old_contents: import sys
  
  import argparse
  
  AVG_COLS = 12
  COV_COLS = 78
  
  if __name__ == "__main__":
      parser = argparse.ArgumentParser()
      parser.add_argument("-a", dest='avg_cols', type=int, required=True, help='number of timbre average columns')
      parser.add_argument("-c", dest='cov_cols', type=int, required=True, help='number of timbre covariance columns')
      parser.add_argument("--no-id", dest='id', action='store_false', default=True, help='include an id [default=true]')
      parser.add_argument("--input", dest='inputtype', help="test or train", required=True)
  
      opt = parser.parse_args(sys.argv[1:])
  
      assert opt.avg_cols <= AVG_COLS
      assert opt.cov_cols <= COV_COLS
  
      sch = []
      if opt.id:
        sch.append(('id', 'LONG_TYPE',))
  
      sch.append(('year', 'LONG_TYPE',))
  
      for i in range(opt.avg_cols):
          sch.append(('x{0}'.format(i), 'DOUBLE_TYPE',))
  
      for i in range(opt.cov_cols):
          sch.append(('x{0}'.format(i+opt.avg_cols), 'DOUBLE_TYPE'))
  
      cat = {}
  
      if opt.inputtype == 'train':
        cat['public:adhoc:trainingdata'] = sch
      else:
        cat['public:adhoc:testdata'] = sch
  
      print cat
  
new_contents: import sys
  
  import argparse
  
  AVG_COLS = 12
  COV_COLS = 78
  
  if __name__ == "__main__":
      parser = argparse.ArgumentParser()
      parser.add_argument("-a", dest='avg_cols', type=int, required=True, help='number of timbre average columns')
      parser.add_argument("-c", dest='cov_cols', type=int, required=True, help='number of timbre covariance columns')
      parser.add_argument("--no-id", dest='id', action='store_false', default=True, help='include an id [default=true]')
      parser.add_argument("--no-y", dest='y', action='store_false', default=True, help='include an id [default=true]')
      parser.add_argument("--input", dest='inputtype', help="test or train", required=True)
  
      opt = parser.parse_args(sys.argv[1:])
  
      assert opt.avg_cols <= AVG_COLS
      assert opt.cov_cols <= COV_COLS
  
      sch = []
      if opt.id:
        sch.append(('id', 'LONG_TYPE',))
  
      if opt.y:
        sch.append(('y', 'LONG_TYPE',))
  
      for i in range(opt.avg_cols):
          sch.append(('x{0}'.format(i), 'DOUBLE_TYPE',))
  
      for i in range(opt.cov_cols):
          sch.append(('x{0}'.format(i+opt.avg_cols), 'DOUBLE_TYPE'))
  
      cat = {}
  
      if opt.inputtype == 'train':
        cat['public:adhoc:trainingdata'] = sch
      else:
        cat['public:adhoc:testdata'] = sch
  
      print cat
  
subject: settle on y not year in naivebayes scheme