How do I use colorbar with hist2d in matplotlib.pyplot?

Question

I want to do something similar to http://matplotlib.org/examples/pylab_examples/hist2d_log_demo.html but I've read that using pylab for code other than in python interactive mode is bad practice so I'd like to do this with matplotlib.pyplot. However, I can't figure out how to make this code work using pyplot. Using, pylab, the example given is

from matplotlib.colors import LogNorm
from pylab import *

#normal distribution center at x=0 and y=5
x = randn(100000)
y = randn(100000)+5

hist2d(x, y, bins=40, norm=LogNorm())
colorbar()
show()

I've tried a lot like

import matplotlib.pyplot as plt
fig = plt.figure()
ax1 = fig.add_subplot(1,1,1)
h1 = ax1.hist2d([1,2],[3,4])

and from here I've tried everything from plt.colorbar(h1) plt.colorbar(ax1) plt.colorbar(fig) ax.colorbar() etc etc and I can't get anything to work.

In general, I'm honestly not really clear on the relationship between pylab and pyplot, even after reading http://matplotlib.org/faq/usage_faq.html. For example show() in pylab seems to become plt.show() in pyplot, but for some reason colorbar doesn't become plt.colorbar()?

For example,

Answer 1

A colorbar needs a ScalarMappable object as its first argument. plt.hist2d returns this as the forth element of the returned tuple.

h = hist2d(x, y, bins=40, norm=LogNorm())
colorbar(h[3])

Complete code:

from matplotlib.colors import LogNorm
import matplotlib.pyplot as plt
import numpy as np

#normal distribution center at x=0 and y=5
x = np.random.randn(100000)
y = np.random.randn(100000)+5

h = plt.hist2d(x, y, bins=40, norm=LogNorm())
plt.colorbar(h[3])
show()

Answer 2

This should do it:

from matplotlib.colors import LogNorm
import matplotlib.pyplot as plt
from numpy.random import randn

#normal distribution center at x=0 and y=5
x = randn(100000)
y = randn(100000)+5

H, xedges, yedges, img = plt.hist2d(x, y, norm=LogNorm())
extent = [yedges[0], yedges[-1], xedges[0], xedges[-1]]
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
im = ax.imshow(H, cmap=plt.cm.jet, extent=extent, norm=LogNorm())
fig.colorbar(im, ax=ax)
plt.show()

Notice how colorbar is attached to "fig", not "sub_plot". There are some other examples of this here. Notice how you also need to generate a ScalarMappable with imshow, as explained in the API here.