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New mo algorithm, prepare for 2.0

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Dr. Matthijs Berends
2022-10-05 09:12:22 +02:00
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parent 63fe160322
commit cd2acc4a29
182 changed files with 4054 additions and 90905 deletions
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38
R/bug_drug_combinations.R
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@ -1,12 +1,16 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# AMR: An R Package for Working with Antimicrobial Resistance Data #
# #
# SOURCE #
# https://github.com/msberends/AMR #
# #
# LICENCE #
# (c) 2018-2022 Berends MS, Luz CF et al. #
# CITE AS #
# 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. #
# doi:10.18637/jss.v104.i03 #
# #
# Developed at the University of Groningen, the Netherlands, in #
# collaboration with non-profit organisations Certe Medical #
# Diagnostics & Advice, and University Medical Center Groningen. #
@ -178,7 +182,7 @@ format.bug_drug_combinations <- function(x,
...) {
meet_criteria(x, allow_class = "data.frame")
meet_criteria(translate_ab, allow_class = c("character", "logical"), has_length = 1, allow_NA = TRUE)
meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
language <- validate_language(language)
meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
meet_criteria(combine_SI, allow_class = "logical", has_length = 1)
meet_criteria(combine_IR, allow_class = "logical", has_length = 1)
@ -196,10 +200,10 @@ format.bug_drug_combinations <- function(x,
x <- data.frame(
mo = gsub("(.*)%%(.*)", "\\1", names(idx)),
ab = gsub("(.*)%%(.*)", "\\2", names(idx)),
S = sapply(idx, function(i) sum(x$S[i], na.rm = TRUE)),
I = sapply(idx, function(i) sum(x$I[i], na.rm = TRUE)),
R = sapply(idx, function(i) sum(x$R[i], na.rm = TRUE)),
total = sapply(idx, function(i) {
S = vapply(FUN.VALUE = double(1), idx, function(i) sum(x$S[i], na.rm = TRUE)),
I = vapply(FUN.VALUE = double(1), idx, function(i) sum(x$I[i], na.rm = TRUE)),
R = vapply(FUN.VALUE = double(1), idx, function(i) sum(x$R[i], na.rm = TRUE)),
total = vapply(FUN.VALUE = double(1), idx, function(i) {
sum(x$S[i], na.rm = TRUE) +
sum(x$I[i], na.rm = TRUE) +
sum(x$R[i], na.rm = TRUE)
@ -214,7 +218,7 @@ format.bug_drug_combinations <- function(x,
if (remove_intrinsic_resistant == TRUE) {
x <- subset(x, R != total)
}
if (combine_SI == TRUE | combine_IR == FALSE) {
if (combine_SI == TRUE || combine_IR == FALSE) {
x$isolates <- x$R
} else {
x$isolates <- x$R + x$I
@ -224,13 +228,13 @@ format.bug_drug_combinations <- function(x,
format <- tolower(format)
ab_txt <- rep(format, length(ab))
for (i in seq_len(length(ab_txt))) {
ab_txt[i] <- gsub("ab", as.character(as.ab(ab[i])), ab_txt[i])
ab_txt[i] <- gsub("cid", ab_cid(ab[i]), ab_txt[i])
ab_txt[i] <- gsub("group", ab_group(ab[i], language = language), ab_txt[i])
ab_txt[i] <- gsub("atc_group1", ab_atc_group1(ab[i], language = language), ab_txt[i])
ab_txt[i] <- gsub("atc_group2", ab_atc_group2(ab[i], language = language), ab_txt[i])
ab_txt[i] <- gsub("atc", ab_atc(ab[i], only_first = TRUE), ab_txt[i])
ab_txt[i] <- gsub("name", ab_name(ab[i], language = language), ab_txt[i])
ab_txt[i] <- gsub("ab", as.character(as.ab(ab[i])), ab_txt[i], fixed = TRUE)
ab_txt[i] <- gsub("cid", ab_cid(ab[i]), ab_txt[i], fixed = TRUE)
ab_txt[i] <- gsub("group", ab_group(ab[i], language = language), ab_txt[i], fixed = TRUE)
ab_txt[i] <- gsub("atc_group1", ab_atc_group1(ab[i], language = language), ab_txt[i], fixed = TRUE)
ab_txt[i] <- gsub("atc_group2", ab_atc_group2(ab[i], language = language), ab_txt[i], fixed = TRUE)
ab_txt[i] <- gsub("atc", ab_atc(ab[i], only_first = TRUE), ab_txt[i], fixed = TRUE)
ab_txt[i] <- gsub("name", ab_name(ab[i], language = language), ab_txt[i], fixed = TRUE)
ab_txt[i]
}
ab_txt
@ -317,7 +321,7 @@ format.bug_drug_combinations <- function(x,
}
if (remove_intrinsic_resistant == TRUE) {
y <- y[, !vapply(FUN.VALUE = logical(1), y, function(col) all(col %like% "100", na.rm = TRUE) & !any(is.na(col))), drop = FALSE]
y <- y[, !vapply(FUN.VALUE = logical(1), y, function(col) all(col %like% "100", na.rm = TRUE) & !anyNA(col)), drop = FALSE]
}
rownames(y) <- NULL