ExpectationSimulationResult

class ExpectationSimulationResult(*args)

Expectation simulation result.

Gathers the results of a ExpectationSimulationAlgorithm algorithm.

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.

getName()

Accessor to the object's name.

getOuterSampling()

Accessor to the outer sampling.

getRandomVector()

Accessor to the random variable.

getStandardDeviation()

Accessor to the expectation distribution.

getTimeDuration()

Accessor to the elapsed time.

getVarianceEstimate()

Accessor to the variance estimate.

hasName()

Test if the object is named.

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.

setTimeDuration(time)

Accessor to the elapsed time.

setVarianceEstimate(varianceEstimate)

Accessor to the variance estimate.

__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.

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.

getStandardDeviation()

Accessor to the expectation distribution.

Returns:
standardDeviationPoint

Standard deviation.

getTimeDuration()

Accessor to the elapsed time.

Returns:
timefloat

Simulation duration in seconds

getVarianceEstimate()

Accessor to the variance estimate.

Returns:
expectationEstimatePoint

Estimate of the variance.

hasName()

Test if the object is named.

Returns:
hasNamebool

True if the name is not empty.

setBlockSize(blockSize)

Accessor to the block size.

Parameters:
blockSizeint, blockSize \geq 0

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, outerSampling \geq 0

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.

setTimeDuration(time)

Accessor to the elapsed time.

Parameters:
timefloat

Simulation duration in seconds

setVarianceEstimate(varianceEstimate)

Accessor to the variance estimate.

Parameters:
expectationEstimatePoint

Estimate of the variance.

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