electricity_demand_model.py

  temperature_effect = tfp.sts.LinearRegression(
      design_matrix=tf.reshape(temperature - np.mean(temperature),
                               (-1, 1)), name='temperature_effect')
  hour_of_day_effect = tfp.sts.Seasonal(
      num_seasons=24,
      observed_time_series=demand,
      name='hour_of_day_effect')
  day_of_week_effect = tfp.sts.Seasonal(
      num_seasons=7,
      num_steps_per_season=24, 
      observed_time_series=demand,
      name='day_of_week_effect')
  residual_level = tfp.sts.Autoregressive(
      order=1,
      observed_time_series=demand, name='residual')
  model = tfp.sts.Sum([temperature_effect,
                       hour_of_day_effect,
                       day_of_week_effect,
                       residual_level],
                       observed_time_series=demand)