content: #! /usr/bin/env python
  # Copyright(c) 2014, The mtSet developers (Francesco Paolo Casale, Barbara Rakitsch, Oliver Stegle)
  # All rights reserved.
  
  from optparse import OptionParser
  from limix.mtSet.core.iset_utils import calc_emp_pv_eff
  import pandas as pd
  import glob
  import os
  import time
  import sys
  
  def entry_point():
  
      parser = OptionParser()
      parser.add_option("--resdir", dest='resdir', type=str, default='./')
      parser.add_option("--outfile", dest='outfile', type=str, default=None)
      #parser.add_option("--manhattan_plot", dest='manhattan',action="store_true",default=False)
      parser.add_option("--tol", dest='tol', type=float, default=4e-3)
      (options, args) = parser.parse_args()
  
  
      resdir = options.resdir
      out_file = options.outfile
      tol = options.tol
  
      print('.. load permutation results')
      file_name = os.path.join(resdir, '*.iSet.perm')
      files = glob.glob(file_name)
      df0 = pd.DataFrame()
      for _file in files:
          print(_file)
          df0 = df0.append(pd.read_csv(_file, index_col=0))
  
      print('.. load real results')
      file_name = os.path.join(resdir, '*.iSet.real')
      files = glob.glob(file_name)
      df = pd.DataFrame()
      for _file in files:
          print(_file)
          df = df.append(pd.read_csv(_file, index_col=0))
  
      #calculate P values for the three tests
      for test in ['mtSet', 'iSet', 'iSet-het']:
          df[test+' pv'] = calc_emp_pv_eff(df[test+' LLR'].values,
                                           df0[test+' LLR0'].values)
  
      print(('.. saving %s' % out_file+'.res'))
      df.to_csv(out_file+'.res')
  
      if 0:
          if options.manhattan:
              import limix.utils.plot as plot
  
              if not os.path.exists(options.outfile):
                  os.makedirs(options.outfile)
  
              def plot_manhattan(pv, out_file):
                  import matplotlib.pylab as PLT
                  import scipy as SP
                  posCum = SP.arange(pv.shape[0])
                  idx=~SP.isnan(pv)
                  plot.plot_manhattan(posCum[idx],pv[idx],alphaNS=1.0,alphaS=1.0)
                  PLT.savefig(out_file)
  
              for test in ['mtSet', 'iSet', 'iSet-het']:
                  out_file = os.path.join(options.outfile,
                                          'iSet.%s_pv.manhattan.png'\
                                          % (test,))
                  print((".. saving " + out_file))
                  plot_manhattan(df['%s pv' % test].values, out_file)
  