I get this error in R when trying to load new libraries.
Installation failed: unable to load shared object 'C:/R/R-3.4.0/library/curl/libs/x64/curl.dll':
`maximal number of DLLs reached...
It's nothing to do with curl, it could be any library. My sessionInfo looks like below:
R version 3.4.0 (2017-04-21)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1
Matrix products: default
locale:
[1] LC_COLLATE=English_United Kingdom.1252
[2] LC_CTYPE=English_United Kingdom.1252
[3] LC_MONETARY=English_United Kingdom.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United Kingdom.1252
attached base packages:
[1] parallel stats graphics grDevices utils datasets
[7] methods base
other attached packages:
[1] M3Drop_1.2.0 numDeriv_2016.8-1 bindrcpp_0.2
[4] Seurat_2.0.1 Matrix_1.2-11 cowplot_0.8.0
[7] scater_1.4.0 Biobase_2.36.2 BiocGenerics_0.22.0
[10] tidyr_0.6.3 dplyr_0.7.2 ggplot2_2.2.1
[13] extrafont_0.17
loaded via a namespace (and not attached):
[1] shinydashboard_0.6.1 R.utils_2.5.0
[3] lme4_1.1-13 RSQLite_2.0
[5] AnnotationDbi_1.38.2 htmlwidgets_0.9
[7] grid_3.4.0 trimcluster_0.1-2
[9] ranger_0.8.0 BiocParallel_1.10.1
[11] Rtsne_0.13 devtools_1.13.3
[13] munsell_0.4.3 codetools_0.2-15
[15] ica_1.0-1 captioner_2.2.3
[17] statmod_1.4.30 withr_2.0.0
[19] colorspace_1.3-2 knitr_1.16
[21] stats4_3.4.0 ROCR_1.0-7
[23] robustbase_0.92-7 dtw_1.18-1
[25] Rttf2pt1_1.3.4 NMF_0.20.6
[27] labeling_0.3 lars_1.2
[29] tximport_1.4.0 bbmle_1.0.19
[31] GenomeInfoDbData_0.99.0 mnormt_1.5-5
[33] bit64_0.9-7 rhdf5_2.20.0
[35] diptest_0.75-7 R6_2.2.2
[37] doParallel_1.0.10 GenomeInfoDb_1.12.2
[39] ggbeeswarm_0.6.0 VGAM_1.0-4
[41] locfit_1.5-9.1 flexmix_2.3-14
[43] bitops_1.0-6 DelayedArray_0.2.7
[45] assertthat_0.2.0 SDMTools_1.1-221
[47] scales_0.4.1 nnet_7.3-12
[49] ggjoy_0.3.0 beeswarm_0.2.3
[51] gtable_0.2.0 rlang_0.1.2
[53] MatrixModels_0.4-1 genefilter_1.58.1
[55] scatterplot3d_0.3-40 splines_3.4.0
[57] extrafontdb_1.0 lazyeval_0.2.0
[59] ModelMetrics_1.1.0 acepack_1.4.1
[61] checkmate_1.8.3 reshape2_1.4.2
[63] backports_1.1.0 httpuv_1.3.5
[65] Hmisc_4.0-3 caret_6.0-76
[67] tools_3.4.0 gridBase_0.4-7
[69] gplots_3.0.1 RColorBrewer_1.1-2
[71] proxy_0.4-17 Rcpp_0.12.12
[73] plyr_1.8.4 base64enc_0.1-3
[75] zlibbioc_1.22.0 purrr_0.2.3
[77] RCurl_1.95-4.8 rpart_4.1-11
[79] pbapply_1.3-3 viridis_0.4.0
[81] S4Vectors_0.14.3 SummarizedExperiment_1.6.3
[83] cluster_2.0.6 magrittr_1.5
[85] data.table_1.10.4 SparseM_1.77
[87] mvtnorm_1.0-6 matrixStats_0.52.2
[89] mime_0.5 xtable_1.8-2
[91] pbkrtest_0.4-7 XML_3.98-1.9
[93] mclust_5.3 IRanges_2.10.2
[95] gridExtra_2.2.1 compiler_3.4.0
[97] biomaRt_2.32.1 tibble_1.3.3
[99] KernSmooth_2.23-15 minqa_1.2.4
[101] R.oo_1.21.0 htmltools_0.3.6
[103] segmented_0.5-2.1 mgcv_1.8-18
[105] Formula_1.2-2 geneplotter_1.54.0
[107] tclust_1.2-7 DBI_0.7
[109] diffusionMap_1.1-0 MASS_7.3-47
[111] fpc_2.1-10 car_2.1-5
[113] R.methodsS3_1.7.1 gdata_2.18.0
[115] bindr_0.1 igraph_1.1.2
[117] GenomicRanges_1.28.4 pkgconfig_2.0.1
[119] sn_1.5-0 registry_0.3
[121] foreign_0.8-69 foreach_1.4.3
[123] annotate_1.54.0 vipor_0.4.5
[125] rngtools_1.2.4 pkgmaker_0.22
[127] XVector_0.16.0 stringr_1.2.0
[129] digest_0.6.12 tsne_0.1-3
[131] htmlTable_1.9 edgeR_3.18.1
[133] kernlab_0.9-25 shiny_1.0.4
[135] gtools_3.5.0 quantreg_5.33
[137] modeltools_0.2-21 rjson_0.2.15
[139] nloptr_1.0.4 nlme_3.1-131
[141] viridisLite_0.2.0 limma_3.32.5
[143] lattice_0.20-35 httr_1.3.0
[145] DEoptimR_1.0-8 survival_2.41-3
[147] glue_1.1.1 FNN_1.1
[149] prabclus_2.2-6 iterators_1.0.8
[151] bit_1.1-12 class_7.3-14
[153] stringi_1.1.5 mixtools_1.1.0
[155] blob_1.1.0 DESeq2_1.16.1
[157] latticeExtra_0.6-28 caTools_1.17.1
[159] memoise_1.1.0 irlba_2.2.1
[161] ape_4.1
I am on windows and I tried Sys.setenv(R_MAX_NUM_DLLS=500), from this question, but it doesn't seem to do anything. I have tried to add it to the Rprofile.site file and restarted R but I still get the error. Unloading libraries or not loading so many libraries etc is not a solution. I have seen an option to add R_MAX_NUM_DLLS=500 to .Renviron file, but I am not sure if windows has this.
I was wondering if anyone has any insight.
Try adding the new environment variable, in System Properties.
System environment variable R_MAX_NUM_DLLS is one of several variables that must be set before or very early on in the R startup process. It is too late to set it .Rprofile. However, you can set it in ~/.Renviron, which should then contain a line with:
R_MAX_NUM_DLLS=500
This works on all platforms / operating systems including Windows. The tricky part on Windows is to figure out where the file should be located. The easiest way to figure this out is to call:
> normalizePath("~/.Renviron", mustWork = FALSE)
[1] "/home/alice/.Renviron"
On Windows, you may see something like:
> normalizePath("~/.Renviron", mustWork = FALSE)
[1] "C:\\Users\\alice\\Documents\\.Renviron"
Note how ~/ points to C:\\Users\\alice\\Documents\\ and not to C:\\Users\\alice\\ as one might expect if one comes from a Unix environment.
Related
I just got a new Acer Swift laptop and installed ubuntu 20.04 on it. I installed R.4.0.3 and Rstudio 1.2.5042
I tried to run a script that is running without problems on my old computer. R crashes and Rstudio aborts when I assign one matrix to another. I tried increasing R memory (it is inf now) and doing the same assignment using matrix subsets. It still crashes. R session is also aborted if I skip the matrix assignment and just try to do other manipulations with the matrix ext_data.df
FYI: data.input is a matrix 33538 x 11366. ext_data.df is properly initialiozed. It is only at the assignment
ext_data.df[common_genes,] = data.input[common_genes,]
that the crash happens.
ext_data.df=matrix(0,dim(gene_list)[1],dim(data.input)[2])
rownames(ext_data.df) = gene_list$X2
colnames(ext_data.df) <- colnames(data.input)
common_genes = intersect(gene_list$X2,rownames(data.input))
ext_data.df[common_genes,] = data.input[common_genes,]
sessionInfo()
R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.1 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-serial/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-serial/liblapack.so.3
locale:
[1] LC_CTYPE=en_SG.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_SG.UTF-8 LC_COLLATE=en_SG.UTF-8
[5] LC_MONETARY=en_SG.UTF-8 LC_MESSAGES=en_SG.UTF-8
[7] LC_PAPER=en_SG.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_SG.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] tensorflow_2.2.0 kknn_1.3.1 plotly_4.9.3 viridis_0.5.1
[5] viridisLite_0.3.0 KernelKnn_1.1.0 forcats_0.5.0 stringr_1.4.0
[9] dplyr_1.0.3 purrr_0.3.4 readr_1.4.0 tidyr_1.1.2
[13] tibble_3.0.5 tidyverse_1.3.0 keras_2.3.0.0 ggpubr_0.4.0
[17] ggplot2_3.3.3 ggsci_2.9 class_7.3-17 Seurat_3.2.3
loaded via a namespace (and not attached):
[1] readxl_1.3.1 backports_1.2.1 plyr_1.8.6
[4] igraph_1.2.6 lazyeval_0.2.2 splines_4.0.3
[7] listenv_0.8.0 scattermore_0.7 tfruns_1.4
[10] digest_0.6.27 htmltools_0.5.1.1 fansi_0.4.2
[13] magrittr_2.0.1 tensor_1.5 cluster_2.1.0
[16] ROCR_1.0-11 openxlsx_4.2.3 globals_0.14.0
[19] modelr_0.1.8 matrixStats_0.57.0 askpass_1.1
[22] colorspace_2.0-0 rvest_0.3.6 rappdirs_0.3.1
[25] ggrepel_0.9.1 haven_2.3.1 crayon_1.3.4
[28] jsonlite_1.7.2 spatstat_1.64-1 spatstat.data_1.7-0
[31] zeallot_0.1.0 survival_3.2-7 zoo_1.8-8
[34] glue_1.4.2 polyclip_1.10-0 gtable_0.3.0
[37] leiden_0.3.7 car_3.0-10 future.apply_1.7.0
[40] abind_1.4-5 scales_1.1.1 DBI_1.1.1
[43] rstatix_0.6.0 miniUI_0.1.1.1 Rcpp_1.0.6
[46] xtable_1.8-4 reticulate_1.18 foreign_0.8-81
[49] rsvd_1.0.3 umap_0.2.7.0 htmlwidgets_1.5.3
[52] httr_1.4.2 RColorBrewer_1.1-2 ellipsis_0.3.1
[55] ica_1.0-2 pkgconfig_2.0.3 uwot_0.1.10
[58] dbplyr_2.0.0 deldir_0.2-9 tidyselect_1.1.0
[61] rlang_0.4.10 reshape2_1.4.4 later_1.1.0.1
[64] munsell_0.5.0 cellranger_1.1.0 tools_4.0.3
[67] cli_2.2.0 generics_0.1.0 broom_0.7.3
[70] ggridges_0.5.3 fastmap_1.1.0 goftest_1.2-2
[73] fs_1.5.0 fitdistrplus_1.1-3 zip_2.1.1
[76] RANN_2.6.1 pbapply_1.4-3 future_1.21.0
[79] nlme_3.1-151 whisker_0.4 mime_0.9
[82] xml2_1.3.2 compiler_4.0.3 rstudioapi_0.13
[85] curl_4.3 png_0.1-7 ggsignif_0.6.0
[88] spatstat.utils_2.0-0 reprex_0.3.0 stringi_1.5.3
[91] RSpectra_0.16-0 lattice_0.20-41 Matrix_1.3-2
[94] vctrs_0.3.6 pillar_1.4.7 lifecycle_0.2.0
[97] lmtest_0.9-38 RcppAnnoy_0.0.18 data.table_1.13.6
[100] cowplot_1.1.1 irlba_2.3.3 httpuv_1.5.5
[103] patchwork_1.1.1 R6_2.5.0 promises_1.1.1
[106] KernSmooth_2.23-18 gridExtra_2.3 rio_0.5.16
[109] parallelly_1.23.0 codetools_0.2-18 MASS_7.3-53
[112] assertthat_0.2.1 openssl_1.4.3 withr_2.4.0
[115] sctransform_0.3.2 mgcv_1.8-33 parallel_4.0.3
[118] hms_1.0.0 grid_4.0.3 rpart_4.1-15
[121] carData_3.0-4 Rtsne_0.15 shiny_1.6.0
[124] lubridate_1.7.9.2 base64enc_0.1-3
Could you please help me solve the problem?
Thank you very much!
Could it be that you are using 32 bit version of R?
32 bit applications can only access a maximum of 4 Gigs of memory.
Can you try the following
.Machine$sizeof.pointer
it should return 8 if you are using 64 bit R
Update: It is clearly a memory problem. When I try to do the assignment
ext_data.df[common_genes,1:1000]=data.input[common_genes, 1:1000] it works.
I monitored the usage with mem_used() and found that it works up to 7.8GB (it happens for ext_data.df[common_genes,1:3000]=data.input[common_genes, 1:3000].
At 8GB, the R session gets aborted. How can I increase the memory above 8GB. In my old laptop (MacBook Pro), the mem_used was 8.21GB for the whole assignment.
I have to note that I use Sys.setenv('R_MAX_MEM_SIZE'=64000000000)
and Sys.setenv('R_MAX_VSIZE'=64000000000) in the beginning of my script.
Maybe you can try increasing the memory via memory.limit().
You can refer to this stackoverflow thread for more information:
Increasing (or decreasing) the memory available to R processes
I recently installed a daily build version of R Studio, 1.4.671. Since that installation, anything that runs in the viewer (e.g. gt or lavaanPlot) gives me an error like this:
/session/viewhtml528813ce72d/index.html?viewer_pane=1&capabilities=1&host=http%3A%2F%2F127.0.0.1%3A27742 not found
I have fully uninstalled 1.4.671, restarted my computer, and reinstalled the version that worked this morning, 1.3.1056. Not sure
This is becoming quite a problem because I am not able to easily see any model coefficients that I am currently working on (in a neat way, they are messy in the console).
I have also reset RStudio's state following https://support.rstudio.com/hc/en-us/articles/200534577-Resetting-RStudio-s-State and removed my .Renviron file.
Update: if the error shows but I choose to export as HTML, the HTML file works.
Update2: both running Shiny and knitting an RMarkdown document to HTML works. It's just displaying something inside RStudio's viewer that is causing issues.
R version 4.0.0 (2020-04-24)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 17763)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods
[7] base
other attached packages:
[1] gt_0.2.1 patchwork_1.0.0 waffle_1.0.1
[4] plotly_4.9.2.1 ggstance_0.3.4 ggridges_0.5.2
[7] foreign_0.8-78 gghighlight_0.3.0 gridExtra_2.3
[10] readxl_1.3.1 emmeans_1.4.7 broom_0.5.6
[13] fastDummies_1.6.1 modelsummary_0.5.0 tables_0.9.3
[16] gtsummary_1.3.2 janitor_2.0.1 haven_2.3.1
[19] forcats_0.5.0 stringr_1.4.0 dplyr_1.0.0
[22] purrr_0.3.4 readr_1.3.1 tidyr_1.1.0
[25] tibble_3.0.1 ggplot2_3.3.1 tidyverse_1.3.0
loaded via a namespace (and not attached):
[1] nlme_3.1-147 fs_1.4.1 lubridate_1.7.8
[4] RColorBrewer_1.1-2 httr_1.4.1 tools_4.0.0
[7] backports_1.1.7 DT_0.13 R6_2.4.1
[10] DBI_1.1.0 lazyeval_0.2.2 colorspace_1.4-1
[13] withr_2.2.0 tidyselect_1.1.0 extrafontdb_1.0
[16] curl_4.3 compiler_4.0.0 cli_2.0.2
[19] rvest_0.3.5 xml2_1.3.2 sandwich_2.5-1
[22] labeling_0.3 sass_0.2.0 scales_1.1.1
[25] checkmate_2.0.0 mvtnorm_1.1-0 commonmark_1.7
[28] digest_0.6.25 rmarkdown_2.2 pkgconfig_2.0.3
[31] htmltools_0.5.0 extrafont_0.17 dbplyr_1.4.4
[34] htmlwidgets_1.5.1 rlang_0.4.6 rstudioapi_0.11
[37] farver_2.0.3 generics_0.0.2 zoo_1.8-8
[40] jsonlite_1.6.1 magrittr_1.5 Matrix_1.2-18
[43] Rcpp_1.0.4.6 munsell_0.5.0 fansi_0.4.1
[46] lifecycle_0.2.0 stringi_1.4.6 multcomp_1.4-13
[49] yaml_2.2.1 snakecase_0.11.0 MASS_7.3-51.5
[52] plyr_1.8.6 grid_4.0.0 blob_1.2.1
[55] crayon_1.3.4 lattice_0.20-41 splines_4.0.0
[58] hms_0.5.3 knitr_1.28 pillar_1.4.4
[61] estimability_1.3 codetools_0.2-16 reprex_0.3.0
[64] glue_1.4.1 packrat_0.5.0 evaluate_0.14
[67] data.table_1.12.8 modelr_0.1.8 vctrs_0.3.0
[70] Rttf2pt1_1.3.8 cellranger_1.1.0 gtable_0.3.0
[73] assertthat_0.2.1 xfun_0.14 xtable_1.8-4
[76] coda_0.19-3 survival_3.1-12 viridisLite_0.3.0
[79] TH.data_1.0-10 ellipsis_0.3.1
>
I want to print a plus minus sign of the form ± into a string in R, so that I can place that string a table with kableextra
Here is the structure of the string :
x = paste0("first_string", 2, "±", 3, "second_string", collapse = "")
However I get the following output:
"first_string2\302\2613second_string"
what should I do to have the output:
"first_string2±3second_string"
I found that \302\261 is the encoding for ± in Octal Escape Sequence according to this website or this website
EDIT Here is the output of sessionInfo():
R version 3.5.0 (2018-04-23)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS 10.14
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
locale:
[1] C
attached base packages:
[1] splines stats graphics grDevices utils datasets methods base
other attached packages:
[1] bindrcpp_0.2.2 rms_5.1-2 SparseM_1.77 Hmisc_4.1-1 Formula_1.2-3
[6] lattice_0.20-35 blme_1.0-4 emmeans_1.2.4 lme4_1.1-18-1 Matrix_1.2-14
[11] multcomp_1.4-8 TH.data_1.0-8 MASS_7.3-49 mvtnorm_1.0-8 survminer_0.4.3
[16] survival_2.41-3 latex2exp_0.4.0 magick_1.9 cowplot_0.9.3 ggpubr_0.1.7
[21] magrittr_1.5 gridExtra_2.3 rcompanion_2.0.0 ggsignif_0.4.0 ggplot2_3.1.0
[26] chron_2.3-52 lubridate_1.7.4 dplyr_0.7.5 kableExtra_0.9.0 knitr_1.20
[31] broom_0.4.5
loaded via a namespace (and not attached):
[1] minqa_1.2.4 colorspace_1.3-2 class_7.3-14 modeltools_0.2-22
[5] rprojroot_1.3-2 estimability_1.3 htmlTable_1.12 base64enc_0.1-3
[9] rstudioapi_0.7 MatrixModels_0.4-1 manipulate_1.0.1 coin_1.2-2
[13] xml2_1.2.0 codetools_0.2-15 mnormt_1.5-5 nloptr_1.0.4
[17] km.ci_0.5-2 cluster_2.0.7-1 readr_1.1.1 compiler_3.5.0
[21] httr_1.3.1 backports_1.1.2 assertthat_0.2.0 lazyeval_0.2.1
[25] quantreg_5.36 acepack_1.4.1 htmltools_0.3.6 tools_3.5.0
[29] coda_0.19-1 gtable_0.2.0 glue_1.3.0 reshape2_1.4.3
[33] Rcpp_1.0.0 nlme_3.1-137 psych_1.8.4 lmtest_0.9-36
[37] stringr_1.3.1 rvest_0.3.2 polspline_1.1.13 zoo_1.8-2
[41] scales_1.0.0 hms_0.4.2 parallel_3.5.0 sandwich_2.4-0
[45] expm_0.999-2 RColorBrewer_1.1-2 yaml_2.1.19 BSDA_1.2.0
[49] KMsurv_0.1-5 EMT_1.1 rpart_4.1-13 latticeExtra_0.6-28
[53] stringi_1.2.4 nortest_1.0-4 e1071_1.6-8 checkmate_1.8.5
[57] boot_1.3-20 rlang_0.3.0.1 pkgconfig_2.0.1 evaluate_0.10.1
[61] purrr_0.2.5 bindr_0.1.1 labeling_0.3 htmlwidgets_1.2
[65] cmprsk_2.2-7 tidyselect_0.2.4 plyr_1.8.4 R6_2.3.0
[69] DescTools_0.99.25 multcompView_0.1-7 pillar_1.2.3 foreign_0.8-70
[73] withr_2.1.2 nnet_7.3-12 tibble_1.4.2 survMisc_0.5.5
[77] rmarkdown_1.10 grid_3.5.0 data.table_1.11.4 digest_0.6.18
[81] xtable_1.8-2 tidyr_0.8.1 stats4_3.5.0 munsell_0.5.0
[85] viridisLite_0.3.0
Locale settings control character sets for input and output. You have
locale:
[1] C
but if you want to print non-ASCII characters such as ±, you'll need something such as UTF-8. One example of how to accomplish this (which seems to have solved your issue per the comments) is
Sys.setlocale("LC_ALL","en_US.UTF-8")
paste0("first_string", 2, "±", 3, "second_string", collapse = "")
which should output
[1] "first_string2±3second_string"
For further information, I'd check out the following sources as a starting point:
R help page for getting or setting the locale
RStudio support on character encoding
readr's locale vignette
While executing the following for linear regression the following error is thrown. The variables are numeric in the dataset.
dtsample2 <- read.csv("dtsample2.csv")
gt <- lm(Sales ~ Discount, data = dtsample2)
Error in lm(Sales ~ Discount, data = dtsample2) : unused argument
(data = dtsample2)
Please find the session info below.
sessionInfo()
R version 3.4.1 (2017-06-30)
Platform: i386-w64-mingw32/i386 (32-bit)
Running under: Windows 7 (build 7601) Service Pack 1
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] tcltk stats4 grid splines stats graphics grDevices utils datasets methods
[11] base
other attached packages:
[1] RcmdrPlugin.FuzzyClust_1.1 FactoMineR_1.36 RcmdrPlugin.EZR_1.35
[4] Hmisc_4.0-3 Formula_1.2-2 xtable_1.8-2
[7] forecast_8.1 xts_0.10-0 zoo_1.8-0
[10] tseries_0.10-42 TeachingDemos_2.10 RcmdrPlugin.EcoVirtual_1.0
[13] EcoVirtual_1.0 RcmdrPlugin.EBM_1.0-10 epiR_0.9-87
[16] RcmdrPlugin.EACSPIR_0.2-2 reshape_0.8.6 nortest_1.0-4
[19] ez_4.4-0 abind_1.4-5 R2HTML_2.3.2
[22] RcmdrPlugin.doex_0.2.0 RcmdrPlugin.DoE_0.12-3 relimp_1.0-5
[25] DoE.wrapper_0.8-10 rsm_2.8 FrF2_1.7-2
[28] DoE.base_0.30 conf.design_2.0.0 RcmdrPlugin.depthTools_1.3
[31] depthTools_0.4 RcmdrPlugin.coin_1.0-22 multcomp_1.4-6
[34] TH.data_1.0-8 mvtnorm_1.0-6 coin_1.2-0
[37] survival_2.41-3 biclust_1.2.0 colorspace_1.3-2
[40] MASS_7.3-47 RcmdrPlugin.BCA_0.9-8 flexclust_1.3-4
[43] modeltools_0.2-21 lattice_0.20-35 BCA_0.9-3
[46] Rcmdr_2.3-2 RcmdrMisc_1.0-5 sandwich_2.3-4
[49] car_2.1-5 ggthemes_3.4.0 ggplot2_2.2.1
[52] e1071_1.6-8 dplyr_0.7.1 rJava_0.9-8
[55] ModelMetrics_1.1.0 lme4_1.1-13 arules_1.5-2
[58] Matrix_1.2-10 ROCR_1.0-7 gplots_3.0.1
[61] RSQLite_2.0
loaded via a namespace (and not attached):
[1] stringr_1.2.0 gdata_2.18.0 gtools_3.5.0
[4] bindrcpp_0.2 rlang_0.1.1 htmlTable_1.9
[7] iterators_1.0.8 mgcv_1.8-17 blob_1.1.0
[10] bitops_1.0-6 base64enc_0.1-3 quantreg_5.33
[13] reshape2_1.4.2 R6_2.2.2 bit_1.1-12
[16] clue_0.3-53 plyr_1.8.4 tkrplot_0.0-23
[19] stringi_1.1.5 tcltk2_1.2-11 BsMD_2013.0718
[22] rpart.plot_2.1.2 munsell_0.4.3 vcd_1.4-3
[25] MatrixModels_0.4-1 ggthemr_1.1.0 htmlwidgets_0.9
[28] leaps_3.0 quadprog_1.5-5 quantmod_0.4-10
[31] pbkrtest_0.4-7 DBI_0.7 memoise_1.1.0
[34] bindr_0.1 foreign_0.8-69 pkgconfig_2.0.1
[37] BiasedUrn_1.07 tools_3.4.1 acepack_1.4.1
[40] SparseM_1.77 clv_0.3-2.1 cluster_2.0.6
[43] compiler_3.4.1 assertthat_0.2.0 caTools_1.17.1
[46] igraph_1.0.1 gtable_0.2.0 RcmdrPlugin.epack_1.2.5
[49] glue_1.1.1 readxl_1.0.0 digest_0.6.12
[52] RColorBrewer_1.1-2 knitr_1.16 doParallel_1.0.10
[55] htmltools_0.3.6 KernSmooth_2.23-15 DiceDesign_1.7
[58] data.table_1.10.4 lmtest_0.9-35 foreach_1.4.3
[61] sfsmisc_1.1-1 flashClust_1.01-2 RcmdrPlugin.FactoMineR_1.6-0
[64] fracdiff_1.4-2 backports_1.1.0 lazyeval_0.2.0
[67] magrittr_1.5 AlgDesign_1.1-7.3 checkmate_1.8.3
[70] estimability_1.2 minqa_1.2.4 timeDate_3012.100
[73] Rcpp_0.12.12 coda_0.19-1 bit64_0.9-7
[76] scales_0.4.1 TTR_0.23-2 lsmeans_2.26-3
[79] nloptr_1.0.4 combinat_0.0-8 tibble_1.3.3
[82] latticeExtra_0.6-28 RcmdrPlugin.Export_0.3-1 cellranger_1.1.0
[85] nnet_7.3-12 codetools_0.2-15 curl_2.7
[88] gridExtra_2.2.1 nlme_3.1-131 class_7.3-14
[91] parallel_3.4.1 lhs_0.14 rpart_4.1-11
[94] scatterplot3d_0.3-40
It may happen because you defined yearlier custom lm function by yourself and/or some package with specific lm definition had overriden base::lm.
You can call rm(list = ls()) as well restart your R session to
avoid this kind of behaviour.
Or you can call gt <- base::lm(Sales ~ Discount, data = dtsample2) to call lm from base package with desired functionality.
Please see the example how it happens:
lm <- function(x) {
0
}
lm(x ~ y, data = df)
# Error in lm(x ~ y, data = df) : unused argument (data = df)
I am using shape method in dtwclust package. When I run the following code:
data(uciCT)
hc.sbd <- tsclust(CharTraj, type = "hierarchical",
k = 20L, distance = "sbd",
preproc = zscore, centroid = shape_extraction,
seed = 320L)
I have the following error information:
Error in eigen(M) : LAPACK routines cannot be loaded
In addition: Warning message:
In eigen(M) :
unable to load shared object '//PAPER/fchen4/R/R-3.3.2/modules/x64/lapack.dll':
`maximal number of DLLs reached...
After I use library(mgcv), I have got:
Error in eigen(M) : LAPACK routines cannot be loaded
How can I fix this error? I have tried the answers in R lapack routines cannot be loaded. But they do not work for me. I have also updated all the packages. But still cannot work.
The information from sessionInfo() is:
R version 3.3.2 (2016-10-31)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)
locale:
[1] LC_COLLATE=English_Australia.1252 LC_CTYPE=English_Australia.1252 LC_MONETARY=English_Australia.1252 LC_NUMERIC=C
[5] LC_TIME=English_Australia.1252
attached base packages:
[1] parallel splines stats graphics grDevices utils datasets methods base
other attached packages:
[1] mgcv_1.8-17 nlme_3.1-131 dtwclust_3.1.2 dtw_1.18-1 clue_0.3-53
[6] ROSE_0.0-3 scatterplot3d_0.3-39 plot3D_1.1 ggrepel_0.6.5 pdfCluster_1.0-2
[11] pastecs_1.3-18 boot_1.3-18 geosphere_1.5-5 sp_1.2-4 XLConnect_0.2-12
[16] XLConnectJars_0.2-12 ica_1.0-1 visNetwork_1.0.3 igraph_1.0.1 Barnard_1.8
[21] Kendall_2.2 pspearman_0.3-0 FSelector_0.21 dunn.test_1.3.4 randomUniformForest_1.1.5
[26] dbscan_1.1-1 Hmisc_4.0-2 Formula_1.2-1 xgboost_0.6-4 doParallel_1.0.10
[31] iterators_1.0.8 foreach_1.4.3 corrplot_0.77 gbm_2.1.3 survival_2.41-3
[36] AppliedPredictiveModeling_1.1-6 e1071_1.6-8 mlbench_2.1-1 caret_6.0-73 lattice_0.20-35
[41] fpc_2.1-10 devtools_1.12.0 lubridate_1.6.0 ggmap_2.6.1 gridExtra_2.2.1
[46] leaflet_1.1.0 qdap_2.2.5 RColorBrewer_1.1-2 qdapTools_1.3.1 qdapRegex_0.6.0
[51] qdapDictionaries_1.0.6 stringr_1.2.0 xtable_1.8-2 tidyr_0.6.1 scales_0.4.1
[56] plotly_4.5.6 ggplot2_2.2.1 psych_1.7.3.21 mxnet_0.9.4 randomForest_4.6-12
[61] cluster_2.0.6 pROC_1.9.1 openxlsx_4.0.17 proxy_0.4-17 dplyr_0.5.0
[66] plyr_1.8.4
loaded via a namespace (and not attached):
[1] backports_1.0.5 lazyeval_0.2.0 entropy_1.2.1 openNLP_0.2-6 crosstalk_1.0.0 digest_0.6.12 htmltools_0.3.5 gender_0.5.1
[9] gdata_2.17.0 magrittr_1.5 checkmate_1.8.2 memoise_1.0.0 xlsx_0.5.7 tm_0.7-1 wordcloud_2.5 jpeg_0.1-8
[17] colorspace_1.3-2 RWeka_0.4-33 RCurl_1.95-4.8 jsonlite_1.4 lme4_1.1-12 registry_0.3 gtable_0.2.0 MatrixModels_0.4-1
[25] car_2.1-4 kernlab_0.9-25 prabclus_2.2-6 DEoptimR_1.0-8 maps_3.1.1 SparseM_1.76 mvtnorm_1.0-6 rngtools_1.2.4
[33] DBI_0.6-1 Rcpp_0.12.10 CORElearn_1.50.3 plotrix_3.6-4 viridisLite_0.2.0 htmlTable_1.9 magic_1.5-6 foreign_0.8-67
[41] mapproj_1.2-4 mclust_5.2.3 stats4_3.3.2 htmlwidgets_0.8 httr_1.2.1 acepack_1.4.1 modeltools_0.2-21 XML_3.98-1.6
[49] rJava_0.9-8 flexmix_2.3-13 openNLPdata_1.5.3-2 nnet_7.3-12 venneuler_1.1-0 reshape2_1.4.2 munsell_0.4.3 tools_3.3.2
[57] geometry_0.3-6 knitr_1.15.1 ModelMetrics_1.1.0 robustbase_0.92-7 caTools_1.17.1 purrr_0.2.2 RgoogleMaps_1.4.1 mime_0.5
[65] quantreg_5.29 slam_0.1-40 compiler_3.3.2 flexclust_1.3-4 pbkrtest_0.4-7 png_0.1-7 tibble_1.3.0 stringi_1.1.5
[73] trimcluster_0.1-2 Matrix_1.2-8 nloptr_1.0.4 RWekajars_3.9.1-3 data.table_1.10.4 bitops_1.0-6 httpuv_1.3.3 R6_2.2.0
[81] latticeExtra_0.6-28 codetools_0.2-15 reports_0.1.4 MASS_7.3-45 gtools_3.5.0 assertthat_0.1 chron_2.3-50 proto_1.0.0
[89] xlsxjars_0.6.1 pkgmaker_0.22 rjson_0.2.15 withr_1.0.2 mnormt_1.5-5 diptest_0.75-7 grid_3.3.2 rpart_4.1-10
[97] class_7.3-14 minqa_1.2.4 misc3d_0.8-4 NLP_0.1-10 shiny_1.0.1 base64enc_0.1-3