code: def test_score_function(daily_data):
      """Checks score function accuracy without null model"""
      model = ProphetEstimator()
      train_df = daily_data["train_df"]
  
      value_col = "y"
      time_col = "ts"
  
      model.fit(train_df, time_col=time_col, value_col=value_col)
      score = model.score(
          daily_data["test_df"], daily_data["test_df"][value_col]
      )
      assert score == pytest.approx(5.77, rel=1e-1)
  
imports: import sys
  import numpy
  import pandas
  import pytest
  from sklearn.exceptions import NotFittedError
  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 EvaluationMetricEnum
  from greykite.common.evaluation import calc_pred_err
  from greykite.common.python_utils import assert_equal
  from greykite.common.testing_utils import generate_df_for_tests
  from greykite.common.testing_utils import generate_df_with_reg_for_tests
  from greykite.sklearn.estimator.prophet_estimator import ProphetEstimator
label_desc: Use image node_id 13 for calling a global function with example usage: test_score_function(daily_data) without return types