SobolAnalysis

class persalys.SobolAnalysis(*args)

Run a Sobol sensitivity analysis.

Parameters:

namestr

Name

physicalModelPhysicalModel

Physical model

Methods

getBlockSize()	Block size accessor.
getClassName()	Accessor to the object's name.
getConfidenceLevel()	Confidence level accessor.
getErrorDescription()	Design of experiments accessor.
getErrorMessage()	Error message accessor.
getFailedInputSample()	Failed input sample accessor.
getInterestVariables()	Get the variables to analyse.
getMaximumCalls()	Maximum calls accessor.
getMaximumCoefficientOfVariation()	Maximum coefficient of variation accessor.
getMaximumElapsedTime()	Maximum elapsed time accessor.
getName()	Accessor to the object's name.
getPhysicalModel()	Physical model accessor.
getPythonScript()	Physical model accessor.
getReplicationSize()	Replication size accessor.
getResult()	Result accessor.
getSeed()	Seed accessor.
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.
setConfidenceLevel(level)	Confidence level accessor.
setInterestVariables(variablesNames)	Set the variables to analyse.
setMaximumCalls(maxi)	Maximum calls accessor.
setMaximumCoefficientOfVariation(coef)	Maximum coefficient of variation accessor.
setMaximumElapsedTime(seconds)	Maximum elapsed time accessor.
setName(name)	Accessor to the object's name.
setReplicationSize(size)	Replication size accessor.
setSeed(seed)	Seed accessor.

getMaximumConfidenceIntervalLength
setMaximumConfidenceIntervalLength

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 Sobol analysis:

>>> analysis = persalys.SobolAnalysis('anAnalysis', myPhysicalModel)
>>> analysis.setMaximumCalls(500)
>>> analysis.setReplicationSize(125)
>>> analysis.run()

Get the result:

>>> result = analysis.getResult()
>>> indices = result.getFirstOrderIndices()

__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__).

getConfidenceLevel()

Confidence level accessor.

Returns:

levelfloat

Confidence level

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

getInterestVariables()

Get the variables to analyse.

Returns:

variablesNamessequence of str

Names of the variables to analyse

getMaximumCalls()

Maximum calls accessor.

Returns:

maxCallspositive int

The maximum calls of the function.

getMaximumCoefficientOfVariation()

Maximum coefficient of variation accessor.

Returns:

maxCoefdouble

The maximum coefficient of variation. It is set by default to 0.01.

getMaximumElapsedTime()

Maximum elapsed time accessor.

Returns:

maxTimepositive int

The maximum elapsed time in seconds. It is set by default to 60 seconds.

getName()

Accessor to the object’s name.

Returns:

namestr

The name of the object.

getPhysicalModel()

Physical model accessor.

Returns:

modelPhysicalModel

Physical model

getPythonScript()

Physical model accessor.

Returns:

scriptstr

Python script to replay the analysis

getReplicationSize()

Replication size accessor.

Returns:

sizeint

Replication size

getResult()

Result accessor.

Returns:

resultSobolResult

Result

getSeed()

Seed accessor.

Returns:

seedint

Seed value

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.

setConfidenceLevel(level)

Confidence level accessor.

Parameters:

levelfloat in ]0,1[

Confidence level

setInterestVariables(variablesNames)

Set the variables to analyse.

Parameters:

variablesNamessequence of str

Names of the variables to analyse

setMaximumCalls(maxi)

Maximum calls accessor.

Parameters:

maxCallspositive int

The maximum calls of the function.

setMaximumCoefficientOfVariation(coef)

Maximum coefficient of variation accessor.

Parameters:

maxCoefdouble

The maximum coefficient of variation. It is set by default to 0.01.

setMaximumElapsedTime(seconds)

Maximum elapsed time accessor.

Parameters:

maxTimepositive int

The maximum elapsed time in seconds. It is set by default to 60 seconds.

setName(name)

Accessor to the object’s name.

Parameters:

namestr

The name of the object.

setReplicationSize(size)

Replication size accessor.

Parameters:

sizeint > 1

Replication size

setSeed(seed)

Seed accessor.

Parameters:

seedint

Seed value