public void CreateCovarianceMatrixAdaptationStrategyReturnsCorrectStrategyType()
{
var localConfiguration = CovarianceMatrixAdaptationInformationFlowSwitchTest.CreateConfiguration(focusOnIncumbent: true);
var strategy =
CovarianceMatrixAdaptationInformationFlowSwitch.CreateCovarianceMatrixAdaptationStrategy <TestInstance, TestResult>(
localConfiguration,
this.GetDefaultParameterTree(),
this.GenomeBuilder,
this.GenomeSorter,
this.ResultStorageActor);
Assert.Equal(
typeof(LocalCovarianceMatrixAdaptationStrategy <TestInstance, TestResult>),
strategy.GetType());
var globalConfiguration = CovarianceMatrixAdaptationInformationFlowSwitchTest.CreateConfiguration(focusOnIncumbent: false);
strategy =
CovarianceMatrixAdaptationInformationFlowSwitch.CreateCovarianceMatrixAdaptationStrategy <TestInstance, TestResult>(
globalConfiguration,
this.GetDefaultParameterTree(),
this.GenomeBuilder,
this.GenomeSorter,
this.ResultStorageActor);
Assert.Equal(
typeof(GlobalCovarianceMatrixAdaptationStrategy <TestInstance, TestResult>),
strategy.GetType());
}
/// <summary>
/// Chooses the next population update strategy after this one finished.
/// </summary>
/// <param name="populationUpdateStrategies">Possible strategies.</param>
/// <returns>Index of the chosen strategy.</returns>
public int NextStrategy(List <IPopulationUpdateStrategy <TInstance, TResult> > populationUpdateStrategies)
{
Type nextStrategyType;
switch (this._configuration.ContinuousOptimizationMethod)
{
case ContinuousOptimizationMethod.None:
nextStrategyType = typeof(GgaStrategy <TInstance, TResult>);
break;
case ContinuousOptimizationMethod.Jade:
nextStrategyType = typeof(DifferentialEvolutionStrategy <TInstance, TResult>);
break;
case ContinuousOptimizationMethod.CmaEs:
nextStrategyType =
CovarianceMatrixAdaptationInformationFlowSwitch.DetermineCovarianceMatrixAdaptationStrategyType <TInstance, TResult>(
this._configuration);
break;
default:
throw new NotImplementedException(
$"{this._configuration.ContinuousOptimizationMethod} is not mapped to a type in GGA strategy.");
}
return(populationUpdateStrategies.FindIndex(strategy => strategy.GetType() == nextStrategyType));
}
public void DetermineCovarianceMatrixAdaptationStrategyTypeReturnsCorrectType()
{
var localConfiguration = CovarianceMatrixAdaptationInformationFlowSwitchTest.CreateConfiguration(focusOnIncumbent: true);
Assert.Equal(
typeof(LocalCovarianceMatrixAdaptationStrategy <TestInstance, TestResult>),
CovarianceMatrixAdaptationInformationFlowSwitch.DetermineCovarianceMatrixAdaptationStrategyType <TestInstance, TestResult>(
localConfiguration));
var globalConfiguration = CovarianceMatrixAdaptationInformationFlowSwitchTest.CreateConfiguration(focusOnIncumbent: false);
Assert.Equal(
typeof(GlobalCovarianceMatrixAdaptationStrategy <TestInstance, TestResult>),
CovarianceMatrixAdaptationInformationFlowSwitch.DetermineCovarianceMatrixAdaptationStrategyType <TestInstance, TestResult>(
globalConfiguration));
}
/// <summary>
/// Creates the different <see cref="IPopulationUpdateStrategy{TInstance,TResult}"/>s that may be used to
/// update the population.
/// </summary>
/// <param name="targetAlgorithmFactory">
/// Produces configured instances of the target algorithm to tune.
/// </param>
/// <param name="runEvaluator">
/// Object for evaluating target algorithm runs.
/// </param>
/// <returns>The created <see cref="IPopulationUpdateStrategy{TInstance,TResult}"/>s.</returns>
private IEnumerable <IPopulationUpdateStrategy <TInstance, TResult> > CreatePopulationUpdateStrategies(
ITargetAlgorithmFactory <TTargetAlgorithm, TInstance, TResult> targetAlgorithmFactory,
IRunEvaluator <TResult> runEvaluator)
{
var tournamentSelector = this._targetAlgorithmRunActors.ActorOf(
Props.Create(
() => new TournamentSelector <TTargetAlgorithm, TInstance, TResult>(
targetAlgorithmFactory,
runEvaluator,
this._configuration,
this._targetRunResultStorage,
this._parameterTree)),
AkkaNames.TournamentSelector);
yield return(new GgaStrategy <TInstance, TResult>(
this._configuration,
this._parameterTree,
this._genomeBuilder,
tournamentSelector,
this.GeneticEngineering));
if (this._configuration.ContinuousOptimizationMethod == ContinuousOptimizationMethod.Jade)
{
yield return(new DifferentialEvolutionStrategy <TInstance, TResult>(
this._configuration,
this._parameterTree,
this._genomeBuilder,
this._genomeSorter,
this._targetRunResultStorage));
}
if (this._configuration.ContinuousOptimizationMethod == ContinuousOptimizationMethod.CmaEs)
{
yield return(CovarianceMatrixAdaptationInformationFlowSwitch.CreateCovarianceMatrixAdaptationStrategy <TInstance, TResult>(
this._configuration,
this._parameterTree,
this._genomeBuilder,
this._genomeSorter,
this._targetRunResultStorage));
}
}
