code: def lazy_create_xarray_filename_pairs(
      test_spec: TestSpec,
  ) -> List[Tuple[xarray.Dataset, str]]:
      n_fft = 4096
      hop_length = int(SAMPLING_RATE / 100)
      decimate_factor = 100
  
      logging.info(
          "Creating 1 month lazy Xarray with decimation and FFT"
      )
      xr1 = LoadRoutines.lazy_load_xarray_one_month(test_spec)
      xr2 = TransformRoutines.decimate_xarray_after_load(
          xr_input=xr1, decimate_factor=decimate_factor
      )
      xr3 = TransformRoutines.fix_last_chunk_error(
          xr2, n_overlap=n_fft - hop_length
      )
      xr4 = TransformRoutines.fft_xarray(
          xr_input=xr3, n_fft=n_fft, hop_length=hop_length
      )
  
      num_segments = int(MINUTES_IN_A_MONTH / NUM_MINS_PER_OUTPUT_FILE)
      start_time = 0
      xarray_filename_pairs: List[Tuple[xarray.Dataset, str]] = list()
      timestamp = int(time.time())
      for step in range(num_segments):
          segment_start = start_time + (
              NUM_MINS_PER_OUTPUT_FILE * step
          )  # in minutes
          segment_start_index = int(
              SECONDS_IN_A_MIN
              * NUM_MINS_PER_OUTPUT_FILE
              * step
              * (SAMPLING_RATE / decimate_factor)
              / hop_length
          )
          segment_end = segment_start + NUM_MINS_PER_OUTPUT_FILE
          segment_len_sec = (
              segment_end - segment_start
          ) * SECONDS_IN_A_MIN
          segment_end_index = int(
              segment_start_index
              + segment_len_sec * SAMPLING_RATE / hop_length
          )
          xr_segment = deepcopy(
              xr4.isel(
                  time=slice(segment_start_index, segment_end_index)
              )
          )
          xarray_filename_pairs.append(
              (
                  xr_segment,
                  "xarray_step_{}_{}.zarr".format(step, timestamp),
              )
          )
  
      return xarray_filename_pairs
  
imports: import argparse
  import json
  import logging
  import math
  import os
  import random
  import time
  from copy import copy, deepcopy
  from typing import List, Tuple
  import dask.array
  import numpy
  import xarray
  import ray
  from ray._private.test_utils import monitor_memory_usage
  from ray.util.dask import ray_dask_get
label_desc: Use image node_id 1 for calling a global function with example usage: lazy_create_xarray_filename_pairs(test_spec) and returns: xarray_filename_pairs