Files
Jungfraujoch/image_analysis/bragg_integration/BackgroundAperture.cpp
T
leonarski_fandClaude Opus 5.5 07a43a13eb Stills: the radial curvature correction decided per run on the same empty apertures
The first stills battery of e8145d8 lost on one Rayonix set (lcls242_s, dimple R_free 0.2302 ->
0.2323): there the whole-frame radial correction hurts. On 40,000 of its frames: battery default
0.2462, ring 12 with the correction 0.2444, ring 12 without it 0.2336, ring 14 with it 0.2467. Its
beam is strongly polarised and the azimuthally averaged ring background does not describe the local
background.

So the empty apertures now also carry the corrected difference: the frame's ring background
(RingBackground, factored out of the engine) averaged over the ring pixels minus over the disk pixels
- what the integrator's kernel takes off a reflection - is subtracted from each disk-minus-ring
difference. The ring is still chosen on the plain differences, so its reach does not rest on the
radial model; where the correction was left to auto it is then kept only if it makes that ring predict
the disk better. Decisions on 15-60 pre-scan frames:
  pal86 ring 10, correction on (240.6 -> 221.1)   lcls222 ring 10, on (6.34e4 -> 3.41e4)
  lcls242_s ring 12, off (277.2 -> 285.8)         alvra213_int16 ring 14, on (0.01424 -> 0.01422)
Choosing ring and correction jointly instead picked ring 14 with the correction on lcls222, where dimple
reads 0.204 against 0.196 at ring 10; a median instead of the mean square picked ring 14 with the
correction on lcls242_s, the worst arm there. The sequential rule is the one that agrees with dimple on
every set measured.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu
2026-10-21 20:58:32 +02:00

166 lines
6.5 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);
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());
// Every candidate ring as the integrator reads it: the mean, then one high-side clip pass. The
// radial correction is taken over the ring's geometry, as the integrator's kernel is.
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, sum_b = 0.0;
int n = 0;
for (const auto &p : ring)
if (p.d2 < r3_sq) {
sum += p.v;
sum_b += p.b;
++n;
}
if (n == 0) {
measured = false;
break;
}
const double mean = sum / n;
const double thr = mean + clip_nsigma * std::sqrt(gain * std::max(mean, 1.0));
double kept = 0.0;
int n_kept = 0;
for (const auto &p : ring)
if (p.d2 < r3_sq && (clip_nsigma <= 0.0f || p.v <= thr)) {
kept += p.v;
++n_kept;
}
measured = n_kept > 0;
if (measured) {
d_plain[k] = disk_v - kept / n_kept;
d_radial[k] = d_plain[k] - (disk_b - sum_b / n);
}
}
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];
}
++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];
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;
}
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());
}