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// 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 spop_normalise
//! @{
template<typename T1>
inline
void
spop_normalise::apply(SpMat<typename T1::elem_type>& out, const SpOp<T1,spop_normalise>& expr)
{
arma_extra_debug_sigprint();
typedef typename T1::elem_type eT;
const uword p = expr.aux_uword_a;
const uword dim = expr.aux_uword_b;
arma_debug_check( (p == 0), "normalise(): unsupported vector norm type" );
arma_debug_check( (dim > 1), "normalise(): parameter 'dim' must be 0 or 1" );
const unwrap_spmat<T1> U(expr.m);
const SpMat<eT>& X = U.M;
X.sync();
if( X.is_empty() || (X.n_nonzero == 0) ) { out.zeros(X.n_rows, X.n_cols); return; }
if(dim == 0)
{
spop_normalise::apply_direct(out, X, p);
}
else
if(dim == 1)
{
SpMat<eT> tmp1;
SpMat<eT> tmp2;
spop_strans::apply_noalias(tmp1, X);
spop_normalise::apply_direct(tmp2, tmp1, p);
spop_strans::apply_noalias(out, tmp2);
}
}
template<typename eT>
inline
void
spop_normalise::apply_direct(SpMat<eT>& out, const SpMat<eT>& X, const uword p)
{
arma_extra_debug_sigprint();
typedef typename get_pod_type<eT>::result T;
SpMat<eT> tmp(arma_reserve_indicator(), X.n_rows, X.n_cols, X.n_nonzero);
bool has_zero = false;
podarray<T> norm_vals(X.n_cols);
T* norm_vals_mem = norm_vals.memptr();
for(uword col=0; col < X.n_cols; ++col)
{
const uword col_offset = X.col_ptrs[col ];
const uword next_col_offset = X.col_ptrs[col + 1];
const eT* start_ptr = &X.values[ col_offset];
const eT* end_ptr = &X.values[next_col_offset];
const uword n_elem = end_ptr - start_ptr;
const Col<eT> fake_vec(const_cast<eT*>(start_ptr), n_elem, false, false);
const T norm_val = norm(fake_vec, p);
norm_vals_mem[col] = (norm_val != T(0)) ? norm_val : T(1);
}
const uword N = X.n_nonzero;
typename SpMat<eT>::const_iterator it = X.begin();
for(uword i=0; i < N; ++i)
{
const uword row = it.row();
const uword col = it.col();
const eT val = (*it) / norm_vals_mem[col];
if(val == eT(0)) { has_zero = true; }
access::rw(tmp.values[i]) = val;
access::rw(tmp.row_indices[i]) = row;
access::rw(tmp.col_ptrs[col + 1])++;
++it;
}
for(uword c=0; c < tmp.n_cols; ++c)
{
access::rw(tmp.col_ptrs[c + 1]) += tmp.col_ptrs[c];
}
if(has_zero) { tmp.remove_zeros(); }
out.steal_mem(tmp);
}
//! @}
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