code: def test_score_null_default(X):
      """Tests default score function with null model"""
      null_model_params = {
          "strategy": "quantile",
          "constant": None,
          "quantile": 0.8,
      }
      model = ConstantBaseForecastEstimator(
          null_model_params=null_model_params
      )
      model.fit(X)
      y = np.repeat(2, X.shape[0])
      score = model.score(X, y=y)
  
      y_pred = np.repeat(1.0, X.shape[0])
      y_pred_null = np.repeat(
          8.0, X.shape[0]
      )  # quantile 0.8 null model
  
      assert score == r2_null_model_score(
          y,
          y_pred,
          y_pred_null=y_pred_null,
          loss_func=mean_squared_error,
      )
  
imports: import numpy
  import pandas
  import pytest
  from pandas.testing import assert_frame_equal
  from sklearn.metrics import mean_absolute_error
  from sklearn.metrics import mean_squared_error
  from testfixtures import LogCapture
  from greykite.common.constants import LOGGER_NAME
  from greykite.common.constants import PREDICTED_COL
  from greykite.common.constants import PREDICTED_LOWER_COL
  from greykite.common.constants import PREDICTED_UPPER_COL
  from greykite.common.constants import TIME_COL
  from greykite.common.constants import VALUE_COL
  from greykite.common.evaluation import r2_null_model_score
  from greykite.sklearn.estimator.base_forecast_estimator import BaseForecastEstimator
  from greykite.sklearn.uncertainty.uncertainty_methods import UncertaintyMethodEnum
label_desc: Use image node_id 9 for calling a global function with example usage: test_score_null_default(X) without return types