code: def params():
      holidays = pd.DataFrame(
          {
              "ds": pd.to_datetime(
                  ["2018-12-25", "2019-12-25", "2020-12-25"]
              ),
              "holiday": ["christmas", "christmas", "christmas"],
              "lower_window": [-2, -2, -2],
              "upper_window": [2, 2, 2],
          }
      )
      return {
          "growth": "linear",
          "changepoints": ["2018-01-02", "2018-01-04"],
          "n_changepoints": None,
          "changepoint_range": 0.7,
          "yearly_seasonality": False,
          "weekly_seasonality": True,
          "daily_seasonality": False,
          "holidays": holidays,
          "seasonality_mode": "multiplicative",
          "seasonality_prior_scale": 5.0,
          "holidays_prior_scale": 5.0,
          "changepoint_prior_scale": 0.10,
          "mcmc_samples": 0,
          "uncertainty_samples": 1000,
      }
  
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 1 for calling a global function with example usage: params() and returns: dict