CCL header file for learning nullspace component. More...

#include <ccl_math.h>
#include <ccl_learn_alpha.h>
#include <gsl/gsl_linalg.h>
#include <gsl/gsl_blas.h>
#include <gsl/gsl_math.h>
#include <gsl/gsl_eigen.h>
#include <gsl/gsl_sf.h>
#include <stdio.h>
#include <string.h>
#include <stdlib.h>
#include <time.h>

Data Structures
struct	LEARN_NCL_MODEL
	This structure describes a "LEARN_NCL_MODEL" (a learn ncl model). This structure constains the dimentionality of the defined problems and the model parameters. It should always initialised with ccl_learn_ncl_model_alloc, and destroyed with ccl_learn_ncl_model_free. More...

struct	LEARN_MODEL_WS
	This structure describes workspace for directly learning the model parameters using linear regression. More...

struct	OBJ_WS
	This structure defines the workspace variables for calculating objective functions. More...

struct	SOLVE_NONLIN_WS
	This structure defines the workspace variables for solving the non-linear LM optimization. More...

Functions
int	ccl_learn_ncl_model_alloc (LEARN_NCL_MODEL *model)
	Allocates the memory for the learn_ncl model. More...

int	ccl_learn_ncl_model_free (LEARN_NCL_MODEL *model)
	Free the memory for the learn_ncl model. More...

void	ccl_learn_ncl (const double X, const double Y, const int dim_x, const int dim_y, const int dim_n, const int dim_b, LEARN_NCL_MODEL *model)
	Computation routine for learn nullspace component . More...

void	ccl_learn_model_dir (LEARN_NCL_MODEL model, const double BX, const double *Y)
	Computation routine for calculating residual errors. More...

int	ccl_learn_model_ws_alloc (LEARN_NCL_MODEL model, LEARN_MODEL_WS ws)
	Allocates the memory for LEARN_MODEL_WS structure. More...

int	ccl_learn_model_ws_free (LEARN_MODEL_WS *ws)
	Free the memory for LEARN_MODEL_WS structure. More...

void	obj_ncl (const LEARN_NCL_MODEL model, const double W, const double BX, const double Y, double fun, double J)
	Computation routine for calculating residual errors. More...

void	obj_ws_alloc (const LEARN_NCL_MODEL model, OBJ_WS ws)
	Allocates the memory for OBJ_WS structure. More...

void	obj_ws_free (OBJ_WS *ws)
	Free the memory for OBJ_WS structure. More...

void	ccl_lsqnonlin (const LEARN_NCL_MODEL model, const double BX, const double Y, const OPTION option, SOLVE_NONLIN_WS lm_ws_param, double *W)
	Computation routine for optimizing non-linear objective functions using LM approach. More...

int	ccl_solve_nonlin_ws_alloc (const LEARN_NCL_MODEL model, SOLVE_NONLIN_WS lm_ws)
	Allocates the memory for SOLVE_NONLIN_WS structure. More...

int	ccl_solve_nonlin_ws_free (SOLVE_NONLIN_WS *lm_ws)
	Free the memory for SOLVE_NONLIN_WS structure. More...

void	predict_ncl (const LEARN_NCL_MODEL model, const double BX, double *Unp)
	Prediction of nullspace components. More...

int	ccl_write_ncl_model (char filename, LEARN_NCL_MODEL model)
	Write model parameters to .txt file. More...

Detailed Description

CCL header file for learning nullspace component.

Function Documentation

void ccl_learn_model_dir	(	LEARN_NCL_MODEL *	model,
		const double *	BX,
		const double *	Y
	)

Computation routine for calculating residual errors.

Parameters

[in]	model	Must be pointer to a valid LEARN_NCL_MODEL structure
[in]	BX	Transformed state variables, must point to an array of dim_b dim_n of doubles*
[in]	Y	Observation actions
[out]	model	Must be pointer to a valid LEARN_NCL_MODEL structure

int ccl_learn_model_ws_alloc	(	LEARN_NCL_MODEL *	model,
		LEARN_MODEL_WS *	ws
	)

Allocates the memory for LEARN_MODEL_WS structure.

Parameters

[in] model Must point to a valid LEARN_MODEL_WS structure

Returns

1 in case of succes
0 in case of failure (e.g. memory could not be allocated)

int ccl_learn_model_ws_free ( LEARN_MODEL_WS * ws )

Free the memory for LEARN_MODEL_WS structure.

Parameters

[in] model Must point to a valid LEARN_MODEL_WS structure

Returns

1 in case of succes
0 in case of failure (e.g. memory could not be freed)

void ccl_learn_ncl	(	const double *	X,
		const double *	Y,
		const int	dim_x,
		const int	dim_y,
		const int	dim_n,
		const int	dim_b,
		LEARN_NCL_MODEL *	model
	)

Computation routine for learn nullspace component .

Parameters

[in]	X	Input state variables, must point to an array of dim_x dim_n doubles*
[in]	Y	Observation actions
[in]	dim_x	Dimensionality of state inputs
[in]	dim_y	Dimensionality of action space
[in]	dim_y	Number of data samples
[in]	dim_y	Dimensionality of rbf
[out]	model	Must be pointer to a valid LEARN_NCL_MODEL structure

int ccl_learn_ncl_model_alloc ( LEARN_NCL_MODEL * model )

Allocates the memory for the learn_ncl model.

Parameters

[in] model Must point to a valid LEARN_NCL_MODEL structure

Returns

1 in case of succes
0 in case of failure (e.g. memory could not be allocated)

int ccl_learn_ncl_model_free ( LEARN_NCL_MODEL * model )

Free the memory for the learn_ncl model.

Parameters

[in] model Must point to a valid LEARN_NCL_MODEL structure

Returns

1 in case of succes
0 in case of failure (e.g. memory could not be freed)

void ccl_lsqnonlin	(	const LEARN_NCL_MODEL *	model,
		const double *	BX,
		const double *	Y,
		const OPTION	option,
		SOLVE_NONLIN_WS *	lm_ws_param,
		double *	W
	)

Computation routine for optimizing non-linear objective functions using LM approach.

Parameters

[in]	model	Must be pointer to a valid LEARN_NCL_MODEL structure.
[in]	BX	Transformed state variables, must point to an array of dim_b dim_n of doubles*
[in]	Y	Observation actions
[in]	option	Options for optimizer
[in]	lm_ws_param	Must point to a valid structure of SOLVE_LM_WS for LM optimizer workspace variables
[out]	W	Returned model parameter, must point to an array of dim_b dim_x doubles*

int ccl_solve_nonlin_ws_alloc	(	const LEARN_NCL_MODEL *	model,
		SOLVE_NONLIN_WS *	lm_ws
	)

Allocates the memory for SOLVE_NONLIN_WS structure.

Parameters

[in] model Must point to a valid SOLVE_NONLIN_WS structure

Returns

1 in case of succes
0 in case of failure (e.g. memory could not be allocated)

int ccl_solve_nonlin_ws_free ( SOLVE_NONLIN_WS * lm_ws )

Free the memory for SOLVE_NONLIN_WS structure.

Parameters

[in] model Must point to a valid SOLVE_NONLIN_WS structure

Returns

1 in case of succes
0 in case of failure (e.g. memory could not be freed)

int ccl_write_ncl_model	(	char *	filename,
		LEARN_NCL_MODEL *	model
	)

Write model parameters to .txt file.

Parameters

[in]	filename	File name
[in]	model	Must be pointer to a valid LEARN_NCL_MODEL structure

void obj_ncl	(	const LEARN_NCL_MODEL *	model,
		const double *	W,
		const double *	BX,
		const double *	Y,
		double *	fun,
		double *	J
	)

Computation routine for calculating residual errors.

Parameters

[in]	model	Must be pointer to a valid LEARN_NCL_MODEL structure
[in]	W	Returned model parameter, must point to an array of dim_b dim_x doubles*
[in]	BX	Transformed state variables, must point to an array of dim_b dim_n of doubles*
[in]	Y	Observation actions
[out]	fun	Returned scalar residual
[out]	J	Returned Jacobian matrix, must point to an array of dim_n dim_x doubles*

void obj_ws_alloc	(	const LEARN_NCL_MODEL *	model,
		OBJ_WS *	ws
	)

Allocates the memory for OBJ_WS structure.

Parameters

[in] model Must point to a valid OBJ_WS structure

Returns

1 in case of succes
0 in case of failure (e.g. memory could not be allocated)

void obj_ws_free ( OBJ_WS * ws )

Free the memory for OBJ_WS structure.

Parameters

[in] model Must point to a valid OBJ_WS structure

Returns

1 in case of succes
0 in case of failure (e.g. memory could not be freed)

void predict_ncl	(	const LEARN_NCL_MODEL *	model,
		const double *	BX,
		double *	Unp
	)

Prediction of nullspace components.

Parameters

[in]	model	Must be pointer to a valid LEARN_NCL_MODEL structure
[in]	BX	Higher dimensionality of the input variable, must point to an array of dim_b dim_n doubles*
[out]	Unp	Prediction of nullspace component, must point to an array of dim_u dum_n doubles*

Data Structures

Functions

Detailed Description

Function Documentation