Nothing
context("category")
suppressWarnings(RNGversion("3.5.0"))
set.seed(123)
dichotomy_matrix = matrix(sample(0:1,40,replace = TRUE,prob=c(.6,.4)),nrow=10)
colnames(dichotomy_matrix) = c("Milk","Sugar","Tea","Coffee")
dichotomy_matrix[] = 0
expect_equal_to_reference(as.category(dichotomy_matrix, prefix = "zero", compress=TRUE),
"rds/category2df.rds", update = FALSE)
expect_equal_to_reference(as.category(dichotomy_matrix, prefix = "zero", compress=FALSE),
"rds/category3df.rds", update = FALSE)
expect_true(is.category(as.category(dichotomy_matrix, prefix = "zero", compress=FALSE)))
expect_equal_to_reference(as.category(dichotomy_matrix[,FALSE, drop = FALSE], compress = FALSE),
"rds/category4df.rds", update = FALSE)
expect_identical(as.category(numeric(0),compress=TRUE),
structure(list(V1 = integer(0)), .Names = "V1", row.names = integer(0), class = c("category",
"data.frame")))
expect_equal_to_reference(as.category(t(t(c(0,1,0,1,0,1))),compress=TRUE),
"rds/category5df.rds", update = FALSE)
expect_equal_to_reference(as.category(t(c(0,1,0,1,0,1)),compress=TRUE),
"rds/category6df.rds", update = FALSE)
expect_equal_to_reference(as.category(c(0,1,0,1,0,1),compress=TRUE),
"rds/category5df.rds", update = FALSE)
set.seed(123)
dichotomy_matrix = matrix(sample(0:1,40,replace = TRUE,prob=c(.6,.4)),nrow=10)
colnames(dichotomy_matrix) = c("Milk","Sugar","Tea","Coffee")
# data.frame with variable labels
dichotomy_dataframe = as.data.frame(dichotomy_matrix)
colnames(dichotomy_dataframe) = paste0("product_", 1:4)
var_lab(dichotomy_dataframe[[1]]) = "Milk"
var_lab(dichotomy_dataframe[[2]]) = "Sugar"
var_lab(dichotomy_dataframe[[3]]) = "Tea"
var_lab(dichotomy_dataframe[[4]]) = "Coffee"
expect_equal_to_reference(as.category(dichotomy_dataframe, prefix = "products_",compress=TRUE),
"rds/category5.rds", update = FALSE)
dichotomy_dataframe2 = dichotomy_dataframe
var_lab(dichotomy_dataframe2[[4]]) = NULL
expect_identical(as.category(dichotomy_dataframe2, prefix = "products_",compress=TRUE),
add_val_lab(
as.category(dichotomy_dataframe, prefix = "products_",compress=TRUE),
c("product_4" = 4L)
)
)
dich = as.data.frame(matrix(NA, nrow = 3, ncol = 3))
expect_identical(as.category(dich, compress = TRUE),
structure(list(`NA` = c(NA, NA, NA)),
.Names = "NA", row.names = c(NA,
-3L),
class = c("category", "data.frame")))
expect_identical(as.category(dich, compress = TRUE),
structure(list(`NA` = c(NA, NA, NA)), .Names = "NA", row.names = c(NA,
-3L), class = c("category", "data.frame"))
)
expect_identical(as.category(dich[FALSE, FALSE, drop = FALSE]),
structure(list(`NA` = logical(0)),
.Names = "NA",
row.names = integer(0),
class = c("category",
"data.frame")))
set.seed(123)
dichotomy_matrix = matrix(sample(0:1,40,replace = TRUE,prob=c(.6,.4)),nrow=10)
colnames(dichotomy_matrix) = c("Used product|Milk","Used product|Sugar",
"Used product|Tea","Used product|Coffee")
expect_equal_to_reference(
as.category(dichotomy_matrix),
"rds/category7.rds", update = FALSE
)
expect_equal_to_reference(
as.category(dichotomy_matrix, compress = TRUE),
"rds/category8.rds", update = FALSE
)
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