class_docstr: An Annotation is a special type of element that is designed to be
  overlaid on top of any arbitrary 2D element. Annotations have
  neither key nor value dimensions allowing them to be overlaid over
  any type of data.
  
  Note that one or more Annotations *can* be displayed without being
  overlaid on top of any other data. In such instances (by default)
  they will be displayed using the unit axis limits (0.0-1.0 in both
  directions) unless an explicit 'extents' parameter is
  supplied. The extents of the bottom Annotation in the Overlay is
  used when multiple Annotations are displayed together.
class_docstr_tok: ["An","Annotation","is","a","special","type","of","element","that","is","designed","to","be","overlaid","on","top","of","any","arbitrary","2D","element",".","Annotations","have","neither","key","nor","value","dimensions","allowing","them","to","be","overlaid","over","any","type","of","data",".","Note","that","one","or","more","Annotations","*","can","*","be","displayed","without","being","overlaid","on","top","of","any","other","data",".","In","such","instances","(","by","default",")","they","will","be","displayed","using","the","unit","axis","limits","(","0.0-1.0","in","both","directions",")","unless","an","explicit","'extents","'","parameter","is","supplied",".","The","extents","of","the","bottom","Annotation","in","the","Overlay","is","used","when","multiple","Annotations","are","displayed","together","."]
docstr: Return the values along the requested dimension.
  
  Args:
      dimension: The dimension to return values for
      expanded (bool, optional): Whether to expand values
      flat (bool, optional): Whether to flatten array
  
  Returns:
      NumPy array of values along the requested dimension
code: def dimension_values(self, dimension, expanded=True, flat=True):
      """Return the values along the requested dimension.
  
      Args:
          dimension: The dimension to return values for
          expanded (bool, optional): Whether to expand values
          flat (bool, optional): Whether to flatten array
  
      Returns:
          NumPy array of values along the requested dimension
      """
      index = self.get_dimension_index(dimension)
      if index == 0:
          return np.array(
              [
                  self.data
                  if np.isscalar(self.data)
                  else self.data[index]
              ]
          )
      elif index == 1:
          return (
              [] if np.isscalar(self.data) else np.array([self.data[1]])
          )
      else:
          return super().dimension_values(dimension)
  
imports: from numbers import Number
  import numpy
  import param
  from ..core import Dimension, Element, Element2D
  from ..core.data import Dataset
  from ..core.util import datetime_types
label_desc: Use image node_id 4 for calling the Annotation obj's underlying member method code with example usage: obj.dimension_values(dimension, expanded, flat) and returns: np, unknown, super