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85 lines
3.8 KiB
R
Executable File
85 lines
3.8 KiB
R
Executable File
# ==================================================================== #
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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://amr-for-r.org #
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# ==================================================================== #
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test_that("tidymodels.R", {
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skip_on_cran()
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if (AMR:::pkg_is_available("recipes", also_load = TRUE) && AMR:::pkg_is_available("dplyr", also_load = TRUE)) {
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# SIR
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df <- tibble(
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sir1 = as.sir(c("S", "I", "R", "S", "R")),
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sir2 = as.sir(c("I", "R", "S", "R", "I")),
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not_sir = c("S", "R", "R", "S", "I")
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)
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rec <- recipe(~., data = df) %>% step_sir_numeric(all_sir())
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prepped <- prep(rec)
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baked <- bake(prepped, new_data = df)
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expect_inherits(baked$sir1, "numeric")
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expect_inherits(baked$sir2, "numeric")
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expect_equal(baked$not_sir, as.factor(df$not_sir))
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# MIC
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df <- tibble(
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mic_col1 = as.mic(c("<=0.002", "0.002", "0.004", "0.016", "32")),
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mic_col2 = as.mic(c("0.5", "1", "2", "4", "8")),
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non_mic = c(1, 2, 3, 4, 5)
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)
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rec <- recipe(~., data = df) %>% step_mic_log2(all_mic())
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prepped <- prep(rec)
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baked <- bake(prepped, new_data = df)
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expect_inherits(baked$mic_col1, "numeric")
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expect_inherits(baked$mic_col2, "numeric")
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expect_equal(baked$non_mic, df$non_mic)
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expect_equal(baked$mic_col2, log2(as.numeric(df$mic_col2)))
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# disk
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df <- tibble(
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disk_col = as.disk(c(21, 22, 23, 24, 25)),
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non_disk = c(21, 22, 23, 24, 25)
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)
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rec <- recipe(~., data = df) %>% step_rm(!all_disk())
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prepped <- prep(rec)
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baked <- bake(prepped, new_data = df)
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expect_inherits(baked$disk_col, "disk")
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# steps check
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df <- tibble(x = as.mic(c("1", "2", "4")))
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rec <- recipe(~x, data = df) %>% step_mic_log2(all_mic())
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prepped <- prep(rec)
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tidy_df <- tidy(prepped, number = 1)
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expect_equal(unname(tidy_df$terms), "x")
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df <- tibble(x = as.sir(c("S", "I", "R")))
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rec <- recipe(~x, data = df) %>% step_sir_numeric(all_sir())
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prepped <- prep(rec)
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tidy_df <- tidy(prepped, number = 1)
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expect_equal(unname(tidy_df$terms), "x")
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}
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})
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