47 lines
871 B
Python
47 lines
871 B
Python
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#!/usr/bin/env python3
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import numpy as np
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import matplotlib.pyplot as plt
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N = 1000
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X = np.random.rand(N)
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X_c = (X - 0.5)*10
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def quantif_uniforme(M,X,xmin=-1,xmax=1,d=0):
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"""
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réalise la quantification uniforme d'un vecteur sur M niveau
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"""
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delta = 2 * xmax/M # pas de quantification
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Q = np.zeros(len(X))
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for k in range(len(X)):
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q = (X[k]/ delta)
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if abs(q)<d: #seuil
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Q[k] = 0
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continue
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elif abs(q)<2*delta:
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if q <0:
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Q[k] =-1
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else:
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Q[k] = 1
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continue
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else:
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Q[k] = int(q)
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return Q,delta
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def reverse_quantif(Q,delta):
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return Q*delta
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Q,delta = quantif_uniforme(4,X_c)
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Q_2,delta = quantif_uniforme(4,X_c,d=0.5):
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print(len(Q),len(X_c))
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plt.figure()
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plt.grid()
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plt.plot(X_c,Q,'.')
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plt.plot(X_c,Q_2,'.')
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plt.show()
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