Base class for GSL algorithms. More...

#include <base_gsl.h>

Inheritance diagram for pagmo::algorithm::base_gsl:

Data Structures
struct	objfun_wrapper_params
	Structure to feed parameters to the wrappers for the objective function and its derivative. More...

Public Member Functions
	base_gsl ()
	Default constructor. More...

Public Member Functions inherited from pagmo::algorithm::base
	base ()
	Default constructor. More...

virtual void	evolve (population &p) const =0
	Evolve method. More...

virtual base_ptr	clone () const =0
	Clone method. More...

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

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

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

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

void	set_screen_output (const bool p)
	Setter-Getter for protected m_screen_output data. More...

bool	get_screen_output () const
	Gets screen output. More...

void	reset_rngs (const unsigned int) const
	Resets the seed of the internal rngs using a user-provided seed. More...

Static Protected Member Functions
static double	objfun_wrapper (const gsl_vector , void )
	Objective function wrapper. More...

Friends
class	boost::serialization::access

Additional Inherited Members
Protected Attributes inherited from pagmo::algorithm::base
bool	m_screen_output
	Indicates to the derived class whether to print stuff on screen.

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_fevals
	A counter for the number of function evaluations.

Detailed Description

Base class for GSL algorithms.

All GSL algorithms should derive from this class, which will automatically setup the GSL environment for use in PaGMO, and will provide building blocks for wrapping the GSL minimisers.

Please note that GSL provides function minimisers, so that regardless of the comparison functions implemented in problem::base, all GSL algorithms will try to minimise the objective function.

Also, please note that this wrapper handles bounds constraints simply by flattening the out-of-bounds coordinates of the optimised decision vector towards the bounds.

This class of algorithms supports single-objective, unconstrained, continuous optimisation.

See also: http://www.gnu.org/software/gsl/manual/html_node/Multidimensional-Minimization.html for an overview of the minimisers available in the GSL.

Author: Francesco Biscani (blues.nosp@m.carn.nosp@m.i@gma.nosp@m.il.c.nosp@m.om)

Definition at line 56 of file base_gsl.h.

Constructor & Destructor Documentation

pagmo::algorithm::base_gsl::base_gsl ( )

Default constructor.

Will make sure that the GSL environment is initialised properly.

Definition at line 53 of file base_gsl.cpp.

Member Function Documentation

double pagmo::algorithm::base_gsl::objfun_wrapper	(	const gsl_vector *	v,
		void *	params
	)

staticprotected

Objective function wrapper.

Parameters

[in]	v	pointer to the gsl_vector representing the decision vector.
[in]	params	pointer to extra parameters for the internal function.

Returns: the fitness of the input decision vector.

Definition at line 67 of file base_gsl.cpp.

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

Data Structures

Public Member Functions

Static Protected Member Functions

Friends

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation