BatchPreprocessingPipeline

Batch preprocessing pipeline for processing multiple files in parallel.

class meeg_utils.preprocessing.BatchPreprocessingPipeline(input_paths, output_dir=None, n_jobs=1, use_cuda=False, random_state=42)

Bases: object

Batch preprocessing pipeline for multiple MEG/EEG datasets.

Parameters:

• input_paths (list[str | Path | BIDSPath]) – List of input paths to process.

• output_dir (str | Path | None, optional) – Output directory for all datasets. If None, uses BIDS derivatives.

• n_jobs (int, optional) – Number of parallel jobs. Default is 1.

• use_cuda (bool, optional) – Whether to use CUDA. Default is False.

• random_state (int, optional) – Random seed. Default is 42.

input_paths

Parsed input paths.

Type:

list[Path | BIDSPath]

output_dir

Output directory.

Type:

Path | None

n_jobs

Number of parallel jobs.

Type:

int

use_cuda

CUDA flag.

Type:

bool

random_state

Random seed.

Type:

int

__init__(input_paths, output_dir=None, n_jobs=1, use_cuda=False, random_state=42)

Initialize batch preprocessing pipeline.

__init__(input_paths, output_dir=None, n_jobs=1, use_cuda=False, random_state=42)

Initialize batch preprocessing pipeline.

run(filter_params=None, detect_bad_channels=True, remove_line_noise=True, apply_ica=True, ica_params=None, save_intermediate=False, skip_existing=False, save_logs=True, logging_level='INFO')

Run batch preprocessing on all datasets.

Parameters:

• filter_params (dict | None, optional) – Filtering parameters.

• detect_bad_channels (bool, optional) – Whether to detect bad channels. Default is True.

• remove_line_noise (bool, optional) – Whether to remove line noise. Default is True.

• apply_ica (bool, optional) – Whether to apply ICA. Default is True.

• ica_params (dict | None, optional) – ICA parameters.

• save_intermediate (bool, optional) – Whether to save intermediate files. Default is False.

• skip_existing (bool, optional) – Whether to skip datasets with existing output. Default is False.

• save_logs (bool, optional) – Whether to save log files. Default is True.

• logging_level (str, optional) – Logging level for the batch process. Default is “INFO”.

Example Usage

from meeg_utils.preprocessing import BatchPreprocessingPipeline
from mne_bids import BIDSPath

# Define inputs
bids_paths = [
    BIDSPath(subject=f"{i:02d}", session="01", task="rest",
             datatype="eeg", root="/data/bids")
    for i in range(1, 11)
]

# Create batch pipeline
batch = BatchPreprocessingPipeline(
    input_paths=bids_paths,
    output_dir="/data/output",
    n_jobs=4,
    random_state=42
)

# Run batch processing
batch.run(
    filter_params={"highpass": 0.1, "lowpass": 100.0},
    detect_bad_channels=True,
    remove_line_noise=True,
    apply_ica=True,
    save_logs=True
)