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Align class name for grouped MC splits #482

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merged 2 commits into from
May 22, 2024
Merged

Align class name for grouped MC splits #482

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aafc978
align class name
hfrick May 21, 2024
9de50fe
Merge commit '3a1b4374848d4ee7922ce42b39938caa3eb0f217'
hfrick May 22, 2024
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4 changes: 4 additions & 0 deletions NEWS.md
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Expand Up @@ -4,6 +4,10 @@

* `vfold_cv()` now utilizes the `breaks` argument correctly for repeated cross-validation (@ZWael, #471).

## Breaking changes

* The class of grouped MC splits is now `group_mc_split` instead of `grouped_mc_split`, aligning it with the other grouped splits (#478).

* The `rsplit` objects of an `apparent()` split now have the correct class inheritance structure. The order is now `apparent_split` and then `rsplit` rather than the other way around (#477).


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2 changes: 1 addition & 1 deletion R/mc.R
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Expand Up @@ -239,7 +239,7 @@ group_mc_splits <- function(data, group, prop = 3 / 4, times = 25, strata = NULL
indices,
make_splits,
data = data,
class = c("grouped_mc_split", "mc_split")
class = c("group_mc_split", "mc_split")
)

all_assessable <- purrr::map(split_objs, function(x) nrow(assessment(x)))
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4 changes: 2 additions & 2 deletions tests/testthat/test-initial.R
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Expand Up @@ -45,7 +45,7 @@ test_that("default time param with lag", {

test_that("default group param", {
rs1 <- group_initial_split(dat1, c)
expect_equal(class(rs1), c("group_initial_split", "initial_split", "grouped_mc_split", "mc_split", "rsplit"))
expect_equal(class(rs1), c("group_initial_split", "initial_split", "group_mc_split", "mc_split", "rsplit"))
tr1 <- training(rs1)
ts1 <- testing(rs1)
expect_equal(nrow(tr1), nrow(dat1) * 3 / 4)
Expand Down Expand Up @@ -103,7 +103,7 @@ test_that("grouping -- strata", {

test_that("`prop` computes the proportion for group analysis", {
rs1 <- group_initial_split(dat1, c, prop = 1 / 2)
expect_equal(class(rs1), c("group_initial_split", "initial_split", "grouped_mc_split", "mc_split", "rsplit"))
expect_equal(class(rs1), c("group_initial_split", "initial_split", "group_mc_split", "mc_split", "rsplit"))
tr1 <- training(rs1)
ts1 <- testing(rs1)
expect_equal(nrow(tr1), nrow(dat1) * 1 / 2)
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