frites.plot.plot_conn_heatmap#

frites.plot.plot_conn_heatmap(conn, cmap='plasma', vmin=None, vmax=None, categories=None, categories_kw={}, cbar=True, cbar_title=None, cbar_kw={}, prop=None, bad=None, xticklabels='auto', yticklabels='auto', square=True, ax=None)[source]#

Plot the connectivity matrix as a heatmap.

Parameters:

connxarray.DataArray | pandas.DataFrame | numpy.ndarray: Either a 2D xarray.DataArray or a pandas DataFrame or a 2D NumPy array
cmapstr | ‘plasma’: Colormap name
vmin, vmaxfloat | None: Minimum and maximum of colorbar limits
categoriesnumpy:array_like | None: Category associated to each region name. Can be hemisphere name, lobe name or indices describing group of regions. By default, an horizontal and a vertical lines are going to be plotted as a separation between categories (see argument below for controlling the aesthetic)
categories_kwdict | {}: Additional arguments to control the aesthetic of the categorical lines (e.g. categories_kw={‘color’: ‘orange’, ‘lw’: 4})
cbarbool | True: Add the colorbar
cbar_titlestr | None: Colorbar title
cbar_kwdict | {}: Additional arguments for controlling the colorbar title (e.g. cbar_kw={‘fontweight’: ‘bold’, ‘fontsize’: 20})
propfloat | None: Proportion of edges to keep. For example, prop=5 means that 95th percentile will be used for thresholding the connections.
badstr | None: Color of bad values in the connectivity matrix (nan or non-finite values). By default, pad pixels are transparent.
xticklabels, yticklabelsstr | None: Use ‘auto’ for the automatic settings of the x and y tick labels. Use an integer to decrease the number of ticks displayed. You can also disable the tick labels using False
squarebool | True: Make the axis square
axmatplotlib Axes | None: Matplotlib axis (to add to a subplot for example)

Returns:

axmatplotlib Axes: Axes object with the heatmap