From 48b574ec451df9429d73e6b638613e92a52c5805 Mon Sep 17 00:00:00 2001
From: Gertjan van den Burg <gertjanvandenburg@gmail.com>
Date: Fri, 14 Oct 2016 22:10:53 +0200
Subject: change markdown to rst

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 README.md  | 83 --------------------------------------------------------------
 README.rst | 70 ++++++++++++++++++++++++++++++++++++++++++++++++++++
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 delete mode 100644 README.md
 create mode 100644 README.rst

diff --git a/README.md b/README.md
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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]`.
-
diff --git a/README.rst b/README.rst
new file mode 100644
index 0000000..bfcf1fe
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+++ b/README.rst
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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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