Add moRandomWalk.h, update lesson 6 sampling.cpp

git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@1775 331e1502-861f-0410-8da2-ba01fb791d7f

trunk/paradiseo-mo/src/algo/moRandomWalk.h

@@ -0,0 +1,86 @@
+/*
+<moRandomWalk.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  ue,
+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".
+
+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 _moRandomWalk_h
+#define _moRandomWalk_h
+
+#include <algo/moLocalSearch.h>
+#include <explorer/moRandomWalkExplorer.h>
+#include <continuator/moTrueContinuator.h>
+#include <eval/moEval.h>
+#include <eoEvalFunc.h>
+
+/********************************************************
+ * Random Walk:
+ * Random walk local search
+ * 
+ * At each iteration,
+ *   one random neighbor is selected and replace the current solution
+ *   the algorithm stops when the number of steps is reached
+ ********************************************************/
+template<class Neighbor>
+class moRandomWalk: public moLocalSearch<Neighbor>
+{
+public:
+  typedef typename Neighbor::EOT EOT;
+  typedef moNeighborhood<Neighbor> Neighborhood ;
+
+  /**
+   * Simple constructor for a random walk
+   * @param _neighborhood the neighborhood
+   * @param _fullEval the full evaluation function
+   * @param _eval neighbor's evaluation function
+   * @param _nbStepMax number of step of the walk
+   */
+  moRandomWalk(Neighborhood& _neighborhood, eoEvalFunc<EOT>& _fullEval, moEval<Neighbor>& _eval, unsigned _nbStepMax):
+    moLocalSearch<Neighbor>(explorer, trueCont, _fullEval),
+    explorer(_neighborhood, _eval, _nbStepMax)
+  {}
+  
+  /**
+   * Simple constructor for a random walk
+   * @param _neighborhood the neighborhood
+   * @param _fullEval the full evaluation function
+   * @param _eval neighbor's evaluation function
+   * @param _nbStepMax number of step of the walk
+   * @param _cont an external continuator
+   */
+  moRandomWalk(Neighborhood& _neighborhood, eoEvalFunc<EOT>& _fullEval, moEval<Neighbor>& _eval, unsigned _nbStepMax, moContinuator<Neighbor>& _cont):
+    moLocalSearch<Neighbor>(explorer, _cont, _fullEval),
+    explorer(_neighborhood, _eval, _nbStepMax)
+  {}
+  
+private:
+  // always true continuator
+  moTrueContinuator<Neighbor> trueCont;
+  // the explorer of the random walk
+  moRandomWalkExplorer<Neighbor> explorer;
+};
+
+#endif

trunk/paradiseo-mo/src/explorer/moRandomWalkExplorer.h

@@ -98,6 +98,7 @@ public:
 
     /**
      * Explore the neighborhood with only one random solution
+     * we supposed that the first neighbor is uniformly selected in the neighborhood
      * @param _solution
      */
     virtual void operator()(EOT & _solution) {

trunk/paradiseo-mo/src/mo.h

@@ -41,6 +41,7 @@
 #include <algo/moFirstImprHC.h>
 #include <algo/moRandomBestHC.h>
 #include <algo/moNeutralHC.h>
+#include <algo/moRandomWalk.h>
 #include <algo/moTS.h>
 
 #include <comparator/moComparator.h>

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

@@ -93,6 +93,7 @@ public:
 
   /**
    * To sample the search and get the statistics
+   * the statistics are stored in the moVectorMonitor vector
    */
   void operator()(void) {
     // clear all statisic vectors
@@ -111,14 +112,16 @@ public:
     // compute the sampling
     localSearch(solution);
 
-    // set to initial continuator
+    // set back to initial continuator
     localSearch.setContinuator(*continuator);
   }
 
   /**
    * to export the vector of values into one file
+   * @param _filename file name 
+   * @param _delim delimiter between statistics
    */
-  void exportFile(std::string _filename, std::string _delim = " ") {
+  void fileExport(std::string _filename, std::string _delim = " ") {
     // create file
     ofstream os(_filename.c_str()); 
 
@@ -145,6 +148,15 @@ public:
     
   }
 
+  /**
+   * to get one vector of values
+   * @param _numStat number of stattistics to get (in order of creation)
+   * @return the vector of value (all values are converted in double)
+   */
+  const std::vector<double> & getVector(unsigned int _numStat) {
+    return monitorVec[_numStat]->getVector();
+  }
+
   /**
    * @return name of the class
    */

trunk/paradiseo-mo/tutorial/Lesson6/sampling.cpp

@@ -17,38 +17,49 @@
 
 // the general include for eo
 #include <eo>
-#include <ga.h>
 
+// declaration of the namespace
 using namespace std;
 
 //-----------------------------------------------------------------------------
-// fitness function
+// representation of solutions, and neighbors
-#include <eval/oneMaxEval.h>
+#include <ga/eoBit.h>                         // bit string : see also EO tutorial lesson 1: FirstBitGA.cpp
-#include <problems/bitString/moBitNeighbor.h>
+#include <problems/bitString/moBitNeighbor.h> // neighbor of bit string
-#include <eoInt.h>
-#include <neighborhood/moRndWithReplNeighborhood.h>
 
+//-----------------------------------------------------------------------------
+// fitness function, and evaluation of neighbors
+#include <eval/oneMaxEval.h>
+#include <problems/eval/moOneMaxIncrEval.h>
 #include <eval/moFullEvalByModif.h>
-#include <eval/moFullEvalByCopy.h>
+
-#include <continuator/moTrueContinuator.h>
+//-----------------------------------------------------------------------------
-#include <algo/moLocalSearch.h>
+// neighborhood description
-#include <explorer/moRandomWalkExplorer.h>
+#include <neighborhood/moRndWithReplNeighborhood.h> // visit one random neighbor possibly the same one several times
-#include <continuator/moCheckpoint.h>
+
+//-----------------------------------------------------------------------------
+// the random walk local search: heuristic to sample the search space
+#include <algo/moRandomWalk.h>
+
+//-----------------------------------------------------------------------------
+// the statistics to compute during the sampling
 #include <continuator/moFitnessStat.h>
-#include <continuator/moSolutionStat.h>
 #include <utils/eoDistance.h>
 #include <continuator/moDistanceStat.h>
 
-#include <utils/eoFileMonitor.h>
+//-----------------------------------------------------------------------------
-#include <utils/eoUpdater.h>
+// the sampling class
-
 #include <sampling/moSampling.h>
 
-// REPRESENTATION
+
+// Declaration of types
 //-----------------------------------------------------------------------------
-typedef eoBit<unsigned> Indi;
+// Indi is the typedef of the solution type like in paradisEO-eo
-typedef moBitNeighbor<unsigned int> Neighbor ; // incremental evaluation
+typedef eoBit<unsigned int> Indi;                      // bit string with unsigned fitness type
-typedef moRndWithReplNeighborhood<Neighbor> Neighborhood ;
+// Neighbor is the typedef of the neighbor type,
+// Neighbor = How to compute the neighbor from the solution + information on it (i.e. fitness)  
+// all classes from paradisEO-mo use this template type
+typedef moBitNeighbor<unsigned int> Neighbor ;         // bit string neighbor with unsigned fitness type
+
 
 void main_function(int argc, char **argv)
 {
@@ -57,6 +68,8 @@ void main_function(int argc, char **argv)
    * Parameters
    *
    * ========================================================= */
+  // more information on the input parameters: see EO tutorial lesson 3
+  // but don't care at first it just read the parameters of the bit string size and the random seed.
 
   // First define a parser from the command-line arguments
   eoParser parser(argc, argv);
@@ -64,16 +77,18 @@ void main_function(int argc, char **argv)
   // For each parameter, define Parameter, read it through the parser,
   // and assign the value to the variable
 
+  // random seed parameter
   eoValueParam<uint32_t> seedParam(time(0), "seed", "Random number seed", 'S');
   parser.processParam( seedParam );
   unsigned seed = seedParam.value();
   
-    // description of genotype
+  // length of the bit string
-    eoValueParam<unsigned int> vecSizeParam(8, "vecSize", "Genotype size", 'V');
+  eoValueParam<unsigned int> vecSizeParam(20, "vecSize", "Genotype size", 'V');
   parser.processParam( vecSizeParam, "Representation" );
   unsigned vecSize = vecSizeParam.value();
   
-    eoValueParam<unsigned int> stepParam(10, "nbStep", "Number of steps of the random walk", 'n');
+  // the number of steps of the random walk
+  eoValueParam<unsigned int> stepParam(100, "nbStep", "Number of steps of the random walk", 'n');
   parser.processParam( stepParam, "Representation" );
   unsigned nbStep = stepParam.value();
   
@@ -104,30 +119,30 @@ void main_function(int argc, char **argv)
    *
    * ========================================================= */
 
-    //reproducible random seed: if you don't change SEED above,
+  // reproducible random seed: if you don't change SEED above,
   // you'll aways get the same result, NOT a random run
+  // more information: see EO tutorial lesson 1 (FirstBitGA.cpp)
   rng.reseed(seed);
 
-
   /* =========================================================
    *
-     * Eval fitness function
+   * Initialization of the solution
    *
    * ========================================================= */
 
-    oneMaxEval<Indi> eval;
+  // a Indi random initializer: each bit is random
-
+  // more information: see EO tutorial lesson 1 (FirstBitGA.cpp)
-
-    /* =========================================================
-     *
-     * Initilisation of the solution
-     *
-     * ========================================================= */
-
-    // a Indi random initializer
   eoUniformGenerator<bool> uGen;
   eoInitFixedLength<Indi> random(vecSize, uGen);
 
+  /* =========================================================
+   *
+   * Eval fitness function (full evaluation)
+   *
+   * ========================================================= */
+
+  // the fitness function is just the number of 1 in the bit string
+  oneMaxEval<Indi> fullEval;
 
   /* =========================================================
    *
@@ -135,11 +150,11 @@ void main_function(int argc, char **argv)
    *
    * ========================================================= */
 
-    moFullEvalByModif<Neighbor> nhEval(eval);
+  // Use it if there is no incremental evaluation: a neighbor is evaluated by the full evaluation of a solution
-
+  // moFullEvalByModif<Neighbor> neighborEval(fullEval);
-    //An eval by copy can be used instead of the eval by modif
-    //moFullEvalByCopy<Neighbor> nhEval(eval);
 
+  // Incremental evaluation of the neighbor: fitness is modified by +/- 1
+  moOneMaxIncrEval<Neighbor> neighborEval;
 
   /* =========================================================
    *
@@ -147,38 +162,32 @@ void main_function(int argc, char **argv)
    *
    * ========================================================= */
 
-    Neighborhood neighborhood(vecSize);
+  // Exploration of the neighborhood in random order
-
+  // at each step one bit is randomly generated
+  moRndWithReplNeighborhood<Neighbor> neighborhood(vecSize);
 
   /* =========================================================
    *
-     * a neighborhood explorer solution
+   * the local search algorithm to sample the search space
    *
    * ========================================================= */
 
-    moRandomWalkExplorer<Neighbor> explorer(neighborhood, nhEval, nbStep);
+  moRandomWalk<Neighbor> walk(neighborhood, fullEval, neighborEval, nbStep);
-
 
   /* =========================================================
    *
-     * the continuator and the checkpoint
+   * the statistics to compute
    *
    * ========================================================= */
   
-    moTrueContinuator<Neighbor> continuator;//always continue
+  // fitness of the solution at each step
-
   moFitnessStat<Indi, unsigned> fStat;
-    eoHammingDistance<Indi> distance;
-    Indi bestSolution(vecSize, true);
-    moDistanceStat<Indi, unsigned> distStat(distance, bestSolution);
 
-    /* =========================================================
+  // Hamming distance to the global optimum
-     *
+  eoHammingDistance<Indi> distance; // Hamming distance
-     * the local search algorithm
+  Indi bestSolution(vecSize, true); // global optimum
-     *
-     * ========================================================= */
 
-    moLocalSearch<Neighbor> localSearch(explorer, continuator, eval);
+  moDistanceStat<Indi, unsigned> distStat(distance, bestSolution); // statistic
 
   /* =========================================================
    *
@@ -186,7 +195,14 @@ void main_function(int argc, char **argv)
    *
    * ========================================================= */
   
-    moSampling<Neighbor> sampling(random, localSearch, fStat);
+  // sampling object : 
+  //    - random initialization
+  //    - local search to sample the search space
+  //    - one statistic to compute
+  moSampling<Neighbor> sampling(random, walk, fStat);
+  
+  // to add another statistics
+  sampling.add(distStat);
 
   /* =========================================================
    *
@@ -196,8 +212,27 @@ void main_function(int argc, char **argv)
   
   sampling();
   
-    sampling.exportFile(str_out);
+  /* =========================================================
+   *
+   * export the sampling
+   *
+   * ========================================================= */
   
+  // to export the statistics into file
+  sampling.fileExport(str_out);
+
+  // to get the values of statistics 
+  // so, you can compute some statistics in c++ from the data
+  const std::vector<double> & fitnessValues = sampling.getVector(0); 
+  const std::vector<double> & distValues = sampling.getVector(1); 
+
+  std::cout << "First values:" << std::endl;
+  std::cout << "Fitness  " << fitnessValues[0] << std::endl;
+  std::cout << "Distance " << distValues[0] << std::endl << std::endl;
+
+  std::cout << "Last values:" << std::endl;
+  std::cout << "Fitness  " << fitnessValues[fitnessValues.size() - 1] << std::endl;
+  std::cout << "Distance " << distValues[distValues.size() - 1] << std::endl;
 }
 
 // A main that catches the exceptions