rmap_prepare
updates a 'raw' unprepared project to a ready to use project.
rmap_prepare
creates the project's canvas and assign each range to its corresponding canvas cells by
performing a spatial intersection between the ranges and the canvas. The canvas is a regular grid
of squares or hexagons.
rmap_prepare(con, grid_type, cellsize, chunksize, ...) # S4 method for rmapConnection,character,numeric,missing rmap_prepare(con, grid_type, cellsize, chunksize, ...) # S4 method for rmapConnection,character,numeric,numeric rmap_prepare(con, grid_type = "hex", cellsize, chunksize = 1/10, ...)
con | a |
---|---|
grid_type | character "hex" (default) or "square", see |
cellsize | target cellsize, see |
chunksize | parallel processing chunk size expressed as proportion from the range size. Default to 1/10. |
... | further arguments passed to |
TRUE when the table is written to the project file, FALSE otherwise.
Because rmap_prepare
can be potentially time consuming it can be run in parallel using the
support provided by the future
package.
future
allows parallel processing on a variety of systems including high performance computing environments.
For details see future::plan()
.
Additionally, you can keep track of of the computations using progressr::handlers()
.
Birch, C. P., Oom, S. P., & Beecham, J. A. (2007). Rectangular and hexagonal grids used for observation, experiment and simulation in ecology. Ecological modelling, 206(3-4), 347-359.
# IN-MEMORY PROJECT require(rangeMapper) wrens = read_wrens() con = rmap_connect() rmap_add_ranges(con, wrens, 'sci_name') rmap_prepare(con, 'hex', cellsize=500)#>#>#>#>#>#>#>dbDisconnect(con) # \dontrun{ # PROJECT PREPARED IN PARALLEL require(future) require(progressr) plan(multisession, workers = 2) handlers(global = TRUE) Path = tempfile() con = rmap_connect(Path) rmap_add_ranges(con, wrens, 'sci_name') rmap_prepare(con, 'hex', cellsize=200, chunksize = 0.1)#>#>#>#>#>#>#>