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AMR/R/misc.R

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# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis #
# #
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# SOURCE #
# https://gitlab.com/msberends/AMR #
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# #
# LICENCE #
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# (c) 2019 Berends MS (m.s.berends@umcg.nl), Luz CF (c.f.luz@umcg.nl) #
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# #
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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. #
# #
# This R package was created for academic research and 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 more info: https://msberends.gitlab.io/AMR. #
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# ==================================================================== #
# No export, no Rd
addin_insert_in <- function() {
rstudioapi::insertText(" %in% ")
}
# No export, no Rd
addin_insert_like <- function() {
rstudioapi::insertText(" %like% ")
}
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# No export, no Rd
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# works exactly like round(), but rounds `round(44.55, 1)` as 44.6 instead of 44.5
# and adds decimal zeroes until `digits` is reached when force_zero = TRUE
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round2 <- function(x, digits = 0, force_zero = TRUE) {
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# https://stackoverflow.com/a/12688836/4575331
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val <- (trunc((abs(x) * 10 ^ digits) + 0.5) / 10 ^ digits) * sign(x)
if (digits > 0 & force_zero == TRUE) {
val[val != as.integer(val)] <- paste0(val[val != as.integer(val)],
strrep("0", max(0, digits - nchar(gsub(".*[.](.*)$", "\\1", val[val != as.integer(val)])))))
}
val
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}
# Coefficient of variation (CV)
cv <- function(x, na.rm = TRUE) {
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stats::sd(x, na.rm = na.rm) / base::abs(base::mean(x, na.rm = na.rm))
}
# Coefficient of dispersion, or coefficient of quartile variation (CQV).
# (Bonett et al., 2006: Confidence interval for a coefficient of quartile variation).
cqv <- function(x, na.rm = TRUE) {
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fives <- stats::fivenum(x, na.rm = na.rm)
(fives[4] - fives[2]) / (fives[4] + fives[2])
}
# show bytes as kB/MB/GB
# size_humanreadable(123456) # 121 kB
# size_humanreadable(12345678) # 11.8 MB
size_humanreadable <- function(bytes, decimals = 1) {
bytes <- bytes %>% as.double()
# Adapted from:
# http://jeffreysambells.com/2012/10/25/human-readable-filesize-php
size <- c('B','kB','MB','GB','TB','PB','EB','ZB','YB')
factor <- floor((nchar(bytes) - 1) / 3)
# added slight improvement; no decimals for B and kB:
decimals <- rep(decimals, length(bytes))
decimals[size[factor + 1] %in% c('B', 'kB')] <- 0
out <- paste(sprintf(paste0("%.", decimals, "f"), bytes / (1024 ^ factor)), size[factor + 1])
out
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}
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percent_scales <- scales::percent
# No export, no Rd
# based on scales::percent
percent <- function(x, round = 1, force_zero = FALSE, decimal.mark = getOption("OutDec"), ...) {
x <- percent_scales(x = as.double(x),
accuracy = 1 / 10 ^ round,
decimal.mark = decimal.mark,
...)
if (force_zero == FALSE) {
x <- gsub("([.]%|%%)", "%", paste0(gsub("0+%$", "", x), "%"))
}
x
}
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#' @importFrom crayon blue bold red
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#' @importFrom dplyr %>% pull
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search_type_in_df <- function(x, type) {
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# try to find columns based on type
found <- NULL
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colnames(x) <- trimws(colnames(x))
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# -- mo
if (type == "mo") {
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if ("mo" %in% lapply(x, class)) {
found <- colnames(x)[lapply(x, class) == "mo"][1]
} else if (any(colnames(x) %like% "^(mo|microorganism|organism|bacteria)s?$")) {
found <- colnames(x)[colnames(x) %like% "^(mo|microorganism|organism|bacteria)s?$"][1]
} else if (any(colnames(x) %like% "species")) {
found <- colnames(x)[colnames(x) %like% "species"][1]
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}
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}
# -- key antibiotics
if (type == "keyantibiotics") {
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if (any(colnames(x) %like% "^key.*(ab|antibiotics)")) {
found <- colnames(x)[colnames(x) %like% "^key.*(ab|antibiotics)"][1]
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}
}
# -- date
if (type == "date") {
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if (any(colnames(x) %like% "^(specimen date|specimen_date|spec_date)")) {
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# WHONET support
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found <- colnames(x)[colnames(x) %like% "^(specimen date|specimen_date|spec_date)"][1]
if (!any(class(x %>% pull(found)) %in% c("Date", "POSIXct"))) {
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stop(red(paste0("ERROR: Found column `", bold(found), "` to be used as input for `col_", type,
"`, but this column contains no valid dates. Transform its values to valid dates first.")),
call. = FALSE)
}
} else {
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for (i in 1:ncol(x)) {
if (any(class(x %>% pull(i)) %in% c("Date", "POSIXct"))) {
found <- colnames(x)[i]
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break
}
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}
}
}
# -- patient id
if (type == "patient_id") {
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if (any(colnames(x) %like% "^(identification |patient|patid)")) {
found <- colnames(x)[colnames(x) %like% "^(identification |patient|patid)"][1]
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}
}
# -- specimen
if (type == "specimen") {
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if (any(colnames(x) %like% "(specimen type|spec_type)")) {
found <- colnames(x)[colnames(x) %like% "(specimen type|spec_type)"][1]
} else if (any(colnames(x) %like% "^(specimen)")) {
found <- colnames(x)[colnames(x) %like% "^(specimen)"][1]
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}
}
if (!is.null(found)) {
msg <- paste0("NOTE: Using column `", bold(found), "` as input for `col_", type, "`.")
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if (type %in% c("keyantibiotics", "specimen")) {
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msg <- paste(msg, "Use", bold(paste0("col_", type), "= FALSE"), "to prevent this.")
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}
message(blue(msg))
}
found
}
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get_column_abx <- function(x,
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soft_dependencies = NULL,
hard_dependencies = NULL,
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verbose = FALSE,
...) {
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# determine from given data set
df_trans <- data.frame(colnames = colnames(x),
abcode = suppressWarnings(as.ab(colnames(x))))
df_trans <- df_trans[!is.na(df_trans$abcode),]
x <- as.character(df_trans$colnames)
names(x) <- df_trans$abcode
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# add from self-defined dots (...):
# get_column_abx(septic_patients %>% rename(thisone = AMX), amox = "thisone")
dots <- list(...)
if (length(dots) > 0) {
dots <- unlist(dots)
newnames <- suppressWarnings(as.ab(names(dots)))
if (any(is.na(newnames))) {
warning("Invalid antibiotic reference(s): ", toString(names(dots)[is.na(newnames)]),
call. = FALSE, immediate. = TRUE)
}
names(dots) <- newnames
dots <- dots[!is.na(names(dots))]
# merge, but overwrite automatically determined ones by 'dots'
x <- c(x[!x %in% dots & !names(x) %in% names(dots)], dots)
}
# sort on name
x <- x[sort(names(x))]
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duplies <- x[base::duplicated(x)]
if (verbose == TRUE) {
for (i in 1:length(x)) {
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if (x[i] %in% duplies) {
message(red(paste0("NOTE: Using column `", bold(x[i]), "` as input for `", names(x)[i],
"` (", ab_name(names(x)[i], language = "en", tolower = TRUE), ") [DUPLICATED USE].")))
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} else {
message(blue(paste0("NOTE: Using column `", bold(x[i]), "` as input for `", names(x)[i],
"` (", ab_name(names(x)[i], language = "en", tolower = TRUE), ").")))
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}
}
}
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if (n_distinct(x) != length(x)) {
msg_txt <- paste("Column(s)", paste0("`", duplies, "`", collapse = " and "), "used for more than one antibiotic.")
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if (verbose == FALSE) {
msg_txt <- paste(msg_txt, "Use verbose = TRUE to see which antibiotics are used by which columns.")
}
stop(msg_txt, call. = FALSE)
}
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if (!is.null(hard_dependencies)) {
if (!all(hard_dependencies %in% names(x))) {
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# missing a hard dependency will return NA and consequently the data will not be analysed
missing <- hard_dependencies[!hard_dependencies %in% names(x)]
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generate_warning_abs_missing(missing, any = FALSE)
return(NA)
}
}
if (!is.null(soft_dependencies)) {
if (!all(soft_dependencies %in% names(x))) {
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# missing a soft dependency may lower the reliability
missing <- soft_dependencies[!soft_dependencies %in% names(x)]
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missing <- paste0(missing, " (", ab_name(missing, tolower = TRUE), ")")
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warning('Reliability might be improved if these antimicrobial results would be available too: ', paste(missing, collapse = ", "),
immediate. = TRUE,
call. = FALSE)
}
}
x
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}
generate_warning_abs_missing <- function(missing, any = FALSE) {
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missing <- paste0(missing, " (", ab_name(missing, tolower = TRUE), ")")
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if (any == TRUE) {
any_txt <- c(" any of", "is")
} else {
any_txt <- c("", "are")
}
warning(paste0("Introducing NAs since", any_txt[1], " these antimicrobials ", any_txt[2], " required: ",
paste(missing, collapse = ", ")),
immediate. = TRUE,
call. = FALSE)
}
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stopifnot_installed_package <- function(package) {
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# no "utils::installed.packages()" since it requires non-staged install since R 3.6.0
# https://developer.r-project.org/Blog/public/2019/02/14/staged-install/index.html
get(".packageName", envir = asNamespace(package))
return(invisible())
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}
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# translate strings based on inst/translations.tsv
#' @importFrom dplyr %>% filter
t <- function(from, language = get_locale()) {
# if (getOption("AMR_locale", "en") != language) {
# language <- getOption("AMR_locale", "en")
# }
if (is.null(language)) {
return(from)
}
if (language %in% c("en", "")) {
return(from)
}
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df_trans <- translations_file # internal data file
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if (!language %in% df_trans$lang) {
stop("Unsupported language: '", language, "' - use one of: ",
paste0("'", sort(unique(df_trans$lang)), "'", collapse = ", "),
call. = FALSE)
}
df_trans <- df_trans %>% filter(lang == language)
# default case sensitive if value if 'ignore.case' is missing:
df_trans$ignore.case[is.na(df_trans$ignore.case)] <- FALSE
# default not using regular expressions (fixed = TRUE) if 'fixed' is missing:
df_trans$fixed[is.na(df_trans$fixed)] <- TRUE
# check if text to look for is in one of the patterns
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any_form_in_patterns <- tryCatch(any(from %like% paste0("(", paste(df_trans$pattern, collapse = "|"), ")")),
error = function(e) {
warning("Translation not possible. Please open an issue on GitLab (https://gitlab.com/msberends/AMR/issues) or GitHub (https://github.com/msberends/AMR/issues).", call. = FALSE)
return(FALSE)
})
if (NROW(df_trans) == 0 | !any_form_in_patterns) {
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return(from)
}
for (i in 1:nrow(df_trans)) {
from <- gsub(x = from,
pattern = df_trans$pattern[i],
replacement = df_trans$replacement[i],
fixed = df_trans$fixed[i],
ignore.case = df_trans$ignore.case[i])
}
# force UTF-8 for diacritics
base::enc2utf8(from)
}
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"%or%" <- function(x, y) {
ifelse(!is.na(x), x, ifelse(!is.na(y), y, NA))
}