#' @export print.summary_multi_cutpointr <- function(x, digits = 4, ...) { cat(paste("Method:", x$cutpointr[[1]]$method, "\n")) cat(paste("Predictor:", paste(unique(purrr::map_chr(x$cutpointr, function(x) x$predictor)), collapse = ", "), "\n")) cat(paste("Outcome:", x$cutpointr[[1]]$outcome, "\n")) if (has_column(x$cutpointr[[1]], "subgroup")) { cat(c("Subgroups:", paste(unique(purrr::map(x$cutpointr, ~ .$subgroup)), collapse = ", "), "\n")) } if (has_boot_results(x)) { cat(paste("Nr. of bootstraps:", x$boot_runs[1], "\n")) } for (i in 1:nrow(x)) { cat("\n") cat(paste("Predictor:", x$cutpointr[[i]]$predictor, "\n")) if (has_column(x$cutpointr[[i]], "subgroup")) { cat(paste("Subgroup:", x$cutpointr[[i]]$subgroup, "\n")) } cat(paste0(rep("-", getOption("width")), collapse = ""), "\n") x$cutpointr[[i]] %>% dplyr::select(.data$AUC) %>% round(digits = digits) %>% dplyr::mutate(n = x$n_obs[i], n_pos = x$n_pos[i], n_neg = x$n_neg[i]) %>% as.data.frame %>% print(row.names = FALSE) cat("\n") purrr::map_df(1:length(x$cutpointr[[i]]$optimal_cutpoint[[1]]), function(j) { x$cutpointr[[i]] %>% dplyr::select(.data$direction, .data$optimal_cutpoint, !!find_metric_name(x$cutpointr[[i]]), .data$acc, .data$sensitivity, .data$specificity) %>% purrr::map_df(get_fnth, n = j) }) %>% as.data.frame %>% dplyr::left_join(y = x$confusion_matrix[[i]], by = c("optimal_cutpoint" = "cutpoint")) %>% dplyr::mutate_if(is.numeric, round, digits = 4) %>% print(row.names = FALSE) cat("\n") cat(paste("Predictor summary:", "\n")) rownames(x$desc[[i]]) <- "overall" print(round(rbind(x$desc[[i]], x$desc_by_class[[i]]), digits = digits)) if (has_boot_results(x[i, ])) { cat("\n") cat(paste("Bootstrap summary:", "\n")) print.data.frame( x[["boot"]][[i]] %>% dplyr::mutate_if(is.numeric, round, digits = digits), row.names = rep("", nrow(x[["boot"]][[i]])) ) } } return(invisible(x)) }