tbats_multi_seasonal_time_series_forecast_quickstart.py

1import numpy as np
2from tbats import TBATS
3
4# Create some toy data with multiple seasonalities
5# (e.g., daily and weekly patterns)
6period_7 = 7
7period_365 = 365.25
8t = np.arange(1000)
9y = (5 * np.sin(t * 2 * np.pi / period_7) +
10     2 * np.sin(t * 2 * np.pi / period_365) +
11     np.random.normal(size=1000))
12
13# Fit the model
14estimator = TBATS(seasonal_periods=[7, 365.25])
15model = estimator.fit(y)
16
17# Forecast for 14 steps ahead
18y_forecast = model.forecast(steps=14)
19
20print(y_forecast)