code: def _gaussian_membership_sigma(
      smoothness, eps=0.0005
  ):  # 275us @ smothness=10
      r"""Compute the sigma required for a gaussian, such that in a neighbourhood of
      smoothness the maximum error is 'eps'.
      The error is here the difference between the clipped integral and one.
      """
      error = 0
      deltas = [0.1, 0.01, 0.001, 0.0001]
      sigma = smoothness * 0.3
      point = -1.0 * (smoothness + 0.5)
      for delta in deltas:
          while error < eps:
              sigma += delta
              error = scipy.stats.norm.cdf(
                  0.5, point, sigma
              ) - scipy.stats.norm.cdf(
                  -0.5, point, sigma
              )  # x, mu, sigma
          sigma -= delta
      return sigma
  
file_path: medpy/medpy/features/histogram.py
imports: import math
  import scipy.stats
label_desc: Use image node_id 5 for calling a global function with example usage: _gaussian_membership_sigma(smoothness, eps) and returns: sigma