code: def compare_results(subj, run, other_root, mask_fname):
      """Find and compare calculated results images from a previous run
  
      This script checks that another directory containing results of this same
      analysis are similar in the sense of numpy ``allclose`` within a brain mask.
  
      Parameters
      ----------
      subj : int
          subject number (0..4, 6..15)
      run : int
          run number (1..4)
      other_root : str
          path to previous run estimation
      mask_fname:
          path to a mask image defining area in which to compare differences
      """
      # Get information for this subject and run
      path_dict = path_info_run(subj, run)
      # Get mask
      msk = load_image(mask_fname).get_fdata().copy().astype(bool)
      # Get results directories for this run
      rootdir = path_dict["rootdir"]
      res_dir = pjoin(rootdir, "results_%02d" % run)
      if not isdir(res_dir):
          return
      for dirpath, dirnames, filenames in os.walk(res_dir):
          for fname in filenames:
              froot, ext = splitext(fname)
              if froot in ("effect", "sd", "F", "t"):
                  this_fname = pjoin(dirpath, fname)
                  other_fname = this_fname.replace(DATADIR, other_root)
                  if not exists(other_fname):
                      print(
                          this_fname,
                          "present but ",
                          other_fname,
                          "missing",
                      )
                      continue
                  this_arr = load_image(this_fname).get_fdata()
                  other_arr = load_image(other_fname).get_fdata()
                  ok = np.allclose(this_arr[msk], other_arr[msk])
                  if not ok and froot in (
                      "effect",
                      "sd",
                      "t",
                  ):  # Maybe a sign flip
                      ok = np.allclose(this_arr[msk], -other_arr[msk])
                  if not ok:
                      print(
                          "Difference between", this_fname, other_fname
                      )
  
imports: import csv
  import os
  from io import StringIO
  from os import listdir, makedirs
  from os.path import abspath, exists, isdir, splitext
  from os.path import join
  import numpy
  import pandas
  from nipy.io.api import load_image
label_desc: Use image node_id 14 for calling a global function with example usage: compare_results(subj, run, other_root, mask_fname) without return types