Running ‘testthat.R’ [9s/23s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(ClusterR)
  Loading required package: gtools
  > 
  > test_check("ClusterR")
  
   *** caught segfault ***
  address 0, cause 'memory not mapped'
  Error in Stack$new() : 
    'rho' must be an environment not pairlist: detected in C-level eval
  Calls: test_check ... o_apply -> lapply -> FUN -> <Anonymous> -> <Anonymous>
  testthat results ================================================================
  Warning: stack imbalance in '{', 56 then 57
  Warning: stack imbalance in '{', 51 then 52
  Warning: stack imbalance in '{', 46 then 47
  Warning: stack imbalance in '$', 55 then 54
  Warning: stack imbalance in '$', 62 then 63
  OK: 92 SKIPPED: 
  Traceback:
   1: Stack$new()
   2: x[[method]](...)
   3: FUN(X[[i]], ...)
   4: lapply(objects, function(x) x[[method]](...))
   5: o_apply(self$reporters, "start_test", context, test)
   6: get_reporter()$start_test(context = get_reporter()$.context,     test = test)
   7: test_code(desc, code, env = parent.frame())
   8: testthat::test_that("KMeans_rcpp returns the correct output if CENTROIDS is user-defined ",     {        clust = 2        cntr = matrix(runif(2 * (ncol(X))), nrow = 2, ncol = ncol(X))        km = KMeans_rcpp(X, clusters = clust, num_init = 5, max_iters = 100,             CENTROIDS = cntr)        testthat::expect_true(names(km) %in% c("clusters", "centroids",             "total_SSE", "best_initialization", "WCSS_per_cluster",             "obs_per_cluster", "between.SS_DIV_total.SS") &&             is.vector(km$clusters) && length(km$clusters) ==             nrow(X) && is.numeric(km$between.SS_DIV_total.SS) &&             length(km$between.SS_DIV_total.SS) == 1 && nrow(km$centroids) ==             clust && ncol(km$centroids) == ncol(X) && length(km$total_SSE) ==             1 && is.numeric(km$total_SSE) && length(km$best_initialization) ==             1 && is.numeric(km$best_initialization) && ncol(km$WCSS_per_cluster) ==             clust && ncol(km$obs_per_cluster) == clust && class(km) ==             "k-means clustering")    })
   9: eval(exprs, env)
  10: eval(exprs, env)
  11: source_file(path, new.env(parent = env), chdir = TRUE)
  12: <80>vI