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test_that("n.show arg has an effect in plotFilterValues()", {
set.seed(getOption("mlr.debug.seed"))
fv = generateFilterValuesData(iris.task, method = "variance")
fv_plot = plotFilterValues(fv, n.show = 2)
vdiffr::expect_doppelganger("n.show", fv_plot)
})
test_that("feat.type.cols arg has an effect in plotFilterValues()", {
set.seed(getOption("mlr.debug.seed"))
fv = generateFilterValuesData(bh.task, method = "praznik_CMIM")
fv_plot1 = plotFilterValues(fv, feat.type.cols = TRUE)
vdiffr::expect_doppelganger("feat.type.cols", fv_plot1)
})
test_that("plotFilterValues shows the correct count when n.show > nfeat", {
set.seed(getOption("mlr.debug.seed"))
fv = generateFilterValuesData(bh.task, method = "praznik_CMIM")
fv_plot2 = plotFilterValues(fv, n.show = 25)
vdiffr::expect_doppelganger("n.show > nfeat", fv_plot2)
})
test_that("plotFilterValues errors if arg 'filter' is not avail", {
set.seed(getOption("mlr.debug.seed"))
fv = generateFilterValuesData(bh.task, method = "praznik_CMIM")
expect_error(plotFilterValues(fv, filter = "foo"))
})
test_that("plotFilterValues errors if arg 'filter' is not avail", {
set.seed(getOption("mlr.debug.seed"))
fv = generateFilterValuesData(iris.task, method = c("variance", "praznik_CMIM"))
expect_error(plotFilterValues(fv))
})
test_that("plotFilterValues arg 'filter' works", {
set.seed(getOption("mlr.debug.seed"))
fv = generateFilterValuesData(iris.task, method = c("variance", "praznik_CMIM"))
fv_plot3 = plotFilterValues(fv, filter = "variance")
vdiffr::expect_doppelganger("filter argument", fv_plot3)
})
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