The per-image resolution estimate was the 5th percentile of the spot d spacings - an extreme order statistic, so it measured where detection stops rather than how well the crystal diffracts. A large cell puts more reflections past the same threshold and scored better than a small cell that diffracts further; intensity was not used at all, so a weak crystal padded with spurious high-resolution detections ran away; and nothing clamped the answer to what the detector can deliver. Against the resolution the merged data actually reach it was 42% out in log-RMS, with 1 of 38 rotation datasets inside 0.2 A. Take instead the 1/d^2 beyond which 30% of the sum of sqrt(I) over the image's non-ice spots lies, report 1/(2.25 sqrt of it), clamp at the detector corner, and take the median over images. A quantile from the middle of the distribution measures the shape of the falloff - the crystal's own exp(-B/2d^2) - where an extreme one measures the threshold. sqrt(I) is the Poisson significance of a summed photon count, so a marginal high-resolution detection cannot carry the answer and neither can a handful of very strong low-resolution reflections. The 2.25 is the multiplicity gain: merging keeps measuring intensities a fixed factor in 1/d past the point where a single frame detects them. Spearman 0.881 -> 0.954, log-RMS 42% -> 8.9%, median error 0.79 -> 0.07 A, and 32 of 38 within 0.2 A. Both constants sit on a broad plateau, the scale is stable across dataset halves and across resolution ranges, and no second predictor survives leave-one-out. The residual is around 9%, set by multiplicity, symmetry and radiation damage - none of which a spot list can see. The estimate feeds only reporting: the image stream, HDF5, the plots, the scan result and the preview ring. It sets no cutoff and no search limit, and the scaling and merging output is byte-identical. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_016NNnL26LAvruQ9eLUUWvrJ
244 lines
11 KiB
C++
244 lines
11 KiB
C++
// SPDX-FileCopyrightText: 2025 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
|
|
// SPDX-License-Identifier: GPL-3.0-only
|
|
|
|
#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) {
|
|
auto spot_q = 2 * PI / s.d_A;
|
|
bool tmp = false;
|
|
for (const auto &q: ice_rings_q)
|
|
tmp |= (fabs(spot_q - q) < tolerance_q_recipA);
|
|
s.ice_ring = tmp;
|
|
}
|
|
}
|
|
|
|
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, float detector_d_min_A) {
|
|
// 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;
|
|
}
|
|
|
|
const float d_A = 1.0f / (SPOT_RESOLUTION_MERGE_REACH * std::sqrt(one_over_d2));
|
|
|
|
// However far the crystal diffracts, no merge reaches past the corner of the detector.
|
|
return detector_d_min_A > 0.0f ? std::max(d_A, detector_d_min_A) : d_A;
|
|
}
|
|
|
|
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;
|
|
|
|
for (const auto &spot: spots) {
|
|
if (auto s = spot.Export(geom, output.number); s.has_value())
|
|
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);
|
|
|
|
// 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, experiment.GetDetectorMaxResolution_A());
|
|
|
|
// 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;
|
|
}
|