include/dai/factorgraph.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 the FactorGraph class
  25 /// \todo Improve documentation
  26
  27
  28 #ifndef __defined_libdai_factorgraph_h
  29 #define __defined_libdai_factorgraph_h
  30
  31
  32 #include <iostream>
  33 #include <map>
  34 #include <dai/bipgraph.h>
  35 #include <dai/factor.h>
  36
  37
  38 namespace dai {
  39
  40
  41 /// Represents a factor graph.
  42 /** Both Bayesian Networks and Markov random fields can be represented in a
  43  *  unifying representation, called <em>factor graph</em> [\ref KFL01],
  44  *  implemented in libDAI by the FactorGraph class.
  45  *
  46  *  Consider a probability distribution over \f$N\f$ discrete random variables
  47  *  \f$x_0,x_1,\dots,x_N\f$ that factorizes as a product of factors, each of
  48  *  which depends on some subset of the variables:
  49  *  \f[
  50  *    P(x_0,x_1,\dots,x_N) = \frac{1}{Z} \prod_{I=0}^M f_I(x_I), \qquad
  51  *    Z = \sum_{x_0}\dots\sum_{x_N} \prod_{I=0}^M f_I(X_I).
  52  *  \f]
  53  *  Each factor \f$f_I\f$ is a function from an associated subset
  54  *  of variables \f$X_I \subset \{x_0,x_1,\dots,x_N\}\f$ to the nonnegative
  55  *  real numbers.
  56  *
  57  *  For a Bayesian network, each factor corresponds to a (conditional)
  58  *  probability table, whereas for a Markov random field, each factor
  59  *  corresponds to a maximal clique of the undirected graph.
  60  *
  61  *  Factor graphs explicitly express the factorization structure of the
  62  *  corresponding probability distribution.
  63  */
  64 class FactorGraph {
  65     public:
  66         /// Stores the neighborhood structure
  67         BipartiteGraph                    G;
  68
  69         /// Shorthand for BipartiteGraph::Neighbor
  70         typedef BipartiteGraph::Neighbor  Neighbor;
  71
  72         /// Shorthand for BipartiteGraph::Neighbors
  73         typedef BipartiteGraph::Neighbors Neighbors;
  74
  75         /// Shorthand for BipartiteGraph::Edge
  76         typedef BipartiteGraph::Edge      Edge;
  77
  78     private:
  79         std::vector<Var>         _vars;
  80         std::vector<Factor>      _factors;
  81         std::map<size_t,Factor>  _backup;
  82
  83     public:
  84         /// Default constructor
  85         FactorGraph() : G(), _vars(), _factors(), _backup() {}
  86
  87         /// Copy constructor
  88         FactorGraph(const FactorGraph & x) : G(x.G), _vars(x._vars), _factors(x._factors), _backup(x._backup) {}
  89
  90         /// Assignment operator
  91         FactorGraph & operator=(const FactorGraph & x) {
  92             if( this != &x ) {
  93                 G          = x.G;
  94                 _vars      = x._vars;
  95                 _factors   = x._factors;
  96                 _backup    = x._backup;
  97             }
  98             return *this;
  99         }
 100
 101         /// Constructs a FactorGraph from a vector of factors
 102         FactorGraph(const std::vector<Factor> &P);
 103
 104         /// Constructs a FactorGraph from given factor and variable iterators
 105         /** \tparam FactorInputIterator Iterator with value_type Factor
 106          *  \tparam VarInputIterator Iterator with value_type Var
 107          *  \pre Assumes that the set of variables in [var_begin,var_end) is the union of the variables in the factors in [fact_begin, fact_end)
 108          */
 109         template<typename FactorInputIterator, typename VarInputIterator>
 110         FactorGraph(FactorInputIterator fact_begin, FactorInputIterator fact_end, VarInputIterator var_begin, VarInputIterator var_end, size_t nr_fact_hint = 0, size_t nr_var_hint = 0 );
 111
 112         /// Destructor
 113         virtual ~FactorGraph() {}
 114
 115         /// Clone *this (virtual copy constructor)
 116         virtual FactorGraph* clone() const { return new FactorGraph(); }
 117
 118         /// Create (virtual default constructor)
 119         virtual FactorGraph* create() const { return new FactorGraph(*this); }
 120
 121         /// Returns const reference to i'th variable
 122         const Var & var(size_t i) const { return _vars[i]; }
 123         /// Returns const reference to all factors
 124         const std::vector<Var> & vars() const { return _vars; }
 125         /// Returns reference to I'th factor
 126         Factor & factor(size_t I) { return _factors[I]; }
 127         /// Returns const reference to I'th factor
 128         const Factor & factor(size_t I) const { return _factors[I]; }
 129         /// Returns const reference to all factors
 130         const std::vector<Factor> & factors() const { return _factors; }
 131
 132         /// Returns number of variables
 133         size_t nrVars() const { return vars().size(); }
 134         /// Returns number of factors
 135         size_t nrFactors() const { return factors().size(); }
 136         /// Calculates number of edges
 137         size_t nrEdges() const { return G.nrEdges(); }
 138
 139         /// Provides read access to neighbors of variable
 140         const Neighbors & nbV( size_t i ) const { return G.nb1(i); }
 141         /// Provides full access to neighbors of variable
 142         Neighbors & nbV( size_t i ) { return G.nb1(i); }
 143         /// Provides read access to neighbors of factor
 144         const Neighbors & nbF( size_t I ) const { return G.nb2(I); }
 145         /// Provides full access to neighbors of factor
 146         Neighbors & nbF( size_t I ) { return G.nb2(I); }
 147         /// Provides read access to neighbor of variable
 148         const Neighbor & nbV( size_t i, size_t _I ) const { return G.nb1(i)[_I]; }
 149         /// Provides full access to neighbor of variable
 150         Neighbor & nbV( size_t i, size_t _I ) { return G.nb1(i)[_I]; }
 151         /// Provides read access to neighbor of factor
 152         const Neighbor & nbF( size_t I, size_t _i ) const { return G.nb2(I)[_i]; }
 153         /// Provides full access to neighbor of factor
 154         Neighbor & nbF( size_t I, size_t _i ) { return G.nb2(I)[_i]; }
 155
 156         /// Returns the index of a particular variable
 157         size_t findVar( const Var & n ) const {
 158             size_t i = find( vars().begin(), vars().end(), n ) - vars().begin();
 159             assert( i != nrVars() );
 160             return i;
 161         }
 162
 163         /// Returns a set of indexes corresponding to a set of variables
 164         std::set<size_t> findVars( VarSet &ns ) const {
 165             std::set<size_t> indexes;
 166             for( VarSet::const_iterator n = ns.begin(); n != ns.end(); n++ )
 167                 indexes.insert( findVar( *n ) );
 168             return indexes;
 169         }
 170
 171         /// Returns index of the first factor that depends on the variables
 172         size_t findFactor(const VarSet &ns) const {
 173             size_t I;
 174             for( I = 0; I < nrFactors(); I++ )
 175                 if( factor(I).vars() == ns )
 176                     break;
 177             assert( I != nrFactors() );
 178             return I;
 179         }
 180
 181         /// Return all variables that occur in a factor involving the i'th variable, itself included
 182         VarSet Delta( unsigned i ) const;
 183
 184         /// Return all variables that occur in a factor involving some variable in ns, ns itself included
 185         VarSet Delta( const VarSet &ns ) const;
 186
 187         /// Return all variables that occur in a factor involving the i'th variable, n itself excluded
 188         VarSet delta( unsigned i ) const;
 189
 190         /// Return all variables that occur in a factor involving some variable in ns, ns itself excluded
 191         VarSet delta( const VarSet & ns ) const {
 192             return Delta( ns ) / ns;
 193         }
 194
 195         /// Set the content of the I'th factor and make a backup of its old content if backup == true
 196         virtual void setFactor( size_t I, const Factor &newFactor, bool backup = false ) {
 197             assert( newFactor.vars() == factor(I).vars() );
 198             if( backup )
 199                 backupFactor( I );
 200             _factors[I] = newFactor;
 201         }
 202
 203         /// Set the contents of all factors as specified by facs and make a backup of the old contents if backup == true
 204         virtual void setFactors( const std::map<size_t, Factor> & facs, bool backup = false ) {
 205             for( std::map<size_t, Factor>::const_iterator fac = facs.begin(); fac != facs.end(); fac++ ) {
 206                 if( backup )
 207                     backupFactor( fac->first );
 208                 setFactor( fac->first, fac->second );
 209             }
 210         }
 211
 212         /// Clamp variable n to value i (i.e. multiply with a Kronecker delta \f$\delta_{x_n, i}\f$);
 213         /// If backup == true, make a backup of all factors that are changed
 214         virtual void clamp( const Var & n, size_t i, bool backup = false );
 215
 216         /// Set all factors interacting with the i'th variable 1
 217         virtual void makeCavity( unsigned i, bool backup = false );
 218
 219         /// Backup the factors specified by indices in facs
 220         virtual void backupFactors( const std::set<size_t> & facs );
 221
 222         /// Restore all factors to the backup copies
 223         virtual void restoreFactors();
 224
 225         /// Returns true if the FactorGraph is connected
 226         bool isConnected() const { return G.isConnected(); }
 227
 228         /// Returns true if the FactorGraph is a tree
 229         bool isTree() const { return G.isTree(); }
 230
 231         /// Returns true if each factor depends on at most two variables
 232         bool isPairwise() const;
 233
 234         /// Returns true if each variable has only two possible values
 235         bool isBinary() const;
 236
 237         /// Reads a FactorGraph from a file
 238         void ReadFromFile(const char *filename);
 239
 240         /// Writes a FactorGraph to a file
 241         void WriteToFile(const char *filename) const;
 242
 243         /// Writes a FactorGraph to a GraphViz .dot file
 244         void printDot( std::ostream& os ) const;
 245
 246         /// Returns the cliques in this FactorGraph
 247         std::vector<VarSet> Cliques() const;
 248
 249         /// Clamp variable v_i to value state (i.e. multiply with a Kronecker delta \f$\delta_{x_{v_i},x}\f$);
 250         /** This version changes the factor graph structure and thus returns a newly constructed FactorGraph
 251          *  and keeps the current one constant, contrary to clamp()
 252          */
 253         FactorGraph clamped( const Var & v_i, size_t x ) const;
 254
 255         /// Returns a copy of *this, where all factors that are subsumed by some larger factor are merged with the larger factors.
 256         FactorGraph maximalFactors() const;
 257
 258         /// Makes a backup of the I'th Factor
 259         void restoreFactor( size_t I );
 260
 261         /// Restores the I'th Factor from the backup (it should be backed up first)
 262         void backupFactor( size_t I );
 263
 264         /// Makes a backup of all factors connected to a set of variables
 265         void backupFactors( const VarSet &ns );
 266         /// Restores all factors connected to a set of variables from their backups
 267         void restoreFactors( const VarSet &ns );
 268
 269         // Friends
 270         friend std::ostream& operator << (std::ostream& os, const FactorGraph& fg);
 271         friend std::istream& operator >> (std::istream& is, FactorGraph& fg);
 272
 273     private:
 274         /// Part of constructors (creates edges, neighbors and adjacency matrix)
 275         void constructGraph( size_t nrEdges );
 276 };
 277
 278
 279 template<typename FactorInputIterator, typename VarInputIterator>
 280 FactorGraph::FactorGraph(FactorInputIterator fact_begin, FactorInputIterator fact_end, VarInputIterator var_begin, VarInputIterator var_end, size_t nr_fact_hint, size_t nr_var_hint ) : G(), _backup() {
 281     // add factors
 282     size_t nrEdges = 0;
 283     _factors.reserve( nr_fact_hint );
 284     for( FactorInputIterator p2 = fact_begin; p2 != fact_end; ++p2 ) {
 285         _factors.push_back( *p2 );
 286         nrEdges += p2->vars().size();
 287     }
 288
 289     // add variables
 290     _vars.reserve( nr_var_hint );
 291     for( VarInputIterator p1 = var_begin; p1 != var_end; ++p1 )
 292         _vars.push_back( *p1 );
 293
 294     // create graph structure
 295     constructGraph( nrEdges );
 296 }
 297
 298
 299 } // end of namespace dai
 300
 301
 302 #endif