Nothing
# library(dplyr)
# library(reshape2)
##TODO:
test_that("compute_U", {
load(test_path("testdata", "ce.RData"))
# single wtp
# c_tmp <- matrix(c(0, 0, 100, 10), nrow = 2)
# e_tmp <- matrix(c(0, 0, 1, -2), nrow = 2)
#
# res <-
# bcea(e = e_tmp,
# c = c_tmp, k = 5)
#
# k <- 5
# n_comparisons <- 1
# delta_e <- c(-1, 2)
# delta_c <- c(-100, -10) # this actually a saving for intervention
# n_sim <- 2
#
# ib_1 <- k*delta_e[1] - delta_c[1] # 5*(-1) - (-100) = 95
# ib_2 <- k*delta_e[2] - delta_c[2] # 5*2 - (-10) = 20
#
# expect_equivalent(c(ib_1, ib_2), res$ib)
#
#
# # multiple wtp
#
# k <- c(5, 10)
# K <- 2
#
# res <-
# bcea(e = e_tmp,
# c = c_tmp, k = k)
#
# ib_1 <- k*delta_e[1] - delta_c[1] # 95, 10*(-1) - (-100) = 90
# ib_2 <- k*delta_e[2] - delta_c[2] # 20, 10*2 - (-10) = 30
#
# expect_equivalent(cbind(ib_1, ib_2), drop(res$ib))
#
#
# # multiple comparisons
#
# c_tmp <- matrix(c(0, 0, 100, 10, 0, 1), nrow = 2)
# e_tmp <- matrix(c(0, 0, 1, -2, -3, -4), nrow = 2)
# n_comparisons <- 2
#
# res <-
# bcea(e = e_tmp,
# c = c_tmp, k = k)
#
# # sim x comprison
# delta_e <- matrix(c(-1,3,
# 2,4), nrow = 2, byrow = TRUE)
# delta_c <- matrix(c(-100, 0,
# -10, -1), nrow = 2, byrow = TRUE)
#
# ib_11 <- k*delta_e[1,1] - delta_c[1,1] # 15 30
# ib_12 <- k*delta_e[1,2] - delta_c[1,2] # 15 30
# ib_21 <- k*delta_e[2,1] - delta_c[2,1] # 15 30
# ib_22 <- k*delta_e[2,2] - delta_c[2,2] # 21 41
#
# expect_equivalent(cbind(ib_11, ib_21), res$ib[,,1 ])
# expect_equivalent(cbind(ib_12, ib_22), res$ib[,,2 ])
})
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