Model.Setting.ChiAndCmv)
* {
* PerformCmv(variantTarget, variantResult, nsgaFv, FeatureTarget, InteractionTarget, interacDist, solution);
* var variant = new BinnedDistance(variantTarget, variantResult, Model.VariantDynamicHist,_counter);
* var feat = new BinnedDistance(nsgaFv, FeatureTarget, Model.FeaturesDynamicHist, _counter);
* var interac = new BinnedDistance(interacDist, InteractionTarget, Model.InteracDynamicHist, _counter);
* solution.Objective[3] = feat.ChiSquaredDist();
* solution.Objective[4] = variant.ChiSquaredDist();
* solution.Objective[5] = interac.ChiSquaredDist();
* }
*/
testWatch.Stop();
fitnessTime += testWatch.ElapsedMilliseconds;
//report our progress to the model for GUI
if (_counter % 200 == 0)
{
if (!Model.Setting.Parallel /*|| (Model.Parallel && parallelIndex % 50 == 0) */)
{
if (Model.Setting.DrawDensity && Model.Setting.DrawHistogram)
{
RIntegrator.FeatureHistAndDens(nsgaFv.Values, FeatureTarget.Values);
RIntegrator.VariantHistAndDens(variantResult.Values, variantTarget.Values);
}
else if (Model.Setting.DrawDensity)
{
RIntegrator.PlotFeatureTarget(nsgaFv.Values, FeatureTarget.Values, Model.Setting.FeatureAdjust);
if (Model.Setting.NoVariantCalculation)
{
if (_counter > 9500)
{
RIntegrator.PlotVariantTarget(variantResult.Values);
}
}
else
{
RIntegrator.PlotVariantTarget(variantResult.Values, variantTarget.Values);
}
if (Model.Setting.NumberOfInteractions > 0)
{
RIntegrator.PlotInteracTarget(interacDist.Values, InteractionTarget.Values);
}
}
else if (Model.Setting.DrawHistogram)
{
RIntegrator.FeatureComparisonHist(nsgaFv.Values, FeatureTarget.Values);
if (Model.Setting.NoVariantCalculation)
{
RIntegrator.PlotVariantTarget(variantResult.Values);
}
else
{
RIntegrator.VariantComparisonHisto(variantResult.Values, variantTarget.Values);
}
}
else
{
}
//ReportProgress(solution);
}
ReportProgress(solution, fitnessValues);
//Worker.ReportProgress((int)(counter * 100 / (double)Model.MaxEvaluations), new UserProgress { VariantP = solution.Objective[1], FeatureP = solution.Objective[0] });
}
if (_counter == Model.Setting.MaxEvaluations)
{
Console.WriteLine("FitnessTime: " + fitnessTime);
Console.WriteLine("ScaleTime: " + scaleTime);
Console.WriteLine("CalcTime: " + calcTime);
}
var cont = new SolutionContainer
{
//TargetVariant = variantTarget,
Variant = variantResult,
Features = nsgaFv,
Interaction = interacDist,
//TargetFeatures = FeatureTarget,
FeatureTVal = fitnessValues.FeatureVal,
InteracTVal = fitnessValues.InteracVal,
VariantTVal = fitnessValues.VariantVal,
CalcTime = watch.ElapsedMilliseconds,
FitnessTime = testWatch.ElapsedMilliseconds,
ScaleTime = scaleWatch.ElapsedMilliseconds,
TestName = GetUsedTest(),
FoundAtEval = _counter,
};
//if (_counter > 7000)
// {
// cont.Write(Model.Setting.LogFolder + "evalstep" + _counter + ".json");
// }
//cont = null;
//Console.WriteLine(cont.FoundAtEval + "\t" + cont.FeatureTVal + "\t" + cont.VariantTVal);
if (Model.Setting.ChiAndCmv || Model.Setting.EuclAndCmv)
{
cont.AdditionalFeatureCmv = solution.Objective[4];
cont.AdditionalVariantCmv = solution.Objective[5];
}
//if (!Model.Setting.Parallel)Model.History.Add(counter, cont);
Model.AddSolutionToHistory(cont);
if (!Model.Setting.Logging)
{
return;
}
var usedTest = GetUsedTest();
//LogArrayValues(nsgaFV.Values, "Features");
//LogArrayValues(variantResult.Values, "Variants");
//LogArrayValues(ScaledVariantTarget.Values, "targetVariants");
if (Model.Setting.NumberOfInteractions > 0)
{
LogSingleValue(fitnessValues.InteracVal, "InteracFitn" + usedTest);
}
if (!Model.Setting.NoVariantCalculation)
{
LogSingleValue(fitnessValues.VariantVal, "VarFitn" + usedTest);
}
LogSingleValue(fitnessValues.FeatureVal, "FeatFitn" + usedTest);
}
public static void Plot(Solution solution)
{
if (!_model.Setting.DrawDensity && !_model.Setting.DrawHistogram)
{
return;
}
_counter++;
if (_counter % (_model.Setting.PlotStepSize / _model.Setting.PopulationSize) != 0)
{
return;
}
var doubleVal = new double[_model.Setting.NumberOfFeatures];
var interacVal = new double[_model.Setting.NumberOfInteractions];
var values = new XReal(solution);
for (var i = 0; i < _model.Setting.NumberOfFeatures; i++)
{
doubleVal[i] = values.GetValue(i);
}
if (_model.Setting.NumberOfInteractions > 0)
{
for (var i = 0; i < _model.Setting.NumberOfInteractions; i++)
{
interacVal[i] = values.GetValue(i + _model.Setting.NumberOfFeatures);
}
}
if (_model.Setting.DrawDensity)
{
RIntegrator.PlotFeatureTarget(doubleVal, _model.DStore.SelectedFeatureDistribution.Values,
_model.Setting.FeatureAdjust);
}
if (_model.Setting.DrawHistogram)
{
RIntegrator.FeatureHistAndDens(doubleVal, _model.DStore.SelectedFeatureDistribution.Values);
}
if (_model.Setting.NumberOfInteractions > 0)
{
if (_model.Setting.DrawDensity)
{
RIntegrator.PlotInteracTarget(interacVal, _model.DStore.SelectedInteractionDistribution.Values);
}
if (_model.Setting.DrawHistogram)
{
RIntegrator.InteracHist(interacVal, _model.DStore.SelectedInteractionDistribution.Values);
}
if (!_model.Setting.NoVariantCalculation)
{
//interactions and variants
var variantValuesWithoutInteraction = _model.FeatureMatrix.Dot(doubleVal);
var interacVals = _model.InteractionMatrix.Dot(interacVal);
var variantResults = variantValuesWithoutInteraction.Add(interacVals);
if (_model.ScaledVariantTarget != null)
{
FMScaling.InteractionToScale(_model.ScaledVariantTarget, variantResults.Min(),
variantResults.Max());
if (_model.Setting.DrawDensity)
{
RIntegrator.PlotVariantTarget(variantResults, _model.ScaledVariantTarget.Values);
}
if (_model.Setting.DrawHistogram)
{
RIntegrator.VariantComparisonHisto(variantResults, _model.ScaledVariantTarget.Values);
}
}
else
{
if (_model.Setting.DrawDensity)
{
RIntegrator.PlotVariantTarget(variantResults);
}
}
}
else
{
//interactions and no variants
}
}
else
{
if (!_model.Setting.NoVariantCalculation)
{
//no interactions and variants
var variantResults = _model.FeatureMatrix.Dot(doubleVal);
//FMScaling.InteractionToScale(_model.ScaledVariantTarget, variantResults.Min(),
// variantResults.Max());
if (_model.Setting.DrawDensity)
{
RIntegrator.PlotVariantTarget(variantResults);
}
if (_model.Setting.DrawHistogram)
{
RIntegrator.VariantComparisonHisto(variantResults, _model.ScaledVariantTarget.Values);
}
}
}
}
