Evaluer Pi avec Monte Carlo (python)

Exemple d'algorithme pour évaluer pi en utilisant la méthode de Monte Carlo:

from random import uniform

import numpy as np
import matplotlib.pyplot as plt

Radius = 1.0
Nb_Data = 10000

x_list = []
y_list = []
test = []
Nb_Data_In = 0
for i in range(Nb_Data):
    x = uniform(-Radius,Radius)
    y = uniform(-Radius,Radius)
    x_list.append(x)
    y_list.append(y)
    if x**2+y**2 > Radius**2:
        test.append(0)
    else:
        test.append(1)  
        Nb_Data_In = Nb_Data_In + 1

pi = 4.0 * Nb_Data_In / Nb_Data
print 'pi: ', pi

color1=(0.69411766529083252, 0.3490196168422699, 0.15686275064945221, 1.0)
color2=(0.65098041296005249, 0.80784314870834351, 0.89019608497619629, 1.0)

colormap = np.array([color1,color2])

plt.scatter(x_list,y_list,c=colormap[test])
plt.savefig("MonteCarloPi.png")
plt.show()

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