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Jungfraujoch/image_analysis/bragg_prediction/BraggPrediction.cpp
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v1.0.0.rc-162 (#72)
**Files written by Jungfraujoch now import correctly in DIALS, XDS and pyFAI.** A tilted detector, a grid scan, a still recorded at a goniometer position, and saturated or unreadable pixels were each described in a way that a third-party program acted on wrongly. If you process Jungfraujoch data outside Jungfraujoch, prefer this release to any earlier one.

* HDF5: the detector tilt (`rot1`/`rot2`/`rot3`) is exported correctly in the NXmx transformation chain; untilted geometries are unaffected.
* HDF5: a still recorded at a goniometer position is no longer read back as a single image, and a grid scan records a stationary spindle so a program that requires a rotation axis can open it.
* HDF5: the sample transformation chain is written in mounting order, with a Smargon head position told apart from the spindle, one entry per image, `module_offset` as a float unit vector, and `offset_units` on every offset.
* HDF5: saturated, underloaded and unreadable pixels are described so a downstream program masks them - `saturation_value`, `underload_value`, `error_value` and `bit_depth_readout` are written correctly, and a data file missing next to a VDS master reads as the error marker rather than as zero counts.
* HDF5: the rotation axis is read back under whatever name it carries, and `mirror_y` records whether the assembled image is mirrored in Y relative to the detector's raw readout.
* A grid scan and a goniometer axis can both be set; they are no longer alternatives.
* `images_per_file` is chosen from the acquisition when it is not given: a rotation sweep of at most 20000 images goes into a single data file, a grid scan splits on whole fast-axis rows, and stills and serial keep 1000.
* The writer refuses a stream whose start message declares a different pixel format than its images carry, and a DECTRIS detector sending signed images is no longer declared unsigned.
* The image stream can carry the sample transformation chain (`transformations`, in the END message); a producer that does not send it gets the same chain built by the writer.
* rugnux: fixing the space group with `-S` no longer prevents the lattice from being found - a lattice indexed in a different setting is reindexed into that group's own setting, and a run whose crystal does not have that group's lattice stops and names the cell it indexed as, rather than reporting statistics that cannot describe it.
* rugnux: the per-image resolution estimate now predicts the resolution the merged data reach rather than the highest-resolution spot found, and is reported as `SPOT_RESOLUTION_ESTIMATE`.
* rugnux: two runs of the same command on the same images produce the same merged intensities; the azimuthal profile written alongside them is not yet reproducible in the same way.
* rugnux: the offline lattice refinement is bounded by iterations rather than by a wall clock, so a loaded machine can no longer refine to a different lattice; a live acquisition keeps its real-time bound.
* rugnux: the detector-frame modulation correction is fitted on a grid spanning the detector, so whether it is applied no longer depends on how far integration reached.
* rugnux: the geometry pre-pass no longer writes `<prefix>_01.mtz`, `_01.cif`, `_01.hkl` and `_01_image.dat`; the refined second pass writes those files under `<prefix>`, and that is the result to use.
* rugnux: `_process.h5` describes the pixel format of the images it links to, and is written on a thread of its own.
* rugnux: the detector geometry is also logged in XDS's convention (`ORGX`/`ORGY`, detector axis vectors, rotation axis), so it can be compared with an XDS refinement.
* rugnux: an image integrated in pyFAI through the `.poni` file written by `--mode calibration` comes out with the correct azimuth, and the file declares pyFAI's `orientation`, which needs pyFAI 2024.01 or newer. Radial integration is unchanged.
* rugnux: a rotation run is substantially faster throughout - beam-stop detection, first-pass indexing, geometry refinement, integration, scaling and merging - and observations outside the scaling resolution range are dropped as they are ingested. The refined geometry, the space group chosen and the merged statistics are unchanged.
* Faster spot finding and indexing, on the broker as well as in rugnux; the spots found and the lattices indexed are unchanged.
* A run reserves substantially less GPU memory: nothing is allocated for buffers that are never read, and a worker builds only the engines it uses.
* rugnux: with `-N` left at its default the per-image loop of `--mode mx` uses at most 16 workers per GPU, rather than one per hardware thread; an explicit `-N` is obeyed as given.
* CUDA 12 builds now contain device code for Volta, so the RHEL 8 packages and the portable Linux `.tgz` run on a V100; the CUDA 13 artefacts (RHEL 9, Ubuntu, Windows) remain Turing and newer.
* The build resolves a single Eigen for the whole project, and refuses to configure if Ceres picks up a different one; a build that mixed two Eigen versions was undefined behaviour and crashed at -O2.
* Documentation: a security page, and the supported GPU generations and minimum NVIDIA driver version of every released artefact.

**Breaking change to OpenAPI** - regenerate the client (`jfjoch-client` 1.0.0-rc.162, `frontend/src/client`):
* `dataset_settings.images_per_file` is no longer `default: 1000` and no longer accepts `0`; it is optional, and its minimum is 1. A client sending `0` (previously "one file for the whole run") is now rejected - omit the field instead, which for a rotation sweep gives the same single file.
* `file_writer_format` now defaults to `NXmxVDS`, matching the server's own default and the layout recommended for DIALS, XDS and CrystFEL. A generated client that fills in schema defaults and does not set the format explicitly will write VDS masters where it previously wrote legacy ones; set `NXmxLegacy` explicitly to keep them.

---------

Co-authored-by: jungfrau <jungfrau@mx-aare-test.psi.ch>
Reviewed-on: #72
Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
2026-08-25 08:21:39 +02:00

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// SPDX-FileCopyrightText: 2025 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#include <algorithm>
#include "../../common/JFJochMath.h"
#include "../../common/Logger.h"
#include "BraggPrediction.h"
#include "../bragg_integration/SystematicAbsence.h"
void BraggPrediction::GrowCapacity(int count) {
reflections.resize(count);
max_reflections = count;
}
void BraggPrediction::OrderOutput(int count) {
order_keys.resize(count);
for (int i = 0; i < count; i++) {
const Reflection &r = reflections[i];
order_keys[i] = {r.h, r.k, r.l, r.delta_phi_deg, i};
}
std::sort(order_keys.begin(), order_keys.end(),
[](const OrderKey &a, const OrderKey &b) {
if (a.h != b.h) return a.h < b.h;
if (a.k != b.k) return a.k < b.k;
if (a.l != b.l) return a.l < b.l;
return a.delta_phi_deg < b.delta_phi_deg;
});
order_scratch.resize(count);
for (int i = 0; i < count; i++) order_scratch[i] = reflections[order_keys[i].index];
std::copy(order_scratch.begin(), order_scratch.end(), reflections.begin());
}
int BraggPrediction::TruncateToOutput(int count) {
if (count <= output_limit)
return count;
// Partiality first, then excitation error: exactly one of the two says anything on each path. On the
// rotation path dist_ewald is identically zero - BraggPredictionRot picks the rocking coordinate so
// that 2*S0.p + p.p = 0, i.e. |S| = 1/lambda exactly - so ranking by it there left an hkl-lexicographic
// prefix rather than the best-recorded reflections. On the still path every partiality is 1, so the
// ranking falls through to dist_ewald, which is what it has always been.
std::partial_sort(reflections.begin(), reflections.begin() + output_limit,
reflections.begin() + count,
[](const Reflection &a, const Reflection &b) {
if (a.partiality != b.partiality) return a.partiality > b.partiality;
if (a.dist_ewald != b.dist_ewald) return a.dist_ewald < b.dist_ewald;
if (a.h != b.h) return a.h < b.h;
if (a.k != b.k) return a.k < b.k;
return a.l < b.l;
});
return output_limit;
}
namespace {
// Number of bandwidth sigmas included in the (radially thickened) Ewald-shell
// acceptance window. 3σ captures essentially the whole pink-beam smear; matches
// the conservative end of the mosaicity cutoff used by callers.
constexpr float kBandwidthCutoffSigmas = 3.0f;
}
BraggPrediction::BraggPrediction(int max_reflections)
: max_reflections(max_reflections), reflections(max_reflections) {}
const std::vector<Reflection> &BraggPrediction::GetReflections() const {
return reflections;
}
int BraggPrediction::Calc(const DiffractionExperiment &experiment, const CrystalLattice &lattice,
const BraggPredictionSettings &settings) {
const auto geom = experiment.GetDiffractionGeometry();
const auto det_width_pxl = static_cast<float>(experiment.GetXPixelsNum());
const auto det_height_pxl = static_cast<float>(experiment.GetYPixelsNum());
const float one_over_dmax = 1.0f / settings.high_res_A;
const float one_over_dmax_sq = one_over_dmax * one_over_dmax;
float one_over_wavelength = 1.0f / geom.GetWavelength_A();
const Coord Astar = lattice.Astar();
const Coord Bstar = lattice.Bstar();
const Coord Cstar = lattice.Cstar();
const Coord S0 = geom.GetScatteringVector();
std::vector<float> rot = geom.GetPoniRotMatrix().transpose().arr();
// Precompute detector geometry constants
float beam_x = geom.GetBeamX_pxl();
float beam_y = geom.GetBeamY_pxl();
float det_distance = geom.GetDetectorDistance_mm();
float pixel_size = geom.GetPixelSize_mm();
float F = det_distance / pixel_size;
const float epsilon = 1e-5f;
const float s0_sq = S0 * S0;
const float rad_to_deg = 180.0f / static_cast<float>(PI);
int i = 0;
for (int h = -settings.max_h; h <= settings.max_h; h++) {
// Precompute A* h contribution
const float Ah_x = Astar.x * h;
const float Ah_y = Astar.y * h;
const float Ah_z = Astar.z * h;
for (int k = -settings.max_k; k <= settings.max_k; k++) {
// Accumulate B* k contribution
const float AhBk_x = Ah_x + Bstar.x * k;
const float AhBk_y = Ah_y + Bstar.y * k;
const float AhBk_z = Ah_z + Bstar.z * k;
for (int l = -settings.max_l; l <= settings.max_l; l++) {
if (systematic_absence(h, k, l, settings.centering))
continue;
if (i >= max_reflections)
continue;
float recip_x = AhBk_x + Cstar.x * l;
float recip_y = AhBk_y + Cstar.y * l;
float recip_z = AhBk_z + Cstar.z * l;
float recip_sq = recip_x * recip_x + recip_y * recip_y + recip_z * recip_z;
if (recip_sq > one_over_dmax_sq)
continue;
float S_x = recip_x + S0.x;
float S_y = recip_y + S0.y;
float S_z = recip_z + S0.z;
float S_len = sqrtf(S_x * S_x + S_y * S_y + S_z * S_z);
float dist_ewald_sphere = std::fabs(S_len - one_over_wavelength);
// Energy bandwidth thickens the Ewald shell radially: at the
// diffraction condition |S|-1/λ shifts by recip_z·(Δλ/λ), i.e.
// σ_bw = |recip_z|·bandwidth_sigma (= bλ/2d²). Broaden the acceptance
// window in quadrature so high-resolution shells (smeared most, ∝1/d²)
// are not clipped.
float radial_cutoff = settings.ewald_dist_cutoff;
if (settings.bandwidth_sigma > 0.0f) {
const float bw_tol = kBandwidthCutoffSigmas * settings.bandwidth_sigma * std::fabs(recip_z);
radial_cutoff = std::sqrt(radial_cutoff * radial_cutoff + bw_tol * bw_tol);
}
if (dist_ewald_sphere <= radial_cutoff ) {
const float s0_p0 = S0.x * recip_x + S0.y * recip_y + S0.z * recip_z;
const float val = s0_sq * recip_sq - s0_p0 * s0_p0;
float delta_phi_deg = NAN;
if (std::fabs(val) >= epsilon && s0_sq > epsilon) {
const float a_num = (s0_sq - 0.25f * recip_sq) * recip_sq;
if (a_num >= 0.0f) {
const float A = std::sqrt(a_num / val);
const float B = (A * s0_p0 + 0.5f * recip_sq) / s0_sq;
const float p_star_x = A * recip_x - B * S0.x;
const float p_star_y = A * recip_y - B * S0.y;
const float p_star_z = A * recip_z - B * S0.z;
const float p_star_sq = p_star_x * p_star_x + p_star_y * p_star_y + p_star_z * p_star_z;
const float denom = std::sqrt(p_star_sq * recip_sq);
if (denom >= epsilon) {
float c = (p_star_x * recip_x + p_star_y * recip_y + p_star_z * recip_z) / denom;
c = std::fmax(-1.0f, std::fmin(1.0f, c));
delta_phi_deg = std::acos(c) * rad_to_deg;
}
}
}
// Inlined RecipToDector with rot1 and rot2 (rot3 = 0)
// Apply rotation matrix transpose
float S_rot_x = rot[0] * S_x + rot[1] * S_y + rot[2] * S_z;
float S_rot_y = rot[3] * S_x + rot[4] * S_y + rot[5] * S_z;
float S_rot_z = rot[6] * S_x + rot[7] * S_y + rot[8] * S_z;
if (S_rot_z <= 0)
continue;
// Project to detector coordinates
// Assume detector is along x,y,z coordinates after rotation
float x = beam_x + F * S_rot_x / S_rot_z;
float y = beam_y + F * S_rot_y / S_rot_z;
if ((x < 0) || (x >= det_width_pxl) || (y < 0) || (y >= det_height_pxl))
continue;
float d = 1.0f / sqrtf(recip_sq);
reflections[i] = Reflection{
.h = h,
.k = k,
.l = l,
.delta_phi_deg = delta_phi_deg,
.predicted_x = x,
.predicted_y = y,
.observed_x = NAN,
.observed_y = NAN,
.d = d,
.dist_ewald = dist_ewald_sphere,
.rlp = 1.0,
.partiality = 1.0f,
.zeta = 1.0,
.image_scale_corr = 1.0
};
++i;
}
}
}
}
return TruncateToOutput(i);
}