/usr/include/openturns/swig/AdaptiveStrategyImplementation_doc.i is in libopenturns-dev 1.7-3.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 | %define OT_AdaptiveStrategy_doc
"Base class for the construction of the truncated multivariate orthogonal basis.
Available constructors:
AdaptiveStrategy(*orthogonalBasis, dimension*)
AdaptiveStrategy(*adaptiveStrategyImplementation*)
Parameters
----------
orthogonalBasis : :class:`~openturns.OrthogonalBasis`
An OrthogonalBasis.
dimension : positive int
Number of terms of the basis. This first usage has the same implementation
as the second with a :class:`~openturns.FixedStrategy`.
adaptiveStrategyImplementation : AdaptiveStrategyImplementation
Adaptive strategy implementation which is a :class:`~openturns.FixedStrategy`,
:class:`~openturns.SequentialStrategy` or a :class:`~openturns.CleaningStrategy`.
See also
--------
FunctionalChaosAlgorithm, FixedStrategy, SequentialStrategy, 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 :math:`K` of :math:`\\\\Nset`.
There are three different strategies in OpenTURNS :
- :class:`~openturns.FixedStrategy`,
- :class:`~openturns.SequentialStrategy`,
- :class:`~openturns.CleaningStrategy`.
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."
%enddef
%feature("docstring") OT::AdaptiveStrategyImplementation
OT_AdaptiveStrategy_doc
// ---------------------------------------------------------------------
%define OT_AdaptiveStrategy_computeInitialBasis_doc
"Compute initial basis for the approximation.
See also
--------
getPsi"
%enddef
%feature("docstring") OT::AdaptiveStrategyImplementation::computeInitialBasis
OT_AdaptiveStrategy_computeInitialBasis_doc
// ---------------------------------------------------------------------
%define OT_AdaptiveStrategy_getBasis_doc
"Accessor to the underlying orthogonal basis.
Returns
-------
basis : :class:`~openturns.OrthogonalBasis`
Orthogonal basis of which the adaptive strategy is based."
%enddef
%feature("docstring") OT::AdaptiveStrategyImplementation::getBasis
OT_AdaptiveStrategy_getBasis_doc
// ---------------------------------------------------------------------
%define OT_AdaptiveStrategy_getMaximumDimension_doc
"Accessor to the maximum dimension of the orthogonal basis.
Returns
-------
P : integer
Maximum dimension of the truncated basis."
%enddef
%feature("docstring") OT::AdaptiveStrategyImplementation::getMaximumDimension
OT_AdaptiveStrategy_getMaximumDimension_doc
// ---------------------------------------------------------------------
%define OT_AdaptiveStrategy_getPsi_doc
"Accessor to the orthogonal polynomials of the basis.
Returns
-------
polynomials : list of polynomials
Sequence of :math:`P` analytical polynomials.
Notes
-----
The method :meth:`computeInitialBasis` must be applied first.
Examples
--------
>>> import openturns as ot
>>> productBasis = ot.OrthogonalProductPolynomialFactory([ot.HermiteFactory()])
>>> adaptiveStrategy = ot.FixedStrategy(productBasis, 3)
>>> adaptiveStrategy.computeInitialBasis()
>>> print(adaptiveStrategy.getPsi())
[1,x,-0.707107 + 0.707107 * x^2]"
%enddef
%feature("docstring") OT::AdaptiveStrategyImplementation::getPsi
OT_AdaptiveStrategy_getPsi_doc
// ---------------------------------------------------------------------
%define OT_AdaptiveStrategy_setMaximumDimension_doc
"Accessor to the maximum dimension of the orthogonal basis.
Parameters
----------
P : integer
Maximum dimension of the truncated basis."
%enddef
%feature("docstring") OT::AdaptiveStrategyImplementation::setMaximumDimension
OT_AdaptiveStrategy_setMaximumDimension_doc
// ---------------------------------------------------------------------
%define OT_AdaptiveStrategy_updateBasis_doc
"Update the basis for the next iteration of approximation.
Notes
-----
No changes are made to the basis in the fixed strategy."
%enddef
%feature("docstring") OT::AdaptiveStrategyImplementation::updateBasis
OT_AdaptiveStrategy_updateBasis_doc
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