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Helper function that prints the output generated by check_forecasts()

Usage

# S3 method for scoringutils_check
print(x, ...)

Arguments

x

An object of class 'scoringutils_check' as produced by check_forecasts()

...

additional arguments (not used here)

Examples

check <- check_forecasts(example_quantile)
#> The following messages were produced when checking inputs:
#> 1.  144 values for `prediction` are NA in the data provided and the corresponding rows were removed. This may indicate a problem if unexpected.
print(check)
#> Your forecasts seem to be for a target of the following type:
#> $target_type
#> [1] "integer"
#> 
#> and in the following format:
#> $prediction_type
#> [1] "quantile"
#> 
#> The unit of a single forecast is defined by:
#> $forecast_unit
#> [1] "location"        "target_end_date" "target_type"     "location_name"  
#> [5] "forecast_date"   "model"           "horizon"        
#> 
#> Cleaned data, rows with NA values in prediction or true_value removed:
#> $cleaned_data
#>        location target_end_date target_type true_value location_name
#>     1:       DE      2021-05-08       Cases     106987       Germany
#>     2:       DE      2021-05-08       Cases     106987       Germany
#>     3:       DE      2021-05-08       Cases     106987       Germany
#>     4:       DE      2021-05-08       Cases     106987       Germany
#>     5:       DE      2021-05-08       Cases     106987       Germany
#>    ---                                                              
#> 20397:       IT      2021-07-24      Deaths         78         Italy
#> 20398:       IT      2021-07-24      Deaths         78         Italy
#> 20399:       IT      2021-07-24      Deaths         78         Italy
#> 20400:       IT      2021-07-24      Deaths         78         Italy
#> 20401:       IT      2021-07-24      Deaths         78         Italy
#>        forecast_date quantile prediction                 model horizon
#>     1:    2021-05-03    0.010      82466 EuroCOVIDhub-ensemble       1
#>     2:    2021-05-03    0.025      86669 EuroCOVIDhub-ensemble       1
#>     3:    2021-05-03    0.050      90285 EuroCOVIDhub-ensemble       1
#>     4:    2021-05-03    0.100      95341 EuroCOVIDhub-ensemble       1
#>     5:    2021-05-03    0.150      99171 EuroCOVIDhub-ensemble       1
#>    ---                                                                
#> 20397:    2021-07-12    0.850        352  epiforecasts-EpiNow2       2
#> 20398:    2021-07-12    0.900        397  epiforecasts-EpiNow2       2
#> 20399:    2021-07-12    0.950        499  epiforecasts-EpiNow2       2
#> 20400:    2021-07-12    0.975        611  epiforecasts-EpiNow2       2
#> 20401:    2021-07-12    0.990        719  epiforecasts-EpiNow2       2
#> 
#> Number of unique values per column per model:
#> $unique_values
#>                    model location target_end_date target_type true_value
#> 1: EuroCOVIDhub-ensemble        4              12           2         96
#> 2: EuroCOVIDhub-baseline        4              12           2         96
#> 3:  epiforecasts-EpiNow2        4              12           2         95
#> 4:       UMass-MechBayes        4              12           1         48
#>    location_name forecast_date quantile prediction horizon
#> 1:             4            11       23       3969       3
#> 2:             4            11       23       3733       3
#> 3:             4            11       23       3903       3
#> 4:             4            11       23       1058       3
#> 
#> $messages
#> [1] "144 values for `prediction` are NA in the data provided and the corresponding rows were removed. This may indicate a problem if unexpected."
#>