[SciPy-Dev] ANN: SciPy 0.10 beta 1

Ralf Gommers ralf.gommers@googlemail....
Mon Sep 12 16:36:11 CDT 2011


I am pleased to announce the availability of the first beta release of
SciPy0.10.0. 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/0.10.0b1/, release notes
are copied below.
Binaries for Python 2.x are available, on Python 3 there are a few known
problems that should be solved first. When they are, a second beta will

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


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

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
has been added to SciPy.  Conversion of linear systems from continuous-time
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

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

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
* The function ``stats.chi2_contingency`` for computing the chi-square test
  independence of factors in a contingency table has been added, along with
  the related utility functions ``stats.contingency.margins`` and

Basic support for Harwell-Boeing file format for sparse matrices

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

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


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


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

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
this distribution is available as `invgauss`.

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

  - ``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
guidelines and specifying which submodules are public and which aren't.


c8c6f3870f9d0ef571861da63b4b374b  release/installers/scipy-0.10.0b1.tar.gz
1ce4f01acfccb68dcd6c387eb08a8a88  release/installers/scipy-0.10.0b1.zip
-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://mail.scipy.org/pipermail/scipy-dev/attachments/20110912/802e3fea/attachment.html 

More information about the SciPy-Dev mailing list