code: def random(target, element, seed=None, num_range=[0, 1]):
      r
      range_size = num_range[1] - num_range[0]
      range_min = num_range[0]
      if seed is not None:
          np.random.seed(seed)
      value = np.random.rand(target._count(element),)
      value = value*range_size + range_min
      return value
docs: r"""
      Create an array of random numbers of a specified size.
  
      Parameters
      ----------
      target : OpenPNM Object
          The object which this model is associated with. This controls the
          length of the calculated array, and also provides access to other
          necessary properties.
  
      seed : int
          The starting seed value to send to Scipy's random number generator.
          The default is None, which means different distribution is returned
          each time the model is run.
  
      num_range : list
          A two element list indicating the low and high end of the returned
          numbers.