text: from netCDF4 import Dataset
  import numpy as np
  import json
  import sys,getopt
  
  opts, args = getopt.getopt(sys.argv[1:],':ir',['nc=', 'cities=', 'variable=', 'attr=', 'output='])
  for opt,arg in opts:
     if opt=='--nc':
        filename=arg
     if opt=='--variable':
        variable=arg
     if opt=='--cities':
        cities=arg
     if opt=='--attr':
        attr=arg
     if opt=='--output':
        output=arg
  
  
  with open(cities, 'r') as infile:
      cities = json.loads(infile.read())
  
  dataset = Dataset(filename, 'r')
  limit = {
      'min': None,
      'max': None
  }
  
  def atributos(group):
  	for name in group.ncattrs():
  		print "Global attr", name, "=", getattr(group,name)
  
  def location(city, limit):
      indlat=0
      indlon=0
      city[attr] = None
      lat1 = dataset.variables['lat']
      lon1 = dataset.variables['lon']
      center = city['center']
      for longitud in lon1:
          if longitud < center['lng']:
              indlon+=1
      for latitud in lat1:
          if latitud < center['lat']:
              indlat+=1
      print variable + ' ' + city['city']
      print limit
      if indlon < lon1[:].size and indlat < lat1[:].size :
          city[attr]=dataset.variables[variable][indlat][indlon].tolist()
          if(city[attr]!=None) :
              if(limit['min']==None or city[attr] < limit['min']) :
                  limit['min'] = city[attr]
              if(limit['max']==None or city[attr] > limit['max']) :
                  limit['max'] = city[attr]
  
  def percentlocation(city, limit):
      value = city[attr]
      if(value != None):
          print 'Percent values: '+variable + ' ' + city['city']
          if (limit['max'] - limit['min']) > 0 :
              city[attr+'_per'] = abs(((city[attr] - limit['min']) * 100) / (limit['max'] - limit['min']))
          else :
              city[attr+'_per'] = 100
  
  for city in cities.values():
      location(city, limit)
  
  for city in cities.values():
      percentlocation(city, limit)
  
  with open(output, 'w') as outfile:
      json.dump(cities, outfile, sort_keys=True, indent=2)
  
  dataset.close()
  