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Alyssa Salazar
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[413088]: / tests / testthat / test-plots.R

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# Testing plotting functions

test_that("non-spatial plots", {



  # get data

  data("xenium_data")

  

  # get custom colors

  # colors <- scales::hue_pal()(length(unique(xenium_data$clusters)))

  colors <- hue_pal(length(unique(xenium_data$clusters)))

  names(colors) <- unique(xenium_data$clusters)

  

  # embedding plot

  vrEmbeddingPlot(xenium_data, group.by = "clusters", embedding = "umap", label = T)

  vrEmbeddingPlot(xenium_data, group.by = "clusters", embedding = "umap", group.ids = c(1,3,4), label = T)

  vrEmbeddingPlot(xenium_data, group.by = "clusters", embedding = "umap", colors = colors, label = T)

  vrEmbeddingPlot(xenium_data, group.by = "clusters", embedding = "umap", group.ids = c(1,3,4), colors = colors[c(1,3,4)], label = T)

  vrEmbeddingPlot(xenium_data, group.by = "clusters", ncol = 3, split.by = "clusters")

  vrEmbeddingPlot(xenium_data, group.by = "clusters", ncol = 3, split.by = "Sample")

  expect_error(vrEmbeddingPlot(xenium_data, group.by = "clusters", ncol = 3, split.by = "art"))

  

  # embedding feature plot

  vrEmbeddingFeaturePlot(xenium_data, features = c("ACTA2", "TACSTD2"), embedding = "umap", combine.features = TRUE)

  

  # scatterplot

  vrScatterPlot(xenium_data, feature.1 = "NKG7", feature.2 = "TRAC")

  xenium_data <- normalizeData(xenium_data)

  vrScatterPlot(xenium_data, feature.1 = "NKG7", feature.2 = "TRAC", norm = TRUE)

})





# Testing plotting functions

test_that("spatial plots", {



  # get data

  data("xenium_data")



  # get custom colors

  # colors <- scales::hue_pal()(length(unique(xenium_data$clusters)))

  colors <- hue_pal(length(unique(xenium_data$clusters)))

  names(colors) <- unique(xenium_data$clusters)



  # spatial plot, groups and colors

  vrSpatialPlot(xenium_data, group.by = "clusters", plot.segments = TRUE)

  vrSpatialPlot(xenium_data, group.by = "clusters", group.ids = c(1,3,4), plot.segments = TRUE)

  vrSpatialPlot(xenium_data, group.by = "clusters", colors = colors, plot.segments = TRUE)

  vrSpatialPlot(xenium_data, group.by = "clusters", group.ids = c(1,3,4), colors = colors[c(1,3,4)], plot.segments = TRUE)

  

  # spatial plot, background color

  vrSpatialPlot(xenium_data, group.by = "clusters", background.color = "black")

  vrSpatialPlot(xenium_data, group.by = "clusters", background.color = "yellow")

  vrSpatialPlot(xenium_data, group.by = "clusters", background.color = "white")

  

  # spatial plot with spatial and channel arguments

  vrSpatialPlot(xenium_data, group.by = "clusters", spatial = "main")

  vrSpatialPlot(xenium_data, group.by = "clusters", spatial = "main", background.color = "yellow")

  vrSpatialPlot(xenium_data, group.by = "clusters", spatial = "main", channel = "DAPI")

  vrSpatialPlot(xenium_data, group.by = "clusters", channel = "DAPI")

  vrSpatialPlot(xenium_data, group.by = "clusters", channel = "DAPI2")

  vrSpatialPlot(xenium_data, group.by = "clusters", spatial = "main", channel = "DAPI2")

  expect_error(vrSpatialPlot(xenium_data, group.by = "clusters", spatial = "main2"))

  expect_error(vrSpatialPlot(xenium_data, group.by = "clusters", spatial = "main2", channel = "DAPI2"))



  # spatial plot, old background argument

  expect_warning(

    expect_warning(vrSpatialPlot(xenium_data, group.by = "clusters", background = "main")))

  expect_warning(

      expect_warning(vrSpatialPlot(xenium_data, group.by = "clusters", background = c("main", "DAPI2"))))

  expect_warning(

    expect_warning(

      expect_error(vrSpatialPlot(xenium_data, group.by = "clusters", background = "main2"))))

  

  # spatial plot without segmentation

  vrSpatialPlot(xenium_data, group.by = "clusters", plot.segments = FALSE)



  # spatial plot of visium

  vrSpatialPlot(visium_data)



  # spatial plot of melc data

  vrSpatialPlot(melc_data, group.by = "Clusters")

  expect_error(vrSpatialPlot(melc_data, group.by = "Clusters_new"))



  # feature plots

  vrSpatialFeaturePlot(visium_data, features = "Count")

  vrSpatialFeaturePlot(visium_data, features = "Stat1", norm = TRUE, log = TRUE)

  expect_error(vrSpatialFeaturePlot(visium_data, features = "Count_new"))

  vrSpatialFeaturePlot(xenium_data, features = c("ACTA2", "TACSTD2"), norm = TRUE, combine.features = TRUE)

  

  # return

  expect_equal(1,1L)

})



# Testing plotting functions

test_that("missing_embedding_values", {

  

  # get data

  data("visium_data")

  data("xenium_data")

  

  # change embeddings 

  vrEmbeddings(xenium_data, type = "new_umap") <- vrEmbeddings(xenium_data, type = "umap")[sample(1:length(vrSpatialPoints(xenium_data)), 500),]

  vrEmbeddingPlot(xenium_data, embedding = "new_umap")

  expect_error(vrEmbeddingPlot(xenium_data, embedding = "new_umap", group.by = "cluster"))

  vrEmbeddingFeaturePlot(xenium_data, embedding = "new_umap", features = "Count")

  expect_error(vrEmbeddingFeaturePlot(xenium_data, embedding = "new_umap", features = "Counts"))

  vrEmbeddingFeaturePlot(xenium_data, embedding = "new_umap", features = "REXO4")

  expect_error(vrEmbeddingFeaturePlot(xenium_data, embedding = "new_umap", features = "REXO4s"))

  

  # return

  expect_equal(1,1L)

})



# Testing plotting functions

test_that("rasterization", {

  

  # get data

  data("xenium_data")

  

  # spatial plot

  vrSpatialPlot(xenium_data, group.by = "clusters", background.color = "black", n.tile = 100)

  vrSpatialPlot(xenium_data, group.by = "clusters", background.color = "black", n.tile = 1)

  vrSpatialPlot(xenium_data, group.by = "clusters", background.color = "black", n.tile = 10)



  # feature plots

  vrSpatialFeaturePlot(xenium_data, features = "Count", n.tile = 20)

  vrSpatialFeaturePlot(xenium_data, features = "KRT14", norm = TRUE, log = TRUE, n.tile = 10)

  expect_error(vrSpatialFeaturePlot(xenium_data, features = "Count_new"))

  vrSpatialFeaturePlot(xenium_data, features = c("ACTA2", "TACSTD2"), norm = TRUE, n.tile = 100, combine.features = TRUE)

  vrSpatialFeaturePlot(xenium_data, features = c("ACTA2", "TACSTD2"), norm = TRUE, n.tile = 2, combine.features = TRUE)

  

  # embedding plots

  vrEmbeddingPlot(xenium_data, n.tile = 1200, group.by = "clusters")

  vrEmbeddingFeaturePlot(xenium_data, n.tile = 1200, features = c("ACTA2", "TACSTD2"))

  vrEmbeddingFeaturePlot(xenium_data, n.tile = 100, features = c("ACTA2", "TACSTD2"), embedding = "umap", combine.features = TRUE)

  vrEmbeddingFeaturePlot(xenium_data, n.tile = 2, features = c("ACTA2", "TACSTD2"), embedding = "umap", combine.features = TRUE)

  vrEmbeddingPlot(xenium_data, n.tile = 2, group.by = "clusters")

  vrEmbeddingFeaturePlot(xenium_data, n.tile = 10, features = c("ACTA2"))

  

  # return

  expect_equal(1,1L)

})



# testing multilayer plots

test_that("multilayer", {

  

  skip_if_not_installed("ggnewscale")

  data("merged_object")

  

  # single

  vrSpatialPlot(merged_object)

  

  # cell vs ROI (without segments)

  vrSpatialPlot(merged_object, plot.segments = FALSE) |>

    addSpatialLayer(merged_object, assay = "Assay3", group.by = "Sample", alpha = 0.3)

  

  # cell vs ROI (with segments)

  vrSpatialPlot(merged_object, plot.segments = TRUE) |>

    addSpatialLayer(merged_object, assay = "Assay3", group.by = "Sample", alpha = 0.4, colors = list(Block = "blue"))



  # ROI vs cell

  vrSpatialPlot(merged_object, assay = "Assay3", group.by = "Sample", alpha = 0.4, colors = list(Block = "blue")) |>

    addSpatialLayer(merged_object, assay = "Assay1")

  vrSpatialPlot(merged_object, assay = "Assay3", group.by = "Sample", alpha = 1, colors = list(Block = "blue")) |>

    addSpatialLayer(merged_object, assay = "Assay1", plot.segments = TRUE, alpha = 0.4)

  vrSpatialPlot(merged_object, assay = "Assay3", group.by = "Sample", alpha = 0.4, colors = list(Block = "blue")) |>

    addSpatialLayer(merged_object, assay = "Assay1", n.tile = 100)

  

  # cell vs molecule (without segments)

  vrSpatialPlot(merged_object, plot.segments = FALSE) |>

    addSpatialLayer(merged_object, assay = "Assay2", group.by = "gene", alpha = 1, colors = list(KRT15 = "blue", KRT14 = "green"))

  

  # cell vs molecule 

  vrSpatialPlot(merged_object, plot.segments = TRUE) |>

    addSpatialLayer(merged_object, assay = "Assay2", group.by = "gene", alpha = 1, colors = list(KRT15 = "blue", KRT14 = "green"))

  

  # molecule vs cell (with segments)

  vrSpatialPlot(merged_object, assay = "Assay2", group.by = "gene", alpha = 1, colors = list(KRT15 = "blue", KRT14 = "green")) |>

    addSpatialLayer(merged_object, assay = "Assay1")

  vrSpatialPlot(merged_object, assay = "Assay2", group.by = "gene", alpha = 1, colors = list(KRT15 = "blue", KRT14 = "green")) |>

    addSpatialLayer(merged_object, assay = "Assay1", plot.segments = TRUE, alpha = 0.4)

  

  # cells, ROIs and molecules together

  vrSpatialPlot(merged_object, plot.segments = TRUE) |>

    addSpatialLayer(merged_object, assay = "Assay2", group.by = "gene", alpha = 1, colors = list(KRT15 = "blue", KRT14 = "green")) |>

    addSpatialLayer(merged_object, assay = "Assay3", group.by = "Layer", alpha = 0.4, colors = list(Section3 = "blue"))

  

  expect_equal(1,1)

})



# testing multilayer plots

# TODO: tiling multilayer visualization behavior is not ideal right now

test_that("multilayer (with tiling)", {

  

  skip_if_not_installed("ggnewscale")

  data("merged_object")

  

  # single

  vrSpatialPlot(merged_object)

  

  # cell vs ROI (without segments)

  vrSpatialPlot(merged_object, plot.segments = FALSE, n.tile = 100) |>

    addSpatialLayer(merged_object, assay = "Assay3", group.by = "Sample", alpha = 0.4, colors = list(Block = "blue"))

  

  # ROI vs cell

  vrSpatialPlot(merged_object, assay = "Assay3", group.by = "Sample", alpha = 0.4, colors = list(Block = "blue")) |>

    addSpatialLayer(merged_object, assay = "Assay1", n.tile = 100)

  

  # cell vs molecule (without segments)

  vrSpatialPlot(merged_object, plot.segments = FALSE) |>

    addSpatialLayer(merged_object, assay = "Assay2", group.by = "gene", alpha = 1, colors = list(KRT15 = "blue", KRT14 = "green"), n.tile = 100)

  vrSpatialPlot(merged_object, plot.segments = FALSE, n.tile = 100) |>

    addSpatialLayer(merged_object, assay = "Assay2", group.by = "gene", alpha = 1, colors = list(KRT15 = "blue", KRT14 = "green"), n.tile = 100)

  

  # cell vs molecule 

  vrSpatialPlot(merged_object, plot.segments = TRUE) |>

    addSpatialLayer(merged_object, assay = "Assay2", group.by = "gene", alpha = 1, colors = list(KRT15 = "blue", KRT14 = "green"), n.tile = 100)

  

  # molecule vs cell (with segments)

  vrSpatialPlot(merged_object, assay = "Assay2", group.by = "gene", alpha = 1, colors = list(KRT15 = "blue", KRT14 = "green")) |>

    addSpatialLayer(merged_object, assay = "Assay1", n.tile = 100)

  vrSpatialPlot(merged_object, assay = "Assay2", group.by = "gene", alpha = 1, colors = list(KRT15 = "blue", KRT14 = "green")) |>

    addSpatialLayer(merged_object, assay = "Assay1", plot.segments = TRUE)

  

  # molecule vs ROI

  vrSpatialPlot(merged_object, assay = "Assay2", group.by = "gene", alpha = 1, colors = list(KRT15 = "blue", KRT14 = "green"), n.tile = 100) |>

    addSpatialLayer(merged_object, assay = "Assay3", group.by = "Sample", alpha = 0.4, colors = list(Block = "blue"))

  

  expect_equal(1,1)

})