def plot_some_zipf(f_counts, N, dom):
plt.loglog(range(1,N+1), f_counts, 'r+')
lgnd = ['play frequencies']+['s='+str(s) for s in dom]
for s in dom:
t = su.zipf_t(s, N)
zipf_vals = [su.zipf(k,s,t) for k in range(1,N+1)]
plt.loglog(range(1,N+1), zipf_vals)
plt.xlim([0.0, float(N)])
plt.xlabel('rank k')
plt.ylabel('frequency f')
plt.legend(lgnd,'upper right')
def plot_fit_zipf(f_counts, N, dom):
res = opt.minimize(su.kl_optimize, [0], args=([f_counts]))
kls = []
for s in dom:
t = su.zipf_t(s, N)
zipf_vals = [su.zipf(k,s,t) for k in range(1,N+1)]
kls.append(float(su.kl_divergence(f_counts, zipf_vals)))
plt.plot(dom, kls)
plt.xlabel('s')
#plt.annotate('global min at ~'+str(0.48) , xy=(res.x, res.fun), xytext=(res.x+res.x/30.0, res.fun+7*res.fun),
# arrowprops=dict(facecolor='black', shrink=0.05),
# )
plt.legend(['KL divergence'], 'upper right')
plt.xlim([dom[0], dom[-1]])
plt.show()