MonteCarloAnalysis

class persalys.MonteCarloAnalysis(*args)

Perform a Monte Carlo central tendency analysis.

Parameters

namestr

Name

physicalModelPhysicalModel

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 Monte Carlo analysis:

>>> analysis = persalys.MonteCarloAnalysis('anAnalysis', myPhysicalModel)
>>> analysis.setMaximumCalls(500)
>>> analysis.setBlockSize(500)
>>> analysis.run()

Get the result:

>>> result = analysis.getResult()
>>> mean = result.getMean()

Methods

getBlockSize()	Block size accessor.
getClassName()	Accessor to the object's name.
getErrorMessage()	Error message accessor.
getFailedInputSample()	Failed input sample accessor.
getInterestVariables()	Get the variables to analyse.
getLevelConfidenceInterval()	Confidence interval level accessor.
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.
getResult()	Result accessor.
getSeed()	Seed accessor.
getWarningMessage()	Warning message accessor.
hasName()	Test if the object is named.
hasValidResult()	Whether the analysis has been run.
isConfidenceIntervalRequired()	Confidence interval flag accessor.
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.
setIsConfidenceIntervalRequired(...)	Confidence interval flag accessor.
setLevelConfidenceInterval(...)	Confidence interval level accessor.
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.
setSeed(seed)	Seed accessor.

canBeLaunched
getElapsedTime
getErrorDescription
getMaximumConfidenceIntervalLength
getParentObserver
setMaximumConfidenceIntervalLength

__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

getInterestVariables()

Get the variables to analyse.

Returns

variablesNamessequence of str

Names of the variables to analyse

getLevelConfidenceInterval()

Confidence interval level accessor.

Returns

levelfloat

Confidence interval level. It is set by default to 0.95.

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

getResult()

Result accessor.

Returns

resultDataAnalysisResult

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

isConfidenceIntervalRequired()

Confidence interval flag accessor.

Returns

flagbool

Confidence interval flag

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

setIsConfidenceIntervalRequired(isConfidenceIntervalRequired)

Confidence interval flag accessor.

Parameters

flagbool

Confidence interval flag

setLevelConfidenceInterval(levelConfidenceInterval)

Confidence interval level accessor.

Parameters

levelfloat

Confidence interval level. It is set by default to 0.95.

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.

setSeed(seed)

Seed accessor.

Parameters

seedint

Seed value