# library(celda)
# context("Testing miscellaneous celda functions")
#
# data(celdaCGGridSearchRes)
# celdaCGSim <- simulateCells("celda_CG", K = 5, L = 10)
# modelCG <- celda_CG(
# counts = celdaCGSim$counts,
# sampleLabel = celdaCGSim$sampleLabel,
# K = celdaCGSim$K,
# L = celdaCGSim$L,
# algorithm = "EM",
# verbose = FALSE,
# nchains = 1)
#
# factorized <- factorizeMatrix(celdaMod = modelCG, counts = celdaCGSim$counts)
#
# test_that(desc = "Testing compareCountMatrix with numeric matrix input", {
# # Case from GitHub issue #137
# counts <- celdaCGSim$counts
# storage.mode(counts) <- "numeric"
# expect_true(compareCountMatrix(counts, modelCG, errorOnMismatch = TRUE))
# })
#
# test_that(desc = "Testing appendCeldaList", {
# expect_error(
# appendCeldaList(celdaCGGridSearchRes, matrix(0)),
# "Both parameters to appendCeldaList must be of class celdaList."
# )
# modifiedEgList <- celdaCGGridSearchRes
# modifiedEgList@countChecksum <- "abcd12345"
# expect_warning(
# appendCeldaList(celdaCGGridSearchRes, modifiedEgList),
# paste0("Provided lists have different countChecksums and may have",
# " been generated from different count matrices. Using checksum",
# " from first list..."))
# expect_equal(length(celdaCGGridSearchRes@resList) * 2,
# length(appendCeldaList(celdaCGGridSearchRes,
# celdaCGGridSearchRes)@resList))
# })
# miscellaneous fxns
# functions used internally
test_that(desc = "Invoking error from distinctColors function", {
expect_error(distinctColors(n = 3, hues = "xx"),
paste0("Only color names listed in the 'color' function can be",
" used in 'hues'"))
})
test_that(desc = "Invoking error from sample labels function", {
expect_error(.processSampleLabels("Sample_1", 5),
paste0("'sampleLabel' must be the same length as the number",
" of columns in the 'counts' matrix."))
})
test_that(desc = "Invoking error from .logMessages function", {
expect_error(.logMessages(date(), logfile = 5))
})
test_that(desc = paste0("miscellaneous distance fxns that are not directly",
" used within celda, but will be tested"), {
x <- data.frame(x = seq(2, 4), y = seq(1, 3))
expect_equal(class(.hellingerDist(x)), "dist")
expect_equal(class(.spearmanDist(x)), "dist")
})
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