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Jungfraujoch/image_analysis/bragg_integration/SpotFootprint.cpp
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leonarski_fandFilip Leonarski 19b135186d
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v1.0.0-rc.175 (#85)
* Rugnux: Processes a collection live while jfjoch_broker writes it (`rugnux <master.h5> <broker URL>`).
* Rugnux: Processing starts on the first images and confirms its choices once all are in, so analysis can begin during collection.
* Rugnux: Faster processing, especially on servers with several GPUs and CPU sockets and on computers without a GPU (`--no-gpu`, macOS).
* Rugnux: Uses much less GPU memory, so large data sets stay on the GPU of smaller cards, and a data set too large for the card is processed on the CPU instead.
* Rugnux: On macOS, Bragg integration runs on the Apple GPU.
* Rugnux: Better handling of twinning and pseudo-symmetry, with the twin hypothesis written as `<prefix>_twin_<SG>.mtz`, and a wrong `--model` no longer confirms the data or decides the hand.
* Rugnux: `--model` accepts predicted (AlphaFold) models and falls back to molecular replacement when the model is not placed as a rigid body (experimental `--mr` forces it), settling space group, hand and twinning and writing a different answer as `<prefix>_mr.mtz`.
* Rugnux: Molecular replacement is faster and settles the space group in more cases with several copies in the asymmetric unit.
* Rugnux: Deposition-ready mmCIF, a richer report, and numbered steps on the terminal with the full log in `<prefix>_log.txt`; `_P1.mtz`, `--estimate-beam-center` and `--beam-center-search` are removed.
* Rugnux: The beam-stop shadow is found correctly on tilted detectors.
* Rugnux: Stills files that record a stationary goniometer axis get the default stills geometry refinement.
* jfjoch_viewer: "Analyze dataset" uses the same defaults as a bare `rugnux <file>`, and shows the results of processed CBF, marCCD and SMV sweeps.
* jfjoch_viewer: The Files panel refreshes on F5 and every few seconds, and the plot type and other selections stay put during live collection.
* jfjoch_writer: Memory stays bounded and old data files are closed efficiently on long runs, any failure ends the run in an error state the broker is told about, and the master file appears only after its data files; the ZeroMQ pusher logs when a stalled writer makes it drop images.
* Fixes: The TCP image pusher no longer blocks the broker's receiver, GPU out-of-memory failures stop with a clear message, and the XDS plugin masks module and chip edges.

---------

Co-authored-by: Filip Leonarski <jungfrau@filips-mac-mini.home>
Reviewed-on: #85
Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
2026-10-16 15:34:43 +02:00

189 lines
8.7 KiB
C++

// SPDX-FileCopyrightText: 2026 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#include "SpotFootprint.h"
#include <algorithm>
#include <cmath>
#include <map>
#include <tuple>
namespace {
// The window around a spot is BRAGG_FOOTPRINT_NSIGMA-like: three of its standard deviations, at least
// a few pixels and at most this many, which is wider than any spot the integrator could hold.
constexpr float WINDOW_NSIGMA = 3.0f;
constexpr float WINDOW_MIN_PX = 3.0f;
constexpr float WINDOW_MAX_PX = 24.0f;
// The background is the median of an elliptical annulus between these multiples of the window.
constexpr float BKG_INNER = 1.5f;
constexpr float BKG_OUTER = 2.2f;
constexpr int ITERATIONS = 8;
inline bool valid(int32_t v) { return v != INT32_MIN && v != INT32_MAX; }
float median_of(std::vector<float> &v) {
const size_t m = v.size() / 2;
std::nth_element(v.begin(), v.begin() + static_cast<std::ptrdiff_t>(m), v.end());
return v[m];
}
} // namespace
FootprintOutcome MeasureFootprintSpot(const FootprintTile &tile, int width, int height, float beam_x, float beam_y,
float x, float y, FootprintSpot &spot) {
const int half = static_cast<int>(std::ceil(BKG_OUTER * WINDOW_MAX_PX)) + 1;
std::vector<float> ring;
const float rx = x - beam_x, ry = y - beam_y;
const float r = std::sqrt(rx * rx + ry * ry);
if (!(r > 1.0f)) return FootprintOutcome::LeftOut;
const float ux = rx / r, uy = ry / r;
const int ix = static_cast<int>(std::lround(x)), iy = static_cast<int>(std::lround(y));
if (ix - half < 0 || iy - half < 0 || ix + half >= width || iy + half >= height) return FootprintOutcome::LeftOut;
// Start from a compact spot at the prediction; each round re-centres on the signal and takes
// the window to three of the widths just measured.
float cx = x, cy = y;
float s2r = 1.0f, s2t = 1.0f;
for (int it = 0; it < ITERATIONS; ++it) {
const float wr = std::clamp(WINDOW_NSIGMA * std::sqrt(s2r), WINDOW_MIN_PX, WINDOW_MAX_PX);
const float wt = std::clamp(WINDOW_NSIGMA * std::sqrt(s2t), WINDOW_MIN_PX, WINDOW_MAX_PX);
const float reach = BKG_OUTER * std::max(wr, wt);
const int x0 = static_cast<int>(std::floor(cx - reach)), x1 = static_cast<int>(std::ceil(cx + reach));
const int y0 = static_cast<int>(std::floor(cy - reach)), y1 = static_cast<int>(std::ceil(cy + reach));
if (x0 < 0 || y0 < 0 || x1 >= width || y1 >= height) return FootprintOutcome::LeftOut;
// The re-centring is not bounded, so the window can walk off a tile the frame still holds.
if (x0 < tile.x0 || y0 < tile.y0 || x1 >= tile.x0 + tile.w || y1 >= tile.y0 + tile.h)
return FootprintOutcome::OffTile;
const auto pixel = [&](int px, int py) {
return tile.pixels[static_cast<size_t>(py - tile.y0) * tile.w + (px - tile.x0)];
};
ring.clear();
for (int py = y0; py <= y1; ++py)
for (int px = x0; px <= x1; ++px) {
const float dx = px - cx, dy = py - cy;
const float rad = dx * ux + dy * uy, tn = -dx * uy + dy * ux;
const float e = rad * rad / (wr * wr) + tn * tn / (wt * wt);
const int32_t v = pixel(px, py);
if (e >= BKG_INNER * BKG_INNER && e < BKG_OUTER * BKG_OUTER && valid(v))
ring.push_back(static_cast<float>(v));
}
if (ring.size() < 10) return FootprintOutcome::LeftOut;
const double bkg = median_of(ring);
double w = 0.0, mr = 0.0, mt = 0.0, m2r = 0.0, m2t = 0.0;
for (int py = y0; py <= y1; ++py)
for (int px = x0; px <= x1; ++px) {
const float dx = px - cx, dy = py - cy;
const float rad = dx * ux + dy * uy, tn = -dx * uy + dy * ux;
if (rad * rad / (wr * wr) + tn * tn / (wt * wt) >= 1.0f) continue;
const int32_t v = pixel(px, py);
if (!valid(v)) return FootprintOutcome::LeftOut;
const double net = static_cast<double>(v) - bkg;
w += net;
mr += net * rad;
mt += net * tn;
m2r += net * rad * rad;
m2t += net * tn * tn;
}
if (!(w > 0.0)) return FootprintOutcome::LeftOut;
const double cr = mr / w, ct = mt / w;
s2r = static_cast<float>(std::max(0.25, m2r / w - cr * cr));
s2t = static_cast<float>(std::max(0.25, m2t / w - ct * ct));
cx += static_cast<float>(cr * ux - ct * uy);
cy += static_cast<float>(cr * uy + ct * ux);
}
spot = {r, std::sqrt(s2r), std::sqrt(s2t)};
return FootprintOutcome::Measured;
}
void MeasureFootprintSpots(const int32_t *img, int width, int height, float beam_x, float beam_y,
const std::vector<float> &x, const std::vector<float> &y,
std::vector<FootprintSpot> &out) {
const FootprintTile frame{img, 0, 0, width, height};
for (size_t s = 0; s < x.size(); ++s) {
FootprintSpot spot;
if (MeasureFootprintSpot(frame, width, height, beam_x, beam_y, x[s], y[s], spot) == FootprintOutcome::Measured)
out.push_back(spot);
}
}
SpotFootprint FootprintFromSpots(const std::vector<FootprintSpot> &spots, float r_max) {
SpotFootprint fp;
if (!(r_max > 0.0f)) return fp;
const float bin = r_max / FOOTPRINT_BINS;
std::vector<std::vector<float>> rad(FOOTPRINT_BINS), tan(FOOTPRINT_BINS);
for (const auto &s : spots) {
const int b = std::clamp(static_cast<int>(s.r_px / bin), 0, FOOTPRINT_BINS - 1);
rad[b].push_back(s.sigma_rad);
tan[b].push_back(s.sigma_tan);
}
std::vector<int> filled;
std::vector<float> mr(FOOTPRINT_BINS, 0.0f), mt(FOOTPRINT_BINS, 0.0f);
for (int b = 0; b < FOOTPRINT_BINS; ++b)
if (static_cast<int>(rad[b].size()) >= FOOTPRINT_MIN_SPOTS_PER_BIN) {
mr[b] = median_of(rad[b]);
mt[b] = median_of(tan[b]);
filled.push_back(b);
}
if (filled.empty()) return fp;
fp.bin_px = bin;
for (int b = 0; b < FOOTPRINT_BINS; ++b) {
// The nearest bin that has enough spots; the inner one on a tie.
int best = filled.front();
for (int f : filled)
if (std::abs(f - b) < std::abs(best - b)) best = f;
fp.sigma_rad.push_back(mr[best]);
fp.sigma_tan.push_back(mt[best]);
}
return fp;
}
void MeasureFootprintOffsets(const std::vector<SpotToSave> &spots, const std::vector<Reflection> &reflections,
float beam_x, float beam_y, std::vector<FootprintOffset> &out) {
std::map<std::tuple<int, int, int>, const Reflection *> predicted;
for (const auto &r : reflections)
predicted[{r.h, r.k, r.l}] = &r;
for (const auto &s : spots) {
if (!s.indexed || s.lattice != 0) continue;
const auto it = predicted.find({static_cast<int>(s.h), static_cast<int>(s.k), static_cast<int>(s.l)});
if (it == predicted.end()) continue;
const float px = it->second->predicted_x, py = it->second->predicted_y;
const float rx = px - beam_x, ry = py - beam_y;
const float r = std::sqrt(rx * rx + ry * ry);
if (!(r > 1.0f)) continue;
const float ux = rx / r, uy = ry / r;
const float dx = s.x - px, dy = s.y - py;
out.push_back({r, dx * ux + dy * uy, -dx * uy + dy * ux});
}
}
SpotFootprint FootprintWithOffsets(const SpotFootprint &widths, std::vector<FootprintOffset> offsets) {
if (widths.empty()) return widths;
// Sorted, so the sums below do not depend on the order the frames were measured in.
std::sort(offsets.begin(), offsets.end());
const int n = static_cast<int>(widths.sigma_rad.size());
std::vector<double> s2r(n, 0.0), s2t(n, 0.0);
std::vector<int> cnt(n, 0);
for (const auto &o : offsets) {
const int b = std::clamp(static_cast<int>(o.r_px / widths.bin_px), 0, n - 1);
s2r[b] += static_cast<double>(o.off_rad) * o.off_rad;
s2t[b] += static_cast<double>(o.off_tan) * o.off_tan;
++cnt[b];
}
std::vector<int> filled;
for (int b = 0; b < n; ++b)
if (cnt[b] >= FOOTPRINT_MIN_SPOTS_PER_BIN) filled.push_back(b);
if (filled.empty()) return widths;
SpotFootprint fp = widths;
for (int b = 0; b < n; ++b) {
int best = filled.front();
for (int f : filled)
if (std::abs(f - b) < std::abs(best - b)) best = f;
fp.sigma_rad[b] = static_cast<float>(std::sqrt(widths.sigma_rad[b] * widths.sigma_rad[b] + s2r[best] / cnt[best]));
fp.sigma_tan[b] = static_cast<float>(std::sqrt(widths.sigma_tan[b] * widths.sigma_tan[b] + s2t[best] / cnt[best]));
}
return fp;
}