netneurotools.plotting.plot_fslr

netneurotools.plotting.plot_fslr(data, lhlabel, rhlabel, surf_atlas='conte69', surf_type='midthickness', vmin=None, vmax=None, colormap='viridis', colorbar=True, num_labels=4, orientation='horizontal', colorbartitle=None, backgroundcolor=(1, 1, 1), foregroundcolor=(0, 0, 0), **kwargs)[source]

Plot surface data on a given fsLR32k atlas.

Parameters:

  • data ((N,) array_like) – Surface data for N parcels

  • lhlabel (str) – Path to .gii file (generic GIFTI file) containing labels to N/2 parcels on the left hemisphere

  • rhlabel (str) – Path to .gii file (generic GIFTI file) containing labels to N/2 parcels on the right hemisphere

  • surf_atlas ({'conte69', 'yerkes19'}, optional) – Surface atlas on which to plot ‘data’. Default: ‘conte69’

  • surf_type ({'midthickness', 'inflated', 'vinflated'}, optional) – Type of brain surface. Default: ‘midthickness’

  • vmin (float, optional) – Minimum value to scale the colormap. If None, the min of the data will be used. Default: None

  • vmax (float, optional) – Maximum value to scale the colormap. If None, the max of the data will be used. Default: None

  • colormap (str, optional) – Any colormap from matplotlib. Default: ‘viridis’

  • colorbar (bool, optional) – Wheter to display a colorbar. Default: True

  • num_labels (int, optional) – The number of labels to display on the colorbar. Available only if colorbar=True. Default: 4

  • orientation (str, optional) – Defines the orientation of colorbar. Can be ‘horizontal’ or ‘vertical’. Available only if colorbar=True. Default: ‘horizontal’

  • colorbartitle (str, optional) – The title of colorbar. Available only if colorbar=True. Default: None

  • backgroundcolor (tuple of float values with RGB code in [0, 1], optional) – Defines the background color. Default: (1, 1, 1)

  • foregroundcolor (tuple of float values with RGB code in [0, 1], optional) – Defines the foreground color (e.g., colorbartitle color). Default: (0, 0, 0)

  • kwargs (key-value mapping) – Keyword arguments for mayavi.mlab.triangular_mesh()

Returns:

scene – Scene object containing plot

Return type:

mayavi.Scene