ModelEvaluation¶

class persalys.ModelEvaluation(*args)¶

Generate a simple evaluation of a model.

Parameters:

name : str

Name

physicalModel : PhysicalModel

Physical model

values : openturns.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

`GetDefaultBounds`
`getBlockSize`()	Block size accessor.
`getClassName`()	Accessor to the object’s name.
`getErrorMessage`()	Error message accessor.
`getFailedInputSample`()	Failed input sample accessor.
`getId`()	Accessor to the object’s id.
`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.
`getResult`()
`getSeed`()	Seed accessor.
`getShadowedId`()	Accessor to the object’s shadowed id.
`getValues`()	Values accessor.
`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.
`setBlockSize`(size)	Block size accessor.
`setInterestVariables`(variablesNames)	Set the variables to analyse.
`setName`(name)	Accessor to the object’s name.
`setSeed`(seed)	Seed accessor.
`setShadowedId`(id)	Accessor to the object’s shadowed id.
`setValues`(values)	Values accessor.
`setVisibility`(visible)	Accessor to the object’s visibility state.

__init__(*args)¶

getBlockSize()¶

Block size accessor.

Returns:

blockSize : positive int

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

getClassName()¶

Accessor to the object’s name.

Returns:

class_name : str

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

getErrorMessage()¶

Error message accessor.

Returns:

message : str

Error message if the analysis failed

getFailedInputSample()¶

Failed input sample accessor.

Returns:

sample : openturns.Sample

Sample with the failed input values

getId()¶

Accessor to the object’s id.

Returns:

id : int

Internal unique identifier.

getInterestVariables()¶

Get the variables to analyse.

Returns:

variablesNames : sequence of str

Names of the variables to analyse

getName()¶

Accessor to the object’s name.

Returns:

name : str

The name of the object.

getNotEvaluatedInputSample()¶

Not evaluated input sample accessor.

Returns:

sample : openturns.Sample

Points of the design of experiments which were not evaluated

getOriginalInputSample()¶

Input sample accessor.

Returns:

sample : openturns.Sample

Input sample.

getPhysicalModel()¶

Physical model accessor.

Returns:

model : PhysicalModel

Physical model

getPythonScript()¶

Physical model accessor.

Returns:

script : str

Python script to replay the analysis

getSeed()¶

Seed accessor.

Returns:

seed : int

Seed value

getShadowedId()¶

Accessor to the object’s shadowed id.

Returns:

id : int

Internal unique identifier.

getValues()¶

Values accessor.

Returns:

values : openturns.Point

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

getVisibility()¶

Accessor to the object’s visibility state.

Returns:

visible : bool

Visibility flag.

getWarningMessage()¶

Warning message accessor.

Returns:

message : str

Warning message which can appear during the analysis computation

hasName()¶

Test if the object is named.

Returns:

hasName : bool

True if the name is not empty.

hasValidResult()¶

Whether the analysis has been run.

Returns:

hasValidResult : bool

Whether the analysis has already been run

hasVisibleName()¶

Test if the object has a distinguishable name.

Returns:

hasVisibleName : bool

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

isReliabilityAnalysis()¶

Whether the analysis involves reliability.

Returns:

isReliabilityAnalysis : bool

Whether the analysis involves a reliability analysis

isRunning()¶

Whether the analysis is running.

Returns:

isRunning : bool

Whether the analysis is running

run()¶: Launch the analysis.

setBlockSize(size)¶

Block size accessor.

Parameters:

blockSize : positive int

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

setInterestVariables(variablesNames)¶

Set the variables to analyse.

Parameters:

variablesNames : sequence of str

Names of the variables to analyse

setName(name)¶

Accessor to the object’s name.

Parameters:

name : str

The name of the object.

setSeed(seed)¶

Seed accessor.

Parameters:

seed : int

Seed value

setShadowedId(id)¶

Accessor to the object’s shadowed id.

Parameters:

id : int

Internal unique identifier.

setValues(values)¶

Values accessor.

Parameters:

values : openturns.Point

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

setVisibility(visible)¶

Accessor to the object’s visibility state.

Parameters:

visible : bool

Visibility flag.

ModelEvaluation¶

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