MetaModel

class persalys.MetaModel(*args)

Metamodel.

Parameters:
namestr

Name

functionopenturns.Function

Function (optional)

Attributes:
thisown

The membership flag

Methods

addInput(input)

Add an input variable.

addOutput(output)

Add an output variable.

clearInputs()

Remove all the input variables.

clearOutputs()

Remove all the output variables.

getClassName()

Accessor to the object's name.

getCopula()

Copula accessor.

getDistribution()

Distribution accessor.

getEvalTime()

Evaluation time accessor.

getFunction(*args)

Accessor to the underlying function.

getId()

Accessor to the object's id.

getInputByName(*args)

Input variable accessor.

getInputDimension()

Number of input variables accessor.

getInputNames()

Input variable names accessor.

getInputRandomVector()

Input random vector accessor.

getInputs()

Input variables accessor.

getMeshModel()

Mesh model accessor.

getName()

Accessor to the object's name.

getOutputByName(*args)

Output variable accessor.

getOutputDimension()

Number of output variables accessor.

getOutputNames()

Output variable names accessor.

getOutputRandomVector(outputNames)

Output random vector accessor.

getOutputs()

Output variables accessor.

getPointToFieldFunction(*args)

Accessor to the underlying function.

getProcessNumber()

Number of concurrent processes.

getPythonScript()

Python script accessor.

getRestrictedFunction(*args)

Accessor to the function restricted to its stochastic inputs.

getRestrictedPointToFieldFunction(outputNames)

Accessor to the field function restricted to its stochastic inputs.

getSelectedOutputsNames()

Accessor to the selected outputs names.

getShadowedId()

Accessor to the object's shadowed id.

getStochasticInputNames()

Accessor to the names of the stochastic input variables.

getVisibility()

Accessor to the object's visibility state.

hasInputNamed(inputName)

Check if an input has the given name.

hasMesh()

Whether the model has a mesh.

hasName()

Test if the object is named.

hasOutputNamed(outputName)

Check if an output has the given name.

hasStochasticInputs()

Whether it contains stochastic variables.

hasVisibleName()

Test if the object has a distinguishable name.

isParallel()

Whether the evaluations of the model are parallelized.

isValid()

Whether it is valid.

removeInput(inputName)

Remove an input variable.

removeOutput(outputName)

Remove an output variable.

selectOutput(outputName, selected)

Select output.

setCopula(inputNames, copula)

Copula accessor.

setDistribution(inputName, distribution)

Input distribution accessor.

setDistributionParametersType(inputName, ...)

Input distribution parameter type accessor.

setEvalTime(evalTime)

Evaluation time accessor.

setFiniteDifferenceStep(inputName, step)

Finite difference step accessor.

setFunction(function)

Metamodel function accessor.

setInputDescription(inputName, description)

Input description accessor.

setInputName(inputName, newName)

Input variable name accessor.

setInputStochastic(inputName, stoch)

Whether the input variable is stochastic.

setInputValue(inputName, value)

Input variable value accessor.

setInputs(inputs)

Input variables accessor.

setMeshModel(meshModel)

Mesh model accessor.

setName(name)

Accessor to the object's name.

setOutputDescription(outputName, description)

Output description accessor.

setOutputName(outputName, newName)

Output variable name accessor.

setOutputValue(outputName, value)

Output variable name accessor.

setOutputs(outputs)

Output variables accessor.

setParallel(flag)

Whether the evaluations of the model are parallelized.

setProcessNumber(processNumber)

Number of concurrent processes.

setShadowedId(id)

Accessor to the object's shadowed id.

setVisibility(visible)

Accessor to the object's visibility state.

__init__(*args)
addInput(input)

Add an input variable.

Parameters:
inputInput

New variable

addOutput(output)

Add an output variable.

Parameters:
outputOutput

New variable

clearInputs()

Remove all the input variables.

clearOutputs()

Remove all the output variables.

getClassName()

Accessor to the object’s name.

Returns:
class_namestr

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

getCopula()

Copula accessor.

Parameters:
copulaopenturns.Copula

The copula

getDistribution()

Distribution accessor.

Parameters:
Distributionopenturns.ComposedDistribution

The composed distribution (marginals and dependence)

getEvalTime()

Evaluation time accessor.

Returns:
evalTimefloat

Evaluation time

getFunction(*args)

Accessor to the underlying function.

Parameters:
outputNamessequence of str

Names of the outputs to be evaluated (optional)

Returns:
functionopenturns.Function

Function evaluating the outputs

getId()

Accessor to the object’s id.

Returns:
idint

Internal unique identifier.

getInputByName(*args)

Input variable accessor.

Parameters:
namestr

Variable name

Returns:
inputInput

Input variable

getInputDimension()

Number of input variables accessor.

Returns:
dimensionint

Number of input variables

getInputNames()

Input variable names accessor.

Returns:
namesopenturns.Description

Input variable names

getInputRandomVector()

Input random vector accessor.

Returns:
namesopenturns.RandomVector

Input random vector

getInputs()

Input variables accessor.

Returns:
inputssequence of Input

Input variables

getMeshModel()

Mesh model accessor.

Returns:
meshMeshModel

Mesh model

getName()

Accessor to the object’s name.

Returns:
namestr

The name of the object.

getOutputByName(*args)

Output variable accessor.

Parameters:
namestr

Variable name

Returns:
inputOutput

Output variable

getOutputDimension()

Number of output variables accessor.

Returns:
dimensionint

Number of output variables

getOutputNames()

Output variable names accessor.

Returns:
namesopenturns.Description

Output variable names

getOutputRandomVector(outputNames)

Output random vector accessor.

Returns:
namesopenturns.RandomVector

Output random vector

getOutputs()

Output variables accessor.

Returns:
outputssequence of Output

Output variables

getPointToFieldFunction(*args)

Accessor to the underlying function.

Parameters:
outputNamessequence of str

Names of the outputs to be evaluated (optional)

Returns:
functionopenturns.PointToFieldFunction

Function evaluating the outputs along the mesh nodes

getProcessNumber()

Number of concurrent processes.

Returns:
process_numberint

Maximum number of processes

getPythonScript()

Python script accessor.

Returns:
scriptstr

Python script to replay the model

getRestrictedFunction(*args)

Accessor to the function restricted to its stochastic inputs.

Parameters:
outputNamessequence of str

Output variables (optional)

Returns:
restrictedopenturns.Function

Stochastic function

getRestrictedPointToFieldFunction(outputNames)

Accessor to the field function restricted to its stochastic inputs.

Parameters:
outputNamessequence of str

Output variables (optional)

Returns:
restrictedopenturns.PointToFieldFunction

Stochastic field function (for model with mesh)

getSelectedOutputsNames()

Accessor to the selected outputs names.

Returns:
namesopenturns.Description

Selected outputs names

getShadowedId()

Accessor to the object’s shadowed id.

Returns:
idint

Internal unique identifier.

getStochasticInputNames()

Accessor to the names of the stochastic input variables.

Returns:
namesopenturns.Description

Names of the stochastic input variables

getVisibility()

Accessor to the object’s visibility state.

Returns:
visiblebool

Visibility flag.

hasInputNamed(inputName)

Check if an input has the given name.

Parameters:
namestr

Variable name

Returns:
hasbool

Whether an input has the given name

hasMesh()

Whether the model has a mesh.

Returns:
hasMeshbool

Whether the model has a mesh

hasName()

Test if the object is named.

Returns:
hasNamebool

True if the name is not empty.

hasOutputNamed(outputName)

Check if an output has the given name.

Parameters:
namestr

Variable name

Returns:
hasbool

Whether an output has the given name

hasStochasticInputs()

Whether it contains stochastic variables.

Returns:
hasbool

Whether it contains stochastic variables

hasVisibleName()

Test if the object has a distinguishable name.

Returns:
hasVisibleNamebool

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

isParallel()

Whether the evaluations of the model are parallelized.

Returns:
isParallelbool

Whether the evaluations of the model are parallelized (available only for the Python model)

isValid()

Whether it is valid.

Returns:
isValidbool

Whether it is valid

removeInput(inputName)

Remove an input variable.

Parameters:
namestr

Variable name

removeOutput(outputName)

Remove an output variable.

Parameters:
namestr

Variable name

selectOutput(outputName, selected)

Select output.

Parameters:
namestr

Output name

isSelectedbool

Whether it is selected

setCopula(inputNames, copula)

Copula accessor.

Parameters:
copulaopenturns.Copula

The copula

setDistribution(inputName, distribution)

Input distribution accessor.

Parameters:
namestr

Variable name

distributionopenturns.Distribution

Variable distribution

setDistributionParametersType(inputName, distributionParametersType)

Input distribution parameter type accessor.

Parameters:
namestr

Variable name

parametersTypeint

Distribution parameter type accessor

setEvalTime(evalTime)

Evaluation time accessor.

Parameters:
evalTimefloat

Evaluation time

setFiniteDifferenceStep(inputName, step)

Finite difference step accessor.

Parameters:
namestr

Variable name

stepfloat

Finite difference step used to define the gradient of the model’s function

setFunction(function)

Metamodel function accessor.

Parameters:
functionopenturns.Function

Metamodel function

setInputDescription(inputName, description)

Input description accessor.

Parameters:
namestr

Variable name

descriptionstr

Description text

setInputName(inputName, newName)

Input variable name accessor.

Parameters:
namestr

Variable name

newNamestr

New name

setInputStochastic(inputName, stoch)

Whether the input variable is stochastic.

Parameters:
namestr

Variable name

isStochasticbool

Whether the input variable is stochastic

setInputValue(inputName, value)

Input variable value accessor.

Parameters:
namestr

Variable name

valuefloat

New value

setInputs(inputs)

Input variables accessor.

Parameters:
inputssequence of Input

Input variables

setMeshModel(meshModel)

Mesh model accessor.

Parameters:
meshMeshModel

Mesh model

setName(name)

Accessor to the object’s name.

Parameters:
namestr

The name of the object.

setOutputDescription(outputName, description)

Output description accessor.

Parameters:
namestr

Variable name

descriptionstr

Description text

setOutputName(outputName, newName)

Output variable name accessor.

Parameters:
namestr

Variable name

newNamestr

New name

setOutputValue(outputName, value)

Output variable name accessor.

Parameters:
namestr

Variable name

valuefloat

New value

setOutputs(outputs)

Output variables accessor.

Parameters:
outputssequence of Output

Output variables

setParallel(flag)

Whether the evaluations of the model are parallelized.

Parameters:
isParallelbool

Whether the evaluations of the model are parallelized

Notes

This is only implemented for the Python model. Also, on Windows platforms, ProcessPoolExecutor startup time being much higher, you may want to evaluate enough points in batch rather than many small blocks. Refer to the setBlockSize method of the various algorithms.

setProcessNumber(processNumber)

Number of concurrent processes.

Parameters:
process_numberint

Maximum number of processes

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