• using R Under development (unstable) (2026-02-12 r89409)
  • using platform: aarch64-apple-darwin23
  • R was compiled by     Apple clang version 17.0.0 (clang-1700.3.19.1)     GNU Fortran (GCC) 14.2.0
  • running under: macOS Sequoia 15.7.1
  • using session charset: UTF-8 * current time: 2026-02-13 02:27:13 UTC
  • checking for file ‘inferCSN/DESCRIPTION’ ... OK
  • checking extension type ... Package
  • this is package ‘inferCSN’ version ‘1.2.0’
  • package encoding: UTF-8
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  • checking for portable file names ... OK
  • checking for sufficient/correct file permissions ... OK
  • checking whether package ‘inferCSN’ can be installed ... [10s/6s] OK See the install log for details.
  • used C++ compiler: ‘Apple clang version 17.0.0 (clang-1700.3.19.1)’
  • used SDK: ‘MacOSX14.5.sdk’
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  • checking code files for non-ASCII characters ... OK
  • checking R files for syntax errors ... OK
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  • checking examples ... [3s/3s] ERROR Running examples in ‘inferCSN-Ex.R’ failed The error most likely occurred in: > ### Name: inferCSN > ### Title: inferring cell-type specific gene regulatory network > ### Aliases: inferCSN inferCSN,matrix-method inferCSN,sparseMatrix-method > ### inferCSN,data.frame-method > > ### ** Examples > > data(example_matrix) > network_table_1 <- inferCSN( + example_matrix + ) ℹ [2026-02-13 15:27:47] Running for <dense matrix>. ◌ [2026-02-13 15:27:47] Checking input parameters... ℹ [2026-02-13 15:27:47] Using `L0` sparse regression model ℹ [2026-02-13 15:27:47] Using 1 core ℹ [2026-02-13 15:27:47] Building results ✔ [2026-02-13 15:27:47] Run done. > > network_table_2 <- inferCSN( + example_matrix, + cores = 2 + ) ℹ [2026-02-13 15:27:47] Running for <dense matrix>. ◌ [2026-02-13 15:27:47] Checking input parameters... ℹ [2026-02-13 15:27:47] Using `L0` sparse regression model ℹ [2026-02-13 15:27:47] Using 2 cores  *** caught segfault *** address 0x110, cause 'invalid permissions'  *** caught segfault *** address 0x110, cause 'invalid permissions' Traceback:  1: L0Learn::L0Learn.fit(x, y, penalty = penalty, maxSuppSize = regulators_num, ...)  2: doTryCatch(return(expr), name, parentenv, handler)  3: tryCatchOne(expr, names, parentenv, handlers[[1L]])  4: tryCatchList(expr, classes, parentenv, handlers)  5: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call, nlines = 1L) prefix <- paste("Error in", dcall, ": ") LONG <- 75L sm <- strsplit(conditionMessage(e), "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(msg[1L])) if (!silent && isTRUE(getOption("show.error.messages"))) { cat(msg, file = outFile) .Internal(printDeferredWarnings()) } invisible(structure(msg, class = "try-error", condition = e))})  6: try(L0Learn::L0Learn.fit(x, y, penalty = penalty, maxSuppSize = regulators_num, ...))  7: fit_srm(x, y, cross_validation = cross_validation, seed = seed, penalty = penalty, n_folds = n_folds, verbose = verbose, ...)  8: single_network(matrix = object, regulators = regulators, target = x, cross_validation = cross_validation, seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold, n_folds = n_folds, verbose = verbose, ...)  9: fun(x[[i]]) 10: doTryCatch(return(expr), name, parentenv, handler) 11: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 12: tryCatchList(expr, classes, parentenv, handlers) 13: tryCatch(fun(x[[i]]), error = function(e) { structure(list(error = e$message, index = i, input = x[[i]]), class = "parallelize_error")}) 14: eval(c.expr, envir = args, enclos = envir) 15: eval(c.expr, envir = args, enclos = envir) 16: doTryCatch(return(expr), name, parentenv, handler) 17: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 18: tryCatchList(expr, classes, parentenv, handlers) 19: tryCatch(eval(c.expr, envir = args, enclos = envir), error = function(e) e) 20: FUN(X[[i]], ...) 21: lapply(X = S, FUN = FUN, ...) 22: doTryCatch(return(expr), name, parentenv, handler) 23: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 24: tryCatchList(expr, classes, parentenv, handlers) 25: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call, nlines = 1L) prefix <- paste("Error in", dcall, ": ") LONG <- 75L sm <- strsplit(conditionMessage(e), "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(msg[1L])) if (!silent && isTRUE(getOption("show.error.messages"))) { cat(msg, file = outFile) .Internal(printDeferredWarnings()) } invisible(structure(msg, class = "try-error", condition = e))}) 26: try(lapply(X = S, FUN = FUN, ...), silent = TRUE) 27: sendMaster(try(lapply(X = S, FUN = FUN, ...), silent = TRUE)) 28: FUN(X[[i]], ...) 29: lapply(seq_len(cores), inner.do) 30: mclapply(argsList, FUN, mc.preschedule = preschedule, mc.set.seed = set.seed, mc.silent = silent, mc.cores = cores) 31: e$fun(obj, substitute(ex), parent.frame(), e$data) 32: foreach::foreach(i = chunk, .combine = "c", .export = export_fun) %dopar% { list(tryCatch(fun(x[[i]]), error = function(e) { structure(list(error = e$message, index = i, input = x[[i]]), class = "parallelize_error") })) } 33: thisutils::parallelize_fun(x = targets, fun = function(x) { single_network(matrix = object, regulators = regulators, target = x, cross_validation = cross_validation, seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold, n_folds = n_folds, verbose = verbose, ...)}, cores = cores, verbose = verbose) 34: obj_check_list(x, call = error_call) 35: check_list_of_data_frames(x) 36: purrr::list_rbind(thisutils::parallelize_fun(x = targets, fun = function(x) { single_network(matrix = object, regulators = regulators, target = x, cross_validation = cross_validation, seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold, n_folds = n_folds, verbose = verbose, ...)}, cores = cores, verbose = verbose)) 37: network_format(purrr::list_rbind(thisutils::parallelize_fun(x = targets, fun = function(x) { single_network(matrix = object, regulators = regulators, target = x, cross_validation = cross_validation, seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold, n_folds = n_folds, verbose = verbose, ...) }, cores = cores, verbose = verbose)), abs_weight = FALSE) 38: inferCSN(example_matrix, cores = 2) 39: inferCSN(example_matrix, cores = 2) An irrecoverable exception occurred. R is aborting now ... Traceback:  1: L0Learn::L0Learn.fit(x, y, penalty = penalty, maxSuppSize = regulators_num, ...)  2: doTryCatch(return(expr), name, parentenv, handler)  3: tryCatchOne(expr, names, parentenv, handlers[[1L]])  4: tryCatchList(expr, classes, parentenv, handlers)  5: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call, nlines = 1L) prefix <- paste("Error in", dcall, ": ") LONG <- 75L sm <- strsplit(conditionMessage(e), "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(msg[1L])) if (!silent && isTRUE(getOption("show.error.messages"))) { cat(msg, file = outFile) .Internal(printDeferredWarnings()) } invisible(structure(msg, class = "try-error", condition = e))})  6: try(L0Learn::L0Learn.fit(x, y, penalty = penalty, maxSuppSize = regulators_num, ...))  7: fit_srm(x, y, cross_validation = cross_validation, seed = seed, penalty = penalty, n_folds = n_folds, verbose = verbose, ...)  8: single_network(matrix = object, regulators = regulators, target = x, cross_validation = cross_validation, seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold, n_folds = n_folds, verbose = verbose, ...)  9: fun(x[[i]]) 10: doTryCatch(return(expr), name, parentenv, handler) 11: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 12: tryCatchList(expr, classes, parentenv, handlers) 13: tryCatch(fun(x[[i]]), error = function(e) { structure(list(error = e$message, index = i, input = x[[i]]), class = "parallelize_error")}) 14: eval(c.expr, envir = args, enclos = envir) 15: eval(c.expr, envir = args, enclos = envir) 16: doTryCatch(return(expr), name, parentenv, handler) 17: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 18: tryCatchList(expr, classes, parentenv, handlers) 19: tryCatch(eval(c.expr, envir = args, enclos = envir), error = function(e) e) 20: FUN(X[[i]], ...) 21: lapply(X = S, FUN = FUN, ...) 22: doTryCatch(return(expr), name, parentenv, handler) 23: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 24: tryCatchList(expr, classes, parentenv, handlers) 25: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call, nlines = 1L) prefix <- paste("Error in", dcall, ": ") LONG <- 75L sm <- strsplit(conditionMessage(e), "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(msg[1L])) if (!silent && isTRUE(getOption("show.error.messages"))) { cat(msg, file = outFile) .Internal(printDeferredWarnings()) } invisible(structure(msg, class = "try-error", condition = e))}) 26: try(lapply(X = S, FUN = FUN, ...), silent = TRUE) 27: sendMaster(try(lapply(X = S, FUN = FUN, ...), silent = TRUE)) 28: FUN(X[[i]], ...) 29: lapply(seq_len(cores), inner.do) 30: mclapply(argsList, FUN, mc.preschedule = preschedule, mc.set.seed = set.seed, mc.silent = silent, mc.cores = cores) 31: e$fun(obj, substitute(ex), parent.frame(), e$data) 32: foreach::foreach(i = chunk, .combine = "c", .export = export_fun) %dopar% { list(tryCatch(fun(x[[i]]), error = function(e) { structure(list(error = e$message, index = i, input = x[[i]]), class = "parallelize_error") })) } 33: thisutils::parallelize_fun(x = targets, fun = function(x) { single_network(matrix = object, regulators = regulators, target = x, cross_validation = cross_validation, seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold, n_folds = n_folds, verbose = verbose, ...)}, cores = cores, verbose = verbose) 34: obj_check_list(x, call = error_call) 35: check_list_of_data_frames(x) 36: purrr::list_rbind(thisutils::parallelize_fun(x = targets, fun = function(x) { single_network(matrix = object, regulators = regulators, target = x, cross_validation = cross_validation, seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold, n_folds = n_folds, verbose = verbose, ...)}, cores = cores, verbose = verbose)) 37: network_format(purrr::list_rbind(thisutils::parallelize_fun(x = targets, fun = function(x) { single_network(matrix = object, regulators = regulators, target = x, cross_validation = cross_validation, seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold, n_folds = n_folds, verbose = verbose, ...) }, cores = cores, verbose = verbose)), abs_weight = FALSE) 38: inferCSN(example_matrix, cores = 2) 39: inferCSN(example_matrix, cores = 2) An irrecoverable exception occurred. R is aborting now ... Warning in mclapply(argsList, FUN, mc.preschedule = preschedule, mc.set.seed = set.seed, :   scheduled cores 1, 2 did not deliver results, all values of the jobs will be affected  *** caught segfault *** address 0x110, cause 'invalid permissions'  *** caught segfault *** address 0x110, cause 'invalid permissions' Traceback:  1: L0Learn::L0Learn.fit(x, y, penalty = penalty, maxSuppSize = regulators_num, ...)  2: doTryCatch(return(expr), name, parentenv, handler)  3: tryCatchOne(expr, names, parentenv, handlers[[1L]])  4: tryCatchList(expr, classes, parentenv, handlers)  5: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call, nlines = 1L) prefix <- paste("Error in", dcall, ": ") LONG <- 75L sm <- strsplit(conditionMessage(e), "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(msg[1L])) if (!silent && isTRUE(getOption("show.error.messages"))) { cat(msg, file = outFile) .Internal(printDeferredWarnings()) } invisible(structure(msg, class = "try-error", condition = e))})  6: try(L0Learn::L0Learn.fit(x, y, penalty = penalty, maxSuppSize = regulators_num, ...))  7: fit_srm(x, y, cross_validation = cross_validation, seed = seed, penalty = penalty, n_folds = n_folds, verbose = verbose, ...)  8: single_network(matrix = object, regulators = regulators, target = x, cross_validation = cross_validation, seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold, n_folds = n_folds, verbose = verbose, ...)  9: fun(x[[i]]) 10: doTryCatch(return(expr), name, parentenv, handler) 11: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 12: tryCatchList(expr, classes, parentenv, handlers) 13: tryCatch(fun(x[[i]]), error = function(e) { structure(list(error = e$message, index = i, input = x[[i]]), class = "parallelize_error")}) 14: eval(c.expr, envir = args, enclos = envir) 15: eval(c.expr, envir = args, enclos = envir) 16: doTryCatch(return(expr), name, parentenv, handler) 17: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 18: tryCatchList(expr, classes, parentenv, handlers) 19: tryCatch(eval(c.expr, envir = args, enclos = envir), error = function(e) e) 20: FUN(X[[i]], ...) 21: lapply(X = S, FUN = FUN, ...) 22: doTryCatch(return(expr), name, parentenv, handler) 23: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 24: tryCatchList(expr, classes, parentenv, handlers) 25: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call, nlines = 1L) prefix <- paste("Error in", dcall, ": ") LONG <- 75L sm <- strsplit(conditionMessage(e), "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(msg[1L])) if (!silent && isTRUE(getOption("show.error.messages"))) { cat(msg, file = outFile) .Internal(printDeferredWarnings()) } invisible(structure(msg, class = "try-error", condition = e))}) 26: try(lapply(X = S, FUN = FUN, ...), silent = TRUE) 27: sendMaster(try(lapply(X = S, FUN = FUN, ...), silent = TRUE)) 28: FUN(X[[i]], ...) 29: lapply(seq_len(cores), inner.do) 30: mclapply(argsList, FUN, mc.preschedule = preschedule, mc.set.seed = set.seed, mc.silent = silent, mc.cores = cores) 31: e$fun(obj, substitute(ex), parent.frame(), e$data) 32: foreach::foreach(i = chunk, .combine = "c", .export = export_fun) %dopar% { list(tryCatch(fun(x[[i]]), error = function(e) { structure(list(error = e$message, index = i, input = x[[i]]), class = "parallelize_error") })) } 33: thisutils::parallelize_fun(x = targets, fun = function(x) { single_network(matrix = object, regulators = regulators, target = x, cross_validation = cross_validation, seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold, n_folds = n_folds, verbose = verbose, ...)}, cores = cores, verbose = verbose) 34: obj_check_list(x, call = error_call) 35: check_list_of_data_frames(x) 36: purrr::list_rbind(thisutils::parallelize_fun(x = targets, fun = function(x) { single_network(matrix = object, regulators = regulators, target = x, cross_validation = cross_validation, seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold, n_folds = n_folds, verbose = verbose, ...)}, cores = cores, verbose = verbose)) 37: network_format(purrr::list_rbind(thisutils::parallelize_fun(x = targets, fun = function(x) { single_network(matrix = object, regulators = regulators, target = x, cross_validation = cross_validation, seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold, n_folds = n_folds, verbose = verbose, ...) }, cores = cores, verbose = verbose)), abs_weight = FALSE) 38: inferCSN(example_matrix, cores = 2) 39: inferCSN(example_matrix, cores = 2) An irrecoverable exception occurred. R is aborting now ... Traceback:  1: L0Learn::L0Learn.fit(x, y, penalty = penalty, maxSuppSize = regulators_num, ...)  2: doTryCatch(return(expr), name, parentenv, handler)  3: tryCatchOne(expr, names, parentenv, handlers[[1L]])  4: tryCatchList(expr, classes, parentenv, handlers)  5: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call, nlines = 1L) prefix <- paste("Error in", dcall, ": ") LONG <- 75L sm <- strsplit(conditionMessage(e), "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(msg[1L])) if (!silent && isTRUE(getOption("show.error.messages"))) { cat(msg, file = outFile) .Internal(printDeferredWarnings()) } invisible(structure(msg, class = "try-error", condition = e))})  6: try(L0Learn::L0Learn.fit(x, y, penalty = penalty, maxSuppSize = regulators_num, ...))  7: fit_srm(x, y, cross_validation = cross_validation, seed = seed, penalty = penalty, n_folds = n_folds, verbose = verbose, ...)  8: single_network(matrix = object, regulators = regulators, target = x, cross_validation = cross_validation, seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold, n_folds = n_folds, verbose = verbose, ...)  9: fun(x[[i]]) 10: doTryCatch(return(expr), name, parentenv, handler) 11: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 12: tryCatchList(expr, classes, parentenv, handlers) 13: tryCatch(fun(x[[i]]), error = function(e) { structure(list(error = e$message, index = i, input = x[[i]]), class = "parallelize_error")}) 14: eval(c.expr, envir = args, enclos = envir) 15: eval(c.expr, envir = args, enclos = envir) 16: doTryCatch(return(expr), name, parentenv, handler) 17: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 18: tryCatchList(expr, classes, parentenv, handlers) 19: tryCatch(eval(c.expr, envir = args, enclos = envir), error = function(e) e) 20: FUN(X[[i]], ...) 21: lapply(X = S, FUN = FUN, ...) 22: doTryCatch(return(expr), name, parentenv, handler) 23: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 24: tryCatchList(expr, classes, parentenv, handlers) 25: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call, nlines = 1L) prefix <- paste("Error in", dcall, ": ") LONG <- 75L sm <- strsplit(conditionMessage(e), "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(msg[1L])) if (!silent && isTRUE(getOption("show.error.messages"))) { cat(msg, file = outFile) .Internal(printDeferredWarnings()) } invisible(structure(msg, class = "try-error", condition = e))}) 26: try(lapply(X = S, FUN = FUN, ...), silent = TRUE) 27: sendMaster(try(lapply(X = S, FUN = FUN, ...), silent = TRUE)) 28: FUN(X[[i]], ...) 29: lapply(seq_len(cores), inner.do) 30: mclapply(argsList, FUN, mc.preschedule = preschedule, mc.set.seed = set.seed, mc.silent = silent, mc.cores = cores) 31: e$fun(obj, substitute(ex), parent.frame(), e$data) 32: foreach::foreach(i = chunk, .combine = "c", .export = export_fun) %dopar% { list(tryCatch(fun(x[[i]]), error = function(e) { structure(list(error = e$message, index = i, input = x[[i]]), class = "parallelize_error") })) } 33: thisutils::parallelize_fun(x = targets, fun = function(x) { single_network(matrix = object, regulators = regulators, target = x, cross_validation = cross_validation, seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold, n_folds = n_folds, verbose = verbose, ...)}, cores = cores, verbose = verbose) 34: obj_check_list(x, call = error_call) 35: check_list_of_data_frames(x) 36: purrr::list_rbind(thisutils::parallelize_fun(x = targets, fun = function(x) { single_network(matrix = object, regulators = regulators, target = x, cross_validation = cross_validation, seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold, n_folds = n_folds, verbose = verbose, ...)}, cores = cores, verbose = verbose)) 37: network_format(purrr::list_rbind(thisutils::parallelize_fun(x = targets, fun = function(x) { single_network(matrix = object, regulators = regulators, target = x, cross_validation = cross_validation, seed = seed, penalty = penalty, r_squared_threshold = r_squared_threshold, n_folds = n_folds, verbose = verbose, ...) }, cores = cores, verbose = verbose)), abs_weight = FALSE) 38: inferCSN(example_matrix, cores = 2) 39: inferCSN(example_matrix, cores = 2) An irrecoverable exception occurred. R is aborting now ... Warning in mclapply(argsList, FUN, mc.preschedule = preschedule, mc.set.seed = set.seed, :   scheduled cores 1, 2 did not deliver results, all values of the jobs will be affected ℹ [2026-02-13 15:27:47] Building results Error in names(output_list) <- x : attempt to set an attribute on NULL Calls: inferCSN ... check_list_of_data_frames -> obj_check_list -> <Anonymous> Execution halted
  • checking PDF version of manual ... [2s/2s] OK
  • DONE Status: 1 ERROR
  • using check arguments '--no-clean-on-error '