19 lines
1.0 KiB
Python
19 lines
1.0 KiB
Python
|
from similarities_helper import similarities
|
||
|
|
import numpy as np
|
||
|
|
import fire
|
||
|
|
|
||
|
|
def wang_similarity(mat):
|
||
|
|
non_zeros = (mat != 0).astype(np.float32)
|
||
|
|
intersection = non_zeros.T @ non_zeros
|
||
|
|
return intersection
|
||
|
|
|
||
|
|
|
||
|
|
infile="/gscratch/comdata/output/reddit_similarity/tfidf/comment_authors.parquet"; outfile="/gscratch/comdata/output/reddit_similarity/wang_similarity_10000.feather"; min_df=1; included_subreddits=None; topN=10000; exclude_phrases=False; from_date=None; to_date=None
|
||
|
|
|
||
|
|
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)
|
||
|
|
|
||
|
|
if __name__ == "__main__":
|
||
|
|
fire.Fire(wang_overlaps)
|