code: def split_feature_names(self, features, available_objects):
      # Attempts to split measurement names into object and feature pairs. Tests against a list of available objects.
      features_list = []
      # We want to test the longest keys first, so that "Cells_Edited" is matched before "Cells".
      available_objects = tuple(
          sorted(available_objects, key=len, reverse=True)
      )
      for feature_name in features:
          obj, feature_name = next(
              (
                  (s, feature_name.split(f"{s}_", 1)[-1])
                  for s in available_objects
                  if feature_name.startswith(s)
              ),
              feature_name.split("_", 1),
          )
          features_list.append((obj, feature_name))
      return features_list
  
imports: from cellprofiler_core.constants.measurement import M_LOCATION_CENTER_X, M_LOCATION_CENTER_Y, C_CHILDREN, C_PARENT, C_LOCATION, C_NUMBER, FTR_OBJECT_NUMBER, C_COUNT, FTR_CENTER_X, FTR_CENTER_Y, FTR_CENTER_Z
  from cellprofiler_core.module.image_segmentation import ObjectProcessing
  from cellprofiler_core.preferences import DEFAULT_INPUT_FOLDER_NAME, ABSOLUTE_FOLDER_NAME, DEFAULT_INPUT_SUBFOLDER_NAME, DEFAULT_OUTPUT_SUBFOLDER_NAME
  from cellprofiler_core.setting import Divider, HiddenCount, SettingsGroup, Measurement, Binary, ValidationError
  from cellprofiler_core.setting.choice import Choice
  from cellprofiler_core.setting.do_something import DoSomething, RemoveSettingButton
  from cellprofiler_core.setting.subscriber import LabelSubscriber
  from cellprofiler_core.setting.text import Directory, Filename, Float, LabelName
  from cellprofiler.modules import _help
  import logging
  import os
  import numpy
  import scipy
  import scipy.ndimage
  import scipy.sparse
  import cellprofiler.gui.help
  import cellprofiler_core.object
  from cellprofiler.utilities.rules import Rules
label_desc: Use image node_id 32 for calling the FilterObjects obj's underlying member method code with example usage: obj.split_feature_names(features, available_objects) and returns: features_list