Deterministic time series returns an assertion error?

Question

I am trying to see how the Transit of Venus could be predicted, I generated data by an algorithm where there's 11000+ rows of datetime objects representing each day and my frequency is set to 'D'. The data is all generated except for one true date in 2004 which is included at the end of the training data. I define each day by a binary variable whether a Transit occurred that year or not. There a few things I don't understand.

How do I include my target variable? Whether a transit occurred or not?

But my main problem is I get an AssertionError from trying to predict out of sample.

"deterministic.py", line 1299, in out_of_sample
    assert self._retain_cols is not None

AssertionError

My code:

from statsmodels.tsa.deterministic import DeterministicProcess as DP
from statsmodels.tsa.deterministic import CalendarFourier, DeterministicProcess
fourier = CalendarFourier(freq="M", order=12)
Fun = DP(DF.index,constant=True, order=1, 
         seasonal=True, fourier=0, additional_terms=[fourier], 
         drop=False)
FutureDF.set_index('date', inplace=True)
FutureDF = FutureDF.asfreq('D')
import traceback
try:
    print(Fun.out_of_sample(steps=2950, forecast_index=FutureDF.index))
except:
    traceback.print_stack()