leonarski_fandClaude Opus 5.5
d6166f6fa5
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
99 lines
5.5 KiB
C++
99 lines
5.5 KiB
C++
// SPDX-FileCopyrightText: 2026 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
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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 <cmath>
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#include <random>
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#include <vector>
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#include "../common/DiffractionGeometry.h"
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#include "../image_analysis/SensorAbsorption.h"
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#include "../image_analysis/bragg_integration/SpotWidth.h"
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namespace {
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constexpr int W = 3000, H = 3000, C = 1500;
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constexpr double DIST_MM = 100.0, PIXEL_MM = 0.075, LAMBDA_A = 1.0;
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constexpr double THICKNESS_UM = 450.0;
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constexpr double ANGULAR_SIGMA = 1.5e-4; // rad: divergence and crystal, the same in every direction
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// Spots on an untilted detector, each an elliptical Gaussian with its long axis along the radius:
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// the isotropic angular width, the bandwidth's radial streak 2 tan(theta) sigma, and the sensor
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// parallax - a conversion depth z moves the photon by z tan(psi) along the radius, and on an
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// untilted detector psi = 2theta. Worked out here from the flat-detector geometry, independently
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// of the estimator's own Jacobians: R = D tan(2theta), so one radian of 2theta is D/cos^2(2theta)
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// along the radius and one radian across the scattering plane D/cos(2theta) across it. Painted
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// with 4x4 sub-pixel sampling so each pixel carries the box it integrates, and Poisson noise.
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void PaintSpots(std::vector<int32_t> &image, std::vector<DiffractionSpot> &spots, double bw_fwhm,
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int offset, std::mt19937 &rng) {
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const double sigma_bw = bw_fwhm / 2.3548;
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const double L_um = sensor_absorption::AttenuationLength_um("Si", LAMBDA_A);
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std::vector<double> mean(image.size(), 3.0);
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for (int cy = 40 + offset; cy < H - 40; cy += 60)
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for (int cx = 40 + offset; cx < W - 40; cx += 60) {
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const double rx = (cx - C) * PIXEL_MM, ry = (cy - C) * PIXEL_MM, r = std::hypot(rx, ry);
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if (r < 8.0) continue;
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const double tt = std::atan2(r, DIST_MM), c2 = std::cos(tt);
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const double jr = DIST_MM / (PIXEL_MM * c2 * c2), jt = DIST_MM / (PIXEL_MM * c2);
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const double depth_var = sensor_absorption::ConversionDepthVariance_um2(L_um * c2, THICKNESS_UM);
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const double par = depth_var * std::tan(tt) * std::tan(tt) / (PIXEL_MM * 1000.0 * PIXEL_MM * 1000.0);
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const double streak = 2.0 * std::tan(tt / 2.0) * sigma_bw;
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const double var_u = jr * jr * (ANGULAR_SIGMA * ANGULAR_SIGMA + streak * streak) + par;
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const double var_v = jt * jt * ANGULAR_SIGMA * ANGULAR_SIGMA;
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const double ux = rx / r, uy = ry / r;
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const double total = 20000.0;
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const double norm = total / (2.0 * M_PI * std::sqrt(var_u * var_v) * 16.0);
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for (int dy = -14; dy <= 14; dy++)
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for (int dx = -14; dx <= 14; dx++) {
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double v = 0.0;
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for (int sy = 0; sy < 4; sy++)
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for (int sx = 0; sx < 4; sx++) {
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const double px = dx - 0.375 + 0.25 * sx, py = dy - 0.375 + 0.25 * sy;
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const double u = px * ux + py * uy, t = -px * uy + py * ux;
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v += std::exp(-0.5 * (u * u / var_u + t * t / var_v));
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}
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mean[static_cast<size_t>(cy + dy) * W + cx + dx] += norm * v;
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}
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spots.emplace_back(static_cast<uint32_t>(cx), static_cast<uint32_t>(cy),
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static_cast<int64_t>(total));
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}
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for (size_t i = 0; i < image.size(); i++)
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image[i] = std::poisson_distribution<int32_t>(mean[i])(rng);
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}
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std::optional<spot_width::BandwidthEstimate> Estimate(double bw_fwhm) {
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DiffractionGeometry geometry;
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geometry.BeamX_pxl(C).BeamY_pxl(C).DetectorDistance_mm(DIST_MM).PixelSize_mm(PIXEL_MM)
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.Wavelength_A(LAMBDA_A);
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std::mt19937 rng(7);
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std::vector<spot_width::FluxCurve> curves;
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for (int offset : {0, 20, 40}) {
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ImagePreprocessorBuffer image(static_cast<size_t>(W) * H);
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std::vector<DiffractionSpot> spots;
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PaintSpots(image.getBuffer(), spots, bw_fwhm, offset, rng);
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MeasureSpotFluxCurves(image, W, H, geometry, DetectorModules(), spots, curves);
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}
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return spot_width::EstimateBandwidth(curves, sensor_absorption::AttenuationLength_um("Si", LAMBDA_A),
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THICKNESS_UM, PIXEL_MM * 1000.0);
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}
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}
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// A 0.45 % FWHM bandwidth - a multilayer's - on a thick silicon sensor, whose parallax elongates the
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// spots along the radius as well and grows with angle much as the bandwidth does. The estimator has
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// to take the parallax out from the sensor's physics and return the bandwidth, significantly.
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TEST_CASE("BandwidthEstimate_RecoversBandwidthPastParallax", "[SpotWidth]") {
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const auto e = Estimate(0.0045);
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REQUIRE(e.has_value());
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CHECK(e->spots >= spot_width::BANDWIDTH_MIN_SPOTS);
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CHECK(e->fwhm == Catch::Approx(0.0045).margin(0.0006));
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CHECK(e->z > spot_width::BANDWIDTH_Z);
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}
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// The same spots from a monochromatic beam: the parallax alone must not read as a bandwidth.
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TEST_CASE("BandwidthEstimate_MonochromaticIsNotSignificant", "[SpotWidth]") {
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const auto e = Estimate(0.0);
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REQUIRE(e.has_value());
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CHECK(e->z < spot_width::BANDWIDTH_Z);
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CHECK(std::abs(e->fwhm) < 0.0015);
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}
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