code: def test_dlt_is_fitted(
      iclaims_training_data, estimator, keep_samples, point_method
  ):
      df = iclaims_training_data
      df["claims"] = np.log(df["claims"])
      regressor_col = ["trend.unemploy"]
  
      dlt = DLT(
          response_col="claims",
          date_col="week",
          regressor_col=regressor_col,
          seasonality=52,
          seed=8888,
          num_warmup=50,
          num_sample=50,
          verbose=False,
          estimator=estimator,
      )
  
      dlt.fit(df, keep_samples=keep_samples, point_method=point_method)
      is_fitted = dlt.is_fitted()
  
      # still True when keep_samples is False
      assert is_fitted
  
imports: from copy import copy
  import pytest
  import numpy
  from orbit.models import DLT
  from orbit.constants.constants import PredictionKeys
  from orbit.exceptions import ModelException, PredictionException
label_desc: Use image node_id 19 for calling a global function with example usage: test_dlt_is_fitted(iclaims_training_data, estimator, keep_samples, point_method) without return types