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Dev/rosenblatttransform (#241)
- added rosenblatttransform - added 3x3 eta methods - interpolation can be used with various eta functions - added documentation for interpolation, eta calculation - exposed full eta struct in python - disable ClusterFinder for 2x2 clusters - factory function for ClusterVector --------- Co-authored-by: Dhanya Thattil <dhanya.thattil@psi.ch> Co-authored-by: Erik Fröjdh <erik.frojdh@psi.ch>
This commit is contained in:
@@ -19,37 +19,124 @@ enum class pixel : int {
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pTopRight = 8
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};
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// TODO: better to have sum after x,y
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/**
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* eta struct
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*/
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template <typename T> struct Eta2 {
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double x;
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double y;
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/// @brief eta in x direction
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double x{};
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/// @brief eta in y direction
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double y{};
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/// @brief index of subcluster given as corner relative to cluster center
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corner c{0};
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T sum;
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/// @brief photon energy (cluster sum)
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T sum{};
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};
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/**
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* @brief Calculate the eta2 values for all clusters in a Clustervector
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* @brief Calculate the eta2 values for all clusters in a ClusterVector
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*/
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template <typename ClusterType,
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typename = std::enable_if_t<is_cluster_v<ClusterType>>>
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NDArray<double, 2> calculate_eta2(const ClusterVector<ClusterType> &clusters) {
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NDArray<double, 2> eta2({static_cast<int64_t>(clusters.size()), 2});
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std::vector<Eta2<typename ClusterType::value_type>>
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calculate_eta2(const ClusterVector<ClusterType> &clusters) {
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std::vector<Eta2<typename ClusterType::value_type>> eta2{};
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eta2.reserve(clusters.size());
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for (size_t i = 0; i < clusters.size(); i++) {
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auto e = calculate_eta2(clusters[i]);
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eta2(i, 0) = e.x;
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eta2(i, 1) = e.y;
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eta2.push_back(e);
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}
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return eta2;
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}
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/**
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* @brief Calculate the full eta2 values for all clusters in a ClusterVector
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*/
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template <typename ClusterType,
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typename = std::enable_if_t<is_cluster_v<ClusterType>>>
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std::vector<Eta2<typename ClusterType::value_type>>
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calculate_full_eta2(const ClusterVector<ClusterType> &clusters) {
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std::vector<Eta2<typename ClusterType::value_type>> eta2{};
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eta2.reserve(clusters.size());
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for (size_t i = 0; i < clusters.size(); i++) {
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auto e = calculate_full_eta2(clusters[i]);
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eta2.push_back(e);
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}
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return eta2;
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}
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/**
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* @brief Calculate eta3 for all 3x3 clusters in a ClusterVector
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*/
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template <typename ClusterType,
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typename = std::enable_if_t<is_cluster_v<ClusterType>>>
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std::vector<Eta2<typename ClusterType::value_type>>
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calculate_eta3(const ClusterVector<ClusterType> &clusters) {
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std::vector<Eta2<typename ClusterType::value_type>> eta2{};
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eta2.reserve(clusters.size());
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for (size_t i = 0; i < clusters.size(); i++) {
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auto e = calculate_eta3(clusters[i]);
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eta2.push_back(e);
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}
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return eta2;
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}
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/**
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* @brief Calculate cross eta3 for all 3x3 clusters in a ClusterVector
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*/
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template <typename ClusterType,
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typename = std::enable_if_t<is_cluster_v<ClusterType>>>
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std::vector<Eta2<typename ClusterType::value_type>>
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calculate_cross_eta3(const ClusterVector<ClusterType> &clusters) {
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std::vector<Eta2<typename ClusterType::value_type>> eta2{};
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eta2.reserve(clusters.size());
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for (size_t i = 0; i < clusters.size(); i++) {
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auto e = calculate_cross_eta3(clusters[i]);
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eta2.push_back(e);
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}
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return eta2;
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}
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/**
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* @brief helper function to calculate eta2 x and y values
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* @param eta reference to the Eta2 object to update
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* @param left_x value of the left pixel
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* @param right_x value of the right pixel
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* @param bottom_y value of the bottom pixel
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* @param top_y value of the top pixel
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*/
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template <typename T>
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inline void calculate_eta2(Eta2<T> &eta, const T left_x, const T right_x,
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const T bottom_y, const T top_y) {
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if ((right_x + left_x) != 0)
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eta.x = static_cast<double>(right_x) /
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static_cast<double>(right_x + left_x); // between (0,1) the
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// closer to zero left
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// value probably larger
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if ((top_y + bottom_y) != 0)
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eta.y = static_cast<double>(top_y) /
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static_cast<double>(top_y + bottom_y); // between (0,1) the
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// closer to zero bottom
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// value probably larger
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}
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/**
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* @brief Calculate the eta2 values for a generic sized cluster and return them
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* in a Eta2 struct containing etay, etax and the index of the respective 2x2
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* subcluster.
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* in a Eta2 struct containing etay, etax and the index (as corner) of the
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* respective 2x2 subcluster relative to the cluster center.
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*/
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template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
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typename CoordType>
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typename CoordType = uint16_t>
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Eta2<T>
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calculate_eta2(const Cluster<T, ClusterSizeX, ClusterSizeY, CoordType> &cl) {
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@@ -66,67 +153,36 @@ calculate_eta2(const Cluster<T, ClusterSizeX, ClusterSizeY, CoordType> &cl) {
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// subcluster top right from center
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switch (c) {
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case (corner::cTopLeft):
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if ((cl.data[cluster_center_index - 1] +
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cl.data[cluster_center_index]) != 0)
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eta.x = static_cast<double>(cl.data[cluster_center_index - 1]) /
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static_cast<double>(cl.data[cluster_center_index - 1] +
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cl.data[cluster_center_index]);
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if ((cl.data[cluster_center_index - ClusterSizeX] +
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cl.data[cluster_center_index]) != 0)
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eta.y = static_cast<double>(
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cl.data[cluster_center_index - ClusterSizeX]) /
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static_cast<double>(
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cl.data[cluster_center_index - ClusterSizeX] +
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cl.data[cluster_center_index]);
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// dx = 0
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// dy = 0
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calculate_eta2(eta, cl.data[cluster_center_index - 1],
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cl.data[cluster_center_index],
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cl.data[cluster_center_index - ClusterSizeX],
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cl.data[cluster_center_index]);
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// dx = -1
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// dy = -1
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break;
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case (corner::cTopRight):
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if (cl.data[cluster_center_index] + cl.data[cluster_center_index + 1] !=
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0)
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eta.x = static_cast<double>(cl.data[cluster_center_index]) /
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static_cast<double>(cl.data[cluster_center_index] +
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cl.data[cluster_center_index + 1]);
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if ((cl.data[cluster_center_index - ClusterSizeX] +
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cl.data[cluster_center_index]) != 0)
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eta.y = static_cast<double>(
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cl.data[cluster_center_index - ClusterSizeX]) /
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static_cast<double>(
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cl.data[cluster_center_index - ClusterSizeX] +
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cl.data[cluster_center_index]);
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// dx = 1
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// dy = 0
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calculate_eta2(eta, cl.data[cluster_center_index],
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cl.data[cluster_center_index + 1],
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cl.data[cluster_center_index - ClusterSizeX],
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cl.data[cluster_center_index]);
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// dx = 0
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// dy = -1
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break;
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case (corner::cBottomLeft):
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if ((cl.data[cluster_center_index - 1] +
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cl.data[cluster_center_index]) != 0)
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eta.x = static_cast<double>(cl.data[cluster_center_index - 1]) /
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static_cast<double>(cl.data[cluster_center_index - 1] +
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cl.data[cluster_center_index]);
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if ((cl.data[cluster_center_index] +
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cl.data[cluster_center_index + ClusterSizeX]) != 0)
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eta.y = static_cast<double>(cl.data[cluster_center_index]) /
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static_cast<double>(
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cl.data[cluster_center_index] +
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cl.data[cluster_center_index + ClusterSizeX]);
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// dx = 0
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// dy = 1
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calculate_eta2(eta, cl.data[cluster_center_index - 1],
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cl.data[cluster_center_index],
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cl.data[cluster_center_index],
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cl.data[cluster_center_index + ClusterSizeX]);
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// dx = -1
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// dy = 0
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break;
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case (corner::cBottomRight):
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if (cl.data[cluster_center_index] + cl.data[cluster_center_index + 1] !=
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0)
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eta.x = static_cast<double>(cl.data[cluster_center_index]) /
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static_cast<double>(cl.data[cluster_center_index] +
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cl.data[cluster_center_index + 1]);
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if ((cl.data[cluster_center_index] +
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cl.data[cluster_center_index + ClusterSizeX]) != 0)
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eta.y = static_cast<double>(cl.data[cluster_center_index]) /
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static_cast<double>(
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cl.data[cluster_center_index] +
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cl.data[cluster_center_index + ClusterSizeX]);
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// dx = 1
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// dy = 1
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calculate_eta2(eta, cl.data[cluster_center_index],
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cl.data[cluster_center_index + 1],
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cl.data[cluster_center_index],
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cl.data[cluster_center_index + ClusterSizeX]);
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// dx = 0
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// dy = 0
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break;
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}
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@@ -135,69 +191,255 @@ calculate_eta2(const Cluster<T, ClusterSizeX, ClusterSizeY, CoordType> &cl) {
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return eta;
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}
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// TODO! Look up eta2 calculation - photon center should be bottom right corner
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template <typename T>
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Eta2<T> calculate_eta2(const Cluster<T, 2, 2, int16_t> &cl) {
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/**
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* @brief Calculate the eta2 values for a generic sized cluster and return them
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* in a Eta2 struct containing etay, etax and the index (as corner) of the
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* respective 2x2 subcluster relative to the cluster center.
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*/
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template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
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typename CoordType>
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Eta2<T> calculate_full_eta2(
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const Cluster<T, ClusterSizeX, ClusterSizeY, CoordType> &cl) {
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static_assert(ClusterSizeX > 1 && ClusterSizeY > 1);
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Eta2<T> eta{};
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if ((cl.data[0] + cl.data[1]) != 0)
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eta.x = static_cast<double>(cl.data[2]) /
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(cl.data[2] + cl.data[3]); // between (0,1) the closer to zero
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// left value probably larger
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if ((cl.data[0] + cl.data[2]) != 0)
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eta.y = static_cast<double>(cl.data[1]) /
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(cl.data[1] + cl.data[3]); // between (0,1) the closer to zero
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// bottom value probably larger
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constexpr size_t cluster_center_index =
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(ClusterSizeX / 2) + (ClusterSizeY / 2) * ClusterSizeX;
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auto max_sum = cl.max_sum_2x2();
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eta.sum = max_sum.sum;
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corner c = max_sum.index;
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// subcluster top right from center
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switch (c) {
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case (corner::cTopLeft):
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if (eta.sum != 0) {
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eta.x = static_cast<double>(
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cl.data[cluster_center_index] +
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cl.data[cluster_center_index - ClusterSizeX]) /
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static_cast<double>(eta.sum);
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eta.y = static_cast<double>(cl.data[cluster_center_index - 1] +
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cl.data[cluster_center_index]) /
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static_cast<double>(eta.sum);
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}
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// dx = -1
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// dy = -1
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break;
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case (corner::cTopRight):
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if (eta.sum != 0) {
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eta.x = static_cast<double>(
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cl.data[cluster_center_index + 1] +
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cl.data[cluster_center_index - ClusterSizeX + 1]) /
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static_cast<double>(eta.sum);
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eta.y = static_cast<double>(cl.data[cluster_center_index] +
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cl.data[cluster_center_index + 1]) /
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static_cast<double>(eta.sum);
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}
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// dx = 0
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// dy = -1
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break;
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case (corner::cBottomLeft):
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if (eta.sum != 0) {
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eta.x = static_cast<double>(
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cl.data[cluster_center_index] +
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cl.data[cluster_center_index + ClusterSizeX]) /
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static_cast<double>(eta.sum);
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eta.y = static_cast<double>(
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cl.data[cluster_center_index + ClusterSizeX] +
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cl.data[cluster_center_index + ClusterSizeX - 1]) /
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static_cast<double>(eta.sum);
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}
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// dx = -1
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// dy = 0
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break;
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case (corner::cBottomRight):
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if (eta.sum != 0) {
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eta.x = static_cast<double>(
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cl.data[cluster_center_index + 1] +
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cl.data[cluster_center_index + ClusterSizeX + 1]) /
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static_cast<double>(eta.sum);
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eta.y = static_cast<double>(
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cl.data[cluster_center_index + ClusterSizeX] +
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cl.data[cluster_center_index + ClusterSizeX + 1]) /
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static_cast<double>(eta.sum);
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}
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// dx = 0
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// dy = 0
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break;
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}
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eta.c = c;
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return eta;
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}
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template <typename T>
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Eta2<T> calculate_eta2(const Cluster<T, 2, 2, uint16_t> &cl) {
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Eta2<T> eta{};
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// TODO: maybe have as member function of cluster
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const uint8_t photon_hit_index =
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std::max_element(cl.data.begin(), cl.data.end()) - cl.data.begin();
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eta.c = static_cast<corner>(3 - photon_hit_index);
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switch (eta.c) {
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case corner::cTopLeft:
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calculate_eta2(eta, cl.data[2], cl.data[3], cl.data[1], cl.data[3]);
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break;
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case corner::cTopRight:
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calculate_eta2(eta, cl.data[2], cl.data[3], cl.data[0], cl.data[2]);
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break;
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case corner::cBottomLeft:
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calculate_eta2(eta, cl.data[0], cl.data[1], cl.data[1], cl.data[3]);
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break;
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case corner::cBottomRight:
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calculate_eta2(eta, cl.data[0], cl.data[1], cl.data[0], cl.data[2]);
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break;
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}
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eta.sum = cl.sum();
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return eta;
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}
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template <typename T>
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Eta2<T> calculate_full_eta2(const Cluster<T, 2, 2, uint16_t> &cl) {
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Eta2<T> eta{};
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eta.sum = cl.sum();
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const uint8_t photon_hit_index =
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std::max_element(cl.data.begin(), cl.data.end()) - cl.data.begin();
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eta.c = static_cast<corner>(3 - photon_hit_index);
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if (eta.sum != 0) {
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eta.x = static_cast<double>(cl.data[1] + cl.data[3]) /
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static_cast<double>(eta.sum);
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eta.y = static_cast<double>(cl.data[2] + cl.data[3]) /
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static_cast<double>(eta.sum);
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}
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return eta;
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}
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// TODO generalize
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template <typename T>
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Eta2<T> calculate_eta2(const Cluster<T, 1, 2, int16_t> &cl) {
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Eta2<T> calculate_eta2(const Cluster<T, 1, 2, uint16_t> &cl) {
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Eta2<T> eta{};
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eta.x = 0;
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eta.y = static_cast<double>(cl.data[0]) / cl.data[1];
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eta.y = static_cast<double>(cl.data[1]) / cl.data[0];
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eta.sum = cl.sum();
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}
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template <typename T>
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Eta2<T> calculate_eta2(const Cluster<T, 2, 1, int16_t> &cl) {
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Eta2<T> calculate_eta2(const Cluster<T, 2, 1, uint16_t> &cl) {
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Eta2<T> eta{};
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eta.x = static_cast<double>(cl.data[0]) / cl.data[1];
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eta.x = static_cast<double>(cl.data[1]) / cl.data[0];
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eta.y = 0;
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eta.sum = cl.sum();
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}
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// calculates Eta3 for 3x3 cluster based on code from analyze_cluster
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// TODO only supported for 3x3 Clusters
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template <typename T> Eta2<T> calculate_eta3(const Cluster<T, 3, 3> &cl) {
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/**
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* @brief calculates cross Eta3 for 3x3 cluster
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* cross Eta3 calculates the eta by taking into account only the cross pixels
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* {top, bottom, left, right, center}
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*/
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template <typename T, typename CoordType = uint16_t>
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Eta2<T> calculate_cross_eta3(const Cluster<T, 3, 3, CoordType> &cl) {
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Eta2<T> eta{};
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T sum = 0;
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T photon_energy = cl.sum();
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std::for_each(std::begin(cl.data), std::end(cl.data),
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[&sum](T x) { sum += x; });
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eta.sum = sum;
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eta.sum = photon_energy;
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if ((cl.data[3] + cl.data[4] + cl.data[5]) != 0)
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eta.x = static_cast<double>(-cl.data[3] + cl.data[3 + 2]) /
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eta.x =
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static_cast<double>(-cl.data[3] + cl.data[3 + 2]) /
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|
||||
(cl.data[3] + cl.data[4] + cl.data[5]); // (-1,1)
|
||||
static_cast<double>(cl.data[3] + cl.data[4] + cl.data[5]); // (-1,1)
|
||||
|
||||
if ((cl.data[1] + cl.data[4] + cl.data[7]) != 0)
|
||||
|
||||
eta.y = static_cast<double>(-cl.data[1] + cl.data[2 * 3 + 1]) /
|
||||
|
||||
(cl.data[1] + cl.data[4] + cl.data[7]);
|
||||
static_cast<double>(cl.data[1] + cl.data[4] + cl.data[7]);
|
||||
|
||||
return eta;
|
||||
}
|
||||
|
||||
template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
|
||||
typename CoordType = uint16_t>
|
||||
Eta2<T> calculate_cross_eta3(
|
||||
const Cluster<T, ClusterSizeX, ClusterSizeY, CoordType> &cl) {
|
||||
|
||||
static_assert(ClusterSizeX > 2 && ClusterSizeY > 2,
|
||||
"calculate_eta3 only defined for clusters larger than 2x2");
|
||||
|
||||
if constexpr (ClusterSizeX != 3 || ClusterSizeY != 3) {
|
||||
auto reduced_cluster = reduce_cluster_to_3x3(cl);
|
||||
return calculate_cross_eta3(reduced_cluster);
|
||||
} else {
|
||||
return calculate_cross_eta3(cl);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief calculates Eta3 for 3x3 cluster
|
||||
* It calculates the eta by taking into account all pixels in the 3x3 cluster
|
||||
*/
|
||||
template <typename T, typename CoordType = uint16_t>
|
||||
Eta2<T> calculate_eta3(const Cluster<T, 3, 3, CoordType> &cl) {
|
||||
|
||||
Eta2<T> eta{};
|
||||
|
||||
T photon_energy = cl.sum();
|
||||
|
||||
eta.sum = photon_energy;
|
||||
|
||||
// TODO: how do we handle potential arithmetic overflows? - T could be
|
||||
// uint16
|
||||
if (photon_energy != 0) {
|
||||
std::array<T, 2> column_sums{
|
||||
static_cast<T>(cl.data[0] + cl.data[3] + cl.data[6]),
|
||||
static_cast<T>(cl.data[2] + cl.data[5] + cl.data[8])};
|
||||
|
||||
eta.x = static_cast<double>(-column_sums[0] + column_sums[1]) /
|
||||
static_cast<double>(photon_energy);
|
||||
|
||||
std::array<T, 2> row_sums{
|
||||
static_cast<T>(cl.data[0] + cl.data[1] + cl.data[2]),
|
||||
static_cast<T>(cl.data[6] + cl.data[7] + cl.data[8])};
|
||||
|
||||
eta.y = static_cast<double>(-row_sums[0] + row_sums[1]) /
|
||||
static_cast<double>(photon_energy);
|
||||
}
|
||||
|
||||
return eta;
|
||||
}
|
||||
|
||||
template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
|
||||
typename CoordType = uint16_t>
|
||||
Eta2<T>
|
||||
calculate_eta3(const Cluster<T, ClusterSizeX, ClusterSizeY, CoordType> &cl) {
|
||||
|
||||
static_assert(ClusterSizeX > 2 && ClusterSizeY > 2,
|
||||
"calculate_eta3 only defined for clusters larger than 2x2");
|
||||
|
||||
if constexpr (ClusterSizeX != 3 || ClusterSizeY != 3) {
|
||||
auto reduced_cluster = reduce_cluster_to_3x3(cl);
|
||||
return calculate_eta3(reduced_cluster);
|
||||
} else {
|
||||
return calculate_eta3(cl);
|
||||
}
|
||||
}
|
||||
|
||||
} // namespace aare
|
||||
@@ -18,6 +18,10 @@
|
||||
namespace aare {
|
||||
|
||||
// requires clause c++20 maybe update
|
||||
|
||||
/**
|
||||
* @brief Cluster struct
|
||||
*/
|
||||
template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
|
||||
typename CoordType = uint16_t>
|
||||
struct Cluster {
|
||||
@@ -28,8 +32,11 @@ struct Cluster {
|
||||
static_assert(ClusterSizeX > 0 && ClusterSizeY > 0,
|
||||
"Cluster sizes must be bigger than zero");
|
||||
|
||||
/// @brief Cluster center x coordinate (in pixel coordinates)
|
||||
CoordType x;
|
||||
/// @brief Cluster center y coordinate (in pixel coordinates)
|
||||
CoordType y;
|
||||
/// @brief Cluster data stored in row-major order starting from top-left
|
||||
std::array<T, ClusterSizeX * ClusterSizeY> data;
|
||||
|
||||
static constexpr uint8_t cluster_size_x = ClusterSizeX;
|
||||
@@ -37,10 +44,12 @@ struct Cluster {
|
||||
using value_type = T;
|
||||
using coord_type = CoordType;
|
||||
|
||||
/**
|
||||
* @brief Sum of all elements in the cluster
|
||||
*/
|
||||
T sum() const { return std::accumulate(data.begin(), data.end(), T{}); }
|
||||
|
||||
// TODO: handle 1 dimensional clusters
|
||||
// TODO: change int to corner
|
||||
/**
|
||||
* @brief sum of 2x2 subcluster with highest energy
|
||||
* @return photon energy of subcluster, 2x2 subcluster index relative to
|
||||
@@ -111,66 +120,71 @@ struct Cluster {
|
||||
* highest sum.
|
||||
* @param c Cluster to reduce
|
||||
* @return reduced cluster
|
||||
* @note The cluster is filled using row major ordering starting at the top-left
|
||||
* (thus for a max subcluster in the top left cornern the photon hit is at
|
||||
* the fourth position)
|
||||
*/
|
||||
template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
|
||||
typename CoordType = int16_t>
|
||||
typename CoordType = uint16_t>
|
||||
Cluster<T, 2, 2, CoordType>
|
||||
reduce_to_2x2(const Cluster<T, ClusterSizeX, ClusterSizeY, CoordType> &c) {
|
||||
|
||||
static_assert(ClusterSizeX >= 2 && ClusterSizeY >= 2,
|
||||
"Cluster sizes must be at least 2x2 for reduction to 2x2");
|
||||
|
||||
// TODO maybe add sanity check and check that center is in max subcluster
|
||||
Cluster<T, 2, 2, CoordType> result;
|
||||
Cluster<T, 2, 2, CoordType> result{};
|
||||
|
||||
auto [sum, index] = c.max_sum_2x2();
|
||||
|
||||
int16_t cluster_center_index =
|
||||
constexpr int16_t cluster_center_index =
|
||||
(ClusterSizeX / 2) + (ClusterSizeY / 2) * ClusterSizeX;
|
||||
|
||||
int16_t index_bottom_left_max_2x2_subcluster =
|
||||
(int(static_cast<int>(index) / (ClusterSizeX - 1))) * ClusterSizeX +
|
||||
static_cast<int>(index) % (ClusterSizeX - 1);
|
||||
int16_t index_top_left_max_2x2_subcluster = cluster_center_index;
|
||||
switch (index) {
|
||||
case corner::cTopLeft:
|
||||
index_top_left_max_2x2_subcluster -= (ClusterSizeX + 1);
|
||||
break;
|
||||
case corner::cTopRight:
|
||||
index_top_left_max_2x2_subcluster -= ClusterSizeX;
|
||||
break;
|
||||
case corner::cBottomLeft:
|
||||
index_top_left_max_2x2_subcluster -= 1;
|
||||
break;
|
||||
case corner::cBottomRight:
|
||||
// no change needed
|
||||
break;
|
||||
}
|
||||
|
||||
result.x =
|
||||
c.x + (index_bottom_left_max_2x2_subcluster - cluster_center_index) %
|
||||
ClusterSizeX;
|
||||
result.x = c.x;
|
||||
result.y = c.y;
|
||||
|
||||
result.y =
|
||||
c.y - (index_bottom_left_max_2x2_subcluster - cluster_center_index) /
|
||||
ClusterSizeX;
|
||||
result.data = {
|
||||
c.data[index_bottom_left_max_2x2_subcluster],
|
||||
c.data[index_bottom_left_max_2x2_subcluster + 1],
|
||||
c.data[index_bottom_left_max_2x2_subcluster + ClusterSizeX],
|
||||
c.data[index_bottom_left_max_2x2_subcluster + ClusterSizeX + 1]};
|
||||
c.data[index_top_left_max_2x2_subcluster],
|
||||
c.data[index_top_left_max_2x2_subcluster + 1],
|
||||
c.data[index_top_left_max_2x2_subcluster + ClusterSizeX],
|
||||
c.data[index_top_left_max_2x2_subcluster + ClusterSizeX + 1]};
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
template <typename T>
|
||||
Cluster<T, 2, 2, int16_t> reduce_to_2x2(const Cluster<T, 3, 3, int16_t> &c) {
|
||||
Cluster<T, 2, 2, int16_t> result;
|
||||
Cluster<T, 2, 2, uint16_t> reduce_to_2x2(const Cluster<T, 3, 3, uint16_t> &c) {
|
||||
Cluster<T, 2, 2, uint16_t> result{};
|
||||
|
||||
auto [s, i] = c.max_sum_2x2();
|
||||
result.x = c.x;
|
||||
result.y = c.y;
|
||||
switch (i) {
|
||||
case corner::cTopLeft:
|
||||
result.x = c.x - 1;
|
||||
result.y = c.y + 1;
|
||||
result.data = {c.data[0], c.data[1], c.data[3], c.data[4]};
|
||||
break;
|
||||
case corner::cTopRight:
|
||||
result.x = c.x;
|
||||
result.y = c.y + 1;
|
||||
result.data = {c.data[1], c.data[2], c.data[4], c.data[5]};
|
||||
break;
|
||||
case corner::cBottomLeft:
|
||||
result.x = c.x - 1;
|
||||
result.y = c.y;
|
||||
result.data = {c.data[3], c.data[4], c.data[6], c.data[7]};
|
||||
break;
|
||||
case corner::cBottomRight:
|
||||
result.x = c.x;
|
||||
result.y = c.y;
|
||||
result.data = {c.data[4], c.data[5], c.data[7], c.data[8]};
|
||||
break;
|
||||
}
|
||||
@@ -178,43 +192,8 @@ Cluster<T, 2, 2, int16_t> reduce_to_2x2(const Cluster<T, 3, 3, int16_t> &c) {
|
||||
return result;
|
||||
}
|
||||
|
||||
template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
|
||||
typename CoordType = int16_t>
|
||||
inline std::pair<T, uint16_t>
|
||||
max_3x3_sum(const Cluster<T, ClusterSizeX, ClusterSizeY, CoordType> &cluster) {
|
||||
|
||||
if constexpr (ClusterSizeX == 3 && ClusterSizeY == 3) {
|
||||
return std::make_pair(cluster.sum(), 0);
|
||||
} else {
|
||||
|
||||
size_t index = 0;
|
||||
T max_3x3_subcluster_sum = 0;
|
||||
for (size_t i = 0; i < ClusterSizeY - 2; ++i) {
|
||||
for (size_t j = 0; j < ClusterSizeX - 2; ++j) {
|
||||
|
||||
T sum = cluster.data[i * ClusterSizeX + j] +
|
||||
cluster.data[i * ClusterSizeX + j + 1] +
|
||||
cluster.data[i * ClusterSizeX + j + 2] +
|
||||
cluster.data[(i + 1) * ClusterSizeX + j] +
|
||||
cluster.data[(i + 1) * ClusterSizeX + j + 1] +
|
||||
cluster.data[(i + 1) * ClusterSizeX + j + 2] +
|
||||
cluster.data[(i + 2) * ClusterSizeX + j] +
|
||||
cluster.data[(i + 2) * ClusterSizeX + j + 1] +
|
||||
cluster.data[(i + 2) * ClusterSizeX + j + 2];
|
||||
if (sum > max_3x3_subcluster_sum) {
|
||||
max_3x3_subcluster_sum = sum;
|
||||
index = i * (ClusterSizeX - 2) + j;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return std::make_pair(max_3x3_subcluster_sum, index);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Reduce a cluster to a 3x3 cluster by selecting the 3x3 block with the
|
||||
* highest sum.
|
||||
* @brief Reduce a cluster to a 3x3 cluster
|
||||
* @param c Cluster to reduce
|
||||
* @return reduced cluster
|
||||
*/
|
||||
@@ -226,40 +205,24 @@ reduce_to_3x3(const Cluster<T, ClusterSizeX, ClusterSizeY, CoordType> &c) {
|
||||
static_assert(ClusterSizeX >= 3 && ClusterSizeY >= 3,
|
||||
"Cluster sizes must be at least 3x3 for reduction to 3x3");
|
||||
|
||||
Cluster<T, 3, 3, CoordType> result;
|
||||
|
||||
// TODO maybe add sanity check and check that center is in max subcluster
|
||||
|
||||
auto [sum, index] = max_3x3_sum(c);
|
||||
Cluster<T, 3, 3, CoordType> result{};
|
||||
|
||||
int16_t cluster_center_index =
|
||||
(ClusterSizeX / 2) + (ClusterSizeY / 2) * ClusterSizeX;
|
||||
|
||||
int16_t index_center_max_3x3_subcluster =
|
||||
(int(index / (ClusterSizeX - 2))) * ClusterSizeX + ClusterSizeX +
|
||||
index % (ClusterSizeX - 2) + 1;
|
||||
result.x = c.x;
|
||||
result.y = c.y;
|
||||
|
||||
int16_t index_3x3_subcluster_cluster_center =
|
||||
int((cluster_center_index - 1 - ClusterSizeX) / ClusterSizeX) *
|
||||
(ClusterSizeX - 2) +
|
||||
(cluster_center_index - 1 - ClusterSizeX) % ClusterSizeX;
|
||||
result.data = {c.data[cluster_center_index - ClusterSizeX - 1],
|
||||
c.data[cluster_center_index - ClusterSizeX],
|
||||
c.data[cluster_center_index - ClusterSizeX + 1],
|
||||
c.data[cluster_center_index - 1],
|
||||
c.data[cluster_center_index],
|
||||
c.data[cluster_center_index + 1],
|
||||
c.data[cluster_center_index + ClusterSizeX - 1],
|
||||
c.data[cluster_center_index + ClusterSizeX],
|
||||
c.data[cluster_center_index + ClusterSizeX + 1]};
|
||||
|
||||
result.x =
|
||||
c.x + (index % (ClusterSizeX - 2) -
|
||||
(index_3x3_subcluster_cluster_center % (ClusterSizeX - 2)));
|
||||
result.y =
|
||||
c.y - (index / (ClusterSizeX - 2) -
|
||||
(index_3x3_subcluster_cluster_center / (ClusterSizeX - 2)));
|
||||
|
||||
result.data = {c.data[index_center_max_3x3_subcluster - ClusterSizeX - 1],
|
||||
c.data[index_center_max_3x3_subcluster - ClusterSizeX],
|
||||
c.data[index_center_max_3x3_subcluster - ClusterSizeX + 1],
|
||||
c.data[index_center_max_3x3_subcluster - 1],
|
||||
c.data[index_center_max_3x3_subcluster],
|
||||
c.data[index_center_max_3x3_subcluster + 1],
|
||||
c.data[index_center_max_3x3_subcluster + ClusterSizeX - 1],
|
||||
c.data[index_center_max_3x3_subcluster + ClusterSizeX],
|
||||
c.data[index_center_max_3x3_subcluster + ClusterSizeX + 1]};
|
||||
return result;
|
||||
}
|
||||
|
||||
|
||||
@@ -10,7 +10,8 @@
|
||||
namespace aare {
|
||||
|
||||
template <typename ClusterType,
|
||||
typename = std::enable_if_t<is_cluster_v<ClusterType>>>
|
||||
typename = std::enable_if_t<is_cluster_v<ClusterType>>,
|
||||
typename = std::enable_if_t<no_2x2_cluster<ClusterType>::value>>
|
||||
class ClusterFileSink {
|
||||
ProducerConsumerQueue<ClusterVector<ClusterType>> *m_source;
|
||||
std::atomic<bool> m_stop_requested{false};
|
||||
|
||||
@@ -10,8 +10,16 @@
|
||||
|
||||
namespace aare {
|
||||
|
||||
template <typename ClusterType,
|
||||
typename = std::enable_if_t<is_cluster_v<ClusterType>>>
|
||||
struct no_2x2_cluster {
|
||||
constexpr static bool value =
|
||||
ClusterType::cluster_size_x > 2 && ClusterType::cluster_size_y > 2;
|
||||
};
|
||||
|
||||
template <typename ClusterType = Cluster<int32_t, 3, 3>,
|
||||
typename FRAME_TYPE = uint16_t, typename PEDESTAL_TYPE = double>
|
||||
typename FRAME_TYPE = uint16_t, typename PEDESTAL_TYPE = double,
|
||||
typename = std::enable_if_t<no_2x2_cluster<ClusterType>::value>>
|
||||
class ClusterFinder {
|
||||
Shape<2> m_image_size;
|
||||
const PEDESTAL_TYPE m_nSigma;
|
||||
|
||||
@@ -32,7 +32,8 @@ struct FrameWrapper {
|
||||
* @tparam CT type of the cluster data
|
||||
*/
|
||||
template <typename ClusterType = Cluster<int32_t, 3, 3>,
|
||||
typename FRAME_TYPE = uint16_t, typename PEDESTAL_TYPE = double>
|
||||
typename FRAME_TYPE = uint16_t, typename PEDESTAL_TYPE = double,
|
||||
typename = std::enable_if_t<no_2x2_cluster<ClusterType>::value>>
|
||||
class ClusterFinderMT {
|
||||
|
||||
protected:
|
||||
|
||||
@@ -28,7 +28,7 @@ class ClusterVector; // Forward declaration
|
||||
* needed.
|
||||
* @tparam T data type of the pixels in the cluster
|
||||
* @tparam CoordType data type of the x and y coordinates of the cluster
|
||||
* (normally int16_t)
|
||||
* (normally uint16_t)
|
||||
*/
|
||||
template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
|
||||
typename CoordType>
|
||||
@@ -176,9 +176,12 @@ class ClusterVector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>> {
|
||||
* highest sum.
|
||||
* @param cv Clustervector containing clusters to reduce
|
||||
* @return Clustervector with reduced clusters
|
||||
* @note The cluster is filled using row major ordering starting at the top-left
|
||||
* (thus for a max subcluster in the top left cornern the photon hit is at
|
||||
* the fourth position)
|
||||
*/
|
||||
template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
|
||||
typename CoordType = uint16_t>
|
||||
typename CoordType>
|
||||
ClusterVector<Cluster<T, 2, 2, CoordType>> reduce_to_2x2(
|
||||
const ClusterVector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>>
|
||||
&cv) {
|
||||
@@ -190,13 +193,12 @@ ClusterVector<Cluster<T, 2, 2, CoordType>> reduce_to_2x2(
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Reduce a cluster to a 3x3 cluster by selecting the 3x3 block with the
|
||||
* highest sum.
|
||||
* @brief Reduce a cluster to a 3x3 cluster
|
||||
* @param cv Clustervector containing clusters to reduce
|
||||
* @return Clustervector with reduced clusters
|
||||
*/
|
||||
template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
|
||||
typename CoordType = uint16_t>
|
||||
typename CoordType>
|
||||
ClusterVector<Cluster<T, 3, 3, CoordType>> reduce_to_3x3(
|
||||
const ClusterVector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>>
|
||||
&cv) {
|
||||
|
||||
@@ -17,7 +17,10 @@ struct Photon {
|
||||
};
|
||||
|
||||
class Interpolator {
|
||||
// marginal CDF of eta_x (if rosenblatt applied), conditional
|
||||
// CDF of eta_x conditioned on eta_y
|
||||
NDArray<double, 3> m_ietax;
|
||||
// conditional CDF of eta_y conditioned on eta_x
|
||||
NDArray<double, 3> m_ietay;
|
||||
|
||||
NDArray<double, 1> m_etabinsx;
|
||||
@@ -25,108 +28,210 @@ class Interpolator {
|
||||
NDArray<double, 1> m_energy_bins;
|
||||
|
||||
public:
|
||||
/**
|
||||
* @brief Constructor for the Interpolator class
|
||||
* @param etacube joint distribution of etaX, etaY and photon energy
|
||||
* @param xbins bin edges for etaX
|
||||
* @param ybins bin edges for etaY
|
||||
* @param ebins bin edges for photon energy
|
||||
* @note note first dimension is etaX, second etaY, third photon energy
|
||||
*/
|
||||
Interpolator(NDView<double, 3> etacube, NDView<double, 1> xbins,
|
||||
NDView<double, 1> ybins, NDView<double, 1> ebins);
|
||||
|
||||
/**
|
||||
* @brief Constructor for the Interpolator class
|
||||
* @param xbins bin edges for etaX
|
||||
* @param ybins bin edges for etaY
|
||||
* @param ebins bin edges for photon energy
|
||||
*/
|
||||
Interpolator(NDView<double, 1> xbins, NDView<double, 1> ybins,
|
||||
NDView<double, 1> ebins);
|
||||
|
||||
/**
|
||||
* @brief transforms the joint eta distribution of etaX and etaY to the two
|
||||
* independant uniform distributions based on the Roseblatt transform for
|
||||
* each energy level
|
||||
* @param etacube joint distribution of etaX, etaY and photon energy
|
||||
* @note note first dimension is etaX, second etaY, third photon energy
|
||||
*/
|
||||
void rosenblatttransform(NDView<double, 3> etacube);
|
||||
|
||||
NDArray<double, 3> get_ietax() { return m_ietax; }
|
||||
NDArray<double, 3> get_ietay() { return m_ietay; }
|
||||
|
||||
template <typename ClusterType,
|
||||
/**
|
||||
* @brief interpolates the cluster centers for all clusters to a better
|
||||
* precision
|
||||
* @tparam ClusterType Type of Clusters to interpolate
|
||||
* @tparam Etafunction Function object that calculates desired eta default:
|
||||
* calculate_eta2
|
||||
* @return interpolated photons (photon positions are given as double but
|
||||
* following row column format e.g. x=0, y=0 means top row and first column
|
||||
* of frame)
|
||||
*/
|
||||
template <auto EtaFunction = calculate_eta2, typename ClusterType,
|
||||
typename Eanble = std::enable_if_t<is_cluster_v<ClusterType>>>
|
||||
std::vector<Photon> interpolate(const ClusterVector<ClusterType> &clusters);
|
||||
|
||||
private:
|
||||
/**
|
||||
* @brief implements underlying interpolation logic based on EtaFunction
|
||||
* Type
|
||||
* @tparam EtaFunction Function object that calculates desired eta default:
|
||||
* @param u: transformed photon position in x between [0,1]
|
||||
* @param v: transformed photon position in y between [0,1]
|
||||
* @param c: corner of eta
|
||||
*/
|
||||
template <auto EtaFunction, typename ClusterType>
|
||||
void interpolation_logic(Photon &photon, const double u, const double v,
|
||||
const corner c = corner::cTopLeft);
|
||||
|
||||
/**
|
||||
* @brief bilinear interpolation of the transformed eta values
|
||||
* @param ix index of etaX bin
|
||||
* @param iy index of etaY bin
|
||||
* @param ie index of energy bin
|
||||
* @return pair of interpolated transformed eta values (ietax, ietay)
|
||||
*/
|
||||
template <typename T>
|
||||
std::pair<double, double>
|
||||
bilinear_interpolation(const size_t ix, const size_t iy, const size_t ie,
|
||||
const Eta2<T> &eta);
|
||||
};
|
||||
|
||||
// TODO: generalize to support any clustertype!!! otherwise add std::enable_if_t
|
||||
// to only take Cluster2x2 and Cluster3x3
|
||||
template <typename ClusterType, typename Enable>
|
||||
template <typename T>
|
||||
std::pair<double, double>
|
||||
Interpolator::bilinear_interpolation(const size_t ix, const size_t iy,
|
||||
const size_t ie, const Eta2<T> &eta) {
|
||||
auto next_index_y = static_cast<ssize_t>(iy + 1) >= m_ietax.shape(1)
|
||||
? m_ietax.shape(1) - 1
|
||||
: iy + 1;
|
||||
auto next_index_x = static_cast<ssize_t>(ix + 1) >= m_ietax.shape(0)
|
||||
? m_ietax.shape(0) - 1
|
||||
: ix + 1;
|
||||
|
||||
// bilinear interpolation
|
||||
double ietax_interp_left = linear_interpolation(
|
||||
{m_etabinsy(iy), m_etabinsy(iy + 1)},
|
||||
{m_ietax(ix, iy, ie), m_ietax(ix, next_index_y, ie)}, eta.y);
|
||||
double ietax_interp_right =
|
||||
linear_interpolation({m_etabinsy(iy), m_etabinsy(iy + 1)},
|
||||
{m_ietax(next_index_x, iy, ie),
|
||||
m_ietax(next_index_x, next_index_y, ie)},
|
||||
eta.y);
|
||||
|
||||
// transformed photon position x between [0,1]
|
||||
double ietax_interpolated =
|
||||
linear_interpolation({m_etabinsx(ix), m_etabinsx(ix + 1)},
|
||||
{ietax_interp_left, ietax_interp_right}, eta.x);
|
||||
|
||||
double ietay_interp_left = linear_interpolation(
|
||||
{m_etabinsx(ix), m_etabinsx(ix + 1)},
|
||||
{m_ietay(ix, iy, ie), m_ietay(next_index_x, iy, ie)}, eta.x);
|
||||
double ietay_interp_right =
|
||||
linear_interpolation({m_etabinsx(ix), m_etabinsx(ix + 1)},
|
||||
{m_ietay(ix, next_index_y, ie),
|
||||
m_ietay(next_index_x, next_index_y, ie)},
|
||||
eta.x);
|
||||
|
||||
// transformed photon position y between [0,1]
|
||||
double ietay_interpolated =
|
||||
linear_interpolation({m_etabinsy(iy), m_etabinsy(iy + 1)},
|
||||
{ietay_interp_left, ietay_interp_right}, eta.y);
|
||||
|
||||
return {ietax_interpolated, ietay_interpolated};
|
||||
}
|
||||
|
||||
template <auto EtaFunction, typename ClusterType, typename Enable>
|
||||
std::vector<Photon>
|
||||
Interpolator::interpolate(const ClusterVector<ClusterType> &clusters) {
|
||||
std::vector<Photon> photons;
|
||||
photons.reserve(clusters.size());
|
||||
|
||||
if (clusters.cluster_size_x() == 3 || clusters.cluster_size_y() == 3) {
|
||||
for (const ClusterType &cluster : clusters) {
|
||||
for (const ClusterType &cluster : clusters) {
|
||||
|
||||
auto eta = calculate_eta2(cluster);
|
||||
auto eta = EtaFunction(cluster);
|
||||
|
||||
Photon photon;
|
||||
photon.x = cluster.x;
|
||||
photon.y = cluster.y;
|
||||
photon.energy = static_cast<decltype(photon.energy)>(eta.sum);
|
||||
Photon photon;
|
||||
photon.x = cluster.x;
|
||||
photon.y = cluster.y;
|
||||
photon.energy = static_cast<decltype(photon.energy)>(eta.sum);
|
||||
|
||||
// auto ie = nearest_index(m_energy_bins, photon.energy)-1;
|
||||
// auto ix = nearest_index(m_etabinsx, eta.x)-1;
|
||||
// auto iy = nearest_index(m_etabinsy, eta.y)-1;
|
||||
// Finding the index of the last element that is smaller
|
||||
// should work fine as long as we have many bins
|
||||
auto ie = last_smaller(m_energy_bins, photon.energy);
|
||||
auto ix = last_smaller(m_etabinsx, eta.x);
|
||||
auto iy = last_smaller(m_etabinsy, eta.y);
|
||||
// std::cout << "eta.x: " << eta.x << " eta.y: " << eta.y << std::endl;
|
||||
|
||||
// fmt::print("ex: {}, ix: {}, iy: {}\n", ie, ix, iy);
|
||||
// Finding the index of the last element that is smaller
|
||||
// should work fine as long as we have many bins
|
||||
auto ie = last_smaller(m_energy_bins, photon.energy);
|
||||
auto ix = last_smaller(m_etabinsx, eta.x);
|
||||
auto iy = last_smaller(m_etabinsy, eta.y);
|
||||
|
||||
double dX, dY;
|
||||
// cBottomLeft = 0,
|
||||
// cBottomRight = 1,
|
||||
// cTopLeft = 2,
|
||||
// cTopRight = 3
|
||||
// TODO: could also chaneg the sign of the eta calculation
|
||||
switch (static_cast<corner>(eta.c)) {
|
||||
case corner::cTopLeft:
|
||||
dX = 0.0;
|
||||
dY = 0.0;
|
||||
break;
|
||||
case corner::cTopRight:;
|
||||
dX = 1.0;
|
||||
dY = 0.0;
|
||||
break;
|
||||
case corner::cBottomLeft:
|
||||
dX = 0.0;
|
||||
dY = 1.0;
|
||||
break;
|
||||
case corner::cBottomRight:
|
||||
dX = 1.0;
|
||||
dY = 1.0;
|
||||
break;
|
||||
}
|
||||
photon.x -= m_ietax(ix, iy, ie) - dX;
|
||||
photon.y -= m_ietay(ix, iy, ie) - dY;
|
||||
photons.push_back(photon);
|
||||
}
|
||||
} else if (clusters.cluster_size_x() == 2 ||
|
||||
clusters.cluster_size_y() == 2) {
|
||||
for (const ClusterType &cluster : clusters) {
|
||||
auto eta = calculate_eta2(cluster);
|
||||
// std::cout << "ix: " << ix << " iy: " << iy << std::endl;
|
||||
|
||||
Photon photon;
|
||||
photon.x = cluster.x;
|
||||
photon.y = cluster.y;
|
||||
photon.energy = static_cast<decltype(photon.energy)>(eta.sum);
|
||||
// TODO: bilinear interpolation only works if all bins have a size > 1 -
|
||||
// otherwise bilinear interpolation with zero values which skew the
|
||||
// results
|
||||
// TODO: maybe trim the bins at the edges with zero values beforehand
|
||||
// auto [ietax_interpolated, ietay_interpolated] =
|
||||
// bilinear_interpolation(ix, iy, ie, eta);
|
||||
|
||||
// Now do some actual interpolation.
|
||||
// Find which energy bin the cluster is in
|
||||
// auto ie = nearest_index(m_energy_bins, photon.energy)-1;
|
||||
// auto ix = nearest_index(m_etabinsx, eta.x)-1;
|
||||
// auto iy = nearest_index(m_etabinsy, eta.y)-1;
|
||||
// Finding the index of the last element that is smaller
|
||||
// should work fine as long as we have many bins
|
||||
auto ie = last_smaller(m_energy_bins, photon.energy);
|
||||
auto ix = last_smaller(m_etabinsx, eta.x);
|
||||
auto iy = last_smaller(m_etabinsy, eta.y);
|
||||
double ietax_interpolated = m_ietax(ix, iy, ie);
|
||||
double ietay_interpolated = m_ietay(ix, iy, ie);
|
||||
|
||||
// TODO: why 2?
|
||||
photon.x -=
|
||||
m_ietax(ix, iy, ie); // eta goes between 0 and 1 but we could
|
||||
// move the hit anywhere in the 2x2
|
||||
photon.y -= m_ietay(ix, iy, ie);
|
||||
photons.push_back(photon);
|
||||
}
|
||||
interpolation_logic<EtaFunction, ClusterType>(
|
||||
photon, ietax_interpolated, ietay_interpolated, eta.c);
|
||||
|
||||
} else {
|
||||
throw std::runtime_error(
|
||||
"Only 3x3 and 2x2 clusters are supported for interpolation");
|
||||
photons.push_back(photon);
|
||||
}
|
||||
|
||||
return photons;
|
||||
}
|
||||
|
||||
template <auto EtaFunction, typename ClusterType>
|
||||
void Interpolator::interpolation_logic(Photon &photon, const double u,
|
||||
const double v, const corner c) {
|
||||
|
||||
// std::cout << "u: " << u << " v: " << v << std::endl;
|
||||
|
||||
// TODO: try to call this with std::is_same_v and have it constexpr if
|
||||
// possible
|
||||
if (EtaFunction == &calculate_eta2<typename ClusterType::value_type,
|
||||
ClusterType::cluster_size_x,
|
||||
ClusterType::cluster_size_y,
|
||||
typename ClusterType::coord_type> ||
|
||||
EtaFunction == &calculate_full_eta2<typename ClusterType::value_type,
|
||||
ClusterType::cluster_size_x,
|
||||
ClusterType::cluster_size_y,
|
||||
typename ClusterType::coord_type>) {
|
||||
double dX{}, dY{};
|
||||
|
||||
// TODO: could also chaneg the sign of the eta calculation
|
||||
switch (c) {
|
||||
case corner::cTopLeft:
|
||||
dX = -1.0;
|
||||
dY = -1.0;
|
||||
break;
|
||||
case corner::cTopRight:;
|
||||
dX = 0.0;
|
||||
dY = -1.0;
|
||||
break;
|
||||
case corner::cBottomLeft:
|
||||
dX = -1.0;
|
||||
dY = 0.0;
|
||||
break;
|
||||
case corner::cBottomRight:
|
||||
dX = 0.0;
|
||||
dY = 0.0;
|
||||
break;
|
||||
}
|
||||
photon.x = photon.x + 0.5 + u + dX; // use pixel center + 0.5
|
||||
photon.y = photon.y + 0.5 + v +
|
||||
dY; // eta2 calculates the ratio between bottom and sum of
|
||||
// bottom and top shift by 1 add eta value correctly
|
||||
} else {
|
||||
photon.x += u;
|
||||
photon.y += v;
|
||||
}
|
||||
}
|
||||
|
||||
} // namespace aare
|
||||
@@ -109,4 +109,19 @@ template <typename Container> bool all_equal(const Container &c) {
|
||||
return false;
|
||||
}
|
||||
|
||||
/**
|
||||
* linear interpolation
|
||||
* @param bin_edge left and right bin edges
|
||||
* @param bin_values function values at bin edges
|
||||
* @param coord coordinate to interpolate at
|
||||
* @return interpolated value at coord
|
||||
*/
|
||||
inline double linear_interpolation(const std::pair<double, double> &bin_edge,
|
||||
const std::pair<double, double> &bin_values,
|
||||
const double coord) {
|
||||
const double bin_width = bin_edge.second - bin_edge.first;
|
||||
return bin_values.first * (1 - (coord - bin_edge.first) / bin_width) +
|
||||
bin_values.second * (coord - bin_edge.first) / bin_width;
|
||||
}
|
||||
|
||||
} // namespace aare
|
||||
Reference in New Issue
Block a user