S_per = pd.Series(per) S_per.describe() peaks = Functions_for_TSP.find_peaks(per, 10) FE = Functions_for_TSP.fourierExtrapolation(Y, n_predict=24) fitted_FE = FE[0:8736] diff = Y - fitted_FE np.mean(diff) np.var(diff) #RMSE = np.sqrt(np.mean(diff**2)) sp_y = Functions_for_TSP.Signum_Process(Y) sp_f = Functions_for_TSP.Signum_Process(fitted_FE) sp_p = sp_y * sp_f perc_err_andamento = sp_p[sp_p <= 0].size / sp_p.size aic = statsmodels.tsa.stattools.arma_order_select_ic(Y, ic='aic') #D2 = D.convert_objects(convert_numeric=True) D3 = D[D.columns[0:215]].convert_objects(convert_numeric=True) #Dnp = float(D.as_matrix(columns=D.columns[0:215])) ardata = pd.DataFrame(data[data.columns[[2, 3, 7, 10, 11, 18, 20]]]) ardata = ardata.convert_objects(convert_numeric=True) ardata = ardata.set_index(prova)
