SORMAnalysis

class persalys.SORMAnalysis(*args)

Run a reliability analysis using the SORM method.

Parameters

namestr

Name

limitStateLimitState

Limit state

Examples

>>> import openturns as ot
>>> import persalys

Create the model:

>>> R = persalys.Input('R', 0., ot.LogNormalMuSigma(300., 30., 0.).getDistribution(), 'Yield strength')
>>> F = persalys.Input('F', 0., ot.Normal(75000., 5000.), 'Traction load')
>>> G = persalys.Output('G', 'deviation')
>>> myPhysicalModel = persalys.SymbolicPhysicalModel('myPhysicalModel', [R, F], [G], ['R-F/(pi_*100.0)'])

Create the limit state:

>>> limitState = persalys.LimitState('ls1', myPhysicalModel, 'G', ot.Less(), 0.)

Process a reliability analysis using the SORM method:

>>> analysis = persalys.SORMAnalysis('myAnalysis', limitState)
>>> analysis.run()

Get the result:

>>> result = analysis.getResult().getSORMResult()
>>> pf = result.getEventProbabilityBreitung()
>>> designPoint = result.getStandardSpaceDesignPoint()

Attributes

thisown

The membership flag

Methods

getClassName()	Accessor to the object's name.
getErrorMessage()	Error message accessor.
getId()	Accessor to the object's id.
getInterestVariables()	Get the variables to analyse.
getLimitState()	Limit-state accessor.
getName()	Accessor to the object's name.
getOptimizationAlgorithm()	Accessor to the optimization algorithm used to find the design point.
getPhysicalModel()	Physical model accessor.
getPhysicalStartingPoint()	Physical starting point accessor.
getPythonScript()	Physical model accessor.
getResult()	Result accessor.
getShadowedId()	Accessor to the object's shadowed id.
getVisibility()	Accessor to the object's visibility state.
getWarningMessage()	Warning message accessor.
hasName()	Test if the object is named.
hasValidResult()	Whether the analysis has been run.
hasVisibleName()	Test if the object has a distinguishable name.
isReliabilityAnalysis()	Whether the analysis involves reliability.
isRunning()	Whether the analysis is running.
run()	Launch the analysis.
setInterestVariables(outputsNames)	Set the variables to analyse.
setName(name)	Accessor to the object's name.
setOptimizationAlgorithm(solver)	Accessor to the optimization algorithm used to find the design point.
setPhysicalStartingPoint(point)	Physical starting point accessor.
setShadowedId(id)	Accessor to the object's shadowed id.
setVisibility(visible)	Accessor to the object's visibility state.

canBeLaunched
getElapsedTime
getParentObserver

__init__(*args)

getClassName()

Accessor to the object’s name.

Returns

class_namestr

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

getErrorMessage()

Error message accessor.

Returns

messagestr

Error message if the analysis failed

getId()

Accessor to the object’s id.

Returns

idint

Internal unique identifier.

getInterestVariables()

Get the variables to analyse.

Returns

variablesNamessequence of str

Names of the variables to analyse

getLimitState()

Limit-state accessor.

Returns

limitStateLimitState

The Limit-state.

getName()

Accessor to the object’s name.

Returns

namestr

The name of the object.

getOptimizationAlgorithm()

Accessor to the optimization algorithm used to find the design point.

Returns

algorithmopenturns.OptimizationAlgorithm

Optimization algorithm used to research the design point. Cobyla is the default used algorithm.

getPhysicalModel()

Physical model accessor.

Returns

modelPhysicalModel

Physical model

getPhysicalStartingPoint()

Physical starting point accessor.

Returns

pointopenturns.Point

Physical starting point. By default it set to the mean of the composed distribution of the physical model

getPythonScript()

Physical model accessor.

Returns

scriptstr

Python script to replay the analysis

getResult()

Result accessor.

Returns

resultSORMAnalysisResult

Result

getShadowedId()

Accessor to the object’s shadowed id.

Returns

idint

Internal unique identifier.

getVisibility()

Accessor to the object’s visibility state.

Returns

visiblebool

Visibility flag.

getWarningMessage()

Warning message accessor.

Returns

messagestr

Warning message which can appear during the analysis computation

hasName()

Test if the object is named.

Returns

hasNamebool

True if the name is not empty.

hasValidResult()

Whether the analysis has been run.

Returns

hasValidResultbool

Whether the analysis has already been run

hasVisibleName()

Test if the object has a distinguishable name.

Returns

hasVisibleNamebool

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

isReliabilityAnalysis()

Whether the analysis involves reliability.

Returns

isReliabilityAnalysisbool

Whether the analysis involves a reliability analysis

isRunning()

Whether the analysis is running.

Returns

isRunningbool

Whether the analysis is running

run()

Launch the analysis.

setInterestVariables(outputsNames)

Set the variables to analyse.

Parameters

variablesNamessequence of str

Names of the variables to analyse

setName(name)

Accessor to the object’s name.

Parameters

namestr

The name of the object.

setOptimizationAlgorithm(solver)

Accessor to the optimization algorithm used to find the design point.

Parameters

algorithmopenturns.OptimizationAlgorithm

Optimization algorithm used to research the design point. Cobyla is the default used algorithm.

setPhysicalStartingPoint(point)

Physical starting point accessor.

Parameters

pointsequence of float

Physical starting point. By default it set to the mean of the composed distribution of the physical model

setShadowedId(id)

Accessor to the object’s shadowed id.

Parameters

idint

Internal unique identifier.

setVisibility(visible)

Accessor to the object’s visibility state.

Parameters

visiblebool

Visibility flag.

property thisown

The membership flag