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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:
-
-```python
-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:
-
-```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 devtools:
-
-```R
-library(devtools)
-devtools::install_github("GjjvdBurg/SyncRNG")
-```
-
-To install SyncRNG as a Python module, first clone the repository. The Python 
-module can then be installed locally for the user using:
-
-```sh
-python setup.py install --user
-```
-or system-wide through:
-
-```sh
-sudo python setup.py install
-```
-
-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]`.
-