CopulaInferenceAnalysis

class persalys.CopulaInferenceAnalysis(*args)

Perform a dependence inference analysis.

Parameters
namestr

Name

designDesignOfExperiment

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

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.

getInterestVariables()

Get the variables to analyse.

getName()

Accessor to the object's name.

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.

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.

buildDefaultVariablesGroups

canBeLaunched

getElapsedTime

getParentObserver

getVariablesGroups

__init__(*args)
getClassName()

Accessor to the object’s name.

Returns
class_namestr

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

getDesignOfExperiment()

Design of experiments accessor.

Returns
modelDesignOfExperiment

Design of experiments

getDistributionsFactories(variablesNames)

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

Parameters
variablessequence of str

Names of the variables

Returns
factoriessequence of openturns.DistributionFactory

Distributions to test for the given set of variables

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.

getPythonScript()

Physical model accessor.

Returns
scriptstr

Python script to replay the analysis

getResult()

Result accessor.

Returns
resultCopulaInferenceResult

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.

setDistributionsFactories(variablesNames, distributionsFactories)

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

Parameters
variablessequence of str

Names of the variables

factoriessequence of openturns.DistributionFactory

Distributions to test

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.