aGrUM
0.20.2
a C++ library for (probabilistic) graphical models
aprioriSmoothing_tpl.h
Go to the documentation of this file.
1
/**
2
*
3
* Copyright 2005-2020 Pierre-Henri WUILLEMIN(@LIP6) & Christophe GONZALES(@AMU)
4
* info_at_agrum_dot_org
5
*
6
* This library is free software: you can redistribute it and/or modify
7
* it under the terms of the GNU Lesser General Public License as published by
8
* the Free Software Foundation, either version 3 of the License, or
9
* (at your option) any later version.
10
*
11
* This library is distributed in the hope that it will be useful,
12
* but WITHOUT ANY WARRANTY; without even the implied warranty of
13
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
14
* GNU Lesser General Public License for more details.
15
*
16
* You should have received a copy of the GNU Lesser General Public License
17
* along with this library. If not, see <http://www.gnu.org/licenses/>.
18
*
19
*/
20
21
22
/** @file
23
* @brief the smooth a priori: adds a weight w to all the countings
24
*
25
* @author Christophe GONZALES(@AMU) and Pierre-Henri WUILLEMIN(@LIP6)
26
*/
27
#
ifndef
DOXYGEN_SHOULD_SKIP_THIS
28
29
namespace
gum
{
30
31
namespace
learning
{
32
33
34
/// default constructor
35
template
<
template
<
typename
>
class
ALLOC >
36
INLINE AprioriSmoothing<
ALLOC
>::
AprioriSmoothing
(
37
const
DatabaseTable
<
ALLOC
>&
database
,
38
const
Bijection
<
NodeId
,
std
::
size_t
,
ALLOC
<
std
::
size_t
> >&
39
nodeId2columns
,
40
const
typename
AprioriSmoothing
<
ALLOC
>::
allocator_type
&
alloc
) :
41
Apriori
<
ALLOC
>(
database
,
nodeId2columns
,
alloc
) {
42
GUM_CONSTRUCTOR
(
AprioriSmoothing
);
43
}
44
45
46
/// copy constructor with a given allocator
47
template
<
template
<
typename
>
class
ALLOC
>
48
INLINE
AprioriSmoothing
<
ALLOC
>::
AprioriSmoothing
(
49
const
AprioriSmoothing
<
ALLOC
>&
from
,
50
const
typename
AprioriSmoothing
<
ALLOC
>::
allocator_type
&
alloc
) :
51
Apriori
<
ALLOC
>(
from
,
alloc
) {
52
GUM_CONS_CPY
(
AprioriSmoothing
);
53
}
54
55
56
/// copy constructor
57
template
<
template
<
typename
>
class
ALLOC
>
58
INLINE
AprioriSmoothing
<
ALLOC
>::
AprioriSmoothing
(
59
const
AprioriSmoothing
<
ALLOC
>&
from
) :
60
AprioriSmoothing
<
ALLOC
>(
from
,
from
.
getAllocator
()) {}
61
62
63
/// move constructor with a given allocator
64
template
<
template
<
typename
>
class
ALLOC
>
65
INLINE
AprioriSmoothing
<
ALLOC
>::
AprioriSmoothing
(
66
AprioriSmoothing
<
ALLOC
>&&
from
,
67
const
typename
AprioriSmoothing
<
ALLOC
>::
allocator_type
&
alloc
) :
68
Apriori
<
ALLOC
>(
std
::
move
(
from
),
alloc
) {
69
GUM_CONS_MOV
(
AprioriSmoothing
);
70
}
71
72
73
/// move constructor
74
template
<
template
<
typename
>
class
ALLOC
>
75
INLINE
AprioriSmoothing
<
ALLOC
>::
AprioriSmoothing
(
76
AprioriSmoothing
<
ALLOC
>&&
from
) :
77
AprioriSmoothing
<
ALLOC
>(
std
::
move
(
from
),
from
.
getAllocator
()) {}
78
79
80
/// virtual copy constructor with a given allocator
81
template
<
template
<
typename
>
class
ALLOC
>
82
AprioriSmoothing
<
ALLOC
>*
AprioriSmoothing
<
ALLOC
>::
clone
(
83
const
typename
AprioriSmoothing
<
ALLOC
>::
allocator_type
&
alloc
)
const
{
84
ALLOC
<
AprioriSmoothing
<
ALLOC
> >
allocator
(
alloc
);
85
AprioriSmoothing
<
ALLOC
>*
apriori
=
allocator
.
allocate
(1);
86
try
{
87
allocator
.
construct
(
apriori
, *
this
,
alloc
);
88
}
catch
(...) {
89
allocator
.
deallocate
(
apriori
, 1);
90
throw
;
91
}
92
93
return
apriori
;
94
}
95
96
97
/// virtual copy constructor
98
template
<
template
<
typename
>
class
ALLOC
>
99
INLINE
AprioriSmoothing
<
ALLOC
>*
AprioriSmoothing
<
ALLOC
>::
clone
()
const
{
100
return
clone
(
this
->
getAllocator
());
101
}
102
103
104
/// destructor
105
template
<
template
<
typename
>
class
ALLOC
>
106
INLINE
AprioriSmoothing
<
ALLOC
>::~
AprioriSmoothing
() {
107
GUM_DESTRUCTOR
(
AprioriSmoothing
);
108
}
109
110
111
/// copy operator
112
template
<
template
<
typename
>
class
ALLOC
>
113
INLINE
AprioriSmoothing
<
ALLOC
>&
AprioriSmoothing
<
ALLOC
>::
operator
=(
114
const
AprioriSmoothing
<
ALLOC
>&
from
) {
115
Apriori
<
ALLOC
>::
operator
=(
from
);
116
return
*
this
;
117
}
118
119
120
/// move operator
121
template
<
template
<
typename
>
class
ALLOC
>
122
INLINE
AprioriSmoothing
<
ALLOC
>&
123
AprioriSmoothing
<
ALLOC
>::
operator
=(
AprioriSmoothing
<
ALLOC
>&&
from
) {
124
Apriori
<
ALLOC
>::
operator
=(
std
::
move
(
from
));
125
return
*
this
;
126
}
127
128
129
/// indicates whether an apriori is of a certain type
130
template
<
template
<
typename
>
class
ALLOC
>
131
INLINE
bool
AprioriSmoothing
<
ALLOC
>::
isOfType
(
const
std
::
string
&
type
) {
132
return
AprioriSmoothingType
::
isOfType
(
type
);
133
}
134
135
136
/// returns the type of the apriori
137
template
<
template
<
typename
>
class
ALLOC
>
138
INLINE
const
std
::
string
&
AprioriSmoothing
<
ALLOC
>::
getType
()
const
{
139
return
AprioriSmoothingType
::
type
;
140
}
141
142
143
/// indicates whether the apriori is potentially informative
144
template
<
template
<
typename
>
class
ALLOC
>
145
INLINE
bool
AprioriSmoothing
<
ALLOC
>::
isInformative
()
const
{
146
return
this
->
weight_
!= 0.0;
147
}
148
149
150
/// returns the apriori vector all the variables in the idset
151
template
<
template
<
typename
>
class
ALLOC
>
152
INLINE
void
AprioriSmoothing
<
ALLOC
>::
addAllApriori
(
153
const
IdCondSet
<
ALLOC
>&
idset
,
154
std
::
vector
<
double
,
ALLOC
<
double
> >&
counts
) {
155
// if the idset is empty or the weight is zero, the apriori is also empty
156
if
(
idset
.
empty
() || (
this
->
weight_
== 0.0))
return
;
157
158
// otherwise, add the weight to all the cells in the counting vector
159
for
(
auto
&
count
:
counts
)
160
count
+=
this
->
weight_
;
161
}
162
163
164
/// returns the apriori vector over only the conditioning set of an idset
165
template
<
template
<
typename
>
class
ALLOC
>
166
void
AprioriSmoothing
<
ALLOC
>::
addConditioningApriori
(
167
const
IdCondSet
<
ALLOC
>&
idset
,
168
std
::
vector
<
double
,
ALLOC
<
double
> >&
counts
) {
169
// if the conditioning set is empty or the weight is equal to zero,
170
// the apriori is also empty
171
if
((
idset
.
size
() ==
idset
.
nbLHSIds
()) || (
this
->
weight_
== 0.0)
172
|| (
idset
.
nbLHSIds
() ==
std
::
size_t
(0)))
173
return
;
174
175
// compute the weight of the conditioning set
176
double
weight
=
this
->
weight_
;
177
if
(
this
->
nodeId2columns_
.
empty
()) {
178
for
(
std
::
size_t
i
=
std
::
size_t
(0);
i
<
idset
.
nbLHSIds
(); ++
i
) {
179
weight
*=
this
->
database_
->
domainSize
(
idset
[
i
]);
180
}
181
}
else
{
182
for
(
std
::
size_t
i
=
std
::
size_t
(0);
i
<
idset
.
nbLHSIds
(); ++
i
) {
183
weight
*=
this
->
database_
->
domainSize
(
184
this
->
nodeId2columns_
.
second
(
idset
[
i
]));
185
}
186
}
187
188
// add the weight to the counting vector
189
for
(
auto
&
count
:
counts
)
190
count
+=
weight
;
191
}
192
193
194
}
/* namespace learning */
195
196
}
/* namespace gum */
197
198
#
endif
/* DOXYGEN_SHOULD_SKIP_THIS */
gum::Set::emplace
INLINE void emplace(Args &&... args)
Definition:
set_tpl.h:669
gum::learning::genericBNLearner::Database::Database
Database(const std::string &filename, const BayesNet< GUM_SCALAR > &bn, const std::vector< std::string > &missing_symbols)
Definition:
genericBNLearner_tpl.h:31