Updated copyright headers

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

diff --git a/include/dai/mf.h b/include/dai/mf.h
index 90e5a4f..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 - 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
+ */
 
-    This file is part of libDAI.
 
-    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
@@ -32,6 +27,7 @@
 namespace dai {
 
 
+/// Approximate inference algorithm "Mean Field"
 class MF : public DAIAlgFG {
     private:
         std::vector<Factor>  _beliefs;
@@ -41,12 +37,22 @@ class MF : public DAIAlgFG {
         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;
+
+        /// Name of this inference algorithm
         static const char *Name;
 
     public:
@@ -59,65 +65,33 @@ class MF : public DAIAlgFG {
             construct();
         }
 
-        /// Copy constructor
-        MF( const MF &x ) : DAIAlgFG(x), _beliefs(x._beliefs), _maxdiff(x._maxdiff), _iters(x._iters), props(x.props) {}
 
-        /// Clone *this (virtual copy constructor)
+        /// @name General InfAlg interface
+        //@{
         virtual MF* clone() const { return new MF(*this); }
-
-        /// Create (virtual default constructor)
-        virtual MF* create() const { return new MF(); }
-
-        /// Assignment operator
-        MF& operator=( const MF &x ) {
-            if( this != &x ) {
-                DAIAlgFG::operator=( x );
-                _beliefs = x._beliefs;
-                _maxdiff = x._maxdiff;
-                _iters   = x._iters;
-                props    = x.props;
-            }
-            return *this;
-        }
-
-        /// Identifies itself for logging purposes
         virtual std::string identify() const;
-
-        /// Get single node belief
         virtual Factor belief( const Var &n ) const;
-
-        /// Get general belief
         virtual Factor belief( const VarSet &ns ) const;
-
-        /// Get all beliefs
         virtual std::vector<Factor> beliefs() const;
-
-        /// Get log partition sum
         virtual Real logZ() const;
-
-        /// Clear messages and beliefs
         virtual void init();
-
-        /// Clear messages and beliefs corresponding to the nodes in ns
         virtual void init( const VarSet &ns );
-
-        /// The actual approximate inference algorithm
         virtual double run();
-
-        /// Return maximum difference between single node beliefs in the last pass
         virtual double maxDiff() const { return _maxdiff; }
-
-        /// Return number of passes over the factorgraph
         virtual size_t Iterations() const { return _iters; }
+        //@}
 
 
-        void construct();
+        /// @name Additional interface specific for MF
+        //@{
+        Factor beliefV( size_t i ) const;
+        //@}
 
+    private:
+        void construct();
         void setProperties( const PropertySet &opts );
         PropertySet getProperties() const;
         std::string printProperties() const;
-
-        Factor beliefV( size_t i ) const;
 };