NewtonStepUpdate.hpp

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// This file is part of GQCG-GQCP.
//
// Copyright (C) 2017-2020  the GQCG developers
//
// GQCG-GQCP is free software: you can redistribute it and/or modify
// it under the terms of the GNU Lesser General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// GQCG-GQCP is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
// GNU Lesser General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public License
// along with GQCG-GQCP.  If not, see <http://www.gnu.org/licenses/>.
 
#pragma once
 
 
#include "Mathematical/Algorithm/Step.hpp"
#include "Mathematical/Optimization/Minimization/MinimizationEnvironment.hpp"
#include "Mathematical/Optimization/NonLinearEquation/NewtonStepUpdate.hpp"
#include "Mathematical/Optimization/NonLinearEquation/NonLinearEquationEnvironment.hpp"
#include "Mathematical/Representation/SquareMatrix.hpp"
 
#include <type_traits>
 
 
namespace GQCP {
namespace Minimization {
 
 
template <typename _Scalar, typename _Environment>
class NewtonStepUpdate:
    public Step<_Environment> {
 
public:
    using Scalar = _Scalar;
    using Environment = _Environment;
    static_assert(std::is_same<Scalar, typename Environment::Scalar>::value, "The scalar type must match that of the environment");
    static_assert(std::is_base_of<MinimizationEnvironment<Scalar>, Environment>::value, "The environment type must derive from MinimizationEnvironment.");
 
 
public:
    /*
     *  PUBLIC OVERRIDDEN METHODS
     */
 
    std::string description() const override {
        return "Calculate a new iteration of the variables and add them to the environment.";
    }
 
 
    void execute(Environment& environment) override {
 
        // Use the non-linear equation Newton step as an implementation
        const auto& variables = environment.variables.back();
        const auto& f = environment.gradient_function;
        const auto& J = environment.hessian_function;
 
        GQCP::NonLinearEquationEnvironment<Scalar> non_linear_environment {variables, f, J};
        GQCP::NonLinearEquation::NewtonStepUpdate<Scalar, NonLinearEquationEnvironment<Scalar>>().execute(non_linear_environment);  // this adds the Newton-step updated variables to the non-linear environment
 
        const auto& new_variables = non_linear_environment.variables.back();
        environment.variables.push_back(new_variables);
    }
};
 
 
}  // namespace Minimization
}  // namespace GQCP