// SPDX-License-Identifier: Apache-2.0
// 
// Copyright 2008-2016 Conrad Sanderson (https://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
// https://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 op_normalise
//! @{



template<typename T1>
inline
void
op_normalise_vec::apply(Mat<typename T1::elem_type>& out, const Op<T1,op_normalise_vec>& in)
  {
  arma_debug_sigprint();
  
  typedef typename T1::elem_type eT;
  typedef typename T1::pod_type   T;
  
  const uword p = in.aux_uword_a;
  
  arma_conform_check( (p == 0), "normalise(): unsupported vector norm type" );
  
  const quasi_unwrap<T1> U(in.m);
  
  const T norm_val_a = norm(U.M, p);
  const T norm_val_b = (norm_val_a != T(0)) ? norm_val_a : T(1);
  
  if(quasi_unwrap<T1>::has_subview && U.is_alias(out))
    {
    Mat<eT> tmp = U.M / norm_val_b;
    
    out.steal_mem(tmp);
    }
  else
    {
    out = U.M / norm_val_b;
    }
  }



template<typename T1>
inline
void
op_normalise_mat::apply(Mat<typename T1::elem_type>& out, const Op<T1,op_normalise_mat>& in)
  {
  arma_debug_sigprint();
  
  typedef typename T1::elem_type eT;
  
  const uword p   = in.aux_uword_a;
  const uword dim = in.aux_uword_b;
  
  arma_conform_check( (p   == 0), "normalise(): unsupported vector norm type"   );
  arma_conform_check( (dim >  1), "normalise(): parameter 'dim' must be 0 or 1" );
  
  const quasi_unwrap<T1> U(in.m);
  
  if(quasi_unwrap<T1>::has_subview && U.is_alias(out))
    {
    Mat<eT> tmp;
    
    op_normalise_mat::apply(tmp, U.M, p, dim);
    
    out.steal_mem(tmp);
    }
  else
    {
    op_normalise_mat::apply(out, U.M, p, dim);
    }
  }



template<typename eT>
inline
void
op_normalise_mat::apply(Mat<eT>& out, const Mat<eT>& A, const uword p, const uword dim)
  {
  arma_debug_sigprint();
  
  typedef typename get_pod_type<eT>::result T;
  
  out.copy_size(A);
  
  if(A.n_elem == 0)  { return; }
  
  if(dim == 0)
    {
    const uword n_cols = A.n_cols;
    
    for(uword i=0; i<n_cols; ++i)
      {
      const T norm_val_a = norm(A.col(i), p);
      const T norm_val_b = (norm_val_a != T(0)) ? norm_val_a : T(1);
      
      out.col(i) = A.col(i) / norm_val_b;
      }
    }
  else
    {
    const uword n_rows = A.n_rows;
    const uword n_cols = A.n_cols;
    
    podarray<T> norm_vals(n_rows);
    
    T* norm_vals_mem = norm_vals.memptr();
    
    for(uword i=0; i<n_rows; ++i)
      {
      const T norm_val = norm(A.row(i), p);
      
      norm_vals_mem[i] = (norm_val != T(0)) ? norm_val : T(1);
      }
    
    const eT*   A_mem =   A.memptr();
          eT* out_mem = out.memptr();
    
    for(uword col=0; col < n_cols; ++col)
    for(uword row=0; row < n_rows; ++row)
      {
      (*out_mem) = (*A_mem) / norm_vals_mem[row];
      
      A_mem++;
      out_mem++;
      }
    }
  }



//! @}