# # generate 1000 random data points between -2 and 2
data = data.frame(x = runif(1000, -2, 2), drop = FALSE)
one_dim_projection = data$x
names(one_dim_projection) = row.names(data)

cover = create_width_balanced_cover(min(one_dim_projection), max(one_dim_projection), 10, 25)

test_that("we can clusterball with clusterball", {
  expect_no_warning(create_clusterball_mapper_object(data, dist(data), dist(data), .3))
})

test_that("mapper happens ok with distance matrix as a matrix", {
  expect_no_warning(create_1D_mapper_object(data, as.matrix(dist(data)), one_dim_projection, cover))
})

test_that("mapper happens ok with distance matrix as a dist", {
  expect_no_warning(create_1D_mapper_object(data, dist(data), one_dim_projection, cover))
})

test_that("mapper is ok with no clustering method", {
  expect_no_warning(create_1D_mapper_object(data, dist(data), one_dim_projection, cover))
})

test_that("mapper works with differently formatted filtered data", {
  expect_no_warning(create_1D_mapper_object(data, dist(data), as.data.frame(one_dim_projection), cover))
  expect_no_warning(create_1D_mapper_object(data, dist(data), as.list(one_dim_projection), cover))
  expect_error(create_1D_mapper_object(data, dist(data), as.vector(one_dim_projection), cover)) # this should break because this removes names
  expect_no_warning(create_1D_mapper_object(data, dist(data), as.matrix(one_dim_projection), cover))
})