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Jungfraujoch/image_analysis/image_preprocessing/ImagePreprocessorCPU.cpp
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leonarski_fandClaude Opus 5.5 094eee31a2
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macOS build: explicit size_t in the XFEL reader's row bounds; parentheses in the CPU preprocessor's select
On macOS size_t (unsigned long) plus int64_t (long long) is unsigned long long, so std::max/std::min had
two argument types; the template argument is now given. The preprocessor's (masked | error) ? ... is what
the code already did - the parentheses only silence clang's -Wbitwise-conditional-parentheses.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu
2026-10-23 13:44:46 +02:00

103 lines
5.2 KiB
C++

// SPDX-FileCopyrightText: 2026 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#include "ImagePreprocessorCPU.h"
#include <algorithm>
#include <limits>
#include <type_traits>
ImagePreprocessorCPU::ImagePreprocessorCPU(const DiffractionExperiment &experiment, const PixelMask &mask)
: ImagePreprocessor(experiment),
mask_bits(mask.GetPackedMask()) {
if (mask.GetMask().size() != npixels)
throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
"Pixel mask size doesn't match the image");
}
ImageStatistics ImagePreprocessorCPU::Analyze(ImagePreprocessorBuffer &processed_image, const uint8_t *image_ptr, CompressedImageMode image_mode) {
if (processed_image.size() != npixels)
throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "Processed image size mismatch");
ImageStatistics ret{};
AnalyzeBlock(processed_image, 0, image_ptr, npixels, image_mode, ret);
return ret;
}
void ImagePreprocessorCPU::AnalyzeBlock(ImagePreprocessorBuffer &processed_image, size_t first, const uint8_t *input,
size_t n, CompressedImageMode image_mode, ImageStatistics &stats) {
switch (image_mode) {
case CompressedImageMode::Int8:
return AnalyzeBlock<int8_t>(processed_image, first, input, n, INT8_MIN, INT8_MAX, stats);
case CompressedImageMode::Int16:
return AnalyzeBlock<int16_t>(processed_image, first, input, n, INT16_MIN, INT16_MAX, stats);
case CompressedImageMode::Int32:
return AnalyzeBlock<int32_t>(processed_image, first, input, n, INT32_MIN, INT32_MAX, stats);
case CompressedImageMode::Uint8:
return AnalyzeBlock<uint8_t>(processed_image, first, input, n, UINT8_MAX, UINT8_MAX, stats);
case CompressedImageMode::Uint16:
return AnalyzeBlock<uint16_t>(processed_image, first, input, n, UINT16_MAX, UINT16_MAX, stats);
case CompressedImageMode::Uint32:
return AnalyzeBlock<uint32_t>(processed_image, first, input, n, UINT32_MAX, UINT32_MAX, stats);
default:
throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "RGB/float mode not supported");
}
}
template<class T>
void ImagePreprocessorCPU::AnalyzeBlock(ImagePreprocessorBuffer &processed_image, size_t first, const uint8_t *input,
size_t n, T err_pixel_val, T sat_pixel_val, ImageStatistics &ret) {
auto image = reinterpret_cast<const T *>(input);
int32_t *out = processed_image.data() + first;
if (sat_pixel_val > saturation_limit)
sat_pixel_val = static_cast<T>(saturation_limit);
// Every pixel is classified without a branch, so that the loop over the pixels vectorises. The
// extremes are taken over keys that order as the values do (a signed type's sign bit flipped), and a
// pixel that does not count gives the key no maximum or minimum can be moved by; the counts are
// integers. So the statistics are those of the pixel-by-pixel tests, whatever the order.
using U = std::make_unsigned_t<T>;
constexpr U flip = std::is_signed_v<T> ? static_cast<U>(U{1} << (8 * sizeof(T) - 1)) : U{0};
uint64_t n_masked = 0, n_error = 0, n_saturated = 0;
U key_max = 0, key_min = std::numeric_limits<U>::max();
const auto pixel = [&](size_t i, bool masked) {
const T v = image[i];
// Error/invalid marker = the pixel type's extreme value (0xFFFFFFFF for EIGER uint32). Tested
// before saturation, since for unsigned types the marker also exceeds sat_pixel_val (which is
// clipped above to the HDF5 saturation_value).
const bool error = !masked & (v == err_pixel_val);
const bool saturated = !masked & !error & (v >= sat_pixel_val);
const U counted = static_cast<U>(-static_cast<int>(!masked & !error & !saturated)); // all bits, or none
out[i] = (masked | error) ? INT32_MIN : saturated ? INT32_MAX : static_cast<int32_t>(v);
n_masked += masked;
n_error += error;
n_saturated += saturated;
const U key = static_cast<U>(v) ^ flip;
key_max = std::max<U>(key_max, key & counted);
key_min = std::min<U>(key_min, key | static_cast<U>(~counted));
};
// Runs of whole mask words with no pixel masked - nearly all of a detector - take a loop of their
// own, which the compiler vectorises; the rest is tested pixel by pixel.
for (size_t i = 0; i < n;) {
size_t end = i;
if ((first + i) % 32 == 0)
while (end + 32 <= n && mask_bits[(first + end) / 32] == 0)
end += 32;
if (end > i) {
for (; i < end; i++)
pixel(i, false);
} else {
pixel(i, (mask_bits[(first + i) / 32] >> ((first + i) % 32)) & 1U);
i++;
}
}
ret.masked_pixel_count += n_masked;
ret.error_pixel_count += n_error;
ret.saturated_pixel_count += n_saturated;
if (n_masked + n_error + n_saturated < n) { // some pixel counted
ret.max_value = std::max<long long>(ret.max_value, static_cast<T>(key_max ^ flip));
ret.min_value = std::min<long long>(ret.min_value, static_cast<T>(key_min ^ flip));
}
}