context("test-learn_graph")
skip_not_travis <- function ()
{
if (identical(Sys.getenv("TRAVIS"), "true")) {
return(invisible(TRUE))
}
skip("Not on Travis")
}
cds <- load_a549()
test_that("test learn_graph error messages work", {
skip_on_travis()
expect_error(cds <- learn_graph(cds),
"No dimensionality reduction for UMAP calculated. Please run reduce_dimension with reduction_method = UMAP and cluster_cells before running learn_graph.")
cds <- preprocess_cds(cds)
expect_error(cds <- learn_graph(cds),
"No dimensionality reduction for UMAP calculated. Please run reduce_dimension with reduction_method = UMAP and cluster_cells before running learn_graph.")
cds <- reduce_dimension(cds)
expect_error(cds <- learn_graph(cds),
"No cell clusters for UMAP calculated. Please run cluster_cells with reduction_method = UMAP before running learn_graph.")
#expect_error(cds <- learn_graph(cds, learn_graph_control = list(FALSE)), "")
expect_error(cds <- learn_graph(cds, learn_graph_control = list(prune = FALSE)), "Unknown variable in learn_graph_control")
})
set.seed(42)
cds <- preprocess_cds(cds)
cds <- reduce_dimension(cds)
cds <- reduce_dimension(cds, umap.fast_sgd=FALSE, cores=1)
cds <- cluster_cells(cds, resolution = .01)
test_that("learn_graph stays the same", {
skip_on_travis()
cds <- learn_graph(cds)
expect_is(principal_graph(cds)[["UMAP"]], "igraph")
expect_equal(length(principal_graph(cds)[["UMAP"]]), 33)
expect_equal(as.character(principal_graph(cds)[["UMAP"]][[1]]$Y_1[[1]]), "24")
# Force partition
temp <- rep(c(1,2), length.out=length(partitions(cds)))
names(temp) <- names(partitions(cds))
cds@clusters[["UMAP"]]$partitions <- temp
cds <- learn_graph(cds, use_partition = FALSE)
expect_is(principal_graph(cds)[["UMAP"]], "igraph")
expect_equal(length(principal_graph(cds)[["UMAP"]]), 33)
expect_equal(as.character(principal_graph(cds)[["UMAP"]][[1]]$Y_1[[1]]), "24")
cds <- learn_graph(cds)
expect_is(principal_graph(cds)[["UMAP"]], "igraph")
expect_equal(length(principal_graph(cds)[["UMAP"]]), 74)
expect_equal(as.character(principal_graph(cds)[["UMAP"]][[1]]$Y_1[[1]]), "36")
cds <- learn_graph(cds, close_loop = TRUE)
expect_is(principal_graph(cds)[["UMAP"]], "igraph")
expect_equal(length(principal_graph(cds)[["UMAP"]]), 74)
expect_equal(as.character(principal_graph(cds)[["UMAP"]][[1]]$Y_1[[1]]), "36")
cds <- learn_graph(cds, learn_graph_control = list(prune_graph = FALSE))
expect_is(principal_graph(cds)[["UMAP"]], "igraph")
expect_equal(length(principal_graph(cds)[["UMAP"]]), 144)
expect_equal(as.character(principal_graph(cds)[["UMAP"]][[1]]$Y_1[[1]]), "8")
})
#### TRAVIS ####
cds <- load_a549()
test_that("test learn_graph error messages work", {
skip_not_travis()
expect_error(cds <- learn_graph(cds),
"No dimensionality reduction for UMAP calculated. Please run reduce_dimension with reduction_method = UMAP and cluster_cells before running learn_graph.")
cds <- preprocess_cds(cds)
expect_error(cds <- learn_graph(cds),
"No dimensionality reduction for UMAP calculated. Please run reduce_dimension with reduction_method = UMAP and cluster_cells before running learn_graph.")
cds <- reduce_dimension(cds)
expect_error(cds <- learn_graph(cds),
"No cell clusters for UMAP calculated. Please run cluster_cells with reduction_method = UMAP before running learn_graph.")
#expect_error(cds <- learn_graph(cds, learn_graph_control = list(FALSE)), "")
expect_error(cds <- learn_graph(cds, learn_graph_control = list(prune = FALSE)), "Unknown variable in learn_graph_control")
})
set.seed(42)
cds <- preprocess_cds(cds)
cds <- reduce_dimension(cds)
cds <- reduce_dimension(cds, umap.fast_sgd=FALSE, cores=1)
cds <- cluster_cells(cds, resolution = .01)
test_that("learn_graph stays the same", {
skip_not_travis()
cds <- learn_graph(cds)
expect_is(principal_graph(cds)[["UMAP"]], "igraph")
expect_equal(length(principal_graph(cds)[["UMAP"]]), 33)
expect_equal(as.character(principal_graph(cds)[["UMAP"]][[1]]$Y_1[[1]]), "24")
# Force partition
temp <- rep(c(1,2), length.out=length(partitions(cds)))
names(temp) <- names(partitions(cds))
cds@clusters[["UMAP"]]$partitions <- temp
cds <- learn_graph(cds, use_partition = FALSE)
expect_is(principal_graph(cds)[["UMAP"]], "igraph")
expect_equal(length(principal_graph(cds)[["UMAP"]]), 33)
expect_equal(as.character(principal_graph(cds)[["UMAP"]][[1]]$Y_1[[1]]), "24")
cds <- learn_graph(cds)
expect_is(principal_graph(cds)[["UMAP"]], "igraph")
expect_equal(length(principal_graph(cds)[["UMAP"]]), 74)
expect_equal(as.character(principal_graph(cds)[["UMAP"]][[1]]$Y_1[[1]]), "36")
cds <- learn_graph(cds, close_loop = TRUE)
expect_is(principal_graph(cds)[["UMAP"]], "igraph")
expect_equal(length(principal_graph(cds)[["UMAP"]]), 74)
expect_equal(as.character(principal_graph(cds)[["UMAP"]][[1]]$Y_1[[1]]), "36")
cds <- learn_graph(cds, learn_graph_control = list(prune_graph = FALSE))
expect_is(principal_graph(cds)[["UMAP"]], "igraph")
expect_equal(length(principal_graph(cds)[["UMAP"]]), 144)
expect_equal(as.character(principal_graph(cds)[["UMAP"]][[1]]$Y_1[[1]]), "8")
})
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