diff armadillo-2.4.4/include/armadillo_bits/op_median_meat.hpp @ 0:8b6102e2a9b0

Armadillo Library

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/armadillo-2.4.4/include/armadillo_bits/op_median_meat.hpp	Wed Apr 11 09:27:06 2012 +0100
@@ -0,0 +1,379 @@
+// Copyright (C) 2009-2011 NICTA (www.nicta.com.au)
+// Copyright (C) 2009-2011 Conrad Sanderson
+// 
+// This file is part of the Armadillo C++ library.
+// It is provided without any warranty of fitness
+// for any purpose. You can redistribute this file
+// and/or modify it under the terms of the GNU
+// Lesser General Public License (LGPL) as published
+// by the Free Software Foundation, either version 3
+// of the License or (at your option) any later version.
+// (see http://www.opensource.org/licenses for more info)
+
+
+//! \addtogroup op_median
+//! @{
+
+
+
+template<typename eT>
+arma_inline
+eT
+op_median::robust_mean(const eT A, const eT B)
+  {
+  return A + (B - A)/eT(2);
+  }
+
+
+
+//! find the median value of a std::vector (contents is modified)
+template<typename eT>
+inline 
+eT
+op_median::direct_median(std::vector<eT>& X)
+  {
+  arma_extra_debug_sigprint();
+  
+  const uword n_elem = X.size();
+  const uword half   = n_elem/2;
+  
+  std::sort(X.begin(), X.end());
+  
+  if((n_elem % 2) == 0)
+    {
+    return op_median::robust_mean(X[half-1], X[half]);
+    }
+  else
+    {
+    return X[half];
+    }
+  }
+
+
+
+template<typename eT>
+inline 
+eT
+op_median::direct_median(const eT* X, const uword n_elem)
+  {
+  arma_extra_debug_sigprint();
+  
+  std::vector<eT> tmp(X, X+n_elem);
+  
+  return op_median::direct_median(tmp);
+  }
+
+
+
+template<typename eT>
+inline 
+eT
+op_median::direct_median(const subview<eT>& X)
+  {
+  arma_extra_debug_sigprint();
+  
+  const uword X_n_elem = X.n_elem;
+  
+  std::vector<eT> tmp(X_n_elem);
+  
+  for(uword i=0; i<X_n_elem; ++i)
+    {
+    tmp[i] = X[i];
+    }
+  
+  return op_median::direct_median(tmp);
+  }
+
+
+
+template<typename eT>
+inline 
+eT
+op_median::direct_median(const diagview<eT>& X)
+  {
+  arma_extra_debug_sigprint();
+  
+  const uword X_n_elem = X.n_elem;
+  
+  std::vector<eT> tmp(X_n_elem);
+  
+  for(uword i=0; i<X_n_elem; ++i)
+    {
+    tmp[i] = X[i];
+    }
+  
+  return op_median::direct_median(tmp);
+  }
+
+
+
+//! \brief
+//! For each row or for each column, find the median value.
+//! The result is stored in a dense matrix that has either one column or one row.
+//! The dimension, for which the medians are found, is set via the median() function.
+template<typename T1>
+inline
+void
+op_median::apply(Mat<typename T1::elem_type>& out, const Op<T1,op_median>& in)
+  {
+  arma_extra_debug_sigprint();
+  
+  typedef typename T1::elem_type eT;
+  
+  const unwrap_check<T1> tmp(in.m, out);
+  const Mat<eT>&     X = tmp.M;
+  
+  const uword X_n_rows = X.n_rows;
+  const uword X_n_cols = X.n_cols;
+  
+  const uword dim = in.aux_uword_a;
+  arma_debug_check( (dim > 1), "median(): incorrect usage. dim must be 0 or 1");
+  
+  if(dim == 0)  // in each column
+    {
+    arma_extra_debug_print("op_median::apply(), dim = 0");
+    
+    arma_debug_check( (X_n_rows == 0), "median(): given object has zero rows" );
+
+    out.set_size(1, X_n_cols);
+    
+    std::vector<eT> tmp_vec(X_n_rows);
+      
+    for(uword col=0; col<X_n_cols; ++col)
+      {
+      const eT* colmem = X.colptr(col);
+      
+      for(uword row=0; row<X_n_rows; ++row)
+        {
+        tmp_vec[row] = colmem[row];
+        }
+      
+      out[col] = op_median::direct_median(tmp_vec);
+      }
+    }
+  else
+  if(dim == 1)  // in each row
+    {
+    arma_extra_debug_print("op_median::apply(), dim = 1");
+    
+    arma_debug_check( (X_n_cols == 0), "median(): given object has zero columns" );
+
+    out.set_size(X_n_rows, 1);
+    
+    std::vector<eT> tmp_vec(X_n_cols);
+      
+    for(uword row=0; row<X_n_rows; ++row)
+      {
+      for(uword col=0; col<X_n_cols; ++col)
+        {
+        tmp_vec[col] = X.at(row,col);
+        }
+      
+      out[row] =  op_median::direct_median(tmp_vec);
+      }
+    }
+  }
+
+
+
+template<typename T>
+arma_inline
+std::complex<T>
+op_median::robust_mean(const std::complex<T>& A, const std::complex<T>& B)
+  {
+  return A + (B - A)/T(2);
+  }
+
+
+
+template<typename T>
+inline 
+void
+op_median::direct_cx_median_index
+  (
+  uword& out_index1, 
+  uword& out_index2, 
+  std::vector< arma_cx_median_packet<T> >& X
+  )
+  {
+  arma_extra_debug_sigprint();
+  
+  const uword n_elem = X.size();
+  const uword half   = n_elem/2;
+  
+  std::sort(X.begin(), X.end());
+  
+  if((n_elem % 2) == 0)
+    {
+    out_index1 = X[half-1].index;
+    out_index2 = X[half  ].index;
+    }
+  else
+    {
+    out_index1 = X[half].index;
+    out_index2 = out_index1;
+    }
+  }
+
+
+
+template<typename T>
+inline 
+void
+op_median::direct_cx_median_index
+  (
+  uword& out_index1, 
+  uword& out_index2, 
+  const std::complex<T>* X, 
+  const uword n_elem
+  )
+  {
+  arma_extra_debug_sigprint();
+  
+  std::vector< arma_cx_median_packet<T> > tmp(n_elem);
+  
+  for(uword i=0; i<n_elem; ++i)
+    {
+    tmp[i].val   = std::abs(X[i]);
+    tmp[i].index = i;
+    }
+  
+  op_median::direct_cx_median_index(out_index1, out_index2, tmp);
+  }
+
+
+
+template<typename T>
+inline 
+void
+op_median::direct_cx_median_index
+  (
+  uword& out_index1, 
+  uword& out_index2, 
+  const subview< std::complex<T> >&X
+  )
+  {
+  arma_extra_debug_sigprint();
+  
+  const uword n_elem = X.n_elem;
+  
+  std::vector< arma_cx_median_packet<T> > tmp(n_elem);
+  
+  for(uword i=0; i<n_elem; ++i)
+    {
+    tmp[i].val   = std::abs(X[i]);
+    tmp[i].index = i;
+    }
+  
+  op_median::direct_cx_median_index(out_index1, out_index2, tmp);
+  }
+
+
+
+template<typename T>
+inline 
+void
+op_median::direct_cx_median_index
+  (
+  uword& out_index1, 
+  uword& out_index2, 
+  const diagview< std::complex<T> >&X
+  )
+  {
+  arma_extra_debug_sigprint();
+  
+  const uword n_elem = X.n_elem;
+  
+  std::vector< arma_cx_median_packet<T> > tmp(n_elem);
+  
+  for(uword i=0; i<n_elem; ++i)
+    {
+    tmp[i].val   = std::abs(X[i]);
+    tmp[i].index = i;
+    }
+  
+  op_median::direct_cx_median_index(out_index1, out_index2, tmp);
+  }
+
+
+
+//! Implementation for complex numbers
+template<typename T, typename T1>
+inline
+void
+op_median::apply(Mat< std::complex<T> >& out, const Op<T1,op_median>& in)
+  {
+  arma_extra_debug_sigprint();
+  
+  typedef typename std::complex<T> eT;
+  
+  arma_type_check(( is_same_type<eT, typename T1::elem_type>::value == false ));
+  
+  const unwrap_check<T1> tmp(in.m, out);
+  const Mat<eT>&     X = tmp.M;
+  
+  const uword X_n_rows = X.n_rows;
+  const uword X_n_cols = X.n_cols;
+  
+  const uword dim = in.aux_uword_a;
+  arma_debug_check( (dim > 1), "median(): incorrect usage. dim must be 0 or 1");
+  
+  if(dim == 0)  // in each column
+    {
+    arma_extra_debug_print("op_median::apply(), dim = 0");
+    
+    arma_debug_check( (X_n_rows == 0), "median(): given object has zero rows" );
+
+    out.set_size(1, X_n_cols);
+    
+    std::vector< arma_cx_median_packet<T> > tmp_vec(X_n_rows);
+    
+    for(uword col=0; col<X_n_cols; ++col)
+      {
+      const eT* colmem = X.colptr(col);
+      
+      for(uword row=0; row<X_n_rows; ++row)
+        {
+        tmp_vec[row].val   = std::abs(colmem[row]);
+        tmp_vec[row].index = row;
+        }
+      
+      uword index1;
+      uword index2;
+      op_median::direct_cx_median_index(index1, index2, tmp_vec);
+        
+      out[col] = op_median::robust_mean(colmem[index1], colmem[index2]);
+      }
+    }
+  else
+  if(dim == 1)  // in each row
+    {
+    arma_extra_debug_print("op_median::apply(), dim = 1");
+    
+    arma_debug_check( (X_n_cols == 0), "median(): given object has zero columns" );
+
+    out.set_size(X_n_rows, 1);
+    
+    std::vector< arma_cx_median_packet<T> > tmp_vec(X_n_cols);
+    
+    for(uword row=0; row<X_n_rows; ++row)
+      {
+      for(uword col=0; col<X_n_cols; ++col)
+        {
+        tmp_vec[col].val   = std::abs(X.at(row,col));
+        tmp_vec[row].index = col;
+        }
+      
+      uword index1;
+      uword index2;
+      op_median::direct_cx_median_index(index1, index2, tmp_vec);
+      
+      out[row] = op_median::robust_mean( X.at(row,index1), X.at(row,index2) );
+      }
+    }
+  }
+
+
+
+//! @}
+