The splitPrediction function is used to
split prediction sets in an SSN object into smaller
prediction sets. It returns a SSN object with additional
prediction sets based on equal interval splits, a factor,
integer, character or logical column stored within the prediction
set, or a logical expression.
ssn_split_predpts(
ssn,
predpts,
size_predpts,
by,
subset,
id_predpts,
keep = TRUE,
drop_levels = FALSE,
overwrite = FALSE
)An SSN object.
A character string representing the name of the prediction dataset.
numeric value representing the size of the new prediction sets. The existing prediction set is split equally to produce multiple prediction sets of this size
character string representing the column name of type factor, integer, character or logical that the split will be based on
logical expression indicating which elements or rows
to keep; missing values are taken as FALSE
character string representing the new prediction dataset name. This value is only specified when the subset method is used
logical value indicating whether the original
prediction dataset should be retained in the SSN
object. Default is TRUE
logical value indicating whether empty factor
levels should be dropped in the by column when the new
prediction dataset(s) are created. Default is FALSE
logical indicating whether the new prediction
dataset geopackage should be deleted in the .ssn directory if it
already exists. Default = FALSE
returns the SSN specified in ssn, with one or more new prediction
sets. Geopackages of the new prediction sets are written to the
.ssn directory designated in ssn$path.
Three methods have been provided to split prediction sets:
size, by, and subset. The
size method is used to split the existing prediction
set into multiple equally-sized prediction sets using the size_predpts argument. Note that the
final prediction set may be smaller in size than the others if
the total number of predictions is not evenly divisible by
size_predpts. The by method is used if the prediction
set is to be split into multiple new prediction sets based on an
existing column of type factor, integer, character, or
logical specified using the argument by. The subset method is used to create one new
prediction set based on a logical expression defined in subset.
When more than one prediction dataset is created the prediction
dataset names will be appended with a hyphen and prediction
dataset number if more than one prediction dataset is
created. For example, when "preds" is split using
size_predpts, the new names will be "preds-1", "preds-2", and
so forth.
When keep=FALSE, the prediction dataset is removed from
the SSN object stored in memory, but is not deleted from
the .ssn directory specified in ssn$path.
Note that, only one
method may be specified when the ssn_split_predpts
function is called. The distance matrices for the new prediction
datasets must be created using the ssn_create_distmat before
predictions can be made.
## Import SSN object
copy_lsn_to_temp() ## Only needed for this example
ssn <- ssn_import(paste0(tempdir(), "/MiddleFork04.ssn"),
predpts = c("pred1km", "CapeHorn"),
overwrite = TRUE
)
## Split predictions based on 'size' method
ssn1 <- ssn_split_predpts(ssn, "CapeHorn",
size_predpts = 200,
keep = FALSE, overwrite = TRUE
)
names(ssn1$preds)
#> [1] "pred1km" "CapeHorn-1" "CapeHorn-2" "CapeHorn-3" "CapeHorn-4"
nrow(ssn1$preds[["CapeHorn-1"]])
#> [1] 200
## Split predictions using 'by' method
ssn$preds$pred1km$net.fac <- as.factor(ssn$preds$pred1km$netID)
ssn2 <- ssn_split_predpts(ssn, "pred1km",
by = "net.fac",
overwrite = TRUE
)
names(ssn2$preds)
#> [1] "pred1km" "CapeHorn" "pred1km-net.fac-1"
#> [4] "pred1km-net.fac-2"
## Split predictions using 'subset' method
ssn3 <- ssn_split_predpts(ssn, "pred1km",
subset = ratio > 0.5,
id_predpts = "RATIO_05", overwrite = TRUE
)
names(ssn3$preds)
#> [1] "pred1km" "CapeHorn" "RATIO_05"