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#ifndef __HYPERNEAT_POPULATION_HPP__
#define __HYPERNEAT_POPULATION_HPP__
#include <HyperNeat/Organism.hpp>
#include <HyperNeat/Innovation.hpp>
#include <HyperNeat/Utils/Random.hpp>
#include <HyperNeat/Utils/Vector.hpp>
#include <HyperNeat/Utils/Pointer.hpp>
#include <HyperNeat/NeuralNetPrms.hpp>
#include <HyperNeat/NoveltyMetric.hpp>
#include <HyperNeat/Utils/Vector2D.hpp>
#include <HyperNeat/Utils/Function.hpp>
#include <HyperNeat/PopulationPrms.hpp>
namespace hyperneat
{
class NeuralNet;
class NoveltyMetricPrms;
class Population
{
public:
void create(const PopulationPrms& popPrms);
void create(const PopulationPrms& popPrms, const NeuralNetPrms& nnPrms);
void create(const PopulationPrms& popPrms, const NeuralNetPrms& nnPrms, const NoveltyMetricPrms& nmPrms);
void shutdown(bool resetOrganisms = false, bool archiveOrganisms = false);
~Population();
void setMinimumLifetime(size_t lifetime);
const PopulationPrms& getPopulationPrms() const;
const NeuralNetPrms& getNeuralNetPrms() const;
bool hasNeuralNets() const;
const Vector<Organism>& getAllOrganisms() const;
const Vector2D<Organism*>& getSpecies() const;
Organism& getOrganism(size_t i);
Organism& getChampion();
const Vector<Organism*>& getSpecie(size_t i) const;
void lock();
void unlock();
bool isLocked() const;
void lockOrganism(size_t i);
void unlockOrganism(size_t i);
bool isOrganismLocked(size_t i) const;
bool isAnyOrganismLocked() const;
size_t getLockedOrganisms() const;
void freezeOrganism(size_t i);
void unfreezeOrganism(size_t i);
bool isOrganismFrozen(size_t i) const;
bool isAnyOrganismFrozen() const;
size_t getFrozenOrganisms() const;
bool isOrganismBeingGenerated(size_t i) const;
bool isAnyOrganismBeingGenerated() const;
size_t getOrganismsBeingGenerated() const;
size_t getReadyOrganisms() const;
const Vector<Innovation>& getInnovations() const;
size_t getInnovationsCount() const;
size_t getBasicInnovationsCount() const;
Organism* getLastReplacement();
Organism* getLastMother();
Organism* getLastFather();
size_t getReplacements() const;
bool recentReplacement() const;
double getDistanceThreshold() const;
size_t getOldOrganisms() const;
size_t getMinimumOldOrganisms() const;
double getAverageFitness() const;
double getAverageOldFitness() const;
void setNoveltyMetric(const NoveltyMetricPrms& prms);
void clearNoveltyMetric();
bool isNoveltyMetricSet() const;
const NoveltyMetric& getNoveltyMetric() const;
size_t getUpdates() const;
double& fitnessOf(size_t i);
bool update(Function<void(void)> beforeReplacement = []() {}, Function<void(void)> afterReplacement = []() {});
private:
void generateAllNeuralNets();
void replaceOrganism();
Organism* killPoorOrganism();
Vector<Organism*>* chooseParentSpecie();
void breedAsexually(Genome& child, const Genome& mother);
void breedSexually(Genome& child, const Genome& mother, const Genome& father);
bool mutateNodesAndLinks(Genome& child);
void assignToSpecie(Organism& org);
void organizeSpecies();
double computeDistance(const Genome& g1, const Genome& g2) const;
size_t getRandSeed() const;
size_t getRandSize(size_t low, size_t hi);
double getRandReal(double low, double hi);
double getRandWeight();
double getWeightDeviation();
NodeType getRandNodeType();
bool getChance(double ratio);
PopulationPrms _prms;
Pointer<NeuralNetPrms> _nnPrms;
Vector2D<Organism*> _species;
Vector<Organism> _allOrganisms;
bool _populationLock = false;
size_t _lockedOrganisms = 0;
size_t _frozenOrganisms = 0;
Atomic<size_t> _organismsBeingGenerated = {0};
Vector<Innovation> _innovations;
size_t _basicInnovs = 0;
Organism* _lastReplacement = nullptr;
Organism* _lastMother = nullptr;
Organism* _lastFather = nullptr;
size_t _replacements = 0;
bool _recentReplacement = false;
double _distanceThreshold = 0.0;
size_t _oldOrganisms = 0;
size_t _minOldOrganisms = 0;
Pointer<NoveltyMetric> _noveltyMetric;
size_t _updates = 0;
RandGen _randGen;
IntDist _nodeTypeSelector = IntDist(0, NODE_TYPES_COUNT - 1);
RealDist _weightSelector = RealDist(0.0, 1.0);
BellDist _weightDeviator;
RealDist _chanceSelector;
friend class LoadFile;
friend class Organism;
friend class NoveltyMetric;
};
}
#endif
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