# ==================================================================== # # TITLE # # Antimicrobial Resistance (AMR) Analysis for R # # # # SOURCE # # https://github.com/msberends/AMR # # # # LICENCE # # (c) 2018-2020 Berends MS, Luz CF et al. # # Developed at the University of Groningen, the Netherlands, in # # collaboration with non-profit organisations Certe Medical # # Diagnostics & Advice, and University Medical Center Groningen. # # # # This R package is free software; you can freely use and distribute # # it for both personal and commercial purposes under the terms of the # # GNU General Public License version 2.0 (GNU GPL-2), as published by # # the Free Software Foundation. # # We created this package for both routine data analysis and academic # # research and it was publicly released in the hope that it will be # # useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. # # # # Visit our website for the full manual and a complete tutorial about # # how to conduct AMR analysis: https://msberends.github.io/AMR/ # # ==================================================================== # #' Check availability of columns #' #' Easy check for data availability of all columns in a data set. This makes it easy to get an idea of which antimicrobial combinations can be used for calculation with e.g. [susceptibility()] and [resistance()]. #' @inheritSection lifecycle Stable lifecycle #' @param tbl a [data.frame] or [list] #' @param width number of characters to present the visual availability, defaults to filling the width of the console #' @details The function returns a [data.frame] with columns `"resistant"` and `"visual_resistance"`. The values in that columns are calculated with [resistance()]. #' @return [data.frame] with column names of `tbl` as row names #' @inheritSection AMR Read more on our website! #' @export #' @examples #' availability(example_isolates) #' #' if (require("dplyr")) { #' example_isolates %>% #' filter(mo == as.mo("E. coli")) %>% #' select_if(is.rsi) %>% #' availability() #' } availability <- function(tbl, width = NULL) { meet_criteria(tbl, allow_class = "data.frame") meet_criteria(width, allow_class = "numeric", allow_NULL = TRUE) x <- sapply(tbl, function(x) { 1 - sum(is.na(x)) / length(x) }) n <- sapply(tbl, function(x) length(x[!is.na(x)])) R <- sapply(tbl, function(x) ifelse(is.rsi(x), resistance(x, minimum = 0), NA)) R_print <- character(length(R)) R_print[!is.na(R)] <- percentage(R[!is.na(R)]) R_print[is.na(R)] <- "" if (is.null(width)) { width <- options()$width - (max(nchar(colnames(tbl))) + # count col 8 + # available % column 10 + # resistant % column 10 + # extra margin 5) width <- width / 2 } if (length(R[is.na(R)]) == ncol(tbl)) { width <- width * 2 + 10 } x_chars_R <- strrep("#", round(width * R, digits = 2)) x_chars_SI <- strrep("-", width - nchar(x_chars_R)) vis_resistance <- paste0("|", x_chars_R, x_chars_SI, "|") vis_resistance[is.na(R)] <- "" x_chars <- strrep("#", round(x, digits = 2) / (1 / width)) x_chars_empty <- strrep("-", width - nchar(x_chars)) df <- data.frame(count = n, available = percentage(x), visual_availabilty = paste0("|", x_chars, x_chars_empty, "|"), resistant = R_print, visual_resistance = vis_resistance) if (length(R[is.na(R)]) == ncol(tbl)) { df[, 1:3] } else { df } }