code: def _random_samples(lb, ub, npts=10000):
      """
      generate npts random samples between given lb & ub
  
      Inputs:
          lower bounds  --  a list of the lower bounds
          upper bounds  --  a list of the upper bounds
          npts  --  number of sample points [default = 10000]"""
      from mystic.tools import random_state
  
      dim = len(lb)
      pts = random_state(module="numpy.random").rand(dim, npts)
      for i in range(dim):
          pts[i] = (pts[i] * abs(ub[i] - lb[i])) + lb[i]
      return pts
  
file_path: mystic/mystic/math/samples.py
label_desc: Use image node_id 1 for calling a global function with example usage: _random_samples(lb, ub, npts) and returns: pts