[Python-checkins] python/dist/src/Lib/test test_random.py,1.5,1.6

[rhettinger@users.sourceforge.net]

Update of /cvsroot/python/python/dist/src/Lib/test
In directory sc8-pr-cvs1:/tmp/cvs-serv21100/test

Modified Files:
	test_random.py 
Log Message:
Move the statistical tests for four distributions into the unittest suite.


Index: test_random.py
===================================================================
RCS file: /cvsroot/python/python/dist/src/Lib/test/test_random.py,v
retrieving revision 1.5
retrieving revision 1.6
diff -C2 -d -r1.5 -r1.6
*** test_random.py	5 Jan 2003 01:08:34 -0000	1.5
--- test_random.py	5 Jan 2003 09:20:06 -0000	1.6
***************
*** 4,7 ****
--- 4,8 ----
  import random
  import time
+ from math import log, exp, sqrt, pi
  from test import test_support
  
***************
*** 183,186 ****
--- 184,199 ----
          self.gen.seed(seed)
  
+ _gammacoeff = (0.9999999999995183, 676.5203681218835, -1259.139216722289,
+               771.3234287757674,  -176.6150291498386, 12.50734324009056,
+               -0.1385710331296526, 0.9934937113930748e-05, 0.1659470187408462e-06)
+ 
+ def gamma(z, cof=_gammacoeff, g=7):
+     z -= 1.0
+     sum = cof[0]
+     for i in xrange(1,len(cof)):
+         sum += cof[i] / (z+i)
+     z += 0.5
+     return (z+g)**z / exp(z+g) * sqrt(2*pi) * sum
+ 
  class TestDistributions(unittest.TestCase):
      def test_zeroinputs(self):
***************
*** 200,203 ****
--- 213,244 ----
          g.random = x[:].pop; g.gammavariate(200.0, 1.0)
          g.random = x[:].pop; g.betavariate(3.0, 3.0)
+ 
+     def test_avg_std(self):
+         # Use integration to test distribution average and standard deviation.
+         # Only works for distributions which do not consume variates in pairs
+         g = random.Random()
+         N = 5000
+         x = [i/float(N) for i in xrange(1,N)]
+         for variate, args, mu, sigmasqrd in [
+                 (g.uniform, (1.0,10.0), (10.0+1.0)/2, (10.0-1.0)**2/12),
+                 (g.expovariate, (1.5,), 1/1.5, 1/1.5**2),
+                 (g.paretovariate, (5.0,), 5.0/(5.0-1),
+                                   5.0/((5.0-1)**2*(5.0-2))),
+                 (g.weibullvariate, (1.0, 3.0), gamma(1+1/3.0),
+                                   gamma(1+2/3.0)-gamma(1+1/3.0)**2) ]:
+             g.random = x[:].pop
+             y = []
+             for i in xrange(len(x)):
+                 try:
+                     y.append(variate(*args))
+                 except IndexError:
+                     pass
+             s1 = s2 = 0
+             for e in y:
+                 s1 += e
+                 s2 += (e - mu) ** 2
+             N = len(y)
+             self.assertAlmostEqual(s1/N, mu, 2)
+             self.assertAlmostEqual(s2/(N-1), sigmasqrd, 2)
  
  class TestModule(unittest.TestCase):