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(v2.1.1.9148) scale fix, antibiogram fix

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dr. M.S. (Matthijs) Berends
2025-02-15 12:38:29 +01:00
parent d94efb0f5e
commit 9d636983ac
12 changed files with 68 additions and 34 deletions
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4
R/aa_globals.R
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@ -179,12 +179,16 @@ globalVariables(c(
"microorganisms.codes",
"mo",
"n",
"n_susceptible",
"n_tested",
"n_total",
"name",
"new",
"numerator",
"observations",
"old",
"old_name",
"p_susceptible",
"pattern",
"R",
"rank_index",

46
R/antibiogram.R
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@ -441,7 +441,7 @@ antibiogram.default <- function(x,
x <- ascertain_sir_classes(x, "x")
meet_criteria(wisca, allow_class = "logical", has_length = 1)
if (isTRUE(wisca)) {
if (!missing(mo_transform)) {
if (!is.null(mo_transform)) {
warning_("WISCA must be based on the species level as WISCA parameters are based on this. For that reason, `mo_transform` will be ignored.")
}
mo_transform <- function(x) suppressMessages(suppressWarnings(paste(mo_genus(x, keep_synonyms = TRUE, language = NULL), mo_species(x, keep_synonyms = TRUE, language = NULL))))
@ -469,7 +469,7 @@ antibiogram.default <- function(x,
# try to find columns based on type
if (is.null(col_mo)) {
col_mo <- search_type_in_df(x = x, type = "mo", info = interactive())
col_mo <- search_type_in_df(x = x, type = "mo", info = info)
stop_if(is.null(col_mo), "`col_mo` must be set")
}
# transform MOs
@ -594,7 +594,7 @@ antibiogram.default <- function(x,
}
if (all(out$n_tested < minimum, na.rm = TRUE) && wisca == FALSE) {
warning_("All combinations had less than `minimum = ", minimum, "` results, returning an empty antibiogram")
return(as_original_data_class(data.frame(), class(out), extra_class = "antibiogram"))
return(as_original_data_class(data.frame(), class(x), extra_class = "antibiogram"))
} else if (any(out$n_tested < minimum, na.rm = TRUE)) {
out <- out %pm>%
# also for WISCA, refrain from anything below 15 isolates:
@ -612,7 +612,7 @@ antibiogram.default <- function(x,
}
if (NROW(out) == 0) {
return(as_original_data_class(data.frame(), class(out), extra_class = "antibiogram"))
return(as_original_data_class(data.frame(), class(x), extra_class = "antibiogram"))
}
out$p_susceptible <- out$n_susceptible / out$n_tested
@ -927,7 +927,6 @@ antibiogram.default <- function(x,
rownames(out) <- NULL
rownames(wisca_parameters) <- NULL
rownames(long_numeric) <- NULL
structure(out,
has_syndromic_group = has_syndromic_group,
combine_SI = combine_SI,
@ -943,7 +942,7 @@ antibiogram.default <- function(x,
#' @export
antibiogram.grouped_df <- function(x,
antibiotics = where(is.sir),
mo_transform = function (...) "no_mo",
mo_transform = NULL,
ab_transform = "name",
syndromic_group = NULL,
add_total_n = FALSE,
@ -960,6 +959,7 @@ antibiogram.grouped_df <- function(x,
conf_interval = 0.95,
interval_side = "two-tailed",
info = interactive()) {
stop_ifnot(is.null(mo_transform), "`mo_transform` must not be set if creating an antibiogram using a grouped tibble. The groups will become the variables over which the antimicrobials are calculated, which could include the pathogen information (though not necessary). Nonetheless, this makes `mo_transform` redundant.", call = FALSE)
stop_ifnot(is.null(syndromic_group), "`syndromic_group` must not be set if creating an antibiogram using a grouped tibble. The groups will become the variables over which the antimicrobials are calculated, making `syndromic_groups` redundant.", call = FALSE)
groups <- attributes(x)$groups
n_groups <- NROW(groups)
@ -969,16 +969,19 @@ antibiogram.grouped_df <- function(x,
title = paste("Calculating AMR for", n_groups, "groups"))
on.exit(close(progress))
out <- NULL
wisca_parameters <- NULL
long_numeric <- NULL
for (i in seq_len(n_groups)) {
if (i > 1) progress$tick()
progress$tick()
rows <- unlist(groups[i, ]$.rows)
if (length(rows) == 0) {
next
}
new_out <- antibiogram(as.data.frame(x)[rows, , drop = FALSE],
antibiotics = antibiotics,
mo_transform = function(x) "no_mo",
mo_transform = NULL,
ab_transform = ab_transform,
syndromic_group = NULL,
add_total_n = add_total_n,
@ -994,17 +997,15 @@ antibiogram.grouped_df <- function(x,
simulations = simulations,
conf_interval = conf_interval,
interval_side = interval_side,
info = i == 1 && info == TRUE)
info = FALSE)
new_wisca_parameters <- attributes(new_out)$wisca_parameters
new_long_numeric <- attributes(new_out)$long_numeric
if (i == 1) progress$tick()
if (NROW(new_out) == 0) {
next
}
# remove first column 'Pathogen' (in whatever language)
# remove first column 'Pathogen' (in whatever language), except WISCA since that never has Pathogen column
if (isFALSE(wisca)) {
new_out <- new_out[, -1, drop = FALSE]
new_long_numeric <- new_long_numeric[, -1, drop = FALSE]
@ -1037,17 +1038,17 @@ antibiogram.grouped_df <- function(x,
long_numeric <- rbind_AMR(long_numeric, new_long_numeric)
}
}
close(progress)
out <- structure(as_original_data_class(out, class(x), extra_class = "antibiogram"),
has_syndromic_group = FALSE,
combine_SI = isTRUE(combine_SI),
wisca = isTRUE(wisca),
conf_interval = conf_interval,
formatting_type = formatting_type,
wisca_parameters = as_original_data_class(wisca_parameters, class(x)),
long_numeric = as_original_data_class(long_numeric, class(x)))
structure(as_original_data_class(out, class(x), extra_class = "antibiogram"),
has_syndromic_group = FALSE,
combine_SI = isTRUE(combine_SI),
wisca = isTRUE(wisca),
conf_interval = conf_interval,
formatting_type = formatting_type,
wisca_parameters = as_original_data_class(wisca_parameters, class(x)),
long_numeric = as_original_data_class(long_numeric, class(x)))
}
#' @export
@ -1072,6 +1073,7 @@ wisca <- function(x,
antibiogram(x = x,
antibiotics = antibiotics,
ab_transform = ab_transform,
mo_transform = NULL,
syndromic_group = syndromic_group,
add_total_n = add_total_n,
only_all_tested = only_all_tested,

34
R/plotting.R
View File

@ -227,10 +227,16 @@
#' }
NULL
create_scale_mic <- function(aest, keep_operators, mic_range, ...) {
create_scale_mic <- function(aest, keep_operators, mic_range = NULL, ...) {
ggplot_fn <- getExportedValue(paste0("scale_", aest, "_continuous"),
ns = asNamespace("ggplot2"))
args <- list(...)
breaks_set <- args$breaks
if (!is.null(args$limits)) {
stop_ifnot(is.null(mic_range),
"In `scale_", aest, "_mic()`, `limits` cannot be combined with `mic_range`, as they working identically. Use `mic_range` OR `limits`.", call = FALSE)
mic_range <- args$limits
}
# do not take these arguments into account, as they will be overwritten and seem to allow weird behaviour
args[c("aesthetics", "trans", "transform", "transform_df", "breaks", "labels", "limits")] <- NULL
scale <- do.call(ggplot_fn, args)
@ -252,8 +258,30 @@ create_scale_mic <- function(aest, keep_operators, mic_range, ...) {
df[[aest]] <- self$`.values_log`
df
}
scale$breaks <- function(..., self) log2(as.mic(self$`.values_levels`))
scale$labels <- function(..., self) self$`.values_levels`
scale$breaks <- function(..., self) {
if (!is.null(breaks_set)) {
if (is.function(breaks_set)) {
breaks_set(...)
} else {
log2(as.mic(breaks_set))
}
} else {
log2(as.mic(self$`.values_levels`))
}
}
scale$labels <- function(..., self) {
if (is.null(breaks_set)) {
self$`.values_levels`
} else {
breaks <- tryCatch(scale$breaks(), error = function(e) NULL)
if (!is.null(breaks)) {
# for when breaks are set by the user
2 ^ breaks
} else {
self$`.values_levels`
}
}
}
scale$limits <- function(x, ..., self) {
rng <- range(log2(as.mic(self$`.values_levels`)))
# add 0.5 extra space