SymbolicPhysicalModel¶

class persalys.SymbolicPhysicalModel(*args)¶

Create a physical model defined by analytical formulas.

Parameters:

name : str

Name

inputs : sequence of Input

Input variables (optional)

outputs : sequence of Output

Output variables (optional)

formulas : sequence of str

List of analytical formulas between the inputs and the outputs (optional). The function is defined by ouputs = formulas(inputs).

Examples

>>> import openturns as ot
>>> import persalys

>>> 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')
>>> model = persalys.SymbolicPhysicalModel('myPhysicalModel', [R, F], [G], ['R-F/(pi_*100.0)'])

>>> y = model.getFunction()([300.0,75000.0])

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.
`getFormula`(outputName)	Output formula accessor.
`getFormulas`()	Formulas 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.
`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.
`setFiniteDifferenceStep`(inputName, step)	Finite difference step accessor.
`setFormula`(outputName, formula)	Output formula accessor.
`setFormulas`(formulas)	Formulas 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.
`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:

input : Input

New variable

addOutput(output)¶

Add an output variable.

Parameters:

output : Output

New variable

clearInputs()¶: Remove all the input variables.

clearOutputs()¶: Remove all the output variables.

getClassName()¶

Accessor to the object’s name.

Returns:

class_name : str

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

getCopula()¶

Copula accessor.

Parameters:

copula : openturns.Copula

The copula

getDistribution()¶

Distribution accessor.

Parameters:

Distribution : openturns.ComposedDistribution

The composed distribution (marginals and dependence)

getFormula(outputName)¶

Output formula accessor.

Parameters:

name : str

Variable name

Returns:

formula : str

Formula text

getFormulas()¶

Formulas accessor.

Returns:

formulas : openturns.Description

Output formulas

getFunction(*args)¶

Accessor to the underlying function.

Parameters:

outputNames : sequence of str

Names of the outputs to be evaluated (optional)

Returns:

function : openturns.Function

Function evaluating the outputs

getId()¶

Accessor to the object’s id.

Returns:

id : int

Internal unique identifier.

getInputByName(*args)¶

Input variable accessor.

Parameters:

name : str

Variable name

Returns:

input : Input

Input variable

getInputDimension()¶

Number of input variables accessor.

Returns:

dimension : int

Number of input variables

getInputNames()¶

Input variable names accessor.

Returns:

names : openturns.Description

Input variable names

getInputRandomVector()¶

Input random vector accessor.

Returns:

names : openturns.RandomVector

Input random vector

getInputs()¶

Input variables accessor.

Returns:

inputs : sequence of Input

Input variables

getMeshModel()¶

Mesh model accessor.

Returns:

mesh : MeshModel

Mesh model

getName()¶

Accessor to the object’s name.

Returns:

name : str

The name of the object.

getOutputByName(*args)¶

Output variable accessor.

Parameters:

name : str

Variable name

Returns:

input : Output

Output variable

getOutputDimension()¶

Number of output variables accessor.

Returns:

dimension : int

Number of output variables

getOutputNames()¶

Output variable names accessor.

Returns:

names : openturns.Description

Ouput variable names

getOutputRandomVector(outputNames)¶

Output random vector accessor.

Returns:

names : openturns.RandomVector

Output random vector

getOutputs()¶

Output variables accessor.

Returns:

outputs : sequence of Output

Output variables

getPointToFieldFunction(*args)¶

Accessor to the underlying function.

Parameters:

outputNames : sequence of str

Names of the outputs to be evaluated (optional)

Returns:

function : openturns.PointToFieldFunction

Function evaluating the outputs along the mesh nodes

getPythonScript()¶

Python script accessor.

Returns:

script : str

Python script to replay the model

getRestrictedFunction(*args)¶

Accessor to the function restricted to its stochastic inputs.

Parameters:

outputNames : sequence of str

Output variables (optional)

Returns:

restricted : openturns.Function

Stochastic function

getRestrictedPointToFieldFunction(outputNames)¶

Accessor to the field function restricted to its stochastic inputs.

Parameters:

outputNames : sequence of str

Output variables (optional)

Returns:

restricted : openturns.PointToFieldFunction

Stochastic field function (for model with mesh)

getSelectedOutputsNames()¶

Accessor to the selected outputs names.

Returns:

names : openturns.Description

Selected outputs names

getShadowedId()¶

Accessor to the object’s shadowed id.

Returns:

id : int

Internal unique identifier.

getStochasticInputNames()¶

Accessor to the names of the stochastic input variables.

Returns:

names : openturns.Description

Names of the stochastic input variables

getVisibility()¶

Accessor to the object’s visibility state.

Returns:

visible : bool

Visibility flag.

hasInputNamed(inputName)¶

Check if an input has the given name.

Parameters:

name : str

Variable name

Returns:

has : bool

Whether an input has the given name

hasMesh()¶

Whether the model has a mesh.

Returns:

hasMesh : bool

Whether the model has a mesh

hasName()¶

Test if the object is named.

Returns:

hasName : bool

True if the name is not empty.

hasOutputNamed(outputName)¶

Check if an output has the given name.

Parameters:

name : str

Variable name

Returns:

has : bool

Whether an output has the given name

hasStochasticInputs()¶

Whether it contains stochastic variables.

Returns:

has : bool

Whether it contains stochastic variables

hasVisibleName()¶

Test if the object has a distinguishable name.

Returns:

hasVisibleName : bool

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

isParallel()¶

Whether the evaluations of the model are parallelized.

Returns:

isParallel : bool

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

isValid()¶

Whether it is valid.

Returns:

isValid : bool

Whether it is valid

removeInput(inputName)¶

Remove an input variable.

Parameters:

name : str

Variable name

removeOutput(outputName)¶

Remove an output variable.

Parameters:

name : str

Variable name

selectOutput(outputName, selected)¶

Select output.

Parameters:

name : str

Output name

isSelected : bool

Whether it is selected

setCopula(inputNames, copula)¶

Copula accessor.

Parameters:

copula : openturns.Copula

The copula

setDistribution(inputName, distribution)¶

Input distribution accessor.

Parameters:

name : str

Variable name

distribution : openturns.Distribution

Variable distribution

setDistributionParametersType(inputName, distributionParametersType)¶

Input distribution parameter type accessor.

Parameters:

name : str

Variable name

parametersType : int

Distribution parameter type accessor

setFiniteDifferenceStep(inputName, step)¶

Finite difference step accessor.

Parameters:

name : str

Variable name

step : float

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

setFormula(outputName, formula)¶

Output formula accessor.

Parameters:

name : str

Variable name

formula : str

Formula text

setFormulas(formulas)¶

Formulas accessor.

Parameters:

formulas : sequence of str

Output formulas

setInputDescription(inputName, description)¶

Input description accessor.

Parameters:

name : str

Variable name

description : str

Description text

setInputName(inputName, newName)¶

Input variable name accessor.

Parameters:

name : str

Variable name

newName : str

New name

setInputStochastic(inputName, stoch)¶

Whether the input variable is stochastic.

Parameters:

name : str

Variable name

isStochastic : bool

Whether the input variable is stochastic

setInputValue(inputName, value)¶

Input variable value accessor.

Parameters:

name : str

Variable name

value : float

New value

setInputs(inputs)¶

Input variables accessor.

Parameters:

inputs : sequence of Input

Input variables

setMeshModel(meshModel)¶

Mesh model accessor.

Parameters:

mesh : MeshModel

Mesh model

setName(name)¶

Accessor to the object’s name.

Parameters:

name : str

The name of the object.

setOutputDescription(outputName, description)¶

Output description accessor.

Parameters:

name : str

Variable name

description : str

Description text

setOutputName(outputName, newName)¶

Output variable name accessor.

Parameters:

name : str

Variable name

newName : str

New name

setOutputValue(outputName, value)¶

Output variable name accessor.

Parameters:

name : str

Variable name

value : float

New value

setOutputs(outputs)¶

Output variables accessor.

Parameters:

outputs : sequence of Output

Output variables

setParallel(flag)¶

Whether the evaluations of the model are parallelized.

Parameters:

isParallel : bool

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

SymbolicPhysicalModel¶

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