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
  22 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):
  23     print(n_components,flush=True)
  24
  25
  26     if lsi_model is None:
  27         if type(n_components) == list:
  28             lsi_model = Path(outfile) / f'{max(n_components)}_{term_colname}_LSIMOD.pkl'
  29         else:
  30             lsi_model = Path(outfile) / f'{n_components}_{term_colname}_LSIMOD.pkl'
  31
  32     simfunc = partial(lsi_column_similarities,n_components=n_components,n_iter=n_iter,random_state=random_state,algorithm=algorithm,lsi_model_save=lsi_model)
  33
  34     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)
  35
  36 # change so that these take in an input as an optional argument (for speed, but also for idf).
  37 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):
  38
  39     res =  lsi_similarities(inpath,
  40                             'term',
  41                             outfile,
  42                             min_df,
  43                             max_df,
  44                             included_subreddits,
  45                             topN,
  46                             from_date,
  47                             to_date,
  48                             n_components=n_components,
  49                             algorithm = algorithm
  50                             )
  51     return res
  52
  53 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):
  54     return lsi_similarities(inpath,
  55                             'author',
  56                             outfile,
  57                             min_df,
  58                             max_df,
  59                             included_subreddits,
  60                             topN,
  61                             from_date=from_date,
  62                             to_date=to_date,
  63                             n_components=n_components
  64                                )
  65
  66 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,algorithm='arpack',n_components=300,n_iter=5,random_state=1968):
  67     return lsi_similarities(inpath,
  68                             'author',
  69                             outfile,
  70                             min_df,
  71                             max_df,
  72                             included_subreddits,
  73                             topN,
  74                             from_date=from_date,
  75                             to_date=to_date,
  76                             tfidf_colname='relative_tf',
  77                             n_components=n_components,
  78                             algorithm=algorithm
  79                             )
  80
  81
  82 if __name__ == "__main__":
  83     fire.Fire({'term':term_lsi_similarities,
  84                'author':author_lsi_similarities,
  85                'author-tf':author_tf_similarities})
  86