Issue 1681432: Add triangular distribution the random module.
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@ -190,6 +190,10 @@ be found in any statistics text.
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Return a random floating point number *N* such that ``a <= N < b``.
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.. function:: triangular(low, high, mode)
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Return a random floating point number *N* such that ``low <= N < high``
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and with the specified *mode* between those bounds.
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.. function:: betavariate(alpha, beta)
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@ -13,6 +13,7 @@
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distributions on the real line:
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------------------------------
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uniform
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triangular
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normal (Gaussian)
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lognormal
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negative exponential
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@ -47,7 +48,7 @@ from binascii import hexlify as _hexlify
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__all__ = ["Random","seed","random","uniform","randint","choice","sample",
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"randrange","shuffle","normalvariate","lognormvariate",
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"expovariate","vonmisesvariate","gammavariate",
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"expovariate","vonmisesvariate","gammavariate","triangular",
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"gauss","betavariate","paretovariate","weibullvariate",
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"getstate","setstate","jumpahead", "WichmannHill", "getrandbits",
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"SystemRandom"]
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@ -350,6 +351,25 @@ class Random(_random.Random):
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"""Get a random number in the range [a, b)."""
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return a + (b-a) * self.random()
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## -------------------- triangular --------------------
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def triangular(self, low, high, mode):
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"""Triangular distribution.
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Continuous distribution bounded by given lower and upper limits,
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and having a given mode value in-between.
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http://en.wikipedia.org/wiki/Triangular_distribution
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"""
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u = self.random()
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c = (mode - low) / (high - low)
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if u > c:
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u = 1 - u
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c = 1 - c
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low, high = high, low
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return low + (high - low) * (u * c) ** 0.5
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## -------------------- normal distribution --------------------
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def normalvariate(self, mu, sigma):
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@ -839,6 +859,7 @@ def _test(N=2000):
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_test_generator(N, gammavariate, (200.0, 1.0))
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_test_generator(N, gauss, (0.0, 1.0))
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_test_generator(N, betavariate, (3.0, 3.0))
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_test_generator(N, triangular, (0.0, 1.0, 1.0/3.0))
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# Create one instance, seeded from current time, and export its methods
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# as module-level functions. The functions share state across all uses
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@ -850,6 +871,7 @@ _inst = Random()
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seed = _inst.seed
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random = _inst.random
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uniform = _inst.uniform
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triangular = _inst.triangular
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randint = _inst.randint
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choice = _inst.choice
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randrange = _inst.randrange
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@ -488,6 +488,7 @@ class TestDistributions(unittest.TestCase):
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g.random = x[:].pop; g.gammavariate(1.0, 1.0)
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g.random = x[:].pop; g.gammavariate(200.0, 1.0)
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g.random = x[:].pop; g.betavariate(3.0, 3.0)
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g.random = x[:].pop; g.triangular(0.0, 1.0, 1.0/3.0)
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def test_avg_std(self):
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# Use integration to test distribution average and standard deviation.
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@ -497,6 +498,7 @@ class TestDistributions(unittest.TestCase):
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x = [i/float(N) for i in xrange(1,N)]
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for variate, args, mu, sigmasqrd in [
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(g.uniform, (1.0,10.0), (10.0+1.0)/2, (10.0-1.0)**2/12),
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(g.triangular, (0.0, 1.0, 1.0/3.0), 4.0/9.0, 7.0/9.0/18.0),
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(g.expovariate, (1.5,), 1/1.5, 1/1.5**2),
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(g.paretovariate, (5.0,), 5.0/(5.0-1),
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5.0/((5.0-1)**2*(5.0-2))),
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@ -66,6 +66,8 @@ Library
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- Issue #2432: give DictReader the dialect and line_num attributes
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advertised in the docs.
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- Issue #1681432: Add triangular distribution to the random module
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- Issue #2136: urllib2's auth handler now allows single-quoted realms in the
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WWW-Authenticate header.
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