class_docstr: Combine different tickers at different scales.
  
  Uses the ``min_interval`` and ``max_interval`` interval attributes
  of the tickers to select the appropriate ticker at different
  scales.
class_docstr_tok: ["Combine","different","tickers","at","different","scales",".","Uses","the","``","min_interval","``","and","``","max_interval","``","interval","attributes","of","the","tickers","to","select","the","appropriate","ticker","at","different","scales","."]
code: def __init__(self, *args, **kwargs) -> None:
      super().__init__(*args, **kwargs)
  
imports: from __future__ import annotations
  import logging
  from ..core.enums import LatLon
  from ..core.has_props import abstract
  from ..core.properties import Auto, Either, Enum, Float, Instance, Int, Nullable, Override, Required, Seq
  from ..core.validation import error
  from ..core.validation.errors import MISSING_MERCATOR_DIMENSION
  from ..model import Model
  from .mappers import ScanningColorMapper
label_desc: Use image node_id 1 to create a new CompositeTicker object from inherited base classes: ContinuousTicker with example: obj = CompositeTicker()