AFAIK Mayavi does not come with any perceptually uniform colormaps. I tried naively to just pass it one of Matplotlib's colormaps but it failed:
from mayavi import mlab
import multiprocessing
import matplotlib.pyplot as plt
plasma = plt.get_cmap('plasma')
...
mlab.pipeline.volume(..., colormap=plasma)
TraitError: Cannot set the undefined 'colormap' attribute of a 'VolumeFactory' object.
Edit: I found a guide to convert Matplotlib colormaps to Mayavi colormaps. However, it unfortunately doesn't work since I am trying to use a volume using a perceptually uniform colormap.
from matplotlib.cm import get_cmap
import numpy as np
from mayavi import mlab
values = np.linspace(0., 1., 256)
lut_dict = {}
lut_dict['plasma'] = get_cmap('plasma')(values.copy())
x, y, z = np.ogrid[-10:10:20j, -10:10:20j, -10:10:20j]
s = np.sin(x*y*z)/(x*y*z)
mlab.pipeline.volume(mlab.pipeline.scalar_field(s), vmin=0, vmax=0.8, colormap=lut_dict['plasma']) # still getting the same error
mlab.axes()
mlab.show()
...
Instead of setting it as the colormap argument, if you set it as the ColorTransferFunction of the volume, it works as expected.
import numpy as np
from mayavi import mlab
from tvtk.util import ctf
from matplotlib.pyplot import cm
values = np.linspace(0., 1., 256)
x, y, z = np.ogrid[-10:10:20j, -10:10:20j, -10:10:20j]
s = np.sin(x*y*z)/(x*y*z)
volume = mlab.pipeline.volume(mlab.pipeline.scalar_field(s), vmin=0, vmax=0.8)
# save the existing colormap
c = ctf.save_ctfs(volume._volume_property)
# change it with the colors of the new colormap
# in this case 'plasma'
c['rgb']=cm.get_cmap('plasma')(values.copy())
# load the color transfer function to the volume
ctf.load_ctfs(c, volume._volume_property)
# signal for update
volume.update_ctf = True
mlab.show()