code: def run_flow(flow):
      """Wraps the process of building an argparser that reflects the workflow
      that we want to run along with some generic parameters like logging,
      force and output strategies. The resulting parameters are then fed to
      the workflow's run method.
      """
      parser = IntrospectiveArgumentParser()
      sub_flows_dicts = parser.add_workflow(flow)
  
      # Common workflow arguments
      parser.add_argument(
          "--force",
          dest="force",
          action="store_true",
          default=False,
          help="Force overwriting output files.",
      )
  
      parser.add_argument(
          "--version",
          action="version",
          version="DIPY {}".format(dipy_version),
      )
  
      parser.add_argument(
          "--out_strat",
          action="store",
          dest="out_strat",
          metavar="string",
          required=False,
          default="absolute",
          help="Strategy to manage output creation.",
      )
  
      parser.add_argument(
          "--mix_names",
          dest="mix_names",
          action="store_true",
          default=False,
          help="Prepend mixed input names to output names.",
      )
  
      # Add logging parameters common to all workflows
      msg = "Log messages display level. Accepted options include CRITICAL,"
      msg += " ERROR, WARNING, INFO, DEBUG and NOTSET (default INFO)."
      parser.add_argument(
          "--log_level",
          action="store",
          dest="log_level",
          metavar="string",
          required=False,
          default="INFO",
          help=msg,
      )
  
      parser.add_argument(
          "--log_file",
          action="store",
          dest="log_file",
          metavar="string",
          required=False,
          default="",
          help="Log file to be saved.",
      )
  
      args = parser.get_flow_args()
  
      logging.basicConfig(
          filename=args["log_file"],
          format="%(levelname)s:%(message)s",
          level=get_level(args["log_level"]),
      )
  
      # Output management parameters
      flow._force_overwrite = args["force"]
      flow._output_strategy = args["out_strat"]
      flow._mix_names = args["mix_names"]
  
      # Keep only workflow related parameters
      del args["force"]
      del args["log_level"]
      del args["log_file"]
      del args["out_strat"]
      del args["mix_names"]
  
      # Remove subflows related params
      for params_dict in list(sub_flows_dicts.values()):
          for key in list(params_dict.keys()):
              if key in args.keys():
                  params_dict[key] = args.pop(key)
  
                  # Rename dictionary key to the original param name
                  params_dict[key.split(".")[1]] = params_dict.pop(key)
  
      if sub_flows_dicts:
          flow.set_sub_flows_optionals(sub_flows_dicts)
  
      return flow.run(**args)
  
imports: import warnings
  import logging
  from dipy import __version__
  from dipy.workflows.base import IntrospectiveArgumentParser
label_desc: Use image node_id 2 for calling a global function with example usage: run_flow(flow) and returns: flow