ProbabilisticDesignOfExperiment

class persalys.ProbabilisticDesignOfExperiment(*args)

Create a probabilistic design of experiments.

Available constructors:

ProbabilisticDesignOfExperiment(name, physicalModel)

ProbabilisticDesignOfExperiment(name, physicalModel, size, designName)

Parameters

namestr

Name

physicalModelPhysicalModel

Physical model with at least a stochastic input variable.

sizepositive int

Number of points in the design.

designNamestr

Name of the design. Use GetDesignNames() to list available names.

Examples

>>> import openturns as ot
>>> import persalys

Create the model:

>>> R = persalys.Input('R', 0., ot.LogNormalMuSigma(300., 30., 0.).getDistribution(), 'Yield strength')
>>> F = persalys.Input('F', 0., ot.Normal(75000., 5000.), 'Traction load')
>>> G = persalys.Output('G', 'deviation')
>>> myPhysicalModel = persalys.SymbolicPhysicalModel('myPhysicalModel', [R, F], [G], ['R-F/(pi_*100.0)'])

Create the design of experiments:

>>> myDOE = persalys.ProbabilisticDesignOfExperiment('myDOE', myPhysicalModel, 10, 'MONTE_CARLO')

Methods

GetDesignNames()	Accessor to the list of designs provided by ProbabilisticDesignOfExperiment.
getBlockSize()	Block size accessor.
getClassName()	Accessor to the object's name.
getDesignName()	Accessor to the design name.
getErrorMessage()	Error message accessor.
getFailedInputSample()	Failed input sample accessor.
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.
getSeed()	Seed accessor.
getSize()	Accessor to the size of the generated sample.
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.
setDesignName(name)	Accessor to the design name.
setInterestVariables(variablesNames)	Set the variables to analyse.
setName(name)	Accessor to the object's name.
setSeed(seed)	Initialize the random generator seed.
setSize(size)	Accessor to the size of the generated sample.

GetSpaceFillings
StopRequested
canBeLaunched
getElapsedTime
getErrorDescription
getMCLHSSize
getParentObserver
getResult
getSpaceFilling
setSpaceFilling

__init__(*args)

static GetDesignNames()

Accessor to the list of designs provided by ProbabilisticDesignOfExperiment.

Returns

namesopenturns.Description

List of design names provided by ProbabilisticDesignOfExperiment.

Examples

>>> import persalys
>>> print(persalys.ProbabilisticDesignOfExperiment.GetDesignNames())
[LHS,SALHS,MCLHS,MONTE_CARLO,QUASI_MONTE_CARLO]

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__).

getDesignName()

Accessor to the design name.

Returns

designNamestr

The design name.

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

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

getSeed()

Seed accessor.

Returns

seedint

Seed value

getSize()

Accessor to the size of the generated sample.

Returns

sizepositive int

Number of points in the design.

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.

setDesignName(name)

Accessor to the design name.

Parameters

designNamestr

The design name. Use GetDesignNames() to list available names.

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)

Initialize the random generator seed.

Parameters

seedint

Seed value.

setSize(size)

Accessor to the size of the generated sample.

Parameters

sizepositive int

Number of points in the design.