code: def get_confounds_file(image_file, flag_full_aroma):
      """Return the confounds file associated with a functional image.
  
      Parameters
      ----------
      image_file : str
          Path to the functional image file.
  
      flag_full_aroma : bool
          True if the input is a full ICA-AROMA output, False otherwise.
  
      Returns
      -------
      confounds_raw_path : str
          Path to the associated confounds file.
      """
      _check_images(image_file, flag_full_aroma)
      confounds_raw_path = _get_file_name(image_file)
      return confounds_raw_path
  
imports: import itertools
  import json
  import os
  import re
  import numpy
  import pandas
  from sklearn.preprocessing import scale
  from nilearn._utils.fmriprep_confounds import flag_single_gifti, is_camel_case
  from nilearn.interfaces.bids import parse_bids_filename
  from .load_confounds_scrub import extract_outlier_regressors
label_desc: Use image node_id 7 for calling a global function with example usage: get_confounds_file(image_file, flag_full_aroma) and returns: confounds_raw_path