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 whrandom
module: choice
,
randint
, random
, uniform
. See the documentation
for the whrandom
module for these functions.
The following functions specific to the 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.
- betavariate (alpha, beta)
-
Beta distribution. Conditions on the parameters are
alpha>-1
and beta>-1
.
Returned values will range between 0 and 1.
- cunifvariate (mean, arc)
-
Circular uniform distribution. mean is the mean angle, and
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
pi
. Returned values will range between
mean - arc/2
and mean + arc/2
.
- expovariate (lambd)
-
Exponential distribution. 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.
- gamma (alpha, beta)
-
Gamma distribution. (Not the gamma function!)
Conditions on the parameters are
alpha>-1
and beta>0
.
- gauss (mu, sigma)
-
Gaussian distribution. mu is the mean, and sigma is the
standard deviation. This is slightly faster than the
normalvariate
function defined below.
- lognormvariate (mu, sigma)
-
Log normal distribution. If you take the natural logarithm of this
distribution, you'll get a normal distribution with mean mu and
standard deviation sigma mu can have any value, and sigma
must be greater than zero.
- normalvariate (mu, sigma)
-
Normal distribution. mu is the mean, and sigma is the
standard deviation.
- vonmisesvariate (mu, kappa)
-
mu is the mean angle, expressed in radians between 0 and pi,
and kappa is the concentration parameter, which must be greater
then or equal to zero. If kappa is equal to zero, this
distribution reduces to a uniform random angle over the range 0 to
2*pi
.
- paretovariate (alpha)
-
XXX
- weibullvariate (alpha, beta)
-
XXX
See Also:
whrandom
(the standard Python random number generator)
guido@CNRI.Reston.Va.US