tests/testthat/test-caret.R
In tidymodels/rsample: General Resampling Infrastructure
###################################################################
## Test cases for caret -> rsample that mimic `trainControl`
check_indices <- function(newer, orig) {
for (i in seq_along(newer$splits)) {
expect_equal(
as.integer(newer$splits[[i]]),
orig$index[[i]]
)
expect_equal(
as.integer(newer$splits[[i]], "assessment"),
orig$indexOut[[i]]
)
}
invisible(NULL)
}
###################################################################
test_that("basic v-fold", {
cv_1 <- structure(
list(
method = "cv",
index = structure(
list(
Fold1 = c(2L, 3L, 4L, 5L, 6L, 7L, 8L, 10L, 11L, 13L),
Fold2 = c(
1L,
4L,
6L,
8L,
9L,
10L,
11L,
12L,
13L,
14L,
15L
),
Fold3 = c(1L, 2L, 3L, 5L, 7L, 9L, 12L, 14L, 15L)
),
.Names = c("Fold1", "Fold2", "Fold3")
),
indexOut = structure(
list(
Resample1 = c(1L, 9L, 12L, 14L, 15L),
Resample2 = c(2L, 3L, 5L, 7L),
Resample3 = c(4L, 6L, 8L, 10L, 11L, 13L)
),
.Names = c("Resample1", "Resample2", "Resample3")
),
number = 3,
repeats = NA
),
.Names = c("method", "index", "indexOut", "number", "repeats")
)
dat <- data.frame(y = 1:15, x = 15:1)
vfold_obj_1 <- caret2rsample(cv_1, data = dat)
check_indices(vfold_obj_1, cv_1)
for (i in seq_along(vfold_obj_1$splits)) {
expect_equal(vfold_obj_1$id[[i]], names(cv_1$index)[i])
}
})
test_that("repeated v-fold", {
cv_2 <-
structure(
list(
method = "repeatedcv",
index = structure(
list(
Fold1.Rep1 = c(1L, 3L, 4L, 6L, 9L, 10L, 12L, 13L, 14L, 15L),
Fold2.Rep1 = c(2L, 5L, 7L, 8L, 10L, 11L, 13L, 14L, 15L),
Fold3.Rep1 = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 11L, 12L),
Fold1.Rep2 = c(1L, 2L, 3L, 5L, 6L, 7L, 10L, 11L, 12L, 14L),
Fold2.Rep2 = c(2L, 4L, 6L, 8L, 9L, 11L, 13L, 14L, 15L),
Fold3.Rep2 = c(1L, 3L, 4L, 5L, 7L, 8L, 9L, 10L, 12L, 13L, 15L)
),
.Names = c(
"Fold1.Rep1",
"Fold2.Rep1",
"Fold3.Rep1",
"Fold1.Rep2",
"Fold2.Rep2",
"Fold3.Rep2"
)
),
indexOut = structure(
list(
Resample1 = c(2L, 5L, 7L, 8L, 11L),
Resample2 = c(1L, 3L, 4L, 6L, 9L, 12L),
Resample3 = c(10L, 13L, 14L, 15L),
Resample4 = c(4L, 8L, 9L, 13L, 15L),
Resample5 = c(1L, 3L, 5L, 7L, 10L, 12L),
Resample6 = c(2L, 6L, 11L, 14L)
),
.Names = c(
"Resample1",
"Resample2",
"Resample3",
"Resample4",
"Resample5",
"Resample6"
)
),
number = 3,
repeats = 2
),
.Names = c("method", "index", "indexOut", "number", "repeats")
)
dat <- data.frame(y = 1:15, x = 15:1)
vfold_obj_2 <- caret2rsample(cv_2, data = dat)
check_indices(vfold_obj_2, cv_2)
for (i in seq_along(vfold_obj_2$splits)) {
expect_equal(
paste(vfold_obj_2$id2[[i]], vfold_obj_2$id[[i]], sep = "."),
names(cv_2$index)[i]
)
}
})
test_that("basic boot", {
bt_1 <-
structure(
list(
method = "boot",
index = structure(
list(
Resample1 = c(
1L,
1L,
4L,
4L,
5L,
7L,
8L,
10L,
11L,
11L,
12L,
13L,
15L,
15L,
15L
),
Resample2 = c(
1L,
2L,
3L,
5L,
5L,
5L,
6L,
7L,
8L,
9L,
9L,
9L,
10L,
10L,
12L
)
),
.Names = c("Resample1", "Resample2")
),
indexOut = structure(
list(
Resample1 = c(2L, 3L, 6L, 9L, 14L),
Resample2 = c(4L, 11L, 13L, 14L, 15L)
),
.Names = c("Resample1", "Resample2")
),
number = 2
),
.Names = c(
"method",
"index",
"indexOut",
"number"
)
)
dat <- data.frame(y = 1:15, x = 15:1)
bt_obj_1 <- caret2rsample(bt_1, data = dat)
check_indices(bt_obj_1, bt_1)
for (i in seq_along(bt_obj_1$splits)) {
expect_equal(bt_obj_1$id[[i]], names(bt_1$index)[i])
}
})
test_that("boot 632", {
bt_2 <-
structure(
list(
method = "boot",
index = structure(
list(
Resample1 = c(
1L,
1L,
4L,
4L,
5L,
7L,
8L,
10L,
11L,
11L,
12L,
13L,
15L,
15L,
15L
),
Resample2 = c(
1L,
2L,
3L,
5L,
5L,
5L,
6L,
7L,
8L,
9L,
9L,
9L,
10L,
10L,
12L
)
),
.Names = c("Resample1", "Resample2")
),
indexOut = structure(
list(
Resample1 = c(2L, 3L, 6L, 9L, 14L),
Resample2 = c(4L, 11L, 13L, 14L, 15L)
),
.Names = c("Resample1", "Resample2")
),
number = 2
),
.Names = c(
"method",
"index",
"indexOut",
"number"
)
)
bt_2$method <- "boot632"
dat <- data.frame(y = 1:15, x = 15:1)
bt_obj_2 <- caret2rsample(bt_2, data = dat)
check_indices(bt_obj_2, bt_2)
for (i in seq_along(bt_obj_2$splits)) {
expect_equal(bt_obj_2$id[[i]], names(bt_2$index)[i])
}
})
test_that("boot optim", {
bt_3 <-
structure(
list(
method = "boot",
index = structure(
list(
Resample1 = c(
1L,
1L,
4L,
4L,
5L,
7L,
8L,
10L,
11L,
11L,
12L,
13L,
15L,
15L,
15L
),
Resample2 = c(
1L,
2L,
3L,
5L,
5L,
5L,
6L,
7L,
8L,
9L,
9L,
9L,
10L,
10L,
12L
)
),
.Names = c("Resample1", "Resample2")
),
indexOut = structure(
list(
Resample1 = c(2L, 3L, 6L, 9L, 14L),
Resample2 = c(4L, 11L, 13L, 14L, 15L)
),
.Names = c("Resample1", "Resample2")
),
number = 2
),
.Names = c(
"method",
"index",
"indexOut",
"number"
)
)
bt_3$method <- "optimism_boot"
dat <- data.frame(y = 1:15, x = 15:1)
bt_obj_3 <- caret2rsample(bt_3, data = dat)
check_indices(bt_obj_3, bt_3)
for (i in seq_along(bt_obj_3$splits)) {
expect_equal(bt_obj_3$id[[i]], names(bt_3$index)[i])
}
})
test_that("boot all", {
bt_4 <-
structure(
list(
method = "boot",
index = structure(
list(
Resample1 = c(
1L,
1L,
4L,
4L,
5L,
7L,
8L,
10L,
11L,
11L,
12L,
13L,
15L,
15L,
15L
),
Resample2 = c(
1L,
2L,
3L,
5L,
5L,
5L,
6L,
7L,
8L,
9L,
9L,
9L,
10L,
10L,
12L
)
),
.Names = c("Resample1", "Resample2")
),
indexOut = structure(
list(
Resample1 = c(2L, 3L, 6L, 9L, 14L),
Resample2 = c(4L, 11L, 13L, 14L, 15L)
),
.Names = c("Resample1", "Resample2")
),
number = 2
),
.Names = c(
"method",
"index",
"indexOut",
"number"
)
)
bt_4$method <- "boot_all"
dat <- data.frame(y = 1:15, x = 15:1)
bt_obj_4 <- caret2rsample(bt_4, data = dat)
check_indices(bt_obj_4, bt_4)
for (i in seq_along(bt_obj_4$splits)) {
expect_equal(bt_obj_4$id[[i]], names(bt_4$index)[i])
}
})
test_that("adaptive boot", {
bt_5 <-
structure(
list(
method = "boot",
index = structure(
list(
Resample1 = c(
1L,
1L,
4L,
4L,
5L,
7L,
8L,
10L,
11L,
11L,
12L,
13L,
15L,
15L,
15L
),
Resample2 = c(
1L,
2L,
3L,
5L,
5L,
5L,
6L,
7L,
8L,
9L,
9L,
9L,
10L,
10L,
12L
)
),
.Names = c("Resample1", "Resample2")
),
indexOut = structure(
list(
Resample1 = c(2L, 3L, 6L, 9L, 14L),
Resample2 = c(4L, 11L, 13L, 14L, 15L)
),
.Names = c("Resample1", "Resample2")
),
number = 2
),
.Names = c(
"method",
"index",
"indexOut",
"number"
)
)
bt_5$method <- "adaptive_boot"
dat <- data.frame(y = 1:15, x = 15:1)
bt_obj_5 <- caret2rsample(bt_5, data = dat)
check_indices(bt_obj_5, bt_5)
for (i in seq_along(bt_obj_5$splits)) {
expect_equal(bt_obj_5$id[[i]], names(bt_5$index)[i])
}
})
test_that("loo", {
loo_1 <-
structure(
list(
method = "LOOCV",
index = structure(
list(
Fold01 = 2:15,
Fold02 = c(
1L,
3L,
4L,
5L,
6L,
7L,
8L,
9L,
10L,
11L,
12L,
13L,
14L,
15L
),
Fold03 = c(
1L,
2L,
4L,
5L,
6L,
7L,
8L,
9L,
10L,
11L,
12L,
13L,
14L,
15L
),
Fold04 = c(
1L,
2L,
3L,
5L,
6L,
7L,
8L,
9L,
10L,
11L,
12L,
13L,
14L,
15L
),
Fold05 = c(
1L,
2L,
3L,
4L,
6L,
7L,
8L,
9L,
10L,
11L,
12L,
13L,
14L,
15L
),
Fold06 = c(
1L,
2L,
3L,
4L,
5L,
7L,
8L,
9L,
10L,
11L,
12L,
13L,
14L,
15L
),
Fold07 = c(
1L,
2L,
3L,
4L,
5L,
6L,
8L,
9L,
10L,
11L,
12L,
13L,
14L,
15L
),
Fold08 = c(
1L,
2L,
3L,
4L,
5L,
6L,
7L,
9L,
10L,
11L,
12L,
13L,
14L,
15L
),
Fold09 = c(
1L,
2L,
3L,
4L,
5L,
6L,
7L,
8L,
10L,
11L,
12L,
13L,
14L,
15L
),
Fold10 = c(
1L,
2L,
3L,
4L,
5L,
6L,
7L,
8L,
9L,
11L,
12L,
13L,
14L,
15L
),
Fold11 = c(
1L,
2L,
3L,
4L,
5L,
6L,
7L,
8L,
9L,
10L,
12L,
13L,
14L,
15L
),
Fold12 = c(
1L,
2L,
3L,
4L,
5L,
6L,
7L,
8L,
9L,
10L,
11L,
13L,
14L,
15L
),
Fold13 = c(
1L,
2L,
3L,
4L,
5L,
6L,
7L,
8L,
9L,
10L,
11L,
12L,
14L,
15L
),
Fold14 = c(
1L,
2L,
3L,
4L,
5L,
6L,
7L,
8L,
9L,
10L,
11L,
12L,
13L,
15L
),
Fold15 = 1:14
),
.Names = c(
"Fold01",
"Fold02",
"Fold03",
"Fold04",
"Fold05",
"Fold06",
"Fold07",
"Fold08",
"Fold09",
"Fold10",
"Fold11",
"Fold12",
"Fold13",
"Fold14",
"Fold15"
)
),
indexOut = structure(
list(
Resample01 = 1L,
Resample02 = 2L,
Resample03 = 3L,
Resample04 = 4L,
Resample05 = 5L,
Resample06 = 6L,
Resample07 = 7L,
Resample08 = 8L,
Resample09 = 9L,
Resample10 = 10L,
Resample11 = 11L,
Resample12 = 12L,
Resample13 = 13L,
Resample14 = 14L,
Resample15 = 15L
),
.Names = c(
"Resample01",
"Resample02",
"Resample03",
"Resample04",
"Resample05",
"Resample06",
"Resample07",
"Resample08",
"Resample09",
"Resample10",
"Resample11",
"Resample12",
"Resample13",
"Resample14",
"Resample15"
)
)
),
.Names = c("method", "index", "indexOut")
)
dat <- data.frame(y = 1:15, x = 15:1)
loo_obj <- caret2rsample(loo_1, data = dat)
check_indices(loo_obj, loo_1)
for (i in seq_along(loo_obj$splits)) {
expect_equal(loo_obj$id[[i]], names(loo_1$index)[i])
}
})
test_that("mcv", {
lgo1 <-
structure(
list(
method = "LGOCV",
index = structure(
list(
Resample1 = c(1L, 4L, 5L, 6L, 7L, 9L, 10L, 14L),
Resample2 = c(2L, 4L, 5L, 6L, 9L, 10L, 14L, 15L),
Resample3 = c(1L, 2L, 3L, 5L, 6L, 7L, 8L, 9L)
),
.Names = c("Resample1", "Resample2", "Resample3")
),
indexOut = structure(
list(
Resample1 = c(2L, 3L, 8L, 11L, 12L, 13L, 15L),
Resample2 = c(1L, 3L, 7L, 8L, 11L, 12L, 13L),
Resample3 = c(4L, 10L, 11L, 12L, 13L, 14L, 15L)
),
.Names = c("Resample1", "Resample2", "Resample3")
),
number = 3,
p = 0.5
),
.Names = c("method", "index", "indexOut", "number", "p")
)
dat <- data.frame(y = 1:15, x = 15:1)
mcv_obj <- caret2rsample(lgo1, data = dat)
check_indices(mcv_obj, lgo1)
for (i in seq_along(mcv_obj$splits)) {
expect_equal(mcv_obj$id[[i]], names(lgo1$index)[i])
}
})
test_that("rolling origin", {
rof_1 <-
structure(
list(
method = "timeSlice",
index = structure(
list(
Training04 = 1:4,
Training05 = 2:5,
Training06 = 3:6,
Training07 = 4:7,
Training08 = 5:8,
Training09 = 6:9,
Training10 = 7:10
),
.Names = c(
"Training04",
"Training05",
"Training06",
"Training07",
"Training08",
"Training09",
"Training10"
)
),
indexOut = structure(
list(
Testing04 = 5:9,
Testing05 = 6:10,
Testing06 = 7:11,
Testing07 = 8:12,
Testing08 = 9:13,
Testing09 = 10:14,
Testing10 = 11:15
),
.Names = c(
"Testing04",
"Testing05",
"Testing06",
"Testing07",
"Testing08",
"Testing09",
"Testing10"
)
),
initialWindow = 4,
horizon = 5,
fixedWindow = TRUE,
skip = 0
),
.Names = c(
"method",
"index",
"indexOut",
"initialWindow",
"horizon",
"fixedWindow",
"skip"
)
)
dat <- data.frame(y = 1:15, x = 15:1)
rof_obj <- caret2rsample(rof_1, data = dat)
check_indices(rof_obj, rof_1)
for (i in seq_along(rof_obj$splits)) {
expect_equal(rof_obj$id[[i]], names(rof_1$index)[i])
}
})
tidymodels/rsample documentation built on June 12, 2025, 9:40 p.m.
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###################################################################
## Test cases for caret -> rsample that mimic `trainControl`
check_indices <- function(newer, orig) {
for (i in seq_along(newer$splits)) {
expect_equal(
as.integer(newer$splits[[i]]),
orig$index[[i]]
)
expect_equal(
as.integer(newer$splits[[i]], "assessment"),
orig$indexOut[[i]]
)
}
invisible(NULL)
}
###################################################################
test_that("basic v-fold", {
cv_1 <- structure(
list(
method = "cv",
index = structure(
list(
Fold1 = c(2L, 3L, 4L, 5L, 6L, 7L, 8L, 10L, 11L, 13L),
Fold2 = c(
1L,
4L,
6L,
8L,
9L,
10L,
11L,
12L,
13L,
14L,
15L
),
Fold3 = c(1L, 2L, 3L, 5L, 7L, 9L, 12L, 14L, 15L)
),
.Names = c("Fold1", "Fold2", "Fold3")
),
indexOut = structure(
list(
Resample1 = c(1L, 9L, 12L, 14L, 15L),
Resample2 = c(2L, 3L, 5L, 7L),
Resample3 = c(4L, 6L, 8L, 10L, 11L, 13L)
),
.Names = c("Resample1", "Resample2", "Resample3")
),
number = 3,
repeats = NA
),
.Names = c("method", "index", "indexOut", "number", "repeats")
)
dat <- data.frame(y = 1:15, x = 15:1)
vfold_obj_1 <- caret2rsample(cv_1, data = dat)
check_indices(vfold_obj_1, cv_1)
for (i in seq_along(vfold_obj_1$splits)) {
expect_equal(vfold_obj_1$id[[i]], names(cv_1$index)[i])
}
})
test_that("repeated v-fold", {
cv_2 <-
structure(
list(
method = "repeatedcv",
index = structure(
list(
Fold1.Rep1 = c(1L, 3L, 4L, 6L, 9L, 10L, 12L, 13L, 14L, 15L),
Fold2.Rep1 = c(2L, 5L, 7L, 8L, 10L, 11L, 13L, 14L, 15L),
Fold3.Rep1 = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 11L, 12L),
Fold1.Rep2 = c(1L, 2L, 3L, 5L, 6L, 7L, 10L, 11L, 12L, 14L),
Fold2.Rep2 = c(2L, 4L, 6L, 8L, 9L, 11L, 13L, 14L, 15L),
Fold3.Rep2 = c(1L, 3L, 4L, 5L, 7L, 8L, 9L, 10L, 12L, 13L, 15L)
),
.Names = c(
"Fold1.Rep1",
"Fold2.Rep1",
"Fold3.Rep1",
"Fold1.Rep2",
"Fold2.Rep2",
"Fold3.Rep2"
)
),
indexOut = structure(
list(
Resample1 = c(2L, 5L, 7L, 8L, 11L),
Resample2 = c(1L, 3L, 4L, 6L, 9L, 12L),
Resample3 = c(10L, 13L, 14L, 15L),
Resample4 = c(4L, 8L, 9L, 13L, 15L),
Resample5 = c(1L, 3L, 5L, 7L, 10L, 12L),
Resample6 = c(2L, 6L, 11L, 14L)
),
.Names = c(
"Resample1",
"Resample2",
"Resample3",
"Resample4",
"Resample5",
"Resample6"
)
),
number = 3,
repeats = 2
),
.Names = c("method", "index", "indexOut", "number", "repeats")
)
dat <- data.frame(y = 1:15, x = 15:1)
vfold_obj_2 <- caret2rsample(cv_2, data = dat)
check_indices(vfold_obj_2, cv_2)
for (i in seq_along(vfold_obj_2$splits)) {
expect_equal(
paste(vfold_obj_2$id2[[i]], vfold_obj_2$id[[i]], sep = "."),
names(cv_2$index)[i]
)
}
})
test_that("basic boot", {
bt_1 <-
structure(
list(
method = "boot",
index = structure(
list(
Resample1 = c(
1L,
1L,
4L,
4L,
5L,
7L,
8L,
10L,
11L,
11L,
12L,
13L,
15L,
15L,
15L
),
Resample2 = c(
1L,
2L,
3L,
5L,
5L,
5L,
6L,
7L,
8L,
9L,
9L,
9L,
10L,
10L,
12L
)
),
.Names = c("Resample1", "Resample2")
),
indexOut = structure(
list(
Resample1 = c(2L, 3L, 6L, 9L, 14L),
Resample2 = c(4L, 11L, 13L, 14L, 15L)
),
.Names = c("Resample1", "Resample2")
),
number = 2
),
.Names = c(
"method",
"index",
"indexOut",
"number"
)
)
dat <- data.frame(y = 1:15, x = 15:1)
bt_obj_1 <- caret2rsample(bt_1, data = dat)
check_indices(bt_obj_1, bt_1)
for (i in seq_along(bt_obj_1$splits)) {
expect_equal(bt_obj_1$id[[i]], names(bt_1$index)[i])
}
})
test_that("boot 632", {
bt_2 <-
structure(
list(
method = "boot",
index = structure(
list(
Resample1 = c(
1L,
1L,
4L,
4L,
5L,
7L,
8L,
10L,
11L,
11L,
12L,
13L,
15L,
15L,
15L
),
Resample2 = c(
1L,
2L,
3L,
5L,
5L,
5L,
6L,
7L,
8L,
9L,
9L,
9L,
10L,
10L,
12L
)
),
.Names = c("Resample1", "Resample2")
),
indexOut = structure(
list(
Resample1 = c(2L, 3L, 6L, 9L, 14L),
Resample2 = c(4L, 11L, 13L, 14L, 15L)
),
.Names = c("Resample1", "Resample2")
),
number = 2
),
.Names = c(
"method",
"index",
"indexOut",
"number"
)
)
bt_2$method <- "boot632"
dat <- data.frame(y = 1:15, x = 15:1)
bt_obj_2 <- caret2rsample(bt_2, data = dat)
check_indices(bt_obj_2, bt_2)
for (i in seq_along(bt_obj_2$splits)) {
expect_equal(bt_obj_2$id[[i]], names(bt_2$index)[i])
}
})
test_that("boot optim", {
bt_3 <-
structure(
list(
method = "boot",
index = structure(
list(
Resample1 = c(
1L,
1L,
4L,
4L,
5L,
7L,
8L,
10L,
11L,
11L,
12L,
13L,
15L,
15L,
15L
),
Resample2 = c(
1L,
2L,
3L,
5L,
5L,
5L,
6L,
7L,
8L,
9L,
9L,
9L,
10L,
10L,
12L
)
),
.Names = c("Resample1", "Resample2")
),
indexOut = structure(
list(
Resample1 = c(2L, 3L, 6L, 9L, 14L),
Resample2 = c(4L, 11L, 13L, 14L, 15L)
),
.Names = c("Resample1", "Resample2")
),
number = 2
),
.Names = c(
"method",
"index",
"indexOut",
"number"
)
)
bt_3$method <- "optimism_boot"
dat <- data.frame(y = 1:15, x = 15:1)
bt_obj_3 <- caret2rsample(bt_3, data = dat)
check_indices(bt_obj_3, bt_3)
for (i in seq_along(bt_obj_3$splits)) {
expect_equal(bt_obj_3$id[[i]], names(bt_3$index)[i])
}
})
test_that("boot all", {
bt_4 <-
structure(
list(
method = "boot",
index = structure(
list(
Resample1 = c(
1L,
1L,
4L,
4L,
5L,
7L,
8L,
10L,
11L,
11L,
12L,
13L,
15L,
15L,
15L
),
Resample2 = c(
1L,
2L,
3L,
5L,
5L,
5L,
6L,
7L,
8L,
9L,
9L,
9L,
10L,
10L,
12L
)
),
.Names = c("Resample1", "Resample2")
),
indexOut = structure(
list(
Resample1 = c(2L, 3L, 6L, 9L, 14L),
Resample2 = c(4L, 11L, 13L, 14L, 15L)
),
.Names = c("Resample1", "Resample2")
),
number = 2
),
.Names = c(
"method",
"index",
"indexOut",
"number"
)
)
bt_4$method <- "boot_all"
dat <- data.frame(y = 1:15, x = 15:1)
bt_obj_4 <- caret2rsample(bt_4, data = dat)
check_indices(bt_obj_4, bt_4)
for (i in seq_along(bt_obj_4$splits)) {
expect_equal(bt_obj_4$id[[i]], names(bt_4$index)[i])
}
})
test_that("adaptive boot", {
bt_5 <-
structure(
list(
method = "boot",
index = structure(
list(
Resample1 = c(
1L,
1L,
4L,
4L,
5L,
7L,
8L,
10L,
11L,
11L,
12L,
13L,
15L,
15L,
15L
),
Resample2 = c(
1L,
2L,
3L,
5L,
5L,
5L,
6L,
7L,
8L,
9L,
9L,
9L,
10L,
10L,
12L
)
),
.Names = c("Resample1", "Resample2")
),
indexOut = structure(
list(
Resample1 = c(2L, 3L, 6L, 9L, 14L),
Resample2 = c(4L, 11L, 13L, 14L, 15L)
),
.Names = c("Resample1", "Resample2")
),
number = 2
),
.Names = c(
"method",
"index",
"indexOut",
"number"
)
)
bt_5$method <- "adaptive_boot"
dat <- data.frame(y = 1:15, x = 15:1)
bt_obj_5 <- caret2rsample(bt_5, data = dat)
check_indices(bt_obj_5, bt_5)
for (i in seq_along(bt_obj_5$splits)) {
expect_equal(bt_obj_5$id[[i]], names(bt_5$index)[i])
}
})
test_that("loo", {
loo_1 <-
structure(
list(
method = "LOOCV",
index = structure(
list(
Fold01 = 2:15,
Fold02 = c(
1L,
3L,
4L,
5L,
6L,
7L,
8L,
9L,
10L,
11L,
12L,
13L,
14L,
15L
),
Fold03 = c(
1L,
2L,
4L,
5L,
6L,
7L,
8L,
9L,
10L,
11L,
12L,
13L,
14L,
15L
),
Fold04 = c(
1L,
2L,
3L,
5L,
6L,
7L,
8L,
9L,
10L,
11L,
12L,
13L,
14L,
15L
),
Fold05 = c(
1L,
2L,
3L,
4L,
6L,
7L,
8L,
9L,
10L,
11L,
12L,
13L,
14L,
15L
),
Fold06 = c(
1L,
2L,
3L,
4L,
5L,
7L,
8L,
9L,
10L,
11L,
12L,
13L,
14L,
15L
),
Fold07 = c(
1L,
2L,
3L,
4L,
5L,
6L,
8L,
9L,
10L,
11L,
12L,
13L,
14L,
15L
),
Fold08 = c(
1L,
2L,
3L,
4L,
5L,
6L,
7L,
9L,
10L,
11L,
12L,
13L,
14L,
15L
),
Fold09 = c(
1L,
2L,
3L,
4L,
5L,
6L,
7L,
8L,
10L,
11L,
12L,
13L,
14L,
15L
),
Fold10 = c(
1L,
2L,
3L,
4L,
5L,
6L,
7L,
8L,
9L,
11L,
12L,
13L,
14L,
15L
),
Fold11 = c(
1L,
2L,
3L,
4L,
5L,
6L,
7L,
8L,
9L,
10L,
12L,
13L,
14L,
15L
),
Fold12 = c(
1L,
2L,
3L,
4L,
5L,
6L,
7L,
8L,
9L,
10L,
11L,
13L,
14L,
15L
),
Fold13 = c(
1L,
2L,
3L,
4L,
5L,
6L,
7L,
8L,
9L,
10L,
11L,
12L,
14L,
15L
),
Fold14 = c(
1L,
2L,
3L,
4L,
5L,
6L,
7L,
8L,
9L,
10L,
11L,
12L,
13L,
15L
),
Fold15 = 1:14
),
.Names = c(
"Fold01",
"Fold02",
"Fold03",
"Fold04",
"Fold05",
"Fold06",
"Fold07",
"Fold08",
"Fold09",
"Fold10",
"Fold11",
"Fold12",
"Fold13",
"Fold14",
"Fold15"
)
),
indexOut = structure(
list(
Resample01 = 1L,
Resample02 = 2L,
Resample03 = 3L,
Resample04 = 4L,
Resample05 = 5L,
Resample06 = 6L,
Resample07 = 7L,
Resample08 = 8L,
Resample09 = 9L,
Resample10 = 10L,
Resample11 = 11L,
Resample12 = 12L,
Resample13 = 13L,
Resample14 = 14L,
Resample15 = 15L
),
.Names = c(
"Resample01",
"Resample02",
"Resample03",
"Resample04",
"Resample05",
"Resample06",
"Resample07",
"Resample08",
"Resample09",
"Resample10",
"Resample11",
"Resample12",
"Resample13",
"Resample14",
"Resample15"
)
)
),
.Names = c("method", "index", "indexOut")
)
dat <- data.frame(y = 1:15, x = 15:1)
loo_obj <- caret2rsample(loo_1, data = dat)
check_indices(loo_obj, loo_1)
for (i in seq_along(loo_obj$splits)) {
expect_equal(loo_obj$id[[i]], names(loo_1$index)[i])
}
})
test_that("mcv", {
lgo1 <-
structure(
list(
method = "LGOCV",
index = structure(
list(
Resample1 = c(1L, 4L, 5L, 6L, 7L, 9L, 10L, 14L),
Resample2 = c(2L, 4L, 5L, 6L, 9L, 10L, 14L, 15L),
Resample3 = c(1L, 2L, 3L, 5L, 6L, 7L, 8L, 9L)
),
.Names = c("Resample1", "Resample2", "Resample3")
),
indexOut = structure(
list(
Resample1 = c(2L, 3L, 8L, 11L, 12L, 13L, 15L),
Resample2 = c(1L, 3L, 7L, 8L, 11L, 12L, 13L),
Resample3 = c(4L, 10L, 11L, 12L, 13L, 14L, 15L)
),
.Names = c("Resample1", "Resample2", "Resample3")
),
number = 3,
p = 0.5
),
.Names = c("method", "index", "indexOut", "number", "p")
)
dat <- data.frame(y = 1:15, x = 15:1)
mcv_obj <- caret2rsample(lgo1, data = dat)
check_indices(mcv_obj, lgo1)
for (i in seq_along(mcv_obj$splits)) {
expect_equal(mcv_obj$id[[i]], names(lgo1$index)[i])
}
})
test_that("rolling origin", {
rof_1 <-
structure(
list(
method = "timeSlice",
index = structure(
list(
Training04 = 1:4,
Training05 = 2:5,
Training06 = 3:6,
Training07 = 4:7,
Training08 = 5:8,
Training09 = 6:9,
Training10 = 7:10
),
.Names = c(
"Training04",
"Training05",
"Training06",
"Training07",
"Training08",
"Training09",
"Training10"
)
),
indexOut = structure(
list(
Testing04 = 5:9,
Testing05 = 6:10,
Testing06 = 7:11,
Testing07 = 8:12,
Testing08 = 9:13,
Testing09 = 10:14,
Testing10 = 11:15
),
.Names = c(
"Testing04",
"Testing05",
"Testing06",
"Testing07",
"Testing08",
"Testing09",
"Testing10"
)
),
initialWindow = 4,
horizon = 5,
fixedWindow = TRUE,
skip = 0
),
.Names = c(
"method",
"index",
"indexOut",
"initialWindow",
"horizon",
"fixedWindow",
"skip"
)
)
dat <- data.frame(y = 1:15, x = 15:1)
rof_obj <- caret2rsample(rof_1, data = dat)
check_indices(rof_obj, rof_1)
for (i in seq_along(rof_obj$splits)) {
expect_equal(rof_obj$id[[i]], names(rof_1$index)[i])
}
})
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