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(v1.2.0.9034) code cleaning

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dr. M.S. (Matthijs) Berends
2020-07-13 09:17:24 +02:00
parent c0cf7ab02b
commit 6ab468362d
36 changed files with 266 additions and 265 deletions
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38
R/mdro.R
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@ -117,7 +117,7 @@ mdro <- function(x,
# allow pct_required_classes = 75 -> pct_required_classes = 0.75
pct_required_classes <- pct_required_classes / 100
}
if (!is.null(list(...)$country)) {
warning("Using `country` is deprecated, use `guideline` instead. Please see ?mdro.", call. = FALSE)
guideline <- list(...)$country
@ -145,7 +145,7 @@ mdro <- function(x,
}
if (is.null(col_mo) & guideline$code == "tb") {
message(font_blue("NOTE: No column found as input for `col_mo`,",
font_bold("assuming all records contain", font_italic("Mycobacterium tuberculosis."))))
font_bold("assuming all records contain", font_italic("Mycobacterium tuberculosis."))))
x$mo <- as.mo("Mycobacterium tuberculosis")
col_mo <- "mo"
}
@ -470,7 +470,7 @@ mdro <- function(x,
}
x_transposed <- as.list(as.data.frame(t(x[, cols, drop = FALSE])))
row_filter <- sapply(x_transposed, function(y) search_function(y %in% search_result, na.rm = TRUE))
row_filter <- x[row_filter, "row_number", drop = TRUE]
row_filter <- x[which(row_filter), "row_number", drop = TRUE]
rows <- rows[rows %in% row_filter]
x[rows, "MDRO"] <<- to
x[rows, "reason"] <<- paste0(any_all, " of the required antibiotics ", ifelse(any_all == "any", "is", "are"), " R")
@ -492,23 +492,23 @@ mdro <- function(x,
if (verbose == TRUE) {
x[rows, "columns_nonsusceptible"] <<- sapply(rows,
function(row, group_vct = lst_vector) {
cols_nonsus <- sapply(x[row, group_vct, drop = FALSE], function(y) y %in% search_result)
paste(sort(names(cols_nonsus)[cols_nonsus]), collapse = ", ")
})
function(row, group_vct = lst_vector) {
cols_nonsus <- sapply(x[row, group_vct, drop = FALSE], function(y) y %in% search_result)
paste(sort(names(cols_nonsus)[cols_nonsus]), collapse = ", ")
})
}
x[rows, "classes_affected"] <<- sapply(rows,
function(row, group_tbl = lst) {
sum(sapply(group_tbl,
function(group) {
any(unlist(x[row, group[!is.na(group)], drop = TRUE]) %in% search_result, na.rm = TRUE)
}),
na.rm = TRUE)
})
function(row, group_tbl = lst) {
sum(sapply(group_tbl,
function(group) {
any(unlist(x[row, group[!is.na(group)], drop = TRUE]) %in% search_result, na.rm = TRUE)
}),
na.rm = TRUE)
})
# for PDR; all agents are R (or I if combine_SI = FALSE)
x_transposed <- as.list(as.data.frame(t(x[rows, lst_vector, drop = FALSE])))
row_filter <- sapply(x_transposed, function(y) all(y %in% search_result, na.rm = TRUE))
x[row_filter, "classes_affected"] <<- 999
x[which(row_filter), "classes_affected"] <<- 999
}
if (info == TRUE) {
@ -523,7 +523,7 @@ mdro <- function(x,
x$row_number <- seq_len(nrow(x))
x$reason <- paste0("not covered by ", toupper(guideline$code), " guideline")
x$columns_nonsusceptible <- ""
if (guideline$code == "cmi2012") {
# CMI, 2012 ---------------------------------------------------------------
# Non-susceptible = R and I
@ -718,7 +718,7 @@ mdro <- function(x,
x[which((x$classes_in_guideline - x$classes_affected) <= 2), "MDRO"] <- 3
if (verbose == TRUE) {
x[which(x$MDRO == 3), "reason"] <- paste0("less than 3 classes remain susceptible (", x$classes_in_guideline[which((x$classes_in_guideline - x$classes_affected) <= 2)] - x$classes_affected[which(x$MDRO == 3)],
" out of ", x$classes_in_guideline[which(x$MDRO == 3)], " classes)")
" out of ", x$classes_in_guideline[which(x$MDRO == 3)], " classes)")
}
# PDR (=4): all agents are R
@ -966,7 +966,7 @@ mdro <- function(x,
ab != "R"
}
}
x$mono_count <- 0
x[drug_is_R(INH), "mono_count"] <- x[drug_is_R(INH), "mono_count"] + 1
x[drug_is_R(RIF), "mono_count"] <- x[drug_is_R(RIF), "mono_count"] + 1
@ -1002,7 +1002,7 @@ mdro <- function(x,
# some more info on negative results
if (verbose == TRUE) {
if (guideline$code == "cmi2012") {
x[which(x$MDRO == 1 & !is.na(x$classes_affected)), "reason"] <- paste0(x$classes_affected[which(x$MDRO == 1 & !is.na(x$classes_affected))], " of ", x$classes_available[which(x$MDRO == 1 & !is.na(x$classes_affected))], " available classes contain R or I (3 required for MDR)")
x[which(x$MDRO == 1 & !is.na(x$classes_affected)), "reason"] <- paste0(x$classes_affected[which(x$MDRO == 1 & !is.na(x$classes_affected))], " of ", x$classes_available[which(x$MDRO == 1 & !is.na(x$classes_affected))], " available classes contain R or I (3 required for MDR)")
} else {
x[which(x$MDRO == 1), "reason"] <- "too few antibiotics are R"
}