get_level_as_timeseries not creating correct time series for seasonal levels

I have a script that was computing incorrect values and traced the issue back to get_level_as_timeseries not creating correct time series for seasonal levels.

For example, given this seasonal level, it creates this time series. As you can see, the 15 Apr value is getting applied on 1 Apr rather than being interpolated to the time window provided.

Seasonal level
Date             Time      Storage
31-Dec-24       24:00	16,160.00
1-Apr-25         5:00	16,160.00
15-Apr-25        5:00   20,226.00
15-Oct-25        5:00	20,226.00
1-Nov-25	     5:00	16,160.00
30-Dec-25       24:00	16,160.00
31-Dec-25       24:00	16,160.00

Resulting Time Series
Date               Time     Storage
4/1/2026	08:00:00+00:00	16160
4/1/2026	08:30:00+00:00	16160
4/1/2026	09:00:00+00:00	16160
4/1/2026	09:30:00+00:00	16160
4/1/2026	10:00:00+00:00	16160
4/1/2026	10:30:00+00:00	17176.5
4/1/2026	11:00:00+00:00	18193
4/1/2026	11:30:00+00:00	19209.5
4/1/2026	12:00:00+00:00	20226

Start by locating get_level_as_timeseries and reproduce the seasonal-level example from the issue, focusing on how the requested time window is handled around 1 Apr and 15 Apr. Compare the generated values with the expected interpolation shown in the report, then add or update a regression test covering seasonal levels and confirm the resulting time series uses the correct dates.