Nothing
test_that("eff_wts", {
# make coin
# build example coin
coin <- build_example_coin(up_to = "new_coin", quietly = TRUE)
# get effective weights as data frame
w_eff <- get_eff_weights(coin, out2 = "df")
expect_s3_class(w_eff, "data.frame")
# expect that all sum to 1 at each level
wsums <- tapply(w_eff$EffWeight, w_eff$Level, sum)
expect_equal(as.numeric(wsums), rep(1, 4))
# append to coin
coin <- get_eff_weights(coin, out2 = "coin")
expect_s3_class(coin, "coin")
})
test_that("opt_weights", {
# build example coin
coin <- build_example_coin(quietly = TRUE)
# optimise weights at level 3
l_opt <- get_opt_weights(coin, itarg = "equal", dset = "Aggregated",
Level = 3, out2 = "list")
# expect normalised results to be equal
expect_equal(round(l_opt$CorrResultsNorm$Obtained, 2),
c(0.5, 0.5))
coin <- get_opt_weights(coin, itarg = "equal", dset = "Aggregated",
Level = 3, weights_to = "OptLev3", out2 = "coin")
expect_s3_class(coin, "coin")
# new situation with unequal influence (one twice as much as the other)
l_opt <- get_opt_weights(coin, itarg = c(1,2), dset = "Aggregated",
Level = 3, weights_to = "OptLev3", out2 = "list", toler = 0.01)
expect_equal(round(l_opt$CorrResultsNorm$Obtained, 2),
c(0.33, 0.67))
})
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