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Impulse-Based Dynamic Simulation 1.09 (Default branch)
03-18-2008
IBDS is a library for dynamic simulation ofmulti-body systems in C++. It simulates rigidbodies, particles, many different joint types, andcollisions with friction.License: zlib/libpng LicenseChanges:|
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simulation::random(n) Tcl Simulation Tools simulation::random(n) __________________________________________________________________________________________________________________________________________________ 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 generators. These new commands deliver o numbers that are distributed normally, uniformly, according to a Pareto or Gumbel distribution and so on o 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. PROCEDURES
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 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 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. 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 numbers 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 distribution 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 COPYRIGHT
Copyright (c) 2004 Arjen Markus <arjenmarkus@users.sourceforge.net> simulation 0.1 simulation::random(n)