mirror of https://github.com/msberends/AMR.git
(v2.1.1.9064) unit tests
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#!/bin/bash
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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 CODE: #
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# https://github.com/msberends/AMR #
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# #
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# PLEASE CITE THIS SOFTWARE AS: #
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# Berends MS, Luz CF, Friedrich AW, et al. (2022). #
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# AMR: An R Package for Working with Antimicrobial Resistance Data. #
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# Journal of Statistical Software, 104(3), 1-31. #
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# https://doi.org/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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# always add these:
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git add data-raw/*
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git add man/*
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git add R/sysdata.rda
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git add NAMESPACE
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git add DESCRIPTION
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git add NEWS.md
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@ -1,5 +1,5 @@
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Package: AMR
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Version: 2.1.1.9063
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Version: 2.1.1.9064
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Date: 2024-07-16
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Title: Antimicrobial Resistance Data Analysis
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Description: Functions to simplify and standardise antimicrobial resistance (AMR)
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2
NEWS.md
2
NEWS.md
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# AMR 2.1.1.9063
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# AMR 2.1.1.9064
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*(this beta version will eventually become v3.0. We're happy to reach a new major milestone soon, which will be all about the new One Health support! Install this beta using [the instructions here](https://msberends.github.io/AMR/#latest-development-version).)*
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19
R/mo.R
19
R/mo.R
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@ -420,17 +420,21 @@ as.mo <- function(x,
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# Keep or replace synonyms ----
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lpsn_matches <- AMR_env$MO_lookup$lpsn_renamed_to[match(out, AMR_env$MO_lookup$mo)]
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lpsn_matches[!lpsn_matches %in% AMR_env$MO_lookup$lpsn] <- NA
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# GBIF only for non-bacteria, since we use LPSN as primary source for bacteria
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mycobank_matches <- AMR_env$MO_lookup$mycobank_renamed_to[match(out, AMR_env$MO_lookup$mo)]
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mycobank_matches[!mycobank_matches %in% AMR_env$MO_lookup$mycobank] <- NA
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# GBIF only for non-bacteria and non-fungi, since we use LPSN as primary source for bacteria and MycoBank for fungi
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# (an example is Strep anginosus, renamed according to GBIF, not according to LPSN)
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gbif_matches <- AMR_env$MO_lookup$gbif_renamed_to[AMR_env$MO_lookup$kingdom != "Bacteria"][match(out, AMR_env$MO_lookup$mo[AMR_env$MO_lookup$kingdom != "Bacteria"])]
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gbif_matches <- AMR_env$MO_lookup$gbif_renamed_to[!AMR_env$MO_lookup$kingdom %in% c("Bacteria", "Fungi")][match(out, AMR_env$MO_lookup$mo[!AMR_env$MO_lookup$kingdom %in% c("Bacteria", "Fungi")])]
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gbif_matches[!gbif_matches %in% AMR_env$MO_lookup$gbif] <- NA
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AMR_env$mo_renamed <- list(
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old = out[!is.na(gbif_matches) | !is.na(lpsn_matches)],
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gbif_matches = gbif_matches[!is.na(gbif_matches) | !is.na(lpsn_matches)],
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lpsn_matches = lpsn_matches[!is.na(gbif_matches) | !is.na(lpsn_matches)]
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old = out[!is.na(gbif_matches) | !is.na(lpsn_matches) | !is.na(mycobank_matches)],
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gbif_matches = gbif_matches[!is.na(gbif_matches) | !is.na(lpsn_matches) | !is.na(mycobank_matches)],
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mycobank_matches = mycobank_matches[!is.na(gbif_matches) | !is.na(lpsn_matches) | !is.na(mycobank_matches)],
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lpsn_matches = lpsn_matches[!is.na(gbif_matches) | !is.na(lpsn_matches) | !is.na(mycobank_matches)]
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)
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if (isFALSE(keep_synonyms)) {
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out[which(!is.na(gbif_matches))] <- AMR_env$MO_lookup$mo[match(gbif_matches[which(!is.na(gbif_matches))], AMR_env$MO_lookup$gbif)]
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out[which(!is.na(mycobank_matches))] <- AMR_env$MO_lookup$mo[match(mycobank_matches[which(!is.na(mycobank_matches))], AMR_env$MO_lookup$mycobank)]
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out[which(!is.na(lpsn_matches))] <- AMR_env$MO_lookup$mo[match(lpsn_matches[which(!is.na(lpsn_matches))], AMR_env$MO_lookup$lpsn)]
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if (isTRUE(info) && length(AMR_env$mo_renamed$old) > 0) {
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print(mo_renamed(), extra_txt = " (use `keep_synonyms = TRUE` to leave uncorrected)")
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@ -1040,13 +1044,14 @@ convert_colloquial_input <- function(x) {
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out[x %like_case% "anaerob[a-z]+ .*gram[ -]?neg.*"] <- "B_ANAER-NEG"
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out[x %like_case% "anaerob[a-z]+ .*gram[ -]?pos.*"] <- "B_ANAER-POS"
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out[is.na(out) & x %like_case% "anaerob[a-z]+ (micro)?.*organism"] <- "B_ANAER"
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out[is.na(out) & x %like_case% "anaerob[a-z]+ bacter"] <- "B_ANAER"
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# coryneform bacteria
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out[x %like_case% "^coryneform"] <- "B_CORYNF"
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# yeasts and fungi
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out[x %like_case% "^yeast?"] <- "F_YEAST"
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out[x %like_case% "^fung(us|i)"] <- "F_FUNGUS"
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out[x %like_case% "(^| )yeast?"] <- "F_YEAST"
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out[x %like_case% "(^| )fung(us|i)"] <- "F_FUNGUS"
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# trivial names known to the field
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out[x %like_case% "meningo[ck]o[ck]"] <- "B_NESSR_MNNG"
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@ -122,7 +122,8 @@ create_species_cons_cops <- function(type = c("CoNS", "CoPS")) {
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"vitulinus", "vitulus", "warneri", "xylosus",
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"caledonicus", "canis",
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"durrellii", "lloydii",
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"ratti", "taiwanensis", "veratri", "urealyticus"
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"ratti", "taiwanensis", "veratri", "urealyticus",
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"americanisciuri", "marylandisciuri", "shinii", "brunensis"
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) |
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# old, now renamed to S. schleiferi (but still as synonym in our data of course):
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(MO_staph$species == "schleiferi" & MO_staph$subspecies %in% c("schleiferi", ""))),
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"Raoultella (here some text) terrigena"
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)
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))),
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c("B_MCRBC_PRXY", "B_STRPT_SUIS", "B_RLTLL_TRRG")
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c("B_MCRBC_PRXY", "B_STRPT_SUIS", "B_KLBSL_TRRG")
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)
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expect_stdout(print(mo_uncertainties()))
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x <- as.mo("Sta. aur")
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@ -104,10 +104,10 @@ expect_true(length(mo_group_members("B_HACEK")) > 1)
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expect_inherits(mo_group_members(c("Candida albicans", "Escherichia coli")), "list")
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expect_identical(mo_oxygen_tolerance(c("Klebsiella pneumoniae", "Clostridioides difficile")),
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c("aerobe", "anaerobe"))
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c("facultative anaerobe", "anaerobe"))
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expect_equal(as.character(table(mo_pathogenicity(example_isolates$mo))),
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c("1874", "109", "1", "16"))
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c("1911", "72", "1", "16"))
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expect_equal(mo_ref("Escherichia coli"), "Castellani et al., 1919")
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expect_equal(mo_authors("Escherichia coli"), "Castellani et al.")
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expect_true(mo_url("Candida albicans") %like% "gbif.org")
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expect_true(mo_url("Escherichia coli") %like% "lpsn.dsmz.de")
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# test integrity
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expect_identical(microorganisms$fullname, mo_fullname(microorganisms$fullname, language = "en", keep_synonyms = TRUE))
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# test integrity of getting back full names
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expect_identical(microorganisms$fullname[microorganisms$fullname %unlike% "(Fungi|{)"],
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suppressWarnings(mo_fullname(microorganisms$fullname[microorganisms$fullname %unlike% "(Fungi|{)"], language = "en", keep_synonyms = TRUE)))
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# check languages
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expect_equal(mo_type("Escherichia coli", language = "de"), "Bakterien")
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