#!/usr/bin/env python3
# plotting a few distribution functions

import math                      # math
import matplotlib.pyplot as plt  # plotting

max_X   = 5.0
nPoints = 100

xData   = [ii*max_X/nPoints for ii in range(nPoints)]

yNormal = [math.exp(-0.5*xx*xx) for xx in xData]
yExp    = [math.exp(-xx)        for xx in xData]
yTsalis = [1.0/(1.0+xx)**2      for xx in xData]

plt.plot(xData, yNormal, "ob", markersize=4, label="normal")
plt.plot(xData, yExp,    "og", markersize=4, label="exponential")
plt.plot(xData, yTsalis, "or", markersize=4, label="Tsalis-Pareto")
#
plt.xlim(0, max_X)
plt.ylim(0, 1.05)                 # axis limits
plt.legend(loc="upper right")     # legend location
plt.savefig('foo.svg')            # export figure
plt.show()