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#include <array>
#include <memory>
#include <random>
#include <boost/math/special_functions/erf.hpp>
#include <sopt/imaging_padmm.h>
#include <sopt/relative_variation.h>
#include <sopt/utilities.h>
#include <sopt/wavelets.h>
#include <sopt/wavelets/sara.h>
#include "purify/MeasurementOperator.h"
#include "purify/directories.h"
#include "purify/pfitsio.h"
#include "purify/types.h"
#include "purify/utilities.h"
#include "purify/logging.h"
using namespace purify;
using namespace purify::notinstalled;
void padmm(const std::string & name, const Image<t_complex> & M31, const std::string & kernel, const t_int J, const utilities::vis_params & uv_data, const t_real sigma){
std::string const outfile = output_filename(name + "_" + kernel + ".tiff");
std::string const outfile_fits = output_filename(name + "_" + kernel + "_solution.fits");
std::string const residual_fits = output_filename(name + "_" + kernel + "_residual.fits");
std::string const dirty_image = output_filename(name + "_" + kernel + "_dirty.tiff");
std::string const dirty_image_fits = output_filename(name + "_" + kernel + "_dirty.fits");
t_real const over_sample = 2;
MeasurementOperator measurements(uv_data, J, J, kernel, M31.cols(), M31.rows(), 100, over_sample);
auto measurements_transform = linear_transform(measurements, uv_data.vis.size());
sopt::wavelets::SARA const sara{
std::make_tuple("Dirac", 3u), std::make_tuple("DB1", 3u), std::make_tuple("DB2", 3u),
std::make_tuple("DB3", 3u), std::make_tuple("DB4", 3u), std::make_tuple("DB5", 3u),
std::make_tuple("DB6", 3u), std::make_tuple("DB7", 3u), std::make_tuple("DB8", 3u)};
auto const Psi
= sopt::linear_transform<t_complex>(sara, measurements.imsizey(), measurements.imsizex());
Vector<> dimage = (measurements_transform.adjoint() * uv_data.vis).real();
Vector<t_complex> initial_estimate = Vector<t_complex>::Zero(dimage.size());
sopt::utilities::write_tiff(
Image<t_real>::Map(dimage.data(), measurements.imsizey(), measurements.imsizex()),
dirty_image);
pfitsio::write2d(
Image<t_real>::Map(dimage.data(), measurements.imsizey(), measurements.imsizex()),
dirty_image_fits);
auto const epsilon = utilities::calculate_l2_radius(uv_data.vis, sigma);
std::printf("Using epsilon of %f \n", epsilon);
std::cout << "Starting sopt" << '\n';
auto const padmm
= sopt::algorithm::ImagingProximalADMM<t_complex>(uv_data.vis)
.itermax(100)
.gamma((measurements_transform.adjoint() * uv_data.vis).real().maxCoeff() * 1e-3)
.relative_variation(1e-3)
.l2ball_proximal_epsilon(epsilon)
.tight_frame(false)
.l1_proximal_tolerance(1e-2)
.l1_proximal_nu(1)
.l1_proximal_itermax(50)
.l1_proximal_positivity_constraint(true)
.l1_proximal_real_constraint(true)
.residual_convergence(epsilon * 1.001)
.lagrange_update_scale(0.9)
.nu(1e0)
.Psi(Psi)
.Phi(measurements_transform);
auto const diagnostic = padmm();
assert(diagnostic.x.size() == M31.size());
Image<t_complex> image
= Image<t_complex>::Map(diagnostic.x.data(), measurements.imsizey(), measurements.imsizex());
pfitsio::write2d(image.real(), outfile_fits);
Image<t_complex> residual = measurements.grid(uv_data.vis - measurements.degrid(image));
pfitsio::write2d(residual.real(), residual_fits);
};
int main(int, char **) {
sopt::logging::initialize();
purify::logging::initialize();
sopt::logging::set_level("debug");
purify::logging::set_level("debug");
const std::string & name = "30dor_256";
const t_real snr = 30;
std::string const fitsfile = image_filename(name + ".fits");
auto M31 = pfitsio::read2d(fitsfile);
std::string const inputfile = output_filename(name + "_" + "input.fits");
t_real const max = M31.array().abs().maxCoeff();
M31 = M31 * 1. / max;
pfitsio::write2d(M31.real(), inputfile);
t_int const number_of_pxiels = M31.size();
t_int const number_of_vis = std::floor( number_of_pxiels * 2.);
// Generating random uv(w) coverage
t_real const sigma_m = constant::pi / 3;
auto uv_data = utilities::random_sample_density(number_of_vis, 0, sigma_m);
uv_data.units = "radians";
std::cout << "Number of measurements / number of pixels: " << uv_data.u.size() * 1. / number_of_pxiels
<< '\n';
// uv_data = utilities::uv_symmetry(uv_data); //reflect uv measurements
MeasurementOperator sky_measurements(uv_data, 8, 8, "kb", M31.cols(), M31.rows(), 100, 2);
uv_data.vis = sky_measurements.degrid(M31);
Vector<t_complex> const y0 = uv_data.vis;
// working out value of signal given SNR of 30
t_real const sigma = utilities::SNR_to_standard_deviation(y0, snr);
// adding noise to visibilities
uv_data.vis = utilities::add_noise(y0, 0., sigma);
padmm(name + "30", M31, "box", 1, uv_data, sigma);
padmm(name + "30", M31, "kb", 4, uv_data, sigma);
return 0;
}
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