code: def get_similar_lag(freq_in_days):
      """For a given frequency, it returns a lag which is likely to be most correlated
      to the observation at current time.
  
      For daily data, this will return 7 and for hourly data it will return 24*7.
      In general for sub-weekly frequencies, it returns the lag which corresponds to
      the same time in the last week.
      For data which is weekly or with frequencies larger than a week, it returns None.
  
      Parameters
      ----------
      freq_in_days : `float`
          The time frequency of the timeseries given in day units.
  
      Returns
      -------
      similar_lag : `int` or None
          The returned lag or None.
      """
      similar_lag = None
      # Get the number of observations per week
      obs_num_per_week = 7 / freq_in_days
  
      if obs_num_per_week > 1:
          similar_lag = math.ceil(obs_num_per_week)
  
      return similar_lag
  
file_path: greykite/greykite/algo/forecast/silverkite/forecast_silverkite_helper.py
imports: import math
  import warnings
  from typing import List
  from typing import Optional
  import pandas
  from greykite.common.constants import TimeFeaturesEnum
  from greykite.common.enums import SimpleTimeFrequencyEnum
  from greykite.common.features.timeseries_features import build_time_features_df
  from greykite.common.features.timeseries_features import get_default_origin_for_time_vars
label_desc: Use image node_id 1 for calling a global function with example usage: get_similar_lag(freq_in_days) and returns: similar_lag