Nothing
context("Object-oriented Features")
data.table::setDTthreads(2) #only needed for CRAN checks
data(caers)
proc <- processRaw(caers)
theta <- c(3.25280367, 0.39983376, 2.02490400, 1.90726819, 0.06536416)
theta_list <- list(estimates = theta)
obj1 <- ebScores(processed = proc, hyper_estimate = theta_list, quantiles = NULL)
obj2 <- ebScores(processed = proc, hyper_estimate = theta_list)
testthat::test_that("Checking the object's size", {
expect_equal(length(obj1), 2)
expect_equal(length(obj2), 3)
expect_equal(ncol(obj1$data), 7)
expect_equal(ncol(obj2$data), 9)
expect_equal(nrow(obj1$dat), nrow(proc))
expect_equal(nrow(obj2$dat), nrow(proc))
})
testthat::test_that("Checking 'data' column names", {
expect_identical(colnames(obj1$data), c("var1", "var2", "N", "E", "RR", "PRR", "EBGM"))
expect_identical(colnames(obj2$data), c("var1", "var2", "N", "E", "RR", "PRR", "EBGM",
"QUANT_05", "QUANT_95"))
})
proc2 <- proc
names(proc2) <- c("N", "E")
testthat::test_that("do errors for ebScores() get correctly printed?", {
expect_error(ebScores(proc, hyper_estimate = theta_list, quantiles = c("5", "95")),
"'quantiles' must be NULL or a numeric vector of quantiles",
fixed = TRUE)
expect_error(ebScores(proc, hyper_estimate = theta),
"'hyper_estimate' must be the list output by autoHyper()",
fixed = TRUE)
expect_error(ebScores(proc, hyper_estimate = list(estimate = theta)),
"'hyper_estimate' must be a list containing an element of hyperparameter
estimates. Was it actually calculated by autoHyper()?",
fixed = TRUE)
expect_error(ebScores(theta, hyper_estimate = theta_list),
"'processed' must be a data frame from processRaw()",
fixed = TRUE)
expect_error(ebScores(proc2, hyper_estimate = theta_list),
"'processed' dataframe does not have 'var' variables. Was this dataframe
actually created by processRaw()?",
fixed = TRUE)
})
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