code: def fetch_atlas_basc_multiscale_2015(
      data_dir=None,
      url=None,
      resume=True,
      verbose=1,
      resolution=None,
      version="sym",
  ):
      """Download and load multiscale functional brain parcellations.
  
      This :term:`Deterministic atlas` includes group brain parcellations
      generated from resting-state
      :term:`functional magnetic resonance images<fMRI>` from about 200 young
      healthy subjects.
  
      Multiple resolutions (number of networks) are available, among
      7, 12, 20, 36, 64, 122, 197, 325, 444. The brain parcellations
      have been generated using a method called bootstrap analysis of
      stable clusters called as BASC :footcite:t:`Bellec2010`,
      and the resolutions have been selected using a data-driven method
      called MSTEPS :footcite:t:`Bellec2013`.
  
      Note that two versions of the template are available, 'sym' or 'asym'.
      The 'asym' type contains brain images that have been registered in the
      asymmetric version of the :term:`MNI` brain template (reflecting that
      the brain is asymmetric), while the 'sym' type contains images registered
      in the symmetric version of the :term:`MNI` template.
      The symmetric template has been forced to be symmetric anatomically, and
      is therefore ideally suited to study homotopic functional connections in
      :term:`fMRI`: finding homotopic regions simply consists of flipping the
      x-axis of the template.
  
      .. versionadded:: 0.2.3
  
      Parameters
      ----------
      %(data_dir)s
      %(url)s
      %(resume)s
      %(verbose)s
      resolution: :ob:`int`, optional
          Number of networks in the dictionary. Valid resolutions
          available are {7, 12, 20, 36, 64, 122, 197, 325, 444}
      version : {'sym', 'asym'}, default='sym'
          Available versions are 'sym' or 'asym'. By default all scales of
          brain parcellations of version 'sym' will be returned.
  
      Returns
      -------
      data : :class:`sklearn.utils.Bunch`
          Dictionary-like object, Keys are:
  
          - "scale007", "scale012", "scale020", "scale036", "scale064",
            "scale122", "scale197", "scale325", "scale444": :obj:`str`, path
            to Nifti file of various scales of brain parcellations.
            Images have shape ``(53, 64, 52)`` and contain consecutive integer
            values from 0 to the selected number of networks (scale).
          - "description": :obj:`str`, details about the data release.
  
      Warns
      -----
      DeprecationWarning
          If a resolution input is provided, the current behavior
          (returning multiple maps) is deprecated.
          Starting in version 0.13, one map will be returned in a 'maps' dict key
          depending on the resolution and version value.
  
      References
      ----------
      .. footbibliography::
  
      Notes
      -----
      For more information on this dataset's structure, see
      https://figshare.com/articles/basc/1285615
  
      """
      versions = ["sym", "asym"]
      if version not in versions:
          raise ValueError(
              f"The version of Brain parcellations requested '{version}' "
              "does not exist. "
              f"Please choose one among them {versions}."
          )
  
      file_number = "1861819" if version == "sym" else "1861820"
      url = f"https://ndownloader.figshare.com/files/{file_number}"
  
      opts = {"uncompress": True}
  
      keys = [
          "scale007",
          "scale012",
          "scale020",
          "scale036",
          "scale064",
          "scale122",
          "scale197",
          "scale325",
          "scale444",
      ]
  
      dataset_name = "basc_multiscale_2015"
      data_dir = get_dataset_dir(
          dataset_name, data_dir=data_dir, verbose=verbose
      )
  
      folder_name = f"template_cambridge_basc_multiscale_nii_{version}"
      fdescr = get_dataset_descr(dataset_name)
  
      if resolution:
          basename = (
              "template_cambridge_basc_multiscale_"
              + version
              + f"_scale{resolution:03}"
              + ".nii.gz"
          )
  
          filename = [(os.path.join(folder_name, basename), url, opts)]
  
          data = fetch_files(
              data_dir, filename, resume=resume, verbose=verbose
          )
          params = Bunch(maps=data[0], description=fdescr)
      else:
          basenames = [
              "template_cambridge_basc_multiscale_"
              + version
              + "_"
              + key
              + ".nii.gz"
              for key in keys
          ]
          filenames = [
              (os.path.join(folder_name, basename), url, opts)
              for basename in basenames
          ]
          data = fetch_files(
              data_dir, filenames, resume=resume, verbose=verbose
          )
  
          descr = get_dataset_descr(dataset_name)
  
          params = dict(zip(keys, data))
          params["description"] = descr
          warnings.warn(
              category=DeprecationWarning,
              message="In release 0.13, this fetcher will return a dictionary "
              "with one map accessed through a 'maps' key. Please use the new "
              "parameters resolution and version.",
          )
      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 15 for calling a global function with example usage: fetch_atlas_basc_multiscale_2015(data_dir, url, resume, verbose, resolution, version) and returns: Bunch