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* Rugnux: Performance improvements on GPU and CPU (more of the pre-scan and of scaling on the GPU, faster CPU spot finding and crystal refinement), with unchanged results. * Rugnux: More robust processing - patches of persistently hot pixels are masked, an inconsistent merge triggers a retry at the measured beam centre, and builds targeting different CPU levels give the same results. * Rugnux: Improved scaling and merging - reflections with an overloaded pixel are dropped, as in XDS, sparse rotation sweeps are scaled more reliably, and French-Wilson amplitudes use an anisotropic Wilson prior. * Rugnux: Improved space-group determination - glide planes in groups without a centre of symmetry, screw axes from short or weak axial rows kept when a higher group is adopted, and more reliable decisions on twinned and pseudo-symmetric crystals. * Rugnux: Improved small-molecule processing - spots that grow wider than the integration disk and split spots are integrated over their measured footprint, sparse lattices are integrated on every frame, and the `.hkl` file holds unmerged scaled reflections (SHELX HKLF 4). * Rugnux: Reads Rigaku d*TREK SMV images (Saturn CCD), including detector 2theta and encoded pixel overflows; home-source (rotating-anode) datasets were added to the validation battery. * jfjoch_viewer: Fixed processing failing at the end with "Wrong JPEG library version" on Linux; the merge window shows the space group with proper subscripts and a checklist of crystal pathologies. Reviewed-on: #84 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
93 lines
4.1 KiB
C++
93 lines
4.1 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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#pragma once
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// The reference the LM solver of XtalRefine is checked against: the same XtalRefineProblem handed to
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// Ceres exactly as XtalOptimizer used to build it - the same residual functors, losses, priors, bounds,
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// manifold and options.
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#include "ceres/ceres.h"
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#include "../image_analysis/geom_refinement/XtalRefine.h"
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struct XtalRefineCeresPrior {
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XtalRefineCeresPrior(double gx, double gy, double p0, double weight)
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: gx(gx), gy(gy), p0(p0), weight(weight) {}
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template<typename T>
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bool operator()(const T *const p, T *residual) const {
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residual[0] = T(weight) * (T(gx) * p[0] + T(gy) * p[1] - T(p0));
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return true;
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}
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double gx, gy, p0, weight;
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};
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inline ceres::Solver::Summary SolveXtalRefineCeres(XtalRefineProblem &p, int num_threads) {
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std::vector<XtalFrameConstants> frame_const;
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frame_const.reserve(p.frame_angle_rad.size());
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if (p.beam_and_orientation_only)
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for (const double angle: p.frame_angle_rad)
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frame_const.emplace_back(p.detector_rot, p.rot_vec, angle, p.latt_vec1, p.latt_vec2, p.crystal_system);
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ceres::Problem problem;
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for (size_t i = 0; i < p.residuals.size(); i++) {
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ceres::LossFunction *loss = p.weight_sq.empty()
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? nullptr
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: new ceres::ScaledLoss(nullptr, p.weight_sq[i], ceres::TAKE_OWNERSHIP);
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if (p.beam_and_orientation_only)
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problem.AddResidualBlock(
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new ceres::AutoDiffCostFunction<XtalResidualBeamOrientation, 3, 2, 3>(
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new XtalResidualBeamOrientation(p.residuals[i], p.distance_mm, frame_const[p.frame[i]])),
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loss, p.beam, p.latt_vec0);
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else
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problem.AddResidualBlock(
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new ceres::AutoDiffCostFunction<XtalResidualFixedDistance, 3, 2, 2, 3, 3, 3, 3>(
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new XtalResidualFixedDistance(p.residuals[i], p.distance_mm)),
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loss, p.beam, p.detector_rot, p.rot_vec, p.latt_vec0, p.latt_vec1, p.latt_vec2);
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}
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for (const auto &prior: p.priors)
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problem.AddResidualBlock(
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new ceres::AutoDiffCostFunction<XtalRefineCeresPrior, 1, 2>(
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new XtalRefineCeresPrior(prior.gx, prior.gy, prior.p0, prior.weight)),
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nullptr, prior.block == XtalRefinePrior::Block::Beam ? p.beam : p.detector_rot);
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const auto bounds = [&](double *block, const double *lo, const double *hi, int n) {
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for (int i = 0; i < n; i++) {
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if (lo[i] > -XtalRefineProblem::kNoBound)
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problem.SetParameterLowerBound(block, i, lo[i]);
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if (hi[i] < XtalRefineProblem::kNoBound)
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problem.SetParameterUpperBound(block, i, hi[i]);
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}
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};
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if (p.beam_constant)
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problem.SetParameterBlockConstant(p.beam);
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if (!p.beam_and_orientation_only) {
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if (p.detector_rot_constant)
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problem.SetParameterBlockConstant(p.detector_rot);
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else
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bounds(p.detector_rot, p.detector_rot_lower, p.detector_rot_upper, 2);
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if (p.rot_vec_constant)
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problem.SetParameterBlockConstant(p.rot_vec);
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else
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problem.SetManifold(p.rot_vec, new ceres::SphereManifold<3>);
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if (p.latt_vec1_constant)
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problem.SetParameterBlockConstant(p.latt_vec1);
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else
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bounds(p.latt_vec1, p.latt_vec1_lower, p.latt_vec1_upper, 3);
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if (p.latt_vec2_constant)
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problem.SetParameterBlockConstant(p.latt_vec2);
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else
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bounds(p.latt_vec2, p.latt_vec2_lower, p.latt_vec2_upper, 3);
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}
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ceres::Solver::Options options;
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options.linear_solver_type = ceres::DENSE_NORMAL_CHOLESKY;
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options.minimizer_progress_to_stdout = false;
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options.max_num_iterations = p.options.max_iterations;
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options.max_solver_time_in_seconds = p.options.max_time_s;
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options.logging_type = ceres::LoggingType::SILENT;
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options.num_threads = num_threads;
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ceres::Solver::Summary summary;
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ceres::Solve(options, &problem, &summary);
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return summary;
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}
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