def number_of_values_to_forecast_test(self):
        data = [[1.5, 152.0],[2.5, 172.8],[3.5, 195.07200000000003],[4.5, 218.30528000000004]]
        ts   = TimeSeries.from_twodim_list(data)
        ts.normalize("second")

        bfm  = BaseForecastingMethod()

        bfm.forecast_until(100)
        bfm._calculate_values_to_forecast(ts)

        assert bfm.get_parameter("valuesToForecast") == 96
Test the valid calculation of values to forecast.
dataset/ETHPy150Open T-002/pycast/pycast/tests/methodtest.py/BaseForecastingMethodTest.number_of_values_to_forecast_test