init_optimization.cpp

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// Copyright 2019, University of Maryland and the MANGO development team.
//
// This file is part of MANGO.
//
// MANGO 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.
//
// MANGO 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 MANGO.  If not, see
// <https://www.gnu.org/licenses/>.
 
#include <iostream>
#include <math.h>
#include <limits>
//#include <cstring>
#include <stdexcept>
#include <ctime>
#include "mango.hpp"
#include "Solver.hpp"
 
void mango::Solver::init_optimization() {
 
  // This subroutine carries out a few steps that are shared by both least_squares and conventional optimization.
 
  if (! mpi_partition->get_proc0_worker_groups()) 
    throw std::runtime_error("Error! The mango::optimize() subroutine should only be called by group leaders, not by all workers.");
 
  function_evaluations = 0;
  at_least_one_success = false;
  best_objective_function = std::numeric_limits<double>::quiet_NaN();
  best_function_evaluation = -1;
  start_time = clock();
 
  // To simplify code a bit...
  MPI_Comm mpi_comm_group_leaders = mpi_partition->get_comm_group_leaders();
 
  // Make sure that parameters used by the finite-difference gradient routine are the same for all group leaders:
  MPI_Bcast(&N_parameters, 1, MPI_INT, 0, mpi_comm_group_leaders);
  MPI_Bcast(&centered_differences, 1, MPI_C_BOOL, 0, mpi_comm_group_leaders);
  MPI_Bcast(&finite_difference_step_size, 1, MPI_DOUBLE, 0, mpi_comm_group_leaders);
  MPI_Bcast(&algorithm, 1, MPI_INT, 0, mpi_comm_group_leaders);
  // 20200127 These next 2 lines should end up in Least_squares_data::optimize()?
  //  MPI_Bcast(&N_terms, 1, MPI_INT, 0, mpi_comm_group_leaders);
  //  MPI_Bcast(&least_squares, 1, MPI_C_BOOL, 0, mpi_comm_group_leaders);
 
  if (algorithms[algorithm].requires_bound_constraints && (!bound_constraints_set)) 
    throw std::runtime_error("Error! A MANGO algorithm was chosen that requires bound constraints, but bound constraints were not set.");
 
  if (bound_constraints_set && (!algorithms[algorithm].allows_bound_constraints) && mpi_partition->get_proc0_world()) {
#define star_line "*******************************************************************************************************"
    std::cerr << star_line << std::endl;
    std::cerr << "WARNING! Bound constraints were set, but an algorithm was chosen that does not allow bound constraints." << std::endl;
    std::cerr << "Therefore, the bound constraints will be ignored for this calculation." << std::endl;
    std::cerr << star_line << std::endl;
  }
 
  if (algorithms[algorithm].uses_derivatives) {
    if (centered_differences) {
      max_function_and_gradient_evaluations = ceil(max_function_evaluations / 7.0);
    } else {
      max_function_and_gradient_evaluations = ceil(max_function_evaluations / 4.0);
    }
  } else {
    max_function_and_gradient_evaluations = max_function_evaluations;
  }
 
  set_package();
 
  if (verbose > 0) {
    std::cout << "Proc " << mpi_partition->get_rank_world() << " is entering optimize(), and thinks proc0_world=" << mpi_partition->get_proc0_world() << std::endl;
    std::cout << "max_function_evaluations = " << max_function_evaluations << 
      ", max_function_and_gradient_evaluations = " << max_function_and_gradient_evaluations << std::endl;
  }
 
  if (mpi_partition->get_proc0_world()) recorder->init();
}