Usage: 3dBlurInMask [options] Blurs a dataset spatially inside a mask. That’s all. Experimental.
- -input ddd = This required ‘option’ specifies the dataset
- that will be smoothed and output.
- -FWHM f = Add this amount of smoothness to the dataset.
- **N.B.: This is also a required ‘option’.
- -mask mmm = Mask dataset, if desired. Blurring will
- occur only within the mask. Voxels NOT in the mask will be set to zero in the output.
- -Mmask mmm = Multi-mask dataset – each distinct nonzero
value in dataset ‘mmm’ will be treated as a separate mask for blurring purposes.**N.B.: ‘mmm’ must be byte- or short-valued!
- -automask = Create an automask from the input dataset.
- **N.B.: only 1 masking option can be used!
- -preserve = Normally, voxels not in the mask will be
- set to zero in the output. If you want the original values in the dataset to be preserved in the output, use this option.
- -prefix ppp = Prefix for output dataset will be ‘ppp’.
- **N.B.: Output dataset is always in float format.
-quiet = Don’t be verbose with the progress reports.
- -float = Save dataset as floats, no matter what the
input data type is.
- **N.B.: If the input dataset is unscaled shorts, then
- the default is to save the output in short format as well. In EVERY other case, the program saves the output as floats. Thus, the ONLY purpose of the ‘-float’ option is to force an all-shorts input dataset to be saved as all-floats after blurring.
- If you don’t provide a mask, then all voxels will be included
in the blurring. (But then why are you using this program?)
- Note that voxels inside the mask that are not contiguous with
any other voxels inside the mask will not be modified at all!
- Works iteratively, similarly to 3dBlurToFWHM, but without
the extensive overhead of monitoring the smoothness.
- But this program will be faster than 3dBlurToFWHM, and probably
slower than 3dmerge.
- Since the blurring is done iteratively, rather than all-at-once as
in 3dmerge, the results will be slightly different than 3dmerge’s, even if no mask is used here (3dmerge, of course, doesn’t take a mask).
- If the original FWHM of the dataset was ‘S’ and you input a value
‘F’ with the ‘-FWHM’ option, then the output dataset’s smoothness will be about sqrt(S*S+F*F). The number of iterations will be about (F*F/d*d) where d=grid spacing; this means that a large value of F might take a lot of CPU time!
- The spatial smoothness of a 3D+time dataset can be estimated with a
- command similar to the following:
3dFWHMx -detrend -mask mmm+orig -input ddd+orig
The minimum number of voxels in the mask is 9
Isolated voxels will be removed from the mask!
automatic parallelizer software toolkit, which splits the work across multiple CPUs/cores on the same shared memory computer.
by a network (e.g., OpenMP doesn’t work with ‘cluster’ setups).
your system. You can control this value by setting environment variable OMP_NUM_THREADS to some smaller value (including 1).
using all CPUs available. ++ However, on some systems (such as the NIH Biowulf), it seems to be
necessary to set OMP_NUM_THREADS explicitly, or you only get one CPU.
count, since using more than (say) 16 threads is probably useless.
since OpenMP queries this variable BEFORE the program actually starts. ++ You can’t usefully set this variable in your ~/.afnirc file or on the
command line with the ‘-D’ option.
it was coded. You’ll have to experiment on your own systems!
The number of CPUs on this particular computer system is ...... 16.
The maximum number of CPUs that will be used is now set to .... 7.
++ Compile date = Dec 16 2015