How to use the pyvista.utilities.wrap function in pyvista

from itertools import cycle
                    cycler = mpl.rcParams['axes.prop_cycle']
                    colors = cycle(cycler)
                except ImportError:
                    multi_colors = False
                    logging.warning('Please install matplotlib for color cycles')
            # Now iteratively plot each element of the multiblock dataset
            actors = []
            for idx in range(mesh.GetNumberOfBlocks()):
                if mesh[idx] is None:
                    continue
                # Get a good name to use
                next_name = '{}-{}'.format(name, idx)
                # Get the data object
                if not is_pyvista_obj(mesh[idx]):
                    data = wrap(mesh.GetBlock(idx))
                    if not is_pyvista_obj(mesh[idx]):
                        continue # move on if we can't plot it
                else:
                    data = mesh.GetBlock(idx)
                if data is None:
                    # Note that a block can exist but be None type
                    continue
                # Now check that scalars is available for this dataset
                if isinstance(data, vtk.vtkMultiBlockDataSet) or get_scalar(data, scalars) is None:
                    ts = None
                else:
                    ts = scalars
                if multi_colors:
                    color = next(colors)['color']
                a = self.add_mesh(data, color=color, style=style,
                                  scalars=ts, rng=rng, stitle=stitle,

categories : bool, optional
            If set to ``True``, then the number of unique values in the scalar
            array will be used as the ``n_colors`` argument.

        use_transparency : bool, optional
            Invert the opacity mapping and make the values correspond to
            transperency.

        Returns
        -------
        actor: vtk.vtkActor
            VTK actor of the mesh.
        """
        # Convert the VTK data object to a pyvista wrapped object if neccessary
        if not is_pyvista_obj(mesh):
            mesh = wrap(mesh)

        ##### Parse arguments to be used for all meshes #####

        if scalar_bar_args is None:
            scalar_bar_args = {}

        if show_edges is None:
            show_edges = rcParams['show_edges']

        if edge_color is None:
            edge_color = rcParams['edge_color']

        if show_scalar_bar is None:
            show_scalar_bar = rcParams['show_scalar_bar']

        if lighting is None:

from itertools import cycle
                    cycler = mpl.rcParams['axes.prop_cycle']
                    colors = cycle(cycler)
                except ImportError:
                    multi_colors = False
                    logging.warning('Please install matplotlib for color cycles')
            # Now iteratively plot each element of the multiblock dataset
            actors = []
            for idx in range(mesh.GetNumberOfBlocks()):
                if mesh[idx] is None:
                    continue
                # Get a good name to use
                next_name = '{}-{}'.format(name, idx)
                # Get the data object
                if not is_pyvista_obj(mesh[idx]):
                    data = wrap(mesh.GetBlock(idx))
                    if not is_pyvista_obj(mesh[idx]):
                        continue # move on if we can't plot it
                else:
                    data = mesh.GetBlock(idx)
                if data is None or (not isinstance(data, pyvista.MultiBlock) and data.n_points < 1):
                    # Note that a block can exist but be None type
                    # or it could have zeros points (be empty) after filtering
                    continue
                # Now check that scalars is available for this dataset
                if isinstance(data, vtk.vtkMultiBlockDataSet) or get_scalar(data, scalars) is None:
                    ts = None
                else:
                    ts = scalars
                if multi_colors:
                    color = next(colors)['color']
                a = self.add_mesh(data, color=color, style=style,

direction[:,0] *= mag
        direction[:,1] *= mag
        direction[:,2] *= mag

        pdata = pyvista.vector_poly_data(cent, direction)
        # Create arrow object
        arrow = vtk.vtkArrowSource()
        arrow.Update()
        glyph3D = vtk.vtkGlyph3D()
        glyph3D.SetSourceData(arrow.GetOutput())
        glyph3D.SetInputData(pdata)
        glyph3D.SetVectorModeToUseVector()
        glyph3D.Update()

        arrows = wrap(glyph3D.GetOutput())

        return self.add_mesh(arrows, **kwargs)

if name is None:
            name = '{}({})'.format(type(volume).__name__, str(hex(id(volume))))

        if rng is None:
            rng = kwargs.get('clim', None)

        if scalar_bar_args is None:
            scalar_bar_args = {}

        if show_scalar_bar is None:
            show_scalar_bar = rcParams['show_scalar_bar']

        # Convert the VTK data object to a pyvista wrapped object if neccessary
        if not is_pyvista_obj(volume):
            if isinstance(volume, np.ndarray):
                volume = wrap(volume)
                if resolution is None:
                    resolution = [1,1,1]
                elif len(resolution) != 3:
                    raise ValueError('Invalid resolution dimensions.')
                volume.spacing = resolution
            else:
                volume = wrap(volume)
        else:
            # HACK: Make a copy so the original object is not altered
            volume = volume.copy()


        if isinstance(volume, pyvista.MultiBlock):
            from itertools import cycle
            cycler = cycle(['Reds', 'Greens', 'Blues', 'Greys', 'Oranges', 'Purples'])
            # Now iteratively plot each element of the multiblock dataset

def _get_output(algorithm, iport=0, iconnection=0, oport=0, active_scalars=None,
                active_scalars_field='point'):
    """Get the algorithm's output and copy input's pyvista meta info."""
    ido = algorithm.GetInputDataObject(iport, iconnection)
    data = wrap(algorithm.GetOutputDataObject(oport))
    if not isinstance(data, pyvista.MultiBlock):
        data.copy_meta_from(ido)
        if active_scalars is not None:
            data.set_active_scalars(active_scalars, preference=active_scalars_field)
    return data