Multiply AFNI datasets slice-by-slice as matrices.

If dataset A has Ra rows and Ca columns (per slice), and dataset B has
Rb rows and Cb columns (per slice), multiply each slice pair as matrices
to obtain a dataset with Ra rows and Cb columns.  Here Ca must equal Rb
and the number of slices must be equal.

In practice the first dataset will probably be a transformation matrix
(or a sequence of them) while the second dataset might just be an image.
For this reason, the output dataset will be based on inputB.


    3dmatmult -inputA matrix+orig -inputB image+orig -prefix transformed

    3dmatmult -inputA matrix+orig -inputB image+orig  \
              -prefix transformed -datum float -verb 2

informational command arguments (execute option and quit):

    -help                   : show this help
    -hist                   : show program history
    -ver                    : show program version

required command arguments:

    -inputA DSET_A          : specify first (matrix) dataset

        The slices of this dataset might be transformation matrices.

    -inputB DSET_B          : specify second (matrix) dataset

        This dataset might be any image.

    -prefix PREFIX          : specify output dataset prefix

        This will be the name of the product (output) dataset.

optional command arguments:

    -datum TYPE             : specify output data type

        Valid TYPEs are 'byte', 'short' and 'float'.  The default is
        that of the inputB dataset.

    -verb LEVEL             : specify verbosity level

        The default level is 1, while 0 is considered 'quiet'.

* If you need to re-orient a 3D dataset so that the rows, columns
  and slices are correct for 3dmatmult, you can use the one of the
  programs 3daxialize or 3dresample for this purpose.

* To multiply a constant matrix into a vector at each voxel, the
  program 3dmatcalc is the proper tool.

R. Reynolds    (requested by W. Gaggl)

3dmatmult version 0.0, 29 September 2008
compiled: Jan 17 2020