]> code.communitydata.science - cdsc_reddit.git/blobdiff - similarities/wang_similarity.py
script for picking the best clustering given constraints
[cdsc_reddit.git] / similarities / wang_similarity.py
index 99dc3cbcd913c70b1d35b46277e2975cebd3ce1f..452e07ae6a7f60165144417e47ead182d1e77125 100644 (file)
@@ -12,7 +12,7 @@ infile="/gscratch/comdata/output/reddit_similarity/tfidf/comment_authors.parquet
     
 def wang_overlaps(infile, outfile="/gscratch/comdata/output/reddit_similarity/wang_similarity_10000.feather", min_df=1, max_df=None, included_subreddits=None, topN=10000, exclude_phrases=False, from_date=None, to_date=None):
 
-    return similarities(infile=infile, simfunc=wang_similarity, term_colname='author', outfile=outfile, min_df=min_df, max_df=None, included_subreddits=included_subreddits, topN=topN, exclude_phrases=exclude_phrases, from_date=from_date, to_date=to_date)
+    return similarities(infile=infile, simfunc=wang_similarity, term_colname='author', outfile=outfile, min_df=min_df, max_df=max_df, included_subreddits=included_subreddits, topN=topN, exclude_phrases=exclude_phrases, from_date=from_date, to_date=to_date)
 
 if __name__ == "__main__":
     fire.Fire(wang_overlaps)

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