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library(bayesplot)
context("Example draws")
test_that("example_mcmc_draws throws correct errors", {
expect_error(example_mcmc_draws(chains = 5), "chains <= 4")
expect_error(example_mcmc_draws(chains = 0), "chains >= 1")
expect_error(example_mcmc_draws(params = 7), "params <= 6")
expect_error(example_mcmc_draws(params = 0), "params >= 1")
})
test_that("example_mcmc_draws returns correct structure", {
expect_identical(dim(example_mcmc_draws()),
c(250L, 4L, 4L))
expect_identical(dim(example_mcmc_draws(chains = 1, params = 6)),
c(250L, 6L))
expect_identical(dim(example_mcmc_draws(params = 1)),
c(250L, 4L, 1L))
expect_identical(dimnames(example_mcmc_draws(4, 6))[[3]],
c("alpha", "sigma", paste0("beta[", 1:4,"]")))
})
test_that("example ppc data works", {
y <- example_y_data()
expect_type(y, "integer")
expect_true(is_vector_or_1Darray(y))
yrep <- example_yrep_draws()
expect_type(yrep, "double")
expect_is(yrep, "matrix")
expect_equal(ncol(yrep), length(y))
group <- example_group_data()
expect_s3_class(group, "factor")
expect_equal(length(group), length(y))
x <- example_x_data()
expect_type(x, "double")
expect_true(is_vector_or_1Darray(x))
expect_equal(length(x), length(y))
})
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