mne.viz.plot_evoked

mne.viz.plot_evoked(evoked, picks=None, exclude='bads', unit=True, show=True, ylim=None, xlim='tight', proj=False, hline=None, units=None, scalings=None, titles=None, axes=None, gfp=False, window_title=None, spatial_colors=False, zorder='unsorted', selectable=True, noise_cov=None, time_unit=None, verbose=None)[source]

Plot evoked data using butterfly plots.

Left click to a line shows the channel name. Selecting an area by clicking and holding left mouse button plots a topographic map of the painted area.

Note

If bad channels are not excluded they are shown in red.

Parameters:
evoked : instance of Evoked

The evoked data

picks : array-like of int | None

The indices of channels to plot. If None show all.

exclude : list of str | ‘bads’

Channels names to exclude from being shown. If ‘bads’, the bad channels are excluded.

unit : bool

Scale plot with channel (SI) unit.

show : bool

Show figure if True.

ylim : dict | None

ylim for plots (after scaling has been applied). e.g. ylim = dict(eeg=[-20, 20]) Valid keys are eeg, mag, grad, misc. If None, the ylim parameter for each channel equals the pyplot default.

xlim : ‘tight’ | tuple | None

xlim for plots.

proj : bool | ‘interactive’

If true SSP projections are applied before display. If ‘interactive’, a check box for reversible selection of SSP projection vectors will be shown.

hline : list of floats | None

The values at which to show an horizontal line.

units : dict | None

The units of the channel types used for axes lables. If None, defaults to dict(eeg=’uV’, grad=’fT/cm’, mag=’fT’).

scalings : dict | None

The scalings of the channel types to be applied for plotting. If None, defaults to dict(eeg=1e6, grad=1e13, mag=1e15).

titles : dict | None

The titles associated with the channels. If None, defaults to dict(eeg=’EEG’, grad=’Gradiometers’, mag=’Magnetometers’).

axes : instance of Axis | list | None

The axes to plot to. If list, the list must be a list of Axes of the same length as the number of channel types. If instance of Axes, there must be only one channel type plotted.

gfp : bool | ‘only’

Plot GFP in green if True or “only”. If “only”, then the individual channel traces will not be shown.

window_title : str | None

The title to put at the top of the figure.

spatial_colors : bool

If True, the lines are color coded by mapping physical sensor coordinates into color values. Spatially similar channels will have similar colors. Bad channels will be dotted. If False, the good channels are plotted black and bad channels red. Defaults to False.

zorder : str | callable

Which channels to put in the front or back. Only matters if spatial_colors is used. If str, must be std or unsorted (defaults to unsorted). If std, data with the lowest standard deviation (weakest effects) will be put in front so that they are not obscured by those with stronger effects. If unsorted, channels are z-sorted as in the evoked instance. If callable, must take one argument: a numpy array of the same dimensionality as the evoked raw data; and return a list of unique integers corresponding to the number of channels.

New in version 0.13.0.

selectable : bool

Whether to use interactive features. If True (default), it is possible to paint an area to draw topomaps. When False, the interactive features are disabled. Disabling interactive features reduces memory consumption and is useful when using axes parameter to draw multiaxes figures.

New in version 0.13.0.

noise_cov : instance of Covariance | str | None

Noise covariance used to whiten the data while plotting. Whitened data channel names are shown in italic. Can be a string to load a covariance from disk. See also mne.Evoked.plot_white() for additional inspection of noise covariance properties when whitening evoked data. For data processed with SSS, the effective dependence between magnetometers and gradiometers may introduce differences in scaling, consider using mne.Evoked.plot_white().

New in version 0.16.0.

time_unit : str

The units for the time axis, can be “ms” (default in 0.16) or “s” (will become the default in 0.17).

New in version 0.16.

verbose : bool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more).

Returns:
fig : instance of matplotlib.figure.Figure

Figure containing the butterfly plots.