annotate matchms_networking_wrapper.py @ 9:bd6a398a05e9 draft

planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/matchms commit 0f836e483fe3727580d6d1239135203b20812504
author recetox
date Wed, 22 Nov 2023 14:24:37 +0000
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e4ec3592507f planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/matchms commit f7bab98744e338dcdbdc9cf6f9de287632c76ea2
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1 import argparse
e4ec3592507f planemo upload for repository https://github.com/RECETOX/galaxytools/tree/master/tools/matchms commit f7bab98744e338dcdbdc9cf6f9de287632c76ea2
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2 import sys
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4 from matchms.importing import scores_from_json
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5 from matchms.networking import SimilarityNetwork
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8 def main(argv):
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9 parser = argparse.ArgumentParser(description="Create network-graph from similarity scores.")
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10 parser.add_argument("--graph_format", type=str, help="Format of the output similarity network.")
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11 parser.add_argument("--score_name", type=str, help="Name of the score layer to use for creating the network graph.")
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12 parser.add_argument("--identifier", type=str, help="Unique metadata identifier of each spectrum from which scores are computed.")
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13 parser.add_argument("--top_n", type=int, help="Number of highest-score edges to keep.")
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14 parser.add_argument("--max_links", type=int, help="Maximum number of links to add per node.")
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15 parser.add_argument("--score_cutoff", type=float, help="Minimum similarity score value to link two spectra.")
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16 parser.add_argument("--link_method", type=str, help="Method for selecting top N edges for each node.")
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17 parser.add_argument("--keep_unconnected_nodes", help="Keep unconnected nodes in the network.", action="store_true")
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18 parser.add_argument("scores", type=str, help="Path to matchms similarity-scores .json file.")
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19 parser.add_argument("output_filename", type=str, help="Path where to store the output similarity network.")
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20 args = parser.parse_args()
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22 scores = scores_from_json(args.scores)
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24 network = SimilarityNetwork(identifier_key=args.identifier,
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25 top_n=args.top_n,
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26 max_links=args.max_links,
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27 score_cutoff=args.score_cutoff,
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28 link_method=args.link_method,
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29 keep_unconnected_nodes=args.keep_unconnected_nodes)
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30 score_name = next((s for s in scores.score_names if args.score_name in s and "score" in s), None)
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31 if score_name is None:
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32 raise ValueError(f"Could not find any score name containing '{args.score_name}'.")
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34 network.create_network(scores, score_name)
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35 network.export_to_file(filename=args.output_filename, graph_format=args.graph_format)
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37 return 0
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40 if __name__ == "__main__":
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41 main(argv=sys.argv[1:])
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42 pass