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@Nick3523
Last active April 28, 2020 10:49
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#!/usr/bin/env python
# coding: utf-8
get_ipython().run_line_magic('matplotlib', 'inline')
import numpy as np
import matplotlib.pyplot as plt
from math import sqrt, pi, exp
import pylab
domaine = range(-100,100)
mu = 0
sigma = 20 #sigma != 1, donc ce n'est pas un loi normal centrée réduite !
#f est la fonction de répartition de la loi normale.
f = lambda x : 1/(sqrt(2*pi*pow(sigma,2))) * exp(-pow((x-mu),2)/(2*pow(sigma,2)))
y = [f(x) for x in domaine]
plt.title("Courbe en cloche de la loi normale")
plt.plot(domaine, y)
plt.savefig("Loi-Normale.png",dpi=144)
matrice_aleatoire = np.random.rand(10000,10000) #génération d'un échantillion sur une matrice 10000x10000 suivant une loi uniforme
sommes = np.sum(matrice_aleatoire,0) #On somme les colonnes
plt.hist(sommes, bins=100)
plt.title("Simulation de la loi normale")
plt.savefig("Simulation-Loi-Normale.png",dpi=144)
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