mne_bids.read_raw_bids#

mne_bids.read_raw_bids(bids_path, extra_params=None, *, return_event_dict=False, verbose=None)[source]#

Read BIDS compatible data.

Will attempt to read associated events.tsv and channels.tsv files to populate the returned raw object with raw.annotations and raw.info[‘bads’].

Parameters:

bids_pathBIDSPath: The file to read. The mne_bids.BIDSPath instance passed here must have the .root attribute set. The .datatype attribute may be set. If .datatype is not set and only one data type (e.g., only EEG or MEG data) is present in the dataset, it will be selected automatically.

Note

If bids_path points to a symbolic link of a .fif file without a split entity, the link will be resolved before reading.
extra_paramsNone | dict: Extra parameters to be passed to MNE read_raw_* functions. Note that the exclude parameter, which is supported by some MNE-Python readers, is not supported; instead, you need to subset your channels after reading.
return_event_dictbool: Whether to return a dictionary that maps annotation descriptions to integer event IDs, in addition to the Raw object. If a value column is present in the *_events.tsv file, it will be used as the source of the integer event ID values (events with value="n/a" will be omitted).
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.

Returns:

rawmne.io.Raw: The data as MNE-Python Raw object.
event_iddict: A mapping from event descriptions to integer event IDs, suitable for, e.g., passing to mne.events_from_annotations(). Only returned if return_event_dict=True.

Raises:

RuntimeError: If multiple recording data types are present in the dataset, but datatype=None.
RuntimeError: If more than one data files exist for the specified recording.
RuntimeError: If no data file in a supported format can be located.
ValueError: If the specified datatype cannot be found in the dataset.