code: def local_mean_gauss(
      image, sigma=5, voxelspacing=None, mask=slice(None)
  ):
      r"""
      Takes a simple or multi-spectral image and returns the approximate mean over a small
      region around each voxel. A multi-spectral image must be supplied as a list or tuple
      of its spectra.
  
      Optionally a binary mask can be supplied to select the voxels for which the feature
      should be extracted.
  
      For this feature a Gaussian smoothing filter is applied to the image / each spectrum
      and then the resulting intensity values returned. Another name for this function
      would be weighted local mean.
  
      Parameters
      ----------
      image : array_like or list/tuple of array_like
          A single image or a list/tuple of images (for multi-spectral case).
      sigma : number or sequence of numbers
          Standard deviation for Gaussian kernel. The standard deviations of the
          Gaussian filter are given for each axis as a sequence, or as a single number,
          in which case it is equal for all axes. Note that the voxel spacing of the image
          is taken into account, the given values are treated as mm.
      voxelspacing : sequence of floats
          The side-length of each voxel.
      mask : array_like
          A binary mask for the image.
  
  
      Returns
      -------
      local_mean_gauss : ndarray
          The weighted mean intensities over a region around each voxel.
  
      """
      return _extract_feature(
          _extract_local_mean_gauss,
          image,
          mask,
          sigma=sigma,
          voxelspacing=voxelspacing,
      )
  
imports: import numpy
  from scipy.ndimage import gaussian_filter, median_filter
  from scipy.ndimage import gaussian_gradient_magnitude
  from scipy.interpolate.interpolate import interp1d
  from scipy.ndimage import distance_transform_edt
  from scipy.ndimage._ni_support import _get_output
  from .utilities import join
  from ..core import ArgumentError
  from ..filter import sum_filter
label_desc: Use image node_id 7 for calling a global function with example usage: local_mean_gauss(image, sigma, voxelspacing, mask) and returns: _extract_feature