new_contents: import numpy as np
  
  import nose.tools as nt
  from numpy.random import seed
  import numpy.testing as nptest
  
  from paramnormal import continuous
  
  @nt.nottest
  def generate_knowns(np_rand_fxn, size, *args, **kwargs):
      seed(0)
      kwargs.update(dict(size=size))
      return np_rand_fxn(*args, **kwargs)
  
  
  @nt.nottest
  def generate_test_dist(cont_rand_fxn, size, *cargs, **ckwargs):
      seed(0)
      return cont_rand_fxn(*cargs, **ckwargs).rvs(size=size)
  
  
  class CheckDist_Mixin(object):
      @nt.nottest
      def do_check(self, size):
          result = generate_test_dist(self.cont_rand_fxn, size, *self.cargs, **self.ckwds)
          known = generate_knowns(self.np_rand_fxn, size, *self.npargs, **self.npkwds)
  
          nptest.assert_array_almost_equal(result, known)
  
      def test_0010(self):
          self.do_check(10)
  
      def test_0037(self):
          self.do_check(37)
  
      def test_0100(self):
          self.do_check(100)
  
      def test_3737(self):
          self.do_check(3737)
  
  
  class Test_uniform(CheckDist_Mixin):
      def setup(self):
          self.cont_rand_fxn = continuous.uniform
          self.cargs = []
          self.ckwds = dict(low=1, high=5)
  
          self.np_rand_fxn = np.random.uniform
          self.npargs = self.cargs.copy()
          self.npkwds = self.ckwds.copy()
  
  
  class Test_normal(CheckDist_Mixin):
      def setup(self):
          self.cont_rand_fxn = continuous.normal
          self.cargs = []
          self.ckwds = dict(mu=4, sigma=1.75)
  
          self.np_rand_fxn = np.random.normal
          self.npargs = []
          self.npkwds = dict(loc=4, scale=1.75)
  
  
  class Test_lognormal(CheckDist_Mixin):
      def setup(self):
          self.cont_rand_fxn = continuous.lognormal
          self.cargs = []
          self.ckwds = dict(mu=4, sigma=1.75)
  
          self.np_rand_fxn = np.random.lognormal
          self.npargs = self.cargs.copy()
          self.npkwds = dict(mean=4, sigma=1.75)
  
  
  class Test_beta(CheckDist_Mixin):
      def setup(self):
          self.cont_rand_fxn = continuous.beta
          self.cargs = [2, 3]
          self.ckwds = dict()
  
          self.np_rand_fxn = np.random.beta
          self.npargs = self.cargs.copy()
          self.npkwds = self.ckwds.copy()
  
subject: add tests for existing continuous distributions