SubsetSamplingResult

class SubsetSamplingResult(*args)

Subset sampling result.

Methods

drawImportanceFactors() Draw the importance factors as an OpenTURNS Graph.
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.
getId() Accessor to the object’s id.
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.
getProbabilityEstimate() Accessor to the probability estimate.
getShadowedId() Accessor to the object’s shadowed id.
getStandardDeviation() Accessor to the standard deviation.
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.
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.
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)

x.__init__(…) initializes x; see help(type(x)) for signature

drawImportanceFactors()

Draw the importance factors as an OpenTURNS Graph.

Warning

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

getBlockSize()

Accessor to the block size.

Returns:

blockSize : int

Number of terms in the probability simulation estimator grouped together.

getClassName()

Accessor to the object’s name.

Returns:

class_name : str

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

getCoefficientOfVariation()

Accessor to the coefficient of variation.

Returns:

coefficient : float

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:

level : float, level \in ]0, 1[

Confidence level. By default, it is 0.95.

Returns:

confidenceLength : float

Length of the confidence interval at the confidence level level.

getEvent()

Accessor to the event.

Returns:

event : Event

Event we want to evaluate the probability.

getId()

Accessor to the object’s id.

Returns:

id : int

Internal unique identifier.

getImportanceFactors()

Accessor to the importance factors.

Returns:

importanceFactors : PointWithDescription

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 mecanism of the model is activated (see enableHistory()).

getMeanPointInEventDomain()

Accessor to the mean point conditioned to the event realization.

Returns:

meanPoint : Point

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

Notes

Warning

This notion is only available if the history mecanism of the model is activated (see enableHistory()).

getName()

Accessor to the object’s name.

Returns:

name : str

The name of the object.

getOuterSampling()

Accessor to the outer sampling.

Returns:

outerSampling : int

Number of groups of terms in the probability simulation estimator.

getProbabilityEstimate()

Accessor to the probability estimate.

Returns:

probaEstimate : float

Estimate of the event probability.

getShadowedId()

Accessor to the object’s shadowed id.

Returns:

id : int

Internal unique identifier.

getStandardDeviation()

Accessor to the standard deviation.

Returns:

sigma : float

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

getVarianceEstimate()

Accessor to the variance estimate.

Returns:

varianceEstimate : float

Variance estimate.

getVisibility()

Accessor to the object’s visibility state.

Returns:

visible : bool

Visibility flag.

hasName()

Test if the object is named.

Returns:

hasName : bool

True if the name is not empty.

hasVisibleName()

Test if the object has a distinguishable name.

Returns:

hasVisibleName : bool

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

setBlockSize(blockSize)

Accessor to the block size.

Parameters:

blockSize : int, blockSize \geq 0

Number of terms in the probability simulation estimator grouped together.

setEvent(event)

Accessor to the event.

Parameters:

event : Event

Event we want to evaluate the probability.

setName(name)

Accessor to the object’s name.

Parameters:

name : str

The name of the object.

setOuterSampling(outerSampling)

Accessor to the outer sampling.

Parameters:

outerSampling : int, outerSampling \geq 0

Number of groups of terms in the probability simulation estimator.

setProbabilityEstimate(probabilityEstimate)

Accessor to the probability estimate.

Parameters:

probaEstimate : float, 0 \leq P_e \leq 1

Estimate of the event probability.

setShadowedId(id)

Accessor to the object’s shadowed id.

Parameters:

id : int

Internal unique identifier.

setVarianceEstimate(varianceEstimate)

Accessor to the variance estimate.

Parameters:

varianceEstimate : float, Var_e \geq 0

Variance estimate.

setVisibility(visible)

Accessor to the object’s visibility state.

Parameters:

visible : bool

Visibility flag.