From 365078d43cfdbb3ec0396414de5c2669aff44328 Mon Sep 17 00:00:00 2001 From: Gertjan van den Burg Date: Sun, 16 Oct 2016 12:19:27 +0200 Subject: correct inline code notation in rst --- README.rst | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/README.rst b/README.rst index bfcf1fe..08afc28 100644 --- a/README.rst +++ b/README.rst @@ -11,7 +11,7 @@ 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 +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. @@ -53,18 +53,18 @@ The Python package can be installed using pip:: Usage ===== -In both R and Python the following methods are available for the `SyncRNG` +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. ``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`. +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]`. +The random numbers are uniformly distributed on ``[0, 2^32 - 1]``. -- cgit v1.2.3