--- /dev/null
+from pyspark.sql import functions as f
+from pyspark.sql import SparkSession
+from pyspark.sql import Window
+import numpy as np
+import pyarrow
+import pandas as pd
+import fire
+from itertools import islice
+from pathlib import Path
+from similarities_helper import *
+
+
+#tfidf = spark.read.parquet('/gscratch/comdata/users/nathante/subreddit_tfidf_weekly.parquet')
+def cosine_similarities_weekly(tfidf_path, outfile, term_colname, min_df = None, included_subreddits = None, topN = 500):
+ spark = SparkSession.builder.getOrCreate()
+ conf = spark.sparkContext.getConf()
+ print(outfile)
+ tfidf = spark.read.parquet(tfidf_path)
+
+ if included_subreddits is None:
+ included_subreddits = select_topN_subreddits(topN)
+ else:
+ included_subreddits = set(open(included_subreddits))
+
+ print(f"computing weekly similarities for {len(included_subreddits)} subreddits")
+
+ print("creating temporary parquet with matrix indicies")
+ tempdir = prep_tfidf_entries_weekly(tfidf, term_colname, min_df, included_subreddits)
+
+ tfidf = spark.read.parquet(tempdir.name)
+
+ # the ids can change each week.
+ subreddit_names = tfidf.select(['subreddit','subreddit_id_new','week']).distinct().toPandas()
+ subreddit_names = subreddit_names.sort_values("subreddit_id_new")
+ subreddit_names['subreddit_id_new'] = subreddit_names['subreddit_id_new'] - 1
+ spark.stop()
+
+ weeks = list(subreddit_names.week.drop_duplicates())
+ for week in weeks:
+ print(f"loading matrix: {week}")
+ mat = read_tfidf_matrix_weekly(tempdir.name, term_colname, week)
+ print('computing similarities')
+ sims = column_similarities(mat)
+ del mat
+
+ names = subreddit_names.loc[subreddit_names.week == week]
+ sims = pd.DataFrame(sims.todense())
+
+ sims = sims.rename({i: sr for i, sr in enumerate(names.subreddit.values)}, axis=1)
+ sims['subreddit'] = names.subreddit.values
+
+ write_weekly_similarities(outfile, sims, week, names)
+
+
+def author_cosine_similarities_weekly(outfile, min_df=None , included_subreddits=None, topN=500):
+ return cosine_similarities_weekly('/gscratch/comdata/output/reddit_similarity/tfidf_weekly/comment_authors.parquet',
+ outfile,
+ 'author',
+ min_df,
+ included_subreddits,
+ topN)
+
+def term_cosine_similarities_weekly(outfile, min_df=None, included_subreddits=None, topN=500):
+ return cosine_similarities_weekly('/gscratch/comdata/output/reddit_similarity/tfidf_weekly/comment_terms.parquet',
+ outfile,
+ 'term',
+ min_df,
+ included_subreddits,
+ topN)
+
+if __name__ == "__main__":
+ fire.Fire({'author':author_cosine_similarities_weekly,
+ 'term':term_cosine_similarities_weekly})