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.