# coding = utf8


import matplotlib.pyplot as plt
import numpy as np
import scipy as sci

nb=200

xdata = np.linspace(0,25,nb) # [-1;1] échantilloné sur 50 valeurs
noise = np.array(np.random.uniform(-1,1,nb)) # 50 valeurs au hasard entre -2 et 2
errs = np.array(np.random.uniform(-1,1,nb))
ydata = 15*np.sin(xdata)*np.exp(-xdata/10)

fig,ax = plt.subplots()

ax.set_title('Mesure d\'une oscillation amortie')
ax.set_xlabel(' time [s]',loc='left')
ax.set_ylabel(r'$l_0=15.sin(t).e^{\frac{-t}{10}}$ [cm]')

ax.set_axisbelow(True)
ax.yaxis.grid(color='gray')

ax.plot(xdata, ydata+noise, marker='o', label='points d\'échantillonage')
ax.errorbar(xdata, ydata+noise, yerr=errs,fmt='none',ecolor='red',capsize=2)

ax.legend(loc='upper right')
ax.spines['bottom'].set_position(('data',0))
ax.spines['top'].set_color('none')
ax.spines['right'].set_color('none')
plt.show()