Note
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Parcellize brain surface¶
Parcellize the brain surface using .annot files. This example use Nibabel to read the .annot file.
See https://surfer.nmr.mgh.harvard.edu/fswiki/CorticalParcellation for files used in this example.

import numpy as np
from visbrain.gui import Brain
from visbrain.objects import BrainObj
from visbrain.io import download_file
file1 = 'lh.aparc.a2009s.annot'
file2 = 'rh.aparc.annot'
# Download files if needed :
path_to_file1 = download_file(file1, astype='example_data')
path_to_file2 = download_file(file2, astype='example_data')
# Define a brain object :
b_obj = BrainObj('inflated', hemisphere='both', translucent=False,
cblabel='Parcellates example', cbtxtsz=4.)
"""Parcellize the left hemisphere using the Destrieux Atlas. By default, no
parcellates are selected
"""
b_obj.parcellize(path_to_file1, hemisphere='left')
"""If you want to get the list of all predefined parcellates, use the
`get_parcellates` method which returns a pandas DataFrame with the index, the
name and the color associated to each parcellates
"""
df = b_obj.get_parcellates(path_to_file2)
# print(df)
"""Select only some parcellates. Note that this parcellization is using an
other atlas (Desikan-Killiany atlas)
"""
select = ['insula', 'paracentral', 'precentral', 'precuneus', 'frontalpole',
'temporalpole', 'fusiform', 'cuneus', 'inferiorparietal',
'inferiortemporal', 'precentral', 'superiorfrontal',
'superiortemporal']
"""Instead of using predefined colors inside the annot file, we use some data
"""
data = np.arange(len(select))
b_obj.parcellize(path_to_file2, hemisphere='right', select=select, data=data,
cmap='Spectral_r')
"""Finally, pass the brain object to `Brain` and disply the GUI
"""
Brain(brain_obj=b_obj).show()
Total running time of the script: ( 0 minutes 0.000 seconds)