Mercurial > repos > imgteam > imagej2_crop

comparison imagej2_analyze_skeleton_jython_script.py @ 0:db3066ae9b09 draft default tip

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/image_processing/imagej2 commit 8f49f3c66b5a1de99ec15e65c2519a56792f1d56
author imgteam
date Wed, 25 Sep 2024 16:28:45 +0000
parents
children
comparison
equal deleted inserted replaced
-1:000000000000 0:db3066ae9b09
1 import math
2 import sys
3
4 from ij import IJ
5 from sc.fiji.analyzeSkeleton import AnalyzeSkeleton_
6
7 BASIC_NAMES = [
8 "Branches",
9 "Junctions",
10 "End-point Voxels",
11 "Junction Voxels",
12 "Slab Voxels",
13 "Average branch length",
14 "Triple Points",
15 "Quadruple Points",
16 "Maximum Branch Length",
17 ]
18 DETAIL_NAMES = [
19 "Skeleton ID",
20 "Branch length",
21 "V1 x",
22 "V1 y",
23 "V1 z",
24 "V2 x",
25 "V2 y",
26 "V2 z",
27 "Euclidean distance",
28 ]
29 OPTIONS = ["edm=Overwrite", "iterations=1", "count=1"]
30
31
32 def get_euclidean_distance(vertex1, vertex2):
33 x1, y1, z1 = get_points(vertex1)
34 x2, y2, z2 = get_points(vertex2)
35 return math.sqrt(
36 math.pow((x2 - x1), 2) + math.pow((y2 - y1), 2) + math.pow((z2 - z1), 2)
37 )
38
39
40 def get_graph_length(graph):
41 length = 0
42 for edge in graph.getEdges():
43 length = length + edge.getLength()
44 return length
45
46
47 def get_points(vertex):
48 # An array of Point, which has attributes x,y,z.
49 point = vertex.getPoints()[0]
50 return point.x, point.y, point.z
51
52
53 def get_sorted_edge_lengths(graph):
54 # Return graph edges sorted from longest to shortest.
55 edges = graph.getEdges()
56 edges = sorted(edges, key=lambda edge: edge.getLength(), reverse=True)
57 return edges
58
59
60 def get_sorted_graph_lengths(result):
61 # Get the separate graphs (skeletons).
62 graphs = result.getGraph()
63 # Sort graphs from longest to shortest.
64 graphs = sorted(graphs, key=lambda g: get_graph_length(g), reverse=True)
65 return graphs
66
67
68 def save(result, output, show_detailed_info, calculate_largest_shortest_path, sep="\t"):
69 num_trees = int(result.getNumOfTrees())
70 outf = open(output, "wb")
71 outf.write("# %s\n" % sep.join(BASIC_NAMES))
72 for index in range(num_trees):
73 outf.write("%d%s" % (result.getBranches()[index], sep))
74 outf.write("%d%s" % (result.getJunctions()[index], sep))
75 outf.write("%d%s" % (result.getEndPoints()[index], sep))
76 outf.write("%d%s" % (result.getJunctionVoxels()[index], sep))
77 outf.write("%d%s" % (result.getSlabs()[index], sep))
78 outf.write("%.3f%s" % (result.getAverageBranchLength()[index], sep))
79 outf.write("%d%s" % (result.getTriples()[index], sep))
80 outf.write("%d%s" % (result.getQuadruples()[index], sep))
81 outf.write("%.3f" % result.getMaximumBranchLength()[index])
82 if calculate_largest_shortest_path:
83 outf.write("%s%.3f%s" % (sep, result.shortestPathList.get(index), sep))
84 outf.write("%d%s" % (result.spStartPosition[index][0], sep))
85 outf.write("%d%s" % (result.spStartPosition[index][1], sep))
86 outf.write("%d\n" % result.spStartPosition[index][2])
87 else:
88 outf.write("\n")
89 if show_detailed_info:
90 outf.write("# %s\n" % sep.join(DETAIL_NAMES))
91 # The following index is a placeholder for the skeleton ID.
92 # The terms "graph" and "skeleton" refer to the same thing.
93 # Also, the SkeletonResult.java code states that the
94 # private Graph[] graph object is an array of graphs (one
95 # per tree).
96 for index, graph in enumerate(get_sorted_graph_lengths(result)):
97 for edge in get_sorted_edge_lengths(graph):
98 vertex1 = edge.getV1()
99 x1, y1, z1 = get_points(vertex1)
100 vertex2 = edge.getV2()
101 x2, y2, z2 = get_points(vertex2)
102 outf.write("%d%s" % (index + 1, sep))
103 outf.write("%.3f%s" % (edge.getLength(), sep))
104 outf.write("%d%s" % (x1, sep))
105 outf.write("%d%s" % (y1, sep))
106 outf.write("%d%s" % (z1, sep))
107 outf.write("%d%s" % (x2, sep))
108 outf.write("%d%s" % (y2, sep))
109 outf.write("%d%s" % (z2, sep))
110 outf.write("%.3f" % get_euclidean_distance(vertex1, vertex2))
111 if calculate_largest_shortest_path:
112 # Keep number of separated items the same for each line.
113 outf.write("%s %s" % (sep, sep))
114 outf.write(" %s" % sep)
115 outf.write(" %s" % sep)
116 outf.write(" \n")
117 else:
118 outf.write("\n")
119 outf.close()
120
121
122 # Fiji Jython interpreter implements Python 2.5 which does not
123 # provide support for argparse.
124 input = sys.argv[-7]
125 black_background = sys.argv[-6] == "yes"
126 prune_cycle_method = sys.argv[-5]
127 prune_ends = sys.argv[-4] == "yes"
128 calculate_largest_shortest_path = sys.argv[-3] == "yes"
129 if calculate_largest_shortest_path:
130 BASIC_NAMES.extend(["Longest Shortest Path", "spx", "spy", "spz"])
131 DETAIL_NAMES.extend([" ", " ", " ", " "])
132 show_detailed_info = sys.argv[-2] == "yes"
133 output = sys.argv[-1]
134
135 # Open the input image file.
136 input_image_plus = IJ.openImage(input)
137
138 # Create a copy of the image.
139 input_image_plus_copy = input_image_plus.duplicate()
140 image_processor_copy = input_image_plus_copy.getProcessor()
141
142 # Set binary options.
143 options_list = OPTIONS
144 if black_background:
145 options_list.append("black")
146 options = " ".join(options_list)
147 IJ.run(input_image_plus_copy, "Options...", options)
148
149 # Convert image to binary if necessary.
150 if not image_processor_copy.isBinary():
151 IJ.run(input_image_plus_copy, "Make Binary", "")
152
153 # Run AnalyzeSkeleton
154 analyze_skeleton = AnalyzeSkeleton_()
155 analyze_skeleton.setup("", input_image_plus_copy)
156 if prune_cycle_method == "none":
157 prune_index = analyze_skeleton.NONE
158 elif prune_cycle_method == "shortest_branch":
159 prune_index = analyze_skeleton.SHORTEST_BRANCH
160 elif prune_cycle_method == "lowest_intensity_voxel":
161 prune_index = analyze_skeleton.LOWEST_INTENSITY_VOXEL
162 elif prune_cycle_method == "lowest_intensity_branch":
163 prune_index = analyze_skeleton.LOWEST_INTENSITY_BRANCH
164 result = analyze_skeleton.run(
165 prune_index,
166 prune_ends,
167 calculate_largest_shortest_path,
168 input_image_plus_copy,
169 True,
170 True,
171 )
172 # Save the results.
173 save(result, output, show_detailed_info, calculate_largest_shortest_path)