This documentation is for development version 0.18.dev0.


mne.viz.plot_ica_components(ica, picks=None, ch_type=None, res=64, layout=None, vmin=None, vmax=None, cmap='RdBu_r', sensors=True, colorbar=False, title=None, show=True, outlines='head', contours=6, image_interp='bilinear', head_pos=None, inst=None)[source]

Project unmixing matrix on interpolated sensor topography.

ica : instance of mne.preprocessing.ICA

The ICA solution.

picks : str | list | slice | None

Channels to include. Slices and lists of integers will be interpreted as channel indices. In lists, channel type strings (e.g., ['meg', 'eeg']) will pick channels of those types, channel name strings (e.g., ['MEG0111', 'MEG2623'] will pick the given channels. Can also be the string values “all” to pick all channels, or “data” to pick data channels. None (default) will pick all channels. If None all are plotted in batches of 20.

ch_type : ‘mag’ | ‘grad’ | ‘planar1’ | ‘planar2’ | ‘eeg’ | None

The channel type to plot. For ‘grad’, the gradiometers are collected in pairs and the RMS for each pair is plotted. If None, then channels are chosen in the order given above.

res : int

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

layout : None | Layout

Layout instance specifying sensor positions (does not need to be specified for Neuromag data). If possible, the correct layout is inferred from the data.

vmin : float | callable | None

The value specifying the lower bound of the color range. If None, and vmax is None, -vmax is used. Else np.min(data). If callable, the output equals vmin(data). Defaults to None.

vmax : float | callable | None

The value specifying the upper bound of the color range. If None, the maximum absolute value is used. If callable, the output equals vmax(data). Defaults to None.

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 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, ‘Reds’ is used for all positive data, otherwise defaults to ‘RdBu_r’. If ‘interactive’, translates to (None, True). Defaults to ‘RdBu_r’.


Interactive mode works smoothly only for a small amount of topomaps.

sensors : bool | str

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

colorbar : bool

Plot a colorbar.

title : str | None

Title to use.

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.

head_pos : dict | None

If None (default), the sensors are positioned such that they span the head circle. If dict, can have entries ‘center’ (tuple) and ‘scale’ (tuple) for what the center and scale of the head should be relative to the electrode locations.

inst : Raw | Epochs | None

To be able to see component properties after clicking on component topomap you need to pass relevant data - instances of Raw or Epochs (for example the data that ICA was trained on). This takes effect only when running matplotlib in interactive mode.

fig : instance of matplotlib.figure.Figure or list

The figure object(s).


When run in interactive mode, plot_ica_components allows to reject components by clicking on their title label. The state of each component is indicated by its label color (gray: rejected; black: retained). It is also possible to open component properties by clicking on the component topomap (this option is only available when the inst argument is supplied).