SSN2 (version 0.2.1)

ssn_import_predpts: Import prediction points into an SSN, ssn_lm, or ssn_glm object

Description

A shapefile of prediction points found in the .ssn directory are imported into an existing object of class SSN, ssn_lm, or ssn_glm.

Usage

ssn_import_predpts(x, predpts)

Value

an object of class SSN, ssn_lm, or ssn_glm which contains the new prediction dataset.

Arguments

x

An object of classSSN, ssn_lm, or ssn_glm.

predpts

Name of the prediction point dataset to import in character format. See details.

Details

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.

Examples

## 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)

## 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)