saveRDS and serialize for SpatVector and SpatRaster*

serialize and saveRDS for SpatVector, SpatRaster, SpatRasterDataset and SpatRasterCollection. Note that these objects will first be "packed" with wrap, and after unserialize/readRDS they need to be unpacked with rast or vect.

Extensive use of these functions is not recommended. Especially for SpatRaster it is generally much more efficient to use writeRaster and write, e.g., a GTiff file.

Usage

# S4 method for class 'SpatRaster'
saveRDS(object, file="", ascii = FALSE, version = NULL, compress=TRUE, refhook = NULL)

# S4 method for class 'SpatRasterDataset'
saveRDS(object, file="", ascii = FALSE, version = NULL, compress=TRUE, refhook = NULL)

# S4 method for class 'SpatRasterCollection'
saveRDS(object, file="", ascii = FALSE, version = NULL, compress=TRUE, refhook = NULL)

# S4 method for class 'SpatVector'
saveRDS(object, file="", ascii = FALSE, version = NULL, compress=TRUE, refhook = NULL)

# S4 method for class 'SpatRaster'
serialize(object, connection, ascii = FALSE, xdr = TRUE, version = NULL, refhook = NULL)

# S4 method for class 'SpatVector'
serialize(object, connection, ascii = FALSE, xdr = TRUE, version = NULL, refhook = NULL)

Arguments

object: SpatVector, SpatRaster, SpatRasterDataset or SpatRasterCollection
file: file name to save object to
connection: see serialize
ascii: see serialize or saveRDS
version: see serialize or saveRDS
compress: see serialize or saveRDS
refhook: see serialize or saveRDS
xdr: see serialize or saveRDS

Value

Packed* object

Examples

f <- system.file("ex/lux.shp", package="terra")
v <- vect(f)
p <- serialize(v, NULL)
head(p)
#> [1] 58 0a 00 00 00 03
x <- unserialize(p)
x
#>  class       : SpatVector 
#>  geometry    : polygons 
#>  dimensions  : 12, 6  (geometries, attributes)
#>  extent      : 5.74414, 6.528252, 49.44781, 50.18162  (xmin, xmax, ymin, ymax)
#>  coord. ref. : lon/lat WGS 84 (EPSG:4326) 
#>  names       :  ID_1   NAME_1  ID_2   NAME_2  AREA   POP
#>  type        : <num>    <chr> <num>    <chr> <num> <int>
#>  values      :     1 Diekirch     1 Clervaux   312 18081
#>                    1 Diekirch     2 Diekirch   218 32543
#>                    1 Diekirch     3  Redange   259 18664