>>>>> Andrzej Oleś <andrzej.o...@gmail.com> >>>>> on Wed, 22 Mar 2017 10:29:57 +0100 writes:
> Just for the record, on R-3.3.2 Herve's code fails with the following error: > Error in x[TRUE] <- new("A") : > incompatible types (from S4 to logical) in subassignment type fix yes, (of course).... and I would be interested in a small reproducible example which uses _valid_ code. We have seen such examples with something (more complicated than, but basically like) df <- data.frame(x=1:5, y=5:1, m=matrix(-pi*1:30, 5,6)) M <- Matrix::Matrix(exp(0:3),2) df[1:2,1:2] <- M which actually calls `[<-`, and then `[<-.data.frame` and always works for me but does seg.fault (in the CRAN checks of package FastImputation (on 3 of the dozen platforms, https://cran.r-project.org/web/checks/check_results_FastImputation.html one of them is https://www.r-project.org/nosvn/R.check/r-devel-macos-x86_64-clang/FastImputation-00check.html I strongly suspect this is the same bug as yours, but for a case where the correct behavior is *not* giving an error. I have also written and shown Herve's example to the R-core team. Unfortunately, I have no platform where I can trigger the bug. Martin > Cheers, > Andrzej > On Wed, Mar 22, 2017 at 1:28 AM, Martin Morgan < > martin.mor...@roswellpark.org> wrote: >> On 03/21/2017 08:21 PM, Hervé Pagès wrote: >> >>> Hi Leonardo, >>> >>> Thanks for hunting down and isolating that bug! I tried to simplify >>> your code even more and was able to get a segfault with just: >>> >>> setClass("A", representation(stuff="numeric")) >>> x <- logical(10) >>> x[TRUE] <- new("A") >>> >>> I get the segfault about 50% of the time on a fresh R session on Mac. >>> I tried this with R 3.3.3 on Mavericks, and with R devel (r72372) >>> on El Capitan. I get the segfault on both. >>> >>> So it looks like a bug in the `[<-` primitive to me (subassignment). >>> >> >> Any insight from >> >> R -d valgrind -f herve.R >> >> where herve.R contains the code above? >> >> Martin >> >> >> >>> Cheers, >>> H. >>> >>> On 03/21/2017 03:06 PM, Leonardo Collado Torres wrote: >>> >>>> Hi bioc-devel, >>>> >>>> This is a story about a bug that took me a long time to trace. The >>>> behaviour was really weird, so I'm sharing the story in case this >>>> helps others in the future. I was originally writing it to request >>>> help, but then I was able to find the issue ^^. The story ends right >>>> now with code that will reproduce the problem with '$<-' from >>>> IRanges/S4Vectors. >>>> >>>> >>>> >>>> >>>> During this Bioc cycle, frequently my package derfinder has failed to >>>> pass R CMD check in OSX. The error is always the same when it appears >>>> and sometimes it shows up in release, but not devel and viceversa. >>>> Right now (3/21/2017) it's visible in both >>>> https://urldefense.proofpoint.com/v2/url?u=http-3A__biocondu >>>> ctor.org_checkResults_release_bioc-2DLATEST_derfinder_ >>>> morelia-2Dchecksrc.html&d=DwIGaQ&c=eRAMFD45gAfqt84VtBcfh >>>> Q&r=BK7q3XeAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=Bw-1Kqy-M_ >>>> t4kmpYWTpYkt5bvj_eTpxriUM3UvtOIzQ&s=RS-lsygPtDdgWKAhjA2BcSLk >>>> Vy9RxxshXWAJaBZa_Yc&e= >>>> >>>> and >>>> https://urldefense.proofpoint.com/v2/url?u=http-3A__biocondu >>>> ctor.org_checkResults_devel_bioc-2DLATEST_derfinder_toluca >>>> 2-2Dchecksrc.html&d=DwIGaQ&c=eRAMFD45gAfqt84VtBcfhQ&r=BK7q3X >>>> eAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=Bw-1Kqy-M_ >>>> t4kmpYWTpYkt5bvj_eTpxriUM3UvtOIzQ&s=a_K-yK7w2LEV72lpHrpp0UoK >>>> Rru_7Aad74T5Uk0R-Fo&e= >>>> . >>>> The end of "test-all.Rout.fail" looks like this: >>>> >>>> Loading required package: foreach >>>> Loading required package: iterators >>>> Loading required package: locfit >>>> locfit 1.5-9.1 2013-03-22 >>>> getSegments: segmenting >>>> getSegments: splitting >>>> 2017-03-20 02:36:52 findRegions: smoothing >>>> 2017-03-20 02:36:52 findRegions: identifying potential segments >>>> 2017-03-20 02:36:52 findRegions: segmenting information >>>> 2017-03-20 02:36:52 .getSegmentsRle: segmenting with cutoff(s) >>>> 16.3681899295041 >>>> 2017-03-20 02:36:52 findRegions: identifying candidate regions >>>> 2017-03-20 02:36:52 findRegions: identifying region clusters >>>> 2017-03-20 02:36:52 findRegions: smoothing >>>> 2017-03-20 02:36:52 findRegions: identifying potential segments >>>> 2017-03-20 02:36:52 findRegions: segmenting information >>>> 2017-03-20 02:36:52 .getSegmentsRle: segmenting with cutoff(s) >>>> 19.7936614060235 >>>> 2017-03-20 02:36:52 findRegions: identifying candidate regions >>>> 2017-03-20 02:36:52 findRegions: identifying region clusters >>>> 2017-03-20 02:36:52 findRegions: smoothing >>>> >>>> *** caught segfault *** >>>> address 0x7f87d2f917e0, cause 'memory not mapped' >>>> >>>> Traceback: >>>> 1: (function (y, x, cluster, weights, smoothFun, ...) { >>>> hostPackage <- environmentName(environment(smoothFun)) >>>> requireNamespace(hostPackage) smoothed <- .runFunFormal(smoothFun, >>>> y = y, x = x, cluster = cluster, weights = weights, ...) if >>>> (any(!smoothed$smoothed)) { smoothed$fitted[!smoothed$smoothed] >>>> <- y[!smoothed$smoothed] } res <- Rle(smoothed$fitted) >>>> return(res)})(dots[[1L]][[1L]], dots[[2L]][[1L]], dots[[3L]][[1L]], >>>> dots[[4L]][[1L]], smoothFun = function (y, x = NULL, cluster, >>>> weights = NULL, minNum = 7, bpSpan = 1000, minInSpan = 0, >>>> verbose = TRUE) { if (is.null(dim(y))) y <- >>>> matrix(y, ncol = 1) if (!is.null(weights) && >>>> is.null(dim(weights))) weights <- matrix(weights, ncol = >>>> 1) if (is.null(x)) x <- seq(along = y) if >>>> (is.null(weights)) weights <- matrix(1, nrow = nrow(y), >>>> ncol = ncol(y)) Indexes <- split(seq(along = cluster), cluster) >>>> clusterL <- sapply(Indexes, length) smoothed <- >>>> rep(TRUE, nrow(y)) for (i in seq(along = Indexes)) { >>>> if (verbose) if (i%%10000 == 0) >>>> cat(".") Index <- Indexes[[i]] if (clusterL[i] >>>> >>>>> = minNum & sum(rowSums(is.na(y[Index, , drop = >>>>> >>>> FALSE])) == 0) >= minNum) { nn <- >>>> minInSpan/length(Index) for (j in 1:ncol(y)) { >>>> sdata <- data.frame(pos = x[Index], y = y[Index, >>>> j], weights = weights[Index, j]) fit <- >>>> locfit(y ˜ lp(pos, nn = nn, h = bpSpan), data = >>>> sdata, weights = weights, family = "gaussian", >>>> maxk = 10000) pp <- preplot(fit, where = "data", band >>>> = "local", newdata = data.frame(pos = x[Index])) >>>> y[Index, j] <- pp$trans(pp$fit) } >>>> } else { y[Index, ] <- NA >>>> smoothed[Index] <- FALSE } } >>>> return(list(fitted = y, smoothed = smoothed, smoother = "locfit")) >>>> }, verbose = TRUE, minNum = 1435) >>>> 2: .mapply(.FUN, dots, .MoreArgs) >>>> 3: FUN(...) >>>> 4: doTryCatch(return(expr), name, parentenv, handler) >>>> 5: tryCatchOne(expr, names, parentenv, handlers[[1L]]) >>>> 6: tryCatchList(expr, classes, parentenv, handlers) >>>> 7: tryCatch({ FUN(...)}, error = handle_error) >>>> 8: withCallingHandlers({ tryCatch({ FUN(...) }, error = >>>> handle_error)}, warning = handle_warning) >>>> 9: FUN(X[[i]], ...) >>>> 10: lapply(X, FUN, ...) >>>> 11: bplapply(X = seq_along(ddd[[1L]]), wrap, .FUN = FUN, .ddd = ddd, >>>> .MoreArgs = MoreArgs, BPREDO = BPREDO, BPPARAM = BPPARAM) >>>> 12: bplapply(X = seq_along(ddd[[1L]]), wrap, .FUN = FUN, .ddd = ddd, >>>> .MoreArgs = MoreArgs, BPREDO = BPREDO, BPPARAM = BPPARAM) >>>> 13: bpmapply(.smoothFstatsFun, fstatsChunks, posChunks, clusterChunks, >>>> weightChunks, MoreArgs = list(smoothFun = smoothFunction, >>>> ...), BPPARAM = BPPARAM) >>>> 14: bpmapply(.smoothFstatsFun, fstatsChunks, posChunks, clusterChunks, >>>> weightChunks, MoreArgs = list(smoothFun = smoothFunction, >>>> ...), BPPARAM = BPPARAM) >>>> 15: .smootherFstats(fstats = fstats, position = position, weights = >>>> weights, smoothFunction = smoothFunction, ...) >>>> 16: findRegions(prep$position, genomeFstats, "chr21", verbose = TRUE, >>>> smooth = TRUE, minNum = 1435) >>>> 17: eval(exprs, env) >>>> 18: eval(exprs, env) >>>> 19: source_file(path, new.env(parent = env), chdir = TRUE) >>>> 20: force(code) >>>> 21: with_reporter(reporter = reporter, start_end_reporter = >>>> start_end_reporter, { lister$start_file(basename(path)) >>>> source_file(path, new.env(parent = env), chdir = TRUE) >>>> end_context() }) >>>> 22: FUN(X[[i]], ...) >>>> 23: lapply(paths, test_file, env = env, reporter = current_reporter, >>>> start_end_reporter = FALSE, load_helpers = FALSE) >>>> 24: force(code) >>>> 25: with_reporter(reporter = current_reporter, results <- >>>> lapply(paths, test_file, env = env, reporter = current_reporter, >>>> start_end_reporter = FALSE, load_helpers = FALSE)) >>>> 26: test_files(paths, reporter = reporter, env = env, ...) >>>> 27: test_dir(test_path, reporter = reporter, env = env, filter = >>>> filter, ...) >>>> 28: with_top_env(env, { test_dir(test_path, reporter = reporter, >>>> env = env, filter = filter, ...)}) >>>> 29: run_tests(package, test_path, filter, reporter, ...) >>>> 30: test_check("derfinder") >>>> An irrecoverable exception occurred. R is aborting now ... >>>> >>>> I was finally able to reproduce this error on my Mac OSX laptop after >>>> running R CMD build and R CMD check (same options as in Bioc) several >>>> times. It took me a while, but I figured out what's the exact code >>>> that's failing. It can be reproduced (noting that it won't always >>>> fail...) in OSX by running: >>>> >>>> library('derfinder') >>>> prep <- preprocessCoverage(genomeData, cutoff=0, scalefac=32, >>>> chunksize=1e3, >>>> colsubset=NULL) >>>> regs_s3 <- findRegions(prep$position, genomeFstats, 'chr21', >>>> verbose=TRUE, smooth = TRUE, minNum = 1435) >>>> >>>> >>>> Here is the output from my laptop one time it actually failed: >>>> >>>> library('derfinder') >>>>> >>>> prep <- preprocessCoverage(genomeData, cutoff=0, scalefac=32, >>>> chunksize=1e3, >>>> colsubset=NULL) >>>> >>>>> prep <- preprocessCoverage(genomeData, cutoff=0, scalefac=32, >>>>> chunksize=1e3, >>>>> >>>> + colsubset=NULL) >>>> >>>>> regs_s3 <- findRegions(prep$position, genomeFstats, 'chr21', >>>>> verbose=TRUE, smooth = TRUE, minNum = 1435) >>>>> >>>> 2017-03-21 16:37:39 findRegions: smoothing >>>> >>>> *** caught segfault *** >>>> address 0x7f958dbf2be0, cause 'memory not mapped' >>>> >>>> Traceback: >>>> 1: (function (y, x, cluster, weights, smoothFun, ...) { >>>> hostPackage <- environmentName(environment(smoothFun)) >>>> requireNamespace(hostPackage) smoothed <- .runFunFormal(smoothFun, >>>> y = y, x = x, cluster = cluster, weights = weights, ...) if >>>> (any(!smoothed$smoothed)) { smoothed$fitted[!smoothed$smoothed] >>>> <- y[!smoothed$smoothed] } res <- Rle(smoothed$fitted) >>>> return(res)})(dots[[1L]][[1L]], dots[[2L]][[1L]], dots[[3L]][[1L]], >>>> dots[[4L]][[1L]], smoothFun = function (y, x = NULL, cluster, >>>> weights = NULL, minNum = 7, bpSpan = 1000, minInSpan = 0, >>>> verbose = TRUE) { if (is.null(dim(y))) y <- >>>> matrix(y, ncol = 1) if (!is.null(weights) && >>>> is.null(dim(weights))) weights <- matrix(weights, ncol = >>>> 1) if (is.null(x)) x <- seq(along = y) if >>>> (is.null(weights)) weights <- matrix(1, nrow = nrow(y), >>>> ncol = ncol(y)) Indexes <- split(seq(along = cluster), cluster) >>>> clusterL <- sapply(Indexes, length) smoothed <- >>>> rep(TRUE, nrow(y)) for (i in seq(along = Indexes)) { >>>> if (verbose) if (i%%10000 == 0) >>>> cat(".") Index <- Indexes[[i]] if (clusterL[i] >>>> >>>>> = minNum & sum(rowSums(is.na(y[Index, , drop = >>>>> >>>> FALSE])) == 0) >= minNum) { nn <- >>>> minInSpan/length(Index) for (j in 1:ncol(y)) { >>>> sdata <- data.frame(pos = x[Index], y = y[Index, >>>> j], weights = weights[Index, j]) fit <- >>>> locfit(y ~ lp(pos, nn = nn, h = bpSpan), data = >>>> sdata, weights = weights, family = "gaussian", >>>> maxk = 10000) pp <- preplot(fit, where = "data", band >>>> = "local", newdata = data.frame(pos = x[Index])) >>>> y[Index, j] <- pp$trans(pp$fit) } >>>> } else { y[Index, ] <- NA >>>> smoothed[Index] <- FALSE } } >>>> return(list(fitted = y, smoothed = smoothed, smoother = "locfit")) >>>> }, verbose = TRUE, minNum = 1435) >>>> 2: .mapply(.FUN, dots, .MoreArgs) >>>> 3: FUN(...) >>>> 4: doTryCatch(return(expr), name, parentenv, handler) >>>> 5: tryCatchOne(expr, names, parentenv, handlers[[1L]]) >>>> 6: tryCatchList(expr, classes, parentenv, handlers) >>>> 7: tryCatch({ FUN(...)}, error = handle_error) >>>> 8: withCallingHandlers({ tryCatch({ FUN(...) }, error = >>>> handle_error)}, warning = handle_warning) >>>> 9: FUN(X[[i]], ...) >>>> 10: lapply(X, FUN, ...) >>>> 11: bplapply(X = seq_along(ddd[[1L]]), wrap, .FUN = FUN, .ddd = ddd, >>>> .MoreArgs = MoreArgs, BPREDO = BPREDO, BPPARAM = BPPARAM) >>>> 12: bplapply(X = seq_along(ddd[[1L]]), wrap, .FUN = FUN, .ddd = ddd, >>>> .MoreArgs = MoreArgs, BPREDO = BPREDO, BPPARAM = BPPARAM) >>>> 13: bpmapply(.smoothFstatsFun, fstatsChunks, posChunks, clusterChunks, >>>> weightChunks, MoreArgs = list(smoothFun = smoothFunction, >>>> ...), BPPARAM = BPPARAM) >>>> 14: bpmapply(.smoothFstatsFun, fstatsChunks, posChunks, clusterChunks, >>>> weightChunks, MoreArgs = list(smoothFun = smoothFunction, >>>> ...), BPPARAM = BPPARAM) >>>> 15: .smootherFstats(fstats = fstats, position = position, weights = >>>> weights, smoothFunction = smoothFunction, ...) >>>> 16: findRegions(prep$position, genomeFstats, "chr21", verbose = TRUE, >>>> smooth = TRUE, minNum = 1435) >>>> >>>> Possible actions: >>>> 1: abort (with core dump, if enabled) >>>> 2: normal R exit >>>> 3: exit R without saving workspace >>>> 4: exit R saving workspace >>>> >>>> The traceback information ends at's bumphunter::loessByCluster(). >>>> >>>> >>>> I have successfully used the following code other times (see below) >>>> where I test the culprit line 100 times. By successfully, I mean that >>>> the code ran without problems... so it was unsuccessful at reproducing >>>> the problem. >>>> >>>> library('derfinder') >>>> prep <- preprocessCoverage(genomeData, cutoff=0, scalefac=32, >>>> chunksize=1e3, >>>> colsubset=NULL) >>>> >>>> for(i in 1:100) { >>>> print(i) >>>> regs_s3 <- findRegions(prep$position, genomeFstats, 'chr21', >>>> verbose=TRUE, smooth = TRUE, minNum = 1435) >>>> } >>>> options(width = 120) >>>> devtools::session_info() >>>> >>>> >>>> I had several R processes open the one time it did fail, but well, >>>> I've had multiple of them open the times that the code didn't fail. So >>>> having multiple R processes doesn't seem to be an issue. >>>> >>>> The line that triggers the segfault is used simply to test that >>>> passing the argument 'minNum' to bumphunter::loessByCluster() via >>>> '...' works. It's not a relevant test for derfinder and I was tempted >>>> to remove it, although before tracing the bug I talked with Valerie >>>> about not removing it. With the upcoming Bioconductor release I >>>> decided to finally trace the line that triggers the segfault. At this >>>> point I was feeling lost... >>>> >>>> >>>> Running the following code seems to trigger the segfault more often (I >>>> got it like 4 times in a row): >>>> >>>> library('derfinder') >>>> prep <- preprocessCoverage(genomeData, cutoff=0, scalefac=32, >>>> chunksize=1e3, >>>> colsubset=NULL) >>>> regs_s1 <- findRegions(prep$position, genomeFstats, 'chr21', >>>> verbose=TRUE, smooth = TRUE) >>>> regs_s2 <- findRegions(prep$position, genomeFstats, 'chr21', >>>> verbose=TRUE, smooth = TRUE, smoothFunction = >>>> bumphunter::runmedByCluster) >>>> regs_s3 <- findRegions(prep$position, genomeFstats, 'chr21', >>>> verbose=TRUE, smooth = TRUE, minNum = 1435) >>>> >>>> But then I can still run the same code without problems on a for loop >>>> for 100 times: >>>> >>>> library('derfinder') >>>> prep <- preprocessCoverage(genomeData, cutoff=0, scalefac=32, >>>> chunksize=1e3, >>>> colsubset=NULL) >>>> >>>> for(i in 1:100) { >>>> print(i) >>>> regs_s1 <- findRegions(prep$position, genomeFstats, 'chr21', >>>> verbose=TRUE, smooth = TRUE) >>>> regs_s2 <- findRegions(prep$position, genomeFstats, 'chr21', >>>> verbose=TRUE, smooth = TRUE, smoothFunction = >>>> bumphunter::runmedByCluster) >>>> regs_s3 <- findRegions(prep$position, genomeFstats, 'chr21', >>>> verbose=TRUE, smooth = TRUE, minNum = 1435) >>>> } >>>> options(width = 120) >>>> devtools::session_info() >>>> >>>> >>>> >>>> >>>> I next thought of going through findRegions() to produce simple >>>> objects that could reproduce the error. I had in mine sharing these >>>> objects so it would be easier for others to help me figure out what >>>> was failing. It turns out that this code segfaulted reliably (all the >>>> times I tested it at least): >>>> >>>> >>>> library('derfinder') >>>> library('BiocParallel') >>>> library('IRanges') >>>> prep <- preprocessCoverage(genomeData, cutoff=0, scalefac=32, >>>> chunksize=1e3, >>>> colsubset=NULL) >>>> fstats <- genomeFstats >>>> position <- prep$position >>>> weights <- NULL >>>> cluster <- derfinder:::.clusterMakerRle(position, 300L) >>>> cluster >>>> BPPARAM <- SerialParam() >>>> iChunks <- rep(1, length(cluster)) >>>> >>>> fstatsChunks <- split(fstats, iChunks) >>>> posChunks <- split(which(position), iChunks) >>>> clusterChunks <- split(cluster, iChunks) >>>> weightChunks <- vector('list', length = length(unique(iChunks))) >>>> >>>> res <- bpmapply(bumphunter::loessByCluster, fstatsChunks, posChunks, >>>> clusterChunks, weightChunks, MoreArgs = list(minNum = 1435), >>>> BPPARAM = BPPARAM, SIMPLIFY = FALSE) >>>> >>>> y <- fstatsChunks[[1]] >>>> smoothed <- res[[1]] >>>> >>>> ## This segfaults: >>>> if(any(!smoothed$smoothed)) { >>>> smoothed$fitted[!smoothed$smoothed] <- y[!smoothed$smoothed] >>>> } >>>> >>>> >>>> The objects on the line that fail are a list and an Rle: >>>> >>>> y >>>>> >>>> numeric-Rle of length 1434 with 358 runs >>>> Lengths: 1 5 >>>> ... 1 >>>> Values : 5.109484425367 3.85228949953674 ... >>>> 3.99765511645983 >>>> >>>>> lapply(smoothed, head) >>>>> >>>> $fitted >>>> [,1] >>>> [1,] NA >>>> [2,] NA >>>> [3,] NA >>>> [4,] NA >>>> [5,] NA >>>> [6,] NA >>>> >>>> $smoothed >>>> [1] FALSE FALSE FALSE FALSE FALSE FALSE >>>> >>>> $smoother >>>> [1] "loess" >>>> >>>>> table(!smoothed$smoothed) >>>>> >>>> >>>> TRUE >>>> 1434 >>>> >>>>> y[!smoothed$smoothed] >>>>> >>>> numeric-Rle of length 1434 with 358 runs >>>> Lengths: 1 5 >>>> ... 1 >>>> Values : 5.109484425367 3.85228949953674 ... >>>> 3.99765511645983 >>>> >>>> So in my derfinder code I was assigning an Rle to a matrix, and that >>>> was the segfault. I have no idea why this doesn't always fail on OSX >>>> and why it never failed on Linux or Windows. >>>> >>>> >>>> This is the super simplified IRanges code that fails: >>>> >>>> library('IRanges') >>>> y <- Rle(runif(10, 1, 1)) >>>> smoothed <- list('fitted' = matrix(NA, ncol = 1, nrow = 10), >>>> 'smoothed' = rep(FALSE, 10), smoother = 'loess') >>>> sessionInfo() >>>> smoothed$fitted[!smoothed$smoothed] <- y[!smoothed$smoothed] >>>> >>>> ## Segfault on OSX >>>> >>>> library('IRanges') >>>>> y <- Rle(runif(10, 1, 1)) >>>>> smoothed <- list('fitted' = matrix(NA, ncol = 1, nrow = 10), >>>>> >>>> + 'smoothed' = rep(FALSE, 10), smoother = 'loess') >>>> >>>>> >>>>> sessionInfo() >>>>> >>>> R Under development (unstable) (2016-10-26 r71594) >>>> Platform: x86_64-apple-darwin13.4.0 (64-bit) >>>> Running under: macOS Sierra 10.12.3 >>>> >>>> locale: >>>> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 >>>> >>>> attached base packages: >>>> [1] stats4 parallel stats graphics grDevices utils >>>> datasets methods base >>>> >>>> other attached packages: >>>> [1] IRanges_2.9.19 S4Vectors_0.13.15 BiocGenerics_0.21.3 >>>> >>>>> smoothed$fitted[!smoothed$smoothed] <- y[!smoothed$smoothed] >>>>> >>>> >>>> *** caught segfault *** >>>> address 0x7fcdc31dffe0, cause 'memory not mapped' >>>> >>>> Possible actions: >>>> 1: abort (with core dump, if enabled) >>>> 2: normal R exit >>>> 3: exit R without saving workspace >>>> 4: exit R saving workspace >>>> >>>> >>>> ## No problems on Linux >>>> >>>> library('IRanges') >>>>> y <- Rle(runif(10, 1, 1)) >>>>> smoothed <- list('fitted' = matrix(NA, ncol = 1, nrow = 10), >>>>> >>>> + 'smoothed' = rep(FALSE, 10), smoother = 'loess') >>>> >>>>> >>>>> sessionInfo() >>>>> >>>> R version 3.3.1 Patched (2016-09-30 r71426) >>>> Platform: x86_64-pc-linux-gnu (64-bit) >>>> Running under: Red Hat Enterprise Linux Server release 6.6 (Santiago) >>>> >>>> locale: >>>> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C >>>> [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 >>>> [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 >>>> [7] LC_PAPER=en_US.UTF-8 LC_NAME=C >>>> [9] LC_ADDRESS=C LC_TELEPHONE=C >>>> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C >>>> >>>> attached base packages: >>>> [1] stats4 parallel stats graphics grDevices datasets utils >>>> [8] methods base >>>> >>>> other attached packages: >>>> [1] IRanges_2.8.2 S4Vectors_0.12.2 BiocGenerics_0.20.0 >>>> [4] colorout_1.1-2 >>>> >>>> loaded via a namespace (and not attached): >>>> [1] tools_3.3.1 >>>> >>>>> smoothed$fitted[!smoothed$smoothed] <- y[!smoothed$smoothed] >>>>> >>>> >>>> >>>> Best, >>>> Leo >>>> >>>> >>>> >>>> The session information for my first tests is below: >>>> >>>> devtools::session_info() >>>>> >>>> Session info >>>> ------------------------------------------------------------ >>>> ----------------------------------------------- >>>> >>>> setting value >>>> version R Under development (unstable) (2016-10-26 r71594) >>>> system x86_64, darwin13.4.0 >>>> ui X11 >>>> language (EN) >>>> collate en_US.UTF-8 >>>> tz America/New_York >>>> date 2017-03-21 >>>> >>>> Packages >>>> ------------------------------------------------------------ >>>> --------------------------------------------------- >>>> >>>> package * version date source >>>> acepack 1.4.1 2016-10-29 CRAN (R 3.4.0) >>>> AnnotationDbi 1.37.4 2017-03-10 Bioconductor >>>> assertthat 0.1 2013-12-06 CRAN (R 3.4.0) >>>> backports 1.0.5 2017-01-18 CRAN (R 3.4.0) >>>> base64enc 0.1-3 2015-07-28 CRAN (R 3.4.0) >>>> Biobase 2.35.1 2017-02-23 Bioconductor >>>> BiocGenerics * 0.21.3 2017-01-12 Bioconductor >>>> BiocParallel 1.9.5 2017-01-24 Bioconductor >>>> biomaRt 2.31.4 2017-01-13 Bioconductor >>>> Biostrings 2.43.5 2017-03-19 cran (@2.43.5) >>>> bitops 1.0-6 2013-08-17 CRAN (R 3.4.0) >>>> BSgenome 1.43.7 2017-02-24 Bioconductor >>>> bumphunter * 1.15.0 2016-10-23 Bioconductor >>>> checkmate 1.8.2 2016-11-02 CRAN (R 3.4.0) >>>> cluster 2.0.6 2017-03-16 CRAN (R 3.4.0) >>>> codetools 0.2-15 2016-10-05 CRAN (R 3.4.0) >>>> colorout * 1.1-2 2016-11-15 Github >>>> (jalvesaq/colorout@6d84420) >>>> colorspace 1.3-2 2016-12-14 CRAN (R 3.4.0) >>>> crayon 1.3.2 2016-06-28 CRAN (R 3.4.0) >>>> data.table 1.10.4 2017-02-01 CRAN (R 3.4.0) >>>> DBI 0.6 2017-03-09 CRAN (R 3.4.0) >>>> DelayedArray 0.1.7 2017-02-17 Bioconductor >>>> derfinder * 1.9.10 2017-03-17 cran (@1.9.10) >>>> derfinderHelper 1.9.4 2017-03-07 Bioconductor >>>> devtools 1.12.0 2016-12-05 CRAN (R 3.4.0) >>>> digest 0.6.12 2017-01-27 CRAN (R 3.4.0) >>>> doRNG 1.6 2014-03-07 CRAN (R 3.4.0) >>>> foreach * 1.4.3 2015-10-13 CRAN (R 3.4.0) >>>> foreign 0.8-67 2016-09-13 CRAN (R 3.4.0) >>>> Formula 1.2-1 2015-04-07 CRAN (R 3.4.0) >>>> GenomeInfoDb * 1.11.9 2017-02-08 Bioconductor >>>> GenomeInfoDbData 0.99.0 2017-02-14 Bioconductor >>>> GenomicAlignments 1.11.12 2017-03-16 cran (@1.11.12) >>>> GenomicFeatures 1.27.10 2017-03-16 cran (@1.27.10) >>>> GenomicFiles 1.11.4 2017-03-10 Bioconductor >>>> 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VariantAnnotation 1.21.17 2017-02-12 Bioconductor >>>> withr 1.0.2 2016-06-20 CRAN (R 3.4.0) >>>> XML 3.98-1.5 2016-11-10 CRAN (R 3.4.0) >>>> xtable 1.8-2 2016-02-05 CRAN (R 3.4.0) >>>> XVector 0.15.2 2017-02-02 Bioconductor >>>> zlibbioc 1.21.0 2016-10-23 Bioconductor >>>> >>>> _______________________________________________ >>>> Bioc-devel@r-project.org mailing list >>>> https://urldefense.proofpoint.com/v2/url?u=https-3A__stat.et >>>> hz.ch_mailman_listinfo_bioc-2Ddevel&d=DwIGaQ&c=eRAMFD45gAfqt >>>> 84VtBcfhQ&r=BK7q3XeAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m= >>>> Bw-1Kqy-M_t4kmpYWTpYkt5bvj_eTpxriUM3UvtOIzQ&s=hEBTd8bPfLVp6H >>>> oN3XSBk6ppmeRZhdLoB8VseYM_Byk&e= >>>> >>>> >>>> >>> >> >> This email message may contain legally privileged and/or...{{dropped:2}} >> >> >> _______________________________________________ >> Bioc-devel@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/bioc-devel >> > [[alternative HTML version deleted]] > 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