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muschellij2 / neurobase

Neuroconductor Base Package
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writenii and readnii bug with binary and missing data #4

Closed avalcarcel9 closed 4 years ago

avalcarcel9 commented 4 years ago

I have an image that is filled with 0/1/NA. Writing and reading using neurobase::writenii and neurobase::readnii fills the NA values with 0. Default function has dtype = TRUE so this is as expected but even after setting dtype to FALSE image is stripped of NA values. See example below:

# Bug in neurobase::writenii and neurobase::readnii
binary_mask = MNITemplate::readMNI()
binary_mask[binary_mask > 0] = 1
any(is.na(binary_mask))
# [1] FALSE
na_mask = binary_mask
na_mask[1,1,1] = NA
any(is.na(na_mask)) 
# [1] TRUE
# Attempt 1 - over-writes NA with binary value because default dtype is TRUE
na_filepath = tempfile(fileext = "na_mask.nii.gz")
neurobase::writenii(na_mask, na_filepath)
na_mask1 = neurobase::readnii(na_filepath)
any(is.na(na_mask1)) 
# [1] FALSE
# Bug in attempt 2
# Attempt 2 - force dtype to FALSE but does not perform as expected still over-writes NA values
neurobase::writenii(na_mask, na_filepath, dtype = FALSE)
na_mask2 = neurobase::readnii(na_filepath, dtype = FALSE)
any(is.na(na_mask2)) 
# [1] FALSE
# Attempt 3 - write with RNifti performs as expected
RNifti::writeNifti(na_mask, na_filepath)
na_mask3 = neurobase::readnii(na_filepath) # did need to specify dtype = FALSE or TRUE here and worked properly
any(is.na(na_mask3))
# [1] TRUE
muschellij2 commented 4 years ago

I believe this is due to oro.nifti::writeNifTI. 

binary_mask = MNITemplate::readMNI()
binary_mask[binary_mask > 0] = 1
any(is.na(binary_mask))
#> [1] FALSE
# [1] FALSE
na_mask = binary_mask
na_mask[1,1,1] = NA
any(is.na(na_mask))
#> [1] TRUE

na_filepath = tempfile(fileext = "na_mask")
oro.nifti::writeNIfTI(na_mask, na_filepath)
na_mask1 = oro.nifti::readNIfTI(paste0(na_filepath, ".nii.gz"), reorient = FALSE)
na_mask1[1,1,1]
#> [1] 0
any(is.na(na_mask1)) 
#> [1] FALSE

Created on 2020-05-28 by the reprex package (v0.3.0.9001)

avalcarcel9 commented 4 years ago

What does dtype = TRUE or FALSE in writenii and readnii control then? Documentation is a little confusing.

muschellij2 commented 4 years ago

So it's an issue with how readBin works with NA and size = 4 from what I can see. I think it's fixed.

muschellij2 commented 4 years ago

Should be fixed with oro.nifti 0.10.3 version.

avalcarcel9 commented 4 years ago

Yup code for attempt 2 now behaves as expected! Thanks so much!

avalcarcel9 commented 4 years ago

Bugs still present related to this issue even in updated package. Using neurobase::writenii with dtype = FALSE where data is numeric and contains no missing (no NA) then image is saved as strange integers. You can manually compare the maps or use summary in R to see that values have been changed drastically.

> set.seed(5)
> dims = rep(10, 3)
> arr = array(rnorm(prod(dims)), dim = dims)
> nim = oro.nifti::nifti(arr)
> summary(nim)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
-3.4981 -0.6556  0.0223  0.0174  0.6919  3.4019 
> # Use default dtype (dtype = TRUE)
> neurobase::writenii(nim, '~/Desktop/test_dtype_default.nii.gz')
> # Set dtype = FALSE
> neurobase::writenii(nim, '~/Desktop/test_dtype_false.nii.gz', dtype = FALSE)
> ## Can manually inspect or compare these images in a viewer or read them back in to compare
> nim_default = neurobase::readnii('~/Desktop/test_dtype_default.nii.gz', dtype = FALSE)
> summary(nim_default)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
-3.4981 -0.6556  0.0223  0.0174  0.6919  3.4019 
> nim_dtype_false = neurobase::readnii('~/Desktop/test_dtype_false.nii.gz', dtype = FALSE)
> summary(nim_dtype_false)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
   0.00    0.00    0.00   38.41    1.00  255.00

Session info below for reference:

> sessioninfo::session_info()
─ Session info ─────────────────────────────────────────────────────────────────────────────────────────────────
 setting  value                       
 version  R version 3.6.1 (2019-07-05)
 os       macOS Catalina 10.15.6      
 system   x86_64, darwin15.6.0        
 ui       RStudio                     
 language (EN)                        
 collate  en_US.UTF-8                 
 ctype    en_US.UTF-8                 
 tz       America/New_York            
 date     2020-09-10                  

─ Packages ─────────────────────────────────────────────────────────────────────────────────────────────────────
 ! package            * version    date       lib source                                 
   abind                1.4-5      2016-07-21 [2] CRAN (R 3.6.0)                         
   aliviateR            0.0.3      2020-07-09 [1] local                                  
   animation            2.6        2018-12-11 [2] CRAN (R 3.6.0)                         
   ANTsR                0.4.9      2019-07-22 [2] Github (stnava/ANTsR@69d65b6)          
   ANTsRCore            0.7.0      2019-07-22 [2] Github (ANTsX/ANTsRCore@8f99c58)       
   assertthat           0.2.1      2019-03-21 [2] CRAN (R 3.6.0)                         
   backports            1.1.6      2020-04-05 [2] CRAN (R 3.6.1)                         
   badgecreatr          0.2.0      2019-01-07 [2] CRAN (R 3.6.0)                         
   BiocGenerics         0.32.0     2019-10-29 [2] Bioconductor                           
   BiocParallel         1.20.1     2019-12-21 [2] Bioconductor                           
   bitops               1.0-6      2013-08-17 [2] CRAN (R 3.6.0)                         
   boot                 1.3-24     2019-12-20 [2] CRAN (R 3.6.0)                         
   broom                0.5.5      2020-02-29 [2] CRAN (R 3.6.0)                         
   broom.mixed          0.2.4      2019-02-21 [2] CRAN (R 3.6.0)                         
   cli                  2.0.2      2020-02-28 [2] CRAN (R 3.6.0)                         
   coda                 0.19-3     2019-07-05 [2] CRAN (R 3.6.0)                         
   colorspace           1.4-1      2019-03-18 [2] CRAN (R 3.6.0)                         
   crayon               1.3.4      2017-09-16 [2] CRAN (R 3.6.0)                         
   crosstalk            1.0.0      2016-12-21 [2] CRAN (R 3.6.0)                         
   data.table           1.12.8     2019-12-09 [2] CRAN (R 3.6.0)                         
   DelayedArray         0.12.3     2020-04-09 [1] Bioconductor                           
   DelayedMatrixStats   1.8.0      2019-10-29 [2] Bioconductor                           
   digest               0.6.25     2020-02-23 [2] CRAN (R 3.6.0)                         
   dplyr                1.0.0      2020-05-29 [1] CRAN (R 3.6.2)                         
   ellipsis             0.3.0      2019-09-20 [2] CRAN (R 3.6.0)                         
   evaluate             0.14       2019-05-28 [2] CRAN (R 3.6.0)                         
   extrantsr            3.9.11     2019-09-04 [2] local                                  
   fansi                0.4.1      2020-01-08 [2] CRAN (R 3.6.0)                         
   fastmap              1.0.1      2019-10-08 [2] CRAN (R 3.6.0)                         
   forcats              0.5.0      2020-03-01 [2] CRAN (R 3.6.0)                         
   fs                   1.3.1      2019-05-06 [2] CRAN (R 3.6.0)                         
   fslr                 2.24.1     2019-08-05 [1] CRAN (R 3.6.0)                         
   geepack              1.3-1      2019-12-13 [2] CRAN (R 3.6.0)                         
   generics             0.0.2      2018-11-29 [2] CRAN (R 3.6.0)                         
   ggplot2              3.3.0      2020-03-05 [1] CRAN (R 3.6.0)                         
   git2r                0.27.1     2020-05-03 [1] CRAN (R 3.6.2)                         
   glue                 1.4.1      2020-05-13 [1] CRAN (R 3.6.2)                         
   gridExtra            2.3        2017-09-09 [2] CRAN (R 3.6.0)                         
   gtable               0.3.0      2019-03-25 [2] CRAN (R 3.6.0)                         
   hash                 2.2.6.1    2019-03-04 [2] CRAN (R 3.6.0)                         
   HDF5Array            1.14.4     2020-04-13 [1] Bioconductor                           
   hms                  0.5.3      2020-01-08 [2] CRAN (R 3.6.0)                         
   htmltools            0.5.0      2020-06-16 [1] CRAN (R 3.6.2)                         
   htmlwidgets          1.5.1      2019-10-08 [2] CRAN (R 3.6.0)                         
   httpuv               1.5.2      2019-09-11 [2] CRAN (R 3.6.0)                         
   imcoext              0.1.4      2020-09-10 [1] local                                  
   imcolegacy           1.7.0      2020-05-27 [1] local                                  
   IRanges              2.20.2     2020-01-13 [2] Bioconductor                           
   iterators            1.0.12     2019-07-26 [2] CRAN (R 3.6.0)                         
   ITKR                 0.5.0      2019-07-22 [2] Github (stnava/ITKR@5e76b7e)           
   jsonlite             1.7.0      2020-06-25 [1] CRAN (R 3.6.2)                         
   knitr                1.29       2020-06-23 [1] CRAN (R 3.6.2)                         
   later                1.0.0      2019-10-04 [2] CRAN (R 3.6.0)                         
   lattice              0.20-38    2018-11-04 [2] CRAN (R 3.6.1)                         
   lifecycle            0.2.0      2020-03-06 [2] CRAN (R 3.6.0)                         
   lme4                 1.1-23     2020-04-07 [2] CRAN (R 3.6.1)                         
   lmerTest             3.1-1      2019-12-13 [2] CRAN (R 3.6.0)                         
   lubridate          * 1.7.9      2020-06-08 [1] CRAN (R 3.6.2)                         
   magrittr           * 1.5        2014-11-22 [2] CRAN (R 3.6.0)                         
   manipulateWidget     0.10.0     2018-06-11 [2] CRAN (R 3.6.0)                         
   MASS                 7.3-51.5   2019-12-20 [2] CRAN (R 3.6.0)                         
   Matrix               1.2-18     2019-11-27 [2] CRAN (R 3.6.0)                         
   matrixStats          0.56.0     2020-03-13 [1] CRAN (R 3.6.0)                         
   mgcv                 1.8-31     2019-11-09 [2] CRAN (R 3.6.0)                         
   mime                 0.9        2020-02-04 [2] CRAN (R 3.6.1)                         
   miniUI               0.1.1.1    2018-05-18 [2] CRAN (R 3.6.0)                         
   minqa                1.2.4      2014-10-09 [2] CRAN (R 3.6.0)                         
   munsell              0.5.0      2018-06-12 [2] CRAN (R 3.6.0)                         
 V neurobase            1.30.1     2020-09-10 [1] Github (muschellij2/neurobase@6946b27) 
   neuroim              0.0.6      2016-01-07 [2] CRAN (R 3.6.0)                         
   NiftiArray           0.99.6.1   2020-05-03 [1] Neuroconductor-Devel-Releases (R 3.6.3)
   nlme                 3.1-143    2019-12-10 [2] CRAN (R 3.6.0)                         
   nloptr               1.2.2.1    2020-03-11 [2] CRAN (R 3.6.0)                         
   numDeriv             2016.8-1.1 2019-06-06 [2] CRAN (R 3.6.0)                         
   oro.nifti            0.11.0     2020-09-08 [1] CRAN (R 3.6.2)                         
   pbapply              1.4-2      2019-08-31 [2] CRAN (R 3.6.0)                         
   pillar               1.4.3      2019-12-20 [2] CRAN (R 3.6.1)                         
   pkgconfig            2.0.3      2019-09-22 [2] CRAN (R 3.6.0)                         
   plyr                 1.8.6      2020-03-03 [2] CRAN (R 3.6.0)                         
   promises             1.1.0      2019-10-04 [2] CRAN (R 3.6.0)                         
   purrr                0.3.3      2019-10-18 [2] CRAN (R 3.6.0)                         
   R.matlab             3.6.2      2018-09-27 [2] CRAN (R 3.6.0)                         
   R.methodsS3          1.8.0      2020-02-14 [1] CRAN (R 3.6.0)                         
   R.oo                 1.23.0     2019-11-03 [2] CRAN (R 3.6.0)                         
   R.utils              2.9.2      2019-12-08 [2] CRAN (R 3.6.0)                         
   R6                   2.4.1      2019-11-12 [2] CRAN (R 3.6.0)                         
   Rcpp                 1.0.4      2020-03-17 [1] CRAN (R 3.6.0)                         
   RcppEigen            0.3.3.7.0  2019-11-16 [2] CRAN (R 3.6.0)                         
   readr                1.3.1      2018-12-21 [2] CRAN (R 3.6.0)                         
   reshape2             1.4.3      2017-12-11 [2] CRAN (R 3.6.0)                         
   rgl                  0.100.30   2019-08-19 [2] CRAN (R 3.6.1)                         
   rhdf5                2.30.1     2019-11-26 [2] Bioconductor                           
   Rhdf5lib             1.8.0      2019-10-29 [2] Bioconductor                           
   rlang                0.4.7      2020-07-09 [1] CRAN (R 3.6.2)                         
   rlist                0.4.6.1    2016-04-04 [2] CRAN (R 3.6.0)                         
   rmarkdown            2.3        2020-06-18 [1] CRAN (R 3.6.2)                         
   RNifti               1.1.0      2020-01-31 [2] CRAN (R 3.6.0)                         
   rstudioapi           0.11       2020-02-07 [1] CRAN (R 3.6.0)                         
   S4Vectors            0.24.4     2020-04-09 [1] Bioconductor                           
   scales               1.1.0      2019-11-18 [2] CRAN (R 3.6.0)                         
   sessioninfo          1.1.1      2018-11-05 [2] CRAN (R 3.6.0)                         
   shiny                1.4.0.2    2020-03-13 [1] CRAN (R 3.6.0)                         
   stapler              0.7.1      2020-01-09 [2] CRAN (R 3.6.0)                         
   statmod              1.4.34     2020-02-17 [2] CRAN (R 3.6.0)                         
   stringi              1.4.6      2020-02-17 [2] CRAN (R 3.6.0)                         
   stringr              1.4.0      2019-02-10 [2] CRAN (R 3.6.0)                         
   tibble               3.0.0      2020-03-30 [2] CRAN (R 3.6.2)                         
   tidyr                1.0.2      2020-01-24 [2] CRAN (R 3.6.0)                         
   tidyselect           1.1.0      2020-05-11 [1] CRAN (R 3.6.2)                         
   TMB                  1.7.16     2020-01-15 [2] CRAN (R 3.6.0)                         
   usethis              1.6.0      2020-04-09 [1] CRAN (R 3.6.1)                         
   vctrs                0.3.1      2020-06-05 [1] CRAN (R 3.6.2)                         
   voxel                1.3.5      2019-12-06 [2] Neuroconductor-Releases (R 3.6.1)      
   webshot              0.5.2      2019-11-22 [2] CRAN (R 3.6.0)                         
   WhiteStripe          2.3.2      2019-10-01 [2] CRAN (R 3.6.0)                         
   withr                2.1.2      2018-03-15 [2] CRAN (R 3.6.0)                         
   xfun                 0.15       2020-06-21 [1] CRAN (R 3.6.2)                         
   xtable               1.8-4      2019-04-21 [2] CRAN (R 3.6.0)                         
   yaImpute             1.0-31     2019-01-09 [2] CRAN (R 3.6.0)                         
   yaml                 2.2.1      2020-02-01 [2] CRAN (R 3.6.0)
avalcarcel9 commented 4 years ago

Also is it concerning that local images are not all equal to read in images?

> all.equal(nim_default, nim)
[1] "Attributes: < Component “bitpix”: Mean relative difference: 0.75 >"         
[2] "Attributes: < Component “cal_max”: Mean relative difference: 3.293414e-08 >"
[3] "Attributes: < Component “datatype”: Mean relative difference: 0.875 >"      
[4] "Attributes: < Component “glmax”: Mean relative difference: 1 >"             
[5] "Attributes: < Component “glmin”: Mean relative difference: 1 >"             
[6] "Mean relative difference: 2.208861e-08"

I know the difference is small but this is a little worrisome to me.

muschellij2 commented 4 years ago

In the future, can you use reprex: https://github.com/tidyverse/reprex, makes things a lot easier - looking into it

muschellij2 commented 4 years ago

This is due to the way you're using oro.nifti::nifti. If you look at oro.nifti::nifti, the datatype=2 by default.

muschellij2 commented 4 years ago

Trying with the default oro.nifti::nifti

set.seed(5)
dims = rep(10, 3)
arr = array(rnorm(prod(dims)), dim = dims)
nim = oro.nifti::nifti(arr)
summary(nim)
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#> -3.4981 -0.6556  0.0223  0.0174  0.6919  3.4019
nim@datatype
#> [1] 2

Writing using writenii (which has dtype = TRUE)

tfile = tempfile(fileext = ".nii.gz")
neurobase::writenii(nim, tfile)
nim_default = neurobase::readnii(tfile)
summary(nim_default)
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#> -3.4981 -0.6556  0.0223  0.0174  0.6919  3.4019

Writing using writenii (which has dtype = TRUE)

bad = abs(nim - nim_default)
max(bad) < 1e-06
#> [1] TRUE
hist(bad)

nim_default = neurobase::readnii(tfile, dtype = FALSE)
summary(nim_default)
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#> -3.4981 -0.6556  0.0223  0.0174  0.6919  3.4019

bad = abs(nim - nim_default)
max(bad)
#> [1] 1.190171e-07
hist(bad)

This is the issue -

nim@datatype
#> [1] 2

So we’re not surprised this doesnt work

tfile_false = tempfile(fileext = ".nii.gz")
neurobase::writenii(nim, tfile_false, dtype = FALSE)
nim_dtype_false = neurobase::readnii(tfile_false, dtype = FALSE)
summary(nim_dtype_false)
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#>    0.00    0.00    0.00   38.41    1.00  255.00

Now if we use nifti correctly

nim = oro.nifti::nifti(arr, datatype = oro.nifti::convert.datatype()[["FLOAT32"]])
nim@datatype
#> [1] 16
nim
#> NIfTI-1 format
#>   Type            : nifti
#>   Data Type       : 16 (FLOAT32)
#>   Bits per Pixel  : 32
#>   Slice Code      : 0 (Unknown)
#>   Intent Code     : 0 (None)
#>   Qform Code      : 0 (Unknown)
#>   Sform Code      : 0 (Unknown)
#>   Dimension       : 10 x 10 x 10
#>   Pixel Dimension : 1 x 1 x 1
#>   Voxel Units     : Unknown
#>   Time Units      : Unknown
summary(nim)
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#> -3.4981 -0.6556  0.0223  0.0174  0.6919  3.4019

tfile = tempfile(fileext = ".nii.gz")
neurobase::writenii(nim, tfile)
nim_default = neurobase::readnii(tfile)
summary(nim_default)
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#> -3.4981 -0.6556  0.0223  0.0174  0.6919  3.4019

bad = abs(nim - nim_default)
max(bad)
#> [1] 1.190171e-07
hist(bad)

nim_default = neurobase::readnii(tfile, dtype = FALSE)
summary(nim_default)
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#> -3.4981 -0.6556  0.0223  0.0174  0.6919  3.4019

bad = abs(nim - nim_default)
max(bad)
#> [1] 1.190171e-07
hist(bad)

tfile_false = tempfile(fileext = ".nii.gz")
neurobase::writenii(nim, tfile_false, dtype = FALSE)
nim_dtype_false = neurobase::readnii(tfile_false, dtype = FALSE)
summary(nim_dtype_false)
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#> -3.4981 -0.6556  0.0223  0.0174  0.6919  3.4019

Created on 2020-09-10 by the reprex package (v0.3.0)

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avalcarcel9 commented 4 years ago

Good to know that the default from oro.nifti::nifti is datatype = 2 or binary data. In the code where I encountered this problem I created the image using the old school approach of setting a mask to a new image and then filling with the numeric values. 

map = mask
# Fill the map with vector values where the mask is 1
map[mask == 1] = vec

So the header transferred with the following:

NIfTI-1 format
  Type            : nifti
  Data Type       : 2 (UINT8)
  Bits per Pixel  : 8

When writing with dtype = FALSE then neurobase::datatyper was not run and neurobase::writenii simply used the header information (which the incorrect data type as binary).

Future me will rely more heavily on the new school neurobase::remake_img which runs neurobase::datatyper to assign the correct header info rather than copying the masks binary header info. If other users encounter this or similar warnings:

Warning message:
In datatyper(average_maps$voxel_data[[1]]) :
  Need to change bitpix and datatype to FLOAT64 due to NAs

They should check that their header Data Type and Bits per Pixel slot values match the image voxel value types.