context("Cox")


set.seed(10101)
N = 1000
p = 30
nzc = p/3
x = matrix(rnorm(N * p), N, p)
beta = rnorm(nzc)
fx = x[, seq(nzc)] %*% beta/3
hx = exp(fx)
ty = rexp(N, hx)
tcens = rbinom(n = N, prob = 0.3, size = 1)  # censoring indicator
y = cbind(time = ty, status = 1 - tcens)  # y=Surv(ty,1-tcens) with library(survival)

fitc = uniLasso(x, y, family = "cox")
cvfitc = cv.uniLasso(x, y, family = "cox")

objects = enlist(fitc,cvfitc)
###saveRDS(objects, "saved_results/test_Cox.RDS")

expected  <- readRDS("saved_results/test_Cox.RDS")
for (x in names(objects)) {
    cat(sprintf("Testing %s\n", x))
    expect_equal(objects[[x]], expected[[x]])
}