NumPy 1.10.0 Release Notes
**************************

This release supports Python 2.6 - 2.7 and 3.2 - 3.4.


Highlights
==========
* numpy.distutils now supports parallel compilation via the --jobs/-j argument
  passed to setup.py build
* Addition of *np.linalg.multi_dot*: compute the dot product of two or more
  arrays in a single function call, while automatically selecting the fastest
  evaluation order.
* Addition of `nanprod` to the set of nanfunctions.


Dropped Support
===============
* The polytemplate.py file has been removed.
* The _dotblas module is no longer available.
* The testcalcs.py file has been removed.


Future Changes
==============
* The SafeEval class will be removed.
* The alterdot and restoredot functions will be removed.


Compatibility notes
===================

numpy version string
~~~~~~~~~~~~~~~~~~~~
The numpy version string for development builds has been changed from
``x.y.z.dev-githash`` to ``x.y.z.dev+githash`` (note the +) in order to comply
with PEP 440.

relaxed stride checking
~~~~~~~~~~~~~~~~~~~~~~~
NPY_RELAXED_STRIDE_CHECKING is now true by default.

*np.ravel*, *np.diagonal* and *np.diag* now preserve subtypes
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
There was inconsistent behavior between *x.ravel()* and *np.ravel(x)*, as well
as between *x.diagonal()* and *np.diagonal(x)*.  For example, if *x* was a
matrix, then *x.ravel()* returned a matrix, while *np.ravel(x)* returned an
ndarray.  In the case of matrices, the returned value will have different
dimensions and that may lead to problems in using the result.


New Features
============

*np.cbrt* to compute cube root for real floats
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
*np.cbrt* wraps the C99 cube root function *cbrt*.
Compared to *np.power(x, 1./3.)* it is well defined for negative real floats
and a bit faster.

numpy.distutils now allows parallel compilation
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
By passing *--jobs=n* or *-j n* to *setup.py build* the compilation of
extensions is now performed in *n* parallel processes.
The parallelization is limited to files within one extension so projects using
Cython will not profit because it builds extensions from single files.


Improvements
============

*np.digitize* using binary search
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
*np.digitize* is now implemented in terms of *np.searchsorted*. This means
that a binary search is used to bin the values, which scales much better
for larger number of bins than the previous linear search. It also removes
the requirement for the input array to be 1-dimensional.

*np.poly* now casts integer inputs to float
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
*np.poly* will now cast 1-dimensional input arrays of integer type to double
precision floating point, to prevent integer overflow when computing the monic
polynomial. It is still possible to obtain higher precision results by
passing in an array of object type, filled e.g. with Python ints.

*np.interp* can now be used with periodic functions
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
*np.interp* now has a new parameter *period* that supplies the period of the
input data *xp*. In such case, the input data is properly normalized to the
given period and one end point is added to each extremity of *xp* in order to
close the previous and the next period cycles, resulting in the correct
interpolation behavior.


Changes
=======

dotblas functionality moved to multiarray
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The cblas versions of dot, inner, and vdot have been integrated into
the multiarray module. In particular, vdot is now a multiarray function,
which it was not before.

stricter check of gufunc signature compliance
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Inputs to generalized universal functions are now more strictly checked
against the function's signature: all core dimensions are now required to
be present in input arrays; core dimensions with the same label must have
the exact same size; and output core dimension's must be specified, either
by a same label input core dimension or by a passed-in output array.

views returned from *np.einsum* are writeable
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Views returned by *np.einsum* will now be writeable whenever the input
array is writeable.


Deprecations
============

SafeEval
~~~~~~~~
The SafeEval class in numpy/lib/utils.py is deprecated and will be removed
in the next release.

alterdot, restoredot
~~~~~~~~~~~~~~~~~~~~
The alterdot and restoredot functions no longer do anything, and are
deprecated.

pkgload, PackageLoader
~~~~~~~~~~~~~~~~~~~~~~
These ways of loading packages are now deprecated.