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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_var
//! @{
template<typename T1>
inline
void
op_var::apply(Mat<typename T1::pod_type>& out, const mtOp<typename T1::pod_type, T1, op_var>& in)
{
arma_extra_debug_sigprint();
typedef typename T1::pod_type out_eT;
const uword norm_type = in.aux_uword_a;
const uword dim = in.aux_uword_b;
arma_debug_check( (norm_type > 1), "var(): parameter 'norm_type' must be 0 or 1" );
arma_debug_check( (dim > 1), "var(): parameter 'dim' must be 0 or 1" );
const quasi_unwrap<T1> U(in.m);
if(U.is_alias(out))
{
Mat<out_eT> tmp;
op_var::apply_noalias(tmp, U.M, norm_type, dim);
out.steal_mem(tmp);
}
else
{
op_var::apply_noalias(out, U.M, norm_type, dim);
}
}
template<typename in_eT>
inline
void
op_var::apply_noalias(Mat<typename get_pod_type<in_eT>::result>& out, const Mat<in_eT>& X, const uword norm_type, const uword dim)
{
arma_extra_debug_sigprint();
typedef typename get_pod_type<in_eT>::result out_eT;
const uword X_n_rows = X.n_rows;
const uword X_n_cols = X.n_cols;
if(dim == 0)
{
arma_extra_debug_print("op_var::apply_noalias(): dim = 0");
out.set_size((X_n_rows > 0) ? 1 : 0, X_n_cols);
if(X_n_rows > 0)
{
out_eT* out_mem = out.memptr();
for(uword col=0; col<X_n_cols; ++col)
{
out_mem[col] = op_var::direct_var( X.colptr(col), X_n_rows, norm_type );
}
}
}
else
if(dim == 1)
{
arma_extra_debug_print("op_var::apply_noalias(): dim = 1");
out.set_size(X_n_rows, (X_n_cols > 0) ? 1 : 0);
if(X_n_cols > 0)
{
podarray<in_eT> dat(X_n_cols);
in_eT* dat_mem = dat.memptr();
out_eT* out_mem = out.memptr();
for(uword row=0; row<X_n_rows; ++row)
{
dat.copy_row(X, row);
out_mem[row] = op_var::direct_var( dat_mem, X_n_cols, norm_type );
}
}
}
}
template<typename T1>
inline
typename T1::pod_type
op_var::var_vec(const Base<typename T1::elem_type, T1>& X, const uword norm_type)
{
arma_extra_debug_sigprint();
arma_debug_check( (norm_type > 1), "var(): parameter 'norm_type' must be 0 or 1" );
const quasi_unwrap<T1> U(X.get_ref());
return op_var::direct_var(U.M.memptr(), U.M.n_elem, norm_type);
}
template<typename eT>
inline
typename get_pod_type<eT>::result
op_var::var_vec(const subview_col<eT>& X, const uword norm_type)
{
arma_extra_debug_sigprint();
arma_debug_check( (norm_type > 1), "var(): parameter 'norm_type' must be 0 or 1" );
return op_var::direct_var(X.colptr(0), X.n_rows, norm_type);
}
template<typename eT>
inline
typename get_pod_type<eT>::result
op_var::var_vec(const subview_row<eT>& X, const uword norm_type)
{
arma_extra_debug_sigprint();
arma_debug_check( (norm_type > 1), "var(): parameter 'norm_type' must be 0 or 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;
podarray<eT> tmp(X.n_elem);
eT* tmp_mem = tmp.memptr();
for(uword i=0, col=start_col; col < end_col_p1; ++col, ++i)
{
tmp_mem[i] = A.at(start_row, col);
}
return op_var::direct_var(tmp.memptr(), tmp.n_elem, norm_type);
}
//! find the variance of an array
template<typename eT>
inline
eT
op_var::direct_var(const eT* const X, const uword n_elem, const uword norm_type)
{
arma_extra_debug_sigprint();
if(n_elem >= 2)
{
const eT acc1 = op_mean::direct_mean(X, n_elem);
eT acc2 = eT(0);
eT acc3 = eT(0);
uword i,j;
for(i=0, j=1; j<n_elem; i+=2, j+=2)
{
const eT Xi = X[i];
const eT Xj = X[j];
const eT tmpi = acc1 - Xi;
const eT tmpj = acc1 - Xj;
acc2 += tmpi*tmpi + tmpj*tmpj;
acc3 += tmpi + tmpj;
}
if(i < n_elem)
{
const eT Xi = X[i];
const eT tmpi = acc1 - Xi;
acc2 += tmpi*tmpi;
acc3 += tmpi;
}
const eT norm_val = (norm_type == 0) ? eT(n_elem-1) : eT(n_elem);
const eT var_val = (acc2 - acc3*acc3/eT(n_elem)) / norm_val;
return arma_isfinite(var_val) ? var_val : op_var::direct_var_robust(X, n_elem, norm_type);
}
else
{
return eT(0);
}
}
//! find the variance of an array (robust but slow)
template<typename eT>
inline
eT
op_var::direct_var_robust(const eT* const X, const uword n_elem, const uword norm_type)
{
arma_extra_debug_sigprint();
if(n_elem > 1)
{
eT r_mean = X[0];
eT r_var = eT(0);
for(uword i=1; i<n_elem; ++i)
{
const eT tmp = X[i] - r_mean;
const eT i_plus_1 = eT(i+1);
r_var = eT(i-1)/eT(i) * r_var + (tmp*tmp)/i_plus_1;
r_mean = r_mean + tmp/i_plus_1;
}
return (norm_type == 0) ? r_var : (eT(n_elem-1)/eT(n_elem)) * r_var;
}
else
{
return eT(0);
}
}
//! find the variance of an array (version for complex numbers)
template<typename T>
inline
T
op_var::direct_var(const std::complex<T>* const X, const uword n_elem, const uword norm_type)
{
arma_extra_debug_sigprint();
typedef typename std::complex<T> eT;
if(n_elem >= 2)
{
const eT acc1 = op_mean::direct_mean(X, n_elem);
T acc2 = T(0);
eT acc3 = eT(0);
for(uword i=0; i<n_elem; ++i)
{
const eT tmp = acc1 - X[i];
acc2 += std::norm(tmp);
acc3 += tmp;
}
const T norm_val = (norm_type == 0) ? T(n_elem-1) : T(n_elem);
const T var_val = (acc2 - std::norm(acc3)/T(n_elem)) / norm_val;
return arma_isfinite(var_val) ? var_val : op_var::direct_var_robust(X, n_elem, norm_type);
}
else
{
return T(0);
}
}
//! find the variance of an array (version for complex numbers) (robust but slow)
template<typename T>
inline
T
op_var::direct_var_robust(const std::complex<T>* const X, const uword n_elem, const uword norm_type)
{
arma_extra_debug_sigprint();
typedef typename std::complex<T> eT;
if(n_elem > 1)
{
eT r_mean = X[0];
T r_var = T(0);
for(uword i=1; i<n_elem; ++i)
{
const eT tmp = X[i] - r_mean;
const T i_plus_1 = T(i+1);
r_var = T(i-1)/T(i) * r_var + std::norm(tmp)/i_plus_1;
r_mean = r_mean + tmp/i_plus_1;
}
return (norm_type == 0) ? r_var : (T(n_elem-1)/T(n_elem)) * r_var;
}
else
{
return T(0);
}
}
//! @}
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