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simulation::random(3tcllib)  Tcl Simulation Tools  simulation::random(3tcllib)

______________________________________________________________________________

NAME
       simulation::random - Pseudo-random number generators

SYNOPSIS
       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

_________________________________________________________________

DESCRIPTION
       This package consists of commands to generate pseudo-random number gen‐
       erators. 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 rec‐
	      tangle

       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 stan‐
       dard deviation of 10.0.

PROCEDURES
       The package defines the following public procedures for	discrete  dis‐
       tributions:

       ::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

	      float p
		     Chance the outcome is 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.

	      float lambda
		     Mean number per time interval

       The package defines the following public procedures for continuous dis‐
       tributions:

       ::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.

	      float min
		     Minimum number that will be generated

	      float mean
		     Mean value for the numbers

       ::simulation::random::prng_Normal mean stdev
	      Create a command (PRNG) that generates normally distributed num‐
	      bers with a given mean value and a given standard deviation.

	      float mean
		     Mean value for the numbers

	      float stdev
		     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  dis‐
	      tribution steepness.

	      float min
		     Minimum number that will be generated

	      float steep
		     Steepness of the distribution

       ::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.

	      float df
		     Degrees of freedom

       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.

	      float rad
		     Radius of the disk

       ::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.

	      float rad
		     Radius of the disk

       ::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.

	      float rad
		     Radius of the ball

       ::simulation::random::prng_Rectangle length width
	      Create a command (PRNG)  that  generates	(x,y)-coordinates  for
	      points uniformly spread over a rectangle.

	      float length
		     Length of the rectangle (x-direction)

	      float width
		     Width of the rectangle (y-direction)

       ::simulation::random::prng_Block length width depth
	      Create  a	 command  (PRNG)  that generates (x,y)-coordinates for
	      points uniformly spread over a block

	      float length
		     Length of the block (x-direction)

	      float width
		     Width of the block (y-direction)

	      float depth
		     Depth of the block (z-direction)

KEYWORDS
       math, random numbers, simulation, statistical distribution

CATEGORY
       Mathematics

COPYRIGHT
       Copyright (c) 2004 Arjen Markus <arjenmarkus@users.sourceforge.net>

simulation			      0.1	   simulation::random(3tcllib)
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