Mercurial > repos > imgteam > imagej2_bunwarpj_compose_raw_elastic
view imagej2_analyze_skeleton_jython_script.py @ 1:8d357579e407 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/image_processing/imagej2 commit 2afb24f3c81d625312186750a714d702363012b5"
author | imgteam |
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date | Mon, 28 Sep 2020 16:56:53 +0000 |
parents | 1bf7e70e67f9 |
children | 4deffc9540a3 |
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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'] 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_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 = 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 = sys.argv[-2] == "yes" 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() # 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", "") # 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)