MNE-Python can read data on-demand using the preload option provided in IO functions. For example:
from mne import io
from mne.datasets import sample
data_path = sample.data_path()
raw_fname = data_path + '/MEG/sample/sample_audvis_filt-0-40_raw.fif'
raw = io.read_raw_fif(raw_fname, preload=False)
Note
Filtering does not work with preload=False.
Similarly, epochs can also be be read from disk on-demand. For example:
import mne
events = mne.find_events(raw)
event_id, tmin, tmax = 1, -0.2, 0.5
picks = mne.pick_types(raw.info, meg=True, eeg=True, stim=False, eog=True)
epochs = mne.Epochs(raw, events, event_id, tmin, tmax, picks=picks, baseline=(None, 0), reject=dict(eeg=80e-6, eog=150e-6),
preload=False)
When preload=False, the epochs data is loaded from the disk on-demand. Note that preload=False for epochs will work even if the raw object
has been loaded with preload=True. Preloading is also supported for mne.read_epochs().
Warning
This comes with a caveat. When preload=False, data rejection based on peak-to-peak thresholds is executed when the data is loaded from disk, not when the Epochs object is created.
To explicitly reject artifacts with preload=False, use the function mne.Epochs.drop_bad().
To load the data if preload=False was initially selected, use the functions mne.io.Raw.load_data() and mne.Epochs.load_data().