Inheritance diagram for pagmo::util::racing::metrics_algos::standard:

Public Member Functions
	standard (const std::vector< problem::base_ptr > &probs=std::vector< problem::base_ptr >(), const std::vector< algorithm::base_ptr > &algos=std::vector< algorithm::base_ptr >(), unsigned int seed=0, unsigned int pop_size=100)
	Constructor of the performance metrics of algorithms on a single problem. More...

Public Member Functions inherited from pagmo::problem::base_stochastic
	base_stochastic (int, unsigned int=0u)
	Constructor from global dimension and random seed. More...

	base_stochastic (int, int, int, int, int, const double &, unsigned int)
	Constructor from global dimension, integer dimension, fitness dimension, global constraints dimension, inequality constraints dimension and constraints tolerance. More...

	base_stochastic (int, int, int, int, int, const std::vector< double > &, unsigned int)
	Constructor from global dimension, integer dimension, fitness dimension, global constraints dimension, inequality constraints dimension and constraints tolerance vector. More...

unsigned int	get_seed () const
	Gets the pseudo random generator seed. More...

void	set_seed (unsigned int) const
	Sets the pseudo random generator seed. More...

Public Member Functions inherited from pagmo::problem::base
	base (int, int=0, int=1, int=0, int=0, const double &=0)
	Constructor from global dimension, integer dimension, fitness dimension, global constraints dimension, inequality constraints dimension and constraints tolerance. More...

	base (int, int, int, int, int, const std::vector< double > &)
	Constructor from global dimension, integer dimension, fitness dimension, global constraints dimension, inequality constraints dimension and constraints tolerance. More...

	base (const double &, const double &, int, int=0, int=1, int=0, int=0, const double &=0)
	Constructor from values for lower and upper bounds, global dimension, integer dimension, fitness dimension, global constraints dimension, inequality constraints dimension and constraints tolerance. More...

	base (const decision_vector &, const decision_vector &, int=0, int=1, int=0, int=0, const double &=0)
	Constructor from upper/lower bounds, integer dimension, fitness dimension, global constraints dimension, inequality constraints dimension and constraints tolerance. More...

template<std::size_t N>
	base (const double(&v1)[N], const double(&v2)[N], int ni=0, int nf=1, int nc=0, int nic=0, const double &c_tol=0)
	Constructor from raw arrays, integer dimension, fitness dimension, global constraints dimension, inequality constraints dimension and constraints tolerance. More...

template<class Iterator1 , class Iterator2 >
	base (Iterator1 start1, Iterator1 end1, Iterator2 start2, Iterator2 end2, int ni=0, int nf=1, int nc=0, int nic=0, const double &c_tol=0)
	Constructor from iterators, integer dimension, fitness dimension, global constraints dimension, inequality constraints dimension and constraints tolerance. More...

virtual	~base ()
	Trivial destructor. More...

std::string	human_readable () const
	Return human readable representation of the problem. More...

virtual std::string	human_readable_extra () const
	Extra information in human readable format. More...

bool	operator== (const base &) const
	Equality operator. More...

bool	operator!= (const base &) const
	Inequality operator. More...

bool	is_compatible (const base &) const
	Compatibility operator. More...

bool	compare_x (const decision_vector &, const decision_vector &) const
	Compare decision vectors. More...

bool	verify_x (const decision_vector &) const
	Verify compatibility of decision vector x with problem. More...

bool	compare_fc (const fitness_vector &, const constraint_vector &, const fitness_vector &, const constraint_vector &) const
	Simultaneous fitness-constraint comparison. More...

virtual void	pre_evolution (population &) const
	Pre-evolution hook. More...

virtual void	post_evolution (population &) const
	Post-evolution hook. More...

virtual void	set_sparsity (int &lenG, std::vector< int > &iGfun, std::vector< int > &jGvar) const
	Sets the sparsity pattern of the gradient. More...

const decision_vector &	get_lb () const
	Lower bounds getter. More...

const decision_vector &	get_ub () const
	Upper bounds getter. More...

void	set_bounds (const decision_vector &, const decision_vector &)
	Bounds setter from pagmo::decision_vector. More...

template<class Iterator1 , class Iterator2 >
void	set_bounds (Iterator1 start1, Iterator1 end1, Iterator2 start2, Iterator2 end2)
	Bounds setter from iterators. More...

template<std::size_t N>
void	set_bounds (const double(&v1)[N], const double(&v2)[N])
	Bounds setter from raw arrays. More...

void	set_bounds (const double &, const double &)
	Set bounds to specified values. More...

void	set_bounds (int, const double &, const double &)
	Set bounds to specified values. More...

void	set_lb (const decision_vector &)
	Set lower bounds from pagmo::decision_vector. More...

void	set_lb (int, const double &)
	Set specific lower bound to value. More...

void	set_lb (const double &)
	Set all lower bounds to value. More...

template<class Iterator >
void	set_lb (Iterator start, Iterator end)
	Lower bounds setter from iterators. More...

template<std::size_t N>
void	set_lb (const double(&v)[N])
	Lower bounds setter from raw array. More...

void	set_ub (const decision_vector &)
	Set upper bounds from pagmo::decision_vector. More...

void	set_ub (int, const double &)
	Set specific upper bound to value. More...

void	set_ub (const double &)
	Set all upper bounds to value. More...

template<class Iterator >
void	set_ub (Iterator start, Iterator end)
	Upper bounds setter from iterators. More...

template<std::size_t N>
void	set_ub (const double(&v)[N])
	Upper bounds setter from raw array. More...

unsigned int	get_fevals () const
	Return number of function evaluations. More...

unsigned int	get_cevals () const
	Return number of constraints function evaluations. More...

size_type	get_dimension () const
	Return global dimension. More...

size_type	get_i_dimension () const
	Return integer dimension. More...

f_size_type	get_f_dimension () const
	Return fitness dimension. More...

c_size_type	get_c_dimension () const
	Return global constraints dimension. More...

c_size_type	get_ic_dimension () const
	Return inequality constraints dimension. More...

const std::vector< double > &	get_c_tol () const
	Return constraints tolerance. More...

double	get_diameter () const
	Get the diameter of the problem. More...

virtual std::string	get_name () const
	Get problem's name. More...

constraint_vector	compute_constraints (const decision_vector &) const
	Compute constraints and return constraint vector. More...

void	compute_constraints (constraint_vector &, const decision_vector &) const
	Compute constraints and write them into contraint vector. More...

bool	compare_constraints (const constraint_vector &, const constraint_vector &) const
	Compare constraint vectors. More...

bool	test_constraint (const constraint_vector &, const c_size_type &) const
	Test i-th constraint of c (using tolerance information). More...

bool	feasibility_x (const decision_vector &) const
	Test feasibility of decision vector. More...

bool	feasibility_c (const constraint_vector &) const
	Test feasibility of constraint vector. More...

fitness_vector	objfun (const decision_vector &) const
	Return fitness of pagmo::decision_vector. More...

void	objfun (fitness_vector &, const decision_vector &) const
	Write fitness of pagmo::decision_vector into pagmo::fitness_vector. More...

bool	compare_fitness (const fitness_vector &, const fitness_vector &) const
	Compare fitness vectors. More...

void	reset_caches () const
	Reset internal caches. More...

const std::vector< constraint_vector > &	get_best_c (void) const
	Get the best known constraint vector. More...

const std::vector< decision_vector > &	get_best_x (void) const
	Get the best known decision vector. More...

const std::vector< fitness_vector > &	get_best_f (void) const
	Get the best known fitness vector. More...

void	set_best_x (const std::vector< decision_vector > &)
	Sets the best known decision vectors. More...

Protected Member Functions
	standard (const standard &)
	Copy Constructor. Performs a deep copy.

problem::base_ptr	clone () const
	Clone method.

void	objfun_impl (fitness_vector &, const decision_vector &) const
	The performance of an algorithm encoded in the fitness function. More...

void	compute_constraints_impl (constraint_vector &, const decision_vector &) const
	The performance of an algorithm in terms of a constraint vector. More...

Protected Member Functions inherited from pagmo::problem::base
virtual bool	equality_operator_extra (const base &) const
	Extra requirements for equality. More...

virtual bool	compare_fc_impl (const fitness_vector &, const constraint_vector &, const fitness_vector &, const constraint_vector &) const
	Implementation of simultaneous fitness-constraint comparison. More...

void	estimate_sparsity (const decision_vector &, int &lenG, std::vector< int > &iGfun, std::vector< int > &jGvar) const
	Heuristics to estimate the sparsity pattern of the problem. More...

void	estimate_sparsity (int &lenG, std::vector< int > &iGfun, std::vector< int > &jGvar) const
	Heuristics to estimate the sparsity pattern of the problem. More...

virtual void	compute_constraints_impl (constraint_vector &, const decision_vector &) const
	Implementation of constraint computation. More...

virtual bool	compare_constraints_impl (const constraint_vector &, const constraint_vector &) const
	Implementation of constraint vector comparison. More...

virtual bool	compare_fitness_impl (const fitness_vector &, const fitness_vector &) const
	Implementation of fitness vectors comparison. More...

Friends
class	boost::serialization::access

Additional Inherited Members
Public Types inherited from pagmo::problem::base
typedef decision_vector::size_type	size_type
	Problem's size type: the same as pagmo::decision_vector's size type.

typedef fitness_vector::size_type	f_size_type
	Fitness' size type: the same as pagmo::fitness_vector's size type.

typedef constraint_vector::size_type	c_size_type
	Constraints' size type: the same as pagmo::constraint_vector's size type.

Static Public Attributes inherited from pagmo::problem::base
static const std::size_t	cache_capacity = 5
	Capacity of the internal caches.

Protected Attributes inherited from pagmo::problem::base_stochastic
rng_double	m_drng
	Random number generator for double-precision floating point values.

rng_uint32	m_urng
	Random number generator for unsigned integer values.

unsigned int	m_seed
	Seed of the random number generator.

Detailed Description

This class implements the mechanism to assign a quality measure to each member of a set of algorithms, while being treated as "a population of algorithms". Required by internally by race_algo to transform the racing of algorithm into racing of individuals.

The decision vector in this case is a single integer, representing which algorithm is to be invoked to evolve the population, e.g. if x = [k], this problem returns some measure of how well the k-th algorithm could evolve a population.

The standard way of assigning fitness to an algorithm contains two cases: (1) Single problem: Algo's fitness assigned to be the fitness of the evolved champion on the problem, evolved by the specified algorithm. (2) Multiple problems: Randomly sample a single problem (based on current seed) from the pool of problems, then proceed as (1).

Currently supports box constrained and equality / inequality constrained single-objective problems

Definition at line 51 of file race_algo.cpp.

Constructor & Destructor Documentation

pagmo::util::racing::metrics_algos::standard::standard	(	const std::vector< problem::base_ptr > &	probs = `std::vector<problem::base_ptr>()`,
		const std::vector< algorithm::base_ptr > &	algos = `std::vector<algorithm::base_ptr>()`,
		unsigned int	seed = `0`,
		unsigned int	pop_size = `100`
	)

Constructor of the performance metrics of algorithms on a single problem.

The performance of each algorithm is encoded in the fitness implementation of this meta-problem. For example, to obtain the performance of the first algorithm, one can do (in fact only race_algo should know about this):

std::vector<unsigned int> idx = {0}; fitness_values f = this->objfun(idx);

Parameters

[in]	probs	std::vector of pagmo::problem::base_ptr against which the algorithms will be evaluated
[in]	algos	std::vector of pagmo::algorithm::base_ptr
[in]	seed	Seed to be used internally as a stochastic problem
[in]	pop_size	Size of the population to be evolved

Exceptions

value_error if there are incompatible algorithms or problems in the supplied sets (multi-objective algorithms not supported yet).

Definition at line 109 of file race_algo.cpp.

Member Function Documentation

void pagmo::util::racing::metrics_algos::standard::compute_constraints_impl	(	constraint_vector &	c,
		const decision_vector &	x
	)		const

protected

The performance of an algorithm in terms of a constraint vector.

Similar to objfun_impl(), the constraint violation is determined by the champion of the evolved population.

Definition at line 182 of file race_algo.cpp.

void pagmo::util::racing::metrics_algos::standard::objfun_impl	(	fitness_vector &	f,
		const decision_vector &	x
	)		const

protectedvirtual

The performance of an algorithm encoded in the fitness function.

The performance of an algorithm is defined as the champion a population, after being evolved by the algorithm.

Implements pagmo::problem::base.

Definition at line 171 of file race_algo.cpp.

The documentation for this class was generated from the following file:

race_algo.cpp

Public Member Functions

Protected Member Functions

Friends

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation