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Format CUDA cluster finder files
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Run tests using data on local RHEL8 / build (push) Successful in 3m48s
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kferjaoui committed 2026-04-27 11:27:47 +02:00
1 parent 133cedf755
commit a086cbb897
8 files changed
+508 -440
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python/src/bind_ClusterFinderCUDA.hpp
+19 -24
View File
@@ -27,19 +27,15 @@ void define_ClusterFinderCUDA(py::module &m, const std::string &typestr) {
auto class_name = fmt::format("ClusterFinderCUDA_{}", typestr);
using ClusterType = Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>;
using CF = ClusterFinderCUDA<ClusterType, uint16_t, pd_type>;
using CF = ClusterFinderCUDA<ClusterType, uint16_t, pd_type>;
py::class_<CF>(m, class_name.c_str())
.def(py::init<Shape<2>, pd_type, size_t, int>(),
py::arg("image_size"),
py::arg("n_sigma") = 5.0,
py::arg("capacity") = 1'000'000,
py::arg("n_streams") = 1)
.def(py::init<Shape<2>, pd_type, size_t, int>(), py::arg("image_size"),
py::arg("n_sigma") = 5.0, py::arg("capacity") = 1'000'000,
py::arg("n_streams") = 1)
.def_property(
"nSigma",
&CF::get_nSigma,
&CF::set_nSigma,
"nSigma", &CF::get_nSigma, &CF::set_nSigma,
R"(Number of sigma above the pedestal to consider a photon during cluster finding.)")
.def("push_pedestal_frame",
@@ -50,21 +46,19 @@ void define_ClusterFinderCUDA(py::module &m, const std::string &typestr) {
.def("clear_pedestal", &CF::clear_pedestal)
.def_property_readonly(
"pedestal",
[](CF &self) {
auto pd = new NDArray<pd_type, 2>{};
*pd = self.pedestal();
return return_image_data(pd);
})
.def_property_readonly("pedestal",
[](CF &self) {
auto pd = new NDArray<pd_type, 2>{};
*pd = self.pedestal();
return return_image_data(pd);
})
.def_property_readonly(
"noise",
[](CF &self) {
auto arr = new NDArray<pd_type, 2>{};
*arr = self.noise();
return return_image_data(arr);
})
.def_property_readonly("noise",
[](CF &self) {
auto arr = new NDArray<pd_type, 2>{};
*arr = self.noise();
return return_image_data(arr);
})
.def(
"steal_clusters",
@@ -86,7 +80,8 @@ void define_ClusterFinderCUDA(py::module &m, const std::string &typestr) {
.def(
"find_clusters_batched",
[](CF &self, py::array_t<uint16_t> frames, uint64_t first_frame) {
// frames is expected as a 3D numpy array (n_frames, nrows, ncols)
// frames is expected as a 3D numpy array (n_frames, nrows,
// ncols)
auto view = make_view_3d(frames);
return self.find_clusters_batched(view, first_frame);
},