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# ==================================================================== #
# TITLE #
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# Antimicrobial Resistance (AMR) Analysis for R #
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# #
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# SOURCE #
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# https://github.com/msberends/AMR #
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# #
# LICENCE #
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# (c) 2018-2020 Berends MS, Luz CF et al. #
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# Developed at the University of Groningen, the Netherlands, in #
# collaboration with non-profit organisations Certe Medical #
# Diagnostics & Advice, and University Medical Center Groningen. #
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# #
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# This R package is free software; you can freely use and distribute #
# it for both personal and commercial purposes under the terms of the #
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
# the Free Software Foundation. #
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# We created this package for both routine data analysis and academic #
# research and it was publicly released in the hope that it will be #
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
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# #
# Visit our website for the full manual and a complete tutorial about #
# how to conduct AMR analysis: https://msberends.github.io/AMR/ #
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# ==================================================================== #
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#' Count available isolates
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#'
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#' @description These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in `summarise()` from the `dplyr` package and also support grouped variables, please see *Examples*.
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#'
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#' [count_resistant()] should be used to count resistant isolates, [count_susceptible()] should be used to count susceptible isolates.
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#' @inheritSection lifecycle Stable lifecycle
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#' @param ... one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with [as.rsi()] if needed.
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#' @inheritParams proportion
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#' @inheritSection as.rsi Interpretation of R and S/I
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#' @details These functions are meant to count isolates. Use the [resistance()]/[susceptibility()] functions to calculate microbial resistance/susceptibility.
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#'
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#' The function [count_resistant()] is equal to the function [count_R()]. The function [count_susceptible()] is equal to the function [count_SI()].
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#'
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#' The function [n_rsi()] is an alias of [count_all()]. They can be used to count all available isolates, i.e. where all input antibiotics have an available result (S, I or R). Their use is equal to `n_distinct()`. Their function is equal to `count_susceptible(...) + count_resistant(...)`.
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#'
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#' The function [count_df()] takes any variable from `data` that has an [`rsi`] class (created with [as.rsi()]) and counts the number of S's, I's and R's. It also supports grouped variables. The function [rsi_df()] works exactly like [count_df()], but adds the percentage of S, I and R.
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#' @inheritSection proportion Combination therapy
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#' @seealso [`proportion_*`][proportion] to calculate microbial resistance and susceptibility.
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#' @return An [integer]
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#' @rdname count
#' @name count
#' @export
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#' @inheritSection AMR Read more on our website!
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#' @examples
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#' # example_isolates is a data set available in the AMR package.
#' ?example_isolates
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#'
#' count_resistant(example_isolates$AMX) # counts "R"
#' count_susceptible(example_isolates$AMX) # counts "S" and "I"
#' count_all(example_isolates$AMX) # counts "S", "I" and "R"
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#'
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#' # be more specific
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#' count_S(example_isolates$AMX)
#' count_SI(example_isolates$AMX)
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#' count_I(example_isolates$AMX)
#' count_IR(example_isolates$AMX)
#' count_R(example_isolates$AMX)
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#'
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#' # Count all available isolates
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#' count_all(example_isolates$AMX)
#' n_rsi(example_isolates$AMX)
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#'
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#' # n_rsi() is an alias of count_all().
#' # Since it counts all available isolates, you can
#' # calculate back to count e.g. susceptible isolates.
#' # These results are the same:
#' count_susceptible(example_isolates$AMX)
#' susceptibility(example_isolates$AMX) * n_rsi(example_isolates$AMX)
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#'
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#'
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#' if (require("dplyr")) {
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#' example_isolates %>%
#' group_by(hospital_id) %>%
#' summarise(R = count_R(CIP),
#' I = count_I(CIP),
#' S = count_S(CIP),
#' n1 = count_all(CIP), # the actual total; sum of all three
#' n2 = n_rsi(CIP), # same - analogous to n_distinct
#' total = n()) # NOT the number of tested isolates!
#'
#' # Count co-resistance between amoxicillin/clav acid and gentamicin,
#' # so we can see that combination therapy does a lot more than mono therapy.
#' # Please mind that `susceptibility()` calculates percentages right away instead.
#' example_isolates %>% count_susceptible(AMC) # 1433
#' example_isolates %>% count_all(AMC) # 1879
#'
#' example_isolates %>% count_susceptible(GEN) # 1399
#' example_isolates %>% count_all(GEN) # 1855
#'
#' example_isolates %>% count_susceptible(AMC, GEN) # 1764
#' example_isolates %>% count_all(AMC, GEN) # 1936
#'
#' # Get number of S+I vs. R immediately of selected columns
#' example_isolates %>%
#' select(AMX, CIP) %>%
#' count_df(translate = FALSE)
#'
#' # It also supports grouping variables
#' example_isolates %>%
#' select(hospital_id, AMX, CIP) %>%
#' group_by(hospital_id) %>%
#' count_df(translate = FALSE)
#' }
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count_resistant <- function ( ... , only_all_tested = FALSE ) {
rsi_calc ( ... ,
ab_result = " R" ,
only_all_tested = only_all_tested ,
only_count = TRUE )
}
#' @rdname count
#' @export
count_susceptible <- function ( ... , only_all_tested = FALSE ) {
rsi_calc ( ... ,
ab_result = c ( " S" , " I" ) ,
only_all_tested = only_all_tested ,
only_count = TRUE )
}
#' @rdname count
#' @export
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count_R <- function ( ... , only_all_tested = FALSE ) {
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rsi_calc ( ... ,
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ab_result = " R" ,
only_all_tested = only_all_tested ,
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only_count = TRUE )
}
#' @rdname count
#' @export
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count_IR <- function ( ... , only_all_tested = FALSE ) {
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warning ( " Using 'count_IR' is discouraged; use 'count_resistant()' instead to not consider \"I\" being resistant." , call. = FALSE )
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rsi_calc ( ... ,
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ab_result = c ( " I" , " R" ) ,
only_all_tested = only_all_tested ,
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only_count = TRUE )
}
#' @rdname count
#' @export
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count_I <- function ( ... , only_all_tested = FALSE ) {
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rsi_calc ( ... ,
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ab_result = " I" ,
only_all_tested = only_all_tested ,
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only_count = TRUE )
}
#' @rdname count
#' @export
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count_SI <- function ( ... , only_all_tested = FALSE ) {
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rsi_calc ( ... ,
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ab_result = c ( " S" , " I" ) ,
only_all_tested = only_all_tested ,
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only_count = TRUE )
}
#' @rdname count
#' @export
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count_S <- function ( ... , only_all_tested = FALSE ) {
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warning ( " Using 'count_S' is discouraged; use 'count_susceptible()' instead to also consider \"I\" being susceptible." , call. = FALSE )
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rsi_calc ( ... ,
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ab_result = " S" ,
only_all_tested = only_all_tested ,
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only_count = TRUE )
}
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#' @rdname count
#' @export
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count_all <- function ( ... , only_all_tested = FALSE ) {
rsi_calc ( ... ,
ab_result = c ( " S" , " I" , " R" ) ,
only_all_tested = only_all_tested ,
only_count = TRUE )
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}
#' @rdname count
#' @export
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n_rsi <- count_all
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#' @rdname count
#' @export
count_df <- function ( data ,
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translate_ab = " name" ,
language = get_locale ( ) ,
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combine_SI = TRUE ,
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combine_IR = FALSE ) {
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rsi_calc_df ( type = " count" ,
data = data ,
translate_ab = translate_ab ,
language = language ,
combine_SI = combine_SI ,
combine_IR = combine_IR ,
combine_SI_missing = missing ( combine_SI ) )
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}