numpy · matthew-brett · Jun 8, 2014 · Jul 7, 2014 · Jul 16, 2014 · Jul 8, 2014
diff --git a/.gitattributes b/.gitattributes
@@ -1,2 +1,5 @@
 * text=auto
 tools/win32build/nsis_scripts/*.nsi.in eol=crlf
+
+# Numerical data files
+numpy/lib/tests/data/*.npy binary
diff --git a/.gitignore b/.gitignore
@@ -15,6 +15,12 @@
 *.tmp
 *.vim
 tags
+cscope.out
+# gnu global
+GPATH
+GRTAGS
+GSYMS
+GTAGS
 
 # Compiled source #
 ###################
@@ -123,7 +129,7 @@ numpy/core/src/private/npy_partition.h
 numpy/core/src/private/scalarmathmodule.h
 numpy/core/src/scalarmathmodule.c
 numpy/core/src/umath/funcs.inc
-numpy/core/src/umath/loops.c
+numpy/core/src/umath/loops.[ch]
 numpy/core/src/umath/operand_flag_tests.c
 numpy/core/src/umath/simd.inc
 numpy/core/src/umath/struct_ufunc_test.c

diff --git a/.travis.yml b/.travis.yml
@@ -13,7 +13,7 @@ matrix:
     - python: 3.2
       env: USE_DEBUG=1
     - python: 2.7
-      env: NPY_SEPARATE_COMPILATION=0
+      env: NPY_SEPARATE_COMPILATION=0 PYTHON_OO=1
     - python: 3.3
       env: NPY_SEPARATE_COMPILATION=0
     - python: 2.7
@@ -31,6 +31,10 @@ before_install:
   - ulimit -a
   - mkdir builds
   - pushd builds
+  # Build into own virtualenv
+  # We therefore control our own environment, avoid travis' numpy
+  - virtualenv --python=python venv
+  - source venv/bin/activate
   - pip install nose
   # pip install coverage
   - python -V

diff --git a/doc/HOWTO_DOCUMENT.rst.txt b/doc/HOWTO_DOCUMENT.rst.txt
@@ -30,14 +30,14 @@ A Guide to NumPy/SciPy Documentation
 
 Overview
 --------
-In general, we follow the standard Python style conventions as described here:
- * `Style Guide for C Code <http://www.python.org/peps/pep-0007.html>`_
- * `Style Guide for Python Code <http://www.python.org/peps/pep-0008.html>`_
- * `Docstring Conventions <http://www.python.org/peps/pep-0257.html>`_
+We mostly follow the standard Python style conventions as described here:
+ * `Style Guide for C Code <http://python.org/dev/peps/pep-0007/>`_
+ * `Style Guide for Python Code <http://python.org/dev/peps/pep-0008/>`_
+ * `Docstring Conventions <http://python.org/dev/peps/pep-0257/>`_
 
 Additional PEPs of interest regarding documentation of code:
- * `Docstring Processing Framework <http://www.python.org/peps/pep-0256.html>`_
- * `Docutils Design Specification <http://www.python.org/peps/pep-0258.html>`_
+ * `Docstring Processing Framework <http://python.org/dev/peps/pep-0256/>`_
+ * `Docutils Design Specification <http://python.org/dev/peps/pep-0258/>`_
 
 Use a code checker:
  * `pylint <http://www.logilab.org/857>`_

diff --git a/doc/release/1.8.2-notes.rst b/doc/release/1.8.2-notes.rst
@@ -0,0 +1,19 @@
+NumPy 1.8.2 Release Notes
+*************************
+
+This is a bugfix only release in the 1.8.x series.
+
+Issues fixed
+============
+
+* gh-4836: partition produces wrong results for multiple selections in equal ranges
+* gh-4656: Make fftpack._raw_fft threadsafe
+* gh-4628: incorrect argument order to _copyto in in np.nanmax, np.nanmin
+* gh-4642: Hold GIL for converting dtypes types with fields
+* gh-4733: fix np.linalg.svd(b, compute_uv=False)
+* gh-4853: avoid unaligned simd load on reductions on i386
+* gh-4722: Fix seg fault converting empty string to object
+* gh-4613: Fix lack of NULL check in array_richcompare
+* gh-4774: avoid unaligned access for strided byteswap
+* gh-650: Prevent division by zero when creating arrays from some buffers
+* gh-4602: ifort has issues with optimization flag O2, use O1
diff --git a/doc/release/1.9.0-notes.rst b/doc/release/1.9.0-notes.rst
@@ -6,8 +6,6 @@ This release supports Python 2.6 - 2.7 and 3.2 - 3.4.
 
 Highlights
 ==========
-* Addition of `__numpy_ufunc__` to allow overriding ufuncs in ndarray
-  subclasses.
 * Numerous performance improvements in various areas, most notably indexing and
   operations on small arrays are significantly faster.
   Indexing operations now also release the GIL.
@@ -35,6 +33,8 @@ Future Changes
 * String version checks will break because, e.g., '1.9' > '1.10' is True. A
   NumpyVersion class has been added that can be used for such comparisons.
 * The diagonal and diag functions will return writeable views in 1.10.0
+* The `S` and/or `a` dtypes may be changed to represent Python strings
+  instead of bytes, in Python 3 these two types are very different.
 
 
 Compatibility notes
@@ -176,6 +176,11 @@ introduced in advanced indexing operations:
 
 * Indexing with more then one ellipsis (``...``) is deprecated.
 
+Non-integer reduction axis indexes are deprecated
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Non-integer axis indexes to reduction ufuncs like `add.reduce` or `sum` are
+deprecated.
+
 ``promote_types`` and string dtype
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 ``promote_types`` function now returns a valid string length when given an
@@ -240,6 +245,11 @@ a problem cannot occur.
 
 This change was already applied to the 1.8.1 release.
 
+``zeros_like`` for string dtypes now returns empty strings
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+To match the `zeros` function `zeros_like` now returns an array initialized
+with empty strings instead of an array filled with `'0'`.
+
 
 New Features
 ============
@@ -257,13 +267,6 @@ ufunc reductions do since 1.7. One can now say axis=(index, index) to pick a
 list of axes for the reduction. The ``keepdims`` keyword argument was also
 added to allow convenient broadcasting to arrays of the original shape.
 
-Ufunc and Dot Overrides
-~~~~~~~~~~~~~~~~~~~~~~~
-For better compatibility with external objects you can now override
-universal functions (ufuncs), ``numpy.core._dotblas.dot``, and
-``numpy.core.multiarray.dot`` (the numpy.dot functions). By defining a
-``__numpy_ufunc__`` method.
-
 Dtype parameter added to ``np.linspace`` and ``np.logspace``
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 The returned data type from the ``linspace`` and ``logspace`` functions can

diff --git a/doc/release/1.9.1-notes.rst b/doc/release/1.9.1-notes.rst
@@ -0,0 +1,33 @@
+NumPy 1.9.1 Release Notes
+*************************
+
+This is a bugfix only release in the 1.9.x series.
+
+Issues fixed
+============
+
+* gh-5184: restore linear edge behaviour of gradient to as it was in < 1.9.
+  The second order behaviour is available via the `edge_order` keyword
+* gh-4007: workaround Accelerate sgemv crash on OSX 10.9
+* gh-5100: restore object dtype inference from iterable objects without `len()`
+* gh-5163: avoid gcc-4.1.2 (red hat 5) miscompilation causing a crash
+* gh-5138: fix nanmedian on arrays containing inf
+* gh-5240: fix not returning out array from ufuncs with subok=False set
+* gh-5203: copy inherited masks in MaskedArray.__array_finalize__
+* gh-2317: genfromtxt did not handle filling_values=0 correctly
+* gh-5067: restore api of npy_PyFile_DupClose in python2
+* gh-5063: cannot convert invalid sequence index to tuple
+* gh-5082: Segmentation fault with argmin() on unicode arrays
+* gh-5095: don't propagate subtypes from np.where
+* gh-5104: np.inner segfaults with SciPy's sparse matrices
+* gh-5251: Issue with fromarrays not using correct format for unicode arrays
+* gh-5136: Import dummy_threading if importing threading fails
+* gh-5148: Make numpy import when run with Python flag '-OO'
+* gh-5147: Einsum double contraction in particular order causes ValueError
+* gh-479: Make f2py work with intent(in out)
+* gh-5170: Make python2 .npy files readable in python3
+* gh-5027: Use 'll' as the default length specifier for long long
+* gh-4896: fix build error with MSVC 2013 caused by C99 complex support
+* gh-4465: Make PyArray_PutTo respect writeable flag
+* gh-5225: fix crash when using arange on datetime without dtype set
+* gh-5231: fix build in c99 mode
diff --git a/doc/release/1.9.2-notes.rst b/doc/release/1.9.2-notes.rst
@@ -0,0 +1,25 @@
+NumPy 1.9.2 Release Notes
+*************************
+
+This is a bugfix only release in the 1.9.x series.
+
+Issues fixed
+============
+
+* `#5316 <https://github.com/numpy/numpy/issues/5316>`__: fix too large dtype alignment of strings and complex types
+* `#5424 <https://github.com/numpy/numpy/issues/5424>`__: fix ma.median when used on ndarrays
+* `#5481 <https://github.com/numpy/numpy/issues/5481>`__: Fix astype for structured array fields of different byte order
+* `#5354 <https://github.com/numpy/numpy/issues/5354>`__: fix segfault when clipping complex arrays
+* `#5524 <https://github.com/numpy/numpy/issues/5524>`__: allow np.argpartition on non ndarrays
+* `#5612 <https://github.com/numpy/numpy/issues/5612>`__: Fixes ndarray.fill to accept full range of uint64
+* `#5155 <https://github.com/numpy/numpy/issues/5155>`__: Fix loadtxt with comments=None and a string None data
+* `#4476 <https://github.com/numpy/numpy/issues/4476>`__: Masked array view fails if structured dtype has datetime component
+* `#5388 <https://github.com/numpy/numpy/issues/5388>`__: Make RandomState.set_state and RandomState.get_state threadsafe
+* `#5390 <https://github.com/numpy/numpy/issues/5390>`__: make seed, randint and shuffle threadsafe
+* `#5374 <https://github.com/numpy/numpy/issues/5374>`__: Fixed incorrect assert_array_almost_equal_nulp documentation
+* `#5393 <https://github.com/numpy/numpy/issues/5393>`__: Add support for ATLAS > 3.9.33.
+* `#5313 <https://github.com/numpy/numpy/issues/5313>`__: PyArray_AsCArray caused segfault for 3d arrays
+* `#5492 <https://github.com/numpy/numpy/issues/5492>`__: handle out of memory in rfftf
+* `#4181 <https://github.com/numpy/numpy/issues/4181>`__: fix a few bugs in the random.pareto docstring
+* `#5359 <https://github.com/numpy/numpy/issues/5359>`__: minor changes to linspace docstring
+* `#4723 <https://github.com/numpy/numpy/issues/4723>`__: fix a compile issues on AIX
diff --git a/doc/release/1.9.3-notes.rst b/doc/release/1.9.3-notes.rst
@@ -0,0 +1,23 @@
+NumPy 1.9.3 Release Notes
+*************************
+
+This is a bugfix only release in the 1.9.x series.
+
+The only changes from 1.9.2 are a fix for reading gzipped text files on Python
+3.5 and some build fixes.
+
+Issues fixed
+============
+
+* `#5866 <https://github.com/numpy/numpy/pull/5866>`__: fix error finding
+  Python headers when ``build_ext`` ``--include-dirs`` is set;
+* `#6016 <https://github.com/numpy/numpy/pull/6016>`__: fix ``np.loadtxt``
+  error on Python 3.5 when reading from gzip files;
+* `#5555 <https://github.com/numpy/numpy/pull/5555>`__: Replace deprecated
+  options for ifort;
+* `#6096 <https://github.com/numpy/numpy/pull/6096>`__: remove /GL for VS2015
+  in check_long_double_representation;
+* `#6141 <https://github.com/numpy/numpy/pull/6141>`__: enable Visual Studio
+  2015 C99 features;
+* `#6171 <https://github.com/numpy/numpy/pull/6171>`__: revert C99 complex for
+  MSVC14.
diff --git a/doc/source/reference/arrays.classes.rst b/doc/source/reference/arrays.classes.rst
@@ -39,76 +39,6 @@ Special attributes and methods
 
 Numpy provides several hooks that classes can customize:
 
-.. function:: class.__numpy_ufunc__(self, ufunc, method, i, inputs, **kwargs)
-
-   .. versionadded:: 1.9
-
-   Any class (ndarray subclass or not) can define this method to
-   override behavior of Numpy's ufuncs. This works quite similarly to
-   Python's ``__mul__`` and other binary operation routines.
-
-   - *ufunc* is the ufunc object that was called. 
-   - *method* is a string indicating which Ufunc method was called
-     (one of ``"__call__"``, ``"reduce"``, ``"reduceat"``,
-     ``"accumulate"``, ``"outer"``, ``"inner"``). 
-   - *i* is the index of *self* in *inputs*.
-   - *inputs* is a tuple of the input arguments to the ``ufunc``
-   - *kwargs* is a dictionary containing the optional input arguments
-     of the ufunc. The ``out`` argument is always contained in
-     *kwargs*, if given. See the discussion in :ref:`ufuncs` for
-     details.
-
-   The method should return either the result of the operation, or
-   :obj:`NotImplemented` if the operation requested is not
-   implemented.
-
-   If one of the arguments has a :func:`__numpy_ufunc__` method, it is
-   executed *instead* of the ufunc.  If more than one of the input
-   arguments implements :func:`__numpy_ufunc__`, they are tried in the
-   order: subclasses before superclasses, otherwise left to right. The
-   first routine returning something else than :obj:`NotImplemented`
-   determines the result. If all of the :func:`__numpy_ufunc__`
-   operations return :obj:`NotImplemented`, a :exc:`TypeError` is
-   raised.
-
-   If an :class:`ndarray` subclass defines the :func:`__numpy_ufunc__`
-   method, this disables the :func:`__array_wrap__`,
-   :func:`__array_prepare__`, :data:`__array_priority__` mechanism
-   described below.
-
-   .. note:: In addition to ufuncs, :func:`__numpy_ufunc__` also
-      overrides the behavior of :func:`numpy.dot` even though it is
-      not an Ufunc.
-
-   .. note:: If you also define right-hand binary operator override
-      methods (such as ``__rmul__``) or comparison operations (such as
-      ``__gt__``) in your class, they take precedence over the
-      :func:`__numpy_ufunc__` mechanism when resolving results of
-      binary operations (such as ``ndarray_obj * your_obj``).
-
-      The technical special case is: ``ndarray.__mul__`` returns
-      ``NotImplemented`` if the other object is *not* a subclass of
-      :class:`ndarray`, and defines both ``__numpy_ufunc__`` and
-      ``__rmul__``. Similar exception applies for the other operations
-      than multiplication.
-
-      In such a case, when computing a binary operation such as
-      ``ndarray_obj * your_obj``, your ``__numpy_ufunc__`` method
-      *will not* be called.  Instead, the execution passes on to your
-      right-hand ``__rmul__`` operation, as per standard Python
-      operator override rules.
-
-      Similar special case applies to *in-place operations*: If you
-      define ``__rmul__``, then ``ndarray_obj *= your_obj`` *will not*
-      call your ``__numpy_ufunc__`` implementation. Instead, the
-      default Python behavior ``ndarray_obj = ndarray_obj * your_obj``
-      occurs.
-
-      Note that the above discussion applies only to Python's builtin
-      binary operation mechanism. ``np.multiply(ndarray_obj,
-      your_obj)`` always calls only your ``__numpy_ufunc__``, as
-      expected.
-
 .. function:: class.__array_finalize__(self)
 
    This method is called whenever the system internally allocates a

diff --git a/doc/source/reference/c-api.types-and-structures.rst b/doc/source/reference/c-api.types-and-structures.rst
@@ -244,7 +244,7 @@ PyArrayDescr_Type
         Indicates that items of this data-type must be reference
         counted (using :cfunc:`Py_INCREF` and :cfunc:`Py_DECREF` ).
 
-    .. cvar:: NPY_ITEM_LISTPICKLE
+    .. cvar:: NPY_LIST_PICKLE
 
         Indicates arrays of this data-type must be converted to a list
         before pickling.

diff --git a/doc/source/reference/routines.array-manipulation.rst b/doc/source/reference/routines.array-manipulation.rst
@@ -54,6 +54,8 @@ Changing kind of array
    asmatrix
    asfarray
    asfortranarray
+   ascontiguousarray
+   asarray_chkfinite
    asscalar
    require
 

diff --git a/doc/source/reference/routines.ma.rst b/doc/source/reference/routines.ma.rst
@@ -65,6 +65,8 @@ Inspecting the array
    ma.nonzero
    ma.shape
    ma.size
+   ma.is_masked
+   ma.is_mask
 
    ma.MaskedArray.data
    ma.MaskedArray.mask
@@ -141,6 +143,7 @@ Joining arrays
 
    ma.column_stack
    ma.concatenate
+   ma.append
    ma.dstack
    ma.hstack
    ma.vstack

diff --git a/doc/source/reference/routines.maskna.rst b/doc/source/reference/routines.maskna.rst
diff --git a/doc/source/reference/routines.polynomials.classes.rst b/doc/source/reference/routines.polynomials.classes.rst
@@ -211,7 +211,7 @@ constant are 0, but both can be specified.::
 In the first case the lower bound of the integration is set to -1 and the
 integration constant is 0. In the second the constant of integration is set
 to 1 as well. Differentiation is simpler since the only option is the
-number times the polynomial is differentiated::
+number of times the polynomial is differentiated::
 
     >>> p = P([1, 2, 3])
     >>> p.deriv(1)
@@ -270,7 +270,7 @@ polynomials up to degree 5 are plotted below.
     >>> import matplotlib.pyplot as plt
     >>> from numpy.polynomial import Chebyshev as T
     >>> x = np.linspace(-1, 1, 100)
-    >>> for i in range(6): ax = plt.plot(x, T.basis(i)(x), lw=2, label="T_%d"%i)
+    >>> for i in range(6): ax = plt.plot(x, T.basis(i)(x), lw=2, label="$T_%d$"%i)
     ...
     >>> plt.legend(loc="upper left")
     <matplotlib.legend.Legend object at 0x3b3ee10>
@@ -284,7 +284,7 @@ The same plots over the range -2 <= `x` <= 2 look very different:
     >>> import matplotlib.pyplot as plt
     >>> from numpy.polynomial import Chebyshev as T
     >>> x = np.linspace(-2, 2, 100)
-    >>> for i in range(6): ax = plt.plot(x, T.basis(i)(x), lw=2, label="T_%d"%i)
+    >>> for i in range(6): ax = plt.plot(x, T.basis(i)(x), lw=2, label="$T_%d$"%i)
     ...
     >>> plt.legend(loc="lower right")
     <matplotlib.legend.Legend object at 0x3b3ee10>

diff --git a/do 95CE c/source/release.rst b/do 95CE c/source/release.rst
@@ -2,7 +2,11 @@
 Release Notes
 *************
 
+.. include:: ../release/1.9.2-notes.rst
+.. include:: ../release/1.9.1-notes.rst
 .. include:: ../release/1.9.0-notes.rst
+.. include:: ../release/1.8.2-notes.rst
+.. include:: ../release/1.8.1-notes.rst
 .. include:: ../release/1.8.0-notes.rst
 .. include:: ../release/1.7.2-notes.rst
 .. include:: ../release/1.7.1-notes.rst