mincApplyRCPP: Perform Arbitrary calculations on a collection of mincVolumes

In Mouse-Imaging-Centre/RMINC: Statistical Tools for Medical Imaging NetCDF (MINC) Files

Perform Arbitrary calculations on a collection of mincVolumes

Description

An RCPP variant of mincApply, the primary advantage being that functions of an arbitrary number of arguments can be passed to mincApplyRCPP.

Usage

mincApplyRCPP(
  filenames,
  fun,
  ...,
  mask = NULL,
  maskval = NULL,
  filter_masked = FALSE,
  slab_sizes = c(1, 1, 1),
  return_indices = FALSE,
  collate = simplify2minc
)

Arguments

filenames	The name of the files to apply over
fun	the function to apply
...	additional parameters to fun
mask	a numeric mask vector
maskval	An integer specifying the value inside the mask where to apply the function. If left blank (the default) then anything above 0.5 will be considered inside the mask. This argument only works for mincApply, not pMincApply.
filter_masked	Whether or not to remove the masked values from the resultant object
slab_sizes	a three element numeric vector indicating the size in voxels of the hyperslab to read for each file. Useful for managing memory use - larger slabs are faster but require more memory. Sizes must be an even factor of their respective volume dimensions.
return_indices	Whether to return the voxel positions of the results generally for internal use only.
collate	A function to (potentially) collapse the result list examples include linkunlist and simplify2array, defaulting to simplify2minc which creates an object of type mincMultiDim, mincSingleDim, or mincList depending on the result structure. If you encounter memory issues, it could be due to minc file caching. Consider trying with the environment variable MINC_FILE_CACHE_MB set to a small value like 1.

Value

a list of results subject the the collate function

Mouse-Imaging-Centre/RMINC documentation built on Nov. 12, 2022, 1:50 p.m.