--- a
+++ b/tests/testthat/test-spatial.R
@@ -0,0 +1,134 @@
+test_that("spatial neighbors", {
+  
+  # get data
+  data("xenium_data")
+  
+  # spatial neighbors, delaunay
+  xenium_data <- getSpatialNeighbors(xenium_data, method = "delaunay", verbose = FALSE)
+  graphs <- vrGraph(xenium_data, graph.type = "delaunay")
+  expect_true(inherits(graphs,"igraph"))
+  expect_true(length(igraph::E(graphs)) > 0)
+  vrSpatialPlot(xenium_data, graph.name = "delaunay", group.by = "clusters")
+  
+  # spatial neighbors, spatialkNN
+  xenium_data <- getSpatialNeighbors(xenium_data, method = "spatialkNN", k = 5, verbose = FALSE)
+  graphs <- vrGraph(xenium_data, graph.type = "spatialkNN")
+  expect_true(inherits(graphs,"igraph"))
+  expect_true(length(igraph::E(graphs)) > 0)
+  vrSpatialPlot(xenium_data, graph.name = "spatialkNN", group.by = "clusters")
+  
+  # spatial neighbors, radius
+  xenium_data <- getSpatialNeighbors(xenium_data, method = "radius", radius = 10, verbose = FALSE)
+  graphs <- vrGraph(xenium_data, graph.type = "radius")
+  expect_true(inherits(graphs,"igraph"))
+  expect_true(length(igraph::E(graphs)) > 0)
+  vrSpatialPlot(xenium_data, graph.name = "radius", group.by = "clusters")
+  
+  # return
+  expect_equal(1,1L)
+})
+
+test_that("spatial neighbors for subsets", {
+  
+  # get data
+  data("xenium_data")
+  
+  # merge two of same types
+  xenium_data2 <- xenium_data
+  xenium_data2$Sample <- "XeniumR2"
+  merged_data <- merge(xenium_data, xenium_data2, verbose = FALSE)
+  
+  # spatial neighbors, delaunay
+  merged_data <- getSpatialNeighbors(merged_data, assay = "Assay1", method = "delaunay", verbose = FALSE)
+  graphs <- vrGraph(merged_data, graph.type = "delaunay")
+  expect_true(inherits(graphs,"igraph"))
+  expect_true(length(igraph::E(graphs)) > 0)
+  vrSpatialPlot(merged_data, graph.name = "delaunay", group.by = "clusters")
+  
+  # return
+  expect_equal(1,1L)
+})
+
+test_that("spatial tests", {
+  
+  # get data
+  data("xenium_data")
+  
+  # spatial neighbors, radius based
+  xenium_data <- getSpatialNeighbors(xenium_data, method = "radius", radius = 10, verbose = FALSE)
+  
+  # getis ord test
+  xenium_data <- getHotSpotAnalysis(xenium_data, graph.type = "radius", features = c("GNLY"), verbose = FALSE)
+  expect_true(all(c("GNLY_hotspot_stat", "GNLY_hotspot_pvalue", "GNLY_hotspot_flag") %in% colnames(Metadata(xenium_data))))
+  xenium_data <- getHotSpotAnalysis(xenium_data, graph.type = "radius", features = c("GNLY", "Count"), verbose = FALSE)
+  expect_error(getHotSpotAnalysis(xenium_data, graph.type = "radius", features = c("GNLY", "Count1"), verbose = FALSE))
+  expect_error(getHotSpotAnalysis(xenium_data, graph.type = "radius", features = c("GNLY2", "Count1"), verbose = FALSE))
+  
+  # multiple assays
+  data("xenium_data")
+  xenium_data2 <- xenium_data
+  xenium_data2$Sample <- "Sample2"
+  xenium_data <- merge(xenium_data, xenium_data2, verbose = FALSE)
+  xenium_data <- getSpatialNeighbors(xenium_data, method = "radius", radius = 10, verbose = FALSE)
+  xenium_data <- getHotSpotAnalysis(xenium_data, graph.type = "radius", features = c("GNLY", "Count"), verbose = FALSE)
+  expect_true(all(c("GNLY_hotspot_stat", "GNLY_hotspot_pvalue", "GNLY_hotspot_flag") %in% colnames(Metadata(xenium_data))))
+  expect_true(all(c("Count_hotspot_stat", "Count_hotspot_pvalue", "Count_hotspot_flag") %in% colnames(Metadata(xenium_data))))
+})
+
+test_that("niche clustering", {
+
+  data("xenium_data")
+  
+  ####
+  # single assay
+  ####
+  
+  # build niche assay
+  xenium_data2 <- getSpatialNeighbors(xenium_data, radius = 15, method = "radius", verbose = FALSE)
+  xenium_data2 <- getNicheAssay(xenium_data2, label = "clusters", graph.type = "radius")
+  expect_equal(vrFeatureTypeNames(xenium_data2), c("RNA", "Niche"))
+  xenium_data2 <- getNicheAssay(xenium_data2, label = "clusters", graph.type = "radius", new_feature_name = "Niche2")
+  expect_equal(vrFeatureTypeNames(xenium_data2), c("RNA", "Niche", "Niche2"))
+  expect_error(getNicheAssay(xenium_data2, label = "clusters1", graph.type = "radius"))
+  
+  # cluster niches
+  vrMainFeatureType(xenium_data2) <- "Niche"
+  xenium_data2 <- getClusters(xenium_data2, nclus = 3, method = "kmeans", label = "cluster_niches")
+  expect_true("cluster_niches" %in% colnames(Metadata(xenium_data2)))
+  expect_error(xenium_data2 <- getClusters(xenium_data2, nclus = 0, method = "kmeans", label = "cluster_niches"))
+  expect_error(xenium_data2 <- getClusters(xenium_data2, nclus = 1.1, method = "kmeans", label = "cluster_niches"))
+  expect_error(xenium_data2 <- getClusters(xenium_data2, nclus = -1, method = "kmeans", label = "cluster_niches"))
+  expect_error(xenium_data2 <- getClusters(xenium_data2, nclus = c(1,2), method = "kmeans", label = "cluster_niches"))
+  
+  # clean
+  rm(xenium_data2)
+
+  ####
+  # multiple assays
+  ####
+  
+  xenium_data2 <- xenium_data
+  xenium_data2$Sample <- "Sample2"
+  xenium_data2 <- merge(xenium_data2, xenium_data, verbose = FALSE)
+  xenium_data2 <- getSpatialNeighbors(xenium_data2, radius = 15, method = "radius", verbose = FALSE)
+  xenium_data3 <- getNicheAssay(xenium_data2, label = "clusters", graph.type = "radius")
+  metadata <- vrFeatureTypeNames(xenium_data3, assay = "all")
+  expect_equal(metadata$Feature, c("RNA,Niche", "RNA,Niche"))
+  xenium_data3 <- getNicheAssay(xenium_data2, assay = "Assay1", label = "clusters", graph.type = "radius")
+  metadata <- vrFeatureTypeNames(xenium_data3, assay = "all")
+  expect_equal(metadata$Feature, c("RNA,Niche", "RNA"))
+  
+  # clean
+  rm(xenium_data2)
+  rm(xenium_data3)
+  
+})
+
+test_that("neighborhood analysis", {
+  
+  data("xenium_data")
+  
+  xenium_data <- getSpatialNeighbors(xenium_data, method = "delaunay", verbose = FALSE)
+  results <- vrNeighbourhoodEnrichment(xenium_data, group.by = "clusters", graph.type = "delaunay")
+  expect_error(results <- vrNeighbourhoodEnrichment(xenium_data, group.by = "clusters2", graph.type = "delaunay"))
+})
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