tests/testthat/test-class_adaptmle.R

In wilsoncai1992/adaptest: Data-Adaptive Statistics for High-Dimensional Multiple Testing

context("adaptmle S4 class.")
library(airway)
data(airway)

################################################################################
## SETUP TESTS #################################################################
################################################################################

example_adaptmle_class <- function(se, n_top = 20, n_fold = 10) {
  call <- match.call(expand.dots = TRUE)
  adaptmle <- .adaptmle(
    SummarizedExperiment::SummarizedExperiment(
      assays = SummarizedExperiment::assay(se),
      colData = SummarizedExperiment::colData(se)
    ),
    call = call,
    folds = list(), # folds (from origami)
    plot_ingredients = list(), # top_colname
    diff_exp = as.numeric(rep(NaN, n_top)), # DE
    p_value = as.numeric(rep(NaN, n_top)), # p_value
    q_value = as.numeric(rep(NaN, n_top)), # q_value
    q_sig = as.numeric(rep(NaN, n_top)), # significant_q
    q_sig_names = list(), # top_colname_significant_q
    rank_mean = as.numeric(rep(NaN, n_top * n_fold)), # mean_rank_top
    prob_top = as.numeric(rep(NaN, n_top * n_fold)), # prob_in_top
    top_index = as.numeric(rep(NaN, n_top * n_fold)) # top_index
  )
  return(adaptmle)
}

adaptmle <- example_adaptmle_class(se = airway)

################################################################################
## BEGIN TESTS #################################################################
################################################################################

test_that("adaptmle object is of class type S4", {
  expect_equivalent(typeof(adaptmle), "S4")
})

test_that("adaptmle object is of appropriate class", {
  expect_equivalent(class(adaptmle), "adapTMLE")
})

test_that("adaptmle is a subclass of SummarizedExperiment", {
  expect_is(adaptmle, "SummarizedExperiment")
})