# opportunity loss # library(dplyr) # library(reshape2) test_that("simple data input parameters", { load(test_path("testdata", "ce.RData")) # only one intervention # limiting case U <- array(c(1,1,1, 1,1,1), dim = c(3,2,1)) # sim, k, ints Ustar <- array(c(1,1,1, 1,1,1), dim = c(3,2)) # sim, k # no loss i.e all optimal best <- c(1,1) # k expect_equal( compute_ol(Ustar, U, best), array(c(0,0,0, 0,0,0), dim = c(3,2))) U <- array(c(1,1,1,1,1,1, 0,0,0,0,0,0), dim = c(3,2,2)) Ustar <- array(c(1,1,1, 1,1,1), dim = c(3,2)) # no loss i.e all optimal best <- c(1,1) expect_equal( compute_ol(Ustar, U, best), array(c(0,0,0, 0,0,0), dim = c(3,2))) # all loss best <- c(2,2) expect_equal( compute_ol(Ustar, U, best), array(c(1,1,1, 1,1,1), dim = c(3,2))) }) test_that("call via bcea", { load(test_path("testdata", "ce.RData")) res <- bcea(e = eff, c = cost) ol <- res$ol n_sim <- nrow(cost) expect_equal(dim(ol), c(n_sim, length(res$k))) expect_true(all(ol >= 0)) }) test_that("errors in dimensions", { U <- array(c(1,1,1,1,1,1, 0,0,0,0,0,0), dim = c(3,2,2)) Ustar <- array(c(1,1,1, 1,1,1), dim = c(3,2)) # too long best <- c(1,1,1) expect_error( compute_ol(Ustar, U, best)) # too short best <- 1 expect_error( compute_ol(Ustar, U, best)) # k out of bounds best <- c(0,1) expect_error( compute_ol(Ustar, U, best)) best <- c(1,3) expect_error( compute_ol(Ustar, U, best)) })