code: def _gaussian_energy(sigma):
      """
      Compute the integral of a squared three-dimensional Gaussian
      kernel with axis-wise standard deviations `sigma`.
      """
      sigma = np.asarray(sigma)
      if sigma.size == 1:
          sigma = np.repeat(sigma, NDIM)
      # Use kernel separability to save memory
      return np.prod([_gaussian_energy_1d(s) for s in sigma])
  
imports: import warnings
  from os.path import join
  import numpy
  import scipy.ndimage
  import scipy.stats
  from nibabel import io_orientation
  from ...None import save_image
  from ...core.image.image_spaces import make_xyz_image, xyz_affine
  from ..kernel_smooth import fwhm2sigma
  from ..registration import resample
  from ..statistics.bayesian_mixed_effects import two_level_glm
  from ..statistics.histogram import histogram
label_desc: Use image node_id 3 for calling a global function with example usage: _gaussian_energy(sigma) and returns: np