mcslibrecollectstats.cpp

Free C++ toolkit to facilitate Monte-Carlo simulation. This is a library covered under the LGPL. "MC

/* 
   mcsLibreCollectStats.cpp - Basic system for collecting statistics on
   some random variable.

   This class is intented to be loaded into classes that define
   variables and attributes for the model and for model components.  */

/*
    MCS-libre, a library to facilite Monte-Carlo simulation.
    Copyright (C) 2002  D. E. Williams

    This library 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 2.1 of the License, or (at your option) any later version.

    This library 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 library; if not, write to the Free Software
    Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA

    The full text of the GNU Lesser General Public License is
    contained in the files COPYING and LICENSE.

    See the 'MCS-libre-HOWTO' in the 'doc' directory for author's
    contact information.  

    Have a nice day!  */

#include <cmath>

#include "mcsLibreCollectStats.h"

void mcsLibreCollectStats::add_value(double newvalue)
{
  number_samples++;
  if (number_samples == 1)
    {
      object_min = newvalue;
      object_max = newvalue;
      object_mean = newvalue;
      object_sum_values = newvalue;
      object_sum_squares = pow(newvalue, 2);
    }
  else
    {
      if (newvalue < object_min)
	{
	  object_min = newvalue;
	}
      if (newvalue > object_max)
	{
	  object_max = newvalue;
	}
      object_sum_values = object_sum_values + newvalue;
      object_sum_squares = object_sum_squares + pow(newvalue, 2); 
      object_mean = object_sum_values / number_samples;	  
      object_stdev = sqrt( ( number_samples*object_sum_squares - pow(object_sum_values, 2)) / ( number_samples*(number_samples - 1)));
    }
}

double mcsLibreCollectStats::get_sum_of_values()
{
  return object_sum_values;
}

double mcsLibreCollectStats::get_mean_value()
{
  return object_mean;
}

double mcsLibreCollectStats::get_stdev_value()
{
  return object_stdev;
}

double mcsLibreCollectStats::get_number_samples()
{
  return number_samples;
}

double mcsLibreCollectStats::get_min_value()
{
  return object_min;
}

double mcsLibreCollectStats::get_max_value()
{
  return object_max;
}

mcsLibreCollectStats::mcsLibreCollectStats(void)
{
  number_samples = 0;
  object_min = 0; 
  object_max = 0;
  object_mean = 0;
  object_stdev = 0; 
  object_sum_values = 0;
  object_sum_squares = 0;
}