ExpectationSimulationResult

class ExpectationSimulationResult(*args)

Expectation simulation result.

Gathers the results of a ExpectationSimulationAlgorithm algorithm.

See also

ExpectationSimulationAlgorithm

Methods

getBlockSize()	Accessor to the block size.
getClassName()	Accessor to the object's name.
getCoefficientOfVariation()	Accessor to the expectation distribution.
getExpectationDistribution()	Accessor to the expectation distribution.
getExpectationEstimate()	Accessor to the expectation estimate.
getId()	Accessor to the object's id.
getName()	Accessor to the object's name.
getOuterSampling()	Accessor to the outer sampling.
getRandomVector()	Accessor to the random variable.
getShadowedId()	Accessor to the object's shadowed id.
getStandardDeviation()	Accessor to the expectation distribution.
getVarianceEstimate()	Accessor to the variance estimate.
getVisibility()	Accessor to the object's visibility state.
hasName()	Test if the object is named.
hasVisibleName()	Test if the object has a distinguishable name.
setBlockSize(blockSize)	Accessor to the block size.
setExpectationEstimate(expectationEstimate)	Accessor to the expectation estimate.
setName(name)	Accessor to the object's name.
setOuterSampling(outerSampling)	Accessor to the outer sampling.
setRandomVector(randomVector)	Accessor to the random variable.
setShadowedId(id)	Accessor to the object's shadowed id.
setVarianceEstimate(varianceEstimate)	Accessor to the variance estimate.
setVisibility(visible)	Accessor to the object's visibility state.

__init__(*args)

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 expectation distribution.

Returns:

coefficientOfVariationPoint

Coefficient of variation.

getExpectationDistribution()

Accessor to the expectation distribution.

Returns:

expectationEstimateDistribution

Distribution of the expectation.

getExpectationEstimate()

Accessor to the expectation estimate.

Returns:

expectationEstimatePoint

Estimate of the expectation.

getId()

Accessor to the object’s id.

Returns:

idint

Internal unique identifier.

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.

getRandomVector()

Accessor to the random variable.

Returns:

eventRandomVector

Random variable we want to study.

getShadowedId()

Accessor to the object’s shadowed id.

Returns:

idint

Internal unique identifier.

getStandardDeviation()

Accessor to the expectation distribution.

Returns:

standardDeviationPoint

Standard deviation.

getVarianceEstimate()

Accessor to the variance estimate.

Returns:

expectationEstimatePoint

Estimate of the variance.

getVisibility()

Accessor to the object’s visibility state.

Returns:

visiblebool

Visibility flag.

hasName()

Test if the object is named.

Returns:

hasNamebool

True if the name is not empty.

hasVisibleName()

Test if the object has a distinguishable name.

Returns:

hasVisibleNamebool

True if the name is not empty and not the default one.

setBlockSize(blockSize)

Accessor to the block size.

Parameters:

blockSizeint,

Number of terms in the probability simulation estimator grouped together.

setExpectationEstimate(expectationEstimate)

Accessor to the expectation estimate.

Parameters:

expectationEstimatePoint

Estimate of the expectation.

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.

setRandomVector(randomVector)

Accessor to the random variable.

Parameters:

eventRandomVector

Random variable we want to study.

setShadowedId(id)

Accessor to the object’s shadowed id.

Parameters:

idint

Internal unique identifier.

setVarianceEstimate(varianceEstimate)

Accessor to the variance estimate.

Parameters:

expectationEstimatePoint

Estimate of the variance.

setVisibility(visible)

Accessor to the object’s visibility state.

Parameters:

visiblebool

Visibility flag.

Examples using the class

Kriging: propagate uncertainties

Kriging: propagate uncertainties

Evaluate the mean of a random vector by simulations

Evaluate the mean of a random vector by simulations

Analyse the central tendency of a cantilever beam

Analyse the central tendency of a cantilever beam