[Numpy-discussion] ANN: SciPy 1.13.0rc1 -- please test

[Tyler Reddy]

ats.f_oneway`,
  `scipy.stats.alexandergovern`, `scipy.stats.combine_pvalues`, and
  `scipy.stats.kstest` have gained ``axis``, ``nan_policy`` and
  ``keepdims`` support.
- `scipy.stats.boxcox_normmax` has gained a ``ymax`` parameter to allow user
  specification of the maximum value of the transformed data.
- `scipy.stats.vonmises` ``pdf`` method has been extended to support
  ``kappa=0``. The ``fit`` method is also more performant due to the use of
  non-trivial bounds to solve for ``kappa``.
- High order ``moment`` calculations for `scipy.stats.powerlaw` are now more
  accurate.
- The ``fit`` methods of  `scipy.stats.gamma` (with ``method='mm'``) and
  `scipy.stats.loglaplace` are faster and more reliable.
- `scipy.stats.goodness_of_fit` now supports the use of a custom
``statistic``
  provided by the user.
- `scipy.stats.wilcoxon` now supports ``PermutationMethod``, enabling
  calculation of accurate p-values in the presence of ties and zeros.
- `scipy.stats.monte_carlo_test` now has improved robustness in the face of
  numerical noise.
- `scipy.stats.wasserstein_distance_nd` was introduced to compute the
  Wasserstein-1 distance between two N-D discrete distributions.


***
Deprecated features
***
- Complex dtypes in ``PchipInterpolator`` and ``Akima1DInterpolator`` have
  been deprecated and will raise an error in SciPy 1.15.0. If you are trying
  to use the real components of the passed array, use ``np.real`` on ``y``.



**
Backwards incompatible changes
**

*
Other changes
*
- The second argument of `scipy.stats.moment` has been renamed to ``order``
  while maintaining backward compatibility.



***
Authors
***

* Name (commits)
* h-vetinari (50)
* acceptacross (1) +
* Petteri Aimonen (1) +
* Francis Allanah (2) +
* Jonas Kock am Brink (1) +
* anupriyakkumari (12) +
* Aman Atman (2) +
* Aaditya Bansal (1) +
* Christoph Baumgarten (2)
* Sebastian Berg (4)
* Nicolas Bloyet (2) +
* Matt Borland (1)
* Jonas Bosse (1) +
* Jake Bowhay (25)
* Matthew Brett (1)
* Dietrich Brunn (7)
* Evgeni Burovski (48)
* Matthias Bussonnier (4)
* Cale (1) +
* CJ Carey (4)
* Thomas A Caswell (1)
* Sean Cheah (44) +
* Lucas Colley (97)
* com3dian (1)
* Gianluca Detommaso (1) +
* Thomas Duvernay (1)
* DWesl (2)
* f380cedric (1) +
* fancidev (13) +
* Daniel Garcia (1) +
* Lukas Geiger (3)
* Ralf Gommers (139)
* Matt Haberland (79)
* Tessa van der Heiden (2) +
* inky (3) +
* Jannes Münchmeyer (2) +
* Aditya Vidyadhar Kamath (2) +
* Agriya Khetarpal (1) +
* Andrew Landau (1) +
* Eric Larson (7)
* Zhen-Qi Liu (1) +
* Adam Lugowski (4)
* m-maggi (6) +
* Chethin Manage (1) +
* Ben Mares (1)
* Chris Markiewicz (1) +
* Mateusz Sokół (3)
* Daniel McCloy (1) +
* Melissa Weber Mendonça (6)
* Josue Melka (1)
* Michał Górny (4)
* Juan Montesinos (1) +
* Juan F. Montesinos (1) +
* Takumasa Nakamura (1)
* Andrew Nelson (26)
* Praveer Nidamaluri (1)
* Yagiz Olmez (5) +
* Dimitri Papadopoulos Orfanos (1)
* Drew Parsons (1) +
* Tirth Patel (7)
* Matti Picus (3)
* Rambaud Pierrick (1) +
* Ilhan Polat (30)
* Quentin Barthélemy (1)
* Tyler Reddy (81)
* Pamphile Roy (10)
* Atsushi Sakai (4)
* Daniel Schmitz (10)
* Dan Schult (16)
* Eli Schwartz (4)
* Stefanie Senger (1) +
* Scott Shambaugh (2)
* Kevin Sheppard (2)
* sidsrinivasan (4) +
* Samuel St-Jean (1)
* Albert Steppi (30)
* Adam J. Stewart (4)
* Kai Striega (3)
* Ruikang Sun (1) +
* Mike Taves (1)
* Nicolas Tessore (3)
* Benedict T Thekkel (1) +
* Will Tirone (4)
* Jacob Vanderplas (2)
* Christian Veenhuis (1)
* Isaac Virshup (2)
* Ben Wallace (1) +
* Xuefeng Xu (3)
* Xiao Yuan (5)
* Irwin Zaid (6)
* Mathias Zechmeister (1) +

A total of 91 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 1.13.0


* `#1603 <https://github.com/scipy/scipy/issues/1603>`__: binomial ppf
gives bogus results for small binomial probability...
* `#2254 <https://github.com/scipy/scipy/issues/2254>`__: linalg.eig test
failure (test_singular) (Trac #1735)
* `#8398 <https://github.com/scipy/scipy/issues/8398>`__: Precision of
CDFLIB too low
* `#9950 <https://github.com/scipy/scipy/issues/9950>`__: "++"
initialization in kmeans2 fails for univariate data
* `#10317 <https://github.com/scipy/scipy/issues/10317>`__:
scipy.stats.nbinom.interval returns wrong result for p=1
* `#10569 <https://github.com/scipy/scipy/issues/10569>`__: API: \`s\`
argument different in scipy.fft and numpy.fft
* `#11577 <https://github.com/scipy/scipy/issues/11577>`__: generalized
eigenvalues are sometimes wrong (on some hardware)
* `#14176 <https://github.com/scipy/scipy/issues/14176>`__: Add option for
terminating solver after n events
* `#14220 <https://github.com/scipy/

[Numpy-discussion] ANN: SciPy 1.11.4

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team, I'm pleased to announce the
release of SciPy 1.11.4,
which is a bug fix release.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.11.4

One of a few ways to install this release with pip:

pip install scipy==1.11.4

==
SciPy 1.11.4 Release Notes
==

SciPy 1.11.4 is a bug-fix release with no new features
compared to 1.11.3.

Authors
==
* Name (commits)
* Jake Bowhay (2)
* Ralf Gommers (4)
* Julien Jerphanion (2)
* Nikolay Mayorov (2)
* Melissa Weber Mendonça (1)
* Tirth Patel (1)
* Tyler Reddy (22)
* Dan Schult (3)
* Nicolas Vetsch (1) +

A total of 9 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 1.11.4


* `#19189 <https://github.com/scipy/scipy/issues/19189>`__: Contradiction
in \`pyproject.toml\` requirements?
* `#19228 <https://github.com/scipy/scipy/issues/19228>`__: Doc build fails
with Python 3.11
* `#19245 <https://github.com/scipy/scipy/issues/19245>`__: BUG: upcasting
of indices dtype from DIA to COO/CSR/BSR arrays
* `#19351 <https://github.com/scipy/scipy/issues/19351>`__: BUG: Regression
in 1.11.3 can still fail for \`optimize.least_squares\`...
* `#19357 <https://github.com/scipy/scipy/issues/19357>`__: BUG: build
failure with Xcode 15 linker
* `#19359 <https://github.com/scipy/scipy/issues/19359>`__: BUG:
DiscreteAliasUrn construction fails with UNURANError for...
* `#19387 <https://github.com/scipy/scipy/issues/19387>`__: BUG: problem
importing libgfortran.5.dylib on macOS Sonoma
* `#19403 <https://github.com/scipy/scipy/issues/19403>`__: BUG:
scipy.sparse.lil_matrix division by complex number leads...
* `#19437 <https://github.com/scipy/scipy/issues/19437>`__: BUG: can't
install scipy on mac m1 with poetry due to incompatible...
* `#19500 <https://github.com/scipy/scipy/issues/19500>`__: DOC: doc build
failing
* `#19513 <https://github.com/scipy/scipy/issues/19513>`__: BUG: Python
version constraints in releases causes issues for...


Pull requests for 1.11.4


* `#19230 <https://github.com/scipy/scipy/pull/19230>`__: DOC, MAINT:
workaround for py311 docs
* `#19307 <https://github.com/scipy/scipy/pull/19307>`__: set idx_dtype in
sparse dia_array.tocoo
* `#19316 <https://github.com/scipy/scipy/pull/19316>`__: MAINT: Prep 1.11.4
* `#19320 <https://github.com/scipy/scipy/pull/19320>`__: BLD: fix up
version parsing issue in cythonize.py for setup.py...
* `#19329 <https://github.com/scipy/scipy/pull/19329>`__: DOC:
stats.chisquare: result object contains attribute 'statistic'
* `#19335 <https://github.com/scipy/scipy/pull/19335>`__: BUG: fix pow
method for sparrays with power zero
* `#19364 <https://github.com/scipy/scipy/pull/19364>`__: MAINT, BUG:
stats: update the UNU.RAN submodule with DAU fix
* `#19379 <https://github.com/scipy/scipy/pull/19379>`__: BUG: Restore the
original behavior of 'trf' from least_squares...
* `#19400 <https://github.com/scipy/scipy/pull/19400>`__: BLD: use classic
linker on macOS 14 (Sonoma), the new linker...
* `#19408 <https://github.com/scipy/scipy/pull/19408>`__: BUG: Fix
typecasting problem in scipy.sparse.lil_matrix truediv
* `#19504 <https://github.com/scipy/scipy/pull/19504>`__: DOC, MAINT: Bump
CircleCI Python version to 3.11
* `#19517 <https://github.com/scipy/scipy/pull/19517>`__: MAINT, REL: unpin
Python 1.11.x branch
* `#19550 <https://github.com/scipy/scipy/pull/19550>`__: MAINT, BLD:
poetry loongarch shims

Checksums
=

MD5
~~~

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 scipy-1.11.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
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 scipy-1.11.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
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 scipy-1.11.4-cp311-cp311-macosx_10_9_x86_64.whl
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340b520348315d183455e7b79fc0c1d3
 scipy-1.11.4-cp311-c

[Numpy-discussion] ANN: SciPy 1.11.3

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team, I'm pleased to announce the
release of SciPy 1.11.3,
which is a bug fix release.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.11.3

One of a few ways to install this release with pip:

pip install scipy==1.11.3

==
SciPy 1.11.3 Release Notes
==

SciPy 1.11.3 is a bug-fix release with no new features
compared to 1.11.2.

Authors
===
* Name (commits)
* Jake Bowhay (2)
* CJ Carey (1)
* Colin Carroll (1) +
* Anirudh Dagar (2)
* drestebon (1) +
* Ralf Gommers (5)
* Matt Haberland (2)
* Julien Jerphanion (1)
* Uwe L. Korn (1) +
* Ellie Litwack (2)
* Andrew Nelson (5)
* Bharat Raghunathan (1)
* Tyler Reddy (37)
* Søren Fuglede Jørgensen (2)
* Hielke Walinga (1) +
* Warren Weckesser (1)
* Bernhard M. Wiedemann (1)

A total of 17 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 1.11.3


* `#15093 <https://github.com/scipy/scipy/issues/15093>`__: BUG:
scipy.optimize's trust-constr algorithm hangs when keep-feasible...
* `#15273 <https://github.com/scipy/scipy/issues/15273>`__: freqz:
suboptimal performance for worN=2\*\*n+1, include_nyquist=True...
* `#17269 <https://github.com/scipy/scipy/issues/17269>`__: Bug in
scipy.sparse.csgraph.min_weight_full_bipartite_matching
* `#17289 <https://github.com/scipy/scipy/issues/17289>`__: BUG: Different
results between numpy.fft.rfft and scipy.signal.freqz
* `#18716 <https://github.com/scipy/scipy/issues/18716>`__: Buffer dtype
mismatch, expected 'ITYPE_t' but got 'long'
* `#18782 <https://github.com/scipy/scipy/issues/18782>`__: BUG: johnsonsu
distribution no longer accepts integer \`b\` parameter
* `#18922 <https://github.com/scipy/scipy/issues/18922>`__: BUG: dev.py has
\`distutils\` usage
* `#19101 <https://github.com/scipy/scipy/issues/19101>`__: BUG: mesonpy
embeds random path in .pyx files
* `#19103 <https://github.com/scipy/scipy/issues/19103>`__: BUG: Regression
in 1.11.2: optimize.least_squares with method='trf'...
* `#19132 <https://github.com/scipy/scipy/issues/19132>`__: BUG: Build
fails on latest commit
* `#19149 <https://github.com/scipy/scipy/issues/19149>`__: BUG:
scipy.sparse.csgraph.laplacian raises AttributeError on...
* `#19197 <https://github.com/scipy/scipy/issues/19197>`__: BUG: Incorrect
sampling from zero rank covariance


Pull requests for 1.11.3
---

* `#17633 <https://github.com/scipy/scipy/pull/17633>`__: BUG: add
infeasibility checks to min_weight_full_bipartite_matching
* `#18784 <https://github.com/scipy/scipy/pull/18784>`__: BUG: Allow
johnsonsu parameters to be floats
* `#18913 <https://github.com/scipy/scipy/pull/18913>`__: BUG:
sparse.csgraph: Support int64 indices in traversal.pyx
* `#18924 <https://github.com/scipy/scipy/pull/18924>`__: BUG: Fix
python3.12 distutils dev.py build
* `#18956 <https://github.com/scipy/scipy/pull/18956>`__: BUG: trust-constr
Bounds exclusive
* `#19076 <https://github.com/scipy/scipy/pull/19076>`__: MAINT: should not
be using np.float64() on arrays
* `#19084 <https://github.com/scipy/scipy/pull/19084>`__: REL, MAINT: prep
for 1.11.3
* `#19111 <https://github.com/scipy/scipy/pull/19111>`__: BUG: Fixes #19103
by adding back make_strictly_feasible to lsq...
* `#19123 <https://github.com/scipy/scipy/pull/19123>`__: BLD: Avoid
absolute pathnames in .pyx files
* `#19135 <https://github.com/scipy/scipy/pull/19135>`__: MAINT: signal:
Remove the cval parameter from the private function...
* `#19139 <https://github.com/scipy/scipy/pull/19139>`__: BLD: revert to
using published wheels [wheel build]
* `#19156 <https://github.com/scipy/scipy/pull/19156>`__: BUG: Support
sparse arrays in scipy.sparse.csgraph.laplacian
* `#19199 <https://github.com/scipy/scipy/pull/19199>`__: MAINT:
stats.CovViaEigendecomposition: fix \`_LA\` attribute...
* `#19200 <https://github.com/scipy/scipy/pull/19200>`__: TST: fix
\`TestODR.test_implicit\` test failure with tolerance...
* `#19208 <https://github.com/scipy/scipy/pull/19208>`__: BUG: freqz rfft
grid fix
* `#19280 <https://github.com/scipy/scipy/pull/19280>`__: MAINT: newton,
make sure x0 is an inexact type
* `#19286 <https://github.com/scipy/scipy/pull/19286>`__: BUG: stats: fix
build failure due to incorrect Boost policies...
* `#19290 <https://github.com/scipy/scipy/pull/19290>`__: BLD: add float.h
include to \`_fpumode.c\`, fixes Clang on Windows...
* `#19299 <https://github.com/scipy/scipy/pull/19299>`__: MAINT: fix
libquadmath licence

Checksums
=

MD

[Numpy-discussion] ANN: SciPy 1.11.2

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team, I'm pleased to announce the
release of SciPy 1.11.2, which
includes new wheels for Python 3.12 and musllinux.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.11.2

One of a few ways to install this release with pip:

pip install scipy==1.11.2

==
SciPy 1.11.2 Release Notes
==

SciPy 1.11.2 is a bug-fix release with no new features
compared to 1.11.1. Python 3.12 and musllinux wheels
are provided with this release.

Authors
===
* Name (commits)
* Evgeni Burovski (2)
* CJ Carey (3)
* Dieter Werthmüller (1)
* elbarso (1) +
* Ralf Gommers (2)
* Matt Haberland (1)
* jokasimr (1) +
* Thilo Leitzbach (1) +
* LemonBoy (1) +
* Ellie Litwack (2) +
* Sturla Molden (1)
* Andrew Nelson (5)
* Tyler Reddy (39)
* Daniel Schmitz (6)
* Dan Schult (2)
* Albert Steppi (1)
* Matus Valo (1)
* Stefan van der Walt (1)

A total of 18 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 1.11.2


* `#4690 <https://github.com/scipy/scipy/issues/4690>`__:
special.jn_zeros(281, 6) hangs
* `#12247 <https://github.com/scipy/scipy/issues/12247>`__: Complex matrix
square root of positive semi-definite matrix
* `#18398 <https://github.com/scipy/scipy/issues/18398>`__: BUG:
\`loadmat\` fails to load matlab structures with anonymous...
* `#18603 <https://github.com/scipy/scipy/issues/18603>`__: BUG: Floating
point CSC with int64 indices doesn't work with...
* `#18730 <https://github.com/scipy/scipy/issues/18730>`__: BUG:
\`scipy.optimize.minimize\` fails when \`dtype=float32\`...
* `#18788 <https://github.com/scipy/scipy/issues/18788>`__: DOC: Broken
link to installation instructions in README.rst
* `#18792 <https://github.com/scipy/scipy/issues/18792>`__: BUG: Build
failure with Cython 3.0.0b3 if scipy is already installed
* `#18793 <https://github.com/scipy/scipy/issues/18793>`__: BUG:
optimize.least_squares with method='trf' yields wrong result...
* `#18800 <https://github.com/scipy/scipy/issues/18800>`__: BUG:
cKDtree.query no longer accepts DataFrame as input
* `#19002 <https://github.com/scipy/scipy/issues/19002>`__: Spalde error
with scipy 1.10: 0-th dimension must be fixed
* `#19022 <https://github.com/scipy/scipy/issues/19022>`__: BUG:

* `#19026 <https://github.com/scipy/scipy/issues/19026>`__: BUG:
Compilation of scipy 1.10.1 and 1.11.1 fails with Python...


Pull requests for 1.11.2
---

* `#17918 <https://github.com/scipy/scipy/pull/17918>`__: BUG: Fix error in
linalg/_matfuncs_sqrtm.py
* `#18644 <https://github.com/scipy/scipy/pull/18644>`__: BUG:
sparse.linalg: Cast index arrays to intc before calling...
* `#18784 <https://github.com/scipy/scipy/pull/18784>`__: Allow johnsonsu
parameters to be floats
* `#18785 <https://github.com/scipy/scipy/pull/18785>`__: MAINT: stats: fix
NumPy DeprecationWarnings
* `#18787 <https://github.com/scipy/scipy/pull/18787>`__: REL, MAINT: prep
for 1.11.2
* `#18790 <https://github.com/scipy/scipy/pull/18790>`__: DOC: Fix broken
link to installation guide in README
* `#18804 <https://github.com/scipy/scipy/pull/18804>`__: BUG: Ensure
cKDtree.query does not pass Pandas DataFrame to np.isfinite
* `#18809 <https://github.com/scipy/scipy/pull/18809>`__: CI, MAINT: 32-bit
Pillow pin
* `#18810 <https://github.com/scipy/scipy/pull/18810>`__: BLD: copy
\`cython_optimize.pxd\` to build dir
* `#18825 <https://github.com/scipy/scipy/pull/18825>`__: BUG: make
\`L-BFGS-B\` optimizer work with single precision gradient
* `#18831 <https://github.com/scipy/scipy/pull/18831>`__: BUG: io/matlab:
Fix loading of mat files containing fn handles...
* `#18859 <https://github.com/scipy/scipy/pull/18859>`__: BUG: make
Bessel-roots function not hang and not skip roots
* `#18894 <https://github.com/scipy/scipy/pull/18894>`__: DOC: linking
interp1d docstring to tutorial
* `#18896 <https://github.com/scipy/scipy/pull/18896>`__: BUG: lsq trf
gives x=1e-10 if x0 is near a bound
* `#18937 <https://github.com/scipy/scipy/pull/18937>`__: CI/BLD: create
cp312 wheels
* `#18961 <https://github.com/scipy/scipy/pull/18961>`__: DOC: Fix
installation instructions using venv/pip
* `#18985 <https://github.com/scipy/scipy/pull/18985>`__: CI: move the
musllinux Cirrus job to GHA, optimize other jobs
* `#18999 <https://github.com/scipy/scipy/pull/18999>`__: CI: reduce Cirrus
CI usage during wheel builds
* `#19004 <https://github.com/scipy/scipy/pull/19004>`__: BUG: interpolate:
fix spalde with len(c) < len(t)
* `#19025 <https://github.com

[Numpy-discussion] ANN: SciPy 1.11.1

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team, I'm pleased to announce the
release of SciPy 1.11.1, which
addresses a few bugs and in particular a licensing issue discovered shortly
after the release of 1.11.0,
which has now been yanked from PyPI.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.11.1

One of a few ways to install this release with pip:

pip install scipy==1.11.1

==
SciPy 1.11.1 Release Notes
==

SciPy 1.11.1 is a bug-fix release with no new features
compared to 1.11.0. In particular, a licensing issue
discovered after the release of 1.11.0 has been addressed.

Authors
===

* Name (commits)
* h-vetinari (1)
* Robert Kern (1)
* Ilhan Polat (4)
* Tyler Reddy (8)

A total of 4 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 1.11.1


* `#18739 <https://github.com/scipy/scipy/issues/18739>`__: BUG: run method
of scipy.odr.ODR class fails when delta0 parameter...
* `#18751 <https://github.com/scipy/scipy/issues/18751>`__: BUG: segfault
in \`scipy.linalg.lu\` on x86_64 windows and macos...
* `#18753 <https://github.com/scipy/scipy/issues/18753>`__: BUG: factorial
return type inconsistent for 0-dim arrays
* `#18759 <https://github.com/scipy/scipy/issues/18759>`__: determinant of
a 1x1 matrix returns an array, not a scalar
* `#18765 <https://github.com/scipy/scipy/issues/18765>`__: Licensing
concern


Pull requests for 1.11.1


* `#18741 <https://github.com/scipy/scipy/pull/18741>`__: BUG: Fix work
array construction for various weight shapes.
* `#18747 <https://github.com/scipy/scipy/pull/18747>`__: REL, MAINT: prep
for 1.11.1
* `#18754 <https://github.com/scipy/scipy/pull/18754>`__: BUG: fix handling
for \`factorial(..., exact=False)\` for 0-dim...
* `#18762 <https://github.com/scipy/scipy/pull/18762>`__: FIX:linalg.lu:Guard
against permute_l out of bound behavior
* `#18763 <https://github.com/scipy/scipy/pull/18763>`__:
MAINT:linalg.det:Return scalars for singleton inputs
* `#18778 <https://github.com/scipy/scipy/pull/18778>`__: MAINT: fix unuran
licensing

Checksums
=

MD5
~~~

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[Numpy-discussion] ANN: SciPy 1.10.1

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team, I'm pleased to announce the
release of SciPy 1.10.1.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.10.1

One of a few ways to install this release with pip:

pip install scipy==1.10.1

==
SciPy 1.10.1 Release Notes
==

SciPy 1.10.1 is a bug-fix release with no new features
compared to 1.10.0.

Authors
===
* Name (commits)
* alice (1) +
* Matt Borland (2) +
* Evgeni Burovski (2)
* CJ Carey (1)
* Ralf Gommers (9)
* Brett Graham (1) +
* Matt Haberland (5)
* Alex Herbert (1) +
* Ganesh Kathiresan (2) +
* Rishi Kulkarni (1) +
* Loïc Estève (1)
* Michał Górny (1) +
* Jarrod Millman (1)
* Andrew Nelson (4)
* Tyler Reddy (50)
* Pamphile Roy (2)
* Eli Schwartz (2)
* Tomer Sery (1) +
* Kai Striega (1)
* Jacopo Tissino (1) +
* windows-server-2003 (1)

A total of 21 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 1.10.1


* `#14980 <https://github.com/scipy/scipy/issues/14980>`__: BUG: Johnson's
algorithm fails without negative cycles
* `#17670 <https://github.com/scipy/scipy/issues/17670>`__: Failed to
install on Raspberry Pi (ARM) 32bit in 3.11.1
* `#17715 <https://github.com/scipy/scipy/issues/17715>`__:
scipy.stats.bootstrap broke with statistic returning multiple...
* `#17716 <https://github.com/scipy/scipy/issues/17716>`__: BUG:
interpolate.interpn fails with read only input
* `#17718 <https://github.com/scipy/scipy/issues/17718>`__: BUG:
RegularGridInterpolator 2D mixed precision crashes
* `#17727 <https://github.com/scipy/scipy/issues/17727>`__: BUG:
RegularGridInterpolator does not work on non-native byteorder...
* `#17736 <https://github.com/scipy/scipy/issues/17736>`__: BUG: SciPy
requires OpenBLAS even when building against a different...
* `#17775 <https://github.com/scipy/scipy/issues/17775>`__: BUG: Asymptotic
computation of ksone.sf has intermediate overflow
* `#17782 <https://github.com/scipy/scipy/issues/17782>`__: BUG: Segfault
in scipy.sparse.csgraph.shortest_path() with v1.10.0
* `#17795 <https://github.com/scipy/scipy/issues/17795>`__: BUG:
stats.pearsonr one-sided hypothesis yields incorrect p-value...
* `#17801 <https://github.com/scipy/scipy/issues/17801>`__: BUG:
stats.powerlaw.fit: raises OverflowError
* `#17808 <https://github.com/scipy/scipy/issues/17808>`__: BUG: name of
cython executable is hardcoded in _build_utils/cythoner.py
* `#17811 <https://github.com/scipy/scipy/issues/17811>`__: CI job with
numpy nightly build failing on missing \`_ArrayFunctionDispatcher.__code__\`
* `#17839 <https://github.com/scipy/scipy/issues/17839>`__: BUG: 1.10.0
tests fail on i386 and other less common arches
* `#17896 <https://github.com/scipy/scipy/issues/17896>`__: DOC: publicly
expose \`multivariate_normal\` attributes \`mean\`...
* `#17934 <https://github.com/scipy/scipy/issues/17934>`__: BUG: meson
\`__config__\` generation - truncated unicode characters
* `#17938 <https://github.com/scipy/scipy/issues/17938>`__: BUG:
\`scipy.stats.qmc.LatinHypercube\` with \`optimization="random-cd"\`...


Pull requests for 1.10.1
---

* `#17712 <https://github.com/scipy/scipy/pull/17712>`__: REL, MAINT:
prepare for 1.10.1
* `#17717 <https://github.com/scipy/scipy/pull/17717>`__: BUG: allow
readonly input to interpolate.interpn
* `#17721 <https://github.com/scipy/scipy/pull/17721>`__: MAINT: update
\`meson-python\` upper bound to <0.13.0
* `#17726 <https://github.com/scipy/scipy/pull/17726>`__: BUG:
interpolate/RGI: upcast float32 to float64
* `#17735 <https://github.com/scipy/scipy/pull/17735>`__: MAINT:
stats.bootstrap: fix BCa with vector-valued statistics
* `#17743 <https://github.com/scipy/scipy/pull/17743>`__: DOC: improve the
docs on using BLAS/LAPACK libraries with Meson
* `#1 <https://github.com/scipy/scipy/pull/1>`__: BLD: link to
libatomic if necessary
* `#17783 <https://github.com/scipy/scipy/pull/17783>`__: BUG: Correct
intermediate overflow in KS one asymptotic in SciPy.stats
* `#17790 <https://github.com/scipy/scipy/pull/17790>`__: BUG: signal: fix
check_malloc extern declaration type
* `#17797 <https://github.com/scipy/scipy/pull/17797>`__: MAINT:
stats.pearsonr: correct p-value with negative correlation...
* `#17800 <https://github.com/scipy/scipy/pull/17800>`__: [sparse.csgraph]
Fix a bug in dijkstra and johnson algorithm
* `#17803 <https://github.com/scipy/scipy/pull/17803>`__: MAINT: add
missing \`__init__.py\` in test folder
* `#17806 <https://github.com/scipy/scipy/pull/17806>`__: MAINT

[Numpy-discussion] Re: Road to NumPy 2.0

[Tyler Reddy]

For NEP 47/array API standard, do we have a sense for how far off
numpy.array_api is from passing a tagged version of the conformance test
suite? Can you do something like "import numpy.array_api as np" and then
"export ARRAY_API_TESTS_MODULE=numpy"? Probably not exactly that, but you
likely know what I mean. I'm guessing someone has already checked this, but
maybe posting a short summary of the current test suite result on the
project board item would be nice. Incidentally, is there a short summary of
how well the other major libs are doing with this suite somewhere?

Would you turn that test suite on in a subset of the CI to enforce
conformance moving forward when the time is right?

On Sun, 15 Jan 2023 at 05:46, Ralf Gommers  wrote:

>
>
> On Wed, Jan 11, 2023 at 1:59 PM Sebastian Berg 
> wrote:
>
>> Hi all,
>>
>> as brought up many times, I would like to aim for a NumPy 2.0.  The
>> current hope would be to release within the year and start adding small
>> breaking changes soon, but hidden behind feature flags.  Similar to what is
>> already the case for NEP 50
>>  with `export
>> NPY_PROMOTION_STATE=weak`.
>>
>> Below, is a draft version for a NEP, I have also created the
>> corresponding project board on github.
>> Clearly, especially specific changes will need more discussion, but there
>> are some clearer bigger ones as well as small changes that are breaking but
>> should be easy to adapt for.
>>
>> Thanks to Inessa and Ralf who helped draft and revise this!
>>
>
> Thanks for drafting this proposal and leading this effort Sebastian!
>
> It seems like no one wants to be the first to reply here, so I'll try to
> get us started:) My opinion has always been that NumPy 2.0 should be a
> "major" thing, and either reserved for a needed ABI break or if we'd have
> other compelling features or needs. It looks to me like we have now reached
> that point. In particular, Sebastian as the main developer of new dtype and
> ufunc internals features, seems to have reached the point where the need
> for backwards compatibility in the C API is imposing too much of a burden.
> Making that work easier is enough of a reason for me to be +1 on a NumPy
> 2.0. After so many years, saying that it's fine to have a breaking release
> to clean things up is very likely a good thing long term.
>
> With that need established, other important improvements that are already
> in the pipeline and best done in a 2.0 release, like enabling NEP 50 and
> Python API improvements, make the overall picture a compelling one.
>
> I also like the proposed logistics: any major change needs to land on a
> roadmap for 2.0, and for that it needs to have two champions who commit to
> getting it done. Not breaking our regular 6-monthly releases schedules
> looks like a good plan. Having a feature flag for the 1.25.0 release (June)
> and then making breaking changes the default in the July-December period
> seems very reasonable.
>
> Cheers,
> Ralf
>
>
>
>>
>>
>> Road to NumPy 2.0
>>
>> *Note:* This is a living document. We are prepared to modify it through
>> continued dialogue with the community. Its acceptance indicates consensus
>> on the process and timelines.
>>
>> <#m_-5453977658075525012_m_-4971028583323681657_Abstract>Abstract
>> NumPy 2.0 release is an opportunity to make some complex changes for
>> which a normal deprecation wouldn’t be viable as the user impact may be
>> larger than is normally considered acceptable for a minor release. Yet,
>> NumPy 2.0 is *not* meant to be a large breaking release. Most users
>> should not need to worry about introduced changes.
>> This document contains essential information about the work on NumPy 2.0
>> release.
>> <#m_-5453977658075525012_m_-4971028583323681657_Motivation-and-impact>Motivation
>> and impact
>> NumPy 2.0 release is required for fixing old bugs and modernizing NumPy’s
>> code base. It is not planned to be a “break the world release”. This means:
>>
>>- It must be possible to compile downstream packages to be compatible
>>with both new and old NumPy versions. However, the C-API is expected to be
>>broken. The path to achieve this compatibility will be defined as a *high
>>priority* project.
>>- The *majority* of users should not require code updates or such
>>updates should be very easy to do. Expert users are likely to notice
>>changes though.
>>- We accept that some NumPy users may not able to adopt NumPy 2.0
>>immediately or may have to wait until following releases for adoption.
>>
>> One should keep in mind that even bug fixes can break the code of a small
>> number of users.
>> <#m_-5453977658075525012_m_-4971028583323681657_Timeline>Timeline
>> NumPy 2.0 will be scheduled for release in Jan 2024. Projects and changes
>> should be proposed as soon as possible. We propose a NumPy team meeting
>> around April 2023 (details to be discussed) in order to finalize
>> high-impact projects and re

[Numpy-discussion] ANN: SciPy 1.9.3

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team, I'm pleased to announce the
release of SciPy 1.9.3, which is a bug fix release.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/ and at:
https://github.com/scipy/scipy/releases/tag/v1.9.3

=
SciPy 1.9.3 Release Notes
=

SciPy 1.9.3 is a bug-fix release with no new features
compared to 1.9.2.

Authors
==

* Jelle Aalbers (1)
* Peter Bell (1)
* Jake Bowhay (3)
* Matthew Brett (3)
* Evgeni Burovski (5)
* drpeteb (1) +
* Sebastian Ehlert (1) +
* GavinZhang (1) +
* Ralf Gommers (2)
* Matt Haberland (15)
* Lakshaya Inani (1) +
* Joseph T. Iosue (1)
* Nathan Jacobi (1) +
* jmkuebler (1) +
* Nikita Karetnikov (1) +
* Lechnio (1) +
* Nicholas McKibben (1)
* Andrew Nelson (1)
* o-alexandre-felipe (1) +
* Tirth Patel (1)
* Tyler Reddy (51)
* Martin Reinecke (1)
* Marie Roald (1) +
* Pamphile Roy (2)
* Eli Schwartz (1)
* serge-sans-paille (1)
* ehsan shirvanian (1) +
* Mamoru TASAKA (1) +
* Samuel Wallan (1)
* Warren Weckesser (7)
* Gavin Zhang (1) +

A total of 31 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 1.9.3
---

* `#3691 <https://github.com/scipy/scipy/issues/3691>`__:
scipy.interpolate.UnivariateSpline segfault
* `#5286 <https://github.com/scipy/scipy/issues/5286>`__: BUG:
multivariate_normal returns a pdf for values outside its...
* `#6551 <https://github.com/scipy/scipy/issues/6551>`__: BUG: stats:
inconsistency in docs and behavior of gmean and hmean
* `#9245 <https://github.com/scipy/scipy/issues/9245>`__: running
scipy.interpolate.tests.test_fitpack::test_bisplev_integer_overflow...
* `#12471 <https://github.com/scipy/scipy/issues/12471>`__:
test_bisplev_integer_overflow: Segmentation fault (core dumped)
* `#13321 <https://github.com/scipy/scipy/issues/13321>`__: Bug: setting
iprint=0 hides all output from fmin_l_bfgs_b, but...
* `#13730 <https://github.com/scipy/scipy/issues/13730>`__:
\`scipy.stats.mood\` does not correct for ties
* `#14019 <https://github.com/scipy/scipy/issues/14019>`__: ks_2samp throws
\`RuntimeWarning: overflow encountered in double_scalars\`
* `#14589 <https://github.com/scipy/scipy/issues/14589>`__: \`shgo\` error
since scipy 1.8.0.dev0+1529.803e52d
* `#14591 <https://github.com/scipy/scipy/issues/14591>`__: Input data
validation for RectSphereBivariateSpline
* `#15101 <https://github.com/scipy/scipy/issues/15101>`__: BUG: binom.pmf
- RuntimeWarning: divide by zero
* `#15342 <https://github.com/scipy/scipy/issues/15342>`__: BUG:
scipy.optimize.minimize: Powell's method function evaluated...
* `#15964 <https://github.com/scipy/scipy/issues/15964>`__: BUG:
lombscargle fails if argument is a view
* `#16211 <https://github.com/scipy/scipy/issues/16211>`__: BUG: Possible
bug when using winsorize on pandas data instead...
* `#16459 <https://github.com/scipy/scipy/issues/16459>`__: BUG:
stats.ttest_ind returns wrong p-values with permutations
* `#16500 <https://github.com/scipy/scipy/issues/16500>`__: odr.Model
default meta value fails with __getattr__
* `#16519 <https://github.com/scipy/scipy/issues/16519>`__: BUG: Error in
error message for incorrect sample dimension in...
* `#16527 <https://github.com/scipy/scipy/issues/16527>`__: BUG: dimension
of isuppz in syevr is mistranslated
* `#16600 <https://github.com/scipy/scipy/issues/16600>`__: BUG:
\`KDTree\`'s optional argument \`eps\` seems to have no...
* `#16656 <https://github.com/scipy/scipy/issues/16656>`__: dtype not
preserved with operations on sparse arrays
* `#16751 <https://github.com/scipy/scipy/issues/16751>`__: BUG:
\`stats.fit\` on \`boltzmann\` expects \`bound\` for \`lambda\`,...
* `#17012 <https://github.com/scipy/scipy/issues/17012>`__: BUG: Small
oversight in sparse.linalg.lsmr?
* `#17020 <https://github.com/scipy/scipy/issues/17020>`__: BUG: Build
failure due to problems with shebang line in cythoner.py
* `#17088 <https://github.com/scipy/scipy/issues/17088>`__: BUG:
stats.rayleigh.fit: returns \`loc\` that is inconsistent...
* `#17104 <https://github.com/scipy/scipy/issues/17104>`__: BUG? Incorrect
branch in \`LAMV\` / \`_specfunc.lamv\`
* `#17196 <https://github.com/scipy/scipy/issues/17196>`__: DOC: keepdims
in stats.mode is incorrectly documented


Pull requests for 1.9.3
--

* `#5288 <https://github.com/scipy/scipy/pull/5288>`__: BUG:
multivariate_normal returns a pdf for values outside its...
* `#13322 <https://github.com/scipy/scipy/pull/13322>`__: Bug: setting
iprint=0 hides all output from fmin_l_bfgs_b, but...
* `#13349 <https://github.com/scipy/scipy/pull/13349>`__: BUG: stats

[Numpy-discussion] ANN: SciPy 1.9.2

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team, I'm pleased to announce the
release of SciPy 1.9.2, which is a bug fix release that includes
binary wheels for Python 3.11.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/ and at:
https://github.com/scipy/scipy/releases/tag/v1.9.2

One of a few ways to install this release with pip:
pip install scipy==1.9.2

=
SciPy 1.9.2 Release Notes
=

SciPy 1.9.2 is a bug-fix release with no new features
compared to 1.9.1. It also provides wheels for Python 3.11
on several platforms.

Authors
==

* Hood Chatham (1)
* Thomas J. Fan (1)
* Ralf Gommers (22)
* Matt Haberland (5)
* Julien Jerphanion (1)
* Loïc Estève (1)
* Nicholas McKibben (2)
* Naoto Mizuno (1)
* Andrew Nelson (3)
* Tyler Reddy (28)
* Pamphile Roy (1)
* Ewout ter Hoeven (2)
* Warren Weckesser (1)
* Meekail Zain (1) +

A total of 14 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 1.9.2
---

* `#16545 <https://github.com/scipy/scipy/issues/16545>`__: BUG: 1.9.0rc1:
\`OptimizeResult\` not populated when \`optimize.milp\`...
* `#16569 <https://github.com/scipy/scipy/issues/16569>`__: BUG:
\`sparse.hstack\` returns incorrect result when the stack...
* `#16898 <https://github.com/scipy/scipy/issues/16898>`__: BUG:
optimize.minimize backwards compatability in scipy 1.9
* `#16935 <https://github.com/scipy/scipy/issues/16935>`__: BUG: using msvc
+ meson to build scipy --> cl cannot be used...
* `#16952 <https://github.com/scipy/scipy/issues/16952>`__: BUG: error from
\`scipy.stats.mode\` with \`NaN\`s, \`axis !=...
* `#16964 <https://github.com/scipy/scipy/issues/16964>`__: BUG: scipy
1.7.3 wheels on PyPI require numpy<1.23 in contradiction...
* `#17026 <https://github.com/scipy/scipy/issues/17026>`__: BUG:
ncf_gen::ppf(..) causes segfault
* `#17050 <https://github.com/scipy/scipy/issues/17050>`__: Pearson3 PPF
does not function properly with negative skew.
* `#17124 <https://github.com/scipy/scipy/issues/17124>`__: BUG: OSX-64
Test failure test_ppf_against_tables getting NaN


Pull requests for 1.9.2
--

* `#16628 <https://github.com/scipy/scipy/pull/16628>`__: FIX: Updated
dtype resolution in \`_stack_along_minor_axis\`
* `#16814 <https://github.com/scipy/scipy/pull/16814>`__: FIX: milp: return
feasible solutions if available on time out
* `#16842 <https://github.com/scipy/scipy/pull/16842>`__: ENH: cibuildwheel
infrastructure
* `#16909 <https://github.com/scipy/scipy/pull/16909>`__: MAINT: minimize,
restore squeezed ((1.0)) addresses #16898
* `#16911 <https://github.com/scipy/scipy/pull/16911>`__: REL: prep for
SciPy 1.9.2
* `#16922 <https://github.com/scipy/scipy/pull/16922>`__: DOC: update
version switcher for 1.9.1 and pin theme to 0.9
* `#16934 <https://github.com/scipy/scipy/pull/16934>`__: MAINT: cast
\`linear_sum_assignment\` to PyCFunction
* `#16943 <https://github.com/scipy/scipy/pull/16943>`__: BLD: use compiler
flags in a more portable way
* `#16954 <https://github.com/scipy/scipy/pull/16954>`__: MAINT:
stats.mode: fix bug with \`axis!=1\`, \`nan_policy='omit'\`,...
* `#16966 <https://github.com/scipy/scipy/pull/16966>`__: MAINT: fix NumPy
upper bound
* `#16969 <https://github.com/scipy/scipy/pull/16969>`__: BLD: fix usage of
\`get_install_data\`, which defaults to purelib
* `#16975 <https://github.com/scipy/scipy/pull/16975>`__: DOC: Update numpy
supported versions for 1.9.2
* `#16991 <https://github.com/scipy/scipy/pull/16991>`__: BLD: fixes for
building with MSVC and Intel Fortran
* `#17011 <https://github.com/scipy/scipy/pull/17011>`__: Rudimentary test
for manylinux_aarch64 with cibuildwheel
* `#17013 <https://github.com/scipy/scipy/pull/17013>`__: BLD: make MKL
detection a little more robust, add notes on TODOs
* `#17046 <https://github.com/scipy/scipy/pull/17046>`__: CI: Update
cibuildwheel to 2.10.1
* `#17055 <https://github.com/scipy/scipy/pull/17055>`__: MAINT:
stats.pearson3: fix ppf for negative skew
* `#17064 <https://github.com/scipy/scipy/pull/17064>`__: BUG: Fix
numerical precision error of \`truncnorm.logcdf\` when...
* `#17096 <https://github.com/scipy/scipy/pull/17096>`__: FIX: ensure a
hold on GIL before raising warnings/errors
* `#17127 <https://github.com/scipy/scipy/pull/17127>`__: TST:
stats.studentized_range: fix incorrect test
* `#17131 <https://github.com/scipy/scipy/pull/17131>`__: MAINT:
pyproject.toml: Update build system requirements
* `#17132 <https://github.com/scipy/scipy/pull/17132>`__: MAINT: 1.9.2
backports

Checksums
=

MD5
~~~

baceb748311a429676fd210c3a97e791

[Numpy-discussion] ANN: SciPy 1.9.1

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team, I'm pleased to announce the
release of SciPy 1.9.1, which is a bug fix release that includes
some important meson build fixes.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/ and at:
https://github.com/scipy/scipy/releases/tag/v1.9.1

One of a few ways to install this release with pip:
pip install scipy==1.9.1

=
SciPy 1.9.1 Release Notes
=

SciPy 1.9.1 is a bug-fix release with no new features
compared to 1.9.0. Notably, some important meson build
fixes are included.

Authors
==

* Anirudh Dagar (1)
* Ralf Gommers (12)
* Matt Haberland (2)
* Andrew Nelson (1)
* Tyler Reddy (14)
* Atsushi Sakai (1)
* Eli Schwartz (1)
* Warren Weckesser (2)

A total of 8 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 1.9.1
--

* `#14517 <https://github.com/scipy/scipy/issues/14517>`__:
scipy/linalg/tests/test_decomp.py::TestSchur::test_sort test...
* `#16765 <https://github.com/scipy/scipy/issues/16765>`__: DOC:
\`scipy.stats.skew\` no longer returns 0 on constant input
* `#16787 <https://github.com/scipy/scipy/issues/16787>`__: BUG: Can't
build 1.10 with mingw-w64 toolchain and numpy 1.21.6...
* `#16813 <https://github.com/scipy/scipy/issues/16813>`__: BUG:
scipy.interpolate interp1d extrapolate behaviour change...
* `#16878 <https://github.com/scipy/scipy/issues/16878>`__: BUG:
optimize.milp fails to execute when given exactly 3 constraints


Pull requests for 1.9.1
--

* `#16709 <https://github.com/scipy/scipy/pull/16709>`__: BLD: make the way
we count commits for version numbering more...
* `#16736 <https://github.com/scipy/scipy/pull/16736>`__: REL: prep for
SciPy 1.9.1
* `#16749 <https://github.com/scipy/scipy/pull/16749>`__: BLD: install
missing \`.pxd\` files, and update TODOs/FIXMEs...
* `#16750 <https://github.com/scipy/scipy/pull/16750>`__: BLD: make
OpenBLAS detection work with CMake
* `#16755 <https://github.com/scipy/scipy/pull/16755>`__: TST:
sparse.linalg: Loosen tolerance for the lobpcg test 'test_tolerance_float32'
* `#16760 <https://github.com/scipy/scipy/pull/16760>`__: BLD: use a bit
more idiomatic approach to constructing paths...
* `#16768 <https://github.com/scipy/scipy/pull/16768>`__: DOC:
stats.skew/kurtosis: returns NaN when input has only one...
* `#16794 <https://github.com/scipy/scipy/pull/16794>`__: BLD/REL: on
Windows use numpy 1.22.3 as the version to build...
* `#16822 <https://github.com/scipy/scipy/pull/16822>`__: BUG/TST: linalg:
Check the results of 'schur' more carefully.
* `#16825 <https://github.com/scipy/scipy/pull/16825>`__: BUG: interpolate:
fix "previous" and "next" extrapolate logic...
* `#16862 <https://github.com/scipy/scipy/pull/16862>`__: BUG, DOC: Fix
sphinx autosummary generation for \`odr\` and \`czt\`
* `#16881 <https://github.com/scipy/scipy/pull/16881>`__: MAINT:
optimize.milp: fix input validation when three constraints...
* `#16901 <https://github.com/scipy/scipy/pull/16901>`__: MAINT: 1.9.1
backports
* `#16904 <https://github.com/scipy/scipy/pull/16904>`__: BLD: update
dependency ranges for meson-python and pybind11 for...

Checksums
=

MD5
~~~

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0f631

[Numpy-discussion] ANN: SciPy 1.8.1

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team, I'm pleased to announce the
release of SciPy 1.8.1, which is a bug fix release that restores
Pythran usage on Windows.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/ and at:
https://github.com/scipy/scipy/releases/tag/v1.8.1

One of a few ways to install this release with pip:
pip install scipy==1.8.1

=
SciPy 1.8.1 Release Notes
=

SciPy 1.8.1 is a bug-fix release with no new features
compared to 1.8.0. Notably, usage of Pythran has been
restored for Windows builds/binaries.

Authors
==

* Henry Schreiner
* Maximilian Nöthe
* Sebastian Berg (1)
* Sameer Deshmukh (1) +
* Niels Doucet (1) +
* DWesl (4)
* Isuru Fernando (1)
* Ralf Gommers (4)
* Matt Haberland (1)
* Andrew Nelson (1)
* Dimitri Papadopoulos Orfanos (1) +
* Tirth Patel (3)
* Tyler Reddy (46)
* Pamphile Roy (7)
* Niyas Sait (1) +
* H. Vetinari (2)
* Warren Weckesser (1)

A total of 17 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 1.8.1
---

* `#15258 <https://github.com/scipy/scipy/issues/15258>`__: BUG: sparse
\`dot\` method should accept scalars
* `#15433 <https://github.com/scipy/scipy/issues/15433>`__: BUG: optimize:
minimize: \`ValueError\` when \`np.all(lb==ub)\`
* `#15539 <https://github.com/scipy/scipy/issues/15539>`__: BUG:
Questionable macOS wheel contents
* `#15543 <https://github.com/scipy/scipy/issues/15543>`__: REL: list
contributors using GitHub handles
* `#15552 <https://github.com/scipy/scipy/issues/15552>`__: BUG: MacOS
universal2 wheels have two gfortran shared libraries,...
* `#15636 <https://github.com/scipy/scipy/issues/15636>`__: BUG: DOCS
incorrect \`source\` link on docs
* `#15678 <https://github.com/scipy/scipy/issues/15678>`__: BUG:
scipy.stats.skew does not work with scipy.stats.bootstrap
* `#16174 <https://github.com/scipy/scipy/issues/16174>`__: Failure of
\`TestCorrelateComplex.test_rank0\` in CI with NumPy...


Pull requests for 1.8.1
--

* `#15167 <https://github.com/scipy/scipy/pull/15167>`__: CI: make sure CI
stays on VS2019 unless changed explicitly
* `#15306 <https://github.com/scipy/scipy/pull/15306>`__: Revert "BLD
Respect the --skip-build flag in setup.py"
* `#15504 <https://github.com/scipy/scipy/pull/15504>`__: MAINT: np.all(lb
== ub) for optimize.minimize
* `#15530 <https://github.com/scipy/scipy/pull/15530>`__: REL: prep for
SciPy 1.8.1
* `#15531 <https://github.com/scipy/scipy/pull/15531>`__: [BUG] Fix
importing scipy.lib._pep440
* `#15558 <https://github.com/scipy/scipy/pull/15558>`__: CI: re-enable
Pythran in Azure Windows CI jobs
* `#15566 <https://github.com/scipy/scipy/pull/15566>`__: BUG: fix error
message
* `#15580 <https://github.com/scipy/scipy/pull/15580>`__: BUG: Avoid C
Preprocessor symbol in _hypotests_pythran.py.
* `#15614 <https://github.com/scipy/scipy/pull/15614>`__: REL: filter out @
in authors name and add count
* `#15637 <https://github.com/scipy/scipy/pull/15637>`__: DOC, MAINT: fix
links to wrapped functions and SciPy's distributions
* `#15669 <https://github.com/scipy/scipy/pull/15669>`__: BUG: stats: fix a
bug in UNU.RAN error handler
* `#15691 <https://github.com/scipy/scipy/pull/15691>`__: MAINT: stats:
bootstrap: fix bug with \`method="BCa"\` when \`statistic\`...
* `#15798 <https://github.com/scipy/scipy/pull/15798>`__: MAINT,BUG: stats:
update to UNU.RAN 1.9.0
* `#15870 <https://github.com/scipy/scipy/pull/15870>`__: TST: signal:
Convert a test with 'assert_array_less' to 'less...
* `#15910 <https://github.com/scipy/scipy/pull/15910>`__: make sure CI
stays on VS2019 unless changed explicitly
* `#15926 <https://github.com/scipy/scipy/pull/15926>`__: MAINT: 1.8.1
backports/prep
* `#16035 <https://github.com/scipy/scipy/pull/16035>`__: BUG: allow scalar
input to the \`.dot\` method of sparse matrices
* `#16041 <https://github.com/scipy/scipy/pull/16041>`__: MAINT: add
include dir explicitly for PROPACK to build with classic...
* `#16139 <https://github.com/scipy/scipy/pull/16139>`__: WIP, BLD, MAINT:
git security/version shim
* `#16152 <https://github.com/scipy/scipy/pull/16152>`__: TST: Fortify
invalid-value warning filters to small changes in...
* `#16155 <https://github.com/scipy/scipy/pull/16155>`__: MAINT: correct
wrong license of Biasedurn
* `#16158 <https://github.com/scipy/scipy/pull/16158>`__: MAINT: better
UNU.RAN licensing information
* `#16163 <https://github.com/scipy/scipy/pull/16163>`__: MAINT: update
UNU.RAN copyright information
* `#16172 <https://github.com

[Numpy-discussion] Re: NEP draft for the future behaviour of scalar promotion

[Tyler Reddy]

I added a few comments on the PR. The main comments of substance I had boil
down to:
- consistency with other programming languages/major frameworks (perhaps a
few more "examples of consistency" for the new approach with others
may help strengthen the arguments?)--I know JAX was mentioned, and their
dtype promotion docs are quite nice
- one thing I struggled with in deciding if some of the "new behaviors"
were nicer was the tension between
protecting from accidental overflow vs. a more "purist" view that types
should be preserved more strictly; the
latter would seem consistent with the "principle of least surprise" when
moving from a typed language to
NumPy work perhaps, though arguably slightly less user-friendly if naively
doing some operations with
a less formal view of typing (new Python user messing around with NumPy?)

On Mon, 21 Feb 2022 at 16:35, Sebastian Berg 
wrote:

> Hi all,
>
> NumPy has awkward behaviour when it comes to promotion with 0-D arrays,
> and Python scalars.  This is both a technical challenge (numpy needs to
> inspect the values where it shouldn't), as well as surprising for
> users.
>
> Roughly speaking, I have made a proposal under the 3 points:
> * NumPy scalars and NumPy arrays always behave the same.
> * A NumPy array always respects the dtype
> * A Python scalar is "weak" so that uint8_arr + 3 returns a uint8_arr
>
> The NEP is here:
>
> https://25105-908607-gh.circle-artifacts.com/0/doc/neps/_build/html/nep-0050-scalar-promotion.html
>
> But please refer to the PR, since above may go away or get outdated:
> https://github.com/numpy/numpy/pull/21103
>
>
> Note that I have not 100% made up my mind on these, because some
> alternatives exist which may give a somewhat easier transition.
> Because of this, this is a very early draft (expect large
> changes/rewrite), but some feedback/input may go a long way to make
> sure we keep moving on this project.
>
> For those aware of the issues, it probably makes sense to skip ahead to
> the "Alternatives" section.  I do expect that a large refactor/rewrite
> will be necessary, but need some feedback to keep moving.
>
>
> I had send the poll recently:
>
> https://discuss.scientific-python.org/t/poll-future-numpy-behavior-when-mixing-arrays-numpy-scalars-and-python-scalars/202
>
> just to say, I have not completely ignored it, although (as expected)
> the results do not give a very simple answer.  Many agree with the
> choices I made, but some also seem to prefer "strong" Python types, or
> more special handling of NumPy scalars.
>
>
> Please do not hesitate to give opinions!  I am not sure we can find a
> clear "obviously right" solution.  Especially since there are tough
> backwards compatibility choices (even if most users are likely not to
> notice).  So any input is appreciated.
>
> Cheers,
>
> Sebastian
>
>
> ___
> NumPy-Discussion mailing list -- numpy-discussion@python.org
> To unsubscribe send an email to numpy-discussion-le...@python.org
> https://mail.python.org/mailman3/lists/numpy-discussion.python.org/
> Member address: tyler.je.re...@gmail.com
>
___
NumPy-Discussion mailing list -- numpy-discussion@python.org
To unsubscribe send an email to numpy-discussion-le...@python.org
https://mail.python.org/mailman3/lists/numpy-discussion.python.org/
Member address: arch...@mail-archive.com

[Numpy-discussion] ANN: SciPy 1.7.3

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team, I'm pleased to announced the
release of SciPy 1.7.3,
which is a bug fix release that includes wheels for MacOS 12+ arm64 at
Python versions 3.8, 3.9, and 3.10.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.7.3
<https://github.com/scipy/scipy/releases/tag/v1.6.3>
<https://github.com/scipy/scipy/releases/tag/v1.6.1>

One of a few ways to install this release with pip:

pip install scipy==1.7.3

=
SciPy 1.7.3 Release Notes
=

SciPy 1.7.3 is a bug-fix release that provides binary wheels
for MacOS arm64 with Python 3.8, 3.9, and 3.10. The MacOS arm64 wheels
are only available for MacOS version 12.0 and greater, as explained
in Issue 14688, linked below.

Authors
==

* Anirudh Dagar
* Ralf Gommers
* Tyler Reddy
* Pamphile Roy
* Olivier Grisel
* Isuru Fernando

A total of 6 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 1.7.3
---

* `#13364 <https://github.com/scipy/scipy/issues/13364>`__: Segmentation
fault on import of scipy.integrate on Apple M1 ARM...
* `#14688 <https://github.com/scipy/scipy/issues/14688>`__: BUG: ARPACK's
eigsh & OpenBLAS from Apple Silicon M1 (arm64)...
* `#14991 <https://github.com/scipy/scipy/issues/14991>`__: four CI
failures on pre-release job
* `#15077 <https://github.com/scipy/scipy/issues/15077>`__: Remaining test
failures for macOS arm64 wheel
* `#15081 <https://github.com/scipy/scipy/issues/15081>`__: BUG:
Segmentation fault caused by scipy.stats.qmc.qmc.update_discrepancy


Pull requests for 1.7.3
--

* `#14990 <https://github.com/scipy/scipy/pull/14990>`__: BLD: update
pyproject.toml for Python 3.10 changes
* `#15086 <https://github.com/scipy/scipy/pull/15086>`__: BUG: out of
bounds indexing in stats.qmc.update_discrepancy
* `#15090 <https://github.com/scipy/scipy/pull/15090>`__: MAINT: skip a few
failing tests in \`1.7.x\` for macOS arm64

Checksums
=

MD5
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6341d96c9f9edfd7221708636d6dab5c
 scipy-1.7.3-cp38-cp38-macosx_10_9_x86_64.whl
919b3f6c4b5f9cc137b2e40c50837ba7
 scipy-1.7.3-cp38-cp38-macosx_12_0_arm64.whl
697cb8e337a8073792aca67aa4dd7f49
 scipy-1.7.3-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl
e1c1c129731f8623f7168153f6088472
 scipy-1.7.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
6203426ffb92a0a12606eaa885d74d54
 scipy-1.7.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
936de7e1b6c4f05079ac2ea4e63d0436  scipy-1.7.3-cp38-cp38-win32.whl
9da686cd27c2e51342deb1d2d060fa08  scipy-1.7.3-cp38-cp38-win_amd64.whl
cf4e152fb2e7241e7bdd7761191590ae
 scipy-1.7.3-cp39-cp39-macosx_10_9_x86_64.whl
97f2f1ee23139230063ff07ce4e9c61b
 scipy-1.7.3-cp39-cp39-macosx_12_0_arm64.whl
df508267071a08b63f21b8ae3dcd5eb2
 scipy-1.7.3-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.whl
391662df3e0411daa08b5421e54ad9c0
 scipy-1.7.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
0587d18e903b1ceaeb6bab73f704872d
 scipy-1.7.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
3a0b4991b3a994fb6e0bbcc9c99ab5c9  scipy-1.7.3-cp39-cp39-win32.whl
4e168ff30d040edbaac53efb43d8cda4  scipy-1.7.3-cp39-cp39-win_amd64.whl
daae4fedcd479738e54fd7035445be89  scipy-1.7.3.tar.gz
9e6a6ae20e68e99031229c430f966672  scipy-1.7.3.tar.xz
1a9ceac2a40fef71b75859040e371906  scipy-1.7.3.zip

SHA256
~~

173308efba2270dcd61cd45a30dfded6ec0085b4b6eb33b5eb11ab443005e088
 scipy-1.7.3-cp310-cp310-macosx_10_9_x86_64.whl
21b66200cf44b1c3e86495e3a436fc7a26608f92b8d43d344457c54f1c024cbc
 scipy-1.7.3-cp310-cp310-macosx_12_0_arm64.whl
ceebc3c4f6a109777c0053dfa0282fddb8893eddfb0d598574acfb734a926168
 scipy-1.7.3-cp310-cp310-manylinux_2_17_aarch64.manyli

[Numpy-discussion] ANN: SciPy 1.7.2

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team I'm pleased to announce the release
of SciPy 1.7.2, which is a bug fix release that includes wheels for Python
3.10 on many platforms. Many thanks to upstream developers in the ecosystem
for their assistance in making this possible.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.7.2
<https://github.com/scipy/scipy/releases/tag/v1.6.3>
<https://github.com/scipy/scipy/releases/tag/v1.6.1>

One of a few ways to install this release with pip:

pip install scipy==1.7.2


SciPy 1.7.2 Release Notes


SciPy 1.7.2 is a bug-fix release with no new features
compared to 1.7.1. Notably, the release includes wheels
for Python 3.10, and wheels are now built with a newer
version of OpenBLAS, 0.3.17. Python 3.10 wheels are provided
for MacOS x86_64 (thin, not universal2 or arm64 at this time),
and Windows/Linux 64-bit. Many wheels are now built with newer
versions of manylinux, which may require newer versions of pip.

Authors
==

* Peter Bell
* da-woods +
* Isuru Fernando
* Ralf Gommers
* Matt Haberland
* Nicholas McKibben
* Ilhan Polat
* Judah Rand +
* Tyler Reddy
* Pamphile Roy
* Charles Harris
* Matti Picus
* Hugo van Kemenade
* Jacob Vanderplas

A total of 14 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 1.7.2
--

* `#6019 <https://github.com/scipy/scipy/issues/6019>`__: minimize_scalar
doesn't seem to honor "disp" option
* `#14321 <https://github.com/scipy/scipy/issues/14321>`__: BUG: Indexing
of CSR matrices with many rows is much slower than...
* `#14465 <https://github.com/scipy/scipy/issues/14465>`__: BUG: n-d
interpolation parameter provided to geometric_slerp
* `#14599 <https://github.com/scipy/scipy/issues/14599>`__: SciPy 1.7
builds as zipped egg, ruining imports
* `#14606 <https://github.com/scipy/scipy/issues/14606>`__: BUG: crash /
core dump when calling scipy.stats.beta.ppf with...
* `#14732 <https://github.com/scipy/scipy/issues/14732>`__: CI, TST:
pre-release failures for scipy/interpolate/tests/test_rbfinterp.py
* `#14802 <https://github.com/scipy/scipy/issues/14802>`__: CI: Azure Main
coverage job failure
* `#14829 <https://github.com/scipy/scipy/issues/14829>`__: macOS CI
failing with \`ld: library not found for -lSystem\`
* `#14887 <https://github.com/scipy/scipy/issues/14887>`__: BUG:
scipy.stats.multivariate_normal.logpdf mutates some inputs

Pull requests for 1.7.2
--

* `#14207 <https://github.com/scipy/scipy/pull/14207>`__: DOC: stats:
remove 'Methods' section from \`binomtest\` docstring...
* `#14316 <https://github.com/scipy/scipy/pull/14316>`__: MAINT: Update
\`openblas_support.py\` to support Apple Silicon
* `#14323 <https://github.com/scipy/scipy/pull/14323>`__: BUG: Speed up
sparse compressed indexing with very many rows
* `#14333 <https://github.com/scipy/scipy/pull/14333>`__: MAINT: Use
/usr/bin/linux32 so that sysconfig.get_platform()...
* `#14478 <https://github.com/scipy/scipy/pull/14478>`__: BUG:
geometric_slerp t ndim guard
* `#14605 <https://github.com/scipy/scipy/pull/14605>`__: MAINT: Skip some
interpolative decomposition tests
* `#14616 <https://github.com/scipy/scipy/pull/14616>`__: REL: update build
dependency versions in pyproject.toml for 1.7.2
* `#14618 <https://github.com/scipy/scipy/pull/14618>`__: FIX: raise
RuntimeWarning when Boost evaluation_error is encountered
* `#14672 <https://github.com/scipy/scipy/pull/14672>`__: BLD: add
\`zip_safe=False\` to the \`setup()\` call
* `#14791 <https://github.com/scipy/scipy/pull/14791>`__: MAINT: SciPy
1.7.2 prep/backports
* `#14803 <https://github.com/scipy/scipy/pull/14803>`__: MAINT: disable
include/source coverage warning.
* `#14813 <https://github.com/scipy/scipy/pull/14813>`__: Added missing
np.import_array()
* `#14831 <https://github.com/scipy/scipy/pull/14831>`__: CI: Add stdlib to
LD_LIBRARY_PATH
* `#14893 <https://github.com/scipy/scipy/pull/14893>`__: BUG: Fix
alignment errors due to relaxed stride checking
* `#14897 <https://github.com/scipy/scipy/pull/14897>`__: BUG: avoid
mutating inputs in multivariate distributions
* `#14921 <https://github.com/scipy/scipy/pull/14921>`__: MAINT: "backport"
3.10 support
* `#14937 <https://github.com/scipy/scipy/pull/14937>`__: MAINT: backports
for 1.7.2, plus update Pythran min version to...
* `#14938 <https://github.com/scipy/scipy/pull/14938>`__: TST: silence test
failures on macOS for \`beta.ppf\` overflow

Checksums
=

MD5
~~~

45913b1797379cc2e258b

[Numpy-discussion] ANN: SciPy 1.7.1

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team I'm pleased to announce
the release of SciPy 1.7.1, which is a bug fix release.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.7.1
<https://github.com/scipy/scipy/releases/tag/v1.6.3>
<https://github.com/scipy/scipy/releases/tag/v1.6.1>

One of a few ways to install this release with pip:

pip install scipy==1.7.1

=
SciPy 1.7.1 Release Notes
=

SciPy 1.7.1 is a bug-fix release with no new features
compared to 1.7.0.

Authors
===

* Peter Bell
* Evgeni Burovski
* Justin Charlong +
* Ralf Gommers
* Matti Picus
* Tyler Reddy
* Pamphile Roy
* Sebastian Wallkötter
* Arthur Volant

A total of 9 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 1.7.1
--

* `#14074 <https://github.com/scipy/scipy/issues/14074>`__: Segmentation
fault when building cKDTree with Scipy 1.6.3.
* `#14271 <https://github.com/scipy/scipy/issues/14271>`__:
scipy.io.loadmat failure in 1.7.0
* `#14273 <https://github.com/scipy/scipy/issues/14273>`__:
\`scipy.signal.{medfilt,medfilt2d}\` hit "Windows fatal exception:...
* `#14282 <https://github.com/scipy/scipy/issues/14282>`__: DOC, CI: stats
skewtest refguide failure
* `#14363 <https://github.com/scipy/scipy/issues/14363>`__: Huge stack
allocation in _sobol.pyx may cause stack overvflow
* `#14382 <https://github.com/scipy/scipy/issues/14382>`__: Memory leak in
\`scipy.spatial.distance\` for \`cdist\`
* `#14396 <https://github.com/scipy/scipy/issues/14396>`__: BUG: Sphinx 4.1
breaks the banner's logo
* `#1 <https://github.com/scipy/scipy/issues/1>`__: DOC/FEAT
Rotation.from_rotvec documents a degrees argument which...

Pull requests for 1.7.1
--

* `#14178 <https://github.com/scipy/scipy/pull/14178>`__: DEV: Update
Boschloo Exact test
* `#14264 <https://github.com/scipy/scipy/pull/14264>`__: REL: prepare for
SciPy 1.7.1
* `#14283 <https://github.com/scipy/scipy/pull/14283>`__: BUG: fix
refguide-check namedtuple handling
* `#14303 <https://github.com/scipy/scipy/pull/14303>`__: FIX: Check for
None before calling str methods
* `#14327 <https://github.com/scipy/scipy/pull/14327>`__: BUG: medfilt can
access beyond the end of an array
* `#14355 <https://github.com/scipy/scipy/pull/14355>`__: BUG: KDTree
balanced_tree is unbalanced for degenerate data
* `#14368 <https://github.com/scipy/scipy/pull/14368>`__: BUG: avoid large
cython global variable in function
* `#14384 <https://github.com/scipy/scipy/pull/14384>`__: BUG: Reference
count leak in distance_pybind
* `#14397 <https://github.com/scipy/scipy/pull/14397>`__: DOC/CI: do not
allow sphinx 4.1.
* `#14417 <https://github.com/scipy/scipy/pull/14417>`__: DOC/CI: pin
sphinx to !=4.1.0
* `#14460 <https://github.com/scipy/scipy/pull/14460>`__: DOC: add required
scipy version to kwarg
* `#14466 <https://github.com/scipy/scipy/pull/14466>`__: MAINT: 1.7.1
backports (round 1)
* `#14508 <https://github.com/scipy/scipy/pull/14508>`__: MAINT: bump
scipy-mathjax
* `#14509 <https://github.com/scipy/scipy/pull/14509>`__: MAINT: 1.7.1
backports (round 2)


Checksums
=

MD5
~~~

ef8b44a175818183de28f2c3dacf4b74
 scipy-1.7.1-cp37-cp37m-macosx_10_9_x86_64.whl
4f717b62946a6306bba88696b4992c73
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 scipy-1.7.1-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl
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 scipy-1.7.1-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl
808a907d994b98fd6dbe2050a48b8c69  scipy-1.7.1-cp38-cp38-win32.whl
688921def6681ee5abe8543aca8383c2  scipy-1.7.1-cp38-cp38-win_amd64.whl
2fe4e958cb14d0b071c494b9faee0c98
 scipy-1.7.1-cp39-cp39-macosx_10_9_x86_64.whl
dd5b4db9cf83a0594e0b651e198b16a4
 scipy-1.7.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
67c5d75378d0ba2803c1b93fe670563b
 scipy-1.7.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl
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 scipy-1.7.1-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.whl
93efd36f2c52dadbe7c

Re: [Numpy-discussion] NumPy 1.21.0 release

[Tyler Reddy]

Thanks Chuck!
___
NumPy-Discussion mailing list
NumPy-Discussion@python.org
https://mail.python.org/mailman/listinfo/numpy-discussion

[Numpy-discussion] ANN: SciPy 1.6.3

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team I'm pleased to announce
the release of SciPy 1.6.3, which is a bug fix release.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.6.3
<https://github.com/scipy/scipy/releases/tag/v1.6.1>

One of a few ways to install this release with pip:

pip install scipy==1.6.3

=
SciPy 1.6.3 Release Notes
=

SciPy 1.6.3 is a bug-fix release with no new features
compared to 1.6.2.

Authors
==

* Peter Bell
* Ralf Gommers
* Matt Haberland
* Peter Mahler Larsen
* Tirth Patel
* Tyler Reddy
* Pamphile ROY +
* Xingyu Liu +

A total of 8 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 1.6.3
---

* `#13772 <https://github.com/scipy/scipy/issues/13772>`__: Divide by zero
in distance.yule
* `#13796 <https://github.com/scipy/scipy/issues/13796>`__: CI:
prerelease_deps failures
* `#13890 <https://github.com/scipy/scipy/issues/13890>`__: TST: spatial
rotation failure in (1.6.3) wheels repo (ARM64)


Pull requests for 1.6.3
--

* `#13755 <https://github.com/scipy/scipy/pull/13755>`__: CI: fix the
matplotlib warning emitted during builing docs
* `#13773 <https://github.com/scipy/scipy/pull/13773>`__: BUG: Divide by
zero in yule dissimilarity of constant vectors
* `#13799 <https://github.com/scipy/scipy/pull/13799>`__: CI/MAINT:
deprecated np.typeDict
* `#13819 <https://github.com/scipy/scipy/pull/13819>`__: substitute
np.math.factorial with math.factorial
* `#13895 <https://github.com/scipy/scipy/pull/13895>`__: TST: add random
seeds in Rotation module

Checksums
=

MD5
~~~

3b75d493f6c93b662f927d6c2ac60053
 scipy-1.6.3-cp37-cp37m-macosx_10_9_x86_64.whl
ada6fa32f066dc58033ab47a4fbcd208  scipy-1.6.3-cp37-cp37m-manylinux1_i686.whl
29c6d6edbe9c2ba17dc4edd89ed31abb
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66b3ea5bb7869af010ae9d6a5015360b
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 scipy-1.6.3-cp39-cp39-manylinux1_x86_64.whl
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 scipy-1.6.3-cp39-cp39-manylinux2014_aarch64.whl
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f13ea8ab38fb03c17e38c3cda7877972  scipy-1.6.3.zip

SHA256
~~

2a799714bf1f791fb2650d73222b248d18d53fd40d6af2df2c898db048189606
 scipy-1.6.3-cp37-cp37m-macosx_10_9_x86_64.whl
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 scipy-1.6.3-cp37-cp37m-win32.whl
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 scipy-1.6.3-cp37-cp37m-win_amd64.whl
1b21c6e0dc97b1762590b70dee0daddb291271be0580384d39f02c480b78290a
 scipy-1.6.3-cp38-cp38-macosx_10_9_x86_64.whl
1caade0ede6967cc675e235c41451f9fb89ae34319ddf4740194094ab736b88d
 scipy-1.6.3-cp38-cp38-manylinux1_i686.whl
19aeac1ad3e57338723f4657ac8520f41714804568f2e30bd547d684d72c392e
 scipy-1.6.3-cp38-cp38-manylinux1_x86_64.whl
ad7269254de06743fb4768f658753de47d8b54e4672c5ebe8612a007a088bd48
 scipy-1.6.3-cp38-cp38-manylinux2014_aarch64.whl
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 scipy-1.6.3-cp38-cp38-win32.whl
33d1677d46111cfa1c84b87472a0274dde9ef4a7ef2e1f155f012f5f1e995d8f
 scipy-1.6.3-cp38-cp38-win_amd64.whl
d449d40e830366b4c612692ad19fbebb722b6b847f78a7b701b1e0d6cda3cc13
 scipy-1.6.3-cp39-cp39-macosx_10_9_x86_64.whl
23995dfcf269ec3735e5a8c80cfceaf384369a47699df111a6246b83a55da582
 scipy-1.6.3-cp39-cp39-manylinux1_i686.whl
fdf606341cd798530b

[Numpy-discussion] ANN: SciPy 1.6.2

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team I'm pleased to announce
the release of SciPy 1.6.2, which is a bug fix release.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.6.2
<https://github.com/scipy/scipy/releases/tag/v1.6.1>

One of a few ways to install this release with pip:

pip install scipy==1.6.2

=
SciPy 1.6.2 Release Notes
=

SciPy 1.6.2 is a bug-fix release with no new features
compared to 1.6.1. This is also the first SciPy release
to place upper bounds on some dependencies to improve
the long-term repeatability of source builds.

Authors
==

* Pradipta Ghosh +
* Tyler Reddy
* Ralf Gommers
* Martin K. Scherer +
* Robert Uhl
* Warren Weckesser

A total of 6 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 1.6.2
--

* `#13512 <https://github.com/scipy/scipy/issues/13512>`__:
\`stats.gaussian_kde.evaluate\` broken on S390X
* `#13584 <https://github.com/scipy/scipy/issues/13584>`__:
rotation._compute_euler_from_matrix() creates an array with negative...
* `#13585 <https://github.com/scipy/scipy/issues/13585>`__: Behavior change
in coo_matrix when dtype=None
* `#13686 <https://github.com/scipy/scipy/issues/13686>`__: delta0 argument
of scipy.odr.ODR() ignored

Pull requests for 1.6.2
--

* `#12862 <https://github.com/scipy/scipy/pull/12862>`__: REL: put upper
bounds on versions of dependencies
* `#13575 <https://github.com/scipy/scipy/pull/13575>`__: BUG: fix
\`gaussian_kernel_estimate\` on S390X
* `#13586 <https://github.com/scipy/scipy/pull/13586>`__: BUG: sparse:
Create a utility function \`getdata\`
* `#13598 <https://github.com/scipy/scipy/pull/13598>`__: MAINT, BUG:
enforce contiguous layout for output array in Rotation.as_euler
* `#13687 <https://github.com/scipy/scipy/pull/13687>`__: BUG: fix
scipy.odr to consider given delta0 argument

Checksums
=

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[Numpy-discussion] ANN: SciPy 1.6.1

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team I'm pleased to announce
the release of SciPy 1.6.1, which is a bug fix release.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.6.1

One of a few ways to install this release with pip:

pip install scipy==1.6.1

=
SciPy 1.6.1 Release Notes
=

SciPy 1.6.1 is a bug-fix release with no new features
compared to 1.6.0.

Please note that for SciPy wheels to correctly install with Pip on
macOS 11, Pip >= 20.3.3 is needed.

Authors
==

* Peter Bell
* Evgeni Burovski
* CJ Carey
* Ralf Gommers
* Peter Mahler Larsen
* Cheng H. Lee +
* Cong Ma
* Nicholas McKibben
* Nikola Forró
* Tyler Reddy
* Warren Weckesser

A total of 11 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 1.6.1
---

* `#13072 <https://github.com/scipy/scipy/issues/13072>`__: BLD: Quadpack
undefined references
* `#13241 <https://github.com/scipy/scipy/issues/13241>`__: Not enough
values to unpack when passing tuple to \`blocksize\`...
* `#13329 <https://github.com/scipy/scipy/issues/13329>`__: Large sparse
matrices of big integers lose information
* `#13342 <https://github.com/scipy/scipy/issues/13342>`__: fftn crashes if
shape arguments are supplied as ndarrays
* `#13356 <https://github.com/scipy/scipy/issues/13356>`__:
LSQBivariateSpline segmentation fault when quitting the Python...
* `#13358 <https://github.com/scipy/scipy/issues/13358>`__:
scipy.spatial.transform.Rotation object can not be deepcopied...
* `#13408 <https://github.com/scipy/scipy/issues/13408>`__: Type of
\`has_sorted_indices\` property
* `#13412 <https://github.com/scipy/scipy/issues/13412>`__: Sorting
spherical Voronoi vertices leads to crash in area calculation
* `#13421 <https://github.com/scipy/scipy/issues/13421>`__:
linear_sum_assignment - support for matrices with more than 2^31...
* `#13428 <https://github.com/scipy/scipy/issues/13428>`__:
\`stats.exponnorm.cdf\` returns \`nan\` for small values of \`K\`...
* `#13465 <https://github.com/scipy/scipy/issues/13465>`__:
KDTree.count_neighbors : 0xC005 error for tuple of different...
* `#13468 <https://github.com/scipy/scipy/issues/13468>`__:
directed_hausdorff issue with shuffle
* `#13472 <https://github.com/scipy/scipy/issues/13472>`__: Failures on
FutureWarnings with numpy 1.20.0 for lfilter, sosfilt...
* `#13565 <https://github.com/scipy/scipy/issues/13565>`__: BUG: 32-bit
wheels repo test failure in optimize

Pull requests for 1.6.1
-

* `#13318 <https://github.com/scipy/scipy/pull/13318>`__: REL: prepare for
SciPy 1.6.1
* `#13344 <https://github.com/scipy/scipy/pull/13344>`__: BUG: fftpack
doesn't work with ndarray shape argument
* `#13345 <https://github.com/scipy/scipy/pull/13345>`__: MAINT: Replace
scipy.take with numpy.take in FFT function docstrings.
* `#13354 <https://github.com/scipy/scipy/pull/13354>`__: BUG: optimize:
rename private functions to include leading underscore
* `#13387 <https://github.com/scipy/scipy/pull/13387>`__: BUG: Support
big-endian platforms and big-endian WAVs
* `#13394 <https://github.com/scipy/scipy/pull/13394>`__: BUG: Fix Python
crash by allocating larger array in LSQBivariateSpline
* `#13400 <https://github.com/scipy/scipy/pull/13400>`__: BUG: sparse:
Better validation for BSR ctor
* `#13403 <https://github.com/scipy/scipy/pull/13403>`__: BUG: sparse:
Propagate dtype through CSR/CSC constructors
* `#13414 <https://github.com/scipy/scipy/pull/13414>`__: BUG: maintain
dtype of SphericalVoronoi regions
* `#13422 <https://github.com/scipy/scipy/pull/13422>`__: FIX: optimize:
use npy_intp to store array dims for lsap
* `#13425 <https://github.com/scipy/scipy/pull/13425>`__: BUG: spatial:
make Rotation picklable
* `#13426 <https://github.com/scipy/scipy/pull/13426>`__: BUG:
\`has_sorted_indices\` and \`has_canonical_format\` should...
* `#13430 <https://github.com/scipy/scipy/pull/13430>`__: BUG: stats: Fix
exponnorm.cdf and exponnorm.sf for small K
* `#13470 <https://github.com/scipy/scipy/pull/13470>`__: MAINT: silence
warning generated by \`spatial.directed_hausdorff\`
* `#13473 <https://github.com/scipy/scipy/pull/13473>`__: TST: fix failures
due to new FutureWarnings in NumPy 1.21.dev0
* `#13479 <https://github.com/scipy/scipy/pull/13479>`__: MAINT: update
directed_hausdorff Cython code
* `#13485 <https://github.com/scipy/scipy/pull/13485>`__: BUG: KDTree
weighted count_neighbors doesn't work between two...
* `#13503 <https://github.com/scipy/scipy/pull/13503>`__: TST: fix
\`test_fort

[Numpy-discussion] ANN: SciPy 1.5.4

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team I'm pleased to announce
the release of SciPy 1.5.4, which is a bug fix release that includes
Python 3.9 wheels and a more complete fix for build issues on XCode 12.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.5.4

One of a few ways to install this release with pip:

pip install scipy==1.5.4

=
SciPy 1.5.4 Release Notes
=

SciPy 1.5.4 is a bug-fix release with no new features
compared to 1.5.3. Importantly, wheels are now available
for Python 3.9 and a more complete fix has been applied for
issues building with XCode 12.

Authors
==

* Peter Bell
* CJ Carey
* Andrew McCluskey +
* Andrew Nelson
* Tyler Reddy
* Eli Rykoff +
* Ian Thomas +

A total of 7 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 1.5.4
---

* `#12763 <https://github.com/scipy/scipy/issues/12763>`__:
ndimage.fourier_ellipsoid segmentation fault
* `#12789 <https://github.com/scipy/scipy/issues/12789>`__:
TestConvolve2d.test_large_array failing on Windows ILP64 CI job
* `#12857 <https://github.com/scipy/scipy/issues/12857>`__: sparse A[0,:] =
ndarray is ok, A[:,0] = ndarray ValueError from...
* `#12860 <https://github.com/scipy/scipy/issues/12860>`__: BUG: Build
failure with Xcode 12
* `#12935 <https://github.com/scipy/scipy/issues/12935>`__: Failure to
build with Python 3.9.0 on macOS
* `#12966 <https://github.com/scipy/scipy/issues/12966>`__: MAINT:
lint_diff.py on some backport PRs
* `#12988 <https://github.com/scipy/scipy/issues/12988>`__: BUG: Highly
multi-dimensional \`gaussian_kde\` giving \`-inf\`...

Pull requests for 1.5.4
--

* `#12790 <https://github.com/scipy/scipy/pull/12790>`__: TST: Skip
TestConvolve2d.test_large_array if not enough memory
* `#12851 <https://github.com/scipy/scipy/pull/12851>`__: BUG: sparse: fix
inner indexed assignment of a 1d array
* `#12875 <https://github.com/scipy/scipy/pull/12875>`__: BUG: segfault in
ndimage.fourier_ellipsoid with length-1 dims
* `#12937 <https://github.com/scipy/scipy/pull/12937>`__: CI: macOS3.9
testing
* `#12957 <https://github.com/scipy/scipy/pull/12957>`__: MAINT: fixes
XCode 12/ python 3.9.0 build for 1.5.x maint branch
* `#12959 <https://github.com/scipy/scipy/pull/12959>`__: CI: add Windows
Python 3.9 to CI
* `#12974 <https://github.com/scipy/scipy/pull/12974>`__: MAINT: Run
lint_diff.py against the merge target and only for...
* `#12978 <https://github.com/scipy/scipy/pull/12978>`__: DOC:
next_fast_len output doesn't match docstring
* `#12979 <https://github.com/scipy/scipy/pull/12979>`__: BUG:
fft.next_fast_len should accept keyword arguments
* `#12989 <https://github.com/scipy/scipy/pull/12989>`__: BUG: improved the
stability of kde for highly (1000s) multi-dimension...
* `#13017 <https://github.com/scipy/scipy/pull/13017>`__: BUG: Add explicit
cast to _tmp sum.
* `#13022 <https://github.com/scipy/scipy/pull/13022>`__: TST: xfail
test_maxiter_worsening()

Checksums
=

MD5
~~~

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 scipy-1.5.4-cp39-cp39-manylinux1_x86_64.whl
efd

[Numpy-discussion] ANN: SciPy 1.5.3

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team I'm pleased to announce
the release of SciPy 1.5.3, which is a bug fix release that includes
Linux ARM64 wheels for the first time.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.5.3

One of a few ways to install this release with pip:

pip install scipy==1.5.3

==
SciPy 1.5.3 Release Notes
==

SciPy 1.5.3 is a bug-fix release with no new features
compared to 1.5.2. In particular, Linux ARM64 wheels are now
available and a compatibility issue with XCode 12 has
been fixed.

Authors
==

* Peter Bell
* CJ Carey
* Thomas Duvernay +
* Gregory Lee
* Eric Moore
* odidev
* Dima Pasechnik
* Tyler Reddy
* Simon Segerblom Rex +
* Daniel B. Smith
* Will Tirone +
* Warren Weckesser

A total of 12 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 1.5.3
--

* `#9611 <https://github.com/scipy/scipy/issues/9611>`__: Overflow error
with new way of p-value calculation in kendall...
* `#10069 <https://github.com/scipy/scipy/issues/10069>`__:
scipy.ndimage.watershed_ift regression in 1.0.0
* `#11260 <https://github.com/scipy/scipy/issues/11260>`__: BUG: DOP853
with complex data computes complex error norm, causing...
* `#11479 <https://github.com/scipy/scipy/issues/11479>`__: RuntimeError:
dictionary changed size during iteration on loading...
* `#11972 <https://github.com/scipy/scipy/issues/11972>`__: BUG (solved):
Error estimation in DOP853 ODE solver fails for...
* `#12543 <https://github.com/scipy/scipy/issues/12543>`__: BUG: Picture
rotated 180 degrees and rotated -180 degrees should...
* `#12613 <https://github.com/scipy/scipy/issues/12613>`__: Travis X.4 and
X.7 failures in master
* `#12654 <https://github.com/scipy/scipy/issues/12654>`__:
scipy.stats.combine_pvalues produces wrong results with
method='mudholkar_george'
* `#12819 <https://github.com/scipy/scipy/issues/12819>`__: BUG: Scipy
Sparse slice indexing assignment Bug with zeros
* `#12834 <https://github.com/scipy/scipy/issues/12834>`__: BUG: ValueError
upon calling Scipy Interpolator objects
* `#12836 <https://github.com/scipy/scipy/issues/12836>`__: ndimage.median
can return incorrect values for integer inputs
* `#12860 <https://github.com/scipy/scipy/issues/12860>`__: Build failure
with Xcode 12

Pull requests for 1.5.3
-

* `#12611 <https://github.com/scipy/scipy/pull/12611>`__: MAINT: prepare
for SciPy 1.5.3
* `#12614 <https://github.com/scipy/scipy/pull/12614>`__: MAINT: prevent
reverse broadcasting
* `#12617 <https://github.com/scipy/scipy/pull/12617>`__: MAINT: optimize:
Handle nonscalar size 1 arrays in fmin_slsqp...
* `#12623 <https://github.com/scipy/scipy/pull/12623>`__: MAINT: stats:
Loosen some test tolerances.
* `#12638 <https://github.com/scipy/scipy/pull/12638>`__: CI, MAINT: pin
pytest for Azure win
* `#12668 <https://github.com/scipy/scipy/pull/12668>`__: BUG: Ensure
factorial is not too large in mstats.kendalltau
* `#12705 <https://github.com/scipy/scipy/pull/12705>`__: MAINT:
\`openblas_support\` added sha256 hash
* `#12706 <https://github.com/scipy/scipy/pull/12706>`__: BUG: fix
incorrect 1d case of the fourier_ellipsoid filter
* `#12721 <https://github.com/scipy/scipy/pull/12721>`__: BUG: use
special.sindg in ndimage.rotate
* `#12724 <https://github.com/scipy/scipy/pull/12724>`__: BUG: per #12654
adjusted mudholkar_george method to combine p...
* `#12726 <https://github.com/scipy/scipy/pull/12726>`__: BUG: Fix DOP853
error norm for complex problems
* `#12730 <https://github.com/scipy/scipy/pull/12730>`__: CI: pin xdist for
Azure windows
* `#12786 <https://github.com/scipy/scipy/pull/12786>`__: BUG: stats: Fix
formula in the \`stats\` method of the ARGUS...
* `#12795 <https://github.com/scipy/scipy/pull/12795>`__: CI: Pin
setuptools on windows CI
* `#12830 <https://github.com/scipy/scipy/pull/12830>`__: [BUG] sparse:
Avoid using size attribute in LIL __setitem__
* `#12833 <https://github.com/scipy/scipy/pull/12833>`__: BUG: change list
of globals items to list of a copy
* `#12842 <https://github.com/scipy/scipy/pull/12842>`__: BUG: Use uint16
for cost in NI_WatershedElement
* `#12845 <https://github.com/scipy/scipy/pull/12845>`__: BUG: avoid
boolean or integer addition error in ndimage.measurements.median
* `#12864 <https://github.com/scipy/scipy/pull/12864>`__: BLD: replace the
#include of libqull_r.h with with this of qhull_ra.h...
* `#12867 <https://github.com/scipy/scipy/pull/12867>`__: BUG: Fixes a
ValueError yielded upon call

[Numpy-discussion] ANN: SciPy 1.5.2

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team I'm pleased to announce
the release of SciPy 1.5.2, which is a bug fix release.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.5.2

One of a few ways to install this release with pip:

pip install scipy==1.5.2

==
SciPy 1.5.2 Release Notes
==

SciPy 1.5.2 is a bug-fix release with no new features
compared to 1.5.1.

Authors
==

* Peter Bell
* Tobias Biester +
* Evgeni Burovski
* Thomas A Caswell
* Ralf Gommers
* Sturla Molden
* Andrew Nelson
* ofirr +
* Sambit Panda
* Ilhan Polat
* Tyler Reddy
* Atsushi Sakai
* Pauli Virtanen

A total of 13 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 1.5.2
--

* `#3847 <https://github.com/scipy/scipy/issues/3847>`__: Crash of
interpolate.splprep(task=-1)
* `#7395 <https://github.com/scipy/scipy/issues/7395>`__: splprep segfaults
if fixed knots are specified
* `#10761 <https://github.com/scipy/scipy/issues/10761>`__:
scipy.signal.convolve2d produces incorrect values for large arrays
* `#11971 <https://github.com/scipy/scipy/issues/11971>`__: DOC: search in
devdocs returns wrong link
* `#12155 <https://github.com/scipy/scipy/issues/12155>`__: BUG: Fix
permutation of distance matrices in scipy.stats.multiscale_graphcorr
* `#12203 <https://github.com/scipy/scipy/issues/12203>`__: Unable to
install on PyPy 7.3.1 (Python 3.6.9)
* `#12316 <https://github.com/scipy/scipy/issues/12316>`__: negative
scipy.spatial.distance.correlation
* `#12422 <https://github.com/scipy/scipy/issues/12422>`__: BUG: slsqp:
ValueError: failed to initialize intent(inout) array...
* `#12428 <https://github.com/scipy/scipy/issues/12428>`__:
stats.truncnorm.rvs() never returns a scalar in 1.5
* `#12441 <https://github.com/scipy/scipy/issues/12441>`__: eigvalsh
inconsistent eigvals= subset_by_index=
* `#12445 <https://github.com/scipy/scipy/issues/12445>`__: DOC:
scipy.linalg.eigh
* `#12449 <https://github.com/scipy/scipy/issues/12449>`__: Warnings are
not filtered in csr_matrix.sum()
* `#12469 <https://github.com/scipy/scipy/issues/12469>`__: SciPy 1.9
exception in LSQSphereBivariateSpline
* `#12487 <https://github.com/scipy/scipy/issues/12487>`__: BUG: optimize:
incorrect result from approx_fprime
* `#12493 <https://github.com/scipy/scipy/issues/12493>`__: CI: GitHub
Actions for maintenance branches
* `#12533 <https://github.com/scipy/scipy/issues/12533>`__: eigh gives
incorrect results
* `#12579 <https://github.com/scipy/scipy/issues/12579>`__: BLD, MAINT:
distutils issues in wheels repo

Pull requests for 1.5.2
---

* `#12156 <https://github.com/scipy/scipy/pull/12156>`__: BUG: Fix
permutation of distance matrices in scipy.stats.multiscale_graphcorr
* `#12238 <https://github.com/scipy/scipy/pull/12238>`__: BUG: Use 64-bit
indexing in convolve2d to avoid overflow
* `#12256 <https://github.com/scipy/scipy/pull/12256>`__: BLD: Build lsap
as a single extension instead of extension +...
* `#12320 <https://github.com/scipy/scipy/pull/12320>`__: BUG: spatial:
avoid returning negative correlation distance
* `#12383 <https://github.com/scipy/scipy/pull/12383>`__: ENH: Make
cKDTree.tree more efficient
* `#12392 <https://github.com/scipy/scipy/pull/12392>`__: DOC: update
scipy-sphinx-theme
* `#12430 <https://github.com/scipy/scipy/pull/12430>`__: BUG: truncnorm
and geninvgauss never return scalars from rvs
* `#12437 <https://github.com/scipy/scipy/pull/12437>`__: BUG: optimize:
cast bounds to floats in new_bounds_to_old/old_bounds_to_new
* `#12442 <https://github.com/scipy/scipy/pull/12442>`__: MAINT:linalg: Fix
for input args of eigvalsh
* `#12461 <https://github.com/scipy/scipy/pull/12461>`__: MAINT: sparse:
write matrix/asmatrix wrappers without warning...
* `#12478 <https://github.com/scipy/scipy/pull/12478>`__: BUG: fix
array_like input defects and add tests for all functions...
* `#12488 <https://github.com/scipy/scipy/pull/12488>`__: BUG: fix
approx_derivative step size. Closes #12487
* `#12500 <https://github.com/scipy/scipy/pull/12500>`__: CI: actions
branch trigger fix
* `#12501 <https://github.com/scipy/scipy/pull/12501>`__: CI: actions
branch trigger fix
* `#12504 <https://github.com/scipy/scipy/pull/12504>`__: BUG: cKDTreeNode
use after free
* `#12529 <https://github.com/scipy/scipy/pull/12529>`__: MAINT: allow
graceful docs re-upload
* `#12538 <https://github.com/scipy/scipy/pull/12538>`__: BUG:linalg: eigh
type parameter handling corrected
* `#12560 <https://github.com/scipy/scipy/pul

[Numpy-discussion] ANN: SciPy 1.5.1

[Tyler Reddy]

Hi all,

On behalf of the SciPy development team I'm pleased to announce
the release of SciPy 1.5.1, which is a bug fix release.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at:  https://github.com/scipy/scipy/releases/tag/v1.5.1

One of a few ways to install this release with pip:

pip install scipy==1.5.1

==
SciPy 1.5.1 Release Notes
==

SciPy 1.5.1 is a bug-fix release with no new features
compared to 1.5.0. In particular, an issue where DLL loading
can fail for SciPy wheels on Windows with Python 3.6 has been
fixed.

Authors
===

* Peter Bell
* Loïc Estève
* Philipp Thölke +
* Tyler Reddy
* Paul van Mulbregt
* Pauli Virtanen
* Warren Weckesser

A total of 7 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 1.5.1


* `#9108 <https://github.com/scipy/scipy/issues/9108>`__: documentation:
scipy.spatial.KDTree vs. scipy.spatial.cKDTree
* `#12218 <https://github.com/scipy/scipy/issues/12218>`__: Type error in
stats.ks_2samp when alternative != 'two-sided-
* `#12406 <https://github.com/scipy/scipy/issues/12406>`__: DOC: Docstring
in stats.anderson function not properly formatted
* `#12418 <https://github.com/scipy/scipy/issues/12418>`__: Regression in
hierarchy.dendogram


Pull requests for 1.5.1


* `#12280 <https://github.com/scipy/scipy/pull/12280>`__: BUG: Fixes
gh-12218, TypeError converting int to float inside...
* `#12336 <https://github.com/scipy/scipy/pull/12336>`__: BUG: KDTree
should reject complex input points
* `#12344 <https://github.com/scipy/scipy/pull/12344>`__: MAINT: Don't use
numpy's aliases of Python builtin objects.
* `#12407 <https://github.com/scipy/scipy/pull/12407>`__: DOC: Fix
docstring for dist param in anderson function
* `#12410 <https://github.com/scipy/scipy/pull/12410>`__: CI: Run the Azure
Windows Python36 32bit tests with mode 'fast'
* `#12421 <https://github.com/scipy/scipy/pull/12421>`__: Fix regression in
scipy 1.5.0 in dendogram when labels is a numpy...
* `#12462 <https://github.com/scipy/scipy/pull/12462>`__: MAINT: move
distributor_init import after __config__ import


Checksums
=

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9

[Numpy-discussion] ANN: SciPy 1.2.3 (LTS)

[Tyler Reddy]

-BEGIN PGP SIGNED MESSAGE-
Hash: SHA256

Hi all,

On behalf of the SciPy development team I'm pleased to announce
the release of SciPy 1.2.3, which is a bug fix release. This is part
of the long-term support (LTS) branch that includes 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/v1.2.3

One of a few ways to install this release with pip:

pip install scipy==1.2.3

==
SciPy 1.2.3 Release Notes
==

SciPy 1.2.3 is a bug-fix release with no new features compared to 1.2.2. It
is
part of the long-term support (LTS) release series for Python 2.7.

Authors
===

* Geordie McBain
* Matt Haberland
* David Hagen
* Tyler Reddy
* Pauli Virtanen
* Eric Larson
* Yu Feng
* ananyashreyjain
* Nikolay Mayorov
* Evgeni Burovski
* Warren Weckesser

Issues closed for 1.2.3

* `#4915 <https://github.com/scipy/scipy/issues/4915>`__: Bug in
unique_roots in scipy.signal.signaltools.py for roots with same magnitude
* `#5546 <https://github.com/scipy/scipy/issues/5546>`__: ValueError raised
if scipy.sparse.linalg.expm recieves array larger than 200x200
* `#7117 <https://github.com/scipy/scipy/issues/7117>`__: Warn users when
using float32 input data to curve_fit and friends
* `#7906 <https://github.com/scipy/scipy/issues/7906>`__: Wrong result from
scipy.interpolate.UnivariateSpline.integral for out-of-bounds
* `#9581 <https://github.com/scipy/scipy/issues/9581>`__: Least-squares
minimization fails silently when x and y data are different types
* `#9901 <https://github.com/scipy/scipy/issues/9901>`__: lsoda fails to
detect stiff problem when called from solve_ivp
* `#9988 <https://github.com/scipy/scipy/issues/9988>`__: doc build broken
with Sphinx 2.0.0
* `#10303 <https://github.com/scipy/scipy/issues/10303>`__: BUG: optimize:
`linprog` failing
TestLinprogSimplexBland::test_unbounded_below_no_presolve_corrected
* `#10376 <https://github.com/scipy/scipy/issues/10376>`__: TST: Travis CI
fails (with pytest 5.0 ?)
* `#10384 <https://github.com/scipy/scipy/issues/10384>`__: CircleCI doc
build failing on new warnings
* `#10535 <https://github.com/scipy/scipy/issues/10535>`__: TST: master
branch CI failures
* `#11121 <https://github.com/scipy/scipy/issues/11121>`__: Calls to
`scipy.interpolate.splprep` increase RAM usage.
* `#11198 <https://github.com/scipy/scipy/issues/11198>`__: BUG: sparse
eigs (arpack) shift-invert drops the smallest eigenvalue for some k
* `#11266 <https://github.com/scipy/scipy/issues/11266>`__: Sparse matrix
constructor data type detection changes on Numpy 1.18.0

Pull requests for 1.2.3

* `#9992 <https://github.com/scipy/scipy/pull/9992>`__: MAINT: Undo Sphinx
pin
* `#10071 <https://github.com/scipy/scipy/pull/10071>`__: DOC: reconstruct
SuperLU permutation matrices avoiding SparseEfficiencyWarning
* `#10076 <https://github.com/scipy/scipy/pull/10076>`__: BUG: optimize:
fix curve_fit for mixed float32/float64 input
* `#10138 <https://github.com/scipy/scipy/pull/10138>`__: BUG: special:
Invalid arguments to ellip_harm can crash Python.
* `#10306 <https://github.com/scipy/scipy/pull/10306>`__: BUG: optimize:
Fix for 10303
* `#10309 <https://github.com/scipy/scipy/pull/10309>`__: BUG: Pass
jac=None directly to lsoda
* `#10377 <https://github.com/scipy/scipy/pull/10377>`__: TST, MAINT:
adjustments for pytest 5.0
* `#10379 <https://github.com/scipy/scipy/pull/10379>`__: BUG: sparse: set
writeability to be forward-compatible with numpy>=1.17
* `#10426 <https://github.com/scipy/scipy/pull/10426>`__: MAINT: Fix doc
build bugs
* `#10540 <https://github.com/scipy/scipy/pull/10540>`__: MAINT: Fix Travis
and Circle
* `#10633 <https://github.com/scipy/scipy/pull/10633>`__: BUG: interpolate:
integral(a, b) should be zero when both limits are outside of the
interpolation range
* `#10833 <https://github.com/scipy/scipy/pull/10833>`__: BUG: Fix
subspace_angles for complex values
* `#10882 <https://github.com/scipy/scipy/pull/10882>`__: BUG:
sparse/arpack: fix incorrect code for complex hermitian M
* `#10906 <https://github.com/scipy/scipy/pull/10906>`__: BUG:
sparse/linalg: fix expm for np.matrix inputs
* `#10961 <https://github.com/scipy/scipy/pull/10961>`__: BUG: Fix
signal.unique_roots
* `#11126 <https://github.com/scipy/scipy/pull/11126>`__: BUG:
interpolate/fitpack: fix memory leak in splprep
* `#11199 <https://github.com/scipy/scipy/pull/11199>`__: BUG:
sparse.linalg: mistake in unsymm. real shift-invert ARPACK eigenvalue
selection
* `#11269 <https://github.com/scipy/scipy/pull/11269>`__: Fix: Sparse
matrix constructor data type detection changes on Numpy 1.18.0



Checksums
=

MD5
~~~

702e7f68e024

[Numpy-discussion] ANN: SciPy 1.4.1

[Tyler Reddy]

-BEGIN PGP SIGNED MESSAGE-
Hash: SHA256

Hi all,

On behalf of the SciPy development team I'm pleased to announce
the release of SciPy 1.4.1, which is a bug fix release.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.4.1

One of a few ways to install this release with pip:

pip install scipy==1.4.1

==
SciPy 1.4.1 Release Notes
==

SciPy 1.4.1 is a bug-fix release with no new features
compared to 1.4.0. Importantly, it aims to fix a problem
where an older version of pybind11 may cause a segmentation
fault when imported alongside incompatible libraries.

Authors
==

* Ralf Gommers
* Tyler Reddy

Issues closed for 1.4.1
-

* `#11237 <https://github.com/scipy/scipy/issues/11237>`__: Seg fault when
importing torch

Pull requests for 1.4.1


* `#11238 <https://github.com/scipy/scipy/pull/11238>`__: BLD: update
minimum pybind11 version to 2.4.0.

Checksums
=

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2586c8563cd6693161e13a0ad6fffe06  scipy-1.4.1.zip

SHA256
~~

c5cac0c0387272ee0e789e94a570ac51deb01c796b37fb2aad1fb13f85e2f97d
 scipy-1.4.1-cp35-cp35m-macosx_10_6_intel.whl
a144811318853a23d32a07bc7fd5561ff0cac5da643d96ed94a4ffe967d89672
 scipy-1.4.1-cp35-cp35m-manylinux1_i686.whl
71eb180f22c49066f25d6df16f8709f215723317cc951d99e54dc88020ea57be
 scipy-1.4.1-cp35-cp35m-manylinux1_x86_64.whl
770254a280d741dd3436919d47e35712fb081a6ff8bafc0f319382b954b77802
 scipy-1.4.1-cp35-cp35m-win32.whl
a1aae70d52d0b074d8121333bc807a485f9f1e6a69742010b33780df2e60cfe0
 scipy-1.4.1-cp35-cp35m-win_amd64.whl
bb517872058a1f087c4528e7429b4a44533a902644987e7b2fe35ecc223bc408
 scipy-1.4.1-cp36-cp36m-macosx_10_6_intel.whl
dba8306f6da99e37ea08c08fef6e274b5bf8567bb094d1dbe86a20e532aca088
 scipy-1.4.1-cp36-cp36m-manylinux1_i686.whl
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 scipy-1.4.1-cp37-cp37m-manylinux1_x86_64.whl
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 scipy-1.4.1-cp37-cp37m-win_amd64.whl
3092857f36b690a321a662fe5496cb816a7f4eecd875e1d36793d92d3f884073
 scipy-1.4.1-cp38-cp38-macosx_10_9_x86_64.whl
8a07760d5c7f3a92e440ad3aedcc98891e915ce857664282ae3c0220f3301eb6
 scipy-1.4.1-cp38-cp38-manylinux1_i686.whl
1e3190466d669d658233e8a583b854f6386dd62d655539b77b3fa25bfb2abb70
 scipy-1.4.1-cp38-cp38-manylinux1_x86_64.whl
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 scipy-1.4.1-cp38-cp38-win_amd64.whl
dee1bbf3a6c8f73b6b218cb28eed8dd13347ea2f87d572ce19b289d6fd3fbc59
 s

[Numpy-discussion] ANN: SciPy 1.3.3

[Tyler Reddy]

-BEGIN PGP SIGNED MESSAGE-
Hash: SHA256

Hi all,

On behalf of the SciPy development team I'm pleased to announce
the release of SciPy 1.3.3, a bug fix release that addresses
a DLL loading issue for wheels and a multiprocessing test issue.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.3.3

One of a few ways to install this release with pip:

pip install scipy==1.3.3

=
SciPy 1.3.3 Release Notes
=

SciPy 1.3.3 is a bug-fix release with no new features
compared to 1.3.2. In particular, a test suite issue
involving multiprocessing was fixed for Windows and
Python 3.8 on macOS.

Wheels were also updated to place msvcp140.dll at the
appropriate location, which was previously causing issues.

Authors
===

Ilhan Polat
Tyler Reddy
Ralf Gommers

Issues closed for 1.3.3


* `#11033 <https://github.com/scipy/scipy/issues/11033>`__: deadlock on osx
for python 3.8


Pull requests for 1.3.3
-

* `#11034 <https://github.com/scipy/scipy/pull/11034>`__: MAINT: TST: Skip
tests with multiprocessing that use "spawn" start method

Checksums
=

MD5
~~~

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 scipy-1.3.3-cp35-cp35m-macosx_10_6_intel.whl
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 scipy-1.3.3-cp37-cp37m-manylinux1_x86_64.whl
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94455bf1e5a6f8bf459bc0971897e2f1
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150c45e2a3c5b14aa089a7f7835212e2  scipy-1.3.3-cp38-cp38-manylinux1_i686.whl
c6e464fdb7e928da58a7bd84f389cb74
 scipy-1.3.3-cp38-cp38-manylinux1_x86_64.whl
08d3a330ef2469d139527163717fc318  scipy-1.3.3-cp38-cp38-win32.whl
286528ecaab3b56d6405d2775604d18d  scipy-1.3.3-cp38-cp38-win_amd64.whl
b265efea6ce2f2c1e580cc66bfb8b117  scipy-1.3.3.tar.gz
4c73d4a86f97f41ceface4fc1622e2f7  scipy-1.3.3.tar.xz
5e8182d8b29b04bfc2f19f6bf5ca1fac  scipy-1.3.3.zip

SHA256
~~

a70308bb065562afb936c963780deab359966d71ab4f230368b154dde3136ea4
 scipy-1.3.3-cp35-cp35m-macosx_10_6_intel.whl
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 scipy-1.3.3-cp36-cp36m-manylinux1_x86_64.whl
b7b8cf45f9a48f23084f19deb9384a1cccb5e92fbc879b12f97dc4d56fb2eb92
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0b8c9dc042b9a47912b18b036b4844029384a5b8d89b64a4901ac3e06876e5f6
 scipy-1.3.3-cp36-cp36m-win_amd64.whl
225d0b5e140bb66df23d438c7b535303ce8e533f94454f4e5bde5f8d109103ea
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583f2ccd6a112656c9feb2345761d2b19e9213a094cfced4e7d2c1cae4173272
 scipy-1.3.3-cp37-cp37m-manylinux1_x86_64.whl
dfcb0f0a2d8e958611e0b56536285bb435f03746b6feac0e29f045f7c6caf164
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 scipy-1.3.3-cp37-cp37m-win_amd64.whl
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a42b0d02150ef4747e225c31c976a304de5dc8202ec35a27111b7bb8176e5f13
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869465c7ff89fc0a1e2ea1642b0c65f1b3c05030f3a4c0d53d6a57b2dba7c242
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4b8746f4a755bdb2eeb39d6e253a60481e165cfd74fdfb54d27394bd2c9ec8ac
 scip

[Numpy-discussion] ANN: SciPy 1.3.2

[Tyler Reddy]

-BEGIN PGP SIGNED MESSAGE-
Hash: SHA256

Hi all,

On behalf of the SciPy development team I'm pleased to announce
the release of SciPy 1.3.2, a maintenance and bug fix release that
adds support for Python 3.8.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.3.2

One of a few ways to install this release with pip:

pip install scipy==1.3.2

==
SciPy 1.3.2 Release Notes
==

SciPy 1.3.2 is a bug-fix and maintenance release that adds
support for Python 3.8.

Authors
===

* CJ Carey
* Dany Vohl
* Martin Gauch +
* Ralf Gommers
* Matt Haberland
* Eric Larson
* Nikolay Mayorov
* Sam McCormack +
* Andrew Nelson
* Tyler Reddy
* Pauli Virtanen
* Huize Wang +
* Warren Weckesser
* Joseph Weston +

A total of 14 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 1.3.2
---

* `#4915 <https://github.com/scipy/scipy/issues/4915>`__: Bug in
unique_roots in scipy.signal.signaltools.py for roots...
* `#5161 <https://github.com/scipy/scipy/issues/5161>`__: Optimizers
reporting success when the minimum is NaN
* `#5546 <https://github.com/scipy/scipy/issues/5546>`__: ValueError raised
if scipy.sparse.linalg.expm recieves array...
* `#10124 <https://github.com/scipy/scipy/issues/10124>`__:
linprog(method='revised simplex') doctest bug
* `#10609 <https://github.com/scipy/scipy/issues/10609>`__: Graph shortest
path with Floyd-Warshall removes explicit zeros.
* `#10658 <https://github.com/scipy/scipy/issues/10658>`__: BUG: stats:
Formula for the variance of the noncentral F distribution...
* `#10695 <https://github.com/scipy/scipy/issues/10695>`__: BUG:
Assignation issues in csr_matrix with fancy indexing
* `#10846 <https://github.com/scipy/scipy/issues/10846>`__: root_scalar
fails when passed a function wrapped with functools.lru_cache
* `#10902 <https://github.com/scipy/scipy/issues/10902>`__: CI: travis osx
build failure
* `#10967 <https://github.com/scipy/scipy/issues/10967>`__: macOS build
failure in SuperLU on maintenance/1.3.x
* `#10976 <https://github.com/scipy/scipy/issues/10976>`__: Typo in
sp.stats.wilcoxon docstring


Pull requests for 1.3.2
--

* `#10498 <https://github.com/scipy/scipy/pull/10498>`__: TST: optimize:
fixed \`linprog\` \`"disp": True\` bug
* `#10536 <https://github.com/scipy/scipy/pull/10536>`__: CI: add 3.8-dev
to travis
* `#10671 <https://github.com/scipy/scipy/pull/10671>`__: BUG: stats: Fix
the formula for the variance of the noncentral...
* `#10693 <https://github.com/scipy/scipy/pull/10693>`__: BUG:
ScalarFunction stores original array
* `#10700 <https://github.com/scipy/scipy/pull/10700>`__: BUG: sparse:
Loosen checks on sparse fancy assignment
* `#10709 <https://github.com/scipy/scipy/pull/10709>`__: BUG: Fix
floyd_warshall to support zero-weight edges
* `#10756 <https://github.com/scipy/scipy/pull/10756>`__: BUG: optimize:
ensure solvers exit with success=False for nan...
* `#10833 <https://github.com/scipy/scipy/pull/10833>`__: BUG: Fix
subspace_angles for complex values
* `#10882 <https://github.com/scipy/scipy/pull/10882>`__: BUG:
sparse/arpack: fix incorrect code for complex hermitian...
* `#10891 <https://github.com/scipy/scipy/pull/10891>`__: BUG: make
C-implemented root finders work with functools.lru_cache
* `#10906 <https://github.com/scipy/scipy/pull/10906>`__: BUG:
sparse/linalg: fix expm for np.matrix inputs
* `#10917 <https://github.com/scipy/scipy/pull/10917>`__: CI: fix travis
osx CI
* `#10930 <https://github.com/scipy/scipy/pull/10930>`__: MAINT: Updates
for 3.8
* `#10938 <https://github.com/scipy/scipy/pull/10938>`__: MAINT: Add Python
3.8 to pyproject.toml
* `#10943 <https://github.com/scipy/scipy/pull/10943>`__: BLD: update
Cython version to 0.29.13
* `#10961 <https://github.com/scipy/scipy/pull/10961>`__: BUG: Fix
signal.unique_roots
* `#10971 <https://github.com/scipy/scipy/pull/10971>`__: MAINT: use 3.8
stable in CI
* `#10977 <https://github.com/scipy/scipy/pull/10977>`__: DOC: Fix typo in
sp.stats.wilcoxon docsting
* `#11025 <https://github.com/scipy/scipy/pull/11025>`__: Update
_peak_finding.py

Checksums
=

MD5
~~~

5acb33b69d73d369b05f10aaf24220c4
 scipy-1.3.2-cp35-cp35m-macosx_10_6_intel.whl
2afea38680dc72f356965178c128747d  scipy-1.3.2-cp35-cp35m-manylinux1_i686.whl
97d2aa748499111d348c283b4e435755
 scipy-1.3.2-cp35-cp35m-manylinux1_x86_64.whl
22cbe9c7a2bef004cda3b18355b5d277  scipy-1.3.2-cp35-cp35m-win32.whl
e6e3d77c7e7d92344263e55b7f7f14ba  scipy-1.3.2-cp35-cp35m-win_amd64.whl
6abb6cdc43950ad3145

Re: [Numpy-discussion] Using hypothesis in testing

[Tyler Reddy]

I think the pros outweigh the cons -- I'll comment briefly on the PR.

On Mon, 9 Sep 2019 at 02:41, Matti Picus  wrote:

> We have discussed using the hypothesis package to generate test cases at a
> few meetings informally. At the EuroSciPy sprint, kitchoi took up the
> challenge and issued a pull request
> https://github.com/numpy/numpy/pull/14440 that actually goes ahead and
> does it. While not finding any new failures, the round-trip testing of s =
> np.array2string(np.array(s)) shows what hypothesis can do. The new test
> runs for about 1/2 a second. In my mind the next step would be to use this
> style of testing to expose problems in the np.chararray routines.
>
>
> What do you think? Is the cost of adding a new dependency worth the more
> thorough testing?
>
> Matti
> ___
> NumPy-Discussion mailing list
> NumPy-Discussion@python.org
> https://mail.python.org/mailman/listinfo/numpy-discussion
>
___
NumPy-Discussion mailing list
NumPy-Discussion@python.org
https://mail.python.org/mailman/listinfo/numpy-discussion

[Numpy-discussion] ANN: SciPy 1.3.1

[Tyler Reddy]

-BEGIN PGP SIGNED MESSAGE-
Hash: SHA256

Hi all,

On behalf of the SciPy development team I'm pleased to announce
the release of SciPy 1.3.1, which is a bug fix release.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.3.1

One of a few ways to install this release with pip:

pip install scipy==1.3.1

==
SciPy 1.3.1 Release Notes
==

SciPy 1.3.1 is a bug-fix release with no new features
compared to 1.3.0.

Authors
===

* Matt Haberland
* Geordie McBain
* Yu Feng
* Evgeni Burovski
* Sturla Molden
* Tapasweni Pathak
* Eric Larson
* Peter Bell
* Carlos Ramos Carreño +
* Ralf Gommers
* David Hagen
* Antony Lee
* Ayappan P
* Tyler Reddy
* Pauli Virtanen

A total of 15 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 1.3.1
---

* `#5040 <https://github.com/scipy/scipy/issues/5040>`__: BUG: Empty data
handling of (c)KDTrees
* `#9901 <https://github.com/scipy/scipy/issues/9901>`__: lsoda fails to
detect stiff problem when called from solve_ivp
* `#10206 <https://github.com/scipy/scipy/issues/10206>`__: sparse matrices
indexing with scipy 1.3
* `#10232 <https://github.com/scipy/scipy/issues/10232>`__: Exception in
loadarff with quoted nominal attributes in scipy...
* `#10292 <https://github.com/scipy/scipy/issues/10292>`__: DOC/REL: Some
sections of the release notes are not nested correctly.
* `#10303 <https://github.com/scipy/scipy/issues/10303>`__: BUG: optimize:
`linprog` failing
TestLinprogSimplexBland::test_unbounded_below_no_presolve_corrected
* `#10376 <https://github.com/scipy/scipy/issues/10376>`__: TST: Travis CI
fails (with pytest 5.0 ?)
* `#10384 <https://github.com/scipy/scipy/issues/10384>`__: CircleCI doc
build failing on new warnings
* `#10398 <https://github.com/scipy/scipy/issues/10398>`__: Scipy 1.3.0
build broken in AIX
* `#10501 <https://github.com/scipy/scipy/issues/10501>`__: BUG:
scipy.spatial.HalfspaceIntersection works incorrectly
* `#10514 <https://github.com/scipy/scipy/issues/10514>`__: BUG: cKDTree
GIL handling is incorrect
* `#10535 <https://github.com/scipy/scipy/issues/10535>`__: TST: master
branch CI failures
* `#10572 <https://github.com/scipy/scipy/issues/10572>`__: BUG: ckdtree
query_ball_point errors on discontiguous input
* `#10597 <https://github.com/scipy/scipy/issues/10597>`__: BUG: No warning
on PchipInterpolator changing from bernstein base to local power base

Pull requests for 1.3.1
--

* `#10071 <https://github.com/scipy/scipy/pull/10071>`__: DOC: reconstruct
SuperLU permutation matrices avoiding SparseEfficiencyWarning
* `#10196 <https://github.com/scipy/scipy/pull/10196>`__: Fewer checks on
xdata for curve_fit.
* `#10207 <https://github.com/scipy/scipy/pull/10207>`__: BUG: Compressed
matrix indexing should return a scalar
* `#10233 <https://github.com/scipy/scipy/pull/10233>`__: Fix for ARFF
reader regression (#10232)
* `#10306 <https://github.com/scipy/scipy/pull/10306>`__: BUG: optimize:
Fix for 10303
* `#10309 <https://github.com/scipy/scipy/pull/10309>`__: BUG: Pass
jac=None directly to lsoda
* `#10377 <https://github.com/scipy/scipy/pull/10377>`__: TST, MAINT:
adjustments for pytest 5.0
* `#10379 <https://github.com/scipy/scipy/pull/10379>`__: BUG: sparse: set
writeability to be forward-compatible with numpy>=1.17
* `#10426 <https://github.com/scipy/scipy/pull/10426>`__: MAINT: Fix doc
build bugs
* `#10431 <https://github.com/scipy/scipy/pull/10431>`__: Update numpy
version for AIX
* `#10457 <https://github.com/scipy/scipy/pull/10457>`__: BUG: Allow
ckdtree to accept empty data input
* `#10503 <https://github.com/scipy/scipy/pull/10503>`__: BUG:
spatial/qhull: get HalfspaceIntersection.dual_points from the correct array
* `#10516 <https://github.com/scipy/scipy/pull/10516>`__: BUG: Use nogil
contexts in cKDTree
* `#10520 <https://github.com/scipy/scipy/pull/10520>`__: DOC: Proper .rst
formatting for deprecated features and Backwards incompatible changes
* `#10540 <https://github.com/scipy/scipy/pull/10540>`__: MAINT: Fix Travis
and Circle
* `#10573 <https://github.com/scipy/scipy/pull/10573>`__: BUG: Fix
query_ball_point with discontiguous input
* `#10600 <https://github.com/scipy/scipy/pull/10600>`__: BUG: interpolate:
fix broken conversions between PPoly/BPoly objects

Checksums
=

MD5
~~~

818dc6325a4511d656582ff2946eed80
 
scipy-1.3.1-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
83a11b3127b19e71353ee2a04c4be20c  scipy-1.3.1-cp35-cp35m-m

Re: [Numpy-discussion] Using a pyproject.toml file

[Tyler Reddy]

For what it's worth, pyproject.toml seems to have been adopted without much
friction in SciPy. In some CI runs in SciPy, we use something like "pip
wheel --no-build-isolation -v -v -v" to disable the isolation in any case.

I suppose NumPy is indeed even closer to the base of the ecosystem, but the
ease of disabling may mitigate concerns related to switching from
system-installed dependencies to an isolated environment for a naive "pip
install"

Tyler

On Sun, 14 Jul 2019 at 08:47, Matti Picus  wrote:

> In PR #13908 I implemented the previously-discussed new method of creating
> the release notes: writing separate fragments and then combining them at
> release time via towncrier. Towncrier requires a PEP-508/PEP-517/PEP-518
> pyproject.toml file for configuration, and does not currently support a
> command line option to specify a different location for this file. That
> means that we now must ship a pyproject.toml file, which subtlely changes
> the way "pip install ." builds NumPy: it does an "isolated build"
> https://pip.pypa.io/en/stable/reference/pip/#pep-517-and-518-support
>
>
> Questions:
>
> - Is the pain of adding a pyproject.toml worth it for using towncrier or
> should we o for another release-note solution
>
> - Is the addition of pyproject.toml problematic enough that I should break
> it out into a separate pull request for evaluation?
>
>
> Matti
> ___
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> https://mail.python.org/mailman/listinfo/numpy-discussion
>
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[Numpy-discussion] NumPy Community Meeting June 12

[Tyler Reddy]

Hi,

There will be a NumPy Community meeting on June 12 at 11 am Pacific Time.
Anyone is free to join and edit the work-in-progress meeting notes:
https://hackmd.io/76o-IxCjQX2mOXO_wwkcpg?view

Best wishes,
Tyler
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[Numpy-discussion] ANN: SciPy 1.2.2 (LTS)

[Tyler Reddy]

-BEGIN PGP SIGNED MESSAGE-
Hash: SHA256

Hi all,

On behalf of the SciPy development team I'm pleased to announce
the release of SciPy 1.2.2, which is a bug fix release. This is part
of the long-term support (LTS) branch that includes 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/v1.2.2

One of a few ways to install this release with pip:

pip install scipy==1.2.2

=
SciPy 1.2.2 Release Notes
=

SciPy 1.2.2 is a bug-fix release with no new features compared to 1.2.1.
Importantly, the SciPy 1.2.2 wheels are built with OpenBLAS 0.3.7.dev to
alleviate issues with SkylakeX AVX512 kernels.

Authors
==

* CJ Carey
* Tyler Dawson +
* Ralf Gommers
* Kai Striega
* Andrew Nelson
* Tyler Reddy
* Kevin Sheppard +

A total of 7 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 1.2.2
--
* `#9611 <https://github.com/scipy/scipy/issues/9611>`__: Overflow error
with new way of p-value calculation in kendall tau correlation for
perfectly monotonic vectors
* `#9964 <https://github.com/scipy/scipy/issues/9964>`__: optimize.newton :
overwrites x0 argument when it is a numpy array
* `#9784 <https://github.com/scipy/scipy/issues/9784>`__: TST: Minimum
NumPy version is not being CI tested
* `#10132 <https://github.com/scipy/scipy/issues/10132>`__: Docs:
Description of nnz attribute of sparse.csc_matrix misleading

Pull requests for 1.2.2
-
* `#10056 <https://github.com/scipy/scipy/pull/10056>`__: BUG: Ensure
factorial is not too large in kendaltau
* `#9991 <https://github.com/scipy/scipy/pull/9991>`__: BUG: Avoid inplace
modification of input array in newton
* `#9788 <https://github.com/scipy/scipy/pull/9788>`__: TST, BUG:
f2py-related issues with NumPy < 1.14.0
* `#9749 <https://github.com/scipy/scipy/pull/9749>`__: BUG:
MapWrapper.__exit__ should terminate
* `#10141 <https://github.com/scipy/scipy/pull/10141>`__: Update
description for nnz on csc.py

Checksums
=

MD5
~~~

f5d23361e78f230f70fd117be20930e1
 
scipy-1.2.2-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
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SHA256
~~

271c6e56c8f9a3d6c3f0bc857d7a6e7cf7a8415c879a3915701cd011e82a83a3
 
scipy

Re: [Numpy-discussion] Moving forward with value based casting

[Tyler Reddy]

A few thoughts:

- We're not trying to achieve systematic guards against integer overflow /
wrapping in ufunc inner loops, right? The performance tradeoffs for a
"result-based" casting / exception handling addition would presumably be
controversial? I know there was some discussion about having an "overflow
detection mode"  (toggle) of some sort that could be activated for ufunc
loops, but don't think that gained much traction/ priority. I think for
floats we have an awkward way to propagate something back to the user if
there's an issue.
- It sounds like the objective is instead primarily to achieve pure
dtype-based promotion, which is then effectively just a casting table,
which is what I think you mean by "cache?"
- Is it a safe assumption that for a cache (dtype-only casting table), the
main tradeoff is that we'd likely tend towards conservative upcasting and
using more memory in output types in many cases vs. NumPy at the moment?
Stephan seems concerned about that, presumably because x + 1 suddenly
changes output dtype in an overwhelming number of current code lines and
future simple examples for end users.
- If np.array + 1 absolutely has to stay the same output dtype moving
forward, then "Keeping Value based casting only for python types" is the
one that looks most promising to me initially, with a few further concerns:

1) Would that give you enough refactoring "wiggle room" to achieve the
simplifications you need? If value-based promotion still happens for a
non-NumPy operand, can you abstract that logic cleanly from the "pure dtype
cache / table" that is planned for NumPy operands?
2) Is the "out" argument to ufuncs a satisfactory alternative to the "power
users" who want to "override" default output casting type? We suggest that
they pre-allocate an output array of the desired type if they want to save
memory and if they overflow or wrap integers that is their problem. Can we
reasonably ask people who currently depend on the memory-conservation they
might get from value-based behavior to adjust in this way?
3) Presumably "out" does / will circumvent the "cache / dtype casting
table?"

Tyler

On Wed, 5 Jun 2019 at 15:37, Sebastian Berg 
wrote:

> Hi all,
>
> Maybe to clarify this at least a little, here are some examples for
> what currently happen and what I could imagine we can go to (all in
> terms of output dtype).
>
> float32_arr = np.ones(10, dtype=np.float32)
> int8_arr = np.ones(10, dtype=np.int8)
> uint8_arr = np.ones(10, dtype=np.uint8)
>
>
> Current behaviour:
> --
>
> float32_arr + 12.  # float32
> float32_arr + 2**200  # float64 (because np.float32(2**200) == np.inf)
>
> int8_arr + 127 # int8
> int8_arr + 128 # int16
> int8_arr + 2**20   # int32
> uint8_arr + -1 # uint16
>
> # But only for arrays that are not 0d:
> int8_arr + np.array(1, dtype=np.int32)  # int8
> int8_arr + np.array([1], dtype=np.int32)  # int32
>
> # When the actual typing is given, this does not change:
>
> float32_arr + np.float64(12.)  # float32
> float32_arr + np.array(12., dtype=np.float64)  # float32
>
> # Except for inexact types, or complex:
> int8_arr + np.float16(3)  # float16  (same as array behaviour)
>
> # The exact same happens with all ufuncs:
> np.add(float32_arr, 1)   # float32
> np.add(float32_arr, np.array(12., dtype=np.float64)  # float32
>
>
> Keeping Value based casting only for python types
> -
>
> In this case, most examples above stay unchanged, because they use
> plain python integers or floats, such as 2, 127, 12., 3, ... without
> any type information attached, such as `np.float64(12.)`.
>
> These change for example:
>
> float32_arr + np.float64(12.)# float64
> float32_arr + np.array(12., dtype=np.float64)# float64
> np.add(float32_arr, np.array(12., dtype=np.float64)  # float64
>
> # so if you use `np.int32` it will be the same as np.uint64(1)
>
> int8_arr + np.int32(1)  # int32
> int8_arr + np.int32(2**20)  # int32
>
>
> Remove Value based casting completely
> -
>
> We could simply abolish it completely, a python `1` would always behave
> the same as `np.int_(1)`. The downside of this is that:
>
> int8_arr + 1  # int64 (or int32)
>
> uses much more memory suddenly. Or, we remove it from ufuncs, but not
> from operators:
>
> int8_arr + 1  # int8 dtype
>
> but:
>
> np.add(int8_arr, 1)  # int64
> # same as:
> np.add(int8_arr, np.array(1))  # int16
>
> The main reason why I was wondering about that is that for operators
> the logic seems fairly simple, but for general ufuncs it seems more
> complex.
>
> Best,
>
> Sebastian
>
>
>
> On Wed, 2019-06-05 at 15:41 -0500, Sebastian Berg wrote:
> > Hi all,
> >
> > TL;DR:
> >
> > Value based promotion seems complex both for users and ufunc-
> > dispatching/promotion logic. Is there any way we can move forward
> > here,
> > and if we do, could we just risk s

Re: [Numpy-discussion] Weekly Community Meeting -- June 5/ 2019

[Tyler Reddy]

11 am Pacific Time

On Tue, 4 Jun 2019 at 16:14, Tyler Reddy  wrote:

> Hi,
>
> There will be a weekly community call on June 5/ 2019--anyone may join and
> edit the work-in-progress meeting notes:
> https://hackmd.io/5fKOqla6SIqKJMtB7w5Law?view
>
> The conference call link should be in that document.
>
> Best wishes,
> Tyler
>
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[Numpy-discussion] Weekly Community Meeting -- June 5/ 2019

[Tyler Reddy]

Hi,

There will be a weekly community call on June 5/ 2019--anyone may join and
edit the work-in-progress meeting notes:
https://hackmd.io/5fKOqla6SIqKJMtB7w5Law?view

The conference call link should be in that document.

Best wishes,
Tyler
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Re: [Numpy-discussion] Community Call -- May 29/ 2019

[Tyler Reddy]

I added a zoom link to the meeting notes--we'll be capped at 40 minutes
time with my free account though.

On Tue, 28 May 2019 at 12:02, Tyler Reddy  wrote:

> Hi,
>
> There will be a NumPy Community Call on May 29/ 2019 at 11 am Pacific
> Time. Anyone may join and edit the work-in-progress meeting notes:
> https://hackmd.io/Au2YB5QpQjyFUcCfdT1efw?view
>
> I think we still need to sort out a link / medium for the call--hopefully
> that will get added to the document in time.
>
> Best wishes,
> Tyler
>
___
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[Numpy-discussion] Community Call -- May 29/ 2019

[Tyler Reddy]

Hi,

There will be a NumPy Community Call on May 29/ 2019 at 11 am Pacific Time.
Anyone may join and edit the work-in-progress meeting notes:
https://hackmd.io/Au2YB5QpQjyFUcCfdT1efw?view

I think we still need to sort out a link / medium for the call--hopefully
that will get added to the document in time.

Best wishes,
Tyler
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[Numpy-discussion] Community Call -- May 22 (New time / platform)

[Tyler Reddy]

Hi,

Starting from this week, the community meetings will be at a new time (11
am Pacific Time) and on a new meeting platform (see the linked doc).

Anyone is free to join and edit the work-in-progress meeting notes:
https://hackmd.io/bQoK2wuaQV2hJSVuoBUUtg?view

Best wishes,
Tyler
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[Numpy-discussion] ANN: SciPy 1.3.0

[Tyler Reddy]

 ``auto`` is the better choice.

Other changes
=

Our tutorial has been expanded with a new section on global optimizers

There has been a rework of the ``stats.distributions`` tutorials.

`scipy.optimize` now correctly sets the convergence flag of the result to
``CONVERR``, a convergence error, for bounded scalar-function root-finders
if the maximum iterations has been exceeded, ``disp`` is false, and
``full_output`` is true.

`scipy.optimize.curve_fit` no longer fails if ``xdata`` and ``ydata``
dtypes
differ; they are both now automatically cast to ``float64``.

`scipy.ndimage` functions including ``binary_erosion``, ``binary_closing``,
and
``binary_dilation`` now require an integer value for the number of
iterations,
which alleviates a number of reported issues.

Fixed normal approximation in case ``zero_method == "pratt"`` in
`scipy.stats.wilcoxon`.

Fixes for incorrect probabilities, broadcasting issues and thread-safety
related to stats distributions setting member variables inside
``_argcheck()``.

`scipy.optimize.newton` now correctly raises a ``RuntimeError``, when
default
arguments are used, in the case that a derivative of value zero is obtained,
which is a special case of failing to converge.

A draft toolchain roadmap is now available, laying out a compatibility plan
including Python versions, C standards, and NumPy versions.


Authors
===

* ananyashreyjain +
* ApamNapat +
* Scott Calabrese Barton +
* Christoph Baumgarten
* Peter Bell +
* Jacob Blomgren +
* Doctor Bob +
* Mana Borwornpadungkitti +
* Matthew Brett
* Evgeni Burovski
* CJ Carey
* Vega Theil Carstensen +
* Robert Cimrman
* Forrest Collman +
* Pietro Cottone +
* David +
* Idan David +
* Christoph Deil
* Dieter Werthmüller
* Conner DiPaolo +
* Dowon
* Michael Dunphy +
* Peter Andreas Entschev +
* Gökçen Eraslan +
* Johann Faouzi +
* Yu Feng
* Piotr Figiel +
* Matthew H Flamm
* Franz Forstmayr +
* Christoph Gohlke
* Richard Janis Goldschmidt +
* Ralf Gommers
* Lars Grueter
* Sylvain Gubian
* Matt Haberland
* Yaroslav Halchenko
* Charles Harris
* Lindsey Hiltner
* JakobStruye +
* He Jia +
* Jwink3101 +
* Greg Kiar +
* Julius Bier Kirkegaard
* John Kirkham +
* Thomas Kluyver
* Vladimir Korolev +
* Joseph Kuo +
* Michael Lamparski +
* Eric Larson
* Denis Laxalde
* Katrin Leinweber
* Jesse Livezey
* ludcila +
* Dhruv Madeka +
* Magnus +
* Nikolay Mayorov
* Mark Mikofski
* Jarrod Millman
* Markus Mohrhard +
* Eric Moore
* Andrew Nelson
* Aki Nishimura +
* OGordon100 +
* Petar Mlinarić +
* Stefan Peterson
* Matti Picus +
* Ilhan Polat
* Aaron Pries +
* Matteo Ravasi +
* Tyler Reddy
* Ashton Reimer +
* Joscha Reimer
* rfezzani +
* Riadh +
* Lucas Roberts
* Heshy Roskes +
* Mirko Scholz +
* Taylor D. Scott +
* Srikrishna Sekhar +
* Kevin Sheppard +
* Sourav Singh
* skjerns +
* Kai Striega
* SyedSaifAliAlvi +
* Gopi Manohar T +
* Albert Thomas +
* Timon +
* Paul van Mulbregt
* Jacob Vanderplas
* Daniel Vargas +
* Pauli Virtanen
* VNMabus +
* Stefan van der Walt
* Warren Weckesser
* Josh Wilson
* Nate Yoder +
* Roman Yurchak

A total of 97 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 1.3.0
---

* `#1320 <https://github.com/scipy/scipy/issues/1320>`__:
scipy.stats.distribution: problem with self.a, self.b if they...
* `#2002 <https://github.com/scipy/scipy/issues/2002>`__: members set in
scipy.stats.distributions.##._argcheck (Trac #1477)
* `#2823 <https://github.com/scipy/scipy/issues/2823>`__: distribution
methods add tmp
* `#3220 <https://github.com/scipy/scipy/issues/3220>`__:
Scipy.opimize.fmin_powell direc argument syntax unclear
* `#3728 <https://github.com/scipy/scipy/issues/3728>`__:
scipy.stats.pearsonr: possible bug with zero variance input
* `#6805 <https://github.com/scipy/scipy/issues/6805>`__:
error-in-scipy-wilcoxon-signed-rank-test-for-equal-series
* `#6873 <https://github.com/scipy/scipy/issues/6873>`__: 'stats.boxcox'
return all same values
* `#7117 <https://github.com/scipy/scipy/issues/7117>`__: Warn users when
using float32 input data to curve_fit and friends
* `#7632 <https://github.com/scipy/scipy/issues/7632>`__: it's not possible
to tell the \`optimize.least_squares\` solver...
* `#7730 <https://github.com/scipy/scipy/issues/7730>`__: stats.pearsonr:
Potential division by zero for dataset of length...
* `#7933 <https://github.com/scipy/scipy/issues/7933>`__: stats.truncnorm
fails when providing values outside truncation...
* `#8033 <https://github.com/scipy/scipy/issues/8033>`__: Add standard
filter types to firwin to set pass_zero intuitively...
* `#8600 <https://github.com/scipy/scipy/issues/8600>`__: lfilter.c.src
zfill has erroneous header
* `#8692 <https://github.com/scipy/scipy/issues/8692>`__: Non-negative
va

[Numpy-discussion] NumPy Community Meeting -- May 15/ 2019

[Tyler Reddy]

Hi,

There will be a community meeting at 12 pm Pacific Time on May 15/ 2019.
Anyone is free to join and edit the work in progress meeting notes:
https://hackmd.io/M-ef_Fu5QOOitACnyoO0kQ?view

Best wishes,
Tyler
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[Numpy-discussion] ANN: SciPy 1.3.0rc2 -- please test

[Tyler Reddy]

he result to
``CONVERR``, a convergence error, for bounded scalar-function root-finders
if the maximum iterations has been exceeded, ``disp`` is false, and
``full_output`` is true.

`scipy.optimize.curve_fit` no longer fails if ``xdata`` and ``ydata``
dtypes
differ; they are both now automatically cast to ``float64``.

`scipy.ndimage` functions including ``binary_erosion``, ``binary_closing``,
and
``binary_dilation`` now require an integer value for the number of
iterations,
which alleviates a number of reported issues.

Fixed normal approximation in case ``zero_method == "pratt"`` in
`scipy.stats.wilcoxon`.

Fixes for incorrect probabilities, broadcasting issues and thread-safety
related to stats distributions setting member variables inside
``_argcheck()``.

`scipy.optimize.newton` now correctly raises a ``RuntimeError``, when
default
arguments are used, in the case that a derivative of value zero is obtained,
which is a special case of failing to converge.

A draft toolchain roadmap is now available, laying out a compatibility plan
including Python versions, C standards, and NumPy versions.


Authors
===

* ananyashreyjain +
* ApamNapat +
* Scott Calabrese Barton +
* Christoph Baumgarten
* Peter Bell +
* Jacob Blomgren +
* Doctor Bob +
* Mana Borwornpadungkitti +
* Matthew Brett
* Evgeni Burovski
* CJ Carey
* Vega Theil Carstensen +
* Robert Cimrman
* Forrest Collman +
* Pietro Cottone +
* David +
* Idan David +
* Christoph Deil
* Dieter Werthmüller
* Conner DiPaolo +
* Dowon
* Michael Dunphy +
* Peter Andreas Entschev +
* Gökçen Eraslan +
* Johann Faouzi +
* Yu Feng
* Piotr Figiel +
* Matthew H Flamm
* Franz Forstmayr +
* Christoph Gohlke
* Richard Janis Goldschmidt +
* Ralf Gommers
* Lars Grueter
* Sylvain Gubian
* Matt Haberland
* Yaroslav Halchenko
* Charles Harris
* Lindsey Hiltner
* JakobStruye +
* He Jia +
* Jwink3101 +
* Greg Kiar +
* Julius Bier Kirkegaard
* John Kirkham +
* Thomas Kluyver
* Vladimir Korolev +
* Joseph Kuo +
* Michael Lamparski +
* Eric Larson
* Denis Laxalde
* Katrin Leinweber
* Jesse Livezey
* ludcila +
* Dhruv Madeka +
* Magnus +
* Nikolay Mayorov
* Mark Mikofski
* Jarrod Millman
* Markus Mohrhard +
* Eric Moore
* Andrew Nelson
* Aki Nishimura +
* OGordon100 +
* Petar Mlinarić +
* Stefan Peterson
* Matti Picus +
* Ilhan Polat
* Aaron Pries +
* Matteo Ravasi +
* Tyler Reddy
* Ashton Reimer +
* Joscha Reimer
* rfezzani +
* Riadh +
* Lucas Roberts
* Heshy Roskes +
* Mirko Scholz +
* Taylor D. Scott +
* Srikrishna Sekhar +
* Kevin Sheppard +
* Sourav Singh
* skjerns +
* Kai Striega
* SyedSaifAliAlvi +
* Gopi Manohar T +
* Albert Thomas +
* Timon +
* Paul van Mulbregt
* Jacob Vanderplas
* Daniel Vargas +
* Pauli Virtanen
* VNMabus +
* Stefan van der Walt
* Warren Weckesser
* Josh Wilson
* Nate Yoder +
* Roman Yurchak

A total of 97 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 1.3.0
- ---

* `#1320 <https://github.com/scipy/scipy/issues/1320>`__:
scipy.stats.distribution: problem with self.a, self.b if they...
* `#2002 <https://github.com/scipy/scipy/issues/2002>`__: members set in
scipy.stats.distributions.##._argcheck (Trac #1477)
* `#2823 <https://github.com/scipy/scipy/issues/2823>`__: distribution
methods add tmp
* `#3220 <https://github.com/scipy/scipy/issues/3220>`__:
Scipy.opimize.fmin_powell direc argument syntax unclear
* `#3728 <https://github.com/scipy/scipy/issues/3728>`__:
scipy.stats.pearsonr: possible bug with zero variance input
* `#6805 <https://github.com/scipy/scipy/issues/6805>`__:
error-in-scipy-wilcoxon-signed-rank-test-for-equal-series
* `#6873 <https://github.com/scipy/scipy/issues/6873>`__: 'stats.boxcox'
return all same values
* `#7117 <https://github.com/scipy/scipy/issues/7117>`__: Warn users when
using float32 input data to curve_fit and friends
* `#7632 <https://github.com/scipy/scipy/issues/7632>`__: it's not possible
to tell the \`optimize.least_squares\` solver...
* `#7730 <https://github.com/scipy/scipy/issues/7730>`__: stats.pearsonr:
Potential division by zero for dataset of length...
* `#7933 <https://github.com/scipy/scipy/issues/7933>`__: stats.truncnorm
fails when providing values outside truncation...
* `#8033 <https://github.com/scipy/scipy/issues/8033>`__: Add standard
filter types to firwin to set pass_zero intuitively...
* `#8600 <https://github.com/scipy/scipy/issues/8600>`__: lfilter.c.src
zfill has erroneous header
* `#8692 <https://github.com/scipy/scipy/issues/8692>`__: Non-negative
values of \`stats.hypergeom.logcdf\`
* `#8734 <https://github.com/scipy/scipy/issues/8734>`__: Enable pip build
isolation
* `#8861 <https://github.com/scipy/scipy/issues/8861>`__: scipy.linalg.pinv
gives wrong result while scipy.linalg.pinv2..

[Numpy-discussion] NumPy Community Meeting May 8/ 2019

[Tyler Reddy]

Hi,

There will be a NumPy Community meeting at 12 pm Pacific Time on May 8/
2019. Anyone is welcome to join and edit the work in progress meeting
document: https://hackmd.io/M-ef_Fu5QOOitACnyoO0kQ?view

Best wishes,
Tyler
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Re: [Numpy-discussion] ANN: SciPy 1.3.0rc1 -- please test

[Tyler Reddy]

I'd very much appreciate if someone with access to Skylake architecture can
confirm linear algebra-related failures / issues
for SciPy 1.2.1 and SciPy 1.3.0rc1:

for a simple example:
https://github.com/numpy/numpy/issues/13401#issuecomment-486690487

There's some credible concern that both of those releases have effectively
broken linear algebra behavior for wheels
with the OpenBLAS versions they are distributed with, but I want to be sure
before investing time in updating two
release branches obviously!

On Fri, 26 Apr 2019 at 18:25, Tyler Reddy  wrote:

> -BEGIN PGP SIGNED MESSAGE-
> Hash: SHA1
>
> Hi all,
>
> On behalf of the SciPy development team I'm pleased to announce
> the release candidate SciPy 1.3.0rc1. Please help us test this pre-release.
>
> Sources and binary wheels can be found at:https://pypi.org/project/scipy/
> and at:https://github.com/scipy/scipy/releases/tag/v1.3.0rc1
> One of a few ways to install the release candidate with pip:
> pip install scipy==1.3.0rc1
>
> ==
> SciPy 1.3.0 Release Notes
> ==
>
> Note: Scipy 1.3.0 is not released yet!
>
> SciPy 1.3.0 is the culmination of 5 months of hard work. It contains
> many new features, numerous bug-fixes, improved test coverage and better
> documentation. There have been some 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
> 1.3.x branch, and on adding new features on the master branch.
>
> This release requires Python 3.5+ and NumPy 1.13.3 or greater.
>
> For running on PyPy, PyPy3 6.0+ and NumPy 1.15.0 are required.
>
> Highlights of this release
> --
>
> - Three new ``stats`` functions, a rewrite of ``pearsonr``, and an exact
>   computation of the Kolmogorov-Smirnov two-sample test
> - A new Cython API for bounded scalar-function root-finders in 
> `scipy.optimize`
> - Substantial ``CSR`` and ``CSC`` sparse matrix indexing performance
>   improvements
> - Added support for interpolation of rotations with continuous angular
>   rate and acceleration in ``RotationSpline``
>
>
> New features
> 
>
> `scipy.interpolate` improvements
> 
>
> A new class ``CubicHermiteSpline`` is introduced. It is a piecewise-cubic
> interpolator which matches observed values and first derivatives. Existing
> cubic interpolators ``CubicSpline``, ``PchipInterpolator`` and
> ``Akima1DInterpolator`` were made subclasses of ``CubicHermiteSpline``.
>
> `scipy.io` improvements
> ---
>
> For the Attribute-Relation File Format (ARFF) `scipy.io.arff.loadarff`
> now supports relational attributes.
>
> `scipy.io.mmread` can now parse Matrix Market format files with empty lines.
>
> `scipy.linalg` improvements
> ---
>
> Added wrappers for ``?syconv`` routines, which convert a symmetric matrix
> given by a triangular matrix factorization into two matrices and vice versa.
>
> `scipy.linalg.clarkson_woodruff_transform` now uses an algorithm that 
> leverages
> sparsity. This may provide a 60-90 percent speedup for dense input matrices.
> Truly sparse input matrices should also benefit from the improved sketch
> algorithm, which now correctly runs in ``O(nnz(A))`` time.
>
> Added new functions to calculate symmetric Fiedler matrices and
> Fiedler companion matrices, named `scipy.linalg.fiedler` and
> `scipy.linalg.fiedler_companion`, respectively. These may be used
> for root finding.
>
> `scipy.ndimage` improvements
> 
>
> Gaussian filter performances may improve by an order of magnitude in
> some cases, thanks to removal of a dependence on ``np.polynomial``. This
> may impact `scipy.ndimage.gaussian_filter` for example.
>
> `scipy.optimize` improvements
> -
>
> The `scipy.optimize.brute` minimizer obtained a new keyword ``workers``, which
> can be used to parallelize computation.
>
> A Cython API for bounded scalar-function root-finders in `scipy.optimize`
> is available in a new module `scipy.optimize.cython_optimize` via ``cimport``.
> This API may be used with ``nogil`` and ``prange`` to loop
> over an array of function arguments to solve for an array of roots more
> quickly than with pure Python.
>
> ``'interior-point'`` i

[Numpy-discussion] NumPy Community Meeting on May 1/ 2019

[Tyler Reddy]

Hi,

There will be a NumPy community meeting at 12 pm Pacific Time on May 1/
2019. Anyone may join & edit the work in progress meeting notes available
here: https://hackmd.io/MzSVnXjiR7ykM6ocNKAOxg?view

Best wishes,
Tyler
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[Numpy-discussion] ANN: SciPy 1.3.0rc1 -- please test

[Tyler Reddy]

e.curve_fit` no longer fails if ``xdata`` and ``ydata`` dtypes
differ; they are both now automatically cast to ``float64``.

`scipy.ndimage` functions including ``binary_erosion``, ``binary_closing``, and
``binary_dilation`` now require an integer value for the number of iterations,
which alleviates a number of reported issues.

Fixed normal approximation in case ``zero_method == "pratt"`` in
`scipy.stats.wilcoxon`.

Fixes for incorrect probabilities, broadcasting issues and thread-safety
related to stats distributions setting member variables inside ``_argcheck()``.

`scipy.optimize.newton` now correctly raises a ``RuntimeError``, when default
arguments are used, in the case that a derivative of value zero is obtained,
which is a special case of failing to converge.

A draft toolchain roadmap is now available, laying out a compatibility plan
including Python versions, C standards, and NumPy versions.


Authors
===

* ananyashreyjain +
* ApamNapat +
* Scott Calabrese Barton +
* Christoph Baumgarten
* Peter Bell +
* Jacob Blomgren +
* Doctor Bob +
* Mana Borwornpadungkitti +
* Matthew Brett
* Evgeni Burovski
* CJ Carey
* Vega Theil Carstensen +
* Robert Cimrman
* Forrest Collman +
* Pietro Cottone +
* David +
* Idan David +
* Christoph Deil
* Dieter Werthmüller
* Conner DiPaolo +
* Dowon
* Michael Dunphy +
* Peter Andreas Entschev +
* Gökçen Eraslan +
* Johann Faouzi +
* Yu Feng
* Piotr Figiel +
* Matthew H Flamm
* Franz Forstmayr +
* Christoph Gohlke
* Richard Janis Goldschmidt +
* Ralf Gommers
* Lars Grueter
* Sylvain Gubian
* Matt Haberland
* Yaroslav Halchenko
* Charles Harris
* Lindsey Hiltner
* JakobStruye +
* He Jia +
* Jwink3101 +
* Greg Kiar +
* Julius Bier Kirkegaard
* John Kirkham +
* Thomas Kluyver
* Vladimir Korolev +
* Joseph Kuo +
* Michael Lamparski +
* Eric Larson
* Denis Laxalde
* Katrin Leinweber
* Jesse Livezey
* ludcila +
* Dhruv Madeka +
* Magnus +
* Nikolay Mayorov
* Mark Mikofski
* Jarrod Millman
* Markus Mohrhard +
* Eric Moore
* Andrew Nelson
* Aki Nishimura +
* OGordon100 +
* Petar Mlinarić +
* Stefan Peterson
* Matti Picus +
* Ilhan Polat
* Aaron Pries +
* Matteo Ravasi +
* Tyler Reddy
* Ashton Reimer +
* Joscha Reimer
* rfezzani +
* Riadh +
* Lucas Roberts
* Heshy Roskes +
* Mirko Scholz +
* Taylor D. Scott +
* Srikrishna Sekhar +
* Kevin Sheppard +
* Sourav Singh
* skjerns +
* Kai Striega
* SyedSaifAliAlvi +
* Gopi Manohar T +
* Albert Thomas +
* Timon +
* Paul van Mulbregt
* Jacob Vanderplas
* Daniel Vargas +
* Pauli Virtanen
* VNMabus +
* Stefan van der Walt
* Warren Weckesser
* Josh Wilson
* Nate Yoder +
* Roman Yurchak

A total of 97 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 1.3.0
---

* `#1320 <https://github.com/scipy/scipy/issues/1320>`__:
scipy.stats.distribution: problem with self.a, self.b if they...
* `#2002 <https://github.com/scipy/scipy/issues/2002>`__: members set
in scipy.stats.distributions.##._argcheck (Trac #1477)
* `#2823 <https://github.com/scipy/scipy/issues/2823>`__: distribution
methods add tmp
* `#3220 <https://github.com/scipy/scipy/issues/3220>`__:
Scipy.opimize.fmin_powell direc argument syntax unclear
* `#3728 <https://github.com/scipy/scipy/issues/3728>`__:
scipy.stats.pearsonr: possible bug with zero variance input
* `#6805 <https://github.com/scipy/scipy/issues/6805>`__:
error-in-scipy-wilcoxon-signed-rank-test-for-equal-series
* `#6873 <https://github.com/scipy/scipy/issues/6873>`__:
'stats.boxcox' return all same values
* `#7117 <https://github.com/scipy/scipy/issues/7117>`__: Warn users
when using float32 input data to curve_fit and friends
* `#7632 <https://github.com/scipy/scipy/issues/7632>`__: it's not
possible to tell the \`optimize.least_squares\` solver...
* `#7730 <https://github.com/scipy/scipy/issues/7730>`__:
stats.pearsonr: Potential division by zero for dataset of length...
* `#7933 <https://github.com/scipy/scipy/issues/7933>`__:
stats.truncnorm fails when providing values outside truncation...
* `#8033 <https://github.com/scipy/scipy/issues/8033>`__: Add standard
filter types to firwin to set pass_zero intuitively...
* `#8600 <https://github.com/scipy/scipy/issues/8600>`__:
lfilter.c.src zfill has erroneous header
* `#8692 <https://github.com/scipy/scipy/issues/8692>`__: Non-negative
values of \`stats.hypergeom.logcdf\`
* `#8734 <https://github.com/scipy/scipy/issues/8734>`__: Enable pip
build isolation
* `#8861 <https://github.com/scipy/scipy/issues/8861>`__:
scipy.linalg.pinv gives wrong result while scipy.linalg.pinv2...
* `#8915 <https://github.com/scipy/scipy/issues/8915>`__: need to fix
macOS build against older numpy versions
* `#8980 <https://github.com/scipy/scipy/issues/8980>`__:
scipy.stats.pea

[Numpy-discussion] NumPy community meeting April 24/ 2019

[Tyler Reddy]

Hi,

There will be a NumPy community meeting at 12 pm Pacific Time on April 24/
2019.

Anyone is welcome to join & edit the meeting notes available here:
https://hackmd.io/a03zhF4TSsewJp_fXXXwOQ?view
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[Numpy-discussion] Weekly NumPy Community Meeting -- April 17/ 2019

[Tyler Reddy]

Hi All,

There will be a community meeting tomorrow, April 17, at 12 pm Pacific Time.

Anyone may join & contribute to the work in progress meeting document
available here: https://hackmd.io/a03zhF4TSsewJp_fXXXwOQ?view

Best wishes,
Tyler
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Re: [Numpy-discussion] Does numpy depend upon a Fortran library?

[Tyler Reddy]

I have a different view on the assessments in this thread, having built
OpenBLAS manually a number of times on different platforms now.

Those shared objects packed in the wheel, including libgfortran and
libquadmath, are proper runtime dependencies for the OpenBLAS library we
ship with wheels, not artifacts of an old ATLAS dependency structure.
Another way to achieve compliance with the wheels standard is to statically
link them in when we build OpenBLAS on macpython / manually. This seems to
be relatively doable on some platforms, and harder on others.

There is a demonstration for Mac OS + NumPy available:
https://github.com/numpy/numpy/pull/13191

On Linux, it is much harder, we would need a custom build of gcc from
source with -fPIC compiler flag used to build libgfortran.a. The Julia
language also faced this challenge on static links:
https://github.com/JuliaLang/julia/issues/326#issuecomment-191781005

I'm not saying we should jump on static linking of the GCC runtime into
OpenBLAS right away, but removing those shared objects from the wheels
without a linking change doesn't seem quite right unless I'm missing
something major. If we do eventually embrace the static link of the GCC
runtime into the OpenBLAS wheels, this also makes our daily CI
infrastructure less complex because we don't get pinned to specific runtime
library versions of libgfortran / libquadmath & could likely just remove
the gfortran-install submodule from our wheels workflow as well.

But we don't get that gain for nothing--we do transfer some non-trivial
burden to "upstream" builds of OpenBLAS & things do mostly tend to work the
way they are now. The PEPs surrounding the wheel ecosystem also contain
some cautions about the complexities of trying to static link with default
OS lib availabilities.

Best wishes,
Tyler





On Thu, 31 Jan 2019 at 15:58, Ralf Gommers  wrote:

>
>
> On Wed, Jan 30, 2019 at 6:03 PM Charles R Harris <
> charlesr.har...@gmail.com> wrote:
>
>>
>>
>> On Wed, Jan 30, 2019 at 6:32 PM Ralf Gommers 
>> wrote:
>>
>>>
>>>
>>> On Wed, Jan 30, 2019 at 5:19 PM Charles R Harris <
>>> charlesr.har...@gmail.com> wrote:
>>>


 On Wed, Jan 30, 2019 at 5:28 PM Marc F Paterno 
 wrote:

> Hello,
>
> I have encountered a problem with a binary incompatibility between the
> Fortran runtime library installed with numpy when using 'pip install 
> --user
> numpy', and that used by the rest of my program, which is built using
> gfortran from GCC 8.2.  The numpy installation uses libgfortran.5.dylib,
> and GCC 8.2 provides libgfortran.5.dylib.
>
> While investigating the source of this problem, I downloaded the numpy
> source
> (
> https://files.pythonhosted.org/packages/04/b6/d7faa70a3e3eac39f943cc6a6a64ce378259677de516bd899dd9eb8f9b32/numpy-1.16.0.zip
> ),
> and tried building it. The resulting libraries have no coupling to any
> Fortran library that I can find.  I can find no Fortran source code files
> in the numpy source,
> except in tests or documentation.
>
> I am working on a MacBook laptop, running macOS Mojave, and so am
> using the Accelerate framework to supply BLAS.
>
> I do not understand why the pip installation of numpy includes a
> Fortran runtime library. Can someone explain to me what I am missing?
>
>
 That's interesting, it looks like the wheel includes four libraries:

 -rw-r--r--. 1 charris charris   273072 Jan  1  1980 libgcc_s.1.dylib
 -rwxr-xr-x. 1 charris charris  1550456 Jan  1  1980 libgfortran.3.dylib
 -rwxr-xr-x. 1 charris charris 63433364 Jan  1  1980
 libopenblasp-r0.3.5.dev.dylib
 -rwxr-xr-x. 1 charris charris   279932 Jan  1  1980 libquadmath.0.dylib

 I thought we only needed the openblas, but that in turn probably
 depends on libgcc. But why we have the fortran library and quadmath escapes
 me. Perhaps someone else knows.

>>>
>>> I suspect it's a leftover from when we were using ATLAS, we did need a
>>> Fortran runtime library at some point. The cause will be somewhere in the
>>> numpy-wheel build scripts, there is a gfortran-install git submodule:
>>> https://github.com/MacPython/numpy-wheels
>>>
>>
>> And fortran is probably why the quadmath is there. Hmm, if we fix it we
>> will need to test it...
>>
>
> I opened an issue: https://github.com/MacPython/numpy-wheels/issues/42
>
> Ralf
>
>
>> Chuck
>>
>>>
>>>

 Note that compiling from source is different and will generally use
 different libraries. We don't use Accelerate because it is buggy, not
 thread safe, and it appears Apple is not interested in doing anything about
 that.

 Chuck
 ___
 NumPy-Discussion mailing list
 NumPy-Discussion@python.org
 https://mail.python.org/mailman/listinfo/numpy-discussion

>>> ___
>>> NumPy-Discussion mai

[Numpy-discussion] BIDS / NumPy community meeting April 10/ 2019

[Tyler Reddy]

Hi,

A reminder of the community call scheduled for April 10/ 2019 at 12 pm
Pacific Time. There's a section for community-suggested topics on the draft
meeting document that may be edited here:
https://hackmd.io/WVHUbdriRe26t6s09HjEhA?view
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[Numpy-discussion] BIDS / NumPy community meeting April 3/ 2019

[Tyler Reddy]

Hi,

A reminder of the NumPy community meeting scheduled for 12pm Pacific time
tomorrow, April 3/ 2019.

There's a work in progress document with a community topics section that
may be edited: https://hackmd.io/30eMeRnDQCSW7yDOG05gxA?view
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[Numpy-discussion] NumPy - BIDS / community meeting March 27

[Tyler Reddy]

Hi,

A reminder of the weekly call tomorrow (March 27) at 12 pm Pacific Time,
with work in progress meeting notes here:
https://hackmd.io/kPZJ6E4aTa-27fsEsgY2Sw?view

There's a section for community-suggested topics.
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[Numpy-discussion] BIDS / NumPy Community Meeting tomorrow (March 20th)

[Tyler Reddy]

Hi,

Just a reminder of the community meeting tomorrow at 12 pm Pacific time.
There's a section for community suggested topics in the work-in-progress
document that can be edited here:
https://hackmd.io/c_SRuI0GTNKBZHzsRX9wSw?view
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[Numpy-discussion] BIDS / community call March 13

[Tyler Reddy]

Hi,

A reminder of our weekly community call tomorrow, March 13th, at 12 pm
Pacific Time. Note that we recently started Daylight Savings Time in
California, so some locations may experience a relative time difference.

There's a section for community-suggested topics in the meeting document
that may be edited: https://hackmd.io/pYftrlnJQR-opNHS9Zg7-A?view
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[Numpy-discussion] Weekly BIDS / community meeting

[Tyler Reddy]

Hi,

Just a reminder of the weekly meeting in a few hours today, March 6, at 12
pm Pacific time.

The document with a space for community suggested topics & video conference
link is available here: https://hackmd.io/4JBjLkbCS02nELfckJWB5Q?view
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[Numpy-discussion] Reminder: weekly status meeting Feb. 13 at 12:00 Pacific Time

[Tyler Reddy]

Draft agenda: https://hackmd.io/f_e6dnssTkuIC0Pa0TEV6w?view

There is a section for community suggested topics, feel free to join the
conversation and add in topics that need attention.

BIDS team
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[Numpy-discussion] ANN: SciPy 1.2.1

[Tyler Reddy]

-BEGIN PGP SIGNED MESSAGE-
Hash: SHA1

Hi all,

On behalf of the SciPy development team I'm pleased to announce
the release of SciPy 1.2.1, which is a bug fix release.

Sources and binary wheels can be found at:
https://pypi.org/project/scipy/
and at: https://github.com/scipy/scipy/releases/tag/v1.2.1

One of a few ways to install this release with pip:

pip install scipy==1.2.1

==
SciPy 1.2.1 Release Notes
==

SciPy 1.2.1 is a bug-fix release with no new features compared to 1.2.0.
Most importantly, it solves the issue that 1.2.0 cannot be installed
from source on Python 2.7 because of non-ASCII character issues.

It is also notable that SciPy 1.2.1 wheels were built with OpenBLAS
0.3.5.dev, which may alleviate some linear algebra issues observed
in SciPy 1.2.0.

Authors
===

* Eric Larson
* Mark Mikofski
* Evgeni Burovski
* Ralf Gommers
* Eric Moore
* Tyler Reddy

Issues closed for 1.2.1


* `#9606 <https://github.com/scipy/scipy/issues/9606>`__: SyntaxError:
Non-ASCII character '\xe2' in file scipy/stats/_continuous_distns.py on
line 3346, but no encoding declared
* `#9608 <https://github.com/scipy/scipy/issues/9608>`__: Version 1.2.0
introduces `too many indices for array` error in...
* `#9709 <https://github.com/scipy/scipy/issues/9709>`__:
scipy.stats.gaussian_kde normalizes the weights keyword argument...
* `#9733 <https://github.com/scipy/scipy/issues/9733>`__:
scipy.linalg.qr_update gives NaN result
* `#9724 <https://github.com/scipy/scipy/issues/9724>`__: CI: Is
scipy.scipy Windows Python36-32bit-full working?

Pull requests for 1.2.1


* `#9612 <https://github.com/scipy/scipy/pull/9612>`__: BUG: don't use
array newton unless size is greater than 1
* `#9615 <https://github.com/scipy/scipy/pull/9615>`__: ENH: Add test for
encoding
* `#9720 <https://github.com/scipy/scipy/pull/9720>`__: BUG: stats:
weighted KDE does not modify the weights array
* `#9739 <https://github.com/scipy/scipy/pull/9739>`__: BUG: qr_updates
fails if u is exactly in span Q
* `#9725 <https://github.com/scipy/scipy/pull/9725>`__: TST: pin mingw for
Azure Win CI
* `#9736 <https://github.com/scipy/scipy/pull/9736>`__: TST: adjust to
vmImage dispatch in Azure
* `#9681 <https://github.com/scipy/scipy/pull/9681>`__: BUG: Fix failing
stats tests (partial backport)
* `#9662 <https://github.com/scipy/scipy/pull/9662>`__: TST: interpolate:
avoid pytest deprecations

Checksums
=

MD5
~~~

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23424815af8e69f945bb406a0c1be6c6  scipy-1.2.1-cp37-cp37m-w

[Numpy-discussion] Reminder: weekly status meeting Feb. 6 at 12:00 Pacific Time

[Tyler Reddy]

Draft agenda: https://hackmd.io/5AUINxNfS3iN0txIaN32HA?view

There is a section for community suggested topics, feel free to join the
conversation and add in topics that need attention.

BIDS team
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Re: [Numpy-discussion] timedelta64 remainder behavior with div by 0

[Tyler Reddy]

Looks like we're still on 1.16.0rc2 -- released 4 days ago.

On Tue, 8 Jan 2019 at 10:28, Eric Wieser 
wrote:

> If we consider it a bug, we could patch it in 1.16.1 (or are we still
> waiting on 1.16.0?), which would minimize the backwards compatibility cost.
>
> Eric
>
> On Tue, 8 Jan 2019 at 10:05 Stefan van der Walt 
> wrote:
>
>> On Tue, 08 Jan 2019 09:57:03 -0800, Tyler Reddy wrote:
>> > np.timedelta64(5) % np.timedelta64(0) -> numpy.timedelta64(0)
>> >
>> > In contrast, np.float64(1) % np.float64(0) -> nan
>> >
>> > There's a suggestion that we should switch to returning NaT for the
>> > timedelta64 case for consistency, and that this probably isn't too
>> harmful
>> > given how recent these additions are.
>>
>> That seems like a reasonable change to me; one could probably consider the
>> previous behavior a bug?
>>
>> Stéfan
>> ___
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> ___
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>
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[Numpy-discussion] timedelta64 remainder behavior with div by 0

[Tyler Reddy]

We are now at the stage of implementing the timedelta64 divmod inner loop
given very recent additions of floordiv and remainder inner loops for this
data type. However, there is some contention about a previous decision
regarding modulus behavior that we'd like to resolve before we bake it in
to divmod.

Currently, a modulus operation with two timedelta64 operands with a 0
denominator returns 0. For example:

np.timedelta64(5) % np.timedelta64(0) -> numpy.timedelta64(0)

In contrast, np.float64(1) % np.float64(0) -> nan

There's a suggestion that we should switch to returning NaT for the
timedelta64 case for consistency, and that this probably isn't too harmful
given how recent these additions are.

Do we have consensus on this?

Ref: https://github.com/numpy/numpy/pull/12683

Thanks!
Tyler
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[Numpy-discussion] ANN: SciPy 1.2.0

[Tyler Reddy]

he 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 Sp

Re: [Numpy-discussion] align `choices` and `sample` with Python `random` module

[Tyler Reddy]

I think the current random infrastructure is mostly considered frozen
anyway, even for bugfixes, given the pending NEP to produce a new random
infrastructure and the commitment therein to guarantee that old random
streams behave the same way given their extensive use in testing and so on.
Maybe there are opportunities to have fruitful suggestions for the new
system moving forward.

On Mon, 10 Dec 2018 at 08:27, Alan Isaac  wrote:

> On 12/10/2018 11:20 AM, Ralf Gommers wrote:
> > there is nothing wrong with the current API
>
> Just to be clear: you completely reject the past
> cautions on this list against creating APIs
> with flag parameters.  Is that correct?
>
> Or is "nothing wrong" just a narrow approval in
> this particular case?
>
> Alan Isaac
> ___
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>
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[Numpy-discussion] ANN: SciPy 1.2.0rc2 -- please test

[Tyler Reddy]

te 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>

[Numpy-discussion] ANN: SciPy 1.2.0rc1 -- please test

[Tyler Reddy]

e 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 +
* 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
- ---

* `#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?
*

Re: [Numpy-discussion] Reminder: weekly status meeting

[Tyler Reddy]

What exactly would you like Cython wrappers for? Some of the C++ code
in scipy/sparse/sparsetools?

I see you have COO.from_scipy_sparse(x) in some pydata/sparse code paths,
which presumably you'd like to avoid or improve?

On Thu, 25 Oct 2018 at 03:41, Hameer Abbasi 
wrote:

> Hi!
>
> Sorry to miss this week’s meeting.
>
> If I may point out an inaccuracy in the notes: in PyData/Sparse most
> things are implemented from the ground up without relying on scipy.sparse.
> The only part that does rely on it is `sparse.matmul`, `sparse.dot` and
> `sparse.tensordot`, as well as a few conversions to/from SciPy, if these
> could depend on Cython wrappers instead that’d be nice.
>
> I should probably update the docs on that. If anyone is willing to discuss
> pydata/sparse with me, I’ll be available for a meeting anytime.
>
> Best Regards,
> Hameer Abbasi
>
> On Thursday, Oct 25, 2018 at 12:08 AM, Stefan van der Walt <
> stef...@berkeley.edu> wrote:
> Hi all,
>
> On Mon, 22 Oct 2018 09:56:37 +0300, Matti Picus wrote:
>
> We therefore invite you to join us for our weekly calls,
> each **Wednesday from 12:00 to 13:00 Pacific Time**.
>
> Detail of the next meeting (2018-10-24) is given in the agenda
>
>
> This week's meeting notes are at:
>
>
> https://github.com/BIDS-numpy/docs/blob/master/status_meetings/status-2018-10-24.md
>
> Stéfan
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Re: [Numpy-discussion] CI Testing

[Tyler Reddy]

Hi Allan,

That's pretty cool -- I should follow-up on the CI part of it!

Tyler

On Wed, 12 Sep 2018 at 20:18, Allan Haldane  wrote:

> On 09/12/2018 08:14 PM, Tyler Reddy wrote:
> > Would also be cool to have native ppc64 arch in CI, but I checked
> > briefly with IBM and no such integration exists with github as far as
> > the contact knew.
>
> Hi Tyler,
>
> ppc64 CI is available through OSUOSL. Earlier this year I requested a
> ppc64be test server through them, for numpy use, see this email and the
> links therein:
>
> https://mail.python.org/pipermail/numpy-discussion/2018-January/077570.html
>
> At the time I didn't sign up for CI because my focus was the test
> server, but I think it is still very much an option to ask for CI if we
> want. I don't yet have the time to do it myself, but I think anyone
> interested could do it pretty easily.
>
> Incidentally, the test server is still available to any numpy devs who
> need it, just ping me for access.
>
> Cheers,
> Allan
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Re: [Numpy-discussion] CI Testing

[Tyler Reddy]

Could initially try just adding some "bonus" jobs (that are useful / nice,
but we can't afford to add to current CI load) as a trial maybe, and if
the free version or a deal / offer on better services proves more expedient
than what we currently have then progressively migrate if / as appropriate.

Would also be cool to have native ppc64 arch in CI, but I checked briefly
with IBM and no such integration exists with github as far as the contact
knew.

On Wed, 12 Sep 2018 at 17:03, Charles R Harris 
wrote:

> Hi All,
>
> We might want to take a look at testing/building on AZURE
> .
> Probably worth exploring, although it is hard to find all information.
> IIRC, we got an offer from Microsoft along these lines a couple of years
> ago when we were looking to support MSVC.
>
> Chuck
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[Numpy-discussion] ARMv8 / shippable addition to CI

[Tyler Reddy]

Hi,

Stefan & Matti wanted me to check on the mailing list about about adding
ARMv8 (free / shippable service) to NumPy CI on github -- is anyone opposed
to that?

Only obvious drawback seems to be that the service sometimes seems a little
unreliable, not that this is new to us; guess we could just turn it off if
so.

The issue with progress: https://github.com/numpy/numpy/issues/11702

All NumPy tests pass (regular not --full suite anyway) on Python 2.7 / 3.7
in 9 minutes if we cache the Cython build:
https://app.shippable.com/github/tylerjereddy/numpy/runs/56/summary/console

If we move forward: I've been testing on a personal branch so that I didn't
have to act on behalf of NumPy officially--does someone on the steering
council want to set up an official NumPy shippable account & ask them for
access (I think I had to push a button / send an email for ARMv8
specifically).

I can open a PR to NumPy proper if this is generally +1 now.

Tyler
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[Numpy-discussion] Possible Deprecation of np.ediff1d

[Tyler Reddy]

Chuck suggested (
https://github.com/numpy/numpy/pull/11805#issuecomment-416069436 ) that we
may want to consider deprecating np.ediff1d, which is perhaps not much more
useful than np.diff, apart from having some arguably strange prepend /
append behavior added in.

Related discussion on SO:
https://stackoverflow.com/questions/39014324/difference-between-numpy-ediff1d-and-diff

Thoughts?

Best wishes,
Tyler
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Re: [Numpy-discussion] pytest, fixture and parametrize

[Tyler Reddy]

+1 for pytest parametrization and some of the more straight forward context
managers like pytest.raises and so on

+0.5 for the fancy fixture stuff in pytest (have to concede that this stuff
can be really hard to reason about sometimes,
especially with custom scoping decorators, but if it helps to mock
something like recently-discovered network dependency
for some unit tests it may be better than adding a new dependency or
reimplementing effectively the same thing)

On Wed, 8 Aug 2018 at 09:09, Chris Barker - NOAA Federal <
chris.bar...@noaa.gov> wrote:

> BTW:
>
> with pytest.raises(AnException):
> 
>
> Is another nice feature.
>
> -CHB
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