SciPy 1.0.0 Release Notes

Contents

• SciPy 1.0.0 Release Notes
  • Why 1.0 now?
  • Some history and perspectives
  • Highlights of this release
  • Upgrading and compatibility
    • New features
  • scipy.cluster improvements
  • scipy.fftpack improvements
  • scipy.integrate improvements
  • scipy.linalg improvements
  • scipy.ndimage improvements
  • scipy.optimize improvements
  • scipy.signal improvements
  • scipy.sparse improvements
  • scipy.sparse.linalg improvements
  • scipy.spatial improvements
  • scipy.stats improvements
    • Deprecated features
    • Backwards incompatible changes
    • Other changes
    • Authors
  • Issues closed for 1.0.0
  • Pull requests for 1.0.0

We are extremely pleased to announce the release of SciPy 1.0, 16 years after version 0.1 saw the light of day. It has been a long, productive journey to get here, and we anticipate many more exciting new features and releases in the future.

Why 1.0 now?

A version number should reflect the maturity of a project - and SciPy was a mature and stable library that is heavily used in production settings for a long time already. From that perspective, the 1.0 version number is long overdue.

Some key project goals, both technical (e.g. Windows wheels and continuous integration) and organisational (a governance structure, code of conduct and a roadmap), have been achieved recently.

Many of us are a bit perfectionist, and therefore are reluctant to call something “1.0” because it may imply that it’s “finished” or “we are 100% happy with it”. This is normal for many open source projects, however that doesn’t make it right. We acknowledge to ourselves that it’s not perfect, and there are some dusty corners left (that will probably always be the case). Despite that, SciPy is extremely useful to its users, on average has high quality code and documentation, and gives the stability and backwards compatibility guarantees that a 1.0 label imply.

Some history and perspectives

• 2001: the first SciPy release
• 2005: transition to NumPy
• 2007: creation of scikits
• 2008: scipy.spatial module and first Cython code added
• 2010: moving to a 6-monthly release cycle
• 2011: SciPy development moves to GitHub
• 2011: Python 3 support
• 2012: adding a sparse graph module and unified optimization interface
• 2012: removal of scipy.maxentropy
• 2013: continuous integration with TravisCI
• 2015: adding Cython interface for BLAS/LAPACK and a benchmark suite
• 2017: adding a unified C API with scipy.LowLevelCallable; removal of scipy.weave
• 2017: SciPy 1.0 release

Pauli Virtanen is SciPy’s Benevolent Dictator For Life (BDFL). He says:

Truthfully speaking, we could have released a SciPy 1.0 a long time ago, so I’m happy we do it now at long last. The project has a long history, and during the years it has matured also as a software project. I believe it has well proved its merit to warrant a version number starting with unity.

Since its conception 15+ years ago, SciPy has largely been written by and for scientists, to provide a box of basic tools that they need. Over time, the set of people active in its development has undergone some rotation, and we have evolved towards a somewhat more systematic approach to development. Regardless, this underlying drive has stayed the same, and I think it will also continue propelling the project forward in future. This is all good, since not long after 1.0 comes 1.1.

Travis Oliphant is one of SciPy’s creators. He says:

I’m honored to write a note of congratulations to the SciPy developers and the entire SciPy community for the release of SciPy 1.0. This release represents a dream of many that has been patiently pursued by a stalwart group of pioneers for nearly 2 decades. Efforts have been broad and consistent over that time from many hundreds of people. From initial discussions to efforts coding and packaging to documentation efforts to extensive conference and community building, the SciPy effort has been a global phenomenon that it has been a privilege to participate in.

The idea of SciPy was already in multiple people’s minds in 1997 when I first joined the Python community as a young graduate student who had just fallen in love with the expressibility and extensibility of Python. The internet was just starting to bringing together like-minded mathematicians and scientists in nascent electronically-connected communities. In 1998, there was a concerted discussion on the matrix-SIG, python mailing list with people like Paul Barrett, Joe Harrington, Perry Greenfield, Paul Dubois, Konrad Hinsen, David Ascher, and others. This discussion encouraged me in 1998 and 1999 to procrastinate my PhD and spend a lot of time writing extension modules to Python that mostly wrapped battle-tested Fortran and C-code making it available to the Python user. This work attracted the help of others like Robert Kern, Pearu Peterson and Eric Jones who joined their efforts with mine in 2000 so that by 2001, the first SciPy release was ready. This was long before Github simplified collaboration and input from others and the “patch” command and email was how you helped a project improve.

Since that time, hundreds of people have spent an enormous amount of time improving the SciPy library and the community surrounding this library has dramatically grown. I stopped being able to participate actively in developing the SciPy library around 2010. Fortunately, at that time, Pauli Virtanen and Ralf Gommers picked up the pace of development supported by dozens of other key contributors such as David Cournapeau, Evgeni Burovski, Josef Perktold, and Warren Weckesser. While I have only been able to admire the development of SciPy from a distance for the past 7 years, I have never lost my love of the project and the concept of community-driven development. I remain driven even now by a desire to help sustain the development of not only the SciPy library but many other affiliated and related open-source projects. I am extremely pleased that SciPy is in the hands of a world-wide community of talented developers who will ensure that SciPy remains an example of how grass-roots, community-driven development can succeed.

Fernando Perez offers a wider community perspective:

The existence of a nascent Scipy library, and the incredible –if tiny by today’s standards– community surrounding it is what drew me into the scientific Python world while still a physics graduate student in 2001. Today, I am awed when I see these tools power everything from high school education to the research that led to the 2017 Nobel Prize in physics.

Don’t be fooled by the 1.0 number: this project is a mature cornerstone of the modern scientific computing ecosystem. I am grateful for the many who have made it possible, and hope to be able to contribute again to it in the future. My sincere congratulations to the whole team!

Highlights of this release

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.

Upgrading and compatibility

There have been a number of deprecations and API changes in this release, which are documented below. 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).

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 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.

Issues closed for 1.0.0

• #2300: scipy.misc.toimage (and therefore imresize) converts to uint32...
• #2347: Several misc.im* functions incorrectly handle 3 or 4-channeled...
• #2442: scipy.misc.pilutil -> scipy.ndimage?
• #2829: Mingw Gfortran on Windows?
• #3154: scipy.misc.imsave creates wrong bitmap header
• #3505: scipy.linalg.lstsq() residual’s help text is a lil strange
• #3808: Is Brent’s method for minimizing the value of a function implemented...
• #4121: Add cdf() method to stats.multivariate_normal
• #4458: scipy.misc.imresize changes image range
• #4575: Docs for L-BFGS-B mention non-existent parameter
• #4893: misc.imsave does not work with file type defined
• #5231: Discrepancies in scipy.optimize.minimize(method=’L-BFGS-B’)
• #5238: Optimal leaf ordering in scipy.cluster.hierarchy.dendrogram
• #5305: Wrong image scaling in scipy/misc/pilutil.py with misc.imsave?
• #5823: test failure in filter_design
• #6061: scipy.stats.spearmanr return values outside range -1 to 1
• #6242: Inconsistency / duplication for imread and imshow, imsave
• #6265: BUG: signal.iirfilter of bandpass type is unstable when high...
• #6370: scipy.optimize.linear_sum_assignment hangs on undefined matrix
• #6417: scipy.misc.imresize converts images to uint8
• #6618: splrep and splprep inconsistent
• #6854: Support PEP 519 in I/O functions
• #6921: [Feature request] Random unitary matrix
• #6930: uniform_filter1d appears to truncate rather than round when output...
• #6949: interp2d function crashes python
• #6959: scipy.interpolate.LSQUnivariateSpline - check for increasing...
• #7005: linear_sum_assignment in scipy.optimize never return if one of...
• #7010: scipy.statsbinned_statistic_2d: incorrect binnumbers returned
• #7049: expm_multiply is excessively slow when called for intervals
• #7050: Documenting _argcheck for rv_discrete
• #7077: coo_matrix.tocsr() still slow
• #7093: Wheels licensing
• #7122: Sketching-based Matrix Computations
• #7133: Discontinuity of a scipy special function
• #7141: Improve documentation for Elliptic Integrals
• #7181: A change in numpy.poly1d is causing the scipy tests to fail.
• #7220: String Formatting Issue in LinearOperator.__init__
• #7239: Source tarball distribution
• #7247: genlaguerre poly1d-object doesn’t respect ‘monic’ option at evaluation
• #7248: BUG: regression in Legendre polynomials on master
• #7316: dgels is missing
• #7381: Krogh interpolation fails to produce derivatives for complex...
• #7416: scipy.stats.kappa4(h,k) raise a ValueError for positive integer...
• #7421: scipy.stats.arcsine().pdf and scipy.stats.beta(0.5, 0.5).pdf...
• #7429: test_matrix_norms() in scipy/linalg/tests/test_basic.py calls...
• #7444: Doc: stats.dirichlet.var output description is wrong
• #7475: Parameter amax in scalar_search_wolfe2 is not used
• #7510: Operations between numpy.array and scipy.sparse matrix return...
• #7550: DOC: signal tutorial: Typo in explanation of convolution
• #7551: stdint.h included in SuperLU header files, but does not exist...
• #7553: Build for master broken on OS X
• #7557: Error in scipy.signal.periodogram example
• #7590: OSX test fail - test_ltisys.TestPlacePoles.test_real
• #7658: optimize.BenchGlobal broken
• #7669: nan result from multivariate_normal.cdf
• #7733: Inconsistent usage of indices, indptr in Delaunay.vertex_neighbor_vertices
• #7747: Numpy changes in np.random.dirichlet cause test failures
• #7772: Fix numpy lstsq rcond= parameter
• #7776: tests require nose
• #7798: contributor names for 1.0 release notes
• #7828: 32-bit Linux test errors on TestCephes
• #7893: scipy.spatial.distance.wminkowski behaviour change in 1.0.0b1
• #7898: DOC: Window functions
• #7959: BUG maybe: fmin_bfgs possibly broken in 1.0
• #7969: scipy 1.0.0rc1 windows wheels depend on missing msvcp140.dll

Pull requests for 1.0.0

• #4978: WIP: add pre_center and normalize options to lombscargle
• #5796: TST: Remove all permanent filter changes from tests
• #5910: ENH: sparse.linalg: add GCROT(m,k)
• #6326: ENH: New ODE solvers
• #6480: ENH: Make signal.decimate default to zero_phase=True
• #6705: ENH: add initial guess to sparse.linalg.lsqr
• #6706: ENH: add initial guess to sparse.linalg.lsmr
• #6769: BUG: optimize: add sufficient descent condition check to CG line...
• #6855: Handle objects supporting PEP 519 in I/O functions
• #6945: MAINT: ckdtree codebase clean up
• #6953: DOC: add a SciPy Project Governance document
• #6998: fix documentation of spearman rank corrcoef
• #7017: ENH: add methods logcdf and cdf to scipy.stats.multivariate_normal
• #7027: Add random unitary matrices
• #7030: ENH: Add strictly-increasing checks for x to 1D splines
• #7031: BUG: Fix linear_sum_assignment hanging on an undefined matrix
• #7041: DOC: Clairfy that windows are DFT-even by default
• #7048: DOC: modified docs for find_peak_cwt. Fixes #6922
• #7056: Fix insufficient precision when calculating spearman/kendall...
• #7057: MAINT: change dtype comparison in optimize.linear_sum_assignment.
• #7059: TST: make Xdist_deprecated_args cover all metrics
• #7061: Fix msvc 9 and 10 compile errors
• #7070: ENH: sparse: optimizing CSR/CSC slicing fast paths
• #7078: ENH: sparse: defer sum_duplicates to csr/csc
• #7079: ENH: sparse: allow subclasses to override specific math operations
• #7081: ENH: sparse: speed up CSR/CSC toarray()
• #7082: MAINT: Add missing PyType_Ready(&SuperLUGlobalType) for Py3
• #7083: Corrected typo in the doc of scipy.linalg.lstsq()
• #7086: Fix bug #7049 causing excessive slowness in expm_multiply
• #7088: Documented _argcheck for rv_discrete
• #7094: MAINT: Fix mistake in PR #7082
• #7098: BF: return NULL from failed Py3 module check
• #7105: MAINT: Customize ?TRSYL call in lyapunov solver
• #7111: Fix error message typo in UnivariateSpline
• #7113: FIX: Add add float to return type in documentation
• #7119: ENH: sparse.linalg: remove _count_nonzero hack
• #7123: ENH: added “interior-point” method for scipy.optimize.linprog
• #7137: DOC: clarify stats.linregress docstring, closes gh-7074
• #7138: DOC: special: Add an example to the airy docstring.
• #7139: DOC: stats: Update stats tutorial
• #7142: BUG: special: prevent segfault in pbwa
• #7143: DOC: special: warn about alternate elliptic integral parameterizations
• #7146: fix docstring of NearestNDInterpolator
• #7148: DOC: special: Add Parameters, Returns and Examples to gamma docstring
• #7152: MAINT: spatial: Remove two unused variables in ckdtree/src/distance.h
• #7153: MAINT: special: remove deprecated variant of gammaln
• #7154: MAINT: Fix some code that generates C compiler warnings
• #7155: DOC: linalg: Add examples for solve_banded and solve_triangular
• #7156: DOC: fix docstring of NearestNDInterpolator
• #7159: BUG: special: fix sign of derivative when x < 0 in pbwa
• #7161: MAINT: interpolate: make Rbf.A array a property
• #7163: MAINT: special: return nan for inaccurate regions of pbwa
• #7165: ENH: optimize: changes to make BFGS implementation more efficient.
• #7166: BUG: Prevent infinite loop in optimize._lsq.trf_linear.py
• #7173: BUG: sparse: return a numpy matrix from _add_dense
• #7179: DOC: Fix an error in sparse argmax docstring
• #7180: MAINT: interpolate: A bit of clean up in interpolate/src/_interpolate.cpp
• #7182: Allow homogeneous coordinate transforms in affine_transform
• #7184: MAINT: Remove hack modifying a readonly attr
• #7185: ENH: Add evaluation of periodic splines #6730
• #7186: MAINT: PPoly: improve error messages for wrong shape/axis
• #7187: DEP: interpolate: deprecate interpolate_wrapper
• #7198: DOC: linalg: Add examples for solveh_banded and solve_toeplitz.
• #7200: DOC: stats: Added tutorial documentation for the generalized...
• #7208: DOC: Added docstrings to issparse/isspmatrix(_...) methods and...
• #7213: DOC: Added examples to circmean, circvar, circstd
• #7215: DOC: Adding examples to scipy.sparse.linalg.... docstrings
• #7223: DOC: special: Add examples for expit and logit.
• #7224: BUG: interpolate: fix integer overflow in fitpack.bispev
• #7225: DOC: update 1.0 release notes for several recent PRs.
• #7226: MAINT: update docs and code for mailing list move to python.org
• #7233: Fix issue #7232: Do not mask exceptions in objective func evaluation
• #7234: MAINT: cluster: cleaning up VQ/k-means code
• #7236: DOC: Fixed typo
• #7238: BUG: fix syntaxerror due to unicode character in trustregion_exact.
• #7243: DOC: Update docstring in misc/pilutil.py
• #7246: DEP: misc: deprecate imported names
• #7249: DOC: Add plotted example to scipy.cluster.vq.kmeans
• #7252: Fix 5231: docs of factr, ftol in sync w/ code
• #7254: ENH: SphericalVoronoi Input Handling
• #7256: fix for issue #7255 - Circular statistics functions give wrong...
• #7263: CI: use python’s faulthandler to ease tracing segfaults
• #7288: ENH: linalg: add subspace_angles function.
• #7290: BUG: stats: Fix spurious warnings in genextreme.
• #7292: ENH: optimize: added trust region method trust-trlib
• #7296: DOC: stats: Add an example to the ttest_ind_from_stats docstring.
• #7297: DOC: signal: Add examples for chirp() and sweep_poly().
• #7299: DOC: Made difference between brent and fminbound clearer
• #7305: Simplify if-statements and constructor calls in integrate._ode
• #7309: Comply with PEP 518.
• #7313: REL: add python_requires to setup.py, fix Python version check.
• #7315: BUG: Fixed bug with Laguerre and Legendre polynomials
• #7320: DOC: clarify meaning of flags in ode.integrate
• #7333: DOC: Add examples to scipy.ndimage.gaussian_filter1d
• #7337: ENH: add n-dimensional DCT and IDCT to fftpack
• #7353: Add _gels functions
• #7357: DOC: linalg: Add examples to the svdvals docstring.
• #7359: Bump Sphinx version to 1.5.5
• #7361: DOC: linalg: Add some ‘See Also’ links among special matrices...
• #7362: TST: Fix some Fedora 25 test failures.
• #7363: DOC: linalg: tweak the docstring example of svd
• #7365: MAINT: fix refguide_check.py for Sphinx >= 1.5
• #7367: BUG: odrpack: fix invalid stride checks in d_lpkbls.f
• #7368: DOC: constants: Add examples to the ‘find’ docstring.
• #7376: MAINT: bundle Mathjax with built docs
• #7377: MAINT: optimize: Better name for trust-region-exact method.
• #7378: Improve wording in tutorial
• #7383: fix KroghInterpolator.derivatives failure with complex input
• #7389: FIX: Copy mutable window in resample_poly
• #7390: DOC: optimize: A few tweaks of the examples in the curve_fit
• #7391: DOC: Add examples to scipy.stats
• #7394: “Weight” is actually mass. Add slugs and slinches/blobs to mass
• #7398: DOC: Correct minor typo in optimize.{brenth,brentq}
• #7401: DOC: zeta only accepts real input
• #7413: BUG: fix error messages in _minimize_trustregion_exact
• #7414: DOC: fix ndimage.distance_transform_bf docstring [ci skip]
• #7415: DOC: fix skew docstring [ci skip]
• #7423: Expand binnumbers with correct dimensions
• #7431: BUG: Extend scipy.stats.arcsine.pdf to endpoints 0 and 1 #7427
• #7432: DOC: Add examples to scipy.cluster.hierarchy
• #7448: ENH: stats: Implement the survival function for pareto.
• #7454: FIX Replaced np.assert_allclose with imported assert_allclose
• #7460: TST: fix integrate.ivp test that fails on 32-bit Python.
• #7461: Doc: Added tutorial documentation for stats distributions ksone
• #7463: DOC: Fix typos and remove trailing whitespace
• #7465: Fix some ndimage.interpolation endianness bugs
• #7468: del redundance in interpolate.py
• #7470: Initialize “info” in minpack_lmdif
• #7478: Added more testing of smirnov/smirnovi functions
• #7479: MAINT: update for new FutureWarning’s in numpy 1.13.0
• #7480: DOC: correctly describe output shape of dirichlet.mean() and...
• #7482: signal.lti: Remove deprecated cross-system properties
• #7484: MAINT: Clean-up uses of np.asarray in ndimage
• #7485: ENH: support any order >=0 in ndimage.gaussian_filter
• #7486: ENH: Support k!=0 for sparse.diagonal()
• #7498: BUG: sparse: pass assumeSortedIndices option to scikit.umfpack
• #7501: ENH: add optimal leaf ordering for linkage matrices
• #7506: MAINT: remove overflow in Metropolis fixes #7495
• #7507: TST: speed up full test suite by less eval points in mpmath tests.
• #7509: BUG: fix issue when using python setup.py somecommand --force.
• #7511: fix some alerts found with lgtm
• #7514: Add explanation what the integer returned mean.
• #7516: BUG: Fix roundoff errors in ndimage.uniform_filter1d.
• #7517: TST: fix signal.convolve test that was effectively being skipped.
• #7523: ENH: linalg: allow lstsq to work with 0-shaped arrays
• #7525: TST: Warning cleanup
• #7526: DOC: params in ndimage.interpolation functions not optional
• #7527: MAINT: Encapsulate error message handling in NI_LineBuffer.
• #7528: MAINT: Remove ndimage aliases for NPY_MAXDIMS.
• #7529: MAINT: Remove NI_(UN)LIKELY macros in favor of numpy ones.
• #7537: MAINT: Use accessor function for numpy array internals
• #7541: MAINT: Remove some uses of Numarray types in ndimage.
• #7543: MAINT: Replace all NumarrayTypes uses in ni_fourier.c
• #7544: MAINT: Replace all uses of NumarrayTypes in ni_interpolation.c
• #7545: MAINT: Replace all uses of NumarrayTypes in ni_measure.c
• #7546: MAINT: Replace all uses of NumarrayTypes in ni_morphology.c
• #7548: DOC: make a note in benchmarks README on how to run without rebuilding.
• #7549: MAINT: Get rid of NumarrayTypes.
• #7552: TST: Fix new warnings -> error bugs found on OSX
• #7554: Update superlu to 5.2.1 + fix stdint.h issue on MSVC
• #7556: MAINT: Fix some types from #7549 + miscellaneous warnings.
• #7558: MAINT: Use correct #define NO_IMPORT_ARRAY, not NO_ARRAY_IMPORT...
• #7562: BUG: Copy import_nose from numpy.
• #7563: ENH: Add the first Wasserstein and the Cramér-von Mises statistical...
• #7568: Test janitoring
• #7571: Test janitoring pt. 2
• #7572: Pytestifying
• #7574: TST: Remove ignore warnings filters from stats
• #7577: MAINT: Remove unused code in ndimage/ni_measure.c and .h
• #7578: TST: Remove ignore warnings filters from sparse, clean up warning...
• #7581: BUG: properly deallocate memory from PyArray_IntpConverter.
• #7582: DOC: signal tutorial: Typo in explanation of convolution
• #7583: Remove remaining ignore warnings filters
• #7586: DOC: add note to HACKING.rst on where to find build docs.
• #7587: DOC: Add examples to scipy.optimize
• #7594: TST: Add tests for ndimage converter functions.
• #7596: Added a sanity check to signal.savgol_filter
• #7599: _upfirdn_apply stopping condition bugfix
• #7601: MAINT: special: remove sph_jn et al.
• #7602: TST: fix test failures in trimmed statistics tests with numpy...
• #7605: Be clear about required dimension order
• #7606: MAINT: Remove unused function NI_NormalizeType.
• #7607: TST: add osx to travis matrix
• #7608: DOC: improve HACKING guide - mention reviewing PRs as contribution.
• #7609: MAINT: Remove unnecessary warning filter by avoding unnecessary...
• #7610: #7557 : fix example code in periodogram
• #7611: #7220 : fix TypeError while raising ValueError for invalid shape
• #7612: Convert yield tests to pytest parametrized tests
• #7613: Add distributor init file
• #7614: fixup header
• #7615: BUG: sparse: Fix assignment w/ non-canonical sparse argument
• #7617: DOC: Clarify digital filter functions
• #7619: ENH: scipy.sparse.spmatrix.astype: casting and copy parameter...
• #7621: Expose VODE/ZVODE/LSODE IDID return code to user
• #7622: MAINT: special: remove out-of-date comment for ellpk
• #7625: TST: Add a test for “ignore” warning filters
• #7628: MAINT: refactoring and cleaning distance.py/.c/.h
• #7629: DEP: deprecate args usage in xdist
• #7630: ENH: weighted metrics
• #7634: Follow-up to #6855
• #7635: interpolate.splprep: Test some error cases, give slightly better...
• #7642: Add an example to interpolate.lagrange
• #7643: ENH: Added wrappers for LAPACK <s,d>stev
• #7649: Fix #7636, add PEP 519 test coverage to remaining I/O functions
• #7650: DOC: signal: Add ‘Examples’ to the docstring for sosfiltfilt.
• #7651: Fix up ccache usage on Travis + try enabling on OSX
• #7653: DOC: transition of examples from 2 to 3. Closes #7366
• #7659: BENCH: fix optimize.BenchGlobal. Closes gh-7658.
• #7662: CI: speed up continuous integration builds
• #7664: Update odr documentation
• #7665: BUG: wolfe2 line/scalar search now uses amax parameter
• #7671: MAINT: _lib/ccallback.h: PyCapsule_GetName returns const char*
• #7672: TST: interpolate: test integrating periodic b-splines against...
• #7674: Tests tuning
• #7675: CI: move refguide-check to faster build
• #7676: DOC: bump scipy-sphinx-theme to fix copybutton.js
• #7678: Note the zero-padding of the results of splrep and splprep
• #7681: MAINT: _lib: add user-overridable available memory determination
• #7684: TST: linalg: explicitly close opened npz files
• #7686: MAINT: remove unnecessary shebang lines and executable bits
• #7687: BUG: stats: don’t emit invalid warnings if moments are infinite
• #7690: ENH: allow int-like parameters in several routines
• #7691: DOC: Drop non-working source links from docs
• #7694: fix ma.rray to ma.array in func median_cihs
• #7698: BUG: stats: fix nan result from multivariate_normal.cdf (#7669)
• #7703: DOC: special: Update the docstrings for noncentral F functions.
• #7709: BLD: integrate: avoid symbol clash between lsoda and vode
• #7711: TST: _lib: make test_parallel_threads to not fail falsely
• #7712: TST: stats: bump test tolerance in TestMultivariateNormal.test_broadcasting
• #7715: MAINT: fix deprecated use of numpy.issubdtype
• #7716: TST: integrate: drop timing tests
• #7717: MAINT: mstats.winsorize inclusion bug fix
• #7719: DOC: stats: Add a note about the special cases of the rdist distribution.
• #7720: DOC: Add example and math to stats.pearsonr
• #7723: DOC: Added Mann-Whitney U statistic reference
• #7727: BUG: special/cdflib: deal with nan and nonfinite inputs
• #7728: BLD: spatial: fix ckdtree depends header list
• #7732: BLD: update Bento build for optimal_leaf_ordering addition
• #7734: DOC: signal: Copy-edit and add examples to the Kaiser-related...
• #7736: BUG: Fixes #7735: Prevent integer overflow in concatenated index...
• #7737: DOC: rename indices/indptr for spatial.Delaunay vertex_neighbor_vertices
• #7738: ENH: Speed up freqz computation
• #7739: TST: ignore ncfdtridfn failure in win32 and warn on FPU mode changes
• #7740: Fix overflow in Anderson-Darling k-sample test
• #7742: TST: special: limit expm1 mpmath comparison range
• #7748: TST: stats: don’t pass invalid alpha to np.random.dirichlet
• #7749: BUG/DOC: optimize: method is ‘interior-point’, not ‘interior...
• #7751: BUG: optimize: show_options('linprog', method='interior-point')...
• #7753: ENH: io: easier syntax for FortranFile read/write of mixed records
• #7754: BLD: add _lib._fpumode extension to Bento build.
• #7756: DOC: Show probability density functions as math
• #7757: MAINT: remove outdated OS X build scripts. Fixes pytest failure.
• #7758: MAINT: stats: pep8, wrap lines
• #7760: DOC: special: add instructions on how to add special functions
• #7761: DOC: allow specifing Python version for Sphinx makefile
• #7765: TST: fix test coverage of mstats_extras.py
• #7767: DOC: update 1.0 release notes.
• #7768: DOC: update notes on how to release. Also change paver file to...
• #7769: Add the _sf and _logsf function for planck dist
• #7770: DOC: Replace rotten links in the docstring of minres
• #7771: MAINT: f2py build output cleanup
• #7773: DOC: optimize: Some copy-editing of linprog docs.
• #7774: MAINT: set rcond explicitly for np.linalg.lstsq calls
• #7777: remove leftover nose imports
• #7780: ENH: Wrap LAPACK’s dsytrd
• #7781: DOC: Link rfft
• #7782: MAINT: run pyx autogeneration in cythonize & remove autogen files
• #7783: FIX: Disallow Wn==1 in digital filters
• #7790: Fix test errors introduced by gh-5910
• #7792: MAINT: fix syntax in pyproject.toml
• #7809: ENH: sketches - Clarkson Woodruff Transform
• #7810: ENH: Add eig(vals)_tridiagonal
• #7811: BUG: stats: Fix warnings in binned_statistics_dd
• #7814: ENH: signal: Replace ‘nyq’ and ‘Hz’ arguments with ‘fs’.
• #7820: DOC: update 1.0 release notes and mailmap
• #7823: BUG: memory leak in messagestream / qhull.pyx
• #7830: DOC: linalg: Add an example to the lstsq docstring.
• #7835: ENH: Automatic FIR order for decimate
• #7838: MAINT: stats: Deprecate frechet_l and frechet_r.
• #7841: slsqp PEP8 formatting fixes, typos, etc.
• #7843: ENH: Wrap all BLAS routines
• #7844: DOC: update LICENSE.txt with licenses of bundled libs as needed.
• #7851: ENH: Add wrappers for ?GGLSE, ?(HE/SY)CON, ?SYTF2, ?(HE/SY)TRF
• #7856: ENH: added out argument to Xdist
• #7858: BUG: special/cdflib: fix fatal loss of precision issues in cumfnc
• #7859: FIX: Squash place_poles warning corner case
• #7861: dummy statement for undefined WITH_THREAD
• #7863: MAINT: add license texts to binary distributions
• #7866: DOC, MAINT: fix links in the doc
• #7867: DOC: fix up descriptions of pdf’s in distribution docstrings.
• #7869: DEP: deprecate misc.pilutil functions
• #7870: DEP: remove deprecated functions
• #7872: TST: silence RuntimeWarning for stats.truncnorm test marked as...
• #7874: TST: fix an optimize.linprog test that fails intermittently.
• #7875: TST: filter two integration warnings in stats tests.
• #7876: GEN: Add comments to the tests for clarification
• #7891: ENH: backport #7879 to 1.0.x
• #7902: MAINT: signal: Make freqz handling of multidim. arrays match...
• #7905: REV: restore wminkowski
• #7908: FIX: Avoid bad __del__ (close) behavior
• #7918: TST: mark two optimize.linprog tests as xfail. See gh-7877.
• #7929: MAINT: changed defaults to lower in sytf2, sytrf and hetrf
• #7939: Fix umfpack solver construction for win-amd64
• #7948: DOC: add note on checking for deprecations before upgrade to...
• #7952: DOC: update SciPy Roadmap for 1.0 release and recent discussions.
• #7960: BUG: optimize: revert changes to bfgs in gh-7165
• #7962: TST: special: mark a failing hyp2f1 test as xfail
• #7973: BUG: fixed keyword in ‘info’ in _get_mem_available utility
• #8001: TST: fix test failures from Matplotlib 2.1 update
• #8010: BUG: signal: fix crash in lfilter
• #8019: MAINT: fix test failures with NumPy master