Prepare a forecast object for scoring — prepare_forecast_for

This function performs the input preparation steps shared by all score() methods: it validates and cleans the forecast object (removing rows with missing values), determines the forecast unit, validates the metrics, and converts the forecast to a plain data.table.

The metrics are validated within this function so that the lazy default metrics = get_metrics(forecast) of the score() methods is forced before those methods rebind forecast to a plain data.table (there is no get_metrics.default(), so forcing the default after that rebind would fail). The default is thereby evaluated on the original forecast object passed to score(), i.e. before rows with missing values are removed. This makes no difference for the built-in get_metrics() methods, which do not inspect the data.

Usage

prepare_forecast_for_scoring(forecast, metrics)

Arguments

forecast: A forecast object (a validated data.table with predicted and observed values).
metrics: A named list of scoring functions. See score() for details.

Value

A list with three elements: forecast (the cleaned forecast as a plain data.table), metrics (the validated list of metrics) and forecast_unit (a character vector with the columns that define the unit of a single forecast).