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library(bayesplot)
context("Extractors")
if (requireNamespace("rstanarm", quietly = TRUE)) {
ITER <- 1000
CHAINS <- 3
fit <- rstanarm::stan_glm(mpg ~ wt + am, data = mtcars,
iter = ITER, chains = CHAINS,
refresh = 0)
}
x <- list(cbind(a = 1:3, b = rnorm(3)), cbind(a = 1:3, b = rnorm(3)))
# nuts_params and log_posterior methods -----------------------------------
test_that("nuts_params.list throws errors", {
x[[3]] <- c(a = 1:3, b = rnorm(3))
expect_error(nuts_params.list(x), "list elements should be matrices")
x[[3]] <- cbind(a = 1:3, d = rnorm(3))
expect_error(nuts_params.list(x), "same column names")
x[[3]] <- cbind(a = 1:4, b = rnorm(4))
expect_error(nuts_params.list(x), "same dimensions")
})
test_that("nuts_params.list parameter selection ok", {
expect_error(nuts_params.list(x, pars = "apple"), "subscript out of bounds")
np <- nuts_params.list(x, pars = "b")
expect_true(all(np$Parameter == "b"))
})
test_that("all nuts_params methods identical", {
skip_if_not_installed("rstanarm")
skip_if_not_installed("rstan")
expect_identical(
nuts_params(fit),
nuts_params(fit$stanfit)
)
expect_identical(
nuts_params(fit),
nuts_params(rstan::get_sampler_params(fit$stanfit, inc_warmup = FALSE))
)
})
test_that("nuts_params.stanreg returns correct structure", {
skip_if_not_installed("rstanarm")
np <- nuts_params(fit)
expect_identical(colnames(np), c("Chain", "Iteration", "Parameter", "Value"))
np_names <- paste0(c("accept_stat", "stepsize", "treedepth", "n_leapfrog",
"divergent", "energy"), "__")
expect_identical(levels(np$Parameter), np_names)
expect_equal(length(unique(np$Iteration)), floor(ITER / 2))
expect_equal(length(unique(np$Chain)), CHAINS)
})
test_that("log_posterior.stanreg returns correct structure", {
skip_if_not_installed("rstanarm")
lp <- log_posterior(fit)
expect_identical(colnames(lp), c("Chain", "Iteration", "Value"))
expect_equal(length(unique(lp$Iteration)), floor(ITER / 2))
expect_equal(length(unique(lp$Chain)), CHAINS)
})
test_that("rhat.stanreg returns correct structure", {
skip_if_not_installed("rstanarm")
r <- rhat(fit)
expect_named(r)
expect_equal(r, summary(fit)[1:length(r), "Rhat"])
expect_identical(names(rhat(fit, regex_pars = c("wt", "am"))),
c("wt", "am"))
})
test_that("neff_ratio.stanreg returns correct structure", {
skip_if_not_installed("rstanarm")
expect_named(neff_ratio(fit, pars = c("wt", "am")), c("wt", "am"))
ratio <- neff_ratio(fit)
expect_named(ratio)
ans <- summary(fit)[1:length(ratio), "n_eff"] / (floor(ITER / 2) * CHAINS)
expect_equal(ratio, ans, tol = 0.001)
})
test_that("rhat.stanfit returns correct structure", {
skip_if_not_installed("rstanarm")
r <- rhat(fit$stanfit)
expect_named(r)
expect_equal(r, summary(fit)[, "Rhat"])
r2 <- rhat(fit$stanfit, pars = c("wt", "sigma"))
expect_named(r2)
expect_equal(r2, summary(fit, pars = c("wt", "sigma"))[, "Rhat"])
})
test_that("neff_ratio.stanreg returns correct structure", {
skip_if_not_installed("rstanarm")
denom <- floor(ITER / 2) * CHAINS
ratio <- neff_ratio(fit$stanfit)
expect_named(ratio)
ans <- summary(fit)[, "n_eff"] / denom
expect_equal(ratio, ans, tol = 0.001)
ratio2 <- neff_ratio(fit$stanfit, pars = c("wt", "sigma"))
expect_named(ratio2)
ans2 <- summary(fit, pars = c("wt", "sigma"))[, "n_eff"] / denom
expect_equal(ratio2, ans2, tol = 0.001)
})
test_that("cmdstanr methods work", {
skip_on_cran()
skip_if_not_installed("cmdstanr")
fit <- cmdstanr::cmdstanr_example("logistic", iter_sampling = 500, chains = 2)
np <- nuts_params(fit)
np_names <- paste0(c("treedepth", "divergent", "energy", "accept_stat", "stepsize", "n_leapfrog"), "__")
expect_identical(levels(np$Parameter), np_names)
expect_equal(range(np$Iteration), c(1, 500))
expect_equal(range(np$Chain), c(1, 2))
expect_true(all(np$Value[np$Parameter == "divergent__"] == 0))
lp <- log_posterior(fit)
expect_named(lp, c("Chain", "Iteration", "Value"))
expect_equal(range(np$Chain), c(1, 2))
expect_equal(range(np$Iteration), c(1, 500))
r <- rhat(fit)
expect_named(head(r, 4), c("alpha", "beta[1]", "beta[2]", "beta[3]"))
expect_true(all(round(r) == 1))
ratio <- neff_ratio(fit)
expect_named(head(ratio, 4), c("alpha", "beta[1]", "beta[2]", "beta[3]"))
expect_true(all(ratio > 0))
})
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