/// <summary>
/// Store tournament results.
/// </summary>
/// <param name="results">
/// The results.
/// </param>
private void StoreTournamentResults(MiniTournamentResult <TResult> results)
{
lock (this._genomeToTournamentResultsLock)
{
for (var rank = 0; rank < results.AllFinishedOrdered.Count; rank++)
{
var participant = results.AllFinishedOrdered[rank];
// update the rank
if (!this.GenomeToTournamentResults.TryGetValue(participant, out var allObservedParticipantResults))
{
allObservedParticipantResults = new List <GenomeTournamentResult>();
this.GenomeToTournamentResults[participant] = allObservedParticipantResults;
}
var result = new GenomeTournamentResult()
{
TournamentRank = rank + 1,
TournamentId = results.MiniTournamentId,
Generation = this._selectCommand.CurrentGeneration,
};
allObservedParticipantResults.Add(result);
}
}
}
/// <summary>
/// Simulates a tuner run for the specified number of generations and stores results in a new <see cref="TrainingDataWrapper"/>.
/// </summary>
/// <param name="tree"><see cref="ParameterTree"/> to base genomes on.</param>
/// <param name="encoder">Strategy to convert genomes to double arrays.</param>
/// <param name="genomeCount">Number of genomes to add to result per generation.</param>
/// <param name="generations">Number of generations to simulate.</param>
/// <param name="config"><see cref="AlgorithmTunerConfiguration"/>, required to generate new genomes.</param>
/// <returns>The created <see cref="TrainingDataWrapper"/>.</returns>
public static TrainingDataWrapper GenerateTrainingData(
ParameterTree tree,
IBulkGenomeTransformation encoder,
int genomeCount,
int generations,
AlgorithmTunerConfiguration config)
{
var result = new TrainingDataWrapper(
new Dictionary <Genome, List <GenomeTournamentResult> >(new Genome.GeneValueComparator()),
generations - 1);
// Start with correct number of random genomes.
var randomGenomes = TestDataUtils.GenerateGenomes(tree, config, genomeCount);
// Then simulate the correct number of generations.
for (var currentGen = 0; currentGen < generations; currentGen++)
{
var fitness = TestDataUtils.EvaluateTargetFunction(encoder, randomGenomes);
// add result for every genome
for (var genomeIndex = 0; genomeIndex < genomeCount; genomeIndex++)
{
var currentGenome = randomGenomes[genomeIndex];
if (!result.TournamentResults.ContainsKey(currentGenome))
{
result.TournamentResults[currentGenome] = new List <GenomeTournamentResult>();
}
var tournamentResult = new GenomeTournamentResult()
{
Generation = currentGen,
TournamentId = currentGen,
TournamentRank = fitness[genomeIndex],
};
result.TournamentResults[currentGenome].Add(tournamentResult);
}
// swap out some genomes
var replaceCount = (int)Math.Ceiling(0.3 * genomeCount);
var indiciesToReplace = Randomizer.Instance.ChooseRandomSubset(
Enumerable.Range(0, genomeCount),
replaceCount);
var newGenomes = TestDataUtils.GenerateGenomes(tree, config, replaceCount);
var replacementIndex = 0;
foreach (var indexToReplace in indiciesToReplace)
{
randomGenomes[indexToReplace] = newGenomes[replacementIndex++];
}
}
return(result);
}
public override void ReadFromFileDeserializesCorrectly()
{
/* Create status. */
/* (1) population */
var competitiveGenome = new Genome(2);
competitiveGenome.SetGene("a", new Allele <int>(6));
var nonCompetitiveGenome = new Genome(1);
nonCompetitiveGenome.SetGene("b", new Allele <string>("oh"));
this._population.AddGenome(competitiveGenome, isCompetitive: true);
this._population.AddGenome(nonCompetitiveGenome, isCompetitive: false);
// (2) counters
int counter = 12;
int stagnation = 7;
/* (3) ranks */
var result = new GenomeTournamentResult
{
TournamentRank = 2,
Generation = 24,
TournamentId = 11,
};
var results = new List <GenomeTournamentResult> {
result
};
var ranks = new Dictionary <Genome, List <GenomeTournamentResult> > {
{ new Genome(), results }
};
var status = new GgaStatus(this._population, counter, stagnation, ranks);
/* Write and read it from file. */
status.WriteToFile(this.StatusFilePath);
var deserializedStatus = StatusBase.ReadFromFile <GgaStatus>(this.StatusFilePath);
/* Check it's still the same. */
/* (a) population */
Assert.Equal(
1,
deserializedStatus.Population.GetCompetitiveIndividuals().Count);
var deserializedCompetitiveGenome = deserializedStatus.Population.GetCompetitiveIndividuals().First();
Assert.True(
new Genome.GeneValueComparator().Equals(competitiveGenome, deserializedCompetitiveGenome),
"Expected different competive genome.");
Assert.Equal(
competitiveGenome.Age,
deserializedCompetitiveGenome.Age);
Assert.Equal(
1,
deserializedStatus.Population.GetNonCompetitiveMates().Count);
var deserializedNonCompetitiveGenome = deserializedStatus.Population.GetNonCompetitiveMates().First();
Assert.True(
new Genome.GeneValueComparator().Equals(nonCompetitiveGenome, deserializedNonCompetitiveGenome),
"Expected different non-competive genome.");
Assert.Equal(
nonCompetitiveGenome.Age,
deserializedNonCompetitiveGenome.Age);
// counters
Assert.Equal(
counter,
deserializedStatus.IterationCounter);
Assert.Equal(
stagnation,
deserializedStatus.IncumbentKeptCounter);
/* (c) ranks */
var singleResult = deserializedStatus.AllKnownRanks.Single().Value.Single();
Assert.Equal(result.Generation, singleResult.Generation);
Assert.Equal(result.TournamentId, singleResult.TournamentId);
Assert.Equal(result.TournamentRank, singleResult.TournamentRank);
}