def test_datetime_attribute_timeseries_indexing_shift(self, config):
        """Check that the original indexing of the attribute is properly shifted to obtain 0-indexing when
        the start timestamp of the index is the first possible value of the attribute

        Note: 2001 is neither leap year nor a year with 53 weeks
        """
        (
            base_freq,
            attribute_freq,
            period,
        ) = config
        start_timestamp = "2001-01-01 00:00:00"

        idx = generate_index(
            start=pd.Timestamp(start_timestamp), length=1, freq=base_freq
        )

        # default encoding should be 0
        vals_exp = np.zeros((1, 1))
        self.helper_routine(
            idx, attribute_freq, vals_exp=vals_exp, one_hot=False, cyclic=False
        )

        # one-hot encoding must be 1 in the first column
        vals_exp = np.zeros((1, period))
        vals_exp[0, 0] = 1
        self.helper_routine(idx, attribute_freq, vals_exp=vals_exp, one_hot=True)

        # cyclic encoding must start at t=0
        vals_exp = np.array([[np.sin(0), np.cos(0)]])
        self.helper_routine(idx, attribute_freq, vals_exp=vals_exp, cyclic=True)
Check that the original indexing of the attribute is properly shifted to obtain 0-indexing when
        the start timestamp of the index is the first possible value of the attribute

        Note: 2001 is neither leap year nor a year with 53 weeks
        
darts/tests/utils/test_timeseries_generation.py