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// SPDX-License-Identifier: LGPL-3.0-only
#ifndef RADLER_GENERIC_CLEAN_H_
#define RADLER_GENERIC_CLEAN_H_
#include <aocommon/optionalnumber.h>
#include <aocommon/uvector.h>
#include "image_set.h"
#include "algorithms/deconvolution_algorithm.h"
#include "algorithms/simple_clean.h"
namespace radler::algorithms {
/**
* This class implements a generalized version of Högbom clean. It performs a
* single-channel or joined cleaning, depending on the number of images
* provided. It can use a Clark-like optimization to speed up the cleaning. When
* multiple frequencies are provided, it can perform spectral fitting.
*/
class GenericClean final : public DeconvolutionAlgorithm {
public:
explicit GenericClean(bool use_sub_minor_optimization);
// TODO(AST-912) Make copy/move operations Google Style compliant.
GenericClean(const GenericClean&) = default;
GenericClean(GenericClean&&) = delete;
GenericClean& operator=(const GenericClean&) = delete;
GenericClean& operator=(GenericClean&&) = delete;
DeconvolutionResult ExecuteMajorIteration(
ImageSet& dirty_set, ImageSet& model_set,
const std::vector<aocommon::Image>& psfs) final;
std::unique_ptr<DeconvolutionAlgorithm> Clone() const final {
return std::make_unique<GenericClean>(*this);
}
private:
size_t convolution_width_;
size_t convolution_height_;
const float convolution_padding_;
bool use_sub_minor_optimization_;
// Scratch buffer should at least accomodate space for image.Size() floats
// and is only used to avoid unnecessary memory allocations.
aocommon::OptionalNumber<float> FindPeak(const aocommon::Image& image,
float* scratch_buffer, size_t& x,
size_t& y);
};
} // namespace radler::algorithms
#endif
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