real_polyhedral_homotopy_continuation/reference/include/trackers/predict.hpp

// This file is part of Bertini 2.
//
// tracking/predict.hpp is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
//(at your option) any later version.
//
// tracking/predict.hpp 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 General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with tracking/predict.hpp.  If not, see <http://www.gnu.org/licenses/>.
//

// Copyright(C) 2015 - 2021 by Bertini2 Development Team
//
// See <http://www.gnu.org/licenses/> for a copy of the license,
// as well as COPYING.  Bertini2 is provided with permitted
// additional terms in the b2/licenses/ directory.

// individual authors of this file include:
// silviana amethyst, university of wisconsin eau claire

/**
\file predict.hpp

\brief Wrapper functions for calling ODE predictors for systems.
*/

#ifndef BERTINI_PREDICT_HPP
#define BERTINI_PREDICT_HPP

#include "trackers/ode_predictors.hpp"

namespace bertini {
namespace tracking {

/**
Wrapper class for calling an ODE predictor, using fixed precision

\param predictor_choice The enum class selecting the predictor to be used.
\param next_space The computed prediction.
\param sys The system being solved.
\param current_space The current space variable vector.
\param current_time The current time.
\param delta_t The size of the time step.
\param condition_number_estimate The computed estimate of the condition number
of the Jacobian. \param num_steps_since_last_condition_number_computation.
Updated in this function. \param frequency_of_CN_estimation How many steps to
take between condition number estimates. \param prec_type The operating
precision type. \param tracking_tolerance How tightly to track the path. \param
AMP_config The settings for adaptive multiple precision.

\tparam ComplexT The complex number type for evaluation.
\tparam TolT The numeric type for tolerances and state.
*/
template <typename ComplexT, typename TolT>
SuccessCode Predict(Predictor predictor_choice, Vec<ComplexT>& next_space,
                    System const& sys, Vec<ComplexT> const& current_space,
                    ComplexT const& current_time, ComplexT const& delta_t,
                    TolT& condition_number_estimate,
                    unsigned& num_steps_since_last_condition_number_computation,
                    unsigned frequency_of_CN_estimation,
                    TolT const& tracking_tolerance) {
  predict::ExplicitRKPredictor predictor(predictor_choice);

  return predictor.Predict(next_space, sys, current_space, current_time,
                           delta_t, condition_number_estimate,
                           num_steps_since_last_condition_number_computation,
                           frequency_of_CN_estimation, tracking_tolerance);
}

/**
An overload of Predict which returns (by reference) error estimate, and
estimates of the norm of \f$J\f$ and \f$J^{-1}\f$ from AMP2 paper \cite AMP2.

\see Predict
*/
template <typename ComplexT, typename TolT>
SuccessCode Predict(Predictor predictor_choice, Vec<ComplexT>& next_space,
                    TolT& size_proportion, /*\f$a\f$ from the AMP2 paper */
                    TolT& norm_J, TolT& norm_J_inverse, System const& sys,
                    Vec<ComplexT> const& current_space, ComplexT current_time,
                    ComplexT const& delta_t, TolT& condition_number_estimate,
                    unsigned& num_steps_since_last_condition_number_computation,
                    unsigned frequency_of_CN_estimation,
                    TolT const& tracking_tolerance,
                    AdaptiveMultiplePrecisionConfig const& AMP_config) {
  predict::ExplicitRKPredictor<ComplexT, TolT> predictor(predictor_choice);

  return predictor.Predict(
      next_space, size_proportion, norm_J, norm_J_inverse, sys, current_space,
      current_time, delta_t, condition_number_estimate,
      num_steps_since_last_condition_number_computation,
      frequency_of_CN_estimation, tracking_tolerance, AMP_config);
}

/**
An overload of Predict which returns (by reference) error estimate, and
estimates of the norm of \f$J\f$ and \f$J^{-1}\f$, and the size proportion
\f$a\f$ from AMP2 paper \cite AMP2.

\see Predict
*/
template <typename ComplexT, typename TolT>
SuccessCode Predict(Predictor predictor_choice, Vec<ComplexT>& next_space,
                    TolT& error_estimate,
                    TolT& size_proportion, /*\f$a\f$ from the AMP2 paper */
                    TolT& norm_J, TolT& norm_J_inverse, System const& sys,
                    Vec<ComplexT> const& current_space, ComplexT current_time,
                    ComplexT const& delta_t, TolT& condition_number_estimate,
                    unsigned& num_steps_since_last_condition_number_computation,
                    unsigned frequency_of_CN_estimation,
                    TolT const& tracking_tolerance,
                    AdaptiveMultiplePrecisionConfig const& AMP_config) {
  predict::ExplicitRKPredictor<ComplexT, TolT> predictor(predictor_choice);

  return predictor.Predict(
      next_space, error_estimate, size_proportion, norm_J, norm_J_inverse, sys,
      current_space, current_time, delta_t, condition_number_estimate,
      num_steps_since_last_condition_number_computation,
      frequency_of_CN_estimation, tracking_tolerance, AMP_config);
}

/**
Wrapper class for calling an ODE predictor, using adaptive precision, not
returning some meta-data about the step.

\param predictor_choice The enum class selecting the predictor to be used.
\param next_space The computed prediction.
\param sys The system being solved.
\param current_space The current space variable vector.
\param current_time The current time.
\param delta_t The size of the time step.
\param condition_number_estimate The computed estimate of the condition number
of the Jacobian. \param num_steps_since_last_condition_number_computation.
Updated in this function. \param frequency_of_CN_estimation How many steps to
take between condition number estimates. \param prec_type The operating
precision type. \param tracking_tolerance How tightly to track the path. \param
AMP_config The settings for adaptive multiple precision.

\tparam ComplexT The complex number type for evaluation.
\tparam TolT The complex number type for evaluation.
*/
template <typename ComplexT, typename TolT>
SuccessCode Predict(Predictor predictor_choice, Vec<ComplexT>& next_space,
                    System const& sys, Vec<ComplexT> const& current_space,
                    ComplexT current_time, ComplexT const& delta_t,
                    TolT& condition_number_estimate,
                    unsigned& num_steps_since_last_condition_number_computation,
                    unsigned frequency_of_CN_estimation,
                    TolT const& tracking_tolerance,
                    AdaptiveMultiplePrecisionConfig const& AMP_config) {
  TolT size_proportion, norm_J, norm_J_inverse;

  return Predict(predictor_choice, next_space, size_proportion, norm_J,
                 norm_J_inverse, sys, current_space, current_time, delta_t,
                 condition_number_estimate,
                 num_steps_since_last_condition_number_computation,
                 frequency_of_CN_estimation, tracking_tolerance, AMP_config);
}

}  // namespace tracking

}  // namespace bertini

#endif