Set unit of a single forecast manually

Helper function to set the unit of a single forecast (i.e. the combination of columns that uniquely define a single forecast) manually. This simple function keeps the columns specified in forecast_unit (plus additional protected columns, e.g. for observed values, predictions or quantile levels) and removes duplicate rows. set_forecast_unit() will mainly be called when constructing a forecast object via the forecast_unit argument in as_forecast_<type>.

If not done explicitly, scoringutils attempts to determine the unit of a single forecast automatically by simply assuming that all column names are relevant to determine the forecast unit. This may lead to unexpected behaviour, so setting the forecast unit explicitly can help make the code easier to debug and easier to read.

Usage

set_forecast_unit(data, forecast_unit)

Arguments

data

A data.frame (or similar) with predicted and observed values. See the details section of for additional information on the required input format.

forecast_unit

Character vector with the names of the columns that uniquely identify a single forecast.

Value

A data.table with only those columns kept that are relevant to scoring or denote the unit of a single forecast as specified by the user.

Examples

library(magrittr) # pipe operator
example_quantile %>%
  scoringutils:::set_forecast_unit(
    c("location", "target_end_date", "target_type", "horizon", "model")
  )
#> Forecast type: quantile
#> Forecast unit:
#> location, target_end_date, target_type, horizon, and model
#> 
#> Key: <location, target_end_date, target_type>
#>        observed quantile_level predicted location target_end_date target_type
#>           <num>          <num>     <int>   <char>          <Date>      <char>
#>     1:   127300             NA        NA       DE      2021-01-02       Cases
#>     2:     4534             NA        NA       DE      2021-01-02      Deaths
#>     3:   154922             NA        NA       DE      2021-01-09       Cases
#>     4:     6117             NA        NA       DE      2021-01-09      Deaths
#>     5:   110183             NA        NA       DE      2021-01-16       Cases
#>    ---                                                                       
#> 20541:       78          0.850       352       IT      2021-07-24      Deaths
#> 20542:       78          0.900       397       IT      2021-07-24      Deaths
#> 20543:       78          0.950       499       IT      2021-07-24      Deaths
#> 20544:       78          0.975       611       IT      2021-07-24      Deaths
#> 20545:       78          0.990       719       IT      2021-07-24      Deaths
#>        horizon                model
#>          <num>               <char>
#>     1:      NA                 <NA>
#>     2:      NA                 <NA>
#>     3:      NA                 <NA>
#>     4:      NA                 <NA>
#>     5:      NA                 <NA>
#>    ---                             
#> 20541:       2 epiforecasts-EpiNow2
#> 20542:       2 epiforecasts-EpiNow2
#> 20543:       2 epiforecasts-EpiNow2
#> 20544:       2 epiforecasts-EpiNow2
#> 20545:       2 epiforecasts-EpiNow2