phython test we should complete the code after txt=...

import numpy as np from random import gauss import matplotlib.pyplot as plt alpha, tau =2.0,1.0 modele = lambda t: alpha*np.exp(-t/tau) sigma_t =0.1 Npoints =20 tk=np.linspace(0.0,5.0, Npoints ) zk= modele (tk) \# modele(t) for t in tk] zk=[zk[k]+ gauss (0.0,sigma_t) for k in range(Npoints) ] sigma_zk = [ sigma_t ]*Npoints from scipy.optimize import curve_fit guess =[1.0,1.0] fitfunc = lambda x,a,b:anpexp((x)/b) p, pcov = curve_fit(fitfunc, tk, zk, pe = guess, sigma=sigma_zk) sigma_p =np. sqrt (np.diag(pcov)) plt. errorbar (tk, zk, yerr=sigma_zk, fmit=' 0 ', color=' b ', capthick=2, capsize=6) plt. plot (tk, modele(tk), ' k ') plt.plot(tk, fitfunc(tk, p[0],p[1]),r) plt.title(txt) plt.xlabel("\$t\$"); plt.ylabel("\$z\$") plt.show()