sgradclc.cpp File Reference

(* $Id$)

Functions to compute gradient from the global gradient_structure. More...

#include "fvar.hpp"
#include <sys/stat.h>
#include <fcntl.h>
#include <string.h>
#include <stdio.h>
#include <stdlib.h>
#include <iostream>
#include <sys/types.h>
#include <unistd.h>
#include <math.h>

Go to the source code of this file.

Defines
#define	__USE_IOSTREAM__
Functions
void	gradcalc (int nvar, const dvector &_g)
	Compute the gradient from the data stored in the global gradient_structure.
double	gradcalc (int nvar, const dvector &_g, dvariable &f)
	Compute the gradient from the data stored in the global gradient_structure.
void	reset_gradient_stack (void)
	Rewind buffer.
void	test_the_pointer (void)

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Detailed Description

Functions to compute gradient from the global gradient_structure.

Definition in file sgradclc.cpp.

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Define Documentation

#define __USE_IOSTREAM__

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Function Documentation

void gradcalc	(	int	nvar,
		const dvector &	_g
	)

Compute the gradient from the data stored in the global gradient_structure.

Parameters:

nvar	Number of variables in the gradient.
_g	Vector from 1 to nvar. On return contains the gradient.

Definition at line 86 of file sgradclc.cpp.

Referenced by laplace_approximation_calculator::banded_calculations_lme(), calculate_importance_sample(), calculate_importance_sample_block_diagonal(), calculate_importance_sample_block_diagonal_funnel(), calculate_importance_sample_block_diagonal_option2(), calculate_importance_sample_block_diagonal_option_antithetical(), calculate_importance_sample_funnel(), calculate_importance_sample_shess(), calculate_laplace_approximation(), function_minimizer::dep_hess_routine(), function_minimizer::depvars_routine(), do_evaluation(), do_gauss_hermite_block_diagonal(), do_gauss_hermite_block_diagonal_multi(), evaluate_function(), evaluate_function_gradient(), evaluate_function_quiet(), evaluate_function_with_quadprior(), laplace_approximation_calculator::get_fx_fu(), laplace_approximation_calculator::get_gradient_for_hessian_calcs(), laplace_approximation_calculator::get_gradient_lme(), laplace_approximation_calculator::get_gradient_lme_hp(), function_minimizer::get_hybrid_monte_carlo_value(), function_minimizer::get_monte_carlo_value(), function_minimizer::get_particular_grad(), laplace_approximation_calculator::get_uhat_lm_newton2(), laplace_approximation_calculator::get_uhat_quasi_newton(), laplace_approximation_calculator::get_uhat_quasi_newton_block_diagonal(), gradcalc(), function_minimizer::hess_routine_and_constraint(), function_minimizer::hess_routine_noparallel(), function_minimizer::hess_routine_noparallel_random_effects(), function_minimizer::hess_routine_slave_random_effects(), function_minimizer::limited_memory_quasi_newton(), function_minimizer::limited_memory_quasi_newton_block(), fmm::minimize(), function_minimizer::prof_minimize(), function_minimizer::prof_minimize_re(), and function_minimizer::quasi_newton_block().

double gradcalc	(	int	nvar,
		const dvector &	_g,
		dvariable &	f
	)

Compute the gradient from the data stored in the global gradient_structure.

Parameters:

nvar	Number of variables in the gradient.
_g	Vector from 1 to nvar. On return contains the gradient.
f	objective function

Returns:

likelihood value

Definition at line 231 of file sgradclc.cpp.

void reset_gradient_stack

(

void

)

Rewind buffer.

Definition at line 392 of file sgradclc.cpp.

Referenced by laplace_approximation_calculator::banded_calculations_lme(), function_minimizer::depvars_routine(), function_minimizer::limited_memory_quasi_newton_block(), and function_minimizer::quasi_newton_block().

void test_the_pointer

(

void

)

Definition at line 432 of file sgradclc.cpp.

Referenced by grad_stack::grad_stack().