code: def get_custom_changepoints_values(
      df,
      changepoint_dates,
      time_col=cst.TIME_COL,
      continuous_time_col=cst.TimeFeaturesEnum.ct1.value,
  ):
      """Returns the values of continuous_time_col at the
          requested changepoint_dates.
  
      :param df: pd.DataFrame
          training dataset. contains continuous_time_col and time_col
      :param changepoint_dates: Iterable[Union[int, float, str, datetime]]
          Changepoint dates, interpreted by pd.to_datetime.
          Changepoints are set at the closest time on or after these dates
          in the dataset
      :param time_col: str
          The column name in `df` representing time for the time series data
          The time column can be anything that can be parsed by pandas DatetimeIndex
      :param continuous_time_col: str
          name of continuous time column (e.g. conti_year, ct1)
      :return: np.array
          values of df[continuous_time_col] at the changepoints
      """
      ts = pd.to_datetime(df[time_col])
      changepoint_dates = pd.to_datetime(changepoint_dates)
      # maps each changepoint to first date >= changepoint in the dataframe
      # if there is no such date, the changepoint is dropped (it would not be useful anyway)
      changepoint_ts = [
          ts[ts >= date].min()
          for date in changepoint_dates
          if any(ts >= date)
      ]
      indices = ts.isin(changepoint_ts)
      changepoints = df[indices][continuous_time_col].values
      if changepoints.shape[0] == 0:
          changepoints = None
      return changepoints
  
imports: import math
  from datetime import datetime
  from datetime import timedelta
  import numpy
  import pandas
  import pytz
  from holidays_ext import get_holidays
  from pandas.tseries.frequencies import to_offset
  from scipy.special import expit
  from greykite.common import constants
  from greykite.common.python_utils import split_offset_str
label_desc: Use image node_id 19 for calling a global function with example usage: get_custom_changepoints_values(df, changepoint_dates, time_col, continuous_time_col) and returns: changepoints