max@0: // Copyright (C) 2009-2011 NICTA (www.nicta.com.au)
max@0: // Copyright (C) 2009-2011 Conrad Sanderson
max@0: // 
max@0: // This file is part of the Armadillo C++ library.
max@0: // It is provided without any warranty of fitness
max@0: // for any purpose. You can redistribute this file
max@0: // and/or modify it under the terms of the GNU
max@0: // Lesser General Public License (LGPL) as published
max@0: // by the Free Software Foundation, either version 3
max@0: // of the License or (at your option) any later version.
max@0: // (see http://www.opensource.org/licenses for more info)
max@0: 
max@0: 
max@0: //! \addtogroup op_mean
max@0: //! @{
max@0: 
max@0: 
max@0: 
max@0: template<typename eT>
max@0: arma_pure
max@0: inline
max@0: eT
max@0: op_mean::direct_mean(const eT* const X, const uword n_elem)
max@0:   {
max@0:   arma_extra_debug_sigprint();
max@0:   
max@0:   typedef typename get_pod_type<eT>::result T;
max@0:   
max@0:   const eT result = arrayops::accumulate(X, n_elem) / T(n_elem);
max@0:   
max@0:   return arma_isfinite(result) ? result : op_mean::direct_mean_robust(X, n_elem);
max@0:   }
max@0: 
max@0: 
max@0: 
max@0: template<typename eT>
max@0: inline
max@0: eT
max@0: op_mean::direct_mean(const Mat<eT>& X, const uword row)
max@0:   {
max@0:   arma_extra_debug_sigprint();
max@0:   
max@0:   typedef typename get_pod_type<eT>::result T;
max@0:   
max@0:   const uword X_n_cols = X.n_cols;
max@0:   
max@0:   eT val = eT(0);
max@0:   
max@0:   for(uword col=0; col<X_n_cols; ++col)
max@0:     {
max@0:     val += X.at(row,col);
max@0:     }
max@0:   
max@0:   const eT result = val / T(X_n_cols);
max@0:   
max@0:   return arma_isfinite(result) ? result : direct_mean_robust(X, row);
max@0:   }
max@0: 
max@0: 
max@0: 
max@0: template<typename eT>
max@0: inline 
max@0: eT
max@0: op_mean::direct_mean(const subview<eT>& X)
max@0:   {
max@0:   arma_extra_debug_sigprint();
max@0:   
max@0:   typedef typename get_pod_type<eT>::result T;
max@0:   
max@0:   const uword X_n_elem = X.n_elem;
max@0:   
max@0:   eT val = eT(0);
max@0:   
max@0:   for(uword i=0; i<X_n_elem; ++i)
max@0:     {
max@0:     val += X[i];
max@0:     }
max@0:   
max@0:   const eT result = val / T(X_n_elem);
max@0:   
max@0:   return arma_isfinite(result) ? result : direct_mean_robust(X);
max@0:   }
max@0: 
max@0: 
max@0: 
max@0: template<typename eT>
max@0: inline 
max@0: eT
max@0: op_mean::direct_mean(const diagview<eT>& X)
max@0:   {
max@0:   arma_extra_debug_sigprint();
max@0:   
max@0:   typedef typename get_pod_type<eT>::result T;
max@0:   
max@0:   const uword X_n_elem = X.n_elem;
max@0:   
max@0:   eT val = eT(0);
max@0:   
max@0:   for(uword i=0; i<X_n_elem; ++i)
max@0:     {
max@0:     val += X[i];
max@0:     }
max@0:   
max@0:   const eT result = val / T(X_n_elem);
max@0:   
max@0:   return arma_isfinite(result) ? result : direct_mean_robust(X);
max@0:   }
max@0: 
max@0: 
max@0: 
max@0: //! \brief
max@0: //! For each row or for each column, find the mean value.
max@0: //! The result is stored in a dense matrix that has either one column or one row.
max@0: //! The dimension, for which the means are found, is set via the mean() function.
max@0: template<typename T1>
max@0: inline
max@0: void
max@0: op_mean::apply(Mat<typename T1::elem_type>& out, const Op<T1,op_mean>& in)
max@0:   {
max@0:   arma_extra_debug_sigprint();
max@0:   
max@0:   typedef typename T1::elem_type            eT;
max@0:   typedef typename get_pod_type<eT>::result  T;
max@0:   
max@0:   const unwrap_check<T1> tmp(in.m, out);
max@0:   const Mat<eT>& X = tmp.M;
max@0:   
max@0:   const uword dim = in.aux_uword_a;
max@0:   arma_debug_check( (dim > 1), "mean(): incorrect usage. dim must be 0 or 1");
max@0:   
max@0:   const uword X_n_rows = X.n_rows;
max@0:   const uword X_n_cols = X.n_cols;
max@0:   
max@0:   if(dim == 0)
max@0:     {
max@0:     arma_extra_debug_print("op_mean::apply(), dim = 0");
max@0:     
max@0:     out.set_size( (X_n_rows > 0) ? 1 : 0, X_n_cols );
max@0:     
max@0:     if(X_n_rows > 0)
max@0:       {
max@0:       eT* out_mem = out.memptr();
max@0:       
max@0:       for(uword col=0; col<X_n_cols; ++col)
max@0:         {
max@0:         out_mem[col] = op_mean::direct_mean( X.colptr(col), X_n_rows );
max@0:         }
max@0:       }
max@0:     }
max@0:   else
max@0:   if(dim == 1)
max@0:     {
max@0:     arma_extra_debug_print("op_mean::apply(), dim = 1");
max@0:     
max@0:     out.set_size(X_n_rows, (X_n_cols > 0) ? 1 : 0);
max@0:     
max@0:     if(X_n_cols > 0)
max@0:       {
max@0:       eT* out_mem = out.memptr();
max@0:       
max@0:       for(uword row=0; row<X_n_rows; ++row)
max@0:         {
max@0:         out_mem[row] = op_mean::direct_mean( X, row );
max@0:         }
max@0:       }
max@0:     }
max@0:   }
max@0: 
max@0: 
max@0: 
max@0: template<typename eT>
max@0: arma_pure
max@0: inline
max@0: eT
max@0: op_mean::direct_mean_robust(const eT* const X, const uword n_elem)
max@0:   {
max@0:   arma_extra_debug_sigprint();
max@0:   
max@0:   // use an adapted form of the mean finding algorithm from the running_stat class
max@0:   
max@0:   typedef typename get_pod_type<eT>::result T;
max@0:   
max@0:   uword i,j;
max@0:   
max@0:   eT r_mean = eT(0);
max@0:   
max@0:   for(i=0, j=1; j<n_elem; i+=2, j+=2)
max@0:     {
max@0:     const eT Xi = X[i];
max@0:     const eT Xj = X[j];
max@0:     
max@0:     r_mean = r_mean + (Xi - r_mean)/T(j);    // we need i+1, and j is equivalent to i+1 here
max@0:     r_mean = r_mean + (Xj - r_mean)/T(j+1);
max@0:     }
max@0:   
max@0:   
max@0:   if(i < n_elem)
max@0:     {
max@0:     const eT Xi = X[i];
max@0:     
max@0:     r_mean = r_mean + (Xi - r_mean)/T(i+1);
max@0:     }
max@0:   
max@0:   return r_mean;
max@0:   }
max@0: 
max@0: 
max@0: 
max@0: template<typename eT>
max@0: inline
max@0: eT
max@0: op_mean::direct_mean_robust(const Mat<eT>& X, const uword row)
max@0:   {
max@0:   arma_extra_debug_sigprint();
max@0:   
max@0:   typedef typename get_pod_type<eT>::result T;
max@0:   
max@0:   const uword X_n_cols = X.n_cols;
max@0:   
max@0:   eT r_mean = eT(0);
max@0:   
max@0:   for(uword col=0; col<X_n_cols; ++col)
max@0:     {
max@0:     r_mean = r_mean + (X.at(row,col) - r_mean)/T(col+1);
max@0:     }
max@0:   
max@0:   return r_mean;
max@0:   }
max@0: 
max@0: 
max@0: 
max@0: template<typename eT>
max@0: inline 
max@0: eT
max@0: op_mean::direct_mean_robust(const subview<eT>& X)
max@0:   {
max@0:   arma_extra_debug_sigprint();
max@0:   
max@0:   typedef typename get_pod_type<eT>::result T;
max@0:   
max@0:   const uword X_n_elem = X.n_elem;
max@0:   
max@0:   eT r_mean = eT(0);
max@0:   
max@0:   for(uword i=0; i<X_n_elem; ++i)
max@0:     {
max@0:     r_mean = r_mean + (X[i] - r_mean)/T(i+1);
max@0:     }
max@0:   
max@0:   return r_mean;
max@0:   }
max@0: 
max@0: 
max@0: 
max@0: template<typename eT>
max@0: inline 
max@0: eT
max@0: op_mean::direct_mean_robust(const diagview<eT>& X)
max@0:   {
max@0:   arma_extra_debug_sigprint();
max@0:   
max@0:   typedef typename get_pod_type<eT>::result T;
max@0:   
max@0:   const uword X_n_elem = X.n_elem;
max@0:   
max@0:   eT r_mean = eT(0);
max@0:   
max@0:   for(uword i=0; i<X_n_elem; ++i)
max@0:     {
max@0:     r_mean = r_mean + (X[i] - r_mean)/T(i+1);
max@0:     }
max@0:   
max@0:   return r_mean;
max@0:   }
max@0: 
max@0: 
max@0: 
max@0: //! @}
max@0: