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`(self)	Block size accessor.
`getClassName`(self)	Accessor to the object’s name.
`getDesignName`(self)	Accessor to the design name.
`getErrorMessage`(self)	Error message accessor.
`getFailedInputSample`(self)	Failed input sample accessor.
`getId`(self)	Accessor to the object’s id.
`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.
`getPhysicalModel`(self)	Physical model accessor.
`getPythonScript`(self)	Physical model accessor.
`getSeed`(self)	Seed accessor.
`getShadowedId`(self)	Accessor to the object’s shadowed id.
`getSize`(self)	Accessor to the size of the generated sample.
`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.
`setDesignName`(self, name)	Accessor to the design name.
`setInterestVariables`(self, variablesNames)	Set the variables to analyse.
`setName`(self, name)	Accessor to the object’s name.
`setSeed`(self, seed)	Initialize the random generator seed.
`setShadowedId`(self, id)	Accessor to the object’s shadowed id.
`setSize`(self, size)	Accessor to the size of the generated sample.
`setVisibility`(self, visible)	Accessor to the object’s visibility state.

GetSpaceFillings
canBeLaunched
getElapsedTime
getMCLHSSize
getParentObserver
getResult
getSpaceFilling
setSpaceFilling

__init__(self, *args)¶: Initialize self. See help(type(self)) for accurate signature.

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(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__).

getDesignName(self)¶

Accessor to the design name.

Returns

designNamestr: The design 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

getId(self)¶

Accessor to the object’s id.

Returns

idint: Internal unique identifier.

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.

getPhysicalModel(self)¶

Physical model accessor.

Returns

modelPhysicalModel: Physical model

getPythonScript(self)¶

Physical model accessor.

Returns

scriptstr: Python script to replay the analysis

getSeed(self)¶

Seed accessor.

Returns

seedint: Seed value

getShadowedId(self)¶

Accessor to the object’s shadowed id.

Returns

idint: Internal unique identifier.

getSize(self)¶

Accessor to the size of the generated sample.

Returns

sizepositive int: Number of points in the design.

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.

setDesignName(self, name)¶

Accessor to the design name.

Parameters

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

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)¶

Initialize the random generator seed.

Parameters

seedint: Seed value.

setShadowedId(self, id)¶

Accessor to the object’s shadowed id.

Parameters

idint: Internal unique identifier.

setSize(self, size)¶

Accessor to the size of the generated sample.

Parameters

sizepositive int: Number of points in the design.

setVisibility(self, visible)¶

Accessor to the object’s visibility state.

Parameters

visiblebool: Visibility flag.

ProbabilisticDesignOfExperiment¶

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