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* jfjoch_broker: Optional per-dataset authentication - statistics, images and plots can require a bearer token, which jfjoch_viewer supports. * jfjoch_viewer: Dark mode and a theme-matched colour scheme, a magnifier panel, and simpler contrast and background controls. * Rugnux: Multiple performance improvements on GPU and CPU (CPU-only processing up to 40% faster, faster image decoding on ARM), with unchanged results. * Rugnux: `--model` rigid-body refinement runs on the GPU, and the model-validation check is faster and more reliable. * Rugnux: Improved scaling and merging - error model, outlier rejection, absorption correction and French-Wilson amplitudes now agree more closely with XDS and ctruncate. * Rugnux: Improved integration - radial background on powder and ice rings, crowded rotation data keep their reflections, and CPU-only builds integrate large unit cells as GPU builds do. * Rugnux: More robust detector geometry - measured beam centre, X-ray bandwidth and goniometer rate, and geometry refinement accepted only on significant evidence. * Rugnux: Merged files are written in the standard setting, or in the setting of a reference MTZ, structure-factor mmCIF or model, with its free-R flags. * Rugnux: Richer report - ice and powder rings, further lattices, superstructure candidates and mosaicity, with warnings worded as prompts to check. * Rugnux: Clear error messages when a data set needs more GPU or host memory than is available. Reviewed-on: #83 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
153 lines
5.8 KiB
C++
153 lines
5.8 KiB
C++
// SPDX-FileCopyrightText: 2024 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
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// SPDX-License-Identifier: GPL-3.0-only
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#pragma once
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#include <map>
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#include <shared_mutex>
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#include <string>
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#include "StatusVector.h"
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#include "Histogram.h"
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#include "ADUHistogram.h"
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#include "AutoIncrVector.h"
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#include "DiffractionExperiment.h"
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#include "AzimuthalIntegrationProfile.h"
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#include "JFJochMessages.h"
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#include "Plot.h"
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#include "ScanResult.h"
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struct MeanProcessingTime {
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float compression;
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float preprocessing;
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float azint;
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float spot_finding;
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float indexing;
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float refinement;
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float integration;
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float bragg_prediction;
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float processing;
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float indexing_analysis;
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float image_scale;
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};
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class JFJochReceiverPlots {
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mutable std::mutex m; // protects xfel_pulse_id, xfel_event_code and az_int_profile
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std::optional<GoniometerAxis> goniometer;
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std::optional<GridScanSettings> grid_scan;
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int64_t default_binning = 1;
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std::unique_ptr<AzimuthalIntegrationProfile> az_int_profile;
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AutoIncrVector<uint64_t> xfel_pulse_id;
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AutoIncrVector<uint64_t> xfel_event_code;
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StatusVector bkg_estimate;
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StatusVector spindle_blind_fraction;
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StatusVector ice_ring_score;
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StatusVector spot_count;
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StatusVector spot_count_low_res;
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StatusVector spot_count_indexed;
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StatusVector spot_count_ice;
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StatusVector spot_count_ice_control;
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StatusVector indexing_solution;
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StatusVector indexing_lattice_count;
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StatusVector indexing_uc_a;
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StatusVector indexing_uc_b;
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StatusVector indexing_uc_c;
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StatusVector indexing_uc_alpha;
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StatusVector indexing_uc_beta;
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StatusVector indexing_uc_gamma;
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StatusVector error_pixels;
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StatusVector saturated_pixels;
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StatusVector strong_pixels;
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StatusVector receiver_delay;
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StatusVector receiver_buf_available;
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StatusVector receiver_buf_in_sending;
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StatusVector receiver_buf_in_preparation;
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StatusVector image_collection_efficiency;
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StatusVector packets_received;
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StatusVector max_value;
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StatusVector resolution_estimate;
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StatusVector integrated_reflections;
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StatusVector image_scale_factor;
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StatusVector image_scale_cc;
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StatusVector compression_ratio;
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// StatusVector objects are fully thread-safe (protected by internal mutex)
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// It is OK to have concurrent access to StatusVector
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// roi_m lock is needed to make sure that std::map<std::string, ROIStatus> is not mutable within critical section
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// so no new elements added outside of a unique lock, but it is OK to modify ROIStatus under shared lock
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struct ROIStatus {
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StatusVector sum;
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StatusVector max_count;
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StatusVector pixels;
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StatusVector x;
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StatusVector y;
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StatusVector mean;
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};
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mutable std::shared_mutex roi_m;
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std::map<std::string, ROIStatus> roi_status;
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StatusVector profile_radius;
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StatusVector mosaicity_deg;
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StatusVector b_factor;
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StatusVector pixel_sum;
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StatusVector beam_center_x;
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StatusVector beam_center_y;
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StatusVector spot_finding_time;
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StatusVector indexing_time;
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StatusVector refinement_time;
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StatusVector integration_time;
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StatusVector bragg_prediction_time;
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StatusVector total_processing_time;
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StatusVector preprocessing_time;
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StatusVector compression_time;
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StatusVector azint_time;
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StatusVector indexing_analysis_time;
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StatusVector image_scale_time;
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MultiLinePlot GetROIPlot(PlotType type, int64_t nbins, float start, float incr,
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const std::optional<float> &fill_value) const;
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void ClearVectors_i(size_t reserve);
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public:
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void Setup(const DiffractionExperiment& experiment, const AzimuthalIntegrationMapping& mapping);
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// Drop the previous run's plots (nothing to plot until the next Setup).
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void Clear();
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void Add(const DataMessage& msg, const AzimuthalIntegrationProfile &profile);
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void AddEmptyImage(const DataMessage& msg);
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MultiLinePlot GetPlots(const PlotRequest& request);
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void GetXFELPulseID(std::vector<uint64_t>& v) const;
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void GetXFELEventCode(std::vector<uint64_t>& v) const;
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std::optional<float> GetIndexingRate() const;
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std::optional<float> GetBkgEstimate() const;
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// Run mean of the per-image spindle severity, over the frames that had one; nothing when none did.
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std::optional<float> GetSpindleBlindFraction() const;
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std::optional<float> GetIceRingScore() const;
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// Pooled over the run: spots on the hexagonal rings over the same q width of ice-free control
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// flanks. 1 = spots spread evenly, > 1 = they pile up on the rings (textured ice).
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[[nodiscard]] std::optional<float> GetIceRingSpotRatio() const;
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// The run's spot-finding resolution estimate: the MEDIAN of the per-image estimates. A median and
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// not a mean - a few blank or badly-shot frames pull a mean a long way and leave the median where
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// the run actually is.
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[[nodiscard]] std::optional<float> GetResolutionEstimate() const;
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std::vector<float> GetIceRingScoreArray() const;
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std::vector<float> GetAzIntProfile() const;
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// The run-summed profile object itself, rather than the array GetAzIntProfile() flattens it to.
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// Powder calibration reads the ring positions off it and wants its own GetResult(), which leaves a
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// bin no pixel fell in as NaN - as 0 it would read as a deep hole in the ring instead. Null before
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// Setup(); not synchronised, so use it once the run is over rather than while images arrive.
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[[nodiscard]] const AzimuthalIntegrationProfile *GetAzIntProfileObject() const { return az_int_profile.get(); }
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MultiLinePlot GetAzIntProfilePlot(bool force_1d = false, PlotAzintUnit azint_unit = PlotAzintUnit::Q_recipA) const;
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MeanProcessingTime GetMeanProcessingTime() const;
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void GetPlotRaw(std::vector<float> &v, PlotType type, const std::string &roi);
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};
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