code: def fetch_atlas_yeo_2011(
      data_dir=None, url=None, resume=True, verbose=1
  ):
      """Download and return file names for the Yeo 2011 :term:`parcellation`.
  
      This function retrieves the so-called yeo
      :term:`deterministic atlases<Deterministic atlas>`. The provided images
      are in MNI152 space and have shapes equal to ``(256, 256, 256, 1)``.
      They contain consecutive integers values from 0 (background) to either
      7 or 17 depending on the atlas version considered.
  
      For more information on this dataset's structure,
      see :footcite:t:`CorticalParcellation_Yeo2011`,
      and :footcite:t:`Yeo2011`.
  
      Parameters
      ----------
      %(data_dir)s
      %(url)s
      %(resume)s
      %(verbose)s
  
      Returns
      -------
      data : :class:`sklearn.utils.Bunch`
          Dictionary-like object, keys are:
  
              - 'thin_7': :obj:`str`, path to nifti file containing the
                7 regions :term:`parcellation` fitted to thin template cortex
                segmentations. The image contains integer values which can be
                interpreted as the indices in ``colors_7``.
              - 'thick_7': :obj:`str`, path to nifti file containing the
                7 region :term:`parcellation` fitted to thick template cortex
                segmentations. The image contains integer values which can be
                interpreted as the indices in ``colors_7``.
              - 'thin_17': :obj:`str`, path to nifti file containing the
                17 region :term:`parcellation` fitted to thin template cortex
                segmentations. The image contains integer values which can be
                interpreted as the indices in ``colors_17``.
              - 'thick_17': :obj:`str`, path to nifti file containing the
                17 region :term:`parcellation` fitted to thick template cortex
                segmentations. The image contains integer values which can be
                interpreted as the indices in ``colors_17``.
              - 'colors_7': :obj:`str`, path to colormaps text file for
                7 region :term:`parcellation`.
                This file maps :term:`voxel` integer
                values from ``data.thin_7`` and ``data.tick_7`` to network
                names.
              - 'colors_17': :obj:`str`, path to colormaps text file for
                17 region :term:`parcellation`.
                This file maps :term:`voxel` integer
                values from ``data.thin_17`` and ``data.tick_17`` to network
                names.
              - 'anat': :obj:`str`, path to nifti file containing the anatomy
                image.
              - 'description': :obj:`str`, description of the atlas.
  
      References
      ----------
      .. footbibliography::
  
      Notes
      -----
      Licence: unknown.
  
      """
      if url is None:
          url = (
              "ftp://surfer.nmr.mgh.harvard.edu/pub/data/"
              "Yeo_JNeurophysiol11_MNI152.zip"
          )
      opts = {"uncompress": True}
  
      dataset_name = "yeo_2011"
      keys = (
          "thin_7",
          "thick_7",
          "thin_17",
          "thick_17",
          "colors_7",
          "colors_17",
          "anat",
      )
      basenames = (
          "Yeo2011_7Networks_MNI152_FreeSurferConformed1mm.nii.gz",
          "Yeo2011_7Networks_MNI152_FreeSurferConformed1mm_LiberalMask.nii.gz",
          "Yeo2011_17Networks_MNI152_FreeSurferConformed1mm.nii.gz",
          "Yeo2011_17Networks_MNI152_FreeSurferConformed1mm_LiberalMask.nii.gz",
          "Yeo2011_7Networks_ColorLUT.txt",
          "Yeo2011_17Networks_ColorLUT.txt",
          "FSL_MNI152_FreeSurferConformed_1mm.nii.gz",
      )
  
      filenames = [
          (os.path.join("Yeo_JNeurophysiol11_MNI152", f), url, opts)
          for f in basenames
      ]
  
      data_dir = get_dataset_dir(
          dataset_name, data_dir=data_dir, verbose=verbose
      )
      sub_files = fetch_files(
          data_dir, filenames, resume=resume, verbose=verbose
      )
  
      fdescr = get_dataset_descr(dataset_name)
  
      params = dict(
          [("description", fdescr)] + list(zip(keys, sub_files))
      )
      return Bunch(**params)
  
imports: import json
  import os
  import re
  import shutil
  import warnings
  import xml.etree.ElementTree
  from pathlib import Path
  from tempfile import mkdtemp
  import nibabel
  import numpy
  import pandas
  from sklearn.utils import Bunch
  from .._utils import check_niimg, fill_doc
  from ..image import get_data, new_img_like, reorder_img
  from ._utils import fetch_files, get_dataset_descr, get_dataset_dir
label_desc: Use image node_id 13 for calling a global function with example usage: fetch_atlas_yeo_2011(data_dir, url, resume, verbose) and returns: Bunch