tests/testthat/test_balance.R
In LudvigOlsen/R-splitters: Creating Groups from Data
library(groupdata2)
context("balance()")
test_that("all size settings work in balance()", {
xpectr::set_test_seed(1)
# Create data frame
df <- data.frame(
"participant" = factor(c(1, 1, 2, 3, 3, 3, 3)),
"trial" = c(1, 2, 1, 1, 2, 3, 4),
"score" = sample(c(1:100), 7)
)
# Using balance() with number
xpectr::set_test_seed(1)
df_3 <- balance(df, 3, "participant")
expect_equal(nrow(df_3), 3 * 3)
expect_equal(df_3$participant, factor(c(1, 1, 1, 2, 2, 2, 3, 3, 3)))
expect_equal(df_3$trial, c(1, 2, 1, 1, 1, 1, 4, 1, 2))
expect_equal(ncol(df_3), 3)
# Using balance() with min
xpectr::set_test_seed(2)
df_min <- balance(df, "min", "participant")
expect_equal(nrow(df_min), 3)
expect_equal(df_min$participant, factor(c(1, 2, 3)))
expect_equal(df_min$trial, c(1, 1, 3))
expect_equal(ncol(df_min), 3)
# Using balance() with max
xpectr::set_test_seed(2)
df_max <- balance(df, "max", "participant")
expect_equal(nrow(df_max), 4 * 3)
expect_equal(df_max$participant, factor(c(1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3)))
expect_equal(df_max$trial, c(1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 3, 4))
expect_equal(ncol(df_max), 3)
# Using balance() with mean
xpectr::set_test_seed(19)
df_mean <- balance(df, "mean", "participant")
expect_equal(nrow(df_mean), 2 * 3)
expect_equal(df_mean$participant, factor(c(1, 1, 2, 2, 3, 3)))
expect_equal(df_mean$trial, c(1, 2, 1, 1, 2, 4))
expect_equal(ncol(df_mean), 3)
# Using balance() with median
xpectr::set_test_seed(19)
df_median <- balance(df, "median", "participant")
expect_equal(nrow(df_median), 2 * 3)
expect_equal(df_median$participant, factor(c(1, 1, 2, 2, 3, 3)))
expect_equal(df_median$trial, c(1, 2, 1, 1, 2, 4))
expect_equal(ncol(df_median), 3)
# Errors
})
test_that("fuzz testing balance()", {
xpectr::set_test_seed(1)
# Create data frame
df <- data.frame(
"participant" = factor(c(1, 1, 2, 3, 3, 3, 3)),
"trial" = c(1, 2, 1, 1, 2, 3, 4),
"diagnosis" = c(1,1,2,2,2,2,2),
"score" = sample(c(1:100), 7)
)
xpectr::set_test_seed(19)
# xpectr::gxs_function(
# balance,
# args_values = list(
# "data" = list(df, df %>% dplyr::mutate(participant = as.character(participant)),
# NA, 1, matrix(1, nrow = 3, ncol = 2)),
# "size" = list("max", 2,-3, 0, "moon", NA),
# "id_col" = list("participant", "hej", NA),
# "cat_col" = list("diagnosis", "trial", "participant", "hej", NA, 2),
# "id_method" = list("n_ids", "n_rows_c", "distributed", "nested", "nope", 1, NA),
# "mark_new_rows" = list(FALSE, TRUE, NA, 1, "TRUE"),
# "new_rows_col_name" = list(".new_row", FALSE, 1, NA)
# ),
# indentation = 2
# )
## Testing 'balance' ####
## Initially generated by xpectr
# Testing different combinations of argument values
# Testing balance(data = df, size = "max", id_col = "par...
xpectr::set_test_seed(42)
# Assigning output
output_11171 <- balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")
# Testing class
expect_equal(
class(output_11171),
"data.frame",
fixed = TRUE)
# Testing column values
expect_equal(
output_11171[["participant"]],
structure(c(1L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 3L), .Label = c("1",
"2", "3"), class = "factor"))
expect_equal(
output_11171[["trial"]],
c(1, 1, 2, 2, 1, 1, 2, 3, 4),
tolerance = 1e-4)
expect_equal(
output_11171[["diagnosis"]],
c(1, 1, 1, 1, 2, 2, 2, 2, 2),
tolerance = 1e-4)
expect_equal(
output_11171[["score"]],
c(27, 27, 37, 37, 57, 89, 20, 86, 97),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(output_11171),
c("participant", "trial", "diagnosis", "score"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_11171),
c("factor", "numeric", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_11171),
c("integer", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_11171),
c(9L, 4L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_11171)),
character(0),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: cat_col
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "trial", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * The value in 'data[[cat_col]]' must",
" be constant within each ID.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: cat_col
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "participant", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip("1 assertions failed:\n * 'id_col' and 'cat_col' cannot contain the same column name."),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: cat_col
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "hej", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip("1 assertions failed:\n * 'cat_col' column(s), 'hej', not found in 'data'."),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: cat_col
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = NA, id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'cat_col': Contains missin",
"g values (element 1).")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: cat_col
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = 2, id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'cat_col': Must be of type",
" 'character', not 'double'.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: cat_col
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = NULL, id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'cat_col': Must be of type",
" 'character', not 'NULL'.")),
fixed = TRUE)
# Testing balance(data = df %>% dplyr::mutate(participan...
# Changed from baseline: data
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df %>% dplyr::mutate(participant = as.character(participant)), size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'data[[id_col]]': Must be ",
"of type 'factor', not 'character'.")),
fixed = TRUE)
# Testing balance(data = NA, size = "max", id_col = "par...
# Changed from baseline: data
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = NA, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'data': Must be of type 'd",
"ata.frame', not 'logical'.")),
fixed = TRUE)
# Testing balance(data = 1, size = "max", id_col = "part...
# Changed from baseline: data
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = 1, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'data': Must be of type 'd",
"ata.frame', not 'double'.")),
fixed = TRUE)
# Testing balance(data = matrix(1, nrow = 3, ncol = 2), ...
# Changed from baseline: data
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = matrix(1, nrow = 3, ncol = 2), size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'data': Must be of type 'd",
"ata.frame', not 'matrix'.")),
fixed = TRUE)
# Testing balance(data = NULL, size = "max", id_col = "p...
# Changed from baseline: data
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = NULL, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'data': Must be of type 'd",
"ata.frame', not 'NULL'.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "hej...
# Changed from baseline: id_col
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "hej", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip("1 assertions failed:\n * 'id_col' column, 'hej', not found in 'data'."),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = NA, ...
# Changed from baseline: id_col
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = NA, cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip("1 assertions failed:\n * Variable 'id_col': May not be NA."),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = NULL...
# Changed from baseline: id_col
xpectr::set_test_seed(42)
# Assigning output
output_12282 <- balance(data = df, size = "max", id_col = NULL, cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")
# Testing class
expect_equal(
class(output_12282),
"data.frame",
fixed = TRUE)
# Testing column values
expect_equal(
output_12282[["participant"]],
structure(c(1L, 1L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 3L), .Label = c("1",
"2", "3"), class = "factor"))
expect_equal(
output_12282[["trial"]],
c(1, 2, 2, 2, 1, 1, 1, 2, 3, 4),
tolerance = 1e-4)
expect_equal(
output_12282[["diagnosis"]],
c(1, 1, 1, 1, 1, 2, 2, 2, 2, 2),
tolerance = 1e-4)
expect_equal(
output_12282[["score"]],
c(27, 37, 37, 37, 27, 57, 89, 20, 86, 97),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(output_12282),
c("participant", "trial", "diagnosis", "score"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_12282),
c("factor", "numeric", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_12282),
c("integer", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_12282),
c(10L, 4L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_12282)),
character(0),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: id_method
xpectr::set_test_seed(42)
# Assigning output
output_19049 <- balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_rows_c", mark_new_rows = FALSE, new_rows_col_name = ".new_row")
# Testing class
expect_equal(
class(output_19049),
"data.frame",
fixed = TRUE)
# Testing column values
expect_equal(
output_19049[["participant"]],
structure(c(1L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 3L), .Label = c("1",
"2", "3"), class = "factor"))
expect_equal(
output_19049[["trial"]],
c(1, 1, 2, 2, 1, 1, 2, 3, 4),
tolerance = 1e-4)
expect_equal(
output_19049[["diagnosis"]],
c(1, 1, 1, 1, 2, 2, 2, 2, 2),
tolerance = 1e-4)
expect_equal(
output_19049[["score"]],
c(27, 27, 37, 37, 57, 89, 20, 86, 97),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(output_19049),
c("participant", "trial", "diagnosis", "score"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19049),
c("factor", "numeric", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19049),
c("integer", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19049),
c(9L, 4L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19049)),
character(0),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: id_method
xpectr::set_test_seed(42)
# Assigning output
output_13975 <- balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "distributed", mark_new_rows = FALSE, new_rows_col_name = ".new_row")
# Testing class
expect_equal(
class(output_13975),
"data.frame",
fixed = TRUE)
# Testing column values
expect_equal(
output_13975[["participant"]],
structure(c(1L, 1L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 3L), .Label = c("1",
"2", "3"), class = "factor"))
expect_equal(
output_13975[["trial"]],
c(1, 2, 2, 1, 2, 1, 1, 2, 3, 4),
tolerance = 1e-4)
expect_equal(
output_13975[["diagnosis"]],
c(1, 1, 1, 1, 1, 2, 2, 2, 2, 2),
tolerance = 1e-4)
expect_equal(
output_13975[["score"]],
c(27, 37, 37, 27, 37, 57, 89, 20, 86, 97),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(output_13975),
c("participant", "trial", "diagnosis", "score"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_13975),
c("factor", "numeric", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_13975),
c("integer", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_13975),
c(10L, 4L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_13975)),
character(0),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: id_method
xpectr::set_test_seed(42)
# Assigning output
output_15676 <- balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "nested", mark_new_rows = FALSE, new_rows_col_name = ".new_row")
# Testing class
expect_equal(
class(output_15676),
"data.frame",
fixed = TRUE)
# Testing column values
expect_equal(
output_15676[["participant"]],
structure(c(1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L), .Label = c("1",
"2", "3"), class = "factor"))
expect_equal(
output_15676[["trial"]],
c(1, 2, 1, 1, 1, 1, 1, 2, 3, 4),
tolerance = 1e-4)
expect_equal(
output_15676[["diagnosis"]],
c(1, 1, 2, 2, 2, 2, 2, 2, 2, 2),
tolerance = 1e-4)
expect_equal(
output_15676[["score"]],
c(27, 37, 57, 57, 57, 57, 89, 20, 86, 97),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(output_15676),
c("participant", "trial", "diagnosis", "score"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_15676),
c("factor", "numeric", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_15676),
c("integer", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_15676),
c(10L, 4L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_15676)),
character(0),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: id_method
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "nope", mark_new_rows = FALSE, new_rows_col_name = ".new_row"), lowercase = TRUE),
xpectr::strip(
ifelse(is_checkmate_v2_1(),
"must be a subset of {n_ids,n_rows_c,distributed,nested}",
"must be a subset of set {n_ids,n_rows_c,distributed,nested}.")
, lowercase = TRUE),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: id_method
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = 1, mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'id_method': Must be of ty",
"pe 'string', not 'double'.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: id_method
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = NA, mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip("1 assertions failed:\n * Variable 'id_method': May not be NA."),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: id_method
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = NULL, mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'id_method': Must be of ty",
"pe 'string', not 'NULL'.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: mark_new_rows
xpectr::set_test_seed(42)
# Assigning output
output_18115 <- balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = TRUE, new_rows_col_name = ".new_row")
# Testing class
expect_equal(
class(output_18115),
"data.frame",
fixed = TRUE)
# Testing column values
expect_equal(
output_18115[["participant"]],
structure(c(1L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 3L), .Label = c("1",
"2", "3"), class = "factor"))
expect_equal(
output_18115[["trial"]],
c(1, 1, 2, 2, 1, 1, 2, 3, 4),
tolerance = 1e-4)
expect_equal(
output_18115[["diagnosis"]],
c(1, 1, 1, 1, 2, 2, 2, 2, 2),
tolerance = 1e-4)
expect_equal(
output_18115[["score"]],
c(27, 27, 37, 37, 57, 89, 20, 86, 97),
tolerance = 1e-4)
expect_equal(
output_18115[[".new_row"]],
c(0, 1, 0, 1, 0, 0, 0, 0, 0),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(output_18115),
c("participant", "trial", "diagnosis", "score", ".new_row"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_18115),
c("factor", "numeric", "numeric", "integer", "numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_18115),
c("integer", "double", "double", "integer", "double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_18115),
c(9L, 5L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_18115)),
character(0),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: mark_new_rows
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = NA, new_rows_col_name = ".new_row")),
xpectr::strip("1 assertions failed:\n * Variable 'mark_new_rows': May not be NA."),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: mark_new_rows
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = 1, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'mark_new_rows': Must be o",
"f type 'logical flag', not 'double'.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: mark_new_rows
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = "TRUE", new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'mark_new_rows': Must be o",
"f type 'logical flag', not 'character'.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: mark_new_rows
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = NULL, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'mark_new_rows': Must be o",
"f type 'logical flag', not 'NULL'.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: new_rows_col_name
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = FALSE)),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'new_rows_col_name': Must ",
"be of type 'string', not 'logical'.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: new_rows_col_name
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = 1)),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'new_rows_col_name': Must ",
"be of type 'string', not 'double'.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: new_rows_col_name
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = NA)),
xpectr::strip("1 assertions failed:\n * Variable 'new_rows_col_name': May not be NA."),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: new_rows_col_name
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = NULL)),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'new_rows_col_name': Must ",
"be of type 'string', not 'NULL'.")),
fixed = TRUE)
# Testing balance(data = df, size = 2, id_col = "partici...
# Changed from baseline: size
xpectr::set_test_seed(42)
# Assigning output
output_16237 <- balance(data = df, size = 2, id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")
# Testing class
expect_equal(
class(output_16237),
"data.frame",
fixed = TRUE)
# Testing column values
expect_equal(
output_16237[["participant"]],
structure(c(1L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 3L), .Label = c("1",
"2", "3"), class = "factor"))
expect_equal(
output_16237[["trial"]],
c(1, 1, 2, 2, 1, 1, 2, 3, 4),
tolerance = 1e-4)
expect_equal(
output_16237[["diagnosis"]],
c(1, 1, 1, 1, 2, 2, 2, 2, 2),
tolerance = 1e-4)
expect_equal(
output_16237[["score"]],
c(27, 27, 37, 37, 57, 89, 20, 86, 97),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(output_16237),
c("participant", "trial", "diagnosis", "score"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_16237),
c("factor", "numeric", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_16237),
c("integer", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_16237),
c(9L, 4L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_16237)),
character(0),
fixed = TRUE)
# Testing balance(data = df, size = -3, id_col = "partic...
# Changed from baseline: size
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = -3, id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * 'size' must be one of 'min','max','",
"mean','median' or a positive whole number.")),
fixed = TRUE)
# Testing balance(data = df, size = 0, id_col = "partici...
# Changed from baseline: size
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = 0, id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * 'size' must be one of 'min','max','",
"mean','median' or a positive whole number.")),
fixed = TRUE)
# Testing balance(data = df, size = "moon", id_col = "pa...
# Changed from baseline: size
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "moon", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * 'size' must be one of 'min','max','",
"mean','median' or a positive whole number.")),
fixed = TRUE)
# Testing balance(data = df, size = NA, id_col = "partic...
# Changed from baseline: size
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = NA, id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * 'size' must be one of 'min','max','",
"mean','median' or a positive whole number.")),
fixed = TRUE)
# Testing balance(data = df, size = NULL, id_col = "part...
# Changed from baseline: size
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = NULL, id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * 'size' must be one of 'min','max','",
"mean','median' or a positive whole number.")),
fixed = TRUE)
## Finished testing 'balance' ####
#
})
test_that("mark_new_rows works in balance()", {
xpectr::set_test_seed(1)
# Create data frame
df <- data.frame(
"participant" = factor(c(1, 1, 2, 3, 3, 3, 3)),
"trial" = c(1, 2, 1, 1, 2, 3, 4),
"score" = sample(c(1:100), 7)
)
xpectr::set_test_seed(1)
df_3 <- balance(df, 3, "participant", mark_new_rows = TRUE)
expect_equal(df_3$.new_row, c(0, 0, 1, 0, 1, 1, 0, 0, 0))
xpectr::set_test_seed(1)
df_3 <- balance(df, 3, "participant", mark_new_rows = TRUE, new_rows_col_name = "someName")
expect_equal(df_3$someName, c(0, 0, 1, 0, 1, 1, 0, 0, 0))
})
test_that("both wrapper functions, upsample() and downsample() work", {
xpectr::set_test_seed(1)
# Create data frame
df <- data.frame(
"participant" = factor(c(1, 1, 2, 3, 3, 3, 3)),
"trial" = c(1, 2, 1, 1, 2, 3, 4),
"score" = sample(c(1:100), 7)
)
xpectr::set_test_seed(1)
df_min_balance <- balance(df, "min", "participant")
xpectr::set_test_seed(1)
df_min_downsample <- downsample(df, "participant")
expect_equal(df_min_balance, df_min_downsample)
xpectr::set_test_seed(1)
df_max_balance <- balance(df, "max", "participant")
xpectr::set_test_seed(1)
df_max_upsample <- upsample(df, "participant")
expect_equal(df_max_balance, df_max_upsample)
})
test_that("balance() works in dplyr pipeline", {
xpectr::set_test_seed(1)
xpectr::suppress_mw(library(dplyr))
# Create data frame
xpectr::set_test_seed(1)
df <- data.frame(
"participant" = factor(c(1, 1, 2, 3, 3, 3, 3)),
"trial" = c(1, 2, 1, 1, 2, 3, 4),
"score" = sample(c(1:100), 7)
) %>%
balance("min", "participant")
expect_equal(nrow(df), 3)
expect_equal(df$participant, factor(c(1, 2, 3)))
expect_equal(df$trial, c(2, 1, 3))
expect_equal(ncol(df), 3)
})
test_that("balance() works with group_by()", {
xpectr::set_test_seed(42)
library(dplyr)
## Testing 'data.frame( "participant" = factor(c(1, 1, 2, ...' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Assigning output
xpectr::suppress_mw(output_19466 <- data.frame(
"participant" = factor(c(1, 1, 2, 3, 2, 3, 3)),
"trial" = c(1, 1, 1, 2, 2, 2, 4),
"score" = sample(c(1:100), 7)
) %>%
dplyr::group_by(trial) %>%
balance("min", "participant")
)
# Testing class
expect_equal(
class(output_19466),
"data.frame",
fixed = TRUE)
# Testing column values
expect_equal(
output_19466[["participant"]],
structure(c(1L, 2L, 2L, 3L, 3L), .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
output_19466[["trial"]],
c(1, 1, 2, 2, 4),
tolerance = 1e-4)
expect_equal(
output_19466[["score"]],
c(92, 29, 62, 50, 70),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(output_19466),
c("participant", "trial", "score"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19466),
c("factor", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19466),
c("integer", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19466),
c(5L, 3L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19466)),
character(0),
fixed = TRUE)
## Finished testing 'data.frame( "participant" = factor(c(1, 1, 2, ...' ####
})
LudvigOlsen/R-splitters documentation built on March 7, 2024, 6:59 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
library(groupdata2)
context("balance()")
test_that("all size settings work in balance()", {
xpectr::set_test_seed(1)
# Create data frame
df <- data.frame(
"participant" = factor(c(1, 1, 2, 3, 3, 3, 3)),
"trial" = c(1, 2, 1, 1, 2, 3, 4),
"score" = sample(c(1:100), 7)
)
# Using balance() with number
xpectr::set_test_seed(1)
df_3 <- balance(df, 3, "participant")
expect_equal(nrow(df_3), 3 * 3)
expect_equal(df_3$participant, factor(c(1, 1, 1, 2, 2, 2, 3, 3, 3)))
expect_equal(df_3$trial, c(1, 2, 1, 1, 1, 1, 4, 1, 2))
expect_equal(ncol(df_3), 3)
# Using balance() with min
xpectr::set_test_seed(2)
df_min <- balance(df, "min", "participant")
expect_equal(nrow(df_min), 3)
expect_equal(df_min$participant, factor(c(1, 2, 3)))
expect_equal(df_min$trial, c(1, 1, 3))
expect_equal(ncol(df_min), 3)
# Using balance() with max
xpectr::set_test_seed(2)
df_max <- balance(df, "max", "participant")
expect_equal(nrow(df_max), 4 * 3)
expect_equal(df_max$participant, factor(c(1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3)))
expect_equal(df_max$trial, c(1, 2, 1, 2, 1, 1, 1, 1, 1, 2, 3, 4))
expect_equal(ncol(df_max), 3)
# Using balance() with mean
xpectr::set_test_seed(19)
df_mean <- balance(df, "mean", "participant")
expect_equal(nrow(df_mean), 2 * 3)
expect_equal(df_mean$participant, factor(c(1, 1, 2, 2, 3, 3)))
expect_equal(df_mean$trial, c(1, 2, 1, 1, 2, 4))
expect_equal(ncol(df_mean), 3)
# Using balance() with median
xpectr::set_test_seed(19)
df_median <- balance(df, "median", "participant")
expect_equal(nrow(df_median), 2 * 3)
expect_equal(df_median$participant, factor(c(1, 1, 2, 2, 3, 3)))
expect_equal(df_median$trial, c(1, 2, 1, 1, 2, 4))
expect_equal(ncol(df_median), 3)
# Errors
})
test_that("fuzz testing balance()", {
xpectr::set_test_seed(1)
# Create data frame
df <- data.frame(
"participant" = factor(c(1, 1, 2, 3, 3, 3, 3)),
"trial" = c(1, 2, 1, 1, 2, 3, 4),
"diagnosis" = c(1,1,2,2,2,2,2),
"score" = sample(c(1:100), 7)
)
xpectr::set_test_seed(19)
# xpectr::gxs_function(
# balance,
# args_values = list(
# "data" = list(df, df %>% dplyr::mutate(participant = as.character(participant)),
# NA, 1, matrix(1, nrow = 3, ncol = 2)),
# "size" = list("max", 2,-3, 0, "moon", NA),
# "id_col" = list("participant", "hej", NA),
# "cat_col" = list("diagnosis", "trial", "participant", "hej", NA, 2),
# "id_method" = list("n_ids", "n_rows_c", "distributed", "nested", "nope", 1, NA),
# "mark_new_rows" = list(FALSE, TRUE, NA, 1, "TRUE"),
# "new_rows_col_name" = list(".new_row", FALSE, 1, NA)
# ),
# indentation = 2
# )
## Testing 'balance' ####
## Initially generated by xpectr
# Testing different combinations of argument values
# Testing balance(data = df, size = "max", id_col = "par...
xpectr::set_test_seed(42)
# Assigning output
output_11171 <- balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")
# Testing class
expect_equal(
class(output_11171),
"data.frame",
fixed = TRUE)
# Testing column values
expect_equal(
output_11171[["participant"]],
structure(c(1L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 3L), .Label = c("1",
"2", "3"), class = "factor"))
expect_equal(
output_11171[["trial"]],
c(1, 1, 2, 2, 1, 1, 2, 3, 4),
tolerance = 1e-4)
expect_equal(
output_11171[["diagnosis"]],
c(1, 1, 1, 1, 2, 2, 2, 2, 2),
tolerance = 1e-4)
expect_equal(
output_11171[["score"]],
c(27, 27, 37, 37, 57, 89, 20, 86, 97),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(output_11171),
c("participant", "trial", "diagnosis", "score"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_11171),
c("factor", "numeric", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_11171),
c("integer", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_11171),
c(9L, 4L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_11171)),
character(0),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: cat_col
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "trial", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * The value in 'data[[cat_col]]' must",
" be constant within each ID.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: cat_col
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "participant", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip("1 assertions failed:\n * 'id_col' and 'cat_col' cannot contain the same column name."),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: cat_col
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "hej", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip("1 assertions failed:\n * 'cat_col' column(s), 'hej', not found in 'data'."),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: cat_col
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = NA, id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'cat_col': Contains missin",
"g values (element 1).")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: cat_col
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = 2, id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'cat_col': Must be of type",
" 'character', not 'double'.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: cat_col
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = NULL, id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'cat_col': Must be of type",
" 'character', not 'NULL'.")),
fixed = TRUE)
# Testing balance(data = df %>% dplyr::mutate(participan...
# Changed from baseline: data
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df %>% dplyr::mutate(participant = as.character(participant)), size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'data[[id_col]]': Must be ",
"of type 'factor', not 'character'.")),
fixed = TRUE)
# Testing balance(data = NA, size = "max", id_col = "par...
# Changed from baseline: data
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = NA, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'data': Must be of type 'd",
"ata.frame', not 'logical'.")),
fixed = TRUE)
# Testing balance(data = 1, size = "max", id_col = "part...
# Changed from baseline: data
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = 1, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'data': Must be of type 'd",
"ata.frame', not 'double'.")),
fixed = TRUE)
# Testing balance(data = matrix(1, nrow = 3, ncol = 2), ...
# Changed from baseline: data
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = matrix(1, nrow = 3, ncol = 2), size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'data': Must be of type 'd",
"ata.frame', not 'matrix'.")),
fixed = TRUE)
# Testing balance(data = NULL, size = "max", id_col = "p...
# Changed from baseline: data
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = NULL, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'data': Must be of type 'd",
"ata.frame', not 'NULL'.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "hej...
# Changed from baseline: id_col
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "hej", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip("1 assertions failed:\n * 'id_col' column, 'hej', not found in 'data'."),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = NA, ...
# Changed from baseline: id_col
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = NA, cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip("1 assertions failed:\n * Variable 'id_col': May not be NA."),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = NULL...
# Changed from baseline: id_col
xpectr::set_test_seed(42)
# Assigning output
output_12282 <- balance(data = df, size = "max", id_col = NULL, cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")
# Testing class
expect_equal(
class(output_12282),
"data.frame",
fixed = TRUE)
# Testing column values
expect_equal(
output_12282[["participant"]],
structure(c(1L, 1L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 3L), .Label = c("1",
"2", "3"), class = "factor"))
expect_equal(
output_12282[["trial"]],
c(1, 2, 2, 2, 1, 1, 1, 2, 3, 4),
tolerance = 1e-4)
expect_equal(
output_12282[["diagnosis"]],
c(1, 1, 1, 1, 1, 2, 2, 2, 2, 2),
tolerance = 1e-4)
expect_equal(
output_12282[["score"]],
c(27, 37, 37, 37, 27, 57, 89, 20, 86, 97),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(output_12282),
c("participant", "trial", "diagnosis", "score"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_12282),
c("factor", "numeric", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_12282),
c("integer", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_12282),
c(10L, 4L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_12282)),
character(0),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: id_method
xpectr::set_test_seed(42)
# Assigning output
output_19049 <- balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_rows_c", mark_new_rows = FALSE, new_rows_col_name = ".new_row")
# Testing class
expect_equal(
class(output_19049),
"data.frame",
fixed = TRUE)
# Testing column values
expect_equal(
output_19049[["participant"]],
structure(c(1L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 3L), .Label = c("1",
"2", "3"), class = "factor"))
expect_equal(
output_19049[["trial"]],
c(1, 1, 2, 2, 1, 1, 2, 3, 4),
tolerance = 1e-4)
expect_equal(
output_19049[["diagnosis"]],
c(1, 1, 1, 1, 2, 2, 2, 2, 2),
tolerance = 1e-4)
expect_equal(
output_19049[["score"]],
c(27, 27, 37, 37, 57, 89, 20, 86, 97),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(output_19049),
c("participant", "trial", "diagnosis", "score"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19049),
c("factor", "numeric", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19049),
c("integer", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19049),
c(9L, 4L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19049)),
character(0),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: id_method
xpectr::set_test_seed(42)
# Assigning output
output_13975 <- balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "distributed", mark_new_rows = FALSE, new_rows_col_name = ".new_row")
# Testing class
expect_equal(
class(output_13975),
"data.frame",
fixed = TRUE)
# Testing column values
expect_equal(
output_13975[["participant"]],
structure(c(1L, 1L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 3L), .Label = c("1",
"2", "3"), class = "factor"))
expect_equal(
output_13975[["trial"]],
c(1, 2, 2, 1, 2, 1, 1, 2, 3, 4),
tolerance = 1e-4)
expect_equal(
output_13975[["diagnosis"]],
c(1, 1, 1, 1, 1, 2, 2, 2, 2, 2),
tolerance = 1e-4)
expect_equal(
output_13975[["score"]],
c(27, 37, 37, 27, 37, 57, 89, 20, 86, 97),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(output_13975),
c("participant", "trial", "diagnosis", "score"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_13975),
c("factor", "numeric", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_13975),
c("integer", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_13975),
c(10L, 4L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_13975)),
character(0),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: id_method
xpectr::set_test_seed(42)
# Assigning output
output_15676 <- balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "nested", mark_new_rows = FALSE, new_rows_col_name = ".new_row")
# Testing class
expect_equal(
class(output_15676),
"data.frame",
fixed = TRUE)
# Testing column values
expect_equal(
output_15676[["participant"]],
structure(c(1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L), .Label = c("1",
"2", "3"), class = "factor"))
expect_equal(
output_15676[["trial"]],
c(1, 2, 1, 1, 1, 1, 1, 2, 3, 4),
tolerance = 1e-4)
expect_equal(
output_15676[["diagnosis"]],
c(1, 1, 2, 2, 2, 2, 2, 2, 2, 2),
tolerance = 1e-4)
expect_equal(
output_15676[["score"]],
c(27, 37, 57, 57, 57, 57, 89, 20, 86, 97),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(output_15676),
c("participant", "trial", "diagnosis", "score"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_15676),
c("factor", "numeric", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_15676),
c("integer", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_15676),
c(10L, 4L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_15676)),
character(0),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: id_method
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "nope", mark_new_rows = FALSE, new_rows_col_name = ".new_row"), lowercase = TRUE),
xpectr::strip(
ifelse(is_checkmate_v2_1(),
"must be a subset of {n_ids,n_rows_c,distributed,nested}",
"must be a subset of set {n_ids,n_rows_c,distributed,nested}.")
, lowercase = TRUE),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: id_method
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = 1, mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'id_method': Must be of ty",
"pe 'string', not 'double'.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: id_method
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = NA, mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip("1 assertions failed:\n * Variable 'id_method': May not be NA."),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: id_method
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = NULL, mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'id_method': Must be of ty",
"pe 'string', not 'NULL'.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: mark_new_rows
xpectr::set_test_seed(42)
# Assigning output
output_18115 <- balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = TRUE, new_rows_col_name = ".new_row")
# Testing class
expect_equal(
class(output_18115),
"data.frame",
fixed = TRUE)
# Testing column values
expect_equal(
output_18115[["participant"]],
structure(c(1L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 3L), .Label = c("1",
"2", "3"), class = "factor"))
expect_equal(
output_18115[["trial"]],
c(1, 1, 2, 2, 1, 1, 2, 3, 4),
tolerance = 1e-4)
expect_equal(
output_18115[["diagnosis"]],
c(1, 1, 1, 1, 2, 2, 2, 2, 2),
tolerance = 1e-4)
expect_equal(
output_18115[["score"]],
c(27, 27, 37, 37, 57, 89, 20, 86, 97),
tolerance = 1e-4)
expect_equal(
output_18115[[".new_row"]],
c(0, 1, 0, 1, 0, 0, 0, 0, 0),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(output_18115),
c("participant", "trial", "diagnosis", "score", ".new_row"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_18115),
c("factor", "numeric", "numeric", "integer", "numeric"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_18115),
c("integer", "double", "double", "integer", "double"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_18115),
c(9L, 5L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_18115)),
character(0),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: mark_new_rows
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = NA, new_rows_col_name = ".new_row")),
xpectr::strip("1 assertions failed:\n * Variable 'mark_new_rows': May not be NA."),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: mark_new_rows
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = 1, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'mark_new_rows': Must be o",
"f type 'logical flag', not 'double'.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: mark_new_rows
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = "TRUE", new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'mark_new_rows': Must be o",
"f type 'logical flag', not 'character'.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: mark_new_rows
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = NULL, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'mark_new_rows': Must be o",
"f type 'logical flag', not 'NULL'.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: new_rows_col_name
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = FALSE)),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'new_rows_col_name': Must ",
"be of type 'string', not 'logical'.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: new_rows_col_name
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = 1)),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'new_rows_col_name': Must ",
"be of type 'string', not 'double'.")),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: new_rows_col_name
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = NA)),
xpectr::strip("1 assertions failed:\n * Variable 'new_rows_col_name': May not be NA."),
fixed = TRUE)
# Testing balance(data = df, size = "max", id_col = "par...
# Changed from baseline: new_rows_col_name
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "max", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = NULL)),
xpectr::strip(paste0("1 assertions failed:\n * Variable 'new_rows_col_name': Must ",
"be of type 'string', not 'NULL'.")),
fixed = TRUE)
# Testing balance(data = df, size = 2, id_col = "partici...
# Changed from baseline: size
xpectr::set_test_seed(42)
# Assigning output
output_16237 <- balance(data = df, size = 2, id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")
# Testing class
expect_equal(
class(output_16237),
"data.frame",
fixed = TRUE)
# Testing column values
expect_equal(
output_16237[["participant"]],
structure(c(1L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 3L), .Label = c("1",
"2", "3"), class = "factor"))
expect_equal(
output_16237[["trial"]],
c(1, 1, 2, 2, 1, 1, 2, 3, 4),
tolerance = 1e-4)
expect_equal(
output_16237[["diagnosis"]],
c(1, 1, 1, 1, 2, 2, 2, 2, 2),
tolerance = 1e-4)
expect_equal(
output_16237[["score"]],
c(27, 27, 37, 37, 57, 89, 20, 86, 97),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(output_16237),
c("participant", "trial", "diagnosis", "score"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_16237),
c("factor", "numeric", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_16237),
c("integer", "double", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_16237),
c(9L, 4L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_16237)),
character(0),
fixed = TRUE)
# Testing balance(data = df, size = -3, id_col = "partic...
# Changed from baseline: size
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = -3, id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * 'size' must be one of 'min','max','",
"mean','median' or a positive whole number.")),
fixed = TRUE)
# Testing balance(data = df, size = 0, id_col = "partici...
# Changed from baseline: size
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = 0, id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * 'size' must be one of 'min','max','",
"mean','median' or a positive whole number.")),
fixed = TRUE)
# Testing balance(data = df, size = "moon", id_col = "pa...
# Changed from baseline: size
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = "moon", id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * 'size' must be one of 'min','max','",
"mean','median' or a positive whole number.")),
fixed = TRUE)
# Testing balance(data = df, size = NA, id_col = "partic...
# Changed from baseline: size
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = NA, id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * 'size' must be one of 'min','max','",
"mean','median' or a positive whole number.")),
fixed = TRUE)
# Testing balance(data = df, size = NULL, id_col = "part...
# Changed from baseline: size
xpectr::set_test_seed(42)
# Testing side effects
expect_error(
xpectr::strip_msg(balance(data = df, size = NULL, id_col = "participant", cat_col = "diagnosis", id_method = "n_ids", mark_new_rows = FALSE, new_rows_col_name = ".new_row")),
xpectr::strip(paste0("1 assertions failed:\n * 'size' must be one of 'min','max','",
"mean','median' or a positive whole number.")),
fixed = TRUE)
## Finished testing 'balance' ####
#
})
test_that("mark_new_rows works in balance()", {
xpectr::set_test_seed(1)
# Create data frame
df <- data.frame(
"participant" = factor(c(1, 1, 2, 3, 3, 3, 3)),
"trial" = c(1, 2, 1, 1, 2, 3, 4),
"score" = sample(c(1:100), 7)
)
xpectr::set_test_seed(1)
df_3 <- balance(df, 3, "participant", mark_new_rows = TRUE)
expect_equal(df_3$.new_row, c(0, 0, 1, 0, 1, 1, 0, 0, 0))
xpectr::set_test_seed(1)
df_3 <- balance(df, 3, "participant", mark_new_rows = TRUE, new_rows_col_name = "someName")
expect_equal(df_3$someName, c(0, 0, 1, 0, 1, 1, 0, 0, 0))
})
test_that("both wrapper functions, upsample() and downsample() work", {
xpectr::set_test_seed(1)
# Create data frame
df <- data.frame(
"participant" = factor(c(1, 1, 2, 3, 3, 3, 3)),
"trial" = c(1, 2, 1, 1, 2, 3, 4),
"score" = sample(c(1:100), 7)
)
xpectr::set_test_seed(1)
df_min_balance <- balance(df, "min", "participant")
xpectr::set_test_seed(1)
df_min_downsample <- downsample(df, "participant")
expect_equal(df_min_balance, df_min_downsample)
xpectr::set_test_seed(1)
df_max_balance <- balance(df, "max", "participant")
xpectr::set_test_seed(1)
df_max_upsample <- upsample(df, "participant")
expect_equal(df_max_balance, df_max_upsample)
})
test_that("balance() works in dplyr pipeline", {
xpectr::set_test_seed(1)
xpectr::suppress_mw(library(dplyr))
# Create data frame
xpectr::set_test_seed(1)
df <- data.frame(
"participant" = factor(c(1, 1, 2, 3, 3, 3, 3)),
"trial" = c(1, 2, 1, 1, 2, 3, 4),
"score" = sample(c(1:100), 7)
) %>%
balance("min", "participant")
expect_equal(nrow(df), 3)
expect_equal(df$participant, factor(c(1, 2, 3)))
expect_equal(df$trial, c(2, 1, 3))
expect_equal(ncol(df), 3)
})
test_that("balance() works with group_by()", {
xpectr::set_test_seed(42)
library(dplyr)
## Testing 'data.frame( "participant" = factor(c(1, 1, 2, ...' ####
## Initially generated by xpectr
xpectr::set_test_seed(42)
# Assigning output
xpectr::suppress_mw(output_19466 <- data.frame(
"participant" = factor(c(1, 1, 2, 3, 2, 3, 3)),
"trial" = c(1, 1, 1, 2, 2, 2, 4),
"score" = sample(c(1:100), 7)
) %>%
dplyr::group_by(trial) %>%
balance("min", "participant")
)
# Testing class
expect_equal(
class(output_19466),
"data.frame",
fixed = TRUE)
# Testing column values
expect_equal(
output_19466[["participant"]],
structure(c(1L, 2L, 2L, 3L, 3L), .Label = c("1", "2", "3"), class = "factor"))
expect_equal(
output_19466[["trial"]],
c(1, 1, 2, 2, 4),
tolerance = 1e-4)
expect_equal(
output_19466[["score"]],
c(92, 29, 62, 50, 70),
tolerance = 1e-4)
# Testing column names
expect_equal(
names(output_19466),
c("participant", "trial", "score"),
fixed = TRUE)
# Testing column classes
expect_equal(
xpectr::element_classes(output_19466),
c("factor", "numeric", "integer"),
fixed = TRUE)
# Testing column types
expect_equal(
xpectr::element_types(output_19466),
c("integer", "double", "integer"),
fixed = TRUE)
# Testing dimensions
expect_equal(
dim(output_19466),
c(5L, 3L))
# Testing group keys
expect_equal(
colnames(dplyr::group_keys(output_19466)),
character(0),
fixed = TRUE)
## Finished testing 'data.frame( "participant" = factor(c(1, 1, 2, ...' ####
})
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.