/* -*- mia-c++  -*-
 *
 * This file is part of MIA - a toolbox for medical image analysis
 * Copyright (c) Leipzig, Madrid 1999-2017 Gert Wollny
 *
 * MIA 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.
 *
 * 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 General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with MIA; if not, see <http://www.gnu.org/licenses/>.
 *
 */

#include <algorithm>
#include <stdexcept>
#include <iostream>
#include <cmath>

#include <mia/core/fullstats.hh>

NS_MIA_BEGIN
using namespace std;

void CFullStats::evaluate(Vector& tmp)
{
       const size_t n = tmp.size();

       if (n < 2)
              throw invalid_argument("CFullStats: require at least two values");

       m_mean /= n;
       m_sigma = sqrt((m_sigma - m_mean * m_mean  * n) / (n - 1));

       if (n & 1) {
              Vector::iterator i = tmp.begin() + (n - 1) / 2;
              std::nth_element(tmp.begin(), i, tmp.end());
              m_median = *i;
       } else {
              Vector::iterator i1 = tmp.begin() + n / 2 - 1;
              Vector::iterator i2 = tmp.begin() + n / 2;
              std::nth_element(tmp.begin(), i1, tmp.end());
              std::nth_element(tmp.begin(), i2, tmp.end());
              m_median = (*i1 + *i2) / 2.0;
       }
}

double CFullStats::mean()const
{
       return m_mean;
}

double CFullStats::sigma()const
{
       return m_sigma;
}

double CFullStats::median()const
{
       return m_median;
}

double CFullStats::max()const
{
       return m_max;
}

double CFullStats::min()const
{
       return m_min;
}


void CFullStats::print(std::ostream& os) const
{
       os << m_mean << " "
          << m_sigma << " "
          << m_median << " "
          << m_min << " "
          << m_max;
}


NS_MIA_END
