- mne.io.read_raw_egi(input_fname, eog=None, misc=None, include=None, exclude=None, preload=False, channel_naming='E%d', verbose=None)¶
Read EGI simple binary as raw object.
This function attempts to create a synthetic trigger channel. See the Notes section below.
Path to the raw file. Files with an extension .mff are automatically considered to be EGI’s native MFF format files.
Names of channels or list of indices that should be designated EOG channels. Default is None.
Names of channels or list of indices that should be designated MISC channels. Default is None.
The event channels to be ignored when creating the synthetic trigger. Defaults to None. Note. Overrides
The event channels to be ignored when creating the synthetic trigger. Defaults to None. If None, channels that have more than one event and the
TREVchannels will be ignored.
- preloadbool or
Preload data into memory for data manipulation and faster indexing. If True, the data will be preloaded into memory (fast, requires large amount of memory). If preload is a string, preload is the file name of a memory-mapped file which is used to store the data on the hard drive (slower, requires less memory).
New in version 0.11.
Channel naming convention for the data channels. Defaults to ‘E%d’ (resulting in channel names ‘E1’, ‘E2’, ‘E3’…). The effective default prior to 0.14.0 was ‘EEG %03d’.
New in version 0.14.0.
- rawinstance of RawEGI
A Raw object containing EGI data.
Documentation of attribute and methods.
The trigger channel names are based on the arbitrary user dependent event codes used. However this function will attempt to generate a synthetic trigger channel named
STI 014in accordance with the general Neuromag / MNE naming pattern.
The event_id assignment equals
np.arange(n_events) + 1. The resulting
event_idmapping is stored as attribute to the resulting raw object but will be ignored when saving to a fiff. Note. The trigger channel is artificially constructed based on timestamps received by the Netstation. As a consequence, triggers have only short durations.
This step will fail if events are not mutually exclusive.