| Parameters: | evokeds : instance of mne.Evoked | list | dict
If a single evoked instance, it is plotted as a time series.
If a dict whose values are Evoked objects, the contents are plotted as
single time series each and the keys are used as condition labels.
If a list of Evokeds, the contents are plotted with indices as labels.
If a [dict/list] of lists, the unweighted mean is plotted as a time
series and the parametric confidence interval is plotted as a shaded
area. All instances must have the same shape - channel numbers, time
points etc.
picks : int | list of int
If int or list of int, the indices of the sensors to average and plot.
Must all be of the same channel type.
If the selected channels are gradiometers, the corresponding pairs
will be selected.
If multiple channel types are selected, one figure will be returned for
each channel type.
If an empty list, gfp will be set to True, and the Global Field
Power plotted.
gfp : bool
If True, the channel type wise GFP is plotted.
If picks is an empty list (default), this is set to True.
colors : list | dict | None
If a list, will be sequentially used for line colors.
If a dict, can map evoked keys or ‘/’-separated (HED) tags to
conditions.
For example, if evokeds is a dict with the keys “Aud/L”, “Aud/R”,
“Vis/L”, “Vis/R”, colors can be dict(Aud=’r’, Vis=’b’) to map both
Aud/L and Aud/R to the color red and both Visual conditions to blue.
If None (default), a sequence of desaturated colors is used.
linestyles : list | dict
If a list, will be sequentially and repeatedly used for evoked plot
linestyles.
If a dict, can map the evoked keys or ‘/’-separated (HED) tags to
conditions.
For example, if evokeds is a dict with the keys “Aud/L”, “Aud/R”,
“Vis/L”, “Vis/R”, linestyles can be dict(L=’–’, R=’-‘) to map both
Aud/L and Vis/L to dashed lines and both Right-side conditions to
straight lines.
styles : dict | None
If a dict, keys must map to evoked keys or conditions, and values must
be a dict of legal inputs to matplotlib.pyplot.plot. These
parameters will be passed to the line plot call of the corresponding
condition, overriding defaults.
E.g., if evokeds is a dict with the keys “Aud/L”, “Aud/R”,
“Vis/L”, “Vis/R”, styles can be {“Aud/L”:{“linewidth”:1}} to set
the linewidth for “Aud/L” to 1. Note that HED (‘/’-separated) tags are
not supported.
vlines : list of int
A list of integers corresponding to the positions, in seconds,
at which to plot dashed vertical lines.
ci : float | None
If not None and evokeds is a [list/dict] of lists, a confidence
interval is drawn around the individual time series. This value
determines the CI width. E.g., if this value is .95 (the default),
the 95% parametric confidence interval is drawn.
If None, no shaded confidence band is plotted.
truncate_yaxis : bool
If True, the left y axis is truncated to half the max value and
rounded to .25 to reduce visual clutter. Defaults to 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.
invert_y : bool
If True, negative values are plotted up (as is sometimes done
for ERPs out of tradition). Defaults to False.
axes : None | matplotlib.pyplot.axes instance | list of axes
What axes to plot to. If None, a new axes is created.
When plotting multiple channel types, can also be a list of axes, one
per channel type.
title : None | str
If str, will be plotted as figure title. If None, the channel
names will be shown.
show : bool
If True, show the figure.
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