Line data    Source code

       1            0 : // Distributed under the MIT License.
       2              : // See LICENSE.txt for details.
       3              : 
       4              : #pragma once
       5              : 
       6              : #include <cstddef>
       7              : 
       8              : #include "DataStructures/Tensor/TypeAliases.hpp"
       9              : #include "Evolution/Systems/GrMhd/GhValenciaDivClean/System.hpp"
      10              : #include "Evolution/Systems/GrMhd/ValenciaDivClean/Tags.hpp"
      11              : #include "NumericalAlgorithms/TensorYlm/ApplyFilter.hpp"
      12              : #include "NumericalAlgorithms/TensorYlm/Filter.hpp"
      13              : 
      14              : /// \cond
      15              : class DataVector;
      16              : namespace RadiationTransport::NoNeutrinos {
      17              : struct System;
      18              : }  // namespace RadiationTransport::NoNeutrinos
      19              : namespace gsl {
      20              : template <typename T>
      21              : class not_null;
      22              : }  // namespace gsl
      23              : template <typename TagsList>
      24              : class Variables;
      25              : /// \endcond
      26              : 
      27              : namespace grmhd::GhValenciaDivClean::filter_detail {
      28              : 
      29              : /// The combined GH + Valencia variables tag list for GhValenciaDivClean.
      30              : using ghmhd_vars_list = typename grmhd::GhValenciaDivClean::System<
      31              :     RadiationTransport::NoNeutrinos::System>::variables_tag::tags_list;
      32              : 
      33              : /// The Valencia variables in their "grid frame" (used for YLM filtering).
      34              : /// Scalars are frame-independent; TildeS uses Grid frame lower index;
      35              : /// TildeB uses Grid frame upper index.
      36              : using valencia_grid_vars_list =
      37              :     tmpl::list<grmhd::ValenciaDivClean::Tags::TildeD,
      38              :                grmhd::ValenciaDivClean::Tags::TildeYe,
      39              :                grmhd::ValenciaDivClean::Tags::TildeTau,
      40              :                grmhd::ValenciaDivClean::Tags::TildeS<Frame::Grid>,
      41              :                grmhd::ValenciaDivClean::Tags::TildeB<Frame::Grid>,
      42              :                grmhd::ValenciaDivClean::Tags::TildePhi>;
      43              : 
      44              : }  // namespace grmhd::GhValenciaDivClean::filter_detail
      45              : 
      46              : namespace ylm::TensorYlm {
      47              : 
      48              : /*!
      49              :  * \brief Applies TensorYlm filter to the combined GH+Valencia variables.
      50              :  *
      51              :  * Applies the GH specialization to the GH part of the variables and
      52              :  * applies a standard scalar/vector filter to the Valencia variables.
      53              :  */
      54              : template <>
      55            1 : void apply_tensor_ylm_filter(
      56              :     gsl::not_null<
      57              :         Variables<grmhd::GhValenciaDivClean::filter_detail::ghmhd_vars_list>*>
      58              :         vars,
      59              :     gsl::not_null<
      60              :         Variables<grmhd::GhValenciaDivClean::filter_detail::ghmhd_vars_list>*>
      61              :         temp_storage,
      62              :     const InverseJacobian<DataVector, 3, Frame::Inertial, Frame::Grid>&
      63              :         jac_inertial_to_grid,
      64              :     const InverseJacobian<DataVector, 3, Frame::Grid, Frame::Inertial>&
      65              :         jac_grid_to_inertial,
      66              :     const ylm::TensorYlm::FilterMatrixHolder& filter_matrices, size_t ell_max,
      67              :     size_t radial_extents);
      68              : 
      69              : }  // namespace ylm::TensorYlm