test_that("digi_norm errors if conditions is missing",{
  data(multi_cond_data)

  expect_error(
    digi_norm(data=multi_cond_data, replicates="Sample_id"),
    "`conditions` must be explicitly specified"
  )
})

test_that("digi_norm errors if replicates is missing",{
  data(multi_cond_data)

  expect_error(
    digi_norm(data=multi_cond_data, conditions="Brain_region"),
    "`replicates` must be explicitly specified"
  )
})

test_that("digi_norm returns a digi_norm object",{
  data(multi_cond_data)

  res<-digi_norm(
    data=multi_cond_data,
    conditions="Brain_region",
    replicates="Sample_id",
    weight_resolution=10
  )

  expect_s3_class(res, "digi_norm")
  expect_true(is.data.frame(res))
})

test_that("digi_norm preserves non-expression metadata",{
  data(multi_cond_data)

  res<-digi_norm(
    data=multi_cond_data,
    conditions="Brain_region",
    replicates="Sample_id",
    weight_resolution=10
  )

  expect_identical(res$Sample_id, multi_cond_data$Sample_id)
  expect_identical(res$Brain_region, multi_cond_data$Brain_region)
})

test_that("digi_norm excludes targets specified by weight_zero", {
  data(multi_cond_data)

  res<-digi_norm(
    data=multi_cond_data,
    conditions="Brain_region",
    replicates="Sample_id",
    weight_zero="Mt3",
    weight_resolution=10,
    show_warnings=FALSE
  )

  w<-attr(res, "weights")
  expect_true(all(w["Mt3", ]==0))
})

test_that("digi_norm works with conditions=NULL", {
  data(single_cond_data)

  expect_warning(
      res<-digi_norm(
      data=single_cond_data,
      conditions=NULL,
      replicates="Sample_id",
      weight_resolution = 10
    )
  )

  expect_s3_class(res, "digi_norm")
  expect_true("cond" %in% names(attributes(res)))
  expect_equal(length(levels(attr(res, "cond"))), 1)
})