--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/matchms_networking_wrapper.py	Tue Oct 18 13:23:28 2022 +0000
@@ -0,0 +1,38 @@
+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("--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)
+
+    network.create_network(scores)
+    network.export_to_file(filename=args.output_filename, graph_format=args.graph_format)
+
+    return 0
+
+
+if __name__ == "__main__":
+    main(argv=sys.argv[1:])
+    pass