Set global package options to change the default behavior of gdalcubes. These include how many parallel processes are used to process data cubes, how created netCDF files are compressed, and whether or not debug messages should be printed.
gdalcubes_options(
...,
parallel,
ncdf_compression_level,
debug,
cache,
ncdf_write_bounds,
use_overview_images,
show_progress,
default_chunksize,
streaming_dir,
log_file,
threads
)not used
number of parallel workers used to process data cubes or TRUE to use the number of available cores automatically
integer; compression level for created netCDF files, 0=no compression, 1=fast compression, 9=small compression
logical; print debug messages
logical; TRUE if temporary data cubes should be cached to support fast reprocessing of the same cubes
logical; write dimension bounds as additional variables in netCDF files
logical; if FALSE, all images are read on original resolution and existing overviews will be ignored
logical; if TRUE, a progress bar will be shown for actual computations
length-three vector with chunk size in t, y, x directions or a function taking a data cube size and returning a suggested chunk size
directory where temporary binary files for process streaming will be written to
character, if empty string or NULL, diagnostic messages will be printed to the console, otherwise to the provided file
number of threads used to process data cubes (deprecated)
Data cubes can be processed in parallel where the number of chunks in a cube is distributed among parallel worker processes. The actual number of used workers can be lower if a data cube as less chunks. If parallel is TRUE, the number of available cores is used. Setting parallel = FALSE can be used to disable parallel processing. Notice that since version 0.6.0, separate processes are being used instead of parallel threads to avoid possible R session crashes due to some multithreading issues.
Caching has no effect on disk or memory consumption,
it simply tries to reuse existing temporary files where possible.
For example, changing only parameters to plot will void
reprocessing the same data cube if cache is TRUE.
The streaming directory can be used to control the performance of user-defined functions, if disk IO is a bottleneck. Ideally, this can be set to a directory on a shared memory device.
Passing no arguments will return the current options as a list.
gdalcubes_options(parallel=4) # set the number
gdalcubes_options() # print current options
gdalcubes_options(parallel=FALSE) # reset
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