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LSST Data Management Base Package
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_gaussianProcess.cc
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1/*
2 * LSST Data Management System
3 * Copyright 2008-2016 AURA/LSST.
4 *
5 * This product includes software developed by the
6 * LSST Project (http://www.lsst.org/).
7 *
8 * This program is free software: you can redistribute it and/or modify
9 * it under the terms of the GNU General Public License as published by
10 * the Free Software Foundation, either version 3 of the License, or
11 * (at your option) any later version.
12 *
13 * This program is distributed in the hope that it will be useful,
14 * but WITHOUT ANY WARRANTY; without even the implied warranty of
15 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
16 * GNU General Public License for more details.
17 *
18 * You should have received a copy of the LSST License Statement and
19 * the GNU General Public License along with this program. If not,
20 * see <https://www.lsstcorp.org/LegalNotices/>.
21 */
22
23#include <pybind11/pybind11.h>
25
26#include "ndarray/pybind11.h"
27
29
30namespace py = pybind11;
31
32using namespace lsst::afw::math;
33namespace lsst {
34namespace afw {
35namespace math {
36namespace {
37template <typename T>
38void declareKdTree(lsst::cpputils::python::WrapperCollection &wrappers, const std::string &suffix) {
39 wrappers.wrapType(
40 py::class_<KdTree<T>>(wrappers.module, ("KdTree" + suffix).c_str()), [](auto &mod, auto &cls) {
41 cls.def(py::init<>());
42 cls.def("Initialize", &KdTree<T>::Initialize);
43 cls.def("removePoint", &KdTree<T>::removePoint);
44 cls.def("getData", (T(KdTree<T>::*)(int, int) const) & KdTree<T>::getData);
45 cls.def("getData", (ndarray::Array<T, 1, 1>(KdTree<T>::*)(int) const) & KdTree<T>::getData);
46 cls.def("addPoint", &KdTree<T>::addPoint);
47 cls.def("getNPoints", &KdTree<T>::getNPoints);
48 cls.def("getTreeNode", &KdTree<T>::getTreeNode);
49 cls.def("findNeighbors", &KdTree<T>::findNeighbors);
50 });
51};
52
53template <typename T>
54void declareCovariograms(lsst::cpputils::python::WrapperCollection &wrappers, const std::string &suffix) {
55 /* Covariogram */
56
58 wrappers.module, ("Covariogram" + suffix).c_str()),
59 [](auto &mod, auto &cls) {
60 cls.def(py::init<>());
61 cls.def("__call__", &Covariogram<T>::operator());
62 });
63 /* SquaredExpCovariogram */
64 wrappers.wrapType(
66 wrappers.module, ("SquaredExpCovariogram" + suffix).c_str()),
67 [](auto &mod, auto &cls) {
68 cls.def(py::init<>());
69 cls.def("__call__", &SquaredExpCovariogram<T>::operator());
70 cls.def("setEllSquared", &SquaredExpCovariogram<T>::setEllSquared);
71 });
72 /* NeuralNetCovariogram */
73 wrappers.wrapType(
75 wrappers.module, ("NeuralNetCovariogram" + suffix).c_str()),
76 [](auto &mod, auto &cls) {
77 cls.def(py::init<>());
78 cls.def("setSigma0", &NeuralNetCovariogram<T>::setSigma0);
79 cls.def("setSigma1", &NeuralNetCovariogram<T>::setSigma1);
80 });
81};
82
83template <typename T>
84void declareGaussianProcess(lsst::cpputils::python::WrapperCollection &wrappers, const std::string &suffix) {
85 wrappers.wrapType(
86 py::class_<GaussianProcess<T>>(wrappers.module, ("GaussianProcess" + suffix).c_str()),
87 [](auto &mod, auto &cls) {
88 /* Constructors */
89 cls.def(py::init<ndarray::Array<T, 2, 2> const &, ndarray::Array<T, 1, 1> const &,
90 std::shared_ptr<Covariogram<T>> const &>());
91 cls.def(py::init<ndarray::Array<T, 2, 2> const &, ndarray::Array<T, 1, 1> const &,
92 ndarray::Array<T, 1, 1> const &, ndarray::Array<T, 1, 1> const &,
93 std::shared_ptr<Covariogram<T>> const &>());
94 cls.def(py::init<ndarray::Array<T, 2, 2> const &, ndarray::Array<T, 2, 2> const &,
95 std::shared_ptr<Covariogram<T>> const &>());
96 cls.def(py::init<ndarray::Array<T, 2, 2> const &, ndarray::Array<T, 1, 1> const &,
97 ndarray::Array<T, 1, 1> const &, ndarray::Array<T, 2, 2> const &,
98 std::shared_ptr<Covariogram<T>> const &>());
99 /* Members */
100 cls.def("interpolate",
101 (T(GaussianProcess<T>::*)(ndarray::Array<T, 1, 1>, ndarray::Array<T, 1, 1> const &,
102 int) const) &
103 GaussianProcess<T>::interpolate);
104 cls.def("interpolate",
105 (void (GaussianProcess<T>::*)(ndarray::Array<T, 1, 1>, ndarray::Array<T, 1, 1>,
106 ndarray::Array<T, 1, 1> const &, int) const) &
107 GaussianProcess<T>::interpolate);
108 cls.def("selfInterpolate",
109 (T(GaussianProcess<T>::*)(ndarray::Array<T, 1, 1>, int, int) const) &
110 GaussianProcess<T>::selfInterpolate);
111 cls.def("selfInterpolate",
112 (void (GaussianProcess<T>::*)(ndarray::Array<T, 1, 1>, ndarray::Array<T, 1, 1>, int,
113 int) const) &
114 GaussianProcess<T>::selfInterpolate);
115 cls.def("setLambda", &GaussianProcess<T>::setLambda);
116 cls.def("setCovariogram", &GaussianProcess<T>::setCovariogram);
117 cls.def("addPoint", (void (GaussianProcess<T>::*)(ndarray::Array<T, 1, 1> const &, T)) &
118 GaussianProcess<T>::addPoint);
119 cls.def("addPoint", (void (GaussianProcess<T>::*)(ndarray::Array<T, 1, 1> const &,
120 ndarray::Array<T, 1, 1> const &)) &
121 GaussianProcess<T>::addPoint);
122 cls.def("batchInterpolate",
123 (void (GaussianProcess<T>::*)(ndarray::Array<T, 1, 1>, ndarray::Array<T, 1, 1>,
124 ndarray::Array<T, 2, 2> const &) const) &
125 GaussianProcess<T>::batchInterpolate);
126 cls.def("batchInterpolate",
127 (void (GaussianProcess<T>::*)(ndarray::Array<T, 1, 1>,
128 ndarray::Array<T, 2, 2> const &) const) &
129 GaussianProcess<T>::batchInterpolate);
130 cls.def("batchInterpolate",
131 (void (GaussianProcess<T>::*)(ndarray::Array<T, 2, 2>, ndarray::Array<T, 2, 2>,
132 ndarray::Array<T, 2, 2> const &) const) &
133 GaussianProcess<T>::batchInterpolate);
134 cls.def("batchInterpolate",
135 (void (GaussianProcess<T>::*)(ndarray::Array<T, 2, 2>,
136 ndarray::Array<T, 2, 2> const &) const) &
137 GaussianProcess<T>::batchInterpolate);
138 cls.def("setKrigingParameter", &GaussianProcess<T>::setKrigingParameter);
139 cls.def("removePoint", &GaussianProcess<T>::removePoint);
140 cls.def("getNPoints", &GaussianProcess<T>::getNPoints);
141 cls.def("getData",
142 (void (GaussianProcess<T>::*)(ndarray::Array<T, 2, 2>, ndarray::Array<T, 1, 1>,
143 ndarray::Array<int, 1, 1>) const) &
144 GaussianProcess<T>::getData);
145 cls.def("getData",
146 (void (GaussianProcess<T>::*)(ndarray::Array<T, 2, 2>, ndarray::Array<T, 2, 2>,
147 ndarray::Array<int, 1, 1>) const) &
148 GaussianProcess<T>::getData);
149 });
150};
151} // namespace
152
154 declareCovariograms<double>(wrappers, "D");
155 declareGaussianProcess<double>(wrappers, "D");
156 declareKdTree<double>(wrappers, "D");
157}
158} // namespace math
159} // namespace afw
160} // namespace lsst
The parent class of covariogram functions for use in Gaussian Process interpolation.
Stores values of a function sampled on an image and allows you to interpolate the function to unsampl...
The data for GaussianProcess is stored in a KD tree to facilitate nearest-neighbor searches.
a Covariogram that recreates a neural network with one hidden layer and infinite units in that layer
A helper class for subdividing pybind11 module across multiple translation units (i....
Definition python.h:242
PyType wrapType(PyType cls, ClassWrapperCallback function, bool setModuleName=true)
Add a type (class or enum) wrapper, deferring method and other attribute definitions until finish() i...
Definition python.h:391
void wrapGaussianProcess(lsst::cpputils::python::WrapperCollection &wrappers)