simulation::random - Pseudo-random number generators
package require Tcl ?8.4?
package require simulation::random 0.1
::simulation::random::prng_Bernoulli p
::simulation::random::prng_Discrete n
::simulation::random::prng_Poisson lambda
::simulation::random::prng_Uniform min
max
::simulation::random::prng_Exponential min
mean
::simulation::random::prng_Normal mean
stdev
::simulation::random::prng_Pareto min
steep
::simulation::random::prng_Gumbel min f
::simulation::random::prng_chiSquared df
::simulation::random::prng_Disk rad
::simulation::random::prng_Sphere rad
::simulation::random::prng_Ball rad
::simulation::random::prng_Rectangle length
width
::simulation::random::prng_Block length width
depth
This package consists of commands to generate pseudo-random number
generators. These new commands deliver
- numbers that are distributed normally, uniformly, according to a Pareto or
Gumbel distribution and so on
- coordinates of points uniformly spread inside a sphere or a rectangle
For example:
set p [::simulation::random::prng_Normal -1.0 10.0]
produces a new command (whose name is stored in the variable "p") that
generates normally distributed numbers with a mean of -1.0 and a standard
deviation of 10.0.
The package defines the following public procedures for
discrete distributions:
- ::simulation::random::prng_Bernoulli p
- Create a command (PRNG) that generates numbers with a Bernoulli
distribution: the value is either 1 or 0, with a chance p to be 1
- ::simulation::random::prng_Discrete n
- Create a command (PRNG) that generates numbers 0 to n-1 with equal
probability.
- int n
- Number of different values (ranging from 0 to n-1)
- ::simulation::random::prng_Poisson lambda
- Create a command (PRNG) that generates numbers according to the Poisson
distribution.
The package defines the following public procedures for
continuous distributions:
- ::simulation::random::prng_Uniform min max
- Create a command (PRNG) that generates uniformly distributed numbers
between "min" and "max".
- float
min
- Minimum number that will be generated
- float
max
- Maximum number that will be generated
- ::simulation::random::prng_Exponential min mean
- Create a command (PRNG) that generates exponentially distributed numbers
with a given minimum value and a given mean value.
- ::simulation::random::prng_Normal mean stdev
- Create a command (PRNG) that generates normally distributed numbers with a
given mean value and a given standard deviation.
- ::simulation::random::prng_Pareto min steep
- Create a command (PRNG) that generates numbers distributed according to
Pareto with a given minimum value and a given distribution steepness.
- ::simulation::random::prng_Gumbel min f
- Create a command (PRNG) that generates numbers distributed according to
Gumbel with a given minimum value and a given scale factor. The
probability density function is:
P(v) = exp( -exp(f*(v-min)))
- float
min
- Minimum number that will be generated
- float
f
- Scale factor for the values
- ::simulation::random::prng_chiSquared df
- Create a command (PRNG) that generates numbers distributed according to
the chi-squared distribution with df degrees of freedom. The mean is 0 and
the standard deviation is 1.
The package defines the following public procedures for random
point sets:
- ::simulation::random::prng_Disk rad
- Create a command (PRNG) that generates (x,y)-coordinates for points
uniformly spread over a disk of given radius.
- ::simulation::random::prng_Sphere rad
- Create a command (PRNG) that generates (x,y,z)-coordinates for points
uniformly spread over the surface of a sphere of given radius.
- ::simulation::random::prng_Ball rad
- Create a command (PRNG) that generates (x,y,z)-coordinates for points
uniformly spread within a ball of given radius.
- ::simulation::random::prng_Rectangle length
width
- Create a command (PRNG) that generates (x,y)-coordinates for points
uniformly spread over a rectangle.
- ::simulation::random::prng_Block length width
depth
- Create a command (PRNG) that generates (x,y)-coordinates for points
uniformly spread over a block
math, random numbers, simulation, statistical distribution
Copyright (c) 2004 Arjen Markus <arjenmarkus@users.sourceforge.net>