149 lines
3.3 KiB
C++
149 lines
3.3 KiB
C++
// SPDX-License-Identifier: Apache-2.0
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//
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// Copyright 2008-2016 Conrad Sanderson (http://conradsanderson.id.au)
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// Copyright 2008-2016 National ICT Australia (NICTA)
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// ------------------------------------------------------------------------
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//! \addtogroup op_normalise
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//! @{
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template<typename T1>
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inline
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void
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op_normalise_vec::apply(Mat<typename T1::elem_type>& out, const Op<T1,op_normalise_vec>& in)
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{
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arma_debug_sigprint();
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typedef typename T1::elem_type eT;
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typedef typename T1::pod_type T;
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const uword p = in.aux_uword_a;
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arma_conform_check( (p == 0), "normalise(): unsupported vector norm type" );
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const quasi_unwrap<T1> U(in.m);
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const T norm_val_a = norm(U.M, p);
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const T norm_val_b = (norm_val_a != T(0)) ? norm_val_a : T(1);
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if(quasi_unwrap<T1>::has_subview && U.is_alias(out))
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{
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Mat<eT> tmp = U.M / norm_val_b;
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out.steal_mem(tmp);
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}
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else
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{
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out = U.M / norm_val_b;
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}
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}
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template<typename T1>
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inline
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void
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op_normalise_mat::apply(Mat<typename T1::elem_type>& out, const Op<T1,op_normalise_mat>& in)
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{
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arma_debug_sigprint();
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typedef typename T1::elem_type eT;
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const uword p = in.aux_uword_a;
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const uword dim = in.aux_uword_b;
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arma_conform_check( (p == 0), "normalise(): unsupported vector norm type" );
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arma_conform_check( (dim > 1), "normalise(): parameter 'dim' must be 0 or 1" );
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const quasi_unwrap<T1> U(in.m);
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if(quasi_unwrap<T1>::has_subview && U.is_alias(out))
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{
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Mat<eT> out2;
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op_normalise_mat::apply(out2, U.M, p, dim);
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out.steal_mem(out2);
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}
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else
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{
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op_normalise_mat::apply(out, U.M, p, dim);
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}
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}
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template<typename eT>
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inline
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void
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op_normalise_mat::apply(Mat<eT>& out, const Mat<eT>& A, const uword p, const uword dim)
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{
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arma_debug_sigprint();
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typedef typename get_pod_type<eT>::result T;
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out.copy_size(A);
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if(A.n_elem == 0) { return; }
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if(dim == 0)
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{
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const uword n_cols = A.n_cols;
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for(uword i=0; i<n_cols; ++i)
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{
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const T norm_val_a = norm(A.col(i), p);
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const T norm_val_b = (norm_val_a != T(0)) ? norm_val_a : T(1);
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out.col(i) = A.col(i) / norm_val_b;
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}
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}
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else
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{
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const uword n_rows = A.n_rows;
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const uword n_cols = A.n_cols;
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podarray<T> norm_vals(n_rows);
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T* norm_vals_mem = norm_vals.memptr();
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for(uword i=0; i<n_rows; ++i)
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{
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const T norm_val = norm(A.row(i), p);
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norm_vals_mem[i] = (norm_val != T(0)) ? norm_val : T(1);
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}
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const eT* A_mem = A.memptr();
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eT* out_mem = out.memptr();
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for(uword col=0; col < n_cols; ++col)
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for(uword row=0; row < n_rows; ++row)
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{
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(*out_mem) = (*A_mem) / norm_vals_mem[row];
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A_mem++;
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out_mem++;
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}
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}
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}
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//! @}
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