Oops, correct previous partial commit.
[libdai.git] / include / dai / jtree.h
1 /* Copyright (C) 2006-2008 Joris Mooij [joris dot mooij at tuebingen dot mpg dot de]
2 Radboud University Nijmegen, The Netherlands /
3 Max Planck Institute for Biological Cybernetics, Germany
4
5 This file is part of libDAI.
6
7 libDAI is free software; you can redistribute it and/or modify
8 it under the terms of the GNU General Public License as published by
9 the Free Software Foundation; either version 2 of the License, or
10 (at your option) any later version.
11
12 libDAI is distributed in the hope that it will be useful,
13 but WITHOUT ANY WARRANTY; without even the implied warranty of
14 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
15 GNU General Public License for more details.
16
17 You should have received a copy of the GNU General Public License
18 along with libDAI; if not, write to the Free Software
19 Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
20 */
21
22
23 /// \file
24 /// \brief Defines class JTree
25 /// \todo Improve documentation
26
27
28 #ifndef __defined_libdai_jtree_h
29 #define __defined_libdai_jtree_h
30
31
32 #include <vector>
33 #include <string>
34 #include <dai/daialg.h>
35 #include <dai/varset.h>
36 #include <dai/regiongraph.h>
37 #include <dai/factorgraph.h>
38 #include <dai/clustergraph.h>
39 #include <dai/weightedgraph.h>
40 #include <dai/enum.h>
41 #include <dai/properties.h>
42
43
44 namespace dai {
45
46
47 /// Exact inference algorithm using junction tree
48 class JTree : public DAIAlgRG {
49 private:
50 std::vector<std::vector<Factor> > _mes;
51 double _logZ;
52
53 public:
54 /// Rooted tree
55 DEdgeVec RTree;
56
57 /// Outer region beliefs
58 std::vector<Factor> Qa;
59
60 /// Inner region beliefs
61 std::vector<Factor> Qb;
62
63 /// Parameters of this inference algorithm
64 struct Properties {
65 /// Enumeration of possible JTree updates
66 DAI_ENUM(UpdateType,HUGIN,SHSH)
67
68 /// Verbosity
69 size_t verbose;
70
71 /// Type of updates
72 UpdateType updates;
73 } props;
74
75 /// Name of this inference algorithm
76 static const char *Name;
77
78 public:
79 /// Default constructor
80 JTree() : DAIAlgRG(), _mes(), _logZ(), RTree(), Qa(), Qb(), props() {}
81
82 /// Copy constructor
83 JTree( const JTree &x ) : DAIAlgRG(x), _mes(x._mes), _logZ(x._logZ), RTree(x.RTree), Qa(x.Qa), Qb(x.Qb), props(x.props) {}
84
85 /// Assignment operator
86 JTree& operator=( const JTree &x ) {
87 if( this != &x ) {
88 DAIAlgRG::operator=( x );
89 _mes = x._mes;
90 _logZ = x._logZ;
91 RTree = x.RTree;
92 Qa = x.Qa;
93 Qb = x.Qb;
94 props = x.props;
95 }
96 return *this;
97 }
98
99 /// Construct from FactorGraph fg and PropertySet opts
100 JTree( const FactorGraph &fg, const PropertySet &opts, bool automatic=true );
101
102
103 /// @name General InfAlg interface
104 //@{
105 virtual JTree* clone() const { return new JTree(*this); }
106 virtual JTree* create() const { return new JTree(); }
107 virtual std::string identify() const;
108 virtual Factor belief( const Var &n ) const;
109 virtual Factor belief( const VarSet &ns ) const;
110 virtual std::vector<Factor> beliefs() const;
111 virtual Real logZ() const;
112 virtual void init() {}
113 virtual void init( const VarSet &/*ns*/ ) {}
114 virtual double run();
115 virtual double maxDiff() const { return 0.0; }
116 virtual size_t Iterations() const { return 1UL; }
117 //@}
118
119
120 /// @name Additional interface specific for JTree
121 //@{
122 void GenerateJT( const std::vector<VarSet> &Cliques );
123
124 /// Returns reference the message from outer region alpha to its _beta'th neighboring inner region
125 Factor & message( size_t alpha, size_t _beta ) { return _mes[alpha][_beta]; }
126 /// Returns const reference to the message from outer region alpha to its _beta'th neighboring inner region
127 const Factor & message( size_t alpha, size_t _beta ) const { return _mes[alpha][_beta]; }
128
129 /// Runs junction-tree with HUGIN updates
130 void runHUGIN();
131
132 /// Runs junction-tree with Shafer-Shenoy updates
133 void runShaferShenoy();
134
135 /// Finds an efficient tree for calculating the marginal of some variables
136 size_t findEfficientTree( const VarSet& ns, DEdgeVec &Tree, size_t PreviousRoot=(size_t)-1 ) const;
137
138 /// Calculates the marginal of a set of variables
139 Factor calcMarginal( const VarSet& ns );
140 //@}
141
142 private:
143 void setProperties( const PropertySet &opts );
144 PropertySet getProperties() const;
145 std::string printProperties() const;
146 };
147
148
149 /// Calculates upper bound to the treewidth of a FactorGraph
150 /** \relates JTree
151 * \return a pair (number of variables in largest clique, number of states in largest clique)
152 */
153 std::pair<size_t,size_t> treewidth( const FactorGraph & fg );
154
155
156 } // end of namespace dai
157
158
159 #endif