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()

Methods

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

canBeLaunched
getElapsedTime
getParentObserver

__init__(self, *args)¶: Initialize self. See help(type(self)) for accurate signature.

getClassName(self)¶

Accessor to the object’s name.

Returns

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

getErrorMessage(self)¶

Error message accessor.

Returns

messagestr: Error message if the analysis failed

getId(self)¶

Accessor to the object’s id.

Returns

idint: Internal unique identifier.

getInterestVariables(self)¶

Get the variables to analyse.

Returns

variablesNamessequence of str: Names of the variables to analyse

getLimitState(self)¶

Limit-state accessor.

Returns

limitStateLimitState: The Limit-state.

getName(self)¶

Accessor to the object’s name.

Returns

namestr: The name of the object.

getOptimizationAlgorithm(self)¶

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(self)¶

Physical model accessor.

Returns

modelPhysicalModel: Physical model

getPhysicalStartingPoint(self)¶

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(self)¶

Physical model accessor.

Returns

scriptstr: Python script to replay the analysis

getResult(self)¶

Result accessor.

Returns

resultSORMAnalysisResult: Result

getShadowedId(self)¶

Accessor to the object’s shadowed id.

Returns

idint: Internal unique identifier.

getVisibility(self)¶

Accessor to the object’s visibility state.

Returns

visiblebool: Visibility flag.

getWarningMessage(self)¶

Warning message accessor.

Returns

messagestr: Warning message which can appear during the analysis computation

hasName(self)¶

Test if the object is named.

Returns

hasNamebool: True if the name is not empty.

hasValidResult(self)¶

Whether the analysis has been run.

Returns

hasValidResultbool: Whether the analysis has already been run

hasVisibleName(self)¶

Test if the object has a distinguishable name.

Returns

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

isReliabilityAnalysis(self)¶

Whether the analysis involves reliability.

Returns

isReliabilityAnalysisbool: Whether the analysis involves a reliability analysis

isRunning(self)¶

Whether the analysis is running.

Returns

isRunningbool: Whether the analysis is running

run(self)¶: Launch the analysis.

setInterestVariables(self, outputsNames)¶

Set the variables to analyse.

Parameters

variablesNamessequence of str: Names of the variables to analyse

setName(self, name)¶

Accessor to the object’s name.

Parameters

namestr: The name of the object.

setOptimizationAlgorithm(self, 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(self, 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(self, id)¶

Accessor to the object’s shadowed id.

Parameters

idint: Internal unique identifier.

setVisibility(self, visible)¶

Accessor to the object’s visibility state.

Parameters

visiblebool: Visibility flag.

SORMAnalysis¶

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