Mercurial > repos > recetox > matchms_metadata_merge
comparison matchms_networking_wrapper.py @ 0:107186a6fcec draft
planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/matchms commit f5f5a8eff32c9b5de792dce99bc3c63dc971e82c
author | recetox |
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date | Thu, 23 Nov 2023 09:56:32 +0000 |
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-1:000000000000 | 0:107186a6fcec |
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1 import argparse | |
2 import sys | |
3 | |
4 from matchms.importing import scores_from_json | |
5 from matchms.networking import SimilarityNetwork | |
6 | |
7 | |
8 def main(argv): | |
9 parser = argparse.ArgumentParser(description="Create network-graph from similarity scores.") | |
10 parser.add_argument("--graph_format", type=str, help="Format of the output similarity network.") | |
11 parser.add_argument("--score_name", type=str, help="Name of the score layer to use for creating the network graph.") | |
12 parser.add_argument("--identifier", type=str, help="Unique metadata identifier of each spectrum from which scores are computed.") | |
13 parser.add_argument("--top_n", type=int, help="Number of highest-score edges to keep.") | |
14 parser.add_argument("--max_links", type=int, help="Maximum number of links to add per node.") | |
15 parser.add_argument("--score_cutoff", type=float, help="Minimum similarity score value to link two spectra.") | |
16 parser.add_argument("--link_method", type=str, help="Method for selecting top N edges for each node.") | |
17 parser.add_argument("--keep_unconnected_nodes", help="Keep unconnected nodes in the network.", action="store_true") | |
18 parser.add_argument("scores", type=str, help="Path to matchms similarity-scores .json file.") | |
19 parser.add_argument("output_filename", type=str, help="Path where to store the output similarity network.") | |
20 args = parser.parse_args() | |
21 | |
22 scores = scores_from_json(args.scores) | |
23 | |
24 network = SimilarityNetwork(identifier_key=args.identifier, | |
25 top_n=args.top_n, | |
26 max_links=args.max_links, | |
27 score_cutoff=args.score_cutoff, | |
28 link_method=args.link_method, | |
29 keep_unconnected_nodes=args.keep_unconnected_nodes) | |
30 score_name = next((s for s in scores.score_names if args.score_name in s and "score" in s), None) | |
31 if score_name is None: | |
32 raise ValueError(f"Could not find any score name containing '{args.score_name}'.") | |
33 | |
34 network.create_network(scores, score_name) | |
35 network.export_to_file(filename=args.output_filename, graph_format=args.graph_format) | |
36 | |
37 return 0 | |
38 | |
39 | |
40 if __name__ == "__main__": | |
41 main(argv=sys.argv[1:]) | |
42 pass |