context("plotting")
test_that("plotting works", {
data(pbmc3ksub)
set.seed(1)
sce <- pbmc3ksub[1:100, 1:100]
dres <- dreval(
sce = sce, dimReds = c("PCA", "PCA_k2"),
refType = "assay", refAssay = "logcounts",
features = NULL, nSamples = NULL, distNorm = "l2",
refDistMethod = "euclidean", kTM = 5,
labelColumn = NULL, verbose = FALSE
)
gg <- plotRankSummary(dres$scores, sortBars = "decreasing")
expect_equal(gg$data$score[gg$data$Method == "PCA"],
rep(2, 10))
expect_equal(gg$data$score[gg$data$Method == "PCA_k2"],
rep(1, 10))
expect_equal(gg$data$Method, factor(rep(c("PCA", "PCA_k2"), each = 10),
levels = c("PCA", "PCA_k2")))
gg <- plotRankSummary(dres$scores, sortBars = "increasing")
expect_equal(gg$data$score[gg$data$Method == "PCA"],
rep(2, 10))
expect_equal(gg$data$score[gg$data$Method == "PCA_k2"],
rep(1, 10))
expect_equal(gg$data$Method, factor(rep(c("PCA_k2", "PCA"), each = 10),
levels = c("PCA_k2", "PCA")))
gg <- plotRankSummary(dres$scores, sortBars = "decreasing",
metrics = "global")
expect_equal(gg$data$score[gg$data$Method == "PCA"],
rep(2, 6))
expect_equal(gg$data$score[gg$data$Method == "PCA_k2"],
rep(1, 6))
expect_equal(gg$data$Method, factor(rep(c("PCA", "PCA_k2"), each = 6),
levels = c("PCA", "PCA_k2")))
expect_equal(sort(unique(as.character(gg$data$metric))),
sort(c("coRankingQglobal", "EuclDistBetweenDists", "KSStatDist",
"PearsonCorrDist", "SammonStress", "SpearmanCorrDist")))
gg <- plotRankSummary(dres$scores, sortBars = "decreasing",
metrics = "local")
expect_equal(gg$data$score[gg$data$Method == "PCA"],
rep(2, 4))
expect_equal(gg$data$score[gg$data$Method == "PCA_k2"],
rep(1, 4))
expect_equal(gg$data$Method, factor(rep(c("PCA", "PCA_k2"), each = 4),
levels = c("PCA", "PCA_k2")))
expect_equal(sort(unique(as.character(gg$data$metric))),
sort(c("Continuity_k5", "Trustworthiness_k5",
"coRankingQlocal", "MeanJaccard_k5")))
})
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