[Bioc-devel] The story of tracing a derfinder bug on OSX that sometimes popped up, sometimes it didn't. Related to IRanges/S4Vectors '$<-'
Michael Lawrence
lawrence.michael at gene.com
Mon Mar 27 18:43:02 CEST 2017
I committed a fix into R trunk with a regression test.
On Mon, Mar 27, 2017 at 8:41 AM, Michael Lawrence <michafla at gene.com> wrote:
> My bad guys, I'll fix when I get to work.
>
> On Mon, Mar 27, 2017 at 3:59 AM, Martin Morgan
> <martin.morgan at roswellpark.org> wrote:
>> On 03/22/2017 01:12 PM, Hervé Pagès wrote:
>>>
>>> Hi Martin,
>>>
>>> On 03/22/2017 03:17 AM, Martin Maechler wrote:
>>>>>>>>>
>>>>>>>>> Andrzej Oleś <andrzej.oles at 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.
>>>
>>>
>>> Looks like before performing the subassignment itself, [<- first tries
>>> to coerce the RHS to the "mode" of the LHS by calling as.vector() on the
>>> former. So if we define an as.vector S3 method for A objects:
>>>
>>> setClass("A", representation(stuff="numeric"))
>>> as.vector.A <- function (x, mode="any") x at stuff
>>> a <- new("A", stuff=c(3.5, 0.1))
>>> x <- numeric(10)
>>> x[3:4] <- a
>>
>>
>> The relevant stack trace is
>>
>> * frame #0: 0x000000010dded77a libR.dylib`R_has_methods(op=<unavailable>)
>> + 74 at objects.c:1415
>> frame #1: 0x000000010ddaabf4
>> libR.dylib`Rf_DispatchOrEval(call=0x00007fcea36f68a8, op=0x00007fcea201a178,
>> generic=0x000000010df0a185, args=<unavailable>, rho=0x00007fcea2053318,
>> ans=0x00007fff51f60c48, dropmissing=<unavailable>, argsevald=1) + 404 at
>> eval.c:3150
>> frame #2: 0x000000010de4e658 libR.dylib`SubassignTypeFix [inlined]
>> dispatch_asvector(x=<unavailable>, call=0x00007fcea36f68a8,
>> rho=0x00007fcea2053318) + 295 at subassign.c:283
>>
>>
>> The segfault is at objects.c:1415
>>
>> offset = PRIMOFFSET(op);
>> if(offset > curMaxOffset || prim_methods[offset] == NO_METHODS
>> || prim_methods[offset] == SUPPRESSED)
>>
>> where offset is negative and prim_methods[offset] fails.
>>
>> (lldb) p *op
>> (SEXPREC) $8 = {
>> sxpinfo = (type = 0, obj = 0, named = 2, gp = 0, mark = 1, debug = 0,
>> trace = 0, spare = 0, gcgen = 1, gccls = 0)
>> attrib = 0x00007fcea201a178
>> gengc_next_node = 0x00007fcea21874e8
>> gengc_prev_node = 0x00007fcea2019ff0
>> u = {
>> primsxp = (offset = -1576951432)
>> symsxp = {
>>
>>
>> 'op' is assigned from subassign.c:287, op = R_Primitive("as.vector")
>>
>> static Rboolean dispatch_asvector(SEXP *x, SEXP call, SEXP rho) {
>> static SEXP op = NULL;
>> SEXP args;
>> Rboolean ans;
>> if (op == NULL)
>> op = R_Primitive("as.vector");
>> PROTECT(args = list2(*x, mkString("any")));
>> ans = DispatchOrEval(call, op, "as.vector", args, rho, x, 0, 1);
>> UNPROTECT(1);
>> return ans;
>> }
>>
>> But as.vector is not a primitive, so gets R_NilValue. This is passed to
>> DispatchOrEval, and then to R_has_methods.
>>
>> It seems like dispatch_asvector() was introduced by
>>
>> $ svn log -c69747
>> ------------------------------------------------------------------------
>> r69747 | lawrence | 2015-12-09 09:04:56 -0500 (Wed, 09 Dec 2015) | 3 lines
>>
>> subassignment of an S4 value into an atomic vector coerces the value
>> with as.vector
>>
>> ------------------------------------------------------------------------
>>
>> So maybe Michael can tell us about his thinking here.
>>
>> Also, should R_has_methods be robust to R_NilValue? And R_NilValue
>> explicitly zero it's data?
>>
>> Martin
>>
>>
>>
>>>
>>> then the code is now valid and we still get the segfault on Mac.
>>>
>>> I didn't define as.vector.A in my original minimalist reproducible
>>> code in order to keep it as simple as possible.
>>>
>>> H.
>>>
>>>
>>>> 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://urldefense.proofpoint.com/v2/url?u=https-3A__cran.r-2Dproject.org_web_checks_check-5Fresults-5FFastImputation.html&d=DwIGaQ&c=eRAMFD45gAfqt84VtBcfhQ&r=BK7q3XeAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=ILfV0tHrE_BxAkWYlvUUwWcBdBdtVD7BlEljGiO3WbY&s=zUahQYlBHRwNf6lPnSA1515Rm-iL5ffQI7hUcDW-JkE&e=
>>>>
>>>>
>>>> one of them is
>>>>
>>>>
>>>> https://urldefense.proofpoint.com/v2/url?u=https-3A__www.r-2Dproject.org_nosvn_R.check_r-2Ddevel-2Dmacos-2Dx86-5F64-2Dclang_FastImputation-2D00check.html&d=DwIGaQ&c=eRAMFD45gAfqt84VtBcfhQ&r=BK7q3XeAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=ILfV0tHrE_BxAkWYlvUUwWcBdBdtVD7BlEljGiO3WbY&s=Z7LkVlUzmdmhqxGNFl4LuMVxYwQQGHSV7KdpKCJu12k&e=
>>>>
>>>>
>>>> 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.morgan at 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 at 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
>>>> >>>> GenomicRanges * 1.27.23 2017-02-25 Bioconductor
>>>> >>>> ggplot2 2.2.1 2016-12-30 CRAN (R 3.4.0)
>>>> >>>> gridExtra 2.2.1 2016-02-29 CRAN (R 3.4.0)
>>>> >>>> gtable 0.2.0 2016-02-26 CRAN (R 3.4.0)
>>>> >>>> Hmisc 4.0-2 2016-12-31 CRAN (R 3.4.0)
>>>> >>>> htmlTable 1.9 2017-01-26 CRAN (R 3.4.0)
>>>> >>>> htmltools 0.3.5 2016-03-21 CRAN (R 3.4.0)
>>>> >>>> htmlwidgets 0.8 2016-11-09 CRAN (R 3.4.0)
>>>> >>>> IRanges * 2.9.19 2017-03-15 cran (@2.9.19)
>>>> >>>> iterators * 1.0.8 2015-10-13 CRAN (R 3.4.0)
>>>> >>>> knitr 1.15.1 2016-11-22 CRAN (R 3.4.0)
>>>> >>>> lattice 0.20-34 2016-09-06 CRAN (R 3.4.0)
>>>> >>>> latticeExtra 0.6-28 2016-02-09 CRAN (R 3.4.0)
>>>> >>>> lazyeval 0.2.0 2016-06-12 CRAN (R 3.4.0)
>>>> >>>> locfit * 1.5-9.1 2013-04-20 CRAN (R 3.4.0)
>>>> >>>> magrittr 1.5 2014-11-22 CRAN (R 3.4.0)
>>>> >>>> Matrix 1.2-8 2017-01-20 CRAN (R 3.4.0)
>>>> >>>> matrixStats 0.51.0 2016-10-09 CRAN (R 3.4.0)
>>>> >>>> memoise 1.0.0 2016-01-29 CRAN (R 3.4.0)
>>>> >>>> munsell 0.4.3 2016-02-13 CRAN (R 3.4.0)
>>>> >>>> nnet 7.3-12 2016-02-02 CRAN (R 3.4.0)
>>>> >>>> pkgmaker 0.22 2014-05-14 CRAN (R 3.4.0)
>>>> >>>> plyr 1.8.4 2016-06-08 CRAN (R 3.4.0)
>>>> >>>> qvalue 2.7.0 2016-10-23 Bioconductor
>>>> >>>> R6 2.2.0 2016-10-05 CRAN (R 3.4.0)
>>>> >>>> RColorBrewer 1.1-2 2014-12-07 CRAN (R 3.4.0)
>>>> >>>> Rcpp 0.12.10 2017-03-19 CRAN (R 3.4.0)
>>>> >>>> RCurl 1.95-4.8 2016-03-01 CRAN (R 3.4.0)
>>>> >>>> registry 0.3 2015-07-08 CRAN (R 3.4.0)
>>>> >>>> reshape2 1.4.2 2016-10-22 CRAN (R 3.4.0)
>>>> >>>> rngtools 1.2.4 2014-03-06 CRAN (R 3.4.0)
>>>> >>>> rpart 4.1-10 2015-06-29 CRAN (R 3.4.0)
>>>> >>>> Rsamtools 1.27.13 2017-03-14 cran (@1.27.13)
>>>> >>>> RSQLite 1.1-2 2017-01-08 CRAN (R 3.4.0)
>>>> >>>> rtracklayer 1.35.9 2017-03-19 cran (@1.35.9)
>>>> >>>> S4Vectors * 0.13.15 2017-02-14 cran (@0.13.15)
>>>> >>>> scales 0.4.1 2016-11-09 CRAN (R 3.4.0)
>>>> >>>> stringi 1.1.2 2016-10-01 CRAN (R 3.4.0)
>>>> >>>> stringr 1.2.0 2017-02-18 CRAN (R 3.4.0)
>>>> >>>> SummarizedExperiment 1.5.7 2017-02-23 Bioconductor
>>>> >>>> survival 2.41-2 2017-03-16 CRAN (R 3.4.0)
>>>> >>>> testthat * 1.0.2 2016-04-23 CRAN (R 3.4.0)
>>>> >>>> tibble 1.2 2016-08-26 CRAN (R 3.4.0)
>>>> >>>> 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 at r-project.org mailing list
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>>>> >>>> oN3XSBk6ppmeRZhdLoB8VseYM_Byk&e=
>>>> >>>>
>>>> >>>>
>>>> >>>>
>>>> >>>
>>>> >>
>>>> >> This email message may contain legally privileged
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