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# ==================================================================== #
# TITLE #
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# Antimicrobial Resistance (AMR) Analysis for R #
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# #
# SOURCE #
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# https://github.com/msberends/AMR #
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# #
# LICENCE #
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# (c) 2018-2021 Berends MS, Luz CF et al. #
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# Developed at the University of Groningen, the Netherlands, in #
# collaboration with non-profit organisations Certe Medical #
# Diagnostics & Advice, and University Medical Center Groningen. #
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# #
# 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. #
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# 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. #
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# #
# Visit our website for the full manual and a complete tutorial about #
# how to conduct AMR analysis: https://msberends.github.io/AMR/ #
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# ==================================================================== #
#' Check availability of columns
#'
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#' 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
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#' @param tbl a [data.frame] or [list]
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#' @param width number of characters to present the visual availability, defaults to filling the width of the console
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#' @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
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#' @inheritSection AMR Read more on our website!
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#' @export
#' @examples
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#' availability(example_isolates)
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#'
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#' if (require("dplyr")) {
#' example_isolates %>%
#' filter(mo == as.mo("E. coli")) %>%
#' select_if(is.rsi) %>%
#' availability()
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#' }
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availability <- function ( tbl , width = NULL ) {
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meet_criteria ( tbl , allow_class = " data.frame" )
meet_criteria ( width , allow_class = " numeric" , allow_NULL = TRUE )
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x <- vapply ( FUN.VALUE = double ( 1 ) , tbl , function ( x ) {
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1 - sum ( is.na ( x ) ) / length ( x )
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} )
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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_ ) )
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R_print <- character ( length ( R ) )
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R_print [ ! is.na ( R ) ] <- percentage ( R [ ! is.na ( R ) ] )
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R_print [is.na ( R ) ] <- " "
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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
}
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if ( length ( R [is.na ( R ) ] ) == ncol ( tbl ) ) {
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width <- width * 2 + 10
}
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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 ) ] <- " "
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x_chars <- strrep ( " #" , round ( x , digits = 2 ) / ( 1 / width ) )
x_chars_empty <- strrep ( " -" , width - nchar ( x_chars ) )
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df <- data.frame ( count = n ,
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available = percentage ( x ) ,
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visual_availabilty = paste0 ( " |" , x_chars , x_chars_empty , " |" ) ,
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resistant = R_print ,
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visual_resistance = vis_resistance ,
stringsAsFactors = FALSE )
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if ( length ( R [is.na ( R ) ] ) == ncol ( tbl ) ) {
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df [ , 1 : 3 ]
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} else {
df
}
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}