[Python-modules-commits] [python-numpy] 02/13: Import python-numpy_1.12.0~b1.orig.tar.gz
Sandro Tosi
morph at moszumanska.debian.org
Sun Dec 18 03:18:44 UTC 2016
This is an automated email from the git hooks/post-receive script.
morph pushed a commit to branch master
in repository python-numpy.
commit d18a9b1d0f2516b44ca02d1415f369f9e40adf61
Author: Sandro Tosi <morph at debian.org>
Date: Sat Dec 17 20:38:50 2016 -0500
Import python-numpy_1.12.0~b1.orig.tar.gz
---
INSTALL.rst.txt | 28 +-
PKG-INFO | 13 +-
doc/f2py/index.html | 2 +-
doc/release/1.11.0-notes.rst | 5 +-
doc/release/1.12.0-notes.rst | 1017 +
doc/source/_static/.gitignore | 2 +
doc/source/_templates/indexcontent.html | 20 +-
doc/source/about.rst | 8 +-
doc/source/bugs.rst | 2 +-
doc/source/conf.py | 10 +-
doc/source/contents.rst | 2 +-
doc/source/dev/development_environment.rst | 28 +-
doc/source/dev/gitwash/development_setup.rst | 42 +-
doc/source/dev/gitwash/development_workflow.rst | 163 +-
doc/source/dev/index.rst | 2 +-
doc/source/f2py/distutils.rst | 2 +-
doc/source/f2py/getting-started.rst | 4 +-
doc/source/f2py/python-usage.rst | 12 +-
doc/source/f2py/signature-file.rst | 6 +-
doc/source/license.rst | 2 +-
doc/source/neps/index.rst | 6 +-
doc/source/reference/arrays.classes.rst | 6 +-
doc/source/reference/arrays.datetime.rst | 6 +-
doc/source/reference/arrays.dtypes.rst | 6 +-
doc/source/reference/arrays.indexing.rst | 4 +-
doc/source/reference/arrays.interface.rst | 2 +-
doc/source/reference/arrays.ndarray.rst | 12 +-
doc/source/reference/arrays.rst | 2 +-
doc/source/reference/arrays.scalars.rst | 4 +-
doc/source/reference/c-api.array.rst | 21 +-
doc/source/reference/c-api.config.rst | 8 +-
doc/source/reference/c-api.coremath.rst | 4 +-
doc/source/reference/c-api.generalized-ufuncs.rst | 6 +-
doc/source/reference/c-api.iterator.rst | 2 +-
doc/source/reference/c-api.rst | 2 +-
.../reference/c-api.types-and-structures.rst | 91 +-
doc/source/reference/distutils.rst | 2 +-
doc/source/reference/index.rst | 8 +-
.../reference/internals.code-explanations.rst | 2 +-
doc/source/reference/internals.rst | 2 +-
doc/source/reference/routines.array-creation.rst | 1 +
.../reference/routines.array-manipulation.rst | 1 +
doc/source/reference/routines.help.rst | 2 +-
doc/source/reference/routines.io.rst | 2 +-
doc/source/reference/routines.math.rst | 4 +
doc/source/reference/routines.numarray.rst | 2 +-
doc/source/reference/routines.oldnumeric.rst | 2 +-
doc/source/reference/routines.other.rst | 2 +-
.../reference/routines.polynomials.classes.rst | 2 +-
.../reference/routines.polynomials.polynomial.rst | 1 +
doc/source/reference/swig.interface-file.rst | 6 +-
doc/source/reference/swig.rst | 2 +-
doc/source/reference/ufuncs.rst | 11 +-
doc/source/release.rst | 1 +
doc/source/user/basics.io.genfromtxt.rst | 54 +-
doc/source/user/basics.io.rst | 2 +-
doc/source/user/basics.rst | 2 +-
doc/source/user/building.rst | 8 +-
doc/source/user/c-info.python-as-glue.rst | 37 +-
doc/source/user/c-info.rst | 2 +-
doc/source/user/c-info.ufunc-tutorial.rst | 38 +-
doc/source/user/numpy-for-matlab-users.rst | 40 +-
doc/source/user/quickstart.rst | 119 +-
doc/sphinxext/.travis.yml | 11 +-
doc/sphinxext/MANIFEST.in | 6 +
doc/sphinxext/README.rst | 8 +
doc/sphinxext/numpydoc/docscrape.py | 160 +-
doc/sphinxext/numpydoc/docscrape_sphinx.py | 32 +-
doc/sphinxext/numpydoc/numpydoc.py | 57 +-
doc/sphinxext/numpydoc/tests/test_docscrape.py | 148 +-
doc/sphinxext/numpydoc/traitsdoc.py | 3 +-
doc/sphinxext/setup.py | 17 +-
numpy/__init__.py | 7 +-
numpy/_build_utils/README | 2 +-
numpy/_build_utils/src/apple_sgemv_fix.c | 2 +-
numpy/_distributor_init.py | 10 +
numpy/_import_tools.py | 2 +-
numpy/add_newdocs.py | 177 +-
numpy/compat/_inspect.py | 2 +-
numpy/compat/py3k.py | 14 +-
numpy/core/__init__.py | 16 +-
numpy/core/_internal.py | 6 +-
numpy/core/_methods.py | 21 +-
numpy/core/arrayprint.py | 158 +-
numpy/core/code_generators/cversions.txt | 3 +-
numpy/core/code_generators/generate_numpy_api.py | 2 +-
numpy/core/code_generators/generate_ufunc_api.py | 2 +-
numpy/core/code_generators/generate_umath.py | 83 +-
numpy/core/code_generators/ufunc_docstrings.py | 76 +-
numpy/core/defchararray.py | 14 +-
numpy/core/einsumfunc.py | 993 +
numpy/core/fromnumeric.py | 393 +-
numpy/core/function_base.py | 168 +-
numpy/core/getlimits.py | 17 +-
numpy/core/include/numpy/_numpyconfig.h.in | 1 +
numpy/core/include/numpy/ndarrayobject.h | 5 +-
numpy/core/include/numpy/ndarraytypes.h | 23 +-
numpy/core/include/numpy/noprefix.h | 2 +
numpy/core/include/numpy/npy_3kcompat.h | 8 +
numpy/core/include/numpy/npy_common.h | 34 +-
numpy/core/include/numpy/npy_endian.h | 7 +-
numpy/core/include/numpy/numpyconfig.h | 3 +-
numpy/core/include/numpy/oldnumeric.h | 2 +
numpy/core/include/numpy/ufuncobject.h | 12 +-
numpy/core/info.py | 2 +-
numpy/core/memmap.py | 45 +-
numpy/core/numeric.py | 425 +-
numpy/core/numerictypes.py | 2 +-
numpy/core/records.py | 2 +-
numpy/core/setup.py | 30 +-
numpy/core/setup_common.py | 17 +-
numpy/core/shape_base.py | 16 +-
numpy/core/src/multiarray/_datetime.h | 2 +-
numpy/core/src/multiarray/alloc.c | 2 +-
numpy/core/src/multiarray/array_assign_array.c | 4 +-
numpy/core/src/multiarray/arrayobject.c | 60 +-
numpy/core/src/multiarray/arraytypes.c.src | 46 +-
numpy/core/src/multiarray/buffer.c | 2 +-
numpy/core/src/multiarray/calculation.c | 22 +-
numpy/core/src/multiarray/common.c | 1 +
numpy/core/src/multiarray/compiled_base.c | 444 +-
numpy/core/src/multiarray/compiled_base.h | 2 +
numpy/core/src/multiarray/conversion_utils.c | 116 +-
numpy/core/src/multiarray/convert.c | 23 +-
numpy/core/src/multiarray/ctors.c | 106 +-
numpy/core/src/multiarray/ctors.h | 6 +
numpy/core/src/multiarray/datetime_busdaycal.c | 2 +-
numpy/core/src/multiarray/datetime_busdaycal.h | 2 +-
numpy/core/src/multiarray/datetime_strings.c | 6 +-
numpy/core/src/multiarray/descriptor.c | 57 +-
numpy/core/src/multiarray/dtype_transfer.c | 117 +-
numpy/core/src/multiarray/einsum.c.src | 2 +-
numpy/core/src/multiarray/getset.c | 12 +-
numpy/core/src/multiarray/item_selection.c | 42 +-
numpy/core/src/multiarray/iterators.c | 157 +-
numpy/core/src/multiarray/iterators.h | 5 -
.../src/multiarray/lowlevel_strided_loops.c.src | 2 +-
numpy/core/src/multiarray/mapping.c | 158 +-
numpy/core/src/multiarray/methods.c | 156 +-
numpy/core/src/multiarray/multiarraymodule.c | 35 +-
numpy/core/src/multiarray/nditer_api.c | 4 +-
numpy/core/src/multiarray/nditer_constr.c | 2 +-
numpy/core/src/multiarray/nditer_pywrap.c | 22 +-
numpy/core/src/multiarray/nditer_templ.c.src | 2 +-
numpy/core/src/multiarray/number.c | 21 +-
numpy/core/src/multiarray/numpyos.c | 2 +-
numpy/core/src/multiarray/numpyos.h | 2 +-
numpy/core/src/multiarray/scalarapi.c | 2 +-
numpy/core/src/multiarray/scalartypes.c.src | 68 +-
numpy/core/src/multiarray/shape.c | 111 +-
numpy/core/src/multiarray/usertypes.c | 2 +-
numpy/core/src/npymath/npy_math.c.src | 4 +-
numpy/core/src/npysort/quicksort.c.src | 101 +-
numpy/core/src/npysort/selection.c.src | 14 +-
numpy/core/src/private/lowlevel_strided_loops.h | 2 +-
numpy/core/src/private/npy_sort.h | 8 +
numpy/core/src/umath/funcs.inc.src | 2 +-
numpy/core/src/umath/loops.c.src | 191 +-
numpy/core/src/umath/loops.h.src | 32 +-
numpy/core/src/umath/reduction.c | 2 +-
numpy/core/src/umath/scalarmath.c.src | 96 +-
numpy/core/src/umath/simd.inc.src | 164 +-
numpy/core/src/umath/struct_ufunc_test.c.src | 2 +-
numpy/core/src/umath/test_rational.c.src | 2 +-
numpy/core/src/umath/ufunc_object.c | 148 +-
numpy/core/src/umath/ufunc_type_resolution.c | 36 +
numpy/core/src/umath/ufunc_type_resolution.h | 122 +-
numpy/core/tests/test_api.py | 25 +-
numpy/core/tests/test_arrayprint.py | 39 +
numpy/core/tests/test_datetime.py | 72 +-
numpy/core/tests/test_deprecations.py | 382 +-
numpy/core/tests/test_dtype.py | 25 +
numpy/core/tests/test_einsum.py | 871 +-
numpy/core/tests/test_function_base.py | 208 +-
numpy/core/tests/test_getlimits.py | 18 +-
numpy/core/tests/test_indexing.py | 284 +-
numpy/core/tests/test_item_selection.py | 8 +-
numpy/core/tests/test_machar.py | 2 +-
numpy/core/tests/test_mem_overlap.py | 6 +
numpy/core/tests/test_memmap.py | 67 +-
numpy/core/tests/test_multiarray.py | 333 +-
numpy/core/tests/test_nditer.py | 76 +-
numpy/core/tests/test_numeric.py | 272 +-
numpy/core/tests/test_records.py | 52 +-
numpy/core/tests/test_regression.py | 228 +-
numpy/core/tests/test_scalarmath.py | 121 +-
numpy/core/tests/test_shape_base.py | 9 +
numpy/core/tests/test_ufunc.py | 19 +
numpy/core/tests/test_umath.py | 152 +-
numpy/core/tests/test_unicode.py | 52 +-
numpy/ctypeslib.py | 8 +-
numpy/distutils/command/build_src.py | 2 +-
numpy/distutils/command/config.py | 4 +-
numpy/distutils/command/egg_info.py | 2 +-
numpy/distutils/conv_template.py | 6 +-
numpy/distutils/core.py | 15 +-
numpy/distutils/cpuinfo.py | 10 +-
numpy/distutils/exec_command.py | 18 +-
numpy/distutils/extension.py | 2 +-
numpy/distutils/fcompiler/__init__.py | 8 +-
numpy/distutils/fcompiler/gnu.py | 16 +-
numpy/distutils/from_template.py | 2 +-
numpy/distutils/mingw32ccompiler.py | 2 +-
numpy/distutils/misc_util.py | 21 +-
numpy/distutils/msvc9compiler.py | 2 +
numpy/distutils/system_info.py | 208 +-
numpy/distutils/tests/test_system_info.py | 5 +-
numpy/doc/basics.py | 10 +-
numpy/doc/byteswapping.py | 4 +-
numpy/doc/constants.py | 12 +-
numpy/doc/creation.py | 6 +-
numpy/doc/glossary.py | 4 +-
numpy/doc/indexing.py | 10 +-
numpy/doc/internals.py | 10 +-
numpy/doc/structured_arrays.py | 4 +-
numpy/doc/subclassing.py | 53 +-
numpy/doc/ufuncs.py | 2 +-
numpy/dual.py | 2 +-
numpy/f2py/capi_maps.py | 2 +-
numpy/f2py/crackfortran.py | 2 +-
numpy/f2py/rules.py | 6 +-
numpy/fft/fftpack.py | 107 +-
numpy/fft/helper.py | 99 +
numpy/fft/tests/test_helper.py | 79 +
numpy/lib/_datasource.py | 4 +-
numpy/lib/_version.py | 6 +-
numpy/lib/arraypad.py | 35 +-
numpy/lib/arraysetops.py | 44 +-
numpy/lib/financial.py | 11 +-
numpy/lib/format.py | 35 +-
numpy/lib/function_base.py | 650 +-
numpy/lib/info.py | 6 +-
numpy/lib/nanfunctions.py | 254 +-
numpy/lib/npyio.py | 121 +-
numpy/lib/polynomial.py | 19 +-
numpy/lib/shape_base.py | 16 +-
numpy/lib/stride_tricks.py | 69 +-
numpy/lib/tests/test_arraypad.py | 18 +
numpy/lib/tests/test_arraysetops.py | 8 +
numpy/lib/tests/test_financial.py | 7 +-
numpy/lib/tests/test_format.py | 22 +
numpy/lib/tests/test_function_base.py | 463 +-
numpy/lib/tests/test_index_tricks.py | 27 +
numpy/lib/tests/test_io.py | 175 +-
numpy/lib/tests/test_nanfunctions.py | 189 +-
numpy/lib/tests/test_polynomial.py | 32 +-
numpy/lib/tests/test_shape_base.py | 60 +-
numpy/lib/tests/test_stride_tricks.py | 17 +
numpy/lib/tests/test_twodim_base.py | 41 +-
numpy/lib/tests/test_type_check.py | 35 +
numpy/lib/tests/test_utils.py | 7 +-
numpy/lib/twodim_base.py | 117 +-
numpy/lib/type_check.py | 18 +-
numpy/lib/ufunclike.py | 4 +-
numpy/lib/utils.py | 16 +-
numpy/linalg/lapack_lite/dlapack_lite.c | 6 +-
numpy/linalg/lapack_lite/zlapack_lite.c | 4 +-
numpy/linalg/linalg.py | 80 +-
numpy/linalg/tests/test_linalg.py | 10 +-
numpy/linalg/tests/test_regression.py | 8 +-
numpy/ma/core.py | 219 +-
numpy/ma/extras.py | 144 +-
numpy/ma/mrecords.py | 10 +-
numpy/ma/tests/test_core.py | 236 +-
numpy/ma/tests/test_extras.py | 105 +-
numpy/ma/tests/test_mrecords.py | 10 +-
numpy/ma/tests/test_old_ma.py | 122 +-
numpy/ma/tests/test_regression.py | 8 +-
numpy/ma/tests/test_subclassing.py | 2 +-
numpy/ma/testutils.py | 8 +-
numpy/matrixlib/defmatrix.py | 2 +-
numpy/polynomial/_polybase.py | 6 +-
numpy/polynomial/chebyshev.py | 4 +-
numpy/polynomial/hermite.py | 4 +-
numpy/polynomial/hermite_e.py | 6 +-
numpy/polynomial/laguerre.py | 4 +-
numpy/polynomial/legendre.py | 4 +-
numpy/polynomial/polynomial.py | 97 +-
numpy/polynomial/polyutils.py | 4 +-
numpy/polynomial/tests/test_chebyshev.py | 2 +-
numpy/polynomial/tests/test_hermite.py | 2 +-
numpy/polynomial/tests/test_hermite_e.py | 2 +-
numpy/polynomial/tests/test_laguerre.py | 2 +-
numpy/polynomial/tests/test_legendre.py | 2 +-
numpy/polynomial/tests/test_polynomial.py | 66 +-
numpy/random/mtrand/Python.pxi | 14 -
numpy/random/mtrand/distributions.c | 5 +
numpy/random/mtrand/mt_compat.h | 68 -
numpy/random/mtrand/mtrand.c | 31649 ++++++++++---------
numpy/random/mtrand/mtrand.pyx | 1503 +-
numpy/random/mtrand/numpy.pxd | 6 -
numpy/random/mtrand/randint_helpers.pxi | 462 +
numpy/random/setup.py | 9 +-
numpy/random/tests/test_random.py | 847 +-
numpy/testing/decorators.py | 13 +-
numpy/testing/nosetester.py | 79 +-
numpy/testing/tests/test_decorators.py | 14 +-
numpy/testing/tests/test_utils.py | 277 +-
numpy/testing/utils.py | 563 +-
numpy/tests/test_ctypeslib.py | 14 +-
numpy/tests/test_scripts.py | 14 +-
numpy/tests/test_warnings.py | 86 +
numpy/version.py | 8 +-
setup.py | 33 +-
site.cfg.example | 23 +-
tools/swig/numpy.i | 7 +-
306 files changed, 30503 insertions(+), 20866 deletions(-)
diff --git a/INSTALL.rst.txt b/INSTALL.rst.txt
index 0b778d9..8b135e3 100644
--- a/INSTALL.rst.txt
+++ b/INSTALL.rst.txt
@@ -1,8 +1,8 @@
Building and installing NumPy
+++++++++++++++++++++++++++++
-**IMPORTANT**: the below notes are about building Numpy, which for most users
-is *not* the recommended way to install Numpy. Instead, use either a complete
+**IMPORTANT**: the below notes are about building NumPy, which for most users
+is *not* the recommended way to install NumPy. Instead, use either a complete
scientific Python distribution (recommended) or a binary installer - see
http://scipy.org/install.html.
@@ -14,8 +14,8 @@ Prerequisites
Building NumPy requires the following software installed:
-1) For Python 2, Python__ 2.6.x or newer.
- For Python 3, Python__ 3.2.x or newer.
+1) For Python 2, Python__ 2.7.x or newer.
+ For Python 3, Python__ 3.4.x or newer.
On Debian and derivative (Ubuntu): python python-dev
@@ -34,18 +34,18 @@ Building NumPy requires the following software installed:
This is required for testing numpy, but not for using it.
Python__ http://www.python.org
-nose__ http://somethingaboutorange.com/mrl/projects/nose/
+nose__ http://nose.readthedocs.io
.. note::
- If you want to build Numpy in order to work on Numpy itself, use
+ If you want to build NumPy in order to work on NumPy itself, use
``runtests.py``. For more details, see
http://docs.scipy.org/doc/numpy-dev/dev/development_environment.html
.. note::
- More extensive information on building Numpy (and Scipy) is maintained at
+ More extensive information on building NumPy (and Scipy) is maintained at
http://scipy.org/scipylib/building/index.html
@@ -68,8 +68,8 @@ NPY_NUM_BUILD_JOBS.
Choosing compilers
==================
-Numpy needs a C compiler, and for development versions also Cython. A Fortran
-compiler isn't needed to build Numpy itself; the ``numpy.f2py`` tests will be
+NumPy needs a C compiler, and for development versions also Cython. A Fortran
+compiler isn't needed to build NumPy itself; the ``numpy.f2py`` tests will be
skipped when running the test suite if no Fortran compiler is available. For
building Scipy a Fortran compiler is needed though, so we include some details
on Fortran compilers in the rest of this section.
@@ -91,7 +91,7 @@ good `application note <https://software.intel.com/en-us/articles/numpyscipy-wit
on this.
If you want to use a free compiler toolchain, the recommended compiler is MingwPy__.
-The older MinGW32 compiler set used to produce older .exe installers for Numpy
+The older MinGW32 compiler set used to produce older .exe installers for NumPy
itself is still available at https://github.com/numpy/numpy-vendor, but not
recommended for use anymore.
@@ -103,7 +103,7 @@ Building with optimized BLAS support
Configuring which BLAS/LAPACK is used if you have multiple libraries installed,
or you have only one installed but in a non-standard location, is done via a
-``site.cfg`` file. See the ``site.cfg.example`` shipped with Numpy for more
+``site.cfg`` file. See the ``site.cfg.example`` shipped with NumPy for more
details.
Windows
@@ -117,7 +117,7 @@ For an overview of the state of BLAS/LAPACK libraries on Windows, see
OS X
----
-OS X ships the Accelerate framework, which Numpy can build against without any
+OS X ships the Accelerate framework, which NumPy can build against without any
manual configuration. Other BLAS/LAPACK implementations (OpenBLAS, Intel MKL,
ATLAS) will also work.
@@ -149,7 +149,7 @@ Or by preloading a specific BLAS library with::
Build issues
============
-If you run into build issues and need help, the Numpy
+If you run into build issues and need help, the NumPy
`mailing list <http://scipy.org/scipylib/mailing-lists.html>`_ is the best
-place to ask. If the issue is clearly a bug in Numpy, please file an issue (or
+place to ask. If the issue is clearly a bug in NumPy, please file an issue (or
even better, a pull request) at https://github.com/numpy/numpy.
diff --git a/PKG-INFO b/PKG-INFO
index 7947ab0..6dad0f2 100644
--- a/PKG-INFO
+++ b/PKG-INFO
@@ -1,6 +1,6 @@
Metadata-Version: 1.1
Name: numpy
-Version: 1.11.2
+Version: 1.12.0b1
Summary: NumPy: array processing for numbers, strings, records, and objects.
Home-page: http://www.numpy.org
Author: NumPy Developers
@@ -18,6 +18,13 @@ Description: NumPy is a general-purpose array-processing package designed to
There are also basic facilities for discrete fourier transform,
basic linear algebra and random number generation.
+ All numpy wheels distributed from pypi are BSD licensed.
+
+ Windows wheels are linked against the ATLAS BLAS / LAPACK library, restricted
+ to SSE2 instructions, so may not give optimal linear algebra performance for
+ your machine. See http://docs.scipy.org/doc/numpy/user/install.html for
+ alternatives.
+
Platform: Windows
Platform: Linux
@@ -31,13 +38,11 @@ Classifier: License :: OSI Approved
Classifier: Programming Language :: C
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
-Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
-Classifier: Programming Language :: Python :: 3.2
-Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
+Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
diff --git a/doc/f2py/index.html b/doc/f2py/index.html
index e162ed4..9f3720e 100644
--- a/doc/f2py/index.html
+++ b/doc/f2py/index.html
@@ -2,7 +2,7 @@
<HTML>
<HEAD>
<META name="Author" content="Pearu Peterson">
-<!-- You may add here some keywords (comma separeted list) -->
+<!-- You may add here some keywords (comma separated list) -->
<META name="Keywords" content="fortran,python,interface,f2py,f2py2e,wrapper,fpig">
<TITLE>F2PY - Fortran to Python Interface Generator</TITLE>
<LINK rel="stylesheet" type="text/css" href="/styles/userstyle.css">
diff --git a/doc/release/1.11.0-notes.rst b/doc/release/1.11.0-notes.rst
index dad5260..02222a5 100644
--- a/doc/release/1.11.0-notes.rst
+++ b/doc/release/1.11.0-notes.rst
@@ -175,9 +175,8 @@ New Features
* ``np.histogram`` now provides plugin estimators for automatically
estimating the optimal number of bins. Passing one of ['auto', 'fd',
- 'scott', 'rice', 'sturges', 'doane', 'sqrt'] as the argument to
- 'bins' results in the corresponding estimator being used. These
- estimators work correctly with the `range` parameter.
+ 'scott', 'rice', 'sturges'] as the argument to 'bins' results in the
+ corresponding estimator being used.
* A benchmark suite using `Airspeed Velocity
<http://spacetelescope.github.io/asv/>`__ has been added, converting the
diff --git a/doc/release/1.12.0-notes.rst b/doc/release/1.12.0-notes.rst
new file mode 100644
index 0000000..8595a9a
--- /dev/null
+++ b/doc/release/1.12.0-notes.rst
@@ -0,0 +1,1017 @@
+NumPy 1.12.0 Release Notes
+**************************
+
+This release supports Python 2.7 and 3.4 - 3.6.
+
+Highlights
+==========
+
+* Order of operations in ``np.einsum`` now can be optimized for large speed improvements.
+* New ``signature`` argument to ``np.vectorize`` for vectorizing with core dimensions.
+* The ``keepdims`` argument was added to many functions.
+
+Dropped Support
+===============
+
+* Support for Python 2.6, 3.2, and 3.3 has been dropped.
+
+
+Added Support
+=============
+
+* Support for PyPy 2.7 v5.6.0 has been added. While not complete (nditer
+ ``updateifcopy`` is not supported yet), this is a milestone for PyPy's
+ C-API compatibility layer.
+
+
+Build System Changes
+====================
+
+* Library order is preserved, instead of being reordered to match that of
+ the directories.
+
+
+Deprecations
+============
+
+Assignment of ndarray object's ``data`` attribute
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Assigning the 'data' attribute is an inherently unsafe operation as pointed
+out in gh-7083. Such a capability will be removed in the future.
+
+Unsafe int casting of the num attribute in ``linspace``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+``np.linspace`` now raises DeprecationWarning when num cannot be safely
+interpreted as an integer.
+
+Insufficient bit width parameter to ``binary_repr``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+If a 'width' parameter is passed into ``binary_repr`` that is insufficient to
+represent the number in base 2 (positive) or 2's complement (negative) form,
+the function used to silently ignore the parameter and return a representation
+using the minimal number of bits needed for the form in question. Such behavior
+is now considered unsafe from a user perspective and will raise an error in the
+future.
+
+
+Future Changes
+==============
+
+* In 1.13 NAT will always compare False except for ``NAT != NAT``,
+ which will be True. In short, NAT will behave like NaN
+* In 1.13 np.average will preserve subclasses, to match the behavior of most
+ other numpy functions such as np.mean. In particular, this means calls which
+ returned a scalar may return a 0-d subclass object instead.
+
+Multiple-field manipulation of structured arrays
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+In 1.13 the behavior of structured arrays involving multiple fields will change
+in two ways:
+
+First, indexing a structured array with multiple fields (eg,
+``arr[['f1', 'f3']]``) will return a view into the original array in 1.13,
+instead of a copy. Note the returned view will have extra padding bytes
+corresponding to intervening fields in the original array, unlike the copy in
+1.12, which will affect code such as ``arr[['f1', 'f3']].view(newdtype)``.
+
+Second, for numpy versions 1.6 to 1.12 assignment between structured arrays
+occurs "by field name": Fields in the destination array are set to the
+identically-named field in the source array or to 0 if the source does not have
+a field::
+
+ >>> a = np.array([(1,2),(3,4)], dtype=[('x', 'i4'), ('y', 'i4')])
+ >>> b = np.ones(2, dtype=[('z', 'i4'), ('y', 'i4'), ('x', 'i4')])
+ >>> b[:] = a
+ >>> b
+ array([(0, 2, 1), (0, 4, 3)],
+ dtype=[('z', '<i4'), ('y', '<i4'), ('x', '<i4')])
+
+In 1.13 assignment will instead occur "by position": The Nth field of the
+destination will be set to the Nth field of the source regardless of field
+name. The old behavior can be obtained by using indexing to reorder the fields
+before
+assignment, e.g., ``b[['x', 'y']] = a[['y', 'x']]``.
+
+
+Compatibility notes
+===================
+
+DeprecationWarning to error
+~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+* Indexing with floats raises ``IndexError``,
+ e.g., a[0, 0.0].
+* Indexing with non-integer array_like raises ``IndexError``,
+ e.g., ``a['1', '2']``
+* Indexing with multiple ellipsis raises ``IndexError``,
+ e.g., ``a[..., ...]``.
+* Non-integers used as index values raise ``TypeError``,
+ e.g., in ``reshape``, ``take``, and specifying reduce axis.
+
+FutureWarning to changed behavior
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+* ``np.full`` now returns an array of the fill-value's dtype if no dtype is
+ given, instead of defaulting to float.
+* np.average will emit a warning if the argument is a subclass of ndarray,
+ as the subclass will be preserved starting in 1.13. (see Future Changes)
+
+``power`` and ``**`` raise errors for integer to negative integer powers
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+The previous behavior depended on whether numpy scalar integers or numpy
+integer arrays were involved.
+
+For arrays
+
+* Zero to negative integer powers returned least integral value.
+* Both 1, -1 to negative integer powers returned correct values.
+* The remaining integers returned zero when raised to negative integer powers.
+
+For scalars
+
+* Zero to negative integer powers returned least integral value.
+* Both 1, -1 to negative integer powers returned correct values.
+* The remaining integers sometimes returned zero, sometimes the
+ correct float depending on the integer type combination.
+
+All of these cases now raise a ``ValueError`` except for those integer
+combinations whose common type is float, for instance uint64 and int8. It was
+felt that a simple rule was the best way to go rather than have special
+exceptions for the integer units. If you need negative powers, use an inexact
+type.
+
+Relaxed stride checking is the default
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+This will have some impact on code that assumed that ``F_CONTIGUOUS`` and
+``C_CONTIGUOUS`` were mutually exclusive and could be set to determine the
+default order for arrays that are now both.
+
+The ``np.percentile`` 'midpoint' interpolation method fixed for exact indices
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+The 'midpoint' interpolator now gives the same result as 'lower' and 'higher' when
+the two coincide. Previous behavior of 'lower' + 0.5 is fixed.
+
+``keepdims`` kwarg is passed through to user-class methods
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+numpy functions that take a ``keepdims`` kwarg now pass the value
+through to the corresponding methods on ndarray sub-classes. Previously the
+``keepdims`` keyword would be silently dropped. These functions now have
+the following behavior:
+
+1. If user does not provide ``keepdims``, no keyword is passed to the underlying
+ method.
+2. Any user-provided value of ``keepdims`` is passed through as a keyword
+ argument to the method.
+
+This will raise in the case where the method does not support a
+``keepdims`` kwarg and the user explicitly passes in ``keepdims``.
+
+The following functions are changed: ``sum``, ``product``,
+``sometrue``, ``alltrue``, ``any``, ``all``, ``amax``, ``amin``,
+``prod``, ``mean``, ``std``, ``var``, ``nanmin``, ``nanmax``,
+``nansum``, ``nanprod``, ``nanmean``, ``nanmedian``, ``nanvar``,
+``nanstd``
+
+``bitwise_and`` identity changed
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+The previous identity was 1, it is now -1. See entry in `Improvements`_ for
+more explanation.
+
+Greater consistancy in ``assert_almost_equal``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+The precision check for scalars has been changed to match that for arrays. It
+is now::
+
+ abs(actual - desired) < 1.5 * 10**(-decimal)
+
+Note that this is looser than previously documented, but agrees with the
+previous implementation used in ``assert_array_almost_equal``. Due to the
+change in implementation some very delicate tests may fail that did not
+fail before.
+
+``NoseTester`` behaviour of warnings during testing
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+When ``raise_warnings="develop"`` is given, all uncaught warnings will now
+be considered a test failure. Previously only selected ones were raised.
+Warnings which are not caught or raised (mostly when in release mode)
+will be shown once during the test cycle similar to the default python
+settings.
+
+``assert_warns`` and ``deprecated`` decorator more specific
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+The ``assert_warns`` function and context manager are now more specific
+to the given warning category. This increased specificity leads to them
+being handled according to the outer warning settings. This means that
+no warning may be raised in cases where a wrong category warning is given
+and ignored outside the context. Alternatively the increased specificity
+may mean that warnings that were incorrectly ignored will now be shown
+or raised. See also the new ``suppress_warnings`` context manager.
+The same is true for the ``deprecated`` decorator.
+
+C API
+~~~~~
+No changes.
+
+
+New Features
+============
+
+Writeable keyword argument for ``as_strided``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+``np.lib.stride_tricks.as_strided`` now has a ``writeable``
+keyword argument. It can be set to False when no write operation
+to the returned array is expected to avoid accidental
+unpredictable writes.
+
+``axes`` keyword argument for ``rot90``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+The ``axes`` keyword argument in ``rot90`` determines the plane in which the
+array is rotated. It defaults to ``axes=(0,1)`` as in the originial function.
+
+Generalized ``flip``
+~~~~~~~~~~~~~~~~~~~~
+``flipud`` and ``fliplr`` reverse the elements of an array along axis=0 and
+axis=1 respectively. The newly added ``flip`` function reverses the elements of
+an array along any given axis.
+
+* ``np.count_nonzero`` now has an ``axis`` parameter, allowing
+ non-zero counts to be generated on more than just a flattened
+ array object.
+
+BLIS support in ``numpy.distutils``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Building against the BLAS implementation provided by the BLIS library is now
+supported. See the ``[blis]`` section in ``site.cfg.example`` (in the root of
+the numpy repo or source distribution).
+
+Hook in ``numpy/__init__.py`` to run distribution-specific checks
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Binary distributions of numpy may need to run specific hardware checks or load
+specific libraries during numpy initialization. For example, if we are
+distributing numpy with a BLAS library that requires SSE2 instructions, we
+would like to check the machine on which numpy is running does have SSE2 in
+order to give an informative error.
+
+Add a hook in ``numpy/__init__.py`` to import a ``numpy/_distributor_init.py``
+file that will remain empty (bar a docstring) in the standard numpy source,
+but that can be overwritten by people making binary distributions of numpy.
+
+New nanfunctions ``nancumsum`` and ``nancumprod`` added
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Nan-functions ``nancumsum`` and ``nancumprod`` have been added to
+compute ``cumsum`` and ``cumprod`` by ignoring nans.
+
+``np.interp`` can now interpolate complex values
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+``np.lib.interp(x, xp, fp)`` now allows the interpolated array ``fp``
+to be complex and will interpolate at ``complex128`` precision.
+
+New polynomial evaluation function ``polyvalfromroots`` added
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+The new function ``polyvalfromroots`` evaluates a polynomial at given points
+from the roots of the polynomial. This is useful for higher order polynomials,
+where expansion into polynomial coefficients is inaccurate at machine
+precision.
+
+New array creation function ``geomspace`` added
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+The new function ``geomspace`` generates a geometric sequence. It is similar
+to ``logspace``, but with start and stop specified directly:
+``geomspace(start, stop)`` behaves the same as
+``logspace(log10(start), log10(stop))``.
+
+New context manager for testing warnings
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+A new context manager ``suppress_warnings`` has been added to the testing
+utils. This context manager is designed to help reliably test warnings.
+Specifically to reliably filter/ignore warnings. Ignoring warnings
+by using an "ignore" filter in Python versions before 3.4.x can quickly
+result in these (or similar) warnings not being tested reliably.
+
+The context manager allows to filter (as well as record) warnings similar
+to the ``catch_warnings`` context, but allows for easier specificity.
+Also printing warnings that have not been filtered or nesting the
+context manager will work as expected. Additionally, it is possible
+to use the context manager as a decorator which can be useful when
+multiple tests give need to hide the same warning.
+
+New masked array functions ``ma.convolve`` and ``ma.correlate`` added
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+These functions wrapped the non-masked versions, but propagate through masked
+values. There are two different propagation modes. The default causes masked
+values to contaminate the result with masks, but the other mode only outputs
+masks if there is no alternative.
+
+New ``float_power`` ufunc
+~~~~~~~~~~~~~~~~~~~~~~~~~
+The new ``float_power`` ufunc is like the ``power`` function except all
+computation is done in a minimum precision of float64. There was a long
+discussion on the numpy mailing list of how to treat integers to negative
+integer powers and a popular proposal was that the ``__pow__`` operator should
+always return results of at least float64 precision. The ``float_power``
+function implements that option. Note that it does not support object arrays.
+
+``np.loadtxt`` now supports a single integer as ``usecol`` argument
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Instead of using ``usecol=(n,)`` to read the nth column of a file
+it is now allowed to use ``usecol=n``. Also the error message is
+more user friendly when a non-integer is passed as a column index.
+
+Improved automated bin estimators for ``histogram``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Added 'doane' and 'sqrt' estimators to ``histogram`` via the ``bins``
+argument. Added support for range-restricted histograms with automated
+bin estimation.
+
+``np.roll`` can now roll multiple axes at the same time
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+The ``shift`` and ``axis`` arguments to ``roll`` are now broadcast against each
+other, and each specified axis is shifted accordingly.
+
+The ``__complex__`` method has been implemented for the ndarrays
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Calling ``complex()`` on a size 1 array will now cast to a python
+complex.
+
+``pathlib.Path`` objects now supported
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+The standard ``np.load``, ``np.save``, ``np.loadtxt``, ``np.savez``, and similar
+functions can now take ``pathlib.Path`` objects as an argument instead of a
+filename or open file object.
+
+New ``bits`` attribute for ``np.finfo``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+This makes ``np.finfo`` consistent with ``np.iinfo`` which already has that
+attribute.
+
+New ``signature`` argument to ``np.vectorize``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+This argument allows for vectorizing user defined functions with core
+dimensions, in the style of NumPy's
+:ref:`generalized universal functions<c-api.generalized-ufuncs>`. This allows
+for vectorizing a much broader class of functions. For example, an arbitrary
+distance metric that combines two vectors to produce a scalar could be
+vectorized with ``signature='(n),(n)->()'``. See ``np.vectorize`` for full
+details.
+
+Emit py3kwarnings for division of integer arrays
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+To help people migrate their code bases from Python 2 to Python 3, the
+python interpreter has a handy option -3, which issues warnings at runtime.
+One of its warnings is for integer division::
+
+ $ python -3 -c "2/3"
+
+ -c:1: DeprecationWarning: classic int division
+
+In Python 3, the new integer division semantics also apply to numpy arrays.
+With this version, numpy will emit a similar warning::
+
+ $ python -3 -c "import numpy as np; np.array(2)/np.array(3)"
+
+ -c:1: DeprecationWarning: numpy: classic int division
+
+numpy.sctypes now includes bytes on Python3 too
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Previously, it included str (bytes) and unicode on Python2, but only str
+(unicode) on Python3.
+
+
+Improvements
+============
+
+``bitwise_and`` identity changed
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+The previous identity was 1 with the result that all bits except the LSB were
+masked out when the reduce method was used. The new identity is -1, which
+should work properly on twos complement machines as all bits will be set to
+one.
+
+Generalized Ufuncs will now unlock the GIL
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Generalized Ufuncs, including most of the linalg module, will now unlock
+the Python global interpreter lock.
+
+Caches in `np.fft` are now bounded in total size and item count
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+The caches in `np.fft` that speed up successive FFTs of the same length can no
+longer grow without bounds. They have been replaced with LRU (least recently
+used) caches that automatically evict no longer needed items if either the
+memory size or item count limit has been reached.
+
+Improved handling of zero-width string/unicode dtypes
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Fixed several interfaces that explicitly disallowed arrays with zero-width
+string dtypes (i.e. ``dtype('S0')`` or ``dtype('U0')``, and fixed several
+bugs where such dtypes were not handled properly. In particular, changed
+``ndarray.__new__`` to not implicitly convert ``dtype('S0')`` to
+``dtype('S1')`` (and likewise for unicode) when creating new arrays.
+
+Integer ufuncs vectorized with AVX2
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+If the cpu supports it at runtime the basic integer ufuncs now use AVX2
+instructions. This feature is currently only available when compiled with GCC.
+
+Order of operations optimization in ``np.einsum``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+``np.einsum`` now supports the ``optimize`` argument which will optimize the
+order of contraction. For example, ``np.einsum`` would complete the chain dot
+example ``np.einsum(‘ij,jk,kl->il’, a, b, c)`` in a single pass which would
+scale like ``N^4``; however, when ``optimize=True`` ``np.einsum`` will create
+an intermediate array to reduce this scaling to ``N^3`` or effectively
+``np.dot(a, b).dot(c)``. Usage of intermediate tensors to reduce scaling has
+been applied to the general einsum summation notation. See ``np.einsum_path``
+for more details.
+
+quicksort has been changed to an introsort
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+The quicksort kind of ``np.sort`` and ``np.argsort`` is now an introsort which
+is regular quicksort but changing to a heapsort when not enough progress is
+made. This retains the good quicksort performance while changing the worst case
+runtime from ``O(N^2)`` to ``O(N*log(N))``.
+
+``ediff1d`` improved performance and subclass handling
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+The ediff1d function uses an array instead on a flat iterator for the
+subtraction. When to_begin or to_end is not None, the subtraction is performed
+in place to eliminate a copy operation. A side effect is that certain
+subclasses are handled better, namely astropy.Quantity, since the complete
+array is created, wrapped, and then begin and end values are set, instead of
+using concatenate.
+
+Improved precision of ``ndarray.mean`` for float16 arrays
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+The computation of the mean of float16 arrays is now carried out in float32 for
+improved precision. This should be useful in packages such as scikit-learn
+where the precision of float16 is adequate and its smaller footprint is
+desireable.
+
+
+Changes
+=======
+
+All array-like methods are now called with keyword arguments in fromnumeric.py
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Internally, many array-like methods in fromnumeric.py were being called with
+positional arguments instead of keyword arguments as their external signatures
+were doing. This caused a complication in the downstream 'pandas' library
+that encountered an issue with 'numpy' compatibility. Now, all array-like
+methods in this module are called with keyword arguments instead.
+
+Operations on np.memmap objects return numpy arrays in most cases
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Previously operations on a memmap object would misleadingly return a memmap
+instance even if the result was actually not memmapped. For example,
+``arr + 1`` or ``arr + arr`` would return memmap instances, although no memory
+from the output array is memmaped. Version 1.12 returns ordinary numpy arrays
+from these operations.
+
+Also, reduction of a memmap (e.g. ``.sum(axis=None``) now returns a numpy
+scalar instead of a 0d memmap.
+
+stacklevel of warnings increased
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+The stacklevel for python based warnings was increased so that most warnings
+will report the offending line of the user code instead of the line the
+warning itself is given. Passing of stacklevel is now tested to ensure that
+new warnings will receive the ``stacklevel`` argument.
+
+This causes warnings with the "default" or "module" filter to be shown once
+for every offending user code line or user module instead of only once. On
+python versions before 3.4, this can cause warnings to appear that were falsely
+ignored before, which may be surprising especially in test suits.
+
+
+Contributors to maintenance/1.12.x
+==================================
+
+A total of 133 people contributed to this release. People with a "+" by their
+names contributed a patch for the first time.
+
+- Aditya Panchal
+- Ales Erjavec +
+- Alex Griffing
+- Alistair Muldal
+- Allan Haldane
+- Amit Aronovitch +
+- Andrei Kucharavy +
+- Antony Lee
+- Antti Kaihola +
+- Arne de Laat +
+- Auke Wiggers +
+- AustereCuriosity +
+- Badhri Narayanan Krishnakumar +
+- Ben North +
+- Ben Rowland +
+- Bertrand Lefebvre
+- Boxiang Sun
+- CJ Carey
+- Charles Harris
+- Christoph Gohlke
+- Daniel Ching +
+- Daniel Rasmussen +
+- Daniel Smith +
+- David Schaich +
... 83040 lines suppressed ...
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