code: def test_norm_cdf():
      # test using the 68-95-99.7 rule
  
      mu = 5
      std = 3
      var = std * std
  
      std_1 = norm_cdf((mu - std, mu + std), mu, var)
      assert abs(std_1 - 0.6827) < 0.0001
  
      std_1 = norm_cdf((mu + std, mu - std), mu, std=std)
      assert abs(std_1 - 0.6827) < 0.0001
  
      std_1half = norm_cdf((mu + std, mu), mu, var)
      assert abs(std_1half - 0.6827 / 2) < 0.0001
  
      std_2 = norm_cdf((mu - 2 * std, mu + 2 * std), mu, var)
      assert abs(std_2 - 0.9545) < 0.0001
  
      std_3 = norm_cdf((mu - 3 * std, mu + 3 * std), mu, var)
      assert abs(std_3 - 0.9973) < 0.0001
  
imports: from __future__ import division
  from math import exp
  import warnings
  import matplotlib.pyplot
  from mpl_toolkits.mplot3d import axes3d
  import numpy
  from numpy.linalg import inv
  import scipy
  from scipy.spatial.distance import mahalanobis
  from filterpy.stats import norm_cdf, multivariate_gaussian, logpdf, mahalanobis
  from scipy import linalg
label_desc: Use image node_id 6 for calling a global function with example usage: test_norm_cdf() without return types