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Create Data Chunks for Processing

Source: R/all_generic.R
data_chunks.Rd

Generic function to create data chunks for parallel processing from various fMRI dataset types. Supports different chunking strategies.

Usage

data_chunks(x, nchunks = 1, runwise = FALSE, ...)

Arguments

x

An fMRI dataset object

nchunks

Number of chunks to create (default: 1)

runwise

If TRUE, create run-wise chunks (default: FALSE)

...

Additional arguments passed to methods

Value

A chunk iterator object that yields data chunks when iterated

Details

Large fMRI datasets can be processed more efficiently by dividing them into chunks. This function creates an iterator that yields data chunks for parallel or sequential processing. Two chunking strategies are supported:

  • Equal-sized chunks: Divides voxels into approximately equal groups

  • Run-wise chunks: Each chunk contains all voxels from one or more complete runs

See also

iter for iteration concepts

Examples

# \donttest{
# Create a dataset
mat <- matrix(rnorm(100 * 1000), nrow = 100, ncol = 1000)
ds <- matrix_dataset(mat, TR = 2, run_length = 100)

# Create 4 chunks for parallel processing
chunks <- data_chunks(ds, nchunks = 4)

# Process chunks (example)
# results <- foreach(chunk = chunks) %dopar% {
#   process_chunk(chunk)
# }
# }