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Jungfraujoch/image_analysis/geom_refinement/AssignSpotsToRings.cpp
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v1.0.0.rc-161 (#71)
This is an UNSTABLE release. It includes many experimental features, as well as many AI generated fixes. We recommend using rc.152 for production use.

* **rugnux: significantly better quality of results, and faster.** A large rework of integration, scaling, merging, geometry refinement and space-group determination, together with measurements the program previously made no attempt at - the direct beam before indexing, the beam stop, the goniometer rotation scale, and the stretches of a sweep the crystal did not deliver. A rotation dataset typically gains observations at better <I/sigma> and R_meas, and every `mx` and `scale` run writes a `<prefix>_report.txt` results report modelled on XDS's `CORRECT.LP`. Many defaults moved with it: spot detection is self-calibrating, beam-stop detection and rotation geometry post-refinement are on, resolution limits default to as far as the detector reaches, and ice-ring handling engages only where the crystal is measured to have ice.
* **jfjoch_viewer:** the beam-stop shadow, the detector calibration and the beam-centre measurement are reachable from "Analyze dataset"; the settings panel reports how the sample moved and how polarized the beam was; image rendering and interaction are faster.
* **Performance:** bitshuffle+LZ4 images are decoded on the GPU rather than on the host, with the bitshuffle inverse fused into preprocessing so the decompressed frame is never held in device memory.
* **Broker, writer, packaging and build:** image-slot lifetime and locking fixes, per-image datasets sized by the images actually written, the Debian/Ubuntu broker package renamed to `jfjoch`, and `image_analysis` compiling under MSVC again.

**Breaking change to the rugnux command line:**
* `--azint-only` and `--scale` are **removed**, replaced by `--mode azint` and `--mode scale`; the full pipeline is `--mode mx` and remains the default. A script passing the old flags now fails with the list of valid modes rather than silently running the wrong one.
* `-t`/`--stride` is **refused on rotation data**: skipping frames cuts every reflection's rocking curve, so the combined fulls and their partiality would be measured over frames the sweep never recorded. Select a contiguous range with `-s`/`-e` instead. `--mode azint` and `--force-still` still take a stride.

**Breaking changes to OpenAPI** - regenerate the client (`jfjoch-client` 1.0.0-rc.161, `frontend/src/client`) or read the affected fields as optional:
* `image_scale_b` is removed from the `plot_type` enum, so a client requesting that plot now gets an error rather than a curve.
* `azim_int_settings.high_q_recipA`, `spot_finding_settings.high_resolution_limit` and `spot_finding_settings.low_resolution_limit` are no longer `required`. All three mean "no limit at that end" when unset and are omitted from the response instead of carrying a placeholder value, which raises in a client generated from an rc.160-or-earlier spec. A value of 0 is still accepted and means the same thing.

**Breaking changes to the stored formats** - a consumer reading these fields must treat them as optional:
* The per-image image-scale B factor is no longer computed, so `/entry/MX/imageScaleBFactor` is absent from newly written HDF5 files and the corresponding key is absent from the CBOR DataMessage and END blocks. Files written by rc.160 and earlier still contain it and still open; nothing in the pipeline reads it any more.
* `_reflns.jfjoch_diffrn_ISa` now carries the whole-range `1/sqrt(a*b)` that XDS's ISa denotes, and the error-model `a` and `b` are reported in XDS's convention; the strong-reflection asymptote moves to `_reflns.jfjoch_diffrn_ISa_asymptotic`. **A file written by an earlier version carries the asymptote under the plain `ISa` name.**

Reviewed-on: #71
Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
2026-08-13 17:03:10 +02:00

301 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 "AssignSpotsToRings.h"
#include <vector>
#include <cmath>
#include <tuple>
#include <algorithm>
#include <iostream>
#include "../../common/CrystalLattice.h"
FindCircleCenterResult FindCircleCenter(const std::vector<SpotToSave> &v, int64_t width, int64_t height, int64_t max_spots) {
if ((width <= 0) || (height <= 0) || (max_spots <= 0))
throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "Invalid image size");
std::vector<int64_t> vote(width * height, 0);
// Limit to only first 250 spots, given the algorithm is N^3
auto task_size = std::min<size_t>(v.size(), max_spots);
for (int i = 0; i < task_size; i++) {
for (int j = i+1; j < task_size; j++) {
for (int k = j+1; k < task_size; k++) {
// Calculation via determinants
float a = v[i].x * (v[j].y - v[k].y) - v[i].y * (v[j].x - v[k].x) + v[j].x * v[k].y - v[k].x * v[j].y;
if (std::abs(a) < 1e-10)
continue; // Points are collinear
float x1_sq = v[i].x*v[i].x + v[i].y*v[i].y;
float x2_sq = v[j].x*v[j].x + v[j].y*v[j].y;
float x3_sq = v[k].x*v[k].x + v[k].y*v[k].y;
float bx = x1_sq * (v[j].y - v[k].y) + x2_sq * (v[k].y - v[i].y) + x3_sq * (v[i].y - v[j].y);
float by = x1_sq * (v[k].x - v[j].x) + x2_sq * (v[i].x - v[k].x) + x3_sq * (v[j].x - v[i].x);
int64_t cx = std::lround(bx / (2.0f * a));
int64_t cy = std::lround(by / (2.0f * a));
if ((cx >= 0) && (cx < width) && (cy >= 0) && (cy < height))
vote[cx + cy * width]++;
}
}
}
int64_t total_votes = 0;
int64_t max_votes = 0;
int64_t cx = 0;
int64_t cy = 0;
for (int64_t y = 0; y < height; y++) {
for (int64_t x = 0; x < width; x++) {
total_votes += vote[x + y * width];
if (vote[x + y * width] > max_votes) {
max_votes = vote[x + y * width];
cx = x;
cy = y;
}
}
}
return {
.total_votes = total_votes,
.votes_for_beam_center = max_votes,
.x = static_cast<float>(cx),
.y = static_cast<float>(cy)
};
}
// Very simple 1D DBSCAN on radii (works for rings)
std::vector<std::vector<int>> ClusterSpotsIntoRings(const std::vector<float>& r, float eps, int minPts) {
size_t n = r.size();
std::vector<int> labels(n, -1); // -1 = unvisited, -2 = noise
int cluster_id = 0;
for (int i=0; i<n; i++) {
if (labels[i] != -1) continue; // already visited
// find neighbors within eps in radius
std::vector<int> neighbors;
for (int j=0; j<n; j++) {
if (std::fabs(r[i] - r[j]) <= eps) neighbors.push_back(j);
}
if ((int)neighbors.size() < minPts) {
labels[i] = -2; // noise
continue;
}
// start new cluster
labels[i] = cluster_id;
std::vector<int> seeds = neighbors;
for (size_t k=0; k<seeds.size(); k++) {
int j = seeds[k];
if (labels[j] == -2) labels[j] = cluster_id;
if (labels[j] != -1) continue;
labels[j] = cluster_id;
// expand cluster
std::vector<int> nbrs2;
for (int m=0; m<n; m++) {
if (std::fabs(r[j] - r[m]) <= eps) nbrs2.push_back(m);
}
if ((int)nbrs2.size() >= minPts) {
seeds.insert(seeds.end(), nbrs2.begin(), nbrs2.end());
}
}
cluster_id++;
}
// Collect results
std::vector<std::vector<int>> clusters(cluster_id);
for (int i=0; i<n; i++) {
if (labels[i] >= 0)
clusters[labels[i]].push_back(i);
}
return clusters;
}
float median(std::vector<float> v) {
if (v.empty()) return std::numeric_limits<float>::quiet_NaN();
size_t n = v.size();
std::nth_element(v.begin(), v.begin()+n/2, v.end());
float m = v[n/2];
if (n % 2 == 0) {
auto it = std::max_element(v.begin(), v.begin()+n/2);
m = 0.5f*(m + *it);
}
return m;
}
std::vector<RingClusters> AnalyzeClusters(const std::vector<float>& r, const std::vector<std::vector<int>> &clusters) {
std::vector<RingClusters> ret;
for (const auto & cluster : clusters) {
std::vector<float> cluster_r;
for (const auto &idx : cluster)
cluster_r.push_back(r[idx]);
if (cluster_r.size() < 2) continue;
float m = median(cluster_r);
ret.push_back({cluster, m, -1});
}
// sort by observed radius
if (!ret.empty())
std::sort(ret.begin(), ret.end(), [](const RingClusters& a, const RingClusters& b)
{ return a.R_obs < b.R_obs; });
return ret;
}
namespace {
bool reflection_present(ReflectionCondition condition, int h, int k, int l) {
const bool all_odd = (h % 2 != 0) && (k % 2 != 0) && (l % 2 != 0);
const bool all_even = (h % 2 == 0) && (k % 2 == 0) && (l % 2 == 0);
switch (condition) {
case ReflectionCondition::FaceCentred:
return all_odd || all_even;
case ReflectionCondition::Diamond:
return all_odd || (all_even && ((h + k + l) % 4 == 0));
case ReflectionCondition::All:
default:
return true;
}
}
}
std::vector<float> CalculateXtalRings(const UnitCell &cell, ReflectionCondition condition, int hkl_max) {
CrystalLattice latt(cell);
Coord Astar = latt.Astar();
Coord Bstar = latt.Bstar();
Coord Cstar = latt.Cstar();
std::vector<float> u;
// Both signs of h and k: only for a diagonal metric does |h a* + k b*| equal |h a* - k b*|, so on a
// triclinic cell (silver behenate) the positive octant alone misses more rings than it finds. l stays
// non-negative because hkl and -h-k-l are the same ring.
for (int h = -hkl_max; h <= hkl_max; h++) {
for (int k = -hkl_max; k <= hkl_max; k++) {
for (int l = 0; l <= hkl_max; l++) {
if (h == 0 && k == 0 && l == 0) continue;
if (!reflection_present(condition, h, k, l)) continue;
auto p = Astar * h + Bstar * k + Cstar * l;
float Q = 2.0f * PI * p.Length();
u.push_back(Q);
}
}
}
std::sort(u.begin(), u.end());
// Deduplicate (since e.g. (100), (010), (001) all give sqrt(1))
u.erase(std::unique(u.begin(), u.end(),
[](float a, float b){ return std::fabs(a-b) < 1e-6; }),
u.end());
return u;
}
std::vector<float> CalculateCubicXtalRings(float a, int hkl_max) {
return CalculateXtalRings(UnitCell(a,a,a,90,90,90), ReflectionCondition::All, hkl_max);
}
float GuessDetectorDistance(const DiffractionGeometry& geom, float ring_radius_pxl, float d_A) {
float sin_theta = geom.GetWavelength_A() / (2 * d_A);
if (sin_theta < 0 || sin_theta > 1)
throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "Geometry makes no sense");
float theta = asinf(sin_theta);
float radius_mm = ring_radius_pxl * geom.GetPixelSize_mm();
float det_dist_mm = radius_mm / tanf(2.0f * theta);
return det_dist_mm;
}
std::vector<RingClusters> GuessInitialGeometry(DiffractionGeometry &geom, const std::vector<SpotToSave> &v, float largest_ring_d_A) {
// Reset rotations. The model assumes these are very small in any case!
geom.PoniRot1_rad(0.0).PoniRot2_rad(0.0).PoniRot3_rad(0.0);
auto center = FindCircleCenter(v);
if (center.votes_for_beam_center < 20)
throw JFJochException(JFJochExceptionCategory::CalibrationError, "Beam center not found");
geom.BeamX_pxl(center.x).BeamY_pxl(center.y);
std::vector<float> radii(v.size());
for (int i = 0; i < v.size(); i++)
radii[i] = std::hypot(v[i].x - center.x, v[i].y - center.y);
auto clusters = ClusterSpotsIntoRings(radii);
if (clusters.empty())
throw JFJochException(JFJochExceptionCategory::CalibrationError, "Couldn't find spot clusters");
auto cluster_annot = AnalyzeClusters(radii, clusters);
float det_distance = GuessDetectorDistance(geom, cluster_annot[0].R_obs, largest_ring_d_A);
geom.DetectorDistance_mm(det_distance);
return cluster_annot;
}
void GuessGeometry(DiffractionGeometry &geom, const std::vector<SpotToSave> &v, const std::vector<float> &ring_q) {
if (ring_q.empty())
throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "No calibrant rings given");
auto cluster_annot = GuessInitialGeometry(geom, v, 2 * PI / ring_q[0]);
std::vector<RingOptimizerInput> optimizer_input;
int ring_idx = 0;
int cluster_idx = 0;
while (cluster_idx < cluster_annot.size() && ring_idx < ring_q.size()) {
float obs_q = 2 * PI / geom.PxlToRes(cluster_annot[cluster_idx].R_obs);
if (std::fabs(ring_q[ring_idx] - obs_q) < 0.1) {
std::cout << "Found ring " << ring_idx
<< " with q_ring = " << ring_q[ring_idx]
<< " and q_obs = " << obs_q
<< " diff = " << std::fabs(ring_q[ring_idx] - obs_q) << std::endl;
for (const auto &spot: cluster_annot[cluster_idx].spots)
optimizer_input.push_back({v[spot].x, v[spot].y, ring_q[ring_idx]});
ring_idx++;
cluster_idx++;
} else {
std::cout << "Cannot match " << ring_idx
<< " with q_ring = " << ring_q[ring_idx]
<< " and q_obs = " << obs_q
<< " diff = " << std::fabs(ring_q[ring_idx] - obs_q) << std::endl;
if (ring_q[ring_idx] < obs_q)
ring_idx++;
else
cluster_idx++;
}
}
RingOptimizer optimizer(geom);
geom = optimizer.Run(optimizer_input);
}
std::vector<RingOptimizerInput> AssignSpotsToRings(const DiffractionGeometry &geom,
const std::vector<SpotToSave> &v,
const std::vector<float> &ring_q) {
std::vector<RingOptimizerInput> optimizer_input;
for (const auto& s: v) {
float q_obs = 2 * PI / geom.PxlToRes(s.x, s.y);
for (const auto &q : ring_q) {
if (std::fabs(q - q_obs) < 0.1) {
optimizer_input.push_back({s.x, s.y, q});
break;
}
}
}
return optimizer_input;
}
void OptimizeGeometry(DiffractionGeometry &geom, const std::vector<SpotToSave> &v, const std::vector<float> &ring_q) {
RingOptimizer optimizer(geom);
geom = optimizer.Run(AssignSpotsToRings(geom, v, ring_q));
}