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# ==================================================================== #
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# TITLE: #
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# AMR: An R Package for Working with Antimicrobial Resistance Data #
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# #
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# SOURCE CODE: #
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# https://github.com/msberends/AMR #
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# #
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# PLEASE CITE THIS SOFTWARE AS: #
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# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. #
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# https://doi.org/10.18637/jss.v104.i03 #
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# #
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# Developed at the University of Groningen and the University Medical #
# Center Groningen in The Netherlands, in collaboration with many #
# colleagues from around the world, see our website. #
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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 #
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# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
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# ==================================================================== #
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#' Check Availability of Columns
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#'
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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()].
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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 - the default is 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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#' @export
#' @examples
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#' availability(example_isolates)
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#' \donttest{
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#' if (require("dplyr")) {
#' example_isolates %>%
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#' filter(mo == as.mo("Escherichia coli")) %>%
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#' select_if(is.sir) %>%
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#' availability()
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#' }
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#' }
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availability <- function ( tbl , width = NULL ) {
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meet_criteria ( tbl , allow_class = " data.frame" )
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meet_criteria ( width , allow_class = c ( " numeric" , " integer" ) , has_length = 1 , allow_NULL = TRUE , is_positive = TRUE , is_finite = TRUE )
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tbl <- as.data.frame ( tbl , stringsAsFactors = FALSE )
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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 ) ] ) )
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R <- vapply ( FUN.VALUE = double ( 1 ) , tbl , function ( x ) ifelse ( is.sir ( 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 ) ) {
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width <- getOption ( " width" , 100 ) -
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( max ( nchar ( colnames ( tbl ) ) ) +
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# count col
8 +
# available % column
10 +
# resistant % column
10 +
# extra margin
5 )
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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 ,
available = percentage ( x ) ,
visual_availabilty = paste0 ( " |" , x_chars , x_chars_empty , " |" ) ,
resistant = R_print ,
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 , drop = FALSE ]
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} else {
df
}
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}