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Whitespace normalized.

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Raymond Hettinger 2002-05-23 23:58:17 +00:00
parent b66e1a3dd2
commit ef4d4bdc3c
1 changed files with 11 additions and 11 deletions
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22
Lib/random.py
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@ -117,7 +117,7 @@ class Random:
Class Random can also be subclassed if you want to use a different basic Class Random can also be subclassed if you want to use a different basic
generator of your own devising: in that case, override the following generator of your own devising: in that case, override the following
methods: random(), seed(), getstate(), setstate() and jumpahead(). methods: random(), seed(), getstate(), setstate() and jumpahead().
""" """
VERSION = 1 # used by getstate/setstate VERSION = 1 # used by getstate/setstate
@ -374,7 +374,7 @@ class Random:
"""Normal distribution. """Normal distribution.
mu is the mean, and sigma is the standard deviation. mu is the mean, and sigma is the standard deviation.
""" """
# mu = mean, sigma = standard deviation # mu = mean, sigma = standard deviation
@ -401,7 +401,7 @@ class Random:
If you take the natural logarithm of this distribution, you'll get a If you take the natural logarithm of this distribution, you'll get a
normal distribution with mean mu and standard deviation sigma. normal distribution with mean mu and standard deviation sigma.
mu can have any value, and sigma must be greater than zero. mu can have any value, and sigma must be greater than zero.
""" """
return _exp(self.normalvariate(mu, sigma)) return _exp(self.normalvariate(mu, sigma))
@ -417,7 +417,7 @@ class Random:
Deprecated in version 2.3. Use: Deprecated in version 2.3. Use:
(mean + arc * (Random.random() - 0.5)) % Math.pi (mean + arc * (Random.random() - 0.5)) % Math.pi
""" """
# mean: mean angle (in radians between 0 and pi) # mean: mean angle (in radians between 0 and pi)
# arc: range of distribution (in radians between 0 and pi) # arc: range of distribution (in radians between 0 and pi)
@ -436,7 +436,7 @@ class Random:
lambd is 1.0 divided by the desired mean. (The parameter would be lambd is 1.0 divided by the desired mean. (The parameter would be
called "lambda", but that is a reserved word in Python.) Returned called "lambda", but that is a reserved word in Python.) Returned
values range from 0 to positive infinity. values range from 0 to positive infinity.
""" """
# lambd: rate lambd = 1/mean # lambd: rate lambd = 1/mean
# ('lambda' is a Python reserved word) # ('lambda' is a Python reserved word)
@ -451,12 +451,12 @@ class Random:
def vonmisesvariate(self, mu, kappa): def vonmisesvariate(self, mu, kappa):
"""Circular data distribution. """Circular data distribution.
mu is the mean angle, expressed in radians between 0 and 2*pi, and mu is the mean angle, expressed in radians between 0 and 2*pi, and
kappa is the concentration parameter, which must be greater than or kappa is the concentration parameter, which must be greater than or
equal to zero. If kappa is equal to zero, this distribution reduces equal to zero. If kappa is equal to zero, this distribution reduces
to a uniform random angle over the range 0 to 2*pi. to a uniform random angle over the range 0 to 2*pi.
""" """
# mu: mean angle (in radians between 0 and 2*pi) # mu: mean angle (in radians between 0 and 2*pi)
# kappa: concentration parameter kappa (>= 0) # kappa: concentration parameter kappa (>= 0)
@ -590,7 +590,7 @@ class Random:
slightly faster than the normalvariate() function. slightly faster than the normalvariate() function.
Not thread-safe without a lock around calls. Not thread-safe without a lock around calls.
""" """
# When x and y are two variables from [0, 1), uniformly # When x and y are two variables from [0, 1), uniformly
@ -641,9 +641,9 @@ class Random:
Conditions on the parameters are alpha > -1 and beta} > -1. Conditions on the parameters are alpha > -1 and beta} > -1.
Returned values range between 0 and 1. Returned values range between 0 and 1.
""" """
# This version due to Janne Sinkkonen, and matches all the std # This version due to Janne Sinkkonen, and matches all the std
# texts (e.g., Knuth Vol 2 Ed 3 pg 134 "the beta distribution"). # texts (e.g., Knuth Vol 2 Ed 3 pg 134 "the beta distribution").
y = self.gammavariate(alpha, 1.) y = self.gammavariate(alpha, 1.)
@ -667,7 +667,7 @@ class Random:
"""Weibull distribution. """Weibull distribution.
alpha is the scale parameter and beta is the shape parameter. alpha is the scale parameter and beta is the shape parameter.
""" """
# Jain, pg. 499; bug fix courtesy Bill Arms # Jain, pg. 499; bug fix courtesy Bill Arms