// Copyright (C) 2012-2015 National ICT Australia (NICTA) // // This Source Code Form is subject to the terms of the Mozilla Public // License, v. 2.0. If a copy of the MPL was not distributed with this // file, You can obtain one at http://mozilla.org/MPL/2.0/. // ------------------------------------------------------------------- // // Written by Conrad Sanderson - http://conradsanderson.id.au // Written by Ryan Curtin //! \addtogroup spop_mean //! @{ template inline void spop_mean::apply(SpMat& out, const SpOp& in) { arma_extra_debug_sigprint(); typedef typename T1::elem_type eT; const uword dim = in.aux_uword_a; arma_debug_check( (dim > 1), "mean(): parameter 'dim' must be 0 or 1" ); const SpProxy p(in.m); if(p.is_alias(out) == false) { spop_mean::apply_noalias_fast(out, p, dim); } else { SpMat tmp; spop_mean::apply_noalias_fast(tmp, p, dim); out.steal_mem(tmp); } } template inline void spop_mean::apply_noalias_fast ( SpMat& out, const SpProxy& p, const uword dim ) { arma_extra_debug_sigprint(); typedef typename T1::elem_type eT; typedef typename T1::pod_type T; const uword p_n_rows = p.get_n_rows(); const uword p_n_cols = p.get_n_cols(); if( (p_n_rows == 0) || (p_n_cols == 0) || (p.get_n_nonzero() == 0) ) { if(dim == 0) { out.zeros((p_n_rows > 0) ? 1 : 0, p_n_cols); } if(dim == 1) { out.zeros(p_n_rows, (p_n_cols > 0) ? 1 : 0); } return; } if(dim == 0) // find the mean in each column { Row acc(p_n_cols, fill::zeros); if(SpProxy::must_use_iterator) { typename SpProxy::const_iterator_type it = p.begin(); typename SpProxy::const_iterator_type it_end = p.end(); while(it != it_end) { acc[it.col()] += (*it); ++it; } acc /= T(p_n_rows); } else { for(uword col = 0; col < p_n_cols; ++col) { acc[col] = arrayops::accumulate ( &p.get_values()[p.get_col_ptrs()[col]], p.get_col_ptrs()[col + 1] - p.get_col_ptrs()[col] ) / T(p_n_rows); } } out = acc; } else if(dim == 1) // find the mean in each row { Col acc(p_n_rows, fill::zeros); typename SpProxy::const_iterator_type it = p.begin(); typename SpProxy::const_iterator_type it_end = p.end(); while(it != it_end) { acc[it.row()] += (*it); ++it; } acc /= T(p_n_cols); out = acc; } if(out.is_finite() == false) { spop_mean::apply_noalias_slow(out, p, dim); } } template inline void spop_mean::apply_noalias_slow ( SpMat& out, const SpProxy& p, const uword dim ) { arma_extra_debug_sigprint(); typedef typename T1::elem_type eT; const uword p_n_rows = p.get_n_rows(); const uword p_n_cols = p.get_n_cols(); if(dim == 0) // find the mean in each column { arma_extra_debug_print("spop_mean::apply_noalias(): dim = 0"); out.set_size((p_n_rows > 0) ? 1 : 0, p_n_cols); if( (p_n_rows == 0) || (p.get_n_nonzero() == 0) ) { return; } for(uword col = 0; col < p_n_cols; ++col) { // Do we have to use an iterator or can we use memory directly? if(SpProxy::must_use_iterator) { typename SpProxy::const_iterator_type it = p.begin_col(col); typename SpProxy::const_iterator_type end = p.begin_col(col + 1); const uword n_zero = p_n_rows - (end.pos() - it.pos()); out.at(0,col) = spop_mean::iterator_mean(it, end, n_zero, eT(0)); } else { out.at(0,col) = spop_mean::direct_mean ( &p.get_values()[p.get_col_ptrs()[col]], p.get_col_ptrs()[col + 1] - p.get_col_ptrs()[col], p_n_rows ); } } } else if(dim == 1) // find the mean in each row { arma_extra_debug_print("spop_mean::apply_noalias(): dim = 1"); out.set_size(p_n_rows, (p_n_cols > 0) ? 1 : 0); if( (p_n_cols == 0) || (p.get_n_nonzero() == 0) ) { return; } for(uword row = 0; row < p_n_rows; ++row) { // We must use an iterator regardless of how it is stored. typename SpProxy::const_row_iterator_type it = p.begin_row(row); typename SpProxy::const_row_iterator_type end = p.end_row(row); const uword n_zero = p_n_cols - (end.pos() - it.pos()); out.at(row,0) = spop_mean::iterator_mean(it, end, n_zero, eT(0)); } } } template inline eT spop_mean::direct_mean ( const eT* const X, const uword length, const uword N ) { arma_extra_debug_sigprint(); typedef typename get_pod_type::result T; const eT result = ((length > 0) && (N > 0)) ? eT(arrayops::accumulate(X, length) / T(N)) : eT(0); return arma_isfinite(result) ? result : spop_mean::direct_mean_robust(X, length, N); } template inline eT spop_mean::direct_mean_robust ( const eT* const X, const uword length, const uword N ) { arma_extra_debug_sigprint(); typedef typename get_pod_type::result T; uword i, j; eT r_mean = eT(0); const uword diff = (N - length); // number of zeros for(i = 0, j = 1; j < length; i += 2, j += 2) { const eT Xi = X[i]; const eT Xj = X[j]; r_mean += (Xi - r_mean) / T(diff + j); r_mean += (Xj - r_mean) / T(diff + j + 1); } if(i < length) { const eT Xi = X[i]; r_mean += (Xi - r_mean) / T(diff + i + 1); } return r_mean; } template inline typename T1::elem_type spop_mean::mean_all(const SpBase& X) { arma_extra_debug_sigprint(); SpProxy p(X.get_ref()); if(SpProxy::must_use_iterator) { typename SpProxy::const_iterator_type it = p.begin(); typename SpProxy::const_iterator_type end = p.end(); return spop_mean::iterator_mean(it, end, p.get_n_elem() - p.get_n_nonzero(), typename T1::elem_type(0)); } else // must_use_iterator == false; that is, we can directly access the values array { return spop_mean::direct_mean(p.get_values(), p.get_n_nonzero(), p.get_n_elem()); } } template inline eT spop_mean::iterator_mean(T1& it, const T1& end, const uword n_zero, const eT junk) { arma_extra_debug_sigprint(); arma_ignore(junk); typedef typename get_pod_type::result T; eT acc = eT(0); T1 backup_it(it); // in case we have to use robust iterator_mean const uword it_begin_pos = it.pos(); while (it != end) { acc += (*it); ++it; } const uword count = n_zero + (it.pos() - it_begin_pos); const eT result = (count > 0) ? eT(acc / T(count)) : eT(0); return arma_isfinite(result) ? result : spop_mean::iterator_mean_robust(backup_it, end, n_zero, eT(0)); } template inline eT spop_mean::iterator_mean_robust(T1& it, const T1& end, const uword n_zero, const eT junk) { arma_extra_debug_sigprint(); arma_ignore(junk); typedef typename get_pod_type::result T; eT r_mean = eT(0); const uword it_begin_pos = it.pos(); while (it != end) { r_mean += ((*it - r_mean) / T(n_zero + (it.pos() - it_begin_pos) + 1)); ++it; } return r_mean; } //! @}