[SciPy-Dev] ANN: SciPy 0.10.0 beta 2

Sun Sep 18 07:02:08 EDT 2011

Hi,

The first beta release of scipy 0.10.0 was, well, beta quality, therefore I
am pleased to announce the availability of the second 0.10.0 beta release.
For this release over a 100 tickets and pull requests have been closed, and
many new features have been added. Some of the highlights are:

  - support for Bento as a build system for scipy
  - generalized and shift-invert eigenvalue problems in sparse.linalg
  - addition of discrete-time linear systems in the signal module

Sources and binaries can be found at
https://sourceforge.net/projects/scipy/files/scipy/0.10.0b2/, release notes
are copied below. SciPy 0.10 is compatible with Python 2.4 - 3.2, and
requires numpy 1.5.1 or higher.

Please try this release and report problems on the mailing list.

Cheers,
Ralf

==========================
SciPy 0.10.0 Release Notes
==========================

.. note:: Scipy 0.10.0 is not released yet!

.. contents::

SciPy 0.10.0 is the culmination of XXX months of hard work. It contains
many new features, numerous bug-fixes, improved test coverage and
better documentation.  There have been a number of deprecations and
API changes in this release, which are documented below.  All users
are encouraged to upgrade to this release, as there are a large number
of bug-fixes and optimizations.  Moreover, our development attention
will now shift to bug-fix releases on the 0.10.x branch, and on adding
new features on the development trunk.

This release requires Python 2.4-2.7 or 3.1- and NumPy 1.5 or greater.

New features
============

Bento: new optional build system
--------------------------------

Scipy can now be built with `Bento <http://cournape.github.com/Bento/>`_.
Bento has some nice features like parallel builds and partial rebuilds, that
are not possible with the default build system (distutils).  For usage
instructions see BENTO_BUILD.txt in the scipy top-level directory.

Currently Scipy has three build systems, distutils, numscons and bento.
Numscons is deprecated and is planned and will likely be removed in the next
release.

Generalized and shift-invert eigenvalue problems in ``scipy.sparse.linalg``
---------------------------------------------------------------------------

The sparse eigenvalue problem solver functions
``scipy.sparse.eigs/eigh`` now support generalized eigenvalue
problems, and all shift-invert modes available in ARPACK.

Discrete-Time Linear Systems (``scipy.signal``)
-----------------------------------------------

Support for simulating discrete-time linear systems, including
``scipy.signal.dlsim``, ``scipy.signal.dimpulse``, and
``scipy.signal.dstep``,
has been added to SciPy.  Conversion of linear systems from continuous-time
to
discrete-time representations is also present via the
``scipy.signal.cont2discrete`` function.

Enhancements to ``scipy.signal``
--------------------------------

A Lomb-Scargle periodogram can now be computed with the new function
``scipy.signal.lombscargle``.

The forward-backward filter function ``scipy.signal.filtfilt`` can now
filter the data in a given axis of an n-dimensional numpy array.
(Previously it only handled a 1-dimensional array.)  Options have been
added to allow more control over how the data is extended before filtering.

FIR filter design with ``scipy.signal.firwin2`` now has options to create
filters of type III (zero at zero and Nyquist frequencies) and IV (zero at
zero
frequency).

Additional decomposition options (``scipy.linalg``)
---------------------------------------------------

A sort keyword has been added to the Schur decomposition routine
(``scipy.linalg.schur``) to allow the sorting of eigenvalues in
the resultant Schur form.

Additional special matrices (``scipy.linalg``)
----------------------------------------------

The functions ``hilbert`` and ``invhilbert`` were added to ``scipy.linalg``.

Enhancements to ``scipy.stats``
-------------------------------

* The *one-sided form* of Fisher's exact test is now also implemented in
  ``stats.fisher_exact``.
* The function ``stats.chi2_contingency`` for computing the chi-square test
of
  independence of factors in a contingency table has been added, along with
  the related utility functions ``stats.contingency.margins`` and
  ``stats.contingency.expected_freq``.

Basic support for Harwell-Boeing file format for sparse matrices
----------------------------------------------------------------

Both read and write are support through a simple function-based API, as well
as
a more complete API to control number format. The functions may be found in
scipy.sparse.io.

The following features are supported:

    * Read and write sparse matrices in the CSC format
    * Only real, symmetric, assembled matrix are supported (RUA format)

Deprecated features
===================

``scipy.maxentropy``
--------------------

The maxentropy module is unmaintained, rarely used and has not been
functioning
well for several releases.  Therefore it has been deprecated for this
release,
and will be removed for scipy 0.11.  Logistic regression in scikits.learn is
a
good alternative for this functionality.  The ``scipy.maxentropy.logsumexp``
function has been moved to ``scipy.misc``.

``scipy.lib.blas``
------------------

There are similar BLAS wrappers in ``scipy.linalg`` and ``scipy.lib``.
These
have now been consolidated as ``scipy.linalg.blas``, and ``scipy.lib.blas``
is
deprecated.

Numscons build system
---------------------

The numscons build system is being replaced by Bento, and will be removed in
one of the next scipy releases.

Removed features
================

The deprecated name `invnorm` was removed from
``scipy.stats.distributions``,
this distribution is available as `invgauss`.

The following deprecated nonlinear solvers from ``scipy.optimize`` have been
removed::

  - ``broyden_modified`` (bad performance)
  - ``broyden1_modified`` (bad performance)
  - ``broyden_generalized`` (equivalent to ``anderson``)
  - ``anderson2`` (equivalent to ``anderson``)
  - ``broyden3`` (obsoleted by new limited-memory broyden methods)
  - ``vackar`` (renamed to ``diagbroyden``)

Other changes
=============

``scipy.constants`` has been updated with the CODATA 2010 constants.

``__all__`` dicts have been added to all modules, which has cleaned up the
namespaces (particularly useful for interactive work).

An API section has been added to the documentation, giving recommended
import
guidelines and specifying which submodules are public and which aren't.

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