CopulaInferenceAnalysis

class persalys.CopulaInferenceAnalysis(*args)

Perform a dependence inference analysis.

Parameters:

name : str

Name

design : DesignOfExperiment

Design of experiments

Examples

Create the model:

>>> import openturns as ot
>>> import persalys
>>> filename = 'data.csv'
>>> ot.RandomGenerator_SetSeed(0)
>>> sample = ot.Normal(3).getSample(100)
>>> sample.exportToCSVFile(filename)
>>> model = persalys.DataModel('myDataModel', 'data.csv', [0, 1, 2])

Create the dependence inference analysis:

>>> analysis = persalys.CopulaInferenceAnalysis('analysis', model)
>>> analysis.run()

Get the result:

>>> result = analysis.getResult()
>>> resultForSet = result.getCopulaInferenceSetResultCollection()

Methods

buildDefaultVariablesGroups()
getClassName()	Accessor to the object’s name.
getDesignOfExperiment()	Design of experiments accessor.
getDistributionsFactories(variablesNames)	Get the sequence of distributions to test for a set of variables.
getErrorMessage()	Error message accessor.
getId()	Accessor to the object’s id.
getInterestVariables()	Get the variables to analyse.
getName()	Accessor to the object’s name.
getPythonScript()	Physical model accessor.
getResult()	Result accessor.
getShadowedId()	Accessor to the object’s shadowed id.
getVariablesGroups()
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.
setDistributionsFactories(variablesNames, …)	Set the sequence of distributions to test for a set of variables.
setInterestVariables(variablesNames)	Set the variables to analyse.
setName(name)	Accessor to the object’s name.
setShadowedId(id)	Accessor to the object’s shadowed id.
setVisibility(visible)	Accessor to the object’s visibility state.

__init__(*args)

getClassName()

Accessor to the object’s name.

Returns:

class_name : str

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

getDesignOfExperiment()

Design of experiments accessor.

Returns:

model : DesignOfExperiment

Design of experiments

getDistributionsFactories(variablesNames)

Get the sequence of distributions to test for a set of variables.

Parameters:

variables : sequence of str

Names of the variables

Returns:

factories : sequence of openturns.DistributionFactory

Distributions to test for the given set of variables

getErrorMessage()

Error message accessor.

Returns:

message : str

Error message if the analysis failed

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.

getPythonScript()

Physical model accessor.

Returns:

script : str

Python script to replay the analysis

getResult()

Result accessor.

Returns:

result : CopulaInferenceResult

Result.

getShadowedId()

Accessor to the object’s shadowed id.

Returns:

id : int

Internal unique identifier.

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.

setDistributionsFactories(variablesNames, distributionsFactories)

Set the sequence of distributions to test for a set of variables.

Parameters:

variables : sequence of str

Names of the variables

factories : sequence of openturns.DistributionFactory

Distributions to test

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.

setShadowedId(id)

Accessor to the object’s shadowed id.

Parameters:

id : int

Internal unique identifier.

setVisibility(visible)

Accessor to the object’s visibility state.

Parameters:

visible : bool

Visibility flag.