ANN: Scipy 0.14.0 beta 1 release
Hi, I'm pleased to announce the availability of the first beta release of Scipy0.14.0. Please try this beta and report any issues on the scipydev mailing list. Source tarballs, binaries and the full release notes can be found at http://sourceforge.net/projects/scipy/files/scipy/0.14.0b1/. Part of the release notes copied below. A big thank you to everyone who contributed to this release! Ralf SciPy 0.14.0 is the culmination of 8 months of hard work. It contains many new features, numerous bugfixes, 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 bugfixes and optimizations. Moreover, our development attention will now shift to bugfix releases on the 0.14.x branch, and on adding new features on the master branch. This release requires Python 2.6, 2.7 or 3.23.4 and NumPy 1.5.1 or greater. New features ============ ``scipy.interpolate`` improvements  A new wrapper function `scipy.interpolate.interpn` for interpolation on regular grids has been added. `interpn` supports linear and nearestneighbor interpolation in arbitrary dimensions and spline interpolation in two dimensions. Faster implementations of piecewise polynomials in power and Bernstein polynomial bases have been added as `scipy.interpolate.PPoly` and `scipy.interpolate.BPoly`. New users should use these in favor of `scipy.interpolate.PiecewisePolynomial`. `scipy.interpolate.interp1d` now accepts nonmonotonic inputs and sorts them. If performance is critical, sorting can be turned off by using the new ``assume_sorted`` keyword. Functionality for evaluation of bivariate spline derivatives in ``scipy.interpolate`` has been added. The new class `scipy.interpolate.Akima1DInterpolator` implements the piecewise cubic polynomial interpolation scheme devised by H. Akima. Functionality for fast interpolation on regular, unevenly spaced grids in arbitrary dimensions has been added as `scipy.interpolate.RegularGridInterpolator` . ``scipy.linalg`` improvements  The new function `scipy.linalg.dft` computes the matrix of the discrete Fourier transform. A condition number estimation function for matrix exponential, `scipy.linalg.expm_cond`, has been added. ``scipy.optimize`` improvements  A set of benchmarks for optimize, which can be run with ``optimize.bench()``, has been added. `scipy.optimize.curve_fit` now has more controllable error estimation via the ``absolute_sigma`` keyword. Support for passing custom minimization methods to ``optimize.minimize()`` and ``optimize.minimize_scalar()`` has been added, currently useful especially for combining ``optimize.basinhopping()`` with custom local optimizer routines. ``scipy.stats`` improvements  A new class `scipy.stats.multivariate_normal` with functionality for multivariate normal random variables has been added. A lot of work on the ``scipy.stats`` distribution framework has been done. Moment calculations (skew and kurtosis mainly) are fixed and verified, all examples are now runnable, and many small accuracy and performance improvements for individual distributions were merged. The new function `scipy.stats.anderson_ksamp` computes the ksample AndersonDarling test for the null hypothesis that k samples come from the same parent population. ``scipy.signal`` improvements  ``scipy.signal.iirfilter`` and related functions to design Butterworth, Chebyshev, elliptical and Bessel IIR filters now all use polezero ("zpk") format internally instead of using transformations to numerator/denominator format. The accuracy of the produced filters, especially highorder ones, is improved significantly as a result. The new function `scipy.signal.vectorstrength` computes the vector strength, a measure of phase synchrony, of a set of events. ``scipy.special`` improvements  The functions `scipy.special.boxcox` and `scipy.special.boxcox1p`, which compute the BoxCox transformation, have been added. ``scipy.sparse`` improvements   Significant performance improvement in CSR, CSC, and DOK indexing speed.  When using Numpy >= 1.9 (to be released in MM 2014), sparse matrices function correctly when given to arguments of ``np.dot``, ``np.multiply`` and other ufuncs. With earlier Numpy and Scipy versions, the results of such operations are undefined and usually unexpected.  Sparse matrices are no longer limited to ``2^31`` nonzero elements. They automatically switch to using 64bit index data type for matrices containing more elements. User code written assuming the sparse matrices use int32 as the index data type will continue to work, except for such large matrices. Code dealing with larger matrices needs to accept either int32 or int64 indices. Deprecated features =================== ``anneal``  The global minimization function `scipy.optimize.anneal` is deprecated. All users should use the `scipy.optimize.basinhopping` function instead. ``scipy.stats``  ``randwcdf`` and ``randwppf`` functions are deprecated. All users should use distributionspecific ``rvs`` methods instead. Probability calculation aliases ``zprob``, ``fprob`` and ``ksprob`` are deprecated. Use instead the ``sf`` methods of the corresponding distributions or the ``special`` functions directly. ``scipy.interpolate``  ``PiecewisePolynomial`` class is deprecated. Backwards incompatible changes ============================== scipy.special.lpmn  ``lpmn`` no longer accepts complexvalued arguments. A new function ``clpmn`` with uniform complex analytic behavior has been added, and it should be used instead. scipy.sparse.linalg  Eigenvectors in the case of generalized eigenvalue problem are normalized to unit vectors in 2norm, rather than following the LAPACK normalization convention. The deprecated UMFPACK wrapper in ``scipy.sparse.linalg`` has been removed due to license and install issues. If available, ``scikits.umfpack`` is still used transparently in the ``spsolve`` and ``factorized`` functions. Otherwise, SuperLU is used instead in these functions. scipy.stats  The deprecated functions ``glm``, ``oneway`` and ``cmedian`` have been removed from ``scipy.stats``. ``stats.scoreatpercentile`` now returns an array instead of a list of percentiles. scipy.interpolate  The API for computing derivatives of a monotone piecewise interpolation has changed: if `p` is a ``PchipInterpolator`` object, `p.derivative(der)` returns a callable object representing the derivative of `p`. For inplace derivatives use the second argument of the `__call__` method: `p(0.1, der=2)` evaluates the second derivative of `p` at `x=0.1`. The method `p.derivatives` has been removed. Authors ======= * Marc Abramowitz + * andbo + * Vincent ArelBundock + * Petr Baudis + * Max Bolingbroke * François Boulogne * Matthew Brett * Lars Buitinck * Evgeni Burovski * CJ Carey + * Thomas A Caswell + * Pawel Chojnacki + * Phillip Cloud + * Stefano Costa + * David Cournapeau * Dapid + * Matthieu Dartiailh + * Christoph Deil + * Jörg Dietrich + * endolith * Francisco de la Peña + * Ben FrantzDale + * Jim Garrison + * André Gaul * Christoph Gohlke * Ralf Gommers * Robert David Grant * Alex Griffing * Blake Griffith * Yaroslav Halchenko * Andreas Hilboll * Kat Huang * GertLudwig Ingold * jamestwebber + * Dorota Jarecka + * Todd Jennings + * Thouis (Ray) Jones * Juan Luis Cano Rodríguez * ktritz + * Jacques Kvam + * Eric Larson + * Justin Lavoie + * Denis Laxalde * Jussi Leinonen + * lemonlaug + * Tim Leslie * Alain Leufroy + * George Lewis + * Max Linke + * Brandon Liu + * Benny Malengier + * Matthias Kümmerer + * Cimarron Mittelsteadt + * Eric Moore * Andrew Nelson + * Niklas Hambüchen + * Joel Nothman + * Clemens Novak * Emanuele Olivetti + * Stefan Otte + * peb + * Josef Perktold * pjwerneck * Andrew Sczesnak + * poolio * Jérôme Roy + * Carl Sandrock + * Shauna + * Fabrice Silva * Daniel B. Smith * Patrick Snape + * Thomas Spura + * Jacob Stevenson * Julian Taylor * Tomas Tomecek * Richard Tsai * Joris Vankerschaver + * Pauli Virtanen * Warren Weckesser A total of 78 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete.
participants (1)

Ralf Gommers