"""
Created on Sun Aug 01 19:20:16 2010

Author: josef-pktd
"""


import numpy as np
from scipy import stats
import matplotlib.pyplot as plt

nobs = 1000
r = stats.pareto.rvs(1, size=nobs)

#rhisto = np.histogram(r, bins=20)
rhisto, e = np.histogram(np.clip(r, 0 , 1000), bins=50)
plt.figure()
plt.loglog(e[:-1]+np.diff(e)/2, rhisto, '-o')
plt.figure()
plt.loglog(e[:-1]+np.diff(e)/2, nobs-rhisto.cumsum(), '-o')
##plt.figure()
##plt.plot(e[:-1]+np.diff(e)/2, rhisto.cumsum(), '-o')
##plt.figure()
##plt.semilogx(e[:-1]+np.diff(e)/2, nobs-rhisto.cumsum(), '-o')

rsind = np.argsort(r)
rs = r[rsind]
rsf = nobs-rsind.argsort()
plt.figure()
plt.loglog(rs, nobs-np.arange(nobs), '-o')
print(stats.linregress(np.log(rs), np.log(nobs-np.arange(nobs))))

plt.show()
