When running unit tests, there are a lot of warnings coming from tests for scoring. Here's an example:
── Warning (test-score_forecasts.R:3323:3): interval coverage is correct, 2 intervals, median and point, use_median_as_point FALSE ──
The following warnings were produced when checking inputs:
1. Some forecasts have different numbers of rows (e.g. quantiles or samples). scoringutils found: 1, 5. This is not necessarily a problem, but make sure this is intended.
Backtrace:
1. covidHubUtils::score_forecasts(...)
at test-score_forecasts.R:3323:2
13. scoringutils::score(data = joint_df_target)
14. scoringutils::check_forecasts(data)
If these warnings are intended, we should check for that with expect_warning. If these warnings are not intended/necessary, we should update test cases to avoid them.
When running unit tests, there are a lot of warnings coming from tests for scoring. Here's an example:
If these warnings are intended, we should check for that with
expect_warning. If these warnings are not intended/necessary, we should update test cases to avoid them.