leonarski_fandClaude Opus 5
4e6eb18d93
48008e144 widens the signal radius on crystals with wide spots. On one
battery crystal - simultaneously the widest-spot and among the highest in
mosaicity - the wider radius left its neighbours' background rings with too
few clean pixels and cost 28.5% of its observations. Pass 1 now measures how
often that happens and, above a bound, hands pass 2 the settings from before
the pre-scan widened them.
The obvious quantity does not work. On the total rate of reflections dropped
for a starved ring, the losing crystal reads 4.08% and the rule's four
biggest winners read 1.89-2.04% - and a crystal at the shipped radius reads
2.37%, above all of them. Re-running the winners at r1 = 4 shows why: they
read 2.20-2.32% there too, and widening moves them down. That floor is module
gaps, the beam stop and the resolution mask, which are properties of the
detector and do not move with the radius.
So the counter separates the two. A ring is neighbour-starved when it would
have kept more than five pixels but for the pixels a neighbouring
reflection's signal region occupies. That is exact rather than estimated: the
reflection mask marks the disk inside r2 and the ring is everything outside
it, so a masked ring pixel always belongs to some other reflection's core.
The separation goes from a factor of 2 to a factor of 13 - over the twelve
crystals the radius moves, the rate is 0.000 five times, 0.001 three times,
then 0.004, 0.235, 0.315 and 4.082 - and the bound is the log-space midpoint
of that one gap, 0.0113, a factor 3.6 clear of the nearest measurement on
either side.
Predicted reflection spacing does not separate them at all: the losing
crystal is 19th of 38, a winner sits at 21.9 px, and the loosest pattern in
the battery starves 1.93% of its rings.
Battery: the space group is identical on all 38 and the merged .hkl is
byte-identical on 37, so it is inert wherever it does not fire. On the one
crystal it fires on, <I/sigma> is up 18.3%, R_meas down 29.4%, observations
up 6.3%, CC1/2 0.944 to 0.974, and its two empty top shells come back as
numbers. Its indexing rate, refined distance, beam centre and cell are
bit-identical between the two arms, so this is the guard and not the two-pass
gate.
The counters are a shared channel through both engines, summed across
workers and logged once per pass; on the GPU it is one atomic add per dropped
reflection. The profile-fit runaway guard reports on the same channel, which
is the first measurement of its trip rate.
This does not recover that crystal fully. With the adaptive radius on, pass 1
reaches a different lattice and pass 2 indexes 21% fewer frames - which
happens before the measurement this guard reads exists, and is unaffected by
it. At matched indexing rate the guard recovers 96% of the baseline's
observations against 90.5% without it.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CHMmeM1d489zvNFT7ZMN2P
104 lines
5.2 KiB
C++
104 lines
5.2 KiB
C++
// SPDX-FileCopyrightText: 2024 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
|
|
// SPDX-License-Identifier: GPL-3.0-only
|
|
|
|
#pragma once
|
|
|
|
#include <mutex>
|
|
|
|
#include "../common/JFJochMessages.h"
|
|
#include "../common/DiffractionExperiment.h"
|
|
#include "../common/AzimuthalIntegrationMapping.h"
|
|
#include "../common/PixelMask.h"
|
|
#include "../common/AzimuthalIntegrationProfile.h"
|
|
#include "bragg_prediction/BraggPrediction.h"
|
|
#include "bragg_integration/BraggIntegrationEngine.h"
|
|
#include "spot_finding/ImageSpotFinder.h"
|
|
#include "spot_finding/AdaptiveSpotFinderCPU.h"
|
|
#include "indexing/IndexerThreadPool.h"
|
|
#include "azint/AzIntEngine.h"
|
|
#include "roi/ROIIntegration.h"
|
|
#include "IndexAndRefine.h"
|
|
#include "image_preprocessing/ImagePreprocessor.h"
|
|
#include "image_preprocessing/ImagePreprocessorBuffer.h"
|
|
|
|
class CudaStream;
|
|
class AdaptiveSpotFinderGPU;
|
|
|
|
// MXAnalysisWithoutFPGA is not thread safe - it has to owned by a single thread
|
|
class MXAnalysisWithoutFPGA {
|
|
const DiffractionExperiment &experiment;
|
|
const AzimuthalIntegrationMapping &integration;
|
|
|
|
std::vector<uint8_t> decompression_buffer;
|
|
|
|
std::unique_ptr<ImagePreprocessor> preprocessor;
|
|
|
|
size_t npixels;
|
|
size_t xpixels;
|
|
|
|
// Built on first use: the fused adaptive finder produces the azimuthal profile as a by-product,
|
|
// so on the rugnux path this engine is constructed and then never run.
|
|
std::unique_ptr<AzIntEngine> azint;
|
|
AzIntEngine &AzInt();
|
|
std::unique_ptr<ROIIntegration> roi;
|
|
// Built on first use. Which finder an image takes arrives with its SpotFindingSettings, and
|
|
// with adaptive detection on - the default everywhere but the broker - this one is never asked
|
|
// for; on the GPU it is ~14 MB and 15 device allocations per worker.
|
|
std::unique_ptr<ImageSpotFinder> spotFinder;
|
|
ImageSpotFinder &FixedThresholdFinder();
|
|
// Self-calibrating finder, used when spot settings request adaptive detection. Kept alongside the
|
|
// default finder because the choice arrives with the per-image settings, not at construction. It is
|
|
// an AdaptiveSpotFinderCPU by default; on the GPU path, when the fused engine is enabled (rugnux
|
|
// offline only), it is instead an AdaptiveSpotFinderGPU that also computes the azimuthal profile,
|
|
// aliased through fused_adaptive so Analyze() can take that profile and skip the separate azint pass.
|
|
std::unique_ptr<ImageSpotFinder> adaptiveSpotFinder;
|
|
AdaptiveSpotFinderGPU *fused_adaptive = nullptr;
|
|
const bool enable_fused_adaptive_gpu;
|
|
IndexAndRefine &indexer;
|
|
std::unique_ptr<BraggPrediction> prediction;
|
|
std::unique_ptr<BraggIntegrationEngine> bragg_engine;
|
|
std::unique_ptr<ImagePreprocessorBuffer> preprocessor_buffer;
|
|
const PixelMask &mask;
|
|
|
|
// Decompress the image into decompression_buffer (or read it straight from the message, when it is
|
|
// not compressed) and return where it landed.
|
|
const uint8_t *Decompress(const CompressedImage &image);
|
|
|
|
// Pixels outside the resolution limits, bit-packed. Built by the integration mapping, which is
|
|
// shared by every worker's engine and hands out the same mask to all of them.
|
|
std::shared_ptr<const std::vector<uint32_t>> mask_resolution;
|
|
// The limits mask_resolution was built for. Kept as the OPTIONAL the caller passed, so an unset
|
|
// high-resolution limit compares equal to itself and the mask is not rebuilt on every image.
|
|
std::optional<float> mask_high_res;
|
|
std::optional<float> mask_low_res;
|
|
void UpdateMaskResolution(const SpotFindingSettings& settings);
|
|
#ifdef JFJOCH_USE_CUDA
|
|
std::shared_ptr<CudaStream> stream; // kept so RebuildROI() can recreate the GPU ROI engine
|
|
#endif
|
|
public:
|
|
// enable_fused_adaptive_gpu turns on the fused GPU azint+adaptive spot finder (only takes effect on
|
|
// the GPU path with adaptive detection). The rugnux offline path and the interactive viewer enable
|
|
// it by default, as does the online receiver. It only changes performance - the fused engine
|
|
// reproduces the CPU finder's spots. Note it also decides whether the preprocessed image is copied
|
|
// back to the host each frame: that copy exists only for a CPU engine to read, and with the flag on
|
|
// no CPU engine is built, so the copy is skipped.
|
|
MXAnalysisWithoutFPGA(const DiffractionExperiment &experiment, const AzimuthalIntegrationMapping &integration,
|
|
const PixelMask &mask, IndexAndRefine &indexer, bool enable_fused_adaptive_gpu = false);
|
|
void Analyze(DataMessage &output, AzimuthalIntegrationProfile &profile, const SpotFindingSettings &spot_finding_settings);
|
|
|
|
// Surgical ROI-only paths used when a full re-analysis is not wanted: rebuild the
|
|
// ROI engine after the ROI set changes, recompute ROIs after preprocessing a new
|
|
// image (reanalyze off), or just rerun ROIs on the current preprocessed image (an
|
|
// interactive ROI move). A full Analyze() already computes ROIs, so needs nothing.
|
|
void RebuildROI();
|
|
void AnalyzeROIOnly(DataMessage &output);
|
|
void RunROIOnly(DataMessage &output);
|
|
|
|
// What this worker's Bragg integrator counted (BraggIntegrationCounts). Each worker builds its own
|
|
// analysis, so a caller that wants the run's totals sums this over the workers it started.
|
|
[[nodiscard]] BraggIntegrationCounts BraggCounts() const;
|
|
};
|
|
|
|
|
|
|