info for the optimizer (see the description of this module) More...

Collaboration diagram for cp_lbfgs_optimizer_gopt::cp_lbfgs_opt_gopt_type:

Private Attributes
CHARACTER(len=60)	task
CHARACTER(len=60)	csave
LOGICAL, dimension(4)	lsave
INTEGER	m
INTEGER	print_every
INTEGER	master
INTEGER	max_f_per_iter
INTEGER	status
INTEGER	n_iter
INTEGER	ref_count
INTEGER	id_nr
INTEGER, dimension(:), pointer	kind_of_bound
INTEGER, dimension(:), pointer	i_work_array
INTEGER, dimension(:), pointer	isave
REAL(kind=dp)	f
REAL(kind=dp)	wanted_relative_f_delta
REAL(kind=dp)	wanted_projected_gradient
REAL(kind=dp)	last_f
REAL(kind=dp)	projected_gradient
REAL(kind=dp)	eold
REAL(kind=dp)	emin
REAL(kind=dp), dimension(:), pointer	x
REAL(kind=dp), dimension(:), pointer	lower_bound
REAL(kind=dp), dimension(:), pointer	upper_bound
REAL(kind=dp), dimension(:), pointer	gradient
REAL(kind=dp), dimension(:), pointer	dsave
REAL(kind=dp), dimension(:), pointer	work_array
TYPE(cp_para_env_type), pointer	para_env
TYPE(gopt_f_type), pointer	obj_funct

Detailed Description

info for the optimizer (see the description of this module)

Parameters:

task	the actual task of the optimizer (in the master it is up to date, in case of error also the slaves one get updated.
csave	internal character string used by the lbfgs optimizer, meaningful only in the master
lsave	logical array used by the lbfgs optimizer, updated only in the master On exit with task = 'NEW_X', the following information is available: lsave(1) = .true. the initial x did not satisfy the bounds; lsave(2) = .true. the problem contains bounds; lsave(3) = .true. each variable has upper and lower bounds.
ref_count	reference count (see doc/ReferenceCounting.html)
id_nr	identification number (unique)
m	the dimension of the subspace used to approximate the second derivative
print_every	every how many iterations output should be written. if 0 only at end, if print_every<0 never
master	the pid of the master processor
max_f_per_iter	the maximum number of function evaluations per iteration
status	0: just initialized, 1: f g calculation, 2: begin new iteration, 3: ended iteration, 4: normal (converged) exit, 5: abnormal (error) exit, 6: daellocated
n_iter	the actual iteration number
kind_of_bound	an array with 0 (no bound), 1 (lower bound), 2 (both bounds), 3 (upper bound), to describe the bounds of every variable
i_work_array	an integer workarray of dimension 3*n, present only in the master
isave	is an INTEGER working array of dimension 44. On exit with task = 'NEW_X', it contains information that the user may want to access:
isave	(30) = the current iteration number;
isave	(34) = the total number of function and gradient evaluations;
isave	(36) = the number of function value or gradient evaluations in the current iteration;
isave	(38) = the number of free variables in the current iteration;
isave	(39) = the number of active constraints at the current iteration;
f	the actual best value of the object function
wanted_relative_f_delta	the wanted relative error on f (to be multiplied by epsilon), 0.0 -> no check
wanted_projected_gradient	the wanted error on the projected gradient (hessian times the gradient), 0.0 -> no check
last_f	the value of f in the last iteration
projected_gradient	the value of the sup norm of the projected gradient
x	the actual evaluation point (best one if converged or stopped)
lower_bound	the lower bounds
upper_bound	the upper bounds
gradient	the actual gradient
dsave	info date for lbfgs (master only)
work_array	a work array for lbfgs (master only)
para_env	the parallel environment for this optimizer
obj_funct	the objective function to be optimized