After looking at various related answers, I could not figure out a straight way.
I have a 3-d numpy array of shape (390, 280, 160). I want to visualize this as an image. What could be the simplest way to do it?
-
Images represent 2D data. How do you expect a visualization of 3D data to appear?user2699– user26992018-08-22 12:27:56 +00:00Commented Aug 22, 2018 at 12:27
Add a comment
|
1 Answer
Here is a minimal example of volumetric plot using mayavi.
You can find more examples of 3d data visualization here
from mayavi import mlab
import numpy as np
s = np.random.rand(20, 20, 20)
volume = mlab.pipeline.volume(mlab.pipeline.scalar_field(s), vmin=0, vmax=0.8)
mlab.draw()
mlab.savefig('output.png')
From mayavi docs
For such a visualization, tweaking the opacity transfer function is critical to achieve a good effect. Typically, it can be useful to limit the lower and upper values to the 20 and 80 percentiles of the data, in order to have a reasonable fraction of the volume transparent.
8 Comments
user10050371
I tried with mayavi on jupyter notebook but it seems to be not working. Is it possible to do it in an alternative way?
user10050371
I tried it by saving the figure, using mlab.savefig('a.png'). It saves an image but the image is homogeneous and has full green color whereas random generator would not have this structure.
taras
@user10050371, Try adding
mlab.draw() before mlab.save(). I think I've had the same issue as well.taras
@user10050371, I updated my answer with the output image.
|