NEWS.md

Changes since last release

• Update load_forecasts_repo() and load_latest_forecasts_repo() to use local data objects to validate targets parameter.
• Update score_forecasts() to return the true_value in function output
• Add hub parameter in plot_forecasts() and get_plot_forecast_data().
• Update validation for locations, truth_source and target_variable in plot_forecasts() and get_plot_forecast_data().
• Add a column that appends state abbreviation to county names in US hub locations data object.
• load_truth() now supports multiple target variables and has a new set of default values for target_variable and truth_source based on hub parameter.
• load_forecasts_repo(), load_latest_forecasts_repo() and load_forecast_files_repo() drop rows with NULLs in value column in forecast files.
• Add date_to_datetime() that converts a date to a date time in the corresponding timezone based on hub and returns that date time in UTC timezone. This function is used when the user is using as_of parameter to load forecasts from zoltar only.
• Add preprocess_visualization_truth() to generate JSON truth file for covid19 hub visualization, and its corresponding unit tests
• Add calc_cramers_dist_equal_space(), calc_cramers_dist_equal_space(), and calc_cramers_dist_one_model_pair() to calculate forecast similarities based on the approximation of Cramer's distance.
• In score_forecasts() calculate one-sided quantile coverage denoted quantile_coverage0.xx.

covidHubUtils 0.1.5

This is a release for renaming plot_forecast() to plot_forecasts(). plot_forecast() is still available to use but will return deprecation warnings to the user.

Package updates

• There is backwards compatibility.

covidHubUtils 0.1.4

This is a release focusing on updates that provide better interface with Zoltar and European COVID-19 Forecast Hub. The release also contains new feature updates and bug fixes in other util functions.

Feature updates

• Update load_forecasts() and load_latest_forecasts()

  • Add hub parameter to specify the forecast hub for which data should be loaded.

  • Add as_of parameter to improve interface with the Zoltar query.

  • Add verbose parameter to specify whether to print out diagnostic messages.

  • Support source = local_hub_repo in load_forecasts(). However, loading versioned forecast files is only available through zoltar.

  • All models inputed into load_latest_forecasts() must be available in the selected source.

  • Refactor to improve efficiency.

• Update plot_forecast()

  • Load "inc hosp" truth data from remote hub repository. The user does not need to provide truth_data parameter to plot daily incident hospitalization forecasts.

  • target_variable is now optional when forecast_data only has one target variable.

  • Add a new parameter use_median_as_point that defaults to FALSE. "TRUE" uses the median quantile and "FALSE" uses the point forecasts.

  • The function now errors when trying to plot multiple locations without a facet formula.

  • Fix bug that model legend is missing when the user is only plotting quantile forecasts.

  • Update quantile forecast color so that color transparency will not be overwritten by fill_transparency when plotting more than five models.

• Update load_truth()

  • Add hub parameter to specify the forecast hub for which data should be loaded.

  • Add "inc hosp" target variable and "HealthData" source.

• score_forecasts() has new parameter use_median_as_point that defaults to FALSE. "TRUE" uses the median quantile when calculating absolute error and "FALSE" uses the point forecasts for absolute error.

• Add optional as_of parameter in get_model_designations(). Currently only support versioned model designation in local hub repo.

Package updates

• There is no backwards compatibility.
• Add Nikos I. Bosse and Ariane Stark to author/contributor list
• Add hub_locations_ecde.rda to data folder

covidHubUtils 0.1.3

This is a release focusing on new scoring function and truth-processing functions. The release also contains new feature updates and bug fixes in other util functions.

covidHubUtils now requires the scoringutils package version to be at least 0.1.5.

Breaking changes

• score_forecasts() is now implemented for quantile-format forecasts to compute absolute error, weighted interval score, sharpness, overprediction, underprediction, and prediction interval coverage at any specified quantile. Minimally one should have the forecasts dataframe produced by load_forecasts() and the truth dataframe produced by load_truth() to calculate scores. If one desires to specify a subset of all available scores, one should consult this reference for valid scores in the desired_score_types vector.

  • wis calculation changed to reflect preferred weighting scheme for interval scores.

• preprocess_truth_for_zoltar() and save_truth_for_zoltar() are now implemented to create standard cumulative and incident death truth csv files for Zoltar.

• preprocess_hospitalization() is now implemented to create standard cumulative and incident hospitalization truth csv files.

Feature updates

• Update load_forecasts() and load_latest_forecasts()

  • Update default value of forecast_date_window_size to 0 inload_latest_forecasts() so that it looks for forecasts on the latest_forecast_date only.

  • Refactor load_latest_forecasts_repo(), splitting out functionality for reading in forecasts into a new exported function load_forecast_files_repo() that loads specific forecast files.

  • Standardize data format and columns types of the output.

  • Fix validation bug for forecast_dates when loading forecasts from zoltar. Loading functions will throw an error if all dates in forecast_dates are invalid forecast dates in Zoltar.

• Update plot_forecast() to use more user-friendly color palettes when plotting a small number of intervals.

• Update get_model_designations() to return NA when model designations for outdated models are not available on Zoltar.

Package updates

• There is no backwards compatibility.
• Minor updates to overview vignette.

covidHubUtils 0.1.2

This is a release focusing on new features in scoring functions and plotting functions.

Feature updates

• Update plot_forecast()

  • Set truth_source to be optional when the user provides truth_data. However, it is still needed when show_caption = TRUE.

  • Remove format validation for model column in user-provided truth_data.

  • Support daily hospitalization plot. When target_variable = "inc hosp", the user needs to provided truth_data. Otherwise, an error will be thrown.

  • Add facet_nrow, facet_ncol, fill_transparency, title and subtitle.

• Update get_plot_forecast_data()

  • Remove format validation for model column in user-provided truth_data.

  • When target_variable = "inc hosp", the user needs to provided truth_data. Otherwise, an error will be thrown.

Package updates

• There is no backwards compatibility.
• Add Khoa Le and Yuxin David Huang to author/contributor list
• Create covidHubUtils-overview vignette

covidHubUtils 0.1.1

This is a release focusing on new features in plotting functions.

Feature updates

• plot_forecast() now supports faceted plots of multiple models, locations and forecast dates for one target variable.

  • In plot_forecast(), facet and facet_scales are equivalent to facets and scales in ggplot2::facet_wrap(). facet takes facet formula, for example facet = ~ model. facet_scales are expecting the same values for scales in ggplot2::facet_wrap(), such as "fixed", "free_y", "free_x" or "free".

  • If fill_by_model = TRUE, each model will be represented by a unique color. If fill_by model = FALSE, all models and selected prediction intervals will be represented by blue colors.

  • For simplicity, prediction interval legends will be grey in faceted plots. Morever, when the user selects more than 5 models, only 95% predicition interval is included. Otherwise, all selected prediction intervals will be plotted.

Package updates

• There is no backwards compatibility due to argument changes in plot_forecast().

covidHubUtils 0.1

This is the first version of the package with a 0.x release.

Feature updates

• details on new features will be listed here for future updates
• current key features include loading and plotting forecast and truth data

Package updates

• details on other changes will be listed here for future updates
• added initial author/contributor list