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support veterinary MIC/disk translation

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dr. M.S. (Matthijs) Berends
2024-02-24 15:16:52 +01:00
parent 74ea6c8c60
commit 7be4dabbc0
69 changed files with 34521 additions and 30207 deletions
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21
R/aa_helper_functions.R
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@@ -237,7 +237,7 @@ addin_insert_like <- function() {
}
}
search_type_in_df <- function(x, type, info = TRUE) {
search_type_in_df <- function(x, type, info = TRUE, add_col_prefix = TRUE) {
meet_criteria(x, allow_class = "data.frame")
meet_criteria(type, allow_class = "character", has_length = 1)
@@ -280,7 +280,7 @@ search_type_in_df <- function(x, type, info = TRUE) {
if (!inherits(pm_pull(x, found), c("Date", "POSIXct"))) {
stop(
font_red(paste0(
"Found column '", font_bold(found), "' to be used as input for `col_", type,
"Found column '", font_bold(found), "' to be used as input for `", ifelse(add_col_prefix, "col_", ""), type,
"`, but this column contains no valid dates. Transform its values to valid dates first."
)),
call. = FALSE
@@ -311,6 +311,14 @@ search_type_in_df <- function(x, type, info = TRUE) {
found <- sort(colnames(x)[colnames_formatted %like_case% "^(specimen)"])
}
}
# -- host (animals)
if (type == "host") {
if (any(colnames_formatted %like_case% "^(host|animal)")) {
found <- sort(colnames(x)[colnames_formatted %like_case% "^(host|animal)"])
} else if (any(colnames_formatted %like_case% "((^|[^A-Za-z])host($|[^A-Za-z])|animal)")) {
found <- sort(colnames(x)[colnames_formatted %like_case% "((^|[^A-Za-z])host($|[^A-Za-z])|animal)"])
}
}
# -- UTI (urinary tract infection)
if (type == "uti") {
if (any(colnames_formatted == "uti")) {
@@ -321,7 +329,7 @@ search_type_in_df <- function(x, type, info = TRUE) {
if (!is.null(found)) {
# this column should contain logicals
if (!is.logical(x[, found, drop = TRUE])) {
message_("Column '", font_bold(found), "' found as input for `col_", type,
message_("Column '", font_bold(found), "' found as input for `", ifelse(add_col_prefix, "col_", ""), type,
"`, but this column does not contain 'logical' values (TRUE/FALSE) and was ignored.",
add_fn = font_red
)
@@ -334,9 +342,9 @@ search_type_in_df <- function(x, type, info = TRUE) {
if (!is.null(found) && isTRUE(info)) {
if (message_not_thrown_before("search_in_type", type)) {
msg <- paste0("Using column '", font_bold(found), "' as input for `col_", type, "`.")
msg <- paste0("Using column '", font_bold(found), "' as input for `", ifelse(add_col_prefix, "col_", ""), type, "`.")
if (type %in% c("keyantibiotics", "keyantimicrobials", "specimen")) {
msg <- paste(msg, "Use", font_bold(paste0("col_", type), "= FALSE"), "to prevent this.")
msg <- paste(msg, "Use", font_bold(paste0(ifelse(add_col_prefix, "col_", ""), type), "= FALSE"), "to prevent this.")
}
message_(msg)
}
@@ -456,7 +464,8 @@ word_wrap <- function(...,
ops <- "([,./><\\]\\[])"
msg <- gsub(paste0(ops, " ", ops), "\\1\\2", msg, perl = TRUE)
# we need to correct for already applied style, that adds text like "\033[31m\"
msg_stripped <- font_stripstyle(msg)
msg_stripped <- gsub("(.*)?\\033\\]8;;.*\\a(.*?)\\033\\]8;;\\a(.*)", "\\1\\2\\3", msg, perl = TRUE) # for font_url()
msg_stripped <- font_stripstyle(msg_stripped)
# where are the spaces now?
msg_stripped_wrapped <- paste0(
strwrap(msg_stripped,

22
R/aa_options.R
View File

@@ -31,19 +31,19 @@
#'
#' This is an overview of all the package-specific [options()] you can set in the `AMR` package.
#' @section Options:
#' * `AMR_custom_ab` \cr Allows to use custom antimicrobial drugs with this package. This is explained in [add_custom_antimicrobials()].
#' * `AMR_custom_mo` \cr Allows to use custom microorganisms with this package. This is explained in [add_custom_microorganisms()].
#' * `AMR_eucastrules` \cr Used for setting the default types of rules for [eucast_rules()] function, must be one or more of: `"breakpoints"`, `"expert"`, `"other"`, `"custom"`, `"all"`, and defaults to `c("breakpoints", "expert")`.
#' * `AMR_guideline` \cr Used for setting the default guideline for interpreting MIC values and disk diffusion diameters with [as.sir()]. Can be only the guideline name (e.g., `"CLSI"`) or the name with a year (e.g. `"CLSI 2019"`). The default to the latest implemented EUCAST guideline, currently \code{"`r clinical_breakpoints$guideline[1]`"}. Supported guideline are currently EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`).
#' * `AMR_breakpoint_type` \cr A [character] to use in [as.sir()], to indicate which breakpoint type to use. This must be either `r vector_or(clinical_breakpoints$type)`.
#' * `AMR_cleaning_regex` \cr A [regular expression][base::regex] (case-insensitive) to use in [as.mo()] and all [`mo_*`][mo_property()] functions, to clean the user input. The default is the outcome of [mo_cleaning_regex()], which removes texts between brackets and texts such as "species" and "serovar".
#' * `AMR_custom_ab` \cr A file location to an RDS file, to use custom antimicrobial drugs with this package. This is explained in [add_custom_antimicrobials()].
#' * `AMR_custom_mo` \cr A file location to an RDS file, to use custom microorganisms with this package. This is explained in [add_custom_microorganisms()].
#' * `AMR_eucastrules` \cr A [character] to set the default types of rules for [eucast_rules()] function, must be one or more of: `"breakpoints"`, `"expert"`, `"other"`, `"custom"`, `"all"`, and defaults to `c("breakpoints", "expert")`.
#' * `AMR_guideline` \cr A [character] to set the default guideline for interpreting MIC values and disk diffusion diameters with [as.sir()]. Can be only the guideline name (e.g., `"CLSI"`) or the name with a year (e.g. `"CLSI 2019"`). The default to the latest implemented EUCAST guideline, currently \code{"`r clinical_breakpoints$guideline[1]`"}. Supported guideline are currently EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`).
#' * `AMR_ignore_pattern` \cr A [regular expression][base::regex] to ignore (i.e., make `NA`) any match given in [as.mo()] and all [`mo_*`][mo_property()] functions.
#' * `AMR_include_PKPD` \cr A [logical] to use in [as.sir()], to indicate that PK/PD clinical breakpoints must be applied as a last resort - the default is `TRUE`.
#' * `AMR_ecoff` \cr A [logical] use in [as.sir()], to indicate that ECOFF (Epidemiological Cut-Off) values must be used - the default is `FALSE`.
#' * `AMR_include_screening` \cr A [logical] to use in [as.sir()], to indicate that clinical breakpoints for screening are allowed - the default is `FALSE`.
#' * `AMR_keep_synonyms` \cr A [logical] to use in [as.mo()] and all [`mo_*`][mo_property()] functions, to indicate if old, previously valid taxonomic names must be preserved and not be corrected to currently accepted names. The default is `FALSE`.
#' * `AMR_cleaning_regex` \cr A [regular expression][base::regex] (case-insensitive) to use in [as.mo()] and all [`mo_*`][mo_property()] functions, to clean the user input. The default is the outcome of [mo_cleaning_regex()], which removes texts between brackets and texts such as "species" and "serovar".
#' * `AMR_locale` \cr A language to use for the `AMR` package, can be one of these supported language names or ISO-639-1 codes: `r vector_or(paste0(sapply(LANGUAGES_SUPPORTED_NAMES, function(x) x[[1]]), " (" , LANGUAGES_SUPPORTED, ")"), quotes = FALSE, sort = FALSE)`. The default is the current system language (if supported).
#' * `AMR_locale` \cr A [character] to set the language for the `AMR` package, can be one of these supported language names or ISO-639-1 codes: `r vector_or(paste0(sapply(LANGUAGES_SUPPORTED_NAMES, function(x) x[[1]]), " (" , LANGUAGES_SUPPORTED, ")"), quotes = FALSE, sort = FALSE)`. The default is the current system language (if supported, English otherwise).
#' * `AMR_mo_source` \cr A file location for a manual code list to be used in [as.mo()] and all [`mo_*`][mo_property()] functions. This is explained in [set_mo_source()].
#'
#'
#' @section Saving Settings Between Sessions:
#' Settings in \R are not saved globally and are thus lost when \R is exited. You can save your options to your own `.Rprofile` file, which is a user-specific file. You can edit it using:
#'
@@ -51,18 +51,18 @@
#' utils::file.edit("~/.Rprofile")
#' ```
#'
#' In this file, you can set options such as:
#' In this file, you can set options such as...
#'
#' ```r
#' options(AMR_locale = "pt")
#' options(AMR_include_PKPD = TRUE)
#' ```
#'
#' to add Portuguese language support of antibiotics, and allow PK/PD rules when interpreting MIC values with [as.sir()].
#' ...to add Portuguese language support of antibiotics, and allow PK/PD rules when interpreting MIC values with [as.sir()].
#'
#' ### Share Options Within Team
#'
#' For a more global approach, e.g. within a data team, save an options file to a remote file location, such as a shared network drive. This would work in this way:
#' For a more global approach, e.g. within a (data) team, save an options file to a remote file location, such as a shared network drive, and have each user read in this file automatically at start-up. This would work in this way:
#'
#' 1. Save a plain text file to e.g. "X:/team_folder/R_options.R" and fill it with preferred settings.
#'

4
R/ab.R
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@@ -117,8 +117,8 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
# remove diacritics
x <- iconv(x, from = "UTF-8", to = "ASCII//TRANSLIT")
x <- gsub('"', "", x, fixed = TRUE)
x <- gsub("(specimen|specimen date|specimen_date|spec_date|gender|^dates?$)", "", x, ignore.case = TRUE, perl = TRUE)
# penicillin is a special case: we call it so, but then mean benzylpenicillin
x <- gsub("(specimen|specimen date|specimen_date|spec_date|gender|^dates?$|animal|host($|[a-z]))", "", x, ignore.case = TRUE, perl = TRUE)
# penicillin is a special case: we call it so, but then most often mean benzylpenicillin
x[x %like_case% "^PENICILLIN" & x %unlike_case% "[ /+-]"] <- "benzylpenicillin"
x_bak_clean <- x
if (already_regex == FALSE) {

5
R/ab_property.R
View File

@@ -310,7 +310,10 @@ ab_url <- function(x, open = FALSE, ...) {
ab <- as.ab(x = x, ...)
atcs <- ab_atc(ab, only_first = TRUE)
u <- paste0("https://www.whocc.no/atc_ddd_index/?code=", atcs, "&showdescription=no")
u <- character(length(atcs))
# veterinary codes
u[atcs %like% "^Q"] <- paste0("https://www.whocc.no/atcvet/atcvet_index/?code=", atcs[atcs %like% "^Q"], "&showdescription=no")
u[atcs %unlike% "^Q"] <- paste0("https://www.whocc.no/atc_ddd_index/?code=", atcs[atcs %unlike% "^Q"], "&showdescription=no")
u[is.na(atcs)] <- NA_character_
names(u) <- ab_name(ab)

6
R/ab_selectors.R
View File

@@ -541,10 +541,10 @@ not_intrinsic_resistant <- function(only_sir_columns = FALSE, col_mo = NULL, ver
),
error = function(e) stop_("in not_intrinsic_resistant(): ", e$message, call = FALSE)
)
agents <- ab_in_data[ab_in_data %in% names(vars_df_R[which(vars_df_R)])]
if (length(agents) > 0 &&
message_not_thrown_before("not_intrinsic_resistant", sort(agents))) {
message_not_thrown_before("not_intrinsic_resistant", sort(agents))) {
agents_formatted <- paste0("'", font_bold(agents, collapse = NULL), "'")
agents_names <- ab_name(names(agents), tolower = TRUE, language = NULL)
need_name <- generalise_antibiotic_name(agents) != generalise_antibiotic_name(agents_names)
@@ -555,7 +555,7 @@ not_intrinsic_resistant <- function(only_sir_columns = FALSE, col_mo = NULL, ver
vector_and(agents_formatted, quotes = FALSE, sort = FALSE)
)
}
vars_df_R <- names(vars_df_R)[which(!vars_df_R)]
# find columns that are abx, but also intrinsic R
out <- unname(intersect(ab_in_data, vars_df_R))

14
R/atc_online.R
View File

@@ -83,7 +83,7 @@ atc_online_property <- function(atc_code,
administration = "O",
url = "https://www.whocc.no/atc_ddd_index/?code=%s&showdescription=no",
url_vet = "https://www.whocc.no/atcvet/atcvet_index/?code=%s&showdescription=no") {
meet_criteria(atc_code, allow_class = "character")
meet_criteria(atc_code, allow_class = "character", allow_NA = TRUE)
meet_criteria(property, allow_class = "character", has_length = 1, is_in = c("ATC", "Name", "DDD", "U", "unit", "Adm.R", "Note", "groups"), ignore.case = TRUE)
meet_criteria(administration, allow_class = "character", has_length = 1)
meet_criteria(url, allow_class = "character", has_length = 1, looks_like = "https?://")
@@ -128,6 +128,10 @@ atc_online_property <- function(atc_code,
for (i in seq_len(length(atc_code))) {
progress$tick()
if (is.na(atc_code[i])) {
next
}
if (atc_code[i] %like% "^Q") {
# veterinary drugs, ATC_vet codes start with a "Q"
@@ -176,7 +180,7 @@ atc_online_property <- function(atc_code,
colnames(out) <- gsub("^atc.*", "atc", tolower(colnames(out)))
if (length(out) == 0) {
warning_("in `atc_online_property()`: ATC not found: ", atc_code[i], ". Please check ", atc_url, ".")
message_("in `atc_online_property()`: no properties found for ATC ", atc_code[i], ". Please check ", font_url(atc_url, "this WHOCC webpage"), ".")
returnvalue[i] <- NA
next
}
@@ -209,20 +213,20 @@ atc_online_property <- function(atc_code,
#' @rdname atc_online
#' @export
atc_online_groups <- function(atc_code, ...) {
meet_criteria(atc_code, allow_class = "character")
meet_criteria(atc_code, allow_class = "character", allow_NA = TRUE)
atc_online_property(atc_code = atc_code, property = "groups", ...)
}
#' @rdname atc_online
#' @export
atc_online_ddd <- function(atc_code, ...) {
meet_criteria(atc_code, allow_class = "character")
meet_criteria(atc_code, allow_class = "character", allow_NA = TRUE)
atc_online_property(atc_code = atc_code, property = "ddd", ...)
}
#' @rdname atc_online
#' @export
atc_online_ddd_units <- function(atc_code, ...) {
meet_criteria(atc_code, allow_class = "character")
meet_criteria(atc_code, allow_class = "character", allow_NA = TRUE)
atc_online_property(atc_code = atc_code, property = "unit", ...)
}

11
R/data.R
View File

@@ -100,7 +100,7 @@
#' - `gbif_parent`\cr GBIF identifier of the parent taxon
#' - `gbif_renamed_to`\cr GBIF identifier of the currently valid taxon
#' - `source`\cr Either `r vector_or(microorganisms$source)` (see *Source*)
#' - `prevalence`\cr Prevalence of the microorganism according to Bartlett *et al.* (2022, \doi{10.1099/mic.0.001269}), see [mo_matching_score()] for the full explanation
#' - `prevalence`\cr Prevalence of the microorganism based on Bartlett *et al.* (2022, \doi{10.1099/mic.0.001269}), see [mo_matching_score()] for the full explanation
#' - `snomed`\cr Systematized Nomenclature of Medicine (SNOMED) code of the microorganism, version of `r documentation_date(TAXONOMY_VERSION$SNOMED$accessed_date)` (see *Source*). Use [mo_snomed()] to retrieve it quickly, see [mo_property()].
#' @details
#' Please note that entries are only based on the List of Prokaryotic names with Standing in Nomenclature (LPSN) and the Global Biodiversity Information Facility (GBIF) (see below). Since these sources incorporate entries based on (recent) publications in the International Journal of Systematic and Evolutionary Microbiology (IJSEM), it can happen that the year of publication is sometimes later than one might expect.
@@ -262,10 +262,17 @@
#' Data Set with Clinical Breakpoints for SIR Interpretation
#'
#' Data set containing clinical breakpoints to interpret MIC and disk diffusion to SIR values, according to international guidelines. Currently implemented guidelines are EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`). Use [as.sir()] to transform MICs or disks measurements to SIR values.
#' @description Data set containing clinical breakpoints to interpret MIC and disk diffusion to SIR values, according to international guidelines. This dataset contain breakpoints for humans, `r length(unique(clinical_breakpoints$host[!clinical_breakpoints$host %in% clinical_breakpoints$type]))` different animal groups, and ECOFFs.
#'
#' Currently available breakpoint guidelines for **clinical microbiology** are EUCAST `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "human")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "human")$guideline)))` and CLSI `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "human")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "human")$guideline)))`.
#'
#' Currently available breakpoint guidelines for **veterinary microbiology** are EUCAST `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "animal")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "animal")$guideline)))` and CLSI `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "animal")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "animal")$guideline)))`.
#'
#' Use [as.sir()] to transform MICs or disks measurements to SIR values.
#' @format A [tibble][tibble::tibble] with `r format(nrow(clinical_breakpoints), big.mark = " ")` observations and `r ncol(clinical_breakpoints)` variables:
#' - `guideline`\cr Name of the guideline
#' - `type`\cr Breakpoint type, either `r vector_or(clinical_breakpoints$type)`
#' - `host`\cr Host of infectious agent. This is mostly useful for veterinary breakpoints and is either `r vector_or(clinical_breakpoints$host)`
#' - `method`\cr Testing method, either `r vector_or(clinical_breakpoints$method)`
#' - `site`\cr Body site for which the breakpoint must be applied, e.g. "Oral" or "Respiratory"
#' - `mo`\cr Microbial ID, see [as.mo()]

77
R/mic.R
View File

@@ -27,48 +27,22 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
# these are allowed MIC values and will become [factor] levels
operators <- c("<", "<=", "", ">=", ">")
# these are allowed MIC values and will become factor levels
VALID_MIC_LEVELS <- c(
c(t(vapply(
FUN.VALUE = character(6), operators,
function(x) paste0(x, "0.000", c(1:4, 6, 8))
))),
c(t(vapply(
FUN.VALUE = character(90), operators,
function(x) paste0(x, "0.00", c(1:9, 11:19, 21:29, 31:39, 41:49, 51:59, 61:69, 71:79, 81:89, 91:99))
))),
unique(c(t(vapply(
FUN.VALUE = character(106), operators,
function(x) {
paste0(x, sort(as.double(paste0(
"0.0",
sort(c(1:99, 125, 128, 156, 165, 256, 512, 625))
))))
}
)))),
unique(c(t(vapply(
FUN.VALUE = character(103), operators,
function(x) {
paste0(x, sort(as.double(paste0(
"0.",
c(1:99, 125, 128, 256, 512)
))))
}
)))),
c(t(vapply(
FUN.VALUE = character(10), operators,
function(x) paste0(x, sort(c(1:9, 1.5)))
))),
c(t(vapply(
FUN.VALUE = character(45), operators,
function(x) paste0(x, c(10:98)[9:98 %% 2 == TRUE])
))),
unique(c(t(vapply(
FUN.VALUE = character(22), operators,
function(x) paste0(x, sort(c(2^c(7:12), 192 * c(1:5), 80 * c(2:12))))
))))
as.double(paste0("0.000", c(1:9))),
as.double(paste0("0.00", c(1:99, 1953125, 390625, 78125))),
as.double(paste0("0.0", c(1:99, 125, 128, 156, 165, 256, 512, 625, 3125, 15625))),
as.double(paste0("0.", c(1:99, 125, 128, 256, 512))),
1:9, 1.5,
c(10:98)[9:98 %% 2 == TRUE],
2^c(7:12), 192 * c(1:5), 80 * c(2:12)
)
VALID_MIC_LEVELS <- trimws(gsub("[.]?0+$", "", format(unique(sort(VALID_MIC_LEVELS)), scientific = FALSE), perl = TRUE))
operators <- c("<", "<=", "", ">=", ">")
VALID_MIC_LEVELS <- c(t(vapply(FUN.VALUE = character(length(VALID_MIC_LEVELS)),
c("<", "<=", "", ">=", ">"),
paste0,
VALID_MIC_LEVELS)))
#' Transform Input to Minimum Inhibitory Concentrations (MIC)
#'
@@ -116,16 +90,16 @@ VALID_MIC_LEVELS <- c(
#' #> 10 16 A
#' ```
#'
#' The following [generic functions][groupGeneric()] are implemented for the MIC class: `!`, `!=`, `%%`, `%/%`, `&`, `*`, `+`, `-`, `/`, `<`, `<=`, `==`, `>`, `>=`, `^`, `|`, [abs()], [acos()], [acosh()], [all()], [any()], [asin()], [asinh()], [atan()], [atanh()], [ceiling()], [cos()], [cosh()], [cospi()], [cummax()], [cummin()], [cumprod()], [cumsum()], [digamma()], [exp()], [expm1()], [floor()], [gamma()], [lgamma()], [log()], [log1p()], [log2()], [log10()], [max()], [mean()], [min()], [prod()], [range()], [round()], [sign()], [signif()], [sin()], [sinh()], [sinpi()], [sqrt()], [sum()], [tan()], [tanh()], [tanpi()], [trigamma()] and [trunc()]. Some functions of the `stats` package are also implemented: [median()], [quantile()], [mad()], [IQR()], [fivenum()]. Also, [boxplot.stats()] is supported. Since [sd()] and [var()] are non-generic functions, these could not be extended. Use [mad()] as an alternative, or use e.g. `sd(as.numeric(x))` where `x` is your vector of MIC values.
#' All so-called [group generic functions][groupGeneric()] are implemented for the MIC class (such as `!`, `!=`, `<`, `>=`, [exp()], [log2()]). Some functions of the `stats` package are also implemented (such as [quantile()], [median()], [fivenum()]). Since [sd()] and [var()] are non-generic functions, these could not be extended. Use [mad()] as an alternative, or use e.g. `sd(as.numeric(x))` where `x` is your vector of MIC values.
#'
#' Using [as.double()] or [as.numeric()] on MIC values will remove the operators and return a numeric vector. Do **not** use [as.integer()] on MIC values as by the \R convention on [factor]s, it will return the index of the factor levels (which is often useless for regular users).
#'
#' Use [droplevels()] to drop unused levels. At default, it will return a plain factor. Use `droplevels(..., as.mic = TRUE)` to maintain the `mic` class.
#'
#' With [rescale_mic()], existing MIC ranges can be rescaled to a defined range of MIC values. This can be useful to better compare MIC distributions.
#' With [limit_mic_range()], existing MIC ranges can be limited to a defined range of MIC values. This can be useful to better compare MIC distributions.
#'
#' For `ggplot2`, use one of the [`scale_*_mic()`][scale_x_mic()] functions to plot MIC values. They allows custom MIC ranges and to plot intermediate log2 levels for missing MIC values.
#' @return Ordered [factor] with additional class [`mic`], that in mathematical operations acts as decimal numbers. Bare in mind that the outcome of any mathematical operation on MICs will return a [numeric] value.
#' @return Ordered [factor] with additional class [`mic`], that in mathematical operations acts as a [numeric] vector. Bear in mind that the outcome of any mathematical operation on MICs will return a [numeric] value.
#' @aliases mic
#' @export
#' @seealso [as.sir()]
@@ -142,8 +116,8 @@ VALID_MIC_LEVELS <- c(
#' quantile(mic_data)
#' all(mic_data < 512)
#'
#' # rescale MICs using rescale_mic()
#' rescale_mic(mic_data, mic_range = c(4, 16))
#' # limit MICs using limit_mic_range()
#' limit_mic_range(mic_data, mic_range = c(4, 16))
#'
#' # interpret MIC values
#' as.sir(
@@ -185,15 +159,16 @@ as.mic <- function(x, na.rm = FALSE, keep_operators = "all") {
x.bak <- NULL
if (is.numeric(x)) {
x.bak <- format(x, scientific = FALSE)
# MICs never need more than 4 decimals, so:
x <- format(round(x, 4), scientific = FALSE)
# MICs never have more than 9 decimals, so:
x <- format(round(x, 9), scientific = FALSE)
} else {
x <- as.character(unlist(x))
}
if (isTRUE(na.rm)) {
x <- x[!is.na(x)]
}
x[trimws2(x) == ""] <- NA
x <- trimws2(x)
x[x == ""] <- NA
if (is.null(x.bak)) {
x.bak <- x
}
@@ -289,12 +264,12 @@ NA_mic_ <- set_clean_class(factor(NA, levels = VALID_MIC_LEVELS, ordered = TRUE)
)
#' @rdname as.mic
#' @param mic_range a manual range to plot the MIC values, e.g., `mic_range = c(0.001, 32)`. Use `NA` to set no limit on one side, e.g., `mic_range = c(NA, 32)`.
#' @param mic_range a manual range to limit the MIC values, e.g., `mic_range = c(0.001, 32)`. Use `NA` to set no limit on one side, e.g., `mic_range = c(NA, 32)`.
#' @export
rescale_mic <- function(x, mic_range, keep_operators = "edges", as.mic = TRUE) {
limit_mic_range <- function(x, mic_range, keep_operators = "edges", as.mic = TRUE) {
meet_criteria(mic_range, allow_class = c("numeric", "integer", "logical"), has_length = 2, allow_NA = TRUE, allow_NULL = TRUE)
stop_ifnot(all(mic_range %in% c(VALID_MIC_LEVELS, NA)),
"Values in `mic_range` must be valid MIC values. Unvalid: ", vector_and(mic_range[mic_range %in% c(levels(as.mic(1)), NA)]))
"Values in `mic_range` must be valid MIC values. Unvalid: ", vector_and(mic_range[mic_range %in% c(VALID_MIC_LEVELS, NA)]))
x <- as.mic(x)
if (is.null(mic_range)) {
mic_range <- c(NA, NA)

2
R/mo.R
View File

@@ -250,7 +250,7 @@ as.mo <- function(x,
x_unique <- unique(x[is.na(out) & !is.na(x)])
# set up progress bar
progress <- progress_ticker(n = length(x_unique), n_min = 10, print = info)
progress <- progress_ticker(n = length(x_unique), n_min = 10, print = info, title = "Converting microorganism input")
on.exit(close(progress))
msg <- character(0)

2
R/mo_property.R
View File

@@ -245,7 +245,7 @@ mo_shortname <- function(x, language = get_AMR_locale(), keep_synonyms = getOpti
# unknown species etc.
shortnames[shortnames %like% "unknown"] <- paste0("(", trimws2(gsub("[^a-zA-Z -]", "", shortnames[shortnames %like% "unknown"], perl = TRUE)), ")")
shortnames[mo_rank(x.mo) %in% c("kingdom", "phylum", "class", "order", "family")] <- mo_name(x.mo, language = NULL, keep_synonyms = keep_synonyms)
shortnames[mo_rank(x.mo) %in% c("kingdom", "phylum", "class", "order", "family")] <- mo_name(x.mo[mo_rank(x.mo) %in% c("kingdom", "phylum", "class", "order", "family")], language = NULL, keep_synonyms = keep_synonyms)
shortnames[is.na(x.mo)] <- NA_character_
load_mo_uncertainties(metadata)

11
R/mo_source.R
View File

@@ -125,14 +125,13 @@
#' If the original file (in the previous case an Excel file) is moved or deleted, the `mo_source.rds` file will be removed upon the next use of [as.mo()] or any [`mo_*`][mo_property()] function.
#' @export
set_mo_source <- function(path, destination = getOption("AMR_mo_source", "~/mo_source.rds")) {
stop_ifnot(interactive(), "this function can only be used in interactive mode, since it must ask for the user's permission to write a file to their file system.")
meet_criteria(path, allow_class = "character", has_length = 1, allow_NULL = TRUE)
meet_criteria(destination, allow_class = "character", has_length = 1)
stop_ifnot(destination %like% "[.]rds$", "the `destination` must be a file location with file extension .rds.")
mo_source_destination <- path.expand(destination)
stop_ifnot(interactive(), "this function can only be used in interactive mode, since it must ask for the user's permission to write a file to their file system.")
if (is.null(path) || path %in% c(FALSE, "")) {
AMR_env$mo_source <- NULL
if (file.exists(mo_source_destination)) {
@@ -247,6 +246,12 @@ get_mo_source <- function(destination = getOption("AMR_mo_source", "~/mo_source.
}
return(NULL)
}
if (destination %unlike% "[.]rds$") {
current_ext <- regexpr("\\.([[:alnum:]]+)$", destination)
current_ext <- ifelse(current_ext > -1L, substring(destination, current_ext + 1L), "")
vowel <- ifelse(current_ext %like% "^[AEFHILMNORSX]", "n", "")
stop_("The AMR mo source must be an RDS file, not a", vowel, " ", toupper(current_ext), " file. If `\"", basename(destination), "\"` was meant as your input file, use `set_mo_source()` on this file. In any case, the option `AMR_mo_source` must be set to another path.")
}
if (is.null(AMR_env$mo_source)) {
AMR_env$mo_source <- readRDS_AMR(path.expand(destination))
}

8
R/plot.R
View File

@@ -117,7 +117,7 @@ scale_x_mic <- function(keep_operators = "edges", mic_range = NULL, drop = FALSE
meet_criteria(drop, allow_class = "logical", has_length = 1)
scale <- ggplot2::scale_x_discrete(drop = drop, ...)
scale$transform <- function(x, keep_ops = keep_operators, mic_rng = mic_range) {
rescale_mic(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
limit_mic_range(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
}
scale
}
@@ -130,7 +130,7 @@ scale_y_mic <- function(keep_operators = "edges", mic_range = NULL, drop = FALSE
meet_criteria(drop, allow_class = "logical", has_length = 1)
scale <- ggplot2::scale_y_discrete(drop = drop, ...)
scale$transform <- function(x, keep_ops = keep_operators, mic_rng = mic_range) {
rescale_mic(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
limit_mic_range(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
}
scale
}
@@ -143,7 +143,7 @@ scale_colour_mic <- function(keep_operators = "edges", mic_range = NULL, drop =
meet_criteria(drop, allow_class = "logical", has_length = 1)
scale <- ggplot2::scale_colour_discrete(drop = drop, ...)
scale$transform <- function(x, keep_ops = keep_operators, mic_rng = mic_range) {
rescale_mic(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
limit_mic_range(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
}
scale
}
@@ -156,7 +156,7 @@ scale_fill_mic <- function(keep_operators = "edges", mic_range = NULL, drop = FA
meet_criteria(drop, allow_class = "logical", has_length = 1)
scale <- ggplot2::scale_fill_discrete(drop = drop, ...)
scale$transform <- function(x, keep_ops = keep_operators, mic_rng = mic_range) {
rescale_mic(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
limit_mic_range(x = x, keep_operators = keep_ops, mic_range = mic_rng, as.mic = FALSE)
}
scale
}

175
R/sir.R
View File

@@ -29,10 +29,13 @@
#' Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data
#'
#' @description Interpret minimum inhibitory concentration (MIC) values and disk diffusion diameters according to EUCAST or CLSI, or clean up existing SIR values. This transforms the input to a new class [`sir`], which is an ordered [factor] with levels `S < I < R`.
#' @description Clean up existing SIR values, or interpret minimum inhibitory concentration (MIC) values and disk diffusion diameters according to EUCAST or CLSI. [as.sir()] transforms the input to a new class [`sir`], which is an ordered [factor] with levels `S < I < R`.
#'
#' Currently breakpoints are available:
#' - For **clinical microbiology** from EUCAST `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "human")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "human")$guideline)))` and CLSI `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "human")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "human")$guideline)))`;
#' - For **veterinary microbiology** from EUCAST `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "animal")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "animal")$guideline)))` and CLSI `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "animal")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "animal")$guideline)))`;
#' - ECOFFs (Epidemiological cut-off values) from EUCAST `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "ECOFF")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "ECOFF")$guideline)))` and CLSI `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "ECOFF")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "ECOFF")$guideline)))`.
#'
#' Currently available **breakpoint guidelines** are EUCAST `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))` and CLSI `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`, and available **breakpoint types** are `r vector_and(clinical_breakpoints$type)`.
#'
#' All breakpoints used for interpretation are publicly available in the [clinical_breakpoints] data set.
#' @rdname as.sir
#' @param x vector of values (for class [`mic`]: MIC values in mg/L, for class [`disk`]: a disk diffusion radius in millimetres)
@@ -45,16 +48,17 @@
#' @param add_intrinsic_resistance *(only useful when using a EUCAST guideline)* a [logical] to indicate whether intrinsic antibiotic resistance must also be considered for applicable bug-drug combinations, meaning that e.g. ampicillin will always return "R" in *Klebsiella* species. Determination is based on the [intrinsic_resistant] data set, that itself is based on `r format_eucast_version_nr(3.3)`.
#' @param include_screening a [logical] to indicate that clinical breakpoints for screening are allowed - the default is `FALSE`. Can also be set with the [package option][AMR-options] [`AMR_include_screening`][AMR-options].
#' @param include_PKPD a [logical] to indicate that PK/PD clinical breakpoints must be applied as a last resort - the default is `TRUE`. Can also be set with the [package option][AMR-options] [`AMR_include_PKPD`][AMR-options].
#' @param breakpoint_type the type of breakpoints to use, either `r vector_or(clinical_breakpoints$type)`. ECOFF stands for Epidemiological Cut-Off values. The default is `"human"`, which can also be set with the [package option][AMR-options] [`AMR_breakpoint_type`][AMR-options].
#' @param breakpoint_type the type of breakpoints to use, either `r vector_or(clinical_breakpoints$type)`. ECOFF stands for Epidemiological Cut-Off values. The default is `"human"`, which can also be set with the [package option][AMR-options] [`AMR_breakpoint_type`][AMR-options]. If `host` is set to values of veterinary species, this will automatically be set to `"animal"`.
#' @param host a vector (or column name) with [character]s to indicate the host. Only useful for veterinary breakpoints, as it requires `breakpoint_type = "animal"`. The values can be any text resembling the animal species, even in any of the `r length(LANGUAGES_SUPPORTED)` supported languages of this package. For foreign languages, be sure to set the language with [set_AMR_locale()] (though it will be automatically guessed based on the system language).
#' @param reference_data a [data.frame] to be used for interpretation, which defaults to the [clinical_breakpoints] data set. Changing this argument allows for using own interpretation guidelines. This argument must contain a data set that is equal in structure to the [clinical_breakpoints] data set (same column names and column types). Please note that the `guideline` argument will be ignored when `reference_data` is manually set.
#' @param threshold maximum fraction of invalid antimicrobial interpretations of `x`, see *Examples*
#' @param ... for using on a [data.frame]: names of columns to apply [as.sir()] on (supports tidy selection such as `column1:column4`). Otherwise: arguments passed on to methods.
#' @details
#' *Note: The clinical breakpoints in this package were validated through and imported from [WHONET](https://whonet.org) and the public use of this `AMR` package has been endorsed by CLSI and EUCAST, please see [clinical_breakpoints] for more information.*
#' *Note: The clinical breakpoints in this package were validated through, and imported from, [WHONET](https://whonet.org). The public use of this `AMR` package has been endorsed by both CLSI and EUCAST. See [clinical_breakpoints] for more information.*
#'
#' ### How it Works
#'
#' The [as.sir()] function works in four ways:
#' The [as.sir()] function can work in four ways:
#'
#' 1. For **cleaning raw / untransformed data**. The data will be cleaned to only contain values S, I and R and will try its best to determine this with some intelligence. For example, mixed values with SIR interpretations and MIC values such as `"<0.25; S"` will be coerced to `"S"`. Combined interpretations for multiple test methods (as seen in laboratory records) such as `"S; S"` will be coerced to `"S"`, but a value like `"S; I"` will return `NA` with a warning that the input is unclear.
#'
@@ -63,6 +67,9 @@
#' ```
#' your_data %>% mutate_if(is.mic, as.sir)
#' your_data %>% mutate(across(where(is.mic), as.sir))
#'
#' # for veterinary breakpoints, also set `host`:
#' your_data %>% mutate_if(is.mic, as.sir, host = "column_with_animal_hosts", guideline = "CLSI")
#' ```
#' * Operators like "<=" will be stripped before interpretation. When using `conserve_capped_values = TRUE`, an MIC value of e.g. ">2" will always return "R", even if the breakpoint according to the chosen guideline is ">=4". This is to prevent that capped values from raw laboratory data would not be treated conservatively. The default behaviour (`conserve_capped_values = FALSE`) considers ">2" to be lower than ">=4" and might in this case return "S" or "I".
#' 3. For **interpreting disk diffusion diameters** according to EUCAST or CLSI. You must clean your disk zones first using [as.disk()], that also gives your columns the new data class [`disk`]. Also, be sure to have a column with microorganism names or codes. It will be found automatically, but can be set manually using the `mo` argument.
@@ -70,6 +77,9 @@
#' ```
#' your_data %>% mutate_if(is.disk, as.sir)
#' your_data %>% mutate(across(where(is.disk), as.sir))
#'
#' # for veterinary breakpoints, also set `host`:
#' your_data %>% mutate_if(is.disk, as.sir, host = "column_with_animal_hosts", guideline = "CLSI")
#' ```
#' 4. For **interpreting a complete data set**, with automatic determination of MIC values, disk diffusion diameters, microorganism names or codes, and antimicrobial test results. This is done very simply by running `as.sir(your_data)`.
#'
@@ -77,7 +87,7 @@
#'
#' ### Supported Guidelines
#'
#' For interpreting MIC values as well as disk diffusion diameters, currently implemented guidelines are EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`).
#' For interpreting MIC values as well as disk diffusion diameters, currently implemented guidelines are for **clinical microbiology**: EUCAST `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "human")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "human")$guideline)))` and CLSI `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "human")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "human")$guideline)))`, and for **veterinary microbiology**: EUCAST `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "animal")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "animal")$guideline)))` and CLSI `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "animal")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "animal")$guideline)))`.
#'
#' Thus, the `guideline` argument must be set to e.g., ``r paste0('"', subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline[1], '"')`` or ``r paste0('"', subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline[1], '"')``. By simply using `"EUCAST"` (the default) or `"CLSI"` as input, the latest included version of that guideline will automatically be selected. You can set your own data set using the `reference_data` argument. The `guideline` argument will then be ignored.
#'
@@ -90,6 +100,13 @@
#' # or to reset:
#' options(AMR_guideline = NULL)
#' ```
#'
#' For veterinary guidelines, these might be the best options:
#'
#' ```
#' options(AMR_guideline = "CLSI")
#' options(AMR_breakpoint_type = "animal")
#' ```
#'
#' ### After Interpretation
#'
@@ -124,9 +141,10 @@
#' @source
#' For interpretations of minimum inhibitory concentration (MIC) values and disk diffusion diameters:
#'
#' - **M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data**, `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`, *Clinical and Laboratory Standards Institute* (CLSI). <https://clsi.org/standards/products/microbiology/documents/m39/>.
#' - **M100 Performance Standard for Antimicrobial Susceptibility Testing**, `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`, *Clinical and Laboratory Standards Institute* (CLSI). <https://clsi.org/standards/products/microbiology/documents/m100/>.
#' - **Breakpoint tables for interpretation of MICs and zone diameters**, `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`, *European Committee on Antimicrobial Susceptibility Testing* (EUCAST). <https://www.eucast.org/clinical_breakpoints>.
#' - **CLSI M39: Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data**, `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`, *Clinical and Laboratory Standards Institute* (CLSI). <https://clsi.org/standards/products/microbiology/documents/m39/>.
#' - **CLSI M100: Performance Standard for Antimicrobial Susceptibility Testing**, `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type != "animal")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type != "animal")$guideline)))`, *Clinical and Laboratory Standards Institute* (CLSI). <https://clsi.org/standards/products/microbiology/documents/m100/>.
#' - **CLSI VET01: Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals**, `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "animal")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "animal")$guideline)))`, *Clinical and Laboratory Standards Institute* (CLSI). <https://clsi.org/standards/products/veterinary-medicine/documents/vet01//>.
#' - **EUCAST Breakpoint tables for interpretation of MICs and zone diameters**, `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`, *European Committee on Antimicrobial Susceptibility Testing* (EUCAST). <https://www.eucast.org/clinical_breakpoints>.
#' @inheritSection AMR Reference Data Publicly Available
#' @examples
#' example_isolates
@@ -226,6 +244,7 @@ as.sir <- function(x, ...) {
#' @rdname as.sir
#' @details `NA_sir_` is a missing value of the new `sir` class, analogous to e.g. base \R's [`NA_character_`][base::NA].
#' @format NULL
#' @export
NA_sir_ <- set_clean_class(factor(NA_character_, levels = c("S", "I", "R"), ordered = TRUE),
new_class = c("sir", "ordered", "factor")
@@ -429,6 +448,7 @@ as.sir.mic <- function(x,
include_screening = getOption("AMR_include_screening", FALSE),
include_PKPD = getOption("AMR_include_PKPD", TRUE),
breakpoint_type = getOption("AMR_breakpoint_type", "human"),
host = NULL,
...) {
as_sir_method(
method_short = "mic",
@@ -444,6 +464,7 @@ as.sir.mic <- function(x,
include_screening = include_screening,
include_PKPD = include_PKPD,
breakpoint_type = breakpoint_type,
host = host,
...
)
}
@@ -460,6 +481,7 @@ as.sir.disk <- function(x,
include_screening = getOption("AMR_include_screening", FALSE),
include_PKPD = getOption("AMR_include_PKPD", TRUE),
breakpoint_type = getOption("AMR_breakpoint_type", "human"),
host = NULL,
...) {
as_sir_method(
method_short = "disk",
@@ -475,6 +497,7 @@ as.sir.disk <- function(x,
include_screening = include_screening,
include_PKPD = include_PKPD,
breakpoint_type = breakpoint_type,
host = NULL,
...
)
}
@@ -491,7 +514,8 @@ as.sir.data.frame <- function(x,
reference_data = AMR::clinical_breakpoints,
include_screening = getOption("AMR_include_screening", FALSE),
include_PKPD = getOption("AMR_include_PKPD", TRUE),
breakpoint_type = getOption("AMR_breakpoint_type", "human")) {
breakpoint_type = getOption("AMR_breakpoint_type", "human"),
host = NULL) {
meet_criteria(x, allow_class = "data.frame") # will also check for dimensions > 0
meet_criteria(col_mo, allow_class = "character", is_in = colnames(x), allow_NULL = TRUE)
meet_criteria(guideline, allow_class = "character", has_length = 1)
@@ -502,7 +526,7 @@ as.sir.data.frame <- function(x,
meet_criteria(include_screening, allow_class = "logical", has_length = 1)
meet_criteria(include_PKPD, allow_class = "logical", has_length = 1)
meet_criteria(breakpoint_type, allow_class = "character", is_in = reference_data$type, has_length = 1)
meet_criteria(host, allow_class = "character", allow_NULL = TRUE, allow_NA = TRUE)
x.bak <- x
for (i in seq_len(ncol(x))) {
# don't keep factors, overwriting them is hard
@@ -516,11 +540,20 @@ as.sir.data.frame <- function(x,
if (is.null(col_mo)) {
col_mo <- search_type_in_df(x = x, type = "mo", info = FALSE)
}
# -- host
if (breakpoint_type == "animal") {
if (is.null(host)) {
host <- search_type_in_df(x = x, type = "host", add_col_prefix = FALSE)
} else if (length(host) == 1 && host %in% colnames(x)) {
host <- x[[host]]
}
}
# -- UTIs
col_uti <- uti
if (is.null(col_uti)) {
col_uti <- search_type_in_df(x = x, type = "uti")
col_uti <- search_type_in_df(x = x, type = "uti", add_col_prefix = FALSE)
}
if (!is.null(col_uti)) {
if (is.logical(col_uti)) {
@@ -634,6 +667,7 @@ as.sir.data.frame <- function(x,
include_screening = include_screening,
include_PKPD = include_PKPD,
breakpoint_type = breakpoint_type,
host = host,
is_data.frame = TRUE
)
} else if (types[i] == "disk") {
@@ -652,6 +686,7 @@ as.sir.data.frame <- function(x,
include_screening = include_screening,
include_PKPD = include_PKPD,
breakpoint_type = breakpoint_type,
host = host,
is_data.frame = TRUE
)
} else if (types[i] == "sir") {
@@ -661,7 +696,7 @@ as.sir.data.frame <- function(x,
if (!all(x[, ab_cols[i], drop = TRUE] %in% c("S", "I", "R", NA), na.rm = TRUE)) {
show_message <- TRUE
# only print message if values are not already clean
message_("=> Cleaning values in column '", font_bold(ab), "' (",
message_("Cleaning values in column '", font_bold(ab), "' (",
ifelse(ab_coerced != toupper(ab), paste0(ab_coerced, ", "), ""),
ab_name(ab_coerced, tolower = TRUE), ")... ",
appendLF = FALSE,
@@ -670,7 +705,7 @@ as.sir.data.frame <- function(x,
} else if (!is.sir(x.bak[, ab_cols[i], drop = TRUE])) {
show_message <- TRUE
# only print message if class not already set
message_("=> Assigning class 'sir' to already clean column '", font_bold(ab), "' (",
message_("Assigning class 'sir' to already clean column '", font_bold(ab), "' (",
ifelse(ab_coerced != toupper(ab), paste0(ab_coerced, ", "), ""),
ab_name(ab_coerced, tolower = TRUE, language = NULL), ")... ",
appendLF = FALSE,
@@ -679,7 +714,7 @@ as.sir.data.frame <- function(x,
}
x[, ab_cols[i]] <- as.sir.default(x = as.character(x[, ab_cols[i], drop = TRUE]))
if (show_message == TRUE) {
message_(" OK.", add_fn = list(font_green), as_note = FALSE)
message(font_green_bg(" OK "))
}
}
}
@@ -709,6 +744,20 @@ get_guideline <- function(guideline, reference_data) {
guideline_param
}
convert_host <- function(x, lang = get_AMR_locale()) {
x <- trimws2(tolower(x))
x_out <- rep(NA_character_, length(x))
# this order is based on: clinical_breakpoints |> filter(type == "animal") |> count(host, sort = TRUE)
x_out[is.na(x_out) & (x %like% "dog|canine" | x %like% translate_AMR("dog|dogs|canine", lang))] <- "dogs"
x_out[is.na(x_out) & (x %like% "cattle|bovine" | x %like% translate_AMR("cattle|bovine", lang))] <- "cattle"
x_out[is.na(x_out) & (x %like% "swine|suida(e)?" | x %like% translate_AMR("swine|swines", lang))] <- "swine"
x_out[is.na(x_out) & (x %like% "cat|feline" | x %like% translate_AMR("cat|cats|feline", lang))] <- "cats"
x_out[is.na(x_out) & (x %like% "horse|equine" | x %like% translate_AMR("horse|horses|equine", lang))] <- "horse"
x_out[is.na(x_out) & (x %like% "aqua|fish" | x %like% translate_AMR("aquatic|fish", lang))] <- "aquatic"
x_out[is.na(x_out) & (x %like% "bird|chicken|poultry|avia" | x %like% translate_AMR("bird|birds|poultry", lang))] <- "poultry"
x_out
}
as_sir_method <- function(method_short,
method_long,
x,
@@ -722,6 +771,7 @@ as_sir_method <- function(method_short,
include_screening,
include_PKPD,
breakpoint_type,
host,
...) {
meet_criteria(x, allow_NA = TRUE, .call_depth = -2)
meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE, .call_depth = -2)
@@ -735,11 +785,43 @@ as_sir_method <- function(method_short,
meet_criteria(include_PKPD, allow_class = "logical", has_length = 1, .call_depth = -2)
check_reference_data(reference_data, .call_depth = -2)
meet_criteria(breakpoint_type, allow_class = "character", is_in = reference_data$type, has_length = 1, .call_depth = -2)
meet_criteria(host, allow_class = "character", allow_NULL = TRUE, allow_NA = TRUE, .call_depth = -2)
# backward compatibilty
dots <- list(...)
dots <- dots[which(!names(dots) %in% c("warn", "mo.bak", "is_data.frame"))]
if (length(dots) != 0) {
warning_("These arguments in `as.sir()` are no longer used: ", vector_and(names(dots), quotes = "`"), ".", call = FALSE)
}
guideline_coerced <- get_guideline(guideline, reference_data)
if (breakpoint_type == "animal") {
if (is.null(host)) {
host <- AMR_env$host_preferred_order[1]
if (message_not_thrown_before("as.sir", "host_missing")) {
message_("Animal hosts not set in `host`, assuming `host = \"", host, "\"`, since these have the highest breakpoint availability.\n\n")
}
}
} else {
if (!is.null(host) && !all(toupper(host) %in% c("HUMAN", "ECOFF"))) {
if (message_not_thrown_before("as.sir", "assumed_breakpoint_animal")) {
message_("Assuming `breakpoint_type = \"animal\"`, since `host` is set.", ifelse(guideline_coerced %like% "EUCAST", " Do you also need to set `guideline = \"CLSI\"`?", ""), "\n\n")
}
breakpoint_type <- "animal"
} else {
host <- NA_character_
}
}
host <- convert_host(host)
host <- tolower(host)
host[host == "ecoff"] <- "ECOFF"
if (message_not_thrown_before("as.sir", "sir_interpretation_history")) {
message_("Run `sir_interpretation_history()` afterwards to retrieve a logbook with all the details of the breakpoint interpretations. Note that some microorganisms might not have breakpoints for each antimicrobial drug in ", guideline_coerced, ".\n\n")
message_("Run `sir_interpretation_history()` afterwards to retrieve a logbook with all the details of the breakpoint interpretations. Note that some ", ifelse(breakpoint_type == "animal", "animal hosts and ", ""), "microorganisms might not have breakpoints for each antimicrobial drug in ", guideline_coerced, ".\n\n")
}
if (breakpoint_type == "animal" && message_not_thrown_before("as.sir", "host_preferred_order")) {
message_("Please note that in the absence of specific veterinary breakpoints for certain animal hosts, breakpoints for dogs, cattle, swine, cats, horse, aquatic, and poultry, in that order, are used as substitutes.\n\n")
}
# for dplyr's across()
@@ -812,7 +894,9 @@ as_sir_method <- function(method_short,
if (length(uti) == 1) {
uti <- rep(uti, length(x))
}
if (length(host) == 1) {
host <- rep(host, length(x))
}
if (isTRUE(add_intrinsic_resistance) && guideline_coerced %unlike% "EUCAST") {
if (message_not_thrown_before("as.sir", "intrinsic")) {
warning_("in `as.sir()`: using 'add_intrinsic_resistance' is only useful when using EUCAST guidelines, since the rules for intrinsic resistance are based on EUCAST.")
@@ -865,6 +949,7 @@ as_sir_method <- function(method_short,
mo = mo,
result = NA_sir_,
uti = uti,
host = host,
stringsAsFactors = FALSE
)
if (method == "mic") {
@@ -874,7 +959,7 @@ as_sir_method <- function(method_short,
# when as.sir.disk is called directly
df$values <- as.disk(df$values)
}
df_unique <- unique(df[ , c("mo", "uti"), drop = FALSE])
df_unique <- unique(df[ , c("mo", "uti", "host"), drop = FALSE])
rise_warning <- FALSE
rise_note <- FALSE
@@ -913,7 +998,7 @@ as_sir_method <- function(method_short,
# apparently no breakpoints found
message(
paste0(font_rose_bg(" WARNING "), "\n"),
font_black(paste0(" ", AMR_env$bullet_icon, " No ", method_coerced, " breakpoints available for ",
font_black(paste0(" ", AMR_env$bullet_icon, " No ", guideline_coerced, " ", method_coerced, " breakpoints available for ",
suppressMessages(suppressWarnings(ab_name(ab_coerced, language = NULL, tolower = TRUE))),
" (", ab_coerced, ").")))
@@ -930,7 +1015,7 @@ as_sir_method <- function(method_short,
has_progress_bar <- !is.null(import_fn("progress_bar", "progress", error_on_fail = FALSE)) && nrow(df_unique) >= 10
on.exit(close(p))
# run the rules
# run the rules (df_unique is a row combination per mo/ab/uti/host)
for (i in seq_len(nrow(df_unique))) {
p$tick()
mo_current <- df_unique[i, "mo", drop = TRUE]
@@ -967,9 +1052,9 @@ as_sir_method <- function(method_short,
suppressMessages(suppressWarnings(ab_name(ab_coerced, language = NULL, tolower = TRUE))),
" (", ab_coerced, ")"
)
# gather all available breakpoints for current MO and sort on taxonomic rank
# (this will prefer species breakpoints over order breakpoints)
# gather all available breakpoints for current MO
breakpoints_current <- breakpoints %pm>%
subset(mo %in% c(
mo_current, mo_current_genus, mo_current_family,
@@ -977,23 +1062,45 @@ as_sir_method <- function(method_short,
mo_current_species_group,
mo_current_other
))
# set the host index according to most available breakpoints (see R/zzz.R where this is set in the pkg environment)
breakpoints_current$host_index <- match(breakpoints_current$host, c("human", "ECOFF", AMR_env$host_preferred_order))
# sort on host and taxonomic rank
# (this will prefer species breakpoints over order breakpoints)
if (is.na(unique(uti_current))) {
breakpoints_current <- breakpoints_current %pm>%
# this will put UTI = FALSE first, then UTI = TRUE, then UTI = NA
pm_arrange(rank_index, uti) # 'uti' is a column in data set 'clinical_breakpoints'
pm_arrange(host_index, rank_index, uti) # 'uti' is a column in data set 'clinical_breakpoints'
} else if (unique(uti_current) == TRUE) {
breakpoints_current <- breakpoints_current %pm>%
subset(uti == TRUE) %pm>%
# be as specific as possible (i.e. prefer species over genus):
pm_arrange(rank_index)
pm_arrange(host_index, rank_index)
} else if (unique(uti_current) == FALSE) {
breakpoints_current <- breakpoints_current %pm>%
subset(uti == FALSE) %pm>%
# be as specific as possible (i.e. prefer species over genus):
pm_arrange(rank_index)
pm_arrange(host_index, rank_index)
}
if (NROW(breakpoints_current) == 0) {
# no note about missing breakpoints - it's already in the header before the interpretation starts
next
}
# veterinary host check
host_current <- unique(df_unique[i, "host", drop = TRUE])[1]
breakpoints_current$host_match <- breakpoints_current$host == host_current
if (breakpoint_type == "animal") {
if (any(breakpoints_current$host_match == TRUE, na.rm = TRUE)) {
breakpoints_current <- breakpoints_current %pm>%
subset(host_match == TRUE)
} else {
# no breakpoint found for this host, so sort on mostly available guidelines
msgs <- c(msgs, paste0("No ", guideline_coerced, " breakpoints for ", font_bold(host_current), " available for ", ab_formatted, " in ", mo_formatted, " - using ", font_bold(breakpoints_current$host[1]), " breakpoints instead."))
}
}
# throw notes for different body sites
site <- breakpoints_current[1L, "site", drop = FALSE] # this is the one we'll take
if (is.na(site)) {
@@ -1007,15 +1114,12 @@ as_sir_method <- function(method_short,
rise_warning <- TRUE
} else if (nrow(breakpoints_current) > 1 && length(unique(breakpoints_current$site)) > 1 && any(is.na(uti_current)) && all(c(TRUE, FALSE) %in% breakpoints_current$uti, na.rm = TRUE) && message_not_thrown_before("as.sir", "siteUTI", mo_current, ab_coerced)) {
# both UTI and Non-UTI breakpoints available
msgs <- c(msgs, paste0("Breakpoints for UTI ", font_underline("and"), " non-UTI available for ", ab_formatted, " in ", mo_formatted, " - assuming ", site, ". Use argument `uti` to set which isolates are from urine. See `?as.sir`."))
msgs <- c(msgs, paste0("Breakpoints for UTI ", font_bold("and"), " non-UTI available for ", ab_formatted, " in ", mo_formatted, " - assuming ", site, ". Use argument `uti` to set which isolates are from urine. See `?as.sir`."))
breakpoints_current <- breakpoints_current %pm>%
pm_filter(uti == FALSE)
} else if (nrow(breakpoints_current) > 1 && length(unique(breakpoints_current$site)) > 1 && all(breakpoints_current$uti == FALSE, na.rm = TRUE) && message_not_thrown_before("as.sir", "siteOther", mo_current, ab_coerced)) {
# breakpoints for multiple body sites available
msgs <- c(msgs, paste0("Multiple breakpoints available for ", ab_formatted, " in ", mo_formatted, " - assuming ", site, "."))
} else if (nrow(breakpoints_current) == 0) {
# # do not note - it's already in the header before the interpretation starts
next
}
# first check if mo is intrinsic resistant
@@ -1076,6 +1180,7 @@ as_sir_method <- function(method_short,
method = rep(method_coerced, length(rows)),
breakpoint_S_R = rep(paste0(breakpoints_current[, "breakpoint_S", drop = TRUE], "-", breakpoints_current[, "breakpoint_R", drop = TRUE]), length(rows)),
guideline = rep(guideline_coerced, length(rows)),
host = rep(breakpoints_current[, "host", drop = TRUE], length(rows)),
ref_table = rep(breakpoints_current[, "ref_tbl", drop = TRUE], length(rows)),
uti = rep(breakpoints_current[, "uti", drop = TRUE], length(rows)),
stringsAsFactors = FALSE

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R/sysdata.rda
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57
R/vctrs.R
View File

@@ -35,33 +35,33 @@
# see https://github.com/tidyverse/dplyr/issues/5955 why this is required
# S3: ab_selector
vec_ptype2.character.ab_selector <- function(x, y, ...) {
vec_ptype2.ab_selector.default <- function (x, y, ..., x_arg = "", y_arg = "") {
x
}
vec_ptype2.ab_selector.character <- function(x, y, ...) {
y
vec_ptype2.ab_selector.ab_selector <- function(x, y, ...) {
x
}
vec_cast.character.ab_selector <- function(x, to, ...) {
unclass(x)
}
# S3: ab_selector_any_all
vec_ptype2.logical.ab_selector_any_all <- function(x, y, ...) {
vec_ptype2.ab_selector_any_all.default <- function (x, y, ..., x_arg = "", y_arg = "") {
x
}
vec_ptype2.ab_selector_any_all.logical <- function(x, y, ...) {
y
vec_ptype2.ab_selector_any_all.ab_selector_any_all <- function(x, y, ...) {
x
}
vec_cast.logical.ab_selector_any_all <- function(x, to, ...) {
unclass(x)
}
# S3: ab
vec_ptype2.character.ab <- function(x, y, ...) {
vec_ptype2.ab.default <- function (x, y, ..., x_arg = "", y_arg = "") {
x
}
vec_ptype2.ab.character <- function(x, y, ...) {
y
vec_ptype2.ab.ab <- function(x, y, ...) {
x
}
vec_cast.character.ab <- function(x, to, ...) {
as.character(x)
@@ -71,11 +71,11 @@ vec_cast.ab.character <- function(x, to, ...) {
}
# S3: av
vec_ptype2.character.av <- function(x, y, ...) {
vec_ptype2.av.default <- function (x, y, ..., x_arg = "", y_arg = "") {
x
}
vec_ptype2.av.character <- function(x, y, ...) {
y
vec_ptype2.av.av <- function(x, y, ...) {
x
}
vec_cast.character.av <- function(x, to, ...) {
as.character(x)
@@ -85,11 +85,11 @@ vec_cast.av.character <- function(x, to, ...) {
}
# S3: mo
vec_ptype2.character.mo <- function(x, y, ...) {
vec_ptype2.mo.default <- function (x, y, ..., x_arg = "", y_arg = "") {
x
}
vec_ptype2.mo.character <- function(x, y, ...) {
y
vec_ptype2.mo.mo <- function(x, y, ...) {
x
}
vec_cast.character.mo <- function(x, to, ...) {
as.character(x)
@@ -100,11 +100,11 @@ vec_cast.mo.character <- function(x, to, ...) {
}
# S3: disk
vec_ptype2.integer.disk <- function(x, y, ...) {
vec_ptype2.disk.default <- function (x, y, ..., x_arg = "", y_arg = "") {
x
}
vec_ptype2.disk.integer <- function(x, y, ...) {
y
vec_ptype2.disk.disk <- function(x, y, ...) {
x
}
vec_cast.integer.disk <- function(x, to, ...) {
unclass(x)
@@ -126,28 +126,43 @@ vec_cast.disk.character <- function(x, to, ...) {
}
# S3: mic
vec_ptype2.mic.default <- function (x, y, ..., x_arg = "", y_arg = "") {
x
}
vec_ptype2.mic.mic <- function(x, y, ...) {
x
}
vec_cast.character.mic <- function(x, to, ...) {
as.character(x)
}
vec_cast.double.mic <- function(x, to, ...) {
as.double(x)
}
vec_cast.integer.mic <- function(x, to, ...) {
as.integer(x)
}
vec_cast.mic.double <- function(x, to, ...) {
as.mic(x)
}
vec_cast.mic.character <- function(x, to, ...) {
as.mic(x)
}
vec_cast.mic.integer <- function(x, to, ...) {
as.mic(x)
}
vec_math.mic <- function(.fn, x, ...) {
.fn(as.double(x), ...)
}
vec_arith.mic <- function(op, x, y, ...) {
vctrs::vec_arith(op, as.double(x), as.double(y))
}
# S3: sir
vec_ptype2.character.sir <- function(x, y, ...) {
vec_ptype2.sir.default <- function (x, y, ..., x_arg = "", y_arg = "") {
x
}
vec_ptype2.sir.character <- function(x, y, ...) {
y
vec_ptype2.sir.sir <- function(x, y, ...) {
x
}
vec_cast.character.sir <- function(x, to, ...) {
as.character(x)

80
R/zzz.R
View File

@@ -55,6 +55,7 @@ AMR_env$av_previously_coerced <- data.frame(
av = character(0),
stringsAsFactors = FALSE
)
AMR_env$host_preferred_order <- names(sort(table(AMR::clinical_breakpoints$host[!AMR::clinical_breakpoints$host %in% AMR::clinical_breakpoints$type]), decreasing = TRUE))
AMR_env$sir_interpretation_history <- data.frame(
datetime = Sys.time()[0],
index = integer(0),
@@ -67,6 +68,7 @@ AMR_env$sir_interpretation_history <- data.frame(
method = character(0),
breakpoint_S_R = character(0),
guideline = character(0),
host = character(0),
ref_table = character(0),
stringsAsFactors = FALSE
)
@@ -130,32 +132,33 @@ if (pkg_is_available("cli")) {
s3_register("knitr::knit_print", "antibiogram")
s3_register("knitr::knit_print", "formatted_bug_drug_combinations")
# Support vctrs package for use in e.g. dplyr verbs
# NOTE 2024-02-22 this is the right way - it should be 2 S3 classes in the second argument
# S3: ab_selector
s3_register("vctrs::vec_ptype2", "character.ab_selector")
s3_register("vctrs::vec_ptype2", "ab_selector.character")
s3_register("vctrs::vec_ptype2", "ab_selector.default")
s3_register("vctrs::vec_ptype2", "ab_selector.ab_selector")
s3_register("vctrs::vec_cast", "character.ab_selector")
# S3: ab_selector_any_all
s3_register("vctrs::vec_ptype2", "logical.ab_selector_any_all")
s3_register("vctrs::vec_ptype2", "ab_selector_any_all.logical")
s3_register("vctrs::vec_ptype2", "ab_selector_any_all.default")
s3_register("vctrs::vec_ptype2", "ab_selector_any_all.ab_selector_any_all")
s3_register("vctrs::vec_cast", "logical.ab_selector_any_all")
# S3: ab
s3_register("vctrs::vec_ptype2", "character.ab")
s3_register("vctrs::vec_ptype2", "ab.character")
s3_register("vctrs::vec_ptype2", "ab.default")
s3_register("vctrs::vec_ptype2", "ab.ab")
s3_register("vctrs::vec_cast", "character.ab")
s3_register("vctrs::vec_cast", "ab.character")
# S3: av
s3_register("vctrs::vec_ptype2", "character.av")
s3_register("vctrs::vec_ptype2", "av.character")
s3_register("vctrs::vec_ptype2", "av.default")
s3_register("vctrs::vec_ptype2", "av.av")
s3_register("vctrs::vec_cast", "character.av")
s3_register("vctrs::vec_cast", "av.character")
# S3: mo
s3_register("vctrs::vec_ptype2", "character.mo")
s3_register("vctrs::vec_ptype2", "mo.character")
s3_register("vctrs::vec_ptype2", "mo.default")
s3_register("vctrs::vec_ptype2", "mo.mo")
s3_register("vctrs::vec_cast", "character.mo")
s3_register("vctrs::vec_cast", "mo.character")
# S3: disk
s3_register("vctrs::vec_ptype2", "integer.disk")
s3_register("vctrs::vec_ptype2", "disk.integer")
s3_register("vctrs::vec_ptype2", "disk.default")
s3_register("vctrs::vec_ptype2", "disk.disk")
s3_register("vctrs::vec_cast", "integer.disk")
s3_register("vctrs::vec_cast", "disk.integer")
s3_register("vctrs::vec_cast", "double.disk")
@@ -163,14 +166,19 @@ if (pkg_is_available("cli")) {
s3_register("vctrs::vec_cast", "character.disk")
s3_register("vctrs::vec_cast", "disk.character")
# S3: mic
s3_register("vctrs::vec_ptype2", "mic.default")
s3_register("vctrs::vec_ptype2", "mic.mic")
s3_register("vctrs::vec_cast", "character.mic")
s3_register("vctrs::vec_cast", "double.mic")
s3_register("vctrs::vec_cast", "integer.mic")
s3_register("vctrs::vec_cast", "mic.character")
s3_register("vctrs::vec_cast", "mic.double")
s3_register("vctrs::vec_cast", "mic.integer")
s3_register("vctrs::vec_math", "mic")
s3_register("vctrs::vec_arith", "mic")
# S3: sir
s3_register("vctrs::vec_ptype2", "character.sir")
s3_register("vctrs::vec_ptype2", "sir.character")
s3_register("vctrs::vec_ptype2", "sir.default")
s3_register("vctrs::vec_ptype2", "sir.sir")
s3_register("vctrs::vec_cast", "character.sir")
s3_register("vctrs::vec_cast", "sir.character")
@@ -192,26 +200,34 @@ if (pkg_is_available("cli")) {
.onAttach <- function(lib, pkg) {
# if custom ab option is available, load it
if (!is.null(getOption("AMR_custom_ab")) && file.exists(getOption("AMR_custom_ab", default = ""))) {
packageStartupMessage("Adding custom antimicrobials from '", getOption("AMR_custom_ab"), "'...", appendLF = FALSE)
x <- readRDS_AMR(getOption("AMR_custom_ab"))
tryCatch(
{
suppressWarnings(suppressMessages(add_custom_antimicrobials(x)))
packageStartupMessage("OK.")
},
error = function(e) packageStartupMessage("Failed: ", e$message)
)
if (getOption("AMR_custom_ab") %unlike% "[.]rds$") {
packageStartupMessage("The file with custom antimicrobials must be an RDS file. Set the option `AMR_custom_ab` to another path.")
} else {
packageStartupMessage("Adding custom antimicrobials from '", getOption("AMR_custom_ab"), "'...", appendLF = FALSE)
x <- readRDS_AMR(getOption("AMR_custom_ab"))
tryCatch(
{
suppressWarnings(suppressMessages(add_custom_antimicrobials(x)))
packageStartupMessage("OK.")
},
error = function(e) packageStartupMessage("Failed: ", e$message)
)
}
}
# if custom mo option is available, load it
if (!is.null(getOption("AMR_custom_mo")) && file.exists(getOption("AMR_custom_mo", default = ""))) {
packageStartupMessage("Adding custom microorganisms from '", getOption("AMR_custom_mo"), "'...", appendLF = FALSE)
x <- readRDS_AMR(getOption("AMR_custom_mo"))
tryCatch(
{
suppressWarnings(suppressMessages(add_custom_microorganisms(x)))
packageStartupMessage("OK.")
},
error = function(e) packageStartupMessage("Failed: ", e$message)
)
if (getOption("AMR_custom_mo") %unlike% "[.]rds$") {
packageStartupMessage("The file with custom microorganisms must be an RDS file. Set the option `AMR_custom_mo` to another path.")
} else {
packageStartupMessage("Adding custom microorganisms from '", getOption("AMR_custom_mo"), "'...", appendLF = FALSE)
x <- readRDS_AMR(getOption("AMR_custom_mo"))
tryCatch(
{
suppressWarnings(suppressMessages(add_custom_microorganisms(x)))
packageStartupMessage("OK.")
},
error = function(e) packageStartupMessage("Failed: ", e$message)
)
}
}
}