Files
Jungfraujoch/image_analysis/MXAnalysisAfterFPGA.h
T
leonarski_f d6389e12da
Build Packages / Unit tests (push) Skipped
Build Packages / build:windows:nocuda (push) Successful in 15m31s
Build Packages / build:viewer-tgz:cpu (push) Successful in 5m46s
Build Packages / build:viewer-tgz:cuda (push) Successful in 6m9s
Build Packages / build:rpm (rocky8_nocuda) (push) Successful in 9m25s
Build Packages / build:rpm (rocky9_nocuda) (push) Successful in 10m21s
Build Packages / build:rpm (ubuntu2204_nocuda) (push) Successful in 9m41s
Build Packages / build:rpm (ubuntu2404_nocuda) (push) Successful in 9m18s
Build Packages / build:rpm (rocky8_sls9) (push) Successful in 10m26s
Build Packages / build:rpm (rocky9_sls9) (push) Successful in 11m33s
Build Packages / build:rpm (rocky8) (push) Successful in 10m32s
Build Packages / build:rpm (rocky9) (push) Successful in 12m23s
Build Packages / build:rpm (ubuntu2204) (push) Successful in 10m50s
Build Packages / build:rpm (ubuntu2404) (push) Successful in 10m12s
Build Packages / DIALS test (push) Successful in 12m6s
Build Packages / XDS test (durin plugin) (push) Successful in 8m15s
Build Packages / XDS test (JFJoch plugin) (push) Successful in 7m12s
Build Packages / XDS test (neggia plugin) (push) Successful in 5m35s
Build Packages / Generate python client (push) Successful in 27s
Build Packages / Build documentation (push) Successful in 54s
Build Packages / Create release (push) Skipped
Build Packages / build:windows:cuda (push) Successful in 12m37s
v1.0.0-rc.156 (#66)
This is an UNSTABLE release. It includes many experimental features, as well as many AI generated fixes. We recommend using rc.152 for production use.

* jfjoch_process: Major rotation (rot3d) data processing overhaul - robust profile-fit integration, Cauchy-loss scaling with optional absorption surface, de-novo indexing and space-group/centering determination fixes, and merging statistics + ISa in the mmCIF output.
* jfjoch_process: Add EXPERIMENTAL ice-ring detection (--detect-ice-rings) that excludes ice reflections from scaling.
* Compression: Add BSHUF_ZSTD_RLE_HUFF, make compression size-aware (drop frames that don't fit rather than aborting), and add the jfjoch_recompress tool.
* jfjoch_viewer: Report "Multiple lattices detected" and grey out "Analyze dataset" on a live connection.
* jfjoch_broker: Write smargon chi/phi goniometer positions to NXmx; read sensor thickness/material from HDF5 metadata.
* CI: Build Windows (CUDA and non-CUDA) installers.Reviewed-on: #66

Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
2026-07-03 19:18:56 +02:00

60 lines
2.4 KiB
C++

// SPDX-FileCopyrightText: 2024 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#pragma once
#include "../common/DiffractionExperiment.h"
#include "bragg_prediction/BraggPrediction.h"
#include "bragg_integration/BraggIntegrationEngineCPU.h"
#include "indexing/IndexerThreadPool.h"
#include "spot_finding/StrongPixelSet.h"
#include "azint/AzIntEngineCPU.h"
#include "IndexAndRefine.h"
class MXAnalysisAfterFPGA {
mutable std::mutex read_from_cpu_mutex;
const DiffractionExperiment &experiment;
const AzimuthalIntegrationMapping &integration;
IndexAndRefine &indexer;
std::unique_ptr<BraggPrediction> prediction;
std::unique_ptr<AzIntEngineCPU> cpu_azint;
// The FPGA host has no usable GPU bandwidth for integration, so Bragg integration here is always on
// the CPU, reading the assembled detector image straight (only the reflection disks - no copy).
std::unique_ptr<BraggIntegrationEngineCPU> bragg_engine;
bool find_spots = false;
std::vector<DiffractionSpot> spots;
constexpr static const float spot_distance_threshold_pxl = 2.0f;
std::vector<float> arr_mean;
std::vector<float> arr_sttdev;
std::vector<uint32_t> arr_valid_count;
std::vector<uint32_t> arr_strong_pixel;
enum class State {Idle, Disabled, Enabled} state = State::Idle;
std::chrono::duration<double, std::micro> spot_finding_time_total{0.0};
bool spot_finding_timing_active = false;
public:
MXAnalysisAfterFPGA(const DiffractionExperiment& experiment,
const AzimuthalIntegrationMapping &integration,
IndexAndRefine &indexer);
void ReadFromFPGA(const DeviceOutput* output,
const SpotFindingSettings& settings,
size_t module_number);
void ReadFromCPU(DeviceOutput *output,
const SpotFindingSettings &settings,
size_t module_number);
// Computes the azimuthal integration profile on the CPU from the assembled image.
// Only active when the settings force the CPU backend; otherwise a no-op (the FPGA
// fills the profile). image points to the uncompressed image of GetByteDepthImage() pixels.
void RunAzimuthalIntegration(const void *image, AzimuthalIntegrationProfile &profile);
void Process(DataMessage &message, const SpotFindingSettings& settings);
};