PS_Method_CCS_test/libarmadillo/include/armadillo_bits/glue_conv_meat.hpp

// 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 glue_conv
//! @{



// TODO: this implementation of conv() is rudimentary; replace with faster version
template<typename eT>
inline
void
glue_conv::apply(Mat<eT>& out, const Mat<eT>& A, const Mat<eT>& B, const bool A_is_col)
  {
  arma_extra_debug_sigprint();
  
  const Mat<eT>& h = (A.n_elem <= B.n_elem) ? A : B;
  const Mat<eT>& x = (A.n_elem <= B.n_elem) ? B : A;
  
  const uword   h_n_elem    = h.n_elem;
  const uword   h_n_elem_m1 = h_n_elem - 1;
  const uword   x_n_elem    = x.n_elem;
  const uword out_n_elem    = ((h_n_elem + x_n_elem) > 0) ? (h_n_elem + x_n_elem - 1) : uword(0);
  
  if( (h_n_elem == 0) || (x_n_elem == 0) )  { out.zeros(); return; }
  
  
  Col<eT> hh(h_n_elem);  // flipped version of h
  
  const eT*   h_mem =  h.memptr();
        eT*  hh_mem = hh.memptr();
  
  for(uword i=0; i < h_n_elem; ++i)
    {
    hh_mem[h_n_elem_m1-i] = h_mem[i];
    }
  
  
  Col<eT> xx( (x_n_elem + 2*h_n_elem_m1), fill::zeros );  // zero padded version of x
  
  const eT*  x_mem =  x.memptr();
        eT* xx_mem = xx.memptr();
  
  arrayops::copy( &(xx_mem[h_n_elem_m1]), x_mem, x_n_elem );
  
  
  (A_is_col) ? out.set_size(out_n_elem, 1) : out.set_size(1, out_n_elem);
  
  eT* out_mem = out.memptr();
  
  for(uword i=0; i < out_n_elem; ++i)
    {
    // out_mem[i] = dot( hh, xx.subvec(i, (i + h_n_elem_m1)) );
    
    out_mem[i] = op_dot::direct_dot( h_n_elem, hh_mem, &(xx_mem[i]) );
    }
  }



// // alternative implementation of 1d convolution
// template<typename eT>
// inline
// void
// glue_conv::apply(Mat<eT>& out, const Mat<eT>& A, const Mat<eT>& B, const bool A_is_col)
//   {
//   arma_extra_debug_sigprint();
//   
//   const Mat<eT>& h = (A.n_elem <= B.n_elem) ? A : B;
//   const Mat<eT>& x = (A.n_elem <= B.n_elem) ? B : A;
//   
//   const uword   h_n_elem    = h.n_elem;
//   const uword   h_n_elem_m1 = h_n_elem - 1;
//   const uword   x_n_elem    = x.n_elem;
//   const uword out_n_elem    = ((h_n_elem + x_n_elem) > 0) ? (h_n_elem + x_n_elem - 1) : uword(0);
//   
//   if( (h_n_elem == 0) || (x_n_elem == 0) )  { out.zeros(); return; }
//   
//   
//   Col<eT> hh(h_n_elem);  // flipped version of h
//   
//   const eT*   h_mem =  h.memptr();
//         eT*  hh_mem = hh.memptr();
//   
//   for(uword i=0; i < h_n_elem; ++i)
//     {
//     hh_mem[h_n_elem_m1-i] = h_mem[i];
//     }
//   
//   // construct HH matrix, with the column containing shifted versions of hh;
//   // upper limit for number of zeros is about 50%; may not be optimal
//   const uword N_copies = (std::min)(uword(10), h_n_elem); 
//   
//   const uword HH_n_rows = h_n_elem + (N_copies-1);
//   
//   Mat<eT> HH(HH_n_rows, N_copies, fill::zeros);
//   
//   for(uword i=0; i<N_copies; ++i)
//     {
//     arrayops::copy(HH.colptr(i) + i, hh.memptr(), h_n_elem);
//     }
//   
//   
//   
//   Col<eT> xx( (x_n_elem + 2*h_n_elem_m1), fill::zeros );  // zero padded version of x
//   
//   const eT*  x_mem =  x.memptr();
//         eT* xx_mem = xx.memptr();
//   
//   arrayops::copy( &(xx_mem[h_n_elem_m1]), x_mem, x_n_elem );
//   
//   
//   (A_is_col) ? out.set_size(out_n_elem, 1) : out.set_size(1, out_n_elem);
//   
//   eT* out_mem = out.memptr();
//   
//   uword last_i      = 0;
//   bool  last_i_done = false;
//   
//   for(uword i=0; i < xx.n_elem; i += N_copies)
//     {
//     if( ((i + HH_n_rows) <= xx.n_elem) && ((i + N_copies) <= out_n_elem) ) 
//       {
//       const Row<eT> xx_sub(xx_mem + i, HH_n_rows, false, true);
//       
//       Row<eT> out_sub(out_mem + i, N_copies, false, true);
//       
//       out_sub = xx_sub * HH;
//       
//       last_i_done = true;
//       }
//     else
//       {
//       last_i = i;
//       last_i_done = false;
//       break;
//       }
//     }
//   
//   if(last_i_done == false)
//     {
//     for(uword i=last_i; i < out_n_elem; ++i)
//       {
//       // out_mem[i] = dot( hh, xx.subvec(i, (i + h_n_elem_m1)) );
//       
//       out_mem[i] = op_dot::direct_dot( h_n_elem, hh_mem, &(xx_mem[i]) );
//       }
//     }
//   }



template<typename T1, typename T2>
inline
void
glue_conv::apply(Mat<typename T1::elem_type>& out, const Glue<T1,T2,glue_conv>& expr)
  {
  arma_extra_debug_sigprint();
  
  typedef typename T1::elem_type eT;
  
  const quasi_unwrap<T1> UA(expr.A);
  const quasi_unwrap<T2> UB(expr.B);
  
  const Mat<eT>& A = UA.M;
  const Mat<eT>& B = UB.M;
  
  arma_debug_check
    (
    ( ((A.is_vec() == false) && (A.is_empty() == false)) || ((B.is_vec() == false) && (B.is_empty() == false)) ),
    "conv(): given object is not a vector"
    );
  
  const bool A_is_col = ((T1::is_col) || (A.n_cols == 1));
  
  const uword mode = expr.aux_uword;
  
  if(mode == 0)  // full convolution
    {
    glue_conv::apply(out, A, B, A_is_col);
    }
  else
  if(mode == 1)  // same size as A
    {
    Mat<eT> tmp;
    
    glue_conv::apply(tmp, A, B, A_is_col);
    
    if( (tmp.is_empty() == false) && (A.is_empty() == false) && (B.is_empty() == false) )
      {
      const uword start = uword( std::floor( double(B.n_elem) / double(2) ) );
      
      out = (A_is_col) ? tmp(start, 0, arma::size(A)) : tmp(0, start, arma::size(A));
      }
    else
      {
      out.zeros( arma::size(A) );
      }
    }
  }



///



// TODO: this implementation of conv2() is rudimentary; replace with faster version
template<typename eT>
inline
void
glue_conv2::apply(Mat<eT>& out, const Mat<eT>& A, const Mat<eT>& B)
  {
  arma_extra_debug_sigprint();
  
  const Mat<eT>& G = (A.n_elem <= B.n_elem) ? A : B;   // unflipped filter coefficients
  const Mat<eT>& W = (A.n_elem <= B.n_elem) ? B : A;   // original 2D image
  
  const uword out_n_rows = ((W.n_rows + G.n_rows) > 0) ? (W.n_rows + G.n_rows - 1) : uword(0);
  const uword out_n_cols = ((W.n_cols + G.n_cols) > 0) ? (W.n_cols + G.n_cols - 1) : uword(0);
  
  if(G.is_empty() || W.is_empty())  { out.zeros(); return; }
  
  
  Mat<eT> H(G.n_rows, G.n_cols);  // flipped filter coefficients
  
  const uword H_n_rows = H.n_rows;
  const uword H_n_cols = H.n_cols;
  
  const uword H_n_rows_m1 = H_n_rows - 1;
  const uword H_n_cols_m1 = H_n_cols - 1;
  
  for(uword col=0; col < H_n_cols; ++col)
    {
          eT* H_colptr = H.colptr(H_n_cols_m1 - col);
    const eT* G_colptr = G.colptr(col);
    
    for(uword row=0; row < H_n_rows; ++row)
      {
      H_colptr[H_n_rows_m1 - row] = G_colptr[row];
      }
    }
  
  
  Mat<eT> X( (W.n_rows + 2*H_n_rows_m1), (W.n_cols + 2*H_n_cols_m1), fill::zeros );
  
  X( H_n_rows_m1, H_n_cols_m1, arma::size(W) ) = W;  // zero padded version of 2D image
  
  
  out.set_size( out_n_rows, out_n_cols );
  
  for(uword col=0; col < out_n_cols; ++col)
    {
    eT* out_colptr = out.colptr(col);
    
    for(uword row=0; row < out_n_rows; ++row)
      {
      // out.at(row, col) = accu( H % X(row, col, size(H)) );
      
      eT acc = eT(0);
      
      for(uword H_col = 0; H_col < H_n_cols; ++H_col)
        {
        const eT* X_colptr = X.colptr(col + H_col);
        
        acc += op_dot::direct_dot( H_n_rows, H.colptr(H_col), &(X_colptr[row]) );
        }
      
      out_colptr[row] = acc;
      }
    }
  }



template<typename T1, typename T2>
inline
void
glue_conv2::apply(Mat<typename T1::elem_type>& out, const Glue<T1,T2,glue_conv2>& expr)
  {
  arma_extra_debug_sigprint();
  
  typedef typename T1::elem_type eT;
  
  const quasi_unwrap<T1> UA(expr.A);
  const quasi_unwrap<T2> UB(expr.B);
  
  const Mat<eT>& A = UA.M;
  const Mat<eT>& B = UB.M;
  
  const uword mode = expr.aux_uword;
  
  if(mode == 0)  // full convolution
    {
    glue_conv2::apply(out, A, B);
    }
  else
  if(mode == 1)  // same size as A
    {
    Mat<eT> tmp;
    
    glue_conv2::apply(tmp, A, B);
    
    if( (tmp.is_empty() == false) && (A.is_empty() == false) && (B.is_empty() == false) )
      {
      const uword start_row = uword( std::floor( double(B.n_rows) / double(2) ) );
      const uword start_col = uword( std::floor( double(B.n_cols) / double(2) ) );
      
      out = tmp(start_row, start_col, arma::size(A));
      }
    else
      {
      out.zeros( arma::size(A) );
      }
    }
  }



//! @}