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bumped version

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This commit is contained in:
froejdh_e 2025-01-07 16:33:16 +01:00
parent acdce8454b
commit 21ce7a3efa
4 changed files with 6 additions and 114 deletions
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2
conda-recipe/meta.yaml
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@ -1,6 +1,6 @@
package:
name: aare
version: 2024.12.16.dev0 #TODO! how to not duplicate this?
version: 2025.1.7.dev0 #TODO! how to not duplicate this?
source:

112
include/aare/ClusterFinder.hpp
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@ -121,8 +121,8 @@ class ClusterFinder {
} else if (total > c3 * m_nSigma * rms) {
// pass
} else {
// m_pedestal.push(iy, ix, frame(iy, ix));
m_pedestal.push_fast(iy, ix, frame(iy, ix));
// m_pedestal.push(iy, ix, frame(iy, ix)); // Safe option
m_pedestal.push_fast(iy, ix, frame(iy, ix)); // Assume we have reached n_samples in the pedestal, slight performance improvement
continue; // It was a pedestal value nothing to store
}
@ -157,114 +157,6 @@ class ClusterFinder {
}
}
}
// // template <typename FRAME_TYPE, typename PEDESTAL_TYPE>
// std::vector<DynamicCluster>
// find_clusters_with_threshold(NDView<FRAME_TYPE, 2> frame,
// Pedestal<PEDESTAL_TYPE> &pedestal) {
// assert(m_threshold > 0);
// std::vector<DynamicCluster> clusters;
// std::vector<std::vector<eventType>> eventMask;
// for (int i = 0; i < frame.shape(0); i++) {
// eventMask.push_back(std::vector<eventType>(frame.shape(1)));
// }
// double tthr, tthr1, tthr2;
// NDArray<FRAME_TYPE, 2> rest({frame.shape(0), frame.shape(1)});
// NDArray<int, 2> nph({frame.shape(0), frame.shape(1)});
// // convert to n photons
// // nph = (frame-pedestal.mean()+0.5*m_threshold)/m_threshold; // can
// be
// // optimized with expression templates?
// for (int iy = 0; iy < frame.shape(0); iy++) {
// for (int ix = 0; ix < frame.shape(1); ix++) {
// auto val = frame(iy, ix) - pedestal.mean(iy, ix);
// nph(iy, ix) = (val + 0.5 * m_threshold) / m_threshold;
// nph(iy, ix) = nph(iy, ix) < 0 ? 0 : nph(iy, ix);
// rest(iy, ix) = val - nph(iy, ix) * m_threshold;
// }
// }
// // iterate over frame pixels
// for (int iy = 0; iy < frame.shape(0); iy++) {
// for (int ix = 0; ix < frame.shape(1); ix++) {
// eventMask[iy][ix] = eventType::PEDESTAL;
// // initialize max and total
// FRAME_TYPE max = std::numeric_limits<FRAME_TYPE>::min();
// long double total = 0;
// if (rest(iy, ix) <= 0.25 * m_threshold) {
// pedestal.push(iy, ix, frame(iy, ix));
// continue;
// }
// eventMask[iy][ix] = eventType::NEIGHBOUR;
// // iterate over cluster pixels around the current pixel
// (ix,iy) for (short ir = -(m_cluster_sizeY / 2);
// ir < (m_cluster_sizeY / 2) + 1; ir++) {
// for (short ic = -(m_cluster_sizeX / 2);
// ic < (m_cluster_sizeX / 2) + 1; ic++) {
// if (ix + ic >= 0 && ix + ic < frame.shape(1) &&
// iy + ir >= 0 && iy + ir < frame.shape(0)) {
// auto val = frame(iy + ir, ix + ic) -
// pedestal.mean(iy + ir, ix + ic);
// total += val;
// if (val > max) {
// max = val;
// }
// }
// }
// }
// auto rms = pedestal.std(iy, ix);
// if (m_nSigma == 0) {
// tthr = m_threshold;
// tthr1 = m_threshold;
// tthr2 = m_threshold;
// } else {
// tthr = m_nSigma * rms;
// tthr1 = m_nSigma * rms * c3;
// tthr2 = m_nSigma * rms * c2;
// if (m_threshold > 2 * tthr)
// tthr = m_threshold - tthr;
// if (m_threshold > 2 * tthr1)
// tthr1 = tthr - tthr1;
// if (m_threshold > 2 * tthr2)
// tthr2 = tthr - tthr2;
// }
// if (total > tthr1 || max > tthr) {
// eventMask[iy][ix] = eventType::PHOTON;
// nph(iy, ix) += 1;
// rest(iy, ix) -= m_threshold;
// } else {
// pedestal.push(iy, ix, frame(iy, ix));
// continue;
// }
// if (eventMask[iy][ix] == eventType::PHOTON &&
// frame(iy, ix) - pedestal.mean(iy, ix) >= max) {
// eventMask[iy][ix] = eventType::PHOTON_MAX;
// DynamicCluster cluster(m_cluster_sizeX, m_cluster_sizeY,
// Dtype(typeid(FRAME_TYPE)));
// cluster.x = ix;
// cluster.y = iy;
// short i = 0;
// for (short ir = -(m_cluster_sizeY / 2);
// ir < (m_cluster_sizeY / 2) + 1; ir++) {
// for (short ic = -(m_cluster_sizeX / 2);
// ic < (m_cluster_sizeX / 2) + 1; ic++) {
// if (ix + ic >= 0 && ix + ic < frame.shape(1) &&
// iy + ir >= 0 && iy + ir < frame.shape(0)) {
// auto tmp = frame(iy + ir, ix + ic) -
// pedestal.mean(iy + ir, ix + ic);
// cluster.set<FRAME_TYPE>(i, tmp);
// i++;
// }
// }
// }
// clusters.push_back(cluster);
// }
// }
// }
// return clusters;
// }
};
} // namespace aare

4
include/aare/Pedestal.hpp
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@ -165,8 +165,8 @@ template <typename SUM_TYPE = double> class Pedestal {
m_sum2(row, col) += val * val;
m_cur_samples(row, col)++;
} else {
m_sum(row, col) += val - m_sum(row, col) / m_cur_samples(row, col);
m_sum2(row, col) += val * val - m_sum2(row, col) / m_cur_samples(row, col);
m_sum(row, col) += val - m_sum(row, col) / m_samples;
m_sum2(row, col) += val * val - m_sum2(row, col) / m_samples;
}
//Since we just did a push we know that m_cur_samples(row, col) is at least 1
m_mean(row, col) = m_sum(row, col) / m_cur_samples(row, col);

2
pyproject.toml
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@ -4,7 +4,7 @@ build-backend = "scikit_build_core.build"
[project]
name = "aare"
version = "2024.12.16.dev0"
version = "2025.1.7.dev0"
[tool.scikit-build]
cmake.verbose = true