451 lines
11 KiB
C++
451 lines
11 KiB
C++
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// Copyright (C) 2009-2015 National ICT Australia (NICTA)
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//
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// This Source Code Form is subject to the terms of the Mozilla Public
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// License, v. 2.0. If a copy of the MPL was not distributed with this
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// file, You can obtain one at http://mozilla.org/MPL/2.0/.
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// -------------------------------------------------------------------
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//
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// Written by Conrad Sanderson - http://conradsanderson.id.au
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//! \addtogroup op_median
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//! @{
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//! \brief
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//! For each row or for each column, find the median value.
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//! The result is stored in a dense matrix that has either one column or one row.
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//! The dimension, for which the medians are found, is set via the median() function.
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template<typename T1>
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inline
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void
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op_median::apply(Mat<typename T1::elem_type>& out, const Op<T1,op_median>& 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 dim = in.aux_uword_a;
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arma_debug_check( (dim > 1), "median(): parameter 'dim' must be 0 or 1" );
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const Proxy<T1> P(in.m);
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typedef typename Proxy<T1>::stored_type P_stored_type;
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const bool is_alias = P.is_alias(out);
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if( (is_Mat<P_stored_type>::value == true) || is_alias )
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{
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const unwrap_check<P_stored_type> tmp(P.Q, is_alias);
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const typename unwrap_check<P_stored_type>::stored_type& X = tmp.M;
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const uword X_n_rows = X.n_rows;
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const uword X_n_cols = X.n_cols;
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if(dim == 0) // in each column
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{
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arma_extra_debug_print("op_median::apply(): dim = 0");
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out.set_size((X_n_rows > 0) ? 1 : 0, X_n_cols);
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if(X_n_rows > 0)
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{
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std::vector<eT> tmp_vec(X_n_rows);
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for(uword col=0; col < X_n_cols; ++col)
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{
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arrayops::copy( &(tmp_vec[0]), X.colptr(col), X_n_rows );
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out[col] = op_median::direct_median(tmp_vec);
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}
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}
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}
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else // in each row
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{
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arma_extra_debug_print("op_median::apply(): dim = 1");
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out.set_size(X_n_rows, (X_n_cols > 0) ? 1 : 0);
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if(X_n_cols > 0)
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{
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std::vector<eT> tmp_vec(X_n_cols);
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for(uword row=0; row < X_n_rows; ++row)
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{
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for(uword col=0; col < X_n_cols; ++col) { tmp_vec[col] = X.at(row,col); }
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out[row] = op_median::direct_median(tmp_vec);
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}
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}
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}
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}
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else
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{
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const uword P_n_rows = P.get_n_rows();
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const uword P_n_cols = P.get_n_cols();
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if(dim == 0) // in each column
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{
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arma_extra_debug_print("op_median::apply(): dim = 0");
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out.set_size((P_n_rows > 0) ? 1 : 0, P_n_cols);
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if(P_n_rows > 0)
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{
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std::vector<eT> tmp_vec(P_n_rows);
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for(uword col=0; col < P_n_cols; ++col)
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{
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for(uword row=0; row < P_n_rows; ++row) { tmp_vec[row] = P.at(row,col); }
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out[col] = op_median::direct_median(tmp_vec);
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}
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}
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}
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else // in each row
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{
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arma_extra_debug_print("op_median::apply(): dim = 1");
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out.set_size(P_n_rows, (P_n_cols > 0) ? 1 : 0);
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if(P_n_cols > 0)
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{
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std::vector<eT> tmp_vec(P_n_cols);
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for(uword row=0; row < P_n_rows; ++row)
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{
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for(uword col=0; col < P_n_cols; ++col) { tmp_vec[col] = P.at(row,col); }
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out[row] = op_median::direct_median(tmp_vec);
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}
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}
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}
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}
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}
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//! Implementation for complex numbers
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template<typename T, typename T1>
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inline
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void
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op_median::apply(Mat< std::complex<T> >& out, const Op<T1,op_median>& in)
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{
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arma_extra_debug_sigprint();
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typedef typename std::complex<T> eT;
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arma_type_check(( is_same_type<eT, typename T1::elem_type>::no ));
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const unwrap_check<T1> tmp(in.m, out);
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const Mat<eT>& X = tmp.M;
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const uword X_n_rows = X.n_rows;
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const uword X_n_cols = X.n_cols;
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const uword dim = in.aux_uword_a;
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arma_debug_check( (dim > 1), "median(): parameter 'dim' must be 0 or 1" );
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if(dim == 0) // in each column
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{
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arma_extra_debug_print("op_median::apply(): dim = 0");
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out.set_size((X_n_rows > 0) ? 1 : 0, X_n_cols);
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if(X_n_rows > 0)
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{
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std::vector< arma_cx_median_packet<T> > tmp_vec(X_n_rows);
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for(uword col=0; col<X_n_cols; ++col)
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{
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const eT* colmem = X.colptr(col);
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for(uword row=0; row<X_n_rows; ++row)
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{
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tmp_vec[row].val = std::abs(colmem[row]);
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tmp_vec[row].index = row;
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}
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uword index1;
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uword index2;
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op_median::direct_cx_median_index(index1, index2, tmp_vec);
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out[col] = op_mean::robust_mean(colmem[index1], colmem[index2]);
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}
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}
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}
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else
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if(dim == 1) // in each row
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{
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arma_extra_debug_print("op_median::apply(): dim = 1");
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out.set_size(X_n_rows, (X_n_cols > 0) ? 1 : 0);
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if(X_n_cols > 0)
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{
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std::vector< arma_cx_median_packet<T> > tmp_vec(X_n_cols);
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for(uword row=0; row<X_n_rows; ++row)
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{
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for(uword col=0; col<X_n_cols; ++col)
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{
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tmp_vec[col].val = std::abs(X.at(row,col));
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tmp_vec[col].index = col;
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}
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uword index1;
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uword index2;
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op_median::direct_cx_median_index(index1, index2, tmp_vec);
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out[row] = op_mean::robust_mean( X.at(row,index1), X.at(row,index2) );
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}
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}
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}
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}
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template<typename T1>
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inline
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typename T1::elem_type
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op_median::median_vec
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(
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const T1& X,
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const typename arma_not_cx<typename T1::elem_type>::result* junk
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)
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{
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arma_extra_debug_sigprint();
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arma_ignore(junk);
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typedef typename T1::elem_type eT;
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typedef typename Proxy<T1>::stored_type P_stored_type;
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const Proxy<T1> P(X);
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const uword n_elem = P.get_n_elem();
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if(n_elem == 0)
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{
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arma_debug_check(true, "median(): object has no elements");
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return Datum<eT>::nan;
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}
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std::vector<eT> tmp_vec(n_elem);
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if(is_Mat<P_stored_type>::value == true)
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{
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const unwrap<P_stored_type> tmp(P.Q);
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const typename unwrap<P_stored_type>::stored_type& Y = tmp.M;
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arrayops::copy( &(tmp_vec[0]), Y.memptr(), n_elem );
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}
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else
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{
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if(Proxy<T1>::prefer_at_accessor == false)
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{
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typedef typename Proxy<T1>::ea_type ea_type;
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ea_type A = P.get_ea();
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for(uword i=0; i<n_elem; ++i) { tmp_vec[i] = A[i]; }
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}
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else
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{
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const uword n_rows = P.get_n_rows();
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const uword n_cols = P.get_n_cols();
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if(n_cols == 1)
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{
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for(uword row=0; row < n_rows; ++row) { tmp_vec[row] = P.at(row,0); }
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}
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else
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if(n_rows == 1)
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{
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for(uword col=0; col < n_cols; ++col) { tmp_vec[col] = P.at(0,col); }
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}
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else
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{
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arma_stop("op_median::median_vec(): expected a vector" );
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}
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}
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}
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return op_median::direct_median(tmp_vec);
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}
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template<typename T1>
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inline
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typename T1::elem_type
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op_median::median_vec
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(
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const T1& X,
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const typename arma_cx_only<typename T1::elem_type>::result* junk
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)
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{
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arma_extra_debug_sigprint();
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arma_ignore(junk);
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typedef typename T1::elem_type eT;
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typedef typename T1::pod_type T;
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const Proxy<T1> P(X);
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const uword n_elem = P.get_n_elem();
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if(n_elem == 0)
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{
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arma_debug_check(true, "median(): object has no elements");
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return Datum<eT>::nan;
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}
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std::vector< arma_cx_median_packet<T> > tmp_vec(n_elem);
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if(Proxy<T1>::prefer_at_accessor == false)
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{
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typedef typename Proxy<T1>::ea_type ea_type;
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ea_type A = P.get_ea();
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for(uword i=0; i<n_elem; ++i)
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{
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tmp_vec[i].val = std::abs( A[i] );
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tmp_vec[i].index = i;
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}
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uword index1;
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uword index2;
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op_median::direct_cx_median_index(index1, index2, tmp_vec);
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return op_mean::robust_mean( A[index1], A[index2] );
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}
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else
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{
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const uword n_rows = P.get_n_rows();
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const uword n_cols = P.get_n_cols();
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if(n_cols == 1)
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{
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for(uword row=0; row < n_rows; ++row)
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{
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tmp_vec[row].val = std::abs( P.at(row,0) );
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tmp_vec[row].index = row;
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}
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uword index1;
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uword index2;
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op_median::direct_cx_median_index(index1, index2, tmp_vec);
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return op_mean::robust_mean( P.at(index1,0), P.at(index2,0) );
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}
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else
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if(n_rows == 1)
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{
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for(uword col=0; col < n_cols; ++col)
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{
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tmp_vec[col].val = std::abs( P.at(0,col) );
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tmp_vec[col].index = col;
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}
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uword index1;
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uword index2;
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op_median::direct_cx_median_index(index1, index2, tmp_vec);
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return op_mean::robust_mean( P.at(0,index1), P.at(0,index2) );
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}
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else
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{
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arma_stop("op_median::median_vec(): expected a vector" );
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return eT(0);
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}
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}
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}
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//! find the median value of a std::vector (contents is modified)
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template<typename eT>
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inline
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eT
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op_median::direct_median(std::vector<eT>& X)
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{
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arma_extra_debug_sigprint();
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const uword n_elem = uword(X.size());
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const uword half = n_elem/2;
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typename std::vector<eT>::iterator first = X.begin();
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typename std::vector<eT>::iterator nth = first + half;
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typename std::vector<eT>::iterator pastlast = X.end();
|
||
|
|
|
||
|
|
std::nth_element(first, nth, pastlast);
|
||
|
|
|
||
|
|
if((n_elem % 2) == 0) // even number of elements
|
||
|
|
{
|
||
|
|
typename std::vector<eT>::iterator start = X.begin();
|
||
|
|
typename std::vector<eT>::iterator pastend = start + half;
|
||
|
|
|
||
|
|
const eT val1 = (*nth);
|
||
|
|
const eT val2 = (*(std::max_element(start, pastend)));
|
||
|
|
|
||
|
|
return op_mean::robust_mean(val1, val2);
|
||
|
|
}
|
||
|
|
else // odd number of elements
|
||
|
|
{
|
||
|
|
return (*nth);
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
template<typename T>
|
||
|
|
inline
|
||
|
|
void
|
||
|
|
op_median::direct_cx_median_index
|
||
|
|
(
|
||
|
|
uword& out_index1,
|
||
|
|
uword& out_index2,
|
||
|
|
std::vector< arma_cx_median_packet<T> >& X
|
||
|
|
)
|
||
|
|
{
|
||
|
|
arma_extra_debug_sigprint();
|
||
|
|
|
||
|
|
typedef arma_cx_median_packet<T> eT;
|
||
|
|
|
||
|
|
const uword n_elem = uword(X.size());
|
||
|
|
const uword half = n_elem/2;
|
||
|
|
|
||
|
|
typename std::vector<eT>::iterator first = X.begin();
|
||
|
|
typename std::vector<eT>::iterator nth = first + half;
|
||
|
|
typename std::vector<eT>::iterator pastlast = X.end();
|
||
|
|
|
||
|
|
std::nth_element(first, nth, pastlast);
|
||
|
|
|
||
|
|
out_index1 = (*nth).index;
|
||
|
|
|
||
|
|
if((n_elem % 2) == 0) // even number of elements
|
||
|
|
{
|
||
|
|
typename std::vector<eT>::iterator start = X.begin();
|
||
|
|
typename std::vector<eT>::iterator pastend = start + half;
|
||
|
|
|
||
|
|
out_index2 = (*(std::max_element(start, pastend))).index;
|
||
|
|
}
|
||
|
|
else // odd number of elements
|
||
|
|
{
|
||
|
|
out_index2 = out_index1;
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
|
||
|
|
//! @}
|
||
|
|
|