Jungfraujoch/rugnux/Rugnux.cpp

// SPDX-FileCopyrightText: 2026 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only

#include "Rugnux.h"
#include "ModelValidation.h"

#include <algorithm>
#include <atomic>
#include <chrono>
#include <cmath>
#include <functional>
#include <future>
#include <mutex>
#include <numeric>
#include <set>
#include <sstream>

#include "../reader/JFJochHDF5Reader.h"
#include "../common/Logger.h"
#include "../common/AzimuthalIntegrationMapping.h"
#include "../common/AzimuthalIntegrationProfile.h"
#include "../common/CUDAWrapper.h"
#include "../common/time_utc.h"
#include "../writer/FileWriter.h"
#include "../image_analysis/MXAnalysisWithoutFPGA.h"
#include "../image_analysis/IndexAndRefine.h"
#include "../image_analysis/geom_refinement/GeometryRefiner.h"
#include "../image_analysis/indexing/IndexerThreadPool.h"
#include "../image_analysis/azint/AzIntEngineCPU.h"
#include "../image_analysis/image_preprocessing/ImagePreprocessorCPU.h"
#include "../image_analysis/image_preprocessing/ImagePreprocessorBuffer.h"
#include "../image_analysis/scale_merge/Merge.h"
#include "../image_analysis/scale_merge/RfreeFlags.h"
#include "../image_analysis/scale_merge/RotationScaleMerge.h"
#include "../image_analysis/scale_merge/ResolutionCutoff.h"
#include "../image_analysis/scale_merge/ReindexAmbiguity.h"
#include "../image_analysis/scale_merge/ScalingResult.h"
#include "../image_analysis/scale_merge/SearchSpaceGroup.h"
#include "../image_analysis/geom_refinement/PostRefine.h"
#include "../image_analysis/lattice_search/LatticeSearch.h"
#include "../image_analysis/scale_merge/TwinningAnalysis.h"
#include "../image_analysis/scale_merge/HKLKey.h"
#include "../image_analysis/scale_merge/StillsPartialityRefine.h"
#include "../image_analysis/WriteReflections.h"
#include "../image_analysis/bragg_integration/CalcISigma.h"
#include "../common/Definitions.h"
#include "../common/CorrelationCoefficient.h"
#include <array>
#include <map>

namespace {
    // Pick up to requested_images ordinals spread evenly across [0, images_to_process) for the
    // first pass of two-pass rotation indexing.
    std::vector<int> select_equally_spaced_image_ordinals(int images_to_process, int requested_images) {
        std::vector<int> ret;
        if (images_to_process <= 0 || requested_images <= 0)
            return ret;

        const int n = std::min(images_to_process, requested_images);
        if (n == 1) {
            ret.push_back(0);
            return ret;
        }

        std::set<int> unique_ordinals;
        for (int i = 0; i < n; i++)
            unique_ordinals.insert(static_cast<int>(
                std::llround(static_cast<double>(i) * static_cast<double>(images_to_process - 1) /
                             static_cast<double>(n - 1))));

        ret.assign(unique_ordinals.begin(), unique_ordinals.end());
        return ret;
    }

}

Rugnux::Rugnux(JFJochHDF5Reader &reader, DiffractionExperiment experiment,
                             PixelMask pixel_mask, ProcessConfig config)
    : reader_(reader), experiment_(std::move(experiment)),
      pixel_mask_(std::move(pixel_mask)), config_(std::move(config)) {}

void Rugnux::RefineStillsGeometry(int start_image, int end_image, int images_to_process,
                                  RugnuxObserver *observer) {
    Logger logger("Rugnux");

    // Rotation has its own two-pass; this is stills only.
    if (experiment_.IsRotationIndexing()) {
        logger.Warning("--refine-geometry is stills-only; rotation data uses two-pass indexing. Ignoring.");
        return;
    }
    // The bundle anchors a known cell; without one there is nothing to refine against.
    const auto cell = experiment_.GetUnitCell();
    if (!cell.has_value()) {
        logger.Warning("--refine-geometry needs a reference unit cell (-C / -S / reference MTZ). Skipping.");
        return;
    }

    const int refine_frames = std::max(1, config_.refine_geometry.value());
    if (observer)
        observer->OnPhase("Geometry refinement (first pass)");

    const auto dataset = reader_.GetDataset();

    // Index a spread sample large enough to yield ~refine_frames strong frames even at a low hit rate.
    const int sample_budget = std::min(images_to_process, std::max(refine_frames * 50, 8000));
    const std::vector<int> sample = select_equally_spaced_image_ordinals(images_to_process, sample_budget);

    // First-pass engines, built from the current (nominal) geometry: an index-only pass (no
    // integration) to obtain each frame's spots + assigned HKL + orientation.
    AzimuthalIntegrationMapping mapping(experiment_, pixel_mask_);
    IndexerThreadPool pool(experiment_.GetIndexingSettings());
    IndexAndRefine indexer(experiment_, &pool, /*retain_outcomes=*/false);

    auto pass_settings = config_.spot_finding;
    pass_settings.enable = true;
    pass_settings.indexing = true;
    pass_settings.quick_integration = false;

    std::vector<GeomRefineFrame> frames;
    std::mutex frames_mutex;
    std::atomic<int> next_i = 0;

    auto worker = [&]() {
        pin_gpu();   // round-robin per worker thread; must precede engine construction
        MXAnalysisWithoutFPGA analysis(experiment_, mapping, pixel_mask_, indexer,
                                       /*enable_fused_adaptive_gpu=*/true);
        AzimuthalIntegrationProfile profile(mapping);

        while (!cancelled_) {
            const int idx = next_i.fetch_add(1);
            if (idx >= static_cast<int>(sample.size())) break;
            const int ordinal = sample[idx];
            const int image_idx = start_image + ordinal * config_.stride;

            std::shared_ptr<JFJochReaderRawImage> img;
            try {
                img = reader_.GetRawImage(image_idx);
            } catch (const std::exception &e) {
                logger.Warning("Geometry refinement: failed to load image {}: {}", image_idx, e.what());
                continue;
            }
            if (!img) continue;

            DataMessage msg{};
            msg.image = img->image;
            msg.number = ordinal;
            msg.original_number = image_idx;
            if (dataset->efficiency.size() > image_idx)
                msg.image_collection_efficiency = dataset->efficiency[image_idx];

            try {
                analysis.Analyze(msg, profile, pass_settings);
            } catch (const std::exception &e) {
                continue;
            }
            if (!msg.indexing_result.value_or(false) || !msg.indexing_lattice.has_value())
                continue;

            GeomRefineFrame f;
            f.lattice = *msg.indexing_lattice;
            for (const auto &s : msg.spots)
                if (s.indexed && s.lattice == 0)
                    f.spots.push_back(GeomRefineSpot{s.x, s.y,
                        static_cast<int32_t>(s.h), static_cast<int32_t>(s.k), static_cast<int32_t>(s.l)});
            if (f.spots.size() >= 6) {
                const std::unique_lock ul(frames_mutex);
                frames.push_back(std::move(f));
            }
        }
    };

    std::vector<std::future<void>> futures;
    futures.reserve(config_.nthreads);
    for (int i = 0; i < config_.nthreads; ++i)
        futures.push_back(std::async(std::launch::async, worker));
    for (auto &fut : futures)
        fut.get();

    if (cancelled_)
        return;

    // Keep the strongest frames (most indexed spots) for the bundle - the true cell indexes many
    // spots per frame, and orientation diversity comes for free from independent serial stills.
    constexpr int MIN_STRONG_SPOTS = 20;
    std::vector<GeomRefineFrame> strong;
    for (auto &f : frames)
        if (static_cast<int>(f.spots.size()) >= MIN_STRONG_SPOTS)
            strong.push_back(std::move(f));
    std::sort(strong.begin(), strong.end(),
              [](const GeomRefineFrame &a, const GeomRefineFrame &b) { return a.spots.size() > b.spots.size(); });
    if (static_cast<int>(strong.size()) > refine_frames)
        strong.resize(refine_frames);

    logger.Info("Geometry refinement: indexed {} of {} sampled frames, bundling {} strong frames (>= {} spots)",
                frames.size(), sample.size(), strong.size(), MIN_STRONG_SPOTS);

    GeometryRefinerSettings gr_settings;
    gr_settings.crystal_system = experiment_.GetCrystalSystem();
    gr_settings.num_threads = config_.nthreads;

    const GeometryRefinerResult r = RefineGlobalGeometry(
        experiment_.GetDiffractionGeometry(), *cell, strong, gr_settings);
    if (!r.ok) {
        logger.Warning("Geometry refinement did not run (too few strong frames / did not converge); "
                       "keeping the input geometry");
        return;
    }

    logger.Info("Geometry refinement: beam ({:.2f}, {:.2f}) -> ({:.2f}, {:.2f}) px, distance {:.4f} -> {:.4f} mm",
                experiment_.GetBeamX_pxl(), experiment_.GetBeamY_pxl(), r.beam_x_px, r.beam_y_px,
                experiment_.GetDetectorDistance_mm(), r.distance_mm);
    logger.Info("Geometry refinement: cell a/b/c {:.3f}/{:.3f}/{:.3f} -> {:.3f}/{:.3f}/{:.3f} A "
                "(median residual {:.3f} px, {} frames, {} spots)",
                cell->a, cell->b, cell->c, r.cell.a, r.cell.b, r.cell.c,
                r.median_residual_px, r.frames_used, r.spots_used);

    experiment_.BeamX_pxl(r.beam_x_px).BeamY_pxl(r.beam_y_px).DetectorDistance_mm(r.distance_mm);
    experiment_.SetUnitCell(r.cell);
}

ProcessResult Rugnux::Run(RugnuxObserver *observer) {
    // Rotation two-pass geometry post-refinement: the first pass integrates at the header geometry and
    // post-refines the detector geometry (distance + beam from the observed spot positions, cell scale + axis
    // from phi_obs); the second pass re-indexes and re-integrates with the refined geometry. BOTH passes are
    // written out - the second (refined-geometry) pass is the CANONICAL result and takes the plain "<prefix>_*"
    // name, while the first (header-geometry) pass is kept as "<prefix>_01_*" for comparison - so the two can be
    // compared and the ice-ring flags / geometry stored in each master reflect the geometry that pass used.
    if (config_.mode == ProcessMode::FullAnalysis && config_.rotation_postrefine_geometry
        && experiment_.IsRotationIndexing()) {
        Logger logger("Rugnux");
        const std::string base_prefix = config_.output_prefix;
        const auto gonio_snapshot = experiment_.GetGoniometer();
        prepass_detector_geometry_.reset();
        prepass_result_.reset();
        force_rotation_result_.reset();
        prepass_sg_reindexed_ = false;
        prepass_merge_sg_.reset();

        logger.Info("Rotation two-pass geometry post-refinement: first pass (header geometry) -> {}_01_*",
                    base_prefix);
        // Keep an empty prefix empty (the "compute stats, persist nothing" mode): the "_01" suffix would
        // make it non-empty and RunPipeline would then write stray _01_* files despite no output wanted.
        config_.output_prefix = base_prefix.empty() ? base_prefix : base_prefix + "_01";
        auto pass1 = RunPipeline(observer, /*write_output=*/true, /*geometry_prepass=*/true);
        if (cancelled_) { config_.output_prefix = base_prefix; return pass1; }
        if (gonio_snapshot) experiment_.Goniometer(*gonio_snapshot);   // undo the pre-pass goniometer shift

        // Apply the post-refined detector geometry for the second pass.
        if (prepass_detector_geometry_) {
            const auto &g = *prepass_detector_geometry_;
            experiment_.BeamX_pxl(g[0]).BeamY_pxl(g[1]).DetectorDistance_mm(g[2]);
        }
        // Space group: the second pass RE-INDEXES DE NOVO (clear the group here) so the indexer's pseudo-
        // symmetry safeguards recover the true cell - reusing pass-1's group in the indexer forces build_sr
        // onto a wrong / doubled cell (a huge oblique cell collapses; a pseudo-centred cell doubles). Pass-1's
        // group is instead reinstated for the MERGE ONLY (RunPipeline, before RotationScaleMerge), so the
        // symmetry stays fixed with no re-search / no flip - EXCEPT a reindex-derived group, whose conventional
        // setting the de-novo primitive frame does not share, which is left to re-search.
        experiment_.SpaceGroupNumber(std::nullopt);
        prepass_merge_sg_ = prepass_sg_reindexed_ ? std::nullopt : pass1.space_group_number;

        logger.Info("Rotation two-pass geometry post-refinement: second pass (refined geometry, canonical) -> {}_*",
                    base_prefix);
        config_.output_prefix = base_prefix;   // the refined pass is the canonical result (no _02 suffix)
        auto pass2 = RunPipeline(observer, /*write_output=*/true, /*geometry_prepass=*/false);

        // Supercell-collapse guard for the second pass. The de-novo lattice search can be BISTABLE on a
        // periodically-modulated dataset: the tiny post-refine geometry move tips it out of the true-cell
        // basin onto a spurious SUPERCELL (a large multiple of pass-1's cell volume), and the space group
        // reused from pass-1 is then stamped onto that wrong-shaped cell - catastrophic. Pass 1 (header
        // geometry, un-perturbed) found the correct lattice, so re-run the second pass with pass-1's FULL
        // indexing result forced (its refined lattice + orientation + rotation axis + geometry - not just the
        // cell, which loses the per-frame orientation and integrates worse): the re-run then matches de-novo
        // quality but at the refined geometry. Only fires when pass 2 is markedly LARGER than pass 1 - a
        // genuine de-novo demotion to a smaller primitive (the pseudo-symmetry case the second pass re-indexes
        // de novo to catch) has pass2 <= pass1 and is left untouched.
        if (!cancelled_ && prepass_result_ && pass1.consensus_cell && pass2.consensus_cell) {
            const double v1 = gemmi::UnitCell(*pass1.consensus_cell).volume;
            const double v2 = gemmi::UnitCell(*pass2.consensus_cell).volume;
            if (v1 > 0.0 && v2 > 1.5 * v1) {
                logger.Info("Two-pass: second-pass cell volume {:.0f} A^3 is {:.2f}x pass-1 ({:.0f} A^3) - a "
                            "spurious supercell; re-running the second pass with pass-1's result forced",
                            v2, v2 / v1, v1);
                force_rotation_result_ = *prepass_result_;
                pass2 = RunPipeline(observer, /*write_output=*/true, /*geometry_prepass=*/false);
                force_rotation_result_.reset();
            }
        }
        return pass2;
    }
    return RunPipeline(observer, /*write_output=*/true, /*geometry_prepass=*/false);
}

namespace {
    // Angle between the crystal's symmetry axes and the spindle. A rotation sweep never records the
    // reflections whose reciprocal vector lies close to the spindle - the blind cusp - and normally
    // symmetry fills it in from an equivalent elsewhere in reciprocal space. It cannot when a symmetry
    // axis IS the spindle: the cusp then maps onto itself, every reflection in it is equivalent only to
    // other reflections in it, and the hole stays empty however long the sweep runs. Returns the
    // smallest angle in degrees between any proper rotation axis of the space group and the goniometer
    // axis, with the order of the axis that achieves it.
    std::optional<std::pair<double, int>> ClosestSymmetryAxisToSpindle(const gemmi::SpaceGroup &sg,
                                                                      const CrystalLattice &lattice,
                                                                      const Coord &spindle) {
        const double spindle_len = spindle.Length();
        if (spindle_len < 1e-9)
            return std::nullopt;
        std::optional<std::pair<double, int>> best;
        for (const auto &op : sg.operations().derive_symmorphic().sym_ops) {
            if (op.rot == gemmi::Op::identity().rot)
                continue;
            // Order of the rotation, then project onto its invariant direction by summing its powers:
            // (1/n) sum_k W^k annihilates everything except the axis.
            gemmi::Op acc = gemmi::Op::identity(), w{op.rot, {0, 0, 0}, op.notation};
            int order = 0;
            gemmi::Op cur = gemmi::Op::identity();
            std::array<std::array<double, 3>, 3> sum{};
            for (int k = 0; k < 6; ++k) {
                for (int i = 0; i < 3; ++i)
                    for (int j = 0; j < 3; ++j)
                        sum[i][j] += static_cast<double>(cur.rot[i][j]) / gemmi::Op::DEN;
                cur = cur.combine(w).wrap();
                ++order;
                if (cur.rot == gemmi::Op::identity().rot)
                    break;
            }
            if (order < 2)
                continue;
            // Any non-degenerate column of the projector is the axis in fractional direct coordinates.
            for (int c = 0; c < 3; ++c) {
                const Coord axis = lattice.Vec0() * static_cast<float>(sum[0][c])
                                 + lattice.Vec1() * static_cast<float>(sum[1][c])
                                 + lattice.Vec2() * static_cast<float>(sum[2][c]);
                const double len = axis.Length();
                if (len < 1e-6 * lattice.Vec0().Length())
                    continue;
                const double cosang = std::abs((axis * spindle) / (len * spindle_len));
                const double ang = std::acos(std::min(1.0, cosang)) * 180.0 / M_PI;
                if (!best.has_value() || ang < best->first)
                    best = std::make_pair(ang, order);
                break;
            }
        }
        return best;
    }
}

ProcessResult Rugnux::RunPipeline(RugnuxObserver *observer, bool write_output, bool geometry_prepass) {
    Logger logger("Rugnux");
    ProcessResult result;

    const auto dataset = reader_.GetDataset();
    if (!dataset)
        throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
                              "No experiment dataset found in the input file");

    if (config_.stride <= 0)
        throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "Image stride must be positive");

    const auto total_images_in_file = static_cast<int>(reader_.GetNumberOfImages());
    int end_image = config_.end_image;
    if (end_image < 0 || end_image > total_images_in_file)
        end_image = total_images_in_file;
    const int start_image = config_.start_image;
    const int images_to_process = (end_image - start_image) / config_.stride;
    if (images_to_process <= 0) {
        logger.Warning("No images to process (start {}, end {}, stride {}, total {})",
                       start_image, end_image, config_.stride, total_images_in_file);
        return result;
    }

    const bool full = (config_.mode == ProcessMode::FullAnalysis);
    const bool write_files = write_output && !config_.output_prefix.empty();

    // Output/runtime invariants. Algorithm settings (indexing, scaling, integration, polarization,
    // space group, unit cell, ...) are configured on experiment_ by the caller.
    experiment_.BitDepthImage(32).PixelSigned(true);
    experiment_.Mode(DetectorMode::Standard);
    experiment_.OverwriteExistingFiles(true);
    // Offline processing: the output prefix is a local path the operator chose (rugnux -o or the
    // viewer's "next to the input file"), so use the trusted setter that permits an absolute path.
    experiment_.FilePrefixTrusted(config_.output_prefix.empty() ? "output" : config_.output_prefix);
    experiment_.SetFileWriterFormat(FileWriterFormat::NXmxLegacy);
    experiment_.ImagesPerTrigger(images_to_process);
    experiment_.NumTriggers(1);
    if (full)
        experiment_.Compression(CompressionAlgorithm::BSHUF_LZ4);

    // The pipeline indexes images 0..N-1 within this run; if we process a sub-range/strided
    // selection, shift the goniometer so local index i maps to the angle of original image
    // start+i*stride (keeping the per-image rotation wedge), otherwise rotation angles would be
    // wrong for any start_image != 0.
    if (const auto g = experiment_.GetGoniometer();
        g.has_value() && (start_image != 0 || config_.stride != 1)) {
        const float incr = g->GetIncrement_deg();
        GoniometerAxis shifted(g->GetName(),
                               g->GetStart_deg() + incr * static_cast<float>(start_image),
                               incr * static_cast<float>(config_.stride),
                               g->GetAxis(), g->GetHelicalStep());
        shifted.ScreeningWedge(g->GetScreeningWedge().value_or(incr));
        experiment_.Goniometer(shifted);
    }

    // Stills global geometry-refinement first pass: bundle-adjust the shared beam/distance/cell from a
    // sample of strongly-indexed frames and apply it to experiment_, so everything below (azimuthal
    // mapping, the main index+integrate pass, scaling) uses the refined geometry. Rotation is skipped
    // inside (it has its own two-pass).
    if (full && config_.refine_geometry.has_value())
        RefineStillsGeometry(start_image, end_image, images_to_process, observer);

    AzimuthalIntegrationMapping mapping(experiment_, pixel_mask_);

    JFJochReceiverPlots plots;
    plots.Setup(experiment_, mapping);

    // Output file (NXmxIntegrated master that links back to the original images).
    StartMessage start_message;
    experiment_.FillMessage(start_message);
    start_message.arm_date = dataset->arm_date;
    start_message.az_int_bin_to_q = mapping.GetBinToQ();
    start_message.az_int_bin_to_two_theta = mapping.GetBinToTwoTheta();
    start_message.az_int_q_bin_count = mapping.GetQBinCount();
    start_message.az_int_phi_bin_count = mapping.GetAzimuthalBinCount();
    if (mapping.GetAzimuthalBinCount() > 1)
        start_message.az_int_bin_to_phi = mapping.GetBinToPhi();
    start_message.pixel_mask["default"] = pixel_mask_.GetMask(experiment_);
    if (full) {
        start_message.rois = experiment_.ROI().ExportMetadata();
        if (!experiment_.ROI().empty())
            start_message.roi_map = experiment_.ExportROIMap();
        start_message.max_spot_count = experiment_.GetMaxSpotCount();
    }
    start_message.master_suffix = "process";
    start_message.file_format = FileWriterFormat::NXmxIntegrated;
    start_message.write_master_file = true;
    start_message.write_images = false;
    start_message.hdf5_source_data = reader_.GetHDF5DataSource(start_image, images_to_process);

    std::unique_ptr<FileWriter> writer;
    if (write_files && config_.write_process_h5)
        writer = std::make_unique<FileWriter>(start_message, /*check_overwrite_at_start=*/true,
                                              /*trusted_path=*/true);

    logger.Info("Processing {} images (range {}-{}, stride {}) using {} threads [{}]",
                images_to_process, start_image, end_image, config_.stride, config_.nthreads,
                full ? "full analysis" : "azimuthal integration");
    if (observer)
        observer->OnPhase(full ? "Full analysis" : "Azimuthal integration");

    // Full-analysis shared engines.
    std::unique_ptr<IndexerThreadPool> indexer_pool;
    std::unique_ptr<IndexAndRefine> indexer;
    if (full) {
        auto indexing_settings = experiment_.GetIndexingSettings();
        // Two-pass rotation fires the FFT indexer only twice - the two first-pass schemes, run in
        // parallel (the main per-image loop then uses the forced lattice, no FFT). Size the pool to
        // those two so a rotation run doesn't pay to initialise (cuFFT plan + GPU alloc) indexers it
        // never uses. Stills fire the FFT once per image across all workers, so keep the default there.
        if (config_.rotation_indexing && config_.two_pass_rotation && experiment_.IsRotationIndexing())
            indexing_settings.IndexingThreads(2);
        indexer_pool = std::make_unique<IndexerThreadPool>(indexing_settings);
        indexer = std::make_unique<IndexAndRefine>(experiment_, indexer_pool.get());
        if (!config_.reference_data.empty())
            indexer->ReferenceIntensities(config_.reference_data);
        // Second pass of the rotation two-pass: predict with the smoothed mosaicity fitted in the pre-pass.
        if (!geometry_prepass && !prepass_mosaicity_.empty())
            indexer->SetPredictionMosaicityOverride(prepass_mosaicity_);
    }

    const auto start_time = std::chrono::steady_clock::now();

    // First pass of two-pass rotation indexing (full analysis only).
    if (full && force_rotation_result_.has_value()) {
        // Supercell-collapse fallback: force pass-1's WHOLE indexing result (lattice + refined orientation /
        // search metadata / axis), not just its lattice - a lattice-only force loses that metadata and
        // integrates markedly worse.
        indexer->ForceRotationIndexerResult(*force_rotation_result_);
        logger.Info("Rotation indexer result forced from pass 1 (lattice + geometry) - skipping first pass");
    } else if (full && config_.forced_rotation_lattice.has_value()) {
        indexer->ForceRotationIndexerLattice(*config_.forced_rotation_lattice);
        logger.Info("Rotation indexer lattice forced externally - skipping first pass");
    } else if (full && config_.rotation_indexing && config_.two_pass_rotation) {
        if (observer)
            observer->OnPhase("Rotation indexing (first pass)");

        // Mid-exposure goniometer angle for an image ordinal (matches the per-image path).
        auto rot_angle = [&](int ordinal) -> std::optional<float> {
            if (const auto g = experiment_.GetGoniometer())
                return g->GetAngle_deg(static_cast<float>(ordinal)) + g->GetWedge_deg() / 2.0f;
            return std::nullopt;
        };

        // Reuse stored spots only if the file actually has them: a plain DECTRIS dataset carries no
        // spot-finding results, so "reusing" would leave every frame with zero spots and fail
        // indexing - find them instead. (--redo-rotation-spots already forces finding.)
        const bool reuse_spots = config_.reuse_rotation_spots && reader_.HasStoredSpots();
        if (config_.reuse_rotation_spots && !reuse_spots)
            logger.Info("Dataset has no stored spots - running spot finding for first-pass rotation indexing");

        // Spots for a first-pass image ordinal, cached (a frame is reused across schemes and the
        // validation set; re-finding is expensive on the --redo-rotation-spots path). Accessed only
        // from single-threaded sections (the scheme feed and the validation loop), so no locking.
        std::map<int, std::vector<SpotToSave>> spot_cache;
        auto get_spots = [&](int ordinal) -> const std::vector<SpotToSave> & {
            auto it = spot_cache.find(ordinal);
            if (it != spot_cache.end())
                return it->second;
            const int image_idx = start_image + ordinal * config_.stride;
            std::vector<SpotToSave> spots;
            try {
                if (reuse_spots) {
                    spots = reader_.ReadSpots(image_idx);
                } else if (auto img = reader_.GetRawImage(image_idx)) {
                    DataMessage m{};
                    m.number = ordinal;
                    m.original_number = image_idx;
                    MXAnalysisWithoutFPGA analysis(experiment_, mapping, pixel_mask_, *indexer,
                                                   /*enable_fused_adaptive_gpu=*/true);
                    AzimuthalIntegrationProfile profile(mapping);
                    auto first_pass = config_.spot_finding;
                    first_pass.indexing = false;
                    first_pass.quick_integration = false;
                    m.image = img->image;
                    if (dataset->efficiency.size() > image_idx)
                        m.image_collection_efficiency = dataset->efficiency[image_idx];
                    analysis.Analyze(m, profile, first_pass);
                    spots = std::move(m.spots);
                }
            } catch (const std::exception &e) {
                logger.Warning("First-pass spot read failed for image {}: {}", image_idx, e.what());
            }
            return spot_cache.emplace(ordinal, std::move(spots)).first->second;
        };

        // How many validation frames a candidate global lattice actually indexes per image, scored on
        // the *real* per-image path (force the candidate, then run the same indexing+refinement the
        // main loop uses). A cell that merely fits the accumulated first-pass cloud (a spurious
        // sub-lattice from an under-sampled scheme) indexes few frames, while the true cell indexes
        // many - this is the discriminator that lets the best scheme win.
        const std::vector<int> validation = select_equally_spaced_image_ordinals(
            images_to_process, std::min(images_to_process, 60));
        auto validation_settings = config_.spot_finding;
        validation_settings.indexing = true;
        validation_settings.quick_integration = false;
        auto count_indexed = [&](IndexAndRefine &idx, const RotationIndexerResult &r) -> int {
            idx.ForceRotationIndexerResult(r);
            int count = 0;
            for (const int ordinal : validation) {
                DataMessage m{};
                m.number = ordinal;
                m.spots = get_spots(ordinal);
                if (idx.IndexFrameOnly(m, validation_settings))
                    count++;
            }
            return count;
        };

        // Feed one first-pass scheme (a set of image ordinals) into its own rotation indexer, ready to
        // be indexed. Spots are pulled from the single-threaded cache here; the FFT + refinement runs
        // separately (RunIndexing) so the two schemes' indexing can overlap.
        auto feed_scheme = [&](IndexerThreadPool &pool, const std::vector<int> &ordinals) {
            auto ri = std::make_unique<RotationIndexer>(experiment_, pool);
            for (const int ordinal : ordinals) {
                if (cancelled_ || ri->AccumulationFull())
                    break;
                ri->ProcessImage(ordinal, get_spots(ordinal), rot_angle(ordinal));
            }
            return ri;
        };

        // Sampling schemes, tried in order of preference. We index each and keep the one that indexes
        // the most frames; the schemes cover complementary failure modes and no single one is best for
        // every crystal:
        //  - "spread": images spread over the whole rotation - full angular range, coarse stride; the
        //    long-standing default, best for typical crystals.
        //  - "wedge": consecutive frames from the clean start - native stride keeps each reflection's
        //    rocking curve continuous across frames, so the FFT can trace a long axis whose fine
        //    reciprocal spacing the coarse spread cannot resolve (e.g. an F-cubic cell viewed down
        //    [111]); bounded by the accumulation cap to the least radiation-damaged early wedge.
        std::vector<int> all_consecutive(images_to_process);
        std::iota(all_consecutive.begin(), all_consecutive.end(), 0);
        const std::vector<int> spread_ordinals = select_equally_spaced_image_ordinals(
            images_to_process, config_.rotation_indexing_image_count);
        const std::vector<std::pair<std::string, std::vector<int>>> schemes = {
            {"spread", spread_ordinals},
            {"wedge",  all_consecutive},
        };

        struct FirstPass { std::optional<RotationIndexerResult> result; int score = -1; std::string name; double vol = 0.0; };

        // Feed both schemes (single-threaded spot cache), run their RunIndexing() concurrently, then keep
        // the lattice that indexes the most validation frames on the real per-image path.
        auto pick_best = [&](IndexerThreadPool &pool, IndexAndRefine &idx) -> FirstPass {
            std::vector<std::unique_ptr<RotationIndexer>> ris;
            ris.reserve(schemes.size());
            for (const auto &[name, ordinals] : schemes) {
                if (cancelled_)
                    break;
                ris.push_back(feed_scheme(pool, ordinals));
            }
            std::vector<std::future<void>> index_futures;
            index_futures.reserve(ris.size());
            for (auto &ri : ris) {
                RotationIndexer *rp = ri.get();
                index_futures.push_back(std::async(std::launch::async, [rp] { rp->RunIndexing(); }));
            }
            for (auto &f : index_futures)
                f.get();

            FirstPass bp;
            for (size_t i = 0; i < ris.size(); i++) {
                if (cancelled_)
                    break;
                const auto result = ris[i]->GetLattice();
                if (!result.has_value())
                    continue;
                const int score = count_indexed(idx, *result);
                // Compare PRIMITIVE volumes: two schemes can find the same lattice in different
                // settings, and a centred setting's cell is an exact integer multiple of its primitive
                // one - a rhombohedral lattice in hexagonal axes is exactly 3x its primitive
                // rhombohedral cell. Comparing the centred volumes makes the supercell test below fire
                // on that pair and "demote" a perfectly good setting to a threefold-smaller merge, which
                // is enough to change the space group the search then picks.
                const double vol = std::abs(
                        result->lattice.ToPrimitive(result->search_result.centering).CalcVolume());
                const std::string &name = schemes[i].first;
                logger.Info("First-pass scheme '{}': indexes {}/{} validation frames", name, score,
                            static_cast<int>(validation.size()));

                // A later scheme wins if it indexes clearly more frames (>10%).
                const bool clearly_more = static_cast<float>(score) > bp.score * 1.1f + 0.5f;

                // Integer-supercell tie-break. The validation-frame count saturates - a spurious axis
                // multiple (2x/3x...) indexes every frame its true cell does, so both schemes reach the
                // same frame total and the count alone cannot tell them apart; the default then keeps
                // whichever ran first. When the two schemes tie on frames but their cell volumes are
                // related by an integer factor >=2, the larger cell is that spurious supercell and the
                // smaller is the true reduced cell: take it, regardless of scheme order. A near-integer
                // ratio separates a real axis multiplication from a centering coincidence. Volumes are
                // primitive (see above), so a pure setting difference is a ratio of 1 and never fires.
                bool integer_subcell = false;
                if (bp.result.has_value() && !clearly_more && vol > 1.0 && bp.vol > 1.0) {
                    const bool tied = static_cast<float>(score) >= bp.score * 0.9f - 0.5f;
                    const double ratio = (vol < bp.vol) ? bp.vol / vol : vol / bp.vol;
                    const double nearest = std::round(ratio);
                    const bool integer_multiple = nearest >= 2.0 && std::abs(ratio - nearest) < 0.15;
                    integer_subcell = tied && integer_multiple && vol < bp.vol;
                }

                if (!bp.result.has_value() || clearly_more || integer_subcell) {
                    if (integer_subcell)
                        logger.Info("Scheme '{}' cell (vol {:.0f}) is a {:.0f}x sub-cell of '{}' (vol {:.0f}) at "
                                    "equal frame count - adopting the smaller true cell", name, vol,
                                    std::round(bp.vol / vol), bp.name, bp.vol);
                    bp.score = score;
                    bp.vol = vol;
                    bp.name = name;
                    bp.result = result;
                }
            }
            return bp;
        };

        FirstPass best = pick_best(*indexer_pool, *indexer);

        // Long-axis rescue. When the de-novo cell indexes few validation frames, a long, finely-spaced
        // axis was likely lost: the unconstrained FFT either collapsed it to a short sub-multiple or let
        // a denser supercell over-fit the accumulated cloud (a small global-orientation error throws the
        // many high-order reflections off along the fine axis, so the true cell scores worst on the raw
        // cloud). Recover the true metric with a COARSE-resolution pass - only low-order reflections,
        // where the fine axis stays robust - then RE-INDEX at full resolution constrained by that cell as
        // a reference (the -C path): the reference filter drops the collapsed/supercell candidates and
        // refines an accurate global lattice. Only runs after a poor standard pass, so well-indexing
        // crystals never pay for it and their result is untouched.
        auto max_axis = [](const RotationIndexerResult &r) {
            const auto uc = r.lattice.GetUnitCell();
            return std::max({uc.a, uc.b, uc.c});
        };
        if (!cancelled_ && best.result.has_value()
            && best.score < 0.5 * static_cast<double>(validation.size())) {
            auto coarse_settings = experiment_.GetIndexingSettings();
            coarse_settings.FFT_HighResolution_A(3.5f);   // low-order reflections only -> robust long axis
            coarse_settings.IndexingThreads(2);
            IndexerThreadPool coarse_pool(coarse_settings);
            // Coarse first pass: keep the recovered cell with the LONGEST axis directly. Its full-
            // resolution per-frame validation would be low (the coarse cell is metrically right but
            // imprecise), so do NOT score it here - it is only the reference for the constrained re-index.
            std::vector<std::unique_ptr<RotationIndexer>> cris;
            cris.reserve(schemes.size());
            for (const auto &[name, ordinals] : schemes) {
                if (cancelled_) break;
                cris.push_back(feed_scheme(coarse_pool, ordinals));
            }
            std::vector<std::future<void>> cfut;
            cfut.reserve(cris.size());
            for (auto &ri : cris) {
                RotationIndexer *rp = ri.get();
                cfut.push_back(std::async(std::launch::async, [rp] { rp->RunIndexing(); }));
            }
            for (auto &f : cfut) f.get();
            std::optional<RotationIndexerResult> coarse_ref;
            for (auto &ri : cris) {
                auto r = ri->GetLattice();
                if (r.has_value() && (!coarse_ref.has_value() || max_axis(*r) > max_axis(*coarse_ref)))
                    coarse_ref = r;
            }
            // A recovered axis at least 30% longer than the standard pass found signals a rescued metric.
            if (!cancelled_ && coarse_ref.has_value()
                && max_axis(*coarse_ref) > 1.3 * max_axis(*best.result)) {
                logger.Info("Long-axis rescue: coarse pass recovered a {:.0f} A axis (was {:.0f} A); "
                            "re-indexing constrained by that cell", max_axis(*coarse_ref), max_axis(*best.result));
                experiment_.SetUnitCell(coarse_ref->lattice.GetUnitCell());
                const FirstPass constrained = pick_best(*indexer_pool, *indexer);
                experiment_.SetUnitCell(std::nullopt);   // leave the space-group / cell determination de-novo
                if (constrained.result.has_value() && constrained.score > best.score)
                    best = constrained;
            }
        }

        if (!cancelled_) {
            if (!best.result.has_value())
                throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
                                      "Two-pass rotation indexing failed");
            indexer->ForceRotationIndexerResult(*best.result);
            logger.Info("Two-pass rotation indexing found lattice (scheme '{}': {}/{} validation frames)",
                        best.name, best.score, static_cast<int>(validation.size()));
        }
    }

    // Main per-image loop, spread over N worker threads pulling from a shared counter. HDF5 reads
    // are serialized by the global hdf5_mutex; the analysis runs in parallel.
    std::atomic<int> next_ordinal = 0;
    std::atomic<int> finished_count = 0;
    std::atomic<uint64_t> total_uncompressed_bytes = 0;

    auto azint_worker = [&]() {
        std::vector<uint8_t> decompression_buffer;
        ImagePreprocessorCPU preprocessor(experiment_, pixel_mask_);
        ImagePreprocessorBuffer buffer(experiment_.GetPixelsNum());
        AzIntEngineCPU azint(mapping);
        AzimuthalIntegrationProfile profile(mapping);

        while (!cancelled_) {
            const int ordinal = next_ordinal.fetch_add(1);
            const int image_idx = start_image + ordinal * config_.stride;
            if (image_idx >= end_image) break;

            std::shared_ptr<JFJochReaderRawImage> img;
            try {
                img = reader_.GetRawImage(image_idx);
            } catch (const std::exception &e) {
                logger.Error("Failed to load image {}: {}", image_idx, e.what());
                continue;
            }
            if (!img) continue;

            DataMessage msg{};
            msg.image = img->image;
            msg.number = ordinal;
            msg.original_number = image_idx;
            if (dataset->efficiency.size() > image_idx)
                msg.image_collection_efficiency = dataset->efficiency[image_idx];
            total_uncompressed_bytes += msg.image.GetUncompressedSize();

            const auto t0 = std::chrono::steady_clock::now();
            try {
                const uint8_t *image_ptr = msg.image.GetUncompressedPtr(decompression_buffer);
                preprocessor.Analyze(buffer, image_ptr, msg.image.GetMode());
                azint.Run(buffer, profile);
            } catch (const std::exception &e) {
                logger.Error("Error integrating image {}: {}", image_idx, e.what());
                continue;
            }
            msg.azint_time_s = std::chrono::duration<float>(std::chrono::steady_clock::now() - t0).count();
            msg.processing_time_s = msg.azint_time_s;
            msg.az_int_profile = profile.GetResult();
            msg.az_int_profile_count = profile.GetPixelCount();
            msg.az_int_profile_std = profile.GetStd();
            msg.bkg_estimate = profile.GetBkgEstimate(mapping.Settings());
            msg.ice_ring_score = profile.GetIceRingScore(mapping.Settings(),
                                                         config_.spot_finding.ice_ring_width_Q_recipA);
            msg.run_number = experiment_.GetRunNumber();
            msg.run_name = experiment_.GetRunName();

            plots.Add(msg, profile);
            if (writer) writer->Write(msg);
            if (observer) observer->OnImageProcessed(msg);
            const int done = finished_count.fetch_add(1) + 1;
            if (observer) observer->OnProgress(done, images_to_process);
        }
    };

    auto full_worker = [&]() {
        pin_gpu();   // round-robin per worker thread; must precede engine construction
        MXAnalysisWithoutFPGA analysis(experiment_, mapping, pixel_mask_, *indexer,
                                       /*enable_fused_adaptive_gpu=*/true);
        AzimuthalIntegrationProfile profile(mapping);

        while (!cancelled_) {
            const int ordinal = next_ordinal.fetch_add(1);
            const int image_idx = start_image + ordinal * config_.stride;
            if (image_idx >= end_image) break;

            std::shared_ptr<JFJochReaderRawImage> img;
            try {
                img = reader_.GetRawImage(image_idx);
            } catch (const std::exception &e) {
                logger.Error("Failed to load image {}: {}", image_idx, e.what());
                continue;
            }
            if (!img) continue;

            DataMessage msg{};
            msg.image = img->image;
            msg.number = ordinal;
            msg.original_number = image_idx;
            if (dataset->efficiency.size() > image_idx)
                msg.image_collection_efficiency = dataset->efficiency[image_idx];
            total_uncompressed_bytes += msg.image.GetUncompressedSize();

            const auto t0 = std::chrono::steady_clock::now();
            try {
                analysis.Analyze(msg, profile, config_.spot_finding);
            } catch (const std::exception &e) {
                logger.Error("Error analyzing image {}: {}", image_idx, e.what());
                continue;
            }
            msg.processing_time_s = std::chrono::duration<float>(std::chrono::steady_clock::now() - t0).count();
            msg.run_number = experiment_.GetRunNumber();
            msg.run_name = experiment_.GetRunName();

            plots.Add(msg, profile);
            if (writer) writer->Write(msg);
            if (observer) observer->OnImageProcessed(msg);
            const int done = finished_count.fetch_add(1) + 1;
            if (observer) observer->OnProgress(done, images_to_process);
        }
    };

    if (observer)
        observer->OnPhase("Processing images");

    std::function<void()> worker = full ? std::function<void()>(full_worker)
                                        : std::function<void()>(azint_worker);
    std::vector<std::future<void> > futures;
    futures.reserve(config_.nthreads);
    for (int i = 0; i < config_.nthreads; ++i)
        futures.push_back(std::async(std::launch::async, worker));
    for (auto &f: futures)
        f.get();

    result.cancelled = cancelled_;
    result.images_processed = finished_count.load();

    // Every image failing is a total failure, not a run that produced nothing: it used to be reported
    // only as per-image log lines while the process still exited 0 with no output file.
    if (!cancelled_ && images_to_process > 0 && result.images_processed == 0)
        throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
                              "No image could be analyzed - see the per-image errors above");

    result.mean_processing_time = plots.GetMeanProcessingTime();
    result.indexing_rate = plots.GetIndexingRate();

    // End message (also written to the file).
    EndMessage end_msg;
    end_msg.max_image_number = result.images_processed;
    end_msg.images_collected_count = result.images_processed;
    end_msg.images_sent_to_write_count = result.images_processed;
    end_msg.end_date = time_UTC(std::chrono::system_clock::now());
    end_msg.run_number = experiment_.GetRunNumber();
    end_msg.run_name = experiment_.GetRunName();
    end_msg.bkg_estimate = plots.GetBkgEstimate();
    end_msg.az_int_result["dataset"] = plots.GetAzIntProfile();
    end_msg.indexing_rate = result.indexing_rate;

    if (full && !cancelled_) {
        if (const auto rot = indexer->FinalizeRotationIndexing(); rot.has_value()) {
            end_msg.rotation_lattice = rot->lattice;
            // Write the refined geometry (not the nominal StartMessage values) into the _process.h5.
            end_msg.refined_beam_center_x = rot->geom.GetBeamX_pxl();
            end_msg.refined_beam_center_y = rot->geom.GetBeamY_pxl();
            end_msg.refined_poni_rot1 = rot->geom.GetPoniRot1_rad();
            end_msg.refined_poni_rot2 = rot->geom.GetPoniRot2_rad();
            end_msg.refined_poni_rot3 = rot->geom.GetPoniRot3_rad();
            if (rot->axis)
                end_msg.refined_rotation_axis = rot->axis->GetAxis();
            end_msg.rotation_lattice_type = LatticeMessage{
                .centering = rot->search_result.centering,
                .niggli_class = rot->search_result.niggli_class,
                .crystal_system = rot->search_result.system
            };
            result.rotation_lattice_found = true;
        }
        result.consensus_cell = indexer->GetConsensusUnitCell();
        end_msg.unit_cell = result.consensus_cell;
    }

    // Scaling and merging (full analysis only).
    if (full && !cancelled_ && result.indexing_rate.has_value() && result.indexing_rate > 0
        && (config_.run_scaling || !config_.reference_data.empty())) {
        // Scaling/merging is a long post-pass; report each sub-step as a phase so the GUI progress
        // bar reflects what is happening instead of freezing on one label.
        auto phase = [&](const std::string &p) {
            if (observer) observer->OnPhase(p);
        };
        phase("Scaling and merging");

        // Ice-ring handling (--detect-ice-rings): flag reflections sitting on a hexagonal-ice powder
        // ring. Their integrated intensity is contaminated by the strong, variable ice background, so
        // they drag the per-image scale fit. Flag them here so scaling (the per-image G fit and the
        // fulls refit) skips them, while the combine, the merge and the statistics keep them - dropping
        // them outright guts low/mid-resolution completeness on crystals that merge them fine.
        if (experiment_.IsDetectIceRings()) {
            const float ice_width = config_.spot_finding.ice_ring_width_Q_recipA;
            size_t total = 0, flagged = 0;
            for (auto &outcome : indexer->GetIntegrationOutcome()) {
                for (auto &r : outcome.reflections) {
                    ++total;
                    r.on_ice_ring = IsOnIceRing(r.d, ice_width);
                    if (r.on_ice_ring)
                        ++flagged;
                }
            }
            logger.Info("Ice-ring handling: flagged {} of {} reflections on ice rings (half-width {:.3f} A^-1); "
                        "excluded from scaling, kept for merging", flagged, total, ice_width);
        }

        // Scale the images and merge. Factored so it can run twice: first in P1 to give the
        // space-group search a merged dataset, then again in the determined space group so the
        // scaling sees symmetry equivalents and the final statistics are in the right symmetry.
        // (With a user-fixed space group it simply runs once, already in that symmetry.)
        struct ScaleMergeResult {
            std::vector<MergedReflection> merged;
            MergeStatistics statistics;
        };
        // The reference path computes each image's G once (per-image scaling against the
        // reference); the scaling loop below is skipped, so G is stable across the two passes.
        // Smoothing it more than once would compound the correction, so do it only on the first
        // pass. The no-reference path recomputes G from scratch each pass and re-smooths correctly.
        // Ice rings masked from the merge by the CC1/2 test after the final merge; empty until then,
        // at which point a re-merge applies them.
        std::vector<char> masked_ice_rings;

        // Rotation self-scaling + 3D combine + merge is done by the dedicated RotationScaleMerge (a single
        // allocate-once engine that recomputes partiality from the fitted mosaicity, combines the per-frame
        // partials, scales the fulls and merges; the whole hot path runs on the GPU when one is present).
        // Ingested once here (after ice flagging) and reused across both space-group passes; a fixed
        // (forced) mosaicity is handled by the recompute. The decay + absorption correction surfaces run as
        // post-scale-fulls stages (on by default, see ScalingSettings::CorrectionSurfaces); external-
        // reference scaling, the stills -B (per-image B-factor) and wedge refinement are unsupported here.
        // Two-pass second pass: if the de-novo indexer DEMOTED to a triclinic (primitive) cell while the reused
        // merge space group is higher-symmetry (a huge oblique cell whose constrained centred refine was
        // ill-posed, so the pseudo-symmetry guard kept the primitive), the reflections are in the primitive
        // frame but the merge expects the group's CONVENTIONAL setting - reindex them into it (the same
        // primitive->conventional change of basis the space-group search applies to a demoted result), else the
        // merge folds the wrong equivalents. No-op when the indexer already produced the group's setting.
        if (prepass_merge_sg_ && end_msg.rotation_lattice.has_value() && end_msg.rotation_lattice_type.has_value()
            && end_msg.rotation_lattice_type->crystal_system == gemmi::CrystalSystem::Triclinic) {
            const auto *msg_sg = gemmi::find_spacegroup_by_number(static_cast<int>(*prepass_merge_sg_));
            if (msg_sg && msg_sg->crystal_system() != gemmi::CrystalSystem::Triclinic) {
                const auto cand = LatticeSearch(*end_msg.rotation_lattice);
                // Exact integer reindex prim->conv: P[i][j] = conv_real[i] . rot_reciprocal[j] (as the
                // centred-lattice test), robust to the refined cell not being exactly LatticeSearch's Niggli cell.
                const Coord cv[3] = {cand.conventional.Vec0(), cand.conventional.Vec1(), cand.conventional.Vec2()};
                const Coord rs[3] = {end_msg.rotation_lattice->Astar(), end_msg.rotation_lattice->Bstar(),
                                     end_msg.rotation_lattice->Cstar()};
                gemmi::Mat33 reindex;
                double reindex_res = 0.0;
                for (int i = 0; i < 3; ++i)
                    for (int j = 0; j < 3; ++j) {
                        const double v = cv[i] * rs[j];
                        reindex.a[i][j] = std::round(v);
                        reindex_res = std::max(reindex_res, std::fabs(v - reindex.a[i][j]));
                    }
                // Only when LatticeSearch recovers the reused group's own metric (system + centring): otherwise
                // the reused group and the indexed metric disagree and reindexing would be wrong - leave it.
                if (cand.system == msg_sg->crystal_system() && cand.centering == msg_sg->centring_type()
                    && reindex_res < 0.1) {
                    for (auto &io : indexer->GetIntegrationOutcome()) {
                        io.latt = io.latt.Multiply(reindex);
                        for (auto &r : io.reflections) {
                            const double h = r.h, k = r.k, l = r.l;
                            r.h = static_cast<int32_t>(std::lround(reindex.a[0][0]*h + reindex.a[0][1]*k + reindex.a[0][2]*l));
                            r.k = static_cast<int32_t>(std::lround(reindex.a[1][0]*h + reindex.a[1][1]*k + reindex.a[1][2]*l));
                            r.l = static_cast<int32_t>(std::lround(reindex.a[2][0]*h + reindex.a[2][1]*k + reindex.a[2][2]*l));
                        }
                    }
                    result.consensus_cell = cand.conventional.GetUnitCell();
                    end_msg.unit_cell = result.consensus_cell;
                    end_msg.rotation_lattice = end_msg.rotation_lattice->Multiply(reindex);
                    end_msg.rotation_lattice_type = LatticeMessage{ .centering = cand.centering,
                        .niggli_class = end_msg.rotation_lattice_type->niggli_class, .crystal_system = cand.system };
                    logger.Info("Two-pass: reindexed the de-novo primitive cell into the space-group {} "
                                "conventional setting for the merge", static_cast<int>(*prepass_merge_sg_));
                }
            }
        }

        // Two-pass second pass only: the indexer above ran DE NOVO (Run() cleared the space group so its
        // pseudo-symmetry safeguards find the true cell); now reinstate pass-1's space group for the merge,
        // exactly as a user -S would, so the symmetry is fixed without a re-search. No-op on pass 1 / single pass.
        if (prepass_merge_sg_)
            experiment_.SpaceGroupNumber(*prepass_merge_sg_);

        const auto &rot_ss = experiment_.GetScalingSettings();
        const bool is_rotation = experiment_.IsRotationIndexing();   // rotation indexing -> rotation scaling/merge
        std::optional<RotationScaleMerge> rsm;
        if (is_rotation) {
            if (experiment_.GetRefineRotationWedgeInScaling()
                || rot_ss.GetRotationWedgeForScaling().has_value())
                throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
                                      "Rotation scaling/merging (RotationScaleMerge) does not support "
                                      "wedge refinement");
            // A reference MTZ is allowed for rotation: it fixes the space group / cell (on the CLI) and
            // resolves the indexing ambiguity (below), but is NOT used to scale - the rotation merge stays
            // self-consistent.
            rsm.emplace(experiment_, indexer->GetIntegrationOutcome(), result.consensus_cell,
                        static_cast<int>(config_.scaling_iter),
                        config_.spot_finding.ice_ring_width_Q_recipA,
                        config_.nthreads, logger, config_.observation_dump_path);
            rsm->Ingest();
        }

        auto scale_and_merge = [&](const std::string &label, bool for_search) -> ScaleMergeResult {
            if (rsm) {
                phase("Scale/combine/merge (" + label + ")");
                auto r = rsm->Run(for_search, masked_ice_rings);
                result.error_model_isa = r.isa;
                return ScaleMergeResult{std::move(r.merged), std::move(r.statistics)};
            }
            // Stills (rotation goes through RotationScaleMerge above): self-scale each image against the
            // running merge with ScaleOnTheFly (fixed partiality), then merge directly. This runs even
            // with an external reference: the reference is used only to break the per-image indexing
            // ambiguity and to report CCref / inherit the R-free set, NOT as a scale anchor (scaling each
            // image against a foreign dataset injects cross-dataset systematics and is a worse reference
            // than the data's own merge). One pass: the per-image scale G is the exact one-pass solution,
            // so iterating would only rebuild the reference from the freshly-scaled (noisy) data and
            // degrade weak stills (measured CC1/2 collapse at the default 3 iters).
            {
                phase("Scaling images (" + label + ")");
                auto merge_result = MergeAll(experiment_, indexer->GetIntegrationOutcome());
                indexer->ScaleAllImages(merge_result);
            }
            // Physical partiality post-refinement (default on; --simple-stills disables): refine a per-crystal
            // orientation tilt against the running merge and recompute each reflection's partiality + scale
            // correction (no re-integration). Never for the P1 search pass.
            if (!for_search && experiment_.GetScalingSettings().GetStillsPartialityRefine()) {
                phase("Partiality post-refine (" + label + ")");
                StillsPartialityRefine refiner(experiment_);
                const double mean_tilt = refiner.Run(indexer->GetIntegrationOutcome(), config_.nthreads);
                logger.Info("Stills partiality post-refine: mean |dpsi| = {:.3f} deg", mean_tilt);
            }
            const std::vector<IntegrationOutcome> &merge_input = indexer->GetIntegrationOutcome();

            phase("Merging");
            MergeOnTheFly merge_engine(experiment_);
            // For the de-novo P1 pass (for_search) drop the ice-ring reflections from the merged
            // intensities and the error model, so the space-group search sees clean data; the final
            // in-symmetry merge keeps them so completeness is not lost.
            merge_engine.ExcludeIceRings(for_search);
            merge_engine.MaskIceRings(masked_ice_rings, config_.spot_finding.ice_ring_width_Q_recipA);
            if (result.consensus_cell.has_value())
                merge_engine.ReferenceCell(*result.consensus_cell);
            // Merge-consistency filter: on floods with many spurious lattices (e.g. XFEL large cells)
            // most indexed crystals do not correlate with the true structure; --min-image-cc drops the
            // crystals whose per-image CC to the reference is below the limit, so the merge keeps only
            // the coherent (real) ones. Set before the error model so the model, the merge and the
            // reported statistics are all fitted over the same set of images. The P1 search pass keeps
            // every image: its job is to find the symmetry, not to produce final intensities.
            merge_engine.FilterByImageCC(!for_search
                                         && experiment_.GetScalingSettings().GetMinCCForImage() > 0.0);
            merge_engine.RefineErrorModel(merge_input);
            if (merge_engine.ErrorModelActive())
                logger.Info("Error model: a={:.3f} b={:.3f} ISa={:.1f} chi2={:.2f}", merge_engine.ErrorModelA(),
                            merge_engine.ErrorModelB(),
                            merge_engine.ErrorModelB() > 0 ? 1.0 / merge_engine.ErrorModelB() : 0.0,
                            merge_engine.ErrorModelChi2());
            for (size_t i = 0; i < merge_input.size(); ++i)
                merge_engine.AddImage(merge_input[i], static_cast<int64_t>(i));

            ScaleMergeResult out;
            out.merged = merge_engine.ExportReflections();

            // Automatic high-resolution cutoff (post-merge): trim the written reflections + reported
            // shells to the CC1/2 fall-off. The merge, scaling and error model above ran over the full
            // range, and the _process.h5 is written from the per-image outcomes, so no data is lost. A
            // manual --scaling-high-resolution wins; the P1 search merge (for_search) is never cut so the
            // space-group search still sees the full range. (Rotation is cut inside RotationScaleMerge.)
            const auto &cut_ss = experiment_.GetScalingSettings();
            const std::optional<double> effective_d_min = ApplyResolutionCutoff(
                out.merged, cut_ss.GetHighResolutionLimit_A(), cut_ss.GetResolutionCutoff(),
                cut_ss.GetResolutionCCTarget(), for_search, logger);

            phase("Computing statistics");
            out.statistics = merge_engine.MergeStats(out.merged, merge_input, config_.reference_data, effective_d_min);
            result.error_model_isa = merge_engine.ErrorModelB() > 0 ? 1.0 / merge_engine.ErrorModelB() : 0.0;
            logger.Info("Merge complete ({} unique reflections, {})", out.merged.size(), label);
            return out;
        };

        // First pass: P1 when searching, or directly the user-fixed space group.
        const auto initial_sg = experiment_.GetGemmiSpaceGroup();
        auto sm = scale_and_merge(initial_sg ? initial_sg->short_name() : "P1", !initial_sg.has_value());

        // Rotation two-pass geometry pre-pass: this first scale/merge has now fitted a frame-order-smoothed
        // mosaicity and written it back onto the per-frame outcomes. Capture it for the second pass's Bragg
        // prediction (so prediction uses the smoothed value, not a fresh per-image estimate) and post-refine +
        // apply the detector geometry from this integration. The pre-pass then CONTINUES through the space-
        // group search (below) so the second pass can reuse the same space group and lattice - re-searching at
        // the slightly changed geometry could flip a borderline determination and mix the two passes.
        if (geometry_prepass && rsm && experiment_.IsRotationIndexing()) {
            const auto &outcomes = indexer->GetIntegrationOutcome();
            prepass_mosaicity_.assign(outcomes.size(), NAN);
            for (size_t o = 0; o < outcomes.size(); ++o)
                if (outcomes[o].mosaicity_deg) prepass_mosaicity_[o] = *outcomes[o].mosaicity_deg;
            if (result.consensus_cell.has_value()) {
                if (const auto rot = indexer->FinalizeRotationIndexing(); rot && rot->axis) {
                    prepass_result_ = *rot;   // full result (lattice+geom+axis), for the supercell fallback
                    PostRefineSettings prs;
                    prs.crystal_system = rot->search_result.system;
                    prs.num_threads = static_cast<int>(config_.nthreads);
                    prs.refine_geometry = true;
                    const auto pr = PostRefineRotationGeometry(outcomes, *rot->axis,
                                        experiment_.GetDiffractionGeometry(), rot->lattice, prs, logger);
                    if (pr.ok && pr.detector_refined) {
                        // Store, don't apply: this pass continues to write its own (header-geometry) output;
                        // Run() applies the refined geometry before the second pass.
                        prepass_detector_geometry_ = std::array<float, 3>{
                            static_cast<float>(pr.beam_x_after_px),
                            static_cast<float>(pr.beam_y_after_px),
                            static_cast<float>(pr.distance_after_mm)};
                        logger.Info("Two-pass: post-refined detector geometry (distance {:.3f} mm, "
                                    "beam {:.2f},{:.2f} px) will drive the second integration pass",
                                    pr.distance_after_mm, pr.beam_x_after_px, pr.beam_y_after_px);
                    } else {
                        logger.Info("Two-pass: geometry post-refine committed no detector change "
                                    "- the second pass reproduces the first");
                    }
                }
            }
        }

        // For a de-novo search, gate the P1 scaling+merge (the pass that feeds the space-group search) at
        // <I/sigma> >= 1 over thin resolution shells: noise-dominated high-res shells otherwise mislead
        // the determination, where a single artifact (a zinger the box sum integrates whole, or a
        // weak-reflection profile-fit runaway) has an astronomical resolution-normalised E and wrecks the
        // intensity-correlation / second-moment statistics. The final in-symmetry merge keeps the full
        // range (only this P1 search pass is cut); a manual --scaling-high-resolution, if coarser, wins.
        double d_min_search = 0.0;
        if (!initial_sg.has_value()) {
            std::vector<std::pair<float, float>> rs;   // (d, I/sigma) over the full P1 merge
            rs.reserve(sm.merged.size());
            for (const auto &m : sm.merged)
                if (std::isfinite(m.I) && std::isfinite(m.sigma) && m.sigma > 0.0f &&
                    std::isfinite(m.d) && m.d > 0.0f)
                    rs.emplace_back(m.d, m.I / m.sigma);
            if (rs.size() >= 400) {
                std::sort(rs.begin(), rs.end(),
                          [](const auto &a, const auto &b) { return a.first > b.first; });   // low -> high res
                const int bins = std::clamp(static_cast<int>(rs.size() / 100), 1, 40);
                const size_t per = (rs.size() + bins - 1) / static_cast<size_t>(bins);
                for (size_t b = 0; b * per < rs.size(); ++b) {
                    const size_t lo = b * per, hi = std::min(rs.size(), lo + per);
                    double sum = 0.0;
                    for (size_t j = lo; j < hi; ++j) sum += rs[j].second;
                    if (sum / static_cast<double>(hi - lo) < 1.0) {
                        // Cut the noise-dominated high-res shells, but only when a good low-res region
                        // exists above the cutoff. If even the lowest-res shell (b == 0) is below the
                        // threshold - as happens for very weak data whose I/sigma is floored by the
                        // error model although CC1/2 is still high - there is no clean/noise boundary,
                        // and cutting here would discard essentially all reflections and leave the
                        // re-merge with no resolution range. Leave d_min_search at 0 (no cut) instead.
                        if (b > 0) d_min_search = rs[lo].first;
                        break;
                    }
                }
            }
            const double d_manual = experiment_.GetScalingSettings().GetHighResolutionLimit_A().value_or(0.0);
            if (rsm && d_min_search > d_manual) {
                logger.Info("Space-group search: re-scaling the P1 pass at {:.2f} A (<I/sigma> >= 1)", d_min_search);
                rsm->SetDMinLimit(d_min_search);
                sm = scale_and_merge("P1, space-group search", true);
                rsm->SetDMinLimit(d_manual > 0.0 ? std::optional<double>(d_manual) : std::nullopt);
            }
        }

        std::ostringstream stats_text;
        // Set when the space group was determined via a change of basis (the intensity-based centred-lattice
        // test): its conventional setting does not match the indexer's primitive frame, so the two-pass must
        // NOT reuse it - the second pass re-searches (and re-runs the same test) instead.
        bool sg_reindexed = false;
        // True when the point group below was chosen BY THE SEARCH (rather than given by the user) and is
        // above triclinic - i.e. a promotion was made, which is what makes a later "the Laue class is
        // holohedral so there is no twin law" conclusion circular.
        bool promoted_point_group = false;
        if (!experiment_.GetGemmiSpaceGroup().has_value()) {
            SearchSpaceGroupOptions sg_opts;
            sg_opts.merge_friedel = experiment_.GetScalingSettings().GetMergeFriedel();
            sg_opts.d_min_limit_A = std::max<double>(
                d_min_search, experiment_.GetScalingSettings().GetHighResolutionLimit_A().value_or(0.0));
            // Constrain the search to subgroups of the lattice (metric) symmetry found by rotation
            // indexing. Centering is not constrained here - it is determined from the absences.
            if (end_msg.rotation_lattice_type.has_value())
                sg_opts.lattice_system = end_msg.rotation_lattice_type->crystal_system;
            auto sg_search = SearchSpaceGroup(sm.merged, sg_opts);

            // Second opinion from a merge that keeps only well-measured observations (see
            // RotationScaleMerge::search_min_zeta), and take whichever search found MORE symmetry.
            // The two disagree in one direction only: every crystal on which the Lorentz filter changes
            // the answer LOSES an operator, because discarding 40-80% of the observations starves the
            // operator correlations - it never invents one. So the higher of the two is the safe pick,
            // and it costs nothing on crystals where the filter is irrelevant. Both searches keep their
            // vetoes, so a merohedral twin stays refused in each (verified on a real twin at the three
            // frame ranges where it over-promotes: refused in both arms every time).
            if (rsm && rsm->GetSearchMinZeta() > 0.0 && !sg_search.point_group_hm.empty()) {
                const double zeta = rsm->GetSearchMinZeta();
                rsm->SetSearchMinZeta(0.0);
                auto sm_all = scale_and_merge("P1, all observations", true);
                rsm->SetSearchMinZeta(zeta);
                const auto alt = SearchSpaceGroup(sm_all.merged, sg_opts);
                // Point-group order = the number of rotations, which is what sym_ops holds (centering
                // lives in cen_ops). Taken from the space group the search chose - a point-group symbol
                // like "422" is not a space-group name and cannot be looked up.
                const auto order_of = [](const SearchSpaceGroupResult &r) -> size_t {
                    return r.best_space_group.has_value()
                           ? r.best_space_group->operations().sym_ops.size() : 0;
                };
                logger.Info("Space-group search: all-observation merge -> {} (order {}), "
                            "Lorentz-filtered -> {} (order {})",
                            alt.point_group_hm.empty() ? "?" : alt.point_group_hm, order_of(alt),
                            sg_search.point_group_hm.empty() ? "?" : sg_search.point_group_hm,
                            order_of(sg_search));
                // The filtered merge is used ONLY to rescue a point group the full merge failed to
                // confirm. Everything else - and the screw/centering determination in particular - comes
                // from the merge with all the observations, because systematic absences are decided by
                // the WEAK reflections and the filter throws most of them away. Preferring the filtered
                // arm on a tie cost four crystals their screw axes (P2(1) read as P2) for exactly that
                // reason, with the point group and every intensity statistic identical.
                if (order_of(sg_search) <= order_of(alt)) {
                    if (order_of(alt) > order_of(sg_search))
                        logger.Info("Space-group search: all-observation merge supports {} where the "
                                    "Lorentz-filtered one supports {} - taking the higher symmetry",
                                    alt.point_group_hm, sg_search.point_group_hm);
                    sg_search = alt;
                    sm = std::move(sm_all);
                } else {
                    logger.Info("Space-group search: Lorentz-filtered merge supports {} where the "
                                "all-observation one supports {} - taking the higher symmetry",
                                sg_search.point_group_hm, alt.point_group_hm);
                }
                if (order_of(alt) > 0 && order_of(alt) == order_of(sg_search)
                    && alt.point_group_hm != sg_search.point_group_hm) {
                    // Same order, different symmetry: the two merges disagree about WHICH operators are
                    // real, and neither is higher, so there is nothing to prefer. Say so instead of
                    // picking silently - the two imply different molecular-replacement searches, and
                    // trying both is cheap next to processing the data again.
                    const std::string a = alt.best_space_group.has_value()
                                          ? alt.best_space_group->short_name() : alt.point_group_hm;
                    const std::string b = sg_search.best_space_group.has_value()
                                          ? sg_search.best_space_group->short_name() : sg_search.point_group_hm;
                    const std::string msg = fmt::format(
                        "Space group is AMBIGUOUS between {} and {} (point groups {} and {}, the same "
                        "order): the merge of all observations and the merge of only the well-measured "
                        "ones each support one of them, and neither is the higher symmetry, so the data "
                        "do not decide. Processing continues in {} - try BOTH in molecular replacement, "
                        "or re-run with --search-min-zeta 0 to force the all-observation choice.",
                        a, b, alt.point_group_hm, sg_search.point_group_hm, a);
                    logger.Warning("{}", msg);
                    stats_text << "  !! " << msg << "\n\n";
                }
            }

            // Twinning evidence measured BEFORE any promotion, on the P1/subgroup merge the search was
            // given. Reported alongside the post-adoption analysis: once a higher Laue class has been
            // adopted, its own twinning test can only say "no twin law exists within this class", which
            // is circular - the promotion is what a twin would have caused. These numbers are not.
            const auto pre_promotion_twinning = AnalyzeTwinning(sm.merged, nullptr);
            if (pre_promotion_twinning.twinning_suspected)
                logger.Warning("Twinning indicators BEFORE the space-group decision (subgroup merge): "
                               "<|L|> = {:.3f}, second moment = {:.3f} (untwinned 0.500 / 2.00) - if the "
                               "search promoted the point group, treat the promotion with suspicion",
                               pre_promotion_twinning.mean_abs_l, pre_promotion_twinning.second_moment);
            promoted_point_group = !sg_search.point_group_hm.empty() && sg_search.point_group_hm != "1";
            if (!sg_search.refused_point_group_hm.empty())
                logger.Warning("Higher symmetry {} was confirmed by the operator correlations but refused: "
                               "{}. Processing in the lower symmetry (the recoverable direction).",
                               sg_search.refused_point_group_hm, sg_search.refused_reason);

            // Miller-index reindex under a change of basis: (h,k,l)_conv = reindex * (h,k,l)_prim.
            const auto reindex_hkl = [](auto &r, const gemmi::Mat33 &m) {
                const double h = r.h, k = r.k, l = r.l;
                r.h = static_cast<int32_t>(std::lround(m.a[0][0] * h + m.a[0][1] * k + m.a[0][2] * l));
                r.k = static_cast<int32_t>(std::lround(m.a[1][0] * h + m.a[1][1] * k + m.a[1][2] * l));
                r.l = static_cast<int32_t>(std::lround(m.a[2][0] * h + m.a[2][1] * k + m.a[2][2] * l));
            };

            // Intensity-based centred-lattice test (XDS CORRECT / POINTLESS style). When the indexer
            // demoted to a primitive/triclinic cell but the metric is pseudo-symmetric, the point-group
            // search above tested no operators (its candidate set is bounded by the indexer's lattice).
            // A genuinely centred lattice and a merely pseudo-symmetric triclinic one are indistinguishable
            // from spot POSITIONS - the 2-fold is an INTENSITY property - so decide it here, after P1
            // integration: reindex the P1-merged data to the metric candidate's conventional setting and
            // re-run the search. The I(h) vs I(Rh) correlation confirms a real centred lattice (high CC ->
            // commit the centring) and rejects a pseudo-symmetric triclinic (low CC -> stays P1, no reindex).
            std::optional<gemmi::Mat33> commit_reindex;
            std::optional<UnitCell> commit_cell;
            std::optional<CrystalLattice> commit_lattice;
            std::optional<LatticeMessage> commit_lattice_type;
            // Only a demoted (triclinic) indexing result reaches here with a primitive cell - that is both
            // the case the point-group search could not test (a triclinic holohedry offers no operators)
            // and the case where LatticeSearch's Niggli reduction is valid (it assumes a primitive input).
            const bool searched_trivial = !sg_search.best_space_group || sg_search.best_space_group->number == 1;
            const bool demoted_triclinic = end_msg.rotation_lattice_type.has_value()
                && end_msg.rotation_lattice_type->crystal_system == gemmi::CrystalSystem::Triclinic;
            if (searched_trivial && demoted_triclinic && end_msg.rotation_lattice.has_value()) {
                // The metric only generates the candidate; the intensity CC gate below makes the decision
                // (a false pseudo-symmetry is rejected by the correlation).
                const auto cand = LatticeSearch(*end_msg.rotation_lattice);
                // Exact integer reindex from the indexed setting straight to the candidate conventional
                // setting: P[i][j] = conv_real[i] . rot_reciprocal[j]. Derived from the two lattices, so it
                // holds even if the refined indexed cell is not exactly LatticeSearch's Niggli cell (whose
                // primitive_reduced->conventional reindex would otherwise be applied in the wrong setting).
                const Coord cv[3] = {cand.conventional.Vec0(), cand.conventional.Vec1(), cand.conventional.Vec2()};
                const Coord rs[3] = {end_msg.rotation_lattice->Astar(), end_msg.rotation_lattice->Bstar(),
                                     end_msg.rotation_lattice->Cstar()};
                gemmi::Mat33 reindex;
                double reindex_res = 0.0;
                for (int i = 0; i < 3; ++i)
                    for (int j = 0; j < 3; ++j) {
                        const double v = cv[i] * rs[j];
                        reindex.a[i][j] = std::round(v);
                        reindex_res = std::max(reindex_res, std::fabs(v - reindex.a[i][j]));
                    }
                if (cand.system != gemmi::CrystalSystem::Triclinic && reindex_res < 0.1) {
                    std::vector<MergedReflection> merged_c = sm.merged;
                    for (auto &m : merged_c)
                        reindex_hkl(m, reindex);
                    SearchSpaceGroupOptions o2 = sg_opts;
                    o2.lattice_system = cand.system;
                    const auto s2 = SearchSpaceGroup(merged_c, o2);
                    if (s2.best_space_group.has_value() && s2.best_space_group->number > 1) {
                        // The centring cannot be confirmed from absences here (integrated in the primitive
                        // cell, so the centring-absent reflections do not exist) - it is metric-determined.
                        // Among the point-group-equivalent candidates the intensities cannot separate
                        // (e.g. P2 / P21 / C2), pick the one matching the metric candidate's centring.
                        gemmi::SpaceGroup chosen = *s2.best_space_group;
                        if (chosen.centring_type() != cand.centering)
                            for (const auto &alt : s2.alternatives)
                                if (alt.centring_type() == cand.centering) { chosen = alt; break; }
                        // Commit only if the adopted centring matches the metric candidate whose conventional
                        // cell we reindex into - otherwise the space group and the written cell disagree.
                        if (chosen.centring_type() == cand.centering) {
                            sg_search = s2;
                            sg_search.best_space_group = chosen;
                            commit_reindex = reindex;
                            commit_cell = cand.conventional.GetUnitCell();
                            commit_lattice = end_msg.rotation_lattice->Multiply(reindex);
                            commit_lattice_type = LatticeMessage{ .centering = cand.centering,
                                .niggli_class = end_msg.rotation_lattice_type->niggli_class,
                                .crystal_system = cand.system };
                        }
                    }
                }
            }

            // Adopt the determined space group and re-scale/merge in it, so scaling uses symmetry
            // equivalents and the statistics come out in the right symmetry. P1 stands when nothing
            // is determined.
            if (sg_search.best_space_group.has_value()) {
                const auto &sg = *sg_search.best_space_group;
                logger.Info("Adopting space group {} (number {})", sg.short_name(), sg.number);
                // A reindex is committed only when the intensity re-test confirmed a higher symmetry in a
                // centred setting: bring the integrated reflections + cell into that setting and re-ingest
                // the rotation merge, so the final scaling/merging folds the equivalents correctly.
                if (commit_reindex) {
                    sg_reindexed = true;
                    for (auto &io : indexer->GetIntegrationOutcome()) {
                        io.latt = io.latt.Multiply(*commit_reindex);
                        for (auto &r : io.reflections)
                            reindex_hkl(r, *commit_reindex);
                    }
                    result.consensus_cell = commit_cell;
                    end_msg.unit_cell = commit_cell;
                    // Keep the lattice metadata (hence the master-file UB matrix and indexed-lattice
                    // vectors) in the same conventional setting as the cell, reflections and space group.
                    end_msg.rotation_lattice = commit_lattice;
                    end_msg.rotation_lattice_type = commit_lattice_type;
                    if (rsm) {
                        rsm.emplace(experiment_, indexer->GetIntegrationOutcome(), result.consensus_cell,
                                    static_cast<int>(config_.scaling_iter),
                                    config_.spot_finding.ice_ring_width_Q_recipA,
                                    config_.nthreads, logger, config_.observation_dump_path);
                        rsm->Ingest();
                    }
                }
                experiment_.SpaceGroupNumber(sg.number);
                end_msg.space_group_number = sg.number;
                result.space_group_number = sg.number;
                phase("Re-scaling in space group " + sg.short_name());
                sm = scale_and_merge(sg.short_name(), false);
            }
            result.space_group_search = sg_search;
        } else {
            // A space group was fixed by the user; surface it so the viewer/CLI can still show it.
            result.space_group_number = experiment_.GetSpaceGroupNumber();
        }

        // Rotation two-pass geometry pre-pass: the determined space group is now fixed on experiment_, so the
        // second pass REUSES it instead of re-searching at the slightly changed geometry (which could flip a
        // borderline determination and mix the two passes). The lattice is deliberately NOT forced - the second
        // pass re-indexes at the refined geometry so the CELL comes out self-consistent with it (forcing the
        // pre-pass lattice would pin the nominal cell and undo the geometry refinement). EXCEPTION: a
        // reindex-derived space group (the centred-lattice test) is in a conventional setting the indexer's
        // primitive frame does not share, so reusing it would break the second pass's indexing - remember it so
        // the caller clears it and lets the second pass re-search. Unlike a throwaway pre-pass, this one now
        // CONTINUES to the write below so its own (header-geometry) result is saved as the first pass.
        if (geometry_prepass)
            prepass_sg_reindexed_ = sg_reindexed;

        // Reference-based indexing-ambiguity resolution (rotation). When a reference MTZ is supplied and
        // the crystal has an indexing ambiguity (merohedral: lattice symmetry higher than the Laue group),
        // pick the reindexing that best correlates with the reference intensities and re-merge in it. The
        // twin-law reindex is metric-preserving, so only the hkl labels change (the cell is unchanged).
        // Stills resolve the ambiguity per image with ReindexAmbiguityResolver, not here.
        if (rsm && !config_.reference_data.empty() && result.consensus_cell
            && experiment_.GetSpaceGroupNumber().has_value()) {
            const int sg_num = static_cast<int>(*experiment_.GetSpaceGroupNumber());
            const auto choice = ChooseReindex(
                sm.merged, *result.consensus_cell, sg_num,
                [&](const std::vector<MergedReflection> &m) {
                    return ReferenceIntensityCC(m, config_.reference_data, sg_num);
                });
            if (!choice.is_identity) {
                logger.Info("Reference: resolved indexing ambiguity by reindexing to match the reference "
                            "(CC {:.3f}, vs {:.3f} unchanged)", choice.score, choice.identity_score);
                for (auto &io : indexer->GetIntegrationOutcome())
                    for (auto &r : io.reflections) {
                        const gemmi::Op::Miller h = choice.op.apply_to_hkl({{r.h, r.k, r.l}});
                        r.h = h[0]; r.k = h[1]; r.l = h[2];
                    }
                rsm.emplace(experiment_, indexer->GetIntegrationOutcome(), result.consensus_cell,
                            static_cast<int>(config_.scaling_iter),
                            config_.spot_finding.ice_ring_width_Q_recipA,
                            config_.nthreads, logger, config_.observation_dump_path);
                rsm->Ingest();
                phase("Re-merging in the reference indexing");
                sm = scale_and_merge(experiment_.GetGemmiSpaceGroup()->short_name(), false);
            }
        }

        // Ice-ring CC1/2 mask: a hexagonal-ice ring whose merged half-set CC1/2 collapses well below its
        // resolution shoulders has been decorrelated by ice (its Bragg is unrecoverable) - drop it and
        // re-merge. Weak/absent rings track their neighbours and stay, so completeness on clean crystals
        // is untouched. Uses the ring band (+/- ice width in q=2pi/d) vs the shoulders either side.
        if (experiment_.IsDetectIceRings() && !sm.merged.empty()) {
            constexpr float two_pi = 6.283185307f;
            const float w = config_.spot_finding.ice_ring_width_Q_recipA;
            std::vector<char> mask(ICE_RING_RES_A.size(), 0);
            for (size_t i = 0; i < ICE_RING_RES_A.size(); ++i) {
                const float q_ring = two_pi / ICE_RING_RES_A[i];
                CorrelationCoefficient ring, shoulder;
                size_t n_ring = 0, n_shoulder = 0;
                for (const auto &m : sm.merged) {
                    if (!(m.d > 0.0f) || !std::isfinite(m.I_half[0]) || !std::isfinite(m.I_half[1]))
                        continue;
                    const float dq = std::fabs(two_pi / m.d - q_ring);
                    if (dq < w) { ring.Add(m.I_half[0], m.I_half[1]); ++n_ring; }
                    else if (dq < 3.0f * w) { shoulder.Add(m.I_half[0], m.I_half[1]); ++n_shoulder; }
                }
                if (n_ring >= 20 && n_shoulder >= 20 && shoulder.GetCC() > 0.5
                    && ring.GetCC() < shoulder.GetCC() - 0.05) {
                    mask[i] = 1;
                    logger.Info("Ice-ring mask: {:.2f} A ring CC1/2 {:.3f} << shoulders {:.3f}; masked from merge",
                                ICE_RING_RES_A[i], ring.GetCC(), shoulder.GetCC());
                }
            }
            if (std::any_of(mask.begin(), mask.end(), [](char c) { return c != 0; })) {
                masked_ice_rings = std::move(mask);
                const auto final_sg = experiment_.GetGemmiSpaceGroup();
                sm = scale_and_merge(final_sg ? final_sg->short_name() : "P1", false);
            }
        }

        const auto twin_sg_number = experiment_.GetSpaceGroupNumber();
        const gemmi::SpaceGroup *twin_sg = twin_sg_number
            ? gemmi::find_spacegroup_by_number(twin_sg_number.value()) : nullptr;
        result.twinning = AnalyzeTwinning(sm.merged, twin_sg);
        // Mark the conclusion as non-authoritative when the Laue class was reached by a promotion the
        // search itself made, so the text cannot claim "no twin law exists" on its own say-so.
        result.twinning.laue_class_was_chosen_by_promotion = promoted_point_group;
        stats_text << TwinningAnalysisToText(result.twinning) << "\n";

        // Symmetry axis vs spindle. Reported always on rotation data (it is a property of how the
        // crystal was mounted, which the user can change), warned about when the two nearly coincide.
        if (experiment_.IsRotationIndexing() && twin_sg && end_msg.rotation_lattice.has_value()) {
            if (const auto gonio = experiment_.GetGoniometer()) {
                const auto closest = ClosestSymmetryAxisToSpindle(*twin_sg, *end_msg.rotation_lattice,
                                                                  gonio->GetAxis());
                if (closest.has_value()) {
                    // Practical bound, not a derived one: the blind cone's half-angle is the maximum
                    // Bragg angle (~15 deg for 2 A data at 1 A), and measured on this battery a 13.6 deg
                    // case shows the loss while a 16.2 deg one is 99.7% complete.
                    constexpr double WARN_DEG = 15.0;
                    const auto [angle, order] = *closest;
                    if (angle < WARN_DEG) {
                        const std::string msg = fmt::format(
                            "The crystal's {}-fold axis is only {:.1f} deg from the spindle. A rotation sweep "
                            "never records the reflections whose reciprocal vector lies within the Bragg angle "
                            "of the spindle, and symmetry normally supplies them from an equivalent elsewhere; "
                            "it cannot here, because that axis maps the blind region onto itself. Those "
                            "reflections stay missing however long the sweep runs. The loss is confined to "
                            "that cone rather than spread over the data, so overall completeness may still "
                            "look reasonable - check it near the spindle direction. A second sweep on a "
                            "different axis, or re-mounting, recovers them.",
                            order, angle);
                        logger.Warning("{}", msg);
                        stats_text << "  !! " << msg << "\n\n";
                    } else {
                        stats_text << "Closest symmetry axis to the spindle: " << order << "-fold at "
                                   << std::fixed << std::setprecision(1) << angle << " deg\n\n";
                    }
                }
            }
        }

        // Indexing-ambiguity (alternative-indexing) advisory. When the lattice metric symmetry exceeds
        // the Laue symmetry the crystal can be validly indexed in several hands related by twin-law
        // operators. For an obvious merohedral case (P3/P4/P6...) users expect this; but a PSEUDO-merohedral
        // metric (e.g. a C2 crystal whose beta makes it pseudo-F-orthorhombic) is easy to miss, so surface it. The
        // reindex operator is applied directly to (h,k,l), so its triplet reads as an h,k,l transform.
        if (result.consensus_cell && twin_sg_number) {
            const auto twin_ops = ReindexAmbiguityOperators(*result.consensus_cell,
                                                            static_cast<int>(*twin_sg_number), 2.0);
            if (!twin_ops.empty()) {
                std::string laws;
                for (const auto &op : twin_ops) {
                    std::string t = op.triplet();
                    std::replace(t.begin(), t.end(), 'x', 'h');
                    std::replace(t.begin(), t.end(), 'y', 'k');
                    std::replace(t.begin(), t.end(), 'z', 'l');
                    laws += (laws.empty() ? "" : " ; ") + t;
                }
                if (config_.reference_data.empty()) {
                    const std::string msg = fmt::format(
                        "Indexing ambiguity: this cell / space group admits alternative indexing "
                        "(reindex operator(s): {}). {} are indexed in one hand at random, and rugnux can only "
                        "break this against an external reference. WITHOUT one the merge mixes the hands and "
                        "CC1/2 is degraded - supply a reference (-z reference.mtz or --model) to resolve it.",
                        laws, experiment_.IsRotationIndexing() ? "Lattices" : "Serial-stills crystals");
                    logger.Warning("{}", msg);
                    stats_text << "  !! " << msg << "\n\n";
                } else {
                    logger.Info("Indexing ambiguity present (reindex operator(s): {}); resolved against the "
                                "supplied reference.", laws);
                }
            }
        }

        // Dataset-wide Wilson B-factor estimate (like XDS's WILSON LINE B). Diagnostic only - it is not
        // fed back into scaling; it just lands in the printed statistics, the mmCIF, and the log.
        {
            const GlobalWilsonB wilson = CalcGlobalWilsonB(sm.merged);
            sm.statistics.wilson_b = wilson.b;
            sm.statistics.wilson_b_correlation = wilson.correlation;
            if (std::isfinite(wilson.b) && wilson.b > 0.0)
                logger.Info("Wilson B-factor estimate: {:.2f} A^2 (correlation {:.3f}, {} shells)",
                            wilson.b, wilson.correlation, wilson.n_shells);
        }

        stats_text << sm.statistics;
        result.merge_statistics_text = stats_text.str();
        result.has_merge_statistics = true;
        result.merge_statistics = sm.statistics;
        result.has_reference = !config_.reference_data.empty();

        // Inherit the campaign's shared R-free test set from the reference MTZ (overriding the
        // per-hkl hash that the merge assigned), so every dataset flags the same free reflections.
        if (config_.reference_has_free_flags && !config_.reference_data.empty() && !sm.merged.empty()) {
            const auto sg = experiment_.GetSpaceGroupNumber().value_or(1);
            const size_t matched = ApplyReferenceFreeFlags(sm.merged, static_cast<int32_t>(sg),
                                                           config_.reference_data);
            logger.Info("R-free flags: inherited the reference test set ({} of {} merged reflections matched)",
                        matched, sm.merged.size());
        }

        // Radiation-damage report (rotation): the per-image scale CC-to-merge and mosaicity across the
        // sweep (the per-image scaling the rotation merge already fits, binned by frame = dose). A
        // per-image CC that falls, and/or a mosaicity that rises, with frame number is the classic
        // radiation-damage signature - a data-quality-vs-dose read complementary to the fitted decay
        // correction. The full per-image table is written to <prefix>_scaling.txt for detail.
        if (experiment_.IsRotationIndexing()) {
            const auto &outs = indexer->GetIntegrationOutcome();
            const int nf = static_cast<int>(outs.size());
            constexpr int nb = 10;
            std::array<double, nb> cc_sum{}, mos_sum{};
            std::array<int, nb> cc_n{}, mos_n{};
            for (int f = 0; f < nf; ++f) {
                const int b = nf > 1 ? std::min(nb - 1, f * nb / nf) : 0;
                if (outs[f].image_scale_cc && std::isfinite(*outs[f].image_scale_cc)) {
                    cc_sum[b] += *outs[f].image_scale_cc; cc_n[b]++;
                }
                if (outs[f].mosaicity_deg && std::isfinite(*outs[f].mosaicity_deg)) {
                    mos_sum[b] += *outs[f].mosaicity_deg; mos_n[b]++;
                }
            }
            int tot = 0;
            for (int n : cc_n) tot += n;
            if (tot >= 20) {
                std::ostringstream os;
                os << fmt::format("Radiation-damage report (per-image scale over {} frames):\n", nf);
                os << "     dose        <CC to merge>   <mosaicity deg>\n";
                for (int b = 0; b < nb; ++b) {
                    if (cc_n[b] == 0 && mos_n[b] == 0) continue;
                    os << fmt::format("     {:3d}-{:3d}%        {:>7}         {:>7}\n", b * 10, (b + 1) * 10,
                                      cc_n[b] ? fmt::format("{:.3f}", cc_sum[b] / cc_n[b]) : std::string("-"),
                                      mos_n[b] ? fmt::format("{:.3f}", mos_sum[b] / mos_n[b]) : std::string("-"));
                }
                if (cc_n[0] > 0 && cc_n[nb - 1] > 0) {
                    const double cc0 = cc_sum[0] / cc_n[0], cc9 = cc_sum[nb - 1] / cc_n[nb - 1];
                    os << fmt::format("   => per-image CC to merge {:.3f} (first 10%) -> {:.3f} (last 10%){}",
                                      cc0, cc9,
                                      cc9 < cc0 - 0.05 ? "  (falling: radiation damage / crystal decay)" : "");
                }
                // Relative B-factor across the sweep (measured before any decay correction, against the
                // low-dose start): the resolution-dependent complement to the CC/mosaicity read above. A large
                // magnitude flags radiation damage; positive is the typical direction (high-res fades with dose).
                if (std::isfinite(sm.statistics.radiation_damage_delta_b)) {
                    os << fmt::format("\n   => relative B-factor change over run = {:+.2f} A^2 (first->last){}",
                                      sm.statistics.radiation_damage_delta_b,
                                      std::fabs(sm.statistics.radiation_damage_delta_b) > 5.0
                                          ? "  (significant dose-dependent scaling: radiation damage)" : "");
                    os << fmt::format("\n      per-batch relative-B (A^2, {:.0f} deg/batch):",
                                      sm.statistics.radiation_damage_batch_deg);
                    for (float bb : sm.statistics.radiation_damage_b_batch)
                        os << fmt::format(" {:.1f}", bb);
                }
                logger.Info("{}", os.str());
            }
        }

        if (result.consensus_cell && write_files && config_.write_merged) {
            phase("Writing reflections");
            WriteReflections(sm.merged, *result.consensus_cell, experiment_, sm.statistics,
                             result.error_model_isa > 0 ? fmt::format("{:.2f}", result.error_model_isa) : "?",
                             result.twinning, config_.output_prefix);
            // Per-image scaling table (G, B-factor, mosaicity, wedge, CC) for inspection / XDS
            // comparison. The offline self-scaling result is otherwise not exposed (process.h5's
            // per-image arrays are only filled on the online per-image path). Sourced from the
            // partials, which carry the first-pass per-image scale.
            ScalingResult(indexer->GetIntegrationOutcome()).SaveToFile(config_.output_prefix);
        }

        if (result.consensus_cell && write_files && !config_.model_path.empty()) {
            phase("Validating against model");
            const auto data_sg = experiment_.GetSpaceGroupNumber();
            // With a reference MTZ the merohedral indexing was already resolved against it (rotation
            // merge / stills scaling), so trust that; only probe indexing by R-free when model-only.
            ValidateAgainstModel(sm.merged, *result.consensus_cell, config_.model_path,
                                 config_.output_prefix, logger,
                                 data_sg ? std::optional<int>(static_cast<int>(*data_sg)) : std::nullopt,
                                 /*probe_indexing_ambiguity=*/config_.reference_data.empty());
        }
    }

    if (writer) {
        writer->WriteHDF5(end_msg);
        writer->Finalize();
        result.written_master_path = config_.output_prefix + "_process.h5";
    }

    if (observer)
        observer->OnPhase(cancelled_ ? "Cancelled" : "Done");

    // Total wall time for the whole run, including scaling/merging/writing above (not just the
    // per-image pass), so the reported rate reflects everything rugnux did.
    result.processing_time_s = std::chrono::duration<double>(std::chrono::steady_clock::now() - start_time).count();
    if (result.processing_time_s > 0.0) {
        result.frame_rate_hz = static_cast<double>(result.images_processed) / result.processing_time_s;
        result.throughput_MBs = static_cast<double>(total_uncompressed_bytes) / (result.processing_time_s * 1e6);
    }

    logger.Info("{} {} images in {:.2f} s ({:.2f} Hz)", cancelled_ ? "Cancelled after" : "Processed",
                result.images_processed, result.processing_time_s, result.frame_rate_hz);
    return result;
}