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=======
SyncRNG
=======
A synchronized Tausworthe RNG usable in R and Python.
Why?
====
This program was created because it was desired to have the same random
numbers in both R and Python programs. Although both languages implement a
Mersenne-Twister RNG, the implementations are so different that it is not
possible to get the same random numbers with the same seed.
SyncRNG is a Tausworthe RNG implemented in ``syncrng.c``, and linked to both R
and Python. Since both use the same underlying C code, the random numbers will
be the same in both languages, provided the same seed is used.
How
===
First install the packages as stated under Installation. Then, in Python you
can do::
from SyncRNG import SyncRNG
s = SyncRNG(seed=123456)
for i in range(10):
print(s.randi())
Similarly, after installing the R library you can do in R::
library(SyncRNG)
s <- SyncRNG(seed=123456)
for (i in 1:10) {
cat(s$randi(), '\n')
}
You'll notice that the random numbers are indeed the same.
Installation
============
Installing the R package can be done through CRAN::
install.packages('SyncRNG')
The Python package can be installed using pip::
pip install syncrng
Usage
=====
In both R and Python the following methods are available for the ``SyncRNG``
class:
1. ``randi()``: generate a random integer on the interval [0, 2^32).
2. ``rand()``: generate a random floating point number on the interval [0.0,
1.0)
3. ``randbelow(n)``: generate a random integer below a given integer ``n``.
4. ``shuffle(x)``: generate a permutation of a given list of numbers ``x``.
Notes
=====
The random numbers are uniformly distributed on ``[0, 2^32 - 1]``.
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