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Jungfraujoch/image_analysis/scale_merge/ResolutionCutoff.cpp
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v1.0.0-rc.158 (#68)
This is an UNSTABLE release. It includes many experimental features, as well as many AI generated fixes. We recommend using rc.152 for production use.

* Analysis: The azimuthal-integration solid-angle correction now follows the incidence angle to the detector normal (`cos^3` of that angle) instead of `cos^3(2*theta)`, so it is correct for a tilted detector and matches PyFAI `solidAngleArray` and MAX IV azint (unchanged for an untilted detector). Crystal geometry refinement (`XtalOptimizer`) no longer silently ignores an imported PONI `rot3` (rotation about the beam): it is applied as a fixed rotation in the residual so refinement stays consistent with the rest of the pipeline. Polarization and azimuthal binning already honoured `rot3` through the full PONI rotation.
* jfjoch_viewer: Open datasets on the WSL2/UNC filesystem (paths starting `\\`); write processing outputs next to the input file, with a Browse button and independent `_process.h5` / merged `.mtz`/`.cif` toggles; and show the determined space group in the merge-statistics window.
* rugnux: Accept an absolute `-o` output prefix in offline processing.
* Packaging: The self-contained Linux viewer `.tgz` now bundles cuFFT, so it runs without a system CUDA toolkit (`.deb`/`.rpm` are unchanged, distro-managed).
* Docs: Bring the analysis references up to date with the code. `docs/CPU_DATA_ANALYSIS.md` now reflects the unified profile-fit Bragg integration engine, multi-lattice indexing, azimuthal phi binning, the radial parallax/bandwidth profile with sub-pixel centring, the rot3d capture-fraction handling and the automatic CC1/2 resolution cutoff, and drops the descriptions of features that were never implemented (French-Wilson amplitudes, the still excitation-error partiality model); `docs/RUGNUX.md` documents the new `--resolution-cutoff`/`--resolution-cc-target`/`--resolution-shells`, `--min-captured-fraction`, `--mosaicity`, `--reference-column`, the azimuthal correction toggles and the geometry-override options, and corrects the `-N` default. The outdated in-source design notes (ICE_RING_DETECTION, BRAGG_INTEGRATION_ENGINE, NEXTGEN_INTEGRATOR) are removed.Reviewed-on: #68

Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
2026-07-12 19:42:29 +02:00

203 lines
9.0 KiB
C++

// SPDX-FileCopyrightText: 2026 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#include "ResolutionCutoff.h"
#include <algorithm>
#include <cmath>
#include <limits>
#include "../../common/CorrelationCoefficient.h"
namespace {
// Fine CC1/2 bins for the fit (finer than the 10 reported shells, per the design). A bin needs
// this many merged reflections for its CC1/2 to be trusted.
constexpr int N_FIT_BINS = 25;
constexpr int MIN_BIN_COUNT = 10;
constexpr int MIN_FIT_BINS = 5; // need at least this many usable bins for a fit
constexpr int EXTEND_BINS_PAST_FALLOFF = 2; // bins kept beyond the first sub-target bin
constexpr double SHELLS_FOR_EXTENSION = 10.0; // "+1 shell" = one 10-shell width in s (report-independent)
double Logistic(double s, double k, double s0) {
return 1.0 / (1.0 + std::exp(k * (s - s0)));
}
// Weighted (equal-weight) sum of squared residuals of the logistic against the binned CC1/2.
double FitSSE(const std::vector<double> &s, const std::vector<double> &cc, double k, double s0) {
double sse = 0.0;
for (size_t i = 0; i < s.size(); ++i) {
const double r = cc[i] - Logistic(s[i], k, s0);
sse += r * r;
}
return sse;
}
}
ResolutionCutoffResult ComputeCCHalfLogisticCutoff(const std::vector<MergedReflection> &merged,
double cc_target, Logger &logger) {
ResolutionCutoffResult result;
if (!(cc_target > 0.0 && cc_target < 1.0)) {
result.note = "invalid CC target";
return result;
}
// s = 1/d^2 range over the merged reflections that carry a half-set pair.
double s_lo = std::numeric_limits<double>::max(), s_hi = 0.0;
double d_data_min = std::numeric_limits<double>::max();
for (const auto &m : merged) {
if (!(m.d > 0.0f) || !std::isfinite(m.I_half[0]) || !std::isfinite(m.I_half[1]))
continue;
const double s = 1.0 / (static_cast<double>(m.d) * m.d);
s_lo = std::min(s_lo, s);
s_hi = std::max(s_hi, s);
d_data_min = std::min(d_data_min, static_cast<double>(m.d));
}
if (!(s_lo < s_hi)) {
result.note = "no half-set data for CC1/2 fit";
return result;
}
// Bin CC1/2 against s (equal width in s, matching the reporting shells which are equal in 1/d^2).
const double bin_w = (s_hi - s_lo) / N_FIT_BINS;
std::vector<CorrelationCoefficient> bin_cc(N_FIT_BINS);
std::vector<int> bin_n(N_FIT_BINS, 0);
for (const auto &m : merged) {
if (!(m.d > 0.0f) || !std::isfinite(m.I_half[0]) || !std::isfinite(m.I_half[1]))
continue;
const double s = 1.0 / (static_cast<double>(m.d) * m.d);
int b = static_cast<int>((s - s_lo) / bin_w);
b = std::clamp(b, 0, N_FIT_BINS - 1);
bin_cc[b].Add(m.I_half[0], m.I_half[1]);
++bin_n[b];
}
// Usable bins (enough counts), in ascending-s order, with their bin-centre s.
std::vector<double> s_bin, cc_bin;
for (int b = 0; b < N_FIT_BINS; ++b) {
if (bin_n[b] < MIN_BIN_COUNT) continue;
const double cc = bin_cc[b].GetCC();
if (!std::isfinite(cc)) continue;
s_bin.push_back(s_lo + (b + 0.5) * bin_w);
cc_bin.push_back(cc);
}
if (static_cast<int>(s_bin.size()) < MIN_FIT_BINS) {
result.note = "too few usable CC1/2 bins";
return result;
}
// Restrict to the contiguous fall-off from low res: keep bins up to a couple past the first one
// that drops below cc_target, so a high-res noise blip cannot pull the fit back up. If the lowest
// bin is already below cc_target there is no low-res plateau to anchor on - bail out.
if (cc_bin.front() < cc_target) {
result.note = "no low-resolution CC1/2 plateau";
return result;
}
size_t keep = cc_bin.size();
for (size_t i = 0; i < cc_bin.size(); ++i) {
if (cc_bin[i] < cc_target) {
keep = std::min(cc_bin.size(), i + 1 + EXTEND_BINS_PAST_FALLOFF);
break;
}
}
s_bin.resize(keep);
cc_bin.resize(keep);
if (static_cast<int>(s_bin.size()) < MIN_FIT_BINS) {
result.note = "too few CC1/2 bins in the fall-off region";
return result;
}
// Fit the logistic by a grid search over (k>0, s0) then a local coordinate-descent refine
// (dependency-free; the fall-off is smooth and the grid lands close). s0 spans the s range; k
// spans transitions from very gradual to very sharp relative to that range.
const double s_range = s_hi - s_lo;
double best_k = 0.0, best_s0 = 0.0, best_sse = std::numeric_limits<double>::max();
constexpr int N_S0 = 60, N_K = 40;
const double k_min = 2.0 / s_range, k_max = 200.0 / s_range;
for (int ik = 0; ik < N_K; ++ik) {
const double k = k_min * std::pow(k_max / k_min, static_cast<double>(ik) / (N_K - 1));
for (int is = 0; is < N_S0; ++is) {
const double s0 = s_lo + s_range * static_cast<double>(is) / (N_S0 - 1);
const double sse = FitSSE(s_bin, cc_bin, k, s0);
if (sse < best_sse) { best_sse = sse; best_k = k; best_s0 = s0; }
}
}
double k = best_k, s0 = best_s0;
double step_s0 = s_range / N_S0, step_k = best_k * 0.5;
for (int iter = 0; iter < 200; ++iter) {
bool improved = false;
for (const double ds : {step_s0, -step_s0}) {
const double sse = FitSSE(s_bin, cc_bin, k, s0 + ds);
if (sse < best_sse) { best_sse = sse; s0 += ds; improved = true; }
}
for (const double dk : {step_k, -step_k}) {
const double kt = k + dk;
if (kt <= 0.0) continue;
const double sse = FitSSE(s_bin, cc_bin, kt, s0);
if (sse < best_sse) { best_sse = sse; k = kt; improved = true; }
}
if (!improved) { step_s0 *= 0.5; step_k *= 0.5; }
if (step_s0 < 1e-6 * s_range && step_k < 1e-6 * best_k) break;
}
// s where the fitted CC1/2 crosses cc_target, then "one shell too far". The extension is one
// reported-shell width, measured over the range that is actually kept and reported (low-res
// plateau -> the fall-off crossing), NOT the full measured range: when the detector reaches far
// past where the crystal diffracts (a high-res-configured detector on a low-res crystal), the
// full range is dominated by high-res noise, so s_range/10 would be a huge over-extension.
const double s_cross = s0 + std::log(1.0 / cc_target - 1.0) / k;
const double delta_s = (s_cross - s_lo) / SHELLS_FOR_EXTENSION;
const double s_final = s_cross + delta_s;
// No cut if the fall-off is beyond the measured edge (CC1/2 still healthy at the highest s).
if (s_final >= s_hi) {
result.note = "CC1/2 does not fall off within the measured range";
return result;
}
// Low-resolution floor: never cut into good low-res data. A fit that puts the cutoff within two
// shells of the lowest-res data is not a real fall-off - keep the full range and warn.
if (s_final <= s_lo + 2.0 * delta_s) {
logger.Warning("Resolution cutoff fit landed at low resolution (degenerate CC1/2 fall-off); "
"keeping the full resolution range");
result.note = "degenerate low-resolution fit";
return result;
}
double d_cut = 1.0 / std::sqrt(s_final);
d_cut = std::max(d_cut, d_data_min); // cannot cut beyond the highest-resolution reflection
// A cut that is not meaningfully coarser than the data edge is a no-op.
if (d_cut <= d_data_min * 1.001) {
result.note = "CC1/2 healthy to the detector edge";
return result;
}
result.d_cut = d_cut;
result.note = "CC1/2 logistic fall-off, +1 shell";
return result;
}
std::optional<double> ApplyResolutionCutoff(std::vector<MergedReflection> &merged,
std::optional<double> manual_limit,
ResolutionCutoffMethod method,
double cc_target,
bool for_search,
Logger &logger) {
std::optional<double> effective_d_min = manual_limit;
if (!effective_d_min && !for_search && method == ResolutionCutoffMethod::CCHalfLogistic) {
const auto rc = ComputeCCHalfLogisticCutoff(merged, cc_target, logger);
if (rc.d_cut) {
effective_d_min = rc.d_cut;
logger.Info("Auto resolution cutoff: {:.2f} A ({}; override with --scaling-high-resolution)",
*rc.d_cut, rc.note);
} else {
logger.Info("Auto resolution cutoff: none ({}); keeping the full resolution range", rc.note);
}
}
if (effective_d_min)
merged.erase(std::remove_if(merged.begin(), merged.end(),
[&](const MergedReflection &m) { return std::isfinite(m.d) && m.d < *effective_d_min; }),
merged.end());
return effective_d_min;
}