running your test code outlined in your paper.
I intall ect and then run the line
YourGenepop <- assignPOP::read.Genepop( "test.txt", pop.names = c("pop_A","pop_B",
"pop_C"), haploid = FALSE)
....where test.txt is the example file you provide on your GitHub page.
I get this error:
Error in dyn.load(file, DLLpath = DLLpath, ...) :
unable to load shared object '/Library/Frameworks/R.framework/Versions/3.4/Resources/library/lubridate/libs/lubridate.so':
`maximal number of DLLs reached...
I am using the latest version of R, see below for the info:
R version 3.4.4 (2018-03-15)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.1
Hey There
running your test code outlined in your paper. I intall ect and then run the line YourGenepop <- assignPOP::read.Genepop( "test.txt", pop.names = c("pop_A","pop_B", "pop_C"), haploid = FALSE)
....where test.txt is the example file you provide on your GitHub page.
I get this error: Error in dyn.load(file, DLLpath = DLLpath, ...) : unable to load shared object '/Library/Frameworks/R.framework/Versions/3.4/Resources/library/lubridate/libs/lubridate.so': `maximal number of DLLs reached...
I am using the latest version of R, see below for the info:
R version 3.4.4 (2018-03-15) Platform: x86_64-apple-darwin15.6.0 (64-bit) Running under: macOS High Sierra 10.13.1
Matrix products: default BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib
locale: [1] en_AU.UTF-8/en_AU.UTF-8/en_AU.UTF-8/C/en_AU.UTF-8/en_AU.UTF-8
attached base packages: [1] stats graphics grDevices utils datasets methods base
other attached packages: [1] bindrcpp_0.2.2 dplyr_0.7.6 ggrepel_0.8.0 marmap_1.0 ggmap_2.6.1
[6] stringr_1.3.1 plyr_1.8.4 qvalue_2.10.0 pcadapt_4.0.3 radiator_0.0.13 [11] adegenet_2.1.1 factoextra_1.0.5 ggplot2_3.0.0 ade4_1.7-11
loaded via a namespace (and not attached): [1] utf8_1.1.4 proto_1.0.0 tidyselect_0.2.4 robust_0.4-18
[5] RSQLite_2.1.1 htmlwidgets_1.2 grid_3.4.4 munsell_0.5.0
[9] codetools_0.2-15 future_1.8.1 withr_2.1.2 colorspace_1.3-2
[13] fst_0.8.8 pegas_0.11 rstudioapi_0.7 geometry_0.3-6
[17] stats4_3.4.4 robustbase_0.93-1 dimRed_0.1.0 pbmcapply_1.2.5
[21] listenv_0.7.0 labeling_0.3 RgoogleMaps_1.4.2 poppr_2.8.0
[25] mnormt_1.5-5 bit64_0.9-7 coda_0.19-1 LearnBayes_2.15.1
[29] ipred_0.9-6 R6_2.2.2 DRR_0.0.3 assertthat_0.2.0
[33] promises_1.0.1 scales_0.5.0 pinfsc50_1.1.0 nnet_7.3-12
[37] gtable_0.2.0 ddalpha_1.3.4 globals_0.12.1 phangorn_2.4.0
[41] timeDate_3043.102 rlang_0.2.1 CVST_0.2-2 RcppRoll_0.3.0
[45] splines_3.4.4 lazyeval_0.2.1 ModelMetrics_1.1.0 broom_0.4.5
[49] yaml_2.1.19 reshape2_1.4.3 abind_1.4-5 httpuv_1.4.4.2
[53] tools_3.4.4 lava_1.6.2 psych_1.8.4 spData_0.2.9.0
[57] raster_2.6-7 Rcpp_0.12.17 purrr_0.2.5 ggpubr_0.1.7
[61] rpart_4.1-13 deldir_0.1-15 sfsmisc_1.1-2 cluster_2.0.7-1
[65] magrittr_1.5 data.table_1.11.4 RSpectra_0.13-1 gmodels_2.18.1
[69] mvtnorm_1.0-8 amap_0.8-16 mmapcharr_0.1.0 hms_0.4.2
[73] mime_0.5 xtable_1.8-2 jpeg_0.1-8 shape_1.4.4
[77] vcfR_1.8.0 compiler_3.4.4 tibble_1.4.2 maps_3.3.0
[81] ncdf4_1.16 crayon_1.3.4 htmltools_0.3.6 mgcv_1.8-24
[85] pcaPP_1.9-73 later_0.7.3 spdep_0.7-7 tidyr_0.8.1
[89] rrcov_1.4-4 expm_0.999-2 DBI_1.0.0 magic_1.5-8
[93] MASS_7.3-50 boot_1.3-20 Matrix_1.2-14 readr_1.1.1
[97] permute_0.9-4 cli_1.0.0 quadprog_1.5-5 gdata_2.18.0
[101] parallel_3.4.4 bindr_0.1.1 gower_0.1.2 igraph_1.2.1
[105] pkgconfig_2.0.1 fit.models_0.5-14 geosphere_1.5-7 foreign_0.8-70
[109] sp_1.3-1 plotly_4.7.1 foreach_1.4.4 prodlim_2018.04.18 [113] digest_0.6.15 vegan_2.5-2 polysat_1.7-3 fastmatch_1.1-0
[117] kernlab_0.9-26 shiny_1.1.0 gtools_3.8.1 rjson_0.2.20
[121] hierfstat_0.04-22 nlme_3.1-137 jsonlite_1.5 mapproj_1.2.6
[125] seqinr_3.4-5 viridisLite_0.3.0 pillar_1.2.3 lattice_0.20-35
[129] httr_1.3.1 DEoptimR_1.0-8 survival_2.42-4 glue_1.2.0
[133] png_0.1-7 iterators_1.0.9 bit_1.1-14 class_7.3-14
[137] adehabitatMA_0.3.12 stringi_1.2.3 blob_1.1.1 memoise_1.1.0
[141] ape_5.1