DOC: Doc string fixes

Fix change log for new release
Typo fixes

[skip ci]

Author: bashtage

README.md

@@ -39,7 +39,7 @@ w = rnd.standard_normal(10000, method='zig')
     * Normals (`standard_normal`, both Box-Muller and Ziggurat)
     * Standard Gammas (via `standard_gamma`) 
 
-  **WARNING**: The 32-bit generators are **experimental** and subjust 
+  **WARNING**: The 32-bit generators are **experimental** and subject 
   to change.
 
   **Note**: There are _no_ plans to extend the alternative precision 
@@ -78,11 +78,11 @@ The RNGs include:
 * `standard_normal`, `normal`, `randn` and `multivariate_normal` all 
 support an additional `method` keyword argument which can be `bm` or 
 `zig` where `bm` corresponds to the current method using the Box-Muller 
-transformation and `zig` uses the much faster (100%+) ziggurat method.
+transformation and `zig` uses the much faster (100%+) Ziggurat method.
 * Core random number generators can produce either single precision
 (`np.float32`) or double precision (`np.float64`, the default) using
 an the optional keyword argument `dtype`
-* Core random number generators can fill existin arrays using the
+* Core random number generators can fill existing arrays using the
 `out` keyword argument
 
 

README.rst

@@ -39,7 +39,7 @@ Features
    -  Normals (``standard_normal``, both Box-Muller and Ziggurat)
    -  Standard Gammas (via ``standard_gamma``)
 
-**WARNING**: The 32-bit generators are **experimental** and subjust to
+**WARNING**: The 32-bit generators are **experimental** and subject to
 change.
 
 **Note**: There are *no* plans to extend the alternative precision
@@ -82,11 +82,11 @@ New Features
    ``multivariate_normal`` all support an additional ``method`` keyword
    argument which can be ``bm`` or ``zig`` where ``bm`` corresponds to
    the current method using the Box-Muller transformation and ``zig``
-   uses the much faster (100%+) ziggurat method.
+   uses the much faster (100%+) Ziggurat method.
 -  Core random number generators can produce either single precision
    (``np.float32``) or double precision (``np.float64``, the default)
    using an the optional keyword argument ``dtype``
--  Core random number generators can fill existin arrays using the
+-  Core random number generators can fill existing arrays using the
    ``out`` keyword argument
 
 New Functions

doc/source/change-log.rst

@@ -3,8 +3,9 @@
 Change Log
 ==========
 
-Changes since 1.11.4
---------------------
+Version 1.12
+------------
+* Synchronize with NumPy 1.12 release
 * Add ``out`` argument which allows filling existing arrays. This feature was
   added to facilitate multithreaded filling of arrays using parallel random
   number generators.

doc/source/conf.py

@@ -58,7 +58,7 @@
 
 # General information about the project.
 project = 'randomstate'
-copyright = '2016, Kevin Sheppard'
+copyright = '2017, Kevin Sheppard'
 author = 'Kevin Sheppard'
 
 # The version info for the project you're documenting, acts as replacement for
@@ -131,7 +131,7 @@
 # Guzzle theme options (see theme.conf for more information)
 html_theme_options = {
     # Set the name of the project to appear in the sidebar
-    "project_nav_name": "randomstate",
+    "project_nav_name": "randomstate " + version,
 }
 
 # Add any paths that contain custom themes here, relative to this directory.
@@ -286,8 +286,8 @@
 #  dir menu entry, description, category)
 texinfo_documents = [
   (master_doc, 'randomstate', 'randomstate Documentation',
-   author, 'randomstate', 'One line description of project.',
-   'Miscellaneous'),
+   author, 'randomstate', 'NumPy-like random number generation supporting multiple core PRNG.',
+   'Random Numbers'),
 ]
 
 # Documents to append as an appendix to all manuals.

doc/source/multithreading.rst

@@ -3,14 +3,14 @@ Multithreaded Generation
 
 The four core distributions all allow existing arrays to be filled using the
 ``out`` keyword argument.  Existing arrays need to be contiguous and
-well-behaved (writable and algined).  Under normal circumstances, arrays
+well-behaved (writable and aligned).  Under normal circumstances, arrays
 created using the common constructors such as ``numpy.empty`` will satisfy
 these requirements.
 
 This example makes use of Python 3 ``futures`` to fill an array using multiple
 threads.  Threads are long-lived so that repeated calls do not require any
-additional overheads from thread creation. The undelying PRNG is xorshift2014
-which is fast, has a long period and supports using ``jump`` to advange the
+additional overheads from thread creation. The underlying PRNG is xorshift2014
+which is fast, has a long period and supports using ``jump`` to advance the
 state. The random numbers generated are reproducible in the sense that the
 same seed will produce the same outputs.
 

randomstate/randomstate.pyx

@@ -172,7 +172,6 @@ cdef object _ensure_string(object s):
 cdef class RandomState:
     CLASS_DOCSTRING
 
-    # cdef rng_t rng
     cdef void *rng_loc
     cdef binomial_t binomial_info
     cdef aug_state rng_state