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diff --git a/src/armadillo/include/armadillo_bits/running_stat_meat.hpp b/src/armadillo/include/armadillo_bits/running_stat_meat.hpp
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+// SPDX-License-Identifier: Apache-2.0
+// 
+// Copyright 2008-2016 Conrad Sanderson (http://conradsanderson.id.au)
+// Copyright 2008-2016 National ICT Australia (NICTA)
+// 
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+// http://www.apache.org/licenses/LICENSE-2.0
+// 
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+// ------------------------------------------------------------------------
+
+
+//! \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_level(3, "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_level(3, "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++;
+  }
+
+
+
+//! @}