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89 lines
4.4 KiB
R
89 lines
4.4 KiB
R
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Analysis #
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# #
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# SOURCE #
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# https://gitlab.com/msberends/AMR #
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# #
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# LICENCE #
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# (c) 2018-2020 Berends MS, Luz CF et al. #
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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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# #
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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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# Visit our website for more info: https://msberends.gitlab.io/AMR. #
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# ==================================================================== #
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context("resistance_predict.R")
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test_that("prediction of rsi works", {
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AMX_R <- example_isolates %>%
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filter(mo == "B_ESCHR_COLI") %>%
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rsi_predict(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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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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x <- resistance_predict(example_isolates, col_ab = "AMX", year_min = 2010, model = "binomial")
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plot(x)
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ggplot_rsi_predict(x)
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expect_error(ggplot_rsi_predict(example_isolates))
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library(dplyr)
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expect_output(rsi_predict(x = filter(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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expect_output(rsi_predict(x = filter(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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expect_output(rsi_predict(x = filter(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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expect_error(rsi_predict(x = filter(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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expect_error(rsi_predict(x = filter(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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expect_error(rsi_predict(x = filter(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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expect_error(rsi_predict(x = filter(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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expect_error(rsi_predict(x = filter(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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# almost all E. coli are MEM S in the Netherlands :)
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expect_error(resistance_predict(x = filter(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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