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Published October 18, 2017 | Version v1.0.0rc2
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scipy/scipy: SciPy 1.0.0rc2

Description

SciPy 1.0.0 Release Notes

.. note:: Scipy 1.0.0 is not released yet!

.. contents::

SciPy 1.0.0 is the culmination of 8 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. Before upgrading, we recommend that users check that their own code does not use deprecated SciPy functionality (to do so, run your code with python -Wd and check for DeprecationWarning s). Our development attention will now shift to bug-fix releases on the 1.0.x branch, and on adding new features on the master branch.

Some of the highlights of this release are:

  • Major build improvements. Windows wheels are available on PyPI for the first time, and continuous integration has been set up on Windows and OS X in addition to Linux.
  • A set of new ODE solvers and a unified interface to them (scipy.integrate.solve_ivp).
  • Two new trust region optimizers and a new linear programming method, with improved performance compared to what scipy.optimize offered previously.
  • Many new BLAS and LAPACK functions were wrapped. The BLAS wrappers are now complete.

This release requires Python 2.7 or 3.4+ and NumPy 1.8.2 or greater.

This is also the last release to support LAPACK 3.1.x - 3.3.x. Moving the lowest supported LAPACK version to >3.2.x was long blocked by Apple Accelerate providing the LAPACK 3.2.1 API. We have decided that it's time to either drop Accelerate or, if there is enough interest, provide shims for functions added in more recent LAPACK versions so it can still be used.

New features scipy.cluster improvements

scipy.cluster.hierarchy.optimal_leaf_ordering, a function to reorder a linkage matrix to minimize distances between adjacent leaves, was added.

scipy.fftpack improvements

N-dimensional versions of the discrete sine and cosine transforms and their inverses were added as dctn, idctn, dstn and idstn.

scipy.integrate improvements

A set of new ODE solvers have been added to scipy.integrate. The convenience function scipy.integrate.solve_ivp allows uniform access to all solvers. The individual solvers (RK23, RK45, Radau, BDF and LSODA) can also be used directly.

scipy.linalg improvements

The BLAS wrappers in scipy.linalg.blas have been completed. Added functions are *gbmv, *hbmv, *hpmv, *hpr, *hpr2, *spmv, *spr, *tbmv, *tbsv, *tpmv, *tpsv, *trsm, *trsv, *sbmv, *spr2,

Wrappers for the LAPACK functions *gels, *stev, *sytrd, *hetrd, *sytf2, *hetrf, *sytrf, *sycon, *hecon, *gglse, *stebz, *stemr, *sterf, and *stein have been added.

The function scipy.linalg.subspace_angles has been added to compute the subspace angles between two matrices.

The function scipy.linalg.clarkson_woodruff_transform has been added. It finds low-rank matrix approximation via the Clarkson-Woodruff Transform.

The functions scipy.linalg.eigh_tridiagonal and scipy.linalg.eigvalsh_tridiagonal, which find the eigenvalues and eigenvectors of tridiagonal hermitian/symmetric matrices, were added.

scipy.ndimage improvements

Support for homogeneous coordinate transforms has been added to scipy.ndimage.affine_transform.

The ndimage C code underwent a significant refactoring, and is now a lot easier to understand and maintain.

scipy.optimize improvements

The methods trust-region-exact and trust-krylov have been added to the function scipy.optimize.minimize. These new trust-region methods solve the subproblem with higher accuracy at the cost of more Hessian factorizations (compared to dogleg) or more matrix vector products (compared to ncg) but usually require less nonlinear iterations and are able to deal with indefinite Hessians. They seem very competitive against the other Newton methods implemented in scipy.

scipy.optimize.linprog gained an interior point method. Its performance is superior (both in accuracy and speed) to the older simplex method.

scipy.signal improvements

An argument fs (sampling frequency) was added to the following functions: firwin, firwin2, firls, and remez. This makes these functions consistent with many other functions in scipy.signal in which the sampling frequency can be specified.

scipy.signal.freqz has been sped up significantly for FIR filters.

scipy.sparse improvements

Iterating over and slicing of CSC and CSR matrices is now faster by up to ~35%.

The tocsr method of COO matrices is now several times faster.

The diagonal method of sparse matrices now takes a parameter, indicating which diagonal to return.

scipy.sparse.linalg improvements

A new iterative solver for large-scale nonsymmetric sparse linear systems, scipy.sparse.linalg.gcrotmk, was added. It implements GCROT(m,k), a flexible variant of GCROT.

scipy.sparse.linalg.lsmr now accepts an initial guess, yielding potentially faster convergence.

SuperLU was updated to version 5.2.1.

scipy.spatial improvements

Many distance metrics in scipy.spatial.distance gained support for weights.

The signatures of scipy.spatial.distance.pdist and scipy.spatial.distance.cdist were changed to *args, **kwargs in order to support a wider range of metrics (e.g. string-based metrics that need extra keywords). Also, an optional out parameter was added to pdist and cdist allowing the user to specify where the resulting distance matrix is to be stored

scipy.stats improvements

The methods cdf and logcdf were added to scipy.stats.multivariate_normal, providing the cumulative distribution function of the multivariate normal distribution.

New statistical distance functions were added, namely scipy.stats.wasserstein_distance for the first Wasserstein distance and scipy.stats.energy_distance for the energy distance.

Deprecated features

The following functions in scipy.misc are deprecated: bytescale, fromimage, imfilter, imread, imresize, imrotate, imsave, imshow and toimage. Most of those functions have unexpected behavior (like rescaling and type casting image data without the user asking for that). Other functions simply have better alternatives.

scipy.interpolate.interpolate_wrapper and all functions in that submodule are deprecated. This was a never finished set of wrapper functions which is not relevant anymore.

The fillvalue of scipy.signal.convolve2d will be cast directly to the dtypes of the input arrays in the future and checked that it is a scalar or an array with a single element.

scipy.spatial.distance.matching is deprecated. It is an alias of scipy.spatial.distance.hamming, which should be used instead.

Implementation of scipy.spatial.distance.wminkowski was based on a wrong interpretation of the metric definition. In scipy 1.0 it has been just deprecated in the documentation to keep retro-compatibility but is recommended to use the new version of scipy.spatial.distance.minkowski that implements the correct behaviour.

Positional arguments of scipy.spatial.distance.pdist and scipy.spatial.distance.cdist should be replaced with their keyword version.

Backwards incompatible changes

The following deprecated functions have been removed from scipy.stats: betai, chisqprob, f_value, histogram, histogram2, pdf_fromgamma, signaltonoise, square_of_sums, ss and threshold.

The following deprecated functions have been removed from scipy.stats.mstats: betai, f_value_wilks_lambda, signaltonoise and threshold.

The deprecated a and reta keywords have been removed from scipy.stats.shapiro.

The deprecated functions sparse.csgraph.cs_graph_components and sparse.linalg.symeig have been removed from scipy.sparse.

The following deprecated keywords have been removed in scipy.sparse.linalg: drop_tol from splu, and xtype from bicg, bicgstab, cg, cgs, gmres, qmr and minres.

The deprecated functions expm2 and expm3 have been removed from scipy.linalg. The deprecated keyword q was removed from scipy.linalg.expm. And the deprecated submodule linalg.calc_lwork was removed.

The deprecated functions C2K, K2C, F2C, C2F, F2K and K2F have been removed from scipy.constants.

The deprecated ppform class was removed from scipy.interpolate.

The deprecated keyword iprint was removed from scipy.optimize.fmin_cobyla.

The default value for the zero_phase keyword of scipy.signal.decimate has been changed to True.

The kmeans and kmeans2 functions in scipy.cluster.vq changed the method used for random initialization, so using a fixed random seed will not necessarily produce the same results as in previous versions.

scipy.special.gammaln does not accept complex arguments anymore.

The deprecated functions sph_jn, sph_yn, sph_jnyn, sph_in, sph_kn, and sph_inkn have been removed. Users should instead use the functions spherical_jn, spherical_yn, spherical_in, and spherical_kn. Be aware that the new functions have different signatures.

The cross-class properties of scipy.signal.lti systems have been removed. The following properties/setters have been removed:

Name - (accessing/setting has been removed) - (setting has been removed)

  • StateSpace - (num, den, gain) - (zeros, poles)
  • TransferFunction (A, B, C, D, gain) - (zeros, poles)
  • ZerosPolesGain (A, B, C, D, num, den) - ()

signal.freqz(b, a) with b or a >1-D raises a ValueError. This was a corner case for which it was unclear that the behavior was well-defined.

The method var of scipy.stats.dirichlet now returns a scalar rather than an ndarray when the length of alpha is 1.

Other changes

SciPy now has a formal governance structure. It consists of a BDFL (Pauli Virtanen) and a Steering Committee. See the governance document <https://github.com/scipy/scipy/blob/master/doc/source/dev/governance/governance.rst>_ for details.

It is now possible to build SciPy on Windows with MSVC + gfortran! Continuous integration has been set up for this build configuration on Appveyor, building against OpenBLAS.

Continuous integration for OS X has been set up on TravisCI.

The SciPy test suite has been migrated from nose to pytest.

scipy/_distributor_init.py was added to allow redistributors of SciPy to add custom code that needs to run when importing SciPy (e.g. checks for hardware, DLL search paths, etc.).

Support for PEP 518 (specifying build system requirements) was added - see pyproject.toml in the root of the SciPy repository.

In order to have consistent function names, the function scipy.linalg.solve_lyapunov is renamed to scipy.linalg.solve_continuous_lyapunov. The old name is kept for backwards-compatibility.

Authors
  • @arcady +
  • @xoviat +
  • Anton Akhmerov
  • Dominic Antonacci +
  • Alessandro Pietro Bardelli
  • Ved Basu +
  • Michael James Bedford +
  • Ray Bell +
  • Juan M. Bello-Rivas +
  • Sebastian Berg
  • Felix Berkenkamp
  • Jyotirmoy Bhattacharya +
  • Matthew Brett
  • Jonathan Bright
  • Bruno Jiménez +
  • Evgeni Burovski
  • Patrick Callier
  • Mark Campanelli +
  • CJ Carey
  • Robert Cimrman
  • Adam Cox +
  • Michael Danilov +
  • David Haberthür +
  • Andras Deak +
  • Philip DeBoer
  • Anne-Sylvie Deutsch
  • Cathy Douglass +
  • Dominic Else +
  • Guo Fei +
  • Roman Feldbauer +
  • Yu Feng
  • Jaime Fernandez del Rio
  • Orestis Floros +
  • David Freese +
  • Adam Geitgey +
  • James Gerity +
  • Dezmond Goff +
  • Christoph Gohlke
  • Ralf Gommers
  • Dirk Gorissen +
  • Matt Haberland +
  • David Hagen +
  • Charles Harris
  • Lam Yuen Hei +
  • Jean Helie +
  • Gaute Hope +
  • Guillaume Horel +
  • Franziska Horn +
  • Yevhenii Hyzyla +
  • Vladislav Iakovlev +
  • Marvin Kastner +
  • Mher Kazandjian
  • Thomas Keck
  • Adam Kurkiewicz +
  • Ronan Lamy +
  • J.L. Lanfranchi +
  • Eric Larson
  • Denis Laxalde
  • Gregory R. Lee
  • Felix Lenders +
  • Evan Limanto
  • Julian Lukwata +
  • François Magimel
  • Syrtis Major +
  • Charles Masson +
  • Nikolay Mayorov
  • Tobias Megies
  • Markus Meister +
  • Roman Mirochnik +
  • Jordi Montes +
  • Nathan Musoke +
  • Andrew Nelson
  • M.J. Nichol
  • Juan Nunez-Iglesias
  • Arno Onken +
  • Nick Papior +
  • Dima Pasechnik +
  • Ashwin Pathak +
  • Oleksandr Pavlyk +
  • Stefan Peterson
  • Ilhan Polat
  • Andrey Portnoy +
  • Ravi Kumar Prasad +
  • Aman Pratik
  • Eric Quintero
  • Vedant Rathore +
  • Tyler Reddy
  • Joscha Reimer
  • Philipp Rentzsch +
  • Antonio Horta Ribeiro
  • Ned Richards +
  • Kevin Rose +
  • Benoit Rostykus +
  • Matt Ruffalo +
  • Eli Sadoff +
  • Pim Schellart
  • Nico Schlömer +
  • Klaus Sembritzki +
  • Nikolay Shebanov +
  • Jonathan Tammo Siebert
  • Scott Sievert
  • Max Silbiger +
  • Mandeep Singh +
  • Michael Stewart +
  • Jonathan Sutton +
  • Deep Tavker +
  • Martin Thoma
  • James Tocknell +
  • Aleksandar Trifunovic +
  • Paul van Mulbregt +
  • Jacob Vanderplas
  • Aditya Vijaykumar
  • Pauli Virtanen
  • James Webber
  • Warren Weckesser
  • Eric Wieser +
  • Josh Wilson
  • Zhiqing Xiao +
  • Evgeny Zhurko
  • Nikolay Zinov +
  • Zé Vinícius +

A total of 121 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.

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