CopulaInferenceAnalysis¶
- class persalys.CopulaInferenceAnalysis(*args)¶
Perform a dependence inference analysis.
- Parameters
- namestr
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
Accessor to the object's name.
Design of experiments accessor.
getDistributionsFactories
(variablesNames)Get the sequence of distributions to test for a set of variables.
Error message accessor.
Get the variables to analyse.
getName
()Accessor to the object's name.
Physical model accessor.
Result accessor.
Warning message accessor.
hasName
()Test if the object is named.
Whether the analysis has been run.
Whether the analysis involves reliability.
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
- model
DesignOfExperiment
Design of experiments
- model
- 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
- factoriessequence of
- 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
- result
CopulaInferenceResult
Result.
- 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.