Learn R Programming

assertive.numbers (version 0.0-2)

assert_all_numbers_are_whole_numbers: Is the input a whole number?

Description

Checks that the (probably floating point) input is a whole number.

Usage

assert_all_numbers_are_whole_numbers(x, tol = 100 * .Machine$double.eps, na_ignore = FALSE, severity = getOption("assertive.severity", "stop"))
assert_any_numbers_are_whole_numbers(x, tol = 100 * .Machine$double.eps, na_ignore = FALSE, severity = getOption("assertive.severity", "stop"))
assert_all_are_whole_numbers(x, tol = 100 * .Machine$double.eps, na_ignore = FALSE, severity = getOption("assertive.severity", "stop"))
assert_any_are_whole_numbers(x, tol = 100 * .Machine$double.eps, na_ignore = FALSE, severity = getOption("assertive.severity", "stop"))
is_whole_number(x, tol = 100 * .Machine$double.eps, .xname = get_name_in_parent(x))

Arguments

x
Input to check.
tol
Differences smaller than tol are not considered.
na_ignore
A logical value. If FALSE, NA values cause an error; otherwise they do not. Like na.rm in many stats package functions, except that the position of the failing values does not change.
severity
How severe should the consequences of the assertion be? Either "stop", "warning", "message", or "none".
.xname
Not intended to be used directly.

Value

TRUE if the input is a whole number.

See Also

is_divisible_by

Examples

Run this code
# 1, plus or minus a very small number
x <- 1 + c(0, .Machine$double.eps, -.Machine$double.neg.eps)
# By default, you get a bit of tolerance for rounding errors
is_whole_number(x)
# Set the tolerance to zero for exact matching.
is_whole_number(x, tol = 0)

Run the code above in your browser using DataLab