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Split a prediction dataset in an SSN object

Source: R/ssn_split_predpts.R
ssn_split_predpts.Rd

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.

Usage

ssn_split_predpts(
  ssn,
  predpts,
  size_predpts,
  by,
  subset,
  id_predpts,
  keep = TRUE,
  drop_levels = FALSE,
  overwrite = FALSE
)

Arguments

ssn

An SSN object.

predpts

A character string representing the name of the prediction dataset

size_predpts

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

by

character string representing the column name of type factor, integer, character or logical that the split will be based on

subset

logical expression indicating which elements or rows to keep; missing values are taken as FALSE

id_predpts

character string representing the new prediction dataset name. This value is only specified when the subset method is used

keep

logical value indicating whether the original prediction dataset should be retained in the SSN object. Default is TRUE

drop_levels

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

overwrite

logical indicating whether the new prediction dataset shapefile should be deleted in the .ssn directory if it already exists. Default = FALSE

Value

returns the SSN specified in ssn, with one or more new prediction sets. Shapefiles of the new prediction sets are written to the .ssn directory designated in ssn$path.

Details

Three methods have been provided to split prediction sets: size_predpts, by, and subset. The size_predpts method is used to split the existing prediction set into multiple equally-sized prediction sets. 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. The subset method is used to create one new prediction set based on a logical expression.

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.

Examples

## Import SSN object
copy_lsn_to_temp() ## Only needed for this example
ssn <- ssn_import(paste0(tempdir(), "/MiddleFork04.ssn"),
  predpts = c("pred1km.shp", "Knapp", "CapeHorn"),
  overwrite = TRUE
)

## Split predictions into size_predpts 200
ssn1 <- ssn_split_predpts(ssn, "CapeHorn",
  size_predpts = 200,
  keep = FALSE, overwrite = TRUE
)
names(ssn1$preds)
#> [1] "pred1km"    "Knapp"      "CapeHorn-1" "CapeHorn-2" "CapeHorn-3"
#> [6] "CapeHorn-4"
nrow(ssn1$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"           "Knapp"             "CapeHorn"         
#> [4] "pred1km-net.fac-1" "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"  "Knapp"    "CapeHorn" "RATIO_05"