Added moStat moFitnessMomentsStat and class moStdDevEstimator for estimating the stddev
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119
mo/src/continuator/moFitnessMomentsStat.h
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119
mo/src/continuator/moFitnessMomentsStat.h
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/*
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<moBestFitnessStat.h>
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Copyright (C) DOLPHIN Project-Team, INRIA Lille - Nord Europe, 2006-2010
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Sébastien Verel, Arnaud Liefooghe, Jérémie Humeau
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This software is governed by the CeCILL license under French law and
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abiding by the rules of distribution of free software. You can use,
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modify and/ or redistribute the software under the terms of the CeCILL
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license as circulated by CEA, CNRS and INRIA at the following URL
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"http://www.cecill.info".
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As a counterpart to the access to the source code and rights to copy,
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modify and redistribute granted by the license, users are provided only
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with a limited warranty and the software's author, the holder of the
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economic rights, and the successive licensors have only limited liability.
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In this respect, the user's attention is drawn to the risks associated
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with loading, using, modifying and/or developing or reproducing the
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software by the user in light of its specific status of free software,
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that may mean that it is complicated to manipulate, and that also
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therefore means that it is reserved for developers and experienced
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professionals having in-depth computer knowledge. Users are therefore
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encouraged to load and test the software's suitability as regards their
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requirements in conditions enabling the security of their systems and/or
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data to be ensured and, more generally, to use and operate it in the
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same conditions as regards security.
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The fact that you are presently reading this means that you have had
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knowledge of the CeCILL license and that you accept its terms.
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ParadisEO WebSite : http://paradiseo.gforge.inria.fr
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Contact: paradiseo-help@lists.gforge.inria.fr
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*/
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#ifndef moFitnessMomentsStat_h
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#define moFitnessMomentsStat_h
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#include <utility>
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#include <continuator/moStat.h>
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/**
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* Statistic that saves the standard deviation of the fitness of the solutions during the search
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*/
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template <class EOT>
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//class moFitnessMomentsStat : public moStat<EOT, std::pair<typename EOT::Fitness,typename EOT::Fitness> >
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class moFitnessMomentsStat : public moStat<EOT, std::pair<double, double> >
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{
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public :
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typedef typename EOT::Fitness Fitness;
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//typedef std::pair<typename EOT::Fitness,typename EOT::Fitness> Pair;
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typedef std::pair<double, double> Pair;
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using moStat<EOT, Pair >::value;
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/**
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* Default Constructor
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* @param _reInitSol when true the best so far is reinitialized
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*/
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moFitnessMomentsStat(bool _reInitSol = true)
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: moStat<EOT, Pair>(Pair(Fitness(), 0.0), "moments (average and stdev)"),
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reInitSol(_reInitSol), firstTime(true),
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nbSolutionsEncountered(0), currentAvg(0), currentVar(0)
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{ }
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/**
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* Initialization of the best solution on the first one
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* @param _sol the first solution
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*/
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virtual void init(EOT & _sol) {
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if (reInitSol || firstTime)
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{
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value() = Pair(0.0,0.0);
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nbSolutionsEncountered = currentAvg = currentVar = 0;
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firstTime = false;
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}
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/*else if (firstTime)
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{
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value() = 0.0;
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firstTime = false;
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}*/
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operator()(_sol);
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}
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/**
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* Update the best solution
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* @param _sol the current solution
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*/
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virtual void operator()(EOT & _sol) {
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++nbSolutionsEncountered;
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double x = _sol.fitness();
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double oldAvg = currentAvg;
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currentAvg = oldAvg + (x - oldAvg)/nbSolutionsEncountered;
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if (nbSolutionsEncountered > 1) // <- not really necessary
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{
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//value() = (value()/nbSolutionsEncountered + _sol.fitness())/(nbSolutionsEncountered+1);
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double oldVar = currentVar;
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currentVar = oldVar + (x - oldAvg) * (x - currentAvg);
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value() = Pair(currentAvg, currentVar/nbSolutionsEncountered);
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}
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}
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/**
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* @return name of the class
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*/
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virtual std::string className(void) const {
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return "moFitnessVarianceStat";
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}
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protected:
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bool reInitSol;
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bool firstTime;
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double
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nbSolutionsEncountered
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, currentAvg
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, currentVar // actually the var * n
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;
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};
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#endif // moFitnessMomentsStat_h
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143
mo/src/continuator/moStdDevEstimator.h
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143
mo/src/continuator/moStdDevEstimator.h
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#ifndef __moStdDevEstimator_h__
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#define __moStdDevEstimator_h__
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#include <eo>
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#include <mo>
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#include <moFitnessVarianceStat.h> // TODO rm
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#include <iostream> // TODO rm
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// TODO make tests
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template< class T >
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class eoOptional {
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public:
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static const eoOptional<T> null; // = eoOptional<T>();
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eoOptional (T& init)
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: _val(&init)
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{ }
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bool hasValue() const
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{
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return _val != NULL;
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}
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T& get () const
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{
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if (!hasValue())
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throw std::runtime_error("Cannot get a reference from a eoOptional wrapper with no value");
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return *_val;
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}
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protected:
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eoOptional ()
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: _val(NULL)
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{ }
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private:
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T* _val;
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};
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template< class T >
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const eoOptional<T> eoOptional<T>::null = eoOptional<T>();
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template< class EOT, class Neighbor >
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class moStdDevEstimator : public eoUF<EOT&, double>
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{
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public:
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/**
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* General constructor for the estimator
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* @param continuator a user-defined continuator
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* @param neighborhood the neighborhood
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* @param fullEval the full evaluation function
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* @param eval neighbor's evaluation function
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* @param walker a local search algorithm
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*/
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moStdDevEstimator<EOT,Neighbor> (
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moContinuator<Neighbor>& continuator,
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moNeighborhood < Neighbor > & neighborhood,
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eoEvalFunc<EOT>& fullEval,
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/* The following should be read:
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moEval<Neighbor> >& eval = _default_eval
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* (which is not possible to achieve as is in C++) */
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const eoOptional< moEval<Neighbor> >& eval = eoOptional< moEval<Neighbor> >::null,
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const eoOptional< moLocalSearch<Neighbor> >& walker = eoOptional< moLocalSearch<Neighbor> >::null
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)
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: _default_eval ( fullEval ),
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_eval(eval.hasValue()? eval.get(): _default_eval),
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_default_continuator( 0 ),
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_continuator( _continuator ),
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_checkpoint( _continuator ),
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_default_walker( neighborhood, fullEval, _eval, _checkpoint ),
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_walker( walker.hasValue()? walker.get(): _default_walker )
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{
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_checkpoint.add( _varStat );
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}
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/**
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* Simpler constructor for the estimator
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* @param max_iters the number of steps the default moIterContinuator should perform
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* @param neighborhood the neighborhood
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* @param fullEval the full evaluation function
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* @param eval neighbor's evaluation function
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* @param walker a local search algorithm
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*/
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moStdDevEstimator<EOT,Neighbor> (
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unsigned int max_iters,
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moNeighborhood < Neighbor > & neighborhood,
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eoEvalFunc<EOT>& fullEval,
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const eoOptional< moEval<Neighbor> >& eval = eoOptional< moEval<Neighbor> >::null,
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const eoOptional< moLocalSearch<Neighbor> >& walker = eoOptional< moLocalSearch<Neighbor> >::null
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)
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: _default_eval ( fullEval ),
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_eval(eval.hasValue()? eval.get(): _default_eval),
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_default_continuator( max_iters, false ),
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_continuator( _default_continuator ),
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_checkpoint( _continuator ),
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_default_walker( neighborhood, fullEval, _eval, _checkpoint ),
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_walker( walker.hasValue()? walker.get(): _default_walker )
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{
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_checkpoint.add( _varStat );
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}
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/**
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* Evaluates the estimator with the walker algorithm and returns the standard deviation
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* @param solution the solution from where to start the walk
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*/
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double operator()( EOT & solution )
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{
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_walker(solution);
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return sqrt(_varStat.value());
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}
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/**
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* @return the class name
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*/
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virtual std::string className(void) const {
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return "moStdDevEstimator";
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}
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private:
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moFullEvalByCopy <Neighbor> _default_eval;
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moEval<Neighbor>& _eval;
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moIterContinuator <Neighbor> _default_continuator;
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moContinuator <Neighbor>& _continuator;
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moCheckpoint <Neighbor> _checkpoint;
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moRandomWalk <Neighbor> _default_walker;
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moLocalSearch <Neighbor> _walker;
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moFitnessVarianceStat<EOT> _varStat;
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};
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#endif // __moStdDevEstimator_h__
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