plt.plot(min_season) D, Y = temp.create_dataset(data, "ven") Y = np.array(Y) acf, Q, P, = statsmodels.tsa.stattools.acf(Y, nlags=48, qstat=True) statsmodels.graphics.tsaplots.plot_acf(Y, lags=1000) per = statsmodels.tsa.stattools.periodogram(Y) plt.plot(per) 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
plt.plot(min_season) D,Y = temp.create_dataset(data, "ven") Y = np.array(Y) acf, Q, P, = statsmodels.tsa.stattools.acf(Y, nlags = 48, qstat = True) statsmodels.graphics.tsaplots.plot_acf(Y, lags=1000) per = statsmodels.tsa.stattools.periodogram(Y) plt.plot(per) 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