library(threshold_analysis)
context('Normalizers')
normalizers <- list(standardize,
max.normalizer,
max.min.normalizer,
q.min.normalizer)
test_that('Normalizers work for edge cases', {
zero.vector <- c() # Empty input
one.vector <- c(0) # Length one input
two.vector <- c(0, 0) # Length n input with only one unique value
zero.test <- lapply(normalizers,
function(f){
expect_equals(zero.vector, f(zero.vector))
expect_equals(one.vector, f(one.vector))
expect_equals(two.vector, f(two.vector))
})
})
test_that('Normalizers work for normal cases', {
test.positive <- c(1, 1, 1, 2)
test.negative <- c(-1, -2, -3)
test.mixed <- c(1, -2)
expect_equals(c(-1, -1, -1, 1), standardize(test.positive))
expect_equals(c(0.5, 0.5, 0.5, 1), max.normalizer(test.positive))
expect_equals(c(0, 0, 0, 1), max.min.normalizer(test.positive))
expect_equals(c(0, 0, 0, 1), q.min.normalizer(test.positive))
# Need more test cases
})
context('Miscellaneous Utils')
context('Distributions')
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