code: def gauss_spline(x, n):
      """Gaussian approximation to B-spline basis function of order n.
  
      Parameters
      ----------
      n : int
          The order of the spline. Must be nonnegative, i.e. n >= 0
  
      References
      ----------
      .. [1] Bouma H., Vilanova A., Bescos J.O., ter Haar Romeny B.M., Gerritsen
         F.A. (2007) Fast and Accurate Gaussian Derivatives Based on B-Splines. In:
         Sgallari F., Murli A., Paragios N. (eds) Scale Space and Variational
         Methods in Computer Vision. SSVM 2007. Lecture Notes in Computer
         Science, vol 4485. Springer, Berlin, Heidelberg
      """
      signsq = (n + 1) / 12.0
      return 1 / sqrt(2 * pi * signsq) * exp(-(x**2) / 2 / signsq)
  
imports: from __future__ import division, print_function, absolute_import
  from scipy._lib.six import xrange
  from numpy import logical_and, asarray, pi, zeros_like, piecewise, array, arctan2, tan, zeros, arange, floor
  from numpy.core.umath import sqrt, exp, greater, less, cos, add, sin, less_equal, greater_equal
  from .spline import cspline2d, sepfir2d
  from scipy.special import comb, gamma
label_desc: Use image node_id 5 for calling a global function with example usage: gauss_spline(x, n) and returns: unknown