arc_control_type structure#
struct arc_control_type{T} f_indexing::Bool error::Int32 out::Int32 print_level::Int32 start_print::Int32 stop_print::Int32 print_gap::Int32 maxit::Int32 alive_unit::Int32 alive_file::NTuple{31,Cchar} non_monotone::Int32 model::Int32 norm::Int32 semi_bandwidth::Int32 lbfgs_vectors::Int32 max_dxg::Int32 icfs_vectors::Int32 mi28_lsize::Int32 mi28_rsize::Int32 advanced_start::Int32 stop_g_absolute::T stop_g_relative::T stop_s::T initial_weight::T minimum_weight::T reduce_gap::T tiny_gap::T large_root::T eta_successful::T eta_very_successful::T eta_too_successful::T weight_decrease_min::T weight_decrease::T weight_increase::T weight_increase_max::T obj_unbounded::T cpu_time_limit::T clock_time_limit::T hessian_available::Bool subproblem_direct::Bool renormalize_weight::Bool quadratic_ratio_test::Bool space_critical::Bool deallocate_error_fatal::Bool prefix::NTuple{31,Cchar} rqs_control::rqs_control_type{T} glrt_control::glrt_control_type{T} dps_control::dps_control_type{T} psls_control::psls_control_type{T} lms_control::lms_control_type{T} lms_control_prec::lms_control_type{T} sha_control::sha_control_type
detailed documentation#
control derived type as a Julia structure
components#
Bool f_indexing
use C or Fortran sparse matrix indexing
Int32 error
error and warning diagnostics occur on stream error
Int32 out
general output occurs on stream out
Int32 print_level
the level of output required.
\(\leq\) 0 gives no output,
= 1 gives a one-line summary for every iteration,
= 2 gives a summary of the inner iteration for each iteration,
\(\geq\) 3 gives increasingly verbose (debugging) output
Int32 start_print
any printing will start on this iteration
Int32 stop_print
any printing will stop on this iteration
Int32 print_gap
the number of iterations between printing
Int32 maxit
the maximum number of iterations performed
Int32 alive_unit
removal of the file alive_file from unit alive_unit terminates execution
char alive_file[31]
see alive_unit
Int32 non_monotone
the descent strategy used.
Possible values are
<= 0 a monotone strategy is used.
anything else, a non-monotone strategy with history length .non_monotine is used.
Int32 model
the model used.
Possible values are
0 dynamic (not yet implemented)
1 first-order (no Hessian)
2 second-order (exact Hessian)
3 barely second-order (identity Hessian)
4 secant second-order (limited-memory BFGS, with .lbfgs_vectors history) (not yet implemented)
5 secant second-order (limited-memory SR1, with .lbfgs_vectors history) (not yet implemented)
Int32 norm
the regularization norm used.
The norm is defined via \(\|v\|^2 = v^T P v\), and will define the preconditioner used for iterative methods. Possible values for \(P\) are
-3 users own preconditioner
-2 \(P =\) limited-memory BFGS matrix (with .lbfgs_vectors history)
-1 identity (= Euclidan two-norm)
0 automatic (not yet implemented)
1 diagonal, \(P =\) diag( max( Hessian, .min_diagonal ) )
2 banded, \(P =\) band( Hessian ) with semi-bandwidth .semi_bandwidth
3 re-ordered band, P=band(order(A)) with semi-bandwidth .semi_bandwidth
4 full factorization, \(P =\) Hessian, Schnabel-Eskow modification
5 full factorization, \(P =\) Hessian, GMPS modification (not yet implemented)
6 incomplete factorization of Hessian, Lin-More’
7 incomplete factorization of Hessian, HSL_MI28
8 incomplete factorization of Hessian, Munskgaard (not yet implemented)
9 expanding band of Hessian (not yet implemented)
10 diagonalizing norm from GALAHAD_DPS (subproblem_direct only)
Int32 semi_bandwidth
specify the semi-bandwidth of the band matrix P if required
Int32 lbfgs_vectors
number of vectors used by the L-BFGS matrix P if required
Int32 max_dxg
number of vectors used by the sparsity-based secant Hessian if required
Int32 icfs_vectors
number of vectors used by the Lin-More’ incomplete factorization matrix P if required
Int32 mi28_lsize
the maximum number of fill entries within each column of the incomplete factor L computed by HSL_MI28. In general, increasing .mi28_lsize improve the quality of the preconditioner but increases the time to compute and then apply the preconditioner. Values less than 0 are treated as 0
Int32 mi28_rsize
the maximum number of entries within each column of the strictly lower triangular matrix \(R\) used in the computation of the preconditioner by HSL_MI28. Rank-1 arrays of size .mi28_rsize \* n are allocated internally to hold \(R\). Thus the amount of memory used, as well as the amount of work involved in computing the preconditioner, depends on .mi28_rsize. Setting .mi28_rsize > 0 generally leads to a higher quality preconditioner than using .mi28_rsize = 0, and choosing .mi28_rsize >= .mi28_lsize is generally recommended
Int32 advanced_start
try to pick a good initial regularization weight using .advanced_start iterates of a variant on the strategy of Sartenaer SISC 18(6) 1990:1788-1803
T stop_g_absolute
overall convergence tolerances. The iteration will terminate when the norm of the gradient of the objective function is smaller than MAX( .stop_g_absolute, .stop_g_relative * norm of the initial gradient ) or if the step is less than .stop_s
T stop_g_relative
see stop_g_absolute
T stop_s
see stop_g_absolute
T initial_weight
Initial value for the regularisation weight (-ve => 1/||g_0||)
T minimum_weight
minimum permitted regularisation weight
T reduce_gap
expert parameters as suggested in Gould, Porcelli & Toint, “Updating the regularization parameter in the adaptive cubic regularization algorithm” RAL-TR-2011-007, Rutherford Appleton Laboratory, England (2011), http://epubs.stfc.ac.uk/bitstream/6181/RAL-TR-2011-007.pdf (these are denoted beta, epsilon_chi and alpha_max in the paper)
T tiny_gap
see reduce_gap
T large_root
see reduce_gap
T eta_successful
a potential iterate will only be accepted if the actual decrease f - f(x_new) is larger than .eta_successful times that predicted by a quadratic model of the decrease. The regularization weight will be decreased if this relative decrease is greater than .eta_very_successful but smaller than .eta_too_successful (the first is eta in Gould, Porcell and Toint, 2011)
T eta_very_successful
see eta_successful
T eta_too_successful
see eta_successful
T weight_decrease_min
on very successful iterations, the regularization weight will be reduced by the factor .weight_decrease but no more than .weight_decrease_min while if the iteration is unsuccessful, the weight will be increased by a factor .weight_increase but no more than .weight_increase_max (these are delta_1, delta_2, delta3 and delta_max in Gould, Porcelli and Toint, 2011)
T weight_decrease
see weight_decrease_min
T weight_increase
see weight_decrease_min
T weight_increase_max
see weight_decrease_min
T obj_unbounded
the smallest value the onjective function may take before the problem is marked as unbounded
T cpu_time_limit
the maximum CPU time allowed (-ve means infinite)
T clock_time_limit
the maximum elapsed clock time allowed (-ve means infinite)
Bool hessian_available
is the Hessian matrix of second derivatives available or is access only via matrix-vector products?
Bool subproblem_direct
use a direct (factorization) or (preconditioned) iterative method to find the search direction
Bool renormalize_weight
should the weight be renormalized to account for a change in preconditioner?
Bool quadratic_ratio_test
should the test for acceptance involve the quadratic model or the cubic?
Bool space_critical
if .space_critical true, every effort will be made to use as little space as possible. This may result in longer computation time
Bool deallocate_error_fatal
if .deallocate_error_fatal is true, any array/pointer deallocation error will terminate execution. Otherwise, computation will continue
NTuple{31,Cchar} prefix
all output lines will be prefixed by .prefix(2:LEN(TRIM(.prefix))-1) where .prefix contains the required string enclosed in quotes, e.g. “string” or ‘string’
struct rqs_control_type rqs_control
control parameters for RQS
struct glrt_control_type glrt_control
control parameters for GLRT
struct dps_control_type dps_control
control parameters for DPS
struct psls_control_type psls_control
control parameters for PSLS
struct lms_control_type lms_control
control parameters for LMS
struct lms_control_type lms_control_prec
control parameters for LMS used for preconditioning
struct sha_control_type sha_control
control parameters for SHA