code: def get_seasonality_changepoint_df_cols(
      df,
      time_col,
      seasonality_changepoints,
      seasonality_components_df,
      include_original_block=True,
      include_components=None,
  ):
      """Gets the seasonality change point feature df column names.
  
      Parameters
      ----------
      df : `pandas.DataFrame`
          The dataframe used to build seasonality feature df.
      time_col : `str`
          The name of the time column in ``df``.
      seasonality_changepoints : `dict`
          The seasonality change point dictionary. The keys are seasonality components, and the values
          are the corresponding change points given in lists.
          For example
  
              "weekly": [Timestamp('2020-01-01 00:00:00'), Timestamp('2021-04-05 00:00:00')]
              "yearly": [Timestamp('2020-08-06 00:00:00')]
  
      seasonality_components_df : `pandas.DataFrame`
          The seasonality components dataframe that is compatible with
          `~greykite.algo.changepoint.adalasso.changepoint_detector.ChangepointDetector.find_seasonality_changepoints`
          The values in "seas_names" must equal to the keys in ``seasonality_changepoints``.
      include_original_block : `bool`, default True
          Whether to include the original untruncated block of sin or cos columns for each component. If set to
          False, the original seasonality block for each component will be dropped.
      include_components : `list` [`str`] or None, default None
          The components to be included from the result. If None, all components will be included.
  
      Returns
      -------
      cols : `list`
          List of column names for seasonality change points df.
      """
      # only needs two rows to get the column names, reduces running time.
      df = df.iloc[:2, :]
      seasonality_cols = []
      for component, dates in seasonality_changepoints.items():
          if (
              include_components is None
              or component in include_components
          ):
              regular_seasonality_df = (
                  build_seasonality_feature_df_with_changes(
                      df=df,
                      time_col=time_col,
                      fs_components_df=seasonality_components_df.loc[
                          seasonality_components_df["seas_names"]
                          == component,
                          :,
                      ],
                  )
              )
              temp_cols = (
                  list(regular_seasonality_df.columns)
                  if include_original_block
                  else []
              )
              for date in dates:
                  temp_cols += [
                      f"{col}{date.strftime('_%Y_%m_%d_%H')}"
                      for col in list(regular_seasonality_df.columns)
                  ]
              seasonality_cols += temp_cols
      return seasonality_cols
  
imports: import warnings
  from datetime import timedelta
  import numpy
  import pandas
  import plotly.graph_objects
  from pandas.plotting import register_matplotlib_converters
  from pandas.tseries.frequencies import to_offset
  from sklearn.linear_model import Lasso
  from sklearn.linear_model import LassoCV
  from sklearn.linear_model import LinearRegression
  from sklearn.linear_model import RidgeCV
  from greykite.common.constants import CHANGEPOINT_COL_PREFIX
  from greykite.common.constants import TimeFeaturesEnum
  from greykite.common.features.timeseries_features import add_time_features_df
  from greykite.common.features.timeseries_features import build_time_features_df
  from greykite.common.features.timeseries_features import fourier_series_multi_fcn
  from greykite.common.features.timeseries_features import get_changepoint_dates_from_changepoints_dict
  from greykite.common.features.timeseries_features import get_changepoint_features
  from greykite.common.features.timeseries_features import get_changepoint_features_and_values_from_config
  from greykite.common.features.timeseries_features import get_default_origin_for_time_vars
  from greykite.common.python_utils import get_pattern_cols
  from greykite.common.python_utils import unique_elements_in_list
label_desc: Use image node_id 16 for calling a global function with example usage: get_seasonality_changepoint_df_cols(df, time_col, seasonality_changepoints, seasonality_components_df, include_original_block, include_components) and returns: seasonality_cols