Input¶

class persalys.Input(*args)¶

Create an input variable.

Represents an input variable.

Parameters

namestr: Name
valuefloat: Default value
distributionDistribution: Associated distribution
descriptionstr: Description text (optional)

Examples

>>> import openturns as ot
>>> import persalys
>>> F = persalys.Input('F', 0., ot.Normal(75000., 5000.), 'Traction load')
>>> R = persalys.Input('R', ot.Normal(75000., 5000.))
>>> S = persalys.Input('S', 10.5)

Methods

`getClassName`(self)	Accessor to the object’s name.
`getDescription`(self)	Description accessor.
`getDistribution`(self)	Distribution accessor.
`getDistributionParametersType`(self)	Distribution parameters type accessor.
`getFiniteDifferenceStep`(self)	Finite difference step accessor.
`getId`(self)	Accessor to the object’s id.
`getName`(self)	Accessor to the object’s name.
`getPythonScript`(self)	Python script accessor.
`getShadowedId`(self)	Accessor to the object’s shadowed id.
`getValue`(self)	Default value accessor.
`getVisibility`(self)	Accessor to the object’s visibility state.
`hasName`(self)	Test if the object is named.
`hasVisibleName`(self)	Test if the object has a distinguishable name.
`isStochastic`(self)	Whether the variable is stochastic.
`setDescription`(self, description)	Description accessor.
`setDistribution`(self, distribution)	Distribution accessor.
`setDistributionParametersType`(self, …)	Distribution parameters type accessor.
`setFiniteDifferenceStep`(self, step)	Finite difference step accessor.
`setName`(self, name)	Accessor to the object’s name.
`setShadowedId`(self, id)	Accessor to the object’s shadowed id.
`setStochastic`(self, stoch)	Whether the variable is stochastic.
`setValue`(self, value)	Default value accessor.
`setVisibility`(self, visible)	Accessor to the object’s visibility state.

__init__(self, *args)¶: Initialize self. See help(type(self)) for accurate signature.

getClassName(self)¶

Accessor to the object’s name.

Returns

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

getDescription(self)¶

Description accessor.

Returns

descriptionopenturns.Description: Text describing the variable

getDistribution(self)¶

Distribution accessor.

Returns

distributionopenturns.Distribution: Distribution associated with the variable

getDistributionParametersType(self)¶

Distribution parameters type accessor.

Returns

parametersTypeint: Distribution parameters index

getFiniteDifferenceStep(self)¶

Finite difference step accessor.

Returns

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

getId(self)¶

Accessor to the object’s id.

Returns

idint: Internal unique identifier.

getName(self)¶

Accessor to the object’s name.

Returns

namestr: The name of the object.

getPythonScript(self)¶

Python script accessor.

Returns

scriptstr: Python script to replay the analysis

getShadowedId(self)¶

Accessor to the object’s shadowed id.

Returns

idint: Internal unique identifier.

getValue(self)¶

Default value accessor.

Returns

valuefloat: Default value

getVisibility(self)¶

Accessor to the object’s visibility state.

Returns

visiblebool: Visibility flag.

hasName(self)¶

Test if the object is named.

Returns

hasNamebool: True if the name is not empty.

hasVisibleName(self)¶

Test if the object has a distinguishable name.

Returns

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

isStochastic(self)¶

Whether the variable is stochastic.

Returns

isStochasticbool: Whether the variable is stochastic

setDescription(self, description)¶

Description accessor.

Parameters

descriptionstr: Text describing the variable

setDistribution(self, distribution)¶

Distribution accessor.

Parameters

distributionopenturns.Distribution: Distribution associated with the variable

setDistributionParametersType(self, distributionParametersType)¶

Distribution parameters type accessor.

Parameters

parametersTypeint: Distribution parameters index

setFiniteDifferenceStep(self, step)¶

Finite difference step accessor.

Parameters

stepfloat: Finite difference step used to define the gradient and the hessian of the model’s function. By default the step is equal to 1e-7. The gradient function is defined with the first order non-centered finite difference scheme and the hessian function with the second order centered finite difference scheme.

Notes

First order non-centered finite difference scheme:

$\frac{\partial f_j}{\partial x_i} \approx \frac{f_j(x + \epsilon_i) - f_j(x)} {\epsilon_i}$

Second order centered finite difference scheme:

$\frac{\partial^2 f_k}{\partial x_i \partial x_j} \approx \frac{ f_k(x + \epsilon_i + \epsilon_j) - f_k(x + \epsilon_i - \epsilon_j) + f_k(x - \epsilon_i - \epsilon_j) - f_k(x - \epsilon_i + \epsilon_j)} {4 \epsilon_i \epsilon_j}$

setName(self, name)¶

Accessor to the object’s name.

Parameters

namestr: The name of the object.

setShadowedId(self, id)¶

Accessor to the object’s shadowed id.

Parameters

idint: Internal unique identifier.

setStochastic(self, stoch)¶

Whether the variable is stochastic.

Parameters

isStochasticbool: Whether the variable is stochastic

setValue(self, value)¶

Default value accessor.

Parameters

valuefloat: Default value

setVisibility(self, visible)¶

Accessor to the object’s visibility state.

Parameters

visiblebool: Visibility flag.

Input¶

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