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Jungfraujoch/image_analysis/beam_stop/ShadowMaskGPU.h
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v1.0.0-rc.179 (#90)
* Rugnux: Stills processing needs only the unit cell and space group beyond what the file records - detector distance, beam centre, tilt, panel placement, saturation level, gain and polarisation plane are found from the images - and is up to twice as fast.
* Rugnux: Stills can be indexed without a GPU, with a CPU implementation of the fast-feedback indexer (macOS, computers without a GPU).
* Rugnux: Rotation and stills data are integrated in the detector's own units with one gain model, improving data from CCD detectors.
* Web frontend: The Rugnux live page shows the placed model with its electron density and anomalous difference map in a Mol* viewer.

Reviewed-on: #90
Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
2026-10-24 14:52:29 +02:00

41 lines
2.1 KiB
C++

// SPDX-FileCopyrightText: 2026 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#pragma once
// Included only under JFJOCH_USE_CUDA.
#include <cstdint>
#include <vector>
#include <cuda_runtime.h>
// What the mask is drawn about: the detector, the beam centre, and the geometry the rings and the
// polarization factor are read off (ShadowFinder keeps it as a DiffractionGeometry; the device takes
// it as numbers).
struct ShadowMaskSetup {
int width = 0, height = 0;
float beam_x = 0.0f, beam_y = 0.0f;
float det_matrix[9] = {}; // row major
float pixel_size_mm = 0.0f;
float distance_mm = 0.0f;
bool has_polarization = false;
float polarization = 0.0f;
float gain = 1.0f; // detector units per photon (ShadowFinder::gain)
};
// ShadowFinder::GetMask on the device, from the projection ShadowAccumulatorGPU holds there. Step for
// step the host's algorithm - the same pooling, ring medians, components, morphology and arm search -
// and the same answer wherever the arithmetic is exact: every integer, comparison, sort and component
// is. What is not is the floating point the two compilers evaluate differently - the polarization
// factor's trigonometry, the Poisson test's logarithm and the azimuth of the arm search - so a pixel
// within a rounding of one of those thresholds can come out the other way.
std::vector<uint32_t> ShadowMaskOnDevice(const ShadowMaskSetup &setup, const std::vector<uint32_t> &pixel_mask,
const int64_t *max_value, const int64_t *sum_value,
const uint32_t *valid_count, uint32_t frames, cudaStream_t stream);
// The mean projection the host's GetMeanProjection makes, computed where the sums are: the same
// division, so the same bits, and a quarter of the bytes to bring back.
std::vector<float> MeanProjectionOnDevice(const std::vector<uint32_t> &pixel_mask, const int64_t *sum_value,
const uint32_t *valid_count, size_t npixels, cudaStream_t stream);