CrossEntropyResult

class CrossEntropyResult(*args)

Cross Entropy result.

Warning

This class is experimental and likely to be modified in future releases. To use it, import the openturns.experimental submodule.

Methods

drawImportanceFactors()

Draw the importance factors.

getAuxiliaryDistribution()

Accessor to the auxiliary distribution at the final Cross Entropy algorithm step.

getAuxiliaryInputSample()

Accessor to the auxiliary distribution input sample at the final Cross Entropy algorithm step.

getAuxiliaryOutputSample()

Accessor to the auxiliary distribution output sample at the final Cross Entropy algorithm step.

getBlockSize()

Accessor to the block size.

getClassName()

Accessor to the object's name.

getCoefficientOfVariation()

Accessor to the coefficient of variation.

getConfidenceLength(*args)

Accessor to the confidence length.

getEvent()

Accessor to the event.

getImportanceFactors()

Accessor to the importance factors.

getMeanPointInEventDomain()

Accessor to the mean point conditioned to the event realization.

getName()

Accessor to the object's name.

getOuterSampling()

Accessor to the outer sampling.

getProbabilityDistribution()

Accessor to the asymptotic probability distribution.

getProbabilityEstimate()

Accessor to the probability estimate.

getStandardDeviation()

Accessor to the standard deviation.

getTimeDuration()

Accessor to the elapsed time.

getVarianceEstimate()

Accessor to the variance estimate.

hasName()

Test if the object is named.

setAuxiliaryDistribution(auxiliaryDistribution)

Accessor to the auxiliary distribution at the final Cross Entropy algorithm step.

setAuxiliaryInputSample(auxiliaryInputSample)

Accessor to the auxiliary distribution input sample at the final Cross Entropy algorithm step.

setAuxiliaryOutputSample(auxiliaryInputSample)

Accessor to the auxiliary distribution output sample at the final Cross Entropy algorithm step.

setBlockSize(blockSize)

Accessor to the block size.

setEvent(event)

Accessor to the event.

setName(name)

Accessor to the object's name.

setOuterSampling(outerSampling)

Accessor to the outer sampling.

setProbabilityEstimate(probabilityEstimate)

Accessor to the probability estimate.

setTimeDuration(time)

Accessor to the elapsed time.

setVarianceEstimate(varianceEstimate)

Accessor to the variance estimate.

__init__(*args)
drawImportanceFactors()

Draw the importance factors.

Warning

It is necessary to enable the history of the model to perform this analysis (see MemoizeFunction).

Returns:
graphGraph

Importance factor graph.

getAuxiliaryDistribution()

Accessor to the auxiliary distribution at the final Cross Entropy algorithm step.

Returns:
auxiliaryDistributionDistribution

Auxiliary distribution at the final Cross Entropy algorithm step.

getAuxiliaryInputSample()

Accessor to the auxiliary distribution input sample at the final Cross Entropy algorithm step.

Returns:
auxiliaryInputSampleSample

Auxiliary distribution input sample at the final Cross Entropy algorithm step.

getAuxiliaryOutputSample()

Accessor to the auxiliary distribution output sample at the final Cross Entropy algorithm step.

Returns:
auxiliaryOutputSampleSample

Auxiliary distribution output sample at the final Cross Entropy algorithm step.

getBlockSize()

Accessor to the block size.

Returns:
blockSizeint

Number of terms in the probability simulation estimator grouped together.

getClassName()

Accessor to the object’s name.

Returns:
class_namestr

The object class name (object.__class__.__name__).

getCoefficientOfVariation()

Accessor to the coefficient of variation.

Returns:
coefficientfloat

Coefficient of variation of the simulated sample which is equal to \sqrt{Var_e} / P_e with Var_e the variance estimate and P_e the probability estimate.

getConfidenceLength(*args)

Accessor to the confidence length.

Parameters:
levelfloat, level \in ]0, 1[

Confidence level. By default, it is 0.95.

Returns:
confidenceLengthfloat

Length of the confidence interval at the confidence level level.

getEvent()

Accessor to the event.

Returns:
eventRandomVector

Event we want to evaluate the probability.

getImportanceFactors()

Accessor to the importance factors.

Returns:
importanceFactorsPointWithDescription

Sequence containing the importance factors with a description for each component.

Notes

The importance factors \alpha_i are evaluated from the coordinates of the mean point of event domain \vect{X}^*_{event}, mapped into the standard space as follows:

\alpha_i = \displaystyle \frac{\left(U_{i}^*\right)^2}{||\vect{U}^*||^2}

where \vect{U}^* = T(\vect{X}^*_{event}) with T the iso-probabilistic transformation and the mean point \vect{X}^*_{event} = \displaystyle \frac{1}{n} \sum_{i=1}^{n} \vect{X}_i 1_{event}(\vect{X}_i).

Warning

This notion is only available if the history mechanism of the model is activated (see MemoizeFunction).

getMeanPointInEventDomain()

Accessor to the mean point conditioned to the event realization.

Returns:
meanPointPoint

Mean point in the physical space of all the simulations generated by the EventSimulation algorithm that failed into the event domain.

Notes

Warning

This notion is only available if the history mechanism of the model is activated (see MemoizeFunction).

getName()

Accessor to the object’s name.

Returns:
namestr

The name of the object.

getOuterSampling()

Accessor to the outer sampling.

Returns:
outerSamplingint

Number of groups of terms in the probability simulation estimator.

getProbabilityDistribution()

Accessor to the asymptotic probability distribution.

Returns:
probaDistributionNormal

Asymptotic normal distribution of the event probability estimate.

getProbabilityEstimate()

Accessor to the probability estimate.

Returns:
probaEstimatefloat

Estimate of the event probability.

getStandardDeviation()

Accessor to the standard deviation.

Returns:
sigmafloat

Standard deviation of the estimator at the end of the simulation.

getTimeDuration()

Accessor to the elapsed time.

Returns:
timefloat

Simulation duration in seconds

getVarianceEstimate()

Accessor to the variance estimate.

Returns:
varianceEstimatefloat

Variance estimate.

hasName()

Test if the object is named.

Returns:
hasNamebool

True if the name is not empty.

setAuxiliaryDistribution(auxiliaryDistribution)

Accessor to the auxiliary distribution at the final Cross Entropy algorithm step.

Parameters:
auxiliaryDistributionDistribution

Auxiliary distribution at the final Cross Entropy algorithm step.

setAuxiliaryInputSample(auxiliaryInputSample)

Accessor to the auxiliary distribution input sample at the final Cross Entropy algorithm step.

Parameters:
auxiliaryInputSampleSample

Auxiliary distribution input sample at the final Cross Entropy algorithm step.

setAuxiliaryOutputSample(auxiliaryInputSample)

Accessor to the auxiliary distribution output sample at the final Cross Entropy algorithm step.

Parameters:
auxiliaryOutputSampleSample

Auxiliary distribution output sample at the final Cross Entropy algorithm step.

setBlockSize(blockSize)

Accessor to the block size.

Parameters:
blockSizeint, blockSize \geq 0

Number of terms in the probability simulation estimator grouped together.

setEvent(event)

Accessor to the event.

Parameters:
eventRandomVector

Event we want to evaluate the probability.

setName(name)

Accessor to the object’s name.

Parameters:
namestr

The name of the object.

setOuterSampling(outerSampling)

Accessor to the outer sampling.

Parameters:
outerSamplingint, outerSampling \geq 0

Number of groups of terms in the probability simulation estimator.

setProbabilityEstimate(probabilityEstimate)

Accessor to the probability estimate.

Parameters:
probaEstimatefloat, 0 \leq P_e \leq 1

Estimate of the event probability.

setTimeDuration(time)

Accessor to the elapsed time.

Parameters:
timefloat

Simulation duration in seconds

setVarianceEstimate(varianceEstimate)

Accessor to the variance estimate.

Parameters:
varianceEstimatefloat, Var_e \geq 0

Variance estimate.

Examples using the class

Cross Entropy Importance Sampling

Cross Entropy Importance Sampling