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`(self)	Block size accessor.
`getClassName`(self)	Accessor to the object’s 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.
`getLevelConfidenceInterval`(self)	Confidence interval level accessor.
`getMaximumCalls`(self)	Maximum calls accessor.
`getMaximumCoefficientOfVariation`(self)	Maximum coefficient of variation accessor.
`getMaximumElapsedTime`(self)	Maximum elapsed time accessor.
`getName`(self)	Accessor to the object’s name.
`getPhysicalModel`(self)	Physical model accessor.
`getPythonScript`(self)	Physical model accessor.
`getResult`(self)	Result accessor.
`getSeed`(self)	Seed accessor.
`getShadowedId`(self)	Accessor to the object’s shadowed id.
`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.
`isConfidenceIntervalRequired`(self)	Confidence interval flag accessor.
`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.
`setInterestVariables`(self, variablesNames)	Set the variables to analyse.
`setIsConfidenceIntervalRequired`(self, …)	Confidence interval flag accessor.
`setLevelConfidenceInterval`(self, …)	Confidence interval level accessor.
`setMaximumCalls`(self, maxi)	Maximum calls accessor.
`setMaximumCoefficientOfVariation`(self, coef)	Maximum coefficient of variation accessor.
`setMaximumElapsedTime`(self, seconds)	Maximum elapsed time accessor.
`setName`(self, name)	Accessor to the object’s name.
`setSeed`(self, seed)	Seed accessor.
`setShadowedId`(self, id)	Accessor to the object’s shadowed id.
`setVisibility`(self, visible)	Accessor to the object’s visibility state.

canBeLaunched
getElapsedTime
getParentObserver

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

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__).

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

getLevelConfidenceInterval(self)¶

Confidence interval level accessor.

Returns

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

getMaximumCalls(self)¶

Maximum calls accessor.

Returns

maxCallspositive int: The maximum calls of the function.

getMaximumCoefficientOfVariation(self)¶

Maximum coefficient of variation accessor.

Returns

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

getMaximumElapsedTime(self)¶

Maximum elapsed time accessor.

Returns

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

getName(self)¶

Accessor to the object’s name.

Returns

namestr: The name of the object.

getPhysicalModel(self)¶

Physical model accessor.

Returns

modelPhysicalModel: Physical model

getPythonScript(self)¶

Physical model accessor.

Returns

scriptstr: Python script to replay the analysis

getResult(self)¶

Result accessor.

Returns

resultDataAnalysisResult: Result

getSeed(self)¶

Seed accessor.

Returns

seedint: Seed value

getShadowedId(self)¶

Accessor to the object’s shadowed id.

Returns

idint: Internal unique identifier.

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.

isConfidenceIntervalRequired(self)¶

Confidence interval flag accessor.

Returns

flagbool: Confidence interval flag

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.

setInterestVariables(self, variablesNames)¶

Set the variables to analyse.

Parameters

variablesNamessequence of str: Names of the variables to analyse

setIsConfidenceIntervalRequired(self, isConfidenceIntervalRequired)¶

Confidence interval flag accessor.

Parameters

flagbool: Confidence interval flag

setLevelConfidenceInterval(self, levelConfidenceInterval)¶

Confidence interval level accessor.

Parameters

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

setMaximumCalls(self, maxi)¶

Maximum calls accessor.

Parameters

maxCallspositive int: The maximum calls of the function.

setMaximumCoefficientOfVariation(self, coef)¶

Maximum coefficient of variation accessor.

Parameters

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

setMaximumElapsedTime(self, seconds)¶

Maximum elapsed time accessor.

Parameters

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

setName(self, name)¶

Accessor to the object’s name.

Parameters

namestr: The name of the object.

setSeed(self, seed)¶

Seed accessor.

Parameters

seedint: Seed value

setShadowedId(self, id)¶

Accessor to the object’s shadowed id.

Parameters

idint: Internal unique identifier.

setVisibility(self, visible)¶

Accessor to the object’s visibility state.

Parameters

visiblebool: Visibility flag.

MonteCarloAnalysis¶

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