mirror of https://github.com/msberends/AMR.git
65 lines
3.9 KiB
R
65 lines
3.9 KiB
R
# ==================================================================== #
|
|
# TITLE: #
|
|
# AMR: An R Package for Working with Antimicrobial Resistance Data #
|
|
# #
|
|
# SOURCE CODE: #
|
|
# https://github.com/msberends/AMR #
|
|
# #
|
|
# PLEASE CITE THIS SOFTWARE 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. #
|
|
# https://doi.org/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/ #
|
|
# ==================================================================== #
|
|
|
|
sir <- random_sir(100)
|
|
rsi <- sir
|
|
class(rsi) <- gsub("sir", "rsi", class(rsi))
|
|
mic <- random_mic(100)
|
|
disk <- random_disk(100)
|
|
|
|
expect_identical(summary(sir), summary(rsi))
|
|
expect_identical(c(sir), c(rsi))
|
|
|
|
expect_identical(suppressWarnings(suppressMessages(as.rsi(as.character(rsi)))),
|
|
suppressWarnings(suppressMessages(as.sir(as.character(sir)))))
|
|
expect_identical(suppressWarnings(suppressMessages(as.rsi(mic, mo = "Escherichia coli", ab = "CIP"))),
|
|
suppressWarnings(suppressMessages(as.sir(mic, mo = "Escherichia coli", ab = "CIP"))))
|
|
expect_identical(suppressWarnings(suppressMessages(as.rsi(disk, mo = "Escherichia coli", ab = "CIP"))),
|
|
suppressWarnings(suppressMessages(as.sir(disk, mo = "Escherichia coli", ab = "CIP"))))
|
|
expect_identical(suppressWarnings(suppressMessages(as.rsi(data.frame(CIP = mic, mo = "Escherichia coli")))),
|
|
suppressWarnings(suppressMessages(as.sir(data.frame(CIP = mic, mo = "Escherichia coli")))))
|
|
|
|
expect_identical(suppressWarnings(n_rsi(example_isolates$CIP)),
|
|
suppressWarnings(n_sir(example_isolates$CIP)))
|
|
|
|
expect_identical(suppressWarnings(rsi_df(example_isolates)),
|
|
suppressWarnings(sir_df(example_isolates)))
|
|
|
|
expect_identical(suppressWarnings(is.rsi.eligible(example_isolates)),
|
|
suppressWarnings(is_sir_eligible(example_isolates)))
|
|
|
|
if (AMR:::pkg_is_available("ggplot2")) {
|
|
expect_equal(suppressWarnings(ggplot_rsi(example_isolates[, c("CIP", "GEN", "TOB")])),
|
|
suppressWarnings(ggplot_sir(example_isolates[, c("CIP", "GEN", "TOB")])))
|
|
|
|
p <- ggplot2::ggplot(example_isolates[, c("CIP", "GEN", "TOB")])
|
|
expect_equal(suppressWarnings(p + geom_rsi() + scale_rsi_colours() + labels_rsi_count() + facet_rsi() + theme_rsi()),
|
|
suppressWarnings(p + geom_sir() + scale_sir_colours() + labels_sir_count() + facet_sir() + theme_sir()))
|
|
}
|