MorrisAnalysis

class persalys.MorrisAnalysis(*args)

Perform a Morris 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 Morris analysis:

>>> analysis = persalys.MorrisAnalysis('anAnalysis', myPhysicalModel)
>>> analysis.setBounds(ot.Interval([100, 60000], [350, 80000]))
>>> analysis.setLevel(5)
>>> 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.

getErrorDescription()

Design of experiments accessor.

getErrorMessage()

Error message accessor.

getFailedInputSample()

Failed input sample accessor.

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.

getTrajectoriesNumber()

Number of trajectories accessor.

getWarningMessage()

Warning message accessor.

hasName()

Test if the object is named.

hasValidResult()

Whether the analysis has been run.

isReliabilityAnalysis()

Whether the analysis involves reliability.

isRunning()

Whether the analysis is running.

run()

Launch the analysis.

setBlockSize(blockSize)

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.

setTrajectoriesNumber(number)

Number of trajectories accessor.

__init__(*args)
getBlockSize()

Block size accessor.

Returns:
blockSizepositive int

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

getBounds()

Bounds of the domain accessor.

Returns:
boundsopenturns.Interval

Bounds of the domain

getClassName()

Accessor to the object’s name.

Returns:
class_namestr

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

getErrorDescription()

Design of experiments accessor.

Returns:
errorDescDescription

Description containing messages from failed points.

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

getInterestVariables()

Get the variables to analyse.

Returns:
variablesNamessequence of str

Names of the variables to analyse

getLevel()

Level accessor.

Returns:
numberint

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

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

getResult()

Morris result accessor.

Returns:
resultMorrisResult

Result

getSeed()

Seed accessor.

Returns:
seedint

Seed value

getTrajectoriesNumber()

Number of trajectories accessor.

Returns:
numberint

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

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

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(blockSize)

Block size accessor.

Parameters:
blockSizepositive int

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

setBounds(bounds)

Bounds of the domain accessor.

Parameters:
boundsopenturns.Interval

Bounds of the domain

setInterestVariables(variablesNames)

Set the variables to analyse.

Parameters:
variablesNamessequence of str

Names of the variables to analyse

setLevel(value)

Level accessor.

Parameters:
numberpositive int

Number of levels for a regular grid

setName(name)

Accessor to the object’s name.

Parameters:
namestr

The name of the object.

setSeed(seed)

Seed accessor.

Parameters:
seedint

Seed value

setTrajectoriesNumber(number)

Number of trajectories accessor.

Parameters:
numberpositive int

Number of trajectories