code: def test_predict_NotFittedError_when_fitted_is_False():
      """
      Test NotFittedError is raised when fitted is False.
      """
      forecaster = ForecasterAutoregMultiVariate(
          LinearRegression(), level="l1", lags=3, steps=3
      )
  
      err_msg = re.escape(
          (
              "This Forecaster instance is not fitted yet. Call `fit` with "
              "appropriate arguments before using predict."
          )
      )
      with pytest.raises(NotFittedError, match=err_msg):
          forecaster.predict_bootstrapping(steps=5)
  
imports: import re
  import pytest
  import numpy
  import pandas
  from sklearn.exceptions import NotFittedError
  from skforecast.ForecasterAutoregMultiVariate import ForecasterAutoregMultiVariate
  from sklearn.linear_model import LinearRegression
  from sklearn.compose import ColumnTransformer
  from sklearn.preprocessing import StandardScaler
  from sklearn.preprocessing import OneHotEncoder
  from .fixtures_ForecasterAutoregMultiVariate import series
  from .fixtures_ForecasterAutoregMultiVariate import exog
  from .fixtures_ForecasterAutoregMultiVariate import exog_predict
label_desc: Use image node_id 1 for calling a global function with example usage: test_predict_NotFittedError_when_fitted_is_False() without return types