import numpy as np
from pylab import *
f1=600
Ne=1000
fe=10000.
Te=1/fe
Ta=Te*Ne
C=np.array([1/Ne]+[2/Ne for k in range(Ne//2)]) # normalisation

def s(t):
    return 0.8 + np.sign(np.sin(2*np.pi*f1*t))

t_ech=np.linspace(0,Ta-Te,Ne)

s_ech=s(t_ech)

spec=abs(np.fft.rfft(s_ech)*C)
f=np.fft.rfftfreq(Ne,Te)


figure('temporel')
plot (t_ech,s_ech,'ro',linestyle='-')
#plot (t_ech,tr(t_ech),color='k',linestyle='-')
axis([0,3/f1,-2.5,2.5]);grid();

figure('fréquentiel')
plot(f,spec,-0.1,1.2)


show()