context("Tip Helpers")
test_that("get_limiting_bound() errors if not significant", {
expect_error(
get_limiting_bound(lb = .9, ub = 1.1),
"Please input a significant result"
)
expect_error(
get_limiting_bound(lb = 1.1, ub = .9),
"Please input a significant result"
)
expect_error(
get_limiting_bound(lb = 1, ub = 1.1),
"Please input a significant result"
)
expect_error(
get_limiting_bound(lb = 1, ub = 1),
"Please input a significant result"
)
expect_error(
get_limiting_bound(),
"Please input a dataset `d`"
)
})
test_that("get_limiting_bound() errors if lb or ub < 0", {
expect_error(get_limiting_bound(lb = .9, ub = -1))
expect_error(get_limiting_bound(lb = -1, ub = .9))
expect_error(get_limiting_bound(lb = -1, ub = -1))
})
test_that("get_limiting_bound() gives correct bound", {
expect_equivalent(get_limiting_bound(lb = 1.1, ub = 1.2), 1.1)
expect_equivalent(get_limiting_bound(lb = 0.8, ub = 0.9), 0.9)
expect_equivalent(get_limiting_bound(lb = 1.1, ub = 1.1), 1.1)
})
test_that("tip_gamma() errors when necessary", {
expect_error(
tip_gamma(p0 = -1, p1 = 1),
"The prevalences entered must be between 0 and 1"
)
expect_error(
tip_gamma(p0 = 1, p1 = -1),
"The prevalences entered must be between 0 and 1"
)
})
test_that("tip_gamma() returns correct result", {
expect_identical(tip_gamma(p0 = 0, p1 = 1, b = 1.2), 1.2)
expect_identical(tip_gamma(p0 = 0, p1 = 1, b = .8), .8)
expect_identical(tip_gamma(p0 = 1, p1 = 0, b = 1.2), 1 / 1.2)
expect_error(
tip_gamma(p0 = .5, p1 = .2, b = 5),
"there does not exist an unmeasured"
)
})
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