|
5261
|
1 \section{Standard Module \sectcode{random}}
|
|
|
2 \stmodindex{random}
|
|
|
3
|
|
|
4 This module implements pseudo-random number generators for various
|
|
|
5 distributions: on the real line, there are functions to compute normal
|
|
|
6 or Gaussian, lognormal, negative exponential, gamma, and beta
|
|
|
7 distributions. For generating distribution of angles, the circular
|
|
|
8 uniform and von Mises distributions are available.
|
|
|
9
|
|
|
10 The module exports the following functions, which are exactly
|
|
|
11 equivalent to those in the \code{whrandom} module: \code{choice},
|
|
|
12 \code{randint}, \code{random}, \code{uniform}. See the documentation
|
|
|
13 for the \code{whrandom} module for these functions.
|
|
|
14
|
|
|
15 The following functions specific to the \code{random} module are also
|
|
|
16 defined, and all return real values. Function parameters are named
|
|
|
17 after the corresponding variables in the distribution's equation, as
|
|
|
18 used in common mathematical practice; most of these equations can be
|
|
|
19 found in any statistics text.
|
|
|
20
|
|
|
21 \renewcommand{\indexsubitem}{(in module random)}
|
|
|
22 \begin{funcdesc}{betavariate}{alpha\, beta}
|
|
|
23 Beta distribution. Conditions on the parameters are \code{alpha>-1}
|
|
|
24 and \code{beta>-1}.
|
|
|
25 Returned values will range between 0 and 1.
|
|
|
26 \end{funcdesc}
|
|
|
27
|
|
|
28 \begin{funcdesc}{cunifvariate}{mean\, arc}
|
|
|
29 Circular uniform distribution. \var{mean} is the mean angle, and
|
|
|
30 \var{arc} is the range of the distribution, centered around the mean
|
|
|
31 angle. Both values must be expressed in radians, and can range
|
|
|
32 between 0 and \code{pi}. Returned values will range between
|
|
|
33 \code{mean - arc/2} and \code{mean + arc/2}.
|
|
|
34 \end{funcdesc}
|
|
|
35
|
|
|
36 \begin{funcdesc}{expovariate}{lambd}
|
|
|
37 Exponential distribution. \var{lambd} is 1.0 divided by the desired mean.
|
|
|
38 (The parameter would be called ``lambda'', but that's also a reserved
|
|
|
39 word in Python.) Returned values will range from 0 to positive infinity.
|
|
|
40 \end{funcdesc}
|
|
|
41
|
|
|
42 \begin{funcdesc}{gamma}{alpha\, beta}
|
|
|
43 Gamma distribution. (\emph{Not} the gamma function!)
|
|
|
44 Conditions on the parameters are \code{alpha>-1} and \code{beta>0}.
|
|
|
45 \end{funcdesc}
|
|
|
46
|
|
|
47 \begin{funcdesc}{gauss}{mu\, sigma}
|
|
|
48 Gaussian distribution. \var{mu} is the mean, and \var{sigma} is the
|
|
|
49 standard deviation. This is slightly faster than the
|
|
|
50 \code{normalvariate} function defined below.
|
|
|
51 \end{funcdesc}
|
|
|
52
|
|
|
53 \begin{funcdesc}{lognormvariate}{mu\, sigma}
|
|
|
54 Log normal distribution. If you take the natural logarithm of this
|
|
|
55 distribution, you'll get a normal distribution with mean \var{mu} and
|
|
|
56 standard deviation \var{sigma} \var{mu} can have any value, and \var{sigma}
|
|
|
57 must be greater than zero.
|
|
|
58 \end{funcdesc}
|
|
|
59
|
|
|
60 \begin{funcdesc}{normalvariate}{mu\, sigma}
|
|
|
61 Normal distribution. \var{mu} is the mean, and \var{sigma} is the
|
|
|
62 standard deviation.
|
|
|
63 \end{funcdesc}
|
|
|
64
|
|
|
65 \begin{funcdesc}{vonmisesvariate}{mu\, kappa}
|
|
|
66 \var{mu} is the mean angle, expressed in radians between 0 and pi,
|
|
|
67 and \var{kappa} is the concentration parameter, which must be greater
|
|
|
68 then or equal to zero. If \var{kappa} is equal to zero, this
|
|
|
69 distribution reduces to a uniform random angle over the range 0 to
|
|
|
70 \code{2*pi}.
|
|
|
71 \end{funcdesc}
|
