mne_bids.anonymize_dataset

mne_bids.anonymize_dataset(bids_root_in, bids_root_out, daysback='auto', subject_mapping='auto', datatypes=None, random_state=None, verbose=None)

Anonymize a BIDS dataset.

This function creates a copy of a BIDS dataset, and tries to remove all personally identifiable information from the copy.

Parameters:

bids_root_inpath-like

The root directory of the input BIDS dataset.

bids_root_outpath-like

The directory to place the anonymized dataset into.

daysbackint | ‘auto’

Number of days by which to move back the recording date in time. If 'auto', tries to randomly pick a suitable number.

subject_mappingdict | callable() | ‘auto’ | None

How to anonymize subject IDs. If a dictionary, maps the original IDs (keys) to the anonymized IDs (values). If a function, must be one that accepts the original IDs as a list of strings and returns a dictionary with original IDs as keys and anonymized IDs as values. If 'auto', automatically produces a mapping (zero-padded numerical IDs) and prints it on the screen. If None, subject IDs are not changed.

datatypeslist of str | str | None

Which data type to anonymize. If can be meg, eeg, ieeg, or anat. Multiple data types may be passed as a collection of strings. If None, try to anonymize the entire input dataset.

random_stateNone | int | instance of RandomState

A seed for the NumPy random number generator (RNG). If None (default), NumPy’s global RandomState singleton is used. Pass an int to use a new RandomState seeded with that value, or a RandomState to control the random-number stream. The RNG will be used to derive daysback and subject_mapping if they are 'auto'.

verbosebool | str | int | None

Control verbosity of the logging output. If None, use the default verbosity level. See the logging documentation and mne.verbose() for details. Should only be passed as a keyword argument.

Examples using mne_bids.anonymize_dataset

Anonymizing a BIDS dataset

Anonymizing a BIDS dataset