class AdaptiveStrategy(*args)

Base class for the construction of the truncated multivariate orthogonal basis.

Available constructors:

Parameters: orthogonalBasis : OrthogonalBasis An OrthogonalBasis. dimension : positive int Number of terms of the basis. This first usage has the same implementation as the second with a FixedStrategy. adaptiveStrategyImplementation : AdaptiveStrategyImplementation Adaptive strategy implementation which is a FixedStrategy, SequentialStrategy or a CleaningStrategy.

Notes

A strategy must be chosen for the selection of the different terms of the multivariate basis in which the response surface by functional chaos is expressed. The selected terms are regrouped in the finite subset of .

There are three different strategies available:

These strategies are conceived in such a way to be adapted for other orthogonal expansions (other than polynomial). For the moment, their implementation are only useful for the polynomial chaos expansion.

Methods

 computeInitialBasis() Compute initial basis for the approximation. getBasis() Accessor to the underlying orthogonal basis. getClassName() Accessor to the object’s name. getId() Accessor to the object’s id. getImplementation(*args) Accessor to the underlying implementation. getMaximumDimension() Accessor to the maximum dimension of the orthogonal basis. getName() Accessor to the object’s name. getPsi() Accessor to the orthogonal polynomials of the basis. setMaximumDimension(maximumDimension) Accessor to the maximum dimension of the orthogonal basis. setName(name) Accessor to the object’s name. updateBasis(alpha_k, residual, relativeError) Update the basis for the next iteration of approximation.
__init__(*args)

Initialize self. See help(type(self)) for accurate signature.

computeInitialBasis()

Compute initial basis for the approximation.

getBasis()

Accessor to the underlying orthogonal basis.

Returns: basis : OrthogonalBasis Orthogonal basis of which the adaptive strategy is based.
getClassName()

Accessor to the object’s name.

Returns: class_name : str The object class name (object.__class__.__name__).
getId()

Accessor to the object’s id.

Returns: id : int Internal unique identifier.
getImplementation(*args)

Accessor to the underlying implementation.

Returns: impl : Implementation The implementation class.
getMaximumDimension()

Accessor to the maximum dimension of the orthogonal basis.

Returns: P : integer Maximum dimension of the truncated basis.
getName()

Accessor to the object’s name.

Returns: name : str The name of the object.
getPsi()

Accessor to the orthogonal polynomials of the basis.

Returns: polynomials : list of polynomials Sequence of analytical polynomials.

Notes

The method computeInitialBasis() must be applied first.

Examples

>>> import openturns as ot
>>> productBasis = ot.OrthogonalProductPolynomialFactory([ot.HermiteFactory()])
[1,x0,-0.707107 + 0.707107 * x0^2]

setMaximumDimension(maximumDimension)

Accessor to the maximum dimension of the orthogonal basis.

Parameters: P : integer Maximum dimension of the truncated basis.
setName(name)

Accessor to the object’s name.

Parameters: name : str The name of the object.
updateBasis(alpha_k, residual, relativeError)

Update the basis for the next iteration of approximation.

Notes

No changes are made to the basis in the fixed strategy.