>>> ax.set_xticklabels(ticks)  # doctest: +SKIP
>>> plt.show()

This random variable will be log-uniform regardless of the base chosen for
``a`` and ``b``. Let's specify with base ``2`` instead:

>>> rvs = %(name)s(2**-2, 2**0).rvs(size=1000)

Values of ``1/4``, ``1/2`` and ``1`` are equally likely with this random
variable.  Here's the histogram:

>>> fig, ax = plt.subplots(1, 1)
>>> ax.hist(np.log2(rvs))
>>> ax.set_ylabel("Frequency")
>>> ax.set_xlabel("Value of random variable")
>>> ax.xaxis.set_major_locator(plt.FixedLocator([-2, -1, 0]))
>>> ticks = ["$2^{{ {} }}$".format(i) for i in [-2, -1, 0]]
>>> ax.set_xticklabels(ticks)  # doctest: +SKIP
>>> plt.show()

c