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57 lines
2.9 KiB
R
57 lines
2.9 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) 2018-2022 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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test_df <- rbind(
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data.frame(
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date = as.Date(c("2015-01-01", "2015-10-01", "2016-02-04", "2016-12-31", "2017-01-01", "2017-02-01", "2017-02-05", "2020-01-01")),
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patient_id = "A"
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),
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data.frame(
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date = as.Date(c("2015-01-01", "2016-02-01", "2016-12-31", "2017-01-01", "2017-02-03")),
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patient_id = "B"
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))
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expect_equal(get_episode(test_df$date, 365),
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c(1, 1, 2, 2, 2, 3, 3, 4, 1, 2, 2, 2, 3))
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expect_equal(get_episode(test_df$date[which(test_df$patient_id == "A")], 365),
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c(1, 1, 2, 2, 2, 2, 3, 4))
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expect_equal(get_episode(test_df$date[which(test_df$patient_id == "B")], 365),
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c(1, 2, 2, 2, 3))
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if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0")) {
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expect_identical(test_df %>% group_by(patient_id) %>% mutate(f = is_new_episode(date, 365)) %>% pull(f),
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c(TRUE, FALSE, TRUE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE))
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suppressMessages(
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x <- example_isolates %>%
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mutate(out = first_isolate(., include_unknown = TRUE, method = "episode-based", info = FALSE))
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)
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y <- example_isolates %>%
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group_by(patient_id, mo) %>%
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mutate(out = is_new_episode(date, 365))
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expect_identical(which(x$out), which(y$out))
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}
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