Files
Jungfraujoch/tests/SpotTilesTest.cpp
T
leonarski_fandClaude Opus 5.5 d6166f6fa5 Panel layout stage 2: prediction and Bragg integration through the panel table
Everything sparse that took a radial quantity from an image coordinate now takes it from the
reflection's (or spot's) position on the detector plane, through its panel (DetectorModules).
With an empty module table every changed expression reduces to the old one in the same
floating-point order, so flat detectors - every rotation set, EIGER, CCDs, assembled JUNGFRAU -
integrate bit for bit as before.

- Prediction (CPU, GPU, rotation CPU and GPU): bounds test against PlaneBounds instead of the
  image rectangle.
- IntegrateOnImage: a prediction in a gap or off every panel is dropped (PlaneToPanel), no longer
  passed through onto an unrelated stored pixel. The panel id stays local: the engine and the way
  back find it from the image position (the panel boxes tile the image), and a prediction that
  rounding to float put on another panel's edge is dropped so the two agree. Nothing is added to
  Reflection.
- Bragg engines (CPU, CUDA, Metal) take a BraggPanel per reflection (BraggStencil.h): its plane
  position, the panel's pixel axes on the plane and its box. The stencil's radial direction is
  taken on the plane and expressed in the panel's pixel axes; r0, the radial background curve,
  the Gaussian's elongation, the learned moments, tan(2theta) and Finalize's polarisation use the
  plane position; r_max / n_rad come from PlaneBounds. The neighbour mask and the owner map are
  clamped to the reflection's own panel; inside the walked box a pixel off the reflection's panel
  is read as a gap (unreadable, statically masked - not an overload), which is what the assembled
  image has there, so a disk cut by a panel edge is partial rather than silently "full".
- Risk R4: the ProfileEmpirical grid is learned and applied in the plane's axes (the panel axes
  taken to the nearest quarter turn, BraggProfileCell), so turned panels pool one shape. Without
  it the stacked layout read up to 0.3 % off the assembled one in the harness.
- SpotWidth / SpotFootprint: aperture bounds against the spot's panel box, beam distance,
  resolution and the shape's 2theta Jacobian on the plane, moments read in the panel's axes.
- GetDetectorMaxQ_recipA, the far-corner radii (first-pass tilt report, metric-symmetry arm,
  footprint table range) from PlaneBounds; pre-scan spot resolution on the plane;
  LogHeaderBeamCenter: geometric centre of the panels' plane box, and the masked-pixel check on
  the panel the beam lands on (none when it is in a gap).

Harness: PanelLayout_BraggIntegration is now a real [PanelLayout] check, over six settings
(default, bandwidth-elongated ring, radial background, overlap exclude, box sum, empirical
profile, all with polarisation), stacked vs assembled to 1e-5; PanelLayout_BraggIntegrationGPU
runs the same on the CUDA engine. Its spots avoid exact half pixels: the grid centres on the
rounded position, and a half rounds to the other neighbour on a turned panel.

The Metal engine (.metal/.mm) mirrors the CPU change exactly but is UNCOMPILED here (no macOS):
it needs a build and BraggIntegrationEngineMetal_BitIdenticalToCPU on a Mac.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu
2026-10-21 10:40:20 +02:00

149 lines
6.8 KiB
C++

// SPDX-FileCopyrightText: 2026 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#include <catch2/catch_all.hpp>
#include <vector>
#include "../common/CUDAWrapper.h"
#include "../common/DiffractionExperiment.h"
#include "../common/PixelMask.h"
#include "../writer/HDF5Objects.h"
#include "../image_analysis/bragg_integration/SpotWidth.h"
#include "../image_analysis/image_preprocessing/ImagePreprocessorCPU.h"
#include "../image_analysis/spot_finding/ImageSpotFinderCPU.h"
#ifdef JFJOCH_USE_CUDA
#include "../image_analysis/image_preprocessing/ImagePreprocessorBufferGPU.h"
#endif
// The pre-scan measures the spot width and the footprint on squares cut out about each spot instead
// of the whole frame (MeasureSpotsOnTiles). That is only allowed because it gives the whole frame's
// answer to the bit, so this checks exactly that on real diffraction frames - including the spots
// whose footprint window walks off its square and is measured again, on a larger square or on the
// frame, and the frame whose squares would be more than the frame itself.
namespace {
struct Frame {
DiffractionExperiment x;
ImagePreprocessorBuffer image;
std::vector<DiffractionSpot> spots;
};
std::vector<Frame> ReadFrames() {
HDF5ReadOnlyFile data("../../tests/test_data/compression_benchmark.h5");
HDF5DataSet dataset(data, "/entry/data/data");
HDF5DataSpace file_space(dataset);
const auto dim = file_space.GetDimensions();
DiffractionExperiment x(DetDECTRIS(dim[2], dim[1], "Test", {}));
x.PixelSigned(true).DetectorDistance_mm(75).BeamY_pxl(1136).BeamX_pxl(1090).IncidentEnergy_keV(12.4);
const PixelMask mask(x);
ImagePreprocessorCPU preprocessor(x, mask);
ImageSpotFinderCPU finder(static_cast<int32_t>(x.GetXPixelsNumConv()), static_cast<int32_t>(x.GetYPixelsNumConv()));
std::vector<Frame> frames;
std::vector<int16_t> raw(dim[1] * dim[2]);
for (hsize_t i = 0; i < dim[0]; i += 4) {
dataset.ReadVector(raw, {i, 0, 0}, {1, dim[1], dim[2]});
Frame f{x, ImagePreprocessorBuffer(x.GetPixelsNum()), {}};
preprocessor.Analyze(f.image, reinterpret_cast<const uint8_t *>(raw.data()), CompressedImageMode::Int16);
f.spots = finder.Run(f.image, SpotFindingSettings{});
frames.push_back(std::move(f));
}
return frames;
}
bool Same(const std::vector<spot_width::FluxCurve> &a, const std::vector<spot_width::FluxCurve> &b) {
if (a.size() != b.size()) return false;
for (size_t k = 0; k < a.size(); k++) {
const auto &p = a[k], &q = b[k];
if (p.d_A != q.d_A || p.c != q.c || p.shape.valid != q.shape.valid || p.shape.two_theta != q.shape.two_theta
|| p.shape.jr != q.shape.jr || p.shape.jt != q.shape.jt || p.shape.m_rad != q.shape.m_rad
|| p.shape.m_tan != q.shape.m_tan || p.shape.cos_psi != q.shape.cos_psi
|| p.shape.par_u != q.shape.par_u || p.shape.par_v != q.shape.par_v)
return false;
}
return true;
}
bool Same(const std::vector<FootprintSpot> &a, const std::vector<FootprintSpot> &b) {
if (a.size() != b.size()) return false;
for (size_t k = 0; k < a.size(); k++)
if (a[k].r_px != b[k].r_px || a[k].sigma_rad != b[k].sigma_rad || a[k].sigma_tan != b[k].sigma_tan)
return false;
return true;
}
// Every frame through MeasureSpotsOnTiles on `image(f)`, against the whole frame; the misses summed.
template <class Image>
SpotTileMisses CheckFrames(std::vector<Frame> &frames, Image &&image, int half, int footprint_half) {
SpotTileMisses total;
size_t curves = 0, footprints = 0;
for (auto &f : frames) {
const int width = static_cast<int>(f.x.GetXPixelsNumConv()), height = static_cast<int>(f.x.GetYPixelsNumConv());
const auto &g = f.x.GetDiffractionGeometry();
std::vector<spot_width::FluxCurve> c_frame, c_tiles;
std::vector<FootprintSpot> f_frame, f_tiles;
MeasureSpotFluxCurves(f.image, width, height, g, DetectorModules(), f.spots, c_frame);
std::vector<float> sx, sy;
for (const auto &s : f.spots) {
sx.push_back(s.RawCoord().x);
sy.push_back(s.RawCoord().y);
}
MeasureFootprintSpots(f.image.data(), width, height, g.GetBeamX_pxl(), g.GetBeamY_pxl(), sx, sy, f_frame);
const auto misses = MeasureSpotsOnTiles(image(f), width, height, g, DetectorModules(), f.spots, c_tiles, f_tiles,
half, footprint_half);
CHECK(Same(c_frame, c_tiles));
CHECK(Same(f_frame, f_tiles));
total.larger += misses.larger;
total.whole_frame += misses.whole_frame;
curves += c_frame.size();
footprints += f_frame.size();
}
// Something was measured, or the comparison says nothing.
CHECK(curves > 0);
CHECK(footprints > 100);
return total;
}
} // namespace
TEST_CASE("SpotTiles_MatchWholeFrame", "[SpotWidth]") {
auto frames = ReadFrames();
REQUIRE(!frames.empty());
const auto host = [](Frame &f) -> ImagePreprocessorBuffer & { return f.image; };
// As the pre-scan reads them.
CheckFrames(frames, host, SPOT_TILE_HALF, FOOTPRINT_TILE_HALF);
// Squares too small for the footprint: its spots are measured again on the larger squares...
CHECK(CheckFrames(frames, host, spot_width::R_BKG_OUT, spot_width::R_BKG_OUT + 1).larger > 0);
// ... and on the frame, where the larger squares would be more than it.
CHECK(CheckFrames(frames, host, spot_width::R_BKG_OUT, 4000).whole_frame > 0);
// Squares so large that the frame is read instead from the start.
CHECK(CheckFrames(frames, host, 1000, FOOTPRINT_TILE_HALF).whole_frame == 0);
}
#ifdef JFJOCH_USE_CUDA
// The same with the squares cut out on the card, from a device image the host never holds.
TEST_CASE("SpotTiles_MatchWholeFrame_GPU", "[SpotWidth][GPU]") {
if (get_gpu_count() == 0)
SKIP("No GPU");
auto frames = ReadFrames();
REQUIRE(!frames.empty());
ImagePreprocessorBufferGPU device(frames.front().x.GetPixelsNum(), /*host_mirror=*/false);
const auto upload = [&](Frame &f) -> ImagePreprocessorBuffer & {
REQUIRE(cudaMemcpy(device.getGPUBuffer(), f.image.data(), f.image.size() * sizeof(int32_t),
cudaMemcpyHostToDevice) == cudaSuccess);
// From pageable memory cudaMemcpy may return before the copy has landed, and the buffer cuts
// its squares on a non-blocking stream that does not wait for the NULL stream.
REQUIRE(cudaDeviceSynchronize() == cudaSuccess);
return device;
};
CheckFrames(frames, upload, SPOT_TILE_HALF, FOOTPRINT_TILE_HALF);
CHECK(CheckFrames(frames, upload, spot_width::R_BKG_OUT, spot_width::R_BKG_OUT + 1).larger > 0);
CHECK(CheckFrames(frames, upload, spot_width::R_BKG_OUT, 4000).whole_frame > 0);
CheckFrames(frames, upload, 1000, FOOTPRINT_TILE_HALF);
}
#endif