checkVector(x, strict = FALSE, any.missing = TRUE, all.missing = TRUE,
len = NULL, min.len = NULL, max.len = NULL, unique = FALSE,
names = NULL)assertVector(x, strict = FALSE, any.missing = TRUE, all.missing = TRUE,
len = NULL, min.len = NULL, max.len = NULL, unique = FALSE,
names = NULL, .var.name)
testVector(x, strict = FALSE, any.missing = TRUE, all.missing = TRUE,
len = NULL, min.len = NULL, max.len = NULL, unique = FALSE,
names = NULL)
x. Defaults to a heuristic to determine
the name using deparse and substitute.logical(1)]
May the vector have additional attributes or perform a
check for additional attributes like is.vector?
Default is FALSE which allows e.g. factors orlogical(1)]
Are vectors with missing values allowed? Default is TRUE.logical(1)]
Are vectors with only missing values allowed? Default is TRUE.integer(1)]
Exact expected length of x.integer(1)]
Minimal length of x.integer(1)]
Maximal length of x.logical(1)]
Must all values be unique? Default is FALSE.character(1)]
Check for names. See checkNamed for possible values.
Default is TRUE.
If the check is not successful, assertVector throws an error message,
testVector returns FALSE and checkVector returns
a string with the error message.assertArray,
checkArray, testArray;
assertAtomicVector,
checkAtomicVector,
testAtomicVector;
assertAtomic, checkAtomic,
testAtomic; assertCharacter,
checkCharacter,
testCharacter; assertComplex,
checkComplex, testComplex;
assertDataFrame,
checkDataFrame,
testDataFrame;
assertEnvironment,
checkEnvironment,
testEnvironment;
assertFactor, checkFactor,
testFactor; assertFunction,
checkFunction, testFunction;
assertIntegerish,
checkIntegerish,
testIntegerish;
assertInteger, checkInteger,
testInteger; assertList,
checkList, testList;
assertLogical, checkLogical,
testLogical; assertMatrix,
checkMatrix, testMatrix;
assertNumeric, checkNumeric,
testNumerictestVector(letters, min.len = 1L, any.missing = FALSE)Run the code above in your browser using DataLab