This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.

7.10.6. nilearn.plotting.plot_matrix

nilearn.plotting.plot_matrix(mat, title=None, labels=None, figure=None, axes=None, colorbar=True, cmap=<matplotlib.colors.LinearSegmentedColormap object>, tri='full', auto_fit=True, grid=False, **kwargs)

Plot the given matrix.


mat : 2-D numpy array

Matrix to be plotted.

title : string or None, optional

A text to add in the upper left corner.

labels : list of strings, optional

The label of each row and column

figure : figure instance, figsize tuple, or None

Sets the figure used. This argument can be either an existing figure, or a pair (width, height) that gives the size of a newly-created figure. Specifying both axes and figure is not allowed.

axes : None or Axes, optional

Axes instance to be plotted on. Creates a new one if None. Specifying both axes and figure is not allowed.

colorbar : boolean, optional

If True, an integrated colorbar is added.

cmap : matplotlib colormap, optional

The colormap for the matrix. Default is RdBu_r.

tri : {‘lower’, ‘diag’, ‘full’}, optional

Which triangular part of the matrix to plot: ‘lower’ is the lower part, ‘diag’ is the lower including diagonal, and ‘full’ is the full matrix.

auto_fit : boolean, optional

If auto_fit is True, the axes are dimensioned to give room for the labels. This assumes that the labels are resting against the bottom and left edges of the figure.

grid : color or False, optional

If not False, a grid is plotted to separate rows and columns using the given color.

kwargs : extra keyword arguments

Extra keyword arguments are sent to pylab.imshow

Returns Matplotlib AxesImage instance