solarforecastarbiter.reference_forecasts.main

Make benchmark irradiance and power forecasts.

The functions in this module use the solarforecastarbiter.datamodel objects.

Functions

all_equal(iterable)	Returns True if all the elements are equal to each other
fill_nwp_forecast_gaps(token, start, end[, …])	Make all reference NWP forecasts that are missing from start to end.
fill_persistence_forecasts_gaps(token, …)	Make all reference persistence forecasts that need to be made between start and end.
fill_probabilistic_persistence_forecasts_gaps(…)	Make all reference probabilistic persistence forecasts that need to be made between start and end.
find_reference_nwp_forecasts(forecasts[, …])	Sort through all forecasts to find those that should be generated by the Arbiter from NWP models.
generate_reference_persistence_forecast_gaps_parameters(…)	Sort through all forecasts to find those with gaps in the data that should be generated by the Arbiter from persisting Observation values.
generate_reference_persistence_forecast_parameters(…)	Sort through all forecasts to find those that should be generated by the Arbiter from persisting Observation values.
make_latest_nwp_forecasts(token, run_time, …)	Make all reference NWP forecasts for run_time that are within issue_buffer of the next issue time for the forecast.
make_latest_persistence_forecasts(token, …)	Make all reference persistence forecasts that need to be made up to max_run_time.
make_latest_probabilistic_persistence_forecasts(…)	Make all reference probabilistic persistence forecasts that need to be made up to max_run_time.
process_nwp_forecast_groups(session, …)	Groups NWP forecasts based on piggyback_on, calculates the forecast as appropriate for run_time, and uploads the values to the API.
run_nwp(forecast, model, run_time, issue_time)	Calculate benchmark irradiance and power forecasts for a Forecast or ProbabilisticForecast.
run_persistence(session, observation, …[, …])	Run a persistence forecast for an observation.