3 from pathlib import Path
 
   4 from similarities_helper import similarities, column_similarities
 
   5 from functools import partial
 
   7 def cosine_similarities(infile, term_colname, outfile, min_df=None, max_df=None, included_subreddits=None, topN=500, exclude_phrases=False, from_date=None, to_date=None, tfidf_colname='tf_idf'):
 
   9     return similarities(infile=infile, simfunc=column_similarities, term_colname=term_colname, 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, tfidf_colname=tfidf_colname)
 
  11 # change so that these take in an input as an optional argument (for speed, but also for idf).
 
  12 def term_cosine_similarities(outfile, min_df=None, max_df=None, included_subreddits=None, topN=500, exclude_phrases=False, from_date=None, to_date=None):
 
  14     return cosine_similarities('/gscratch/comdata/output/reddit_similarity/tfidf/comment_terms_100k.parquet',
 
  26 def author_cosine_similarities(outfile, min_df=2, max_df=None, included_subreddits=None, topN=10000, from_date=None, to_date=None):
 
  27     return cosine_similarities('/gscratch/comdata/output/reddit_similarity/tfidf/comment_authors_100k.parquet',
 
  34                                exclude_phrases=False,
 
  39 def author_tf_similarities(outfile, min_df=2, max_df=None, included_subreddits=None, topN=10000, from_date=None, to_date=None):
 
  40     return cosine_similarities('/gscratch/comdata/output/reddit_similarity/tfidf/comment_authors_100k.parquet',
 
  47                                exclude_phrases=False,
 
  50                                tfidf_colname='relative_tf'
 
  54 if __name__ == "__main__":
 
  55     fire.Fire({'term':term_cosine_similarities,
 
  56                'author':author_cosine_similarities,
 
  57                'author-tf':author_tf_similarities})