/****************************************************************************
 *   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 Free Software Foundation, either version 3 of the License,      *
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 *    - the MIT license (MIT),                                              *
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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 The class for computing Log2 (Gamma(x)).
 *
 * @author Christophe GONZALES(_at_AMU) and Pierre-Henri WUILLEMIN(_at_LIP6)
 */

#include <agrum/base/core/math/gammaLog2.h>   // to ease IDE parser

namespace gum {

  ALWAYS_INLINE double GammaLog2::gammaLog2(double x) const {
    if (x <= 0) GUM_ERROR(OutOfBounds, "log2(gamma()) should be called with a positive argument")

    // if x is small, use precomputed values
    if (x < 50) {
      if (x >= 0.01) {
        if (_requires_precision_) {
          const Idx index = int(x * 100);
          return _small_values_[index]
               + (_small_values_[index + 1] - _small_values_[index]) * double(x * 100 - index);
        } else {
          const Idx index = int(x * 100 + 0.5);
          return _small_values_[index];
        }
      } else {
        // for very small values of x, Gamma(x) is approximately equal to
        // 1/x. Hence gammaLog2(x) is approximately equal to log2(1/x)
        return std::log2(1.0 / x);
      }
    }

    // returns the approximation by the stirling formula
    return (_log_sqrt_2pi_ + (x - 0.5f) * log(x) - x + log(1.0 + 1.0 / (12 * x))) * _inv_log2_;
  }

  ALWAYS_INLINE double GammaLog2::operator()(double x) const { return gammaLog2(x); }

  INLINE void GammaLog2::setPrecision(bool prec) { _requires_precision_ = prec; }

} /* namespace gum */
