Nothing
library(testthat)
library(shinymodels)
source(test_path("helper.R"))
test_that("can accurately plot predicted probabilities vs true class plot", {
skip_on_cran()
data(scat_fda_bt)
org <- organize_data(scat_fda_bt)
org$predictions$.color <- "black"
expect_snapshot(
error = TRUE,
plot_multiclass_obs_pred(org, org$y_name)
)
a <- plot_multiclass_obs_pred(org$predictions, org$y_name)
expect_doppelganger("plot_multiclass_obs_pred", a)
})
test_that("can accurately plot confusion matrix plot", {
skip_on_cran()
data(scat_fda_bt)
org <- organize_data(scat_fda_bt)
org$predictions$.color <- "black"
expect_snapshot(
error = TRUE,
plot_multiclass_conf_mat(org)
)
b <- plot_multiclass_conf_mat(org$predictions)
expect_doppelganger("plot_multiclass_conf_mat", b)
})
test_that("can accurately plot predicted probabilities vs. a numeric column plot", {
skip_on_cran()
data(scat_fda_bt)
org <- organize_data(scat_fda_bt)
org$predictions$.color <- "black"
expect_snapshot(
error = TRUE,
plot_multiclass_pred_numcol(org, org$y_name, "Diameter")
)
expect_snapshot_error(
plot_multiclass_pred_numcol(org$predictions, y_name)
)
suppressWarnings(
expect_snapshot_error(
plot_multiclass_pred_numcol(org$predictions, org$y_name, "AXL")
)
)
expect_warning(
c <- plot_multiclass_pred_numcol(org$predictions, org$y_name, "Diameter"),
"Ignoring unknown aesthetics"
)
expect_doppelganger("plot_multiclass_pred_numcol", c)
})
test_that("can accurately plot predicted probabilities vs. a factor column plot", {
skip_on_cran()
data(scat_fda_bt)
org <- organize_data(scat_fda_bt)
org$predictions$.color <- "black"
expect_snapshot(
error = TRUE,
plot_multiclass_pred_factorcol(org, org$y_name, "tectonic_settings")
)
expect_snapshot_error(
plot_multiclass_pred_factorcol(org$predictions, y_name)
)
suppressWarnings(
expect_snapshot_error(
plot_multiclass_pred_factorcol(org$predictions, org$y_name, "Genotype"),
)
)
expect_warning(
d <- plot_multiclass_pred_factorcol(org$predictions, org$y_name, "Month"),
"Ignoring unknown aesthetics"
)
expect_doppelganger("plot_multiclass_pred_factorcol", d)
})
test_that("can accurately plot the ROC curve", {
# Remove with yardstick version >1.1.0.9000
withr::local_options(lifecycle_verbosity = "quiet")
skip_on_cran()
data(scat_fda_bt)
org <- organize_data(scat_fda_bt)
org$predictions$.color <- "black"
expect_snapshot(
error = TRUE,
plot_multiclass_roc(org, org$y_name)
)
expect_snapshot_error(
plot_multiclass_roc()
)
e <- plot_multiclass_roc(org$predictions, org$y_name)
expect_doppelganger("plot_multiclass_roc", e)
})
test_that("can accurately plot the PR curve", {
# Remove with yardstick version >1.1.0.9000
withr::local_options(lifecycle_verbosity = "quiet")
skip_on_cran()
data(scat_fda_bt)
org <- organize_data(scat_fda_bt)
org$predictions$.color <- "black"
expect_snapshot(
error = TRUE,
plot_multiclass_pr(org, org$y_name)
)
expect_snapshot_error(
plot_multiclass_pr()
)
f <- plot_multiclass_pr(org$predictions, org$y_name)
expect_doppelganger("plot_multiclass_pr", f)
})
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