Note
This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.
nilearn.plotting.plot_event¶
- nilearn.plotting.plot_event(model_event, cmap=None, output_file=None, **fig_kwargs)[source]¶
Create plot for event visualization.
Warning
Events with a duration of 0 seconds will be plotted by a ‘delta function’.
- Parameters:
- model_event
pandas.DataFrame
orlist
ofpandas.DataFrame
The
pandas.DataFrame
must have three columns:trial_type
with event name,onset
andduration
. Seemake_first_level_design_matrix
for details on the required content of events dataframes.Note
The
pandas.DataFrame
can also be obtained fromnilearn.glm.first_level.first_level_from_bids
.- cmap
matplotlib.colors.Colormap
, orstr
, optional The colormap to use. Either a string which is a name of a matplotlib colormap, or a matplotlib colormap object.
- output_file
str
, or None, optional The name of an image file to export the plot to. Valid extensions are .png, .pdf, .svg. If output_file is not None, the plot is saved to a file, and the display is closed.
- **fig_kwargsextra keyword arguments, optional
Extra arguments passed to
matplotlib.pyplot.subplots
.
- model_event
- Returns:
- figure
matplotlib.figure.Figure
Plot Figure object.
- figure
Examples using nilearn.plotting.plot_event
¶
Generate an events.tsv file for the NeuroSpin localizer task