code: def get_extents(
      self, element, ranges, range_type="combined", **kwargs
  ):
      opts = self.lookup_options(element, "plot").options
      if len(element.dimensions()) > 1 and "spike_length" not in opts:
          ydim = element.get_dimension(1)
          s0, s1 = ranges[ydim.name]["soft"]
          s0 = min(s0, 0) if util.isfinite(s0) else 0
          s1 = max(s1, 0) if util.isfinite(s1) else 0
          ranges[ydim.name]["soft"] = (s0, s1)
      proxy_dim = None
      if "spike_length" in opts or len(element.dimensions()) == 1:
          proxy_dim = Dimension("proxy_dim")
          length = opts.get("spike_length", self.spike_length)
          if self.batched:
              bs, ts = [], []
              # Iterate over current NdOverlay and compute extents
              # from position and length plot options
              frame = self.current_frame or self.hmap.last
              for el in frame.values():
                  opts = self.lookup_options(el, "plot").options
                  pos = opts.get("position", self.position)
                  bs.append(pos)
                  ts.append(pos + length)
              proxy_range = (np.nanmin(bs), np.nanmax(ts))
          else:
              proxy_range = (self.position, self.position + length)
          ranges["proxy_dim"] = {
              "data": proxy_range,
              "hard": (np.nan, np.nan),
              "soft": proxy_range,
              "combined": proxy_range,
          }
      return super().get_extents(
          element, ranges, range_type, ydim=proxy_dim
      )
  
imports: import numpy
  from ..core import Dataset, Dimension, util
  from ..element import Bars, Graph
  from ..element.util import categorical_aggregate2d
  from .util import get_axis_padding
label_desc: Use image node_id 2 for calling the SpikesMixin obj's underlying member method code with example usage: obj.get_extents(element, ranges, range_type) and returns: super