code: def _flat_mesh(x_s, y_s, z=0):
      # outer normals point upwards ie [0, 0, 1]
      x, y = np.mgrid[:x_s, :y_s]
      x, y = x.ravel(), y.ravel()
      z = np.ones(len(x)) * z
      vertices = np.asarray([x, y, z]).T
      triangulation = Delaunay(vertices[:, :2]).simplices
      mesh = [vertices, triangulation]
      return mesh
  
imports: import os
  import tempfile
  import warnings
  import nibabel
  import numpy
  import pytest
  from nibabel import gifti
  from numpy.testing import assert_array_almost_equal, assert_array_equal
  from scipy.spatial import Delaunay
  from scipy.stats import pearsonr
  from nilearn import datasets, image
  from nilearn._utils import data_gen
  from nilearn.image import resampling
  from nilearn.surface import Mesh, Surface, load_surf_data, load_surf_mesh, surface
  from nilearn.surface.surface import _gifti_img_to_mesh, _load_surf_files_gifti_gzip
  from nilearn.surface.tests._testing import flat_mesh, generate_surf, z_const_img
label_desc: Use image node_id 17 for calling a global function with example usage: _flat_mesh(x_s, y_s, z) and returns: mesh