Visualizing scalar fields in Python
I need to render multiple overlapping scalar fields in Python. I found a library mayavi
to do similar graphs. The problem is I don't understand how to set up the colormap for the scalar fields. My idea is to have shades of the same color for each field. I tried to take an example but it doesn't work. Here's my code for rendering a scalar field using shades of red:
import numpy as np
from mayavi import mlab
x, y, z = np.ogrid[-10:10:20j, -10:10:20j, -10:10:20j]
s = np.sin(x*y*z)/(x*y*z)
src = mlab.pipeline.scalar_field(s)
volume = mlab.pipeline.volume(src)
lut = np.zeros((256, 4), np.uint8)
lut[:,-1] = 255
lut[:, 0] = np.linspace(0, 255, 256)
volume.module_manager.scalar_lut_manager.lut.table = lut
mlab.draw()
mlab.view(40, 85)
mlab.show()
However, the output graph is always with the standard blue-red lookup table.
+3
source to share
1 answer
I have not been able to find a solution using lut_manager
, however below, below, this github answer works for me.
import numpy as np
from mayavi import mlab
# import color transfer function from vtk
from tvtk.util import ctf
# import matlab colormaps
from matplotlib.pyplot import cm
x, y, z = np.ogrid[-10:10:20j, -10:10:20j, -10:10:20j]
s = np.sin(x*y*z)/(x*y*z)
src = mlab.pipeline.scalar_field(s)
volume = mlab.pipeline.volume(src)
# save the color transfer function of the current volume
c = ctf.save_ctfs(volume._volume_property)
# change the alpha channel as needed
c['alpha'][1][1] = 0.5
# change the color points to another color scheme
# in this case 'magma'
c['rgb']=[[a[0],a[1],a[2],cm.magma.colors.index(a)/255] for a in cm.magma.colors]
# load the new color transfer function
ctf.load_ctfs(c, volume._volume_property)
# signal for update
volume.update_ctf = True
mlab.show()
0
source to share