similarities/lsi_similarities.py

   1 import pandas as pd
   2 import fire
   3 from pathlib import Path
   4 from similarities_helper import *
   5 #from similarities_helper import similarities, lsi_column_similarities
   6 from functools import partial
   7
   8 inpath = "/gscratch/comdata/users/nathante/competitive_exclusion_reddit/data/tfidf/comment_terms_compex.parquet/"
   9 term_colname='term'
  10 outfile='/gscratch/comdata/users/nathante/competitive_exclusion_reddit/data/similarity/comment_terms_compex_LSI'
  11 n_components=[10,50,100]
  12 included_subreddits="/gscratch/comdata/users/nathante/competitive_exclusion_reddit/data/included_subreddits.txt"
  13 n_iter=5
  14 random_state=1968
  15 algorithm='arpack'
  16 topN = None
  17 from_date=None
  18 to_date=None
  19 min_df=None
  20 max_df=None
  21 def lsi_similarities(inpath, term_colname, outfile, min_df=None, max_df=None, included_subreddits=None, topN=None, from_date=None, to_date=None, tfidf_colname='tf_idf',n_components=100,n_iter=5,random_state=1968,algorithm='arpack',lsi_model=None):
  22     print(n_components,flush=True)
  23
  24
  25     if lsi_model is None:
  26         if type(n_components) == list:
  27             lsi_model = Path(outfile) / f'{max(n_components)}_{term_colname}_LSIMOD.pkl'
  28         else:
  29             lsi_model = Path(outfile) / f'{n_components}_{term_colname}_LSIMOD.pkl'
  30
  31     simfunc = partial(lsi_column_similarities,n_components=n_components,n_iter=n_iter,random_state=random_state,algorithm=algorithm,lsi_model_save=lsi_model)
  32
  33     return similarities(inpath=inpath, simfunc=simfunc, term_colname=term_colname, outfile=outfile, min_df=min_df, max_df=max_df, included_subreddits=included_subreddits, topN=topN, from_date=from_date, to_date=to_date, tfidf_colname=tfidf_colname)
  34
  35 # change so that these take in an input as an optional argument (for speed, but also for idf).
  36 def term_lsi_similarities(inpath='/gscratch/comdata/output/reddit_similarity/tfidf/comment_terms_100k.parquet',outfile=None, min_df=None, max_df=None, included_subreddits=None, topN=None, from_date=None, to_date=None, algorithm='arpack', n_components=300,n_iter=5,random_state=1968):
  37
  38     res =  lsi_similarities(inpath,
  39                             'term',
  40                             outfile,
  41                             min_df,
  42                             max_df,
  43                             included_subreddits,
  44                             topN,
  45                             from_date,
  46                             to_date,
  47                             n_components=n_components,
  48                             algorithm = algorithm
  49                             )
  50     return res
  51
  52 def author_lsi_similarities(inpath='/gscratch/comdata/output/reddit_similarity/tfidf/comment_authors_100k.parquet',outfile=None, min_df=2, max_df=None, included_subreddits=None, topN=None, from_date=None, to_date=None,algorithm='arpack',n_components=300,n_iter=5,random_state=1968):
  53     return lsi_similarities(inpath,
  54                             'author',
  55                             outfile,
  56                             min_df,
  57                             max_df,
  58                             included_subreddits,
  59                             topN,
  60                             from_date=from_date,
  61                             to_date=to_date,
  62                             n_components=n_components
  63                                )
  64
  65 def author_tf_similarities(inpath='/gscratch/comdata/output/reddit_similarity/tfidf/comment_authors_100k.parquet',outfile=None, min_df=2, max_df=None, included_subreddits=None, topN=None, from_date=None, to_date=None,n_components=300,n_iter=5,random_state=1968):
  66     return lsi_similarities(inpath,
  67                             'author',
  68                             outfile,
  69                             min_df,
  70                             max_df,
  71                             included_subreddits,
  72                             topN,
  73                             from_date=from_date,
  74                             to_date=to_date,
  75                             tfidf_colname='relative_tf',
  76                             n_components=n_components,
  77                             algorithm=algorithm
  78                             )
  79
  80
  81 if __name__ == "__main__":
  82     fire.Fire({'term':term_lsi_similarities,
  83                'author':author_lsi_similarities,
  84                'author-tf':author_tf_similarities})
  85