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