import numpy as np
import matplotlib.pyplot as plt


l = 1
P = []
C = []

X = np.arange(0, 10, 0.1)
for i in X:
    P.append(l*np.exp(-l*i))
for i in X:
    C.append(1-np.exp(-l*i))

plt.figure('Probability Distribution')
plt.plot(X, P)
x_axis = range(10)
y_axis = np.arange(0, 1.1, 0.1)
plt.xticks(x_axis)
plt.yticks(y_axis)
plt.xlabel('x')
plt.ylabel('Pr[X=x]')
plt.title('Exponential PDF with λ=%.2f' %l)

if(1):
    plt.figure('Cumulative Distribution')
    plt.plot(X, C)
    x_axis = range(10)
    y_axis = np.arange(0, 1.1, 0.1)
    plt.xticks(x_axis)
    plt.yticks(y_axis)
    plt.xlabel('x')
    plt.ylabel('Pr[X<=x]')
    plt.title('Exponential CDF with λ=%.2f' %l)

plt.grid()
plt.show()