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# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
# #
# LICENCE #
# (c) 2018-2022 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 data 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)
#' \donttest{
#' 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 = c("numeric", "integer"), has_length = 1, allow_NULL = TRUE, is_positive = TRUE, is_finite = TRUE)
x <- vapply(FUN.VALUE = double(1), tbl, function(x) {
1 - sum(is.na(x)) / length(x)
})
n <- vapply(FUN.VALUE = double(1), tbl, function(x) length(x[!is.na(x)]))
R <- vapply(FUN.VALUE = double(1), tbl, function(x) ifelse(is.rsi(x), resistance(x, minimum = 0), NA_real_))
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,
stringsAsFactors = FALSE)
if (length(R[is.na(R)]) == ncol(tbl)) {
df[, 1:3]
} else {
df
}
}