context("remove_outliers")
# mungebit tests
mungebits_loaded <- 'mungebits' %in% loadedNamespaces(); suppressMessages(require(mungebits))
test_that("removes eggregious outliers ", {
vec = runif(min = 0, max = 1, n=20)
vec[10] = 10
df <- data.frame(vec)
mb <- mungebits:::mungebit(remove_outliers)
mp <-mungebits:::mungeplane(df)
mb$run(mp)
expect_that(is.na(mp$data[10, ]), equals(TRUE))
})
test_that("works with negative values ", {
vec = runif(min = 0, max = 1, n = 20)
vec[10] = -10
df <- data.frame(vec)
mb <- mungebits:::mungebit(remove_outliers)
mp <-mungebits:::mungeplane(df)
mb$run(mp)
expect_that(is.na(mp$data[10, ]), equals(TRUE))
})
test_that("will remove outliers based upon TRAIN mean & sd ", {
vec = runif(min = 0, max = 1, n = 20)
vec[10] = 10
df <- data.frame(vec)
mb <- mungebits:::mungebit(remove_outliers)
mp <-mungebits:::mungeplane(df)
mb$run(mp)
mp2 <-mungebits:::mungeplane(data.frame(vec = c(33, 19, 44, 1)))
mb$run(mp2)
expect_that(sum(is.na(mp2$data[, 1])), equals(3)) # all but last value is an outlier
})
test_that("threshold argument works ", {
vec = runif(min = 0, max = 1, n = 20)
vec[10] = -10
df <- data.frame(vec)
mb <- mungebits:::mungebit(remove_outliers)
mp <-mungebits:::mungeplane(df)
mb$run(mp, threshold = 0 ) # will remove all values as the absolute value of all z-scores > 0
expect_that(all(is.na(mp$data[, 1])), equals(TRUE))
})
if (!mungebits_loaded) unloadNamespace('mungebits')
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.