clustering/pick_best_clustering.py

   1 import fire
   2 import pandas as pd
   3 from pathlib import Path
   4 import shutil
   5
   6 selection_data="/gscratch/comdata/output/reddit_clustering/subreddit_comment_authors-tf_10k_LSI/affinity/selection_data.csv"
   7
   8 outpath = 'test_best.feather'
   9
  10 # pick the best clustering according to silhouette score subject to contraints
  11 def pick_best_clustering(selection_data, output, min_clusters, max_isolates):
  12     df = pd.read_csv(selection_data,index_col=0)
  13     df = df.sort_values("silhouette_score")
  14
  15     # not sure I fixed the bug underlying this fully or not.
  16     df['n_isolates_str'] = df.n_isolates.str.strip("[]")
  17     df['n_isolates_0'] = df['n_isolates_str'].apply(lambda l: len(l) == 0)
  18     df.loc[df.n_isolates_0,'n_isolates'] = 0
  19     df.loc[~df.n_isolates_0,'n_isolates'] = df.loc[~df.n_isolates_0].n_isolates_str.apply(lambda l: int(l))
  20
  21     best_cluster = df[(df.n_isolates <= max_isolates)&(df.n_clusters >= min_clusters)].iloc[df.shape[1]]
  22
  23     print(best_cluster.to_dict())
  24     best_path = Path(best_cluster.outpath) / (str(best_cluster['name']) + ".feather")
  25
  26     shutil.copy(best_path,output)
  27
  28 if __name__ == "__main__":
  29     fire.Fire(pick_best_clustering)