MorrisAnalysis

class persalys.MorrisAnalysis(*args)

Perform a Morris 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 Morris analysis:

>>> analysis = persalys.MorrisAnalysis('anAnalysis', myPhysicalModel)
>>> analysis.setBounds(ot.Interval([100, 60000], [350, 80000]))
>>> analysis.setLevel(4)
>>> analysis.run()

Get the result:

>>> result = analysis.getResult()
>>> meanAbsEE = result.getMeanAbsoluteElementaryEffects(0)

Methods

getBlockSize() Block size accessor.
getBounds() Bounds of the domain 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.
getLevel() Level accessor.
getName() Accessor to the object’s name.
getPhysicalModel() Physical model accessor.
getPythonScript() Physical model accessor.
getResult() Morris result accessor.
getSeed() Seed accessor.
getShadowedId() Accessor to the object’s shadowed id.
getTrajectoriesNumber() Number of trajectories accessor.
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.
setBounds(bounds) Bounds of the domain accessor.
setInterestVariables(variablesNames) Set the variables to analyse.
setLevel(value) Level accessor.
setName(name) Accessor to the object’s name.
setSeed(seed) Seed accessor.
setShadowedId(id) Accessor to the object’s shadowed id.
setTrajectoriesNumber(number) Number of trajectories accessor.
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.

getBounds()

Bounds of the domain accessor.

Returns:

bounds : openturns.Interval

Bounds of the domain

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

getLevel()

Level accessor.

Returns:

number : int

Number of levels for a regular grid. It is set by default to 4.

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()

Morris result accessor.

Returns:

result : MorrisResult

Result

getSeed()

Seed accessor.

Returns:

seed : int

Seed value

getShadowedId()

Accessor to the object’s shadowed id.

Returns:

id : int

Internal unique identifier.

getTrajectoriesNumber()

Number of trajectories accessor.

Returns:

number : int

Number of trajectories. It is set by default to 10.

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.

setBlockSize(size)

Block size accessor.

Parameters:

blockSize : positive int

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

setBounds(bounds)

Bounds of the domain accessor.

Parameters:

bounds : openturns.Interval

Bounds of the domain

setInterestVariables(variablesNames)

Set the variables to analyse.

Parameters:

variablesNames : sequence of str

Names of the variables to analyse

setLevel(value)

Level accessor.

Parameters:

number : positive int

Number of levels for a regular grid

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.

setTrajectoriesNumber(number)

Number of trajectories accessor.

Parameters:

number : positive int

Number of trajectories

setVisibility(visible)

Accessor to the object’s visibility state.

Parameters:

visible : bool

Visibility flag.