mirror of https://github.com/msberends/AMR.git
220 lines
7.0 KiB
R
Executable File
220 lines
7.0 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 #
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# https://github.com/msberends/AMR #
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# #
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# CITE 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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# doi: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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# thoroughly check input table
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expect_equal(
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colnames(AMR:::EUCAST_RULES_DF),
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c(
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"if_mo_property", "like.is.one_of", "this_value",
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"and_these_antibiotics", "have_these_values",
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"then_change_these_antibiotics", "to_value",
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"reference.rule", "reference.rule_group",
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"reference.version",
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"note"
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)
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)
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MOs_mentioned <- unique(AMR:::EUCAST_RULES_DF$this_value)
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MOs_mentioned <- sort(trimws(unlist(strsplit(MOs_mentioned[!AMR:::is_valid_regex(MOs_mentioned)], ",", fixed = TRUE))))
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MOs_test <- suppressWarnings(suppressMessages(mo_name(MOs_mentioned, keep_synonyms = TRUE, language = NULL)))
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expect_true(length(MOs_mentioned[MOs_test != MOs_mentioned]) == 0)
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expect_error(suppressWarnings(eucast_rules(example_isolates, col_mo = "Non-existing")))
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expect_error(eucast_rules(x = "text"))
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expect_error(eucast_rules(data.frame(a = "test")))
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expect_error(eucast_rules(data.frame(mo = "test"), rules = "invalid rules set"))
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# expect_warning(eucast_rules(data.frame(mo = "Escherichia coli", vancomycin = "S", stringsAsFactors = TRUE)))
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expect_identical(
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colnames(example_isolates),
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colnames(suppressWarnings(eucast_rules(example_isolates, info = FALSE)))
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)
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expect_stdout(suppressMessages(eucast_rules(example_isolates, info = TRUE)))
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a <- data.frame(
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mo = c(
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"Klebsiella pneumoniae",
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"Pseudomonas aeruginosa",
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"Enterobacter cloacae"
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),
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amox = "-", # Amoxicillin
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stringsAsFactors = FALSE
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)
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b <- data.frame(
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mo = c(
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"Klebsiella pneumoniae",
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"Pseudomonas aeruginosa",
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"Enterobacter cloacae"
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),
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amox = "R", # Amoxicillin
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stringsAsFactors = FALSE
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)
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expect_identical(suppressWarnings(eucast_rules(a, "mo", info = FALSE)), b)
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expect_stdout(suppressMessages(suppressWarnings(eucast_rules(a, "mo", info = TRUE))))
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a <- data.frame(
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mo = c(
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"Staphylococcus aureus",
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"Streptococcus group A"
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),
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COL = "-", # Colistin
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stringsAsFactors = FALSE
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)
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b <- data.frame(
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mo = c(
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"Staphylococcus aureus",
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"Streptococcus group A"
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),
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COL = "R", # Colistin
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stringsAsFactors = FALSE
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)
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expect_equal(suppressWarnings(eucast_rules(a, "mo", info = FALSE)), b)
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# piperacillin must be R in Enterobacteriaceae when tica is R
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if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0", also_load = TRUE)) {
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expect_equal(
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suppressWarnings(
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example_isolates %>%
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filter(mo_family(mo) == "Enterobacteriaceae") %>%
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mutate(
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TIC = as.sir("R"),
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PIP = as.sir("S")
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) %>%
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eucast_rules(col_mo = "mo", version_expertrules = 3.1, info = FALSE) %>%
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pull(PIP) %>%
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unique() %>%
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as.character()
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),
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"R"
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)
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}
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# azithromycin and clarythromycin must be equal to Erythromycin
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a <- suppressWarnings(as.sir(eucast_rules(data.frame(
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mo = example_isolates$mo,
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ERY = example_isolates$ERY,
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AZM = as.sir("R"),
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CLR = factor("R"),
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stringsAsFactors = FALSE
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),
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version_expertrules = 3.1,
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only_sir_columns = FALSE
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)$CLR))
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b <- example_isolates$ERY
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expect_identical(
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a[!is.na(b)],
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b[!is.na(b)]
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)
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# amox is inferred by benzylpenicillin in Kingella kingae
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expect_equal(
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suppressWarnings(
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as.list(eucast_rules(
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data.frame(
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mo = as.mo("Kingella kingae"),
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PEN = "S",
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AMX = "-",
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stringsAsFactors = FALSE
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),
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info = FALSE
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))$AMX
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),
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"S"
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)
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# also test norf
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if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0", also_load = TRUE)) {
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expect_stdout(suppressWarnings(eucast_rules(example_isolates %>% mutate(NOR = "S", NAL = "S"), info = TRUE)))
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}
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# check verbose output
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expect_stdout(suppressWarnings(eucast_rules(example_isolates, verbose = TRUE, rules = "all", info = TRUE)))
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# AmpC de-repressed cephalo mutants
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expect_identical(
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eucast_rules(data.frame(
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mo = c("Escherichia coli", "Enterobacter cloacae"),
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cefotax = as.sir(c("S", "S"))
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),
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ampc_cephalosporin_resistance = TRUE,
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info = FALSE
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)$cefotax,
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as.sir(c("S", "R"))
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)
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expect_identical(
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eucast_rules(data.frame(
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mo = c("Escherichia coli", "Enterobacter cloacae"),
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cefotax = as.sir(c("S", "S"))
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),
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ampc_cephalosporin_resistance = NA,
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info = FALSE
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)$cefotax,
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as.sir(c("S", NA))
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)
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expect_identical(
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eucast_rules(data.frame(
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mo = c("Escherichia coli", "Enterobacter cloacae"),
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cefotax = as.sir(c("S", "S"))
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),
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ampc_cephalosporin_resistance = NULL,
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info = FALSE
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)$cefotax,
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as.sir(c("S", "S"))
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)
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# EUCAST dosage -----------------------------------------------------------
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expect_equal(nrow(eucast_dosage(c("tobra", "genta", "cipro"))), 3)
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expect_inherits(eucast_dosage(c("tobra", "genta", "cipro")), "data.frame")
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x <- custom_eucast_rules(
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AMC == "R" & genus == "Klebsiella" ~ aminopenicillins == "R",
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AMC == "I" & genus == "Klebsiella" ~ aminopenicillins == "I",
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AMX == "S" ~ AMC == "S"
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)
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expect_stdout(print(x))
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expect_stdout(print(c(x, x)))
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expect_stdout(print(as.list(x, x)))
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# this custom rules makes 8 changes
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expect_equal(nrow(eucast_rules(example_isolates,
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rules = "custom",
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custom_rules = x,
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info = FALSE,
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verbose = TRUE
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)),
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8,
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tolerance = 0.5
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)
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