// 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 op_rank //! @{ template inline bool op_rank::apply(uword& out, const Base& expr, const typename T1::pod_type tol) { arma_extra_debug_sigprint(); typedef typename T1::elem_type eT; Mat A(expr.get_ref()); if(A.is_empty()) { out = uword(0); return true; } if(is_op_diagmat::value || A.is_diagmat()) { arma_extra_debug_print("op_rank::apply(): detected diagonal matrix"); return op_rank::apply_diag(out, A, tol); } bool do_sym = false; if((arma_config::optimise_sym) && (auxlib::crippled_lapack(A) == false) && (A.n_rows >= (is_cx::yes ? uword(64) : uword(128)))) { bool is_approx_sym = false; bool is_approx_sympd = false; sym_helper::analyse_matrix(is_approx_sym, is_approx_sympd, A); do_sym = (is_cx::no) ? (is_approx_sym) : (is_approx_sym && is_approx_sympd); } if(do_sym) { arma_extra_debug_print("op_rank::apply(): symmetric/hermitian optimisation"); return op_rank::apply_sym(out, A, tol); } return op_rank::apply_gen(out, A, tol); } template inline bool op_rank::apply_diag(uword& out, Mat& A, typename get_pod_type::result tol) { arma_extra_debug_sigprint(); typedef typename get_pod_type::result T; const uword N = (std::min)(A.n_rows, A.n_cols); podarray diag_abs_vals(N); T max_abs_Aii = T(0); for(uword i=0; i max_abs_Aii) ? abs_Aii : max_abs_Aii; } // set tolerance to default if it hasn't been specified if(tol == T(0)) { tol = (std::max)(A.n_rows, A.n_cols) * max_abs_Aii * std::numeric_limits::epsilon(); } uword count = 0; for(uword i=0; i tol) ? uword(1) : uword(0); } out = count; return true; } template inline bool op_rank::apply_sym(uword& out, Mat& A, typename get_pod_type::result tol) { arma_extra_debug_sigprint(); typedef typename get_pod_type::result T; if(A.is_square() == false) { out = uword(0); return false; } Col v; const bool status = auxlib::eig_sym(v, A); if(status == false) { out = uword(0); return false; } const uword v_n_elem = v.n_elem; T* v_mem = v.memptr(); if(v_n_elem == 0) { out = uword(0); return true; } T max_abs_v = T(0); for(uword i=0; i < v_n_elem; ++i) { const T val = std::abs(v_mem[i]); v_mem[i] = val; if(val > max_abs_v) { max_abs_v = val; } } // set tolerance to default if it hasn't been specified if(tol == T(0)) { tol = (std::max)(A.n_rows, A.n_cols) * max_abs_v * std::numeric_limits::epsilon(); } uword count = 0; for(uword i=0; i < v_n_elem; ++i) { count += (v_mem[i] > tol) ? uword(1) : uword(0); } out = count; return true; } template inline bool op_rank::apply_gen(uword& out, Mat& A, typename get_pod_type::result tol) { arma_extra_debug_sigprint(); typedef typename get_pod_type::result T; Col s; const bool status = auxlib::svd_dc(s, A); if(status == false) { out = uword(0); return false; } const uword s_n_elem = s.n_elem; const T* s_mem = s.memptr(); if(s_n_elem == 0) { out = uword(0); return true; } // set tolerance to default if it hasn't been specified if(tol == T(0)) { tol = (std::max)(A.n_rows, A.n_cols) * s_mem[0] * std::numeric_limits::epsilon(); } uword count = 0; for(uword i=0; i < s_n_elem; ++i) { count += (s_mem[i] > tol) ? uword(1) : uword(0); } out = count; return true; } //! @}