Last updated on 2024-11-15 19:49:52 CET.
| Package | ERROR | OK |
|---|---|---|
| pmlbr | 2 | 11 |
| treeheatr | 1 | 12 |
Current CRAN status: ERROR: 2, OK: 11
Version: 0.2.2
Check: examples
Result: ERROR
Running examples in ‘pmlbr-Ex.R’ failed
The error most likely occurred in:
> ### Name: fetch_data
> ### Title: fetch_data function
> ### Aliases: fetch_data
>
> ### ** Examples
>
> # Features and labels in single data frame
> penguins <- fetch_data("penguins")
trying URL 'https://github.com/EpistasisLab/pmlb/raw/master/datasets/penguins/penguins.tsv.gz'
Warning in utils::download.file(url, destfile) :
URL 'https://media.githubusercontent.com/media/EpistasisLab/pmlb/master/datasets/penguins/penguins.tsv.gz': status was 'SSL peer certificate or SSH remote key was not OK'
Attempt 1 failed: cannot open URL 'https://github.com/EpistasisLab/pmlb/raw/master/datasets/penguins/penguins.tsv.gz'
trying URL 'https://github.com/EpistasisLab/pmlb/raw/master/datasets/penguins/penguins.tsv.gz'
Warning in utils::download.file(url, destfile) :
URL 'https://media.githubusercontent.com/media/EpistasisLab/pmlb/master/datasets/penguins/penguins.tsv.gz': status was 'SSL peer certificate or SSH remote key was not OK'
Attempt 2 failed: cannot open URL 'https://github.com/EpistasisLab/pmlb/raw/master/datasets/penguins/penguins.tsv.gz'
trying URL 'https://github.com/EpistasisLab/pmlb/raw/master/datasets/penguins/penguins.tsv.gz'
Warning in utils::download.file(url, destfile) :
URL 'https://media.githubusercontent.com/media/EpistasisLab/pmlb/master/datasets/penguins/penguins.tsv.gz': status was 'SSL peer certificate or SSH remote key was not OK'
Attempt 3 failed: cannot open URL 'https://github.com/EpistasisLab/pmlb/raw/master/datasets/penguins/penguins.tsv.gz'
Warning in graceful_download(dataset_url, tmp) :
Download failed after 3 attempts.
Continuing gracefully without the dataset.
Error in fetch_data("penguins") : object 'dataset' not found
Calls: fetch_data -> <Anonymous>
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Current CRAN status: ERROR: 1, OK: 12
Version: 0.2.1
Check: examples
Result: ERROR
Running examples in ‘treeheatr-Ex.R’ failed
The error most likely occurred in:
> ### Name: compute_tree
> ### Title: Compute decision tree from data set
> ### Aliases: compute_tree
>
> ### ** Examples
>
> fit_tree <- compute_tree(penguins, target_lab = 'species')
*** caught segfault ***
address 0x1, cause 'memory not mapped'
Traceback:
1: method$fun(x, control = control)
2: system.time(order <- method$fun(x, control = control))
3: seriate.dist(., method = "ARSA")
4: seriation::seriate(., method = "ARSA")
5: seriation::get_order(.)
6: df[, clust_vec] %>% cluster::daisy(metric = "gower") %>% seriation::seriate(method = "ARSA") %>% seriation::get_order()
7: FUN(X[[i]], ...)
8: lapply(unique(.$node_id), clust_samp_func, dat = ., clust_vec = if (clust_target) colnames(data) else setdiff(colnames(data), fit$target_lab), clust_samps = clust_samps)
9: list2(...)
10: bind_rows(.)
11: mutate(., Sample = row_number())
12: data %>% cbind(node_id = node_pred, y_hat = y_pred) %>% lapply(unique(.$node_id), clust_samp_func, dat = ., clust_vec = if (clust_target) colnames(data) else setdiff(colnames(data), fit$target_lab), clust_samps = clust_samps) %>% bind_rows() %>% mutate(Sample = row_number())
13: prediction_df(fit, task, clust_samps, clust_target)
14: compute_tree(penguins, target_lab = "species")
An irrecoverable exception occurred. R is aborting now ...
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.2.1
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
--- re-building ‘explore.Rmd’ using rmarkdown
*** caught segfault ***
address 0x1, cause 'memory not mapped'
Traceback:
1: method$fun(x, control = control)
2: system.time(order <- method$fun(x, control = control))
3: seriate.dist(., method = "ARSA")
4: seriation::seriate(., method = "ARSA")
5: seriation::get_order(.)
6: df[, clust_vec] %>% cluster::daisy(metric = "gower") %>% seriation::seriate(method = "ARSA") %>% seriation::get_order()
7: FUN(X[[i]], ...)
8: lapply(unique(.$node_id), clust_samp_func, dat = ., clust_vec = if (clust_target) colnames(data) else setdiff(colnames(data), fit$target_lab), clust_samps = clust_samps)
9: list2(...)
10: bind_rows(.)
11: mutate(., Sample = row_number())
12: data %>% cbind(node_id = node_pred, y_hat = y_pred) %>% lapply(unique(.$node_id), clust_samp_func, dat = ., clust_vec = if (clust_target) colnames(data) else setdiff(colnames(data), fit$target_lab), clust_samps = clust_samps) %>% bind_rows() %>% mutate(Sample = row_number())
13: prediction_df(fit, task, clust_samps, clust_target)
14: compute_tree(x = penguins, target_lab = "species")
15: eval(ctree_result, parent.frame())
16: eval(ctree_result, parent.frame())
17: heat_tree(penguins, target_lab = "species")
18: eval(expr, envir)
19: eval(expr, envir)
20: withVisible(eval(expr, envir))
21: withCallingHandlers(code, message = function (cnd) { watcher$capture_plot_and_output() if (on_message$capture) { watcher$push(cnd) } if (on_message$silence) { invokeRestart("muffleMessage") }}, warning = function (cnd) { if (getOption("warn") >= 2 || getOption("warn") < 0) { return() } watcher$capture_plot_and_output() if (on_warning$capture) { cnd <- sanitize_call(cnd) watcher$push(cnd) } if (on_warning$silence) { invokeRestart("muffleWarning") }}, error = function (cnd) { watcher$capture_plot_and_output() cnd <- sanitize_call(cnd) watcher$push(cnd) switch(on_error, continue = invokeRestart("eval_continue"), stop = invokeRestart("eval_stop"), error = invokeRestart("eval_error", cnd))})
22: eval(call)
23: eval(call)
24: with_handlers({ for (expr in tle$exprs) { ev <- withVisible(eval(expr, envir)) watcher$capture_plot_and_output() watcher$print_value(ev$value, ev$visible, envir) } TRUE}, handlers)
25: doWithOneRestart(return(expr), restart)
26: withOneRestart(expr, restarts[[1L]])
27: withRestartList(expr, restarts[-nr])
28: doWithOneRestart(return(expr), restart)
29: withOneRestart(withRestartList(expr, restarts[-nr]), restarts[[nr]])
30: withRestartList(expr, restarts[-nr])
31: doWithOneRestart(return(expr), restart)
32: withOneRestart(withRestartList(expr, restarts[-nr]), restarts[[nr]])
33: withRestartList(expr, restarts)
34: withRestarts(with_handlers({ for (expr in tle$exprs) { ev <- withVisible(eval(expr, envir)) watcher$capture_plot_and_output() watcher$print_value(ev$value, ev$visible, envir) } TRUE}, handlers), eval_continue = function() TRUE, eval_stop = function() FALSE, eval_error = function(cnd) { signalCondition(cnd) stop(cnd) })
35: evaluate::evaluate(...)
36: evaluate(code, envir = env, new_device = FALSE, keep_warning = if (is.numeric(options$warning)) TRUE else options$warning, keep_message = if (is.numeric(options$message)) TRUE else options$message, stop_on_error = if (is.numeric(options$error)) options$error else { if (options$error && options$include) 0L else 2L }, output_handler = knit_handlers(options$render, options))
37: in_dir(input_dir(), expr)
38: in_input_dir(evaluate(code, envir = env, new_device = FALSE, keep_warning = if (is.numeric(options$warning)) TRUE else options$warning, keep_message = if (is.numeric(options$message)) TRUE else options$message, stop_on_error = if (is.numeric(options$error)) options$error else { if (options$error && options$include) 0L else 2L }, output_handler = knit_handlers(options$render, options)))
39: eng_r(options)
40: block_exec(params)
41: call_block(x)
42: process_group(group)
43: withCallingHandlers(if (tangle) process_tangle(group) else process_group(group), error = function(e) if (xfun::pkg_available("rlang", "1.0.0")) rlang::entrace(e))
44: xfun:::handle_error(withCallingHandlers(if (tangle) process_tangle(group) else process_group(group), error = function(e) if (xfun::pkg_available("rlang", "1.0.0")) rlang::entrace(e)), function(loc) { setwd(wd) write_utf8(res, output %n% stdout()) paste0("\nQuitting from lines ", loc) }, if (labels[i] != "") sprintf(" [%s]", labels[i]), get_loc)
45: process_file(text, output)
46: knitr::knit(knit_input, knit_output, envir = envir, quiet = quiet)
47: rmarkdown::render(file, encoding = encoding, quiet = quiet, envir = globalenv(), output_dir = getwd(), ...)
48: vweave_rmarkdown(...)
49: engine$weave(file, quiet = quiet, encoding = enc)
50: doTryCatch(return(expr), name, parentenv, handler)
51: tryCatchOne(expr, names, parentenv, handlers[[1L]])
52: tryCatchList(expr, classes, parentenv, handlers)
53: tryCatch({ engine$weave(file, quiet = quiet, encoding = enc) setwd(startdir) output <- find_vignette_product(name, by = "weave", engine = engine) if (!have.makefile && vignette_is_tex(output)) { texi2pdf(file = output, clean = FALSE, quiet = quiet) output <- find_vignette_product(name, by = "texi2pdf", engine = engine) } outputs <- c(outputs, output)}, error = function(e) { thisOK <<- FALSE fails <<- c(fails, file) message(gettextf("Error: processing vignette '%s' failed with diagnostics:\n%s", file, conditionMessage(e)))})
54: tools::buildVignettes(dir = "/data/gannet/ripley/R/packages/tests-devel/treeheatr.Rcheck/vign_test/treeheatr", skip = TRUE, ser_elibs = "/tmp/RtmpLGhJY5/file2b0c4f7bb9e793.rds")
An irrecoverable exception occurred. R is aborting now ...
Flavor: r-devel-linux-x86_64-fedora-gcc