mirror of
https://github.com/slsdetectorgroup/aare.git
synced 2025-04-20 05:40:03 +02:00
complete mess but need to install RedHat 9
This commit is contained in:
parent
e59a361b51
commit
6e7e81b36b
@ -8,16 +8,12 @@
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namespace aare {
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//TODO! Template this?
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struct Cluster3x3 {
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int16_t x;
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int16_t y;
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int32_t data[9];
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};
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struct Cluster2x2 {
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int16_t x;
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int16_t y;
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int32_t data[4];
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template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
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typename CoordType = int16_t>
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struct Cluster {
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CoordType x;
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CoordType y;
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T data[ClusterSizeX * ClusterSizeY];
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};
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typedef enum {
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@ -93,8 +89,7 @@ class ClusterFile {
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*/
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ClusterFile(const std::filesystem::path &fname, size_t chunk_size = 1000,
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const std::string &mode = "r");
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~ClusterFile();
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/**
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@ -109,26 +104,26 @@ class ClusterFile {
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/**
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* @brief Read a single frame from the file and return the clusters. The
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* cluster vector will have the frame number set.
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* @throws std::runtime_error if the file is not opened for reading or the file pointer not
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* at the beginning of a frame
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* @throws std::runtime_error if the file is not opened for reading or the
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* file pointer not at the beginning of a frame
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*/
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ClusterVector<int32_t> read_frame();
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void write_frame(const ClusterVector<int32_t> &clusters);
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// Need to be migrated to support NDArray and return a ClusterVector
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// std::vector<Cluster3x3>
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// read_cluster_with_cut(size_t n_clusters, double *noise_map, int nx, int ny);
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// read_cluster_with_cut(size_t n_clusters, double *noise_map, int nx, int
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// ny);
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/**
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* @brief Return the chunk size
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*/
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size_t chunk_size() const { return m_chunk_size; }
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/**
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* @brief Close the file. If not closed the file will be closed in the destructor
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* @brief Close the file. If not closed the file will be closed in the
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* destructor
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*/
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void close();
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};
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@ -138,8 +133,17 @@ int analyze_data(int32_t *data, int32_t *t2, int32_t *t3, char *quad,
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int analyze_cluster(Cluster3x3 &cl, int32_t *t2, int32_t *t3, char *quad,
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double *eta2x, double *eta2y, double *eta3x, double *eta3y);
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NDArray<double, 2> calculate_eta2(ClusterVector<int> &clusters);
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Eta2 calculate_eta2(Cluster3x3 &cl);
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template <typename ClusterType>
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NDArray<double, 2> calculate_eta2(ClusterVector<ClusterType> &clusters);
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template <typename T> Eta2 calculate_eta2(Cluster<T, 3, 3> &cl);
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Eta2 calculate_eta2(Cluster2x2 &cl);
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template <typename ClusterType> Eta2 calculate_eta2(ClusterType &cl);
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template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
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typename CoordType>
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Eta2 calculate_eta2(Cluster<T, ClusterSizeX, ClusterSizeY, CoordType> &cl);
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} // namespace aare
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@ -10,6 +10,8 @@
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namespace aare {
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template <typename ClusterType> class ClusterVector; // Forward declaration
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/**
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* @brief ClusterVector is a container for clusters of various sizes. It uses a
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* contiguous memory buffer to store the clusters. It is templated on the data
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@ -21,10 +23,12 @@ namespace aare {
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* @tparam CoordType data type of the x and y coordinates of the cluster
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* (normally int16_t)
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*/
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template <typename T, typename CoordType = int16_t> class ClusterVector {
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template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
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typename CoordType>
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class ClusterVector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>> {
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using value_type = T;
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size_t m_cluster_size_x;
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size_t m_cluster_size_y;
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// size_t m_cluster_size_x;
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// size_t m_cluster_size_y;
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std::byte *m_data{};
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size_t m_size{0};
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size_t m_capacity;
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@ -40,6 +44,8 @@ template <typename T, typename CoordType = int16_t> class ClusterVector {
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constexpr static char m_fmt_base[] = "=h:x:\nh:y:\n({},{}){}:data:";
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public:
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using ClusterType = Cluster<T, SizeX, SizeY>;
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/**
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* @brief Construct a new ClusterVector object
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* @param cluster_size_x size of the cluster in x direction
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@ -48,10 +54,8 @@ template <typename T, typename CoordType = int16_t> class ClusterVector {
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* @param frame_number frame number of the clusters. Default is 0, which is
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* also used to indicate that the clusters come from many frames
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*/
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ClusterVector(size_t cluster_size_x = 3, size_t cluster_size_y = 3,
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size_t capacity = 1024, uint64_t frame_number = 0)
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: m_cluster_size_x(cluster_size_x), m_cluster_size_y(cluster_size_y),
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m_capacity(capacity), m_frame_number(frame_number) {
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ClusterVector(size_t capacity = 1024, uint64_t frame_number = 0)
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: m_capacity(capacity), m_frame_number(frame_number) {
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allocate_buffer(capacity);
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}
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@ -59,10 +63,8 @@ template <typename T, typename CoordType = int16_t> class ClusterVector {
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// Move constructor
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ClusterVector(ClusterVector &&other) noexcept
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: m_cluster_size_x(other.m_cluster_size_x),
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m_cluster_size_y(other.m_cluster_size_y), m_data(other.m_data),
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m_size(other.m_size), m_capacity(other.m_capacity),
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m_frame_number(other.m_frame_number) {
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: m_data(other.m_data), m_size(other.m_size),
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m_capacity(other.m_capacity), m_frame_number(other.m_frame_number) {
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other.m_data = nullptr;
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other.m_size = 0;
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other.m_capacity = 0;
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@ -72,8 +74,6 @@ template <typename T, typename CoordType = int16_t> class ClusterVector {
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ClusterVector &operator=(ClusterVector &&other) noexcept {
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if (this != &other) {
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delete[] m_data;
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m_cluster_size_x = other.m_cluster_size_x;
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m_cluster_size_y = other.m_cluster_size_y;
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m_data = other.m_data;
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m_size = other.m_size;
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m_capacity = other.m_capacity;
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@ -116,8 +116,7 @@ template <typename T, typename CoordType = int16_t> class ClusterVector {
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*reinterpret_cast<CoordType *>(ptr) = y;
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ptr += sizeof(CoordType);
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std::copy(data, data + m_cluster_size_x * m_cluster_size_y * sizeof(T),
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ptr);
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std::copy(data, data + ClusterSizeX * ClusterSizeY * sizeof(T), ptr);
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m_size++;
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}
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ClusterVector &operator+=(const ClusterVector &other) {
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@ -137,7 +136,7 @@ template <typename T, typename CoordType = int16_t> class ClusterVector {
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std::vector<T> sum() {
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std::vector<T> sums(m_size);
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const size_t stride = item_size();
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const size_t n_pixels = m_cluster_size_x * m_cluster_size_y;
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const size_t n_pixels = ClusterSizeX * ClusterSizeY;
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std::byte *ptr = m_data + 2 * sizeof(CoordType); // skip x and y
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for (size_t i = 0; i < m_size; i++) {
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@ -159,7 +158,7 @@ template <typename T, typename CoordType = int16_t> class ClusterVector {
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std::vector<T> sums(m_size);
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const size_t stride = item_size();
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if (m_cluster_size_x != 3 || m_cluster_size_y != 3) {
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if (ClusterSizeX != 3 || ClusterSizeY != 3) {
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throw std::runtime_error(
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"Only 3x3 clusters are supported for the 2x2 sum.");
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}
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@ -196,8 +195,7 @@ template <typename T, typename CoordType = int16_t> class ClusterVector {
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* @brief Return the size in bytes of a single cluster
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*/
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size_t item_size() const {
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return 2 * sizeof(CoordType) +
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m_cluster_size_x * m_cluster_size_y * sizeof(T);
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return 2 * sizeof(CoordType) + ClusterSizeX * ClusterSizeY * sizeof(T);
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}
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/**
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@ -217,8 +215,8 @@ template <typename T, typename CoordType = int16_t> class ClusterVector {
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return m_data + element_offset(i);
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}
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size_t cluster_size_x() const { return m_cluster_size_x; }
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size_t cluster_size_y() const { return m_cluster_size_y; }
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// size_t cluster_size_x() const { return m_cluster_size_x; }
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// size_t cluster_size_y() const { return m_cluster_size_y; }
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std::byte *data() { return m_data; }
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std::byte const *data() const { return m_data; }
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@ -227,12 +225,12 @@ template <typename T, typename CoordType = int16_t> class ClusterVector {
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* @brief Return a reference to the i-th cluster casted to type V
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* @tparam V type of the cluster
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*/
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template <typename V> V &at(size_t i) {
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return *reinterpret_cast<V *>(element_ptr(i));
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ClusterType &at(size_t i) {
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return *reinterpret_cast<ClusterType *>(element_ptr(i));
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}
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template <typename V> const V &at(size_t i) const {
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return *reinterpret_cast<const V *>(element_ptr(i));
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const ClusterType &at(size_t i) const {
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return *reinterpret_cast<const ClusterType *>(element_ptr(i));
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}
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const std::string_view fmt_base() const {
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@ -59,8 +59,8 @@ ClusterVector<int32_t> ClusterFile::read_clusters(size_t n_clusters) {
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if (m_mode != "r") {
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throw std::runtime_error("File not opened for reading");
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}
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ClusterVector<int32_t> clusters(3,3, n_clusters);
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ClusterVector<int32_t> clusters(3, 3, n_clusters);
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int32_t iframe = 0; // frame number needs to be 4 bytes!
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size_t nph_read = 0;
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@ -78,7 +78,7 @@ ClusterVector<int32_t> ClusterFile::read_clusters(size_t n_clusters) {
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} else {
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nn = nph;
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}
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nph_read += fread((buf + nph_read*clusters.item_size()),
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nph_read += fread((buf + nph_read * clusters.item_size()),
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clusters.item_size(), nn, fp);
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m_num_left = nph - nn; // write back the number of photons left
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}
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@ -93,7 +93,7 @@ ClusterVector<int32_t> ClusterFile::read_clusters(size_t n_clusters) {
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else
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nn = nph;
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nph_read += fread((buf + nph_read*clusters.item_size()),
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nph_read += fread((buf + nph_read * clusters.item_size()),
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clusters.item_size(), nn, fp);
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m_num_left = nph - nn;
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}
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@ -112,8 +112,8 @@ ClusterVector<int32_t> ClusterFile::read_clusters(size_t n_clusters, ROI roi) {
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if (m_mode != "r") {
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throw std::runtime_error("File not opened for reading");
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}
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ClusterVector<int32_t> clusters(3,3);
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ClusterVector<int32_t> clusters(3, 3);
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clusters.reserve(n_clusters);
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int32_t iframe = 0; // frame number needs to be 4 bytes!
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@ -124,7 +124,7 @@ ClusterVector<int32_t> ClusterFile::read_clusters(size_t n_clusters, ROI roi) {
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// auto buf = reinterpret_cast<Cluster3x3 *>(clusters.data());
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// auto buf = clusters.data();
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Cluster3x3 tmp; //this would break if the cluster size changes
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Cluster3x3 tmp; // this would break if the cluster size changes
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// if there are photons left from previous frame read them first
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if (nph) {
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@ -135,13 +135,15 @@ ClusterVector<int32_t> ClusterFile::read_clusters(size_t n_clusters, ROI roi) {
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} else {
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nn = nph;
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}
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//Read one cluster, in the ROI push back
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// nph_read += fread((buf + nph_read*clusters.item_size()),
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// clusters.item_size(), nn, fp);
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for(size_t i = 0; i < nn; i++){
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// Read one cluster, in the ROI push back
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// nph_read += fread((buf + nph_read*clusters.item_size()),
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// clusters.item_size(), nn, fp);
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for (size_t i = 0; i < nn; i++) {
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fread(&tmp, sizeof(tmp), 1, fp);
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if(tmp.x >= roi.xmin && tmp.x <= roi.xmax && tmp.y >= roi.ymin && tmp.y <= roi.ymax){
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clusters.push_back(tmp.x, tmp.y, reinterpret_cast<std::byte*>(tmp.data));
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if (tmp.x >= roi.xmin && tmp.x <= roi.xmax && tmp.y >= roi.ymin &&
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tmp.y <= roi.ymax) {
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clusters.push_back(tmp.x, tmp.y,
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reinterpret_cast<std::byte *>(tmp.data));
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nph_read++;
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}
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}
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@ -161,10 +163,13 @@ ClusterVector<int32_t> ClusterFile::read_clusters(size_t n_clusters, ROI roi) {
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// nph_read += fread((buf + nph_read*clusters.item_size()),
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// clusters.item_size(), nn, fp);
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for(size_t i = 0; i < nn; i++){
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for (size_t i = 0; i < nn; i++) {
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fread(&tmp, sizeof(tmp), 1, fp);
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if(tmp.x >= roi.xmin && tmp.x <= roi.xmax && tmp.y >= roi.ymin && tmp.y <= roi.ymax){
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clusters.push_back(tmp.x, tmp.y, reinterpret_cast<std::byte*>(tmp.data));
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if (tmp.x >= roi.xmin && tmp.x <= roi.xmax &&
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tmp.y >= roi.ymin && tmp.y <= roi.ymax) {
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clusters.push_back(
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tmp.x, tmp.y,
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reinterpret_cast<std::byte *>(tmp.data));
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nph_read++;
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}
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}
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@ -210,7 +215,6 @@ ClusterVector<int32_t> ClusterFile::read_frame() {
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return clusters;
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}
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// std::vector<Cluster3x3> ClusterFile::read_cluster_with_cut(size_t n_clusters,
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// double *noise_map,
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// int nx, int ny) {
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@ -218,7 +222,8 @@ ClusterVector<int32_t> ClusterFile::read_frame() {
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// throw std::runtime_error("File not opened for reading");
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// }
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// std::vector<Cluster3x3> clusters(n_clusters);
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// // size_t read_clusters_with_cut(FILE *fp, size_t n_clusters, Cluster *buf,
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// // size_t read_clusters_with_cut(FILE *fp, size_t n_clusters, Cluster
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// *buf,
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// // uint32_t *n_left, double *noise_map, int
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// // nx, int ny) {
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// int iframe = 0;
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@ -249,7 +254,8 @@ ClusterVector<int32_t> ClusterFile::read_frame() {
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// for (size_t iph = 0; iph < nn; iph++) {
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// // read photons 1 by 1
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// size_t n_read =
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// fread(reinterpret_cast<void *>(ptr), sizeof(Cluster3x3), 1, fp);
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// fread(reinterpret_cast<void *>(ptr), sizeof(Cluster3x3), 1,
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// fp);
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// if (n_read != 1) {
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// clusters.resize(nph_read);
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// return clusters;
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@ -257,12 +263,15 @@ ClusterVector<int32_t> ClusterFile::read_frame() {
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// // TODO! error handling on read
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// good = 1;
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// if (noise_map) {
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// if (ptr->x >= 0 && ptr->x < nx && ptr->y >= 0 && ptr->y < ny) {
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// if (ptr->x >= 0 && ptr->x < nx && ptr->y >= 0 && ptr->y < ny)
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// {
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// tot1 = ptr->data[4];
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// analyze_cluster(*ptr, &t2max, &tot3, NULL, NULL, NULL, NULL,
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// analyze_cluster(*ptr, &t2max, &tot3, NULL, NULL, NULL,
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// NULL,
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// NULL);
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// noise = noise_map[ptr->y * nx + ptr->x];
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// if (tot1 > noise || t2max > 2 * noise || tot3 > 3 * noise) {
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// if (tot1 > noise || t2max > 2 * noise || tot3 > 3 *
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// noise) {
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// ;
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// } else {
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// good = 0;
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@ -316,8 +325,8 @@ ClusterVector<int32_t> ClusterFile::read_frame() {
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// } else
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// good = 0;
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// } else {
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// printf("Bad pixel number %d %d\n", ptr->x, ptr->y);
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// good = 0;
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// printf("Bad pixel number %d %d\n", ptr->x,
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// ptr->y); good = 0;
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// }
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// }
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// if (good) {
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@ -338,37 +347,81 @@ ClusterVector<int32_t> ClusterFile::read_frame() {
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// return clusters;
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// }
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NDArray<double, 2> calculate_eta2(ClusterVector<int> &clusters) {
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//TOTO! make work with 2x2 clusters
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template <typename ClusterType>
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NDArray<double, 2> calculate_eta2(ClusterVector<ClusterType> &clusters) {
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// TOTO! make work with 2x2 clusters
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NDArray<double, 2> eta2({static_cast<int64_t>(clusters.size()), 2});
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if (clusters.cluster_size_x() == 3 || clusters.cluster_size_y() == 3) {
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for (size_t i = 0; i < clusters.size(); i++) {
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auto e = calculate_eta2(clusters.at<Cluster3x3>(i));
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eta2(i, 0) = e.x;
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eta2(i, 1) = e.y;
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}
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}else if(clusters.cluster_size_x() == 2 || clusters.cluster_size_y() == 2){
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for (size_t i = 0; i < clusters.size(); i++) {
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auto e = calculate_eta2(clusters.at<Cluster2x2>(i));
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eta2(i, 0) = e.x;
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eta2(i, 1) = e.y;
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}
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}else{
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throw std::runtime_error("Only 3x3 and 2x2 clusters are supported");
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for (size_t i = 0; i < clusters.size(); i++) {
|
||||
auto e = calculate_eta2<ClusterType>(clusters.at(i));
|
||||
eta2(i, 0) = e.x;
|
||||
eta2(i, 1) = e.y;
|
||||
}
|
||||
|
||||
|
||||
return eta2;
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Calculate the eta2 values for a 3x3 cluster and return them in a Eta2 struct
|
||||
* containing etay, etax and the corner of the cluster.
|
||||
*/
|
||||
Eta2 calculate_eta2(Cluster3x3 &cl) {
|
||||
/**
|
||||
* @brief Calculate the eta2 values for a generic sized cluster and return them
|
||||
* in a Eta2 struct containing etay, etax and the index of the respective 2x2
|
||||
* subcluster.
|
||||
*/
|
||||
template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
|
||||
typename CoordType>
|
||||
Eta2 calculate_eta2(Cluster<T, ClusterSizeX, ClusterSizeY, CoordType> &cl) {
|
||||
Eta2 eta{};
|
||||
|
||||
std::array<int32_t, 4> tot2;
|
||||
// TODO loads of overhead for a 2x2 clsuter maybe keep 2x2 calculation
|
||||
size_t num_2x2_subclusters = (ClusterSizeX - 1) * (ClusterSizeY - 1);
|
||||
std::array<int32_t, num_2x2_subclusters> sum_2x2_subcluster;
|
||||
for (size_t i = 0; i < ClusterSizeY - 1; ++i) {
|
||||
for (size_t j = 0; j < ClusterSizeX - 1; ++j)
|
||||
sum_2x2_subcluster[i * (ClusterSizeX - 1) + j] =
|
||||
cl.data[i * ClusterSizeX + j] +
|
||||
cl.data[i * ClusterSizeX + j + 1] +
|
||||
cl.data[(i + 1) * ClusterSizeX + j] +
|
||||
cl.data[(i + 1) * ClusterSizeX + j + 1];
|
||||
}
|
||||
|
||||
auto c = std::max_element(sum_2x2_subclusters.begin(),
|
||||
sum_2x2_subcluster.end()) -
|
||||
sum_2x2_subcluster.begin();
|
||||
|
||||
eta.sum = sum_2x2_subcluster[c];
|
||||
|
||||
eta.x = static_cast<double>(cl.data[(c + 1) * ClusterSizeX + 1]) /
|
||||
(cl.data[0] + cl.data[1]);
|
||||
|
||||
size_t index_top_left_2x2_subcluster =
|
||||
(int(c / (ClusterSizeX - 1)) + 1) * ClusterSizeX +
|
||||
c % (ClusterSizeX - 1) * 2 + 1;
|
||||
if ((cl.data[index_top_left_2x2_subcluster] +
|
||||
cl.data[index_top_left_2x2_subcluster - 1]) != 0)
|
||||
eta.x =
|
||||
static_cast<double>(cl.data[index_top_left_2x2_subcluster] /
|
||||
(cl.data[index_top_left_2x2_subcluster] +
|
||||
cl.data[index_top_left_2x2_subcluster - 1]));
|
||||
|
||||
if ((cl.data[index_top_left_2x2_subcluster] +
|
||||
cl.data[index_top_left_2x2_subcluster - ClusterSizeX]) != 0)
|
||||
eta.y = static_cast<double>(
|
||||
cl.data[index_top_left_2x2_subcluster] /
|
||||
(cl.data[index_top_left_2x2_subcluster] +
|
||||
cl.data[index_top_left_2x2_subcluster - ClusterSizeX]));
|
||||
|
||||
eta.c = c; // TODO only supported for 2x2 and 3x3 clusters -> at least no
|
||||
// underyling enum class
|
||||
return eta;
|
||||
}
|
||||
|
||||
/**
|
||||
* @brief Calculate the eta2 values for a 3x3 cluster and return them in a Eta2
|
||||
* struct containing etay, etax and the corner of the cluster.
|
||||
*/
|
||||
template <typename T> Eta2 calculate_eta2(Cluster<T, 3, 3> &cl) {
|
||||
Eta2 eta{};
|
||||
|
||||
std::array<T, 4> tot2;
|
||||
tot2[0] = cl.data[0] + cl.data[1] + cl.data[3] + cl.data[4];
|
||||
tot2[1] = cl.data[1] + cl.data[2] + cl.data[4] + cl.data[5];
|
||||
tot2[2] = cl.data[3] + cl.data[4] + cl.data[6] + cl.data[7];
|
||||
@ -379,58 +432,47 @@ Eta2 calculate_eta2(Cluster3x3 &cl) {
|
||||
switch (c) {
|
||||
case cBottomLeft:
|
||||
if ((cl.data[3] + cl.data[4]) != 0)
|
||||
eta.x =
|
||||
static_cast<double>(cl.data[4]) / (cl.data[3] + cl.data[4]);
|
||||
eta.x = static_cast<double>(cl.data[4]) / (cl.data[3] + cl.data[4]);
|
||||
if ((cl.data[1] + cl.data[4]) != 0)
|
||||
eta.y =
|
||||
static_cast<double>(cl.data[4]) / (cl.data[1] + cl.data[4]);
|
||||
eta.y = static_cast<double>(cl.data[4]) / (cl.data[1] + cl.data[4]);
|
||||
eta.c = cBottomLeft;
|
||||
break;
|
||||
case cBottomRight:
|
||||
if ((cl.data[2] + cl.data[5]) != 0)
|
||||
eta.x =
|
||||
static_cast<double>(cl.data[5]) / (cl.data[4] + cl.data[5]);
|
||||
eta.x = static_cast<double>(cl.data[5]) / (cl.data[4] + cl.data[5]);
|
||||
if ((cl.data[1] + cl.data[4]) != 0)
|
||||
eta.y =
|
||||
static_cast<double>(cl.data[4]) / (cl.data[1] + cl.data[4]);
|
||||
eta.y = static_cast<double>(cl.data[4]) / (cl.data[1] + cl.data[4]);
|
||||
eta.c = cBottomRight;
|
||||
break;
|
||||
case cTopLeft:
|
||||
if ((cl.data[7] + cl.data[4]) != 0)
|
||||
eta.x =
|
||||
static_cast<double>(cl.data[4]) / (cl.data[3] + cl.data[4]);
|
||||
eta.x = static_cast<double>(cl.data[4]) / (cl.data[3] + cl.data[4]);
|
||||
if ((cl.data[7] + cl.data[4]) != 0)
|
||||
eta.y =
|
||||
static_cast<double>(cl.data[7]) / (cl.data[7] + cl.data[4]);
|
||||
eta.y = static_cast<double>(cl.data[7]) / (cl.data[7] + cl.data[4]);
|
||||
eta.c = cTopLeft;
|
||||
break;
|
||||
case cTopRight:
|
||||
if ((cl.data[5] + cl.data[4]) != 0)
|
||||
eta.x =
|
||||
static_cast<double>(cl.data[5]) / (cl.data[5] + cl.data[4]);
|
||||
eta.x = static_cast<double>(cl.data[5]) / (cl.data[5] + cl.data[4]);
|
||||
if ((cl.data[7] + cl.data[4]) != 0)
|
||||
eta.y =
|
||||
static_cast<double>(cl.data[7]) / (cl.data[7] + cl.data[4]);
|
||||
eta.y = static_cast<double>(cl.data[7]) / (cl.data[7] + cl.data[4]);
|
||||
eta.c = cTopRight;
|
||||
break;
|
||||
// no default to allow compiler to warn about missing cases
|
||||
// no default to allow compiler to warn about missing cases
|
||||
}
|
||||
return eta;
|
||||
}
|
||||
|
||||
|
||||
Eta2 calculate_eta2(Cluster2x2 &cl) {
|
||||
template <typename T> Eta2 calculate_eta2(Cluster<T, 2, 2> &cl) {
|
||||
Eta2 eta{};
|
||||
|
||||
eta.x = static_cast<double>(cl.data[1]) / (cl.data[0] + cl.data[1]);
|
||||
eta.y = static_cast<double>(cl.data[2]) / (cl.data[0] + cl.data[2]);
|
||||
eta.sum = cl.data[0] + cl.data[1] + cl.data[2]+ cl.data[3];
|
||||
eta.c = cBottomLeft; //TODO! This is not correct, but need to put something
|
||||
eta.sum = cl.data[0] + cl.data[1] + cl.data[2] + cl.data[3];
|
||||
eta.c = cBottomLeft; // TODO! This is not correct, but need to put something
|
||||
return eta;
|
||||
}
|
||||
|
||||
|
||||
|
||||
int analyze_cluster(Cluster3x3 &cl, int32_t *t2, int32_t *t3, char *quad,
|
||||
double *eta2x, double *eta2y, double *eta3x,
|
||||
double *eta3y) {
|
||||
|
Loading…
x
Reference in New Issue
Block a user