Running rarecurve() crashes vscode in querying par()
maartenciers opened this issue · 8 comments
When I'm Running:
size = min(colSums2(assay(tseObj)))
ASVs = t(assay(tseObj,"counts")[])
rare_df = rarecurve(ASVs, sample = size, tidy = TRUE, step = 10)
It crashes my terminal in vscode. I can't see the error as it crashes to quickly and the terminal disappears.
SessionInfo:
> sessionInfo()
R version 4.4.0 (2024-04-24)
Platform: x86_64-redhat-linux-gnu
Running under: AlmaLinux 9.4 (Seafoam Ocelot)
Matrix products: default
BLAS/LAPACK: FlexiBLAS OPENBLAS-OPENMP; LAPACK version 3.9.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
time zone: Europe/Brussels
tzcode source: system (glibc)
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] miaViz_1.12.0 ggraph_2.2.1
[3] ggplot2_3.5.1 vegan_2.6-7
[5] lattice_0.22-6 permute_0.9-7
[7] tibble_3.2.1 writexl_1.5.0
[9] readxl_1.4.3 mia_1.13.18
[11] MultiAssayExperiment_1.30.1 TreeSummarizedExperiment_2.12.0
[13] Biostrings_2.72.0 XVector_0.44.0
[15] SingleCellExperiment_1.26.0 SummarizedExperiment_1.34.0
[17] Biobase_2.64.0 GenomicRanges_1.56.0
[19] GenomeInfoDb_1.40.0 IRanges_2.38.0
[21] S4Vectors_0.42.0 BiocGenerics_0.50.0
[23] MatrixGenerics_1.16.0 matrixStats_1.3.0
[25] phyloseq_1.48.0
loaded via a namespace (and not attached):
[1] rstudioapi_0.16.0 jsonlite_1.8.8
[3] magrittr_2.0.3 ggbeeswarm_0.7.2
[5] farver_2.1.2 nloptr_2.0.3
[7] rmarkdown_2.27 fs_1.6.4
[9] zlibbioc_1.50.0 vctrs_0.6.5
[11] multtest_2.60.0 minqa_1.2.7
[13] memoise_2.0.1 DelayedMatrixStats_1.26.0
[15] ggtree_3.12.0 base64enc_0.1-3
[17] htmltools_0.5.8.1 S4Arrays_1.4.1
[19] BiocNeighbors_1.22.0 cellranger_1.1.0
[21] Rhdf5lib_1.26.0 gridGraphics_0.5-1
[23] SparseArray_1.4.5 Formula_1.2-5
[25] rhdf5_2.48.0 htmlwidgets_1.6.4
[27] sandwich_3.1-0 plyr_1.8.9
[29] DECIPHER_3.0.0 zoo_1.8-12
[31] cachem_1.1.0 igraph_2.0.3
[33] lifecycle_1.0.4 iterators_1.0.14
[35] pkgconfig_2.0.3 rsvd_1.0.5
[37] Matrix_1.7-0 R6_2.5.1
[39] fastmap_1.2.0 GenomeInfoDbData_1.2.12
[41] aplot_0.2.2 digest_0.6.35
[43] ggnewscale_0.4.10 colorspace_2.1-0
[45] patchwork_1.2.0 scater_1.32.0
[47] irlba_2.3.5.1 Hmisc_5.1-2
[49] beachmat_2.20.0 fansi_1.0.6
[51] polyclip_1.10-6 httr_1.4.7
[53] abind_1.4-5 mgcv_1.9-1
[55] compiler_4.4.0 withr_3.0.0
[57] htmlTable_2.4.2 backports_1.4.1
[59] BiocParallel_1.38.0 viridis_0.6.5
[61] DBI_1.2.2 ggforce_0.4.2
[63] MASS_7.3-60.2 DelayedArray_0.30.1
[65] biomformat_1.32.0 bluster_1.14.0
[67] tools_4.4.0 vipor_0.4.7
[69] foreign_0.8-86 beeswarm_0.4.0
[71] ape_5.8 nnet_7.3-19
[73] glue_1.7.0 nlme_3.1-164
[75] rhdf5filters_1.16.0 grid_4.4.0
[77] checkmate_2.3.1 cluster_2.1.6
[79] reshape2_1.4.4 ade4_1.7-22
[81] lpSolve_5.6.20 generics_0.1.3
[83] gtable_0.3.5 mediation_4.5.0
[85] tidyr_1.3.1 data.table_1.15.4
[87] tidygraph_1.3.1 BiocSingular_1.20.0
[89] ScaledMatrix_1.12.0 utf8_1.2.4
[91] ggrepel_0.9.5 foreach_1.5.2
[93] pillar_1.9.0 stringr_1.5.1
[95] yulab.utils_0.1.4 splines_4.4.0
[97] tweenr_2.0.3 dplyr_1.1.4
[99] treeio_1.28.0 survival_3.6-4
[101] tidyselect_1.2.1 DirichletMultinomial_1.46.0
[103] scuttle_1.14.0 knitr_1.46
[105] gridExtra_2.3 xfun_0.44
[107] graphlayouts_1.1.1 stringi_1.8.4
[109] UCSC.utils_1.0.0 ggfun_0.1.4
[111] boot_1.3-30 lazyeval_0.2.2
[113] evaluate_0.23 codetools_0.2-20
[115] ggplotify_0.1.2 cli_3.6.2
[117] rpart_4.1.23 munsell_0.5.1
[119] Rcpp_1.0.12 parallel_4.4.0
[121] sparseMatrixStats_1.16.0 lme4_1.1-35.3
[123] mvtnorm_1.2-5 decontam_1.24.0
[125] viridisLite_0.4.2 tidytree_0.4.6
[127] scales_1.3.0 purrr_1.0.2
[129] crayon_1.5.2 rlang_1.1.3
What are the dimensions of ASVs? I suspect they are pretty big and that's resulting in some memory mangling, but it would help to know how big these things are.
They are actually not that big as you would expect.
> dim(ASVs)
[1] 9 2321
This is not reproducible and there is no information to help in guessing. If you are in Linux, can you run this command in shell (bash, zsh, csh what ever) to see the error message.
It is surprising that this crashes the window. Such crashes can happen when we use compiled code, but rarecurve (and rarefy it calls) are both implemented in pure R.
I've tried it but I have to say I find it quite weird that it works in terminal but not in vscode terminal. So I guess it's not package related then... Sorry to bother
Before running the command in vscode, say debugonce(rarecurve): this steps through the function line by line. Then you can at least see which line crashes even if you cannot see the error message.
This was very helpful! my R crashes when running par() so either this is 4.4.0 related or something else.
The manual says ?par
Each device has its own set of graphical parameters. If the
current device is the null device, ‘par’ will open a new device
before querying/setting parameters. (What device is controlled by
‘options("device")’.)
So it must be how vscode sets (or does not set) its graphical device.
Does it help if you say plot(1) before the call? This should open the graphical device, andpar() should be able to read its graphical parameters.
You are correct it works after running plot(1) . That would explain why it sometimes didn't crash. Thank you so much!