Nothing
# testthat for gg_partial_coplot function
context("gg_partial_coplot tests")
test_that("gg_error classifications", {
data(Boston, package = "MASS")
# Unless we are on the same version as Travis-CI,
# we need to build rather than cache the rfsrc
rfsrc_boston <- rfsrc(
medv ~ .,
data = Boston,
importance = "none",
nsplit = 5,
forest = TRUE
)
# fast.restore can be added after randomForestSRC V1.6 release
# Find the rm variable points to create 6 intervals of roughly
# equal size population
rm_pts <-
quantile_pts(rfsrc_boston$xvar$rm,
groups = 3,
intervals = TRUE)
# Pass these variable points to create the 6 (factor) intervals
rm_grp <- cut(rfsrc_boston$xvar$rm, breaks = rm_pts)
# This is the expensive part.
partial_coplot_boston <-
gg_partial_coplot(
rfsrc_boston,
xvar = "lstat",
groups = rm_grp,
show.plots = FALSE,
npts = 5
)
expect_is(partial_coplot_boston, "gg_partial_coplot")
expect_equal(ncol(partial_coplot_boston), 4)
expect_equal(length(unique(partial_coplot_boston$group)), 3)
expect_error(gg_partial_coplot(
partial_coplot_boston,
xvar = "lstat",
groups = rm_grp,
npts = 5
))
expect_error(gg_partial_coplot(rfsrc_boston, xvar = "lstat",
npts = 5))
rfsrc_boston$forest <- NULL
expect_error(
gg_partial_coplot(
rfsrc_boston,
xvar = "lstat",
groups = rm_grp,
show.plots = FALSE,
npts = 5
)
)
})
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