code: def test_create_train_X_y_ValueError_when_series_length_is_lower_than_windows_size():
      """
      Test ValueError is raised when length of series is less than self.window_size + 1.
      """
      series = pd.DataFrame(
          {"1": pd.Series(np.arange(2)), "2": pd.Series(np.arange(2))}
      )
  
      forecaster = ForecasterAutoregMultiSeriesCustom(
          regressor=LinearRegression(),
          fun_predictors=create_predictors_nan,
          name_predictors=["lag_1", "lag_2", "lag_3"],
          window_size=3,
      )
  
      err_msg = re.escape(
          (
              f"`series` must have as many values as the windows_size needed by "
              f"{forecaster.fun_predictors.__name__}. For this Forecaster the "
              f"minimum length is {forecaster.window_size + 1}"
          )
      )
      with pytest.raises(ValueError, match=err_msg):
          forecaster.create_train_X_y(series=series)
  
imports: import re
  import pytest
  import numpy
  import pandas
  from skforecast.ForecasterAutoregMultiSeriesCustom import ForecasterAutoregMultiSeriesCustom
  from skforecast.exceptions import MissingValuesExogWarning
  from sklearn.linear_model import LinearRegression
  from sklearn.compose import ColumnTransformer
  from sklearn.preprocessing import StandardScaler
  from sklearn.preprocessing import OneHotEncoder
label_desc: Use image node_id 7 for calling a global function with example usage: test_create_train_X_y_ValueError_when_series_length_is_lower_than_windows_size() without return types