CRAN Package Check Results for Package nc

Last updated on 2024-05-02 06:11:55 CEST.

Flavor	Version	Tinstall	Tcheck	Ttotal	Status	Flags
r-devel-linux-x86_64-debian-clang	2024.2.21	2.70	116.66	119.36	OK
r-devel-linux-x86_64-debian-gcc	2024.2.21	2.65	87.46	90.11	OK
r-devel-linux-x86_64-fedora-clang	2024.2.21			150.40	OK
r-devel-linux-x86_64-fedora-gcc	2024.2.21			156.77	OK
r-devel-windows-x86_64	2024.2.21	5.00	369.00	374.00	OK
r-patched-linux-x86_64	2024.2.21	4.74	110.56	115.30	OK
r-release-linux-x86_64	2024.2.21	3.26	107.58	110.84	OK
r-release-macos-arm64	2024.2.21			50.00	ERROR
r-release-macos-x86_64	2024.2.21			139.00	OK
r-release-windows-x86_64	2024.2.21	5.00	568.00	573.00	OK
r-oldrel-macos-arm64	2024.2.21			67.00	OK
r-oldrel-macos-x86_64	2024.2.21			139.00	OK
r-oldrel-windows-x86_64	2024.2.21	4.00	406.00	410.00	OK

Check Details

Version: 2024.2.21
Check: examples
Result: ERROR Running examples in ‘nc-Ex.R’ failed The error most likely occurred in: > ### Name: capture_first_glob > ### Title: capture first glob > ### Aliases: capture_first_glob > > ### ** Examples > > > data.table::setDTthreads(1) > > ## Example 0: iris data, one file per species. > library(data.table) > dir.create(iris.dir <- tempfile()) > icsv <- function(sp)file.path(iris.dir, paste0(sp, ".csv")) > data.table(iris)[, fwrite(.SD, icsv(Species)), by=Species] Empty data.table (0 rows and 1 cols): Species > dir(iris.dir) [1] "setosa.csv" "versicolor.csv" "virginica.csv" > data.table::fread(file.path(iris.dir,"setosa.csv"), nrows=2) Sepal.Length Sepal.Width Petal.Length Petal.Width <num> <num> <num> <num> 1: 5.1 3.5 1.4 0.2 2: 4.9 3.0 1.4 0.2 > (iglob <- file.path(iris.dir,"*.csv")) [1] "/var/folders/k4/0jwzxmln0nb8y6rkzprptb640000gq/T//RtmpxNPzlE/file463c41145017/*.csv" > nc::capture_first_glob(iglob, Species="[^/]+", "[.]csv") Species Sepal.Length Sepal.Width Petal.Length Petal.Width <char> <num> <num> <num> <num> 1: setosa 5.1 3.5 1.4 0.2 2: setosa 4.9 3.0 1.4 0.2 3: setosa 4.7 3.2 1.3 0.2 4: setosa 4.6 3.1 1.5 0.2 5: setosa 5.0 3.6 1.4 0.2 --- 146: virginica 6.7 3.0 5.2 2.3 147: virginica 6.3 2.5 5.0 1.9 148: virginica 6.5 3.0 5.2 2.0 149: virginica 6.2 3.4 5.4 2.3 150: virginica 5.9 3.0 5.1 1.8 > > ## Example 1: four files, two capture groups, custom read function. > db <- system.file("extdata/chip-seq-chunk-db", package="nc", mustWork=TRUE) > suffix <- if(interactive())"gz" else "head" > (glob <- paste0(db, "/*/*/counts/*", suffix)) [1] "/Volumes/Builds/packages/big-sur-arm64/results/4.4/nc.Rcheck/nc/extdata/chip-seq-chunk-db/*/*/counts/*head" > Sys.glob(glob) [1] "/Volumes/Builds/packages/big-sur-arm64/results/4.4/nc.Rcheck/nc/extdata/chip-seq-chunk-db/H3K36me3_AM_immune/9/counts/McGill0101.bedGraph.head" [2] "/Volumes/Builds/packages/big-sur-arm64/results/4.4/nc.Rcheck/nc/extdata/chip-seq-chunk-db/H3K36me3_TDH_other/1/counts/McGill0019.bedGraph.head" [3] "/Volumes/Builds/packages/big-sur-arm64/results/4.4/nc.Rcheck/nc/extdata/chip-seq-chunk-db/H3K4me3_TDH_immune/9/counts/McGill0024.bedGraph.head" [4] "/Volumes/Builds/packages/big-sur-arm64/results/4.4/nc.Rcheck/nc/extdata/chip-seq-chunk-db/H3K4me3_XJ_immune/2/counts/McGill0024.bedGraph.head" > read.bedGraph <- function(f)data.table::fread( + f, skip=1, col.names = c("chrom","start", "end", "count")) > data.chunk.pattern <- list( + data="H.*?", + "/", + chunk="[0-9]+", as.integer) > (data.chunk.dt <- nc::capture_first_glob(glob, data.chunk.pattern, READ=read.bedGraph)) data chunk chrom start end count <char> <int> <char> <int> <int> <int> 1: H3K36me3_AM_immune 9 chr10 111456281 111456338 2 2: H3K36me3_AM_immune 9 chr10 111456338 111456381 1 3: H3K36me3_AM_immune 9 chr10 111456381 111459312 0 4: H3K36me3_AM_immune 9 chr10 111459312 111459316 5 5: H3K36me3_AM_immune 9 chr10 111459316 111459409 10 6: H3K36me3_AM_immune 9 chr10 111459409 111459411 8 7: H3K36me3_AM_immune 9 chr10 111459411 111459415 5 8: H3K36me3_AM_immune 9 chr10 111459415 111463412 0 9: H3K36me3_AM_immune 9 chr10 111463412 111463512 2 10: H3K36me3_AM_immune 9 chr10 111463512 111466726 0 11: H3K36me3_TDH_other 1 chr21 43119165 43119386 0 12: H3K36me3_TDH_other 1 chr21 43119386 43119407 1 13: H3K36me3_TDH_other 1 chr21 43119407 43119475 2 14: H3K36me3_TDH_other 1 chr21 43119475 43119502 1 15: H3K36me3_TDH_other 1 chr21 43119502 43119987 0 16: H3K36me3_TDH_other 1 chr21 43119987 43120007 1 17: H3K36me3_TDH_other 1 chr21 43120007 43120086 2 18: H3K36me3_TDH_other 1 chr21 43120086 43120107 1 19: H3K36me3_TDH_other 1 chr21 43120107 43120743 0 20: H3K36me3_TDH_other 1 chr21 43120743 43120789 1 21: H3K4me3_TDH_immune 9 chr1 36926536 36926549 10 22: H3K4me3_TDH_immune 9 chr1 36926549 36926554 9 23: H3K4me3_TDH_immune 9 chr1 36926554 36926565 11 24: H3K4me3_TDH_immune 9 chr1 36926565 36926569 9 25: H3K4me3_TDH_immune 9 chr1 36926569 36926571 8 26: H3K4me3_TDH_immune 9 chr1 36926571 36926580 7 27: H3K4me3_TDH_immune 9 chr1 36926580 36926593 8 28: H3K4me3_TDH_immune 9 chr1 36926593 36926606 7 29: H3K4me3_TDH_immune 9 chr1 36926606 36926622 8 30: H3K4me3_TDH_immune 9 chr1 36926622 36926634 9 31: H3K4me3_XJ_immune 2 chr22 20688396 20688502 0 32: H3K4me3_XJ_immune 2 chr22 20688502 20688602 1 33: H3K4me3_XJ_immune 2 chr22 20688602 20688869 0 34: H3K4me3_XJ_immune 2 chr22 20688869 20688932 2 35: H3K4me3_XJ_immune 2 chr22 20688932 20688934 3 36: H3K4me3_XJ_immune 2 chr22 20688934 20688936 4 37: H3K4me3_XJ_immune 2 chr22 20688936 20688963 5 38: H3K4me3_XJ_immune 2 chr22 20688963 20688968 7 39: H3K4me3_XJ_immune 2 chr22 20688968 20688969 6 40: H3K4me3_XJ_immune 2 chr22 20688969 20688979 5 data chunk chrom start end count > > ## Write same data set in Hive partition, then re-read. > if(requireNamespace("arrow")){ + path <- tempfile() + max_rows_per_file <- if(interactive())3 else 1000 + arrow::write_dataset( + dataset=data.chunk.dt, + path=path, + format="csv", + partitioning=c("data","chunk"), + max_rows_per_file=max_rows_per_file) + hive.glob <- file.path(path, "*", "*", "*.csv") + hive.pattern <- list( + nc::field("data","=",".*?"), + "/", + nc::field("chunk","=",".*?", as.integer), + "/", + nc::field("part","-","[0-9]+", as.integer)) + hive.dt <- nc::capture_first_glob(hive.glob, hive.pattern) + hive.dt[, .(rows=.N), by=.(data,chunk,part)] + } Loading required namespace: arrow Error in dataset___HivePartitioning(schm, null_fallback = null_fallback_or_default(null_fallback), : Cannot call dataset___HivePartitioning(). See https://arrow.apache.org/docs/r/articles/install.html for help installing Arrow C++ libraries. Calls: <Anonymous> -> <Anonymous> -> dataset___HivePartitioning Execution halted Flavor: r-release-macos-arm64

Version: 2024.2.21
Check: re-building of vignette outputs
Result: ERROR Error(s) in re-building vignettes: --- re-building ‘v0-overview.Rmd’ using rmarkdown --- finished re-building ‘v0-overview.Rmd’ --- re-building ‘v1-capture-first.Rmd’ using rmarkdown --- finished re-building ‘v1-capture-first.Rmd’ --- re-building ‘v2-capture-all.Rmd’ using rmarkdown --- finished re-building ‘v2-capture-all.Rmd’ --- re-building ‘v3-capture-melt.Rmd’ using rmarkdown --- finished re-building ‘v3-capture-melt.Rmd’ --- re-building ‘v4-comparisons.Rmd’ using rmarkdown --- finished re-building ‘v4-comparisons.Rmd’ --- re-building ‘v5-helpers.Rmd’ using rmarkdown --- finished re-building 'v5-helpers.Rmd' --- re-building ‘v6-engines.Rmd’ using rmarkdown --- finished re-building ‘v6-engines.Rmd’ --- re-building ‘v7-capture-glob.Rmd’ using rmarkdown Quitting from lines 152-163 [unnamed-chunk-11] (v7-capture-glob.Rmd) Error: processing vignette 'v7-capture-glob.Rmd' failed with diagnostics: Cannot call dataset___HivePartitioning(). See https://arrow.apache.org/docs/r/articles/install.html for help installing Arrow C++ libraries. --- failed re-building ‘v7-capture-glob.Rmd’ SUMMARY: processing the following file failed: ‘v7-capture-glob.Rmd’ Error: Vignette re-building failed. Execution halted Flavor: r-release-macos-arm64