data = data.frame(x = runif(1000, -2, 2), drop= FALSE) lens = data$x names(lens) = row.names(data) cover = create_width_balanced_cover(min(lens), max(lens), 10, 25) dists = dist(data) test_that("global clustering", { expect_no_warning(create_1D_mapper_object(data, dists, lens, cover, global_hierarchical_clusterer("single", dists))) }) test_that("local clustering", { expect_no_warning(create_1D_mapper_object(data, dists, lens, cover, local_hierarchical_clusterer("complete"))) }) test_that("no clustering", { expect_no_warning(create_1D_mapper_object(data, dists, lens, cover, NULL)) }) test_that("we can hierarchically cluster differently", { expect_no_warning(create_1D_mapper_object(data, dists, lens, cover, clusterer = local_hierarchical_clusterer("mcquitty"))) })