#include <garp.hh>

Inheritance diagram for Garp:

Collaboration diagram for Garp:

Public Member Functions
	Garp ()

virtual	~Garp ()

int	initialize ()

int	iterate ()

int	done () const

float	getProgress () const

Scalar	getValue (const Sample &x) const

int	getConvergence (Scalar *const val) const

int	getGeneration ()

void	deleteTempDataMembers ()

Public Member Functions inherited from AlgorithmImpl
	AlgorithmImpl (AlgMetadata const *metadata)

virtual	~AlgorithmImpl ()

void	setParameters (int nparam, AlgParameter const *param)

void	setParameters (const ParamSetType &)

std::string const	getID () const

AlgMetadata const *	getMetadata () const

AlgorithmPtr	getFreshCopy ()

virtual int	supportsModelProjection () const

Model	createModel (const SamplerPtr &samp, CallbackWrapper *func=0)

void	setSampler (const SamplerPtr &samp)

virtual int	finalize ()

virtual int	needNormalization ()

Normalizer *	getNormalizer () const

void	setNormalization (const SamplerPtr &samp) const

void	setNormalization (const EnvironmentPtr &env) const

virtual Model	getModel () const

ConfigurationPtr	getConfiguration () const

void	setConfiguration (const ConstConfigurationPtr &)

Public Member Functions inherited from Configurable
virtual	~Configurable ()

Protected Member Functions
virtual void	_getConfiguration (ConfigurationPtr &) const

virtual void	_setConfiguration (const ConstConfigurationPtr &)

Protected Member Functions inherited from AlgorithmImpl
int	dimDomain ()

int	getParameter (std::string const &name, std::string *value)

int	getParameter (std::string const &name, double *value)

int	getParameter (std::string const &name, float *value)

int	getParameter (std::string const &name, int *value)

Private Member Functions
void	cacheSamples (const SamplerPtr &, OccurrencesPtr &, int resamples)

void	colonize (GarpRuleSet *ruleset, int numRules)

void	evaluate (GarpRuleSet *ruleset)

void	keepFittest (GarpRuleSet source, GarpRuleSet target, PerfIndex perfIndex)

void	select (GarpRuleSet source, GarpRuleSet target, double gapsize)

void	mutate (GarpRuleSet *ruleset)

void	crossover (GarpRuleSet *ruleset)

Private Attributes
int	_max_gen

int	_popsize

int	_resamples

double	_acc_limit

double	_conv_limit

double	_mortality

double	_significance

double	_crossover_rate

double	_mutation_rate

double	_gapsize

GarpRuleSet *	_fittest

GarpRuleSet *	_offspring

BioclimHistogram	_bioclimHistogram

Regression	_regression

OccurrencesPtr	_cachedOccs

double	_convergence

int	_improvements

int	_curr_heur_count [5]

int	_prev_heur_count [5]

int	_gen

float	_maxProgress

Additional Inherited Members
Public Types inherited from AlgorithmImpl
typedef std::map< icstring, std::string >	ParamSetType

Protected Attributes inherited from AlgorithmImpl
SamplerPtr	_samp

Normalizer *	_normalizerPtr

ParamSetType	_param

Detailed Description

Implementation of GARP: Genetic Algorithm for Rule-set Production

Definition at line 57 of file garp.hh.

Constructor & Destructor Documentation

Garp::Garp ( )

Definition at line 231 of file garp.cpp.

References _acc_limit, _conv_limit, _convergence, _crossover_rate, _curr_heur_count, _fittest, _gapsize, _gen, _improvements, _max_gen, _maxProgress, _mortality, _mutation_rate, AlgorithmImpl::_normalizerPtr, _offspring, _popsize, _prev_heur_count, _resamples, and _significance.

Garp::~Garp ( )

virtual

Definition at line 270 of file garp.cpp.

References _fittest, and _offspring.

Member Function Documentation

void Garp::_getConfiguration ( ConfigurationPtr & config ) const

protectedvirtual

Reimplemented from AlgorithmImpl.

Definition at line 444 of file garp.cpp.

References _acc_limit, _crossover_rate, _fittest, _gapsize, _gen, _mortality, _mutation_rate, _significance, done(), GarpRuleSet::get(), GarpRule::getChrom1(), GarpRule::getChrom2(), GarpRule::getPerformanceArray(), GarpRule::getPrediction(), GarpRuleSet::numRules(), and GarpRule::type().

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void Garp::_setConfiguration ( const ConstConfigurationPtr & config )

protectedvirtual

Reimplemented from AlgorithmImpl.

Definition at line 489 of file garp.cpp.

References _acc_limit, _crossover_rate, _fittest, _gapsize, _gen, _mortality, _mutation_rate, _offspring, _popsize, _significance, GarpRuleSet::add(), Log::error(), AlgorithmImpl::getParameter(), Log::instance(), and Sample::size().

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void Garp::cacheSamples	(	const SamplerPtr &	sampler,
		OccurrencesPtr &	cachedOccs,
		int	resamples
	)

private

Definition at line 331 of file garp.cpp.

References GeoTransform::getDefaultCS(), and OccurrencesImpl::reserve().

Referenced by initialize().

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void Garp::colonize	(	GarpRuleSet *	ruleset,
		int	numRules
	)

private

Fill a rule set with newly generated rules

Parameters

ruleset	rule set where rules will be added to
numRules	number of rules to be added to the rule set.

Definition at line 656 of file garp.cpp.

References _bioclimHistogram, _regression, AlgorithmImpl::_samp, GarpRuleSet::add(), Random::get(), GarpRuleSet::numRules(), and GarpRule::setPrediction().

Referenced by initialize(), and iterate().

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void Garp::crossover ( GarpRuleSet * ruleset )

private

Perform crossing over with rules in a rule set

Parameters

ruleset Rule set containing rules to be crossed over

Definition at line 793 of file garp.cpp.

References _crossover_rate, AlgorithmImpl::_samp, GarpRule::crossover(), Random::get(), GarpRuleSet::get(), and GarpRuleSet::numRules().

Referenced by iterate().

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void Garp::deleteTempDataMembers ( )

Deletes data structures that are not needed once the model is generated. Implemented to save some memory when clients have to store too many Garp objects.

Definition at line 818 of file garp.cpp.

References _offspring.

int Garp::done ( ) const

virtual

Check if the model generation is completed (e.g. convergence point has been met.

Returns: Implementation specific but usually 1 for completion.

Reimplemented from AlgorithmImpl.

Definition at line 419 of file garp.cpp.

References _conv_limit, _convergence, _gen, and _max_gen.

Referenced by _getConfiguration(), getProgress(), and iterate().

void Garp::evaluate ( GarpRuleSet * ruleset )

private

Evaluate rules from a rule set based on their performance to predict points provided by a sampler object.

Parameters

ruleset rule set to be tested.

Definition at line 640 of file garp.cpp.

References _cachedOccs, GarpRule::evaluate(), GarpRuleSet::get(), and GarpRuleSet::numRules().

Referenced by iterate().

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int Garp::getConvergence ( Scalar *const val ) const

virtual

Returns a value that represents the convergence of the algorithm expressed as a number between 0 and 1 where 0 represents model completion.

Returns

Parameters

val

Reimplemented from AlgorithmImpl.

Definition at line 435 of file garp.cpp.

References _convergence.

int Garp::getGeneration ( )

inline

Definition at line 111 of file garp.hh.

References _gen.

float Garp::getProgress ( ) const

virtual

Return progress so far

Reimplemented from AlgorithmImpl.

Definition at line 401 of file garp.cpp.

References _conv_limit, _convergence, _gen, _max_gen, _maxProgress, and done().

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Scalar Garp::getValue ( const Sample & x ) const

virtual

This method is used when projecting the model.

Note: This method is inherited from the Algorithm class

Returns

Parameters

x	a pointer to a vector of openModeller Scalar type (currently double). The vector should contain values looked up on the environmental variable layers into which the mode is being projected.

Implements AlgorithmImpl.

Definition at line 427 of file garp.cpp.

References _fittest, and GarpRuleSet::getValue().

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int Garp::initialize ( )

virtual

Initialize model by colonizing it with new rules.

Note: This method is inherited from the Algorithm class

Returns: 0 on error

Implements AlgorithmImpl.

Definition at line 290 of file garp.cpp.

References _bioclimHistogram, _cachedOccs, _conv_limit, _fittest, _max_gen, _offspring, _popsize, _regression, _resamples, AlgorithmImpl::_samp, cacheSamples(), Regression::calculateParameters(), colonize(), Log::error(), AlgorithmImpl::getParameter(), BioclimHistogram::initialize(), and Log::instance().

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int Garp::iterate ( )

virtual

Start model execution (build the model). This method is the main body of the Genetic Algorithm. The steps during the algorithm are: 1) Evaluate current population testing the rules against data points 2) Select fittest individuals from population based on significance 3) If reached any stop condition (# of iterations or convergence limit) then output best result and stop 4) Else perform reproduction, generating a new offspring from current population 5) Repeat from step 1.

Returns: 0 on error

Reimplemented from AlgorithmImpl.

Definition at line 351 of file garp.cpp.

References _fittest, _gapsize, _gen, _offspring, _popsize, _significance, colonize(), crossover(), defaultPerfIndex, done(), evaluate(), GarpRuleSet::filter(), keepFittest(), mutate(), GarpRuleSet::performanceSummary(), select(), and GarpRuleSet::trim().

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void Garp::keepFittest	(	GarpRuleSet *	source,
		GarpRuleSet *	target,
		PerfIndex	perfIndex
	)

private

Keep fittest individuals from source rule set storing them in target rule set in descending order of fitness.

Parameters

source	Pointer to the source rule set where rules will be selected from (usually the previous generated population)
target	Pointer to the target rule set where fittest rules will be transferred to (usually the fittest rule set)
perfIndex	Index of value on performance array that will be used to select individuals.

Note: : This method produces a side effect that is to update the statistics about heuristic operators performance (that will be used to adjust probabilities of application of those operators on future generations) and overall rule performance that will be used to compute the changes to the convergence value.

Definition at line 579 of file garp.cpp.

References _convergence, _improvements, GarpRule::clone(), GarpRuleSet::findSimilar(), GarpRuleSet::get(), GarpRule::getPerformance(), GarpRuleSet::insert(), GarpRuleSet::numRules(), and GarpRuleSet::remove().

Referenced by iterate().

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void Garp::mutate ( GarpRuleSet * ruleset )

private

Mutate rules in a rule set

Parameters

ruleset Rule set containing rules to be mutated

Definition at line 780 of file garp.cpp.

References _gen, GarpRuleSet::get(), GarpRule::mutate(), and GarpRuleSet::numRules().

Referenced by iterate().

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void Garp::select	(	GarpRuleSet *	source,
		GarpRuleSet *	target,
		double	gapsize
	)

private

Select fittest individuals and store them into target ruleset

Parameters

source	Pointer to the rule set containing parents (individuals that will provide genes to create new individuals).
target	Pointer to the target rule set where offspring will be transferred to.
gapsize	Proportion of contribution from the objBest archive set to the new population.

Definition at line 699 of file garp.cpp.

References _popsize, GarpRuleSet::add(), GarpRuleSet::clear(), GarpRule::clone(), defaultPerfIndex, error, Log::error(), GarpRule::forceEvaluation(), Random::get(), GarpRuleSet::get(), GarpRule::getPerformance(), Log::instance(), GarpRuleSet::numRules(), and GarpRuleSet::performanceSummary().