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_eventpandas.DataFrame, str or pathlib.Path to a TSV event file, or a list or tuple of pandas.DataFrame, str or pathlib.Path to a TSV event file.

The pandas.DataFrame must have three columns: trial_type with event name, onset and duration. See make_first_level_design_matrix for details on the required content of events dataframes.

Note

The pandas.DataFrame can also be obtained from nilearn.glm.first_level.first_level_from_bids.

cmapmatplotlib.colors.Colormap, or str, optional

The colormap to use. Either a string which is a name of a matplotlib colormap, or a matplotlib colormap object.

output_filestr, 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.

Returns:
figurematplotlib.figure.Figure

Plot Figure object.

Examples using nilearn.plotting.plot_event

Generate an events.tsv file for the NeuroSpin localizer task

Generate an events.tsv file for the NeuroSpin localizer task