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Jungfraujoch/image_analysis/roi/ROIIntegrationCPU.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

79 lines
3.1 KiB
C++

// SPDX-FileCopyrightText: 2026 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#pragma once
#include <algorithm>
#include <limits>
#include <type_traits>
#include "ROIIntegration.h"
#include "../../common/JFJochException.h"
class ROIIntegrationCPU : public ROIIntegration {
public:
explicit ROIIntegrationCPU(const DiffractionExperiment &experiment);
// image is anything indexable with operator[] and size(). Templated on the
// pixel type so a future narrow-integer (e.g. 16-bit) path works as well.
template <class T>
void RunROI(const T &image, std::map<std::string, ROIMessage> &out) {
if (image.size() != npixel)
throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
"ROIIntegration: mismatch in image size");
for (uint16_t r = 0; r < roi_count; r++) {
roi_sum[r] = 0;
roi_sum2[r] = 0;
roi_pixels[r] = 0;
roi_max[r] = INT64_MIN;
}
std::fill(roi_panel_v.begin(), roi_panel_v.end(), 0);
std::fill(roi_panel_x.begin(), roi_panel_x.end(), 0);
std::fill(roi_panel_y.begin(), roi_panel_y.end(), 0);
using pixel_t = std::remove_cv_t<std::remove_reference_t<decltype(image[0])>>;
// Pixels on no panel are not visited.
modules.ForEachPixel(static_cast<int64_t>(width), static_cast<int64_t>(npixel / width),
[&](int64_t panel, size_t i, double, double) {
const uint16_t mask = roi_map[i];
if (mask == 0)
return;
const pixel_t v = image[i];
// masked/bad pixels (signed types only) are excluded entirely
if constexpr (std::is_signed_v<pixel_t>) {
if (v == std::numeric_limits<pixel_t>::min())
return;
}
// saturated pixels still count towards the max, but not the sums
const bool saturated = (v == std::numeric_limits<pixel_t>::max());
const int64_t val = static_cast<int64_t>(v);
const int64_t x = static_cast<int64_t>(i % width);
const int64_t y = static_cast<int64_t>(i / width);
const size_t slot = panel < 0 ? 0 : static_cast<size_t>(panel);
for (uint16_t r = 0; r < roi_count; r++) {
if (!(mask & (1u << r)))
continue;
if (!saturated) {
roi_sum[r] += val;
roi_sum2[r] += static_cast<uint64_t>(val * val);
roi_pixels[r] += 1;
roi_panel_v[r * panel_slots + slot] += val;
roi_panel_x[r * panel_slots + slot] += val * x;
roi_panel_y[r * panel_slots + slot] += val * y;
}
if (val > roi_max[r])
roi_max[r] = val;
}
});
PlaceWeighted();
Export(out);
}
void Run(const ImagePreprocessorBuffer &image, std::map<std::string, ROIMessage> &out) override;
};