TaylorExpansionMomentsAnalysis

class persalys.TaylorExpansionMomentsAnalysis(*args)

Get the Taylor expansions for moments estimation.

Parameters:

namestr

Name

physicalModelPhysicalModel

Physical model

Methods

getClassName()	Accessor to the object's name.
getErrorMessage()	Error message accessor.
getInterestVariables()	Get the variables to analyse.
getName()	Accessor to the object's name.
getPhysicalModel()	Physical model accessor.
getPythonScript()	Physical model accessor.
getResult()	Result accessor.
getWarningMessage()	Warning message accessor.
hasName()	Test if the object is named.
hasValidResult()	Whether the analysis has been run.
isReliabilityAnalysis()	Whether the analysis involves reliability.
isRunning()	Whether the analysis is running.
run()	Launch the analysis.
setInterestVariables(variablesNames)	Set the variables to analyse.
setName(name)	Accessor to the object's name.

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 Taylor expansion analysis:

>>> analysis = persalys.TaylorExpansionMomentsAnalysis('anAnalysis', myPhysicalModel)
>>> analysis.run()

Get the result:

>>> result = analysis.getResult()
>>> mean = result.getMeanFirstOrder()

__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

getInterestVariables()

Get the variables to analyse.

Returns:

variablesNamessequence of str

Names of the variables to analyse

getName()

Accessor to the object’s name.

Returns:

namestr

The name of the object.

getPhysicalModel()

Physical model accessor.

Returns:

modelPhysicalModel

Physical model

getPythonScript()

Physical model accessor.

Returns:

scriptstr

Python script to replay the analysis

getResult()

Result accessor.

Returns:

resultTaylorExpansionMomentsResult

Result

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

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(variablesNames)

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.