detectors/aare
25
0
Fork 0
mirror of https://github.com/slsdetectorgroup/aare.git synced 2026-06-05 06:58:42 +02:00
Code Issues Actions Packages Releases Activity

Format CUDA cluster finder files
Build on RHEL8 / build (push) Successful in 3m13s
Details
Build on RHEL9 / build (push) Successful in 3m34s
Details
Run tests using data on local RHEL8 / build (push) Successful in 3m48s
Details

Browse Source
This commit is contained in:
kferjaoui
2026-04-27 11:27:47 +02:00
parent 133cedf755
commit a086cbb897
8 changed files with 508 additions and 440 deletions
Download Patch File Download Diff File Expand all files Collapse all files
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);
},
python/src/bind_ClusterVector.hpp
+1 -2
View File
@@ -30,8 +30,7 @@ void define_ClusterVector(py::module &m, const std::string &typestr) {
py::class_<ClusterVector<
Cluster<Type, ClusterSizeX, ClusterSizeY, CoordType>, void>>(
m, class_name.c_str(),
py::buffer_protocol(),
m, class_name.c_str(), py::buffer_protocol(),
py::module_local())
.def(py::init()) // TODO change!!!
python/src/cuda_bindings.cu
+19 -19
View File
@@ -6,8 +6,8 @@
// back a usable ClusterVector without _aare needing to be imported first.
#include "bind_Cluster.hpp"
#include "bind_ClusterVector.hpp"
#include "bind_ClusterFinderCUDA.hpp"
#include "bind_ClusterVector.hpp"
#include <pybind11/pybind11.h>
@@ -22,45 +22,45 @@ namespace py = pybind11;
define_Cluster<T, N, M, U>(m, #N "x" #M #TYPE_CODE);
#define DEFINE_BINDINGS_CLUSTERFINDER_CUDA(T, N, M, U, TYPE_CODE) \
aare::define_ClusterFinderCUDA<T, N, M, U>( \
m, "Cluster" #N "x" #M #TYPE_CODE);
aare::define_ClusterFinderCUDA<T, N, M, U>(m, "Cluster" #N \
"x" #M #TYPE_CODE);
PYBIND11_MODULE(_aare_cuda, m) {
// Types first — finders reference them in their signatures.
// SFINAE excludes 2x2 on ClusterFinderCUDA, so we skip it here too.
DEFINE_CUDA_CLUSTER_TYPES(int, 3, 3, uint16_t, i);
DEFINE_CUDA_CLUSTER_TYPES(int, 3, 3, uint16_t, i);
DEFINE_CUDA_CLUSTER_TYPES(double, 3, 3, uint16_t, d);
DEFINE_CUDA_CLUSTER_TYPES(float, 3, 3, uint16_t, f);
DEFINE_CUDA_CLUSTER_TYPES(float, 3, 3, uint16_t, f);
DEFINE_CUDA_CLUSTER_TYPES(int, 5, 5, uint16_t, i);
DEFINE_CUDA_CLUSTER_TYPES(int, 5, 5, uint16_t, i);
DEFINE_CUDA_CLUSTER_TYPES(double, 5, 5, uint16_t, d);
DEFINE_CUDA_CLUSTER_TYPES(float, 5, 5, uint16_t, f);
DEFINE_CUDA_CLUSTER_TYPES(float, 5, 5, uint16_t, f);
DEFINE_CUDA_CLUSTER_TYPES(int, 7, 7, uint16_t, i);
DEFINE_CUDA_CLUSTER_TYPES(int, 7, 7, uint16_t, i);
DEFINE_CUDA_CLUSTER_TYPES(double, 7, 7, uint16_t, d);
DEFINE_CUDA_CLUSTER_TYPES(float, 7, 7, uint16_t, f);
DEFINE_CUDA_CLUSTER_TYPES(float, 7, 7, uint16_t, f);
DEFINE_CUDA_CLUSTER_TYPES(int, 9, 9, uint16_t, i);
DEFINE_CUDA_CLUSTER_TYPES(int, 9, 9, uint16_t, i);
DEFINE_CUDA_CLUSTER_TYPES(double, 9, 9, uint16_t, d);
DEFINE_CUDA_CLUSTER_TYPES(float, 9, 9, uint16_t, f);
DEFINE_CUDA_CLUSTER_TYPES(float, 9, 9, uint16_t, f);
// Finders
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(int, 3, 3, uint16_t, i);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(int, 3, 3, uint16_t, i);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(double, 3, 3, uint16_t, d);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(float, 3, 3, uint16_t, f);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(float, 3, 3, uint16_t, f);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(int, 5, 5, uint16_t, i);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(int, 5, 5, uint16_t, i);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(double, 5, 5, uint16_t, d);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(float, 5, 5, uint16_t, f);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(float, 5, 5, uint16_t, f);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(int, 7, 7, uint16_t, i);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(int, 7, 7, uint16_t, i);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(double, 7, 7, uint16_t, d);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(float, 7, 7, uint16_t, f);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(float, 7, 7, uint16_t, f);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(int, 9, 9, uint16_t, i);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(int, 9, 9, uint16_t, i);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(double, 9, 9, uint16_t, d);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(float, 9, 9, uint16_t, f);
DEFINE_BINDINGS_CLUSTERFINDER_CUDA(float, 9, 9, uint16_t, f);
}
#undef DEFINE_CUDA_CLUSTER_TYPES