Usage: 3dMSE [options] dset
  Computes voxelwise multi-scale entropy.
  -polort m = Remove polynomial trend of order 'm', for m=-1..3.
               [default is m=1; removal is by least squares].
               Using m=-1 means no detrending; this is only useful
               for data/information that has been pre-processed.

  -autoclip = Clip off low-intensity regions in the dataset,
  -automask =  so that the correlation is only computed between
               high-intensity (presumably brain) voxels.  The
               mask is determined the same way that 3dAutomask works.

  -mask mmm = Mask to define 'in-brain' voxels. Reducing the number
               the number of voxels included in the calculation will
               significantly speedup the calculation. Consider using
               a mask to constrain the calculations to the grey matter
               rather than the whole brain. This is also preferable
               to using -autoclip or -automask.

  -prefix p = Save output into dataset with prefix 'p', this file will
               contain bricks for both 'weighted' or 'degree' centrality
               [default prefix is 'MSE'].

  -scales N = The number of scales to be used in the calculation.
               [default is 5].

  -entwin w = The window size used in the calculation.
               [default is 2].

  -rthresh r = The radius threshold for determining if values are the
                same in the SampleEn calculation, in fractions of the
                standard deviation.
               [default is .5].

 * The output dataset is a bucket type of floats.

-- RWCox - 31 Jan 2002 and 16 Jul 2010
-- Cameron Craddock - 26 Sept 2015

* This binary version of 3dMSE is compiled using OpenMP, a semi-
   automatic parallelizer software toolkit, which splits the work across
   multiple CPUs/cores on the same shared memory computer.
* OpenMP is NOT like MPI -- it does not work with CPUs connected only
   by a network (e.g., OpenMP doesn't work across cluster nodes).
* For some implementation and compilation details, please see
* The number of CPU threads used will default to the maximum number on
   your system. You can control this value by setting environment variable
   OMP_NUM_THREADS to some smaller value (including 1).
* Un-setting OMP_NUM_THREADS resets OpenMP back to its default state of
   using all CPUs available.
   ++ However, on some systems, it seems to be necessary to set variable
      OMP_NUM_THREADS explicitly, or you only get one CPU.
   ++ On other systems with many CPUS, you probably want to limit the CPU
      count, since using more than (say) 16 threads is probably useless.
* You must set OMP_NUM_THREADS in the shell BEFORE running the program,
   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.
* How many threads are useful? That varies with the program, and how well
   it was coded. You'll have to experiment on your own systems!
* The number of CPUs on this particular computer system is ...... 2.
* The maximum number of CPUs that will be used is now set to .... 2.

++ Compile date = May 27 2024 {AFNI_24.1.15:linux_ubuntu_16_64}