Rework add coverage to work with raw forecasts#426
Rework add coverage to work with raw forecasts#426nikosbosse merged 8 commits intoadd-coverage-deviationfrom
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…ame of the coverage columns
…eviously failing due to `add_coverage()`
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nikosbosse
changed the title
| data[, quantile_coverage_deviation := quantile_coverage - quantile] | ||
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| # reset column order | ||
| new_metrics <- c("interval_coverage", "interval_coverage_deviation", |
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can you use the metrices functions vs duplicating here to make the code cleaner?
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At the moment not really - the thing is that the metrics functions do a many-to-one mapping (i.e. you get one coverage value per forecast (which comprises several quantiles)), whereas this is one-to-one, i.e. one value per quantile / interval.
We need to think again about how to handle one-to-one functions that exist currently and what to do with them: #451
| example_quantile %>% | ||
| set_forecast_unit(c("location", "target_end_date", "target_type", "horizon", "model")) %>% | ||
| validate() %>% | ||
| add_coverage() %>% |
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if its in the default metrics list what does this actually do? Is it going to be clear to users why it isn't part of score?
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Updating the readme is on the list: #439
seabbs
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Linting issues otherwise fine.
Its not clear to me what the workflow is with add_coverage vs the coverage metrics in score or how that is going to be communicated to the user.
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Linting issues otherwise fine.
Its not clear to me what the workflow is with add_coverage vs the coverage metrics in score or how that is going to be communicated to the user.
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This function updates the
add_coverage()function yet again. This timeadd_coverage()now adds rowwise coverage values for interval coverage and quantile coverage