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75 lines
5.2 KiB
R
75 lines
5.2 KiB
R
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Data Analysis for R #
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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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# LICENCE #
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# (c) 2018-2021 Berends MS, Luz CF et al. #
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# Developed at the University of Groningen, the Netherlands, in #
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# collaboration with non-profit organisations Certe Medical #
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# Diagnostics & Advice, and University Medical Center Groningen. #
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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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# antibiotic class selectors
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expect_true(ncol(example_isolates[, ab_class("antimyco"), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, aminoglycosides(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, aminopenicillins(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, betalactams(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, carbapenems(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, cephalosporins(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, cephalosporins_1st(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, cephalosporins_2nd(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, cephalosporins_3rd(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, cephalosporins_4th(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, cephalosporins_5th(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, fluoroquinolones(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, glycopeptides(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, lincosamides(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, lipoglycopeptides(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, macrolides(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, oxazolidinones(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, penicillins(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, polymyxins(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, streptogramins(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, quinolones(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, tetracyclines(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, trimethoprims(), drop = FALSE]) < ncol(example_isolates))
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expect_true(ncol(example_isolates[, ureidopenicillins(), drop = FALSE]) < ncol(example_isolates))
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# Examples:
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# select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB'
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expect_equal(ncol(example_isolates[, c("mo", aminoglycosides())]), 5, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, c(administerable_per_os() & penicillins())]), 5, tolerance = 0.5)
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expect_equal(ncol(example_isolates[, c(administerable_iv() & penicillins())]), 7, tolerance = 0.5)
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# filter using any() or all()
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expect_equal(nrow(example_isolates[any(carbapenems() == "R"), ]), 55, tolerance = 0.5)
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expect_equal(nrow(subset(example_isolates, any(carbapenems() == "R"))), 55, tolerance = 0.5)
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# filter on any or all results in the carbapenem columns (i.e., IPM, MEM):
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expect_equal(nrow(example_isolates[any(carbapenems()), ]), 962, tolerance = 0.5)
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expect_equal(nrow(example_isolates[all(carbapenems()), ]), 756, tolerance = 0.5)
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# filter with multiple antibiotic selectors using c()
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expect_equal(nrow(example_isolates[all(c(carbapenems(), aminoglycosides()) == "R"), ]), 26, tolerance = 0.5)
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# filter + select in one go: get penicillins in carbapenems-resistant strains
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expect_equal(nrow(example_isolates[any(carbapenems() == "R"), penicillins()]), 55, tolerance = 0.5)
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expect_equal(ncol(example_isolates[any(carbapenems() == "R"), penicillins()]), 7, tolerance = 0.5)
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