Nothing
tests/testthat/test-prep_valuelabels_from_data.R
In dataquieR: Data Quality in Epidemiological Research
test_that("prep_datatype_from_data works", {
skip_if_not_installed("withr")
withr::local_options(dataquieR.CONDITIONS_WITH_STACKTRACE = TRUE,
dataquieR.ERRORS_WITH_CALLER = TRUE,
dataquieR.WARNINGS_WITH_CALLER = TRUE,
dataquieR.MESSAGES_WITH_CALLER = TRUE)
expect_message(
prep_valuelabels_from_data(c("Species", "xzy", "Sepal.Width"), iris),
all = TRUE,
regexp =
paste("The following.+resp_vars.+are missing from the",
".+study_data.+Won.t return a type for them:.+xzy.+")
)
expect_error(
prep_valuelabels_from_data(1234, iris),
regexp =
paste(".+resp_vars.+should be missing or give variable",
"names referring the study_data."))
expect_identical(
dataquieR::prep_valuelabels_from_data(tibble::as_tibble(iris)),
dataquieR::prep_valuelabels_from_data(iris))
expect_error(dataquieR::prep_valuelabels_from_data(),
regexp =
"Need study data as a data frame in the argument .+study_data.+")
vl <- dataquieR::prep_valuelabels_from_data(iris)
expect_equal(vl,
list(
VALUE_LABELS = c(
Sepal.Length = NA,
Sepal.Width = NA,
Petal.Length = NA,
Petal.Width = NA,
Species = "1 = setosa | 2 = versicolor | 3 = virginica"
),
ModifiedStudyData = structure(
list(
Sepal.Length = c(
5.1,
4.9,
4.7,
4.6,
5,
5.4,
4.6,
5,
4.4,
4.9,
5.4,
4.8,
4.8,
4.3,
5.8,
5.7,
5.4,
5.1,
5.7,
5.1,
5.4,
5.1,
4.6,
5.1,
4.8,
5,
5,
5.2,
5.2,
4.7,
4.8,
5.4,
5.2,
5.5,
4.9,
5,
5.5,
4.9,
4.4,
5.1,
5,
4.5,
4.4,
5,
5.1,
4.8,
5.1,
4.6,
5.3,
5,
7,
6.4,
6.9,
5.5,
6.5,
5.7,
6.3,
4.9,
6.6,
5.2,
5,
5.9,
6,
6.1,
5.6,
6.7,
5.6,
5.8,
6.2,
5.6,
5.9,
6.1,
6.3,
6.1,
6.4,
6.6,
6.8,
6.7,
6,
5.7,
5.5,
5.5,
5.8,
6,
5.4,
6,
6.7,
6.3,
5.6,
5.5,
5.5,
6.1,
5.8,
5,
5.6,
5.7,
5.7,
6.2,
5.1,
5.7,
6.3,
5.8,
7.1,
6.3,
6.5,
7.6,
4.9,
7.3,
6.7,
7.2,
6.5,
6.4,
6.8,
5.7,
5.8,
6.4,
6.5,
7.7,
7.7,
6,
6.9,
5.6,
7.7,
6.3,
6.7,
7.2,
6.2,
6.1,
6.4,
7.2,
7.4,
7.9,
6.4,
6.3,
6.1,
7.7,
6.3,
6.4,
6,
6.9,
6.7,
6.9,
5.8,
6.8,
6.7,
6.7,
6.3,
6.5,
6.2,
5.9
),
Sepal.Width = c(
3.5,
3,
3.2,
3.1,
3.6,
3.9,
3.4,
3.4,
2.9,
3.1,
3.7,
3.4,
3,
3,
4,
4.4,
3.9,
3.5,
3.8,
3.8,
3.4,
3.7,
3.6,
3.3,
3.4,
3,
3.4,
3.5,
3.4,
3.2,
3.1,
3.4,
4.1,
4.2,
3.1,
3.2,
3.5,
3.6,
3,
3.4,
3.5,
2.3,
3.2,
3.5,
3.8,
3,
3.8,
3.2,
3.7,
3.3,
3.2,
3.2,
3.1,
2.3,
2.8,
2.8,
3.3,
2.4,
2.9,
2.7,
2,
3,
2.2,
2.9,
2.9,
3.1,
3,
2.7,
2.2,
2.5,
3.2,
2.8,
2.5,
2.8,
2.9,
3,
2.8,
3,
2.9,
2.6,
2.4,
2.4,
2.7,
2.7,
3,
3.4,
3.1,
2.3,
3,
2.5,
2.6,
3,
2.6,
2.3,
2.7,
3,
2.9,
2.9,
2.5,
2.8,
3.3,
2.7,
3,
2.9,
3,
3,
2.5,
2.9,
2.5,
3.6,
3.2,
2.7,
3,
2.5,
2.8,
3.2,
3,
3.8,
2.6,
2.2,
3.2,
2.8,
2.8,
2.7,
3.3,
3.2,
2.8,
3,
2.8,
3,
2.8,
3.8,
2.8,
2.8,
2.6,
3,
3.4,
3.1,
3,
3.1,
3.1,
3.1,
2.7,
3.2,
3.3,
3,
2.5,
3,
3.4,
3
),
Petal.Length = c(
1.4,
1.4,
1.3,
1.5,
1.4,
1.7,
1.4,
1.5,
1.4,
1.5,
1.5,
1.6,
1.4,
1.1,
1.2,
1.5,
1.3,
1.4,
1.7,
1.5,
1.7,
1.5,
1,
1.7,
1.9,
1.6,
1.6,
1.5,
1.4,
1.6,
1.6,
1.5,
1.5,
1.4,
1.5,
1.2,
1.3,
1.4,
1.3,
1.5,
1.3,
1.3,
1.3,
1.6,
1.9,
1.4,
1.6,
1.4,
1.5,
1.4,
4.7,
4.5,
4.9,
4,
4.6,
4.5,
4.7,
3.3,
4.6,
3.9,
3.5,
4.2,
4,
4.7,
3.6,
4.4,
4.5,
4.1,
4.5,
3.9,
4.8,
4,
4.9,
4.7,
4.3,
4.4,
4.8,
5,
4.5,
3.5,
3.8,
3.7,
3.9,
5.1,
4.5,
4.5,
4.7,
4.4,
4.1,
4,
4.4,
4.6,
4,
3.3,
4.2,
4.2,
4.2,
4.3,
3,
4.1,
6,
5.1,
5.9,
5.6,
5.8,
6.6,
4.5,
6.3,
5.8,
6.1,
5.1,
5.3,
5.5,
5,
5.1,
5.3,
5.5,
6.7,
6.9,
5,
5.7,
4.9,
6.7,
4.9,
5.7,
6,
4.8,
4.9,
5.6,
5.8,
6.1,
6.4,
5.6,
5.1,
5.6,
6.1,
5.6,
5.5,
4.8,
5.4,
5.6,
5.1,
5.1,
5.9,
5.7,
5.2,
5,
5.2,
5.4,
5.1
),
Petal.Width = c(
0.2,
0.2,
0.2,
0.2,
0.2,
0.4,
0.3,
0.2,
0.2,
0.1,
0.2,
0.2,
0.1,
0.1,
0.2,
0.4,
0.4,
0.3,
0.3,
0.3,
0.2,
0.4,
0.2,
0.5,
0.2,
0.2,
0.4,
0.2,
0.2,
0.2,
0.2,
0.4,
0.1,
0.2,
0.2,
0.2,
0.2,
0.1,
0.2,
0.2,
0.3,
0.3,
0.2,
0.6,
0.4,
0.3,
0.2,
0.2,
0.2,
0.2,
1.4,
1.5,
1.5,
1.3,
1.5,
1.3,
1.6,
1,
1.3,
1.4,
1,
1.5,
1,
1.4,
1.3,
1.4,
1.5,
1,
1.5,
1.1,
1.8,
1.3,
1.5,
1.2,
1.3,
1.4,
1.4,
1.7,
1.5,
1,
1.1,
1,
1.2,
1.6,
1.5,
1.6,
1.5,
1.3,
1.3,
1.3,
1.2,
1.4,
1.2,
1,
1.3,
1.2,
1.3,
1.3,
1.1,
1.3,
2.5,
1.9,
2.1,
1.8,
2.2,
2.1,
1.7,
1.8,
1.8,
2.5,
2,
1.9,
2.1,
2,
2.4,
2.3,
1.8,
2.2,
2.3,
1.5,
2.3,
2,
2,
1.8,
2.1,
1.8,
1.8,
1.8,
2.1,
1.6,
1.9,
2,
2.2,
1.5,
1.4,
2.3,
2.4,
1.8,
1.8,
2.1,
2.4,
2.3,
1.9,
2.3,
2.5,
2.3,
1.9,
2,
2.3,
1.8
),
Species = 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,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L
)
),
row.names = c(NA,-150L),
class = "data.frame"
)
))
})
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test_that("prep_datatype_from_data works", {
skip_if_not_installed("withr")
withr::local_options(dataquieR.CONDITIONS_WITH_STACKTRACE = TRUE,
dataquieR.ERRORS_WITH_CALLER = TRUE,
dataquieR.WARNINGS_WITH_CALLER = TRUE,
dataquieR.MESSAGES_WITH_CALLER = TRUE)
expect_message(
prep_valuelabels_from_data(c("Species", "xzy", "Sepal.Width"), iris),
all = TRUE,
regexp =
paste("The following.+resp_vars.+are missing from the",
".+study_data.+Won.t return a type for them:.+xzy.+")
)
expect_error(
prep_valuelabels_from_data(1234, iris),
regexp =
paste(".+resp_vars.+should be missing or give variable",
"names referring the study_data."))
expect_identical(
dataquieR::prep_valuelabels_from_data(tibble::as_tibble(iris)),
dataquieR::prep_valuelabels_from_data(iris))
expect_error(dataquieR::prep_valuelabels_from_data(),
regexp =
"Need study data as a data frame in the argument .+study_data.+")
vl <- dataquieR::prep_valuelabels_from_data(iris)
expect_equal(vl,
list(
VALUE_LABELS = c(
Sepal.Length = NA,
Sepal.Width = NA,
Petal.Length = NA,
Petal.Width = NA,
Species = "1 = setosa | 2 = versicolor | 3 = virginica"
),
ModifiedStudyData = structure(
list(
Sepal.Length = c(
5.1,
4.9,
4.7,
4.6,
5,
5.4,
4.6,
5,
4.4,
4.9,
5.4,
4.8,
4.8,
4.3,
5.8,
5.7,
5.4,
5.1,
5.7,
5.1,
5.4,
5.1,
4.6,
5.1,
4.8,
5,
5,
5.2,
5.2,
4.7,
4.8,
5.4,
5.2,
5.5,
4.9,
5,
5.5,
4.9,
4.4,
5.1,
5,
4.5,
4.4,
5,
5.1,
4.8,
5.1,
4.6,
5.3,
5,
7,
6.4,
6.9,
5.5,
6.5,
5.7,
6.3,
4.9,
6.6,
5.2,
5,
5.9,
6,
6.1,
5.6,
6.7,
5.6,
5.8,
6.2,
5.6,
5.9,
6.1,
6.3,
6.1,
6.4,
6.6,
6.8,
6.7,
6,
5.7,
5.5,
5.5,
5.8,
6,
5.4,
6,
6.7,
6.3,
5.6,
5.5,
5.5,
6.1,
5.8,
5,
5.6,
5.7,
5.7,
6.2,
5.1,
5.7,
6.3,
5.8,
7.1,
6.3,
6.5,
7.6,
4.9,
7.3,
6.7,
7.2,
6.5,
6.4,
6.8,
5.7,
5.8,
6.4,
6.5,
7.7,
7.7,
6,
6.9,
5.6,
7.7,
6.3,
6.7,
7.2,
6.2,
6.1,
6.4,
7.2,
7.4,
7.9,
6.4,
6.3,
6.1,
7.7,
6.3,
6.4,
6,
6.9,
6.7,
6.9,
5.8,
6.8,
6.7,
6.7,
6.3,
6.5,
6.2,
5.9
),
Sepal.Width = c(
3.5,
3,
3.2,
3.1,
3.6,
3.9,
3.4,
3.4,
2.9,
3.1,
3.7,
3.4,
3,
3,
4,
4.4,
3.9,
3.5,
3.8,
3.8,
3.4,
3.7,
3.6,
3.3,
3.4,
3,
3.4,
3.5,
3.4,
3.2,
3.1,
3.4,
4.1,
4.2,
3.1,
3.2,
3.5,
3.6,
3,
3.4,
3.5,
2.3,
3.2,
3.5,
3.8,
3,
3.8,
3.2,
3.7,
3.3,
3.2,
3.2,
3.1,
2.3,
2.8,
2.8,
3.3,
2.4,
2.9,
2.7,
2,
3,
2.2,
2.9,
2.9,
3.1,
3,
2.7,
2.2,
2.5,
3.2,
2.8,
2.5,
2.8,
2.9,
3,
2.8,
3,
2.9,
2.6,
2.4,
2.4,
2.7,
2.7,
3,
3.4,
3.1,
2.3,
3,
2.5,
2.6,
3,
2.6,
2.3,
2.7,
3,
2.9,
2.9,
2.5,
2.8,
3.3,
2.7,
3,
2.9,
3,
3,
2.5,
2.9,
2.5,
3.6,
3.2,
2.7,
3,
2.5,
2.8,
3.2,
3,
3.8,
2.6,
2.2,
3.2,
2.8,
2.8,
2.7,
3.3,
3.2,
2.8,
3,
2.8,
3,
2.8,
3.8,
2.8,
2.8,
2.6,
3,
3.4,
3.1,
3,
3.1,
3.1,
3.1,
2.7,
3.2,
3.3,
3,
2.5,
3,
3.4,
3
),
Petal.Length = c(
1.4,
1.4,
1.3,
1.5,
1.4,
1.7,
1.4,
1.5,
1.4,
1.5,
1.5,
1.6,
1.4,
1.1,
1.2,
1.5,
1.3,
1.4,
1.7,
1.5,
1.7,
1.5,
1,
1.7,
1.9,
1.6,
1.6,
1.5,
1.4,
1.6,
1.6,
1.5,
1.5,
1.4,
1.5,
1.2,
1.3,
1.4,
1.3,
1.5,
1.3,
1.3,
1.3,
1.6,
1.9,
1.4,
1.6,
1.4,
1.5,
1.4,
4.7,
4.5,
4.9,
4,
4.6,
4.5,
4.7,
3.3,
4.6,
3.9,
3.5,
4.2,
4,
4.7,
3.6,
4.4,
4.5,
4.1,
4.5,
3.9,
4.8,
4,
4.9,
4.7,
4.3,
4.4,
4.8,
5,
4.5,
3.5,
3.8,
3.7,
3.9,
5.1,
4.5,
4.5,
4.7,
4.4,
4.1,
4,
4.4,
4.6,
4,
3.3,
4.2,
4.2,
4.2,
4.3,
3,
4.1,
6,
5.1,
5.9,
5.6,
5.8,
6.6,
4.5,
6.3,
5.8,
6.1,
5.1,
5.3,
5.5,
5,
5.1,
5.3,
5.5,
6.7,
6.9,
5,
5.7,
4.9,
6.7,
4.9,
5.7,
6,
4.8,
4.9,
5.6,
5.8,
6.1,
6.4,
5.6,
5.1,
5.6,
6.1,
5.6,
5.5,
4.8,
5.4,
5.6,
5.1,
5.1,
5.9,
5.7,
5.2,
5,
5.2,
5.4,
5.1
),
Petal.Width = c(
0.2,
0.2,
0.2,
0.2,
0.2,
0.4,
0.3,
0.2,
0.2,
0.1,
0.2,
0.2,
0.1,
0.1,
0.2,
0.4,
0.4,
0.3,
0.3,
0.3,
0.2,
0.4,
0.2,
0.5,
0.2,
0.2,
0.4,
0.2,
0.2,
0.2,
0.2,
0.4,
0.1,
0.2,
0.2,
0.2,
0.2,
0.1,
0.2,
0.2,
0.3,
0.3,
0.2,
0.6,
0.4,
0.3,
0.2,
0.2,
0.2,
0.2,
1.4,
1.5,
1.5,
1.3,
1.5,
1.3,
1.6,
1,
1.3,
1.4,
1,
1.5,
1,
1.4,
1.3,
1.4,
1.5,
1,
1.5,
1.1,
1.8,
1.3,
1.5,
1.2,
1.3,
1.4,
1.4,
1.7,
1.5,
1,
1.1,
1,
1.2,
1.6,
1.5,
1.6,
1.5,
1.3,
1.3,
1.3,
1.2,
1.4,
1.2,
1,
1.3,
1.2,
1.3,
1.3,
1.1,
1.3,
2.5,
1.9,
2.1,
1.8,
2.2,
2.1,
1.7,
1.8,
1.8,
2.5,
2,
1.9,
2.1,
2,
2.4,
2.3,
1.8,
2.2,
2.3,
1.5,
2.3,
2,
2,
1.8,
2.1,
1.8,
1.8,
1.8,
2.1,
1.6,
1.9,
2,
2.2,
1.5,
1.4,
2.3,
2.4,
1.8,
1.8,
2.1,
2.4,
2.3,
1.9,
2.3,
2.5,
2.3,
1.9,
2,
2.3,
1.8
),
Species = 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,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
1L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
2L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L,
3L
)
),
row.names = c(NA,-150L),
class = "data.frame"
)
))
})
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