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/builds/MusicScience37Projects/numerical-analysis/numerical-collection-cpp/include/num_collect/ode/rosenbrock/rodaspr_formula.h
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/*
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 * Copyright 2021 MusicScience37 (Kenta Kabashima)
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 *
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 * Licensed under the Apache License, Version 2.0 (the "License");
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 * you may not use this file except in compliance with the License.
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 * You may obtain a copy of the License at
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 *
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 *     http://www.apache.org/licenses/LICENSE-2.0
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 *
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 * Unless required by applicable law or agreed to in writing, software
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 * distributed under the License is distributed on an "AS IS" BASIS,
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 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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 * See the License for the specific language governing permissions and
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 * limitations under the License.
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 */
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/*!
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 * \file
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 * \brief Definition of rodaspr_formula class.
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 */
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#pragma once
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#include "num_collect/base/index_type.h"
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#include "num_collect/logging/log_tag_view.h"
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#include "num_collect/ode/concepts/problem.h"
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#include "num_collect/ode/concepts/rosenbrock_equation_solver.h"
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#include "num_collect/ode/embedded_solver.h"
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#include "num_collect/ode/evaluation_type.h"
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#include "num_collect/ode/rosenbrock/default_rosenbrock_equation_solver.h"
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#include "num_collect/ode/rosenbrock/rosenbrock_formula_base.h"
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namespace num_collect::ode::rosenbrock {
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/*!
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 * \brief Class of RODASPR formula \cite Rang2015 for Rosenbrock method.
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 *
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 * \tparam Problem Type of problem.
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 * \tparam EquationSolver Type of class to solve equations in Rosenbrock
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 * methods.
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 */
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template <concepts::problem Problem,
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    concepts::rosenbrock_equation_solver EquationSolver =
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        default_rosenbrock_equation_solver_t<Problem>>
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class rodaspr_formula
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    : public rosenbrock_formula_base<rodaspr_formula<Problem, EquationSolver>,
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          Problem, EquationSolver> {
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public:
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    //! Type of base class.
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    using base_type =
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        rosenbrock_formula_base<rodaspr_formula<Problem, EquationSolver>,
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            Problem, EquationSolver>;
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    using typename base_type::equation_solver_type;
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    using typename base_type::problem_type;
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    using typename base_type::scalar_type;
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    using typename base_type::variable_type;
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    using base_type::base_type;
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    using base_type::equation_solver;
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    using base_type::problem;
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protected:
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    using base_type::coeff;
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public:
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    //! Number of stages of this formula.
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    static constexpr index_type stages = 6;
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    //! Order of this formula.
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    static constexpr index_type order = 4;
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    /*!
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     * \brief Order of lesser coefficients of this formula.
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     *
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     * \warning Exact information has not been found.
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     */
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    static constexpr index_type lesser_order = 3;
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    //! Log tag.
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    static constexpr auto log_tag =
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        logging::log_tag_view("num_collect::ode::rosenbrock::rodaspr_formula");
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    /*!
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     * \name Coefficients in Rosenbrock method.
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     *
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     * - `a` is coefficients of intermidiate variables in calculation of
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     *   intermidiate variables.
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     * - `b` is coefficients of time in calculation of intermidiate variables.
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     * - `c` is coefficients of intermidiate variables in calculation of
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     *   estimates of next variables.
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     * - `g` is coefficients of intermidiate variables in calculation of
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     *   intermidiate variables.
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     */
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    ///@{
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    //! Coefficient in Rosenbrock method.
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    static constexpr scalar_type a21 = coeff(0.75);
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    static constexpr scalar_type a31 = coeff(7.5162877593868457e-2);
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    static constexpr scalar_type a32 = coeff(2.4837122406131545e-2);
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    static constexpr scalar_type a41 = coeff(1.6532708886396510);
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    static constexpr scalar_type a42 = coeff(0.21545706385445562);
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    static constexpr scalar_type a43 = coeff(-1.3157488872766792);
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    static constexpr scalar_type a51 = coeff(19.385003738039885);
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    static constexpr scalar_type a52 = coeff(1.2007117225835324);
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    static constexpr scalar_type a53 = coeff(-19.337924059522791);
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    static constexpr scalar_type a54 = coeff(-0.24779140110062559);
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    static constexpr scalar_type a61 = coeff(-7.3844531665375115);
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    static constexpr scalar_type a62 = coeff(-0.30593419030174646);
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    static constexpr scalar_type a63 = coeff(7.8622074209377981);
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    static constexpr scalar_type a64 = coeff(0.57817993590145966);
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    static constexpr scalar_type a65 = coeff(0.25);
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    static constexpr scalar_type b1 = coeff(0);
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    static constexpr scalar_type b2 = a21;
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    static constexpr scalar_type b3 = a31 + a32;
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    static constexpr scalar_type b4 = a41 + a42 + a43;
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    static constexpr scalar_type b5 = a51 + a52 + a53 + a54;
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    static constexpr scalar_type b6 = a61 + a62 + a63 + a64 + a65;
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    static constexpr scalar_type g21 = coeff(-0.75);
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    static constexpr scalar_type g31 = coeff(-8.8644359075349941e-2);
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    static constexpr scalar_type g32 = coeff(-2.8688974257983398e-2);
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    static constexpr scalar_type g41 = coeff(-4.8470034585330284);
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    static constexpr scalar_type g42 = coeff(-0.31583244269672095);
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    static constexpr scalar_type g43 = coeff(4.9536568360123221);
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    static constexpr scalar_type g51 = coeff(-26.769456904577400);
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    static constexpr scalar_type g52 = coeff(-1.5066459128852787);
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    static constexpr scalar_type g53 = coeff(27.200131480460591);
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    static constexpr scalar_type g54 = coeff(0.82597133700208525);
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    static constexpr scalar_type g61 = coeff(6.5876206496361416);
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    static constexpr scalar_type g62 = coeff(0.36807059172993878);
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    static constexpr scalar_type g63 = coeff(-6.7423520694658121);
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    static constexpr scalar_type g64 = coeff(-0.10619631475741095);
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    static constexpr scalar_type g65 = coeff(-0.35714285714285715);
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    static constexpr scalar_type g = coeff(0.25);
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    static constexpr scalar_type g1 = g;
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    static constexpr scalar_type g2 = g21 + g;
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    static constexpr scalar_type g3 = g31 + g32 + g;
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    static constexpr scalar_type g4 = g41 + g42 + g43 + g;
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    static constexpr scalar_type g5 = g51 + g52 + g53 + g54 + g;
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    static constexpr scalar_type g6 = g61 + g62 + g63 + g64 + g65 + g;
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    static constexpr scalar_type c1 = coeff(-0.79683251690137014);
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    static constexpr scalar_type c2 = coeff(6.2136401428192344e-02);
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    static constexpr scalar_type c3 = coeff(1.1198553514719862);
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    static constexpr scalar_type c4 = coeff(0.47198362114404874);
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    static constexpr scalar_type c5 = coeff(-0.10714285714285714);
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    static constexpr scalar_type c6 = coeff(0.25);
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    static constexpr scalar_type cw1 = coeff(-7.3844531665375115);
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    static constexpr scalar_type cw2 = coeff(-0.30593419030174646);
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    static constexpr scalar_type cw3 = coeff(7.8622074209377981);
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    static constexpr scalar_type cw4 = coeff(0.57817993590145966);
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    static constexpr scalar_type cw5 = coeff(0.25);
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    static constexpr scalar_type ce1 = c1 - cw1;
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    static constexpr scalar_type ce2 = c2 - cw2;
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    static constexpr scalar_type ce3 = c3 - cw3;
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    static constexpr scalar_type ce4 = c4 - cw4;
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    static constexpr scalar_type ce5 = c5 - cw5;
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    static constexpr scalar_type ce6 = c6;
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    ///@}
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    /*!
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     * \brief Constructor.
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     *
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     * \param[in] problem Problem.
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     */
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    explicit rodaspr_formula(const problem_type& problem)
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        : base_type(problem, g) {}
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        : base_type(problem, g) {}
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        : base_type(problem, g) {}
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        : base_type(problem, g) {}
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        : base_type(problem, g) {}
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        : base_type(problem, g) {}
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        : base_type(problem, g) {}
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        : base_type(problem, g) {}
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    //! \copydoc ode::formula_base::step
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    void step(scalar_type time, scalar_type step_size,
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        const variable_type& current, variable_type& estimate) {
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        variable_type unused;
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        step_embedded(time, step_size, current, estimate, unused);
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    }
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    /*!
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     * \brief Compute the next variable and weak estimate of it with embedded
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     * formula.
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     *
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     * \param[in] time Current time.
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     * \param[in] step_size Step size.
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     * \param[in] current Current variable.
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     * \param[out] estimate Estimate of the next variable.
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     * \param[out] error Estimate of error.
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     */
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    void step_embedded(scalar_type time, scalar_type step_size,
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        const variable_type& current, variable_type& estimate,
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        variable_type& error) {
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        equation_solver().evaluate_and_update_jacobian(
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            problem(), time, step_size, current);
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        // 1st stage
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        temp_rhs_ = problem().diff_coeff();
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        equation_solver().add_time_derivative_term(step_size, g1, temp_rhs_);
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        equation_solver().solve(temp_rhs_, k1_);
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        // 2nd stage
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        temp_var_ = g21 * k1_;
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        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
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        temp_rhs_ *= step_size;
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        temp_var_ = current + step_size * (a21 * k1_);
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        problem().evaluate_on(time + b2 * step_size, temp_var_,
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            evaluation_type{.diff_coeff = true});
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        temp_rhs_ += problem().diff_coeff();
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        equation_solver().add_time_derivative_term(step_size, g2, temp_rhs_);
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        equation_solver().solve(temp_rhs_, k2_);
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        // 3rd stage
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        temp_var_ = g31 * k1_ + g32 * k2_;
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        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
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        temp_rhs_ *= step_size;
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        temp_var_ = current + step_size * (a31 * k1_ + a32 * k2_);
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        problem().evaluate_on(time + b3 * step_size, temp_var_,
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            evaluation_type{.diff_coeff = true});
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        temp_rhs_ += problem().diff_coeff();
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        equation_solver().add_time_derivative_term(step_size, g3, temp_rhs_);
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        equation_solver().solve(temp_rhs_, k3_);
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        // 4th stage
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        temp_var_ = g41 * k1_ + g42 * k2_ + g43 * k3_;
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        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
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        temp_rhs_ *= step_size;
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        temp_var_ = current + step_size * (a41 * k1_ + a42 * k2_ + a43 * k3_);
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        problem().evaluate_on(time + b4 * step_size, temp_var_,
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            evaluation_type{.diff_coeff = true});
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        temp_rhs_ += problem().diff_coeff();
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        equation_solver().add_time_derivative_term(step_size, g4, temp_rhs_);
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        equation_solver().solve(temp_rhs_, k4_);
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        // 5th stage
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        temp_var_ = g51 * k1_ + g52 * k2_ + g53 * k3_ + g54 * k4_;
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        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
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        temp_rhs_ *= step_size;
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        temp_var_ = current +
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            step_size * (a51 * k1_ + a52 * k2_ + a53 * k3_ + a54 * k4_);
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        problem().evaluate_on(time + b5 * step_size, temp_var_,
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            evaluation_type{.diff_coeff = true});
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        temp_rhs_ += problem().diff_coeff();
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        equation_solver().add_time_derivative_term(step_size, g5, temp_rhs_);
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        equation_solver().solve(temp_rhs_, k5_);
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        // 6th stage
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        temp_var_ = g61 * k1_ + g62 * k2_ + g63 * k3_ + g64 * k4_ + g65 * k5_;
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        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
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        temp_rhs_ *= step_size;
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        temp_var_ = current +
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            step_size *
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                (a61 * k1_ + a62 * k2_ + a63 * k3_ + a64 * k4_ + a65 * k5_);
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        problem().evaluate_on(time + b6 * step_size, temp_var_,
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            evaluation_type{.diff_coeff = true});
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        temp_rhs_ += problem().diff_coeff();
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        equation_solver().add_time_derivative_term(step_size, g6, temp_rhs_);
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        equation_solver().solve(temp_rhs_, k6_);
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        estimate = current +
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            step_size *
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                (c1 * k1_ + c2 * k2_ + c3 * k3_ + c4 * k4_ + c5 * k5_ +
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                    c6 * k6_);
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        error = step_size *
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            (ce1 * k1_ + ce2 * k2_ + ce3 * k3_ + ce4 * k4_ + ce5 * k5_ +
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                ce6 * k6_);
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    }
_ZN11num_collect3ode10rosenbrock15rodaspr_formulaIN16num_prob_collect3ode33changing_mass_exponential_problemENS1_33scalar_rosenbrock_equation_solverIS5_EEE13step_embeddedEddRKdRdSB_
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        variable_type& error) {
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        equation_solver().evaluate_and_update_jacobian(
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            problem(), time, step_size, current);
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        // 1st stage
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        temp_rhs_ = problem().diff_coeff();
196
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        equation_solver().add_time_derivative_term(step_size, g1, temp_rhs_);
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        equation_solver().solve(temp_rhs_, k1_);
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        // 2nd stage
200
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        temp_var_ = g21 * k1_;
201
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        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
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        temp_rhs_ *= step_size;
203
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        temp_var_ = current + step_size * (a21 * k1_);
204
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        problem().evaluate_on(time + b2 * step_size, temp_var_,
205
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            evaluation_type{.diff_coeff = true});
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        temp_rhs_ += problem().diff_coeff();
207
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        equation_solver().add_time_derivative_term(step_size, g2, temp_rhs_);
208
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        equation_solver().solve(temp_rhs_, k2_);
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        // 3rd stage
211
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        temp_var_ = g31 * k1_ + g32 * k2_;
212
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        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
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        temp_rhs_ *= step_size;
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        temp_var_ = current + step_size * (a31 * k1_ + a32 * k2_);
215
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        problem().evaluate_on(time + b3 * step_size, temp_var_,
216
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            evaluation_type{.diff_coeff = true});
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        temp_rhs_ += problem().diff_coeff();
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        equation_solver().add_time_derivative_term(step_size, g3, temp_rhs_);
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        equation_solver().solve(temp_rhs_, k3_);
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        // 4th stage
222
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        temp_var_ = g41 * k1_ + g42 * k2_ + g43 * k3_;
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        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
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        temp_rhs_ *= step_size;
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        temp_var_ = current + step_size * (a41 * k1_ + a42 * k2_ + a43 * k3_);
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        problem().evaluate_on(time + b4 * step_size, temp_var_,
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            evaluation_type{.diff_coeff = true});
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        temp_rhs_ += problem().diff_coeff();
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        equation_solver().add_time_derivative_term(step_size, g4, temp_rhs_);
230
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        equation_solver().solve(temp_rhs_, k4_);
231
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        // 5th stage
233
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        temp_var_ = g51 * k1_ + g52 * k2_ + g53 * k3_ + g54 * k4_;
234
243
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
235
243
        temp_rhs_ *= step_size;
236
243
        temp_var_ = current +
237
243
            step_size * (a51 * k1_ + a52 * k2_ + a53 * k3_ + a54 * k4_);
238
243
        problem().evaluate_on(time + b5 * step_size, temp_var_,
239
243
            evaluation_type{.diff_coeff = true});
240
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        temp_rhs_ += problem().diff_coeff();
241
243
        equation_solver().add_time_derivative_term(step_size, g5, temp_rhs_);
242
243
        equation_solver().solve(temp_rhs_, k5_);
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244
        // 6th stage
245
243
        temp_var_ = g61 * k1_ + g62 * k2_ + g63 * k3_ + g64 * k4_ + g65 * k5_;
246
243
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
247
243
        temp_rhs_ *= step_size;
248
243
        temp_var_ = current +
249
243
            step_size *
250
243
                (a61 * k1_ + a62 * k2_ + a63 * k3_ + a64 * k4_ + a65 * k5_);
251
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        problem().evaluate_on(time + b6 * step_size, temp_var_,
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            evaluation_type{.diff_coeff = true});
253
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        temp_rhs_ += problem().diff_coeff();
254
243
        equation_solver().add_time_derivative_term(step_size, g6, temp_rhs_);
255
243
        equation_solver().solve(temp_rhs_, k6_);
256
257
243
        estimate = current +
258
243
            step_size *
259
243
                (c1 * k1_ + c2 * k2_ + c3 * k3_ + c4 * k4_ + c5 * k5_ +
260
243
                    c6 * k6_);
261
243
        error = step_size *
262
243
            (ce1 * k1_ + ce2 * k2_ + ce3 * k3_ + ce4 * k4_ + ce5 * k5_ +
263
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                ce6 * k6_);
264
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    }
_ZN11num_collect3ode10rosenbrock15rodaspr_formulaIN16num_prob_collect3ode19exponential_problemENS1_33scalar_rosenbrock_equation_solverIS5_EEE13step_embeddedEddRKdRdSB_
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        variable_type& error) {
191
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        equation_solver().evaluate_and_update_jacobian(
192
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            problem(), time, step_size, current);
193
194
        // 1st stage
195
57
        temp_rhs_ = problem().diff_coeff();
196
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        equation_solver().add_time_derivative_term(step_size, g1, temp_rhs_);
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        equation_solver().solve(temp_rhs_, k1_);
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        // 2nd stage
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        temp_var_ = g21 * k1_;
201
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        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
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        temp_rhs_ *= step_size;
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        temp_var_ = current + step_size * (a21 * k1_);
204
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        problem().evaluate_on(time + b2 * step_size, temp_var_,
205
57
            evaluation_type{.diff_coeff = true});
206
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        temp_rhs_ += problem().diff_coeff();
207
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        equation_solver().add_time_derivative_term(step_size, g2, temp_rhs_);
208
57
        equation_solver().solve(temp_rhs_, k2_);
209
210
        // 3rd stage
211
57
        temp_var_ = g31 * k1_ + g32 * k2_;
212
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        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
213
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        temp_rhs_ *= step_size;
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        temp_var_ = current + step_size * (a31 * k1_ + a32 * k2_);
215
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        problem().evaluate_on(time + b3 * step_size, temp_var_,
216
57
            evaluation_type{.diff_coeff = true});
217
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        temp_rhs_ += problem().diff_coeff();
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        equation_solver().add_time_derivative_term(step_size, g3, temp_rhs_);
219
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        equation_solver().solve(temp_rhs_, k3_);
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221
        // 4th stage
222
57
        temp_var_ = g41 * k1_ + g42 * k2_ + g43 * k3_;
223
57
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
224
57
        temp_rhs_ *= step_size;
225
57
        temp_var_ = current + step_size * (a41 * k1_ + a42 * k2_ + a43 * k3_);
226
57
        problem().evaluate_on(time + b4 * step_size, temp_var_,
227
57
            evaluation_type{.diff_coeff = true});
228
57
        temp_rhs_ += problem().diff_coeff();
229
57
        equation_solver().add_time_derivative_term(step_size, g4, temp_rhs_);
230
57
        equation_solver().solve(temp_rhs_, k4_);
231
232
        // 5th stage
233
57
        temp_var_ = g51 * k1_ + g52 * k2_ + g53 * k3_ + g54 * k4_;
234
57
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
235
57
        temp_rhs_ *= step_size;
236
57
        temp_var_ = current +
237
57
            step_size * (a51 * k1_ + a52 * k2_ + a53 * k3_ + a54 * k4_);
238
57
        problem().evaluate_on(time + b5 * step_size, temp_var_,
239
57
            evaluation_type{.diff_coeff = true});
240
57
        temp_rhs_ += problem().diff_coeff();
241
57
        equation_solver().add_time_derivative_term(step_size, g5, temp_rhs_);
242
57
        equation_solver().solve(temp_rhs_, k5_);
243
244
        // 6th stage
245
57
        temp_var_ = g61 * k1_ + g62 * k2_ + g63 * k3_ + g64 * k4_ + g65 * k5_;
246
57
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
247
57
        temp_rhs_ *= step_size;
248
57
        temp_var_ = current +
249
57
            step_size *
250
57
                (a61 * k1_ + a62 * k2_ + a63 * k3_ + a64 * k4_ + a65 * k5_);
251
57
        problem().evaluate_on(time + b6 * step_size, temp_var_,
252
57
            evaluation_type{.diff_coeff = true});
253
57
        temp_rhs_ += problem().diff_coeff();
254
57
        equation_solver().add_time_derivative_term(step_size, g6, temp_rhs_);
255
57
        equation_solver().solve(temp_rhs_, k6_);
256
257
57
        estimate = current +
258
57
            step_size *
259
57
                (c1 * k1_ + c2 * k2_ + c3 * k3_ + c4 * k4_ + c5 * k5_ +
260
57
                    c6 * k6_);
261
57
        error = step_size *
262
57
            (ce1 * k1_ + ce2 * k2_ + ce3 * k3_ + ce4 * k4_ + ce5 * k5_ +
263
57
                ce6 * k6_);
264
57
    }
_ZN11num_collect3ode10rosenbrock15rodaspr_formulaIN16num_prob_collect3ode32external_force_vibration_problemENS1_29lu_rosenbrock_equation_solverIS5_EEE13step_embeddedEddRKN5Eigen6MatrixIdLi2ELi1ELi0ELi2ELi1EEERSB_SE_
Line
Count
Source
190
46
        variable_type& error) {
191
46
        equation_solver().evaluate_and_update_jacobian(
192
46
            problem(), time, step_size, current);
193
194
        // 1st stage
195
46
        temp_rhs_ = problem().diff_coeff();
196
46
        equation_solver().add_time_derivative_term(step_size, g1, temp_rhs_);
197
46
        equation_solver().solve(temp_rhs_, k1_);
198
199
        // 2nd stage
200
46
        temp_var_ = g21 * k1_;
201
46
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
202
46
        temp_rhs_ *= step_size;
203
46
        temp_var_ = current + step_size * (a21 * k1_);
204
46
        problem().evaluate_on(time + b2 * step_size, temp_var_,
205
46
            evaluation_type{.diff_coeff = true});
206
46
        temp_rhs_ += problem().diff_coeff();
207
46
        equation_solver().add_time_derivative_term(step_size, g2, temp_rhs_);
208
46
        equation_solver().solve(temp_rhs_, k2_);
209
210
        // 3rd stage
211
46
        temp_var_ = g31 * k1_ + g32 * k2_;
212
46
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
213
46
        temp_rhs_ *= step_size;
214
46
        temp_var_ = current + step_size * (a31 * k1_ + a32 * k2_);
215
46
        problem().evaluate_on(time + b3 * step_size, temp_var_,
216
46
            evaluation_type{.diff_coeff = true});
217
46
        temp_rhs_ += problem().diff_coeff();
218
46
        equation_solver().add_time_derivative_term(step_size, g3, temp_rhs_);
219
46
        equation_solver().solve(temp_rhs_, k3_);
220
221
        // 4th stage
222
46
        temp_var_ = g41 * k1_ + g42 * k2_ + g43 * k3_;
223
46
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
224
46
        temp_rhs_ *= step_size;
225
46
        temp_var_ = current + step_size * (a41 * k1_ + a42 * k2_ + a43 * k3_);
226
46
        problem().evaluate_on(time + b4 * step_size, temp_var_,
227
46
            evaluation_type{.diff_coeff = true});
228
46
        temp_rhs_ += problem().diff_coeff();
229
46
        equation_solver().add_time_derivative_term(step_size, g4, temp_rhs_);
230
46
        equation_solver().solve(temp_rhs_, k4_);
231
232
        // 5th stage
233
46
        temp_var_ = g51 * k1_ + g52 * k2_ + g53 * k3_ + g54 * k4_;
234
46
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
235
46
        temp_rhs_ *= step_size;
236
46
        temp_var_ = current +
237
46
            step_size * (a51 * k1_ + a52 * k2_ + a53 * k3_ + a54 * k4_);
238
46
        problem().evaluate_on(time + b5 * step_size, temp_var_,
239
46
            evaluation_type{.diff_coeff = true});
240
46
        temp_rhs_ += problem().diff_coeff();
241
46
        equation_solver().add_time_derivative_term(step_size, g5, temp_rhs_);
242
46
        equation_solver().solve(temp_rhs_, k5_);
243
244
        // 6th stage
245
46
        temp_var_ = g61 * k1_ + g62 * k2_ + g63 * k3_ + g64 * k4_ + g65 * k5_;
246
46
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
247
46
        temp_rhs_ *= step_size;
248
46
        temp_var_ = current +
249
46
            step_size *
250
46
                (a61 * k1_ + a62 * k2_ + a63 * k3_ + a64 * k4_ + a65 * k5_);
251
46
        problem().evaluate_on(time + b6 * step_size, temp_var_,
252
46
            evaluation_type{.diff_coeff = true});
253
46
        temp_rhs_ += problem().diff_coeff();
254
46
        equation_solver().add_time_derivative_term(step_size, g6, temp_rhs_);
255
46
        equation_solver().solve(temp_rhs_, k6_);
256
257
46
        estimate = current +
258
46
            step_size *
259
46
                (c1 * k1_ + c2 * k2_ + c3 * k3_ + c4 * k4_ + c5 * k5_ +
260
46
                    c6 * k6_);
261
46
        error = step_size *
262
46
            (ce1 * k1_ + ce2 * k2_ + ce3 * k3_ + ce4 * k4_ + ce5 * k5_ +
263
46
                ce6 * k6_);
264
46
    }
_ZN11num_collect3ode10rosenbrock15rodaspr_formulaIN16num_prob_collect3ode28implicit_exponential_problemENS1_33scalar_rosenbrock_equation_solverIS5_EEE13step_embeddedEddRKdRdSB_
Line
Count
Source
190
46
        variable_type& error) {
191
46
        equation_solver().evaluate_and_update_jacobian(
192
46
            problem(), time, step_size, current);
193
194
        // 1st stage
195
46
        temp_rhs_ = problem().diff_coeff();
196
46
        equation_solver().add_time_derivative_term(step_size, g1, temp_rhs_);
197
46
        equation_solver().solve(temp_rhs_, k1_);
198
199
        // 2nd stage
200
46
        temp_var_ = g21 * k1_;
201
46
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
202
46
        temp_rhs_ *= step_size;
203
46
        temp_var_ = current + step_size * (a21 * k1_);
204
46
        problem().evaluate_on(time + b2 * step_size, temp_var_,
205
46
            evaluation_type{.diff_coeff = true});
206
46
        temp_rhs_ += problem().diff_coeff();
207
46
        equation_solver().add_time_derivative_term(step_size, g2, temp_rhs_);
208
46
        equation_solver().solve(temp_rhs_, k2_);
209
210
        // 3rd stage
211
46
        temp_var_ = g31 * k1_ + g32 * k2_;
212
46
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
213
46
        temp_rhs_ *= step_size;
214
46
        temp_var_ = current + step_size * (a31 * k1_ + a32 * k2_);
215
46
        problem().evaluate_on(time + b3 * step_size, temp_var_,
216
46
            evaluation_type{.diff_coeff = true});
217
46
        temp_rhs_ += problem().diff_coeff();
218
46
        equation_solver().add_time_derivative_term(step_size, g3, temp_rhs_);
219
46
        equation_solver().solve(temp_rhs_, k3_);
220
221
        // 4th stage
222
46
        temp_var_ = g41 * k1_ + g42 * k2_ + g43 * k3_;
223
46
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
224
46
        temp_rhs_ *= step_size;
225
46
        temp_var_ = current + step_size * (a41 * k1_ + a42 * k2_ + a43 * k3_);
226
46
        problem().evaluate_on(time + b4 * step_size, temp_var_,
227
46
            evaluation_type{.diff_coeff = true});
228
46
        temp_rhs_ += problem().diff_coeff();
229
46
        equation_solver().add_time_derivative_term(step_size, g4, temp_rhs_);
230
46
        equation_solver().solve(temp_rhs_, k4_);
231
232
        // 5th stage
233
46
        temp_var_ = g51 * k1_ + g52 * k2_ + g53 * k3_ + g54 * k4_;
234
46
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
235
46
        temp_rhs_ *= step_size;
236
46
        temp_var_ = current +
237
46
            step_size * (a51 * k1_ + a52 * k2_ + a53 * k3_ + a54 * k4_);
238
46
        problem().evaluate_on(time + b5 * step_size, temp_var_,
239
46
            evaluation_type{.diff_coeff = true});
240
46
        temp_rhs_ += problem().diff_coeff();
241
46
        equation_solver().add_time_derivative_term(step_size, g5, temp_rhs_);
242
46
        equation_solver().solve(temp_rhs_, k5_);
243
244
        // 6th stage
245
46
        temp_var_ = g61 * k1_ + g62 * k2_ + g63 * k3_ + g64 * k4_ + g65 * k5_;
246
46
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
247
46
        temp_rhs_ *= step_size;
248
46
        temp_var_ = current +
249
46
            step_size *
250
46
                (a61 * k1_ + a62 * k2_ + a63 * k3_ + a64 * k4_ + a65 * k5_);
251
46
        problem().evaluate_on(time + b6 * step_size, temp_var_,
252
46
            evaluation_type{.diff_coeff = true});
253
46
        temp_rhs_ += problem().diff_coeff();
254
46
        equation_solver().add_time_derivative_term(step_size, g6, temp_rhs_);
255
46
        equation_solver().solve(temp_rhs_, k6_);
256
257
46
        estimate = current +
258
46
            step_size *
259
46
                (c1 * k1_ + c2 * k2_ + c3 * k3_ + c4 * k4_ + c5 * k5_ +
260
46
                    c6 * k6_);
261
46
        error = step_size *
262
46
            (ce1 * k1_ + ce2 * k2_ + ce3 * k3_ + ce4 * k4_ + ce5 * k5_ +
263
46
                ce6 * k6_);
264
46
    }
_ZN11num_collect3ode10rosenbrock15rodaspr_formulaIN16num_prob_collect3ode21implicit_kaps_problemENS1_29lu_rosenbrock_equation_solverIS5_EEE13step_embeddedEddRKN5Eigen6MatrixIdLi2ELi1ELi0ELi2ELi1EEERSB_SE_
Line
Count
Source
190
100
        variable_type& error) {
191
100
        equation_solver().evaluate_and_update_jacobian(
192
100
            problem(), time, step_size, current);
193
194
        // 1st stage
195
100
        temp_rhs_ = problem().diff_coeff();
196
100
        equation_solver().add_time_derivative_term(step_size, g1, temp_rhs_);
197
100
        equation_solver().solve(temp_rhs_, k1_);
198
199
        // 2nd stage
200
100
        temp_var_ = g21 * k1_;
201
100
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
202
100
        temp_rhs_ *= step_size;
203
100
        temp_var_ = current + step_size * (a21 * k1_);
204
100
        problem().evaluate_on(time + b2 * step_size, temp_var_,
205
100
            evaluation_type{.diff_coeff = true});
206
100
        temp_rhs_ += problem().diff_coeff();
207
100
        equation_solver().add_time_derivative_term(step_size, g2, temp_rhs_);
208
100
        equation_solver().solve(temp_rhs_, k2_);
209
210
        // 3rd stage
211
100
        temp_var_ = g31 * k1_ + g32 * k2_;
212
100
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
213
100
        temp_rhs_ *= step_size;
214
100
        temp_var_ = current + step_size * (a31 * k1_ + a32 * k2_);
215
100
        problem().evaluate_on(time + b3 * step_size, temp_var_,
216
100
            evaluation_type{.diff_coeff = true});
217
100
        temp_rhs_ += problem().diff_coeff();
218
100
        equation_solver().add_time_derivative_term(step_size, g3, temp_rhs_);
219
100
        equation_solver().solve(temp_rhs_, k3_);
220
221
        // 4th stage
222
100
        temp_var_ = g41 * k1_ + g42 * k2_ + g43 * k3_;
223
100
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
224
100
        temp_rhs_ *= step_size;
225
100
        temp_var_ = current + step_size * (a41 * k1_ + a42 * k2_ + a43 * k3_);
226
100
        problem().evaluate_on(time + b4 * step_size, temp_var_,
227
100
            evaluation_type{.diff_coeff = true});
228
100
        temp_rhs_ += problem().diff_coeff();
229
100
        equation_solver().add_time_derivative_term(step_size, g4, temp_rhs_);
230
100
        equation_solver().solve(temp_rhs_, k4_);
231
232
        // 5th stage
233
100
        temp_var_ = g51 * k1_ + g52 * k2_ + g53 * k3_ + g54 * k4_;
234
100
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
235
100
        temp_rhs_ *= step_size;
236
100
        temp_var_ = current +
237
100
            step_size * (a51 * k1_ + a52 * k2_ + a53 * k3_ + a54 * k4_);
238
100
        problem().evaluate_on(time + b5 * step_size, temp_var_,
239
100
            evaluation_type{.diff_coeff = true});
240
100
        temp_rhs_ += problem().diff_coeff();
241
100
        equation_solver().add_time_derivative_term(step_size, g5, temp_rhs_);
242
100
        equation_solver().solve(temp_rhs_, k5_);
243
244
        // 6th stage
245
100
        temp_var_ = g61 * k1_ + g62 * k2_ + g63 * k3_ + g64 * k4_ + g65 * k5_;
246
100
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
247
100
        temp_rhs_ *= step_size;
248
100
        temp_var_ = current +
249
100
            step_size *
250
100
                (a61 * k1_ + a62 * k2_ + a63 * k3_ + a64 * k4_ + a65 * k5_);
251
100
        problem().evaluate_on(time + b6 * step_size, temp_var_,
252
100
            evaluation_type{.diff_coeff = true});
253
100
        temp_rhs_ += problem().diff_coeff();
254
100
        equation_solver().add_time_derivative_term(step_size, g6, temp_rhs_);
255
100
        equation_solver().solve(temp_rhs_, k6_);
256
257
100
        estimate = current +
258
100
            step_size *
259
100
                (c1 * k1_ + c2 * k2_ + c3 * k3_ + c4 * k4_ + c5 * k5_ +
260
100
                    c6 * k6_);
261
100
        error = step_size *
262
100
            (ce1 * k1_ + ce2 * k2_ + ce3 * k3_ + ce4 * k4_ + ce5 * k5_ +
263
100
                ce6 * k6_);
264
100
    }
_ZN11num_collect3ode10rosenbrock15rodaspr_formulaIN16num_prob_collect3ode33no_jacobian_implicit_kaps_problemENS1_35bicgstab_rosenbrock_equation_solverIS5_EEE13step_embeddedEddRKN5Eigen6MatrixIdLi2ELi1ELi0ELi2ELi1EEERSB_SE_
Line
Count
Source
190
100
        variable_type& error) {
191
100
        equation_solver().evaluate_and_update_jacobian(
192
100
            problem(), time, step_size, current);
193
194
        // 1st stage
195
100
        temp_rhs_ = problem().diff_coeff();
196
100
        equation_solver().add_time_derivative_term(step_size, g1, temp_rhs_);
197
100
        equation_solver().solve(temp_rhs_, k1_);
198
199
        // 2nd stage
200
100
        temp_var_ = g21 * k1_;
201
100
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
202
100
        temp_rhs_ *= step_size;
203
100
        temp_var_ = current + step_size * (a21 * k1_);
204
100
        problem().evaluate_on(time + b2 * step_size, temp_var_,
205
100
            evaluation_type{.diff_coeff = true});
206
100
        temp_rhs_ += problem().diff_coeff();
207
100
        equation_solver().add_time_derivative_term(step_size, g2, temp_rhs_);
208
100
        equation_solver().solve(temp_rhs_, k2_);
209
210
        // 3rd stage
211
100
        temp_var_ = g31 * k1_ + g32 * k2_;
212
100
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
213
100
        temp_rhs_ *= step_size;
214
100
        temp_var_ = current + step_size * (a31 * k1_ + a32 * k2_);
215
100
        problem().evaluate_on(time + b3 * step_size, temp_var_,
216
100
            evaluation_type{.diff_coeff = true});
217
100
        temp_rhs_ += problem().diff_coeff();
218
100
        equation_solver().add_time_derivative_term(step_size, g3, temp_rhs_);
219
100
        equation_solver().solve(temp_rhs_, k3_);
220
221
        // 4th stage
222
100
        temp_var_ = g41 * k1_ + g42 * k2_ + g43 * k3_;
223
100
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
224
100
        temp_rhs_ *= step_size;
225
100
        temp_var_ = current + step_size * (a41 * k1_ + a42 * k2_ + a43 * k3_);
226
100
        problem().evaluate_on(time + b4 * step_size, temp_var_,
227
100
            evaluation_type{.diff_coeff = true});
228
100
        temp_rhs_ += problem().diff_coeff();
229
100
        equation_solver().add_time_derivative_term(step_size, g4, temp_rhs_);
230
100
        equation_solver().solve(temp_rhs_, k4_);
231
232
        // 5th stage
233
100
        temp_var_ = g51 * k1_ + g52 * k2_ + g53 * k3_ + g54 * k4_;
234
100
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
235
100
        temp_rhs_ *= step_size;
236
100
        temp_var_ = current +
237
100
            step_size * (a51 * k1_ + a52 * k2_ + a53 * k3_ + a54 * k4_);
238
100
        problem().evaluate_on(time + b5 * step_size, temp_var_,
239
100
            evaluation_type{.diff_coeff = true});
240
100
        temp_rhs_ += problem().diff_coeff();
241
100
        equation_solver().add_time_derivative_term(step_size, g5, temp_rhs_);
242
100
        equation_solver().solve(temp_rhs_, k5_);
243
244
        // 6th stage
245
100
        temp_var_ = g61 * k1_ + g62 * k2_ + g63 * k3_ + g64 * k4_ + g65 * k5_;
246
100
        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
247
100
        temp_rhs_ *= step_size;
248
100
        temp_var_ = current +
249
100
            step_size *
250
100
                (a61 * k1_ + a62 * k2_ + a63 * k3_ + a64 * k4_ + a65 * k5_);
251
100
        problem().evaluate_on(time + b6 * step_size, temp_var_,
252
100
            evaluation_type{.diff_coeff = true});
253
100
        temp_rhs_ += problem().diff_coeff();
254
100
        equation_solver().add_time_derivative_term(step_size, g6, temp_rhs_);
255
100
        equation_solver().solve(temp_rhs_, k6_);
256
257
100
        estimate = current +
258
100
            step_size *
259
100
                (c1 * k1_ + c2 * k2_ + c3 * k3_ + c4 * k4_ + c5 * k5_ +
260
100
                    c6 * k6_);
261
100
        error = step_size *
262
100
            (ce1 * k1_ + ce2 * k2_ + ce3 * k3_ + ce4 * k4_ + ce5 * k5_ +
263
100
                ce6 * k6_);
264
100
    }
_ZN11num_collect3ode10rosenbrock15rodaspr_formulaIN16num_prob_collect3ode23spring_movement_problemENS1_29lu_rosenbrock_equation_solverIS5_EEE13step_embeddedEddRKN5Eigen6MatrixIdLi2ELi1ELi0ELi2ELi1EEERSB_SE_
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        variable_type& error) {
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        equation_solver().evaluate_and_update_jacobian(
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            problem(), time, step_size, current);
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        // 1st stage
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        temp_rhs_ = problem().diff_coeff();
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        equation_solver().add_time_derivative_term(step_size, g1, temp_rhs_);
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        equation_solver().solve(temp_rhs_, k1_);
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        // 2nd stage
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        temp_var_ = g21 * k1_;
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        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
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        temp_rhs_ *= step_size;
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        temp_var_ = current + step_size * (a21 * k1_);
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        problem().evaluate_on(time + b2 * step_size, temp_var_,
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            evaluation_type{.diff_coeff = true});
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        temp_rhs_ += problem().diff_coeff();
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        equation_solver().add_time_derivative_term(step_size, g2, temp_rhs_);
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        equation_solver().solve(temp_rhs_, k2_);
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        // 3rd stage
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        temp_var_ = g31 * k1_ + g32 * k2_;
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        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
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        temp_rhs_ *= step_size;
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        temp_var_ = current + step_size * (a31 * k1_ + a32 * k2_);
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        problem().evaluate_on(time + b3 * step_size, temp_var_,
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            evaluation_type{.diff_coeff = true});
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        temp_rhs_ += problem().diff_coeff();
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        equation_solver().add_time_derivative_term(step_size, g3, temp_rhs_);
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        equation_solver().solve(temp_rhs_, k3_);
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        // 4th stage
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        temp_var_ = g41 * k1_ + g42 * k2_ + g43 * k3_;
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        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
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        temp_rhs_ *= step_size;
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        temp_var_ = current + step_size * (a41 * k1_ + a42 * k2_ + a43 * k3_);
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        problem().evaluate_on(time + b4 * step_size, temp_var_,
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            evaluation_type{.diff_coeff = true});
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        temp_rhs_ += problem().diff_coeff();
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        equation_solver().add_time_derivative_term(step_size, g4, temp_rhs_);
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        equation_solver().solve(temp_rhs_, k4_);
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        // 5th stage
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        temp_var_ = g51 * k1_ + g52 * k2_ + g53 * k3_ + g54 * k4_;
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        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
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        temp_rhs_ *= step_size;
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        temp_var_ = current +
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            step_size * (a51 * k1_ + a52 * k2_ + a53 * k3_ + a54 * k4_);
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        problem().evaluate_on(time + b5 * step_size, temp_var_,
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            evaluation_type{.diff_coeff = true});
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        temp_rhs_ += problem().diff_coeff();
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        equation_solver().add_time_derivative_term(step_size, g5, temp_rhs_);
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        equation_solver().solve(temp_rhs_, k5_);
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        // 6th stage
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        temp_var_ = g61 * k1_ + g62 * k2_ + g63 * k3_ + g64 * k4_ + g65 * k5_;
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        equation_solver().apply_jacobian(temp_var_, temp_rhs_);
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        temp_rhs_ *= step_size;
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        temp_var_ = current +
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            step_size *
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                (a61 * k1_ + a62 * k2_ + a63 * k3_ + a64 * k4_ + a65 * k5_);
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        problem().evaluate_on(time + b6 * step_size, temp_var_,
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            evaluation_type{.diff_coeff = true});
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        temp_rhs_ += problem().diff_coeff();
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        equation_solver().add_time_derivative_term(step_size, g6, temp_rhs_);
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        equation_solver().solve(temp_rhs_, k6_);
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        estimate = current +
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            step_size *
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                (c1 * k1_ + c2 * k2_ + c3 * k3_ + c4 * k4_ + c5 * k5_ +
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                    c6 * k6_);
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        error = step_size *
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            (ce1 * k1_ + ce2 * k2_ + ce3 * k3_ + ce4 * k4_ + ce5 * k5_ +
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                ce6 * k6_);
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    }
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private:
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    /*!
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     * \name Intermediate variables.
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     */
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    ///@{
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    //! Intermediate variable.
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    variable_type k1_{};
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    variable_type k2_{};
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    variable_type k3_{};
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    variable_type k4_{};
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    variable_type k5_{};
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    variable_type k6_{};
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    ///@}
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    //! Temporary variable.
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    variable_type temp_var_{};
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    //! Temporary right-hand-side vector.
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    variable_type temp_rhs_{};
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};
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/*!
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 * \brief Class of solver using RODASPR formula \cite Rang2015.
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 *
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 * \tparam Problem Type of problem.
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 */
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template <concepts::problem Problem>
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using rodaspr_solver = embedded_solver<rodaspr_formula<Problem>>;
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}  // namespace num_collect::ode::rosenbrock