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Jungfraujoch/rugnux/HotPixels.cpp
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leonarski_fandClaude Opus 5.5 023afc4ee2 HotPixelFinder: read a ring's median and spread off a histogram of its counts 
Each frame packed every ring's pixels together and selected in them twice - the median, then the
median absolute deviation - about 40% of the pass. A ring's background is a few counts, so both are
now read off a histogram of the values 0..1023, exactly, wherever the statistic lands inside it (and,
for the spread, no count is negative); otherwise the ring is packed and selected as before.

Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01D1G8gJVAy6gp1K5Dz3NE5C
2026-09-26 23:03:21 +02:00

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// SPDX-FileCopyrightText: 2026 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#include "HotPixels.h"
#include <algorithm>
#include <cmath>
#include <cstring>
#include <limits>
#include <optional>
#include "../common/JFJochMath.h"
#include "../common/ParallelFor.h"
namespace {
// The lower median of v[0..n), reordering it.
int32_t median_of(int32_t *v, size_t n) {
std::nth_element(v, v + n / 2, v + n);
return v[n / 2];
}
// A ring's background is a few counts, so its order statistics are read off a histogram of the values
// 0..RING_HIST_VALUES-1 - exactly, as long as the one asked for lands inside that range.
constexpr int32_t RING_HIST_VALUES = 1024;
// The rank-th smallest value, if it is inside the histogram; `below` counts the values under 0.
std::optional<int32_t> hist_order_statistic(const std::vector<uint32_t> &hist, size_t below, size_t rank) {
if (rank < below)
return std::nullopt;
size_t seen = below;
for (int32_t v = 0; v < RING_HIST_VALUES; v++) {
seen += hist[v];
if (seen > rank)
return v;
}
return std::nullopt;
}
// The rank-th smallest |value - m|, if every value that close to m is inside the histogram (none
// below 0 anywhere, and m + d still in range).
std::optional<int32_t> hist_deviation_order_statistic(const std::vector<uint32_t> &hist, size_t below,
int32_t m, size_t rank) {
if (below > 0)
return std::nullopt;
size_t seen = hist[m];
for (int32_t d = 0; seen <= rank; ) {
d++;
if (m + d >= RING_HIST_VALUES)
return std::nullopt;
seen += hist[m + d] + (m - d >= 0 ? hist[m - d] : 0);
if (seen > rank)
return d;
}
return 0;
}
// The smallest k with npix * P(Binomial(n, q) >= k) below the family-wise rate, n + 1 if none.
int binomial_bound(int n, double q, double npix, double rate) {
double tail = 0.0;
int k = n + 1;
for (int j = n; j >= 0; j--) {
tail += std::exp(std::lgamma(n + 1.0) - std::lgamma(j + 1.0) - std::lgamma(n - j + 1.0)
+ j * std::log(q) + (n - j) * std::log1p(-q));
if (npix * tail >= rate) break;
k = j;
}
return k;
}
} // namespace
HotPixelFinder::HotPixelFinder(const DiffractionExperiment &experiment, const PixelMask &mask, size_t nthreads)
: geometry(experiment.GetDiffractionGeometry()),
axis(experiment.GetGoniometer() ? experiment.GetGoniometer()->GetAxis().Normalize() : Coord(0, 0, 0)),
width(experiment.GetXPixelsNumConv()), height(experiment.GetYPixelsNumConv()),
key(width * height, -1),
n_lit(width * height, 0), n_error(width * height, 0), sum_value(width * height, 0),
n_error_ring_ok(width * height, 0), error_level_sum(width * height, 0) {
const auto &m = mask.GetMask();
// Rings of equal 2theta, RING_WIDTH_PX wide where the beam meets the detector.
const float ring_rad = RING_WIDTH_PX * geometry.GetPixelSize_mm() / geometry.GetDetectorDistance_mm();
ParallelChunks(static_cast<int>(height), nthreads, [&](int y0, int y1) {
for (size_t y = y0; y < static_cast<size_t>(y1); y++)
for (size_t x = 0; x < width; x++) {
const size_t i = y * width + x;
if (m[i] != 0) continue;
const float fx = static_cast<float>(x), fy = static_cast<float>(y);
const int ring = static_cast<int>(geometry.TwoTheta_rad(fx, fy) / ring_rad);
const int sector = std::min(SECTORS - 1, static_cast<int>(geometry.Phi_rad(fx, fy)
/ static_cast<float>(2.0 * PI) * SECTORS));
key[i] = ring * SECTORS + sector;
}
});
for (const int32_t k : key)
if (k >= 0) {
nrings = std::max(nrings, k / SECTORS + 1);
unmasked++;
}
key_frames.assign(static_cast<size_t>(nrings) * SECTORS, 0);
key_level_sum.assign(static_cast<size_t>(nrings) * SECTORS, 0);
key_begin.assign(static_cast<size_t>(nrings) * SECTORS + 1, 0);
for (const int32_t k : key)
if (k >= 0) key_begin[k + 1]++;
for (size_t k = 1; k < key_begin.size(); k++)
key_begin[k] += key_begin[k - 1];
}
void HotPixelFinder::AddImage(const int32_t *image, std::vector<int32_t> &scratch) {
const size_t npix = width * height;
const size_t nkeys = static_cast<size_t>(nrings) * SECTORS;
// The frame's valid counts laid out by ring and sector. A saturated pixel has no count to add.
scratch.resize(npix);
std::vector<uint32_t> count(nkeys, 0);
for (size_t i = 0; i < npix; i++) {
const int32_t k = key[i], v = image[i];
if (k < 0 || v == INT32_MIN || v == INT32_MAX) continue;
scratch[key_begin[k] + count[k]++] = v;
}
std::vector<int32_t> sector_level(nkeys, 0);
for (size_t k = 0; k < nkeys; k++)
if (count[k] >= MIN_SECTOR_PIXELS)
sector_level[k] = median_of(scratch.data() + key_begin[k], count[k]);
// Each ring's median and its robust spread about that median: off the histogram of its values
// where both land inside it, otherwise with the ring's sectors packed together - forward into the
// space the ring owns, so nothing is overwritten before it is moved - and selected.
std::vector<int32_t> ring_level(nrings, 0);
std::vector<float> ring_spread(nrings, 0.0f);
std::vector<char> ring_ok(nrings, 0);
std::vector<uint32_t> hist(RING_HIST_VALUES);
for (int r = 0; r < nrings; r++) {
size_t n = 0;
for (int s = 0; s < SECTORS; s++)
n += count[r * SECTORS + s];
if (n < MIN_RING_PIXELS) continue;
ring_ok[r] = 1;
std::fill(hist.begin(), hist.end(), 0);
size_t below = 0;
for (int s = 0; s < SECTORS; s++) {
const size_t k = r * SECTORS + s;
for (size_t j = 0; j < count[k]; j++) {
const int32_t v = scratch[key_begin[k] + j];
if (v < 0) below++;
else if (v < RING_HIST_VALUES) hist[v]++;
}
}
const auto median = hist_order_statistic(hist, below, n / 2);
const auto mad = median ? hist_deviation_order_statistic(hist, below, *median, n / 2) : std::nullopt;
if (median && mad) {
ring_level[r] = *median;
ring_spread[r] = 1.4826f * static_cast<float>(*mad);
continue;
}
int32_t *ring = scratch.data() + key_begin[r * SECTORS];
size_t packed = 0;
for (int s = 0; s < SECTORS; s++) {
const size_t k = r * SECTORS + s;
std::memmove(ring + packed, scratch.data() + key_begin[k], count[k] * sizeof(int32_t));
packed += count[k];
}
ring_level[r] = median_of(ring, n);
for (size_t j = 0; j < n; j++)
ring[j] = std::abs(ring[j] - ring_level[r]);
ring_spread[r] = 1.4826f * static_cast<float>(median_of(ring, n));
}
std::vector<int32_t> level(nkeys, 0);
std::vector<float> threshold(nkeys, 0.0f);
for (size_t k = 0; k < nkeys; k++) {
const int r = static_cast<int>(k / SECTORS);
level[k] = std::max(ring_level[r], sector_level[k]);
const float noise = std::max(std::sqrt(static_cast<float>(std::max(level[k], 0))), ring_spread[r]);
threshold[k] = static_cast<float>(level[k]) + LIT_NSIGMA * noise + LIT_OFFSET;
}
// Every sum is an integer, so the result does not depend on the order the frames arrive in.
{
std::lock_guard lock(m);
frames++;
for (size_t k = 0; k < nkeys; k++)
if (ring_ok[k / SECTORS]) {
key_frames[k]++;
key_level_sum[k] += level[k];
}
}
const size_t rows_per_band = (height + BANDS - 1) / BANDS;
const size_t first = next_band.fetch_add(1);
for (size_t b = 0; b < BANDS; b++) {
const size_t band = (first + b) % BANDS;
const size_t begin = std::min(npix, band * rows_per_band * width);
const size_t end = std::min(npix, (band + 1) * rows_per_band * width);
std::lock_guard lock(band_mutex[band]);
for (size_t i = begin; i < end; i++) {
const int32_t k = key[i], v = image[i];
if (k < 0) continue;
if (v == INT32_MIN) {
n_error[i]++;
if (ring_ok[k / SECTORS]) { // counted in its ring-sector's frames, but not valid here
n_error_ring_ok[i]++;
error_level_sum[i] += level[k];
}
continue;
}
if (!ring_ok[k / SECTORS]) continue;
sum_value[i] += v;
if (v == INT32_MAX || static_cast<float>(v) > threshold[k])
n_lit[i]++;
}
}
}
HotPixelFinder::Result HotPixelFinder::GetMask(double oscillation_deg, double spacing_deg,
size_t nthreads) const {
std::lock_guard lock(m);
Result ret;
ret.frames = frames;
ret.mask.assign(width * height, 0);
const int n = static_cast<int>(frames);
// The chance rate per ring, from the pixels lit on no more than half of their frames: whatever
// lights those - reflections, zingers, noise above the bound - lights a defect-free pixel too.
std::vector<double> lit(nrings, 0.0), seen(nrings, 0.0);
for (size_t i = 0; i < key.size(); i++)
if (key[i] >= 0 && n_valid(i) > 0 && 2 * n_lit[i] <= n_valid(i)) {
lit[key[i] / SECTORS] += n_lit[i];
seen[key[i] / SECTORS] += n_valid(i);
}
std::vector<int> k_chance(nrings, n + 1);
for (int r = 0; r < nrings; r++)
if (seen[r] > 0.0)
k_chance[r] = binomial_bound(n, std::clamp(lit[r] / seen[r], 1e-6, 0.999),
static_cast<double>(unmasked), FAMILY_WISE_RATE);
// Persistent: lit on more frames than one reflection or chance explains.
const int min_valid = std::max(10, n / 2);
std::vector<uint8_t> persistent(width * height, 0);
ParallelChunks(static_cast<int>(height), nthreads, [&](int y0, int y1) {
for (size_t y = y0; y < static_cast<size_t>(y1); y++)
for (size_t x = 0; x < width; x++) {
const size_t i = y * width + x;
if (key[i] < 0 || n_valid(i) < min_valid || n_lit[i] == 0 || !(spacing_deg > 0.0)) continue;
// One reflection's stay on this pixel, in sampled frames: 1 / |zeta| turns the rocking
// width into rotation, and zeta = |axis . (s1 x s0)| with s0 along z.
const Coord s1 = geometry.LabCoord(static_cast<float>(x), static_cast<float>(y)).Normalize();
const double zeta = std::max(1e-4, static_cast<double>(std::fabs(axis * (s1 % Coord(0, 0, 1)))));
const double stay = (oscillation_deg + ROCKING_WIDTH_DEG) / zeta;
const double k_bragg = 1.0 + std::ceil(stay / spacing_deg);
const double k = std::min<double>(std::max<double>(k_bragg, k_chance[key[i] / SECTORS]),
n_valid(i));
persistent[i] = n_lit[i] >= k;
}
});
// Masked: a persistent pixel standing alone - on its own or as one of a pair; a larger patch is
// a feature of the scattering, not a defect - whose mean is STRONG_RATIO times its ring's and
// whose excess is above the Poisson bound. A weaker one cannot make an outlier.
const auto persistent_neighbours = [&](size_t x, size_t y) {
int count = 0;
for (size_t yy = (y > 0 ? y - 1 : 0); yy <= std::min(height - 1, y + 1); yy++)
for (size_t xx = (x > 0 ? x - 1 : 0); xx <= std::min(width - 1, x + 1); xx++)
if ((xx != x || yy != y) && persistent[yy * width + xx]) count++;
return count;
};
ParallelChunks(static_cast<int>(height), nthreads, [&](int y0, int y1) {
for (size_t y = y0; y < static_cast<size_t>(y1); y++)
for (size_t x = 0; x < width; x++) {
const size_t i = y * width + x;
if (key[i] < 0) continue;
if (2 * n_error[i] > n) {
ret.mask[i] = 2;
continue;
}
if (!persistent[i]) continue;
const int neighbours = persistent_neighbours(x, y);
bool isolated = neighbours == 0;
if (neighbours == 1)
for (size_t yy = (y > 0 ? y - 1 : 0); yy <= std::min(height - 1, y + 1); yy++)
for (size_t xx = (x > 0 ? x - 1 : 0); xx <= std::min(width - 1, x + 1); xx++)
if ((xx != x || yy != y) && persistent[yy * width + xx])
isolated = persistent_neighbours(xx, yy) == 1;
const double mean_level = static_cast<double>(sum_level(i)) / n_valid(i);
const double excess = static_cast<double>(sum_value[i] - sum_level(i)) / n_valid(i);
if (isolated
&& static_cast<double>(sum_value[i]) >= STRONG_RATIO * static_cast<double>(sum_level(i))
&& excess >= LIT_NSIGMA * std::sqrt(std::max(mean_level, 0.0)) + LIT_OFFSET)
ret.mask[i] = 1;
}
});
for (const uint32_t v : ret.mask) {
ret.hot += v == 1;
ret.error += v == 2;
}
return ret;
}
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