/usr/include/gamera/knnga.hpp is in python-gamera-dev 3.4.2+svn1437-2.
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* Copyright (C) 2012 Tobias Bolten
*
* This program 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.
*
* This program 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 this program; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
*/
#ifndef gamodule201206
#define gamodule201206
#include "knncoremodule.hpp"
#include <iostream>
#include <stdio.h>
#include <vector>
#include <string>
#include <stdexcept>
#include <cmath>
#include <limits>
#include <algorithm>
#include <sstream>
#include <time.h>
#include <map>
#ifdef _OPENMP
#include <omp.h>
#endif
#include <eo>
#include <es.h>
#include <ga/eoBitOp.h>
#include <eoStochasticUniversalSelect.h>
#include <eoShiftMutation.h>
#include <eoSwapMutation.h>
#include <eoTwoOptMutation.h>
namespace Gamera { namespace GA {
typedef eoBit<double> SelectionIndi;
typedef eoReal<double> WeightingIndi;
enum OperationMode {GA_SELECTION, GA_WEIGHTING};
template <typename EOT>
class SelectOneDefaultWorth : public eoSelectOne<EOT> {};
/**************************************************************************/
template<class EOT>
class GATwoOptMutation : public eoMonOp<EOT> {
/**************************************************************************/
public:
typedef typename EOT::AtomType GeneType;
GATwoOptMutation(){}
virtual std::string className() const { return "GATwoOptMutation"; }
bool operator()(EOT& _eo) {
// generate two different indices
unsigned int i = eo::rng.random(_eo.size());
unsigned int j;
do {
j = eo::rng.random(_eo.size());
} while(i == j);
unsigned int from = std::min(i,j);
unsigned int to = std::max(i,j);
unsigned int idx = (to - from) / 2;
// inverse between from and to
for(unsigned k = 0; k <= idx; ++k) {
GeneType tmp = _eo[from+k];
_eo[from+k] = _eo[to-k];
_eo[to-k] = tmp;
}
return true;
}
};
/**************************************************************************/
template<class EOT>
class GASwapMutation : public eoMonOp<EOT> {
/**************************************************************************/
public:
typedef typename EOT::AtomType GeneType;
GASwapMutation(const unsigned _howManySwaps=1): howManySwaps(_howManySwaps) {
if(howManySwaps < 1) {
throw std::runtime_error("Invalid number of swaps in GASwapMutation");
}
}
virtual std::string className() const { return "GASwapMutation"; }
bool operator()(EOT& chrom) {
unsigned i, j;
for(unsigned int swap = 0; swap < howManySwaps; swap++) {
// generate two different indices
i=eo::rng.random(chrom.size());
do {
j = eo::rng.random(chrom.size());
} while (i == j);
// swap
GeneType tmp = chrom[i];
chrom[i] = chrom[j];
chrom[j] = tmp;
}
return true;
}
private:
unsigned int howManySwaps;
};
/**************************************************************************/
template <typename EOT>
class GAManualStop : public eoContinue<EOT> {
/**************************************************************************/
protected:
bool continueFlag;
public:
GAManualStop() {
this->continueFlag = true;
}
virtual bool operator() ( const eoPop<EOT>& _vEO ) {
return this->continueFlag;
}
bool getFlag() {
return this->continueFlag;
}
void setFlag(bool flag) {
this->continueFlag = flag;
}
};
/**************************************************************************/
template <typename EOT>
class GABestIndiStat : public eoStat<EOT, std::string> {
/**************************************************************************/
public:
using eoStat<EOT, std::string>::value;
GABestIndiStat(std::string name = "bestIndi")
: eoStat<EOT, std::string>(std::string(""), name)
{}
void operator()(const eoPop<EOT> &pop) {
const EOT bestIndi = pop.best_element();
typename EOT::const_iterator it;
std::ostringstream indiStream;
indiStream << "[";
for (it = bestIndi.begin(); it != bestIndi.end(); ++it) {
indiStream << *it << " , ";
}
indiStream << "]";
value() = indiStream.str();
}
virtual std::string className(void) const { return "GABestIndiStat"; }
};
/**************************************************************************/
template <typename EOT>
class GAClassifierUpdater : public eoContinue<EOT> {
/**************************************************************************/
protected:
KnnObject *knn;
double bestFitness;
std::vector<EOT> bestSolution;
std::map<unsigned int, unsigned int> *indexRelation;
public:
GAClassifierUpdater(KnnObject *knn, std::map<unsigned int, unsigned int> *indexRelation) {
this->knn = knn;
this->bestFitness = 0.0;
this->bestSolution.resize(this->knn->num_features);
this->indexRelation = indexRelation;
}
double getBestFitness() {
return this->bestFitness;
}
virtual bool operator()(const eoPop<EOT>& pop);
virtual std::string className(void) const { return "GAClassifierUpdater"; }
};
template <>
bool GAClassifierUpdater<WeightingIndi>::operator() (const eoPop<WeightingIndi> &pop) {
const WeightingIndi bestIndi = pop.best_element();
WeightingIndi::const_iterator it;
if (bestIndi.fitness() > this->bestFitness) {
this->bestFitness = bestIndi.fitness();
std::fill(this->knn->weight_vector, this->knn->weight_vector + this->knn->num_features, 0.0);
std::fill(this->bestSolution.begin(), this->bestSolution.end(), 0.0);
for (size_t i = 0; i < bestIndi.size(); ++i) {
this->knn->weight_vector[(*this->indexRelation)[i]] = bestIndi[i];
this->bestSolution[(*this->indexRelation)[i]] = bestIndi[i];
}
}
return true;
}
template <>
bool GAClassifierUpdater<SelectionIndi>::operator() (const eoPop<SelectionIndi> &pop) {
const SelectionIndi bestIndi = pop.best_element();
SelectionIndi::const_iterator it;
if (bestIndi.fitness() > this->bestFitness) {
this->bestFitness = bestIndi.fitness();
std::fill(this->knn->selection_vector, this->knn->selection_vector + this->knn->num_features, 0);
std::fill(this->bestSolution.begin(), this->bestSolution.end(), false);
for (size_t i = 0; i < bestIndi.size(); ++i) {
this->knn->selection_vector[(*this->indexRelation)[i]] = bestIndi[i];
this->bestSolution[(*this->indexRelation)[i]] = bestIndi[i];
}
}
return true;
}
// *************************************************************************
template <typename EOT>
class GAFitnessEval : public eoEvalFunc<EOT> {
// *************************************************************************
protected:
KnnObject *knn;
std::map<unsigned int, unsigned int> *indexRelation;
typedef typename EOT::ContainerType ContainerType;
typedef typename EOT::AtomType AtomType;
public:
GAFitnessEval(KnnObject *knn, std::map<unsigned int, unsigned int> *indexRelation) {
this->knn = knn;
this->indexRelation = indexRelation;
}
virtual std::string className(void) const { return "GAFitnessEval"; }
virtual void operator()( EOT &individual );
};
// specialization for weighting individual
template <>
void GAFitnessEval<WeightingIndi>::operator()( WeightingIndi &individual ) {
AtomType* convertedVector = new AtomType[this->knn->num_features];
std::fill(convertedVector, convertedVector + this->knn->num_features, 0.0);
for (size_t i = 0; i < individual.size(); ++i) {
convertedVector[(*this->indexRelation)[i]] = individual[i];
}
std::pair<int, int> looEvalRes;
looEvalRes = leave_one_out(this->knn, std::numeric_limits<int>::max(),
NULL, convertedVector, NULL);
individual.fitness( looEvalRes.first / (double) looEvalRes.second );
delete [] convertedVector;
}
// specialization for selection individual
template <>
void GAFitnessEval<SelectionIndi>::operator()( SelectionIndi &individual ) {
int* convertedVector = new int[this->knn->num_features];
std::fill(convertedVector, convertedVector + this->knn->num_features, 0);
for (size_t i = 0; i < individual.size(); ++i) {
// ยง4.7/4 from the C++ Standard (Integral Conversion):
// If the source type is bool, the value false is converted to zero
// and the value true is converted to one.
convertedVector[(*this->indexRelation)[i]] = (int) individual[i];
}
std::pair<int, int> looEvalRes;
looEvalRes = leave_one_out(this->knn, std::numeric_limits<int>::max(),
convertedVector, NULL, NULL);
individual.fitness( looEvalRes.first / (double) looEvalRes.second );
delete [] convertedVector;
}
////////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////
/**************************************************************************/
template <typename EOT, template <typename IndiType> class EO>
class GAMultiSettingBase {
/**************************************************************************/
protected:
std::vector<EO<EOT>*> *settings;
public:
GAMultiSettingBase<EOT, EO>();
~GAMultiSettingBase<EOT, EO>();
std::vector<EO<EOT>*> * getSettings();
};
/**************************************************************************/
template <typename EOT, template <typename IndiType> class EO>
class GASingleSettingBase {
/**************************************************************************/
protected:
EO<EOT> *setting;
public:
GASingleSettingBase<EOT, EO>();
~GASingleSettingBase<EOT, EO>();
EO<EOT> * getSetting();
};
/**************************************************************************/
class GABaseSetting {
/**************************************************************************/
protected:
int opMode;
unsigned int pSize;
double cRate;
double mRate;
public:
GABaseSetting(int opMode = GA_SELECTION,
unsigned int pSize = 75,
double cRate = 0.95, double mRate = 0.05);
// getter
int getOpMode();
unsigned int getPopSize();
double getCrossRate();
double getMutRate();
// setter
void setOpMode(int opMode);
void setPopSize(unsigned int pSize);
void setCrossRate(double cRate);
void setMutRate(double mRate);
};
/**************************************************************************/
template <typename EOT, template <typename IndiType> class EO = SelectOneDefaultWorth>
class GASelection : public GASingleSettingBase<EOT, EO> {
/**************************************************************************/
public:
void setRoulettWheel();
void setRoulettWheelScaled(double preasure = 2.0);
void setStochUniSampling();
void setRankSelection(double preasure = 2.0, double exponent = 1.0);
void setTournamentSelection(unsigned int tSize = 3);
void setRandomSelection();
};
/**************************************************************************/
template <typename EOT, template <typename IndiType> class EO = eoQuadOp>
class GACrossover : public GAMultiSettingBase<EOT, EO> {
/**************************************************************************/
protected:
eoRealVectorBounds *bound;
public:
GACrossover();
~GACrossover();
// generic functions
void setNPointCrossover(unsigned int n = 1);
void setUniformCrossover(double preference = 0.5);
// weighting functions
void setSBXcrossover(unsigned int numFeatures, double min,
double max, double eta = 1.0);
void setSegmentCrossover(unsigned int numFeatures, double min,
double max, double alpha = 0.0);
void setHypercubeCrossover(unsigned int numFeatures, double min,
double max, double alpha = 0.0);
};
/**************************************************************************/
template <typename EOT, template <typename IndiType> class EO = eoMonOp>
class GAMutation : public GAMultiSettingBase<EOT, EO> {
/**************************************************************************/
protected:
eoRealVectorBounds *bound;
public:
GAMutation();
~GAMutation();
void setShiftMutation();
void setSwapMutation();
void setInversionMutation();
// selection functions
void setBinaryMutation(double rate = 0.05, bool normalize = false);
// weighting functions
void setGaussMutation(unsigned int numFeatures, double min,
double max, double sigma, double p_change = 1.0);
};
/**************************************************************************/
template <typename EOT, template <typename IndiType> class EO = eoReplacement>
class GAReplacement : public GASingleSettingBase<EOT, EO> {
/**************************************************************************/
public:
void setGenerationalReplacement();
void setSSGAworse();
void setSSGAdetTournament(unsigned int tSize = 3);
};
/**************************************************************************/
template <typename EOT, template <typename IndiType> class EO = eoContinue>
class GAStopCriteria : public GAMultiSettingBase<EOT, EO> {
/**************************************************************************/
public:
void setBestFitnessStop(double optimum = 1.0);
void setMaxGenerations(unsigned int n = 100);
void setMaxFitnessEvals(unsigned int n = 5000);
void setSteadyStateStop(unsigned int minGens = 40, unsigned int noChangeGens = 10);
};
/**************************************************************************/
class GAParallelization {
/**************************************************************************/
protected:
bool parallelMode;
unsigned int threadNum;
public:
GAParallelization(bool mode = true, unsigned int threads = 2);
bool isParallel();
void changeMode(bool mode = true);
unsigned int getThreadNum();
void setThreadNum(unsigned int n = 2);
};
/**************************************************************************/
template <typename EOT>
class GAOptimization {
/**************************************************************************/
protected:
bool running;
// basic GA settings
unsigned int popSize;
double crossoverRate;
double mutationRate;
KnnObject *knn;
GABaseSetting *baseSetting;
GASelection<EOT> *selection;
GACrossover<EOT> *crossover;
GAMutation<EOT> *mutation;
GAReplacement<EOT> *replacement;
GAStopCriteria<EOT> *stop;
GAParallelization *parallelization;
GAManualStop<EOT> manualStop;
eoIncrementorParam<unsigned int> *generationCounter;
eoBestFitnessStat<EOT> *bestStat;
GAClassifierUpdater<EOT> *kNNUpdater;
std::ostringstream *monitorStream;
std::ostringstream *bestIndiStream;
public:
GAOptimization<EOT>(KnnObject *knn,
GABaseSetting *baseSetting,
GASelection<EOT> *selection,
GACrossover<EOT> *crossover,
GAMutation<EOT> *mutation,
GAReplacement<EOT> *replacement,
GAStopCriteria<EOT> *stop,
GAParallelization *parallel);
~GAOptimization<EOT>();
void StartCalculation();
void StopCalculation();
// getter
bool getRunStatus();
KnnObject *getKnnObject();
GABaseSetting * getBaseSetting();
GASelection<EOT> * getSelection();
GACrossover<EOT> * getCrossover();
GAMutation<EOT> * getMutation();
GAReplacement<EOT> * getReplacement();
GAStopCriteria<EOT> * getStopCriteria();
GAParallelization * getParallelization();
unsigned int getGenerationCount();
double getBestFitnessValue();
std::string getMonitorString();
std::string getBestIndiString();
// setter
void setKnnObject(KnnObject *knn);
void setBaseSetting(GABaseSetting * baseSetting);
void setSelection(GASelection<EOT> *selection);
void setCrossover(GACrossover<EOT> *crossover);
void setMutation(GAMutation<EOT> *mutation);
void setReplacement(GAReplacement<EOT> *replacement);
void setStopCriteria(GAStopCriteria<EOT> *stop);
void setParallelization(GAParallelization *parallel);
};
#include "knnga.cpp"
}} // end of namespaces
#endif
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