ImportedDesignOfExperiment

class persalys.ImportedDesignOfExperiment(*args)

Create a design of experiments, using an imported design.

Available constructors:

ImportedDesignOfExperiment(name, physicalModel, fileName, columns)

Parameters
namestr

Name

physicalModelPhysicalModel

Physical model

fileNamestr

Name of a data file to load

columnssequence of int

Indices of columns in files to consider

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])

Methods

getBlockSize(self)

Block size accessor.

getClassName(self)

Accessor to the object’s name.

getErrorMessage(self)

Error message accessor.

getFailedInputSample(self)

Failed input sample accessor.

getFileName(self)

File name accessor.

getId(self)

Accessor to the object’s id.

getInputColumns(self)

Columns of the input variables accessor.

getInterestVariables(self)

Get the variables to analyse.

getName(self)

Accessor to the object’s name.

getNotEvaluatedInputSample(self)

Not evaluated input sample accessor.

getOriginalInputSample(self)

Input sample accessor.

getOutputColumns(self)

Columns of the ouput variables accessor.

getPhysicalModel(self)

Physical model accessor.

getPythonScript(self)

Physical model accessor.

getSampleFromFile(self)

Sample from the file accessor.

getSeed(self)

Seed accessor.

getShadowedId(self)

Accessor to the object’s shadowed id.

getVisibility(self)

Accessor to the object’s visibility state.

getWarningMessage(self)

Warning message accessor.

hasName(self)

Test if the object is named.

hasValidResult(self)

Whether the analysis has been run.

hasVisibleName(self)

Test if the object has a distinguishable name.

isReliabilityAnalysis(self)

Whether the analysis involves reliability.

isRunning(self)

Whether the analysis is running.

run(self)

Launch the analysis.

setBlockSize(self, size)

Block size accessor.

setFileName(self, fileName)

File name accessor.

setInputColumns(self, inputColumns)

Input columns accessor.

setInterestVariables(self, variablesNames)

Set the variables to analyse.

setName(self, name)

Accessor to the object’s name.

setSeed(self, seed)

Seed accessor.

setShadowedId(self, id)

Accessor to the object’s shadowed id.

setVisibility(self, visible)

Accessor to the object’s visibility state.

canBeLaunched

getElapsedTime

getParentObserver

getResult

__init__(self, *args)

Initialize self. See help(type(self)) for accurate signature.

getBlockSize(self)

Block size accessor.

Returns
blockSizepositive int

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

getClassName(self)

Accessor to the object’s name.

Returns
class_namestr

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

getErrorMessage(self)

Error message accessor.

Returns
messagestr

Error message if the analysis failed

getFailedInputSample(self)

Failed input sample accessor.

Returns
sampleopenturns.Sample

Sample with the failed input values

getFileName(self)

File name accessor.

Returns
fileNamestr

Name of the file containing data

getId(self)

Accessor to the object’s id.

Returns
idint

Internal unique identifier.

getInputColumns(self)

Columns of the input variables accessor.

Returns
columnsopenturns.Indices

Columns of the input variables

getInterestVariables(self)

Get the variables to analyse.

Returns
variablesNamessequence of str

Names of the variables to analyse

getName(self)

Accessor to the object’s name.

Returns
namestr

The name of the object.

getNotEvaluatedInputSample(self)

Not evaluated input sample accessor.

Returns
sampleopenturns.Sample

Points of the design of experiments which were not evaluated

getOriginalInputSample(self)

Input sample accessor.

Returns
sampleopenturns.Sample

Input sample.

getOutputColumns(self)

Columns of the ouput variables accessor.

Returns
columnsopenturns.Indices

Columns of the output variables

getPhysicalModel(self)

Physical model accessor.

Returns
modelPhysicalModel

Physical model

getPythonScript(self)

Physical model accessor.

Returns
scriptstr

Python script to replay the analysis

getSampleFromFile(self)

Sample from the file accessor.

Returns
sampleopenturns.Sample

Sample from the file

getSeed(self)

Seed accessor.

Returns
seedint

Seed value

getShadowedId(self)

Accessor to the object’s shadowed id.

Returns
idint

Internal unique identifier.

getVisibility(self)

Accessor to the object’s visibility state.

Returns
visiblebool

Visibility flag.

getWarningMessage(self)

Warning message accessor.

Returns
messagestr

Warning message which can appear during the analysis computation

hasName(self)

Test if the object is named.

Returns
hasNamebool

True if the name is not empty.

hasValidResult(self)

Whether the analysis has been run.

Returns
hasValidResultbool

Whether the analysis has already been run

hasVisibleName(self)

Test if the object has a distinguishable name.

Returns
hasVisibleNamebool

True if the name is not empty and not the default one.

isReliabilityAnalysis(self)

Whether the analysis involves reliability.

Returns
isReliabilityAnalysisbool

Whether the analysis involves a reliability analysis

isRunning(self)

Whether the analysis is running.

Returns
isRunningbool

Whether the analysis is running

run(self)

Launch the analysis.

setBlockSize(self, size)

Block size accessor.

Parameters
blockSizepositive int

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

setFileName(self, fileName)

File name accessor.

Parameters
fileNamestr

Name of the file containing data

setInputColumns(self, inputColumns)

Input columns accessor.

Parameters
columnssequence of int

Columns of the input variables

setInterestVariables(self, variablesNames)

Set the variables to analyse.

Parameters
variablesNamessequence of str

Names of the variables to analyse

setName(self, name)

Accessor to the object’s name.

Parameters
namestr

The name of the object.

setSeed(self, seed)

Seed accessor.

Parameters
seedint

Seed value

setShadowedId(self, id)

Accessor to the object’s shadowed id.

Parameters
idint

Internal unique identifier.

setVisibility(self, visible)

Accessor to the object’s visibility state.

Parameters
visiblebool

Visibility flag.