FieldMonteCarloAnalysis¶

class persalys.FieldMonteCarloAnalysis(*args)¶

Run a Monte Carlo analysis for models with mesh.

Parameters:

namestr: Name
modelPhysicalModel: Model containing a mesh

Examples

>>> import openturns as ot
>>> import persalys

Create the model:

>>> meshModel = persalys.GridMeshModel(ot.Interval(0., 12.), [5])

>>> z0 = persalys.Input('z0', 100, ot.Uniform(100, 150))
>>> v0 = persalys.Input('v0', 55, ot.Normal(55, 10))
>>> m = persalys.Input('m', 80, ot.Normal(80, 8))
>>> c = persalys.Input('c', 15, ot.Uniform(0, 30))
>>> z = persalys.Output('z', '')
>>> formula = ['max(0, z0 + (m * 9.81 / c) * t + (m / c) * (v0 - (m * 9.81 / c)) * (1 - exp(-t * c / m)))']

>>> model = persalys.SymbolicFieldModel('aModel', meshModel, [z0, v0, m, c], [z], formula)

Create the analysis:

>>> analysis = persalys.FieldMonteCarloAnalysis('analysis', model)
>>> analysis.setMaximumCalls(30)
>>> analysis.run()

Get the result:

>>> result = analysis.getResult()

Attributes:

thisown: The membership flag

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.
`getKarhunenLoeveThreshold`()	Accessor to the limit ratio on eigenvalues.
`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.
`getQuantileLevel`()	Probability level 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.
`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.
`setKarhunenLoeveThreshold`(threshold)	Accessor to the limit ratio on eigenvalues.
`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.
`setQuantileLevel`(proba)	Probability level accessor.
`setSeed`(seed)	Seed accessor.
`setShadowedId`(id)	Accessor to the object's shadowed id.
`setVisibility`(visible)	Accessor to the object's visibility state.

canBeLaunched
getElapsedTime
getErrorDescription
getParentObserver

__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

getId()¶

Accessor to the object’s id.

Returns:

idint: Internal unique identifier.

getInterestVariables()¶

Get the variables to analyse.

Returns:

variablesNamessequence of str: Names of the variables to analyse

getKarhunenLoeveThreshold()¶

Accessor to the limit ratio on eigenvalues.

Returns:

thresholdfloat, positive: The threshold s defined in openturns.KarhunenLoeveAlgorithm.setThreshold()

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

getQuantileLevel()¶

Probability level accessor.

Returns:

levelfloat: Probability level

getResult()¶

Result accessor.

Returns:

resultpersalys.FieldMonteCarloResult: Result

getSeed()¶

Seed accessor.

Returns:

seedint: Seed value

getShadowedId()¶

Accessor to the object’s shadowed id.

Returns:

idint: Internal unique identifier.

getVisibility()¶

Accessor to the object’s visibility state.

Returns:

visiblebool: Visibility flag.

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

hasVisibleName()¶

Test if the object has a distinguishable name.

Returns:

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

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

setKarhunenLoeveThreshold(threshold)¶

Accessor to the limit ratio on eigenvalues.

Parameters:

thresholdfloat, positive: The threshold s defined in openturns.KarhunenLoeveAlgorithm.getThreshold()

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.

setQuantileLevel(proba)¶

Probability level accessor.

Parameters:

levelfloat, $0 < p < 1$: Probability level

setSeed(seed)¶

Seed accessor.

Parameters:

seedint: Seed value

setShadowedId(id)¶

Accessor to the object’s shadowed id.

Parameters:

idint: Internal unique identifier.

setVisibility(visible)¶

Accessor to the object’s visibility state.

Parameters:

visiblebool: Visibility flag.

property thisown¶: The membership flag

FieldMonteCarloAnalysis¶

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