code: def _evaluate_assuming_gaussian(
      loc, scale, k_s_limit, expected, lb, ub
  ):
      dist = stats.norm(loc=loc, scale=scale)
      too_low_p = dist.cdf(lb)
      too_high_p = dist.sf(ub)
      return _GaussianResult(
          loc, scale, k_s_limit, too_low_p, too_high_p, expected, lb, ub
      )
  
imports: import collections
  import numpy
  import scipy.optimize
  import scipy.stats
label_desc: Use image node_id 6 for calling a global function with example usage: _evaluate_assuming_gaussian(loc, scale, k_s_limit, expected, lb, ub) and returns: _GaussianResult