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Jungfraujoch/image_analysis/geom_refinement/BeamCenterFFTCPU.cpp
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leonarski_fandFilip Leonarski 19b135186d
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v1.0.0-rc.175 (#85)
* Rugnux: Processes a collection live while jfjoch_broker writes it (`rugnux <master.h5> <broker URL>`).
* Rugnux: Processing starts on the first images and confirms its choices once all are in, so analysis can begin during collection.
* Rugnux: Faster processing, especially on servers with several GPUs and CPU sockets and on computers without a GPU (`--no-gpu`, macOS).
* Rugnux: Uses much less GPU memory, so large data sets stay on the GPU of smaller cards, and a data set too large for the card is processed on the CPU instead.
* Rugnux: On macOS, Bragg integration runs on the Apple GPU.
* Rugnux: Better handling of twinning and pseudo-symmetry, with the twin hypothesis written as `<prefix>_twin_<SG>.mtz`, and a wrong `--model` no longer confirms the data or decides the hand.
* Rugnux: `--model` accepts predicted (AlphaFold) models and falls back to molecular replacement when the model is not placed as a rigid body (experimental `--mr` forces it), settling space group, hand and twinning and writing a different answer as `<prefix>_mr.mtz`.
* Rugnux: Molecular replacement is faster and settles the space group in more cases with several copies in the asymmetric unit.
* Rugnux: Deposition-ready mmCIF, a richer report, and numbered steps on the terminal with the full log in `<prefix>_log.txt`; `_P1.mtz`, `--estimate-beam-center` and `--beam-center-search` are removed.
* Rugnux: The beam-stop shadow is found correctly on tilted detectors.
* Rugnux: Stills files that record a stationary goniometer axis get the default stills geometry refinement.
* jfjoch_viewer: "Analyze dataset" uses the same defaults as a bare `rugnux <file>`, and shows the results of processed CBF, marCCD and SMV sweeps.
* jfjoch_viewer: The Files panel refreshes on F5 and every few seconds, and the plot type and other selections stay put during live collection.
* jfjoch_writer: Memory stays bounded and old data files are closed efficiently on long runs, any failure ends the run in an error state the broker is told about, and the master file appears only after its data files; the ZeroMQ pusher logs when a stalled writer makes it drop images.
* Fixes: The TCP image pusher no longer blocks the broker's receiver, GPU out-of-memory failures stop with a clear message, and the XDS plugin masks module and chip edges.

---------

Co-authored-by: Filip Leonarski <jungfrau@filips-mac-mini.home>
Reviewed-on: #85
Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
2026-10-16 15:34:43 +02:00

117 lines
5.0 KiB
C++

// SPDX-FileCopyrightText: 2026 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#include "BeamCenterFFTCPU.h"
#include <algorithm>
#include <complex>
#include <cstring>
#include <future>
#include <memory>
#include <mutex>
#include <stdexcept>
#include <fftw3.h>
#include "../../common/FFTWPlannerLock.h"
namespace {
// One real-to-complex 2D FFT workspace of fixed padded size, reused for every forward transform.
class Rfft2 {
int64_t ny, nx, nxc;
std::vector<float> real;
fftwf_plan fwd = nullptr;
fftwf_plan bwd = nullptr;
public:
std::vector<std::complex<float>> spectrum;
Rfft2(int64_t ny_, int64_t nx_) : ny(ny_), nx(nx_), nxc(nx_ / 2 + 1) {
real.resize(static_cast<size_t>(ny * nx));
spectrum.resize(static_cast<size_t>(ny * nxc));
std::unique_lock lock(FFTWPlannerMutex());
fwd = fftwf_plan_dft_r2c_2d(static_cast<int>(ny), static_cast<int>(nx), real.data(),
reinterpret_cast<fftwf_complex *>(spectrum.data()),
FFTW_ESTIMATE);
bwd = fftwf_plan_dft_c2r_2d(static_cast<int>(ny), static_cast<int>(nx),
reinterpret_cast<fftwf_complex *>(spectrum.data()),
real.data(), FFTW_ESTIMATE);
if (!fwd || !bwd)
throw std::runtime_error("BeamCenterFFT: fftwf plan failed");
}
Rfft2(const Rfft2 &) = delete;
Rfft2 &operator=(const Rfft2 &) = delete;
~Rfft2() {
std::unique_lock lock(FFTWPlannerMutex());
if (fwd)
fftwf_destroy_plan(fwd);
if (bwd)
fftwf_destroy_plan(bwd);
}
// Zero-pad `src` (height x width) into the workspace and return its spectrum.
std::vector<std::complex<float>> Forward(const std::vector<float> &src, int64_t height,
int64_t width) {
std::fill(real.begin(), real.end(), 0.0f);
for (int64_t y = 0; y < height; y++)
std::memcpy(&real[static_cast<size_t>(y * nx)], &src[static_cast<size_t>(y * width)],
sizeof(float) * static_cast<size_t>(width));
fftwf_execute(fwd);
return spectrum; // copy: the workspace is reused
}
// Inverse-transform the elementwise product u*v, normalised, cropped to out_h x out_w.
std::vector<float> InverseProduct(const std::vector<std::complex<float>> &u,
const std::vector<std::complex<float>> &v, int64_t out_h,
int64_t out_w) {
const float norm = 1.0f / (static_cast<float>(ny) * static_cast<float>(nx));
for (size_t i = 0; i < spectrum.size(); i++)
spectrum[i] = u[i] * v[i];
fftwf_execute(bwd);
std::vector<float> out(static_cast<size_t>(out_h * out_w));
for (int64_t y = 0; y < out_h; y++)
for (int64_t x = 0; x < out_w; x++)
out[static_cast<size_t>(y * out_w + x)] =
real[static_cast<size_t>(y * nx + x)] * norm;
return out;
}
};
} // namespace
BeamCenterConvSurfaces2D BeamCenterFFTCPU::PointSurfaces(const std::vector<float> &a,
const std::vector<float> &m, int64_t h,
int64_t w) {
// The three forward transforms are independent of each other, and so are the four inverse ones,
// so each group runs at the same time, one workspace per transform. A workspace is built exactly
// as a single one was - its own buffers and its own plan for them - so every transform is the one
// it was, bit for bit; the four inverse ones reuse the three forward workspaces and one more.
const int64_t ny = BeamCenterFFTPadSize(2 * h), nx = BeamCenterFFTPadSize(2 * w);
std::vector<std::unique_ptr<Rfft2>> fft;
for (int i = 0; i < 4; i++)
fft.push_back(std::make_unique<Rfft2>(ny, nx));
std::vector<float> a2(a.size());
for (size_t i = 0; i < a2.size(); i++)
a2[i] = a[i] * a[i];
auto fA = std::async(std::launch::async, [&] { return fft[0]->Forward(a, h, w); });
auto fM = std::async(std::launch::async, [&] { return fft[1]->Forward(m, h, w); });
auto fA2 = std::async(std::launch::async, [&] { return fft[2]->Forward(a2, h, w); });
const auto A = fA.get();
const auto M = fM.get();
const auto A2 = fA2.get();
BeamCenterConvSurfaces2D out;
auto fC = std::async(std::launch::async, [&] { return fft[0]->InverseProduct(A, A, 2 * h, 2 * w); });
auto fS = std::async(std::launch::async, [&] { return fft[1]->InverseProduct(A, M, 2 * h, 2 * w); });
auto fQ = std::async(std::launch::async, [&] { return fft[2]->InverseProduct(A2, M, 2 * h, 2 * w); });
auto fD = std::async(std::launch::async, [&] { return fft[3]->InverseProduct(M, M, 2 * h, 2 * w); });
out.C = fC.get();
out.S = fS.get();
out.Q = fQ.get();
out.D = fD.get();
return out;
}