code: def spherical_radial_sigmas(x, P):
      r"""Creates cubature points for the the specified state and covariance
      according to [1].
  
      Parameters
      ----------
  
      x: ndarray (column vector)
          examples:  np.array([[1.], [2.]])
  
      P : scalar, or np.array
         Covariance of the filter.
  
      References
      ----------
  
      .. [1] Arasaratnam, I, Haykin, S. "Cubature Kalman Filters,"
         IEEE Transactions on Automatic Control, 2009, pp 1254-1269, vol 54, No 6
      """
  
      n, _ = P.shape
      x = x.flatten()
  
      sigmas = np.empty((2 * n, n))
      U = cholesky(P) * sqrt(n)
      for k in range(n):
          sigmas[k] = x + U[k]
          sigmas[n + k] = x - U[k]
  
      return sigmas
  
file_path: filterpy/filterpy/kalman/CubatureKalmanFilter.py
imports: from __future__ import absolute_import, division
  from copy import deepcopy
  from math import log, exp, sqrt
  import sys
  import numpy
  from numpy import eye, zeros, dot, isscalar
  from scipy.linalg import inv, cholesky
  from filterpy.stats import logpdf
  from filterpy.common import pretty_str, outer_product_sum
label_desc: Use image node_id 1 for calling a global function with example usage: spherical_radial_sigmas(x, P) and returns: sigmas