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Jungfraujoch/image_analysis/scale_merge/ScaleOnTheFly.cpp
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leonarski_fandClaude Opus 5 26fc4b02b3 symmetry: carry the space group as the group, not as its number
The adopted space group travelled the pipeline as a bare int and was rebuilt
downstream with find_spacegroup_by_number, which returns the reference setting.
So every setting a number cannot name was destroyed one line after it was
determined: P 1 1 2 came back as P 1 2 1, I 1 1 2 as C 1 2 1, R 3:R as R 3:H.

DatasetSettings now holds the gemmi::SpaceGroup itself, DiffractionExperiment
exposes it as GetGemmiSpaceGroup() / GetSpaceGroupOrP1(), and everything that
used to take an int - HKLKeyGenerator (its int constructor is gone, so the
compiler finds the callers), the merge, the R-free flags, French-Wilson, the
reindexing ambiguity, the completeness enumeration, the MTZ and mmCIF exports,
the model validation - takes the group. -S keeps the setting the symbol names
rather than reducing it to a number.

The end message carries both spellings and a reader prefers the name, since
only the name keeps the setting while the number is what a reader written
before the name understands. It carries them over CBOR too: the determined
group was never serialised at all, so a group rugnux chose reached the master
file only when the same process wrote it, and an online writer fell back to
whatever the user had supplied at the start. Both keys are optional additions,
so an older reader skips them and a newer one reads an older sender.

On disk the master's /entry/sample/space_group carries the extended
Hermann-Mauguin name and is what the reader takes the group from, so a setting
survives a _process.h5 and the --mode scale that re-reads it; the number stays
beside it and is the fallback for files written before. Every one of the 230
reference settings the old writer could produce reads back as itself, so older
files are unaffected.

Stage A and Stage B of the search still enumerate reference settings only, so
this determines no group differently today - it is what the enumeration needs
before it can be widened.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EFEJG6WBQv8th4UJFNe53N
2026-08-31 07:16:43 +02:00

221 lines
9.0 KiB
C++

// SPDX-FileCopyrightText: 2025 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#include "ScaleOnTheFly.h"
#include "../../common/Logger.h"
#include <algorithm>
#include <chrono>
#include <cmath>
#include <future>
#include <vector>
namespace {
// Robust loss scale (in sigma units) for the per-image scale fit: a few outlier reflections
// (zingers, overlaps, a mis-predicted spot) must not drag a frame's G/B into a bad optimum -
// that is the stochastic per-frame mis-scaling that elevates R-meas and collapses CC1/2 at low
// symmetry. Cauchy down-weights residuals beyond ~this many sigma without a hard cut.
constexpr double SCALE_ROBUST_K = 3.0;
// Smallest per-image scale, relative to the run's median, that is still believable as a scale
// rather than a failed fit. The same ratio guards the rotation path's per-frame scales.
constexpr double MIN_CREDIBLE_SCALE_RATIO = 0.02;
double SafeInv(double x, double fallback) {
if (!std::isfinite(x) || x == 0.0)
return fallback;
return 1.0 / x;
}
// One reflection reduced to the 1-D scale fit: predicted intensity is G * coeff (coeff is constant
// while B is fixed), measured is Iobs, weighted by 1/sigma.
struct ScaleObs {
double coeff;
double Iobs;
double weight;
};
// Robust per-image scale: minimise sum_i Cauchy_k( weight_i (G*coeff_i - Iobs_i) ) over G >= 0. The
// model is linear in G, so this M-estimate is a few reweighted-least-squares steps (each a closed-form
// weighted ratio) - the same objective the Ceres path solves, without a per-image problem/autodiff/
// trust-region. Seeded from the plain weighted-LS solution; Cauchy weight is 1/(1 + (res/k)^2).
double SolveScaleIRLS(const std::vector<ScaleObs> &obs, double robust_k) {
auto weighted_scale = [&obs](auto robust_weight) {
double num = 0.0, den = 0.0;
for (const auto &o: obs) {
const double rw = robust_weight(o);
const double w2 = o.weight * o.weight;
num += rw * w2 * o.coeff * o.Iobs;
den += rw * w2 * o.coeff * o.coeff;
}
return den > 0.0 ? num / den : NAN;
};
double G = weighted_scale([](const ScaleObs &) { return 1.0; });
if (!std::isfinite(G))
return 1.0;
G = std::max(0.0, G);
const double k2 = robust_k * robust_k;
for (int iter = 0; iter < 30; ++iter) {
const double G_prev = G;
const double G_next = weighted_scale([&](const ScaleObs &o) {
const double res = o.weight * (G * o.coeff - o.Iobs);
return 1.0 / (1.0 + res * res / k2);
});
if (!std::isfinite(G_next))
break;
G = std::max(0.0, G_next);
if (std::abs(G - G_prev) <= 1e-7 * std::max(G, 1.0))
break;
}
return G;
}
}
ScaleOnTheFly::ScaleOnTheFly(const DiffractionExperiment &x, const std::vector<MergedReflection> &ref)
: s(x.GetScalingSettings()),
hkl_key_generator(s.GetMergeFriedel(), x.GetSpaceGroupOrP1()) {
for (const auto &r: ref) {
const auto key = hkl_key_generator(r);
reference_data[key] = r.I;
}
}
bool ScaleOnTheFly::Accept(const Reflection &r) const {
if (r.on_ice_ring) // ice-contaminated intensity would drag the per-image scale; keep it out of the fit
return false;
return AcceptReflection(r, s.GetHighResolutionLimit_A(), s.GetLowResolutionLimit_A());
}
void ScaleOnTheFly::Scale(IntegrationOutcome &integration_outcome) const {
if (integration_outcome.reflections.empty())
return;
ScaleOnTheFlyResult result{ .G = 1.0 };
auto clear_scale = [&]() {
integration_outcome.image_scale_cc.reset();
integration_outcome.image_scale_cc_n.reset();
integration_outcome.image_scale_g.reset();
};
// The fixed-partiality model G * coeff is linear in G, so the robust per-image scale is a 1-D
// M-estimate solved directly (IRLS) rather than a Ceres problem per image.
{
std::vector<ScaleObs> obs;
obs.reserve(integration_outcome.reflections.size());
for (const auto &r: integration_outcome.reflections) {
if (!Accept(r))
continue;
const auto it = reference_data.find(hkl_key_generator(r));
if (it == reference_data.end())
continue;
const double coeff = r.partiality * SafeInv(r.rlp, 1.0) * it->second;
obs.push_back({coeff, static_cast<double>(r.I), SafeInv(r.sigma, 1.0)});
}
if (obs.size() < MIN_REFLECTIONS) {
clear_scale();
return;
}
result.G = SolveScaleIRLS(obs, SCALE_ROBUST_K);
}
for (auto &r: integration_outcome.reflections) {
const double denom = r.partiality * result.G;
r.image_scale_corr = (std::isfinite(r.rlp) && std::isfinite(denom) && denom > 0.0)
? static_cast<float>(r.rlp / denom)
: NAN;
}
const auto [cc, cc_n] = ImageReferenceCC(integration_outcome.reflections, reference_data,
hkl_key_generator, s.GetHighResolutionLimit_A(),
s.GetLowResolutionLimit_A(), s.GetMinPartiality());
result.cc = cc;
result.cc_n = cc_n;
integration_outcome.image_scale_cc = cc;
integration_outcome.image_scale_cc_n = cc_n;
integration_outcome.image_scale_g = result.G;
integration_outcome.image_scale_wedge_deg.reset();
}
// A per-image scale that has collapsed toward zero multiplies that image's intensities by 1/G - and its
// sigmas by the same factor, so nothing downstream can recognise it: the merge's n-sigma outlier test
// scales with the very number that is wrong. The rotation path already refuses a per-frame scale this
// far below its neighbours; the stills path had no such guard.
//
// Such an image is DROPPED from the merge, not merged unscaled. Substituting G = 1 looks conservative
// but is the more damaging of the two errors: if the collapsed value was a failed fit, the image goes in
// mis-scaled by an unknown factor, and if it was a real scale (per-crystal scales on serial stills
// genuinely span orders of magnitude, unlike frames of one rotation sweep) then G = 1 divides both its
// intensities AND its sigmas by 1/G, so it enters at 1/G^2 times the weight it deserves - the merge
// cannot down-weight it, because the number that is wrong is the same number the weight is built from.
// An image whose scale is not believable has no usable scale, so it contributes nothing instead.
void ScaleOnTheFly::RejectCollapsedScales(std::vector<IntegrationOutcome> &integration) {
std::vector<double> fitted;
fitted.reserve(integration.size());
for (const auto &i: integration)
if (i.image_scale_g && std::isfinite(*i.image_scale_g) && *i.image_scale_g > 0.0)
fitted.push_back(*i.image_scale_g);
if (fitted.size() < 2)
return;
const size_t mid = fitted.size() / 2;
std::nth_element(fitted.begin(), fitted.begin() + mid, fitted.end());
const double g_floor = fitted[mid] * MIN_CREDIBLE_SCALE_RATIO;
int64_t n_rejected = 0;
for (auto &i: integration) {
if (!i.image_scale_g || !std::isfinite(*i.image_scale_g) || *i.image_scale_g >= g_floor)
continue;
// A non-finite correction is what every merge path already skips on (Merge.cpp), so this drops
// the image consistently from the merged intensities, the error model and the statistics.
for (auto &r: i.reflections)
r.image_scale_corr = NAN;
i.image_scale_cc.reset();
i.image_scale_cc_n.reset();
i.image_scale_g.reset();
++n_rejected;
}
if (n_rejected > 0)
Logger("ScaleOnTheFly").Warning(
"Dropped {} image(s) from the merge: their per-image scale collapsed more than {:.0f}x below "
"the run median, so it is not a scale the intensities can be put on",
n_rejected, 1.0 / MIN_CREDIBLE_SCALE_RATIO);
}
void ScaleOnTheFly::Scale(std::vector<IntegrationOutcome> &integration, size_t nthreads) const {
if (nthreads == 0)
nthreads = std::thread::hardware_concurrency();
if (nthreads <= 1) {
for (auto & i : integration)
Scale(i);
} else {
auto local_nthreads = std::min(nthreads, integration.size());
std::vector<std::future<void>> futures;
futures.reserve(local_nthreads);
std::atomic<size_t> curr_image = 0;
for (size_t t = 0; t < local_nthreads; ++t)
futures.emplace_back(std::async(std::launch::async, [&] {
size_t i = curr_image.fetch_add(1);
while (i < integration.size()) {
Scale(integration[i]);
i = curr_image.fetch_add(1);
}
}));
for (auto &f: futures)
f.get();
}
RejectCollapsedScales(integration);
}