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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. * **rugnux: significantly better quality of results, and faster.** A large rework of integration, scaling, merging, geometry refinement and space-group determination, together with measurements the program previously made no attempt at - the direct beam before indexing, the beam stop, the goniometer rotation scale, and the stretches of a sweep the crystal did not deliver. A rotation dataset typically gains observations at better <I/sigma> and R_meas, and every `mx` and `scale` run writes a `<prefix>_report.txt` results report modelled on XDS's `CORRECT.LP`. Many defaults moved with it: spot detection is self-calibrating, beam-stop detection and rotation geometry post-refinement are on, resolution limits default to as far as the detector reaches, and ice-ring handling engages only where the crystal is measured to have ice. * **jfjoch_viewer:** the beam-stop shadow, the detector calibration and the beam-centre measurement are reachable from "Analyze dataset"; the settings panel reports how the sample moved and how polarized the beam was; image rendering and interaction are faster. * **Performance:** bitshuffle+LZ4 images are decoded on the GPU rather than on the host, with the bitshuffle inverse fused into preprocessing so the decompressed frame is never held in device memory. * **Broker, writer, packaging and build:** image-slot lifetime and locking fixes, per-image datasets sized by the images actually written, the Debian/Ubuntu broker package renamed to `jfjoch`, and `image_analysis` compiling under MSVC again. **Breaking change to the rugnux command line:** * `--azint-only` and `--scale` are **removed**, replaced by `--mode azint` and `--mode scale`; the full pipeline is `--mode mx` and remains the default. A script passing the old flags now fails with the list of valid modes rather than silently running the wrong one. * `-t`/`--stride` is **refused on rotation data**: skipping frames cuts every reflection's rocking curve, so the combined fulls and their partiality would be measured over frames the sweep never recorded. Select a contiguous range with `-s`/`-e` instead. `--mode azint` and `--force-still` still take a stride. **Breaking changes to OpenAPI** - regenerate the client (`jfjoch-client` 1.0.0-rc.161, `frontend/src/client`) or read the affected fields as optional: * `image_scale_b` is removed from the `plot_type` enum, so a client requesting that plot now gets an error rather than a curve. * `azim_int_settings.high_q_recipA`, `spot_finding_settings.high_resolution_limit` and `spot_finding_settings.low_resolution_limit` are no longer `required`. All three mean "no limit at that end" when unset and are omitted from the response instead of carrying a placeholder value, which raises in a client generated from an rc.160-or-earlier spec. A value of 0 is still accepted and means the same thing. **Breaking changes to the stored formats** - a consumer reading these fields must treat them as optional: * The per-image image-scale B factor is no longer computed, so `/entry/MX/imageScaleBFactor` is absent from newly written HDF5 files and the corresponding key is absent from the CBOR DataMessage and END blocks. Files written by rc.160 and earlier still contain it and still open; nothing in the pipeline reads it any more. * `_reflns.jfjoch_diffrn_ISa` now carries the whole-range `1/sqrt(a*b)` that XDS's ISa denotes, and the error-model `a` and `b` are reported in XDS's convention; the strong-reflection asymptote moves to `_reflns.jfjoch_diffrn_ISa_asymptotic`. **A file written by an earlier version carries the asymptote under the plain `ISa` name.** Reviewed-on: #71 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
168 lines
7.3 KiB
C++
168 lines
7.3 KiB
C++
// SPDX-FileCopyrightText: 2026 Filip Leonarski, Paul Scherrer Institute
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// SPDX-License-Identifier: GPL-3.0-only
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#include <catch2/catch_all.hpp>
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#include "../common/CUDAWrapper.h"
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#ifdef JFJOCH_USE_CUDA
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#include <random>
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#include <vector>
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#include "../common/PixelMask.h"
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#include "../compression/JFJochCompressor.h"
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#include "../image_analysis/image_preprocessing/ImagePreprocessorCPU.h"
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#include "../image_analysis/image_preprocessing/ImagePreprocessorGPU.h"
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#include "../image_analysis/image_preprocessing/ImagePreprocessorBufferGPU.h"
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// The device-decode path does NOT decompress into a buffer and then preprocess it: one kernel
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// un-transposes the bitshuffle blocks and applies the mask, the error marker, the saturation cap and
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// the statistics as it goes, so the decompressed image never exists. That is a different code path
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// from the host-upload one, not a reordering of it, and the thing it has to reproduce is the whole
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// observable output - every preprocessed pixel AND every counter - against the CPU preprocessor fed
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// the host-decompressed image.
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//
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// Masked, error and saturated pixels are the interesting part: their priority (masked > error >
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// saturated) and their sentinel outputs (INT32_MIN / INT32_MIN / INT32_MAX) are decided in the fused
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// kernel now, so the image below deliberately contains all three, and the mask deliberately covers
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// some of them.
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namespace {
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DiffractionExperiment MakeExperiment(size_t saturation) {
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DiffractionExperiment x(DetJF4M());
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x.DetectorDistance_mm(80).BeamX_pxl(1030).BeamY_pxl(1080);
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return x;
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}
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template <class T>
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std::vector<T> MakeImage(size_t npixels, T err_value, uint32_t seed) {
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std::mt19937 rng(seed);
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std::vector<T> img(npixels, 0);
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// Sparse background with long runs, so LZ4 produces overlapping matches.
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for (size_t i = npixels / 4; i < npixels / 2; i++)
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img[i] = static_cast<T>(rng() % 11);
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// Bright spots, some above any plausible saturation cap.
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for (size_t s = 0; s < 500; s++) {
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const size_t c = rng() % npixels;
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for (size_t d = 0; d < 5 && c + d < npixels; d++)
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img[c + d] = static_cast<T>(30000 + (rng() % 5000));
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}
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// Explicit error markers, scattered.
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for (size_t s = 0; s < 300; s++)
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img[rng() % npixels] = err_value;
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return img;
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}
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bool SameStats(const ImageStatistics &a, const ImageStatistics &b) {
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return a.max_value == b.max_value && a.min_value == b.min_value
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&& a.masked_pixel_count == b.masked_pixel_count
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&& a.error_pixel_count == b.error_pixel_count
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&& a.saturated_pixel_count == b.saturated_pixel_count;
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}
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// One element size end to end: compress, decode+preprocess on the device, and compare against the
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// host decompression fed through the CPU preprocessor.
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template <class T>
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void CheckFusedMatchesCPU(CompressedImageMode mode, T err_value, uint32_t seed) {
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DiffractionExperiment x = MakeExperiment(32000);
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const size_t npixels = x.GetPixelsNum();
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PixelMask mask(x);
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// Mask a deterministic scatter of pixels, so masked-vs-error-vs-saturated priority is exercised
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// rather than assumed.
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auto &m = const_cast<std::vector<uint32_t> &>(mask.GetMask());
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for (size_t i = 0; i < npixels; i += 997) m[i] = 1;
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for (size_t i = 13; i < npixels; i += 4001) m[i] = 1;
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const auto img = MakeImage<T>(npixels, err_value, seed);
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JFJochBitShuffleCompressor compressor(CompressionAlgorithm::BSHUF_LZ4);
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const std::vector<uint8_t> compressed = compressor.Compress(img);
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const CompressedImage image(compressed.data(), compressed.size(),
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x.GetXPixelsNum(), x.GetYPixelsNum(), mode,
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CompressionAlgorithm::BSHUF_LZ4);
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REQUIRE(BSLZ4DecoderGPU::Supports(image));
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// Reference: host decompression + CPU preprocessing.
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ImagePreprocessorCPU cpu_pre(x, mask);
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ImagePreprocessorBuffer cpu_buf(npixels);
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std::vector<uint8_t> decompression_buffer;
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const uint8_t *raw = image.GetUncompressedPtr(decompression_buffer);
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const ImageStatistics cpu_stats = cpu_pre.Analyze(cpu_buf, raw, mode);
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// Under test: compressed chunk straight to the device, decoded and preprocessed in one pass.
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auto stream = std::make_shared<CudaStream>();
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ImagePreprocessorGPU gpu_pre(x, mask, stream, /*copy_image_to_host=*/true);
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ImagePreprocessorBufferGPU gpu_buf(npixels);
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ImageStatistics gpu_stats{};
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REQUIRE(gpu_pre.AnalyzeCompressed(gpu_buf, image, gpu_stats));
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INFO("mode " << static_cast<int>(mode));
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CHECK(SameStats(cpu_stats, gpu_stats));
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size_t ndiff = 0, first = 0;
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for (size_t i = 0; i < npixels; i++) {
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if (gpu_buf[i] != cpu_buf[i]) {
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if (ndiff == 0) first = i;
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ndiff++;
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}
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}
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INFO("first differing pixel " << first << " cpu " << cpu_buf[first] << " gpu " << gpu_buf[first]
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<< " of " << ndiff << " differing");
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CHECK(ndiff == 0);
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}
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} // namespace
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TEST_CASE("ImagePreprocessorGPU_FusedDecodeMatchesCPU", "[ImagePreprocessorGPU]") {
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if (get_gpu_count() == 0)
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SKIP("No CUDA GPU present");
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CheckFusedMatchesCPU<uint32_t>(CompressedImageMode::Uint32, UINT32_MAX, 1);
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CheckFusedMatchesCPU<uint16_t>(CompressedImageMode::Uint16, UINT16_MAX, 2);
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CheckFusedMatchesCPU<int32_t>(CompressedImageMode::Int32, INT32_MIN, 3);
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CheckFusedMatchesCPU<int16_t>(CompressedImageMode::Int16, INT16_MIN, 4);
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}
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// The host-upload path must keep producing exactly what it did - it is still what every non-LZ4
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// image takes - so the two entry points are held against each other on the same frame.
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TEST_CASE("ImagePreprocessorGPU_FusedMatchesHostUpload", "[ImagePreprocessorGPU]") {
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if (get_gpu_count() == 0)
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SKIP("No CUDA GPU present");
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DiffractionExperiment x = MakeExperiment(32000);
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const size_t npixels = x.GetPixelsNum();
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PixelMask mask(x);
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auto &m = const_cast<std::vector<uint32_t> &>(mask.GetMask());
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for (size_t i = 0; i < npixels; i += 1301) m[i] = 1;
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const auto img = MakeImage<uint32_t>(npixels, UINT32_MAX, 77);
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JFJochBitShuffleCompressor compressor(CompressionAlgorithm::BSHUF_LZ4);
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const std::vector<uint8_t> compressed = compressor.Compress(img);
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const CompressedImage image(compressed.data(), compressed.size(),
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x.GetXPixelsNum(), x.GetYPixelsNum(), CompressedImageMode::Uint32,
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CompressionAlgorithm::BSHUF_LZ4);
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auto stream = std::make_shared<CudaStream>();
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ImagePreprocessorGPU pre(x, mask, stream, /*copy_image_to_host=*/true);
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ImagePreprocessorBufferGPU fused_buf(npixels);
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ImageStatistics fused_stats{};
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REQUIRE(pre.AnalyzeCompressed(fused_buf, image, fused_stats));
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// Same engine, same frame, but decompressed on the host and uploaded.
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std::vector<uint8_t> decompression_buffer;
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const uint8_t *raw = image.GetUncompressedPtr(decompression_buffer);
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ImagePreprocessorBufferGPU upload_buf(npixels);
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const ImageStatistics upload_stats = pre.Analyze(upload_buf, raw, CompressedImageMode::Uint32);
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CHECK(SameStats(fused_stats, upload_stats));
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size_t ndiff = 0;
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for (size_t i = 0; i < npixels; i++) if (fused_buf[i] != upload_buf[i]) ndiff++;
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CHECK(ndiff == 0);
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// Decoding on the device replaced a host decompression, so the cost is still reported as one.
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CHECK(pre.GetLastDecompressionTime_s() > 0.0f);
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}
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#endif
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