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.experimentalsubmodule.- See also - Methods - Draw the importance factors. - Accessor to the auxiliary distribution at the final Cross Entropy algorithm step. - Accessor to the auxiliary distribution input sample at the final Cross Entropy algorithm step. - Accessor to the auxiliary distribution output sample at the final Cross Entropy algorithm step. - Accessor to the block size. - Accessor to the object's name. - Accessor to the coefficient of variation. - getConfidenceLength(*args)- Accessor to the confidence length. - getEvent()- Accessor to the event. - Accessor to the importance factors. - Accessor to the mean point conditioned to the event realization. - getName()- Accessor to the object's name. - Accessor to the outer sampling. - Accessor to the asymptotic probability distribution. - Accessor to the probability estimate. - Accessor to the standard deviation. - Accessor to the elapsed time. - 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. 
 
- graph
 - See also 
 - getAuxiliaryDistribution()¶
- Accessor to the auxiliary distribution at the final Cross Entropy algorithm step. - Returns:
- auxiliaryDistributionDistribution
- Auxiliary distribution at the final Cross Entropy algorithm step. 
 
- auxiliaryDistribution
 
 - 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. 
 
- auxiliaryInputSample
 
 - 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. 
 
- auxiliaryOutputSample
 
 - 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 - with - the variance estimate and - the probability estimate. 
 
 
 - getConfidenceLength(*args)¶
- Accessor to the confidence length. - Parameters:
- levelfloat, 
- Confidence level. By default, it is - . 
 
- levelfloat, 
- 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. 
 
- event
 
 - getImportanceFactors()¶
- Accessor to the importance factors. - Returns:
- importanceFactorsPointWithDescription
- Sequence containing the importance factors with a description for each component. 
 
- importanceFactors
 - See also - Notes - The importance factors - are evaluated from the coordinates of the mean point of event domain - , mapped into the standard space as follows: - where - with - the iso-probabilistic transformation and the mean point - . - 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 - EventSimulationalgorithm that failed into the event domain.
 
- meanPoint
 - 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. 
 
- probaDistribution
 
 - 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. 
 
- auxiliaryDistribution
 
 - 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. 
 
- auxiliaryInputSample
 
 - 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. 
 
- auxiliaryOutputSample
 
 - setBlockSize(blockSize)¶
- Accessor to the block size. - Parameters:
- blockSizeint, 
- Number of terms in the probability simulation estimator grouped together. 
 
- blockSizeint, 
 
 - setEvent(event)¶
- Accessor to the event. - Parameters:
- eventRandomVector
- Event we want to evaluate the probability. 
 
- event
 
 - setName(name)¶
- Accessor to the object’s name. - Parameters:
- namestr
- The name of the object. 
 
 
 - setOuterSampling(outerSampling)¶
- Accessor to the outer sampling. - Parameters:
- outerSamplingint, 
- Number of groups of terms in the probability simulation estimator. 
 
- outerSamplingint, 
 
 - setProbabilityEstimate(probabilityEstimate)¶
- Accessor to the probability estimate. - Parameters:
- probaEstimatefloat, 
- Estimate of the event probability. 
 
- probaEstimatefloat, 
 
 - setTimeDuration(time)¶
- Accessor to the elapsed time. - Parameters:
- timefloat
- Simulation duration in seconds 
 
 
 - setVarianceEstimate(varianceEstimate)¶
- Accessor to the variance estimate. - Parameters:
- varianceEstimatefloat, 
- Variance estimate. 
 
- varianceEstimatefloat, 
 
 
 OpenTURNS
      OpenTURNS
    