# # This cannot be tested with Travis or CRAN
# # For personal use only
# library(DivNet)
# context("Test parallelisation")
#
# set.seed(1)
# my_counts <- matrix(rpois(30, lambda=10), nrow = 6)
# my_counts
# my_covariate <- cbind(1, rep(c(0,1), each = 3), rep(c(0,1), 3))
# my_covariate
#
# # This cannot be tested with Travis or CRAN
# #
# test_that("parallel works", {
# expect_is(divnet(my_counts, my_covariate,
# variance="parametric",
# nsub = 3, B = 2, ncores = 4,
# tuning="test"), "list")
# expect_is(divnet(my_counts, my_covariate,
# variance="nonparametric", ncores = 4,
# nsub = 3, B = 2, tuning="test"), "list")
#
# expect_is(phylodivnet(lp,
# "type",
# c("t1.txt", "t2.txt"),
# ncores = 4,
# tuning = "test",
# B = 2),
# "list")
# })
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