checkScalar(x, na.ok = FALSE, null.ok = FALSE)
check_scalar(x, na.ok = FALSE, null.ok = FALSE)
assertScalar(x, na.ok = FALSE, null.ok = FALSE, .var.name = vname(x), add = NULL)
assert_scalar(x, na.ok = FALSE, null.ok = FALSE, .var.name = vname(x), add = NULL)
testScalar(x, na.ok = FALSE, null.ok = FALSE)
test_scalar(x, na.ok = FALSE, null.ok = FALSE)
expect_scalar(x, na.ok = FALSE, null.ok = FALSE, info = NULL, label = vname(x))
logical(1)
]
Are missing values allowed? Default is FALSE
.logical(1)
]
If set to TRUE
, x
may also be NULL
.
In this case only a type check of x
is performed, all additional checks are disabled.character(1)
]
Name of the checked object to print in assertions. Defaults to
the heuristic implemented in vname
.AssertCollection
]
Collection to store assertion messages. See AssertCollection
.expect_that
.character(1)
]
Name of the checked object to print in messages. Defaults to
the heuristic implemented in vname
.TRUE
. If the check
is not successful, assertScalar
/assert_scalar
throws an error message, testScalar
/test_scalar
returns FALSE
,
and checkScalar
returns a string with the error message.
The function expect_scalar
always returns an
expectation
.
NA
, NA_integer_
, NA_real_
, NA_complex_
NA_character_
and NaN
.
checkCount
,
checkFlag
, checkInt
,
checkScalarNA
, checkString
testScalar(1)
testScalar(1:10)
Run the code above in your browser using DataLab