163 lines
4.5 KiB
C++
163 lines
4.5 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_sp_stddev
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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_sp_stddev::apply(Mat<typename T1::pod_type>& out, const mtSpReduceOp<typename T1::pod_type, T1, op_sp_stddev>& in)
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{
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arma_debug_sigprint();
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const uword norm_type = in.aux_uword_a;
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const uword dim = in.aux_uword_b;
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arma_conform_check( (norm_type > 1), "stddev(): parameter 'norm_type' must be 0 or 1" );
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arma_conform_check( (dim > 1), "stddev(): parameter 'dim' must be 0 or 1" );
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const SpProxy<T1> p(in.m);
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const uword p_n_rows = p.get_n_rows();
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const uword p_n_cols = p.get_n_cols();
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if( (p_n_rows == 0) || (p_n_cols == 0) || (p.get_n_nonzero() == 0) )
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{
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if(dim == 0) { out.zeros((p_n_rows > 0) ? 1 : 0, p_n_cols); }
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if(dim == 1) { out.zeros(p_n_rows, (p_n_cols > 0) ? 1 : 0); }
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return;
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}
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op_sp_stddev::apply_slow(out, p, norm_type, dim);
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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_sp_stddev::apply_slow
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(
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Mat<typename T1::pod_type>& out,
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const SpProxy<T1>& p,
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const uword norm_type,
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const uword dim
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)
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{
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arma_debug_sigprint();
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typedef typename T1::elem_type in_eT;
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//typedef typename T1::pod_type out_eT;
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const uword p_n_rows = p.get_n_rows();
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const uword p_n_cols = p.get_n_cols();
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if(dim == 0) // find variance in each column
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{
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arma_debug_print("op_sp_stddev::apply_slow(): dim = 0");
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out.zeros(1, p_n_cols);
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for(uword col = 0; col < p_n_cols; ++col)
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{
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if(SpProxy<T1>::use_iterator)
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{
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// We must use an iterator; we can't access memory directly.
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typename SpProxy<T1>::const_iterator_type it = p.begin_col(col);
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typename SpProxy<T1>::const_iterator_type end = p.begin_col(col + 1);
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const uword n_zero = p_n_rows - (end.pos() - it.pos());
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// in_eT is used just to get the specialization right (complex / noncomplex)
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out.at(0, col) = std::sqrt( op_sp_var::iterator_var(it, end, n_zero, norm_type, in_eT(0)) );
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}
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else
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{
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// We can use direct memory access to calculate the variance.
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out.at(0, col) = std::sqrt(
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op_sp_var::direct_var
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(
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&p.get_values()[p.get_col_ptrs()[col]],
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p.get_col_ptrs()[col + 1] - p.get_col_ptrs()[col],
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p_n_rows,
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norm_type
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)
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);
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}
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}
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}
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else
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if(dim == 1) // find variance in each row
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{
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arma_debug_print("op_sp_stddev::apply_slow(): dim = 1");
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out.zeros(p_n_rows, 1);
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for(uword row = 0; row < p_n_rows; ++row)
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{
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// We have to use an iterator here regardless of whether or not we can
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// directly access memory.
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typename SpProxy<T1>::const_row_iterator_type it = p.begin_row(row);
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typename SpProxy<T1>::const_row_iterator_type end = p.end_row(row);
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const uword n_zero = p_n_cols - (end.pos() - it.pos());
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out.at(row, 0) = std::sqrt( op_sp_var::iterator_var(it, end, n_zero, norm_type, in_eT(0)) );
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}
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}
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}
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template<typename T1>
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inline
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typename T1::pod_type
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op_sp_stddev::stddev_vec
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(
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const T1& X,
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const uword norm_type
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)
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{
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arma_debug_sigprint();
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typedef typename T1::pod_type T;
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arma_conform_check( (norm_type > 1), "stddev(): parameter 'norm_type' must be 0 or 1" );
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// conditionally unwrap it into a temporary and then directly operate.
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const unwrap_spmat<T1> tmp(X);
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if(tmp.M.n_elem == 0)
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{
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arma_conform_check(true, "stddev(): object has no elements");
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return Datum<T>::nan;
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}
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return std::sqrt( op_sp_var::direct_var(tmp.M.values, tmp.M.n_nonzero, tmp.M.n_elem, norm_type) );
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}
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//! @}
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