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Jungfraujoch/image_analysis/geom_refinement/GeometryRefiner.cpp
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v1.0.0-rc.179 (#90)
* Rugnux: Stills processing needs only the unit cell and space group beyond what the file records - detector distance, beam centre, tilt, panel placement, saturation level, gain and polarisation plane are found from the images - and is up to twice as fast.
* Rugnux: Stills can be indexed without a GPU, with a CPU implementation of the fast-feedback indexer (macOS, computers without a GPU).
* Rugnux: Rotation and stills data are integrated in the detector's own units with one gain model, improving data from CCD detectors.
* Web frontend: The Rugnux live page shows the placed model with its electron density and anomalous difference map in a Mol* viewer.

Reviewed-on: #90
Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
2026-10-24 14:52:29 +02:00

817 lines
41 KiB
C++

// SPDX-FileCopyrightText: 2026 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#include "GeometryRefiner.h"
#include <algorithm>
#include <array>
#include <cmath>
#include <vector>
#include "../../common/JFJochMath.h" // PI
#include "../../common/ParallelFor.h"
#include "LatticeReduction.h"
#include "XtalResidual.h"
#include "ceres/ceres.h"
namespace {
// Trigonal is described with the hexagonal cell + B, same as the per-image XtalOptimizer.
gemmi::CrystalSystem MapSystem(gemmi::CrystalSystem s) {
return (s == gemmi::CrystalSystem::Trigonal) ? gemmi::CrystalSystem::Hexagonal : s;
}
// The cell angles (radians) that XtalResidual bakes into its B matrix for a given system. Only
// monoclinic (beta) and triclinic (all three) read p2; the rest use fixed symmetry angles. We keep the
// angles constant in v1, so these are set once from the input cell.
void InitCellAngles(gemmi::CrystalSystem system, const UnitCell &cell, double ang[3]) {
const double d2r = PI / 180.0;
switch (system) {
case gemmi::CrystalSystem::Hexagonal:
ang[0] = PI / 2.0; ang[1] = PI / 2.0; ang[2] = 2.0 * PI / 3.0;
break;
case gemmi::CrystalSystem::Monoclinic:
// XtalResidual reads p2[0] as beta.
ang[0] = cell.beta * d2r; ang[1] = PI / 2.0; ang[2] = PI / 2.0;
break;
case gemmi::CrystalSystem::Triclinic:
ang[0] = cell.alpha * d2r; ang[1] = cell.beta * d2r; ang[2] = cell.gamma * d2r;
break;
default: // orthorhombic / tetragonal / cubic
ang[0] = PI / 2.0; ang[1] = PI / 2.0; ang[2] = PI / 2.0;
break;
}
}
// Effective (lengths, alpha,beta,gamma) that reproduce the lattice XtalResidual builds from (len, ang),
// so a frame's lattice can be reconstructed with AngleAxisAndCellToLattice for HKL re-assignment.
void EffectiveCell(gemmi::CrystalSystem system, const double len[3], const double ang[3],
double lengths[3], double &alpha, double &beta, double &gamma) {
switch (system) {
case gemmi::CrystalSystem::Hexagonal:
lengths[0] = len[0]; lengths[1] = len[0]; lengths[2] = len[2];
alpha = PI / 2.0; beta = PI / 2.0; gamma = 2.0 * PI / 3.0;
break;
case gemmi::CrystalSystem::Tetragonal:
lengths[0] = len[0]; lengths[1] = len[0]; lengths[2] = len[2];
alpha = PI / 2.0; beta = PI / 2.0; gamma = PI / 2.0;
break;
case gemmi::CrystalSystem::Cubic:
lengths[0] = len[0]; lengths[1] = len[0]; lengths[2] = len[0];
alpha = PI / 2.0; beta = PI / 2.0; gamma = PI / 2.0;
break;
case gemmi::CrystalSystem::Monoclinic:
lengths[0] = len[0]; lengths[1] = len[1]; lengths[2] = len[2];
alpha = PI / 2.0; beta = ang[0]; gamma = PI / 2.0;
break;
case gemmi::CrystalSystem::Triclinic:
lengths[0] = len[0]; lengths[1] = len[1]; lengths[2] = len[2];
alpha = ang[0]; beta = ang[1]; gamma = ang[2];
break;
default: // orthorhombic
lengths[0] = len[0]; lengths[1] = len[1]; lengths[2] = len[2];
alpha = PI / 2.0; beta = PI / 2.0; gamma = PI / 2.0;
break;
}
}
// Orientation seed (angle-axis) for a frame's lattice, using the per-system decomposition the per-image
// optimizer uses so it matches XtalResidual's B convention.
void OrientationSeed(gemmi::CrystalSystem system, const CrystalLattice &latt, double rod[3]) {
double scratch[3];
if (system == gemmi::CrystalSystem::Hexagonal) {
LatticeToRodriguesAndLengths_Hex(latt, rod, scratch);
} else if (system == gemmi::CrystalSystem::Monoclinic) {
double beta;
LatticeToRodriguesLengthsBeta_Mono(latt, rod, scratch, beta);
} else {
LatticeToRodriguesAndLengths_GS(latt, rod, scratch);
}
}
UnitCell BuildUnitCell(gemmi::CrystalSystem system, const double len[3], const double ang[3]) {
const double r2d = 180.0 / PI;
UnitCell uc{};
switch (system) {
case gemmi::CrystalSystem::Hexagonal:
uc = {(float)len[0], (float)len[0], (float)len[2], 90.0f, 90.0f, 120.0f};
break;
case gemmi::CrystalSystem::Tetragonal:
uc = {(float)len[0], (float)len[0], (float)len[2], 90.0f, 90.0f, 90.0f};
break;
case gemmi::CrystalSystem::Cubic:
uc = {(float)len[0], (float)len[0], (float)len[0], 90.0f, 90.0f, 90.0f};
break;
case gemmi::CrystalSystem::Monoclinic:
uc = {(float)len[0], (float)len[1], (float)len[2], 90.0f, (float)(ang[0] * r2d), 90.0f};
break;
case gemmi::CrystalSystem::Triclinic:
uc = {(float)len[0], (float)len[1], (float)len[2],
(float)(ang[0] * r2d), (float)(ang[1] * r2d), (float)(ang[2] * r2d)};
break;
default: // orthorhombic
uc = {(float)len[0], (float)len[1], (float)len[2], 90.0f, 90.0f, 90.0f};
break;
}
return uc;
}
// Anchors the cell lengths to the input cell. Penalises each length's deviation from its input value
// with a large weight, breaking the low-resolution distance<->cell-scale degeneracy (position ~
// distance / cell_scale) so distance is determined by the data with the cell pinned.
struct CellLengthRegularizer {
double w0, w1, w2;
double l0, l1, l2;
template <typename T>
bool operator()(const T *const len, T *r) const {
r[0] = T(w0) * (len[0] - T(l0));
r[1] = T(w1) * (len[1] - T(l1));
r[2] = T(w2) * (len[2] - T(l2));
return true;
}
};
// Where a spot found at (x, y) on module m really is (ModuleShift).
void PlaceOnModule(const ModuleShift &m, const double move[3], double x, double y, double &px, double &py) {
const double ux = x - m.x0, uy = y - m.y0;
const double c = std::cos(move[2]), s = std::sin(move[2]);
px = m.x0 + c * ux - s * uy + move[0];
py = m.y0 + s * ux + c * uy + move[1];
}
// How a residual reads the beam block. Without the tilt refined it is the PONI, as everywhere else. With the
// tilt refined it is the DIRECT BEAM, the point the undeflected beam lands on, and the PONI is worked out from
// it: a tilt moves the whole pattern by D tan(tilt)/pixel, exactly as a moved PONI does, so in PONI terms
// the two trade tens of pixels for each other (and the beam's box cannot hold the trade), while the direct
// beam does not move with the tilt and the tilt is left with only what no beam can imitate - the keystone.
// In XtalResidual's frame the direct beam is where M (u, v) = (-D tan rot1, -D tan rot2 / cos rot1), with
// (u, v) its offset from the PONI in mm and M the image orientation (a mirror and quarter turns, so M^-1 = M^T).
struct BeamBlock {
bool direct = false;
double m00 = 1, m01 = 0, m10 = 0, m11 = 1; // DetectorOrientation::Matrix(), as XtalResidual takes it
double pixel = 1;
template <typename T, typename R>
void Poni(const T *const beam, const T &distance_mm, const R *const detector_rot, T *poni) const {
if (!direct) {
poni[0] = beam[0];
poni[1] = beam[1];
return;
}
using std::cos;
using std::tan;
const T dx = -distance_mm * tan(detector_rot[0]);
const T dy = -distance_mm * tan(detector_rot[1]) / cos(detector_rot[0]);
poni[0] = beam[0] - (T(m00) * dx + T(m10) * dy) / T(pixel);
poni[1] = beam[1] - (T(m01) * dx + T(m11) * dy) / T(pixel);
}
};
// The residual of one spot (XtalResidual) on the blocks this refinement can move, in this order: the beam
// (read through BeamBlock) and the distance as one block, the tilt where it is refined, the frame's orientation,
// the cell lengths, and the module's move (dx, dy, rot) where the spot's module is placed. The rotation axis, the
// cell angles and a held tilt enter as plain numbers.
//
// The residual is the difference of two halves that share no block: the observed reciprocal vector (beam,
// distance, tilt, move) and the predicted one (orientation, cell). Ceres' AutoDiffCostFunction would carry the
// derivatives of every block through both halves; here each half is differentiated on its own blocks only, which
// gives the same values and the same derivatives with half as many of them per number.
//
// A placed module: moving the spot by R(rot) u - u + (dx, dy), with (ux, uy) its offset from the module
// centre, shifts its offset from the beam exactly as moving the beam the other way does, so the beam handed
// to XtalResidual carries the move and everything else is the residual of an unmoved spot.
class SpotCost : public ceres::CostFunction {
public:
SpotCost(const XtalResidual &residual, const BeamBlock &beam_block, const double *detector_rot,
const double *rotation_axis, const double *cell_ang, bool tilt, bool module, double ux = 0,
double uy = 0)
: residual(residual), beam_block(beam_block), detector_rot(detector_rot), rotation_axis(rotation_axis),
cell_ang(cell_ang), tilt(tilt), module(module), ux(ux), uy(uy) {
set_num_residuals(3);
std::vector<int32_t> &sizes = *mutable_parameter_block_sizes();
sizes.push_back(3);
if (tilt)
sizes.push_back(2);
sizes.push_back(3);
sizes.push_back(3);
if (module)
sizes.push_back(3);
}
bool Evaluate(double const *const *parameters, double *residuals, double **jacobians) const override {
if (tilt)
return module ? EvaluateWith<true, true>(parameters, residuals, jacobians)
: EvaluateWith<true, false>(parameters, residuals, jacobians);
return module ? EvaluateWith<false, true>(parameters, residuals, jacobians)
: EvaluateWith<false, false>(parameters, residuals, jacobians);
}
private:
template <bool TILT, bool MODULE>
bool EvaluateWith(double const *const *p, double *out, double **jac) const {
constexpr int N_OBS = 3 + (TILT ? 2 : 0) + (MODULE ? 3 : 0);
using JO = ceres::Jet<double, N_OBS>;
using JP = ceres::Jet<double, 6>;
constexpr int TILT_BLOCK = 1, P0_BLOCK = TILT ? 2 : 1, P1_BLOCK = P0_BLOCK + 1, MOVE_BLOCK = P1_BLOCK + 1;
// The observed half, on the beam and distance, the tilt and the move.
JO bd[3], t[2], m[3];
for (int j = 0; j < 3; ++j)
bd[j] = JO(p[0][j], j);
if constexpr (TILT)
for (int j = 0; j < 2; ++j)
t[j] = JO(p[TILT_BLOCK][j], 3 + j);
if constexpr (MODULE)
for (int j = 0; j < 3; ++j)
m[j] = JO(p[MOVE_BLOCK][j], N_OBS - 3 + j);
JO obs[3];
if constexpr (TILT)
Observed(bd, t, MODULE ? m : nullptr, obs);
else
Observed(bd, detector_rot, MODULE ? m : nullptr, obs);
// The predicted half, on the orientation and the cell lengths.
JP p0[3], p1[3];
for (int j = 0; j < 3; ++j) {
p0[j] = JP(p[P0_BLOCK][j], j);
p1[j] = JP(p[P1_BLOCK][j], 3 + j);
}
const JP p2[3] = {JP(cell_ang[0]), JP(cell_ang[1]), JP(cell_ang[2])};
JP recip_unrot[3];
residual.PredictedRecipUnrot(p1, p2, recip_unrot);
JP pred[3];
const AngleAxisRotator<JP> rot_p0(p0);
rot_p0.Rotate(recip_unrot, pred);
for (int r = 0; r < 3; ++r)
out[r] = obs[r].a - pred[r].a;
if (!jac)
return true;
// Row-major 3 x size blocks; a block held constant has no Jacobian asked for.
auto fill = [](double *block, int size, auto derivative) {
if (block)
for (int r = 0; r < 3; ++r)
for (int c = 0; c < size; ++c)
block[r * size + c] = derivative(r, c);
};
fill(jac[0], 3, [&](int r, int c) { return obs[r].v[c]; });
if constexpr (TILT)
fill(jac[TILT_BLOCK], 2, [&](int r, int c) { return obs[r].v[3 + c]; });
if constexpr (MODULE)
fill(jac[MOVE_BLOCK], 3, [&](int r, int c) { return obs[r].v[N_OBS - 3 + c]; });
fill(jac[P0_BLOCK], 3, [&](int r, int c) { return -pred[r].v[c]; });
fill(jac[P1_BLOCK], 3, [&](int r, int c) { return -pred[r].v[3 + c]; });
return true;
}
template <typename T, typename R>
void Observed(const T *const beam_distance, const R *const tilt, const T *const move, T *recip_obs) const {
using std::cos;
using std::sin;
T b[2];
beam_block.Poni(beam_distance, beam_distance[2], tilt, b);
if (move) {
const T c = cos(move[2]), s = sin(move[2]);
b[0] = b[0] - ((c - T(1)) * T(ux) - s * T(uy) + move[0]);
b[1] = b[1] - (s * T(ux) + (c - T(1)) * T(uy) + move[1]);
}
const R axis[3] = {R(rotation_axis[0]), R(rotation_axis[1]), R(rotation_axis[2])};
residual.ObservedRecip(b, beam_distance[2], tilt, axis, recip_obs);
}
const XtalResidual residual;
const BeamBlock beam_block;
const double *detector_rot; // the tilt where it is held
const double *rotation_axis;
const double *cell_ang;
const bool tilt, module;
const double ux, uy;
};
// The residual of a fit that moves only the crystal orientations (refine_beam_distance off, no module
// placed): the observed reciprocal vector and the unrotated prediction are then constants of the spot, taken
// once in plain numbers, and only the orientation's three derivatives are carried.
struct OrientationResidual {
double recip_obs[3];
double recip_unrot[3];
template <typename T>
bool operator()(const T *const p0, T *out) const {
T e_pred_recip[3];
const AngleAxisRotator<T> rot_p0(p0);
rot_p0.Rotate(recip_unrot, e_pred_recip);
out[0] = recip_obs[0] - e_pred_recip[0];
out[1] = recip_obs[1] - e_pred_recip[1];
out[2] = recip_obs[2] - e_pred_recip[2];
return true;
}
};
// What module moves cannot be told apart from: all modules shifted alike is the beam centre, all turned
// alike (about their own centres) is the crystal orientations, and all pushed outwards alike is the
// distance. The sums of those three over the moved modules are held at zero - the beam, the orientations
// and the distance then carry them - so the modules are left with what only they can explain. The sums are
// weighted by the spots each module holds: a module the frames barely reach is placed poorly, and an
// unweighted sum would hand its error to all the others.
//
// The detector tilt is not among them. Within one module a tilt is a gradient (a scale and a shear across
// it), which no rigid move of the module makes, and with the tilt refined the placement gains no new
// direction it cannot tell apart; holding the modules' moves to no tilt-like pattern as well only cost
// accuracy on frames the fit had not seen.
struct ModuleGauge {
std::vector<std::array<double, 2>> outward; // unit vector from the beam to each module centre
std::vector<double> share; // each module's fraction of the spots
double lever_px; // turns are weighed at this distance from the centre
double weight;
template <typename T>
bool operator()(T const *const *move, T *out) const {
T sx(0), sy(0), sr(0), so(0);
for (size_t i = 0; i < outward.size(); ++i) {
const T w(share[i]);
sx += w * move[i][0];
sy += w * move[i][1];
sr += w * move[i][2] * T(lever_px);
so += w * (move[i][0] * T(outward[i][0]) + move[i][1] * T(outward[i][1]));
}
out[0] = T(weight) * sx;
out[1] = T(weight) * sy;
out[2] = T(weight) * sr;
out[3] = T(weight) * so;
return true;
}
};
} // namespace
GeometryRefinerResult RefineGlobalGeometry(const DiffractionGeometry &nominal_geom,
const UnitCell &input_cell,
const std::vector<GeomRefineFrame> &frames,
const GeometryRefinerSettings &settings) {
GeometryRefinerResult result;
try {
const gemmi::CrystalSystem system = MapSystem(settings.crystal_system);
// Shared geometry parameter blocks (refined). The rotation axis is constant, and so is the detector tilt
// unless settings.refine_tilt. The beam and the distance are one block of three: every block refined
// beside it has three parameters too (orientations, cell lengths, module moves), so Ceres eliminates the
// orientations with its fixed-size Schur code rather than the general one (1.7x faster on one thread).
double beam_distance[3] = {nominal_geom.GetBeamX_pxl(), nominal_geom.GetBeamY_pxl(),
nominal_geom.GetDetectorDistance_mm()};
double *const beam = beam_distance;
double &distance_mm = beam_distance[2];
double detector_rot[2] = {nominal_geom.GetPoniRot1_rad(), nominal_geom.GetPoniRot2_rad()};
double rot_vec[3] = {1.0, 0.0, 0.0};
const double rot3 = nominal_geom.GetPoniRot3_rad();
// Same for every spot of every frame, so taken once here rather than per residual.
const double cos_rot3 = std::cos(rot3), sin_rot3 = std::sin(rot3);
const DetectorOrientation orientation = nominal_geom.GetOrientation();
const double lambda = nominal_geom.GetWavelength_A();
const double pixel = nominal_geom.GetPixelSize_mm();
// With the tilt refined, the beam block is the direct beam (BeamBlock), started and bounded where the
// nominal geometry puts the direct beam.
const bool refine_tilt = settings.refine_tilt && settings.refine_beam_distance;
BeamBlock beam_block;
if (refine_tilt) {
const RotMatrix m = orientation.Matrix();
beam_block = {true, m.Column(0).x, m.Column(1).x, m.Column(0).y, m.Column(1).y, pixel};
double poni_at_zero[2];
const double zero[2] = {0, 0};
beam_block.Poni(zero, distance_mm, detector_rot, poni_at_zero);
beam[0] -= poni_at_zero[0];
beam[1] -= poni_at_zero[1];
}
const double beam0[2] = {beam[0], beam[1]};
// The PONI the beam block stands for, at the current tilt and distance.
auto poni = [&](double &x, double &y) {
double p[2];
beam_block.Poni(beam, distance_mm, detector_rot, p);
x = p[0];
y = p[1];
};
// Shared cell blocks. Lengths refined (regularized); angles constant.
double cell_len[3] = {input_cell.a, input_cell.b, input_cell.c};
const double cell_len0[3] = {input_cell.a, input_cell.b, input_cell.c};
double cell_ang[3];
InitCellAngles(system, input_cell, cell_ang);
double eff_len[3], eff_alpha, eff_beta, eff_gamma; // recomputed each round from cell_len/ang
// Per-frame orientation seeds.
std::vector<std::array<double, 3>> orient(frames.size());
for (size_t i = 0; i < frames.size(); ++i)
OrientationSeed(system, frames[i].lattice, orient[i].data());
// Reciprocal length of one detector pixel at the nominal geometry, used to scale the robust
// loss (~3 px) into the reciprocal-space residual units.
const double recip_per_px = pixel / (distance_mm * lambda);
const double loss_scale = 3.0 * recip_per_px;
// The modules' moves (dx, dy, rot), starting where settings put them. Which of them are refined is
// decided once, on the indexed spots each holds, so the problem keeps its shape from round to round.
const auto &modules = settings.modules;
std::vector<std::array<double, 3>> move(modules.size());
for (size_t m = 0; m < modules.size(); ++m)
move[m] = {modules[m].dx, modules[m].dy, modules[m].rot_rad};
// A module counts the spots on it that its frame's lattice indexes where the module starts - not
// every spot found on it: a frame's other spots (noise, a second lattice, ice) would otherwise make a
// module the frames barely reach look well determined.
std::vector<int> module_spots(modules.size(), 0);
for (const auto &f : frames) {
const Coord v0 = f.lattice.Vec0(), v1 = f.lattice.Vec1(), v2 = f.lattice.Vec2();
for (const auto &s : f.spots)
if (s.module >= 0 && static_cast<size_t>(s.module) < modules.size()) {
double x, y;
PlaceOnModule(modules[s.module], move[s.module].data(), s.x, s.y, x, y);
const Coord recip = nominal_geom.DetectorToRecip(x, y);
const double hf = recip * v0, kf = recip * v1, lf = recip * v2;
if (std::fabs(hf - std::round(hf)) < 0.15 && std::fabs(kf - std::round(kf)) < 0.15
&& std::fabs(lf - std::round(lf)) < 0.15)
module_spots[s.module]++;
}
}
std::vector<bool> refined(modules.size(), false);
int refined_count = 0;
for (size_t m = 0; m < modules.size(); ++m)
if (settings.refine_modules && module_spots[m] >= settings.min_module_spots) {
refined[m] = true;
refined_count++;
}
// One module alone has nothing to be placed against: its move is the beam and the orientation.
if (refined_count < 2)
std::fill(refined.begin(), refined.end(), false);
// A module too thin to be placed stays where it was given, whatever its start: a search on a few dozen
// spots finds noise.
if (settings.refine_modules)
for (size_t m = 0; m < modules.size(); ++m)
if (!refined[m])
move[m] = {0, 0, 0};
// Where nothing but the crystal orientations moves, each spot's residual is reduced to them
// (OrientationResidual).
const bool orientation_only = !settings.refine_beam_distance
&& std::none_of(refined.begin(), refined.end(), [](bool r) { return r; });
auto place = [&](const GeomRefineSpot &s, double &x, double &y) {
if (s.module >= 0 && static_cast<size_t>(s.module) < modules.size())
PlaceOnModule(modules[s.module], move[s.module].data(), s.x, s.y, x, y);
else {
x = s.x;
y = s.y;
}
};
// Tolerance schedule (fractional-hkl norm), tightening each round like the per-image optimizer.
auto round_tol = [&](int r) {
if (settings.rounds <= 1) return 0.2;
const double t = static_cast<double>(r) / (settings.rounds - 1);
return 0.3 - (0.3 - 0.1) * t;
};
ceres::CauchyLoss loss(loss_scale);
// Whether the last solve that ran produced a usable solution; folded into result.ok below,
// which otherwise reports success on spot and frame counts alone.
bool solve_usable = false;
for (int round = 0; round < settings.rounds; ++round) {
EffectiveCell(system, cell_len, cell_ang, eff_len, eff_alpha, eff_beta, eff_gamma);
double poni_x, poni_y;
poni(poni_x, poni_y);
DiffractionGeometry cur = nominal_geom;
cur.BeamX_pxl(poni_x).BeamY_pxl(poni_y).DetectorDistance_mm(distance_mm)
.PoniRot1_rad(static_cast<float>(detector_rot[0])).PoniRot2_rad(static_cast<float>(detector_rot[1]));
const double tol = round_tol(round);
const double tol_sq = tol * tol;
// One robust loss for every spot, kept here rather than one allocated (and freed) per spot.
ceres::Problem::Options problem_options;
problem_options.loss_function_ownership = ceres::DO_NOT_TAKE_OWNERSHIP;
ceres::Problem problem(problem_options);
auto ordering = std::make_shared<ceres::ParameterBlockOrdering>();
int spots_used = 0, frames_used = 0;
for (size_t i = 0; i < frames.size(); ++i) {
const CrystalLattice latt = AngleAxisAndCellToLattice(
orient[i].data(), eff_len, eff_alpha, eff_beta, eff_gamma);
const Coord v0 = latt.Vec0(), v1 = latt.Vec1(), v2 = latt.Vec2();
int used_in_frame = 0;
for (const auto &s : frames[i].spots) {
double x, y;
place(s, x, y);
const Coord recip = cur.DetectorToRecip(x, y);
const double hf = recip * v0, kf = recip * v1, lf = recip * v2;
const double h = std::round(hf), k = std::round(kf), l = std::round(lf);
const double dn = (hf - h) * (hf - h) + (kf - k) * (kf - k) + (lf - l) * (lf - l);
if (dn > tol_sq)
continue;
const XtalResidual xr(x, y, lambda, pixel, cos_rot3, sin_rot3, 0.0, h, k, l, system, orientation);
if (orientation_only) {
auto *r = new OrientationResidual;
double b[2];
beam_block.Poni(beam, distance_mm, detector_rot, b);
xr.ObservedRecip(b, distance_mm, detector_rot, rot_vec, r->recip_obs);
xr.PredictedRecipUnrot(cell_len, cell_ang, r->recip_unrot);
problem.AddResidualBlock(new ceres::AutoDiffCostFunction<OrientationResidual, 3, 3>(r),
&loss, orient[i].data());
} else if (s.module >= 0 && static_cast<size_t>(s.module) < modules.size() && refined[s.module]) {
// The spot as found: the module's move is a block of the residual.
const auto &m = modules[s.module];
const XtalResidual found(s.x, s.y, lambda, pixel, cos_rot3, sin_rot3, 0.0, h, k, l, system,
orientation);
auto *cost = new SpotCost(found, beam_block, detector_rot, rot_vec, cell_ang, refine_tilt, true,
s.x - m.x0, s.y - m.y0);
if (refine_tilt)
problem.AddResidualBlock(cost, &loss, beam_distance, detector_rot, orient[i].data(),
cell_len, move[s.module].data());
else
problem.AddResidualBlock(cost, &loss, beam_distance, orient[i].data(), cell_len,
move[s.module].data());
} else {
auto *cost = new SpotCost(xr, beam_block, detector_rot, rot_vec, cell_ang, refine_tilt, false);
if (refine_tilt)
problem.AddResidualBlock(cost, &loss, beam_distance, detector_rot, orient[i].data(),
cell_len);
else
problem.AddResidualBlock(cost, &loss, beam_distance, orient[i].data(), cell_len);
}
++used_in_frame;
++spots_used;
}
if (used_in_frame > 0) {
ordering->AddElementToGroup(orient[i].data(), 0); // eliminate orientations first
++frames_used;
}
}
if (spots_used < settings.min_spots_total) {
if (round == 0)
return result; // ok stays false
break; // keep the previous round's solution
}
// Cell-length regularizer (weight ~ coeff * sqrt(N_obs) / L0^2 -> effectively pins the cell).
const double sqrtN = std::sqrt(static_cast<double>(spots_used));
if (settings.refine_beam_distance) {
CellLengthRegularizer *reg = new CellLengthRegularizer{
settings.cell_reg_coeff * sqrtN / (cell_len0[0] * cell_len0[0]),
settings.cell_reg_coeff * sqrtN / (cell_len0[1] * cell_len0[1]),
settings.cell_reg_coeff * sqrtN / (cell_len0[2] * cell_len0[2]),
cell_len0[0], cell_len0[1], cell_len0[2]};
problem.AddResidualBlock(
new ceres::AutoDiffCostFunction<CellLengthRegularizer, 3, 3>(reg), nullptr, cell_len);
}
// Shared blocks go in the second elimination group (those the problem has; constant ones are
// stripped by Ceres).
for (double *b : {beam_distance, detector_rot, cell_len})
if (problem.HasParameterBlock(b))
ordering->AddElementToGroup(b, 1);
// The refined modules' moves: bounded to what a misplaced module plausibly is, and held to
// zero in sum by the gauge (ModuleGauge). A 1 px mean shift costs as much there as moving
// every spot by 1 px would, ten times over.
std::vector<size_t> moved;
for (size_t m = 0; m < modules.size(); ++m)
if (refined[m] && problem.HasParameterBlock(move[m].data()))
moved.push_back(m);
if (moved.size() >= 2) {
auto *gauge = new ModuleGauge;
double lever = 0, total = 0;
for (size_t m : moved)
total += module_spots[m];
for (size_t m : moved) {
const double ox = modules[m].x0 - nominal_geom.GetBeamX_pxl();
const double oy = modules[m].y0 - nominal_geom.GetBeamY_pxl();
const double r = std::max(1.0, std::hypot(ox, oy));
gauge->outward.push_back({ox / r, oy / r});
gauge->share.push_back(module_spots[m] / total);
lever += r;
}
gauge->lever_px = lever / static_cast<double>(moved.size());
gauge->weight = 10.0 * recip_per_px * sqrtN;
auto *cost = new ceres::DynamicAutoDiffCostFunction<ModuleGauge, 4>(gauge);
std::vector<double *> blocks;
for (size_t m : moved) {
cost->AddParameterBlock(3);
blocks.push_back(move[m].data());
}
cost->SetNumResiduals(4);
problem.AddResidualBlock(cost, nullptr, blocks);
}
for (size_t m : moved) {
ordering->AddElementToGroup(move[m].data(), 1);
const double start[3] = {modules[m].dx, modules[m].dy, modules[m].rot_rad};
const double range[3] = {12.0, 12.0, 1.5 * PI / 180.0};
for (int j = 0; j < 3; ++j) {
problem.SetParameterLowerBound(move[m].data(), j, start[j] - range[j]);
problem.SetParameterUpperBound(move[m].data(), j, start[j] + range[j]);
}
}
// Beam + distance bounds around the nominal value; cell lengths loosely bounded (the
// regularizer does the anchoring).
if (!orientation_only) {
problem.SetParameterLowerBound(beam_distance, 0, beam0[0] - settings.beam_range_px);
problem.SetParameterUpperBound(beam_distance, 0, beam0[0] + settings.beam_range_px);
problem.SetParameterLowerBound(beam_distance, 1, beam0[1] - settings.beam_range_px);
problem.SetParameterUpperBound(beam_distance, 1, beam0[1] + settings.beam_range_px);
problem.SetParameterLowerBound(beam_distance, 2,
std::max(1.0, nominal_geom.GetDetectorDistance_mm() - settings.distance_range_mm));
problem.SetParameterUpperBound(beam_distance, 2,
nominal_geom.GetDetectorDistance_mm() + settings.distance_range_mm);
for (int j = 0; j < 3; ++j) {
problem.SetParameterLowerBound(cell_len, j, 0.7 * cell_len0[j]);
problem.SetParameterUpperBound(cell_len, j, 1.3 * cell_len0[j]);
}
if (!settings.refine_beam_distance) {
problem.SetParameterBlockConstant(beam_distance);
problem.SetParameterBlockConstant(cell_len);
} else if (!settings.refine_distance)
problem.SetManifold(beam_distance, new ceres::SubsetManifold(3, {2}));
}
if (refine_tilt) {
const double tilt_range = 2.0 * PI / 180.0;
for (int j = 0; j < 2; ++j) {
problem.SetParameterLowerBound(detector_rot, j, (j == 0 ? nominal_geom.GetPoniRot1_rad()
: nominal_geom.GetPoniRot2_rad()) - tilt_range);
problem.SetParameterUpperBound(detector_rot, j, (j == 0 ? nominal_geom.GetPoniRot1_rad()
: nominal_geom.GetPoniRot2_rad()) + tilt_range);
}
}
ceres::Solver::Options options;
options.linear_solver_type = ceres::DENSE_SCHUR;
options.linear_solver_ordering = ordering;
options.num_threads = std::max(1, settings.num_threads);
options.max_num_iterations = 100;
options.max_solver_time_in_seconds = 60.0;
options.logging_type = ceres::LoggingType::SILENT;
options.minimizer_progress_to_stdout = false;
ceres::Solver::Summary summary;
ceres::Solve(options, &problem, &summary);
solve_usable = summary.IsSolutionUsable();
result.frames_used = frames_used;
result.spots_used = spots_used;
}
// Final fit quality: median detector residual of the retained spots at the refined geometry.
EffectiveCell(system, cell_len, cell_ang, eff_len, eff_alpha, eff_beta, eff_gamma);
double poni_x, poni_y;
poni(poni_x, poni_y);
DiffractionGeometry cur = nominal_geom;
cur.BeamX_pxl(poni_x).BeamY_pxl(poni_y).DetectorDistance_mm(distance_mm)
.PoniRot1_rad(static_cast<float>(detector_rot[0])).PoniRot2_rad(static_cast<float>(detector_rot[1]));
std::vector<double> residuals;
constexpr double CAP_PX = 2.0;
double capped_sum = 0;
size_t capped_n = 0;
std::vector<double> module_sq(modules.size(), 0), module_d(modules.size(), 0);
std::vector<size_t> module_n(modules.size(), 0);
result.predicted_px.resize(frames.size());
for (size_t i = 0; i < frames.size(); ++i) {
const CrystalLattice latt = AngleAxisAndCellToLattice(
orient[i].data(), eff_len, eff_alpha, eff_beta, eff_gamma);
const Coord a = latt.Astar(), b = latt.Bstar(), c = latt.Cstar();
const Coord v0 = latt.Vec0(), v1 = latt.Vec1(), v2 = latt.Vec2();
for (const auto &s : frames[i].spots) {
double x, y;
place(s, x, y);
const Coord recip = cur.DetectorToRecip(x, y);
const double hf = recip * v0, kf = recip * v1, lf = recip * v2;
const double h = std::round(hf), k = std::round(kf), l = std::round(lf);
const double dn = (hf - h) * (hf - h) + (kf - k) * (kf - k) + (lf - l) * (lf - l);
const Coord recip_pred = a * (float)h + b * (float)k + c * (float)l;
const auto [px, py] = cur.RecipToDetector(recip_pred);
const double res = (std::isfinite(px) && std::isfinite(py)) ? std::hypot(px - x, py - y) : CAP_PX;
capped_sum += std::min(res, CAP_PX) * std::min(res, CAP_PX);
capped_n++;
// The prediction where the spot would be found: the spot's own module's move taken back.
float fx = NAN, fy = NAN;
if (std::isfinite(px) && std::isfinite(py)) {
fx = static_cast<float>(s.x + (px - x));
fy = static_cast<float>(s.y + (py - y));
}
result.predicted_px[i].push_back({fx, fy});
if (s.module >= 0 && static_cast<size_t>(s.module) < modules.size()) {
module_sq[s.module] += std::min(res, CAP_PX) * std::min(res, CAP_PX);
module_d[s.module] += 1.0 / std::max(1e-6f, recip.Length());
module_n[s.module]++;
}
if (dn > 0.1 * 0.1)
continue;
if (std::isfinite(px) && std::isfinite(py))
residuals.push_back(res);
}
}
if (capped_n > 0)
result.capped_rms_px = std::sqrt(capped_sum / static_cast<double>(capped_n));
if (!residuals.empty()) {
std::nth_element(residuals.begin(), residuals.begin() + residuals.size() / 2, residuals.end());
result.median_residual_px = residuals[residuals.size() / 2];
}
result.ok = solve_usable && result.spots_used >= settings.min_spots_total && result.frames_used > 0;
result.beam_x_px = poni_x;
result.beam_y_px = poni_y;
result.distance_mm = distance_mm;
result.cell = BuildUnitCell(system, cell_len, cell_ang);
result.rot1_rad = detector_rot[0];
result.rot2_rad = detector_rot[1];
result.module_capped_rms_px.resize(modules.size(), 0);
result.module_mean_d_A.resize(modules.size(), 0);
for (size_t m = 0; m < modules.size(); ++m)
if (module_n[m] > 0) {
result.module_capped_rms_px[m] = std::sqrt(module_sq[m] / static_cast<double>(module_n[m]));
result.module_mean_d_A[m] = module_d[m] / static_cast<double>(module_n[m]);
}
result.modules = modules;
for (size_t m = 0; m < modules.size(); ++m) {
result.modules[m].dx = move[m][0];
result.modules[m].dy = move[m][1];
result.modules[m].rot_rad = move[m][2];
result.modules[m].spots = module_spots[m];
}
return result;
} catch (...) {
result.ok = false;
return result;
}
}
std::vector<ModuleScan> ScanModuleShifts(const DiffractionGeometry &geom,
const std::vector<GeomRefineFrame> &frames,
const std::vector<ModuleShift> &modules,
double range_px, size_t nthreads) {
// A spot is on its lattice when every fractional index is within this of a whole number.
constexpr double ON_LATTICE = 0.15;
struct Spot { float x, y; int frame; };
std::vector<std::vector<Spot>> on_module(modules.size());
for (size_t i = 0; i < frames.size(); i++)
for (const auto *list : {&frames[i].spots, &frames[i].unindexed})
for (const auto &s : *list)
if (s.module >= 0 && static_cast<size_t>(s.module) < modules.size())
on_module[s.module].push_back({s.x, s.y, static_cast<int>(i)});
std::vector<std::array<Coord, 3>> axes(frames.size());
for (size_t i = 0; i < frames.size(); i++)
axes[i] = {frames[i].lattice.Vec0(), frames[i].lattice.Vec1(), frames[i].lattice.Vec2()};
auto score = [&](const std::vector<Spot> &spots, const ModuleShift &m, double dx, double dy) {
int n = 0;
for (const auto &s : spots) {
double x, y;
const double move[3] = {m.dx + dx, m.dy + dy, m.rot_rad};
PlaceOnModule(m, move, s.x, s.y, x, y);
const Coord recip = geom.DetectorToRecip(x, y);
bool on = true;
for (const auto &v : axes[s.frame]) {
const double f = recip * v;
on &= std::fabs(f - std::round(f)) < ON_LATTICE;
}
n += on;
}
return n;
};
std::vector<ModuleScan> out(modules.size());
for (size_t m = 0; m < modules.size(); m++) {
auto &r = out[m];
r.on_lattice_at_zero = r.on_lattice_at_best = score(on_module[m], modules[m], 0, 0);
// Coarse: whole-pixel steps over the range; then half-pixel steps around the best of them.
for (int pass = 0; pass < 2; pass++) {
const double step = pass == 0 ? 1.0 : 0.5;
const double half = pass == 0 ? range_px : 1.0;
const double cx = r.dx, cy = r.dy;
std::vector<double> offsets;
for (double d = -half; d <= half; d += step)
offsets.push_back(d);
// Every shift of the grid is scored on the workers, then the grid is walked in order: the first
// shift with the most spots wins, as it would on one thread.
const int n = static_cast<int>(offsets.size());
std::vector<int> on_lattice(n * n);
ParallelFor(n * n, nthreads, [&](int k) {
on_lattice[k] = score(on_module[m], modules[m], cx + offsets[k % n], cy + offsets[k / n]);
});
for (int k = 0; k < n * n; k++)
if (on_lattice[k] > r.on_lattice_at_best) {
r.on_lattice_at_best = on_lattice[k];
r.dx = cx + offsets[k % n];
r.dy = cy + offsets[k / n];
}
}
}
return out;
}