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(Annotation, self).dimension_values(dimension)
def dimension_values ( self , dimension , expanded = True , flat = True ) : 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 ( Annotation , self ) . dimension_values ( dimension )
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