aare/python/src/interpolation.hpp
Erik Fröjdh 11cd2ec654
Interpolate (#137)
- added eta based interpolation
2025-03-18 17:45:38 +01:00

58 lines
2.2 KiB
C++

#include "aare/Interpolator.hpp"
#include "aare/NDArray.hpp"
#include "aare/NDView.hpp"
#include "np_helper.hpp"
#include <cstdint>
#include <filesystem>
#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
namespace py = pybind11;
void define_interpolation_bindings(py::module &m) {
PYBIND11_NUMPY_DTYPE(aare::Photon, x,y,energy);
py::class_<aare::Interpolator>(m, "Interpolator")
.def(py::init([](py::array_t<double, py::array::c_style | py::array::forcecast> etacube, py::array_t<double> xbins,
py::array_t<double> ybins, py::array_t<double> ebins) {
return Interpolator(make_view_3d(etacube), make_view_1d(xbins),
make_view_1d(ybins), make_view_1d(ebins));
}))
.def("get_ietax", [](Interpolator& self){
auto*ptr = new NDArray<double,3>{};
*ptr = self.get_ietax();
return return_image_data(ptr);
})
.def("get_ietay", [](Interpolator& self){
auto*ptr = new NDArray<double,3>{};
*ptr = self.get_ietay();
return return_image_data(ptr);
})
.def("interpolate", [](Interpolator& self, const ClusterVector<int32_t>& clusters){
auto photons = self.interpolate(clusters);
auto* ptr = new std::vector<Photon>{photons};
return return_vector(ptr);
});
// TODO! Evaluate without converting to double
m.def(
"hej",
[]() {
// auto boost_histogram = py::module_::import("boost_histogram");
// py::object axis =
// boost_histogram.attr("axis").attr("Regular")(10, 0.0, 10.0);
// py::object histogram = boost_histogram.attr("Histogram")(axis);
// return histogram;
// return h;
},
R"(
Evaluate a 1D Gaussian function for all points in x using parameters par.
Parameters
----------
x : array_like
The points at which to evaluate the Gaussian function.
par : array_like
The parameters of the Gaussian function. The first element is the amplitude, the second element is the mean, and the third element is the standard deviation.
)");
}