/// <summary>
/// Uses a status dump.
/// </summary>
/// <param name="currentStrategyIndex">
/// Index of the current <see cref="IPopulationUpdateStrategy{TInstance,TResult}"/> in
/// <see cref="_populationUpdateStrategies"/>.
/// </param>
/// <param name="population">The population as stored in <see cref="BasePopulation"/>.</param>
/// <param name="geneticEngineering">
/// Reference to genetic engineering used by
/// <see cref="AlgorithmTuner{TTargetAlgorithm,TInstance,TResult,TModelLearner,TPredictorModel,TSamplingStrategy}"/>.
/// </param>
public void UseStatusDump(int currentStrategyIndex, Population population, IGeneticEngineering geneticEngineering)
{
this.CurrentUpdateStrategyIndex = currentStrategyIndex;
this.BasePopulation = population;
// Restore status of all population update strategies.
foreach (var strategy in this._populationUpdateStrategies)
{
strategy.UseStatusDump(geneticEngineering);
}
}
/// <inheritdoc />
public override void UseStatusDump(IGeneticEngineering evaluationModel)
{
// The CMA-ES runner must be reinitialized for every phase in order to use the correct genome as base.
// Recreate the latest runner.
var strategyStatus = this.DeserializeStrategyStatusFile();
var originalIncumbent = strategyStatus.OriginalIncumbent;
if (originalIncumbent != null)
{
this._cmaEsRunner = this.CreateCmaEsRunner(evaluationBase: originalIncumbent);
}
base.UseStatusDump(evaluationModel);
}
/// <inheritdoc />
public virtual void UseStatusDump(IGeneticEngineering evaluationModel)
{
var strategyStatus = this.DeserializeStrategyStatusFile();
this.OriginalIncumbent = strategyStatus.OriginalIncumbent;
this.MostRecentSorting = strategyStatus.MostRecentSorting?.Select(point => point.Restore()).ToList();
this.CurrentEvaluationInstances = strategyStatus.CurrentEvaluationInstances;
// Instances must be updated in case they are fixed, i.e. only updated at initialization.
if (this.CurrentEvaluationInstances != null)
{
this.SearchPointSorter.UpdateInstances(this.CurrentEvaluationInstances);
}
this.ContinuousOptimizer.UseStatusDump(this.ContinuousOptimizerStatusFilePath);
}
/// <summary>
/// Initializes a new instance of the <see cref="GgaStrategy{TInstance, TResult}"/> class.
/// </summary>
/// <param name="configuration">Options used for this instance.</param>
/// <param name="parameterTree">Provides the tuneable parameters.</param>
/// <param name="genomeBuilder">Responsible for creation, modification and crossover of genomes.
/// Needs to be compatible with the given parameter tree and configuration.</param>
/// <param name="tournamentSelector">An <see cref="IActorRef" /> to a
/// <see cref="GenerationEvaluationActor{TTargetAlgorithm,TInstance,TResult}" /> which decides which competitive
/// genomes are allowed to reproduce.</param>
/// <param name="geneticEngineering">Object which trains a model and enables model-based crossovers.</param>
public GgaStrategy(
AlgorithmTunerConfiguration configuration,
ParameterTree parameterTree,
GenomeBuilder genomeBuilder,
IActorRef tournamentSelector,
IGeneticEngineering geneticEngineering)
{
this._configuration = configuration ?? throw new ArgumentNullException(nameof(configuration));
this._parameterTree = parameterTree ?? throw new ArgumentNullException(nameof(parameterTree));
this._genomeBuilder = genomeBuilder ?? throw new ArgumentNullException(nameof(genomeBuilder));
this._tournamentSelector = tournamentSelector ?? throw new ArgumentNullException(nameof(tournamentSelector));
this._geneticEngineering = geneticEngineering ?? throw new ArgumentNullException(nameof(geneticEngineering));
this.AllKnownRanks = new Dictionary <Genome, List <GenomeTournamentRank> >(
3 * this._configuration.PopulationSize,
Genome.GenomeComparer);
}
/// <summary>
/// Called before every test case.
/// </summary>
protected override void InitializeDefault()
{
this._configuration = this.GetDefaultAlgorithmTunerConfiguration();
this._genomeBuilder = new ValueGenomeBuilder(this._parameterTree, this._configuration, this._genomeValues);
this._geneticEngineering =
new GeneticEngineering <StandardRandomForestLearner <ReuseOldTreesStrategy>, GenomePredictionForestModel <GenomePredictionTree>,
ReuseOldTreesStrategy>(
this._parameterTree,
this._configuration);
this.ActorSystem = ActorSystem.Create(TestBase.ActorSystemName, this._configuration.AkkaConfiguration);
this._resultStorageActor = this.ActorSystem.ActorOf(
Props.Create(
() => new ResultStorageActor <TestInstance, IntegerResult>()),
AkkaNames.ResultStorageActor);
this._generationEvaluationActor = this.CreateTournamentSelector(
this.ActorSystem,
new ExtractIntegerValueCreator(),
new TargetAlgorithm.InterfaceImplementations.ValueConsideration.SortByDescendingIntegerValue <TestInstance>());
}
/// <summary>
/// Reads all internal data from file.
/// </summary>
/// <param name="evaluationModel">Reference to up-to-date evaluation model.</param>
public void UseStatusDump(IGeneticEngineering evaluationModel)
{
// Update evaluation model.
this._geneticEngineering = evaluationModel;
// Read status from file.
var status = StatusBase.ReadFromFile <GgaStatus>(this.StatusFilePath);
this._population = status.Population;
this._iterationCounter = status.IterationCounter;
this._incumbentKeptCounter = status.IncumbentKeptCounter;
this.AllKnownRanks = status.AllKnownRanks;
// somehow, the equality comparer is not restored properly.
// fix this.
var restoredRanks = this.AllKnownRanks.GroupBy(kr => kr.Key, Genome.GenomeComparer).ToDictionary(
grp => grp.Key,
grp => grp.SelectMany(ranks => ranks.Value).ToList(),
Genome.GenomeComparer);
this.AllKnownRanks = restoredRanks;
}