The goal of hubVis is to provide plotting methods for hub model outputs, following the hubverse format. The hubverse is a collection of open-source software and data tools, developed by the Consortium of Infectious Disease Modeling Hubs. For more information, please consult the hubDocs website
You can install the latest version of hubVis from the R-universe:
install.packages("hubVis", repos = c("https://hubverse-org.r-universe.dev", "https://cloud.r-project.org"))
If you want to test out new features that have not yet been released, you can install the development version of hubVis from GitHub with:
remotes::install_github("hubverse-org/hubVis")
The R package contains currently one function plot_step_ahead_model_output()
plotting 50%, 80%, and 95% quantiles intervals, with a specific color per
"model_id".
The function can output 2 types of plots:
library(hubVis)
library(hubExamples)
head(scenario_outputs)
head(scenario_target_ts)
projection_data <- dplyr::mutate(scenario_outputs,
target_date = as.Date(origin_date) + (horizon * 7) - 1)
target_data_us <- dplyr::filter(scenario_target_ts, location == "US",
date < min(projection_data$target_date) + 21,
date > "2020-10-01")
projection_data_us <- dplyr::filter(projection_data,
scenario_id == "A-2021-03-05",
location == "US")
plot_step_ahead_model_output(projection_data_us, target_data_us)
Faceted plots can be created for multiple scenarios, locations, targets, models, etc.
projection_data_us <- dplyr::filter(projection_data,
location == "US")
plot_step_ahead_model_output(projection_data_us, target_data_us,
use_median_as_point = TRUE,
facet = "scenario_id", facet_scales = "free_x",
facet_nrow = 2, facet_title = "bottom left")
Please note that the hubVis package is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
Interested in contributing back to the open-source Hubverse project? Learn more about how to get involved in the Hubverse Community or how to contribute to the hubVis package.