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)[source]¶

Plot events to get a visual display of the paradigm.

Parameters:

Parameters:	events : array, shape (n_events, 3) The events. sfreq : float \| None The sample frequency. If None, data will be displayed in samples (not seconds). first_samp : int The index of the first sample. Typically the raw.first_samp attribute. It is needed for recordings on a Neuromag system as the events are defined relative to the system start and not to the beginning of the recording. color : dict \| None Dictionary of event_id value and its associated color. If None, colors are automatically drawn from a default list (cycled through if number of events longer than list of default colors). event_id : dict \| None Dictionary of event label (e.g. ‘aud_l’) and its associated event_id value. Label used to plot a legend. If None, no legend is drawn. axes : instance of matplotlib.axes.AxesSubplot The subplot handle. equal_spacing : bool Use equal spacing between events in y-axis. show : bool Show figure if True.
Returns:	fig : matplotlib.figure.Figure The figure object containing the plot.

events : array, shape (n_events, 3)

The events.

sfreq : float | None

The sample frequency. If None, data will be displayed in samples (not seconds).

first_samp : int

The index of the first sample. Typically the raw.first_samp attribute. It is needed for recordings on a Neuromag system as the events are defined relative to the system start and not to the beginning of the recording.

color : dict | None

Dictionary of event_id value and its associated color. If None, colors are automatically drawn from a default list (cycled through if number of events longer than list of default colors).

event_id : dict | None