def test_cv_predictions(cv, est, avg, return_raw_predictions): preds = cross_val_predict(est, y, cv=cv, verbose=4, averaging=avg, return_raw_predictions=return_raw_predictions) assert isinstance(preds, np.ndarray) if return_raw_predictions: assert preds.shape[0] == len(y) assert preds.shape[1] == cv.horizon else: assert preds.ndim == 1
def test_cross_val_predict_error(): cv = SlidingWindowForecastCV(step=24, h=1) with pytest.raises(ValueError): cross_val_predict(ARIMA(order=(2, 1, 0), maxiter=3), y, cv=cv)
def test_cv_predictions(cv, est, avg): preds = cross_val_predict(est, y, cv=cv, verbose=4, averaging=avg) assert isinstance(preds, np.ndarray) assert preds.ndim == 1