Hi all,
It is almost 6 months after the 1.1.0 release on May 5, so probably time to
plan the 1.2.0 release. It would be a good idea to look over the PRs with a
1.2.0 milestone
<https://github.com/scipy/scipy/pulls?q=is%3Aopen+is%3Apr+milestone%3A1.2.0>,
and tag anything else that should have this milestone appropriately.
I'd like to propose the following schedule:
Nov. 5: branch 1.2.x
Nov. 8: rc1
Nov. 21: rc2 (if needed)
Nov. 30: final release
Thoughts?
Best wishes,
Tyler

Hi all,
TL;DR, let's write the long journal paper on SciPy that we've wanted for a
while, let's form a small committee to coordinate, and get it out the door
in 2-3 months.
Motivation
---------------
(credits for most of this text: Evgeni)
Many scipy contributors' day jobs are in academia. Bibliometry -- papers in
refereed journals and citations of papers by other papers -- is one of the
main
performance indicators in most academic establishments. Since we do not
generate papers, scipy contributions are all but invisible for the purposes
of a
contributor's annual report. Of course, details vary wildly; in many cases a
contributor manages to balance their time, or to argue common sense with
their
superiors, or get an approval for scipy work, or just ignores the issue
altogether -- but sooner or later there is a form to be filled or boxes to
be
checked, and scipy contributions simply do not fit in. A peer-reviewed
journal paper on scipy will help contributors get the academic credit they
deserve.
We can write *the* paper for SciPy 1.0, with overall project structure,
goals, etc., and for specific features/modules a focus on say the last 3
years.
History
----------
For SciPy 1.0 we had three targets on the publicity/credits front: an
interesting release announcement, interesting blogs/stories (NumFOCUS blog,
Hacker News, etc.) and a paper. We didn't have the bandwidth for a paper in
the end, the rest was successful.
[1] is a previous announcement on this list about writing (a) paper(s) on
SciPy. We wanted both "short papers" to cover one or two releases (target
journal JOSS) and a full paper as the authoritative reference for SciPy.
We had an earlier attempt for a "short paper", it's mostly written but has
stalled (see [2]). We ran out of steam on that one. To avoid that this time
around, it would be good to have a clear public plan, target dates, and a
small committee rather than one person to drive things forward.
Proposal
------------
Here's a proposal for all aspects of this exercise that I can think about
now. Some parts stolen from the AstroPy paper [3] (because their process
worked quite well).
Form a small coordination committee of 3-5 people that set up the paper
structure, move things along when parts stall, propose/take decisions as
needed, invite co-authors, and organise paper submission/rework.
Paper writing to be done by whoever volunteers for a section, not just the
coordination committee. First outline/structure to be done by committee,
which then asks for review of structure and volunteers for section writing.
Scope: a 6-10 page paper, covering history, package scope and structure,
community/organisational aspects, key features and recent enhancements per
module, and roadmap.
Authorship: anyone who made a substantial contribution in the history of
the project. Here "substantial" is interpreted as anything beyond a
one-line doc fix. Rationale: better to be too inclusive than exclusive.
Sign-up via a web form, we send the link to that form to all email
addresses in the commit history till v1.0.
Author order (details tbd by committee):
1. The SciPy Developers
2. Maintainers, paper writers, other key contributors - in order of
contribution level
3. All other authors - alphabetically ordered
Submission target: mid-April, to either PeerJ Computer Science or Journal
of Open Research Software (tbd by committee).
Comments? Volunteers for committee?
References
----------------
[1] https://mail.python.org/pipermail/scipy-dev/2016-August/021474.html
[2] https://github.com/scipy/scipy-articles/pull/4
[3] https://github.com/astropy/astropy-v2.0-paper
Cheers,
Ralf

-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA256
Hi all,
On behalf of the SciPy development team I'm pleased to announce
the release of SciPy 1.2.0. This is an LTS release and the
last to support Python 2.7.
Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at:
https://github.com/scipy/scipy/releases/tag/v1.2.0
One of a few ways to install this release with pip:
pip install scipy==1.2.0
==========================
SciPy 1.2.0 Release Notes
==========================
SciPy 1.2.0 is the culmination of 6 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
1.2.x branch, and on adding new features on the master branch.
This release requires Python 2.7 or 3.4+ and NumPy 1.8.2 or greater.
Note: This will be the last SciPy release to support Python 2.7.
Consequently, the 1.2.x series will be a long term support (LTS)
release; we will backport bug fixes until 1 Jan 2020.
For running on PyPy, PyPy3 6.0+ and NumPy 1.15.0 are required.
Highlights of this release
---------------------------
- 1-D root finding improvements with a new solver, ``toms748``, and a new
unified interface, ``root_scalar``
- New ``dual_annealing`` optimization method that combines stochastic and
local deterministic searching
- A new optimization algorithm, ``shgo`` (simplicial homology
global optimization) for derivative free optimization problems
- A new category of quaternion-based transformations are available in
`scipy.spatial.transform`
New features
============
`scipy.ndimage` improvements
---------------------------------
Proper spline coefficient calculations have been added for the ``mirror``,
``wrap``, and ``reflect`` modes of `scipy.ndimage.rotate`
`scipy.fftpack` improvements
---------------------------------
DCT-IV, DST-IV, DCT-I, and DST-I orthonormalization are now supported in
`scipy.fftpack`.
`scipy.interpolate` improvements
---------------------------------
`scipy.interpolate.pade` now accepts a new argument for the order of the
numerator
`scipy.cluster` improvements
-----------------------------
`scipy.cluster.vq.kmeans2` gained a new initialization method, kmeans++.
`scipy.special` improvements
-----------------------------
The function ``softmax`` was added to `scipy.special`.
`scipy.optimize` improvements
------------------------------
The one-dimensional nonlinear solvers have been given a unified interface
`scipy.optimize.root_scalar`, similar to the `scipy.optimize.root` interface
for multi-dimensional solvers. ``scipy.optimize.root_scalar(f, bracket=[a
,b],
method="brenth")`` is equivalent to ``scipy.optimize.brenth(f, a ,b)``. If
no
``method`` is specified, an appropriate one will be selected based upon the
bracket and the number of derivatives available.
The so-called Algorithm 748 of Alefeld, Potra and Shi for root-finding
within
an enclosing interval has been added as `scipy.optimize.toms748`. This
provides
guaranteed convergence to a root with convergence rate per function
evaluation
of approximately 1.65 (for sufficiently well-behaved functions.)
``differential_evolution`` now has the ``updating`` and ``workers``
keywords.
The first chooses between continuous updating of the best solution vector
(the
default), or once per generation. Continuous updating can lead to faster
convergence. The ``workers`` keyword accepts an ``int`` or map-like
callable,
and parallelises the solver (having the side effect of updating once per
generation). Supplying an ``int`` evaluates the trial solutions in N
parallel
parts. Supplying a map-like callable allows other parallelisation approaches
(such as ``mpi4py``, or ``joblib``) to be used.
``dual_annealing`` (and ``shgo`` below) is a powerful new general purpose
global optizimation (GO) algorithm. ``dual_annealing`` uses two annealing
processes to accelerate the convergence towards the global minimum of an
objective mathematical function. The first annealing process controls the
stochastic Markov chain searching and the second annealing process controls
the
deterministic minimization. So, dual annealing is a hybrid method that takes
advantage of stochastic and local deterministic searching in an efficient
way.
``shgo`` (simplicial homology global optimization) is a similar algorithm
appropriate for solving black box and derivative free optimization (DFO)
problems. The algorithm generally converges to the global solution in finite
time. The convergence holds for non-linear inequality and
equality constraints. In addition to returning a global minimum, the
algorithm also returns any other global and local minima found after every
iteration. This makes it useful for exploring the solutions in a domain.
`scipy.optimize.newton` can now accept a scalar or an array
``MINPACK`` usage is now thread-safe, such that ``MINPACK`` + callbacks may
be used on multiple threads.
`scipy.signal` improvements
----------------------------
Digital filter design functions now include a parameter to specify the
sampling
rate. Previously, digital filters could only be specified using normalized
frequency, but different functions used different scales (e.g. 0 to 1 for
``butter`` vs 0 to π for ``freqz``), leading to errors and confusion. With
the ``fs`` parameter, ordinary frequencies can now be entered directly into
functions, with the normalization handled internally.
``find_peaks`` and related functions no longer raise an exception if the
properties of a peak have unexpected values (e.g. a prominence of 0). A
``PeakPropertyWarning`` is given instead.
The new keyword argument ``plateau_size`` was added to ``find_peaks``.
``plateau_size`` may be used to select peaks based on the length of the
flat top of a peak.
``welch()`` and ``csd()`` methods in `scipy.signal` now support calculation
of a median average PSD, using ``average='mean'`` keyword
`scipy.sparse` improvements
----------------------------
The `scipy.sparse.bsr_matrix.tocsr` method is now implemented directly
instead
of converting via COO format, and the `scipy.sparse.bsr_matrix.tocsc` method
is now also routed via CSR conversion instead of COO. The efficiency of both
conversions is now improved.
The issue where SuperLU or UMFPACK solvers crashed on matrices with
non-canonical format in `scipy.sparse.linalg` was fixed. The solver wrapper
canonicalizes the matrix if necessary before calling the SuperLU or UMFPACK
solver.
The ``largest`` option of `scipy.sparse.linalg.lobpcg()` was fixed to have
a correct (and expected) behavior. The order of the eigenvalues was made
consistent with the ARPACK solver (``eigs()``), i.e. ascending for the
smallest eigenvalues, and descending for the largest eigenvalues.
The `scipy.sparse.random` function is now faster and also supports integer
and
complex values by passing the appropriate value to the ``dtype`` argument.
`scipy.spatial` improvements
-----------------------------
The function `scipy.spatial.distance.jaccard` was modified to return 0
instead
of ``np.nan`` when two all-zero vectors are compared.
Support for the Jensen Shannon distance, the square-root of the divergence,
has
been added under `scipy.spatial.distance.jensenshannon`
An optional keyword was added to the function
`scipy.spatial.cKDTree.query_ball_point()` to sort or not sort the returned
indices. Not sorting the indices can speed up calls.
A new category of quaternion-based transformations are available in
`scipy.spatial.transform`, including spherical linear interpolation of
rotations (``Slerp``), conversions to and from quaternions, Euler angles,
and general rotation and inversion capabilities
(`spatial.transform.Rotation`), and uniform random sampling of 3D
rotations (`spatial.transform.Rotation.random`).
`scipy.stats` improvements
---------------------------
The Yeo-Johnson power transformation is now supported (``yeojohnson``,
``yeojohnson_llf``, ``yeojohnson_normmax``, ``yeojohnson_normplot``). Unlike
the Box-Cox transformation, the Yeo-Johnson transformation can accept
negative
values.
Added a general method to sample random variates based on the density only,
in
the new function ``rvs_ratio_uniforms``.
The Yule-Simon distribution (``yulesimon``) was added -- this is a new
discrete probability distribution.
``stats`` and ``mstats`` now have access to a new regression method,
``siegelslopes``, a robust linear regression algorithm
`scipy.stats.gaussian_kde` now has the ability to deal with weighted
samples,
and should have a modest improvement in performance
Levy Stable Parameter Estimation, PDF, and CDF calculations are now
supported
for `scipy.stats.levy_stable`.
The Brunner-Munzel test is now available as ``brunnermunzel`` in ``stats``
and ``mstats``
`scipy.linalg` improvements
---------------------------
`scipy.linalg.lapack` now exposes the LAPACK routines using the Rectangular
Full Packed storage (RFP) for upper triangular, lower triangular, symmetric,
or Hermitian matrices; the upper trapezoidal fat matrix RZ decomposition
routines are now available as well.
Deprecated features
===================
The functions ``hyp2f0``, ``hyp1f2`` and ``hyp3f0`` in ``scipy.special``
have
been deprecated.
Backwards incompatible changes
==============================
LAPACK version 3.4.0 or later is now required. Building with
Apple Accelerate is no longer supported.
The function ``scipy.linalg.subspace_angles(A, B)`` now gives correct
results for all angles. Before this, the function only returned
correct values for those angles which were greater than pi/4.
Support for the Bento build system has been removed. Bento has not been
maintained for several years, and did not have good Python 3 or wheel
support,
hence it was time to remove it.
The required signature of `scipy.optimize.lingprog` ``method=simplex``
callback function has changed. Before iteration begins, the simplex solver
first converts the problem into a standard form that does not, in general,
have the same variables or constraints
as the problem defined by the user. Previously, the simplex solver would
pass a
user-specified callback function several separate arguments, such as the
current solution vector ``xk``, corresponding to this standard form problem.
Unfortunately, the relationship between the standard form problem and the
user-defined problem was not documented, limiting the utility of the
information passed to the callback function.
In addition to numerous bug fix changes, the simplex solver now passes a
user-specified callback function a single ``OptimizeResult`` object
containing
information that corresponds directly to the user-defined problem. In future
releases, this ``OptimizeResult`` object may be expanded to include
additional
information, such as variables corresponding to the standard-form problem
and
information concerning the relationship between the standard-form and
user-defined problems.
The implementation of `scipy.sparse.random` has changed, and this affects
the
numerical values returned for both ``sparse.random`` and ``sparse.rand`` for
some matrix shapes and a given seed.
`scipy.optimize.newton` will no longer use Halley's method in cases where it
negatively impacts convergence
Other changes
=============
Authors
=======
* @endolith
* @luzpaz
* Hameer Abbasi +
* akahard2dj +
* Anton Akhmerov
* Joseph Albert
* alexthomas93 +
* ashish +
* atpage +
* Blair Azzopardi +
* Yoshiki Vázquez Baeza
* Bence Bagi +
* Christoph Baumgarten
* Lucas Bellomo +
* BH4 +
* Aditya Bharti
* Max Bolingbroke
* François Boulogne
* Ward Bradt +
* Matthew Brett
* Evgeni Burovski
* Rafał Byczek +
* Alfredo Canziani +
* CJ Carey
* Lucía Cheung +
* Poom Chiarawongse +
* Jeanne Choo +
* Robert Cimrman
* Graham Clenaghan +
* cynthia-rempel +
* Johannes Damp +
* Jaime Fernandez del Rio
* Dowon +
* emmi474 +
* Stefan Endres +
* Thomas Etherington +
* Piotr Figiel
* Alex Fikl +
* fo40225 +
* Joseph Fox-Rabinovitz
* Lars G
* Abhinav Gautam +
* Stiaan Gerber +
* C.A.M. Gerlach +
* Ralf Gommers
* Todd Goodall
* Lars Grueter +
* Sylvain Gubian +
* Matt Haberland
* David Hagen
* Will Handley +
* Charles Harris
* Ian Henriksen
* Thomas Hisch +
* Theodore Hu
* Michael Hudson-Doyle +
* Nicolas Hug +
* jakirkham +
* Jakob Jakobson +
* James +
* Jan Schlüter
* jeanpauphilet +
* josephmernst +
* Kai +
* Kai-Striega +
* kalash04 +
* Toshiki Kataoka +
* Konrad0 +
* Tom Krauss +
* Johannes Kulick
* Lars Grüter +
* Eric Larson
* Denis Laxalde
* Will Lee +
* Katrin Leinweber +
* Yin Li +
* P. L. Lim +
* Jesse Livezey +
* Duncan Macleod +
* MatthewFlamm +
* Nikolay Mayorov
* Mike McClurg +
* Christian Meyer +
* Mark Mikofski
* Naoto Mizuno +
* mohmmadd +
* Nathan Musoke
* Anju Geetha Nair +
* Andrew Nelson
* Ayappan P +
* Nick Papior
* Haesun Park +
* Ronny Pfannschmidt +
* pijyoi +
* Ilhan Polat
* Anthony Polloreno +
* Ted Pudlik
* puenka
* Eric Quintero
* Pradeep Reddy Raamana +
* Vyas Ramasubramani +
* Ramon Viñas +
* Tyler Reddy
* Joscha Reimer
* Antonio H Ribeiro
* richardjgowers +
* Rob +
* robbystk +
* Lucas Roberts +
* rohan +
* Joaquin Derrac Rus +
* Josua Sassen +
* Bruce Sharpe +
* Max Shinn +
* Scott Sievert
* Sourav Singh
* Strahinja Lukić +
* Kai Striega +
* Shinya SUZUKI +
* Mike Toews +
* Piotr Uchwat
* Miguel de Val-Borro +
* Nicky van Foreest
* Paul van Mulbregt
* Gael Varoquaux
* Pauli Virtanen
* Stefan van der Walt
* Warren Weckesser
* Joshua Wharton +
* Bernhard M. Wiedemann +
* Eric Wieser
* Josh Wilson
* Tony Xiang +
* Roman Yurchak +
* Roy Zywina +
A total of 137 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 1.2.0
------------------------
* `#9520 <https://github.com/scipy/scipy/issues/9520>`__: signal.correlate
with method='fft' doesn't benefit from long...
* `#9547 <https://github.com/scipy/scipy/issues/9547>`__: signature of
dual_annealing doesn't match other optimizers
* `#9540 <https://github.com/scipy/scipy/issues/9540>`__: SciPy v1.2.0rc1
cannot be imported on Python 2.7.15
* `#1240 <https://github.com/scipy/scipy/issues/1240>`__: Allowing
multithreaded use of minpack through scipy.optimize...
* `#1432 <https://github.com/scipy/scipy/issues/1432>`__: scipy.stats.mode
extremely slow (Trac #905)
* `#3372 <https://github.com/scipy/scipy/issues/3372>`__: Please add Sphinx
search field to online scipy html docs
* `#3678 <https://github.com/scipy/scipy/issues/3678>`__:
_clough_tocher_2d_single direction between centroids
* `#4174 <https://github.com/scipy/scipy/issues/4174>`__: lobpcg "largest"
option invalid?
* `#5493 <https://github.com/scipy/scipy/issues/5493>`__: anderson_ksamp
p-values>1
* `#5743 <https://github.com/scipy/scipy/issues/5743>`__: slsqp fails to
detect infeasible problem
* `#6139 <https://github.com/scipy/scipy/issues/6139>`__:
scipy.optimize.linprog failed to find a feasible starting point...
* `#6358 <https://github.com/scipy/scipy/issues/6358>`__: stats: docstring
for `vonmises_line` points to `vonmises_line`...
* `#6498 <https://github.com/scipy/scipy/issues/6498>`__: runtests.py is
missing in pypi distfile
* `#7426 <https://github.com/scipy/scipy/issues/7426>`__:
scipy.stats.ksone(n).pdf(x) returns nan for positive values of...
* `#7455 <https://github.com/scipy/scipy/issues/7455>`__:
scipy.stats.ksone.pdf(2,x) return incorrect values for x near...
* `#7456 <https://github.com/scipy/scipy/issues/7456>`__:
scipy.special.smirnov and scipy.special.smirnovi have accuracy...
* `#7492 <https://github.com/scipy/scipy/issues/7492>`__:
scipy.special.kolmogorov(x)/kolmogi(p) inefficient, inaccurate...
* `#7914 <https://github.com/scipy/scipy/issues/7914>`__: TravisCI not
failing when it should for -OO run
* `#8064 <https://github.com/scipy/scipy/issues/8064>`__: linalg.solve test
crashes on Windows
* `#8212 <https://github.com/scipy/scipy/issues/8212>`__: LAPACK
Rectangular Full Packed routines
* `#8256 <https://github.com/scipy/scipy/issues/8256>`__:
differential_evolution bug converges to wrong results in complex...
* `#8443 <https://github.com/scipy/scipy/issues/8443>`__: Deprecate
`hyp2f0`, `hyp1f2`, and `hyp3f0`?
* `#8452 <https://github.com/scipy/scipy/issues/8452>`__: DOC: ARPACK
tutorial has two conflicting equations
* `#8680 <https://github.com/scipy/scipy/issues/8680>`__: scipy fails
compilation when building from source
* `#8686 <https://github.com/scipy/scipy/issues/8686>`__: Division by zero
in _trustregion.py when x0 is exactly equal...
* `#8700 <https://github.com/scipy/scipy/issues/8700>`__: _MINPACK_LOCK not
held when calling into minpack from least_squares
* `#8786 <https://github.com/scipy/scipy/issues/8786>`__: erroneous moment
values for t-distribution
* `#8791 <https://github.com/scipy/scipy/issues/8791>`__: Checking COLA
condition in istft should be optional (or omitted)
* `#8843 <https://github.com/scipy/scipy/issues/8843>`__: imresize cannot
be deprecated just yet
* `#8844 <https://github.com/scipy/scipy/issues/8844>`__: Inverse Wishart
Log PDF Incorrect for Non-diagonal Scale Matrix?
* `#8878 <https://github.com/scipy/scipy/issues/8878>`__: vonmises and
vonmises_line in stats: vonmises wrong and superfluous?
* `#8895 <https://github.com/scipy/scipy/issues/8895>`__: v1.1.0
`ndi.rotate` documentation – reused parameters not filled...
* `#8900 <https://github.com/scipy/scipy/issues/8900>`__: Missing complex
conjugation in scipy.sparse.linalg.LinearOperator
* `#8904 <https://github.com/scipy/scipy/issues/8904>`__: BUG: if zero
derivative at root, then Newton fails with RuntimeWarning
* `#8911 <https://github.com/scipy/scipy/issues/8911>`__:
make_interp_spline bc_type incorrect input interpretation
* `#8942 <https://github.com/scipy/scipy/issues/8942>`__: MAINT: Refactor
`_linprog.py` and `_linprog_ip.py` to remove...
* `#8947 <https://github.com/scipy/scipy/issues/8947>`__: np.int64 in
scipy.fftpack.next_fast_len
* `#9020 <https://github.com/scipy/scipy/issues/9020>`__: BUG:
linalg.subspace_angles gives wrong results
* `#9033 <https://github.com/scipy/scipy/issues/9033>`__:
scipy.stats.normaltest sometimes gives incorrect returns b/c...
* `#9036 <https://github.com/scipy/scipy/issues/9036>`__: Bizarre times for
`scipy.sparse.rand` function with 'low' density...
* `#9044 <https://github.com/scipy/scipy/issues/9044>`__:
optimize.minimize(method=`trust-constr`) result dict does not...
* `#9071 <https://github.com/scipy/scipy/issues/9071>`__: doc/linalg: add
cho_solve_banded to see also of cholesky_banded
* `#9082 <https://github.com/scipy/scipy/issues/9082>`__: eigenvalue
sorting in scipy.sparse.linalg.eigsh
* `#9086 <https://github.com/scipy/scipy/issues/9086>`__:
signaltools.py:491: FutureWarning: Using a non-tuple sequence...
* `#9091 <https://github.com/scipy/scipy/issues/9091>`__:
test_spline_filter failure on 32-bit
* `#9122 <https://github.com/scipy/scipy/issues/9122>`__: Typo on scipy
minimization tutorial
* `#9135 <https://github.com/scipy/scipy/issues/9135>`__: doc error at
https://docs.scipy.org/doc/scipy/reference/tutorial/stats/discrete_poisson.…
* `#9167 <https://github.com/scipy/scipy/issues/9167>`__: DOC: BUG: typo in
ndimage LowLevelCallable tutorial example
* `#9169 <https://github.com/scipy/scipy/issues/9169>`__: truncnorm does
not work if b < a in scipy.stats
* `#9250 <https://github.com/scipy/scipy/issues/9250>`__:
scipy.special.tests.test_mpmath::TestSystematic::test_pcfw fails...
* `#9259 <https://github.com/scipy/scipy/issues/9259>`__: rv.expect() ==
rv.mean() is false for rv.mean() == nan (and inf)
* `#9286 <https://github.com/scipy/scipy/issues/9286>`__: DOC: Rosenbrock
expression in optimize.minimize tutorial
* `#9316 <https://github.com/scipy/scipy/issues/9316>`__: SLSQP fails in
nested optimization
* `#9337 <https://github.com/scipy/scipy/issues/9337>`__:
scipy.signal.find_peaks key typo in documentation
* `#9345 <https://github.com/scipy/scipy/issues/9345>`__: Example from
documentation of scipy.sparse.linalg.eigs raises...
* `#9383 <https://github.com/scipy/scipy/issues/9383>`__: Default value for
"mode" in "ndimage.shift"
* `#9419 <https://github.com/scipy/scipy/issues/9419>`__: dual_annealing
off by one in the number of iterations
* `#9442 <https://github.com/scipy/scipy/issues/9442>`__: Error in
Defintion of Rosenbrock Function
* `#9453 <https://github.com/scipy/scipy/issues/9453>`__: TST:
test_eigs_consistency() doesn't have consistent results
Pull requests for 1.2.0
------------------------
* `#9526 <https://github.com/scipy/scipy/pull/9526>`__: TST: relax
precision requirements in signal.correlate tests
* `#9507 <https://github.com/scipy/scipy/pull/9507>`__: CI: MAINT: Skip a
ckdtree test on pypy
* `#9512 <https://github.com/scipy/scipy/pull/9512>`__: TST:
test_random_sampling 32-bit handling
* `#9494 <https://github.com/scipy/scipy/pull/9494>`__: TST:
test_kolmogorov xfail 32-bit
* `#9486 <https://github.com/scipy/scipy/pull/9486>`__: BUG: fix sparse
random int handling
* `#9550 <https://github.com/scipy/scipy/pull/9550>`__: BUG:
scipy/_lib/_numpy_compat: get_randint
* `#9549 <https://github.com/scipy/scipy/pull/9549>`__: MAINT: make
dual_annealing signature match other optimizers
* `#9541 <https://github.com/scipy/scipy/pull/9541>`__: BUG: fix
SyntaxError due to non-ascii character on Python 2.7
* `#7352 <https://github.com/scipy/scipy/pull/7352>`__: ENH: add Brunner
Munzel test to scipy.stats.
* `#7373 <https://github.com/scipy/scipy/pull/7373>`__: BUG: Jaccard
distance for all-zero arrays would return np.nan
* `#7374 <https://github.com/scipy/scipy/pull/7374>`__: ENH: Add PDF, CDF
and parameter estimation for Stable Distributions
* `#8098 <https://github.com/scipy/scipy/pull/8098>`__: ENH: Add shgo for
global optimization of NLPs.
* `#8203 <https://github.com/scipy/scipy/pull/8203>`__: ENH: adding
simulated dual annealing to optimize
* `#8259 <https://github.com/scipy/scipy/pull/8259>`__: Option to follow
original Storn and Price algorithm and its parallelisation
* `#8293 <https://github.com/scipy/scipy/pull/8293>`__: ENH add
ratio-of-uniforms method for rv generation to scipy.stats
* `#8294 <https://github.com/scipy/scipy/pull/8294>`__: BUG: Fix slowness
in stats.mode
* `#8295 <https://github.com/scipy/scipy/pull/8295>`__: ENH: add Jensen
Shannon distance to `scipy.spatial.distance`
* `#8357 <https://github.com/scipy/scipy/pull/8357>`__: ENH: vectorize
scalar zero-search-functions
* `#8397 <https://github.com/scipy/scipy/pull/8397>`__: Add `fs=` parameter
to filter design functions
* `#8537 <https://github.com/scipy/scipy/pull/8537>`__: ENH: Implement mode
parameter for spline filtering.
* `#8558 <https://github.com/scipy/scipy/pull/8558>`__: ENH: small speedup
for stats.gaussian_kde
* `#8560 <https://github.com/scipy/scipy/pull/8560>`__: BUG: fix p-value
calc of anderson_ksamp in scipy.stats
* `#8614 <https://github.com/scipy/scipy/pull/8614>`__: ENH: correct
p-values for stats.kendalltau and stats.mstats.kendalltau
* `#8670 <https://github.com/scipy/scipy/pull/8670>`__: ENH: Require Lapack
3.4.0
* `#8683 <https://github.com/scipy/scipy/pull/8683>`__: Correcting kmeans
documentation
* `#8725 <https://github.com/scipy/scipy/pull/8725>`__: MAINT: Cleanup
scipy.optimize.leastsq
* `#8726 <https://github.com/scipy/scipy/pull/8726>`__: BUG: Fix
_get_output in scipy.ndimage to support string
* `#8733 <https://github.com/scipy/scipy/pull/8733>`__: MAINT: stats: A bit
of clean up.
* `#8737 <https://github.com/scipy/scipy/pull/8737>`__: BUG: Improve
numerical precision/convergence failures of smirnov/kolmogorov
* `#8738 <https://github.com/scipy/scipy/pull/8738>`__: MAINT: stats: A bit
of clean up in test_distributions.py.
* `#8740 <https://github.com/scipy/scipy/pull/8740>`__: BF/ENH: make
minpack thread safe
* `#8742 <https://github.com/scipy/scipy/pull/8742>`__: BUG: Fix division
by zero in trust-region optimization methods
* `#8746 <https://github.com/scipy/scipy/pull/8746>`__: MAINT: signal: Fix
a docstring of a private function, and fix...
* `#8750 <https://github.com/scipy/scipy/pull/8750>`__: DOC clarified
description of norminvgauss in scipy.stats
* `#8753 <https://github.com/scipy/scipy/pull/8753>`__: DOC: signal: Fix a
plot title in the chirp docstring.
* `#8755 <https://github.com/scipy/scipy/pull/8755>`__: DOC: MAINT: Fix
link to the wheel documentation in developer...
* `#8760 <https://github.com/scipy/scipy/pull/8760>`__: BUG: stats:
boltzmann wasn't setting the upper bound.
* `#8763 <https://github.com/scipy/scipy/pull/8763>`__: [DOC] Improved
scipy.cluster.hierarchy documentation
* `#8765 <https://github.com/scipy/scipy/pull/8765>`__: DOC: added example
for scipy.stat.mstats.tmin
* `#8788 <https://github.com/scipy/scipy/pull/8788>`__: DOC: fix definition
of optional `disp` parameter
* `#8802 <https://github.com/scipy/scipy/pull/8802>`__: MAINT: Suppress
dd_real unused function compiler warnings.
* `#8803 <https://github.com/scipy/scipy/pull/8803>`__: ENH: Add
full_output support to optimize.newton()
* `#8804 <https://github.com/scipy/scipy/pull/8804>`__: MAINT: stats cleanup
* `#8808 <https://github.com/scipy/scipy/pull/8808>`__: DOC: add note about
isinstance for frozen rvs
* `#8812 <https://github.com/scipy/scipy/pull/8812>`__: Updated numpydoc
submodule
* `#8813 <https://github.com/scipy/scipy/pull/8813>`__: MAINT: stats: Fix
multinomial docstrings, and do some clean up.
* `#8816 <https://github.com/scipy/scipy/pull/8816>`__: BUG: fixed _stats
of t-distribution in scipy.stats
* `#8817 <https://github.com/scipy/scipy/pull/8817>`__: BUG: ndimage: Fix
validation of the origin argument in correlate...
* `#8822 <https://github.com/scipy/scipy/pull/8822>`__: BUG: integrate: Fix
crash with repeated t values in odeint.
* `#8832 <https://github.com/scipy/scipy/pull/8832>`__: Hyperlink DOIs
against preferred resolver
* `#8837 <https://github.com/scipy/scipy/pull/8837>`__: BUG: sparse: Ensure
correct dtype for sparse comparison operations.
* `#8839 <https://github.com/scipy/scipy/pull/8839>`__: DOC: stats: A few
tweaks to the linregress docstring.
* `#8846 <https://github.com/scipy/scipy/pull/8846>`__: BUG: stats: Fix
logpdf method of invwishart.
* `#8849 <https://github.com/scipy/scipy/pull/8849>`__: DOC: signal: Fixed
mistake in the firwin docstring.
* `#8854 <https://github.com/scipy/scipy/pull/8854>`__: DOC: fix type
descriptors in ltisys documentation
* `#8865 <https://github.com/scipy/scipy/pull/8865>`__: Fix tiny typo in
docs for chi2 pdf
* `#8870 <https://github.com/scipy/scipy/pull/8870>`__: Fixes related to
invertibility of STFT
* `#8872 <https://github.com/scipy/scipy/pull/8872>`__: ENH: special: Add
the softmax function
* `#8874 <https://github.com/scipy/scipy/pull/8874>`__: DOC correct gamma
function in docstrings in scipy.stats
* `#8876 <https://github.com/scipy/scipy/pull/8876>`__: ENH: Added TOMS
Algorithm 748 as 1-d root finder; 17 test function...
* `#8882 <https://github.com/scipy/scipy/pull/8882>`__: ENH: Only use
Halley's adjustment to Newton if close enough.
* `#8883 <https://github.com/scipy/scipy/pull/8883>`__: FIX: optimize: make
jac and hess truly optional for 'trust-constr'
* `#8885 <https://github.com/scipy/scipy/pull/8885>`__: TST: Do not error
on warnings raised about non-tuple indexing.
* `#8887 <https://github.com/scipy/scipy/pull/8887>`__: MAINT: filter out
np.matrix PendingDeprecationWarning's in numpy...
* `#8889 <https://github.com/scipy/scipy/pull/8889>`__: DOC: optimize:
separate legacy interfaces from new ones
* `#8890 <https://github.com/scipy/scipy/pull/8890>`__: ENH: Add
optimize.root_scalar() as a universal dispatcher for...
* `#8899 <https://github.com/scipy/scipy/pull/8899>`__: DCT-IV, DST-IV and
DCT-I, DST-I orthonormalization support in...
* `#8901 <https://github.com/scipy/scipy/pull/8901>`__: MAINT: Reorganize
flapack.pyf.src file
* `#8907 <https://github.com/scipy/scipy/pull/8907>`__: BUG: ENH: Check if
guess for newton is already zero before checking...
* `#8908 <https://github.com/scipy/scipy/pull/8908>`__: ENH: Make sorting
optional for cKDTree.query_ball_point()
* `#8910 <https://github.com/scipy/scipy/pull/8910>`__: DOC: sparse.csgraph
simple examples.
* `#8914 <https://github.com/scipy/scipy/pull/8914>`__: DOC: interpolate:
fix equivalences of string aliases
* `#8918 <https://github.com/scipy/scipy/pull/8918>`__: add
float_control(precise, on) to _fpumode.c
* `#8919 <https://github.com/scipy/scipy/pull/8919>`__: MAINT: interpolate:
improve error messages for common `bc_type`...
* `#8920 <https://github.com/scipy/scipy/pull/8920>`__: DOC: update
Contributing to SciPy to say "prefer no PEP8 only...
* `#8924 <https://github.com/scipy/scipy/pull/8924>`__: MAINT: special:
deprecate `hyp2f0`, `hyp1f2`, and `hyp3f0`
* `#8927 <https://github.com/scipy/scipy/pull/8927>`__: MAINT: special:
remove `errprint`
* `#8932 <https://github.com/scipy/scipy/pull/8932>`__: Fix broadcasting
scale arg of entropy
* `#8936 <https://github.com/scipy/scipy/pull/8936>`__: Fix (some)
non-tuple index warnings
* `#8937 <https://github.com/scipy/scipy/pull/8937>`__: ENH: implement
sparse matrix BSR to CSR conversion directly.
* `#8938 <https://github.com/scipy/scipy/pull/8938>`__: DOC: add
@_ni_docstrings.docfiller in ndimage.rotate
* `#8940 <https://github.com/scipy/scipy/pull/8940>`__: Update
_discrete_distns.py
* `#8943 <https://github.com/scipy/scipy/pull/8943>`__: DOC: Finish
dangling sentence in `convolve` docstring
* `#8944 <https://github.com/scipy/scipy/pull/8944>`__: MAINT: Address
tuple indexing and warnings
* `#8945 <https://github.com/scipy/scipy/pull/8945>`__: ENH:
spatial.transform.Rotation [GSOC2018]
* `#8950 <https://github.com/scipy/scipy/pull/8950>`__: csgraph Dijkstra
function description rewording
* `#8953 <https://github.com/scipy/scipy/pull/8953>`__: DOC, MAINT: HTTP ->
HTTPS, and other linkrot fixes
* `#8955 <https://github.com/scipy/scipy/pull/8955>`__: BUG: np.int64 in
scipy.fftpack.next_fast_len
* `#8958 <https://github.com/scipy/scipy/pull/8958>`__: MAINT: Add more
descriptive error message for phase one simplex.
* `#8962 <https://github.com/scipy/scipy/pull/8962>`__: BUG: sparse.linalg:
add missing conjugate to _ScaledLinearOperator.adjoint
* `#8963 <https://github.com/scipy/scipy/pull/8963>`__: BUG: sparse.linalg:
downgrade LinearOperator TypeError to warning
* `#8965 <https://github.com/scipy/scipy/pull/8965>`__: ENH: Wrapped RFP
format and RZ decomposition routines
* `#8969 <https://github.com/scipy/scipy/pull/8969>`__: MAINT: doc and code
fixes for optimize.newton
* `#8970 <https://github.com/scipy/scipy/pull/8970>`__: Added 'average'
keyword for welch/csd to enable median averaging
* `#8971 <https://github.com/scipy/scipy/pull/8971>`__: Better imresize
deprecation warning
* `#8972 <https://github.com/scipy/scipy/pull/8972>`__: MAINT: Switch
np.where(c) for np.nonzero(c)
* `#8975 <https://github.com/scipy/scipy/pull/8975>`__: MAINT: Fix
warning-based failures
* `#8979 <https://github.com/scipy/scipy/pull/8979>`__: DOC: fix
description of count_sort keyword of dendrogram
* `#8982 <https://github.com/scipy/scipy/pull/8982>`__: MAINT: optimize:
Fixed minor mistakes in test_linprog.py (#8978)
* `#8984 <https://github.com/scipy/scipy/pull/8984>`__: BUG: sparse.linalg:
ensure expm casts integer inputs to float
* `#8986 <https://github.com/scipy/scipy/pull/8986>`__: BUG:
optimize/slsqp: do not exit with convergence on steps where...
* `#8989 <https://github.com/scipy/scipy/pull/8989>`__: MAINT: use
collections.abc in basinhopping
* `#8990 <https://github.com/scipy/scipy/pull/8990>`__: ENH extend p-values
of anderson_ksamp in scipy.stats
* `#8991 <https://github.com/scipy/scipy/pull/8991>`__: ENH: Weighted kde
* `#8993 <https://github.com/scipy/scipy/pull/8993>`__: ENH:
spatial.transform.Rotation.random [GSOC 2018]
* `#8994 <https://github.com/scipy/scipy/pull/8994>`__: ENH:
spatial.transform.Slerp [GSOC 2018]
* `#8995 <https://github.com/scipy/scipy/pull/8995>`__: TST: time.time in
test
* `#9007 <https://github.com/scipy/scipy/pull/9007>`__: Fix typo in
fftpack.rst
* `#9013 <https://github.com/scipy/scipy/pull/9013>`__: Added correct
plotting code for two sided output from spectrogram
* `#9014 <https://github.com/scipy/scipy/pull/9014>`__: BUG:
differential_evolution with inf objective functions
* `#9017 <https://github.com/scipy/scipy/pull/9017>`__: BUG: fixed #8446
corner case for asformat(array|dense)
* `#9018 <https://github.com/scipy/scipy/pull/9018>`__: MAINT:
_lib/ccallback: remove unused code
* `#9021 <https://github.com/scipy/scipy/pull/9021>`__: BUG: Issue with
subspace_angles
* `#9022 <https://github.com/scipy/scipy/pull/9022>`__: DOC: Added "See
Also" section to lombscargle docstring
* `#9034 <https://github.com/scipy/scipy/pull/9034>`__: BUG: Fix tolerance
printing behavior, remove meaningless tol...
* `#9035 <https://github.com/scipy/scipy/pull/9035>`__: TST: improve
signal.bsplines test coverage
* `#9037 <https://github.com/scipy/scipy/pull/9037>`__: ENH: add a new init
method for k-means
* `#9039 <https://github.com/scipy/scipy/pull/9039>`__: DOC: Add examples
to fftpack.irfft docstrings
* `#9048 <https://github.com/scipy/scipy/pull/9048>`__: ENH:
scipy.sparse.random
* `#9050 <https://github.com/scipy/scipy/pull/9050>`__: BUG:
scipy.io.hb_write: fails for matrices not in csc format
* `#9051 <https://github.com/scipy/scipy/pull/9051>`__: MAINT: Fix slow
sparse.rand for k < mn/3 (#9036).
* `#9054 <https://github.com/scipy/scipy/pull/9054>`__: MAINT: spatial:
Explicitly initialize LAPACK output parameters.
* `#9055 <https://github.com/scipy/scipy/pull/9055>`__: DOC: Add examples
to scipy.special docstrings
* `#9056 <https://github.com/scipy/scipy/pull/9056>`__: ENH: Use one thread
in OpenBLAS
* `#9059 <https://github.com/scipy/scipy/pull/9059>`__: DOC: Update README
with link to Code of Conduct
* `#9060 <https://github.com/scipy/scipy/pull/9060>`__: BLD: remove support
for the Bento build system.
* `#9062 <https://github.com/scipy/scipy/pull/9062>`__: DOC add sections to
overview in scipy.stats
* `#9066 <https://github.com/scipy/scipy/pull/9066>`__: BUG: Correct
"remez" error message
* `#9069 <https://github.com/scipy/scipy/pull/9069>`__: DOC: update linalg
section of roadmap for LAPACK versions.
* `#9079 <https://github.com/scipy/scipy/pull/9079>`__: MAINT: add
spatial.transform to refguide check; complete some...
* `#9081 <https://github.com/scipy/scipy/pull/9081>`__: MAINT: Add warnings
if pivot value is close to tolerance in linprog(method='simplex')
* `#9084 <https://github.com/scipy/scipy/pull/9084>`__: BUG fix incorrect
p-values of kurtosistest in scipy.stats
* `#9095 <https://github.com/scipy/scipy/pull/9095>`__: DOC: add sections
to mstats overview in scipy.stats
* `#9096 <https://github.com/scipy/scipy/pull/9096>`__: BUG: Add test for
Stackoverflow example from issue 8174.
* `#9101 <https://github.com/scipy/scipy/pull/9101>`__: ENH: add Siegel
slopes (robust regression) to scipy.stats
* `#9105 <https://github.com/scipy/scipy/pull/9105>`__: allow
resample_poly() to output float32 for float32 inputs.
* `#9112 <https://github.com/scipy/scipy/pull/9112>`__: MAINT: optimize:
make trust-constr accept constraint dict (#9043)
* `#9118 <https://github.com/scipy/scipy/pull/9118>`__: Add doc entry to
cholesky_banded
* `#9120 <https://github.com/scipy/scipy/pull/9120>`__: eigsh documentation
parameters
* `#9125 <https://github.com/scipy/scipy/pull/9125>`__: interpolative:
correctly reconstruct full rank matrices
* `#9126 <https://github.com/scipy/scipy/pull/9126>`__: MAINT: Use warnings
for unexpected peak properties
* `#9129 <https://github.com/scipy/scipy/pull/9129>`__: BUG: Do not catch
and silence KeyboardInterrupt
* `#9131 <https://github.com/scipy/scipy/pull/9131>`__: DOC: Correct the
typo in scipy.optimize tutorial page
* `#9133 <https://github.com/scipy/scipy/pull/9133>`__: FIX: Avoid use of
bare except
* `#9134 <https://github.com/scipy/scipy/pull/9134>`__: DOC: Update of
'return_eigenvectors' description
* `#9137 <https://github.com/scipy/scipy/pull/9137>`__: DOC: typo fixes for
discrete Poisson tutorial
* `#9139 <https://github.com/scipy/scipy/pull/9139>`__: FIX: Doctest
failure in optimize tutorial
* `#9143 <https://github.com/scipy/scipy/pull/9143>`__: DOC: missing sigma
in Pearson r formula
* `#9145 <https://github.com/scipy/scipy/pull/9145>`__: MAINT: Refactor
linear programming solvers
* `#9149 <https://github.com/scipy/scipy/pull/9149>`__: FIX: Make
scipy.odr.ODR ifixx equal to its data.fix if given
* `#9156 <https://github.com/scipy/scipy/pull/9156>`__: DOC: special:
Mention the sigmoid function in the expit docstring.
* `#9160 <https://github.com/scipy/scipy/pull/9160>`__: Fixed a latex
delimiter error in levy()
* `#9170 <https://github.com/scipy/scipy/pull/9170>`__: DOC: correction /
update of docstrings of distributions in scipy.stats
* `#9171 <https://github.com/scipy/scipy/pull/9171>`__: better description
of the hierarchical clustering parameter
* `#9174 <https://github.com/scipy/scipy/pull/9174>`__: domain check for a
< b in stats.truncnorm
* `#9175 <https://github.com/scipy/scipy/pull/9175>`__: DOC: Minor grammar
fix
* `#9176 <https://github.com/scipy/scipy/pull/9176>`__: BUG:
CloughTocher2DInterpolator: fix miscalculation at neighborless...
* `#9177 <https://github.com/scipy/scipy/pull/9177>`__: BUILD: Document the
"clean" target in the doc/Makefile.
* `#9178 <https://github.com/scipy/scipy/pull/9178>`__: MAINT: make
refguide-check more robust for printed numpy arrays
* `#9186 <https://github.com/scipy/scipy/pull/9186>`__: MAINT: Remove
np.ediff1d occurence
* `#9188 <https://github.com/scipy/scipy/pull/9188>`__: DOC: correct typo
in extending ndimage with C
* `#9190 <https://github.com/scipy/scipy/pull/9190>`__: ENH: Support
specifying axes for fftconvolve
* `#9192 <https://github.com/scipy/scipy/pull/9192>`__: MAINT: optimize:
fixed @pv style suggestions from #9112
* `#9200 <https://github.com/scipy/scipy/pull/9200>`__: Fix
make_interp_spline(..., k=0 or 1, axis<0)
* `#9201 <https://github.com/scipy/scipy/pull/9201>`__: BUG:
sparse.linalg/gmres: use machine eps in breakdown check
* `#9204 <https://github.com/scipy/scipy/pull/9204>`__: MAINT: fix up
stats.spearmanr and match mstats.spearmanr with...
* `#9206 <https://github.com/scipy/scipy/pull/9206>`__: MAINT: include
benchmarks and dev files in sdist.
* `#9208 <https://github.com/scipy/scipy/pull/9208>`__: TST: signal: bump
bsplines test tolerance for complex data
* `#9210 <https://github.com/scipy/scipy/pull/9210>`__: TST: mark tests as
slow, fix missing random seed
* `#9211 <https://github.com/scipy/scipy/pull/9211>`__: ENH: add capability
to specify orders in pade func
* `#9217 <https://github.com/scipy/scipy/pull/9217>`__: MAINT: Include
``success`` and ``nit`` in OptimizeResult returned...
* `#9222 <https://github.com/scipy/scipy/pull/9222>`__: ENH: interpolate:
Use scipy.spatial.distance to speed-up Rbf
* `#9229 <https://github.com/scipy/scipy/pull/9229>`__: MNT: Fix Fourier
filter double case
* `#9233 <https://github.com/scipy/scipy/pull/9233>`__: BUG:
spatial/distance: fix pdist/cdist performance regression...
* `#9234 <https://github.com/scipy/scipy/pull/9234>`__: FIX: Proper
suppression
* `#9235 <https://github.com/scipy/scipy/pull/9235>`__: BENCH: rationalize
slow benchmarks + miscellaneous fixes
* `#9238 <https://github.com/scipy/scipy/pull/9238>`__: BENCH: limit number
of parameter combinations in spatial.*KDTree...
* `#9239 <https://github.com/scipy/scipy/pull/9239>`__: DOC: stats: Fix
LaTeX markup of a couple distribution PDFs.
* `#9241 <https://github.com/scipy/scipy/pull/9241>`__: ENH: Evaluate
plateau size during peak finding
* `#9242 <https://github.com/scipy/scipy/pull/9242>`__: ENH: stats:
Implement _ppf and _logpdf for crystalball, and do...
* `#9246 <https://github.com/scipy/scipy/pull/9246>`__: DOC: Properly
render versionadded directive in HTML documentation
* `#9255 <https://github.com/scipy/scipy/pull/9255>`__: DOC: mention
RootResults in optimization reference guide
* `#9260 <https://github.com/scipy/scipy/pull/9260>`__: TST: relax some
tolerances so tests pass with x87 math
* `#9264 <https://github.com/scipy/scipy/pull/9264>`__: TST Use
assert_raises "match" parameter instead of the "message"...
* `#9267 <https://github.com/scipy/scipy/pull/9267>`__: DOC: clarify
expect() return val when moment is inf/nan
* `#9272 <https://github.com/scipy/scipy/pull/9272>`__: DOC: Add
description of default bounds to linprog
* `#9277 <https://github.com/scipy/scipy/pull/9277>`__: MAINT:
sparse/linalg: make test deterministic
* `#9278 <https://github.com/scipy/scipy/pull/9278>`__: MAINT: interpolate:
pep8 cleanup in test_polyint
* `#9279 <https://github.com/scipy/scipy/pull/9279>`__: Fixed docstring for
resample
* `#9280 <https://github.com/scipy/scipy/pull/9280>`__: removed first check
for float in get_sum_dtype
* `#9281 <https://github.com/scipy/scipy/pull/9281>`__: BUG: only accept 1d
input for bartlett / levene in scipy.stats
* `#9282 <https://github.com/scipy/scipy/pull/9282>`__: MAINT: dense_output
and t_eval are mutually exclusive inputs
* `#9283 <https://github.com/scipy/scipy/pull/9283>`__: MAINT: add docs and
do some cleanups in interpolate.Rbf
* `#9288 <https://github.com/scipy/scipy/pull/9288>`__: Run
distance_transform_edt tests on all types
* `#9294 <https://github.com/scipy/scipy/pull/9294>`__: DOC: fix the
formula typo
* `#9298 <https://github.com/scipy/scipy/pull/9298>`__: MAINT:
optimize/trust-constr: restore .niter attribute for backward-compat
* `#9299 <https://github.com/scipy/scipy/pull/9299>`__: DOC: clarification
of default rvs method in scipy.stats
* `#9301 <https://github.com/scipy/scipy/pull/9301>`__: MAINT: removed
unused import sys
* `#9302 <https://github.com/scipy/scipy/pull/9302>`__: MAINT: removed
unused imports
* `#9303 <https://github.com/scipy/scipy/pull/9303>`__: DOC: signal: Refer
to fs instead of nyq in the firwin docstring.
* `#9305 <https://github.com/scipy/scipy/pull/9305>`__: ENH: Added
Yeo-Johnson power transformation
* `#9306 <https://github.com/scipy/scipy/pull/9306>`__: ENH - add dual
annealing
* `#9309 <https://github.com/scipy/scipy/pull/9309>`__: ENH add the
yulesimon distribution to scipy.stats
* `#9317 <https://github.com/scipy/scipy/pull/9317>`__: Nested SLSQP bug
fix.
* `#9320 <https://github.com/scipy/scipy/pull/9320>`__: MAINT: stats: avoid
underflow in stats.geom.ppf
* `#9326 <https://github.com/scipy/scipy/pull/9326>`__: Add example for
Rosenbrock function
* `#9332 <https://github.com/scipy/scipy/pull/9332>`__: Sort file lists
* `#9340 <https://github.com/scipy/scipy/pull/9340>`__: Fix typo in
find_peaks documentation
* `#9343 <https://github.com/scipy/scipy/pull/9343>`__: MAINT Use np.full
when possible
* `#9344 <https://github.com/scipy/scipy/pull/9344>`__: DOC: added examples
to docstring of dirichlet class
* `#9346 <https://github.com/scipy/scipy/pull/9346>`__: DOC: Fix import of
scipy.sparse.linalg in example (#9345)
* `#9350 <https://github.com/scipy/scipy/pull/9350>`__: Fix interpolate
read only
* `#9351 <https://github.com/scipy/scipy/pull/9351>`__: MAINT: special.erf:
use the x->-x symmetry
* `#9356 <https://github.com/scipy/scipy/pull/9356>`__: Fix documentation
typo
* `#9358 <https://github.com/scipy/scipy/pull/9358>`__: DOC: improve doc
for ksone and kstwobign in scipy.stats
* `#9362 <https://github.com/scipy/scipy/pull/9362>`__: DOC: Change
datatypes of A matrices in linprog
* `#9364 <https://github.com/scipy/scipy/pull/9364>`__: MAINT: Adds
implicit none to fftpack fortran sources
* `#9369 <https://github.com/scipy/scipy/pull/9369>`__: DOC: minor tweak to
CoC (updated NumFOCUS contact address).
* `#9373 <https://github.com/scipy/scipy/pull/9373>`__: Fix exception if
python is called with -OO option
* `#9374 <https://github.com/scipy/scipy/pull/9374>`__: FIX: AIX
compilation issue with NAN and INFINITY
* `#9376 <https://github.com/scipy/scipy/pull/9376>`__: COBLYA -> COBYLA in
docs
* `#9377 <https://github.com/scipy/scipy/pull/9377>`__: DOC: Add examples
integrate: fixed_quad and quadrature
* `#9379 <https://github.com/scipy/scipy/pull/9379>`__: MAINT: TST: Make
tests NumPy 1.8 compatible
* `#9385 <https://github.com/scipy/scipy/pull/9385>`__: CI: On Travis
matrix "OPTIMIZE=-OO" flag ignored
* `#9387 <https://github.com/scipy/scipy/pull/9387>`__: Fix defaut value
for 'mode' in 'ndimage.shift' in the doc
* `#9392 <https://github.com/scipy/scipy/pull/9392>`__: BUG: rank has to be
integer in rank_filter: fixed issue 9388
* `#9399 <https://github.com/scipy/scipy/pull/9399>`__: DOC: Misc. typos
* `#9400 <https://github.com/scipy/scipy/pull/9400>`__: TST: stats: Fix the
expected r-value of a linregress test.
* `#9405 <https://github.com/scipy/scipy/pull/9405>`__: BUG: np.hstack does
not accept generator expressions
* `#9408 <https://github.com/scipy/scipy/pull/9408>`__: ENH: linalg:
Shorter ill-conditioned warning message
* `#9418 <https://github.com/scipy/scipy/pull/9418>`__: DOC: Fix ndimage
docstrings and reduce doc build warnings
* `#9421 <https://github.com/scipy/scipy/pull/9421>`__: DOC: Add missing
docstring examples in scipy.spatial
* `#9422 <https://github.com/scipy/scipy/pull/9422>`__: DOC: Add an example
to integrate.newton_cotes
* `#9427 <https://github.com/scipy/scipy/pull/9427>`__: BUG: Fixed defect
with maxiter #9419 in dual annealing
* `#9431 <https://github.com/scipy/scipy/pull/9431>`__: BENCH: Add dual
annealing to scipy benchmark (see #9415)
* `#9435 <https://github.com/scipy/scipy/pull/9435>`__: DOC: Add docstring
examples for stats.binom_test
* `#9443 <https://github.com/scipy/scipy/pull/9443>`__: DOC: Fix the order
of indices in optimize tutorial
* `#9444 <https://github.com/scipy/scipy/pull/9444>`__: MAINT: interpolate:
use operator.index for checking/coercing...
* `#9445 <https://github.com/scipy/scipy/pull/9445>`__: DOC: Added missing
example to stats.mstats.kruskal
* `#9446 <https://github.com/scipy/scipy/pull/9446>`__: DOC: Add note about
version changed for jaccard distance
* `#9447 <https://github.com/scipy/scipy/pull/9447>`__: BLD: version-script
handling in setup.py
* `#9448 <https://github.com/scipy/scipy/pull/9448>`__: TST: skip a
problematic linalg test
* `#9449 <https://github.com/scipy/scipy/pull/9449>`__: TST: fix missing
seed in lobpcg test.
* `#9456 <https://github.com/scipy/scipy/pull/9456>`__: TST:
test_eigs_consistency() now sorts output
Checksums
=========
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Hi all,
To start with the idea: I propose that SciPy applies for comprehensive
project sponsorship with NumFOCUS, and sign a fiscal sponsorship agreement
(FSA) to that effect.
Why?
----
We're already an "affiliated project", which lets us participate in the
small development grants program, the NumFOCUS project mailing list and
Slack channel, and a few other benefits. The main difference that
comprehensive sponsorship will make is that it will allow us to accept
donations, grants and other kinds of funding as a project. In addition we
get funding for a representative of the project to attend the yearly
NumFOCUS Summit, some hours of high-quality legal help in case we need that
(for example in case of licensing questions), and probably a few other
things that I'm forgetting right now. NumFOCUS sets a higher bar for
comprehensive sponsorship than for affiliation, but we should easily clear
that bar. We'll be joining most other core scientific Python projects, who
are already sponsored [1].
I'll also steal some language from Nathaniel when he made the same proposal
for NumPy [2]:
The basic idea here is that there are times when you really need some kind
of corporation to represent the project -- the legal system for better or
worse does not understand "a bunch of folks on a mailing list" as a legal
entity capable of accepting donations, or holding funds or other assets
like domain names. The obvious solution is to incorporate a company to
represent the project -- but incorporating a company involves lots of
super-annoying paperwork. (Like, *super*
annoying.) So a standard trick is that a single non-profit corporation acts
as an umbrella organization providing these services to multiple projects
at once, and this is called "fiscal sponsorship". You can read more about
it here: https://en.wikipedia.org/wiki/Fiscal_sponsorship
How?
----
We form a subcommittee of 5 people that will sign the sponsorship
agreement. Those people mostly should be part of the SciPy Steering
Council; there can be an external member. The job of that group is
basically to interface with NumFOCUS (in practice there will be 1-2 people
as first contacts), and to ensure that if we use funds, that they are used
in agreement with the mission and nonprofit status of NumFOCUS. Once we
have those 5 people, we can send in a formal application. In practice that
takes very little time - probably no more than an hour per year, except for
the 1-2 first contacts (they get 1-2 emails per month that need responding
to).
For more background and details on the how and why, see
https://numfocus.org/information-fiscal-sponsorship.
Thoughts? Questions? Volunteers to be on the subcommittee?
Cheers,
Ralf
[1] https://numfocus.org/sponsored-projects
[2]
https://mail.python.org/pipermail/numpy-discussion/2015-October/073889.html

I am pleased to announce release 2018.4 of SfePy.
Description
-----------
SfePy (simple finite elements in Python) is a software for solving systems of
coupled partial differential equations by the finite element method or by the
isogeometric analysis (limited support). It is distributed under the new BSD
license.
Home page: http://sfepy.org
Mailing list: https://mail.python.org/mm3/mailman3/lists/sfepy.python.org/
Git (source) repository, issue tracker: https://github.com/sfepy/sfepy
Highlights of this release
--------------------------
- better support for eigenvalue problems
- improved MUMPS solver interface
- support for logging and plotting of complex values
For full release notes see [1].
Cheers,
Robert Cimrman
[1] http://docs.sfepy.org/doc/release_notes.html#id1
---
Contributors to this release in alphabetical order:
Robert Cimrman
Vladimir Lukes
Matyas Novak
Jan Heczko
Lubos Kejzlar

Hi All,
On behalf of the NumPy team I'm pleased to announce the release of NumPy
1.16.0rc1. This is the last NumPy release to support Python 2.7 and will be
maintained as a long term release with bug fixes until 2020. This release
has seen a lot of refactoring and features many bug fixes, improved code
organization, and better cross platform compatibility. Not all of these
improvements will be visible to users, but they should help make
maintenance easier going forward. Highlights are
- Experimental support for overriding numpy functions in downstream
projects.
- The matmul function is now a ufunc and can be overridden using
__array_ufunc__.
- Improved support for the ARM and POWER architectures.
- Improved support for AIX and PyPy.
- Improved interoperation with ctypes.
- Improved support for PEP 3118.
The supported Python versions are 2.7 and 3.5-3.7, support for 3.4 has been
dropped. The wheels on PyPI are linked with OpenBLAS v0.3.4+, which should
fix the known threading issues found in previous OpenBLAS versions.
Downstream developers building this release should use Cython >= 0.29 and,
if linking OpenBLAS, OpenBLAS > v0.3.4.
Wheels for this release can be downloaded from PyPI
<https://pypi.org/project/numpy/1.16.0rc1/>, source archives are available
from Github <https://github.com/numpy/numpy/releases/tag/v1.16.0rc1>.
*Contributors*
A total of 111 people contributed to this release. People with a "+" by
their
names contributed a patch for the first time.
- Alan Fontenot +
- Allan Haldane
- Alon Hershenhorn +
- Alyssa Quek +
- Andreas Nussbaumer +
- Anner +
- Anthony Sottile +
- Antony Lee
- Ayappan P +
- Bas van Schaik +
- C.A.M. Gerlach +
- Charles Harris
- Chris Billington
- Christian Clauss
- Christoph Gohlke
- Christopher Pezley +
- Daniel B Allan +
- Daniel Smith
- Dawid Zych +
- Derek Kim +
- Dima Pasechnik +
- Edgar Giovanni Lepe +
- Elena Mokeeva +
- Elliott Sales de Andrade +
- Emil Hessman +
- Eric Schles +
- Eric Wieser
- Giulio Benetti +
- Guillaume Gautier +
- Guo Ci
- Heath Henley +
- Isuru Fernando +
- J. Lewis Muir +
- Jack Vreeken +
- Jaime Fernandez
- James Bourbeau
- Jeff VanOss
- Jeffrey Yancey +
- Jeremy Chen +
- Jeremy Manning +
- Jeroen Demeyer
- John Darbyshire +
- John Zwinck
- Jonas Jensen +
- Joscha Reimer +
- Juan Azcarreta +
- Julian Taylor
- Kevin Sheppard
- Krzysztof Chomski +
- Kyle Sunden
- Lars Grüter
- Lilian Besson +
- MSeifert04
- Mark Harfouche
- Marten van Kerkwijk
- Martin Thoma
- Matt Harrigan +
- Matthew Bowden +
- Matthew Brett
- Matthias Bussonnier
- Matti Picus
- Max Aifer +
- Michael Hirsch, Ph.D +
- Michael James Jamie Schnaitter +
- MichaelSaah +
- Mike Toews
- Minkyu Lee +
- Mircea Akos Bruma +
- Mircea-Akos Brumă +
- Moshe Looks +
- Muhammad Kasim +
- Nathaniel J. Smith
- Nikita Titov +
- Paul Müller +
- Paul van Mulbregt
- Pauli Virtanen
- Pierre Glaser +
- Pim de Haan
- Ralf Gommers
- Robert Kern
- Robin Aggleton +
- Rohit Pandey +
- Roman Yurchak +
- Ryan Soklaski
- Sebastian Berg
- Sho Nakamura +
- Simon Gibbons
- Stan Seibert +
- Stefan Otte
- Stefan van der Walt
- Stephan Hoyer
- Stuart Archibald
- Taylor Smith +
- Tim Felgentreff +
- Tim Swast +
- Tim Teichmann +
- Toshiki Kataoka
- Travis Oliphant
- Tyler Reddy
- Uddeshya Singh +
- Warren Weckesser
- Weitang Li +
- Wenjamin Petrenko +
- William D. Irons
- Yannick Jadoul +
- Yaroslav Halchenko
- Yug Khanna +
- Yuji Kanagawa +
- Yukun Guo +
- lerbuke +
- @ankokumoyashi +
Cheers,
Charles Harris

Hello, everyone!
I’ll be speaking about PyData/Sparse in a webinar hosted by Quansight. It’ll include a project demo, in case you’re interested, as well as the directions the project can take. You can register for the webinar at https://app.livestorm.co/quansight/
Best Regards,
Hameer Abbasi

Hi everyone,
Apologies in advance for the cross-post.
On behalf of all the contributors, I’m pleased to announce that PyData/Sparse 0.6.0 has been released. The wheel is up on PyPI and the conda-forge package should be up before the end of the day.
The wheels and sources can be found at:
https://github.com/pydata/sparse/releases/tag/0.6.0https://pypi.org/project/sparse/#files
The documentation for this package is available at http://sparse.pydata.org/en/0.6.0/
This is mainly a bug-fix release. The changelog can be found at: http://sparse.pydata.org/en/latest/changelog.html
The main highlight is that we changed the default behaviour to raise an exception when using functions meant for NumPy arrays which would densify the array. This is also configurable via the SPARSE_AUTO_DENSIFY environment variable before importing the module.
Best Regards,
Hameer Abbasi

Dear Scipy-dev community,
I would like to bring forward two proposals related to your scipy.sparse.linalg.LinearOperator class and linear solvers in general:
LinearOperator: I am the main developer and maintainer of the PyLops library that has been recently open-sourced (git repo: https://github.com/Statoil/pylops, doc: https://pylops.readthedocs.io/en/latest/index.html). As you will see I heavily rely on your LinearOperator class and build on top of it creating various basic linear operators and more specific ones for signal processing and geoscience applications of inverse problems. When I started working on this I was surprised to find very little information and examples online on how to use your LinearOperator and the possibility to subclass it was only mentioned in one line of your documentation and nowhere else online to my knowledge. I wonder if you would consider pointing to PyLops in your documentation to facilitate users i) to know how to get started with LinearOperator, ii) avoid rebuilding the wheel if what they are after can be done or is done already in PyLops. I find your class fantastic and saved me lots of time but I feel is one of those things that few people realize exist and understand how to use it ;)
Solvers: I would like to know if you would be interested to add a new solver to your suite of linear solvers. Specifically the solver is called SPGL1 and it is a very popular solver in the mathematical community for sparsity-promoting linear optimization. It was developed at UBC (University of British Columbia) https://www.cs.ubc.ca/~mpf/spgl1/ and has a Matlab open-source code. I have been thinking about porting it to python for a while and recently another python user started a git repo called https://github.com/drrelyea/SPGL1_python_port. However this is something I would more naturally see as part of scipy instead of an indipendent library. I am willing to contact the author of this repo and help him out directly to finish the porting and make it to (or close to) scipy standards... so far the code and repo is not ready to be included in professional code like scipy in my opinion. But I would like to hear what you think, if you would consider adding this to scipy once in good shape or if you think this is not in the scope of scipy library :)
Looking forward to hearing from you,
Best wishes
MR