RunningAverage.hpp

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/*
 * Copyright (C) 2010-2022 The ESPResSo project
 * Copyright (C) 2002,2003,2004,2005,2006,2007,2008,2009,2010
 *   Max-Planck-Institute for Polymer Research, Theory Group
 *
 * This file is part of ESPResSo.
 *
 * ESPResSo 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.
 *
 * ESPResSo 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 this program.  If not, see <http://www.gnu.org/licenses/>.
 */
 
#ifndef STATISTICS_RUNING_AVERAGE_HPP
#define STATISTICS_RUNING_AVERAGE_HPP
 
#include <algorithm>
#include <cmath>
#include <limits>
 
namespace Utils {
namespace Statistics {
 
/**
 * \brief Keep running average and variance.
 * The average should be numerically stable.
 */
template <typename Scalar> class RunningAverage {
public:
  RunningAverage()
      : m_n(0), m_old_avg(0), m_new_avg(0), m_old_var(0), m_new_var(0.0),
        m_min(std::numeric_limits<Scalar>::max()),
        m_max(-std::numeric_limits<Scalar>::max()) {}
  void add_sample(Scalar s) {
    m_n++;
 
    if (m_n == 1) {
      m_old_avg = m_new_avg = s;
    } else {
      m_new_avg = m_old_avg + (s - m_old_avg) / m_n;
      m_new_var = m_old_var + (s - m_old_avg) * (s - m_new_avg);
 
      m_old_avg = m_new_avg;
      m_old_var = m_new_var;
    }
 
    m_min = std::min(m_min, s);
    m_max = std::max(m_max, s);
  }
 
  void clear() { m_n = 0; }
 
  int n() const { return m_n; }
 
  /** Average of the samples */
  Scalar avg() const {
    if (m_n > 0)
      return m_new_avg;
 
    return 0.0;
  }
  /** Variance of the samples */
  Scalar var() const {
    if (m_n > 1)
      return m_new_var / m_n;
 
    return 0.0;
  }
 
  /** Standard deviation of the samples */
  Scalar sig() const { return std::sqrt(var()); }
 
  /** Minimum */
  Scalar min() const { return m_min; }
 
  /** Minimum */
  Scalar max() const { return m_max; }
 
private:
  int m_n;
  Scalar m_old_avg, m_new_avg;
  Scalar m_old_var, m_new_var;
  Scalar m_min, m_max;
};
} // namespace Statistics
} // namespace Utils
 
#endif