Create a Memory-Mapped Neuroimaging Vector

Creates a BigNeuroVec object, which represents a large neuroimaging vector using memory-mapped file storage. This allows working with neuroimaging data that is too large to fit in memory.

Usage

BigNeuroVec(
  data,
  space,
  mask,
  label = "",
  type = c("double", "float", "integer"),
  backingfile = tempfile()
)

Arguments

data: The input data to be stored
space: A NeuroSpace object defining the spatial properties
mask: A logical mask indicating which voxels contain data
label: Optional character string label for the vector
type: Storage type, one of "double", "float", or "integer"
backingfile: Path to the file used for memory mapping (defaults to tempfile())

Value

A new BigNeuroVec object

Examples

if (FALSE) { # \dontrun{
# Load an example 4D brain image
example_file <- system.file("extdata", "global_mask_v4.nii", package = "neuroim2")
example_4d_image <- read_vec(example_file)

# Create a mask (e.g., selecting voxels with values > 0)
mask <- array(as.vector(example_4d_image[,,,1]) > 0,
             dim = dim(example_4d_image)[1:3])

if(requireNamespace("bigstatsr", quietly = TRUE)) {
  # Create a BigNeuroVec with memory mapping
  big_vec <- BigNeuroVec(data = example_4d_image@.Data,
                         space = space(example_4d_image),
                         mask = mask,
                         label = "Example BigNeuroVec")
  print(big_vec)
}
} # }