def test_predict_pred(reg_dataset):
x_train = reg_dataset[0]
y_train = reg_dataset[1]
x_cal = reg_dataset[2]
y_cal = reg_dataset[3]
x_test = reg_dataset[4]
adapt_model = Adapt_to_CP(RandomForestRegressor(n_estimators=10), True)
adapt_model.fit(x_train, y_train)
adapt_model.calibrate(x_cal, y_cal)
pred = adapt_model.predict(x_test, 0.8)
assert type(pred[1]) == np.ndarray
def test_calibrate(reg_dataset):
x_train = reg_dataset[0]
y_train = reg_dataset[1]
x_cal = reg_dataset[2]
y_cal = reg_dataset[3]
adapt_model = Adapt_to_CP(RandomForestRegressor(n_estimators=10), True)
adapt_model.fit(x_train, y_train)
assert adapt_model.calibrate(x_cal, y_cal) == None