/usr/include/openturns/swig/CleaningStrategy

%feature("docstring") OT::CleaningStrategy
"Cleaning truncation strategy.

Available constructors:
    CleaningStrategy(*orthogonalBasis, maximumDimension*)

    CleaningStrategy(*orthogonalBasis, maximumDimension, verbose*)

    CleaningStrategy(*orthogonalBasis, maximumDimension, maximumSize, 
    significanceFactor*)

    CleaningStrategy(*orthogonalBasis, maximumDimension, maximumSize, 
    significanceFactor, verbose*)

Parameters
----------
orthogonalBasis : :class:`~openturns.OrthogonalBasis`
    An OrthogonalBasis.
maximumDimension : positive int
    Maximum index that can be used by the :class:`~openturns.EnumerateFunction`
    to determine the last term of the basis.
maximumSize : positve int
    Parameter that characterizes the cleaning strategy. It represents the 
    number of efficient coefficients of the basis. Its default value is set to 
    20.
significanceFactor : float 
    Parameter used as a threshold for selecting the efficient coefficients of
    the basis. The real threshold represents the multiplication of the
    significanceFactor with the maximum magnitude of the current determined 
    coefficients. Its default value is equal to :math:`1e^{-4}`.
verbose : bool
    Used for the online monitoring of the current basis updates (removed or
    added coefficients).


See also
--------
AdaptiveStrategy, FixedStrategy, SequentialStrategy

Notes
-----
The cleaning strategy aims at building a PC expansion containing at most
:math:`P` significant coefficients, i.e. at most :math:`P` significant basis
functions. It proceeds as follows:

- Generate an initial PC basis made of the :math:`P` first polynomials
  (according to the adopted :class:`~openturns.EnumerateFunction`), or
  equivalently an initial set of indices :math:`K = \\\\{0, \\\\ldots, P-1\\\\}`.

- Discard from the basis all those polynomials :math:`\\\\Psi_j` associated with 
  insignificance coefficients, i.e. the coefficients that satisfy:

.. math::

    |a_j| \\\\leq \\\\epsilon \\\\times \\\\max_{ k \\\\in K } |a_k|

where :math:`\\\\epsilon` is the significance factor, default is
:math:`\\\\epsilon = 10^{-4}`.

- Add the next basis term :math:`\\\\Psi_{k+1}` to the current basis :math:`K`.
- Reiterate the procedure until either :math:`P` terms have been retained or if
  the given maximum index :math:`P_{max}` has been reached.


Examples
--------
>>> import openturns as ot
>>> ot.RandomGenerator.SetSeed(0)
>>> # Define the model
>>> inputDim = 1
>>> model = ot.NumericalMathFunction(['x'], ['y'], ['x*sin(x)'])
>>> # Create the input distribution
>>> distribution = ot.ComposedDistribution([ot.Uniform()]*inputDim)
>>> # Construction of the multivariate orthonormal basis
>>> polyColl = [0.]*inputDim
>>> for i in range(distribution.getDimension()):
...     polyColl[i] = ot.StandardDistributionPolynomialFactory(distribution.getMarginal(i))
>>> enumerateFunction = ot.LinearEnumerateFunction(inputDim)
>>> productBasis = ot.OrthogonalProductPolynomialFactory(polyColl, enumerateFunction)
>>> # Truncature strategy of the multivariate orthonormal basis
>>> # We want to select, among the maximumDimension = 100 first polynomials of
>>> # the multivariate basis, those which have the maximumSize = 20 most 
>>> # significant contribution (greatest coefficients), with respect to the 
>>> # significance factor = 10^-4.
>>> maximumDimension = 100
>>> maximumSize = 20
>>> significanceFactor = 1e-4
>>> adaptiveStrategy = ot.CleaningStrategy(productBasis, maximumDimension,
...                                          maximumSize, significanceFactor)"

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%feature("docstring") OT::CleaningStrategy::getCurrentVectorIndex
"Accessor to the current vector index.

Returns
-------
index : integer
    Current index of the basis term."

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%feature("docstring") OT::CleaningStrategy::getMaximumSize
"Accessor to the maximum size of the orthogonal basis.

Returns
-------
size : integer
    Maximum number of significant terms of the basis.

See also
--------
setMaximumSize"

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%feature("docstring") OT::CleaningStrategy::getSignificanceFactor
"Accessor to the significance factor.

Returns
-------
factor : float
    Value of the significance factor.

See also
--------
setSignificanceFactor"

// ---------------------------------------------------------------------

%feature("docstring") OT::CleaningStrategy::getVerbose
"Accessor to the verbose.

Returns
-------
verbose : bool
    Return if the online monitoring of the current basis updates is enabled or not.

See also
--------
setVerbose"

// ---------------------------------------------------------------------

%feature("docstring") OT::CleaningStrategy::setMaximumSize
"Accessor to the maximum size of the orthogonal basis.

Parameters
----------
size : integer
    Maximum number of significant terms of the basis.

See also
--------
getMaximumSize"

// ---------------------------------------------------------------------

%feature("docstring") OT::CleaningStrategy::setSignificanceFactor
"Accessor to the significance factor.

Parameters
----------
factor : float
    Value of the significance factor.

See also
--------
getSignificanceFactor"

// ---------------------------------------------------------------------

%feature("docstring") OT::CleaningStrategy::setVerbose
"Accessor to the verbose.

Parameters
----------
verbose : bool
    Enable the online monitoring of the current basis updates or not.

See also
--------
getVerbose"
libopenturns-dev 1.7-3 / usr / include / openturns / swig / CleaningStrategy_doc.i
