Ajout du Metropolis-Hasting LS, du samplinf MH fitness cloud

git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@1792 331e1502-861f-0410-8da2-ba01fb791d7f

trunk/paradiseo-mo/src/sampling/moMHFitnessCloudSampling.h

@@ -0,0 +1,100 @@
+/*
+  <moMHFitnessCloudSampling.h>
+  Copyright (C) DOLPHIN Project-Team, INRIA Lille - Nord Europe, 2006-2010
+
+  Sebastien Verel, Arnaud Liefooghe, Jeremie Humeau
+
+  This software is governed by the CeCILL license under French law and
+  abiding by the rules of distribution of free software.  You can  use,
+  modify and/ or redistribute the software under the terms of the CeCILL
+  license as circulated by CEA, CNRS and INRIA at the following URL
+  "http://www.cecill.info".
+
+  As a counterpart to the access to the source code and  rights to copy,
+  modify and redistribute granted by the license, users are provided only
+  with a limited warranty  and the software's author,  the holder of the
+  economic rights,  and the successive licensors  have only  limited liability.
+
+  In this respect, the user's attention is drawn to the risks associated
+  with loading,  using,  modifying and/or developing or reproducing the
+  software by the user in light of its specific status of free software,
+  that may mean  that it is complicated to manipulate,  and  that  also
+  therefore means  that it is reserved for developers  and  experienced
+  professionals having in-depth computer knowledge. Users are therefore
+  encouraged to load and test the software's suitability as regards their
+  requirements in conditions enabling the security of their systems and/or
+  data to be ensured and,  more generally, to use and operate it in the
+  same conditions as regards security.
+  The fact that you are presently reading this means that you have had
+  knowledge of the CeCILL license and that you accept its terms.
+
+  ParadisEO WebSite : http://paradiseo.gforge.inria.fr
+  Contact: paradiseo-help@lists.gforge.inria.fr
+*/
+
+#ifndef moMHFitnessCloudSampling_h
+#define moMHFitnessCloudSampling_h
+
+#include <eoInit.h>
+#include <neighborhood/moNeighborhood.h>
+#include <eval/moEval.h>
+#include <eoEvalFunc.h>
+#include <algo/moMetropolisHasting.h>
+#include <continuator/moFitnessStat.h>
+#include <continuator/moNeighborFitnessStat.h>
+#include <sampling/moSampling.h>
+
+/**
+ * To compute an estimation of the fitness cloud, 
+ *   i.e. the scatter plot of solution fitness versus neighbor fitness: 
+ *   Here solution are sampled with Metropolis-Hasting method
+ *
+ *   Sample the fitness of solutions from Metropolis-Hasting sampling
+ *   and the fitness of one random neighbor
+ *
+ *   The values are collected during the random search
+ * 
+ */
+template <class Neighbor>
+class moMHFitnessCloudSampling : public moSampling<Neighbor>
+{
+public:
+  typedef typename Neighbor::EOT EOT ;
+  
+  using moSampling<Neighbor>::localSearch;
+
+  /**
+   * Default Constructor
+   * @param _init initialisation method of the solution
+   * @param _neighborhood neighborhood to get one random neighbor (supposed to be random neighborhood)
+   * @param _fullEval Fitness function, full evaluation function
+   * @param _eval neighbor evaluation, incremental evaluation function
+   * @param _nbStep Number of step of the MH sampling
+   */
+  moMHFitnessCloudSampling(eoInit<EOT> & _init, 
+			  moNeighborhood<Neighbor> & _neighborhood, 
+			  eoEvalFunc<EOT>& _fullEval, 
+			  moEval<Neighbor>& _eval, 
+			  unsigned int _nbStep) : 
+    moSampling<Neighbor>(_init, * new moMetropolisHasting<Neighbor>(_neighborhood, _fullEval, _eval, _nbStep), fitnessStat),
+    neighborFitnessStat(_neighborhood, _eval)
+  {
+    add(neighborFitnessStat);
+  }
+
+  /** 
+   * default destructor
+   */
+  ~moMHFitnessCloudSampling() {
+    // delete the pointer on the local search which has been constructed in the constructor
+    delete &localSearch;
+  }
+
+protected:
+  moFitnessStat<EOT> fitnessStat;
+  moNeighborFitnessStat< Neighbor > neighborFitnessStat;
+
+};
+
+
+#endif

trunk/paradiseo-mo/src/sampling/moSampling.h

@@ -62,6 +62,7 @@ public:
    * @param _init initialisation method of the solution
    * @param _localSearch  local search to sample the search space
    * @param _stat statistic to compute during the search
+   * @param _monitoring the statistic is saved into the monitor if true
    */
   template <class ValueType>
   moSampling(eoInit<EOT> & _init, moLocalSearch<Neighbor> & _localSearch, moStat<EOT,ValueType> & _stat, bool _monitoring = true) : init(_init), localSearch(_localSearch), continuator(_localSearch.getContinuator())
@@ -85,6 +86,7 @@ public:
   /**
    * Add a statistic
    * @param _stat another statistic to compute during the search
+   * @param _monitoring the statistic is saved into the monitor if true
    */
   template< class ValueType >
   void add(moStat<EOT, ValueType> & _stat, bool _monitoring = true) {