code: def is_fitted(self):
      # if either point posterior or posterior_samples are non-empty, claim it as fitted model (true),
      # else false.
      if bool(self._posterior_samples):
          return True
      for key in self._point_posteriors.keys():
          if bool(self._point_posteriors[key]):
              return True
      return False
  
imports: from copy import deepcopy
  import numpy
  import pandas
  import warnings
  from enum import Enum
  from typing import Dict, Any
  from ..exceptions import ForecasterException, AbstractMethodException, IllegalArgument
  from ..utils.general import is_ordered_datetime, is_even_gap_datetime
  from ..template.model_template import ModelTemplate
  from ..estimators.stan_estimator import StanEstimatorMCMC
  from ..constants.constants import TrainingMetaKeys, PredictionMetaKeys
label_desc: Use image node_id 10 for calling the Forecaster obj's underlying member method code with example usage: obj.is_fitted() and returns: False, True, True