/usr/include/openturns/swig/KrigingResult_doc.i is in libopenturns-dev 1.5-7build2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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 | %feature("docstring") OT::KrigingResult
"Kriging result.
Notes
-----
Structure created by the method run() of a :class:`~openturns.KrigingAlgorithm`,
and obtained thanks to the method getResult().
Examples
--------
>>> import openturns as ot
>>> f = ot.NumericalMathFunction(['x0'], ['y'], ['x0 * sin(x0)'])
>>> sampleX = [[1.0], [2.0], [3.0], [4.0], [5.0], [6.0]]
>>> sampleY = f(sampleX)
>>> basis = ot.Basis([ot.NumericalMathFunction('x', 'x'), ot.NumericalMathFunction('x', 'x^2')])
>>> covarianceModel = ot.GeneralizedExponential(1, 2.0, 2.0)
>>> algoKriging = ot.KrigingAlgorithm(sampleX, sampleY, basis, covarianceModel)
>>> algoKriging.run()
>>> resKriging = algoKriging.getResult()
>>> metaModel = resKriging.getMetaModel()
>>> graph = metaModel.draw(0.0, 7.0)
>>> cloud = ot.Cloud(sampleX, sampleY)
>>> cloud.setPointStyle('fcircle')
>>> graph.add(cloud)
>>> graph.add(f.draw(0.0, 7.0))
>>> graph.setColors(['black', 'blue', 'red'])
"
// ---------------------------------------------------------------------
%feature("docstring") OT::KrigingResult::getCovarianceCoefficients
"Accessor to the covariance coefficients.
Returns
-------
covCoeff : :class:`~openturns.NumericalSample` which size is the ouput dimension of :math:`f` and which dimension is :math:`p`.
Notes
-----
Each point of the sample refers to the vector:
.. math::
\\\\Tr{\\\\vect{c}_{\\\\vect{\\\\theta}}(\\\\vect{x})}\\\\mat{C}^{-1}(\\\\vect{y}-\\\\mat{F}\\\\, \\\\tilde{\\\\vect{\\\\beta}})
"
// ---------------------------------------------------------------------
%feature("docstring") OT::KrigingResult::getTrendCoefficients
"Accessor to the coefficients of the generalized linear model of the trend.
Parameters
----------
trendCoef : :class:`~openturns.NumericalSample` which size is the ouput dimension of :math:`f` and which dimension is :math:`p`.
Notes
-----
Each point of the sample refers to the vector:
.. math::
\\\\left(\\\\beta_1, \\\\ldots, \\\\beta_p\\\\right)
"
// ---------------------------------------------------------------------
%feature("docstring") OT::KrigingResult::getCovarianceModels
"Accessor to the collection of covariance models.
Returns
-------
covModelColl : list of :class:`~openturns.CovarianceModel` which size is the ouput dimension of :math:`f`.
Notes
-----
Each covariance model refers to the function :math:`c_{\\\\vect{\\\\theta}}(\\\\vect{x}, \\\\vect{y})`.
"
// ---------------------------------------------------------------------
%feature("docstring") OT::KrigingResult::getBasis
"Accessor to the basis of the generalized linear model.
Returns
-------
basis : :class:`~openturns.Basis`
Basis of the generalized linear model.
"
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