2018-12-16 22:45:12 +01:00
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# ==================================================================== #
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# TITLE #
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2021-02-02 23:57:35 +01:00
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# Antimicrobial Resistance (AMR) Data Analysis for R #
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2018-12-16 22:45:12 +01:00
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# #
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2019-01-02 23:24:07 +01:00
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# SOURCE #
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2020-07-08 14:48:06 +02:00
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# https://github.com/msberends/AMR #
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2018-12-16 22:45:12 +01:00
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# #
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# LICENCE #
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2020-12-27 00:30:28 +01:00
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# (c) 2018-2021 Berends MS, Luz CF et al. #
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2020-10-08 11:16:03 +02:00
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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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2018-12-16 22:45:12 +01:00
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# #
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2019-01-02 23:24:07 +01:00
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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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2020-01-05 17:22:09 +01:00
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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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2020-10-08 11:16:03 +02:00
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# #
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# Visit our website for the full manual and a complete tutorial about #
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2021-02-02 23:57:35 +01:00
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# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
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2018-12-16 22:45:12 +01:00
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# ==================================================================== #
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2018-08-12 17:44:06 +02:00
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context("ggplot_rsi.R")
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test_that("ggplot_rsi works", {
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2020-02-14 20:03:43 +01:00
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skip_on_cran()
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2020-07-31 10:50:08 +02:00
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skip_if_not_installed("ggplot2")
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2018-08-12 17:44:06 +02:00
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2020-09-26 16:26:01 +02:00
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library(dplyr, warn.conflicts = FALSE)
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2018-08-12 17:44:06 +02:00
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library(ggplot2)
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2020-09-25 14:44:50 +02:00
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pdf(NULL) # prevent Rplots.pdf being created
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2018-08-12 17:44:06 +02:00
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# data should be equal
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expect_equal(
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2019-11-10 12:16:56 +01:00
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(example_isolates %>% select(AMC, CIP) %>% ggplot_rsi())$data %>% summarise_all(resistance) %>% as.double(),
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example_isolates %>% select(AMC, CIP) %>% summarise_all(resistance) %>% as.double()
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2018-08-12 17:44:06 +02:00
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)
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2019-08-27 16:45:42 +02:00
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print(example_isolates %>% select(AMC, CIP) %>% ggplot_rsi(x = "interpretation", facet = "antibiotic"))
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print(example_isolates %>% select(AMC, CIP) %>% ggplot_rsi(x = "antibiotic", facet = "interpretation"))
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2019-06-27 11:57:45 +02:00
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2018-08-12 17:44:06 +02:00
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expect_equal(
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2019-11-10 12:16:56 +01:00
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(example_isolates %>% select(AMC, CIP) %>% ggplot_rsi(x = "interpretation", facet = "antibiotic"))$data %>% summarise_all(resistance) %>% as.double(),
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example_isolates %>% select(AMC, CIP) %>% summarise_all(resistance) %>% as.double()
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2018-08-12 17:44:06 +02:00
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)
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expect_equal(
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2019-11-10 12:16:56 +01:00
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(example_isolates %>% select(AMC, CIP) %>% ggplot_rsi(x = "antibiotic", facet = "interpretation"))$data %>% summarise_all(resistance) %>% as.double(),
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example_isolates %>% select(AMC, CIP) %>% summarise_all(resistance) %>% as.double()
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2018-08-12 17:44:06 +02:00
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)
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2018-08-22 00:02:26 +02:00
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expect_equal(
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2019-11-10 12:16:56 +01:00
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(example_isolates %>% select(AMC, CIP) %>% ggplot_rsi(x = "antibiotic", facet = "interpretation"))$data %>% summarise_all(count_resistant) %>% as.double(),
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example_isolates %>% select(AMC, CIP) %>% summarise_all(count_resistant) %>% as.double()
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2018-08-22 00:02:26 +02:00
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)
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2019-06-08 23:50:06 +02:00
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# support for scale_type ab and mo
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expect_equal(class((data.frame(mo = as.mo(c("e. coli", "s aureus")),
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n = c(40, 100)) %>%
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ggplot(aes(x = mo, y = n)) +
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geom_col())$data),
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"data.frame")
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expect_equal(class((data.frame(ab = as.ab(c("amx", "amc")),
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n = c(40, 100)) %>%
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ggplot(aes(x = ab, y = n)) +
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geom_col())$data),
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"data.frame")
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2018-08-12 17:44:06 +02:00
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})
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