Files
Jungfraujoch/image_analysis/indexing/FFTIndexerCPU.cpp
T
leonarski_fandClaude Opus 4.8 d393ec814c Remove residual sample identities missed by the earlier scrub
The rc.160 sample-identity cleanup left protein names, internal dataset
codes, and a measured cell angle in several source comments and one test.
Most sensitive: a measured monoclinic beta tied to an internal code in
Rugnux.cpp and IndexAndRefine.cpp. Rewrite each to describe the
crystallographic situation only (space group / metric relation), keeping
the technical reasoning intact. Comment- and string-only; no behaviour
change. (rugnux_cli.cpp's remaining name is scrubbed in the following
commit, alongside its other change to that file.)

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-15 22:18:32 +02:00

131 lines
4.7 KiB
C++

// SPDX-FileCopyrightText: 2025 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#include "FFTIndexerCPU.h"
#include <cmath>
#include <algorithm>
#include <stdexcept>
#include <cassert>
#include <mutex>
#include <vector>
static std::mutex fftw_plan_mutex;
static inline double dot_abs(const Coord& a, const Coord& b) {
return std::fabs(a.x * b.x + a.y * b.y + a.z * b.z);
}
FFTIndexerCPU::FFTIndexerCPU(const IndexingSettings& settings)
: FFTIndexer(settings) {
// Allocate host buffers
h_input_fft.resize(input_size, 0.0);
h_output_fft.resize(output_size);
// Validate allocations vs. expected sizes
if (h_input_fft.size() != input_size)
throw std::runtime_error("FFTWIndexer: input buffer size mismatch");
if (h_output_fft.size() != output_size)
throw std::runtime_error("FFTWIndexer: output buffer size mismatch");
const int H = static_cast<int>(histogram_size);
const int out_len = (H / 2) + 1;
int n[1] = { H };
{
std::unique_lock ul(fftw_plan_mutex);
plan = fftwf_plan_many_dft_r2c(
1, n, nDirections,
h_input_fft.data(), nullptr, 1, H,
reinterpret_cast<fftwf_complex*>(h_output_fft.data()), nullptr, 1, out_len,
FFTW_ESTIMATE);
}
if (!plan)
throw std::runtime_error("fftw_plan_many_dft_r2c failed");
}
FFTIndexerCPU::~FFTIndexerCPU() {
std::unique_lock ul(fftw_plan_mutex);
fftwf_destroy_plan(plan);
}
void FFTIndexerCPU::ExecuteFFT(const std::vector<Coord> &coord, size_t nspots) {
// Build histograms: one per direction
const int H = static_cast<int>(histogram_size);
const int D = nDirections;
const int out_len = (H / 2) + 1;
std::fill(h_input_fft.begin(), h_input_fft.end(), 0.0);
for (int d = 0; d < D; ++d) {
float* hist = h_input_fft.data() + static_cast<size_t>(d) * H;
for (size_t i = 0; i < nspots; i++) {
const auto& r = coord[i];
double dot = dot_abs(direction_vectors[d], r);
long long bin = static_cast<long long>(dot / histogram_spacing);
if (bin >= 0 && bin < H) {
hist[bin] += 1.0;
}
}
}
// Plan and execute batched R2C FFT with FFTW
fftwf_execute(plan);
// Post-process: pick the peak past min_length_A by PROMINENCE above a local background.
// The projected histogram has a broad low-frequency ENVELOPE (spots cluster near the
// origin) whose magnitude can exceed the true lattice peaks; a plain argmax|spec| then
// returns a short envelope vector (~10A) on weak/pink-beam frames and the real axes are
// lost. Subtracting a running-mean background of half-width BG_HALF bins removes that
// smooth envelope (it cancels to ~0) while sharp lattice peaks - fundamentals AND
// harmonics - keep their height. The prominence is also reported as the magnitude so
// FilterFFTResults ranks directions by real-peak strength, not by envelope.
const double len_coeff = 2.0 * static_cast<double>(max_length_A) / static_cast<double>(H);
// Background half-window ~15 A (in length, so it is independent of the histogram sizing);
// wide enough to span the envelope yet narrow enough not to smooth real peaks. Validated
// optimum on serial-still jet data (de-novo indexing improved markedly vs FFBIDX); a second dataset unchanged.
constexpr double BG_HALF_WIDTH_A = 15.0;
const int bg_half = std::max(1, static_cast<int>(std::lround(BG_HALF_WIDTH_A / len_coeff)));
std::vector<double> mag(out_len), pref(out_len + 1);
for (int d = 0; d < D; ++d) {
const auto* spec = h_output_fft.data() + static_cast<size_t>(d) * out_len;
pref[0] = 0.0;
for (int j = 0; j < out_len; ++j) {
mag[j] = std::hypot(spec[j][0], spec[j][1]);
pref[j + 1] = pref[j] + mag[j];
}
double best_prom = 0.0;
double best_len = -1.0;
for (int j = 0; j < out_len; ++j) {
double len = len_coeff * static_cast<double>(j);
if (len <= static_cast<double>(min_length_A)) continue;
const int lo = std::max(0, j - bg_half);
const int hi = std::min(out_len, j + bg_half + 1);
const double background = (pref[hi] - pref[lo]) / static_cast<double>(hi - lo);
const double prominence = mag[j] - background;
if (prominence > best_prom) {
best_prom = prominence;
best_len = len;
}
}
result_fft[d] = FFTResult{
.magnitude = static_cast<float>(best_prom),
.direction = d,
.length = static_cast<float>(best_len)
};
}
}