prog_breaks: Generate breakpoints and other values for printing progress

In adaptr: Adaptive Trial Simulator

Generate breakpoints and other values for printing progress

Description

Used internally. Generates breakpoints, messages, and 'batches' of trial numbers to simulate when using run_trials() with the progress argument in use. Breaks will be multiples of the number of cores, and repeated use of the same values for breaks is avoided (if, e.g., the number of breaks times the number of cores is not possible if few new trials are to be run). Inputs are validated by run_trials().

Usage

prog_breaks(progress, prev_n_rep, n_rep_new, cores)

Arguments

progress	single numeric ⁠> 0⁠ and ⁠<= 1⁠ or NULL. If NULL (default), no progress is printed to the console. Otherwise, progress messages are printed to the control at intervals proportional to the value specified by progress. Note: as printing is not possible from within clusters on multiple cores, the function conducts batches of simulations on multiple cores (if specified), with intermittent printing of statuses. Thus, all cores have to finish running their current assigned batches before the other cores may proceed with the next batch. If there are substantial differences in the simulation speeds across cores, using progress may thus increase total run time (especially with small values).
prev_n_rep	single integer, the previous number of simulations run (to add to the indices generated and used).
n_rep_new	single integers, number of new simulations to run (i.e., n_rep as supplied to run_trials() minus the number of previously run simulations if grow is used in run_trials()).
cores	NULL or single integer. If NULL, a default value/cluster set by setup_cluster() will be used to control whether simulations are run in parallel on a default cluster or sequentially in the main process; if a cluster/value has not been specified by setup_cluster(), cores will then be set to the value stored in the global "mc.cores" option (if previously set by ⁠options(mc.cores = <number of cores>⁠), and 1 if that option has not been specified. If the resulting number of cores = 1, computations will be run sequentially in the primary process, and if cores > 1, a new parallel cluster will be setup using the parallel library and removed once the function completes. See setup_cluster() for details.

Value

List containing breaks (the number of patients at each break), start_mess and prog_mess (the basis of the first and subsequent progress messages), and batches (a list with each entry corresponding to the simulation numbers in each batch).

adaptr documentation built on May 29, 2024, 7:48 a.m.