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121 lines
4.3 KiB
R
121 lines
4.3 KiB
R
# ==================================================================== #
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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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if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0", also_load = TRUE)) {
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expect_stdout(AMX_R <- example_isolates %>%
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filter(mo == "B_ESCHR_COLI") %>%
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sir_predict(
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col_ab = "AMX",
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col_date = "date",
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model = "binomial",
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minimum = 10,
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info = TRUE
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) %>%
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pull("value"))
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# AMX resistance will increase according to data set `example_isolates`
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expect_true(AMX_R[3] < AMX_R[20])
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}
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expect_stdout(x <- suppressMessages(resistance_predict(example_isolates,
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col_ab = "AMX",
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year_min = 2010,
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model = "binomial",
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info = TRUE
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)))
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pdf(NULL) # prevent Rplots.pdf being created
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expect_silent(plot(x))
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if (AMR:::pkg_is_available("ggplot2")) {
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expect_silent(ggplot_sir_predict(x))
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expect_silent(ggplot2::autoplot(x))
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expect_error(ggplot_sir_predict(example_isolates))
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}
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expect_stdout(sir_predict(
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x = subset(example_isolates, mo == "B_ESCHR_COLI"),
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model = "binomial",
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col_ab = "AMX",
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col_date = "date",
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info = TRUE
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))
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expect_stdout(sir_predict(
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x = subset(example_isolates, mo == "B_ESCHR_COLI"),
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model = "loglin",
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col_ab = "AMX",
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col_date = "date",
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info = TRUE
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))
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expect_stdout(sir_predict(
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x = subset(example_isolates, mo == "B_ESCHR_COLI"),
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model = "lin",
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col_ab = "AMX",
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col_date = "date",
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info = TRUE
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))
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expect_error(sir_predict(
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x = subset(example_isolates, mo == "B_ESCHR_COLI"),
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model = "INVALID MODEL",
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col_ab = "AMX",
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col_date = "date",
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info = TRUE
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))
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expect_error(sir_predict(
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x = subset(example_isolates, mo == "B_ESCHR_COLI"),
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model = "binomial",
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col_ab = "NOT EXISTING COLUMN",
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col_date = "date",
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info = TRUE
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))
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expect_error(sir_predict(
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x = subset(example_isolates, mo == "B_ESCHR_COLI"),
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model = "binomial",
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col_ab = "AMX",
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col_date = "NOT EXISTING COLUMN",
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info = TRUE
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))
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expect_error(sir_predict(
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x = subset(example_isolates, mo == "B_ESCHR_COLI"),
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col_ab = "AMX",
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col_date = "NOT EXISTING COLUMN",
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info = TRUE
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))
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expect_error(sir_predict(
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x = subset(example_isolates, mo == "B_ESCHR_COLI"),
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col_ab = "AMX",
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col_date = "date",
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info = TRUE
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))
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# almost all E. coli are MEM S in the Netherlands :)
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expect_error(resistance_predict(
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x = subset(example_isolates, mo == "B_ESCHR_COLI"),
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model = "binomial",
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col_ab = "MEM",
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col_date = "date",
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info = TRUE
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))
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