Running examples in ‘batchtools-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: estimateRuntimes
> ### Title: Estimate Remaining Runtimes
> ### Aliases: estimateRuntimes print.RuntimeEstimate
> 
> ### ** Examples
> 
> ## Don't show: 
>  batchtools:::example_push_temp(1) 
> ## End(Don't show)
> # Create a simple toy registry
> set.seed(1)
> tmp = makeExperimentRegistry(file.dir = NA, make.default = FALSE, seed = 1)
No readable configuration file found
Created registry in '/home/hornik/tmp/scratch/RtmpkIqTie/registry3950f321200b6c' using cluster functions 'Interactive'
> addProblem(name = "iris", data = iris, fun = function(data, ...) nrow(data), reg = tmp)
Adding problem 'iris'
> addAlgorithm(name = "nrow", function(instance, ...) nrow(instance), reg = tmp)
Adding algorithm 'nrow'
> addAlgorithm(name = "ncol", function(instance, ...) ncol(instance), reg = tmp)
Adding algorithm 'ncol'
> addExperiments(algo.designs = list(nrow = data.table::CJ(x = 1:50, y = letters[1:5])), reg = tmp)
Adding 250 experiments ('iris'[1] x 'nrow'[250] x repls[1]) ...
> addExperiments(algo.designs = list(ncol = data.table::CJ(x = 1:50, y = letters[1:5])), reg = tmp)
Adding 250 experiments ('iris'[1] x 'ncol'[250] x repls[1]) ...
> 
> # We use the job parameters to predict runtimes
> tab = unwrap(getJobPars(reg = tmp))
> 
> # First we need to submit some jobs so that the forest can train on some data.
> # Thus, we just sample some jobs from the registry while grouping by factor variables.
> library(data.table)
> ids = tab[, .SD[sample(nrow(.SD), 5)], by = c("problem", "algorithm", "y")]
> setkeyv(ids, "job.id")
> submitJobs(ids, reg = tmp)
Submitting 50 jobs in 50 chunks using cluster functions 'Interactive' ...
> waitForJobs(reg = tmp)
[1] TRUE
> 
> # We "simulate" some more realistic runtimes here to demonstrate the functionality:
> # - Algorithm "ncol" is 5 times more expensive than "nrow"
> # - x has no effect on the runtime
> # - If y is "a" or "b", the runtimes are really high
> runtime = function(algorithm, x, y) {
+   ifelse(algorithm == "nrow", 100L, 500L) + 1000L * (y %in% letters[1:2])
+ }
> tmp$status[ids, done := done + tab[ids, runtime(algorithm, x, y)]]
> rjoin(sjoin(tab, ids), getJobStatus(ids, reg = tmp)[, c("job.id", "time.running")])
Key: <job.id>
    job.id problem algorithm     x      y   time.running
     <int>  <char>    <char> <int> <char>     <difftime>
 1:     32    iris      nrow     7      b 1100.0021 secs
 2:     42    iris      nrow     9      b 1100.0061 secs
 3:     47    iris      nrow    10      b 1100.0061 secs
 4:     66    iris      nrow    14      a 1100.0020 secs
 5:     73    iris      nrow    15      c  100.0020 secs
 6:     75    iris      nrow    15      e  100.0018 secs
 7:     86    iris      nrow    18      a 1100.0017 secs
 8:    100    iris      nrow    20      e  100.0018 secs
 9:    101    iris      nrow    21      a 1100.0062 secs
10:    103    iris      nrow    21      c  100.0019 secs
11:    123    iris      nrow    25      c  100.0018 secs
12:    125    iris      nrow    25      e  100.0017 secs
13:    161    iris      nrow    33      a 1100.0017 secs
14:    165    iris      nrow    33      e  100.0020 secs
15:    169    iris      nrow    34      d  100.0017 secs
16:    183    iris      nrow    37      c  100.0019 secs
17:    184    iris      nrow    37      d  100.0062 secs
18:    203    iris      nrow    41      c  100.0017 secs
19:    207    iris      nrow    42      b 1100.0018 secs
20:    209    iris      nrow    42      d  100.0019 secs
21:    220    iris      nrow    44      e  100.0061 secs
22:    227    iris      nrow    46      b 1100.0018 secs
23:    229    iris      nrow    46      d  100.0017 secs
24:    231    iris      nrow    47      a 1100.0019 secs
25:    244    iris      nrow    49      d  100.0060 secs
26:    260    iris      ncol     2      e  500.0017 secs
27:    276    iris      ncol     6      a 1500.0018 secs
28:    278    iris      ncol     6      c  500.0018 secs
29:    279    iris      ncol     6      d  500.0019 secs
30:    296    iris      ncol    10      a 1500.0018 secs
31:    320    iris      ncol    14      e  500.0017 secs
32:    340    iris      ncol    18      e  500.0017 secs
33:    347    iris      ncol    20      b 1500.0016 secs
34:    363    iris      ncol    23      c  500.0018 secs
35:    369    iris      ncol    24      d  500.0016 secs
36:    373    iris      ncol    25      c  500.0017 secs
37:    387    iris      ncol    28      b 1500.0017 secs
38:    410    iris      ncol    32      e  500.0020 secs
39:    421    iris      ncol    35      a 1500.0016 secs
40:    436    iris      ncol    38      a 1500.0018 secs
41:    444    iris      ncol    39      d  500.0018 secs
42:    448    iris      ncol    40      c  500.0064 secs
43:    456    iris      ncol    42      a 1500.0063 secs
44:    459    iris      ncol    42      d  500.0019 secs
45:    467    iris      ncol    44      b 1500.0060 secs
46:    468    iris      ncol    44      c  500.0063 secs
47:    475    iris      ncol    45      e  500.0061 secs
48:    482    iris      ncol    47      b 1500.0060 secs
49:    492    iris      ncol    49      b 1500.0020 secs
50:    499    iris      ncol    50      d  500.0061 secs
    job.id problem algorithm     x      y   time.running
> 
> # Estimate runtimes:
> est = estimateRuntimes(tab, reg = tmp)
Error in estimateRuntimes(tab, reg = tmp) : 
  Please install package 'ranger' for runtime estimation
Execution halted