// SPDX-License-Identifier: Apache-2.0
//
// 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 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> out2;

    op_normalise_mat::apply(out2, U.M, p, dim);

    out.steal_mem(out2);
  } 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++;
      }
  }
}

//! @}
