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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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63
examples/cluster_finder_example.cpp Normal file
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#include "aare.hpp"
#include "aare/examples/defs.hpp"
#include <cassert>
#include <iostream>
using namespace aare;
int main() {
auto PROJECT_ROOT_DIR = std::filesystem::path(getenv("AARE_ROOT_DIR"));
std::filesystem::path const fpath_frame("/home/l_bechir/tmp/testNewFW20230714/cu_half_speed_master_4.json");
std::filesystem::path const fpath_cluster("/home/l_bechir/tmp/testNewFW20230714/clust/cu_half_speed_d0_f0_4.clust");
auto file = RawFile(fpath_frame, "r");
logger::info("RAW file");
logger::info("file rows:", file.rows(), "cols:", file.cols());
logger::info(file.total_frames());
Frame frame(0, 0, 0);
for (auto i = 0; i < 10000; i++) {
if (file.frame_number(i) == 23389) {
logger::info("frame_number:", file.frame_number(i));
frame = file.read();
}
}
logger::info("frame", frame.rows(), frame.cols(), frame.bitdepth());
ClusterFileV2 cf(fpath_cluster, "r");
auto anna_clusters = cf.read();
logger::info("Cluster file");
logger::info("nclusters:", anna_clusters.size());
logger::info("frame_number", anna_clusters[0].frame_number);
ClusterFinder clusterFinder(3, 3, 5, 0);
Pedestal p(file.rows(), file.cols());
file.seek(0);
logger::info("Starting Pedestal calculation");
for (auto i = 0; i < 1000; i++) {
p.push(file.read().view<uint16_t>());
}
logger::info("Pedestal calculation done");
logger::info("Pedestal mean:", p.mean(0, 0), "std:", p.standard_deviation(0, 0));
logger::info("Pedestal mean:", p.mean(200, 200), "std:", p.standard_deviation(200, 200));
FileConfig cfg;
cfg.dtype = DType(typeid(double));
cfg.rows = p.rows();
cfg.cols = p.cols();
NumpyFile np_pedestal("/home/l_bechir/tmp/testNewFW20230714/pedestal.npy", "w", cfg);
cfg.dtype = DType(typeid(uint16_t));
NumpyFile np_frame("/home/l_bechir/tmp/testNewFW20230714/frame.npy", "w", cfg);
np_pedestal.write(p.mean());
np_frame.write(frame.view<uint16_t>());
auto clusters = clusterFinder.find_clusters(frame.view<uint16_t>(), p);
logger::info("nclusters:", clusters.size());
// aare::logger::info("nclusters:", clusters.size());
// for (auto &cluster : clusters) {
// aare::logger::info("cluster center:", cluster.to_string<double>());
// }
}