GridDesignOfExperiment

class persalys.GridDesignOfExperiment(*args)

Create a grid design of experiments.

Available constructors:

GridDesignOfExperiment(name, physicalModel)

GridDesignOfExperiment(name, physicalModel, bounds, nbValues, values)

Parameters:

namestr

Name

physicalModelPhysicalModel

Physical model

boundsopenturns.Interval

Bounds

nbValuessequence of int

Number of values along each direction

valuessequence of float

Values of the constant variables (optional)

Notes

The sequences must have a dimension equal to the number of inputs in the physical model.

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.GridDesignOfExperiment('myDOE', myPhysicalModel)

Attributes:

thisown

The membership flag

Methods

getBlockSize()	Block size accessor.
getClassName()	Accessor to the object's name.
getErrorMessage()	Error message accessor.
getFailedInputSample()	Failed input sample accessor.
getId()	Accessor to the object's id.
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.
getShadowedId()	Accessor to the object's shadowed id.
getValues()	Values accessor.
getVisibility()	Accessor to the object's visibility state.
getWarningMessage()	Warning message accessor.
hasName()	Test if the object is named.
hasValidResult()	Whether the analysis has been run.
hasVisibleName()	Test if the object has a distinguishable name.
isReliabilityAnalysis()	Whether the analysis involves reliability.
isRunning()	Whether the analysis is running.
run()	Launch the analysis.
setBlockSize(size)	Block size accessor.
setInterestVariables(variablesNames)	Set the variables to analyse.
setName(name)	Accessor to the object's name.
setSeed(seed)	Seed accessor.
setShadowedId(id)	Accessor to the object's shadowed id.
setValues(values)	Values accessor.
setVisibility(visible)	Accessor to the object's visibility state.

GetDefaultBounds
canBeLaunched
getElapsedTime
getParentObserver
getResult

__init__(*args)

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__).

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

getId()

Accessor to the object’s id.

Returns:

idint

Internal unique identifier.

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

getShadowedId()

Accessor to the object’s shadowed id.

Returns:

idint

Internal unique identifier.

getValues()

Values accessor.

Returns:

valuesopenturns.Point

Inputs values used in the case where there is at least a constant variable.

getVisibility()

Accessor to the object’s visibility state.

Returns:

visiblebool

Visibility flag.

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

hasVisibleName()

Test if the object has a distinguishable name.

Returns:

hasVisibleNamebool

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

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.

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

setShadowedId(id)

Accessor to the object’s shadowed id.

Parameters:

idint

Internal unique identifier.

setValues(values)

Values accessor.

Parameters:

valuesopenturns.Point

Inputs values used in the case where there is at least a constant variable.

setVisibility(visible)

Accessor to the object’s visibility state.

Parameters:

visiblebool

Visibility flag.

property thisown

The membership flag