mne.viz.plot_events#

mne.viz.plot_events(events, sfreq=None, first_samp=0, color=None, event_id=None, axes=None, equal_spacing=True, show=True, on_missing='raise', verbose=None)[source]#

Plot events to get a visual display of the paradigm.

Parameters:

eventsndarray of int, shape (n_events, 3): The identity and timing of experimental events, around which the epochs were created. See events for more information.
sfreqfloat | None: The sample frequency. If None, data will be displayed in samples (not seconds).
first_sampint: The index of the first sample. Recordings made on Neuromag systems number samples relative to the system start (not relative to the beginning of the recording). In such cases the raw.first_samp attribute can be passed here. Default is 0.
colordict | None: Dictionary of event_id integers as keys and colors as values. If None, colors are automatically drawn from a default list (cycled through if number of events longer than list of default colors). Color can be any valid matplotlib color.
event_iddict | None: Dictionary of event labels (e.g. ‘aud_l’) as keys and their associated event_id values. Labels are used to plot a legend. If None, no legend is drawn.
axesinstance of Axes: The subplot handle.
equal_spacingbool: Use equal spacing between events in y-axis.
showbool: Show figure if True.
on_missing‘raise’ | ‘warn’ | ‘ignore’: Can be 'raise' (default) to raise an error, 'warn' to emit a warning, or 'ignore' to ignore when event numbers from event_id are missing from events. When numbers from events are missing from event_id they will be ignored and a warning emitted; consider using verbose='error' in this case.

New in v0.21.
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: