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(cell_race)
org <- organize_data(cell_race)
org$predictions$.color <- "black"
expect_error(
plot_twoclass_obs_pred(org, org$y_name),
"'class' is not a column in the dataset"
)
expect_error(
plot_twoclass_obs_pred(org$predictions, y_name),
"object 'y_name' not found"
)
a <- plot_twoclass_obs_pred(org$predictions, org$y_name)
expect_snapshot_output(make_clean_snapshot(a))
})
test_that("can accurately plot confusion matrix plot", {
skip_on_cran()
data(cell_race)
org <- organize_data(cell_race)
org$predictions$.color <- "black"
expect_error(
plot_twoclass_conf_mat(org),
"no applicable method for 'conf_mat' applied to an object of class"
)
b <- plot_twoclass_conf_mat(org$predictions)
expect_snapshot_output(make_clean_snapshot(b))
})
test_that("can accurately plot predicted probabilities vs. a numeric column plot", {
skip_on_cran()
data(cell_race)
org <- organize_data(cell_race)
org$predictions$.color <- "black"
expect_error(
plot_twoclass_pred_numcol(org, org$y_name, "AXL"),
"'class' is not a column in the dataset"
)
expect_error(
plot_twoclass_pred_numcol(org$predictions, y_name, "AXL"),
"object 'y_name' not found"
)
expect_warning(
expect_error(
plot_twoclass_pred_numcol(org$predictions, org$y_name, "potato"),
"object 'potato' not found"
),
"Ignoring unknown aesthetics"
)
expect_warning(
c <- plot_twoclass_pred_numcol(org$predictions, org$y_name, "angle_ch_1"),
"Ignoring unknown aesthetics"
)
expect_snapshot_output(make_clean_snapshot(c))
})
test_that("can accurately plot predicted probabilities vs. a factor column plot", {
skip_on_cran()
data(cell_race)
org <- organize_data(cell_race)
set.seed(1)
org$predictions <-
org$predictions %>%
mutate(
fact_col = sample(letters[1:2], nrow(org$predictions), replace = TRUE),
fact_col = factor(fact_col),
.color = "black"
)
expect_error(
plot_twoclass_pred_factorcol(org, org$y_name, "fact_col"),
"'class' is not a column in the dataset"
)
expect_error(
plot_twoclass_pred_factorcol(org$predictions, y_name, "fact_col"),
"object 'y_name' not found"
)
expect_warning(
expect_error(
plot_twoclass_pred_factorcol(org$predictions, org$y_name, "potato"),
"object 'potato' not found"
),
"Ignoring unknown aesthetics"
)
expect_warning(
d <- plot_twoclass_pred_factorcol(org$predictions, org$y_name, "fact_col"),
"Ignoring unknown aesthetics"
)
expect_snapshot_output(make_clean_snapshot(d))
})
test_that("can accurately plot the ROC curve", {
skip_on_cran()
data(cell_race)
org <- organize_data(cell_race)
org$predictions$.color <- "black"
expect_error(
plot_twoclass_roc(org, org$y_name),
"'class' is not a column in the dataset"
)
expect_error(
plot_twoclass_roc(org$predictions, y_name),
"object 'y_name' not found"
)
e <- plot_twoclass_roc(org$predictions, org$y_name)
expect_snapshot_output(make_clean_snapshot(e))
})
test_that("can accurately plot the PR curve", {
skip_on_cran()
data(cell_race)
org <- organize_data(cell_race)
org$predictions$.color <- "black"
expect_error(
plot_twoclass_pr(org, org$y_name),
"'class' is not a column in the dataset"
)
expect_error(
plot_twoclass_pr(org$predictions, y_name),
"object 'y_name' not found"
)
expect_error(
plot_twoclass_pr(org$predictions, "mpg"),
"'mpg' is not a column in the dataset"
)
f <- plot_twoclass_pr(org$predictions, org$y_name)
expect_snapshot_output(make_clean_snapshot(f))
})
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.