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use dplyr where available, new antibiogram() for WISCA, fixed Salmonella Typhi/Paratyphi

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dr. M.S. (Matthijs) Berends
2023-02-06 11:57:22 +01:00
parent 4b133d4c96
commit 9e99e66f01
69 changed files with 1670 additions and 650 deletions
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132
inst/tinytest/test-antibiogram.R Normal file
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@ -0,0 +1,132 @@
# ==================================================================== #
# TITLE #
# AMR: An R Package for Working with Antimicrobial Resistance Data #
# #
# SOURCE #
# https://github.com/msberends/AMR #
# #
# CITE AS #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. #
# doi:10.18637/jss.v104.i03 #
# #
# Developed at the University of Groningen and the University Medical #
# Center Groningen in The Netherlands, in collaboration with many #
# colleagues from around the world, see our website. #
# #
# 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. #
# 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. #
# #
# Visit our website for the full manual and a complete tutorial about #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
# Traditional antibiogram ----------------------------------------------
ab1 <- antibiogram(example_isolates,
antibiotics = c(aminoglycosides(), carbapenems()))
ab2 <- antibiogram(example_isolates,
antibiotics = aminoglycosides(),
ab_transform = "atc",
mo_transform = "gramstain")
ab3 <- antibiogram(example_isolates,
antibiotics = carbapenems(),
ab_transform = "name",
mo_transform = "name")
expect_inherits(ab1, "antibiogram")
expect_inherits(ab2, "antibiogram")
expect_inherits(ab3, "antibiogram")
expect_equal(colnames(ab1), c("Pathogen (N min-max)", "AMK", "GEN", "IPM", "KAN", "MEM", "TOB"))
expect_equal(colnames(ab2), c("Pathogen (N min-max)", "J01GB01", "J01GB03", "J01GB04", "J01GB06"))
expect_equal(colnames(ab3), c("Pathogen (N min-max)", "Imipenem", "Meropenem"))
expect_equal(ab3$Meropenem, c(52, NA, 100, 100, NA))
# Combined antibiogram -------------------------------------------------
# combined antibiotics yield higher empiric coverage
ab4 <- antibiogram(example_isolates,
antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"),
mo_transform = "gramstain")
ab5 <- antibiogram(example_isolates,
antibiotics = c("TZP", "TZP+TOB"),
mo_transform = "gramstain",
ab_transform = "name",
sep = " & ",
add_total_n = FALSE)
expect_inherits(ab4, "antibiogram")
expect_inherits(ab5, "antibiogram")
expect_equal(colnames(ab4), c("Pathogen (N min-max)", "TZP", "TZP + GEN", "TZP + TOB"))
expect_equal(colnames(ab5), c("Pathogen", "Piperacillin/tazobactam", "Piperacillin/tazobactam & Tobramycin"))
# Syndromic antibiogram ------------------------------------------------
# the data set could contain a filter for e.g. respiratory specimens
ab6 <- antibiogram(example_isolates,
antibiotics = c(aminoglycosides(), carbapenems()),
syndromic_group = "ward")
# with a custom language, though this will be determined automatically
# (i.e., this table will be in Spanish on Spanish systems)
ex1 <- example_isolates[which(mo_genus() == "Escherichia"), ]
ab7 <- antibiogram(ex1,
antibiotics = aminoglycosides(),
ab_transform = "name",
syndromic_group = ifelse(ex1$ward == "ICU",
"UCI", "No UCI"),
language = "es")
expect_inherits(ab6, "antibiogram")
expect_inherits(ab7, "antibiogram")
expect_equal(colnames(ab6), c("Syndromic Group", "Pathogen (N min-max)", "AMK", "GEN", "IPM", "KAN", "MEM", "TOB"))
expect_equal(colnames(ab7), c("Grupo sindrómico", "Patógeno (N min-max)", "Amikacina", "Gentamicina", "Tobramicina"))
# Weighted-incidence syndromic combination antibiogram (WISCA) ---------
# the data set could contain a filter for e.g. respiratory specimens
ab8 <- antibiogram(example_isolates,
antibiotics = c("AMC", "AMC+CIP", "TZP", "TZP+TOB"),
mo_transform = "gramstain",
minimum = 10, # this should be >= 30, but now just as example
syndromic_group = ifelse(example_isolates$age >= 65 &
example_isolates$gender == "M",
"WISCA Group 1", "WISCA Group 2"))
expect_inherits(ab8, "antibiogram")
expect_equal(colnames(ab8), c("Syndromic Group", "Pathogen (N min-max)", "AMC", "AMC + CIP", "TZP", "TZP + TOB"))
# Generate plots with ggplot2 or base R --------------------------------
pdf(NULL) # prevent Rplots.pdf being created
expect_silent(plot(ab1))
expect_silent(plot(ab2))
expect_silent(plot(ab3))
expect_silent(plot(ab4))
expect_silent(plot(ab5))
expect_silent(plot(ab6))
expect_silent(plot(ab7))
expect_silent(plot(ab8))
if (AMR:::pkg_is_available("ggplot2")) {
expect_inherits(autoplot(ab1), "gg")
expect_inherits(autoplot(ab2), "gg")
expect_inherits(autoplot(ab3), "gg")
expect_inherits(autoplot(ab4), "gg")
expect_inherits(autoplot(ab5), "gg")
expect_inherits(autoplot(ab6), "gg")
expect_inherits(autoplot(ab7), "gg")
expect_inherits(autoplot(ab8), "gg")
}

2
inst/tinytest/test-first_isolate.R
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@ -228,7 +228,7 @@ expect_identical(
# notice that all mo's are distinct, so all are TRUE
expect_true(all(first_isolate(AMR:::pm_distinct(example_isolates, mo, .keep_all = TRUE), info = TRUE) == TRUE))
expect_true(all(first_isolate(AMR:::distinct(example_isolates, mo, .keep_all = TRUE), info = TRUE) == TRUE))
# only one isolate, so return fast
expect_true(first_isolate(data.frame(mo = "Escherichia coli", date = Sys.Date(), patient = "patient"), info = TRUE))

26
inst/tinytest/test-zzz.R
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@ -32,11 +32,21 @@
# functions used by import_fn()
import_functions <- c(
"%>%" = "dplyr",
"%chin%" = "data.table",
"across" = "dplyr",
"anti_join" = "dplyr",
"arrange" = "dplyr",
"bind_rows" = "dplyr",
"chmatch" = "data.table",
"count" = "dplyr",
"cur_column" = "dplyr",
"desc" = "dplyr",
"distinct" = "dplyr",
"everything" = "dplyr",
"full_join" = "dplyr",
"group_by" = "dplyr",
"group_vars" = "dplyr",
"has_internet" = "curl",
"html_attr" = "rvest",
"html_children" = "rvest",
@ -46,13 +56,24 @@ import_functions <- c(
"html_text" = "rvest",
"inner_join" = "dplyr",
"insertText" = "rstudioapi",
"kable" = "knitr",
"lag" = "dplyr",
"left_join" = "dplyr",
"mutate" = "dplyr",
"n_distinct" = "dplyr",
"new_pillar_shaft_simple" = "pillar",
"pivot_longer" = "tidyr",
"progress_bar" = "progress",
"pull" = "dplyr",
"read_html" = "xml2",
"rename" = "dplyr",
"right_join" = "dplyr",
"row_number" = "dplyr",
"select" = "dplyr",
"semi_join" = "dplyr",
"showQuestion" = "rstudioapi"
"showQuestion" = "rstudioapi",
"summarise" = "dplyr",
"ungroup" = "dplyr"
)
# functions that are called directly with ::
@ -71,6 +92,7 @@ call_functions <- c(
"element_text" = "ggplot2",
"expand_limits" = "ggplot2",
"facet_wrap" = "ggplot2",
"geom_col" = "ggplot2",
"geom_errorbar" = "ggplot2",
"geom_path" = "ggplot2",
"geom_point" = "ggplot2",
@ -115,7 +137,7 @@ for (i in seq_len(length(import_functions))) {
# function should exist in foreign pkg namespace
if (AMR:::pkg_is_available(pkg,
also_load = FALSE,
min_version = if (pkg == "dplyr") "1.0.0" else NULL
min_version = if (pkg %in% c("dplyr", "tidyr")) "1.0.0" else NULL
)) {
tst <- !is.null(AMR:::import_fn(name = fn, pkg = pkg, error_on_fail = FALSE))
expect_true(tst,