river_flow_eval_model.py

from darts.metrics import rmse

# We first set aside the first 80% as training series:
flow_train, _ = flow.split_before(0.8)

def eval_model(model, past_covariates=None, future_covariates=None):
    # Past and future covariates are optional because they won't always be used in our tests
    
    # We backtest the model on the last 20% of the flow series, with a horizon of 10 steps:
    backtest = model.historical_forecasts(series=flow, 
                                          past_covariates=past_covariates,
                                          future_covariates=future_covariates,
                                          start=0.8, 
                                          retrain=False,
                                          verbose=True, 
                                          forecast_horizon=10)
    
    flow[-len(backtest)-100:].plot()
    backtest.plot(label='backtest (n=10)')
    print('Backtest RMSE = {}'.format(rmse(flow, backtest)))