set matplotlib 3d plot aspect ratio?

If you know the bounds, eg. +-3 centered around (0,0,0), you can add invisible points like this:

import numpy as np
import pylab as pl
from mpl_toolkits.mplot3d import Axes3D
fig = pl.figure()
ax = fig.add_subplot(projection='3d')
ax.set_aspect('equal')
MAX = 3
for direction in (-1, 1):
    for point in np.diag(direction * MAX * np.array([1,1,1])):
        ax.plot([point[0]], [point[1]], [point[2]], 'w')

As of matplotlib 3.3.0, Axes3D.set_box_aspect seems to be the recommended approach.

import numpy as np
import matplotlib.pyplot as plt

xs, ys, zs = ...
ax = plt.axes(projection='3d')

ax.set_box_aspect((np.ptp(xs), np.ptp(ys), np.ptp(zs)))  # aspect ratio is 1:1:1 in data space

ax.plot(xs, ys, zs)

Looks like this feature has since been added so thought I'd add an answer for people who come by this thread in the future like I did:

fig = plt.figure(figsize=plt.figaspect(0.5)*1.5) #Adjusts the aspect ratio and enlarges the figure (text does not enlarge)
ax = fig.add_subplot(projection='3d')

figaspect(0.5) makes the figure twice as wide as it is tall. Then the *1.5 increases the size of the figure. The labels etc won't increase so this is a way to make the graph look less cluttered by the labels.

I didn't try all of these answers, but this kludge did it for me:

def axisEqual3D(ax):
    extents = np.array([getattr(ax, 'get_{}lim'.format(dim))() for dim in 'xyz'])
    sz = extents[:,1] - extents[:,0]
    centers = np.mean(extents, axis=1)
    maxsize = max(abs(sz))
    r = maxsize/2
    for ctr, dim in zip(centers, 'xyz'):
        getattr(ax, 'set_{}lim'.format(dim))(ctr - r, ctr + r)