[Bioc-devel] The story of tracing a derfinder bug on OSX that sometimes popped up, sometimes it didn't. Related to IRanges/S4Vectors '$<-'
Martin Morgan
martin.morgan at roswellpark.org
Mon Mar 27 12:59:06 CEST 2017
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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>> >>>>
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