old_contents: """The script to calc cluster center and store in json file
  """
  
  import numpy as np
  import sklearn.preprocessing as sklpp
  import pandas as pd
  import pymysql
  
  import os
  import json
  from pathlib import Path
  import time
  
  import Cluster_determ as cd
  
  __location__ = os.path.join(os.getcwd(), os.path.dirname(os.path.realpath(__file__)))
  __path__ = Path(__location__)
  
  if __name__ == '__main__':
      with open(os.path.join(__location__, "config.json"), 'r') as config:
          conf = json.load(config)
          HOST = conf['host']
          USER = conf['user']
          PASS = conf['pass']
          DATABASE = conf['database']
          CHARSET = conf['charset']
  
      connection = pymysql.connect(host=HOST, user=USER, password=PASS, db=DATABASE, charset=CHARSET, cursorclass=pymysql.cursors.DictCursor)
  
      print("Loding data from SQL…")
      sql = "SELECT usr_count_json, x, y FROM `loc_week_count_reshape`"
      data = pd.read_sql(sql, connection)
      print("Data loded.")
  
      print("Building data structure…")
      dset = {}
      for i in range(len(data)):
          row = data.iloc[i]
          dset[(row.x, row.y)] = json.loads(row.usr_count_json)
      dframe = pd.DataFrame.from_dict(dset, orient='index')
      print("Data structure builded.")
  
      print("Preprocessing data…")
      X = sklpp.maxabs_scale(np.matrix(dframe, dtype=np.double), copy=False)
      print("Data preprocessed.")
  
      print("Calculating cluster centers…")
      t0 = time.time()
      result = cd.method_1994(X, sample=1000)
      t1 = time.time()
      print("Cluster centers calculated.")
      print("Total time: %.2f" % (t1 - t0))
  
      print("Dumping result…")
      with open(os.path.join(__location__, 'cluster_centers.json'), 'w', encoding='utf_8') as f:
          json.dump(result, f, indent=4)
      print("Result dumped.")
  
      connection.close()
  
new_contents: """The script to calc cluster center and store in json file
  """
  
  import numpy as np
  import sklearn.preprocessing as sklpp
  import pandas as pd
  import pymysql
  
  import os
  import json
  from pathlib import Path
  import time
  
  import Cluster_determ as cd
  
  __location__ = os.path.join(os.getcwd(), os.path.dirname(os.path.realpath(__file__)))
  __path__ = Path(__location__)
  
  if __name__ == '__main__':
      with open(os.path.join(__location__, "config.json"), 'r') as config:
          conf = json.load(config)
          HOST = conf['host']
          USER = conf['user']
          PASS = conf['pass']
          DATABASE = conf['database']
          CHARSET = conf['charset']
  
      connection = pymysql.connect(host=HOST, user=USER, password=PASS, db=DATABASE, charset=CHARSET, cursorclass=pymysql.cursors.DictCursor)
  
      print("Loding data from SQL…")
      sql = "SELECT usr_count_json, x, y FROM `loc_week_count_reshape`"
      data = pd.read_sql(sql, connection)
      print("Data loded.")
  
      print("Building data structure…")
      dset = {}
      for i in range(len(data)):
          row = data.iloc[i]
          dset[(row.x, row.y)] = json.loads(row.usr_count_json)
      dframe = pd.DataFrame.from_dict(dset, orient='index')
      print("Data structure builded.")
  
      print("Preprocessing data…")
      X = sklpp.maxabs_scale(np.matrix(dframe, dtype=np.double), copy=False)
      print("Data preprocessed.")
  
      print("Calculating cluster centers…")
      t0 = time.time()
      result = cd.method_1994(X)
      t1 = time.time()
      print("Cluster centers calculated.")
      print("Total time: %.2f" % (t1 - t0))
  
      print("Dumping result…")
      with open(os.path.join(__location__, 'cluster_centers.json'), 'w', encoding='utf_8') as f:
          json.dump(result, f, indent=4)
      print("Result dumped.")
  
      connection.close()
  
subject: remove sample