NEWS.md

Changes since last release

• All locations parameters now take location names. This parameter should be a vector of strings of fips code or CBSA codes or location names, such as "Hampshire County, MA", "Alabama", "United Kingdom".
• Support loading data from local zoltar module in load_forecasts() when source = "local_zoltar". Please follow instructions in load_forecasts_local_zoltar() to set up required environment for this functionality.
• Sort models parameter in load_forecasts() and load_latest_forecasts() so that the resulting data frame is locale-independent
• Add hub parameter in get_all_models(). It does not support loading model names for ECDC hub from remote hub repo for now.
• Rename sharpness score as dispersion.
• Update warning messages and error messages in load_forecasts_zoltar().
• Remove as_of functionality in get_model_metadata() and get_model_designations(). as_of parameter is not available now.
• Fix bug resulting in error in get_model_metadata() when a metadata file has NULL fields.
• Fix bug resulting in empty ouput in load_forecats_zoltar() when verbose is TRUE.
• Add validation for temporal_resolution in calc_target_end_date().
• Update load_truth() to turn off "inc case" and "inc death" target variables for "ECDC" truth soource.

covidHubUtils 0.1.6

This is a release focusing on new features in most of the major functions.

covidHubUtils now requires additional R packages doParallel, parallel and foreach.

Feature updates

• Update load_forecasts() and deprecate load_latest_forecasts().

  • The new implementation of load_forecasts() combines the functionality of the previous version of load_forecasts() and load_latest_forecasts(). Details about this change are in load_forecasts() documentation.

  • Rename forecast_dates to dates.

  • Add date_window_size to specify the number of days across each date in dates parameter to look for the most recent forecasts.

  • Use local data objects to validate targets parameter when source = "local_hub_repo".

  • Drop rows with NULLs in value column in forecast files when source = "local_hub_repo".

  • Add helper functiondate_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 helper function reformat_forecasts() to format dataframe returned by a zoltar query.

• Update plot_forecasts()

  • Add hub parameter to plot forecasts from US and ECDC hub.

  • Update validation for locations, truth_source and target_variable parameters.

  • Add top_layer parameter to switch layers of forecasts and truth data.

• Update load_truth()

  • Support multiple target variables and has a new set of default values for target_variable and truth_source based on hub parameter. There are special cases for weekly aggregations when "inc hosp" is in target_variable. Please refer to the detail tab in function documentation.

  • Support loading truth data from covidData. as_of parameter is only supported when data_location = "covidData". Otherwise, this function will return warnings.

  • Add daily and weekly incident hospitalization data from ECDC source in load_truth().

  • Refactor code and add helper functions load_from_hub_repo(), load_from_coviddata() and aggregate_to_weekly()

• Update score_forecasts()

  • Return true_value in function output.

  • Calculate one-sided quantile coverage denoted quantile_coverage0.xx.

  • Add metrics parameter which is a character vector of the metrics to be returned with options "abs_error", "wis", "wis_components","interval_coverage", and "quantile_coverage"

• Update save_truth_for_zoltar() to return differences between the new version and the current version of truth on zoltar server.

• Update get_model_designations() to handle spaces in hub_repo_path parameters.

• Add get_model_metadata() based off of get_model_designations() but to retrieve all fields in metadata.

• 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.

Package updates

• There is no backwards compatibility.
• Add a column that appends state abbreviation to county names in US hub locations data object.
• New pkgdown site

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