Open muschellij2 opened 4 years ago
muschellij2
commented
4 years ago This works however:
library(ANTsRCore)
dims = c(50, 50)
img<-makeImage(imagesize = dims, rnorm(prod(dims)) )
n4img<-n4BiasFieldCorrection(img)
n4img<-n4BiasFieldCorrection(img, mask = img > 0)library(ANTsRCore)
#>
#> Attaching package: 'ANTsRCore'
#> The following objects are masked from 'package:stats':
#>
#> sd, var
#> The following objects are masked from 'package:base':
#>
#> all, any, apply, max, min, prod, range, sum
fname = getANTsRData("r16")
in_img = antsImageRead(fname)
n4 = n4BiasFieldCorrection(in_img)
plot(n4)
#> NULLCreated on 2019-12-05 by the reprex package (v0.3.0.9000)
muschellij2
commented
4 years ago Also weirdly it may be due to dimensions!?
No segfault:
library(ANTsRCore)
for (i in 1:5) {
print(i)
dims = c(50, 50)
img <-makeImage(imagesize = dims, rnorm(prod(dims)) )
n4img<-n4BiasFieldCorrection(img)
n4img<-n4BiasFieldCorrection(img, mask = img > 0)
}Will segfault
for (i in 1:5) {
print(i)
dims = c(256, 256)
img <-makeImage(imagesize = dims, rnorm(prod(dims)) )
n4img<-n4BiasFieldCorrection(img)
# segfault
sum(img > 0)
n4img<-n4BiasFieldCorrection(img, mask = img > 0)
n4img
}Reinstalling to see if this goes away.
stnava
commented
4 years ago yes. I suspect something is out of sync.
brian
On Thu, Dec 5, 2019 at 3:26 PM John Muschelli notifications@github.com wrote:
Reinstalling to see if this goes away.
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muschellij2
commented
4 years ago Still getting same error after installing locally. GitHub install may be different - but something is off.
stnava
commented
4 years ago tested on OS X and ubuntu 18.04 with recent full stack installs - no issues.
but perhaps I have something out of date. not sure.
brian
On Thu, Dec 5, 2019 at 4:55 PM John Muschelli notifications@github.com wrote:
Still getting same error after installing locally. GitHub install may be different - but something is off.
— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/ANTsX/ANTsRCore/issues/109?email_source=notifications&email_token=AACPE7XFURNC37KMATAHFYDQXF2FRA5CNFSM4JV7SL6KYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEGCJDRY#issuecomment-562336199, or unsubscribe https://github.com/notifications/unsubscribe-auth/AACPE7VBXKEFREI6DJIB7ZLQXF2FRANCNFSM4JV7SL6A .
muschellij2
commented
4 years ago Still failingwith
─ Packages ───────────────────────────────────────────────────────────────────
package * version date lib source
ANTsRCore * 0.7.3 2019-12-11 [1] Github (ANTsX/ANTsRCore@416d8f1)
ITKR 0.5.2 2019-11-05 [1] Github (stnava/ITKR@fe97efa) Can you send your session info? Having problems in 3D with mask in n4 and so is @adigherman
stnava
commented
4 years ago I suspect this was fixed by @ntustison just yesterday ( in ANTs ) ...
muschellij2
commented
4 years ago That's great news! Either way, here should be a reproducible example: Archive.zip
library(ANTsRCore)
#>
#> Attaching package: 'ANTsRCore'
#> The following objects are masked from 'package:stats':
#>
#> sd, var
#> The following objects are masked from 'package:base':
#>
#> all, any, apply, max, min, prod, range, sum
library(neurobase)
#> Loading required package: oro.nifti
#> oro.nifti 0.10.1
#>
#> Attaching package: 'oro.nifti'
#> The following objects are masked from 'package:ANTsRCore':
#>
#> origin, origin<-
library(extrantsr)
#>
#> Attaching package: 'extrantsr'
#> The following object is masked from 'package:neurobase':
#>
#> zero_pad
#> The following objects are masked from 'package:oro.nifti':
#>
#> origin, origin<-
#> The following objects are masked from 'package:ANTsRCore':
#>
#> origin, origin<-
destfile = tempfile(fileext = ".zip")
download.file("https://github.com/ANTsX/ANTsRCore/files/4073596/Archive.zip",
destfile = destfile)
unzip(destfile, exdir = tempdir())
files = "IXI002-Guys-0828-T1_bias_correct.nii.gz"
files = file.path(tempdir(), files)
img = antsImageRead(files)
maskfile = "IXI002-Guys-0828-T1_brain_mask.nii.gz"
maskfile = file.path(tempdir(), maskfile)
mask = antsImageRead(maskfile)
img
#> antsImage
#> Pixel Type : float
#> Components Per Pixel: 1
#> Dimensions : 150x256x202
#> Voxel Spacing : 1.19999694824219x0.9375x0.9375
#> Origin : -90.15966 120.7078 -82.64942
#> Direction : 1 3.756096e-08 2.323527e-09 3.756096e-08 -0.9923758 -0.1232487 2.323527e-09 -0.1232487 0.9923758
#> Filename : /var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmpJ141o8/IXI002-Guys-0828-T1_bias_correct.nii.gz
mask
#> antsImage
#> Pixel Type : float
#> Components Per Pixel: 1
#> Dimensions : 150x256x202
#> Voxel Spacing : 1.19999694824219x0.9375x0.9375
#> Origin : -90.15966 120.7078 -82.64942
#> Direction : 1 3.756095e-08 2.323527e-09 3.756095e-08 -0.9923758 -0.1232487 2.323527e-09 -0.1232487 0.9923758
#> Filename : /var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmpJ141o8/IXI002-Guys-0828-T1_brain_mask.nii.gz
range(img)
#> [1] 0.0000 988.2431
range(mask)
#> [1] 0 1
unique(c(as.array(mask)))
#> [1] 0 1
ortho2(img)
ortho2(mask)
outfiles = tempfile(fileext = ".nii.gz")
bc = n4BiasFieldCorrection(img, verbose = TRUE)
antsImageWrite(bc, outfiles)
range(bc)
#> [1] 0.00 2161.69
ortho2(bc, mask)
masked_image = maskImage(bc, mask)
range(masked_image)
#> [1] 0.000 1163.379
ortho2(masked_image)
ofile1 = outfiles
f = outfiles[1]
fslr::fslmask(file = f, mask = maskfile,
outfile = f,
retimg = FALSE)
#> Warning in get.fsl(): Setting fsl.path to /usr/local/fsl
#> Warning in get.fsloutput(): Can't find FSLOUTPUTTYPE, setting to NIFTI_GZ
#> FSLDIR='/usr/local/fsl'; PATH=${FSLDIR}/bin:${PATH};export PATH FSLDIR; sh "${FSLDIR}/etc/fslconf/fsl.sh"; FSLOUTPUTTYPE=NIFTI_GZ; export FSLOUTPUTTYPE; ${FSLDIR}/bin/fslmaths "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmpJ141o8/file597b5872170e.nii.gz" -mas "/private/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T/RtmpJ141o8/IXI002-Guys-0828-T1_brain_mask.nii.gz" "/var/folders/1s/wrtqcpxn685_zk570bnx9_rr0000gr/T//RtmpJ141o8/file597b5872170e"
#> [1] 0
fsl_masked_image = antsImageRead(f)
ortho2(fsl_masked_image)
range(fsl_masked_image)
#> [1] 0.000 1163.379
all.equal(as.array(fsl_masked_image), as.array(masked_image))
#> [1] TRUEbc2 = n4BiasFieldCorrection(masked_image, mask = mask, verbose = TRUE)Running N4 for 3-dimensional images.
Original intensity range: [0, 1163.38]
***********************************************************
Warning: Your input image contains nonpositive values
which could cause failure or problematic results. A
possible workaround would be to:
1. rescale your image to positive values e.g., [10,100].
2. run N4 on your rescaled image.
3. (optional) rescale the N4 output to the original
intensity range.
***********************************************************
Specified spline distance: 200mm
original image size: [150, 256, 202]
padded image size: [168, 428, 214]
number of control points: [4, 5, 4]
Current level = 1
Iteration 1 (of 50). Current convergence value = 0.000170185 (threshold = 1e-07)
Iteration 2 (of 50). Current convergence value = 0.000169809 (threshold = 1e-07)
Iteration 3 (of 50). Current convergence value = 0.000169486 (threshold = 1e-07)
Iteration 4 (of 50). Current convergence value = 0.000169141 (threshold = 1e-07)
Iteration 5 (of 50). Current convergence value = 0.000168838 (threshold = 1e-07)
Iteration 6 (of 50). Current convergence value = 0.000168541 (threshold = 1e-07)
Iteration 7 (of 50). Current convergence value = 0.000168237 (threshold = 1e-07)
Iteration 8 (of 50). Current convergence value = 0.000167974 (threshold = 1e-07)
Iteration 9 (of 50). Current convergence value = 0.000167724 (threshold = 1e-07)
Iteration 10 (of 50). Current convergence value = 0.000167464 (threshold = 1e-07)
Iteration 11 (of 50). Current convergence value = 0.000167247 (threshold = 1e-07)
Iteration 12 (of 50). Current convergence value = 0.000166963 (threshold = 1e-07)
Iteration 13 (of 50). Current convergence value = 0.000166759 (threshold = 1e-07)
Iteration 14 (of 50). Current convergence value = 0.000166538 (threshold = 1e-07)
Iteration 15 (of 50). Current convergence value = 0.000166299 (threshold = 1e-07)
Iteration 16 (of 50). Current convergence value = 0.000166066 (threshold = 1e-07)
Iteration 17 (of 50). Current convergence value = 0.000165876 (threshold = 1e-07)
Iteration 18 (of 50). Current convergence value = 0.000165647 (threshold = 1e-07)
Iteration 19 (of 50). Current convergence value = 0.000165474 (threshold = 1e-07)
Iteration 20 (of 50). Current convergence value = 0.000165285 (threshold = 1e-07)
Iteration 21 (of 50). Current convergence value = 0.000165109 (threshold = 1e-07)
Iteration 22 (of 50). Current convergence value = 0.00016496 (threshold = 1e-07)
Iteration 23 (of 50). Current convergence value = 0.000164833 (threshold = 1e-07)
Iteration 24 (of 50). Current convergence value = 0.00016471 (threshold = 1e-07)
Iteration 25 (of 50). Current convergence value = 0.000164579 (threshold = 1e-07)
Iteration 26 (of 50). Current convergence value = 0.000164442 (threshold = 1e-07)
Iteration 27 (of 50). Current convergence value = 0.000164275 (threshold = 1e-07)
Iteration 28 (of 50). Current convergence value = 0.000164179 (threshold = 1e-07)
Iteration 29 (of 50). Current convergence value = 0.000164016 (threshold = 1e-07)
Iteration 30 (of 50). Current convergence value = 0.000163885 (threshold = 1e-07)
Iteration 31 (of 50). Current convergence value = 0.00016375 (threshold = 1e-07)
Iteration 32 (of 50). Current convergence value = 0.000163598 (threshold = 1e-07)
Iteration 33 (of 50). Current convergence value = 0.00016348 (threshold = 1e-07)
Iteration 34 (of 50). Current convergence value = 0.00016336 (threshold = 1e-07)
Iteration 35 (of 50). Current convergence value = 0.00016327 (threshold = 1e-07)
Iteration 36 (of 50). Current convergence value = 0.000163142 (threshold = 1e-07)
Iteration 37 (of 50). Current convergence value = 0.000163054 (threshold = 1e-07)
Iteration 38 (of 50). Current convergence value = 0.000162918 (threshold = 1e-07)
Iteration 39 (of 50). Current convergence value = 0.00016276 (threshold = 1e-07)
Iteration 40 (of 50). Current convergence value = 0.000162607 (threshold = 1e-07)
Iteration 41 (of 50). Current convergence value = 0.000162515 (threshold = 1e-07)
Iteration 42 (of 50). Current convergence value = 0.000162417 (threshold = 1e-07)
Iteration 43 (of 50). Current convergence value = 0.000162307 (threshold = 1e-07)
Iteration 44 (of 50). Current convergence value = 0.000162165 (threshold = 1e-07)
Iteration 45 (of 50). Current convergence value = 0.000162049 (threshold = 1e-07)
Iteration 46 (of 50). Current convergence value = 0.000161911 (threshold = 1e-07)
Iteration 47 (of 50). Current convergence value = 0.0001618 (threshold = 1e-07)
Iteration 48 (of 50). Current convergence value = 0.000161695 (threshold = 1e-07)
Iteration 49 (of 50). Current convergence value = 0.000161571 (threshold = 1e-07)
Iteration 50 (of 50). Current convergence value = 0.000161437 (threshold = 1e-07)
Current level = 2
Iteration 1 (of 50). Current convergence value = 0.000392126 (threshold = 1e-07)
Iteration 2 (of 50). Current convergence value = 0.000386467 (threshold = 1e-07)
Iteration 3 (of 50). Current convergence value = 0.00038131 (threshold = 1e-07)
Iteration 4 (of 50). Current convergence value = 0.000376658 (threshold = 1e-07)
Iteration 5 (of 50). Current convergence value = 0.000372321 (threshold = 1e-07)
Iteration 6 (of 50). Current convergence value = 0.000368349 (threshold = 1e-07)
Iteration 7 (of 50). Current convergence value = 0.000364589 (threshold = 1e-07)
Iteration 8 (of 50). Current convergence value = 0.000361172 (threshold = 1e-07)
Iteration 9 (of 50). Current convergence value = 0.000357932 (threshold = 1e-07)
Iteration 10 (of 50). Current convergence value = 0.000354765 (threshold = 1e-07)
Iteration 11 (of 50). Current convergence value = 0.000351997 (threshold = 1e-07)
Iteration 12 (of 50). Current convergence value = 0.000349178 (threshold = 1e-07)
Iteration 13 (of 50). Current convergence value = 0.000346434 (threshold = 1e-07)
Iteration 14 (of 50). Current convergence value = 0.000343781 (threshold = 1e-07)
Iteration 15 (of 50). Current convergence value = 0.000341215 (threshold = 1e-07)
Iteration 16 (of 50). Current convergence value = 0.000338913 (threshold = 1e-07)
Iteration 17 (of 50). Current convergence value = 0.000336595 (threshold = 1e-07)
Iteration 18 (of 50). Current convergence value = 0.000334385 (threshold = 1e-07)
Iteration 19 (of 50). Current convergence value = 0.000332281 (threshold = 1e-07)
Iteration 20 (of 50). Current convergence value = 0.000330136 (threshold = 1e-07)
Iteration 21 (of 50). Current convergence value = 0.000328145 (threshold = 1e-07)
Iteration 22 (of 50). Current convergence value = 0.000326041 (threshold = 1e-07)
Iteration 23 (of 50). Current convergence value = 0.000324014 (threshold = 1e-07)
Iteration 24 (of 50). Current convergence value = 0.000322037 (threshold = 1e-07)
Iteration 25 (of 50). Current convergence value = 0.000320137 (threshold = 1e-07)
Iteration 26 (of 50). Current convergence value = 0.000318197 (threshold = 1e-07)
Iteration 27 (of 50). Current convergence value = 0.000316221 (threshold = 1e-07)
Iteration 28 (of 50). Current convergence value = 0.000314323 (threshold = 1e-07)
Iteration 29 (of 50). Current convergence value = 0.000312342 (threshold = 1e-07)
Iteration 30 (of 50). Current convergence value = 0.000310367 (threshold = 1e-07)
Iteration 31 (of 50). Current convergence value = 0.000308531 (threshold = 1e-07)
Iteration 32 (of 50). Current convergence value = 0.000306533 (threshold = 1e-07)
Iteration 33 (of 50). Current convergence value = 0.000304734 (threshold = 1e-07)
Iteration 34 (of 50). Current convergence value = 0.000302763 (threshold = 1e-07)
Iteration 35 (of 50). Current convergence value = 0.000300927 (threshold = 1e-07)
Iteration 36 (of 50). Current convergence value = 0.000299018 (threshold = 1e-07)
Iteration 37 (of 50). Current convergence value = 0.000297152 (threshold = 1e-07)
Iteration 38 (of 50). Current convergence value = 0.000295324 (threshold = 1e-07)
Iteration 39 (of 50). Current convergence value = 0.000293401 (threshold = 1e-07)
Iteration 40 (of 50). Current convergence value = 0.000291651 (threshold = 1e-07)
Iteration 41 (of 50). Current convergence value = 0.00028986 (threshold = 1e-07)
Iteration 42 (of 50). Current convergence value = 0.000288172 (threshold = 1e-07)
Iteration 43 (of 50). Current convergence value = 0.000286338 (threshold = 1e-07)
Iteration 44 (of 50). Current convergence value = 0.000284567 (threshold = 1e-07)
Iteration 45 (of 50). Current convergence value = 0.000282876 (threshold = 1e-07)
Iteration 46 (of 50). Current convergence value = 0.000281259 (threshold = 1e-07)
Iteration 47 (of 50). Current convergence value = 0.000279537 (threshold = 1e-07)
Iteration 48 (of 50). Current convergence value = 0.000277779 (threshold = 1e-07)
Iteration 49 (of 50). Current convergence value = 0.000276155 (threshold = 1e-07)
Iteration 50 (of 50). Current convergence value = 0.00027451 (threshold = 1e-07)
Current level = 3
Iteration 1 (of 50). Current convergence value = 0.00117787 (threshold = 1e-07)
Iteration 2 (of 50). Current convergence value = 0.00104279 (threshold = 1e-07)
Iteration 3 (of 50). Current convergence value = 0.000932065 (threshold = 1e-07)
Iteration 4 (of 50). Current convergence value = 0.000837382 (threshold = 1e-07)
Iteration 5 (of 50). Current convergence value = 0.000758244 (threshold = 1e-07)
Iteration 6 (of 50). Current convergence value = 0.000691914 (threshold = 1e-07)
Iteration 7 (of 50). Current convergence value = 0.000635234 (threshold = 1e-07)
Iteration 8 (of 50). Current convergence value = 0.000586462 (threshold = 1e-07)
Iteration 9 (of 50). Current convergence value = 0.000544243 (threshold = 1e-07)
Iteration 10 (of 50). Current convergence value = 0.000507039 (threshold = 1e-07)
Iteration 11 (of 50). Current convergence value = 0.000474265 (threshold = 1e-07)
Iteration 12 (of 50). Current convergence value = 0.000445284 (threshold = 1e-07)
Iteration 13 (of 50). Current convergence value = 0.000419429 (threshold = 1e-07)
Iteration 14 (of 50). Current convergence value = 0.00039655 (threshold = 1e-07)
Iteration 15 (of 50). Current convergence value = 0.000376236 (threshold = 1e-07)
Iteration 16 (of 50). Current convergence value = 0.000358155 (threshold = 1e-07)
Iteration 17 (of 50). Current convergence value = 0.000342299 (threshold = 1e-07)
Iteration 18 (of 50). Current convergence value = 0.000328231 (threshold = 1e-07)
Iteration 19 (of 50). Current convergence value = 0.000316114 (threshold = 1e-07)
Iteration 20 (of 50). Current convergence value = 0.000305372 (threshold = 1e-07)
Iteration 21 (of 50). Current convergence value = 0.000295865 (threshold = 1e-07)
Iteration 22 (of 50). Current convergence value = 0.000287637 (threshold = 1e-07)
Iteration 23 (of 50). Current convergence value = 0.000280429 (threshold = 1e-07)
Iteration 24 (of 50). Current convergence value = 0.000274329 (threshold = 1e-07)
Iteration 25 (of 50). Current convergence value = 0.000268953 (threshold = 1e-07)
Iteration 26 (of 50). Current convergence value = 0.000264463 (threshold = 1e-07)
Iteration 27 (of 50). Current convergence value = 0.000260294 (threshold = 1e-07)
Iteration 28 (of 50). Current convergence value = 0.000256875 (threshold = 1e-07)
Iteration 29 (of 50). Current convergence value = 0.000254035 (threshold = 1e-07)
Iteration 30 (of 50). Current convergence value = 0.000251563 (threshold = 1e-07)
Iteration 31 (of 50). Current convergence value = 0.000249495 (threshold = 1e-07)
Iteration 32 (of 50). Current convergence value = 0.000247592 (threshold = 1e-07)
Iteration 33 (of 50). Current convergence value = 0.000246182 (threshold = 1e-07)
Iteration 34 (of 50). Current convergence value = 0.000244917 (threshold = 1e-07)
Iteration 35 (of 50). Current convergence value = 0.000243947 (threshold = 1e-07)
Iteration 36 (of 50). Current convergence value = 0.000243253 (threshold = 1e-07)
Iteration 37 (of 50). Current convergence value = 0.000242601 (threshold = 1e-07)
Iteration 38 (of 50). Current convergence value = 0.000242048 (threshold = 1e-07)
Iteration 39 (of 50). Current convergence value = 0.000241528 (threshold = 1e-07)
Iteration 40 (of 50). Current convergence value = 0.000241199 (threshold = 1e-07)
Iteration 41 (of 50). Current convergence value = 0.000241001 (threshold = 1e-07)
Iteration 42 (of 50). Current convergence value = 0.000240682 (threshold = 1e-07)
Iteration 43 (of 50). Current convergence value = 0.000240574 (threshold = 1e-07)
Iteration 44 (of 50). Current convergence value = 0.000240482 (threshold = 1e-07)
Iteration 45 (of 50). Current convergence value = 0.000240339 (threshold = 1e-07)
Iteration 46 (of 50). Current convergence value = 0.000240376 (threshold = 1e-07)
Iteration 47 (of 50). Current convergence value = 0.000240253 (threshold = 1e-07)
Iteration 48 (of 50). Current convergence value = 0.000240278 (threshold = 1e-07)
Iteration 49 (of 50). Current convergence value = 0.000240312 (threshold = 1e-07)
Iteration 50 (of 50). Current convergence value = 0.000240308 (threshold = 1e-07)
Current level = 4
Iteration 1 (of 50). Current convergence value = 0.001782 (threshold = 1e-07)
Iteration 2 (of 50). Current convergence value = 0.00156208 (threshold = 1e-07)
Iteration 3 (of 50). Current convergence value = 0.00139646 (threshold = 1e-07)
Iteration 4 (of 50). Current convergence value = 0.0012663 (threshold = 1e-07)
Iteration 5 (of 50). Current convergence value = 0.00115761 (threshold = 1e-07)
Iteration 6 (of 50). Current convergence value = 0.00106128 (threshold = 1e-07)
Iteration 7 (of 50). Current convergence value = 0.000977442 (threshold = 1e-07)
Iteration 8 (of 50). Current convergence value = 0.0009069 (threshold = 1e-07)
Iteration 9 (of 50). Current convergence value = 0.000854281 (threshold = 1e-07)
Iteration 10 (of 50). Current convergence value = 0.000824263 (threshold = 1e-07)
Iteration 11 (of 50). Current convergence value = 0.000798742 (threshold = 1e-07)
Iteration 12 (of 50). Current convergence value = 0.000774882 (threshold = 1e-07)
Iteration 13 (of 50). Current convergence value = 0.000753969 (threshold = 1e-07)
Iteration 14 (of 50). Current convergence value = 0.000734392 (threshold = 1e-07)
Iteration 15 (of 50). Current convergence value = 0.000716537 (threshold = 1e-07)
Iteration 16 (of 50). Current convergence value = 0.00067648 (threshold = 1e-07)
Iteration 17 (of 50). Current convergence value = 0.000629249 (threshold = 1e-07)
Iteration 18 (of 50). Current convergence value = 0.000587428 (threshold = 1e-07)
Iteration 19 (of 50). Current convergence value = 0.000550789 (threshold = 1e-07)
Iteration 20 (of 50). Current convergence value = 0.000518716 (threshold = 1e-07)
Iteration 21 (of 50). Current convergence value = 0.000490014 (threshold = 1e-07)
Iteration 22 (of 50). Current convergence value = 0.000468032 (threshold = 1e-07)
Iteration 23 (of 50). Current convergence value = 0.000452666 (threshold = 1e-07)
Iteration 24 (of 50). Current convergence value = 0.000438076 (threshold = 1e-07)
Iteration 25 (of 50). Current convergence value = 0.000424235 (threshold = 1e-07)
Iteration 26 (of 50). Current convergence value = 0.000410572 (threshold = 1e-07)
Iteration 27 (of 50). Current convergence value = 0.000397035 (threshold = 1e-07)
Iteration 28 (of 50). Current convergence value = 0.000384567 (threshold = 1e-07)
Iteration 29 (of 50). Current convergence value = 0.000372828 (threshold = 1e-07)
Iteration 30 (of 50). Current convergence value = 0.000361394 (threshold = 1e-07)
Iteration 31 (of 50). Current convergence value = 0.000350582 (threshold = 1e-07)
Iteration 32 (of 50). Current convergence value = 0.000340399 (threshold = 1e-07)
Iteration 33 (of 50). Current convergence value = 0.000330342 (threshold = 1e-07)
Iteration 34 (of 50). Current convergence value = 0.000321403 (threshold = 1e-07)
Iteration 35 (of 50). Current convergence value = 0.000313031 (threshold = 1e-07)
Iteration 36 (of 50). Current convergence value = 0.000305041 (threshold = 1e-07)
Iteration 37 (of 50). Current convergence value = 0.000297436 (threshold = 1e-07)
Iteration 38 (of 50). Current convergence value = 0.000290269 (threshold = 1e-07)
Iteration 39 (of 50). Current convergence value = 0.000283651 (threshold = 1e-07)
Iteration 40 (of 50). Current convergence value = 0.000277123 (threshold = 1e-07)
Iteration 41 (of 50). Current convergence value = 0.000270909 (threshold = 1e-07)
Iteration 42 (of 50). Current convergence value = 0.000265105 (threshold = 1e-07)
Iteration 43 (of 50). Current convergence value = 0.00025969 (threshold = 1e-07)
Iteration 44 (of 50). Current convergence value = 0.000254835 (threshold = 1e-07)
Iteration 45 (of 50). Current convergence value = 0.0002524 (threshold = 1e-07)
Iteration 46 (of 50). Current convergence value = 0.00025043 (threshold = 1e-07)
Iteration 47 (of 50). Current convergence value = 0.000248814 (threshold = 1e-07)
Iteration 48 (of 50). Current convergence value = 0.000246734 (threshold = 1e-07)
Iteration 49 (of 50). Current convergence value = 0.000244866 (threshold = 1e-07)
Iteration 50 (of 50). Current convergence value = 0.0002433 (threshold = 1e-07)
N4BiasFieldCorrectionImageFilter (0x7f8b3d0339d0)
RTTI typeinfo: itk::N4BiasFieldCorrectionImageFilter<itk::Image<float, 3u>, itk::Image<float, 3u>, itk::Image<float, 3u> >
Reference Count: 1
Modified Time: 232600
Debug: Off
Object Name:
Observers:
IterationEvent(Command)
Inputs:
ConfidenceImage: (0x0)
MaskImage: (0x7f8b3d028060)
Primary: (0x7f8b3d027c40) *
Indexed Inputs:
0: Primary (0x7f8b3d027c40)
1: MaskImage (0x7f8b3d028060)
2: ConfidenceImage (0x0)
Required Input Names: Primary
NumberOfRequiredInputs: 1
Outputs:
Primary: (0x7f8b3d0342b0)
Indexed Outputs:
0: Primary (0x7f8b3d0342b0)
NumberOfRequiredOutputs: 1
Number Of Work Units: 16
ReleaseDataFlag: Off
ReleaseDataBeforeUpdateFlag: Off
AbortGenerateData: Off
Progress: 0
Multithreader:
RTTI typeinfo: itk::PoolMultiThreader
Reference Count: 1
Modified Time: 232339
Debug: Off
Object Name:
Observers:
none
Number of Work Units: 16
Number of Threads: 4
Global Maximum Number Of Threads: 128
Global Default Number Of Threads: 4
Global Default Threader Type: PoolMultiThreader
SingleMethod: 0
SingleData: 0x0
DynamicMultiThreading: On
CoordinateTolerance: 1e-06
DirectionTolerance: 1e-06
Use Mask Label: 0
Mask label: 1
Number of histogram bins: 200
Wiener filter noise: 0.01
Bias field FWHM: 0.15
Maximum number of iterations: [50, 50, 50, 50]
Convergence threshold: 1e-07
Spline order: 3
Number of fitting levels: [4, 4, 4]
Number of control points: [4, 5, 4]
CurrentConvergenceMeasurement: 0.0002433
CurrentLevel: 4
ElapsedIterations: 51
LogBiasFieldControlPointLattice:
Image (0x7f8b3d02bd70)
RTTI typeinfo: itk::Image<itk::Vector<float, 1u>, 3u>
Reference Count: 1
Modified Time: 461775
Debug: Off
Object Name:
Observers:
none
Source: (none)
Source output name: (none)
Release Data: Off
Data Released: False
Global Release Data: Off
PipelineMTime: 0
UpdateMTime: 0
RealTimeStamp: 0 seconds
LargestPossibleRegion:
Dimension: 3
Index: [0, 0, 0]
Size: [11, 19, 11]
BufferedRegion:
Dimension: 3
Index: [0, 0, 0]
Size: [11, 19, 11]
RequestedRegion:
Dimension: 3
Index: [0, 0, 0]
Size: [11, 19, 11]
Spacing: [24.5999, 24.8438, 24.375]
Origin: [-24.5999, 27.6585, -21.1272]
Direction:
1 3.7561e-08 2.32353e-09
3.7561e-08 -0.992376 -0.123249
2.32353e-09 -0.123249 0.992376
IndexToPointMatrix:
24.5999 9.33155e-07 5.6636e-08
9.23997e-07 -24.6543 -3.00419
5.71586e-08 -3.06196 24.1892
PointToIndexMatrix:
0.0406505 1.52687e-09 9.44525e-11
1.51189e-09 -0.0399447 -0.00496095
9.53242e-11 -0.00505636 0.0407129
Inverse Direction:
1 3.7561e-08 2.32353e-09
3.7561e-08 -0.992376 -0.123249
2.32353e-09 -0.123249 0.992376
PixelContainer:
ImportImageContainer (0x7f8b3d02c020)
RTTI typeinfo: itk::ImportImageContainer<unsigned long, itk::Vector<float, 1u> >
Reference Count: 1
Modified Time: 461776
Debug: Off
Object Name:
Observers:
none
Pointer: 0x7f8b39d05e00
Container manages memory: true
Size: 2299
Capacity: 2299
Elapsed time: 12.0611
*** caught segfault ***
address 0x12b97f400, cause 'memory not mapped'
Traceback:
1: .helpn4BiasFieldCorrection(args)
2: n4BiasFieldCorrection(masked_image, mask = mask, verbose = TRUE)
Possible actions:
1: abort (with core dump, if enabled)
2: normal R exit
3: exit R without saving workspace
4: exit R saving workspace
Selection: 2020-01-16 15:22:08.189 R[23012:3370064] WARNING: nextEventMatchingMask should only be called from the Main Thread! This will throw an exception in the future.
Created on 2020-01-16 by the reprex package (v0.3.0.9001)
muschellij2
commented
4 years ago Still getting N4 fails with 3D: https://travis-ci.org/muschellij2/ANTsRCore/jobs/645574697#L4437
stnava
commented
4 years ago yes - I saw this recently as well. it's a familiar error and occurs at the end of the pipeline, after n4 runs.
brian
On Mon, Feb 3, 2020 at 2:11 PM John Muschelli notifications@github.com wrote:
Still getting N4 fails with 3D: https://travis-ci.org/muschellij2/ANTsRCore/jobs/645574697#L4437
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ntustison
commented
4 years ago Looking at this now. I wonder if our previous attempt at eliminating a similar ANTsPy occurrence is now causing this.
stnava
commented
4 years ago yes possible - would float type be more general?
brian
On Tue, Feb 4, 2020 at 11:41 AM Nick Tustison notifications@github.com wrote:
Looking at this now. I wonder if our previous attempt https://github.com/ANTsX/ANTs/commit/4528978446c73ed09927ea5ae1721b280d534dc0 at eliminating a similar ANTsPy occurrence is now causing this.
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ntustison
commented
4 years ago Yeah, that's the next thing I was going to try as soon as I can reproduce it on the dgx. Apparently my ANTsRCore was older so I wasn't able to reproduce.
stnava
commented
4 years ago hmm .... well let me know if you can't reproduce and I will clean everything out and start again
brian
On Tue, Feb 4, 2020 at 12:13 PM Nick Tustison notifications@github.com wrote:
Yeah, that's the next thing I was going to try as soon as I can reproduce it on the dgx. Apparently my ANTsRCore was older so I wasn't able to reproduce.
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ntustison
commented
4 years ago Hey @stnava , I'm having trouble reproducing so, as you suggested, can you just go change line 144 from int to float in your local ANTsRCore copy and see if that works for you? If so, then I'll change it in ANTs and hopefully we won't have any more problems with this.
muschellij2
commented
4 years ago Is this resolved? I am still getting segfaults (which is a pretty strong fail - are there possibilities to make this robust in R to fail but not segfault?). I'm reinstalling everything from scratch today (ITKR and ANTsRCore), and retry
ntustison
commented
4 years ago @muschellij2 --- can you try the small change I recommended to Brian in the comment previous to yours? My guess is that this change should fix it but I'm unable to reproduce the segfault on my end.
stnava
commented
4 years ago @ntustison - I tried that change but still got issues .... however, I would like to know if anyone else can reproduce. my finding was that the error only occurred (on my example data) if I both used a mask and downsampling >2. the error occurs after the filter completes (judging by verbose mode).
ntustison
commented
4 years ago Awesome. Thanks. Too bad it didn't work, though.
There's not an insignificant amount of processing that takes place after the verbose output which is why I really need to be able to reproduce before I can debug. I'll take a look at this again today and see if somehow things are different this time around.
muschellij2
commented
4 years ago library(ANTsRCore)
#>
#> Attaching package: 'ANTsRCore'
#> The following objects are masked from 'package:stats':
#>
#> sd, var
#> The following objects are masked from 'package:base':
#>
#> all, any, apply, max, min, prod, range, sum
dims = c(50, 50)
img<-makeImage(imagesize = dims, rnorm(prod(dims)) )
n4img<-n4BiasFieldCorrection(img)
n4img<-n4BiasFieldCorrection(img, mask = img > 0)
testthat::expect_error(n4BiasFieldCorrection(img, weight_mask = "somepath"))
testthat::expect_error(n4BiasFieldCorrection(img, splineParam = rep(200, 3)))
n4img<-n4BiasFieldCorrection(img, splineParam = c(200, 20))
rm(img); gc()
#> used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
#> Ncells 1860508 99.4 3551941 189.7 NA 2702461 144.4
#> Vcells 3323055 25.4 8388608 64.0 16384 5520418 42.2
rm(n4img); gc()
#> used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
#> Ncells 1860765 99.4 3551941 189.7 NA 2702461 144.4
#> Vcells 3323714 25.4 8388608 64.0 16384 5520418 42.2
fname = getANTsRData("r16")
in_img = antsImageRead(fname)
n4 = n4BiasFieldCorrection(in_img)
rm(n4); gc()
#> used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
#> Ncells 1863010 99.5 3551941 189.7 NA 2702461 144.4
#> Vcells 3329119 25.4 8388608 64.0 16384 5520418 42.2
mask = in_img > 0
mask2 = antsImageClone(mask, out_pixeltype = "float")
# failsCreated on 2020-02-20 by the reprex package (v0.3.0.9001)
> n4 = n4BiasFieldCorrection(in_img, mask = mask, verbose = TRUE)This seems to fail even before N4 starts:
Running N4 for 2-dimensional images.
*** caught segfault ***
*** caught segfault ***
address 0x109bc1000, cause 'memory not mapped'
address 0x109bc5000, cause 'memory not mapped'
Traceback:
Traceback:
1: 1: .helpn4BiasFieldCorrection(args).helpn4BiasFieldCorrection(args)
2: 2: n4BiasFieldCorrection(in_img, mask = mask, verbose = TRUE)n4BiasFieldCorrection(in_img, mask = mask, verbose = TRUE)
Possible actions:
1: abort (with core dump, if enabled)
2: normal R exit
3: exit R without saving workspace
4: exit R saving workspace
Possible actions:
1: abort (with core dump, if enabled)
2: normal R exit
3: exit R without saving workspace
4: exit R saving workspacethis example works fine for me on both OSX (Catalina) and on Ubuntu 18.04
@ntustison - still fails on dgx with data I sent previously ... am using /usr/bin/R
with ~/R/x86_64-pc-linux-gnu-library/
example is ~/code/n4biasfieldsegfault/run.R
On Thu, Feb 20, 2020 at 1:00 PM John Muschelli notifications@github.com wrote:
library(ANTsRCore)
>
> Attaching package: 'ANTsRCore'
> The following objects are masked from 'package:stats':
>
> sd, var
> The following objects are masked from 'package:base':
>
> all, any, apply, max, min, prod, range, sum
dims = c(50, 50) img<-makeImage(imagesize = dims, rnorm(prod(dims)) ) n4img<-n4BiasFieldCorrection(img) n4img<-n4BiasFieldCorrection(img, mask = img > 0) testthat::expect_error(n4BiasFieldCorrection(img, weight_mask = "somepath")) testthat::expect_error(n4BiasFieldCorrection(img, splineParam = rep(200, 3))) n4img<-n4BiasFieldCorrection(img, splineParam = c(200, 20))
rm(img); gc()
> used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
> Ncells 1860508 99.4 3551941 189.7 NA 2702461 144.4
> Vcells 3323055 25.4 8388608 64.0 16384 5520418 42.2
rm(n4img); gc()
> used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
> Ncells 1860765 99.4 3551941 189.7 NA 2702461 144.4
> Vcells 3323714 25.4 8388608 64.0 16384 5520418 42.2
fname = getANTsRData("r16") in_img = antsImageRead(fname) n4 = n4BiasFieldCorrection(in_img)
rm(n4); gc()
> used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
> Ncells 1863010 99.5 3551941 189.7 NA 2702461 144.4
> Vcells 3329119 25.4 8388608 64.0 16384 5520418 42.2
mask = in_img > 0 mask2 = antsImageClone(mask, out_pixeltype = "float")
fails
Created on 2020-02-20 by the reprex package https://reprex.tidyverse.org (v0.3.0.9001) Session info
sessioninfo::session_info()
> ─ Session info ───────────────────────────────────────────────────────────────
> setting value
> version R version 3.6.2 (2019-12-12)
> os macOS Mojave 10.14.6
> system x86_64, darwin15.6.0
> ui X11
> language (EN)
> collate en_US.UTF-8
> ctype en_US.UTF-8
> tz America/New_York
> date 2020-02-20
>
> ─ Packages ───────────────────────────────────────────────────────────────────
> package * version date lib source
> ANTsRCore * 0.7.3 2020-02-20 [1] Github (ANTsX/ANTsRCore@6f7e9aa)
> assertthat 0.2.1 2019-03-21 [1] CRAN (R 3.6.0)
> backports 1.1.5 2019-10-02 [1] CRAN (R 3.6.0)
> cli 2.0.1 2020-01-08 [1] CRAN (R 3.6.0)
> crayon 1.3.4 2017-09-16 [1] CRAN (R 3.6.0)
> digest 0.6.23 2019-11-23 [1] CRAN (R 3.6.0)
> ellipsis 0.3.0 2019-09-20 [1] CRAN (R 3.6.0)
> evaluate 0.14 2019-05-28 [1] CRAN (R 3.6.0)
> fansi 0.4.1 2020-01-08 [1] CRAN (R 3.6.0)
> fs 1.3.1 2019-05-06 [1] CRAN (R 3.6.0)
> glue 1.3.1 2019-03-12 [1] CRAN (R 3.6.0)
> highr 0.8 2019-03-20 [1] CRAN (R 3.6.0)
> htmltools 0.4.0 2019-10-04 [1] CRAN (R 3.6.0)
> ITKR 0.5.2 2020-02-20 [1] Github (stnava/ITKR@fe97efa)
> knitr 1.26.1 2020-01-05 [1] Github (muschellij2/knitr@f5af631)
> lattice 0.20-38 2018-11-04 [1] CRAN (R 3.6.2)
> magrittr 1.5 2014-11-22 [1] CRAN (R 3.6.0)
> Matrix 1.2-18 2019-11-27 [1] CRAN (R 3.6.2)
> pillar 1.4.3 2019-12-20 [1] CRAN (R 3.6.0)
> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 3.6.0)
> purrr 0.3.3 2019-10-18 [1] CRAN (R 3.6.0)
> R6 2.4.1 2019-11-12 [1] CRAN (R 3.6.0)
> Rcpp 1.0.3 2019-11-08 [1] CRAN (R 3.6.2)
> RcppEigen 0.3.3.7.0 2019-11-16 [1] CRAN (R 3.6.0)
> reprex 0.3.0.9001 2020-01-05 [1] Github (tidyverse/reprex@5ae0b29)
> rlang 0.4.4 2020-01-28 [1] CRAN (R 3.6.0)
> rmarkdown 2.0.7 2020-01-17 [1] Github (rstudio/rmarkdown@2faf16a)
> rstudioapi 0.11.0-9000 2020-02-19 [1] Github (rstudio/rstudioapi@deb9c47)
> sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 3.6.0)
> stringi 1.4.5 2020-01-11 [1] CRAN (R 3.6.0)
> stringr 1.4.0 2019-02-10 [1] CRAN (R 3.6.0)
> styler 1.1.1 2019-05-06 [1] CRAN (R 3.6.0)
> testthat 2.3.0 2019-11-05 [1] CRAN (R 3.6.0)
> tibble 2.1.3 2019-06-06 [1] CRAN (R 3.6.0)
> withr 2.1.2 2018-03-15 [1] CRAN (R 3.6.0)
> xfun 0.11 2019-11-12 [1] CRAN (R 3.6.0)
> yaml 2.2.0 2018-07-25 [1] CRAN (R 3.6.0)
>
> [1] /Library/Frameworks/R.framework/Versions/3.6/Resources/library
n4 = n4BiasFieldCorrection(in_img, mask = mask, verbose = TRUE)
Running N4 for 2-dimensional images.
caught segfault
caught segfault
address 0x109bc1000, cause 'memory not mapped'
address 0x109bc5000, cause 'memory not mapped'
Traceback:
Traceback:
1: 1: .helpn4BiasFieldCorrection(args).helpn4BiasFieldCorrection(args)
2: 2: n4BiasFieldCorrection(in_img, mask = mask, verbose = TRUE)n4BiasFieldCorrection(in_img, mask = mask, verbose = TRUE)
Possible actions:
1: abort (with core dump, if enabled)
2: normal R exit
3: exit R without saving workspace
4: exit R saving workspace
Possible actions:
1: abort (with core dump, if enabled)
2: normal R exit
3: exit R without saving workspace
4: exit R saving workspace
— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/ANTsX/ANTsRCore/issues/109?email_source=notifications&email_token=AACPE7WWYTKSBQZJK6ODAVDRD3ALNA5CNFSM4JV7SL6KYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEMPOJCY#issuecomment-589227147, or unsubscribe https://github.com/notifications/unsubscribe-auth/AACPE7SLGJX5IOD4OD75O6DRD3ALNANCNFSM4JV7SL6A .
ntustison
commented
4 years ago Yeah, that example works for me, too. @stnava --- it looks I don't have permission to access that example. Can you open up the permissions?
stnava
commented
4 years ago Done
On Thu, Feb 20, 2020 at 2:29 PM Nick Tustison notifications@github.com wrote:
Yeah, that example works for me, too. @stnava https://github.com/stnava --- it looks I don't have permission to access that example. Can you open up the permissions?
— You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub https://github.com/ANTsX/ANTsRCore/issues/109?email_source=notifications&email_token=AACPE7WEJ4OTQFSWL5ANMC3RD3K27A5CNFSM4JV7SL6KYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEMPYCMI#issuecomment-589267249, or unsubscribe https://github.com/notifications/unsubscribe-auth/AACPE7X2HOBM67HGQS6RNXTRD3K27ANCNFSM4JV7SL6A .
--
brian
ntustison
commented
4 years ago Thanks @stnava . This ("/usr/bin/R") was particularly useful. I installed a different version of R on the DGX which is why I haven't been able to reproduce. So, in summary, for me
R --version = 3.5.1 ---> passes/usr/bin/R --version = 3.6.1 ---> segfaultsI assume both you and @muschellij2 are using 3.6.1, correct?
stnava
commented
4 years ago yes
brian
On Thu, Feb 20, 2020 at 4:11 PM Nick Tustison notifications@github.com wrote:
Thanks @stnava https://github.com/stnava . This ("/usr/bin/R") was particularly useful. I installed a different version of R on the DGX which is why I haven't been able to reproduce. So, in summary, for me
- R --version = 3.5.1 ---> passes
- /usr/bin/R --version = 3.6.1 ---> segfaults
I assume both you and @muschellij2 https://github.com/muschellij2 are using 3.6.1, correct?
— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/ANTsX/ANTsRCore/issues/109?email_source=notifications&email_token=AACPE7VP5ATVFWT7MNGPV2DRD3WXFA5CNFSM4JV7SL6KYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEMQFBDI#issuecomment-589320333, or unsubscribe https://github.com/notifications/unsubscribe-auth/AACPE7XUXKK3WAS6CI7B65LRD3WXFANCNFSM4JV7SL6A .
muschellij2
commented
4 years ago Using 3.6.2 Best, John
On Thu, Feb 20, 2020 at 4:49 PM stnava notifications@github.com wrote:
yes
brian
On Thu, Feb 20, 2020 at 4:11 PM Nick Tustison notifications@github.com wrote:
Thanks @stnava https://github.com/stnava . This ("/usr/bin/R") was particularly useful. I installed a different version of R on the DGX which is why I haven't been able to reproduce. So, in summary, for me
- R --version = 3.5.1 ---> passes
- /usr/bin/R --version = 3.6.1 ---> segfaults
I assume both you and @muschellij2 https://github.com/muschellij2 are using 3.6.1, correct?
— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub < https://github.com/ANTsX/ANTsRCore/issues/109?email_source=notifications&email_token=AACPE7VP5ATVFWT7MNGPV2DRD3WXFA5CNFSM4JV7SL6KYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEMQFBDI#issuecomment-589320333 , or unsubscribe < https://github.com/notifications/unsubscribe-auth/AACPE7XUXKK3WAS6CI7B65LRD3WXFANCNFSM4JV7SL6A
.
— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/ANTsX/ANTsRCore/issues/109?email_source=notifications&email_token=AAIGPLRERVKGMHU6B3MZEIDRD33INA5CNFSM4JV7SL6KYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEMQI7GI#issuecomment-589336473, or unsubscribe https://github.com/notifications/unsubscribe-auth/AAIGPLQ5A2S3EGY7DJGJ7ETRD33INANCNFSM4JV7SL6A .
ntustison
commented
4 years ago muschellij2
commented
4 years ago Same behavior - still failing if both sets of code are run, but not failing if first set of code is not run.
ib> sessioninfo::session_info("ANTsRCore")
─ Session info ───────────────────────────────────────────────────────────────
setting value
version R version 3.6.3 (2020-02-29)
os macOS Mojave 10.14.6
system x86_64, darwin15.6.0
ui X11
language (EN)
collate en_US.UTF-8
ctype en_US.UTF-8
tz America/New_York
date 2020-03-23
─ Packages ───────────────────────────────────────────────────────────────────
package * version date lib source
ANTsRCore 0.7.3.1 2020-03-23 [1] Github (ANTsX/ANTsRCore@074e8cd)
ITKR 0.5.3 2020-03-18 [1] Github (stnava/ITKR@715331d)
lattice 0.20-38 2018-11-04 [1] CRAN (R 3.6.3)
magrittr 1.5 2014-11-22 [1] CRAN (R 3.6.0)
Matrix 1.2-18 2019-11-27 [1] CRAN (R 3.6.3)
Rcpp 1.0.4.3 2020-03-20 [1] Github (RcppCore/Rcpp@ce5538b)
RcppEigen 0.3.3.7.0 2019-11-16 [1] CRAN (R 3.6.0)
[1] /Library/Frameworks/R.framework/Versions/3.6/Resources/libraryThat's unfortunate. I was able to reproduce the issue on my laptop if I went the git clone ..; R CMD INSTALL ANTsRCore installation route vs. devtools::install_github(). And what I corrected seemed to fit this bizarre behavior and it certainly fixed it on my laptop. At this point, I don't know what else to do.
muschellij2
commented
4 years ago OK - I'll remove all and reload all the packages today. Best, John
On Mon, Mar 23, 2020 at 12:20 PM Nick Tustison notifications@github.com wrote:
That's unfortunate. I was able to reproduce the issue on my laptop if I went the git clone ..; R CMD INSTALL ANTsRCore installation route vs. devtools::install_github(). And what I corrected seemed to fit this bizarre behavior and it certainly fixed it on my laptop. At this point, I don't know what else to do.
— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/ANTsX/ANTsRCore/issues/109#issuecomment-602705340, or unsubscribe https://github.com/notifications/unsubscribe-auth/AAIGPLSJFVFT6TDQQCBT3LLRI6D3HANCNFSM4JV7SL6A .
ntustison
commented
4 years ago Okay, if that doesn't work, one thing we can do is some simplistic, yet effective, debugging by placing std::cout statements in N4BiasFieldCorrection.cxx before compilation and seeing where it segfaults.
muschellij2
commented
4 years ago Still failing - It's a bit complicated to change what is being used, need to change ANTs tag, then make sure ANTs tag really matches up with ITKR ITK tag. So if that can be merged after testing, it may be easier to set this.
muschellij2
commented
4 years ago Not sure what to do here?
ntustison
commented
4 years ago I'm sorry but I don't either at this point. Originally, there was an obvious memory problem with one of the image iterators which definitely needed to be fixed. After fixing that, there was an additional memory issue (or, I would say, idiosyncrasy with specific platforms) that I was able to reproduce on only one of my machines through a specific build process. After modifying that, I can no longer reproduce the issue on any machine to which I have access.
Are you able to reproduce this on more than one machine? And, if so, can you isolate the section of code through the use of std::cout statements so I have some idea where this memory issue is surfacing?
muschellij2
commented
4 years ago I don't have another mac to use, and didn't want to fiddle around with the xcode installs (to try to make a similar machine on Travis). TL;DR - I need my PR https://github.com/ANTsX/ANTs/pull/978 accepted before I can debug using std::cout
The impossibility of "adding std::cout" statements is because N4 is really called from ANTs, not ANTsRCore code, so you have to send a PR to ANTs, not ANTsRCore, which I've done here: https://github.com/ANTsX/ANTs/pull/978, but need some review and then integration. Then, I need to make sure that I update the configure git tag to point to that ANTs installation, but also double check that the external ITK tag in the cmake builds hasn't changed because it then hasn't been checked against that ITK build and ensure that ITK tag is the same one with ITKR.
Sorry - bit of a rant, but also a useful pointer in the future to people who want to debug/make additions. Small recap So it's ITK tag → ITKR, is also referenced in CMake of ANTs, which is what ANTsRCore will pull and reference against. So the ANTs Tag needs ot refer to the ITKR ITK tag (for consistency) and then the ANTsRCore tag needs to be updated to the ANTs Tag. Then building with ANTsRCore will refer to a specific ANTs tag, which references a specific ITK tag, which should be the same ITK tag in stnava/ITKR.
Best, John
On Mon, Mar 30, 2020 at 4:41 PM Nick Tustison notifications@github.com wrote:
I'm sorry but I don't either at this point. Originally, there was an obvious memory problem with one of the image iterators which definitely needed to be fixed. After fixing that, there was an additional memory issue (or, I would say, idiosyncrasy with specific platforms) that I was able to reproduce on only one of my machines through a specific build process. After modifying that, I can no longer reproduce the issue on any machine to which I have access.
Are you able to reproduce this on more than one machine? And, if so, can you isolate the section of code through the use of std::cout statements so I have some idea where this memory issue is surfacing?
— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/ANTsX/ANTsRCore/issues/109#issuecomment-606237685, or unsubscribe https://github.com/notifications/unsubscribe-auth/AAIGPLVE7IBNXICWF3C5PSDRKD7YHANCNFSM4JV7SL6A .
muschellij2
commented
4 years ago Oddly, all the fails for that PR are Xcode 10: https://travis-ci.org/github/ANTsX/ANTs/builds/665998685?utm_source=github_status&utm_medium=notification
ntustison
commented
4 years ago Why do you need to modify N4BiasFieldCorrection.cxx in the ANTsX GitHub repo? When I discovered the second issue, I was only modifying it locally in the ANTsRCore directory.
$ pwd
/Users/ntustison/Pkg/ANTsRCore
$ find . -name N4BiasFieldCorrection.cxx
./inst/include/N4BiasFieldCorrection.cxx
./src/ants/Examples/N4BiasFieldCorrection.cxxBut, I agree, it's a burden. However, I don't what else to tell you as I can't reproduce it. It would be nice if there were another machine that could verify that this isn't an isolated issue.
muschellij2
commented
4 years ago OK - added the lines and seems to segfault at: https://github.com/muschellij2/ANTs/blob/master/Examples/N4BiasFieldCorrection.cxx#L147
> n4 = n4BiasFieldCorrection(in_img, mask = mask, verbose = TRUE)
Creating ImageType
Creating MaskImageType
Running N4 for 2-dimensional images.
Getting CorrecterType
Reading in Input Image
maskImageOption: Option (0x7faae9e1cb40)
RTTI typeinfo: itk::ants::CommandLineOption
Reference Count: 3
Modified Time: 739716
Debug: Off
Object Name:
Observers:
none
Source: (none)
Source output name: (none)
Release Data: Off
Data Released: False
Global Release Data: Off
PipelineMTime: 0
UpdateMTime: 0
RealTimeStamp: 0 seconds
Reading in Mask file: 0x7faae9a604b0
*** caught segfault ***Interesting. So it seems there's something going on that the reader doesn't like in this particular spot of this particular program. Not surprising as there's a bit of pointer stuff going on there. Before we dive into that, perhaps you should try replacing the ReadImageData call with the more ITK direct substitute. Specifically, comment out line 147 of your code and add the following:
using MaskImageReaderType = itk::ImageFileReader<MaskImageType>;
typename MaskImageReaderType::Pointer maskImageReader = MaskImageReaderType::New();
maskImageReader->SetFileName( inputMaskFile.c_str() );
maskImage = maskImageReader->GetOutput();
maskImage->Update();
maskImage->DisconnectPipeline();Seems to have broken all the code:
library(ANTsRCore)
#>
#> Attaching package: 'ANTsRCore'
#> The following objects are masked from 'package:stats':
#>
#> sd, var
#> The following objects are masked from 'package:base':
#>
#> all, any, apply, max, min, prod, range, sum
dims = c(50, 50)
img<-makeImage(imagesize = dims, rnorm(prod(dims)) )
n4img<-n4BiasFieldCorrection(img)
n4img<-n4BiasFieldCorrection(img, mask = img > 0)
#> /Library/Frameworks/R.framework/Versions/3.6/Resources/library/ITKR/libs/include/ITK-5.1/itkImageFileReader.hxx:133:
#> Could not create IO object for reading file 0x7f88c286b610
#> The file doesn't exist.
#> Filename = 0x7f88c286b610
testthat::expect_error(n4BiasFieldCorrection(img, weight_mask = "somepath"))
testthat::expect_error(n4BiasFieldCorrection(img, splineParam = rep(200, 3)))
n4img<-n4BiasFieldCorrection(img, splineParam = c(200, 20))
rm(img); gc()
#> used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
#> Ncells 1893705 101.2 3797505 202.9 NA 2451542 131.0
#> Vcells 3381342 25.8 8388608 64.0 16384 4749362 36.3
rm(n4img); gc()
#> used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
#> Ncells 1893944 101.2 3797505 202.9 NA 2451542 131.0
#> Vcells 3381972 25.9 8388608 64.0 16384 4749362 36.3
fname = getANTsRData("r16")
in_img = antsImageRead(fname)
n4 = n4BiasFieldCorrection(in_img)
rm(n4); gc()
#> used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
#> Ncells 1897591 101.4 3797505 202.9 NA 2451542 131.0
#> Vcells 3390396 25.9 8388608 64.0 16384 4749362 36.3
mask = in_img > 0
mask2 = antsImageClone(mask, out_pixeltype = "float")
# fails
mask
#> antsImage
#> Pixel Type : unsigned char
#> Components Per Pixel: 1
#> Dimensions : 256x256
#> Voxel Spacing : 1x1
#> Origin : 0 0
#> Direction : 1 0 0 1
sum(mask)
#> [1] 19278
n4 = n4BiasFieldCorrection(in_img, mask = mask, verbose = TRUE)
#> /Library/Frameworks/R.framework/Versions/3.6/Resources/library/ITKR/libs/include/ITK-5.1/itkImageFileReader.hxx:133:
#> Could not create IO object for reading file 0x7f88bde1f0f0
#> The file doesn't exist.
#> Filename = 0x7f88bde1f0f0
# failsCreated on 2020-03-30 by the reprex package (v0.3.0.9001)
ntustison
commented
4 years ago Sorry, my bad---I forgot that all the R overhead was added to the ANTs Read/Write functionality.
So I don't know what to do at this point. As far as I can tell, it doesn't look to be anything specific to the N4 program. If I could reproduce the error, then I would see where it's segfaulting in the reader or switch the order of reading in the input image vs. the mask. But all this would be just trial-and-error and certainly not something that can be done in a GitHub repo thread.
muschellij2
commented
4 years ago FYI - we're trying using GitHub actions to compile/test the packages and found that this still is lurking:
https://github.com/muschellij2/ANTsRCore/runs/832316950?check_suite_focus=true#step:9:185
ntustison
commented
4 years ago Thanks @muschellij2 .
I would assume the seg faulting is the same as before in that it occurs when the mask is read using the ReadImage function. However, I still can't reproduce this error on any of my machines or any of the machines to which I have access. Maybe it has something to do with this comment here but without being able to reproduce, I can't diagnose properly or provide a possible fix. Perhaps you can try to pinpoint the precise line in that function where it seg faults.
Describe the bug Segfault when mask is 2D unsigned char.
To Reproduce
Created on 2019-12-05 by the reprex package (v0.3.0.9000)
Session info
``` r sessioninfo::session_info() #> ─ Session info ────────────────────────────────────────────────────────── #> setting value #> version R version 3.6.0 (2019-04-26) #> os macOS Mojave 10.14.6 #> system x86_64, darwin15.6.0 #> ui X11 #> language (EN) #> collate en_US.UTF-8 #> ctype en_US.UTF-8 #> tz America/New_York #> date 2019-12-05 #> #> ─ Packages ────────────────────────────────────────────────────────────── #> package * version date lib source #> ANTsRCore * 0.7.3 2019-11-26 [1] local #> assertthat 0.2.1 2019-03-21 [1] CRAN (R 3.6.0) #> cli 1.1.0 2019-03-19 [1] CRAN (R 3.6.0) #> crayon 1.3.4 2017-09-16 [1] CRAN (R 3.6.0) #> digest 0.6.23 2019-11-23 [1] CRAN (R 3.6.0) #> evaluate 0.14 2019-05-28 [1] CRAN (R 3.6.0) #> highr 0.8 2019-03-20 [1] CRAN (R 3.6.0) #> htmltools 0.4.0 2019-10-04 [1] CRAN (R 3.6.0) #> ITKR 0.5.2 2019-11-05 [1] Github (stnava/ITKR@fe97efa) #> knitr 1.24.3 2019-08-28 [1] Github (muschellij2/knitr@abcea3d) #> lattice 0.20-38 2018-11-04 [1] CRAN (R 3.6.0) #> magrittr 1.5 2014-11-22 [1] CRAN (R 3.6.0) #> Matrix 1.2-17 2019-03-22 [1] CRAN (R 3.6.0) #> Rcpp 1.0.3 2019-11-08 [1] CRAN (R 3.6.0) #> RcppEigen 0.3.3.5.0 2018-11-24 [1] CRAN (R 3.6.0) #> rlang 0.4.2 2019-11-23 [1] CRAN (R 3.6.0) #> rmarkdown 1.16 2019-10-01 [1] CRAN (R 3.6.0) #> sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 3.6.0) #> stringi 1.4.3 2019-03-12 [1] CRAN (R 3.6.0) #> stringr 1.4.0 2019-02-10 [1] CRAN (R 3.6.0) #> withr 2.1.2 2018-03-15 [1] CRAN (R 3.6.0) #> xfun 0.11 2019-11-12 [1] CRAN (R 3.6.0) #> yaml 2.2.0 2018-07-25 [1] CRAN (R 3.6.0) #> #> [1] /Library/Frameworks/R.framework/Versions/3.6/Resources/library ```