code: def test_forecast_via_prophet_daily_reg(
      daily_data_reg, params_add_seasonality, params_multiple_regressors
  ):
      """Tests fit and predict with regressors and custom seasonality."""
      model = ProphetEstimator(
          score_func=mean_squared_error,
          null_model_params=None,
          **params_multiple_regressors,
          **params_add_seasonality,
      )
      train_df = daily_data_reg["train_df"]
      test_df = daily_data_reg["test_df"]
  
      model.fit(train_df, time_col=TIME_COL, value_col=VALUE_COL)
      pred = model.predict(test_df)
      assert list(pred.columns) == [
          TIME_COL,
          PREDICTED_COL,
          PREDICTED_LOWER_COL,
          PREDICTED_UPPER_COL,
      ]
  
      y_true = test_df[VALUE_COL]
      y_pred = pred[PREDICTED_COL]
  
      err = calc_pred_err(y_true, y_pred)
      enum = EvaluationMetricEnum.Correlation
      assert err[enum.get_metric_name()] > 0.50
      enum = EvaluationMetricEnum.MeanAbsoluteError
      assert err[enum.get_metric_name()] < 2.5
      enum = EvaluationMetricEnum.RootMeanSquaredError
      assert err[enum.get_metric_name()] < 3.0
      enum = EvaluationMetricEnum.MedianAbsoluteError
      assert err[enum.get_metric_name()] < 3.0
  
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 16 for calling a global function with example usage: test_forecast_via_prophet_daily_reg(daily_data_reg, params_add_seasonality, params_multiple_regressors) without return types