Mercurial > repos > recetox > matchms_fingerprint_similarity
view matchms_networking_wrapper.py @ 8:f87b1c271012 draft
planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/matchms commit 98223db312c30b0e121a1422a9534a3db3fbf0c0
author | recetox |
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date | Thu, 14 Dec 2023 13:48:50 +0000 |
parents | 9f846954928f |
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import argparse import sys from matchms.importing import scores_from_json from matchms.networking import SimilarityNetwork def main(argv): parser = argparse.ArgumentParser(description="Create network-graph from similarity scores.") parser.add_argument("--graph_format", type=str, help="Format of the output similarity network.") parser.add_argument("--score_name", type=str, help="Name of the score layer to use for creating the network graph.") parser.add_argument("--identifier", type=str, help="Unique metadata identifier of each spectrum from which scores are computed.") parser.add_argument("--top_n", type=int, help="Number of highest-score edges to keep.") parser.add_argument("--max_links", type=int, help="Maximum number of links to add per node.") parser.add_argument("--score_cutoff", type=float, help="Minimum similarity score value to link two spectra.") parser.add_argument("--link_method", type=str, help="Method for selecting top N edges for each node.") parser.add_argument("--keep_unconnected_nodes", help="Keep unconnected nodes in the network.", action="store_true") parser.add_argument("scores", type=str, help="Path to matchms similarity-scores .json file.") parser.add_argument("output_filename", type=str, help="Path where to store the output similarity network.") args = parser.parse_args() scores = scores_from_json(args.scores) network = SimilarityNetwork(identifier_key=args.identifier, top_n=args.top_n, max_links=args.max_links, score_cutoff=args.score_cutoff, link_method=args.link_method, keep_unconnected_nodes=args.keep_unconnected_nodes) score_name = next((s for s in scores.score_names if args.score_name in s and "score" in s), None) if score_name is None: raise ValueError(f"Could not find any score name containing '{args.score_name}'.") network.create_network(scores, score_name) network.export_to_file(filename=args.output_filename, graph_format=args.graph_format) return 0 if __name__ == "__main__": main(argv=sys.argv[1:]) pass