code: def norm_cdf(x_range, mu, var=1, std=None):
      """
      Computes the probability that a Gaussian distribution lies
      within a range of values.
  
      Parameters
      ----------
  
      x_range : (float, float)
          tuple of range to compute probability for
  
      mu : float
          mean of the Gaussian
  
      var : float, optional
          variance of the Gaussian. Ignored if `std` is provided
  
      std : float, optional
         standard deviation of the Gaussian. This overrides the `var` parameter
  
      Returns
      -------
  
      probability : float
          probability that Gaussian is within x_range. E.g. .1 means 10%.
      """
  
      if std is None:
          std = math.sqrt(var)
      return abs(
          norm.cdf(x_range[0], loc=mu, scale=std)
          - norm.cdf(x_range[1], loc=mu, scale=std)
      )
  
imports: from __future__ import absolute_import, division, unicode_literals
  import math
  from math import cos, sin
  import random
  import warnings
  import numpy
  from numpy.linalg import inv
  import scipy.linalg
  import scipy.sparse
  import scipy.sparse.linalg
  from scipy.stats import norm, multivariate_normal
label_desc: Use image node_id 22 for calling a global function with example usage: norm_cdf(x_range, mu, var, std) and returns: abs