tests/testthat/test_collapse_groups.R
In LudvigOlsen/R-splitters: Creating Groups from Data
library(groupdata2)
context("collapse_groups()")
test_that("testing summaries of method ascending-descending", {
# Set seed
xpectr::set_test_seed(42)
# Create data frame
df <- data.frame(
"participant" = factor(rep(1:20, 3)),
"participant_2" = factor(rep(1:20, 3)),
"age" = rep(sample(c(1:100), 20), 3),
"answer" = factor(sample(c("a", "b", "c", "d"), 60, replace = TRUE)),
"score" = sample(c(1:100), 20 * 3)
)
df <- df %>% dplyr::arrange(participant)
df$session <- rep(c("1", "2", "3"), 20)
# Sample rows to get unequal sizes per participant
df <- dplyr::sample_n(df, size = 53)
# Create the initial groups (to be collapsed)
df <- fold(
data = df,
k = 8,
method = "n_dist",
id_col = "participant"
)
# Ungroup the data frame
# Otherwise `collapse_groups()` would be
# applied to each fold separately!
df <- dplyr::ungroup(df)
# Method ascending
# With size balancing
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
cat_cols = "answer",
num_cols = "score",
id_cols = "participant",
balance_size = TRUE,
method = "ascending",
)
## Testing 'df_coll$.coll_groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing is factor
expect_true(
is.factor(df_coll$.coll_groups))
# Testing values
expect_equal(
xpectr::smpl(as.character(df_coll$.coll_groups), n = 30),
c("3", "3", "2", "2", "2", "2", "2", "2", "3", "3", "3", "3", "1",
"1", "3", "3", "3", "3", "1", "1", "1", "3", "3", "2", "2",
"2", "2", "1", "1", "1"),
fixed = TRUE)
## Finished testing 'df_coll$.coll_groups' ####
summ <- summarize_balances(df_coll,
group_cols = ".coll_groups",
cat_cols = "answer",
num_cols = "score",
id_cols = "participant")
# Check most of the group summaries are ascending in order
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(11, 17, 25),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# participant"]],
c(4, 7, 9),
tolerance = 1e-4)
expect_equal(
summ$Groups[["mean(score)"]],
c(32, 54.41176, 50.84),
tolerance = 1e-4)
expect_equal(
summ$Groups[["sum(score)"]],
c(352, 925, 1271),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_a"]],
c(1, 5, 8),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_b"]],
c(3, 4, 6),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_c"]],
c(3, 4, 5),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_d"]],
c(4, 4, 6),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "# participant", "mean(score)",
"sum(score)", "# answ_a", "# answ_b", "# answ_c", "# answ_d"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "integer", "numeric", "integer",
"numeric", "numeric", "numeric", "numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "integer", "double", "integer",
"double", "double", "double", "double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 10L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
# Without size balancing
xpectr::set_test_seed(42)
df_coll_2 <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
cat_cols = "answer",
num_cols = "score",
id_cols = "participant",
balance_size = FALSE,
method = "ascending",
)
# Gets the same split
expect_equal(
df_coll$.coll_groups,
df_coll_2$.coll_groups
)
# Method descending
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
cat_cols = "answer",
num_cols = "score",
id_cols = "participant",
balance_size = TRUE,
method = "descending",
)
## Testing 'df_coll$.coll_groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing is factor
expect_true(
is.factor(df_coll$.coll_groups))
# Testing values
expect_equal(
xpectr::smpl(as.character(df_coll$.coll_groups), n = 30),
c("1", "1", "2", "2", "2", "2", "2", "2", "1", "1", "1", "1", "3",
"3", "1", "1", "1", "1", "3", "3", "3", "1", "1", "2", "2",
"2", "2", "3", "3", "3"),
fixed = TRUE)
## Finished testing 'df_coll$.coll_groups' ####
summ <- summarize_balances(df_coll,
group_cols = ".coll_groups",
cat_cols = "answer",
num_cols = "score",
id_cols = "participant")
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(25, 17, 11),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# participant"]],
c(9, 7, 4),
tolerance = 1e-4)
expect_equal(
summ$Groups[["mean(score)"]],
c(50.84, 54.41176, 32),
tolerance = 1e-4)
expect_equal(
summ$Groups[["sum(score)"]],
c(1271, 925, 352),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_a"]],
c(8, 5, 1),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_b"]],
c(6, 4, 3),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_c"]],
c(5, 4, 3),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_d"]],
c(6, 4, 4),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "# participant", "mean(score)",
"sum(score)", "# answ_a", "# answ_b", "# answ_c", "# answ_d"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "integer", "numeric", "integer",
"numeric", "numeric", "numeric", "numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "integer", "double", "integer",
"double", "double", "double", "double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 10L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
})
test_that("testing summaries of cat_levels", {
# Set seed
xpectr::set_test_seed(42)
# Create data frame
df <- data.frame(
"participant" = factor(rep(1:20, 3)),
"participant_2" = factor(rep(1:20, 3)),
"age" = rep(sample(c(1:100), 20), 3),
"answer" = factor(sample(c("a", "b", "c", "d"), 60, replace = TRUE)),
"score" = sample(c(1:100), 20 * 3)
)
df <- df %>% dplyr::arrange(participant)
df$session <- rep(c("1", "2", "3"), 20)
# Sample rows to get unequal sizes per participant
df <- dplyr::sample_n(df, size = 53)
# Create the initial groups (to be collapsed)
df <- fold(
data = df,
k = 8,
method = "n_dist",
id_col = "participant"
)
# Ungroup the data frame
# Otherwise `collapse_groups()` would be
# applied to each fold separately!
df <- dplyr::ungroup(df)
# We use method ascending as its
# pattern is likely easier to spot than balance
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
cat_cols = "answer",
cat_levels = ".minority",
method = "ascending",
balance_size = FALSE
)
## Testing 'df_coll$.coll_groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing is factor
expect_true(
is.factor(df_coll$.coll_groups))
# Testing values
expect_equal(
xpectr::smpl(as.character(df_coll$.coll_groups), n = 30),
c("3", "3", "1", "1", "1", "2", "2", "2", "3", "3", "1", "1", "2",
"2", "2", "2", "1", "1", "3", "3", "3", "2", "2", "3", "3",
"3", "3", "2", "2", "2"),
fixed = TRUE)
## Finished testing 'df_coll$.coll_groups' ####
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups",
cat_cols = "answer"
)
# Only the minor cat_level ("c") is in ascending order!
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(15, 20, 18),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_a"]],
c(5, 5, 4),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_b"]],
c(6, 5, 2),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_c"]],
c(0, 5, 7),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_d"]],
c(4, 5, 5),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "# answ_a", "# answ_b", "# answ_c",
"# answ_d"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "numeric", "numeric", "numeric",
"numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "double", "double", "double",
"double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 7L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
# Set minority level manually
xpectr::set_test_seed(42)
df_coll_2 <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
cat_cols = "answer",
cat_levels = "c", # c is the minority class
method = "ascending",
balance_size = FALSE
)
expect_equal(
df_coll$.coll_groups,
df_coll_2$.coll_groups
)
# .majority
# We method balance as all classes were kind
# of ascending with the "ascending"
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
cat_cols = "answer",
cat_levels = ".majority",
method = "balance",
balance_size = FALSE
)
## Testing 'df_coll$.coll_groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing is factor
expect_true(
is.factor(df_coll$.coll_groups))
# Testing values
expect_equal(
xpectr::smpl(as.character(df_coll$.coll_groups), n = 30),
c("1", "1", "2", "2", "2", "1", "1", "1", "1", "1", "3", "3", "3",
"3", "2", "2", "3", "3", "3", "3", "3", "2", "2", "1", "1",
"1", "1", "3", "3", "3"),
fixed = TRUE)
## Finished testing 'df_coll$.coll_groups' ####
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups",
cat_cols = "answer"
)
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(19, 14, 20),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_a"]],
c(6, 4, 4),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_b"]],
c(2, 5, 6),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_c"]],
c(7, 2, 3),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_d"]],
c(4, 3, 7),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "# answ_a", "# answ_b", "# answ_c",
"# answ_d"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "numeric", "numeric", "numeric",
"numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "double", "double", "double",
"double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 7L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
# Set specific level
xpectr::set_test_seed(42)
df_coll_2 <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
cat_cols = "answer",
cat_levels = "a", # a is the first majority class
method = "balance",
balance_size = FALSE
)
expect_equal(
df_coll$.coll_groups,
df_coll_2$.coll_groups
)
# Weighted cat levels
# We should see the "b" level be pretty balanced
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
cat_cols = "answer",
cat_levels = c("a" = 2, "b" = 1000, "c"=1),
method = "balance",
balance_size = FALSE
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups",
cat_cols = "answer"
)
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(11, 22, 20),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_a"]],
c(2, 6, 6),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_b"]],
c(4, 5, 4), # Fairly balanced yes!
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_c"]],
c(2, 6, 4),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_d"]],
c(3, 5, 6),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "# answ_a", "# answ_b", "# answ_c",
"# answ_d"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "numeric", "numeric", "numeric",
"numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "double", "double", "double",
"double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 7L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
# List of weights per cat col with multiple cat cols
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df %>% dplyr::mutate(session = factor(.data$session)),
n = 3,
group_cols = ".folds",
cat_cols = c("answer", "session"),
cat_levels = list("answer" = c("a" = 2, "b" = 1000, "c" = 1),
"session" = c("1" = 1, "2" = 1000)),
method = "ascending",
balance_size = FALSE
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups",
cat_cols = c("answer","session")
)
# Note: We can't expect to see clear signs of them working
# as they may cancel out, etc.
# But both "b" and "2" are ascending, so that's something!
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(10, 18, 25),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_a"]],
c(1, 5, 8),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_b"]],
c(1, 6, 6),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_c"]],
c(4, 3, 5),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_d"]],
c(4, 4, 6),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# sess_1"]],
c(3, 6, 8),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# sess_2"]],
c(4, 6, 9),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# sess_3"]],
c(3, 6, 8),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "# answ_a", "# answ_b", "# answ_c",
"# answ_d", "# sess_1", "# sess_2", "# sess_3"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "numeric", "numeric", "numeric",
"numeric", "numeric", "numeric", "numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "double", "double", "double",
"double", "double", "double", "double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 10L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
})
test_that("testing summaries of balance_size options", {
# Set seed
xpectr::set_test_seed(42)
# Create data frame
df <- data.frame(
"participant" = factor(rep(1:20, 3)),
"answer" = factor(sample(c("a", "b", "c", "d"), 60, replace = TRUE))
)
df <- df %>% dplyr::arrange(participant)
# Sample rows to get unequal sizes per participant
df <- dplyr::sample_n(df, size = 53)
# Create the initial groups (to be collapsed)
df <- fold(
data = df,
k = 8,
method = "n_dist",
id_col = "participant"
)
# Ungroup the data frame
# Otherwise `collapse_groups()` would be
# applied to each fold separately!
df <- dplyr::ungroup(df)
# No size balancing
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "balance",
balance_size = FALSE
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups"
)
expect_equal(summ$Groups$`# rows`,
c(17L, 23L, 13L))
# ascending
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "ascending",
balance_size = FALSE
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups"
)
expect_equal(summ$Groups$`# rows`,
c(11, 22, 20))
# WITH size balancing
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "balance",
balance_size = TRUE
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups"
)
# Different for the same seed
expect_equal(summ$Groups$`# rows`,
c(14L, 21L, 18L))
# ascending
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "ascending",
balance_size = TRUE
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups"
)
expect_equal(summ$Groups$`# rows`,
c(9, 18, 26))
})
test_that("testing summaries of different group_aggregation_fn", {
# Set seed
xpectr::set_test_seed(42)
# Create data frame
df <- data.frame(
"participant" = factor(rep(1:20, 3)),
"age" = rep(sample(c(1:100), 20), 3),
"score" = sample(c(1:100), 20 * 3)
)
df <- df %>% dplyr::arrange(participant)
# Sample rows to get unequal sizes per participant
df <- dplyr::sample_n(df, size = 53)
# Create the initial groups (to be collapsed)
df <- fold(
data = df,
k = 8,
method = "n_dist",
id_col = "participant"
)
# Ungroup the data frame
# Otherwise `collapse_groups()` would be
# applied to each fold separately!
df <- dplyr::ungroup(df)
# group_aggregation_fn: mean (default)
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "balance",
balance_size = FALSE,
num_cols = "score",
group_aggregation_fn = mean
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups",
num_cols = "score"
)
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(22, 16, 15),
tolerance = 1e-4)
expect_equal(
summ$Groups[["mean(score)"]],
c(50.54545, 52.5625, 57.53333),
tolerance = 1e-4)
expect_equal(
summ$Groups[["sum(score)"]],
c(1112, 841, 863),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "mean(score)", "sum(score)"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 5L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
# Relevant in comparison to later test
spread_summ <- df_coll %>%
dplyr::group_by(.data$.coll_groups) %>%
dplyr::summarise(SD = sd(.data$score),
iqr = IQR(.data$score))
## Testing 'spread_summ' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(spread_summ),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
spread_summ[[".coll_groups"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
spread_summ[["SD"]],
c(25.7196, 31.09977, 31.36619),
tolerance = 1e-4)
expect_equal(
spread_summ[["iqr"]],
c(36.75, 54.75, 47),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(spread_summ),
c(".coll_groups", "SD", "iqr"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(spread_summ),
c("factor", "numeric", "numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(spread_summ),
c("integer", "double", "double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(spread_summ),
c(3L, 3L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(spread_summ)),
character(0),
fixed = TRUE)
## Finished testing 'spread_summ' ####
# group_aggregation_fn: sum
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "balance",
balance_size = FALSE,
num_cols = "score",
group_aggregation_fn = sum
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups",
num_cols = "score"
)
# Different but not actually better balanced sums
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(14, 21, 18),
tolerance = 1e-4)
expect_equal(
summ$Groups[["mean(score)"]],
c(53.92857, 44.66667, 62.38889),
tolerance = 1e-4)
expect_equal(
summ$Groups[["sum(score)"]],
c(755, 938, 1123),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "mean(score)", "sum(score)"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 5L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
# group_aggregation_fn: IQR
# NOTE: The mean values might actually play a larger
# role than the IQRs/SDs in the IQR/SD of the
# collapsed groups, so this cannot guarantee
# balanced IQRs/SDs
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "balance",
balance_size = FALSE,
num_cols = "score",
group_aggregation_fn = IQR
)
summ <- df_coll %>%
dplyr::group_by(.data$.coll_groups) %>%
dplyr::summarise(SD = sd(.data$score),
iqr = IQR(.data$score))
# The IQRs and SDs are less balanced
# than when using mean()
# But they are different for sure
## Testing 'summ' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ[[".coll_groups"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ[["SD"]],
c(29.23815, 35.09606, 23.74006),
tolerance = 1e-4)
expect_equal(
summ[["iqr"]],
c(45, 58.25, 41),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ),
c(".coll_groups", "SD", "iqr"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ),
c("factor", "numeric", "numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ),
c("integer", "double", "double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ),
c(3L, 3L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ)),
character(0),
fixed = TRUE)
## Finished testing 'summ' ####
# Method ascending
# Mean (default)
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "ascending",
balance_size = FALSE,
num_cols = "score",
group_aggregation_fn = mean
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups",
num_cols = "score"
)
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(12, 19, 22),
tolerance = 1e-4)
expect_equal(
summ$Groups[["mean(score)"]],
c(38.33333, 45.57895, 67.72727),
tolerance = 1e-4)
expect_equal(
summ$Groups[["sum(score)"]],
c(460, 866, 1490),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "mean(score)", "sum(score)"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 5L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
# Sum
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "ascending",
balance_size = FALSE,
num_cols = "score",
group_aggregation_fn = sum
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups",
num_cols = "score"
)
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(10, 21, 22),
tolerance = 1e-4)
expect_equal(
summ$Groups[["mean(score)"]],
c(38.8, 44.66667, 67.72727),
tolerance = 1e-4)
expect_equal(
summ$Groups[["sum(score)"]],
c(388, 938, 1490),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "mean(score)", "sum(score)"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 5L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
# IQR
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "ascending",
balance_size = FALSE,
num_cols = "score",
group_aggregation_fn = IQR
)
summ <- df_coll %>%
dplyr::group_by(.data$.coll_groups) %>%
dplyr::summarise(SD = sd(.data$score),
iqr = IQR(.data$score))
## Testing 'summ' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ[[".coll_groups"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ[["SD"]],
c(27.69586, 28.89417, 27.40917),
tolerance = 1e-4)
expect_equal(
summ[["iqr"]],
c(40.25, 45, 49.75), # Ascending ftw!
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ),
c(".coll_groups", "SD", "iqr"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ),
c("factor", "numeric", "numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ),
c("integer", "double", "double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ),
c(3L, 3L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ)),
character(0),
fixed = TRUE)
## Finished testing 'summ' ####
})
test_that("testing calculate_summary_collapse_groups_()", {
# Set seed
xpectr::set_test_seed(42)
# Create data frame
df <- data.frame(
"participant" = factor(rep(1:20, 3)),
"age" = rep(sample(c(1:100), 20), 3),
"diagnosis" = factor(rep(sample(c(1:3), 20, replace = TRUE), 3)),
"score" = sample(c(1:100), 20 * 3)
)
df <- df %>% dplyr::arrange(participant)
# Sample rows to get unequal sizes per participant
df <- dplyr::sample_n(df, size = 53)
# Create the initial groups (to be collapsed)
df <- fold(
data = df,
k = 8,
method = "n_dist",
id_col = "participant"
)
# Ungroup the data frame
# Otherwise `collapse_groups()` would be
# applied to each fold separately!
df <- dplyr::ungroup(df)
prepped <- prepare_collapse_groups_run_(
data = df,
group_cols = ".folds",
cat_cols = "diagnosis",
num_cols = c("age", "score"),
id_cols = "participant",
weights = NULL,
balance_size = TRUE
)
# Created expected summary
expected_summ <- prepped[["data"]] %>%
dplyr::group_by(.data$.____.folds) %>%
dplyr::summarise(
age = sum(age),
score = sum(score),
size = n(),
participant = length(unique(participant))
)
cat_summ <- prepped[["data"]] %>%
dplyr::group_by(.data$.____.folds) %>%
dplyr::count(diagnosis) %>%
tidyr::spread(key = "diagnosis", value = "n", fill = 0) %>%
dplyr::ungroup() %>%
dplyr::mutate(dplyr::across(where(is.numeric), .fns = ~ {
(.x - mean(.x)) / sd(.x)
}),
diagnosis = (`1` + `2` + `3`) / 3,
majority = `3`)
expected_summ$diagnosis <- cat_summ$diagnosis
expected_summ$majority <- cat_summ$majority
summ <- calculate_summary_collapse_groups_(
data = prepped[["data"]],
tmp_old_group_var = prepped[["group_cols"]],
cat_cols = prepped[["cat_cols"]],
cat_levels = NULL,
num_cols = prepped[["num_cols"]],
group_aggregation_fn = sum,
balance_size = TRUE,
id_cols = prepped[["id_cols"]]
)
summ_ordered <- dplyr::arrange(summ, .____.folds)
# Check that we get the same as the manual calculations
expect_equal(sort(colnames(summ_ordered)),
sort(colnames(expected_summ)[-7])) # Remove "majority" - it's for later
expect_equal(summ_ordered$.____.folds, expected_summ$.____.folds)
expect_equal(summ_ordered$diagnosis, expected_summ$diagnosis)
expect_equal(summ_ordered$age, expected_summ$age)
expect_equal(summ_ordered$score, expected_summ$score)
expect_equal(summ_ordered$size, expected_summ$size)
expect_equal(summ_ordered$participant, expected_summ$participant)
## Testing 'summ' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ[[".____.folds"]],
structure(c(3L, 8L, 5L, 4L, 2L, 1L, 6L, 7L), .Label = c("1", "2",
"3", "4", "5", "6", "7", "8"), class = "factor"))
expect_equal(
summ[["diagnosis"]],
c(-0.41471, 0.30371, -0.41471, 0.24455, 0.08321, 0.13948, 0.26193,
-0.20346),
tolerance = 1e-4)
expect_equal(
summ[["age"]],
c(369, 667, 166, 528, 396, 213, 405, 237),
tolerance = 1e-4)
expect_equal(
summ[["score"]],
c(172, 416, 194, 398, 443, 255, 428, 407),
tolerance = 1e-4)
expect_equal(
summ[["size"]],
c(4, 8, 4, 9, 9, 6, 7, 6),
tolerance = 1e-4)
expect_equal(
summ[["participant"]],
c(2, 3, 2, 3, 3, 2, 3, 2),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ),
c(".____.folds", "diagnosis", "age", "score", "size", "participant"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ),
c("factor", "numeric", "integer", "integer", "integer", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ),
c("integer", "double", "integer", "integer", "integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ),
c(8L, 6L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ)),
character(0),
fixed = TRUE)
## Finished testing 'summ' ####
# With majority cat_level only
summ <- calculate_summary_collapse_groups_(
data = prepped[["data"]],
tmp_old_group_var = prepped[["group_cols"]],
cat_cols = prepped[["cat_cols"]],
cat_levels = ".majority",
num_cols = prepped[["num_cols"]],
group_aggregation_fn = sum,
balance_size = TRUE,
id_cols = prepped[["id_cols"]]
)
summ_ordered <- dplyr::arrange(summ, .____.folds)
expect_equal(summ_ordered$diagnosis, expected_summ$majority)
# Edge cases
# diagnosis leads to zero-variance vector
# Create data frame
df <- data.frame(
"participant" = factor(rep(1, 10)),
"age" = c(-5, 5, -5, 5, -5, 5, -5, 5, -5, 5),
"diagnosis" = factor(c(1,1,2,2,1,1,2,2,1,1)),
".__.folds" = factor(c(1, 1, 2, 2, 3, 3, 4, 4, 5, 5))
)
## Testing 'summ <- calculate_summary_collapse_groups_( data = df, tmp_o...' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19148 <- xpectr::capture_side_effects(summ <- calculate_summary_collapse_groups_(
data = df,
tmp_old_group_var = ".__.folds",
cat_cols = "diagnosis",
cat_levels = NULL,
num_cols = "age",
group_aggregation_fn = sum,
balance_size = FALSE,
id_cols = "participant"
), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['warnings']]),
xpectr::strip("Combining the standardized level counts for the `cat_cols` column 'diagnosis' led to a zero-variance vector. Consider not balancing this column or change the included `cat_levels`."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['messages']]),
xpectr::strip(character(0)),
fixed = TRUE)
# Assigning output
output_19148 <- xpectr::suppress_mw(summ <- calculate_summary_collapse_groups_(
data = df,
tmp_old_group_var = ".__.folds",
cat_cols = "diagnosis",
cat_levels = NULL,
num_cols = "age",
group_aggregation_fn = sum,
balance_size = FALSE,
id_cols = "participant"
))
# Testing class
expect_equal(
class(output_19148),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
output_19148[[".__.folds"]],
factor(c(1, 2, 3, 4, 5)),
tolerance = 1e-4)
expect_equal(
output_19148[["diagnosis"]],
c(0, 0, 0, 0, 0),
tolerance = 1e-4)
expect_equal(
output_19148[["age"]],
c(0, 0, 0, 0, 0),
tolerance = 1e-4)
expect_equal(
output_19148[["participant"]],
c(1, 1, 1, 1, 1),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(output_19148),
c(".__.folds", "diagnosis", "age", "participant"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19148),
c("factor", "numeric", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19148),
c("integer", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19148),
5:4)
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19148)),
character(0),
fixed = TRUE)
## Finished testing 'summ <- calculate_summary_collapse_groups_( data = df, tmp_o...' ####
})
test_that("testing scale_and_combine_()", {
xpectr::set_test_seed(42)
df = data.frame(
"a" = c(1,2,3,4,5,6),
"b" = c(1,2,3,4,5,6) * -1,
"c" = c(1,2,3,4,5,6) * 10
)
w <- c("b"=2, "c"=1, "a"=5)
# Expected
w_norm <- w / sum(w)
df_scaled <- df %>%
dplyr::mutate(
a = standardize_(a) * w_norm[["a"]],
b = standardize_(b) * w_norm[["b"]],
c = standardize_(c) * w_norm[["c"]],
new = a + b + c
)
# Observed
combined <- scale_and_combine_(
data = df,
weights = w,
include_cols = c("a", "b", "c"),
scale_fn=standardize_,
col_name="new")$new
expect_equal(df_scaled$new, combined)
# Names in weights must match
## Testing 'scale_and_combine_( data = df, weights = c("...' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19148 <- xpectr::capture_side_effects(scale_and_combine_(
data = df,
weights = c("b"=2, "c"=1, "d"=5),
include_cols = c("a", "b", "c"),
scale_fn=standardize_,
col_name="new"), reset_seed = TRUE)
expect_match(
xpectr::strip(side_effects_19148[['error']], lowercase = TRUE),
xpectr::strip("must be a permutation of set {'a','b','c'}", lowercase = TRUE),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
## Finished testing 'scale_and_combine_( data = df, weights = c("...' ####
# Include cols
## Testing 'scale_and_combine_( data = df, weights = w, ...' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19148 <- xpectr::capture_side_effects(scale_and_combine_(
data = df,
weights = w,
include_cols = c("a", "b", "d"),
scale_fn=standardize_,
col_name="new"), reset_seed = TRUE)
expect_match(
xpectr::strip(side_effects_19148[['error']], lowercase = TRUE),
xpectr::strip("must include the elements {'a','b','d'}.", lowercase = TRUE),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
## Finished testing 'scale_and_combine_( data = df, weights = w, ...' ####
})
test_that("testing add_new_groups_()", {
# Set seed
xpectr::set_test_seed(42)
# Create data frame
df <- data.frame(
"participant" = factor(rep(1:20, 3)),
"age" = rep(sample(c(1:100), 20), 3),
"diagnosis" = factor(rep(sample(c(1:3), 20, replace = TRUE), 3)),
"score" = sample(c(1:100), 20 * 3)
)
df <- df %>% dplyr::arrange(participant)
# Sample rows to get unequal sizes per participant
df <- dplyr::sample_n(df, size = 53)
# Create the initial groups (to be collapsed)
df <- fold(
data = df,
k = 8,
method = "n_dist",
id_col = "participant"
)
# Ungroup the data frame
# Otherwise `collapse_groups()` would be
# applied to each fold separately!
df <- dplyr::ungroup(df)
# One row per fold / input group
xpectr::set_test_seed(42)
new_groups = data.frame(
".folds" = factor(sample(1:8, 8)),
"combined" = runif(8),
".coll_g" = factor(sample(c(1:4, 1:4), 8))
) %>%
dplyr::group_by(.data$.coll_g)
# Add .coll_g to df
df_added_groups <- add_new_groups_(
data = df,
new_groups = new_groups,
tmp_old_group_var = ".folds",
col_name = ".coll_g"
)
expect_equal(
colnames(df_added_groups),
c("participant", "age", "diagnosis", "score", ".coll_g")
)
## Testing 'df_added_groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(df_added_groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(df_added_groups[["participant"]], n = 30),
structure(c(1L, 10L, 11L, 12L, 13L, 14L, 14L, 16L, 16L, 16L, 17L,
18L, 19L, 19L, 2L, 20L, 3L, 3L, 3L, 4L, 5L, 5L, 6L, 6L, 7L,
8L, 8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6",
"7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17",
"18", "19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(df_added_groups[["age"]], n = 30),
c(92, 65, 42, 91, 83, 23, 23, 80, 80, 80, 88, 10, 39, 39, 93, 46,
29, 29, 29, 81, 62, 62, 50, 50, 70, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(df_added_groups[["diagnosis"]], n = 30),
structure(c(3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 3L,
3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
xpectr::smpl(df_added_groups[["score"]], n = 30),
c(35, 18, 86, 73, 75, 56, 33, 47, 72, 64, 68, 24, 80, 32, 44, 85,
4, 93, 74, 37, 42, 65, 91, 62, 21, 60, 5, 90, 50, 53),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(df_added_groups[[".coll_g"]], n = 30),
structure(c(4L, 4L, 2L, 4L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 1L, 3L,
3L, 4L, 3L, 1L, 1L, 1L, 3L, 3L, 3L, 1L, 1L, 2L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4"), class = "factor"))
# Testing column names
expect_equal(
names(df_added_groups),
c("participant", "age", "diagnosis", "score", ".coll_g"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(df_added_groups),
c("factor", "integer", "factor", "integer", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(df_added_groups),
c("integer", "integer", "integer", "integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(df_added_groups),
c(53L, 5L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(df_added_groups)),
character(0),
fixed = TRUE)
## Finished testing 'df_added_groups' ####
## Testing 'add_new_groups_( data = df, new_groups = new...' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19148 <- xpectr::capture_side_effects(add_new_groups_(
data = df,
new_groups = new_groups,
tmp_old_group_var = ".folds",
col_name = ".folds"
), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['error']]),
xpectr::strip("`tmp_old_group_var` and `col_name` were identical."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
## Finished testing 'add_new_groups_( data = df, new_groups = new...' ####
## Testing 'add_new_groups_( data = df %>% dplyr::mutate...' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19148 <- xpectr::capture_side_effects(add_new_groups_(
data = df %>%
dplyr::mutate(.folds = as.numeric(.folds)),
new_groups = new_groups,
tmp_old_group_var = ".folds",
col_name = ".coll_g"
), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['error']]),
xpectr::strip("Assertion on 'data[[tmp_old_group_var]]' failed: Must be of type 'factor', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
## Finished testing 'add_new_groups_( data = df %>% dplyr::mutate...' ####
## Testing 'add_new_groups_( data = df, new_groups = new...' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19148 <- xpectr::capture_side_effects(add_new_groups_(
data = df,
new_groups = new_groups %>%
dplyr::mutate(.folds = as.numeric(.folds)),
tmp_old_group_var = ".folds",
col_name = ".coll_g"
), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['error']]),
xpectr::strip("Assertion on 'new_groups[[tmp_old_group_var]]' failed: Must be of type 'factor', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
## Finished testing 'add_new_groups_( data = df, new_groups = new...' ####
})
test_that("testing add_ordered_summary_groups_()", {
# Set seed
xpectr::set_test_seed(42)
# Create data frame
df <- data.frame(
"participant" = factor(rep(1:20, 3)),
"age" = rep(sample(c(1:100), 20), 3),
"diagnosis" = factor(rep(sample(c(1:3), 20, replace = TRUE), 3)),
"score" = sample(c(1:100), 20 * 3)
)
df <- df %>% dplyr::arrange(participant)
# Sample rows to get unequal sizes per participant
df <- dplyr::sample_n(df, size = 53)
# Create the initial groups (to be collapsed)
df <- fold(
data = df,
k = 8,
method = "n_dist",
id_col = "participant"
)
# Ungroup the data frame
# Otherwise `collapse_groups()` would be
# applied to each fold separately!
df <- dplyr::ungroup(df)
# One row per fold / input group
xpectr::set_test_seed(42)
summary <- data.frame(
".folds" = factor(sample(1:8, 8)),
"combined" = runif(8)
)
# DESCENDING
expected_grouping <- summary %>%
dplyr::arrange(dplyr::desc(.data$combined)) %>%
dplyr::mutate(.coll_g = factor(rep(1:4, each=2))) %>%
dplyr::select(.folds, .coll_g) %>%
dplyr::arrange(.folds)
df_added <- add_ordered_summary_groups_(
data = df,
summary = summary,
n = 4,
group_cols = ".folds",
num_col = "combined",
method = "descending",
col_name = ".coll_g"
)
observed_grouping <- df_added %>%
dplyr::count(.folds, .coll_g) %>%
dplyr::select(-"n") %>%
dplyr::arrange(.folds)
# Check we get the expected results
expect_identical(
as.data.frame(observed_grouping),
as.data.frame(expected_grouping)
)
## Testing 'observed_grouping' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(observed_grouping),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
observed_grouping[[".folds"]],
structure(1:8, .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
observed_grouping[[".coll_g"]],
structure(c(1L, 4L, 1L, 3L, 2L, 4L, 2L, 3L), .Label = c("1", "2",
"3", "4"), class = "factor"))
# Testing column names
expect_equal(
names(observed_grouping),
c(".folds", ".coll_g"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(observed_grouping),
c("factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(observed_grouping),
c("integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(observed_grouping),
c(8L, 2L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(observed_grouping)),
character(0),
fixed = TRUE)
## Finished testing 'observed_grouping' ####
# ASCENDING
expected_grouping <- summary %>%
dplyr::arrange(.data$combined) %>%
dplyr::mutate(.coll_g = factor(rep(1:4, each=2))) %>%
dplyr::select(.folds, .coll_g) %>%
dplyr::arrange(.folds)
df_added <- add_ordered_summary_groups_(
data = df,
summary = summary,
n = 4,
group_cols = ".folds",
num_col = "combined",
method = "ascending",
col_name = ".coll_g"
)
observed_grouping <- df_added %>%
dplyr::count(.folds, .coll_g) %>%
dplyr::select(-"n") %>%
dplyr::arrange(.folds)
# Check we get the expected results
expect_identical(
as.data.frame(observed_grouping),
as.data.frame(expected_grouping)
)
## Testing 'observed_grouping' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(observed_grouping),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
observed_grouping[[".folds"]],
structure(1:8, .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
observed_grouping[[".coll_g"]],
structure(c(4L, 1L, 4L, 2L, 3L, 1L, 3L, 2L), .Label = c("1", "2",
"3", "4"), class = "factor"))
# Testing column names
expect_equal(
names(observed_grouping),
c(".folds", ".coll_g"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(observed_grouping),
c("factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(observed_grouping),
c("integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(observed_grouping),
c(8L, 2L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(observed_grouping)),
character(0),
fixed = TRUE)
## Finished testing 'observed_grouping' ####
})
test_that("testing replace_forbidden_names_()", {
# Set seed
xpectr::set_test_seed(42)
# Create data frame
df <- data.frame(
"participant" = factor(rep(1:20, 3)),
"age" = rep(sample(c(1:100), 20), 3),
"diagnosis" = factor(rep(sample(c(1:3), 20, replace = TRUE), 3)),
"score" = sample(c(1:100), 20 * 3),
"combined" = runif(60),
"n" = rep(sample(c(1:100), 20), 3),
".folder" = rep(sample(c(1:100), 20), 3)
)
df <- df %>% dplyr::arrange(participant)
# Sample rows to get unequal sizes per participant
df <- dplyr::sample_n(df, size = 23)
# Create the initial groups (to be collapsed)
df <- fold(
data = df,
k = 8,
method = "n_dist",
id_col = "participant"
)
# Ungroup the data frame
# Otherwise `collapse_groups()` would be
# applied to each fold separately!
df <- dplyr::ungroup(df)
replaced <- replace_forbidden_names_(
data = df,
data_group_cols = ".foldings",
group_cols = ".folds",
cat_cols = c("diagnosis", ".folds"),
num_cols = c("n", "score"),
id_cols = c("participant", "combined"),
weights = c("score" = 3, "combined" = 8, ".folds" = 2),
invert = FALSE)
expect_equal(
colnames(replaced$data),
c("participant", "age", "diagnosis", "score", ".____combined",
".____n", ".____.folder", ".____.folds")
)
expect_equal(
dplyr::group_vars(replaced$data),
character(0)
)
expect_equal(
replaced$data_group_cols,
".____.foldings"
)
expect_equal(
replaced$group_cols,
".____.folds"
)
expect_equal(
replaced$cat_cols,
c("diagnosis", ".____.folds")
)
expect_equal(
replaced$num_cols,
c(".____n", "score")
)
expect_equal(
replaced$id_cols,
c("participant", ".____combined")
)
expect_equal(
replaced$weights,
c("score" = 3, ".____combined" = 8, ".____.folds" = 2)
)
# Grouped data
replaced <- replace_forbidden_names_(
data = dplyr::group_by(df, .folds),
data_group_cols = ".foldings",
group_cols = ".folds",
cat_cols = c("diagnosis", ".folds"),
num_cols = c("n", "score"),
id_cols = c("participant", "combined"),
weights = c("score" = 3, "combined" = 8, ".folds" = 2),
invert = FALSE)
expect_equal(
colnames(replaced$data),
c("participant", "age", "diagnosis", "score", ".____combined",
".____n", ".____.folder", ".____.folds")
)
expect_equal(
dplyr::group_vars(replaced$data),
".____.folds"
)
## INVERSE!
inverse_replaced <- replace_forbidden_names_(
data = replaced$data, # Still grouped
data_group_cols = replaced$data_group_cols,
group_cols = replaced$group_cols,
cat_cols = replaced$cat_cols,
num_cols = replaced$num_cols,
id_cols = replaced$id_cols,
weights = replaced$weights,
invert = TRUE)
expect_identical(
as.data.frame(inverse_replaced$data),
as.data.frame(df)
)
expect_equal(
colnames(inverse_replaced$data),
c("participant", "age", "diagnosis", "score", "combined",
"n", ".folder", ".folds")
)
expect_equal(
dplyr::group_vars(inverse_replaced$data),
".folds"
)
expect_equal(
inverse_replaced$data_group_cols,
".foldings"
)
expect_equal(
inverse_replaced$group_cols,
".folds"
)
expect_equal(
inverse_replaced$cat_cols,
c("diagnosis", ".folds")
)
expect_equal(
inverse_replaced$num_cols,
c("n", "score")
)
expect_equal(
inverse_replaced$id_cols,
c("participant", "combined")
)
expect_equal(
inverse_replaced$weights,
c("score" = 3, "combined" = 8, ".folds" = 2)
)
})
test_that("fuzz testing collapse_groups() without auto-tune", {
# Set seed
xpectr::set_test_seed(42)
# Create data frame
df <- data.frame(
"participant" = factor(rep(1:20, 3)),
"participant_2" = factor(rep(1:20, 3)),
"age" = rep(sample(c(1:100), 20), 3),
"answer" = factor(sample(c("a", "b", "c", "d"), 60, replace = TRUE)),
"score" = sample(c(1:100), 20 * 3)
)
df <- df %>% dplyr::arrange(participant)
df$session <- rep(c("1", "2", "3"), 20)
# Sample rows to get unequal sizes per participant
df <- dplyr::sample_n(df, size = 53)
# Create the initial groups (to be collapsed)
df <- fold(
data = df,
k = 8,
method = "n_dist",
id_col = "participant"
)
# Ungroup the data frame
# Otherwise `collapse_groups()` would be
# applied to each fold separately!
df <- dplyr::ungroup(df)
# Generate expectations for 'collapse_groups'
# Tip: comment out the gxs_function() call
# so it is easy to regenerate the tests
# xpectr::set_test_seed(42)
# xpectr::gxs_function(
# fn = collapse_groups,
# args_values = list(
# "data" = list(df, c(1,2,3), 1, NA),
# "n" = list(3, 4, 1, 8, 9, "5", NA),
# "group_cols" = list(".folds", c(".folds", "participant"), "answer", 1, NA),
# "cat_cols" = list("answer", c("answer", "session"), "score", ".folds", 1, NA),
# "cat_levels" = list(NULL, ".majority", ".minority", "nope", c("a" = 2, "b" = 3),
# c("nope" = 2, "b" = 3), list("answer" = c("a" = 2)),
# list("session" = c("a" = 2)), list("sdfs" = c("a" = 2)), NA),
# "num_cols" = list("score", c("score", "age"), "answer", ".folds", 1, NA),
# "id_cols" = list("participant", c("participant_2", "participant"), "score", ".folds", 1, NA),
# "balance_size" = list(TRUE, FALSE, 1, NA),
# "auto_tune" = list(FALSE, 1, NA), # TRUE is tested elsewhere
# "weights" = list(NULL, c("size" = 2, "answer" = 7, "score" = 1, "participant" = 2),
# c("size" = 3, "nope" = 5), c("participant" = 2,"participant_2" = 2),
# list("size" = 2, "answer" = 7), c("size" = NA, "answer" = 7),
# 1, NA),
# "method" = list("balance", "ascending", "descending", "none", list("balance"), 1, NA),
# "group_aggregation_fn" = list(mean, sum, sd, 2, NA),
# "num_new_group_cols" = list(1, 2, "two", NA),
# "unique_new_group_cols_only" = list(TRUE, FALSE, 1, NA),
# "max_iters" = list(2, 0, "sdf", NA),
# "extreme_pairing_levels" = list(1, 2, 0, "str", NA),
# "combine_method" = list("avg_standardized", "avg_min_max_scaled", "nope", 1, NA),
# "col_name" = list(".collg", ".some_name.", ".folds", "answer", 1, NA),
# "parallel" = list(FALSE, 1, NA),
# "verbose" = list(FALSE, 1, NA)
# ),
# extra_combinations = list(
# list("cat_cols" = NULL, "num_cols" = NULL, "id_cols" = NULL, "balance_size" = FALSE),
# list("cat_cols" = "answer", "num_cols" = NULL, "id_cols" = NULL, "balance_size" = FALSE),
# list("cat_cols" = NULL, "num_cols" = "score", "id_cols" = NULL, "balance_size" = FALSE),
# list("cat_cols" = NULL, "num_cols" = NULL, "id_cols" = "participant", "balance_size" = FALSE),
# list("cat_cols" = NULL, "num_cols" = NULL, "id_cols" = NULL, "balance_size" = TRUE),
# list("auto_tune" = TRUE, "method" = "ascending")
# ),
# indentation = 2,
# copy_env = FALSE
# )
## Testing 'collapse_groups' ####
## Initially generated by xpectr
# Testing different combinations of argument values
# Testing collapse_groups(data = df, n = 3, group_cols...
xpectr::set_test_seed(42)
# Assigning output
output_19148 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_19148),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_19148[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19148[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19148[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19148[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_19148[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19148[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_19148[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_19148[[".collg"]], n = 30),
structure(c(2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 2L,
2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_19148),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19148),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19148),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19148),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19148)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = c(1, 2, 3), n = 3, gr...
# Changed from baseline: data = c(1, 2, 3)
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19370 <- xpectr::capture_side_effects(collapse_groups(data = c(1, 2, 3), n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19370[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'data': Must be of type 'data.frame', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19370[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = 1, n = 3, group_cols ...
# Changed from baseline: data = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_12861 <- xpectr::capture_side_effects(collapse_groups(data = 1, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_12861[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'data': Must be of type 'data.frame', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_12861[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = NA, n = 3, group_cols...
# Changed from baseline: data = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_18304 <- xpectr::capture_side_effects(collapse_groups(data = NA, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_18304[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'data': Must be of type 'data.frame', not 'logical'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_18304[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = NULL, n = 3, group_co...
# Changed from baseline: data = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16417 <- xpectr::capture_side_effects(collapse_groups(data = NULL, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16417[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'data': Must be of type 'data.frame', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16417[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 4, group_cols...
# Changed from baseline: n = 4
xpectr::set_test_seed(42)
# Assigning output
output_15190 <- collapse_groups(data = df, n = 4, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_15190),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_15190[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_15190[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_15190[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_15190[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_15190[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_15190[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_15190[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_15190[[".collg"]], n = 30),
structure(c(3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 4L, 4L, 3L,
3L, 1L, 1L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 3L,
3L, 3L), .Label = c("1", "2", "3", "4"), class = "factor"))
# Testing column names
expect_equal(
names(output_15190),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_15190),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_15190),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_15190),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_15190)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 1, group_cols...
# Changed from baseline: n = 1
xpectr::set_test_seed(42)
# Assigning output
output_17365 <- collapse_groups(data = df, n = 1, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_17365),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_17365[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_17365[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_17365[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_17365[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_17365[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_17365[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_17365[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_17365[[".collg"]], n = 30),
structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = "1", class = "factor"))
# Testing column names
expect_equal(
names(output_17365),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_17365),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_17365),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_17365),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_17365)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 8, group_cols...
# Changed from baseline: n = 8
xpectr::set_test_seed(42)
# Assigning output
output_11346 <- collapse_groups(data = df, n = 8, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_11346),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_11346[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11346[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11346[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11346[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_11346[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11346[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_11346[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_11346[[".collg"]], n = 30),
structure(c(7L, 7L, 2L, 2L, 2L, 8L, 8L, 8L, 7L, 7L, 3L, 3L, 4L,
4L, 5L, 5L, 3L, 3L, 6L, 6L, 6L, 5L, 5L, 1L, 1L, 1L, 1L, 4L,
4L, 4L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
# Testing column names
expect_equal(
names(output_11346),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_11346),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_11346),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_11346),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_11346)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 9, group_cols...
# Changed from baseline: n = 9
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16569 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 9, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16569[['error']]),
xpectr::strip("`data` subset had fewer `group_cols` groups (8) than `n` (9). If `data` was originally grouped, the `group_cols` within each of those subsets must contain `>= n` groups to collapse."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16569[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = "5", group_co...
# Changed from baseline: n = "5"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17050 <- xpectr::capture_side_effects(collapse_groups(data = df, n = "5", group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17050[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'n': Must be of type 'numeric', not 'character'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17050[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = NA, group_col...
# Changed from baseline: n = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_14577 <- xpectr::capture_side_effects(collapse_groups(data = df, n = NA, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_14577[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'n': Contains missing values (element 1)."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_14577[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = NULL, group_c...
# Changed from baseline: n = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17191 <- xpectr::capture_side_effects(collapse_groups(data = df, n = NULL, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17191[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'n': Must be of type 'numeric', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17191[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_cols = c(".fold...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19346 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = c(".folds", "participant"), cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19346[['error']]),
xpectr::strip("1 assertions failed:\n * All columns in 'c(group_cols, cat_cols, num_cols, id_cols)' must be unique. Found duplicates: 'participant'"),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19346[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_cols = "answer"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_12554 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = "answer", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_12554[['error']]),
xpectr::strip("1 assertions failed:\n * All columns in 'c(group_cols, cat_cols, num_cols, id_cols)' must be unique. Found duplicates: 'answer'"),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_12554[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_cols = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_14622 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = 1, cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_14622[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'group_cols': Must be of type 'character', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_14622[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_cols = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19400 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = NA, cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19400[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'group_cols': Contains missing values (element 1)."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19400[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_cols = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19782 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = NULL, cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19782[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'group_cols': Must be of type 'character', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19782[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols = c("answer"...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_11174 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = c("answer", "session"), cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_11174[['error']]),
xpectr::strip("1 assertions failed:\n * Variable '`cat_cols` column data[['session']]': Must be of type 'factor', not 'character'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_11174[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols = "score"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_14749 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "score", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_14749[['error']]),
xpectr::strip("1 assertions failed:\n * All columns in 'c(group_cols, cat_cols, num_cols, id_cols)' must be unique. Found duplicates: 'score'"),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_14749[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols = ".folds"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_15603 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = ".folds", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_15603[['error']]),
xpectr::strip("1 assertions failed:\n * All columns in 'c(group_cols, cat_cols, num_cols, id_cols)' must be unique. Found duplicates: '.folds'"),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_15603[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19040 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = 1, cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19040[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'cat_cols': Must be of type 'character' (or 'NULL'), not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19040[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_11387 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = NA, cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_11387[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'cat_cols': Contains missing values (element 1)."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_11387[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols = NULL
xpectr::set_test_seed(42)
# Assigning output
output_19888 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = NULL, cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_19888),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_19888[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19888[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19888[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19888[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_19888[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19888[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_19888[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_19888[[".collg"]], n = 30),
structure(c(2L, 2L, 1L, 1L, 1L, 3L, 3L, 3L, 2L, 2L, 1L, 1L, 2L,
2L, 3L, 3L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_19888),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19888),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19888),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19888),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19888)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols, num_cols, i...
xpectr::set_test_seed(42)
# Assigning output
output_19466 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = NULL, cat_levels = NULL, num_cols = NULL, id_cols = NULL, balance_size = FALSE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_19466),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_19466[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19466[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19466[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19466[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_19466[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19466[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_19466[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_19466[[".collg"]], n = 30),
structure(c(1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 1L, 1L, 2L, 2L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_19466),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19466),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19466),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19466),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19466)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols, num_cols, i...
xpectr::set_test_seed(42)
# Assigning output
output_10824 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = NULL, id_cols = NULL, balance_size = FALSE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_10824),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_10824[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_10824[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_10824[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_10824[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_10824[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_10824[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_10824[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_10824[[".collg"]], n = 30),
structure(c(1L, 1L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L,
1L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_10824),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_10824),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_10824),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_10824),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_10824)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols, num_cols, i...
xpectr::set_test_seed(42)
# Assigning output
output_15142 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = NULL, cat_levels = NULL, num_cols = "score", id_cols = NULL, balance_size = FALSE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_15142),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_15142[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_15142[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_15142[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_15142[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_15142[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_15142[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_15142[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_15142[[".collg"]], n = 30),
structure(c(3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 1L, 1L, 3L,
3L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 3L,
3L, 3L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_15142),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_15142),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_15142),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_15142),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_15142)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols, num_cols, i...
xpectr::set_test_seed(42)
# Assigning output
output_13902 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = NULL, cat_levels = NULL, num_cols = NULL, id_cols = "participant", balance_size = FALSE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_13902),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_13902[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_13902[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_13902[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_13902[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_13902[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_13902[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_13902[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_13902[[".collg"]], n = 30),
structure(c(2L, 2L, 1L, 1L, 1L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_13902),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_13902),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_13902),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_13902),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_13902)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols, num_cols, i...
xpectr::set_test_seed(42)
# Assigning output
output_19057 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = NULL, cat_levels = NULL, num_cols = NULL, id_cols = NULL, balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_19057),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_19057[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19057[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19057[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19057[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_19057[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19057[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_19057[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_19057[[".collg"]], n = 30),
structure(c(1L, 1L, 3L, 3L, 3L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L,
1L, 3L, 3L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 1L,
1L, 1L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_19057),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19057),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19057),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19057),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19057)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_levels = ".majority"
xpectr::set_test_seed(42)
# Assigning output
output_14469 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = ".majority", num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_14469),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_14469[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_14469[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_14469[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_14469[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_14469[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_14469[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_14469[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_14469[[".collg"]], n = 30),
structure(c(2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 3L, 3L, 2L,
2L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_14469),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_14469),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_14469),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_14469),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_14469)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_levels = ".minority"
xpectr::set_test_seed(42)
# Assigning output
output_18360 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = ".minority", num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_18360),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_18360[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_18360[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_18360[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_18360[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_18360[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_18360[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_18360[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_18360[[".collg"]], n = 30),
structure(c(3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 2L, 2L, 3L,
3L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 3L,
3L, 3L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_18360),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_18360),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_18360),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_18360),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_18360)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_levels = "nope"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17375 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = "nope", num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_match(
xpectr::strip(side_effects_17375[['error']], lowercase = TRUE),
xpectr::strip(
ifelse(
is_checkmate_v2_1(),
"must be a subset of {'.minority','.majority','a','b','c','d'}",
"must be a subset of set {'.minority','.majority','a','b','c','d'}"
), lowercase = TRUE),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17375[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_levels = c(a = 2,...
xpectr::set_test_seed(42)
# Assigning output
output_18110 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = c(a = 2, b = 3), num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_18110),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_18110[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_18110[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_18110[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_18110[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_18110[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_18110[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_18110[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_18110[[".collg"]], n = 30),
structure(c(3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 1L, 1L, 1L,
1L, 3L, 3L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_18110),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_18110),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_18110),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_18110),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_18110)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_levels = c(nope =...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13881 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = c(nope = 2, b = 3), num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_match(
xpectr::strip(side_effects_13881[['error']], lowercase = TRUE),
xpectr::strip(
ifelse(
is_checkmate_v2_1(),
"must be a subset of {'.minority','.majority','a','b','c','d'}",
"must be a subset of set {'.minority','.majority','a','b','c','d'}"
), lowercase = TRUE),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13881[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_levels = list(ans...
xpectr::set_test_seed(42)
# Assigning output
output_16851 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = list(answer = c(a = 2)), num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_16851),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_16851[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_16851[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_16851[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_16851[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_16851[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_16851[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_16851[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_16851[[".collg"]], n = 30),
structure(c(2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 3L, 3L, 2L,
2L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_16851),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_16851),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_16851),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_16851),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_16851)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_levels = list(ses...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_10039 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = list(session = c(a = 2)), num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_10039[['error']]),
xpectr::strip("1 assertions failed:\n * when `cat_levels` is a list, its names must be equal to those in `cat_cols`."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_10039[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_levels = list(sdf...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_18329 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = list(sdfs = c(a = 2)), num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_18329[['error']]),
xpectr::strip("1 assertions failed:\n * when `cat_levels` is a list, its names must be equal to those in `cat_cols`."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_18329[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_levels = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_10073 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NA, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_10073[['error']], lowercase = TRUE),
xpectr::strip(
ifelse(is_checkmate_v2_1(),
"Assertion on 'cat_levels' failed: One of the following must apply:\n * checkmate::check_character(cat_levels): Contains missing values (element 1)\n * checkmate::check_numeric(cat_levels): Must have names\n * checkmate::check_list(cat_levels): Must be of type 'list' (or 'NULL'), not 'logical'.",
"Assertion failed: One of the following must apply:\n * checkmate::check_character(cat_levels): Contains missing values (element 1)\n * checkmate::check_numeric(cat_levels): Must have names\n * checkmate::check_list(cat_levels): Must be of type 'list' (or 'NULL'), not 'logical'."),
lowercase = TRUE),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_10073[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_cols = c("score",...
xpectr::set_test_seed(42)
# Assigning output
output_12076 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = c("score", "age"), id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_12076),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_12076[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_12076[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_12076[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_12076[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_12076[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_12076[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_12076[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_12076[[".collg"]], n = 30),
structure(c(3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 2L, 2L, 1L,
1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_12076),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_12076),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_12076),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_12076),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_12076)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_cols = "answer"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19066 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "answer", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19066[['error']]),
xpectr::strip("1 assertions failed:\n * All columns in 'c(group_cols, cat_cols, num_cols, id_cols)' must be unique. Found duplicates: 'answer'"),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19066[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_cols = ".folds"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16117 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = ".folds", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16117[['error']]),
xpectr::strip("1 assertions failed:\n * All columns in 'c(group_cols, cat_cols, num_cols, id_cols)' must be unique. Found duplicates: '.folds'"),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16117[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_cols = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13795 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = 1, id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_13795[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'num_cols': Must be of type 'character' (or 'NULL'), not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13795[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_cols = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_14357 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = NA, id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_14357[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'num_cols': Contains missing values (element 1)."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_14357[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_cols = NULL
xpectr::set_test_seed(42)
# Assigning output
output_10374 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = NULL, id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_10374),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_10374[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_10374[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_10374[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_10374[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_10374[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_10374[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_10374[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_10374[[".collg"]], n = 30),
structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 3L,
3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_10374),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_10374),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_10374),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_10374),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_10374)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: id_cols = c("particip...
xpectr::set_test_seed(42)
# Assigning output
output_19735 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = c("participant_2", "participant"), balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_19735),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_19735[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19735[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19735[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19735[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_19735[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19735[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_19735[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_19735[[".collg"]], n = 30),
structure(c(2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 2L,
2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_19735),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19735),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19735),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19735),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19735)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: id_cols = "score"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_14317 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "score", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_14317[['error']]),
xpectr::strip("1 assertions failed:\n * All columns in 'c(group_cols, cat_cols, num_cols, id_cols)' must be unique. Found duplicates: 'score'"),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_14317[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: id_cols = ".folds"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19575 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = ".folds", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19575[['error']]),
xpectr::strip("1 assertions failed:\n * All columns in 'c(group_cols, cat_cols, num_cols, id_cols)' must be unique. Found duplicates: '.folds'"),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19575[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: id_cols = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_18877 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = 1, balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_18877[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'id_cols': Must be of type 'character' (or 'NULL'), not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_18877[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: id_cols = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16399 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = NA, balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16399[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'id_cols': Contains missing values (element 1)."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16399[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: id_cols = NULL
xpectr::set_test_seed(42)
# Assigning output
output_19709 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = NULL, balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_19709),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_19709[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19709[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19709[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19709[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_19709[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19709[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_19709[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_19709[[".collg"]], n = 30),
structure(c(2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 2L,
2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_19709),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19709),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19709),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19709),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19709)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: balance_size = FALSE
xpectr::set_test_seed(42)
# Assigning output
output_16188 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = FALSE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_16188),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_16188[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_16188[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_16188[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_16188[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_16188[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_16188[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_16188[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_16188[[".collg"]], n = 30),
structure(c(3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L,
3L, 1L, 1L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L,
3L, 3L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_16188),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_16188),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_16188),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_16188),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_16188)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: balance_size = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13334 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = 1, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_13334[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'balance_size': Must be of type 'logical flag', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13334[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: balance_size = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13467 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = NA, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_13467[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'balance_size': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13467[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: balance_size = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13984 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = NULL, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_13984[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'balance_size': Must be of type 'logical flag', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13984[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: auto_tune = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17846 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = 1, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17846[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'auto_tune': Must be of type 'logical flag', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17846[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: auto_tune = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_10389 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = NA, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_10389[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'auto_tune': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_10389[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: auto_tune = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17487 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = NULL, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17487[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'auto_tune': Must be of type 'logical flag', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17487[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: auto_tune, method
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16772 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = TRUE, weights = NULL, method = "ascending", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16772[['error']]),
xpectr::strip("1 assertions failed:\n * when `method` != 'balance', `auto_tune` must be disabled."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16772[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: weights = c(size = 2,...
xpectr::set_test_seed(42)
# Assigning output
output_11712 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = c(size = 2, answer = 7, score = 1, participant = 2), method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_11712),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_11712[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11712[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11712[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11712[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_11712[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11712[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_11712[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_11712[[".collg"]], n = 30),
structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 3L,
3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_11712),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_11712),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_11712),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_11712),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_11712)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: weights = c(size = 3,...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_12610 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = c(size = 3, nope = 5), method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_match(
xpectr::strip(side_effects_12610[['error']], lowercase = TRUE),
xpectr::strip(
ifelse(
is_checkmate_v2_1(),
"must be a subset of {'size','answer','score','participant'}",
"must be a subset of set {'size','answer','score','participant'}"
), lowercase = TRUE),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_12610[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: weights = c(participa...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_15144 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = c(participant = 2, participant_2 = 2), method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_match(
xpectr::strip(side_effects_15144[['error']], lowercase = TRUE),
xpectr::strip(
ifelse(
is_checkmate_v2_1(),
"must be a subset of {'size','answer','score','participant'}",
"must be a subset of set {'size','answer','score','participant'}"
), lowercase = TRUE),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_15144[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: weights = list(size =...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16756 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = list(size = 2, answer = 7), method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16756[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'weights': Must be of type 'numeric' (or 'NULL'), not 'list'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16756[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: weights = c(size = NA...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19828 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = c(size = NA, answer = 7), method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19828[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'weights': Contains missing values (element 1)."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19828[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: weights = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17595 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = 1, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17595[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'weights': Must have names."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17595[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: weights = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_15664 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NA, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_15664[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'weights': Must have names."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_15664[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: method = "ascending"
xpectr::set_test_seed(42)
# Assigning output
output_18496 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "ascending", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_18496),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_18496[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_18496[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_18496[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_18496[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_18496[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_18496[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_18496[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_18496[[".collg"]], n = 30),
structure(c(3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 1L,
1L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 2L, 2L, 2L, 2L, 1L,
1L, 1L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_18496),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_18496),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_18496),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_18496),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_18496)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: method = "descending"
xpectr::set_test_seed(42)
# Assigning output
output_11894 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "descending", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_11894),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_11894[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11894[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11894[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11894[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_11894[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11894[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_11894[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_11894[[".collg"]], n = 30),
structure(c(1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 3L,
3L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 1L, 1L, 2L, 2L, 2L, 2L, 3L,
3L, 3L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_11894),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_11894),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_11894),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_11894),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_11894)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: method = "none"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_12712 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "none", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_match(
xpectr::strip(side_effects_12712[['error']], lowercase = TRUE),
xpectr::strip(
ifelse(
is_checkmate_v2_1(),
"must be a subset of {'balance','ascending','descending'}",
"must be a subset of set {'balance','ascending','descending'}"
), lowercase = TRUE),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_12712[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: method = list("balance")
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_18281 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = list("balance"), group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_18281[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'method': Must be of type 'string', not 'list'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_18281[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: method = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16932 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = 1, group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16932[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'method': Must be of type 'string', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16932[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: method = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_12405 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = NA, group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_12405[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'method': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_12405[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: method = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_10429 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = NULL, group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_10429[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'method': Must be of type 'string', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_10429[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_aggregation_fn ...
xpectr::set_test_seed(42)
# Assigning output
output_11404 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = sum, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_11404),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_11404[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11404[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11404[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11404[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_11404[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11404[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_11404[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_11404[[".collg"]], n = 30),
structure(c(2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L,
3L, 1L, 1L, 3L, 3L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 3L,
3L, 3L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_11404),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_11404),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_11404),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_11404),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_11404)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_aggregation_fn ...
xpectr::set_test_seed(42)
# Assigning output
output_12163 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = sd, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_12163),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_12163[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_12163[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_12163[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_12163[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_12163[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_12163[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_12163[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_12163[[".collg"]], n = 30),
structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 1L,
1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_12163),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_12163),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_12163),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_12163),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_12163)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_aggregation_fn = 2
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_14793 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = 2, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_14793[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'group_aggregation_fn': Must be a function, not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_14793[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_aggregation_fn ...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_11974 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = NA, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_11974[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'group_aggregation_fn': Must be a function, not 'logical'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_11974[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_aggregation_fn ...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17193 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = NULL, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17193[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'group_aggregation_fn': Must be a function, not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17193[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_new_group_cols = 2
xpectr::set_test_seed(42)
# Assigning output
output_10078 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 2, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_10078),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_10078[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_10078[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_10078[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_10078[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_10078[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_10078[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_10078[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_10078[[".collg_1"]], n = 30),
structure(c(2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 2L,
2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
xpectr::smpl(output_10078[[".collg_2"]], n = 30),
structure(c(2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 2L, 1L, 1L, 1L,
1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_10078),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg_1", ".collg_2"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_10078),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_10078),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_10078),
c(53L, 9L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_10078)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_new_group_cols = ...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13754 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = "two", unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_13754[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'num_new_group_cols': Must be of type 'number', not 'character'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13754[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_new_group_cols = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_10015 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = NA, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_10015[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'num_new_group_cols': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_10015[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_new_group_cols = ...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_15816 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = NULL, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_15816[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'num_new_group_cols': Must be of type 'number', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_15816[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: unique_new_group_cols...
xpectr::set_test_seed(42)
# Assigning output
output_11579 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = FALSE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_11579),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_11579[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11579[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11579[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11579[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_11579[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11579[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_11579[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_11579[[".collg"]], n = 30),
structure(c(2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 2L,
2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_11579),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_11579),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_11579),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_11579),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_11579)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: unique_new_group_cols...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13590 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = 1, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_13590[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'unique_fold_cols_only': Must be of type 'logical flag', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13590[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: unique_new_group_cols...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16456 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = NA, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16456[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'unique_fold_cols_only': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16456[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: unique_new_group_cols...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17758 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = NULL, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17758[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'unique_fold_cols_only': Must be of type 'logical flag', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17758[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: max_iters = 0
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_15636 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 0, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_15636[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'max_iters': Must be >= 1."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_15636[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: max_iters = "sdf"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_12337 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = "sdf", extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_12337[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'max_iters': Must be of type 'count', not 'character'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_12337[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: max_iters = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_10899 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = NA, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_10899[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'max_iters': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_10899[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: max_iters = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_10856 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = NULL, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_10856[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'max_iters': Must be of type 'count', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_10856[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: extreme_pairing_level...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13052 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 2, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_13052[['error']]),
xpectr::strip("`num_col`: The (subset of) data is too small to perform 2 levels of extreme pairing. Decrease `extreme_pairing_levels`."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13052[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: extreme_pairing_level...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16674 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 0, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16674[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'extreme_pairing_levels': Must be >= 1."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16674[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: extreme_pairing_level...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_10002 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = "str", combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_10002[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'extreme_pairing_levels': Must be of type 'count', not 'character'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_10002[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: extreme_pairing_level...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_12085 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = NA, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_12085[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'extreme_pairing_levels': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_12085[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: extreme_pairing_level...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19330 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = NULL, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19330[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'extreme_pairing_levels': Must be of type 'count', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19330[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: combine_method = "avg...
xpectr::set_test_seed(42)
# Assigning output
output_19256 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_min_max_scaled", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_19256),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_19256[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19256[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19256[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19256[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_19256[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19256[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_19256[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_19256[[".collg"]], n = 30),
structure(c(2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 2L,
2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_19256),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19256),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19256),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19256),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19256)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: combine_method = "nope"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17340 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "nope", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_match(
xpectr::strip(side_effects_17340[['error']], lowercase = TRUE),
xpectr::strip(
ifelse(
is_checkmate_v2_1(),
"must be a subset of {'avg_standardized','avg_min_max_scaled'}",
"must be a subset of set {'avg_standardized','avg_min_max_scaled'}"
), lowercase = TRUE),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17340[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: combine_method = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13330 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = 1, col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_13330[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'combine_method': Must be of type 'string', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13330[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: combine_method = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_15150 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = NA, col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_15150[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'combine_method': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_15150[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: combine_method = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17439 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = NULL, col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17439[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'combine_method': Must be of type 'string', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17439[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: col_name = ".some_name."
xpectr::set_test_seed(42)
# Assigning output
output_16191 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".some_name.", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_16191),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_16191[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_16191[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_16191[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_16191[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_16191[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_16191[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_16191[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_16191[[".some_name."]], n = 30),
structure(c(2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 2L,
2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_16191),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".some_name."),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_16191),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_16191),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_16191),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_16191)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: col_name = ".folds"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16262 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".folds", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16262[['error']]),
xpectr::strip("1 assertions failed:\n * `col_name` is already a column in `data`."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16262[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: col_name = "answer"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_12171 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = "answer", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_12171[['error']]),
xpectr::strip("1 assertions failed:\n * `col_name` is already a column in `data`."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_12171[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: col_name = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_12165 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = 1, parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_12165[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'col_name': Must be of type 'string', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_12165[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: col_name = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13889 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = NA, parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_13889[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'col_name': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13889[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: col_name = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19424 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = NULL, parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19424[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'col_name': Must be of type 'string', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19424[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: parallel = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19626 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = 1, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19626[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'parallel': Must be of type 'logical flag', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19626[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: parallel = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17398 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = NA, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17398[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'parallel': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17398[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: parallel = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17332 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = NULL, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17332[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'parallel': Must be of type 'logical flag', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17332[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: verbose = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_15357 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = 1), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_15357[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'verbose': Must be of type 'logical flag', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_15357[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: verbose = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_10022 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = NA), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_10022[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'verbose': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_10022[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: verbose = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16089 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = NULL), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16089[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'verbose': Must be of type 'logical flag', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16089[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
## Finished testing 'collapse_groups' ####
#
})
LudvigOlsen/R-splitters documentation built on March 7, 2024, 6:59 p.m.
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library(groupdata2)
context("collapse_groups()")
test_that("testing summaries of method ascending-descending", {
# Set seed
xpectr::set_test_seed(42)
# Create data frame
df <- data.frame(
"participant" = factor(rep(1:20, 3)),
"participant_2" = factor(rep(1:20, 3)),
"age" = rep(sample(c(1:100), 20), 3),
"answer" = factor(sample(c("a", "b", "c", "d"), 60, replace = TRUE)),
"score" = sample(c(1:100), 20 * 3)
)
df <- df %>% dplyr::arrange(participant)
df$session <- rep(c("1", "2", "3"), 20)
# Sample rows to get unequal sizes per participant
df <- dplyr::sample_n(df, size = 53)
# Create the initial groups (to be collapsed)
df <- fold(
data = df,
k = 8,
method = "n_dist",
id_col = "participant"
)
# Ungroup the data frame
# Otherwise `collapse_groups()` would be
# applied to each fold separately!
df <- dplyr::ungroup(df)
# Method ascending
# With size balancing
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
cat_cols = "answer",
num_cols = "score",
id_cols = "participant",
balance_size = TRUE,
method = "ascending",
)
## Testing 'df_coll$.coll_groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing is factor
expect_true(
is.factor(df_coll$.coll_groups))
# Testing values
expect_equal(
xpectr::smpl(as.character(df_coll$.coll_groups), n = 30),
c("3", "3", "2", "2", "2", "2", "2", "2", "3", "3", "3", "3", "1",
"1", "3", "3", "3", "3", "1", "1", "1", "3", "3", "2", "2",
"2", "2", "1", "1", "1"),
fixed = TRUE)
## Finished testing 'df_coll$.coll_groups' ####
summ <- summarize_balances(df_coll,
group_cols = ".coll_groups",
cat_cols = "answer",
num_cols = "score",
id_cols = "participant")
# Check most of the group summaries are ascending in order
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(11, 17, 25),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# participant"]],
c(4, 7, 9),
tolerance = 1e-4)
expect_equal(
summ$Groups[["mean(score)"]],
c(32, 54.41176, 50.84),
tolerance = 1e-4)
expect_equal(
summ$Groups[["sum(score)"]],
c(352, 925, 1271),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_a"]],
c(1, 5, 8),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_b"]],
c(3, 4, 6),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_c"]],
c(3, 4, 5),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_d"]],
c(4, 4, 6),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "# participant", "mean(score)",
"sum(score)", "# answ_a", "# answ_b", "# answ_c", "# answ_d"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "integer", "numeric", "integer",
"numeric", "numeric", "numeric", "numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "integer", "double", "integer",
"double", "double", "double", "double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 10L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
# Without size balancing
xpectr::set_test_seed(42)
df_coll_2 <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
cat_cols = "answer",
num_cols = "score",
id_cols = "participant",
balance_size = FALSE,
method = "ascending",
)
# Gets the same split
expect_equal(
df_coll$.coll_groups,
df_coll_2$.coll_groups
)
# Method descending
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
cat_cols = "answer",
num_cols = "score",
id_cols = "participant",
balance_size = TRUE,
method = "descending",
)
## Testing 'df_coll$.coll_groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing is factor
expect_true(
is.factor(df_coll$.coll_groups))
# Testing values
expect_equal(
xpectr::smpl(as.character(df_coll$.coll_groups), n = 30),
c("1", "1", "2", "2", "2", "2", "2", "2", "1", "1", "1", "1", "3",
"3", "1", "1", "1", "1", "3", "3", "3", "1", "1", "2", "2",
"2", "2", "3", "3", "3"),
fixed = TRUE)
## Finished testing 'df_coll$.coll_groups' ####
summ <- summarize_balances(df_coll,
group_cols = ".coll_groups",
cat_cols = "answer",
num_cols = "score",
id_cols = "participant")
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(25, 17, 11),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# participant"]],
c(9, 7, 4),
tolerance = 1e-4)
expect_equal(
summ$Groups[["mean(score)"]],
c(50.84, 54.41176, 32),
tolerance = 1e-4)
expect_equal(
summ$Groups[["sum(score)"]],
c(1271, 925, 352),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_a"]],
c(8, 5, 1),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_b"]],
c(6, 4, 3),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_c"]],
c(5, 4, 3),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_d"]],
c(6, 4, 4),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "# participant", "mean(score)",
"sum(score)", "# answ_a", "# answ_b", "# answ_c", "# answ_d"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "integer", "numeric", "integer",
"numeric", "numeric", "numeric", "numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "integer", "double", "integer",
"double", "double", "double", "double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 10L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
})
test_that("testing summaries of cat_levels", {
# Set seed
xpectr::set_test_seed(42)
# Create data frame
df <- data.frame(
"participant" = factor(rep(1:20, 3)),
"participant_2" = factor(rep(1:20, 3)),
"age" = rep(sample(c(1:100), 20), 3),
"answer" = factor(sample(c("a", "b", "c", "d"), 60, replace = TRUE)),
"score" = sample(c(1:100), 20 * 3)
)
df <- df %>% dplyr::arrange(participant)
df$session <- rep(c("1", "2", "3"), 20)
# Sample rows to get unequal sizes per participant
df <- dplyr::sample_n(df, size = 53)
# Create the initial groups (to be collapsed)
df <- fold(
data = df,
k = 8,
method = "n_dist",
id_col = "participant"
)
# Ungroup the data frame
# Otherwise `collapse_groups()` would be
# applied to each fold separately!
df <- dplyr::ungroup(df)
# We use method ascending as its
# pattern is likely easier to spot than balance
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
cat_cols = "answer",
cat_levels = ".minority",
method = "ascending",
balance_size = FALSE
)
## Testing 'df_coll$.coll_groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing is factor
expect_true(
is.factor(df_coll$.coll_groups))
# Testing values
expect_equal(
xpectr::smpl(as.character(df_coll$.coll_groups), n = 30),
c("3", "3", "1", "1", "1", "2", "2", "2", "3", "3", "1", "1", "2",
"2", "2", "2", "1", "1", "3", "3", "3", "2", "2", "3", "3",
"3", "3", "2", "2", "2"),
fixed = TRUE)
## Finished testing 'df_coll$.coll_groups' ####
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups",
cat_cols = "answer"
)
# Only the minor cat_level ("c") is in ascending order!
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(15, 20, 18),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_a"]],
c(5, 5, 4),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_b"]],
c(6, 5, 2),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_c"]],
c(0, 5, 7),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_d"]],
c(4, 5, 5),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "# answ_a", "# answ_b", "# answ_c",
"# answ_d"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "numeric", "numeric", "numeric",
"numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "double", "double", "double",
"double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 7L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
# Set minority level manually
xpectr::set_test_seed(42)
df_coll_2 <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
cat_cols = "answer",
cat_levels = "c", # c is the minority class
method = "ascending",
balance_size = FALSE
)
expect_equal(
df_coll$.coll_groups,
df_coll_2$.coll_groups
)
# .majority
# We method balance as all classes were kind
# of ascending with the "ascending"
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
cat_cols = "answer",
cat_levels = ".majority",
method = "balance",
balance_size = FALSE
)
## Testing 'df_coll$.coll_groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing is factor
expect_true(
is.factor(df_coll$.coll_groups))
# Testing values
expect_equal(
xpectr::smpl(as.character(df_coll$.coll_groups), n = 30),
c("1", "1", "2", "2", "2", "1", "1", "1", "1", "1", "3", "3", "3",
"3", "2", "2", "3", "3", "3", "3", "3", "2", "2", "1", "1",
"1", "1", "3", "3", "3"),
fixed = TRUE)
## Finished testing 'df_coll$.coll_groups' ####
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups",
cat_cols = "answer"
)
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(19, 14, 20),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_a"]],
c(6, 4, 4),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_b"]],
c(2, 5, 6),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_c"]],
c(7, 2, 3),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_d"]],
c(4, 3, 7),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "# answ_a", "# answ_b", "# answ_c",
"# answ_d"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "numeric", "numeric", "numeric",
"numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "double", "double", "double",
"double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 7L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
# Set specific level
xpectr::set_test_seed(42)
df_coll_2 <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
cat_cols = "answer",
cat_levels = "a", # a is the first majority class
method = "balance",
balance_size = FALSE
)
expect_equal(
df_coll$.coll_groups,
df_coll_2$.coll_groups
)
# Weighted cat levels
# We should see the "b" level be pretty balanced
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
cat_cols = "answer",
cat_levels = c("a" = 2, "b" = 1000, "c"=1),
method = "balance",
balance_size = FALSE
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups",
cat_cols = "answer"
)
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(11, 22, 20),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_a"]],
c(2, 6, 6),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_b"]],
c(4, 5, 4), # Fairly balanced yes!
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_c"]],
c(2, 6, 4),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_d"]],
c(3, 5, 6),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "# answ_a", "# answ_b", "# answ_c",
"# answ_d"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "numeric", "numeric", "numeric",
"numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "double", "double", "double",
"double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 7L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
# List of weights per cat col with multiple cat cols
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df %>% dplyr::mutate(session = factor(.data$session)),
n = 3,
group_cols = ".folds",
cat_cols = c("answer", "session"),
cat_levels = list("answer" = c("a" = 2, "b" = 1000, "c" = 1),
"session" = c("1" = 1, "2" = 1000)),
method = "ascending",
balance_size = FALSE
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups",
cat_cols = c("answer","session")
)
# Note: We can't expect to see clear signs of them working
# as they may cancel out, etc.
# But both "b" and "2" are ascending, so that's something!
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(10, 18, 25),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_a"]],
c(1, 5, 8),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_b"]],
c(1, 6, 6),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_c"]],
c(4, 3, 5),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# answ_d"]],
c(4, 4, 6),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# sess_1"]],
c(3, 6, 8),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# sess_2"]],
c(4, 6, 9),
tolerance = 1e-4)
expect_equal(
summ$Groups[["# sess_3"]],
c(3, 6, 8),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "# answ_a", "# answ_b", "# answ_c",
"# answ_d", "# sess_1", "# sess_2", "# sess_3"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "numeric", "numeric", "numeric",
"numeric", "numeric", "numeric", "numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "double", "double", "double",
"double", "double", "double", "double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 10L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
})
test_that("testing summaries of balance_size options", {
# Set seed
xpectr::set_test_seed(42)
# Create data frame
df <- data.frame(
"participant" = factor(rep(1:20, 3)),
"answer" = factor(sample(c("a", "b", "c", "d"), 60, replace = TRUE))
)
df <- df %>% dplyr::arrange(participant)
# Sample rows to get unequal sizes per participant
df <- dplyr::sample_n(df, size = 53)
# Create the initial groups (to be collapsed)
df <- fold(
data = df,
k = 8,
method = "n_dist",
id_col = "participant"
)
# Ungroup the data frame
# Otherwise `collapse_groups()` would be
# applied to each fold separately!
df <- dplyr::ungroup(df)
# No size balancing
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "balance",
balance_size = FALSE
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups"
)
expect_equal(summ$Groups$`# rows`,
c(17L, 23L, 13L))
# ascending
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "ascending",
balance_size = FALSE
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups"
)
expect_equal(summ$Groups$`# rows`,
c(11, 22, 20))
# WITH size balancing
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "balance",
balance_size = TRUE
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups"
)
# Different for the same seed
expect_equal(summ$Groups$`# rows`,
c(14L, 21L, 18L))
# ascending
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "ascending",
balance_size = TRUE
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups"
)
expect_equal(summ$Groups$`# rows`,
c(9, 18, 26))
})
test_that("testing summaries of different group_aggregation_fn", {
# Set seed
xpectr::set_test_seed(42)
# Create data frame
df <- data.frame(
"participant" = factor(rep(1:20, 3)),
"age" = rep(sample(c(1:100), 20), 3),
"score" = sample(c(1:100), 20 * 3)
)
df <- df %>% dplyr::arrange(participant)
# Sample rows to get unequal sizes per participant
df <- dplyr::sample_n(df, size = 53)
# Create the initial groups (to be collapsed)
df <- fold(
data = df,
k = 8,
method = "n_dist",
id_col = "participant"
)
# Ungroup the data frame
# Otherwise `collapse_groups()` would be
# applied to each fold separately!
df <- dplyr::ungroup(df)
# group_aggregation_fn: mean (default)
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "balance",
balance_size = FALSE,
num_cols = "score",
group_aggregation_fn = mean
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups",
num_cols = "score"
)
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(22, 16, 15),
tolerance = 1e-4)
expect_equal(
summ$Groups[["mean(score)"]],
c(50.54545, 52.5625, 57.53333),
tolerance = 1e-4)
expect_equal(
summ$Groups[["sum(score)"]],
c(1112, 841, 863),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "mean(score)", "sum(score)"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 5L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
# Relevant in comparison to later test
spread_summ <- df_coll %>%
dplyr::group_by(.data$.coll_groups) %>%
dplyr::summarise(SD = sd(.data$score),
iqr = IQR(.data$score))
## Testing 'spread_summ' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(spread_summ),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
spread_summ[[".coll_groups"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
spread_summ[["SD"]],
c(25.7196, 31.09977, 31.36619),
tolerance = 1e-4)
expect_equal(
spread_summ[["iqr"]],
c(36.75, 54.75, 47),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(spread_summ),
c(".coll_groups", "SD", "iqr"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(spread_summ),
c("factor", "numeric", "numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(spread_summ),
c("integer", "double", "double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(spread_summ),
c(3L, 3L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(spread_summ)),
character(0),
fixed = TRUE)
## Finished testing 'spread_summ' ####
# group_aggregation_fn: sum
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "balance",
balance_size = FALSE,
num_cols = "score",
group_aggregation_fn = sum
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups",
num_cols = "score"
)
# Different but not actually better balanced sums
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(14, 21, 18),
tolerance = 1e-4)
expect_equal(
summ$Groups[["mean(score)"]],
c(53.92857, 44.66667, 62.38889),
tolerance = 1e-4)
expect_equal(
summ$Groups[["sum(score)"]],
c(755, 938, 1123),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "mean(score)", "sum(score)"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 5L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
# group_aggregation_fn: IQR
# NOTE: The mean values might actually play a larger
# role than the IQRs/SDs in the IQR/SD of the
# collapsed groups, so this cannot guarantee
# balanced IQRs/SDs
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "balance",
balance_size = FALSE,
num_cols = "score",
group_aggregation_fn = IQR
)
summ <- df_coll %>%
dplyr::group_by(.data$.coll_groups) %>%
dplyr::summarise(SD = sd(.data$score),
iqr = IQR(.data$score))
# The IQRs and SDs are less balanced
# than when using mean()
# But they are different for sure
## Testing 'summ' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ[[".coll_groups"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ[["SD"]],
c(29.23815, 35.09606, 23.74006),
tolerance = 1e-4)
expect_equal(
summ[["iqr"]],
c(45, 58.25, 41),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ),
c(".coll_groups", "SD", "iqr"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ),
c("factor", "numeric", "numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ),
c("integer", "double", "double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ),
c(3L, 3L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ)),
character(0),
fixed = TRUE)
## Finished testing 'summ' ####
# Method ascending
# Mean (default)
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "ascending",
balance_size = FALSE,
num_cols = "score",
group_aggregation_fn = mean
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups",
num_cols = "score"
)
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(12, 19, 22),
tolerance = 1e-4)
expect_equal(
summ$Groups[["mean(score)"]],
c(38.33333, 45.57895, 67.72727),
tolerance = 1e-4)
expect_equal(
summ$Groups[["sum(score)"]],
c(460, 866, 1490),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "mean(score)", "sum(score)"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 5L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
# Sum
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "ascending",
balance_size = FALSE,
num_cols = "score",
group_aggregation_fn = sum
)
summ <- summarize_balances(
data = df_coll,
group_cols = ".coll_groups",
num_cols = "score"
)
## Testing 'summ$Groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ$Groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ$Groups[[".group_col"]],
structure(c(1L, 1L, 1L), .Label = ".coll_groups", class = "factor"))
expect_equal(
summ$Groups[[".group"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ$Groups[["# rows"]],
c(10, 21, 22),
tolerance = 1e-4)
expect_equal(
summ$Groups[["mean(score)"]],
c(38.8, 44.66667, 67.72727),
tolerance = 1e-4)
expect_equal(
summ$Groups[["sum(score)"]],
c(388, 938, 1490),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ$Groups),
c(".group_col", ".group", "# rows", "mean(score)", "sum(score)"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ$Groups),
c("factor", "factor", "integer", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ$Groups),
c("integer", "integer", "integer", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ$Groups),
c(3L, 5L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ$Groups)),
character(0),
fixed = TRUE)
## Finished testing 'summ$Groups' ####
# IQR
xpectr::set_test_seed(42)
df_coll <- collapse_groups(
data = df,
n = 3,
group_cols = ".folds",
method = "ascending",
balance_size = FALSE,
num_cols = "score",
group_aggregation_fn = IQR
)
summ <- df_coll %>%
dplyr::group_by(.data$.coll_groups) %>%
dplyr::summarise(SD = sd(.data$score),
iqr = IQR(.data$score))
## Testing 'summ' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ[[".coll_groups"]],
structure(1:3, .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
summ[["SD"]],
c(27.69586, 28.89417, 27.40917),
tolerance = 1e-4)
expect_equal(
summ[["iqr"]],
c(40.25, 45, 49.75), # Ascending ftw!
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ),
c(".coll_groups", "SD", "iqr"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ),
c("factor", "numeric", "numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ),
c("integer", "double", "double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ),
c(3L, 3L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ)),
character(0),
fixed = TRUE)
## Finished testing 'summ' ####
})
test_that("testing calculate_summary_collapse_groups_()", {
# Set seed
xpectr::set_test_seed(42)
# Create data frame
df <- data.frame(
"participant" = factor(rep(1:20, 3)),
"age" = rep(sample(c(1:100), 20), 3),
"diagnosis" = factor(rep(sample(c(1:3), 20, replace = TRUE), 3)),
"score" = sample(c(1:100), 20 * 3)
)
df <- df %>% dplyr::arrange(participant)
# Sample rows to get unequal sizes per participant
df <- dplyr::sample_n(df, size = 53)
# Create the initial groups (to be collapsed)
df <- fold(
data = df,
k = 8,
method = "n_dist",
id_col = "participant"
)
# Ungroup the data frame
# Otherwise `collapse_groups()` would be
# applied to each fold separately!
df <- dplyr::ungroup(df)
prepped <- prepare_collapse_groups_run_(
data = df,
group_cols = ".folds",
cat_cols = "diagnosis",
num_cols = c("age", "score"),
id_cols = "participant",
weights = NULL,
balance_size = TRUE
)
# Created expected summary
expected_summ <- prepped[["data"]] %>%
dplyr::group_by(.data$.____.folds) %>%
dplyr::summarise(
age = sum(age),
score = sum(score),
size = n(),
participant = length(unique(participant))
)
cat_summ <- prepped[["data"]] %>%
dplyr::group_by(.data$.____.folds) %>%
dplyr::count(diagnosis) %>%
tidyr::spread(key = "diagnosis", value = "n", fill = 0) %>%
dplyr::ungroup() %>%
dplyr::mutate(dplyr::across(where(is.numeric), .fns = ~ {
(.x - mean(.x)) / sd(.x)
}),
diagnosis = (`1` + `2` + `3`) / 3,
majority = `3`)
expected_summ$diagnosis <- cat_summ$diagnosis
expected_summ$majority <- cat_summ$majority
summ <- calculate_summary_collapse_groups_(
data = prepped[["data"]],
tmp_old_group_var = prepped[["group_cols"]],
cat_cols = prepped[["cat_cols"]],
cat_levels = NULL,
num_cols = prepped[["num_cols"]],
group_aggregation_fn = sum,
balance_size = TRUE,
id_cols = prepped[["id_cols"]]
)
summ_ordered <- dplyr::arrange(summ, .____.folds)
# Check that we get the same as the manual calculations
expect_equal(sort(colnames(summ_ordered)),
sort(colnames(expected_summ)[-7])) # Remove "majority" - it's for later
expect_equal(summ_ordered$.____.folds, expected_summ$.____.folds)
expect_equal(summ_ordered$diagnosis, expected_summ$diagnosis)
expect_equal(summ_ordered$age, expected_summ$age)
expect_equal(summ_ordered$score, expected_summ$score)
expect_equal(summ_ordered$size, expected_summ$size)
expect_equal(summ_ordered$participant, expected_summ$participant)
## Testing 'summ' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(summ),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
summ[[".____.folds"]],
structure(c(3L, 8L, 5L, 4L, 2L, 1L, 6L, 7L), .Label = c("1", "2",
"3", "4", "5", "6", "7", "8"), class = "factor"))
expect_equal(
summ[["diagnosis"]],
c(-0.41471, 0.30371, -0.41471, 0.24455, 0.08321, 0.13948, 0.26193,
-0.20346),
tolerance = 1e-4)
expect_equal(
summ[["age"]],
c(369, 667, 166, 528, 396, 213, 405, 237),
tolerance = 1e-4)
expect_equal(
summ[["score"]],
c(172, 416, 194, 398, 443, 255, 428, 407),
tolerance = 1e-4)
expect_equal(
summ[["size"]],
c(4, 8, 4, 9, 9, 6, 7, 6),
tolerance = 1e-4)
expect_equal(
summ[["participant"]],
c(2, 3, 2, 3, 3, 2, 3, 2),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(summ),
c(".____.folds", "diagnosis", "age", "score", "size", "participant"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(summ),
c("factor", "numeric", "integer", "integer", "integer", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(summ),
c("integer", "double", "integer", "integer", "integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(summ),
c(8L, 6L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(summ)),
character(0),
fixed = TRUE)
## Finished testing 'summ' ####
# With majority cat_level only
summ <- calculate_summary_collapse_groups_(
data = prepped[["data"]],
tmp_old_group_var = prepped[["group_cols"]],
cat_cols = prepped[["cat_cols"]],
cat_levels = ".majority",
num_cols = prepped[["num_cols"]],
group_aggregation_fn = sum,
balance_size = TRUE,
id_cols = prepped[["id_cols"]]
)
summ_ordered <- dplyr::arrange(summ, .____.folds)
expect_equal(summ_ordered$diagnosis, expected_summ$majority)
# Edge cases
# diagnosis leads to zero-variance vector
# Create data frame
df <- data.frame(
"participant" = factor(rep(1, 10)),
"age" = c(-5, 5, -5, 5, -5, 5, -5, 5, -5, 5),
"diagnosis" = factor(c(1,1,2,2,1,1,2,2,1,1)),
".__.folds" = factor(c(1, 1, 2, 2, 3, 3, 4, 4, 5, 5))
)
## Testing 'summ <- calculate_summary_collapse_groups_( data = df, tmp_o...' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19148 <- xpectr::capture_side_effects(summ <- calculate_summary_collapse_groups_(
data = df,
tmp_old_group_var = ".__.folds",
cat_cols = "diagnosis",
cat_levels = NULL,
num_cols = "age",
group_aggregation_fn = sum,
balance_size = FALSE,
id_cols = "participant"
), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['warnings']]),
xpectr::strip("Combining the standardized level counts for the `cat_cols` column 'diagnosis' led to a zero-variance vector. Consider not balancing this column or change the included `cat_levels`."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['messages']]),
xpectr::strip(character(0)),
fixed = TRUE)
# Assigning output
output_19148 <- xpectr::suppress_mw(summ <- calculate_summary_collapse_groups_(
data = df,
tmp_old_group_var = ".__.folds",
cat_cols = "diagnosis",
cat_levels = NULL,
num_cols = "age",
group_aggregation_fn = sum,
balance_size = FALSE,
id_cols = "participant"
))
# Testing class
expect_equal(
class(output_19148),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
output_19148[[".__.folds"]],
factor(c(1, 2, 3, 4, 5)),
tolerance = 1e-4)
expect_equal(
output_19148[["diagnosis"]],
c(0, 0, 0, 0, 0),
tolerance = 1e-4)
expect_equal(
output_19148[["age"]],
c(0, 0, 0, 0, 0),
tolerance = 1e-4)
expect_equal(
output_19148[["participant"]],
c(1, 1, 1, 1, 1),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(output_19148),
c(".__.folds", "diagnosis", "age", "participant"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19148),
c("factor", "numeric", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19148),
c("integer", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19148),
5:4)
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19148)),
character(0),
fixed = TRUE)
## Finished testing 'summ <- calculate_summary_collapse_groups_( data = df, tmp_o...' ####
})
test_that("testing scale_and_combine_()", {
xpectr::set_test_seed(42)
df = data.frame(
"a" = c(1,2,3,4,5,6),
"b" = c(1,2,3,4,5,6) * -1,
"c" = c(1,2,3,4,5,6) * 10
)
w <- c("b"=2, "c"=1, "a"=5)
# Expected
w_norm <- w / sum(w)
df_scaled <- df %>%
dplyr::mutate(
a = standardize_(a) * w_norm[["a"]],
b = standardize_(b) * w_norm[["b"]],
c = standardize_(c) * w_norm[["c"]],
new = a + b + c
)
# Observed
combined <- scale_and_combine_(
data = df,
weights = w,
include_cols = c("a", "b", "c"),
scale_fn=standardize_,
col_name="new")$new
expect_equal(df_scaled$new, combined)
# Names in weights must match
## Testing 'scale_and_combine_( data = df, weights = c("...' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19148 <- xpectr::capture_side_effects(scale_and_combine_(
data = df,
weights = c("b"=2, "c"=1, "d"=5),
include_cols = c("a", "b", "c"),
scale_fn=standardize_,
col_name="new"), reset_seed = TRUE)
expect_match(
xpectr::strip(side_effects_19148[['error']], lowercase = TRUE),
xpectr::strip("must be a permutation of set {'a','b','c'}", lowercase = TRUE),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
## Finished testing 'scale_and_combine_( data = df, weights = c("...' ####
# Include cols
## Testing 'scale_and_combine_( data = df, weights = w, ...' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19148 <- xpectr::capture_side_effects(scale_and_combine_(
data = df,
weights = w,
include_cols = c("a", "b", "d"),
scale_fn=standardize_,
col_name="new"), reset_seed = TRUE)
expect_match(
xpectr::strip(side_effects_19148[['error']], lowercase = TRUE),
xpectr::strip("must include the elements {'a','b','d'}.", lowercase = TRUE),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
## Finished testing 'scale_and_combine_( data = df, weights = w, ...' ####
})
test_that("testing add_new_groups_()", {
# Set seed
xpectr::set_test_seed(42)
# Create data frame
df <- data.frame(
"participant" = factor(rep(1:20, 3)),
"age" = rep(sample(c(1:100), 20), 3),
"diagnosis" = factor(rep(sample(c(1:3), 20, replace = TRUE), 3)),
"score" = sample(c(1:100), 20 * 3)
)
df <- df %>% dplyr::arrange(participant)
# Sample rows to get unequal sizes per participant
df <- dplyr::sample_n(df, size = 53)
# Create the initial groups (to be collapsed)
df <- fold(
data = df,
k = 8,
method = "n_dist",
id_col = "participant"
)
# Ungroup the data frame
# Otherwise `collapse_groups()` would be
# applied to each fold separately!
df <- dplyr::ungroup(df)
# One row per fold / input group
xpectr::set_test_seed(42)
new_groups = data.frame(
".folds" = factor(sample(1:8, 8)),
"combined" = runif(8),
".coll_g" = factor(sample(c(1:4, 1:4), 8))
) %>%
dplyr::group_by(.data$.coll_g)
# Add .coll_g to df
df_added_groups <- add_new_groups_(
data = df,
new_groups = new_groups,
tmp_old_group_var = ".folds",
col_name = ".coll_g"
)
expect_equal(
colnames(df_added_groups),
c("participant", "age", "diagnosis", "score", ".coll_g")
)
## Testing 'df_added_groups' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(df_added_groups),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(df_added_groups[["participant"]], n = 30),
structure(c(1L, 10L, 11L, 12L, 13L, 14L, 14L, 16L, 16L, 16L, 17L,
18L, 19L, 19L, 2L, 20L, 3L, 3L, 3L, 4L, 5L, 5L, 6L, 6L, 7L,
8L, 8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6",
"7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17",
"18", "19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(df_added_groups[["age"]], n = 30),
c(92, 65, 42, 91, 83, 23, 23, 80, 80, 80, 88, 10, 39, 39, 93, 46,
29, 29, 29, 81, 62, 62, 50, 50, 70, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(df_added_groups[["diagnosis"]], n = 30),
structure(c(3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 3L,
3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
xpectr::smpl(df_added_groups[["score"]], n = 30),
c(35, 18, 86, 73, 75, 56, 33, 47, 72, 64, 68, 24, 80, 32, 44, 85,
4, 93, 74, 37, 42, 65, 91, 62, 21, 60, 5, 90, 50, 53),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(df_added_groups[[".coll_g"]], n = 30),
structure(c(4L, 4L, 2L, 4L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 1L, 3L,
3L, 4L, 3L, 1L, 1L, 1L, 3L, 3L, 3L, 1L, 1L, 2L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4"), class = "factor"))
# Testing column names
expect_equal(
names(df_added_groups),
c("participant", "age", "diagnosis", "score", ".coll_g"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(df_added_groups),
c("factor", "integer", "factor", "integer", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(df_added_groups),
c("integer", "integer", "integer", "integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(df_added_groups),
c(53L, 5L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(df_added_groups)),
character(0),
fixed = TRUE)
## Finished testing 'df_added_groups' ####
## Testing 'add_new_groups_( data = df, new_groups = new...' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19148 <- xpectr::capture_side_effects(add_new_groups_(
data = df,
new_groups = new_groups,
tmp_old_group_var = ".folds",
col_name = ".folds"
), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['error']]),
xpectr::strip("`tmp_old_group_var` and `col_name` were identical."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
## Finished testing 'add_new_groups_( data = df, new_groups = new...' ####
## Testing 'add_new_groups_( data = df %>% dplyr::mutate...' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19148 <- xpectr::capture_side_effects(add_new_groups_(
data = df %>%
dplyr::mutate(.folds = as.numeric(.folds)),
new_groups = new_groups,
tmp_old_group_var = ".folds",
col_name = ".coll_g"
), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['error']]),
xpectr::strip("Assertion on 'data[[tmp_old_group_var]]' failed: Must be of type 'factor', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
## Finished testing 'add_new_groups_( data = df %>% dplyr::mutate...' ####
## Testing 'add_new_groups_( data = df, new_groups = new...' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19148 <- xpectr::capture_side_effects(add_new_groups_(
data = df,
new_groups = new_groups %>%
dplyr::mutate(.folds = as.numeric(.folds)),
tmp_old_group_var = ".folds",
col_name = ".coll_g"
), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['error']]),
xpectr::strip("Assertion on 'new_groups[[tmp_old_group_var]]' failed: Must be of type 'factor', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19148[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
## Finished testing 'add_new_groups_( data = df, new_groups = new...' ####
})
test_that("testing add_ordered_summary_groups_()", {
# Set seed
xpectr::set_test_seed(42)
# Create data frame
df <- data.frame(
"participant" = factor(rep(1:20, 3)),
"age" = rep(sample(c(1:100), 20), 3),
"diagnosis" = factor(rep(sample(c(1:3), 20, replace = TRUE), 3)),
"score" = sample(c(1:100), 20 * 3)
)
df <- df %>% dplyr::arrange(participant)
# Sample rows to get unequal sizes per participant
df <- dplyr::sample_n(df, size = 53)
# Create the initial groups (to be collapsed)
df <- fold(
data = df,
k = 8,
method = "n_dist",
id_col = "participant"
)
# Ungroup the data frame
# Otherwise `collapse_groups()` would be
# applied to each fold separately!
df <- dplyr::ungroup(df)
# One row per fold / input group
xpectr::set_test_seed(42)
summary <- data.frame(
".folds" = factor(sample(1:8, 8)),
"combined" = runif(8)
)
# DESCENDING
expected_grouping <- summary %>%
dplyr::arrange(dplyr::desc(.data$combined)) %>%
dplyr::mutate(.coll_g = factor(rep(1:4, each=2))) %>%
dplyr::select(.folds, .coll_g) %>%
dplyr::arrange(.folds)
df_added <- add_ordered_summary_groups_(
data = df,
summary = summary,
n = 4,
group_cols = ".folds",
num_col = "combined",
method = "descending",
col_name = ".coll_g"
)
observed_grouping <- df_added %>%
dplyr::count(.folds, .coll_g) %>%
dplyr::select(-"n") %>%
dplyr::arrange(.folds)
# Check we get the expected results
expect_identical(
as.data.frame(observed_grouping),
as.data.frame(expected_grouping)
)
## Testing 'observed_grouping' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(observed_grouping),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
observed_grouping[[".folds"]],
structure(1:8, .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
observed_grouping[[".coll_g"]],
structure(c(1L, 4L, 1L, 3L, 2L, 4L, 2L, 3L), .Label = c("1", "2",
"3", "4"), class = "factor"))
# Testing column names
expect_equal(
names(observed_grouping),
c(".folds", ".coll_g"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(observed_grouping),
c("factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(observed_grouping),
c("integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(observed_grouping),
c(8L, 2L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(observed_grouping)),
character(0),
fixed = TRUE)
## Finished testing 'observed_grouping' ####
# ASCENDING
expected_grouping <- summary %>%
dplyr::arrange(.data$combined) %>%
dplyr::mutate(.coll_g = factor(rep(1:4, each=2))) %>%
dplyr::select(.folds, .coll_g) %>%
dplyr::arrange(.folds)
df_added <- add_ordered_summary_groups_(
data = df,
summary = summary,
n = 4,
group_cols = ".folds",
num_col = "combined",
method = "ascending",
col_name = ".coll_g"
)
observed_grouping <- df_added %>%
dplyr::count(.folds, .coll_g) %>%
dplyr::select(-"n") %>%
dplyr::arrange(.folds)
# Check we get the expected results
expect_identical(
as.data.frame(observed_grouping),
as.data.frame(expected_grouping)
)
## Testing 'observed_grouping' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Testing class
expect_equal(
class(observed_grouping),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
observed_grouping[[".folds"]],
structure(1:8, .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
observed_grouping[[".coll_g"]],
structure(c(4L, 1L, 4L, 2L, 3L, 1L, 3L, 2L), .Label = c("1", "2",
"3", "4"), class = "factor"))
# Testing column names
expect_equal(
names(observed_grouping),
c(".folds", ".coll_g"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(observed_grouping),
c("factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(observed_grouping),
c("integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(observed_grouping),
c(8L, 2L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(observed_grouping)),
character(0),
fixed = TRUE)
## Finished testing 'observed_grouping' ####
})
test_that("testing replace_forbidden_names_()", {
# Set seed
xpectr::set_test_seed(42)
# Create data frame
df <- data.frame(
"participant" = factor(rep(1:20, 3)),
"age" = rep(sample(c(1:100), 20), 3),
"diagnosis" = factor(rep(sample(c(1:3), 20, replace = TRUE), 3)),
"score" = sample(c(1:100), 20 * 3),
"combined" = runif(60),
"n" = rep(sample(c(1:100), 20), 3),
".folder" = rep(sample(c(1:100), 20), 3)
)
df <- df %>% dplyr::arrange(participant)
# Sample rows to get unequal sizes per participant
df <- dplyr::sample_n(df, size = 23)
# Create the initial groups (to be collapsed)
df <- fold(
data = df,
k = 8,
method = "n_dist",
id_col = "participant"
)
# Ungroup the data frame
# Otherwise `collapse_groups()` would be
# applied to each fold separately!
df <- dplyr::ungroup(df)
replaced <- replace_forbidden_names_(
data = df,
data_group_cols = ".foldings",
group_cols = ".folds",
cat_cols = c("diagnosis", ".folds"),
num_cols = c("n", "score"),
id_cols = c("participant", "combined"),
weights = c("score" = 3, "combined" = 8, ".folds" = 2),
invert = FALSE)
expect_equal(
colnames(replaced$data),
c("participant", "age", "diagnosis", "score", ".____combined",
".____n", ".____.folder", ".____.folds")
)
expect_equal(
dplyr::group_vars(replaced$data),
character(0)
)
expect_equal(
replaced$data_group_cols,
".____.foldings"
)
expect_equal(
replaced$group_cols,
".____.folds"
)
expect_equal(
replaced$cat_cols,
c("diagnosis", ".____.folds")
)
expect_equal(
replaced$num_cols,
c(".____n", "score")
)
expect_equal(
replaced$id_cols,
c("participant", ".____combined")
)
expect_equal(
replaced$weights,
c("score" = 3, ".____combined" = 8, ".____.folds" = 2)
)
# Grouped data
replaced <- replace_forbidden_names_(
data = dplyr::group_by(df, .folds),
data_group_cols = ".foldings",
group_cols = ".folds",
cat_cols = c("diagnosis", ".folds"),
num_cols = c("n", "score"),
id_cols = c("participant", "combined"),
weights = c("score" = 3, "combined" = 8, ".folds" = 2),
invert = FALSE)
expect_equal(
colnames(replaced$data),
c("participant", "age", "diagnosis", "score", ".____combined",
".____n", ".____.folder", ".____.folds")
)
expect_equal(
dplyr::group_vars(replaced$data),
".____.folds"
)
## INVERSE!
inverse_replaced <- replace_forbidden_names_(
data = replaced$data, # Still grouped
data_group_cols = replaced$data_group_cols,
group_cols = replaced$group_cols,
cat_cols = replaced$cat_cols,
num_cols = replaced$num_cols,
id_cols = replaced$id_cols,
weights = replaced$weights,
invert = TRUE)
expect_identical(
as.data.frame(inverse_replaced$data),
as.data.frame(df)
)
expect_equal(
colnames(inverse_replaced$data),
c("participant", "age", "diagnosis", "score", "combined",
"n", ".folder", ".folds")
)
expect_equal(
dplyr::group_vars(inverse_replaced$data),
".folds"
)
expect_equal(
inverse_replaced$data_group_cols,
".foldings"
)
expect_equal(
inverse_replaced$group_cols,
".folds"
)
expect_equal(
inverse_replaced$cat_cols,
c("diagnosis", ".folds")
)
expect_equal(
inverse_replaced$num_cols,
c("n", "score")
)
expect_equal(
inverse_replaced$id_cols,
c("participant", "combined")
)
expect_equal(
inverse_replaced$weights,
c("score" = 3, "combined" = 8, ".folds" = 2)
)
})
test_that("fuzz testing collapse_groups() without auto-tune", {
# Set seed
xpectr::set_test_seed(42)
# Create data frame
df <- data.frame(
"participant" = factor(rep(1:20, 3)),
"participant_2" = factor(rep(1:20, 3)),
"age" = rep(sample(c(1:100), 20), 3),
"answer" = factor(sample(c("a", "b", "c", "d"), 60, replace = TRUE)),
"score" = sample(c(1:100), 20 * 3)
)
df <- df %>% dplyr::arrange(participant)
df$session <- rep(c("1", "2", "3"), 20)
# Sample rows to get unequal sizes per participant
df <- dplyr::sample_n(df, size = 53)
# Create the initial groups (to be collapsed)
df <- fold(
data = df,
k = 8,
method = "n_dist",
id_col = "participant"
)
# Ungroup the data frame
# Otherwise `collapse_groups()` would be
# applied to each fold separately!
df <- dplyr::ungroup(df)
# Generate expectations for 'collapse_groups'
# Tip: comment out the gxs_function() call
# so it is easy to regenerate the tests
# xpectr::set_test_seed(42)
# xpectr::gxs_function(
# fn = collapse_groups,
# args_values = list(
# "data" = list(df, c(1,2,3), 1, NA),
# "n" = list(3, 4, 1, 8, 9, "5", NA),
# "group_cols" = list(".folds", c(".folds", "participant"), "answer", 1, NA),
# "cat_cols" = list("answer", c("answer", "session"), "score", ".folds", 1, NA),
# "cat_levels" = list(NULL, ".majority", ".minority", "nope", c("a" = 2, "b" = 3),
# c("nope" = 2, "b" = 3), list("answer" = c("a" = 2)),
# list("session" = c("a" = 2)), list("sdfs" = c("a" = 2)), NA),
# "num_cols" = list("score", c("score", "age"), "answer", ".folds", 1, NA),
# "id_cols" = list("participant", c("participant_2", "participant"), "score", ".folds", 1, NA),
# "balance_size" = list(TRUE, FALSE, 1, NA),
# "auto_tune" = list(FALSE, 1, NA), # TRUE is tested elsewhere
# "weights" = list(NULL, c("size" = 2, "answer" = 7, "score" = 1, "participant" = 2),
# c("size" = 3, "nope" = 5), c("participant" = 2,"participant_2" = 2),
# list("size" = 2, "answer" = 7), c("size" = NA, "answer" = 7),
# 1, NA),
# "method" = list("balance", "ascending", "descending", "none", list("balance"), 1, NA),
# "group_aggregation_fn" = list(mean, sum, sd, 2, NA),
# "num_new_group_cols" = list(1, 2, "two", NA),
# "unique_new_group_cols_only" = list(TRUE, FALSE, 1, NA),
# "max_iters" = list(2, 0, "sdf", NA),
# "extreme_pairing_levels" = list(1, 2, 0, "str", NA),
# "combine_method" = list("avg_standardized", "avg_min_max_scaled", "nope", 1, NA),
# "col_name" = list(".collg", ".some_name.", ".folds", "answer", 1, NA),
# "parallel" = list(FALSE, 1, NA),
# "verbose" = list(FALSE, 1, NA)
# ),
# extra_combinations = list(
# list("cat_cols" = NULL, "num_cols" = NULL, "id_cols" = NULL, "balance_size" = FALSE),
# list("cat_cols" = "answer", "num_cols" = NULL, "id_cols" = NULL, "balance_size" = FALSE),
# list("cat_cols" = NULL, "num_cols" = "score", "id_cols" = NULL, "balance_size" = FALSE),
# list("cat_cols" = NULL, "num_cols" = NULL, "id_cols" = "participant", "balance_size" = FALSE),
# list("cat_cols" = NULL, "num_cols" = NULL, "id_cols" = NULL, "balance_size" = TRUE),
# list("auto_tune" = TRUE, "method" = "ascending")
# ),
# indentation = 2,
# copy_env = FALSE
# )
## Testing 'collapse_groups' ####
## Initially generated by xpectr
# Testing different combinations of argument values
# Testing collapse_groups(data = df, n = 3, group_cols...
xpectr::set_test_seed(42)
# Assigning output
output_19148 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_19148),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_19148[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19148[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19148[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19148[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_19148[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19148[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_19148[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_19148[[".collg"]], n = 30),
structure(c(2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 2L,
2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_19148),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19148),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19148),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19148),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19148)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = c(1, 2, 3), n = 3, gr...
# Changed from baseline: data = c(1, 2, 3)
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19370 <- xpectr::capture_side_effects(collapse_groups(data = c(1, 2, 3), n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19370[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'data': Must be of type 'data.frame', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19370[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = 1, n = 3, group_cols ...
# Changed from baseline: data = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_12861 <- xpectr::capture_side_effects(collapse_groups(data = 1, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_12861[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'data': Must be of type 'data.frame', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_12861[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = NA, n = 3, group_cols...
# Changed from baseline: data = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_18304 <- xpectr::capture_side_effects(collapse_groups(data = NA, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_18304[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'data': Must be of type 'data.frame', not 'logical'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_18304[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = NULL, n = 3, group_co...
# Changed from baseline: data = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16417 <- xpectr::capture_side_effects(collapse_groups(data = NULL, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16417[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'data': Must be of type 'data.frame', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16417[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 4, group_cols...
# Changed from baseline: n = 4
xpectr::set_test_seed(42)
# Assigning output
output_15190 <- collapse_groups(data = df, n = 4, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_15190),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_15190[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_15190[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_15190[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_15190[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_15190[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_15190[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_15190[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_15190[[".collg"]], n = 30),
structure(c(3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 4L, 4L, 3L,
3L, 1L, 1L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 3L,
3L, 3L), .Label = c("1", "2", "3", "4"), class = "factor"))
# Testing column names
expect_equal(
names(output_15190),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_15190),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_15190),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_15190),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_15190)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 1, group_cols...
# Changed from baseline: n = 1
xpectr::set_test_seed(42)
# Assigning output
output_17365 <- collapse_groups(data = df, n = 1, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_17365),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_17365[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_17365[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_17365[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_17365[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_17365[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_17365[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_17365[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_17365[[".collg"]], n = 30),
structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = "1", class = "factor"))
# Testing column names
expect_equal(
names(output_17365),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_17365),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_17365),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_17365),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_17365)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 8, group_cols...
# Changed from baseline: n = 8
xpectr::set_test_seed(42)
# Assigning output
output_11346 <- collapse_groups(data = df, n = 8, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_11346),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_11346[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11346[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11346[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11346[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_11346[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11346[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_11346[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_11346[[".collg"]], n = 30),
structure(c(7L, 7L, 2L, 2L, 2L, 8L, 8L, 8L, 7L, 7L, 3L, 3L, 4L,
4L, 5L, 5L, 3L, 3L, 6L, 6L, 6L, 5L, 5L, 1L, 1L, 1L, 1L, 4L,
4L, 4L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
# Testing column names
expect_equal(
names(output_11346),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_11346),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_11346),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_11346),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_11346)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 9, group_cols...
# Changed from baseline: n = 9
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16569 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 9, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16569[['error']]),
xpectr::strip("`data` subset had fewer `group_cols` groups (8) than `n` (9). If `data` was originally grouped, the `group_cols` within each of those subsets must contain `>= n` groups to collapse."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16569[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = "5", group_co...
# Changed from baseline: n = "5"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17050 <- xpectr::capture_side_effects(collapse_groups(data = df, n = "5", group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17050[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'n': Must be of type 'numeric', not 'character'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17050[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = NA, group_col...
# Changed from baseline: n = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_14577 <- xpectr::capture_side_effects(collapse_groups(data = df, n = NA, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_14577[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'n': Contains missing values (element 1)."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_14577[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = NULL, group_c...
# Changed from baseline: n = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17191 <- xpectr::capture_side_effects(collapse_groups(data = df, n = NULL, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17191[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'n': Must be of type 'numeric', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17191[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_cols = c(".fold...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19346 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = c(".folds", "participant"), cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19346[['error']]),
xpectr::strip("1 assertions failed:\n * All columns in 'c(group_cols, cat_cols, num_cols, id_cols)' must be unique. Found duplicates: 'participant'"),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19346[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_cols = "answer"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_12554 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = "answer", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_12554[['error']]),
xpectr::strip("1 assertions failed:\n * All columns in 'c(group_cols, cat_cols, num_cols, id_cols)' must be unique. Found duplicates: 'answer'"),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_12554[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_cols = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_14622 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = 1, cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_14622[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'group_cols': Must be of type 'character', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_14622[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_cols = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19400 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = NA, cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19400[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'group_cols': Contains missing values (element 1)."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19400[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_cols = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19782 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = NULL, cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19782[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'group_cols': Must be of type 'character', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19782[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols = c("answer"...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_11174 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = c("answer", "session"), cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_11174[['error']]),
xpectr::strip("1 assertions failed:\n * Variable '`cat_cols` column data[['session']]': Must be of type 'factor', not 'character'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_11174[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols = "score"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_14749 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "score", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_14749[['error']]),
xpectr::strip("1 assertions failed:\n * All columns in 'c(group_cols, cat_cols, num_cols, id_cols)' must be unique. Found duplicates: 'score'"),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_14749[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols = ".folds"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_15603 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = ".folds", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_15603[['error']]),
xpectr::strip("1 assertions failed:\n * All columns in 'c(group_cols, cat_cols, num_cols, id_cols)' must be unique. Found duplicates: '.folds'"),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_15603[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19040 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = 1, cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19040[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'cat_cols': Must be of type 'character' (or 'NULL'), not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19040[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_11387 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = NA, cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_11387[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'cat_cols': Contains missing values (element 1)."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_11387[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols = NULL
xpectr::set_test_seed(42)
# Assigning output
output_19888 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = NULL, cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_19888),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_19888[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19888[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19888[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19888[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_19888[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19888[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_19888[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_19888[[".collg"]], n = 30),
structure(c(2L, 2L, 1L, 1L, 1L, 3L, 3L, 3L, 2L, 2L, 1L, 1L, 2L,
2L, 3L, 3L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_19888),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19888),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19888),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19888),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19888)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols, num_cols, i...
xpectr::set_test_seed(42)
# Assigning output
output_19466 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = NULL, cat_levels = NULL, num_cols = NULL, id_cols = NULL, balance_size = FALSE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_19466),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_19466[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19466[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19466[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19466[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_19466[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19466[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_19466[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_19466[[".collg"]], n = 30),
structure(c(1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 1L, 1L, 2L, 2L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_19466),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19466),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19466),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19466),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19466)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols, num_cols, i...
xpectr::set_test_seed(42)
# Assigning output
output_10824 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = NULL, id_cols = NULL, balance_size = FALSE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_10824),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_10824[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_10824[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_10824[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_10824[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_10824[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_10824[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_10824[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_10824[[".collg"]], n = 30),
structure(c(1L, 1L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L,
1L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_10824),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_10824),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_10824),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_10824),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_10824)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols, num_cols, i...
xpectr::set_test_seed(42)
# Assigning output
output_15142 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = NULL, cat_levels = NULL, num_cols = "score", id_cols = NULL, balance_size = FALSE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_15142),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_15142[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_15142[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_15142[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_15142[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_15142[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_15142[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_15142[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_15142[[".collg"]], n = 30),
structure(c(3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 1L, 1L, 3L,
3L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 3L,
3L, 3L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_15142),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_15142),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_15142),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_15142),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_15142)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols, num_cols, i...
xpectr::set_test_seed(42)
# Assigning output
output_13902 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = NULL, cat_levels = NULL, num_cols = NULL, id_cols = "participant", balance_size = FALSE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_13902),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_13902[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_13902[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_13902[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_13902[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_13902[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_13902[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_13902[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_13902[[".collg"]], n = 30),
structure(c(2L, 2L, 1L, 1L, 1L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_13902),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_13902),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_13902),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_13902),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_13902)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_cols, num_cols, i...
xpectr::set_test_seed(42)
# Assigning output
output_19057 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = NULL, cat_levels = NULL, num_cols = NULL, id_cols = NULL, balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_19057),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_19057[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19057[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19057[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19057[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_19057[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19057[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_19057[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_19057[[".collg"]], n = 30),
structure(c(1L, 1L, 3L, 3L, 3L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L,
1L, 3L, 3L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 1L,
1L, 1L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_19057),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19057),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19057),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19057),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19057)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_levels = ".majority"
xpectr::set_test_seed(42)
# Assigning output
output_14469 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = ".majority", num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_14469),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_14469[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_14469[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_14469[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_14469[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_14469[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_14469[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_14469[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_14469[[".collg"]], n = 30),
structure(c(2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 3L, 3L, 2L,
2L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_14469),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_14469),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_14469),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_14469),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_14469)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_levels = ".minority"
xpectr::set_test_seed(42)
# Assigning output
output_18360 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = ".minority", num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_18360),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_18360[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_18360[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_18360[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_18360[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_18360[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_18360[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_18360[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_18360[[".collg"]], n = 30),
structure(c(3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 2L, 2L, 3L,
3L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 3L,
3L, 3L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_18360),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_18360),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_18360),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_18360),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_18360)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_levels = "nope"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17375 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = "nope", num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_match(
xpectr::strip(side_effects_17375[['error']], lowercase = TRUE),
xpectr::strip(
ifelse(
is_checkmate_v2_1(),
"must be a subset of {'.minority','.majority','a','b','c','d'}",
"must be a subset of set {'.minority','.majority','a','b','c','d'}"
), lowercase = TRUE),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17375[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_levels = c(a = 2,...
xpectr::set_test_seed(42)
# Assigning output
output_18110 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = c(a = 2, b = 3), num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_18110),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_18110[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_18110[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_18110[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_18110[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_18110[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_18110[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_18110[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_18110[[".collg"]], n = 30),
structure(c(3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 1L, 1L, 1L,
1L, 3L, 3L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_18110),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_18110),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_18110),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_18110),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_18110)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_levels = c(nope =...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13881 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = c(nope = 2, b = 3), num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_match(
xpectr::strip(side_effects_13881[['error']], lowercase = TRUE),
xpectr::strip(
ifelse(
is_checkmate_v2_1(),
"must be a subset of {'.minority','.majority','a','b','c','d'}",
"must be a subset of set {'.minority','.majority','a','b','c','d'}"
), lowercase = TRUE),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13881[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_levels = list(ans...
xpectr::set_test_seed(42)
# Assigning output
output_16851 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = list(answer = c(a = 2)), num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_16851),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_16851[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_16851[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_16851[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_16851[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_16851[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_16851[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_16851[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_16851[[".collg"]], n = 30),
structure(c(2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 3L, 3L, 2L,
2L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_16851),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_16851),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_16851),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_16851),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_16851)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_levels = list(ses...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_10039 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = list(session = c(a = 2)), num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_10039[['error']]),
xpectr::strip("1 assertions failed:\n * when `cat_levels` is a list, its names must be equal to those in `cat_cols`."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_10039[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_levels = list(sdf...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_18329 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = list(sdfs = c(a = 2)), num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_18329[['error']]),
xpectr::strip("1 assertions failed:\n * when `cat_levels` is a list, its names must be equal to those in `cat_cols`."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_18329[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: cat_levels = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_10073 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NA, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_10073[['error']], lowercase = TRUE),
xpectr::strip(
ifelse(is_checkmate_v2_1(),
"Assertion on 'cat_levels' failed: One of the following must apply:\n * checkmate::check_character(cat_levels): Contains missing values (element 1)\n * checkmate::check_numeric(cat_levels): Must have names\n * checkmate::check_list(cat_levels): Must be of type 'list' (or 'NULL'), not 'logical'.",
"Assertion failed: One of the following must apply:\n * checkmate::check_character(cat_levels): Contains missing values (element 1)\n * checkmate::check_numeric(cat_levels): Must have names\n * checkmate::check_list(cat_levels): Must be of type 'list' (or 'NULL'), not 'logical'."),
lowercase = TRUE),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_10073[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_cols = c("score",...
xpectr::set_test_seed(42)
# Assigning output
output_12076 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = c("score", "age"), id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_12076),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_12076[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_12076[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_12076[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_12076[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_12076[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_12076[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_12076[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_12076[[".collg"]], n = 30),
structure(c(3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 2L, 2L, 1L,
1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_12076),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_12076),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_12076),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_12076),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_12076)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_cols = "answer"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19066 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "answer", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19066[['error']]),
xpectr::strip("1 assertions failed:\n * All columns in 'c(group_cols, cat_cols, num_cols, id_cols)' must be unique. Found duplicates: 'answer'"),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19066[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_cols = ".folds"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16117 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = ".folds", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16117[['error']]),
xpectr::strip("1 assertions failed:\n * All columns in 'c(group_cols, cat_cols, num_cols, id_cols)' must be unique. Found duplicates: '.folds'"),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16117[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_cols = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13795 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = 1, id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_13795[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'num_cols': Must be of type 'character' (or 'NULL'), not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13795[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_cols = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_14357 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = NA, id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_14357[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'num_cols': Contains missing values (element 1)."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_14357[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_cols = NULL
xpectr::set_test_seed(42)
# Assigning output
output_10374 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = NULL, id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_10374),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_10374[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_10374[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_10374[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_10374[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_10374[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_10374[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_10374[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_10374[[".collg"]], n = 30),
structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 3L,
3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_10374),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_10374),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_10374),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_10374),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_10374)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: id_cols = c("particip...
xpectr::set_test_seed(42)
# Assigning output
output_19735 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = c("participant_2", "participant"), balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_19735),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_19735[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19735[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19735[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19735[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_19735[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19735[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_19735[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_19735[[".collg"]], n = 30),
structure(c(2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 2L,
2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_19735),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19735),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19735),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19735),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19735)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: id_cols = "score"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_14317 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "score", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_14317[['error']]),
xpectr::strip("1 assertions failed:\n * All columns in 'c(group_cols, cat_cols, num_cols, id_cols)' must be unique. Found duplicates: 'score'"),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_14317[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: id_cols = ".folds"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19575 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = ".folds", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19575[['error']]),
xpectr::strip("1 assertions failed:\n * All columns in 'c(group_cols, cat_cols, num_cols, id_cols)' must be unique. Found duplicates: '.folds'"),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19575[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: id_cols = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_18877 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = 1, balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_18877[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'id_cols': Must be of type 'character' (or 'NULL'), not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_18877[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: id_cols = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16399 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = NA, balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16399[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'id_cols': Contains missing values (element 1)."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16399[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: id_cols = NULL
xpectr::set_test_seed(42)
# Assigning output
output_19709 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = NULL, balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_19709),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_19709[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19709[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19709[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19709[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_19709[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19709[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_19709[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_19709[[".collg"]], n = 30),
structure(c(2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 2L,
2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_19709),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19709),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19709),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19709),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19709)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: balance_size = FALSE
xpectr::set_test_seed(42)
# Assigning output
output_16188 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = FALSE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_16188),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_16188[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_16188[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_16188[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_16188[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_16188[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_16188[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_16188[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_16188[[".collg"]], n = 30),
structure(c(3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L,
3L, 1L, 1L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L,
3L, 3L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_16188),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_16188),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_16188),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_16188),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_16188)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: balance_size = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13334 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = 1, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_13334[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'balance_size': Must be of type 'logical flag', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13334[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: balance_size = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13467 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = NA, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_13467[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'balance_size': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13467[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: balance_size = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13984 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = NULL, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_13984[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'balance_size': Must be of type 'logical flag', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13984[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: auto_tune = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17846 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = 1, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17846[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'auto_tune': Must be of type 'logical flag', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17846[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: auto_tune = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_10389 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = NA, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_10389[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'auto_tune': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_10389[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: auto_tune = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17487 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = NULL, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17487[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'auto_tune': Must be of type 'logical flag', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17487[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: auto_tune, method
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16772 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = TRUE, weights = NULL, method = "ascending", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16772[['error']]),
xpectr::strip("1 assertions failed:\n * when `method` != 'balance', `auto_tune` must be disabled."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16772[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: weights = c(size = 2,...
xpectr::set_test_seed(42)
# Assigning output
output_11712 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = c(size = 2, answer = 7, score = 1, participant = 2), method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_11712),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_11712[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11712[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11712[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11712[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_11712[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11712[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_11712[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_11712[[".collg"]], n = 30),
structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 3L,
3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_11712),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_11712),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_11712),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_11712),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_11712)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: weights = c(size = 3,...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_12610 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = c(size = 3, nope = 5), method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_match(
xpectr::strip(side_effects_12610[['error']], lowercase = TRUE),
xpectr::strip(
ifelse(
is_checkmate_v2_1(),
"must be a subset of {'size','answer','score','participant'}",
"must be a subset of set {'size','answer','score','participant'}"
), lowercase = TRUE),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_12610[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: weights = c(participa...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_15144 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = c(participant = 2, participant_2 = 2), method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_match(
xpectr::strip(side_effects_15144[['error']], lowercase = TRUE),
xpectr::strip(
ifelse(
is_checkmate_v2_1(),
"must be a subset of {'size','answer','score','participant'}",
"must be a subset of set {'size','answer','score','participant'}"
), lowercase = TRUE),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_15144[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: weights = list(size =...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16756 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = list(size = 2, answer = 7), method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16756[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'weights': Must be of type 'numeric' (or 'NULL'), not 'list'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16756[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: weights = c(size = NA...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19828 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = c(size = NA, answer = 7), method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19828[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'weights': Contains missing values (element 1)."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19828[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: weights = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17595 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = 1, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17595[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'weights': Must have names."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17595[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: weights = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_15664 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NA, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_15664[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'weights': Must have names."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_15664[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: method = "ascending"
xpectr::set_test_seed(42)
# Assigning output
output_18496 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "ascending", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_18496),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_18496[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_18496[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_18496[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_18496[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_18496[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_18496[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_18496[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_18496[[".collg"]], n = 30),
structure(c(3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 1L,
1L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 2L, 2L, 2L, 2L, 1L,
1L, 1L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_18496),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_18496),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_18496),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_18496),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_18496)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: method = "descending"
xpectr::set_test_seed(42)
# Assigning output
output_11894 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "descending", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_11894),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_11894[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11894[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11894[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11894[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_11894[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11894[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_11894[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_11894[[".collg"]], n = 30),
structure(c(1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 3L,
3L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 1L, 1L, 2L, 2L, 2L, 2L, 3L,
3L, 3L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_11894),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_11894),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_11894),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_11894),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_11894)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: method = "none"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_12712 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "none", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_match(
xpectr::strip(side_effects_12712[['error']], lowercase = TRUE),
xpectr::strip(
ifelse(
is_checkmate_v2_1(),
"must be a subset of {'balance','ascending','descending'}",
"must be a subset of set {'balance','ascending','descending'}"
), lowercase = TRUE),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_12712[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: method = list("balance")
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_18281 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = list("balance"), group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_18281[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'method': Must be of type 'string', not 'list'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_18281[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: method = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16932 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = 1, group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16932[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'method': Must be of type 'string', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16932[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: method = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_12405 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = NA, group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_12405[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'method': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_12405[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: method = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_10429 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = NULL, group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_10429[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'method': Must be of type 'string', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_10429[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_aggregation_fn ...
xpectr::set_test_seed(42)
# Assigning output
output_11404 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = sum, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_11404),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_11404[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11404[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11404[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11404[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_11404[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11404[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_11404[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_11404[[".collg"]], n = 30),
structure(c(2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L,
3L, 1L, 1L, 3L, 3L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 3L,
3L, 3L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_11404),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_11404),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_11404),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_11404),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_11404)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_aggregation_fn ...
xpectr::set_test_seed(42)
# Assigning output
output_12163 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = sd, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_12163),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_12163[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_12163[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_12163[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_12163[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_12163[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_12163[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_12163[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_12163[[".collg"]], n = 30),
structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 1L,
1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_12163),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_12163),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_12163),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_12163),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_12163)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_aggregation_fn = 2
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_14793 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = 2, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_14793[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'group_aggregation_fn': Must be a function, not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_14793[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_aggregation_fn ...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_11974 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = NA, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_11974[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'group_aggregation_fn': Must be a function, not 'logical'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_11974[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: group_aggregation_fn ...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17193 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = NULL, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17193[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'group_aggregation_fn': Must be a function, not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17193[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_new_group_cols = 2
xpectr::set_test_seed(42)
# Assigning output
output_10078 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 2, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_10078),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_10078[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_10078[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_10078[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_10078[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_10078[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_10078[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_10078[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_10078[[".collg_1"]], n = 30),
structure(c(2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 2L,
2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
xpectr::smpl(output_10078[[".collg_2"]], n = 30),
structure(c(2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 2L, 1L, 1L, 1L,
1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_10078),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg_1", ".collg_2"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_10078),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_10078),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_10078),
c(53L, 9L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_10078)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_new_group_cols = ...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13754 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = "two", unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_13754[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'num_new_group_cols': Must be of type 'number', not 'character'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13754[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_new_group_cols = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_10015 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = NA, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_10015[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'num_new_group_cols': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_10015[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: num_new_group_cols = ...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_15816 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = NULL, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_15816[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'num_new_group_cols': Must be of type 'number', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_15816[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: unique_new_group_cols...
xpectr::set_test_seed(42)
# Assigning output
output_11579 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = FALSE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_11579),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_11579[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11579[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_11579[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11579[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_11579[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_11579[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_11579[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_11579[[".collg"]], n = 30),
structure(c(2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 2L,
2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_11579),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_11579),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_11579),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_11579),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_11579)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: unique_new_group_cols...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13590 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = 1, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_13590[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'unique_fold_cols_only': Must be of type 'logical flag', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13590[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: unique_new_group_cols...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16456 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = NA, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16456[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'unique_fold_cols_only': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16456[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: unique_new_group_cols...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17758 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = NULL, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17758[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'unique_fold_cols_only': Must be of type 'logical flag', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17758[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: max_iters = 0
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_15636 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 0, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_15636[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'max_iters': Must be >= 1."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_15636[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: max_iters = "sdf"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_12337 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = "sdf", extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_12337[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'max_iters': Must be of type 'count', not 'character'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_12337[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: max_iters = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_10899 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = NA, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_10899[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'max_iters': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_10899[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: max_iters = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_10856 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = NULL, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_10856[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'max_iters': Must be of type 'count', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_10856[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: extreme_pairing_level...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13052 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 2, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_13052[['error']]),
xpectr::strip("`num_col`: The (subset of) data is too small to perform 2 levels of extreme pairing. Decrease `extreme_pairing_levels`."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13052[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: extreme_pairing_level...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16674 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 0, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16674[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'extreme_pairing_levels': Must be >= 1."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16674[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: extreme_pairing_level...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_10002 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = "str", combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_10002[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'extreme_pairing_levels': Must be of type 'count', not 'character'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_10002[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: extreme_pairing_level...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_12085 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = NA, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_12085[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'extreme_pairing_levels': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_12085[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: extreme_pairing_level...
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19330 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = NULL, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19330[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'extreme_pairing_levels': Must be of type 'count', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19330[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: combine_method = "avg...
xpectr::set_test_seed(42)
# Assigning output
output_19256 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_min_max_scaled", col_name = ".collg", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_19256),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_19256[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19256[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_19256[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19256[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_19256[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_19256[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_19256[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_19256[[".collg"]], n = 30),
structure(c(2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 2L,
2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_19256),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".collg"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19256),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19256),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19256),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19256)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: combine_method = "nope"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17340 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "nope", col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_match(
xpectr::strip(side_effects_17340[['error']], lowercase = TRUE),
xpectr::strip(
ifelse(
is_checkmate_v2_1(),
"must be a subset of {'avg_standardized','avg_min_max_scaled'}",
"must be a subset of set {'avg_standardized','avg_min_max_scaled'}"
), lowercase = TRUE),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17340[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: combine_method = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13330 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = 1, col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_13330[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'combine_method': Must be of type 'string', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13330[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: combine_method = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_15150 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = NA, col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_15150[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'combine_method': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_15150[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: combine_method = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17439 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = NULL, col_name = ".collg", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17439[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'combine_method': Must be of type 'string', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17439[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: col_name = ".some_name."
xpectr::set_test_seed(42)
# Assigning output
output_16191 <- collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".some_name.", parallel = FALSE, verbose = FALSE)
# Testing class
expect_equal(
class(output_16191),
c("tbl_df", "tbl", "data.frame"),
fixed = TRUE)
# Testing column values
expect_equal(
xpectr::smpl(output_16191[["participant"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_16191[["participant_2"]], n = 30),
structure(c(10L, 11L, 12L, 13L, 13L, 15L, 16L, 16L, 17L, 17L, 18L,
18L, 2L, 2L, 20L, 20L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 6L, 6L, 8L,
8L, 9L, 9L, 9L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18",
"19", "20"), class = "factor"))
expect_equal(
xpectr::smpl(output_16191[["age"]], n = 30),
c(65, 42, 91, 83, 83, 40, 80, 80, 88, 88, 10, 10, 93, 93, 46, 46,
29, 29, 81, 81, 81, 62, 62, 50, 50, 13, 13, 61, 61, 61),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_16191[["answer"]], n = 30),
structure(c(4L, 3L, 4L, 2L, 2L, 1L, 3L, 3L, 1L, 1L, 1L, 2L, 2L,
4L, 3L, 3L, 1L, 4L, 4L, 3L, 4L, 1L, 4L, 3L, 4L, 4L, 3L, 3L,
2L, 4L), .Label = c("a", "b", "c", "d"), class = "factor"))
expect_equal(
xpectr::smpl(output_16191[["score"]], n = 30),
c(28, 61, 1, 52, 19, 40, 27, 35, 91, 90, 43, 5, 18, 25, 86, 51,
17, 36, 63, 69, 30, 75, 41, 54, 73, 9, 95, 13, 8, 39),
tolerance = 1e-4)
expect_equal(
xpectr::smpl(output_16191[["session"]], n = 30),
c("1", "1", "1", "2", "1", "3", "3", "2", "1", "3", "1", "3", "2",
"3", "2", "1", "2", "1", "1", "3", "2", "1", "3", "1", "2",
"1", "2", "3", "1", "2"),
fixed = TRUE)
expect_equal(
xpectr::smpl(output_16191[[".folds"]], n = 30),
structure(c(6L, 6L, 7L, 7L, 7L, 4L, 4L, 4L, 6L, 6L, 2L, 2L, 1L,
1L, 8L, 8L, 2L, 2L, 5L, 5L, 5L, 8L, 8L, 3L, 3L, 3L, 3L, 1L,
1L, 1L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"),
class = "factor"))
expect_equal(
xpectr::smpl(output_16191[[".some_name."]], n = 30),
structure(c(2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 2L,
2L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L), .Label = c("1", "2", "3"), class = "factor"))
# Testing column names
expect_equal(
names(output_16191),
c("participant", "participant_2", "age", "answer", "score", "session",
".folds", ".some_name."),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_16191),
c("factor", "factor", "integer", "factor", "integer", "character",
"factor", "factor"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_16191),
c("integer", "integer", "integer", "integer", "integer", "character",
"integer", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_16191),
c(53L, 8L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_16191)),
character(0),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: col_name = ".folds"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16262 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".folds", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16262[['error']]),
xpectr::strip("1 assertions failed:\n * `col_name` is already a column in `data`."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16262[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: col_name = "answer"
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_12171 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = "answer", parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_12171[['error']]),
xpectr::strip("1 assertions failed:\n * `col_name` is already a column in `data`."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_12171[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: col_name = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_12165 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = 1, parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_12165[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'col_name': Must be of type 'string', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_12165[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: col_name = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_13889 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = NA, parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_13889[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'col_name': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_13889[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: col_name = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19424 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = NULL, parallel = FALSE, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19424[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'col_name': Must be of type 'string', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19424[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: parallel = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_19626 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = 1, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_19626[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'parallel': Must be of type 'logical flag', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_19626[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: parallel = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17398 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = NA, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17398[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'parallel': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17398[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: parallel = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_17332 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = NULL, verbose = FALSE), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_17332[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'parallel': Must be of type 'logical flag', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_17332[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: verbose = 1
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_15357 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = 1), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_15357[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'verbose': Must be of type 'logical flag', not 'double'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_15357[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: verbose = NA
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_10022 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = NA), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_10022[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'verbose': May not be NA."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_10022[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
# Testing collapse_groups(data = df, n = 3, group_cols...
# Changed from baseline: verbose = NULL
xpectr::set_test_seed(42)
# Testing side effects
# Assigning side effects
side_effects_16089 <- xpectr::capture_side_effects(collapse_groups(data = df, n = 3, group_cols = ".folds", cat_cols = "answer", cat_levels = NULL, num_cols = "score", id_cols = "participant", balance_size = TRUE, auto_tune = FALSE, weights = NULL, method = "balance", group_aggregation_fn = mean, num_new_group_cols = 1, unique_new_group_cols_only = TRUE, max_iters = 2, extreme_pairing_levels = 1, combine_method = "avg_standardized", col_name = ".collg", parallel = FALSE, verbose = NULL), reset_seed = TRUE)
expect_equal(
xpectr::strip(side_effects_16089[['error']]),
xpectr::strip("1 assertions failed:\n * Variable 'verbose': Must be of type 'logical flag', not 'NULL'."),
fixed = TRUE)
expect_equal(
xpectr::strip(side_effects_16089[['error_class']]),
xpectr::strip(c("simpleError", "error", "condition")),
fixed = TRUE)
## Finished testing 'collapse_groups' ####
#
})
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