This documentation is for development version 0.18.dev0.

mne.viz.plot_projs_topomap

mne.viz.plot_projs_topomap(projs, layout=None, cmap=None, sensors=True, colorbar=False, res=64, size=1, show=True, outlines='head', contours=6, image_interp='bilinear', axes=None, info=None)[source]

Plot topographic maps of SSP projections.

Parameters:
projs : list of Projection

The projections

layout : None | Layout | list of Layout

Layout instance specifying sensor positions (does not need to be specified for Neuromag data). Or a list of Layout if projections are from different sensor types.

cmap : matplotlib colormap | (colormap, bool) | ‘interactive’ | None

Colormap to use. If tuple, the first value indicates the colormap to use and the second value is a boolean defining interactivity. In interactive mode (only works if colorbar=True) 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 range. Up and down arrows can be used to change the colormap. If None (default), ‘Reds’ is used for all positive data, otherwise defaults to ‘RdBu_r’. If ‘interactive’, translates to (None, True).

sensors : bool | str

Add markers for sensor locations to the plot. Accepts matplotlib plot format string (e.g., ‘r+’ for red plusses). If True, a circle will be used (via .add_artist). Defaults to True.

colorbar : bool

Plot a colorbar.

res : int

The resolution of the topomap image (n pixels along each side).

size : scalar

Side length of the topomaps in inches (only applies when plotting multiple topomaps at a time).

show : bool

Show figure if True.

outlines : ‘head’ | ‘skirt’ | dict | None

The outlines to be drawn. If ‘head’, the default head scheme will be drawn. If ‘skirt’ the head scheme will be drawn, but sensors are allowed to be plotted outside of the head circle. If dict, each key refers to a tuple of x and y positions, the values in ‘mask_pos’ will serve as image mask, and the ‘autoshrink’ (bool) field will trigger automated shrinking of the positions due to points outside the outline. Alternatively, a matplotlib patch object can be passed for advanced masking options, either directly or as a function that returns patches (required for multi-axis plots). If None, nothing will be drawn. Defaults to ‘head’.

contours : int | array of float

The number of contour lines to draw. If 0, no contours will be drawn. When an integer, matplotlib ticker locator is used to find suitable values for the contour thresholds (may sometimes be inaccurate, use array for accuracy). If an array, the values represent the levels for the contours. Defaults to 6.

image_interp : str

The image interpolation to be used. All matplotlib options are accepted.

axes : instance of Axes | 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 projectors. If instance of Axes, there must be only one projector. Defaults to None.

info : instance of Info | None

The measurement information to use to determine the layout. If not None, layout must be None.

Returns:
fig : instance of matplotlib.figure.Figure

Figure distributing one image per channel across sensor topography.

Notes

New in version 0.9.0.