I was wondering how it would be possible to plot the following graph with a yscale that is logarithmic, due to the massive difference between numbers in the 'sample' list.
ax.set_yscale('log') seems to just cause errors.
import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure(figsize=(8,8))
ax = fig.add_subplot(111,polar=True)
sample = np.random.uniform(low=0.5, high=13.3, size=(15,))
sample = [35.417256011315416, 0.028288543140028287, 1.3578500707213579, 3.3663366336633667, 0.8203677510608205, 35.445544554455445, 3.3946251768033946, 19.46251768033946, 0.7072135785007072]
N = len(sample)
theta = np.arange(0, 2*np.pi, 2*np.pi/N)
bars = ax.bar(theta, sample, width=0.4)
#ax.set_yscale('log')
ax.set_xticks(theta)
ax.set_xticklabels(range(1, len(theta)+1))
ax.yaxis.grid(True)
plt.show()
Just use ax.set_yscale('symlog', linthresh=0.01) or ax.set_rscale('symlog', linthresh=0.01) (is the same in a polar plot) instead of ax.set_yscale('log').
A day ago I uploaded a jupyter-notebook for more details at GitHub.
