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#include "catch2/catch_all.hpp"
#include "purify/config.h"
#include "purify/logging.h"
#include "purify/types.h"
#include "purify/directories.h"
#include "purify/pfitsio.h"
#include "purify/utilities.h"
#include "purify/algorithm_factory.h"
#include "purify/measurement_operator_factory.h"
#include "purify/wavelet_operator_factory.h"
#ifdef PURIFY_ONNXRT
#include <sopt/onnx_differentiable_func.h>
#endif
#ifdef PURIFY_H5
#include "purify/h5reader.h"
#endif
#include <sopt/gradient_utils.h>
#include <sopt/power_method.h>
#include "purify/test_data.h"
using namespace purify;
TEST_CASE("padmm_factory") {
const std::string &test_dir = "expected/padmm/";
const std::string &input_data_path = data_filename(test_dir + "input_data.vis");
const std::string &expected_solution_path = data_filename(test_dir + "solution.fits");
const std::string &expected_residual_path = data_filename(test_dir + "residual.fits");
const auto solution = pfitsio::read2d(expected_solution_path);
const auto residual = pfitsio::read2d(expected_residual_path);
auto uv_data = utilities::read_visibility(input_data_path, false);
uv_data.units = utilities::vis_units::radians;
CAPTURE(uv_data.vis.head(5));
REQUIRE(uv_data.size() == 13107);
t_uint const imsizey = 128;
t_uint const imsizex = 128;
Vector<t_complex> const init = Vector<t_complex>::Ones(imsizex * imsizey);
auto measurements_transform = factory::measurement_operator_factory<Vector<t_complex>>(
factory::distributed_measurement_operator::serial, uv_data, imsizey, imsizex, 1, 1, 2,
kernels::kernel_from_string.at("kb"), 4, 4);
auto const power_method_stuff =
sopt::algorithm::power_method<Vector<t_complex>>(*measurements_transform, 1000, 1e-5, init);
const t_real op_norm = std::get<0>(power_method_stuff);
measurements_transform->set_norm(op_norm);
std::vector<std::tuple<std::string, t_uint>> 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 wavelets = factory::wavelet_operator_factory<Vector<t_complex>>(
factory::distributed_wavelet_operator::serial, sara, imsizey, imsizex);
t_real const sigma = 0.016820222945913496 * std::sqrt(2); // see test_parameters file
auto const padmm = factory::padmm_factory<sopt::algorithm::ImagingProximalADMM<t_complex>>(
factory::algo_distribution::serial, measurements_transform, wavelets, uv_data, sigma, imsizey,
imsizex, sara.size(), 300, true, true, false, 1e-2, 1e-3, 50, 1);
auto const diagnostic = (*padmm)();
const Image<t_complex> image = Image<t_complex>::Map(diagnostic.x.data(), imsizey, imsizex);
// pfitsio::write2d(image.real(), expected_solution_path);
CAPTURE(Vector<t_complex>::Map(solution.data(), solution.size()).real().head(10));
CAPTURE(Vector<t_complex>::Map(image.data(), image.size()).real().head(10));
CAPTURE(Vector<t_complex>::Map((image / solution).eval().data(), image.size()).real().head(10));
CHECK(image.isApprox(solution, 1e-4));
const Vector<t_complex> residuals = measurements_transform->adjoint() *
(uv_data.vis - ((*measurements_transform) * diagnostic.x));
const Image<t_complex> residual_image = Image<t_complex>::Map(residuals.data(), imsizey, imsizex);
// pfitsio::write2d(residual_image.real(), expected_residual_path);
CAPTURE(Vector<t_complex>::Map(residual.data(), residual.size()).real().head(10));
CAPTURE(Vector<t_complex>::Map(residuals.data(), residuals.size()).real().head(10));
CHECK(residual_image.real().isApprox(residual.real(), 1e-4));
}
TEST_CASE("primal_dual_factory") {
const std::string &test_dir = "expected/primal_dual/";
const std::string &input_data_path = data_filename(test_dir + "input_data.vis");
const std::string &expected_solution_path = data_filename(test_dir + "solution.fits");
const std::string &expected_residual_path = data_filename(test_dir + "residual.fits");
const std::string &result_path = data_filename(test_dir + "pd_result.fits");
const auto solution = pfitsio::read2d(expected_solution_path);
const auto residual = pfitsio::read2d(expected_residual_path);
auto uv_data = utilities::read_visibility(input_data_path, false);
uv_data.units = utilities::vis_units::radians;
CAPTURE(uv_data.vis.head(5));
REQUIRE(uv_data.size() == 13107);
t_uint const imsizey = 128;
t_uint const imsizex = 128;
Vector<t_complex> const init = Vector<t_complex>::Ones(imsizex * imsizey);
auto measurements_transform = factory::measurement_operator_factory<Vector<t_complex>>(
factory::distributed_measurement_operator::serial, uv_data, imsizey, imsizex, 1, 1, 2,
kernels::kernel_from_string.at("kb"), 4, 4);
auto const power_method_stuff =
sopt::algorithm::power_method<Vector<t_complex>>(*measurements_transform, 1000, 1e-5, init);
const t_real op_norm = std::get<0>(power_method_stuff);
measurements_transform->set_norm(op_norm);
std::vector<std::tuple<std::string, t_uint>> 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 wavelets = factory::wavelet_operator_factory<Vector<t_complex>>(
factory::distributed_wavelet_operator::serial, sara, imsizey, imsizex);
t_real const sigma = 0.016820222945913496 * std::sqrt(2); // see test_parameters file
auto const primaldual =
factory::primaldual_factory<sopt::algorithm::ImagingPrimalDual<t_complex>>(
factory::algo_distribution::serial, measurements_transform, wavelets, uv_data, sigma,
imsizey, imsizex, sara.size(), 1000, true, true, 1e-3, 1);
auto const diagnostic = (*primaldual)();
const Image<t_complex> image = Image<t_complex>::Map(diagnostic.x.data(), imsizey, imsizex);
// pfitsio::write2d(image.real(), result_path);
double brightness = solution.real().cwiseAbs().maxCoeff();
double mse = (Vector<t_complex>::Map(solution.data(), solution.size()) - diagnostic.x)
.real()
.squaredNorm() /
solution.size();
double rms = sqrt(mse);
CHECK(rms <= brightness * 5e-2);
}
TEST_CASE("fb_factory") {
const std::string &test_dir = "expected/fb/";
const std::string &input_data_path = data_filename(test_dir + "input_data.vis");
const std::string &expected_solution_path = data_filename(test_dir + "solution.fits");
const std::string &expected_residual_path = data_filename(test_dir + "residual.fits");
const std::string &result_path = data_filename(test_dir + "fb_result.fits");
const auto solution = pfitsio::read2d(expected_solution_path);
const auto residual = pfitsio::read2d(expected_residual_path);
auto uv_data = utilities::read_visibility(input_data_path, false);
uv_data.units = utilities::vis_units::radians;
CAPTURE(uv_data.vis.head(5));
REQUIRE(uv_data.size() == 13107);
t_uint const imsizey = 128;
t_uint const imsizex = 128;
Vector<t_complex> const init = Vector<t_complex>::Ones(imsizex * imsizey);
auto measurements_transform = factory::measurement_operator_factory<Vector<t_complex>>(
factory::distributed_measurement_operator::serial, uv_data, imsizey, imsizex, 1, 1, 2,
kernels::kernel_from_string.at("kb"), 4, 4);
auto const power_method_stuff =
sopt::algorithm::power_method<Vector<t_complex>>(*measurements_transform, 1000, 1e-5, init);
const t_real op_norm = std::get<0>(power_method_stuff);
measurements_transform->set_norm(op_norm);
std::vector<std::tuple<std::string, t_uint>> 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 wavelets = factory::wavelet_operator_factory<Vector<t_complex>>(
factory::distributed_wavelet_operator::serial, sara, imsizey, imsizex);
t_real const sigma = 0.016820222945913496 * std::sqrt(2); // see test_parameters file
t_real const beta = sigma * sigma;
t_real const gamma = 0.0001;
auto const fb = factory::fb_factory<sopt::algorithm::ImagingForwardBackward<t_complex>>(
factory::algo_distribution::serial, measurements_transform, wavelets, uv_data, sigma, beta,
gamma, imsizey, imsizex, sara.size(), 1000, true, true, false, 1e-2, 1e-3, 50);
auto const diagnostic = (*fb)();
const Image<t_complex> image = Image<t_complex>::Map(diagnostic.x.data(), imsizey, imsizex);
pfitsio::write2d(image.real(), result_path);
// pfitsio::write2d(residual_image.real(), expected_residual_path);
double brightness = solution.real().cwiseAbs().maxCoeff();
double mse = (Vector<t_complex>::Map(solution.data(), solution.size()) - diagnostic.x)
.real()
.squaredNorm() /
solution.size();
double rms = sqrt(mse);
CHECK(rms <= brightness * 5e-2);
}
#ifdef PURIFY_H5
TEST_CASE("fb_factory_stochastic") {
const std::string &test_dir = "expected/fb/";
const std::string &input_data_path = data_filename(test_dir + "input_data.vis");
const std::string &expected_solution_path = data_filename(test_dir + "solution.fits");
const std::string &expected_residual_path = data_filename(test_dir + "residual.fits");
const std::string &result_path = data_filename(test_dir + "fb_result_stochastic.fits");
auto uv_data = utilities::read_visibility(input_data_path, false);
uv_data.units = utilities::vis_units::radians;
CAPTURE(uv_data.vis.head(5));
REQUIRE(uv_data.size() == 13107);
t_uint const imsizey = 128;
t_uint const imsizex = 128;
// This functor would be defined in Purify
std::mt19937 rng(0);
const size_t N = 1000;
std::function<std::shared_ptr<sopt::IterationState<Vector<t_complex>>>()> random_updater =
[&input_data_path, imsizex, imsizey, &rng, &N]() {
utilities::vis_params uv_data = utilities::read_visibility(input_data_path, false);
uv_data.units = utilities::vis_units::radians;
// Get random subset
std::vector<size_t> indices(uv_data.size());
size_t i = 0;
for (auto &x : indices) {
x = i++;
}
std::shuffle(indices.begin(), indices.end(), rng);
Vector<t_real> u_fragment(N);
Vector<t_real> v_fragment(N);
Vector<t_real> w_fragment(N);
Vector<t_complex> vis_fragment(N);
Vector<t_complex> weights_fragment(N);
for (i = 0; i < N; i++) {
size_t j = indices[i];
u_fragment[i] = uv_data.u[j];
v_fragment[i] = uv_data.v[j];
w_fragment[i] = uv_data.w[j];
vis_fragment[i] = uv_data.vis[j];
weights_fragment[i] = uv_data.weights[j];
}
utilities::vis_params uv_data_fragment(u_fragment, v_fragment, w_fragment, vis_fragment,
weights_fragment, uv_data.units, uv_data.ra,
uv_data.dec, uv_data.average_frequency);
auto phi = factory::measurement_operator_factory<Vector<t_complex>>(
factory::distributed_measurement_operator::serial, uv_data_fragment, imsizey, imsizex,
1, 1, 2, kernels::kernel_from_string.at("kb"), 4, 4);
Vector<t_complex> const init = Vector<t_complex>::Ones(imsizex * imsizey);
auto const power_method_stuff =
sopt::algorithm::power_method<Vector<t_complex>>(*phi, 1000, 1e-5, init);
const t_real op_norm = std::get<0>(power_method_stuff);
phi->set_norm(op_norm);
return std::make_shared<sopt::IterationState<Vector<t_complex>>>(uv_data_fragment.vis, phi);
};
const auto solution = pfitsio::read2d(expected_solution_path);
// wavelets
std::vector<std::tuple<std::string, t_uint>> 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 wavelets = factory::wavelet_operator_factory<Vector<t_complex>>(
factory::distributed_wavelet_operator::serial, sara, imsizey, imsizex);
// algorithm
t_real const sigma = 0.016820222945913496 * std::sqrt(2); // see test_parameters file
t_real const beta = sigma * sigma;
t_real const gamma = 0.0001;
sopt::algorithm::ImagingForwardBackward<t_complex> fb(random_updater);
fb.itermax(1000)
.step_size(beta * sqrt(2))
.sigma(sigma * sqrt(2))
.regulariser_strength(gamma)
.relative_variation(1e-3)
.residual_tolerance(0)
.tight_frame(true);
auto gp = std::make_shared<sopt::algorithm::L1GProximal<t_complex>>(false);
gp->l1_proximal_tolerance(1e-4)
.l1_proximal_nu(1)
.l1_proximal_itermax(50)
.l1_proximal_positivity_constraint(true)
.l1_proximal_real_constraint(true)
.Psi(*wavelets);
fb.g_function(gp);
auto const diagnostic = fb();
const Image<t_complex> image = Image<t_complex>::Map(diagnostic.x.data(), imsizey, imsizex);
// pfitsio::write2d(image.real(), result_path);
// pfitsio::write2d(residual_image.real(), expected_residual_path);
auto soln_flat = Vector<t_complex>::Map(solution.data(), solution.size());
double brightness = soln_flat.real().cwiseAbs().maxCoeff();
double mse = (soln_flat - diagnostic.x).real().squaredNorm() / solution.size();
SOPT_HIGH_LOG("MSE = {}", mse);
CHECK(mse <= brightness * 5e-2);
}
#endif
#ifdef PURIFY_ONNXRT
TEST_CASE("tf_fb_factory") {
const std::string &test_dir = "expected/fb/";
const std::string &input_data_path = data_filename(test_dir + "input_data.vis");
const std::string &expected_solution_path = data_filename(test_dir + "solution.fits");
const std::string &expected_residual_path = data_filename(test_dir + "residual.fits");
const std::string &result_path = data_filename(test_dir + "tf_result.fits");
const auto solution = pfitsio::read2d(expected_solution_path);
const auto residual = pfitsio::read2d(expected_residual_path);
auto uv_data = utilities::read_visibility(input_data_path, false);
uv_data.units = utilities::vis_units::radians;
CAPTURE(uv_data.vis.head(5));
REQUIRE(uv_data.size() == 13107);
t_uint const imsizey = 128;
t_uint const imsizex = 128;
Vector<t_complex> const init = Vector<t_complex>::Ones(imsizex * imsizey);
auto measurements_transform = factory::measurement_operator_factory<Vector<t_complex>>(
factory::distributed_measurement_operator::serial, uv_data, imsizey, imsizex, 1, 1, 2,
kernels::kernel_from_string.at("kb"), 4, 4);
auto const power_method_stuff =
sopt::algorithm::power_method<Vector<t_complex>>(*measurements_transform, 1000, 1e-5, init);
const t_real op_norm = std::get<0>(power_method_stuff);
measurements_transform->set_norm(op_norm);
std::vector<std::tuple<std::string, t_uint>> 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 wavelets = factory::wavelet_operator_factory<Vector<t_complex>>(
factory::distributed_wavelet_operator::serial, sara, imsizey, imsizex);
t_real const sigma = 0.016820222945913496 * std::sqrt(2); // see test_parameters file
t_real const beta = sigma * sigma;
t_real const gamma = 0.0001;
std::string tf_model_path = purify::models_directory() + "/snr_15_model_dynamic.onnx";
auto const fb = factory::fb_factory<sopt::algorithm::ImagingForwardBackward<t_complex>>(
factory::algo_distribution::serial, measurements_transform, wavelets, uv_data, sigma, beta,
gamma, imsizey, imsizex, sara.size(), 1000, true, true, false, 1e-2, 1e-3, 50, tf_model_path,
nondiff_func_type::Denoiser);
auto const diagnostic = (*fb)();
const Image<t_complex> image = Image<t_complex>::Map(diagnostic.x.data(), imsizey, imsizex);
// pfitsio::write2d(image.real(), result_path);
// pfitsio::write2d(residual_image.real(), expected_residual_path);
double brightness = solution.real().cwiseAbs().maxCoeff();
double mse = (Vector<t_complex>::Map(solution.data(), solution.size()) - diagnostic.x)
.real()
.squaredNorm() /
solution.size();
double rms = sqrt(mse);
CHECK(rms <= brightness * 5e-2);
}
TEST_CASE("onnx_fb_factory") {
const std::string &test_dir = "expected/fb/";
const std::string &input_data_path = data_filename(test_dir + "input_data.vis");
const std::string &expected_solution_path = data_filename(test_dir + "solution.fits");
const std::string &expected_residual_path = data_filename(test_dir + "residual.fits");
const std::string &result_path = data_filename(test_dir + "onnx_result.fits");
const auto solution = pfitsio::read2d(expected_solution_path);
const auto residual = pfitsio::read2d(expected_residual_path);
auto uv_data = utilities::read_visibility(input_data_path, false);
uv_data.units = utilities::vis_units::radians;
CAPTURE(uv_data.vis.head(5));
REQUIRE(uv_data.size() == 13107);
t_uint const imsizey = 128;
t_uint const imsizex = 128;
Vector<t_complex> const init = Vector<t_complex>::Ones(imsizex * imsizey);
auto measurements_transform = factory::measurement_operator_factory<Vector<t_complex>>(
factory::distributed_measurement_operator::serial, uv_data, imsizey, imsizex, 1, 1, 2,
kernels::kernel_from_string.at("kb"), 4, 4);
auto const power_method_stuff =
sopt::algorithm::power_method<Vector<t_complex>>(*measurements_transform, 1000, 1e-5, init);
const t_real op_norm = std::get<0>(power_method_stuff);
measurements_transform->set_norm(op_norm);
std::vector<std::tuple<std::string, t_uint>> 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 wavelets = factory::wavelet_operator_factory<Vector<t_complex>>(
factory::distributed_wavelet_operator::serial, sara, imsizey, imsizex);
t_real const sigma = 0.016820222945913496 * std::sqrt(2); // see test_parameters file
t_real const beta = sigma * sigma;
t_real const gamma = 0.0001;
std::string const prior_path =
purify::models_directory() + "/example_cost_dynamic_CRR_sigma_5_t_5.onnx";
std::string const prior_gradient_path =
purify::models_directory() + "/example_grad_dynamic_CRR_sigma_5_t_5.onnx";
std::shared_ptr<sopt::ONNXDifferentiableFunc<t_complex>> diff_function =
std::make_shared<sopt::ONNXDifferentiableFunc<t_complex>>(
prior_path, prior_gradient_path, sigma, 20, 5e4, *measurements_transform);
auto const fb = factory::fb_factory<sopt::algorithm::ImagingForwardBackward<t_complex>>(
factory::algo_distribution::serial, measurements_transform, wavelets, uv_data, sigma, beta,
gamma, imsizey, imsizex, sara.size(), 1000, true, true, false, 1e-3, 1e-3, 50, "",
nondiff_func_type::RealIndicator, diff_function);
auto const diagnostic = (*fb)();
const Image<t_complex> image = Image<t_complex>::Map(diagnostic.x.data(), imsizey, imsizex);
// pfitsio::write2d(image.real(), result_path);
// pfitsio::write2d(residual_image.real(), expected_residual_path);
double brightness = solution.real().cwiseAbs().maxCoeff();
double mse = (Vector<t_complex>::Map(solution.data(), solution.size()) - diagnostic.x)
.real()
.squaredNorm() /
solution.size();
double rms = sqrt(mse);
CHECK(rms <= brightness * 5e-2);
}
#endif
TEST_CASE("joint_map_factory") {
const std::string &test_dir = "expected/joint_map/";
const std::string &input_data_path = data_filename(test_dir + "input_data.vis");
const std::string &expected_solution_path = data_filename(test_dir + "solution.fits");
const std::string &expected_residual_path = data_filename(test_dir + "residual.fits");
const auto solution = pfitsio::read2d(expected_solution_path);
const auto residual = pfitsio::read2d(expected_residual_path);
auto uv_data = utilities::read_visibility(input_data_path, false);
uv_data.units = utilities::vis_units::radians;
CAPTURE(uv_data.vis.head(5));
REQUIRE(uv_data.size() == 13107);
t_uint const imsizey = 128;
t_uint const imsizex = 128;
Vector<t_complex> const init = Vector<t_complex>::Ones(imsizex * imsizey);
auto measurements_transform = factory::measurement_operator_factory<Vector<t_complex>>(
factory::distributed_measurement_operator::serial, uv_data, imsizey, imsizex, 1, 1, 2,
kernels::kernel_from_string.at("kb"), 4, 4);
auto const power_method_stuff =
sopt::algorithm::power_method<Vector<t_complex>>(*measurements_transform, 1000, 1e-5, init);
const t_real op_norm = std::get<0>(power_method_stuff);
measurements_transform->set_norm(op_norm);
std::vector<std::tuple<std::string, t_uint>> 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 wavelets = factory::wavelet_operator_factory<Vector<t_complex>>(
factory::distributed_wavelet_operator::serial, sara, imsizey, imsizex);
t_real const sigma = 0.016820222945913496 * std::sqrt(2); // see test_parameters file
t_real const beta = sigma * sigma;
t_real const gamma = 1;
auto const fb = factory::fb_factory<sopt::algorithm::ImagingForwardBackward<t_complex>>(
factory::algo_distribution::serial, measurements_transform, wavelets, uv_data, sigma, beta,
gamma, imsizey, imsizex, sara.size(), 1000, true, true, false, 1e-2, 1e-3, 50);
auto const l1_norm = [wavelets](const Vector<t_complex> &x) {
auto val = sopt::l1_norm(wavelets->adjoint() * x);
return val;
};
auto const joint_map =
sopt::algorithm::JointMAP<sopt::algorithm::ImagingForwardBackward<t_complex>>(
fb, l1_norm, imsizex * imsizey * sara.size())
.relative_variation(1e-3)
.objective_variation(1e-3)
.beta(1.)
.alpha(1.);
auto const diagnostic = joint_map();
const Image<t_complex> image = Image<t_complex>::Map(diagnostic.x.data(), imsizey, imsizex);
// CAPTURE(Vector<t_complex>::Map(solution.data(), solution.size()).real().head(10));
// CAPTURE(Vector<t_complex>::Map(image.data(), image.size()).real().head(10));
// CAPTURE(Vector<t_complex>::Map((image / solution).eval().data(),
// image.size()).real().head(10));
// CHECK(image.isApprox(solution, 1e-6));
const Vector<t_complex> residuals = measurements_transform->adjoint() *
(uv_data.vis - ((*measurements_transform) * diagnostic.x));
const Image<t_complex> residual_image = Image<t_complex>::Map(residuals.data(), imsizey, imsizex);
// CAPTURE(Vector<t_complex>::Map(residual.data(), residual.size()).real().head(10));
// CAPTURE(Vector<t_complex>::Map(residuals.data(), residuals.size()).real().head(10));
// CHECK(residual_image.real().isApprox(residual.real(), 1e-6));
}
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