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Jungfraujoch/image_analysis/spot_finding/SpotUtils.cpp
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leonarski_fandClaude Opus 5.5 0a515bb086 rc179: everything on rc178 after its merge into main (#88), except the CHANGELOG
The rc178 branch continued after #88 was squash-merged; this is its content from b9ada7914 (the tree
#88 squashed) to 094eee31a, as one change on main. The individual commits stay on the rc178 branch:

- still battery: --cold evicts each set's input from the page cache; Alvra pixel masks; manifest fixes
- AGIPD: converter to one rigid panel per module, int16 photons, mask folded in; still battery reads the converted sets
- DetectorModules: panel look-up by id, plane -> panel, plane bounds and a per-pixel walk; mask size checked
- tests: [PanelLayout] equivalence harness, stacked vs assembled panel layout
- Dense per-pixel maps through the panel table (panel layout stage 1)
- Panel id on spots and the panel table in the start message
- Viewer and preview show a panel detector as it lies on the detector plane
- Panel layout stage 3: per-panel spot finding (CPU+GPU, CCL) and raster algorithms on the plane raster
- Panel layout stage 2: prediction and Bragg integration through the panel table
- XTC reader: frames handed up as stored, streams indexed in parallel
- XFEL reader: integer frames stay integer, one gain, placement by panel
- EXTERNAL_TEST_DATA_STILLS.md: images used vs the entry for every set; drop "Not in the battery"
- still battery: EuXFEL sets read the depositors' Cheetah CXI files directly; AGIPD converter removed
- float32_to_int16.py: a non-finite pixel becomes -32768, the int16 error marker, not a zero count
- CrystFEL geometry: read the pixel masks and bad regions instead of ignoring them
- Panel layout stage 5: the XFEL reader hands up the stored frame and its panel table
- Panel table persisted in NXmx; modulation grid and pre-scan memo key on the plane
- still battery: Alvra sets take their pixel mask from the CrystFEL geometry, not --mask-good
- still battery: take the deposited model as mmCIF where the RCSB has no PDB-format file
- still battery: dimple gets PDB-format coordinates converted from an mmCIF-only deposition
- stills fixed cost: geometry refinement and pre-scan do the same work in less wall time
- stills geometry sample and trial spot finding run as many workers as the image pass
- Stills integration: background ring reach measured on empty apertures, radial curvature from the whole frame
- StillsPartialityRefine: the partiality width is the run's, measured on the crystals, not the prediction window's
- MergeOnTheFly: capture term and multiplicative outlier band for the stills merge (both opt-in)
- Stills given a cell: the written cell is the mean over the frames that are merged
- Stills: the radial curvature correction decided per run on the same empty apertures
- StillsPartialityRefine: measure the run width only on shells with signal
- Stills pre-scan: report the paired z of the radial-correction comparison
- module placement: the five concurrent fits each keep every thread
- still battery: score R-free against the deposited data through the same dimple protocol
- still battery: the R-free target is the lower of the deposition's dimple and published values
- Stills: background clip follows the radial curve; signal disk from the lattice spacing
- Stills keep an overloaded observation as a lower bound instead of dropping it
- Stills: drop the lattice-spacing signal disk; the correction decision back on the plain clip
- battery: R-free against the deposition without refinement only, one protocol for rotation and stills
- still battery: EuXFEL sets run on a 2,000-image subset for now
- stills geometry refinement: fit the detector distance and the cell together
- stills geometry refinement: a distance given with --detector-distance is held in the joint fit
- Metal integration engine: back to its panel-s5 kernels; Mac stills keep the old clip, no saturation count
- Metal integration test: the CPU comparison runs on a rotation experiment
- Stills: kept overloads go back to the drop where they are not concentrated at low resolution
- stills distance search: an absolute 30-3000 mm scan, a sample found without d-limits, the fit iterated
- battery results: XFEL still battery 20261022-1358 on rc178 0cf62452c - 12 sets, cold, R_free unrefined
- battery results: still summary gains the resolution of our merge and of the deposition
- Pre-scan masks a pixel at the saturation limit on most frames, as one holding the error value
- Stills keep an overload as a lower bound only where it has pixels at the limit; run-level gate removed
- XFEL reader: a per-frame mask is read the way the frames are, its chunk inflated outside the HDF5 lock
- stills distance search: every centre scanned with a wider acceptance, a larger sample where nothing indexes
- rugnux usage: --beam-center-check describes the absolute 30-3000 mm stills distance scan, not the old 60-160 % grid
- stills: detector tilt refined in the geometry pre-pass, kept where held-out frames agree
- CLAUDE.md: the changelog is written once, just before the merge into main - condensed one-liners of what users get
- broker: serve the placed model and its maps of the last rugnux live run (/rugnux/model.cif, /rugnux/map.ccp4)
- frontend: Mol* viewer of the placed model and its density on the Rugnux live page
- writer: _model.cif from rugnux live keeps the input model's metadata, as the served model.cif does
- rugnux live maps: one unit cell centred on the model; the viewer opens on all of it
- Anomalous difference map: ANOM/PHANOM in _maps.mtz, /rugnux/map.ccp4?type=anom, a magenta mesh in the viewer
- Mol* viewer: open with the maps drawn within 10 A of the centre of view
- Mol* viewer: aaredb's structure-viewer setup, on a black stage
- rugnux: the gain of a stills file that states none is read off its single-photon peak where the background resolves photons
- Mol* viewer: in line with AareDB's StructureView at its current head (8ece2c2)
- ACKNOWLEDGEMENT: the web frontend's Mol* viewer follows AareDB's setup (G. Gotthard, PSI)
- stills tilt decision: the modules stay where the run placed them
- still battery: no distance pins and no per-set tuning flags; gain from the data except where a file's baseline hides it
- battery results: rc178 6f6f69 - full still battery and full rotation battery with REFMAC
- Bragg integration: a CCD rotation sweep's sigmas at the measured gain, intensities in photons
- BackgroundGain: the gain of a frame that resolves photons is the spacing of its photon peaks, so a baseline left in the frame no longer hides it
- ShadowFinder: measure the background's azimuthal modulation instead of predicting it from the polarization
- BackgroundGain: one gain estimate for rotation and stills; the still battery no longer gives EuXFEL 152 its gain
- ShadowFinder: measure the modulation robustly under a wide one-sided shadow
- ShadowFinderTest: a one-sided shadow is not fitted as part of the background's modulation
- ShadowFinder: back to the predicted polarization factor, in the plane the background shows
- MXAnalysisAfterFPGA: the Bragg engine's edge mask in the image's layout, so raw / untransformed FPGA runs start again
- battery results: still battery on rc178 e54f55 replaces the earlier rc178 still tables
- XFELReader: per-frame mask and photon conversion without a library call or a branch per pixel
- stills geometry trial: the hypotheses a search asks are indexed side by side
- stills tilt decision: the fits start beside the pre-scan and the geometry trial
- XFELReader: a deflated frame is inflated and converted a piece at a time, while it is in the cache
- XFELReader: a byte-shuffled frame is unshuffled a piece at a time, a whole pixel per step
- GeometryRefiner: residuals carry only the blocks a fit moves; beam and distance one block
- GeometryRefiner: a spot's residual differentiates its observed and predicted halves apart
- docs: EXTERNAL_TEST_DATA lists every open-arm battery set, with corrected values and counts
- battery: doc_check.py cross-checks the manifests against the dataset pages
- stills module placement: the placement fit gets half the threads, each held-out fit an eighth
- still battery: the EuXFEL sets run on all their frames, as the published still runs did
- battery results: still battery on rc178 a0ce6c, cold on a quiet machine, replaces the earlier rc178 table
- macOS build: explicit size_t in the XFEL reader's row bounds; parentheses in the CPU preprocessor's select

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu
2026-10-23 17:56:42 +02:00

423 lines
19 KiB
C++

// SPDX-FileCopyrightText: 2025 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#include <algorithm>
#include <cmath>
#include <limits>
#include <optional>
#include "../../common/JFJochMath.h"
#include "SpotUtils.h"
#include "../../common/ResolutionShells.h"
void CountSpots(DataMessage &msg,
const std::vector<SpotToSave> &spots,
float d_min_A) {
int64_t low_res = 0;
int64_t ice_ring = 0;
for (auto &s: spots) {
if (s.ice_ring)
ice_ring++;
if (s.d_A > d_min_A)
low_res++;
}
msg.spot_count = spots.size();
msg.spot_count_low_res = low_res;
msg.spot_count_ice_rings = ice_ring;
}
// Spots in the ice-free control flanks either side of the hexagonal rings, rescaled to the ring bands'
// own q width. The control for one ring is the two intervals [w, 2w) beside it - same total width as
// the ring band, and symmetric, so the fall-off of spot density with resolution cancels to first
// order. A flank that lands on another ring is not a control and is dropped, its width with it; the
// three rings at 1.947/1.916/1.882 A are 0.05-0.06 apart in q and usually lose both.
float CountIceRingControlSpots(const std::vector<SpotToSave> &spots, float w) {
if (!(w > 0.0f))
return 0.0f;
float control = 0.0f;
for (const float d : ICE_RING_RES_A) {
const float q_ring = 2 * PI / d;
bool lo_free = true, hi_free = true;
for (const float other : ICE_RING_RES_A) {
const float q_other = 2 * PI / other;
if (q_other > q_ring && q_other < q_ring + 3 * w) hi_free = false;
if (q_other < q_ring && q_other > q_ring - 3 * w) lo_free = false;
}
const int free_flanks = (lo_free ? 1 : 0) + (hi_free ? 1 : 0);
if (free_flanks == 0)
continue;
int64_t n = 0;
for (const auto &s: spots) {
if (!(s.d_A > 0.0f)) continue;
const float dq = 2 * PI / s.d_A - q_ring;
if (hi_free && dq >= w && dq < 2 * w) n++;
if (lo_free && dq <= -w && dq > -2 * w) n++;
}
// One free flank covers half the ring band's width, so it counts double.
control += static_cast<float>(n) * 2.0f / static_cast<float>(free_flanks);
}
return control;
}
void MarkIceRings(std::vector<SpotToSave> &spots, float tolerance_q_recipA) {
std::vector<float> ice_rings_q;
for (const auto &i: ICE_RING_RES_A)
ice_rings_q.push_back(2 * PI / i);
for (auto &s: spots)
s.ice_ring = false;
MarkRings(spots, ice_rings_q, tolerance_q_recipA);
}
void MarkRings(std::vector<SpotToSave> &spots, const std::vector<float> &rings_q_recipA,
float tolerance_q_recipA) {
if (rings_q_recipA.empty())
return;
for (auto &s: spots) {
if (!(s.d_A > 0.0f))
continue;
const float spot_q = 2 * PI / s.d_A;
for (const float q: rings_q_recipA)
if (fabs(spot_q - q) < tolerance_q_recipA) {
s.ice_ring = true;
break;
}
}
}
namespace {
// A bin has to hold this many spots before its excess is looked at, so a pair of noise detections
// in an otherwise empty bin cannot pose as a ring.
constexpr int64_t RING_MIN_SPOTS_PER_BIN = 8;
// ... and the excess over the local baseline has to be this many times its Poisson noise, AND
// this large a fraction of the baseline. Both, because either alone fails at one end of the
// range: the Poisson test alone calls a 5% rise a ring where the pool is large, and the fractional
// test alone calls a two-spot bin a ring where it is small.
constexpr float RING_MIN_SIGMA = 4.0f;
constexpr float RING_MIN_EXCESS_FRACTION = 1.0f;
// Bins of the running median that sets the baseline. Wide compared with the 2-3 bins a ring covers,
// so the rings themselves do not pull the median up, and narrow compared with the whole q range,
// so it still follows the fall-off of spot density with resolution.
constexpr size_t RING_BASELINE_BINS = 41;
// Past the q where this share of a baseline window's bins are ring bins, the rings have merged:
// the median that the excess is measured against is itself a ring value, and nothing further out
// can be told from the crystal. Half, because that is what "the median is a ring" means - it is
// the definition of the running median failing, not a tuned number.
constexpr float RING_MERGED_BIN_FRACTION = 0.5f;
// The pool a measurement needs at all. Below this the histogram is counting statistics.
constexpr size_t RING_MIN_POOLED_SPOTS = 500;
// The share of the spots the rings have to hold before they are a PHASE rather than the crystal's
// own rows. Every pattern has some q bins fuller than their neighbours - a crystal with a short
// axis puts its reflections in sheets - and calling those a contaminant would be wrong. Calibrated
// on the 100-dataset open battery, where the measured fractions run as a continuum from 83% down:
// the sets with a visible powder sit at 8-83%, and below about a twentieth the "rings" are two or
// three bins holding a percent of the spots, which every clean crystal in that battery also shows.
constexpr float RING_MIN_SPOT_FRACTION = 0.05f;
}
PowderRings MeasurePowderRings(const std::vector<float> &spot_q_recipA, float half_width_q_recipA) {
PowderRings out;
if (!(half_width_q_recipA > 0.0f) || spot_q_recipA.size() < RING_MIN_POOLED_SPOTS)
return out;
float q_min = std::numeric_limits<float>::max(), q_max = 0.0f;
for (const float q : spot_q_recipA) {
if (!(q > 0.0f)) continue;
q_min = std::min(q_min, q);
q_max = std::max(q_max, q);
}
if (!(q_max > q_min))
return out;
// One bin per ring half-width, so a ring covers two or three of them.
const size_t nbins = static_cast<size_t>((q_max - q_min) / half_width_q_recipA) + 1;
if (nbins < RING_BASELINE_BINS)
return out;
std::vector<int64_t> count(nbins, 0);
int64_t total = 0;
for (const float q : spot_q_recipA) {
if (!(q > 0.0f)) continue;
const auto bin = static_cast<size_t>((q - q_min) / half_width_q_recipA);
if (bin < nbins) { count[bin]++; total++; }
}
if (total == 0)
return out;
// Running median of the counts. The window is clipped at the ends rather than padded, so the first
// and last few bins are judged against the baseline of the range they have.
std::vector<float> baseline(nbins, 0.0f);
std::vector<int64_t> window;
window.reserve(RING_BASELINE_BINS);
for (size_t i = 0; i < nbins; i++) {
const size_t lo = i > RING_BASELINE_BINS / 2 ? i - RING_BASELINE_BINS / 2 : 0;
const size_t hi = std::min(nbins, i + RING_BASELINE_BINS / 2 + 1);
window.assign(count.begin() + static_cast<long>(lo), count.begin() + static_cast<long>(hi));
std::ranges::nth_element(window, window.begin() + static_cast<long>(window.size() / 2));
baseline[i] = static_cast<float>(window[window.size() / 2]);
}
std::vector<char> is_ring(nbins, 0);
for (size_t i = 0; i < nbins; i++) {
const float excess = static_cast<float>(count[i]) - baseline[i];
is_ring[i] = count[i] >= RING_MIN_SPOTS_PER_BIN
&& excess > RING_MIN_SIGMA * std::sqrt(std::max(baseline[i], 1.0f))
&& excess > RING_MIN_EXCESS_FRACTION * baseline[i];
}
// Where the rings have merged. Read outwards over the same window the baseline uses: the first q
// at which ring bins are the majority of that window is where the measurement stops meaning
// anything, and everything past it is left alone.
for (size_t i = RING_BASELINE_BINS / 2; i + RING_BASELINE_BINS / 2 < nbins; i++) {
size_t n_ring = 0;
for (size_t j = i - RING_BASELINE_BINS / 2; j <= i + RING_BASELINE_BINS / 2; j++)
n_ring += is_ring[j] ? 1 : 0;
if (static_cast<float>(n_ring) > RING_MERGED_BIN_FRACTION * static_cast<float>(RING_BASELINE_BINS)) {
out.resolved_to_d_A = 2 * PI / (q_min + static_cast<float>(i) * half_width_q_recipA);
break;
}
}
// Contiguous runs of ring bins are one ring, placed at their count-weighted centre.
double excess_total = 0.0, ice_excess = 0.0;
size_t run_start = nbins;
const auto close_run = [&](size_t run_end) {
double num = 0.0, den = 0.0;
for (size_t j = run_start; j < run_end; j++) {
const auto w = static_cast<double>(count[j]) - baseline[j];
num += w * (q_min + (static_cast<double>(j) + 0.5) * half_width_q_recipA);
den += w;
}
if (den > 0.0) {
out.rings_q_recipA.push_back(static_cast<float>(num / den));
excess_total += den;
if (IsOnIceRing(static_cast<float>(2.0 * PI * den / num), half_width_q_recipA)) {
ice_excess += den;
out.ice_ring_count++;
}
}
run_start = nbins;
};
for (size_t i = 0; i < nbins; i++) {
if (is_ring[i] && run_start == nbins)
run_start = i;
else if (!is_ring[i] && run_start != nbins)
close_run(i);
}
if (run_start != nbins)
close_run(nbins);
out.spot_fraction = static_cast<float>(excess_total / static_cast<double>(total));
out.ice_spot_fraction = static_cast<float>(ice_excess / static_cast<double>(total));
out.non_ice_spot_fraction = static_cast<float>((excess_total - ice_excess) / static_cast<double>(total));
if (out.spot_fraction < RING_MIN_SPOT_FRACTION)
return {}; // measured, and it is not a phase
return out;
}
std::optional<float> SpotResolutionQuantile(const std::vector<float> &spot_q_recipA, float fraction) {
if (spot_q_recipA.size() < RING_MIN_POOLED_SPOTS || !(fraction > 0.0f) || !(fraction < 1.0f))
return std::nullopt;
std::vector<float> q;
q.reserve(spot_q_recipA.size());
for (const float v : spot_q_recipA)
if (v > 0.0f) q.push_back(v);
if (q.size() < RING_MIN_POOLED_SPOTS)
return std::nullopt;
const auto rank = static_cast<long>(static_cast<float>(q.size()) * fraction);
std::ranges::nth_element(q, q.begin() + rank);
return q[rank] > 0.0f ? std::optional<float>(2 * PI / q[rank]) : std::nullopt;
}
void FilterSpotsByCount(std::vector<SpotToSave> &input, int64_t count, bool deprioritise_ice) {
size_t output_size = std::min<size_t>(input.size(), count);
std::ranges::partial_sort(input, input.begin() + output_size,
std::ranges::less{}, // comparator on the projected key
[deprioritise_ice](const SpotToSave &s) {
// projection: non-ice first (false < true), then strongest intensity
// first. Where the run has no measurable ice the flag marks ordinary
// reflections that happen to lie in the fixed bands, so ordering on it
// would discard a fifth of the strongest spots for nothing.
return std::tuple{deprioritise_ice && s.ice_ring, -s.intensity};
});
input.resize(output_size);
}
void FilterSpuriousHighResolutionSpots(std::vector<SpotToSave> &spots, float threshold) {
std::ranges::sort(spots, [](SpotToSave &a, SpotToSave &b) {
return a.d_A > b.d_A;
});
// Apply 1/d gap threshold: find first gap in q = 1/d exceeding dist_threshold and ignore spots after it
if (spots.size() >= 2 && threshold > 0.0f) {
size_t cut_index = spots.size(); // default: keep all
// d_A sorted descending → q = 1/d_A sorted ascending
// We check consecutive q gaps: Δq_i = (1/d_i) - (1/d_{i+1})
for (size_t i = 0; i + 1 < spots.size(); ++i) {
float d1 = spots[i].d_A;
float d2 = spots[i + 1].d_A;
// Avoid division by zero; d_A should be > 0 in valid data
if (d1 <= 0.0f || d2 <= 0.0f)
continue;
float q1 = 2 * PI / d1;
float q2 = 2 * PI / d2;
float dq = q2 - q1; // should be >= 0 due to sorting
if (dq > threshold) {
cut_index = i + 1; // keep up to i inclusive
break;
}
}
if (cut_index < spots.size())
spots.resize(cut_index);
}
}
namespace {
// Fraction of the image's weighted spot signal that is allowed to lie beyond the quantile read
// off below. A quantile near the middle of the distribution measures the shape of the fall-off,
// which is the crystal's own; the extreme end of it measures the detection threshold and how many
// reflections the unit cell puts on the frame, which are not.
constexpr float SPOT_RESOLUTION_TAIL_FRACTION = 0.30f;
// How much further in 1/d the merged data reach than that quantile. Merging averages many
// observations of each reflection, so intensities go on being measurable well past the point where
// one image's spot finder still detects them. Calibrated on rotation data against the resolution at
// which per-shell CC1/2 falls through 0.30.
constexpr float SPOT_RESOLUTION_MERGE_REACH = 2.25f;
// Fewer spots than this and the quantile is not a fall-off, it is a handful of points.
constexpr size_t SPOT_RESOLUTION_MIN_SPOTS = 4;
}
std::optional<float> GetResolution(const std::vector<SpotToSave> &spots) {
// Each spot enters weighted by its own signal-to-noise. The intensity is a summed photon count, so
// it is Poisson and its significance is sqrt(I): that keeps a marginal high-resolution detection
// from counting for as much as a real reflection, without letting the handful of very strong
// low-resolution reflections - which say nothing about how far the crystal diffracts - decide the
// answer, as weighting by intensity itself would.
std::vector<std::pair<float, float>> spot_1_over_d2_weight; // (1/d^2, sqrt(intensity))
spot_1_over_d2_weight.reserve(spots.size());
float total_weight = 0.0f;
for (const auto &spot: spots) {
if (spot.ice_ring || !(spot.d_A > 0.0f) || !(spot.intensity > 0.0f))
continue;
const float weight = std::sqrt(spot.intensity);
spot_1_over_d2_weight.emplace_back(1.0f / (spot.d_A * spot.d_A), weight);
total_weight += weight;
}
if (spot_1_over_d2_weight.size() < SPOT_RESOLUTION_MIN_SPOTS || !(total_weight > 0.0f))
return std::nullopt;
// Walk in from the highest-resolution spot until the tail fraction of the weight is behind us.
std::ranges::sort(spot_1_over_d2_weight, std::ranges::greater{},
[](const std::pair<float, float> &s) { return s.first; });
float walked = 0.0f;
float one_over_d2 = spot_1_over_d2_weight.front().first;
for (const auto &[s, weight]: spot_1_over_d2_weight) {
walked += weight;
one_over_d2 = s;
if (walked >= SPOT_RESOLUTION_TAIL_FRACTION * total_weight)
break;
}
// Not clamped at the corner of the detector. The quantile is read from the middle of the
// fall-off, so it still measures the crystal where the detector cuts that fall-off short;
// clamping reported where the detector stops instead, which is the one thing this is not for.
return 1.0f / (SPOT_RESOLUTION_MERGE_REACH * std::sqrt(one_over_d2));
}
void GenerateSpotPlot(DataMessage &msg, const std::vector<SpotToSave> &spots, float d_min_A) {
const int nshells = 20;
// The geometry gives no usable high-resolution corner (no distance or no wavelength), so there is
// no resolution axis to plot the spots against. ResolutionShells would throw on it, once per image.
if (d_min_A <= 0.0f || d_min_A >= 50.0f)
return;
ResolutionShells shells(d_min_A, 50.0, nshells);
std::vector<float> intensity(nshells);
std::vector<float> count(nshells);
for (const auto &s: spots) {
if (s.ice_ring)
continue;
if (auto shell = shells.GetShell(s.d_A)) {
intensity[*shell] += s.intensity;
count[*shell] += 1.0f;
}
}
std::vector<float> result(nshells);
for (int i = 0; i < nshells; ++i) {
if (count[i] > 0)
result[i] = intensity[i] / count[i];
else
result[i] = 0.0f;
}
msg.spot_plot_one_over_d_square = shells.GetShellMeanOneOverResSq();
msg.spot_plot_intensity = result;
msg.spot_plot_count = count;
}
void SpotAnalyze(const DiffractionExperiment &experiment,
const SpotFindingSettings &spot_finding_settings,
const std::vector<DiffractionSpot> &spots,
DataMessage &output) {
auto geom = experiment.GetDiffractionGeometry();
std::vector<SpotToSave> spots_out;
// A spot is found on the image; from here on it is where its panel puts it on the detector plane.
const auto &modules = experiment.GetModules();
for (const auto &spot: spots) {
if (auto s = spot.Export(geom, output.number); s.has_value()) {
if (!modules.empty()) {
const auto [px, py] = modules.ImageToPlane(spot.Panel(), s->x, s->y);
s->x = static_cast<float>(px);
s->y = static_cast<float>(py);
s->d_A = geom.PxlToRes(s->x, s->y);
}
spots_out.push_back(s.value());
}
}
if (spot_finding_settings.high_res_gap_Q_recipA.has_value())
FilterSpuriousHighResolutionSpots(spots_out, spot_finding_settings.high_res_gap_Q_recipA.value());
if (experiment.GetDatasetSettings().IsDetectIceRings() && spot_finding_settings.ice_ring_width_Q_recipA > 0.0f) {
MarkIceRings(spots_out, spot_finding_settings.ice_ring_width_Q_recipA);
// Before FilterSpotsByCount below, which orders ice spots LAST and would throw them away first.
output.spot_count_ice_control =
CountIceRingControlSpots(spots_out, spot_finding_settings.ice_ring_width_Q_recipA);
}
CountSpots(output, spots_out, spot_finding_settings.cutoff_spot_count_low_res);
// The rings this run measured for itself, flagged after the ice counters above so those go on
// reporting hexagonal ice and only hexagonal ice, and before the resolution estimate and the spot
// budget below, which both want the contaminant out of the way: a powder ring reaching the corner
// of the detector otherwise sets the estimate, and the budget otherwise spends itself on it.
MarkRings(spots_out, spot_finding_settings.measured_ring_q_recipA,
spot_finding_settings.ice_ring_width_Q_recipA);
// 0 spells "no limit" everywhere else the limit is read (value_or(0) then compares against it), so it
// has to mean the same here - passing it on as a resolution makes ResolutionShells throw per image.
const auto &spot_d_min = spot_finding_settings.high_resolution_limit;
GenerateSpotPlot(output, spots_out,
spot_d_min.value_or(0.0f) > 0 ? *spot_d_min : experiment.GetDetectorMaxResolution_A());
output.resolution_estimate = GetResolution(spots_out);
// One decision drives both: if indexing is to use the ice-band spots, the spot budget must not
// throw them away before it gets the chance.
FilterSpotsByCount(spots_out, experiment.GetMaxSpotCount(),
!experiment.GetIndexingSettings().GetIndexIceRings());
output.spots = spots_out;
}