# ==================================================================== # # 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/ # # ==================================================================== # b <- suppressWarnings(bug_drug_combinations(example_isolates)) expect_inherits(b, "bug_drug_combinations") expect_stdout(suppressMessages(print(b))) expect_true(is.data.frame(format(b))) expect_true(is.data.frame(format(b, add_ab_group = FALSE))) if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0", also_load = TRUE)) { expect_true(example_isolates %>% group_by(ward) %>% bug_drug_combinations(FUN = mo_gramstain) %>% is.data.frame()) }