annotate imagej2_analyze_skeleton_jython_script.py @ 1:e9243cad1d67 draft

"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/image_processing/imagej2 commit 2afb24f3c81d625312186750a714d702363012b5"
author imgteam
date Mon, 28 Sep 2020 16:40:20 +0000
parents ab54024c0a88
children 0a0d2dfd17e0
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1 import math
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2 import sys
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4 from ij import IJ
ab54024c0a88 "planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/image_processing/imagej2 commit b08f0e6d1546caaf627b21f8c94044285d5d5b9c-dirty"
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5 from sc.fiji.analyzeSkeleton import AnalyzeSkeleton_
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7 BASIC_NAMES = ['Branches', 'Junctions', 'End-point Voxels',
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8 'Junction Voxels', 'Slab Voxels', 'Average branch length',
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9 'Triple Points', 'Quadruple Points', 'Maximum Branch Length']
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10 DETAIL_NAMES = ['Skeleton ID', 'Branch length', 'V1 x', 'V1 y', 'V1 z', 'V2 x',
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11 'V2 y', 'V2 z', 'Euclidean distance']
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12 OPTIONS = ['edm=Overwrite', 'iterations=1', 'count=1']
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15 def get_euclidean_distance(vertex1, vertex2):
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16 x1, y1, z1 = get_points(vertex1)
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17 x2, y2, z2 = get_points(vertex2)
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18 return math.sqrt(math.pow((x2 - x1), 2) + math.pow((y2 - y1), 2) + math.pow((z2 - z1), 2))
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21 def get_graph_length(graph):
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22 length = 0
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23 for edge in graph.getEdges():
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24 length = length + edge.getLength()
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25 return length
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28 def get_points(vertex):
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29 # An array of Point, which has attributes x,y,z.
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30 point = vertex.getPoints()[0]
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31 return point.x, point.y, point.z
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34 def get_sorted_edge_lengths(graph):
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35 # Return graph edges sorted from longest to shortest.
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36 edges = graph.getEdges()
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37 edges = sorted(edges, key=lambda edge: edge.getLength(), reverse=True)
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38 return edges
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39
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41 def get_sorted_graph_lengths(result):
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42 # Get the separate graphs (skeletons).
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43 graphs = result.getGraph()
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44 # Sort graphs from longest to shortest.
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45 graphs = sorted(graphs, key=lambda g: get_graph_length(g), reverse=True)
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46 return graphs
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47
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49 def save(result, output, show_detailed_info, calculate_largest_shortest_path, sep='\t'):
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50 num_trees = int(result.getNumOfTrees())
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51 outf = open(output, 'wb')
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52 outf.write('# %s\n' % sep.join(BASIC_NAMES))
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53 for index in range(num_trees):
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54 outf.write('%d%s' % (result.getBranches()[index], sep))
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55 outf.write('%d%s' % (result.getJunctions()[index], sep))
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56 outf.write('%d%s' % (result.getEndPoints()[index], sep))
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57 outf.write('%d%s' % (result.getJunctionVoxels()[index], sep))
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58 outf.write('%d%s' % (result.getSlabs()[index], sep))
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59 outf.write('%.3f%s' % (result.getAverageBranchLength()[index], sep))
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60 outf.write('%d%s' % (result.getTriples()[index], sep))
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61 outf.write('%d%s' % (result.getQuadruples()[index], sep))
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62 outf.write('%.3f' % result.getMaximumBranchLength()[index])
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63 if calculate_largest_shortest_path:
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64 outf.write('%s%.3f%s' % (sep, result.shortestPathList.get(index), sep))
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65 outf.write('%d%s' % (result.spStartPosition[index][0], sep))
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66 outf.write('%d%s' % (result.spStartPosition[index][1], sep))
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67 outf.write('%d\n' % result.spStartPosition[index][2])
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68 else:
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69 outf.write('\n')
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70 if show_detailed_info:
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71 outf.write('# %s\n' % sep.join(DETAIL_NAMES))
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72 # The following index is a placeholder for the skeleton ID.
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73 # The terms "graph" and "skeleton" refer to the same thing.
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74 # Also, the SkeletonResult.java code states that the
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75 # private Graph[] graph object is an array of graphs (one
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76 # per tree).
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77 for index, graph in enumerate(get_sorted_graph_lengths(result)):
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78 for edge in get_sorted_edge_lengths(graph):
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79 vertex1 = edge.getV1()
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80 x1, y1, z1 = get_points(vertex1)
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81 vertex2 = edge.getV2()
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82 x2, y2, z2 = get_points(vertex2)
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83 outf.write('%d%s' % (index + 1, sep))
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84 outf.write('%.3f%s' % (edge.getLength(), sep))
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85 outf.write('%d%s' % (x1, sep))
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86 outf.write('%d%s' % (y1, sep))
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87 outf.write('%d%s' % (z1, sep))
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88 outf.write('%d%s' % (x2, sep))
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89 outf.write('%d%s' % (y2, sep))
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90 outf.write('%d%s' % (z2, sep))
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91 outf.write('%.3f' % get_euclidean_distance(vertex1, vertex2))
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92 if calculate_largest_shortest_path:
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93 # Keep number of separated items the same for each line.
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94 outf.write('%s %s' % (sep, sep))
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95 outf.write(' %s' % sep)
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96 outf.write(' %s' % sep)
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97 outf.write(' \n')
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98 else:
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99 outf.write('\n')
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100 outf.close()
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101
1
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102
0
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103 # Fiji Jython interpreter implements Python 2.5 which does not
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104 # provide support for argparse.
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105 error_log = sys.argv[-8]
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106 input = sys.argv[-7]
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107 black_background = sys.argv[-6] == "yes"
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108 prune_cycle_method = sys.argv[-5]
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109 prune_ends = sys.argv[-4] == "yes"
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110 calculate_largest_shortest_path = sys.argv[-3] == "yes"
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111 if calculate_largest_shortest_path:
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112 BASIC_NAMES.extend(['Longest Shortest Path', 'spx', 'spy', 'spz'])
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113 DETAIL_NAMES.extend([' ', ' ', ' ', ' '])
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114 show_detailed_info = sys.argv[-2] == "yes"
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115 output = sys.argv[-1]
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116
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117 # Open the input image file.
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118 input_image_plus = IJ.openImage(input)
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119
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120 # Create a copy of the image.
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121 input_image_plus_copy = input_image_plus.duplicate()
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122 image_processor_copy = input_image_plus_copy.getProcessor()
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123
1
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124 # Set binary options.
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125 options_list = OPTIONS
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126 if black_background:
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127 options_list.append("black")
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128 options = " ".join(options_list)
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129 IJ.run(input_image_plus_copy, "Options...", options)
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130
1
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131 # Convert image to binary if necessary.
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132 if not image_processor_copy.isBinary():
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133 IJ.run(input_image_plus_copy, "Make Binary", "")
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134
1
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135 # Run AnalyzeSkeleton
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136 analyze_skeleton = AnalyzeSkeleton_()
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137 analyze_skeleton.setup("", input_image_plus_copy)
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138 if prune_cycle_method == 'none':
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139 prune_index = analyze_skeleton.NONE
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140 elif prune_cycle_method == 'shortest_branch':
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141 prune_index = analyze_skeleton.SHORTEST_BRANCH
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142 elif prune_cycle_method == 'lowest_intensity_voxel':
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143 prune_index = analyze_skeleton.LOWEST_INTENSITY_VOXEL
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144 elif prune_cycle_method == 'lowest_intensity_branch':
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145 prune_index = analyze_skeleton.LOWEST_INTENSITY_BRANCH
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146 result = analyze_skeleton.run(prune_index, prune_ends, calculate_largest_shortest_path, input_image_plus_copy, True, True)
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147 # Save the results.
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148 save(result, output, show_detailed_info, calculate_largest_shortest_path)