MonteCarloAnalysis¶

class persalys.MonteCarloAnalysis(*args)¶

Perform a Monte Carlo central tendency analysis.

Parameters:

name : str

Name

physicalModel : PhysicalModel

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.
`getId`()	Accessor to the object’s id.
`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.
`getShadowedId`()	Accessor to the object’s shadowed id.
`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.
`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.
`setShadowedId`(id)	Accessor to the object’s shadowed id.
`setVisibility`(visible)	Accessor to the object’s visibility state.

__init__(*args)¶

getBlockSize()¶

Block size accessor.

Returns:

blockSize : positive int

Number of terms analysed together. It is set by default to 1.

getClassName()¶

Accessor to the object’s name.

Returns:

class_name : str

The object class name (object.__class__.__name__).

getErrorMessage()¶

Error message accessor.

Returns:

message : str

Error message if the analysis failed

getFailedInputSample()¶

Failed input sample accessor.

Returns:

sample : openturns.Sample

Sample with the failed input values

getId()¶

Accessor to the object’s id.

Returns:

id : int

Internal unique identifier.

getInterestVariables()¶

Get the variables to analyse.

Returns:

variablesNames : sequence of str

Names of the variables to analyse

getLevelConfidenceInterval()¶

Confidence interval level accessor.

Returns:

level : float

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

getMaximumCalls()¶

Maximum calls accessor.

Returns:

maxCalls : positive int

The maximum calls of the function.

getMaximumCoefficientOfVariation()¶

Maximum coefficient of variation accessor.

Returns:

maxCoef : double

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

getMaximumElapsedTime()¶

Maximum elapsed time accessor.

Returns:

maxTime : positive int

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

getName()¶

Accessor to the object’s name.

Returns:

name : str

The name of the object.

getPhysicalModel()¶

Physical model accessor.

Returns:

model : PhysicalModel

Physical model

getPythonScript()¶

Physical model accessor.

Returns:

script : str

Python script to replay the analysis

getResult()¶

Result accessor.

Returns:

result : DataAnalysisResult

Result

getSeed()¶

Seed accessor.

Returns:

seed : int

Seed value

getShadowedId()¶

Accessor to the object’s shadowed id.

Returns:

id : int

Internal unique identifier.

getVisibility()¶

Accessor to the object’s visibility state.

Returns:

visible : bool

Visibility flag.

getWarningMessage()¶

Warning message accessor.

Returns:

message : str

Warning message which can appear during the analysis computation

hasName()¶

Test if the object is named.

Returns:

hasName : bool

True if the name is not empty.

hasValidResult()¶

Whether the analysis has been run.

Returns:

hasValidResult : bool

Whether the analysis has already been run

hasVisibleName()¶

Test if the object has a distinguishable name.

Returns:

hasVisibleName : bool

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

isConfidenceIntervalRequired()¶

Confidence interval flag accessor.

Returns:

flag : bool

Confidence interval flag

isReliabilityAnalysis()¶

Whether the analysis involves reliability.

Returns:

isReliabilityAnalysis : bool

Whether the analysis involves a reliability analysis

isRunning()¶

Whether the analysis is running.

Returns:

isRunning : bool

Whether the analysis is running

run()¶: Launch the analysis.

setBlockSize(size)¶

Block size accessor.

Parameters:

blockSize : positive int

Number of terms analysed together. It is set by default to 1.

setInterestVariables(variablesNames)¶

Set the variables to analyse.

Parameters:

variablesNames : sequence of str

Names of the variables to analyse

setIsConfidenceIntervalRequired(isConfidenceIntervalRequired)¶

Confidence interval flag accessor.

Parameters:

flag : bool

Confidence interval flag

setLevelConfidenceInterval(levelConfidenceInterval)¶

Confidence interval level accessor.

Parameters:

level : float

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

setMaximumCalls(maxi)¶

Maximum calls accessor.

Parameters:

maxCalls : positive int

The maximum calls of the function.

setMaximumCoefficientOfVariation(coef)¶

Maximum coefficient of variation accessor.

Parameters:

maxCoef : double

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

setMaximumElapsedTime(seconds)¶

Maximum elapsed time accessor.

Parameters:

maxTime : positive int

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

setName(name)¶

Accessor to the object’s name.

Parameters:

name : str

The name of the object.

setSeed(seed)¶

Seed accessor.

Parameters:

seed : int

Seed value

setShadowedId(id)¶

Accessor to the object’s shadowed id.

Parameters:

id : int

Internal unique identifier.

setVisibility(visible)¶

Accessor to the object’s visibility state.

Parameters:

visible : bool

Visibility flag.

MonteCarloAnalysis¶

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