code: def add_suffix(params, model):
      """Add derivative suffixes to a list of parameters.
  
      Used from motion, wm_csf, global_signal.
  
      Parameters
      ----------
      params : list of str
          List of parameters to add suffixes to.
      model : str
          Model to use. Options are "basic", "derivatives", "power2", or
          "full".
  
      Returns
      -------
      params_full : list of str
          List of parameters with suffixes added.
      """
      params_full = params.copy()
      suffix = {
          "basic": {},
          "derivatives": {"derivative1"},
          "power2": {"power2"},
          "full": {"derivative1", "power2", "derivative1_power2"},
      }
      for par in params:
          for suff in suffix[model]:
              params_full.append(f"{par}_{suff}")
      return params_full
  
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 4 for calling a global function with example usage: add_suffix(params, model) and returns: params_full