Running ‘testthat.R’ [69s/98s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(diceR)
  > 
  > test_check("diceR")
  ── 1. Error: evaluation works with reference class and can plot (@test-consensus
  VECTOR_ELT() can only be applied to a 'list', not a 'double'
  1: expect_length(consensus_evaluate(x, CC1, CC2, cons.cl = cons.cl, ref.cl = ref.cl, 
         plot = TRUE), 5) at testthat/test-consensus_combine.R:25
  2: quasi_label(enquo(object))
  3: eval_bare(get_expr(quo), get_env(quo))
  4: consensus_evaluate(x, CC1, CC2, cons.cl = cons.cl, ref.cl = ref.cl, plot = TRUE)
  5: graph_all(E)
  6: graph_cdf(mat)
  7: print(p)
  8: print.ggplot(p)
  9: ggplot_gtable(data)
  10: ggplot_gtable.ggplot_built(data)
  11: layout$render(geom_grobs, data, theme, plot$labels)
  12: f(..., self = self)
  13: self$facet$draw_panels(panels, self$layout, self$panel_scales_x, self$panel_scales_y, 
         self$panel_params, self$coord, data, theme, self$facet_params)
  14: f(...)
  15: render_strips(structure(labels_df, type = "rows"), structure(labels_df, type = "cols"), 
         params$labeller, theme)
  16: build_strip(x, labeller, theme, TRUE)
  17: ggstrip(grobs, theme, element, gp, horizontal, clip = "on")
  18: Summary.unit(structure(c(4.4, 4.4), unit = 8L, class = c("margin", "unit")), na.rm = FALSE)
  
  Selecting k and imputing non-clustered cases
  Computing consensus functions
  Evaluating output with consensus function results
  Diverse Cluster Ensemble Completed
  Selecting k and imputing non-clustered cases
  Computing consensus functions
  Evaluating output with consensus function results
  Diverse Cluster Ensemble Completed
  Selecting k and imputing non-clustered cases
  Computing consensus functions
  Evaluating output with consensus function results
  Diverse Cluster Ensemble Completed
  Selecting k and imputing non-clustered cases
  Computing consensus functions
  Diverse Cluster Ensemble Completed
  Selecting k and imputing non-clustered cases
  Computing consensus functions
  Diverse Cluster Ensemble Completed
  Selecting k and imputing non-clustered cases
  Computing consensus functions
  Diverse Cluster Ensemble Completed
  Selecting k and imputing non-clustered cases
  Computing consensus functions
  ── 2. Error: algorithm vs internal index heatmap works (@test-dice.R#52)  ──────
  REAL() can only be applied to a 'numeric', not a 'integer'
  1: dice(hgsc, nk = 4, reps = 3, algorithms = "hc", cons.funs = "kmodes", ref.cl = ref.cl, 
         evaluate = FALSE, plot = TRUE) at testthat/test-dice.R:52
  2: algii_heatmap(data, k, E, clusters, ref.cl)
  3: NMF::aheatmap(hm, annCol = data.frame(Criteria = c(rep("Maximized", 5), rep("Minimized", 
         ncol(hm) - 5))), annColors = list(Criteria = stats::setNames(c("darkgreen", "deeppink4"), 
         c("Maximized", "Minimized"))), Colv = NA, Rowv = NA, scale = "column", col = "PiYG", 
         main = "Ranked Algorithms on Internal Validity Indices")
  4: heatmap_motor(mat, border_color = border_color, cellwidth = cellwidth, cellheight = cellheight, 
         treeheight_col = treeheight_col, treeheight_row = treeheight_row, tree_col = tree_col, 
         tree_row = tree_row, filename = filename, width = width, height = height, breaks = breaks, 
         color = color, legend = legend, annTracks = annTracks, annotation_legend = annotation_legend, 
         txt = txt, fontsize = fontsize, fontsize_row = cexRow * fontsize, fontsize_col = cexCol * 
             fontsize, main = main, sub = sub, info = info, verbose = verbose, gp = gp)
  5: draw_colnames(colnames(matrix), gp = c_gpar(gp, fontsize = fontsize_col))
  6: Ops.unit(m, unit(1, "grobwidth", textGrob(coln[i <- which.max(nchar(coln))], gp = gp)))
  
  ── 3. Error: (unknown) (@test-graphs.R#8)  ─────────────────────────────────────
  VECTOR_ELT() can only be applied to a 'list', not a 'double'
  1: graph_cdf(CC1) at testthat/test-graphs.R:8
  2: print(p)
  3: print.ggplot(p)
  4: ggplot_gtable(data)
  5: ggplot_gtable.ggplot_built(data)
  6: layout$render(geom_grobs, data, theme, plot$labels)
  7: f(..., self = self)
  8: self$facet$draw_panels(panels, self$layout, self$panel_scales_x, self$panel_scales_y, 
         self$panel_params, self$coord, data, theme, self$facet_params)
  9: f(...)
  10: render_strips(structure(labels_df, type = "rows"), structure(labels_df, type = "cols"), 
         params$labeller, theme)
  11: build_strip(x, labeller, theme, TRUE)
  12: ggstrip(grobs, theme, element, gp, horizontal, clip = "on")
  13: Summary.unit(structure(c(4.4, 4.4), unit = 8L, class = c("margin", "unit")), na.rm = FALSE)
  
  ══ testthat results  ═══════════════════════════════════════════════════════════
  OK: 99 SKIPPED: 0 FAILED: 3
  1. Error: evaluation works with reference class and can plot (@test-consensus_combine.R#25) 
  2. Error: algorithm vs internal index heatmap works (@test-dice.R#52) 
  3. Error: (unknown) (@test-graphs.R#8) 
  
  Error: testthat unit tests failed
  Execution halted