CENFA: parScale – R documentation

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parScale

Efficient scaling of Raster* objects

Description

parScale expands the raster::scale function to allow for faster parallel processing, scaling each layer of x in parallel.

Usage

parScale(x, ...)

## S4 method for signature 'Raster'
parScale(
  x,
  center = TRUE,
  scale = TRUE,
  filename = "",
  progress = FALSE,
  parallel = FALSE,
  n = 1,
  cl = NULL,
  keep.open = FALSE,
  ...
)

Arguments

`x`	Raster* object
`...`	Additional arguments for `writeRaster`
`center`	logical or numeric. If `TRUE`, centering is done by subtracting the layer means (omitting NAs), and if `FALSE`, no centering is done. If `center` is a numeric vector with length equal to the `nlayers(x)`, then each layer of `x` has the corresponding value from center subtracted from it
`scale`	logical or numeric. If `TRUE`, scaling is done by dividing the (centered) layers of `x` by their standard deviations if center is `TRUE`, and the root mean square otherwise. If scale is `FALSE`, no scaling is done. If scale is a numeric vector with length equal to `nlayers(x)`, each layer of `x` is divided by the corresponding value. Scaling is done after centering
`filename`	character. Optional filename to save the Raster* output to file. If this is not provided, a temporary file will be created for large `x`
`progress`	logical. If `TRUE`, messages and progress bar will be printed
`parallel`	logical. If `TRUE` then multiple cores are utilized
`n`	numeric. Number of CPU cores to utilize for parallel processing
`cl`	optional cluster object
`keep.open`	logical. If `TRUE` and `parallel = TRUE`, the cluster object will not be closed after the function has finished

Value

Raster* object

Examples

ch.scale <- parScale(x = climdat.hist)

CENFA

Climate and Ecological Niche Factor Analysis

v1.1.0

GPL (>= 3)

Authors

D. Scott Rinnan

Initial release

2020-02-15