FieldKarhunenLoeveAnalysis

class persalys.FieldKarhunenLoeveAnalysis(*args)

Create a Karhunen-Loeve decomposition of a DataFieldModel

Parameters:

namestr

Name

dataModelDataFieldModel

Data to decompose

Notes

The class has two main uses. Direct: when handling a DataFieldModel. Indirect: used internally in FieldMonteCarloAnalysis

Methods

getClassName()	Accessor to the object's name.
getDataFieldModel()	DataFieldModel accessor.
getErrorMessage()	Error message accessor.
getInterestVariables()	Get the variables to analyse.
getKarhunenLoeveThreshold()	Accessor to the limit ratio on eigenvalues.
getName()	Accessor to the object's name.
getPythonScript()	Physical model accessor.
getQuantileLevel()	Probability level accessor.
getResult()	Result 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.
setInterestVariables(variablesNames)	Set the variables to analyse.
setKarhunenLoeveThreshold(threshold)	Accessor to the limit ratio on eigenvalues.
setName(name)	Accessor to the object's name.
setQuantileLevel(proba)	Probability level accessor.

launch

__init__(*args)

getClassName()

Accessor to the object’s name.

Returns:

class_namestr

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

getDataFieldModel()

DataFieldModel accessor.

Returns:

dataModelDataFieldModel

DataFieldModel associated to the analysis.

getErrorMessage()

Error message accessor.

Returns:

messagestr

Error message if the analysis failed

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()

getName()

Accessor to the object’s name.

Returns:

namestr

The name of the object.

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

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.

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()

setName(name)

Accessor to the object’s name.

Parameters:

namestr

The name of the object.

setQuantileLevel(proba)

Probability level accessor.

Parameters:

levelfloat,

Probability level