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diff --git a/README.rst b/README.rst deleted file mode 100644 index 08afc28..0000000 --- a/README.rst +++ /dev/null @@ -1,70 +0,0 @@ -======= -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]``. - - |