/****************************************************************************
 *   This file is part of the aGrUM/pyAgrum library.                        *
 *                                                                          *
 *   Copyright (c) 2005-2026 by                                             *
 *       - Pierre-Henri WUILLEMIN(_at_LIP6)                                 *
 *       - Christophe GONZALES(_at_AMU)                                     *
 *                                                                          *
 *   The aGrUM/pyAgrum library is free software; you can redistribute it    *
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 *    - the GNU Lesser General Public License as published by               *
 *      the Free Software Foundation, either version 3 of the License,      *
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 *    - the MIT license (MIT),                                              *
 *    - or both in dual license, as here.                                   *
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 *   (see https://agrum.gitlab.io/articles/dual-licenses-lgplv3mit.html)    *
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 *   See LICENCES for more details.                                         *
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 *   SPDX-FileCopyrightText: Copyright 2005-2026                            *
 *       - Pierre-Henri WUILLEMIN(_at_LIP6)                                 *
 *       - Christophe GONZALES(_at_AMU)                                     *
 *   SPDX-License-Identifier: LGPL-3.0-or-later OR MIT                      *
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 *   Contact  : info_at_agrum_dot_org                                       *
 *   homepage : http://agrum.gitlab.io                                      *
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 *                                                                          *
 ****************************************************************************/

#pragma once

/**
 * @file
 * @brief Contains useful methods for random stuff.
 *
 * @author Vincent RENAUDINEAU and Pierre-Henri WUILLEMIN(_at_LIP6)
 */

#include <agrum/base/core/utils_random.h>   // to ease IDE parser

namespace gum {

  // return a random discrete distribution
  // @param n is the number of modalities for the distribution
  template < GUM_Numeric GUM_SCALAR >
  std::vector< GUM_SCALAR > randomDistribution(Size n) {
    if (n < 2) n = 2;

    if (n == std::numeric_limits< Size >::max()) {
      GUM_ERROR(OutOfBounds, "randomDistribution: n is too large (SIZE_MAX would overflow n+1)")
    }

    // using sort method for uniformly distributed distributions
    // https://doi.org/10.1016/0377-2217(82)90161-8
    std::vector< GUM_SCALAR > v(n + 1);
    std::vector< GUM_SCALAR > res(n);
    v[0] = (GUM_SCALAR)0.0;
    v[n] = (GUM_SCALAR)1.0;
    for (Idx i = 1; i < n; i++) {
      v[i] = (GUM_SCALAR)randomProba();
    }
    std::sort(v.begin(), v.end());

    for (Idx i = 0; i < n; i++) {
      res[i] = v[i + 1] - v[i];
    }

    return res;
  }

  template < typename GENERATOR >
  Idx randomValue(GENERATOR& generator, const Size max) {
    std::uniform_int_distribution< Idx > uni_int(0, max - 1);
    return uni_int(generator);
  }


}   // namespace gum
