gaussianProcess.cc

Go to the documentation of this file.

/*
 * LSST Data Management System
 * Copyright 2008-2016  AURA/LSST.
 *
 * This product includes software developed by the
 * LSST Project (http://www.lsst.org/).
 *
 * This program is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the LSST License Statement and
 * the GNU General Public License along with this program.  If not,
 * see <https://www.lsstcorp.org/LegalNotices/>.
 */
 
#include <pybind11/pybind11.h>
//#include <pybind11/operators.h>
#include <pybind11/stl.h>
 
#include "ndarray/pybind11.h"
 
#include "lsst/afw/math/GaussianProcess.h"
 
namespace py = pybind11;
 
using namespace lsst::afw::math;
 
template <typename T>
void declareKdTree(py::module &mod, const std::string &suffix) {
    py::class_<KdTree<T>> clsKdTree(mod, ("KdTree" + suffix).c_str());
    clsKdTree.def(py::init<>());
    clsKdTree.def("Initialize", &KdTree<T>::Initialize);
    clsKdTree.def("removePoint", &KdTree<T>::removePoint);
    clsKdTree.def("getData", (T (KdTree<T>::*)(int, int) const) & KdTree<T>::getData);
    clsKdTree.def("getData", (ndarray::Array<T, 1, 1> (KdTree<T>::*)(int) const) & KdTree<T>::getData);
    clsKdTree.def("addPoint", &KdTree<T>::addPoint);
    clsKdTree.def("getNPoints", &KdTree<T>::getNPoints);
    clsKdTree.def("getTreeNode", &KdTree<T>::getTreeNode);
    clsKdTree.def("findNeighbors", &KdTree<T>::findNeighbors);
};
 
template <typename T>
void declareCovariograms(py::module &mod, const std::string &suffix) {
    /* Covariogram */
    py::class_<Covariogram<T>, std::shared_ptr<Covariogram<T>>> clsCovariogram(
            mod, ("Covariogram" + suffix).c_str());
    clsCovariogram.def(py::init<>());
    clsCovariogram.def("__call__", &Covariogram<T>::operator());
 
    /* SquaredExpCovariogram */
    py::class_<SquaredExpCovariogram<T>, std::shared_ptr<SquaredExpCovariogram<T>>, Covariogram<T>>
            clsSquaredExpCovariogram(mod, ("SquaredExpCovariogram" + suffix).c_str());
    clsSquaredExpCovariogram.def(py::init<>());
    clsSquaredExpCovariogram.def("__call__", &SquaredExpCovariogram<T>::operator());
    clsSquaredExpCovariogram.def("setEllSquared", &SquaredExpCovariogram<T>::setEllSquared);
 
    /* SquaredExpCovariogram */
    py::class_<NeuralNetCovariogram<T>, std::shared_ptr<NeuralNetCovariogram<T>>, Covariogram<T>>
            clsNeuralNetCovariogram(mod, ("NeuralNetCovariogram" + suffix).c_str());
    clsNeuralNetCovariogram.def(py::init<>());
    clsNeuralNetCovariogram.def("setSigma0", &NeuralNetCovariogram<T>::setSigma0);
    clsNeuralNetCovariogram.def("setSigma1", &NeuralNetCovariogram<T>::setSigma1);
};
 
template <typename T>
void declareGaussianProcess(py::module &mod, const std::string &suffix) {
    py::class_<GaussianProcess<T>> clsGaussianProcess(mod, ("GaussianProcess" + suffix).c_str());
    /* Constructors */
    clsGaussianProcess.def(py::init<ndarray::Array<T, 2, 2> const &, ndarray::Array<T, 1, 1> const &,
                                    std::shared_ptr<Covariogram<T>> const &>());
    clsGaussianProcess.def(py::init<ndarray::Array<T, 2, 2> const &, ndarray::Array<T, 1, 1> const &,
                                    ndarray::Array<T, 1, 1> const &, ndarray::Array<T, 1, 1> const &,
                                    std::shared_ptr<Covariogram<T>> const &>());
    clsGaussianProcess.def(py::init<ndarray::Array<T, 2, 2> const &, ndarray::Array<T, 2, 2> const &,
                                    std::shared_ptr<Covariogram<T>> const &>());
    clsGaussianProcess.def(py::init<ndarray::Array<T, 2, 2> const &, ndarray::Array<T, 1, 1> const &,
                                    ndarray::Array<T, 1, 1> const &, ndarray::Array<T, 2, 2> const &,
                                    std::shared_ptr<Covariogram<T>> const &>());
    /* Members */
    clsGaussianProcess.def(
            "interpolate",
            (T (GaussianProcess<T>::*)(ndarray::Array<T, 1, 1>, ndarray::Array<T, 1, 1> const &, int) const) &
                    GaussianProcess<T>::interpolate);
    clsGaussianProcess.def("interpolate",
                           (void (GaussianProcess<T>::*)(ndarray::Array<T, 1, 1>, ndarray::Array<T, 1, 1>,
                                                         ndarray::Array<T, 1, 1> const &, int) const) &
                                   GaussianProcess<T>::interpolate);
    clsGaussianProcess.def("selfInterpolate",
                           (T (GaussianProcess<T>::*)(ndarray::Array<T, 1, 1>, int, int) const) &
                                   GaussianProcess<T>::selfInterpolate);
    clsGaussianProcess.def(
            "selfInterpolate",
            (void (GaussianProcess<T>::*)(ndarray::Array<T, 1, 1>, ndarray::Array<T, 1, 1>, int, int) const) &
                    GaussianProcess<T>::selfInterpolate);
    clsGaussianProcess.def("setLambda", &GaussianProcess<T>::setLambda);
    clsGaussianProcess.def("setCovariogram", &GaussianProcess<T>::setCovariogram);
    clsGaussianProcess.def("addPoint", (void (GaussianProcess<T>::*)(ndarray::Array<T, 1, 1> const &, T)) &
                                               GaussianProcess<T>::addPoint);
    clsGaussianProcess.def("addPoint", (void (GaussianProcess<T>::*)(ndarray::Array<T, 1, 1> const &,
                                                                     ndarray::Array<T, 1, 1> const &)) &
                                               GaussianProcess<T>::addPoint);
    clsGaussianProcess.def("batchInterpolate",
                           (void (GaussianProcess<T>::*)(ndarray::Array<T, 1, 1>, ndarray::Array<T, 1, 1>,
                                                         ndarray::Array<T, 2, 2> const &) const) &
                                   GaussianProcess<T>::batchInterpolate);
    clsGaussianProcess.def(
            "batchInterpolate",
            (void (GaussianProcess<T>::*)(ndarray::Array<T, 1, 1>, ndarray::Array<T, 2, 2> const &) const) &
                    GaussianProcess<T>::batchInterpolate);
    clsGaussianProcess.def("batchInterpolate",
                           (void (GaussianProcess<T>::*)(ndarray::Array<T, 2, 2>, ndarray::Array<T, 2, 2>,
                                                         ndarray::Array<T, 2, 2> const &) const) &
                                   GaussianProcess<T>::batchInterpolate);
    clsGaussianProcess.def(
            "batchInterpolate",
            (void (GaussianProcess<T>::*)(ndarray::Array<T, 2, 2>, ndarray::Array<T, 2, 2> const &) const) &
                    GaussianProcess<T>::batchInterpolate);
    clsGaussianProcess.def("setKrigingParameter", &GaussianProcess<T>::setKrigingParameter);
    clsGaussianProcess.def("removePoint", &GaussianProcess<T>::removePoint);
    clsGaussianProcess.def("getNPoints", &GaussianProcess<T>::getNPoints);
    clsGaussianProcess.def("getData",
                           (void (GaussianProcess<T>::*)(ndarray::Array<T, 2, 2>, ndarray::Array<T, 1, 1>,
                                                         ndarray::Array<int, 1, 1>) const) &
                                   GaussianProcess<T>::getData);
    clsGaussianProcess.def("getData",
                           (void (GaussianProcess<T>::*)(ndarray::Array<T, 2, 2>, ndarray::Array<T, 2, 2>,
                                                         ndarray::Array<int, 1, 1>) const) &
                                   GaussianProcess<T>::getData);
};
 
PYBIND11_MODULE(gaussianProcess, mod) {
    declareCovariograms<double>(mod, "D");
    declareGaussianProcess<double>(mod, "D");
    declareKdTree<double>(mod, "D");
}