Plot Event Related Potential / Fields image on topographies.
Epochs
The epochs.
Layout
System specific sensor positions.
float
The standard deviation of the Gaussian smoothing to apply along the epoch axis to apply in the image. If 0., no smoothing is applied.
float
The min value in the image. The unit is µV for EEG channels, fT for magnetometers and fT/cm for gradiometers.
float
The max value in the image. The unit is µV for EEG channels, fT for magnetometers and fT/cm for gradiometers.
None
Whether to display a colorbar or not. If None
a colorbar will be
shown only if all channels are of the same type. Defaults to None
.
None
| array
of int
| callable()
If not None, order is used to reorder the epochs on the y-axis of the image. If it’s an array of int it should be of length the number of good epochs. If it’s a callable the arguments passed are the times vector and the data as 2d array (data.shape[1] == len(times)).
Colors to be mapped to the values.
float
Scaling factor for adjusting the relative size of the layout on the canvas.
str
Title of the figure.
dict
| None
The scalings of the channel types to be applied for plotting. If
None
, defaults to dict(eeg=1e6, grad=1e13, mag=1e15)
.
str
Matplotlib borders style to be used for each sensor plot.
The figure face color. Defaults to black.
None
| array
A background image for the figure. This must be a valid input to
matplotlib.pyplot.imshow()
. Defaults to None
.
The color of tick labels in the colorbar. Defaults to white.
Whether to show the figure. Defaults to True
.
matplotlib.figure.Figure
Figure distributing one image per channel across sensor topography.
Notes
In an interactive Python session, this plot will be interactive; clicking on a channel image will pop open a larger view of the image; this image will always have a colorbar even when the topo plot does not (because it shows multiple sensor types).