Inheritance diagram for bio_ik::IKNeural2:

Collaboration diagram for bio_ik::IKNeural2:

[legend]

Public Member Functions
	IKNeural2 (const IKParams &p)

void	train ()

void	initialize (const Problem &problem)

const std::vector< double > &	getSolution () const

void	step ()

Public Member Functions inherited from bio_ik::IKBase
virtual void	setParams (const IKParams &p)

	IKBase (const IKParams &p)

double	computeSecondaryFitnessActiveVariables (const double *active_variable_positions)

double	computeSecondaryFitnessAllVariables (const std::vector< double > &variable_positions)

double	computeFitnessActiveVariables (const std::vector< Frame > &tip_frames, const double *active_variable_positions)

double	computeFitnessActiveVariables (const aligned_vector< Frame > &tip_frames, const double *active_variable_positions)

double	computeCombinedFitnessActiveVariables (const std::vector< Frame > &tip_frames, const double *active_variable_positions)

double	computeCombinedFitnessActiveVariables (const aligned_vector< Frame > &tip_frames, const double *active_variable_positions)

bool	checkSolutionActiveVariables (const std::vector< Frame > &tip_frames, const double *active_variable_positions)

bool	checkSolution (const std::vector< double > &variable_positions, const std::vector< Frame > &tips)

double *	extractActiveVariables (const std::vector< double > &variable_positions)

double	computeFitness (const std::vector< double > &variable_positions, const std::vector< Frame > &tip_frames)

double	computeFitness (const std::vector< double > &variable_positions)

virtual size_t	concurrency () const

Public Member Functions inherited from bio_ik::Random
double	random ()

std::size_t	random_index (std::size_t s)

double	random_gauss ()

double	random (double min, double max)

template<class e >
e &	random_element (std::vector< e > &l)

template<class e >
const e &	random_element (const std::vector< e > &l)

size_t	fast_random_index (size_t mod)

template<class T >
const T &	fast_random_element (const std::vector< T > &v)

const double *	make_random_buffer ()

double	fast_random ()

const double *	make_random_gauss_buffer ()

double	fast_random_gauss ()

const double *	fast_random_gauss_n (size_t n)

Static Public Member Functions
static void	find_minmax (const std::vector< fann_type > &values, std::vector< std::pair< fann_type, fann_type >> &minmax)

static void	normalize (std::vector< fann_type > &values, const std::vector< std::pair< fann_type, fann_type >> &minmax)

static void	denormalize (std::vector< fann_type > &values, const std::vector< std::pair< fann_type, fann_type >> &minmax)

Public Attributes
std::vector< double >	solution

FANN::neural_net	net

std::vector< std::pair< fann_type, fann_type > >	input_minmax

std::vector< std::pair< fann_type, fann_type > >	output_minmax

unsigned int	input_count

unsigned int	output_count

bool	trained

size_t	iterations = 0

std::vector< fann_type >	inputs

std::vector< fann_type >	outputs

std::vector< Frame >	tip_objectives

Public Attributes inherited from bio_ik::IKBase
IKParams	params

RobotFK	model

RobotInfo	modelInfo

int	thread_index

Problem	problem

std::vector< Frame >	null_tip_frames

volatile int	canceled

std::vector< double >	temp_active_variable_positions

Public Attributes inherited from bio_ik::Random
std::minstd_rand	rng

std::normal_distribution< double >	normal_distribution

XORShift64	_xorshift

const double *	random_buffer

size_t	random_buffer_index

const double *	random_gauss_buffer

size_t	random_gauss_index

Additional Inherited Members
Static Public Attributes inherited from bio_ik::Random
static const size_t	random_buffer_size = 1024 * 1024 * 8

Detailed Description

Definition at line 432 of file ik_neural.cpp.

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

src/ik_neural.cpp

Public Member Functions

Static Public Member Functions

Public Attributes

Additional Inherited Members

Detailed Description