ImportedDesignOfExperiment¶

class persalys.ImportedDesignOfExperiment(*args)¶

Create a design of experiments, using an imported design.

Available constructors:: ImportedDesignOfExperiment(name, physicalModel) ImportedDesignOfExperiment(name, physicalModel, fileName, inputColumns, outputColumns, type)

Parameters:

namestr: Name
physicalModelPhysicalModel: Physical model
fileNamestr: Name of a data file to load
inputColumnssequence of int: Columns of the input variables
outputColumnssequence of int: Columns of the output variables (optional)
typeint: Type of the imported design of experiments (optional, default is GENERIC)

Methods

`checkAndSetEvaluations`(evaluatedDoE)	Checks that the input values of the given DOE correspond to the current DOE and copy the evaluations of the given DOE to the current DOE
`getBlockSize`()	Block size accessor.
`getClassName`()	Accessor to the object's name.
`getErrorDescription`()	Design of experiments accessor.
`getErrorMessage`()	Error message accessor.
`getFailedInputSample`()	Failed input sample accessor.
`getImportedDataset`()	Get the imported dataset.
`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`()	Get the data analysis result.
`getSeed`()	Seed accessor.
`getType`()	Get the type of the imported design of experiments.
`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.
`setBlockSize`(size)	Block size accessor.
`setColumns`(*args)	Set the columns of the variables.
`setEvaluations`(arg2)	Add evaluations for the design of experiments
`setFileName`(fileName)	Set the name of the data file to load.
`setInterestVariables`(variablesNames)	Set the variables to analyse.
`setName`(name)	Accessor to the object's name.
`setSeed`(seed)	Seed accessor.
`setType`(type)	Set the type of the imported design of experiments.

Examples

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

Create the model:

>>> X0 = persalys.Input('X0')
>>> X1 = persalys.Input('X1')
>>> Y0 = persalys.Output('Y0')
>>> model = persalys.SymbolicPhysicalModel('aModelPhys', [X0, X1], [Y0], ['sin(X0)+8*X1'])

Create the design of experiments:

>>> filename = 'normal.csv'
>>> ot.Normal(3).getSample(10).exportToCSVFile(filename)
>>> aDesign = persalys.ImportedDesignOfExperiment('aDesign', model, filename, [0, 2])

__init__(*args)¶

checkAndSetEvaluations(evaluatedDoE)¶

Checks that the input values of the given DOE correspond to the current DOE and copy the evaluations of the given DOE to the current DOE

Parameters:

evaluatedDoE:py:DesignOfExperiment: Design of experiments containing evaluations to copy

getBlockSize()¶

Block size accessor.

Returns:

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

getClassName()¶

Accessor to the object’s name.

Returns:

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

getErrorDescription()¶

Design of experiments accessor.

Returns:

errorDescDescription: Description containing messages from failed points.

getErrorMessage()¶

Error message accessor.

Returns:

messagestr: Error message if the analysis failed

getFailedInputSample()¶

Failed input sample accessor.

Returns:

sampleopenturns.Sample: Sample with the failed input values

getImportedDataset()¶

Get the imported dataset.

Returns:

importedDatasetImportedDataset: The imported dataset

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.

getNotEvaluatedInputSample()¶

Not evaluated input sample accessor.

Returns:

sampleopenturns.Sample: Points of the design of experiments which were not evaluated

getOriginalInputSample()¶

Input sample accessor.

Returns:

sampleopenturns.Sample: Input sample.

getPhysicalModel()¶

Physical model accessor.

Returns:

modelPhysicalModel: Physical model

getPythonScript()¶

Physical model accessor.

Returns:

scriptstr: Python script to replay the analysis

getResult()¶

Get the data analysis result.

Returns:

resultDataAnalysisResult: Data analysis result associated to the design of experiments

getSeed()¶

Seed accessor.

Returns:

seedint: Seed value

getType()¶

Get the type of the imported design of experiments.

Returns:

typeint: Type of the imported design of experiments

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.

setBlockSize(size)¶

Block size accessor.

Parameters:

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

setColumns(*args)¶

Set the columns of the variables.

Parameters:

inputColumnssequence of int: Columns of the input variables
outputColumnssequence of int (optional): Columns of the output variables

setEvaluations(arg2)¶

Add evaluations for the design of experiments

Parameters:

outputSample:py:openturns.Sample: sample containing values for the output variables

setFileName(fileName)¶

Set the name of the data file to load.

Parameters:

fileNamestr: Name of a data file to load

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.

setSeed(seed)¶

Seed accessor.

Parameters:

seedint: Seed value

setType(type)¶

Set the type of the imported design of experiments. By default, the type is Monte-Carlo.

Parameters:

typeint: Type of the imported design of experiments

ImportedDesignOfExperiment¶

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