In epiforecasts/covid.german.forecasts: Forecasting Covid-19 related metrics for the German/Poland Forecast Hub

scores <- scoringutils::eval_forecasts(data,
                                         summarise_by = c("model", 
                                                          "location_name", 
                                                          "target_type",
                                                          "forecast_date"), 
                                       compute_relative_skill = FALSE)

ranked_scores <- scores %>%
  dplyr::mutate(forecast_date = as.Date(forecast_date)) %>%
  dplyr::group_by(forecast_date, location_name, target_type) %>%
  dplyr::mutate(num_forecasts = dplyr::n(), 
                rank = rank(interval_score, ties.method = "average",
                                           na.last = NA), 
                standard_rank = round((1 - (rank - 1) / (num_forecasts - 1)) * 100)) %>%
  dplyr::ungroup()

cat("\n\n## model rank\n\n")
plot <- score_heatmap(ranked_scores, metric = "rank", 
                      x = "forecast_date",
                      facet_wrap_or_grid = "grid",
                      facet_formula = location_name ~ target_type) + 
  ggplot2::theme(legend.position = "bottom") +
    ggplot2::scale_fill_gradient(low = "white", high = "coral")

print(plot)

cat("\n\n## standardised model rank\n\n")
plot <- score_heatmap(ranked_scores, metric = "standard_rank", 
                      x = "forecast_date",
                      facet_wrap_or_grid = "grid",
                      facet_formula = location_name ~ target_type) + 
  ggplot2::theme(legend.position = "bottom") +
    ggplot2::scale_fill_gradient(high = "white", low = "coral")


print(plot)

epiforecasts/covid.german.forecasts documentation built on Jan. 25, 2024, 4:44 p.m.