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random-mtzig

An implementation of the MT19937 random number generator with Marsaglia and Tang's Ziggurat algorithm to generate random numbers from a non-uniform distribution.

Usage

(require-extension random-mtzig)

Documentation

The random-mtzig library is Chicken Scheme wrapper for the MT19937 random number generator used in GNU Octave.

Procedures

[procedure] random-mtzig:init :: [SEED] -> STATE

Creates an initial seed array and returns the corresponding generator state vector. If the optional SEED is not specified, the generator is initialized with a seed from /dev/urandom or with the current time in seconds. If SEED can be an integer or an u32vector.

[procedure] random-mtzig:random! :: STATE -> INTEGER

Returns a random integer value between 0 and the largest machine-representable unsigned integer on the current platform.

[procedure] random-mtzig:randu! :: STATE -> NUMBER

Returns a random value from a uniform distribution on the interval (0, 1).

[procedure] random-mtzig:randn! :: STATE -> NUMBER

Returns a random value from a normal (Gaussian) distribution, using Marsaglia and Tsang's Ziggurat algorithm to transform a uniform distribution into a normal one.

[procedure] random-mtzig:rande! :: STATE -> NUMBER

Returns a random value from an exponential distribution, using Marsaglia and Tsang's Ziggurat algorithm to transform a uniform distribution into an exponential one.

[procedure] random-mtzig:randb! :: N * P * STATE -> NUMBER

Returns a random value from a binomial distribution with N experiments and probability P.

[procedure] random-mtzig:randp! :: L * STATE -> NUMBER

Returns a random value from a Poisson distribution with mean value L.

[procedure] random-mtzig:f64vector-randu! :: N * STATE -> F64VECTOR

Returns an SRFI-4 f64 vector of random values from a uniform distribution on the interval (0, 1).

[procedure] random-mtzig:f64vector-randn! :: N * STATE -> F64VECTOR

Returns an SRFI-4 f64 vector of random values from a normal (Gaussian) distribution, using Marsaglia and Tsang's Ziggurat algorithm to transform a uniform distribution into a normal one.

[procedure] random-mtzig:f64vector-rande! :: N * STATE -> F64VECTOR

Returns an SRFI-4 f64 vector of random values from am exponential distribution, using Marsaglia and Tsang's Ziggurat algorithm to transform a uniform distribution into an exponential one.

[procedure] random-mtzig:f64vector-randb! :: N * P * XN * STATE -> F64VECTOR

Returns an SRFI-4 f64 vector of random values from a binomial distribution with N experiments and probability P.

[procedure] random-mtzig:f64vector-randp! :: L * XN * STATE -> F64VECTOR

Returns an SRFI-4 f64 vector of random values from a Poisson distribution with mean value L.

[procedure] random-mtzig:f32vector-randu! :: N * STATE -> F32VECTOR

Returns an SRFI-4 f32 vector of random values from a uniform distribution on the interval (0, 1).

[procedure] random-mtzig:f32vector-randn! :: N * STATE -> F32VECTOR

Returns an SRFI-4 f32 vector of random values from a normal (Gaussian) distribution, using Marsaglia and Tsang's Ziggurat algorithm to transform a uniform distribution into a normal one.

[procedure] random-mtzig:f32vector-rande! :: N * STATE -> F32VECTOR

Returns an SRFI-4 f32 vector of random values from am exponential distribution, using Marsaglia and Tsang's Ziggurat algorithm to transform a uniform distribution into an exponential one.

[procedure] random-mtzig:f32vector-randb! :: N * P * XN * STATE -> F32VECTOR

Returns an SRFI-4 f32 vector of random values from a binomial distribution with N experiments and probability P.

[procedure] random-mtzig:f32vector-randb! :: L * XN * STATE -> F32VECTOR

Returns an SRFI-4 f32 vector of random values from a Poisson distribution with mean value L.

Examples

```csi> (require-extension random-mtzig)
csi> (define st (random-mtzig:init 24))
csi> (random-mtzig:f64vector-randu! 20 st)
#f64(0.960017303335919 0.699512049949576 0.999867292623879 0.220067299782852
0.361056353964058 0.739840990209437 0.996455725089097 0.316346977790608
0.136544579823525 0.3839800101516 0.320519283565193 0.366414753083515
0.709651562588127 0.900142430523374 0.534115439197721 0.247293764909945
0.671806562577075 0.561729107313138 0.54255987670951 0.893447603694901)```

Ivan Raikov

Version history

3.0
Added procedures for generating random numbers from a Poisson distribution
2.9
Documentation converted to wiki format
2.8
Ported to Chicken 4
2.7
2.6
Build script updated for better cross-platform compatibility
2.5
Example updated to match 2.0 API [thanks to Terrence Brannon]
2.4
Bug fix in random-mtzig:f32vector-rande!
2.3
C interface bug fixes
2.2
Changed type definition for uint64_t so it doesn't collide with stdint.h
2.1
Bug fix in init procedure for vector case
2.0
Created reentrant interface
1.0
Initial release

```Chicken Scheme egg scripts and documentation Copyright 2007-2011 Ivan Raikov.

Coded by Takuji Nishimura and Makoto Matsumoto.
This is a faster version by taking Shawn Cokus's optimization,
Matthe Bellew's simplification, Isaku Wada's real version.
David Bateman added normal and exponential distributions following
Marsaglia and Tang's Ziggurat algorithm.

Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura,

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:

1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.

3. The names of its contributors may not be used to endorse or promote
products derived from this software without specific prior written
permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL THE COPYRIGHT OWNER
OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.```