Files
Jungfraujoch/image_analysis/bragg_integration/BackgroundAperture.cpp
T
leonarski_f fac2a17428 Radial background: with the frame's curve, the correction is taken over the pixels read, at their 2 theta
With the frame's curve in use (D5: stills, and rotation runs whose empty apertures ask for it) the
correction was a precomputed annulus-minus-disk kernel over radial offset, applied to the curve at the
reflection's distance from the PONI. The empty apertures that decide it compute the same quantity over
the pixels they actually read, at each pixel's own 2 theta. The two differ exactly next to the beam stop:
the ring's beam-side pixels are masked by the shadow, but the kernel still averaged the curve over them
(the curve there holds the shadow's edge, a cliff of several hundred counts), and on a tilted detector
the PONI is a few pixels from where the beam lands, where the curve is steepest. On a binned-Rayonix
still run with the beam stop off the beam this sent low-resolution reflections next to the stop to large
negative intensities (median -854 -> -4171 at 42-50 px), destabilised the per-image scales and collapsed
the lowest shell's CC1/2 (0.906 -> 0.448, "not usable" warning).

Now, where the frame's curve is in use:
- the correction is the curve's mean over the ring pixels the background was taken from (after the
  clip) minus its mean over the readable disk pixels (BraggCurveCorrection), summed in pass A while the
  box is read anyway - in fixed point (1/256 count), so CPU and GPU sums are exact and order-independent;
- the curve is read at the 2 theta of the reflection's position (CurveRadius, from the geometry), the
  radius it is tabulated against, and the clip offset follows it there;
- BackgroundAperture takes the curve's mean over the ring pixels the clip kept, so the decision
  measures exactly what is applied.
The kernel stays for the curve accumulated from the reflections' rings (rotation's per-image ice gate),
unchanged. Metal unchanged (it hands such frames to the CPU engine).

Validation. Rotation, CPU A/B vs 87684012f over 18 sets: .hkl byte-identical on the 12 sets where D5 is
off (and on the 3 ice-gated D14 sets identical to D5); the three D5-on sets improve: a home-source CCD
set R-free 0.210 -> 0.194 (D5 0.201), ISa 10.4 -> 10.8, anomalous 3.70 -> 3.94; the ice set
0.315 -> 0.312, ISa 22.3 -> 22.7 (D5 lost ISa there); the third neutral. Stills (0-cycle REFMAC, 9 sets):
R-free within +0.0021/-0.0039 of 87684012f on every set, verdicts unchanged except one draw -> win,
no "not usable" warning on any set (two base runs had one). The lowest shell's CC1/2 on the run above
stays low (0.44): it is set by three to five reflections at 30-41 A in the penumbra of the stop, which
integrate as garbage with every variant (the uncorrected run included); with the merge's low-resolution
limit at 30 A it reads 0.79.

Tests: BraggIntegrationEngineCPU_RadialCurveOverThePixelsRead (shadow edge on a tilted detector; fails
with the kernel or with the PONI radius), the GPU parity test now with a masked ring.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu
(cherry picked from commit d225b546c613ab2266c63ff2add02624b04d5e25)
2026-10-24 07:27:12 +02:00

204 lines
8.5 KiB
C++

// SPDX-FileCopyrightText: 2026 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#include "BackgroundAperture.h"
#include <algorithm>
#include <cmath>
#include "../../common/JFJochMath.h"
std::vector<float> background_aperture::CandidateR3(float r2, float max_r3) {
std::vector<float> out;
for (float r3 = r2 + 2.0f; r3 <= max_r3 + 1e-3f; r3 += 1.0f)
out.push_back(r3);
return out;
}
void background_aperture::MeasureFrame(ImagePreprocessorBuffer &image, int width, int height,
const std::vector<DiffractionSpot> &spots, float r1, float r2,
const std::vector<float> &r3, float clip_nsigma, float gain,
const RingBackground &rings, const DiffractionGeometry &geometry,
const DetectorModules &modules, Tally &tally) {
if (r3.empty())
return;
tally.sum_d2.resize(r3.size(), 0.0);
tally.sum_d2_radial.resize(r3.size(), 0.0);
tally.sum_dd2.resize(r3.size(), 0.0);
const float r_max = r3.back();
const int half = static_cast<int>(std::ceil(r_max));
const int side = 2 * half + 1;
// A grid of centres, at least one aperture apart, kept clear of every found spot.
const double area = static_cast<double>(width) * height;
const int step = std::max(side, static_cast<int>(std::ceil(std::sqrt(area / MAX_APERTURES_PER_FRAME))));
const float clear = r_max + SPOT_CLEARANCE_PX;
std::vector<int32_t> cx, cy;
for (int y = half; y + half < height; y += step)
for (int x = half; x + half < width; x += step) {
bool near_spot = false;
for (const auto &s : spots) {
const Coord c = s.RawCoord();
if ((c.x - x) * (c.x - x) + (c.y - y) * (c.y - y) < clear * clear) {
near_spot = true;
break;
}
}
if (!near_spot) {
cx.push_back(x);
cy.push_back(y);
}
}
if (cx.empty())
return;
const int32_t *tiles = image.GatherTiles(cx, cy, width, half);
struct Pixel {
int32_t v;
float d2; // squared distance from the aperture centre
double b; // the ring background at this pixel's resolution
};
std::vector<Pixel> disk, ring;
for (size_t a = 0; a < cx.size(); ++a) {
const int32_t *t = tiles + a * static_cast<size_t>(side) * side;
const int64_t panel = modules.ModuleOfImagePixel(cx[a], cy[a]);
bool readable = true;
disk.clear();
ring.clear();
for (int dy = -half; dy <= half && readable; ++dy)
for (int dx = -half; dx <= half; ++dx) {
const float d2 = static_cast<float>(dx * dx + dy * dy);
if (d2 >= r_max * r_max || (d2 >= r1 * r1 && d2 < r2 * r2))
continue;
const int32_t v = t[(dy + half) * side + dx + half];
if (v == INT32_MIN || v == INT32_MAX) {
readable = false;
break;
}
double b = 0.0;
if (!rings.empty()) {
const auto [px, py] = modules.ImageToPlane(panel, cx[a] + dx, cy[a] + dy);
b = rings.At(2.0 * PI / geometry.PxlToRes(static_cast<float>(px), static_cast<float>(py)));
}
(d2 < r1 * r1 ? disk : ring).push_back({v, d2, b});
}
if (!readable || disk.empty())
continue;
double disk_v = 0.0, disk_b = 0.0;
for (const auto &p : disk) {
disk_v += p.v;
disk_b += p.b;
}
disk_v /= static_cast<double>(disk.size());
disk_b /= static_cast<double>(disk.size());
// The curve at the aperture's centre, which the corrected clip measures the ring's rise from.
double centre_b = 0.0;
if (!rings.empty()) {
const auto [px, py] = modules.ImageToPlane(panel, cx[a], cy[a]);
centre_b = rings.At(2.0 * PI / geometry.PxlToRes(static_cast<float>(px), static_cast<float>(py)));
}
// Every candidate ring as the integrator reads it: the mean, then one high-side clip pass. With the
// radial correction, as the integrator applies it: the clip follows the curve (each pixel's
// threshold raised by the curve's rise from the centre to it, in whole counts -
// RadialClipOffset), and the correction is the curve's mean over the ring pixels the clip kept
// minus its mean over the disk (BraggCurveCorrection).
std::vector<double> d_plain(r3.size()), d_radial(r3.size());
bool measured = true;
for (size_t k = 0; k < r3.size() && measured; ++k) {
const float r3_sq = r3[k] * r3[k];
double sum = 0.0;
int n = 0;
for (const auto &p : ring)
if (p.d2 < r3_sq) {
sum += p.v;
++n;
}
if (n == 0) {
measured = false;
break;
}
const double mean = sum / n;
const double thr = mean + clip_nsigma * std::sqrt(gain * std::max(mean, static_cast<double>(gain)));
double kept = 0.0, kept_radial = 0.0, kept_radial_b = 0.0;
int n_kept = 0, n_kept_radial = 0;
for (const auto &p : ring) {
if (p.d2 >= r3_sq)
continue;
if (clip_nsigma <= 0.0f || p.v <= thr) {
kept += p.v;
++n_kept;
}
if (clip_nsigma <= 0.0f || p.v <= thr + static_cast<double>(std::lround(p.b - centre_b))) {
kept_radial += p.v;
kept_radial_b += p.b;
++n_kept_radial;
}
}
measured = n_kept > 0 && n_kept_radial > 0;
if (measured) {
d_plain[k] = disk_v - kept / n_kept;
d_radial[k] = disk_v - kept_radial / n_kept_radial - (disk_b - kept_radial_b / n_kept_radial);
}
}
if (!measured)
continue;
for (size_t k = 0; k < r3.size(); ++k) {
tally.sum_d2[k] += d_plain[k] * d_plain[k];
if (!rings.empty()) {
tally.sum_d2_radial[k] += d_radial[k] * d_radial[k];
const double dd = d_radial[k] * d_radial[k] - d_plain[k] * d_plain[k];
tally.sum_dd2[k] += dd * dd;
}
}
++tally.apertures;
if (!rings.empty())
++tally.apertures_radial;
}
}
void background_aperture::Tally::Add(const Tally &other) {
sum_d2.resize(std::max(sum_d2.size(), other.sum_d2.size()), 0.0);
sum_d2_radial.resize(std::max(sum_d2_radial.size(), other.sum_d2_radial.size()), 0.0);
for (size_t k = 0; k < other.sum_d2.size(); ++k)
sum_d2[k] += other.sum_d2[k];
for (size_t k = 0; k < other.sum_d2_radial.size(); ++k)
sum_d2_radial[k] += other.sum_d2_radial[k];
sum_dd2.resize(std::max(sum_dd2.size(), other.sum_dd2.size()), 0.0);
for (size_t k = 0; k < other.sum_dd2.size(); ++k)
sum_dd2[k] += other.sum_dd2[k];
apertures += other.apertures;
apertures_radial += other.apertures_radial;
}
std::vector<double> background_aperture::Tally::MeanSquare(bool radial) const {
const size_t n = radial ? apertures_radial : apertures;
std::vector<double> out;
if (n == 0)
return out;
for (const double v : radial ? sum_d2_radial : sum_d2)
out.push_back(v / static_cast<double>(n));
return out;
}
double background_aperture::Tally::RadialZ(size_t k) const {
if (apertures_radial < 2 || apertures_radial != apertures || k >= sum_dd2.size())
return 0.0;
const double n = static_cast<double>(apertures_radial);
const double mean = (sum_d2_radial[k] - sum_d2[k]) / n;
const double var = std::max(sum_dd2[k] / n - mean * mean, 0.0);
return var > 0.0 ? -mean / std::sqrt(var / n) : 0.0;
}
int background_aperture::Best(const std::vector<double> &mean_square) {
if (mean_square.empty())
return -1;
return static_cast<int>(std::min_element(mean_square.begin(), mean_square.end()) - mean_square.begin());
}
bool background_aperture::RadialHelps(const Tally &tally, size_t k, double min_gain) {
if (tally.apertures == 0 || tally.apertures_radial != tally.apertures || k >= tally.sum_d2.size())
return false;
return tally.sum_d2_radial[k] < (1.0 - min_gain) * tally.sum_d2[k];
}