ModelEvaluation

class persalys.ModelEvaluation(*args)

Generate a simple evaluation of a model.

Parameters

namestr

Name

physicalModelPhysicalModel

Physical model

valuesopenturns.Point

Input values (optional)

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 Model evaluation:

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

Get the result:

>>> outputValues = analysis.getResult().getDesignOfExperiment().getOutputSample()

Methods

getBlockSize()	Block size accessor.
getClassName()	Accessor to the object's name.
getErrorMessage()	Error message accessor.
getFailedInputSample()	Failed input sample accessor.
getInterestVariables()	Get the variables to analyse.
getName()	Accessor to the object's name.
getNotEvaluatedInputSample()	Not evaluated input sample accessor.
getOriginalInputSample()	Input sample accessor.
getPhysicalModel()	Physical model accessor.
getPythonScript()	Physical model accessor.
getSeed()	Seed accessor.
getValues()	Values 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.
setBlockSize(size)	Block size accessor.
setInterestVariables(variablesNames)	Set the variables to analyse.
setName(name)	Accessor to the object's name.
setSeed(seed)	Seed accessor.
setValues(values)	Values accessor.

GetDefaultBounds
StopRequested
canBeLaunched
getElapsedTime
getErrorDescription
getParentObserver
getResult

__init__(*args)

getBlockSize()

Block size accessor.

Returns

blockSizepositive int

Number of terms analysed together. It is set by default to 1.

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

getFailedInputSample()

Failed input sample accessor.

Returns

sampleopenturns.Sample

Sample with the failed input values

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.

getNotEvaluatedInputSample()

Not evaluated input sample accessor.

Returns

sampleopenturns.Sample

Points of the design of experiments which were not evaluated

getOriginalInputSample()

Input sample accessor.

Returns

sampleopenturns.Sample

Input sample.

getPhysicalModel()

Physical model accessor.

Returns

modelPhysicalModel

Physical model

getPythonScript()

Physical model accessor.

Returns

scriptstr

Python script to replay the analysis

getSeed()

Seed accessor.

Returns

seedint

Seed value

getValues()

Values accessor.

Returns

valuesopenturns.Point

Inputs values used in the case where there is at least a constant variable.

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.

setBlockSize(size)

Block size accessor.

Parameters

blockSizepositive int

Number of terms analysed together. It is set by default to 1.

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.

setSeed(seed)

Seed accessor.

Parameters

seedint

Seed value

setValues(values)

Values accessor.

Parameters

valuesopenturns.Point

Inputs values used in the case where there is at least a constant variable.