Add the autocorrelation sampling

git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@1777 331e1502-861f-0410-8da2-ba01fb791d7f

trunk/paradiseo-mo/src/continuator/moFitnessStat.h

@@ -42,35 +42,35 @@
  * that need to be calculated over the solution
  * It is a moStatBase AND an eoValueParam so it can be used in Monitors.
 */
-template <class EOT, class T=typename EOT::Fitness>
-class moFitnessStat : public moStat<EOT, T>
+template <class EOT>
+class moFitnessStat : public moStat<EOT, typename EOT::Fitness>
 {
 public :
-    typedef T Fitness;
-    using moStat< EOT, Fitness >::value;
+  typedef typename EOT::Fitness Fitness;
+  using moStat< EOT, Fitness >::value;
 
-    /**
-     * Default Constructor
-     * @param _description a description of the stat
-     */
-    moFitnessStat(std::string _description = "fitness"):
-            moStat<EOT, Fitness>(Fitness(), _description) {}
-
-    /**
-     * store fitness value
-     * @param _sol the corresponding solution
-     */
-    virtual void operator()(EOT & _sol)
-    {
-        value() = _sol.fitness();
-    }
-
-    /**
-     * @return the name of the class
-     */
-    virtual std::string className(void) const {
-        return "moFitnessStat";
-    }
+  /**
+   * Default Constructor
+   * @param _description a description of the stat
+   */
+  moFitnessStat(std::string _description = "fitness"):
+    moStat<EOT, Fitness>(Fitness(), _description) {}
+  
+  /**
+   * store fitness value
+   * @param _sol the corresponding solution
+   */
+  virtual void operator()(EOT & _sol)
+  {
+    value() = _sol.fitness();
+  }
+  
+  /**
+   * @return the name of the class
+   */
+  virtual std::string className(void) const {
+    return "moFitnessStat";
+  }
 };
 
 #endif

trunk/paradiseo-mo/src/mo.h

@@ -132,6 +132,7 @@
 #include <coolingSchedule/moSimpleCoolingSchedule.h>
 
 #include <sampling/moSampling.h>
+#include <sampling/moAutocorrelationSampling.h>
 
 #include <problems/bitString/moBitNeighbor.h>
 #include <problems/eval/moOneMaxIncrEval.h>

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

@@ -0,0 +1,88 @@
+/*
+  <moAutocorrelationSampling.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 moAutocorrelationSampling_h
+#define moAutocorrelationSampling_h
+
+#include <eoInit.h>
+#include <eval/moEval.h>
+#include <eoEvalFunc.h>
+#include <algo/moRandomWalk.h>
+#include <continuator/moFitnessStat.h>
+#include <sampling/moSampling.h>
+
+/**
+ * To compute the autocorrelation function:
+ *   Perform a random walk based on the neighborhood,
+ *   The fitness values of solutions are collected during the random walk
+ *   The autocorrelation can be computed from the serie of fitness values  
+ * 
+ */
+template <class Neighbor>
+class moAutocorrelationSampling : 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 giving neighbor in random order
+   * @param _nbStep Number of steps of the random walk 
+   */
+  moAutocorrelationSampling(eoInit<EOT> & _init, 
+			    moNeighborhood<Neighbor> & _neighborhood, 
+			    eoEvalFunc<EOT>& _fullEval, moEval<Neighbor>& _eval, 
+			    unsigned int _nbStep) : 
+    moSampling<Neighbor>(_init, * new moRandomWalk<Neighbor>(_neighborhood, _fullEval, _eval, _nbStep), fitnessStat)
+  {
+  }
+
+  /** 
+   * default destructor
+   */
+  ~moAutocorrelationSampling() {
+    // delete the pointer on the local search which has been constructed in the constructor
+    delete &localSearch;
+  }
+
+protected:
+  moFitnessStat<EOT> fitnessStat;
+
+};
+
+
+#endif

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

@@ -41,6 +41,7 @@
 #include <continuator/moStat.h>
 #include <continuator/moCheckpoint.h>
 #include <continuator/moVectorMonitor.h>
+#include <algo/moLocalSearch.h>
 #include <eoInit.h>
 
 /**
@@ -69,10 +70,15 @@ public:
     add(_stat);
   }
 
+  /**
+   * default destructor
+   */
   ~moSampling() {
+    // delete all monitors
     for(unsigned i = 0; i < monitorVec.size(); i++)
       delete monitorVec[i];
 
+    // delete the checkpoint
     delete checkpoint ;
   }
 

trunk/paradiseo-mo/tutorial/Lesson6/CMakeLists.txt

@@ -10,8 +10,10 @@ ADD_EXECUTABLE(testRandomWalk testRandomWalk.cpp)
 ADD_EXECUTABLE(testMetropolisHasting testMetropolisHasting.cpp) 
 ADD_EXECUTABLE(testRandomNeutralWalk testRandomNeutralWalk.cpp) 
 ADD_EXECUTABLE(sampling sampling.cpp) 
+ADD_EXECUTABLE(autocorrelation autocorrelation.cpp) 
 
 TARGET_LINK_LIBRARIES(testRandomWalk eoutils ga eo) 
 TARGET_LINK_LIBRARIES(testMetropolisHasting eoutils ga eo) 
 TARGET_LINK_LIBRARIES(testRandomNeutralWalk eoutils ga eo)
+TARGET_LINK_LIBRARIES(autocorrelation eoutils ga eo)
 TARGET_LINK_LIBRARIES(sampling eoutils ga eo)

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

@@ -0,0 +1,209 @@
+//-----------------------------------------------------------------------------
+/** sampling.cpp
+ *
+ * SV - 03/05/10
+ *
+ */
+//-----------------------------------------------------------------------------
+
+// standard includes
+#define HAVE_SSTREAM
+
+#include <stdexcept>  // runtime_error 
+#include <iostream>   // cout
+#include <sstream>    // ostrstream, istrstream
+#include <fstream>
+#include <string.h>
+
+// the general include for eo
+#include <eo>
+
+// declaration of the namespace
+using namespace std;
+
+//-----------------------------------------------------------------------------
+// representation of solutions, and neighbors
+#include <ga/eoBit.h>                         // bit string : see also EO tutorial lesson 1: FirstBitGA.cpp
+#include <problems/bitString/moBitNeighbor.h> // neighbor of bit string
+
+//-----------------------------------------------------------------------------
+// fitness function, and evaluation of neighbors
+#include <eval/oneMaxEval.h>
+#include <problems/eval/moOneMaxIncrEval.h>
+#include <eval/moFullEvalByModif.h>
+
+//-----------------------------------------------------------------------------
+// neighborhood description
+#include <neighborhood/moRndWithReplNeighborhood.h> // visit one random neighbor possibly the same one several times
+
+//-----------------------------------------------------------------------------
+// the sampling class
+#include <sampling/moAutocorrelationSampling.h>
+
+// Declaration of types
+//-----------------------------------------------------------------------------
+// Indi is the typedef of the solution type like in paradisEO-eo
+typedef eoBit<unsigned int> Indi;                      // bit string with unsigned fitness type
+// 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)
+{
+  /* =========================================================
+   *
+   * 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);
+  
+  // 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();
+  
+  // length of the bit string
+  eoValueParam<unsigned int> vecSizeParam(20, "vecSize", "Genotype size", 'V');
+  parser.processParam( vecSizeParam, "Representation" );
+  unsigned vecSize = vecSizeParam.value();
+  
+  // 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();
+  
+  // the name of the output file
+  string str_out = "out.dat"; // default value
+  eoValueParam<string> outParam(str_out.c_str(), "out", "Output file of the sampling", 'o');
+  parser.processParam(outParam, "Persistence" );
+  
+  // the name of the "status" file where all actual parameter values will be saved
+  string str_status = parser.ProgramName() + ".status"; // default value
+  eoValueParam<string> statusParam(str_status.c_str(), "status", "Status file");
+  parser.processParam( statusParam, "Persistence" );
+  
+  // do the following AFTER ALL PARAMETERS HAVE BEEN PROCESSED
+  // i.e. in case you need parameters somewhere else, postpone these
+  if (parser.userNeedsHelp()) {
+    parser.printHelp(cout);
+    exit(1);
+  }
+  if (statusParam.value() != "") {
+    ofstream os(statusParam.value().c_str());
+    os << parser;// and you can use that file as parameter file
+  }
+
+  /* =========================================================
+   *
+   * Random seed
+   *
+   * ========================================================= */
+
+  // 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);
+
+  /* =========================================================
+   *
+   * Initialization of the solution
+   *
+   * ========================================================= */
+
+  // a Indi random initializer: each bit is random
+  // more information: see EO tutorial lesson 1 (FirstBitGA.cpp)
+  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;
+
+  /* =========================================================
+   *
+   * evaluation of a neighbor solution
+   *
+   * ========================================================= */
+
+  // Use it if there is no incremental evaluation: a neighbor is evaluated by the full evaluation of a solution
+  // moFullEvalByModif<Neighbor> neighborEval(fullEval);
+
+  // Incremental evaluation of the neighbor: fitness is modified by +/- 1
+  moOneMaxIncrEval<Neighbor> neighborEval;
+
+  /* =========================================================
+   *
+   * the neighborhood of a solution
+   *
+   * ========================================================= */
+
+  // Exploration of the neighborhood in random order
+  // at each step one bit is randomly generated
+  moRndWithReplNeighborhood<Neighbor> neighborhood(vecSize);
+
+  /* =========================================================
+   *
+   * The sampling of the search space
+   *
+   * ========================================================= */
+  
+  // sampling object : 
+  //    - random initialization
+  //    - local search to sample the search space
+  //    - one statistic to compute
+  moAutocorrelationSampling<Neighbor> sampling(random, neighborhood, fullEval, neighborEval, nbStep);
+  
+  /* =========================================================
+   *
+   * execute the sampling
+   *
+   * ========================================================= */
+  
+  sampling();
+  
+  /* =========================================================
+   *
+   * 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); 
+
+  std::cout << "First values:" << std::endl;
+  std::cout << "Fitness  " << fitnessValues[0] << std::endl;
+
+  std::cout << "Last values:" << std::endl;
+  std::cout << "Fitness  " << fitnessValues[fitnessValues.size() - 1] << std::endl;
+}
+
+// A main that catches the exceptions
+
+int main(int argc, char **argv)
+{
+    try {
+        main_function(argc, argv);
+    }
+    catch (exception& e) {
+        cout << "Exception: " << e.what() << '\n';
+    }
+    return 1;
+}

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

@@ -50,7 +50,6 @@ using namespace std;
 // the sampling class
 #include <sampling/moSampling.h>
 
-
 // Declaration of types
 //-----------------------------------------------------------------------------
 // Indi is the typedef of the solution type like in paradisEO-eo
@@ -181,7 +180,7 @@ void main_function(int argc, char **argv)
    * ========================================================= */
   
   // fitness of the solution at each step
-  moFitnessStat<Indi, unsigned> fStat;
+  moFitnessStat<Indi> fStat;
 
   // Hamming distance to the global optimum
   eoHammingDistance<Indi> distance; // Hamming distance

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

@@ -197,7 +197,7 @@ void main_function(int argc, char **argv)
 
     moCheckpoint<Neighbor> checkpoint(continuator);
 
-    moFitnessStat<Indi, unsigned> fStat;
+    moFitnessStat<Indi> fStat;
 
     eoHammingDistance<Indi> distance;
     moDistanceStat<Indi, unsigned> distStat(distance, solution);  // distance from the intial solution

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

@@ -162,7 +162,7 @@ void main_function(int argc, char **argv)
 
     moCheckpoint<Neighbor> checkpoint(continuator);
 
-    moFitnessStat<Indi, unsigned> fStat;
+    moFitnessStat<Indi> fStat;
     eoHammingDistance<Indi> distance;
     Indi bestSolution(vecSize, true);
     moDistanceStat<Indi, unsigned> distStat(distance, bestSolution);