add note to try other tf normalization strategies.

[cdsc_reddit.git] / similarities / similarities_helper.py

diff --git a/similarities/similarities_helper.py b/similarities/similarities_helper.py
index 9e33c9d105c4c4190ce47c84cf56be3b753326b0..3ace8f29f3922838009adfb4dccf77e5f03b1e34 100644 (file)
--- a/similarities/similarities_helper.py
+++ b/similarities/similarities_helper.py
@@ -60,7 +60,7 @@ def reindex_tfidf(infile, term_colname, min_df=None, max_df=None, included_subre
     if included_subreddits is None:
         included_subreddits = select_topN_subreddits(topN)
     else:
-        included_subreddits = set(open(included_subreddits))
+        included_subreddits = set(map(str.strip,map(str.lower,open(included_subreddits))))
 
     if exclude_phrases == True:
         tfidf = tfidf.filter(~f.col(term_colname).contains("_"))
@@ -89,7 +89,8 @@ def similarities(infile, simfunc, term_colname, outfile, min_df=None, max_df=Non
     print("loading matrix")
     #    mat = read_tfidf_matrix("term_tfidf_entries7ejhvnvl.parquet", term_colname)
     mat = read_tfidf_matrix(tempdir.name, term_colname, tfidf_colname)
-    print('computing similarities')
+    print(f'computing similarities on mat. mat.shape:{mat.shape}')
+    print(f"size of mat is:{mat.data.nbytes}")
     sims = simfunc(mat)
     del mat
 
@@ -387,7 +388,7 @@ def build_tfidf_dataset(df, include_subs, term_colname, tf_family=tf_weight.Norm
 
     return df
 
-def select_topN_subreddits(topN, path="/gscratch/comdata/output/reddit_similarity/subreddits_by_num_comments_nonswf.csv"):
+def select_topN_subreddits(topN, path="/gscratch/comdata/output/reddit_similarity/subreddits_by_num_comments_nonsfw.csv"):
     rankdf = pd.read_csv(path)
     included_subreddits = set(rankdf.loc[rankdf.comments_rank <= topN,'subreddit'].values)
     return included_subreddits