text: #!/usr/bin/env python
  
  from frovedis.exrpc.server import FrovedisServer
  from frovedis.mllib.naive_bayes import MultinomialNB, BernoulliNB
  import sys
  import numpy as np
  import pandas as pd
  
  # Objective: testing with dataframe matrix and numpy label 
  
  # initializing the Frovedis server
  argvs = sys.argv
  argc = len(argvs)
  if (argc < 2):
      print 'Please give frovedis_server calling command as the first argument \n(e.g. "mpirun -np 2 -x /opt/nec/nosupport/frovedis/ve/bin/frovedis_server")'
      quit()
  FrovedisServer.initialize(argvs[1])
  
  mat = pd.DataFrame([[1.0, 0.0, 1.0, 0.0, 0.0, 1.0, 0.0],
                      [0.0, 1.0, 0.0, 1.0, 0.0, 1.0, 0.0],
                      [0.0, 1.0, 0.0, 0.0, 1.0, 0.0, 1.0],
                      [1.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0]])
  lbl = np.array([0.0, 1.0, 1.0, 0.0])
  
  # one-liner prediction
  ret1 = MultinomialNB(alpha=1.0).fit(mat,lbl).predict(mat)
  ret2 = BernoulliNB(alpha=1.0).fit(mat,lbl).predict(mat)
  if (ret1 == lbl).all() and (ret2 == lbl).all(): 
    print("Status: Passed")
  else: 
    print("Status: Failed")
  
  FrovedisServer.shut_down()
  