Adopt Nick's suggestion for useful default arguments.
Clean-up floating point issues by adding true division and float constants.
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@ -195,6 +195,11 @@ be found in any statistics text.
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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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If *mode* is not specified or is ``None``, it defaults to the midpoint
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between the upper and lower bounds, producing a symmetric distribution.
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The default values for *low* and *high* are zero and one.
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.. function:: betavariate(alpha, beta)
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Beta distribution. Conditions on the parameters are ``alpha > 0`` and ``beta >
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@ -39,6 +39,7 @@ General notes on the underlying Mersenne Twister core generator:
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"""
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from __future__ import division
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from warnings import warn as _warn
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from types import MethodType as _MethodType, BuiltinMethodType as _BuiltinMethodType
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from math import log as _log, exp as _exp, pi as _pi, e as _e, ceil as _ceil
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@ -353,7 +354,7 @@ class Random(_random.Random):
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## -------------------- triangular --------------------
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def triangular(self, low, high, mode):
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def triangular(self, low=0.0, high=1.0, mode=None):
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"""Triangular distribution.
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Continuous distribution bounded by given lower and upper limits,
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@ -363,10 +364,10 @@ class Random(_random.Random):
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"""
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u = self.random()
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c = (mode - low) / (high - low)
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c = 0.5 if mode is None else (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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u = 1.0 - u
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c = 1.0 - 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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