/*-------------------------------------------------------------------------------------*/
/*  sgtelib - A surrogate model library for derivative-free optimization               */
/*  Version 2.0.1                                                                      */
/*                                                                                     */
/*  Copyright (C) 2012-2017  Sebastien Le Digabel - Ecole Polytechnique, Montreal      */ 
/*                           Bastien Talgorn - McGill University, Montreal             */
/*                                                                                     */
/*  Author: Bastien Talgorn                                                            */
/*  email: bastientalgorn@fastmail.com                                                 */
/*                                                                                     */
/*  This program 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.                                                                           */
/*                                                                                     */
/*  This program 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 this program. If not, see <http://www.gnu.org/licenses/>.                     */
/*                                                                                     */
/*  You can find information on sgtelib at https://github.com/bastientalgorn/sgtelib   */
/*-------------------------------------------------------------------------------------*/

#ifndef __SGTELIB_DEFINES__
#define __SGTELIB_DEFINES__

#include <iostream>
#include <iomanip>
#include <cmath>
#include <sstream>
#include <string.h>

#include <limits>
#include <limits.h>

// debug flag:
//#define SGTELIB_DEBUG
//#define ENSEMBLE_DEBUG

namespace SGTELIB {
  
  const double EPSILON = 1E-13;
  const double PI = 3.141592654;
  const double INF = std::numeric_limits<double>::max(); ///< Infinity
  const double NaN = std::numeric_limits<double>::quiet_NaN();

  const bool APPROX_CDF = true;
  // If true, then the lower bound of standard deviation is EPSILON. 
  // This allows to avoid flat EI and P functions. 

  enum scaling_t {
    SCALING_NONE ,
    SCALING_MEANSTD ,
    SCALING_BOUNDS
  };

  const scaling_t scaling_method = SCALING_MEANSTD;
  //const scaling_t scaling_method = SCALING_NONE;


  // model output type:
  enum model_output_t {
    NORMAL_OUTPUT ,
    FIXED_OUTPUT  ,
    BINARY_OUTPUT
  };

  // model output type:
  enum bbo_t {
    BBO_OBJ , // Objective
    BBO_CON , // Constraint
    BBO_DUM   // Dummy
  };

  enum param_domain_t {
    PARAM_DOMAIN_CONTINUOUS,
    PARAM_DOMAIN_INTEGER,
    PARAM_DOMAIN_BOOL,
    PARAM_DOMAIN_CAT,
    PARAM_DOMAIN_MISC
  };

  // FIXED => Parameter is set once and for all
  // OPTIM => Parameter is optimized so as to minimize a metric
  // MODEL_DEFINED => The surrogate model is able to define/chose the parameter
  enum param_status_t {
    STATUS_FIXED,
    STATUS_OPTIM,
    STATUS_MODEL_DEFINED
  };
    


}

#endif
