code: def test_scaled_weights():
      for n in range(1, 5):
          for alpha in np.linspace(0.99, 1.01, 100):
              for beta in range(0, 2):
                  for kappa in range(0, 2):
                      sp = MerweScaledSigmaPoints(n, alpha, 0, 3 - n)
                      Wm, Wc = sp.weights()
                      assert abs(sum(Wm) - 1) < 1.0e-1
                      assert abs(sum(Wc) - 1) < 1.0e-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 5 for calling a global function with example usage: test_scaled_weights() without return types