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cluster finder (#72)

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implement fixed size cluster finder algorithm 
clusterFile functions are commented and put on hold.

---------

Co-authored-by: Bechir <bechir.brahem420@gmail.com>
Co-authored-by: Erik Fröjdh <erik.frojdh@gmail.com>
This commit is contained in:
Bechir Braham
2024-06-17 10:57:23 +02:00
committed by GitHub
parent 1dd361a343
commit 5b7ab5a810
33 changed files with 845 additions and 111 deletions
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57
examples/cluster_example.cpp
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@ -7,48 +7,33 @@
using namespace aare;
int main() {
auto PROJECT_ROOT_DIR = std::filesystem::path(getenv("AARE_ROOT_DIR"));
std::filesystem::path const fpath(PROJECT_ROOT_DIR / "data" / "clusters" / "single_frame_97_clustrers.clust");
std::filesystem::path const fpath("/mnt/sls_det_storage/moench_data/testNewFW20230714/cu_half_speed_master_4.json");
// reading a file
aare::ClusterFile cf(fpath, "r");
std::cout << "file opened " << '\n';
std::cout << "n_clusters " << cf.count() << '\n';
std::cout << "frame_number " << cf.frame() << '\n';
std::cout << "file size: " << cf.count() << '\n';
cf.seek(0); // seek to the beginning of the file (this is the default behavior of the constructor)
NDArray<double, 2> frame({10, 10});
frame = 0;
auto cluster = cf.read(97);
std::cout << "read 10 clusters" << '\n';
int offset = 0;
int data_offset = 0;
for (auto c : cluster) {
assert(c.y == offset + 200);
for (int i = 0; i < 9; i++) {
assert(c.data[i] == data_offset + i);
for (int i = 5; i < 8; i++) {
for (int j = 5; j < 8; j++) {
frame(i, j) = (i + j) % 10;
}
offset++;
data_offset += 9;
}
// writing a file
std::filesystem::path const fpath_out("/tmp/cluster_example_file.clust");
aare::ClusterFile cf_out(fpath_out, "w", ClusterFileConfig(1, 44));
std::cout << "file opened for writing" << '\n';
std::vector<Cluster> clusters;
for (int i = 0; i < 1084; i++) {
Cluster c;
c.x = i;
c.y = i + 200;
for (int j = 0; j < 9; j++) {
c.data[j] = j;
for (int i = 0; i < frame.shape(0); i++) {
for (int j = 0; j < frame.shape(1); j++) {
std::cout << frame(i, j) << " ";
}
clusters.push_back(c);
std::cout << std::endl;
}
cf_out.write(clusters);
std::cout << "wrote 10 clusters" << '\n';
cf_out.update_header();
return 0;
ClusterFinder clusterFinder(3, 3, 1, 1); // 3x3 cluster, 1 nSigma, 1 threshold
Pedestal p(10, 10);
auto clusters = clusterFinder.find_clusters(frame.span(), p);
aare::logger::info("nclusters:", clusters.size());
for (auto &cluster : clusters) {
aare::logger::info("cluster center:", cluster.to_string<double>());
}
}