ANN: SciPy 0.13.0 release

Ralf Gommers ralf.gommers at
Sat Oct 19 23:40:15 CEST 2013

On behalf of the SciPy development team I'm pleased to announce the
availability of SciPy 0.13.0. This release contains some interesting new
features (see highlights below) and half a year's worth of maintenance
work. 65 people contributed to this release.

Some of the highlights are:

  - support for fancy indexing and boolean comparisons with sparse matrices
  - interpolative decompositions and matrix functions in the linalg module
  - two new trust-region solvers for unconstrained minimization

This release requires Python 2.6, 2.7 or 3.1-3.3 and NumPy 1.5.1 or
greater. Support for Python 2.4 and 2.5 has been dropped as of this release.

Sources and binaries can be found at, release notes
are copied below.


SciPy 0.13.0 Release Notes

.. contents::

SciPy 0.13.0 is the culmination of 7 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 0.13.x branch, and on adding
new features on the master branch.

This release requires Python 2.6, 2.7 or 3.1-3.3 and NumPy 1.5.1 or greater.
Highlights of this release are:

  - support for fancy indexing and boolean comparisons with sparse matrices
  - interpolative decompositions and matrix functions in the linalg module
  - two new trust-region solvers for unconstrained minimization

New features

``scipy.integrate`` improvements

N-dimensional numerical integration

A new function `scipy.integrate.nquad`, which provides N-dimensional
integration functionality with a more flexible interface than ``dblquad``
``tplquad``, has been added.

``dopri*`` improvements

The intermediate results from the ``dopri`` family of ODE solvers can now be
accessed by a *solout* callback function.

``scipy.linalg`` improvements

Interpolative decompositions

Scipy now includes a new module `scipy.linalg.interpolative`
containing routines for computing interpolative matrix decompositions
(ID). This feature is based on the ID software package by
P.G. Martinsson, V. Rokhlin, Y. Shkolnisky, and M. Tygert, previously
adapted for Python in the PymatrixId package by K.L. Ho.

Polar decomposition

A new function `scipy.linalg.polar`, to compute the polar decomposition
of a matrix, was added.

BLAS level 3 functions

The BLAS functions ``symm``, ``syrk``, ``syr2k``, ``hemm``, ``herk`` and
``her2k`` are now wrapped in `scipy.linalg`.

Matrix functions

Several matrix function algorithms have been implemented or updated
detailed descriptions in recent papers of Nick Higham and his co-authors.
These include the matrix square root (``sqrtm``), the matrix logarithm
(``logm``), the matrix exponential (``expm``) and its Frechet derivative
(``expm_frechet``), and fractional matrix powers

``scipy.optimize`` improvements

Trust-region unconstrained minimization algorithms

The ``minimize`` function gained two trust-region solvers for unconstrained
minimization: ``dogleg`` and ``trust-ncg``.

``scipy.sparse`` improvements

Boolean comparisons and sparse matrices

All sparse matrix types now support boolean data, and boolean operations.
sparse matrices `A` and `B` can be compared in all the expected ways `A <
`A >= B`, `A != B`, producing similar results as dense Numpy arrays.
Comparisons with dense matrices and scalars are also supported.

CSR and CSC fancy indexing

Compressed sparse row and column sparse matrix types now support fancy
with boolean matrices, slices, and lists. So where A is a (CSC or CSR)
matrix, you can do things like::

    >>> A[A > 0.5] = 1  # since Boolean sparse matrices work
    >>> A[:2, :3] = 2
    >>> A[[1,2], 2] = 3

``scipy.sparse.linalg`` improvements

The new function ``onenormest`` provides a lower bound of the 1-norm of a
linear operator and has been implemented according to Higham and Tisseur
(2000).  This function is not only useful for sparse matrices, but can also
used to estimate the norm of products or powers of dense matrices without
explictly building the intermediate matrix.

The multiplicative action of the matrix exponential of a linear operator
(``expm_multiply``) has been implemented following the description in
and Higham (2011).

Abstract linear operators (`scipy.sparse.linalg.LinearOperator`) can now be
multiplied, added to each other, and exponentiated, producing new linear
operators. This enables easier construction of composite linear operations.

``scipy.spatial`` improvements

The vertices of a `ConvexHull` can now be accessed via the `vertices`
which gives proper orientation in 2-D.

``scipy.signal`` improvements

The cosine window function `scipy.signal.cosine` was added.

``scipy.special`` improvements

New functions `scipy.special.xlogy` and `scipy.special.xlog1py` were added.
These functions can simplify and speed up code that has to calculate
``x * log(y)`` and give 0 when ``x == 0``.

```` improvements

Unformatted Fortran file reader

The new class `` facilitates reading unformatted
sequential files written by Fortran code.

```` enhancements

`` now accepts a file buffer. Previously it only
accepted a filename.

`` and `` can now handle floating
point WAV files.

``scipy.interpolate`` improvements

B-spline derivatives and antiderivatives

`scipy.interpolate.splder` and `scipy.interpolate.splantider` functions
for computing B-splines that represent derivatives and antiderivatives
of B-splines were added.  These functions are also available in the
class-based FITPACK interface as ``UnivariateSpline.derivative`` and

``scipy.stats`` improvements

Distributions now allow using keyword parameters in addition to
positional parameters in all methods.

The function `scipy.stats.power_divergence` has been added for the
Cressie-Read power divergence statistic and goodness of fit test.
Included in this family of statistics is the "G-test"

`scipy.stats.mood` now accepts multidimensional input.

An option was added to `scipy.stats.wilcoxon` for continuity correction.

`scipy.stats.chisquare` now has an `axis` argument.

`scipy.stats.mstats.chisquare` now has `axis` and `ddof` arguments.

Deprecated features

``expm2`` and ``expm3``

The matrix exponential functions `scipy.linalg.expm2` and
are deprecated. All users should use the numerically more robust
`scipy.linalg.expm` function instead.

``scipy.stats`` functions

`scipy.stats.oneway` is deprecated; `scipy.stats.f_oneway` should be used

`scipy.stats.glm` is deprecated.  `scipy.stats.ttest_ind` is an equivalent
function; more full-featured general (and generalized) linear model
implementations can be found in statsmodels.

`scipy.stats.cmedian` is deprecated; ``numpy.median`` should be used

Backwards incompatible changes

LIL matrix assignment
Assigning values to LIL matrices with two index arrays now works similarly
assigning into ndarrays::

    >>> x = lil_matrix((3, 3))
    >>> x[[0,1,2],[0,1,2]]=[0,1,2]
    >>> x.todense()
    matrix([[ 0.,  0.,  0.],
            [ 0.,  1.,  0.],
            [ 0.,  0.,  2.]])

rather than giving the result::

    >>> x.todense()
    matrix([[ 0.,  1.,  2.],
            [ 0.,  1.,  2.],
            [ 0.,  1.,  2.]])

Users relying on the previous behavior will need to revisit their code.
The previous behavior is obtained by ``x[numpy.ix_([0,1,2],[0,1,2])] = ...`.

Deprecated ``radon`` function removed

The ``misc.radon`` function, which was deprecated in scipy 0.11.0, has been
removed.  Users can find a more full-featured ``radon`` function in

Removed deprecated keywords ``xa`` and ``xb`` from ``stats.distributions``

The keywords ``xa`` and ``xb``, which were deprecated since 0.11.0, have
been removed from the distributions in ``scipy.stats``.

Changes to MATLAB file readers / writers

The major change is that 1D arrays in numpy now become row vectors (shape
1, N)
when saved to a MATLAB 5 format file.  Previously 1D arrays saved as column
vectors (N, 1).  This is to harmonize the behavior of writing MATLAB 4 and 5
formats, and adapt to the defaults of numpy and MATLAB - for example
``np.atleast_2d`` returns 1D arrays as row vectors.

Trying to save arrays of greater than 2 dimensions in MATLAB 4 format now
an error instead of silently reshaping the array as 2D.

``'afile')`` used to look for `afile` on the Python system
(``sys.path``); now ``loadmat`` only looks in the current directory for a
relative path filename.

Other changes

Security fix: ``scipy.weave`` previously used temporary directories in an
insecure manner under certain circumstances.

Cython is now required to build *unreleased* versions of scipy.
The C files generated from Cython sources are not included in the git repo
anymore.  They are however still shipped in source releases.

The code base received a fairly large PEP8 cleanup.  A ``tox pep8``
command has been added; new code should pass this test command.

Scipy cannot be compiled with gfortran 4.1 anymore (at least on RH5), likely
due to that compiler version not supporting entry constructs well.


This release contains work by the following people (contributed at least
one patch to this release, names in alphabetical order):

* Jorge Cañardo Alastuey +
* Tom Aldcroft +
* Max Bolingbroke +
* Joseph Jon Booker +
* François Boulogne
* Matthew Brett
* Christian Brodbeck +
* Per Brodtkorb +
* Christian Brueffer +
* Lars Buitinck
* Evgeni Burovski +
* Tim Cera
* Lawrence Chan +
* David Cournapeau
* Dražen Lučanin +
* Alexander J. Dunlap +
* endolith
* André Gaul +
* Christoph Gohlke
* Ralf Gommers
* Alex Griffing +
* Blake Griffith +
* Charles Harris
* Bob Helmbold +
* Andreas Hilboll
* Kat Huang +
* Oleksandr (Sasha) Huziy +
* Gert-Ludwig Ingold +
* Thouis (Ray) Jones
* Juan Luis Cano Rodríguez +
* Robert Kern
* Andreas Kloeckner +
* Sytse Knypstra +
* Gustav Larsson +
* Denis Laxalde
* Christopher Lee
* Tim Leslie
* Wendy Liu +
* Clemens Novak +
* Takuya Oshima +
* Josef Perktold
* Illia Polosukhin +
* Przemek Porebski +
* Steve Richardson +
* Branden Rolston +
* Skipper Seabold
* Fazlul Shahriar
* Leo Singer +
* Rohit Sivaprasad +
* Daniel B. Smith +
* Julian Taylor
* Louis Thibault +
* Tomas Tomecek +
* John Travers
* Richard Tsai +
* Jacob Vanderplas
* Patrick Varilly
* Pauli Virtanen
* Stefan van der Walt
* Warren Weckesser
* Pedro Werneck +
* Nils Werner +
* Michael Wimmer +
* Nathan Woods +
* Tony S. Yu +

A total of 65 people contributed to this release.
People with a "+" by their names contributed a patch for the first time.

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