Use Latent semantic indexing and hdbscan

[cdsc_reddit.git] / similarities / cosine_similarities.py

diff --git a/similarities/cosine_similarities.py b/similarities/cosine_similarities.py
index 95fa1fbf6ca70111838a05b4272fb39e1b7464bf..0c9c986c3e60ff28224f1eaed0072453af5d2948 100644 (file)
--- a/similarities/cosine_similarities.py
+++ b/similarities/cosine_similarities.py
@@ -2,14 +2,16 @@ import pandas as pd
 import fire
 from pathlib import Path
 from similarities_helper import similarities, column_similarities
+from functools import partial
 
 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'):
 
     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)
 
-
+# change so that these take in an input as an optional argument (for speed, but also for idf).
 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):
-    return cosine_similarities('/gscratch/comdata/output/reddit_similarity/tfidf/comment_terms.parquet',
+
+    return cosine_similarities('/gscratch/comdata/output/reddit_similarity/tfidf/comment_terms_100k.parquet',
                                'term',
                                outfile,
                                min_df,
@@ -22,7 +24,7 @@ def term_cosine_similarities(outfile, min_df=None, max_df=None, included_subredd
                                )
 
 def author_cosine_similarities(outfile, min_df=2, max_df=None, included_subreddits=None, topN=10000, from_date=None, to_date=None):
-    return cosine_similarities('/gscratch/comdata/output/reddit_similarity/tfidf/comment_authors.parquet',
+    return cosine_similarities('/gscratch/comdata/output/reddit_similarity/tfidf/comment_authors_100k.parquet',
                                'author',
                                outfile,
                                min_df,
@@ -35,7 +37,7 @@ def author_cosine_similarities(outfile, min_df=2, max_df=None, included_subreddi
                                )
 
 def author_tf_similarities(outfile, min_df=2, max_df=None, included_subreddits=None, topN=10000, from_date=None, to_date=None):
-    return cosine_similarities('/gscratch/comdata/output/reddit_similarity/tfidf/comment_authors.parquet',
+    return cosine_similarities('/gscratch/comdata/output/reddit_similarity/tfidf/comment_authors_100k.parquet',
                                'author',
                                outfile,
                                min_df,