diff imagej2_analyze_skeleton_jython_script.py @ 1:c8bb47840c8d draft default tip

"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/image_processing/imagej2 commit 2afb24f3c81d625312186750a714d702363012b5"
author imgteam
date Mon, 28 Sep 2020 16:51:33 +0000
parents 7baf811ed973
children
line wrap: on
line diff
--- a/imagej2_analyze_skeleton_jython_script.py	Tue Sep 17 16:59:39 2019 -0400
+++ b/imagej2_analyze_skeleton_jython_script.py	Mon Sep 28 16:51:33 2020 +0000
@@ -1,147 +1,148 @@
-import jython_utils
 import math
 import sys
+
 from ij import IJ
 from sc.fiji.analyzeSkeleton 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' ]
+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']
+OPTIONS = ['edm=Overwrite', 'iterations=1', 'count=1']
+
 
-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_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 ):
+
+def get_graph_length(graph):
     length = 0
     for edge in graph.getEdges():
         length = length + edge.getLength()
     return length
 
-def get_points( vertex ):
+
+def get_points(vertex):
     # An array of Point, which has attributes x,y,z.
-    point = vertex.getPoints()[ 0 ]
+    point = vertex.getPoints()[0]
     return point.x, point.y, point.z
-    
-def get_sorted_edge_lengths( graph ):
+
+
+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 )
+    edges = sorted(edges, key=lambda edge: edge.getLength(), reverse=True)
     return edges
 
-def get_sorted_graph_lengths( result ):
+
+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 )
+    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 ] )
+
+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 ] )
+            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' )
+            outf.write('\n')
     if show_detailed_info:
-        outf.write( '# %s\n' % sep.join( DETAIL_NAMES ) )
+        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 ):
+        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 )
+                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 ) )
+                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' )
+                    outf.write('%s %s' % (sep, sep))
+                    outf.write(' %s' % sep)
+                    outf.write(' %s' % sep)
+                    outf.write(' \n')
                 else:
-                    outf.write( '\n' )
+                    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 ] )
+error_log = sys.argv[-8]
+input = sys.argv[-7]
+black_background = sys.argv[-6] == "yes"
+prune_cycle_method = sys.argv[-5]
+prune_ends = sys.argv[-4] == "yes"
+calculate_largest_shortest_path = sys.argv[-3] == "yes"
 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 ]
+    BASIC_NAMES.extend(['Longest Shortest Path', 'spx', 'spy', 'spz'])
+    DETAIL_NAMES.extend([' ', ' ', ' ', ' '])
+show_detailed_info = sys.argv[-2] == "yes"
+output = sys.argv[-1]
 
 # Open the input image file.
-input_image_plus = IJ.openImage( input )
+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 )
+# Set binary options.
+options_list = OPTIONS
+if black_background:
+    options_list.append("black")
+options = " ".join(options_list)
+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", "" )
+# 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 ) )
+# 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)