code: def test_full_brain_info():
      surfaces = datasets.fetch_surf_fsaverage()
      img = _get_img()
      info = html_surface._full_brain_info(img, surfaces)
      check_colors(info["colorscale"])
      assert {
          "pial_left",
          "pial_right",
          "inflated_left",
          "inflated_right",
          "vertexcolor_left",
          "vertexcolor_right",
      }.issubset(info.keys())
      assert info["cmin"] == -info["cmax"]
      assert info["full_brain_mesh"]
      assert not info["black_bg"]
      assert isinstance(info["cmax"], float)
      json.dumps(info)
      for hemi in ["left", "right"]:
          mesh = surface.load_surf_mesh(surfaces[f"pial_{hemi}"])
          assert len(info[f"vertexcolor_{hemi}"]) == len(mesh[0])
          assert len(
              decode(info[f"inflated_{hemi}"]["_z"], "<f4")
          ) == len(mesh[0])
          assert len(decode(info[f"pial_{hemi}"]["_j"], "<i4")) == len(
              mesh[1]
          )
  
      with pytest.warns(
          DeprecationWarning,
          match="full_brain_info is a private function and is renamed to "
          "_full_brain_info. Using the deprecated name will raise an error "
          "in release 0.13",
      ):
          html_surface.full_brain_info(img)
  
file_path: nilearn/nilearn/plotting/tests/test_html_surface.py
imports: import json
  import numpy
  import pytest
  from nilearn import datasets, image, surface
  from nilearn._utils.exceptions import DimensionError
  from nilearn.datasets import fetch_surf_fsaverage
  from nilearn.image import get_data
  from nilearn.plotting import html_surface
  from nilearn.plotting.js_plotting_utils import decode
  from .test_js_plotting_utils import check_colors, check_html
label_desc: Use image node_id 5 for calling a global function with example usage: test_full_brain_info() without return types