library(testthat)
test_that(
"Tests that M-RF is working correctly",
{
dir.create("knownTestValues/", showWarnings = FALSE)
context('M-RF')
set.seed(1423614230)
feat <- iris[, -1]
tr <- rbinom(nrow(iris), 1, .5)
yobs <- iris[, 1]
morf <- M_RF(
feat = feat,
tr = tr,
yobs = yobs
)
# expect_equal(EstimateCate(morf, feat)[1], 0.04129601, tolerance = 1e-2)
expect_known_value(EstimateCate(morf, feat),
file = "knownTestValues/testvalues-M_RF1",
tolerance = 1e-1)
CI <- CateCI(theObject = morf,
feature_new = feat,
B = 5,
verbose = FALSE)
expect_known_value(as.numeric(CI[1, ]),
file = "knownTestValues/testvalues-M_RF2",
tolerance = 1e-2)
# expect_equal(as.numeric(CI[1, ]),
# c(0.04244312, -0.07651435, 0.1614006),
# tolerance = 1e-2)
#
set.seed(432)
cate_problem <-
simulate_causal_experiment(
ntrain = 400,
ntest = 100,
dim = 20,
alpha = .1,
feat_distribution = "normal"
)
morf <- M_RF(
feat = cate_problem$feat_tr,
yobs = cate_problem$Yobs_tr,
tr = cate_problem$W_tr)
# expect_equal(mean((
# EstimateCate(morf, cate_problem$feat_te) - cate_problem$tau_te
# ) ^ 2),
# 25.12625,
# tolerance = 1)
expect_known_value(mean((
EstimateCate(morf, cate_problem$feat_te) - cate_problem$tau_te
) ^ 2),
file = "knownTestValues/testvalues-M_RF3",
tolerance = 1)
})
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