source: trunk/src/Averager.h @ 218

// $Id: Averager.h 218 2004-12-30 22:29:15Z peter $

#ifndef _theplu_cpptools_averager_
#define _theplu_cpptools_averager_

#include <cmath>
#include "vector.h"

namespace theplu{
namespace statistics{
  class ostream;

  ///
  /// Class to calulate simple (first and second moments) averages.
  ///
  /// @see WeightedAverager
  ///
  class Averager
  {
  public:

    ///
    /// Default constructor
    ///
    Averager(void);
    
    ///
    /// Constructor taking sum of \a x, sum of squared x, \a xx, and
    /// number of samples \a n.
    ///
    Averager(const double x, const double xx, const long n);

    ///
    /// Copy constructor
    ///
    Averager(const Averager&);
    
    ///
    /// Adding \a n (default=1) number of data point(s) with value \a d.
    ///
    inline void add(const double d,const long n=1)
    {n_+=n; x_+=n*d; xx_+=n*d*d;}

    ///
    /// @return Mean of presented data, \f$ \frac{1}{n}\sum x_i \f$
    ///
    inline double mean(void) const { return n_ ? x_/n_ : 0; }
  
    ///
    /// @return Mean of squared values \f$ \frac{1}{n}\sum x_i^2 \f$.
    ///
    inline double mean_sqr(void) const { return n_ ? xx_/n_ : 0; }

    ///
    /// @return Number of data points
    ///
    inline long n(void) const { return n_; }

    ///
    /// Rescales the object, \f$ \forall x_i \rightarrow a*x_i\f$, \f$
    /// \forall x_i^2 \rightarrow a^2*x_i^2 \f$
    ///
    inline void rescale(double a) { x_*=a; xx_*=a*a; }

    ///
    /// Resets everything to zero
    ///
    inline void reset(void) { n_=0; x_=xx_=0.0;}

    ///
    /// The standard deviation is defined as the square root of the
    /// variance.
    ///
    /// @return The standard deviation, root of the variance().
    ///
    inline double std(void) const { return sqrt(variance()); }

    ///
    /// @return Standard error, i.e. standard deviation of the mean
    /// \f$ \sqrt{variance()/n} \f$
    ///
    inline double standard_error(void) const { return sqrt(variance()/n_); }

    ///
    /// @return The sum of x
    ///
    inline double sum_x(void) const { return x_; }

    ///
    /// @return The sum of squares
    ///
    inline double sum_xsqr(void) const { return xx_; }

    ///
    /// @return \f$ \sum_i (x_i-m)^2\f$
    ///
    inline double sum_xsqr_centered(void) const { return xx_-x_*x_/n_; }

    ///
    /// The variance is calculated using the \f$ (n-1) \f$ correction,
    /// which means it is the best unbiased estimator of the variance
    /// \f$ \frac{1}{N-1}\sum_i (x_i-m)^2\f$, where \f$m\f$ is the
    /// mean.
    ///
    /// @return The variance
    ///
    inline double variance(void) const 
    { return (n_>1) ? sum_xsqr_centered()/(n_-1) : 0; }

    ///
    /// The assignment operator
    ///
    inline const Averager& operator=(const Averager& a)
      { n_=a.n_; x_=a.x_; xx_=a.xx_; return *this; }

    ///
    /// Operator to add another Averager
    ///
    const Averager& operator+=(const Averager&);

  private:
    long  n_;
    double  x_, xx_;
  };

}} // of namespace statistics and namespace theplu

#endif