hubhelpr is an in-progress R package for maintaining the CDC/CFA respiratory virus forecast hubs: covid19-forecast-hub and rsv-forecast-hub.
It provides functions for:
- Target Data: pulling NHSN hospital admissions and NSSP emergency department visit data and writing hubverse-format time-series and oracle-output target data (see:
update_hub_target_data(),generate_oracle_output()). - Forecast Generation: producing the hubs' baseline and ensemble models (see:
generate_hub_baseline(),generate_hub_ensemble()). - Visualization Data: generating the weekly summary files and web text for the public visualizations at CDC.gov (
write_ref_date_summary_*(),write_webtext()). - Submission Management: checking that pull requests concern only authorized model-output directories so they can be auto-approved (see:
check_changes_for_autoapproval()). - Hub Utilities: disease/hub name mappings and hub-config task helpers (see:
get_hub_name(),get_hub_tasks()).
The full function reference can be found at https://cdcgov.github.io/hubhelpr/.
Most hub maintenance runs through the composite actions in actions/.
| Action | Purpose |
|---|---|
setup-hubhelpr |
set up R with hubhelpr installed (required to run first) |
update-target-data |
pull NHSN/NSSP data and open a PR with updated target data |
generate-baseline |
generate baseline forecasts and open a PR |
generate-ensemble |
generate ensemble forecasts and open a PR |
check-authorized-users |
validate PR changes for auto-approval |
generate-viz-data |
generate weekly visualization data files and open a PR |
- uses: cdcgov/hubhelpr/actions/setup-hubhelpr@main
- uses: cdcgov/hubhelpr/actions/generate-baseline@main
with:
disease: "covid" # 'covid' or 'rsv'
reference_date: ${{ inputs.reference_date }}
github_token: ${{ secrets.GITHUB_TOKEN }}Used By
- covid19-forecast-hub and rsv-forecast-hub: target-data, baseline, ensemble, and PR auto-approval workflows.
- cfa-forecast-hub-reports: weekly visualization data for the public CDC.gov forecast pages.
- cfa-forecast-hub-internal-reports (internal): hub/model naming helpers in evaluation reports.
You can install hubhelpr via pak. If you do not yet have pak, you should be able to install it with install.packages('pak').
Once pak is installed, run the following in an R session:
pak::pkg_install('cdcgov/hubhelpr')You can also install hubhelpr using the remotes R package (which itself can be installed with install.packages('remotes')):
remotes::install_github('cdcgov/hubhelpr')
- Subekshya Bidari, zib2@cdc.gov (CDC/IOD/ORR/CFA)
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