yasa.topoplot

yasa.topoplot(data, montage='standard_1020', vmin=None, vmax=None, mask=None, title=None, cmap=None, n_colors=100, cbar_title=None, cbar_ticks=None, figsize=4, 4, dpi=80, fontsize=14, **kwargs)[source]

Topoplot.

This is a wrapper around mne.viz.plot_topomap().

For more details, please refer to this example notebook.

New in version 0.4.1.

Parameters
datapandas.Series

A pandas Series with the values to plot. The index MUST be the channel names (e.g. [‘C4’, ‘F4’] or [‘C4-M1’, ‘C3-M2’]).

montagestr

The name of the montage to use. Valid montages can be found at mne.channels.make_standard_montage().

vmin, vmaxfloat

The minimum and maximum values of the colormap. If None, these will be defined based on the min / max values of data.

maskpandas.Series

A pandas Series indicating the significant electrodes. The index MUST be the channel names (e.g. [‘C4’, ‘F4’] or [‘C4-M1’, ‘C3-M2’]).

titlestr

The plot title.

cmapstr

A matplotlib color palette. A list of color palette can be found at: https://seaborn.pydata.org/tutorial/color_palettes.html

n_colorsint

The number of colors to discretize the color palette.

cbar_titlestr

The title of the colorbar.

cbar_tickslist

The ticks of the colorbar.

figsizetuple

Width, height in inches.

dpiint

The resolution of the plot.

fontsizeint

Global font size of all the elements of the plot.

**kwargsdict

Other arguments that are passed to mne.viz.plot_topomap().

Returns
figmatplotlib.figure.Figure

Matplotlib Figure

Examples

  1. Plot all-positive values

>>> import yasa
>>> import pandas as pd
>>> data = pd.Series([4, 8, 7, 1, 2, 3, 5],
...                  index=['F4', 'F3', 'C4', 'C3', 'P3', 'P4', 'Oz'],
...                  name='Values')
>>> fig = yasa.topoplot(data, title='My first topoplot')
../_images/yasa-topoplot-1.png
  1. Plot correlation coefficients (values ranging from -1 to 1)

>>> import yasa
>>> import pandas as pd
>>> data = pd.Series([-0.5, -0.7, -0.3, 0.1, 0.15, 0.3, 0.55],
...                  index=['F3', 'Fz', 'F4', 'C3', 'Cz', 'C4', 'Pz'])
>>> fig = yasa.topoplot(data, vmin=-1, vmax=1, n_colors=8,
...                     cbar_title="Pearson correlation")
../_images/yasa-topoplot-2.png