text: import warnings
  from abc import ABC, abstractmethod
  from collections import namedtuple
  from contextlib import contextmanager
  from typing import List, Optional
  
  import numpy as np
  
  from ...utils.dask_utils import configure_dask
  from ...utils.events import EmitterGroup, Event
  from ...utils.key_bindings import KeymapProvider
  from ...utils.misc import ROOT_DIR
  from ...utils.mouse_bindings import MousemapProvider
  from ...utils.naming import magic_name
  from ...utils.status_messages import generate_layer_status
  from ...utils.transforms import Affine, TransformChain
  from ..utils.layer_utils import (
      compute_multiscale_level_and_corners,
      convert_to_uint8,
  )
  from ._base_constants import Blending
  
  Extent = namedtuple('Extent', 'data world step')
  
  
  class Layer(KeymapProvider, MousemapProvider, ABC):
      """Base layer class.
  
      Parameters
      ----------
      name : str
          Name of the layer.
      metadata : dict
          Layer metadata.
      scale : tuple of float
          Scale factors for the layer.
      translate : tuple of float
          Translation values for the layer.
      rotate : float, 3-tuple of float, or n-D array.
          If a float convert into a 2D rotation matrix using that value as an
          angle. If 3-tuple convert into a 3D rotation matrix, using a yaw,
          pitch, roll convention. Otherwise assume an nD rotation. Angles are
          assumed to be in degrees. They can be converted from radians with
          np.degrees if needed.
      shear : 1-D array or n-D array
          Either a vector of upper triangular values, or an nD shear matrix with
          ones along the main diagonal.
      affine : n-D array or napari.utils.transforms.Affine
          (N+1, N+1) affine transformation matrix in homogeneous coordinates.
          The first (N, N) entries correspond to a linear transform and
          the final column is a lenght N translation vector and a 1 or a napari
          AffineTransform object. If provided then translate, scale, rotate, and
          shear values are ignored.
      opacity : float
          Opacity of the layer visual, between 0.0 and 1.0.
      blending : str
          One of a list of preset blending modes that determines how RGB and
          alpha values of the layer visual get mixed. Allowed values are
          {'opaque', 'translucent', and 'additive'}.
      visible : bool
          Whether the layer visual is currently being displayed.
      multiscale : bool
          Whether the data is multiscale or not. Multiscale data is
          represented by a list of data objects and should go from largest to
          smallest.
  
      Attributes
      ----------
      name : str
          Unique name of the layer.
      opacity : float
          Opacity of the layer visual, between 0.0 and 1.0.
      visible : bool
          Whether the layer visual is currently being displayed.
      blending : Blending
          Determines how RGB and alpha values get mixed.
              Blending.OPAQUE
                  Allows for only the top layer to be visible and corresponds to
                  depth_test=True, cull_face=False, blend=False.
              Blending.TRANSLUCENT
                  Allows for multiple layers to be blended with different opacity
                  and corresponds to depth_test=True, cull_face=False,
                  blend=True, blend_func=('src_alpha', 'one_minus_src_alpha').
              Blending.ADDITIVE
                  Allows for multiple layers to be blended together with
                  different colors and opacity. Useful for creating overlays. It
                  corresponds to depth_test=False, cull_face=False, blend=True,
                  blend_func=('src_alpha', 'one').
      scale : tuple of float
          Scale factors for the layer.
      translate : tuple of float
          Translation values for the layer.
      rotate : float, 3-tuple of float, or n-D array.
          If a float convert into a 2D rotation matrix using that value as an
          angle. If 3-tuple convert into a 3D rotation matrix, using a yaw,
          pitch, roll convention. Otherwise assume an nD rotation. Angles are
          assumed to be in degrees. They can be converted from radians with
          np.degrees if needed.
      shear : 1-D array or n-D array
          Either a vector of upper triangular values, or an nD shear matrix with
          ones along the main diagonal.
      affine : n-D array or napari.utils.transforms.Affine
          (N+1, N+1) affine transformation matrix in homogeneous coordinates.
          The first (N, N) entries correspond to a linear transform and
          the final column is a lenght N translation vector and a 1 or a napari
          AffineTransform object. If provided then translate, scale, rotate, and
          shear values are ignored.
      multiscale : bool
          Whether the data is multiscale or not. Multiscale data is
          represented by a list of data objects and should go from largest to
          smallest.
      z_index : int
          Depth of the layer visual relative to other visuals in the scenecanvas.
      coordinates : tuple of float
          Cursor position in data coordinates.
      corner_pixels : array
          Coordinates of the top-left and bottom-right canvas pixels in the data
          coordinates of each layer. For multiscale data the coordinates are in
          the space of the currently viewed data level, not the highest resolution
          level.
      position : tuple
          Cursor position in world coordinates.
      ndim : int
          Dimensionality of the layer.
      selected : bool
          Flag if layer is selected in the viewer or not.
      thumbnail : (N, M, 4) array
          Array of thumbnail data for the layer.
      status : str
          Displayed in status bar bottom left.
      help : str
          Displayed in status bar bottom right.
      interactive : bool
          Determine if canvas pan/zoom interactivity is enabled.
      cursor : str
          String identifying which cursor displayed over canvas.
      cursor_size : int | None
          Size of cursor if custom. None yields default size
      scale_factor : float
          Conversion factor from canvas coordinates to image coordinates, which
          depends on the current zoom level.
  
  
      Notes
      -----
      Must define the following:
          * `_extent_data`: property
          * `data` property (setter & getter)
  
      May define the following:
          * `_set_view_slice()`: called to set currently viewed slice
          * `_basename()`: base/default name of the layer
      """
  
      def __init__(
          self,
          data,
          ndim,
          *,
          name=None,
          metadata=None,
          scale=None,
          translate=None,
          rotate=None,
          shear=None,
          affine=None,
          opacity=1,
          blending='translucent',
          visible=True,
          multiscale=False,
      ):
          super().__init__()
  
          if name is None and data is not None:
              name = magic_name(data, path_prefix=ROOT_DIR)
  
          self.dask_optimized_slicing = configure_dask(data)
          self.metadata = metadata or {}
          self._opacity = opacity
          self._blending = Blending(blending)
          self._visible = visible
          self._selected = True
          self._freeze = False
          self._status = 'Ready'
          self._help = ''
          self._cursor = 'standard'
          self._cursor_size = 1
          self._interactive = True
          self._value = None
          self.scale_factor = 1
          self.multiscale = multiscale
  
          self._ndim = ndim
          self._ndisplay = 2
          self._dims_order = list(range(ndim))
  
          # Create a transform chain consisting of three transforms:
          # 1. `tile2data`: An initial transform only needed displaying tiles
          #   of an image. It maps pixels of the tile into the coordinate space
          #   of the full resolution data and can usually be represented by a
          #   scale factor and a translation. A common use case is viewing part
          #   of lower resolution level of a multiscale image, another is using a
          #   downsampled version of an image when the full image size is larger
          #   than the maximum allowed texture size of your graphics card.
          # 2. `data2world`: The main transform mapping data to a world-like
          #   coordinate.
          # 3. `world2grid`: An additional transform mapping world-coordinates
          #   into a grid for looking at layers side-by-side.
  
          # First create the `data2world` transform from the input parameters
          if affine is None:
              if scale is None:
                  scale = [1] * ndim
              if translate is None:
                  translate = [0] * ndim
              data2world_transform = Affine(
                  scale,
                  translate,
                  rotate=rotate,
                  shear=shear,
                  name='data2world',
              )
          elif isinstance(affine, np.ndarray) or isinstance(affine, list):
              data2world_transform = Affine(
                  affine_matrix=np.array(affine),
                  name='data2world',
              )
          elif isinstance(affine, Affine):
              affine.name = 'data2world'
              data2world_transform = affine
          else:
              raise TypeError(
                  'affine input not recognized. '
                  'must be either napari.utils.transforms.Affine, '
                  f'ndarray, or None. Got {type(affine)}'
              )
  
          self._transforms = TransformChain(
              [
                  Affine(np.ones(ndim), np.zeros(ndim), name='tile2data'),
                  data2world_transform,
                  Affine(np.ones(ndim), np.zeros(ndim), name='world2grid'),
              ]
          )
  
          self._position = (0,) * ndim
          self._dims_point = [0] * ndim
          self.corner_pixels = np.zeros((2, ndim), dtype=int)
          self._editable = True
  
          self._thumbnail_shape = (32, 32, 4)
          self._thumbnail = np.zeros(self._thumbnail_shape, dtype=np.uint8)
          self._update_properties = True
          self._name = ''
          self.events = EmitterGroup(
              source=self,
              auto_connect=False,
              refresh=Event,
              set_data=Event,
              blending=Event,
              opacity=Event,
              visible=Event,
              select=Event,
              deselect=Event,
              scale=Event,
              translate=Event,
              rotate=Event,
              shear=Event,
              affine=Event,
              data=Event,
              name=Event,
              thumbnail=Event,
              status=Event,
              help=Event,
              interactive=Event,
              cursor=Event,
              cursor_size=Event,
              editable=Event,
              loaded=Event,
              _ndisplay=Event,
          )
          self.name = name
  
      def __str__(self):
          """Return self.name."""
          return self.name
  
      def __repr__(self):
          cls = type(self)
          return f"<{cls.__name__} layer {repr(self.name)} at {hex(id(self))}>"
  
      @classmethod
      def _basename(cls):
          return f'{cls.__name__}'
  
      @property
      def name(self):
          """str: Unique name of the layer."""
          return self._name
  
      @property
      def loaded(self) -> bool:
          """Return True if this layer is fully loaded in memory.
  
          This base class says that layers are permanently in the loaded state.
          Derived classes that do asynchronous loading can override this.
          """
          return True
  
      @name.setter
      def name(self, name):
          if name == self.name:
              return
          if not name:
              name = self._basename()
          self._name = name
          self.events.name()
  
      @property
      def opacity(self):
          """float: Opacity value between 0.0 and 1.0."""
          return self._opacity
  
      @opacity.setter
      def opacity(self, opacity):
          if not 0.0 <= opacity <= 1.0:
              raise ValueError(
                  'opacity must be between 0.0 and 1.0; ' f'got {opacity}'
              )
  
          self._opacity = opacity
          self._update_thumbnail()
          self.events.opacity()
  
      @property
      def blending(self):
          """Blending mode: Determines how RGB and alpha values get mixed.
  
          Blending.OPAQUE
              Allows for only the top layer to be visible and corresponds to
              depth_test=True, cull_face=False, blend=False.
          Blending.TRANSLUCENT
              Allows for multiple layers to be blended with different opacity
              and corresponds to depth_test=True, cull_face=False,
              blend=True, blend_func=('src_alpha', 'one_minus_src_alpha').
          Blending.ADDITIVE
              Allows for multiple layers to be blended together with
              different colors and opacity. Useful for creating overlays. It
              corresponds to depth_test=False, cull_face=False, blend=True,
              blend_func=('src_alpha', 'one').
          """
          return str(self._blending)
  
      @blending.setter
      def blending(self, blending):
          self._blending = Blending(blending)
          self.events.blending()
  
      @property
      def visible(self):
          """bool: Whether the visual is currently being displayed."""
          return self._visible
  
      @visible.setter
      def visible(self, visibility):
          self._visible = visibility
          self.refresh()
          self.events.visible()
          if self.visible:
              self.editable = self._set_editable()
          else:
              self.editable = False
  
      @property
      def editable(self):
          """bool: Whether the current layer data is editable from the viewer."""
          return self._editable
  
      @editable.setter
      def editable(self, editable):
          if self._editable == editable:
              return
          self._editable = editable
          self._set_editable(editable=editable)
          self.events.editable()
  
      @property
      def scale(self):
          """list: Anisotropy factors to scale data into world coordinates."""
          return self._transforms['data2world'].scale
  
      @scale.setter
      def scale(self, scale):
          self._transforms['data2world'].scale = np.array(scale)
          self._update_dims()
          self.events.scale()
  
      @property
      def translate(self):
          """list: Factors to shift the layer by in units of world coordinates."""
          return self._transforms['data2world'].translate
  
      @translate.setter
      def translate(self, translate):
          self._transforms['data2world'].translate = np.array(translate)
          self._update_dims()
          self.events.translate()
  
      @property
      def rotate(self):
          """array: Rotation matrix in world coordinates."""
          return self._transforms['data2world'].rotate
  
      @rotate.setter
      def rotate(self, rotate):
          self._transforms['data2world'].rotate = rotate
          self._update_dims()
          self.events.rotate()
  
      @property
      def shear(self):
          """array: Sheer matrix in world coordinates."""
          return self._transforms['data2world'].shear
  
      @shear.setter
      def shear(self, shear):
          self._transforms['data2world'].shear = shear
          self._update_dims()
          self.events.shear()
  
      @property
      def affine(self):
          """napari.utils.transforms.Affine: Affine transform."""
          return self._transforms['data2world']
  
      @affine.setter
      def affine(self, affine):
          if isinstance(affine, np.ndarray) or isinstance(affine, list):
              self._transforms['data2world'].affine_matrix = np.array(affine)
          elif isinstance(affine, Affine):
              affine.name = 'data2world'
              self._transforms['data2world'] = affine
          else:
              raise TypeError(
                  'affine input not recognized. '
                  'must be either napari.utils.transforms.Affine '
                  f'or ndarray. Got {type(affine)}'
              )
          self._update_dims()
          self.events.affine()
  
      @property
      def translate_grid(self):
          """list: Factors to shift the layer by."""
          return self._transforms['world2grid'].translate
  
      @translate_grid.setter
      def translate_grid(self, translate_grid):
          if np.all(self.translate_grid == translate_grid):
              return
          self._transforms['world2grid'].translate = np.array(translate_grid)
          self.events.translate()
  
      @property
      def position(self):
          """tuple: Cursor position in world slice coordinates."""
          return self._position
  
      @position.setter
      def position(self, position):
          _position = position[-self.ndim :]
          if self._position == _position:
              return
          self._position = _position
          self._value = self.get_value(self.position, world=True)
  
      @property
      def _dims_displayed(self):
          """To be removed displayed dimensions."""
          # Ultimately we aim to remove all slicing information from the layer
          # itself so that layers can be sliced in different ways for multiple
          # canvas. See https://github.com/napari/napari/pull/1919#issuecomment-738585093
          # for additional discussion.
          return self._dims_order[-self._ndisplay :]
  
      @property
      def _dims_not_displayed(self):
          """To be removed not displayed dimensions."""
          # Ultimately we aim to remove all slicing information from the layer
          # itself so that layers can be sliced in different ways for multiple
          # canvas. See https://github.com/napari/napari/pull/1919#issuecomment-738585093
          # for additional discussion.
          return self._dims_order[: -self._ndisplay]
  
      @property
      def _dims_displayed_order(self):
          """To be removed order of displayed dimensions."""
          # Ultimately we aim to remove all slicing information from the layer
          # itself so that layers can be sliced in different ways for multiple
          # canvas. See https://github.com/napari/napari/pull/1919#issuecomment-738585093
          # for additional discussion.
          order = np.array(self._dims_displayed)
          order[np.argsort(order)] = list(range(len(order)))
          return tuple(order)
  
      def _update_dims(self, event=None):
          """Updates dims model, which is useful after data has been changed."""
          ndim = self._get_ndim()
  
          old_ndim = self._ndim
          if old_ndim > ndim:
              keep_axes = range(old_ndim - ndim, old_ndim)
              self._transforms = self._transforms.set_slice(keep_axes)
              self._dims_point = self._dims_point[-ndim:]
              arr = np.array(self._dims_order[-ndim:])
              arr[np.argsort(arr)] = range(len(arr))
              self._dims_order = arr.tolist()
              self._position = self._position[-ndim:]
          elif old_ndim < ndim:
              new_axes = range(ndim - old_ndim)
              self._transforms = self._transforms.expand_dims(new_axes)
              self._dims_point = [0] * (ndim - old_ndim) + self._dims_point
              self._dims_order = list(range(ndim - old_ndim)) + [
                  o + ndim - old_ndim for o in self._dims_order
              ]
              self._position = (0,) * (ndim - old_ndim) + self._position
  
          self._ndim = ndim
  
          self.refresh()
          self._value = self.get_value(self.position, world=True)
  
      @property
      @abstractmethod
      def data(self):
          # user writes own docstring
          raise NotImplementedError()
  
      @data.setter
      @abstractmethod
      def data(self, data):
          raise NotImplementedError()
  
      @property
      @abstractmethod
      def _extent_data(self) -> np.ndarray:
          """Extent of layer in data coordinates.
  
          Returns
          -------
          extent_data : array, shape (2, D)
          """
          raise NotImplementedError()
  
      @property
      def _extent_world(self) -> np.ndarray:
          """Range of layer in world coordinates.
  
          Returns
          -------
          extent_world : array, shape (2, D)
          """
          # Get full nD bounding box
          return self._get_extent_world(self._extent_data)
  
      def _get_extent_world(self, data_extent):
          """Range of layer in world coordinates base on provided data_extent
  
          Returns
          -------
          extent_world : array, shape (2, D)
          """
          D = data_extent.shape[1]
          full_data_extent = np.array(np.meshgrid(*data_extent.T)).T.reshape(
              -1, D
          )
          full_world_extent = self._transforms['data2world'](full_data_extent)
          world_extent = np.array(
              [
                  np.min(full_world_extent, axis=0),
                  np.max(full_world_extent, axis=0),
              ]
          )
          return world_extent
  
      @property
      def extent(self) -> Extent:
          """Extent of layer in data and world coordinates."""
          data = self._extent_data
          return Extent(
              data=data,
              world=self._get_extent_world(data),
              step=abs(self.scale),
          )
  
      @property
      def _slice_indices(self):
          """(D, ) array: Slice indices in data coordinates."""
          inv_transform = self._transforms['data2world'].inverse
  
          if self.ndim > self._ndisplay:
              # Subspace spanned by non displayed dimensions
              non_displayed_subspace = np.zeros(self.ndim)
              for d in self._dims_not_displayed:
                  non_displayed_subspace[d] = 1
              # Map subspace through inverse transform, ignoring translation
              mapped_nd_subspace = inv_transform(
                  non_displayed_subspace
              ) - inv_transform(np.zeros(self.ndim))
              # Look at displayed subspace
              displayed_mapped_subspace = [
                  mapped_nd_subspace[d] for d in self._dims_displayed
              ]
              # Check that displayed subspace is null
              if not np.allclose(displayed_mapped_subspace, 0):
                  warnings.warn(
                      'Non-orthogonal slicing is being requested, but'
                      ' is not fully supported. Data is displayed without'
                      ' applying an out-of-slice rotation or shear component.',
                      category=UserWarning,
                  )
  
          slice_inv_transform = inv_transform.set_slice(self._dims_not_displayed)
  
          world_pts = [self._dims_point[ax] for ax in self._dims_not_displayed]
          data_pts = slice_inv_transform(world_pts)
          if not hasattr(self, "_round_index") or self._round_index:
              # A round is taken to convert these values to slicing integers
              data_pts = np.round(data_pts).astype(int)
  
          indices = [slice(None)] * self.ndim
          for i, ax in enumerate(self._dims_not_displayed):
              indices[ax] = data_pts[i]
  
          return tuple(indices)
  
      @abstractmethod
      def _get_ndim(self):
          raise NotImplementedError()
  
      def _set_editable(self, editable=None):
          if editable is None:
              self.editable = True
  
      def _get_base_state(self):
          """Get dictionary of attributes on base layer.
  
          Returns
          -------
          state : dict
              Dictionary of attributes on base layer.
          """
          base_dict = {
              'name': self.name,
              'metadata': self.metadata,
              'scale': list(self.scale),
              'translate': list(self.translate),
              'rotate': [list(r) for r in self.rotate],
              'shear': list(self.shear),
              'opacity': self.opacity,
              'blending': self.blending,
              'visible': self.visible,
          }
          return base_dict
  
      @abstractmethod
      def _get_state(self):
          raise NotImplementedError()
  
      @property
      def _type_string(self):
          return self.__class__.__name__.lower()
  
      def as_layer_data_tuple(self):
          state = self._get_state()
          state.pop('data', None)
          return self.data, state, self._type_string
  
      @property
      def thumbnail(self):
          """array: Integer array of thumbnail for the layer"""
          return self._thumbnail
  
      @thumbnail.setter
      def thumbnail(self, thumbnail):
          if 0 in thumbnail.shape:
              thumbnail = np.zeros(self._thumbnail_shape, dtype=np.uint8)
          if thumbnail.dtype != np.uint8:
              with warnings.catch_warnings():
                  warnings.simplefilter("ignore")
                  thumbnail = convert_to_uint8(thumbnail)
  
          padding_needed = np.subtract(self._thumbnail_shape, thumbnail.shape)
          pad_amounts = [(p // 2, (p + 1) // 2) for p in padding_needed]
          thumbnail = np.pad(thumbnail, pad_amounts, mode='constant')
  
          # blend thumbnail with opaque black background
          background = np.zeros(self._thumbnail_shape, dtype=np.uint8)
          background[..., 3] = 255
  
          f_dest = thumbnail[..., 3][..., None] / 255
          f_source = 1 - f_dest
          thumbnail = thumbnail * f_dest + background * f_source
  
          self._thumbnail = thumbnail.astype(np.uint8)
          self.events.thumbnail()
  
      @property
      def ndim(self):
          """int: Number of dimensions in the data."""
          return self._ndim
  
      @property
      def selected(self):
          """bool: Whether this layer is selected or not."""
          return self._selected
  
      @selected.setter
      def selected(self, selected):
          if selected == self.selected:
              return
          self._selected = selected
  
          if selected:
              self.events.select()
          else:
              self.events.deselect()
  
      @property
      def status(self):
          """str: displayed in status bar bottom left."""
          warnings.warn(
              (
                  "The status attribute is deprecated and will be removed in version 0.4.6."
                  " Instead you should use the get_status method with the position where you"
                  " want to get the status from."
              ),
              category=FutureWarning,
              stacklevel=2,
          )
          return self._status
  
      @status.setter
      def status(self, status):
          if status == self.status:
              return
          self.events.status(status=status)
          self._status = status
  
      @property
      def help(self):
          """str: displayed in status bar bottom right."""
          return self._help
  
      @help.setter
      def help(self, help):
          if help == self.help:
              return
          self.events.help(help=help)
          self._help = help
  
      @property
      def interactive(self):
          """bool: Determine if canvas pan/zoom interactivity is enabled."""
          return self._interactive
  
      @interactive.setter
      def interactive(self, interactive):
          if interactive == self.interactive:
              return
          self.events.interactive(interactive=interactive)
          self._interactive = interactive
  
      @property
      def cursor(self):
          """str: String identifying cursor displayed over canvas."""
          return self._cursor
  
      @cursor.setter
      def cursor(self, cursor):
          if cursor == self.cursor:
              return
          self.events.cursor(cursor=cursor)
          self._cursor = cursor
  
      @property
      def cursor_size(self):
          """int | None: Size of cursor if custom. None yields default size."""
          return self._cursor_size
  
      @cursor_size.setter
      def cursor_size(self, cursor_size):
          if cursor_size == self.cursor_size:
              return
          self.events.cursor_size(cursor_size=cursor_size)
          self._cursor_size = cursor_size
  
      def set_view_slice(self):
          with self.dask_optimized_slicing():
              self._set_view_slice()
  
      @abstractmethod
      def _set_view_slice(self):
          raise NotImplementedError()
  
      def _slice_dims(self, point=None, ndisplay=2, order=None):
          """Slice data with values from a global dims model.
  
          Note this will likely be moved off the base layer soon.
  
          Parameters
          ----------
          point : list
              Values of data to slice at in world coordinates.
          ndisplay : int
              Number of dimensions to be displayed.
          order : list of int
              Order of dimensions, where last `ndisplay` will be
              rendered in canvas.
          """
          if point is None:
              ndim = self.ndim
          else:
              ndim = len(point)
  
          if order is None:
              order = list(range(ndim))
  
          # adjust the order of the global dims based on the number of
          # dimensions that a layer has - for example a global order of
          # [2, 1, 0, 3] -> [0, 1] for a layer that only has two dimensions
          # or -> [1, 0, 2] for a layer with three as that corresponds to
          # the relative order of the last two and three dimensions
          # respectively
          offset = ndim - self.ndim
          order = np.array(order)
          if offset <= 0:
              order = list(range(-offset)) + list(order - offset)
          else:
              order = list(order[order >= offset] - offset)
  
          if point is None:
              point = [0] * ndim
              nd = min(self.ndim, ndisplay)
              for i in order[-nd:]:
                  point[i] = slice(None)
          else:
              point = list(point)
  
          # If no slide data has changed, then do nothing
          if (
              np.all(order == self._dims_order)
              and ndisplay == self._ndisplay
              and np.all(point[offset:] == self._dims_point)
          ):
              return
  
          self._dims_order = order
          if self._ndisplay != ndisplay:
              self._ndisplay = ndisplay
              self.events._ndisplay()
  
          # Update the point values
          self._dims_point = point[offset:]
          self._update_dims()
          self._set_editable()
  
      @abstractmethod
      def _update_thumbnail(self):
          raise NotImplementedError()
  
      @abstractmethod
      def _get_value(self, position):
          """Value of the data at a position in data coordinates.
  
          Parameters
          ----------
          position : tuple
              Position in data coordinates.
  
          Returns
          -------
          value : tuple
              Value of the data.
          """
          raise NotImplementedError()
  
      def get_value(self, position=None, *, world=False):
          """Value of the data at a position.
  
          Parameters
          ----------
          position : tuple
              Position in either data or world coordinates.
          world : bool
              If True the position is taken to be in world coordinates
              and converted into data coordinates. False by default.
  
          Returns
          -------
          value : tuple, None
              Value of the data.
          """
          if self.visible:
              if position is None:
                  warnings.warn(
                      (
                          "The position argument of get_value will no longer be optional in 0.4.6."
                          " Instead you should provide the position where you want to get the value."
                      ),
                      category=FutureWarning,
                      stacklevel=2,
                  )
                  position = self.coordinates
              elif world:
                  position = self._world_to_data(position)
              return self._get_value(position=tuple(position))
          else:
              return None
  
      @contextmanager
      def block_update_properties(self):
          self._update_properties = False
          yield
          self._update_properties = True
  
      def _set_highlight(self, force=False):
          """Render layer highlights when appropriate.
  
          Parameters
          ----------
          force : bool
              Bool that forces a redraw to occur when `True`.
          """
          pass
  
      def refresh(self, event=None):
          """Refresh all layer data based on current view slice."""
          if self.visible:
              self.set_view_slice()
              self.events.set_data()
              self._update_thumbnail()
              self._value = self.get_value(self.position, world=True)
              self._set_highlight(force=True)
  
      @property
      def coordinates(self):
          """Cursor position in data coordinates."""
          # Note we ignore the first transform which is tile2data
          return self._world_to_data(self.position)
  
      def _world_to_data(self, position):
          """Convert from world coordinates to data coordinates.
  
          Parameters
          ----------
          position : tuple, list, 1D array
              Position in world coorindates. If longer then the
              number of dimensions of the layer, the later
              dimensions will be used.
  
          Returns
          -------
          tuple
              Position in data coordinates.
          """
          if len(position) >= self.ndim:
              coords = list(position[-self.ndim :])
          else:
              coords = [0] * (self.ndim - len(position)) + list(position)
  
          return tuple(self._transforms[1:].simplified.inverse(coords))
  
      def _update_draw(self, scale_factor, corner_pixels, shape_threshold):
          """Update canvas scale and corner values on draw.
          For layer multiscale determing if a new resolution level or tile is
          required.
          Parameters
          ----------
          scale_factor : float
              Scale factor going from canvas to world coordinates.
          corner_pixels : array
              Coordinates of the top-left and bottom-right canvas pixels in the
              world coordinates.
          shape_threshold : tuple
              Requested shape of field of view in data coordinates.
          """
          # Note we ignore the first transform which is tile2data
          data_corners = self._transforms[1:].simplified.inverse(corner_pixels)
  
          self.scale_factor = scale_factor
  
          # Round and clip data corners
          data_corners = np.array(
              [np.floor(data_corners[0]), np.ceil(data_corners[1])]
          ).astype(int)
          data_corners = np.clip(
              data_corners, self.extent.data[0], self.extent.data[1]
          )
  
          if self._ndisplay == 2 and self.multiscale:
              level, displayed_corners = compute_multiscale_level_and_corners(
                  data_corners[:, self._dims_displayed],
                  shape_threshold,
                  self.downsample_factors[:, self._dims_displayed],
              )
              corners = np.zeros((2, self.ndim))
              corners[:, self._dims_displayed] = displayed_corners
              corners = corners.astype(int)
              if self.data_level != level or not np.all(
                  self.corner_pixels == corners
              ):
                  self._data_level = level
                  self.corner_pixels = corners
                  self.refresh()
  
          else:
              self.corner_pixels = data_corners
  
      @property
      def displayed_coordinates(self):
          """list: List of currently displayed coordinates.
  
          displayed_coordinates is deprecated and will be removed in version 0.4.9.
          It should no longer be used as layers should will soon not know
          which dimensions are displayed. Instead you should use
          `[layer.coordinates[d] for d in viewer.dims.displayed]
          """
          warnings.warn(
              "displayed_coordinates is deprecated and will be removed in version 0.4.9."
              " It should no longer be used as layers should will soon not know"
              " which dimensions are displayed. Instead you should use"
              " [layer.coordinates[d] for d in viewer.dims.displayed]",
              category=DeprecationWarning,
              stacklevel=2,
          )
          coordinates = self.coordinates
          return [coordinates[i] for i in self._dims_displayed]
  
      def get_status(self, position=None, *, world=False):
          """Status message of the data at a coordinate position.
  
          Parameters
          ----------
          position : tuple
              Position in either data or world coordinates.
          world : bool
              If True the position is taken to be in world coordinates
              and converted into data coordinates. False by default.
  
          Returns
          -------
          msg : string
              String containing a message that can be used as a status update.
          """
          value = self.get_value(position, world=world)
          return generate_layer_status(self.name, position, value)
  
      def get_message(self):
          """Generate a status message based on the coordinates and value
  
          Returns
          -------
          msg : string
              String containing a message that can be used as a status update.
          """
          warnings.warn(
              (
                  "The get_message method is deprecated and will be removed in version 0.4.6."
                  " Instead you should use the get_status method with the position where you"
                  " want to get the status from."
              ),
              category=FutureWarning,
              stacklevel=2,
          )
          return generate_layer_status(self.name, self.coordinates, self._value)
  
      def save(self, path: str, plugin: Optional[str] = None) -> List[str]:
          """Save this layer to ``path`` with default (or specified) plugin.
  
          Parameters
          ----------
          path : str
              A filepath, directory, or URL to open.  Extensions may be used to
              specify output format (provided a plugin is available for the
              requested format).
          plugin : str, optional
              Name of the plugin to use for saving. If ``None`` then all plugins
              corresponding to appropriate hook specification will be looped
              through to find the first one that can save the data.
  
          Returns
          -------
          list of str
              File paths of any files that were written.
          """
          from ...plugins.io import save_layers
  
          return save_layers(path, [self], plugin=plugin)
  