A script to create composite edge-enhanced datasets and drive
 the AFNI interface to display the results
The script helps visualize registration results and is an important
 part of assessing image alignmnent

Basic usage:

   @AddEdge base_dset dset1 dset2 ....

   The output is a composite image of each dset nn with the base
   dataset where the composite image is the base dataset with the
   edges of each input dataset and its own edges

   Use without any parameters to drive AFNI's display to show
   the previously computed results from this script

   The script requires all input datasets to share the same grid, so
   a previous resample step may be required. Also it is recommended
   to use skull-stripped input datasets to avoid extraneous and
   extracranial edges.

A typical use may be to compare the effect of alignment
 as in this example for the alignment of anatomical dataset with an
 epi dataset:

   @AddEdge epi_rs+orig. anat_ns+orig anat_ns_al2epi+orig

 Note this particular kind of usage is included in the
   align_epi_anat.py script as the -AddEdge option

To examine results, rerun @AddEdge with -auto

   @AddEdge -auto

Using the typical case example above, the edges from the EPI
 are shown in cyan (light blue); the edges from the anat dataset
 are shown in purple. Overlapping edges are shown in dark purple
 Non-edge areas (most of the volume) are shown in a monochromatic
 amber color scale in the overlay layer of the AFNI image window
 The underlay contains the edge-enhanced anat dataset with edges
 of the anat dataset alone snd no EPI edges
By looking for significant overlap and close alignment of the
 edges of internal structures of the brain, one can assess the
 quality of the alignment.
The script prompts the user in the terminal window to cycle between
 the pre-aligned and post-aligned dataset views. Options are also
 given to save images as jpeg files or to quit the @AddEdge script

The colormap used is the AddEdge color scale which uses a monochrome
 amber for the overlay and purple, cyan and dark purple for edges

Several types of datasets are created by this script, but using the
 @AddEdge script without options is the best way to visualize these
 datasets. The result datasets can be grouped by their suffix as

dset_nn_ec : edge composite image of dataset with its own edges
base_dset_dset_nn_ec : edge composite image of base dataset together
                 with the edges of the input dset_nn dataset
base_dset_e3, dset_nn_e3: edge-only datasets - used in single edge
                 display option

Available options (must precede the dataset names):

 -help         : this help screen
 -examinelist mmmm : use list of paired datasets from file mmmm
               (default is _ae.ExamineList.log)
 -ax_mont 'montformat': axial montage string (default='2x2:24')
 -ax_geom 'geomformat': axial image window geometry
               (default = '777x702+433+334')
 -sag_geom 'geomformat': sagittal image window geometry
               (default = '540x360+4+436')
 -layout mmmm  : use AFNI layout file mmmm for display
 -no_layout    : do not use layout. Use AFNI as it is open.
 -edge_percentile nn: specify edge threshold value (default=30%)
 -single_edge  : show only a single edge in composite image
 -opa          : set opacity of overlay (default=9 opaque)
 -keep_temp    : do not remove temporary files
 -no_deoblique : do not deoblique any data to show overlap
 -auto_record  : save jpeg files of current slices  without prompting
 -auto: Closes old AFNI sessions and relaunch a new one that
        ready to listen to @AddEdge in review mode. This is
        the current default in review mode
 -no_auto: Opposite of -auto