code: def test_apply_roll_with_offset_data_frequency_higher_than_parameters_frequency():
      window_length = "5D"  # 120 hours
      window_length_num = 5
      # In order for min periods to be the length of the window, we multiply 24hours*5
      min_periods = window_length_num * 24
  
      datetimes = list(
          pd.date_range(start="2017-01-01", freq="1H", periods=200)
      )
      high_frequency_series = pd.Series(range(200), index=datetimes)
  
      # Check without gap
      gap = "0d"
      gap_num = 0
  
      def max_wrapper(sub_s):
          return apply_roll_with_offset_gap(
              sub_s, gap, max, min_periods=min_periods
          )
  
      rolling_max_obj = roll_series_with_gap(
          high_frequency_series,
          window_length,
          min_periods=min_periods,
          gap=gap,
      )
      rolling_max_series = rolling_max_obj.apply(max_wrapper)
  
      assert (
          rolling_max_series.isna().sum() == (min_periods - 1) + gap_num
      )
  
      # Check with small gap
      gap = "3H"
      gap_num = 3
  
      def max_wrapper(sub_s):
          return apply_roll_with_offset_gap(
              sub_s, gap, max, min_periods=min_periods
          )
  
      rolling_max_obj = roll_series_with_gap(
          high_frequency_series,
          window_length,
          min_periods=min_periods,
          gap=gap,
      )
      rolling_max_series = rolling_max_obj.apply(max_wrapper)
  
      assert (
          rolling_max_series.isna().sum() == (min_periods - 1) + gap_num
      )
  
      # Check with large gap - in terms of days, so we'll multiply by 24hours for number of nans
      gap = "2D"
      gap_num = 2
  
      def max_wrapper(sub_s):
          return apply_roll_with_offset_gap(
              sub_s, gap, max, min_periods=min_periods
          )
  
      rolling_max_obj = roll_series_with_gap(
          high_frequency_series,
          window_length,
          min_periods=min_periods,
          gap=gap,
      )
      rolling_max_series = rolling_max_obj.apply(max_wrapper)
  
      assert rolling_max_series.isna().sum() == (min_periods - 1) + (
          gap_num * 24
      )
  
imports: from unittest.mock import patch
  import numpy
  import pandas
  import pytest
  from featuretools.primitives import RollingCount, RollingMax, RollingMean, RollingMin, RollingSTD, RollingTrend
  from featuretools.primitives.standard.transform.time_series.utils import _get_rolled_series_without_gap, apply_roll_with_offset_gap, roll_series_with_gap
  from featuretools.tests.primitive_tests.utils import get_number_from_offset
label_desc: Use image node_id 14 for calling a global function with example usage: test_apply_roll_with_offset_data_frequency_higher_than_parameters_frequency() and returns: apply_roll_with_offset_gap, apply_roll_with_offset_gap, apply_roll_with_offset_gap