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Batch Reduce Multiple Volumes by an Atlas

Source: R/batch_reduce.R
batch_reduce.Rd

Applies reduce_atlas to multiple input volumes (or file paths) and combines the results into a single tibble with a subject column identifying each input.

Usage

batch_reduce(
  inputs,
  atlas,
  stat_func = mean,
  ...,
  format = "long",
  parallel = FALSE,
  .progress = TRUE
)

Arguments

inputs

A named list of inputs. Each element can be:

  • A NeuroVol (3D) or NeuroVec (4D) object

  • A character string file path (read via neuroim2::read_vol)

If unnamed, subjects are auto-named "sub_001", "sub_002", etc.

atlas

An atlas object.

stat_func

Function to apply within each ROI (default: mean).

...

Additional arguments passed to reduce_atlas.

format

Character, output format passed to reduce_atlas. Default "long".

parallel

Logical. If TRUE, uses future.apply::future_lapply() for parallel processing. Requires the future.apply package.

.progress

Logical. If TRUE (default), displays a cli progress bar.

Value

A tibble with a subject column prepended to the reduce_atlas output for each input.

See also

reduce_atlas for single-volume extraction

Examples

if (FALSE) { # \dontrun{
# With NeuroVol objects
vols <- list(sub01 = vol1, sub02 = vol2, sub03 = vol3)
results <- batch_reduce(vols, atlas, mean)

# With file paths
files <- list(sub01 = "path/to/sub01.nii.gz",
              sub02 = "path/to/sub02.nii.gz")
results <- batch_reduce(files, atlas, mean, parallel = TRUE)
} # }