python 标量_Python中的标量字段可视化

I need to visualize several overlapping scalar fields in Python. I found mayavi library to do this kind of plots. The problem is that I don't understand how to customize a color map for scalar fields. My idea is to have shades of one color for each field. I tried to adopt an example, but it doesn't work. Here there is my code to visualize 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 plot is always with a standard blue-red look-up table.

解决方案

I couldn't find a solution using the lut_manager, however the solution below, following this github reply 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()