/// <summary>Initializes a new instance of the
/// <see cref="TestablePartitionOptimizationContext"/>
/// class.</summary>
/// <param name="context">The context to test.</param>
/// <param name="stateDimension">The expected state dimension.</param>
/// <param name="eliteSampleDefinition">The expected elite sample definition.</param>
/// <param name="traceExecution">The expected value about tracing context execution.</param>
/// <param name="optimizationGoal">The expected optimization goal.</param>
/// <param name="initialParameter">The expected initial parameter.</param>
/// <param name="minimumNumberOfIterations">
/// The expected minimum number of iterations.</param>
/// <param name="maximumNumberOfIterations">
/// The expected maximum number of iterations.</param>
/// <param name="optimalState">The expected optimal state.</param>
/// <param name="optimalPerformance">The expected optimal performance.</param>
/// <param name="objectiveFunction">The expected objective function.</param>
/// <param name="partitionDimension">The expected partition dimension.</param>
/// <param name="probabilitySmoothingCoefficient">The expected probability smoothing coefficient.</param>
public TestablePartitionOptimizationContext(
PartitionOptimizationContext context,
int stateDimension,
EliteSampleDefinition eliteSampleDefinition,
bool traceExecution,
OptimizationGoal optimizationGoal,
DoubleMatrix initialParameter,
int minimumNumberOfIterations,
int maximumNumberOfIterations,
DoubleMatrix optimalState,
double optimalPerformance,
Func <DoubleMatrix, double> objectiveFunction,
int partitionDimension,
double probabilitySmoothingCoefficient
) : base(
context,
stateDimension,
eliteSampleDefinition,
traceExecution,
optimizationGoal,
initialParameter,
minimumNumberOfIterations,
maximumNumberOfIterations,
optimalState,
optimalPerformance)
{
this.ObjectiveFunction = objectiveFunction;
this.PartitionDimension = partitionDimension;
this.ProbabilitySmoothingCoefficient = probabilitySmoothingCoefficient;
}
/// <summary>Initializes a new instance of the
/// <see cref="TestableCrossEntropyContext"/>
/// class.</summary>
/// <param name="stateDimension">The expected state dimension.</param>
/// <param name="eliteSampleDefinition">The expected elite sample definition.</param>
/// <param name="traceExecution">The expected value about tracing context execution.</param>
public TestableCrossEntropyContext(
TCrossEntropyContext context,
int stateDimension,
EliteSampleDefinition eliteSampleDefinition,
bool traceExecution
)
{
this.Context = context;
this.StateDimension = stateDimension;
this.EliteSampleDefinition = eliteSampleDefinition;
this.TraceExecution = traceExecution;
}
/// <summary>Initializes a new instance of the
/// <see cref="TestablePartitionOptimizationContext"/>
/// class.</summary>
/// <param name="context">The context to test.</param>
/// <param name="stateDimension">The expected state dimension.</param>
/// <param name="eliteSampleDefinition">The expected elite sample definition.</param>
/// <param name="traceExecution">The expected value about tracing context execution.</param>
/// <param name="optimizationGoal">The expected optimization goal.</param>
/// <param name="initialParameter">The expected initial parameter.</param>
/// <param name="minimumNumberOfIterations">
/// The expected minimum number of iterations.</param>
/// <param name="maximumNumberOfIterations">
/// The expected maximum number of iterations.</param>
/// <param name="optimalState">The expected optimal state.</param>
/// <param name="optimalPerformance">The expected optimal performance.</param>
/// <param name="objectiveFunction">The expected objective function.</param>
/// <param name="featureVariables">
/// The expected feature variables.</param>
/// <param name="responseVariable">
/// The expected response variable.</param>
/// <param name="numberOfResponseCategories">
/// The expected number of response categories</param>
/// <param name="numberOfCategoricalEntailments">
/// The expected number of categorical entailments.
/// </param>
/// <param name="allowEntailmentPartialTruthValues">
/// The expected allowance for entailment partial truth values.
/// </param>
/// <param name="probabilitySmoothingCoefficient">
/// The expected probability smoothing coefficient.</param>
public TestableCategoricalEntailmentEnsembleOptimizationContext(
CategoricalEntailmentEnsembleOptimizationContext context,
int stateDimension,
EliteSampleDefinition eliteSampleDefinition,
bool traceExecution,
OptimizationGoal optimizationGoal,
DoubleMatrix initialParameter,
int minimumNumberOfIterations,
int maximumNumberOfIterations,
DoubleMatrix optimalState,
double optimalPerformance,
Func <DoubleMatrix, double> objectiveFunction,
List <CategoricalVariable> featureVariables,
CategoricalVariable responseVariable,
int numberOfResponseCategories,
int numberOfCategoricalEntailments,
bool allowEntailmentPartialTruthValues,
double probabilitySmoothingCoefficient
) : base(
context,
stateDimension,
eliteSampleDefinition,
traceExecution,
optimizationGoal,
initialParameter,
minimumNumberOfIterations,
maximumNumberOfIterations,
optimalState,
optimalPerformance)
{
this.ObjectiveFunction = objectiveFunction;
this.FeatureVariables = featureVariables;
this.ResponseVariable = responseVariable;
var featureCategoryCounts = new List <int>(featureVariables.Count);
for (int i = 0; i < featureVariables.Count; i++)
{
featureCategoryCounts.Add(featureVariables[i].NumberOfCategories);
}
this.FeatureCategoryCounts = featureCategoryCounts;
this.NumberOfResponseCategories = numberOfResponseCategories;
this.NumberOfCategoricalEntailments = numberOfCategoricalEntailments;
this.AllowEntailmentPartialTruthValues = allowEntailmentPartialTruthValues;
this.ProbabilitySmoothingCoefficient = probabilitySmoothingCoefficient;
}
/// <summary>Initializes a new instance of the
/// <see cref="TestableRareEventProbabilityEstimationContext"/>
/// class.</summary>
/// <param name="context">The context to test.</param>
/// <param name="stateDimension">The expected state dimension.</param>
/// <param name="eliteSampleDefinition">The expected elite sample definition.</param>
/// <param name="traceExecution">The expected value about tracing context execution.</param>
/// <param name="thresholdLevel">The expected elite threshold level.</param>
/// <param name="rareEventPerformanceBoundedness">The expected rare event performance boundedness.</param>
/// <param name="initialParameter">The expected nominal parameter.</param>
/// <param name="rareEventProbability">The expected rare event probability.</param>
public TestableRareEventProbabilityEstimationContext(
RareEventProbabilityEstimationContext context,
int stateDimension,
EliteSampleDefinition eliteSampleDefinition,
bool traceExecution,
double thresholdLevel,
RareEventPerformanceBoundedness rareEventPerformanceBoundedness,
DoubleMatrix initialParameter,
double rareEventProbability
) : base(
context,
stateDimension,
eliteSampleDefinition,
traceExecution)
{
this.ThresholdLevel = thresholdLevel;
this.RareEventPerformanceBoundedness = rareEventPerformanceBoundedness;
this.NominalParameter = initialParameter;
this.RareEventProbability = rareEventProbability;
}
/// <summary>Initializes a new instance of the
/// <see cref="TestableContinuousOptimizationContext"/>
/// class.</summary>
/// <param name="context">The context to test.</param>
/// <param name="stateDimension">The expected state dimension.</param>
/// <param name="eliteSampleDefinition">The expected elite sample definition.</param>
/// <param name="traceExecution">The expected value about tracing context execution.</param>
/// <param name="optimizationGoal">The expected optimization goal.</param>
/// <param name="initialParameter">The expected initial parameter.</param>
/// <param name="minimumNumberOfIterations">
/// The expected minimum number of iterations.</param>
/// <param name="maximumNumberOfIterations">
/// The expected maximum number of iterations.</param>
/// <param name="optimalState">The expected optimal state.</param>
/// <param name="optimalPerformance">The expected optimal performance.</param>
/// <param name="objectiveFunction">The expected objective function.</param>
/// <param name="initialArgument">The expected initial argument.</param>
/// <param name="meanSmoothingCoefficient">The expected mean smoothing coefficient.</param>
/// <param name="standardDeviationSmoothingCoefficient">The expected standard deviation smoothing coefficient.</param>
/// <param name="standardDeviationSmoothingExponent">The expected standard deviation smoothing exponent.</param>
/// <param name="initialStandardDeviation">The expected initial standard deviation.</param>
/// <param name="terminationTolerance">The expected termination tolerance.</param>
public TestableContinuousOptimizationContext(
ContinuousOptimizationContext context,
int stateDimension,
EliteSampleDefinition eliteSampleDefinition,
bool traceExecution,
OptimizationGoal optimizationGoal,
DoubleMatrix initialParameter,
int minimumNumberOfIterations,
int maximumNumberOfIterations,
DoubleMatrix optimalState,
double optimalPerformance,
Func <DoubleMatrix, double> objectiveFunction,
DoubleMatrix initialArgument,
double meanSmoothingCoefficient,
double standardDeviationSmoothingCoefficient,
int standardDeviationSmoothingExponent,
double initialStandardDeviation,
double terminationTolerance
) : base(
context,
stateDimension,
eliteSampleDefinition,
traceExecution,
optimizationGoal,
initialParameter,
minimumNumberOfIterations,
maximumNumberOfIterations,
optimalState,
optimalPerformance)
{
this.ObjectiveFunction = objectiveFunction;
this.InitialArgument = initialArgument;
this.MeanSmoothingCoefficient = meanSmoothingCoefficient;
this.StandardDeviationSmoothingCoefficient = standardDeviationSmoothingCoefficient;
this.StandardDeviationSmoothingExponent = standardDeviationSmoothingExponent;
this.InitialStandardDeviation = initialStandardDeviation;
this.TerminationTolerance = terminationTolerance;
}
/// <summary>Initializes a new instance of the
/// <see cref="TestableSystemPerformanceOptimizationContext"/>
/// class.</summary>
/// <param name="context">The context to test.</param>
/// <param name="stateDimension">The expected state dimension.</param>
/// <param name="eliteSampleDefinition">The expected elite sample definition.</param>
/// <param name="traceExecution">The expected value about tracing context execution.</param>
/// <param name="optimizationGoal">The expected optimization goal.</param>
/// <param name="initialParameter">The expected initial parameter.</param>
/// <param name="minimumNumberOfIterations">
/// The expected minimum number of iterations.</param>
/// <param name="maximumNumberOfIterations">
/// The expected maximum number of iterations.</param>
/// <param name="optimalState">The expected optimal state.</param>
/// <param name="optimalPerformance">The expected optimal performance.</param>
public TestableSystemPerformanceOptimizationContext(
TCrossEntropyContext context,
int stateDimension,
EliteSampleDefinition eliteSampleDefinition,
bool traceExecution,
OptimizationGoal optimizationGoal,
DoubleMatrix initialParameter,
int minimumNumberOfIterations,
int maximumNumberOfIterations,
DoubleMatrix optimalState,
double optimalPerformance
) : base(
context,
stateDimension,
eliteSampleDefinition,
traceExecution)
{
this.OptimizationGoal = optimizationGoal;
this.InitialParameter = initialParameter;
this.MinimumNumberOfIterations = minimumNumberOfIterations;
this.MaximumNumberOfIterations = maximumNumberOfIterations;
this.OptimalState = optimalState;
this.OptimalPerformance = optimalPerformance;
}
/// <summary>
/// Updates the performance level for the current iteration
/// of a <see cref="CrossEntropyProgram"/> executing in
/// this context
/// and determines the corresponding elite sample.
/// </summary>
/// <param name="performances">
/// The performances of the
/// points in the current sample.
/// </param>
/// <param name="sample">
/// The current sample.
/// </param>
/// <param name="eliteSampleDefinition">
/// The elite sample mode.
/// </param>
/// <param name="rarity">
/// The rarity applied to define the elite sample.
/// </param>
/// <param name="eliteSample">
/// The elite sample.
/// </param>
/// <returns>
/// The performance level for the current iteration.
/// </returns>
/// <remarks>
/// <inheritdoc cref="CrossEntropyContext"
/// path="para[@id='LevelUpdate']"/>
/// </remarks>
protected internal abstract double UpdateLevel(
DoubleMatrix performances,
DoubleMatrix sample,
EliteSampleDefinition eliteSampleDefinition,
double rarity,
out DoubleMatrix eliteSample);
/// <inheritdoc/>
/// <exception cref="ArgumentNullException">
/// <paramref name="performances"/> is <b>null</b>.<br/>
/// -or-<br/>
/// <paramref name="sample"/> is <b>null</b>.
/// </exception>
protected internal override sealed double UpdateLevel(
DoubleMatrix performances,
DoubleMatrix sample,
EliteSampleDefinition eliteSampleDefinition,
double rarity,
out DoubleMatrix eliteSample)
{
if (performances is null)
{
throw new ArgumentNullException(nameof(performances));
}
if (sample is null)
{
throw new ArgumentNullException(nameof(sample));
}
var performanceArray = performances.GetStorage();
SortHelper.Sort(
performanceArray,
SortDirection.Ascending,
out int[] indexTable);
if (this.TraceExecution)
{
Trace.WriteLine(
"Sample points ordered by performance:");
var sampleInfo = DoubleMatrix.Dense(
numberOfRows: sample.NumberOfRows,
numberOfColumns: this.StateDimension + 1);
sampleInfo.SetColumnName(0, "Performance");
for (int j = 1; j < sampleInfo.NumberOfColumns; j++)
{
sampleInfo.SetColumnName(j, "S" + j);
}
sampleInfo[":", 0] = performances;
sampleInfo[":", IndexCollection.Range(1, this.StateDimension)]
= sample[
IndexCollection.FromArray(indexTable, false), ":"];
Trace.WriteLine(sampleInfo);
}
int eliteFirstIndex = 0;
int eliteLastIndex = 0;
int sampleSize = sample.NumberOfRows;
double level = Double.NaN;
double thresholdLevel = this.ThresholdLevel;
// Compute the relevant sample percentile (the level)
// and achieved performance
switch (eliteSampleDefinition)
{
case EliteSampleDefinition.HigherThanLevel:
eliteFirstIndex = Convert.ToInt32(
Math.Ceiling(sampleSize * (1 - rarity)));
eliteLastIndex = sampleSize - 1;
level = performanceArray[eliteFirstIndex];
if (level > thresholdLevel)
{
level = thresholdLevel;
}
break;
case EliteSampleDefinition.LowerThanLevel:
eliteFirstIndex = 0;
eliteLastIndex = Convert.ToInt32(
Math.Ceiling(sampleSize * rarity));
level = performanceArray[eliteLastIndex];
if (level < thresholdLevel)
{
level = thresholdLevel;
}
break;
}
// Update the reference parameter
var eliteSamplePositions =
IndexCollection.Range(eliteFirstIndex, eliteLastIndex);
if (this.TraceExecution)
{
Trace.WriteLine(
string.Format(
CultureInfo.InvariantCulture,
"Elite positions: {0} - {1}.",
eliteFirstIndex,
eliteLastIndex));
}
var sortedIndexes =
IndexCollection.FromArray(indexTable, false);
eliteSample = sample[sortedIndexes[eliteSamplePositions], ":"];
return(level);
}
