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Jungfraujoch/writer/HDF5DataFilePluginMX.h
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leonarski_f b00c668e3a
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v1.0.0-rc.179 (#90)
* Rugnux: Stills processing needs only the unit cell and space group beyond what the file records - detector distance, beam centre, tilt, panel placement, saturation level, gain and polarisation plane are found from the images - and is up to twice as fast.
* Rugnux: Stills can be indexed without a GPU, with a CPU implementation of the fast-feedback indexer (macOS, computers without a GPU).
* Rugnux: Rotation and stills data are integrated in the detector's own units with one gain model, improving data from CCD detectors.
* Web frontend: The Rugnux live page shows the placed model with its electron density and anomalous difference map in a Mol* viewer.

Reviewed-on: #90
Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
2026-10-24 14:52:29 +02:00

75 lines
2.6 KiB
C++

// SPDX-FileCopyrightText: 2024 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#pragma once
#include "HDF5DataFilePlugin.h"
#include "../common/AutoIncrVector.h"
class HDF5DataFilePluginMX : public HDF5DataFilePlugin {
const size_t max_spots;
const size_t max_extra_lattices;
const bool indexing;
// spots
std::vector<float> spot_x;
std::vector<float> spot_y;
std::vector<float> spot_int;
std::vector<int8_t> spot_indexed;
std::vector<int8_t> spot_ice_ring;
std::vector<int8_t> spot_lattice;
std::vector<int32_t> spot_h;
std::vector<int32_t> spot_k;
std::vector<int32_t> spot_l;
std::vector<float> spot_dist_ewald;
std::vector<int16_t> spot_panel;
bool spot_panel_present = false; // written only for a detector with a panel table
AutoIncrVector<float> beam_corr_x{NAN};
AutoIncrVector<float> beam_corr_y{NAN};
AutoIncrVector<uint32_t> npeaks;
AutoIncrVector<uint32_t> strong_pixel_count;
AutoIncrVector<uint32_t> spot_count_total;
AutoIncrVector<uint32_t> spot_count_ice;
AutoIncrVector<float> spot_count_ice_control{NAN};
AutoIncrVector<uint32_t> spot_count_indexed;
AutoIncrVector<uint32_t> spot_count_low_res;
// indexing
AutoIncrVector<uint8_t> indexed;
AutoIncrVector<uint32_t> indexing_lattice_count;
std::vector<float> indexed_lattice;
std::vector<float> extra_lattices; // [nimages, max_extra_lattices, 9], NaN-filled
// crystal
AutoIncrVector<float> profile_radius{NAN};
AutoIncrVector<float> mosaicity_deg{NAN};
AutoIncrVector<float> b_factor{NAN};
// bkg_estimate
AutoIncrVector<float> bkg_estimate{NAN};
AutoIncrVector<float> ice_ring_score{NAN};
// NaN = the frame had no value (CANNOT SAY), which is not a zero - see SpindleTrigger.
AutoIncrVector<float> spindle_blind_fraction{NAN};
// resolution_estimation
AutoIncrVector<float> resolution_estimate{NAN};
AutoIncrVector<uint32_t> niggli_class;
AutoIncrVector<std::string> bravais_lattice;
AutoIncrVector<int64_t> integrated_reflections;
// scaling
bool image_scale_present = false;
AutoIncrVector<float> image_scale_factor{NAN};
AutoIncrVector<float> image_scale_cc{NAN};
AutoIncrVector<float> image_scale_mosaicity{NAN};
public:
explicit HDF5DataFilePluginMX(const StartMessage& msg);
void OpenFile(HDF5File &data_file, const DataMessage& msg, size_t images_per_file) override;
void Write(const DataMessage& msg, uint64_t image_number) override;
void WriteFinal(HDF5File &data_file) override;
};