old_contents: from __future__ import print_function
  import argparse
  import mdtraj as md
  import multiprocessing as mp
  import AdaptivePELE.analysis.trajectory_processing as tp
  
  
  def parseArguments():
      desc = "Program that extracts residue coordinates for a posterior MSM analysis."
      parser = argparse.ArgumentParser(description=desc)
      parser.add_argument("--dont-image", action="store_false", help="Flag to set whether trajectories should be imaged before the alignment (if not specfied performs the imaging)")
      parser.add_argument("--offset", type=int, default=0, help="Offset to add to trajectory number")
      parser.add_argument("--processors", type=int, default=4, help="Number of cpus to use")
      parser.add_argument("resname", help="Ligand resname")
      parser.add_argument("reference", help="Ligand resname")
      parser.add_argument("topology", help="Glob string for the topology")
      parser.add_argument("trajectories", help="Glob string for the trajectories")
      args = parser.parse_args()
      return args.trajectories, args.resname, args.topology, args.reference, args.processors, args.offset, args.image
  
  
  def process_traj(traj, top, ligand_name, reference, num, image=True):
      reference = md.load(reference)
      reference = tp.dehidratate(reference)
      md_traj = md.load(traj, top=top)
      if image:
          md_traj = md_traj.image_molecules()
      nowat_traj = tp.dehidratate(md_traj)
      aligned_traj = nowat_traj.superpose(reference, frame=0, atom_indices=tp.extract_heavyatom_indexes(nowat_traj), ref_atom_indices=tp.extract_heavyatom_indexes(reference))
      aligned_traj.save_xtc("trajectory_aligned_%s.xtc" % num)
      if num == 0:
          aligned_traj[0].save_pdb("top%s.pdb" % ligand_name)
  
  
  def main(trajectory_template, ligand_name, topology, reference, processors, off_set, image):
      pool = mp.Pool(processors)
      workers = []
      num = off_set
      for traj, top in tp.load_trajs(trajectory_template, topology, PELE_order=True):
          print("Procesing %s num %s with top %s" % (traj, num, top))
          workers.append(pool.apply_async(process_traj, args=(traj, top, ligand_name, reference, num, image)))
          num = num + 1
      for worker in workers:
          worker.get()
  
  
  if __name__ == "__main__":
      trajectory_template, ligand_name, topology, reference, processors, off_set, image = parseArguments()
      main(trajectory_template, ligand_name, topology, reference, processors, off_set, image)
  
new_contents: from __future__ import print_function
  import argparse
  import mdtraj as md
  import multiprocessing as mp
  import AdaptivePELE.analysis.trajectory_processing as tp
  
  
  def parseArguments():
      desc = "Program that extracts residue coordinates for a posterior MSM analysis."
      parser = argparse.ArgumentParser(description=desc)
      parser.add_argument("--dont_image", action="store_false", help="Flag to set whether trajectories should be imaged before the alignment (if not specfied performs the imaging)")
      parser.add_argument("--offset", type=int, default=0, help="Offset to add to trajectory number")
      parser.add_argument("--processors", type=int, default=4, help="Number of cpus to use")
      parser.add_argument("resname", help="Ligand resname")
      parser.add_argument("reference", help="Ligand resname")
      parser.add_argument("topology", help="Glob string for the topology")
      parser.add_argument("trajectories", help="Glob string for the trajectories")
      args = parser.parse_args()
      return args.trajectories, args.resname, args.topology, args.reference, args.processors, args.offset, args.dont_image
  
  
  def process_traj(traj, top, ligand_name, reference, num, image=True):
      reference = md.load(reference)
      reference = tp.dehidratate(reference)
      md_traj = md.load(traj, top=top)
      if image:
          md_traj = md_traj.image_molecules()
      nowat_traj = tp.dehidratate(md_traj)
      aligned_traj = nowat_traj.superpose(reference, frame=0, atom_indices=tp.extract_heavyatom_indexes(nowat_traj), ref_atom_indices=tp.extract_heavyatom_indexes(reference))
      aligned_traj.save_xtc("trajectory_aligned_%s.xtc" % num)
      if num == 0:
          aligned_traj[0].save_pdb("top%s.pdb" % ligand_name)
  
  
  def main(trajectory_template, ligand_name, topology, reference, processors, off_set, image):
      pool = mp.Pool(processors)
      workers = []
      num = off_set
      for traj, top in tp.load_trajs(trajectory_template, topology, PELE_order=True):
          print("Procesing %s num %s with top %s" % (traj, num, top))
          workers.append(pool.apply_async(process_traj, args=(traj, top, ligand_name, reference, num, image)))
          num = num + 1
      for worker in workers:
          worker.get()
  
  
  if __name__ == "__main__":
      trajectory_template, ligand_name, topology, reference, processors, off_set, image = parseArguments()
      main(trajectory_template, ligand_name, topology, reference, processors, off_set, image)
  
subject: Fix parameter name