test_that("error handling works", {
df <- data.frame(
subj = 1:30,
y = sample.int(30, replace = TRUE),
x = sample(c("A", "B"), 30, replace = TRUE, prob = c(0.6, 0.4))
)
m <- stats::glm(y ~ x, df, family = poisson())
expect_error(
plot_bland_altman(m),
glue::glue(
"The method `model_data` is not yet implemented for an object \\
of class `glm`.
If you would like it to be implemented, please file an issue at \\
https://github.com/verasls/lvmisc/issues."
),
class = "error_no_method_for_class"
)
expect_error(
plot_bland_altman("m"),
glue::glue(
"The method `model_data` is not yet implemented for an object \\
of class `character`.
If you would like it to be implemented, please file an issue at \\
https://github.com/verasls/lvmisc/issues."
),
class = "error_no_method_for_class"
)
})
test_that("output of plot_bland_altman() is stable", {
mtcars <- tibble::as_tibble(mtcars, rownames = "car")
m1 <- stats::lm(disp ~ mpg, mtcars)
m2 <- lme4::lmer(disp ~ mpg + (1 | gear), mtcars)
cv <- loo_cv(m1, mtcars, car)
skip_on_ci()
skip_on_cran()
vdiffr::expect_doppelganger(
"Bland Altman plot - cv",
plot_bland_altman(cv, colour = as.factor(am))
)
vdiffr::expect_doppelganger(
"Bland Altman plot - lm",
plot_bland_altman(m1)
)
vdiffr::expect_doppelganger(
"Bland Altman plot - lmerMod",
plot_bland_altman(m2)
)
})
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