training data time_idx should be end-align

[workhours]

when I try a dataset with time series like:
ts1: year from 2001 to 2020 => time_idx=[0,19]
ts2: year from 2010 to 2020 => time_idx=[10,19]
with:
min_prediction_idx=6
min_prediction_length=5
ts2 will be removed from training data since 5+6>len(ts2)
actually ts2 can be used for training e.g. time_idx[10:15] as input and time_idx[15:20] as target, and this case prediction_idx is 15>6
I don't know current implementation is wanting time_idx should be start-align, so:
ts1=> time_idx=[0,19]
ts2=> time_idx=[0,9]
if this is the case, ts2 will expose future information to training model
so at least TimeSeriesDataSet need a configuration time_idx is start align or end align.
most cases time series prediction is handling latest n years prediction, the age of some group of data always less than n

[workhours]

and if the software support only start-align, then min_prediction_idx will filter most of training data which length less than max of the time series lengths

[fkiraly]

could you post a full piece of code with all imports, and explain:

• what happens
• what you think should happen (e.g., "output should be ...")

[kentstone84]

Add a time_idx_alignment parameter to TimeSeriesDataSet, supporting:

"start" (default, current behavior)

"end" (align prediction window to the end of each series)

"sliding" (allow prediction windows anywhere they fit — most flexible)

This would allow valid windows from shorter time series to contribute to training without leaking future information.