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author | Raymond Hettinger <python@rcn.com> | 2002-05-14 06:40:34 (GMT) |
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committer | Raymond Hettinger <python@rcn.com> | 2002-05-14 06:40:34 (GMT) |
commit | b760efb08d509bb2acfdef8f4e59dfafa20ca57f (patch) | |
tree | 601137eb4974d2b9c3c5117f5153d79fd9ccba7d /Lib/random.py | |
parent | bdc8289e06fb95578187e203048d7ae445e5bb6d (diff) | |
download | cpython-b760efb08d509bb2acfdef8f4e59dfafa20ca57f.zip cpython-b760efb08d509bb2acfdef8f4e59dfafa20ca57f.tar.gz cpython-b760efb08d509bb2acfdef8f4e59dfafa20ca57f.tar.bz2 |
Closes patch 529408 deprecating random.stdgamma().
Diffstat (limited to 'Lib/random.py')
-rw-r--r-- | Lib/random.py | 46 |
1 files changed, 35 insertions, 11 deletions
diff --git a/Lib/random.py b/Lib/random.py index affa381..8747b06 100644 --- a/Lib/random.py +++ b/Lib/random.py @@ -445,14 +445,15 @@ class Random: ## -------------------- gamma distribution -------------------- def gammavariate(self, alpha, beta): - # beta times standard gamma - return beta * self.stdgamma(alpha) - - def stdgamma(self, alpha, *args): # *args for Py2.2 compatiblity + + # alpha > 0, beta > 0, mean is alpha*beta, variance is alpha*beta**2 + + # Warning: a few older sources define the gamma distribution in terms + # of alpha > -1.0 + if alpha <= 0.0 or beta <= 0.0: + raise ValueError, 'gammavariate: alpha and beta must be > 0.0' + random = self.random - if alpha <= 0.0: - raise ValueError, 'stdgamma: alpha must be > 0.0' - if alpha > 1.0: # Uses R.C.H. Cheng, "The generation of Gamma @@ -471,14 +472,14 @@ class Random: z = u1*u1*u2 r = bbb+ccc*v-x if r + SG_MAGICCONST - 4.5*z >= 0.0 or r >= _log(z): - return x + return x * beta elif alpha == 1.0: # expovariate(1) u = random() while u <= 1e-7: u = random() - return -_log(u) + return -_log(u) * beta else: # alpha is between 0 and 1 (exclusive) @@ -497,7 +498,27 @@ class Random: if not (((p <= 1.0) and (u1 > _exp(-x))) or ((p > 1) and (u1 > pow(x, alpha - 1.0)))): break - return x + return x * beta + + + def stdgamma(self, alpha, ainv, bbb, ccc): + # This method was (and shall remain) undocumented. + # This method is deprecated + # for the following reasons: + # 1. Returns same as .gammavariate(alpha, 1.0) + # 2. Requires caller to provide 3 extra arguments + # that are functions of alpha anyway + # 3. Can't be used for alpha < 0.5 + + # ainv = sqrt(2 * alpha - 1) + # bbb = alpha - log(4) + # ccc = alpha + ainv + import warnings + warnings.warn("The stdgamma function is deprecated; " + "use gammavariate() instead", + DeprecationWarning) + return self.gammavariate(alpha, 1.0) + ## -------------------- Gauss (faster alternative) -------------------- @@ -596,7 +617,7 @@ def _test_generator(n, funccall): print 'avg %g, stddev %g, min %g, max %g' % \ (avg, stddev, smallest, largest) -def _test(N=200): +def _test(N=20000): print 'TWOPI =', TWOPI print 'LOG4 =', LOG4 print 'NV_MAGICCONST =', NV_MAGICCONST @@ -607,6 +628,9 @@ def _test(N=200): _test_generator(N, 'cunifvariate(0.0, 1.0)') _test_generator(N, 'expovariate(1.0)') _test_generator(N, 'vonmisesvariate(0.0, 1.0)') + _test_generator(N, 'gammavariate(0.01, 1.0)') + _test_generator(N, 'gammavariate(0.1, 1.0)') + _test_generator(N, 'gammavariate(0.1, 2.0)') _test_generator(N, 'gammavariate(0.5, 1.0)') _test_generator(N, 'gammavariate(0.9, 1.0)') _test_generator(N, 'gammavariate(1.0, 1.0)') |