diff armadillo-3.900.4/include/armadillo_bits/op_sum_meat.hpp @ 49:1ec0e2823891

Switch to using subrepo copies of qm-dsp, nnls-chroma, vamp-plugin-sdk; update Armadillo version; assume build without external BLAS/LAPACK

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/armadillo-3.900.4/include/armadillo_bits/op_sum_meat.hpp	Thu Jun 13 10:25:24 2013 +0100
@@ -0,0 +1,141 @@
+// Copyright (C) 2008-2013 NICTA (www.nicta.com.au)
+// Copyright (C) 2008-2013 Conrad Sanderson
+// 
+// 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/.
+
+
+//! \addtogroup op_sum
+//! @{
+
+//! \brief
+//! Immediate sum of elements of a matrix along a specified dimension (either rows or columns).
+//! The result is stored in a dense matrix that has either one column or one row.
+//! See the sum() function for more details.
+template<typename T1>
+arma_hot
+inline
+void
+op_sum::apply(Mat<typename T1::elem_type>& out, const Op<T1,op_sum>& in)
+  {
+  arma_extra_debug_sigprint();
+  
+  typedef typename T1::elem_type eT;
+  
+  const uword dim = in.aux_uword_a;
+  arma_debug_check( (dim > 1), "sum(): incorrect usage. dim must be 0 or 1");
+  
+  const Proxy<T1> P(in.m);
+  
+  typedef typename Proxy<T1>::stored_type P_stored_type;
+  
+  const bool is_alias = P.is_alias(out);
+  
+  if( (is_Mat<P_stored_type>::value == true) || is_alias )
+    {
+    const unwrap_check<P_stored_type> tmp(P.Q, is_alias);
+    
+    const typename unwrap_check<P_stored_type>::stored_type& X = tmp.M;
+    
+    const uword X_n_rows = X.n_rows;
+    const uword X_n_cols = X.n_cols;
+    
+    if(dim == 0)  // traverse across rows (i.e. find the sum in each column)
+      {
+      out.set_size(1, X_n_cols);
+      
+      eT* out_mem = out.memptr();
+      
+      for(uword col=0; col < X_n_cols; ++col)
+        {
+        out_mem[col] = arrayops::accumulate( X.colptr(col), X_n_rows );
+        }
+      }
+    else  // traverse across columns (i.e. find the sum in each row)
+      {
+      out.set_size(X_n_rows, 1);
+      
+      eT* out_mem = out.memptr();
+        
+      for(uword row=0; row < X_n_rows; ++row)
+        {
+        eT val = eT(0);
+        
+        uword i,j;
+        for(i=0, j=1; j < X_n_cols; i+=2, j+=2)
+          {
+          val += X.at(row,i);
+          val += X.at(row,j);
+          }
+        
+        if(i < X_n_cols)
+          {
+          val += X.at(row,i);
+          }
+        
+        out_mem[row] = val;
+        }
+      }
+    }
+  else
+    {
+    const uword P_n_rows = P.get_n_rows();
+    const uword P_n_cols = P.get_n_cols();
+    
+    if(dim == 0)  // traverse across rows (i.e. find the sum in each column)
+      {
+      out.set_size(1, P_n_cols);
+      
+      eT* out_mem = out.memptr();
+      
+      for(uword col=0; col < P_n_cols; ++col)
+        {
+        eT val = eT(0);
+        
+        uword i,j;
+        for(i=0, j=1; j < P_n_rows; i+=2, j+=2)
+          {
+          val += P.at(i,col);
+          val += P.at(j,col);
+          }
+        
+        if(i < P_n_rows)
+          {
+          val += P.at(i,col);
+          }
+        
+        out_mem[col] = val;
+        }
+      }
+    else  // traverse across columns (i.e. find the sum in each row)
+      {
+      out.set_size(P_n_rows, 1);
+      
+      eT* out_mem = out.memptr();
+      
+      for(uword row=0; row < P_n_rows; ++row)
+        {
+        eT val = eT(0);
+        
+        uword i,j;
+        for(i=0, j=1; j < P_n_cols; i+=2, j+=2)
+          {
+          val += P.at(row,i);
+          val += P.at(row,j);
+          }
+        
+        if(i < P_n_cols)
+          {
+          val += P.at(row,i);
+          }
+        
+        out_mem[row] = val;
+        }
+      }
+    }
+  }
+
+
+
+//! @}