Parameters: |
- evoked : instance of Evoked
The evoked data
- picks : array-like of int | None
The indices of channels to plot. If None show all.
This parameter can also be used to set the order the channels
are shown in, as the channel image is sorted by the order of picks.
- 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.
- clim : dict | None
clim for plots (after scaling has been applied). e.g.
clim = dict(eeg=[-20, 20])
Valid keys are eeg, mag, grad, misc. If None, the clim 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.
- units : dict | None
The units of the channel types used for axes labels. 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 | dict | 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.
If group_by is a dict, this cannot be a list, but it can be a dict
of lists of axes, with the keys matching those of group_by. In that
case, the provided axes will be used for the corresponding groups.
Defaults to None.
- cmap : matplotlib colormap | (colormap, bool) | ‘interactive’
Colormap. If tuple, the first value indicates the colormap to use and
the second value is a boolean defining interactivity. In interactive
mode the colors are adjustable by clicking and dragging the colorbar
with left and right mouse button. Left mouse button moves the scale up
and down and right mouse button adjusts the range. Hitting space bar
resets the scale. Up and down arrows can be used to change the
colormap. If ‘interactive’, translates to ('RdBu_r', True) .
Defaults to 'RdBu_r' .
- colorbar : bool
If True, plot a colorbar. Defaults to True.
- mask : ndarray | None
An array of booleans of the same shape as the data. Entries of the
data that correspond to `False in the mask are masked (see
do_mask below). Useful for, e.g., masking for statistical
significance.
- mask_style: None | ‘both’ | ‘contour’ | ‘mask’
If mask is not None: if ‘contour’, a contour line is drawn around
the masked areas (True in mask). If ‘mask’, entries not
True in mask are shown transparently. If ‘both’, both a contour
and transparency are used.
If None , defaults to ‘both’ if mask is not None, and is ignored
otherwise.
- mask_cmap : matplotlib colormap | (colormap, bool) | ‘interactive’
The colormap chosen for masked parts of the image (see below), if
mask is not None . If None, cmap is reused. Defaults to
Greys . Not interactive. Otherwise, as cmap.
- mask_alpha : float
A float between 0 and 1. If mask is not None, this sets the
alpha level (degree of transparency) for the masked-out segments.
I.e., if 0, masked-out segments are not visible at all.
Defaults to .25.
- time_unit : str
The units for the time axis, can be “ms” or “s” (default).
- show_names : bool | str
Determines if channel names should be plotted on the y axis. If False,
no names are shown. If True, ticks are set automatically and the
corresponding channel names are shown. If str, must be “auto” or “all”.
If “all”, all channel names are shown.
If “auto”, is set to False if picks is None ; to True if
picks is not None and fewer than 25 picks are shown; to “all”
if picks is not None and contains fewer than 25 entries.
- group_by : None | dict
If a dict, the values must be picks, and axes must also be a dict
with matching keys, or None. If axes is None, one figure and one axis
will be created for each entry in group_by.
Then, for each entry, the picked channels will be plotted
to the corresponding axis. If titles are None, keys will become plot
titles. This is useful for e.g. ROIs. Each entry must contain only
one channel type. For example:
group_by=dict(Left_ROI=[1, 2, 3, 4], Right_ROI=[5, 6, 7, 8])
If None, all picked channels are plotted to the same axis.
|