"""PyVista plotting module."""
import collections.abc
from contextlib import contextmanager
from copy import deepcopy
import ctypes
from functools import wraps
import io
import logging
import os
import pathlib
import platform
import sys
import textwrap
from threading import Thread
import time
from typing import Dict, Optional
import warnings
import weakref

import matplotlib
import numpy as np
import scooby

import pyvista
from pyvista.core._typing_core import BoundsLike
from pyvista.core.errors import MissingDataError, PyVistaDeprecationWarning
from pyvista.core.utilities.arrays import (
    FieldAssociation,
    _coerce_pointslike_arg,
    convert_array,
    get_array,
    get_array_association,
    raise_not_matching,
)
from pyvista.core.utilities.helpers import is_pyvista_dataset, wrap
from pyvista.core.utilities.misc import abstract_class, assert_empty_kwargs

from . import _vtk
from ._plotting import (
    USE_SCALAR_BAR_ARGS,
    _common_arg_parser,
    prepare_smooth_shading,
    process_opacity,
)
from ._property import Property
from .actor import Actor
from .colors import Color, get_cmap_safe
from .composite_mapper import CompositePolyDataMapper
from .errors import RenderWindowUnavailable
from .mapper import (
    DataSetMapper,
    FixedPointVolumeRayCastMapper,
    GPUVolumeRayCastMapper,
    OpenGLGPUVolumeRayCastMapper,
    PointGaussianMapper,
    SmartVolumeMapper,
    UnstructuredGridVolumeRayCastMapper,
)
from .picking import PickingHelper
from .render_window_interactor import RenderWindowInteractor
from .renderer import Camera, Renderer
from .renderers import Renderers
from .scalar_bars import ScalarBars
from .text import CornerAnnotation, Text, TextProperty
from .texture import numpy_to_texture
from .themes import Theme
from .tools import normalize, opacity_transfer_function, parse_font_family  # noqa
from .utilities.algorithms import (
    active_scalars_algorithm,
    algorithm_to_mesh_handler,
    decimation_algorithm,
    extract_surface_algorithm,
    pointset_to_polydata_algorithm,
    set_algorithm_input,
    triangulate_algorithm,
)
from .utilities.gl_checks import uses_egl
from .utilities.regression import image_from_window, run_image_filter
from .volume import Volume
from .volume_property import VolumeProperty
from .widgets import WidgetHelper

SUPPORTED_FORMATS = [".png", ".jpeg", ".jpg", ".bmp", ".tif", ".tiff"]

# EXPERIMENTAL: permit pyvista to kill the render window
KILL_DISPLAY = platform.system() == 'Linux' and os.environ.get('PYVISTA_KILL_DISPLAY')
if KILL_DISPLAY:  # pragma: no cover
    # this won't work under wayland
    try:
        X11 = ctypes.CDLL("libX11.so")
        X11.XCloseDisplay.argtypes = [ctypes.c_void_p]
    except OSError:
        warnings.warn('PYVISTA_KILL_DISPLAY: Unable to load X11.\nProbably using wayland')
        KILL_DISPLAY = False

def close_all():
    """Close all open/active plotters and clean up memory.

    Returns
    -------
    bool
        ``True`` when all plotters have been closed.

    """
    for pl in list(_ALL_PLOTTERS.values()):
        if not pl._closed:
            pl.close()
    _ALL_PLOTTERS.clear()
    return True

log = logging.getLogger(__name__)
log.setLevel('CRITICAL')
log.addHandler(logging.StreamHandler())

def _warn_xserver():  # pragma: no cover
    """Check if plotting is supported and persist this state.

    Check once and cache this value between calls.  Warn the user if
    plotting is not supported.  Configured to check on Linux and Mac
    OS since the Windows check is not quick.

    """
    # disable windows check until we can get a fast way of verifying
    # if windows has a windows manager (which it generally does)
    if os.name == 'nt':
        return

    if not hasattr(_warn_xserver, 'has_support'):
        _warn_xserver.has_support = pyvista.system_supports_plotting()

    if not _warn_xserver.has_support:
        # check if a display has been set
        if 'DISPLAY' in os.environ:
            return

        # finally, check if using a backend that doesn't require an xserver
        if pyvista.global_theme.jupyter_backend in [
            'client',
        ]:
            return

        # Check if VTK has EGL support
        if uses_egl():
            return

        warnings.warn(
            '\n'
            'This system does not appear to be running an xserver.\n'
            'PyVista will likely segfault when rendering.\n\n'
            'Try starting a virtual frame buffer with xvfb, or using\n '
            ' ``pyvista.start_xvfb()``\n'
        )

@abstract_class
class BasePlotter(PickingHelper, WidgetHelper):
    """Base plotting class.

    To be used by the :class:`pyvista.Plotter` and
    :class:`pyvistaqt.QtInteractor` classes.

    Parameters
    ----------
    shape : sequence[int] | str, optional
        Two item sequence of sub-render windows inside of the main window.
        Specify two across with ``shape=(2, 1)`` and a two by two grid
        with ``shape=(2, 2)``.  By default there is only one renderer.
        Can also accept a string descriptor as shape. For example:

        * ``shape="3|1"`` means 3 plots on the left and 1 on the right,
        * ``shape="4/2"`` means 4 plots on top and 2 at the bottom.

    border : bool, default: False
        Draw a border around each render window.

    border_color : ColorLike, default: 'k'
        Either a string, rgb list, or hex color string.  For example:

        * ``color='white'``
        * ``color='w'``
        * ``color=[1.0, 1.0, 1.0]``
        * ``color='#FFFFFF'``

    border_width : float, default: 2.0
        Width of the border in pixels when enabled.

    title : str, optional
        Window title.

    splitting_position : float, optional
        The splitting position of the renderers.

    groups : tuple, optional
        Grouping for renderers.

    row_weights : tuple
        Row weights for renderers.

    col_weights : tuple, optional
        Column weights for renderers.

    lighting : str, default: 'light kit'
        What lighting to set up for the plotter.  Accepted options:

        * ``'light_kit'``: a vtk Light Kit composed of 5 lights.
        * ``'three lights'``: illumination using 3 lights.
        * ``'none'``: no light sources at instantiation.

    theme : pyvista.plotting.themes.Theme, optional
        Plot-specific theme.

    image_scale : int, optional
        Scale factor when saving screenshots. Image sizes will be
        the ``window_size`` multiplied by this scale factor.

    **kwargs : dict, optional
        Additional keyword arguments.

    Examples
    --------
    Simple plotter example showing a blurred cube with a gradient background.

    >>> import pyvista as pv
    >>> pl = pv.Plotter()
    >>> _ = pl.add_mesh(pv.Cube())
    >>> pl.set_background('black', top='white')
    >>> pl.add_blurring()
    >>> pl.show()

    """

    mouse_position = None
    click_position = None

    def __init__(
        self,
        shape=(1, 1),
        border=None,
        border_color='k',
        border_width=2.0,
        title=None,
        splitting_position=None,
        groups=None,
        row_weights=None,
        col_weights=None,
        lighting='light kit',
        theme=None,
        image_scale=None,
        **kwargs,
    ):
        """Initialize base plotter."""
        super().__init__(**kwargs)  # cooperative multiple inheritance
        log.debug('BasePlotter init start')
        self._initialized = False

        self._theme = Theme()
        if theme is None:
            # copy global theme to ensure local plot theme is fixed
            # after creation.
            self._theme.load_theme(pyvista.global_theme)
        else:
            if not isinstance(theme, pyvista.plotting.themes.Theme):
                raise TypeError(
                    'Expected ``pyvista.plotting.themes.Theme`` for '
                    f'``theme``, not {type(theme).__name__}.'
                )
            self._theme.load_theme(theme)

        self.image_transparent_background = self._theme.transparent_background

        # optional function to be called prior to closing
        self.__before_close_callback = None
        self.mesh = None
        if title is None:
            title = self._theme.title
        self.title = str(title)

        # add renderers
        self.renderers = Renderers(
            self,
            shape,
            splitting_position,
            row_weights,
            col_weights,
            groups,
            border,
            border_color,
            border_width,
        )

        # This keeps track of scalars names already plotted and their ranges
        self._scalar_bars = ScalarBars(self)

        # track if the camera has been set up
        self._first_time = True
        # Keep track of the scale

        # track if render window has ever been rendered
        self._rendered = False

        self._on_render_callbacks = set()

        # this helps managing closed plotters
        self._closed = False

        # lighting style; be forgiving with input (accept underscores
        # and ignore case)
        lighting_normalized = str(lighting).replace('_', ' ').lower()
        if lighting_normalized == 'light kit':
            self.enable_lightkit()
        elif lighting_normalized == 'three lights':
            self.enable_3_lights()
        elif lighting_normalized != 'none':
            raise ValueError(f'Invalid lighting option "{lighting}".')

        # Track all active plotters. This has the side effect of ensuring that plotters are not
        # collected until `close()`. See https://github.com//pull/3216
        # This variable should be safe as a variable name
        self._id_name = f"P_{hex(id(self))}_{len(_ALL_PLOTTERS)}"
        _ALL_PLOTTERS[self._id_name] = self

        # Key bindings
        self.reset_key_events()
        log.debug('BasePlotter init stop')

        self._image_depth_null = None
        self.last_image_depth = None
        self.last_image = None
        self.last_vtksz = None
        self._has_background_layer = False
        if image_scale is None:
            image_scale = self._theme.image_scale
        self._image_scale = image_scale

        # set hidden line removal based on theme
        if self.theme.hidden_line_removal:
            self.enable_hidden_line_removal()

        self._initialized = True
        self._suppress_rendering = False

    @property
    def suppress_rendering(self):  # numpydoc ignore=RT01
        """Get or set whether to suppress render calls.

        Returns
        -------
        bool
            ``True`` when rendering is suppressed.

        """
        return self._suppress_rendering

    @suppress_rendering.setter
    def suppress_rendering(self, value):  # numpydoc ignore=GL08
        self._suppress_rendering = bool(value)

    @property
    def render_window(self):  # numpydoc ignore=RT01
        """Access the vtkRenderWindow attached to this plotter.

        If the plotter is closed, this will return ``None``.

        Returns
        -------
        vtk.vtkRenderWindow or None
            Render window if the plotter is not closed.

        Notes
        -----
        Subclass must set ``ren_win`` on initialization.
        """
        if not hasattr(self, 'ren_win'):
            return
        return self.ren_win

    @property
    def theme(self):  # numpydoc ignore=RT01
        """Return or set the theme used for this plotter.

        Returns
        -------
        pyvista.Theme
            Theme of this plotter.

        Examples
        --------
        Use the dark theme for a plotter.

        >>> import pyvista as pv
        >>> from pyvista import themes
        >>> pl = pv.Plotter()
        >>> pl.theme = themes.DarkTheme()
        >>> actor = pl.add_mesh(pv.Sphere())
        >>> pl.show()

        """
        return self._theme

    @theme.setter
    def theme(self, theme):  # numpydoc ignore=GL08
        if not isinstance(theme, pyvista.plotting.themes.Theme):
            raise TypeError(
                'Expected a pyvista theme like '
                '``pyvista.plotting.themes.Theme``, '
                f'not {type(theme).__name__}.'
            )
        self._theme.load_theme(theme)

    def import_gltf(self, filename, set_camera=True):
        """Import a glTF file into the plotter.

        See https://www.khronos.org/gltf/ for more information.

        Parameters
        ----------
        filename : str
            Path to the glTF file.

        set_camera : bool, default: True
            Set the camera viewing angle to one compatible with the
            default three.js perspective (``'xy'``).

        Examples
        --------
        >>> import pyvista as pv
        >>> from pyvista import examples
        >>> helmet_file = (
        ...     examples.gltf.download_damaged_helmet()
        ... )  # doctest:+SKIP
        >>> texture = (
        ...     examples.hdr.download_dikhololo_night()
        ... )  # doctest:+SKIP
        >>> pl = pv.Plotter()  # doctest:+SKIP
        >>> pl.import_gltf(helmet_file)  # doctest:+SKIP
        >>> pl.set_environment_texture(cubemap)  # doctest:+SKIP
        >>> pl.camera.zoom(1.8)  # doctest:+SKIP
        >>> pl.show()  # doctest:+SKIP

        See :ref:`load_gltf` for a full example using this method.

        """
        filename = os.path.abspath(os.path.expanduser(str(filename)))
        if not os.path.isfile(filename):
            raise FileNotFoundError(f'Unable to locate {filename}')

        # lazy import here to avoid importing unused modules
        from vtkmodules.vtkIOImport import vtkGLTFImporter

        importer = vtkGLTFImporter()
        importer.SetFileName(filename)
        importer.SetRenderWindow(self.render_window)
        importer.Update()

        # register last actor in actors
        actor = self.renderer.GetActors().GetLastItem()
        name = actor.GetAddressAsString("")
        self.renderer._actors[name] = actor

        # set camera position to a three.js viewing perspective
        if set_camera:
            self.camera_position = 'xy'

    def import_vrml(self, filename):
        """Import a VRML file into the plotter.

        Parameters
        ----------
        filename : str
            Path to the VRML file.

        Examples
        --------
        >>> import pyvista as pv
        >>> from pyvista import examples
        >>> sextant_file = (
        ...     examples.vrml.download_sextant()
        ... )  # doctest:+SKIP
        >>> pl = pv.Plotter()  # doctest:+SKIP
        >>> pl.import_vrml(sextant_file)  # doctest:+SKIP
        >>> pl.show()  # doctest:+SKIP

        See :ref:`load_vrml_example` for a full example using this method.

        """
        from vtkmodules.vtkIOImport import vtkVRMLImporter

        filename = os.path.abspath(os.path.expanduser(str(filename)))
        if not os.path.isfile(filename):
            raise FileNotFoundError(f'Unable to locate {filename}')

        # lazy import here to avoid importing unused modules
        importer = vtkVRMLImporter()
        importer.SetFileName(filename)
        importer.SetRenderWindow(self.render_window)
        importer.Update()

    def export_html(self, filename):
        """Export this plotter as an interactive scene to a HTML file.

        Parameters
        ----------
        filename : str
            Path to export the html file to.

        Returns
        -------
        StringIO
            If filename is None, returns the HTML as a StringIO object.

        Notes
        -----
        You will need ``trame`` installed.

        Examples
        --------
        >>> import pyvista as pv
        >>> from pyvista import examples
        >>> mesh = examples.load_uniform()
        >>> pl = pv.Plotter(shape=(1, 2))
        >>> _ = pl.add_mesh(
        ...     mesh, scalars='Spatial Point Data', show_edges=True
        ... )
        >>> pl.subplot(0, 1)
        >>> _ = pl.add_mesh(
        ...     mesh, scalars='Spatial Cell Data', show_edges=True
        ... )
        >>> pl.export_html('pv.html')  # doctest:+SKIP

        """
        try:
            from trame_vtk.tools.vtksz2html import write_html
        except ImportError:  # pragma: no cover
            raise ImportError('Please install trame-vtk to export')

        data = self.export_vtksz(filename=None)
        buffer = io.StringIO()
        write_html(data, buffer)
        buffer.seek(0)

        if filename is None:
            return buffer

        if not filename.endswith('.html'):
            filename += '.html'

        # Move to final destination
        with open(filename, 'w', encoding='utf-8') as f:
            f.write(buffer.read())

    def export_vtksz(self, filename='scene-export.vtksz', format='zip'):
        """Export this plotter as a VTK.js OfflineLocalView file.

        The exported file can be viewed with the OfflineLocalView viewer
        available at https://kitware.github.io/vtk-js/examples/OfflineLocalView.html

        Parameters
        ----------
        filename : str, optional
            Path to export the file to. Defaults to ``'scene-export.vtksz'``.

        format : str, optional
            The format of the exported file. Defaults to ``'zip'``. Can be
            either ``'zip'`` or ``'json'``.

        Returns
        -------
        str
            The exported filename.

        """
        try:
            from pyvista.trame import PyVistaLocalView
            from pyvista.trame.jupyter import elegantly_launch
            from pyvista.trame.views import get_server
        except ImportError:  # pragma: no cover
            raise ImportError('Please install trame to export')

        # Ensure trame server is launched
        server = get_server(pyvista.global_theme.trame.jupyter_server_name)
        if not server.running:
            elegantly_launch(pyvista.global_theme.trame.jupyter_server_name)

        view = PyVistaLocalView(self, trame_server=server)

        content = view.export(format=format)

        view.release_resources()
        # Make sure callbacks are unregistered
        self._on_render_callbacks.remove(view._plotter_render_callback)

        if filename is None:
            return content

        with open(filename, 'wb') as f:
            f.write(content)

        return filename

    def export_gltf(self, filename, inline_data=True, rotate_scene=True, save_normals=True):
        """Export the current rendering scene as a glTF file.

        Visit https://gltf-viewer.donmccurdy.com/ for an online viewer.

        See https://vtk.org/doc/nightly/html/classvtkGLTFExporter.html
        for limitations regarding the exporter.

        Parameters
        ----------
        filename : str
            Path to export the gltf file to.

        inline_data : bool, default: True
            Sets if the binary data be included in the json file as a
            base64 string.  When ``True``, only one file is exported.

        rotate_scene : bool, default: True
            Rotate scene to be compatible with the glTF specifications.

        save_normals : bool, default: True
            Saves the point array ``'Normals'`` as ``'NORMAL'`` in
            the outputted scene.

        Notes
        -----
        The VTK exporter only supports :class:`pyvista.PolyData` datasets. If
        the plotter contains any non-PolyData datasets, these will be converted
        in the plotter, leading to a copy of the data internally.

        Examples
        --------
        Output a simple point cloud represented as balls.

        >>> import numpy as np
        >>> import pyvista as pv
        >>> point_cloud = np.random.random((100, 3))
        >>> pdata = pv.PolyData(point_cloud)
        >>> pdata['orig_sphere'] = np.arange(100)
        >>> sphere = pv.Sphere(radius=0.02)
        >>> pc = pdata.glyph(scale=False, geom=sphere, orient=False)
        >>> pl = pv.Plotter()
        >>> _ = pl.add_mesh(
        ...     pc,
        ...     cmap='reds',
        ...     smooth_shading=True,
        ...     show_scalar_bar=False,
        ... )
        >>> pl.export_gltf('balls.gltf')  # doctest:+SKIP
        >>> pl.show()

        Output the orientation plotter.

        >>> from pyvista import demos
        >>> pl = demos.orientation_plotter()
        >>> pl.export_gltf('orientation_plotter.gltf')  # doctest:+SKIP
        >>> pl.show()

        """
        if self.render_window is None:
            raise RuntimeError('This plotter has been closed and is unable to export the scene.')

        from vtkmodules.vtkIOExport import vtkGLTFExporter

        # rotate scene to gltf compatible view
        renamed_arrays = []  # any renamed normal arrays
        if rotate_scene:
            for renderer in self.renderers:
                for actor in renderer.actors.values():
                    if hasattr(actor, 'RotateX'):
                        actor.RotateX(-90)
                        actor.RotateZ(-90)

                    if save_normals:
                        try:
                            mapper = actor.GetMapper()
                            if mapper is None:
                                continue
                            dataset = mapper.dataset
                            if not isinstance(dataset, pyvista.PolyData):
                                warnings.warn(
                                    'Plotter contains non-PolyData datasets. These have been '
                                    'overwritten with PolyData surfaces and are internally '
                                    'copies of the original datasets.'
                                )

                                try:
                                    dataset = dataset.extract_surface()
                                    mapper.SetInputData(dataset)
                                except:  # pragma: no cover
                                    warnings.warn(
                                        'During gLTF export, failed to convert some '
                                        'datasets to PolyData. Exported scene will not have '
                                        'all datasets.'
                                    )

                            if 'Normals' in dataset.point_data:
                                # By default VTK uses the 'Normals' point data for normals
                                # but gLTF uses NORMAL.
                                point_data = dataset.GetPointData()
                                array = point_data.GetArray('Normals')
                                array.SetName('NORMAL')
                                renamed_arrays.append(array)

                        except:  # noqa: E722
                            pass

        exporter = vtkGLTFExporter()
        exporter.SetRenderWindow(self.render_window)
        exporter.SetFileName(filename)
        exporter.SetInlineData(inline_data)
        exporter.SetSaveNormal(save_normals)
        exporter.Update()

        # rotate back if applicable
        if rotate_scene:
            for renderer in self.renderers:
                for actor in renderer.actors.values():
                    if hasattr(actor, 'RotateX'):
                        actor.RotateZ(90)
                        actor.RotateX(90)

        # revert any renamed arrays
        for array in renamed_arrays:
            array.SetName('Normals')

    def export_vrml(self, filename):
        """Export the current rendering scene as a VRML file.

        See `vtk.VRMLExporter <https://vtk.org/doc/nightly/html/classvtkVRMLExporter.html>`_
        for limitations regarding the exporter.

        Parameters
        ----------
        filename : str
            Filename to export the scene to.

        Examples
        --------
        >>> import pyvista as pv
        >>> from pyvista import examples
        >>> pl = pv.Plotter()
        >>> _ = pl.add_mesh(examples.load_hexbeam())
        >>> pl.export_vrml("sample")  # doctest:+SKIP

        """
        from vtkmodules.vtkIOExport import vtkVRMLExporter

        if self.render_window is None:
            raise RuntimeError("This plotter has been closed and cannot be shown.")

        exporter = vtkVRMLExporter()
        exporter.SetFileName(filename)
        exporter.SetRenderWindow(self.render_window)
        exporter.Write()

    def enable_hidden_line_removal(self, all_renderers=True):
        """Enable hidden line removal.

        Wireframe geometry will be drawn using hidden line removal if
        the rendering engine supports it.

        Disable this with :func:`disable_hidden_line_removal
        <Plotter.disable_hidden_line_removal>`.

        Parameters
        ----------
        all_renderers : bool, default: True
            If ``True``, applies to all renderers in subplots. If
            ``False``, then only applies to the active renderer.

        Examples
        --------
        Create a side-by-side plotter and render a sphere in wireframe
        with hidden line removal enabled on the left and disabled on
        the right.

        >>> import pyvista as pv
        >>> sphere = pv.Sphere(theta_resolution=20, phi_resolution=20)
        >>> pl = pv.Plotter(shape=(1, 2))
        >>> _ = pl.add_mesh(sphere, line_width=3, style='wireframe')
        >>> _ = pl.add_text("With hidden line removal")
        >>> pl.enable_hidden_line_removal(all_renderers=False)
        >>> pl.subplot(0, 1)
        >>> pl.disable_hidden_line_removal(all_renderers=False)
        >>> _ = pl.add_mesh(sphere, line_width=3, style='wireframe')
        >>> _ = pl.add_text("Without hidden line removal")
        >>> pl.show()

        """
        if all_renderers:
            for renderer in self.renderers:
                renderer.enable_hidden_line_removal()
        else:
            self.renderer.enable_hidden_line_removal()

    def disable_hidden_line_removal(self, all_renderers=True):
        """Disable hidden line removal.

        Enable again with :func:`enable_hidden_line_removal
        <Plotter.enable_hidden_line_removal>`.

        Parameters
        ----------
        all_renderers : bool, default: True
            If ``True``, applies to all renderers in subplots. If
            ``False``, then only applies to the active renderer.

        Examples
        --------
        Enable and then disable hidden line removal.

        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> pl.enable_hidden_line_removal()
        >>> pl.disable_hidden_line_removal()

        """
        if all_renderers:
            for renderer in self.renderers:
                renderer.disable_hidden_line_removal()
        else:
            self.renderer.disable_hidden_line_removal()

    @property
    def scalar_bar(self):  # numpydoc ignore=RT01
        """First scalar bar (kept for backwards compatibility).

        Returns
        -------
        vtk.vtkScalarBarActor
            First scalar bar actor.

        """
        return list(self.scalar_bars.values())[0]

    @property
    def scalar_bars(self):  # numpydoc ignore=RT01
        """Scalar bars.

        Returns
        -------
        pyvista.ScalarBars
            Scalar bar object.

        Examples
        --------
        >>> import pyvista as pv
        >>> sphere = pv.Sphere()
        >>> sphere['Data'] = sphere.points[:, 2]
        >>> plotter = pv.Plotter()
        >>> _ = plotter.add_mesh(sphere)
        >>> plotter.scalar_bars
        Scalar Bar Title     Interactive
        "Data"               False

        Select a scalar bar actor based on the title of the bar.

        >>> plotter.scalar_bars['Data']
        <vtkmodules.vtkRenderingAnnotation.vtkScalarBarActor(...) at ...>

        """
        return self._scalar_bars

    @property
    def _before_close_callback(self):
        """Return the cached function (expecting a reference)."""
        if self.__before_close_callback is not None:
            return self.__before_close_callback()

    @_before_close_callback.setter
    def _before_close_callback(self, func):
        """Store a weakref.ref of the function being called."""
        if func is not None:
            self.__before_close_callback = weakref.ref(func)
        else:
            self.__before_close_callback = None

    @property
    def shape(self):  # numpydoc ignore=RT01
        """Return the shape of the plotter.

        Returns
        -------
        tuple[numpy.int32, numpy.int32]
            Shape of the plotter.

        Examples
        --------
        Return the plotter shape.

        >>> import pyvista as pv
        >>> plotter = pv.Plotter(shape=(2, 2))
        >>> plotter.shape
        (2, 2)
        """
        return self.renderers._shape

    @property
    def renderer(self):  # numpydoc ignore=RT01
        """Return the active renderer.

        Returns
        -------
        pyvista.Renderer
            Active render.

        Examples
        --------
        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> pl.renderer
        <Renderer(...) at ...>

        """
        return self.renderers.active_renderer

    def subplot(self, index_row, index_column=None):
        """Set the active subplot.

        Parameters
        ----------
        index_row : int
            Index of the subplot to activate along the rows.

        index_column : int, optional
            Index of the subplot to activate along the columns.

        Examples
        --------
        Create a 2 wide plot and set the background of right-hand plot
        to orange.  Add a cube to the left plot and a sphere to the
        right.

        >>> import pyvista as pv
        >>> pl = pv.Plotter(shape=(1, 2))
        >>> actor = pl.add_mesh(pv.Cube())
        >>> pl.subplot(0, 1)
        >>> actor = pl.add_mesh(pv.Sphere())
        >>> pl.set_background('orange', all_renderers=False)
        >>> pl.show()

        """
        self.renderers.set_active_renderer(index_row, index_column)

    @wraps(Renderer.add_ruler)
    def add_ruler(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.add_ruler``."""
        return self.renderer.add_ruler(*args, **kwargs)

    @wraps(Renderer.add_legend_scale)
    def add_legend_scale(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.add_legend_scale``."""
        return self.renderer.add_legend_scale(*args, **kwargs)

    @wraps(Renderer.add_legend)
    def add_legend(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.add_legend``."""
        return self.renderer.add_legend(*args, **kwargs)

    @wraps(Renderer.remove_legend)
    def remove_legend(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.remove_legend``."""
        return self.renderer.remove_legend(*args, **kwargs)

    @property
    def legend(self):  # numpydoc ignore=RT01
        """Legend actor.

        There can only be one legend actor per renderer.  If
        ``legend`` is ``None``, there is no legend actor.

        Returns
        -------
        vtk.vtkLegendBoxActor
            Legend actor.

        """
        return self.renderer.legend

    @wraps(Renderer.add_floor)
    def add_floor(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.add_floor``."""
        return self.renderer.add_floor(*args, **kwargs)

    @wraps(Renderer.remove_floors)
    def remove_floors(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.remove_floors``."""
        return self.renderer.remove_floors(*args, **kwargs)

    def enable_3_lights(self, only_active=False):
        """Enable 3-lights illumination.

        This will replace all pre-existing lights in the scene.

        Parameters
        ----------
        only_active : bool, default: False
            If ``True``, only change the active renderer. The default
            is that every renderer is affected.

        Examples
        --------
        >>> from pyvista import demos
        >>> pl = demos.orientation_plotter()
        >>> pl.enable_3_lights()
        >>> pl.show()

        Note how this varies from the default plotting.

        >>> pl = demos.orientation_plotter()
        >>> pl.show()

        """

        def _to_pos(elevation, azimuth):
            theta = azimuth * np.pi / 180.0
            phi = (90.0 - elevation) * np.pi / 180.0
            x = np.sin(theta) * np.sin(phi)
            y = np.cos(phi)
            z = np.cos(theta) * np.sin(phi)
            return x, y, z

        renderers = [self.renderer] if only_active else self.renderers
        for renderer in renderers:
            renderer.remove_all_lights()

        # Inspired from Mayavi's version of Raymond Maple 3-lights illumination
        intensities = [1, 0.6, 0.5]
        all_angles = [(45.0, 45.0), (-30.0, -60.0), (-30.0, 60.0)]
        for intensity, angles in zip(intensities, all_angles):
            light = pyvista.Light(light_type='camera light')
            light.intensity = intensity
            light.position = _to_pos(*angles)
            for renderer in renderers:
                renderer.add_light(light)

    def disable_3_lights(self):
        """Please use ``enable_lightkit``, this method has been deprecated."""
        from pyvista.core.errors import DeprecationError

        raise DeprecationError('DEPRECATED: Please use ``enable_lightkit``')

    def enable_lightkit(self, only_active=False):
        """Enable the default light-kit lighting.

        See:
        https://www.researchgate.net/publication/2926068_LightKit_A_lighting_system_for_effective_visualization

        This will replace all pre-existing lights in the renderer.

        Parameters
        ----------
        only_active : bool, default: False
            If ``True``, only change the active renderer. The default is that
            every renderer is affected.

        Examples
        --------
        Create a plotter without any lights and then enable the
        default light kit.

        >>> import pyvista as pv
        >>> pl = pv.Plotter(lighting=None)
        >>> pl.enable_lightkit()
        >>> actor = pl.add_mesh(pv.Cube(), show_edges=True)
        >>> pl.show()

        """
        renderers = [self.renderer] if only_active else self.renderers

        light_kit = _vtk.vtkLightKit()
        for renderer in renderers:
            renderer.remove_all_lights()
            # Use the renderer as a vtkLightKit parser.
            # Feed it the LightKit, pop off the vtkLights, put back
            # pyvista Lights. This is the price we must pay for using
            # inheritance rather than composition.
            light_kit.AddLightsToRenderer(renderer)
            vtk_lights = renderer.lights
            renderer.remove_all_lights()
            for vtk_light in vtk_lights:
                light = pyvista.Light.from_vtk(vtk_light)
                renderer.add_light(light)
            renderer.LightFollowCameraOn()

    def enable_anti_aliasing(self, aa_type='ssaa', multi_samples=None, all_renderers=True):
        """Enable anti-aliasing.

        This tends to make edges appear softer and less pixelated.

        Parameters
        ----------
        aa_type : str, default: "ssaa"
            Anti-aliasing type. See the notes below. One of the following:

            * ``"ssaa"`` - Super-Sample Anti-Aliasing
            * ``"msaa"`` - Multi-Sample Anti-Aliasing
            * ``"fxaa"`` - Fast Approximate Anti-Aliasing

        multi_samples : int, optional
            The number of multi-samples when ``aa_type`` is ``"msaa"``. Note
            that using this setting automatically enables this for all
            renderers. Defaults to the theme multi_samples.

        all_renderers : bool, default: True
            If ``True``, applies to all renderers in subplots. If ``False``,
            then only applies to the active renderer.

        Notes
        -----
        SSAA, or Super-Sample Anti-Aliasing is a brute force method of
        anti-aliasing. It results in the best image quality but comes at a
        tremendous resource cost. SSAA works by rendering the scene at a higher
        resolution. The final image is produced by downsampling the
        massive source image using an averaging filter. This acts as a low pass
        filter which removes the high frequency components that would cause
        jaggedness.

        MSAA, or Multi-Sample Anti-Aliasing is an optimization of SSAA that
        reduces the amount of pixel shader evaluations that need to be computed
        by focusing on overlapping regions of the scene. The result is
        anti-aliasing along edges that is on par with SSAA and less
        anti-aliasing along surfaces as these make up the bulk of SSAA
        computations. MSAA is substantially less computationally expensive than
        SSAA and results in comparable image quality.

        FXAA, or Fast Approximate Anti-Aliasing is an Anti-Aliasing technique
        that is performed entirely in post processing. FXAA operates on the
        rasterized image rather than the scene geometry. As a consequence,
        forcing FXAA or using FXAA incorrectly can result in the FXAA filter
        smoothing out parts of the visual overlay that are usually kept sharp
        for reasons of clarity as well as smoothing out textures. FXAA is
        inferior to MSAA but is almost free computationally and is thus
        desirable on low end platforms.

        Examples
        --------
        Enable super-sample anti-aliasing (SSAA).

        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> pl.enable_anti_aliasing('ssaa')
        >>> _ = pl.add_mesh(pv.Sphere(), show_edges=True)
        >>> pl.show()

        See :ref:`anti_aliasing_example` for a full example demonstrating
        VTK's anti-aliasing approaches.

        """
        # apply MSAA to entire render window
        if aa_type == 'msaa':
            if self.render_window is None:
                raise AttributeError('The render window has been closed.')
            if multi_samples is None:
                multi_samples = self._theme.multi_samples
            self.render_window.SetMultiSamples(multi_samples)
            return
        elif aa_type not in ['ssaa', 'fxaa']:
            raise ValueError(
                f'Invalid `aa_type` "{aa_type}". Should be either "fxaa", "ssaa", or "msaa"'
            )
        else:
            # disable MSAA as SSAA or FXAA is being enabled
            self.render_window.SetMultiSamples(0)

        if all_renderers:
            for renderer in self.renderers:
                renderer.enable_anti_aliasing(aa_type)
        else:
            self.renderer.enable_anti_aliasing(aa_type)

    def disable_anti_aliasing(self, all_renderers=True):
        """Disable anti-aliasing.

        Parameters
        ----------
        all_renderers : bool, default: True
            If ``True``, applies to all renderers in subplots. If ``False``,
            then only applies to the active renderer.

        Examples
        --------
        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> pl.disable_anti_aliasing()
        >>> _ = pl.add_mesh(pv.Sphere(), show_edges=True)
        >>> pl.show()

        See :ref:`anti_aliasing_example` for a full example demonstrating
        VTK's anti-aliasing approaches.

        """
        self.render_window.SetMultiSamples(0)

        if all_renderers:
            for renderer in self.renderers:
                renderer.disable_anti_aliasing()
        else:
            self.renderer.disable_anti_aliasing()

    @wraps(Renderer.set_focus)
    def set_focus(self, *args, render=True, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.set_focus``."""
        log.debug('set_focus: %s, %s', str(args), str(kwargs))
        self.renderer.set_focus(*args, **kwargs)
        if render:
            self.render()

    @wraps(Renderer.set_position)
    def set_position(self, *args, render=True, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.set_position``."""
        self.renderer.set_position(*args, **kwargs)
        if render:
            self.render()

    @wraps(Renderer.set_viewup)
    def set_viewup(self, *args, render=True, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.set_viewup``."""
        self.renderer.set_viewup(*args, **kwargs)
        if render:
            self.render()

    @wraps(Renderer.add_orientation_widget)
    def add_orientation_widget(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.add_orientation_widget``."""
        return self.renderer.add_orientation_widget(*args, **kwargs)

    @wraps(Renderer.add_axes)
    def add_axes(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.add_axes``."""
        return self.renderer.add_axes(*args, **kwargs)

    @wraps(Renderer.hide_axes)
    def hide_axes(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.hide_axes``."""
        return self.renderer.hide_axes(*args, **kwargs)

    @wraps(Renderer.show_axes)
    def show_axes(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.show_axes``."""
        return self.renderer.show_axes(*args, **kwargs)

    @wraps(Renderer.update_bounds_axes)
    def update_bounds_axes(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.update_bounds_axes``."""
        return self.renderer.update_bounds_axes(*args, **kwargs)

    @wraps(Renderer.add_chart)
    def add_chart(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.add_chart``."""
        return self.renderer.add_chart(*args, **kwargs)

    @wraps(Renderer.remove_chart)
    def remove_chart(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.remove_chart``."""
        return self.renderer.remove_chart(*args, **kwargs)

    @wraps(Renderers.set_chart_interaction)
    def set_chart_interaction(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderers.set_chart_interaction``."""
        return self.renderers.set_chart_interaction(*args, **kwargs)

    @wraps(Renderer.add_actor)
    def add_actor(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.add_actor``."""
        return self.renderer.add_actor(*args, **kwargs)

    @wraps(Renderer.enable_parallel_projection)
    def enable_parallel_projection(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.enable_parallel_projection``."""
        return self.renderer.enable_parallel_projection(*args, **kwargs)

    @wraps(Renderer.disable_parallel_projection)
    def disable_parallel_projection(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.disable_parallel_projection``."""
        return self.renderer.disable_parallel_projection(*args, **kwargs)

    @wraps(Renderer.enable_ssao)
    def enable_ssao(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.enable_ssao``."""
        return self.renderer.enable_ssao(*args, **kwargs)

    @wraps(Renderer.disable_ssao)
    def disable_ssao(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.disable_ssao``."""
        return self.renderer.disable_ssao(*args, **kwargs)

    @wraps(Renderer.enable_shadows)
    def enable_shadows(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.enable_shadows``."""
        return self.renderer.enable_shadows(*args, **kwargs)

    @wraps(Renderer.disable_shadows)
    def disable_shadows(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.disable_shadows``."""
        return self.renderer.disable_shadows(*args, **kwargs)

    @property
    def parallel_projection(self):  # numpydoc ignore=RT01
        """Return or set parallel projection state of active render window."""
        return self.renderer.parallel_projection

    @parallel_projection.setter
    def parallel_projection(self, state):  # numpydoc ignore=GL08
        self.renderer.parallel_projection = state

    @property
    def parallel_scale(self):  # numpydoc ignore=RT01
        """Return or set parallel scale of active render window."""
        return self.renderer.parallel_scale

    @parallel_scale.setter
    def parallel_scale(self, value):  # numpydoc ignore=GL08
        self.renderer.parallel_scale = value

    @wraps(Renderer.add_axes_at_origin)
    def add_axes_at_origin(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.add_axes_at_origin``."""
        return self.renderer.add_axes_at_origin(*args, **kwargs)

    @wraps(Renderer.show_bounds)
    def show_bounds(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.show_bounds``."""
        return self.renderer.show_bounds(*args, **kwargs)

    @wraps(Renderer.add_bounding_box)
    def add_bounding_box(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.add_bounding_box``."""
        return self.renderer.add_bounding_box(*args, **kwargs)

    @wraps(Renderer.remove_bounding_box)
    def remove_bounding_box(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.remove_bounding_box``."""
        return self.renderer.remove_bounding_box(*args, **kwargs)

    @wraps(Renderer.remove_bounds_axes)
    def remove_bounds_axes(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.remove_bounds_axes``."""
        return self.renderer.remove_bounds_axes(*args, **kwargs)

    @wraps(Renderer.show_grid)
    def show_grid(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.show_grid``."""
        return self.renderer.show_grid(*args, **kwargs)

    @wraps(Renderer.set_scale)
    def set_scale(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.set_scale``."""
        return self.renderer.set_scale(*args, **kwargs)

    @wraps(Renderer.enable_depth_of_field)
    def enable_depth_of_field(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.enable_depth_of_field``."""
        return self.renderer.enable_depth_of_field(*args, **kwargs)

    @wraps(Renderer.disable_depth_of_field)
    def disable_depth_of_field(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.disable_depth_of_field``."""
        return self.renderer.disable_depth_of_field(*args, **kwargs)

    @wraps(Renderer.add_blurring)
    def add_blurring(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.add_blurring``."""
        return self.renderer.add_blurring(*args, **kwargs)

    @wraps(Renderer.remove_blurring)
    def remove_blurring(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.remove_blurring``."""
        return self.renderer.remove_blurring(*args, **kwargs)

    @wraps(Renderer.enable_eye_dome_lighting)
    def enable_eye_dome_lighting(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.enable_eye_dome_lighting``."""
        return self.renderer.enable_eye_dome_lighting(*args, **kwargs)

    @wraps(Renderer.disable_eye_dome_lighting)
    def disable_eye_dome_lighting(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.disable_eye_dome_lighting``."""
        self.renderer.disable_eye_dome_lighting(*args, **kwargs)

    @wraps(Renderer.reset_camera)
    def reset_camera(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.reset_camera``."""
        self.renderer.reset_camera(*args, **kwargs)
        self.render()

    @wraps(Renderer.isometric_view)
    def isometric_view(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.isometric_view``."""
        self.renderer.isometric_view(*args, **kwargs)

    @wraps(Renderer.view_isometric)
    def view_isometric(self, *args, **kwarg):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.view_isometric``."""
        self.renderer.view_isometric(*args, **kwarg)

    @wraps(Renderer.view_vector)
    def view_vector(self, *args, **kwarg):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.view_vector``."""
        self.renderer.view_vector(*args, **kwarg)

    @wraps(Renderer.view_xy)
    def view_xy(self, *args, **kwarg):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.view_xy``."""
        self.renderer.view_xy(*args, **kwarg)

    @wraps(Renderer.view_yx)
    def view_yx(self, *args, **kwarg):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.view_yx``."""
        self.renderer.view_yx(*args, **kwarg)

    @wraps(Renderer.view_xz)
    def view_xz(self, *args, **kwarg):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.view_xz``."""
        self.renderer.view_xz(*args, **kwarg)

    @wraps(Renderer.view_zx)
    def view_zx(self, *args, **kwarg):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.view_zx``."""
        self.renderer.view_zx(*args, **kwarg)

    @wraps(Renderer.view_yz)
    def view_yz(self, *args, **kwarg):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.view_yz``."""
        self.renderer.view_yz(*args, **kwarg)

    @wraps(Renderer.view_zy)
    def view_zy(self, *args, **kwarg):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.view_zy``."""
        self.renderer.view_zy(*args, **kwarg)

    @wraps(Renderer.disable)
    def disable(self, *args, **kwarg):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.disable``."""
        self.renderer.disable(*args, **kwarg)

    @wraps(Renderer.enable)
    def enable(self, *args, **kwarg):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.enable``."""
        self.renderer.enable(*args, **kwarg)

    @wraps(Renderer.enable_depth_peeling)
    def enable_depth_peeling(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.enable_depth_peeling``."""
        if self.render_window is not None:
            result = self.renderer.enable_depth_peeling(*args, **kwargs)
            if result:
                self.render_window.AlphaBitPlanesOn()
            return result

    @wraps(Renderer.disable_depth_peeling)
    def disable_depth_peeling(self):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.disable_depth_peeling``."""
        if self.render_window is not None:
            self.render_window.AlphaBitPlanesOff()
            return self.renderer.disable_depth_peeling()

    @wraps(Renderer.get_default_cam_pos)
    def get_default_cam_pos(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.get_default_cam_pos``."""
        return self.renderer.get_default_cam_pos(*args, **kwargs)

    @wraps(Renderer.remove_actor)
    def remove_actor(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.remove_actor``."""
        for renderer in self.renderers:
            renderer.remove_actor(*args, **kwargs)
        return True

    @wraps(Renderer.set_environment_texture)
    def set_environment_texture(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.set_environment_texture``."""
        return self.renderer.set_environment_texture(*args, **kwargs)

    @wraps(Renderer.remove_environment_texture)
    def remove_environment_texture(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderer.remove_environment_texture``."""
        return self.renderer.remove_environment_texture(*args, **kwargs)

    #### Properties from Renderer ####

    @property
    def actors(self):  # numpydoc ignore=RT01
        """Return the actors of the active renderer.

        Returns
        -------
        dict
            Dictionary of active actors.

        """
        return self.renderer.actors

    @property
    def camera(self):  # numpydoc ignore=RT01
        """Return the active camera of the active renderer.

        Returns
        -------
        pyvista.Camera
            Camera from the active renderer.

        """
        if not self.renderer.camera.is_set:
            self.camera_position = self.get_default_cam_pos()
            self.reset_camera()
            self.renderer.camera.is_set = True
        return self.renderer.camera

    @camera.setter
    def camera(self, camera):  # numpydoc ignore=GL08
        self.renderer.camera = camera

    @property
    def camera_set(self):  # numpydoc ignore=RT01
        """Return or set if the camera of the active renderer has been set."""
        return self.renderer.camera.is_set

    @camera_set.setter
    def camera_set(self, is_set):  # numpydoc ignore=GL08
        self.renderer.camera.is_set = is_set

    @property
    def bounds(self) -> BoundsLike:  # numpydoc ignore=RT01
        """Return the bounds of the active renderer.

        Returns
        -------
        tuple[numpy.float64, numpy.float64, numpy.float64, numpy.float64, numpy.float64, numpy.float64]
            Bounds of the active renderer.

        Examples
        --------
        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> _ = pl.add_mesh(pv.Cube())
        >>> pl.bounds
        (-0.5, 0.5, -0.5, 0.5, -0.5, 0.5)

        """
        return self.renderer.bounds

    @property
    def length(self):  # numpydoc ignore=RT01
        """Return the length of the diagonal of the bounding box of the scene."""
        return self.renderer.length

    @property
    def center(self):  # numpydoc ignore=RT01
        """Return the center of the active renderer.

        Returns
        -------
        list[numpy.float64, numpy.float64, numpy.float64]
            Center of the active renderer.

        Examples
        --------
        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> _ = pl.add_mesh(pv.Cube())
        >>> pl.center
        [0.0, 0.0, 0.0]

        """
        return self.renderer.center

    @property
    def _scalar_bar_slots(self):
        """Return the scalar bar slots of the active renderer."""
        return self.renderer._scalar_bar_slots

    @_scalar_bar_slots.setter
    def _scalar_bar_slots(self, value):
        """Set the scalar bar slots of the active renderer."""
        self.renderer._scalar_bar_slots = value

    @property
    def _scalar_bar_slot_lookup(self):
        """Return the scalar bar slot lookup of the active renderer."""
        return self.renderer._scalar_bar_slot_lookup

    @_scalar_bar_slot_lookup.setter
    def _scalar_bar_slot_lookup(self, value):
        self.renderer._scalar_bar_slot_lookup = value

    @property
    def scale(self):  # numpydoc ignore=RT01
        """Return the scaling of the active renderer."""
        return self.renderer.scale

    @scale.setter
    def scale(self, scale):  # numpydoc ignore=GL08
        self.renderer.set_scale(*scale)

    @property
    def camera_position(self):  # numpydoc ignore=RT01
        """Return camera position of the active render window.

        Examples
        --------
        Return camera's position and then reposition it via a list of tuples.

        >>> import pyvista as pv
        >>> from pyvista import examples
        >>> mesh = examples.download_bunny_coarse()
        >>> pl = pv.Plotter()
        >>> _ = pl.add_mesh(mesh, show_edges=True, reset_camera=True)
        >>> pl.camera_position
        [(0.02430, 0.0336, 0.9446),
         (0.02430, 0.0336, -0.02225),
         (0.0, 1.0, 0.0)]
        >>> pl.camera_position = [
        ...     (0.3914, 0.4542, 0.7670),
        ...     (0.0243, 0.0336, -0.0222),
        ...     (-0.2148, 0.8998, -0.3796),
        ... ]
        >>> pl.show()

        Set the camera position using a string and look at the ``'xy'`` plane.

        >>> pl = pv.Plotter()
        >>> _ = pl.add_mesh(mesh, show_edges=True)
        >>> pl.camera_position = 'xy'
        >>> pl.show()

        Set the camera position using a string and look at the ``'zy'`` plane.

        >>> pl = pv.Plotter()
        >>> _ = pl.add_mesh(mesh, show_edges=True)
        >>> pl.camera_position = 'zy'
        >>> pl.show()

        For more examples, see :ref:`cameras_api`.

        """
        return self.renderer.camera_position

    @camera_position.setter
    def camera_position(self, camera_location):  # numpydoc ignore=GL08
        self.renderer.camera_position = camera_location

    @property
    def background_color(self):  # numpydoc ignore=RT01
        """Return the background color of the active render window.

        Examples
        --------
        Set the background color to ``"pink"`` and plot it.

        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> _ = pl.add_mesh(pv.Cube(), show_edges=True)
        >>> pl.background_color = "pink"
        >>> pl.background_color
        Color(name='pink', hex='#ffc0cbff', opacity=255)
        >>> pl.show()

        """
        return self.renderers.active_renderer.background_color

    @background_color.setter
    def background_color(self, color):  # numpydoc ignore=GL08
        self.set_background(color)

    @property
    def window_size(self):  # numpydoc ignore=RT01
        """Return the render window size in ``(width, height)``.

        Examples
        --------
        Change the window size from ``200 x 200`` to ``400 x 400``.

        >>> import pyvista as pv
        >>> pl = pv.Plotter(window_size=[200, 200])
        >>> pl.window_size
        [200, 200]
        >>> pl.window_size = [400, 400]
        >>> pl.window_size
        [400, 400]

        """
        return list(self.render_window.GetSize())

    @window_size.setter
    def window_size(self, window_size):  # numpydoc ignore=GL08
        self.render_window.SetSize(window_size[0], window_size[1])
        self._window_size_unset = False
        self.render()

    @contextmanager
    def window_size_context(self, window_size=None):
        """Set the render window size in an isolated context.

        Parameters
        ----------
        window_size : sequence[int], optional
            Window size in pixels.  Defaults to :attr:`pyvista.Plotter.window_size`.

        Examples
        --------
        Take two different screenshots with two different window sizes.

        >>> import pyvista as pv
        >>> pl = pv.Plotter(off_screen=True)
        >>> _ = pl.add_mesh(pv.Cube())
        >>> with pl.window_size_context((400, 400)):
        ...     pl.screenshot('/tmp/small_screenshot.png')  # doctest:+SKIP
        ...
        >>> with pl.window_size_context((1000, 1000)):
        ...     pl.screenshot('/tmp/big_screenshot.png')  # doctest:+SKIP
        ...

        """
        # No op if not set
        if window_size is None:
            yield self
            return
        # If render window is not current
        if self.render_window is None:
            warnings.warn('Attempting to set window_size on an unavailable render widow.')
            yield self
            return
        size_before = self.window_size
        if window_size is not None:
            self.window_size = window_size
        try:
            yield self
        finally:
            # Sometimes the render window is destroyed within the context
            # and re-setting will fail
            if self.render_window is not None:
                self.window_size = size_before

    @property
    def image_depth(self):  # numpydoc ignore=RT01
        """Return a depth image representing current render window.

        Helper attribute for ``get_image_depth``.

        """
        return self.get_image_depth()

    def _check_rendered(self):
        """Check if the render window has been shown and raise an exception if not."""
        if not self._rendered:
            raise AttributeError(
                '\nThis plotter has not yet been set up and rendered '
                'with ``show()``.\n'
                'Consider setting ``off_screen=True`` '
                'for off screen rendering.\n'
            )

    def _check_has_ren_win(self):
        """Check if render window attribute exists and raise an exception if not."""
        if self.render_window is None:
            raise RenderWindowUnavailable('Render window is not available.')
        if not self.render_window.IsCurrent():
            raise RenderWindowUnavailable('Render window is not current.')

    def _make_render_window_current(self):
        if self.render_window is None:
            raise RenderWindowUnavailable('Render window is not available.')
        self.render_window.MakeCurrent()  # pragma: no cover

    @property
    def image(self):  # numpydoc ignore=RT01
        """Return an image array of current render window.

        Returns
        -------
        pyvista.pyvista_ndarray
            Image array of current render window.

        Examples
        --------
        >>> import pyvista as pv
        >>> pl = pv.Plotter(off_screen=True)
        >>> _ = pl.add_mesh(pv.Cube())
        >>> pl.show()
        >>> pl.image  # doctest:+SKIP

        """
        if self.render_window is None and self.last_image is not None:
            return self.last_image

        self._check_rendered()
        self._check_has_ren_win()

        data = image_from_window(self.render_window, scale=self.image_scale)
        if self.image_transparent_background:
            return data

        # ignore alpha channel
        return data[:, :, :-1]

    @property
    def image_scale(self) -> int:  # numpydoc ignore=RT01
        """Get or set the scale factor when saving a screenshot.

        This will scale up the screenshots taken of the render window to save a
        higher resolution image than what is rendered on screen.

        Image sizes will be the :py:attr:`window_size
        <pyvista.Plotter.window_size>` multiplied by this scale factor.

        Returns
        -------
        int
            Image scale factor.

        Examples
        --------
        Double the resolution of a screenshot.

        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> _ = pl.add_mesh(pv.Sphere())
        >>> pl.image_scale = 2
        >>> pl.screenshot('screenshot.png')  # doctest:+SKIP

        Set the image scale from ``Plotter``.

        >>> import pyvista as pv
        >>> pl = pv.Plotter(image_scale=2)
        >>> _ = pl.add_mesh(pv.Sphere())
        >>> pl.screenshot('screenshot.png')  # doctest:+SKIP

        """
        return self._image_scale

    @image_scale.setter
    def image_scale(self, value: int):  # numpydoc ignore=GL08
        value = int(value)
        if value < 1:
            raise ValueError('Scale factor must be a positive integer.')
        self._image_scale = value

    @contextmanager
    def image_scale_context(self, scale: Optional[int] = None):
        """Set the image scale in an isolated context.

        Parameters
        ----------
        scale : int, optional
            Integer scale factor.  Defaults to :attr:`pyvista.Plotter.image_scale`.

        """
        scale_before = self.image_scale
        if scale is not None:
            self.image_scale = scale
        try:
            yield self
        finally:
            self.image_scale = scale_before

    def render(self):
        """Render the main window.

        Will not render until ``show`` has been called.

        Any render callbacks added with
        :func:`add_on_render_callback() <pyvista.Plotter.add_on_render_callback>`
        and the ``render_event=False`` option set will still execute on any call.
        """
        if self.render_window is not None and not self._first_time and not self._suppress_rendering:
            log.debug('Rendering')
            self.renderers.on_plotter_render()
            self.render_window.Render()
            self._rendered = True
        for callback in self._on_render_callbacks:
            callback(self)

    def add_on_render_callback(self, callback, render_event=False):
        """Add a method to be called post-render.

        Parameters
        ----------
        callback : callable
            The callback method to run post-render. This takes a single
            argument which is the plotter object.

        render_event : bool, default: False
            If ``True``, associate with all VTK RenderEvents. Otherwise, the
            callback is only handled on a successful ``render()`` from the
            PyVista plotter directly.

        """
        if render_event:
            for renderer in self.renderers:
                renderer.AddObserver(_vtk.vtkCommand.RenderEvent, lambda *args: callback(self))
        else:
            self._on_render_callbacks.add(callback)

    def clear_on_render_callbacks(self):
        """Clear all callback methods previously registered with ``render()``."""
        for renderer in self.renderers:
            renderer.RemoveObservers(_vtk.vtkCommand.RenderEvent)
        self._on_render_callbacks = set()

    @wraps(RenderWindowInteractor.add_key_event)
    def add_key_event(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap RenderWindowInteractor.add_key_event."""
        if hasattr(self, 'iren'):
            self.iren.add_key_event(*args, **kwargs)

    @wraps(RenderWindowInteractor.add_timer_event)
    def add_timer_event(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap RenderWindowInteractor.add_timer_event."""
        if hasattr(self, 'iren'):
            self.iren.add_timer_event(*args, **kwargs)

    @wraps(RenderWindowInteractor.clear_events_for_key)
    def clear_events_for_key(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap RenderWindowInteractor.clear_events_for_key."""
        if hasattr(self, 'iren'):
            self.iren.clear_events_for_key(*args, **kwargs)

    def store_mouse_position(self, *args):
        """Store mouse position."""
        if not hasattr(self, "iren"):
            raise AttributeError("This plotting window is not interactive.")
        self.mouse_position = self.iren.get_event_position()

    def store_click_position(self, *args):
        """Store click position in viewport coordinates."""
        if not hasattr(self, "iren"):
            raise AttributeError("This plotting window is not interactive.")
        self.click_position = self.iren.get_event_position()
        self.mouse_position = self.click_position

    def track_mouse_position(self):
        """Keep track of the mouse position.

        This will potentially slow down the interactor. No callbacks
        supported here - use
        :func:`pyvista.Plotter.track_click_position` instead.

        """
        self.iren.track_mouse_position(self.store_mouse_position)

    def untrack_mouse_position(self):
        """Stop tracking the mouse position."""
        self.iren.untrack_mouse_position()

    @wraps(RenderWindowInteractor.track_click_position)
    def track_click_position(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap RenderWindowInteractor.track_click_position."""
        self.iren.track_click_position(*args, **kwargs)

    @wraps(RenderWindowInteractor.untrack_click_position)
    def untrack_click_position(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Stop tracking the click position."""
        self.iren.untrack_click_position(*args, **kwargs)

    @property
    def pickable_actors(self):  # numpydoc ignore=RT01
        """Return or set the pickable actors.

        When setting, this will be the list of actors to make
        pickable. All actors not in the list will be made unpickable.
        If ``actors`` is ``None``, all actors will be made unpickable.

        Returns
        -------
        list[pyvista.Actor]
            List of actors.

        Examples
        --------
        Add two actors to a :class:`pyvista.Plotter`, make one
        pickable, and then list the pickable actors.

        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> sphere_actor = pl.add_mesh(pv.Sphere())
        >>> cube_actor = pl.add_mesh(
        ...     pv.Cube(), pickable=False, style='wireframe'
        ... )
        >>> len(pl.pickable_actors)
        1

        Set the pickable actors to both actors.

        >>> pl.pickable_actors = [sphere_actor, cube_actor]
        >>> len(pl.pickable_actors)
        2

        Set the pickable actors to ``None``.

        >>> pl.pickable_actors = None
        >>> len(pl.pickable_actors)
        0

        """
        pickable = []
        for renderer in self.renderers:
            for actor in renderer.actors.values():
                if actor.GetPickable():
                    pickable.append(actor)
        return pickable

    @pickable_actors.setter
    def pickable_actors(self, actors=None):  # numpydoc ignore=GL08
        actors = [] if actors is None else actors
        if isinstance(actors, _vtk.vtkActor):
            actors = [actors]

        if not all([isinstance(actor, _vtk.vtkActor) for actor in actors]):
            raise TypeError(
                f'Expected a vtkActor instance or a list of vtkActors, got '
                f'{[type(actor) for actor in actors]} instead.'
            )

        for renderer in self.renderers:
            for actor in renderer.actors.values():
                actor.SetPickable(actor in actors)

    def _prep_for_close(self):
        """Make sure a screenshot is acquired before closing.

        This doesn't actually close anything. It just preps the plotter for
        closing.
        """
        # Grab screenshot right before renderer closes
        self.last_image = self.screenshot(True, return_img=True)
        self.last_image_depth = self.get_image_depth()

    def increment_point_size_and_line_width(self, increment):
        """Increment point size and line width of all actors.

        For every actor in the scene, increment both its point size
        and line width by the given value.

        Parameters
        ----------
        increment : float
            Amount to increment point size and line width.

        """
        for renderer in self.renderers:
            for actor in renderer._actors.values():
                if hasattr(actor, "GetProperty"):
                    prop = actor.GetProperty()
                    if hasattr(prop, "SetPointSize"):
                        prop.SetPointSize(prop.GetPointSize() + increment)
                    if hasattr(prop, "SetLineWidth"):
                        prop.SetLineWidth(prop.GetLineWidth() + increment)
        self.render()
        return

    def zoom_camera(self, value):
        """Zoom of the camera and render.

        Parameters
        ----------
        value : float or str
            Zoom of the camera. If a float, must be greater than 0. Otherwise,
            if a string, must be ``"tight"``. If tight, the plot will be zoomed
            such that the actors fill the entire viewport.

        """
        self.camera.zoom(value)
        self.render()
        return

    def reset_key_events(self):
        """Reset all of the key press events to their defaults."""
        if not hasattr(self, 'iren'):
            return

        self.iren.clear_key_event_callbacks()

        self.add_key_event('q', self._prep_for_close)  # Add no matter what
        b_left_down_callback = lambda: self.iren.add_observer(
            'LeftButtonPressEvent', self.left_button_down
        )
        self.add_key_event('b', b_left_down_callback)
        self.add_key_event('v', lambda: self.isometric_view_interactive())
        self.add_key_event('C', lambda: self.enable_cell_picking())
        self.add_key_event('Up', lambda: self.zoom_camera(1.05))
        self.add_key_event('Down', lambda: self.zoom_camera(0.95))
        self.add_key_event('plus', lambda: self.increment_point_size_and_line_width(1))
        self.add_key_event('minus', lambda: self.increment_point_size_and_line_width(-1))

    @wraps(RenderWindowInteractor.key_press_event)
    def key_press_event(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap RenderWindowInteractor.key_press_event."""
        self.iren.key_press_event(*args, **kwargs)

    def left_button_down(self, obj, event_type):
        """Register the event for a left button down click."""
        if hasattr(self.render_window, 'GetOffScreenFramebuffer'):
            if not self.render_window.GetOffScreenFramebuffer().GetFBOIndex():
                # must raise a runtime error as this causes a segfault on VTK9
                raise ValueError('Invoking helper with no framebuffer')
        # Get 2D click location on window
        click_pos = self.iren.get_event_position()

        # Get corresponding click location in the 3D plot
        picker = _vtk.vtkWorldPointPicker()
        picker.Pick(click_pos[0], click_pos[1], 0, self.renderer)
        self.pickpoint = np.asarray(picker.GetPickPosition()).reshape((-1, 3))
        if np.any(np.isnan(self.pickpoint)):
            self.pickpoint[:] = 0

    @wraps(RenderWindowInteractor.enable_trackball_style)
    def enable_trackball_style(self):  # numpydoc ignore=PR01,RT01
        """Wrap RenderWindowInteractor.enable_trackball_style."""
        self.iren.enable_trackball_style()

    @wraps(RenderWindowInteractor.enable_trackball_actor_style)
    def enable_trackball_actor_style(self):  # numpydoc ignore=PR01,RT01
        """Wrap RenderWindowInteractor.enable_trackball_actor_style."""
        self.iren.enable_trackball_actor_style()

    @wraps(RenderWindowInteractor.enable_image_style)
    def enable_image_style(self):  # numpydoc ignore=PR01,RT01
        """Wrap RenderWindowInteractor.enable_image_style."""
        self.iren.enable_image_style()

    @wraps(RenderWindowInteractor.enable_joystick_style)
    def enable_joystick_style(self):  # numpydoc ignore=PR01,RT01
        """Wrap RenderWindowInteractor.enable_joystick_style."""
        self.iren.enable_joystick_style()

    @wraps(RenderWindowInteractor.enable_joystick_actor_style)
    def enable_joystick_actor_style(self):  # numpydoc ignore=PR01,RT01
        """Wrap RenderWindowInteractor.enable_joystick_actor_style."""
        self.iren.enable_joystick_actor_style()

    @wraps(RenderWindowInteractor.enable_zoom_style)
    def enable_zoom_style(self):  # numpydoc ignore=PR01,RT01
        """Wrap RenderWindowInteractor.enable_zoom_style."""
        self.iren.enable_zoom_style()

    @wraps(RenderWindowInteractor.enable_terrain_style)
    def enable_terrain_style(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap RenderWindowInteractor.enable_terrain_style."""
        self.iren.enable_terrain_style(*args, **kwargs)

    @wraps(RenderWindowInteractor.enable_rubber_band_style)
    def enable_rubber_band_style(self):  # numpydoc ignore=PR01,RT01
        """Wrap RenderWindowInteractor.enable_rubber_band_style."""
        self.iren.enable_rubber_band_style()

    @wraps(RenderWindowInteractor.enable_rubber_band_2d_style)
    def enable_rubber_band_2d_style(self):  # numpydoc ignore=PR01,RT01
        """Wrap RenderWindowInteractor.enable_rubber_band_2d_style."""
        self.iren.enable_rubber_band_2d_style()

    def enable_stereo_render(self):
        """Enable anaglyph stereo rendering.

        Disable this with :func:`disable_stereo_render
        <Plotter.disable_stereo_render>`

        Examples
        --------
        Enable stereo rendering to show a cube as an anaglyph image.

        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> _ = pl.add_mesh(pv.Cube())
        >>> pl.enable_stereo_render()
        >>> pl.show()

        """
        if self.render_window is not None:
            self.render_window.SetStereoTypeToAnaglyph()
            self.render_window.StereoRenderOn()

    def disable_stereo_render(self):
        """Disable anaglyph stereo rendering.

        Enable again with :func:`enable_stereo_render
        <Plotter.enable_stereo_render>`

        Examples
        --------
        Enable and then disable stereo rendering. It should show a simple cube.

        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> _ = pl.add_mesh(pv.Cube())
        >>> pl.enable_stereo_render()
        >>> pl.disable_stereo_render()
        >>> pl.show()

        """
        if self.render_window is not None:
            self.render_window.StereoRenderOff()

    def hide_axes_all(self):
        """Hide the axes orientation widget in all renderers."""
        for renderer in self.renderers:
            renderer.hide_axes()

    def show_axes_all(self):
        """Show the axes orientation widget in all renderers.

        Examples
        --------
        >>> import pyvista as pv
        >>> from pyvista import examples
        >>>
        >>> mesh = examples.load_globe()
        >>> texture = examples.load_globe_texture()
        >>>
        >>> # create multi-window plot (1 row, 2 columns)
        >>> pl = pv.Plotter(shape=(1, 2))
        >>>
        >>> # activate subplot 1 and add a mesh
        >>> pl.subplot(0, 0)
        >>> _ = pl.add_mesh(mesh, texture=texture)
        >>>
        >>> # activate subplot 2 and add a mesh
        >>> pl.subplot(0, 1)
        >>> _ = pl.add_mesh(examples.load_airplane())
        >>>
        >>> # show the axes orientation widget in all subplots
        >>> pl.show_axes_all()
        >>>
        >>> # display the window
        >>> pl.show()

        """
        for renderer in self.renderers:
            renderer.show_axes()

    def isometric_view_interactive(self):
        """Set the current interactive render window to isometric view."""
        interactor = self.iren.get_interactor_style()
        renderer = interactor.GetCurrentRenderer()
        if renderer is None:
            renderer = self.renderer
        renderer.view_isometric()

    def update(self, stime=1, force_redraw=True):
        """Update window, redraw, process messages query.

        Parameters
        ----------
        stime : int, default: 1
            Duration of timer that interrupt vtkRenderWindowInteractor
            in milliseconds.

        force_redraw : bool, default: True
            Call ``render`` immediately.

        """
        if stime <= 0:
            stime = 1

        curr_time = time.time()
        if Plotter.last_update_time > curr_time:
            Plotter.last_update_time = curr_time

        if self.iren is not None:
            update_rate = self.iren.get_desired_update_rate()
            if (curr_time - Plotter.last_update_time) > (1.0 / update_rate):
                # Allow interaction for a brief moment during interactive updating
                # Use the non-blocking ProcessEvents method.
                self.iren.process_events()
                # Rerender
                self.render()
                Plotter.last_update_time = curr_time
                return

        if force_redraw:
            self.render()

    def add_composite(
        self,
        dataset,
        color=None,
        style=None,
        scalars=None,
        clim=None,
        show_edges=None,
        edge_color=None,
        point_size=None,
        line_width=None,
        opacity=1.0,
        flip_scalars=False,
        lighting=None,
        n_colors=256,
        interpolate_before_map=True,
        cmap=None,
        label=None,
        reset_camera=None,
        scalar_bar_args=None,
        show_scalar_bar=None,
        multi_colors=False,
        name=None,
        render_points_as_spheres=None,
        render_lines_as_tubes=None,
        smooth_shading=None,
        split_sharp_edges=None,
        ambient=None,
        diffuse=None,
        specular=None,
        specular_power=None,
        nan_color=None,
        nan_opacity=1.0,
        culling=None,
        rgb=None,
        below_color=None,
        above_color=None,
        annotations=None,
        pickable=True,
        preference="point",
        log_scale=False,
        pbr=None,
        metallic=None,
        roughness=None,
        render=True,
        component=None,
        color_missing_with_nan=False,
        copy_mesh=False,
        show_vertices=None,
        **kwargs,
    ):
        """Add a composite dataset to the plotter.

        Parameters
        ----------
        dataset : pyvista.MultiBlock
            A :class:`pyvista.MultiBlock` dataset.

        color : ColorLike, default: :attr:`pyvista.plotting.themes.Theme.color`
            Use to make the entire mesh have a single solid color.
            Either a string, RGB list, or hex color string.  For example:
            ``color='white'``, ``color='w'``, ``color=[1.0, 1.0, 1.0]``, or
            ``color='#FFFFFF'``. Color will be overridden if scalars are
            specified. To color each element of the composite dataset
            individually, you will need to iteratively call ``add_mesh`` for
            each sub-dataset.

        style : str, default: 'wireframe'
            Visualization style of the mesh.  One of the following:
            ``style='surface'``, ``style='wireframe'``, ``style='points'``.
            Defaults to ``'surface'``. Note that ``'wireframe'`` only shows a
            wireframe of the outer geometry.

        scalars : str, optional
            Scalars used to "color" the points or cells of the dataset.
            Accepts only a string name of an array that is present on the
            composite dataset.

        clim : sequence[float], optional
            Two item color bar range for scalars.  Defaults to minimum and
            maximum of scalars array.  Example: ``[-1, 2]``. ``rng`` is
            also an accepted alias for this.

        show_edges : bool, default: :attr:`pyvista.global_theme.show_edges <pyvista.plotting.themes.Theme.show_edges>`
            Shows the edges of a mesh.  Does not apply to a wireframe
            representation.

        edge_color : ColorLike, default: :attr:`pyvista.global_theme.edge_color <pyvista.plotting.themes.Theme.edge_color>`
            The solid color to give the edges when ``show_edges=True``.
            Either a string, RGB list, or hex color string.

            Defaults to :attr:`pyvista.global_theme.edge_color
            <pyvista.plotting.themes.Theme.edge_color>`.

        point_size : float, default: 5.0
            Point size of any points in the dataset plotted. Also
            applicable when style='points'. Default ``5.0``.

        line_width : float, optional
            Thickness of lines.  Only valid for wireframe and surface
            representations.

        opacity : float, default: 1.0
            Opacity of the mesh. A single float value that will be applied
            globally opacity of the mesh and uniformly
            applied everywhere - should be between 0 and 1.

        flip_scalars : bool, default: False
            Flip direction of cmap. Most colormaps allow ``*_r``
            suffix to do this as well.

        lighting : bool, default: True
            Enable or disable view direction lighting.

        n_colors : int, default: 256
            Number of colors to use when displaying scalars.  The scalar bar
            will also have this many colors.

        interpolate_before_map : bool, default: True
            Enabling makes for a smoother scalars display.  When ``False``,
            OpenGL will interpolate the mapped colors which can result in
            showing colors that are not present in the color map.

        cmap : str | list, | pyvista.LookupTable, default: :attr:`pyvista.plotting.themes.Theme.cmap`
            If a string, this is the name of the ``matplotlib`` colormap to use
            when mapping the ``scalars``.  See available Matplotlib colormaps.
            Only applicable for when displaying ``scalars``.
            ``colormap`` is also an accepted alias
            for this. If ``colorcet`` or ``cmocean`` are installed, their
            colormaps can be specified by name.

            You can also specify a list of colors to override an existing
            colormap with a custom one.  For example, to create a three color
            colormap you might specify ``['green', 'red', 'blue']``.

            This parameter also accepts a :class:`pyvista.LookupTable`. If this
            is set, all parameters controlling the color map like ``n_colors``
            will be ignored.

        label : str, optional
            String label to use when adding a legend to the scene with
            :func:`pyvista.Plotter.add_legend`.

        reset_camera : bool, optional
            Reset the camera after adding this mesh to the scene. The default
            setting is ``None``, where the camera is only reset if this plotter
            has already been shown. If ``False``, the camera is not reset
            regardless of the state of the ``Plotter``. When ``True``, the
            camera is always reset.

        scalar_bar_args : dict, optional
            Dictionary of keyword arguments to pass when adding the
            scalar bar to the scene. For options, see
            :func:`pyvista.Plotter.add_scalar_bar`.

        show_scalar_bar : bool
            If ``False``, a scalar bar will not be added to the
            scene. Defaults to ``True`` unless ``rgba=True``.

        multi_colors : bool | str | cycler.Cycler | sequence[ColorLike], default: False
            Color each block by a solid color using a custom cycler.

            If ``True``, the default 'matplotlib' color cycler is used.

            See :func:`set_color_cycler<Plotter.set_color_cycler>` for usage of
            custom color cyclers.

        name : str, optional
            The name for the added mesh/actor so that it can be easily
            updated.  If an actor of this name already exists in the
            rendering window, it will be replaced by the new actor.

        render_points_as_spheres : bool, default: False
            Render points as spheres rather than dots.

        render_lines_as_tubes : bool, default: False
            Show lines as thick tubes rather than flat lines.  Control
            the width with ``line_width``.

        smooth_shading : bool, default: :attr`pyvista.plotting.themes.Theme.smooth_shading`
            Enable smooth shading when ``True`` using the Phong shading
            algorithm.  When ``False``, uses flat shading.  Automatically
            enabled when ``pbr=True``.  See :ref:`shading_example`.

        split_sharp_edges : bool, default: False
            Split sharp edges exceeding 30 degrees when plotting with smooth
            shading.  Control the angle with the optional keyword argument
            ``feature_angle``.  By default this is ``False`` unless overridden
            by the global or plotter theme.  Note that enabling this will
            create a copy of the input mesh within the plotter.  See
            :ref:`shading_example`.

        ambient : float, default: 0.0
            When lighting is enabled, this is the amount of light in
            the range of 0 to 1 (default 0.0) that reaches the actor
            when not directed at the light source emitted from the
            viewer.

        diffuse : float, default: 1.0
            The diffuse lighting coefficient.

        specular : float, default: 0.0
            The specular lighting coefficient.

        specular_power : float, default: 1.0
            The specular power. Between 0.0 and 128.0.

        nan_color : ColorLike, default: :attr:`pyvista.plotting.themes.Theme.nan_color`
            The color to use for all ``NaN`` values in the plotted
            scalar array.

        nan_opacity : float, default: 1.0
            Opacity of ``NaN`` values.  Should be between 0 and 1.

        culling : str, bool, default: False
            Does not render faces that are culled. This can be helpful for
            dense surface meshes, especially when edges are visible, but can
            cause flat meshes to be partially displayed. One of the following:

            * ``True`` - Enable backface culling
            * ``"b"`` - Enable backface culling
            * ``"back"`` - Enable backface culling
            * ``"backface"`` - Enable backface culling
            * ``"f"`` - Enable frontface culling
            * ``"front"`` - Enable frontface culling
            * ``"frontface"`` - Enable frontface culling
            * ``False`` - Disable both backface and frontface culling

        rgb : bool, default: False
            If an 2 dimensional array is passed as the scalars, plot
            those values as RGB(A) colors. ``rgba`` is also an
            accepted alias for this.  Opacity (the A) is optional.  If
            a scalars array ending with ``"_rgba"`` is passed, the default
            becomes ``True``.  This can be overridden by setting this
            parameter to ``False``.

        below_color : ColorLike, optional
            Solid color for values below the scalars range
            (``clim``). This will automatically set the scalar bar
            ``below_label`` to ``'below'``.

        above_color : ColorLike, optional
            Solid color for values below the scalars range
            (``clim``). This will automatically set the scalar bar
            ``above_label`` to ``'above'``.

        annotations : dict, optional
            Pass a dictionary of annotations. Keys are the float
            values in the scalars range to annotate on the scalar bar
            and the values are the string annotations.

        pickable : bool, default: True
            Set whether this actor is pickable.

        preference : str, default: 'point'
            For each block, when ``block.n_points == block.n_cells`` and
            setting scalars, this parameter sets how the scalars will be mapped
            to the mesh.  For example, when ``'point'`` the scalars will be
            associated with the mesh points if available.  Can be either
            ``'point'`` or ``'cell'``.

        log_scale : bool, default: False
            Use log scale when mapping data to colors. Scalars less
            than zero are mapped to the smallest representable
            positive float.

        pbr : bool, default: False
            Enable physics based rendering (PBR) if the mesh is
            ``PolyData``.  Use the ``color`` argument to set the base
            color.

        metallic : float, default: 0.0
            Usually this value is either 0 or 1 for a real material
            but any value in between is valid. This parameter is only
            used by PBR interpolation.

        roughness : float, default: 0.5
            This value has to be between 0 (glossy) and 1 (rough). A
            glossy material has reflections and a high specular
            part. This parameter is only used by PBR
            interpolation.

        render : bool, default: True
            Force a render when ``True``.

        component : int, optional
            Set component of vector valued scalars to plot.  Must be
            nonnegative, if supplied. If ``None``, the magnitude of
            the vector is plotted.

        color_missing_with_nan : bool, default: False
            Color any missing values with the ``nan_color``. This is useful
            when not all blocks of the composite dataset have the specified
            ``scalars``.

        copy_mesh : bool, default: False
            If ``True``, a copy of the mesh will be made before adding it to
            the plotter.  This is useful if e.g. you would like to add the same
            mesh to a plotter multiple times and display different
            scalars. Setting ``copy_mesh`` to ``False`` is necessary if you
            would like to update the mesh after adding it to the plotter and
            have these updates rendered, e.g. by changing the active scalars or
            through an interactive widget.

        show_vertices : bool, optional
            When ``style`` is not ``'points'``, render the external surface
            vertices. The following optional keyword arguments may be used to
            control the style of the vertices:

            * ``vertex_color`` - The color of the vertices
            * ``vertex_style`` - Change style to ``'points_gaussian'``
            * ``vertex_opacity`` - Control the opacity of the vertices

        **kwargs : dict, optional
            Optional keyword arguments.

        Returns
        -------
        pyvista.Actor
            Actor of the composite dataset.

        pyvista.CompositePolyDataMapper
            Composite PolyData mapper.

        Examples
        --------
        Add a sphere and a cube as a multiblock dataset to a plotter and then
        change the visibility and color of the blocks.

        Note index ``1`` and ``2`` are used to access the individual blocks of
        the composite dataset. This is because the :class:`pyvista.MultiBlock`
        is the root node of the "tree" and is index ``0``. This allows you to
        access individual blocks or the entire composite dataset itself in the
        case of multiple nested composite datasets.

        >>> import pyvista as pv
        >>> dataset = pv.MultiBlock(
        ...     [pv.Cube(), pv.Sphere(center=(0, 0, 1))]
        ... )
        >>> pl = pv.Plotter()
        >>> actor, mapper = pl.add_composite(dataset)
        >>> mapper.block_attr[1].color = 'b'
        >>> mapper.block_attr[1].opacity = 0.5
        >>> mapper.block_attr[2].color = 'r'
        >>> pl.show()

        """
        if not isinstance(dataset, _vtk.vtkCompositeDataSet):
            raise TypeError(f'Invalid type ({type(dataset)}). Must be a composite dataset.')
        # always convert
        dataset = dataset.as_polydata_blocks(copy_mesh)
        self.mesh = dataset  # for legacy behavior

        # Parse arguments
        (
            scalar_bar_args,
            split_sharp_edges,
            show_scalar_bar,
            feature_angle,
            render_points_as_spheres,
            smooth_shading,
            clim,
            cmap,
            culling,
            name,
            nan_color,
            color,
            texture,
            rgb,
            interpolation,
            remove_existing_actor,
            vertex_color,
            vertex_style,
            vertex_opacity,
        ) = _common_arg_parser(
            dataset,
            self._theme,
            n_colors,
            scalar_bar_args,
            split_sharp_edges,
            show_scalar_bar,
            render_points_as_spheres,
            smooth_shading,
            pbr,
            clim,
            cmap,
            culling,
            name,
            nan_color,
            nan_opacity,
            color,
            None,
            rgb,
            style,
            **kwargs,
        )
        if show_vertices is None:
            show_vertices = self._theme.show_vertices

        # Compute surface normals if using smooth shading
        if smooth_shading:
            dataset = dataset._compute_normals(
                cell_normals=False,
                split_vertices=True,
                feature_angle=feature_angle,
            )

        self.mapper = CompositePolyDataMapper(
            dataset,
            theme=self._theme,
            color_missing_with_nan=color_missing_with_nan,
            interpolate_before_map=interpolate_before_map,
        )

        actor, _ = self.add_actor(self.mapper)

        prop = Property(
            self._theme,
            interpolation=interpolation,
            metallic=metallic,
            roughness=roughness,
            point_size=point_size,
            ambient=ambient,
            diffuse=diffuse,
            specular=specular,
            specular_power=specular_power,
            show_edges=show_edges,
            color=self.renderer.next_color if color is None else color,
            style=style,
            edge_color=edge_color,
            render_points_as_spheres=render_points_as_spheres,
            render_lines_as_tubes=render_lines_as_tubes,
            lighting=lighting,
            line_width=line_width,
            opacity=opacity,
            culling=culling,
        )
        actor.SetProperty(prop)

        if label is not None:
            self._add_legend_label(actor, label, None, prop.color)

        # check if there are any consistent active scalars
        if color is not None:
            self.mapper.scalar_visibility = False
        elif multi_colors:
            self.mapper.set_unique_colors(multi_colors)
        else:
            if scalars is None:
                point_name, cell_name = dataset._get_consistent_active_scalars()
                if point_name and cell_name:
                    if preference == 'point':
                        scalars = point_name
                    else:
                        scalars = cell_name
                else:
                    scalars = point_name if point_name is not None else cell_name

            elif not isinstance(scalars, str):
                raise TypeError(
                    f'`scalars` must be a string for `add_composite`, not ({type(scalars)})'
                )

            if scalars is not None:
                scalar_bar_args = self.mapper.set_scalars(
                    scalars,
                    preference,
                    component,
                    annotations,
                    rgb,
                    scalar_bar_args,
                    n_colors,
                    nan_color,
                    above_color,
                    below_color,
                    clim,
                    cmap,
                    flip_scalars,
                    log_scale,
                )
            else:
                self.mapper.scalar_visibility = False

        # Only show scalar bar if there are scalars
        if show_scalar_bar and scalars is not None:
            self.add_scalar_bar(**scalar_bar_args)

        # by default reset the camera if the plotting window has been rendered
        if reset_camera is None:
            reset_camera = not self._first_time and not self.camera_set

        # add this immediately prior to adding the actor to ensure vertices
        # are rendered
        if show_vertices and style not in ['points', 'points_gaussian']:
            self.add_composite(
                dataset,
                style=vertex_style,
                point_size=point_size,
                color=vertex_color,
                render_points_as_spheres=render_points_as_spheres,
                name=f'{name}-vertices',
                opacity=vertex_opacity,
                lighting=lighting,
                render=False,
                show_vertices=False,
            )

        self.add_actor(
            actor,
            reset_camera=reset_camera,
            name=name,
            pickable=pickable,
            render=render,
            remove_existing_actor=remove_existing_actor,
        )

        return actor, self.mapper

    def add_mesh(
        self,
        mesh,
        color=None,
        style=None,
        scalars=None,
        clim=None,
        show_edges=None,
        edge_color=None,
        point_size=None,
        line_width=None,
        opacity=None,
        flip_scalars=False,
        lighting=None,
        n_colors=256,
        interpolate_before_map=None,
        cmap=None,
        label=None,
        reset_camera=None,
        scalar_bar_args=None,
        show_scalar_bar=None,
        multi_colors=False,
        name=None,
        texture=None,
        render_points_as_spheres=None,
        render_lines_as_tubes=None,
        smooth_shading=None,
        split_sharp_edges=None,
        ambient=None,
        diffuse=None,
        specular=None,
        specular_power=None,
        nan_color=None,
        nan_opacity=1.0,
        culling=None,
        rgb=None,
        categories=False,
        silhouette=None,
        use_transparency=False,
        below_color=None,
        above_color=None,
        annotations=None,
        pickable=True,
        preference="point",
        log_scale=False,
        pbr=None,
        metallic=None,
        roughness=None,
        render=True,
        user_matrix=np.eye(4),
        component=None,
        emissive=None,
        copy_mesh=False,
        backface_params=None,
        show_vertices=None,
        **kwargs,
    ):
        """Add any PyVista/VTK mesh or dataset that PyVista can wrap to the scene.

        This method is using a mesh representation to view the surfaces
        and/or geometry of datasets. For volume rendering, see
        :func:`pyvista.Plotter.add_volume`.

        To see the what most of the following parameters look like in action,
        please refer to :class:`pyvista.Property`.

        Parameters
        ----------
        mesh : pyvista.DataSet or pyvista.MultiBlock or vtk.vtkAlgorithm
            Any PyVista or VTK mesh is supported. Also, any dataset
            that :func:`pyvista.wrap` can handle including NumPy
            arrays of XYZ points. Plotting also supports VTK algorithm
            objects (``vtk.vtkAlgorithm`` and ``vtk.vtkAlgorithmOutput``).
            When passing an algorithm, the rendering pipeline will be
            connected to the passed algorithm to dynamically update
            the scene.

        color : ColorLike, optional
            Use to make the entire mesh have a single solid color.
            Either a string, RGB list, or hex color string.  For example:
            ``color='white'``, ``color='w'``, ``color=[1.0, 1.0, 1.0]``, or
            ``color='#FFFFFF'``. Color will be overridden if scalars are
            specified.

            Defaults to :attr:`pyvista.global_theme.color
            <pyvista.plotting.themes.Theme.color>`.

        style : str, optional
            Visualization style of the mesh.  One of the following:
            ``style='surface'``, ``style='wireframe'``, ``style='points'``,
            ``style='points_gaussian'``. Defaults to ``'surface'``. Note that
            ``'wireframe'`` only shows a wireframe of the outer geometry.
            ``'points_gaussian'`` can be modified with the ``emissive``,
            ``render_points_as_spheres`` options.

        scalars : str | numpy.ndarray, optional
            Scalars used to "color" the mesh.  Accepts a string name
            of an array that is present on the mesh or an array equal
            to the number of cells or the number of points in the
            mesh.  Array should be sized as a single vector. If both
            ``color`` and ``scalars`` are ``None``, then the active
            scalars are used.

        clim : sequence[float], optional
            Two item color bar range for scalars.  Defaults to minimum and
            maximum of scalars array.  Example: ``[-1, 2]``. ``rng`` is
            also an accepted alias for this.

        show_edges : bool, optional
            Shows the edges of a mesh.  Does not apply to a wireframe
            representation.

        edge_color : ColorLike, optional
            The solid color to give the edges when ``show_edges=True``.
            Either a string, RGB list, or hex color string.

            Defaults to :attr:`pyvista.global_theme.edge_color
            <pyvista.plotting.themes.Theme.edge_color>`.

        point_size : float, optional
            Point size of any nodes in the dataset plotted. Also
            applicable when style='points'. Default ``5.0``.

        line_width : float, optional
            Thickness of lines.  Only valid for wireframe and surface
            representations.  Default ``None``.

        opacity : float | str| array_like
            Opacity of the mesh. If a single float value is given, it
            will be the global opacity of the mesh and uniformly
            applied everywhere - should be between 0 and 1. A string
            can also be specified to map the scalars range to a
            predefined opacity transfer function (options include:
            ``'linear'``, ``'linear_r'``, ``'geom'``, ``'geom_r'``).
            A string could also be used to map a scalars array from
            the mesh to the opacity (must have same number of elements
            as the ``scalars`` argument). Or you can pass a custom
            made transfer function that is an array either
            ``n_colors`` in length or shorter.

        flip_scalars : bool, default: False
            Flip direction of cmap. Most colormaps allow ``*_r``
            suffix to do this as well.

        lighting : bool, optional
            Enable or disable view direction lighting. Default ``False``.

        n_colors : int, optional
            Number of colors to use when displaying scalars. Defaults to 256.
            The scalar bar will also have this many colors.

        interpolate_before_map : bool, optional
            Enabling makes for a smoother scalars display.  Default is
            ``True``.  When ``False``, OpenGL will interpolate the
            mapped colors which can result is showing colors that are
            not present in the color map.

        cmap : str | list | pyvista.LookupTable, default: :attr:`pyvista.plotting.themes.Theme.cmap`
            If a string, this is the name of the ``matplotlib`` colormap to use
            when mapping the ``scalars``.  See available Matplotlib colormaps.
            Only applicable for when displaying ``scalars``.
            ``colormap`` is also an accepted alias
            for this. If ``colorcet`` or ``cmocean`` are installed, their
            colormaps can be specified by name.

            You can also specify a list of colors to override an existing
            colormap with a custom one.  For example, to create a three color
            colormap you might specify ``['green', 'red', 'blue']``.

            This parameter also accepts a :class:`pyvista.LookupTable`. If this
            is set, all parameters controlling the color map like ``n_colors``
            will be ignored.

        label : str, optional
            String label to use when adding a legend to the scene with
            :func:`pyvista.Plotter.add_legend`.

        reset_camera : bool, optional
            Reset the camera after adding this mesh to the scene. The default
            setting is ``None``, where the camera is only reset if this plotter
            has already been shown. If ``False``, the camera is not reset
            regardless of the state of the ``Plotter``. When ``True``, the
            camera is always reset.

        scalar_bar_args : dict, optional
            Dictionary of keyword arguments to pass when adding the
            scalar bar to the scene. For options, see
            :func:`pyvista.Plotter.add_scalar_bar`.

        show_scalar_bar : bool, optional
            If ``False``, a scalar bar will not be added to the
            scene.

        multi_colors : bool | str | cycler.Cycler | sequence[ColorLike], default: False
            If a :class:`pyvista.MultiBlock` dataset is given this will color
            each block by a solid color using a custom cycler.

            If ``True``, the default 'matplotlib' color cycler is used.

            See :func:`set_color_cycler<Plotter.set_color_cycler>` for usage of
            custom color cycles.

        name : str, optional
            The name for the added mesh/actor so that it can be easily
            updated.  If an actor of this name already exists in the
            rendering window, it will be replaced by the new actor.

        texture : pyvista.Texture or np.ndarray, optional
            A texture to apply if the input mesh has texture
            coordinates.  This will not work with MultiBlock
            datasets.

        render_points_as_spheres : bool, optional
            Render points as spheres rather than dots.

        render_lines_as_tubes : bool, optional
            Show lines as thick tubes rather than flat lines.  Control
            the width with ``line_width``.

        smooth_shading : bool, optional
            Enable smooth shading when ``True`` using the Phong
            shading algorithm.  When ``False``, use flat shading.
            Automatically enabled when ``pbr=True``.  See
            :ref:`shading_example`.

        split_sharp_edges : bool, optional
            Split sharp edges exceeding 30 degrees when plotting with smooth
            shading.  Control the angle with the optional keyword argument
            ``feature_angle``.  By default this is ``False`` unless overridden
            by the global or plotter theme.  Note that enabling this will
            create a copy of the input mesh within the plotter.  See
            :ref:`shading_example`.

        ambient : float, optional
            When lighting is enabled, this is the amount of light in
            the range of 0 to 1 (default 0.0) that reaches the actor
            when not directed at the light source emitted from the
            viewer.

        diffuse : float, optional
            The diffuse lighting coefficient. Default 1.0.

        specular : float, optional
            The specular lighting coefficient. Default 0.0.

        specular_power : float, optional
            The specular power. Between 0.0 and 128.0.

        nan_color : ColorLike, optional
            The color to use for all ``NaN`` values in the plotted
            scalar array.

        nan_opacity : float, optional
            Opacity of ``NaN`` values.  Should be between 0 and 1.
            Default 1.0.

        culling : str, optional
            Does not render faces that are culled. Options are
            ``'front'`` or ``'back'``. This can be helpful for dense
            surface meshes, especially when edges are visible, but can
            cause flat meshes to be partially displayed.  Defaults to
            ``False``.

        rgb : bool, optional
            If an 2 dimensional array is passed as the scalars, plot
            those values as RGB(A) colors. ``rgba`` is also an
            accepted alias for this.  Opacity (the A) is optional.  If
            a scalars array ending with ``"_rgba"`` is passed, the default
            becomes ``True``.  This can be overridden by setting this
            parameter to ``False``.

        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.

        silhouette : dict, bool, optional
            If set to ``True``, plot a silhouette highlight for the
            mesh. This feature is only available for a triangulated
            ``PolyData``.  As a ``dict``, it contains the properties
            of the silhouette to display:

                * ``color``: ``ColorLike``, color of the silhouette
                * ``line_width``: ``float``, edge width
                * ``opacity``: ``float`` between 0 and 1, edge transparency
                * ``feature_angle``: If a ``float``, display sharp edges
                  exceeding that angle in degrees.
                * ``decimate``: ``float`` between 0 and 1, level of decimation

        use_transparency : bool, optional
            Invert the opacity mappings and make the values correspond
            to transparency.

        below_color : ColorLike, optional
            Solid color for values below the scalars range
            (``clim``). This will automatically set the scalar bar
            ``below_label`` to ``'below'``.

        above_color : ColorLike, optional
            Solid color for values below the scalars range
            (``clim``). This will automatically set the scalar bar
            ``above_label`` to ``'above'``.

        annotations : dict, optional
            Pass a dictionary of annotations. Keys are the float
            values in the scalars range to annotate on the scalar bar
            and the values are the string annotations.

        pickable : bool, optional
            Set whether this actor is pickable.

        preference : str, default: "point"
            When ``mesh.n_points == mesh.n_cells`` and setting
            scalars, this parameter sets how the scalars will be
            mapped to the mesh.  Default ``'point'``, causes the
            scalars will be associated with the mesh points.  Can be
            either ``'point'`` or ``'cell'``.

        log_scale : bool, default: False
            Use log scale when mapping data to colors. Scalars less
            than zero are mapped to the smallest representable
            positive float.

        pbr : bool, optional
            Enable physics based rendering (PBR) if the mesh is
            ``PolyData``.  Use the ``color`` argument to set the base
            color.

        metallic : float, optional
            Usually this value is either 0 or 1 for a real material
            but any value in between is valid. This parameter is only
            used by PBR interpolation.

        roughness : float, optional
            This value has to be between 0 (glossy) and 1 (rough). A
            glossy material has reflections and a high specular
            part. This parameter is only used by PBR
            interpolation.

        render : bool, default: True
            Force a render when ``True``.

        user_matrix : np.ndarray | vtk.vtkMatrix4x4, default: np.eye(4)
            Matrix passed to the Actor class before rendering. This affects the
            actor/rendering only, not the input volume itself. The user matrix is the
            last transformation applied to the actor before rendering. Defaults to the
            identity matrix.

        component : int, optional
            Set component of vector valued scalars to plot.  Must be
            nonnegative, if supplied. If ``None``, the magnitude of
            the vector is plotted.

        emissive : bool, optional
            Treat the points/splats as emissive light sources. Only valid for
            ``style='points_gaussian'`` representation.

        copy_mesh : bool, default: False
            If ``True``, a copy of the mesh will be made before adding it to
            the plotter.  This is useful if you would like to add the same
            mesh to a plotter multiple times and display different
            scalars. Setting ``copy_mesh`` to ``False`` is necessary if you
            would like to update the mesh after adding it to the plotter and
            have these updates rendered, e.g. by changing the active scalars or
            through an interactive widget. This should only be set to ``True``
            with caution. Defaults to ``False``. This is ignored if the input
            is a ``vtkAlgorithm`` subclass.

        backface_params : dict | pyvista.Property, optional
            A :class:`pyvista.Property` or a dict of parameters to use for
            backface rendering. This is useful for instance when the inside of
            oriented surfaces has a different color than the outside. When a
            :class:`pyvista.Property`, this is directly used for backface
            rendering. When a dict, valid keys are :class:`pyvista.Property`
            attributes, and values are corresponding values to use for the
            given property. Omitted keys (or the default of
            ``backface_params=None``) default to the corresponding frontface
            properties.

        show_vertices : bool, optional
            When ``style`` is not ``'points'``, render the external surface
            vertices. The following optional keyword arguments may be used to
            control the style of the vertices:

            * ``vertex_color`` - The color of the vertices
            * ``vertex_style`` - Change style to ``'points_gaussian'``
            * ``vertex_opacity`` - Control the opacity of the vertices

        **kwargs : dict, optional
            Optional keyword arguments.

        Returns
        -------
        pyvista.plotting.actor.Actor
            Actor of the mesh.

        Examples
        --------
        Add a sphere to the plotter and show it with a custom scalar
        bar title.

        >>> import pyvista as pv
        >>> sphere = pv.Sphere()
        >>> sphere['Data'] = sphere.points[:, 2]
        >>> plotter = pv.Plotter()
        >>> _ = plotter.add_mesh(
        ...     sphere, scalar_bar_args={'title': 'Z Position'}
        ... )
        >>> plotter.show()

        Plot using RGB on a single cell.  Note that since the number of
        points and the number of cells are identical, we have to pass
        ``preference='cell'``.

        >>> import pyvista as pv
        >>> import numpy as np
        >>> vertices = np.array(
        ...     [
        ...         [0, 0, 0],
        ...         [1, 0, 0],
        ...         [0.5, 0.667, 0],
        ...         [0.5, 0.33, 0.667],
        ...     ]
        ... )
        >>> faces = np.hstack(
        ...     [[3, 0, 1, 2], [3, 0, 3, 2], [3, 0, 1, 3], [3, 1, 2, 3]]
        ... )
        >>> mesh = pv.PolyData(vertices, faces)
        >>> mesh.cell_data['colors'] = [
        ...     [255, 255, 255],
        ...     [0, 255, 0],
        ...     [0, 0, 255],
        ...     [255, 0, 0],
        ... ]
        >>> plotter = pv.Plotter()
        >>> _ = plotter.add_mesh(
        ...     mesh,
        ...     scalars='colors',
        ...     lighting=False,
        ...     rgb=True,
        ...     preference='cell',
        ... )
        >>> plotter.camera_position = 'xy'
        >>> plotter.show()

        Note how this varies from ``preference=='point'``.  This is
        because each point is now being individually colored, versus
        in ``preference=='point'``, each cell face is individually
        colored.

        >>> plotter = pv.Plotter()
        >>> _ = plotter.add_mesh(
        ...     mesh,
        ...     scalars='colors',
        ...     lighting=False,
        ...     rgb=True,
        ...     preference='point',
        ... )
        >>> plotter.camera_position = 'xy'
        >>> plotter.show()

        Plot a plane with a constant color and vary its opacity by point.

        >>> plane = pv.Plane()
        >>> plane.plot(
        ...     color='b',
        ...     opacity=np.linspace(0, 1, plane.n_points),
        ...     show_edges=True,
        ... )

        Plot the points of a sphere with Gaussian smoothing while coloring by z
        position.

        >>> mesh = pv.Sphere()
        >>> mesh.plot(
        ...     scalars=mesh.points[:, 2],
        ...     style='points_gaussian',
        ...     opacity=0.5,
        ...     point_size=10,
        ...     render_points_as_spheres=False,
        ...     show_scalar_bar=False,
        ... )

        """
        if style == 'points_gaussian':
            self.mapper = PointGaussianMapper(theme=self.theme, emissive=emissive)
        else:
            self.mapper = DataSetMapper(theme=self.theme)

        if render_lines_as_tubes and show_edges:
            warnings.warn(
                '`show_edges=True` not supported when `render_lines_as_tubes=True`. Ignoring `show_edges`.',
                UserWarning,
            )
            show_edges = False

        mesh, algo = algorithm_to_mesh_handler(mesh)

        # Convert the VTK data object to a pyvista wrapped object if necessary
        if not is_pyvista_dataset(mesh):
            mesh = wrap(mesh)
            if not is_pyvista_dataset(mesh):
                raise TypeError(
                    f'Object type ({type(mesh)}) not supported for plotting in PyVista.'
                )
        if isinstance(mesh, pyvista.PointSet):
            # cast to PointSet to PolyData
            if algo is not None:
                algo = pointset_to_polydata_algorithm(algo)
                mesh, algo = algorithm_to_mesh_handler(algo)
            else:
                mesh = mesh.cast_to_polydata(deep=False)
        elif isinstance(mesh, pyvista.MultiBlock):
            if algo is not None:
                raise TypeError(
                    'Algorithms with `MultiBlock` output type are not supported by `add_mesh` at this time.'
                )
            actor, _ = self.add_composite(
                mesh,
                color=color,
                style=style,
                scalars=scalars,
                clim=clim,
                show_edges=show_edges,
                edge_color=edge_color,
                point_size=point_size,
                line_width=line_width,
                opacity=opacity,
                flip_scalars=flip_scalars,
                lighting=lighting,
                n_colors=n_colors,
                interpolate_before_map=interpolate_before_map,
                cmap=cmap,
                label=label,
                reset_camera=reset_camera,
                scalar_bar_args=scalar_bar_args,
                show_scalar_bar=show_scalar_bar,
                multi_colors=multi_colors,
                name=name,
                render_points_as_spheres=render_points_as_spheres,
                render_lines_as_tubes=render_lines_as_tubes,
                smooth_shading=smooth_shading,
                split_sharp_edges=split_sharp_edges,
                ambient=ambient,
                diffuse=diffuse,
                specular=specular,
                specular_power=specular_power,
                nan_color=nan_color,
                nan_opacity=nan_opacity,
                culling=culling,
                rgb=rgb,
                below_color=below_color,
                above_color=above_color,
                pickable=pickable,
                preference=preference,
                log_scale=log_scale,
                pbr=pbr,
                metallic=metallic,
                roughness=roughness,
                render=render,
                show_vertices=show_vertices,
                **kwargs,
            )
            return actor
        elif copy_mesh and algo is None:
            # A shallow copy of `mesh` is made here so when we set (or add) scalars
            # active, it doesn't modify the original input mesh.
            # We ignore `copy_mesh` if the input is an algorithm
            mesh = mesh.copy(deep=False)

        # Parse arguments
        (
            scalar_bar_args,
            split_sharp_edges,
            show_scalar_bar,
            feature_angle,
            render_points_as_spheres,
            smooth_shading,
            clim,
            cmap,
            culling,
            name,
            nan_color,
            color,
            texture,
            rgb,
            interpolation,
            remove_existing_actor,
            vertex_color,
            vertex_style,
            vertex_opacity,
        ) = _common_arg_parser(
            mesh,
            self._theme,
            n_colors,
            scalar_bar_args,
            split_sharp_edges,
            show_scalar_bar,
            render_points_as_spheres,
            smooth_shading,
            pbr,
            clim,
            cmap,
            culling,
            name,
            nan_color,
            nan_opacity,
            color,
            texture,
            rgb,
            style,
            **kwargs,
        )

        if show_vertices is None:
            show_vertices = self._theme.show_vertices

        if silhouette is None:
            silhouette = self._theme.silhouette.enabled
        if silhouette:
            if isinstance(silhouette, dict):
                self.add_silhouette(algo or mesh, **silhouette)
            else:
                self.add_silhouette(algo or mesh)

        # Try to plot something if no preference given
        if scalars is None and color is None and texture is None:
            # Make sure scalars components are not vectors/tuples
            scalars = mesh.active_scalars_name
            # Don't allow plotting of string arrays by default
            if scalars is not None:  # and np.issubdtype(mesh.active_scalars.dtype, np.number):
                scalar_bar_args.setdefault('title', scalars)
            else:
                scalars = None

        # Make sure scalars is a numpy array after this point
        original_scalar_name = None
        scalars_name = pyvista.DEFAULT_SCALARS_NAME
        if isinstance(scalars, str):
            self.mapper.array_name = scalars

            # enable rgb if the scalars name ends with rgb or rgba
            if rgb is None:
                if scalars.endswith('_rgb') or scalars.endswith('_rgba'):
                    rgb = True

            original_scalar_name = scalars
            scalars = get_array(mesh, scalars, preference=preference, err=True)
            scalar_bar_args.setdefault('title', original_scalar_name)
            scalars_name = original_scalar_name

            # Set the active scalars name here. If the name already exists in
            # the input mesh, it may not be set as the active scalars within
            # the mapper. This should be refactored by 0.36.0
            field = get_array_association(mesh, original_scalar_name, preference=preference)
            self.mapper.scalar_map_mode = field.name

            if algo is not None:
                # Ensures that the right scalars are set as active on
                # each pipeline request
                algo = active_scalars_algorithm(algo, original_scalar_name, preference=preference)
                mesh, algo = algorithm_to_mesh_handler(algo)
            else:
                # Otherwise, make sure the mesh object's scalars are set
                if field == FieldAssociation.POINT:
                    mesh.point_data.active_scalars_name = original_scalar_name
                elif field == FieldAssociation.CELL:
                    mesh.cell_data.active_scalars_name = original_scalar_name

        # Compute surface normals if using smooth shading
        if smooth_shading:
            if algo is not None:
                raise TypeError(
                    'Smooth shading is not currently supported when a vtkAlgorithm is passed.'
                )
            mesh, scalars = prepare_smooth_shading(
                mesh, scalars, texture, split_sharp_edges, feature_angle, preference
            )

        if rgb:
            show_scalar_bar = False
            if scalars.ndim != 2 or scalars.shape[1] < 3 or scalars.shape[1] > 4:
                raise ValueError('RGB array must be n_points/n_cells by 3/4 in shape.')

        if algo is None and not mesh.n_points:
            # Algorithms may initialize with an empty mesh
            raise ValueError('Empty meshes cannot be plotted. Input mesh has zero points.')

        # set main values
        self.mesh = mesh
        self.mapper.dataset = self.mesh
        if interpolate_before_map is not None:
            self.mapper.interpolate_before_map = interpolate_before_map
        set_algorithm_input(self.mapper, algo or mesh)

        actor = Actor(mapper=self.mapper)
        actor.user_matrix = user_matrix

        if texture is not None:
            if isinstance(texture, np.ndarray):
                texture = numpy_to_texture(texture)
            if not isinstance(texture, (_vtk.vtkTexture, _vtk.vtkOpenGLTexture)):
                raise TypeError(f'Invalid texture type ({type(texture)})')
            if mesh.GetPointData().GetTCoords() is None:
                raise ValueError(
                    'Input mesh does not have texture coordinates to support the texture.'
                )
            actor.texture = texture
            # Set color to white by default when using a texture
            if color is None:
                color = 'white'
            if scalars is None:
                show_scalar_bar = False
            self.mapper.scalar_visibility = False

            # see https://github.com/pyvista/pyvista/issues/950
            mesh.set_active_scalars(None)

        # Handle making opacity array
        custom_opac, opacity = process_opacity(
            mesh, opacity, preference, n_colors, scalars, use_transparency
        )

        # Scalars formatting ==================================================
        if scalars is not None:
            self.mapper.set_scalars(
                scalars,
                scalars_name,
                n_colors,
                scalar_bar_args,
                rgb,
                component,
                preference,
                custom_opac,
                annotations,
                log_scale,
                nan_color,
                above_color,
                below_color,
                cmap,
                flip_scalars,
                opacity,
                categories,
                clim,
            )
            self.mapper.scalar_visibility = True
        elif custom_opac:  # no scalars but custom opacity
            self.mapper.set_custom_opacity(
                opacity,
                color,
                n_colors,
                preference,
            )
            self.mapper.scalar_visibility = True
        else:
            self.mapper.scalar_visibility = False

        # Set actor properties ================================================
        prop_kwargs = dict(
            theme=self._theme,
            interpolation=interpolation,
            metallic=metallic,
            roughness=roughness,
            point_size=point_size,
            ambient=ambient,
            diffuse=diffuse,
            specular=specular,
            specular_power=specular_power,
            show_edges=show_edges,
            color=self.renderer.next_color if color is None else color,
            style=style if style != 'points_gaussian' else 'points',
            edge_color=edge_color,
            render_lines_as_tubes=render_lines_as_tubes,
            lighting=lighting,
            line_width=line_width,
            culling=culling,
        )

        if isinstance(opacity, (float, int)):
            prop_kwargs['opacity'] = opacity
        prop = Property(**prop_kwargs)
        actor.SetProperty(prop)

        if style == 'points_gaussian':
            self.mapper.scale_factor = prop.point_size * self.mapper.dataset.length / 1300
            if not render_points_as_spheres and not self.mapper.emissive:
                if prop.opacity >= 1.0:
                    prop.opacity = 0.9999  # otherwise, weird triangles

        if render_points_as_spheres:
            if style == 'points_gaussian':
                self.mapper.use_circular_splat(prop.opacity)
                prop.opacity = 1.0
            else:
                prop.render_points_as_spheres = render_points_as_spheres

        if backface_params is not None:
            if isinstance(backface_params, Property):
                backface_prop = backface_params
            elif isinstance(backface_params, dict):
                # preserve omitted kwargs from frontface
                backface_kwargs = deepcopy(prop_kwargs)
                backface_kwargs.update(backface_params)
                backface_prop = Property(**backface_kwargs)
            else:
                raise TypeError(
                    'Backface params must be a pyvista.Property or a dict, '
                    f'not {type(backface_params).__name__}.'
                )
            actor.backface_prop = backface_prop

        # legend label
        if label is not None:
            self._add_legend_label(actor, label, scalars, actor.prop.color)

        # by default reset the camera if the plotting window has been rendered
        if reset_camera is None:
            reset_camera = not self._first_time and not self.camera_set

        # add this immediately prior to adding the actor to ensure vertices
        # are rendered
        if show_vertices and style not in ['points', 'points_gaussian']:
            self.add_mesh(
                extract_surface_algorithm(algo or mesh),
                style=vertex_style,
                point_size=point_size,
                color=vertex_color,
                render_points_as_spheres=render_points_as_spheres,
                name=f'{name}-vertices',
                opacity=vertex_opacity,
                lighting=lighting,
                render=False,
                show_vertices=False,
            )

        self.add_actor(
            actor,
            reset_camera=reset_camera,
            name=name,
            pickable=pickable,
            render=render,
            remove_existing_actor=remove_existing_actor,
        )

        # hide scalar bar if using special scalars
        if scalar_bar_args.get('title') == '__custom_rgba':
            show_scalar_bar = False

        # Only show scalar bar if there are scalars
        if show_scalar_bar and scalars is not None:
            self.add_scalar_bar(**scalar_bar_args)

        self.renderer.Modified()

        return actor

    def _add_legend_label(self, actor, label, scalars, color):
        """Add a legend label based on an actor and its scalars."""
        if not isinstance(label, str):
            raise TypeError('Label must be a string')
        geom = pyvista.Triangle()
        if scalars is not None:
            geom = pyvista.Box()
            color = Color('black')
        geom.points -= geom.center
        addr = actor.GetAddressAsString("")
        self.renderer._labels[addr] = [geom, label, color]

    def add_volume(
        self,
        volume,
        scalars=None,
        clim=None,
        resolution=None,
        opacity='linear',
        n_colors=256,
        cmap=None,
        flip_scalars=False,
        reset_camera=None,
        name=None,
        ambient=None,
        categories=False,
        culling=False,
        multi_colors=False,
        blending='composite',
        mapper=None,
        scalar_bar_args=None,
        show_scalar_bar=None,
        annotations=None,
        pickable=True,
        preference="point",
        opacity_unit_distance=None,
        shade=False,
        diffuse=0.7,  # TODO: different default for volumes
        specular=0.2,  # TODO: different default for volumes
        specular_power=10.0,  # TODO: different default for volumes
        render=True,
        user_matrix=np.eye(4),
        log_scale=False,
        **kwargs,
    ):
        """Add a volume, rendered using a smart mapper by default.

        Requires a 3D data type like :class:`numpy.ndarray`,
        :class:`pyvista.ImageData`, :class:`pyvista.RectilinearGrid`,
        or :class:`pyvista.UnstructuredGrid`.

        Parameters
        ----------
        volume : 3D numpy.ndarray | pyvista.DataSet
            The input volume to visualize. 3D numpy arrays are accepted.

            .. warning::
                If the input is not :class:`numpy.ndarray`,
                :class:`pyvista.ImageData`, or :class:`pyvista.RectilinearGrid`,
                volume rendering will often have poor performance.

        scalars : str | numpy.ndarray, optional
            Scalars used to "color" the mesh.  Accepts a string name of an
            array that is present on the mesh or an array with length equal
            to the number of cells or the number of points in the
            mesh. If ``scalars`` is ``None``, then the active scalars are used.

            Scalars may be 1 dimensional or 2 dimensional. If 1 dimensional,
            the scalars will be mapped to the lookup table. If 2 dimensional
            the scalars will be directly mapped to RGBA values, array should be
            shaped ``(N, 4)`` where ``N`` is the number of points, and of
            datatype ``np.uint8``.

            Scalars may be 1 dimensional or 2 dimensional. If 1 dimensional,
            the scalars will be mapped to the lookup table. If 2 dimensional
            the scalars will be directly mapped to RGBA values, array should be
            shaped ``(N, 4)`` where ``N`` is the number of points, and of
            datatype ``np.uint8``.

        clim : sequence[float] | float, optional
            Color bar range for scalars.  For example: ``[-1, 2]``. Defaults to
            minimum and maximum of scalars array if the scalars dtype is not
            ``np.uint8``. ``rng`` is also an accepted alias for this parameter.

            If the scalars datatype is ``np.uint8``, this parameter defaults to
            ``[0, 256]``.

            If a single value is given, the range ``[-clim, clim]`` is used.

        resolution : list, optional
            Block resolution. For example ``[1, 1, 1]``. Resolution must be
            non-negative. While VTK accepts negative spacing, this results in
            unexpected behavior. See:
            `pyvista #1967 <https://github.com/pyvista/pyvista/issues/1967>`_.

        opacity : str | numpy.ndarray, optional
            Opacity mapping for the scalars array.

            A string can also be specified to map the scalars range to a
            predefined opacity transfer function. Or you can pass a custom made
            transfer function that is an array either ``n_colors`` in length or
            array, or you can pass a string to select a built in transfer
            function. If a string, should be one of the following:

            * ``'linear'`` - Linear
            * ``'linear_r'`` - Linear except reversed
            * ``'geom'`` - Evenly spaced on the log scale
            * ``'geom_r'`` - Evenly spaced on the log scale except reversed
            * ``'sigmoid'`` - Linear map between -10.0 and 10.0
            * ``'sigmoid_1'`` - Linear map between -1.0 and 1.0
            * ``'sigmoid_2'`` - Linear map between -2.0 and 2.0
            * ``'sigmoid_3'`` - Linear map between -3.0 and 3.0
            * ``'sigmoid_4'`` - Linear map between -4.0 and 4.0
            * ``'sigmoid_5'`` - Linear map between -5.0 and 5.0
            * ``'sigmoid_6'`` - Linear map between -6.0 and 6.0
            * ``'sigmoid_7'`` - Linear map between -7.0 and 7.0
            * ``'sigmoid_8'`` - Linear map between -8.0 and 8.0
            * ``'sigmoid_9'`` - Linear map between -9.0 and 9.0
            * ``'sigmoid_10'`` - Linear map between -10.0 and 10.0
            * ``'foreground'`` - Transparent background and opaque foreground.
                Intended for use with segmentation labels. Assumes the smallest
                scalar value of the array is the background value (e.g. 0).

            If RGBA scalars are provided, this parameter is set to ``'linear'``
            to ensure the opacity transfer function has no effect on the input
            opacity values.

        n_colors : int, optional
            Number of colors to use when displaying scalars. Defaults to 256.
            The scalar bar will also have this many colors.

        cmap : str | list | pyvista.LookupTable, default: :attr:`pyvista.plotting.themes.Theme.cmap`
            If a string, this is the name of the ``matplotlib`` colormap to use
            when mapping the ``scalars``.  See available Matplotlib colormaps.
            Only applicable for when displaying ``scalars``.
            ``colormap`` is also an accepted alias
            for this. If ``colorcet`` or ``cmocean`` are installed, their
            colormaps can be specified by name.

            You can also specify a list of colors to override an existing
            colormap with a custom one.  For example, to create a three color
            colormap you might specify ``['green', 'red', 'blue']``.

            This parameter also accepts a :class:`pyvista.LookupTable`. If this
            is set, all parameters controlling the color map like ``n_colors``
            will be ignored.

        flip_scalars : bool, optional
            Flip direction of cmap. Most colormaps allow ``*_r`` suffix to do
            this as well.

        reset_camera : bool, optional
            Reset the camera after adding this mesh to the scene.

        name : str, optional
            The name for the added actor so that it can be easily
            updated.  If an actor of this name already exists in the
            rendering window, it will be replaced by the new actor.

        ambient : float, optional
            When lighting is enabled, this is the amount of light from
            0 to 1 that reaches the actor when not directed at the
            light source emitted from the viewer.  Default 0.0.

        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.

        culling : str, optional
            Does not render faces that are culled. Options are ``'front'`` or
            ``'back'``. This can be helpful for dense surface meshes,
            especially when edges are visible, but can cause flat
            meshes to be partially displayed.  Defaults ``False``.

        multi_colors : bool, optional
            Whether or not to use multiple colors when plotting MultiBlock
            object. Blocks will be colored sequentially as 'Reds', 'Greens',
            'Blues', and 'Grays'.

        blending : str, optional
            Blending mode for visualisation of the input object(s). Can be
            one of 'additive', 'maximum', 'minimum', 'composite', or
            'average'. Defaults to 'composite'.

        mapper : str, optional
            Volume mapper to use given by name. Options include:
            ``'fixed_point'``, ``'gpu'``, ``'open_gl'``, and
            ``'smart'``.  If ``None`` the ``"volume_mapper"`` in the
            ``self._theme`` is used. If using ``'fixed_point'``,
            only ``ImageData`` types can be used.

            .. note::
                If a :class:`pyvista.UnstructuredGrid` is input, the 'ugrid'
                mapper (``vtkUnstructuredGridVolumeRayCastMapper``) will be
                used regardless.

            .. note::
                The ``'smart'`` mapper chooses one of the other listed
                mappers based on rendering parameters and available
                hardware. Most of the time the ``'smart'`` simply checks
                if a GPU is available and if so, uses the ``'gpu'``
                mapper, otherwise using the ``'fixed_point'`` mapper.

            .. warning::
                The ``'fixed_point'`` mapper is CPU-based and will have
                lower performance than the ``'gpu'`` or ``'open_gl'``
                mappers.

        scalar_bar_args : dict, optional
            Dictionary of keyword arguments to pass when adding the
            scalar bar to the scene. For options, see
            :func:`pyvista.Plotter.add_scalar_bar`.

        show_scalar_bar : bool
            If ``False``, a scalar bar will not be added to the
            scene. Defaults to ``True``.

        annotations : dict, optional
            Pass a dictionary of annotations. Keys are the float
            values in the scalars range to annotate on the scalar bar
            and the values are the string annotations.

        pickable : bool, optional
            Set whether this mesh is pickable.

        preference : str, optional
            When ``mesh.n_points == mesh.n_cells`` and setting
            scalars, this parameter sets how the scalars will be
            mapped to the mesh.  Default ``'point'``, causes the
            scalars will be associated with the mesh points.  Can be
            either ``'point'`` or ``'cell'``.

        opacity_unit_distance : float, optional
            Set/Get the unit distance on which the scalar opacity
            transfer function is defined. Meaning that over that
            distance, a given opacity (from the transfer function) is
            accumulated. This is adjusted for the actual sampling
            distance during rendering. By default, this is the length
            of the diagonal of the bounding box of the volume divided
            by the dimensions.

        shade : bool, default: False
            Default off. If shading is turned on, the mapper may
            perform shading calculations - in some cases shading does
            not apply (for example, in a maximum intensity projection)
            and therefore shading will not be performed even if this
            flag is on.

        diffuse : float, default: 0.7
            The diffuse lighting coefficient.

        specular : float, default: 0.2
            The specular lighting coefficient.

        specular_power : float, default: 10.0
            The specular power. Between ``0.0`` and ``128.0``.

        render : bool, default: True
            Force a render when True.

        user_matrix : np.ndarray | vtk.vtkMatrix4x4, default: np.eye(4)
            Matrix passed to the Volume class before rendering. This affects the
            actor/rendering only, not the input volume itself. The user matrix is the
            last transformation applied to the actor before rendering. Defaults to the
            identity matrix.

        log_scale : bool, default: False
            Use log scale when mapping data to colors. Scalars less
            than zero are mapped to the smallest representable
            positive float.

        **kwargs : dict, optional
            Optional keyword arguments.

        Returns
        -------
        pyvista.Actor
            Actor of the volume.

        Examples
        --------
        Show a built-in volume example with the coolwarm colormap.

        >>> from pyvista import examples
        >>> import pyvista as pv
        >>> bolt_nut = examples.download_bolt_nut()
        >>> pl = pv.Plotter()
        >>> _ = pl.add_volume(bolt_nut, cmap="coolwarm")
        >>> pl.show()

        Create a volume from scratch and plot it using single vector of
        scalars.

        >>> import pyvista as pv
        >>> grid = pv.ImageData(dimensions=(9, 9, 9))
        >>> grid['scalars'] = -grid.x
        >>> pl = pv.Plotter()
        >>> _ = pl.add_volume(grid, opacity='linear')
        >>> pl.show()

        Plot a volume from scratch using RGBA scalars

        >>> import pyvista as pv
        >>> import numpy as np
        >>> grid = pv.ImageData(dimensions=(5, 20, 20))
        >>> scalars = grid.points - (grid.origin)
        >>> scalars /= scalars.max()
        >>> opacity = np.linalg.norm(
        ...     grid.points - grid.center, axis=1
        ... ).reshape(-1, 1)
        >>> opacity /= opacity.max()
        >>> scalars = np.hstack((scalars, opacity**3))
        >>> scalars *= 255
        >>> pl = pv.Plotter()
        >>> vol = pl.add_volume(grid, scalars=scalars.astype(np.uint8))
        >>> vol.prop.interpolation_type = 'linear'
        >>> pl.show()

        Plot an UnstructuredGrid.

        >>> from pyvista import examples
        >>> import pyvista as pv
        >>> mesh = examples.download_letter_a()
        >>> mesh['scalars'] = mesh.points[:, 1]
        >>> pl = pv.Plotter()
        >>> _ = pl.add_volume(mesh, opacity_unit_distance=0.1)
        >>> pl.show()

        """
        # Handle default arguments

        # Supported aliases
        clim = kwargs.pop('rng', clim)
        cmap = kwargs.pop('colormap', cmap)
        culling = kwargs.pop('backface_culling', culling)

        if "scalar" in kwargs:
            raise TypeError(
                "`scalar` is an invalid keyword argument for `add_mesh`. Perhaps you mean `scalars` with an s?"
            )
        assert_empty_kwargs(**kwargs)

        if show_scalar_bar is None:
            show_scalar_bar = self._theme.show_scalar_bar or scalar_bar_args

        # Avoid mutating input
        if scalar_bar_args is None:
            scalar_bar_args = {}
        else:
            scalar_bar_args = scalar_bar_args.copy()
        # account for legacy behavior
        if 'stitle' in kwargs:  # pragma: no cover
            # Deprecated on ..., estimated removal on v0.40.0
            warnings.warn(USE_SCALAR_BAR_ARGS, PyVistaDeprecationWarning)
            scalar_bar_args.setdefault('title', kwargs.pop('stitle'))

        if culling is True:
            culling = 'backface'

        if mapper is None:
            # Default mapper choice. Overridden later if UnstructuredGrid
            mapper = self._theme.volume_mapper

        # only render when the plotter has already been shown
        if render is None:
            render = not self._first_time

        # Convert the VTK data object to a pyvista wrapped object if necessary
        if not is_pyvista_dataset(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)
                if not is_pyvista_dataset(volume):
                    raise TypeError(
                        f'Object type ({type(volume)}) not supported for plotting in PyVista.'
                    )
        else:
            # HACK: Make a copy so the original object is not altered.
            #       Also, place all data on the nodes as issues arise when
            #       volume rendering on the cells.
            volume = volume.cell_data_to_point_data()

        if name is None:
            name = f'{type(volume).__name__}({volume.memory_address})'

        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
            actors = []
            for idx in range(volume.GetNumberOfBlocks()):
                if volume[idx] is None:
                    continue
                # Get a good name to use
                next_name = f'{name}-{idx}'
                # Get the data object
                block = wrap(volume.GetBlock(idx))
                if resolution is None:
                    try:
                        block_resolution = block.GetSpacing()
                    except AttributeError:
                        block_resolution = resolution
                else:
                    block_resolution = resolution
                if multi_colors:
                    color = next(cycler)
                else:
                    color = cmap

                a = self.add_volume(
                    block,
                    resolution=block_resolution,
                    opacity=opacity,
                    n_colors=n_colors,
                    cmap=color,
                    flip_scalars=flip_scalars,
                    reset_camera=reset_camera,
                    name=next_name,
                    ambient=ambient,
                    categories=categories,
                    culling=culling,
                    clim=clim,
                    mapper=mapper,
                    pickable=pickable,
                    opacity_unit_distance=opacity_unit_distance,
                    shade=shade,
                    diffuse=diffuse,
                    specular=specular,
                    specular_power=specular_power,
                    render=render,
                    show_scalar_bar=show_scalar_bar,
                )

                actors.append(a)
            return actors

        # Make sure structured grids are not less than 3D
        # ImageData and RectilinearGrid should be olay as <3D
        if isinstance(volume, pyvista.StructuredGrid):
            if any(d < 2 for d in volume.dimensions):
                raise ValueError('StructuredGrids must be 3D dimensional.')

        if isinstance(volume, pyvista.PolyData):
            raise TypeError(
                f'Type {type(volume)} not supported for volume rendering as it is not 3D.'
            )
        elif not isinstance(
            volume, (pyvista.ImageData, pyvista.RectilinearGrid, pyvista.UnstructuredGrid)
        ):
            volume = volume.cast_to_unstructured_grid()

        # Override mapper choice for UnstructuredGrid
        if isinstance(volume, pyvista.UnstructuredGrid):
            # Unstructured grid must be all tetrahedrals
            if not (volume.celltypes == pyvista.CellType.TETRA).all():
                volume = volume.triangulate()
            mapper = 'ugrid'

        if mapper == 'fixed_point' and not isinstance(volume, pyvista.ImageData):
            raise TypeError(
                f'Type {type(volume)} not supported for volume rendering with the `"fixed_point"` mapper. Use `pyvista.ImageData`.'
            )
        elif isinstance(volume, pyvista.UnstructuredGrid) and mapper != 'ugrid':
            raise TypeError(
                f'Type {type(volume)} not supported for volume rendering with the `{mapper}` mapper. Use the "ugrid" mapper or simply leave as None.'
            )

        if opacity_unit_distance is None and not isinstance(volume, pyvista.UnstructuredGrid):
            opacity_unit_distance = volume.length / (np.mean(volume.dimensions) - 1)

        if scalars is None:
            # Make sure scalars components are not vectors/tuples
            scalars = volume.active_scalars
            # Don't allow plotting of string arrays by default
            if scalars is not None and np.issubdtype(scalars.dtype, np.number):
                scalar_bar_args.setdefault('title', volume.active_scalars_info[1])
            else:
                raise MissingDataError('No scalars to use for volume rendering.')

        title = 'Data'
        if isinstance(scalars, str):
            title = scalars
            scalars = get_array(volume, scalars, preference=preference, err=True)
            scalar_bar_args.setdefault('title', title)
        elif not isinstance(scalars, np.ndarray):
            scalars = np.asarray(scalars)

        if scalars.ndim != 1:
            if scalars.ndim != 2:
                raise ValueError('`add_volume` only supports scalars with 1 or 2 dimensions')
            if scalars.shape[1] != 4 or scalars.dtype != np.uint8:
                raise ValueError(
                    '`add_volume` only supports scalars with 2 dimensions that have 4 components of datatype np.uint8.\n\n'
                    f'Scalars have shape {scalars.shape} and dtype {scalars.dtype.name!r}.'
                )

        if not np.issubdtype(scalars.dtype, np.number):
            raise TypeError('Non-numeric scalars are currently not supported for volume rendering.')
        if scalars.ndim != 1:
            if scalars.ndim != 2:
                raise ValueError('`add_volume` only supports scalars with 1 or 2 dimensions')
            if scalars.shape[1] != 4 or scalars.dtype != np.uint8:
                raise ValueError(
                    f'`add_volume` only supports scalars with 2 dimension that have 4 components of datatype np.uint8, scalars have shape {scalars.shape} and datatype {scalars.dtype}'
                )
            if opacity != 'linear':
                opacity = 'linear'
                warnings.warn('Ignoring custom opacity due to RGBA scalars.')

        # Define mapper, volume, and add the correct properties
        mappers_lookup = {
            'fixed_point': FixedPointVolumeRayCastMapper,
            'gpu': GPUVolumeRayCastMapper,
            'open_gl': OpenGLGPUVolumeRayCastMapper,
            'smart': SmartVolumeMapper,
            'ugrid': UnstructuredGridVolumeRayCastMapper,
        }
        if not isinstance(mapper, str) or mapper not in mappers_lookup.keys():
            raise TypeError(
                f"Mapper ({mapper}) unknown. Available volume mappers include: {', '.join(mappers_lookup.keys())}"
            )
        self.mapper = mappers_lookup[mapper](theme=self._theme)

        # Set scalars range
        min_, max_ = None, None
        if clim is None:
            if scalars.dtype == np.uint8:
                clim = [0, 255]
            else:
                min_, max_ = np.nanmin(scalars), np.nanmax(scalars)
                clim = [min_, max_]
        elif isinstance(clim, float) or isinstance(clim, int):
            clim = [-clim, clim]

        if log_scale:
            if clim[0] <= 0:
                clim = [sys.float_info.min, clim[1]]

        # data must be between [0, 255], but not necessarily UINT8
        # Preserve backwards compatibility and have same behavior as VTK.
        if scalars.dtype != np.uint8 and clim != [0, 255]:
            # must copy to avoid modifying inplace and remove any VTK weakref
            scalars = np.array(scalars)
            clim = np.asarray(clim, dtype=scalars.dtype)
            scalars.clip(clim[0], clim[1], out=scalars)
            if log_scale:
                out = matplotlib.colors.LogNorm(clim[0], clim[1])(scalars)
                scalars = out.data * 255
            else:
                if min_ is None:
                    min_, max_ = np.nanmin(scalars), np.nanmax(scalars)
                np.true_divide((scalars - min_), (max_ - min_) / 255, out=scalars, casting='unsafe')

        volume[title] = scalars
        volume.active_scalars_name = title

        # Scalars interpolation approach
        if scalars.shape[0] == volume.n_points:
            self.mapper.scalar_mode = 'point'
        elif scalars.shape[0] == volume.n_cells:
            self.mapper.scalar_mode = 'cell'
        else:
            raise_not_matching(scalars, volume)

        self.mapper.scalar_range = clim

        if isinstance(cmap, pyvista.LookupTable):
            self.mapper.lookup_table = cmap
        else:
            if cmap is None:
                cmap = self._theme.cmap

            cmap = get_cmap_safe(cmap)
            if categories:
                if categories is True:
                    n_colors = len(np.unique(scalars))
                elif isinstance(categories, int):
                    n_colors = categories

            if flip_scalars:
                cmap = cmap.reversed()

            # Set colormap and build lookup table
            self.mapper.lookup_table.apply_cmap(cmap, n_colors)
            self.mapper.lookup_table.apply_opacity(opacity)
            self.mapper.lookup_table.scalar_range = clim
            self.mapper.lookup_table.log_scale = log_scale
            if isinstance(annotations, dict):
                self.mapper.lookup_table.annotations = annotations

        self.mapper.dataset = volume
        self.mapper.blend_mode = blending
        self.mapper.update()

        self.volume = Volume()
        self.volume.mapper = self.mapper
        self.volume.user_matrix = user_matrix

        self.volume.prop = VolumeProperty(
            lookup_table=self.mapper.lookup_table,
            ambient=ambient,
            shade=shade,
            specular=specular,
            specular_power=specular_power,
            diffuse=diffuse,
            opacity_unit_distance=opacity_unit_distance,
        )

        if scalars.ndim == 2:
            self.volume.prop.independent_components = False
            show_scalar_bar = False

        actor, prop = self.add_actor(
            self.volume,
            reset_camera=reset_camera,
            name=name,
            culling=culling,
            pickable=pickable,
            render=render,
        )

        # Add scalar bar if scalars are available
        if show_scalar_bar and scalars is not None:
            self.add_scalar_bar(**scalar_bar_args)

        self.renderer.Modified()
        return actor

    def add_silhouette(
        self,
        mesh,
        color=None,
        line_width=None,
        opacity=None,
        feature_angle=None,
        decimate=None,
    ):
        """Add a silhouette of a PyVista or VTK dataset to the scene.

        A silhouette can also be generated directly in
        :func:`add_mesh <pyvista.Plotter.add_mesh>`. See also
        :ref:`silhouette_example`.

        Parameters
        ----------
        mesh : pyvista.DataSet | vtk.vtkAlgorithm
            Mesh or mesh-producing algorithm for generating silhouette
            to plot.

        color : ColorLike, optional
            Color of the silhouette lines.

        line_width : float, optional
            Silhouette line width.

        opacity : float, optional
            Line transparency between ``0`` and ``1``.

        feature_angle : float, optional
            If set, display sharp edges exceeding that angle in degrees.

        decimate : float, optional
            Level of decimation between ``0`` and ``1``. Decimating will
            improve rendering performance. A good rule of thumb is to
            try ``0.9``  first and decrease until the desired rendering
            performance is achieved.

        Returns
        -------
        pyvista.Actor
            Actor of the silhouette.

        Examples
        --------
        >>> import pyvista as pv
        >>> from pyvista import examples
        >>> bunny = examples.download_bunny()
        >>> plotter = pv.Plotter()
        >>> _ = plotter.add_mesh(bunny, color='lightblue')
        >>> _ = plotter.add_silhouette(bunny, color='red', line_width=8.0)
        >>> plotter.view_xy()
        >>> plotter.show()

        """
        mesh, algo = algorithm_to_mesh_handler(mesh)
        if not isinstance(mesh, pyvista.PolyData):
            algo = extract_surface_algorithm(algo or mesh)
            mesh, algo = algorithm_to_mesh_handler(algo)

        silhouette_params = self._theme.silhouette.to_dict()

        if color is None:
            color = silhouette_params["color"]
        if line_width is None:
            line_width = silhouette_params["line_width"]
        if opacity is None:
            opacity = silhouette_params["opacity"]
        if feature_angle is None:
            feature_angle = silhouette_params["feature_angle"]
        if decimate is None:
            decimate = silhouette_params["decimate"]

        # At this point we are dealing with a pipeline, so no `algo or mesh`
        if decimate:
            # Always triangulate as decimation filters needs it
            # and source mesh could have been any type
            algo = triangulate_algorithm(algo or mesh)
            algo = decimation_algorithm(algo, decimate)
            mesh, algo = algorithm_to_mesh_handler(algo)

        alg = _vtk.vtkPolyDataSilhouette()
        set_algorithm_input(alg, algo or mesh)
        alg.SetCamera(self.renderer.camera)
        if feature_angle is not None:
            alg.SetEnableFeatureAngle(True)
            alg.SetFeatureAngle(feature_angle)
        else:
            alg.SetEnableFeatureAngle(False)
        mapper = DataSetMapper(theme=self._theme)
        mapper.SetInputConnection(alg.GetOutputPort())
        actor, prop = self.add_actor(mapper)
        prop.SetColor(Color(color).float_rgb)
        prop.SetOpacity(opacity)
        prop.SetLineWidth(line_width)

        return actor

    def update_scalar_bar_range(self, clim, name=None):
        """Update the value range of the active or named scalar bar.

        Parameters
        ----------
        clim : sequence[float]
            The new range of scalar bar. For example ``[-1, 2]``.

        name : str, optional
            The title of the scalar bar to update.

        """
        if isinstance(clim, (float, int)):
            clim = [-clim, clim]
        if len(clim) != 2:
            raise TypeError('clim argument must be a length 2 iterable of values: (min, max).')
        if name is None:
            if not hasattr(self, 'mapper'):
                raise AttributeError('This plotter does not have an active mapper.')
            self.mapper.scalar_range = clim
            return

        try:
            # use the name to find the desired actor
            for mh in self.scalar_bars._scalar_bar_mappers[name]:
                mh.scalar_range = clim
        except KeyError:
            raise ValueError(f'Name ({name!r}) not valid/not found in this plotter.') from None

    def clear_actors(self):
        """Clear actors from all renderers."""
        self.renderers.clear_actors()

    def clear(self):
        """Clear plot by removing all actors and properties.

        Examples
        --------
        >>> import pyvista as pv
        >>> plotter = pv.Plotter()
        >>> actor = plotter.add_mesh(pv.Sphere())
        >>> plotter.clear()
        >>> plotter.renderer.actors
        {}

        """
        self.renderers.clear()
        self.scalar_bars.clear()
        self.mesh = None
        self.mapper = None

    def link_views(self, views=0):
        """Link the views' cameras.

        Parameters
        ----------
        views : int | tuple | list, default: 0
            If ``views`` is int, link the views to the given view
            index or if ``views`` is a tuple or a list, link the given
            views cameras.

        Examples
        --------
        Not linked view case.

        >>> import pyvista as pv
        >>> from pyvista import demos
        >>> ocube = demos.orientation_cube()
        >>> pl = pv.Plotter(shape=(1, 2))
        >>> pl.subplot(0, 0)
        >>> _ = pl.add_mesh(ocube['cube'], show_edges=True)
        >>> _ = pl.add_mesh(ocube['x_p'], color='blue')
        >>> _ = pl.add_mesh(ocube['x_n'], color='blue')
        >>> _ = pl.add_mesh(ocube['y_p'], color='green')
        >>> _ = pl.add_mesh(ocube['y_n'], color='green')
        >>> _ = pl.add_mesh(ocube['z_p'], color='red')
        >>> _ = pl.add_mesh(ocube['z_n'], color='red')
        >>> pl.camera_position = 'yz'
        >>> pl.subplot(0, 1)
        >>> _ = pl.add_mesh(ocube['cube'], show_edges=True)
        >>> _ = pl.add_mesh(ocube['x_p'], color='blue')
        >>> _ = pl.add_mesh(ocube['x_n'], color='blue')
        >>> _ = pl.add_mesh(ocube['y_p'], color='green')
        >>> _ = pl.add_mesh(ocube['y_n'], color='green')
        >>> _ = pl.add_mesh(ocube['z_p'], color='red')
        >>> _ = pl.add_mesh(ocube['z_n'], color='red')
        >>> pl.show_axes()
        >>> pl.show()

        Linked view case.

        >>> pl = pv.Plotter(shape=(1, 2))
        >>> pl.subplot(0, 0)
        >>> _ = pl.add_mesh(ocube['cube'], show_edges=True)
        >>> _ = pl.add_mesh(ocube['x_p'], color='blue')
        >>> _ = pl.add_mesh(ocube['x_n'], color='blue')
        >>> _ = pl.add_mesh(ocube['y_p'], color='green')
        >>> _ = pl.add_mesh(ocube['y_n'], color='green')
        >>> _ = pl.add_mesh(ocube['z_p'], color='red')
        >>> _ = pl.add_mesh(ocube['z_n'], color='red')
        >>> pl.camera_position = 'yz'
        >>> pl.subplot(0, 1)
        >>> _ = pl.add_mesh(ocube['cube'], show_edges=True)
        >>> _ = pl.add_mesh(ocube['x_p'], color='blue')
        >>> _ = pl.add_mesh(ocube['x_n'], color='blue')
        >>> _ = pl.add_mesh(ocube['y_p'], color='green')
        >>> _ = pl.add_mesh(ocube['y_n'], color='green')
        >>> _ = pl.add_mesh(ocube['z_p'], color='red')
        >>> _ = pl.add_mesh(ocube['z_n'], color='red')
        >>> pl.show_axes()
        >>> pl.link_views()
        >>> pl.show()

        """
        if isinstance(views, (int, np.integer)):
            camera = self.renderers[views].camera
            camera_status = self.renderers[views].camera.is_set
            for renderer in self.renderers:
                renderer.camera = camera
                renderer.camera.is_set = camera_status
            return
        views = np.asarray(views)
        if np.issubdtype(views.dtype, np.integer):
            camera = self.renderers[views[0]].camera
            camera_status = self.renderers[views[0]].camera.is_set
            for view_index in views:
                self.renderers[view_index].camera = camera
                self.renderers[view_index].camera.is_set = camera_status
        else:
            raise TypeError(f'Expected type is int, list or tuple: {type(views)} is given')

    def unlink_views(self, views=None):
        """Unlink the views' cameras.

        Parameters
        ----------
        views : int | tuple | list, optional
            If ``views`` is None unlink all the views, if ``views``
            is int unlink the selected view's camera or if ``views``
            is a tuple or a list, unlink the given views cameras.

        """
        if views is None:
            for renderer in self.renderers:
                renderer.camera = Camera()
                renderer.reset_camera()
                renderer.camera.is_set = False
        elif isinstance(views, int):
            self.renderers[views].camera = Camera()
            self.renderers[views].reset_camera()
            self.renderers[views].camera.is_set = False
        elif isinstance(views, collections.abc.Iterable):
            for view_index in views:
                self.renderers[view_index].camera = Camera()
                self.renderers[view_index].reset_camera()
                self.renderers[view_index].cemera_set = False
        else:
            raise TypeError(f'Expected type is None, int, list or tuple: {type(views)} is given')

    @wraps(ScalarBars.add_scalar_bar)
    def add_scalar_bar(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap for ``ScalarBars.add_scalar_bar``."""
        # only render when the plotter has already been shown
        render = kwargs.get('render', None)
        if render is None:
            kwargs['render'] = not self._first_time

        # check if maper exists
        mapper = kwargs.get('mapper', None)
        if mapper is None:
            if not hasattr(self, 'mapper') or self.mapper is None:
                raise AttributeError('Mapper does not exist.  Add a mesh with scalars first.')
            kwargs['mapper'] = self.mapper

        # title can be the first and only arg
        if len(args):
            title = args[0]
        else:
            title = kwargs.get('title', '')
        if title is None:
            title = ''
        kwargs['title'] = title

        interactive = kwargs.get('interactive', None)
        if interactive is None:
            interactive = self._theme.interactive
            if self.shape != (1, 1):
                interactive = False
        elif interactive and self.shape != (1, 1):
            raise ValueError('Interactive scalar bars disabled for multi-renderer plots')
        # by default, use the plotter local theme
        kwargs.setdefault('theme', self._theme)
        return self.scalar_bars.add_scalar_bar(**kwargs)

    def update_scalars(self, scalars, mesh=None, render=True):
        """Update scalars of an object in the plotter.

        Parameters
        ----------
        scalars : sequence
            Scalars to replace existing scalars.

        mesh : vtk.PolyData | vtk.UnstructuredGrid, optional
            Object that has already been added to the Plotter.  If
            None, uses last added mesh.

        render : bool, default: True
            Force a render when True.
        """
        if mesh is None:
            mesh = self.mesh

        if isinstance(mesh, (collections.abc.Iterable, pyvista.MultiBlock)):
            # Recursive if need to update scalars on many meshes
            for m in mesh:
                self.update_scalars(scalars, mesh=m, render=False)
            if render:
                self.render()
            return

        if isinstance(scalars, str):
            # Grab scalars array if name given
            scalars = get_array(mesh, scalars)

        if scalars is None:
            if render:
                self.render()
            return

        if scalars.shape[0] == mesh.GetNumberOfPoints():
            data = mesh.GetPointData()
        elif scalars.shape[0] == mesh.GetNumberOfCells():
            data = mesh.GetCellData()
        else:
            raise_not_matching(scalars, mesh)

        vtk_scalars = data.GetScalars()
        if vtk_scalars is None:
            raise ValueError('No active scalars')
        s = convert_array(vtk_scalars)
        s[:] = scalars
        vtk_scalars.Modified()
        data.Modified()
        try:
            # Why are the points updated here? Not all datasets have points
            # and only the scalars array is modified by this function...
            mesh.GetPoints().Modified()
        except:
            pass

        if render:
            self.render()

    def update_coordinates(self, points, mesh=None, render=True):
        """Update the points of an object in the plotter.

        Parameters
        ----------
        points : np.ndarray
            Points to replace existing points.

        mesh : vtk.PolyData | vtk.UnstructuredGrid, optional
            Object that has already been added to the Plotter.  If ``None``, uses
            last added mesh.

        render : bool, default: True
            Force a render when True.
        """
        if mesh is None:
            mesh = self.mesh

        mesh.points = points

        # only render when the plotter has already been shown
        if render is None:
            render = not self._first_time

        if render:
            self.render()

    def _clear_ren_win(self):
        """Clear the render window."""
        # Not using `render_window` property here to enforce clean up
        if hasattr(self, 'ren_win'):
            self.ren_win.Finalize()
            del self.ren_win

    def close(self, render=False):
        """Close the render window.

        Parameters
        ----------
        render : bool
            Unused argument.

        """
        # optionally run just prior to exiting the plotter
        if self._before_close_callback is not None:
            self._before_close_callback(self)
            self._before_close_callback = None

        # must close out widgets first
        super().close()
        # Renderer has an axes widget, so close it
        self.renderers.close()
        self.renderers.remove_all_lights()

        # Grab screenshots of last render
        # self.last_image = self.screenshot(None, return_img=True)
        # self.last_image_depth = self.get_image_depth()

        # reset scalar bars
        self.scalar_bars.clear()
        self.mesh = None
        self.mapper = None

        # grab the display id before clearing the window
        # this is an experimental feature
        if KILL_DISPLAY:  # pragma: no cover
            disp_id = None
            if self.render_window is not None:
                disp_id = self.render_window.GetGenericDisplayId()
        self._clear_ren_win()

        if self.iren is not None:
            self.iren.close()
            if KILL_DISPLAY:  # pragma: no cover
                _kill_display(disp_id)
            self.iren = None

        if hasattr(self, 'text'):
            del self.text

        # end movie
        if hasattr(self, 'mwriter'):
            try:
                self.mwriter.close()
            except BaseException:
                pass

        # Remove the global reference to this plotter unless building the
        # gallery to allow it to collect.
        if not pyvista.BUILDING_GALLERY:
            if _ALL_PLOTTERS is not None:
                _ALL_PLOTTERS.pop(self._id_name, None)

        # this helps managing closed plotters
        self._closed = True

    def deep_clean(self):
        """Clean the plotter of the memory."""
        self.disable_picking()
        if hasattr(self, 'renderers'):
            self.renderers.deep_clean()
        self.mesh = None
        self.mapper = None
        self.volume = None
        self.text = None

    def add_text(
        self,
        text,
        position='upper_left',
        font_size=18,
        color=None,
        font=None,
        shadow=False,
        name=None,
        viewport=False,
        orientation=0.0,
        font_file=None,
        *,
        render=True,
    ):
        """Add text to plot object in the top left corner by default.

        Parameters
        ----------
        text : str
            The text to add the rendering.

        position : str | sequence[float], default: "upper_left"
            Position to place the bottom left corner of the text box.
            If tuple is used, the position of the text uses the pixel
            coordinate system (default). In this case,
            it returns a more general `vtkOpenGLTextActor`.
            If string name is used, it returns a `vtkCornerAnnotation`
            object normally used for fixed labels (like title or xlabel).
            Default is to find the top left corner of the rendering window
            and place text box up there. Available position: ``'lower_left'``,
            ``'lower_right'``, ``'upper_left'``, ``'upper_right'``,
            ``'lower_edge'``, ``'upper_edge'``, ``'right_edge'``, and
            ``'left_edge'``.

        font_size : float, default: 18
            Sets the size of the title font.

        color : ColorLike, optional
            Either a string, RGB list, or hex color string.  For example:

            * ``color='white'``
            * ``color='w'``
            * ``color=[1.0, 1.0, 1.0]``
            * ``color='#FFFFFF'``

            Defaults to :attr:`pyvista.global_theme.font.color <pyvista.plotting.themes._Font.color>`.

        font : str, default: 'arial'
            Font name may be ``'courier'``, ``'times'``, or ``'arial'``.
            This is ignored if the `font_file` is set.

        shadow : bool, default: False
            Adds a black shadow to the text.

        name : str, optional
            The name for the added actor so that it can be easily updated.
            If an actor of this name already exists in the rendering window, it
            will be replaced by the new actor.

        viewport : bool, default: False
            If ``True`` and position is a tuple of float, uses the
            normalized viewport coordinate system (values between 0.0
            and 1.0 and support for HiDPI).

        orientation : float, default: 0.0
            Angle orientation of text counterclockwise in degrees.  The text
            is rotated around an anchor point that may be on the edge or
            corner of the text.  The default is horizontal (0.0 degrees).

        font_file : str, default: None
            The absolute file path to a local file containing a freetype
            readable font.

        render : bool, default: True
            Force a render when ``True``.

        Returns
        -------
        vtk.vtkTextActor
            Text actor added to plot.

        Examples
        --------
        Add blue text to the upper right of the plotter.

        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> actor = pl.add_text(
        ...     'Sample Text',
        ...     position='upper_right',
        ...     color='blue',
        ...     shadow=True,
        ...     font_size=26,
        ... )
        >>> pl.show()

        Add text and use a custom freetype readable font file.

        >>> pl = pv.Plotter()
        >>> actor = pl.add_text(
        ...     'Text',
        ...     font_file='/home/user/Mplus2-Regular.ttf',
        ... )  # doctest:+SKIP

        """
        if font_size is None:
            font_size = self._theme.font.size
        if position is None:
            # Set the position of the text to the top left corner
            window_size = self.window_size
            x = (window_size[0] * 0.02) / self.shape[0]
            y = (window_size[1] * 0.85) / self.shape[0]
            position = [x, y]
        text_prop = TextProperty(
            color=color,
            font_family=font,
            orientation=orientation,
            font_file=font_file,
            shadow=shadow,
        )
        if isinstance(position, (int, str, bool)):
            self.text = CornerAnnotation(position, text, linear_font_scale_factor=font_size // 2)
        else:
            self.text = Text(text=text, position=position)
            if viewport:
                self.text.GetActualPositionCoordinate().SetCoordinateSystemToNormalizedViewport()
                self.text.GetActualPosition2Coordinate().SetCoordinateSystemToNormalizedViewport()
            text_prop.font_size = int(font_size * 2)
        self.text.prop = text_prop
        self.add_actor(self.text, reset_camera=False, name=name, pickable=False, render=render)
        return self.text

    def open_movie(self, filename, framerate=24, quality=5, **kwargs):
        """Establish a connection to the ffmpeg writer.

        Requires ``imageio`` to be installed.

        Parameters
        ----------
        filename : str
            Filename of the movie to open.  Filename should end in mp4,
            but other filetypes may be supported.  See :func:`imageio.get_writer()
            <imageio.v2.get_writer>`.

        framerate : int, default: 24
            Frames per second.

        quality : int, default: 5
            Quality 10 is the top possible quality for any codec. The
            range is ``0 - 10``.  Higher quality leads to a larger file.

        **kwargs : dict, optional
            See the documentation for :func:`imageio.get_writer()
            <imageio.v2.get_writer>` for additional kwargs.

        Notes
        -----
        See the documentation for :func:`imageio.get_writer() <imageio.v2.get_writer>`.

        Examples
        --------
        Open a MP4 movie and set the quality to maximum.

        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> pl.open_movie('movie.mp4', quality=10)  # doctest:+SKIP

        """
        try:
            from imageio import get_writer
        except ModuleNotFoundError:  # pragma: no cover
            raise ModuleNotFoundError(
                'Install imageio to use `open_movie` with:\n\n   pip install imageio'
            ) from None

        if isinstance(pyvista.FIGURE_PATH, str) and not os.path.isabs(filename):
            filename = os.path.join(pyvista.FIGURE_PATH, filename)
        self.mwriter = get_writer(filename, fps=framerate, quality=quality, **kwargs)

    def open_gif(
        self,
        filename,
        loop=0,
        fps=10,
        palettesize=256,
        subrectangles=False,
        **kwargs,
    ):
        """Open a gif file.

        Requires ``imageio`` to be installed.

        Parameters
        ----------
        filename : str
            Filename of the gif to open.  Filename must end in ``"gif"``.

        loop : int, default: 0
            The number of iterations. Default value of 0 loops indefinitely.

        fps : float, default: 10
            The number of frames per second. If duration is not given, the
            duration for each frame is set to 1/fps.

        palettesize : int, default: 256
            The number of colors to quantize the image to. Is rounded to the
            nearest power of two. Must be between 2 and 256.

        subrectangles : bool, default: False
            If ``True``, will try and optimize the GIF by storing only the rectangular
            parts of each frame that change with respect to the previous.

            .. note::
               Setting this to ``True`` may help reduce jitter in colorbars.

        **kwargs : dict, optional
            See the documentation for :func:`imageio.get_writer() <imageio.v2.get_writer>`
            for additional kwargs.

        Notes
        -----
        Consider using `pygifsicle
        <https://github.com/LucaCappelletti94/pygifsicle>`_ to reduce the final
        size of the gif. See `Optimizing a GIF using pygifsicle
        <https://imageio.readthedocs.io/en/stable/examples.html#optimizing-a-gif-using-pygifsicle>`_.

        Examples
        --------
        Open a gif file, setting the framerate to 8 frames per second and
        reducing the colorspace to 64.

        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> pl.open_gif(
        ...     'movie.gif', fps=8, palettesize=64
        ... )  # doctest:+SKIP

        See :ref:`gif_movie_example` for a full example using this method.

        """
        try:
            from imageio import __version__, get_writer
        except ModuleNotFoundError:  # pragma: no cover
            raise ModuleNotFoundError(
                'Install imageio to use `open_gif` with:\n\n   pip install imageio'
            ) from None

        if filename[-3:] != 'gif':
            raise ValueError('Unsupported filetype.  Must end in .gif')
        if isinstance(pyvista.FIGURE_PATH, str) and not os.path.isabs(filename):
            filename = os.path.join(pyvista.FIGURE_PATH, filename)
        self._gif_filename = os.path.abspath(filename)

        kwargs['mode'] = 'I'
        kwargs['loop'] = loop
        kwargs['palettesize'] = palettesize
        kwargs['subrectangles'] = subrectangles
        if scooby.meets_version(__version__, '2.28.1'):
            kwargs['duration'] = 1000 * 1 / fps
        else:  # pragma: no cover
            kwargs['fps'] = fps

        self.mwriter = get_writer(filename, **kwargs)

    def write_frame(self):
        """Write a single frame to the movie file.

        Examples
        --------
        >>> import pyvista as pv
        >>> plotter = pv.Plotter()
        >>> plotter.open_movie(filename)  # doctest:+SKIP
        >>> plotter.add_mesh(pv.Sphere())  # doctest:+SKIP
        >>> plotter.write_frame()  # doctest:+SKIP

        See :ref:`movie_example` for a full example using this method.

        """
        # if off screen, show has not been called and we must render
        # before extracting an image
        if self._first_time:
            self._on_first_render_request()
            self.render()

        if not hasattr(self, 'mwriter'):
            raise RuntimeError('This plotter has not opened a movie or GIF file.')
        self.update()
        self.mwriter.append_data(self.image)

    def get_image_depth(self, fill_value=np.nan, reset_camera_clipping_range=True):
        """Return a depth image representing current render window.

        Parameters
        ----------
        fill_value : float, default: numpy.nan
            Fill value for points in image that do not include objects
            in scene.  To not use a fill value, pass ``None``.

        reset_camera_clipping_range : bool, default: True
            Reset the camera clipping range to include data in view.

        Returns
        -------
        pyvista.pyvista_ndarray
            Image of depth values from camera orthogonal to image
            plane.

        Notes
        -----
        Values in image_depth are negative to adhere to a
        right-handed coordinate system.

        Examples
        --------
        >>> import pyvista as pv
        >>> plotter = pv.Plotter()
        >>> actor = plotter.add_mesh(pv.Sphere())
        >>> plotter.show()
        >>> zval = plotter.get_image_depth()

        """
        # allow no render window
        if self.render_window is None and self.last_image_depth is not None:
            zval = self.last_image_depth.copy()
            if fill_value is not None:
                zval[self._image_depth_null] = fill_value
            return zval

        self._check_rendered()
        self._check_has_ren_win()

        # Ensure points in view are within clipping range of renderer?
        if reset_camera_clipping_range:
            self.renderer.ResetCameraClippingRange()

        # Get the z-buffer image
        ifilter = _vtk.vtkWindowToImageFilter()
        ifilter.SetInput(self.render_window)
        ifilter.SetScale(self.image_scale)
        ifilter.ReadFrontBufferOff()
        ifilter.SetInputBufferTypeToZBuffer()
        zbuff = run_image_filter(ifilter)[:, :, 0]

        # Convert z-buffer values to depth from camera
        with warnings.catch_warnings():
            warnings.filterwarnings('ignore')
            near, far = self.camera.clipping_range
            if self.camera.parallel_projection:
                zval = (zbuff - near) / (far - near)
            else:
                zval = 2 * near * far / ((zbuff - 0.5) * 2 * (far - near) - near - far)

            # Consider image values outside clipping range as nans
            self._image_depth_null = np.logical_or(zval < -far, np.isclose(zval, -far))

        if fill_value is not None:
            zval[self._image_depth_null] = fill_value

        return zval

    def add_lines(self, lines, color='w', width=5, label=None, name=None, connected=False):
        """Add lines to the plotting object.

        Parameters
        ----------
        lines : np.ndarray
            Points representing line segments.  For example, two line
            segments would be represented as ``np.array([[0, 1, 0],
            [1, 0, 0], [1, 1, 0], [2, 0, 0]])``.

        color : ColorLike, default: 'w'
            Either a string, rgb list, or hex color string.  For example:

            * ``color='white'``
            * ``color='w'``
            * ``color=[1.0, 1.0, 1.0]``
            * ``color='#FFFFFF'``

        width : float, default: 5
            Thickness of lines.

        label : str, default: None
            String label to use when adding a legend to the scene with
            :func:`pyvista.Plotter.add_legend`.

        name : str, default: None
            The name for the added actor so that it can be easily updated.
            If an actor of this name already exists in the rendering window, it
            will be replaced by the new actor.

        connected : bool, default: False
            Treat ``lines`` as points representing a series of *connected* lines.
            For example, two connected line segments would be represented as
            ``np.array([[0, 0, 0], [1, 0, 0], [1, 1, 0]])``. If ``False``, an *even*
            number of points must be passed to ``lines``, and the lines need not be
            connected.

        Returns
        -------
        vtk.vtkActor
            Lines actor.

        Examples
        --------
        Plot two lines.

        >>> import numpy as np
        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> points = np.array([[0, 1, 0], [1, 0, 0], [1, 1, 0], [2, 0, 0]])
        >>> actor = pl.add_lines(points, color='purple', width=3)
        >>> pl.camera_position = 'xy'
        >>> pl.show()

        Adding lines with ``connected=True`` will add a series of connected
        line segments.

        >>> pl = pv.Plotter()
        >>> points = np.array([[0, 1, 0], [1, 0, 0], [1, 1, 0], [2, 0, 0]])
        >>> actor = pl.add_lines(
        ...     points, color='purple', width=3, connected=True
        ... )
        >>> pl.camera_position = 'xy'
        >>> pl.show()

        """
        if not isinstance(lines, np.ndarray):
            raise TypeError('Input should be an array of point segments')

        lines = (
            pyvista.lines_from_points(lines)
            if connected
            else pyvista.line_segments_from_points(lines)
        )

        actor = Actor(mapper=DataSetMapper(lines))
        actor.prop.line_width = width
        actor.prop.show_edges = True
        actor.prop.edge_color = color
        actor.prop.color = color
        actor.prop.lighting = False

        # legend label
        if label:
            if not isinstance(label, str):
                raise TypeError('Label must be a string')
            addr = actor.GetAddressAsString("")
            self.renderer._labels[addr] = [lines, label, Color(color)]

        # Add to renderer
        self.add_actor(actor, reset_camera=False, name=name, pickable=False)
        return actor

    @wraps(ScalarBars.remove_scalar_bar)
    def remove_scalar_bar(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Remove the active scalar bar."""
        self.scalar_bars.remove_scalar_bar(*args, **kwargs)

    def add_point_labels(
        self,
        points,
        labels,
        italic=False,
        bold=True,
        font_size=None,
        text_color=None,
        font_family=None,
        shadow=False,
        show_points=True,
        point_color=None,
        point_size=None,
        name=None,
        shape_color='grey',
        shape='rounded_rect',
        fill_shape=True,
        margin=3,
        shape_opacity=1.0,
        pickable=False,
        render_points_as_spheres=False,
        tolerance=0.001,
        reset_camera=None,
        always_visible=False,
        render=True,
    ):
        """Create a point actor with one label from list labels assigned to each point.

        Parameters
        ----------
        points : sequence | pyvista.DataSet | vtk.vtkAlgorithm
            An ``n x 3`` sequence points or :class:`pyvista.DataSet` with
            points or mesh-producing algorithm.

        labels : list | str
            List of labels.  Must be the same length as points. If a
            string name is given with a :class:`pyvista.DataSet` input for
            points, then these are fetched.

        italic : bool, default: False
            Italicises title and bar labels.

        bold : bool, default: True
            Bolds title and bar labels.

        font_size : float, optional
            Sets the size of the title font.

        text_color : ColorLike, optional
            Color of text. Either a string, RGB sequence, or hex color string.

            * ``text_color='white'``
            * ``text_color='w'``
            * ``text_color=[1.0, 1.0, 1.0]``
            * ``text_color='#FFFFFF'``

        font_family : str, optional
            Font family.  Must be either ``'courier'``, ``'times'``,
            or ``'arial``.

        shadow : bool, default: False
            Adds a black shadow to the text.

        show_points : bool, default: True
            Controls if points are visible.

        point_color : ColorLike, optional
            Either a string, rgb list, or hex color string.  One of
            the following.

            * ``point_color='white'``
            * ``point_color='w'``
            * ``point_color=[1.0, 1.0, 1.0]``
            * ``point_color='#FFFFFF'``

        point_size : float, optional
            Size of points if visible.

        name : str, optional
            The name for the added actor so that it can be easily
            updated.  If an actor of this name already exists in the
            rendering window, it will be replaced by the new actor.

        shape_color : ColorLike, default: "grey"
            Color of shape (if visible).  Either a string, rgb
            sequence, or hex color string.

        shape : str, default: "rounded_rect"
            The string name of the shape to use. Options are ``'rect'`` or
            ``'rounded_rect'``. If you want no shape, pass ``None``.

        fill_shape : bool, default: True
            Fill the shape with the ``shape_color``. Outlines if ``False``.

        margin : int, default: 3
            The size of the margin on the label background shape.

        shape_opacity : float, default: 1.0
            The opacity of the shape in the range of ``[0, 1]``.

        pickable : bool, default: False
            Set whether this actor is pickable.

        render_points_as_spheres : bool, default: False
            Render points as spheres rather than dots.

        tolerance : float, default: 0.001
            A tolerance to use to determine whether a point label is
            visible.  A tolerance is usually required because the
            conversion from world space to display space during
            rendering introduces numerical round-off.

        reset_camera : bool, optional
            Reset the camera after adding the points to the scene.

        always_visible : bool, default: False
            Skip adding the visibility filter.

        render : bool, default: True
            Force a render when ``True``.

        Returns
        -------
        vtk.vtkActor2D
            VTK label actor.  Can be used to change properties of the labels.

        Examples
        --------
        >>> import numpy as np
        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> points = np.array(
        ...     [[0.0, 0.0, 0.0], [1.0, 1.0, 0.0], [2.0, 0.0, 0.0]]
        ... )
        >>> labels = ['Point A', 'Point B', 'Point C']
        >>> actor = pl.add_point_labels(
        ...     points,
        ...     labels,
        ...     italic=True,
        ...     font_size=20,
        ...     point_color='red',
        ...     point_size=20,
        ...     render_points_as_spheres=True,
        ...     always_visible=True,
        ...     shadow=True,
        ... )
        >>> pl.camera_position = 'xy'
        >>> pl.show()

        """
        if font_family is None:
            font_family = self._theme.font.family
        if font_size is None:
            font_size = self._theme.font.size
        point_color = Color(point_color, default_color=self._theme.color)

        if isinstance(points, (list, tuple)):
            points = np.array(points)

        if isinstance(points, np.ndarray):
            points = pyvista.PolyData(points)  # Cast to poly data
        elif not is_pyvista_dataset(points) and not isinstance(points, _vtk.vtkAlgorithm):
            raise TypeError(f'Points type not usable: {type(points)}')
        points, algo = algorithm_to_mesh_handler(points)
        if algo is not None:
            if pyvista.vtk_version_info < (9, 1):  # pragma: no cover
                from pyvista.core.errors import VTKVersionError

                raise VTKVersionError(
                    'To use vtkAlgorithms with `add_point_labels` requires VTK 9.1 or later.'
                )
            # Extract points filter
            pc_algo = _vtk.vtkConvertToPointCloud()
            set_algorithm_input(pc_algo, algo)
            algo = pc_algo

        if name is None:
            name = f'{type(points).__name__}({points.memory_address})'

        hier = _vtk.vtkPointSetToLabelHierarchy()
        if not isinstance(labels, str):
            if algo is not None:
                raise TypeError(
                    'If using a vtkAlgorithm input, the labels must be a named array on the dataset.'
                )
            points = pyvista.PolyData(points.points)
            if len(points.points) != len(labels):
                raise ValueError('There must be one label for each point')
            vtklabels = _vtk.vtkStringArray()
            vtklabels.SetName('labels')
            for item in labels:
                vtklabels.InsertNextValue(str(item))
            points.GetPointData().AddArray(vtklabels)
            hier.SetLabelArrayName('labels')
        else:
            # Make sure PointData
            if labels not in points.point_data:
                raise ValueError(f'Array {labels!r} not found in point data.')
            hier.SetLabelArrayName(labels)

        if always_visible:
            set_algorithm_input(hier, algo or points)
        else:
            # Only show visible points
            vis_points = _vtk.vtkSelectVisiblePoints()
            set_algorithm_input(vis_points, algo or points)
            vis_points.SetRenderer(self.renderer)
            vis_points.SetTolerance(tolerance)

            hier.SetInputConnection(vis_points.GetOutputPort())

        # create label mapper
        label_mapper = _vtk.vtkLabelPlacementMapper()
        label_mapper.SetInputConnection(hier.GetOutputPort())
        if not isinstance(shape, str):
            label_mapper.SetShapeToNone()
        elif shape.lower() in 'rect':
            label_mapper.SetShapeToRect()
        elif shape.lower() in 'rounded_rect':
            label_mapper.SetShapeToRoundedRect()
        else:
            raise ValueError(f'Shape ({shape}) not understood')
        if fill_shape:
            label_mapper.SetStyleToFilled()
        else:
            label_mapper.SetStyleToOutline()
        label_mapper.SetBackgroundColor(Color(shape_color).float_rgb)
        label_mapper.SetBackgroundOpacity(shape_opacity)
        label_mapper.SetMargin(margin)

        textprop = hier.GetTextProperty()
        textprop.SetItalic(italic)
        textprop.SetBold(bold)
        textprop.SetFontSize(font_size)
        textprop.SetFontFamily(parse_font_family(font_family))
        textprop.SetColor(Color(text_color, default_color=self._theme.font.color).float_rgb)
        textprop.SetShadow(shadow)

        self.remove_actor(f'{name}-points', reset_camera=False)
        self.remove_actor(f'{name}-labels', reset_camera=False)

        # add points
        if show_points:
            self.add_mesh(
                algo or points,
                color=point_color,
                point_size=point_size,
                name=f'{name}-points',
                pickable=pickable,
                render_points_as_spheres=render_points_as_spheres,
                reset_camera=reset_camera,
                render=render,
            )

        label_actor = _vtk.vtkActor2D()
        label_actor.SetMapper(label_mapper)
        self.add_actor(label_actor, reset_camera=False, name=f'{name}-labels', pickable=False)
        return label_actor

    def add_point_scalar_labels(self, points, labels, fmt=None, preamble='', **kwargs):
        """Label the points from a dataset with the values of their scalars.

        Wrapper for :func:`pyvista.Plotter.add_point_labels`.

        Parameters
        ----------
        points : sequence[float] | np.ndarray | pyvista.DataSet
            An ``n x 3`` numpy.ndarray or pyvista dataset with points.

        labels : list | str
            List of scalars of labels.  Must be the same length as points. If a
            string name is given with a :class:`pyvista.DataSet` input for
            points, then these are fetched.

        fmt : str, optional
            String formatter used to format numerical data.

        preamble : str, default: ""
            Text before the start of each label.

        **kwargs : dict, optional
            Keyword arguments passed to
            :func:`pyvista.Plotter.add_point_labels`.

        Returns
        -------
        vtk.vtkActor2D
            VTK label actor.  Can be used to change properties of the labels.

        """
        if not is_pyvista_dataset(points):
            points, _ = _coerce_pointslike_arg(points, copy=False)
        if not isinstance(labels, (str, list)):
            raise TypeError(
                'labels must be a string name of the scalars array to use or list of scalars'
            )
        if fmt is None:
            fmt = self._theme.font.fmt
        if fmt is None:
            fmt = '%.6e'
        if isinstance(points, np.ndarray):
            scalars = labels
        elif is_pyvista_dataset(points):
            scalars = points.point_data[labels]
        phrase = f'{preamble} {fmt}'
        labels = [phrase % val for val in scalars]
        return self.add_point_labels(points, labels, **kwargs)

    def add_points(self, points, style='points', **kwargs):
        """Add points to a mesh.

        Parameters
        ----------
        points : numpy.ndarray or pyvista.DataSet
            Array of points or the points from a pyvista object.

        style : str, default: 'points'
            Visualization style of the mesh.  One of the following:
            ``style='points'``, ``style='points_gaussian'``.
            ``'points_gaussian'`` can be controlled with the ``emissive`` and
            ``render_points_as_spheres`` options.

        **kwargs : dict, optional
            See :func:`pyvista.Plotter.add_mesh` for optional
            keyword arguments.

        Returns
        -------
        pyvista.Actor
            Actor of the mesh.

        Examples
        --------
        Add a numpy array of points to a mesh.

        >>> import numpy as np
        >>> import pyvista as pv
        >>> points = np.random.random((10, 3))
        >>> pl = pv.Plotter()
        >>> actor = pl.add_points(
        ...     points, render_points_as_spheres=True, point_size=100.0
        ... )
        >>> pl.show()

        Plot using the ``'points_gaussian'`` style

        >>> points = np.random.random((10, 3))
        >>> pl = pv.Plotter()
        >>> actor = pl.add_points(points, style='points_gaussian')
        >>> pl.show()

        """
        if style not in ['points', 'points_gaussian']:
            raise ValueError(
                f'Invalid style {style} for add_points. Should be either "points" or '
                '"points_gaussian".'
            )
        return self.add_mesh(points, style=style, **kwargs)

    def add_arrows(self, cent, direction, mag=1, **kwargs):
        """Add arrows to the plotter.

        Parameters
        ----------
        cent : np.ndarray
            Array of centers.

        direction : np.ndarray
            Array of direction vectors.

        mag : float, optional
            Amount to scale the direction vectors.

        **kwargs : dict, optional
            See :func:`pyvista.Plotter.add_mesh` for optional
            keyword arguments.

        Returns
        -------
        pyvista.Actor
            Actor of the arrows.

        Examples
        --------
        Plot a random field of vectors and save a screenshot of it.

        >>> import numpy as np
        >>> import pyvista as pv
        >>> cent = np.random.random((10, 3))
        >>> direction = np.random.random((10, 3))
        >>> plotter = pv.Plotter()
        >>> _ = plotter.add_arrows(cent, direction, mag=2)
        >>> plotter.show()

        """
        if cent.shape != direction.shape:  # pragma: no cover
            raise ValueError('center and direction arrays must have the same shape')

        direction = direction.copy()
        if cent.ndim != 2:
            cent = cent.reshape((-1, 3))

        if direction.ndim != 2:
            direction = direction.reshape((-1, 3))

        if mag != 1:
            direction = direction * 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)

    @staticmethod
    def _save_image(image, filename, return_img):
        """Save to file and/or return a NumPy image array.

        This is an internal helper.

        """
        if not image.size:
            raise ValueError('Empty image. Have you run plot() first?')
        # write screenshot to file if requested
        if isinstance(filename, (str, pathlib.Path, io.BytesIO)):
            from PIL import Image

            if isinstance(filename, (str, pathlib.Path)):
                filename = pathlib.Path(filename)
                if isinstance(pyvista.FIGURE_PATH, str) and not filename.is_absolute():
                    filename = pathlib.Path(os.path.join(pyvista.FIGURE_PATH, filename))
                if not filename.suffix:
                    filename = filename.with_suffix('.png')
                elif filename.suffix not in SUPPORTED_FORMATS:
                    raise ValueError(
                        f'Unsupported extension {filename.suffix}\n'
                        f'Must be one of the following: {SUPPORTED_FORMATS}'
                    )
                filename = os.path.abspath(os.path.expanduser(str(filename)))
                Image.fromarray(image).save(filename)
            else:
                Image.fromarray(image).save(filename, format="PNG")
        # return image array if requested
        if return_img:
            return image

    def save_graphic(self, filename, title='PyVista Export', raster=True, painter=True):
        """Save a screenshot of the rendering window as a graphic file.

        This can be helpful for publication documents.

        The supported formats are:

        * ``'.svg'``
        * ``'.eps'``
        * ``'.ps'``
        * ``'.pdf'``
        * ``'.tex'``

        Parameters
        ----------
        filename : str
            Path to fsave the graphic file to.

        title : str, default: "PyVista Export"
            Title to use within the file properties.

        raster : bool, default: True
            Attempt to write 3D properties as a raster image.

        painter : bool, default: True
            Configure the exporter to expect a painter-ordered 2D
            rendering, that is, a rendering at a fixed depth where
            primitives are drawn from the bottom up.

        Examples
        --------
        >>> import pyvista as pv
        >>> from pyvista import examples
        >>> pl = pv.Plotter()
        >>> _ = pl.add_mesh(examples.load_airplane(), smooth_shading=True)
        >>> _ = pl.add_background_image(examples.mapfile)
        >>> pl.save_graphic("img.svg")  # doctest:+SKIP

        """
        from vtkmodules.vtkIOExportGL2PS import vtkGL2PSExporter

        if self.render_window is None:
            raise AttributeError('This plotter is closed and unable to save a screenshot.')
        if self._first_time:
            self._on_first_render_request()
            self.render()
        if isinstance(pyvista.FIGURE_PATH, str) and not os.path.isabs(filename):
            filename = os.path.join(pyvista.FIGURE_PATH, filename)
        filename = os.path.abspath(os.path.expanduser(filename))
        extension = pyvista.core.utilities.fileio.get_ext(filename)

        writer = vtkGL2PSExporter()
        modes = {
            '.svg': writer.SetFileFormatToSVG,
            '.eps': writer.SetFileFormatToEPS,
            '.ps': writer.SetFileFormatToPS,
            '.pdf': writer.SetFileFormatToPDF,
            '.tex': writer.SetFileFormatToTeX,
        }
        if extension not in modes:
            raise ValueError(
                f"Extension ({extension}) is an invalid choice.\n\n"
                f"Valid options include: {', '.join(modes.keys())}"
            )
        writer.CompressOff()
        writer.SetFilePrefix(filename.replace(extension, ''))
        writer.SetInput(self.render_window)
        modes[extension]()
        writer.SetTitle(title)
        writer.SetWrite3DPropsAsRasterImage(raster)
        if painter:
            writer.UsePainterSettings()
        writer.Update()

    def screenshot(
        self,
        filename=None,
        transparent_background=None,
        return_img=True,
        window_size=None,
        scale=None,
    ):
        """Take screenshot at current camera position.

        Parameters
        ----------
        filename : str | pathlib.Path | io.BytesIO, optional
            Location to write image to.  If ``None``, no image is written.

        transparent_background : bool, optional
            Whether to make the background transparent.  The default is
            looked up on the plotter's theme.

        return_img : bool, default: True
            If ``True``, a :class:`numpy.ndarray` of the image will be
            returned.

        window_size : sequence[int], optional
            Set the plotter's size to this ``(width, height)`` before
            taking the screenshot.

        scale : int, optional
            Set the factor to scale the window size to make a higher
            resolution image. If ``None`` this will use the ``image_scale``
            property on this plotter which defaults to one.

        Returns
        -------
        pyvista.pyvista_ndarray
            Array containing pixel RGB and alpha.  Sized:

            * [Window height x Window width x 3] if
              ``transparent_background`` is set to ``False``.
            * [Window height x Window width x 4] if
              ``transparent_background`` is set to ``True``.

        Examples
        --------
        >>> import pyvista as pv
        >>> sphere = pv.Sphere()
        >>> plotter = pv.Plotter(off_screen=True)
        >>> actor = plotter.add_mesh(sphere)
        >>> plotter.screenshot('screenshot.png')  # doctest:+SKIP

        """
        with self.window_size_context(window_size):
            # configure image filter
            if transparent_background is None:
                transparent_background = self._theme.transparent_background
            self.image_transparent_background = transparent_background

            # This if statement allows you to save screenshots of closed plotters
            # This is needed for the sphinx-gallery to work
            if self.render_window is None:
                # If plotter has been closed...
                # check if last_image exists
                if self.last_image is not None:
                    # Save last image
                    if scale is not None:
                        warnings.warn(
                            'This plotter is closed and cannot be scaled. Using the last saved image. Try using the `image_scale` property directly.'
                        )
                    return self._save_image(self.last_image, filename, return_img)
                # Plotter hasn't been rendered or was improperly closed
                raise RuntimeError('This plotter is closed and unable to save a screenshot.')

            if self._first_time and not self.off_screen:
                raise RuntimeError(
                    "Nothing to screenshot - call .show first or use the off_screen argument"
                )

            # if off screen, show has not been called and we must render
            # before extracting an image
            if self._first_time:
                self._on_first_render_request()
                self.render()

            with self.image_scale_context(scale):
                self._make_render_window_current()
                return self._save_image(self.image, filename, return_img)

    @wraps(Renderers.set_background)
    def set_background(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderers.set_background``."""
        self.renderers.set_background(*args, **kwargs)

    @wraps(Renderers.set_color_cycler)
    def set_color_cycler(self, *args, **kwargs):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderers.set_color_cycler``."""
        self.renderers.set_color_cycler(*args, **kwargs)

    def generate_orbital_path(self, factor=3.0, n_points=20, viewup=None, shift=0.0):
        """Generate an orbital path around the data scene.

        Parameters
        ----------
        factor : float, default: 3.0
            A scaling factor when building the orbital extent.

        n_points : int, default: 20
            Number of points on the orbital path.

        viewup : sequence[float], optional
            The normal to the orbital plane.

        shift : float, default: 0.0
            Shift the plane up/down from the center of the scene by
            this amount.

        Returns
        -------
        pyvista.PolyData
            PolyData containing the orbital path.

        Examples
        --------
        Generate an orbital path around a sphere.

        >>> import pyvista as pv
        >>> plotter = pv.Plotter()
        >>> _ = plotter.add_mesh(pv.Sphere())
        >>> viewup = [0, 0, 1]
        >>> orbit = plotter.generate_orbital_path(
        ...     factor=2.0, n_points=50, shift=0.0, viewup=viewup
        ... )

        See :ref:`orbiting_example` for a full example using this method.

        """
        if viewup is None:
            viewup = self._theme.camera['viewup']
        center = np.array(self.center)
        bnds = np.array(self.bounds)
        radius = (bnds[1] - bnds[0]) * factor
        y = (bnds[3] - bnds[2]) * factor
        if y > radius:
            radius = y
        center += np.array(viewup) * shift
        return pyvista.Polygon(center=center, radius=radius, normal=viewup, n_sides=n_points)

    def fly_to(self, point):
        """Move the current camera's focal point to a position point.

        The movement is animated over the number of frames specified in
        NumberOfFlyFrames. The LOD desired frame rate is used.

        Parameters
        ----------
        point : sequence[float]
            Point to fly to in the form of ``(x, y, z)``.

        """
        self.iren.fly_to(self.renderer, point)

    def orbit_on_path(
        self,
        path=None,
        focus=None,
        step=0.5,
        viewup=None,
        write_frames=False,
        threaded=False,
        progress_bar=False,
    ):
        """Orbit on the given path focusing on the focus point.

        Parameters
        ----------
        path : pyvista.PolyData
            Path of orbital points. The order in the points is the order of
            travel.

        focus : sequence[float], optional
            The point of focus the camera. For example ``(0.0, 0.0, 0.0)``.

        step : float, default: 0.5
            The timestep between flying to each camera position. Ignored when
            ``plotter.off_screen = True``.

        viewup : sequence[float], optional
            The normal to the orbital plane.

        write_frames : bool, default: False
            Assume a file is open and write a frame on each camera
            view during the orbit.

        threaded : bool, default: False
            Run this as a background thread.  Generally used within a
            GUI (i.e. PyQt).

        progress_bar : bool, default: False
            Show the progress bar when proceeding through the path.
            This can be helpful to show progress when generating
            movies with ``off_screen=True``.

        Examples
        --------
        Plot an orbit around the earth.  Save the gif as a temporary file.

        >>> import os
        >>> from tempfile import mkdtemp
        >>> import pyvista as pv
        >>> from pyvista import examples
        >>> mesh = examples.load_globe()
        >>> texture = examples.load_globe_texture()
        >>> filename = os.path.join(mkdtemp(), 'orbit.gif')
        >>> plotter = pv.Plotter(window_size=[300, 300])
        >>> _ = plotter.add_mesh(
        ...     mesh, texture=texture, smooth_shading=True
        ... )
        >>> plotter.open_gif(filename)
        >>> viewup = [0, 0, 1]
        >>> orbit = plotter.generate_orbital_path(
        ...     factor=2.0, n_points=24, shift=0.0, viewup=viewup
        ... )
        >>> plotter.orbit_on_path(
        ...     orbit, write_frames=True, viewup=viewup, step=0.02
        ... )

        See :ref:`orbiting_example` for a full example using this method.

        """
        if focus is None:
            focus = self.center
        if viewup is None:
            viewup = self._theme.camera['viewup']
        if path is None:
            path = self.generate_orbital_path(viewup=viewup)
        if not is_pyvista_dataset(path):
            path = pyvista.PolyData(path)
        points = path.points

        # Make sure the whole scene is visible
        self.camera.thickness = path.length

        if progress_bar:
            try:
                from tqdm import tqdm
            except ImportError:  # pragma: no cover
                raise ImportError("Please install `tqdm` to use ``progress_bar=True``")

        def orbit():
            """Define the internal thread for running the orbit."""
            if progress_bar:
                points_seq = tqdm(points)
            else:
                points_seq = points

            for point in points_seq:
                tstart = time.time()  # include the render time in the step time
                self.set_position(point, render=False)
                self.set_focus(focus, render=False)
                self.set_viewup(viewup, render=False)
                self.renderer.ResetCameraClippingRange()
                if write_frames:
                    self.write_frame()
                else:
                    self.render()
                sleep_time = step - (time.time() - tstart)
                if sleep_time > 0 and not self.off_screen:
                    time.sleep(sleep_time)
            if write_frames:
                self.mwriter.close()

        if threaded:
            thread = Thread(target=orbit)
            thread.start()
        else:
            orbit()

    def export_obj(self, filename):
        """Export scene to OBJ format.

        Parameters
        ----------
        filename : str
            Filename to export the scene to.  Must end in ``'.obj'``.

        Examples
        --------
        Export the scene to "scene.obj"

        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> _ = pl.add_mesh(pv.Sphere())
        >>> pl.export_obj('scene.obj')  # doctest:+SKIP

        """
        from vtkmodules.vtkIOExport import vtkOBJExporter

        if self.render_window is None:
            raise RuntimeError("This plotter must still have a render window open.")
        if isinstance(pyvista.FIGURE_PATH, str) and not os.path.isabs(filename):
            filename = os.path.join(pyvista.FIGURE_PATH, filename)
        else:
            filename = os.path.abspath(os.path.expanduser(filename))

        if not filename.endswith('.obj'):
            raise ValueError('`filename` must end with ".obj"')

        exporter = vtkOBJExporter()
        # remove the extension as VTK always adds it in
        exporter.SetFilePrefix(filename[:-4])
        exporter.SetRenderWindow(self.render_window)
        exporter.Write()

    @property
    def _datasets(self):
        """Return a list of all datasets associated with this plotter."""
        datasets = []
        for renderer in self.renderers:
            for actor in renderer.actors.values():
                mapper = actor.GetMapper()

                # ignore any mappers whose inputs are not datasets
                if hasattr(mapper, 'GetInputAsDataSet'):
                    datasets.append(wrap(mapper.GetInputAsDataSet()))

        return datasets

    def __del__(self):
        """Delete the plotter."""
        # We have to check here if the plotter was only partially initialized
        if self._initialized:
            if not self._closed:
                self.close()
        self.deep_clean()
        if self._initialized:
            del self.renderers

    def add_background_image(self, image_path, scale=1.0, auto_resize=True, as_global=True):
        """Add a background image to a plot.

        Parameters
        ----------
        image_path : str
            Path to an image file.

        scale : float, default: 1.0
            Scale the image larger or smaller relative to the size of
            the window.  For example, a scale size of 2 will make the
            largest dimension of the image twice as large as the
            largest dimension of the render window.

        auto_resize : bool, default: True
            Resize the background when the render window changes size.

        as_global : bool, default: True
            When multiple render windows are present, setting
            ``as_global=False`` will cause the background to only
            appear in one window.

        Examples
        --------
        >>> import pyvista as pv
        >>> from pyvista import examples
        >>> plotter = pv.Plotter()
        >>> actor = plotter.add_mesh(pv.Sphere())
        >>> plotter.add_background_image(examples.mapfile)
        >>> plotter.show()

        """
        if self.renderers.has_active_background_renderer:
            raise RuntimeError(
                'A background image already exists.  '
                'Remove it with ``remove_background_image`` '
                'before adding one'
            )

        # Need to change the number of layers to support an additional
        # background layer
        if not self._has_background_layer:
            self.render_window.SetNumberOfLayers(3)
        renderer = self.renderers.add_background_renderer(image_path, scale, as_global)
        self.render_window.AddRenderer(renderer)

        # set up autoscaling of the image
        if auto_resize:  # pragma: no cover
            self.iren.add_observer('ModifiedEvent', renderer.resize)

    @wraps(Renderers.remove_background_image)
    def remove_background_image(self):  # numpydoc ignore=PR01,RT01
        """Wrap ``Renderers.remove_background_image``."""
        self.renderers.remove_background_image()

        # return the active renderer to the top, otherwise flat background
        # will not be rendered
        self.renderer.layer = 0

    def _on_first_render_request(self):
        """Once an image or render is officially requested, run this routine.

        For example on the show call or any screenshot producing code.
        """
        # reset unless camera for the first render unless camera is set
        if self._first_time:
            for renderer in self.renderers:
                if not renderer.camera.is_set:
                    renderer.camera_position = renderer.get_default_cam_pos()
                    renderer.ResetCamera()
            self._first_time = False

    def reset_camera_clipping_range(self):
        """Reset camera clipping planes."""
        self.renderer.ResetCameraClippingRange()

    def add_light(self, light, only_active=False):
        """Add a Light to the scene.

        Parameters
        ----------
        light : Light or vtkLight
            The light to be added.

        only_active : bool, default: False
            If ``True``, only add the light to the active
            renderer. The default is that every renderer adds the
            light. To add the light to an arbitrary renderer, see
            :func:`pyvista.Renderer.add_light`.

        Examples
        --------
        Create a plotter that we initialize with no lights, and add a
        cube and a single headlight to it.

        >>> import pyvista as pv
        >>> plotter = pv.Plotter(lighting='none')
        >>> _ = plotter.add_mesh(pv.Cube())
        >>> light = pv.Light(color='cyan', light_type='headlight')
        >>> plotter.add_light(light)
        >>> plotter.show()

        """
        renderers = [self.renderer] if only_active else self.renderers
        for renderer in renderers:
            renderer.add_light(light)

    def remove_all_lights(self, only_active=False):
        """Remove all lights from the scene.

        Parameters
        ----------
        only_active : bool, default: False
            If ``True``, only remove lights from the active
            renderer. The default is that lights are stripped from
            every renderer.

        Examples
        --------
        Create a plotter and remove all lights after initialization.
        Note how the mesh rendered is completely flat

        >>> import pyvista as pv
        >>> plotter = pv.Plotter()
        >>> plotter.remove_all_lights()
        >>> plotter.renderer.lights
        []
        >>> _ = plotter.add_mesh(pv.Sphere(), show_edges=True)
        >>> plotter.show()

        Note how this differs from a plot with default lighting

        >>> pv.Sphere().plot(show_edges=True, lighting=True)

        """
        renderers = [self.renderer] if only_active else self.renderers
        for renderer in renderers:
            renderer.remove_all_lights()

    def where_is(self, name):
        """Return the subplot coordinates of a given actor.

        Parameters
        ----------
        name : str
            Actor's name.

        Returns
        -------
        list[tuple[numpy.int64, numpy.int64]]
            A list with the subplot coordinates of the actor.

        Examples
        --------
        >>> import pyvista as pv
        >>> plotter = pv.Plotter(shape=(2, 2))
        >>> plotter.subplot(0, 0)
        >>> _ = plotter.add_mesh(pv.Box(), name='box')
        >>> plotter.subplot(0, 1)
        >>> _ = plotter.add_mesh(pv.Sphere(), name='sphere')
        >>> plotter.subplot(1, 0)
        >>> _ = plotter.add_mesh(pv.Box(), name='box')
        >>> plotter.subplot(1, 1)
        >>> _ = plotter.add_mesh(pv.Cone(), name='cone')
        >>> plotter.where_is('box')
        [(0, 0), (1, 0)]

        >>> plotter.show()
        """
        places = []
        for index in range(len(self.renderers)):
            if name in self.renderers[index]._actors:
                places.append(tuple(self.renderers.index_to_loc(index)))
        return places

class Plotter(BasePlotter):
    """Plotting object to display vtk meshes or numpy arrays.

    Parameters
    ----------
    off_screen : bool, optional
        Renders off screen when ``True``.  Useful for automated
        screenshots.

    notebook : bool, optional
        When ``True``, the resulting plot is placed inline a jupyter
        notebook.  Assumes a jupyter console is active.  Automatically
        enables ``off_screen``.

    shape : sequence[int], optional
        Number of sub-render windows inside of the main window.
        Specify two across with ``shape=(2, 1)`` and a two by two grid
        with ``shape=(2, 2)``.  By default there is only one render
        window.  Can also accept a string descriptor as shape. E.g.:

        * ``shape="3|1"`` means 3 plots on the left and 1 on the right,
        * ``shape="4/2"`` means 4 plots on top and 2 at the bottom.

    border : bool, optional
        Draw a border around each render window.

    border_color : ColorLike, default: "k"
        Either a string, rgb list, or hex color string.  For example:

            * ``color='white'``
            * ``color='w'``
            * ``color=[1.0, 1.0, 1.0]``
            * ``color='#FFFFFF'``

    window_size : sequence[int], optional
        Window size in pixels.  Defaults to ``[1024, 768]``, unless
        set differently in the relevant theme's ``window_size``
        property.

    multi_samples : int, optional
        The number of multi-samples used to mitigate aliasing. 4 is a
        good default but 8 will have better results with a potential
        impact on performance.

    line_smoothing : bool, default: False
        If ``True``, enable line smoothing.

    polygon_smoothing : bool, default: False
        If ``True``, enable polygon smoothing.

    lighting : str, default: 'light kit"
        Lighting to set up for the plotter. Accepted options:

        * ``'light kit'``: a vtk Light Kit composed of 5 lights.
        * ``'three lights'``: illumination using 3 lights.
        * ``'none'``: no light sources at instantiation.

        The default is a ``'light kit'`` (to be precise, 5 separate
        lights that act like a Light Kit).

    theme : pyvista.plotting.themes.Theme, optional
        Plot-specific theme.

    image_scale : int, optional
        Scale factor when saving screenshots. Image sizes will be
        the ``window_size`` multiplied by this scale factor.

    Examples
    --------
    >>> import pyvista as pv
    >>> mesh = pv.Cube()
    >>> another_mesh = pv.Sphere()
    >>> pl = pv.Plotter()
    >>> actor = pl.add_mesh(
    ...     mesh, color='red', style='wireframe', line_width=4
    ... )
    >>> actor = pl.add_mesh(another_mesh, color='blue')
    >>> pl.show()

    """

    last_update_time = 0.0

    def __init__(
        self,
        off_screen=None,
        notebook=None,
        shape=(1, 1),
        groups=None,
        row_weights=None,
        col_weights=None,
        border=None,
        border_color='k',
        border_width=2.0,
        window_size=None,
        multi_samples=None,
        line_smoothing=False,
        point_smoothing=False,
        polygon_smoothing=False,
        splitting_position=None,
        title=None,
        lighting='light kit',
        theme=None,
        image_scale=None,
    ):
        """Initialize a vtk plotting object."""
        super().__init__(
            shape=shape,
            border=border,
            border_color=border_color,
            border_width=border_width,
            groups=groups,
            row_weights=row_weights,
            col_weights=col_weights,
            splitting_position=splitting_position,
            title=title,
            lighting=lighting,
            theme=theme,
            image_scale=image_scale,
        )
        # reset partial initialization flag
        self._initialized = False

        log.debug('Plotter init start')

        # check if a plotting backend is enabled
        _warn_xserver()

        if off_screen is None:
            off_screen = pyvista.OFF_SCREEN

        if notebook is None:
            if self._theme.notebook is not None:
                notebook = self._theme.notebook
            else:
                notebook = scooby.in_ipykernel()

        self.notebook = notebook
        if self.notebook:
            off_screen = True
        self.off_screen = off_screen

        # initialize render window
        self.ren_win = _vtk.vtkRenderWindow()
        self.render_window.SetMultiSamples(0)
        self.render_window.SetBorders(True)
        if line_smoothing:
            self.render_window.LineSmoothingOn()
        if point_smoothing:
            self.render_window.PointSmoothingOn()
        if polygon_smoothing:
            self.render_window.PolygonSmoothingOn()

        for renderer in self.renderers:
            self.render_window.AddRenderer(renderer)

        # Add the shadow renderer to allow us to capture interactions within
        # a given viewport
        # https://vtk.org/pipermail/vtkusers/2018-June/102030.html
        number_or_layers = self.render_window.GetNumberOfLayers()
        current_layer = self.renderer.GetLayer()
        self.render_window.SetNumberOfLayers(number_or_layers + 1)
        self.render_window.AddRenderer(self.renderers.shadow_renderer)
        self.renderers.shadow_renderer.SetLayer(current_layer + 1)
        self.renderers.shadow_renderer.SetInteractive(False)  # never needs to capture

        if self.off_screen:
            self.render_window.SetOffScreenRendering(1)
            # vtkGenericRenderWindowInteractor has no event loop and
            # allows the display client to close on Linux when
            # off_screen.  We still want an interactor for off screen
            # plotting since there are some widgets (like the axes
            # widget) that need an interactor
            interactor = _vtk.vtkGenericRenderWindowInteractor()
        else:
            interactor = None

        # Add ren win and interactor
        self.iren = RenderWindowInteractor(self, light_follow_camera=False, interactor=interactor)
        self.iren.set_render_window(self.render_window)
        self.reset_key_events()
        self.enable_trackball_style()  # internally calls update_style()
        self.iren.add_observer("KeyPressEvent", self.key_press_event)

        # Set camera widget based on theme. This requires that an
        # interactor be present.
        if self.theme._enable_camera_orientation_widget:
            self.add_camera_orientation_widget()

        # Set background
        self.set_background(self._theme.background)

        # Set window size
        self._window_size_unset = False
        if window_size is None:
            self.window_size = self._theme.window_size
            if self.window_size == pyvista.plotting.themes.Theme().window_size:
                self._window_size_unset = True
        else:
            self.window_size = window_size

        if self._theme.depth_peeling.enabled:
            if self.enable_depth_peeling():
                for renderer in self.renderers:
                    renderer.enable_depth_peeling()

        # set anti_aliasing based on theme
        if self.theme.anti_aliasing:
            self.enable_anti_aliasing(self.theme.anti_aliasing)

        # some cleanup only necessary for fully initialized plotters
        self._initialized = True
        log.debug('Plotter init stop')

    def show(
        self,
        title=None,
        window_size=None,
        interactive=True,
        auto_close=None,
        interactive_update=False,
        full_screen=None,
        screenshot=False,
        return_img=False,
        cpos=None,
        jupyter_backend=None,
        return_viewer=False,
        return_cpos=None,
        before_close_callback=None,
        **kwargs,
    ):
        """Display the plotting window.

        Parameters
        ----------
        title : str, optional
            Title of plotting window.  Defaults to
            :attr:`pyvista.global_theme.title <pyvista.plotting.themes.Theme.title>`.

        window_size : list, optional
            Window size in pixels.  Defaults to
            :attr:`pyvista.global_theme.window_size <pyvista.plotting.themes.Theme.window_size>`.

        interactive : bool, optional
            Enabled by default.  Allows user to pan and move figure.
            Defaults to
            :attr:`pyvista.global_theme.interactive <pyvista.plotting.themes.Theme.interactive>`.

        auto_close : bool, optional
            Exits plotting session when user closes the window when
            interactive is ``True``.  Defaults to
            :attr:`pyvista.global_theme.auto_close <pyvista.plotting.themes.Theme.auto_close>`.

        interactive_update : bool, default: False
            Allows user to non-blocking draw, user should call
            :func:`Plotter.update` in each iteration.

        full_screen : bool, optional
            Opens window in full screen.  When enabled, ignores
            ``window_size``.  Defaults to
            :attr:`pyvista.global_theme.full_screen <pyvista.plotting.themes.Theme.full_screen>`.

        screenshot : str | pathlib.Path | io.BytesIO | bool, default: False
            Take a screenshot of the initial state of the plot.  If a string,
            it specifies the path to which the screenshot is saved. If
            ``True``, the screenshot is returned as an array. For interactive
            screenshots it's recommended to first call ``show()`` with
            ``auto_close=False`` to set the scene, then save the screenshot in
            a separate call to ``show()`` or :func:`Plotter.screenshot`.
            See also the ``before_close_callback`` parameter for an
            alternative.

        return_img : bool, default: False
            Returns a numpy array representing the last image along
            with the camera position.

        cpos : sequence[sequence[float]], optional
            The camera position.  You can also set this with
            :attr:`Plotter.camera_position`.

        jupyter_backend : str, optional
            Jupyter notebook plotting backend to use.  One of the
            following:

            * ``'none'`` : Do not display in the notebook.
            * ``'static'`` : Display a static figure.
            * ``'trame'`` : Display a dynamic figure with Trame.

            This can also be set globally with
            :func:`pyvista.set_jupyter_backend`.

            A dictionary ``jupyter_kwargs`` can also be passed to further
            configure how the backend displays.

        return_viewer : bool, default: False
            Return the jupyterlab viewer, scene, or display object when
            plotting with Jupyter notebook. When ``False`` and within a Jupyter
            environment, the scene will be immediately shown within the
            notebook. Set this to ``True`` to return the scene instead.

        return_cpos : bool, optional
            Return the last camera position from the render window
            when enabled.  Default based on theme setting.  See
            :attr:`pyvista.plotting.themes.Theme.return_cpos`.

        before_close_callback : Callable, optional
            Callback that is called before the plotter is closed.
            The function takes a single parameter, which is the plotter object
            before it closes. An example of use is to capture a screenshot after
            interaction::

                def fun(plotter):
                    plotter.screenshot('file.png')

        **kwargs : dict, optional
            Developer keyword arguments.

        Returns
        -------
        cpos : list
            List of camera position, focal point, and view up.
            Returned only when ``return_cpos=True`` or set in the
            default global or plot theme.

        image : np.ndarray
            Numpy array of the last image when either ``return_img=True``
            or ``screenshot=True`` is set. Optionally contains alpha
            values. Sized:

            * [Window height x Window width x 3] if the theme sets
              ``transparent_background=False``.
            * [Window height x Window width x 4] if the theme sets
              ``transparent_background=True``.

        widget : ipywidgets.Widget
            IPython widget when ``return_viewer=True``.

        Notes
        -----
        Please use the ``q``-key to close the plotter as some
        operating systems (namely Windows) will experience issues
        saving a screenshot if the exit button in the GUI is pressed.

        Examples
        --------
        Simply show the plot of a mesh.

        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> _ = pl.add_mesh(pv.Cube())
        >>> pl.show()

        Take a screenshot interactively.  Screenshot will be of the
        first image shown, so use the first call with
        ``auto_close=False`` to set the scene before taking the
        screenshot.

        >>> pl = pv.Plotter()
        >>> _ = pl.add_mesh(pv.Cube())
        >>> pl.show(auto_close=False)  # doctest:+SKIP
        >>> pl.show(screenshot='my_image.png')  # doctest:+SKIP

        Obtain the camera position when using ``show``.

        >>> pl = pv.Plotter()
        >>> _ = pl.add_mesh(pv.Sphere())
        >>> pl.show(return_cpos=True)  # doctest:+SKIP
        [(2.223005211686484, -0.3126909484828709, 2.4686209867735065),
        (0.0, 0.0, 0.0),
        (-0.6839951597283509, -0.47207319712073137, 0.5561452310578585)]

        """
        jupyter_kwargs = kwargs.pop('jupyter_kwargs', {})
        assert_empty_kwargs(**kwargs)

        if before_close_callback is None:
            before_close_callback = pyvista.global_theme._before_close_callback
        self._before_close_callback = before_close_callback

        if interactive_update and auto_close is None:
            auto_close = False
        elif interactive_update and auto_close:
            warnings.warn(
                textwrap.dedent(
                    """
                    The plotter will close immediately automatically since ``auto_close=True``.
                    Either, do not specify ``auto_close``, or set it to ``False`` if you want to
                    interact with the plotter interactively.
                    """
                ).strip()
            )
        elif auto_close is None:
            auto_close = self._theme.auto_close

        if self.render_window is None:
            raise RuntimeError("This plotter has been closed and cannot be shown.")

        if full_screen is None:
            full_screen = self._theme.full_screen

        if full_screen:
            self.render_window.SetFullScreen(True)
            self.render_window.BordersOn()  # super buggy when disabled
        else:
            if window_size is None:
                window_size = self.window_size
            else:
                self._window_size_unset = False
            self.render_window.SetSize(window_size[0], window_size[1])

        # reset unless camera for the first render unless camera is set
        self.camera_position = cpos
        self._on_first_render_request()

        # handle plotter notebook
        if jupyter_backend and not self.notebook:
            warnings.warn(
                'Not within a jupyter notebook environment.\nIgnoring ``jupyter_backend``.'
            )

        jupyter_disp = None
        if self.notebook:
            from pyvista.jupyter.notebook import handle_plotter

            if jupyter_backend is None:
                jupyter_backend = self._theme.jupyter_backend

            if jupyter_backend.lower() != 'none':
                jupyter_disp = handle_plotter(self, backend=jupyter_backend, **jupyter_kwargs)

        self.render()

        # initial double render needed for certain passes when offscreen
        if self.off_screen and 'vtkDepthOfFieldPass' in self.renderer._render_passes._passes:
            self.render()

        # This has to be after the first render for some reason
        if title is None:
            title = self.title
        if title:
            self.render_window.SetWindowName(title)
            self.title = title

        # Keep track of image for sphinx-gallery
        if pyvista.BUILDING_GALLERY:
            # always save screenshots for sphinx_gallery
            self.last_image = self.screenshot(screenshot, return_img=True)
            self.last_image_depth = self.get_image_depth()
            try:
                self.last_vtksz = self.export_vtksz(filename=None)
            except ImportError:
                pass

        # See: https://github.com/pyvista/pyvista/issues/186#issuecomment-550993270
        if interactive and not self.off_screen:
            try:  # interrupts will be caught here
                log.debug('Starting iren')
                self.iren.update_style()
                if not interactive_update:
                    # Resolves #1260
                    if os.name == 'nt':  # pragma: no cover
                        self.iren.process_events()
                    self.iren.start()

                if pyvista.vtk_version_info < (9, 2, 3):  # pragma: no cover
                    self.iren.initialize()

            except KeyboardInterrupt:
                log.debug('KeyboardInterrupt')
                self.close()
                raise KeyboardInterrupt
        # In the event that the user hits the exit-button on the GUI  (on
        # Windows OS) then it must be finalized and deleted as accessing it
        # will kill the kernel.
        # Here we check for that and clean it up before moving on to any of
        # the closing routines that might try to still access that
        # render window.
        # Ignore if using a Jupyter display
        _is_current = self.render_window.IsCurrent()
        if jupyter_disp is None and not _is_current:
            self._clear_ren_win()  # The ren_win is deleted
            # proper screenshots cannot be saved if this happens
            if not auto_close:
                warnings.warn(
                    "`auto_close` ignored: by clicking the exit button, "
                    "you have destroyed the render window and we have to "
                    "close it out."
                )
            self.close()
            if screenshot:
                warnings.warn(
                    "A screenshot is unable to be taken as the render window is not current or rendering is suppressed."
                )
        if _is_current:
            self.last_image = self.screenshot(screenshot, return_img=True)
            self.last_image_depth = self.get_image_depth()
        # NOTE: after this point, nothing from the render window can be accessed
        #       as if a user pressed the close button, then it destroys the
        #       the render view and a stream of errors will kill the Python
        #       kernel if code here tries to access that renderer.
        #       See issues #135 and #186 for insight before editing the
        #       remainder of this function.

        # Close the render window if requested
        if jupyter_disp is None and auto_close:
            # Plotters are never auto-closed in Jupyter
            self.close()

        if jupyter_disp is not None and not return_viewer:
            # Default behaviour is to display the Jupyter viewer
            try:
                from IPython import display
            except ImportError:  # pragma: no cover
                raise ImportError('Install IPython to display an image in a notebook')
            display.display(jupyter_disp)

        # Three possible return values: (cpos, image, widget)
        return_values = tuple(
            val
            for val in (
                self.camera_position if return_cpos else None,
                self.last_image if return_img or screenshot is True else None,
                jupyter_disp if return_viewer else None,
            )
            if val is not None
        )
        if len(return_values) == 1:
            return return_values[0]
        return return_values or None

    def add_title(self, title, font_size=18, color=None, font=None, shadow=False):
        """Add text to the top center of the plot.

        This is merely a convenience method that calls ``add_text``
        with ``position='upper_edge'``.

        Parameters
        ----------
        title : str
            The text to add the rendering.

        font_size : float, default: 18
            Sets the size of the title font.

        color : ColorLike, optional
            Either a string, rgb list, or hex color string.  Defaults
            to white or the value of the global theme if set.  For
            example:

            * ``color='white'``
            * ``color='w'``
            * ``color=[1.0, 1.0, 1.0]``
            * ``color='#FFFFFF'``

        font : str, optional
            Font name may be ``'courier'``, ``'times'``, or ``'arial'``.

        shadow : bool, default: False
            Adds a black shadow to the text.

        Returns
        -------
        vtk.vtkTextActor
            Text actor added to plot.

        Examples
        --------
        >>> import pyvista as pv
        >>> pl = pv.Plotter()
        >>> pl.background_color = 'grey'
        >>> actor = pl.add_title(
        ...     'Plot Title', font='courier', color='k', font_size=40
        ... )
        >>> pl.show()

        """
        # add additional spacing from the top of the figure by default
        title = '\n' + title
        return self.add_text(
            title,
            position='upper_edge',
            font_size=font_size,
            color=color,
            font=font,
            shadow=shadow,
            name='title',
            viewport=False,
        )

    def add_cursor(
        self,
        bounds=(-1.0, 1.0, -1.0, 1.0, -1.0, 1.0),
        focal_point=(0.0, 0.0, 0.0),
        color=None,
    ):
        """Add a cursor of a PyVista or VTK dataset to the scene.

        Parameters
        ----------
        bounds : sequence[float], default: (-1.0, 1.0, -1.0, 1.0, -1.0, 1.0)
            Specify the bounds in the format of:

            - ``(xmin, xmax, ymin, ymax, zmin, zmax)``

        focal_point : sequence[float], default: (0.0, 0.0, 0.0)
            The focal point of the cursor.

        color : ColorLike, optional
            Either a string, RGB sequence, or hex color string.  For one
            of the following.

            * ``color='white'``
            * ``color='w'``
            * ``color=[1.0, 1.0, 1.0]``
            * ``color='#FFFFFF'``

        Returns
        -------
        vtk.vtkActor
            VTK actor of the 2D cursor.

        Examples
        --------
        >>> import pyvista as pv
        >>> sphere = pv.Sphere()
        >>> plotter = pv.Plotter()
        >>> _ = plotter.add_mesh(sphere)
        >>> _ = plotter.add_cursor()
        >>> plotter.show()

        """
        alg = _vtk.vtkCursor3D()
        alg.SetModelBounds(bounds)
        alg.SetFocalPoint(focal_point)
        alg.AllOn()
        mapper = DataSetMapper(theme=self._theme)
        mapper.SetInputConnection(alg.GetOutputPort())
        actor, prop = self.add_actor(mapper)
        prop.SetColor(Color(color).float_rgb)

        return actor

    @property
    def meshes(self):  # numpydoc ignore=RT01
        """Return plotter meshes.

        Returns
        -------
        List[Union[pyvista.DataSet, PyVista.MultiBlock]]
            List of mesh objects such as pyvista.PolyData, pyvista.UnstructuredGrid, etc.
        """
        meshes = []
        for actor in self.actors.values():
            if hasattr(actor, 'mapper'):
                meshes.append(actor.mapper.dataset)

        return meshes

# Tracks created plotters.  This is the end of the module as we need to
# define ``BasePlotter`` before including it in the type definition.
#
# When pyvista.BUILDING_GALLERY = False, the objects will be ProxyType, and
# when True, BasePlotter.
_ALL_PLOTTERS: Dict[str, BasePlotter] = {}

def _kill_display(disp_id):  # pragma: no cover
    """Forcibly close the display on Linux.

    See: https://gitlab.kitware.com/vtk/vtk/-/issues/17917#note_783584

    And more details into why...
    https://stackoverflow.com/questions/64811503

    Notes
    -----
    This is to be used experimentally and is known to cause issues
    on `pyvistaqt`

    """
    if platform.system() != 'Linux':
        raise OSError('This method only works on Linux')

    if disp_id:
        cdisp_id = int(disp_id[1:].split('_')[0], 16)

        # this is unsafe as events might be queued, but sometimes the
        # window fails to close if we don't just close it
        Thread(target=X11.XCloseDisplay, args=(cdisp_id,)).start()