mirror of https://github.com/msberends/AMR.git
240 lines
11 KiB
R
Executable File
240 lines
11 KiB
R
Executable File
# ==================================================================== #
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# TITLE: #
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# AMR: An R Package for Working with Antimicrobial Resistance Data #
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# #
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# SOURCE CODE: #
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# https://github.com/msberends/AMR #
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# #
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# PLEASE CITE THIS SOFTWARE AS: #
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# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
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# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
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# Data. Journal of Statistical Software, 104(3), 1-31. #
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# https://doi.org/10.18637/jss.v104.i03 #
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# #
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# Developed at the University of Groningen and the University Medical #
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# Center Groningen in The Netherlands, in collaboration with many #
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# colleagues from around the world, see our website. #
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# #
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# This R package is free software; you can freely use and distribute #
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# it for both personal and commercial purposes under the terms of the #
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# GNU General Public License version 2.0 (GNU GPL-2), as published by #
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# the Free Software Foundation. #
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# We created this package for both routine data analysis and academic #
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# research and it was publicly released in the hope that it will be #
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# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
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# #
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# Visit our website for the full manual and a complete tutorial about #
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# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
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# ==================================================================== #
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# set up package environment, used by numerous AMR functions
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AMR_env <- new.env(hash = FALSE)
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AMR_env$mo_uncertainties <- data.frame(
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original_input = character(0),
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input = character(0),
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fullname = character(0),
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mo = character(0),
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candidates = character(0),
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minimum_matching_score = integer(0),
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keep_synonyms = logical(0),
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stringsAsFactors = FALSE
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)
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AMR_env$mo_renamed <- list()
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AMR_env$mo_previously_coerced <- data.frame(
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x = character(0),
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mo = character(0),
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stringsAsFactors = FALSE
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)
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AMR_env$ab_previously_coerced <- data.frame(
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x = character(0),
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ab = character(0),
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stringsAsFactors = FALSE
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)
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AMR_env$av_previously_coerced <- data.frame(
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x = character(0),
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av = character(0),
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stringsAsFactors = FALSE
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)
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AMR_env$sir_interpretation_history <- data.frame(
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datetime = Sys.time()[0],
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index = integer(0),
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ab_given = character(0),
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mo_given = character(0),
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host_given = character(0),
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ab = set_clean_class(character(0), c("ab", "character")),
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mo = set_clean_class(character(0), c("mo", "character")),
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host = character(0),
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method = character(0),
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input = double(0),
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outcome = NA_sir_[0],
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notes = character(0),
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guideline = character(0),
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ref_table = character(0),
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uti = logical(0),
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breakpoint_S_R = character(0),
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stringsAsFactors = FALSE
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)
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AMR_env$custom_ab_codes <- character(0)
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AMR_env$custom_mo_codes <- character(0)
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AMR_env$is_dark_theme <- NULL
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AMR_env$chmatch <- import_fn("chmatch", "data.table", error_on_fail = FALSE)
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AMR_env$chin <- import_fn("%chin%", "data.table", error_on_fail = FALSE)
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# take cli symbols if available
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AMR_env$info_icon <- import_fn("symbol", "cli", error_on_fail = FALSE)$info %or% "i"
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AMR_env$bullet_icon <- import_fn("symbol", "cli", error_on_fail = FALSE)$bullet %or% "*"
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AMR_env$dots <- import_fn("symbol", "cli", error_on_fail = FALSE)$ellipsis %or% "..."
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AMR_env$sup_1_icon <- import_fn("symbol", "cli", error_on_fail = FALSE)$sup_1 %or% "*"
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.onLoad <- function(lib, pkg) {
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# Support for tibble headers (type_sum) and tibble columns content (pillar_shaft)
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# without the need to depend on other packages. This was suggested by the
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# developers of the vctrs package:
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# https://github.com/r-lib/vctrs/blob/05968ce8e669f73213e3e894b5f4424af4f46316/R/register-s3.R
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s3_register("pillar::pillar_shaft", "ab")
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s3_register("pillar::pillar_shaft", "av")
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s3_register("pillar::pillar_shaft", "mo")
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s3_register("pillar::pillar_shaft", "sir")
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s3_register("pillar::pillar_shaft", "mic")
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s3_register("pillar::pillar_shaft", "disk")
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# no type_sum of disk, that's now in vctrs::vec_ptype_full
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s3_register("pillar::type_sum", "ab")
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s3_register("pillar::type_sum", "av")
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s3_register("pillar::type_sum", "mo")
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s3_register("pillar::type_sum", "sir")
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s3_register("pillar::type_sum", "mic")
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# Support for frequency tables from the cleaner package
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s3_register("cleaner::freq", "mo")
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s3_register("cleaner::freq", "sir")
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# Support for skim() from the skimr package
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if (pkg_is_available("skimr", min_version = "2.0.0")) {
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s3_register("skimr::get_skimmers", "mo")
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s3_register("skimr::get_skimmers", "sir")
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s3_register("skimr::get_skimmers", "mic")
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s3_register("skimr::get_skimmers", "disk")
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}
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# Support for autoplot() from the ggplot2 package
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s3_register("ggplot2::autoplot", "sir")
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s3_register("ggplot2::autoplot", "mic")
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s3_register("ggplot2::autoplot", "disk")
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s3_register("ggplot2::autoplot", "resistance_predict")
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s3_register("ggplot2::autoplot", "antibiogram")
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# Support for fortify from the ggplot2 package
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s3_register("ggplot2::fortify", "sir")
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s3_register("ggplot2::fortify", "mic")
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s3_register("ggplot2::fortify", "disk")
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# Support for knitr (R Markdown/Quarto)
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s3_register("knitr::knit_print", "antibiogram")
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s3_register("knitr::knit_print", "formatted_bug_drug_combinations")
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# Support vctrs package for use in e.g. dplyr verbs
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# NOTE 2024-02-22 this is the right way - it should be 2 S3 classes in the second argument
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# S3: ab_selector
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s3_register("vctrs::vec_ptype2", "character.ab_selector")
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s3_register("vctrs::vec_ptype2", "ab_selector.character")
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s3_register("vctrs::vec_cast", "character.ab_selector")
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# S3: ab_selector_any_all
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s3_register("vctrs::vec_ptype2", "logical.ab_selector_any_all")
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s3_register("vctrs::vec_ptype2", "ab_selector_any_all.logical")
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s3_register("vctrs::vec_cast", "logical.ab_selector_any_all")
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# S3: ab
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s3_register("vctrs::vec_ptype2", "ab.default")
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s3_register("vctrs::vec_ptype2", "ab.ab")
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s3_register("vctrs::vec_cast", "character.ab")
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s3_register("vctrs::vec_cast", "ab.character")
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# S3: av
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s3_register("vctrs::vec_ptype2", "av.default")
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s3_register("vctrs::vec_ptype2", "av.av")
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s3_register("vctrs::vec_cast", "character.av")
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s3_register("vctrs::vec_cast", "av.character")
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# S3: mo
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s3_register("vctrs::vec_ptype2", "mo.default")
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s3_register("vctrs::vec_ptype2", "mo.mo")
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s3_register("vctrs::vec_cast", "character.mo")
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s3_register("vctrs::vec_cast", "mo.character")
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# S3: disk
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s3_register("vctrs::vec_ptype_full", "disk")
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s3_register("vctrs::vec_ptype_abbr", "disk")
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s3_register("vctrs::vec_ptype2", "disk.default")
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s3_register("vctrs::vec_ptype2", "disk.disk")
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s3_register("vctrs::vec_cast", "disk.disk")
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s3_register("vctrs::vec_cast", "integer.disk")
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s3_register("vctrs::vec_cast", "disk.integer")
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s3_register("vctrs::vec_cast", "double.disk")
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s3_register("vctrs::vec_cast", "disk.double")
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s3_register("vctrs::vec_cast", "character.disk")
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s3_register("vctrs::vec_cast", "disk.character")
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# S3: mic
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s3_register("vctrs::vec_ptype2", "mic.default")
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s3_register("vctrs::vec_ptype2", "mic.mic")
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s3_register("vctrs::vec_cast", "character.mic")
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s3_register("vctrs::vec_cast", "double.mic")
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s3_register("vctrs::vec_cast", "integer.mic")
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s3_register("vctrs::vec_cast", "factor.mic")
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s3_register("vctrs::vec_cast", "mic.character")
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s3_register("vctrs::vec_cast", "mic.double")
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s3_register("vctrs::vec_cast", "mic.integer")
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s3_register("vctrs::vec_cast", "mic.factor")
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s3_register("vctrs::vec_cast", "mic.mic")
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s3_register("vctrs::vec_math", "mic")
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s3_register("vctrs::vec_arith", "mic")
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# S3: sir
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s3_register("vctrs::vec_ptype2", "sir.default")
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s3_register("vctrs::vec_ptype2", "sir.sir")
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s3_register("vctrs::vec_ptype2", "character.sir")
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s3_register("vctrs::vec_cast", "character.sir")
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s3_register("vctrs::vec_cast", "sir.character")
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s3_register("vctrs::vec_cast", "sir.sir")
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# if mo source exists, fire it up (see mo_source())
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if (tryCatch(file.exists(getOption("AMR_mo_source", "~/mo_source.rds")), error = function(e) FALSE)) {
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try(invisible(get_mo_source()), silent = TRUE)
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}
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# be sure to print tibbles as tibbles
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if (pkg_is_available("tibble")) {
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try(loadNamespace("tibble"), silent = TRUE)
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}
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# reference data - they have additional data to improve algorithm speed
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# they cannot be part of R/sysdata.rda since CRAN thinks it would make the package too large (+3 MB)
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AMR_env$AB_lookup <- cbind(AMR::antibiotics, AB_LOOKUP)
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AMR_env$AV_lookup <- cbind(AMR::antivirals, AV_LOOKUP)
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AMR_env$host_preferred_order <- names(sort(table(AMR::clinical_breakpoints$host[!AMR::clinical_breakpoints$host %in% AMR::clinical_breakpoints$type]), decreasing = TRUE))
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}
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.onAttach <- function(lib, pkg) {
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# if custom ab option is available, load it
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if (!is.null(getOption("AMR_custom_ab")) && file.exists(getOption("AMR_custom_ab", default = ""))) {
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if (getOption("AMR_custom_ab") %unlike% "[.]rds$") {
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packageStartupMessage("The file with custom antimicrobials must be an RDS file. Set the option `AMR_custom_ab` to another path.")
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} else {
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packageStartupMessage("Adding custom antimicrobials from '", getOption("AMR_custom_ab"), "'...", appendLF = FALSE)
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x <- readRDS_AMR(getOption("AMR_custom_ab"))
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tryCatch(
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{
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suppressWarnings(suppressMessages(add_custom_antimicrobials(x)))
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packageStartupMessage("OK.")
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},
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error = function(e) packageStartupMessage("Failed: ", e$message)
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)
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}
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}
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# if custom mo option is available, load it
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if (!is.null(getOption("AMR_custom_mo")) && file.exists(getOption("AMR_custom_mo", default = ""))) {
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if (getOption("AMR_custom_mo") %unlike% "[.]rds$") {
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packageStartupMessage("The file with custom microorganisms must be an RDS file. Set the option `AMR_custom_mo` to another path.")
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} else {
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packageStartupMessage("Adding custom microorganisms from '", getOption("AMR_custom_mo"), "'...", appendLF = FALSE)
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x <- readRDS_AMR(getOption("AMR_custom_mo"))
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tryCatch(
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{
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suppressWarnings(suppressMessages(add_custom_microorganisms(x)))
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packageStartupMessage("OK.")
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},
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error = function(e) packageStartupMessage("Failed: ", e$message)
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)
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}
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}
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}
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