[FIXED] What is the most efficient way to plot 3d array in Python?

Issue

What is the most efficient way to plot 3d array in Python?

For example:

volume = np.random.rand(512, 512, 512)

where array items represent grayscale color of each pixel.

---

The following code works too slow:

import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
import matplotlib.pyplot as plt

fig = plt.figure()
ax = fig.gca(projection='3d')
volume = np.random.rand(20, 20, 20)
for x in range(len(volume[:, 0, 0])):
    for y in range(len(volume[0, :, 0])):
        for z in range(len(volume[0, 0, :])):
            ax.scatter(x, y, z, c = tuple([volume[x, y, z], volume[x, y, z], volume[x, y, z], 1]))
plt.show()

Solution

First, a dense grid of 512x512x512 points is way too much data to plot, not from a technical perspective but from being able to see anything useful from it when observing the plot. You probably need to extract some isosurfaces, look at slices, etc. If most of the points are invisible, then it's probably okay, but then you should ask ax.scatter to only show the nonzero points to make it faster.

That said, here's how you can do it much more quickly. The tricks are to eliminate all Python loops, including ones that would be hidden in libraries like itertools.

import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
import matplotlib.pyplot as plt

# Make this bigger to generate a dense grid.
N = 8

# Create some random data.
volume = np.random.rand(N, N, N)

# Create the x, y, and z coordinate arrays.  We use 
# numpy's broadcasting to do all the hard work for us.
# We could shorten this even more by using np.meshgrid.
x = np.arange(volume.shape[0])[:, None, None]
y = np.arange(volume.shape[1])[None, :, None]
z = np.arange(volume.shape[2])[None, None, :]
x, y, z = np.broadcast_arrays(x, y, z)

# Turn the volumetric data into an RGB array that's
# just grayscale.  There might be better ways to make
# ax.scatter happy.
c = np.tile(volume.ravel()[:, None], [1, 3])

# Do the plotting in a single call.
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.scatter(x.ravel(),
           y.ravel(),
           z.ravel(),
           c=c)

Answered By - Mr Fooz