CRAN Package Check Results for Package normalblockr

Last updated on 2026-09-11 21:51:08 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.2.1 50.54 228.81 279.35 OK
r-devel-linux-x86_64-debian-gcc 0.2.1 37.37 179.56 216.93 OK
r-devel-linux-x86_64-fedora-clang 0.3.0 46.00 ERROR
r-devel-linux-x86_64-fedora-gcc 0.2.1 43.00 154.90 197.90 ERROR
r-devel-windows-x86_64 0.2.1 57.00 330.00 387.00 OK
r-patched-linux-x86_64 0.2.1 51.09 223.76 274.85 OK
r-release-linux-x86_64 0.2.1 54.48 221.89 276.37 OK
r-release-macos-arm64 0.2.1 12.00 74.00 86.00 OK
r-release-macos-x86_64 0.2.1 38.00 252.00 290.00 OK
r-release-windows-x86_64 0.2.1 58.00 349.00 407.00 OK
r-oldrel-macos-arm64 0.2.1 OK
r-oldrel-macos-x86_64 0.2.1 39.00 290.00 329.00 OK
r-oldrel-windows-x86_64 0.2.1 80.00 340.00 420.00 OK

Additional issues

linux-arm64

Check Details

Version: 0.3.0
Check: tests
Result: ERROR Running ‘testthat.R’ [15s/18s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > # This file is part of the standard setup for testthat. > # It is recommended that you do not modify it. > # > # Where should you do additional test configuration? > # Learn more about the roles of various files in: > # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview > # * https://testthat.r-lib.org/articles/special-files.html > > library(testthat) > library(normalblockr) > > test_check("normalblockr") number of blocks = 1 number of blocks = 2 number of blocks = 3 number of blocks = 2 number of blocks = 3 number of blocks = 4 number of blocks = 2 penalty = 0.2315772 penalty = 0.1975743 penalty = 0.168564 penalty = 0.1438134 penalty = 0.122697 penalty = 0.1046811 penalty = 0.08931055 penalty = 0.07619689 penalty = 0.06500874 penalty = 0.05546336 penalty = 0.04731956 penalty = 0.04037153 penalty = 0.03444369 penalty = 0.02938625 penalty = 0.0250714 penalty = 0.02139011 penalty = 0.01824936 penalty = 0.01556977 penalty = 0.01328362 penalty = 0.01133316 penalty = 0.009669088 penalty = 0.008249355 penalty = 0.007038085 penalty = 0.006004668 penalty = 0.005122989 penalty = 0.00437077 penalty = 0.003729 penalty = 0.003181463 penalty = 0.002714322 penalty = 0.002315772 number of blocks = 3 penalty = 0.2959283 penalty = 0.2524765 penalty = 0.2154049 penalty = 0.1837765 penalty = 0.1567922 penalty = 0.1337701 penalty = 0.1141283 penalty = 0.09737062 penalty = 0.08307348 penalty = 0.07087562 penalty = 0.0604688 penalty = 0.05159004 penalty = 0.04401496 penalty = 0.03755215 penalty = 0.03203829 penalty = 0.02733404 penalty = 0.02332052 penalty = 0.01989632 penalty = 0.0169749 penalty = 0.01448244 penalty = 0.01235595 penalty = 0.0105417 penalty = 0.00899384 penalty = 0.007673255 penalty = 0.006546575 penalty = 0.005585327 penalty = 0.004765222 penalty = 0.004065534 penalty = 0.003468583 penalty = 0.002959283 number of blocks = 4 penalty = 0.3171464 penalty = 0.2705791 penalty = 0.2308494 penalty = 0.1969533 penalty = 0.1680342 penalty = 0.1433614 penalty = 0.1223113 penalty = 0.1043521 penalty = 0.08902984 penalty = 0.0759574 penalty = 0.06480441 penalty = 0.05528904 penalty = 0.04717083 penalty = 0.04024464 penalty = 0.03433543 penalty = 0.02929389 penalty = 0.0249926 penalty = 0.02132288 penalty = 0.018192 penalty = 0.01552083 penalty = 0.01324187 penalty = 0.01129754 penalty = 0.009638698 penalty = 0.008223427 penalty = 0.007015964 penalty = 0.005985795 penalty = 0.005106888 penalty = 0.004357032 penalty = 0.00371728 penalty = 0.003171464 number of blocks = 2 penalty = 0.3050263 penalty = 0.2602386 penalty = 0.2220272 penalty = 0.1894265 penalty = 0.1616126 penalty = 0.1378827 penalty = 0.1176371 penalty = 0.1003642 penalty = 0.08562747 penalty = 0.0730546 penalty = 0.06232784 penalty = 0.05317611 penalty = 0.04536815 penalty = 0.03870664 penalty = 0.03302326 penalty = 0.02817439 penalty = 0.02403748 penalty = 0.02050801 penalty = 0.01749677 penalty = 0.01492768 penalty = 0.01273582 penalty = 0.01086579 penalty = 0.009270344 penalty = 0.00790916 penalty = 0.006747841 penalty = 0.005757041 penalty = 0.004911722 penalty = 0.004190523 penalty = 0.00357522 penalty = 0.003050263 number of blocks = 3 penalty = 0.3303011 penalty = 0.2818023 penalty = 0.2404246 penalty = 0.2051226 penalty = 0.175004 penalty = 0.1493078 penalty = 0.1273846 penalty = 0.1086804 penalty = 0.09272265 penalty = 0.07910799 penalty = 0.06749239 penalty = 0.05758234 penalty = 0.0491274 penalty = 0.04191392 penalty = 0.03575961 penalty = 0.03050895 penalty = 0.02602925 penalty = 0.02220732 penalty = 0.01894657 penalty = 0.01616461 penalty = 0.01379112 penalty = 0.01176614 penalty = 0.0100385 penalty = 0.008564521 penalty = 0.007306974 penalty = 0.006234076 penalty = 0.005318713 penalty = 0.004537755 penalty = 0.003871467 penalty = 0.003303011 number of blocks = 4 penalty = 0.5085554 penalty = 0.4338831 penalty = 0.3701751 penalty = 0.3158215 penalty = 0.2694488 penalty = 0.229885 penalty = 0.1961305 penalty = 0.1673322 penalty = 0.1427625 penalty = 0.1218004 penalty = 0.1039162 penalty = 0.08865792 penalty = 0.07564009 penalty = 0.06453369 penalty = 0.05505807 penalty = 0.04697378 penalty = 0.04007652 penalty = 0.034192 penalty = 0.02917151 penalty = 0.0248882 penalty = 0.02123381 penalty = 0.018116 penalty = 0.01545599 penalty = 0.01318656 penalty = 0.01125034 penalty = 0.009598433 penalty = 0.008189074 penalty = 0.006986655 penalty = 0.005960789 penalty = 0.005085554 No model with this penalty in the collection. Returning model with closest penalty: 0.0927226549989336 Collection penalty values can be found via $sparsity penalty = 0.2959283 penalty = 0.2524765 penalty = 0.2154049 penalty = 0.1837765 penalty = 0.1567922 penalty = 0.1337701 penalty = 0.1141283 penalty = 0.09737062 penalty = 0.08307348 penalty = 0.07087562 penalty = 0.0604688 penalty = 0.05159004 penalty = 0.04401496 penalty = 0.03755215 penalty = 0.03203829 penalty = 0.02733404 penalty = 0.02332052 penalty = 0.01989632 penalty = 0.0169749 penalty = 0.01448244 penalty = 0.01235595 penalty = 0.0105417 penalty = 0.00899384 penalty = 0.007673255 penalty = 0.006546575 penalty = 0.005585327 penalty = 0.004765222 penalty = 0.004065534 penalty = 0.003468583 penalty = 0.002959283 penalty = 0.3303011 penalty = 0.2818023 penalty = 0.2404246 penalty = 0.2051226 penalty = 0.175004 penalty = 0.1493078 penalty = 0.1273846 penalty = 0.1086804 penalty = 0.09272265 penalty = 0.07910799 penalty = 0.06749239 penalty = 0.05758234 penalty = 0.0491274 penalty = 0.04191392 penalty = 0.03575961 penalty = 0.03050895 penalty = 0.02602925 penalty = 0.02220732 penalty = 0.01894657 penalty = 0.01616461 penalty = 0.01379112 penalty = 0.01176614 penalty = 0.0100385 penalty = 0.008564521 penalty = 0.007306974 penalty = 0.006234076 penalty = 0.005318713 penalty = 0.004537755 penalty = 0.003871467 penalty = 0.003303011 A diagonal normal-block-var model with 3 unknown blocks . =========================================================================== nb_param q n_edges sparsity loglik deviance BIC ICL EBIC niter 48 3 3 0 -912.19 1824.379 2034.716 1727.892 2041.308 8 =========================================================================== * Useful fields $model_par, $posterior_par / $var_par, $clustering $loglik, $BIC, $ICL, $objective, $nb_param, $criteria * Useful S3 methods print(), summary(), plot(), coef(), sigma(), fitted(), predict() A diagonal normal-block-var model with unknown q =========================================================================== 3 model(s) explored q ranging from 2 to 4 =========================================================================== * Useful fields $models, $criteria * Useful methods print(), summary(), plot(), $get_best_model() Saving _problems/test-clustering-heuristics-18.R Saving _problems/test-clustering-heuristics-58.R Saving _problems/test-clustering-heuristics-90.R A sequential mean-then-variance normal-block fit =========================================================================== mean-block stage : 3 clusters -- diagonal normal-block-mean model with fixed blocks variance-block stage: 2 clusters -- diagonal normal-block-var model with 2 unknown blocks ARI between the two partitions: -0.032 (near 0 means the two structures are unrelated, as is usual) =========================================================================== * Useful fields $mean, $var (both ordinary fitted models), $residuals Saving _problems/test-shared-initialization-186.R Saving _problems/test-shared-initialization-204.R Saving _problems/test-shared-initialization-210.R Saving _problems/test-shared-initialization-237.R Saving _problems/test-shared-initialization-244.R Saving _problems/test-shared-initialization-253.R [ FAIL 9 | WARN 59 | SKIP 0 | PASS 560 ] ══ Failed tests ════════════════════════════════════════════════════════════════ ── Failure ('test-clustering-heuristics.R:18:5'): every user-selectable clustering heuristic name produces a valid q-cluster init ── Expected `model$optimize(control = list(niter = 2, threshold = -1))` not to throw any errors. Actually got a <functionNotFoundError> with message: could not find function "initRefFields" ── Error ('test-clustering-heuristics.R:58:3'): the heuristics reach comparable optima on a variance-block model ── <functionNotFoundError/objectNotFoundError/error/condition> Error in `initRefFields(.self, .refClassDef, as.environment(.self), list(...))`: could not find function "initRefFields" Backtrace: ▆ 1. └─model_sbm$optimize() at test-clustering-heuristics.R:58:3 2. └─private$optimizer(control) 3. └─private$optim_initialize() 4. └─private$get_heuristic_parameters() 5. └─private$heuristic_clustering(reg_res$R) 6. └─private$clustering_methods[[private$clustering_approx]](R, self$q) 7. └─sbm::estimateSimpleSBM(cov(R), "gaussian", estimOptions = options) 8. └─mySBM$optimize(currentOptions) 9. ├─base::do.call(paste0("BM_", model_type), args) 10. └─blockmodels::BM_gaussian(...) 11. └─methods::new(`<chr>`, ...) 12. ├─methods::initialize(value, ...) 13. └─methods::initialize(value, ...) 14. └─.Object$initialize(...) 15. └─.self$initFields(...) ── Error ('test-clustering-heuristics.R:90:3'): the heuristics reach comparable optima on a zero-inflated model ── <functionNotFoundError/objectNotFoundError/error/condition> Error in `initRefFields(.self, .refClassDef, as.environment(.self), list(...))`: could not find function "initRefFields" Backtrace: ▆ 1. └─model_sbm$optimize() at test-clustering-heuristics.R:90:3 2. └─private$optimizer(control) 3. └─private$optim_initialize() 4. └─private$get_heuristic_parameters() 5. └─private$heuristic_clustering(zi_diag$R) 6. └─private$clustering_methods[[private$clustering_approx]](R, self$q) 7. └─sbm::estimateSimpleSBM(cov(R), "gaussian", estimOptions = options) 8. └─mySBM$optimize(currentOptions) 9. ├─base::do.call(paste0("BM_", model_type), args) 10. └─blockmodels::BM_gaussian(...) 11. └─methods::new(`<chr>`, ...) 12. ├─methods::initialize(value, ...) 13. └─methods::initialize(value, ...) 14. └─.Object$initialize(...) 15. └─.self$initFields(...) ── Error ('test-shared-initialization.R:186:3'): sbm_clustering_path() returns one valid membership vector per q, named by q, never NULL ── <functionNotFoundError/objectNotFoundError/error/condition> Error in `initRefFields(.self, .refClassDef, as.environment(.self), list(...))`: could not find function "initRefFields" Backtrace: ▆ 1. └─normalblockr:::sbm_clustering_path(sbm_R, q_list) at test-shared-initialization.R:186:3 2. └─sbm::estimateSimpleSBM(stats::cov(R), "gaussian", estimOptions = options) 3. └─mySBM$optimize(currentOptions) 4. ├─base::do.call(paste0("BM_", model_type), args) 5. └─blockmodels::BM_gaussian(...) 6. └─methods::new(`<chr>`, ...) 7. ├─methods::initialize(value, ...) 8. └─methods::initialize(value, ...) 9. └─.Object$initialize(...) 10. └─.self$initFields(...) ── Error ('test-shared-initialization.R:204:3'): sbm_clustering_path() falls back to a cheap ward2 clustering for q's the SBM exploration doesn't reach ── <functionNotFoundError/objectNotFoundError/error/condition> Error in `initRefFields(.self, .refClassDef, as.environment(.self), list(...))`: could not find function "initRefFields" Backtrace: ▆ 1. └─normalblockr:::sbm_clustering_path(sbm_R, q_list) at test-shared-initialization.R:204:3 2. └─sbm::estimateSimpleSBM(stats::cov(R), "gaussian", estimOptions = options) 3. └─mySBM$optimize(currentOptions) 4. ├─base::do.call(paste0("BM_", model_type), args) 5. └─blockmodels::BM_gaussian(...) 6. └─methods::new(`<chr>`, ...) 7. ├─methods::initialize(value, ...) 8. └─methods::initialize(value, ...) 9. └─.Object$initialize(...) 10. └─.self$initFields(...) ── Error ('test-shared-initialization.R:210:3'): NormalBlockVarCollectionClusters with clustering_init = 'sbm' eagerly resolves it from the shared path ── <functionNotFoundError/objectNotFoundError/error/condition> Error in `initRefFields(.self, .refClassDef, as.environment(.self), list(...))`: could not find function "initRefFields" Backtrace: ▆ 1. └─NormalBlockVarCollectionClusters$new(...) at test-shared-initialization.R:210:3 2. └─normalblockr (local) initialize(...) 3. └─normalblockr:::clustering_path_for_family(...) 4. └─normalblockr:::clustering_path_for_collection(R, q_list, method) 5. └─normalblockr:::sbm_clustering_path(R, q_list) 6. └─sbm::estimateSimpleSBM(stats::cov(R), "gaussian", estimOptions = options) 7. └─mySBM$optimize(currentOptions) 8. ├─base::do.call(paste0("BM_", model_type), args) 9. └─blockmodels::BM_gaussian(...) 10. └─methods::new(`<chr>`, ...) 11. ├─methods::initialize(value, ...) 12. └─methods::initialize(value, ...) 13. └─.Object$initialize(...) 14. └─.self$initFields(...) ── Error ('test-shared-initialization.R:235:3'): NormalBlockVarCollectionClustersSparsity also uses the shared sbm path ── <functionNotFoundError/objectNotFoundError/error/condition> Error in `initRefFields(.self, .refClassDef, as.environment(.self), list(...))`: could not find function "initRefFields" Backtrace: ▆ 1. └─NormalBlockVarCollectionClustersSparsity$new(...) at test-shared-initialization.R:235:3 2. └─normalblockr (local) initialize(...) 3. └─normalblockr:::clustering_path_for_family(...) 4. └─normalblockr:::clustering_path_for_collection(R, q_list, method) 5. └─normalblockr:::sbm_clustering_path(R, q_list) 6. └─sbm::estimateSimpleSBM(stats::cov(R), "gaussian", estimOptions = options) 7. └─mySBM$optimize(currentOptions) 8. ├─base::do.call(paste0("BM_", model_type), args) 9. └─blockmodels::BM_gaussian(...) 10. └─methods::new(`<chr>`, ...) 11. ├─methods::initialize(value, ...) 12. └─methods::initialize(value, ...) 13. └─.Object$initialize(...) 14. └─.self$initFields(...) ── Error ('test-shared-initialization.R:244:3'): sbm_clustering_path()'s ward2 fallback does not error on a (near-)constant column ── <functionNotFoundError/objectNotFoundError/error/condition> Error in `initRefFields(.self, .refClassDef, as.environment(.self), list(...))`: could not find function "initRefFields" Backtrace: ▆ 1. ├─testthat::expect_no_warning(...) at test-shared-initialization.R:244:3 2. │ └─testthat:::expect_no_(...) 3. │ └─testthat:::quasi_capture(enquo(object), NULL, capture) 4. │ ├─testthat (local) .capture(...) 5. │ │ ├─base::withRestarts(...) 6. │ │ │ └─base (local) withOneRestart(expr, restarts[[1L]]) 7. │ │ │ └─base (local) doWithOneRestart(return(expr), restart) 8. │ │ └─base::withCallingHandlers(...) 9. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo)) 10. └─normalblockr:::sbm_clustering_path(sbm_R_const, 2:20) 11. └─sbm::estimateSimpleSBM(stats::cov(R), "gaussian", estimOptions = options) 12. └─mySBM$optimize(currentOptions) 13. ├─base::do.call(paste0("BM_", model_type), args) 14. └─blockmodels::BM_gaussian(...) 15. └─methods::new(`<chr>`, ...) 16. ├─methods::initialize(value, ...) 17. └─methods::initialize(value, ...) 18. └─.Object$initialize(...) 19. └─.self$initFields(...) ── Error ('test-shared-initialization.R:252:3'): zero-inflated collections also use the shared sbm path, clustering on zi_residuals() instead of ols_residuals() ── <functionNotFoundError/objectNotFoundError/error/condition> Error in `initRefFields(.self, .refClassDef, as.environment(.self), list(...))`: could not find function "initRefFields" Backtrace: ▆ 1. └─NormalBlockVarCollectionClusters$new(...) at test-shared-initialization.R:252:3 2. └─normalblockr (local) initialize(...) 3. └─normalblockr:::clustering_path_for_family(...) 4. └─normalblockr:::clustering_path_for_collection(R, q_list, method) 5. └─normalblockr:::sbm_clustering_path(R, q_list) 6. └─sbm::estimateSimpleSBM(stats::cov(R), "gaussian", estimOptions = options) 7. └─mySBM$optimize(currentOptions) 8. ├─base::do.call(paste0("BM_", model_type), args) 9. └─blockmodels::BM_gaussian(...) 10. └─methods::new(`<chr>`, ...) 11. ├─methods::initialize(value, ...) 12. └─methods::initialize(value, ...) 13. └─.Object$initialize(...) 14. └─.self$initFields(...) [ FAIL 9 | WARN 59 | SKIP 0 | PASS 560 ] Error: ! Test failures. Execution halted Flavor: r-devel-linux-x86_64-fedora-clang

Version: 0.2.1
Check: re-building of vignette outputs
Result: ERROR Error(s) in re-building vignettes: --- re-building ‘breast-cancer-proteomics.Rmd’ using rmarkdown malloc(): unsorted double linked list corrupted --- re-building ‘normal-block.Rmd’ using rmarkdown [WARNING] Deprecated: --mathjax. Use --math-method=mathjax[:URL] instead. --- finished re-building ‘normal-block.Rmd’ --- re-building ‘zero-inflated-normal-block.Rmd’ using rmarkdown [WARNING] Deprecated: --mathjax. Use --math-method=mathjax[:URL] instead. --- finished re-building ‘zero-inflated-normal-block.Rmd’ SUMMARY: processing the following file failed: ‘breast-cancer-proteomics.Rmd’ Error: Vignette re-building failed. Execution halted Flavor: r-devel-linux-x86_64-fedora-gcc