--- a/jython_script.py	Sun Oct 11 13:29:30 2015 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,147 +0,0 @@
-import jython_utils
-import math
-import sys
-from ij import IJ
-from skeleton_analysis import AnalyzeSkeleton_
-
-BASIC_NAMES = [ 'Branches', 'Junctions', 'End-point Voxels',
-                'Junction Voxels', 'Slab Voxels', 'Average branch length',
-                'Triple Points', 'Quadruple Points', 'Maximum Branch Length' ]
-DETAIL_NAMES = [ 'Skeleton ID', 'Branch length', 'V1 x', 'V1 y', 'V1 z', 'V2 x',
-                 'V2 y', 'V2 z', 'Euclidean distance' ]
-
-def get_euclidean_distance( vertex1, vertex2 ):
-    x1, y1, z1 = get_points( vertex1 )
-    x2, y2, z2 = get_points( vertex2 )
-    return math.sqrt( math.pow( ( x2 - x1 ), 2 ) +
-                      math.pow( ( y2 - y1 ), 2 ) +
-                      math.pow( ( z2 - z1 ), 2 ) )
-
-def get_graph_length( graph ):
-    length = 0
-    for edge in graph.getEdges():
-        length = length + edge.getLength()
-    return length
-
-def get_points( vertex ):
-    # An array of Point, which has attributes x,y,z.
-    point = vertex.getPoints()[ 0 ]
-    return point.x, point.y, point.z
-    
-def get_sorted_edge_lengths( graph ):
-    # Return graph edges sorted from longest to shortest.
-    edges = graph.getEdges()
-    edges = sorted( edges, key=lambda edge: edge.getLength(), reverse=True )
-    return edges
-
-def get_sorted_graph_lengths( result ):
-    # Get the separate graphs (skeletons).
-    graphs = result.getGraph()
-    # Sort graphs from longest to shortest.
-    graphs = sorted( graphs, key=lambda g: get_graph_length( g ), reverse=True )
-    return graphs
-
-def save( result, output, show_detailed_info, calculate_largest_shortest_path, sep='\t' ):
-    num_trees = int( result.getNumOfTrees() )
-    outf = open( output, 'wb' )
-    outf.write( '# %s\n' % sep.join( BASIC_NAMES ) )
-    for index in range( num_trees ):
-        outf.write( '%d%s' % ( result.getBranches()[ index ], sep ) )
-        outf.write( '%d%s' % ( result.getJunctions()[ index ], sep ) )
-        outf.write( '%d%s' % ( result.getEndPoints()[ index ], sep ) )
-        outf.write( '%d%s' % ( result.getJunctionVoxels()[ index ], sep ) )
-        outf.write( '%d%s' % ( result.getSlabs()[ index ], sep ) )
-        outf.write( '%.3f%s' % ( result.getAverageBranchLength()[ index ], sep ) )
-        outf.write( '%d%s' % ( result.getTriples()[ index ], sep ) )
-        outf.write( '%d%s' % ( result.getQuadruples()[ index ], sep ) )
-        outf.write( '%.3f' % result.getMaximumBranchLength()[ index ] )
-        if calculate_largest_shortest_path:
-            outf.write( '%s%.3f%s' % ( sep, result.shortestPathList.get( index ), sep ) )
-            outf.write( '%d%s' % ( result.spStartPosition[ index ][ 0 ], sep ) )
-            outf.write( '%d%s' % ( result.spStartPosition[ index ][ 1 ], sep ) )
-            outf.write( '%d\n' % result.spStartPosition[ index ][ 2 ] )
-        else:
-            outf.write( '\n' )
-    if show_detailed_info:
-        outf.write( '# %s\n' % sep.join( DETAIL_NAMES ) )
-        # The following index is a placeholder for the skeleton ID.
-        # The terms "graph" and "skeleton" refer to the same thing.
-        # Also, the SkeletonResult.java code states that the
-        # private Graph[] graph object is an array of graphs (one
-        # per tree).
-        for index, graph in enumerate( get_sorted_graph_lengths( result ) ):
-            for edge in get_sorted_edge_lengths( graph ):
-                vertex1 = edge.getV1()
-                x1, y1, z1 = get_points( vertex1 )
-                vertex2 = edge.getV2()
-                x2, y2, z2 = get_points( vertex2 )
-                outf.write( '%d%s' % ( index+1, sep ) )
-                outf.write( '%.3f%s' % ( edge.getLength(), sep ) )
-                outf.write( '%d%s' % ( x1, sep ) )
-                outf.write( '%d%s' % ( y1, sep ) )
-                outf.write( '%d%s' % ( z1, sep ) )
-                outf.write( '%d%s' % ( x2, sep ) )
-                outf.write( '%d%s' % ( y2, sep ) )
-                outf.write( '%d%s' % ( z2, sep ) )
-                outf.write( '%.3f' % get_euclidean_distance( vertex1, vertex2 ) )
-                if calculate_largest_shortest_path:
-                    # Keep number of separated items the same for each line.
-                    outf.write( '%s %s' % ( sep, sep ) )
-                    outf.write( ' %s' % sep )
-                    outf.write( ' %s' % sep )
-                    outf.write( ' \n' )
-                else:
-                    outf.write( '\n' )
-    outf.close()
-
-# Fiji Jython interpreter implements Python 2.5 which does not
-# provide support for argparse.
-error_log = sys.argv[ -8 ]
-input = sys.argv[ -7 ]
-black_background = jython_utils.asbool( sys.argv[ -6 ] )
-prune_cycle_method = sys.argv[ -5 ]
-prune_ends = jython_utils.asbool( sys.argv[ -4 ] )
-calculate_largest_shortest_path = jython_utils.asbool( sys.argv[ -3 ] )
-if calculate_largest_shortest_path:
-    BASIC_NAMES.extend( [ 'Longest Shortest Path', 'spx', 'spy', 'spz' ] )
-    DETAIL_NAMES.extend( [ ' ', ' ', ' ', ' ' ] )
-show_detailed_info = jython_utils.asbool( sys.argv[ -2 ] )
-output = sys.argv[ -1 ]
-
-# Open the input image file.
-input_image_plus = IJ.openImage( input )
-
-# Create a copy of the image.
-input_image_plus_copy = input_image_plus.duplicate()
-image_processor_copy = input_image_plus_copy.getProcessor()
-
-try:
-    # Set binary options.
-    options = jython_utils.get_binary_options( black_background=black_background )
-    IJ.run( input_image_plus_copy, "Options...", options )
-
-    # Convert image to binary if necessary.
-    if not image_processor_copy.isBinary():
-        IJ.run( input_image_plus_copy, "Make Binary", "" )
-
-    # Run AnalyzeSkeleton
-    analyze_skeleton = AnalyzeSkeleton_()
-    analyze_skeleton.setup( "", input_image_plus_copy )
-    if prune_cycle_method == 'none':
-        prune_index  = analyze_skeleton.NONE
-    elif prune_cycle_method == 'shortest_branch':
-        prune_index  = analyze_skeleton.SHORTEST_BRANCH
-    elif prune_cycle_method == 'lowest_intensity_voxel':
-        prune_index  = analyze_skeleton.LOWEST_INTENSITY_VOXEL
-    elif prune_cycle_method == 'lowest_intensity_branch':
-        prune_index  = analyze_skeleton.LOWEST_INTENSITY_BRANCH
-    result = analyze_skeleton.run( prune_index,
-                                   prune_ends,
-                                   calculate_largest_shortest_path,
-                                   input_image_plus_copy,
-                                   True,
-                                   True )
-    # Save the results.
-    save( result, output, show_detailed_info, calculate_largest_shortest_path )
-except Exception, e:
-    jython_utils.handle_error( error_log, str( e ) )