FORMAnalysis¶

class persalys.FORMAnalysis(*args)¶

Process a reliability analysis using the FORM method.

Parameters:

name : str

Name

limitState : LimitState

Limit state

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 limit state:

>>> limitState = persalys.LimitState('ls1', myPhysicalModel, 'G', ot.Less(), 0.)

Process a reliability analysis using the FORM method:

>>> analysis = persalys.FORMAnalysis('myAnalysis', limitState)
>>> analysis.run()

Get the result:

>>> result = analysis.getResult().getFORMResult()
>>> pf = result.getEventProbability()
>>> designPoint = result.getStandardSpaceDesignPoint()

Methods

`getClassName`()	Accessor to the object’s name.
`getErrorMessage`()	Error message accessor.
`getId`()	Accessor to the object’s id.
`getInterestVariables`()	Get the variables to analyse.
`getLimitState`()	Limit-state accessor.
`getName`()	Accessor to the object’s name.
`getOptimizationAlgorithm`()	Accessor to the optimization algorithm used to find the design point.
`getPhysicalModel`()	Physical model accessor.
`getPhysicalStartingPoint`()	Physical starting point accessor.
`getPythonScript`()	Physical model accessor.
`getResult`()	Result 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.
`setInterestVariables`(outputsNames)	Set the variables to analyse.
`setName`(name)	Accessor to the object’s name.
`setOptimizationAlgorithm`(solver)	Accessor to the optimization algorithm used to find the design point.
`setPhysicalStartingPoint`(point)	Physical starting point accessor.
`setShadowedId`(id)	Accessor to the object’s shadowed id.
`setVisibility`(visible)	Accessor to the object’s visibility state.

__init__(*args)¶

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

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

getLimitState()¶

Limit-state accessor.

Returns:

limitState : LimitState

The Limit-state.

getName()¶

Accessor to the object’s name.

Returns:

name : str

The name of the object.

getOptimizationAlgorithm()¶

Accessor to the optimization algorithm used to find the design point.

Returns:

algorithm : openturns.OptimizationAlgorithm

Optimization algorithm used to research the design point. Cobyla is the default used algorithm.

getPhysicalModel()¶

Physical model accessor.

Returns:

model : PhysicalModel

Physical model

getPhysicalStartingPoint()¶

Physical starting point accessor.

Returns:

point : openturns.Point

Physical starting point. By default it set to the mean of the composed distribution of the physical model

getPythonScript()¶

Physical model accessor.

Returns:

script : str

Python script to replay the analysis

getResult()¶

Result accessor.

Returns:

result : FORMAnalysisResult

Result

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.

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.

setInterestVariables(outputsNames)¶

Set the variables to analyse.

Parameters:

variablesNames : sequence of str

Names of the variables to analyse

setName(name)¶

Accessor to the object’s name.

Parameters:

name : str

The name of the object.

setOptimizationAlgorithm(solver)¶

Accessor to the optimization algorithm used to find the design point.

Parameters:

algorithm : openturns.OptimizationAlgorithm

Optimization algorithm used to research the design point. Cobyla is the default used algorithm.

setPhysicalStartingPoint(point)¶

Physical starting point accessor.

Parameters:

point : sequence of float

Physical starting point. By default it set to the mean of the composed distribution of the physical model

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.

FORMAnalysis¶

Previous topic

Next topic

This Page