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(v3.0.1.9005) re-add tidymodels implementation

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dr. M.S. (Matthijs) Berends
2025-12-21 12:19:43 +01:00
parent 225c73f7e7
commit 151af21f38
16 changed files with 502 additions and 61 deletions
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tests/testthat/test-tidymodels.R Executable file
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# ==================================================================== #
# TITLE: #
# AMR: An R Package for Working with Antimicrobial Resistance Data #
# #
# SOURCE CODE: #
# https://github.com/msberends/AMR #
# #
# PLEASE CITE THIS SOFTWARE AS: #
# Berends MS, Luz CF, Friedrich AW, et al. (2022). #
# AMR: An R Package for Working with Antimicrobial Resistance Data. #
# Journal of Statistical Software, 104(3), 1-31. #
# https://doi.org/10.18637/jss.v104.i03 #
# #
# Developed at the University of Groningen and the University Medical #
# Center Groningen in The Netherlands, in collaboration with many #
# colleagues from around the world, see our website. #
# #
# This R package is free software; you can freely use and distribute #
# it for both personal and commercial purposes under the terms of the #
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
# the Free Software Foundation. #
# We created this package for both routine data analysis and academic #
# research and it was publicly released in the hope that it will be #
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
# #
# Visit our website for the full manual and a complete tutorial about #
# how to conduct AMR data analysis: https://amr-for-r.org #
# ==================================================================== #
test_that("tidymodels.R", {
skip_on_cran()
if (AMR:::pkg_is_available("recipes", also_load = TRUE) && AMR:::pkg_is_available("dplyr", also_load = TRUE)) {
# SIR
df <- tibble(
sir1 = as.sir(c("S", "I", "R", "S", "R")),
sir2 = as.sir(c("I", "R", "S", "R", "I")),
not_sir = c("S", "R", "R", "S", "I")
)
rec <- recipe(~., data = df) %>% step_sir_numeric(all_sir())
prepped <- prep(rec)
baked <- bake(prepped, new_data = df)
expect_inherits(baked$sir1, "numeric")
expect_inherits(baked$sir2, "numeric")
expect_equal(baked$not_sir, as.factor(df$not_sir))
# MIC
df <- tibble(
mic_col1 = as.mic(c("<=0.002", "0.002", "0.004", "0.016", "32")),
mic_col2 = as.mic(c("0.5", "1", "2", "4", "8")),
non_mic = c(1, 2, 3, 4, 5)
)
rec <- recipe(~., data = df) %>% step_mic_log2(all_mic())
prepped <- prep(rec)
baked <- bake(prepped, new_data = df)
expect_inherits(baked$mic_col1, "numeric")
expect_inherits(baked$mic_col2, "numeric")
expect_equal(baked$non_mic, df$non_mic)
expect_equal(baked$mic_col2, log2(as.numeric(df$mic_col2)))
# disk
df <- tibble(
disk_col = as.disk(c(21, 22, 23, 24, 25)),
non_disk = c(21, 22, 23, 24, 25)
)
rec <- recipe(~., data = df) %>% step_rm(!all_disk())
prepped <- prep(rec)
baked <- bake(prepped, new_data = df)
expect_inherits(baked$disk_col, "disk")
# steps check
df <- tibble(x = as.mic(c("1", "2", "4")))
rec <- recipe(~x, data = df) %>% step_mic_log2(all_mic())
prepped <- prep(rec)
tidy_df <- tidy(prepped, number = 1)
expect_equal(unname(tidy_df$terms), "x")
df <- tibble(x = as.sir(c("S", "I", "R")))
rec <- recipe(~x, data = df) %>% step_sir_numeric(all_sir())
prepped <- prep(rec)
tidy_df <- tidy(prepped, number = 1)
expect_equal(unname(tidy_df$terms), "x")
}
})