# SimulationSensitivityAnalysis¶

class SimulationSensitivityAnalysis(*args)

Class to perform a sensitivity analysis based on a reliability event.

Available constructor:

SimulationSensitivityAnalysis(inputSample, outputSample, transformation, comparisonOp, threshold)

SimulationSensitivityAnalysis(event)

SimulationSensitivityAnalysis(simulationRes)

Parameters: inputSample, outputSample : 2-d sequence of float Input sample and output sample of a model evaluated apart. transformation : Function An isoprobabilistic transformation function. comparisonOp : ComparisonOperator A comparison operator. threshold : float A threshold. event : Event An event which it composite (test is with the method isComposite). simulationRes : ProbabilitySimulationResult A simulation result.

Notes

The simulation sensitivity analysis is based on:

• in the first usage, the inputSample and outputSample given:
• in the second usage, the samples which have been stored by the function defining the event. Care if the sample is not a statistical sample: post treatment proposed by the object might not be right.
• in the third usage, the samples generated by the simulation that produced simulationRes.

Methods

 computeImportanceFactors(*args) Compute the importance factors. computeMeanPointInEventDomain(*args) Accessor to the mean point. drawImportanceFactors() Draw the importance factors. drawImportanceFactorsRange(*args) Draw the importance factors evolution. getClassName() Accessor to the object’s name. getComparisonOperator() Accessor to the comparison operator. getId() Accessor to the object’s id. getInputSample() Accessor to the input sample. getName() Accessor to the object’s name. getOutputSample() Accessor to the output sample. getShadowedId() Accessor to the object’s shadowed id. getThreshold() Accessor to the threshold. getTransformation() Accessor to the isoprobabilistic transformation function. getVisibility() Accessor to the object’s visibility state. hasName() Test if the object is named. hasVisibleName() Test if the object has a distinguishable name. setComparisonOperator(comparisonOperator) Accessor to the comparison operator. setName(name) Accessor to the object’s name. setShadowedId(id) Accessor to the object’s shadowed id. setThreshold(threshold) Accessor to the threshold. setVisibility(visible) Accessor to the object’s visibility state.
__init__(*args)

Initialize self. See help(type(self)) for accurate signature.

computeImportanceFactors(*args)

Compute the importance factors.

Returns: impFactors : Point The importance factors.

Notes

The importance factors, given in (2), are evaluated from the coordinates of the mean point (1) of the event domain, mapped into the standard space as follows:

(1)

(2)

where

Be careful: this notion is only valid for MonteCarlo or LHS sampling as the mean is evaluated from the equation (2) (only uniform weights over the realizations .

computeMeanPointInEventDomain(*args)

Accessor to the mean point.

Returns: mean : Point The mean point in the failure domain.

Notes

This method computes the mean point in the physical space of all the simulations generated by the simulation that failed into the event domain.

Be carefull: this notion is only valid for Monte Carlo or LHS sampling as the mean is evaluated from the equation (1) (only uniform weights over the realizations .

drawImportanceFactors()

Draw the importance factors.

Returns: graph : Graph Graph containing the pie corresponding to the importance factors of the probabilistic variables.
drawImportanceFactorsRange(*args)

Draw the importance factors evolution.

Parameters: probabilityScale : boolean Set True if the limits are the probability levels; set False if the limits are the thresholds defining the event. lower, upper : floats Define the boundaries of the probability levels and or those of the thresholds and . graph : Graph A graph that draws the evolution of the importance factors of each direction with respect to or . The importance factors are evaluated from the definition (2) for each threshold s or probability p.
getClassName()

Accessor to the object’s name.

Returns: class_name : str The object class name (object.__class__.__name__).
getComparisonOperator()

Accessor to the comparison operator.

Returns: operator : ComparisonOperator The comparison operator.
getId()

Accessor to the object’s id.

Returns: id : int Internal unique identifier.
getInputSample()

Accessor to the input sample.

Returns: inputSample : Sample The input sample.
getName()

Accessor to the object’s name.

Returns: name : str The name of the object.
getOutputSample()

Accessor to the output sample.

Returns: outputSample : Sample The output sample.
getShadowedId()

Accessor to the object’s shadowed id.

Returns: id : int Internal unique identifier.
getThreshold()

Accessor to the threshold.

Returns: s : float The threshold.
getTransformation()

Accessor to the isoprobabilistic transformation function.

Returns: transformation : Function The isoprobabilistic transformation function.
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.
setComparisonOperator(comparisonOperator)

Accessor to the comparison operator.

Parameters: operator : ComparisonOperator The comparison operator.
setName(name)

Accessor to the object’s name.

Parameters: name : str The name of the object.
setShadowedId(id)

Accessor to the object’s shadowed id.

Parameters: id : int Internal unique identifier.
setThreshold(threshold)

Accessor to the threshold.

Parameters: s : float The threshold.
setVisibility(visible)

Accessor to the object’s visibility state.

Parameters: visible : bool Visibility flag.