seasonal_arima_model.py

def seasonal_arima_model(time_series, order, seasonal_order, trend):
    """
    Generate a seasonal ARIMA model using a set of hyperparameters. Returns the model fit, and the 
    associated model AIC and BIC values.
    """ 
    try:
        model = sm_api.tsa.SARIMAX(time_series, 
                                   order=order, 
                                   seasonal_order=seasonal_order, 
                                   trend = trend,
                                   enforce_stationarity=False, 
                                   enforce_invertibility=False)
        model_fit = model.fit()
        #Print the model results
        print(model_fit.summary())
        return model_fit, model_fit.aic, model_fit.bic
    except:
        print("Could not fit with the designated model parameters")
        return None, None, None

### EXECUTE IN MAIN FUNCTION ###
lowest_aic_val = 100000000000
#Generate  model for each of hyperparameter combination in a loop
for order_combo in order_combos:
    for seasonal_order_combo in seasonal_order_combos:
        #Convert the combination to list format
        seasonal_order_combo = list(seasonal_order_combo)
        #Generate the SARIMA model
        model_fit, model_aic, model_bic = seasonal_arima_model(time_series = training_set, 
                                                    order = order_combo, 
                                                    seasonal_order = seasonal_order_combo[0:4],
                                                    trend = seasonal_order_combo[-1])
        #Test model performance, and keep running tab of best performing model
        #Set with the newest value if the lowest_aic_value hasn't yet been calculated (on first run),
        #or if the newly calculated model AIC is lower than the lowest calculated AIC value
        if (model_aic < lowest_aic_val):
            lowest_aic_val = model_aic
            best_model = model_fit
            best_order = order_combo
            best_seasonal_order = seasonal_order_combo
#Print the best model parameters after the 
print("Best model paramaters: order-- ", best_order, ", seasonal order-- ", best_seasonal_order)