code: def normal(target, seeds, scale, loc):
      r
      seeds = target[seeds]
      value = spts.norm.ppf(q=seeds, scale=scale, loc=loc)
      return value
docs: r"""
      Produces values from a Weibull distribution given a set of random numbers.
  
      Parameters
      ----------
      target : OpenPNM Object
          The object with which this function as associated.  This argument
          is required to (1) set number of values to generate (geom.Np or
          geom.Nt) and (2) provide access to other necessary values
          (i.e. geom['pore.seed']).
  
      seeds : string, optional
          The dictionary key on the Geometry object containing random seed values
          (between 0 and 1) to use in the statistical distribution.
  
      scale : float
          The standard deviation of the Normal distribution
  
      loc : float
          The mean of the Normal distribution
  
      Examples
      --------
      The following code illustrates the inner workings of this function,
      which uses the 'norm' method of the scipy.stats module.  This can
      be used to find suitable values of 'scale' and 'loc'.
  
      >>> import scipy
      >>> func = scipy.stats.norm(scale=.0001, loc=0.001)
      >>> import matplotlib.pyplot as plt
      >>> fig = plt.hist(func.ppf(q=scipy.rand(10000)), bins=50)