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expert rules 12.0

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dr. M.S. (Matthijs) Berends
2022-11-14 15:20:39 +01:00
parent 7ca44fb756
commit f6862a139d
35 changed files with 433 additions and 128 deletions
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22
R/first_isolate.R
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@ -243,7 +243,7 @@ first_isolate <- function(x = NULL,
if (method == "phenotype-based" && !any_col_contains_rsi) {
method <- "episode-based"
}
if (info == TRUE && message_not_thrown_before("first_isolate", "method")) {
if (isTRUE(info) && message_not_thrown_before("first_isolate", "method")) {
message_(paste0(
"Determining first isolates ",
ifelse(method %in% c("episode-based", "phenotype-based"),
@ -353,7 +353,7 @@ first_isolate <- function(x = NULL,
testcodes_exclude <- NULL
}
# remove testcodes
if (!is.null(testcodes_exclude) && info == TRUE && message_not_thrown_before("first_isolate", "excludingtestcodes")) {
if (!is.null(testcodes_exclude) && isTRUE(info) && message_not_thrown_before("first_isolate", "excludingtestcodes")) {
message_("Excluding test codes: ", vector_and(testcodes_exclude, quotes = TRUE),
add_fn = font_black,
as_note = FALSE
@ -367,7 +367,7 @@ first_isolate <- function(x = NULL,
# filter on specimen group and keyantibiotics when they are filled in
if (!is.null(specimen_group)) {
check_columns_existance(col_specimen, x)
if (info == TRUE && message_not_thrown_before("first_isolate", "excludingspecimen")) {
if (isTRUE(info) && message_not_thrown_before("first_isolate", "excludingspecimen")) {
message_("Excluding other than specimen group '", specimen_group, "'",
add_fn = font_black,
as_note = FALSE
@ -411,7 +411,7 @@ first_isolate <- function(x = NULL,
# speed up - return immediately if obvious
if (abs(row.start) == Inf || abs(row.end) == Inf) {
if (info == TRUE) {
if (isTRUE(info)) {
message_("=> Found ", font_bold("no isolates"),
add_fn = font_black,
as_note = FALSE
@ -420,7 +420,7 @@ first_isolate <- function(x = NULL,
return(rep(FALSE, nrow(x)))
}
if (row.start == row.end) {
if (info == TRUE) {
if (isTRUE(info)) {
message_("=> Found ", font_bold("1 first isolate"), ", as the data only contained 1 row",
add_fn = font_black,
as_note = FALSE
@ -429,7 +429,7 @@ first_isolate <- function(x = NULL,
return(TRUE)
}
if (length(c(row.start:row.end)) == pm_n_distinct(x[c(row.start:row.end), col_mo, drop = TRUE])) {
if (info == TRUE) {
if (isTRUE(info)) {
message_("=> Found ", font_bold(paste(length(c(row.start:row.end)), "first isolates")),
", as all isolates were different microbial species",
add_fn = font_black,
@ -447,7 +447,7 @@ first_isolate <- function(x = NULL,
# Analysis of first isolate ----
if (!is.null(col_keyantimicrobials)) {
if (info == TRUE && message_not_thrown_before("first_isolate", "type")) {
if (isTRUE(info) && message_not_thrown_before("first_isolate", "type")) {
if (type == "keyantimicrobials") {
message_("Basing inclusion on key antimicrobials, ",
ifelse(ignore_I == FALSE, "not ", ""),
@ -533,7 +533,7 @@ first_isolate <- function(x = NULL,
decimal.mark <- getOption("OutDec")
big.mark <- ifelse(decimal.mark != ",", ",", ".")
if (info == TRUE) {
if (isTRUE(info)) {
# print group name if used in dplyr::group_by()
cur_group <- import_fn("cur_group", "dplyr", error_on_fail = FALSE)
if (!is.null(cur_group)) {
@ -558,7 +558,7 @@ first_isolate <- function(x = NULL,
}
# handle empty microorganisms
if (any(x$newvar_mo == "UNKNOWN", na.rm = TRUE) && info == TRUE) {
if (any(x$newvar_mo == "UNKNOWN", na.rm = TRUE) && isTRUE(info)) {
message_(
ifelse(include_unknown == TRUE, "Included ", "Excluded "),
format(sum(x$newvar_mo == "UNKNOWN", na.rm = TRUE),
@ -570,7 +570,7 @@ first_isolate <- function(x = NULL,
x[which(x$newvar_mo == "UNKNOWN"), "newvar_first_isolate"] <- include_unknown
# exclude all NAs
if (anyNA(x$newvar_mo) && info == TRUE) {
if (anyNA(x$newvar_mo) && isTRUE(info)) {
message_(
"Excluded ", format(sum(is.na(x$newvar_mo), na.rm = TRUE),
decimal.mark = decimal.mark, big.mark = big.mark
@ -594,7 +594,7 @@ first_isolate <- function(x = NULL,
x <- x[order(x$newvar_row_index), , drop = FALSE]
rownames(x) <- NULL
if (info == TRUE) {
if (isTRUE(info)) {
n_found <- sum(x$newvar_first_isolate, na.rm = TRUE)
p_found_total <- percentage(n_found / nrow(x[which(!is.na(x$newvar_mo)), , drop = FALSE]), digits = 1)
p_found_scope <- percentage(n_found / scope.size, digits = 1)