From: Ralf Gommers ralf.gommers@gmail.com

Subject: [Numpy-discussion] SciPy 1.0 released!

Date: October 25, 2017 at 03:14:07 PDT

To: SciPy Developers List scipy-dev@python.org, SciPy Users List scipy-user@python.org, Discussion of Numerical Python numpy-discussion@python.org, python-announce-list@python.org

Reply-To: Discussion of Numerical Python numpy-discussion@python.orgHi all,

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 Virtanenis 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 Oliphantis 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 Perezoffers 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`

improvementsN-dimensional versions of the discrete sine and cosine transforms and their

inverses were added as`dctn`

,`idctn`

,`dstn`

and`idstn`

.

`scipy.integrate`

improvementsA 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`

improvementsThe 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`

improvementsSupport 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`

improvementsThe 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`

improvementsAn 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`

improvementsIterating 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`

improvementsA 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`

improvementsMany 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`

improvementsThe 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 <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.Cheers,

Ralf

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# [Numpy-discussion] SciPy 1.0 released!

**christie**(Christie Koehler) #1