Cleaned up variable elimination code in ClusterGraph
[libdai.git] / include / dai / mf.h
1 /* This file is part of libDAI - http://www.libdai.org/
2 *
3 * libDAI is licensed under the terms of the GNU General Public License version
4 * 2, or (at your option) any later version. libDAI is distributed without any
5 * warranty. See the file COPYING for more details.
6 *
7 * Copyright (C) 2006-2009 Joris Mooij [joris dot mooij at libdai dot org]
8 * Copyright (C) 2006-2007 Radboud University Nijmegen, The Netherlands
9 */
10
11
12 /// \file
13 /// \brief Defines class MF which implements the Mean Field algorithm
14
15
16 #ifndef __defined_libdai_mf_h
17 #define __defined_libdai_mf_h
18
19
20 #include <string>
21 #include <dai/daialg.h>
22 #include <dai/factorgraph.h>
23 #include <dai/properties.h>
24
25
26 namespace dai {
27
28
29 /// Approximate inference algorithm "Mean Field"
30 /** The Mean Field algorithm iteratively calculates approximations of
31 * single variable marginals (beliefs). The update equation for
32 * a single belief \f$b_i\f$ is given by:
33 * \f[ b_i^{\mathrm{new}}(x_i) \propto \prod_{I\in N_i} \exp \left( \sum_{x_{N_I \setminus \{i\}}} \log f_I(x_I) \prod_{j \in N_I \setminus \{i\}} b_j(x_j) \right) \f]
34 * These update equations are performed for all variables until convergence.
35 */
36 class MF : public DAIAlgFG {
37 private:
38 /// Current approximations of single variable marginals
39 std::vector<Factor> _beliefs;
40 /// Maximum difference encountered so far
41 Real _maxdiff;
42 /// Number of iterations needed
43 size_t _iters;
44
45 public:
46 /// Parameters for MF
47 struct Properties {
48 /// Verbosity (amount of output sent to stderr)
49 size_t verbose;
50
51 /// Maximum number of iterations
52 size_t maxiter;
53
54 /// Tolerance for convergence test
55 Real tol;
56
57 /// Damping constant (0.0 means no damping, 1.0 is maximum damping)
58 Real damping;
59 } props;
60
61 /// Name of this inference algorithm
62 static const char *Name;
63
64 public:
65 /// \name Constructors/destructors
66 //@{
67 /// Default constructor
68 MF() : DAIAlgFG(), _beliefs(), _maxdiff(0.0), _iters(0U), props() {}
69
70 /// Construct from FactorGraph \a fg and PropertySet \a opts
71 /** \param opts Parameters @see Properties
72 */
73 MF( const FactorGraph &fg, const PropertySet &opts ) : DAIAlgFG(fg), _beliefs(), _maxdiff(0.0), _iters(0U), props() {
74 setProperties( opts );
75 construct();
76 }
77 //@}
78
79 /// \name General InfAlg interface
80 //@{
81 virtual MF* clone() const { return new MF(*this); }
82 virtual std::string identify() const;
83 virtual Factor belief( const Var &v ) const { return beliefV( findVar( v ) ); }
84 virtual Factor belief( const VarSet &vs ) const;
85 virtual Factor beliefV( size_t i ) const;
86 virtual std::vector<Factor> beliefs() const;
87 virtual Real logZ() const;
88 virtual void init();
89 virtual void init( const VarSet &ns );
90 virtual Real run();
91 virtual Real maxDiff() const { return _maxdiff; }
92 virtual size_t Iterations() const { return _iters; }
93 virtual void setProperties( const PropertySet &opts );
94 virtual PropertySet getProperties() const;
95 virtual std::string printProperties() const;
96 //@}
97
98 private:
99 /// Helper function for constructors
100 void construct();
101
102 /// Calculates an updated belief of variable \a i
103 Factor calcNewBelief( size_t i );
104 };
105
106
107 } // end of namespace dai
108
109
110 #endif