Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

skip snapshots with glue() error on R 4.3.3+ #210

Merged
merged 2 commits into from
Mar 4, 2024
Merged

skip snapshots with glue() error on R 4.3.3+ #210

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
2f0b3d8
skip snapshots with `glue()` error on R 4.3.3+
simonpcouch Mar 4, 2024
8dad6c4
update snaps for survival/finetune
simonpcouch Mar 4, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
30 changes: 15 additions & 15 deletions tests/testthat/_snaps/survival-tune_race_anova.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -42,11 +42,11 @@
# A tibble: 5 x 6
cost_complexity .metric .eval_time mean n std_err
<dbl> <chr> <dbl> <dbl> <int> <dbl>
1 0.0000000001 brier_survival 1 0.177 30 0.00707
2 0.0841 brier_survival 1 0.201 30 0.00415
3 0.0891 brier_survival 1 0.201 30 0.00415
4 0.0944 brier_survival 1 0.201 30 0.00415
5 0.1 brier_survival 1 0.201 30 0.00415
1 0.0841 brier_survival 1 0.201 30 0.00415
2 0.0891 brier_survival 1 0.201 30 0.00415
3 0.0944 brier_survival 1 0.201 30 0.00415
4 0.1 brier_survival 1 0.201 30 0.00415
5 0.0794 brier_survival 1 0.202 30 0.00418

---

Expand All @@ -69,11 +69,11 @@
# A tibble: 5 x 6
cost_complexity .metric .eval_time mean n std_err
<dbl> <chr> <dbl> <dbl> <int> <dbl>
1 0.0000000001 brier_survival 1 0.177 30 0.00707
2 0.0841 brier_survival 1 0.201 30 0.00415
3 0.0891 brier_survival 1 0.201 30 0.00415
4 0.0944 brier_survival 1 0.201 30 0.00415
5 0.1 brier_survival 1 0.201 30 0.00415
1 0.0841 brier_survival 1 0.201 30 0.00415
2 0.0891 brier_survival 1 0.201 30 0.00415
3 0.0944 brier_survival 1 0.201 30 0.00415
4 0.1 brier_survival 1 0.201 30 0.00415
5 0.0794 brier_survival 1 0.202 30 0.00418

---

Expand All @@ -87,11 +87,11 @@
# A tibble: 5 x 6
cost_complexity .metric .eval_time mean n std_err
<dbl> <chr> <dbl> <dbl> <int> <dbl>
1 0.0000000001 brier_survival_integrated NA 0.285 30 0.00426
2 0.0794 brier_survival_integrated NA 0.338 30 0.00487
3 0.0841 brier_survival_integrated NA 0.338 30 0.00480
4 0.0891 brier_survival_integrated NA 0.338 30 0.00480
5 0.0944 brier_survival_integrated NA 0.338 30 0.00480
1 0.0794 brier_survival_integrated NA 0.338 30 0.00487
2 0.0841 brier_survival_integrated NA 0.338 30 0.00480
3 0.0891 brier_survival_integrated NA 0.338 30 0.00480
4 0.0944 brier_survival_integrated NA 0.338 30 0.00480
5 0.1 brier_survival_integrated NA 0.338 30 0.00480

# race tuning (anova) - unneeded eval_time

Expand Down
2 changes: 1 addition & 1 deletion tests/testthat/test-glmnet-linear.R
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -265,6 +265,7 @@ test_that('multi_predict() with default or single penalty value', {

test_that('error traps', {
skip_if_not_installed("glmnet")
skip_if_not_installed("parsnip", minimum_version = "1.2.0.9001")

expect_snapshot(error = TRUE, {
linear_reg(penalty = 0.01) %>%
Expand All @@ -277,7 +278,6 @@ test_that('error traps', {
set_engine("glmnet") %>%
fit(mpg ~ ., data = mtcars[-(1:4), ])
})
skip_if_not_installed("parsnip", minimum_version = "1.0.4.9003")
expect_snapshot(error = TRUE, {
linear_reg(penalty = 0.01) %>%
set_engine("glmnet") %>%
Expand Down
2 changes: 1 addition & 1 deletion tests/testthat/test-glmnet-logistic.R
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -377,6 +377,7 @@ test_that("class predictions are factors with all levels", {

test_that('error traps', {
skip_if_not_installed("glmnet")
skip_if_not_installed("parsnip", minimum_version = "1.2.0.9001")

data("lending_club", package = "modeldata", envir = rlang::current_env())

Expand All @@ -393,7 +394,6 @@ test_that('error traps', {
fit(Class ~ log(funded_amnt) + int_rate + term,
data = lending_club)
})
skip_if_not_installed("parsnip", minimum_version = "1.0.4.9003")
expect_snapshot(error = TRUE, {
logistic_reg(penalty = 0.01) %>%
set_engine("glmnet") %>%
Expand Down
2 changes: 1 addition & 1 deletion tests/testthat/test-glmnet-multinom.R
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -399,6 +399,7 @@ test_that("class predictions are factors with all levels", {

test_that('error traps', {
skip_if_not_installed("glmnet")
skip_if_not_installed("parsnip", minimum_version = "1.2.0.9001")

data("hpc_data", package = "modeldata", envir = rlang::current_env())

Expand All @@ -413,7 +414,6 @@ test_that('error traps', {
set_engine("glmnet") %>%
fit(class ~ ., data = hpc_data)
})
skip_if_not_installed("parsnip", minimum_version = "1.0.4.9003")
expect_snapshot(error = TRUE, {
multinom_reg(penalty = 0.01) %>%
set_engine("glmnet") %>%
Expand Down
1 change: 1 addition & 0 deletions tests/testthat/test-glmnet-poisson.R
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -134,6 +134,7 @@ test_that("model errors on missing penalty value", {

test_that("predict() errors with multiple penalty values", {
skip_if_not_installed("glmnet")
skip_if_not_installed("parsnip", minimum_version = "1.2.0.9001")

skip_if_not_installed("poissonreg", minimum_version = "1.0.1.9000")
expect_snapshot(error = TRUE, {
Expand Down
Loading