import matplotlib.pyplot as plt #Plot tool
import scipy as sp #For numeric arrays
import numpy.random as rd
import numpy as np

probs=sp.array([0.5,0.1,0.2,0.2]) #Probs de cada evento
N=10000
nbins=100

#Para p(x)=l*exp(-l*x)
#comulativa=1-exp(-l*x)
#inversa, x=-1/l*log(1-y)
#Gerar random sample y
y=rd.random_sample(N)
#Calcular inversa
l=20
x=-1/l*np.log(1-y)

plt.hist(x, nbins, normed=1)
plt.show()