optimize

optimize.py

    print('>>> Logistic Model')
    fit_i = curve_fit(logistic_model,x,y,p0=[3,20,5000], maxfev=10000)#, bounds=([0,0,0],[10,100,150000]))
    ai,bi,ci = fit_i[0]
    sigma_ai, sigma_bi, sigma_ci = np.sqrt(np.diag(fit_i[1]))

    c_pars[(country,'Logistic','a')] = ai
    c_pars[(country,'Logistic','b')] = bi
    c_pars[(country,'Logistic','c')] = ci
    c_pars[(country,'Logistic','sga')] = sigma_ai
    c_pars[(country,'Logistic','sgb')] = sigma_bi
    c_pars[(country,'Logistic','sgc')] = sigma_ci
    print([ss+'='+'{:.3f}'.format(xx) for ss, xx in zip(('a','b','c'),
                                                        (ai,bi,ci))])
    print([ss+'='+'{:.3f}'.format(xx) for ss, xx in zip(('sigma_a','sigma_b','sigma_c'),
                                                        (sigma_ai,sigma_bi,sigma_ci))])