STY: Giant whitespace cleanup.

Now is as good a time as any with open PR's at a low.

Author: charris

BENTO_BUILD.txt

@@ -3,7 +3,7 @@ No-frill version:
 	* Clone bento::
 
 		git clone git://github.com/cournape/Bento.git bento-git
-	
+
 	* Bootstrap bento::
 
 		cd bento-git && python bootstrap.py

DEV_README.txt

@@ -1,19 +1,18 @@
 Thank you for your willingness to help make NumPy the best array system
 available.
 
-We have a few simple rules: 
+We have a few simple rules:
 
    * try hard to keep the Git repository in a buildable state and to not
      indiscriminately muck with what others have contributed.
 
-   * Simple changes (including bug fixes) and obvious improvements are 
-     always welcome.  Changes that fundamentally change behavior need 
-     discussion on [email protected] before anything is 
+   * Simple changes (including bug fixes) and obvious improvements are
+     always welcome.  Changes that fundamentally change behavior need
+     discussion on [email protected] before anything is
      done.
 
    * Please add meaningful comments when you check changes in.  These
-     comments form the basis of the change-log.  
+     comments form the basis of the change-log.
 
    * Add unit tests to exercise new code, and regression tests
      whenever you fix a bug.
-

README.txt

@@ -1,10 +1,10 @@
-NumPy is the fundamental package needed for scientific computing with Python. 
+NumPy is the fundamental package needed for scientific computing with Python.
 This package contains:
 
     * a powerful N-dimensional array object
     * sophisticated (broadcasting) functions
     * tools for integrating C/C++ and Fortran code
-    * useful linear algebra, Fourier transform, and random number capabilities. 
+    * useful linear algebra, Fourier transform, and random number capabilities.
 
 It derives from the old Numeric code base and can be used as a replacement for Numeric. It also adds the features introduced by numarray and can be used to replace numarray.
 

doc/CAPI.rst.txt

@@ -15,7 +15,7 @@ of the API) that will need to be changed:
 
 * If you used any of the function pointers in the ``PyArray_Descr``
   structure you will have to modify your usage of those.  First,
-  the pointers are all under the member named ``f``.  So ``descr->cast`` 
+  the pointers are all under the member named ``f``.  So ``descr->cast``
   is now ``descr->f->cast``.  In addition, the
   casting functions have eliminated the strides argument (use
   ``PyArray_CastTo`` if you need strided casting). All functions have
@@ -238,7 +238,7 @@ segfaults may result.
 There are 6 (binary) flags that describe the memory area used by the
 data buffer.  These constants are defined in ``arrayobject.h`` and
 determine the bit-position of the flag.  Python exposes a nice attribute-
-based interface as well as a dictionary-like interface for getting 
+based interface as well as a dictionary-like interface for getting
 (and, if appropriate, setting) these flags.
 
 Memory areas of all kinds can be pointed to by an ndarray, necessitating
@@ -254,7 +254,7 @@ PyArray_FromAny function.
 ``NPY_FORTRAN``
     True if the array is (Fortran-style) contiguous in memory.
 
-Notice that contiguous 1-d arrays are always both ``NPY_FORTRAN`` contiguous 
+Notice that contiguous 1-d arrays are always both ``NPY_FORTRAN`` contiguous
 and C contiguous. Both of these flags can be checked and are convenience
 flags only as whether or not an array is ``NPY_CONTIGUOUS`` or ``NPY_FORTRAN``
 can be determined by the ``strides``, ``dimensions``, and ``itemsize``

doc/DISTUTILS.rst.txt

@@ -29,8 +29,8 @@ Requirements for SciPy packages
 
 SciPy consists of Python packages, called SciPy packages, that are
 available to Python users via the ``scipy`` namespace. Each SciPy package
-may contain other SciPy packages. And so on. Therefore, the SciPy 
-directory tree is a tree of packages with arbitrary depth and width. 
+may contain other SciPy packages. And so on. Therefore, the SciPy
+directory tree is a tree of packages with arbitrary depth and width.
 Any SciPy package may depend on NumPy packages but the dependence on other
 SciPy packages should be kept minimal or zero.
 
@@ -46,12 +46,12 @@ Their contents are described below.
 The ``setup.py`` file
 '''''''''''''''''''''
 
-In order to add a Python package to SciPy, its build script (``setup.py``) 
-must meet certain requirements. The most important requirement is that the 
-package define a ``configuration(parent_package='',top_path=None)`` function 
-which returns a dictionary suitable for passing to 
-``numpy.distutils.core.setup(..)``. To simplify the construction of 
-this dictionary, ``numpy.distutils.misc_util`` provides the 
+In order to add a Python package to SciPy, its build script (``setup.py``)
+must meet certain requirements. The most important requirement is that the
+package define a ``configuration(parent_package='',top_path=None)`` function
+which returns a dictionary suitable for passing to
+``numpy.distutils.core.setup(..)``. To simplify the construction of
+this dictionary, ``numpy.distutils.misc_util`` provides the
 ``Configuration`` class, described below.
 
 SciPy pure Python package example
@@ -72,13 +72,13 @@ Below is an example of a minimal ``setup.py`` file for a pure SciPy package::
 
 The arguments of the ``configuration`` function specifiy the name of
 parent SciPy package (``parent_package``) and the directory location
-of the main ``setup.py`` script (``top_path``).  These arguments, 
+of the main ``setup.py`` script (``top_path``).  These arguments,
 along with the name of the current package, should be passed to the
 ``Configuration`` constructor.
 
 The ``Configuration`` constructor has a fourth optional argument,
 ``package_path``, that can be used when package files are located in
-a different location than the directory of the ``setup.py`` file. 
+a different location than the directory of the ``setup.py`` file.
 
 Remaining ``Configuration`` arguments are all keyword arguments that will
 be used to initialize attributes of ``Configuration``
@@ -159,12 +159,12 @@ in writing setup scripts:
         sun.dat
       bar/
         car.dat
-      can.dat 
+      can.dat
 
   Path to data files can be a function taking no arguments and
   returning path(s) to data files -- this is a useful when data files
   are generated while building the package. (XXX: explain the step
-  when this function are called exactly) 
+  when this function are called exactly)
 
 + ``config.add_data_dir(data_path)`` --- add directory ``data_path``
   recursively to ``data_files``. The whole directory tree starting at
@@ -174,14 +174,14 @@ in writing setup scripts:
   directory and the second element specifies the path to data directory.
   By default, data directory are copied under package installation
   directory under the basename of ``data_path``. For example,
- 
+
   ::
 
     config.add_data_dir('fun')  # fun/ contains foo.dat bar/car.dat
     config.add_data_dir(('sun','fun'))
     config.add_data_dir(('gun','/full/path/to/fun'))
 
-  will install data files to the following locations 
+  will install data files to the following locations
 
   ::
 
@@ -204,7 +204,7 @@ in writing setup scripts:
   modules of the current package.
 
 + ``config.add_headers(*files)`` --- prepend ``files`` to ``headers``
-  list. By default, headers will be installed under 
+  list. By default, headers will be installed under
   ``<prefix>/include/pythonX.X/<config.name.replace('.','/')>/``
   directory. If ``files`` item is a tuple then it's first argument
   specifies the installation suffix relative to
@@ -216,7 +216,7 @@ in writing setup scripts:
   list. Scripts will be installed under ``<prefix>/bin/`` directory.
 
 + ``config.add_extension(name,sources,*kw)`` --- create and add an
-  ``Extension`` instance to ``ext_modules`` list. The first argument 
+  ``Extension`` instance to ``ext_modules`` list. The first argument
   ``name`` defines the name of the extension module that will be
   installed under ``config.name`` package. The second argument is
   a list of sources. ``add_extension`` method takes also keyword
@@ -269,10 +269,10 @@ in writing setup scripts:
   more information on arguments.
 
 + ``config.have_f77c()`` --- return True if Fortran 77 compiler is
-  available (read: a simple Fortran 77 code compiled succesfully). 
+  available (read: a simple Fortran 77 code compiled succesfully).
 
 + ``config.have_f90c()`` --- return True if Fortran 90 compiler is
-  available (read: a simple Fortran 90 code compiled succesfully). 
+  available (read: a simple Fortran 90 code compiled succesfully).
 
 + ``config.get_version()`` --- return version string of the current package,
   ``None`` if version information could not be detected. This methods
@@ -405,7 +405,7 @@ The header of a typical SciPy ``__init__.py`` is::
   """
   Package docstring, typically with a brief description and function listing.
   """
-  
+
   # py3k related imports
   from __future__ import division, print_function, absolute_import
 
@@ -414,7 +414,7 @@ The header of a typical SciPy ``__init__.py`` is::
   ...
 
   __all__ = [s for s in dir() if not s.startswith('_')]
-  
+
   from numpy.testing import Tester
   test = Tester().test
   bench = Tester().bench
@@ -441,7 +441,7 @@ will compile the ``library`` sources without optimization flags.
 It's recommended to specify only those config_fc options in such a way
 that are compiler independent.
 
-Getting extra Fortran 77 compiler options from source 
+Getting extra Fortran 77 compiler options from source
 -----------------------------------------------------
 
 Some old Fortran codes need special compiler options in order to
@@ -452,7 +452,7 @@ pattern::
   CF77FLAGS(<fcompiler type>) = <fcompiler f77flags>
 
 in the first 20 lines of the source and use the ``f77flags`` for
-specified type of the fcompiler (the first character ``C`` is optional). 
+specified type of the fcompiler (the first character ``C`` is optional).
 
 TODO: This feature can be easily extended for Fortran 90 codes as
 well. Let us know if you would need such a feature.

doc/HOWTO_DOCUMENT.rst.txt

@@ -142,15 +142,15 @@ The sections of the docstring are:
 2. **Deprecation warning**
 
    A section (use if applicable) to warn users that the object is deprecated.
-   Section contents should include: 
+   Section contents should include:
 
    * In what Numpy version the object was deprecated, and when it will be
      removed.
 
    * Reason for deprecation if this is useful information (e.g., object
      is superseded, duplicates functionality found elsewhere, etc.).
 
-   * New recommended way of obtaining the same functionality. 
+   * New recommended way of obtaining the same functionality.
 
    This section should use the note Sphinx directive instead of an
    underlined section header.
@@ -182,7 +182,7 @@ The sections of the docstring are:
      x : type
          Description of parameter `x`.
 
-   Enclose variables in single backticks.  The colon must be preceded 
+   Enclose variables in single backticks.  The colon must be preceded
    by a space, or omitted if the type is absent.
 
    For the parameter types, be as precise as possible.  Below are a
@@ -195,7 +195,7 @@ The sections of the docstring are:
      filename : str
      copy : bool
      dtype : data-type
-     iterable : iterable object     
+     iterable : iterable object
      shape : int or tuple of int
      files : list of str
 
@@ -370,7 +370,7 @@ The sections of the docstring are:
    Referencing sources of a temporary nature, like web pages, is
    discouraged.  References are meant to augment the docstring, but
    should not be required to understand it.  References are numbered, starting
-   from one, in the order in which they are cited.  
+   from one, in the order in which they are cited.
 
 11. **Examples**
 
@@ -397,7 +397,7 @@ The sections of the docstring are:
 
      >>> import numpy.random
      >>> np.random.rand(2)
-     array([ 0.35773152,  0.38568979])  #random     
+     array([ 0.35773152,  0.38568979])  #random
 
    You can run examples as doctests using::
 
@@ -427,7 +427,7 @@ The sections of the docstring are:
    *matplotlib* for plotting, but should import it explicitly, e.g.,
    ``import matplotlib.pyplot as plt``.
 
-   
+
 Documenting classes
 -------------------
 
@@ -498,7 +498,7 @@ Document these as you would any other function.  Do not include
 ``self`` in the list of parameters.  If a method has an equivalent function
 (which is the case for many ndarray methods for example), the function
 docstring should contain the detailed documentation, and the method docstring
-should refer to it.  Only put brief summary and **See Also** sections in the 
+should refer to it.  Only put brief summary and **See Also** sections in the
 method docstring.
 
 
@@ -514,7 +514,7 @@ instances a useful docstring, we do the following:
 * Multiple instances: If multiple instances are exposed, docstrings
   for each instance are written and assigned to the instances'
   ``__doc__`` attributes at run time. The class is documented as usual, and
-  the exposed instances can be mentioned in the **Notes** and **See Also** 
+  the exposed instances can be mentioned in the **Notes** and **See Also**
   sections.
 
 
@@ -553,16 +553,16 @@ hard to get a good overview of all functionality provided by looking at the
 source file(s) or the ``__all__`` dict.
 
 Note that license and author info, while often included in source files, do not
-belong in docstrings. 
+belong in docstrings.
 
 
 Other points to keep in mind
 ----------------------------
-* Equations : as discussed in the **Notes** section above, LaTeX formatting 
-  should be kept to a minimum.  Often it's possible to show equations as 
-  Python code or pseudo-code instead, which is much more readable in a 
-  terminal.  For inline display use double backticks (like ``y = np.sin(x)``). 
-  For display with blank lines above and below, use a double colon and indent 
+* Equations : as discussed in the **Notes** section above, LaTeX formatting
+  should be kept to a minimum.  Often it's possible to show equations as
+  Python code or pseudo-code instead, which is much more readable in a
+  terminal.  For inline display use double backticks (like ``y = np.sin(x)``).
+  For display with blank lines above and below, use a double colon and indent
   the code, like::
 
     end of previous sentence::
@@ -597,7 +597,7 @@ output. New paragraphs are marked with a blank line.
 
 Use *italics*, **bold**, and ``monospace`` if needed in any explanations
 (but not for variable names and doctest code or multi-line code).
-Variable, module, function, and class names should be written between 
+Variable, module, function, and class names should be written between
 single back-ticks (```numpy```).
 
 A more extensive example of reST markup can be found in `this example

doc/Py3K.rst.txt

@@ -483,21 +483,21 @@ So what is done in ``PyArray_FromAny`` currently is that:
   3118 buffers, so that::
 
       array([some_3118_object])
-  
+
   will treat the object similarly as it would handle an `ndarray`.
 
   However, again, bytes (and unicode) have priority and will not be
   handled as buffer objects.
 
 This amounts to possible semantic changes:
 
-- ``array(buffer)`` will no longer create an object array 
+- ``array(buffer)`` will no longer create an object array
   ``array([buffer], dtype='O')``, but will instead expand to a view
   on the buffer.
 
 .. todo::
 
-   Take a second look at places that used PyBuffer_FromMemory and 
+   Take a second look at places that used PyBuffer_FromMemory and
    PyBuffer_FromReadWriteMemory -- what can be done with these?
 
 .. todo::
@@ -633,7 +633,7 @@ Currently, the following is done:
 
 1) Numpy's integer types no longer inherit from Python integer.
 2) int is taken dtype-equivalent to NPY_LONG
-3) ints are converted to NPY_LONG 
+3) ints are converted to NPY_LONG
 
 PyInt methods are currently replaced by PyLong, via macros in npy_3kcompat.h.
 

doc/TESTS.rst.txt

@@ -206,7 +206,7 @@ but ``test_evens`` is a generator that returns a series of tests, using
 A problem with generator tests can be that if a test is failing, it's
 hard to see for which parameters.  To avoid this problem, ensure that:
 
-  - No computation related to the features tested is done in the 
+  - No computation related to the features tested is done in the
     ``test_*`` generator function, but delegated to a corresponding
     ``check_*`` function (can be inside the generator, to share namespace).
   - The generators are used *solely* for loops over parameters.
@@ -236,7 +236,7 @@ for numpy.lib::
 The doctests are run as if they are in a fresh Python instance which
 has executed ``import numpy as np``. Tests that are part of a SciPy
 subpackage will have that subpackage already imported. E.g. for a test
-in ``scipy/linalg/tests/``, the namespace will be created such that 
+in ``scipy/linalg/tests/``, the namespace will be created such that
 ``from scipy import linalg`` has already executed.
 
 

doc/cython/README.txt

@@ -17,4 +17,4 @@ To run it locally, simply type::
   make help
 
 which shows you the currently available targets (these are just handy
-shorthands for common commands).
+shorthands for common commands).