mirror of https://github.com/msberends/AMR.git
176 lines
8.9 KiB
R
176 lines
8.9 KiB
R
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# ==================================================================== #
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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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expect_identical(as.mo("Enterobacter asburiae/cloacae"),
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as.mo("Enterobacter asburiae"))
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suppressMessages(
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add_custom_microorganisms(
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data.frame(mo = "ENT_ASB_CLO",
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genus = "Enterobacter",
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species = "asburiae/cloacae")
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)
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)
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expect_identical(as.character(as.mo("ENT_ASB_CLO")), "ENT_ASB_CLO")
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expect_identical(mo_name("ENT_ASB_CLO"), "Enterobacter asburiae/cloacae")
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expect_identical(mo_gramstain("ENT_ASB_CLO", language = NULL), "Gram-negative")
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# ==================================================================== #
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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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#
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#
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# # Traditional antibiogram ----------------------------------------------
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#
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# ab1 <- antibiogram(example_isolates,
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# antibiotics = c(aminoglycosides(), carbapenems()))
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#
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# ab2 <- antibiogram(example_isolates,
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# antibiotics = aminoglycosides(),
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# ab_transform = "atc",
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# mo_transform = "gramstain")
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#
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# ab3 <- antibiogram(example_isolates,
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# antibiotics = carbapenems(),
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# ab_transform = "name",
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# mo_transform = "name")
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#
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# expect_inherits(ab1, "antibiogram")
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# expect_inherits(ab2, "antibiogram")
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# expect_inherits(ab3, "antibiogram")
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# expect_equal(colnames(ab1), c("Pathogen (N min-max)", "AMK", "GEN", "IPM", "KAN", "MEM", "TOB"))
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# expect_equal(colnames(ab2), c("Pathogen (N min-max)", "J01GB01", "J01GB03", "J01GB04", "J01GB06"))
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# expect_equal(colnames(ab3), c("Pathogen (N min-max)", "Imipenem", "Meropenem"))
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# expect_equal(ab3$Meropenem, c(52, NA, 100, 100, NA))
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#
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# # Combined antibiogram -------------------------------------------------
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#
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# # combined antibiotics yield higher empiric coverage
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# ab4 <- antibiogram(example_isolates,
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# antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"),
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# mo_transform = "gramstain")
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#
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# ab5 <- antibiogram(example_isolates,
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# antibiotics = c("TZP", "TZP+TOB"),
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# mo_transform = "gramstain",
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# ab_transform = "name",
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# sep = " & ",
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# add_total_n = FALSE)
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#
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# expect_inherits(ab4, "antibiogram")
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# expect_inherits(ab5, "antibiogram")
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# expect_equal(colnames(ab4), c("Pathogen (N min-max)", "TZP", "TZP + GEN", "TZP + TOB"))
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# expect_equal(colnames(ab5), c("Pathogen", "Piperacillin/tazobactam", "Piperacillin/tazobactam & Tobramycin"))
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#
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# # Syndromic antibiogram ------------------------------------------------
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#
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# # the data set could contain a filter for e.g. respiratory specimens
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# ab6 <- antibiogram(example_isolates,
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# antibiotics = c(aminoglycosides(), carbapenems()),
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# syndromic_group = "ward")
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#
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# # with a custom language, though this will be determined automatically
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# # (i.e., this table will be in Spanish on Spanish systems)
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# ex1 <- example_isolates[which(mo_genus() == "Escherichia"), ]
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# ab7 <- antibiogram(ex1,
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# antibiotics = aminoglycosides(),
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# ab_transform = "name",
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# syndromic_group = ifelse(ex1$ward == "ICU",
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# "UCI", "No UCI"),
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# language = "es")
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#
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# expect_inherits(ab6, "antibiogram")
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# expect_inherits(ab7, "antibiogram")
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# expect_equal(colnames(ab6), c("Syndromic Group", "Pathogen (N min-max)", "AMK", "GEN", "IPM", "KAN", "MEM", "TOB"))
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# expect_equal(colnames(ab7), c("Grupo sindrómico", "Patógeno (N min-max)", "Amikacina", "Gentamicina", "Tobramicina"))
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#
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# # Weighted-incidence syndromic combination antibiogram (WISCA) ---------
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#
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# # the data set could contain a filter for e.g. respiratory specimens
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# ab8 <- antibiogram(example_isolates,
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# antibiotics = c("AMC", "AMC+CIP", "TZP", "TZP+TOB"),
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# mo_transform = "gramstain",
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# minimum = 10, # this should be >= 30, but now just as example
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# syndromic_group = ifelse(example_isolates$age >= 65 &
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# example_isolates$gender == "M",
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# "WISCA Group 1", "WISCA Group 2"))
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#
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# expect_inherits(ab8, "antibiogram")
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# expect_equal(colnames(ab8), c("Syndromic Group", "Pathogen (N min-max)", "AMC", "AMC + CIP", "TZP", "TZP + TOB"))
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#
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# # Generate plots with ggplot2 or base R --------------------------------
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#
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# pdf(NULL) # prevent Rplots.pdf being created
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#
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# expect_silent(plot(ab1))
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# expect_silent(plot(ab2))
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# expect_silent(plot(ab3))
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# expect_silent(plot(ab4))
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# expect_silent(plot(ab5))
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# expect_silent(plot(ab6))
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# expect_silent(plot(ab7))
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# expect_silent(plot(ab8))
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#
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# if (AMR:::pkg_is_available("ggplot2")) {
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# expect_inherits(autoplot(ab1), "gg")
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# expect_inherits(autoplot(ab2), "gg")
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# expect_inherits(autoplot(ab3), "gg")
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# expect_inherits(autoplot(ab4), "gg")
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# expect_inherits(autoplot(ab5), "gg")
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# expect_inherits(autoplot(ab6), "gg")
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# expect_inherits(autoplot(ab7), "gg")
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# expect_inherits(autoplot(ab8), "gg")
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# }
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