clustering/pick_best_clustering.py

   1 #!/usr/bin/env python3
   2 import fire
   3 import pandas as pd
   4 from pathlib import Path
   5 import shutil
   6 selection_data="/gscratch/comdata/users/nathante/competitive_exclusion_reddit/data/clustering/comment_authors_compex_LSI/selection_data.csv"
   7
   8 outpath = 'test_best.feather'
   9 min_clusters=50; max_isolates=7500; min_cluster_size=2
  10
  11 # pick the best clustering according to silhouette score subject to contraints
  12 def pick_best_clustering(selection_data, output, min_clusters, max_isolates, min_cluster_size):
  13     df = pd.read_csv(selection_data,index_col=0)
  14     df = df.sort_values("silhouette_score",ascending=False)
  15
  16     # not sure I fixed the bug underlying this fully or not.
  17     df['n_isolates_str'] = df.n_isolates.str.strip("[]")
  18     df['n_isolates_0'] = df['n_isolates_str'].apply(lambda l: len(l) == 0)
  19     df.loc[df.n_isolates_0,'n_isolates'] = 0
  20     df.loc[~df.n_isolates_0,'n_isolates'] = df.loc[~df.n_isolates_0].n_isolates_str.apply(lambda l: int(l))
  21
  22     best_cluster = df[(df.n_isolates <= max_isolates)&(df.n_clusters >= min_clusters)&(df.min_cluster_size==min_cluster_size)]
  23
  24     best_cluster = best_cluster.iloc[0]
  25
  26     best_lsi_dimensions = best_cluster.lsi_dimensions
  27     print(best_cluster.to_dict())
  28     best_path = Path(best_cluster.outpath) / (str(best_cluster['name']) + ".feather")
  29     shutil.copy(best_path,output)
  30     print(f"lsi dimensions:{best_lsi_dimensions}")
  31
  32 if __name__ == "__main__":
  33     fire.Fire(pick_best_clustering)