125 lines
3.0 KiB
C++
125 lines
3.0 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_cor
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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_cor::apply(Mat<typename T1::elem_type>& out, const Op<T1,op_cor>& in)
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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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const uword norm_type = in.aux_uword_a;
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const unwrap<T1> U(in.m);
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const Mat<eT>& A = U.M;
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if(A.n_elem == 0)
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{
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out.reset();
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return;
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}
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if(A.n_elem == 1)
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{
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out.set_size(1,1);
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out[0] = eT(1);
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return;
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}
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const Mat<eT>& AA = (A.n_rows == 1)
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? Mat<eT>(const_cast<eT*>(A.memptr()), A.n_cols, A.n_rows, false, false)
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: Mat<eT>(const_cast<eT*>(A.memptr()), A.n_rows, A.n_cols, false, false);
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const uword N = AA.n_rows;
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const eT norm_val = (norm_type == 0) ? ( (N > 1) ? eT(N-1) : eT(1) ) : eT(N);
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const Mat<eT> tmp = AA.each_row() - mean(AA,0);
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out = tmp.t() * tmp;
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out /= norm_val;
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const Col<eT> s = sqrt(out.diag());
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out /= (s * s.t()); // TODO: check for zeros in s?
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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_cor::apply(Mat<typename T1::elem_type>& out, const Op< Op<T1,op_htrans>, op_cor>& in)
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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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const uword norm_type = in.aux_uword_a;
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if(is_cx<eT>::yes)
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{
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const Mat<eT> tmp = in.m; // force the evaluation of Op<T1,op_htrans>
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out = cor(tmp, norm_type);
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}
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else
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{
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const unwrap<T1> U(in.m.m);
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const Mat<eT>& A = U.M;
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if(A.n_elem == 0)
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{
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out.reset();
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return;
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}
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if(A.n_elem == 1)
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{
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out.set_size(1,1);
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out[0] = eT(1);
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return;
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}
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const Mat<eT>& AA = (A.n_cols == 1)
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? Mat<eT>(const_cast<eT*>(A.memptr()), A.n_cols, A.n_rows, false, false)
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: Mat<eT>(const_cast<eT*>(A.memptr()), A.n_rows, A.n_cols, false, false);
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const uword N = AA.n_cols;
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const eT norm_val = (norm_type == 0) ? ( (N > 1) ? eT(N-1) : eT(1) ) : eT(N);
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const Mat<eT> tmp = AA.each_col() - mean(AA,1);
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out = tmp * tmp.t();
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out /= norm_val;
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const Col<eT> s = sqrt(out.diag());
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out /= (s * s.t()); // TODO: check for zeros in s?
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}
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}
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//! @}
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