441 lines
9.2 KiB
C++
441 lines
9.2 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_mean
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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_mean::apply(Mat<typename T1::elem_type>& out, const Op<T1,op_mean>& 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 dim = in.aux_uword_a;
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arma_conform_check( (dim > 1), "mean(): parameter 'dim' must be 0 or 1" );
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const quasi_unwrap<T1> U(in.m);
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if(U.is_alias(out))
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{
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Mat<eT> tmp;
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op_mean::apply_noalias(tmp, U.M, dim);
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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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op_mean::apply_noalias(out, U.M, 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_mean::apply_noalias(Mat<eT>& out, const Mat<eT>& X, 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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const uword X_n_rows = X.n_rows;
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const uword X_n_cols = X.n_cols;
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if(dim == 0)
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{
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out.set_size((X_n_rows > 0) ? 1 : 0, X_n_cols);
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if(X_n_rows == 0) { return; }
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eT* out_mem = out.memptr();
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for(uword col=0; col < X_n_cols; ++col)
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{
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out_mem[col] = op_mean::direct_mean( X.colptr(col), X_n_rows );
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}
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}
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else
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if(dim == 1)
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{
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out.zeros(X_n_rows, (X_n_cols > 0) ? 1 : 0);
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if(X_n_cols == 0) { return; }
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eT* out_mem = out.memptr();
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for(uword col=0; col < X_n_cols; ++col)
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{
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arrayops::inplace_plus(out_mem, X.colptr(col), X_n_rows);
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}
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out /= T(X_n_cols);
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if(out.internal_has_nonfinite())
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{
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podarray<eT> tmp;
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for(uword row=0; row < X_n_rows; ++row)
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{
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const eT old_mean = out_mem[row];
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if(arma_isnonfinite(old_mean))
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{
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tmp.copy_row(X, row);
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out_mem[row] = op_mean::direct_mean_robust(old_mean, tmp.memptr(), tmp.n_elem);
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}
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}
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}
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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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void
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op_mean::apply(Cube<typename T1::elem_type>& out, const OpCube<T1,op_mean>& 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 dim = in.aux_uword_a;
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arma_conform_check( (dim > 2), "mean(): parameter 'dim' must be 0 or 1 or 2" );
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const unwrap_cube<T1> U(in.m);
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if(U.is_alias(out))
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{
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Cube<eT> tmp;
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op_mean::apply_noalias(tmp, U.M, dim);
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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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op_mean::apply_noalias(out, U.M, 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_mean::apply_noalias(Cube<eT>& out, const Cube<eT>& X, 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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const uword X_n_rows = X.n_rows;
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const uword X_n_cols = X.n_cols;
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const uword X_n_slices = X.n_slices;
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if(dim == 0)
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{
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out.set_size((X_n_rows > 0) ? 1 : 0, X_n_cols, X_n_slices);
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if(X_n_rows == 0) { return; }
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for(uword slice=0; slice < X_n_slices; ++slice)
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{
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eT* out_mem = out.slice_memptr(slice);
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for(uword col=0; col < X_n_cols; ++col)
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{
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out_mem[col] = op_mean::direct_mean( X.slice_colptr(slice,col), X_n_rows );
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}
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}
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}
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else
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if(dim == 1)
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{
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out.zeros(X_n_rows, (X_n_cols > 0) ? 1 : 0, X_n_slices);
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if(X_n_cols == 0) { return; }
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for(uword slice=0; slice < X_n_slices; ++slice)
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{
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eT* out_mem = out.slice_memptr(slice);
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for(uword col=0; col < X_n_cols; ++col)
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{
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arrayops::inplace_plus(out_mem, X.slice_colptr(slice,col), X_n_rows);
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}
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for(uword row=0; row < X_n_rows; ++row) { out_mem[row] /= T(X_n_cols); }
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if(arrayops::is_finite(out_mem, X_n_rows) == false)
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{
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const Mat<eT> tmp_mat('j', X.slice_memptr(slice), X_n_rows, X_n_cols);
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podarray<eT> tmp_vec;
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for(uword row=0; row < X_n_rows; ++row)
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{
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const eT old_mean = out_mem[row];
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if(arma_isnonfinite(old_mean))
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{
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tmp_vec.copy_row(tmp_mat, row);
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out_mem[row] = op_mean::direct_mean_robust(old_mean, tmp_vec.memptr(), tmp_vec.n_elem);
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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 == 2)
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{
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out.zeros(X_n_rows, X_n_cols, (X_n_slices > 0) ? 1 : 0);
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if(X_n_slices == 0) { return; }
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eT* out_mem = out.memptr();
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for(uword slice=0; slice < X_n_slices; ++slice)
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{
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arrayops::inplace_plus(out_mem, X.slice_memptr(slice), X.n_elem_slice );
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}
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out /= T(X_n_slices);
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if(out.internal_has_nonfinite())
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{
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podarray<eT> tmp(X_n_slices);
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for(uword col=0; col < X_n_cols; ++col)
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for(uword row=0; row < X_n_rows; ++row)
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{
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const eT old_mean = out.at(row,col,0);
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if(arma_isnonfinite(old_mean))
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{
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for(uword slice=0; slice < X_n_slices; ++slice) { tmp[slice] = X.at(row,col,slice); }
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out.at(row,col,0) = op_mean::direct_mean_robust(old_mean, tmp.memptr(), tmp.n_elem);
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}
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}
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}
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}
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}
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//
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template<typename eT>
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inline
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eT
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op_mean::direct_mean(const eT* X_mem, const uword N)
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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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const eT mean = arrayops::accumulate(X_mem, N) / T(N);
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return arma_isfinite(mean) ? mean : op_mean::direct_mean_robust(mean, X_mem, N);
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}
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template<typename eT>
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inline
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eT
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op_mean::direct_mean_robust(const eT old_mean, const eT* X_mem, const uword N)
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{
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arma_debug_sigprint();
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// use an adapted form of the mean finding algorithm from the running_stat class
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typedef typename get_pod_type<eT>::result T;
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if(arrayops::is_finite(X_mem, N) == false) { return old_mean; }
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eT r_mean = eT(0);
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for(uword i=0; i < N; ++i)
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{
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r_mean = r_mean + (X_mem[i] - r_mean) / T(i+1);
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}
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return r_mean;
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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::elem_type
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op_mean::mean_all(const T1& X)
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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 quasi_unwrap<T1> U(X);
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if(U.M.n_elem == 0)
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{
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arma_conform_check(true, "mean(): object has no elements");
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return Datum<eT>::nan;
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}
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return op_mean::direct_mean(U.M.memptr(), U.M.n_elem);
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}
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template<typename T1>
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inline
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typename T1::elem_type
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op_mean::mean_all(const Op<T1, op_omit>& 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 omit_mode = in.aux_uword_a;
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if(arma_config::fast_math_warn)
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{
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if(omit_mode == 1) { arma_warn(1, "omit_nan(): detection of NaN is not reliable in fast math mode"); }
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if(omit_mode == 2) { arma_warn(1, "omit_nonfinite(): detection of non-finite values is not reliable in fast math mode"); }
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}
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const quasi_unwrap<T1> U(in.m);
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if(U.M.n_elem == 0)
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{
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arma_conform_check(true, "mean(): object has no elements");
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return Datum<eT>::nan;
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}
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auto is_omitted_1 = [](const eT& x) -> bool { return arma_isnan(x); };
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auto is_omitted_2 = [](const eT& x) -> bool { return arma_isnonfinite(x); };
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eT result = eT(0);
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if(omit_mode == 1) { result = op_mean::mean_all_omit(U.M.memptr(), U.M.n_elem, is_omitted_1); }
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if(omit_mode == 2) { result = op_mean::mean_all_omit(U.M.memptr(), U.M.n_elem, is_omitted_2); }
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return result;
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}
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template<typename eT, typename functor>
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inline
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eT
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op_mean::mean_all_omit(const eT* X_mem, const uword N, functor is_omitted)
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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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uword count = 0;
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eT acc = eT(0);
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for(uword i=0; i < N; ++i)
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{
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const eT val = X_mem[i];
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if(is_omitted(val) == false) { acc += val; ++count; }
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}
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acc /= T(count);
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if(arma_isfinite(acc)) { return acc; }
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// handle possible overflow
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eT r_mean = eT(0);
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count = 0;
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for(uword i=0; i < N; ++i)
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{
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const eT val = X_mem[i];
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if(is_omitted(val) == false)
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{
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r_mean = r_mean + (val - r_mean) / T(count+1); // kept as count+1 to use same algorithm as op_mean::direct_mean_robust()
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++count;
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}
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}
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return r_mean;
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}
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//
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template<typename eT>
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arma_inline
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eT
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op_mean::robust_mean(const eT A, const eT B)
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{
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return (arma_isfinite(A) && arma_isfinite(B)) ? eT( A + (B - A)/eT(2) ) : eT( (A+B)/eT(2) );
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}
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template<typename T>
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arma_inline
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std::complex<T>
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op_mean::robust_mean(const std::complex<T>& A, const std::complex<T>& B)
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{
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typedef typename std::complex<T> eT;
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return (arma_isfinite(A) && arma_isfinite(B)) ? eT( A + (B - A)/T(2) ) : eT( (A+B)/T(2) );
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}
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//! @}
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