12#include <Eigen/Sparse>
15#include <spdlog/spdlog.h>
16#include <unsupported/Eigen/Splines>
19template <
typename Scalar>
20GreenTensor<Scalar>::ConstantEntry::ConstantEntry(
int row,
int col, Scalar val)
21 : row_(row), col_(col), val_(val) {}
23template <
typename Scalar>
28template <
typename Scalar>
33template <
typename Scalar>
38template <
typename Scalar>
40 Eigen::Spline<real_t, 1> real_spline,
41 Eigen::Spline<real_t, 1> imag_spline)
42 : row_(row), col_(col), real_spline(std::move(real_spline)),
43 imag_spline(std::move(imag_spline)) {}
45template <
typename Scalar>
48 return {real_spline(omega)(0), imag_spline(omega)(0)};
50 return real_spline(omega)(0);
54template <
typename Scalar>
59template <
typename Scalar>
64template <
typename Scalar>
68 const real_t scale = tensor_in_cartesian_coordinates.norm();
69 const real_t numerical_precision = 100 * scale * std::numeric_limits<real_t>::epsilon();
71 Eigen::SparseMatrix<complex_t> tensor =
72 (spherical::get_transformator<complex_t>(kappa1) * tensor_in_cartesian_coordinates *
73 spherical::get_transformator<complex_t>(kappa2).adjoint())
74 .sparseView(1, numerical_precision);
76 std::vector<Entry> entries;
77 for (
int k = 0; k < tensor.outerSize(); ++k) {
78 for (
typename Eigen::SparseMatrix<complex_t>::InnerIterator it(tensor, k); it; ++it) {
80 entries.emplace_back(
ConstantEntry(it.row(), it.col(), it.value()));
82 entries.emplace_back(
ConstantEntry(it.row(), it.col(), it.value().real()));
83 assert(abs(it.value().imag()) < numerical_precision);
87 entries_map[{kappa1, kappa2}] = std::move(entries);
90template <
typename Scalar>
92 int kappa1,
int kappa2,
94 const std::vector<double> &omegas) {
96 if (tensors_in_cartesian_coordinates.size() != omegas.size()) {
97 throw std::invalid_argument(
"The number of tensors and omegas must match.");
100 if (tensors_in_cartesian_coordinates.size() < 4) {
101 throw std::invalid_argument(
102 "At least 4 tensors are required for the applied cubic spline interpolation.");
105 auto num_knots =
static_cast<int>(omegas.size());
106 Eigen::Map<const Eigen::RowVectorXd> knots(omegas.data(), num_knots);
108 constexpr int spline_degree = 3;
111 std::map<std::pair<int, int>, std::pair<Eigen::RowVectorXd, Eigen::RowVectorXd>> temp_map;
112 for (
int idx = 0; idx < num_knots; ++idx) {
114 const real_t scale = tensors_in_cartesian_coordinates[idx].norm();
115 const real_t numerical_precision = 100 * scale * std::numeric_limits<real_t>::epsilon();
117 Eigen::SparseMatrix<complex_t> tensor =
118 (spherical::get_transformator<complex_t>(kappa1) *
119 tensors_in_cartesian_coordinates[idx] *
120 spherical::get_transformator<complex_t>(kappa2).adjoint())
121 .sparseView(1, numerical_precision);
123 for (
int k = 0; k < tensor.outerSize(); ++k) {
124 for (
typename Eigen::SparseMatrix<complex_t>::InnerIterator it(tensor, k); it; ++it) {
125 std::pair<int, int> key{it.row(), it.col()};
126 auto &[vec_real, vec_imag] =
128 .try_emplace(key, Eigen::RowVectorXd::Zero(num_knots),
129 Eigen::RowVectorXd::Zero(num_knots))
131 vec_real(idx) = it.value().real();
133 vec_imag(idx) = it.value().imag();
135 assert(abs(it.value().imag()) < numerical_precision);
142 std::vector<Entry> entries;
143 entries.reserve(temp_map.size());
144 for (
const auto &[key, value] : temp_map) {
145 const auto &[vec_real, vec_imag] = value;
146 const auto &[row, col] = key;
148 Eigen::Spline<real_t, 1> real_spline =
149 Eigen::SplineFitting<Eigen::Spline<real_t, 1>>::Interpolate(vec_real, spline_degree,
152 Eigen::Spline<real_t, 1> imag_spline;
154 imag_spline = Eigen::SplineFitting<Eigen::Spline<real_t, 1>>::Interpolate(
155 vec_imag, spline_degree, knots);
158 entries.emplace_back(
161 entries_map[{kappa1, kappa2}] = std::move(entries);
164template <
typename Scalar>
165const std::vector<typename GreenTensor<Scalar>::Entry> &
167 if (
auto it = entries_map.find({kappa1, kappa2}); it != entries_map.end()) {
170 static const std::vector<Entry> empty_entries;
171 return empty_entries;
Scalar val(double omega) const
typename traits::NumTraits< Scalar >::real_t real_t
void create_entries_from_cartesian(int kappa1, int kappa2, const Eigen::MatrixX< Scalar > &tensor_in_cartesian_coordinates)
const std::vector< Entry > & get_spherical_entries(int kappa1, int kappa2) const
Matrix< Type, Dynamic, Dynamic > MatrixX
Helper struct to extract types from a numerical type.