@Laure

#1 import numpy as np import numpy.random as rd #2 def unlancer(p): x = rd.random() if x <= p: return(1) else:

import numpy as np def f(x): return(np.sin(2*x)) def integrale(a, b, n): S = 0 for i in range (1, n+1): S = S + f(a+i*((b-a)/n)) I =((b-a)/n)*S

import numpy as np import matplotlib.pyplot as plt x = np.linspace (-2,2,100) print(x) y = np.exp(x) g = x+1 s = for k in range (1,n+1):

import numpy.random as rd import numpy as np # Q1 f=np.zeros(100000) for k in range (0,10000): n = rd.poisson(40) x = rd.binomial (n,1/10) f[k] = x print(f)

import numpy as np import numpy.random as rd import matplotlib.pyplot as plt X = rd.geometric(0.4,10000) f = np.zeros(11) for k in range(1,11): f[k-1] = np.mean(X == k) print(f)

import numpy as np import numpy.random as rd import matplotlib.pyplot as plt X = rd.binomial(10, 0.4, 10000) f = np.zeros(11) for k in range (0,11): f[k] = np.mean(X == k) print(f)

import numpy as np import matplotlib.pyplot as plt x = np.linspace(0, 10, 20, 30) print (x) y = np.sin(x) plt.plot(x, y, c="blue", ls="--", lw=1, alpha=0.5) plt.scatter(x, y, c="red", marker="+") plt.show()

import numpy.random as rd def EML(n): b = 1 r = 2 s = 0 for k in range (1,n+1): x = rd.randint(1,b+r+1) if x > b: s = s+1

import numpy as np a = 1 b = 2 c = 3 d = 4 e = 5 f = 6 g = 7 h = 8 i = 9

import numpy as np def f(x): return(4*x-np.exp(x)) def f_prime(x): return(4-np.exp(x)) def phi(x): return(x-(f(x)/f_prime(x))) n = 2 x = 0 eps = 10**-3

def f(t): return(1+t**2) def integrale(a, b, n): S = 0 for i in range (1, n+1): S = S + f(a+i*((b-a)/n)) I =((b-a)/n)*S return (I) print (integrale (0, 1, 10000))

import numpy.random as rd def Y(n,p): X = rd.binomial(n,p) if X == 0 or X ==n : y = rd.randint(1,n) else : y = X return (y) N = 10000

import numpy as np v = 1 w = np.exp (-1) while abs(v-w) >= 10**-6 : v = np.exp (-w) w = np.exp (-v) print (w)

import numpy as np A = np.array([[1,1],[3,4]]) B = np.array([[5,1],[0,-2]]) C = np.dot(A,B) D = np.dot(B,A) if np.all(C==D): print ("true") else : print ("false")

import numpy as np import numpy.random as rd A = np.zeros ((1,10000)) print(A) def une_simul () : de = rd.randint(1,7) piece = rd.randint(0,2) if piece == 0 or de == 1 : gain = 1 elif (piece == 1 and de == 5) or (piece == 1 and de == 6) :

import numpy as np def f(x): return np.log(x)+2-x a = 0.001 b = 1 while abs(b-a)>=0.001 : c = (a+b)/2 if f(c)<0 : a = c

def f (x): return (x**2-5) a = 0 b = 3 while abs(b-a)>=10**-6 : c = (a+b)/2 if f(c)<0 : a = c else :

import numpy as np def inverse_2_2(A): a = A[0][0] b = A[0][1] c = A[1][0] d = A[1][1] det = a*d - b*c if det == 0: return (False) else:

import numpy as np A = np.array([[0,0], [0,0]]) print(A) print(A[0][0]) print(A[0][0]) print(np.shape(A)) #Q2: I = np.eye(2) print(I)

import numpy.random as rd N = int(input("combien d'expérience voulez-vous simuler ?")) nb_09 = 0 nb_10 = 0 nb_11 = 0 nb_12 = 0 for k in range (1,N+1): de1 = rd.randint(1,7) de2 = rd.randint(1,7)