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authorNao Pross <np@0hm.ch>2024-02-12 14:52:43 +0100
committerNao Pross <np@0hm.ch>2024-02-12 14:52:43 +0100
commiteda5bc26f44ee9a6f83dcf8c91f17296d7fc509d (patch)
treebc2efa38ff4e350f9a111ac87065cd7ae9a911c7 /src/armadillo/include/armadillo_bits/op_mean_meat.hpp
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+// 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_mean
+//! @{
+
+
+
+template<typename T1>
+inline
+void
+op_mean::apply(Mat<typename T1::elem_type>& out, const Op<T1,op_mean>& in)
+ {
+ arma_extra_debug_sigprint();
+
+ typedef typename T1::elem_type eT;
+
+ const uword dim = in.aux_uword_a;
+ arma_debug_check( (dim > 1), "mean(): parameter 'dim' must be 0 or 1" );
+
+ const Proxy<T1> P(in.m);
+
+ if(P.is_alias(out) == false)
+ {
+ op_mean::apply_noalias(out, P, dim);
+ }
+ else
+ {
+ Mat<eT> tmp;
+
+ op_mean::apply_noalias(tmp, P, dim);
+
+ out.steal_mem(tmp);
+ }
+ }
+
+
+
+template<typename T1>
+inline
+void
+op_mean::apply_noalias(Mat<typename T1::elem_type>& out, const Proxy<T1>& P, const uword dim)
+ {
+ arma_extra_debug_sigprint();
+
+ if(is_Mat<typename Proxy<T1>::stored_type>::value)
+ {
+ op_mean::apply_noalias_unwrap(out, P, dim);
+ }
+ else
+ {
+ op_mean::apply_noalias_proxy(out, P, dim);
+ }
+ }
+
+
+
+template<typename T1>
+inline
+void
+op_mean::apply_noalias_unwrap(Mat<typename T1::elem_type>& out, const Proxy<T1>& P, const uword dim)
+ {
+ arma_extra_debug_sigprint();
+
+ typedef typename T1::elem_type eT;
+ typedef typename get_pod_type<eT>::result T;
+
+ typedef typename Proxy<T1>::stored_type P_stored_type;
+
+ const unwrap<P_stored_type> tmp(P.Q);
+
+ const typename unwrap<P_stored_type>::stored_type& X = tmp.M;
+
+ const uword X_n_rows = X.n_rows;
+ const uword X_n_cols = X.n_cols;
+
+ if(dim == 0)
+ {
+ out.set_size((X_n_rows > 0) ? 1 : 0, X_n_cols);
+
+ if(X_n_rows == 0) { return; }
+
+ eT* out_mem = out.memptr();
+
+ for(uword col=0; col < X_n_cols; ++col)
+ {
+ out_mem[col] = op_mean::direct_mean( X.colptr(col), X_n_rows );
+ }
+ }
+ else
+ if(dim == 1)
+ {
+ out.zeros(X_n_rows, (X_n_cols > 0) ? 1 : 0);
+
+ if(X_n_cols == 0) { return; }
+
+ eT* out_mem = out.memptr();
+
+ for(uword col=0; col < X_n_cols; ++col)
+ {
+ const eT* col_mem = X.colptr(col);
+
+ for(uword row=0; row < X_n_rows; ++row)
+ {
+ out_mem[row] += col_mem[row];
+ }
+ }
+
+ out /= T(X_n_cols);
+
+ for(uword row=0; row < X_n_rows; ++row)
+ {
+ if(arma_isfinite(out_mem[row]) == false)
+ {
+ out_mem[row] = op_mean::direct_mean_robust( X, row );
+ }
+ }
+ }
+ }
+
+
+
+template<typename T1>
+inline
+void
+op_mean::apply_noalias_proxy(Mat<typename T1::elem_type>& out, const Proxy<T1>& P, const uword dim)
+ {
+ arma_extra_debug_sigprint();
+
+ typedef typename T1::elem_type eT;
+ typedef typename get_pod_type<eT>::result T;
+
+ const uword P_n_rows = P.get_n_rows();
+ const uword P_n_cols = P.get_n_cols();
+
+ if(dim == 0)
+ {
+ out.set_size((P_n_rows > 0) ? 1 : 0, P_n_cols);
+
+ if(P_n_rows == 0) { return; }
+
+ eT* out_mem = out.memptr();
+
+ for(uword col=0; col < P_n_cols; ++col)
+ {
+ eT val1 = eT(0);
+ eT val2 = eT(0);
+
+ uword i,j;
+ for(i=0, j=1; j < P_n_rows; i+=2, j+=2)
+ {
+ val1 += P.at(i,col);
+ val2 += P.at(j,col);
+ }
+
+ if(i < P_n_rows)
+ {
+ val1 += P.at(i,col);
+ }
+
+ out_mem[col] = (val1 + val2) / T(P_n_rows);
+ }
+ }
+ else
+ if(dim == 1)
+ {
+ out.zeros(P_n_rows, (P_n_cols > 0) ? 1 : 0);
+
+ if(P_n_cols == 0) { return; }
+
+ eT* out_mem = out.memptr();
+
+ for(uword col=0; col < P_n_cols; ++col)
+ for(uword row=0; row < P_n_rows; ++row)
+ {
+ out_mem[row] += P.at(row,col);
+ }
+
+ out /= T(P_n_cols);
+ }
+
+ if(out.internal_has_nonfinite())
+ {
+ // TODO: replace with dedicated handling to avoid unwrapping
+ op_mean::apply_noalias_unwrap(out, P, dim);
+ }
+ }
+
+
+
+//
+// cubes
+
+
+
+template<typename T1>
+inline
+void
+op_mean::apply(Cube<typename T1::elem_type>& out, const OpCube<T1,op_mean>& in)
+ {
+ arma_extra_debug_sigprint();
+
+ typedef typename T1::elem_type eT;
+
+ const uword dim = in.aux_uword_a;
+ arma_debug_check( (dim > 2), "mean(): parameter 'dim' must be 0 or 1 or 2" );
+
+ const ProxyCube<T1> P(in.m);
+
+ if(P.is_alias(out) == false)
+ {
+ op_mean::apply_noalias(out, P, dim);
+ }
+ else
+ {
+ Cube<eT> tmp;
+
+ op_mean::apply_noalias(tmp, P, dim);
+
+ out.steal_mem(tmp);
+ }
+ }
+
+
+
+template<typename T1>
+inline
+void
+op_mean::apply_noalias(Cube<typename T1::elem_type>& out, const ProxyCube<T1>& P, const uword dim)
+ {
+ arma_extra_debug_sigprint();
+
+ if(is_Cube<typename ProxyCube<T1>::stored_type>::value)
+ {
+ op_mean::apply_noalias_unwrap(out, P, dim);
+ }
+ else
+ {
+ op_mean::apply_noalias_proxy(out, P, dim);
+ }
+ }
+
+
+
+template<typename T1>
+inline
+void
+op_mean::apply_noalias_unwrap(Cube<typename T1::elem_type>& out, const ProxyCube<T1>& P, const uword dim)
+ {
+ arma_extra_debug_sigprint();
+
+ typedef typename T1::elem_type eT;
+ typedef typename get_pod_type<eT>::result T;
+
+ typedef typename ProxyCube<T1>::stored_type P_stored_type;
+
+ const unwrap_cube<P_stored_type> U(P.Q);
+
+ const Cube<eT>& X = U.M;
+
+ const uword X_n_rows = X.n_rows;
+ const uword X_n_cols = X.n_cols;
+ const uword X_n_slices = X.n_slices;
+
+ if(dim == 0)
+ {
+ out.set_size((X_n_rows > 0) ? 1 : 0, X_n_cols, X_n_slices);
+
+ if(X_n_rows == 0) { return; }
+
+ for(uword slice=0; slice < X_n_slices; ++slice)
+ {
+ eT* out_mem = out.slice_memptr(slice);
+
+ for(uword col=0; col < X_n_cols; ++col)
+ {
+ out_mem[col] = op_mean::direct_mean( X.slice_colptr(slice,col), X_n_rows );
+ }
+ }
+ }
+ else
+ if(dim == 1)
+ {
+ out.zeros(X_n_rows, (X_n_cols > 0) ? 1 : 0, X_n_slices);
+
+ if(X_n_cols == 0) { return; }
+
+ for(uword slice=0; slice < X_n_slices; ++slice)
+ {
+ eT* out_mem = out.slice_memptr(slice);
+
+ for(uword col=0; col < X_n_cols; ++col)
+ {
+ const eT* col_mem = X.slice_colptr(slice,col);
+
+ for(uword row=0; row < X_n_rows; ++row)
+ {
+ out_mem[row] += col_mem[row];
+ }
+ }
+
+ const Mat<eT> tmp('j', X.slice_memptr(slice), X_n_rows, X_n_cols);
+
+ for(uword row=0; row < X_n_rows; ++row)
+ {
+ out_mem[row] /= T(X_n_cols);
+
+ if(arma_isfinite(out_mem[row]) == false)
+ {
+ out_mem[row] = op_mean::direct_mean_robust( tmp, row );
+ }
+ }
+ }
+ }
+ else
+ if(dim == 2)
+ {
+ out.zeros(X_n_rows, X_n_cols, (X_n_slices > 0) ? 1 : 0);
+
+ if(X_n_slices == 0) { return; }
+
+ eT* out_mem = out.memptr();
+
+ for(uword slice=0; slice < X_n_slices; ++slice)
+ {
+ arrayops::inplace_plus(out_mem, X.slice_memptr(slice), X.n_elem_slice );
+ }
+
+ out /= T(X_n_slices);
+
+ podarray<eT> tmp(X_n_slices);
+
+ for(uword col=0; col < X_n_cols; ++col)
+ for(uword row=0; row < X_n_rows; ++row)
+ {
+ if(arma_isfinite(out.at(row,col,0)) == false)
+ {
+ for(uword slice=0; slice < X_n_slices; ++slice)
+ {
+ tmp[slice] = X.at(row,col,slice);
+ }
+
+ out.at(row,col,0) = op_mean::direct_mean_robust(tmp.memptr(), X_n_slices);
+ }
+ }
+ }
+ }
+
+
+
+template<typename T1>
+inline
+void
+op_mean::apply_noalias_proxy(Cube<typename T1::elem_type>& out, const ProxyCube<T1>& P, const uword dim)
+ {
+ arma_extra_debug_sigprint();
+
+ op_mean::apply_noalias_unwrap(out, P, dim);
+
+ // TODO: implement specialised handling
+ }
+
+
+
+
+//
+
+
+
+template<typename eT>
+inline
+eT
+op_mean::direct_mean(const eT* const X, const uword n_elem)
+ {
+ arma_extra_debug_sigprint();
+
+ typedef typename get_pod_type<eT>::result T;
+
+ const eT result = arrayops::accumulate(X, n_elem) / T(n_elem);
+
+ return arma_isfinite(result) ? result : op_mean::direct_mean_robust(X, n_elem);
+ }
+
+
+
+template<typename eT>
+inline
+eT
+op_mean::direct_mean_robust(const eT* const X, const uword n_elem)
+ {
+ arma_extra_debug_sigprint();
+
+ // use an adapted form of the mean finding algorithm from the running_stat class
+
+ typedef typename get_pod_type<eT>::result T;
+
+ uword i,j;
+
+ eT r_mean = eT(0);
+
+ for(i=0, j=1; j<n_elem; i+=2, j+=2)
+ {
+ const eT Xi = X[i];
+ const eT Xj = X[j];
+
+ r_mean = r_mean + (Xi - r_mean)/T(j); // we need i+1, and j is equivalent to i+1 here
+ r_mean = r_mean + (Xj - r_mean)/T(j+1);
+ }
+
+
+ if(i < n_elem)
+ {
+ const eT Xi = X[i];
+
+ r_mean = r_mean + (Xi - r_mean)/T(i+1);
+ }
+
+ return r_mean;
+ }
+
+
+
+template<typename eT>
+inline
+eT
+op_mean::direct_mean(const Mat<eT>& X, const uword row)
+ {
+ arma_extra_debug_sigprint();
+
+ typedef typename get_pod_type<eT>::result T;
+
+ const uword X_n_cols = X.n_cols;
+
+ eT val = eT(0);
+
+ uword i,j;
+ for(i=0, j=1; j < X_n_cols; i+=2, j+=2)
+ {
+ val += X.at(row,i);
+ val += X.at(row,j);
+ }
+
+ if(i < X_n_cols)
+ {
+ val += X.at(row,i);
+ }
+
+ const eT result = val / T(X_n_cols);
+
+ return arma_isfinite(result) ? result : op_mean::direct_mean_robust(X, row);
+ }
+
+
+
+template<typename eT>
+inline
+eT
+op_mean::direct_mean_robust(const Mat<eT>& X, const uword row)
+ {
+ arma_extra_debug_sigprint();
+
+ typedef typename get_pod_type<eT>::result T;
+
+ const uword X_n_cols = X.n_cols;
+
+ eT r_mean = eT(0);
+
+ for(uword col=0; col < X_n_cols; ++col)
+ {
+ r_mean = r_mean + (X.at(row,col) - r_mean)/T(col+1);
+ }
+
+ return r_mean;
+ }
+
+
+
+template<typename eT>
+inline
+eT
+op_mean::mean_all(const subview<eT>& X)
+ {
+ arma_extra_debug_sigprint();
+
+ typedef typename get_pod_type<eT>::result T;
+
+ const uword X_n_rows = X.n_rows;
+ const uword X_n_cols = X.n_cols;
+ const uword X_n_elem = X.n_elem;
+
+ if(X_n_elem == 0)
+ {
+ arma_debug_check(true, "mean(): object has no elements");
+
+ return Datum<eT>::nan;
+ }
+
+ eT val = eT(0);
+
+ if(X_n_rows == 1)
+ {
+ const Mat<eT>& A = X.m;
+
+ const uword start_row = X.aux_row1;
+ const uword start_col = X.aux_col1;
+
+ const uword end_col_p1 = start_col + X_n_cols;
+
+ uword i,j;
+ for(i=start_col, j=start_col+1; j < end_col_p1; i+=2, j+=2)
+ {
+ val += A.at(start_row, i);
+ val += A.at(start_row, j);
+ }
+
+ if(i < end_col_p1)
+ {
+ val += A.at(start_row, i);
+ }
+ }
+ else
+ {
+ for(uword col=0; col < X_n_cols; ++col)
+ {
+ val += arrayops::accumulate(X.colptr(col), X_n_rows);
+ }
+ }
+
+ const eT result = val / T(X_n_elem);
+
+ return arma_isfinite(result) ? result : op_mean::mean_all_robust(X);
+ }
+
+
+
+template<typename eT>
+inline
+eT
+op_mean::mean_all_robust(const subview<eT>& X)
+ {
+ arma_extra_debug_sigprint();
+
+ typedef typename get_pod_type<eT>::result T;
+
+ const uword X_n_rows = X.n_rows;
+ const uword X_n_cols = X.n_cols;
+
+ const uword start_row = X.aux_row1;
+ const uword start_col = X.aux_col1;
+
+ const uword end_row_p1 = start_row + X_n_rows;
+ const uword end_col_p1 = start_col + X_n_cols;
+
+ const Mat<eT>& A = X.m;
+
+
+ eT r_mean = eT(0);
+
+ if(X_n_rows == 1)
+ {
+ uword i=0;
+
+ for(uword col = start_col; col < end_col_p1; ++col, ++i)
+ {
+ r_mean = r_mean + (A.at(start_row,col) - r_mean)/T(i+1);
+ }
+ }
+ else
+ {
+ uword i=0;
+
+ for(uword col = start_col; col < end_col_p1; ++col)
+ for(uword row = start_row; row < end_row_p1; ++row, ++i)
+ {
+ r_mean = r_mean + (A.at(row,col) - r_mean)/T(i+1);
+ }
+ }
+
+ return r_mean;
+ }
+
+
+
+template<typename eT>
+inline
+eT
+op_mean::mean_all(const diagview<eT>& X)
+ {
+ arma_extra_debug_sigprint();
+
+ typedef typename get_pod_type<eT>::result T;
+
+ const uword X_n_elem = X.n_elem;
+
+ if(X_n_elem == 0)
+ {
+ arma_debug_check(true, "mean(): object has no elements");
+
+ return Datum<eT>::nan;
+ }
+
+ eT val = eT(0);
+
+ for(uword i=0; i<X_n_elem; ++i)
+ {
+ val += X[i];
+ }
+
+ const eT result = val / T(X_n_elem);
+
+ return arma_isfinite(result) ? result : op_mean::mean_all_robust(X);
+ }
+
+
+
+template<typename eT>
+inline
+eT
+op_mean::mean_all_robust(const diagview<eT>& X)
+ {
+ arma_extra_debug_sigprint();
+
+ typedef typename get_pod_type<eT>::result T;
+
+ const uword X_n_elem = X.n_elem;
+
+ eT r_mean = eT(0);
+
+ for(uword i=0; i<X_n_elem; ++i)
+ {
+ r_mean = r_mean + (X[i] - r_mean)/T(i+1);
+ }
+
+ return r_mean;
+ }
+
+
+
+template<typename T1>
+inline
+typename T1::elem_type
+op_mean::mean_all(const Op<T1,op_vectorise_col>& X)
+ {
+ arma_extra_debug_sigprint();
+
+ return op_mean::mean_all(X.m);
+ }
+
+
+
+template<typename T1>
+inline
+typename T1::elem_type
+op_mean::mean_all(const Base<typename T1::elem_type, T1>& X)
+ {
+ arma_extra_debug_sigprint();
+
+ typedef typename T1::elem_type eT;
+
+ const quasi_unwrap<T1> tmp(X.get_ref());
+ const Mat<eT>& A = tmp.M;
+
+ const uword A_n_elem = A.n_elem;
+
+ if(A_n_elem == 0)
+ {
+ arma_debug_check(true, "mean(): object has no elements");
+
+ return Datum<eT>::nan;
+ }
+
+ return op_mean::direct_mean(A.memptr(), A_n_elem);
+ }
+
+
+
+template<typename eT>
+arma_inline
+eT
+op_mean::robust_mean(const eT A, const eT B)
+ {
+ return A + (B - A)/eT(2);
+ }
+
+
+
+template<typename T>
+arma_inline
+std::complex<T>
+op_mean::robust_mean(const std::complex<T>& A, const std::complex<T>& B)
+ {
+ return A + (B - A)/T(2);
+ }
+
+
+
+//! @}
+