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(v1.6.0.9021) join functions update

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dr. M.S. (Matthijs) Berends
2021-05-12 18:15:03 +02:00
parent 3319fbae58
commit 29dbfa2f49
119 changed files with 973 additions and 1040 deletions
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12
R/key_antimicrobials.R
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@ -28,18 +28,18 @@
#' These functions can be used to determine first weighted isolates by considering the phenotype for isolate selection (see [first_isolate()]). Using a phenotype-based method to determine first isolates is more reliable than methods that disregard phenotypes.
#' @inheritSection lifecycle Stable Lifecycle
#' @param x a [data.frame] with antibiotics columns, like `AMX` or `amox`. Can be left blank to determine automatically
#' @param y,z character vectors to compare
#' @param y,z [character] vectors to compare
#' @inheritParams first_isolate
#' @param universal names of **broad-spectrum** antimicrobial agents, case-insensitive. Set to `NULL` to ignore. See *Details* for the default agents.
#' @param gram_negative names of antibiotic agents for **Gram-positives**, case-insensitive. Set to `NULL` to ignore. See *Details* for the default agents.
#' @param gram_positive names of antibiotic agents for **Gram-negatives**, case-insensitive. Set to `NULL` to ignore. See *Details* for the default agents.
#' @param antifungal names of antifungal agents for **fungi**, case-insensitive. Set to `NULL` to ignore. See *Details* for the default agents.
#' @param only_rsi_columns a logical to indicate whether only columns must be included that were transformed to class `<rsi>` (see [as.rsi()]) on beforehand (defaults to `FALSE`)
#' @param only_rsi_columns a [logical] to indicate whether only columns must be included that were transformed to class `<rsi>` (see [as.rsi()]) on beforehand (defaults to `FALSE`)
#' @param ... ignored, only in place to allow future extensions
#' @details
#' The [key_antimicrobials()] and [all_antimicrobials()] functions are context-aware. This means that then the `x` argument can be left blank, see *Examples*.
#'
#' The function [key_antimicrobials()] returns a character vector with 12 antimicrobial results for every isolate. The function [all_antimicrobials()] returns a character vector with all antimicrobial results for every isolate. These vectors can then be compared using [antimicrobials_equal()], to check if two isolates have generally the same antibiogram. Missing and invalid values are replaced with a dot (`"."`) by [key_antimicrobials()] and ignored by [antimicrobials_equal()].
#' The function [key_antimicrobials()] returns a [character] vector with 12 antimicrobial results for every isolate. The function [all_antimicrobials()] returns a [character] vector with all antimicrobial results for every isolate. These vectors can then be compared using [antimicrobials_equal()], to check if two isolates have generally the same antibiogram. Missing and invalid values are replaced with a dot (`"."`) by [key_antimicrobials()] and ignored by [antimicrobials_equal()].
#'
#' Please see the [first_isolate()] function how these important functions enable the 'phenotype-based' method for determination of first isolates.
#'
@ -96,7 +96,7 @@
#' # TRUE, because I is ignored (as well as missing values)
#'
#' antimicrobials_equal(strainA, strainB, type = "keyantimicrobials", ignore_I = FALSE)
#' # FALSE, because I is not ignored and so the 4th character differs
#' # FALSE, because I is not ignored and so the 4th [character] differs
#'
#' \donttest{
#' if (require("dplyr")) {
@ -140,7 +140,7 @@ key_antimicrobials <- function(x = NULL,
meet_criteria(antifungal, allow_class = "character", allow_NULL = TRUE)
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
# force regular data.frame, not a tibble or data.table
# force regular [data.frame], not a tibble or data.table
x <- as.data.frame(x, stringsAsFactors = FALSE)
cols <- get_column_abx(x, info = FALSE, only_rsi_columns = only_rsi_columns)
@ -237,7 +237,7 @@ all_antimicrobials <- function(x = NULL,
meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
meet_criteria(only_rsi_columns, allow_class = "logical", has_length = 1)
# force regular data.frame, not a tibble or data.table
# force regular [data.frame], not a tibble or data.table
x <- as.data.frame(x, stringsAsFactors = FALSE)
cols <- get_column_abx(x, only_rsi_columns = only_rsi_columns, info = FALSE, sort = FALSE)