How to use the pyuvsim.analyticbeam.AnalyticBeam function in pyuvsim

def _str_to_obj(self, beam_model, use_shared_mem=False):
        # Convert beam strings to objects.
        if isinstance(beam_model, (AnalyticBeam, UVBeam)):
            return beam_model
        if beam_model.startswith('analytic'):
            bspl = beam_model.split('_')
            model = bspl[1]

            to_set = {}
            for extra in bspl[2:]:
                par, val = extra.split('=')
                full = self._float_params[par]
                to_set[full] = float(val)

            return AnalyticBeam(model, **to_set)

        path = beam_model  # beam_model = path to beamfits
        uvb = UVBeam()
        if use_shared_mem and (mpi.world_comm is not None):
            if mpi.rank == 0:
                uvb.read_beamfits(path)
                uvb.peak_normalize()
            for key, attr in uvb.__dict__.items():
                if not isinstance(attr, parameter.UVParameter):
                    continue
                if key == '_data_array':
                    uvb.__dict__[key].value = mpi.shared_mem_bcast(attr.value, root=0)
                else:
                    uvb.__dict__[key].value = mpi.world_comm.bcast(attr.value, root=0)
            mpi.world_comm.Barrier()
        else:

and (os.path.exists(beam_model)
                     or os.path.exists(os.path.join(SIM_DATA_PATH, beam_model)))):
            if os.path.exists(beam_model):
                beam_list.append(beam_model)
            else:
                beam_list.append(os.path.join(SIM_DATA_PATH, beam_model))
        # Failing that, try to parse the beam string as an analytic beam.
        else:
            if isinstance(beam_model, str):
                beam_type = beam_model
            elif 'type' in beam_model:
                beam_type = beam_model['type']
            else:
                raise ValueError("Beam model must have a 'type' field.")

            if beam_type not in AnalyticBeam.supported_types:
                raise ValueError("Undefined beam model type: {}".format(beam_type))

            this_beam_opts = {}
            if isinstance(beam_model, dict):
                for key in beam_model:
                    if key != 'type':
                        this_beam_opts[key] = beam_model[key]

            # Gaussian beam requires either diameter or sigma
            # Airy beam requires diameter

            # Default to None for diameter and sigma.
            # Values in the "beam_paths" override globally-defined options.
            beam_opts = {'diameter': None, 'sigma': None}
            for opt in beam_opts.keys():
                val = telconfig.get(opt, None)

def _obj_to_str(self, beam_model):
        # Convert beam objects to strings that may generate them.

        if isinstance(beam_model, str):
            return beam_model
        if isinstance(beam_model, AnalyticBeam):
            btype = beam_model.type

            bm_str = 'analytic_' + btype
            for abbrv, full in self._float_params.items():
                val = getattr(beam_model, full)
                if val is not None:
                    bm_str += '_' + abbrv + '=' + str(val)
            return bm_str

        # If not AnalyticBeam, it's UVBeam.
        try:
            path = beam_model.extra_keywords['beam_path']
        except KeyError:
            raise ValueError("Need to set 'beam_path' key in extra_keywords for UVBeam objects.")

        return path