Replace or supplement the history_duration and forecast_duration parameters with interval_start and interval_end
Detailed Description
In writing some pipelines for PVNet which include dropout and assuming data latency, I've come across some use cases which are made slightly unclear by the current parameters.
Examples
In production we can expect a delay of at least 15 minutes in satellite data, so I'd like to build a pipeline with satellite data which is between 60 and 15 minutes before t0.
Currently this can be done by setting
history_duration=timedelta(minutes=30)
forecast_duration=timedelta(minutes=-15).
The alternative could be
interval_start=timedelta(minutes=-60)
interval_end=timedelta(minutes-15)
For the dropout pipelines, I'd like to slice the data into future and historical sections so that I can apply dropout on the historical section as inputs but keep the future data clean. I want to select the future GSP data from one step ahead of t0 (i.e. 30 minutes) until 180 minutes into the future.
Currently this can be done with
history_duration=timedelta(minutes=-30)
forecast_duration=timedelta(minutes=180)
The alternative could be
interval_start=timedelta(minutes=30)
interval_end=timedelta(minutes=180)
Possible Implementation
Either replace the parameters history_duration and forecast_duration parameters with interval_start and interval_end, or add interval_start and interval_end as optional parameters and allow either *_duration or interval_* to be set.
Replace or supplement the
history_duration
andforecast_duration
parameters withinterval_start
andinterval_end
Detailed Description
In writing some pipelines for
PVNet
which include dropout and assuming data latency, I've come across some use cases which are made slightly unclear by the current parameters.Examples
In production we can expect a delay of at least 15 minutes in satellite data, so I'd like to build a pipeline with satellite data which is between 60 and 15 minutes before t0.
history_duration=timedelta(minutes=30)
forecast_duration=timedelta(minutes=-15)
.interval_start=timedelta(minutes=-60)
interval_end=timedelta(minutes-15)
For the dropout pipelines, I'd like to slice the data into future and historical sections so that I can apply dropout on the historical section as inputs but keep the future data clean. I want to select the future GSP data from one step ahead of t0 (i.e. 30 minutes) until 180 minutes into the future.
history_duration=timedelta(minutes=-30)
forecast_duration=timedelta(minutes=180)
interval_start=timedelta(minutes=30)
interval_end=timedelta(minutes=180)
Possible Implementation
Either replace the parameters
history_duration
andforecast_duration
parameters withinterval_start
andinterval_end
, or addinterval_start
andinterval_end
as optional parameters and allow either*_duration
orinterval_*
to be set.