library(dplyr)

test_that("parallisation works as expected", {
    suppressMessages({
        ss <- set_n(
            ssC = 80,
            ssE = 90,
            ssExt = 150
        )

        covset1 <- set_cov(
            n_cat = 2,
            n_cont = 1,
            mu_int = c(0, 0.5, 0.5),
            mu_ext = c(0.7, 0.5, 0.9),
            var = c(1, 1.2, 1),
            cov = c(0.5, 0.7, 0.9),
            prob_int = c(0.45, 0.55),
            prob_ext = c(0.65, 0.55)
        )

        sample_cov <- simu_cov(
            ssObj = ss,
            covObj = covset1,
            HR = c(0.67),
            driftHR = c(1),
            nsim = 4,
            seed = 47
        )

        evt <- set_event(
            event = "weibull",
            shape = 0.9,
            lambdaC = 0.0135,
            beta = 0.5
        )

        c_int <- set_clin(
            gamma = c(2, 3, 16),
            e_itv = c(5, 10),
            CCOD = "fixed-first",
            CCOD_t = 45,
            etaC = c(0.02, 0.03),
            etaE = c(0.2, 0.3),
            d_itv = 2
        )

        c_ext <- set_clin(
            gamma = 10,
            CCOD = "event",
            CCOD_t = 150,
            etaC = 0.05
        )

        sample_time <- simu_time(
            dt = sample_cov,
            eventObj = evt,
            clinInt = c_int,
            clinExt = c_ext,
            seed = 47
        )

        res <- run_mcmc(
            dt = sample_time,
            set_prior(pred = "all", prior = "gamma", r0 = 1,  alpha = c(0, 0)),
            n.chains = 2,
            n.adapt = 100,
            n.burn = 100,
            n.iter = 200,
            seed = 47
        )

        res2 <- run_mcmc_p(
            dt = sample_time,
            set_prior(pred = "all", prior = "gamma", r0 = 1,  alpha = c(0, 0)),
            n.chains = 2,
            n.adapt = 100,
            n.burn = 100,
            n.iter = 200,
            seed = 47,
            n.cores = 2
        )
    })

    expect_equal(res, res2)
})