code: def test_simplex_sigma_points_1D():
      """tests passing 1D data into sigma_points"""
  
      sp = SimplexSigmaPoints(1)
  
      # ukf = UKF(dim_x=1, dim_z=1, dt=0.1, hx=None, fx=None, kappa=kappa)
  
      Wm, Wc = sp.weights()
      assert np.allclose(Wm, Wc, 1e-12)
      assert len(Wm) == 2
  
      mean = 5
      cov = 9
  
      Xi = sp.sigma_points(mean, cov)
      xm, ucov = unscented_transform(Xi, Wm, Wc, 0)
  
      # sum of weights*sigma points should be the original mean
      m = 0.0
      for x, w in zip(Xi, Wm):
          m += x * w
  
      assert abs(m - mean) < 1.0e-12
      assert abs(xm[0] - mean) < 1.0e-12
      assert abs(ucov[0, 0] - cov) < 1.0e-12
  
      assert Xi.shape == (2, 1)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import matplotlib.pyplot
  import numpy.random
  from numpy.random import randn
  from numpy import asarray
  import numpy
  from filterpy.kalman import UnscentedKalmanFilter
  from filterpy.kalman import unscented_transform, MerweScaledSigmaPoints, JulierSigmaPoints, SimplexSigmaPoints
  from filterpy.common import Q_discrete_white_noise
  import filterpy.stats
  from math import cos, sin
  from filterpy.kalman import UnscentedKalmanFilter2
label_desc: Use image node_id 7 for calling a global function with example usage: test_simplex_sigma_points_1D() without return types