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#' Confidence Score Ridge Plot
#'
#' Display a ridge plot of confidence scores for each aggregation method
#'
#' @param confidence_scores A data frame of confidence scores in long format in the form of [data_confidence_scores]
#'
#' @return A density ridge plot of aggregation methods
#'
#' @examples
#' \donttest{confidence_scores_ridgeplot(data_confidence_scores)}
#'
#' @export
confidence_score_ridgeplot <- function(confidence_scores = NULL){
if(is.null(confidence_scores)){
cli::cli_alert_info("No Confidence Scores Provided. Using Package Default")
confidence_scores <- aggreCAT::data_confidence_scores
} else {
confidence_scores <- confidence_scores
}
number_of_claims <- dplyr::n_distinct(confidence_scores$paper_id)
confidence_scores %>%
ggplot2::ggplot(ggplot2::aes(x = cs,
y = factor(method,
levels = rev(levels(factor(method)))),
fill = factor(ggplot2::after_stat(stats::quantile))
)) +
ggridges::stat_density_ridges(
geom = "density_ridges_gradient",
calc_ecdf = TRUE,
quantiles = c(0.025, 0.975)) +
ggplot2::scale_fill_manual(
name = "Probability",
values = c("#D55E00", "#A0A0A0A0", "#0072B2"), # colour friendly
labels = c("(0, 0.025]", "(0.025, 0.975]", "(0.975, 1]")) +
ggplot2::scale_x_continuous(breaks = c(0, .25, .5, .75, 1)) +
ggplot2::scale_y_discrete(expand = c(0, 0)) +
ggplot2::geom_vline(xintercept = .50,
linetype = "dashed",
color = "black",
alpha = 1,
show.legend = TRUE) +
ggplot2::theme_bw() +
ggplot2::labs(title = "Density of Aggregated Confidence Scores",
subtitle = paste0("Claims Assessed N = ", number_of_claims),
x = "Confidence Scores",
y = "Aggregation Method")
}
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