import cortex
import numpy as np
from matplotlib import pyplot as plt

subject = 'S1'
transform = 'fullhead'

for type_ in ["thin", "thick"]:
    # create dataset with volume from 0 to n_voxels
    mask = cortex.db.get_mask(subject, transform, type=type_)
    vol = cortex.Volume(np.ones(mask.sum()), subject, transform, cmap="viridis", vmin=0, vmax=1)

    # set 50% of the values in the dataset to NaN
    vol.data[np.random.rand(*vol.data.shape) > 0.5] = np.nan

    _ = cortex.quickshow(vol, nanmean=True, with_curvature=False)
    plt.show()