DataAnalysis

class persalys.DataAnalysis(*args)

Create a data analysis of a design of experiments.

Parameters

namestr

Name

designDesignOfExperiment

Design of experiments

Examples

>>> import openturns as ot
>>> import persalys
>>> ot.RandomGenerator.SetSeed(0)

Create the model:

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

Create the Data analysis:

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

Get the result:

>>> result = analysis.getResult()
>>> mean = result.getMean()

Methods

getClassName()	Accessor to the object's name.
getDesignOfExperiment()	Design of experiments accessor.
getErrorMessage()	Error message accessor.
getInterestVariables()	Get the variables to analyse.
getLevelConfidenceInterval()	Confidence interval level accessor.
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.
isConfidenceIntervalRequired()	Whether a confidence interval is required.
isReliabilityAnalysis()	Whether the analysis involves reliability.
isRunning()	Whether the analysis is running.
run()	Launch the analysis.
setInterestVariables(variablesNames)	Set the variables to analyse.
setIsConfidenceIntervalRequired(isRequired)	Whether a confidence interval is required.
setLevelConfidenceInterval(level)	Confidence interval level accessor.
setName(name)	Accessor to the object's name.

canBeLaunched
getElapsedTime
getParentObserver

__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

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

getLevelConfidenceInterval()

Confidence interval level accessor.

Returns

valuefloat

Confidence interval level.

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

resultDataAnalysisResult

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

isConfidenceIntervalRequired()

Whether a confidence interval is required.

Returns

valuebool

Whether a confidence interval is required.

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.

setInterestVariables(variablesNames)

Set the variables to analyse.

Parameters

variablesNamessequence of str

Names of the variables to analyse

setIsConfidenceIntervalRequired(isRequired)

Whether a confidence interval is required.

Parameters

valuebool

Whether a confidence interval is required

setLevelConfidenceInterval(level)

Confidence interval level accessor.

Parameters

valuefloat

Confidence interval level

setName(name)

Accessor to the object’s name.

Parameters

namestr

The name of the object.