matplotlib contour plot with lognorm - colorbar levels

Question

I am trying to make a contour plot with defined levels and log norm. Below is an example:

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LogNorm
delta = 0.025

x = y = np.arange(0, 3.01, delta)
X, Y = np.meshgrid(x, y)
Z1 = plt.mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = plt.mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
Z = 10 * (Z1* Z2)

fig=plt.figure()
ax1 = fig.add_subplot(111)
lvls = np.logspace(-4,0,20)
CF = ax1.contourf(X,Y,Z,
         norm = LogNorm(),
         levels = lvls
        )
CS = ax1.contour(X,Y,Z,
         norm = LogNorm(),
         colors = 'k',
         levels = lvls
        )
cbar = plt.colorbar(CF, ticks=lvls, format='%.4f')
plt.show()

My questions is:
The levels should be written in the format: '1x10^-4', '1.6x10^-4', ... How do i do this, without specifying each level manually?

I am using python 2.7.3 with matplotlib 1.1.1 on Windows 7.

Answer 1

From here I found an approach that seems to fit your question:

from matplotlib.ticker import LogFormatter
l_f = LogFormatter(10, labelOnlyBase=False)
cbar = plt.colorbar(CF, ticks=lvls, format=l_f)

which will give:

note that the spacing between the ticks are indeed in log scale...