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This is an UNSTABLE release. This version adds scalign and merging. These are experimental at the moment, and should not be used for production analysis. If things go wrong with analysis, it is better to revert to 1.0.0-rc.124. * jfjoch_broker: Improve logic on switching on/off spot finding * jfjoch_broker: Increase maximum spot count for FFBIDX to 65536 * jfjoch_broker: Increase default maximum unit cell for FFT to 500 A (could have performance impact, TBD) * jfjoch_process: Add scalign and merging functionality - program is experimental at the moment and should not be used for production analysis * jfjoch_viewer: Display partiality and reciprocal Lorentz-polarization correction for each reflection * jfjoch_writer: Save more information about each reflection Reviewed-on: #32 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch> Co-committed-by: Filip Leonarski <filip.leonarski@psi.ch>
129 lines
5.3 KiB
C++
129 lines
5.3 KiB
C++
// SPDX-FileCopyrightText: 2025 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
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// SPDX-License-Identifier: GPL-3.0-only
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#include "BraggIntegrate2D.h"
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template<class T>
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void IntegrateReflection(Reflection &r, const T *image, size_t xpixel, size_t ypixel,
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int64_t special_value, int64_t saturation,
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float r_3, float r_1_sq, float r_2_sq, float r_3_sq) {
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int64_t x0 = std::floor(r.predicted_x - r_3 - 1.0);
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int64_t x1 = std::ceil(r.predicted_x + r_3 + 1.0);
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int64_t y0 = std::floor(r.predicted_y - r_3 - 1.0);
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int64_t y1 = std::ceil(r.predicted_y + r_3 + 1.0);
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if (x0 < 0)
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x0 = 0;
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if (y0 < 0)
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y0 = 0;
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if (x1 >= xpixel)
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x1 = xpixel - 1;
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if (y1 >= ypixel)
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y1 = ypixel - 1;
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int64_t I_sum = 0;
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int64_t bkg_sum = 0;
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int64_t bkg_npixel = 0;
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int64_t I_npixel_inner = 0;
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int64_t I_npixel_integrated = 0;
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for (int64_t y = y0; y <= y1; y++) {
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for (int64_t x = x0; x <= x1; x++) {
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float dist_sq = (x - r.predicted_x) * (x - r.predicted_x) + (y - r.predicted_y) * (y - r.predicted_y);
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if (dist_sq < r_1_sq)
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I_npixel_inner++;
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if (image[y * xpixel + x] == special_value || image[y * xpixel + x] == saturation)
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continue;
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if (dist_sq < r_1_sq) {
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I_sum += image[y * xpixel + x];
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I_npixel_integrated++;
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} else if (dist_sq >= r_2_sq && dist_sq < r_3_sq) {
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bkg_sum += image[y * xpixel + x];
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bkg_npixel++;
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}
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}
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}
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if ((I_npixel_integrated == I_npixel_inner) && (bkg_npixel > 5)) {
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r.bkg = static_cast<float>(bkg_sum) / static_cast<float>(bkg_npixel);
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r.I = static_cast<float>(I_sum) - static_cast<float>(I_npixel_integrated) * r.bkg;
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// minimum sigma is 1!
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if (I_sum >= 1)
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r.sigma = std::sqrt(static_cast<float>(I_sum));
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else
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r.sigma = 1;
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r.observed = true;
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} else {
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r.I = 0;
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r.bkg = 0;
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r.observed = false;
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}
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}
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template<class T>
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std::vector<Reflection> IntegrateInternal(const DiffractionExperiment &experiment,
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const CompressedImage &image,
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const std::vector<Reflection> &predicted,
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size_t npredicted,
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int64_t special_value,
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int64_t saturation,
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int64_t image_number) {
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std::vector<Reflection> ret;
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ret.reserve(npredicted);
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auto settings = experiment.GetBraggIntegrationSettings();
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auto geom = experiment.GetDiffractionGeometry();
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std::vector<uint8_t> buffer;
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auto ptr = reinterpret_cast<const T *>(image.GetUncompressedPtr(buffer));
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const float r_3 = settings.GetR3();
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const float r_1_sq = settings.GetR1() * settings.GetR1();
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const float r_2_sq = settings.GetR2() * settings.GetR2();
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const float r_3_sq = settings.GetR3() * settings.GetR3();
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for (int i = 0; i < npredicted; i++) {
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auto r = predicted.at(i);
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IntegrateReflection(r, ptr, image.GetWidth(), image.GetHeight(), special_value, saturation,
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r_3, r_1_sq, r_2_sq, r_3_sq);
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if (r.observed) {
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if (experiment.GetPolarizationFactor())
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r.rlp /= geom.CalcAzIntPolarizationCorr(r.predicted_x, r.predicted_y, experiment.GetPolarizationFactor().value());
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r.image_number = static_cast<float>(image_number);
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ret.emplace_back(r);
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}
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}
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return ret;
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}
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std::vector<Reflection> BraggIntegrate2D(const DiffractionExperiment &experiment,
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const CompressedImage &image,
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const std::vector<Reflection> &predicted,
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size_t npredicted,
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int64_t image_number) {
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if (image.GetCompressedSize() == 0 || predicted.empty())
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return {};
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switch (image.GetMode()) {
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case CompressedImageMode::Int8:
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return IntegrateInternal<int8_t>(experiment, image, predicted, npredicted, INT8_MIN, INT8_MAX, image_number);
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case CompressedImageMode::Int16:
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return IntegrateInternal<int16_t>(experiment, image, predicted, npredicted, INT16_MIN, INT16_MAX, image_number);
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case CompressedImageMode::Int32:
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return IntegrateInternal<int32_t>(experiment, image, predicted, npredicted, INT32_MIN, INT32_MAX, image_number);
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case CompressedImageMode::Uint8:
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return IntegrateInternal<uint8_t>(experiment, image, predicted, npredicted, UINT8_MAX, UINT8_MAX, image_number);
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case CompressedImageMode::Uint16:
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return IntegrateInternal<uint16_t>(experiment, image, predicted, npredicted, UINT16_MAX, UINT16_MAX, image_number);
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case CompressedImageMode::Uint32:
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return IntegrateInternal<uint16_t>(experiment, image, predicted, npredicted, UINT32_MAX, UINT32_MAX, image_number);
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default:
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
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"Image mode not supported");
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}
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}
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