Updated copyright headers

[libdai.git] / include / dai / mf.h

diff --git a/include/dai/mf.h b/include/dai/mf.h
index 2befe07..644ddd4 100644 (file)
--- a/include/dai/mf.h
+++ b/include/dai/mf.h
@@ -1,22 +1,17 @@
-/*  Copyright (C) 2006-2008  Joris Mooij  [j dot mooij at science dot ru dot nl]
-    Radboud University Nijmegen, The Netherlands
-    
-    This file is part of libDAI.
+/*  This file is part of libDAI - http://www.libdai.org/
+ *
+ *  libDAI is licensed under the terms of the GNU General Public License version
+ *  2, or (at your option) any later version. libDAI is distributed without any
+ *  warranty. See the file COPYING for more details.
+ *
+ *  Copyright (C) 2006-2009  Joris Mooij  [joris dot mooij at libdai dot org]
+ *  Copyright (C) 2006-2007  Radboud University Nijmegen, The Netherlands
+ */
 
-    libDAI is free software; you can redistribute it and/or modify
-    it under the terms of the GNU General Public License as published by
-    the Free Software Foundation; either version 2 of the License, or
-    (at your option) any later version.
 
-    libDAI is distributed in the hope that it will be useful,
-    but WITHOUT ANY WARRANTY; without even the implied warranty of
-    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-    GNU General Public License for more details.
-
-    You should have received a copy of the GNU General Public License
-    along with libDAI; if not, write to the Free Software
-    Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA
-*/
+/// \file
+/// \brief Defines class MF
+/// \todo Improve documentation
 
 
 #ifndef __defined_libdai_mf_h
@@ -32,56 +27,71 @@
 namespace dai {
 
 
+/// Approximate inference algorithm "Mean Field"
 class MF : public DAIAlgFG {
-    protected:
+    private:
         std::vector<Factor>  _beliefs;
+        /// Maximum difference encountered so far
+        double _maxdiff;
+        /// Number of iterations needed
+        size_t _iters;
 
     public:
+        /// Parameters of this inference algorithm
         struct Properties {
+            /// Verbosity
             size_t verbose;
+
+            /// Maximum number of iterations
             size_t maxiter;
+
+            /// Tolerance
             double tol;
+
+            /// Damping constant
+            double damping;
         } props;
-        double maxdiff;
-        
+
+        /// Name of this inference algorithm
+        static const char *Name;
+
     public:
-        // default constructor
-        MF() : DAIAlgFG(), _beliefs(), props(), maxdiff(0.0) {}
-        // copy constructor
-        MF( const MF& x ) : DAIAlgFG(x), _beliefs(x._beliefs), props(x.props), maxdiff(x.maxdiff) {}
-        MF* clone() const { return new MF(*this); }
-        // construct MF object from FactorGraph
-        MF( const FactorGraph & fg, const PropertySet &opts ) : DAIAlgFG(fg), _beliefs(), props(), maxdiff(0.0) {
+        /// Default constructor
+        MF() : DAIAlgFG(), _beliefs(), _maxdiff(0.0), _iters(0U), props() {}
+
+        /// Construct from FactorGraph fg and PropertySet opts
+        MF( const FactorGraph &fg, const PropertySet &opts ) : DAIAlgFG(fg), _beliefs(), _maxdiff(0.0), _iters(0U), props() {
             setProperties( opts );
-            create();
-        }
-        // assignment operator
-        MF& operator=( const MF &x ) {
-            if( this != &x ) {
-                DAIAlgFG::operator=( x );
-                _beliefs = x._beliefs;
-                props = x.props;
-                maxdiff = x.maxdiff;
-            }
-            return *this;
+            construct();
         }
 
-        static const char *Name;
-        std::string identify() const;
-        void create();
-        void init();
-        double run();
-        Factor beliefV (size_t i) const;
-        Factor belief (const Var &n) const;
-        Factor belief (const VarSet &ns) const;
-        std::vector<Factor> beliefs() const;
-        Real logZ() const;
-
-        void init( const VarSet &ns );
-        void undoProbs( const VarSet &ns ) { FactorGraph::undoProbs(ns); init(ns); }
+
+        /// @name General InfAlg interface
+        //@{
+        virtual MF* clone() const { return new MF(*this); }
+        virtual std::string identify() const;
+        virtual Factor belief( const Var &n ) const;
+        virtual Factor belief( const VarSet &ns ) const;
+        virtual std::vector<Factor> beliefs() const;
+        virtual Real logZ() const;
+        virtual void init();
+        virtual void init( const VarSet &ns );
+        virtual double run();
+        virtual double maxDiff() const { return _maxdiff; }
+        virtual size_t Iterations() const { return _iters; }
+        //@}
+
+
+        /// @name Additional interface specific for MF
+        //@{
+        Factor beliefV( size_t i ) const;
+        //@}
+
+    private:
+        void construct();
         void setProperties( const PropertySet &opts );
         PropertySet getProperties() const;
-        double maxDiff() const { return maxdiff; }
+        std::string printProperties() const;
 };