// SPDX-FileCopyrightText: 2025 Filip Leonarski, Paul Scherrer Institute // SPDX-License-Identifier: GPL-3.0-only #include "Merge.h" #include #include #include #include #include #include #include "../../common/CorrelationCoefficient.h" #include "../../common/ResolutionShells.h" #include "HKLKey.h" size_t CalcMergeMaskCC(const DiffractionExperiment &x, const std::vector &scale_cc, std::vector &result_mask) { if (scale_cc.size() != result_mask.size()) throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "Scale CC size mismatch"); size_t n_rejected = 0; auto min_cc = x.GetScalingSettings().GetMinCCForImage(); if (min_cc > 0.0) { for (int i = 0; i < result_mask.size(); ++i) { if (result_mask[i] && (scale_cc[i] < min_cc)) { result_mask[i] = 0; ++n_rejected; } } } return n_rejected; } size_t CalcMergeMaskUnitCell(const DiffractionExperiment &x, const UnitCell &ref_cell, const std::vector > &unit_cells, std::vector &mask) { if (mask.size() != unit_cells.size()) throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "Mismatch in vector size"); size_t n_rejected = 0; const auto dtol = x.GetIndexingSettings().GetUnitCellDistTolerance(); const auto atol = x.GetIndexingSettings().GetUnitCellAngleTolerance_deg(); for (size_t i = 0; i < unit_cells.size(); ++i) { if (mask[i]) { // Counter should not include trivial case (non-indexed image or weird things) // It should only count where indexing did happen, but cell was too far from reference if (!unit_cells[i] || !unit_cells[i]->is_finite()) mask[i] = 0; else if (!unit_cells[i]->is_close(ref_cell, dtol, atol)) { mask[i] = 0; ++n_rejected; } } } return n_rejected; } std::vector MergeAll(const DiffractionExperiment &x, const std::vector > &reflections, const std::vector &merge_mask) { // To select images for half-datasets to calculate CC1/2, I use a random number generator with a fixed seed. // This makes sure that images are selected randomly, but in a fully reproducible manner (at least for the same binary) std::mt19937 rng(123456789u); std::bernoulli_distribution half_dist(0.5); if (!merge_mask.empty() && merge_mask.size() != reflections.size()) throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "Merge mask size mismatch"); auto scaling_settings = x.GetScalingSettings(); HKLKeyGenerator key_generator(scaling_settings.GetMergeFriedel(), x.GetSpaceGroupNumber().value_or(1)); const std::optional high_resolution_limit = scaling_settings.GetHighResolutionLimit_A(); auto min_partiality = scaling_settings.GetMinPartiality(); struct Accum { int32_t h = 0; int32_t k = 0; int32_t l = 0; float d = NAN; double sum_wI = 0.0; double sum_w = 0.0; double sum_wI_half[2] = {0.0, 0.0}; double sum_w_half[2] = {0.0, 0.0}; size_t n_half[2] = {0, 0}; }; std::unordered_map acc; for (int i = 0; i < reflections.size(); ++i) { const int half = half_dist(rng); if (!merge_mask.empty() && merge_mask[i] == 0) continue; if (reflections[i].empty()) continue; for (const auto &r: reflections[i]) { if (key_generator.IsSystematicallyAbsent(r)) continue; if (r.image_scale_corr <= 0.0 || !std::isfinite(r.image_scale_corr)) continue; if (!AcceptReflection(r, high_resolution_limit)) continue; if (r.partiality < min_partiality) continue; const float I_corr = r.I * r.image_scale_corr; const float sigma_corr = r.sigma * r.image_scale_corr; if (!std::isfinite(I_corr) || !std::isfinite(sigma_corr) || sigma_corr <= 0.0) continue; auto hkl = key_generator(r); auto hkl_key = hkl.pack(); auto it = acc.find(hkl_key); if (it == acc.end()) it = acc.emplace(hkl_key, Accum{ .h = hkl.plus ? hkl.h : -hkl.h, .k = hkl.plus ? hkl.k : -hkl.k, .l = hkl.plus ? hkl.l : -hkl.l, }).first; const float w = 1.0f / (sigma_corr * sigma_corr); const float wI = w * I_corr; it->second.sum_wI += wI; it->second.sum_w += w; it->second.sum_wI_half[half] += wI; it->second.sum_w_half[half] += w; it->second.n_half[half]++; if (!std::isfinite(it->second.d) && std::isfinite(r.d) && r.d > 0.0f) it->second.d = r.d; } } std::vector out; out.reserve(acc.size()); for (const auto &[key, accum]: acc) { if (accum.sum_w <= 0.0) continue; MergedReflection mr{ .h = accum.h, .k = accum.k, .l = accum.l, .I = static_cast(accum.sum_wI / accum.sum_w), .sigma = 1.0f / std::sqrt(static_cast(accum.sum_w)), .I_half = {NAN, NAN}, .sigma_half = {NAN, NAN}, .d = accum.d }; if (accum.n_half[0] + accum.n_half[1] > 0 && accum.sum_w_half[0] > 0.0 && accum.sum_w_half[1] > 0.0) { for (int i = 0; i < 2; ++i) { mr.I_half[i] = static_cast(accum.sum_wI_half[i] / accum.sum_w_half[i]); mr.sigma_half[i] = 1.0f / std::sqrt(static_cast(accum.sum_w_half[i])); } } out.emplace_back(mr); } return out; } struct ShellAccum { int total_obs = 0; int unique = 0; int possible = 0; double sum_i_over_sigma = 0.0; int n_i_over_sigma = 0; CorrelationCoefficient cc_half; CorrelationCoefficient cc_ref; }; void CalcPossibleReflections(const DiffractionExperiment &x, const UnitCell &cell, double d_min, double d_max, const ResolutionShells &shells, std::vector &acc) { gemmi::UnitCell gemmi_cell = cell; const gemmi::SpaceGroup *sg = gemmi::find_spacegroup_by_number(x.GetSpaceGroupNumber().value_or(1)); // Generate unique reflections std::vector possible_hkls = gemmi::make_miller_vector(gemmi_cell, sg, d_min, d_max, true); CrystalLattice lattice(cell); const auto astar = lattice.Astar(); const auto bstar = lattice.Bstar(); const auto cstar = lattice.Cstar(); for (const auto& hkl: possible_hkls) { const auto q = hkl[0] * astar + hkl[1] * bstar + hkl[2] * cstar; const auto qlen = q.Length(); if (qlen < 1e-6) continue; const auto d = 1.0 / qlen; const auto shell = shells.GetShell(d); if (!shell.has_value()) continue; const int s = *shell; if (s >= 0 && s < acc.size()) acc[s].possible++; } } MergeStatistics MergeStats(const DiffractionExperiment &x, const std::vector &merged, const std::vector > &reflections, const UnitCell &cell, const std::vector &merge_mask, const std::vector &reference) { if (!merge_mask.empty() && merge_mask.size() != reflections.size()) throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "Merge mask size mismatch"); constexpr int n_shells = 10; float d_min = std::numeric_limits::max(); float d_max = 0.0f; auto min_partiality = x.GetScalingSettings().GetMinPartiality(); auto d_min_limit_A = x.GetScalingSettings().GetHighResolutionLimit_A(); auto scaling_settings = x.GetScalingSettings(); HKLKeyGenerator key_generator(scaling_settings.GetMergeFriedel(), x.GetSpaceGroupNumber().value_or(1)); std::unordered_map reference_intensities; if (!reference.empty()) { reference_intensities.reserve(reference.size()); for (const auto &r: reference) { if (!std::isfinite(r.I)) continue; const auto hkl = key_generator(r); reference_intensities[hkl.pack()] = r.I; } } for (const auto &m: merged) { if (!std::isfinite(m.d) || m.d <= 0.0f) continue; if (d_min_limit_A && m.d < d_min_limit_A) continue; d_min = std::min(d_min, m.d); d_max = std::max(d_max, m.d); } if (!(d_min < d_max && d_min > 0.0f)) throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "MergeStats: Error in resolution calculation"); const float d_min_pad = d_min * 0.999f; const float d_max_pad = d_max * 1.001f; ResolutionShells shells(d_min_pad, d_max_pad, n_shells); const auto shell_mean_1_d2 = shells.GetShellMeanOneOverResSq(); const auto shell_min_res = shells.GetShellMinRes(); std::vector acc(n_shells); CalcPossibleReflections(x, cell, d_min_pad, d_max_pad, shells, acc); CorrelationCoefficient cc_half_overall; CorrelationCoefficient cc_ref_overall; for (const auto &m: merged) { const auto shell = shells.GetShell(m.d); if (!shell.has_value()) continue; const int s = *shell; if (s >= 0 && s < n_shells) { if (std::isfinite(m.I) && std::isfinite(m.sigma) && m.sigma > 0.0) { acc[s].unique++; acc[s].sum_i_over_sigma += m.I / m.sigma; ++acc[s].n_i_over_sigma; if (!reference_intensities.empty()) { const auto hkl = key_generator(m); const auto ref_it = reference_intensities.find(hkl.pack()); if (ref_it != reference_intensities.end() && std::isfinite(ref_it->second)) { acc[s].cc_ref.Add(m.I, ref_it->second); cc_ref_overall.Add(m.I, ref_it->second); } } if (std::isfinite(m.I_half[0]) && std::isfinite(m.I_half[1])) { acc[s].cc_half.Add(m.I_half[0], m.I_half[1]); cc_half_overall.Add(m.I_half[0], m.I_half[1]); } } } } for (int i = 0; i < reflections.size(); ++i) { if (!merge_mask.empty() && merge_mask[i] == 0) continue; for (const auto &r: reflections[i]) { if (key_generator.IsSystematicallyAbsent(r)) continue; if (r.image_scale_corr <= 0.0 || !std::isfinite(r.image_scale_corr)) continue; if (!AcceptReflection(r, d_min_limit_A)) continue; if (r.partiality < min_partiality) continue; const float I_corr = r.I * r.image_scale_corr; const float sigma_corr = r.sigma * r.image_scale_corr; if (!std::isfinite(I_corr) || !std::isfinite(sigma_corr) || sigma_corr <= 0.0f) continue; const auto shell = shells.GetShell(r.d); if (!shell.has_value()) continue; const int s = *shell; if (s >= 0 && s < n_shells) acc[s].total_obs++; } } MergeStatistics out; out.shells.resize(n_shells); for (int s = 0; s < n_shells; ++s) { const auto &sa = acc[s]; auto &ss = out.shells[s]; ss.mean_one_over_d2 = shell_mean_1_d2[s]; ss.d_min = shell_min_res[s]; ss.d_max = s == 0 ? d_max_pad : shell_min_res[s - 1]; ss.total_observations = sa.total_obs; ss.unique_reflections = sa.unique; ss.possible_unique_reflections = sa.possible; ss.mean_i_over_sigma = sa.n_i_over_sigma > 0 ? sa.sum_i_over_sigma / sa.n_i_over_sigma : 0.0; ss.cc_half = sa.cc_half.GetCC(); ss.cc_ref = sa.cc_ref.GetCC(); } auto &overall = out.overall; overall.d_min = d_min; overall.d_max = d_max; int all_possible = 0; int all_unique = 0; double sum_i_over_sigma = 0.0; int n_i_over_sigma = 0; for (const auto &sa: acc) { overall.total_observations += sa.total_obs; all_unique += sa.unique; all_possible += sa.possible; sum_i_over_sigma += sa.sum_i_over_sigma; n_i_over_sigma += sa.n_i_over_sigma; } overall.possible_unique_reflections = all_possible; overall.unique_reflections = all_unique; overall.mean_i_over_sigma = n_i_over_sigma > 0 ? sum_i_over_sigma / n_i_over_sigma : 0.0; overall.cc_half = cc_half_overall.GetCC(); overall.cc_ref = cc_ref_overall.GetCC(); return out; } void MergeStatistics::Print(Logger &logger) const { logger.Info(""); logger.Info(" {:>8s} {:>8s} {:>8s} {:>8s} {:>8s} {:>8s} {:>8s} {:>8s}", "d_min", "N_obs", "N_uniq", "N_possib", "Compl","", "CC1/2", "CCref"); logger.Info(" {:->8s} {:->8s} {:->8s} {:->8s} {:->8s} {:->8s} {:->8s} {:->8s}", "", "", "", "", "", "", "", ""); for (const auto &sh: shells) { if (sh.unique_reflections == 0) continue; double completeness = sh.possible_unique_reflections > 0 ? static_cast(sh.unique_reflections) / sh.possible_unique_reflections * 100.0 : 0.0; logger.Info(" {:8.2f} {:8d} {:8d} {:8d} {:7.1f}% {:8.1f} {:7.1f}% {:7.1f}%", sh.d_min, sh.total_observations, sh.unique_reflections, sh.possible_unique_reflections, completeness, sh.mean_i_over_sigma, sh.cc_half*100.0, sh.cc_ref*100.0); } { const auto &ov = overall; double completeness = ov.possible_unique_reflections > 0 ? static_cast(ov.unique_reflections) / ov.possible_unique_reflections * 100.0 : 0.0; logger.Info(" {:->8s} {:->8s} {:->8s} {:->8s} {:->8s} {:->8s} {:->8s} {:->8s}", "", "", "", "", "", "", "", ""); logger.Info(" {:>8s} {:8d} {:8d} {:8d} {:7.1f}% {:8.1f} {:7.1f}% {:7.1f}%", "Overall", ov.total_observations, ov.unique_reflections, ov.possible_unique_reflections, completeness, ov.mean_i_over_sigma, ov.cc_half*100.0, ov.cc_ref*100.0); } logger.Info(""); }