new_contents: 
  '''
  Only image the region directly around the OH detection
  '''
  
  import os
  import json
  
  from tasks import rmtables, impbcor, exportfits, tclean
  
  orig_dir = os.getcwd()
  
  
  # The VLA_Lband directory needs to be in the path
  # from CASA_functions import (set_imagermode, set_imagesize, set_cellsize)
  
  # Loop through all 4 lines
  
  line = 'OH1665'
  
  line_file = \
      os.path.expanduser(
          "~/Dropbox/code_development/VLA_Lband/14B-088/Lines/spw_dict.txt")
  with open(line_file, 'r') as f:
      line_dict = json.load(f)
  
  rest_freq = str(line_dict[line])
  
  print("On line: {0} {1}".format(line, rest_freq))
  
  os.chdir(line)
  
  ms_active = "{0}_14B-088.ms.contsub".format(line)
  out_directory = "detection_imaging_1point5km_s".format(line)
  
  if not os.path.exists(out_directory):
      os.mkdir(out_directory)
  
  # Imaging parameters
  mode = 'velocity'
  nchan = 40
  width = "1.5km/s"
  start = "-230.0km/s"
  threshold = "3mJy/beam"
  field = "M33*"
  phasecenter = 'J2000 01h34m00.122 +30d40m47.19'
  spw = ""
  imagermode = "mosaic"
  multiscale = []
  outframe = "LSRK"
  veltype = "radio"
  pbcor = False
  robust = 0.0
  restfreq = rest_freq
  interpolation = 'linear'
  pblimit = 0.1
  
  spw_num = 0
  max_size = 15000
  
  # Determine imagermode, cell size, and image size
  # imagermode = set_imagermode(ms_active, field.rstrip("*"))
  # cellsize = set_cellsize(ms_active, 0, sample_factor=6.)
  # imagesize = set_imagesize(ms_active, 0, field.rstrip("*"), sample_factor=6.,
  #                           pblevel=pblimit, max_size=max_size)
  imagermode = 'cube'
  cellsize = '2.3arcsec'
  imagesize = [300, 300]
  
  print("Output image cell size: {}".format(cellsize))
  print("Image pixel size: {}".format(imagesize))
  
  # Re-image with 3 different weighting choices
  # robust has 0.0 set above
  # weightings = ["natural", "briggs", "uniform"]
  
  weighting = "uniform"
  
  out_image = os.path.join(out_directory,
                           "{0}_14B-088_{1}".format(line, weighting))
  
  # Ensure there aren't any old versions
  rmtables(out_image + ".*")
  
  # This one is interactive so that a clean mask can be added.
  tclean(vis=ms_active,
         datacolumn='data',
         field=field,
         imagename=out_image,
         imsize=imagesize,
         cell=cellsize,
         specmode='cube',
         start=start,
         width=width,
         nchan=nchan,
         startmodel=None,
         gridder='mosaic',
         weighting=weighting,
         niter=10000,
         threshold=threshold,
         phasecenter=phasecenter,
         restfreq=rest_freq,
         outframe=outframe,
         pblimit=pblimit,
         usemask='user',
         mask='circle[[150pix,150pix],12pix]',
         deconvolver='hogbom',
         pbcor=False,
         chanchunks=-1,
         interactive=True
         )
  
  # Now run the pbcor
  impbcor(imagename="{}.image".format(out_image),
          pbimage="{}.pb".format(out_image),
          outfile="{}.image.pbcor".format(out_image),
          cutoff=pblimit, mode='divide')
  
  exportfits(imagename="{}.image.pbcor".format(out_image),
             fitsimage="{}.image.pbcor.fits".format(out_image),
             velocity=True, overwrite=True,
             dropdeg=True, history=False)
  
  exportfits(imagename="{}.pb".format(out_image),
             fitsimage="{}.pb.fits".format(out_image),
             velocity=True, overwrite=True,
             dropdeg=True, history=False)
  
  os.chdir(orig_dir)
  
subject: Make a small version of the OH 1665 detection