1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
|
// 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_stddev
//! @{
//! \brief
//! For each row or for each column, find the standard deviation.
//! The result is stored in a dense matrix that has either one column or one row.
//! The dimension for which the standard deviations are found is set via the stddev() function.
template<typename T1>
inline
void
op_stddev::apply(Mat<typename T1::pod_type>& out, const mtOp<typename T1::pod_type, T1, op_stddev>& in)
{
arma_extra_debug_sigprint();
typedef typename T1::elem_type in_eT;
typedef typename T1::pod_type out_eT;
const unwrap_check_mixed<T1> tmp(in.m, out);
const Mat<in_eT>& X = tmp.M;
const uword norm_type = in.aux_uword_a;
const uword dim = in.aux_uword_b;
arma_debug_check( (norm_type > 1), "stddev(): parameter 'norm_type' must be 0 or 1" );
arma_debug_check( (dim > 1), "stddev(): parameter 'dim' must be 0 or 1" );
const uword X_n_rows = X.n_rows;
const uword X_n_cols = X.n_cols;
if(dim == 0)
{
arma_extra_debug_print("op_stddev::apply(): 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] = std::sqrt( op_var::direct_var( X.colptr(col), X_n_rows, norm_type ) );
}
}
}
else
if(dim == 1)
{
arma_extra_debug_print("op_stddev::apply(): 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] = std::sqrt( op_var::direct_var( dat_mem, X_n_cols, norm_type) );
}
}
}
}
//! @}
|
