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authorGertjan van den Burg <gertjanvandenburg@gmail.com>2017-12-18 09:39:49 -0500
committerGertjan van den Burg <gertjanvandenburg@gmail.com>2017-12-18 09:39:49 -0500
commit3a2fb08bf58d5889a4b71f06eb3033abfe6e43f1 (patch)
treeb04d5125af5982d9d13e1b4b129f56fa2e17988e
parentupdate master with python branch (diff)
downloadSyncRNG-3a2fb08bf58d5889a4b71f06eb3033abfe6e43f1.tar.gz
SyncRNG-3a2fb08bf58d5889a4b71f06eb3033abfe6e43f1.zip
update readme with new R feature
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--- a/README.rst
+++ b/README.rst
@@ -15,6 +15,9 @@ 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.
+You can read more about my motivations for creating this `here
+<https://gertjanvandenburg.com/blog/syncrng/>`_.
+
How
===
@@ -38,6 +41,21 @@ Similarly, after installing the R library you can do in R::
You'll notice that the random numbers are indeed the same.
+R - User defined RNG
+--------------------
+
+R allows the user to define a custom random number generator, which is then
+used for the common ``runif`` and ``rnorm`` functions in R. This has also been
+implemented in SyncRNG as of version 1.3.0. To enable this, run::
+
+ library(SyncRNG)
+
+ set.seed(123456, 'user', 'user')
+ runif(10)
+
+These numbers are between [0, 1) and multiplying by ``2**32 - 1`` gives the
+same results as above.
+
Installation
============
@@ -67,4 +85,8 @@ Notes
The random numbers are uniformly distributed on ``[0, 2^32 - 1]``.
+Questions and Issues
+====================
+If you have questions about SyncRNG or you encounter a problem, please open an
+`issue on GitHub <https://github.com/GjjvdBurg/SyncRNG/>`_.