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=========================
NumPy 1.4.0 Release Notes
=========================
This minor includes numerous bug fixes as well as a few new features.
Highlights
==========
New features
============
Extended array wrapping mechanism for ufuncs
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
An __array_prepare__ method has been added to ndarray to provide subclasses
greater flexibility to interact with ufuncs and ufunc-like functions. ndarray
already provided __array_wrap__, which allowed subclasses to set the array type
for the result and populate metadata on the way out of the ufunc (as seen in
the implementation of MaskedArray). For some applications it is necessary to
provide checks and populate metadata *on the way in*. __array_prepare__ is
therefore called just after the ufunc has initialized the output array but
before computing the results and populating it. This way, checks can be made
and errors raised before operations which may modify data in place.
Automatic detection of forward incompatibilities
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Previously, if an extension was built against a version N of NumPy, and used on
a system with NumPy M < N, the import_array was successfull, which could cause
crashes because the version M does not have a function in N. Starting from
NumPy 1.4.0, this will cause a failure in import_array, so the error will be
catched early on.
New C API
~~~~~~~~~
The following C functions have been added to the C API:
#. PyArray_GetNDArrayCFeatureVersion: return the *API* version of the
loaded numpy.
#. PyArray_Correlate2 - like PyArray_Correlate, but implements the usual
definition of correlation. Inputs are not swapped, and conjugate is
taken for complex arrays.
#. PyArray_NeighborhoodIterNew - a new iterator to iterate over a
neighborhood of a point, with automatic boundaries handling.
New ufuncs
~~~~~~~~~~
The following ufuncs have been added to the C API:
#. copysign - return the value of the first argument with the sign copied
from the second argument.
New defines
~~~~~~~~~~~
The alpha processor is now defined and available in numpy/npy_cpu.h. The
failed detection of the PARISC processor has been fixed. The defines are:
#. NPY_CPU_HPPA: PARISC
#. NPY_CPU_ALPHA: Alpha
Enhancements
~~~~~~~~~~~~
#. The sort functions now sort nans to the end.
* Real sort order is [R, nan]
* Complex sort order is [R + Rj, R + nanj, nan + Rj, nan + nanj]
Complex numbers with the same nan placements are sorted according to
the non-nan part if it exists.
#. The type comparison functions have been made consistent with the new
sort order of nans. Searchsorted now works with sorted arrays
containing nan values.
#. Complex division has been made more resistent to overflow.
#. Complex floor division has been made more resistent to overflow.
Testing
~~~~~~~
#. deprecated decorator: this decorator may be used to avoid cluttering
testing output while testing DeprecationWarning is effectively raised by
the decorated test.
Deprecations
============
The following functions are deprecated:
#. correlate: it takes a new keyword argument old_behavior. When True (the
default), it returns the same result as before. When False, compute the
conventional correlation, and take the conjugate for complex arrays. The
old behavior will be removed in NumPy 1.5, and raises a
DeprecationWarning in 1.4.
New iterators
~~~~~~~~~~~~~
A new neighborhood iterator has been added to the C API. It can be used to
iterate over the items in a neighborhood of an array, and can handle boundaries
conditions automatically. Zero and one padding are available, as well as
arbitrary constant value, mirror and circular padding.
Internal changes
================
split multiarray and umath source code
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The source code of multiarray and umath has been split into separate logic
compilation units. This should make the source code more amenable for
newcomers.
Separate compilation
~~~~~~~~~~~~~~~~~~~~
By default, every file of multiarray (and umath) is merged into one for
compilation as was the case before, but if NPY_SEPARATE_COMPILATION env
variable is set to a non-negative value, experimental individual compilation of
each file is enabled. This makes the compile/debug cycle much faster when
working on core numpy.
Separate core math library
~~~~~~~~~~~~~~~~~~~~~~~~~~
New functions which have been added:
* npy_copysign
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