CRAN Package Check Results for Package treeheatr

Last updated on 2024-10-14 07:49:54 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.2.1 5.99 224.78 230.77 OK
r-devel-linux-x86_64-debian-gcc 0.2.1 3.83 172.12 175.95 OK
r-devel-linux-x86_64-fedora-clang 0.2.1 374.28 OK
r-devel-linux-x86_64-fedora-gcc 0.2.1 95.67 ERROR
r-devel-windows-x86_64 0.2.1 7.00 219.00 226.00 OK
r-patched-linux-x86_64 0.2.1 5.52 217.63 223.15 OK
r-release-linux-x86_64 0.2.1 5.89 215.56 221.45 OK
r-release-macos-arm64 0.2.1 137.00 OK
r-release-macos-x86_64 0.2.1 198.00 OK
r-release-windows-x86_64 0.2.1 9.00 222.00 231.00 OK
r-oldrel-macos-arm64 0.2.1 110.00 OK
r-oldrel-macos-x86_64 0.2.1 195.00 OK
r-oldrel-windows-x86_64 0.2.1 9.00 278.00 287.00 OK

Check Details

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/Rtmp1i9qEq/file37f83d555224e4.rds") An irrecoverable exception occurred. R is aborting now ... Flavor: r-devel-linux-x86_64-fedora-gcc