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Separated cluster size for finding and saving. You now specfic the cluster size you want when search through a frame, but you can also now specify a cluster size to save afterwards. For example, you search for 3x3s but save 9x9s

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This commit is contained in:
mulvey_j
2025-08-13 11:46:24 +02:00
parent 12498dacaa
commit faaa831238
5 changed files with 36 additions and 24 deletions
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29
include/aare/ClusterFinder.hpp
View File

@@ -21,9 +21,11 @@ class ClusterFinder {
const PEDESTAL_TYPE c3;
ChunkedPedestal<PEDESTAL_TYPE> m_pedestal;
ClusterVector<ClusterType> m_clusters;
const uint32_t ClusterSizeX;
const uint32_t ClusterSizeY;
static const uint8_t ClusterSizeX = ClusterType::cluster_size_x;
static const uint8_t ClusterSizeY = ClusterType::cluster_size_y;
static const uint8_t SavedClusterSizeX = ClusterType::cluster_size_x;
static const uint8_t SavedClusterSizeY = ClusterType::cluster_size_y;
using CT = typename ClusterType::value_type;
public:
@@ -37,10 +39,12 @@ class ClusterFinder {
*/
ClusterFinder(Shape<2> image_size, PEDESTAL_TYPE nSigma = 5.0,
size_t capacity = 1000000,
uint32_t chunk_size = 50000, uint32_t n_chunks = 10)
uint32_t chunk_size = 50000, uint32_t n_chunks = 10,
uint32_t cluster_size_x = 3, uint32_t cluster_size_y = 3)
: m_image_size(image_size), m_nSigma(nSigma),
c2(sqrt((ClusterSizeY + 1) / 2 * (ClusterSizeX + 1) / 2)),
c3(sqrt(ClusterSizeX * ClusterSizeY)),
c2(sqrt((cluster_size_y + 1) / 2 * (cluster_size_x + 1) / 2)),
c3(sqrt(cluster_size_x * cluster_size_y)),
ClusterSizeX(cluster_size_x), ClusterSizeY(cluster_size_y),
m_pedestal(image_size[0], image_size[1], chunk_size, n_chunks), m_clusters(capacity) {
LOG(logDEBUG) << "ClusterFinder: "
<< "image_size: " << image_size[0] << "x" << image_size[1]
@@ -80,11 +84,13 @@ class ClusterFinder {
return tmp;
}
void find_clusters(NDView<FRAME_TYPE, 2> frame, uint64_t frame_number = 0) {
// // TODO! deal with even size clusters
// // currently 3,3 -> +/- 1
// // 4,4 -> +/- 2
int dy = ClusterSizeY / 2;
int dx = ClusterSizeX / 2;
int dy2 = SavedClusterSizeY / 2;
int dx2 = SavedClusterSizeX / 2;
int has_center_pixel_x =
ClusterSizeX %
2; // for even sized clusters there is no proper cluster center and
@@ -179,16 +185,19 @@ class ClusterFinder {
// It's worth redoing the look since most of the time we
// don't have a photon
int i = 0;
for (int ir = -dy; ir < dy + has_center_pixel_y; ir++) {
for (int ir = -dy2; ir < dy2 + has_center_pixel_y; ir++) {
size_t inner_row_offset = row_offset + (ir * frame.shape(1));
for (int ic = -dx; ic < dx + has_center_pixel_y; ic++) {
for (int ic = -dx2; ic < dx2 + has_center_pixel_y; ic++) {
if (ix + ic >= 0 && ix + ic < frame.shape(1) &&
iy + ir >= 0 && iy + ir < frame.shape(0)) {
// if (m_pedestal.std(iy + ir, ix + ic) == 0) continue;
if (std_ptr[inner_row_offset + ix + ic] == 0) continue;
// if (std_ptr[inner_row_offset + ix + ic] == 0) continue;
// CT tmp = static_cast<CT>(frame(iy + ir, ix + ic)) - static_cast<CT>(m_pedestal.mean(iy + ir, ix + ic));
CT tmp = static_cast<CT>(frame(iy + ir, ix + ic)) - static_cast<CT>(mean_ptr[inner_row_offset + ix + ic]);
CT tmp = 0;
if (std_ptr[inner_row_offset + ix + ic] != 0)
tmp = static_cast<CT>(frame(iy + ir, ix + ic)) - static_cast<CT>(mean_ptr[inner_row_offset + ix + ic]);
cluster.data[i] = tmp; // Watch for out of bounds access
i++;

5
include/aare/ClusterFinderMT.hpp
View File

@@ -129,7 +129,8 @@ class ClusterFinderMT {
*/
ClusterFinderMT(Shape<2> image_size, PEDESTAL_TYPE nSigma = 5.0,
size_t capacity = 2000, size_t n_threads = 3,
uint32_t chunk_size = 50000, uint32_t n_chunks = 10)
uint32_t chunk_size = 50000, uint32_t n_chunks = 10,
uint32_t cluster_size_x = 3, uint32_t cluster_size_y = 3)
: m_n_threads(n_threads) {
LOG(logDEBUG1) << "ClusterFinderMT: "
@@ -142,7 +143,7 @@ class ClusterFinderMT {
m_cluster_finders.push_back(
std::make_unique<
ClusterFinder<ClusterType, FRAME_TYPE, PEDESTAL_TYPE>>(
image_size, nSigma, capacity, chunk_size, n_chunks));
image_size, nSigma, capacity, chunk_size, n_chunks, cluster_size_x, cluster_size_y));
}
for (size_t i = 0; i < n_threads; i++) {
m_input_queues.emplace_back(std::make_unique<InputQueue>(200));

12
python/aare/ClusterFinder.py
View File

@@ -26,24 +26,24 @@ def _get_class(name, cluster_size, dtype):
def ClusterFinder(image_size, cluster_size, n_sigma=5, dtype = np.int32, capacity = 1024, chunk_size=50000, n_chunks = 10):
def ClusterFinder(image_size, saved_cluster_size, checked_cluster_size, n_sigma=5, dtype = np.int32, capacity = 1024, chunk_size=50000, n_chunks = 10):
"""
Factory function to create a ClusterFinder object. Provides a cleaner syntax for
the templated ClusterFinder in C++.
"""
cls = _get_class("ClusterFinder", cluster_size, dtype)
return cls(image_size, n_sigma=n_sigma, capacity=capacity, chunk_size=chunk_size, n_chunks=n_chunks)
cls = _get_class("ClusterFinder", saved_cluster_size, dtype)
return cls(image_size, n_sigma=n_sigma, capacity=capacity, chunk_size=chunk_size, n_chunks=n_chunks, cluster_size_x=checked_cluster_size[0], cluster_size_y=checked_cluster_size[1])
def ClusterFinderMT(image_size, cluster_size = (3,3), dtype=np.int32, n_sigma=5, capacity = 1024, n_threads = 3, chunk_size=50000, n_chunks = 10):
def ClusterFinderMT(image_size, saved_cluster_size = (3,3), checked_cluster_size = (3,3), dtype=np.int32, n_sigma=5, capacity = 1024, n_threads = 3, chunk_size=50000, n_chunks = 10):
"""
Factory function to create a ClusterFinderMT object. Provides a cleaner syntax for
the templated ClusterFinderMT in C++.
"""
cls = _get_class("ClusterFinderMT", cluster_size, dtype)
return cls(image_size, n_sigma=n_sigma, capacity=capacity, n_threads=n_threads, chunk_size=chunk_size, n_chunks=n_chunks)
cls = _get_class("ClusterFinderMT", saved_cluster_size, dtype)
return cls(image_size, n_sigma=n_sigma, capacity=capacity, n_threads=n_threads, chunk_size=chunk_size, n_chunks=n_chunks, cluster_size_x=checked_cluster_size[0], cluster_size_y=checked_cluster_size[1])

7
python/src/bind_ClusterFinder.hpp
View File

@@ -30,9 +30,10 @@ void define_ClusterFinder(py::module &m, const std::string &typestr) {
py::class_<ClusterFinder<ClusterType, uint16_t, pd_type>>(
m, class_name.c_str())
.def(py::init<Shape<2>, pd_type, size_t, uint32_t, uint32_t>(), py::arg("image_size"),
py::arg("n_sigma") = 5.0, py::arg("capacity") = 1'000'000,
py::arg("chunk_size") = 50'000, py::arg("n_chunks") = 10)
.def(py::init<Shape<2>, pd_type, size_t, uint32_t, uint32_t, uint32_t, uint32_t>(),
py::arg("image_size"), py::arg("n_sigma") = 5.0, py::arg("capacity") = 1'000'000,
py::arg("chunk_size") = 50'000, py::arg("n_chunks") = 10,
py::arg("cluster_size_x") = 3, py::arg("cluster_size_y") = 3)
.def("push_pedestal_frame",
[](ClusterFinder<ClusterType, uint16_t, pd_type> &self,
py::array_t<uint16_t> frame) {

5
python/src/bind_ClusterFinderMT.hpp
View File

@@ -30,10 +30,11 @@ void define_ClusterFinderMT(py::module &m, const std::string &typestr) {
py::class_<ClusterFinderMT<ClusterType, uint16_t, pd_type>>(
m, class_name.c_str())
.def(py::init<Shape<2>, pd_type, size_t, size_t, uint32_t, uint32_t>(),
.def(py::init<Shape<2>, pd_type, size_t, size_t, uint32_t, uint32_t, uint32_t, uint32_t>(),
py::arg("image_size"), py::arg("n_sigma") = 5.0,
py::arg("capacity") = 2048, py::arg("n_threads") = 3,
py::arg("chunk_size") = 50'000, py::arg("n_chunks") = 10)
py::arg("chunk_size") = 50'000, py::arg("n_chunks") = 10,
py::arg("cluster_size_x") = 3, py::arg("cluster_size_y") = 3)
.def("push_pedestal_frame",
[](ClusterFinderMT<ClusterType, uint16_t, pd_type> &self,
py::array_t<uint16_t> frame) {