Nothing
# test S3 methods in alphabetical order
test_that("as_draws and friends have resonable outputs", {
skip_on_cran()
n_iter <- 200
n_warmup <- 100
n_chains <- 2
suppressMessages(suppressWarnings(
{
withr::with_options(list(RBesT.MC.save_warmup = FALSE), {
set.seed(34563)
map <- gMAP(
cbind(r, n - r) ~ 1 | study,
family = binomial,
data = AS,
tau.dist = "Fixed",
tau.prior = 0.5,
beta.prior = 2,
warmup = n_warmup,
iter = n_iter,
chains = n_chains,
thin = 1
)
})
withr::with_options(list(RBesT.MC.save_warmup = TRUE), {
set.seed(34563)
map_full <- gMAP(
cbind(r, n - r) ~ 1 | study,
family = binomial,
data = AS,
tau.dist = "Fixed",
tau.prior = 0.5,
beta.prior = 2,
warmup = n_warmup,
iter = n_iter,
chains = n_chains,
thin = 1
)
})
}
))
draws <- as_draws(
map,
variable = "theta_resp_pred"
)
expect_s3_class(draws, "draws_list")
expect_equal(
posterior::variables(draws),
"theta_resp_pred"
)
expect_equal(posterior::ndraws(draws), nsamples(map))
draws <- suppressMessages(as_draws_matrix(
map,
variable = "theta_resp_pred"
))
expect_s3_class(draws, "draws_matrix")
expect_equal(
posterior::variables(draws),
"theta_resp_pred"
)
expect_equal(posterior::ndraws(draws), nsamples(map))
draws <- as_draws_array(
map,
variable = "theta_resp_pred"
)
expect_s3_class(draws, "draws_array")
expect_equal(
posterior::variables(draws),
"theta_resp_pred"
)
expect_equal(posterior::ndraws(draws), nsamples(map))
draws <- as_draws_df(
map,
variable = "theta_resp_pred"
)
expect_s3_class(draws, "draws_df")
expect_equal(
posterior::variables(draws),
"theta_resp_pred"
)
expect_equal(posterior::ndraws(draws), nsamples(map))
draws <- as_draws_list(
map,
variable = "theta_resp_pred"
)
expect_s3_class(draws, "draws_list")
expect_equal(
posterior::variables(draws),
"theta_resp_pred"
)
expect_equal(posterior::ndraws(draws), nsamples(map))
draws <- as_draws_rvars(map)
expect_s3_class(draws, "draws_rvars")
expect_true(posterior::nvariables(draws) > 0)
expect_equal(posterior::ndraws(draws), nsamples(map))
n_saved_samples <- sum(map$fit@sim$n_save)
expect_equal(posterior::ndraws(draws), n_saved_samples)
expect_equal(posterior::ndraws(draws), (n_iter - n_warmup) * n_chains)
expect_equal(nsamples(map), (n_iter - n_warmup) * n_chains)
draws_full <- as_draws_rvars(map_full, inc_warmup = TRUE)
expect_s3_class(draws_full, "draws_rvars")
expect_true(posterior::nvariables(draws_full) > 0)
expect_equal(
posterior::ndraws(draws_full),
nsamples(map_full) + n_warmup * n_chains
)
n_saved_samples_full <- sum(map_full$fit@sim$n_save)
expect_equal(posterior::ndraws(draws_full), n_saved_samples_full)
expect_equal(posterior::ndraws(draws_full), n_iter * n_chains)
expect_equal(nsamples(map_full), (n_iter - n_warmup) * n_chains)
})
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