# Residuals -------------------------------------------------------------------
test_that("a `tibble` of residuals are extracted from `lm` model", {
local_edition(3)
resids_tbl <- calculate_residuals(mod_lm_fit)
expect_s3_class(resids_tbl, "tbl_df")
check_names(resids_tbl, c(".pred", ".resid"))
expect_snapshot(utils::head(resids_tbl, n = 10))
})
test_that("a `tibble` of residuals is calculated using an `lm` model", {
local_edition(3)
resids_tbl <- calculate_residuals(mod_lm_fit, mtcars[1:10, ])
expect_s3_class(resids_tbl, "tbl_df")
check_names(resids_tbl, c(".pred", ".resid"))
expect_snapshot(utils::head(resids_tbl, n = 10))
})
# Plots -----------------------------------------------------------------------
test_that("can plot a predictions vs residuals plot from `data.frame` input", {
local_edition(3)
skip_if_not_installed("vdiffr")
resids_df <- data.frame(
.pred = c(23.6, 22.6, 25.3, 21.2, 18.2, 20.5, 15.6),
.resid = c(-2.57, -1.60, -2.49, 0.183, 0.459, -2.37, -1.27)
)
vdiffr::expect_doppelganger(
title = "Predictions vs Residuals Plot",
fig = plot_predictions_vs_residuals(resids_df)
)
})
test_that("can plot a QQ-plot from `data.frame` input", {
local_edition(3)
skip_if_not_installed("vdiffr")
resids_df <- data.frame(
.pred = c(23.6, 22.6, 25.3, 21.2, 18.2, 20.5, 15.6),
.resid = c(-2.57, -1.60, -2.49, 0.183, 0.459, -2.37, -1.27)
)
vdiffr::expect_doppelganger(
title = "QQ-Plot",
fig = plot_qq_normality(resids_df)
)
})
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