mirror of
https://github.com/python/cpython.git
synced 2025-11-03 19:34:08 +00:00
e47da0ae04
* \bcode, \ecode added everywhere
* \label{module-foo} added everywhere
* A few \seealso sections added.
* Indentation fixed inside verbatim in lib*tex files
77 lines
3.1 KiB
TeX
77 lines
3.1 KiB
TeX
\section{Standard Module \sectcode{random}}
|
|
\label{module-random}
|
|
\stmodindex{random}
|
|
|
|
This module implements pseudo-random number generators for various
|
|
distributions: on the real line, there are functions to compute normal
|
|
or Gaussian, lognormal, negative exponential, gamma, and beta
|
|
distributions. For generating distribution of angles, the circular
|
|
uniform and von Mises distributions are available.
|
|
|
|
The module exports the following functions, which are exactly
|
|
equivalent to those in the \code{whrandom} module: \code{choice},
|
|
\code{randint}, \code{random}, \code{uniform}. See the documentation
|
|
for the \code{whrandom} module for these functions.
|
|
|
|
The following functions specific to the \code{random} module are also
|
|
defined, and all return real values. Function parameters are named
|
|
after the corresponding variables in the distribution's equation, as
|
|
used in common mathematical practice; most of these equations can be
|
|
found in any statistics text.
|
|
|
|
\renewcommand{\indexsubitem}{(in module random)}
|
|
\begin{funcdesc}{betavariate}{alpha\, beta}
|
|
Beta distribution. Conditions on the parameters are \code{alpha>-1}
|
|
and \code{beta>-1}.
|
|
Returned values will range between 0 and 1.
|
|
\end{funcdesc}
|
|
|
|
\begin{funcdesc}{cunifvariate}{mean\, arc}
|
|
Circular uniform distribution. \var{mean} is the mean angle, and
|
|
\var{arc} is the range of the distribution, centered around the mean
|
|
angle. Both values must be expressed in radians, and can range
|
|
between 0 and \code{pi}. Returned values will range between
|
|
\code{mean - arc/2} and \code{mean + arc/2}.
|
|
\end{funcdesc}
|
|
|
|
\begin{funcdesc}{expovariate}{lambd}
|
|
Exponential distribution. \var{lambd} is 1.0 divided by the desired mean.
|
|
(The parameter would be called ``lambda'', but that's also a reserved
|
|
word in Python.) Returned values will range from 0 to positive infinity.
|
|
\end{funcdesc}
|
|
|
|
\begin{funcdesc}{gamma}{alpha\, beta}
|
|
Gamma distribution. (\emph{Not} the gamma function!)
|
|
Conditions on the parameters are \code{alpha>-1} and \code{beta>0}.
|
|
\end{funcdesc}
|
|
|
|
\begin{funcdesc}{gauss}{mu\, sigma}
|
|
Gaussian distribution. \var{mu} is the mean, and \var{sigma} is the
|
|
standard deviation. This is slightly faster than the
|
|
\code{normalvariate} function defined below.
|
|
\end{funcdesc}
|
|
|
|
\begin{funcdesc}{lognormvariate}{mu\, sigma}
|
|
Log normal distribution. If you take the natural logarithm of this
|
|
distribution, you'll get a normal distribution with mean \var{mu} and
|
|
standard deviation \var{sigma} \var{mu} can have any value, and \var{sigma}
|
|
must be greater than zero.
|
|
\end{funcdesc}
|
|
|
|
\begin{funcdesc}{normalvariate}{mu\, sigma}
|
|
Normal distribution. \var{mu} is the mean, and \var{sigma} is the
|
|
standard deviation.
|
|
\end{funcdesc}
|
|
|
|
\begin{funcdesc}{vonmisesvariate}{mu\, kappa}
|
|
\var{mu} is the mean angle, expressed in radians between 0 and pi,
|
|
and \var{kappa} is the concentration parameter, which must be greater
|
|
then or equal to zero. If \var{kappa} is equal to zero, this
|
|
distribution reduces to a uniform random angle over the range 0 to
|
|
\code{2*pi}.
|
|
\end{funcdesc}
|
|
|
|
|
|
\begin{seealso}
|
|
\seemodule{whrandom}{the standard Python random number generator}
|
|
\end{seealso}
|