/// <summary>
/// Checks adding a 0.2-standard deviation vector in any single coordinate does
/// not change the distribution mean.
/// </summary>
/// <param name="data">Internal <see cref="CmaEs{TSearchPoint}"/> data.</param>
/// <returns>Whether no change occurred in distribution mean.</returns>
public bool IsMet(CmaEsElements data)
{
if (data == null)
{
throw new ArgumentNullException(nameof(data));
}
if (!data.IsCompletelySpecified())
{
throw new ArgumentOutOfRangeException(
nameof(data),
"Data must be completely specified for this termination criterion.");
}
for (int i = 0; i < data.Configuration.SearchSpaceDimension; i++)
{
var shiftedMean = data.DistributionMean[i] + ((0.2 * data.StepSize) * data.Covariances[i, i]);
if (data.DistributionMean[i].Equals(shiftedMean))
{
// Might be true due to numerical issues. Then we should stop.
return(true);
}
}
return(false);
}
public void PropertiesAreSetCorrectly()
{
var data = new CmaEsElements(
this._configuration,
this._generation,
this._distributionMean,
this._stepSize,
this._covariances,
this._covariancesDecomposition,
this._evolutionPath,
this._conjugateEvolutionPath);
Assert.Equal(this._configuration, data.Configuration);
Assert.Equal(this._generation, data.Generation);
Assert.Equal(this._distributionMean, data.DistributionMean);
Assert.Equal(this._stepSize, data.StepSize);
Assert.Equal(this._covariances, data.Covariances);
Assert.Equal(this._diagonal, data.CovariancesDiagonal);
Assert.Equal(
this._eigenvectors,
data.CovariancesEigenVectors);
Assert.Equal(this._evolutionPath, data.EvolutionPath);
Assert.Equal(
this._conjugateEvolutionPath,
data.ConjugateEvolutionPath);
}
/// <summary>
/// Checks whether the current generation should be the last one.
/// </summary>
/// <param name="data">Internal <see cref="CmaEs{TSearchPoint}"/> data.</param>
/// <returns>Whether the generation was the <see cref="_maximum"/>th one.</returns>
public bool IsMet(CmaEsElements data)
{
if (data == null)
{
throw new ArgumentNullException(nameof(data));
}
return(data.Generation >= this._maximum);
}
/// <summary>
/// Called before every test case.
/// </summary>
protected override void InitializeDefault()
{
this._data = new CmaEsElements(
configuration: new CmaEsConfiguration(20, Vector <double> .Build.Random(3), 0.1),
generation: 1,
stepSize: 0.1,
distributionMean: Vector <double> .Build.Random(2),
covariances: Matrix <double> .Build.DenseIdentity(2),
covariancesDecomposition: Matrix <double> .Build.DenseIdentity(2).Evd(),
evolutionPath: Vector <double> .Build.Random(2),
conjugateEvolutionPath: Vector <double> .Build.Random(2));
this._terminationCriteria = new List <ITerminationCriterion> {
new MaxIterations(57)
};
}
/// <summary>
/// Checks whether the condition number of the covariance matrix exceeds <see cref="MaxCondition"/>.
/// </summary>
/// <param name="data">Internal <see cref="CmaEs{TSearchPoint}"/> data.</param>
/// <returns>Whether the condition number exceeds <see cref="MaxCondition"/>.</returns>
public bool IsMet(CmaEsElements data)
{
if (data == null)
{
throw new ArgumentNullException(nameof(data));
}
if (data.Covariances == null)
{
throw new ArgumentOutOfRangeException(
nameof(data),
"Data must have the covariance matrix set for this termination criterion.");
}
return(data.Covariances.ConditionNumber() > MaxCondition);
}
public void IsCompletelySpecifiedReturnsTrueForEverythingSpecified()
{
var data = new CmaEsElements(
this._configuration,
this._generation,
this._distributionMean,
this._stepSize,
this._covariances,
this._covariancesDecomposition,
this._evolutionPath,
this._conjugateEvolutionPath);
Assert.True(
data.IsCompletelySpecified(),
"Data is completely specified.");
}
public void IsCompletelySpecifiedReturnsFalseForMissingConjugateEvolutionPath()
{
var noConjugateEvolutionPath = new CmaEsElements(
this._configuration,
this._generation,
this._distributionMean,
this._stepSize,
this._covariances,
this._covariancesDecomposition,
this._evolutionPath,
conjugateEvolutionPath: null);
Assert.False(
noConjugateEvolutionPath.IsCompletelySpecified(),
"Data without a conjugate evolution path is not completely specified.");
}
public void IsCompletelySpecifiedReturnsFalseForMissingDistributionMean()
{
var noDistributionMean = new CmaEsElements(
this._configuration,
this._generation,
distributionMean: null,
stepSize: this._stepSize,
covariances: this._covariances,
covariancesDecomposition: this._covariancesDecomposition,
evolutionPath: this._evolutionPath,
conjugateEvolutionPath: this._conjugateEvolutionPath);
Assert.False(
noDistributionMean.IsCompletelySpecified(),
"Data without a distribution mean is not completely specified.");
}
public void IsMetThrowsForMissingConfiguration()
{
var covariances = Matrix <double> .Build.DenseOfDiagonalArray(new[] { 1d, 1d, 1d });
var data = new CmaEsElements(
configuration: null,
generation: 5,
distributionMean: Vector <double> .Build.Dense(3),
stepSize: 0.2,
covariances: covariances,
covariancesDecomposition: covariances.Evd(),
evolutionPath: Vector <double> .Build.Dense(3),
conjugateEvolutionPath: Vector <double> .Build.Dense(3));
var terminationCriterion = new NoEffectAxis();
Assert.Throws <ArgumentOutOfRangeException>(() => terminationCriterion.IsMet(data));
}
/// <summary>
/// Checks if the factor between current and initial step size is greater than a <see cref="MaxFactor"/> times
/// the square root of the covariance matrix's largest eigenvalue.
/// </summary>
/// <param name="data">Internal <see cref="CmaEs{TSearchPoint}"/> data.</param>
/// <returns>Whether the factor is greater.</returns>
public bool IsMet(CmaEsElements data)
{
if (data == null)
{
throw new ArgumentNullException(nameof(data));
}
if (!data.IsCompletelySpecified())
{
throw new ArgumentOutOfRangeException(
nameof(data),
"Data must be completely specified for this termination criterion.");
}
var largestEigenvalue = data.CovariancesDiagonal.Diagonal().Maximum();
return(data.StepSize / data.Configuration.InitialStepSize > MaxFactor *Math.Sqrt(largestEigenvalue));
}
/// <summary>
/// Checks adding a 0.1-standard deviation vector in a principal axis direction of the covariance matrix does
/// not change the distribution mean.
/// <para>Axis is chosen dependent on generation.</para>
/// </summary>
/// <param name="data">Internal <see cref="CmaEs{TSearchPoint}"/> data.</param>
/// <returns>Whether no change occurred in distribution mean.</returns>
public bool IsMet(CmaEsElements data)
{
if (data == null)
{
throw new ArgumentNullException(nameof(data));
}
if (!data.IsCompletelySpecified())
{
throw new ArgumentOutOfRangeException(
nameof(data),
"Data must be completely specified for this termination criterion.");
}
int index = data.Generation % data.Configuration.SearchSpaceDimension;
var principalAxisDirection =
Math.Sqrt(data.CovariancesDiagonal[index, index]) * data.CovariancesEigenVectors.Column(index);
var shiftedMean = data.DistributionMean + ((0.1 * data.StepSize) * principalAxisDirection);
// Might be true due to numerical issues.
return(data.DistributionMean.Equals(shiftedMean));
}
public void PropertiesAreSetCorrectlyForMinimumSpecification()
{
var data = new CmaEsElements(
configuration: null,
generation: this._generation,
distributionMean: null,
stepSize: this._stepSize,
covariances: null,
covariancesDecomposition: null,
evolutionPath: null,
conjugateEvolutionPath: null);
Assert.Null(data.Configuration);
Assert.Equal(this._generation, data.Generation);
Assert.Null(data.DistributionMean);
Assert.Equal(this._stepSize, data.StepSize);
Assert.Null(data.Covariances);
Assert.Null(data.CovariancesDiagonal);
Assert.Null(data.CovariancesEigenVectors);
Assert.Null(data.EvolutionPath);
Assert.Null(data.ConjugateEvolutionPath);
}
public override void ReadFromFileDeserializesCorrectly()
{
/* Create status. */
this._terminationCriteria = new List <ITerminationCriterion> {
new TolUpSigma()
};
var configuration = new CmaEsConfiguration(
populationSize: 20,
initialDistributionMean: Vector <double> .Build.Random(3),
initialStepSize: 0.1);
var covariances = 17 * Matrix <double> .Build.DenseIdentity(2);
var covariancesDecomposition = covariances.Evd(Symmetricity.Symmetric);
this._data = new CmaEsElements(
configuration,
generation: 24,
stepSize: 0.14,
distributionMean: Vector <double> .Build.Random(2),
covariances: covariances,
covariancesDecomposition: covariancesDecomposition,
evolutionPath: Vector <double> .Build.Random(2),
conjugateEvolutionPath: Vector <double> .Build.Random(2));
var cmaEsStatus = new CmaEsStatus(this._terminationCriteria, this._data);
/* Write and read it from file. */
cmaEsStatus.WriteToFile(this.StatusFilePath);
var deserializedStatus = StatusBase.ReadFromFile <CmaEsStatus>(this.StatusFilePath);
/* Check it's still the same. */
Assert.Equal(
this._terminationCriteria.Count,
deserializedStatus.TerminationCriteria.Count);
Assert.Equal(
this._terminationCriteria[0].GetType(),
deserializedStatus.TerminationCriteria[0].GetType());
Assert.Equal(
configuration.PopulationSize,
deserializedStatus.Data.Configuration.PopulationSize);
Assert.Equal(
configuration.InitialDistributionMean,
deserializedStatus.Data.Configuration.InitialDistributionMean);
Assert.Equal(
configuration.InitialStepSize,
deserializedStatus.Data.Configuration.InitialStepSize);
Assert.Equal(
this._data.Generation,
deserializedStatus.Data.Generation);
Assert.Equal(
this._data.StepSize,
deserializedStatus.Data.StepSize);
Assert.Equal(
this._data.DistributionMean,
deserializedStatus.Data.DistributionMean);
Assert.Equal(
this._data.Covariances,
deserializedStatus.Data.Covariances);
Assert.Equal(
this._data.CovariancesDiagonal,
deserializedStatus.Data.CovariancesDiagonal);
Assert.Equal(
this._data.CovariancesEigenVectors,
deserializedStatus.Data.CovariancesEigenVectors);
Assert.Equal(
this._data.EvolutionPath,
deserializedStatus.Data.EvolutionPath);
Assert.Equal(
this._data.ConjugateEvolutionPath,
deserializedStatus.Data.ConjugateEvolutionPath);
}
public void ObjectIsImmutable()
{
var data = new CmaEsElements(
this._configuration,
this._generation,
this._distributionMean,
this._stepSize,
this._covariances,
this._covariancesDecomposition,
this._evolutionPath,
this._conjugateEvolutionPath);
// Play around with getters
var returnedMean = data.DistributionMean;
returnedMean.Clear();
Assert.NotEqual(returnedMean, this._distributionMean);
Assert.Equal(this._distributionMean, data.DistributionMean);
var returnedCovariances = data.Covariances;
returnedCovariances.Clear();
Assert.NotEqual(returnedCovariances, this._covariances);
Assert.Equal(this._covariances, data.Covariances);
var returnedDiagonal = data.CovariancesDiagonal;
returnedDiagonal.Clear();
Assert.NotEqual(returnedDiagonal, this._diagonal);
Assert.Equal(this._diagonal, data.CovariancesDiagonal);
var returnedEigenVectors = data.CovariancesEigenVectors;
returnedEigenVectors.Clear();
Assert.NotEqual(returnedEigenVectors, this._eigenvectors);
Assert.Equal(
this._eigenvectors,
data.CovariancesEigenVectors);
var returnedEvolutionPath = data.EvolutionPath;
returnedEvolutionPath.Clear();
Assert.NotEqual(
returnedEvolutionPath,
this._evolutionPath);
Assert.Equal(this._evolutionPath, data.EvolutionPath);
var returnedConjugateEvolutionPath = data.ConjugateEvolutionPath;
returnedConjugateEvolutionPath.Clear();
Assert.NotEqual(
returnedConjugateEvolutionPath,
this._conjugateEvolutionPath);
Assert.Equal(
this._conjugateEvolutionPath,
data.ConjugateEvolutionPath);
// Then change values the object was initialized with.
this._distributionMean.Clear();
Assert.NotEqual(
this._distributionMean,
data.DistributionMean);
this._covariances.Clear();
Assert.NotEqual(this._covariances, data.Covariances);
this._covariancesDecomposition.D.Clear();
Assert.NotEqual(
this._diagonal,
data.CovariancesDiagonal);
this._covariancesDecomposition.EigenVectors.Clear();
Assert.NotEqual(
this._eigenvectors,
data.CovariancesEigenVectors);
this._evolutionPath.Clear();
Assert.NotEqual(this._evolutionPath, data.EvolutionPath);
this._conjugateEvolutionPath.Clear();
Assert.NotEqual(
this._conjugateEvolutionPath,
data.ConjugateEvolutionPath);
}
