X-Git-Url: http://git.tuebingen.mpg.de/?p=libdai.git;a=blobdiff_plain;f=include%2Fdai%2Fgibbs.h;h=2e5ec68f314118382babab8654c6d851626ff21b;hp=fa9e2965b72febda7ed2588115d886cb466deb5f;hb=87c6827445f8fd67801efb6e818771e16229313b;hpb=9bbf3b86c3e9316ad786d5c5514a7f16a23b8259

diff --git a/include/dai/gibbs.h b/include/dai/gibbs.h
index fa9e296..2e5ec68 100644
--- a/include/dai/gibbs.h
+++ b/include/dai/gibbs.h
@@ -1,4 +1,5 @@
-/*  Copyright (C) 2008  Frederik Eaton [frederik at ofb dot net]
+/*  Copyright (C) 2008  Frederik Eaton  [frederik at ofb dot net],
+                        Joris Mooij  [joris dot mooij at tuebingen dot mpg dot de]
 
     This file is part of libDAI.
 
@@ -18,6 +19,11 @@
 */
 
 
+/// \file
+/// \brief Defines class Gibbs
+/// \todo Improve documentation
+
+
 #ifndef __defined_libdai_gibbs_h
 #define __defined_libdai_gibbs_h
 
@@ -30,7 +36,17 @@
 namespace dai {
 
 
+/// Approximate inference algorithm "Gibbs sampling"
 class Gibbs : public DAIAlgFG {
+    private:
+        typedef std::vector<size_t> _count_t;
+        typedef std::vector<size_t> _state_t;
+
+        size_t _sample_count;
+        std::vector<_count_t> _var_counts;
+        std::vector<_count_t> _factor_counts;
+        _state_t _state;
+
     public:
         /// Parameters of this inference algorithm
         struct Properties {
@@ -44,40 +60,19 @@ class Gibbs : public DAIAlgFG {
         /// Name of this inference algorithm
         static const char *Name;
 
-    protected:
-        typedef std::vector<size_t> _count_t;
-        size_t _sample_count;
-        std::vector<_count_t> _var_counts;
-        std::vector<_count_t> _factor_counts;
-
-        typedef std::vector<size_t> _state_t;
-        void update_counts(_state_t &st);
-        void randomize_state(_state_t &st);
-        Prob get_var_dist(_state_t &st, size_t i);
-        void resample_var(_state_t &st, size_t i);
-        size_t get_factor_entry(const _state_t &st, int factor);
-
     public:
-        // default constructor
-        Gibbs() : DAIAlgFG() {}
-        // copy constructor
-        Gibbs(const Gibbs & x) : DAIAlgFG(x), _sample_count(x._sample_count), _var_counts(x._var_counts), _factor_counts(x._factor_counts) {}
-        // construct Gibbs object from FactorGraph
-        Gibbs( const FactorGraph & fg, const PropertySet &opts ) : DAIAlgFG(fg) {
+        /// Default constructor
+        Gibbs() : DAIAlgFG(), _sample_count(0), _var_counts(), _factor_counts(), _state() {}
+
+        /// Construct from FactorGraph fg and PropertySet opts
+        Gibbs( const FactorGraph &fg, const PropertySet &opts ) : DAIAlgFG(fg), _sample_count(0), _var_counts(), _factor_counts(), _state() {
             setProperties( opts );
             construct();
         }
-        // assignment operator
-        Gibbs & operator=(const Gibbs & x) {
-            if(this!=&x) {
-                DAIAlgFG::operator=(x);
-                _sample_count = x._sample_count;
-                _var_counts = x._var_counts;
-                _factor_counts = x._factor_counts;
-            }
-            return *this;
-        }
-        
+
+
+        /// @name General InfAlg interface
+        //@{
         virtual Gibbs* clone() const { return new Gibbs(*this); }
         virtual Gibbs* create() const { return new Gibbs(); }
         virtual std::string identify() const { return std::string(Name) + printProperties(); }
@@ -90,9 +85,28 @@ class Gibbs : public DAIAlgFG {
         virtual double run();
         virtual double maxDiff() const { DAI_THROW(NOT_IMPLEMENTED); return 0.0; }
         virtual size_t Iterations() const { return props.iters; }
+        //@}
+
 
+        /// @name Additional interface specific for Gibbs
+        //@{
         Factor beliefV( size_t i ) const;
         Factor beliefF( size_t I ) const;
+        void randomizeState();
+        //@}
+
+        /// Return reference to current state vector
+        std::vector<size_t>& state() { return _state; }
+
+        /// Return const reference to current state vector
+        const std::vector<size_t>& state() const { return _state; }
+
+    private:
+        void updateCounts();
+        Prob getVarDist( size_t i );
+        void resampleVar( size_t i );
+        size_t getFactorEntry( size_t I );
+        size_t getFactorEntryDiff( size_t I, size_t i );
 
         void construct();
         /// Set Props according to the PropertySet opts, where the values can be stored as std::strings or as the type of the corresponding Props member