text: // Copyright (C) 2009-2016 National ICT Australia (NICTA)
  // 
  // This Source Code Form is subject to the terms of the Mozilla Public
  // License, v. 2.0. If a copy of the MPL was not distributed with this
  // file, You can obtain one at http://mozilla.org/MPL/2.0/.
  // -------------------------------------------------------------------
  // 
  // Written by Conrad Sanderson - http://conradsanderson.id.au
  
  
  //! \addtogroup running_stat
  //! @{
  
  
  
  template<typename eT>
  inline
  arma_counter<eT>::~arma_counter()
    {
    arma_extra_debug_sigprint_this(this);
    }
  
  
  
  template<typename eT>
  inline
  arma_counter<eT>::arma_counter()
    : d_count(   eT(0))
    , i_count(uword(0))
    {
    arma_extra_debug_sigprint_this(this);
    }
  
  
  
  template<typename eT>
  inline
  const arma_counter<eT>& 
  arma_counter<eT>::operator++()
    {
    if(i_count < ARMA_MAX_UWORD)
      {
      i_count++;
      }
    else
      {
      d_count += eT(ARMA_MAX_UWORD);
      i_count  = 1;
      }
    
    return *this;
    }
  
  
  
  template<typename eT>
  inline
  void
  arma_counter<eT>::operator++(int)
    {
    operator++();
    }
  
  
  
  template<typename eT>
  inline
  void
  arma_counter<eT>::reset()
    {
    d_count =    eT(0);
    i_count = uword(0);
    }
  
  
  
  template<typename eT>
  inline
  eT
  arma_counter<eT>::value() const
    {
    return d_count + eT(i_count);
    }
  
  
  
  template<typename eT>
  inline
  eT
  arma_counter<eT>::value_plus_1() const
    {
    if(i_count < ARMA_MAX_UWORD)
      {
      return d_count + eT(i_count + 1);
      }
    else
      {
      return d_count + eT(ARMA_MAX_UWORD) + eT(1);
      }
    }
  
  
  
  template<typename eT>
  inline
  eT
  arma_counter<eT>::value_minus_1() const
    {
    if(i_count > 0)
      {
      return d_count + eT(i_count - 1);
      }
    else
      {
      return d_count - eT(1);
      }
    }
  
  
  
  //
  
  
  
  template<typename eT>
  inline
  running_stat<eT>::~running_stat()
    {
    arma_extra_debug_sigprint_this(this);
    }
  
  
  
  template<typename eT>
  inline
  running_stat<eT>::running_stat()
    : r_mean      (                          eT(0))
    , r_var       (typename running_stat<eT>::T(0))
    , min_val     (                          eT(0))
    , max_val     (                          eT(0))
    , min_val_norm(typename running_stat<eT>::T(0))
    , max_val_norm(typename running_stat<eT>::T(0))
    {
    arma_extra_debug_sigprint_this(this);
    }
  
  
  
  //! update statistics to reflect new sample
  template<typename eT>
  inline
  void
  running_stat<eT>::operator() (const typename running_stat<eT>::T sample)
    {
    arma_extra_debug_sigprint();
    
    if( arma_isfinite(sample) == false )
      {
      arma_debug_warn("running_stat: sample ignored as it is non-finite" );
      return;
      }
    
    running_stat_aux::update_stats(*this, sample);
    }
  
  
  
  //! update statistics to reflect new sample (version for complex numbers)
  template<typename eT>
  inline
  void
  running_stat<eT>::operator() (const std::complex< typename running_stat<eT>::T >& sample)
    {
    arma_extra_debug_sigprint();
    
    if( arma_isfinite(sample) == false )
      {
      arma_debug_warn("running_stat: sample ignored as it is non-finite" );
      return;
      }
    
    running_stat_aux::update_stats(*this, sample);
    }
  
  
  
  //! set all statistics to zero
  template<typename eT>
  inline
  void
  running_stat<eT>::reset()
    {
    arma_extra_debug_sigprint();
    
    // typedef typename running_stat<eT>::T T;
    
    counter.reset();
    
    r_mean       = eT(0);
    r_var        =  T(0);
    
    min_val      = eT(0);
    max_val      = eT(0);
    
    min_val_norm =  T(0);
    max_val_norm =  T(0);
    }
  
  
  
  //! mean or average value
  template<typename eT>
  inline
  eT
  running_stat<eT>::mean() const
    {
    arma_extra_debug_sigprint();
    
    return r_mean;
    }
  
  
  
  //! variance
  template<typename eT>
  inline
  typename running_stat<eT>::T
  running_stat<eT>::var(const uword norm_type) const
    {
    arma_extra_debug_sigprint();
    
    const T N = counter.value();
    
    if(N > T(1))
      {
      if(norm_type == 0)
        {
        return r_var;
        }
      else
        {
        const T N_minus_1 = counter.value_minus_1();
        return (N_minus_1/N) * r_var;
        }
      }
    else
      {
      return T(0);
      }
    }
  
  
  
  //! standard deviation
  template<typename eT>
  inline
  typename running_stat<eT>::T
  running_stat<eT>::stddev(const uword norm_type) const
    {
    arma_extra_debug_sigprint();
    
    return std::sqrt( (*this).var(norm_type) );
    }
  
  
  
  //! minimum value
  template<typename eT>
  inline
  eT
  running_stat<eT>::min() const
    {
    arma_extra_debug_sigprint();
    
    return min_val;
    }
  
  
  
  //! maximum value
  template<typename eT>
  inline
  eT
  running_stat<eT>::max() const
    {
    arma_extra_debug_sigprint();
    
    return max_val;
    }
  
  
  
  template<typename eT>
  inline
  eT
  running_stat<eT>::range() const
    {
    arma_extra_debug_sigprint();
    
    return (max_val - min_val);
    }
  
  
  
  //! number of samples so far
  template<typename eT>
  inline
  typename get_pod_type<eT>::result
  running_stat<eT>::count() const
    {
    arma_extra_debug_sigprint();
    
    return counter.value();
    }
  
  
  
  //! update statistics to reflect new sample (version for non-complex numbers, non-complex sample)
  template<typename eT>
  inline
  void
  running_stat_aux::update_stats(running_stat<eT>& x, const eT sample, const typename arma_not_cx<eT>::result* junk)
    {
    arma_extra_debug_sigprint();
    arma_ignore(junk);
    
    typedef typename running_stat<eT>::T T;
    
    const T N = x.counter.value();
    
    if(N > T(0))
      {
      if(sample < x.min_val)
        {
        x.min_val = sample;
        }
      
      if(sample > x.max_val)
        {
        x.max_val = sample;
        }
      
      const T  N_plus_1   = x.counter.value_plus_1();
      const T  N_minus_1  = x.counter.value_minus_1();
      
      // note: variance has to be updated before the mean
      
      const eT tmp = sample - x.r_mean;
      
      x.r_var  = N_minus_1/N * x.r_var + (tmp*tmp)/N_plus_1;
      
      x.r_mean = x.r_mean + (sample - x.r_mean)/N_plus_1;
      //x.r_mean = (N/N_plus_1)*x.r_mean + sample/N_plus_1;
      //x.r_mean = (x.r_mean + sample/N) * N/N_plus_1;
      }
    else
      {
      x.r_mean  = sample;
      x.min_val = sample;
      x.max_val = sample;
      
      // r_var is initialised to zero
      // in the constructor and reset()
      }
    
    x.counter++;
    }
  
  
  
  //! update statistics to reflect new sample (version for non-complex numbers, complex sample)
  template<typename eT>
  inline
  void
  running_stat_aux::update_stats(running_stat<eT>& x, const std::complex<eT>& sample, const typename arma_not_cx<eT>::result* junk)
    {
    arma_extra_debug_sigprint();
    arma_ignore(junk);
    
    running_stat_aux::update_stats(x, std::real(sample));
    }
  
  
  
  //! update statistics to reflect new sample (version for complex numbers, non-complex sample)
  template<typename eT>
  inline
  void
  running_stat_aux::update_stats(running_stat<eT>& x, const typename eT::value_type sample, const typename arma_cx_only<eT>::result* junk)
    {
    arma_extra_debug_sigprint();
    arma_ignore(junk);
    
    typedef typename eT::value_type T;
    
    running_stat_aux::update_stats(x, std::complex<T>(sample));
    }
  
  
  
  //! alter statistics to reflect new sample (version for complex numbers, complex sample)
  template<typename eT>
  inline
  void
  running_stat_aux::update_stats(running_stat<eT>& x, const eT& sample, const typename arma_cx_only<eT>::result* junk)
    {
    arma_extra_debug_sigprint();
    arma_ignore(junk);
    
    typedef typename eT::value_type T;
    
    const T sample_norm = std::norm(sample);
    const T N           = x.counter.value();
    
    if(N > T(0))
      {
      if(sample_norm < x.min_val_norm)
        {
        x.min_val_norm = sample_norm;
        x.min_val      = sample;
        }
      
      if(sample_norm > x.max_val_norm)
        {
        x.max_val_norm = sample_norm;
        x.max_val      = sample;
        }
      
      const T  N_plus_1   = x.counter.value_plus_1();
      const T  N_minus_1  = x.counter.value_minus_1();
      
      x.r_var = N_minus_1/N * x.r_var + std::norm(sample - x.r_mean)/N_plus_1;
      
      x.r_mean = x.r_mean + (sample - x.r_mean)/N_plus_1;
      //x.r_mean = (N/N_plus_1)*x.r_mean + sample/N_plus_1;
      //x.r_mean = (x.r_mean + sample/N) * N/N_plus_1;
      }
    else
      {
      x.r_mean       = sample;
      x.min_val      = sample;
      x.max_val      = sample;
      x.min_val_norm = sample_norm;
      x.max_val_norm = sample_norm;
      
      // r_var is initialised to zero
      // in the constructor and reset()
      }
    
    x.counter++;
    }
  
  
  
  //! @}
  