code: def test_holidays_with_neighbor_and_remove_intercept():
      """Tests holiday with additional neighbors and removing intercept."""
      dl = DataLoader()
      df = dl.load_peyton_manning()
      df[TIME_COL] = pd.to_datetime(df[TIME_COL])
      silverkite = SimpleSilverkiteForecast()
      trained_model = silverkite.forecast_simple(
          df=df,
          time_col=TIME_COL,
          value_col=VALUE_COL,
          forecast_horizon=7,
          holidays_to_model_separately=[],
          holiday_lookup_countries=["US"],
          holiday_pre_num_days=0,
          holiday_post_num_days=0,
          daily_event_shifted_effect=["7D"],
          growth_term=None,
          changepoints_dict=None,
          yearly_seasonality=False,
          quarterly_seasonality=False,
          monthly_seasonality=False,
          weekly_seasonality=False,
          daily_seasonality=False,
          feature_sets_enabled=False,
          fit_algorithm="ridge",
          remove_intercept=True,
          extra_pred_cols=["0"],
      )
      assert (
          trained_model["drop_intercept_col"]
          == "C(Q('events_Other'), levels=['', 'event'])[]"
      )
      assert trained_model["daily_event_shifted_effect"] == ["7D"]
      assert (
          "C(Q('events_Other'), levels=['', 'event'])[]"
          not in trained_model["x_mat"].columns
      )
      assert (
          "C(Q('events_Other_7D_after'), levels=['', 'event_7D_after'])[T.event_7D_after]"
          in trained_model["x_mat"].columns
      )
      silverkite.predict(df, trained_model=trained_model)["fut_df"]
  
imports: import datetime
  import math
  import sys
  import warnings
  from datetime import timedelta
  import pandas
  import pytest
  from testfixtures import LogCapture
  import greykite.common.constants
  from greykite.algo.changepoint.adalasso.changepoint_detector import ChangepointDetector
  from greykite.algo.forecast.silverkite.constants.silverkite_column import SilverkiteColumn
  from greykite.algo.forecast.silverkite.constants.silverkite_holiday import SilverkiteHoliday
  from greykite.algo.forecast.silverkite.constants.silverkite_seasonality import SilverkiteSeasonality
  from greykite.algo.forecast.silverkite.constants.silverkite_seasonality import SilverkiteSeasonalityEnum
  from greykite.algo.forecast.silverkite.forecast_simple_silverkite import SimpleSilverkiteForecast
  from greykite.algo.forecast.silverkite.forecast_simple_silverkite_helper import generate_holiday_events
  from greykite.common.constants import CHANGEPOINT_COL_PREFIX
  from greykite.common.constants import EVENT_DF_DATE_COL
  from greykite.common.constants import EVENT_DF_LABEL_COL
  from greykite.common.constants import LOGGER_NAME
  from greykite.common.constants import TIME_COL
  from greykite.common.constants import VALUE_COL
  from greykite.common.data_loader import DataLoader
  from greykite.common.enums import SimpleTimeFrequencyEnum
  from greykite.common.enums import TimeEnum
  from greykite.common.features.timeseries_features import get_available_holidays_across_countries
  from greykite.common.features.timeseries_features import get_holidays
  from greykite.common.python_utils import assert_equal
  from greykite.common.python_utils import update_dictionary
  from greykite.common.testing_utils import generate_df_for_tests
  from greykite.common.testing_utils import generate_df_with_reg_for_tests
label_desc: Use image node_id 23 for calling a global function with example usage: test_holidays_with_neighbor_and_remove_intercept() without return types