R/ssn_import_predpts.R
ssn_import_predpts.Rd
A shapefile of prediction points found in the .ssn
directory are imported into an existing object of class
SSN
, ssn_lm
, or ssn_glm
.
ssn_import_predpts(x, predpts)
An object of classSSN
, ssn_lm
, or
ssn_glm
.
Name of the prediction point dataset to import in character format. See details.
an object of class SSN
, ssn_lm
, or
ssn_glm
which contains the new prediction dataset.
ssn_import_predpts
imports one set of prediction
points residing in the .ssn directory into an existing
SSN
, ssn_lm
, or ssn_glm
object. The
prediction dataset must be in shapefile or geopackage format
(.shp or .gpkg, respectively) and reside in the ssn.object$path
directory. The path for an SSN
object can be updated using
ssn_update_path()
prior to importing prediction
datasets. The argument predpts
accepts the name of the
prediction point dataset, with or without the file extension. If
it is passed as a named vector (of length 1), then the name
provided is used as the prediction dataset name in the SSN
object prediction sites list
(e.g. names(ssn.obj$preds)
). Otherwise, the file basename
is used in the names attribute. See
ssn_import
for a detailed description of the
prediction dataset format within the SSN
class object.
When the prediction dataset is imported, a new column named
netgeom
is created. If this column already exists it is
overwritten. Please see create_netgeom
for a
detailed description of the netgeom
column and the
information it contains.
The prediction dataset specified in predpts
must contain the
spatial, topological and attribute information needed to make
predictions using an ssn_lm or ssn_glm object. This information
is generated using the SSNbler
package, which makes use of
the functionality found in the sf
and igraph
packages to process streams data in vector format.
## Create local temporary copy of MiddleFork04.ssn found in
# SSN2/lsndata folder. Only necessary for this example.
copy_lsn_to_temp()
## Import SSN object with no prediction sites
mf04p <- ssn_import(paste0(tempdir(), "/MiddleFork04.ssn"),
overwrite = TRUE
)
## Import pred1km prediction dataset into SSN object and assign the
## name preds1
mf04p <- ssn_import(paste0(tempdir(), "/MiddleFork04.ssn"),
overwrite = TRUE)
mf04p <- ssn_import_predpts(mf04p, predpts = c(preds1 = "pred1km"))
names(mf04p$preds)
#> [1] "preds1"
## Import CapeHorn prediction dataset into a ssn_glm object, using
## the default file basename as the name
ssn_gmod <- ssn_glm(Summer_mn ~ netID, mf04p,
family = "Gamma",
tailup_type = "exponential", additive = "afvArea"
)
ssn_gmod <- ssn_import_predpts(ssn_gmod, predpts = "CapeHorn")
names(ssn_gmod$ssn.object$preds)
#> [1] "preds1" "CapeHorn"