class_docstr: An abstract canvas representing the space in which to bin.
  
  Parameters
  ----------
  plot_width, plot_height : int, optional
      Width and height of the output aggregate in pixels.
  x_range, y_range : tuple, optional
      A tuple representing the bounds inclusive space ``[min, max]`` along
      the axis.
  x_axis_type, y_axis_type : str, optional
      The type of the axis. Valid options are ``'linear'`` [default], and
      ``'log'``.
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code: def validate_ranges(self, x_range, y_range):
      self.x_axis.validate(x_range)
      self.y_axis.validate(y_range)
  
imports: from __future__ import annotations
  from numbers import Number
  from math import log10
  import warnings
  import numpy
  import pandas
  import dask.dataframe
  import dask.array
  from xarray import DataArray, Dataset
  from .utils import Dispatcher, ngjit, calc_res, calc_bbox, orient_array, dshape_from_xarray_dataset
  from .utils import get_indices, dshape_from_pandas, dshape_from_dask
  from .utils import Expr
  from .resampling import resample_2d, resample_2d_distributed
  from .None import reductions
label_desc: Use image node_id 9 for calling the Canvas obj's underlying member method code with example usage: obj.validate_ranges(x_range, y_range) without return types