185 lines
4.6 KiB
C++
185 lines
4.6 KiB
C++
// 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_pinv
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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_pinv::apply(Mat<typename T1::elem_type>& out, const Op<T1,op_pinv>& in)
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{
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arma_extra_debug_sigprint();
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typedef typename T1::pod_type T;
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const T tol = access::tmp_real(in.aux);
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const uword method_id = in.aux_uword_a;
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const bool status = op_pinv::apply_direct(out, in.m, tol, method_id);
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if(status == false)
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{
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out.soft_reset();
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arma_stop_runtime_error("pinv(): svd failed");
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}
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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_pinv::apply_direct(Mat<typename T1::elem_type>& out, const Base<typename T1::elem_type,T1>& expr, typename T1::pod_type tol, const uword method_id)
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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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typedef typename T1::pod_type T;
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arma_debug_check((tol < T(0)), "pinv(): tolerance must be >= 0");
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// method_id = 0 -> default setting
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// method_id = 1 -> use standard algorithm
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// method_id = 2 -> use divide and conquer algorithm
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Mat<eT> A(expr.get_ref());
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const uword n_rows = A.n_rows;
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const uword n_cols = A.n_cols;
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if(A.is_empty()) { out.set_size(n_cols,n_rows); return true; }
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#if defined(ARMA_OPTIMISE_SYMPD)
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const bool try_sympd = (auxlib::crippled_lapack(A) == false) && (tol == T(0)) && (method_id == uword(0)) && sympd_helper::guess_sympd_anysize(A);
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#else
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const bool try_sympd = false;
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#endif
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if(try_sympd)
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{
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arma_extra_debug_print("op_pinv: attempting sympd optimisation");
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out = A;
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const T rcond_threshold = T((std::max)(uword(100), uword(A.n_rows))) * std::numeric_limits<T>::epsilon();
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const bool status = auxlib::inv_sympd_rcond(out, rcond_threshold);
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if(status) { return true; }
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arma_extra_debug_print("op_pinv: sympd optimisation failed");
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// auxlib::inv_sympd_rcond() will fail if A isn't really positive definite or its rcond is below rcond_threshold
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}
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// economical SVD decomposition
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Mat<eT> U;
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Col< T> s;
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Mat<eT> V;
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if(n_cols > n_rows) { A = trans(A); }
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const bool status = ((method_id == uword(0)) || (method_id == uword(2))) ? auxlib::svd_dc_econ(U, s, V, A) : auxlib::svd_econ(U, s, V, A, 'b');
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if(status == false) { 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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// set tolerance to default if it hasn't been specified
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if( (tol == T(0)) && (s_n_elem > 0) )
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{
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tol = (std::max)(n_rows, n_cols) * s_mem[0] * std::numeric_limits<T>::epsilon();
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}
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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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if(count == 0) { out.zeros(n_cols, n_rows); return true; }
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Col<T> s2(count, arma_nozeros_indicator());
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T* s2_mem = s2.memptr();
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uword count2 = 0;
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for(uword i=0; i < s_n_elem; ++i)
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{
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const T val = s_mem[i];
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if(val >= tol) { s2_mem[count2] = (val > T(0)) ? T(T(1) / val) : T(0); ++count2; }
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}
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Mat<eT> tmp;
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if(n_rows >= n_cols)
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{
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// out = ( (V.n_cols > count) ? V.cols(0,count-1) : V ) * diagmat(s2) * trans( (U.n_cols > count) ? U.cols(0,count-1) : U );
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if(count < V.n_cols)
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{
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tmp = V.cols(0,count-1) * diagmat(s2);
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}
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else
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{
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tmp = V * diagmat(s2);
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}
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if(count < U.n_cols)
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{
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out = tmp * trans(U.cols(0,count-1));
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}
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else
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{
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out = tmp * trans(U);
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}
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}
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else
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{
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// out = ( (U.n_cols > count) ? U.cols(0,count-1) : U ) * diagmat(s2) * trans( (V.n_cols > count) ? V.cols(0,count-1) : V );
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if(count < U.n_cols)
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{
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tmp = U.cols(0,count-1) * diagmat(s2);
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}
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else
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{
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tmp = U * diagmat(s2);
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}
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if(count < V.n_cols)
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{
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out = tmp * trans(V.cols(0,count-1));
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}
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else
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{
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out = tmp * trans(V);
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}
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}
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return true;
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}
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//! @}
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