def second_forecasting_test(self):
       data  = [[0.0, 152], [1, 176], [2, 160], [3, 192], [4, 220]]
       tsSrc = TimeSeries.from_twodim_list(data)
       tsSrc.normalize("second")

       hm  = HoltMethod(0.2, 0.3, 5)
       res = tsSrc.apply(hm)

       # test if the correct number of values have been forecasted
       assert len(tsSrc) + 4 == len(res)

       # Validate the first forecasted value
       assert str(res[4][1])[:8] == "241.2419"
Test forecast part of HoltSmoothing.
dataset/ETHPy150Open T-002/pycast/pycast/tests/methodtest.py/HoltMethodTest.second_forecasting_test