ApproximationAlgorithm

class ApproximationAlgorithm(*args)

Approximation algorithm.

See also

LeastSquaresStrategy, ApproximationAlgorithmImplementationFactory

LeastSquaresMetaModelSelectionFactory

Notes

The ApproximationAlgorithm is built from an approximation algorithm implementation factory which is a ApproximationAlgorithmImplementationFactory or a LeastSquaresMetaModelSelectionFactory.

This class is not usable because it has sense only whithin the FunctionalChaosAlgorithm.

Methods

getClassName()	Accessor to the object's name.
getCoefficients()	Accessor to the coefficients.
getId()	Accessor to the object's id.
getImplementation()	Accessor to the underlying implementation.
getName()	Accessor to the object's name.
getPsi()	Accessor to the basis.
getRelativeError()	Accessor to the coefficients.
getResidual()	Accessor to the coefficients.
getVerbose()	Accessor to the verbosity flag.
getWeight()	Accessor to the weights.
getX()	Accessor to the input sample.
getY()	Accessor to the output sample.
run()	Run the algorithm.
setName(name)	Accessor to the object's name.
setVerbose(verbose)	Accessor to the verbosity flag.

__init__(*args)

getClassName()

Accessor to the object’s name.

Returns

class_namestr

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

getCoefficients()

Accessor to the coefficients.

Returns

coefficientsPoint

The coefficients

getId()

Accessor to the object’s id.

Returns

idint

Internal unique identifier.

getImplementation()

Accessor to the underlying implementation.

Returns

implImplementation

The implementation class.

getName()

Accessor to the object’s name.

Returns

namestr

The name of the object.

getPsi()

Accessor to the basis.

Returns

coefficientsBasis

The basis

getRelativeError()

Accessor to the coefficients.

Returns

relativeErrorfloat

The relative error

getResidual()

Accessor to the coefficients.

Returns

coefficientsfloat

The residual

getVerbose()

Accessor to the verbosity flag.

Returns

vbool.

Verbosity

getWeight()

Accessor to the weights.

Returns

weightPoint

Output weights

getX()

Accessor to the input sample.

Returns

xSample

Input sample

getY()

Accessor to the output sample.

Returns

ySample

Input sample

run()

Run the algorithm.

setName(name)

Accessor to the object’s name.

Parameters

namestr

The name of the object.

setVerbose(verbose)

Accessor to the verbosity flag.

Parameters

vbool

Enable or disable the verbosity.