class_docstr: Base adapter class for StatsForecast models.
class_docstr_tok: ["Base","adapter","class","for","StatsForecast","models","."]
docstr: Return parameter dict with only parameters accepted by statsforecast API.
  
  Checks if the parameters passed to the statsforecast forecaster
  are valid in the __init__ method of the aforementioned forecaster.
  If the parameter is not there it will just not be passed. Furthermore
  if the parameter is modified by the sktime user,
  he will be notified that the parameter does not exist
  anymore in the version installed of statsforecast by the user.
docstr_tok: ["Return","parameter","dict","with","only","parameters","accepted","by","statsforecast","API",".","Checks","if","the","parameters","passed","to","the","statsforecast","forecaster","are","valid","in","the","__init__","method","of","the","aforementioned","forecaster",".","If","the","parameter","is","not","there","it","will","just","not","be","passed",".","Furthermore","if","the","parameter","is","modified","by","the","sktime","user",",","he","will","be","notified","that","the","parameter","does","not","exist","anymore","in","the","version","installed","of","statsforecast","by","the","user","."]
code: def _get_validated_statsforecast_params(self) -> dict:
      """Return parameter dict with only parameters accepted by statsforecast API.
  
      Checks if the parameters passed to the statsforecast forecaster
      are valid in the __init__ method of the aforementioned forecaster.
      If the parameter is not there it will just not be passed. Furthermore
      if the parameter is modified by the sktime user,
      he will be notified that the parameter does not exist
      anymore in the version installed of statsforecast by the user.
  
      """
      params_sktime_to_statsforecast: dict = (
          self._get_statsforecast_params()
      )
      params_sktime_to_statsforecast_default: dict = (
          self._get_statsforecast_default_params()
      )
      statsforecast_init_params = set(
          self._get_init_statsforecast_params()
      )
  
      # Filter sktime_params to only include keys in statsforecast_params
      filtered_sktime_params = {
          key: value
          for key, value in params_sktime_to_statsforecast.items()
          if key in statsforecast_init_params
      }
  
      non_default_params = [
          p
          for p in params_sktime_to_statsforecast
          if params_sktime_to_statsforecast[p]
          != params_sktime_to_statsforecast_default[p]
      ]
      # Find parameters not in statsforecast_params or sktime_default_params
      param_diff = set(non_default_params) - statsforecast_init_params
  
      if param_diff:
          params_str = ", ".join([f'"{param}"' for param in param_diff])
          warning_message = (
              f"Keyword arguments {params_str} "
              f"will be omitted as they are not found in the __init__ method from "
              f"{self._get_statsforecast_class()}. Check your statsforecast version "
              f"to find out the right API parameters."
          )
          warn(warning_message)
  
      return filtered_sktime_params
  
imports: from inspect import signature
  from typing import Dict
  from warnings import warn
  import pandas
  from sktime.forecasting.base import BaseForecaster
label_desc: Use image node_id 6 for calling the _GeneralisedStatsForecastAdapter obj's underlying member method code with example usage: obj._get_validated_statsforecast_params() and returns: filtered_sktime_params