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Added numpy

This commit is contained in:
Netkas 2021-01-12 22:41:40 -05:00
parent 171e72efd8
commit 43c9aa1cac
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# Python CircleCI 2.0 configuration file
#
# Check https://circleci.com/docs/2.0/language-python/ for more details
#
version: 2
jobs:
build:
docker:
# CircleCI maintains a library of pre-built images
# documented at https://circleci.com/docs/2.0/circleci-images/
- image: circleci/python:3.6.6
working_directory: ~/repo
steps:
- checkout
- run:
name: install dependencies
command: |
python3 -m venv venv
ln -s $(which python3) venv/bin/python3.6
. venv/bin/activate
pip install cython sphinx==2.3.1 matplotlib ipython
sudo apt-get update
sudo apt-get install -y graphviz texlive-fonts-recommended texlive-latex-recommended texlive-latex-extra texlive-generic-extra latexmk texlive-xetex
- run:
name: build numpy
command: |
. venv/bin/activate
pip install --upgrade pip 'setuptools<49.2.0'
pip install cython
pip install .
pip install scipy
pip install pandas
- run:
name: create release notes
command: |
. venv/bin/activate
pip install git+https://github.com/hawkowl/towncrier.git@master
VERSION=$(python -c "import setup; print(setup.VERSION)")
towncrier --version $VERSION --yes
./tools/ci/test_all_newsfragments_used.py
- run:
name: run doctests on documentation
command: |
. venv/bin/activate
(cd doc ; git submodule update --init)
python tools/refguide_check.py --rst
- run:
name: build devdocs
command: |
. venv/bin/activate
cd doc
SPHINXOPTS=-q make -e html
- run:
name: build neps
command: |
. venv/bin/activate
cd doc/neps
SPHINXOPTS=-q make -e html
- store_artifacts:
path: doc/build/html/
# - store_artifacts:
# path: doc/neps/_build/html/
# destination: neps
- add_ssh_keys:
fingerprints:
- "9f:8c:e5:3f:53:40:0b:ee:c9:c3:0f:fd:0f:3c:cc:55"
- run:
name: deploy devdocs
command: |
if [ "${CIRCLE_BRANCH}" == "master" ]; then
touch doc/build/html/.nojekyll
./tools/ci/push_docs_to_repo.py doc/build/html \
git@github.com:numpy/devdocs.git \
--committer "numpy-circleci-bot" \
--email "numpy-circleci-bot@nomail" \
--message "Docs build of $CIRCLE_SHA1" \
--force
else
echo "Not on the master branch; skipping deployment"
fi
- add_ssh_keys:
fingerprints:
- "11:fb:19:69:80:3a:6d:37:9c:d1:ac:20:17:cd:c8:17"
- run:
name: select SSH key for neps repo
command: |
cat <<\EOF > ~/.ssh/config
Host github.com
IdentitiesOnly yes
IdentityFile /home/circleci/.ssh/id_rsa_11fb1969803a6d379cd1ac2017cdc817
EOF
- run:
name: deploy neps
command: |
if [ "${CIRCLE_BRANCH}" == "master" ]; then
touch doc/neps/_build/html/.nojekyll
./tools/ci/push_docs_to_repo.py doc/neps/_build/html \
git@github.com:numpy/neps.git \
--committer "numpy-circleci-bot" \
--email "numpy-circleci-bot@nomail" \
--message "Docs build of $CIRCLE_SHA1" \
--force
else
echo "Not on the master branch; skipping deployment"
fi

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codecov:
notify:
require_ci_to_pass: no
after_n_builds: 1
coverage:
status:
project:
default:
# Require 1% coverage, i.e., always succeed
target: 1
patch: false
changes: false
comment: off

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[run]
branch = True
include = */numpy/*
disable_warnings = include-ignored

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--langmaps=c:+.src

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version: 1
update_configs:
- package_manager: "python"
directory: "/"
update_schedule: "weekly"
commit_message:
prefix: "MAINT"
default_labels:
- "03 - Maintenance"

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# Numerical data files
numpy/lib/tests/data/*.npy binary
# Release notes, reduce number of conflicts.
doc/release/*.rst merge=union

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NumPy has a Code of Conduct, please see: https://www.numpy.org/devdocs/dev/conduct/code_of_conduct.html

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# Contributing to numpy
## Reporting issues
When reporting issues please include as much detail as possible about your
operating system, numpy version and python version. Whenever possible, please
also include a brief, self-contained code example that demonstrates the problem.
If you are reporting a segfault please include a GDB traceback, which you can
generate by following
[these instructions.](https://github.com/numpy/numpy/blob/master/doc/source/dev/development_environment.rst#debugging)
## Contributing code
Thanks for your interest in contributing code to numpy!
+ If this is your first time contributing to a project on GitHub, please read
through our
[guide to contributing to numpy](https://numpy.org/devdocs/dev/index.html)
+ If you have contributed to other projects on GitHub you can go straight to our
[development workflow](https://numpy.org/devdocs/dev/development_workflow.html)
Either way, please be sure to follow our
[convention for commit messages](https://numpy.org/devdocs/dev/development_workflow.html#writing-the-commit-message).
If you are writing new C code, please follow the style described in
``doc/C_STYLE_GUIDE``.
Suggested ways to work on your development version (compile and run
the tests without interfering with system packages) are described in
``doc/source/dev/development_environment.rst``.

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github: [numfocus]
tidelift: pypi/numpy
custom: https://www.numpy.org/#support-numpy

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<!-- Please describe the issue in detail here, and fill in the fields below -->
### Reproducing code example:
<!-- A short code example that reproduces the problem/missing feature. It should be
self-contained, i.e., possible to run as-is via 'python myproblem.py' -->
```python
import numpy as np
<< your code here >>
```
<!-- Remove these sections for a feature request -->
### Error message:
<!-- If you are reporting a segfault please include a GDB traceback, which you
can generate by following
https://github.com/numpy/numpy/blob/master/doc/source/dev/development_environment.rst#debugging -->
<!-- Full error message, if any (starting from line Traceback: ...) -->
### Numpy/Python version information:
<!-- Output from 'import sys, numpy; print(numpy.__version__, sys.version)' -->

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<!-- Please be sure you are following the instructions in the dev guidelines
http://www.numpy.org/devdocs/dev/development_workflow.html
-->
<!-- We'd appreciate it if your commit message is properly formatted
http://www.numpy.org/devdocs/dev/development_workflow.html#writing-the-commit-message
-->

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# Editor temporary/working/backup files #
#########################################
.#*
[#]*#
*~
*$
*.bak
*.diff
.idea/
*.iml
*.ipr
*.iws
*.org
.project
pmip
*.rej
.settings/
.*.sw[nop]
.sw[nop]
*.tmp
*.vim
.vscode
tags
cscope.out
# gnu global
GPATH
GRTAGS
GSYMS
GTAGS
.cache
# Compiled source #
###################
*.a
*.com
*.class
*.dll
*.exe
*.o
*.o.d
*.py[ocd]
*.so
# Packages #
############
# it's better to unpack these files and commit the raw source
# git has its own built in compression methods
*.7z
*.bz2
*.bzip2
*.dmg
*.gz
*.iso
*.jar
*.rar
*.tar
*.tbz2
*.tgz
*.zip
# Python files #
################
# setup.py working directory
build
# sphinx build directory
_build
# setup.py dist directory
dist
doc/build
doc/cdoc/build
# Egg metadata
*.egg-info
# The shelf plugin uses this dir
./.shelf
MANIFEST
.cache
# Paver generated files #
#########################
/release
# Logs and databases #
######################
*.log
*.sql
*.sqlite
# Patches #
###########
*.patch
*.diff
# OS generated files #
######################
.DS_Store*
.VolumeIcon.icns
.fseventsd
Icon?
.gdb_history
ehthumbs.db
Thumbs.db
.directory
# pytest generated files #
##########################
/.pytest_cache
# Things specific to this project #
###################################
numpy/core/__svn_version__.py
doc/numpy.scipy.org/_build
numpy/__config__.py
numpy/core/include/numpy/__multiarray_api.h
numpy/core/include/numpy/__ufunc_api.h
numpy/core/include/numpy/_numpyconfig.h
numpy/version.py
site.cfg
setup.cfg
.tox
numpy/core/include/numpy/__multiarray_api.c
numpy/core/include/numpy/__ufunc_api.c
numpy/core/include/numpy/__umath_generated.c
numpy/core/include/numpy/config.h
numpy/core/include/numpy/multiarray_api.txt
numpy/core/include/numpy/ufunc_api.txt
numpy/core/lib/
numpy/core/src/common/npy_binsearch.h
numpy/core/src/common/npy_cpu_features.c
numpy/core/src/common/npy_partition.h
numpy/core/src/common/npy_sort.h
numpy/core/src/common/templ_common.h
numpy/core/src/multiarray/_multiarray_tests.c
numpy/core/src/multiarray/arraytypes.c
numpy/core/src/multiarray/einsum.c
numpy/core/src/multiarray/lowlevel_strided_loops.c
numpy/core/src/multiarray/multiarray_tests.c
numpy/core/src/multiarray/nditer_templ.c
numpy/core/src/multiarray/scalartypes.c
numpy/core/src/npymath/ieee754.c
numpy/core/src/npymath/npy_math_complex.c
numpy/core/src/npymath/npy_math_internal.h
numpy/core/src/npysort/binsearch.c
numpy/core/src/npysort/heapsort.c
numpy/core/src/npysort/mergesort.c
numpy/core/src/npysort/quicksort.c
numpy/core/src/npysort/radixsort.c
numpy/core/src/npysort/selection.c
numpy/core/src/npysort/timsort.c
numpy/core/src/npysort/sort.c
numpy/core/src/private/npy_binsearch.h
numpy/core/src/private/npy_partition.h
numpy/core/src/private/templ_common.h
numpy/core/src/umath/_operand_flag_tests.c
numpy/core/src/umath/_rational_tests.c
numpy/core/src/umath/_struct_ufunc_tests.c
numpy/core/src/umath/_umath_tests.c
numpy/core/src/umath/scalarmath.c
numpy/core/src/umath/funcs.inc
numpy/core/src/umath/clip.[ch]
numpy/core/src/umath/loops.[ch]
numpy/core/src/umath/matmul.[ch]
numpy/core/src/umath/operand_flag_tests.c
numpy/core/src/umath/simd.inc
numpy/core/src/umath/struct_ufunc_test.c
numpy/core/src/umath/test_rational.c
numpy/core/src/umath/umath_tests.c
numpy/distutils/__config__.py
numpy/linalg/umath_linalg.c
doc/source/**/generated/
benchmarks/results
benchmarks/html
benchmarks/env
benchmarks/numpy
# cythonized files
cythonize.dat
numpy/random/_mtrand/_mtrand.c
numpy/random/*.c
numpy/random/legacy/*.c
numpy/random/_mtrand/randint_helpers.pxi
numpy/random/bounded_integers.pyx
numpy/random/bounded_integers.pxd
tools/swig/test/Array_wrap.cxx
tools/swig/test/Farray_wrap.cxx
tools/swig/test/Farray.py
tools/swig/test/Flat_wrap.cxx
tools/swig/test/Flat.py
tools/swig/test/Fortran_wrap.cxx
tools/swig/test/Fortran.py
tools/swig/test/Matrix_wrap.cxx
tools/swig/test/Matrix.py
tools/swig/test/Tensor_wrap.cxx
tools/swig/test/Tensor.py
tools/swig/test/Vector.py
tools/swig/test/Vector_wrap.cxx
tools/swig/test/Array.py

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[submodule "doc/scipy-sphinx-theme"]
path = doc/scipy-sphinx-theme
url = https://github.com/scipy/scipy-sphinx-theme.git
[submodule "doc/sphinxext"]
path = doc/sphinxext
url = https://github.com/numpy/numpydoc.git

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path_classifiers:
library:
- tools
generated:
# The exports defined in __init__.py are defined in the Cython module
# np.random.mtrand. By excluding this file we suppress a number of
# "undefined export" alerts
- numpy/random/__init__.py
extraction:
python:
python_setup:
requirements:
- cython>=0.29
cpp:
index:
build_command:
- python3 setup.py build
after_prepare:
- pip3 install --upgrade --user cython
- export PATH="$HOME/.local/bin:$PATH"
queries:
- include: py/file-not-closed

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# Prevent git from showing duplicate names with commands like "git shortlog"
# See the manpage of git-shortlog for details.
# The syntax is:
# Name that should be used <email that should be used> Bad name <bad email>
#
# You can skip Bad name if it is the same as the one that should be used, and is unique.
#
# This file is up-to-date if the command git log --format="%aN <%aE>" | sort -u
# gives no duplicates.
Aaron Baecker <abaecker@localhost> abaecker <abaecker@localhost>
Alan Fontenot <logeaux@yahoo.com> logeaux <logeaux@yahoo.com>
Alan Fontenot <logeaux@yahoo.com> logeaux <36168460+logeaux@users.noreply.github.com>
Abdul Muneer <abdulmuneer@gmail.com> abdulmuneer <abdulmuneer@gmail.com>
Adam Ginsburg <adam.g.ginsburg@gmail.com> Adam Ginsburg <keflavich@gmail.com>
Albert Jornet Puig <albert.jornet@ic3.cat> jurnix <albert.jornet@ic3.cat>
Alex Griffing <argriffi@ncsu.edu> alex <argriffi@ncsu.edu>
Alex Griffing <argriffi@ncsu.edu> argriffing <argriffi@ncsu.edu>
Alex Griffing <argriffi@ncsu.edu> argriffing <argriffing@gmail.com>
Alex Griffing <argriffi@ncsu.edu> argriffing <argriffing@users.noreply.github.com>
Alex Thomas <alexthomas93@users.noreply.github.com> alexthomas93 <alexthomas93@users.noreply.github.com>
Alexander Belopolsky <abalkin@enlnt.com> Alexander Belopolsky <a@enlnt.com>
Alexander Belopolsky <abalkin@enlnt.com> Alexander Belopolsky <a@enlnt.com>
Alexander Belopolsky <abalkin@enlnt.com> sasha <sasha@localhost>
Alexander Jung <kontakt@ajung.name> aleju <kontakt@ajung.name>
Alexander Shadchin <alexandr.shadchin@gmail.com> Alexandr Shadchin <alexandr.shadchin@gmail.com>
Alexander Shadchin <alexandr.shadchin@gmail.com> shadchin <alexandr.shadchin@gmail.com>
Allan Haldane <allan.haldane@gmail.com> ahaldane <ealloc@gmail.com>
Alok Singhal <gandalf013@gmail.com> Alok Singhal <alok@merfinllc.com>
Alyssa Quek <alyssaquek@gmail.com> alyssaq <alyssaquek@gmail.com>
Amir Sarabadani <ladsgroup@gmail.com> amir <ladsgroup@gmail.com>
Anatoly Techtonik <techtonik@gmail.com> anatoly techtonik <techtonik@gmail.com>
Andras Deak <deak.andris@gmail.com> adeak <adeak@users.noreply.github.com>
Andrea Pattori <andrea.pattori@gmail.com> patto90 <andrea.pattori@gmail.com>
Andrea Sangalli <and-sang@outlook.com> and-sang <53617841+and-sang@users.noreply.github.com>
Andrei Kucharavy <ank@andreikucharavy.com> chiffa <ank@andreikucharavy.com>
Anne Archibald <peridot.faceted@gmail.com> aarchiba <peridot.faceted@gmail.com>
Anne Archibald <peridot.faceted@gmail.com> Anne Archibald <archibald@astron.nl>
Anže Starič <anze.staric@gmail.com> astaric <anze.staric@gmail.com>
Aron Ahmadia <aron@ahmadia.net> ahmadia <aron@ahmadia.net>
Aarthi Agurusa <agurusa@gmail.com> agurusa <agurusa@gmail.com>
Arun Persaud <apersaud@lbl.gov> Arun Persaud <arun@nubati.net>
Åsmund Hjulstad <ahju@statoil.com> Åsmund Hjulstad <asmund@hjulstad.com>
Auke Wiggers <wiggers.auke@gmail.com> auke <wiggers.auke@gmail.com>
Badhri Narayanan Krishnakumar <badhrinarayanan.k@gmail.com> badhrink <badhrinarayanan.k@gmail.com>
Behzad Nouri <behzadnouri@gmail.com> behzad nouri <behzadnouri@gmail.com>
Benjamin Root <ben.v.root@gmail.com> Ben Root <ben.v.root@gmail.com>
Benjamin Root <ben.v.root@gmail.com> weathergod <?@?>
Bernardt Duvenhage <bernardt.duvenhage@gmail.com> bduvenhage <bernardt.duvenhage@gmail.com>
Bertrand Lefebvre <bertrand.l3f@gmail.com> bertrand <bertrand.l3f@gmail.com>
Bertrand Lefebvre <bertrand.l3f@gmail.com> Bertrand <bertrand.l3f@gmail.com>
Bharat Raghunathan <bharatr@symphonyai.com> Bharat123Rox <bharatr@symphonyai.com>
Bill Spotz <wfspotz@sandia.gov> William Spotz <wfspotz@sandia.gov@localhost>
Bill Spotz <wfspotz@sandia.gov> wfspotz@sandia.gov <wfspotz@sandia.gov@localhost>
Bob Eldering <eldering@jive.eu> bobeldering <eldering@jive.eu>
Brett R Murphy <bmurphy@enthought.com> brettrmurphy <bmurphy@enthought.com>
Bryan Van de Ven <bryanv@continuum.io> Bryan Van de Ven <bryan@Laptop-3.local>
Bryan Van de Ven <bryanv@continuum.io> Bryan Van de Ven <bryan@laptop.local>
Bui Duc Minh <buiducminh287@gmail.com> Mibu287 <41239569+Mibu287@users.noreply.github.com>
Carl Kleffner <cmkleffner@gmail.com> carlkl <cmkleffner@gmail.com>
Chris Burns <chris.burns@localhost> chris.burns <chris.burns@localhost>
Chris Kerr <debdepba@dasganma.tk> Chris Kerr <cjk34@cam.ac.uk>
Christian Clauss <cclauss@bluewin.ch> cclauss <cclauss@bluewin.ch>
Christopher Hanley <chanley@gmail.com> chanley <chanley@gmail.com>
Christoph Gohlke <cgohlke@uci.edu> cgholke <?@?>
Christoph Gohlke <cgohlke@uci.edu> cgohlke <cgohlke@uci.edu>
Christoph Gohlke <cgohlke@uci.edu> Christolph Gohlke <cgohlke@uci.edu>
Chunlin Fang <fangchunlin@huawei.com> Qiyu8 <fangchunlin@huawei.com>
Chunlin Fang <fangchunlin@huawei.com> Chunlin <fangchunlin@huawei.com>
Colin Snyder <47012605+colinsnyder@users.noreply.github.com> colinsnyder <47012605+colinsnyder@users.noreply.github.com>
Daniel B Allan <daniel.b.allan@gmail.com> danielballan <daniel.b.allan@gmail.com>
Daniel da Silva <mail@danieldasilva.org> Daniel da Silva <daniel@meltingwax.net>
Daniel da Silva <mail@danieldasilva.org> Daniel da Silva <var.mail.daniel@gmail.com>
Daniel Hrisca <daniel.hrisca@gmail.com> danielhrisca <daniel.hrisca@gmail.com>
Daniel J Farrell <danieljfarrel@me.com> danieljfarrell <danieljfarrel@me.com>
Daniel Müllner <Daniel Müllner muellner@math.stanford.edu> Daniel <muellner@localhost.localdomain>
Daniel Müllner <Daniel Müllner muellner@math.stanford.edu> dmuellner <Daniel Müllner muellner@math.stanford.edu>
Daniel Rasmussen <daniel.rasmussen@appliedbrainresearch.com> drasmuss <daniel.rasmussen@appliedbrainresearch.com>
David Huard <david.huard@gmail.com> dhuard <dhuard@localhost>
David M Cooke <cookedm@localhost> cookedm <cookedm@localhost>
David Nicholson <davidjn@google.com> davidjn <dnic12345@gmail.com>
David Ochoa <ochoadavid@gmail.com> ochoadavid <ochoadavid@gmail.com>
Dawid Zych <dawid.zych@yandex.com> silenc3r <dawid.zych@yandex.com>
Dennis Zollo <dzollo@swift-nav.com> denniszollo <dzollo@swift-nav.com>
Derek Homeier <derek@astro.physik.uni-goettingen.de> Derek Homeier <dhomeie@gwdg.de>
Derek Homeier <derek@astro.physik.uni-goettingen.de> Derek Homeir <derek@astro.phsik.uni-goettingen.de>
Derek Homeier <derek@astro.physik.uni-goettingen.de> Derek Homier <derek@astro.physik.uni-goettingen.de>
Derrick Williams <myutat@gmail.com> derrick <myutat@gmail.com>
Dmitriy Shalyga <zuko3d@gmail.com> zuko3d <zuko3d@gmail.com>
Dustan Levenstein <dlevenstein@gmail.com> dustanlevenstein <43019642+dustanlevenstein@users.noreply.github.com>
Ed Schofield <edschofield@localhost> edschofield <edschofield@localhost>
Egor Zindy <ezindy@gmail.com> zindy <ezindy@gmail.com>
Endolith <endolith@gmail.com>
Erik M. Bray <erik.bray@lri.fr> E. M. Bray <erik.bray@lri.fr>
Erik M. Bray <erik.bray@lri.fr> Erik Bray <erik.m.bray@gmail.com>
Eric Fode <ericfode@gmail.com> Eric Fode <ericfode@linuxlaptop.(none)>
Eric Quintero <eric.antonio.quintero@gmail.com> e-q <eric.antonio.quintero@gmail.com>
Ernest N. Mamikonyan <ernest.mamikonyan@gmail.com> mamikony <ernest.mamikonyan@sig.com>
Etienne Guesnet <etienne.guesnet.external@atos.net> EGuesnet <51407514+EGuesnet@users.noreply.github.com>
Evgeni Burovski <evgeny.burovskiy@gmail.com> Evgeni Burovski <evgeni@burovski.me>
Evgeny Toder <evgeny.toder@jpmorgan.com> eltjpm <evgeny.toder@jpmorgan.com>
Fernando Perez <Fernando.Perez@berkeley.edu> Fernando Perez <fperez@fperez.org>
Friedrich Dunne <dunneff@tcd.ie> dunneff <dunneff@tcd.ie>
Frederic Bastien <nouiz@nouiz.org> Frederic <nouiz@nouiz.org>
Gael Varoquaux <gael.varoquaux@normalesup.org> GaelVaroquaux <gael.varoquaux@normalesup.org>
Gerrit Holl <gerrit.holl@utoronto.ca> Gerrit Holl <g.holl@reading.ac.uk>
Giuseppe Venturini <ggventurini@users.noreply.github.com> ggventurini <ggventurini@users.noreply.github.com>
Golnaz Irannejad <golnazirannejad@gmail.com> golnazir <golnazirannejad@gmail.com>
Gopal Singh Meena <gopalmeena94@gmail.com> gopalmeena <gopalmeena94@gmail.com>
Greg Knoll <gregory@bccn-berlin.de> gkBCCN <gregory@bccn-berlin.de>
Greg Yang <sorcererofdm@gmail.com> eulerreich <sorcererofdm@gmail.com>
Greg Young <gfyoung17@gmail.com> gfyoung <gfyoung17@gmail.com>
Greg Young <gfyoung17@gmail.com> gfyoung <gfyoung@mit.edu>
Guo Ci <zguoci@gmail.com> guoci <zguoci@gmail.com>
Han Genuit <hangenuit@gmail.com> 87 <hangenuit@gmail.com>
Han Genuit <hangenuit@gmail.com> hangenuit@gmail.com <hangenuit@gmail.com>
Han Genuit <hangenuit@gmail.com> Han <hangenuit@gmail.com>
Hanno Klemm <hanno.klemm@maerskoil.com> hklemm <hanno.klemm@maerskoil.com>
Hemil Desai <desai38@purdue.edu> hemildesai <desai38@purdue.edu>
Hiroyuki V. Yamazaki <hiroyuki.vincent.yamazaki@gmail.com> hvy <hiroyuki.vincent.yamazaki@gmail.com>
Gerhard Hobler <gerhard.hobler@tuwien.ac.at> hobler <gerhard.hobler@tuwien.ac.at>
Guillaume Peillex <guillaume.peillex@gmail.com> hippo91 <guillaume.peillex@gmail.com>
Irvin Probst <irvin.probst@ensta-bretagne.fr> I--P <irvin.probst@ensta-bretagne.fr>
Jaime Fernandez <jaime.frio@gmail.com> Jaime Fernandez <jaime.fernandez@hp.com>
Jaime Fernandez <jaime.frio@gmail.com> jaimefrio <jaime.frio@gmail.com>
Jaime Fernandez <jaime.frio@gmail.com> Jaime <jaime.frio@gmail.com>
James Webber <jamestwebber@gmail.com> jamestwebber <jamestwebber@gmail.com>
Jarrod Millman <millman@berkeley.edu> Jarrod Millman <jarrod.millman@gmail.com>
Jason Grout <jason-github@creativetrax.com> Jason Grout <jason.grout@drake.edu>
Jason King <pizza@netspace.net.au> jason king <pizza@netspace.net.au>
Jay Bourque <jay.bourque@continuum.io> jayvius <jay.bourque@continuum.io>
Jean Utke <jutke@allstate.com> jutke <jutke@allstate.com>
Jeffrey Yancey <jeffrey@octane5.com> Jeff <3820914+jeffyancey@users.noreply.github.com>
Jeremy Lay <jlay80@gmail.com> jeremycl01 <jlay80@gmail.com>
Jérémie du Boisberranger <jeremie.du-boisberranger@inria.fr> jeremiedbb <34657725+jeremiedbb@users.noreply.github.com>
Jerome Kelleher <jerome.kelleher@ed.ac.uk> jeromekelleher <jerome.kelleher@ed.ac.uk>
Johannes Hampp <johannes.hampp@zeu.uni-giessen.de> euronion <42553970+euronion@users.noreply.github.com>
Johannes Schönberger <hannesschoenberger@gmail.com> Johannes Schönberger <jschoenberger@demuc.de>
Johann Faouzi <johann.faouzi@gmail.com> johann.faouzi <johann.faouzi@icm-institute.org>
John Darbyshire <24256554+attack68@users.noreply.github.com> attack68 <24256554+attack68@users.noreply.github.com>
John Kirkham <kirkhamj@janelia.hhmi.org> jakirkham <jakirkham@gmail.com>
Joseph Fox-Rabinovitz <jfoxrabinovitz@gmail.com> Joseph Fox-Rabinovitz <joseph.r.fox-rabinovitz@nasa.gov>
Joseph Fox-Rabinovitz <jfoxrabinovitz@gmail.com> Joseph Fox-Rabinovitz <madphysicist@users.noreply.github.com>
Joseph Fox-Rabinovitz <jfoxrabinovitz@gmail.com> Mad Physicist <madphysicist@users.noreply.github.com>
Joseph Martinot-Lagarde <contrebasse@gmail.com> Joseph Martinot-Lagarde <joseph.martinot-lagarde@onera.fr>
Julian Taylor <juliantaylor108@gmail.com> Julian Taylor <jtaylor.debian@googlemail.com>
Julian Taylor <juliantaylor108@gmail.com> Julian Taylor <juliantaylor108@googlemail.com>
Julien Lhermitte <jrmlhermitte@gmail.com> Julien Lhermitte <lhermitte@bnl.gov>
Julien Schueller <julien.schueller@gmail.com> jschueller <julien.schueller@gmail.com>
Justus Magin <keewis@posteo.de> keewis <keewis@users.noreply.github.com>
Justus Magin <keewis@posteo.de> Keewis <keewis@posteo.de>
Kai Striega <kaistriega@gmail.com> kai <kaistriega@gmail.com>
Kai Striega <kaistriega@gmail.com> kai-striega <kaistriega@gmail.com>
Kai Striega <kaistriega@gmail.com> kai-striega <kaistriega+github@gmail.com>
Khaled Ben Abdallah Okuda <khaled.ben.okuda@gmail.com> KhaledTo <khaled.ben.okuda@gmail.com>
Kiko Correoso <kachine@protonmail.com> kikocorreoso <kikocorreoso@gmail.com>
Kiko Correoso <kachine@protonmail.com> kikocorreoso <kikocorreoso@users.noreply.github.com>
Konrad Kapp <k_kapp@yahoo.com> k_kapp@yahoo.com <k_kapp@yahoo.com>
Kriti Singh <kritisingh1.ks@gmail.com> kritisingh1 <kritisingh1.ks@gmail.com>
Kmol Yuan <pyslvs@gmail.com> Yuan <pyslvs@gmail.com>
Lars Buitinck <larsmans@gmail.com> Lars Buitinck <l.buitinck@esciencecenter.nl>
Lars Buitinck <larsmans@gmail.com> Lars Buitinck <L.J.Buitinck@uva.nl>
Lars Grüter <lagru@mailbox.org> Lars G <lagru@mailbox.org>
Luis Pedro Coelho <luis@luispedro.org> Luis Pedro Coelho <lpc@cmu.edu>
Luke Zoltan Kelley <lkelley@cfa.harvard.edu> lzkelley <lkelley@cfa.harvard.edu>
Magdalena Proszewska <magdalena.proszewska@gmail.com> mpro <magdalena.proszewska@gmail.com>
Magdalena Proszewska <magdalena.proszewska@gmail.com> mproszewska <38814059+mproszewska@users.noreply.github.com>
Manoj Kumar <manojkumarsivaraj334@gmail.com> MechCoder <manojkumarsivaraj334@gmail.com>
Marcin Podhajski <podhajskimarcin@gmail.com> m-podhajski <36967358+m-podhajski@users.noreply.github.com>
Mark DePristo <mdepristo@synapdx.com> markdepristo <mdepristo@synapdx.com>
Mark Weissman <mw9050@gmail.com> m-d-w <mw9050@gmail.com>
Mark Wiebe <mwwiebe@gmail.com> Mark <mwwiebe@gmail.com>
Mark Wiebe <mwwiebe@gmail.com> Mark Wiebe <mwiebe@continuum.io>
Mark Wiebe <mwwiebe@gmail.com> Mark Wiebe <mwiebe@enthought.com>
Mark Wiebe <mwwiebe@gmail.com> Mark Wiebe <mwiebe@georg.(none)>
Martin Goodson <martingoodson@gmail.com> martingoodson <martingoodson@gmail.com>
Martin Reinecke <martin@mpa-garching.mpg.de> mreineck <martin@mpa-garching.mpg.de>
Martin Teichmann <martin.teichmann@xfel.eu> Martin Teichmann <lkb.teichmann@gmail.com>
Matt Hancock <not.matt.hancock@gmail.com> matt <mhancock743@gmail.com>
Martino Sorbaro <martino.sorbaro@ed.ac.uk> martinosorb <martino.sorbaro@ed.ac.uk>
Mattheus Ueckermann <empeeu@yahoo.com> empeeu <empeeu@yahoo.com>
Matthew Harrigan <harrigan.matthew@gmail.com> MattHarrigan <harrigan.matthew@gmail.com>
Matti Picus <matti.picus@gmail.com> mattip <matti.picus@gmail.com>
Maximilian Konrad <maximilianlukaskonrad@hotmail.de> MLK97 <maximilianlukaskonrad@hotmail.de>
Melissa Weber Mendonça <melissawm@gmail.com> Melissa Weber Mendonca <melissawm@gmail.com>
Melissa Weber Mendonça <melissawm@gmail.com> melissawm <melissawm@gmail.com>
Michael Behrisch <oss@behrisch.de> behrisch <behrisch@users.sourceforge.net>
Michael Droettboom <mdboom@gmail.com> mdroe <mdroe@localhost>
Michael K. Tran <trankmichael@gmail.com> mtran <trankmichael@gmail.com>
Michael Martin <mmartin4242@gmail.com> mmartin <mmartin4242@gmail.com>
Michael Schnaitter <schnaitterm@knights.ucf.edu> schnaitterm <schnaitterm@users.noreply.github.com>
Muhammad Kasim <firman.kasim@gmail.com> mfkasim91 <firman.kasim@gmail.com>
Masashi Kishimoto <drehbleistift@gmail.com> kishimoto-banana <drehbleistift@gmail.com>
Nathaniel J. Smith <njs@pobox.com> njsmith <njs@pobox.com>
Naveen Arunachalam <notatroll.troll@gmail.com> naveenarun <notatroll.troll@gmail.com>
Nicolas Scheffer <nicolas.scheffer@sri.com> Nicolas Scheffer <scheffer@speech.sri.com>
Nicholas A. Del Grosso <delgrosso@bio.lmu.de> nickdg <delgrosso@bio.lmu.de>
Nick Minkyu Lee <mknicklee@protonmail.com> fivemok <9394929+fivemok@users.noreply.github.com>
Ondřej Čertík <ondrej.certik@gmail.com> Ondrej Certik <ondrej.certik@gmail.com>
Óscar Villellas Guillén <oscar.villellas@continuum.io> ovillellas <oscar.villellas@continuum.io>
Pat Miller <patmiller@localhost> patmiller <patmiller@localhost>
Paul Ivanov <pi@berkeley.edu> Paul Ivanov <paul.ivanov@local>
Paul Jacobson <hpj3@myuw.net> hpaulj <hpj3@myuw.net>
Pearu Peterson <pearu.peterson@gmail.com> Pearu Peterson <pearu@pearu-laptop.(none)>
Pete Peeradej Tanruangporn <pete.tanru@gmail.com> petetanru <pete.tanru@gmail.com>
Peter J Cock <p.j.a.cock@googlemail.com> peterjc <p.j.a.cock@googlemail.com>
Phil Elson <pelson.pub@gmail.com>
Pierre GM <pierregmcode@gmail.com> pierregm <pierregmcode@gmail.com>
Pierre GM <pierregmcode@gmail.com> pierregm <pierregm@localhost>
Piotr Gaiński <dociebieaniuszlem@gmail.com> panpiort8 <dociebieaniuszlem@gmail.com>
Prabhu Ramachandran <prabhu@localhost> prabhu <prabhu@localhost>
Przemyslaw Bartosik <sendthenote@gmail.com> przemb <sendthenote@gmail.com>
Ralf Gommers <ralf.gommers@gmail.com> Ralf Gommers <ralf.gommers@googlemail.com>
Ralf Gommers <ralf.gommers@gmail.com> rgommers <ralf.gommers@googlemail.com>
Rehas Sachdeva <aquannie@gmail.com> rehassachdeva <aquannie@gmail.com>
Ritta Narita <narittan@gmail.com> RittaNarita <narittan@gmail.com>
Riya Sharma <navneet.nmk@gmail.com> ayir <navneet.nmk@gmail.com>
Robert Kern <rkern@enthought.com> Robert Kern <robert.kern@gmail.com>
Robert LU <robberphex@gmail.com> RobberPhex <robberphex@gmail.com>
Ronan Lamy <ronan.lamy@gmail.com> Ronan Lamy <Ronan.Lamy@normalesup.org>
Russell Hewett <rhewett@mit.edu> rhewett <rhewett@mit.edu>
Ryan Blakemore <rbtnet@gmail.com> ryanblak <rbtnet@gmail.com>
Sam Preston <j.sam.preston@gmail.com> jspreston <j.sam.preston@gmail.com>
Sam Radhakrishnan <sk09idm@gmail.com> = <=>
Sam Radhakrishnan <sk09idm@gmail.com> sam09 <sk09idm@gmail.com>
Sanchez Gonzalez Alvaro <as12513@imperial.ac.uk> alvarosg <as12513@imperial.ac.uk>
Saullo Giovani <saullogiovani@gmail.com> saullogiovani <saullogiovani@gmail.com>
Saurabh Mehta <e.samehta@gmail.com>
Sebastian Berg <sebastian@sipsolutions.net> seberg <sebastian@sipsolutions.net>
Shekhar Prasad Rajak <shekharrajak@live.com> shekharrajak <shekharrajak@live.com>
Shota Kawabuchi <shota.kawabuchi+GitHub@gmail.com> skwbc <shota.kawabuchi+GitHub@gmail.com>
Siavash Eliasi <siavashserver@gmail.com> siavashserver <siavashserver@gmail.com>
Simon Gasse <simon.gasse@gmail.com> sgasse <sgasse@users.noreply.github.com>
Søren Rasmussen <soren.rasmussen@alexandra.dk> sorenrasmussenai <47032123+sorenrasmussenai@users.noreply.github.com>
Stefan Behnel <stefan_ml@behnel.de> scoder <stefan_ml@behnel.de>
Stefan van der Walt <stefanv@berkeley.edu> Stefan van der Walt <sjvdwalt@gmail.com>
Stefan van der Walt <stefanv@berkeley.edu> Stefan van der Walt <stefan@sun.ac.za>
Stephan Hoyer <shoyer@gmail.com> Stephan Hoyer <shoyer@climate.com>
Steven J Kern <kern.steven0@gmail.com>
SuryaChand P <psschand@gmail.com> Surya P <psschand@gmail.com>
SuryaChand P <psschand@gmail.com> psschand <psschand@gmail.com>
Thomas A Caswell <tcaswell@gmail.com> Thomas A Caswell <tcaswell@bnl.gov>
Tim Cera <tim@cerazone.net> tim cera <tcera@sjrwmd.com>
Tim Teichmann <t.teichmann@dashdos.com> tteichmann <t.teichmann@dashdos.com>
Tim Teichmann <t.teichmann@dashdos.com> tteichmann <44259103+tteichmann@users.noreply.github.com>
Tom Boyd <pezcore@users.noreply.github.com> pezcore <pezcore@users.noreply.github.com>
Tom Poole <t.b.poole@gmail.com> tpoole <t.b.poole@gmail.com>
Tony LaTorre <tlatorre@uchicago.edu> tlatorre <tlatorre@uchicago.edu>
Travis Oliphant <travis@continuum.io> Travis E. Oliphant <teoliphant@gmail.com>
Travis Oliphant <travis@continuum.io> Travis Oliphant <oliphant@enthought.com>
Valentin Haenel <valentin@haenel.co> Valentin Haenel <valentin.haenel@gmx.de>
Rakesh Vasudevan <rakesh.nvasudev@gmail.com> vrakesh <rakesh.nvasudev@gmail.com>
Vrinda Narayan <talk2vrinda@gmail.com> vrindaaa <48102157+vrindaaa@users.noreply.github.com>
Warren Weckesser <warren.weckesser@enthought.com> Warren Weckesser <warren.weckesser@gmail.com>
Weitang Li <liwt31@163.com> wtli@Dirac <liwt31@163.com>
Weitang Li <liwt31@163.com> wtli <liwt31@163.com>
Wendell Smith <wendellwsmith@gmail.com> Wendell Smith <wackywendell@gmail.com>
Wim Glenn <wim.glenn@melbourneit.com.au> wim glenn <wim.glenn@melbourneit.com.au>
Wojtek Ruszczewski <git@wr.waw.pl> wrwrwr <git@wr.waw.pl>
Yuji Kanagawa <yuji.kngw.80s.revive@gmail.com> kngwyu <yuji.kngw.80s.revive@gmail.com>
Yury Kirienko <yury.kirienko@gmail.com> kirienko <yury.kirienko@gmail.com>
Zac Hatfield-Dodds <zac.hatfield.dodds@gmail.com> Zac-HD <zac.hatfield.dodds@gmail.com>
Zixu Zhao <zixu.zhao.tireless@gmail.com> ZZhaoTireless <zixu.zhao.tireless@gmail.com>
Ziyan Zhou <ziyan.zhou@mujin.co.jp> Ziyan <ziyan.zhou@mujin.co.jp>
Zieji Pohz <poh.ziji@gmail.com> jpoh <poh.zijie@gmail.com>
Zieji Pohz <poh.ziji@gmail.com> zjpoh <poh.zijie@gmail.com>
Zieji Pohz <poh.ziji@gmail.com> Zijie (ZJ) Poh <8103276+zjpoh@users.noreply.github.com>
Zolisa Bleki <zolisa.bleki@gmail.com> zoj613 <44142765+zoj613@users.noreply.github.com>
Zolisa Bleki <zolisa.bleki@gmail.com> RedRuM <44142765+zoj613@users.noreply.github.com>
luzpaz <kunda@scribus.net> luz.paz <luzpaz@users.noreply.github.com>
luzpaz <kunda@scribus.net> luzpaz <luzpaz@users.noreply.github.com>
spacescientist <aspacescientist@protonmail.com> spacescientist <spacescientist@pm.me>

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# After changing this file, check it on:
# http://lint.travis-ci.org/
language: python
group: travis_latest
os: linux
dist: bionic
# Travis whitelists the installable packages, additions can be requested
# https://github.com/travis-ci/apt-package-whitelist
addons:
apt:
packages: &common_packages
- gfortran
- libgfortran5
- libgfortran3
- libatlas-base-dev
# Speedup builds, particularly when USE_CHROOT=1
- eatmydata
cache:
directories:
- $HOME/.cache/pip
stages:
# Do the style check and a single test job, don't proceed if it fails
- name: Initial tests
# Do the rest of the tests
- name: Comprehensive tests
env:
global:
- WHEELHOUSE_UPLOADER_USERNAME=travis.numpy
# The following is generated with the command:
# travis encrypt -r numpy/numpy WHEELHOUSE_UPLOADER_SECRET=tH3AP1KeY
- secure: "IEicLPrP2uW+jW51GRwkONQpdPqMVtQL5bdroqR/U8r9Tr\
XrbCVRhp4AP8JYZT0ptoBpmZWWGjmKBndB68QlMiUjQPow\
iFWt9Ka92CaqYdU7nqfWp9VImSndPmssjmCXJ1v1IjZPAM\
ahp7Qnm0rWRmA0z9SomuRUQOJQ6s684vU="
jobs:
include:
# Do all python versions without environment variables set
- stage: Initial tests
python: 3.8
- stage: Comprehensive tests
python: 3.6
- python: 3.7
- python: 3.9
- python: 3.6
env: USE_DEBUG=1
addons:
apt:
packages:
- *common_packages
- cython3-dbg
- python3-dbg
- python3-dev
- python3-setuptools
- python: 3.7
env: USE_WHEEL=1 RUN_FULL_TESTS=1 RUN_COVERAGE=1 INSTALL_PICKLE5=1
- python: 3.7
env: USE_SDIST=1
- python: 3.7
env:
- PYTHONOPTIMIZE=2
- BLAS=None
- LAPACK=None
- ATLAS=None
- NPY_BLAS_ORDER=mkl,blis,openblas,atlas,accelerate,blas
- NPY_LAPACK_ORDER=MKL,OPENBLAS,ATLAS,ACCELERATE,LAPACK
- USE_ASV=1
- python: 3.7
env:
- NPY_RELAXED_STRIDES_CHECKING=0
# use custom symbol-suffixed openblas build, not system ATLAS
- DOWNLOAD_OPENBLAS=1
- CHECK_BLAS=1
- NPY_USE_BLAS_ILP64=1
addons:
apt:
packages:
- gfortran
- eatmydata
- libgfortran5
- libgfortran3
- python: 3.7
env: USE_WHEEL=1 NPY_RELAXED_STRIDES_DEBUG=1
- python: 3.7
env: NUMPY_EXPERIMENTAL_ARRAY_FUNCTION=0
- python: 3.7
env:
- BLAS=None
- LAPACK=None
- ATLAS=None
- python: 3.7
os: linux
arch: ppc64le
env:
# use OpenBLAS build, not system ATLAS
- DOWNLOAD_OPENBLAS=1
- ATLAS=None
- python: 3.7
os: linux
arch: s390x
env:
# use OpenBLAS build, not system ATLAS
- DOWNLOAD_OPENBLAS=1
- NPY_USE_BLAS_ILP64=1
- ATLAS=None
- python: 3.7
os: linux
arch: arm64
env:
# use OpenBLAS build, not system ATLAS
- DOWNLOAD_OPENBLAS=1
- ATLAS=None
before_install:
- ./tools/travis-before-install.sh
script:
- ./tools/travis-test.sh
after_success:
- ./tools/travis-upload-wheel.sh

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Building and installing NumPy
+++++++++++++++++++++++++++++
**IMPORTANT**: the below notes are about building NumPy, which for most users
is *not* the recommended way to install NumPy. Instead, use either a complete
scientific Python distribution (recommended) or a binary installer - see
https://scipy.org/install.html.
.. Contents::
Prerequisites
=============
Building NumPy requires the following installed software:
1) Python__ 3.6.x or newer.
Please note that the Python development headers also need to be installed,
e.g., on Debian/Ubuntu one needs to install both `python3` and
`python3-dev`. On Windows and macOS this is normally not an issue.
2) Cython >= 0.29.21
3) pytest__ (optional) 1.15 or later
This is required for testing NumPy, but not for using it.
4) Hypothesis__ (optional) 5.3.0 or later
This is required for testing NumPy, but not for using it.
Python__ http://www.python.org
pytest__ http://pytest.readthedocs.io
Hypothesis__ https://hypothesis.readthedocs.io/en/latest/
.. note::
If you want to build NumPy in order to work on NumPy itself, use
``runtests.py``. For more details, see
https://docs.scipy.org/doc/numpy/dev/development_environment.html
.. note::
More extensive information on building NumPy (and SciPy) is maintained at
https://scipy.github.io/devdocs/building/
Basic Installation
==================
To install NumPy, run::
python setup.py build -j 4 install --prefix $HOME/.local
This will compile numpy on 4 CPUs and install it into the specified prefix.
To perform an inplace build that can be run from the source folder run::
python setup.py build_ext --inplace -j 4
See `Requirements for Installing Packages <https://packaging.python.org/tutorials/installing-packages/>`_
for more details.
The number of build jobs can also be specified via the environment variable
NPY_NUM_BUILD_JOBS.
Choosing compilers
==================
NumPy needs a C compiler, and for development versions also Cython. A Fortran
compiler isn't needed to build NumPy itself; the ``numpy.f2py`` tests will be
skipped when running the test suite if no Fortran compiler is available. For
building Scipy a Fortran compiler is needed though, so we include some details
on Fortran compilers in the rest of this section.
On OS X and Linux, all common compilers will work.
For Fortran, ``gfortran`` works, ``g77`` does not. In case ``g77`` is
installed then ``g77`` will be detected and used first. To explicitly select
``gfortran`` in that case, do::
python setup.py build --fcompiler=gnu95
Windows
-------
On Windows, building from source can be difficult (in particular if you need to
build SciPy as well, because that requires a Fortran compiler). Currently, the
most robust option is to use MSVC (for NumPy only). If you also need SciPy,
you can either use MSVC + Intel Fortran or the Intel compiler suite.
Intel itself maintains a good `application note
<https://software.intel.com/en-us/articles/numpyscipy-with-intel-mkl>`_
on this.
If you want to use a free compiler toolchain, our current recommendation is to
use Docker or Windows subsystem for Linux (WSL). See
https://scipy.github.io/devdocs/dev/contributor/contributor_toc.html#development-environment
for more details.
Building with optimized BLAS support
====================================
Configuring which BLAS/LAPACK is used if you have multiple libraries installed,
or you have only one installed but in a non-standard location, is done via a
``site.cfg`` file. See the ``site.cfg.example`` shipped with NumPy for more
details.
Windows
-------
The Intel compilers work with Intel MKL, see the application note linked above.
For an overview of the state of BLAS/LAPACK libraries on Windows, see
`here <https://mingwpy.github.io/blas_lapack.html>`_.
macOS
-----
You will need to install a BLAS/LAPACK library. We recommend using OpenBLAS or
Intel MKL. Apple's Accelerate also still works, however it has bugs and we are
likely to drop support for it in the near future.
Ubuntu/Debian
-------------
For best performance, a development package providing BLAS and CBLAS should be
installed. Some of the options available are:
- ``libblas-dev``: reference BLAS (not very optimized)
- ``libatlas-base-dev``: generic tuned ATLAS, it is recommended to tune it to
the available hardware, see /usr/share/doc/libatlas3-base/README.Debian for
instructions
- ``libopenblas-base``: fast and runtime detected so no tuning required but a
very recent version is needed (>=0.2.15 is recommended). Older versions of
OpenBLAS suffered from correctness issues on some CPUs.
The package linked to when numpy is loaded can be chosen after installation via
the alternatives mechanism::
update-alternatives --config libblas.so.3
update-alternatives --config liblapack.so.3
Or by preloading a specific BLAS library with::
LD_PRELOAD=/usr/lib/atlas-base/atlas/libblas.so.3 python ...
Build issues
============
If you run into build issues and need help, the NumPy
`mailing list <https://scipy.org/scipylib/mailing-lists.html>`_ is the best
place to ask. If the issue is clearly a bug in NumPy, please file an issue (or
even better, a pull request) at https://github.com/numpy/numpy.

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Copyright (c) 2005-2020, NumPy Developers.
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are
met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above
copyright notice, this list of conditions and the following
disclaimer in the documentation and/or other materials provided
with the distribution.
* Neither the name of the NumPy Developers nor the names of any
contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

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The NumPy repository and source distributions bundle several libraries that are
compatibly licensed. We list these here.
Name: Numpydoc
Files: doc/sphinxext/numpydoc/*
License: BSD-2-Clause
For details, see doc/sphinxext/LICENSE.txt
Name: scipy-sphinx-theme
Files: doc/scipy-sphinx-theme/*
License: BSD-3-Clause AND PSF-2.0 AND Apache-2.0
For details, see doc/scipy-sphinx-theme/LICENSE.txt
Name: lapack-lite
Files: numpy/linalg/lapack_lite/*
License: BSD-3-Clause
For details, see numpy/linalg/lapack_lite/LICENSE.txt
Name: tempita
Files: tools/npy_tempita/*
License: MIT
For details, see tools/npy_tempita/license.txt
Name: dragon4
Files: numpy/core/src/multiarray/dragon4.c
License: MIT
For license text, see numpy/core/src/multiarray/dragon4.c

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#
# Use .add_data_files and .add_data_dir methods in a appropriate
# setup.py files to include non-python files such as documentation,
# data, etc files to distribution (*for installation*).
# Avoid using MANIFEST.in for that.
#
include MANIFEST.in
include pyproject.toml
include pytest.ini
include *.txt
include README.md
include site.cfg.example
include runtests.py
include tox.ini
include .coveragerc
include test_requirements.txt
recursive-include numpy/random *.pyx *.pxd *.pyx.in *.pxd.in
include numpy/random/include/*
include numpy/*.pxd
# Add build support that should go in sdist, but not go in bdist/be installed
# Note that sub-directories that don't have __init__ are apparently not
# included by 'recursive-include', so list those separately
recursive-include numpy *
recursive-include numpy/_build_utils *
recursive-include numpy/linalg/lapack_lite *
recursive-include tools *
# Add sdist files whose use depends on local configuration.
include numpy/core/src/common/cblasfuncs.c
include numpy/core/src/common/python_xerbla.c
# Adding build related files not found by distutils
recursive-include numpy/core/code_generators *.py *.txt
recursive-include numpy/core *.in *.h
# Add documentation and benchmarks: we don't use add_data_dir since we do not
# want to include this at installation, only for sdist-generated tarballs
# Docs:
recursive-include doc *
prune doc/build
prune doc/source/generated
# Benchmarks:
recursive-include benchmarks *
prune benchmarks/env
prune benchmarks/results
prune benchmarks/html
prune benchmarks/numpy
# Exclude generated files
prune */__pycache__
global-exclude *.pyc *.pyo *.pyd *.swp *.bak *~
# Exclude license file that we append to the main license when running
# `python setup.py sdist`
exclude LICENSES_bundled.txt

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# <img alt="NumPy" src="https://cdn.rawgit.com/numpy/numpy/master/branding/icons/numpylogo.svg" height="60">
[![Travis](https://img.shields.io/travis/numpy/numpy/master.svg?label=Travis%20CI)](
https://travis-ci.org/numpy/numpy)
[![Azure](https://dev.azure.com/numpy/numpy/_apis/build/status/azure-pipeline%20numpy.numpy)](
https://dev.azure.com/numpy/numpy/_build/latest?definitionId=5)
[![codecov](https://codecov.io/gh/numpy/numpy/branch/master/graph/badge.svg)](
https://codecov.io/gh/numpy/numpy)
NumPy is the fundamental package needed for scientific computing with Python.
- **Website:** https://www.numpy.org
- **Documentation:** https://numpy.org/doc
- **Mailing list:** https://mail.python.org/mailman/listinfo/numpy-discussion
- **Source code:** https://github.com/numpy/numpy
- **Contributing:** https://www.numpy.org/devdocs/dev/index.html
- **Bug reports:** https://github.com/numpy/numpy/issues
- **Report a security vulnerability:** https://tidelift.com/docs/security
It provides:
- a powerful N-dimensional array object
- sophisticated (broadcasting) functions
- tools for integrating C/C++ and Fortran code
- useful linear algebra, Fourier transform, and random number capabilities
Testing:
- NumPy versions &ge; 1.15 require `pytest`
- NumPy versions &lt; 1.15 require `nose`
Tests can then be run after installation with:
python -c 'import numpy; numpy.test()'
Call for Contributions
----------------------
NumPy appreciates help from a wide range of different backgrounds.
Work such as high level documentation or website improvements are valuable
and we would like to grow our team with people filling these roles.
Small improvements or fixes are always appreciated and issues labeled as easy
may be a good starting point.
If you are considering larger contributions outside the traditional coding work,
please contact us through the mailing list.
[![Powered by NumFOCUS](https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)](https://numfocus.org)

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Travis Oliphant for the NumPy core, the NumPy guide, various
bug-fixes and code contributions.
Paul Dubois, who implemented the original Masked Arrays.
Pearu Peterson for f2py, numpy.distutils and help with code
organization.
Robert Kern for mtrand, bug fixes, help with distutils, code
organization, strided tricks and much more.
Eric Jones for planning and code contributions.
Fernando Perez for code snippets, ideas, bugfixes, and testing.
Ed Schofield for matrix.py patches, bugfixes, testing, and docstrings.
Robert Cimrman for array set operations and numpy.distutils help.
John Hunter for code snippets from matplotlib.
Chris Hanley for help with records.py, testing, and bug fixes.
Travis Vaught for administration, community coordination and
marketing.
Joe Cooper, Jeff Strunk for administration.
Eric Firing for bugfixes.
Arnd Baecker for 64-bit testing.
David Cooke for many code improvements including the auto-generated C-API,
and optimizations.
Andrew Straw for help with the web-page, documentation, packaging and
testing.
Alexander Belopolsky (Sasha) for Masked array bug-fixes and tests,
rank-0 array improvements, scalar math help and other code additions.
Francesc Altet for unicode, work on nested record arrays, and bug-fixes.
Tim Hochberg for getting the build working on MSVC, optimization
improvements, and code review.
Charles (Chuck) Harris for the sorting code originally written for
Numarray and for improvements to polyfit, many bug fixes, delving
into the C code, release management, and documentation.
David Huard for histogram improvements including 2-D and d-D code and
other bug-fixes.
Stefan van der Walt for numerous bug-fixes, testing and documentation.
Albert Strasheim for documentation, bug-fixes, regression tests and
Valgrind expertise.
David Cournapeau for build support, doc-and-bug fixes, and code
contributions including fast_clipping.
Jarrod Millman for release management, community coordination, and code
clean up.
Chris Burns for work on memory mapped arrays and bug-fixes.
Pauli Virtanen for documentation, bug-fixes, lookfor and the
documentation editor.
A.M. Archibald for no-copy-reshape code, strided array tricks,
documentation and bug-fixes.
Pierre Gerard-Marchant for rewriting masked array functionality.
Roberto de Almeida for the buffered array iterator.
Alan McIntyre for updating the NumPy test framework to use nose, improve
the test coverage, and enhancing the test system documentation.
Joe Harrington for administering the 2008 Documentation Sprint.
Mark Wiebe for the new NumPy iterator, the float16 data type, improved
low-level data type operations, and other NumPy core improvements.
NumPy is based on the Numeric (Jim Hugunin, Paul Dubois, Konrad
Hinsen, and David Ascher) and NumArray (Perry Greenfield, J Todd
Miller, Rick White and Paul Barrett) projects. We thank them for
paving the way ahead.
Institutions
------------
Enthought for providing resources and finances for development of NumPy.
UC Berkeley for providing travel money and hosting numerous sprints.
The University of Central Florida for funding the 2008 Documentation Marathon.
The University of Stellenbosch for hosting the buildbot.

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trigger:
# start a new build for every push
batch: False
branches:
include:
- master
- maintenance/*
pr:
branches:
include:
- '*' # must quote since "*" is a YAML reserved character; we want a string
stages:
- stage: InitialTests
jobs:
- job: WindowsFast
pool:
vmImage: 'VS2017-Win2016'
strategy:
matrix:
Python36-64bit-fast:
PYTHON_VERSION: '3.6'
PYTHON_ARCH: 'x64'
TEST_MODE: fast
BITS: 64
steps:
- template: azure-steps-windows.yml
- stage: ComprehensiveTests
jobs:
- job: Linux_Python_38_32bit_full_with_asserts
pool:
vmImage: 'ubuntu-18.04'
steps:
- script: |
docker pull quay.io/pypa/manylinux2010_i686
docker run -v $(pwd):/numpy -e CFLAGS="-msse2 -std=c99 -UNDEBUG" \
-e F77=gfortran-5 -e F90=gfortran-5 quay.io/pypa/manylinux2010_i686 \
/bin/bash -xc "cd numpy && \
/opt/python/cp38-cp38/bin/python -mvenv venv &&\
source venv/bin/activate && \
target=\$(python3 tools/openblas_support.py) && \
cp -r \$target/lib/* /usr/lib && \
cp \$target/include/* /usr/include && \
python3 -m pip install -r test_requirements.txt && \
echo CFLAGS \$CFLAGS && \
python3 -m pip install -v . && \
python3 runtests.py -n --debug-info --mode=full -- -rsx --junitxml=junit/test-results.xml && \
python3 tools/openblas_support.py --check_version"
displayName: 'Run 32-bit manylinux2010 Docker Build / Tests'
- task: PublishTestResults@2
condition: succeededOrFailed()
inputs:
testResultsFiles: '**/test-*.xml'
failTaskOnFailedTests: true
testRunTitle: 'Publish test results for Python 3.8-32 bit full Linux'
- job: macOS
pool:
# NOTE: at time of writing, there is a danger
# that using an invalid vmIMage string for macOS
# image silently redirects to a Windows build on Azure;
# for now, use the only image name officially present in
# the docs even though i.e., numba uses another in their
# azure config for mac os -- Microsoft has indicated
# they will patch this issue
vmImage: macOS-10.14
strategy:
maxParallel: 3
matrix:
Python36:
PYTHON_VERSION: '3.6'
USE_OPENBLAS: '1'
Python39:
PYTHON_VERSION: '3.9'
USE_OPENBLAS: '1'
Python36-ILP64:
PYTHON_VERSION: '3.6'
NPY_USE_BLAS_ILP64: '1'
USE_OPENBLAS: '1'
USE_XCODE_10: '1'
Accelerate:
PYTHON_VERSION: '3.6'
USE_OPENBLAS: '0'
steps:
# the @0 refers to the (major) version of the *task* on Microsoft's
# end, not the order in the build matrix nor anything to do
# with version of Python selected
- task: UsePythonVersion@0
inputs:
versionSpec: $(PYTHON_VERSION)
addToPath: true
architecture: 'x64'
- script: |
set -xe
[ -n "$USE_XCODE_10" ] && /bin/bash -c "sudo xcode-select -s /Applications/Xcode_10.app/Contents/Developer"
clang --version
displayName: 'report clang version'
# NOTE: might be better if we could avoid installing
# two C compilers, but with homebrew looks like we're
# now stuck getting the full gcc toolchain instead of
# just pulling in gfortran
- script: |
set -xe
# same version of gfortran as the open-libs and numpy-wheel builds
curl -L https://github.com/MacPython/gfortran-install/raw/master/archives/gfortran-4.9.0-Mavericks.dmg -o gfortran.dmg
GFORTRAN_SHA256=$(shasum -a 256 gfortran.dmg)
KNOWN_SHA256="d2d5ca5ba8332d63bbe23a07201c4a0a5d7e09ee56f0298a96775f928c3c4b30 gfortran.dmg"
if [ "$GFORTRAN_SHA256" != "$KNOWN_SHA256" ]; then
echo sha256 mismatch
exit 1
fi
hdiutil attach -mountpoint /Volumes/gfortran gfortran.dmg
sudo installer -pkg /Volumes/gfortran/gfortran.pkg -target /
otool -L /usr/local/gfortran/lib/libgfortran.3.dylib
# Manually symlink gfortran-4.9 to plain gfortran for f2py.
# No longer needed after Feb 13 2020 as gfortran is already present
# and the attempted link errors. Keep this for future reference.
# ln -s /usr/local/bin/gfortran-4.9 /usr/local/bin/gfortran
displayName: 'make libgfortran available on mac os for openblas'
# use the pre-built openblas binary that most closely
# matches our MacOS wheel builds -- currently based
# primarily on file size / name details
- script: |
set -xe
target=$(python tools/openblas_support.py)
ls -lR $target
# manually link to appropriate system paths
cp $target/lib/lib* /usr/local/lib/
cp $target/include/* /usr/local/include/
otool -L /usr/local/lib/libopenblas*
displayName: 'install pre-built openblas'
condition: eq(variables['USE_OPENBLAS'], '1')
- script: python -m pip install --upgrade pip 'setuptools<49.2.0' wheel
displayName: 'Install tools'
- script: |
python -m pip install -r test_requirements.txt
python -m pip install vulture docutils sphinx==2.2.0 numpydoc
displayName: 'Install dependencies; some are optional to avoid test skips'
- script: /bin/bash -c "! vulture . --min-confidence 100 --exclude doc/,numpy/distutils/ | grep 'unreachable'"
displayName: 'Check for unreachable code paths in Python modules'
# prefer usage of clang over gcc proper
# to match likely scenario on many user mac machines
- script: python setup.py build -j 4 build_src --verbose-cfg install
displayName: 'Build NumPy'
env:
BLAS: None
LAPACK: None
ATLAS: None
ACCELERATE: None
CC: /usr/bin/clang
condition: eq(variables['USE_OPENBLAS'], '1')
- script: python setup.py build -j 4 build_ext --inplace install
displayName: 'Build NumPy without OpenBLAS'
env:
BLAS: None
LAPACK: None
ATLAS: None
CC: /usr/bin/clang
condition: eq(variables['USE_OPENBLAS'], '0')
# wait until after dev build of NumPy to pip
# install matplotlib to avoid pip install of older numpy
- script: python -m pip install matplotlib
displayName: 'Install matplotlib before refguide run'
- script: python runtests.py -g --refguide-check
displayName: 'Run Refuide Check'
condition: eq(variables['USE_OPENBLAS'], '1')
- script: python runtests.py -n --mode=full -- -rsx --junitxml=junit/test-results.xml
displayName: 'Run Full NumPy Test Suite'
condition: eq(variables['USE_OPENBLAS'], '1')
- bash: python tools/openblas_support.py --check_version
displayName: 'Verify OpenBLAS version'
condition: eq(variables['USE_OPENBLAS'], '1')
# import doesn't work when in numpy src directory , so do a pip dev install of build lib to test
- script: |
#!/bin/bash -v
set +e
python -c "import numpy as np" > test_output.log 2>&1
check_output_code=$?
cat test_output.log
grep "buggy Accelerate backend" test_output.log
check_message=$?
if [ $check_output_code == 1 ] && [ $check_message == 0 ]; then exit 0; else exit 1;fi
displayName: "Check if numpy import fails with accelerate"
condition: eq(variables['USE_OPENBLAS'], '0')
- task: PublishTestResults@2
condition: succeededOrFailed()
inputs:
testResultsFiles: '**/test-*.xml'
failTaskOnFailedTests: true
testRunTitle: 'Publish test results for Python 3.6 64-bit full Mac OS'
- job: Windows
pool:
vmImage: 'VS2017-Win2016'
strategy:
maxParallel: 6
matrix:
Python36-32bit-fast:
PYTHON_VERSION: '3.6'
PYTHON_ARCH: 'x86'
TEST_MODE: fast
BITS: 32
Python37-32bit-fast:
PYTHON_VERSION: '3.7'
PYTHON_ARCH: 'x86'
TEST_MODE: fast
BITS: 32
Python38-32bit-fast:
PYTHON_VERSION: '3.8'
PYTHON_ARCH: 'x86'
TEST_MODE: fast
BITS: 32
Python39-32bit-fast:
PYTHON_VERSION: '3.9'
PYTHON_ARCH: 'x86'
TEST_MODE: fast
BITS: 32
Python36-64bit-full:
PYTHON_VERSION: '3.6'
PYTHON_ARCH: 'x64'
TEST_MODE: full
BITS: 64
Python37-64bit-full:
PYTHON_VERSION: '3.7'
PYTHON_ARCH: 'x64'
TEST_MODE: full
BITS: 64
Python38-64bit-full:
PYTHON_VERSION: '3.8'
PYTHON_ARCH: 'x64'
TEST_MODE: full
BITS: 64
Python39-64bit-full:
PYTHON_VERSION: '3.9'
PYTHON_ARCH: 'x64'
TEST_MODE: full
BITS: 64
NPY_USE_BLAS_ILP64: '1'
OPENBLAS_SUFFIX: '64_'
steps:
- template: azure-steps-windows.yml
- job: Linux_PyPy3
pool:
vmIMage: 'ubuntu-18.04'
steps:
- script: source tools/pypy-test.sh
displayName: 'Run PyPy3 Build / Tests'
- task: PublishTestResults@2
condition: succeededOrFailed()
inputs:
testResultsFiles: '**/test-*.xml'
testRunTitle: 'Publish test results for PyPy3'
failTaskOnFailedTests: true
- job: Linux_gcc48
pool:
vmImage: 'ubuntu-18.04'
steps:
- script: |
if ! `gcc-4.8 2>/dev/null`; then
sudo apt install gcc-4.8
fi
displayName: 'add gcc 4.8'
- script: |
# python3 has no setuptools, so install one to get us going
python3 -m pip install --user --upgrade pip 'setuptools<49.2.0'
python3 -m pip install --user -r test_requirements.txt
CPPFLAGS='' CC=gcc-4.8 F77=gfortran-5 F90=gfortran-5 \
python3 runtests.py --debug-info --mode=full -- -rsx --junitxml=junit/test-results.xml
displayName: 'Run gcc4.8 Build / Tests'
- task: PublishTestResults@2
condition: succeededOrFailed()
inputs:
testResultsFiles: '**/test-*.xml'
failTaskOnFailedTests: true
testRunTitle: 'Publish test results for gcc 4.8'

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steps:
- task: UsePythonVersion@0
inputs:
versionSpec: $(PYTHON_VERSION)
addToPath: true
architecture: $(PYTHON_ARCH)
- script: python -m pip install --upgrade pip wheel
displayName: 'Install tools'
- script: python -m pip install -r test_requirements.txt
displayName: 'Install dependencies; some are optional to avoid test skips'
- powershell: |
$ErrorActionPreference = "Stop"
# Download and get the path to "openblas.a". We cannot copy it
# to $PYTHON_EXE's directory since that is on a different drive which
# mingw does not like. Instead copy it to a directory and set OPENBLAS,
# since OPENBLAS will be picked up by the openblas discovery
$target = $(python tools/openblas_support.py)
mkdir openblas
echo "Copying $target to openblas/openblas$env:OPENBLAS_SUFFIX.a"
cp $target openblas/openblas$env:OPENBLAS_SUFFIX.a
If ( Test-Path env:NPY_USE_BLAS_ILP64 ){
echo "##vso[task.setvariable variable=OPENBLAS64_]$pwd\openblas"
} else {
echo "##vso[task.setvariable variable=OPENBLAS]$pwd\openblas"
}
displayName: 'Download / Install OpenBLAS'
- powershell: |
choco install -y mingw --forcex86 --force --version=7.3.0
refreshenv
displayName: 'Install 32-bit mingw for 32-bit builds'
condition: eq(variables['BITS'], 32)
# NOTE: for Windows builds it seems much more tractable to use runtests.py
# vs. manual setup.py and then runtests.py for testing only
- powershell: |
If ($(BITS) -eq 32) {
$env:CFLAGS = "-m32"
$env:LDFLAGS = "-m32"
$env:PATH = "C:\\ProgramData\\chocolatey\\lib\\mingw\\tools\\install\\mingw$(BITS)\\bin;" + $env:PATH
}
python -c "from tools import openblas_support; openblas_support.make_init('numpy')"
python -m pip wheel -v -v -v --no-build-isolation --no-use-pep517 --wheel-dir=dist .
ls dist -r | Foreach-Object {
python -m pip install $_.FullName
}
displayName: 'Build NumPy'
- bash: |
pushd . && cd .. && target=$(python -c "import numpy, os; print(os.path.abspath(os.path.join(os.path.dirname(numpy.__file__), '.libs')))") && popd
python -m pip download -d destination --only-binary :all: --no-deps numpy==1.14
cd destination && unzip numpy*.whl && cp numpy/.libs/*.dll $target
ls $target
displayName: 'Add extraneous & older DLL to numpy/.libs to probe DLL handling robustness'
condition: eq(variables['PYTHON_VERSION'], '3.6')
- script: pushd . && cd .. && python -c "from ctypes import windll; windll.kernel32.SetDefaultDllDirectories(0x00000800); import numpy" && popd
displayName: 'For gh-12667; Windows DLL resolution'
condition: eq(variables['PYTHON_VERSION'], '3.6')
- script: python runtests.py -n --show-build-log --mode=$(TEST_MODE) -- -rsx --junitxml=junit/test-results.xml
displayName: 'Run NumPy Test Suite'
- task: PublishTestResults@2
condition: succeededOrFailed()
inputs:
testResultsFiles: '**/test-*.xml'
failTaskOnFailedTests: true
testRunTitle: 'Publish test results for Python $(PYTHON_VERSION) $(BITS)-bit $(TEST_MODE) Windows'

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.. -*- rst -*-
================
NumPy benchmarks
================
Benchmarking NumPy with Airspeed Velocity.
Usage
-----
Airspeed Velocity manages building and Python virtualenvs by itself,
unless told otherwise. Some of the benchmarking features in
``runtests.py`` also tell ASV to use the NumPy compiled by
``runtests.py``. To run the benchmarks, you do not need to install a
development version of NumPy to your current Python environment.
Before beginning, ensure that *airspeed velocity* is installed.
By default, `asv` ships with support for anaconda and virtualenv::
pip install asv
pip install virtualenv
After contributing new benchmarks, you should test them locally
before submitting a pull request.
To run all benchmarks, navigate to the root NumPy directory at
the command line and execute::
python runtests.py --bench
where ``--bench`` activates the benchmark suite instead of the
test suite. This builds NumPy and runs all available benchmarks
defined in ``benchmarks/``. (Note: this could take a while. Each
benchmark is run multiple times to measure the distribution in
execution times.)
To run benchmarks from a particular benchmark module, such as
``bench_core.py``, simply append the filename without the extension::
python runtests.py --bench bench_core
To run a benchmark defined in a class, such as ``Mandelbrot``
from ``bench_avx.py``::
python runtests.py --bench bench_avx.Mandelbrot
Compare change in benchmark results to another version/commit/branch::
python runtests.py --bench-compare v1.6.2 bench_core
python runtests.py --bench-compare 8bf4e9b bench_core
python runtests.py --bench-compare master bench_core
All of the commands above display the results in plain text in
the console, and the results are not saved for comparison with
future commits. For greater control, a graphical view, and to
have results saved for future comparison you can run ASV commands
(record results and generate HTML)::
cd benchmarks
asv run -n -e --python=same
asv publish
asv preview
More on how to use ``asv`` can be found in `ASV documentation`_
Command-line help is available as usual via ``asv --help`` and
``asv run --help``.
.. _ASV documentation: https://asv.readthedocs.io/
Writing benchmarks
------------------
See `ASV documentation`_ for basics on how to write benchmarks.
Some things to consider:
- The benchmark suite should be importable with any NumPy version.
- The benchmark parameters etc. should not depend on which NumPy version
is installed.
- Try to keep the runtime of the benchmark reasonable.
- Prefer ASV's ``time_`` methods for benchmarking times rather than cooking up
time measurements via ``time.clock``, even if it requires some juggling when
writing the benchmark.
- Preparing arrays etc. should generally be put in the ``setup`` method rather
than the ``time_`` methods, to avoid counting preparation time together with
the time of the benchmarked operation.
- Be mindful that large arrays created with ``np.empty`` or ``np.zeros`` might
not be allocated in physical memory until the memory is accessed. If this is
desired behaviour, make sure to comment it in your setup function. If
you are benchmarking an algorithm, it is unlikely that a user will be
executing said algorithm on a newly created empty/zero array. One can force
pagefaults to occur in the setup phase either by calling ``np.ones`` or
``arr.fill(value)`` after creating the array,

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{
// The version of the config file format. Do not change, unless
// you know what you are doing.
"version": 1,
// The name of the project being benchmarked
"project": "numpy",
// The project's homepage
"project_url": "https://www.numpy.org/",
// The URL or local path of the source code repository for the
// project being benchmarked
"repo": "..",
// List of branches to benchmark. If not provided, defaults to "master"
// (for git) or "tip" (for mercurial).
"branches": ["HEAD"],
// The DVCS being used. If not set, it will be automatically
// determined from "repo" by looking at the protocol in the URL
// (if remote), or by looking for special directories, such as
// ".git" (if local).
"dvcs": "git",
// The tool to use to create environments. May be "conda",
// "virtualenv" or other value depending on the plugins in use.
// If missing or the empty string, the tool will be automatically
// determined by looking for tools on the PATH environment
// variable.
"environment_type": "virtualenv",
// the base URL to show a commit for the project.
"show_commit_url": "https://github.com/numpy/numpy/commit/",
// The Pythons you'd like to test against. If not provided, defaults
// to the current version of Python used to run `asv`.
"pythons": ["3.7"],
// The matrix of dependencies to test. Each key is the name of a
// package (in PyPI) and the values are version numbers. An empty
// list indicates to just test against the default (latest)
// version.
"matrix": {
"Cython": [],
},
// The directory (relative to the current directory) that benchmarks are
// stored in. If not provided, defaults to "benchmarks"
"benchmark_dir": "benchmarks",
// The directory (relative to the current directory) to cache the Python
// environments in. If not provided, defaults to "env"
"env_dir": "env",
// The directory (relative to the current directory) that raw benchmark
// results are stored in. If not provided, defaults to "results".
"results_dir": "results",
// The directory (relative to the current directory) that the html tree
// should be written to. If not provided, defaults to "html".
"html_dir": "html",
// The number of characters to retain in the commit hashes.
// "hash_length": 8,
// `asv` will cache wheels of the recent builds in each
// environment, making them faster to install next time. This is
// number of builds to keep, per environment.
"build_cache_size": 8,
// The commits after which the regression search in `asv publish`
// should start looking for regressions. Dictionary whose keys are
// regexps matching to benchmark names, and values corresponding to
// the commit (exclusive) after which to start looking for
// regressions. The default is to start from the first commit
// with results. If the commit is `null`, regression detection is
// skipped for the matching benchmark.
//
// "regressions_first_commits": {
// "some_benchmark": "352cdf", // Consider regressions only after this commit
// "another_benchmark": null, // Skip regression detection altogether
// }
}

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from . import common

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from .common import Benchmark
import numpy as np
class LaplaceInplace(Benchmark):
params = ['inplace', 'normal']
param_names = ['update']
def setup(self, update):
N = 150
Niter = 1000
dx = 0.1
dy = 0.1
dx2 = (dx * dx)
dy2 = (dy * dy)
def num_update(u, dx2, dy2):
u[1:(-1), 1:(-1)] = ((((u[2:, 1:(-1)] + u[:(-2), 1:(-1)]) * dy2) +
((u[1:(-1), 2:] + u[1:(-1), :(-2)]) * dx2))
/ (2 * (dx2 + dy2)))
def num_inplace(u, dx2, dy2):
tmp = u[:(-2), 1:(-1)].copy()
np.add(tmp, u[2:, 1:(-1)], out=tmp)
np.multiply(tmp, dy2, out=tmp)
tmp2 = u[1:(-1), 2:].copy()
np.add(tmp2, u[1:(-1), :(-2)], out=tmp2)
np.multiply(tmp2, dx2, out=tmp2)
np.add(tmp, tmp2, out=tmp)
np.multiply(tmp, (1.0 / (2.0 * (dx2 + dy2))),
out=u[1:(-1), 1:(-1)])
def laplace(N, Niter=100, func=num_update, args=()):
u = np.zeros([N, N], order='C')
u[0] = 1
for i in range(Niter):
func(u, *args)
return u
func = {'inplace': num_inplace, 'normal': num_update}[update]
def run():
laplace(N, Niter, func, args=(dx2, dy2))
self.run = run
def time_it(self, update):
self.run()
class MaxesOfDots(Benchmark):
def setup(self):
np.random.seed(1)
nsubj = 5
nfeat = 100
ntime = 200
self.arrays = [np.random.normal(size=(ntime, nfeat))
for i in range(nsubj)]
def maxes_of_dots(self, arrays):
"""
A magical feature score for each feature in each dataset
:ref:`Haxby et al., Neuron (2011) <HGC+11>`.
If arrays are column-wise zscore-d before computation it
results in characterizing each column in each array with
sum of maximal correlations of that column with columns
in other arrays.
Arrays must agree only on the first dimension.
For numpy it a join benchmark of dot products and max()
on a set of arrays.
"""
feature_scores = ([0] * len(arrays))
for (i, sd) in enumerate(arrays):
for (j, sd2) in enumerate(arrays[(i + 1):]):
corr_temp = np.dot(sd.T, sd2)
feature_scores[i] += np.max(corr_temp, axis=1)
feature_scores[((j + i) + 1)] += np.max(corr_temp, axis=0)
return feature_scores
def time_it(self):
self.maxes_of_dots(self.arrays)

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from __future__ import absolute_import, division, print_function
from .common import Benchmark
import numpy as np
class ArrayCoercionSmall(Benchmark):
# More detailed benchmarks for array coercion,
# some basic benchmarks are in `bench_core.py`.
params = [[range(3), [1], 1, np.array([5], dtype=np.int64), np.int64(5)]]
param_names = ['array_like']
int64 = np.dtype(np.int64)
def time_array_invalid_kwarg(self, array_like):
try:
np.array(array_like, ndmin="not-integer")
except TypeError:
pass
def time_array(self, array_like):
np.array(array_like)
def time_array_dtype_not_kwargs(self, array_like):
np.array(array_like, self.int64)
def time_array_no_copy(self, array_like):
np.array(array_like, copy=False)
def time_array_subok(self, array_like):
np.array(array_like, subok=True)
def time_array_all_kwargs(self, array_like):
np.array(array_like, dtype=self.int64, copy=False, order="F",
subok=False, ndmin=2)
def time_asarray(self, array_like):
np.asarray(array_like)
def time_asarray_dtype(self, array_like):
np.array(array_like, dtype=self.int64)
def time_asarray_dtype(self, array_like):
np.array(array_like, dtype=self.int64, order="F")
def time_asanyarray(self, array_like):
np.asarray(array_like)
def time_asanyarray_dtype(self, array_like):
np.array(array_like, dtype=self.int64)
def time_asanyarray_dtype(self, array_like):
np.array(array_like, dtype=self.int64, order="F")
def time_ascontiguousarray(self, array_like):
np.ascontiguousarray(array_like)

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from .common import Benchmark
import numpy as np
avx_ufuncs = ['sin',
'cos',
'exp',
'log',
'sqrt',
'absolute',
'reciprocal',
'square',
'rint',
'floor',
'ceil' ,
'trunc']
stride = [1, 2, 4]
dtype = ['f', 'd']
class AVX_UFunc(Benchmark):
params = [avx_ufuncs, stride, dtype]
param_names = ['avx_based_ufunc', 'stride', 'dtype']
timeout = 10
def setup(self, ufuncname, stride, dtype):
np.seterr(all='ignore')
try:
self.f = getattr(np, ufuncname)
except AttributeError:
raise NotImplementedError()
N = 10000
self.arr = np.ones(stride*N, dtype)
def time_ufunc(self, ufuncname, stride, dtype):
self.f(self.arr[::stride])
avx_bfuncs = ['maximum',
'minimum']
class AVX_BFunc(Benchmark):
params = [avx_bfuncs, dtype, stride]
param_names = ['avx_based_bfunc', 'dtype', 'stride']
timeout = 10
def setup(self, ufuncname, dtype, stride):
np.seterr(all='ignore')
try:
self.f = getattr(np, ufuncname)
except AttributeError:
raise NotImplementedError()
N = 10000
self.arr1 = np.array(np.random.rand(stride*N), dtype=dtype)
self.arr2 = np.array(np.random.rand(stride*N), dtype=dtype)
def time_ufunc(self, ufuncname, dtype, stride):
self.f(self.arr1[::stride], self.arr2[::stride])
cmplx_bfuncs = ['add',
'subtract',
'multiply',
'divide']
cmplxstride = [1, 2, 4]
cmplxdtype = ['F', 'D']
class AVX_cmplx_arithmetic(Benchmark):
params = [cmplx_bfuncs, cmplxstride, cmplxdtype]
param_names = ['bfunc', 'stride', 'dtype']
timeout = 10
def setup(self, bfuncname, stride, dtype):
np.seterr(all='ignore')
try:
self.f = getattr(np, bfuncname)
except AttributeError:
raise NotImplementedError()
N = 10000
self.arr1 = np.ones(stride*N, dtype)
self.arr2 = np.ones(stride*N, dtype)
def time_ufunc(self, bfuncname, stride, dtype):
self.f(self.arr1[::stride], self.arr2[::stride])
cmplx_ufuncs = ['reciprocal',
'absolute',
'square',
'conjugate']
class AVX_cmplx_funcs(Benchmark):
params = [cmplx_ufuncs, cmplxstride, cmplxdtype]
param_names = ['bfunc', 'stride', 'dtype']
timeout = 10
def setup(self, bfuncname, stride, dtype):
np.seterr(all='ignore')
try:
self.f = getattr(np, bfuncname)
except AttributeError:
raise NotImplementedError()
N = 10000
self.arr1 = np.ones(stride*N, dtype)
def time_ufunc(self, bfuncname, stride, dtype):
self.f(self.arr1[::stride])
class Mandelbrot(Benchmark):
def f(self,z):
return np.abs(z) < 4.0
def g(self,z,c):
return np.sum(np.multiply(z,z) + c)
def mandelbrot_numpy(self, c, maxiter):
output = np.zeros(c.shape, np.int)
z = np.empty(c.shape, np.complex64)
for it in range(maxiter):
notdone = self.f(z)
output[notdone] = it
z[notdone] = self.g(z[notdone],c[notdone])
output[output == maxiter-1] = 0
return output
def mandelbrot_set(self,xmin,xmax,ymin,ymax,width,height,maxiter):
r1 = np.linspace(xmin, xmax, width, dtype=np.float32)
r2 = np.linspace(ymin, ymax, height, dtype=np.float32)
c = r1 + r2[:,None]*1j
n3 = self.mandelbrot_numpy(c,maxiter)
return (r1,r2,n3.T)
def time_mandel(self):
self.mandelbrot_set(-0.74877,-0.74872,0.06505,0.06510,1000,1000,2048)
class LogisticRegression(Benchmark):
param_names = ['dtype']
params = [np.float32, np.float64]
timeout = 1000
def train(self, max_epoch):
for epoch in range(max_epoch):
z = np.matmul(self.X_train, self.W)
A = 1 / (1 + np.exp(-z)) # sigmoid(z)
loss = -np.mean(self.Y_train * np.log(A) + (1-self.Y_train) * np.log(1-A))
dz = A - self.Y_train
dw = (1/self.size) * np.matmul(self.X_train.T, dz)
self.W = self.W - self.alpha*dw
def setup(self, dtype):
np.random.seed(42)
self.size = 250
features = 16
self.X_train = np.random.rand(self.size,features).astype(dtype)
self.Y_train = np.random.choice(2,self.size).astype(dtype)
# Initialize weights
self.W = np.zeros((features,1), dtype=dtype)
self.b = np.zeros((1,1), dtype=dtype)
self.alpha = 0.1
def time_train(self, dtype):
self.train(1000)

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from .common import Benchmark
import numpy as np
class Core(Benchmark):
def setup(self):
self.l100 = range(100)
self.l50 = range(50)
self.l = [np.arange(1000), np.arange(1000)]
self.l_view = [memoryview(a) for a in self.l]
self.l10x10 = np.ones((10, 10))
def time_array_1(self):
np.array(1)
def time_array_empty(self):
np.array([])
def time_array_l1(self):
np.array([1])
def time_array_l100(self):
np.array(self.l100)
def time_array_l(self):
np.array(self.l)
def time_array_l_view(self):
np.array(self.l_view)
def time_vstack_l(self):
np.vstack(self.l)
def time_hstack_l(self):
np.hstack(self.l)
def time_dstack_l(self):
np.dstack(self.l)
def time_arange_100(self):
np.arange(100)
def time_zeros_100(self):
np.zeros(100)
def time_ones_100(self):
np.ones(100)
def time_empty_100(self):
np.empty(100)
def time_eye_100(self):
np.eye(100)
def time_identity_100(self):
np.identity(100)
def time_eye_3000(self):
np.eye(3000)
def time_identity_3000(self):
np.identity(3000)
def time_diag_l100(self):
np.diag(self.l100)
def time_diagflat_l100(self):
np.diagflat(self.l100)
def time_diagflat_l50_l50(self):
np.diagflat([self.l50, self.l50])
def time_triu_l10x10(self):
np.triu(self.l10x10)
def time_tril_l10x10(self):
np.tril(self.l10x10)
class Temporaries(Benchmark):
def setup(self):
self.amid = np.ones(50000)
self.bmid = np.ones(50000)
self.alarge = np.ones(1000000)
self.blarge = np.ones(1000000)
def time_mid(self):
(self.amid * 2) + self.bmid
def time_mid2(self):
(self.amid + self.bmid) - 2
def time_large(self):
(self.alarge * 2) + self.blarge
def time_large2(self):
(self.alarge + self.blarge) - 2
class CorrConv(Benchmark):
params = [[50, 1000, int(1e5)],
[10, 100, 1000, int(1e4)],
['valid', 'same', 'full']]
param_names = ['size1', 'size2', 'mode']
def setup(self, size1, size2, mode):
self.x1 = np.linspace(0, 1, num=size1)
self.x2 = np.cos(np.linspace(0, 2*np.pi, num=size2))
def time_correlate(self, size1, size2, mode):
np.correlate(self.x1, self.x2, mode=mode)
def time_convolve(self, size1, size2, mode):
np.convolve(self.x1, self.x2, mode=mode)
class CountNonzero(Benchmark):
param_names = ['numaxes', 'size', 'dtype']
params = [
[1, 2, 3],
[100, 10000, 1000000],
[bool, int, str, object]
]
def setup(self, numaxes, size, dtype):
self.x = np.arange(numaxes * size).reshape(numaxes, size)
self.x = (self.x % 3).astype(dtype)
def time_count_nonzero(self, numaxes, size, dtype):
np.count_nonzero(self.x)
def time_count_nonzero_axis(self, numaxes, size, dtype):
np.count_nonzero(self.x, axis=self.x.ndim - 1)
def time_count_nonzero_multi_axis(self, numaxes, size, dtype):
if self.x.ndim >= 2:
np.count_nonzero(self.x, axis=(
self.x.ndim - 1, self.x.ndim - 2))
class PackBits(Benchmark):
param_names = ['dtype']
params = [[bool, np.uintp]]
def setup(self, dtype):
self.d = np.ones(10000, dtype=dtype)
self.d2 = np.ones((200, 1000), dtype=dtype)
def time_packbits(self, dtype):
np.packbits(self.d)
def time_packbits_axis0(self, dtype):
np.packbits(self.d2, axis=0)
def time_packbits_axis1(self, dtype):
np.packbits(self.d2, axis=1)
class UnpackBits(Benchmark):
def setup(self):
self.d = np.ones(10000, dtype=np.uint8)
self.d2 = np.ones((200, 1000), dtype=np.uint8)
def time_unpackbits(self):
np.unpackbits(self.d)
def time_unpackbits_little(self):
np.unpackbits(self.d, bitorder="little")
def time_unpackbits_axis0(self):
np.unpackbits(self.d2, axis=0)
def time_unpackbits_axis1(self):
np.unpackbits(self.d2, axis=1)
def time_unpackbits_axis1_little(self):
np.unpackbits(self.d2, bitorder="little", axis=1)
class Indices(Benchmark):
def time_indices(self):
np.indices((1000, 500))
class VarComplex(Benchmark):
params = [10**n for n in range(1, 9)]
def setup(self, n):
self.arr = np.random.randn(n) + 1j * np.random.randn(n)
def teardown(self, n):
del self.arr
def time_var(self, n):
self.arr.var()

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from .common import Benchmark
import numpy as np
class Histogram1D(Benchmark):
def setup(self):
self.d = np.linspace(0, 100, 100000)
def time_full_coverage(self):
np.histogram(self.d, 200, (0, 100))
def time_small_coverage(self):
np.histogram(self.d, 200, (50, 51))
def time_fine_binning(self):
np.histogram(self.d, 10000, (0, 100))
class Histogram2D(Benchmark):
def setup(self):
self.d = np.linspace(0, 100, 200000).reshape((-1,2))
def time_full_coverage(self):
np.histogramdd(self.d, (200, 200), ((0, 100), (0, 100)))
def time_small_coverage(self):
np.histogramdd(self.d, (200, 200), ((50, 51), (50, 51)))
def time_fine_binning(self):
np.histogramdd(self.d, (10000, 10000), ((0, 100), (0, 100)))
class Bincount(Benchmark):
def setup(self):
self.d = np.arange(80000, dtype=np.intp)
self.e = self.d.astype(np.float64)
def time_bincount(self):
np.bincount(self.d)
def time_weights(self):
np.bincount(self.d, weights=self.e)
class Median(Benchmark):
def setup(self):
self.e = np.arange(10000, dtype=np.float32)
self.o = np.arange(10001, dtype=np.float32)
def time_even(self):
np.median(self.e)
def time_odd(self):
np.median(self.o)
def time_even_inplace(self):
np.median(self.e, overwrite_input=True)
def time_odd_inplace(self):
np.median(self.o, overwrite_input=True)
def time_even_small(self):
np.median(self.e[:500], overwrite_input=True)
def time_odd_small(self):
np.median(self.o[:500], overwrite_input=True)
class Percentile(Benchmark):
def setup(self):
self.e = np.arange(10000, dtype=np.float32)
self.o = np.arange(10001, dtype=np.float32)
def time_quartile(self):
np.percentile(self.e, [25, 75])
def time_percentile(self):
np.percentile(self.e, [25, 35, 55, 65, 75])
class Select(Benchmark):
def setup(self):
self.d = np.arange(20000)
self.e = self.d.copy()
self.cond = [(self.d > 4), (self.d < 2)]
self.cond_large = [(self.d > 4), (self.d < 2)] * 10
def time_select(self):
np.select(self.cond, [self.d, self.e])
def time_select_larger(self):
np.select(self.cond_large, ([self.d, self.e] * 10))
def memoize(f):
_memoized = {}
def wrapped(*args):
if args not in _memoized:
_memoized[args] = f(*args)
return _memoized[args].copy()
return f
class SortGenerator:
# The size of the unsorted area in the "random unsorted area"
# benchmarks
AREA_SIZE = 100
# The size of the "partially ordered" sub-arrays
BUBBLE_SIZE = 100
@staticmethod
@memoize
def random(size, dtype):
"""
Returns a randomly-shuffled array.
"""
arr = np.arange(size, dtype=dtype)
np.random.shuffle(arr)
return arr
@staticmethod
@memoize
def ordered(size, dtype):
"""
Returns an ordered array.
"""
return np.arange(size, dtype=dtype)
@staticmethod
@memoize
def reversed(size, dtype):
"""
Returns an array that's in descending order.
"""
return np.arange(size-1, -1, -1, dtype=dtype)
@staticmethod
@memoize
def uniform(size, dtype):
"""
Returns an array that has the same value everywhere.
"""
return np.ones(size, dtype=dtype)
@staticmethod
@memoize
def swapped_pair(size, dtype, swap_frac):
"""
Returns an ordered array, but one that has ``swap_frac * size``
pairs swapped.
"""
a = np.arange(size, dtype=dtype)
for _ in range(int(size * swap_frac)):
x, y = np.random.randint(0, size, 2)
a[x], a[y] = a[y], a[x]
return a
@staticmethod
@memoize
def sorted_block(size, dtype, block_size):
"""
Returns an array with blocks that are all sorted.
"""
a = np.arange(size, dtype=dtype)
b = []
if size < block_size:
return a
block_num = size // block_size
for i in range(block_num):
b.extend(a[i::block_num])
return np.array(b)
@classmethod
@memoize
def random_unsorted_area(cls, size, dtype, frac, area_size=None):
"""
This type of array has random unsorted areas such that they
compose the fraction ``frac`` of the original array.
"""
if area_size is None:
area_size = cls.AREA_SIZE
area_num = int(size * frac / area_size)
a = np.arange(size, dtype=dtype)
for _ in range(area_num):
start = np.random.randint(size-area_size)
end = start + area_size
np.random.shuffle(a[start:end])
return a
@classmethod
@memoize
def random_bubble(cls, size, dtype, bubble_num, bubble_size=None):
"""
This type of array has ``bubble_num`` random unsorted areas.
"""
if bubble_size is None:
bubble_size = cls.BUBBLE_SIZE
frac = bubble_size * bubble_num / size
return cls.random_unsorted_area(size, dtype, frac, bubble_size)
class Sort(Benchmark):
"""
This benchmark tests sorting performance with several
different types of arrays that are likely to appear in
real-world applications.
"""
params = [
# In NumPy 1.17 and newer, 'merge' can be one of several
# stable sorts, it isn't necessarily merge sort.
['quick', 'merge', 'heap'],
['float64', 'int64', 'int16'],
[
('random',),
('ordered',),
('reversed',),
('uniform',),
('sorted_block', 10),
('sorted_block', 100),
('sorted_block', 1000),
# ('swapped_pair', 0.01),
# ('swapped_pair', 0.1),
# ('swapped_pair', 0.5),
# ('random_unsorted_area', 0.5),
# ('random_unsorted_area', 0.1),
# ('random_unsorted_area', 0.01),
# ('random_bubble', 1),
# ('random_bubble', 5),
# ('random_bubble', 10),
],
]
param_names = ['kind', 'dtype', 'array_type']
# The size of the benchmarked arrays.
ARRAY_SIZE = 10000
def setup(self, kind, dtype, array_type):
np.random.seed(1234)
array_class = array_type[0]
self.arr = getattr(SortGenerator, array_class)(self.ARRAY_SIZE, dtype, *array_type[1:])
def time_sort(self, kind, dtype, array_type):
# Using np.sort(...) instead of arr.sort(...) because it makes a copy.
# This is important because the data is prepared once per benchmark, but
# used across multiple runs.
np.sort(self.arr, kind=kind)
def time_argsort(self, kind, dtype, array_type):
np.argsort(self.arr, kind=kind)
class SortWorst(Benchmark):
def setup(self):
# quicksort median of 3 worst case
self.worst = np.arange(1000000)
x = self.worst
while x.size > 3:
mid = x.size // 2
x[mid], x[-2] = x[-2], x[mid]
x = x[:-2]
def time_sort_worst(self):
np.sort(self.worst)
# Retain old benchmark name for backward compatibility
time_sort_worst.benchmark_name = "bench_function_base.Sort.time_sort_worst"
class Where(Benchmark):
def setup(self):
self.d = np.arange(20000)
self.e = self.d.copy()
self.cond = (self.d > 5000)
def time_1(self):
np.where(self.cond)
def time_2(self):
np.where(self.cond, self.d, self.e)
def time_2_broadcast(self):
np.where(self.cond, self.d, 0)

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from subprocess import call
from sys import executable
from timeit import default_timer
from .common import Benchmark
class Import(Benchmark):
timer = default_timer
def execute(self, command):
call((executable, '-c', command))
def time_numpy(self):
self.execute('import numpy')
def time_numpy_inspect(self):
# What are the savings from avoiding to import the inspect module?
self.execute('import numpy, inspect')
def time_fft(self):
self.execute('from numpy import fft')
def time_linalg(self):
self.execute('from numpy import linalg')
def time_ma(self):
self.execute('from numpy import ma')
def time_matlib(self):
self.execute('from numpy import matlib')
def time_random(self):
self.execute('from numpy import random')

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from .common import Benchmark, get_squares_, get_indexes_, get_indexes_rand_
from os.path import join as pjoin
import shutil
from numpy import memmap, float32, array
import numpy as np
from tempfile import mkdtemp
class Indexing(Benchmark):
params = [["indexes_", "indexes_rand_"],
['I', ':,I', 'np.ix_(I, I)'],
['', '=1']]
param_names = ['indexes', 'sel', 'op']
def setup(self, indexes, sel, op):
sel = sel.replace('I', indexes)
ns = {'squares_': get_squares_(),
'np': np,
'indexes_': get_indexes_(),
'indexes_rand_': get_indexes_rand_()}
code = "def run():\n for a in squares_.values(): a[%s]%s"
code = code % (sel, op)
exec(code, ns)
self.func = ns['run']
def time_op(self, indexes, sel, op):
self.func()
class IndexingSeparate(Benchmark):
def setup(self):
self.tmp_dir = mkdtemp()
self.fp = memmap(pjoin(self.tmp_dir, 'tmp.dat'),
dtype=float32, mode='w+', shape=(50, 60))
self.indexes = array([3, 4, 6, 10, 20])
def teardown(self):
del self.fp
shutil.rmtree(self.tmp_dir)
def time_mmap_slicing(self):
for i in range(1000):
self.fp[5:10]
def time_mmap_fancy_indexing(self):
for i in range(1000):
self.fp[self.indexes]
class IndexingStructured0D(Benchmark):
def setup(self):
self.dt = np.dtype([('a', 'f4', 256)])
self.A = np.zeros((), self.dt)
self.B = self.A.copy()
self.a = np.zeros(1, self.dt)[0]
self.b = self.a.copy()
def time_array_slice(self):
self.B['a'][:] = self.A['a']
def time_array_all(self):
self.B['a'] = self.A['a']
def time_scalar_slice(self):
self.b['a'][:] = self.a['a']
def time_scalar_all(self):
self.b['a'] = self.a['a']

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from .common import Benchmark, get_squares
import numpy as np
from io import StringIO
class Copy(Benchmark):
params = ["int8", "int16", "float32", "float64",
"complex64", "complex128"]
param_names = ['type']
def setup(self, typename):
dtype = np.dtype(typename)
self.d = np.arange((50 * 500), dtype=dtype).reshape((500, 50))
self.e = np.arange((50 * 500), dtype=dtype).reshape((50, 500))
self.e_d = self.e.reshape(self.d.shape)
self.dflat = np.arange((50 * 500), dtype=dtype)
def time_memcpy(self, typename):
self.d[...] = self.e_d
def time_memcpy_large_out_of_place(self, typename):
l = np.ones(1024**2, dtype=np.dtype(typename))
l.copy()
def time_cont_assign(self, typename):
self.d[...] = 1
def time_strided_copy(self, typename):
self.d[...] = self.e.T
def time_strided_assign(self, typename):
self.dflat[::2] = 2
class CopyTo(Benchmark):
def setup(self):
self.d = np.ones(50000)
self.e = self.d.copy()
self.m = (self.d == 1)
self.im = (~ self.m)
self.m8 = self.m.copy()
self.m8[::8] = (~ self.m[::8])
self.im8 = (~ self.m8)
def time_copyto(self):
np.copyto(self.d, self.e)
def time_copyto_sparse(self):
np.copyto(self.d, self.e, where=self.m)
def time_copyto_dense(self):
np.copyto(self.d, self.e, where=self.im)
def time_copyto_8_sparse(self):
np.copyto(self.d, self.e, where=self.m8)
def time_copyto_8_dense(self):
np.copyto(self.d, self.e, where=self.im8)
class Savez(Benchmark):
def setup(self):
self.squares = get_squares()
def time_vb_savez_squares(self):
np.savez('tmp.npz', **self.squares)
class LoadtxtCSVComments(Benchmark):
# benchmarks for np.loadtxt comment handling
# when reading in CSV files
params = [10, int(1e2), int(1e4), int(1e5)]
param_names = ['num_lines']
def setup(self, num_lines):
data = [u'1,2,3 # comment'] * num_lines
# unfortunately, timeit will only run setup()
# between repeat events, but not for iterations
# within repeats, so the StringIO object
# will have to be rewinded in the benchmark proper
self.data_comments = StringIO(u'\n'.join(data))
def time_comment_loadtxt_csv(self, num_lines):
# benchmark handling of lines with comments
# when loading in from csv files
# inspired by similar benchmark in pandas
# for read_csv
# need to rewind StringIO object (unfortunately
# confounding timing result somewhat) for every
# call to timing test proper
np.loadtxt(self.data_comments,
delimiter=u',')
self.data_comments.seek(0)
class LoadtxtCSVdtypes(Benchmark):
# benchmarks for np.loadtxt operating with
# different dtypes parsed / cast from CSV files
params = (['float32', 'float64', 'int32', 'int64',
'complex128', 'str', 'object'],
[10, int(1e2), int(1e4), int(1e5)])
param_names = ['dtype', 'num_lines']
def setup(self, dtype, num_lines):
data = [u'5, 7, 888'] * num_lines
self.csv_data = StringIO(u'\n'.join(data))
def time_loadtxt_dtypes_csv(self, dtype, num_lines):
# benchmark loading arrays of various dtypes
# from csv files
# state-dependent timing benchmark requires
# rewind of StringIO object
np.loadtxt(self.csv_data,
delimiter=u',',
dtype=dtype)
self.csv_data.seek(0)
class LoadtxtCSVStructured(Benchmark):
# benchmarks for np.loadtxt operating with
# a structured data type & CSV file
def setup(self):
num_lines = 50000
data = [u"M, 21, 72, X, 155"] * num_lines
self.csv_data = StringIO(u'\n'.join(data))
def time_loadtxt_csv_struct_dtype(self):
# obligate rewind of StringIO object
# between iterations of a repeat:
np.loadtxt(self.csv_data,
delimiter=u',',
dtype=[('category_1', 'S1'),
('category_2', 'i4'),
('category_3', 'f8'),
('category_4', 'S1'),
('category_5', 'f8')])
self.csv_data.seek(0)
class LoadtxtCSVSkipRows(Benchmark):
# benchmarks for loadtxt row skipping when
# reading in csv file data; a similar benchmark
# is present in the pandas asv suite
params = [0, 500, 10000]
param_names = ['skiprows']
def setup(self, skiprows):
np.random.seed(123)
test_array = np.random.rand(100000, 3)
self.fname = 'test_array.csv'
np.savetxt(fname=self.fname,
X=test_array,
delimiter=',')
def time_skiprows_csv(self, skiprows):
np.loadtxt(self.fname,
delimiter=',',
skiprows=skiprows)
class LoadtxtReadUint64Integers(Benchmark):
# pandas has a similar CSV reading benchmark
# modified to suit np.loadtxt
params = [550, 1000, 10000]
param_names = ['size']
def setup(self, size):
arr = np.arange(size).astype('uint64') + 2**63
self.data1 = StringIO(u'\n'.join(arr.astype(str).tolist()))
arr = arr.astype(object)
arr[500] = -1
self.data2 = StringIO(u'\n'.join(arr.astype(str).tolist()))
def time_read_uint64(self, size):
# mandatory rewind of StringIO object
# between iterations of a repeat:
np.loadtxt(self.data1)
self.data1.seek(0)
def time_read_uint64_neg_values(self, size):
# mandatory rewind of StringIO object
# between iterations of a repeat:
np.loadtxt(self.data2)
self.data2.seek(0)
class LoadtxtUseColsCSV(Benchmark):
# benchmark selective column reading from CSV files
# using np.loadtxt
params = [2, [1, 3], [1, 3, 5, 7]]
param_names = ['usecols']
def setup(self, usecols):
num_lines = 5000
data = [u'0, 1, 2, 3, 4, 5, 6, 7, 8, 9'] * num_lines
self.csv_data = StringIO(u'\n'.join(data))
def time_loadtxt_usecols_csv(self, usecols):
# must rewind StringIO because of state
# dependence of file reading
np.loadtxt(self.csv_data,
delimiter=u',',
usecols=usecols)
self.csv_data.seek(0)
class LoadtxtCSVDateTime(Benchmark):
# benchmarks for np.loadtxt operating with
# datetime data in a CSV file
params = [20, 200, 2000, 20000]
param_names = ['num_lines']
def setup(self, num_lines):
# create the equivalent of a two-column CSV file
# with date strings in the first column and random
# floating point data in the second column
dates = np.arange('today', 20, dtype=np.datetime64)
np.random.seed(123)
values = np.random.rand(20)
date_line = u''
for date, value in zip(dates, values):
date_line += (str(date) + ',' + str(value) + '\n')
# expand data to specified number of lines
data = date_line * (num_lines // 20)
self.csv_data = StringIO(data)
def time_loadtxt_csv_datetime(self, num_lines):
# rewind StringIO object -- the timing iterations
# are state-dependent
X = np.loadtxt(self.csv_data,
delimiter=u',',
dtype=([('dates', 'M8[us]'),
('values', 'float64')]))
self.csv_data.seek(0)

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from __future__ import absolute_import, division, print_function
from .common import Benchmark, TYPES1
import numpy as np
class Take(Benchmark):
params = [
[(1000, 1), (1000, 2), (2, 1000, 1), (1000, 3)],
["raise", "wrap", "clip"],
TYPES1]
param_names = ["shape", "mode", "dtype"]
def setup(self, shape, mode, dtype):
self.arr = np.ones(shape, dtype)
self.indices = np.arange(1000)
def time_contiguous(self, shape, mode, dtype):
self.arr.take(self.indices, axis=-2, mode=mode)
class PutMask(Benchmark):
params = [
[True, False],
TYPES1]
param_names = ["values_is_scalar", "dtype"]
def setup(self, values_is_scalar, dtype):
if values_is_scalar:
self.vals = np.array(1., dtype=dtype)
else:
self.vals = np.ones(1000, dtype=dtype)
self.arr = np.ones(1000, dtype=dtype)
self.dense_mask = np.ones(1000, dtype="bool")
self.sparse_mask = np.zeros(1000, dtype="bool")
def time_dense(self, values_is_scalar, dtype):
np.putmask(self.arr, self.dense_mask, self.vals)
def time_sparse(self, values_is_scalar, dtype):
np.putmask(self.arr, self.sparse_mask, self.vals)

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"""Benchmarks for `numpy.lib`."""
from .common import Benchmark
import numpy as np
class Pad(Benchmark):
"""Benchmarks for `numpy.pad`.
When benchmarking the pad function it is useful to cover scenarios where
the ratio between the size of the input array and the output array differs
significantly (original area vs. padded area). This allows to evaluate for
which scenario a padding algorithm is optimized. Furthermore involving
large range of array sizes ensures that the effects of CPU-bound caching is
visible.
The table below shows the sizes of the arrays involved in this benchmark:
+-----------------+----------+-----------+-----------+-----------------+
| shape | original | padded: 1 | padded: 8 | padded: (0, 32) |
+=================+==========+===========+===========+=================+
| (2 ** 22,) | 32 MiB | 32.0 MiB | 32.0 MiB | 32.0 MiB |
+-----------------+----------+-----------+-----------+-----------------+
| (1024, 1024) | 8 MiB | 8.03 MiB | 8.25 MiB | 8.51 MiB |
+-----------------+----------+-----------+-----------+-----------------+
| (256, 256, 1) | 256 KiB | 786 KiB | 5.08 MiB | 11.6 MiB |
+-----------------+----------+-----------+-----------+-----------------+
| (4, 4, 4, 4) | 2 KiB | 10.1 KiB | 1.22 MiB | 12.8 MiB |
+-----------------+----------+-----------+-----------+-----------------+
| (1, 1, 1, 1, 1) | 8 B | 1.90 MiB | 10.8 MiB | 299 MiB |
+-----------------+----------+-----------+-----------+-----------------+
"""
param_names = ["shape", "pad_width", "mode"]
params = [
# Shape of the input arrays
[(2 ** 22,), (1024, 1024), (256, 128, 1),
(4, 4, 4, 4), (1, 1, 1, 1, 1)],
# Tested pad widths
[1, 8, (0, 32)],
# Tested modes: mean, median, minimum & maximum use the same code path
# reflect & symmetric share a lot of their code path
["constant", "edge", "linear_ramp", "mean", "reflect", "wrap"],
]
def setup(self, shape, pad_width, mode):
# Make sure to fill the array to make the OS page fault
# in the setup phase and not the timed phase
self.array = np.full(shape, fill_value=1, dtype=np.float64)
def time_pad(self, shape, pad_width, mode):
np.pad(self.array, pad_width, mode)
class Nan(Benchmark):
"""Benchmarks for nan functions"""
param_names = ["array_size", "percent_nans"]
params = [
# sizes of the 1D arrays
[200, int(2e5)],
# percent of np.nan in arrays
[0, 0.1, 2., 50., 90.],
]
def setup(self, array_size, percent_nans):
np.random.seed(123)
# produce a randomly shuffled array with the
# approximate desired percentage np.nan content
base_array = np.random.uniform(size=array_size)
base_array[base_array < percent_nans / 100.] = np.nan
self.arr = base_array
def time_nanmin(self, array_size, percent_nans):
np.nanmin(self.arr)
def time_nanmax(self, array_size, percent_nans):
np.nanmax(self.arr)
def time_nanargmin(self, array_size, percent_nans):
np.nanargmin(self.arr)
def time_nanargmax(self, array_size, percent_nans):
np.nanargmax(self.arr)
def time_nansum(self, array_size, percent_nans):
np.nansum(self.arr)
def time_nanprod(self, array_size, percent_nans):
np.nanprod(self.arr)
def time_nancumsum(self, array_size, percent_nans):
np.nancumsum(self.arr)
def time_nancumprod(self, array_size, percent_nans):
np.nancumprod(self.arr)
def time_nanmean(self, array_size, percent_nans):
np.nanmean(self.arr)
def time_nanvar(self, array_size, percent_nans):
np.nanvar(self.arr)
def time_nanstd(self, array_size, percent_nans):
np.nanstd(self.arr)
def time_nanmedian(self, array_size, percent_nans):
np.nanmedian(self.arr)
def time_nanquantile(self, array_size, percent_nans):
np.nanquantile(self.arr, q=0.2)
def time_nanpercentile(self, array_size, percent_nans):
np.nanpercentile(self.arr, q=50)

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from .common import Benchmark, get_squares_, get_indexes_rand, TYPES1
import numpy as np
class Eindot(Benchmark):
def setup(self):
self.a = np.arange(60000.0).reshape(150, 400)
self.ac = self.a.copy()
self.at = self.a.T
self.atc = self.a.T.copy()
self.b = np.arange(240000.0).reshape(400, 600)
self.c = np.arange(600)
self.d = np.arange(400)
self.a3 = np.arange(480000.).reshape(60, 80, 100)
self.b3 = np.arange(192000.).reshape(80, 60, 40)
def time_dot_a_b(self):
np.dot(self.a, self.b)
def time_dot_d_dot_b_c(self):
np.dot(self.d, np.dot(self.b, self.c))
def time_dot_trans_a_at(self):
np.dot(self.a, self.at)
def time_dot_trans_a_atc(self):
np.dot(self.a, self.atc)
def time_dot_trans_at_a(self):
np.dot(self.at, self.a)
def time_dot_trans_atc_a(self):
np.dot(self.atc, self.a)
def time_einsum_i_ij_j(self):
np.einsum('i,ij,j', self.d, self.b, self.c)
def time_einsum_ij_jk_a_b(self):
np.einsum('ij,jk', self.a, self.b)
def time_einsum_ijk_jil_kl(self):
np.einsum('ijk,jil->kl', self.a3, self.b3)
def time_inner_trans_a_a(self):
np.inner(self.a, self.a)
def time_inner_trans_a_ac(self):
np.inner(self.a, self.ac)
def time_matmul_a_b(self):
np.matmul(self.a, self.b)
def time_matmul_d_matmul_b_c(self):
np.matmul(self.d, np.matmul(self.b, self.c))
def time_matmul_trans_a_at(self):
np.matmul(self.a, self.at)
def time_matmul_trans_a_atc(self):
np.matmul(self.a, self.atc)
def time_matmul_trans_at_a(self):
np.matmul(self.at, self.a)
def time_matmul_trans_atc_a(self):
np.matmul(self.atc, self.a)
def time_tensordot_a_b_axes_1_0_0_1(self):
np.tensordot(self.a3, self.b3, axes=([1, 0], [0, 1]))
class Linalg(Benchmark):
params = [['svd', 'pinv', 'det', 'norm'],
TYPES1]
param_names = ['op', 'type']
def setup(self, op, typename):
np.seterr(all='ignore')
self.func = getattr(np.linalg, op)
if op == 'cholesky':
# we need a positive definite
self.a = np.dot(get_squares_()[typename],
get_squares_()[typename].T)
else:
self.a = get_squares_()[typename]
# check that dtype is supported at all
try:
self.func(self.a[:2, :2])
except TypeError:
raise NotImplementedError()
def time_op(self, op, typename):
self.func(self.a)
class Lstsq(Benchmark):
def setup(self):
self.a = get_squares_()['float64']
self.b = get_indexes_rand()[:100].astype(np.float64)
def time_numpy_linalg_lstsq_a__b_float64(self):
np.linalg.lstsq(self.a, self.b, rcond=-1)

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from .common import Benchmark
import numpy as np
class MA(Benchmark):
def setup(self):
self.l100 = range(100)
self.t100 = ([True] * 100)
def time_masked_array(self):
np.ma.masked_array()
def time_masked_array_l100(self):
np.ma.masked_array(self.l100)
def time_masked_array_l100_t100(self):
np.ma.masked_array(self.l100, self.t100)
class Indexing(Benchmark):
param_names = ['masked', 'ndim', 'size']
params = [[True, False],
[1, 2],
[10, 100, 1000]]
def setup(self, masked, ndim, size):
x = np.arange(size**ndim).reshape(ndim * (size,))
if masked:
self.m = np.ma.array(x, mask=x%2 == 0)
else:
self.m = np.ma.array(x)
self.idx_scalar = (size//2,) * ndim
self.idx_0d = (size//2,) * ndim + (Ellipsis,)
self.idx_1d = (size//2,) * (ndim - 1)
def time_scalar(self, masked, ndim, size):
self.m[self.idx_scalar]
def time_0d(self, masked, ndim, size):
self.m[self.idx_0d]
def time_1d(self, masked, ndim, size):
self.m[self.idx_1d]
class UFunc(Benchmark):
param_names = ['a_masked', 'b_masked', 'size']
params = [[True, False],
[True, False],
[10, 100, 1000]]
def setup(self, a_masked, b_masked, size):
x = np.arange(size).astype(np.uint8)
self.a_scalar = np.ma.masked if a_masked else 5
self.b_scalar = np.ma.masked if b_masked else 3
self.a_1d = np.ma.array(x, mask=x%2 == 0 if a_masked else np.ma.nomask)
self.b_1d = np.ma.array(x, mask=x%3 == 0 if b_masked else np.ma.nomask)
self.a_2d = self.a_1d.reshape(1, -1)
self.b_2d = self.a_1d.reshape(-1, 1)
def time_scalar(self, a_masked, b_masked, size):
np.ma.add(self.a_scalar, self.b_scalar)
def time_scalar_1d(self, a_masked, b_masked, size):
np.ma.add(self.a_scalar, self.b_1d)
def time_1d(self, a_masked, b_masked, size):
np.ma.add(self.a_1d, self.b_1d)
def time_2d(self, a_masked, b_masked, size):
# broadcasting happens this time
np.ma.add(self.a_2d, self.b_2d)
class Concatenate(Benchmark):
param_names = ['mode', 'n']
params = [
['ndarray', 'unmasked',
'ndarray+masked', 'unmasked+masked',
'masked'],
[2, 100, 2000]
]
def setup(self, mode, n):
# avoid np.zeros's lazy allocation that cause page faults during benchmark.
# np.fill will cause pagefaults to happen during setup.
normal = np.full((n, n), 0, int)
unmasked = np.ma.zeros((n, n), int)
masked = np.ma.array(normal, mask=True)
mode_parts = mode.split('+')
base = mode_parts[0]
promote = 'masked' in mode_parts[1:]
if base == 'ndarray':
args = 10 * (normal,)
elif base == 'unmasked':
args = 10 * (unmasked,)
else:
args = 10 * (masked,)
if promote:
args = args[:-1] + (masked,)
self.args = args
def time_it(self, mode, n):
np.ma.concatenate(self.args)

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from .common import Benchmark
try:
from numpy.core.overrides import array_function_dispatch
except ImportError:
# Don't fail at import time with old Numpy versions
def array_function_dispatch(*args, **kwargs):
def wrap(*args, **kwargs):
return None
return wrap
import numpy as np
def _broadcast_to_dispatcher(array, shape, subok=None):
return (array,)
@array_function_dispatch(_broadcast_to_dispatcher)
def mock_broadcast_to(array, shape, subok=False):
pass
def _concatenate_dispatcher(arrays, axis=None, out=None):
if out is not None:
arrays = list(arrays)
arrays.append(out)
return arrays
@array_function_dispatch(_concatenate_dispatcher)
def mock_concatenate(arrays, axis=0, out=None):
pass
class DuckArray:
def __array_function__(self, func, types, args, kwargs):
pass
class ArrayFunction(Benchmark):
def setup(self):
self.numpy_array = np.array(1)
self.numpy_arrays = [np.array(1), np.array(2)]
self.many_arrays = 500 * self.numpy_arrays
self.duck_array = DuckArray()
self.duck_arrays = [DuckArray(), DuckArray()]
self.mixed_arrays = [np.array(1), DuckArray()]
def time_mock_broadcast_to_numpy(self):
mock_broadcast_to(self.numpy_array, ())
def time_mock_broadcast_to_duck(self):
mock_broadcast_to(self.duck_array, ())
def time_mock_concatenate_numpy(self):
mock_concatenate(self.numpy_arrays, axis=0)
def time_mock_concatenate_many(self):
mock_concatenate(self.many_arrays, axis=0)
def time_mock_concatenate_duck(self):
mock_concatenate(self.duck_arrays, axis=0)
def time_mock_concatenate_mixed(self):
mock_concatenate(self.mixed_arrays, axis=0)

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from .common import Benchmark
import numpy as np
try:
from numpy.random import Generator
except ImportError:
pass
class Random(Benchmark):
params = ['normal', 'uniform', 'weibull 1', 'binomial 10 0.5',
'poisson 10']
def setup(self, name):
items = name.split()
name = items.pop(0)
params = [float(x) for x in items]
self.func = getattr(np.random, name)
self.params = tuple(params) + ((100, 100),)
def time_rng(self, name):
self.func(*self.params)
class Shuffle(Benchmark):
def setup(self):
self.a = np.arange(100000)
def time_100000(self):
np.random.shuffle(self.a)
class Randint(Benchmark):
def time_randint_fast(self):
"""Compare to uint32 below"""
np.random.randint(0, 2**30, size=10**5)
def time_randint_slow(self):
"""Compare to uint32 below"""
np.random.randint(0, 2**30 + 1, size=10**5)
class Randint_dtype(Benchmark):
high = {
'bool': 1,
'uint8': 2**7,
'uint16': 2**15,
'uint32': 2**31,
'uint64': 2**63
}
param_names = ['dtype']
params = ['bool', 'uint8', 'uint16', 'uint32', 'uint64']
def setup(self, name):
from numpy.lib import NumpyVersion
if NumpyVersion(np.__version__) < '1.11.0.dev0':
raise NotImplementedError
def time_randint_fast(self, name):
high = self.high[name]
np.random.randint(0, high, size=10**5, dtype=name)
def time_randint_slow(self, name):
high = self.high[name]
np.random.randint(0, high + 1, size=10**5, dtype=name)
class Permutation(Benchmark):
def setup(self):
self.n = 10000
self.a_1d = np.random.random(self.n)
self.a_2d = np.random.random((self.n, 2))
def time_permutation_1d(self):
np.random.permutation(self.a_1d)
def time_permutation_2d(self):
np.random.permutation(self.a_2d)
def time_permutation_int(self):
np.random.permutation(self.n)
nom_size = 100000
class RNG(Benchmark):
param_names = ['rng']
params = ['PCG64', 'MT19937', 'Philox', 'SFC64', 'numpy']
def setup(self, bitgen):
if bitgen == 'numpy':
self.rg = np.random.RandomState()
else:
self.rg = Generator(getattr(np.random, bitgen)())
self.rg.random()
self.int32info = np.iinfo(np.int32)
self.uint32info = np.iinfo(np.uint32)
self.uint64info = np.iinfo(np.uint64)
def time_raw(self, bitgen):
if bitgen == 'numpy':
self.rg.random_integers(self.int32info.max, size=nom_size)
else:
self.rg.integers(self.int32info.max, size=nom_size, endpoint=True)
def time_32bit(self, bitgen):
min, max = self.uint32info.min, self.uint32info.max
if bitgen == 'numpy':
self.rg.randint(min, max + 1, nom_size, dtype=np.uint32)
else:
self.rg.integers(min, max + 1, nom_size, dtype=np.uint32)
def time_64bit(self, bitgen):
min, max = self.uint64info.min, self.uint64info.max
if bitgen == 'numpy':
self.rg.randint(min, max + 1, nom_size, dtype=np.uint64)
else:
self.rg.integers(min, max + 1, nom_size, dtype=np.uint64)
def time_normal_zig(self, bitgen):
self.rg.standard_normal(nom_size)
class Bounded(Benchmark):
u8 = np.uint8
u16 = np.uint16
u32 = np.uint32
u64 = np.uint64
param_names = ['rng', 'dt_max']
params = [['PCG64', 'MT19937', 'Philox', 'SFC64', 'numpy'],
[[u8, 95],
[u8, 64], # Worst case for legacy
[u8, 127], # Best case for legacy
[u16, 95],
[u16, 1024], # Worst case for legacy
[u16, 1535], # Typ. avg. case for legacy
[u16, 2047], # Best case for legacy
[u32, 1024], # Worst case for legacy
[u32, 1535], # Typ. avg. case for legacy
[u32, 2047], # Best case for legacy
[u64, 95],
[u64, 1024], # Worst case for legacy
[u64, 1535], # Typ. avg. case for legacy
[u64, 2047], # Best case for legacy
]]
def setup(self, bitgen, args):
if bitgen == 'numpy':
self.rg = np.random.RandomState()
else:
self.rg = Generator(getattr(np.random, bitgen)())
self.rg.random()
def time_bounded(self, bitgen, args):
"""
Timer for 8-bit bounded values.
Parameters (packed as args)
----------
dt : {uint8, uint16, uint32, unit64}
output dtype
max : int
Upper bound for range. Lower is always 0. Must be <= 2**bits.
"""
dt, max = args
if bitgen == 'numpy':
self.rg.randint(0, max + 1, nom_size, dtype=dt)
else:
self.rg.integers(0, max + 1, nom_size, dtype=dt)
class Choice(Benchmark):
params = [1e3, 1e6, 1e8]
def setup(self, v):
self.a = np.arange(v)
self.rng = np.random.default_rng()
def time_legacy_choice(self, v):
np.random.choice(self.a, 1000, replace=False)
def time_choice(self, v):
self.rng.choice(self.a, 1000, replace=False)

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from .common import Benchmark
import numpy as np
class Records(Benchmark):
def setup(self):
self.l50 = np.arange(1000)
self.fields_number = 10000
self.arrays = [self.l50 for _ in range(self.fields_number)]
self.formats = [self.l50.dtype.str for _ in range(self.fields_number)]
self.formats_str = ','.join(self.formats)
self.dtype_ = np.dtype(
[
('field_{}'.format(i), self.l50.dtype.str)
for i in range(self.fields_number)
]
)
self.buffer = self.l50.tostring() * self.fields_number
def time_fromarrays_w_dtype(self):
np.core.records.fromarrays(self.arrays, dtype=self.dtype_)
def time_fromarrays_wo_dtype(self):
np.core.records.fromarrays(self.arrays)
def time_fromarrays_formats_as_list(self):
np.core.records.fromarrays(self.arrays, formats=self.formats)
def time_fromarrays_formats_as_string(self):
np.core.records.fromarrays(self.arrays, formats=self.formats_str)
def time_fromstring_w_dtype(self):
np.core.records.fromstring(self.buffer, dtype=self.dtype_)
def time_fromstring_formats_as_list(self):
np.core.records.fromstring(self.buffer, formats=self.formats)
def time_fromstring_formats_as_string(self):
np.core.records.fromstring(self.buffer, formats=self.formats_str)

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from .common import Benchmark, TYPES1, get_squares
import numpy as np
class AddReduce(Benchmark):
def setup(self):
self.squares = get_squares().values()
def time_axis_0(self):
[np.add.reduce(a, axis=0) for a in self.squares]
def time_axis_1(self):
[np.add.reduce(a, axis=1) for a in self.squares]
class AddReduceSeparate(Benchmark):
params = [[0, 1], TYPES1]
param_names = ['axis', 'type']
def setup(self, axis, typename):
self.a = get_squares()[typename]
def time_reduce(self, axis, typename):
np.add.reduce(self.a, axis=axis)
class AnyAll(Benchmark):
def setup(self):
# avoid np.zeros's lazy allocation that would
# cause page faults during benchmark
self.zeros = np.full(100000, 0, bool)
self.ones = np.full(100000, 1, bool)
def time_all_fast(self):
self.zeros.all()
def time_all_slow(self):
self.ones.all()
def time_any_fast(self):
self.ones.any()
def time_any_slow(self):
self.zeros.any()
class MinMax(Benchmark):
params = [np.float32, np.float64, np.intp]
param_names = ['dtype']
def setup(self, dtype):
self.d = np.ones(20000, dtype=dtype)
def time_min(self, dtype):
np.min(self.d)
def time_max(self, dtype):
np.max(self.d)
class SmallReduction(Benchmark):
def setup(self):
self.d = np.ones(100, dtype=np.float32)
def time_small(self):
np.sum(self.d)

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from .common import Benchmark
import numpy as np
class Block(Benchmark):
params = [1, 10, 100]
param_names = ['size']
def setup(self, n):
self.a_2d = np.ones((2 * n, 2 * n))
self.b_1d = np.ones(2 * n)
self.b_2d = 2 * self.a_2d
self.a = np.ones(3 * n)
self.b = np.ones(3 * n)
self.one_2d = np.ones((1 * n, 3 * n))
self.two_2d = np.ones((1 * n, 3 * n))
self.three_2d = np.ones((1 * n, 6 * n))
self.four_1d = np.ones(6 * n)
self.five_0d = np.ones(1 * n)
self.six_1d = np.ones(5 * n)
# avoid np.zeros's lazy allocation that might cause
# page faults during benchmark
self.zero_2d = np.full((2 * n, 6 * n), 0)
self.one = np.ones(3 * n)
self.two = 2 * np.ones((3, 3 * n))
self.three = 3 * np.ones(3 * n)
self.four = 4 * np.ones(3 * n)
self.five = 5 * np.ones(1 * n)
self.six = 6 * np.ones(5 * n)
# avoid np.zeros's lazy allocation that might cause
# page faults during benchmark
self.zero = np.full((2 * n, 6 * n), 0)
def time_block_simple_row_wise(self, n):
np.block([self.a_2d, self.b_2d])
def time_block_simple_column_wise(self, n):
np.block([[self.a_2d], [self.b_2d]])
def time_block_complicated(self, n):
np.block([[self.one_2d, self.two_2d],
[self.three_2d],
[self.four_1d],
[self.five_0d, self.six_1d],
[self.zero_2d]])
def time_nested(self, n):
np.block([
[
np.block([
[self.one],
[self.three],
[self.four]
]),
self.two
],
[self.five, self.six],
[self.zero]
])
def time_no_lists(self, n):
np.block(1)
np.block(np.eye(3 * n))
class Block2D(Benchmark):
params = [[(16, 16), (32, 32), (64, 64), (128, 128), (256, 256), (512, 512), (1024, 1024)],
['uint8', 'uint16', 'uint32', 'uint64'],
[(2, 2), (4, 4)]]
param_names = ['shape', 'dtype', 'n_chunks']
def setup(self, shape, dtype, n_chunks):
self.block_list = [
[np.full(shape=[s//n_chunk for s, n_chunk in zip(shape, n_chunks)],
fill_value=1, dtype=dtype) for _ in range(n_chunks[1])]
for _ in range(n_chunks[0])
]
def time_block2d(self, shape, dtype, n_chunks):
np.block(self.block_list)
class Block3D(Benchmark):
"""This benchmark concatenates an array of size ``(5n)^3``"""
# Having copy as a `mode` of the block3D
# allows us to directly compare the benchmark of block
# to that of a direct memory copy into new buffers with
# the ASV framework.
# block and copy will be plotted on the same graph
# as opposed to being displayed as separate benchmarks
params = [[1, 10, 100],
['block', 'copy']]
param_names = ['n', 'mode']
def setup(self, n, mode):
# Slow setup method: hence separated from the others above
self.a000 = np.ones((2 * n, 2 * n, 2 * n), int) * 1
self.a100 = np.ones((3 * n, 2 * n, 2 * n), int) * 2
self.a010 = np.ones((2 * n, 3 * n, 2 * n), int) * 3
self.a001 = np.ones((2 * n, 2 * n, 3 * n), int) * 4
self.a011 = np.ones((2 * n, 3 * n, 3 * n), int) * 5
self.a101 = np.ones((3 * n, 2 * n, 3 * n), int) * 6
self.a110 = np.ones((3 * n, 3 * n, 2 * n), int) * 7
self.a111 = np.ones((3 * n, 3 * n, 3 * n), int) * 8
self.block = [
[
[self.a000, self.a001],
[self.a010, self.a011],
],
[
[self.a100, self.a101],
[self.a110, self.a111],
]
]
self.arr_list = [a
for two_d in self.block
for one_d in two_d
for a in one_d]
def time_3d(self, n, mode):
if mode == 'block':
np.block(self.block)
else: # mode == 'copy'
[arr.copy() for arr in self.arr_list]
# Retain old benchmark name for backward compat
time_3d.benchmark_name = "bench_shape_base.Block.time_3d"

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from .common import Benchmark, get_squares_
import numpy as np
ufuncs = ['abs', 'absolute', 'add', 'arccos', 'arccosh', 'arcsin', 'arcsinh',
'arctan', 'arctan2', 'arctanh', 'bitwise_and', 'bitwise_not',
'bitwise_or', 'bitwise_xor', 'cbrt', 'ceil', 'conj', 'conjugate',
'copysign', 'cos', 'cosh', 'deg2rad', 'degrees', 'divide', 'divmod',
'equal', 'exp', 'exp2', 'expm1', 'fabs', 'float_power', 'floor',
'floor_divide', 'fmax', 'fmin', 'fmod', 'frexp', 'gcd', 'greater',
'greater_equal', 'heaviside', 'hypot', 'invert', 'isfinite',
'isinf', 'isnan', 'isnat', 'lcm', 'ldexp', 'left_shift', 'less',
'less_equal', 'log', 'log10', 'log1p', 'log2', 'logaddexp',
'logaddexp2', 'logical_and', 'logical_not', 'logical_or',
'logical_xor', 'matmul', 'maximum', 'minimum', 'mod', 'modf', 'multiply',
'negative', 'nextafter', 'not_equal', 'positive', 'power',
'rad2deg', 'radians', 'reciprocal', 'remainder', 'right_shift',
'rint', 'sign', 'signbit', 'sin', 'sinh', 'spacing', 'sqrt',
'square', 'subtract', 'tan', 'tanh', 'true_divide', 'trunc']
for name in dir(np):
if isinstance(getattr(np, name, None), np.ufunc) and name not in ufuncs:
print("Missing ufunc %r" % (name,))
class Broadcast(Benchmark):
def setup(self):
self.d = np.ones((50000, 100), dtype=np.float64)
self.e = np.ones((100,), dtype=np.float64)
def time_broadcast(self):
self.d - self.e
class UFunc(Benchmark):
params = [ufuncs]
param_names = ['ufunc']
timeout = 10
def setup(self, ufuncname):
np.seterr(all='ignore')
try:
self.f = getattr(np, ufuncname)
except AttributeError:
raise NotImplementedError()
self.args = []
for t, a in get_squares_().items():
arg = (a,) * self.f.nin
try:
self.f(*arg)
except TypeError:
continue
self.args.append(arg)
def time_ufunc_types(self, ufuncname):
[self.f(*arg) for arg in self.args]
class Custom(Benchmark):
def setup(self):
self.b = np.ones(20000, dtype=bool)
def time_nonzero(self):
np.nonzero(self.b)
def time_not_bool(self):
(~self.b)
def time_and_bool(self):
(self.b & self.b)
def time_or_bool(self):
(self.b | self.b)
class CustomInplace(Benchmark):
def setup(self):
self.c = np.ones(500000, dtype=np.int8)
self.i = np.ones(150000, dtype=np.int32)
self.f = np.zeros(150000, dtype=np.float32)
self.d = np.zeros(75000, dtype=np.float64)
# fault memory
self.f *= 1.
self.d *= 1.
def time_char_or(self):
np.bitwise_or(self.c, 0, out=self.c)
np.bitwise_or(0, self.c, out=self.c)
def time_char_or_temp(self):
0 | self.c | 0
def time_int_or(self):
np.bitwise_or(self.i, 0, out=self.i)
np.bitwise_or(0, self.i, out=self.i)
def time_int_or_temp(self):
0 | self.i | 0
def time_float_add(self):
np.add(self.f, 1., out=self.f)
np.add(1., self.f, out=self.f)
def time_float_add_temp(self):
1. + self.f + 1.
def time_double_add(self):
np.add(self.d, 1., out=self.d)
np.add(1., self.d, out=self.d)
def time_double_add_temp(self):
1. + self.d + 1.
class CustomScalar(Benchmark):
params = [np.float32, np.float64]
param_names = ['dtype']
def setup(self, dtype):
self.d = np.ones(20000, dtype=dtype)
def time_add_scalar2(self, dtype):
np.add(self.d, 1)
def time_divide_scalar2(self, dtype):
np.divide(self.d, 1)
def time_divide_scalar2_inplace(self, dtype):
np.divide(self.d, 1, out=self.d)
def time_less_than_scalar2(self, dtype):
(self.d < 1)
class Scalar(Benchmark):
def setup(self):
self.x = np.asarray(1.0)
self.y = np.asarray((1.0 + 1j))
self.z = complex(1.0, 1.0)
def time_add_scalar(self):
(self.x + self.x)
def time_add_scalar_conv(self):
(self.x + 1.0)
def time_add_scalar_conv_complex(self):
(self.y + self.z)
class ArgPack:
__slots__ = ['args', 'kwargs']
def __init__(self, *args, **kwargs):
self.args = args
self.kwargs = kwargs
def __repr__(self):
return '({})'.format(', '.join(
[repr(a) for a in self.args] +
['{}={}'.format(k, repr(v)) for k, v in self.kwargs.items()]
))
class ArgParsing(Benchmark):
# In order to benchmark the speed of argument parsing, all but the
# out arguments are chosen such that they have no effect on the
# calculation. In particular, subok=True and where=True are
# defaults, and the dtype is the correct one (the latter will
# still have some effect on the search for the correct inner loop).
x = np.array(1.)
y = np.array(2.)
out = np.array(3.)
param_names = ['arg_kwarg']
params = [[
ArgPack(x, y),
ArgPack(x, y, out),
ArgPack(x, y, out=out),
ArgPack(x, y, out=(out,)),
ArgPack(x, y, out=out, subok=True, where=True),
ArgPack(x, y, subok=True),
ArgPack(x, y, subok=True, where=True),
ArgPack(x, y, out, subok=True, where=True)
]]
def time_add_arg_parsing(self, arg_pack):
np.add(*arg_pack.args, **arg_pack.kwargs)
class ArgParsingReduce(Benchmark):
# In order to benchmark the speed of argument parsing, all but the
# out arguments are chosen such that they have minimal effect on the
# calculation.
a = np.arange(2.)
out = np.array(0.)
param_names = ['arg_kwarg']
params = [[
ArgPack(a,),
ArgPack(a, 0),
ArgPack(a, axis=0),
ArgPack(a, 0, None),
ArgPack(a, axis=0, dtype=None),
ArgPack(a, 0, None, out),
ArgPack(a, axis=0, dtype=None, out=out),
ArgPack(a, out=out)
]]
def time_add_reduce_arg_parsing(self, arg_pack):
np.add.reduce(*arg_pack.args, **arg_pack.kwargs)

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import numpy
import random
# Various pre-crafted datasets/variables for testing
# !!! Must not be changed -- only appended !!!
# while testing numpy we better not rely on numpy to produce random
# sequences
random.seed(1)
# but will seed it nevertheless
numpy.random.seed(1)
nx, ny = 1000, 1000
# reduced squares based on indexes_rand, primarily for testing more
# time-consuming functions (ufunc, linalg, etc)
nxs, nys = 100, 100
# a set of interesting types to test
TYPES1 = [
'int16', 'float16',
'int32', 'float32',
'int64', 'float64', 'complex64',
'longfloat', 'complex128',
]
if 'complex256' in numpy.typeDict:
TYPES1.append('complex256')
def memoize(func):
result = []
def wrapper():
if not result:
result.append(func())
return result[0]
return wrapper
# values which will be used to construct our sample data matrices
# replicate 10 times to speed up initial imports of this helper
# and generate some redundancy
@memoize
def get_values():
rnd = numpy.random.RandomState(1)
values = numpy.tile(rnd.uniform(0, 100, size=nx*ny//10), 10)
return values
@memoize
def get_squares():
values = get_values()
squares = {t: numpy.array(values,
dtype=getattr(numpy, t)).reshape((nx, ny))
for t in TYPES1}
# adjust complex ones to have non-degenerated imagery part -- use
# original data transposed for that
for t, v in squares.items():
if t.startswith('complex'):
v += v.T*1j
return squares
@memoize
def get_squares_():
# smaller squares
squares_ = {t: s[:nxs, :nys] for t, s in get_squares().items()}
return squares_
@memoize
def get_vectors():
# vectors
vectors = {t: s[0] for t, s in get_squares().items()}
return vectors
@memoize
def get_indexes():
indexes = list(range(nx))
# so we do not have all items
indexes.pop(5)
indexes.pop(95)
indexes = numpy.array(indexes)
return indexes
@memoize
def get_indexes_rand():
rnd = random.Random(1)
indexes_rand = get_indexes().tolist() # copy
rnd.shuffle(indexes_rand) # in-place shuffle
indexes_rand = numpy.array(indexes_rand)
return indexes_rand
@memoize
def get_indexes_():
# smaller versions
indexes = get_indexes()
indexes_ = indexes[indexes < nxs]
return indexes_
@memoize
def get_indexes_rand_():
indexes_rand = get_indexes_rand()
indexes_rand_ = indexes_rand[indexes_rand < nxs]
return indexes_rand_
class Benchmark:
goal_time = 0.25

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===================
NumPy C Style Guide
===================
The NumPy C coding conventions are based on Python PEP-0007 by Guido van
Rossum with a few added strictures. There are many C coding conventions and
it must be emphasized that the primary goal of the NumPy conventions isn't
to choose the 'best', about which there is certain to be disagreement, but
to achieve uniformity. Because the NumPy conventions are very close to
those in PEP-0007, that PEP is used as a template below with the NumPy
additions and variations in the appropriate spots.
Introduction
------------
This document gives coding conventions for the C code comprising
the C implementation of NumPy. Note, rules are there to be broken.
Two good reasons to break a particular rule:
1. When applying the rule would make the code less readable, even
for someone who is used to reading code that follows the rules.
2. To be consistent with surrounding code that also breaks it
(maybe for historic reasons) -- although this is also an
opportunity to clean up someone else's mess.
C dialect
---------
* Use C99 (that is, the standard defined by ISO/IEC 9899:1999).
* Don't use GCC extensions (e.g. don't write multi-line strings
without trailing backslashes). Preferably break long strings
up onto separate lines like so::
"blah blah"
"blah blah"
This will work with MSVC, which otherwise chokes on very long
strings.
* All function declarations and definitions must use full
prototypes (i.e. specify the types of all arguments).
* No compiler warnings with major compilers (gcc, VC++, a few others).
Note: NumPy still produces compiler warnings that need to be addressed.
Code lay-out
------------
* Use 4-space indents and no tabs at all.
* No line should be longer than 80 characters. If this and the
previous rule together don't give you enough room to code, your code is
too complicated, consider using subroutines.
* No line should end in whitespace. If you think you need
significant trailing whitespace, think again, somebody's editor might
delete it as a matter of routine.
* Function definition style: function name in column 1, outermost
curly braces in column 1, blank line after local variable declarations::
static int
extra_ivars(PyTypeObject *type, PyTypeObject *base)
{
int t_size = PyType_BASICSIZE(type);
int b_size = PyType_BASICSIZE(base);
assert(t_size >= b_size); /* type smaller than base! */
...
return 1;
}
If the transition to C++ goes through it is possible that this form will
be relaxed so that short class methods meant to be inlined can have the
return type on the same line as the function name. However, that is yet to
be determined.
* Code structure: one space between keywords like ``if``, ``for`` and
the following left parenthesis; no spaces inside the parenthesis; braces
around all ``if`` branches and no statements on the same line as the
``if``. They should be formatted as shown::
if (mro != NULL) {
one_line_statement;
}
else {
...
}
for (i = 0; i < n; i++) {
one_line_statement;
}
while (isstuff) {
dostuff;
}
do {
stuff;
} while (isstuff);
switch (kind) {
/* Boolean kind */
case 'b':
return 0;
/* Unsigned int kind */
case 'u':
...
/* Anything else */
default:
return 3;
}
* The return statement should *not* get redundant parentheses::
return Py_None; /* correct */
return(Py_None); /* incorrect */
* Function and macro call style: ``foo(a, b, c)``, no space before
the open paren, no spaces inside the parens, no spaces before
commas, one space after each comma.
* Always put spaces around the assignment, Boolean and comparison
operators. In expressions using a lot of operators, add spaces
around the outermost (lowest priority) operators.
* Breaking long lines: if you can, break after commas in the
outermost argument list. Always indent continuation lines
appropriately, e.g., ::
PyErr_SetString(PyExc_TypeError,
"Oh dear, you messed up.");
Here appropriately means at least two tabs. It isn't necessary to
line everything up with the opening parenthesis of the function
call.
* When you break a long expression at a binary operator, the
operator goes at the end of the previous line, e.g., ::
if (type > tp_dictoffset != 0 &&
base > tp_dictoffset == 0 &&
type > tp_dictoffset == b_size &&
(size_t)t_size == b_size + sizeof(PyObject *)) {
return 0;
}
Note that the terms in the multi-line Boolean expression are indented so
as to make the beginning of the code block clearly visible.
* Put blank lines around functions, structure definitions, and
major sections inside functions.
* Comments go before the code they describe. Multi-line comments should
be like so::
/*
* This would be a long
* explanatory comment.
*/
Trailing comments should be used sparingly. Instead of ::
if (yes) { // Success!
do ::
if (yes) {
// Success!
* All functions and global variables should be declared static
when they aren't needed outside the current compilation unit.
* Declare external functions and variables in a header file.
Naming conventions
------------------
* There has been no consistent prefix for NumPy public functions, but
they all begin with a prefix of some sort, followed by an underscore, and
are in camel case: ``PyArray_DescrAlignConverter``, ``NpyIter_GetIterNext``.
In the future the names should be of the form ``Npy*_PublicFunction``,
where the star is something appropriate.
* Public Macros should have a ``NPY_`` prefix and then use upper case,
for example, ``NPY_DOUBLE``.
* Private functions should be lower case with underscores, for example:
``array_real_get``. Single leading underscores should not be used, but
some current function names violate that rule due to historical accident.
Those functions should be renamed at some point.
Function documentation
----------------------
NumPy doesn't have a C function documentation standard at this time, but
needs one. Most numpy functions are not documented in the code and that
should change. One possibility is Doxygen with a plugin so that the same
NumPy style used for Python functions can also be used for documenting
C functions, see the files in doc/cdoc/.

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.. -*- rest -*-
NumPy Distutils - Users Guide
=============================
.. contents::
SciPy structure
'''''''''''''''
Currently SciPy project consists of two packages:
- NumPy --- it provides packages like:
+ numpy.distutils - extension to Python distutils
+ numpy.f2py - a tool to bind Fortran/C codes to Python
+ numpy.core - future replacement of Numeric and numarray packages
+ numpy.lib - extra utility functions
+ numpy.testing - numpy-style tools for unit testing
+ etc
- SciPy --- a collection of scientific tools for Python.
The aim of this document is to describe how to add new tools to SciPy.
Requirements for SciPy packages
'''''''''''''''''''''''''''''''
SciPy consists of Python packages, called SciPy packages, that are
available to Python users via the ``scipy`` namespace. Each SciPy package
may contain other SciPy packages. And so on. Therefore, the SciPy
directory tree is a tree of packages with arbitrary depth and width.
Any SciPy package may depend on NumPy packages but the dependence on other
SciPy packages should be kept minimal or zero.
A SciPy package contains, in addition to its sources, the following
files and directories:
+ ``setup.py`` --- building script
+ ``__init__.py`` --- package initializer
+ ``tests/`` --- directory of unittests
Their contents are described below.
The ``setup.py`` file
'''''''''''''''''''''
In order to add a Python package to SciPy, its build script (``setup.py``)
must meet certain requirements. The most important requirement is that the
package define a ``configuration(parent_package='',top_path=None)`` function
which returns a dictionary suitable for passing to
``numpy.distutils.core.setup(..)``. To simplify the construction of
this dictionary, ``numpy.distutils.misc_util`` provides the
``Configuration`` class, described below.
SciPy pure Python package example
---------------------------------
Below is an example of a minimal ``setup.py`` file for a pure SciPy package::
#!/usr/bin/env python3
def configuration(parent_package='',top_path=None):
from numpy.distutils.misc_util import Configuration
config = Configuration('mypackage',parent_package,top_path)
return config
if __name__ == "__main__":
from numpy.distutils.core import setup
#setup(**configuration(top_path='').todict())
setup(configuration=configuration)
The arguments of the ``configuration`` function specify the name of
parent SciPy package (``parent_package``) and the directory location
of the main ``setup.py`` script (``top_path``). These arguments,
along with the name of the current package, should be passed to the
``Configuration`` constructor.
The ``Configuration`` constructor has a fourth optional argument,
``package_path``, that can be used when package files are located in
a different location than the directory of the ``setup.py`` file.
Remaining ``Configuration`` arguments are all keyword arguments that will
be used to initialize attributes of ``Configuration``
instance. Usually, these keywords are the same as the ones that
``setup(..)`` function would expect, for example, ``packages``,
``ext_modules``, ``data_files``, ``include_dirs``, ``libraries``,
``headers``, ``scripts``, ``package_dir``, etc. However, the direct
specification of these keywords is not recommended as the content of
these keyword arguments will not be processed or checked for the
consistency of SciPy building system.
Finally, ``Configuration`` has ``.todict()`` method that returns all
the configuration data as a dictionary suitable for passing on to the
``setup(..)`` function.
``Configuration`` instance attributes
-------------------------------------
In addition to attributes that can be specified via keyword arguments
to ``Configuration`` constructor, ``Configuration`` instance (let us
denote as ``config``) has the following attributes that can be useful
in writing setup scripts:
+ ``config.name`` - full name of the current package. The names of parent
packages can be extracted as ``config.name.split('.')``.
+ ``config.local_path`` - path to the location of current ``setup.py`` file.
+ ``config.top_path`` - path to the location of main ``setup.py`` file.
``Configuration`` instance methods
----------------------------------
+ ``config.todict()`` --- returns configuration dictionary suitable for
passing to ``numpy.distutils.core.setup(..)`` function.
+ ``config.paths(*paths) --- applies ``glob.glob(..)`` to items of
``paths`` if necessary. Fixes ``paths`` item that is relative to
``config.local_path``.
+ ``config.get_subpackage(subpackage_name,subpackage_path=None)`` ---
returns a list of subpackage configurations. Subpackage is looked in the
current directory under the name ``subpackage_name`` but the path
can be specified also via optional ``subpackage_path`` argument.
If ``subpackage_name`` is specified as ``None`` then the subpackage
name will be taken the basename of ``subpackage_path``.
Any ``*`` used for subpackage names are expanded as wildcards.
+ ``config.add_subpackage(subpackage_name,subpackage_path=None)`` ---
add SciPy subpackage configuration to the current one. The meaning
and usage of arguments is explained above, see
``config.get_subpackage()`` method.
+ ``config.add_data_files(*files)`` --- prepend ``files`` to ``data_files``
list. If ``files`` item is a tuple then its first element defines
the suffix of where data files are copied relative to package installation
directory and the second element specifies the path to data
files. By default data files are copied under package installation
directory. For example,
::
config.add_data_files('foo.dat',
('fun',['gun.dat','nun/pun.dat','/tmp/sun.dat']),
'bar/car.dat'.
'/full/path/to/can.dat',
)
will install data files to the following locations
::
<installation path of config.name package>/
foo.dat
fun/
gun.dat
pun.dat
sun.dat
bar/
car.dat
can.dat
Path to data files can be a function taking no arguments and
returning path(s) to data files -- this is a useful when data files
are generated while building the package. (XXX: explain the step
when this function are called exactly)
+ ``config.add_data_dir(data_path)`` --- add directory ``data_path``
recursively to ``data_files``. The whole directory tree starting at
``data_path`` will be copied under package installation directory.
If ``data_path`` is a tuple then its first element defines
the suffix of where data files are copied relative to package installation
directory and the second element specifies the path to data directory.
By default, data directory are copied under package installation
directory under the basename of ``data_path``. For example,
::
config.add_data_dir('fun') # fun/ contains foo.dat bar/car.dat
config.add_data_dir(('sun','fun'))
config.add_data_dir(('gun','/full/path/to/fun'))
will install data files to the following locations
::
<installation path of config.name package>/
fun/
foo.dat
bar/
car.dat
sun/
foo.dat
bar/
car.dat
gun/
foo.dat
bar/
car.dat
+ ``config.add_include_dirs(*paths)`` --- prepend ``paths`` to
``include_dirs`` list. This list will be visible to all extension
modules of the current package.
+ ``config.add_headers(*files)`` --- prepend ``files`` to ``headers``
list. By default, headers will be installed under
``<prefix>/include/pythonX.X/<config.name.replace('.','/')>/``
directory. If ``files`` item is a tuple then it's first argument
specifies the installation suffix relative to
``<prefix>/include/pythonX.X/`` path. This is a Python distutils
method; its use is discouraged for NumPy and SciPy in favour of
``config.add_data_files(*files)``.
+ ``config.add_scripts(*files)`` --- prepend ``files`` to ``scripts``
list. Scripts will be installed under ``<prefix>/bin/`` directory.
+ ``config.add_extension(name,sources,**kw)`` --- create and add an
``Extension`` instance to ``ext_modules`` list. The first argument
``name`` defines the name of the extension module that will be
installed under ``config.name`` package. The second argument is
a list of sources. ``add_extension`` method takes also keyword
arguments that are passed on to the ``Extension`` constructor.
The list of allowed keywords is the following: ``include_dirs``,
``define_macros``, ``undef_macros``, ``library_dirs``, ``libraries``,
``runtime_library_dirs``, ``extra_objects``, ``extra_compile_args``,
``extra_link_args``, ``export_symbols``, ``swig_opts``, ``depends``,
``language``, ``f2py_options``, ``module_dirs``, ``extra_info``,
``extra_f77_compile_args``, ``extra_f90_compile_args``.
Note that ``config.paths`` method is applied to all lists that
may contain paths. ``extra_info`` is a dictionary or a list
of dictionaries that content will be appended to keyword arguments.
The list ``depends`` contains paths to files or directories
that the sources of the extension module depend on. If any path
in the ``depends`` list is newer than the extension module, then
the module will be rebuilt.
The list of sources may contain functions ('source generators')
with a pattern ``def <funcname>(ext, build_dir): return
<source(s) or None>``. If ``funcname`` returns ``None``, no sources
are generated. And if the ``Extension`` instance has no sources
after processing all source generators, no extension module will
be built. This is the recommended way to conditionally define
extension modules. Source generator functions are called by the
``build_src`` sub-command of ``numpy.distutils``.
For example, here is a typical source generator function::
def generate_source(ext,build_dir):
import os
from distutils.dep_util import newer
target = os.path.join(build_dir,'somesource.c')
if newer(target,__file__):
# create target file
return target
The first argument contains the Extension instance that can be
useful to access its attributes like ``depends``, ``sources``,
etc. lists and modify them during the building process.
The second argument gives a path to a build directory that must
be used when creating files to a disk.
+ ``config.add_library(name, sources, **build_info)`` --- add a
library to ``libraries`` list. Allowed keywords arguments are
``depends``, ``macros``, ``include_dirs``, ``extra_compiler_args``,
``f2py_options``, ``extra_f77_compile_args``,
``extra_f90_compile_args``. See ``.add_extension()`` method for
more information on arguments.
+ ``config.have_f77c()`` --- return True if Fortran 77 compiler is
available (read: a simple Fortran 77 code compiled successfully).
+ ``config.have_f90c()`` --- return True if Fortran 90 compiler is
available (read: a simple Fortran 90 code compiled successfully).
+ ``config.get_version()`` --- return version string of the current package,
``None`` if version information could not be detected. This methods
scans files ``__version__.py``, ``<packagename>_version.py``,
``version.py``, ``__svn_version__.py`` for string variables
``version``, ``__version__``, ``<packagename>_version``.
+ ``config.make_svn_version_py()`` --- appends a data function to
``data_files`` list that will generate ``__svn_version__.py`` file
to the current package directory. The file will be removed from
the source directory when Python exits.
+ ``config.get_build_temp_dir()`` --- return a path to a temporary
directory. This is the place where one should build temporary
files.
+ ``config.get_distribution()`` --- return distutils ``Distribution``
instance.
+ ``config.get_config_cmd()`` --- returns ``numpy.distutils`` config
command instance.
+ ``config.get_info(*names)`` ---
.. _templating:
Conversion of ``.src`` files using Templates
--------------------------------------------
NumPy distutils supports automatic conversion of source files named
<somefile>.src. This facility can be used to maintain very similar
code blocks requiring only simple changes between blocks. During the
build phase of setup, if a template file named <somefile>.src is
encountered, a new file named <somefile> is constructed from the
template and placed in the build directory to be used instead. Two
forms of template conversion are supported. The first form occurs for
files named <file>.ext.src where ext is a recognized Fortran
extension (f, f90, f95, f77, for, ftn, pyf). The second form is used
for all other cases.
.. index::
single: code generation
Fortran files
-------------
This template converter will replicate all **function** and
**subroutine** blocks in the file with names that contain '<...>'
according to the rules in '<...>'. The number of comma-separated words
in '<...>' determines the number of times the block is repeated. What
these words are indicates what that repeat rule, '<...>', should be
replaced with in each block. All of the repeat rules in a block must
contain the same number of comma-separated words indicating the number
of times that block should be repeated. If the word in the repeat rule
needs a comma, leftarrow, or rightarrow, then prepend it with a
backslash ' \'. If a word in the repeat rule matches ' \\<index>' then
it will be replaced with the <index>-th word in the same repeat
specification. There are two forms for the repeat rule: named and
short.
Named repeat rule
^^^^^^^^^^^^^^^^^
A named repeat rule is useful when the same set of repeats must be
used several times in a block. It is specified using <rule1=item1,
item2, item3,..., itemN>, where N is the number of times the block
should be repeated. On each repeat of the block, the entire
expression, '<...>' will be replaced first with item1, and then with
item2, and so forth until N repeats are accomplished. Once a named
repeat specification has been introduced, the same repeat rule may be
used **in the current block** by referring only to the name
(i.e. <rule1>).
Short repeat rule
^^^^^^^^^^^^^^^^^
A short repeat rule looks like <item1, item2, item3, ..., itemN>. The
rule specifies that the entire expression, '<...>' should be replaced
first with item1, and then with item2, and so forth until N repeats
are accomplished.
Pre-defined names
^^^^^^^^^^^^^^^^^
The following predefined named repeat rules are available:
- <prefix=s,d,c,z>
- <_c=s,d,c,z>
- <_t=real, double precision, complex, double complex>
- <ftype=real, double precision, complex, double complex>
- <ctype=float, double, complex_float, complex_double>
- <ftypereal=float, double precision, \\0, \\1>
- <ctypereal=float, double, \\0, \\1>
Other files
------------
Non-Fortran files use a separate syntax for defining template blocks
that should be repeated using a variable expansion similar to the
named repeat rules of the Fortran-specific repeats.
NumPy Distutils preprocesses C source files (extension: :file:`.c.src`) written
in a custom templating language to generate C code. The :c:data:`@` symbol is
used to wrap macro-style variables to empower a string substitution mechanism
that might describe (for instance) a set of data types.
The template language blocks are delimited by :c:data:`/**begin repeat`
and :c:data:`/**end repeat**/` lines, which may also be nested using
consecutively numbered delimiting lines such as :c:data:`/**begin repeat1`
and :c:data:`/**end repeat1**/`:
1. "/\**begin repeat "on a line by itself marks the beginning of
a segment that should be repeated.
2. Named variable expansions are defined using ``#name=item1, item2, item3,
..., itemN#`` and placed on successive lines. These variables are
replaced in each repeat block with corresponding word. All named
variables in the same repeat block must define the same number of
words.
3. In specifying the repeat rule for a named variable, ``item*N`` is short-
hand for ``item, item, ..., item`` repeated N times. In addition,
parenthesis in combination with \*N can be used for grouping several
items that should be repeated. Thus, #name=(item1, item2)*4# is
equivalent to #name=item1, item2, item1, item2, item1, item2, item1,
item2#
4. "\*/ "on a line by itself marks the end of the variable expansion
naming. The next line is the first line that will be repeated using
the named rules.
5. Inside the block to be repeated, the variables that should be expanded
are specified as ``@name@``
6. "/\**end repeat**/ "on a line by itself marks the previous line
as the last line of the block to be repeated.
7. A loop in the NumPy C source code may have a ``@TYPE@`` variable, targeted
for string substitution, which is preprocessed to a number of otherwise
identical loops with several strings such as INT, LONG, UINT, ULONG. The
``@TYPE@`` style syntax thus reduces code duplication and maintenance burden by
mimicking languages that have generic type support.
The above rules may be clearer in the following template source example:
.. code-block:: NumPyC
:linenos:
:emphasize-lines: 3, 13, 29, 31
/* TIMEDELTA to non-float types */
/**begin repeat
*
* #TOTYPE = BYTE, UBYTE, SHORT, USHORT, INT, UINT, LONG, ULONG,
* LONGLONG, ULONGLONG, DATETIME,
* TIMEDELTA#
* #totype = npy_byte, npy_ubyte, npy_short, npy_ushort, npy_int, npy_uint,
* npy_long, npy_ulong, npy_longlong, npy_ulonglong,
* npy_datetime, npy_timedelta#
*/
/**begin repeat1
*
* #FROMTYPE = TIMEDELTA#
* #fromtype = npy_timedelta#
*/
static void
@FROMTYPE@_to_@TOTYPE@(void *input, void *output, npy_intp n,
void *NPY_UNUSED(aip), void *NPY_UNUSED(aop))
{
const @fromtype@ *ip = input;
@totype@ *op = output;
while (n--) {
*op++ = (@totype@)*ip++;
}
}
/**end repeat1**/
/**end repeat**/
The preprocessing of generically typed C source files (whether in NumPy
proper or in any third party package using NumPy Distutils) is performed
by `conv_template.py`_.
The type specific C files generated (extension: .c)
by these modules during the build process are ready to be compiled. This
form of generic typing is also supported for C header files (preprocessed
to produce .h files).
.. _conv_template.py: https://github.com/numpy/numpy/blob/master/numpy/distutils/conv_template.py
Useful functions in ``numpy.distutils.misc_util``
-------------------------------------------------
+ ``get_numpy_include_dirs()`` --- return a list of NumPy base
include directories. NumPy base include directories contain
header files such as ``numpy/arrayobject.h``, ``numpy/funcobject.h``
etc. For installed NumPy the returned list has length 1
but when building NumPy the list may contain more directories,
for example, a path to ``config.h`` file that
``numpy/base/setup.py`` file generates and is used by ``numpy``
header files.
+ ``append_path(prefix,path)`` --- smart append ``path`` to ``prefix``.
+ ``gpaths(paths, local_path='')`` --- apply glob to paths and prepend
``local_path`` if needed.
+ ``njoin(*path)`` --- join pathname components + convert ``/``-separated path
to ``os.sep``-separated path and resolve ``..``, ``.`` from paths.
Ex. ``njoin('a',['b','./c'],'..','g') -> os.path.join('a','b','g')``.
+ ``minrelpath(path)`` --- resolves dots in ``path``.
+ ``rel_path(path, parent_path)`` --- return ``path`` relative to ``parent_path``.
+ ``def get_cmd(cmdname,_cache={})`` --- returns ``numpy.distutils``
command instance.
+ ``all_strings(lst)``
+ ``has_f_sources(sources)``
+ ``has_cxx_sources(sources)``
+ ``filter_sources(sources)`` --- return ``c_sources, cxx_sources,
f_sources, fmodule_sources``
+ ``get_dependencies(sources)``
+ ``is_local_src_dir(directory)``
+ ``get_ext_source_files(ext)``
+ ``get_script_files(scripts)``
+ ``get_lib_source_files(lib)``
+ ``get_data_files(data)``
+ ``dot_join(*args)`` --- join non-zero arguments with a dot.
+ ``get_frame(level=0)`` --- return frame object from call stack with given level.
+ ``cyg2win32(path)``
+ ``mingw32()`` --- return ``True`` when using mingw32 environment.
+ ``terminal_has_colors()``, ``red_text(s)``, ``green_text(s)``,
``yellow_text(s)``, ``blue_text(s)``, ``cyan_text(s)``
+ ``get_path(mod_name,parent_path=None)`` --- return path of a module
relative to parent_path when given. Handles also ``__main__`` and
``__builtin__`` modules.
+ ``allpath(name)`` --- replaces ``/`` with ``os.sep`` in ``name``.
+ ``cxx_ext_match``, ``fortran_ext_match``, ``f90_ext_match``,
``f90_module_name_match``
``numpy.distutils.system_info`` module
--------------------------------------
+ ``get_info(name,notfound_action=0)``
+ ``combine_paths(*args,**kws)``
+ ``show_all()``
``numpy.distutils.cpuinfo`` module
----------------------------------
+ ``cpuinfo``
``numpy.distutils.log`` module
------------------------------
+ ``set_verbosity(v)``
``numpy.distutils.exec_command`` module
---------------------------------------
+ ``get_pythonexe()``
+ ``find_executable(exe, path=None)``
+ ``exec_command( command, execute_in='', use_shell=None, use_tee=None, **env )``
The ``__init__.py`` file
''''''''''''''''''''''''
The header of a typical SciPy ``__init__.py`` is::
"""
Package docstring, typically with a brief description and function listing.
"""
# import functions into module namespace
from .subpackage import *
...
__all__ = [s for s in dir() if not s.startswith('_')]
from numpy.testing import Tester
test = Tester().test
bench = Tester().bench
Note that NumPy submodules still use a file named ``info.py`` in which the
module docstring and ``__all__`` dict are defined. These files will be removed
at some point.
Extra features in NumPy Distutils
'''''''''''''''''''''''''''''''''
Specifying config_fc options for libraries in setup.py script
-------------------------------------------------------------
It is possible to specify config_fc options in setup.py scripts.
For example, using
config.add_library('library',
sources=[...],
config_fc={'noopt':(__file__,1)})
will compile the ``library`` sources without optimization flags.
It's recommended to specify only those config_fc options in such a way
that are compiler independent.
Getting extra Fortran 77 compiler options from source
-----------------------------------------------------
Some old Fortran codes need special compiler options in order to
work correctly. In order to specify compiler options per source
file, ``numpy.distutils`` Fortran compiler looks for the following
pattern::
CF77FLAGS(<fcompiler type>) = <fcompiler f77flags>
in the first 20 lines of the source and use the ``f77flags`` for
specified type of the fcompiler (the first character ``C`` is optional).
TODO: This feature can be easily extended for Fortran 90 codes as
well. Let us know if you would need such a feature.

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.. Here follows an example docstring for a C-function. Note that the
signature is given. This is done only for functions written is C,
since Python cannot find their signature by inspection. For all
other functions, start with the one line description.
multivariate_normal(mean, cov[, shape])
Draw samples from a multivariate normal distribution.
The multivariate normal, multinormal or Gaussian distribution is a
generalisation of the one-dimensional normal distribution to higher
dimensions.
Such a distribution is specified by its mean and covariance matrix,
which are analogous to the mean (average or "centre") and variance
(standard deviation squared or "width") of the one-dimensional normal
distribution.
Parameters
----------
mean : (N,) ndarray
Mean of the N-dimensional distribution.
cov : (N,N) ndarray
Covariance matrix of the distribution.
shape : tuple of ints, optional
Given a shape of, for example, (m,n,k), m*n*k samples are
generated, and packed in an m-by-n-by-k arrangement. Because each
sample is N-dimensional, the output shape is (m,n,k,N). If no
shape is specified, a single sample is returned.
Returns
-------
out : ndarray
The drawn samples, arranged according to `shape`. If the
shape given is (m,n,...), then the shape of `out` is
(m,n,...,N).
In other words, each entry ``out[i,j,...,:]`` is an N-dimensional
value drawn from the distribution.
See Also
--------
normal
scipy.stats.norm : Provides random variates, as well as probability density
function, cumulative density function, etc.
Notes
-----
The mean is a coordinate in N-dimensional space, which represents the
location where samples are most likely to be generated. This is
analogous to the peak of the bell curve for the one-dimensional or
univariate normal distribution.
Covariance indicates the level to which two variables vary together.
From the multivariate normal distribution, we draw N-dimensional
samples, :math:`X = [x_1, x_2, ... x_N]`. The covariance matrix
element :math:`C_ij` is the covariance of :math:`x_i` and :math:`x_j`.
The element :math:`C_ii` is the variance of :math:`x_i` (i.e. its
"spread").
Instead of specifying the full covariance matrix, popular
approximations include:
- Spherical covariance (`cov` is a multiple of the identity matrix)
- Diagonal covariance (`cov` has non-negative elements, and only on
the diagonal)
This geometrical property can be seen in two dimensions by plotting
generated data-points:
>>> mean = [0,0]
>>> cov = [[1,0],[0,100]] # diagonal covariance, points lie on x or y-axis
>>> x,y = np.random.multivariate_normal(mean,cov,5000).T
>>> import matplotlib.pyplot as plt
>>> plt.plot(x,y,'x'); plt.axis('equal'); pyplot.show()
Note that the covariance matrix must be non-negative definite.
References
----------
.. [1] A. Papoulis, "Probability, Random Variables, and Stochastic
Processes," 3rd ed., McGraw-Hill Companies, 1991
.. [2] R.O. Duda, P.E. Hart, and D.G. Stork, "Pattern Classification,"
2nd ed., Wiley, 2001.
Examples
--------
>>> mean = (1,2)
>>> cov = [[1,0],[1,0]]
>>> x = np.random.multivariate_normal(mean,cov,(3,3))
>>> x.shape
(3, 3, 2)
The following is probably true, given that 0.6 is roughly twice the
standard deviation:
>>> print list( (x[0,0,:] - mean) < 0.6 )
[True, True]
.. index:
:refguide: random:distributions

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This document has been replaced, see https://numpydoc.readthedocs.io/en/latest/format.html#docstring-standard

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This file gives an overview of what is necessary to build binary releases for
NumPy.
Current build and release info
==============================
The current info on building and releasing NumPy and SciPy is scattered in
several places. It should be summarized in one place, updated, and where
necessary described in more detail. The sections below list all places where
useful info can be found.
Source tree
-----------
- INSTALL.rst.txt
- release.sh
- pavement.py
NumPy Docs
----------
- https://github.com/numpy/numpy/blob/master/doc/HOWTO_RELEASE.rst.txt
- http://projects.scipy.org/numpy/wiki/MicrosoftToolchainSupport (dead link)
SciPy.org wiki
--------------
- https://www.scipy.org/Installing_SciPy and links on that page.
- http://new.scipy.org/building/windows.html (dead link)
Doc wiki
--------
- http://docs.scipy.org/numpy/docs/numpy-docs/user/install.rst/ (dead link)
Release Scripts
---------------
- https://github.com/numpy/numpy-vendor
Supported platforms and versions
================================
`NEP 29`_ outlines which Python versions are supported; For the first half of
2020, this will be Python >= 3.6. We test NumPy against all these versions
every time we merge code to master. Binary installers may be available for a
subset of these versions (see below).
OS X
----
OS X versions >= 10.9 are supported, for Python version support see `NEP 29`_.
We build binary wheels for OSX that are compatible with Python.org Python,
system Python, homebrew and macports - see this `OSX wheel building summary
<https://github.com/MacPython/wiki/wiki/Spinning-wheels>`_ for details.
Windows
-------
We build 32- and 64-bit wheels on Windows. Windows 7, 8 and 10 are supported.
We build NumPy using the `mingw-w64 toolchain`_ on Appveyor.
Linux
-----
We build and ship `manylinux1 <https://www.python.org/dev/peps/pep-0513>`_
wheels for NumPy. Many Linux distributions include their own binary builds
of NumPy.
BSD / Solaris
-------------
No binaries are provided, but successful builds on Solaris and BSD have been
reported.
Tool chain
==========
We build all our wheels on cloud infrastructure - so this list of compilers is
for information and debugging builds locally. See the ``.travis.yml`` and
``appveyor.yml`` scripts in the `numpy wheels`_ repo for the definitive source
of the build recipes. Packages that are available using pip are noted.
Compilers
---------
The same gcc version is used as the one with which Python itself is built on
each platform. At the moment this means:
- OS X builds on travis currently use `clang`. It appears that binary wheels
for OSX >= 10.6 can be safely built from the travis-ci OSX 10.9 VMs
when building against the Python from the Python.org installers;
- Windows builds use the `mingw-w64 toolchain`_;
- Manylinux1 wheels use the gcc provided on the Manylinux docker images.
You will need Cython for building the binaries. Cython compiles the ``.pyx``
files in the NumPy distribution to ``.c`` files.
.. _mingw-w64 toolchain : https://mingwpy.github.io
.. _NEP 29 : https://numpy.org/neps/nep-0029-deprecation_policy.html
OpenBLAS
------------
All the wheels link to a version of OpenBLAS_ supplied via the openblas-libs_ repo.
The shared object (or DLL) is shipped with in the wheel, renamed to prevent name
collisions with other OpenBLAS shared objects that may exist in the filesystem.
.. _OpenBLAS: https://github.com/xianyi/OpenBLAS
.. _openblas-libs: https://github.com/MacPython/openblas-libs
Building source archives and wheels
-----------------------------------
You will need write permission for numpy-wheels in order to trigger wheel
builds.
- Python(s) from `python.org <https://python.org>`_ or linux distro.
- cython (pip)
- virtualenv (pip)
- Paver (pip)
- pandoc `pandoc.org <https://www.pandoc.org>`_ or linux distro.
- numpy-wheels `<https://github.com/MacPython/numpy-wheels>`_ (clone)
Building docs
-------------
Building the documents requires a number of latex ``.sty`` files. Install them
all to avoid aggravation.
- Sphinx (pip)
- numpydoc (pip)
- Matplotlib
- Texlive (or MikTeX on Windows)
Uploading to PyPI
-----------------
- terryfy `<https://github.com/MacPython/terryfy>`_ (clone).
- beautifulsoup4 (pip)
- delocate (pip)
- auditwheel (pip)
- twine (pip)
Generating author/pr lists
--------------------------
You will need a personal access token
`<https://help.github.com/articles/creating-a-personal-access-token-for-the-command-line/>`_
so that scripts can access the github NumPy repository.
- gitpython (pip)
- pygithub (pip)
Virtualenv
----------
Virtualenv is a very useful tool to keep several versions of packages around.
It is also used in the Paver script to build the docs.
What is released
================
Wheels
------
We currently support Python 3.6-3.8 on Windows, OSX, and Linux
* Windows: 32-bit and 64-bit wheels built using Appveyor;
* OSX: x64_86 OSX wheels built using travis-ci;
* Linux: 32-bit and 64-bit Manylinux1 wheels built using travis-ci.
See the `numpy wheels`_ building repository for more detail.
.. _numpy wheels : https://github.com/MacPython/numpy-wheels
Other
-----
- Release Notes
- Changelog
Source distribution
-------------------
We build source releases in both .zip and .tar.gz formats.
Release process
===============
Agree on a release schedule
---------------------------
A typical release schedule is one beta, two release candidates and a final
release. It's best to discuss the timing on the mailing list first, in order
for people to get their commits in on time, get doc wiki edits merged, etc.
After a date is set, create a new maintenance/x.y.z branch, add new empty
release notes for the next version in the master branch and update the Trac
Milestones.
Make sure current branch builds a package correctly
---------------------------------------------------
::
git clean -fxd
python setup.py bdist
python setup.py sdist
To actually build the binaries after everything is set up correctly, the
release.sh script can be used. For details of the build process itself, it is
best to read the pavement.py script.
.. note:: The following steps are repeated for the beta(s), release
candidates(s) and the final release.
Check deprecations
------------------
Before the release branch is made, it should be checked that all deprecated
code that should be removed is actually removed, and all new deprecations say
in the docstring or deprecation warning at what version the code will be
removed.
Check the C API version number
------------------------------
The C API version needs to be tracked in three places
- numpy/core/setup_common.py
- numpy/core/code_generators/cversions.txt
- numpy/core/include/numpy/numpyconfig.h
There are three steps to the process.
1. If the API has changed, increment the C_API_VERSION in setup_common.py. The
API is unchanged only if any code compiled against the current API will be
backward compatible with the last released NumPy version. Any changes to
C structures or additions to the public interface will make the new API
not backward compatible.
2. If the C_API_VERSION in the first step has changed, or if the hash of
the API has changed, the cversions.txt file needs to be updated. To check
the hash, run the script numpy/core/cversions.py and note the API hash that
is printed. If that hash does not match the last hash in
numpy/core/code_generators/cversions.txt the hash has changed. Using both
the appropriate C_API_VERSION and hash, add a new entry to cversions.txt.
If the API version was not changed, but the hash differs, you will need to
comment out the previous entry for that API version. For instance, in NumPy
1.9 annotations were added, which changed the hash, but the API was the
same as in 1.8. The hash serves as a check for API changes, but it is not
definitive.
If steps 1 and 2 are done correctly, compiling the release should not give
a warning "API mismatch detect at the beginning of the build".
3. The numpy/core/include/numpy/numpyconfig.h will need a new
NPY_X_Y_API_VERSION macro, where X and Y are the major and minor version
numbers of the release. The value given to that macro only needs to be
increased from the previous version if some of the functions or macros in
the include files were deprecated.
The C ABI version number in numpy/core/setup_common.py should only be
updated for a major release.
Check the release notes
-----------------------
Use `towncrier`_ to build the release note and
commit the changes. This will remove all the fragments from
``doc/release/upcoming_changes`` and add ``doc/release/<version>-note.rst``.
Note that currently towncrier must be installed from its master branch as the
last release (19.2.0) is outdated.
towncrier --version "<version>"
git commit -m"Create release note"
Check that the release notes are up-to-date.
Update the release notes with a Highlights section. Mention some of the
following:
- major new features
- deprecated and removed features
- supported Python versions
- for SciPy, supported NumPy version(s)
- outlook for the near future
.. _towncrier: https://github.com/hawkowl/towncrier
Update the release status and create a release "tag"
----------------------------------------------------
Identify the commit hash of the release, e.g. 1b2e1d63ff.
::
git co 1b2e1d63ff # gives warning about detached head
First, change/check the following variables in ``pavement.py`` depending on the
release version::
RELEASE_NOTES = 'doc/release/1.7.0-notes.rst'
LOG_START = 'v1.6.0'
LOG_END = 'maintenance/1.7.x'
Do any other changes. When you are ready to release, do the following
changes::
diff --git a/setup.py b/setup.py
index b1f53e3..8b36dbe 100755
--- a/setup.py
+++ b/setup.py
@@ -57,7 +57,7 @@ PLATFORMS = ["Windows", "Linux", "Solaris", "Mac OS-
MAJOR = 1
MINOR = 7
MICRO = 0
-ISRELEASED = False
+ISRELEASED = True
VERSION = '%d.%d.%drc1' % (MAJOR, MINOR, MICRO)
# Return the git revision as a string
And make sure the ``VERSION`` variable is set properly.
Now you can make the release commit and tag. We recommend you don't push
the commit or tag immediately, just in case you need to do more cleanup. We
prefer to defer the push of the tag until we're confident this is the exact
form of the released code (see: :ref:`push-tag-and-commit`):
git commit -s -m "REL: Release." setup.py
git tag -s <version>
The ``-s`` flag makes a PGP (usually GPG) signed tag. Please do sign the
release tags.
The release tag should have the release number in the annotation (tag
message). Unfortunately, the name of a tag can be changed without breaking the
signature, the contents of the message cannot.
See: https://github.com/scipy/scipy/issues/4919 for a discussion of signing
release tags, and https://keyring.debian.org/creating-key.html for instructions
on creating a GPG key if you do not have one.
To make your key more readily identifiable as you, consider sending your key
to public keyservers, with a command such as::
gpg --send-keys <yourkeyid>
Update the version of the master branch
---------------------------------------
Increment the release number in setup.py. Release candidates should have "rc1"
(or "rc2", "rcN") appended to the X.Y.Z format.
Also create a new version hash in cversions.txt and a corresponding version
define NPY_x_y_API_VERSION in numpyconfig.h
Trigger the wheel builds
------------------------
See the `MacPython/numpy wheels` repository.
In that repository edit the files:
- ``azure/posix.yml``
- ``azure/windows.yml``.
In both cases, set the ``BUILD_COMMIT`` variable to the current release tag -
e.g. ``v1.19.0``::
$ gvim azure/posix.yml azure/windows.yml
$ git commit -a
$ git push upstream HEAD
Make sure that the release tag has been pushed.
Trigger a build by pushing a commit of your edits to the repository. Note that
you can do this on a branch, but it must be pushed upstream to the
``MacPython/numpy-wheels`` repository to trigger uploads since only
that repo has the appropriate tokens to allow uploads.
The wheels, once built, appear at https://anaconda.org/multibuild-wheels-staging/numpy
Make the release
----------------
Build the changelog and notes for upload with::
paver write_release
Build and archive documentation
-------------------------------
Do::
cd doc/
make dist
to check that the documentation is in a buildable state. Then, after tagging,
create an archive of the documentation in the numpy/doc repo::
# This checks out github.com/numpy/doc and adds (``git add``) the
# documentation to the checked out repo.
make merge-doc
# Now edit the ``index.html`` file in the repo to reflect the new content,
# and commit the changes
git -C build/merge commit -am "Add documentation for <version>"
# Push to numpy/doc repo
git -C build/merge push
Update PyPI
-----------
The wheels and source should be uploaded to PyPI.
You should upload the wheels first, and the source formats last, to make sure
that pip users don't accidentally get a source install when they were
expecting a binary wheel.
You can do this automatically using the ``wheel-uploader`` script from
https://github.com/MacPython/terryfy. Here is the recommended incantation for
downloading all the Windows, Manylinux, OSX wheels and uploading to PyPI. ::
NPY_WHLS=~/wheelhouse # local directory to cache wheel downloads
CDN_URL=https://anaconda.org/multibuild-wheels-staging/numpy/files
wheel-uploader -u $CDN_URL -w $NPY_WHLS -v -s -t win numpy 1.11.1rc1
wheel-uploader -u $CDN_URL -w warehouse -v -s -t macosx numpy 1.11.1rc1
wheel-uploader -u $CDN_URL -w warehouse -v -s -t manylinux1 numpy 1.11.1rc1
The ``-v`` flag gives verbose feedback, ``-s`` causes the script to sign the
wheels with your GPG key before upload. Don't forget to upload the wheels
before the source tarball, so there is no period for which people switch from
an expected binary install to a source install from PyPI.
There are two ways to update the source release on PyPI, the first one is::
$ git clean -fxd # to be safe
$ python setup.py sdist --formats=gztar,zip # to check
# python setup.py sdist --formats=gztar,zip upload --sign
This will ask for your key PGP passphrase, in order to sign the built source
packages.
The second way is to upload the PKG_INFO file inside the sdist dir in the
web interface of PyPI. The source tarball can also be uploaded through this
interface.
.. _push-tag-and-commit:
Push the release tag and commit
-------------------------------
Finally, now you are confident this tag correctly defines the source code that
you released you can push the tag and release commit up to github::
git push # Push release commit
git push upstream <version> # Push tag named <version>
where ``upstream`` points to the main https://github.com/numpy/numpy.git
repository.
Update scipy.org
----------------
A release announcement with a link to the download site should be placed in the
sidebar of the front page of scipy.org.
The scipy.org should be a PR at https://github.com/scipy/scipy.org. The file
that needs modification is ``www/index.rst``. Search for ``News``.
Announce to the lists
---------------------
The release should be announced on the mailing lists of
NumPy and SciPy, to python-announce, and possibly also those of
Matplotlib, IPython and/or Pygame.
During the beta/RC phase, an explicit request for testing the binaries with
several other libraries (SciPy/Matplotlib/Pygame) should be posted on the
mailing list.
Announce to Linux Weekly News
-----------------------------
Email the editor of LWN to let them know of the release. Directions at:
https://lwn.net/op/FAQ.lwn#contact
After the final release
-----------------------
After the final release is announced, a few administrative tasks are left to be
done:
- Forward port changes in the release branch to release notes and release
scripts, if any, to master branch.
- Update the Milestones in Trac.

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# Makefile for Sphinx documentation
#
# PYVER needs to be major.minor, just "3" doesn't work - it will result in
# issues with the amendments to PYTHONPATH and install paths (see DIST_VARS).
# Use explicit "version_info" indexing since make cannot handle colon characters, and
# evaluate it now to allow easier debugging when printing the variable
PYVER:=$(shell python3 -c 'from sys import version_info as v; print("{0}.{1}".format(v[0], v[1]))')
PYTHON = python$(PYVER)
# You can set these variables from the command line.
SPHINXOPTS ?=
SPHINXBUILD ?= LANG=C sphinx-build
PAPER ?=
# For merging a documentation archive into a git checkout of numpy/doc
# Turn a tag like v1.18.0 into 1.18
# Use sed -n -e 's/patttern/match/p' to return a blank value if no match
TAG ?= $(shell git describe --tag | sed -n -e's,v\([1-9]\.[0-9]*\)\.[0-9].*,\1,p')
FILES=
# Internal variables.
PAPEROPT_a4 = -D latex_paper_size=a4
PAPEROPT_letter = -D latex_paper_size=letter
ALLSPHINXOPTS = -WT --keep-going -d build/doctrees $(PAPEROPT_$(PAPER)) \
$(SPHINXOPTS) source
.PHONY: help clean html web pickle htmlhelp latex changes linkcheck \
dist dist-build gitwash-update version-check html-build latex-build \
merge-doc
#------------------------------------------------------------------------------
help:
@echo "Please use \`make <target>' where <target> is one of"
@echo " html to make standalone HTML files"
@echo " html-scipyorg to make standalone HTML files with scipy.org theming"
@echo " pickle to make pickle files (usable by e.g. sphinx-web)"
@echo " htmlhelp to make HTML files and a HTML help project"
@echo " latex to make LaTeX files, you can set PAPER=a4 or PAPER=letter"
@echo " changes to make an overview over all changed/added/deprecated items"
@echo " linkcheck to check all external links for integrity"
@echo " dist PYVER=... to make a distribution-ready tree"
@echo " gitwash-update GITWASH=path/to/gitwash update gitwash developer docs"
@echo " upload USERNAME=... RELEASE=... to upload built docs to docs.scipy.org"
@echo " merge-doc TAG=... to clone numpy/doc and archive documentation into it"
clean:
-rm -rf build/*
find . -name generated -type d -prune -exec rm -rf "{}" ";"
gitwash-update:
rm -rf source/dev/gitwash
install -d source/dev/gitwash
python $(GITWASH)/gitwash_dumper.py source/dev NumPy \
--repo-name=numpy \
--github-user=numpy
cat source/dev/gitwash_links.txt >> source/dev/gitwash/git_links.inc
#------------------------------------------------------------------------------
# Automated generation of all documents
#------------------------------------------------------------------------------
# Build the current numpy version, and extract docs from it.
# We have to be careful of some issues:
#
# - Everything must be done using the same Python version
# - We must use eggs (otherwise they might override PYTHONPATH on import).
# - Different versions of easy_install install to different directories (!)
#
INSTALL_DIR = $(CURDIR)/build/inst-dist
INSTALL_PPH = $(INSTALL_DIR)/lib/python$(PYVER)/site-packages:$(INSTALL_DIR)/local/lib/python$(PYVER)/site-packages:$(INSTALL_DIR)/lib/python$(PYVER)/dist-packages:$(INSTALL_DIR)/local/lib/python$(PYVER)/dist-packages
UPLOAD_DIR=/srv/docs_scipy_org/doc/numpy-$(RELEASE)
DIST_VARS=SPHINXBUILD="LANG=C PYTHONPATH=$(INSTALL_PPH) python$(PYVER) `which sphinx-build`" PYTHON="PYTHONPATH=$(INSTALL_PPH) python$(PYVER)"
NUMPYVER:=$(shell $(PYTHON) -c "import numpy; print(numpy.version.git_revision[:10])" 2>/dev/null)
GITVER ?= $(shell cd ..; $(PYTHON) -c "from setup import git_version; \
print(git_version()[:10])")
version-check:
ifeq "$(GITVER)" "Unknown"
# @echo sdist build with unlabeled sources
else ifeq ("", "$(NUMPYVER)")
@echo numpy not found, cannot build documentation without successful \"import numpy\"
@exit 1
else ifneq ($(NUMPYVER),$(GITVER))
@echo installed numpy $(NUMPYVER) != current repo git version \'$(GITVER)\'
@echo use '"make dist"' or '"GITVER=$(NUMPYVER) make $(MAKECMDGOALS) ..."'
@exit 1
else
# for testing
# @echo installed numpy $(NUMPYVER) matches git version $(GITVER); exit 1
endif
dist: build/dist.tar.gz
build/dist.tar.gz:
make $(DIST_VARS) real-dist
real-dist: dist-build html-build
test -d build/latex || make latex-build
make -C build/latex all-pdf
-rm -rf build/dist
cp -r build/html build/dist
cd build/html && zip -9r ../dist/numpy-html.zip .
cp build/latex/numpy-ref.pdf build/dist
cp build/latex/numpy-user.pdf build/dist
cd build/dist && tar czf ../dist.tar.gz *
chmod ug=rwX,o=rX -R build/dist
find build/dist -type d -print0 | xargs -0r chmod g+s
dist-build:
rm -f ../dist/*.egg
cd .. && $(PYTHON) setup.py bdist_egg
install -d $(subst :, ,$(INSTALL_PPH))
$(PYTHON) `which easy_install` --prefix=$(INSTALL_DIR) ../dist/*.egg
upload: build/dist.tar.gz
# SSH must be correctly configured for this to work.
# Assumes that ``make dist`` was already run
# Example usage: ``make upload USERNAME=rgommers RELEASE=1.10.1``
ssh $(USERNAME)@docs.scipy.org mkdir $(UPLOAD_DIR)
scp build/dist.tar.gz $(USERNAME)@docs.scipy.org:$(UPLOAD_DIR)
ssh $(USERNAME)@docs.scipy.org tar xvC $(UPLOAD_DIR) \
-zf $(UPLOAD_DIR)/dist.tar.gz
ssh $(USERNAME)@docs.scipy.org mv $(UPLOAD_DIR)/numpy-ref.pdf \
$(UPLOAD_DIR)/numpy-ref-$(RELEASE).pdf
ssh $(USERNAME)@docs.scipy.org mv $(UPLOAD_DIR)/numpy-user.pdf \
$(UPLOAD_DIR)/numpy-user-$(RELEASE).pdf
ssh $(USERNAME)@docs.scipy.org mv $(UPLOAD_DIR)/numpy-html.zip \
$(UPLOAD_DIR)/numpy-html-$(RELEASE).zip
ssh $(USERNAME)@docs.scipy.org rm $(UPLOAD_DIR)/dist.tar.gz
ssh $(USERNAME)@docs.scipy.org ln -snf numpy-$(RELEASE) /srv/docs_scipy_org/doc/numpy
merge-doc: build/dist.tar.gz
ifeq "$(TAG)" ""
echo tag "$(TAG)" not of the form 1.18;
exit 1;
endif
@# Only clone if the directory does not exist
@if ! test -d build/merge; then \
git clone https://github.com/numpy/doc build/merge; \
fi;
@# Remove any old content and copy in the new, add it to git
-rm -rf build/merge/$(TAG)/*
-mkdir -p build/merge/$(TAG)
@# -C changes working directory
tar -C build/merge/$(TAG) -xf build/dist.tar.gz
git -C build/merge add $(TAG)
@# For now, the user must do this. If it is onerous, automate it and change
@# the instructions in doc/HOWTO_RELEASE.rst.txt
@echo " "
@echo New documentation archive added to ./build/merge.
@echo Now add/modify the appropriate section after
@echo " <!-- insert here -->"
@echo in build/merge/index.html,
@echo then \"git commit\", \"git push\"
#------------------------------------------------------------------------------
# Basic Sphinx generation rules for different formats
#------------------------------------------------------------------------------
generate: build/generate-stamp
build/generate-stamp: $(wildcard source/reference/*.rst)
mkdir -p build
touch build/generate-stamp
html: version-check html-build
html-build: generate
mkdir -p build/html build/doctrees
$(SPHINXBUILD) -b html $(ALLSPHINXOPTS) build/html $(FILES)
$(PYTHON) postprocess.py html build/html/*.html
@echo
@echo "Build finished. The HTML pages are in build/html."
html-scipyorg:
mkdir -p build/html build/doctrees
$(SPHINXBUILD) -t scipyorg -b html $(ALLSPHINXOPTS) build/html-scipyorg $(FILES)
@echo
@echo "Build finished. The HTML pages are in build/html."
pickle: generate version-check
mkdir -p build/pickle build/doctrees
$(SPHINXBUILD) -b pickle $(ALLSPHINXOPTS) build/pickle $(FILES)
@echo
@echo "Build finished; now you can process the pickle files or run"
@echo " sphinx-web build/pickle"
@echo "to start the sphinx-web server."
web: pickle
htmlhelp: generate version-check
mkdir -p build/htmlhelp build/doctrees
$(SPHINXBUILD) -b htmlhelp $(ALLSPHINXOPTS) build/htmlhelp $(FILES)
@echo
@echo "Build finished; now you can run HTML Help Workshop with the" \
".hhp project file in build/htmlhelp."
htmlhelp-build: htmlhelp build/htmlhelp/numpy.chm
%.chm: %.hhp
-hhc.exe $^
qthelp: generate version-check
mkdir -p build/qthelp build/doctrees
$(SPHINXBUILD) -b qthelp $(ALLSPHINXOPTS) build/qthelp $(FILES)
latex: version-check latex-build
latex-build: generate
mkdir -p build/latex build/doctrees
$(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) build/latex $(FILES)
$(PYTHON) postprocess.py tex build/latex/*.tex
perl -pi -e 's/LATEXOPTS =/LATEXOPTS ?= --halt-on-error/' build/latex/Makefile
@echo
@echo "Build finished; the LaTeX files are in build/latex."
@echo "Run \`make all-pdf' or \`make all-ps' in that directory to" \
"run these through (pdf)latex."
coverage: build version-check
mkdir -p build/coverage build/doctrees
$(SPHINXBUILD) -b coverage $(ALLSPHINXOPTS) build/coverage $(FILES)
@echo "Coverage finished; see c.txt and python.txt in build/coverage"
changes: generate version-check
mkdir -p build/changes build/doctrees
$(SPHINXBUILD) -b changes $(ALLSPHINXOPTS) build/changes $(FILES)
@echo
@echo "The overview file is in build/changes."
linkcheck: generate version-check
mkdir -p build/linkcheck build/doctrees
$(SPHINXBUILD) -b linkcheck $(ALLSPHINXOPTS) build/linkcheck $(FILES)
@echo
@echo "Link check complete; look for any errors in the above output " \
"or in build/linkcheck/output.txt."
texinfo:
$(SPHINXBUILD) -b texinfo $(ALLSPHINXOPTS) build/texinfo
@echo
@echo "Build finished. The Texinfo files are in build/texinfo."
@echo "Run \`make' in that directory to run these through makeinfo" \
"(use \`make info' here to do that automatically)."
info:
$(SPHINXBUILD) -b texinfo $(ALLSPHINXOPTS) build/texinfo
@echo "Running Texinfo files through makeinfo..."
make -C build/texinfo info
@echo "makeinfo finished; the Info files are in build/texinfo."

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@ -0,0 +1,903 @@
.. -*-rst-*-
*********************************************
Developer notes on the transition to Python 3
*********************************************
:date: 2010-07-11
:author: Charles R. Harris
:author: Pauli Virtanen
General
=======
NumPy has now been ported to Python 3.
Some glitches may still be present; however, we are not aware of any
significant ones, the test suite passes.
Resources
---------
Information on porting to 3K:
- https://wiki.python.org/moin/cporting
- https://wiki.python.org/moin/PortingExtensionModulesToPy3k
Prerequisites
-------------
The Nose test framework has currently (Nov 2009) no released Python 3
compatible version. Its 3K SVN branch, however, works quite well:
- http://python-nose.googlecode.com/svn/branches/py3k
Known semantic changes on Py2
=============================
As a side effect, the Py3 adaptation has caused the following semantic
changes that are visible on Py2.
* Objects (except bytes and str) that implement the PEP 3118 array interface
will behave as ndarrays in `array(...)` and `asarray(...)`; the same way
as if they had ``__array_interface__`` defined.
* Otherwise, there are no known semantic changes.
Known semantic changes on Py3
=============================
The following semantic changes have been made on Py3:
* Division: integer division is by default true_divide, also for arrays.
* Dtype field names are Unicode.
* Only unicode dtype field titles are included in fields dict.
* :pep:`3118` buffer objects will behave differently from Py2 buffer objects
when used as an argument to `array(...)`, `asarray(...)`.
In Py2, they would cast to an object array.
In Py3, they cast similarly as objects having an
``__array_interface__`` attribute, ie., they behave as if they were
an ndarray view on the data.
Python code
===========
2to3 in setup.py
----------------
Currently, setup.py calls 2to3 automatically to convert Python sources
to Python 3 ones, and stores the results under::
build/py3k
Only changed files will be re-converted when setup.py is called a second
time, making development much faster.
Currently, this seems to handle all of the necessary Python code
conversion.
Not all of the 2to3 transformations are appropriate for all files.
Especially, 2to3 seems to be quite trigger-happy in replacing e.g.
``unicode`` by ``str`` which causes problems in ``defchararray.py``.
For files that need special handling, add entries to
``tools/py3tool.py``.
numpy.compat.py3k
-----------------
There are some utility functions needed for 3K compatibility in
``numpy.compat.py3k`` -- they can be imported from ``numpy.compat``:
- bytes, unicode: bytes and unicode constructors
- asbytes: convert string to bytes (no-op on Py2)
- asbytes_nested: convert strings in lists to Bytes
- asunicode: convert string to unicode
- asunicode_nested: convert strings in lists to Unicode
- asstr: convert item to the str type
- getexception: get current exception (see below)
- isfileobj: detect Python file objects
- strchar: character for Unicode (Py3) or Strings (Py2)
- open_latin1: open file in the latin1 text mode
More can be added as needed.
numpy.f2py
----------
F2py is ported to Py3.
Bytes vs. strings
-----------------
At many points in NumPy, bytes literals are needed. These can be created via
numpy.compat.asbytes and asbytes_nested.
Exception syntax
----------------
Syntax change: "except FooException, bar:" -> "except FooException as bar:"
This is taken care by 2to3, however.
Relative imports
----------------
The new relative import syntax,
from . import foo
is not available on Py2.4, so we can't simply use it.
Using absolute imports everywhere is probably OK, if they just happen
to work.
2to3, however, converts the old syntax to new syntax, so as long as we
use the converter, it takes care of most parts.
Print
-----
The Print statement changed to a builtin function in Py3.
Also this is taken care of by 2to3.
types module
------------
The following items were removed from `types` module in Py3:
- StringType (Py3: `bytes` is equivalent, to some degree)
- InstanceType (Py3: ???)
- IntType (Py3: no equivalent)
- LongType (Py3: equivalent `long`)
- FloatType (Py3: equivalent `float`)
- BooleanType (Py3: equivalent `bool`)
- ComplexType (Py3: equivalent `complex`)
- UnicodeType (Py3: equivalent `str`)
- BufferType (Py3: more-or-less equivalent `memoryview`)
In ``numerictypes.py``, the "common" types were replaced by their
plain equivalents, and `IntType` was dropped.
numpy.core.numerictypes
-----------------------
In numerictypes, types on Python 3 were changed so that:
=========== ============
Scalar type Value
=========== ============
str_ This is the basic Unicode string type on Py3
bytes_ This is the basic Byte-string type on Py3
string_ bytes_ alias
unicode_ str_ alias
=========== ============
numpy.loadtxt et al
-------------------
These routines are difficult to duck-type to read both Unicode and
Bytes input.
I assumed they are meant for reading Bytes streams -- this is probably
the far more common use case with scientific data.
Cyclic imports
--------------
Python 3 is less forgiving about cyclic imports than Python 2. Cycles
need to be broken to have the same code work both on Python 2 and 3.
C Code
======
NPY_PY3K
--------
A #define in config.h, defined when building for Py3.
.. todo::
Currently, this is generated as a part of the config.
Is this sensible (we could also use Py_VERSION_HEX)?
private/npy_3kcompat.h
----------------------
Convenience macros for Python 3 support:
- PyInt -> PyLong on Py3
- PyString -> PyBytes on Py3
- PyUString -> PyUnicode on Py3 and PyString on Py2
- PyBytes on Py2
- PyUnicode_ConcatAndDel, PyUnicode_Concat2
- Py_SIZE et al., for older Python versions
- npy_PyFile_Dup, etc. to get FILE* from Py3 file objects
- PyObject_Cmp, convenience comparison function on Py3
- NpyCapsule_* helpers: PyCObject
Any new ones that need to be added should be added in this file.
.. todo::
Remove PyString_* eventually -- having a call to one of these in NumPy
sources is a sign of an error...
ob_type, ob_size
----------------
These use Py_SIZE, etc. macros now. The macros are also defined in
npy_3kcompat.h for the Python versions that don't have them natively.
Py_TPFLAGS_CHECKTYPES
---------------------
Python 3 no longer supports type coercion in arithmetic.
Py_TPFLAGS_CHECKTYPES is now on by default, and so the C-level
interface, ``nb_*`` methods, still unconditionally receive whatever
types as their two arguments.
However, this will affect Python-level code: previously if you
inherited from a Py_TPFLAGS_CHECKTYPES enabled class that implemented
a ``__mul__`` method, the same ``__mul__`` method would still be
called also as when a ``__rmul__`` was required, but with swapped
arguments (see Python/Objects/typeobject.c:wrap_binaryfunc_r).
However, on Python 3, arguments are swapped only if both are of same
(sub-)type, and otherwise things fail.
This means that ``ndarray``-derived subclasses must now implement all
relevant ``__r*__`` methods, since they cannot any more automatically
fall back to ndarray code.
PyNumberMethods
---------------
The structures have been converted to the new format:
- number.c
- scalartypes.c.src
- scalarmathmodule.c.src
The slots np_divide, np_long, np_oct, np_hex, and np_inplace_divide
have gone away. The slot np_int is what np_long used to be, tp_divide
is now tp_floor_divide, and np_inplace_divide is now
np_inplace_floor_divide.
These have simply been #ifdef'd out on Py3.
The Py2/Py3 compatible structure definition looks like::
static PyNumberMethods @name@_as_number = {
(binaryfunc)0, /*nb_add*/
(binaryfunc)0, /*nb_subtract*/
(binaryfunc)0, /*nb_multiply*/
#if defined(NPY_PY3K)
#else
(binaryfunc)0, /*nb_divide*/
#endif
(binaryfunc)0, /*nb_remainder*/
(binaryfunc)0, /*nb_divmod*/
(ternaryfunc)0, /*nb_power*/
(unaryfunc)0,
(unaryfunc)0, /*nb_pos*/
(unaryfunc)0, /*nb_abs*/
#if defined(NPY_PY3K)
(inquiry)0, /*nb_bool*/
#else
(inquiry)0, /*nb_nonzero*/
#endif
(unaryfunc)0, /*nb_invert*/
(binaryfunc)0, /*nb_lshift*/
(binaryfunc)0, /*nb_rshift*/
(binaryfunc)0, /*nb_and*/
(binaryfunc)0, /*nb_xor*/
(binaryfunc)0, /*nb_or*/
#if defined(NPY_PY3K)
#else
0, /*nb_coerce*/
#endif
(unaryfunc)0, /*nb_int*/
#if defined(NPY_PY3K)
(unaryfunc)0, /*nb_reserved*/
#else
(unaryfunc)0, /*nb_long*/
#endif
(unaryfunc)0, /*nb_float*/
#if defined(NPY_PY3K)
#else
(unaryfunc)0, /*nb_oct*/
(unaryfunc)0, /*nb_hex*/
#endif
0, /*inplace_add*/
0, /*inplace_subtract*/
0, /*inplace_multiply*/
#if defined(NPY_PY3K)
#else
0, /*inplace_divide*/
#endif
0, /*inplace_remainder*/
0, /*inplace_power*/
0, /*inplace_lshift*/
0, /*inplace_rshift*/
0, /*inplace_and*/
0, /*inplace_xor*/
0, /*inplace_or*/
(binaryfunc)0, /*nb_floor_divide*/
(binaryfunc)0, /*nb_true_divide*/
0, /*nb_inplace_floor_divide*/
0, /*nb_inplace_true_divide*/
(unaryfunc)NULL, /*nb_index*/
};
PyBuffer (provider)
-------------------
PyBuffer usage is widely spread in multiarray:
1) The void scalar makes use of buffers
2) Multiarray has methods for creating buffers etc. explicitly
3) Arrays can be created from buffers etc.
4) The .data attribute of an array is a buffer
Py3 introduces the PEP 3118 buffer protocol as the *only* protocol,
so we must implement it.
The exporter parts of the PEP 3118 buffer protocol are currently
implemented in ``buffer.c`` for arrays, and in ``scalartypes.c.src``
for generic array scalars. The generic array scalar exporter, however,
doesn't currently produce format strings, which needs to be fixed.
Also some code also stops working when ``bf_releasebuffer`` is
defined. Most importantly, ``PyArg_ParseTuple("s#", ...)`` refuses to
return a buffer if ``bf_releasebuffer`` is present. For this reason,
the buffer interface for arrays is implemented currently *without*
defining ``bf_releasebuffer`` at all. This forces us to go through
some additional work.
There are a couple of places that need further attention:
- VOID_getitem
In some cases, this returns a buffer object on Python 2. On Python 3,
there is no stand-alone buffer object, so we return a byte array instead.
The Py2/Py3 compatible PyBufferMethods definition looks like::
NPY_NO_EXPORT PyBufferProcs array_as_buffer = {
#if !defined(NPY_PY3K)
#if PY_VERSION_HEX >= 0x02050000
(readbufferproc)array_getreadbuf, /*bf_getreadbuffer*/
(writebufferproc)array_getwritebuf, /*bf_getwritebuffer*/
(segcountproc)array_getsegcount, /*bf_getsegcount*/
(charbufferproc)array_getcharbuf, /*bf_getcharbuffer*/
#else
(getreadbufferproc)array_getreadbuf, /*bf_getreadbuffer*/
(getwritebufferproc)array_getwritebuf, /*bf_getwritebuffer*/
(getsegcountproc)array_getsegcount, /*bf_getsegcount*/
(getcharbufferproc)array_getcharbuf, /*bf_getcharbuffer*/
#endif
#endif
#if PY_VERSION_HEX >= 0x02060000
(getbufferproc)array_getbuffer, /*bf_getbuffer*/
(releasebufferproc)array_releasebuffer, /*bf_releasebuffer*/
#endif
};
.. todo::
Produce PEP 3118 format strings for array scalar objects.
.. todo::
There's stuff to clean up in numarray/_capi.c
PyBuffer (consumer)
-------------------
There are two places in which we may want to be able to consume buffer
objects and cast them to ndarrays:
1) `multiarray.frombuffer`, ie., ``PyArray_FromAny``
The frombuffer returns only arrays of a fixed dtype. It does not
make sense to support PEP 3118 at this location, since not much
would be gained from that -- the backward compatibility functions
using the old array interface still work.
So no changes needed here.
2) `multiarray.array`, ie., ``PyArray_FromAny``
In general, we would like to handle :pep:`3118` buffers in the same way
as ``__array_interface__`` objects. Hence, we want to be able to cast
them to arrays already in ``PyArray_FromAny``.
Hence, ``PyArray_FromAny`` needs additions.
There are a few caveats in allowing :pep:`3118` buffers in
``PyArray_FromAny``:
a) `bytes` (and `str` on Py2) objects offer a buffer interface that
specifies them as 1-D array of bytes.
Previously ``PyArray_FromAny`` has cast these to 'S#' dtypes. We
don't want to change this, since will cause problems in many places.
We do, however, want to allow other objects that provide 1-D byte arrays
to be cast to 1-D ndarrays and not 'S#' arrays -- for instance, 'S#'
arrays tend to strip trailing NUL characters.
So what is done in ``PyArray_FromAny`` currently is that:
- Presence of :pep:`3118` buffer interface is checked before checking
for array interface. If it is present *and* the object is not
`bytes` object, then it is used for creating a view on the buffer.
- We also check in ``discover_depth`` and ``_array_find_type`` for the
3118 buffers, so that::
array([some_3118_object])
will treat the object similarly as it would handle an `ndarray`.
However, again, bytes (and unicode) have priority and will not be
handled as buffer objects.
This amounts to possible semantic changes:
- ``array(buffer)`` will no longer create an object array
``array([buffer], dtype='O')``, but will instead expand to a view
on the buffer.
.. todo::
Take a second look at places that used PyBuffer_FromMemory and
PyBuffer_FromReadWriteMemory -- what can be done with these?
.. todo::
There's some buffer code in numarray/_capi.c that needs to be addressed.
PyBuffer (object)
-----------------
Since there is a native buffer object in Py3, the `memoryview`, the
`newbuffer` and `getbuffer` functions are removed from `multiarray` in
Py3: their functionality is taken over by the new `memoryview` object.
PyString
--------
There is no PyString in Py3, everything is either Bytes or Unicode.
Unicode is also preferred in many places, e.g., in __dict__.
There are two issues related to the str/bytes change:
1) Return values etc. should prefer unicode
2) The 'S' dtype
This entry discusses return values etc. only, the 'S' dtype is a
separate topic.
All uses of PyString in NumPy should be changed to one of
- PyBytes: one-byte character strings in Py2 and Py3
- PyUString (defined in npy_3kconfig.h): PyString in Py2, PyUnicode in Py3
- PyUnicode: UCS in Py2 and Py3
In many cases the conversion only entails replacing PyString with
PyUString.
PyString is currently defined to PyBytes in npy_3kcompat.h, for making
things to build. This definition will be removed when Py3 support is
finished.
Where ``*_AsStringAndSize`` is used, more care needs to be taken, as
encoding Unicode to Bytes may needed. If this cannot be avoided, the
encoding should be ASCII, unless there is a very strong reason to do
otherwise. Especially, I don't believe we should silently fall back to
UTF-8 -- raising an exception may be a better choice.
Exceptions should use PyUnicode_AsUnicodeEscape -- this should result
to an ASCII-clean string that is appropriate for the exception
message.
Some specific decisions that have been made so far:
* descriptor.c: dtype field names are UString
At some places in NumPy code, there are some guards for Unicode field
names. However, the dtype constructor accepts only strings as field names,
so we should assume field names are *always* UString.
* descriptor.c: field titles can be arbitrary objects.
If they are UString (or, on Py2, Bytes or Unicode), insert to fields dict.
* descriptor.c: dtype strings are Unicode.
* descriptor.c: datetime tuple contains Bytes only.
* repr() and str() should return UString
* comparison between Unicode and Bytes is not defined in Py3
* Type codes in numerictypes.typeInfo dict are Unicode
* Func name in errobj is Bytes (should be forced to ASCII)
.. todo::
tp_doc -- it's a char* pointer, but what is the encoding?
Check esp. lib/src/_compiled_base
Currently, UTF-8 is assumed.
.. todo::
ufunc names -- again, what's the encoding?
.. todo::
Cleanup to do later on: Replace all occurrences of PyString by
PyBytes, PyUnicode, or PyUString.
.. todo::
Revise errobj decision?
.. todo::
Check that non-UString field names are not accepted anywhere.
PyUnicode
---------
PyUnicode in Py3 is pretty much as it was in Py2, except that it is
now the only "real" string type.
In Py3, Unicode and Bytes are not comparable, ie., 'a' != b'a'. NumPy
comparison routines were handled to act in the same way, leaving
comparison between Unicode and Bytes undefined.
.. todo::
Check that indeed all comparison routines were changed.
Fate of the 'S' dtype
---------------------
On Python 3, the 'S' dtype will still be Bytes.
However,::
str, str_ == unicode_
PyInt
-----
There is no limited-range integer type any more in Py3. It makes no
sense to inherit NumPy ints from Py3 ints.
Currently, the following is done:
1) NumPy's integer types no longer inherit from Python integer.
2) int is taken dtype-equivalent to NPY_LONG
3) ints are converted to NPY_LONG
PyInt methods are currently replaced by PyLong, via macros in npy_3kcompat.h.
Dtype decision rules were changed accordingly, so that NumPy understands
Py3 int translate to NPY_LONG as far as dtypes are concerned.
array([1]).dtype will be the default NPY_LONG integer.
.. todo::
Not inheriting from `int` on Python 3 makes the following not work:
``np.intp("0xff", 16)`` -- because the NumPy type does not take
the second argument. This could perhaps be fixed...
Divide
------
The Divide operation is no more.
Calls to PyNumber_Divide were replaced by FloorDivide or TrueDivide,
as appropriate.
The PyNumberMethods entry is #ifdef'd out on Py3, see above.
tp_compare, PyObject_Compare
----------------------------
The compare method has vanished, and is replaced with richcompare.
We just #ifdef the compare methods out on Py3.
New richcompare methods were implemented for:
* flagsobject.c
On the consumer side, we have a convenience wrapper in npy_3kcompat.h
providing PyObject_Cmp also on Py3.
Pickling
--------
The ndarray and dtype __setstate__ were modified to be
backward-compatible with Py3: they need to accept a Unicode endian
character, and Unicode data since that's what Py2 str is unpickled to
in Py3.
An encoding assumption is required for backward compatibility: the user
must do
loads(f, encoding='latin1')
to successfully read pickles created by Py2.
.. todo::
Forward compatibility? Is it even possible?
For sure, we are not knowingly going to store data in PyUnicode,
so probably the only way for forward compatibility is to implement
a custom Unpickler for Py2?
.. todo::
If forward compatibility is not possible, aim to store also the endian
character as Bytes...
Module initialization
---------------------
The module initialization API changed in Python 3.1.
Most NumPy modules are now converted.
PyTypeObject
------------
The PyTypeObject of py3k is binary compatible with the py2k version and the
old initializers should work. However, there are several considerations to
keep in mind.
1) Because the first three slots are now part of a struct some compilers issue
warnings if they are initialized in the old way.
2) The compare slot has been made reserved in order to preserve binary
compatibility while the tp_compare function went away. The tp_richcompare
function has replaced it and we need to use that slot instead. This will
likely require modifications in the searchsorted functions and generic sorts
that currently use the compare function.
3) The previous numpy practice of initializing the COUNT_ALLOCS slots was
bogus. They are not supposed to be explicitly initialized and were out of
place in any case because an extra base slot was added in python 2.6.
Because of these facts it is better to use #ifdefs to bring the old
initializers up to py3k snuff rather than just fill the tp_richcompare
slot. They also serve to mark the places where changes have been
made. Note that explicit initialization can stop once none of the
remaining entries are non-zero, because zero is the default value that
variables with non-local linkage receive.
The Py2/Py3 compatible TypeObject definition looks like::
NPY_NO_EXPORT PyTypeObject Foo_Type = {
#if defined(NPY_PY3K)
PyVarObject_HEAD_INIT(0,0)
#else
PyObject_HEAD_INIT(0)
0, /* ob_size */
#endif
"numpy.foo" /* tp_name */
0, /* tp_basicsize */
0, /* tp_itemsize */
/* methods */
0, /* tp_dealloc */
0, /* tp_print */
0, /* tp_getattr */
0, /* tp_setattr */
#if defined(NPY_PY3K)
(void *)0, /* tp_reserved */
#else
0, /* tp_compare */
#endif
0, /* tp_repr */
0, /* tp_as_number */
0, /* tp_as_sequence */
0, /* tp_as_mapping */
0, /* tp_hash */
0, /* tp_call */
0, /* tp_str */
0, /* tp_getattro */
0, /* tp_setattro */
0, /* tp_as_buffer */
0, /* tp_flags */
0, /* tp_doc */
0, /* tp_traverse */
0, /* tp_clear */
0, /* tp_richcompare */
0, /* tp_weaklistoffset */
0, /* tp_iter */
0, /* tp_iternext */
0, /* tp_methods */
0, /* tp_members */
0, /* tp_getset */
0, /* tp_base */
0, /* tp_dict */
0, /* tp_descr_get */
0, /* tp_descr_set */
0, /* tp_dictoffset */
0, /* tp_init */
0, /* tp_alloc */
0, /* tp_new */
0, /* tp_free */
0, /* tp_is_gc */
0, /* tp_bases */
0, /* tp_mro */
0, /* tp_cache */
0, /* tp_subclasses */
0, /* tp_weaklist */
0, /* tp_del */
0 /* tp_version_tag (2.6) */
};
PySequenceMethods
-----------------
Types with tp_as_sequence defined
* multiarray/descriptor.c
* multiarray/scalartypes.c.src
* multiarray/arrayobject.c
PySequenceMethods in py3k are binary compatible with py2k, but some of the
slots have gone away. I suspect this means some functions need redefining so
the semantics of the slots needs to be checked::
PySequenceMethods foo_sequence_methods = {
(lenfunc)0, /* sq_length */
(binaryfunc)0, /* sq_concat */
(ssizeargfunc)0, /* sq_repeat */
(ssizeargfunc)0, /* sq_item */
(void *)0, /* nee sq_slice */
(ssizeobjargproc)0, /* sq_ass_item */
(void *)0, /* nee sq_ass_slice */
(objobjproc)0, /* sq_contains */
(binaryfunc)0, /* sq_inplace_concat */
(ssizeargfunc)0 /* sq_inplace_repeat */
};
PyMappingMethods
----------------
Types with tp_as_mapping defined
* multiarray/descriptor.c
* multiarray/iterators.c
* multiarray/scalartypes.c.src
* multiarray/flagsobject.c
* multiarray/arrayobject.c
PyMappingMethods in py3k look to be the same as in py2k. The semantics
of the slots needs to be checked::
PyMappingMethods foo_mapping_methods = {
(lenfunc)0, /* mp_length */
(binaryfunc)0, /* mp_subscript */
(objobjargproc)0 /* mp_ass_subscript */
};
PyFile
------
Many of the PyFile items have disappeared:
1) PyFile_Type
2) PyFile_AsFile
3) PyFile_FromString
Most importantly, in Py3 there is no way to extract a FILE* pointer
from the Python file object. There are, however, new PyFile_* functions
for writing and reading data from the file.
Compatibility wrappers that return a dup-ed `fdopen` file pointer are
in private/npy_3kcompat.h. This causes more flushing to be necessary,
but it appears there is no alternative solution. The FILE pointer so
obtained must be closed with fclose after use.
.. todo::
Should probably be done much later on...
Adapt all NumPy I/O to use the PyFile_* methods or the low-level
IO routines. In any case, it's unlikely that C stdio can be used any more.
Perhaps using PyFile_* makes numpy.tofile e.g. to a gzip to work?
READONLY
--------
The RO alias for READONLY is no more.
These were replaced, as READONLY is present also on Py2.
PyOS
----
Deprecations:
1) PyOS_ascii_strtod -> PyOS_double_from_string;
curiously enough, PyOS_ascii_strtod is not only deprecated but also
causes segfaults
PyInstance
----------
There are some checks for PyInstance in ``common.c`` and ``ctors.c``.
Currently, ``PyInstance_Check`` is just #ifdef'd out for Py3. This is,
possibly, not the correct thing to do.
.. todo::
Do the right thing for PyInstance checks.
PyCObject / PyCapsule
---------------------
The PyCObject API is removed in Python 3.2, so we need to rewrite it
using PyCapsule.
NumPy was changed to use the Capsule API, using NpyCapsule* wrappers.

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This file contains a walkthrough of the NumPy 1.14.5 release on Linux, modified
for building on azure and uploading to anaconda.org
The commands can be copied into the command line, but be sure to
replace 1.14.5 by the correct version.
This should be read together with the general directions in `releasing`.
Release Walkthrough
====================
Note that in the code snippets below, ``upstream`` refers to the root repository on
github and ``origin`` to a fork in your personal account. You may need to make adjustments
if you have not forked the repository but simply cloned it locally. You can
also edit ``.git/config`` and add ``upstream`` if it isn't already present.
Backport Pull Requests
----------------------
Changes that have been marked for this release must be backported to the
maintenance/1.14.x branch.
Update Release documentation
----------------------------
The file ``doc/changelog/1.14.5-changelog.rst`` should be updated to reflect
the final list of changes and contributors. This text can be generated by::
$ python tools/changelog.py $GITHUB v1.14.4..maintenance/1.14.x > doc/changelog/1.14.5-changelog.rst
where ``GITHUB`` contains your github access token. This text may also be
appended to ``doc/release/1.14.5-notes.rst`` for release updates, though not
for new releases like ``1.14.0``, as the changelogs for ``*.0`` releases tend to be
excessively long. The ``doc/source/release.rst`` file should also be
updated with a link to the new release notes. These changes should be committed
to the maintenance branch, and later will be forward ported to master.
Finish the Release Note
-----------------------
.. note:
This has changed now that we use ``towncrier``. See the instructions for
creating the release note in ``doc/release/upcoming_changes/README.rst``.
Fill out the release note ``doc/release/1.14.5-notes.rst`` calling out
significant changes.
Prepare the release commit
--------------------------
Checkout the branch for the release, make sure it is up to date, and clean the
repository::
$ git checkout maintenance/1.14.x
$ git pull upstream maintenance/1.14.x
$ git submodule update
$ git clean -xdfq
Edit pavement.py and setup.py as detailed in HOWTO_RELEASE::
$ gvim pavement.py setup.py
$ git commit -a -m"REL: NumPy 1.14.5 release."
Sanity check::
$ python3 runtests.py -m "full"
Push this release directly onto the end of the maintenance branch. This
requires write permission to the numpy repository::
$ git push upstream maintenance/1.14.x
As an example, see the 1.14.3 REL commit: `<https://github.com/numpy/numpy/commit/73299826729be58cec179b52c656adfcaefada93>`_.
Build source releases
---------------------
Paver is used to build the source releases. It will create the ``release`` and
``release/installers`` directories and put the ``*.zip`` and ``*.tar.gz``
source releases in the latter. ::
$ python3 -m cython --version # check for correct cython version
$ paver sdist # sdist will do a git clean -xdf, so we omit that
Build wheels
------------
Trigger the wheels build by pointing the numpy-wheels repository at this
commit. This can take up to an hour. The numpy-wheels repository is cloned from
`<https://github.com/MacPython/numpy-wheels>`_. Start with a pull as the repo
may have been accessed and changed by someone else and a push will fail::
$ cd ../numpy-wheels
$ git pull upstream master
$ git branch <new version> # only when starting new numpy version
$ git checkout v1.14.x # v1.14.x already existed for the 1.14.4 release
Edit the ``azure/posix.yml`` and ``azure/windows.yml`` files to make sure they
have the correct version, and put in the commit hash for the ``REL`` commit
created above for ``BUILD_COMMIT``, see an _example::
$ gvim azure/posix.yml azure/windows.yml
$ git commit -a
$ git push upstream HEAD
Now wait. If you get nervous at the amount of time taken -- the builds can take
a while -- you can check the build progress by following the links
provided at `<https://github.com/MacPython/numpy-wheels>`_ to check the
build status. Check if all the needed wheels have been built and
uploaded before proceeding. There should currently be 21 of them at
`<https://anaconda.org/multibuild-wheels-staging/numpy/files>`_, 3 for Mac, 6
for Windows, and 12 for Linux.
.. example_: https://github.com/MacPython/numpy-wheels/pull/80/commits/cbf4af4
Note that sometimes builds, like tests, fail for unrelated reasons and
you will need to restart them.
Download wheels
---------------
When the wheels have all been successfully built, download them using the ``wheel-uploader``
in the ``terryfy`` repository. The terryfy repository may be cloned from
`<https://github.com/MacPython/terryfy>`_ if you don't already have it. The
wheels can also be uploaded using the ``wheel-uploader``, but we prefer to
download all the wheels to the ``../numpy/release/installers`` directory and
upload later using ``twine``::
$ cd ../terryfy
$ git pull upstream master
$ CDN_URL=https://anaconda.org/multibuild-wheels-staging/numpy/files
$ NPY_WHLS=../numpy/release/installers
$ ./wheel-uploader -u $CDN_URL -n -v -w $NPY_WHLS -t win numpy 1.14.5
$ ./wheel-uploader -u $CDN_URL -n -v -w $NPY_WHLS -t manylinux1 numpy 1.14.5
$ ./wheel-uploader -u $CDN_URL -n -v -w $NPY_WHLS -t macosx numpy 1.14.5
If you do this often, consider making CDN_URL and NPY_WHLS part of your default
environment.
Generate the README files
-------------------------
This needs to be done after all installers are downloaded, but before the pavement
file is updated for continued development::
$ cd ../numpy
$ paver write_release
Tag the release
---------------
Once the wheels have been built and downloaded without errors, go back to your
numpy repository in the maintenance branch and tag the ``REL`` commit, signing
it with your gpg key::
$ git tag -s v1.14.5
You should upload your public gpg key to github, so that the tag will appear
"verified" there.
Check that the files in ``release/installers`` have the correct versions, then
push the tag upstream::
$ git push upstream v1.14.5
We wait until this point to push the tag because it is public and should not
be changed after it has been pushed.
Reset the maintenance branch into a development state
-----------------------------------------------------
Add another ``REL`` commit to the numpy maintenance branch, which resets the
``ISREALEASED`` flag to ``False`` and increments the version counter::
$ gvim pavement.py setup.py
Create release notes for next release and edit them to set the version::
$ cp doc/source/release/template.rst doc/source/release/1.14.6-notes.rst
$ gvim doc/source/release/1.14.6-notes.rst
$ git add doc/source/release/1.14.6-notes.rst
Add new release notes to the documentation release list::
$ gvim doc/source/release.rst
Commit the result::
$ git commit -a -m"REL: prepare 1.14.x for further development"
$ git push upstream maintenance/1.14.x
Upload to PyPI
--------------
Upload to PyPI using ``twine``. A recent version of ``twine`` of is needed
after recent PyPI changes, version ``1.11.0`` was used here.
.. code-block:: sh
$ cd ../numpy
$ twine upload release/installers/*.whl
$ twine upload release/installers/numpy-1.14.5.zip # Upload last.
If one of the commands breaks in the middle, which is not uncommon, you may
need to selectively upload the remaining files because PyPI does not allow the
same file to be uploaded twice. The source file should be uploaded last to
avoid synchronization problems if pip users access the files while this is in
process. Note that PyPI only allows a single source distribution, here we have
chosen the zip archive.
Upload files to github
----------------------
Go to `<https://github.com/numpy/numpy/releases>`_, there should be a ``v1.14.5
tag``, click on it and hit the edit button for that tag. There are two ways to
add files, using an editable text window and as binary uploads.
- Cut and paste the ``release/README.md`` file contents into the text window.
- Upload ``release/installers/numpy-1.14.5.tar.gz`` as a binary file.
- Upload ``release/installers/numpy-1.14.5.zip`` as a binary file.
- Upload ``release/README.rst`` as a binary file.
- Upload ``doc/changelog/1.14.5-changelog.rst`` as a binary file.
- Check the pre-release button if this is a pre-releases.
- Hit the ``{Publish,Update} release`` button at the bottom.
Upload documents to numpy.org
-----------------------------
This step is only needed for final releases and can be skipped for
pre-releases. ``make merge-doc`` clones the ``numpy/doc`` repo into
``doc/build/merge`` and updates it with the new documentation::
$ pushd doc
$ make dist
$ make merge-doc
$ popd
If the release series is a new one, you will need to add a new section to the
``doc/build/merge/index.html`` front page just after the "insert here" comment::
$ gvim doc/build/merge/index.html +/'insert here'
Otherwise, only the ``zip`` and ``pdf`` links should be updated with the
new tag name::
$ gvim doc/build/merge/index.html +/'tag v1.14'
You can "test run" the new documentation in a browser to make sure the links
work::
$ firefox doc/build/merge/index.html
Once everything seems satisfactory, commit and upload the changes::
$ pushd doc/build/merge
$ git commit -am"Add documentation for v1.14.5"
$ git push
$ popd
Announce the release on scipy.org
---------------------------------
This assumes that you have forked `<https://github.com/scipy/scipy.org>`_::
$ cd ../scipy.org
$ git checkout master
$ git pull upstream master
$ git checkout -b numpy-1.14.5
$ gvim www/index.rst # edit the News section
$ git commit -a
$ git push origin HEAD
Now go to your fork and make a pull request for the branch.
Announce to mailing lists
-------------------------
The release should be announced on the numpy-discussion, scipy-devel,
scipy-user, and python-announce-list mailing lists. Look at previous
announcements for the basic template. The contributor and PR lists are the same
as generated for the release notes above. If you crosspost, make sure that
python-announce-list is BCC so that replies will not be sent to that list.
Post-Release Tasks
------------------
Checkout master and forward port the documentation changes::
$ git checkout -b update-after-1.14.5-release
$ git checkout maintenance/1.14.x doc/source/release/1.14.5-notes.rst
$ git checkout maintenance/1.14.x doc/changelog/1.14.5-changelog.rst
$ gvim doc/source/release.rst # Add link to new notes
$ git add doc/changelog/1.14.5-changelog.rst doc/source/release/1.14.5-notes.rst
$ git status # check status before commit
$ git commit -a -m"REL: Update master after 1.14.5 release."
$ git push origin HEAD
Go to github and make a PR.

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NumPy/SciPy Testing Guidelines
==============================
.. contents::
Introduction
''''''''''''
Until the 1.15 release, NumPy used the `nose`_ testing framework, it now uses
the `pytest`_ framework. The older framework is still maintained in order to
support downstream projects that use the old numpy framework, but all tests
for NumPy should use pytest.
Our goal is that every module and package in NumPy
should have a thorough set of unit
tests. These tests should exercise the full functionality of a given
routine as well as its robustness to erroneous or unexpected input
arguments. Long experience has shown that by far the best time to
write the tests is before you write or change the code - this is
`test-driven development
<https://en.wikipedia.org/wiki/Test-driven_development>`__. The
arguments for this can sound rather abstract, but we can assure you
that you will find that writing the tests first leads to more robust
and better designed code. Well-designed tests with good coverage make
an enormous difference to the ease of refactoring. Whenever a new bug
is found in a routine, you should write a new test for that specific
case and add it to the test suite to prevent that bug from creeping
back in unnoticed.
.. note::
SciPy uses the testing framework from :mod:`numpy.testing`,
so all of the NumPy examples shown below are also applicable to SciPy
Testing NumPy
'''''''''''''
NumPy can be tested in a number of ways, choose any way you feel comfortable.
Running tests from inside Python
--------------------------------
You can test an installed NumPy by `numpy.test`, for example,
To run NumPy's full test suite, use the following::
>>> import numpy
>>> numpy.test(label='slow')
The test method may take two or more arguments; the first ``label`` is a
string specifying what should be tested and the second ``verbose`` is an
integer giving the level of output verbosity. See the docstring
`numpy.test`
for details. The default value for ``label`` is 'fast' - which
will run the standard tests. The string 'full' will run the full battery
of tests, including those identified as being slow to run. If ``verbose``
is 1 or less, the tests will just show information messages about the tests
that are run; but if it is greater than 1, then the tests will also provide
warnings on missing tests. So if you want to run every test and get
messages about which modules don't have tests::
>>> numpy.test(label='full', verbose=2) # or numpy.test('full', 2)
Finally, if you are only interested in testing a subset of NumPy, for
example, the ``core`` module, use the following::
>>> numpy.core.test()
Running tests from the command line
-----------------------------------
If you want to build NumPy in order to work on NumPy itself, use
``runtests.py``.To run NumPy's full test suite::
$ python runtests.py
Testing a subset of NumPy::
$python runtests.py -t numpy/core/tests
For detailed info on testing, see :ref:`testing-builds`
Other methods of running tests
------------------------------
Run tests using your favourite IDE such as `vscode`_ or `pycharm`_
Writing your own tests
''''''''''''''''''''''
If you are writing a package that you'd like to become part of NumPy,
please write the tests as you develop the package.
Every Python module, extension module, or subpackage in the NumPy
package directory should have a corresponding ``test_<name>.py`` file.
Pytest examines these files for test methods (named ``test*``) and test
classes (named ``Test*``).
Suppose you have a NumPy module ``numpy/xxx/yyy.py`` containing a
function ``zzz()``. To test this function you would create a test
module called ``test_yyy.py``. If you only need to test one aspect of
``zzz``, you can simply add a test function::
def test_zzz():
assert_(zzz() == 'Hello from zzz')
More often, we need to group a number of tests together, so we create
a test class::
from numpy.testing import assert_, assert_raises
# import xxx symbols
from numpy.xxx.yyy import zzz
class TestZzz:
def test_simple(self):
assert_(zzz() == 'Hello from zzz')
def test_invalid_parameter(self):
assert_raises(...)
Within these test methods, ``assert_()`` and related functions are used to test
whether a certain assumption is valid. If the assertion fails, the test fails.
Note that the Python builtin ``assert`` should not be used, because it is
stripped during compilation with ``-O``.
Note that ``test_`` functions or methods should not have a docstring, because
that makes it hard to identify the test from the output of running the test
suite with ``verbose=2`` (or similar verbosity setting). Use plain comments
(``#``) if necessary.
Also since much of NumPy is legacy code that was
originally written without unit tests, there are still several modules
that don't have tests yet. Please feel free to choose one of these
modules and develop tests for it.
Labeling tests
--------------
As an alternative to ``pytest.mark.<label>``, there are a number of labels you
can use.
Unlabeled tests like the ones above are run in the default
``numpy.test()`` run. If you want to label your test as slow - and
therefore reserved for a full ``numpy.test(label='full')`` run, you
can label it with a decorator::
# numpy.testing module includes 'import decorators as dec'
from numpy.testing import dec, assert_
@dec.slow
def test_big(self):
print 'Big, slow test'
Similarly for methods::
class test_zzz:
@dec.slow
def test_simple(self):
assert_(zzz() == 'Hello from zzz')
Available labels are:
- ``slow``: marks a test as taking a long time
- ``setastest(tf)``: work-around for test discovery when the test name is
non conformant
- ``skipif(condition, msg=None)``: skips the test when ``eval(condition)`` is
``True``
- ``knownfailureif(fail_cond, msg=None)``: will avoid running the test if
``eval(fail_cond)`` is ``True``, useful for tests that conditionally segfault
- ``deprecated(conditional=True)``: filters deprecation warnings emitted in the
test
- ``paramaterize(var, input)``: an alternative to
`pytest.mark.paramaterized
<https://docs.pytest.org/en/latest/parametrize.html>`_
Easier setup and teardown functions / methods
---------------------------------------------
Testing looks for module-level or class-level setup and teardown functions by
name; thus::
def setup():
"""Module-level setup"""
print 'doing setup'
def teardown():
"""Module-level teardown"""
print 'doing teardown'
class TestMe:
def setup():
"""Class-level setup"""
print 'doing setup'
def teardown():
"""Class-level teardown"""
print 'doing teardown'
Setup and teardown functions to functions and methods are known as "fixtures",
and their use is not encouraged.
Parametric tests
----------------
One very nice feature of testing is allowing easy testing across a range
of parameters - a nasty problem for standard unit tests. Use the
``dec.paramaterize`` decorator.
Doctests
--------
Doctests are a convenient way of documenting the behavior of a function
and allowing that behavior to be tested at the same time. The output
of an interactive Python session can be included in the docstring of a
function, and the test framework can run the example and compare the
actual output to the expected output.
The doctests can be run by adding the ``doctests`` argument to the
``test()`` call; for example, to run all tests (including doctests)
for numpy.lib::
>>> import numpy as np
>>> np.lib.test(doctests=True)
The doctests are run as if they are in a fresh Python instance which
has executed ``import numpy as np``. Tests that are part of a NumPy
subpackage will have that subpackage already imported. E.g. for a test
in ``numpy/linalg/tests/``, the namespace will be created such that
``from numpy import linalg`` has already executed.
``tests/``
----------
Rather than keeping the code and the tests in the same directory, we
put all the tests for a given subpackage in a ``tests/``
subdirectory. For our example, if it doesn't already exist you will
need to create a ``tests/`` directory in ``numpy/xxx/``. So the path
for ``test_yyy.py`` is ``numpy/xxx/tests/test_yyy.py``.
Once the ``numpy/xxx/tests/test_yyy.py`` is written, its possible to
run the tests by going to the ``tests/`` directory and typing::
python test_yyy.py
Or if you add ``numpy/xxx/tests/`` to the Python path, you could run
the tests interactively in the interpreter like this::
>>> import test_yyy
>>> test_yyy.test()
``__init__.py`` and ``setup.py``
--------------------------------
Usually, however, adding the ``tests/`` directory to the python path
isn't desirable. Instead it would better to invoke the test straight
from the module ``xxx``. To this end, simply place the following lines
at the end of your package's ``__init__.py`` file::
...
def test(level=1, verbosity=1):
from numpy.testing import Tester
return Tester().test(level, verbosity)
You will also need to add the tests directory in the configuration
section of your setup.py::
...
def configuration(parent_package='', top_path=None):
...
config.add_subpackage('tests')
return config
...
Now you can do the following to test your module::
>>> import numpy
>>> numpy.xxx.test()
Also, when invoking the entire NumPy test suite, your tests will be
found and run::
>>> import numpy
>>> numpy.test()
# your tests are included and run automatically!
Tips & Tricks
'''''''''''''
Creating many similar tests
---------------------------
If you have a collection of tests that must be run multiple times with
minor variations, it can be helpful to create a base class containing
all the common tests, and then create a subclass for each variation.
Several examples of this technique exist in NumPy; below are excerpts
from one in `numpy/linalg/tests/test_linalg.py
<https://github.com/numpy/numpy/blob/master/numpy/linalg/tests/test_linalg.py>`__::
class LinalgTestCase:
def test_single(self):
a = array([[1.,2.], [3.,4.]], dtype=single)
b = array([2., 1.], dtype=single)
self.do(a, b)
def test_double(self):
a = array([[1.,2.], [3.,4.]], dtype=double)
b = array([2., 1.], dtype=double)
self.do(a, b)
...
class TestSolve(LinalgTestCase):
def do(self, a, b):
x = linalg.solve(a, b)
assert_almost_equal(b, dot(a, x))
assert_(imply(isinstance(b, matrix), isinstance(x, matrix)))
class TestInv(LinalgTestCase):
def do(self, a, b):
a_inv = linalg.inv(a)
assert_almost_equal(dot(a, a_inv), identity(asarray(a).shape[0]))
assert_(imply(isinstance(a, matrix), isinstance(a_inv, matrix)))
In this case, we wanted to test solving a linear algebra problem using
matrices of several data types, using ``linalg.solve`` and
``linalg.inv``. The common test cases (for single-precision,
double-precision, etc. matrices) are collected in ``LinalgTestCase``.
Known failures & skipping tests
-------------------------------
Sometimes you might want to skip a test or mark it as a known failure,
such as when the test suite is being written before the code it's
meant to test, or if a test only fails on a particular architecture.
To skip a test, simply use ``skipif``::
import pytest
@pytest.mark.skipif(SkipMyTest, reason="Skipping this test because...")
def test_something(foo):
...
The test is marked as skipped if ``SkipMyTest`` evaluates to nonzero,
and the message in verbose test output is the second argument given to
``skipif``. Similarly, a test can be marked as a known failure by
using ``xfail``::
import pytest
@pytest.mark.xfail(MyTestFails, reason="This test is known to fail because...")
def test_something_else(foo):
...
Of course, a test can be unconditionally skipped or marked as a known
failure by using ``skip`` or ``xfail`` without argument, respectively.
A total of the number of skipped and known failing tests is displayed
at the end of the test run. Skipped tests are marked as ``'S'`` in
the test results (or ``'SKIPPED'`` for ``verbose > 1``), and known
failing tests are marked as ``'x'`` (or ``'XFAIL'`` if ``verbose >
1``).
Tests on random data
--------------------
Tests on random data are good, but since test failures are meant to expose
new bugs or regressions, a test that passes most of the time but fails
occasionally with no code changes is not helpful. Make the random data
deterministic by setting the random number seed before generating it. Use
either Python's ``random.seed(some_number)`` or NumPy's
``numpy.random.seed(some_number)``, depending on the source of random numbers.
Alternatively, you can use `Hypothesis`_ to generate arbitrary data.
Hypothesis manages both Python's and Numpy's random seeds for you, and
provides a very concise and powerful way to describe data (including
``hypothesis.extra.numpy``, e.g. for a set of mutually-broadcastable shapes).
The advantages over random generation include tools to replay and share
failures without requiring a fixed seed, reporting *minimal* examples for
each failure, and better-than-naive-random techniques for triggering bugs.
Documentation for ``numpy.test``
--------------------------------
.. autofunction:: numpy.test
.. _nose: https://nose.readthedocs.io/en/latest/
.. _pytest: https://pytest.readthedocs.io
.. _parameterization: https://docs.pytest.org/en/latest/parametrize.html
.. _Hypothesis: https://hypothesis.readthedocs.io/en/latest/
.. _vscode: https://code.visualstudio.com/docs/python/testing#_enable-a-test-framework
.. _pycharm: https://www.jetbrains.com/help/pycharm/testing-your-first-python-application.html

0
deps/numpy/doc/__init__.py vendored Normal file
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29
deps/numpy/doc/cdoc/Doxyfile vendored Normal file
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@ -0,0 +1,29 @@
# Doxyfile for NumPy C API
# See http://www.doxygen.nl/manual/config.html
PROJECT_NAME = numpy
PROJECT_NUMBER = 2.0.0
OUTPUT_DIRECTORY = build
STRIP_FROM_PATH = ../../numpy/core
INHERIT_DOCS = YES
TAB_SIZE = 8
OPTIMIZE_OUTPUT_FOR_C = YES
EXTRACT_ALL = YES
EXTRACT_PRIVATE = YES
EXTRACT_STATIC = YES
CASE_SENSE_NAMES = NO
INPUT = ../../numpy/core/src \
../../numpy/core/include
FILE_PATTERNS = *.h *.c *.src
RECURSIVE = YES
INPUT_FILTER = ./numpyfilter.py
REFERENCED_BY_RELATION = YES
REFERENCES_RELATION = YES
ALPHABETICAL_INDEX = NO
GENERATE_HTML = YES
HTML_TIMESTAMP = YES
GENERATE_TREEVIEW = YES
SEARCHENGINE = NO
GENERATE_LATEX = NO
PAPER_TYPE = a4wide
GENERATE_XML = NO
HAVE_DOT = NO

10
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all: build
build:
doxygen
clean:
rm -rf build
.PHONY: all build clean

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@ -0,0 +1,31 @@
cdoc
====
This is a simple Doxygen project for building NumPy C code documentation,
with docstrings extracted from the C sources themselves.
The understood syntax for documentation in the C source is
/*
* Some text in reStructuredText format
*/
int function_to_which_the_text_applies()
{
...
}
/*
* More text in reStructuredText format
*/
struct
{
int variable_1; /* Documentation for variable_1 */
/*
* Documentation for variable_2
*/
int variable_2;
} struct_name_t;
Please do not use JavaDoc or Doxygen-specific formatting at the moment.

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104
deps/numpy/doc/cdoc/numpyfilter.py vendored Normal file
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#!/usr/bin/env python3
"""
numpyfilter.py [-h] inputfile
Interpret C comments as ReStructuredText, and replace them by the HTML output.
Also, add Doxygen /** and /**< syntax automatically where appropriate.
"""
import sys
import re
import os
import textwrap
from numpy.compat import pickle
CACHE_FILE = 'build/rst-cache.pck'
def main():
import argparse
parser = argparse.ArgumentParser(usage=__doc__.strip())
parser.add_argument('input_file', help='input file')
args = parser.parse_args()
comment_re = re.compile(r'(\n.*?)/\*(.*?)\*/', re.S)
cache = load_cache()
try:
with open(args.input_file, 'r') as f:
text = f.read()
text = comment_re.sub(lambda m: process_match(m, cache), text)
sys.stdout.write(text)
finally:
save_cache(cache)
def filter_comment(text):
if text.startswith('NUMPY_API'):
text = text[9:].strip()
if text.startswith('UFUNC_API'):
text = text[9:].strip()
html = render_html(text)
return html
def process_match(m, cache=None):
pre, rawtext = m.groups()
preline = pre.split("\n")[-1]
if cache is not None and rawtext in cache:
text = cache[rawtext]
else:
text = re.compile(r'^\s*\*', re.M).sub('', rawtext)
text = textwrap.dedent(text)
text = filter_comment(text)
if cache is not None:
cache[rawtext] = text
if preline.strip():
return pre + "/**< " + text + " */"
else:
return pre + "/** " + text + " */"
def load_cache():
if os.path.exists(CACHE_FILE):
with open(CACHE_FILE, 'rb') as f:
try:
cache = pickle.load(f)
except Exception:
cache = {}
else:
cache = {}
return cache
def save_cache(cache):
with open(CACHE_FILE + '.new', 'wb') as f:
pickle.dump(cache, f)
os.rename(CACHE_FILE + '.new', CACHE_FILE)
def render_html(text):
import docutils.parsers.rst
import docutils.writers.html4css1
import docutils.core
docutils.parsers.rst.roles.DEFAULT_INTERPRETED_ROLE = 'title-reference'
writer = docutils.writers.html4css1.Writer()
parts = docutils.core.publish_parts(
text,
writer=writer,
settings_overrides = dict(halt_level=5,
traceback=True,
default_reference_context='title-reference',
stylesheet_path='',
# security settings:
raw_enabled=0,
file_insertion_enabled=0,
_disable_config=1,
)
)
return parts['html_body']
if __name__ == "__main__": main()

573
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@ -0,0 +1,573 @@
=========
Changelog
=========
Contributors
============
A total of 139 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Aditya Panchal +
* Ales Erjavec +
* Alex Griffing
* Alexandr Shadchin +
* Alistair Muldal
* Allan Haldane
* Amit Aronovitch +
* Andrei Kucharavy +
* Antony Lee
* Antti Kaihola +
* Arne de Laat +
* Auke Wiggers +
* AustereCuriosity +
* Badhri Narayanan Krishnakumar +
* Ben North +
* Ben Rowland +
* Bertrand Lefebvre
* Boxiang Sun
* CJ Carey
* Charles Harris
* Christoph Gohlke
* Daniel Ching +
* Daniel Rasmussen +
* Daniel Smith +
* David Schaich +
* Denis Alevi +
* Devin Jeanpierre +
* Dmitry Odzerikho
* Dongjoon Hyun +
* Edward Richards +
* Ekaterina Tuzova +
* Emilien Kofman +
* Endolith
* Eren Sezener +
* Eric Moore
* Eric Quintero +
* Eric Wieser +
* Erik M. Bray
* Frederic Bastien
* Friedrich Dunne +
* Gerrit Holl
* Golnaz Irannejad +
* Graham Markall +
* Greg Knoll +
* Greg Young
* Gustavo Serra Scalet +
* Ines Wichert +
* Irvin Probst +
* Jaime Fernandez
* James Sanders +
* Jan David Mol +
* Jan Schlüter
* Jeremy Tuloup +
* John Kirkham
* John Zwinck +
* Jonathan Helmus
* Joseph Fox-Rabinovitz
* Josh Wilson +
* Joshua Warner +
* Julian Taylor
* Ka Wo Chen +
* Kamil Rytarowski +
* Kelsey Jordahl +
* Kevin Deldycke +
* Khaled Ben Abdallah Okuda +
* Lion Krischer +
* Loïc Estève +
* Luca Mussi +
* Mads Ohm Larsen +
* Manoj Kumar +
* Mario Emmenlauer +
* Marshall Bockrath-Vandegrift +
* Marshall Ward +
* Marten van Kerkwijk
* Mathieu Lamarre +
* Matthew Brett
* Matthew Harrigan +
* Matthias Geier
* Matti Picus +
* Meet Udeshi +
* Michael Felt +
* Michael Goerz +
* Michael Martin +
* Michael Seifert +
* Mike Nolta +
* Nathaniel Beaver +
* Nathaniel J. Smith
* Naveen Arunachalam +
* Nick Papior
* Nikola Forró +
* Oleksandr Pavlyk +
* Olivier Grisel
* Oren Amsalem +
* Pauli Virtanen
* Pavel Potocek +
* Pedro Lacerda +
* Peter Creasey +
* Phil Elson +
* Philip Gura +
* Phillip J. Wolfram +
* Pierre de Buyl +
* Raghav RV +
* Ralf Gommers
* Ray Donnelly +
* Rehas Sachdeva
* Rob Malouf +
* Robert Kern
* Samuel St-Jean
* Sanchez Gonzalez Alvaro +
* Saurabh Mehta +
* Scott Sanderson +
* Sebastian Berg
* Shayan Pooya +
* Shota Kawabuchi +
* Simon Conseil
* Simon Gibbons
* Sorin Sbarnea +
* Stefan van der Walt
* Stephan Hoyer
* Steven J Kern +
* Stuart Archibald
* Tadeu Manoel +
* Takuya Akiba +
* Thomas A Caswell
* Tom Bird +
* Tony Kelman +
* Toshihiro Kamishima +
* Valentin Valls +
* Varun Nayyar
* Victor Stinner +
* Warren Weckesser
* Wendell Smith
* Wojtek Ruszczewski +
* Xavier Abellan Ecija +
* Yaroslav Halchenko
* Yash Shah +
* Yinon Ehrlich +
* Yu Feng +
* nevimov +
Pull requests merged
====================
A total of 418 pull requests were merged for this release.
* `#4073 <https://github.com/numpy/numpy/pull/4073>`__: BUG: change real output checking to test if all imaginary parts...
* `#4619 <https://github.com/numpy/numpy/pull/4619>`__: BUG : np.sum silently drops keepdims for sub-classes of ndarray
* `#5488 <https://github.com/numpy/numpy/pull/5488>`__: ENH: add `contract`: optimizing numpy's einsum expression
* `#5706 <https://github.com/numpy/numpy/pull/5706>`__: ENH: make some masked array methods behave more like ndarray...
* `#5822 <https://github.com/numpy/numpy/pull/5822>`__: Allow many distributions to have a scale of 0.
* `#6054 <https://github.com/numpy/numpy/pull/6054>`__: WIP: MAINT: Add deprecation warning to views of multi-field indexes
* `#6298 <https://github.com/numpy/numpy/pull/6298>`__: Check lower base limit in base_repr.
* `#6430 <https://github.com/numpy/numpy/pull/6430>`__: Fix issues with zero-width string fields
* `#6656 <https://github.com/numpy/numpy/pull/6656>`__: ENH: usecols now accepts an int when only one column has to be...
* `#6660 <https://github.com/numpy/numpy/pull/6660>`__: Added pathlib support for several functions
* `#6872 <https://github.com/numpy/numpy/pull/6872>`__: ENH: linear interpolation of complex values in lib.interp
* `#6997 <https://github.com/numpy/numpy/pull/6997>`__: MAINT: Simplify mtrand.pyx helpers
* `#7003 <https://github.com/numpy/numpy/pull/7003>`__: BUG: Fix string copying for np.place
* `#7026 <https://github.com/numpy/numpy/pull/7026>`__: DOC: Clarify behavior in np.random.uniform
* `#7055 <https://github.com/numpy/numpy/pull/7055>`__: BUG: One Element Array Inputs Return Scalars in np.random
* `#7063 <https://github.com/numpy/numpy/pull/7063>`__: REL: Update master branch after 1.11.x branch has been made.
* `#7073 <https://github.com/numpy/numpy/pull/7073>`__: DOC: Update the 1.11.0 release notes.
* `#7076 <https://github.com/numpy/numpy/pull/7076>`__: MAINT: Update the git .mailmap file.
* `#7082 <https://github.com/numpy/numpy/pull/7082>`__: TST, DOC: Added Broadcasting Tests in test_random.py
* `#7087 <https://github.com/numpy/numpy/pull/7087>`__: BLD: fix compilation on non glibc-Linuxes
* `#7088 <https://github.com/numpy/numpy/pull/7088>`__: BUG: Have `norm` cast non-floating point arrays to 64-bit float...
* `#7090 <https://github.com/numpy/numpy/pull/7090>`__: ENH: Added 'doane' and 'sqrt' estimators to np.histogram in numpy.function_base
* `#7091 <https://github.com/numpy/numpy/pull/7091>`__: Revert "BLD: fix compilation on non glibc-Linuxes"
* `#7092 <https://github.com/numpy/numpy/pull/7092>`__: BLD: fix compilation on non glibc-Linuxes
* `#7099 <https://github.com/numpy/numpy/pull/7099>`__: TST: Suppressed warnings
* `#7102 <https://github.com/numpy/numpy/pull/7102>`__: MAINT: Removed conditionals that are always false in datetime_strings.c
* `#7105 <https://github.com/numpy/numpy/pull/7105>`__: DEP: Deprecate as_strided returning a writable array as default
* `#7109 <https://github.com/numpy/numpy/pull/7109>`__: DOC: update Python versions requirements in the install docs
* `#7114 <https://github.com/numpy/numpy/pull/7114>`__: MAINT: Fix typos in docs
* `#7116 <https://github.com/numpy/numpy/pull/7116>`__: TST: Fixed f2py test for win32 virtualenv
* `#7118 <https://github.com/numpy/numpy/pull/7118>`__: TST: Fixed f2py test for non-versioned python executables
* `#7119 <https://github.com/numpy/numpy/pull/7119>`__: BUG: Fixed mingw.lib error
* `#7125 <https://github.com/numpy/numpy/pull/7125>`__: DOC: Updated documentation wording and examples for np.percentile.
* `#7129 <https://github.com/numpy/numpy/pull/7129>`__: BUG: Fixed 'midpoint' interpolation of np.percentile in odd cases.
* `#7131 <https://github.com/numpy/numpy/pull/7131>`__: Fix setuptools sdist
* `#7133 <https://github.com/numpy/numpy/pull/7133>`__: ENH: savez: temporary file alongside with target file and improve...
* `#7134 <https://github.com/numpy/numpy/pull/7134>`__: MAINT: Fix some typos in a code string and comments
* `#7141 <https://github.com/numpy/numpy/pull/7141>`__: BUG: Unpickled void scalars should be contiguous
* `#7144 <https://github.com/numpy/numpy/pull/7144>`__: MAINT: Change `call_fortran` into `callfortran` in comments.
* `#7145 <https://github.com/numpy/numpy/pull/7145>`__: BUG: Fixed regressions in np.piecewise in ref to #5737 and #5729.
* `#7147 <https://github.com/numpy/numpy/pull/7147>`__: Temporarily disable __numpy_ufunc__
* `#7148 <https://github.com/numpy/numpy/pull/7148>`__: ENH,TST: Bump stacklevel and add tests for warnings
* `#7149 <https://github.com/numpy/numpy/pull/7149>`__: TST: Add missing suffix to temppath manager
* `#7152 <https://github.com/numpy/numpy/pull/7152>`__: BUG: mode kwargs passed as unicode to np.pad raises an exception
* `#7156 <https://github.com/numpy/numpy/pull/7156>`__: BUG: Reascertain that linspace respects ndarray subclasses in...
* `#7167 <https://github.com/numpy/numpy/pull/7167>`__: DOC: Update Wikipedia references for mtrand.pyx
* `#7171 <https://github.com/numpy/numpy/pull/7171>`__: TST: Fixed f2py test for Anaconda non-win32
* `#7174 <https://github.com/numpy/numpy/pull/7174>`__: DOC: Fix broken pandas link in release notes
* `#7177 <https://github.com/numpy/numpy/pull/7177>`__: ENH: added axis param for np.count_nonzero
* `#7178 <https://github.com/numpy/numpy/pull/7178>`__: BUG: Fix binary_repr for negative numbers
* `#7180 <https://github.com/numpy/numpy/pull/7180>`__: BUG: Fixed previous attempt to fix dimension mismatch in nanpercentile
* `#7181 <https://github.com/numpy/numpy/pull/7181>`__: DOC: Updated minor typos in function_base.py and test_function_base.py
* `#7191 <https://github.com/numpy/numpy/pull/7191>`__: DOC: add vstack, hstack, dstack reference to stack documentation.
* `#7193 <https://github.com/numpy/numpy/pull/7193>`__: MAINT: Removed supurious assert in histogram estimators
* `#7194 <https://github.com/numpy/numpy/pull/7194>`__: BUG: Raise a quieter `MaskedArrayFutureWarning` for mask changes.
* `#7195 <https://github.com/numpy/numpy/pull/7195>`__: STY: Drop some trailing spaces in `numpy.ma.core`.
* `#7196 <https://github.com/numpy/numpy/pull/7196>`__: Revert "DOC: add vstack, hstack, dstack reference to stack documentation."
* `#7197 <https://github.com/numpy/numpy/pull/7197>`__: TST: Pin virtualenv used on Travis CI.
* `#7198 <https://github.com/numpy/numpy/pull/7198>`__: ENH: Unlock the GIL for gufuncs
* `#7199 <https://github.com/numpy/numpy/pull/7199>`__: MAINT: Cleanup for histogram bin estimator selection
* `#7201 <https://github.com/numpy/numpy/pull/7201>`__: Raise IOError on not a file in python2
* `#7202 <https://github.com/numpy/numpy/pull/7202>`__: MAINT: Made `iterable` return a boolean
* `#7209 <https://github.com/numpy/numpy/pull/7209>`__: TST: Bump `virtualenv` to 14.0.6
* `#7211 <https://github.com/numpy/numpy/pull/7211>`__: DOC: Fix fmin examples
* `#7215 <https://github.com/numpy/numpy/pull/7215>`__: MAINT: Use PySlice_GetIndicesEx instead of custom reimplementation
* `#7229 <https://github.com/numpy/numpy/pull/7229>`__: ENH: implement __complex__
* `#7231 <https://github.com/numpy/numpy/pull/7231>`__: MRG: allow distributors to run custom init
* `#7232 <https://github.com/numpy/numpy/pull/7232>`__: BLD: Switch order of test for lapack_mkl and openblas_lapack
* `#7239 <https://github.com/numpy/numpy/pull/7239>`__: DOC: Removed residual merge markup from previous commit
* `#7240 <https://github.com/numpy/numpy/pull/7240>`__: Change 'pubic' to 'public'.
* `#7241 <https://github.com/numpy/numpy/pull/7241>`__: MAINT: update doc/sphinxext to numpydoc 0.6.0, and fix up some...
* `#7243 <https://github.com/numpy/numpy/pull/7243>`__: ENH: Adding support to the range keyword for estimation of the...
* `#7246 <https://github.com/numpy/numpy/pull/7246>`__: DOC: mention writeable keyword in as_strided in release notes
* `#7247 <https://github.com/numpy/numpy/pull/7247>`__: TST: Fail quickly on AppVeyor for superseded PR builds
* `#7248 <https://github.com/numpy/numpy/pull/7248>`__: DOC: remove link to documentation wiki editor from HOWTO_DOCUMENT.
* `#7250 <https://github.com/numpy/numpy/pull/7250>`__: DOC,REL: Update 1.11.0 notes.
* `#7251 <https://github.com/numpy/numpy/pull/7251>`__: BUG: only benchmark complex256 if it exists
* `#7252 <https://github.com/numpy/numpy/pull/7252>`__: Forward port a fix and enhancement from 1.11.x
* `#7253 <https://github.com/numpy/numpy/pull/7253>`__: DOC: note in h/v/dstack points users to stack/concatenate
* `#7254 <https://github.com/numpy/numpy/pull/7254>`__: BUG: Enforce dtype for randint singletons
* `#7256 <https://github.com/numpy/numpy/pull/7256>`__: MAINT: Use `is None` or `is not None` instead of `== None` or...
* `#7257 <https://github.com/numpy/numpy/pull/7257>`__: DOC: Fix mismatched variable names in docstrings.
* `#7258 <https://github.com/numpy/numpy/pull/7258>`__: ENH: Make numpy floor_divide and remainder agree with Python...
* `#7260 <https://github.com/numpy/numpy/pull/7260>`__: BUG/TST: Fix #7259, do not "force scalar" for already scalar...
* `#7261 <https://github.com/numpy/numpy/pull/7261>`__: Added self to mailmap
* `#7266 <https://github.com/numpy/numpy/pull/7266>`__: BUG: Segfault for classes with deceptive __len__
* `#7268 <https://github.com/numpy/numpy/pull/7268>`__: ENH: add geomspace function
* `#7274 <https://github.com/numpy/numpy/pull/7274>`__: BUG: Preserve array order in np.delete
* `#7275 <https://github.com/numpy/numpy/pull/7275>`__: DEP: Warn about assigning 'data' attribute of ndarray
* `#7276 <https://github.com/numpy/numpy/pull/7276>`__: DOC: apply_along_axis missing whitespace inserted (before colon)
* `#7278 <https://github.com/numpy/numpy/pull/7278>`__: BUG: Make returned unravel_index arrays writeable
* `#7279 <https://github.com/numpy/numpy/pull/7279>`__: TST: Fixed elements being shuffled
* `#7280 <https://github.com/numpy/numpy/pull/7280>`__: MAINT: Remove redundant trailing semicolons.
* `#7285 <https://github.com/numpy/numpy/pull/7285>`__: BUG: Make Randint Backwards Compatible with Pandas
* `#7286 <https://github.com/numpy/numpy/pull/7286>`__: MAINT: Fix typos in docs/comments of `ma` and `polynomial` modules.
* `#7292 <https://github.com/numpy/numpy/pull/7292>`__: Clarify error on repr failure in assert_equal.
* `#7294 <https://github.com/numpy/numpy/pull/7294>`__: ENH: add support for BLIS to numpy.distutils
* `#7295 <https://github.com/numpy/numpy/pull/7295>`__: DOC: understanding code and getting started section to dev doc
* `#7296 <https://github.com/numpy/numpy/pull/7296>`__: Revert part of #3907 which incorrectly propagated MaskedArray...
* `#7299 <https://github.com/numpy/numpy/pull/7299>`__: DOC: Fix mismatched variable names in docstrings.
* `#7300 <https://github.com/numpy/numpy/pull/7300>`__: DOC: dev: stop recommending keeping local master updated with...
* `#7301 <https://github.com/numpy/numpy/pull/7301>`__: DOC: Update release notes
* `#7305 <https://github.com/numpy/numpy/pull/7305>`__: BUG: Remove data race in mtrand: two threads could mutate the...
* `#7307 <https://github.com/numpy/numpy/pull/7307>`__: DOC: Missing some characters in link.
* `#7308 <https://github.com/numpy/numpy/pull/7308>`__: BUG: Incrementing the wrong reference on return
* `#7310 <https://github.com/numpy/numpy/pull/7310>`__: STY: Fix GitHub rendering of ordered lists >9
* `#7311 <https://github.com/numpy/numpy/pull/7311>`__: ENH: Make _pointer_type_cache functional
* `#7313 <https://github.com/numpy/numpy/pull/7313>`__: DOC: corrected grammatical error in quickstart doc
* `#7325 <https://github.com/numpy/numpy/pull/7325>`__: BUG, MAINT: Improve fromnumeric.py interface for downstream compatibility
* `#7328 <https://github.com/numpy/numpy/pull/7328>`__: DEP: Deprecated using a float index in linspace
* `#7331 <https://github.com/numpy/numpy/pull/7331>`__: Add comment, TST: fix MemoryError on win32
* `#7332 <https://github.com/numpy/numpy/pull/7332>`__: Check for no solution in np.irr Fixes #6744
* `#7338 <https://github.com/numpy/numpy/pull/7338>`__: TST: Install `pytz` in the CI.
* `#7340 <https://github.com/numpy/numpy/pull/7340>`__: DOC: Fixed math rendering in tensordot docs.
* `#7341 <https://github.com/numpy/numpy/pull/7341>`__: TST: Add test for #6469
* `#7344 <https://github.com/numpy/numpy/pull/7344>`__: DOC: Fix more typos in docs and comments.
* `#7346 <https://github.com/numpy/numpy/pull/7346>`__: Generalized flip
* `#7347 <https://github.com/numpy/numpy/pull/7347>`__: ENH Generalized rot90
* `#7348 <https://github.com/numpy/numpy/pull/7348>`__: Maint: Removed extra space from `ureduce`
* `#7349 <https://github.com/numpy/numpy/pull/7349>`__: MAINT: Hide nan warnings for masked internal MA computations
* `#7350 <https://github.com/numpy/numpy/pull/7350>`__: BUG: MA ufuncs should set mask to False, not array([False])
* `#7351 <https://github.com/numpy/numpy/pull/7351>`__: TST: Fix some MA tests to avoid looking at the .data attribute
* `#7358 <https://github.com/numpy/numpy/pull/7358>`__: BUG: pull request related to the issue #7353
* `#7359 <https://github.com/numpy/numpy/pull/7359>`__: Update 7314, DOC: Clarify valid integer range for random.seed...
* `#7361 <https://github.com/numpy/numpy/pull/7361>`__: MAINT: Fix copy and paste oversight.
* `#7363 <https://github.com/numpy/numpy/pull/7363>`__: ENH: Make no unshare mask future warnings less noisy
* `#7366 <https://github.com/numpy/numpy/pull/7366>`__: TST: fix #6542, add tests to check non-iterable argument raises...
* `#7373 <https://github.com/numpy/numpy/pull/7373>`__: ENH: Add bitwise_and identity
* `#7378 <https://github.com/numpy/numpy/pull/7378>`__: added NumPy logo and separator
* `#7382 <https://github.com/numpy/numpy/pull/7382>`__: MAINT: cleanup np.average
* `#7385 <https://github.com/numpy/numpy/pull/7385>`__: DOC: note about wheels / windows wheels for pypi
* `#7386 <https://github.com/numpy/numpy/pull/7386>`__: Added label icon to Travis status
* `#7397 <https://github.com/numpy/numpy/pull/7397>`__: BUG: incorrect type for objects whose __len__ fails
* `#7398 <https://github.com/numpy/numpy/pull/7398>`__: DOC: fix typo
* `#7404 <https://github.com/numpy/numpy/pull/7404>`__: Use PyMem_RawMalloc on Python 3.4 and newer
* `#7406 <https://github.com/numpy/numpy/pull/7406>`__: ENH ufunc called on memmap return a ndarray
* `#7407 <https://github.com/numpy/numpy/pull/7407>`__: BUG: Fix decref before incref for in-place accumulate
* `#7410 <https://github.com/numpy/numpy/pull/7410>`__: DOC: add nanprod to the list of math routines
* `#7414 <https://github.com/numpy/numpy/pull/7414>`__: Tweak corrcoef
* `#7415 <https://github.com/numpy/numpy/pull/7415>`__: DOC: Documentation fixes
* `#7416 <https://github.com/numpy/numpy/pull/7416>`__: BUG: Incorrect handling of range in `histogram` with automatic...
* `#7418 <https://github.com/numpy/numpy/pull/7418>`__: DOC: Minor typo fix, hermefik -> hermefit.
* `#7421 <https://github.com/numpy/numpy/pull/7421>`__: ENH: adds np.nancumsum and np.nancumprod
* `#7423 <https://github.com/numpy/numpy/pull/7423>`__: BUG: Ongoing fixes to PR#7416
* `#7430 <https://github.com/numpy/numpy/pull/7430>`__: DOC: Update 1.11.0-notes.
* `#7433 <https://github.com/numpy/numpy/pull/7433>`__: MAINT: FutureWarning for changes to np.average subclass handling
* `#7437 <https://github.com/numpy/numpy/pull/7437>`__: np.full now defaults to the filling value's dtype.
* `#7438 <https://github.com/numpy/numpy/pull/7438>`__: Allow rolling multiple axes at the same time.
* `#7439 <https://github.com/numpy/numpy/pull/7439>`__: BUG: Do not try sequence repeat unless necessary
* `#7442 <https://github.com/numpy/numpy/pull/7442>`__: MANT: Simplify diagonal length calculation logic
* `#7445 <https://github.com/numpy/numpy/pull/7445>`__: BUG: reference count leak in bincount, fixes #6805
* `#7446 <https://github.com/numpy/numpy/pull/7446>`__: DOC: ndarray typo fix
* `#7447 <https://github.com/numpy/numpy/pull/7447>`__: BUG: scalar integer negative powers gave wrong results.
* `#7448 <https://github.com/numpy/numpy/pull/7448>`__: DOC: array "See also" link to full and full_like instead of fill
* `#7456 <https://github.com/numpy/numpy/pull/7456>`__: BUG: int overflow in reshape, fixes #7455, fixes #7293
* `#7463 <https://github.com/numpy/numpy/pull/7463>`__: BUG: fix array too big error for wide dtypes.
* `#7466 <https://github.com/numpy/numpy/pull/7466>`__: BUG: segfault inplace object reduceat, fixes #7465
* `#7468 <https://github.com/numpy/numpy/pull/7468>`__: BUG: more on inplace reductions, fixes #615
* `#7469 <https://github.com/numpy/numpy/pull/7469>`__: MAINT: Update git .mailmap
* `#7472 <https://github.com/numpy/numpy/pull/7472>`__: MAINT: Update .mailmap.
* `#7477 <https://github.com/numpy/numpy/pull/7477>`__: MAINT: Yet more .mailmap updates for recent contributors.
* `#7481 <https://github.com/numpy/numpy/pull/7481>`__: BUG: Fix segfault in PyArray_OrderConverter
* `#7482 <https://github.com/numpy/numpy/pull/7482>`__: BUG: Memory Leak in _GenericBinaryOutFunction
* `#7489 <https://github.com/numpy/numpy/pull/7489>`__: Faster real_if_close.
* `#7491 <https://github.com/numpy/numpy/pull/7491>`__: DOC: Update subclassing doc regarding downstream compatibility
* `#7496 <https://github.com/numpy/numpy/pull/7496>`__: BUG: don't use pow for integer power ufunc loops.
* `#7504 <https://github.com/numpy/numpy/pull/7504>`__: DOC: remove "arr" from keepdims docstrings
* `#7505 <https://github.com/numpy/numpy/pull/7505>`__: MAIN: fix to #7382, make scl in np.average writeable
* `#7507 <https://github.com/numpy/numpy/pull/7507>`__: MAINT: Remove nose.SkipTest import.
* `#7508 <https://github.com/numpy/numpy/pull/7508>`__: DOC: link frompyfunc and vectorize
* `#7511 <https://github.com/numpy/numpy/pull/7511>`__: numpy.power(0, 0) should return 1
* `#7515 <https://github.com/numpy/numpy/pull/7515>`__: BUG: MaskedArray.count treats negative axes incorrectly
* `#7518 <https://github.com/numpy/numpy/pull/7518>`__: BUG: Extend glibc complex trig functions blacklist to glibc <...
* `#7521 <https://github.com/numpy/numpy/pull/7521>`__: DOC: rephrase writeup of memmap changes
* `#7522 <https://github.com/numpy/numpy/pull/7522>`__: BUG: Fixed iteration over additional bad commands
* `#7526 <https://github.com/numpy/numpy/pull/7526>`__: DOC: Removed an extra `:const:`
* `#7529 <https://github.com/numpy/numpy/pull/7529>`__: BUG: Floating exception with invalid axis in np.lexsort
* `#7534 <https://github.com/numpy/numpy/pull/7534>`__: MAINT: Update setup.py to reflect supported python versions.
* `#7536 <https://github.com/numpy/numpy/pull/7536>`__: MAINT: Always use PyCapsule instead of PyCObject in mtrand.pyx
* `#7539 <https://github.com/numpy/numpy/pull/7539>`__: MAINT: Cleanup of random stuff
* `#7549 <https://github.com/numpy/numpy/pull/7549>`__: BUG: allow graceful recovery for no Linux compiler
* `#7562 <https://github.com/numpy/numpy/pull/7562>`__: BUG: Fix test_from_object_array_unicode (test_defchararray.TestBasic)…
* `#7565 <https://github.com/numpy/numpy/pull/7565>`__: BUG: Fix test_ctypeslib and test_indexing for debug interpreter
* `#7566 <https://github.com/numpy/numpy/pull/7566>`__: MAINT: use manylinux1 wheel for cython
* `#7568 <https://github.com/numpy/numpy/pull/7568>`__: Fix a false positive OverflowError in Python 3.x when value above...
* `#7579 <https://github.com/numpy/numpy/pull/7579>`__: DOC: clarify purpose of Attributes section
* `#7584 <https://github.com/numpy/numpy/pull/7584>`__: BUG: fixes #7572, percent in path
* `#7586 <https://github.com/numpy/numpy/pull/7586>`__: Make np.ma.take works on scalars
* `#7587 <https://github.com/numpy/numpy/pull/7587>`__: BUG: linalg.norm(): Don't convert object arrays to float
* `#7598 <https://github.com/numpy/numpy/pull/7598>`__: Cast array size to int64 when loading from archive
* `#7602 <https://github.com/numpy/numpy/pull/7602>`__: DOC: Remove isreal and iscomplex from ufunc list
* `#7605 <https://github.com/numpy/numpy/pull/7605>`__: DOC: fix incorrect Gamma distribution parameterization comments
* `#7609 <https://github.com/numpy/numpy/pull/7609>`__: BUG: Fix TypeError when raising TypeError
* `#7611 <https://github.com/numpy/numpy/pull/7611>`__: ENH: expose test runner raise_warnings option
* `#7614 <https://github.com/numpy/numpy/pull/7614>`__: BLD: Avoid using os.spawnve in favor of os.spawnv in exec_command
* `#7618 <https://github.com/numpy/numpy/pull/7618>`__: BUG: distance arg of np.gradient must be scalar, fix docstring
* `#7626 <https://github.com/numpy/numpy/pull/7626>`__: DOC: RST definition list fixes
* `#7627 <https://github.com/numpy/numpy/pull/7627>`__: MAINT: unify tup processing, move tup use to after all PyTuple_SetItem...
* `#7630 <https://github.com/numpy/numpy/pull/7630>`__: MAINT: add ifdef around PyDictProxy_Check macro
* `#7631 <https://github.com/numpy/numpy/pull/7631>`__: MAINT: linalg: fix comment, simplify math
* `#7634 <https://github.com/numpy/numpy/pull/7634>`__: BLD: correct C compiler customization in system_info.py Closes...
* `#7635 <https://github.com/numpy/numpy/pull/7635>`__: BUG: ma.median alternate fix for #7592
* `#7636 <https://github.com/numpy/numpy/pull/7636>`__: MAINT: clean up testing.assert_raises_regexp, 2.6-specific code...
* `#7637 <https://github.com/numpy/numpy/pull/7637>`__: MAINT: clearer exception message when importing multiarray fails.
* `#7639 <https://github.com/numpy/numpy/pull/7639>`__: TST: fix a set of test errors in master.
* `#7643 <https://github.com/numpy/numpy/pull/7643>`__: DOC : minor changes to linspace docstring
* `#7651 <https://github.com/numpy/numpy/pull/7651>`__: BUG: one to any power is still 1. Broken edgecase for int arrays
* `#7655 <https://github.com/numpy/numpy/pull/7655>`__: BLD: Remove Intel compiler flag -xSSE4.2
* `#7658 <https://github.com/numpy/numpy/pull/7658>`__: BUG: fix incorrect printing of 1D masked arrays
* `#7659 <https://github.com/numpy/numpy/pull/7659>`__: BUG: Temporary fix for str(mvoid) for object field types
* `#7664 <https://github.com/numpy/numpy/pull/7664>`__: BUG: Fix unicode with byte swap transfer and copyswap
* `#7667 <https://github.com/numpy/numpy/pull/7667>`__: Restore histogram consistency
* `#7668 <https://github.com/numpy/numpy/pull/7668>`__: ENH: Do not check the type of module.__dict__ explicit in test.
* `#7669 <https://github.com/numpy/numpy/pull/7669>`__: BUG: boolean assignment no GIL release when transfer needs API
* `#7673 <https://github.com/numpy/numpy/pull/7673>`__: DOC: Create Numpy 1.11.1 release notes.
* `#7675 <https://github.com/numpy/numpy/pull/7675>`__: BUG: fix handling of right edge of final bin.
* `#7678 <https://github.com/numpy/numpy/pull/7678>`__: BUG: Fix np.clip bug NaN handling for Visual Studio 2015
* `#7679 <https://github.com/numpy/numpy/pull/7679>`__: MAINT: Fix up C++ comment in arraytypes.c.src.
* `#7681 <https://github.com/numpy/numpy/pull/7681>`__: DOC: Update 1.11.1 release notes.
* `#7686 <https://github.com/numpy/numpy/pull/7686>`__: ENH: Changing FFT cache to a bounded LRU cache
* `#7688 <https://github.com/numpy/numpy/pull/7688>`__: DOC: fix broken genfromtxt examples in user guide. Closes gh-7662.
* `#7689 <https://github.com/numpy/numpy/pull/7689>`__: BENCH: add correlate/convolve benchmarks.
* `#7696 <https://github.com/numpy/numpy/pull/7696>`__: DOC: update wheel build / upload instructions
* `#7699 <https://github.com/numpy/numpy/pull/7699>`__: BLD: preserve library order
* `#7704 <https://github.com/numpy/numpy/pull/7704>`__: ENH: Add bits attribute to np.finfo
* `#7712 <https://github.com/numpy/numpy/pull/7712>`__: BUG: Fix race condition with new FFT cache
* `#7715 <https://github.com/numpy/numpy/pull/7715>`__: BUG: Remove memory leak in np.place
* `#7719 <https://github.com/numpy/numpy/pull/7719>`__: BUG: Fix segfault in np.random.shuffle for arrays of different...
* `#7723 <https://github.com/numpy/numpy/pull/7723>`__: Change mkl_info.dir_env_var from MKL to MKLROOT
* `#7727 <https://github.com/numpy/numpy/pull/7727>`__: DOC: Corrections in Datetime Units-arrays.datetime.rst
* `#7729 <https://github.com/numpy/numpy/pull/7729>`__: DOC: fix typo in savetxt docstring (closes #7620)
* `#7733 <https://github.com/numpy/numpy/pull/7733>`__: Update 7525, DOC: Fix order='A' docs of np.array.
* `#7734 <https://github.com/numpy/numpy/pull/7734>`__: Update 7542, ENH: Add `polyrootval` to numpy.polynomial
* `#7735 <https://github.com/numpy/numpy/pull/7735>`__: BUG: fix issue on OS X with Python 3.x where npymath.ini was...
* `#7739 <https://github.com/numpy/numpy/pull/7739>`__: DOC: Mention the changes of #6430 in the release notes.
* `#7740 <https://github.com/numpy/numpy/pull/7740>`__: DOC: add reference to poisson rng
* `#7743 <https://github.com/numpy/numpy/pull/7743>`__: Update 7476, DEP: deprecate Numeric-style typecodes, closes #2148
* `#7744 <https://github.com/numpy/numpy/pull/7744>`__: DOC: Remove "ones_like" from ufuncs list (it is not)
* `#7746 <https://github.com/numpy/numpy/pull/7746>`__: DOC: Clarify the effect of rcond in numpy.linalg.lstsq.
* `#7747 <https://github.com/numpy/numpy/pull/7747>`__: Update 7672, BUG: Make sure we don't divide by zero
* `#7748 <https://github.com/numpy/numpy/pull/7748>`__: DOC: Update float32 mean example in docstring
* `#7754 <https://github.com/numpy/numpy/pull/7754>`__: Update 7612, ENH: Add broadcast.ndim to match code elsewhere.
* `#7757 <https://github.com/numpy/numpy/pull/7757>`__: Update 7175, BUG: Invalid read of size 4 in PyArray_FromFile
* `#7759 <https://github.com/numpy/numpy/pull/7759>`__: BUG: Fix numpy.i support for numpy API < 1.7.
* `#7760 <https://github.com/numpy/numpy/pull/7760>`__: ENH: Make assert_almost_equal & assert_array_almost_equal consistent.
* `#7766 <https://github.com/numpy/numpy/pull/7766>`__: fix an English typo
* `#7771 <https://github.com/numpy/numpy/pull/7771>`__: DOC: link geomspace from logspace
* `#7773 <https://github.com/numpy/numpy/pull/7773>`__: DOC: Remove a redundant the
* `#7777 <https://github.com/numpy/numpy/pull/7777>`__: DOC: Update Numpy 1.11.1 release notes.
* `#7785 <https://github.com/numpy/numpy/pull/7785>`__: DOC: update wheel building procedure for release
* `#7789 <https://github.com/numpy/numpy/pull/7789>`__: MRG: add note of 64-bit wheels on Windows
* `#7791 <https://github.com/numpy/numpy/pull/7791>`__: f2py.compile issues (#7683)
* `#7799 <https://github.com/numpy/numpy/pull/7799>`__: "lambda" is not allowed to use as keyword arguments in a sample...
* `#7803 <https://github.com/numpy/numpy/pull/7803>`__: BUG: interpret 'c' PEP3118/struct type as 'S1'.
* `#7807 <https://github.com/numpy/numpy/pull/7807>`__: DOC: Misplaced parens in formula
* `#7817 <https://github.com/numpy/numpy/pull/7817>`__: BUG: Make sure npy_mul_with_overflow_<type> detects overflow.
* `#7818 <https://github.com/numpy/numpy/pull/7818>`__: numpy/distutils/misc_util.py fix for #7809: check that _tmpdirs...
* `#7820 <https://github.com/numpy/numpy/pull/7820>`__: MAINT: Allocate fewer bytes for empty arrays.
* `#7823 <https://github.com/numpy/numpy/pull/7823>`__: BUG: Fixed masked array behavior for scalar inputs to np.ma.atleast_*d
* `#7834 <https://github.com/numpy/numpy/pull/7834>`__: DOC: Added an example
* `#7839 <https://github.com/numpy/numpy/pull/7839>`__: Pypy fixes
* `#7840 <https://github.com/numpy/numpy/pull/7840>`__: Fix ATLAS version detection
* `#7842 <https://github.com/numpy/numpy/pull/7842>`__: Fix versionadded tags
* `#7848 <https://github.com/numpy/numpy/pull/7848>`__: MAINT: Fix remaining uses of deprecated Python imp module.
* `#7853 <https://github.com/numpy/numpy/pull/7853>`__: BUG: Make sure numpy globals keep identity after reload.
* `#7863 <https://github.com/numpy/numpy/pull/7863>`__: ENH: turn quicksort into introsort
* `#7866 <https://github.com/numpy/numpy/pull/7866>`__: Document runtests extra argv
* `#7871 <https://github.com/numpy/numpy/pull/7871>`__: BUG: handle introsort depth limit properly
* `#7879 <https://github.com/numpy/numpy/pull/7879>`__: DOC: fix typo in documentation of loadtxt (closes #7878)
* `#7885 <https://github.com/numpy/numpy/pull/7885>`__: Handle NetBSD specific <sys/endian.h>
* `#7889 <https://github.com/numpy/numpy/pull/7889>`__: DOC: #7881. Fix link to record arrays
* `#7894 <https://github.com/numpy/numpy/pull/7894>`__: fixup-7790, BUG: construct ma.array from np.array which contains...
* `#7898 <https://github.com/numpy/numpy/pull/7898>`__: Spelling and grammar fix.
* `#7903 <https://github.com/numpy/numpy/pull/7903>`__: BUG: fix float16 type not being called due to wrong ordering
* `#7908 <https://github.com/numpy/numpy/pull/7908>`__: BLD: Fixed detection for recent MKL versions
* `#7911 <https://github.com/numpy/numpy/pull/7911>`__: BUG: fix for issue#7835 (ma.median of 1d)
* `#7912 <https://github.com/numpy/numpy/pull/7912>`__: ENH: skip or avoid gc/objectmodel differences btwn pypy and cpython
* `#7918 <https://github.com/numpy/numpy/pull/7918>`__: ENH: allow numpy.apply_along_axis() to work with ndarray subclasses
* `#7922 <https://github.com/numpy/numpy/pull/7922>`__: ENH: Add ma.convolve and ma.correlate for #6458
* `#7925 <https://github.com/numpy/numpy/pull/7925>`__: Monkey-patch _msvccompile.gen_lib_option like any other compilators
* `#7931 <https://github.com/numpy/numpy/pull/7931>`__: BUG: Check for HAVE_LDOUBLE_DOUBLE_DOUBLE_LE in npy_math_complex.
* `#7936 <https://github.com/numpy/numpy/pull/7936>`__: ENH: improve duck typing inside iscomplexobj
* `#7937 <https://github.com/numpy/numpy/pull/7937>`__: BUG: Guard against buggy comparisons in generic quicksort.
* `#7938 <https://github.com/numpy/numpy/pull/7938>`__: DOC: add cbrt to math summary page
* `#7941 <https://github.com/numpy/numpy/pull/7941>`__: BUG: Make sure numpy globals keep identity after reload.
* `#7943 <https://github.com/numpy/numpy/pull/7943>`__: DOC: #7927. Remove deprecated note for memmap relevant for Python...
* `#7952 <https://github.com/numpy/numpy/pull/7952>`__: BUG: Use keyword arguments to initialize Extension base class.
* `#7956 <https://github.com/numpy/numpy/pull/7956>`__: BLD: remove __NUMPY_SETUP__ from builtins at end of setup.py
* `#7963 <https://github.com/numpy/numpy/pull/7963>`__: BUG: MSVCCompiler grows 'lib' & 'include' env strings exponentially.
* `#7965 <https://github.com/numpy/numpy/pull/7965>`__: BUG: cannot modify tuple after use
* `#7976 <https://github.com/numpy/numpy/pull/7976>`__: DOC: Fixed documented dimension of return value
* `#7977 <https://github.com/numpy/numpy/pull/7977>`__: DOC: Create 1.11.2 release notes.
* `#7979 <https://github.com/numpy/numpy/pull/7979>`__: DOC: Corrected allowed keywords in ``add_installed_library``
* `#7980 <https://github.com/numpy/numpy/pull/7980>`__: ENH: Add ability to runtime select ufunc loops, add AVX2 integer...
* `#7985 <https://github.com/numpy/numpy/pull/7985>`__: Rebase 7763, ENH: Add new warning suppression/filtering context
* `#7987 <https://github.com/numpy/numpy/pull/7987>`__: DOC: See also np.load and np.memmap in np.lib.format.open_memmap
* `#7988 <https://github.com/numpy/numpy/pull/7988>`__: DOC: Include docstring for cbrt, spacing and fabs in documentation
* `#7999 <https://github.com/numpy/numpy/pull/7999>`__: ENH: add inplace cases to fast ufunc loop macros
* `#8006 <https://github.com/numpy/numpy/pull/8006>`__: DOC: Update 1.11.2 release notes.
* `#8008 <https://github.com/numpy/numpy/pull/8008>`__: MAINT: Remove leftover imp module imports.
* `#8009 <https://github.com/numpy/numpy/pull/8009>`__: DOC: Fixed three typos in the c-info.ufunc-tutorial
* `#8011 <https://github.com/numpy/numpy/pull/8011>`__: DOC: Update 1.11.2 release notes.
* `#8014 <https://github.com/numpy/numpy/pull/8014>`__: BUG: Fix fid.close() to use os.close(fid)
* `#8016 <https://github.com/numpy/numpy/pull/8016>`__: BUG: Fix numpy.ma.median.
* `#8018 <https://github.com/numpy/numpy/pull/8018>`__: BUG: Fixes return for np.ma.count if keepdims is True and axis...
* `#8021 <https://github.com/numpy/numpy/pull/8021>`__: DOC: change all non-code instances of Numpy to NumPy
* `#8027 <https://github.com/numpy/numpy/pull/8027>`__: ENH: Add platform independent lib dir to PYTHONPATH
* `#8028 <https://github.com/numpy/numpy/pull/8028>`__: DOC: Update 1.11.2 release notes.
* `#8030 <https://github.com/numpy/numpy/pull/8030>`__: BUG: fix np.ma.median with only one non-masked value and an axis...
* `#8038 <https://github.com/numpy/numpy/pull/8038>`__: MAINT: Update error message in rollaxis.
* `#8040 <https://github.com/numpy/numpy/pull/8040>`__: Update add_newdocs.py
* `#8042 <https://github.com/numpy/numpy/pull/8042>`__: BUG: core: fix bug in NpyIter buffering with discontinuous arrays
* `#8045 <https://github.com/numpy/numpy/pull/8045>`__: DOC: Update 1.11.2 release notes.
* `#8050 <https://github.com/numpy/numpy/pull/8050>`__: remove refcount semantics, now a.resize() almost always requires...
* `#8051 <https://github.com/numpy/numpy/pull/8051>`__: Clear signaling NaN exceptions
* `#8054 <https://github.com/numpy/numpy/pull/8054>`__: ENH: add signature argument to vectorize for vectorizing like...
* `#8057 <https://github.com/numpy/numpy/pull/8057>`__: BUG: lib: Simplify (and fix) pad's handling of the pad_width
* `#8061 <https://github.com/numpy/numpy/pull/8061>`__: BUG : financial.pmt modifies input (issue #8055)
* `#8064 <https://github.com/numpy/numpy/pull/8064>`__: MAINT: Add PMIP files to .gitignore
* `#8065 <https://github.com/numpy/numpy/pull/8065>`__: BUG: Assert fromfile ending earlier in pyx_processing
* `#8066 <https://github.com/numpy/numpy/pull/8066>`__: BUG, TST: Fix python3-dbg bug in Travis script
* `#8071 <https://github.com/numpy/numpy/pull/8071>`__: MAINT: Add Tempita to randint helpers
* `#8075 <https://github.com/numpy/numpy/pull/8075>`__: DOC: Fix description of isinf in nan_to_num
* `#8080 <https://github.com/numpy/numpy/pull/8080>`__: BUG: non-integers can end up in dtype offsets
* `#8081 <https://github.com/numpy/numpy/pull/8081>`__: Update outdated Nose URL to nose.readthedocs.io
* `#8083 <https://github.com/numpy/numpy/pull/8083>`__: ENH: Deprecation warnings for `/` integer division when running...
* `#8084 <https://github.com/numpy/numpy/pull/8084>`__: DOC: Fix erroneous return type description for np.roots.
* `#8087 <https://github.com/numpy/numpy/pull/8087>`__: BUG: financial.pmt modifies input #8055
* `#8088 <https://github.com/numpy/numpy/pull/8088>`__: MAINT: Remove duplicate randint helpers code.
* `#8093 <https://github.com/numpy/numpy/pull/8093>`__: MAINT: fix assert_raises_regex when used as a context manager
* `#8096 <https://github.com/numpy/numpy/pull/8096>`__: ENH: Vendorize tempita.
* `#8098 <https://github.com/numpy/numpy/pull/8098>`__: DOC: Enhance description/usage for np.linalg.eig*h
* `#8103 <https://github.com/numpy/numpy/pull/8103>`__: Pypy fixes
* `#8104 <https://github.com/numpy/numpy/pull/8104>`__: Fix test code on cpuinfo's main function
* `#8107 <https://github.com/numpy/numpy/pull/8107>`__: BUG: Fix array printing with precision=0.
* `#8109 <https://github.com/numpy/numpy/pull/8109>`__: Fix bug in ravel_multi_index for big indices (Issue #7546)
* `#8110 <https://github.com/numpy/numpy/pull/8110>`__: BUG: distutils: fix issue with rpath in fcompiler/gnu.py
* `#8111 <https://github.com/numpy/numpy/pull/8111>`__: ENH: Add a tool for release authors and PRs.
* `#8112 <https://github.com/numpy/numpy/pull/8112>`__: DOC: Fix "See also" links in linalg.
* `#8114 <https://github.com/numpy/numpy/pull/8114>`__: BUG: core: add missing error check after PyLong_AsSsize_t
* `#8121 <https://github.com/numpy/numpy/pull/8121>`__: DOC: Improve histogram2d() example.
* `#8122 <https://github.com/numpy/numpy/pull/8122>`__: BUG: Fix broken pickle in MaskedArray when dtype is object (Return...
* `#8124 <https://github.com/numpy/numpy/pull/8124>`__: BUG: Fixed build break
* `#8125 <https://github.com/numpy/numpy/pull/8125>`__: Rebase, BUG: Fixed deepcopy of F-order object arrays.
* `#8127 <https://github.com/numpy/numpy/pull/8127>`__: BUG: integers to a negative integer powers should error.
* `#8141 <https://github.com/numpy/numpy/pull/8141>`__: improve configure checks for broken systems
* `#8142 <https://github.com/numpy/numpy/pull/8142>`__: BUG: np.ma.mean and var should return scalar if no mask
* `#8148 <https://github.com/numpy/numpy/pull/8148>`__: BUG: import full module path in npy_load_module
* `#8153 <https://github.com/numpy/numpy/pull/8153>`__: MAINT: Expose void-scalar "base" attribute in python
* `#8156 <https://github.com/numpy/numpy/pull/8156>`__: DOC: added example with empty indices for a scalar, #8138
* `#8160 <https://github.com/numpy/numpy/pull/8160>`__: BUG: fix _array2string for structured array (issue #5692)
* `#8164 <https://github.com/numpy/numpy/pull/8164>`__: MAINT: Update mailmap for NumPy 1.12.0
* `#8165 <https://github.com/numpy/numpy/pull/8165>`__: Fixup 8152, BUG: assert_allclose(..., equal_nan=False) doesn't...
* `#8167 <https://github.com/numpy/numpy/pull/8167>`__: Fixup 8146, DOC: Clarify when PyArray_{Max, Min, Ptp} return...
* `#8168 <https://github.com/numpy/numpy/pull/8168>`__: DOC: Minor spelling fix in genfromtxt() docstring.
* `#8173 <https://github.com/numpy/numpy/pull/8173>`__: BLD: Enable build on AIX
* `#8174 <https://github.com/numpy/numpy/pull/8174>`__: DOC: warn that dtype.descr is only for use in PEP3118
* `#8177 <https://github.com/numpy/numpy/pull/8177>`__: MAINT: Add python 3.6 support to suppress_warnings
* `#8178 <https://github.com/numpy/numpy/pull/8178>`__: MAINT: Fix ResourceWarning new in Python 3.6.
* `#8180 <https://github.com/numpy/numpy/pull/8180>`__: FIX: protect stolen ref by PyArray_NewFromDescr in array_empty
* `#8181 <https://github.com/numpy/numpy/pull/8181>`__: ENH: Improve announce to find github squash-merge commits.
* `#8182 <https://github.com/numpy/numpy/pull/8182>`__: MAINT: Update .mailmap
* `#8183 <https://github.com/numpy/numpy/pull/8183>`__: MAINT: Ediff1d performance
* `#8184 <https://github.com/numpy/numpy/pull/8184>`__: MAINT: make `assert_allclose` behavior on nans match pre 1.12
* `#8188 <https://github.com/numpy/numpy/pull/8188>`__: DOC: 'highest' is exclusive for randint()
* `#8189 <https://github.com/numpy/numpy/pull/8189>`__: BUG: setfield should raise if arr is not writeable
* `#8190 <https://github.com/numpy/numpy/pull/8190>`__: ENH: Add a float_power function with at least float64 precision.
* `#8197 <https://github.com/numpy/numpy/pull/8197>`__: DOC: Add missing arguments to np.ufunc.outer
* `#8198 <https://github.com/numpy/numpy/pull/8198>`__: DEP: Deprecate the keepdims argument to accumulate
* `#8199 <https://github.com/numpy/numpy/pull/8199>`__: MAINT: change path to env in distutils.system_info. Closes gh-8195.
* `#8200 <https://github.com/numpy/numpy/pull/8200>`__: BUG: Fix structured array format functions
* `#8202 <https://github.com/numpy/numpy/pull/8202>`__: ENH: specialize name of dev package by interpreter
* `#8205 <https://github.com/numpy/numpy/pull/8205>`__: DOC: change development instructions from SSH to HTTPS access.
* `#8216 <https://github.com/numpy/numpy/pull/8216>`__: DOC: Patch doc errors for atleast_nd and frombuffer
* `#8218 <https://github.com/numpy/numpy/pull/8218>`__: BUG: ediff1d should return subclasses
* `#8219 <https://github.com/numpy/numpy/pull/8219>`__: DOC: Turn SciPy references into links.
* `#8222 <https://github.com/numpy/numpy/pull/8222>`__: ENH: Make numpy.mean() do more precise computation
* `#8227 <https://github.com/numpy/numpy/pull/8227>`__: BUG: Better check for invalid bounds in np.random.uniform.
* `#8231 <https://github.com/numpy/numpy/pull/8231>`__: ENH: Refactor numpy ** operators for numpy scalar integer powers
* `#8234 <https://github.com/numpy/numpy/pull/8234>`__: DOC: Clarified when a copy is made in numpy.asarray
* `#8236 <https://github.com/numpy/numpy/pull/8236>`__: DOC: Fix documentation pull requests.
* `#8238 <https://github.com/numpy/numpy/pull/8238>`__: MAINT: Update pavement.py
* `#8239 <https://github.com/numpy/numpy/pull/8239>`__: ENH: Improve announce tool.
* `#8240 <https://github.com/numpy/numpy/pull/8240>`__: REL: Prepare for 1.12.x branch
* `#8243 <https://github.com/numpy/numpy/pull/8243>`__: BUG: Update operator `**` tests for new behavior.
* `#8246 <https://github.com/numpy/numpy/pull/8246>`__: REL: Reset strides for RELAXED_STRIDE_CHECKING for 1.12 releases.
* `#8265 <https://github.com/numpy/numpy/pull/8265>`__: BUG: np.piecewise not working for scalars
* `#8272 <https://github.com/numpy/numpy/pull/8272>`__: TST: Path test should resolve symlinks when comparing
* `#8282 <https://github.com/numpy/numpy/pull/8282>`__: DOC: Update 1.12.0 release notes.
* `#8286 <https://github.com/numpy/numpy/pull/8286>`__: BUG: Fix pavement.py write_release_task.
* `#8296 <https://github.com/numpy/numpy/pull/8296>`__: BUG: Fix iteration over reversed subspaces in mapiter_@name@.
* `#8304 <https://github.com/numpy/numpy/pull/8304>`__: BUG: Fix PyPy crash in PyUFunc_GenericReduction.
* `#8319 <https://github.com/numpy/numpy/pull/8319>`__: BLD: blacklist powl (longdouble power function) on OS X.
* `#8320 <https://github.com/numpy/numpy/pull/8320>`__: BUG: do not link to Accelerate if OpenBLAS, MKL or BLIS are found.
* `#8322 <https://github.com/numpy/numpy/pull/8322>`__: BUG: fixed kind specifications for parameters
* `#8336 <https://github.com/numpy/numpy/pull/8336>`__: BUG: fix packbits and unpackbits to correctly handle empty arrays
* `#8338 <https://github.com/numpy/numpy/pull/8338>`__: BUG: fix test_api test that fails intermittently in python 3
* `#8339 <https://github.com/numpy/numpy/pull/8339>`__: BUG: Fix ndarray.tofile large file corruption in append mode.
* `#8359 <https://github.com/numpy/numpy/pull/8359>`__: BUG: Fix suppress_warnings (again) for Python 3.6.
* `#8372 <https://github.com/numpy/numpy/pull/8372>`__: BUG: Fixes for ma.median and nanpercentile.
* `#8373 <https://github.com/numpy/numpy/pull/8373>`__: BUG: correct letter case
* `#8379 <https://github.com/numpy/numpy/pull/8379>`__: DOC: Update 1.12.0-notes.rst.
* `#8390 <https://github.com/numpy/numpy/pull/8390>`__: ENH: retune apply_along_axis nanmedian cutoff in 1.12
* `#8391 <https://github.com/numpy/numpy/pull/8391>`__: DEP: Fix escaped string characters deprecated in Python 3.6.
* `#8394 <https://github.com/numpy/numpy/pull/8394>`__: DOC: create 1.11.3 release notes.
* `#8399 <https://github.com/numpy/numpy/pull/8399>`__: BUG: Fix author search in announce.py
* `#8402 <https://github.com/numpy/numpy/pull/8402>`__: DOC, MAINT: Update 1.12.0 notes and mailmap.
* `#8418 <https://github.com/numpy/numpy/pull/8418>`__: BUG: Fix ma.median even elements for 1.12
* `#8424 <https://github.com/numpy/numpy/pull/8424>`__: DOC: Fix tools and release notes to be more markdown compatible.
* `#8427 <https://github.com/numpy/numpy/pull/8427>`__: BUG: Add a lock to assert_equal and other testing functions
* `#8431 <https://github.com/numpy/numpy/pull/8431>`__: BUG: Fix apply_along_axis() for when func1d() returns a non-ndarray.
* `#8432 <https://github.com/numpy/numpy/pull/8432>`__: BUG: Let linspace accept input that has an array_interface.
* `#8437 <https://github.com/numpy/numpy/pull/8437>`__: TST: Update 3.6-dev tests to 3.6 after Python final release.
* `#8439 <https://github.com/numpy/numpy/pull/8439>`__: DOC: Update 1.12.0 release notes.
* `#8466 <https://github.com/numpy/numpy/pull/8466>`__: MAINT: Update mailmap entries.
* `#8467 <https://github.com/numpy/numpy/pull/8467>`__: DOC: Back-port the missing part of gh-8464.
* `#8476 <https://github.com/numpy/numpy/pull/8476>`__: DOC: Update 1.12.0 release notes.
* `#8477 <https://github.com/numpy/numpy/pull/8477>`__: DOC: Update 1.12.0 release notes.

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=========
Changelog
=========
Contributors
============
A total of 10 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Charles Harris
* Eric Wieser
* Greg Young
* Joerg Behrmann +
* John Kirkham
* Julian Taylor
* Marten van Kerkwijk
* Matthew Brett
* Shota Kawabuchi
* Jean Utke +
Pull requests merged
====================
* `#8483 <https://github.com/numpy/numpy/pull/8483>`__: BUG: Fix wrong future nat warning and equiv type logic error...
* `#8489 <https://github.com/numpy/numpy/pull/8489>`__: BUG: Fix wrong masked median for some special cases
* `#8490 <https://github.com/numpy/numpy/pull/8490>`__: DOC: Place np.average in inline code
* `#8491 <https://github.com/numpy/numpy/pull/8491>`__: TST: Work around isfinite inconsistency on i386
* `#8494 <https://github.com/numpy/numpy/pull/8494>`__: BUG: Guard against replacing constants without '_' spec in f2py.
* `#8524 <https://github.com/numpy/numpy/pull/8524>`__: BUG: Fix mean for float 16 non-array inputs for 1.12
* `#8571 <https://github.com/numpy/numpy/pull/8571>`__: BUG: Fix calling python api with error set and minor leaks for...
* `#8602 <https://github.com/numpy/numpy/pull/8602>`__: BUG: Make iscomplexobj compatible with custom dtypes again
* `#8618 <https://github.com/numpy/numpy/pull/8618>`__: BUG: Fix undefined behaviour induced by bad __array_wrap__
* `#8648 <https://github.com/numpy/numpy/pull/8648>`__: BUG: Fix MaskedArray.__setitem__
* `#8659 <https://github.com/numpy/numpy/pull/8659>`__: BUG: PPC64el machines are POWER for Fortran in f2py
* `#8665 <https://github.com/numpy/numpy/pull/8665>`__: BUG: Look up methods on MaskedArray in `_frommethod`
* `#8674 <https://github.com/numpy/numpy/pull/8674>`__: BUG: Remove extra digit in binary_repr at limit
* `#8704 <https://github.com/numpy/numpy/pull/8704>`__: BUG: Fix deepcopy regression for empty arrays.
* `#8707 <https://github.com/numpy/numpy/pull/8707>`__: BUG: Fix ma.median for empty ndarrays

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=========
Changelog
=========
Contributors
============
A total of 102 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* A. Jesse Jiryu Davis +
* Alessandro Pietro Bardelli +
* Alex Rothberg +
* Alexander Shadchin
* Allan Haldane
* Andres Guzman-Ballen +
* Antoine Pitrou
* Antony Lee
* B R S Recht +
* Baurzhan Muftakhidinov +
* Ben Rowland
* Benda Xu +
* Blake Griffith
* Bradley Wogsland +
* Brandon Carter +
* CJ Carey
* Charles Harris
* Christoph Gohlke
* Danny Hermes +
* David Hagen +
* Duke Vijitbenjaronk +
* Egor Klenin +
* Elliott Forney +
* Elliott M Forney +
* Endolith
* Eric Wieser
* Erik M. Bray
* Eugene +
* Evan Limanto +
* Felix Berkenkamp +
* François Bissey +
* Frederic Bastien
* Greg Young
* Gregory R. Lee
* Importance of Being Ernest +
* Jaime Fernandez
* Jakub Wilk +
* James Cowgill +
* James Sanders
* Jean Utke +
* Jesse Thoren +
* Jim Crist +
* Joerg Behrmann +
* John Kirkham
* Jonathan Helmus
* Jonathan L Long
* Jonathan Tammo Siebert +
* Joseph Fox-Rabinovitz
* Joshua Loyal +
* Juan Nunez-Iglesias +
* Julian Taylor
* Kirill Balunov +
* Likhith Chitneni +
* Loïc Estève
* Mads Ohm Larsen
* Marein Könings +
* Marten van Kerkwijk
* Martin Thoma
* Martino Sorbaro +
* Marvin Schmidt +
* Matthew Brett
* Matthias Bussonnier +
* Matthias C. M. Troffaes +
* Matti Picus
* Michael Seifert
* Mikhail Pak +
* Mortada Mehyar
* Nathaniel J. Smith
* Nick Papior
* Oscar Villellas +
* Pauli Virtanen
* Pavel Potocek
* Pete Peeradej Tanruangporn +
* Philipp A +
* Ralf Gommers
* Robert Kern
* Roland Kaufmann +
* Ronan Lamy
* Sami Salonen +
* Sanchez Gonzalez Alvaro
* Sebastian Berg
* Shota Kawabuchi
* Simon Gibbons
* Stefan Otte
* Stefan Peterson +
* Stephan Hoyer
* Søren Fuglede Jørgensen +
* Takuya Akiba
* Tom Boyd +
* Ville Skyttä +
* Warren Weckesser
* Wendell Smith
* Yu Feng
* Zixu Zhao +
* Zè Vinícius +
* aha66 +
* davidjn +
* drabach +
* drlvk +
* jsh9 +
* solarjoe +
* zengi +
Pull requests merged
====================
A total of 309 pull requests were merged for this release.
* `#3861 <https://github.com/numpy/numpy/pull/3861>`__: ENH: Make it possible to NpyIter_RemoveAxis an empty dimension
* `#5302 <https://github.com/numpy/numpy/pull/5302>`__: Fixed meshgrid to return arrays with same dtype as arguments.
* `#5726 <https://github.com/numpy/numpy/pull/5726>`__: BUG, API: np.random.multivariate_normal behavior with bad covariance...
* `#6632 <https://github.com/numpy/numpy/pull/6632>`__: TST/BUG: fromfile - fix test and expose bug with io class argument
* `#6659 <https://github.com/numpy/numpy/pull/6659>`__: BUG: Let linspace accept input that has an array_interface.
* `#7742 <https://github.com/numpy/numpy/pull/7742>`__: Add `axis` argument to numpy.unique
* `#7862 <https://github.com/numpy/numpy/pull/7862>`__: BLD: rewrite np.distutils.exec_command.exec_command()
* `#7997 <https://github.com/numpy/numpy/pull/7997>`__: ENH: avoid temporary arrays in expressions (again)
* `#8043 <https://github.com/numpy/numpy/pull/8043>`__: ENH: umath: ensure ufuncs are well-defined with memory overlapping...
* `#8106 <https://github.com/numpy/numpy/pull/8106>`__: DOC: Document release procedure with a walkthrough.
* `#8194 <https://github.com/numpy/numpy/pull/8194>`__: BUG: np.piecewise not working for scalars
* `#8235 <https://github.com/numpy/numpy/pull/8235>`__: BUG: add checks for some invalid structured dtypes. Fixes #2865.
* `#8241 <https://github.com/numpy/numpy/pull/8241>`__: MAINT: Prepare for 1.13.0 after 1.12.x branch
* `#8242 <https://github.com/numpy/numpy/pull/8242>`__: BUG: Update operator `**` tests for new behavior.
* `#8244 <https://github.com/numpy/numpy/pull/8244>`__: DOC: fix typos in arrayprint docstrings.
* `#8247 <https://github.com/numpy/numpy/pull/8247>`__: ENH: Add `__array_ufunc__`
* `#8251 <https://github.com/numpy/numpy/pull/8251>`__: MAINT: Cleaned up mailmap
* `#8267 <https://github.com/numpy/numpy/pull/8267>`__: DOC: Changed shape assignment example to reshape. Elaborated...
* `#8271 <https://github.com/numpy/numpy/pull/8271>`__: TST: Path test should resolve symlinks when comparing
* `#8277 <https://github.com/numpy/numpy/pull/8277>`__: DOC: improve comment in prepare_index
* `#8279 <https://github.com/numpy/numpy/pull/8279>`__: BUG: bool(dtype) is True
* `#8281 <https://github.com/numpy/numpy/pull/8281>`__: DOC: Update 1.12.0 release notes.
* `#8284 <https://github.com/numpy/numpy/pull/8284>`__: BUG: Fix iteration over reversed subspaces in mapiter_@name@
* `#8285 <https://github.com/numpy/numpy/pull/8285>`__: BUG: Fix pavement.py write_release_task.
* `#8287 <https://github.com/numpy/numpy/pull/8287>`__: DOC: Update 1.13.0 release notes.
* `#8290 <https://github.com/numpy/numpy/pull/8290>`__: MAINT: let average preserve subclass information.
* `#8297 <https://github.com/numpy/numpy/pull/8297>`__: DEP: Handle expired deprecations.
* `#8299 <https://github.com/numpy/numpy/pull/8299>`__: BUG: Make f2py respect kind specifications for real parameters
* `#8302 <https://github.com/numpy/numpy/pull/8302>`__: BUG: Fix PyPy crash in PyUFunc_GenericReduction.
* `#8308 <https://github.com/numpy/numpy/pull/8308>`__: BUG: do not link to Accelerate if OpenBLAS, MKL or BLIS are found.
* `#8312 <https://github.com/numpy/numpy/pull/8312>`__: DEP: Drop deprecated boolean indexing behavior and update to...
* `#8318 <https://github.com/numpy/numpy/pull/8318>`__: BLD: blacklist powl (longdouble power function) on OS X.
* `#8326 <https://github.com/numpy/numpy/pull/8326>`__: ENH: Vectorize packbits with SSE2
* `#8327 <https://github.com/numpy/numpy/pull/8327>`__: BUG: Fix packbits to correctly handle empty arrays
* `#8335 <https://github.com/numpy/numpy/pull/8335>`__: BUG: Fix ndarray.tofile large file corruption in append mode
* `#8337 <https://github.com/numpy/numpy/pull/8337>`__: BUG: fix test_api test that fails intermittently in python 3
* `#8343 <https://github.com/numpy/numpy/pull/8343>`__: TST: Ellipsis indexing creates a view
* `#8348 <https://github.com/numpy/numpy/pull/8348>`__: ENH: Allow bincount(..., minlength=0).
* `#8349 <https://github.com/numpy/numpy/pull/8349>`__: BUG: Apply more robust string converts in loadtxt
* `#8351 <https://github.com/numpy/numpy/pull/8351>`__: BUG: correct letter case
* `#8354 <https://github.com/numpy/numpy/pull/8354>`__: BUG: Fix suppress_warnings (again) for Python 3.6.
* `#8355 <https://github.com/numpy/numpy/pull/8355>`__: Fix building extensions with MinGW for Python 3.5
* `#8356 <https://github.com/numpy/numpy/pull/8356>`__: Allow extensions to be built with MinGW in a virtualenv
* `#8360 <https://github.com/numpy/numpy/pull/8360>`__: MAINT: Drop special case code for python2 < 2.7 and python3 <...
* `#8364 <https://github.com/numpy/numpy/pull/8364>`__: BUG: handle unmasked NaN in ma.median like normal median
* `#8366 <https://github.com/numpy/numpy/pull/8366>`__: BUG: fix nanpercentile not returning scalar with axis argument
* `#8367 <https://github.com/numpy/numpy/pull/8367>`__: xlocale.h is not available in newlib / Cygwin
* `#8368 <https://github.com/numpy/numpy/pull/8368>`__: ENH: Implement most linalg operations for 0x0 matrices
* `#8369 <https://github.com/numpy/numpy/pull/8369>`__: TST: Fix various incorrect linalg tests
* `#8374 <https://github.com/numpy/numpy/pull/8374>`__: DOC: Fixed minor typo in William Gosset's name
* `#8377 <https://github.com/numpy/numpy/pull/8377>`__: Switch to the PyPI version of plex to generate lapack_lite
* `#8380 <https://github.com/numpy/numpy/pull/8380>`__: DOC: Update 1.12.0-notes.rst.
* `#8381 <https://github.com/numpy/numpy/pull/8381>`__: MAINT: Rebuild lapack lite
* `#8382 <https://github.com/numpy/numpy/pull/8382>`__: DEP: Fix escaped string characters deprecated in Python 3.6.
* `#8384 <https://github.com/numpy/numpy/pull/8384>`__: ENH: Add tool to check for deprecated escaped characters.
* `#8388 <https://github.com/numpy/numpy/pull/8388>`__: API: Return scalars for scalar inputs to np.real/imag
* `#8389 <https://github.com/numpy/numpy/pull/8389>`__: ENH: retune apply_along_axis nanmedian cutoff
* `#8395 <https://github.com/numpy/numpy/pull/8395>`__: DOC: create 1.11.3 release notes.
* `#8398 <https://github.com/numpy/numpy/pull/8398>`__: BUG: Fix author search in announce.py
* `#8400 <https://github.com/numpy/numpy/pull/8400>`__: Fix `corrcoef` and `cov` rowvar param handling
* `#8401 <https://github.com/numpy/numpy/pull/8401>`__: DOC, MAINT: Update 1.12.0 notes and mailmap.
* `#8410 <https://github.com/numpy/numpy/pull/8410>`__: BUG: Fixed behavior of assert_array_less for +/-inf
* `#8414 <https://github.com/numpy/numpy/pull/8414>`__: BUG: fixed failure of np.ma.median for 1-D even arrays.
* `#8416 <https://github.com/numpy/numpy/pull/8416>`__: BUG operations involving MaskedArray with output given do not...
* `#8421 <https://github.com/numpy/numpy/pull/8421>`__: ENH: Add isnat function and make comparison tests NAT specific
* `#8423 <https://github.com/numpy/numpy/pull/8423>`__: Adding isin function for multidimensional arrays
* `#8426 <https://github.com/numpy/numpy/pull/8426>`__: BUG: Fix apply_along_axis() for when func1d() returns a non-ndarray
* `#8434 <https://github.com/numpy/numpy/pull/8434>`__: TST: Update 3.6-dev tests to 3.6 after Python final release.
* `#8441 <https://github.com/numpy/numpy/pull/8441>`__: BUG: Fix crash on 0d return value in apply_along_axis
* `#8443 <https://github.com/numpy/numpy/pull/8443>`__: BUG: fix set memmap offset attribute correctly when offset is...
* `#8445 <https://github.com/numpy/numpy/pull/8445>`__: BUG: correct norm='ortho' scaling for rfft when n != None
* `#8446 <https://github.com/numpy/numpy/pull/8446>`__: ENH: gradient support for unevenly spaced data
* `#8448 <https://github.com/numpy/numpy/pull/8448>`__: TST: remove a duplicate test. Closes gh-8447.
* `#8452 <https://github.com/numpy/numpy/pull/8452>`__: BUG: assert_almost_equal fails on subclasses that cannot handle...
* `#8454 <https://github.com/numpy/numpy/pull/8454>`__: MAINT: Fix building extensions with MinGW in WinPython 3.4
* `#8464 <https://github.com/numpy/numpy/pull/8464>`__: [DOC]Small release doc fix
* `#8468 <https://github.com/numpy/numpy/pull/8468>`__: BUG: Ensure inf/nan removal in assert_array_compare is matrix-safe.
* `#8470 <https://github.com/numpy/numpy/pull/8470>`__: DOC: Add example to np.savez_compressed
* `#8474 <https://github.com/numpy/numpy/pull/8474>`__: MAINT: use env in shebang instead of absolute path to python
* `#8475 <https://github.com/numpy/numpy/pull/8475>`__: DOC: improve clip docstring
* `#8478 <https://github.com/numpy/numpy/pull/8478>`__: MAINT: Forward port accumulated changes from the 1.12.0 release.
* `#8482 <https://github.com/numpy/numpy/pull/8482>`__: TST: switch to ubuntu yakkety for i386 testing
* `#8483 <https://github.com/numpy/numpy/pull/8483>`__: BUG: fix wrong future nat warning and equiv type logic error
* `#8486 <https://github.com/numpy/numpy/pull/8486>`__: BUG: Prevent crash for length-0 input to fromrecords
* `#8488 <https://github.com/numpy/numpy/pull/8488>`__: ENH: Improve the alignment of `recarray.__repr__`
* `#8489 <https://github.com/numpy/numpy/pull/8489>`__: BUG: fix wrong masked median for some special cases
* `#8490 <https://github.com/numpy/numpy/pull/8490>`__: DOC: Place np.average in inline code
* `#8491 <https://github.com/numpy/numpy/pull/8491>`__: TST: work around isfinite inconsistency on i386
* `#8494 <https://github.com/numpy/numpy/pull/8494>`__: BUG: guard against replacing constants without `'_'` spec
* `#8496 <https://github.com/numpy/numpy/pull/8496>`__: Update LICENSE.txt to 2017
* `#8497 <https://github.com/numpy/numpy/pull/8497>`__: BUG: Fix creating a np.matrix from string syntax involving booleans
* `#8501 <https://github.com/numpy/numpy/pull/8501>`__: Changing spurious Legendre reference to Chebyshev in chebfit...
* `#8504 <https://github.com/numpy/numpy/pull/8504>`__: ENH: hard-code finfo parameters for known types
* `#8508 <https://github.com/numpy/numpy/pull/8508>`__: BUG: Fix loss of dimensionality of np.ma.masked in ufunc
* `#8524 <https://github.com/numpy/numpy/pull/8524>`__: BUG: fix mean for float 16 non-array inputs
* `#8527 <https://github.com/numpy/numpy/pull/8527>`__: DOC: fix return value for PyArray_Resize
* `#8539 <https://github.com/numpy/numpy/pull/8539>`__: BUG: core: in dot(), make copies if out has memory overlap with...
* `#8540 <https://github.com/numpy/numpy/pull/8540>`__: DOC: Update arrays.ndarray.rst
* `#8541 <https://github.com/numpy/numpy/pull/8541>`__: DOC: Revert 8540 patch 1
* `#8542 <https://github.com/numpy/numpy/pull/8542>`__: MAINT: typo in histogram docstring
* `#8551 <https://github.com/numpy/numpy/pull/8551>`__: DOC: Missing backticks
* `#8555 <https://github.com/numpy/numpy/pull/8555>`__: Fixing docstring error in polyvander2d
* `#8558 <https://github.com/numpy/numpy/pull/8558>`__: DOC: Improve documentation of None as interval bounds in clip.
* `#8567 <https://github.com/numpy/numpy/pull/8567>`__: TST: core: use aligned memory for dot() out= arrays
* `#8568 <https://github.com/numpy/numpy/pull/8568>`__: TST: re-enable PPC longdouble spacing tests
* `#8569 <https://github.com/numpy/numpy/pull/8569>`__: ENH: Add missing `__tracebackhide__` to testing functions.
* `#8570 <https://github.com/numpy/numpy/pull/8570>`__: BUG: fix issue #8250 when np.array gets called on an invalid...
* `#8571 <https://github.com/numpy/numpy/pull/8571>`__: BUG: fix calling python api with error set and minor leaks
* `#8572 <https://github.com/numpy/numpy/pull/8572>`__: MAINT: remove ma out= workaround
* `#8575 <https://github.com/numpy/numpy/pull/8575>`__: DOC: fix several typos #8537.
* `#8584 <https://github.com/numpy/numpy/pull/8584>`__: MAINT: Use the same exception for all bad axis requests
* `#8586 <https://github.com/numpy/numpy/pull/8586>`__: MAINT: PyPy3 compatibility: sys.getsizeof()
* `#8590 <https://github.com/numpy/numpy/pull/8590>`__: BUG MaskedArray `__eq__` wrong for masked scalar, multi-d recarray
* `#8591 <https://github.com/numpy/numpy/pull/8591>`__: BUG: make np.squeeze always return an array, never a scalar
* `#8592 <https://github.com/numpy/numpy/pull/8592>`__: MAINT: Remove `__setslice__` and `__getslice__`
* `#8594 <https://github.com/numpy/numpy/pull/8594>`__: BUG: Fix `MaskedArray.__setitem__`
* `#8596 <https://github.com/numpy/numpy/pull/8596>`__: BUG: match hard-coded finfo to calculated MachAr
* `#8602 <https://github.com/numpy/numpy/pull/8602>`__: BUG: Make iscomplexobj compatible with custom dtypes again
* `#8605 <https://github.com/numpy/numpy/pull/8605>`__: DOC: gradient uses 1st order central difference in the interior
* `#8606 <https://github.com/numpy/numpy/pull/8606>`__: Revert "DOC: gradient uses 1st order central difference in the...
* `#8610 <https://github.com/numpy/numpy/pull/8610>`__: Revert "BUG: make np.squeeze always return an array, never a...
* `#8611 <https://github.com/numpy/numpy/pull/8611>`__: DOC: The axis argument of average can be a tuple of ints
* `#8612 <https://github.com/numpy/numpy/pull/8612>`__: MAINT: Decrease merge conflicts in release notes
* `#8614 <https://github.com/numpy/numpy/pull/8614>`__: BUG: Don't leak internal exceptions when given an empty array
* `#8617 <https://github.com/numpy/numpy/pull/8617>`__: BUG: Copy meshgrid after broadcasting
* `#8618 <https://github.com/numpy/numpy/pull/8618>`__: BUG: Fix undefined behaviour induced by bad `__array_wrap__`
* `#8619 <https://github.com/numpy/numpy/pull/8619>`__: BUG: blas_info should record include_dirs
* `#8625 <https://github.com/numpy/numpy/pull/8625>`__: DOC: Create 1.12.1 release notes.
* `#8629 <https://github.com/numpy/numpy/pull/8629>`__: ENH: Improve the efficiency of indices
* `#8631 <https://github.com/numpy/numpy/pull/8631>`__: Fix typo in fill_diagonal docstring.
* `#8633 <https://github.com/numpy/numpy/pull/8633>`__: DOC: Mention boolean arrays in the ix_ documentation.
* `#8636 <https://github.com/numpy/numpy/pull/8636>`__: MAINT: ensure benchmark suite is importable on old numpy versions
* `#8638 <https://github.com/numpy/numpy/pull/8638>`__: BUG: fix wrong odd determination in packbits
* `#8643 <https://github.com/numpy/numpy/pull/8643>`__: BUG: Fix double-wrapping of object scalars
* `#8645 <https://github.com/numpy/numpy/pull/8645>`__: MAINT: Use getmask where possible
* `#8646 <https://github.com/numpy/numpy/pull/8646>`__: ENH: Allow for an in-place nan_to_num conversion
* `#8647 <https://github.com/numpy/numpy/pull/8647>`__: Fix various bugs in np.ma.where
* `#8649 <https://github.com/numpy/numpy/pull/8649>`__: Upgrade to Lapack lite 3.2.2
* `#8650 <https://github.com/numpy/numpy/pull/8650>`__: DOC: Fix obsolete data in readme
* `#8651 <https://github.com/numpy/numpy/pull/8651>`__: MAINT: Split lapack_lite more logically across files
* `#8652 <https://github.com/numpy/numpy/pull/8652>`__: TST: Improve testing of read-only mmaps
* `#8655 <https://github.com/numpy/numpy/pull/8655>`__: MAINT: Squelch parenthesis warnings from GCC
* `#8656 <https://github.com/numpy/numpy/pull/8656>`__: BUG: allow for precision > 17 in longdouble repr test
* `#8658 <https://github.com/numpy/numpy/pull/8658>`__: BUG: fix denormal linspace test for longdouble
* `#8659 <https://github.com/numpy/numpy/pull/8659>`__: BUG: PPC64el machines are POWER for Fortran
* `#8663 <https://github.com/numpy/numpy/pull/8663>`__: ENH: Fix alignment of repr for array subclasses
* `#8665 <https://github.com/numpy/numpy/pull/8665>`__: BUG: Look up methods on MaskedArray in _frommethod
* `#8667 <https://github.com/numpy/numpy/pull/8667>`__: BUG: Preserve identity of dtypes in make_mask_descr
* `#8668 <https://github.com/numpy/numpy/pull/8668>`__: DOC: Add more examples for `np.c_`
* `#8669 <https://github.com/numpy/numpy/pull/8669>`__: MAINT: Warn users when calling np.ma.MaskedArray.partition function.
* `#8672 <https://github.com/numpy/numpy/pull/8672>`__: BUG: Use int for axes, not intp
* `#8674 <https://github.com/numpy/numpy/pull/8674>`__: BUG: Remove extra digit in binary_repr at limit
* `#8675 <https://github.com/numpy/numpy/pull/8675>`__: BUG: Fix problems detecting runtime for MSYS2 compiler on Windows
* `#8677 <https://github.com/numpy/numpy/pull/8677>`__: MAINT: We can now rely on itertools.izip_longest existing
* `#8678 <https://github.com/numpy/numpy/pull/8678>`__: BUG: Fix argsort vs sort in Masked arrays
* `#8680 <https://github.com/numpy/numpy/pull/8680>`__: DOC: Removed broken link
* `#8682 <https://github.com/numpy/numpy/pull/8682>`__: ENH: allow argument to matrix_rank to be stacked
* `#8685 <https://github.com/numpy/numpy/pull/8685>`__: ENH: add dtype.ndim
* `#8688 <https://github.com/numpy/numpy/pull/8688>`__: DOC: Added note to np.diff
* `#8692 <https://github.com/numpy/numpy/pull/8692>`__: MAINT: Fix deprecated escape sequences
* `#8694 <https://github.com/numpy/numpy/pull/8694>`__: BUG: missing comma disabled some header checks
* `#8695 <https://github.com/numpy/numpy/pull/8695>`__: MAINT: Remove numpy-macosx-installer and win32build directories.
* `#8698 <https://github.com/numpy/numpy/pull/8698>`__: DOC: fix incorrect mask value when value was changed
* `#8702 <https://github.com/numpy/numpy/pull/8702>`__: DOC: Fixed small mistakes in numpy.copy documentation.
* `#8704 <https://github.com/numpy/numpy/pull/8704>`__: BUG: Fix deepcopy regression for empty arrays.
* `#8705 <https://github.com/numpy/numpy/pull/8705>`__: BUG: fix ma.median for empty ndarrays
* `#8709 <https://github.com/numpy/numpy/pull/8709>`__: DOC: Fixed minor typos in temp_elide.c
* `#8713 <https://github.com/numpy/numpy/pull/8713>`__: BUG: Don't signal FP exceptions in np.absolute
* `#8716 <https://github.com/numpy/numpy/pull/8716>`__: MAINT: Mark some tests with slow decorator
* `#8718 <https://github.com/numpy/numpy/pull/8718>`__: BUG: Fix assert statements in random.choice tests
* `#8729 <https://github.com/numpy/numpy/pull/8729>`__: DOC: Add float_power to routines.math documentation autosummary
* `#8731 <https://github.com/numpy/numpy/pull/8731>`__: DOC: added linalg.multi_dot to doc
* `#8737 <https://github.com/numpy/numpy/pull/8737>`__: DOC: Mention that expand_dims and squeeze are inverses
* `#8744 <https://github.com/numpy/numpy/pull/8744>`__: MAINT: Remove files and constants that were only needed for Bento.
* `#8745 <https://github.com/numpy/numpy/pull/8745>`__: TST: Remove unused env from tox
* `#8746 <https://github.com/numpy/numpy/pull/8746>`__: DOC: Update 1.12.1 release notes.
* `#8749 <https://github.com/numpy/numpy/pull/8749>`__: DOC: Add 1.12.1 release notes to documentation.
* `#8750 <https://github.com/numpy/numpy/pull/8750>`__: BUG: Fix np.average for object arrays
* `#8754 <https://github.com/numpy/numpy/pull/8754>`__: ENH: Allows building npy_math with static inlining
* `#8756 <https://github.com/numpy/numpy/pull/8756>`__: BUG: Correct lapack ld* args
* `#8759 <https://github.com/numpy/numpy/pull/8759>`__: BUG: Add HOME to the git environment.
* `#8761 <https://github.com/numpy/numpy/pull/8761>`__: MAINT: better warning message when running build_src from sdist
* `#8762 <https://github.com/numpy/numpy/pull/8762>`__: BUG: Prevent crash in `poly1d.__eq__`
* `#8781 <https://github.com/numpy/numpy/pull/8781>`__: BUG: Revert gh-8570.
* `#8788 <https://github.com/numpy/numpy/pull/8788>`__: BUG: Fix scipy incompatibility with cleanup to poly1d
* `#8792 <https://github.com/numpy/numpy/pull/8792>`__: DOC: Fix typos
* `#8793 <https://github.com/numpy/numpy/pull/8793>`__: DOC: fix minor docstring typos
* `#8795 <https://github.com/numpy/numpy/pull/8795>`__: ENH: Add the 'heaviside' ufunc.
* `#8796 <https://github.com/numpy/numpy/pull/8796>`__: BUG: fix regex of determineexprtype_re_3 in numpy/f2py/crackfortran.py
* `#8799 <https://github.com/numpy/numpy/pull/8799>`__: DOC: Include np. prefix in meshgrid examples
* `#8801 <https://github.com/numpy/numpy/pull/8801>`__: BUG: fix the error msg of empty hstack input
* `#8806 <https://github.com/numpy/numpy/pull/8806>`__: BUG: Raise TypeError on ternary power
* `#8807 <https://github.com/numpy/numpy/pull/8807>`__: TST: Prove that poly1d coeffs are immutable
* `#8813 <https://github.com/numpy/numpy/pull/8813>`__: MAINT: tidy up some of npyio
* `#8816 <https://github.com/numpy/numpy/pull/8816>`__: BUG: `np.lib.index_tricks.r_` mutates its own state
* `#8820 <https://github.com/numpy/numpy/pull/8820>`__: DOC: Add 'heaviside' to the ufunc documentation.
* `#8822 <https://github.com/numpy/numpy/pull/8822>`__: DOC: Use gray and hsv colormaps in examples
* `#8824 <https://github.com/numpy/numpy/pull/8824>`__: MAINT: a couple distutils cleanups
* `#8825 <https://github.com/numpy/numpy/pull/8825>`__: STY: Fix bad style in umath_linalg
* `#8828 <https://github.com/numpy/numpy/pull/8828>`__: DOC: Add missing release note for #8584
* `#8830 <https://github.com/numpy/numpy/pull/8830>`__: DOC: added a whitespace so that sphinx directive displays correctly
* `#8832 <https://github.com/numpy/numpy/pull/8832>`__: MAINT: Remove python <2.7,<3.3 string/unicode workarounds
* `#8834 <https://github.com/numpy/numpy/pull/8834>`__: BENCH: use initialized memory for count_nonzero benchmark
* `#8835 <https://github.com/numpy/numpy/pull/8835>`__: DOC: Include nextafter and spacing function in documentation.
* `#8836 <https://github.com/numpy/numpy/pull/8836>`__: DOC: Several documentation fixes (broken links, incorrect sphinx...
* `#8837 <https://github.com/numpy/numpy/pull/8837>`__: DOC: Spell out note for `hstack`
* `#8840 <https://github.com/numpy/numpy/pull/8840>`__: DOC: update docs and comments for move of mailing list to python.org
* `#8843 <https://github.com/numpy/numpy/pull/8843>`__: MAINT: Use AxisError in more places
* `#8844 <https://github.com/numpy/numpy/pull/8844>`__: DOC: Spell out note for `dstack`
* `#8845 <https://github.com/numpy/numpy/pull/8845>`__: DOC: Add release note about np.real and np.conj
* `#8846 <https://github.com/numpy/numpy/pull/8846>`__: BUG: Buttress handling of extreme values in randint
* `#8847 <https://github.com/numpy/numpy/pull/8847>`__: DOC: Preliminary edit of 1.13.0 release notes.
* `#8850 <https://github.com/numpy/numpy/pull/8850>`__: DOC: Updated doc of nonzero()
* `#8852 <https://github.com/numpy/numpy/pull/8852>`__: MAINT: restore auto-vectorization of inplace operations
* `#8854 <https://github.com/numpy/numpy/pull/8854>`__: MAINT: Remove manual expansion of template loop for some ufuncs
* `#8857 <https://github.com/numpy/numpy/pull/8857>`__: DOC: remove empty jargon reference in glossary
* `#8859 <https://github.com/numpy/numpy/pull/8859>`__: DOC: Fixed README formatting
* `#8861 <https://github.com/numpy/numpy/pull/8861>`__: MAINT: Include the function name in all argument error messages
* `#8862 <https://github.com/numpy/numpy/pull/8862>`__: BUG: do not memcpy ptr to freed object
* `#8870 <https://github.com/numpy/numpy/pull/8870>`__: TST: Respect compiler customizations
* `#8871 <https://github.com/numpy/numpy/pull/8871>`__: DOC: Replace line that was errantly removed in #8850
* `#8873 <https://github.com/numpy/numpy/pull/8873>`__: BUG: Make runtests.py --shell behave better on windows
* `#8874 <https://github.com/numpy/numpy/pull/8874>`__: TST: Use explicit NaT in test_structure_format
* `#8876 <https://github.com/numpy/numpy/pull/8876>`__: MAINT: Minor ufunc cleanup
* `#8883 <https://github.com/numpy/numpy/pull/8883>`__: BUG: Ensure Errors are correctly checked when PyFloat_AsDouble...
* `#8884 <https://github.com/numpy/numpy/pull/8884>`__: BUG: Check for errors when PyInt_AsLong is called in np.random
* `#8885 <https://github.com/numpy/numpy/pull/8885>`__: ENH: add support for python3.6 memory tracing
* `#8886 <https://github.com/numpy/numpy/pull/8886>`__: ENH: add np.block to improve upon np.bmat
* `#8888 <https://github.com/numpy/numpy/pull/8888>`__: BUG: Don't modify types after PyType_Ready
* `#8890 <https://github.com/numpy/numpy/pull/8890>`__: DOC: proposed fixes for issues #7622 and #7914
* `#8894 <https://github.com/numpy/numpy/pull/8894>`__: MAINT: Use PyArray_FROM_* macros
* `#8895 <https://github.com/numpy/numpy/pull/8895>`__: BUG: return values of exec_command were swapped
* `#8896 <https://github.com/numpy/numpy/pull/8896>`__: ENH: do integer**2. inplace
* `#8897 <https://github.com/numpy/numpy/pull/8897>`__: ENH: don't rebuild unchanged files
* `#8898 <https://github.com/numpy/numpy/pull/8898>`__: BUG: Move ctypes ImportError catching to appropriate place
* `#8900 <https://github.com/numpy/numpy/pull/8900>`__: Fix typos.
* `#8903 <https://github.com/numpy/numpy/pull/8903>`__: BUG: Fix setitem on UNICODE, STRING, and LONGDOUBLE
* `#8905 <https://github.com/numpy/numpy/pull/8905>`__: BUG: Correctly distinguish between 0d arrays and scalars in `MaskedArray.__getitem__`
* `#8907 <https://github.com/numpy/numpy/pull/8907>`__: COMPAT: notify garbage collector when memory is allocated
* `#8911 <https://github.com/numpy/numpy/pull/8911>`__: BUG: check_api_dict does not correctly handle tuple values
* `#8914 <https://github.com/numpy/numpy/pull/8914>`__: DOC: Replace reference to np.swapaxis with np.swapaxes
* `#8918 <https://github.com/numpy/numpy/pull/8918>`__: DEP: deprecate calling ma.argsort without an axis
* `#8919 <https://github.com/numpy/numpy/pull/8919>`__: MAINT, TST: Remove duplicated code for testing the two types...
* `#8921 <https://github.com/numpy/numpy/pull/8921>`__: MAINT: avoid memcpy when i == j
* `#8925 <https://github.com/numpy/numpy/pull/8925>`__: DOC: Fix incorrect call to set_printoptions
* `#8928 <https://github.com/numpy/numpy/pull/8928>`__: BUG: runtests --bench fails on windows
* `#8929 <https://github.com/numpy/numpy/pull/8929>`__: BENCH: Masked array benchmarks
* `#8939 <https://github.com/numpy/numpy/pull/8939>`__: DEP: Deprecate `np.ma.MaskedArray.mini`
* `#8942 <https://github.com/numpy/numpy/pull/8942>`__: DOC: stop referring to 'S' dtype as string
* `#8948 <https://github.com/numpy/numpy/pull/8948>`__: DEP: Deprecate NPY_CHAR
* `#8949 <https://github.com/numpy/numpy/pull/8949>`__: REL: add `python_requires` to setup.py
* `#8951 <https://github.com/numpy/numpy/pull/8951>`__: ENH: Add ufunc.identity for hypot and logical_xor
* `#8953 <https://github.com/numpy/numpy/pull/8953>`__: DEP: Add back `ndarray.__[sg]etslice__`, but deprecate it
* `#8959 <https://github.com/numpy/numpy/pull/8959>`__: DEP: Remove alter/restore dot methods
* `#8961 <https://github.com/numpy/numpy/pull/8961>`__: MAINT: Update Intel compiler options.
* `#8962 <https://github.com/numpy/numpy/pull/8962>`__: DOC: Wrong return type of np.random.choice and wrong variable...
* `#8963 <https://github.com/numpy/numpy/pull/8963>`__: BUG: Prevent crash on repr of recursive array
* `#8964 <https://github.com/numpy/numpy/pull/8964>`__: BUG: don't create array with invalid memory in where
* `#8967 <https://github.com/numpy/numpy/pull/8967>`__: ENH: add np.positive ufunc
* `#8971 <https://github.com/numpy/numpy/pull/8971>`__: BUG: do not change size 0 description when viewing data
* `#8976 <https://github.com/numpy/numpy/pull/8976>`__: BUG: Prevent VOID_copyswapn ignoring strides
* `#8978 <https://github.com/numpy/numpy/pull/8978>`__: TST: enable shadowed test
* `#8980 <https://github.com/numpy/numpy/pull/8980>`__: DOC: Correct shape of edges in np.histogram2d
* `#8988 <https://github.com/numpy/numpy/pull/8988>`__: DOC: Explain the behavior of diff on unsigned types
* `#8989 <https://github.com/numpy/numpy/pull/8989>`__: ENH: Print object arrays containing lists unambiguously
* `#8996 <https://github.com/numpy/numpy/pull/8996>`__: BUG/DEP: Make ufunclike functions more ufunc-like
* `#8997 <https://github.com/numpy/numpy/pull/8997>`__: TST: fix io test that doesn't close file
* `#8998 <https://github.com/numpy/numpy/pull/8998>`__: DOC: Use ` instead of * to refer to a function parameter.
* `#8999 <https://github.com/numpy/numpy/pull/8999>`__: TST: Enable NPY_RELAXED_STRIDES_DEBUG environment variable.
* `#9002 <https://github.com/numpy/numpy/pull/9002>`__: MAINT: Document ufunc(where=...) as defaulting to True
* `#9012 <https://github.com/numpy/numpy/pull/9012>`__: MAINT: Set the `__name__` of generated methods
* `#9013 <https://github.com/numpy/numpy/pull/9013>`__: BUG: Fix np.lib.nanfunctions on object arrays
* `#9014 <https://github.com/numpy/numpy/pull/9014>`__: BUG: `__array_ufunc__= None` -> TypeError
* `#9015 <https://github.com/numpy/numpy/pull/9015>`__: ENH: Use `__array_ufunc__ = None` in polynomial convenience classes.
* `#9021 <https://github.com/numpy/numpy/pull/9021>`__: BUG: Make ndarray inplace operators forward calls when needed.
* `#9024 <https://github.com/numpy/numpy/pull/9024>`__: DOC: Correct default stop index value for negative stepping.
* `#9026 <https://github.com/numpy/numpy/pull/9026>`__: ENH: Show full PEP 457 argument lists for ufuncs
* `#9027 <https://github.com/numpy/numpy/pull/9027>`__: DOC: update binary-op / ufunc interactions and recommendations...
* `#9038 <https://github.com/numpy/numpy/pull/9038>`__: BUG: check compiler flags to determine the need for a rebuild
* `#9039 <https://github.com/numpy/numpy/pull/9039>`__: DOC: actually produce docs for as_strided
* `#9050 <https://github.com/numpy/numpy/pull/9050>`__: BUG: distutils, add compatibility python parallelization
* `#9054 <https://github.com/numpy/numpy/pull/9054>`__: BUG: Various fixes to _dtype_from_pep3118
* `#9058 <https://github.com/numpy/numpy/pull/9058>`__: MAINT: Update FutureWarning message.
* `#9060 <https://github.com/numpy/numpy/pull/9060>`__: DEP: deprecate ndarray.conjugate's no-op fall through for non-numeric...
* `#9061 <https://github.com/numpy/numpy/pull/9061>`__: BUG: ndarray.conjugate broken for custom dtypes (unlike np.conjugate)
* `#9062 <https://github.com/numpy/numpy/pull/9062>`__: STY: two blank lines between classes per PEP8
* `#9063 <https://github.com/numpy/numpy/pull/9063>`__: ENH: add np.divmod ufunc
* `#9070 <https://github.com/numpy/numpy/pull/9070>`__: BUG: Preserve field order in join_by, avoids FutureWarning
* `#9072 <https://github.com/numpy/numpy/pull/9072>`__: BUG: if importing multiarray fails, don't discard the error message
* `#9074 <https://github.com/numpy/numpy/pull/9074>`__: MAINT: Python 3.6 invalid escape sequence deprecation fixes
* `#9075 <https://github.com/numpy/numpy/pull/9075>`__: ENH: Spelling fixes
* `#9077 <https://github.com/numpy/numpy/pull/9077>`__: BUG: Prevent stackoverflow on self-containing arrays
* `#9080 <https://github.com/numpy/numpy/pull/9080>`__: MAINT, DOC: Update 1.13.0 release notes and .mailmap
* `#9087 <https://github.com/numpy/numpy/pull/9087>`__: BUG: `__array_ufunc__` should always be looked up on the type,...
* `#9091 <https://github.com/numpy/numpy/pull/9091>`__: MAINT: refine error message for `__array_ufunc__` not implemented
* `#9093 <https://github.com/numpy/numpy/pull/9093>`__: BUG remove memory leak in array ufunc override.
* `#9097 <https://github.com/numpy/numpy/pull/9097>`__: TST: fix test_basic failure on Windows
* `#9111 <https://github.com/numpy/numpy/pull/9111>`__: BUG: Array ufunc reduce out tuple
* `#9123 <https://github.com/numpy/numpy/pull/9123>`__: DOC: update 1.13 release note for MaskedArray, masked constants...
* `#9124 <https://github.com/numpy/numpy/pull/9124>`__: BUG: Do not elide complex abs() for 1.13
* `#9129 <https://github.com/numpy/numpy/pull/9129>`__: BUG: `ndarray.__pow__` does not check result of fast_scalar_power
* `#9133 <https://github.com/numpy/numpy/pull/9133>`__: DEP: Deprecate incorrect behavior of expand_dims.
* `#9135 <https://github.com/numpy/numpy/pull/9135>`__: BUG: delay calls of array repr in getlimits
* `#9136 <https://github.com/numpy/numpy/pull/9136>`__: BUG: Compilation crashes in MSVC when LIB or INCLUDE is not set
* `#9173 <https://github.com/numpy/numpy/pull/9173>`__: BUG: have as_strided() keep custom dtypes
* `#9175 <https://github.com/numpy/numpy/pull/9175>`__: BUG: ensure structured `ndarray.__eq__,__ne__` defer when appropriate.
* `#9196 <https://github.com/numpy/numpy/pull/9196>`__: BUG: pull request 9087 modifies a tuple after use
* `#9199 <https://github.com/numpy/numpy/pull/9199>`__: DOC: Update bincount docs to reflect gh-8348 (backport)

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Contributors
============
A total of 12 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Andras Deak +
* Bob Eldering +
* Charles Harris
* Daniel Hrisca +
* Eric Wieser
* Joshua Leahy +
* Julian Taylor
* Michael Seifert
* Pauli Virtanen
* Ralf Gommers
* Roland Kaufmann
* Warren Weckesser
Pull requests merged
====================
A total of 19 pull requests were merged for this release.
* `#9240 <https://github.com/numpy/numpy/pull/9240>`__: DOC: BLD: fix lots of Sphinx warnings/errors.
* `#9255 <https://github.com/numpy/numpy/pull/9255>`__: Revert "DEP: Raise TypeError for subtract(bool_, bool_)."
* `#9261 <https://github.com/numpy/numpy/pull/9261>`__: BUG: don't elide into readonly and updateifcopy temporaries for...
* `#9262 <https://github.com/numpy/numpy/pull/9262>`__: BUG: fix missing keyword rename for common block in numpy.f2py
* `#9263 <https://github.com/numpy/numpy/pull/9263>`__: BUG: handle resize of 0d array
* `#9267 <https://github.com/numpy/numpy/pull/9267>`__: DOC: update f2py front page and some doc build metadata.
* `#9299 <https://github.com/numpy/numpy/pull/9299>`__: BUG: Fix Intel compilation on Unix.
* `#9317 <https://github.com/numpy/numpy/pull/9317>`__: BUG: fix wrong ndim used in empty where check
* `#9319 <https://github.com/numpy/numpy/pull/9319>`__: BUG: Make extensions compilable with MinGW on Py2.7
* `#9339 <https://github.com/numpy/numpy/pull/9339>`__: BUG: Prevent crash if ufunc doc string is null
* `#9340 <https://github.com/numpy/numpy/pull/9340>`__: BUG: umath: un-break ufunc where= when no out= is given
* `#9371 <https://github.com/numpy/numpy/pull/9371>`__: DOC: Add isnat/positive ufunc to documentation
* `#9372 <https://github.com/numpy/numpy/pull/9372>`__: BUG: Fix error in fromstring function from numpy.core.records...
* `#9373 <https://github.com/numpy/numpy/pull/9373>`__: BUG: ')' is printed at the end pointer of the buffer in numpy.f2py.
* `#9374 <https://github.com/numpy/numpy/pull/9374>`__: DOC: Create NumPy 1.13.1 release notes.
* `#9376 <https://github.com/numpy/numpy/pull/9376>`__: BUG: Prevent hang traversing ufunc userloop linked list
* `#9377 <https://github.com/numpy/numpy/pull/9377>`__: DOC: Use x1 and x2 in the heaviside docstring.
* `#9378 <https://github.com/numpy/numpy/pull/9378>`__: DOC: Add $PARAMS to the isnat docstring
* `#9379 <https://github.com/numpy/numpy/pull/9379>`__: DOC: Update the 1.13.1 release notes

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Contributors
============
A total of 12 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Allan Haldane
* Brandon Carter
* Charles Harris
* Eric Wieser
* Iryna Shcherbina +
* James Bourbeau +
* Jonathan Helmus
* Julian Taylor
* Matti Picus
* Michael Lamparski +
* Michael Seifert
* Ralf Gommers
Pull requests merged
====================
A total of 21 pull requests were merged for this release.
* `#9390 <https://github.com/numpy/numpy/pull/9390>`__: BUG: Return the poly1d coefficients array directly
* `#9555 <https://github.com/numpy/numpy/pull/9555>`__: BUG: fix regression in 1.13.x in distutils.mingw32ccompiler.
* `#9556 <https://github.com/numpy/numpy/pull/9556>`__: BUG: Fix true_divide when dtype=np.float64 specified.
* `#9557 <https://github.com/numpy/numpy/pull/9557>`__: DOC: Fix some rst markup in numpy/doc/basics.py.
* `#9558 <https://github.com/numpy/numpy/pull/9558>`__: BLD: remove -xhost flag from IntelFCompiler.
* `#9559 <https://github.com/numpy/numpy/pull/9559>`__: DOC: removes broken docstring example (source code, png, pdf)...
* `#9580 <https://github.com/numpy/numpy/pull/9580>`__: BUG: Add hypot and cabs functions to WIN32 blacklist.
* `#9732 <https://github.com/numpy/numpy/pull/9732>`__: BUG: Make scalar function elision check if temp is writeable.
* `#9736 <https://github.com/numpy/numpy/pull/9736>`__: BUG: various fixes to np.gradient
* `#9742 <https://github.com/numpy/numpy/pull/9742>`__: BUG: Fix np.pad for CVE-2017-12852
* `#9744 <https://github.com/numpy/numpy/pull/9744>`__: BUG: Check for exception in sort functions, add tests
* `#9745 <https://github.com/numpy/numpy/pull/9745>`__: DOC: Add whitespace after "versionadded::" directive so it actually...
* `#9746 <https://github.com/numpy/numpy/pull/9746>`__: BUG: memory leak in np.dot of size 0
* `#9747 <https://github.com/numpy/numpy/pull/9747>`__: BUG: adjust gfortran version search regex
* `#9757 <https://github.com/numpy/numpy/pull/9757>`__: BUG: Cython 0.27 breaks NumPy on Python 3.
* `#9764 <https://github.com/numpy/numpy/pull/9764>`__: BUG: Ensure `_npy_scaled_cexp{,f,l}` is defined when needed.
* `#9765 <https://github.com/numpy/numpy/pull/9765>`__: BUG: PyArray_CountNonzero does not check for exceptions
* `#9766 <https://github.com/numpy/numpy/pull/9766>`__: BUG: Fixes histogram monotonicity check for unsigned bin values
* `#9767 <https://github.com/numpy/numpy/pull/9767>`__: BUG: ensure consistent result dtype of count_nonzero
* `#9771 <https://github.com/numpy/numpy/pull/9771>`__: MAINT,BUG: Fix mtrand for Cython 0.27.
* `#9772 <https://github.com/numpy/numpy/pull/9772>`__: DOC: Create the 1.13.2 release notes.

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Contributors
============
A total of 19 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Allan Haldane
* Andras Deak +
* Bob Eldering +
* Brandon Carter
* Charles Harris
* Daniel Hrisca +
* Eric Wieser
* Iryna Shcherbina +
* James Bourbeau +
* Jonathan Helmus
* Joshua Leahy +
* Julian Taylor
* Matti Picus
* Michael Lamparski +
* Michael Seifert
* Pauli Virtanen
* Ralf Gommers
* Roland Kaufmann
* Warren Weckesser
Pull requests merged
====================
A total of 41 pull requests were merged for this release.
* `#9240 <https://github.com/numpy/numpy/pull/9240>`__: DOC: BLD: fix lots of Sphinx warnings/errors.
* `#9255 <https://github.com/numpy/numpy/pull/9255>`__: Revert "DEP: Raise TypeError for subtract(bool_, bool_)."
* `#9261 <https://github.com/numpy/numpy/pull/9261>`__: BUG: don't elide into readonly and updateifcopy temporaries for...
* `#9262 <https://github.com/numpy/numpy/pull/9262>`__: BUG: fix missing keyword rename for common block in numpy.f2py
* `#9263 <https://github.com/numpy/numpy/pull/9263>`__: BUG: handle resize of 0d array
* `#9267 <https://github.com/numpy/numpy/pull/9267>`__: DOC: update f2py front page and some doc build metadata.
* `#9299 <https://github.com/numpy/numpy/pull/9299>`__: BUG: Fix Intel compilation on Unix.
* `#9317 <https://github.com/numpy/numpy/pull/9317>`__: BUG: fix wrong ndim used in empty where check
* `#9319 <https://github.com/numpy/numpy/pull/9319>`__: BUG: Make extensions compilable with MinGW on Py2.7
* `#9339 <https://github.com/numpy/numpy/pull/9339>`__: BUG: Prevent crash if ufunc doc string is null
* `#9340 <https://github.com/numpy/numpy/pull/9340>`__: BUG: umath: un-break ufunc where= when no out= is given
* `#9371 <https://github.com/numpy/numpy/pull/9371>`__: DOC: Add isnat/positive ufunc to documentation
* `#9372 <https://github.com/numpy/numpy/pull/9372>`__: BUG: Fix error in fromstring function from numpy.core.records...
* `#9373 <https://github.com/numpy/numpy/pull/9373>`__: BUG: ')' is printed at the end pointer of the buffer in numpy.f2py.
* `#9374 <https://github.com/numpy/numpy/pull/9374>`__: DOC: Create NumPy 1.13.1 release notes.
* `#9376 <https://github.com/numpy/numpy/pull/9376>`__: BUG: Prevent hang traversing ufunc userloop linked list
* `#9377 <https://github.com/numpy/numpy/pull/9377>`__: DOC: Use x1 and x2 in the heaviside docstring.
* `#9378 <https://github.com/numpy/numpy/pull/9378>`__: DOC: Add $PARAMS to the isnat docstring
* `#9379 <https://github.com/numpy/numpy/pull/9379>`__: DOC: Update the 1.13.1 release notes
* `#9390 <https://github.com/numpy/numpy/pull/9390>`__: BUG: Return the poly1d coefficients array directly
* `#9555 <https://github.com/numpy/numpy/pull/9555>`__: BUG: fix regression in 1.13.x in distutils.mingw32ccompiler.
* `#9556 <https://github.com/numpy/numpy/pull/9556>`__: BUG: Fix true_divide when dtype=np.float64 specified.
* `#9557 <https://github.com/numpy/numpy/pull/9557>`__: DOC: Fix some rst markup in numpy/doc/basics.py.
* `#9558 <https://github.com/numpy/numpy/pull/9558>`__: BLD: remove -xhost flag from IntelFCompiler.
* `#9559 <https://github.com/numpy/numpy/pull/9559>`__: DOC: removes broken docstring example (source code, png, pdf)...
* `#9580 <https://github.com/numpy/numpy/pull/9580>`__: BUG: Add hypot and cabs functions to WIN32 blacklist.
* `#9732 <https://github.com/numpy/numpy/pull/9732>`__: BUG: Make scalar function elision check if temp is writeable.
* `#9736 <https://github.com/numpy/numpy/pull/9736>`__: BUG: various fixes to np.gradient
* `#9742 <https://github.com/numpy/numpy/pull/9742>`__: BUG: Fix np.pad for CVE-2017-12852
* `#9744 <https://github.com/numpy/numpy/pull/9744>`__: BUG: Check for exception in sort functions, add tests
* `#9745 <https://github.com/numpy/numpy/pull/9745>`__: DOC: Add whitespace after "versionadded::" directive so it actually...
* `#9746 <https://github.com/numpy/numpy/pull/9746>`__: BUG: memory leak in np.dot of size 0
* `#9747 <https://github.com/numpy/numpy/pull/9747>`__: BUG: adjust gfortran version search regex
* `#9757 <https://github.com/numpy/numpy/pull/9757>`__: BUG: Cython 0.27 breaks NumPy on Python 3.
* `#9764 <https://github.com/numpy/numpy/pull/9764>`__: BUG: Ensure `_npy_scaled_cexp{,f,l}` is defined when needed.
* `#9765 <https://github.com/numpy/numpy/pull/9765>`__: BUG: PyArray_CountNonzero does not check for exceptions
* `#9766 <https://github.com/numpy/numpy/pull/9766>`__: BUG: Fixes histogram monotonicity check for unsigned bin values
* `#9767 <https://github.com/numpy/numpy/pull/9767>`__: BUG: ensure consistent result dtype of count_nonzero
* `#9771 <https://github.com/numpy/numpy/pull/9771>`__: MAINT,BUG: Fix mtrand for Cython 0.27.
* `#9772 <https://github.com/numpy/numpy/pull/9772>`__: DOC: Create the 1.13.2 release notes.
* `#9794 <https://github.com/numpy/numpy/pull/9794>`__: DOC: Create 1.13.3 release notes.

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Contributors
============
A total of 100 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Alexey Brodkin +
* Allan Haldane
* Andras Deak +
* Andrew Lawson +
* Anna Chiara +
* Antoine Pitrou
* Bernhard M. Wiedemann +
* Bob Eldering +
* Brandon Carter
* CJ Carey
* Charles Harris
* Chris Lamb
* Christoph Boeddeker +
* Christoph Gohlke
* Daniel Hrisca +
* Daniel Smith
* Danny Hermes
* David Freese
* David Hagen
* David Linke +
* David Schaefer +
* Dillon Niederhut +
* Egor Panfilov +
* Emilien Kofman
* Eric Wieser
* Erik Bray +
* Erik Quaeghebeur +
* Garry Polley +
* Gunjan +
* Han Shen +
* Henke Adolfsson +
* Hidehiro NAGAOKA +
* Hemil Desai +
* Hong Xu +
* Iryna Shcherbina +
* Jaime Fernandez
* James Bourbeau +
* Jamie Townsend +
* Jarrod Millman
* Jean Helie +
* Jeroen Demeyer +
* John Goetz +
* John Kirkham
* John Zwinck
* Jonathan Helmus
* Joseph Fox-Rabinovitz
* Joseph Paul Cohen +
* Joshua Leahy +
* Julian Taylor
* Jörg Döpfert +
* Keno Goertz +
* Kevin Sheppard +
* Kexuan Sun +
* Konrad Kapp +
* Kristofor Maynard +
* Licht Takeuchi +
* Loïc Estève
* Lukas Mericle +
* Marten van Kerkwijk
* Matheus Portela +
* Matthew Brett
* Matti Picus
* Michael Lamparski +
* Michael Odintsov +
* Michael Schnaitter +
* Michael Seifert
* Mike Nolta
* Nathaniel J. Smith
* Nelle Varoquaux +
* Nicholas Del Grosso +
* Nico Schlömer +
* Oleg Zabluda +
* Oleksandr Pavlyk
* Pauli Virtanen
* Pim de Haan +
* Ralf Gommers
* Robert T. McGibbon +
* Roland Kaufmann
* Sebastian Berg
* Serhiy Storchaka +
* Shitian Ni +
* Spencer Hill +
* Srinivas Reddy Thatiparthy +
* Stefan Winkler +
* Stephan Hoyer
* Steven Maude +
* SuperBo +
* Thomas Köppe +
* Toon Verstraelen
* Vedant Misra +
* Warren Weckesser
* Wirawan Purwanto +
* Yang Li +
* Ziyan Zhou +
* chaoyu3 +
* orbit-stabilizer +
* solarjoe
* wufangjie +
* xoviat +
* Élie Gouzien +
Pull requests merged
====================
A total of 381 pull requests were merged for this release.
* `#5580 <https://github.com/numpy/numpy/pull/5580>`__: BUG, DEP: Fix masked arrays to properly edit views. ( #5558 )
* `#6053 <https://github.com/numpy/numpy/pull/6053>`__: MAINT: struct assignment "by field position", multi-field indices...
* `#7994 <https://github.com/numpy/numpy/pull/7994>`__: BUG: Allow 'shape': () in __array_interface__ regardless of the...
* `#8187 <https://github.com/numpy/numpy/pull/8187>`__: MAINT: Remove the unused keepdim argument from np.ufunc.accumulate
* `#8278 <https://github.com/numpy/numpy/pull/8278>`__: MAINT: Make the refactor suggested in prepare_index
* `#8557 <https://github.com/numpy/numpy/pull/8557>`__: ENH: add hermitian=False kwarg to np.linalg.matrix_rank
* `#8722 <https://github.com/numpy/numpy/pull/8722>`__: DOC: Clarifying the meaning of small values for `suppress` print...
* `#8827 <https://github.com/numpy/numpy/pull/8827>`__: BUG: Fix pinv for stacked matrices
* `#8920 <https://github.com/numpy/numpy/pull/8920>`__: ENH: use caching memory allocator in more places
* `#8934 <https://github.com/numpy/numpy/pull/8934>`__: MAINT: Use np.concatenate instead of np.vstack
* `#8977 <https://github.com/numpy/numpy/pull/8977>`__: BUG: Fix all kinds of problems when itemsize == 0
* `#8981 <https://github.com/numpy/numpy/pull/8981>`__: ENH: implement voidtype_repr and voidtype_str
* `#8983 <https://github.com/numpy/numpy/pull/8983>`__: ENH: fix str/repr for 0d-arrays and int* scalars
* `#9020 <https://github.com/numpy/numpy/pull/9020>`__: BUG: don't silence warnings in ufunc.reduce
* `#9025 <https://github.com/numpy/numpy/pull/9025>`__: ENH: np.save() to align data at 64 bytes
* `#9056 <https://github.com/numpy/numpy/pull/9056>`__: DOC: update structured array docs to reflect #6053
* `#9065 <https://github.com/numpy/numpy/pull/9065>`__: DEP: 0 should be passed to bincount, not None
* `#9083 <https://github.com/numpy/numpy/pull/9083>`__: MAINT: Improve error message from sorting with duplicate key
* `#9089 <https://github.com/numpy/numpy/pull/9089>`__: MAINT: refine error message for __array_ufunc__ not implemented
* `#9090 <https://github.com/numpy/numpy/pull/9090>`__: MAINT: Update master branch for 1.14.0 development.
* `#9092 <https://github.com/numpy/numpy/pull/9092>`__: BUG remove memory leak in array ufunc override.
* `#9096 <https://github.com/numpy/numpy/pull/9096>`__: ENH: Allow inplace also as keyword parameter for ndarray.byteswap
* `#9099 <https://github.com/numpy/numpy/pull/9099>`__: TST: fix test_basic failure on Windows
* `#9106 <https://github.com/numpy/numpy/pull/9106>`__: BUG: Array ufunc reduce out tuple
* `#9110 <https://github.com/numpy/numpy/pull/9110>`__: BUG: Do not elide complex abs()
* `#9112 <https://github.com/numpy/numpy/pull/9112>`__: BUG: ndarray.__pow__ does not check result of fast_scalar_power
* `#9113 <https://github.com/numpy/numpy/pull/9113>`__: BUG: delay calls of array repr in getlimits
* `#9115 <https://github.com/numpy/numpy/pull/9115>`__: BUG: Compilation crashes in MSVC when LIB or INCLUDE is not set
* `#9116 <https://github.com/numpy/numpy/pull/9116>`__: DOC: link to stack from column_stack
* `#9118 <https://github.com/numpy/numpy/pull/9118>`__: BUG: Fix reference count error of types when init multiarraymodule
* `#9119 <https://github.com/numpy/numpy/pull/9119>`__: BUG: Fix error handling on PyCapsule when initializing multiarraymodule
* `#9122 <https://github.com/numpy/numpy/pull/9122>`__: DOC: update 1.13 release note for MaskedArray, masked constants...
* `#9132 <https://github.com/numpy/numpy/pull/9132>`__: DEP: Deprecate incorrect behavior of expand_dims.
* `#9138 <https://github.com/numpy/numpy/pull/9138>`__: MAINT: Update .mailmap
* `#9139 <https://github.com/numpy/numpy/pull/9139>`__: ENH: remove unneeded spaces in float/bool reprs, fixes 0d str
* `#9141 <https://github.com/numpy/numpy/pull/9141>`__: DOC: Update ufunc documentation
* `#9142 <https://github.com/numpy/numpy/pull/9142>`__: BUG: set default type for empty index array to `numpy.intp`
* `#9149 <https://github.com/numpy/numpy/pull/9149>`__: DOC: Fix incorrect function signature in UFunc documentation.
* `#9151 <https://github.com/numpy/numpy/pull/9151>`__: DOC: better link display text for Developer Zone.
* `#9152 <https://github.com/numpy/numpy/pull/9152>`__: DOC: Fix some very minor spelling/grammar mistakes in docs
* `#9155 <https://github.com/numpy/numpy/pull/9155>`__: MAINT: Take out code that will never be executed
* `#9157 <https://github.com/numpy/numpy/pull/9157>`__: DOC: Fixed broken link to scipy developer zone
* `#9164 <https://github.com/numpy/numpy/pull/9164>`__: BUG: have as_strided() keep custom dtypes
* `#9167 <https://github.com/numpy/numpy/pull/9167>`__: BUG: ensure structured ndarray.__eq__,__ne__ defer when appropriate.
* `#9168 <https://github.com/numpy/numpy/pull/9168>`__: MAINT: Simplify if statement
* `#9174 <https://github.com/numpy/numpy/pull/9174>`__: BUG: allow pickling generic datetime
* `#9176 <https://github.com/numpy/numpy/pull/9176>`__: DOC: Update protocols in git development document.
* `#9181 <https://github.com/numpy/numpy/pull/9181>`__: COMPAT: PyPy calls clongdouble_int which raises a warning
* `#9195 <https://github.com/numpy/numpy/pull/9195>`__: BUG: pull request 9087 modifies a tuple after use
* `#9200 <https://github.com/numpy/numpy/pull/9200>`__: DOC: Update bincount docs to reflect gh-8348
* `#9201 <https://github.com/numpy/numpy/pull/9201>`__: BUG: Fix unicode(unicode_array_0d) on python 2.7
* `#9202 <https://github.com/numpy/numpy/pull/9202>`__: MAINT: Move ndarray.__str__ and ndarray.__repr__ to their own...
* `#9205 <https://github.com/numpy/numpy/pull/9205>`__: DOC: Remove all references to bigndarray in documentation.
* `#9209 <https://github.com/numpy/numpy/pull/9209>`__: ENH: Add an out argument to concatenate
* `#9212 <https://github.com/numpy/numpy/pull/9212>`__: MAINT: Combine similar branches
* `#9214 <https://github.com/numpy/numpy/pull/9214>`__: MAINT: Don't internally use the one-argument where
* `#9215 <https://github.com/numpy/numpy/pull/9215>`__: BUG: Avoid bare except clauses
* `#9217 <https://github.com/numpy/numpy/pull/9217>`__: BUG: handle resize of 0d array
* `#9218 <https://github.com/numpy/numpy/pull/9218>`__: BUG: Only propagate TypeError from where we throw it
* `#9219 <https://github.com/numpy/numpy/pull/9219>`__: DOC: Link to ufunc.outer from np.outer
* `#9220 <https://github.com/numpy/numpy/pull/9220>`__: MAINT: Factor out code duplicated by nanmedian and nanpercentile
* `#9226 <https://github.com/numpy/numpy/pull/9226>`__: DOC, ENH: Add 1.13.0-changelog.rst
* `#9238 <https://github.com/numpy/numpy/pull/9238>`__: DOC: BLD: fix lots of Sphinx warnings/errors.
* `#9241 <https://github.com/numpy/numpy/pull/9241>`__: MAINT: Fixup release notes, changelogs after #9238 merge.
* `#9242 <https://github.com/numpy/numpy/pull/9242>`__: BUG: Make 0-length dim handling of tensordot consistent with...
* `#9246 <https://github.com/numpy/numpy/pull/9246>`__: ENH: Release the GIL in einsum() special-cased loops
* `#9247 <https://github.com/numpy/numpy/pull/9247>`__: BUG: fix missing keyword rename for common block in numpy.f2py
* `#9253 <https://github.com/numpy/numpy/pull/9253>`__: DOC: Add isnat/positive ufunc to documentation.
* `#9259 <https://github.com/numpy/numpy/pull/9259>`__: MAINT: Use XOR for bool arrays in `np.diff`
* `#9260 <https://github.com/numpy/numpy/pull/9260>`__: BUG: don't elide into readonly and updateifcopy temporaries
* `#9264 <https://github.com/numpy/numpy/pull/9264>`__: DOC: some doc build maintenance and f2py doc updates
* `#9266 <https://github.com/numpy/numpy/pull/9266>`__: BUG: Fix unused variable in ufunc_object.c,
* `#9268 <https://github.com/numpy/numpy/pull/9268>`__: ENH: testing: load available nose plugins that are external to...
* `#9271 <https://github.com/numpy/numpy/pull/9271>`__: BUG: fix issue when using ``python setup.py somecommand --force``.
* `#9280 <https://github.com/numpy/numpy/pull/9280>`__: BUG: Make extensions compilable with MinGW on Py2.7
* `#9281 <https://github.com/numpy/numpy/pull/9281>`__: DOC: add @ operator in array vs. matrix comparison doc
* `#9285 <https://github.com/numpy/numpy/pull/9285>`__: BUG: Fix Intel compilation on Unix.
* `#9292 <https://github.com/numpy/numpy/pull/9292>`__: MAINT: Fix lgtm alerts
* `#9294 <https://github.com/numpy/numpy/pull/9294>`__: BUG: Fixes histogram monotonicity check for unsigned bin values
* `#9300 <https://github.com/numpy/numpy/pull/9300>`__: BUG: PyArray_CountNonzero does not check for exceptions
* `#9302 <https://github.com/numpy/numpy/pull/9302>`__: BUG: Fix fillvalue
* `#9306 <https://github.com/numpy/numpy/pull/9306>`__: BUG: f2py: Convert some error messages printed to stderr to exceptions.
* `#9310 <https://github.com/numpy/numpy/pull/9310>`__: BUG: fix wrong ndim used in empty where check
* `#9316 <https://github.com/numpy/numpy/pull/9316>`__: BUG: `runtest -t` should recognize development mode
* `#9320 <https://github.com/numpy/numpy/pull/9320>`__: DOC: Use x1 and x2 in the heaviside docstring.
* `#9322 <https://github.com/numpy/numpy/pull/9322>`__: BUG: np.ma.astype fails on structured types
* `#9323 <https://github.com/numpy/numpy/pull/9323>`__: DOC: Add $PARAMS to the isnat docstring
* `#9324 <https://github.com/numpy/numpy/pull/9324>`__: DOC: Fix missing asterisks in git development_setup doc page
* `#9325 <https://github.com/numpy/numpy/pull/9325>`__: DOC: add a NumFOCUS badge to README.md
* `#9332 <https://github.com/numpy/numpy/pull/9332>`__: ENH: fix 0d array printing using `str` or `formatter`.
* `#9335 <https://github.com/numpy/numpy/pull/9335>`__: BUG: umath: un-break ufunc where= when no out= is given
* `#9336 <https://github.com/numpy/numpy/pull/9336>`__: BUG: Fix various problems with the np.ma.masked constant
* `#9337 <https://github.com/numpy/numpy/pull/9337>`__: BUG: Prevent crash if ufunc doc string is null
* `#9341 <https://github.com/numpy/numpy/pull/9341>`__: BUG: np.resize discards empty shapes
* `#9343 <https://github.com/numpy/numpy/pull/9343>`__: BUG: recfunctions fail in a bunch of ways due to using .descr
* `#9344 <https://github.com/numpy/numpy/pull/9344>`__: DOC: fixes issue #9326, by removing the statement.
* `#9346 <https://github.com/numpy/numpy/pull/9346>`__: BUG: void masked fillvalue cannot be cast to void in python 3
* `#9354 <https://github.com/numpy/numpy/pull/9354>`__: BUG: Prevent hang traversing ufunc userloop linked list
* `#9357 <https://github.com/numpy/numpy/pull/9357>`__: DOC: Add examples for complex dtypes
* `#9361 <https://github.com/numpy/numpy/pull/9361>`__: DOC: isscalar add example for str
* `#9362 <https://github.com/numpy/numpy/pull/9362>`__: ENH: Rearrange testing module to isolate nose dependency.
* `#9364 <https://github.com/numpy/numpy/pull/9364>`__: BUG: ')' is printed at the end pointer of the buffer in numpy.f2py.
* `#9369 <https://github.com/numpy/numpy/pull/9369>`__: BUG: fix error in fromstring function from numpy.core.records
* `#9375 <https://github.com/numpy/numpy/pull/9375>`__: DOC: Document the internal workings of PY_ARRAY_UNIQUE_SYMBOL
* `#9380 <https://github.com/numpy/numpy/pull/9380>`__: DOC: Forward port 1.13.1 notes and changelog.
* `#9381 <https://github.com/numpy/numpy/pull/9381>`__: TST: test doc string of COMMON block arrays for numpy.f2py.
* `#9387 <https://github.com/numpy/numpy/pull/9387>`__: MAINT: Simplify code using PyArray_ISBYTESWAPPED macro.
* `#9388 <https://github.com/numpy/numpy/pull/9388>`__: MAINT: Use PyArray_ISBYTESWAPPED instead of !PyArray_ISNOTSWAPPED.
* `#9389 <https://github.com/numpy/numpy/pull/9389>`__: DOC: Fix reference, PyArray_DescrNew -> PyArray_NewFromDescr
* `#9392 <https://github.com/numpy/numpy/pull/9392>`__: DOC: UPDATEIFCOPY raises an error if not an array.
* `#9399 <https://github.com/numpy/numpy/pull/9399>`__: DOC: document how to free memory from PyArray_IntpConverter.
* `#9400 <https://github.com/numpy/numpy/pull/9400>`__: MAINT: Further unify handling of unnamed ufuncs
* `#9403 <https://github.com/numpy/numpy/pull/9403>`__: MAINT: Replace tab escapes with four spaces
* `#9407 <https://github.com/numpy/numpy/pull/9407>`__: DOC: add ``suppress_warnings`` to the testing routine listing.
* `#9408 <https://github.com/numpy/numpy/pull/9408>`__: BUG: various fixes to np.gradient
* `#9411 <https://github.com/numpy/numpy/pull/9411>`__: MAINT/BUG: improve gradient dtype handling
* `#9412 <https://github.com/numpy/numpy/pull/9412>`__: BUG: Check for exception in sort functions
* `#9422 <https://github.com/numpy/numpy/pull/9422>`__: DOC: correct formatting of basic.types.html
* `#9423 <https://github.com/numpy/numpy/pull/9423>`__: MAINT: change http to https for numfocus.org link in README
* `#9425 <https://github.com/numpy/numpy/pull/9425>`__: ENH: Einsum calls BLAS if it advantageous to do so
* `#9426 <https://github.com/numpy/numpy/pull/9426>`__: DOC: Add a link to einsum_path
* `#9431 <https://github.com/numpy/numpy/pull/9431>`__: ENH: distutils: make msvc + mingw-gfortran work
* `#9432 <https://github.com/numpy/numpy/pull/9432>`__: BUG: Fix loss of masks in masked 0d methods
* `#9433 <https://github.com/numpy/numpy/pull/9433>`__: BUG: make np.transpose return a view of the mask
* `#9434 <https://github.com/numpy/numpy/pull/9434>`__: MAINT: Remove unittest dependencies
* `#9437 <https://github.com/numpy/numpy/pull/9437>`__: DOC: Update 1.14.0 release notes.
* `#9446 <https://github.com/numpy/numpy/pull/9446>`__: BUG: Inlined functions must be defined somewhere.
* `#9447 <https://github.com/numpy/numpy/pull/9447>`__: API: Make ``a.flat.__array__`` return a copy when ``a`` non-contiguous.
* `#9452 <https://github.com/numpy/numpy/pull/9452>`__: MAINT: Use new-style classes on 2.7
* `#9454 <https://github.com/numpy/numpy/pull/9454>`__: MAINT: Remove branch in __array__ where if and else were the...
* `#9457 <https://github.com/numpy/numpy/pull/9457>`__: MAINT: Add a common subclass to all the masked ufunc wrappers
* `#9458 <https://github.com/numpy/numpy/pull/9458>`__: MAINT: Improve performance of np.copyto(where=scalar)
* `#9469 <https://github.com/numpy/numpy/pull/9469>`__: BUG: Fix true_divide when dtype=np.float64 specified.
* `#9470 <https://github.com/numpy/numpy/pull/9470>`__: MAINT: Make `setxor1d` a bit clearer and speed it up
* `#9471 <https://github.com/numpy/numpy/pull/9471>`__: BLD: remove -xhost flag from IntelFCompiler.
* `#9475 <https://github.com/numpy/numpy/pull/9475>`__: DEP: deprecate rollaxis
* `#9482 <https://github.com/numpy/numpy/pull/9482>`__: MAINT: Make diff iterative instead of recursive
* `#9487 <https://github.com/numpy/numpy/pull/9487>`__: DEP: Letting fromstring pretend to be frombuffer is a bad idea
* `#9490 <https://github.com/numpy/numpy/pull/9490>`__: DOC: Replace xrange by range in quickstart docs
* `#9491 <https://github.com/numpy/numpy/pull/9491>`__: TST: Add filter for new Py3K warning in python 2
* `#9492 <https://github.com/numpy/numpy/pull/9492>`__: ENH: Add np.polynomial.chebyshev.chebinterpolate function.
* `#9498 <https://github.com/numpy/numpy/pull/9498>`__: DOC: fix versionadded in docstring for moveaxis
* `#9499 <https://github.com/numpy/numpy/pull/9499>`__: MAINT/BUG: Improve error messages for dtype reassigment, fix...
* `#9503 <https://github.com/numpy/numpy/pull/9503>`__: MAINT: Move variables into deepest relevant scope, for clarity
* `#9505 <https://github.com/numpy/numpy/pull/9505>`__: BUG: issubdtype is inconsistent on types and dtypes
* `#9517 <https://github.com/numpy/numpy/pull/9517>`__: MAINT/DOC: Use builtin when np.{x} is builtins.{x}.
* `#9519 <https://github.com/numpy/numpy/pull/9519>`__: MAINT: Remove `level=` keyword from test arguments.
* `#9520 <https://github.com/numpy/numpy/pull/9520>`__: MAINT: types.TypeType does not ever need to be used
* `#9521 <https://github.com/numpy/numpy/pull/9521>`__: BUG: Make issubclass(np.number, numbers.Number) return true
* `#9522 <https://github.com/numpy/numpy/pull/9522>`__: BUG: Fix problems with obj2sctype
* `#9524 <https://github.com/numpy/numpy/pull/9524>`__: TST, MAINT: Add `__init__.py` files to tests directories.
* `#9527 <https://github.com/numpy/numpy/pull/9527>`__: BUG: Fix scalar methods to receive keyword arguments
* `#9529 <https://github.com/numpy/numpy/pull/9529>`__: BUG: The NAT deprecation warning should not be given for every...
* `#9536 <https://github.com/numpy/numpy/pull/9536>`__: ENH: Show domain and window as kwargs in repr
* `#9540 <https://github.com/numpy/numpy/pull/9540>`__: BUG: MaskedArray _optinfo dictionary is not updated when calling...
* `#9543 <https://github.com/numpy/numpy/pull/9543>`__: DOC: Adding backslash between double-backtick and s.
* `#9544 <https://github.com/numpy/numpy/pull/9544>`__: MAINT: Use the error_converting macro where possible
* `#9545 <https://github.com/numpy/numpy/pull/9545>`__: DEP: Deprecate the event argument to datetime types, which is...
* `#9550 <https://github.com/numpy/numpy/pull/9550>`__: DOC: removes broken docstring example (source code, png, pdf)...
* `#9552 <https://github.com/numpy/numpy/pull/9552>`__: DOC, BUG: Fix Python 3.6 invalid escape sequence.
* `#9554 <https://github.com/numpy/numpy/pull/9554>`__: BUG: fix regression in 1.13.x in distutils.mingw32ccompiler.
* `#9564 <https://github.com/numpy/numpy/pull/9564>`__: BUG: fix distutils/cpuinfo.py:getoutput()
* `#9574 <https://github.com/numpy/numpy/pull/9574>`__: BUG: deal with broken hypot() for MSVC on win32
* `#9575 <https://github.com/numpy/numpy/pull/9575>`__: BUG: deal with broken cabs*() for MSVC on win32
* `#9577 <https://github.com/numpy/numpy/pull/9577>`__: BUG: Missing dirichlet input validation
* `#9581 <https://github.com/numpy/numpy/pull/9581>`__: DOC: Fix link in numpy.ndarray.copy method (missing backticks)
* `#9582 <https://github.com/numpy/numpy/pull/9582>`__: ENH: Warn to change lstsq default for rcond
* `#9586 <https://github.com/numpy/numpy/pull/9586>`__: DOC: update example in np.nonzero docstring
* `#9588 <https://github.com/numpy/numpy/pull/9588>`__: MAINT: Remove direct access to flatiter attributes
* `#9590 <https://github.com/numpy/numpy/pull/9590>`__: ENH: Remove unnecessary restriction in noncen-f
* `#9591 <https://github.com/numpy/numpy/pull/9591>`__: MAINT: Remove unnecessary imports
* `#9599 <https://github.com/numpy/numpy/pull/9599>`__: BUG: fix infinite loop when creating np.pad on an empty array
* `#9601 <https://github.com/numpy/numpy/pull/9601>`__: DOC: rot90 wrongly positioned versionadded directive.
* `#9604 <https://github.com/numpy/numpy/pull/9604>`__: MAINT: Refactor the code used to compute sha256, md5 hashes
* `#9606 <https://github.com/numpy/numpy/pull/9606>`__: MAINT: Remove global statement in linalg.py
* `#9609 <https://github.com/numpy/numpy/pull/9609>`__: BUG: Add `__ne__` method to dummy_ctype class.
* `#9610 <https://github.com/numpy/numpy/pull/9610>`__: BUG: core: fix wrong method flags for scalartypes.c.src:gentype_copy
* `#9611 <https://github.com/numpy/numpy/pull/9611>`__: MAINT: remove try..except clause.
* `#9613 <https://github.com/numpy/numpy/pull/9613>`__: DOC: Update release notes for noncentral_f changes.
* `#9614 <https://github.com/numpy/numpy/pull/9614>`__: MAINT: Fix a comment regarding the formula for arange length
* `#9618 <https://github.com/numpy/numpy/pull/9618>`__: DOC: Fix type definitions in mtrand
* `#9619 <https://github.com/numpy/numpy/pull/9619>`__: ENH: Allow Fortran arrays of dimension 0
* `#9624 <https://github.com/numpy/numpy/pull/9624>`__: BUG: memory leak in np.dot of size 0
* `#9626 <https://github.com/numpy/numpy/pull/9626>`__: BUG: Fix broken runtests '-t' option.
* `#9629 <https://github.com/numpy/numpy/pull/9629>`__: BUG: test, fix issue #9620 __radd__ in char scalars
* `#9630 <https://github.com/numpy/numpy/pull/9630>`__: DOC: Updates order of parameters in save docstring
* `#9636 <https://github.com/numpy/numpy/pull/9636>`__: MAINT: Fix compiler warnings and update travis jobs
* `#9638 <https://github.com/numpy/numpy/pull/9638>`__: BUG: ensure consistent result dtype of count_nonzero
* `#9639 <https://github.com/numpy/numpy/pull/9639>`__: MAINT: Refactor updateifcopy
* `#9640 <https://github.com/numpy/numpy/pull/9640>`__: BUG: fix padding an empty array in reflect mode.
* `#9643 <https://github.com/numpy/numpy/pull/9643>`__: DOC: add new steering council members.
* `#9645 <https://github.com/numpy/numpy/pull/9645>`__: ENH: enable OpenBLAS on windows.
* `#9648 <https://github.com/numpy/numpy/pull/9648>`__: DOC: Correct the signature in pad doc for callable mode.
* `#9649 <https://github.com/numpy/numpy/pull/9649>`__: DOC: Fixed doc example of apply along axis with 3D return
* `#9652 <https://github.com/numpy/numpy/pull/9652>`__: BUG: Make system_info output reproducible
* `#9658 <https://github.com/numpy/numpy/pull/9658>`__: BUG: Fix usage of keyword "from" as argument name for "can_cast".
* `#9667 <https://github.com/numpy/numpy/pull/9667>`__: MAINT: Simplify block implementation
* `#9668 <https://github.com/numpy/numpy/pull/9668>`__: DOC: clarify wording in tutorial
* `#9672 <https://github.com/numpy/numpy/pull/9672>`__: BUG: dot/matmul 'out' arg should accept any ndarray subclass
* `#9681 <https://github.com/numpy/numpy/pull/9681>`__: MAINT: Add block benchmarks
* `#9682 <https://github.com/numpy/numpy/pull/9682>`__: DOC: Add whitespace after "versionadded::" directive so it actually...
* `#9683 <https://github.com/numpy/numpy/pull/9683>`__: DOC: Add polyutils subpackage to reference documentation
* `#9685 <https://github.com/numpy/numpy/pull/9685>`__: BUG: Fixes #7395, operator.index now fails on numpy.bool_
* `#9688 <https://github.com/numpy/numpy/pull/9688>`__: MAINT: rework recursive guard to keep array2string signature
* `#9691 <https://github.com/numpy/numpy/pull/9691>`__: PEP 3141 numbers should be considered scalars
* `#9692 <https://github.com/numpy/numpy/pull/9692>`__: ENH: Add support of ARC architecture
* `#9695 <https://github.com/numpy/numpy/pull/9695>`__: DOC: `start` is not needed even when `step` is given.
* `#9700 <https://github.com/numpy/numpy/pull/9700>`__: DOC: Add mandatory memo argument to __deepcopy__ method documentation
* `#9701 <https://github.com/numpy/numpy/pull/9701>`__: DOC: Add keepdims argument for ndarray.max documentation
* `#9702 <https://github.com/numpy/numpy/pull/9702>`__: DOC: Warn about the difference between np.remainder and math.remainder
* `#9703 <https://github.com/numpy/numpy/pull/9703>`__: DOC: Fix mistaken word in nanprod docstring
* `#9707 <https://github.com/numpy/numpy/pull/9707>`__: MAINT: When linspace's step is a NumPy scalar, do multiplication in-place
* `#9709 <https://github.com/numpy/numpy/pull/9709>`__: DOC: allclose doesn't require matching shapes
* `#9711 <https://github.com/numpy/numpy/pull/9711>`__: BUG: Make scalar function elision check if writeable.
* `#9715 <https://github.com/numpy/numpy/pull/9715>`__: MAINT: Fix typo "Porland" -> "Portland" in `building` doc.
* `#9718 <https://github.com/numpy/numpy/pull/9718>`__: DEP: Deprecate truth testing on empty arrays
* `#9720 <https://github.com/numpy/numpy/pull/9720>`__: MAINT: Remove unnecessary special-casing of scalars in isclose
* `#9724 <https://github.com/numpy/numpy/pull/9724>`__: BUG: adjust gfortran version search regex
* `#9725 <https://github.com/numpy/numpy/pull/9725>`__: MAINT: cleanup circular import b/w arrayprint.py,numeric.py
* `#9726 <https://github.com/numpy/numpy/pull/9726>`__: ENH: Better error message for savetxt when X.ndim > 2 or X.ndim...
* `#9737 <https://github.com/numpy/numpy/pull/9737>`__: MAINT: Use zip, not enumerate
* `#9740 <https://github.com/numpy/numpy/pull/9740>`__: BUG: Ensure `_npy_scaled_cexp{,f,l}` is defined when needed.
* `#9741 <https://github.com/numpy/numpy/pull/9741>`__: BUG: core: use npy_cabs for abs() for np.complex* scalar types
* `#9743 <https://github.com/numpy/numpy/pull/9743>`__: MAINT: Use PyArray_CHKFLAGS in more places.
* `#9749 <https://github.com/numpy/numpy/pull/9749>`__: BUG: Fix loss of precision for large values in long double divmod
* `#9752 <https://github.com/numpy/numpy/pull/9752>`__: BUG: Errors thrown by 0d arrays in setitem are silenced and replaced
* `#9753 <https://github.com/numpy/numpy/pull/9753>`__: DOC: Fix ndarray.__setstate__ documentation, it only takes one...
* `#9755 <https://github.com/numpy/numpy/pull/9755>`__: BUG: Cython 0.27 breaks NumPy on Python 3.
* `#9756 <https://github.com/numpy/numpy/pull/9756>`__: BUG/TST: Check if precision is lost in longcomplex
* `#9762 <https://github.com/numpy/numpy/pull/9762>`__: MAINT: Use the PyArray_(GET|SET)_ITEM functions where possible
* `#9768 <https://github.com/numpy/numpy/pull/9768>`__: MAINT: Cleanup `ma.array.__str__`
* `#9770 <https://github.com/numpy/numpy/pull/9770>`__: MAINT,BUG: Fix mtrand for Cython 0.27.
* `#9773 <https://github.com/numpy/numpy/pull/9773>`__: BUG: Fixes optimal einsum path for multi-term intermediates
* `#9778 <https://github.com/numpy/numpy/pull/9778>`__: BUG: can_cast(127, np.int8) is False
* `#9779 <https://github.com/numpy/numpy/pull/9779>`__: BUG: np.ma.trace gives the wrong result on ND arrays
* `#9780 <https://github.com/numpy/numpy/pull/9780>`__: MAINT: Make f2py generated file not contain the (local) date.
* `#9782 <https://github.com/numpy/numpy/pull/9782>`__: DOC: Update after NumPy 1.13.2 release.
* `#9784 <https://github.com/numpy/numpy/pull/9784>`__: BUG: remove voidtype-repr recursion in scalartypes.c/arrayprint.py
* `#9785 <https://github.com/numpy/numpy/pull/9785>`__: BUG: Fix size-checking in masked_where, and structured shrink_mask
* `#9792 <https://github.com/numpy/numpy/pull/9792>`__: ENH: Various improvements to Maskedarray repr
* `#9796 <https://github.com/numpy/numpy/pull/9796>`__: TST: linalg: add basic smoketest for cholesky
* `#9800 <https://github.com/numpy/numpy/pull/9800>`__: DOC: Clean up README
* `#9803 <https://github.com/numpy/numpy/pull/9803>`__: DOC: add missing underscore in set_printoptions
* `#9805 <https://github.com/numpy/numpy/pull/9805>`__: CI: set correct test mode for appveyor
* `#9806 <https://github.com/numpy/numpy/pull/9806>`__: MAINT: Add appveyor badge to README
* `#9807 <https://github.com/numpy/numpy/pull/9807>`__: MAINT: Make appveyor config a dot-file
* `#9810 <https://github.com/numpy/numpy/pull/9810>`__: DOC: Improve ndarray.shape documentation.
* `#9812 <https://github.com/numpy/numpy/pull/9812>`__: DOC: update scipy.integrate recommendation
* `#9814 <https://github.com/numpy/numpy/pull/9814>`__: BUG: Fix datetime->string conversion
* `#9815 <https://github.com/numpy/numpy/pull/9815>`__: BUG: fix stray comma in _array2string
* `#9817 <https://github.com/numpy/numpy/pull/9817>`__: BUG: Added exception for casting numpy.ma.masked to long
* `#9822 <https://github.com/numpy/numpy/pull/9822>`__: BUG: Allow subclasses of MaskedConstant to behave as unique singletons
* `#9824 <https://github.com/numpy/numpy/pull/9824>`__: BUG: Fixes for np.random.zipf
* `#9826 <https://github.com/numpy/numpy/pull/9826>`__: DOC: Add unravel_index examples to np.arg(min|max|sort)
* `#9828 <https://github.com/numpy/numpy/pull/9828>`__: DOC: Improve documentation of axis parameter in numpy.unpackbits()
* `#9835 <https://github.com/numpy/numpy/pull/9835>`__: BENCH: Added missing ufunc benchmarks
* `#9840 <https://github.com/numpy/numpy/pull/9840>`__: DOC: ndarray.__copy__ takes no arguments
* `#9842 <https://github.com/numpy/numpy/pull/9842>`__: BUG: Prevent invalid array shapes in seed
* `#9845 <https://github.com/numpy/numpy/pull/9845>`__: DOC: Refine SVD documentation
* `#9849 <https://github.com/numpy/numpy/pull/9849>`__: MAINT: Fix all special-casing of dtypes in `count_nonzero`
* `#9854 <https://github.com/numpy/numpy/pull/9854>`__: BLD: distutils: auto-find vcpkg include and library directories
* `#9856 <https://github.com/numpy/numpy/pull/9856>`__: BUG: Make bool(void_scalar) and void_scalar.astype(bool) consistent
* `#9858 <https://github.com/numpy/numpy/pull/9858>`__: DOC: Some minor fixes regarding import_array
* `#9862 <https://github.com/numpy/numpy/pull/9862>`__: BUG: Restore the environment variables when import multiarray...
* `#9863 <https://github.com/numpy/numpy/pull/9863>`__: ENH: Save to ZIP files without using temporary files.
* `#9865 <https://github.com/numpy/numpy/pull/9865>`__: DOC: Replace PyFITS reference with Astropy and PyTables with...
* `#9866 <https://github.com/numpy/numpy/pull/9866>`__: BUG: Fix runtests --benchmark-compare in python 3
* `#9868 <https://github.com/numpy/numpy/pull/9868>`__: DOC: Update arraypad to use np.pad in examples
* `#9869 <https://github.com/numpy/numpy/pull/9869>`__: DOC: Make qr options render correctly as list.
* `#9881 <https://github.com/numpy/numpy/pull/9881>`__: BUG: count_nonzero treats empty axis tuples strangely
* `#9883 <https://github.com/numpy/numpy/pull/9883>`__: ENH: Implement ndarray.__format__ for 0d arrays
* `#9884 <https://github.com/numpy/numpy/pull/9884>`__: BUG: Allow `unravel_index(0, ())` to return ()
* `#9887 <https://github.com/numpy/numpy/pull/9887>`__: BUG: add.reduce gives wrong results for arrays with funny strides
* `#9888 <https://github.com/numpy/numpy/pull/9888>`__: MAINT: Remove workarounds for gh-9527
* `#9889 <https://github.com/numpy/numpy/pull/9889>`__: MAINT: Tidy np.histogram, and improve error messages
* `#9893 <https://github.com/numpy/numpy/pull/9893>`__: ENH: Added compatibility for the NAG Fortran compiler, nagfor
* `#9896 <https://github.com/numpy/numpy/pull/9896>`__: DOC: Unindent enumeration in savetxt docstring
* `#9899 <https://github.com/numpy/numpy/pull/9899>`__: Remove unused isscalar imports, and incorrect documentation using...
* `#9900 <https://github.com/numpy/numpy/pull/9900>`__: MAINT/BUG: Remove special-casing for 0d arrays, now that indexing...
* `#9904 <https://github.com/numpy/numpy/pull/9904>`__: MAINT: Make warnings for nanmin and nanmax consistent
* `#9911 <https://github.com/numpy/numpy/pull/9911>`__: CI: travis: switch to container
* `#9912 <https://github.com/numpy/numpy/pull/9912>`__: BENCH: histogramming benchmarks
* `#9913 <https://github.com/numpy/numpy/pull/9913>`__: MAINT: Tidy up Maskedarray repr
* `#9916 <https://github.com/numpy/numpy/pull/9916>`__: DOC: Clarify behavior of genfromtxt names field
* `#9920 <https://github.com/numpy/numpy/pull/9920>`__: DOC: dot: Add explanation in case `b` has only 1 dimension.
* `#9925 <https://github.com/numpy/numpy/pull/9925>`__: DOC: ndarray.reshape allows shape as int arguments or tuple
* `#9930 <https://github.com/numpy/numpy/pull/9930>`__: MAINT: Add parameter checks to polynomial integration functions.
* `#9936 <https://github.com/numpy/numpy/pull/9936>`__: DOC: Clarify docstring for numpy.array_split
* `#9941 <https://github.com/numpy/numpy/pull/9941>`__: ENH: Use Dragon4 algorithm to print floating values
* `#9942 <https://github.com/numpy/numpy/pull/9942>`__: ENH: Add PGI flang compiler support for Windows
* `#9944 <https://github.com/numpy/numpy/pull/9944>`__: MAINT/BUG: Don't squash useful error messages in favor of generic...
* `#9945 <https://github.com/numpy/numpy/pull/9945>`__: DOC: fix operation plural in along axis glossary
* `#9946 <https://github.com/numpy/numpy/pull/9946>`__: DOC: describe the expansion of take and apply_along_axis in detail
* `#9947 <https://github.com/numpy/numpy/pull/9947>`__: MAINT/TST: Tidy dtype indexing
* `#9950 <https://github.com/numpy/numpy/pull/9950>`__: BUG: Passing an incorrect type to dtype.__getitem__ should raise...
* `#9952 <https://github.com/numpy/numpy/pull/9952>`__: ENH: add Decimal support to numpy.lib.financial
* `#9953 <https://github.com/numpy/numpy/pull/9953>`__: MAINT: Add a PyDataType_ISUNSIZED macro
* `#9957 <https://github.com/numpy/numpy/pull/9957>`__: DOC: update asv url
* `#9961 <https://github.com/numpy/numpy/pull/9961>`__: BUG: Allow float64('1e10000') to overflow
* `#9962 <https://github.com/numpy/numpy/pull/9962>`__: MAINT: Rename formatters to match scalar type names
* `#9965 <https://github.com/numpy/numpy/pull/9965>`__: BLD: Disable npymath whole program opt (LTCG) on win32
* `#9966 <https://github.com/numpy/numpy/pull/9966>`__: BUG: str(np.float) should print with the same number of digits...
* `#9967 <https://github.com/numpy/numpy/pull/9967>`__: MAINT: Separate correct `longdouble.__float__` from incorrect...
* `#9971 <https://github.com/numpy/numpy/pull/9971>`__: BUG: Fix casting from longdouble to long
* `#9973 <https://github.com/numpy/numpy/pull/9973>`__: TST: Fix error in test on PyPy, add comment explaining known...
* `#9976 <https://github.com/numpy/numpy/pull/9976>`__: BUG: Ensure lstsq can handle RHS with all sizes.
* `#9977 <https://github.com/numpy/numpy/pull/9977>`__: MAINT: distutils: trivial cleanups
* `#9978 <https://github.com/numpy/numpy/pull/9978>`__: BUG: cast to str_ should not convert to pure-python intermediate
* `#9983 <https://github.com/numpy/numpy/pull/9983>`__: ENH: let f2py discover location of libgfortran
* `#9985 <https://github.com/numpy/numpy/pull/9985>`__: ENH: skip NPY_ALLOW_C_API for UFUNC_ERR_IGNORE
* `#9986 <https://github.com/numpy/numpy/pull/9986>`__: MAINT: Remove similar branches from linalg.lstsq
* `#9991 <https://github.com/numpy/numpy/pull/9991>`__: MAINT: small robustness change for mingw support on Windows.
* `#9994 <https://github.com/numpy/numpy/pull/9994>`__: BUG: test was not using 'mode'
* `#9996 <https://github.com/numpy/numpy/pull/9996>`__: ENH: Adding `order=` keyword to `np.eye()`.
* `#9997 <https://github.com/numpy/numpy/pull/9997>`__: BUG: prototypes for [cz]dot[uc] are incorrect
* `#9999 <https://github.com/numpy/numpy/pull/9999>`__: ENH: Make `np.in1d()` work for unorderable object arrays
* `#10000 <https://github.com/numpy/numpy/pull/10000>`__: MAINT: Fix test_int_from_huge_longdouble on Darwin.
* `#10005 <https://github.com/numpy/numpy/pull/10005>`__: DOC: reword PyArray_DiscardWritebackIfCopy description
* `#10006 <https://github.com/numpy/numpy/pull/10006>`__: NEP: Drop Python2 support.
* `#10007 <https://github.com/numpy/numpy/pull/10007>`__: MAINT: simplify logic from #9983
* `#10008 <https://github.com/numpy/numpy/pull/10008>`__: MAINT: Backcompat fixes for dragon4 changes
* `#10011 <https://github.com/numpy/numpy/pull/10011>`__: TST: Group together all the nested_iter tests
* `#10017 <https://github.com/numpy/numpy/pull/10017>`__: REV: Undo bad rebase in 7fdfdd6a52fc0761c0d45931247c5ed2480224eb...
* `#10021 <https://github.com/numpy/numpy/pull/10021>`__: ENH: Don't show the boolean dtype in array_repr
* `#10022 <https://github.com/numpy/numpy/pull/10022>`__: MAINT: Update c-api version and hash for NumPy 1.14.
* `#10030 <https://github.com/numpy/numpy/pull/10030>`__: MAINT: Legacy mode specified as string, fix all-zeros legacy...
* `#10031 <https://github.com/numpy/numpy/pull/10031>`__: BUG: Fix f2py string variables in callbacks.
* `#10032 <https://github.com/numpy/numpy/pull/10032>`__: MAINT: Remove newline before dtype in repr of arrays
* `#10034 <https://github.com/numpy/numpy/pull/10034>`__: MAINT: legacy-printing-mode preserves 1.13 float & complex str
* `#10042 <https://github.com/numpy/numpy/pull/10042>`__: BUG: Allow `int` to be called on nested object arrays, fix `np.str_.__int__`
* `#10044 <https://github.com/numpy/numpy/pull/10044>`__: DEP: FutureWarning for void.item(): Will return bytes
* `#10049 <https://github.com/numpy/numpy/pull/10049>`__: DOC: Add copy of deprecated defindex.html template.
* `#10052 <https://github.com/numpy/numpy/pull/10052>`__: BUG: Fix legacy printing mode check.
* `#10053 <https://github.com/numpy/numpy/pull/10053>`__: STY: C style whitespace fixups
* `#10054 <https://github.com/numpy/numpy/pull/10054>`__: ENH: Add encoding option to numpy text IO.
* `#10055 <https://github.com/numpy/numpy/pull/10055>`__: BUG: Changed dump(a, F) so it would close file
* `#10057 <https://github.com/numpy/numpy/pull/10057>`__: DOC: v/h/dstack docstr shouldn't imply deprecation
* `#10065 <https://github.com/numpy/numpy/pull/10065>`__: DOC, BLD: Update site.cfg.example on the MKL part.
* `#10067 <https://github.com/numpy/numpy/pull/10067>`__: MAINT: Replace sphinx extension sphinx.ext.pngmath by sphinx.ext.imgmath.
* `#10068 <https://github.com/numpy/numpy/pull/10068>`__: BUG: Fix memory leak for subclass slicing
* `#10072 <https://github.com/numpy/numpy/pull/10072>`__: MAINT: Fix minor typos in numpy/core/fromnumeric.py
* `#10079 <https://github.com/numpy/numpy/pull/10079>`__: DOC: mention generalized ufuncs, document signature attribute
* `#10096 <https://github.com/numpy/numpy/pull/10096>`__: BUG: Fix assert_equal on time-like objects
* `#10097 <https://github.com/numpy/numpy/pull/10097>`__: BUG: Fix crash for 0d timedelta repr
* `#10101 <https://github.com/numpy/numpy/pull/10101>`__: BUG: Fix out-of-bounds access when handling rank-zero ndarrays.
* `#10105 <https://github.com/numpy/numpy/pull/10105>`__: DOC: Update license documentation.
* `#10108 <https://github.com/numpy/numpy/pull/10108>`__: DOC: Add documentation for datetime_data
* `#10109 <https://github.com/numpy/numpy/pull/10109>`__: DOC: fix the lack of np.
* `#10111 <https://github.com/numpy/numpy/pull/10111>`__: ENH: Improve alignment of datetime64 arrays containing NaT
* `#10112 <https://github.com/numpy/numpy/pull/10112>`__: MAINT: Simplify IntegerFormatter
* `#10113 <https://github.com/numpy/numpy/pull/10113>`__: BUG: Fix further out-of-bounds accesses when handling 0d ndarrays
* `#10114 <https://github.com/numpy/numpy/pull/10114>`__: MAINT: Remove duplicate cond check from assert_array_compare
* `#10116 <https://github.com/numpy/numpy/pull/10116>`__: BLD: [ipo] compilation error with intel compiler
* `#10120 <https://github.com/numpy/numpy/pull/10120>`__: BUG: stray comma should be preserved for legacy printing
* `#10121 <https://github.com/numpy/numpy/pull/10121>`__: DOC: Summarize printing changes in release notes
* `#10125 <https://github.com/numpy/numpy/pull/10125>`__: BLD: Add license file to NumPy wheels.
* `#10129 <https://github.com/numpy/numpy/pull/10129>`__: ENH: Strip trailing spaces from continuation in multiline arrayprint
* `#10130 <https://github.com/numpy/numpy/pull/10130>`__: MAINT: Simplify _leading_trailing
* `#10131 <https://github.com/numpy/numpy/pull/10131>`__: BUG: Fix downcasting in _array2string
* `#10136 <https://github.com/numpy/numpy/pull/10136>`__: BUG: edgeitems kwarg is ignored
* `#10143 <https://github.com/numpy/numpy/pull/10143>`__: MAINT: Combine legacy sections of _formatArray
* `#10159 <https://github.com/numpy/numpy/pull/10159>`__: DOC: Update 1.14 notes
* `#10160 <https://github.com/numpy/numpy/pull/10160>`__: BUG: test, fix problems from PR #9639
* `#10164 <https://github.com/numpy/numpy/pull/10164>`__: MAINT/BUG: Simplify _formatArray, fixing array_repr(matrix) in...
* `#10166 <https://github.com/numpy/numpy/pull/10166>`__: DOC: document PyArray_ResolveWritebackIfCopy
* `#10168 <https://github.com/numpy/numpy/pull/10168>`__: DOC: continuation of PyArray_ResolveIfCopy fixes
* `#10172 <https://github.com/numpy/numpy/pull/10172>`__: BUG: The last line of formatArray is not always wrapped correctly
* `#10175 <https://github.com/numpy/numpy/pull/10175>`__: BUG: linewidth was not respected for arrays other than 1d
* `#10176 <https://github.com/numpy/numpy/pull/10176>`__: ENH: add suffix option to array2str, wraps properly
* `#10177 <https://github.com/numpy/numpy/pull/10177>`__: MAINT, BUG: Final 1.14 formatting fixes
* `#10182 <https://github.com/numpy/numpy/pull/10182>`__: BUG: Extra space is inserted on first line for long elements
* `#10190 <https://github.com/numpy/numpy/pull/10190>`__: BUG: Fix regression in np.ma.load in gh-10055
* `#10200 <https://github.com/numpy/numpy/pull/10200>`__: BUG: Ufunc reduce reference leak (backport)
* `#10202 <https://github.com/numpy/numpy/pull/10202>`__: BUG: Fix bugs found by testing in release mode.
* `#10272 <https://github.com/numpy/numpy/pull/10272>`__: BUG: Align extra-dll folder name with auditwheel
* `#10275 <https://github.com/numpy/numpy/pull/10275>`__: BUG: fix duplicate message print
* `#10276 <https://github.com/numpy/numpy/pull/10276>`__: MAINT: Workaround for new travis sdist failures.
* `#10311 <https://github.com/numpy/numpy/pull/10311>`__: BUG: Make sure einsum default value of `optimize` is True.
* `#10312 <https://github.com/numpy/numpy/pull/10312>`__: BUG: Handle NaNs correctly in arange
* `#10313 <https://github.com/numpy/numpy/pull/10313>`__: BUG: Don't reimplement isclose in np.ma
* `#10315 <https://github.com/numpy/numpy/pull/10315>`__: DOC: NumPy 1.14.0 release prep.

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Contributors
============
A total of 14 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Allan Haldane
* Charles Harris
* Daniel Smith
* Dennis Weyland +
* Eric Larson
* Eric Wieser
* Jarrod Millman
* Kenichi Maehashi +
* Marten van Kerkwijk
* Mathieu Lamarre
* Sebastian Berg
* Simon Conseil
* Simon Gibbons
* xoviat
Pull requests merged
====================
A total of 36 pull requests were merged for this release.
* `#10339 <https://github.com/numpy/numpy/pull/10339>`__: BUG: restrict the __config__ modifications to win32
* `#10368 <https://github.com/numpy/numpy/pull/10368>`__: MAINT: Adjust type promotion in linalg.norm
* `#10375 <https://github.com/numpy/numpy/pull/10375>`__: BUG: add missing paren and remove quotes from repr of fieldless...
* `#10395 <https://github.com/numpy/numpy/pull/10395>`__: MAINT: Update download URL in setup.py.
* `#10396 <https://github.com/numpy/numpy/pull/10396>`__: BUG: fix einsum issue with unicode input and py2
* `#10397 <https://github.com/numpy/numpy/pull/10397>`__: BUG: fix error message not formatted in einsum
* `#10398 <https://github.com/numpy/numpy/pull/10398>`__: DOC: add documentation about how to handle new array printing
* `#10403 <https://github.com/numpy/numpy/pull/10403>`__: BUG: Set einsum optimize parameter default to `False`.
* `#10424 <https://github.com/numpy/numpy/pull/10424>`__: ENH: Fix repr of np.record objects to match np.void types #10412
* `#10425 <https://github.com/numpy/numpy/pull/10425>`__: MAINT: Update zesty to artful for i386 testing
* `#10431 <https://github.com/numpy/numpy/pull/10431>`__: REL: Add 1.14.1 release notes template
* `#10435 <https://github.com/numpy/numpy/pull/10435>`__: MAINT: Use ValueError for duplicate field names in lookup (backport)
* `#10534 <https://github.com/numpy/numpy/pull/10534>`__: BUG: Provide a better error message for out-of-order fields
* `#10536 <https://github.com/numpy/numpy/pull/10536>`__: BUG: Resize bytes_ columns in genfromtxt (backport of #10401)
* `#10537 <https://github.com/numpy/numpy/pull/10537>`__: BUG: multifield-indexing adds padding bytes: revert for 1.14.1
* `#10539 <https://github.com/numpy/numpy/pull/10539>`__: BUG: fix np.save issue with python 2.7.5
* `#10540 <https://github.com/numpy/numpy/pull/10540>`__: BUG: Add missing DECREF in Py2 int() cast
* `#10541 <https://github.com/numpy/numpy/pull/10541>`__: TST: Add circleci document testing to maintenance/1.14.x
* `#10542 <https://github.com/numpy/numpy/pull/10542>`__: BUG: complex repr has extra spaces, missing + (1.14 backport)
* `#10550 <https://github.com/numpy/numpy/pull/10550>`__: BUG: Set missing exception after malloc
* `#10557 <https://github.com/numpy/numpy/pull/10557>`__: BUG: In numpy.i, clear CARRAY flag if wrapped buffer is not C_CONTIGUOUS.
* `#10558 <https://github.com/numpy/numpy/pull/10558>`__: DEP: Issue FutureWarning when malformed records detected.
* `#10559 <https://github.com/numpy/numpy/pull/10559>`__: BUG: Fix einsum optimize logic for singleton dimensions
* `#10560 <https://github.com/numpy/numpy/pull/10560>`__: BUG: Fix calling ufuncs with a positional output argument.
* `#10561 <https://github.com/numpy/numpy/pull/10561>`__: BUG: Fix various Big-Endian test failures (ppc64)
* `#10562 <https://github.com/numpy/numpy/pull/10562>`__: BUG: Make dtype.descr error for out-of-order fields.
* `#10563 <https://github.com/numpy/numpy/pull/10563>`__: BUG: arrays not being flattened in `union1d`
* `#10607 <https://github.com/numpy/numpy/pull/10607>`__: MAINT: Update sphinxext submodule hash.
* `#10608 <https://github.com/numpy/numpy/pull/10608>`__: BUG: Revert sort optimization in np.unique.
* `#10609 <https://github.com/numpy/numpy/pull/10609>`__: BUG: infinite recursion in str of 0d subclasses
* `#10610 <https://github.com/numpy/numpy/pull/10610>`__: BUG: Align type definition with generated lapack
* `#10612 <https://github.com/numpy/numpy/pull/10612>`__: BUG/ENH: Improve output for structured non-void types
* `#10622 <https://github.com/numpy/numpy/pull/10622>`__: BUG: deallocate recursive closure in arrayprint.py (1.14 backport)
* `#10624 <https://github.com/numpy/numpy/pull/10624>`__: BUG: Correctly identify comma separated dtype strings
* `#10629 <https://github.com/numpy/numpy/pull/10629>`__: BUG: deallocate recursive closure in arrayprint.py (backport...
* `#10630 <https://github.com/numpy/numpy/pull/10630>`__: REL: Prepare for 1.14.1 release.

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Contributors
============
A total of 4 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Allan Haldane
* Charles Harris
* Eric Wieser
* Pauli Virtanen
Pull requests merged
====================
A total of 5 pull requests were merged for this release.
* `#10674 <https://github.com/numpy/numpy/pull/10674>`__: BUG: Further back-compat fix for subclassed array repr
* `#10725 <https://github.com/numpy/numpy/pull/10725>`__: BUG: dragon4 fractional output mode adds too many trailing zeros
* `#10726 <https://github.com/numpy/numpy/pull/10726>`__: BUG: Fix f2py generated code to work on PyPy
* `#10727 <https://github.com/numpy/numpy/pull/10727>`__: BUG: Fix missing NPY_VISIBILITY_HIDDEN on npy_longdouble_to_PyLong
* `#10729 <https://github.com/numpy/numpy/pull/10729>`__: DOC: Create 1.14.2 notes and changelog.

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Contributors
============
A total of 6 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Allan Haldane
* Charles Harris
* Jonathan March +
* Malcolm Smith +
* Matti Picus
* Pauli Virtanen
Pull requests merged
====================
A total of 8 pull requests were merged for this release.
* `#10862 <https://github.com/numpy/numpy/pull/10862>`__: BUG: floating types should override tp_print (1.14 backport)
* `#10905 <https://github.com/numpy/numpy/pull/10905>`__: BUG: for 1.14 back-compat, accept list-of-lists in fromrecords
* `#10947 <https://github.com/numpy/numpy/pull/10947>`__: BUG: 'style' arg to array2string broken in legacy mode (1.14...
* `#10959 <https://github.com/numpy/numpy/pull/10959>`__: BUG: test, fix for missing flags['WRITEBACKIFCOPY'] key
* `#10960 <https://github.com/numpy/numpy/pull/10960>`__: BUG: Add missing underscore to prototype in check_embedded_lapack
* `#10961 <https://github.com/numpy/numpy/pull/10961>`__: BUG: Fix encoding regression in ma/bench.py (Issue #10868)
* `#10962 <https://github.com/numpy/numpy/pull/10962>`__: BUG: core: fix NPY_TITLE_KEY macro on pypy
* `#10974 <https://github.com/numpy/numpy/pull/10974>`__: BUG: test, fix PyArray_DiscardWritebackIfCopy...

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Contributors
============
A total of 7 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Allan Haldane
* Charles Harris
* Marten van Kerkwijk
* Matti Picus
* Pauli Virtanen
* Ryan Soklaski +
* Sebastian Berg
Pull requests merged
====================
A total of 11 pull requests were merged for this release.
* `#11104 <https://github.com/numpy/numpy/pull/11104>`__: BUG: str of DOUBLE_DOUBLE format wrong on ppc64
* `#11170 <https://github.com/numpy/numpy/pull/11170>`__: TST: linalg: add regression test for gh-8577
* `#11174 <https://github.com/numpy/numpy/pull/11174>`__: MAINT: add sanity-checks to be run at import time
* `#11181 <https://github.com/numpy/numpy/pull/11181>`__: BUG: void dtype setup checked offset not actual pointer for alignment
* `#11194 <https://github.com/numpy/numpy/pull/11194>`__: BUG: Python2 doubles don't print correctly in interactive shell.
* `#11198 <https://github.com/numpy/numpy/pull/11198>`__: BUG: optimizing compilers can reorder call to npy_get_floatstatus
* `#11199 <https://github.com/numpy/numpy/pull/11199>`__: BUG: reduce using SSE only warns if inside SSE loop
* `#11203 <https://github.com/numpy/numpy/pull/11203>`__: BUG: Bytes delimiter/comments in genfromtxt should be decoded
* `#11211 <https://github.com/numpy/numpy/pull/11211>`__: BUG: Fix reference count/memory leak exposed by better testing
* `#11219 <https://github.com/numpy/numpy/pull/11219>`__: BUG: Fixes einsum broadcasting bug when optimize=True
* `#11251 <https://github.com/numpy/numpy/pull/11251>`__: DOC: Document 1.14.4 release.

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Contributors
============
A total of 1 person contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Charles Harris
Pull requests merged
====================
A total of 2 pull requests were merged for this release.
* `#11274 <https://github.com/numpy/numpy/pull/11274>`__: BUG: Correct use of NPY_UNUSED.
* `#11294 <https://github.com/numpy/numpy/pull/11294>`__: BUG: Remove extra trailing parentheses.

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Contributors
============
A total of 4 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Charles Harris
* Eric Wieser
* Julian Taylor
* Matti Picus
Pull requests merged
====================
A total of 4 pull requests were merged for this release.
* `#11985 <https://github.com/numpy/numpy/pull/11985>`__: BUG: fix cached allocations without the GIL
* `#11986 <https://github.com/numpy/numpy/pull/11986>`__: BUG: Undo behavior change in ma.masked_values(shrink=True)
* `#11987 <https://github.com/numpy/numpy/pull/11987>`__: BUG: fix refcount leak in PyArray_AdaptFlexibleDType
* `#11995 <https://github.com/numpy/numpy/pull/11995>`__: TST: Add Python 3.7 testing to NumPy 1.14.

584
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Contributors
============
A total of 133 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Aaron Critchley +
* Aarthi +
* Aarthi Agurusa +
* Alex Thomas +
* Alexander Belopolsky
* Allan Haldane
* Anas Khan +
* Andras Deak
* Andrey Portnoy +
* Anna Chiara
* Aurelien Jarno +
* Baurzhan Muftakhidinov
* Berend Kapelle +
* Bernhard M. Wiedemann
* Bjoern Thiel +
* Bob Eldering
* Cenny Wenner +
* Charles Harris
* ChloeColeongco +
* Chris Billington +
* Christopher +
* Chun-Wei Yuan +
* Claudio Freire +
* Daniel Smith
* Darcy Meyer +
* David Abdurachmanov +
* David Freese
* Deepak Kumar Gouda +
* Dennis Weyland +
* Derrick Williams +
* Dmitriy Shalyga +
* Eric Cousineau +
* Eric Larson
* Eric Wieser
* Evgeni Burovski
* Frederick Lefebvre +
* Gaspar Karm +
* Geoffrey Irving
* Gerhard Hobler +
* Gerrit Holl
* Guo Ci +
* Hameer Abbasi +
* Han Shen
* Hiroyuki V. Yamazaki +
* Hong Xu
* Ihor Melnyk +
* Jaime Fernandez
* Jake VanderPlas +
* James Tocknell +
* Jarrod Millman
* Jeff VanOss +
* John Kirkham
* Jonas Rauber +
* Jonathan March +
* Joseph Fox-Rabinovitz
* Julian Taylor
* Junjie Bai +
* Juris Bogusevs +
* Jörg Döpfert
* Kenichi Maehashi +
* Kevin Sheppard
* Kimikazu Kato +
* Kirit Thadaka +
* Kritika Jalan +
* Kyle Sunden +
* Lakshay Garg +
* Lars G +
* Licht Takeuchi
* Louis Potok +
* Luke Zoltan Kelley
* MSeifert04 +
* Mads R. B. Kristensen +
* Malcolm Smith +
* Mark Harfouche +
* Marten H. van Kerkwijk +
* Marten van Kerkwijk
* Matheus Vieira Portela +
* Mathieu Lamarre
* Mathieu Sornay +
* Matthew Brett
* Matthew Rocklin +
* Matthias Bussonnier
* Matti Picus
* Michael Droettboom
* Miguel Sánchez de León Peque +
* Mike Toews +
* Milo +
* Nathaniel J. Smith
* Nelle Varoquaux
* Nicholas Nadeau, P.Eng., AVS +
* Nick Minkyu Lee +
* Nikita +
* Nikita Kartashov +
* Nils Becker +
* Oleg Zabluda
* Orestis Floros +
* Pat Gunn +
* Paul van Mulbregt +
* Pauli Virtanen
* Pierre Chanial +
* Ralf Gommers
* Raunak Shah +
* Robert Kern
* Russell Keith-Magee +
* Ryan Soklaski +
* Samuel Jackson +
* Sebastian Berg
* Siavash Eliasi +
* Simon Conseil
* Simon Gibbons
* Stefan Krah +
* Stefan van der Walt
* Stephan Hoyer
* Subhendu +
* Subhendu Ranjan Mishra +
* Tai-Lin Wu +
* Tobias Fischer +
* Toshiki Kataoka +
* Tyler Reddy +
* Unknown +
* Varun Nayyar
* Victor Rodriguez +
* Warren Weckesser
* William D. Irons +
* Zane Bradley +
* cclauss +
* fo40225 +
* lapack_lite code generator +
* lumbric +
* luzpaz +
* mamrehn +
* tynn +
* xoviat
Pull requests merged
====================
A total of 438 pull requests were merged for this release.
* `#8157 <https://github.com/numpy/numpy/pull/8157>`__: BUG: void .item() doesn't hold reference to original array
* `#8774 <https://github.com/numpy/numpy/pull/8774>`__: ENH: Add gcd and lcm ufuncs
* `#8819 <https://github.com/numpy/numpy/pull/8819>`__: ENH: Implement axes keyword argument for gufuncs.
* `#8952 <https://github.com/numpy/numpy/pull/8952>`__: MAINT: Removed duplicated code around `ufunc->identity`
* `#9686 <https://github.com/numpy/numpy/pull/9686>`__: DEP: Deprecate non-tuple nd-indices
* `#9980 <https://github.com/numpy/numpy/pull/9980>`__: MAINT: Implement `lstsq` as a `gufunc`
* `#9998 <https://github.com/numpy/numpy/pull/9998>`__: ENH: Nditer as context manager
* `#10073 <https://github.com/numpy/numpy/pull/10073>`__: ENH: Implement fft.fftshift/ifftshift with np.roll for improved...
* `#10078 <https://github.com/numpy/numpy/pull/10078>`__: DOC: document nested_iters
* `#10128 <https://github.com/numpy/numpy/pull/10128>`__: BUG: Prefix library names with `lib` on windows.
* `#10142 <https://github.com/numpy/numpy/pull/10142>`__: DEP: Pending deprecation warning for matrix
* `#10154 <https://github.com/numpy/numpy/pull/10154>`__: MAINT: Use a StructSequence in place of the typeinfo tuples
* `#10158 <https://github.com/numpy/numpy/pull/10158>`__: BUG: Fix a few smaller valgrind errors
* `#10178 <https://github.com/numpy/numpy/pull/10178>`__: MAINT: Prepare master for 1.15 development.
* `#10186 <https://github.com/numpy/numpy/pull/10186>`__: MAINT: Move histogram and histogramdd into their own module
* `#10187 <https://github.com/numpy/numpy/pull/10187>`__: BUG: Extra space is inserted on first line for long elements
* `#10192 <https://github.com/numpy/numpy/pull/10192>`__: DEP: Deprecate the pickle aliases
* `#10193 <https://github.com/numpy/numpy/pull/10193>`__: BUG: Fix bugs found by testing in release mode.
* `#10194 <https://github.com/numpy/numpy/pull/10194>`__: BUG, MAINT: Ufunc reduce reference leak
* `#10195 <https://github.com/numpy/numpy/pull/10195>`__: DOC: Fixup percentile docstring, from review in gh-9213
* `#10196 <https://github.com/numpy/numpy/pull/10196>`__: BUG: Fix regression in np.ma.load in gh-10055
* `#10199 <https://github.com/numpy/numpy/pull/10199>`__: ENH: Quantile
* `#10203 <https://github.com/numpy/numpy/pull/10203>`__: MAINT: Update development branch version to 1.15.0.
* `#10205 <https://github.com/numpy/numpy/pull/10205>`__: BUG: Handle NaNs correctly in arange
* `#10207 <https://github.com/numpy/numpy/pull/10207>`__: ENH: Allow `np.r_` to accept 0d arrays
* `#10208 <https://github.com/numpy/numpy/pull/10208>`__: MAINT: Improve error message for void(-1)
* `#10210 <https://github.com/numpy/numpy/pull/10210>`__: DOC: change 'a'->'prototype' in empty_like docs (addresses #10209)
* `#10211 <https://github.com/numpy/numpy/pull/10211>`__: MAINT,ENH: remove MaskedArray.astype, as the base type does everything.
* `#10212 <https://github.com/numpy/numpy/pull/10212>`__: DOC: fix minor typos
* `#10213 <https://github.com/numpy/numpy/pull/10213>`__: ENH: Set up proposed NEP process
* `#10214 <https://github.com/numpy/numpy/pull/10214>`__: DOC: add warning to isclose function
* `#10216 <https://github.com/numpy/numpy/pull/10216>`__: BUG: Fix broken format string picked up by LGTM.com
* `#10220 <https://github.com/numpy/numpy/pull/10220>`__: DOC: clarify that np.absolute == np.abs
* `#10223 <https://github.com/numpy/numpy/pull/10223>`__: ENH: added masked version of 'numpy.stack' with tests.
* `#10225 <https://github.com/numpy/numpy/pull/10225>`__: ENH: distutils: parallelize builds by default
* `#10226 <https://github.com/numpy/numpy/pull/10226>`__: BUG: distutils: use correct top-level package name
* `#10229 <https://github.com/numpy/numpy/pull/10229>`__: BUG: distutils: fix extra DLL loading in certain scenarios
* `#10231 <https://github.com/numpy/numpy/pull/10231>`__: BUG: Fix sign-compare warnings in datetime.c and datetime_strings.c.
* `#10232 <https://github.com/numpy/numpy/pull/10232>`__: BUG: Don't reimplement isclose in np.ma
* `#10237 <https://github.com/numpy/numpy/pull/10237>`__: DOC: give correct version of np.nansum change
* `#10241 <https://github.com/numpy/numpy/pull/10241>`__: MAINT: Avoid repeated validation of percentiles in nanpercentile
* `#10247 <https://github.com/numpy/numpy/pull/10247>`__: MAINT: fix typo
* `#10248 <https://github.com/numpy/numpy/pull/10248>`__: DOC: Add installation notes for Linux users
* `#10249 <https://github.com/numpy/numpy/pull/10249>`__: MAINT: Fix tests failures on travis CI merge.
* `#10250 <https://github.com/numpy/numpy/pull/10250>`__: MAINT: Check for `__array_ufunc__` before doing anything else.
* `#10251 <https://github.com/numpy/numpy/pull/10251>`__: ENH: Enable AVX2/AVX512 support to numpy
* `#10252 <https://github.com/numpy/numpy/pull/10252>`__: MAINT: Workaround for new travis sdist failures.
* `#10255 <https://github.com/numpy/numpy/pull/10255>`__: MAINT: Fix loop and simd sign-compare warnings.
* `#10257 <https://github.com/numpy/numpy/pull/10257>`__: BUG: duplicate message print if warning raises an exception
* `#10259 <https://github.com/numpy/numpy/pull/10259>`__: BUG: Make sure einsum default value of `optimize` is True.
* `#10260 <https://github.com/numpy/numpy/pull/10260>`__: ENH: Add pytest support
* `#10261 <https://github.com/numpy/numpy/pull/10261>`__: MAINT: Extract helper functions from histogram
* `#10262 <https://github.com/numpy/numpy/pull/10262>`__: DOC: Add missing release note for #10207
* `#10263 <https://github.com/numpy/numpy/pull/10263>`__: BUG: Fix strange behavior of infinite-step-size/underflow-case...
* `#10264 <https://github.com/numpy/numpy/pull/10264>`__: MAINT: Fix (some) yield warnings
* `#10266 <https://github.com/numpy/numpy/pull/10266>`__: BUG: distutils: fix locale decoding errors
* `#10268 <https://github.com/numpy/numpy/pull/10268>`__: BUG: Fix misleading error when coercing to array
* `#10269 <https://github.com/numpy/numpy/pull/10269>`__: MAINT: extract private helper function to compute histogram bin...
* `#10271 <https://github.com/numpy/numpy/pull/10271>`__: BUG: Allow nan values in the data when the bins are explicit
* `#10278 <https://github.com/numpy/numpy/pull/10278>`__: ENH: Add support for datetimes to histograms
* `#10282 <https://github.com/numpy/numpy/pull/10282>`__: MAINT: Extract helper function for last-bound-inclusive search_sorted
* `#10283 <https://github.com/numpy/numpy/pull/10283>`__: MAINT: Fallback on the default sequence multiplication behavior
* `#10284 <https://github.com/numpy/numpy/pull/10284>`__: MAINT/BUG: Tidy gen_umath
* `#10286 <https://github.com/numpy/numpy/pull/10286>`__: BUG: Fix memory leak (#10157).
* `#10287 <https://github.com/numpy/numpy/pull/10287>`__: ENH: Allow ptp to take an axis tuple and keepdims
* `#10292 <https://github.com/numpy/numpy/pull/10292>`__: BUG: Masked singleton can be reshaped to be non-scalar
* `#10293 <https://github.com/numpy/numpy/pull/10293>`__: MAINT: Fix sign-compare warnings in mem_overlap.c.
* `#10294 <https://github.com/numpy/numpy/pull/10294>`__: MAINT: pytest cleanups
* `#10298 <https://github.com/numpy/numpy/pull/10298>`__: DOC: Explain np.digitize and np.searchsorted more clearly
* `#10300 <https://github.com/numpy/numpy/pull/10300>`__: MAINT, DOC: Documentation and misc. typos
* `#10303 <https://github.com/numpy/numpy/pull/10303>`__: MAINT: Array wrap/prepare identification cleanup
* `#10309 <https://github.com/numpy/numpy/pull/10309>`__: MAINT: deduplicate check_nonreorderable_axes
* `#10314 <https://github.com/numpy/numpy/pull/10314>`__: BUG: Ensure `__array_finalize__` cannot back-mangle shape
* `#10316 <https://github.com/numpy/numpy/pull/10316>`__: DOC: add documentation about how to handle new array printing
* `#10320 <https://github.com/numpy/numpy/pull/10320>`__: BUG: skip the extra-dll directory when there are no DLLS
* `#10323 <https://github.com/numpy/numpy/pull/10323>`__: MAINT: Remove duplicated code for promoting dtype and array types.
* `#10324 <https://github.com/numpy/numpy/pull/10324>`__: BUG: Fix crashes when using float32 values in uniform histograms
* `#10325 <https://github.com/numpy/numpy/pull/10325>`__: MAINT: Replace manual expansion of PyArray_MinScalarType with...
* `#10327 <https://github.com/numpy/numpy/pull/10327>`__: MAINT: Fix misc. typos
* `#10333 <https://github.com/numpy/numpy/pull/10333>`__: DOC: typo fix in numpy.linalg.det docstring
* `#10334 <https://github.com/numpy/numpy/pull/10334>`__: DOC: Fix typos in docs for partition method
* `#10336 <https://github.com/numpy/numpy/pull/10336>`__: DOC: Post 1.14.0 release updates.
* `#10337 <https://github.com/numpy/numpy/pull/10337>`__: ENH: Show the silenced error and traceback in warning `__cause__`
* `#10341 <https://github.com/numpy/numpy/pull/10341>`__: BUG: fix config where PATH isn't set on win32
* `#10342 <https://github.com/numpy/numpy/pull/10342>`__: BUG: arrays not being flattened in `union1d`
* `#10346 <https://github.com/numpy/numpy/pull/10346>`__: ENH: Check matching inputs/outputs in umath generation
* `#10352 <https://github.com/numpy/numpy/pull/10352>`__: BUG: Fix einsum optimize logic for singleton dimensions
* `#10354 <https://github.com/numpy/numpy/pull/10354>`__: BUG: fix error message not formatted in einsum
* `#10359 <https://github.com/numpy/numpy/pull/10359>`__: BUG: do not optimize einsum with only 2 arguments.
* `#10361 <https://github.com/numpy/numpy/pull/10361>`__: BUG: complex repr has extra spaces, missing +
* `#10362 <https://github.com/numpy/numpy/pull/10362>`__: MAINT: Update download URL in setup.py.
* `#10367 <https://github.com/numpy/numpy/pull/10367>`__: BUG: add missing paren and remove quotes from repr of fieldless...
* `#10371 <https://github.com/numpy/numpy/pull/10371>`__: BUG: fix einsum issue with unicode input and py2
* `#10381 <https://github.com/numpy/numpy/pull/10381>`__: BUG/ENH: Improve output for structured non-void types
* `#10388 <https://github.com/numpy/numpy/pull/10388>`__: ENH: Add types for int and uint of explicit sizes to swig.
* `#10390 <https://github.com/numpy/numpy/pull/10390>`__: MAINT: Adjust type promotion in linalg.norm
* `#10391 <https://github.com/numpy/numpy/pull/10391>`__: BUG: Make dtype.descr error for out-of-order fields
* `#10392 <https://github.com/numpy/numpy/pull/10392>`__: DOC: Document behaviour of `np.concatenate` with `axis=None`
* `#10401 <https://github.com/numpy/numpy/pull/10401>`__: BUG: Resize bytes_ columns in genfromtxt
* `#10402 <https://github.com/numpy/numpy/pull/10402>`__: DOC: added "steals a reference" to PyArray_FromAny
* `#10406 <https://github.com/numpy/numpy/pull/10406>`__: ENH: add `np.printoptions`, a context manager
* `#10411 <https://github.com/numpy/numpy/pull/10411>`__: BUG: Revert multifield-indexing adds padding bytes for NumPy...
* `#10412 <https://github.com/numpy/numpy/pull/10412>`__: ENH: Fix repr of np.record objects to match np.void types
* `#10414 <https://github.com/numpy/numpy/pull/10414>`__: MAINT: Fix sign-compare warnings in umath_linalg.
* `#10415 <https://github.com/numpy/numpy/pull/10415>`__: MAINT: Fix sign-compare warnings in npy_binsearch, npy_partition.
* `#10416 <https://github.com/numpy/numpy/pull/10416>`__: MAINT: Fix sign-compare warnings in dragon4.c.
* `#10418 <https://github.com/numpy/numpy/pull/10418>`__: MAINT: Remove repeated #ifdefs implementing `isinstance(x, basestring)`...
* `#10420 <https://github.com/numpy/numpy/pull/10420>`__: DOC: Fix version added labels in numpy.unique docs
* `#10421 <https://github.com/numpy/numpy/pull/10421>`__: DOC: Fix type of axis in nanfunctions
* `#10423 <https://github.com/numpy/numpy/pull/10423>`__: MAINT: Update zesty to artful for i386 testing
* `#10426 <https://github.com/numpy/numpy/pull/10426>`__: DOC: Add version when linalg.norm accepted axis
* `#10427 <https://github.com/numpy/numpy/pull/10427>`__: DOC: Fix typo in docs for argpartition
* `#10430 <https://github.com/numpy/numpy/pull/10430>`__: MAINT: Use ValueError for duplicate field names in lookup
* `#10433 <https://github.com/numpy/numpy/pull/10433>`__: DOC: Add 1.14.1 release notes template (forward port)
* `#10434 <https://github.com/numpy/numpy/pull/10434>`__: MAINT: Move `tools/announce.py` to `tools/changelog.py`.
* `#10441 <https://github.com/numpy/numpy/pull/10441>`__: BUG: Fix nan_to_num return with integer input
* `#10443 <https://github.com/numpy/numpy/pull/10443>`__: BUG: Fix various Big-Endian test failures (ppc64)
* `#10444 <https://github.com/numpy/numpy/pull/10444>`__: MAINT: Implement float128 dragon4 for IBM double-double (ppc64)
* `#10451 <https://github.com/numpy/numpy/pull/10451>`__: BUG: prevent the MSVC 14.1 compiler (Visual Studio 2017) from...
* `#10453 <https://github.com/numpy/numpy/pull/10453>`__: Revert "BUG: prevent the MSVC 14.1 compiler (Visual Studio 2017)...
* `#10458 <https://github.com/numpy/numpy/pull/10458>`__: BLD: Use zip_safe=False in setup() call
* `#10459 <https://github.com/numpy/numpy/pull/10459>`__: MAINT: Remove duplicated logic between array_wrap and array_prepare
* `#10463 <https://github.com/numpy/numpy/pull/10463>`__: ENH: Add entry_points for f2py, conv_template, and from_template.
* `#10465 <https://github.com/numpy/numpy/pull/10465>`__: MAINT: Fix miscellaneous sign-compare warnings.
* `#10472 <https://github.com/numpy/numpy/pull/10472>`__: DOC: Document A@B in Matlab/NumPy summary table
* `#10473 <https://github.com/numpy/numpy/pull/10473>`__: BUG: Fixed polydiv for Complex Numbers
* `#10475 <https://github.com/numpy/numpy/pull/10475>`__: DOC: Add CircleCI builder for devdocs
* `#10476 <https://github.com/numpy/numpy/pull/10476>`__: DOC: fix formatting in interp example
* `#10477 <https://github.com/numpy/numpy/pull/10477>`__: BUG: Align type definition with generated lapack
* `#10478 <https://github.com/numpy/numpy/pull/10478>`__: DOC: Minor punctuation cleanups and improved explanation.
* `#10479 <https://github.com/numpy/numpy/pull/10479>`__: BUG: Fix calling ufuncs with a positional output argument.
* `#10482 <https://github.com/numpy/numpy/pull/10482>`__: BUG: Add missing DECREF in Py2 int() cast
* `#10484 <https://github.com/numpy/numpy/pull/10484>`__: MAINT: Remove unused code path for applying maskedarray domains...
* `#10497 <https://github.com/numpy/numpy/pull/10497>`__: DOC: Tell matlab users about np.block
* `#10498 <https://github.com/numpy/numpy/pull/10498>`__: MAINT: Remove special cases in np.unique
* `#10501 <https://github.com/numpy/numpy/pull/10501>`__: BUG: fromregex: asbytes called on regexp objects
* `#10502 <https://github.com/numpy/numpy/pull/10502>`__: MAINT: Use AxisError in swapaxes, unique, and diagonal
* `#10503 <https://github.com/numpy/numpy/pull/10503>`__: BUG: Fix unused-result warning.
* `#10506 <https://github.com/numpy/numpy/pull/10506>`__: MAINT: Delete unused `_build_utils/common.py`
* `#10508 <https://github.com/numpy/numpy/pull/10508>`__: BUG: Add missing `#define _MULTIARRAYMODULE` to vdot.c
* `#10509 <https://github.com/numpy/numpy/pull/10509>`__: MAINT: Use new-style format strings for clarity
* `#10516 <https://github.com/numpy/numpy/pull/10516>`__: MAINT: Allow errors to escape from InitOperators
* `#10518 <https://github.com/numpy/numpy/pull/10518>`__: ENH: Add a repr to np._NoValue
* `#10522 <https://github.com/numpy/numpy/pull/10522>`__: MAINT: Remove the unmaintained umath ``__version__`` constant.
* `#10524 <https://github.com/numpy/numpy/pull/10524>`__: BUG: fix np.save issue with python 2.7.5
* `#10529 <https://github.com/numpy/numpy/pull/10529>`__: BUG: Provide a better error message for out-of-order fields
* `#10543 <https://github.com/numpy/numpy/pull/10543>`__: DEP: Issue FutureWarning when malformed records detected.
* `#10544 <https://github.com/numpy/numpy/pull/10544>`__: BUG: infinite recursion in str of 0d subclasses
* `#10546 <https://github.com/numpy/numpy/pull/10546>`__: BUG: In numpy.i, clear CARRAY flag if wrapped buffer is not C_CONTIGUOUS.
* `#10547 <https://github.com/numpy/numpy/pull/10547>`__: DOC: Fix incorrect formula in gradient docstring.
* `#10548 <https://github.com/numpy/numpy/pull/10548>`__: BUG: Set missing exception after malloc
* `#10549 <https://github.com/numpy/numpy/pull/10549>`__: ENH: Make NpzFile conform to the Mapping protocol
* `#10553 <https://github.com/numpy/numpy/pull/10553>`__: MAINT: Cleanups to promote_types and result_types
* `#10554 <https://github.com/numpy/numpy/pull/10554>`__: DOC: promote_types is not associative by design,
* `#10555 <https://github.com/numpy/numpy/pull/10555>`__: BUG: Add missing PyErr_NoMemory() after malloc
* `#10564 <https://github.com/numpy/numpy/pull/10564>`__: BUG: Provide correct format in Py_buffer for scalars
* `#10566 <https://github.com/numpy/numpy/pull/10566>`__: BUG: Fix travis failure in previous commit
* `#10571 <https://github.com/numpy/numpy/pull/10571>`__: BUG: Fix corner-case behavior of cond() and use SVD when possible
* `#10576 <https://github.com/numpy/numpy/pull/10576>`__: MAINT: Fix misc. documentation typos
* `#10583 <https://github.com/numpy/numpy/pull/10583>`__: MAINT: Fix typos in DISTUTILS.rst.txt.
* `#10588 <https://github.com/numpy/numpy/pull/10588>`__: BUG: Revert sort optimization in np.unique.
* `#10589 <https://github.com/numpy/numpy/pull/10589>`__: BUG: fix entry_points typo for from-template
* `#10591 <https://github.com/numpy/numpy/pull/10591>`__: ENH: Add histogram_bin_edges function and test
* `#10592 <https://github.com/numpy/numpy/pull/10592>`__: DOC: Corrected url for Guide to NumPy book; see part of #8520,...
* `#10596 <https://github.com/numpy/numpy/pull/10596>`__: MAINT: Update sphinxext submodule hash.
* `#10599 <https://github.com/numpy/numpy/pull/10599>`__: ENH: Make flatnonzero call asanyarray before ravel()
* `#10603 <https://github.com/numpy/numpy/pull/10603>`__: MAINT: Improve error message in histogram.
* `#10604 <https://github.com/numpy/numpy/pull/10604>`__: MAINT: Fix Misc. typos
* `#10606 <https://github.com/numpy/numpy/pull/10606>`__: MAINT: Do not use random roots when testing roots.
* `#10618 <https://github.com/numpy/numpy/pull/10618>`__: MAINT: Stop using non-tuple indices internally
* `#10619 <https://github.com/numpy/numpy/pull/10619>`__: BUG: np.ma.flatnotmasked_contiguous behaves differently on mask=nomask...
* `#10621 <https://github.com/numpy/numpy/pull/10621>`__: BUG: deallocate recursive closure in arrayprint.py
* `#10623 <https://github.com/numpy/numpy/pull/10623>`__: BUG: Correctly identify comma separated dtype strings
* `#10625 <https://github.com/numpy/numpy/pull/10625>`__: BUG: Improve the accuracy of the FFT implementation
* `#10635 <https://github.com/numpy/numpy/pull/10635>`__: ENH: Implement initial kwarg for ufunc.add.reduce
* `#10641 <https://github.com/numpy/numpy/pull/10641>`__: MAINT: Post 1.14.1 release updates for master branch
* `#10650 <https://github.com/numpy/numpy/pull/10650>`__: BUG: Fix missing NPY_VISIBILITY_HIDDEN on npy_longdouble_to_PyLong
* `#10653 <https://github.com/numpy/numpy/pull/10653>`__: MAINT: Remove duplicate implementation for aliased functions.
* `#10657 <https://github.com/numpy/numpy/pull/10657>`__: BUG: f2py: fix f2py generated code to work on Pypy
* `#10658 <https://github.com/numpy/numpy/pull/10658>`__: BUG: Make np.partition and np.sort work on np.matrix when axis=None
* `#10660 <https://github.com/numpy/numpy/pull/10660>`__: BUG/MAINT: Remove special cases for 0d arrays in interp
* `#10661 <https://github.com/numpy/numpy/pull/10661>`__: MAINT: Unify reductions in fromnumeric.py
* `#10665 <https://github.com/numpy/numpy/pull/10665>`__: ENH: umath: don't make temporary copies for in-place accumulation
* `#10666 <https://github.com/numpy/numpy/pull/10666>`__: BUG: fix complex casting error in cov with aweights
* `#10669 <https://github.com/numpy/numpy/pull/10669>`__: MAINT: Covariance must be symmetric as well as positive-semidefinite.
* `#10670 <https://github.com/numpy/numpy/pull/10670>`__: DEP: Deprecate np.sum(generator)
* `#10671 <https://github.com/numpy/numpy/pull/10671>`__: DOC/MAINT: More misc. typos
* `#10672 <https://github.com/numpy/numpy/pull/10672>`__: ENH: Allow dtype field names to be ascii encoded unicode in Python2
* `#10676 <https://github.com/numpy/numpy/pull/10676>`__: BUG: F2py mishandles quoted control characters
* `#10677 <https://github.com/numpy/numpy/pull/10677>`__: STY: Minor stylistic cleanup of numeric.py
* `#10679 <https://github.com/numpy/numpy/pull/10679>`__: DOC: zeros, empty, and ones now have consistent docstrings
* `#10684 <https://github.com/numpy/numpy/pull/10684>`__: ENH: Modify intersect1d to return common indices
* `#10689 <https://github.com/numpy/numpy/pull/10689>`__: BLD: Add configuration changes to allow cross platform builds...
* `#10691 <https://github.com/numpy/numpy/pull/10691>`__: DOC: add versionadded for NDArrayOperatorsMixin.
* `#10694 <https://github.com/numpy/numpy/pull/10694>`__: DOC: Improve docstring of memmap
* `#10698 <https://github.com/numpy/numpy/pull/10698>`__: BUG: Further back-compat fix for subclassed array repr (forward...
* `#10699 <https://github.com/numpy/numpy/pull/10699>`__: DOC: Grammar of np.gradient docstring
* `#10702 <https://github.com/numpy/numpy/pull/10702>`__: TST, DOC: Upload devdocs and neps after circleci build
* `#10703 <https://github.com/numpy/numpy/pull/10703>`__: MAINT: NEP process updates
* `#10708 <https://github.com/numpy/numpy/pull/10708>`__: BUG: fix problem with modifying pyf lines containing ';' in f2py
* `#10710 <https://github.com/numpy/numpy/pull/10710>`__: BUG: fix error message in numpy.select
* `#10711 <https://github.com/numpy/numpy/pull/10711>`__: MAINT: Hard tab and whitespace cleanup.
* `#10715 <https://github.com/numpy/numpy/pull/10715>`__: MAINT: Fixed C++ guard in f2py test.
* `#10716 <https://github.com/numpy/numpy/pull/10716>`__: BUG: dragon4 fractional output mode adds too many trailing zeros
* `#10718 <https://github.com/numpy/numpy/pull/10718>`__: BUG: Fix bug in asserting near equality of float16 arrays.
* `#10719 <https://github.com/numpy/numpy/pull/10719>`__: DOC: add documentation for constants
* `#10720 <https://github.com/numpy/numpy/pull/10720>`__: BUG: distutils: Remove named templates from the processed output...
* `#10722 <https://github.com/numpy/numpy/pull/10722>`__: MAINT: Misc small fixes.
* `#10730 <https://github.com/numpy/numpy/pull/10730>`__: DOC: Fix minor typo in how-to-document.
* `#10732 <https://github.com/numpy/numpy/pull/10732>`__: BUG: Fix `setup.py build install egg_info`, which did not previously...
* `#10734 <https://github.com/numpy/numpy/pull/10734>`__: DOC: Post 1.14.2 release update.
* `#10737 <https://github.com/numpy/numpy/pull/10737>`__: MAINT: Fix low-hanging PyPy compatibility issues
* `#10739 <https://github.com/numpy/numpy/pull/10739>`__: BUG: Fix histogram bins="auto" for data with little variance
* `#10740 <https://github.com/numpy/numpy/pull/10740>`__: MAINT, TST: Fixes for Python 3.7
* `#10743 <https://github.com/numpy/numpy/pull/10743>`__: MAINT: Import abstract classes from collections.abc
* `#10745 <https://github.com/numpy/numpy/pull/10745>`__: ENH: Add object loops to the comparison ufuncs
* `#10746 <https://github.com/numpy/numpy/pull/10746>`__: MAINT: Fix typo in warning message
* `#10748 <https://github.com/numpy/numpy/pull/10748>`__: DOC: a.size and np.prod(a.shape) are not equivalent
* `#10750 <https://github.com/numpy/numpy/pull/10750>`__: DOC: Add graph showing different behaviors of np.percentile
* `#10755 <https://github.com/numpy/numpy/pull/10755>`__: DOC: Move bin estimator documentation from `histogram` to `histogram_bin_edges`
* `#10758 <https://github.com/numpy/numpy/pull/10758>`__: TST: Change most travisci tests to Python3.6.
* `#10763 <https://github.com/numpy/numpy/pull/10763>`__: BUG: floating types should override tp_print
* `#10766 <https://github.com/numpy/numpy/pull/10766>`__: MAINT: Remove the unused scalarmath getters for fmod and sqrt
* `#10773 <https://github.com/numpy/numpy/pull/10773>`__: BUG: Use dummy_threading on platforms that don't support threading
* `#10774 <https://github.com/numpy/numpy/pull/10774>`__: BUG: Fix SQRT_MIN for platforms with 8-byte long double
* `#10775 <https://github.com/numpy/numpy/pull/10775>`__: BUG: Return NULL from PyInit_* when exception is raised
* `#10777 <https://github.com/numpy/numpy/pull/10777>`__: MAINT: Remove use of unittest in NumPy tests.
* `#10778 <https://github.com/numpy/numpy/pull/10778>`__: BUG: test, fix for missing flags['WRITEBACKIFCOPY'] key
* `#10781 <https://github.com/numpy/numpy/pull/10781>`__: ENH: NEP index builder
* `#10785 <https://github.com/numpy/numpy/pull/10785>`__: DOC: Fixed author name in reference to book
* `#10786 <https://github.com/numpy/numpy/pull/10786>`__: ENH: Add "stable" option to np.sort as an alias for "mergesort".
* `#10790 <https://github.com/numpy/numpy/pull/10790>`__: TST: Various fixes prior to switching to pytest
* `#10795 <https://github.com/numpy/numpy/pull/10795>`__: BUG: Allow spaces in output string of einsum
* `#10796 <https://github.com/numpy/numpy/pull/10796>`__: BUG: fix wrong inplace vectorization on overlapping arguments
* `#10798 <https://github.com/numpy/numpy/pull/10798>`__: BUG: error checking before mapping of einsum axes.
* `#10800 <https://github.com/numpy/numpy/pull/10800>`__: DOC: Add remarks about array vs scalar output to every ufunc
* `#10802 <https://github.com/numpy/numpy/pull/10802>`__: BUG/DOC/MAINT: Tidy up histogramdd
* `#10807 <https://github.com/numpy/numpy/pull/10807>`__: DOC: Update link to tox in development docs (#10806)
* `#10812 <https://github.com/numpy/numpy/pull/10812>`__: MAINT: Rearrange `numpy/testing` files
* `#10814 <https://github.com/numpy/numpy/pull/10814>`__: BUG: verify the OS supports avx instruction
* `#10822 <https://github.com/numpy/numpy/pull/10822>`__: BUG: fixes exception in numpy.genfromtxt, see #10780
* `#10824 <https://github.com/numpy/numpy/pull/10824>`__: BUG: test, fix PyArray_DiscardWritebackIfCopy refcount issue...
* `#10826 <https://github.com/numpy/numpy/pull/10826>`__: BUG: np.squeeze() now respects older API axis expectation
* `#10827 <https://github.com/numpy/numpy/pull/10827>`__: ENH: Add tester for pytest.
* `#10828 <https://github.com/numpy/numpy/pull/10828>`__: BUG: fix obvious mistake in testing/decorators warning.
* `#10829 <https://github.com/numpy/numpy/pull/10829>`__: BLD: use Python 3.6 instead of 2.7 as default for doc build.
* `#10830 <https://github.com/numpy/numpy/pull/10830>`__: BUG: Fix obvious warning bugs.
* `#10831 <https://github.com/numpy/numpy/pull/10831>`__: DOC: Fix minor typos
* `#10832 <https://github.com/numpy/numpy/pull/10832>`__: ENH: datetime64: support AC dates starting with '+'
* `#10833 <https://github.com/numpy/numpy/pull/10833>`__: ENH: Add support for the 64-bit RISC-V architecture
* `#10834 <https://github.com/numpy/numpy/pull/10834>`__: DOC: note that NDEBUG should be set when OPT should increase...
* `#10836 <https://github.com/numpy/numpy/pull/10836>`__: MAINT: Fix script name for pushing NEP docs to repo
* `#10840 <https://github.com/numpy/numpy/pull/10840>`__: MAINT: Fix typo in code example.
* `#10842 <https://github.com/numpy/numpy/pull/10842>`__: TST: Switch to pytest
* `#10849 <https://github.com/numpy/numpy/pull/10849>`__: DOC: fix examples in docstring for np.flip
* `#10850 <https://github.com/numpy/numpy/pull/10850>`__: DEP: Issue deprecation warnings for some imports.
* `#10858 <https://github.com/numpy/numpy/pull/10858>`__: MAINT: Post pytest switch cleanup
* `#10859 <https://github.com/numpy/numpy/pull/10859>`__: MAINT: Remove yield tests
* `#10860 <https://github.com/numpy/numpy/pull/10860>`__: BUG: core: fix NPY_TITLE_KEY macro on pypy
* `#10863 <https://github.com/numpy/numpy/pull/10863>`__: MAINT: More Histogramdd cleanup
* `#10867 <https://github.com/numpy/numpy/pull/10867>`__: DOC: Cross Link full/full_like in a few see-also sections.
* `#10869 <https://github.com/numpy/numpy/pull/10869>`__: BUG: Fix encoding regression in ma/bench.py (Issue #10868)
* `#10871 <https://github.com/numpy/numpy/pull/10871>`__: MAINT: Remove unnecessary special case in np.histogramdd for...
* `#10872 <https://github.com/numpy/numpy/pull/10872>`__: ENH: Extend np.flip to work over multiple axes
* `#10874 <https://github.com/numpy/numpy/pull/10874>`__: DOC: State in docstring that lexsort is stable (#10873).
* `#10875 <https://github.com/numpy/numpy/pull/10875>`__: BUG: fix savetxt, loadtxt for '+-' in complex
* `#10878 <https://github.com/numpy/numpy/pull/10878>`__: DOC: rework documents and silence warnings during sphinx build
* `#10882 <https://github.com/numpy/numpy/pull/10882>`__: BUG: have `_array_from_buffer_3118` correctly handle errors
* `#10883 <https://github.com/numpy/numpy/pull/10883>`__: DOC: Fix negative binomial documentation.
* `#10885 <https://github.com/numpy/numpy/pull/10885>`__: TST: Re-enable test display on appveyor
* `#10890 <https://github.com/numpy/numpy/pull/10890>`__: MAINT: lstsq: compute residuals inside the ufunc
* `#10891 <https://github.com/numpy/numpy/pull/10891>`__: TST: Extract a helper function to test for reference cycles
* `#10898 <https://github.com/numpy/numpy/pull/10898>`__: ENH: Have dtype transfer for equivalent user dtypes prefer user-defined...
* `#10901 <https://github.com/numpy/numpy/pull/10901>`__: DOC, BUG : Bad link to `np.random.randint`
* `#10903 <https://github.com/numpy/numpy/pull/10903>`__: DOC: Fix link in `See Also` section of `randn` docstring.
* `#10907 <https://github.com/numpy/numpy/pull/10907>`__: TST: reactivate module docstring tests, fix float formatting
* `#10911 <https://github.com/numpy/numpy/pull/10911>`__: BUG: Fix casting between npy_half and float in einsum
* `#10916 <https://github.com/numpy/numpy/pull/10916>`__: BUG: Add missing underscore to prototype in check_embedded_lapack
* `#10919 <https://github.com/numpy/numpy/pull/10919>`__: BUG: Pass non-None outputs to `__array_prepare__` and `__array_wrap__`
* `#10921 <https://github.com/numpy/numpy/pull/10921>`__: DOC: clear up warnings, fix matplotlib plot
* `#10923 <https://github.com/numpy/numpy/pull/10923>`__: BUG: fixed dtype alignment for array of structs in case of converting...
* `#10925 <https://github.com/numpy/numpy/pull/10925>`__: DOC: Fix typos in 1.15.0 changelog
* `#10936 <https://github.com/numpy/numpy/pull/10936>`__: DOC: Fix NumpyVersion example (closes gh-10935)
* `#10938 <https://github.com/numpy/numpy/pull/10938>`__: MAINT: One step closer to vectorizing lstsq
* `#10940 <https://github.com/numpy/numpy/pull/10940>`__: DOC: fix broken links for developer documentation
* `#10943 <https://github.com/numpy/numpy/pull/10943>`__: ENH: Add a search box to the sidebar in the docs
* `#10945 <https://github.com/numpy/numpy/pull/10945>`__: MAINT: Remove references to the 2008 documentation marathon
* `#10946 <https://github.com/numpy/numpy/pull/10946>`__: BUG: 'style' arg to array2string broken in legacy mode
* `#10949 <https://github.com/numpy/numpy/pull/10949>`__: DOC: cleanup documentation, continuation of nditer PR #9998
* `#10951 <https://github.com/numpy/numpy/pull/10951>`__: BUG: it.close() disallows access to iterator, fixes #10950
* `#10953 <https://github.com/numpy/numpy/pull/10953>`__: MAINT: address extraneous shape tuple checks in descriptor.c
* `#10958 <https://github.com/numpy/numpy/pull/10958>`__: MAINT, DOC: Fix typos
* `#10967 <https://github.com/numpy/numpy/pull/10967>`__: DOC: add quantile, nanquantile to toc
* `#10970 <https://github.com/numpy/numpy/pull/10970>`__: WIP: Remove fragile use of `__array_interface__` in ctypeslib.as_array
* `#10971 <https://github.com/numpy/numpy/pull/10971>`__: MAINT: Remove workaround for gh-10891
* `#10973 <https://github.com/numpy/numpy/pull/10973>`__: DOC: advise against use of matrix.
* `#10975 <https://github.com/numpy/numpy/pull/10975>`__: MAINT: move linalg tests using matrix to matrixlib
* `#10980 <https://github.com/numpy/numpy/pull/10980>`__: DOC: link to governance, convert external link to internal
* `#10984 <https://github.com/numpy/numpy/pull/10984>`__: MAINT: Added pytest cache folder to .gitignore
* `#10985 <https://github.com/numpy/numpy/pull/10985>`__: MAINT, ENH: Move matrix_power to linalg and allow higher dimensions.
* `#10986 <https://github.com/numpy/numpy/pull/10986>`__: MAINT: move all masked array matrix tests to matrixlib.
* `#10987 <https://github.com/numpy/numpy/pull/10987>`__: DOC: Correction to docstring example (result was correct)
* `#10988 <https://github.com/numpy/numpy/pull/10988>`__: MAINT: Small tidy-ups to ufunc_object.c
* `#10991 <https://github.com/numpy/numpy/pull/10991>`__: DOC: Update genfromtxt docs to use StringIO and u-strings
* `#10996 <https://github.com/numpy/numpy/pull/10996>`__: DOC: Make doc examples using StringIO python2-3 compatible
* `#11003 <https://github.com/numpy/numpy/pull/11003>`__: DOC: work around GH isaacs/github#316 to show SVG image
* `#11005 <https://github.com/numpy/numpy/pull/11005>`__: MAINT: Misc. typos
* `#11006 <https://github.com/numpy/numpy/pull/11006>`__: TST, BUILD: add latex to circleci doc build
* `#11008 <https://github.com/numpy/numpy/pull/11008>`__: REL: Fwd port 1.14.3 changelog
* `#11009 <https://github.com/numpy/numpy/pull/11009>`__: DOC: release walkthrough updates from 1.14.3
* `#11010 <https://github.com/numpy/numpy/pull/11010>`__: Move remaining Matrix tests to matrixlib
* `#11011 <https://github.com/numpy/numpy/pull/11011>`__: MAINT: Simplify dimension-juggling in np.pad
* `#11012 <https://github.com/numpy/numpy/pull/11012>`__: MAINT: np.pad: Add helper functions for producing slices along...
* `#11018 <https://github.com/numpy/numpy/pull/11018>`__: ENH: Implement axis for generalized ufuncs.
* `#11023 <https://github.com/numpy/numpy/pull/11023>`__: BUG: np.histogramdd loses precision on its inputs, leading to...
* `#11026 <https://github.com/numpy/numpy/pull/11026>`__: MAINT: reduce code duplication in ufunc_frompyfunc
* `#11033 <https://github.com/numpy/numpy/pull/11033>`__: BUG: Fix padding with large integers
* `#11036 <https://github.com/numpy/numpy/pull/11036>`__: BUG: optimizing compilers can reorder call to npy_get_floatstatus
* `#11037 <https://github.com/numpy/numpy/pull/11037>`__: BUG: initialize value before use
* `#11038 <https://github.com/numpy/numpy/pull/11038>`__: ENH: Add `__deepcopy__` to MaskedConstant
* `#11043 <https://github.com/numpy/numpy/pull/11043>`__: BUG: reduce using SSE only warns if inside SSE loop
* `#11050 <https://github.com/numpy/numpy/pull/11050>`__: BUG: remove fast scalar power for arrays with object dtype
* `#11053 <https://github.com/numpy/numpy/pull/11053>`__: DOC: bump scipy-sphinx-theme to current version
* `#11055 <https://github.com/numpy/numpy/pull/11055>`__: DOC: Add explanation for comments=None in loadtxt.
* `#11056 <https://github.com/numpy/numpy/pull/11056>`__: MAINT: Improve performance of random permutation
* `#11057 <https://github.com/numpy/numpy/pull/11057>`__: BUG: use absolute imports in test files
* `#11066 <https://github.com/numpy/numpy/pull/11066>`__: MAINT: `distutils.system_info`: handle Accelerate like any other...
* `#11073 <https://github.com/numpy/numpy/pull/11073>`__: DOC: expand reasoning behind npy_*floatstatus_barrer()
* `#11076 <https://github.com/numpy/numpy/pull/11076>`__: BUG: Ensure `PyArray_AssignRawScalar` respects `NPY_NEEDS_INIT`
* `#11082 <https://github.com/numpy/numpy/pull/11082>`__: DOC: link to updated module docstring, not NEP
* `#11083 <https://github.com/numpy/numpy/pull/11083>`__: ENH: remove nose from travis tests
* `#11085 <https://github.com/numpy/numpy/pull/11085>`__: DOC: create label and ref, fixes broken link
* `#11086 <https://github.com/numpy/numpy/pull/11086>`__: DOC: Mention we can return unitinitialized values
* `#11089 <https://github.com/numpy/numpy/pull/11089>`__: BLD: cleanup `_configtest.o.d` during build
* `#11090 <https://github.com/numpy/numpy/pull/11090>`__: BUG: Added support for index values 27-52 in C einsum
* `#11091 <https://github.com/numpy/numpy/pull/11091>`__: BUG: Python2 doubles don't print correctly in interactive shell
* `#11094 <https://github.com/numpy/numpy/pull/11094>`__: DOC: add numpy.lib.format to docs and link to it
* `#11095 <https://github.com/numpy/numpy/pull/11095>`__: MAINT: Einsum argument parsing cleanup
* `#11097 <https://github.com/numpy/numpy/pull/11097>`__: BUG: fix datetime.timedelta->timedelta64 unit detection logic
* `#11098 <https://github.com/numpy/numpy/pull/11098>`__: ENH: Add keepdims argument for generalized ufuncs.
* `#11105 <https://github.com/numpy/numpy/pull/11105>`__: ENH: Add (put|take)_along_axis
* `#11111 <https://github.com/numpy/numpy/pull/11111>`__: BUG: fix case of ISA selector in ufunc selection
* `#11116 <https://github.com/numpy/numpy/pull/11116>`__: BUG: Typo in variable name in binary_repr
* `#11120 <https://github.com/numpy/numpy/pull/11120>`__: MAINT: remove redundant code in `MaskedArray.__new__`
* `#11122 <https://github.com/numpy/numpy/pull/11122>`__: BUG,MAINT: Ensure masked elements can be tested against nan and...
* `#11124 <https://github.com/numpy/numpy/pull/11124>`__: BUG: Ensure that fully masked arrays pass assert_array_equal.
* `#11134 <https://github.com/numpy/numpy/pull/11134>`__: DOC: Clarify tofile requirements
* `#11137 <https://github.com/numpy/numpy/pull/11137>`__: MAINT: move remaining MaskedArray matrix tests to matrixlib.
* `#11139 <https://github.com/numpy/numpy/pull/11139>`__: TST: turn some build warnings into errors
* `#11140 <https://github.com/numpy/numpy/pull/11140>`__: MAINT: Update artful to bionic for i386 testing
* `#11141 <https://github.com/numpy/numpy/pull/11141>`__: MAINT: Extract a helper function for prepending and appending
* `#11145 <https://github.com/numpy/numpy/pull/11145>`__: DOC: cleanup NEP creation
* `#11146 <https://github.com/numpy/numpy/pull/11146>`__: DOC: add a NEP to split MaskedArray into a separate package
* `#11148 <https://github.com/numpy/numpy/pull/11148>`__: TST: make build warning into an error in runtest.py
* `#11149 <https://github.com/numpy/numpy/pull/11149>`__: BUG: guessing datetime, time precedence
* `#11152 <https://github.com/numpy/numpy/pull/11152>`__: BENCH: Add basic benchmarks for numpy.pad
* `#11155 <https://github.com/numpy/numpy/pull/11155>`__: BUG: Prevent stackoverflow in conversion to datetime types
* `#11158 <https://github.com/numpy/numpy/pull/11158>`__: TST: disable gc in refcount test
* `#11159 <https://github.com/numpy/numpy/pull/11159>`__: TST: Skip ctypes dependent test that fails on Python < 2.7.7.
* `#11160 <https://github.com/numpy/numpy/pull/11160>`__: TST: windows builds now properly support floating error states
* `#11163 <https://github.com/numpy/numpy/pull/11163>`__: MAINT: Work around non-deterministic Python readdir order in...
* `#11167 <https://github.com/numpy/numpy/pull/11167>`__: MAINT: Cleanup dragon4 code in various ways
* `#11168 <https://github.com/numpy/numpy/pull/11168>`__: TST: linalg: add regression test for gh-8577
* `#11169 <https://github.com/numpy/numpy/pull/11169>`__: MAINT: add sanity-checks to be run at import time
* `#11173 <https://github.com/numpy/numpy/pull/11173>`__: MAINT: Ensure that parsing errors are passed on even in tests.
* `#11176 <https://github.com/numpy/numpy/pull/11176>`__: MAINT: avoid setting non-existing gufunc strides for keepdims=True.
* `#11177 <https://github.com/numpy/numpy/pull/11177>`__: DOC: improvement of the documentation for gufunc.
* `#11178 <https://github.com/numpy/numpy/pull/11178>`__: TST: Test dimensions/indices found from parsed gufunc signatures.
* `#11180 <https://github.com/numpy/numpy/pull/11180>`__: BUG: void dtype setup checked offset not actual pointer for alignment
* `#11182 <https://github.com/numpy/numpy/pull/11182>`__: BUG: Avoid deprecated non-tuple indexing
* `#11184 <https://github.com/numpy/numpy/pull/11184>`__: MAINT: Add bitmask helper functions
* `#11185 <https://github.com/numpy/numpy/pull/11185>`__: MAINT: Add comments to long_double detection code
* `#11186 <https://github.com/numpy/numpy/pull/11186>`__: TST: Add np.core._multiarray_tests.format_float_OSprintf_g
* `#11187 <https://github.com/numpy/numpy/pull/11187>`__: MAINT: Use the more common -1 / 0 to indicate error / success
* `#11189 <https://github.com/numpy/numpy/pull/11189>`__: NEP: Array function protocol
* `#11190 <https://github.com/numpy/numpy/pull/11190>`__: DOC: Update NEP0 to clarify that discussion should happen on...
* `#11191 <https://github.com/numpy/numpy/pull/11191>`__: MAINT: remove darwin hardcoded LDOUBLE detection
* `#11193 <https://github.com/numpy/numpy/pull/11193>`__: BUG: Fix reference count/memory leak exposed by better testing
* `#11200 <https://github.com/numpy/numpy/pull/11200>`__: BUG: Bytes delimiter/comments in genfromtxt should be decoded
* `#11209 <https://github.com/numpy/numpy/pull/11209>`__: DOC: Fix doctest formatting in `rot90()` examples
* `#11218 <https://github.com/numpy/numpy/pull/11218>`__: BUG: Fixes einsum broadcasting bug when optimize=True
* `#11222 <https://github.com/numpy/numpy/pull/11222>`__: DOC: Make reference doc nditer examples python3 friendly
* `#11223 <https://github.com/numpy/numpy/pull/11223>`__: BUG: Forcibly promote shape to uint64 in numpy.memmap.
* `#11225 <https://github.com/numpy/numpy/pull/11225>`__: DOC: add existing recfunctions documentation to output
* `#11226 <https://github.com/numpy/numpy/pull/11226>`__: MAINT: add 'rst' to nep filename, fixup urls
* `#11229 <https://github.com/numpy/numpy/pull/11229>`__: NEP: New RNG policy
* `#11231 <https://github.com/numpy/numpy/pull/11231>`__: MAINT: ensure we do not create unnecessary tuples for outputs
* `#11238 <https://github.com/numpy/numpy/pull/11238>`__: MAINT: Don't update the flags a second time
* `#11239 <https://github.com/numpy/numpy/pull/11239>`__: MAINT: Use PyArray_NewFromDescr where possible, remove unused...
* `#11240 <https://github.com/numpy/numpy/pull/11240>`__: MAINT: Remove dead code backporting py2.6 warnings
* `#11246 <https://github.com/numpy/numpy/pull/11246>`__: BUG: Set ndarray.base before `__array_finalize__`
* `#11247 <https://github.com/numpy/numpy/pull/11247>`__: MAINT/BUG: Remove out-of-band reference count in PyArray_Newshape,...
* `#11248 <https://github.com/numpy/numpy/pull/11248>`__: MAINT: Don't update the flags a second time
* `#11249 <https://github.com/numpy/numpy/pull/11249>`__: BUG: Remove errant flag meddling in .real and .imag
* `#11252 <https://github.com/numpy/numpy/pull/11252>`__: DOC: show how to generate release notes in release walkthrough
* `#11257 <https://github.com/numpy/numpy/pull/11257>`__: BUG: ensure extobj and axes have their own references.
* `#11260 <https://github.com/numpy/numpy/pull/11260>`__: MAINT: Do proper cleanup in get_ufunc_arguments.
* `#11263 <https://github.com/numpy/numpy/pull/11263>`__: DOC: Update master after NumPy 1.14.4 release.
* `#11269 <https://github.com/numpy/numpy/pull/11269>`__: BUG: Correct use of NPY_UNUSED.
* `#11273 <https://github.com/numpy/numpy/pull/11273>`__: BUG: Remove invalid read in searchsorted if needle is empty
* `#11275 <https://github.com/numpy/numpy/pull/11275>`__: TST: Do not use empty arrays in tests (unless they are not read)
* `#11277 <https://github.com/numpy/numpy/pull/11277>`__: BUG: Work around past and present PEP3118 issues in ctypes
* `#11280 <https://github.com/numpy/numpy/pull/11280>`__: DOC: make docstring of np.interp clearer
* `#11286 <https://github.com/numpy/numpy/pull/11286>`__: BUG: einsum needs to check overlap on an out argument
* `#11287 <https://github.com/numpy/numpy/pull/11287>`__: DOC: Minor documentation improvements
* `#11291 <https://github.com/numpy/numpy/pull/11291>`__: BUG: Remove extra trailing parentheses.
* `#11293 <https://github.com/numpy/numpy/pull/11293>`__: DOC: fix hierarchy of numericaltype
* `#11296 <https://github.com/numpy/numpy/pull/11296>`__: BUG: Fix segfault on failing `__array_wrap__`
* `#11298 <https://github.com/numpy/numpy/pull/11298>`__: BUG: Undo behavior change in ma.masked_values(shrink=True)
* `#11307 <https://github.com/numpy/numpy/pull/11307>`__: BUG: Fix memmap regression when shape=None
* `#11314 <https://github.com/numpy/numpy/pull/11314>`__: MAINT: remove unused "npy_import"
* `#11315 <https://github.com/numpy/numpy/pull/11315>`__: MAINT: Package `tools/allocation_tracking`
* `#11319 <https://github.com/numpy/numpy/pull/11319>`__: REL, REV: Revert f2py fixes that exposed SciPy bug.
* `#11327 <https://github.com/numpy/numpy/pull/11327>`__: DOC: Update release notes for 1.15.0.
* `#11339 <https://github.com/numpy/numpy/pull/11339>`__: BUG: decref in failure path; replace PyObject_Type by Py_TYPE
* `#11352 <https://github.com/numpy/numpy/pull/11352>`__: DEP: Actually deprecate the normed argument to histogram
* `#11359 <https://github.com/numpy/numpy/pull/11359>`__: DOC: document new functions
* `#11367 <https://github.com/numpy/numpy/pull/11367>`__: BUG: add missing NpyIter_Close in einsum
* `#11368 <https://github.com/numpy/numpy/pull/11368>`__: BUG/TST: String indexing should just fail, not emit a futurewarning
* `#11389 <https://github.com/numpy/numpy/pull/11389>`__: ENH: Remove NpyIter_Close
* `#11392 <https://github.com/numpy/numpy/pull/11392>`__: BUG: Make scalar.squeeze accept axis arg
* `#11393 <https://github.com/numpy/numpy/pull/11393>`__: REL,MAINT: Update numpyconfig.h for 1.15.
* `#11394 <https://github.com/numpy/numpy/pull/11394>`__: MAINT: Update mailmap
* `#11403 <https://github.com/numpy/numpy/pull/11403>`__: DOC: Remove npyiter close from notes
* `#11427 <https://github.com/numpy/numpy/pull/11427>`__: BUG: Fix incorrect deprecation logic for histogram(normed=...)...
* `#11489 <https://github.com/numpy/numpy/pull/11489>`__: BUG: Ensure out is returned in einsum.
* `#11491 <https://github.com/numpy/numpy/pull/11491>`__: BUG/ENH: Einsum optimization path updates and bug fixes.
* `#11493 <https://github.com/numpy/numpy/pull/11493>`__: BUG: Revert #10229 to fix DLL loads on Windows.
* `#11494 <https://github.com/numpy/numpy/pull/11494>`__: MAINT: add PyPI classifier for Python 3.7
* `#11495 <https://github.com/numpy/numpy/pull/11495>`__: BENCH: belated addition of lcm, gcd to ufunc benchmark.
* `#11496 <https://github.com/numpy/numpy/pull/11496>`__: BUG: Advanced indexing assignment incorrectly took 1-D fastpath
* `#11511 <https://github.com/numpy/numpy/pull/11511>`__: BUG: Fix #define for ppc64 and ppc64le
* `#11529 <https://github.com/numpy/numpy/pull/11529>`__: ENH: Add density argument to histogramdd.
* `#11532 <https://github.com/numpy/numpy/pull/11532>`__: BUG: Decref of field title caused segfault
* `#11540 <https://github.com/numpy/numpy/pull/11540>`__: DOC: Update the 1.15.0 release notes.
* `#11577 <https://github.com/numpy/numpy/pull/11577>`__: BLD: Modify cpu detection and printing to get working aarch64...
* `#11578 <https://github.com/numpy/numpy/pull/11578>`__: DOC: link to TESTS.rst.txt testing guidelines, tweak testing...
* `#11602 <https://github.com/numpy/numpy/pull/11602>`__: TST: Add Python 3.7 to CI testing

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Contributors
============
A total of 7 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Charles Harris
* Chris Billington
* Elliott Sales de Andrade +
* Eric Wieser
* Jeremy Manning +
* Matti Picus
* Ralf Gommers
Pull requests merged
====================
A total of 24 pull requests were merged for this release.
* `#11647 <https://github.com/numpy/numpy/pull/11647>`__: MAINT: Filter Cython warnings in ``__init__.py``
* `#11648 <https://github.com/numpy/numpy/pull/11648>`__: BUG: Fix doc source links to unwrap decorators
* `#11657 <https://github.com/numpy/numpy/pull/11657>`__: BUG: Ensure singleton dimensions are not dropped when converting...
* `#11661 <https://github.com/numpy/numpy/pull/11661>`__: BUG: Warn on Nan in minimum,maximum for scalars
* `#11665 <https://github.com/numpy/numpy/pull/11665>`__: BUG: cython sometimes emits invalid gcc attribute
* `#11682 <https://github.com/numpy/numpy/pull/11682>`__: BUG: Fix regression in void_getitem
* `#11698 <https://github.com/numpy/numpy/pull/11698>`__: BUG: Make matrix_power again work for object arrays.
* `#11700 <https://github.com/numpy/numpy/pull/11700>`__: BUG: Add missing PyErr_NoMemory after failing malloc
* `#11719 <https://github.com/numpy/numpy/pull/11719>`__: BUG: Fix undefined functions on big-endian systems.
* `#11720 <https://github.com/numpy/numpy/pull/11720>`__: MAINT: Make einsum optimize default to False.
* `#11746 <https://github.com/numpy/numpy/pull/11746>`__: BUG: Fix regression in loadtxt for bz2 text files in Python 2.
* `#11757 <https://github.com/numpy/numpy/pull/11757>`__: BUG: Revert use of `console_scripts`.
* `#11758 <https://github.com/numpy/numpy/pull/11758>`__: BUG: Fix Fortran kind detection for aarch64 & s390x.
* `#11759 <https://github.com/numpy/numpy/pull/11759>`__: BUG: Fix printing of longdouble on ppc64le.
* `#11760 <https://github.com/numpy/numpy/pull/11760>`__: BUG: Fixes for unicode field names in Python 2
* `#11761 <https://github.com/numpy/numpy/pull/11761>`__: BUG: Increase required cython version on python 3.7
* `#11763 <https://github.com/numpy/numpy/pull/11763>`__: BUG: check return value of _buffer_format_string
* `#11775 <https://github.com/numpy/numpy/pull/11775>`__: MAINT: Make assert_array_compare more generic.
* `#11776 <https://github.com/numpy/numpy/pull/11776>`__: TST: Fix urlopen stubbing.
* `#11777 <https://github.com/numpy/numpy/pull/11777>`__: BUG: Fix regression in intersect1d.
* `#11779 <https://github.com/numpy/numpy/pull/11779>`__: BUG: Fix test sensitive to platform byte order.
* `#11781 <https://github.com/numpy/numpy/pull/11781>`__: BUG: Avoid signed overflow in histogram
* `#11785 <https://github.com/numpy/numpy/pull/11785>`__: BUG: Fix pickle and memoryview for datetime64, timedelta64 scalars
* `#11786 <https://github.com/numpy/numpy/pull/11786>`__: BUG: Deprecation triggers segfault

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Contributors
============
A total of 4 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Charles Harris
* Julian Taylor
* Marten van Kerkwijk
* Matti Picus
Pull requests merged
====================
A total of 4 pull requests were merged for this release.
* `#11902 <https://github.com/numpy/numpy/pull/11902>`__: BUG: Fix matrix PendingDeprecationWarning suppression for pytest...
* `#11981 <https://github.com/numpy/numpy/pull/11981>`__: BUG: fix cached allocations without the GIL for 1.15.x
* `#11982 <https://github.com/numpy/numpy/pull/11982>`__: BUG: fix refcount leak in PyArray_AdaptFlexibleDType
* `#11992 <https://github.com/numpy/numpy/pull/11992>`__: BUG: Ensure boolean indexing of subclasses sets base correctly.

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Contributors
============
A total of 7 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Allan Haldane
* Charles Harris
* Jeroen Demeyer
* Kevin Sheppard
* Matthew Bowden +
* Matti Picus
* Tyler Reddy
Pull requests merged
====================
A total of 12 pull requests were merged for this release.
* `#12080 <https://github.com/numpy/numpy/pull/12080>`__: MAINT: Blacklist some MSVC complex functions.
* `#12083 <https://github.com/numpy/numpy/pull/12083>`__: TST: Add azure CI testing to 1.15.x branch.
* `#12084 <https://github.com/numpy/numpy/pull/12084>`__: BUG: test_path() now uses Path.resolve()
* `#12085 <https://github.com/numpy/numpy/pull/12085>`__: TST, MAINT: Fix some failing tests on azure-pipelines mac and...
* `#12187 <https://github.com/numpy/numpy/pull/12187>`__: BUG: Fix memory leak in mapping.c
* `#12188 <https://github.com/numpy/numpy/pull/12188>`__: BUG: Allow boolean subtract in histogram
* `#12189 <https://github.com/numpy/numpy/pull/12189>`__: BUG: Fix in-place permutation
* `#12190 <https://github.com/numpy/numpy/pull/12190>`__: BUG: limit default for get_num_build_jobs() to 8
* `#12191 <https://github.com/numpy/numpy/pull/12191>`__: BUG: OBJECT_to_* should check for errors
* `#12192 <https://github.com/numpy/numpy/pull/12192>`__: DOC: Prepare for NumPy 1.15.3 release.
* `#12237 <https://github.com/numpy/numpy/pull/12237>`__: BUG: Fix MaskedArray fill_value type conversion.
* `#12238 <https://github.com/numpy/numpy/pull/12238>`__: TST: Backport azure-pipeline testing fixes for Mac

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Contributors
============
A total of 4 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Charles Harris
* Matti Picus
* Sebastian Berg
* bbbbbbbbba +
Pull requests merged
====================
A total of 4 pull requests were merged for this release.
* `#12296 <https://github.com/numpy/numpy/pull/12296>`__: BUG: Dealloc cached buffer info (#12249)
* `#12297 <https://github.com/numpy/numpy/pull/12297>`__: BUG: Fix fill value in masked array '==' and '!=' ops.
* `#12307 <https://github.com/numpy/numpy/pull/12307>`__: DOC: Correct the default value of `optimize` in `numpy.einsum`
* `#12320 <https://github.com/numpy/numpy/pull/12320>`__: REL: Prepare for the NumPy 1.15.4 release

616
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Contributors
============
A total of 113 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Alan Fontenot +
* Allan Haldane
* Alon Hershenhorn +
* Alyssa Quek +
* Andreas Nussbaumer +
* Anner +
* Anthony Sottile +
* Antony Lee
* Ayappan P +
* Bas van Schaik +
* C.A.M. Gerlach +
* Charles Harris
* Chris Billington
* Christian Clauss
* Christoph Gohlke
* Christopher Pezley +
* Daniel B Allan +
* Daniel Smith
* Dawid Zych +
* Derek Kim +
* Dima Pasechnik +
* Edgar Giovanni Lepe +
* Elena Mokeeva +
* Elliott Sales de Andrade +
* Emil Hessman +
* Eric Larson
* Eric Schles +
* Eric Wieser
* Giulio Benetti +
* Guillaume Gautier +
* Guo Ci
* Heath Henley +
* Isuru Fernando +
* J. Lewis Muir +
* Jack Vreeken +
* Jaime Fernandez
* James Bourbeau
* Jeff VanOss
* Jeffrey Yancey +
* Jeremy Chen +
* Jeremy Manning +
* Jeroen Demeyer
* John Darbyshire +
* John Kirkham
* John Zwinck
* Jonas Jensen +
* Joscha Reimer +
* Juan Azcarreta +
* Julian Taylor
* Kevin Sheppard
* Krzysztof Chomski +
* Kyle Sunden
* Lars Grüter
* Lilian Besson +
* MSeifert04
* Mark Harfouche
* Marten van Kerkwijk
* Martin Thoma
* Matt Harrigan +
* Matthew Bowden +
* Matthew Brett
* Matthias Bussonnier
* Matti Picus
* Max Aifer +
* Michael Hirsch, Ph.D +
* Michael James Jamie Schnaitter +
* MichaelSaah +
* Mike Toews
* Minkyu Lee +
* Mircea Akos Bruma +
* Mircea-Akos Brumă +
* Moshe Looks +
* Muhammad Kasim +
* Nathaniel J. Smith
* Nikita Titov +
* Paul Müller +
* Paul van Mulbregt
* Pauli Virtanen
* Pierre Glaser +
* Pim de Haan
* Ralf Gommers
* Robert Kern
* Robin Aggleton +
* Rohit Pandey +
* Roman Yurchak +
* Ryan Soklaski
* Sebastian Berg
* Sho Nakamura +
* Simon Gibbons
* Stan Seibert +
* Stefan Otte
* Stefan van der Walt
* Stephan Hoyer
* Stuart Archibald
* Taylor Smith +
* Tim Felgentreff +
* Tim Swast +
* Tim Teichmann +
* Toshiki Kataoka
* Travis Oliphant
* Tyler Reddy
* Uddeshya Singh +
* Warren Weckesser
* Weitang Li +
* Wenjamin Petrenko +
* William D. Irons
* Yannick Jadoul +
* Yaroslav Halchenko
* Yug Khanna +
* Yuji Kanagawa +
* Yukun Guo +
* @ankokumoyashi +
* @lerbuke +
Pull requests merged
====================
A total of 490 pull requests were merged for this release.
* `#6256 <https://github.com/numpy/numpy/pull/6256>`__: NEP: Add proposal for oindex and vindex.
* `#6377 <https://github.com/numpy/numpy/pull/6377>`__: BUG: define "uint-alignment", fixes complex64 alignment
* `#8206 <https://github.com/numpy/numpy/pull/8206>`__: ENH: add padding options to diff
* `#8923 <https://github.com/numpy/numpy/pull/8923>`__: ENH: Add 'stone' estimator to np.histogram
* `#8955 <https://github.com/numpy/numpy/pull/8955>`__: ENH: Allow ufunc.identity to be any python object
* `#9022 <https://github.com/numpy/numpy/pull/9022>`__: BUG: don't silence `__array_wrap__` errors in `ufunc.reduce`
* `#10551 <https://github.com/numpy/numpy/pull/10551>`__: BUG: memmap close files when it shouldn't, load leaves them open...
* `#10602 <https://github.com/numpy/numpy/pull/10602>`__: MAINT: Move dtype string functions to python
* `#10704 <https://github.com/numpy/numpy/pull/10704>`__: NEP 15: Merging multiarray and umath
* `#10797 <https://github.com/numpy/numpy/pull/10797>`__: DEP: Updated `unravel_index()` to support `shape` kwarg
* `#10915 <https://github.com/numpy/numpy/pull/10915>`__: ENH: implement nep 0015: merge multiarray and umath
* `#10998 <https://github.com/numpy/numpy/pull/10998>`__: DOC: removed spurious FIXME comment in number.c
* `#11002 <https://github.com/numpy/numpy/pull/11002>`__: MAINT: add clearer message to assist users with failed builds.
* `#11016 <https://github.com/numpy/numpy/pull/11016>`__: ENH: Add AARCH32 support.
* `#11084 <https://github.com/numpy/numpy/pull/11084>`__: DOC: link to TESTS.rst.txt testing guidelines, tweak testing...
* `#11119 <https://github.com/numpy/numpy/pull/11119>`__: ENH: Chain exceptions to give better error messages for invalid...
* `#11175 <https://github.com/numpy/numpy/pull/11175>`__: ENH: Generalized ufunc signature expansion for frozen and flexible...
* `#11197 <https://github.com/numpy/numpy/pull/11197>`__: BUG/ENH: Removed non-standard scaling of the covariance matrix...
* `#11234 <https://github.com/numpy/numpy/pull/11234>`__: DOC: Update einsum docs
* `#11282 <https://github.com/numpy/numpy/pull/11282>`__: MAINT: move comparison operator special-handling out of ufunc...
* `#11297 <https://github.com/numpy/numpy/pull/11297>`__: NEP: Expansion of gufunc signatures.
* `#11299 <https://github.com/numpy/numpy/pull/11299>`__: BUG: Prevent crashes on 0-length structured void scalars
* `#11303 <https://github.com/numpy/numpy/pull/11303>`__: DOC: revision of NEP-18 (`__array_function__`)
* `#11312 <https://github.com/numpy/numpy/pull/11312>`__: WIP: DOC: slightly tweak the directions to create a release
* `#11318 <https://github.com/numpy/numpy/pull/11318>`__: REL: Setup master for 1.16 development.
* `#11323 <https://github.com/numpy/numpy/pull/11323>`__: DEP: Actually deprecate the normed argument to histogram
* `#11324 <https://github.com/numpy/numpy/pull/11324>`__: MAINT: Don't use dtype strings when the dtypes themselves can...
* `#11326 <https://github.com/numpy/numpy/pull/11326>`__: DOC: Update master after NumPy 1.14.5 release.
* `#11328 <https://github.com/numpy/numpy/pull/11328>`__: MAINT: Misc numeric cleanup
* `#11335 <https://github.com/numpy/numpy/pull/11335>`__: DOC: Change array lengths/entries in `broadcast_arrays` example...
* `#11336 <https://github.com/numpy/numpy/pull/11336>`__: BUG: decref in failure path; replace `PyObject_Type` by `Py_TYPE`
* `#11338 <https://github.com/numpy/numpy/pull/11338>`__: MAINT: Ensure ufunc override call each class only once, plus...
* `#11340 <https://github.com/numpy/numpy/pull/11340>`__: BUG: sctypeDict['f8'] randomly points to double or longdouble...
* `#11345 <https://github.com/numpy/numpy/pull/11345>`__: BUG/ENH: Einsum optimization path updates and bug fixes.
* `#11347 <https://github.com/numpy/numpy/pull/11347>`__: DOC: Silence many sphinx warnings
* `#11348 <https://github.com/numpy/numpy/pull/11348>`__: ENH: Improve support for pathlib.Path objects in load functions
* `#11349 <https://github.com/numpy/numpy/pull/11349>`__: DOC: document new functions
* `#11351 <https://github.com/numpy/numpy/pull/11351>`__: MAINT: Improve speed of ufunc kwargs parsing
* `#11353 <https://github.com/numpy/numpy/pull/11353>`__: DOC, MAINT: HTTP -> HTTPS, and other linkrot fixes
* `#11356 <https://github.com/numpy/numpy/pull/11356>`__: NEP: Update NEP 19: RNG Policy
* `#11357 <https://github.com/numpy/numpy/pull/11357>`__: MAINT: Add new `_test.c` files and `benchmarks/html` to `gitignore`
* `#11365 <https://github.com/numpy/numpy/pull/11365>`__: BUG: add missing NpyIter_Close in einsum
* `#11366 <https://github.com/numpy/numpy/pull/11366>`__: BUG/TST: String indexing should just fail, not emit a futurewarning
* `#11371 <https://github.com/numpy/numpy/pull/11371>`__: DOC: Clarify requirement that histogram bins are monotonic.
* `#11373 <https://github.com/numpy/numpy/pull/11373>`__: TST: Show that histogramdd's normed argument is histogram's density
* `#11374 <https://github.com/numpy/numpy/pull/11374>`__: WIP: additional revision for NEP-18 (`__array_function__`)
* `#11376 <https://github.com/numpy/numpy/pull/11376>`__: ENH: Remove NpyIter_Close
* `#11379 <https://github.com/numpy/numpy/pull/11379>`__: BUG: changed hardcoded axis to 0 for checking indices
* `#11382 <https://github.com/numpy/numpy/pull/11382>`__: DEP: deprecate undocumented, unused dtype type dicts
* `#11383 <https://github.com/numpy/numpy/pull/11383>`__: ENH: Allow size=0 in numpy.random.choice
* `#11385 <https://github.com/numpy/numpy/pull/11385>`__: BUG: Make scalar.squeeze accept axis arg
* `#11390 <https://github.com/numpy/numpy/pull/11390>`__: REL,MAINT: Update numpyconfig.h for 1.15.
* `#11391 <https://github.com/numpy/numpy/pull/11391>`__: MAINT: Update mailmap
* `#11396 <https://github.com/numpy/numpy/pull/11396>`__: TST: Added regression test for #11395
* `#11405 <https://github.com/numpy/numpy/pull/11405>`__: BUG: Ensure comparisons on scalar strings pass without warning.
* `#11406 <https://github.com/numpy/numpy/pull/11406>`__: BUG: Ensure out is returned in einsum.
* `#11409 <https://github.com/numpy/numpy/pull/11409>`__: DOC: Update testing section of README.
* `#11414 <https://github.com/numpy/numpy/pull/11414>`__: DOC: major revision of NEP 21, advanced indexing
* `#11422 <https://github.com/numpy/numpy/pull/11422>`__: BENCH: Add benchmarks for np.loadtxt reading from CSV format...
* `#11424 <https://github.com/numpy/numpy/pull/11424>`__: ENH: Allow use of svd on empty arrays
* `#11425 <https://github.com/numpy/numpy/pull/11425>`__: DOC: Clear up confusion between np.where(cond) and np.where(cond,...
* `#11428 <https://github.com/numpy/numpy/pull/11428>`__: BUG: Fix incorrect deprecation logic for histogram(normed=...)...
* `#11429 <https://github.com/numpy/numpy/pull/11429>`__: NEP: accept NEP 20 partially (frozen, flexible, but not broadcastable...
* `#11432 <https://github.com/numpy/numpy/pull/11432>`__: MAINT: Refactor differences between cblas_matrixproduct and PyArray_MatrixProduct2
* `#11434 <https://github.com/numpy/numpy/pull/11434>`__: MAINT: add PyPI classifier for Python 3.7
* `#11436 <https://github.com/numpy/numpy/pull/11436>`__: DOC: Document average return type
* `#11440 <https://github.com/numpy/numpy/pull/11440>`__: BUG: fix interpolation with inf and NaN present
* `#11444 <https://github.com/numpy/numpy/pull/11444>`__: DOC: Fix documentation for fromfunction
* `#11449 <https://github.com/numpy/numpy/pull/11449>`__: BUG: Revert #10229 to fix DLL loads on Windows.
* `#11450 <https://github.com/numpy/numpy/pull/11450>`__: MAINT/DEP: properly implement `ndarray.__pos__`
* `#11453 <https://github.com/numpy/numpy/pull/11453>`__: BENCH: add ufunc argument parsing benchmarks.
* `#11455 <https://github.com/numpy/numpy/pull/11455>`__: BENCH: belated addition of lcm, gcd to ufunc benchmark.
* `#11459 <https://github.com/numpy/numpy/pull/11459>`__: NEP: Add some text to NEP 0 to clarify how a NEP is accepted
* `#11461 <https://github.com/numpy/numpy/pull/11461>`__: MAINT: Add discussion link to NEP 15
* `#11462 <https://github.com/numpy/numpy/pull/11462>`__: Add NEP 22, a high level overview for the duck array work
* `#11463 <https://github.com/numpy/numpy/pull/11463>`__: MAINT: Produce a more readable repr of argument packs in benchmark
* `#11464 <https://github.com/numpy/numpy/pull/11464>`__: BUG: Don't convert inputs to `np.float64` in digitize
* `#11468 <https://github.com/numpy/numpy/pull/11468>`__: BUG: Advanced indexing assignment incorrectly took 1-D fastpath
* `#11470 <https://github.com/numpy/numpy/pull/11470>`__: BLD: Don't leave the build task running if runtests.py is interrupted
* `#11471 <https://github.com/numpy/numpy/pull/11471>`__: MAINT: Remove python-side docstrings from add_newdocs.
* `#11472 <https://github.com/numpy/numpy/pull/11472>`__: DOC: include NEP number on each NEP page
* `#11473 <https://github.com/numpy/numpy/pull/11473>`__: MAINT: Move pytesttester outside of np.testing, to avoid creating...
* `#11474 <https://github.com/numpy/numpy/pull/11474>`__: MAINT: Move add_newdocs into core, since it only adds docs to...
* `#11479 <https://github.com/numpy/numpy/pull/11479>`__: BUG: Fix #define for ppc64 and ppc64le
* `#11480 <https://github.com/numpy/numpy/pull/11480>`__: MAINT: move ufunc override code to umath and multiarray as much...
* `#11482 <https://github.com/numpy/numpy/pull/11482>`__: DOC: Include warning in np.resize() docs
* `#11484 <https://github.com/numpy/numpy/pull/11484>`__: BUG: Increase required cython version on python 3.7
* `#11487 <https://github.com/numpy/numpy/pull/11487>`__: DOC: extend sanity check message
* `#11488 <https://github.com/numpy/numpy/pull/11488>`__: NEP: clarify bugfix policy for legacy RandomState.
* `#11501 <https://github.com/numpy/numpy/pull/11501>`__: MAINT: Tidy cython invocation
* `#11503 <https://github.com/numpy/numpy/pull/11503>`__: MAINT: improve error message for isposinf and isneginf on complex...
* `#11512 <https://github.com/numpy/numpy/pull/11512>`__: DOC: Add templates for issues and PRs
* `#11514 <https://github.com/numpy/numpy/pull/11514>`__: Prefer the same-python cython to the on-PATH cython
* `#11515 <https://github.com/numpy/numpy/pull/11515>`__: BUG: decref of field title caused segfault
* `#11518 <https://github.com/numpy/numpy/pull/11518>`__: MAINT: Speed up normalize_axis_tuple by about 30%
* `#11522 <https://github.com/numpy/numpy/pull/11522>`__: BUG: fix np.load() of empty .npz file
* `#11525 <https://github.com/numpy/numpy/pull/11525>`__: MAINT: Append `*FLAGS` instead of overriding
* `#11526 <https://github.com/numpy/numpy/pull/11526>`__: ENH: add multi-field assignment helpers in np.lib.recfunctions
* `#11527 <https://github.com/numpy/numpy/pull/11527>`__: DOC: Note that method is the polar form of Box-Muller.
* `#11528 <https://github.com/numpy/numpy/pull/11528>`__: ENH: Add support for ipython latex printing to polynomial
* `#11531 <https://github.com/numpy/numpy/pull/11531>`__: ENH: Add density argument to histogramdd.
* `#11533 <https://github.com/numpy/numpy/pull/11533>`__: DOC: Fixed example code for cheb2poly and poly2cheb (see #11519)
* `#11534 <https://github.com/numpy/numpy/pull/11534>`__: DOC: Minor improvements to np.concatenate docstring
* `#11535 <https://github.com/numpy/numpy/pull/11535>`__: MAINT: Improve memory usage in PEP3118 format parsing
* `#11553 <https://github.com/numpy/numpy/pull/11553>`__: DOC: Tiny typo on numpy/reference/arrays.dtypes.html
* `#11556 <https://github.com/numpy/numpy/pull/11556>`__: BUG: Make assert_string_equal check str equality simply without...
* `#11559 <https://github.com/numpy/numpy/pull/11559>`__: NEP: accept nep 0015
* `#11560 <https://github.com/numpy/numpy/pull/11560>`__: NEP: accept nep 0019
* `#11562 <https://github.com/numpy/numpy/pull/11562>`__: DOC: update release notes for LDFLAGS append behavior (gh-11525).
* `#11565 <https://github.com/numpy/numpy/pull/11565>`__: MAINT: convert the doctests for polynomial to regular tests
* `#11566 <https://github.com/numpy/numpy/pull/11566>`__: BLD: Do not use gcc warnings flags when 'gcc' is actually clang.
* `#11567 <https://github.com/numpy/numpy/pull/11567>`__: TST: Integrate codecov testing
* `#11568 <https://github.com/numpy/numpy/pull/11568>`__: BLD: Modify cpu detection and printing to get working aarch64...
* `#11571 <https://github.com/numpy/numpy/pull/11571>`__: DOC: Updated array2string description
* `#11572 <https://github.com/numpy/numpy/pull/11572>`__: DOC: Updated Slice Description
* `#11573 <https://github.com/numpy/numpy/pull/11573>`__: TST: add broadcast_arrays() kwarg unit test for TypeError
* `#11580 <https://github.com/numpy/numpy/pull/11580>`__: MAINT: refactor ufunc iter operand flags handling
* `#11591 <https://github.com/numpy/numpy/pull/11591>`__: MAINT: update runtests.py node id example for pytest usage
* `#11592 <https://github.com/numpy/numpy/pull/11592>`__: DOC: add Stefan van der Walt to Steering Council
* `#11593 <https://github.com/numpy/numpy/pull/11593>`__: ENH: handle empty matrices in qr decomposition
* `#11594 <https://github.com/numpy/numpy/pull/11594>`__: ENH: support for empty matrices in linalg.lstsq
* `#11595 <https://github.com/numpy/numpy/pull/11595>`__: BUG:warn on Nan in minimum,maximum for scalars, float16
* `#11596 <https://github.com/numpy/numpy/pull/11596>`__: NEP: backwards compatibility and deprecation policy
* `#11598 <https://github.com/numpy/numpy/pull/11598>`__: TST: Add Python 3.7 to CI testing
* `#11601 <https://github.com/numpy/numpy/pull/11601>`__: BUG: Make np.array([[1], 2]) and np.array([1, [2]]) behave in...
* `#11606 <https://github.com/numpy/numpy/pull/11606>`__: DOC: Post 1.15.0 release updates for master.
* `#11607 <https://github.com/numpy/numpy/pull/11607>`__: DOC: minor clarification and typo fix to NEP 21 (outer indexing).
* `#11610 <https://github.com/numpy/numpy/pull/11610>`__: TST: including C source line coverage for CI / codecov
* `#11611 <https://github.com/numpy/numpy/pull/11611>`__: NEP: Add roadmap section and subdocuments to NEPs
* `#11613 <https://github.com/numpy/numpy/pull/11613>`__: BUG: have geometric() raise ValueError on p=0
* `#11615 <https://github.com/numpy/numpy/pull/11615>`__: BUG: Clip uses wrong memory order in output
* `#11616 <https://github.com/numpy/numpy/pull/11616>`__: DOC: add a brief note on "Protocols for methods" to NEP 18
* `#11621 <https://github.com/numpy/numpy/pull/11621>`__: DOC: Use "real symmetric" rather than "symmetric" in ``eigh``...
* `#11626 <https://github.com/numpy/numpy/pull/11626>`__: DOC: Show plot in meshgrid example.
* `#11630 <https://github.com/numpy/numpy/pull/11630>`__: DOC: Include the versionadded to the isnat documentation.
* `#11634 <https://github.com/numpy/numpy/pull/11634>`__: MAINT: Filter Cython warnings in `__init__.py`
* `#11637 <https://github.com/numpy/numpy/pull/11637>`__: ENH: np.angle: Remove unnecessary multiplication, and allow subclasses...
* `#11638 <https://github.com/numpy/numpy/pull/11638>`__: ENH: Make expand_dims work on subclasses
* `#11642 <https://github.com/numpy/numpy/pull/11642>`__: BUG: Fixes for unicode field names in Python 2
* `#11643 <https://github.com/numpy/numpy/pull/11643>`__: DOC: Insert up to date link to Spyder website in Dev Env doc...
* `#11644 <https://github.com/numpy/numpy/pull/11644>`__: BUG: Fix doc source links to unwrap decorators
* `#11652 <https://github.com/numpy/numpy/pull/11652>`__: BUG: Ensure singleton dimensions are not dropped when converting...
* `#11660 <https://github.com/numpy/numpy/pull/11660>`__: ENH: Add Nan warnings for maximum, minimum on more dtypes
* `#11669 <https://github.com/numpy/numpy/pull/11669>`__: BUG: Fix regression in `void_getitem`
* `#11670 <https://github.com/numpy/numpy/pull/11670>`__: MAINT: trivially refactor mapped indexing
* `#11673 <https://github.com/numpy/numpy/pull/11673>`__: DOC: Add geomspace to "See also" of linspace
* `#11679 <https://github.com/numpy/numpy/pull/11679>`__: TST: ignore setup.py files for codecov reports
* `#11688 <https://github.com/numpy/numpy/pull/11688>`__: DOC: Update broadcasting doc with current exception details
* `#11691 <https://github.com/numpy/numpy/pull/11691>`__: BUG: Make matrix_power again work for object arrays.
* `#11692 <https://github.com/numpy/numpy/pull/11692>`__: MAINT: Remove duplicate code.
* `#11693 <https://github.com/numpy/numpy/pull/11693>`__: NEP: Mark NEP 18 as accepted
* `#11694 <https://github.com/numpy/numpy/pull/11694>`__: BUG: Fix pickle and memoryview for datetime64, timedelta64 scalars
* `#11695 <https://github.com/numpy/numpy/pull/11695>`__: BUG: Add missing PyErr_NoMemory after failing malloc
* `#11703 <https://github.com/numpy/numpy/pull/11703>`__: MAINT: Remove np.pkgload, which seems to be unusable anyway
* `#11708 <https://github.com/numpy/numpy/pull/11708>`__: BUG: Fix regression in np.loadtxt for bz2 text files in Python...
* `#11710 <https://github.com/numpy/numpy/pull/11710>`__: BUG: Check for compiler used in env['CC'], then config_vars['CC']
* `#11711 <https://github.com/numpy/numpy/pull/11711>`__: BUG: Fix undefined functions on big-endian systems.
* `#11715 <https://github.com/numpy/numpy/pull/11715>`__: TST: Fix urlopen stubbing.
* `#11717 <https://github.com/numpy/numpy/pull/11717>`__: MAINT: Make einsum optimize default to False.
* `#11718 <https://github.com/numpy/numpy/pull/11718>`__: BUG: Revert use of `console_scripts`.
* `#11722 <https://github.com/numpy/numpy/pull/11722>`__: MAINT: Remove duplicate docstring and correct location of `__all__`...
* `#11725 <https://github.com/numpy/numpy/pull/11725>`__: BUG: Fix Fortran kind detection for aarch64 & s390x.
* `#11727 <https://github.com/numpy/numpy/pull/11727>`__: BUG: Fix printing of longdouble on ppc64le.
* `#11729 <https://github.com/numpy/numpy/pull/11729>`__: DOC: fix capitalization of kilojoules
* `#11731 <https://github.com/numpy/numpy/pull/11731>`__: DOC: fix typo in vectorize docstring
* `#11733 <https://github.com/numpy/numpy/pull/11733>`__: DOC: recommend polynomial.Polynomial over np.polyfit
* `#11735 <https://github.com/numpy/numpy/pull/11735>`__: BUG: Fix test sensitive to platform byte order.
* `#11738 <https://github.com/numpy/numpy/pull/11738>`__: TST, MAINT: add lgtm.yml to tweak LGTM.com analysis
* `#11739 <https://github.com/numpy/numpy/pull/11739>`__: BUG: disallow setting flag to writeable after fromstring, frombuffer
* `#11740 <https://github.com/numpy/numpy/pull/11740>`__: BUG: Deprecation triggers segfault
* `#11742 <https://github.com/numpy/numpy/pull/11742>`__: DOC: Reduce warnings and cleanup redundant c-api documentation
* `#11745 <https://github.com/numpy/numpy/pull/11745>`__: DOC: Small docstring fixes for old polyfit.
* `#11754 <https://github.com/numpy/numpy/pull/11754>`__: BUG: check return value of `_buffer_format_string`
* `#11755 <https://github.com/numpy/numpy/pull/11755>`__: MAINT: Fix typos in random.hypergeometric's notes
* `#11756 <https://github.com/numpy/numpy/pull/11756>`__: MAINT: Make assert_array_compare more generic.
* `#11765 <https://github.com/numpy/numpy/pull/11765>`__: DOC: Move documentation from `help(ndarray.ctypes)` to `help(some_array.ctypes)`
* `#11771 <https://github.com/numpy/numpy/pull/11771>`__: BUG: Make `random.shuffle` work on 1-D instances of `ndarray`...
* `#11774 <https://github.com/numpy/numpy/pull/11774>`__: BUG: Fix regression in intersect1d.
* `#11778 <https://github.com/numpy/numpy/pull/11778>`__: BUG: Avoid signed overflow in histogram
* `#11783 <https://github.com/numpy/numpy/pull/11783>`__: MAINT: check `_append_char` return value
* `#11784 <https://github.com/numpy/numpy/pull/11784>`__: MAINT: reformat line spacing before test methods
* `#11797 <https://github.com/numpy/numpy/pull/11797>`__: DOC: Update docs after 1.15.1 release.
* `#11800 <https://github.com/numpy/numpy/pull/11800>`__: DOC: document use when f2py is not in the PATH
* `#11802 <https://github.com/numpy/numpy/pull/11802>`__: ENH: Use entry_points to install the f2py scripts.
* `#11805 <https://github.com/numpy/numpy/pull/11805>`__: BUG: add type cast check for ediff1d
* `#11806 <https://github.com/numpy/numpy/pull/11806>`__: DOC: Polybase augmented assignment notes
* `#11812 <https://github.com/numpy/numpy/pull/11812>`__: DOC: edit setup.py docstring that is displayed on PyPI.
* `#11813 <https://github.com/numpy/numpy/pull/11813>`__: BUG: fix array_split incorrect behavior with array size bigger...
* `#11814 <https://github.com/numpy/numpy/pull/11814>`__: DOC, MAINT: Fixes for errstate() and README.md documentation.
* `#11817 <https://github.com/numpy/numpy/pull/11817>`__: DOC: add examples and extend existing dos for polynomial subclasses
* `#11818 <https://github.com/numpy/numpy/pull/11818>`__: TST: add missing tests for all polynomial subclass pow fns.
* `#11823 <https://github.com/numpy/numpy/pull/11823>`__: TST: add test for array2string unexpected kwarg
* `#11830 <https://github.com/numpy/numpy/pull/11830>`__: MAINT: reduce void type repr code duplication
* `#11834 <https://github.com/numpy/numpy/pull/11834>`__: MAINT, DOC: Replace 'an' by 'a' in some docstrings.
* `#11837 <https://github.com/numpy/numpy/pull/11837>`__: DOC: Make clear the connection between numpy types and C types
* `#11840 <https://github.com/numpy/numpy/pull/11840>`__: BUG: Let 0-D arrays of Python timedelta convert to np.timedelta64.
* `#11843 <https://github.com/numpy/numpy/pull/11843>`__: MAINT: remove surviving, unused, list comprehension
* `#11849 <https://github.com/numpy/numpy/pull/11849>`__: TST: reorder duplicate mem_overlap.c compile
* `#11850 <https://github.com/numpy/numpy/pull/11850>`__: DOC: add comment to remove fn after python 2 support is dropped
* `#11852 <https://github.com/numpy/numpy/pull/11852>`__: BUG: timedelta64 now accepts NumPy ints
* `#11858 <https://github.com/numpy/numpy/pull/11858>`__: DOC: add docstrings for numeric types
* `#11862 <https://github.com/numpy/numpy/pull/11862>`__: BUG: Re-add `_ones_like` to numpy.core.umath.
* `#11864 <https://github.com/numpy/numpy/pull/11864>`__: TST: Update travis testing to use latest virtualenv.
* `#11865 <https://github.com/numpy/numpy/pull/11865>`__: DOC: add a Code of Conduct document.
* `#11866 <https://github.com/numpy/numpy/pull/11866>`__: TST: Drop Python 3.4 testing
* `#11868 <https://github.com/numpy/numpy/pull/11868>`__: MAINT: include benchmarks, complete docs, dev tool files in sdist.
* `#11870 <https://github.com/numpy/numpy/pull/11870>`__: MAINT: dtype(unicode) should raise TypeError on failure
* `#11874 <https://github.com/numpy/numpy/pull/11874>`__: BENCH: split out slow setup method in bench_shape_base.Block
* `#11877 <https://github.com/numpy/numpy/pull/11877>`__: BUG: Fix memory leak in pyfragments.swg
* `#11880 <https://github.com/numpy/numpy/pull/11880>`__: BUG: The multiarray/ufunc merge broke old wheels.
* `#11882 <https://github.com/numpy/numpy/pull/11882>`__: DOC: Recommend the use of `np.ndim` over `np.isscalar`, and explain...
* `#11889 <https://github.com/numpy/numpy/pull/11889>`__: BENCH: Split bench_function_base.Sort into Sort and SortWorst.
* `#11891 <https://github.com/numpy/numpy/pull/11891>`__: MAINT: remove exec_command() from build_ext
* `#11892 <https://github.com/numpy/numpy/pull/11892>`__: TST: Parametrize PEP3118 scalar tests.
* `#11893 <https://github.com/numpy/numpy/pull/11893>`__: TST: Fix duplicated test name.
* `#11894 <https://github.com/numpy/numpy/pull/11894>`__: TST: Parametrize f2py tests.
* `#11895 <https://github.com/numpy/numpy/pull/11895>`__: TST: Parametrize some linalg tests over types.
* `#11896 <https://github.com/numpy/numpy/pull/11896>`__: BUG: Fix matrix PendingDeprecationWarning suppression for pytest...
* `#11898 <https://github.com/numpy/numpy/pull/11898>`__: MAINT: remove exec_command usage from ccompiler.py
* `#11899 <https://github.com/numpy/numpy/pull/11899>`__: MAINT: remove exec_command from system_info.py
* `#11900 <https://github.com/numpy/numpy/pull/11900>`__: MAINT: remove exec_command from gnu.py
* `#11901 <https://github.com/numpy/numpy/pull/11901>`__: MAINT: remove exec_command usage in ibm.py
* `#11904 <https://github.com/numpy/numpy/pull/11904>`__: Use pytest for some already-parametrized core tests
* `#11905 <https://github.com/numpy/numpy/pull/11905>`__: TST: Start testing with "-std=c99" on travisCI.
* `#11906 <https://github.com/numpy/numpy/pull/11906>`__: TST: add shippable ARMv8 to CI
* `#11907 <https://github.com/numpy/numpy/pull/11907>`__: Link HOWTO_DOCUMENT to specific section on docstrings
* `#11909 <https://github.com/numpy/numpy/pull/11909>`__: MAINT: flake8 cleanups
* `#11910 <https://github.com/numpy/numpy/pull/11910>`__: MAINT: test, refactor design of recursive closures
* `#11912 <https://github.com/numpy/numpy/pull/11912>`__: DOC: dtype offset and itemsize is limited by range of C int
* `#11914 <https://github.com/numpy/numpy/pull/11914>`__: DOC: Clarify difference between PySequence_GETITEM, PyArray_GETITEM
* `#11916 <https://github.com/numpy/numpy/pull/11916>`__: DEP: deprecate np.set_numeric_ops and friends
* `#11920 <https://github.com/numpy/numpy/pull/11920>`__: TST: Fix 'def' test_numerictypes.py::TestSctypeDict to 'class'...
* `#11921 <https://github.com/numpy/numpy/pull/11921>`__: MAINT: Don't rely on `__name__` in bitname - use the information...
* `#11922 <https://github.com/numpy/numpy/pull/11922>`__: TST: Add tests for maximum_sctype
* `#11929 <https://github.com/numpy/numpy/pull/11929>`__: DOC: #defining -> #define / Added a short explanation for Numeric
* `#11930 <https://github.com/numpy/numpy/pull/11930>`__: DOC: fix scipy-sphinx-theme license path
* `#11932 <https://github.com/numpy/numpy/pull/11932>`__: MAINT: Move `np.dtype.name.__get__` to python
* `#11933 <https://github.com/numpy/numpy/pull/11933>`__: TST: Fix unit tests that used to call unittest.TestCase.fail
* `#11934 <https://github.com/numpy/numpy/pull/11934>`__: NEP: Revert "NEP: Mark NEP 18 as accepted"
* `#11935 <https://github.com/numpy/numpy/pull/11935>`__: MAINT: remove usage of exec_command in config.py
* `#11937 <https://github.com/numpy/numpy/pull/11937>`__: MAINT: remove exec_command() from f2py init
* `#11941 <https://github.com/numpy/numpy/pull/11941>`__: BUG: Ensure einsum(optimize=True) dispatches tensordot deterministically
* `#11943 <https://github.com/numpy/numpy/pull/11943>`__: DOC: Add warning/clarification about backwards compat in NEP-18
* `#11948 <https://github.com/numpy/numpy/pull/11948>`__: DEP: finish making all comparisons to NaT false
* `#11949 <https://github.com/numpy/numpy/pull/11949>`__: MAINT: Small tidy-ups to `np.core._dtype`
* `#11950 <https://github.com/numpy/numpy/pull/11950>`__: MAINT: Extract tangential improvements made in #11175
* `#11952 <https://github.com/numpy/numpy/pull/11952>`__: MAINT: test NPY_INTERNAL_BUILD only if defined
* `#11953 <https://github.com/numpy/numpy/pull/11953>`__: TST: codecov.yml improvements
* `#11957 <https://github.com/numpy/numpy/pull/11957>`__: ENH: mark that large allocations can use huge pages
* `#11958 <https://github.com/numpy/numpy/pull/11958>`__: TST: Add a test for np.pad where constant_values is an object
* `#11959 <https://github.com/numpy/numpy/pull/11959>`__: MAINT: Explicitely cause pagefaults to happen before starting...
* `#11961 <https://github.com/numpy/numpy/pull/11961>`__: TST: Add more tests for np.pad
* `#11962 <https://github.com/numpy/numpy/pull/11962>`__: ENH: maximum lines of content to be read from numpy.loadtxt
* `#11965 <https://github.com/numpy/numpy/pull/11965>`__: BENCH: Add a benchmark comparing block to copy in the 3D case
* `#11966 <https://github.com/numpy/numpy/pull/11966>`__: MAINT: Rewrite shape normalization in pad function
* `#11967 <https://github.com/numpy/numpy/pull/11967>`__: BUG: fix refcount leak in PyArray_AdaptFlexibleDType
* `#11971 <https://github.com/numpy/numpy/pull/11971>`__: MAINT: Block algorithm with a single copy per call to `block`
* `#11973 <https://github.com/numpy/numpy/pull/11973>`__: BUG: fix cached allocations without the GIL
* `#11976 <https://github.com/numpy/numpy/pull/11976>`__: MAINT/DOC: Show the location of an empty list in np.block
* `#11979 <https://github.com/numpy/numpy/pull/11979>`__: MAINT: Ensure that a copy of the array is returned when calling...
* `#11989 <https://github.com/numpy/numpy/pull/11989>`__: BUG: Ensure boolean indexing of subclasses sets base correctly.
* `#11991 <https://github.com/numpy/numpy/pull/11991>`__: MAINT: speed up `_block` by avoiding a recursive closure
* `#11996 <https://github.com/numpy/numpy/pull/11996>`__: TST: Parametrize and break apart dtype tests
* `#11997 <https://github.com/numpy/numpy/pull/11997>`__: MAINT: Extract string helpers to a new private file
* `#12002 <https://github.com/numpy/numpy/pull/12002>`__: Revert "NEP: Revert "NEP: Mark NEP 18 as accepted""
* `#12004 <https://github.com/numpy/numpy/pull/12004>`__: BUG: Fix f2py compile function testing.
* `#12005 <https://github.com/numpy/numpy/pull/12005>`__: ENH: initial implementation of core `__array_function__` machinery
* `#12008 <https://github.com/numpy/numpy/pull/12008>`__: MAINT: Reassociate `np.cast` with the comment describing it
* `#12009 <https://github.com/numpy/numpy/pull/12009>`__: MAINT: Eliminate the private `numerictypes._typestr`
* `#12011 <https://github.com/numpy/numpy/pull/12011>`__: ENH: implementation of array_reduce_ex
* `#12012 <https://github.com/numpy/numpy/pull/12012>`__: MAINT: Extract the crazy number of type aliases to their own...
* `#12014 <https://github.com/numpy/numpy/pull/12014>`__: TST: prefer pytest.skip() over SkipTest
* `#12015 <https://github.com/numpy/numpy/pull/12015>`__: TST: improve warnings parallel test safety
* `#12017 <https://github.com/numpy/numpy/pull/12017>`__: NEP: add 3 missing data NEPs rescued from 2011-2012
* `#12018 <https://github.com/numpy/numpy/pull/12018>`__: MAINT: Simplify parts of `_type_aliases`
* `#12019 <https://github.com/numpy/numpy/pull/12019>`__: DOC: MAINT: address comments @eric-wieser on NEP 24-26 PR.
* `#12020 <https://github.com/numpy/numpy/pull/12020>`__: TST: Add tests for np.sctype2char
* `#12021 <https://github.com/numpy/numpy/pull/12021>`__: DOC: Post NumPy 1.15.2 release updates.[ci skip]
* `#12024 <https://github.com/numpy/numpy/pull/12024>`__: MAINT: Normalize axes the normal way in fftpack.py
* `#12027 <https://github.com/numpy/numpy/pull/12027>`__: DOC: Add docstrings for abstract types in scalar type hierarchy
* `#12030 <https://github.com/numpy/numpy/pull/12030>`__: DOC: use "import numpy as np" style
* `#12032 <https://github.com/numpy/numpy/pull/12032>`__: BUG: check return value from PyArray_PromoteTypes
* `#12033 <https://github.com/numpy/numpy/pull/12033>`__: TST: Mark check for f2py script xfail.
* `#12034 <https://github.com/numpy/numpy/pull/12034>`__: MAINT: Add version deprecated to some deprecation messages.
* `#12035 <https://github.com/numpy/numpy/pull/12035>`__: BUG: Fix memory leak in PY3K buffer code.
* `#12041 <https://github.com/numpy/numpy/pull/12041>`__: MAINT: remove duplicate imports
* `#12042 <https://github.com/numpy/numpy/pull/12042>`__: MAINT: cleanup and better document core/overrides.py
* `#12045 <https://github.com/numpy/numpy/pull/12045>`__: BUG: fix memory leak of buffer format string
* `#12048 <https://github.com/numpy/numpy/pull/12048>`__: BLD: pin sphinx to 1.7.9
* `#12051 <https://github.com/numpy/numpy/pull/12051>`__: TST: add macos azure testing to CI
* `#12054 <https://github.com/numpy/numpy/pull/12054>`__: MAINT: avoid modifying mutable default values
* `#12056 <https://github.com/numpy/numpy/pull/12056>`__: MAINT: The crackfortran function is called with an extra argument
* `#12057 <https://github.com/numpy/numpy/pull/12057>`__: MAINT: remove unused imports
* `#12058 <https://github.com/numpy/numpy/pull/12058>`__: MAINT: remove redundant assignment
* `#12060 <https://github.com/numpy/numpy/pull/12060>`__: MAINT: remove unused stdlib imports
* `#12061 <https://github.com/numpy/numpy/pull/12061>`__: MAINT: remove redundant imports
* `#12062 <https://github.com/numpy/numpy/pull/12062>`__: BUG: `OBJECT_to_*` should check for errors
* `#12064 <https://github.com/numpy/numpy/pull/12064>`__: MAINT: delay initialization of getlimits (circular imports)
* `#12072 <https://github.com/numpy/numpy/pull/12072>`__: BUG: test_path() now uses Path.resolve()
* `#12073 <https://github.com/numpy/numpy/pull/12073>`__: MAINT Avoid some memory copies in numpy.polynomial.hermite
* `#12079 <https://github.com/numpy/numpy/pull/12079>`__: MAINT: Blacklist some MSVC complex functions.
* `#12081 <https://github.com/numpy/numpy/pull/12081>`__: TST: add Windows test matrix to Azure CI
* `#12082 <https://github.com/numpy/numpy/pull/12082>`__: TST: Add Python 3.5 to Azure windows CI.
* `#12088 <https://github.com/numpy/numpy/pull/12088>`__: BUG: limit default for get_num_build_jobs() to 8
* `#12089 <https://github.com/numpy/numpy/pull/12089>`__: BUG: Fix in-place permutation
* `#12090 <https://github.com/numpy/numpy/pull/12090>`__: TST, MAINT: Update pickling tests by making them loop over all...
* `#12091 <https://github.com/numpy/numpy/pull/12091>`__: TST: Install pickle5 for CI testing with python 3.6/7
* `#12093 <https://github.com/numpy/numpy/pull/12093>`__: Provide information about what kind is actually not integer kind
* `#12099 <https://github.com/numpy/numpy/pull/12099>`__: ENH: Validate dispatcher functions in array_function_dispatch
* `#12102 <https://github.com/numpy/numpy/pull/12102>`__: TST: improve coverage of nd_grid
* `#12103 <https://github.com/numpy/numpy/pull/12103>`__: MAINT: Add azure-pipeline status badge to README.md
* `#12106 <https://github.com/numpy/numpy/pull/12106>`__: TST, MAINT: Skip some f2py tests on Mac.
* `#12108 <https://github.com/numpy/numpy/pull/12108>`__: BUG: Allow boolean subtract in histogram
* `#12109 <https://github.com/numpy/numpy/pull/12109>`__: TST: add unit test for issctype
* `#12112 <https://github.com/numpy/numpy/pull/12112>`__: ENH: check getfield arguments to prevent invalid memory access
* `#12115 <https://github.com/numpy/numpy/pull/12115>`__: ENH: `__array_function__` support for most of `numpy.core`
* `#12116 <https://github.com/numpy/numpy/pull/12116>`__: ENH: `__array_function__` support for `np.lib`, part 1/2
* `#12117 <https://github.com/numpy/numpy/pull/12117>`__: ENH: `__array_function__` support for `np.fft` and `np.linalg`
* `#12119 <https://github.com/numpy/numpy/pull/12119>`__: ENH: `__array_function__` support for `np.lib`, part 2/2
* `#12120 <https://github.com/numpy/numpy/pull/12120>`__: ENH: add timedelta modulus operator support (mm)
* `#12121 <https://github.com/numpy/numpy/pull/12121>`__: MAINT: Clarify the error message for resize failure
* `#12123 <https://github.com/numpy/numpy/pull/12123>`__: DEP: deprecate asscalar
* `#12124 <https://github.com/numpy/numpy/pull/12124>`__: BUG: refactor float error status to support Alpine linux
* `#12125 <https://github.com/numpy/numpy/pull/12125>`__: TST: expand cases in test_issctype()
* `#12127 <https://github.com/numpy/numpy/pull/12127>`__: BUG: Fix memory leak in mapping.c
* `#12131 <https://github.com/numpy/numpy/pull/12131>`__: BUG: fix PyDataType_ISBOOL
* `#12133 <https://github.com/numpy/numpy/pull/12133>`__: MAINT, TST refactor pickle imports and tests
* `#12134 <https://github.com/numpy/numpy/pull/12134>`__: DOC: Remove duplicated sentence in numpy.multiply
* `#12137 <https://github.com/numpy/numpy/pull/12137>`__: TST: error tests for fill_diagonal()
* `#12138 <https://github.com/numpy/numpy/pull/12138>`__: TST: error tests for diag_indices_from()
* `#12140 <https://github.com/numpy/numpy/pull/12140>`__: DOC: fixups for NEP-18 based on the implementation
* `#12141 <https://github.com/numpy/numpy/pull/12141>`__: DOC: minor tweak to CoC (update NumFOCUS contact address).
* `#12145 <https://github.com/numpy/numpy/pull/12145>`__: MAINT: Update ndarrayobject.h `__cplusplus` block.
* `#12146 <https://github.com/numpy/numpy/pull/12146>`__: MAINT: Fix typo in comment
* `#12147 <https://github.com/numpy/numpy/pull/12147>`__: MAINT: Move duplicated type_reso_error code into a helper function
* `#12148 <https://github.com/numpy/numpy/pull/12148>`__: DOC: document NEP-18 overrides in release notes
* `#12151 <https://github.com/numpy/numpy/pull/12151>`__: TST: byte_bounds contiguity handling
* `#12153 <https://github.com/numpy/numpy/pull/12153>`__: DOC, TST: cover setdiff1d assume_unique
* `#12154 <https://github.com/numpy/numpy/pull/12154>`__: ENH: `__array_function__` for `np.core.defchararray`
* `#12155 <https://github.com/numpy/numpy/pull/12155>`__: MAINT: Define Py_SETREF for pre-3.5.2 python and use in code
* `#12157 <https://github.com/numpy/numpy/pull/12157>`__: ENH: Add support for third-party path-like objects by backporting...
* `#12159 <https://github.com/numpy/numpy/pull/12159>`__: MAINT: remove unused nd_grid `__len__`.
* `#12163 <https://github.com/numpy/numpy/pull/12163>`__: ENH: `__array_function__` for `np.einsum` and `np.block`
* `#12165 <https://github.com/numpy/numpy/pull/12165>`__: Mark NEP 22 as accepted, and add "Informational" NEPs to NEP...
* `#12166 <https://github.com/numpy/numpy/pull/12166>`__: NEP: Add zero-rank arrays historical info NEP
* `#12173 <https://github.com/numpy/numpy/pull/12173>`__: NEP: add notes about updates to NEP-18
* `#12174 <https://github.com/numpy/numpy/pull/12174>`__: NEP 16 abstract arrays: rebased and marked as "Withdrawn"
* `#12175 <https://github.com/numpy/numpy/pull/12175>`__: ENH: `__array_function__` for multiarray functions
* `#12176 <https://github.com/numpy/numpy/pull/12176>`__: TST: add test for weighted histogram mismatch
* `#12177 <https://github.com/numpy/numpy/pull/12177>`__: MAINT: remove unused `_assertSquareness()`
* `#12179 <https://github.com/numpy/numpy/pull/12179>`__: MAINT: Move `_kind_to_stem` to `np.core._dtype`, so that it can...
* `#12180 <https://github.com/numpy/numpy/pull/12180>`__: NEP: change toc titles, cross reference, mark 16 superseded
* `#12181 <https://github.com/numpy/numpy/pull/12181>`__: MAINT: fix depreciation message typo for np.sum
* `#12185 <https://github.com/numpy/numpy/pull/12185>`__: TST: test multi_dot with 2 arrays
* `#12199 <https://github.com/numpy/numpy/pull/12199>`__: TST: add Azure CI triggers
* `#12209 <https://github.com/numpy/numpy/pull/12209>`__: Delay import of distutils.msvccompiler to avoid warning on non-Windows.
* `#12211 <https://github.com/numpy/numpy/pull/12211>`__: DOC: Clarify the examples for argmax and argmin
* `#12212 <https://github.com/numpy/numpy/pull/12212>`__: MAINT: `ndarray.__repr__` should not rely on `__array_function__`
* `#12214 <https://github.com/numpy/numpy/pull/12214>`__: TST: add test for tensorinv()
* `#12215 <https://github.com/numpy/numpy/pull/12215>`__: TST: test dims match on lstsq()
* `#12216 <https://github.com/numpy/numpy/pull/12216>`__: TST: test invalid histogram range
* `#12217 <https://github.com/numpy/numpy/pull/12217>`__: TST: test histogram bins dims
* `#12219 <https://github.com/numpy/numpy/pull/12219>`__: ENH: make matmul into a ufunc
* `#12222 <https://github.com/numpy/numpy/pull/12222>`__: TST: unit tests for column_stack.
* `#12224 <https://github.com/numpy/numpy/pull/12224>`__: BUG: Fix MaskedArray fill_value type conversion.
* `#12229 <https://github.com/numpy/numpy/pull/12229>`__: MAINT: Fix typo in comment
* `#12236 <https://github.com/numpy/numpy/pull/12236>`__: BUG: maximum, minimum no longer emit warnings on NAN
* `#12240 <https://github.com/numpy/numpy/pull/12240>`__: BUG: Fix crash in repr of void subclasses
* `#12241 <https://github.com/numpy/numpy/pull/12241>`__: TST: arg handling tests in histogramdd
* `#12243 <https://github.com/numpy/numpy/pull/12243>`__: BUG: Fix misleading assert message in assert_almost_equal #12200
* `#12245 <https://github.com/numpy/numpy/pull/12245>`__: TST: tests for sort_complex()
* `#12246 <https://github.com/numpy/numpy/pull/12246>`__: DOC: Update docs after NumPy 1.15.3 release.
* `#12249 <https://github.com/numpy/numpy/pull/12249>`__: BUG: Dealloc cached buffer info
* `#12250 <https://github.com/numpy/numpy/pull/12250>`__: DOC: add missing docs
* `#12251 <https://github.com/numpy/numpy/pull/12251>`__: MAINT: improved error message when no `__array_function__` implementation...
* `#12254 <https://github.com/numpy/numpy/pull/12254>`__: MAINT: Move ctype -> dtype conversion to python
* `#12257 <https://github.com/numpy/numpy/pull/12257>`__: BUG: Fix fill value in masked array '==' and '!=' ops.
* `#12259 <https://github.com/numpy/numpy/pull/12259>`__: TST: simplify how the different code paths for block are tested.
* `#12265 <https://github.com/numpy/numpy/pull/12265>`__: BUG: Revert linspace import for concatenation funcs
* `#12266 <https://github.com/numpy/numpy/pull/12266>`__: BUG: Avoid SystemErrors by checking the return value of PyPrint
* `#12268 <https://github.com/numpy/numpy/pull/12268>`__: DOC: add broadcasting article from scipy old-wiki
* `#12270 <https://github.com/numpy/numpy/pull/12270>`__: MAINT: set `__module__` for more `array_function_dispatch` uses
* `#12276 <https://github.com/numpy/numpy/pull/12276>`__: MAINT: remove unused parse_index()
* `#12279 <https://github.com/numpy/numpy/pull/12279>`__: NEP: tweak and mark NEP 0027 as final
* `#12280 <https://github.com/numpy/numpy/pull/12280>`__: DEP: deprecate passing a generator to stack functions
* `#12281 <https://github.com/numpy/numpy/pull/12281>`__: NEP: revise note for NEP 27
* `#12285 <https://github.com/numpy/numpy/pull/12285>`__: ENH: array does not need to be writable to use as input to take
* `#12286 <https://github.com/numpy/numpy/pull/12286>`__: ENH: Do not emit compiler warning if forcing old API
* `#12288 <https://github.com/numpy/numpy/pull/12288>`__: BUILD: force LGTM to use cython>=0.29
* `#12291 <https://github.com/numpy/numpy/pull/12291>`__: MAINT: `_set_out_array()` syntax fix
* `#12292 <https://github.com/numpy/numpy/pull/12292>`__: MAINT: removed unused vars in f2py test code
* `#12299 <https://github.com/numpy/numpy/pull/12299>`__: BUILD: use system python3 in the chroot
* `#12302 <https://github.com/numpy/numpy/pull/12302>`__: DOC: Update the docstring of asfortranarray and ascontiguousarray
* `#12306 <https://github.com/numpy/numpy/pull/12306>`__: TST: add 32-bit linux Azure CI job
* `#12312 <https://github.com/numpy/numpy/pull/12312>`__: MAINT, TST: unreachable Python code paths
* `#12321 <https://github.com/numpy/numpy/pull/12321>`__: MAINT: Simple speed-ups for getting overloaded types
* `#12326 <https://github.com/numpy/numpy/pull/12326>`__: DOC: NumPy 1.15.4 post release documentation update.
* `#12328 <https://github.com/numpy/numpy/pull/12328>`__: MAINT: Allow subclasses in `ndarray.__array_function__`.
* `#12330 <https://github.com/numpy/numpy/pull/12330>`__: TST: test_tofile_fromfile now uses initialized memory
* `#12331 <https://github.com/numpy/numpy/pull/12331>`__: DEV: change ASV benchmarks to run on Python 3.6 by default
* `#12338 <https://github.com/numpy/numpy/pull/12338>`__: DOC: add a docstring for the function 'compare_chararrays' (See...
* `#12342 <https://github.com/numpy/numpy/pull/12342>`__: BUG: Fix for np.dtype(ctypes.Structure) does not respect _pack_...
* `#12347 <https://github.com/numpy/numpy/pull/12347>`__: DOC: typo in docstring numpy.random.beta, shape parameters must...
* `#12349 <https://github.com/numpy/numpy/pull/12349>`__: TST, DOC: store circleci doc artifacts
* `#12353 <https://github.com/numpy/numpy/pull/12353>`__: BUG: test, fix for threshold='nan'
* `#12354 <https://github.com/numpy/numpy/pull/12354>`__: BUG: Fix segfault when an error occurs in np.fromfile
* `#12355 <https://github.com/numpy/numpy/pull/12355>`__: BUG: fix a bug in npy_PyFile_Dup2 where it didn't return immediately...
* `#12357 <https://github.com/numpy/numpy/pull/12357>`__: MAINT: Cleanup pavement file
* `#12358 <https://github.com/numpy/numpy/pull/12358>`__: BUG: test, fix loading structured dtypes with padding
* `#12362 <https://github.com/numpy/numpy/pull/12362>`__: MAINT: disable `__array_function__` dispatch unless environment...
* `#12363 <https://github.com/numpy/numpy/pull/12363>`__: MAINT: update gfortran RPATH for AIX/Windows non-support.
* `#12364 <https://github.com/numpy/numpy/pull/12364>`__: NEP: clarify the purpose of "types" in `__array_function__`.
* `#12366 <https://github.com/numpy/numpy/pull/12366>`__: MAINT: Refactor sorting header file
* `#12372 <https://github.com/numpy/numpy/pull/12372>`__: BUG: random: Fix handling of a=0 for numpy.random.weibull.
* `#12373 <https://github.com/numpy/numpy/pull/12373>`__: MAINT: Improve error message for legal but unsupported PEP3118...
* `#12376 <https://github.com/numpy/numpy/pull/12376>`__: BUG: do not override exception on import failure
* `#12377 <https://github.com/numpy/numpy/pull/12377>`__: NEP: move nep 15 from accepted to final
* `#12378 <https://github.com/numpy/numpy/pull/12378>`__: TST: Update complex long double precision tests.
* `#12380 <https://github.com/numpy/numpy/pull/12380>`__: BUG: Fix for #10533 np.dtype(ctype) does not respect endianness
* `#12381 <https://github.com/numpy/numpy/pull/12381>`__: BUG: graceful DataSource __del__ when __init__ fails
* `#12382 <https://github.com/numpy/numpy/pull/12382>`__: ENH: set correct __module__ for objects in numpy's public API
* `#12388 <https://github.com/numpy/numpy/pull/12388>`__: ENH: allow arrays for start and stop in {lin,log,geom}space
* `#12390 <https://github.com/numpy/numpy/pull/12390>`__: DEV: remove shim added in 1.4
* `#12391 <https://github.com/numpy/numpy/pull/12391>`__: DEP: raise on a call to deprecated numpy.lib.function_base.unique
* `#12392 <https://github.com/numpy/numpy/pull/12392>`__: DOC: Add release notes for ctypes improvements
* `#12398 <https://github.com/numpy/numpy/pull/12398>`__: BUG: fix possible overlap issues with avx enabled
* `#12399 <https://github.com/numpy/numpy/pull/12399>`__: DOC: Fix typo in polyint. Fixes #12386.
* `#12405 <https://github.com/numpy/numpy/pull/12405>`__: ENH: Add support for `np.dtype(ctypes.Union)`
* `#12407 <https://github.com/numpy/numpy/pull/12407>`__: BUG: Fall back to 'ascii' locale in build (if needed)
* `#12408 <https://github.com/numpy/numpy/pull/12408>`__: BUG: multifield-view of MaskedArray gets bad fill_value
* `#12409 <https://github.com/numpy/numpy/pull/12409>`__: MAINT: correct the dtype.descr docstring
* `#12413 <https://github.com/numpy/numpy/pull/12413>`__: BUG: Do not double-quote arguments to the command line
* `#12414 <https://github.com/numpy/numpy/pull/12414>`__: MAINT: Update cversion hash.
* `#12417 <https://github.com/numpy/numpy/pull/12417>`__: BUG: Fix regression on np.dtype(ctypes.c_void_p)
* `#12419 <https://github.com/numpy/numpy/pull/12419>`__: Fix PyArray_FillFunc function definitions
* `#12420 <https://github.com/numpy/numpy/pull/12420>`__: gfortran needs -lpthread & -maix64(64 build) in AIX
* `#12422 <https://github.com/numpy/numpy/pull/12422>`__: MNT: Reword error message about loading pickled data.
* `#12424 <https://github.com/numpy/numpy/pull/12424>`__: BUG: Fix inconsistent cache keying in ndpointer
* `#12429 <https://github.com/numpy/numpy/pull/12429>`__: MAINT: Update mailmap for 1.16.0 release.
* `#12431 <https://github.com/numpy/numpy/pull/12431>`__: BUG/ENH: Fix use of ndpointer in return values
* `#12437 <https://github.com/numpy/numpy/pull/12437>`__: MAINT: refactor datetime.c_metadata creation
* `#12439 <https://github.com/numpy/numpy/pull/12439>`__: BUG: test, fix NPY_VISIBILITY_HIDDEN on gcc, which becomes NPY_NO_EXPORT
* `#12440 <https://github.com/numpy/numpy/pull/12440>`__: BUG: don't override original errors when casting inside np.dot()...
* `#12443 <https://github.com/numpy/numpy/pull/12443>`__: MAINT Use set litterals
* `#12445 <https://github.com/numpy/numpy/pull/12445>`__: MAINT: Use list and dict comprehension when possible
* `#12446 <https://github.com/numpy/numpy/pull/12446>`__: MAINT: Fixups to new functions in np.lib.recfunctions
* `#12447 <https://github.com/numpy/numpy/pull/12447>`__: ENH: add back the multifield copy->view change
* `#12448 <https://github.com/numpy/numpy/pull/12448>`__: MAINT: Review F401,F841,F842 flake8 errors (unused variables...
* `#12455 <https://github.com/numpy/numpy/pull/12455>`__: TST: use condition directive for Azure 2.7 check
* `#12458 <https://github.com/numpy/numpy/pull/12458>`__: MAINT, DOC: fix Azure README badge
* `#12464 <https://github.com/numpy/numpy/pull/12464>`__: BUG: IndexError for empty list on structured MaskedArray.
* `#12466 <https://github.com/numpy/numpy/pull/12466>`__: TST: use openblas for Windows CI
* `#12470 <https://github.com/numpy/numpy/pull/12470>`__: MAINT: remove wrapper functions from numpy.core.multiarray
* `#12471 <https://github.com/numpy/numpy/pull/12471>`__: ENH: override support for np.linspace and friends
* `#12474 <https://github.com/numpy/numpy/pull/12474>`__: TST: enable dispatcher test coverage
* `#12477 <https://github.com/numpy/numpy/pull/12477>`__: DOC: fix example for __call__. See #12451
* `#12486 <https://github.com/numpy/numpy/pull/12486>`__: DOC: Update copyright year in the license
* `#12488 <https://github.com/numpy/numpy/pull/12488>`__: ENH: implement matmul on NDArrayOperatorsMixin
* `#12493 <https://github.com/numpy/numpy/pull/12493>`__: BUG: fix records.fromfile fails to read data >4 GB
* `#12494 <https://github.com/numpy/numpy/pull/12494>`__: BUG: test, fix matmul, dot for vector array with stride[i]=0
* `#12498 <https://github.com/numpy/numpy/pull/12498>`__: TST: sync Azure Win openblas
* `#12501 <https://github.com/numpy/numpy/pull/12501>`__: MAINT: removed word/typo from comment in site.cfg.example
* `#12556 <https://github.com/numpy/numpy/pull/12556>`__: BUG: only override vector size for avx code for 1.16
* `#12562 <https://github.com/numpy/numpy/pull/12562>`__: DOC, MAINT: Make `PYVER = 3` in doc/Makefile.
* `#12563 <https://github.com/numpy/numpy/pull/12563>`__: DOC: more doc updates for structured arrays
* `#12564 <https://github.com/numpy/numpy/pull/12564>`__: BUG: fix an unsafe PyTuple_GET_ITEM call
* `#12565 <https://github.com/numpy/numpy/pull/12565>`__: Fix lgtm.com C/C++ build
* `#12567 <https://github.com/numpy/numpy/pull/12567>`__: BUG: reorder operations for VS2015
* `#12568 <https://github.com/numpy/numpy/pull/12568>`__: BUG: fix improper use of C-API
* `#12569 <https://github.com/numpy/numpy/pull/12569>`__: BUG: Make new-lines in compiler error messages print to the console
* `#12570 <https://github.com/numpy/numpy/pull/12570>`__: MAINT: don't check alignment size=0 arrays (RELAXED_STRIDES)
* `#12573 <https://github.com/numpy/numpy/pull/12573>`__: BUG: fix refcount issue caused by #12524
* `#12580 <https://github.com/numpy/numpy/pull/12580>`__: BUG: fix segfault in ctypeslib with obj being collected
* `#12581 <https://github.com/numpy/numpy/pull/12581>`__: TST: activate shippable maintenance branches
* `#12582 <https://github.com/numpy/numpy/pull/12582>`__: BUG: fix f2py pep338 execution method
* `#12587 <https://github.com/numpy/numpy/pull/12587>`__: BUG: Make `arr.ctypes.data` hold a reference to the underlying...
* `#12588 <https://github.com/numpy/numpy/pull/12588>`__: BUG: check for errors after PyArray_DESCR_REPLACE
* `#12590 <https://github.com/numpy/numpy/pull/12590>`__: DOC, MAINT: Prepare for 1.16.0rc1 release.
* `#12603 <https://github.com/numpy/numpy/pull/12603>`__: DOC: Fix markup in 1.16.0 release notes.
* `#12621 <https://github.com/numpy/numpy/pull/12621>`__: BUG: longdouble with elsize 12 is never uint alignable.
* `#12622 <https://github.com/numpy/numpy/pull/12622>`__: BUG: Add missing free in ufunc dealloc
* `#12623 <https://github.com/numpy/numpy/pull/12623>`__: MAINT: add test for 12-byte alignment
* `#12655 <https://github.com/numpy/numpy/pull/12655>`__: BUG: fix uint alignment asserts in lowlevel loops
* `#12656 <https://github.com/numpy/numpy/pull/12656>`__: BENCH: don't fail at import time with old Numpy
* `#12657 <https://github.com/numpy/numpy/pull/12657>`__: DOC: update 2018 -> 2019
* `#12705 <https://github.com/numpy/numpy/pull/12705>`__: ENH: Better links in documentation
* `#12706 <https://github.com/numpy/numpy/pull/12706>`__: MAINT: Further fixups to uint alignment checks
* `#12707 <https://github.com/numpy/numpy/pull/12707>`__: BUG: Add 'sparc' to platforms implementing 16 byte reals.
* `#12708 <https://github.com/numpy/numpy/pull/12708>`__: TST: Fix endianness in unstuctured_to_structured test
* `#12710 <https://github.com/numpy/numpy/pull/12710>`__: TST: pin Azure brew version for stability.

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Contributors
============
A total of 16 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Antoine Pitrou
* Arcesio Castaneda Medina +
* Charles Harris
* Chris Markiewicz +
* Christoph Gohlke
* Christopher J. Markiewicz +
* Daniel Hrisca +
* EelcoPeacs +
* Eric Wieser
* Kevin Sheppard
* Matti Picus
* OBATA Akio +
* Ralf Gommers
* Sebastian Berg
* Stephan Hoyer
* Tyler Reddy
Pull requests merged
====================
A total of 33 pull requests were merged for this release.
* `#12754 <https://github.com/numpy/numpy/pull/12754>`__: BUG: Check paths are unicode, bytes or path-like
* `#12767 <https://github.com/numpy/numpy/pull/12767>`__: ENH: add mm->q floordiv
* `#12768 <https://github.com/numpy/numpy/pull/12768>`__: ENH: port np.core.overrides to C for speed
* `#12769 <https://github.com/numpy/numpy/pull/12769>`__: ENH: Add np.ctypeslib.as_ctypes_type(dtype), improve `np.ctypeslib.as_ctypes`
* `#12771 <https://github.com/numpy/numpy/pull/12771>`__: BUG: Ensure probabilities are not NaN in choice
* `#12772 <https://github.com/numpy/numpy/pull/12772>`__: MAINT: add warning to numpy.distutils for LDFLAGS append behavior.
* `#12773 <https://github.com/numpy/numpy/pull/12773>`__: ENH: add "max difference" messages to np.testing.assert_array_equal...
* `#12774 <https://github.com/numpy/numpy/pull/12774>`__: BUG: Fix incorrect/missing reference cleanups found using valgrind
* `#12776 <https://github.com/numpy/numpy/pull/12776>`__: BUG,TST: Remove the misguided `run_command` that wraps subprocess
* `#12777 <https://github.com/numpy/numpy/pull/12777>`__: DOC, TST: Clean up matplotlib imports
* `#12781 <https://github.com/numpy/numpy/pull/12781>`__: BUG: Fix reference counting for subarrays containing objects
* `#12782 <https://github.com/numpy/numpy/pull/12782>`__: BUG: Ensure failing memory allocations are reported
* `#12784 <https://github.com/numpy/numpy/pull/12784>`__: BUG: Fix leak of void scalar buffer info
* `#12788 <https://github.com/numpy/numpy/pull/12788>`__: MAINT: Change the order of checking for local file.
* `#12808 <https://github.com/numpy/numpy/pull/12808>`__: BUG: loosen kwargs requirements in ediff1d
* `#12809 <https://github.com/numpy/numpy/pull/12809>`__: DOC: clarify the extend of __array_function__ support in NumPy...
* `#12810 <https://github.com/numpy/numpy/pull/12810>`__: BUG: Check that dtype or formats arguments are not None.
* `#12811 <https://github.com/numpy/numpy/pull/12811>`__: BUG: fix f2py problem to build wrappers using PGI's Fortran
* `#12812 <https://github.com/numpy/numpy/pull/12812>`__: BUG: double decref of dtype in failure codepath. Test and fix
* `#12813 <https://github.com/numpy/numpy/pull/12813>`__: BUG, DOC: test, fix that f2py.compile accepts str and bytes,...
* `#12816 <https://github.com/numpy/numpy/pull/12816>`__: BUG: resolve writeback in arr_insert failure paths
* `#12820 <https://github.com/numpy/numpy/pull/12820>`__: ENH: Add mm->qm divmod
* `#12843 <https://github.com/numpy/numpy/pull/12843>`__: BUG: fix to check before apply `shlex.split`
* `#12844 <https://github.com/numpy/numpy/pull/12844>`__: BUG: Fix SystemError when pickling datetime64 array with pickle5
* `#12845 <https://github.com/numpy/numpy/pull/12845>`__: BUG: Fix rounding of denormals in double and float to half casts.
* `#12868 <https://github.com/numpy/numpy/pull/12868>`__: TEST: pin mingw version
* `#12869 <https://github.com/numpy/numpy/pull/12869>`__: BUG: ndarrays pickled by 1.16 cannot be loaded by 1.15.4 and...
* `#12870 <https://github.com/numpy/numpy/pull/12870>`__: BUG: do not Py_DECREF NULL pointer
* `#12890 <https://github.com/numpy/numpy/pull/12890>`__: ENH: add _dtype_ctype to namespace for freeze analysis
* `#12891 <https://github.com/numpy/numpy/pull/12891>`__: BUG: fail if old multiarray module detected
* `#12898 <https://github.com/numpy/numpy/pull/12898>`__: BUG: Do not double-quote arguments passed on to the linker
* `#12899 <https://github.com/numpy/numpy/pull/12899>`__: BUG: Do not insert extra double quote into preprocessor macros
* `#12902 <https://github.com/numpy/numpy/pull/12902>`__: DOC: Prepare for 1.16.1 release.

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Contributors
============
A total of 5 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Charles Harris
* Eric Wieser
* Matti Picus
* Tyler Reddy
* Tony LaTorre +
Pull requests merged
====================
A total of 7 pull requests were merged for this release.
* `#12909 <https://github.com/numpy/numpy/pull/12909>`__: TST: fix vmImage dispatch in Azure
* `#12923 <https://github.com/numpy/numpy/pull/12923>`__: MAINT: remove complicated test of multiarray import failure mode
* `#13020 <https://github.com/numpy/numpy/pull/13020>`__: BUG: fix signed zero behavior in npy_divmod
* `#13026 <https://github.com/numpy/numpy/pull/13026>`__: MAINT: Add functions to parse shell-strings in the platform-native...
* `#13028 <https://github.com/numpy/numpy/pull/13028>`__: BUG: Fix regression in parsing of F90 and F77 environment variables
* `#13038 <https://github.com/numpy/numpy/pull/13038>`__: BUG: parse shell escaping in extra_compile_args and extra_link_args
* `#13041 <https://github.com/numpy/numpy/pull/13041>`__: BLD: Windows absolute path DLL loading

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Contributors
============
A total of 16 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Andreas Schwab
* Bharat Raghunathan +
* Bran +
* Charles Harris
* Eric Wieser
* Jakub Wilk
* Kevin Sheppard
* Marten van Kerkwijk
* Matti Picus
* Paul Ivanov
* Ralf Gommers
* Sebastian Berg
* Tyler Reddy
* Warren Weckesser
* Yu Feng
* adeak +
Pull requests merged
====================
A total of 26 pull requests were merged for this release.
* `#13072 <https://github.com/numpy/numpy/pull/13072>`__: BUG: Fixes to numpy.distutils.Configuration.get_version (#13056)
* `#13082 <https://github.com/numpy/numpy/pull/13082>`__: BUG: Fix errors in string formatting while producing an error
* `#13083 <https://github.com/numpy/numpy/pull/13083>`__: BUG: Convert fortran flags in environment variable
* `#13084 <https://github.com/numpy/numpy/pull/13084>`__: BUG: Remove error-prone borrowed reference handling
* `#13085 <https://github.com/numpy/numpy/pull/13085>`__: BUG: Add error checks when converting integers to datetime types
* `#13091 <https://github.com/numpy/numpy/pull/13091>`__: BUG: Remove our patched version of `distutils.split_quoted`
* `#13141 <https://github.com/numpy/numpy/pull/13141>`__: BUG: Fix testsuite failures on ppc and riscv
* `#13142 <https://github.com/numpy/numpy/pull/13142>`__: BUG: Fix parameter validity checks in ``random.choice``
* `#13143 <https://github.com/numpy/numpy/pull/13143>`__: BUG: Ensure linspace works on object input.
* `#13144 <https://github.com/numpy/numpy/pull/13144>`__: BLD: fix include list for sdist building.
* `#13145 <https://github.com/numpy/numpy/pull/13145>`__: BUG: __array_interface__ offset was always ignored
* `#13274 <https://github.com/numpy/numpy/pull/13274>`__: MAINT: f2py: Add a cast to avoid a compiler warning.
* `#13275 <https://github.com/numpy/numpy/pull/13275>`__: BUG, MAINT: fix reference count error on invalid input to ndarray.flat
* `#13276 <https://github.com/numpy/numpy/pull/13276>`__: ENH: Cast covariance to double in random mvnormal
* `#13278 <https://github.com/numpy/numpy/pull/13278>`__: BUG: Fix null pointer dereference in PyArray_DTypeFromObjectHelper
* `#13339 <https://github.com/numpy/numpy/pull/13339>`__: BUG: Use C call to sysctlbyname for AVX detection on MacOS.
* `#13340 <https://github.com/numpy/numpy/pull/13340>`__: BUG: Fix crash when calling savetxt on a padded array
* `#13341 <https://github.com/numpy/numpy/pull/13341>`__: BUG: ufunc.at iteration variable size fix
* `#13342 <https://github.com/numpy/numpy/pull/13342>`__: DOC: Add as_ctypes_type to the documentation
* `#13350 <https://github.com/numpy/numpy/pull/13350>`__: BUG: Return the coefficients array directly
* `#13351 <https://github.com/numpy/numpy/pull/13351>`__: BUG/MAINT: Tidy typeinfo.h and .c
* `#13359 <https://github.com/numpy/numpy/pull/13359>`__: BUG: Make allow_pickle=False the default for loading
* `#13360 <https://github.com/numpy/numpy/pull/13360>`__: DOC: fix some doctest failures
* `#13363 <https://github.com/numpy/numpy/pull/13363>`__: BUG/MAINT: Tidy typeinfo.h and .c
* `#13381 <https://github.com/numpy/numpy/pull/13381>`__: BLD: address mingw-w64 issue. Follow-up to gh-9977
* `#13382 <https://github.com/numpy/numpy/pull/13382>`__: REL: Prepare for the NumPy release.

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Contributors
============
A total of 10 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Charles Harris
* Eric Wieser
* Dennis Zollo +
* Hunter Damron +
* Jingbei Li +
* Kevin Sheppard
* Matti Picus
* Nicola Soranzo +
* Sebastian Berg
* Tyler Reddy
Pull requests merged
====================
A total of 16 pull requests were merged for this release.
* `#13392 <https://github.com/numpy/numpy/pull/13392>`__: BUG: Some PyPy versions lack PyStructSequence_InitType2.
* `#13394 <https://github.com/numpy/numpy/pull/13394>`__: MAINT, DEP: Fix deprecated ``assertEquals()``
* `#13396 <https://github.com/numpy/numpy/pull/13396>`__: BUG: Fix structured_to_unstructured on single-field types (backport)
* `#13549 <https://github.com/numpy/numpy/pull/13549>`__: BLD: Make CI pass again with pytest 4.5
* `#13552 <https://github.com/numpy/numpy/pull/13552>`__: TST: Register markers in conftest.py.
* `#13559 <https://github.com/numpy/numpy/pull/13559>`__: BUG: Removes ValueError for empty kwargs in arraymultiter_new
* `#13560 <https://github.com/numpy/numpy/pull/13560>`__: BUG: Add TypeError to accepted exceptions in crackfortran.
* `#13561 <https://github.com/numpy/numpy/pull/13561>`__: BUG: Handle subarrays in descr_to_dtype
* `#13562 <https://github.com/numpy/numpy/pull/13562>`__: BUG: Protect generators from log(0.0)
* `#13563 <https://github.com/numpy/numpy/pull/13563>`__: BUG: Always return views from structured_to_unstructured when...
* `#13564 <https://github.com/numpy/numpy/pull/13564>`__: BUG: Catch stderr when checking compiler version
* `#13565 <https://github.com/numpy/numpy/pull/13565>`__: BUG: longdouble(int) does not work
* `#13587 <https://github.com/numpy/numpy/pull/13587>`__: BUG: distutils/system_info.py fix missing subprocess import (#13523)
* `#13620 <https://github.com/numpy/numpy/pull/13620>`__: BUG,DEP: Fix writeable flag setting for arrays without base
* `#13641 <https://github.com/numpy/numpy/pull/13641>`__: MAINT: Prepare for the 1.16.4 release.
* `#13644 <https://github.com/numpy/numpy/pull/13644>`__: BUG: special case object arrays when printing rel-, abs-error

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Contributors
============
A total of 18 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Alexander Shadchin
* Allan Haldane
* Bruce Merry +
* Charles Harris
* Colin Snyder +
* Dan Allan +
* Emile +
* Eric Wieser
* Grey Baker +
* Maksim Shabunin +
* Marten van Kerkwijk
* Matti Picus
* Peter Andreas Entschev +
* Ralf Gommers
* Richard Harris +
* Sebastian Berg
* Sergei Lebedev +
* Stephan Hoyer
Pull requests merged
====================
A total of 23 pull requests were merged for this release.
* `#13742 <https://github.com/numpy/numpy/pull/13742>`__: ENH: Add project URLs to setup.py
* `#13823 <https://github.com/numpy/numpy/pull/13823>`__: TEST, ENH: fix tests and ctypes code for PyPy
* `#13845 <https://github.com/numpy/numpy/pull/13845>`__: BUG: use npy_intp instead of int for indexing array
* `#13867 <https://github.com/numpy/numpy/pull/13867>`__: TST: Ignore DeprecationWarning during nose imports
* `#13905 <https://github.com/numpy/numpy/pull/13905>`__: BUG: Fix use-after-free in boolean indexing
* `#13933 <https://github.com/numpy/numpy/pull/13933>`__: MAINT/BUG/DOC: Fix errors in _add_newdocs
* `#13984 <https://github.com/numpy/numpy/pull/13984>`__: BUG: fix byte order reversal for datetime64[ns]
* `#13994 <https://github.com/numpy/numpy/pull/13994>`__: MAINT,BUG: Use nbytes to also catch empty descr during allocation
* `#14042 <https://github.com/numpy/numpy/pull/14042>`__: BUG: np.array cleared errors occurred in PyMemoryView_FromObject
* `#14043 <https://github.com/numpy/numpy/pull/14043>`__: BUG: Fixes for Undefined Behavior Sanitizer (UBSan) errors.
* `#14044 <https://github.com/numpy/numpy/pull/14044>`__: BUG: ensure that casting to/from structured is properly checked.
* `#14045 <https://github.com/numpy/numpy/pull/14045>`__: MAINT: fix histogram*d dispatchers
* `#14046 <https://github.com/numpy/numpy/pull/14046>`__: BUG: further fixup to histogram2d dispatcher.
* `#14052 <https://github.com/numpy/numpy/pull/14052>`__: BUG: Replace contextlib.suppress for Python 2.7
* `#14056 <https://github.com/numpy/numpy/pull/14056>`__: BUG: fix compilation of 3rd party modules with Py_LIMITED_API...
* `#14057 <https://github.com/numpy/numpy/pull/14057>`__: BUG: Fix memory leak in dtype from dict constructor
* `#14058 <https://github.com/numpy/numpy/pull/14058>`__: DOC: Document array_function at a higher level.
* `#14084 <https://github.com/numpy/numpy/pull/14084>`__: BUG, DOC: add new recfunctions to `__all__`
* `#14162 <https://github.com/numpy/numpy/pull/14162>`__: BUG: Remove stray print that causes a SystemError on python 3.7
* `#14297 <https://github.com/numpy/numpy/pull/14297>`__: TST: Pin pytest version to 5.0.1.
* `#14322 <https://github.com/numpy/numpy/pull/14322>`__: ENH: Enable huge pages in all Linux builds
* `#14346 <https://github.com/numpy/numpy/pull/14346>`__: BUG: fix behavior of structured_to_unstructured on non-trivial...
* `#14382 <https://github.com/numpy/numpy/pull/14382>`__: REL: Prepare for the NumPy 1.16.5 release.

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Contributors
============
A total of 10 people contributed to this release.
* CakeWithSteak
* Charles Harris
* Chris Burr
* Eric Wieser
* Fernando Saravia
* Lars Grueter
* Matti Picus
* Maxwell Aladago
* Qiming Sun
* Warren Weckesser
Pull requests merged
====================
A total of 14 pull requests were merged for this release.
* `#14211 <https://github.com/numpy/numpy/pull/14211>`__: BUG: Fix uint-overflow if padding with linear_ramp and negative...
* `#14275 <https://github.com/numpy/numpy/pull/14275>`__: BUG: fixing to allow unpickling of PY3 pickles from PY2
* `#14340 <https://github.com/numpy/numpy/pull/14340>`__: BUG: Fix misuse of .names and .fields in various places (backport...
* `#14423 <https://github.com/numpy/numpy/pull/14423>`__: BUG: test, fix regression in converting to ctypes.
* `#14434 <https://github.com/numpy/numpy/pull/14434>`__: BUG: Fixed maximum relative error reporting in assert_allclose
* `#14509 <https://github.com/numpy/numpy/pull/14509>`__: BUG: Fix regression in boolean matmul.
* `#14686 <https://github.com/numpy/numpy/pull/14686>`__: BUG: properly define PyArray_DescrCheck
* `#14853 <https://github.com/numpy/numpy/pull/14853>`__: BLD: add 'apt update' to shippable
* `#14854 <https://github.com/numpy/numpy/pull/14854>`__: BUG: Fix _ctypes class circular reference. (#13808)
* `#14856 <https://github.com/numpy/numpy/pull/14856>`__: BUG: Fix `np.einsum` errors on Power9 Linux and z/Linux
* `#14863 <https://github.com/numpy/numpy/pull/14863>`__: BLD: Prevent -flto from optimising long double representation...
* `#14864 <https://github.com/numpy/numpy/pull/14864>`__: BUG: lib: Fix histogram problem with signed integer arrays.
* `#15172 <https://github.com/numpy/numpy/pull/15172>`__: ENH: Backport improvements to testing functions.
* `#15191 <https://github.com/numpy/numpy/pull/15191>`__: REL: Prepare for 1.16.6 release.

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Contributors
============
A total of 150 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Aaron Voelker +
* Abdur Rehman +
* Abdur-Rahmaan Janhangeer +
* Abhinav Sagar +
* Adam J. Stewart +
* Adam Orr +
* Albert Thomas +
* Alex Watt +
* Alexander Blinne +
* Alexander Shadchin
* Allan Haldane
* Ander Ustarroz +
* Andras Deak
* Andrea Pattori +
* Andreas Schwab
* Andrew Naguib +
* Andy Scholand +
* Ankit Shukla +
* Anthony Sottile
* Antoine Pitrou
* Antony Lee
* Arcesio Castaneda Medina +
* Assem +
* Bernardt Duvenhage +
* Bharat Raghunathan +
* Bharat123rox +
* Bran +
* Bruce Merry +
* Charles Harris
* Chirag Nighut +
* Christoph Gohlke
* Christopher Whelan +
* Chuanzhu Xu +
* Colin Snyder +
* Dan Allan +
* Daniel Hrisca
* Daniel Lawrence +
* Debsankha Manik +
* Dennis Zollo +
* Dieter Werthmüller +
* Dominic Jack +
* EelcoPeacs +
* Eric Larson
* Eric Wieser
* Fabrice Fontaine +
* Gary Gurlaskie +
* Gregory Lee +
* Gregory R. Lee
* Guillaume Horel +
* Hameer Abbasi
* Haoyu Sun +
* Harmon +
* He Jia +
* Hunter Damron +
* Ian Sanders +
* Ilja +
* Isaac Virshup +
* Isaiah Norton +
* Jackie Leng +
* Jaime Fernandez
* Jakub Wilk
* Jan S. (Milania1) +
* Jarrod Millman
* Javier Dehesa +
* Jeremy Lay +
* Jim Turner +
* Jingbei Li +
* Joachim Hereth +
* Johannes Hampp +
* John Belmonte +
* John Kirkham
* John Law +
* Jonas Jensen
* Joseph Fox-Rabinovitz
* Joseph Martinot-Lagarde
* Josh Wilson
* Juan Luis Cano Rodríguez
* Julian Taylor
* Jérémie du Boisberranger +
* Kai Striega +
* Katharine Hyatt +
* Kevin Sheppard
* Kexuan Sun
* Kiko Correoso +
* Kriti Singh +
* Lars Grueter +
* Luis Pedro Coelho
* Maksim Shabunin +
* Manvi07 +
* Mark Harfouche
* Marten van Kerkwijk
* Martin Reinecke +
* Matthew Brett
* Matthias Bussonnier
* Matti Picus
* Michel Fruchart +
* Mike Lui +
* Mike Taves +
* Min ho Kim +
* Mircea Akos Bruma
* Nick Minkyu Lee
* Nick Papior
* Nick R. Papior +
* Nicola Soranzo +
* Nimish Telang +
* OBATA Akio +
* Oleksandr Pavlyk
* Ori Broda +
* Paul Ivanov
* Pauli Virtanen
* Peter Andreas Entschev +
* Peter Bell +
* Pierre de Buyl
* Piyush Jaipuriayar +
* Prithvi MK +
* Raghuveer Devulapalli +
* Ralf Gommers
* Richard Harris +
* Rishabh Chakrabarti +
* Riya Sharma +
* Robert Kern
* Roman Yurchak
* Ryan Levy +
* Sebastian Berg
* Sergei Lebedev +
* Shekhar Prasad Rajak +
* Stefan van der Walt
* Stephan Hoyer
* Steve Stagg +
* SuryaChand P +
* Søren Rasmussen +
* Thibault Hallouin +
* Thomas A Caswell
* Tobias Uelwer +
* Tony LaTorre +
* Toshiki Kataoka
* Tyler Moncur +
* Tyler Reddy
* Valentin Haenel
* Vrinda Narayan +
* Warren Weckesser
* Weitang Li
* Wojtek Ruszczewski
* Yu Feng
* Yu Kobayashi +
* Yury Kirienko +
* aashuli +
* luzpaz
* parul +
* spacescientist +
Pull requests merged
====================
A total of 531 pull requests were merged for this release.
* `#4808 <https://github.com/numpy/numpy/pull/4808>`__: ENH: Make the `mode` parameter of np.pad default to 'constant'
* `#8131 <https://github.com/numpy/numpy/pull/8131>`__: BUG: Fix help() formatting for deprecated functions.
* `#8159 <https://github.com/numpy/numpy/pull/8159>`__: ENH: Add import time benchmarks.
* `#8641 <https://github.com/numpy/numpy/pull/8641>`__: BUG: Preserve types of empty arrays in ix_ when known
* `#8662 <https://github.com/numpy/numpy/pull/8662>`__: ENH: preserve subclasses in ufunc.outer
* `#9330 <https://github.com/numpy/numpy/pull/9330>`__: ENH: Make errstate a ContextDecorator in Python3
* `#10308 <https://github.com/numpy/numpy/pull/10308>`__: API: Make MaskedArray.mask return a view, rather than the underlying...
* `#10417 <https://github.com/numpy/numpy/pull/10417>`__: ENH: Allow dtype objects to be indexed with multiple fields at...
* `#10723 <https://github.com/numpy/numpy/pull/10723>`__: BUG: longdouble(int) does not work
* `#10741 <https://github.com/numpy/numpy/pull/10741>`__: ENH: Implement `np.floating.as_integer_ratio`
* `#10855 <https://github.com/numpy/numpy/pull/10855>`__: ENH: Adding a count parameter to np.unpackbits
* `#11230 <https://github.com/numpy/numpy/pull/11230>`__: MAINT: More cleanup of einsum
* `#11233 <https://github.com/numpy/numpy/pull/11233>`__: BUG: ensure i0 does not change the shape.
* `#11684 <https://github.com/numpy/numpy/pull/11684>`__: BUG: Raise when unravel_index, ravel_multi_index are given empty...
* `#11689 <https://github.com/numpy/numpy/pull/11689>`__: DOC: Add ref docs for C generic types.
* `#11721 <https://github.com/numpy/numpy/pull/11721>`__: BUG: Make `arr.ctypes.data` hold onto a reference to the underlying...
* `#11829 <https://github.com/numpy/numpy/pull/11829>`__: MAINT: Use textwrap.dedent in f2py tests
* `#11859 <https://github.com/numpy/numpy/pull/11859>`__: BUG: test and fix np.dtype('i,L') #5645
* `#11888 <https://github.com/numpy/numpy/pull/11888>`__: ENH: Add pocketfft sources to numpy for testing, benchmarks,...
* `#11977 <https://github.com/numpy/numpy/pull/11977>`__: BUG: reference cycle in np.vectorize
* `#12025 <https://github.com/numpy/numpy/pull/12025>`__: DOC: add detail for 'where' argument in ufunc
* `#12152 <https://github.com/numpy/numpy/pull/12152>`__: TST: Added tests for np.tensordot()
* `#12201 <https://github.com/numpy/numpy/pull/12201>`__: TST: coverage for _commonType()
* `#12234 <https://github.com/numpy/numpy/pull/12234>`__: MAINT: refactor PyArray_AdaptFlexibleDType to return a meaningful...
* `#12239 <https://github.com/numpy/numpy/pull/12239>`__: BUG: polyval returned non-masked arrays for masked input.
* `#12253 <https://github.com/numpy/numpy/pull/12253>`__: DOC, TST: enable doctests
* `#12308 <https://github.com/numpy/numpy/pull/12308>`__: ENH: add mm->q floordiv
* `#12317 <https://github.com/numpy/numpy/pull/12317>`__: ENH: port np.core.overrides to C for speed
* `#12333 <https://github.com/numpy/numpy/pull/12333>`__: DOC: update description of the Dirichlet distribution
* `#12418 <https://github.com/numpy/numpy/pull/12418>`__: ENH: Add timsort to npysort
* `#12428 <https://github.com/numpy/numpy/pull/12428>`__: ENH: always use zip64, upgrade pickle protocol to 3
* `#12456 <https://github.com/numpy/numpy/pull/12456>`__: ENH: Add np.ctypeslib.as_ctypes_type(dtype), improve `np.ctypeslib.as_ctypes`
* `#12457 <https://github.com/numpy/numpy/pull/12457>`__: TST: openblas for Azure MacOS
* `#12463 <https://github.com/numpy/numpy/pull/12463>`__: DOC: fix docstrings for broadcastable inputs in ufunc
* `#12502 <https://github.com/numpy/numpy/pull/12502>`__: TST: Azure Python version fix
* `#12506 <https://github.com/numpy/numpy/pull/12506>`__: MAINT: Prepare master for 1.17.0 development.
* `#12508 <https://github.com/numpy/numpy/pull/12508>`__: DOC, MAINT: Make `PYVER = 3` in doc/Makefile.
* `#12511 <https://github.com/numpy/numpy/pull/12511>`__: BUG: don't check alignment of size=0 arrays (RELAXED_STRIDES)
* `#12512 <https://github.com/numpy/numpy/pull/12512>`__: added template-generated files to .gitignore
* `#12519 <https://github.com/numpy/numpy/pull/12519>`__: ENH/DEP: Use a ufunc under the hood for ndarray.clip
* `#12522 <https://github.com/numpy/numpy/pull/12522>`__: BUG: Make new-lines in compiler error messages print to the console
* `#12524 <https://github.com/numpy/numpy/pull/12524>`__: BUG: fix improper use of C-API
* `#12526 <https://github.com/numpy/numpy/pull/12526>`__: BUG: reorder operations for VS2015
* `#12527 <https://github.com/numpy/numpy/pull/12527>`__: DEV: Fix lgtm.com C/C++ build
* `#12528 <https://github.com/numpy/numpy/pull/12528>`__: BUG: fix an unsafe PyTuple_GET_ITEM call
* `#12532 <https://github.com/numpy/numpy/pull/12532>`__: DEV: add ctags option file
* `#12534 <https://github.com/numpy/numpy/pull/12534>`__: DOC: Fix desc. of Ellipsis behavior in reference
* `#12537 <https://github.com/numpy/numpy/pull/12537>`__: DOC: Change 'num' to 'np'
* `#12538 <https://github.com/numpy/numpy/pull/12538>`__: MAINT: remove VC 9.0 from CI
* `#12539 <https://github.com/numpy/numpy/pull/12539>`__: DEV: remove travis 32 bit job since it is running on azure
* `#12543 <https://github.com/numpy/numpy/pull/12543>`__: TST: wheel-match Linux openblas in CI
* `#12544 <https://github.com/numpy/numpy/pull/12544>`__: BUG: fix refcount issue caused by #12524
* `#12545 <https://github.com/numpy/numpy/pull/12545>`__: BUG: Ensure probabilities are not NaN in choice
* `#12546 <https://github.com/numpy/numpy/pull/12546>`__: BUG: check for errors after PyArray_DESCR_REPLACE
* `#12547 <https://github.com/numpy/numpy/pull/12547>`__: ENH: Cast covariance to double in random mvnormal
* `#12549 <https://github.com/numpy/numpy/pull/12549>`__: TST: relax codecov project threshold
* `#12551 <https://github.com/numpy/numpy/pull/12551>`__: MAINT: add warning to numpy.distutils for LDFLAGS append behavior.
* `#12552 <https://github.com/numpy/numpy/pull/12552>`__: BENCH: Improve benchmarks for numpy.pad
* `#12554 <https://github.com/numpy/numpy/pull/12554>`__: DOC: more doc updates for structured arrays
* `#12555 <https://github.com/numpy/numpy/pull/12555>`__: BUG: only override vector size for avx code
* `#12560 <https://github.com/numpy/numpy/pull/12560>`__: DOC: fix some doctest failures
* `#12566 <https://github.com/numpy/numpy/pull/12566>`__: BUG: fix segfault in ctypeslib with obj being collected
* `#12571 <https://github.com/numpy/numpy/pull/12571>`__: Revert "Merge pull request #11721 from eric-wieser/fix-9647"
* `#12572 <https://github.com/numpy/numpy/pull/12572>`__: BUG: Make `arr.ctypes.data` hold a reference to the underlying...
* `#12575 <https://github.com/numpy/numpy/pull/12575>`__: ENH: improve performance for numpy.core.records.find_duplicate
* `#12577 <https://github.com/numpy/numpy/pull/12577>`__: BUG: fix f2py pep338 execution method
* `#12578 <https://github.com/numpy/numpy/pull/12578>`__: TST: activate shippable maintenance branches
* `#12583 <https://github.com/numpy/numpy/pull/12583>`__: TST: add test for 'python -mnumpy.f2py'
* `#12584 <https://github.com/numpy/numpy/pull/12584>`__: Clarify skiprows in loadtxt
* `#12586 <https://github.com/numpy/numpy/pull/12586>`__: ENH: Implement radix sort
* `#12589 <https://github.com/numpy/numpy/pull/12589>`__: MAINT: Update changelog.py for Python 3.
* `#12591 <https://github.com/numpy/numpy/pull/12591>`__: ENH: add "max difference" messages to np.testing.assert_array_equal
* `#12592 <https://github.com/numpy/numpy/pull/12592>`__: BUG,TST: Remove the misguided `run_command` that wraps subprocess
* `#12593 <https://github.com/numpy/numpy/pull/12593>`__: ENH,WIP: Use richer exception types for ufunc type resolution...
* `#12594 <https://github.com/numpy/numpy/pull/12594>`__: DEV, BUILD: add pypy3 to azure CI
* `#12596 <https://github.com/numpy/numpy/pull/12596>`__: ENH: improve performance of numpy.core.records.fromarrays
* `#12601 <https://github.com/numpy/numpy/pull/12601>`__: DOC: Correct documentation of `numpy.delete` obj parameter.
* `#12602 <https://github.com/numpy/numpy/pull/12602>`__: DOC: Update RELEASE_WALKTHROUGH.rst.txt.
* `#12604 <https://github.com/numpy/numpy/pull/12604>`__: BUG: Check that dtype and formats arguments for None.
* `#12606 <https://github.com/numpy/numpy/pull/12606>`__: DOC: Document NPY_SORTKIND parameter in PyArray_Sort
* `#12608 <https://github.com/numpy/numpy/pull/12608>`__: MAINT: Use `*.format` for some strings.
* `#12609 <https://github.com/numpy/numpy/pull/12609>`__: ENH: Deprecate writeable broadcast_array
* `#12610 <https://github.com/numpy/numpy/pull/12610>`__: TST: Update runtests.py to specify C99 for gcc.
* `#12611 <https://github.com/numpy/numpy/pull/12611>`__: BUG: longdouble with elsize 12 is never uint alignable
* `#12612 <https://github.com/numpy/numpy/pull/12612>`__: TST: Update `travis-test.sh` for C99
* `#12616 <https://github.com/numpy/numpy/pull/12616>`__: BLD: Fix minimum Python version in setup.py
* `#12617 <https://github.com/numpy/numpy/pull/12617>`__: BUG: Add missing free in ufunc dealloc
* `#12618 <https://github.com/numpy/numpy/pull/12618>`__: MAINT: add test for 12-byte alignment
* `#12620 <https://github.com/numpy/numpy/pull/12620>`__: BLD: move -std=c99 addition to CFLAGS to Azure config
* `#12624 <https://github.com/numpy/numpy/pull/12624>`__: BUG: Fix incorrect/missing reference cleanups found using valgrind
* `#12626 <https://github.com/numpy/numpy/pull/12626>`__: BUG: fix uint alignment asserts in lowlevel loops
* `#12631 <https://github.com/numpy/numpy/pull/12631>`__: BUG: fix f2py problem to build wrappers using PGI's Fortran
* `#12634 <https://github.com/numpy/numpy/pull/12634>`__: DOC, TST: remove "agg" setting from docs
* `#12639 <https://github.com/numpy/numpy/pull/12639>`__: BENCH: don't fail at import time with old Numpy
* `#12641 <https://github.com/numpy/numpy/pull/12641>`__: DOC: update 2018 -> 2019
* `#12644 <https://github.com/numpy/numpy/pull/12644>`__: ENH: where for ufunc reductions
* `#12645 <https://github.com/numpy/numpy/pull/12645>`__: DOC: Minor fix to pocketfft release note
* `#12650 <https://github.com/numpy/numpy/pull/12650>`__: BUG: Fix reference counting for subarrays containing objects
* `#12651 <https://github.com/numpy/numpy/pull/12651>`__: DOC: SimpleNewFromDescr cannot be given NULL for descr
* `#12666 <https://github.com/numpy/numpy/pull/12666>`__: BENCH: add asv nanfunction benchmarks
* `#12668 <https://github.com/numpy/numpy/pull/12668>`__: ENH: Improve error messages for non-matching shapes in concatenate.
* `#12671 <https://github.com/numpy/numpy/pull/12671>`__: TST: Fix endianness in unstuctured_to_structured test
* `#12672 <https://github.com/numpy/numpy/pull/12672>`__: BUG: Add 'sparc' to platforms implementing 16 byte reals.
* `#12677 <https://github.com/numpy/numpy/pull/12677>`__: MAINT: Further fixups to uint alignment checks
* `#12679 <https://github.com/numpy/numpy/pull/12679>`__: ENH: remove "Invalid value" warnings from median, percentile
* `#12680 <https://github.com/numpy/numpy/pull/12680>`__: BUG: Ensure failing memory allocations are reported
* `#12683 <https://github.com/numpy/numpy/pull/12683>`__: ENH: add mm->qm divmod
* `#12684 <https://github.com/numpy/numpy/pull/12684>`__: DEV: remove _arg from public API, add matmul to benchmark ufuncs
* `#12685 <https://github.com/numpy/numpy/pull/12685>`__: BUG: Make pocketfft handle long doubles.
* `#12687 <https://github.com/numpy/numpy/pull/12687>`__: ENH: Better links in documentation
* `#12690 <https://github.com/numpy/numpy/pull/12690>`__: WIP, ENH: add _nan_mask function
* `#12693 <https://github.com/numpy/numpy/pull/12693>`__: ENH: Add a hermitian argument to `pinv` and `svd`, matching `matrix_rank`
* `#12696 <https://github.com/numpy/numpy/pull/12696>`__: BUG: Fix leak of void scalar buffer info
* `#12698 <https://github.com/numpy/numpy/pull/12698>`__: DOC: improve comments in copycast_isaligned
* `#12700 <https://github.com/numpy/numpy/pull/12700>`__: ENH: chain additional exception on ufunc method lookup error
* `#12702 <https://github.com/numpy/numpy/pull/12702>`__: TST: Check FFT results for C/Fortran ordered and non contiguous...
* `#12704 <https://github.com/numpy/numpy/pull/12704>`__: TST: pin Azure brew version for stability
* `#12709 <https://github.com/numpy/numpy/pull/12709>`__: TST: add ppc64le to Travis CI matrix
* `#12713 <https://github.com/numpy/numpy/pull/12713>`__: BUG: loosen kwargs requirements in ediff1d
* `#12722 <https://github.com/numpy/numpy/pull/12722>`__: BUG: Fix rounding of denormals in double and float to half casts...
* `#12723 <https://github.com/numpy/numpy/pull/12723>`__: BENCH: Include other sort benchmarks
* `#12724 <https://github.com/numpy/numpy/pull/12724>`__: BENCH: quiet DeprecationWarning
* `#12727 <https://github.com/numpy/numpy/pull/12727>`__: DOC: fix and doctest tutorial
* `#12728 <https://github.com/numpy/numpy/pull/12728>`__: DOC: clarify the suffix of single/extended precision math constants
* `#12729 <https://github.com/numpy/numpy/pull/12729>`__: DOC: Extend documentation of `ndarray.tolist`
* `#12731 <https://github.com/numpy/numpy/pull/12731>`__: DOC: Update release notes and changelog after 1.16.0 release.
* `#12733 <https://github.com/numpy/numpy/pull/12733>`__: DOC: clarify the extend of __array_function__ support in NumPy...
* `#12741 <https://github.com/numpy/numpy/pull/12741>`__: DOC: fix generalized eigenproblem reference in "NumPy for MATLAB...
* `#12743 <https://github.com/numpy/numpy/pull/12743>`__: BUG: Fix crash in error message formatting introduced by gh-11230
* `#12748 <https://github.com/numpy/numpy/pull/12748>`__: BUG: Fix SystemError when pickling datetime64 array with pickle5
* `#12757 <https://github.com/numpy/numpy/pull/12757>`__: BUG: Added parens to macro argument expansions
* `#12758 <https://github.com/numpy/numpy/pull/12758>`__: DOC: Update docstring of diff() to use 'i' not 'n'
* `#12762 <https://github.com/numpy/numpy/pull/12762>`__: MAINT: Change the order of checking for locale file and import...
* `#12783 <https://github.com/numpy/numpy/pull/12783>`__: DOC: document C99 requirement in dev guide
* `#12787 <https://github.com/numpy/numpy/pull/12787>`__: DOC: remove recommendation to add main for testing
* `#12805 <https://github.com/numpy/numpy/pull/12805>`__: BUG: double decref of dtype in failure codepath. Test and fix
* `#12807 <https://github.com/numpy/numpy/pull/12807>`__: BUG, DOC: test, fix that f2py.compile accepts str and bytes,...
* `#12814 <https://github.com/numpy/numpy/pull/12814>`__: BUG: resolve writeback in arr_insert failure paths
* `#12815 <https://github.com/numpy/numpy/pull/12815>`__: BUG: Fix testing of f2py.compile from strings.
* `#12818 <https://github.com/numpy/numpy/pull/12818>`__: DOC: remove python2-only methods, small cleanups
* `#12824 <https://github.com/numpy/numpy/pull/12824>`__: BUG: fix to check before apply `shlex.split`
* `#12830 <https://github.com/numpy/numpy/pull/12830>`__: ENH: __array_function__ updates for NumPy 1.17.0
* `#12831 <https://github.com/numpy/numpy/pull/12831>`__: BUG: Catch stderr when checking compiler version
* `#12842 <https://github.com/numpy/numpy/pull/12842>`__: BUG: ndarrays pickled by 1.16 cannot be loaded by 1.15.4 and...
* `#12846 <https://github.com/numpy/numpy/pull/12846>`__: BUG: fix signed zero behavior in npy_divmod
* `#12850 <https://github.com/numpy/numpy/pull/12850>`__: BUG: fail if old multiarray module detected
* `#12851 <https://github.com/numpy/numpy/pull/12851>`__: TEST: use xenial by default for travis
* `#12854 <https://github.com/numpy/numpy/pull/12854>`__: BUG: do not Py_DECREF NULL pointer
* `#12857 <https://github.com/numpy/numpy/pull/12857>`__: STY: simplify code
* `#12863 <https://github.com/numpy/numpy/pull/12863>`__: TEST: pin mingw version
* `#12866 <https://github.com/numpy/numpy/pull/12866>`__: DOC: link to benchmarking info
* `#12867 <https://github.com/numpy/numpy/pull/12867>`__: TST: Use same OpenBLAS build for testing as for current wheels.
* `#12871 <https://github.com/numpy/numpy/pull/12871>`__: ENH: add c-imported modules to namespace for freeze analysis
* `#12877 <https://github.com/numpy/numpy/pull/12877>`__: Remove deprecated ``sudo: false`` from .travis.yml
* `#12879 <https://github.com/numpy/numpy/pull/12879>`__: DEP: deprecate exec_command
* `#12885 <https://github.com/numpy/numpy/pull/12885>`__: DOC: fix math formatting of np.linalg.lstsq docs
* `#12886 <https://github.com/numpy/numpy/pull/12886>`__: DOC: add missing character routines, fix #8578
* `#12887 <https://github.com/numpy/numpy/pull/12887>`__: BUG: Fix np.rec.fromarrays on arrays which are already structured
* `#12889 <https://github.com/numpy/numpy/pull/12889>`__: BUG: Make allow_pickle=False the default for loading
* `#12892 <https://github.com/numpy/numpy/pull/12892>`__: BUG: Do not double-quote arguments passed on to the linker
* `#12894 <https://github.com/numpy/numpy/pull/12894>`__: MAINT: Removed unused and confusingly indirect imports from mingw32ccompiler
* `#12895 <https://github.com/numpy/numpy/pull/12895>`__: BUG: Do not insert extra double quote into preprocessor macros
* `#12903 <https://github.com/numpy/numpy/pull/12903>`__: TST: fix vmImage dispatch in Azure
* `#12905 <https://github.com/numpy/numpy/pull/12905>`__: BUG: fix byte order reversal for datetime64[ns]
* `#12908 <https://github.com/numpy/numpy/pull/12908>`__: DOC: Update master following 1.16.1 release.
* `#12911 <https://github.com/numpy/numpy/pull/12911>`__: BLD: fix doc build for distribution.
* `#12915 <https://github.com/numpy/numpy/pull/12915>`__: ENH: pathlib support for fromfile(), .tofile() and .dump()
* `#12920 <https://github.com/numpy/numpy/pull/12920>`__: MAINT: remove complicated test of multiarray import failure mode
* `#12922 <https://github.com/numpy/numpy/pull/12922>`__: DOC: Add note about arbitrary code execution to numpy.load
* `#12925 <https://github.com/numpy/numpy/pull/12925>`__: BUG: parse shell escaping in extra_compile_args and extra_link_args
* `#12928 <https://github.com/numpy/numpy/pull/12928>`__: MAINT: Merge together the unary and binary type resolvers
* `#12929 <https://github.com/numpy/numpy/pull/12929>`__: DOC: fix documentation bug in np.argsort and extend examples
* `#12931 <https://github.com/numpy/numpy/pull/12931>`__: MAINT: Remove recurring check
* `#12932 <https://github.com/numpy/numpy/pull/12932>`__: BUG: do not dereference NULL pointer
* `#12937 <https://github.com/numpy/numpy/pull/12937>`__: DOC: Correct negative_binomial docstring
* `#12944 <https://github.com/numpy/numpy/pull/12944>`__: BUG: Make timsort deal with zero length elements.
* `#12945 <https://github.com/numpy/numpy/pull/12945>`__: BUG: Add timsort without breaking the API.
* `#12949 <https://github.com/numpy/numpy/pull/12949>`__: DOC: ndarray.max is missing
* `#12962 <https://github.com/numpy/numpy/pull/12962>`__: ENH: Add 'bitorder' keyword to packbits, unpackbits
* `#12963 <https://github.com/numpy/numpy/pull/12963>`__: DOC: Grammatical fix in numpy doc
* `#12964 <https://github.com/numpy/numpy/pull/12964>`__: DOC: Document that ``scale==0`` is now allowed in many distributions.
* `#12965 <https://github.com/numpy/numpy/pull/12965>`__: DOC: Properly format Return section of ogrid Docstring,
* `#12968 <https://github.com/numpy/numpy/pull/12968>`__: BENCH: Re-write sorting benchmarks
* `#12971 <https://github.com/numpy/numpy/pull/12971>`__: ENH: Add 'offset' keyword to 'numpy.fromfile()'
* `#12973 <https://github.com/numpy/numpy/pull/12973>`__: DOC: Recommend adding dimension to switch between row and column...
* `#12983 <https://github.com/numpy/numpy/pull/12983>`__: DOC: Randomstate docstring fixes
* `#12984 <https://github.com/numpy/numpy/pull/12984>`__: DOC: Add examples of negative shifts in np.roll
* `#12986 <https://github.com/numpy/numpy/pull/12986>`__: BENCH: set ones in any/all benchmarks to 1 instead of 0
* `#12988 <https://github.com/numpy/numpy/pull/12988>`__: ENH: Create boolean and integer ufuncs for isnan, isinf, and...
* `#12989 <https://github.com/numpy/numpy/pull/12989>`__: ENH: Correct handling of infinities in np.interp (option B)
* `#12995 <https://github.com/numpy/numpy/pull/12995>`__: BUG: Add missing PyErr_NoMemory() for reporting a failed malloc
* `#12996 <https://github.com/numpy/numpy/pull/12996>`__: MAINT: Use the same multiplication order in interp for cached...
* `#13002 <https://github.com/numpy/numpy/pull/13002>`__: DOC: reduce warnings when building, and rephrase slightly
* `#13004 <https://github.com/numpy/numpy/pull/13004>`__: MAINT: minor changes for consistency to site.cfg.example
* `#13008 <https://github.com/numpy/numpy/pull/13008>`__: MAINT: Move pickle import to numpy.compat
* `#13019 <https://github.com/numpy/numpy/pull/13019>`__: BLD: Windows absolute path DLL loading
* `#13023 <https://github.com/numpy/numpy/pull/13023>`__: BUG: Changes to string-to-shell parsing behavior broke paths...
* `#13027 <https://github.com/numpy/numpy/pull/13027>`__: BUG: Fix regression in parsing of F90 and F77 environment variables
* `#13031 <https://github.com/numpy/numpy/pull/13031>`__: MAINT: Replace if statement with a dictionary lookup for ease...
* `#13032 <https://github.com/numpy/numpy/pull/13032>`__: MAINT: Extract the loop macros into their own header
* `#13033 <https://github.com/numpy/numpy/pull/13033>`__: MAINT: Convert property to @property
* `#13035 <https://github.com/numpy/numpy/pull/13035>`__: DOC: Draw more attention to which functions in random are convenience...
* `#13036 <https://github.com/numpy/numpy/pull/13036>`__: BUG: __array_interface__ offset was always ignored
* `#13039 <https://github.com/numpy/numpy/pull/13039>`__: BUG: Remove error-prone borrowed reference handling
* `#13044 <https://github.com/numpy/numpy/pull/13044>`__: DOC: link to devdocs in README
* `#13046 <https://github.com/numpy/numpy/pull/13046>`__: ENH: Add shape to *_like() array creation
* `#13049 <https://github.com/numpy/numpy/pull/13049>`__: MAINT: remove undocumented __buffer__ attribute lookup
* `#13050 <https://github.com/numpy/numpy/pull/13050>`__: BLD: make doc build work more robustly.
* `#13054 <https://github.com/numpy/numpy/pull/13054>`__: DOC: Added maximum_sctype to documentation
* `#13055 <https://github.com/numpy/numpy/pull/13055>`__: DOC: Post NumPy 1.16.2 release update.
* `#13056 <https://github.com/numpy/numpy/pull/13056>`__: BUG: Fixes to numpy.distutils.Configuration.get_version
* `#13058 <https://github.com/numpy/numpy/pull/13058>`__: DOC: update docstring in numpy.interp docstring
* `#13060 <https://github.com/numpy/numpy/pull/13060>`__: BUG: Use C call to sysctlbyname for AVX detection on MacOS
* `#13063 <https://github.com/numpy/numpy/pull/13063>`__: DOC: revert PR #13058 and fixup Makefile
* `#13067 <https://github.com/numpy/numpy/pull/13067>`__: MAINT: Use with statements for opening files in distutils
* `#13068 <https://github.com/numpy/numpy/pull/13068>`__: BUG: Add error checks when converting integers to datetime types
* `#13071 <https://github.com/numpy/numpy/pull/13071>`__: DOC: Removed incorrect claim regarding shape constraints for...
* `#13073 <https://github.com/numpy/numpy/pull/13073>`__: MAINT: Fix ABCPolyBase in various ways
* `#13075 <https://github.com/numpy/numpy/pull/13075>`__: BUG: Convert fortran flags in environment variable
* `#13076 <https://github.com/numpy/numpy/pull/13076>`__: BUG: Remove our patched version of `distutils.split_quoted`
* `#13077 <https://github.com/numpy/numpy/pull/13077>`__: BUG: Fix errors in string formatting while producing an error
* `#13078 <https://github.com/numpy/numpy/pull/13078>`__: MAINT: deduplicate fromroots in np.polynomial
* `#13079 <https://github.com/numpy/numpy/pull/13079>`__: MAINT: Merge duplicate implementations of `*vander2d` and `*vander3d`...
* `#13086 <https://github.com/numpy/numpy/pull/13086>`__: BLD: fix include list for sdist building
* `#13090 <https://github.com/numpy/numpy/pull/13090>`__: BUILD: sphinx 1.8.3 can be used with our outdated templates
* `#13092 <https://github.com/numpy/numpy/pull/13092>`__: BUG: ensure linspace works on object input.
* `#13093 <https://github.com/numpy/numpy/pull/13093>`__: BUG: Fix parameter validity checks in ``random.choice``.
* `#13095 <https://github.com/numpy/numpy/pull/13095>`__: BUG: Fix testsuite failures on ppc and riscv
* `#13096 <https://github.com/numpy/numpy/pull/13096>`__: TEST: allow refcheck result to vary, increase discoverability...
* `#13097 <https://github.com/numpy/numpy/pull/13097>`__: DOC: update doc of `ndarray.T`
* `#13099 <https://github.com/numpy/numpy/pull/13099>`__: DOC: Add note about "copy and slicing"
* `#13104 <https://github.com/numpy/numpy/pull/13104>`__: DOC: fix references in docs
* `#13107 <https://github.com/numpy/numpy/pull/13107>`__: MAINT: Unify polynomial valnd functions
* `#13108 <https://github.com/numpy/numpy/pull/13108>`__: MAINT: Merge duplicate implementations of `hermvander2d` and...
* `#13109 <https://github.com/numpy/numpy/pull/13109>`__: Prevent traceback chaining in _wrapfunc.
* `#13111 <https://github.com/numpy/numpy/pull/13111>`__: MAINT: Unify polydiv
* `#13115 <https://github.com/numpy/numpy/pull/13115>`__: DOC: Fix #12050 by updating numpy.random.hypergeometric docs
* `#13116 <https://github.com/numpy/numpy/pull/13116>`__: DOC: Add backticks in linalg docstrings.
* `#13117 <https://github.com/numpy/numpy/pull/13117>`__: DOC: Fix arg type for np.pad, fix #9489
* `#13118 <https://github.com/numpy/numpy/pull/13118>`__: DOC: update scipy-sphinx-theme, fixes search
* `#13119 <https://github.com/numpy/numpy/pull/13119>`__: DOC: Fix c-api function documentation duplication.
* `#13125 <https://github.com/numpy/numpy/pull/13125>`__: BUG: Fix unhandled exception in CBLAS detection
* `#13126 <https://github.com/numpy/numpy/pull/13126>`__: DEP: polynomial: Be stricter about integral arguments
* `#13127 <https://github.com/numpy/numpy/pull/13127>`__: DOC: Tidy 1.17.0 release note newlines
* `#13128 <https://github.com/numpy/numpy/pull/13128>`__: MAINT: Unify polynomial addition and subtraction functions
* `#13130 <https://github.com/numpy/numpy/pull/13130>`__: MAINT: Unify polynomial fitting functions
* `#13131 <https://github.com/numpy/numpy/pull/13131>`__: BUILD: use 'quiet' when building docs
* `#13132 <https://github.com/numpy/numpy/pull/13132>`__: BLD: Allow users to specify BLAS and LAPACK library link order
* `#13134 <https://github.com/numpy/numpy/pull/13134>`__: ENH: Use AVX for float32 implementation of np.exp & np.log
* `#13137 <https://github.com/numpy/numpy/pull/13137>`__: BUG: Fix build for glibc on ARC and uclibc.
* `#13140 <https://github.com/numpy/numpy/pull/13140>`__: DEV: cleanup imports and some assignments (from LGTM)
* `#13146 <https://github.com/numpy/numpy/pull/13146>`__: MAINT: Unify polynomial power functions
* `#13147 <https://github.com/numpy/numpy/pull/13147>`__: DOC: Add description of overflow errors
* `#13149 <https://github.com/numpy/numpy/pull/13149>`__: DOC: correction to numpy.pad docstring
* `#13157 <https://github.com/numpy/numpy/pull/13157>`__: BLD: streamlined library names in site.cfg sections
* `#13158 <https://github.com/numpy/numpy/pull/13158>`__: BLD: Add libflame as a LAPACK back-end
* `#13161 <https://github.com/numpy/numpy/pull/13161>`__: BLD: streamlined CBLAS linkage tries, default to try libraries...
* `#13162 <https://github.com/numpy/numpy/pull/13162>`__: BUILD: update numpydoc to latest version
* `#13163 <https://github.com/numpy/numpy/pull/13163>`__: ENH: randomgen
* `#13169 <https://github.com/numpy/numpy/pull/13169>`__: STY: Fix weird indents to be multiples of 4 spaces
* `#13170 <https://github.com/numpy/numpy/pull/13170>`__: DOC, BUILD: fail the devdoc build if there are warnings
* `#13174 <https://github.com/numpy/numpy/pull/13174>`__: DOC: Removed some c-api duplication
* `#13176 <https://github.com/numpy/numpy/pull/13176>`__: BUG: fix reference count error on invalid input to ndarray.flat
* `#13181 <https://github.com/numpy/numpy/pull/13181>`__: BENCH, BUG: fix Savez suite, previously was actually calling...
* `#13182 <https://github.com/numpy/numpy/pull/13182>`__: MAINT: add overlap checks to choose, take, put, putmask
* `#13188 <https://github.com/numpy/numpy/pull/13188>`__: MAINT: Simplify logic in convert_datetime_to_datetimestruct
* `#13202 <https://github.com/numpy/numpy/pull/13202>`__: ENH: use rotated companion matrix to reduce error
* `#13203 <https://github.com/numpy/numpy/pull/13203>`__: DOC: Use std docstring for multivariate normal
* `#13205 <https://github.com/numpy/numpy/pull/13205>`__: DOC : Fix C-API documentation references to items that don't...
* `#13206 <https://github.com/numpy/numpy/pull/13206>`__: BUILD: pin sphinx to 1.8.5
* `#13208 <https://github.com/numpy/numpy/pull/13208>`__: MAINT: cleanup of fast_loop_macros.h
* `#13216 <https://github.com/numpy/numpy/pull/13216>`__: Adding an example of successful execution of numpy.test() to...
* `#13217 <https://github.com/numpy/numpy/pull/13217>`__: TST: always publish Azure tests
* `#13218 <https://github.com/numpy/numpy/pull/13218>`__: ENH: `isfinite` support for `datetime64` and `timedelta64`
* `#13219 <https://github.com/numpy/numpy/pull/13219>`__: ENH: nan_to_num keyword addition (was #9355)
* `#13222 <https://github.com/numpy/numpy/pull/13222>`__: DOC: Document/ Deprecate functions exposed in "numpy" namespace
* `#13224 <https://github.com/numpy/numpy/pull/13224>`__: Improve error message for negative valued argument
* `#13226 <https://github.com/numpy/numpy/pull/13226>`__: DOC: Fix small issues in mtrand doc strings
* `#13231 <https://github.com/numpy/numpy/pull/13231>`__: DOC: Change the required Sphinx version to build documentation
* `#13234 <https://github.com/numpy/numpy/pull/13234>`__: DOC : PyArray_Descr.names undocumented
* `#13239 <https://github.com/numpy/numpy/pull/13239>`__: DOC: Minor grammatical fixes in NumPy docs
* `#13242 <https://github.com/numpy/numpy/pull/13242>`__: DOC: fix docstring for floor_divide
* `#13243 <https://github.com/numpy/numpy/pull/13243>`__: MAINT: replace SETREF with assignment to ret array in ndarray.flat
* `#13244 <https://github.com/numpy/numpy/pull/13244>`__: DOC: Improve mtrand docstrings
* `#13250 <https://github.com/numpy/numpy/pull/13250>`__: MAINT: Improve efficiency of pad by avoiding use of apply_along_axis
* `#13253 <https://github.com/numpy/numpy/pull/13253>`__: TST: fail Azure CI if test failures
* `#13259 <https://github.com/numpy/numpy/pull/13259>`__: DOC: Small readability improvement
* `#13262 <https://github.com/numpy/numpy/pull/13262>`__: DOC : Correcting bug on Documentation Page (Byteswapping)
* `#13264 <https://github.com/numpy/numpy/pull/13264>`__: TST: use OpenBLAS v0.3.5 for POWER8 CI runs
* `#13269 <https://github.com/numpy/numpy/pull/13269>`__: BUG, MAINT: f2py: Add a cast to avoid a compiler warning.
* `#13270 <https://github.com/numpy/numpy/pull/13270>`__: TST: use OpenBLAS v0.3.5 for ARMv8 CI
* `#13271 <https://github.com/numpy/numpy/pull/13271>`__: ENH: vectorize np.abs for unsigned ints and half, improving performance...
* `#13273 <https://github.com/numpy/numpy/pull/13273>`__: BUG: Fix null pointer dereference in PyArray_DTypeFromObject
* `#13277 <https://github.com/numpy/numpy/pull/13277>`__: DOC: Document caveat in random.uniform
* `#13287 <https://github.com/numpy/numpy/pull/13287>`__: Add benchmark for sorting random array.
* `#13289 <https://github.com/numpy/numpy/pull/13289>`__: DOC: add Quansight Labs as an Institutional Partner
* `#13291 <https://github.com/numpy/numpy/pull/13291>`__: MAINT: fix unused variable warning in npy_math_complex.c.src
* `#13292 <https://github.com/numpy/numpy/pull/13292>`__: DOC: update numpydoc to latest master
* `#13293 <https://github.com/numpy/numpy/pull/13293>`__: DOC: add more info to failure message
* `#13298 <https://github.com/numpy/numpy/pull/13298>`__: ENH: Added clearer exception for np.diff on 0-dimensional ndarray
* `#13301 <https://github.com/numpy/numpy/pull/13301>`__: BUG: Fix crash when calling savetxt on a padded array
* `#13305 <https://github.com/numpy/numpy/pull/13305>`__: NEP: Update NEP-18 to include the ``__skip_array_function__``...
* `#13306 <https://github.com/numpy/numpy/pull/13306>`__: MAINT: better MemoryError message (#13225)
* `#13309 <https://github.com/numpy/numpy/pull/13309>`__: DOC: list Quansight rather than Quansight Labs as Institutional...
* `#13310 <https://github.com/numpy/numpy/pull/13310>`__: ENH: Add project_urls to setup
* `#13311 <https://github.com/numpy/numpy/pull/13311>`__: BUG: Fix bad error message in np.memmap
* `#13312 <https://github.com/numpy/numpy/pull/13312>`__: BUG: Close files if an error occurs in genfromtxt
* `#13313 <https://github.com/numpy/numpy/pull/13313>`__: MAINT: fix typo in 'self'
* `#13314 <https://github.com/numpy/numpy/pull/13314>`__: DOC: remove misplaced section at bottom of governance people...
* `#13316 <https://github.com/numpy/numpy/pull/13316>`__: DOC: Added anti-diagonal examples to np.diagonal and np.fill_diagonal
* `#13320 <https://github.com/numpy/numpy/pull/13320>`__: MAINT: remove unused file
* `#13321 <https://github.com/numpy/numpy/pull/13321>`__: MAINT: Move exceptions from core._internal to core._exceptions
* `#13322 <https://github.com/numpy/numpy/pull/13322>`__: MAINT: Move umath error helpers into their own module
* `#13323 <https://github.com/numpy/numpy/pull/13323>`__: BUG: ufunc.at iteration variable size fix
* `#13324 <https://github.com/numpy/numpy/pull/13324>`__: MAINT: Move asarray helpers into their own module
* `#13326 <https://github.com/numpy/numpy/pull/13326>`__: DEP: Deprecate collapsing shape-1 dtype fields to scalars.
* `#13328 <https://github.com/numpy/numpy/pull/13328>`__: MAINT: Tidy up error message for accumulate and reduceat
* `#13331 <https://github.com/numpy/numpy/pull/13331>`__: DOC, BLD: fix doc build issues in preparation for the next numpydoc...
* `#13332 <https://github.com/numpy/numpy/pull/13332>`__: BUG: Always return views from structured_to_unstructured when...
* `#13334 <https://github.com/numpy/numpy/pull/13334>`__: BUG: Fix structured_to_unstructured on single-field types
* `#13335 <https://github.com/numpy/numpy/pull/13335>`__: DOC: Add as_ctypes_type to the documentation
* `#13336 <https://github.com/numpy/numpy/pull/13336>`__: BUILD: fail documentation build if numpy version does not match
* `#13337 <https://github.com/numpy/numpy/pull/13337>`__: DOC: Add docstrings for consistency in aliases
* `#13346 <https://github.com/numpy/numpy/pull/13346>`__: BUG/MAINT: Tidy typeinfo.h and .c
* `#13348 <https://github.com/numpy/numpy/pull/13348>`__: BUG: Return the coefficients array directly
* `#13354 <https://github.com/numpy/numpy/pull/13354>`__: TST: Added test_fftpocket.py::test_axes
* `#13367 <https://github.com/numpy/numpy/pull/13367>`__: DOC: reorganize developer docs, use scikit-image as a base for...
* `#13371 <https://github.com/numpy/numpy/pull/13371>`__: BUG/ENH: Make floor, ceil, and trunc call the matching special...
* `#13374 <https://github.com/numpy/numpy/pull/13374>`__: DOC: Specify range for numpy.angle
* `#13377 <https://github.com/numpy/numpy/pull/13377>`__: DOC: Add missing macros to C API documentation
* `#13379 <https://github.com/numpy/numpy/pull/13379>`__: BLD: address mingw-w64 issue. Follow-up to gh-9977
* `#13383 <https://github.com/numpy/numpy/pull/13383>`__: MAINT, DOC: Post 1.16.3 release updates
* `#13388 <https://github.com/numpy/numpy/pull/13388>`__: BUG: Some PyPy versions lack PyStructSequence_InitType2.
* `#13389 <https://github.com/numpy/numpy/pull/13389>`__: ENH: implement ``__skip_array_function__`` attribute for NEP-18
* `#13390 <https://github.com/numpy/numpy/pull/13390>`__: ENH: Add support for Fraction to percentile and quantile
* `#13391 <https://github.com/numpy/numpy/pull/13391>`__: MAINT, DEP: Fix deprecated ``assertEquals()``
* `#13395 <https://github.com/numpy/numpy/pull/13395>`__: DOC: note re defaults allclose to assert_allclose
* `#13397 <https://github.com/numpy/numpy/pull/13397>`__: DOC: Resolve confusion regarding hashtag in header line of csv
* `#13399 <https://github.com/numpy/numpy/pull/13399>`__: ENH: Improved performance of PyArray_FromAny for sequences of...
* `#13402 <https://github.com/numpy/numpy/pull/13402>`__: DOC: Show the default value of deletechars in the signature of...
* `#13403 <https://github.com/numpy/numpy/pull/13403>`__: DOC: fix typos in dev/index
* `#13404 <https://github.com/numpy/numpy/pull/13404>`__: DOC: Add Sebastian Berg as sponsored by BIDS
* `#13406 <https://github.com/numpy/numpy/pull/13406>`__: DOC: clarify array_{2string,str,repr} defaults
* `#13409 <https://github.com/numpy/numpy/pull/13409>`__: BUG: (py2 only) fix unicode support for savetxt fmt string
* `#13413 <https://github.com/numpy/numpy/pull/13413>`__: DOC: document existence of linalg backends
* `#13415 <https://github.com/numpy/numpy/pull/13415>`__: BUG: fixing bugs in AVX exp/log while handling special value...
* `#13416 <https://github.com/numpy/numpy/pull/13416>`__: BUG: Protect generators from log(0.0)
* `#13417 <https://github.com/numpy/numpy/pull/13417>`__: DOC: dimension sizes are non-negative, not positive
* `#13425 <https://github.com/numpy/numpy/pull/13425>`__: MAINT: fixed typo 'Mismacth' from numpy/core/setup_common.py
* `#13433 <https://github.com/numpy/numpy/pull/13433>`__: BUG: Handle subarrays in descr_to_dtype
* `#13435 <https://github.com/numpy/numpy/pull/13435>`__: BUG: Add TypeError to accepted exceptions in crackfortran.
* `#13436 <https://github.com/numpy/numpy/pull/13436>`__: TST: Add file-not-closed check to LGTM analysis.
* `#13440 <https://github.com/numpy/numpy/pull/13440>`__: MAINT: fixed typo 'wtihout' from numpy/core/shape_base.py
* `#13443 <https://github.com/numpy/numpy/pull/13443>`__: BLD, TST: implicit func errors
* `#13445 <https://github.com/numpy/numpy/pull/13445>`__: MAINT: refactor PyArrayMultiIterObject constructors
* `#13446 <https://github.com/numpy/numpy/pull/13446>`__: MANT: refactor unravel_index for code repetition
* `#13449 <https://github.com/numpy/numpy/pull/13449>`__: BUG: missing git raises an OSError
* `#13456 <https://github.com/numpy/numpy/pull/13456>`__: TST: refine Azure fail reports
* `#13463 <https://github.com/numpy/numpy/pull/13463>`__: BUG,DEP: Fix writeable flag setting for arrays without base
* `#13467 <https://github.com/numpy/numpy/pull/13467>`__: ENH: err msg for too large sequences. See #13450
* `#13469 <https://github.com/numpy/numpy/pull/13469>`__: DOC: correct "version added" in npymath docs
* `#13471 <https://github.com/numpy/numpy/pull/13471>`__: LICENSE: split license file in standard BSD 3-clause and bundled.
* `#13477 <https://github.com/numpy/numpy/pull/13477>`__: DOC: have notes in histogram_bin_edges match parameter style
* `#13479 <https://github.com/numpy/numpy/pull/13479>`__: DOC: Mention the handling of nan in the assert_equal docstring.
* `#13482 <https://github.com/numpy/numpy/pull/13482>`__: TEST: add duration report to tests, speed up two outliers
* `#13483 <https://github.com/numpy/numpy/pull/13483>`__: DOC: update mailmap for Bill Spotz
* `#13485 <https://github.com/numpy/numpy/pull/13485>`__: DOC: add security vulnerability reporting and doc links to README
* `#13491 <https://github.com/numpy/numpy/pull/13491>`__: BUG/ENH: Create npy format 3.0 to support extended unicode characters...
* `#13495 <https://github.com/numpy/numpy/pull/13495>`__: BUG: test all ufunc.types for return type, fix for exp, log
* `#13496 <https://github.com/numpy/numpy/pull/13496>`__: BUG: ma.tostring should respect the order parameter
* `#13498 <https://github.com/numpy/numpy/pull/13498>`__: DOC: Clarify rcond normalization in linalg.pinv
* `#13499 <https://github.com/numpy/numpy/pull/13499>`__: MAINT: Use with statement to open/close files to fix LGTM alerts
* `#13503 <https://github.com/numpy/numpy/pull/13503>`__: ENH: Support object arrays in matmul
* `#13504 <https://github.com/numpy/numpy/pull/13504>`__: DOC: Update links in PULL_REQUEST_TEMPLATE.md
* `#13506 <https://github.com/numpy/numpy/pull/13506>`__: ENH: Add sparse option to np.core.numeric.indices
* `#13507 <https://github.com/numpy/numpy/pull/13507>`__: BUG: np.array cleared errors occurred in PyMemoryView_FromObject
* `#13508 <https://github.com/numpy/numpy/pull/13508>`__: BUG: Removes ValueError for empty kwargs in arraymultiter_new
* `#13518 <https://github.com/numpy/numpy/pull/13518>`__: MAINT: implement assert_array_compare without converting array...
* `#13520 <https://github.com/numpy/numpy/pull/13520>`__: BUG: exp, log AVX loops do not use steps
* `#13523 <https://github.com/numpy/numpy/pull/13523>`__: BUG: distutils/system_info.py fix missing subprocess import
* `#13529 <https://github.com/numpy/numpy/pull/13529>`__: MAINT: Use exec() instead array_function_dispatch to improve...
* `#13530 <https://github.com/numpy/numpy/pull/13530>`__: BENCH: Modify benchmarks for radix sort.
* `#13534 <https://github.com/numpy/numpy/pull/13534>`__: BLD: Make CI pass again with pytest 4.5
* `#13541 <https://github.com/numpy/numpy/pull/13541>`__: ENH: restore unpack bit lookup table
* `#13544 <https://github.com/numpy/numpy/pull/13544>`__: ENH: Allow broadcast to be called with zero arguments
* `#13550 <https://github.com/numpy/numpy/pull/13550>`__: TST: Register markers in conftest.py.
* `#13551 <https://github.com/numpy/numpy/pull/13551>`__: DOC: Add note to ``nonzero`` docstring.
* `#13558 <https://github.com/numpy/numpy/pull/13558>`__: MAINT: Fix errors seen on new python 3.8
* `#13570 <https://github.com/numpy/numpy/pull/13570>`__: DOC: Remove duplicate documentation of the PyArray_SimpleNew...
* `#13571 <https://github.com/numpy/numpy/pull/13571>`__: DOC: Mention that expand_dims returns a view
* `#13574 <https://github.com/numpy/numpy/pull/13574>`__: DOC: remove performance claim from searchsorted()
* `#13575 <https://github.com/numpy/numpy/pull/13575>`__: TST: Apply ufunc signature and type test fixmes.
* `#13581 <https://github.com/numpy/numpy/pull/13581>`__: ENH: AVX support for exp/log for strided float32 arrays
* `#13584 <https://github.com/numpy/numpy/pull/13584>`__: DOC: roadmap update
* `#13589 <https://github.com/numpy/numpy/pull/13589>`__: MAINT: Increment stacklevel for warnings to account for NEP-18...
* `#13590 <https://github.com/numpy/numpy/pull/13590>`__: BUG: Fixes for Undefined Behavior Sanitizer (UBSan) errors.
* `#13595 <https://github.com/numpy/numpy/pull/13595>`__: NEP: update NEP 19 with API terminology
* `#13599 <https://github.com/numpy/numpy/pull/13599>`__: DOC: Fixed minor doc error in take_along_axis
* `#13603 <https://github.com/numpy/numpy/pull/13603>`__: TST: bump / verify OpenBLAS in CI
* `#13619 <https://github.com/numpy/numpy/pull/13619>`__: DOC: Add missing return value documentation in ndarray.require
* `#13621 <https://github.com/numpy/numpy/pull/13621>`__: DOC: Update boolean indices in index arrays with slices example
* `#13623 <https://github.com/numpy/numpy/pull/13623>`__: BUG: Workaround for bug in clang7.0
* `#13624 <https://github.com/numpy/numpy/pull/13624>`__: DOC: revert __skip_array_function__ from NEP-18
* `#13626 <https://github.com/numpy/numpy/pull/13626>`__: DOC: update isfortran docs with return value
* `#13627 <https://github.com/numpy/numpy/pull/13627>`__: MAINT: revert __skip_array_function__ from NEP-18
* `#13629 <https://github.com/numpy/numpy/pull/13629>`__: BUG: setup.py install --skip-build fails
* `#13632 <https://github.com/numpy/numpy/pull/13632>`__: MAINT: Collect together the special-casing of 0d nonzero into...
* `#13633 <https://github.com/numpy/numpy/pull/13633>`__: DOC: caution against relying upon NumPy's implementation in subclasses
* `#13634 <https://github.com/numpy/numpy/pull/13634>`__: MAINT: avoid nested dispatch in numpy.core.shape_base
* `#13636 <https://github.com/numpy/numpy/pull/13636>`__: DOC: Add return section to linalg.matrix_rank & tensordot
* `#13639 <https://github.com/numpy/numpy/pull/13639>`__: MAINT: Update mailmap for 1.17.0
* `#13642 <https://github.com/numpy/numpy/pull/13642>`__: BUG: special case object arrays when printing rel-, abs-error...
* `#13648 <https://github.com/numpy/numpy/pull/13648>`__: BUG: ensure that casting to/from structured is properly checked.
* `#13649 <https://github.com/numpy/numpy/pull/13649>`__: DOC: Mention PyArray_GetField steals a reference
* `#13652 <https://github.com/numpy/numpy/pull/13652>`__: MAINT: remove superfluous setting in can_cast_safely_table.
* `#13655 <https://github.com/numpy/numpy/pull/13655>`__: BUG/MAINT: Non-native byteorder in random ints
* `#13656 <https://github.com/numpy/numpy/pull/13656>`__: PERF: Use intrinsic rotr on Windows
* `#13657 <https://github.com/numpy/numpy/pull/13657>`__: BUG: Avoid leading underscores in C function names.
* `#13660 <https://github.com/numpy/numpy/pull/13660>`__: DOC: Updates following NumPy 1.16.4 release.
* `#13663 <https://github.com/numpy/numpy/pull/13663>`__: BUG: regression for array([pandas.DataFrame()])
* `#13664 <https://github.com/numpy/numpy/pull/13664>`__: MAINT: Misc. typo fixes
* `#13665 <https://github.com/numpy/numpy/pull/13665>`__: MAINT: Use intrinsics in Win64-PCG64
* `#13670 <https://github.com/numpy/numpy/pull/13670>`__: BUG: Fix RandomState argument name
* `#13672 <https://github.com/numpy/numpy/pull/13672>`__: DOC: Fix rst markup in RELEASE_WALKTHROUGH.
* `#13678 <https://github.com/numpy/numpy/pull/13678>`__: BUG: fix benchmark suite importability on Numpy<1.17
* `#13682 <https://github.com/numpy/numpy/pull/13682>`__: ENH: Support __length_hint__ in PyArray_FromIter
* `#13684 <https://github.com/numpy/numpy/pull/13684>`__: BUG: Move ndarray.dump to python and make it close the file it...
* `#13687 <https://github.com/numpy/numpy/pull/13687>`__: DOC: Remove misleading statement
* `#13688 <https://github.com/numpy/numpy/pull/13688>`__: MAINT: Correct masked aliases
* `#13690 <https://github.com/numpy/numpy/pull/13690>`__: MAINT: Remove version added from Generator
* `#13691 <https://github.com/numpy/numpy/pull/13691>`__: BUG: Prevent passing of size 0 to array alloc C functions
* `#13692 <https://github.com/numpy/numpy/pull/13692>`__: DOC: Update C-API documentation of scanfunc, fromstr
* `#13693 <https://github.com/numpy/numpy/pull/13693>`__: ENH: Pass input strides and dimensions by pointer to const
* `#13695 <https://github.com/numpy/numpy/pull/13695>`__: BUG: Ensure Windows choice returns int32
* `#13696 <https://github.com/numpy/numpy/pull/13696>`__: DOC: Put the useful constants first
* `#13697 <https://github.com/numpy/numpy/pull/13697>`__: MAINT: speed up hstack and vstack by eliminating list comprehension.
* `#13700 <https://github.com/numpy/numpy/pull/13700>`__: Add links for GitHub Sponsors button.
* `#13703 <https://github.com/numpy/numpy/pull/13703>`__: DOC: Adds documentation for numpy.dtype.base
* `#13704 <https://github.com/numpy/numpy/pull/13704>`__: DOC: Mention PyArray_DIMS can be NULL
* `#13708 <https://github.com/numpy/numpy/pull/13708>`__: DEP: Deprecate nonzero(0d) in favor of calling atleast_1d explicitly
* `#13715 <https://github.com/numpy/numpy/pull/13715>`__: BUG: Fix use-after-free in boolean indexing
* `#13716 <https://github.com/numpy/numpy/pull/13716>`__: BUG: Fix random.choice when probability is not C contiguous
* `#13720 <https://github.com/numpy/numpy/pull/13720>`__: MAINT/BUG: Manage more files with with statements
* `#13721 <https://github.com/numpy/numpy/pull/13721>`__: MAINT,BUG: More ufunc exception cleanup
* `#13724 <https://github.com/numpy/numpy/pull/13724>`__: MAINT: fix use of cache_dim
* `#13725 <https://github.com/numpy/numpy/pull/13725>`__: BUG: fix compilation of 3rd party modules with Py_LIMITED_API...
* `#13726 <https://github.com/numpy/numpy/pull/13726>`__: MAINT: Update PCG jump sizes
* `#13729 <https://github.com/numpy/numpy/pull/13729>`__: DOC: Merge together DISTUTILS.rst.txt#template-files" and distutils.r…
* `#13730 <https://github.com/numpy/numpy/pull/13730>`__: MAINT: Change keyword from reserved word
* `#13737 <https://github.com/numpy/numpy/pull/13737>`__: DOC: Mention and try to explain pairwise summation in sum
* `#13741 <https://github.com/numpy/numpy/pull/13741>`__: MAINT: random: Remove unused empty file binomial.h.
* `#13743 <https://github.com/numpy/numpy/pull/13743>`__: MAINT: random: Rename legacy distributions file.
* `#13744 <https://github.com/numpy/numpy/pull/13744>`__: DOC: Update the C style guide for C99.
* `#13745 <https://github.com/numpy/numpy/pull/13745>`__: BUG: fix segfault on side-effect in __bool__ function in array.nonzero()
* `#13746 <https://github.com/numpy/numpy/pull/13746>`__: [WIP] DOC : Refactor C-API -- Python Types and C structures
* `#13757 <https://github.com/numpy/numpy/pull/13757>`__: MAINT: fix histogram*d dispatchers
* `#13760 <https://github.com/numpy/numpy/pull/13760>`__: DOC: update test guidelines document to use pytest for skipif
* `#13761 <https://github.com/numpy/numpy/pull/13761>`__: MAINT: random: Rewrite the hypergeometric distribution.
* `#13762 <https://github.com/numpy/numpy/pull/13762>`__: MAINT: Use textwrap.dedent for multiline strings
* `#13763 <https://github.com/numpy/numpy/pull/13763>`__: MAINT: Use with statements and dedent in core/setup.py
* `#13767 <https://github.com/numpy/numpy/pull/13767>`__: DOC: Adds examples for dtype attributes
* `#13770 <https://github.com/numpy/numpy/pull/13770>`__: MAINT: random: Combine ziggurat.h and ziggurat_constants.h
* `#13771 <https://github.com/numpy/numpy/pull/13771>`__: DOC: Change random to uninitialized and unpredictable in empty...
* `#13772 <https://github.com/numpy/numpy/pull/13772>`__: BUILD: use numpy-wheels/openblas_support.py to create _distributor_init.py
* `#13773 <https://github.com/numpy/numpy/pull/13773>`__: DOC: Update of reference to paper for Lemire's method
* `#13774 <https://github.com/numpy/numpy/pull/13774>`__: BUG: Make ``Generator._masked`` flag default to ``False``.
* `#13777 <https://github.com/numpy/numpy/pull/13777>`__: MAINT: Remove duplication of should_use_min_scalar_type function
* `#13780 <https://github.com/numpy/numpy/pull/13780>`__: ENH: use SeedSequence instead of seed()
* `#13781 <https://github.com/numpy/numpy/pull/13781>`__: DOC: Update TESTS.rst.txt for pytest
* `#13786 <https://github.com/numpy/numpy/pull/13786>`__: MAINT: random: Fix a few compiler warnings.
* `#13787 <https://github.com/numpy/numpy/pull/13787>`__: DOC: Fixed the problem of "versionadded"
* `#13788 <https://github.com/numpy/numpy/pull/13788>`__: MAINT: fix 'in' -> 'is' typo
* `#13789 <https://github.com/numpy/numpy/pull/13789>`__: MAINT: Fix warnings in radixsort.c.src: comparing integers of...
* `#13791 <https://github.com/numpy/numpy/pull/13791>`__: MAINT: remove dSFMT
* `#13792 <https://github.com/numpy/numpy/pull/13792>`__: LICENSE: update dragon4 license to MIT
* `#13793 <https://github.com/numpy/numpy/pull/13793>`__: MAINT: remove xoshiro* BitGenerators
* `#13795 <https://github.com/numpy/numpy/pull/13795>`__: DOC: Update description of sep in fromstring
* `#13803 <https://github.com/numpy/numpy/pull/13803>`__: DOC: Improve documentation for ``defchararray``
* `#13813 <https://github.com/numpy/numpy/pull/13813>`__: BUG: further fixup to histogram2d dispatcher.
* `#13815 <https://github.com/numpy/numpy/pull/13815>`__: MAINT: Correct intrinsic use on Windows
* `#13818 <https://github.com/numpy/numpy/pull/13818>`__: TST: Add tests for ComplexWarning in astype
* `#13819 <https://github.com/numpy/numpy/pull/13819>`__: DOC: Fix documented default value of ``__array_priority__`` for...
* `#13820 <https://github.com/numpy/numpy/pull/13820>`__: MAINT, DOC: Fix misspelled words in documentation.
* `#13821 <https://github.com/numpy/numpy/pull/13821>`__: MAINT: core: Fix a compiler warning.
* `#13830 <https://github.com/numpy/numpy/pull/13830>`__: MAINT: Update tox for supported Python versions
* `#13832 <https://github.com/numpy/numpy/pull/13832>`__: MAINT: remove pcg32 BitGenerator
* `#13833 <https://github.com/numpy/numpy/pull/13833>`__: MAINT: remove ThreeFry BitGenerator
* `#13837 <https://github.com/numpy/numpy/pull/13837>`__: MAINT, BUG: fixes from seedsequence
* `#13838 <https://github.com/numpy/numpy/pull/13838>`__: ENH: SFC64 BitGenerator
* `#13839 <https://github.com/numpy/numpy/pull/13839>`__: MAINT: Ignore some generated files.
* `#13840 <https://github.com/numpy/numpy/pull/13840>`__: ENH: np.random.default_gen()
* `#13843 <https://github.com/numpy/numpy/pull/13843>`__: DOC: remove note about `__array_ufunc__` being provisional for...
* `#13849 <https://github.com/numpy/numpy/pull/13849>`__: DOC: np.random documentation cleanup and expansion.
* `#13850 <https://github.com/numpy/numpy/pull/13850>`__: DOC: Update performance numbers
* `#13851 <https://github.com/numpy/numpy/pull/13851>`__: MAINT: Update shippable.yml to remove Python 2 dependency
* `#13855 <https://github.com/numpy/numpy/pull/13855>`__: BUG: Fix memory leak in dtype from dict constructor
* `#13856 <https://github.com/numpy/numpy/pull/13856>`__: MAINT: move location of bitgen.h
* `#13858 <https://github.com/numpy/numpy/pull/13858>`__: BUG: do not force emulation of 128-bit arithmetic.
* `#13859 <https://github.com/numpy/numpy/pull/13859>`__: DOC: Update performance numbers for PCG64
* `#13861 <https://github.com/numpy/numpy/pull/13861>`__: BUG: Ensure consistent interpretation of uint64 states.
* `#13863 <https://github.com/numpy/numpy/pull/13863>`__: DOC: Document the precise PCG variant.
* `#13864 <https://github.com/numpy/numpy/pull/13864>`__: TST: Ignore DeprecationWarning during nose imports
* `#13869 <https://github.com/numpy/numpy/pull/13869>`__: DOC: Prepare for 1.17.0rc1 release
* `#13870 <https://github.com/numpy/numpy/pull/13870>`__: MAINT,BUG: Use nbytes to also catch empty descr during allocation
* `#13873 <https://github.com/numpy/numpy/pull/13873>`__: ENH: Rename default_gen -> default_rng
* `#13893 <https://github.com/numpy/numpy/pull/13893>`__: DOC: fix links in 1.17 release note
* `#13897 <https://github.com/numpy/numpy/pull/13897>`__: DOC: Use Cython >= 0.29.11 for Python 3.8 support.
* `#13932 <https://github.com/numpy/numpy/pull/13932>`__: MAINT,BUG,DOC: Fix errors in _add_newdocs
* `#13963 <https://github.com/numpy/numpy/pull/13963>`__: ENH, BUILD: refactor all OpenBLAS downloads into a single, testable...
* `#13971 <https://github.com/numpy/numpy/pull/13971>`__: DOC: emphasize random API changes
* `#13972 <https://github.com/numpy/numpy/pull/13972>`__: MAINT: Rewrite Floyd algorithm
* `#13992 <https://github.com/numpy/numpy/pull/13992>`__: BUG: Do not crash on recursive `.dtype` attribute lookup.
* `#13993 <https://github.com/numpy/numpy/pull/13993>`__: DEP: Speed up WarnOnWrite deprecation in buffer interface
* `#13995 <https://github.com/numpy/numpy/pull/13995>`__: BLD: Remove Trusty dist in Travis CI build
* `#13996 <https://github.com/numpy/numpy/pull/13996>`__: BUG: Handle weird bytestrings in dtype()
* `#13997 <https://github.com/numpy/numpy/pull/13997>`__: BUG: i0 Bessel function regression on array-likes supporting...
* `#13998 <https://github.com/numpy/numpy/pull/13998>`__: BUG: Missing warnings import in polyutils.
* `#13999 <https://github.com/numpy/numpy/pull/13999>`__: DOC: Document array_function at a higher level.
* `#14001 <https://github.com/numpy/numpy/pull/14001>`__: DOC: Show workaround for Generator.integers backward compatibility
* `#14021 <https://github.com/numpy/numpy/pull/14021>`__: DOC: Prepare 1.17.0rc2 release.
* `#14040 <https://github.com/numpy/numpy/pull/14040>`__: DOC: Improve quickstart documentation of new random Generator.
* `#14041 <https://github.com/numpy/numpy/pull/14041>`__: TST, MAINT: expand OpenBLAS version checking
* `#14080 <https://github.com/numpy/numpy/pull/14080>`__: BUG, DOC: add new recfunctions to `__all__`
* `#14081 <https://github.com/numpy/numpy/pull/14081>`__: BUG: fix build issue on icc 2016
* `#14082 <https://github.com/numpy/numpy/pull/14082>`__: BUG: Fix file-like object check when saving arrays
* `#14109 <https://github.com/numpy/numpy/pull/14109>`__: REV: "ENH: Improved performance of PyArray_FromAny for sequences...
* `#14126 <https://github.com/numpy/numpy/pull/14126>`__: BUG, TEST: Adding validation test suite to validate float32 exp
* `#14127 <https://github.com/numpy/numpy/pull/14127>`__: DOC: Add blank line above doctest for intersect1d
* `#14128 <https://github.com/numpy/numpy/pull/14128>`__: MAINT: adjustments to test_ufunc_noncontigous
* `#14129 <https://github.com/numpy/numpy/pull/14129>`__: MAINT: Use equality instead of identity check with literal
* `#14133 <https://github.com/numpy/numpy/pull/14133>`__: MAINT: Update mailmap and changelog for 1.17.0

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Contributors
============
A total of 17 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Alexander Jung +
* Allan Haldane
* Charles Harris
* Eric Wieser
* Giuseppe Cuccu +
* Hiroyuki V. Yamazaki
* Jérémie du Boisberranger
* Kmol Yuan +
* Matti Picus
* Max Bolingbroke +
* Maxwell Aladago +
* Oleksandr Pavlyk
* Peter Andreas Entschev
* Sergei Lebedev
* Seth Troisi +
* Vladimir Pershin +
* Warren Weckesser
Pull requests merged
====================
A total of 24 pull requests were merged for this release.
* `#14156 <https://github.com/numpy/numpy/pull/14156>`__: TST: Allow fuss in testing strided/non-strided exp/log loops
* `#14157 <https://github.com/numpy/numpy/pull/14157>`__: BUG: avx2_scalef_ps must be static
* `#14158 <https://github.com/numpy/numpy/pull/14158>`__: BUG: Remove stray print that causes a SystemError on python 3.7.
* `#14159 <https://github.com/numpy/numpy/pull/14159>`__: BUG: Fix DeprecationWarning in python 3.8.
* `#14160 <https://github.com/numpy/numpy/pull/14160>`__: BLD: Add missing gcd/lcm definitions to npy_math.h
* `#14161 <https://github.com/numpy/numpy/pull/14161>`__: DOC, BUILD: cleanups and fix (again) 'build dist'
* `#14166 <https://github.com/numpy/numpy/pull/14166>`__: TST: Add 3.8-dev to travisCI testing.
* `#14194 <https://github.com/numpy/numpy/pull/14194>`__: BUG: Remove the broken clip wrapper (Backport)
* `#14198 <https://github.com/numpy/numpy/pull/14198>`__: DOC: Fix hermitian argument docs in svd.
* `#14199 <https://github.com/numpy/numpy/pull/14199>`__: MAINT: Workaround for Intel compiler bug leading to failing test
* `#14200 <https://github.com/numpy/numpy/pull/14200>`__: TST: Clean up of test_pocketfft.py
* `#14201 <https://github.com/numpy/numpy/pull/14201>`__: BUG: Make advanced indexing result on read-only subclass writeable...
* `#14236 <https://github.com/numpy/numpy/pull/14236>`__: BUG: Fixed default BitGenerator name
* `#14237 <https://github.com/numpy/numpy/pull/14237>`__: ENH: add c-imported modules for freeze analysis in np.random
* `#14296 <https://github.com/numpy/numpy/pull/14296>`__: TST: Pin pytest version to 5.0.1
* `#14301 <https://github.com/numpy/numpy/pull/14301>`__: BUG: Fix leak in the f2py-generated module init and `PyMem_Del`...
* `#14302 <https://github.com/numpy/numpy/pull/14302>`__: BUG: Fix formatting error in exception message
* `#14307 <https://github.com/numpy/numpy/pull/14307>`__: MAINT: random: Match type of SeedSequence.pool_size to DEFAULT_POOL_SIZE.
* `#14308 <https://github.com/numpy/numpy/pull/14308>`__: BUG: Fix numpy.random bug in platform detection
* `#14309 <https://github.com/numpy/numpy/pull/14309>`__: ENH: Enable huge pages in all Linux builds
* `#14330 <https://github.com/numpy/numpy/pull/14330>`__: BUG: Fix segfault in `random.permutation(x)` when x is a string.
* `#14338 <https://github.com/numpy/numpy/pull/14338>`__: BUG: don't fail when lexsorting some empty arrays (#14228)
* `#14339 <https://github.com/numpy/numpy/pull/14339>`__: BUG: Fix misuse of .names and .fields in various places (backport...
* `#14345 <https://github.com/numpy/numpy/pull/14345>`__: BUG: fix behavior of structured_to_unstructured on non-trivial...
* `#14350 <https://github.com/numpy/numpy/pull/14350>`__: REL: Prepare 1.17.1 release

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Contributors
============
A total of 7 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* CakeWithSteak +
* Charles Harris
* Dan Allan
* Hameer Abbasi
* Lars Grueter
* Matti Picus
* Sebastian Berg
Pull requests merged
====================
A total of 8 pull requests were merged for this release.
* `#14418 <https://github.com/numpy/numpy/pull/14418>`__: BUG: Fix aradixsort indirect indexing.
* `#14420 <https://github.com/numpy/numpy/pull/14420>`__: DOC: Fix a minor typo in dispatch documentation.
* `#14421 <https://github.com/numpy/numpy/pull/14421>`__: BUG: test, fix regression in converting to ctypes
* `#14430 <https://github.com/numpy/numpy/pull/14430>`__: BUG: Do not show Override module in private error classes.
* `#14432 <https://github.com/numpy/numpy/pull/14432>`__: BUG: Fixed maximum relative error reporting in assert_allclose.
* `#14433 <https://github.com/numpy/numpy/pull/14433>`__: BUG: Fix uint-overflow if padding with linear_ramp and negative...
* `#14436 <https://github.com/numpy/numpy/pull/14436>`__: BUG: Update 1.17.x with 1.18.0-dev pocketfft.py.
* `#14446 <https://github.com/numpy/numpy/pull/14446>`__: REL: Prepare for NumPy 1.17.2 release.

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Contributors
============
A total of 7 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Allan Haldane
* Charles Harris
* Kevin Sheppard
* Matti Picus
* Ralf Gommers
* Sebastian Berg
* Warren Weckesser
Pull requests merged
====================
A total of 12 pull requests were merged for this release.
* `#14456 <https://github.com/numpy/numpy/pull/14456>`__: MAINT: clean up pocketfft modules inside numpy.fft namespace.
* `#14463 <https://github.com/numpy/numpy/pull/14463>`__: BUG: random.hypergeometic assumes npy_long is npy_int64, hung...
* `#14502 <https://github.com/numpy/numpy/pull/14502>`__: BUG: random: Revert gh-14458 and refix gh-14557.
* `#14504 <https://github.com/numpy/numpy/pull/14504>`__: BUG: add a specialized loop for boolean matmul.
* `#14506 <https://github.com/numpy/numpy/pull/14506>`__: MAINT: Update pytest version for Python 3.8
* `#14512 <https://github.com/numpy/numpy/pull/14512>`__: DOC: random: fix doc linking, was referencing private submodules.
* `#14513 <https://github.com/numpy/numpy/pull/14513>`__: BUG,MAINT: Some fixes and minor cleanup based on clang analysis
* `#14515 <https://github.com/numpy/numpy/pull/14515>`__: BUG: Fix randint when range is 2**32
* `#14519 <https://github.com/numpy/numpy/pull/14519>`__: MAINT: remove the entropy c-extension module
* `#14563 <https://github.com/numpy/numpy/pull/14563>`__: DOC: remove note about Pocketfft license file (non-existing here).
* `#14578 <https://github.com/numpy/numpy/pull/14578>`__: BUG: random: Create a legacy implementation of random.binomial.
* `#14687 <https://github.com/numpy/numpy/pull/14687>`__: BUG: properly define PyArray_DescrCheck

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Contributors
============
A total of 5 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Charles Harris
* Chris Burr +
* Matti Picus
* Qiming Sun +
* Warren Weckesser
Pull requests merged
====================
A total of 8 pull requests were merged for this release.
* `#14758 <https://github.com/numpy/numpy/pull/14758>`__: BLD: declare support for python 3.8
* `#14781 <https://github.com/numpy/numpy/pull/14781>`__: BUG: random: biased samples from integers() with 8 or 16 bit...
* `#14851 <https://github.com/numpy/numpy/pull/14851>`__: BUG: Fix _ctypes class circular reference. (#13808)
* `#14852 <https://github.com/numpy/numpy/pull/14852>`__: BLD: add 'apt update' to shippable
* `#14855 <https://github.com/numpy/numpy/pull/14855>`__: BUG: Fix `np.einsum` errors on Power9 Linux and z/Linux
* `#14857 <https://github.com/numpy/numpy/pull/14857>`__: BUG: lib: Fix histogram problem with signed integer arrays.
* `#14858 <https://github.com/numpy/numpy/pull/14858>`__: BLD: Prevent -flto from optimising long double representation...
* `#14866 <https://github.com/numpy/numpy/pull/14866>`__: MAINT: move buffer.h -> npy_buffer.h to avoid conflicts

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Contributors
============
A total of 6 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Charles Harris
* Eric Wieser
* Ilhan Polat
* Matti Picus
* Michael Hudson-Doyle
* Ralf Gommers
Pull requests merged
====================
A total of 7 pull requests were merged for this release.
* `#14593 <https://github.com/numpy/numpy/pull/14593>`__: MAINT: backport Cython API cleanup to 1.17.x, remove docs
* `#14937 <https://github.com/numpy/numpy/pull/14937>`__: BUG: fix integer size confusion in handling array's ndmin argument
* `#14939 <https://github.com/numpy/numpy/pull/14939>`__: BUILD: remove SSE2 flag from numpy.random builds
* `#14993 <https://github.com/numpy/numpy/pull/14993>`__: MAINT: Added Python3.8 branch to dll lib discovery
* `#15038 <https://github.com/numpy/numpy/pull/15038>`__: BUG: Fix refcounting in ufunc object loops
* `#15067 <https://github.com/numpy/numpy/pull/15067>`__: BUG: Exceptions tracebacks are dropped
* `#15175 <https://github.com/numpy/numpy/pull/15175>`__: ENH: Backport improvements to testing functions.

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Contributors
============
A total of 114 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Abhinav Sagar
* Alex Henrie +
* Alexander Jung +
* Allan Haldane
* Andrea Pattori
* Andrew Liu +
* Anis Ladram +
* Anne Bonner +
* Antoine Dechaume +
* Aryan Naraghi +
* Bastian Eichenberger +
* Brian Wignall +
* Brigitta Sipocz
* CakeWithSteak +
* Charles Harris
* Chris Barker
* Chris Burr +
* Chris Markiewicz +
* Christoph Gohlke
* Christopher Whelan
* Colin Snyder
* Dan Allan
* Daniel Ching
* David Stansby +
* David Zwicker +
* Dieter Werthmüller
* Disconnect3d +
* Dmytro +
* Doug Davis +
* Eric Larson
* Eric Wieser
* Esben Haabendal +
* Eugene Prilepin +
* Felix Divo +
* Gary Gurlaskie
* Gina +
* Giuseppe Cuccu +
* Grzegorz Bokota +
* Guanqun Lu +
* Guilherme Leobas +
* Guillaume Horel
* Géraud Le Falher +
* Hameer Abbasi
* Harmon
* Hiroyuki V. Yamazaki
* Huang, Guangtai +
* Hugo +
* Hyeonguk Ryu +
* Ilhan Polat +
* Isaac Virshup
* Jack J. Woehr +
* Jack Woehr +
* Jackie Leng
* Jaime Fernandez
* Jeff Hale +
* Johann Faouzi +
* Jon Dufresne +
* Joseph Fox-Rabinovitz
* Joseph R. Fox-Rabinovitz +
* João Marcos Gris +
* Justus Magin +
* Jérémie du Boisberranger
* Kai Striega
* Kevin Sheppard
* Kexuan Sun
* Kmol Yuan +
* Kriti Singh
* Larry Bradley +
* Lars Grueter
* Luis Pedro Coelho
* MSeifert04
* Magdalena Proszewska +
* Manny +
* Mark Harfouche
* Martin Reinecke
* Martin Thoma
* Matt Haberland +
* Matt McCormick +
* Matthias Bussonnier
* Matti Picus
* Max Bolingbroke +
* Maxwell Aladago +
* Michael Hudson-Doyle +
* Oleksandr Pavlyk
* Omar Merghany +
* Pauli Virtanen
* Peter Andreas Entschev
* Peter Bell
* Peter Cock +
* Pradeep Reddy Raamana +
* Qiming Sun +
* Raghuveer Devulapalli
* Ralf Gommers
* Samesh +
* Samesh Lakhotia +
* Sebastian Berg
* Sergei Lebedev
* Seth Troisi +
* Siddhesh Poyarekar +
* Simon +
* Simon Notley +
* Stefan van der Walt
* Stephan Hoyer
* Steve Stagg
* Thomas A Caswell
* Thomas Kluyver
* Tim Hoffmann +
* Tirth Patel +
* Tyler Reddy
* Vladimir Pershin +
* Warren Weckesser
* Yadong Zhang +
* Zieji Pohz +
* Zolisa Bleki +
Pull requests merged
====================
A total of 406 pull requests were merged for this release.
* `#9301 <https://github.com/numpy/numpy/pull/9301>`__: DOC: added note to docstring of numpy.savez
* `#10151 <https://github.com/numpy/numpy/pull/10151>`__: BUG: Numpy scalar types sometimes have the same name
* `#12129 <https://github.com/numpy/numpy/pull/12129>`__: DOC: Improve axes shift description and example in np.tensordot
* `#12205 <https://github.com/numpy/numpy/pull/12205>`__: MAINT: avoid relying on `np.generic.__name__` in `np.dtype.name`
* `#12284 <https://github.com/numpy/numpy/pull/12284>`__: ENH: supply our version of numpy.pxd, requires cython>=0.29
* `#12633 <https://github.com/numpy/numpy/pull/12633>`__: BUG: General fixes to f2py reference counts (dereferencing)
* `#12658 <https://github.com/numpy/numpy/pull/12658>`__: BUG: NaT now sorts to ends of arrays
* `#12828 <https://github.com/numpy/numpy/pull/12828>`__: DOC: Updates to nditer usage instructions
* `#13003 <https://github.com/numpy/numpy/pull/13003>`__: BUG: Do not crash on recursive `.dtype` attribute lookup.
* `#13368 <https://github.com/numpy/numpy/pull/13368>`__: ENH: Use AVX for float32 implementation of np.sin & np.cos
* `#13605 <https://github.com/numpy/numpy/pull/13605>`__: DEP: Deprecate silent ignoring of bad data in fromfile/fromstring
* `#13610 <https://github.com/numpy/numpy/pull/13610>`__: ENH: Always produce a consistent shape in the result of `argwhere`
* `#13673 <https://github.com/numpy/numpy/pull/13673>`__: DOC: array(obj, dtype=dt) can downcast
* `#13698 <https://github.com/numpy/numpy/pull/13698>`__: DOC: Document ma.filled behavior with non-scalar fill_value
* `#13710 <https://github.com/numpy/numpy/pull/13710>`__: DOC: Add note to irfft-like functions about the default sizes
* `#13739 <https://github.com/numpy/numpy/pull/13739>`__: BUG: Don't produce undefined behavior for a << b if b >= bitsof(a)
* `#13766 <https://github.com/numpy/numpy/pull/13766>`__: MAINT: Update NEP template.
* `#13794 <https://github.com/numpy/numpy/pull/13794>`__: ENH: random: Add the multivariate hypergeometric distribution.
* `#13799 <https://github.com/numpy/numpy/pull/13799>`__: DOC: Fix unrendered links
* `#13812 <https://github.com/numpy/numpy/pull/13812>`__: MAINT: Rewrite Floyd algorithm
* `#13825 <https://github.com/numpy/numpy/pull/13825>`__: DOC: Add missing macros to C-API documentation
* `#13829 <https://github.com/numpy/numpy/pull/13829>`__: ENH: Add axis argument to random.permutation and random.shuffle
* `#13847 <https://github.com/numpy/numpy/pull/13847>`__: DOC: Adds documentation of functions exposed in numpy namespace
* `#13860 <https://github.com/numpy/numpy/pull/13860>`__: BUG: Refcount fixes
* `#13871 <https://github.com/numpy/numpy/pull/13871>`__: MAINT: Ensure array_dealloc does not modify refcount of self
* `#13874 <https://github.com/numpy/numpy/pull/13874>`__: MAINT: Prepare master for 1.18.0 development.
* `#13876 <https://github.com/numpy/numpy/pull/13876>`__: MAINT,BUG,DOC: Fix errors in _add_newdocs
* `#13880 <https://github.com/numpy/numpy/pull/13880>`__: MAINT: Remove an unnessary backslash between two string literals
* `#13881 <https://github.com/numpy/numpy/pull/13881>`__: MAINT: Update pavement to use python3 in shell commands.
* `#13882 <https://github.com/numpy/numpy/pull/13882>`__: MAINT: Remove unnecessary backslashes (and replace others by...
* `#13883 <https://github.com/numpy/numpy/pull/13883>`__: MAINT: Replace integers in places where booleans are expected
* `#13884 <https://github.com/numpy/numpy/pull/13884>`__: DOC: Add missing parameter description for keepdims in MaskedArray
* `#13885 <https://github.com/numpy/numpy/pull/13885>`__: ENH: use AVX for float32 and float64 implementation of sqrt,...
* `#13886 <https://github.com/numpy/numpy/pull/13886>`__: DOC: reformat top-level release index
* `#13892 <https://github.com/numpy/numpy/pull/13892>`__: DOC : Refactor Array API documentation -- Array Structure and...
* `#13895 <https://github.com/numpy/numpy/pull/13895>`__: DOC: Fix typo in "make_mask" documentation
* `#13896 <https://github.com/numpy/numpy/pull/13896>`__: MAINT: Delete unused _aliased_types.py
* `#13901 <https://github.com/numpy/numpy/pull/13901>`__: BLD: Remove Trusty dist in Travis CI build
* `#13907 <https://github.com/numpy/numpy/pull/13907>`__: BUG: Handle weird bytestrings in dtype()
* `#13908 <https://github.com/numpy/numpy/pull/13908>`__: ENH: use towncrier to build the release note
* `#13913 <https://github.com/numpy/numpy/pull/13913>`__: ENH: improve error message for ragged-array creation failure
* `#13914 <https://github.com/numpy/numpy/pull/13914>`__: DOC: Update the description of byteswap
* `#13916 <https://github.com/numpy/numpy/pull/13916>`__: BUG: i0 Bessel function regression on array-likes supporting...
* `#13920 <https://github.com/numpy/numpy/pull/13920>`__: ENH, BUILD: refactor all OpenBLAS downloads into a single, testable...
* `#13922 <https://github.com/numpy/numpy/pull/13922>`__: MAINT: Remove unnecessary parenthesis in numpy.ma.core
* `#13925 <https://github.com/numpy/numpy/pull/13925>`__: MAINT: Fix wrong spelling of ufunc
* `#13926 <https://github.com/numpy/numpy/pull/13926>`__: DOC: Remove explicit .next method calls with built-in next function...
* `#13928 <https://github.com/numpy/numpy/pull/13928>`__: DOC: Don't override MaskedArray.view documentation with the one...
* `#13930 <https://github.com/numpy/numpy/pull/13930>`__: BUG: Fix incorrect GIL release in array.nonzero
* `#13935 <https://github.com/numpy/numpy/pull/13935>`__: MAINT: Warn if `_add_newdocs.py` is used to add docstrings to...
* `#13943 <https://github.com/numpy/numpy/pull/13943>`__: MAINT: Revert #13876, "MAINT,BUG,DOC: Fix errors in _add_newdocs"
* `#13944 <https://github.com/numpy/numpy/pull/13944>`__: MAINT,BUG,DOC: Fix errors in _add_newdocs
* `#13945 <https://github.com/numpy/numpy/pull/13945>`__: DOC, MAINT: emphasize random API changes, remove Generator.randint
* `#13946 <https://github.com/numpy/numpy/pull/13946>`__: DOC: Add a numpy-doc docstring to add_newdoc
* `#13947 <https://github.com/numpy/numpy/pull/13947>`__: DOC: Fix rst rendering in data types
* `#13948 <https://github.com/numpy/numpy/pull/13948>`__: DOC:Update the description of set_printoptions in quickstart...
* `#13950 <https://github.com/numpy/numpy/pull/13950>`__: Fixing failure on Python 2.7 on Windows 7
* `#13952 <https://github.com/numpy/numpy/pull/13952>`__: Fix a typo related to the range of indices
* `#13959 <https://github.com/numpy/numpy/pull/13959>`__: DOC: add space between words across lines
* `#13964 <https://github.com/numpy/numpy/pull/13964>`__: BUG, DOC: add new recfunctions to `__all__`
* `#13967 <https://github.com/numpy/numpy/pull/13967>`__: DOC: Change (old) range() to np.arange()
* `#13968 <https://github.com/numpy/numpy/pull/13968>`__: DOC: improve np.sort docstring
* `#13970 <https://github.com/numpy/numpy/pull/13970>`__: DOC: spellcheck numpy/doc/broadcasting.py
* `#13976 <https://github.com/numpy/numpy/pull/13976>`__: MAINT, TST: remove test-installed-numpy.py
* `#13979 <https://github.com/numpy/numpy/pull/13979>`__: DOC: Document array_function at a higher level.
* `#13985 <https://github.com/numpy/numpy/pull/13985>`__: DOC: show workaround for backward compatibility
* `#13988 <https://github.com/numpy/numpy/pull/13988>`__: DOC: Add a call for contribution paragraph to the readme
* `#13989 <https://github.com/numpy/numpy/pull/13989>`__: BUG: Missing warnings import in polyutils
* `#13990 <https://github.com/numpy/numpy/pull/13990>`__: BUILD: adapt "make version-check" to "make dist"
* `#13991 <https://github.com/numpy/numpy/pull/13991>`__: DOC: emphasize need for matching numpy, git versions
* `#14002 <https://github.com/numpy/numpy/pull/14002>`__: TST, MAINT, BUG: expand OpenBLAS version checking
* `#14004 <https://github.com/numpy/numpy/pull/14004>`__: ENH: Chain exception for typed item assignment
* `#14005 <https://github.com/numpy/numpy/pull/14005>`__: MAINT: Fix spelling error in npy_tempita kwarg
* `#14010 <https://github.com/numpy/numpy/pull/14010>`__: DOC: Array API : Directory restructure and code cleanup
* `#14011 <https://github.com/numpy/numpy/pull/14011>`__: [DOC] Remove unused/deprecated functions
* `#14022 <https://github.com/numpy/numpy/pull/14022>`__: Update system_info.py
* `#14025 <https://github.com/numpy/numpy/pull/14025>`__: DOC:Link between the two indexing documentation pages
* `#14026 <https://github.com/numpy/numpy/pull/14026>`__: DOC: Update NumFOCUS subcommittee replacing Nathaniel with Sebastian
* `#14027 <https://github.com/numpy/numpy/pull/14027>`__: DOC: update "Contributing to NumPy" with more activities/roles
* `#14028 <https://github.com/numpy/numpy/pull/14028>`__: DOC: Improve quickstart documentation of new random Generator
* `#14030 <https://github.com/numpy/numpy/pull/14030>`__: DEP: Speed up WarnOnWrite deprecation in buffer interface
* `#14032 <https://github.com/numpy/numpy/pull/14032>`__: NEP: numpy.org website redesign
* `#14035 <https://github.com/numpy/numpy/pull/14035>`__: DOC: Fix docstring of numpy.allclose regarding NaNs
* `#14036 <https://github.com/numpy/numpy/pull/14036>`__: DEP: Raise warnings for deprecated functions PyArray_As1D, PyArray_As2D
* `#14039 <https://github.com/numpy/numpy/pull/14039>`__: DEP: Remove np.rank which has been deprecated for more than 5...
* `#14048 <https://github.com/numpy/numpy/pull/14048>`__: BUG, TEST: Adding validation test suite to validate float32 exp
* `#14051 <https://github.com/numpy/numpy/pull/14051>`__: ENH,DEP: Allow multiple axes in expand_dims
* `#14053 <https://github.com/numpy/numpy/pull/14053>`__: ENH: add pyproject.toml
* `#14060 <https://github.com/numpy/numpy/pull/14060>`__: DOC: Update cversions.py links and wording
* `#14062 <https://github.com/numpy/numpy/pull/14062>`__: DOC, BUILD: cleanups and fix (again) 'make dist'
* `#14063 <https://github.com/numpy/numpy/pull/14063>`__: BUG: Fix file-like object check when saving arrays
* `#14064 <https://github.com/numpy/numpy/pull/14064>`__: DOC: Resolve bad references in Sphinx warnings
* `#14068 <https://github.com/numpy/numpy/pull/14068>`__: MAINT: bump ARMv8 / POWER8 OpenBLAS in CI
* `#14069 <https://github.com/numpy/numpy/pull/14069>`__: DOC: Emphasize the need to run tests when building from source
* `#14070 <https://github.com/numpy/numpy/pull/14070>`__: DOC:Add example to clarify "numpy.save" behavior on already open...
* `#14072 <https://github.com/numpy/numpy/pull/14072>`__: DEP: Deprecate full and economic modes for linalg.qr
* `#14073 <https://github.com/numpy/numpy/pull/14073>`__: DOC: Doc release
* `#14074 <https://github.com/numpy/numpy/pull/14074>`__: BUG: fix build issue on icc 2016
* `#14076 <https://github.com/numpy/numpy/pull/14076>`__: TST: Add 3.8-dev to travisCI testing.
* `#14085 <https://github.com/numpy/numpy/pull/14085>`__: DOC: Add blank line above doctest for intersect1d
* `#14086 <https://github.com/numpy/numpy/pull/14086>`__: ENH: Propose standard policy for dropping support of old Python...
* `#14089 <https://github.com/numpy/numpy/pull/14089>`__: DOC: Use `pip install .` where possible instead of calling setup.py
* `#14091 <https://github.com/numpy/numpy/pull/14091>`__: MAINT: adjustments to test_ufunc_noncontigous
* `#14092 <https://github.com/numpy/numpy/pull/14092>`__: MAINT: Improve NEP template
* `#14096 <https://github.com/numpy/numpy/pull/14096>`__: DOC: fix documentation of i and j for tri.
* `#14097 <https://github.com/numpy/numpy/pull/14097>`__: MAINT: Lazy import testing on python >=3.7
* `#14100 <https://github.com/numpy/numpy/pull/14100>`__: DEP: Deprecate PyArray_FromDimsAndDataAndDescr, PyArray_FromDims
* `#14101 <https://github.com/numpy/numpy/pull/14101>`__: MAINT: Clearer error message while padding with stat_length=0
* `#14106 <https://github.com/numpy/numpy/pull/14106>`__: MAINT: remove duplicate variable assignments
* `#14108 <https://github.com/numpy/numpy/pull/14108>`__: BUG: initialize variable that is passed by pointer
* `#14110 <https://github.com/numpy/numpy/pull/14110>`__: DOC: fix typo in c-api/array.rst doc
* `#14121 <https://github.com/numpy/numpy/pull/14121>`__: BUG: Add gcd/lcm definitions to npy_math.h
* `#14122 <https://github.com/numpy/numpy/pull/14122>`__: MAINT: Mark umath accuracy test xfail.
* `#14124 <https://github.com/numpy/numpy/pull/14124>`__: MAINT: Use equality instead of identity check with literal
* `#14130 <https://github.com/numpy/numpy/pull/14130>`__: MAINT: Fix small typo in quickstart docs
* `#14134 <https://github.com/numpy/numpy/pull/14134>`__: DOC, MAINT: Update master after 1.17.0 release.
* `#14141 <https://github.com/numpy/numpy/pull/14141>`__: ENH: add c-imported modules for freeze analysis in np.random
* `#14143 <https://github.com/numpy/numpy/pull/14143>`__: BUG: Fix DeprecationWarning in python 3.8
* `#14144 <https://github.com/numpy/numpy/pull/14144>`__: BUG: Remove stray print that causes a SystemError on python 3.7...
* `#14145 <https://github.com/numpy/numpy/pull/14145>`__: BUG: Remove the broken clip wrapper
* `#14152 <https://github.com/numpy/numpy/pull/14152>`__: BUG: avx2_scalef_ps must be static
* `#14153 <https://github.com/numpy/numpy/pull/14153>`__: TST: Allow fuss in testing strided/non-strided exp/log loops
* `#14170 <https://github.com/numpy/numpy/pull/14170>`__: NEP: Proposal for __duckarray__ protocol
* `#14171 <https://github.com/numpy/numpy/pull/14171>`__: BUG: Make advanced indexing result on read-only subclass writeable
* `#14178 <https://github.com/numpy/numpy/pull/14178>`__: TST: Clean up of test_pocketfft.py
* `#14181 <https://github.com/numpy/numpy/pull/14181>`__: DEP: Deprecate np.alen
* `#14185 <https://github.com/numpy/numpy/pull/14185>`__: MAINT: Workaround for Intel compiler bug leading to failing test
* `#14190 <https://github.com/numpy/numpy/pull/14190>`__: DOC: Fix hermitian argument docs in `svd`
* `#14195 <https://github.com/numpy/numpy/pull/14195>`__: MAINT: Fix a docstring typo.
* `#14196 <https://github.com/numpy/numpy/pull/14196>`__: DOC: Fix links in `/.github/CONTRIBUTING.md`.
* `#14197 <https://github.com/numpy/numpy/pull/14197>`__: ENH: Multivariate normal speedups
* `#14203 <https://github.com/numpy/numpy/pull/14203>`__: MAINT: Improve mismatch message of np.testing.assert_array_equal
* `#14204 <https://github.com/numpy/numpy/pull/14204>`__: DOC,MAINT: Move towncrier files and fixup categories
* `#14207 <https://github.com/numpy/numpy/pull/14207>`__: BUG: Fixed default BitGenerator name
* `#14209 <https://github.com/numpy/numpy/pull/14209>`__: BUG: Fix uint-overflow if padding with linear_ramp and negative...
* `#14216 <https://github.com/numpy/numpy/pull/14216>`__: ENH: Enable huge pages in all Linux builds
* `#14217 <https://github.com/numpy/numpy/pull/14217>`__: BUG: Fix leak in the f2py-generated module init and `PyMem_Del`...
* `#14219 <https://github.com/numpy/numpy/pull/14219>`__: DOC: new nan_to_num keywords are from 1.17 onwards
* `#14223 <https://github.com/numpy/numpy/pull/14223>`__: TST: Add tests for deprecated C functions (PyArray_As1D, PyArray_As1D)
* `#14224 <https://github.com/numpy/numpy/pull/14224>`__: DOC: mention `take_along_axis` in `choose`
* `#14227 <https://github.com/numpy/numpy/pull/14227>`__: ENH: Parse complex number from string
* `#14231 <https://github.com/numpy/numpy/pull/14231>`__: DOC: update or remove outdated sourceforge links
* `#14234 <https://github.com/numpy/numpy/pull/14234>`__: MAINT: Better error message for norm
* `#14235 <https://github.com/numpy/numpy/pull/14235>`__: DOC: add backlinks to numpy.org
* `#14240 <https://github.com/numpy/numpy/pull/14240>`__: BUG: Don't fail when lexsorting some empty arrays.
* `#14241 <https://github.com/numpy/numpy/pull/14241>`__: BUG: Fix segfault in `random.permutation(x)` when x is a string.
* `#14245 <https://github.com/numpy/numpy/pull/14245>`__: Doc: fix a typo in NEP21
* `#14249 <https://github.com/numpy/numpy/pull/14249>`__: DOC: set status of NEP 28 (website redesign) to Accepted
* `#14250 <https://github.com/numpy/numpy/pull/14250>`__: BLD: MAINT: change default behavior of build flag appending.
* `#14252 <https://github.com/numpy/numpy/pull/14252>`__: BUG: Fixes StopIteration error from 'np.genfromtext' for empty...
* `#14255 <https://github.com/numpy/numpy/pull/14255>`__: BUG: fix inconsistent axes ordering for axis in function `unique`
* `#14256 <https://github.com/numpy/numpy/pull/14256>`__: DEP: Deprecate load/dump functions in favour of pickle methods
* `#14257 <https://github.com/numpy/numpy/pull/14257>`__: MAINT: Update NEP-30
* `#14259 <https://github.com/numpy/numpy/pull/14259>`__: DEP: Deprecate arrayprint formatting functions
* `#14266 <https://github.com/numpy/numpy/pull/14266>`__: DOC: remove scipy.org from the breadcrumb formattiong
* `#14270 <https://github.com/numpy/numpy/pull/14270>`__: BUG: Fix formatting error in exception message
* `#14272 <https://github.com/numpy/numpy/pull/14272>`__: DOC: Address typos in dispatch docs
* `#14279 <https://github.com/numpy/numpy/pull/14279>`__: BUG: Fix ZeroDivisionError for zero length arrays in pocketfft.
* `#14290 <https://github.com/numpy/numpy/pull/14290>`__: BUG: Fix misuse of .names and .fields in various places
* `#14291 <https://github.com/numpy/numpy/pull/14291>`__: TST, BUG: Use python3.6-dbg.
* `#14295 <https://github.com/numpy/numpy/pull/14295>`__: BUG: core: Handle large negative np.int64 args in binary_repr.
* `#14298 <https://github.com/numpy/numpy/pull/14298>`__: BUG: Fix numpy.random bug in platform detection
* `#14303 <https://github.com/numpy/numpy/pull/14303>`__: MAINT: random: Match type of SeedSequence.pool_size to DEFAULT_POOL_SIZE.
* `#14310 <https://github.com/numpy/numpy/pull/14310>`__: Bug: Fix behavior of structured_to_unstructured on non-trivial...
* `#14311 <https://github.com/numpy/numpy/pull/14311>`__: DOC: add two commas, move one word
* `#14313 <https://github.com/numpy/numpy/pull/14313>`__: DOC: Clarify rules about broadcasting when empty arrays are involved.
* `#14321 <https://github.com/numpy/numpy/pull/14321>`__: TST, MAINT: bump to OpenBLAS 0.3.7 stable
* `#14325 <https://github.com/numpy/numpy/pull/14325>`__: DEP: numpy.testing.rand
* `#14335 <https://github.com/numpy/numpy/pull/14335>`__: DEP: Deprecate class `SafeEval`
* `#14341 <https://github.com/numpy/numpy/pull/14341>`__: BUG: revert detecting and raising error on ragged arrays
* `#14342 <https://github.com/numpy/numpy/pull/14342>`__: DOC: Improve documentation of `isscalar`.
* `#14349 <https://github.com/numpy/numpy/pull/14349>`__: MAINT: Fix bloated mismatch error percentage in array comparisons.
* `#14351 <https://github.com/numpy/numpy/pull/14351>`__: DOC: Fix a minor typo in dispatch documentation.
* `#14352 <https://github.com/numpy/numpy/pull/14352>`__: MAINT: Remove redundant deprecation checks
* `#14353 <https://github.com/numpy/numpy/pull/14353>`__: MAINT: polynomial: Add an N-d vander implementation used under...
* `#14355 <https://github.com/numpy/numpy/pull/14355>`__: DOC: clarify that PytestTester is non-public
* `#14356 <https://github.com/numpy/numpy/pull/14356>`__: DOC: support and require sphinx>=2.2
* `#14360 <https://github.com/numpy/numpy/pull/14360>`__: DOC: random: fix doc linking, was referencing private submodules.
* `#14364 <https://github.com/numpy/numpy/pull/14364>`__: MAINT: Fixes for prospective Python 3.10 and 4.0
* `#14365 <https://github.com/numpy/numpy/pull/14365>`__: DOC: lib: Add more explanation of the weighted average calculation.
* `#14368 <https://github.com/numpy/numpy/pull/14368>`__: MAINT: Avoid BytesWarning in PyArray_DescrConverter()
* `#14369 <https://github.com/numpy/numpy/pull/14369>`__: MAINT: Post NumPy 1.17.1 update.
* `#14370 <https://github.com/numpy/numpy/pull/14370>`__: DOC: Fixed dtype docs for var, nanvar.
* `#14372 <https://github.com/numpy/numpy/pull/14372>`__: DOC: Document project as Python 3 only with a trove classifier
* `#14378 <https://github.com/numpy/numpy/pull/14378>`__: BUILD: move all test dependencies to ./test_requirements.txt
* `#14381 <https://github.com/numpy/numpy/pull/14381>`__: BUG: lib: Fix histogram problem with signed integer arrays.
* `#14385 <https://github.com/numpy/numpy/pull/14385>`__: REL: Update master after NumPy 1.16.5 release.
* `#14387 <https://github.com/numpy/numpy/pull/14387>`__: BUG: test, fix regression in converting to ctypes
* `#14389 <https://github.com/numpy/numpy/pull/14389>`__: NEP: Add initial draft of NEP-31: Context-local and global overrides...
* `#14390 <https://github.com/numpy/numpy/pull/14390>`__: DOC: document numpy/doc update process
* `#14392 <https://github.com/numpy/numpy/pull/14392>`__: DOC: update np.around docstring with note about floating-point...
* `#14393 <https://github.com/numpy/numpy/pull/14393>`__: BUG: view with fieldless dtype should raise if itemsize != 0
* `#14395 <https://github.com/numpy/numpy/pull/14395>`__: DOC: fix issue with __new__ usage in subclassing doc.
* `#14398 <https://github.com/numpy/numpy/pull/14398>`__: DOC: Fix release notes table of contents
* `#14399 <https://github.com/numpy/numpy/pull/14399>`__: NEP 32: Remove the financial functions from NumPy
* `#14404 <https://github.com/numpy/numpy/pull/14404>`__: BLD: Update RELEASE_WALKTHROUGH and cythonize.
* `#14407 <https://github.com/numpy/numpy/pull/14407>`__: Bump pytest from 5.1.1 to 5.1.2
* `#14408 <https://github.com/numpy/numpy/pull/14408>`__: TST: Remove build job since we now use Dependabot
* `#14410 <https://github.com/numpy/numpy/pull/14410>`__: BLD: Only allow using Cython module when cythonizing.
* `#14411 <https://github.com/numpy/numpy/pull/14411>`__: TST: Add dependabot config file.
* `#14416 <https://github.com/numpy/numpy/pull/14416>`__: BUG: Fix format statement associated with AttributeError.
* `#14417 <https://github.com/numpy/numpy/pull/14417>`__: BUG: Fix aradixsort indirect indexing.
* `#14426 <https://github.com/numpy/numpy/pull/14426>`__: DOC: add the reference to 'printoptions'
* `#14429 <https://github.com/numpy/numpy/pull/14429>`__: BUG: Do not show Override module in private error classes.
* `#14444 <https://github.com/numpy/numpy/pull/14444>`__: DOC: Make implementation bullet points consistent in NEP 29
* `#14447 <https://github.com/numpy/numpy/pull/14447>`__: MAINT: Clarify policy language in NEP-29.
* `#14448 <https://github.com/numpy/numpy/pull/14448>`__: REL: Update master after 1.17.2 release.
* `#14452 <https://github.com/numpy/numpy/pull/14452>`__: MAINT: clean up pocketfft modules inside numpy.fft namespace
* `#14453 <https://github.com/numpy/numpy/pull/14453>`__: BLD: remove generated Cython files from sdist
* `#14454 <https://github.com/numpy/numpy/pull/14454>`__: MAINT: add test to prevent new public-looking modules being added
* `#14458 <https://github.com/numpy/numpy/pull/14458>`__: BUG: random.hypergeometic assumes npy_long is npy_int64, hangs...
* `#14459 <https://github.com/numpy/numpy/pull/14459>`__: ENH: Print the amount of memory that would be used by a failed...
* `#14460 <https://github.com/numpy/numpy/pull/14460>`__: MAINT: use test_requirements.txt in tox and shippable, ship it...
* `#14464 <https://github.com/numpy/numpy/pull/14464>`__: BUG: add a specialized loop for boolean matmul
* `#14469 <https://github.com/numpy/numpy/pull/14469>`__: BUG: Fix _ctypes class circular reference. (#13808)
* `#14472 <https://github.com/numpy/numpy/pull/14472>`__: BUG: core: Fix the str function of the rational dtype.
* `#14475 <https://github.com/numpy/numpy/pull/14475>`__: DOC: add timedelta64 signature
* `#14477 <https://github.com/numpy/numpy/pull/14477>`__: MAINT: Extract raising of MemoryError to a helper function
* `#14483 <https://github.com/numpy/numpy/pull/14483>`__: BUG,MAINT: Some fixes and minor cleanup based on clang analysis
* `#14484 <https://github.com/numpy/numpy/pull/14484>`__: MAINT: Add `NPY_UNUSED` and `const` qualified suggested by clang
* `#14485 <https://github.com/numpy/numpy/pull/14485>`__: MAINT: Silence integer comparison build warnings in assert statements
* `#14486 <https://github.com/numpy/numpy/pull/14486>`__: MAINT: distutils: Add newline at the end of printed warnings.
* `#14490 <https://github.com/numpy/numpy/pull/14490>`__: BUG: random: Revert gh-14458 and refix gh-14557.
* `#14493 <https://github.com/numpy/numpy/pull/14493>`__: DOC: Fix reference NPY_ARRAY_OWNDATA instead of NPY_OWNDATA.
* `#14495 <https://github.com/numpy/numpy/pull/14495>`__: ENH: Allow NPY_PKG_CONFIG_PATH environment variable override
* `#14498 <https://github.com/numpy/numpy/pull/14498>`__: MAINT: remove the entropy c-extension module
* `#14499 <https://github.com/numpy/numpy/pull/14499>`__: DOC: Add backslashes so PyUFunc_FromFuncAndDataAndSignatureAndIdentity...
* `#14500 <https://github.com/numpy/numpy/pull/14500>`__: DOC: Fix a minor typo in changelog readme
* `#14501 <https://github.com/numpy/numpy/pull/14501>`__: BUG: Fix randint when range is 2**32
* `#14503 <https://github.com/numpy/numpy/pull/14503>`__: DOC: tweak np.round docstring to clarify floating-point error
* `#14508 <https://github.com/numpy/numpy/pull/14508>`__: DOC: Add warning to NPV function
* `#14510 <https://github.com/numpy/numpy/pull/14510>`__: API: Do not return None from recfunctions.drop_fields
* `#14511 <https://github.com/numpy/numpy/pull/14511>`__: BUG: Fix flatten_dtype so that nested 0-field structs are flattened...
* `#14514 <https://github.com/numpy/numpy/pull/14514>`__: DOC: Build release notes during CircleCI step
* `#14518 <https://github.com/numpy/numpy/pull/14518>`__: BUILD: Hide platform configuration probe behind --debug-configure
* `#14520 <https://github.com/numpy/numpy/pull/14520>`__: Mention that split() returns views into the original array
* `#14521 <https://github.com/numpy/numpy/pull/14521>`__: MAINT: Simplify lookfor function
* `#14523 <https://github.com/numpy/numpy/pull/14523>`__: MAINT: random: Remove a few duplicated C function prototypes.
* `#14525 <https://github.com/numpy/numpy/pull/14525>`__: BUILD, MAINT: run tests with verbose for PyPY, also do not leak...
* `#14526 <https://github.com/numpy/numpy/pull/14526>`__: BUG: fix release snippet failures caught only after merging
* `#14527 <https://github.com/numpy/numpy/pull/14527>`__: BLD: add warn-error option, adds -Werror to compiler
* `#14531 <https://github.com/numpy/numpy/pull/14531>`__: BUG: random: Create a legacy implementation of random.binomial.
* `#14534 <https://github.com/numpy/numpy/pull/14534>`__: MAINT: remove unused functions, rearrange headers (from CC=clang)
* `#14535 <https://github.com/numpy/numpy/pull/14535>`__: DOC: Fix a bit of code in 'Beyond the Basics' C API user guide.
* `#14536 <https://github.com/numpy/numpy/pull/14536>`__: MAINT: Cleanup old_defines in DOC
* `#14540 <https://github.com/numpy/numpy/pull/14540>`__: DOC: Added missing versionadded to diff(prepend)
* `#14543 <https://github.com/numpy/numpy/pull/14543>`__: BUG: Avoid ctypes in Generators
* `#14545 <https://github.com/numpy/numpy/pull/14545>`__: Changing ImportWarning to DeprecationWarning
* `#14548 <https://github.com/numpy/numpy/pull/14548>`__: MAINT: handle case where GIT_VERSION is empty string
* `#14554 <https://github.com/numpy/numpy/pull/14554>`__: MAINT: core: Remove duplicated inner loop ee->e from log, exp,...
* `#14555 <https://github.com/numpy/numpy/pull/14555>`__: DOC: clarify input types in basics.io.genfromtxt.rst
* `#14557 <https://github.com/numpy/numpy/pull/14557>`__: DOC: remove note about Pocketfft license file (non-existing here).
* `#14558 <https://github.com/numpy/numpy/pull/14558>`__: DOC: Fix code that generates the table in the 'Casting Rules'...
* `#14562 <https://github.com/numpy/numpy/pull/14562>`__: MAINT: don't install partial numpy.random C/Cython API.
* `#14564 <https://github.com/numpy/numpy/pull/14564>`__: TST: ensure coercion tables aren't printed on failing public...
* `#14567 <https://github.com/numpy/numpy/pull/14567>`__: DEP: remove deprecated (and private) numpy.testing submodules.
* `#14568 <https://github.com/numpy/numpy/pull/14568>`__: BLD, DOC: fix gh-14518, add release note
* `#14570 <https://github.com/numpy/numpy/pull/14570>`__: BUG: importing build_src breaks setuptools monkeypatch for msvc14
* `#14572 <https://github.com/numpy/numpy/pull/14572>`__: DOC: Note runtests.py `-- -s` method to use pytests `-s`
* `#14573 <https://github.com/numpy/numpy/pull/14573>`__: DOC: update submodule docstrings, remove info.py files
* `#14576 <https://github.com/numpy/numpy/pull/14576>`__: DOC: Document the NPY_SCALARKIND values as C variables.
* `#14582 <https://github.com/numpy/numpy/pull/14582>`__: MAINT: Bump pytest from 5.1.2 to 5.1.3
* `#14583 <https://github.com/numpy/numpy/pull/14583>`__: DEP: remove deprecated select behaviour
* `#14585 <https://github.com/numpy/numpy/pull/14585>`__: BUG: Add missing check for 0-sized array in ravel_multi_index
* `#14586 <https://github.com/numpy/numpy/pull/14586>`__: BUG: dtype refcount cleanups
* `#14587 <https://github.com/numpy/numpy/pull/14587>`__: DOC: Fix a minor typo in changelog entry
* `#14592 <https://github.com/numpy/numpy/pull/14592>`__: MAINT: Fix typo: remoge → remove
* `#14595 <https://github.com/numpy/numpy/pull/14595>`__: DOC: Change the promotion table checkmark to 'Y'.
* `#14596 <https://github.com/numpy/numpy/pull/14596>`__: DEP: Complete deprecation of invalid array/memory order
* `#14598 <https://github.com/numpy/numpy/pull/14598>`__: DOC: Add to doc that interp cannot contain NaN
* `#14600 <https://github.com/numpy/numpy/pull/14600>`__: NEP: Accept NEP 32.
* `#14601 <https://github.com/numpy/numpy/pull/14601>`__: NEP: Fix discrepancies in NEPs
* `#14603 <https://github.com/numpy/numpy/pull/14603>`__: NEP: Only list "Active" NEPs under "Meta-NEPs"
* `#14604 <https://github.com/numpy/numpy/pull/14604>`__: API: restructure and document numpy.random C-API
* `#14605 <https://github.com/numpy/numpy/pull/14605>`__: BUG: properly define PyArray_DescrCheck{,Exact}
* `#14607 <https://github.com/numpy/numpy/pull/14607>`__: MAINT: Remove duplicate files from .gitignore
* `#14608 <https://github.com/numpy/numpy/pull/14608>`__: API: rearrange the cython files in numpy.random
* `#14614 <https://github.com/numpy/numpy/pull/14614>`__: MAINT: Bump pytest from 5.1.3 to 5.2.0
* `#14615 <https://github.com/numpy/numpy/pull/14615>`__: MAINT: Add "MAINT" tag to dependabot commit msg
* `#14616 <https://github.com/numpy/numpy/pull/14616>`__: DOC: Updated sphinx directive formatting
* `#14620 <https://github.com/numpy/numpy/pull/14620>`__: DEP: Finish deprecation of non-integer `num` in linspace
* `#14621 <https://github.com/numpy/numpy/pull/14621>`__: DOC: s/OR/AND/ in np.logical_and docstring
* `#14623 <https://github.com/numpy/numpy/pull/14623>`__: DOC: misleading np.sinc() documentation
* `#14629 <https://github.com/numpy/numpy/pull/14629>`__: DOC: clarify residual in np.polyfit
* `#14630 <https://github.com/numpy/numpy/pull/14630>`__: BUILD: change to build_src --verbose-cfg, runtests.py --debug-info
* `#14631 <https://github.com/numpy/numpy/pull/14631>`__: BUG: always free clean_sep
* `#14634 <https://github.com/numpy/numpy/pull/14634>`__: DOC: Create `class Extension` docstring and add it to documentation.
* `#14636 <https://github.com/numpy/numpy/pull/14636>`__: DOC: add `printoptions` as a context manager to `set_printoptions`
* `#14639 <https://github.com/numpy/numpy/pull/14639>`__: DOC: Fix typo in NEP 29
* `#14643 <https://github.com/numpy/numpy/pull/14643>`__: MAINT: Use scalar math power function directly
* `#14649 <https://github.com/numpy/numpy/pull/14649>`__: DOC: Add IPython to dependencies needed to build docs.
* `#14652 <https://github.com/numpy/numpy/pull/14652>`__: MAINT: Bump pytest-cov from 2.7.1 to 2.8.1
* `#14653 <https://github.com/numpy/numpy/pull/14653>`__: MAINT: Bump pytest from 5.2.0 to 5.2.1
* `#14654 <https://github.com/numpy/numpy/pull/14654>`__: MAINT: Bump pytz from 2019.2 to 2019.3
* `#14656 <https://github.com/numpy/numpy/pull/14656>`__: MAINT: Use `extract_unit` throughout datetime
* `#14657 <https://github.com/numpy/numpy/pull/14657>`__: BUG: fix fromfile behavior when reading sub-array dtypes
* `#14662 <https://github.com/numpy/numpy/pull/14662>`__: BUG: random: Use correct length when axis is given to shuffle.
* `#14669 <https://github.com/numpy/numpy/pull/14669>`__: BUG: Do not rely on undefined behaviour to cast from float to...
* `#14674 <https://github.com/numpy/numpy/pull/14674>`__: NEP: add default-dtype-object-deprecation nep 34
* `#14681 <https://github.com/numpy/numpy/pull/14681>`__: MAINT: Remove unused boolean negative/subtract loops
* `#14682 <https://github.com/numpy/numpy/pull/14682>`__: DEP: ufunc `out` argument must be a tuple for multiple outputs
* `#14693 <https://github.com/numpy/numpy/pull/14693>`__: BUG: Fix `np.einsum` errors on Power9 Linux and z/Linux
* `#14696 <https://github.com/numpy/numpy/pull/14696>`__: DOC: Note release notes process changes on devdocs start page
* `#14699 <https://github.com/numpy/numpy/pull/14699>`__: Doc warnings
* `#14705 <https://github.com/numpy/numpy/pull/14705>`__: DOC: Switch Markdown link to RST in NEP 29
* `#14709 <https://github.com/numpy/numpy/pull/14709>`__: TST: Divide Azure CI Pipelines into stages.
* `#14710 <https://github.com/numpy/numpy/pull/14710>`__: DEP: Finish the out kwarg deprecation for ufunc calls
* `#14711 <https://github.com/numpy/numpy/pull/14711>`__: DOC: Removing mentions of appveyor
* `#14714 <https://github.com/numpy/numpy/pull/14714>`__: BUG: Default start to 0 for timedelta arange
* `#14717 <https://github.com/numpy/numpy/pull/14717>`__: API: NaT (arg)min/max behavior
* `#14718 <https://github.com/numpy/numpy/pull/14718>`__: API: Forbid Q<->m safe casting
* `#14720 <https://github.com/numpy/numpy/pull/14720>`__: DEP: deprecate financial functions.
* `#14721 <https://github.com/numpy/numpy/pull/14721>`__: DOC: Move newsfragment to correct folder
* `#14723 <https://github.com/numpy/numpy/pull/14723>`__: DOC: cleaning up examples in maskedarray.generic
* `#14725 <https://github.com/numpy/numpy/pull/14725>`__: MAINT: umath: Change error message for unsupported bool subtraction.
* `#14730 <https://github.com/numpy/numpy/pull/14730>`__: ENH: Add complex number support for fromfile
* `#14732 <https://github.com/numpy/numpy/pull/14732>`__: TST: run refguide-check on rst files in doc/*
* `#14734 <https://github.com/numpy/numpy/pull/14734>`__: DOC: Edit NEP procedure for better discussion
* `#14736 <https://github.com/numpy/numpy/pull/14736>`__: DOC: Post 1.17.3 release update.
* `#14737 <https://github.com/numpy/numpy/pull/14737>`__: NEP: Accept NEP 29 as final
* `#14738 <https://github.com/numpy/numpy/pull/14738>`__: BUG: Don't narrow intp to int when producing error messages
* `#14742 <https://github.com/numpy/numpy/pull/14742>`__: DOC: lib: Fix deprecation markup in financial function docstrings.
* `#14743 <https://github.com/numpy/numpy/pull/14743>`__: DOC: Change from HTTP to HTTPS
* `#14745 <https://github.com/numpy/numpy/pull/14745>`__: BUG: clear only attribute errors in get_attr_string.h::maybe_get_attr
* `#14762 <https://github.com/numpy/numpy/pull/14762>`__: MAINT: doc: Remove doc/newdtype_example/
* `#14763 <https://github.com/numpy/numpy/pull/14763>`__: Reword cautionary note about dtype.descr
* `#14769 <https://github.com/numpy/numpy/pull/14769>`__: BUG: fix integer size confusion in handling array's ndmin argument
* `#14771 <https://github.com/numpy/numpy/pull/14771>`__: TST, BUILD: add a gcc 4.8 run on ubuntu 18.04
* `#14775 <https://github.com/numpy/numpy/pull/14775>`__: Update CLASSIFIERS with python 3.8 support
* `#14777 <https://github.com/numpy/numpy/pull/14777>`__: BUG: random: biased samples from integers() with 8 or 16 bit...
* `#14782 <https://github.com/numpy/numpy/pull/14782>`__: DOC: Add release note about changed random variate stream from...
* `#14786 <https://github.com/numpy/numpy/pull/14786>`__: DOC: Make changes to NEP procedure
* `#14790 <https://github.com/numpy/numpy/pull/14790>`__: DOC: random: Remove redundant 'See Also' entry in 'uniform' docstring.
* `#14791 <https://github.com/numpy/numpy/pull/14791>`__: MAINT: Minor typo fix
* `#14792 <https://github.com/numpy/numpy/pull/14792>`__: MAINT: Bump pytest from 5.2.1 to 5.2.2
* `#14793 <https://github.com/numpy/numpy/pull/14793>`__: DOC: Adjust NEP-31 to new template.
* `#14794 <https://github.com/numpy/numpy/pull/14794>`__: DEP: issue deprecation warning when creating ragged array (NEP...
* `#14798 <https://github.com/numpy/numpy/pull/14798>`__: NEP: move 'NEP 29 random' from Accepted to Final
* `#14799 <https://github.com/numpy/numpy/pull/14799>`__: DOC: Add take_along_axis to the see also section in argmin, argmax...
* `#14800 <https://github.com/numpy/numpy/pull/14800>`__: ENH: change object-array comparisons to prefer OO->O unfuncs
* `#14805 <https://github.com/numpy/numpy/pull/14805>`__: TST: Don't construct Fraction instances from numpy scalars
* `#14814 <https://github.com/numpy/numpy/pull/14814>`__: Rename helper functions to not use the word rank
* `#14820 <https://github.com/numpy/numpy/pull/14820>`__: MAINT: Use templating to merge float loops
* `#14826 <https://github.com/numpy/numpy/pull/14826>`__: BUILD: ignore more build.log warnings
* `#14827 <https://github.com/numpy/numpy/pull/14827>`__: BLD: Prevent -flto from optimising long double representation...
* `#14829 <https://github.com/numpy/numpy/pull/14829>`__: BUG: raise ValueError for empty arrays passed to _pyarray_correlate
* `#14830 <https://github.com/numpy/numpy/pull/14830>`__: MAINT: move buffer.h -> npy_buffer.h to avoid conflicts
* `#14836 <https://github.com/numpy/numpy/pull/14836>`__: MAINT: Bump cython from 0.29.13 to 0.29.14
* `#14841 <https://github.com/numpy/numpy/pull/14841>`__: ENH: add isinf, isnan, fmin, fmax loops for datetime64, timedelta64
* `#14842 <https://github.com/numpy/numpy/pull/14842>`__: BLD: add 'apt update' to shippable
* `#14845 <https://github.com/numpy/numpy/pull/14845>`__: MAINT: revert gh-14800, which gave precedence to OO->O over OO->?
* `#14874 <https://github.com/numpy/numpy/pull/14874>`__: REL: Update master after 1.17.4 release.
* `#14878 <https://github.com/numpy/numpy/pull/14878>`__: BUILD: remove SSE2 flag from numpy.random builds
* `#14879 <https://github.com/numpy/numpy/pull/14879>`__: DOC: Update NEP29 with Python3.8 informations.
* `#14881 <https://github.com/numpy/numpy/pull/14881>`__: BUG: Remove builtins from __all__
* `#14898 <https://github.com/numpy/numpy/pull/14898>`__: MAINT: Delete and ignore generated files
* `#14899 <https://github.com/numpy/numpy/pull/14899>`__: Update FUNDING.yml
* `#14901 <https://github.com/numpy/numpy/pull/14901>`__: MAINT: Remove uses of scalar aliases
* `#14903 <https://github.com/numpy/numpy/pull/14903>`__: NEP: move nep 34 to accepted
* `#14907 <https://github.com/numpy/numpy/pull/14907>`__: TST: Add s390x to the TravisCI test matrix.
* `#14912 <https://github.com/numpy/numpy/pull/14912>`__: DOC: Note FFT type promotion
* `#14914 <https://github.com/numpy/numpy/pull/14914>`__: TST: Test with Python3.8 on Windows.
* `#14915 <https://github.com/numpy/numpy/pull/14915>`__: TST: Update travis.yml
* `#14921 <https://github.com/numpy/numpy/pull/14921>`__: TST: add no_tracing decorator to refcount-sensitive codepath...
* `#14926 <https://github.com/numpy/numpy/pull/14926>`__: MAINT: Bump pytest from 5.2.2 to 5.2.4
* `#14929 <https://github.com/numpy/numpy/pull/14929>`__: BUG: Fix step returned by linspace when num=1 and endpoint=False
* `#14932 <https://github.com/numpy/numpy/pull/14932>`__: DOC: Compare 'tolist' function to 'list' in example
* `#14935 <https://github.com/numpy/numpy/pull/14935>`__: DOC: Clarify return type for default_rng
* `#14944 <https://github.com/numpy/numpy/pull/14944>`__: MAINT: move numpy/random/examples -> numpy/random/_examples
* `#14947 <https://github.com/numpy/numpy/pull/14947>`__: DOC: testing: Note handling of scalars in assert_array_equal...
* `#14948 <https://github.com/numpy/numpy/pull/14948>`__: DOC, API: add random.__init__.pxd and document random.* functions
* `#14951 <https://github.com/numpy/numpy/pull/14951>`__: DOC: Clean up examples of low-level random access
* `#14954 <https://github.com/numpy/numpy/pull/14954>`__: TST. API: test using distributions.h via cffi
* `#14962 <https://github.com/numpy/numpy/pull/14962>`__: TST: skip if cython is not available
* `#14967 <https://github.com/numpy/numpy/pull/14967>`__: MAINT: Cleaned up mintypecode for Py3
* `#14973 <https://github.com/numpy/numpy/pull/14973>`__: DOC: fix docstring of np.linalg.norm
* `#14974 <https://github.com/numpy/numpy/pull/14974>`__: MAINT: Added Python3.8 branch to dll lib discovery on Windows
* `#14976 <https://github.com/numpy/numpy/pull/14976>`__: DEV: update asv.conf.json
* `#14978 <https://github.com/numpy/numpy/pull/14978>`__: MAINT: Bump pytest from 5.2.4 to 5.3.0
* `#14982 <https://github.com/numpy/numpy/pull/14982>`__: MAINT: Fix typos
* `#14983 <https://github.com/numpy/numpy/pull/14983>`__: REV: "ENH: Improved performance of PyArray_FromAny for sequences...
* `#14994 <https://github.com/numpy/numpy/pull/14994>`__: BUG: warn when saving dtype with metadata
* `#14996 <https://github.com/numpy/numpy/pull/14996>`__: DEP: Deprecate the axis argument to masked_rows and masked_cols
* `#15004 <https://github.com/numpy/numpy/pull/15004>`__: MAINT: Fix long name of PCG64
* `#15007 <https://github.com/numpy/numpy/pull/15007>`__: DOC, API: improve the C-API/Cython documentation and interfaces...
* `#15009 <https://github.com/numpy/numpy/pull/15009>`__: DOC: Fix typo in numpy.loadtxt and numpy.genfromtxt documentation
* `#15012 <https://github.com/numpy/numpy/pull/15012>`__: ENH: allow using symbol-suffixed 64-bit BLAS/LAPACK for numpy.dot...
* `#15014 <https://github.com/numpy/numpy/pull/15014>`__: DOC: add a more useful comment to compat.py3k.py
* `#15019 <https://github.com/numpy/numpy/pull/15019>`__: DOC: lib: Use a clearer example of ddof in the notes of the cov...
* `#15021 <https://github.com/numpy/numpy/pull/15021>`__: TST: machinery for tests requiring large memory + lapack64 smoketest
* `#15023 <https://github.com/numpy/numpy/pull/15023>`__: MAINT: Only copy input array in _replace_nan() if there are nans...
* `#15025 <https://github.com/numpy/numpy/pull/15025>`__: MAINT: Bump pytest from 5.3.0 to 5.3.1
* `#15027 <https://github.com/numpy/numpy/pull/15027>`__: REV: "ENH: Improved performance of PyArray_FromAny for sequences...
* `#15031 <https://github.com/numpy/numpy/pull/15031>`__: REL: Prepare for 1.18 branch
* `#15032 <https://github.com/numpy/numpy/pull/15032>`__: MAINT: Cleaned up mintypecode for Py3 (pt. 2)
* `#15036 <https://github.com/numpy/numpy/pull/15036>`__: BUG: Fix refcounting in ufunc object loops
* `#15039 <https://github.com/numpy/numpy/pull/15039>`__: BUG: Exceptions tracebacks are dropped
* `#15053 <https://github.com/numpy/numpy/pull/15053>`__: REV: Revert "Merge pull request #14794 from mattip/nep-0034-impl"
* `#15058 <https://github.com/numpy/numpy/pull/15058>`__: API, DOC: change names to multivariate_hypergeometric, improve docs
* `#15059 <https://github.com/numpy/numpy/pull/15059>`__: REL: Prepare for NumPy 1.18.0 release.
* `#15109 <https://github.com/numpy/numpy/pull/15109>`__: TST: Check requires_memory immediately before the test
* `#15111 <https://github.com/numpy/numpy/pull/15111>`__: ENH: Add support to sort timedelta64 `NaT` to end of the array
* `#15112 <https://github.com/numpy/numpy/pull/15112>`__: MAINT: follow-up cleanup for blas64 PR
* `#15113 <https://github.com/numpy/numpy/pull/15113>`__: ENH: f2py: add --f2cmap option for specifying the name of .f2py_f2cmap
* `#15114 <https://github.com/numpy/numpy/pull/15114>`__: ENH: add support for ILP64 OpenBLAS (without symbol suffix)
* `#15146 <https://github.com/numpy/numpy/pull/15146>`__: REL: Prepare for 1.18.0 release.

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Contributors
============
A total of 7 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Charles Harris
* Matti Picus
* Maxwell Aladago
* Pauli Virtanen
* Ralf Gommers
* Tyler Reddy
* Warren Weckesser
Pull requests merged
====================
A total of 13 pull requests were merged for this release.
* `#15158 <https://github.com/numpy/numpy/pull/15158>`__: MAINT: Update pavement.py for towncrier.
* `#15159 <https://github.com/numpy/numpy/pull/15159>`__: DOC: add moved modules to 1.18 release note
* `#15161 <https://github.com/numpy/numpy/pull/15161>`__: MAINT, DOC: Minor backports and updates for 1.18.x
* `#15176 <https://github.com/numpy/numpy/pull/15176>`__: TST: Add assert_array_equal test for big integer arrays
* `#15184 <https://github.com/numpy/numpy/pull/15184>`__: BUG: use tmp dir and check version for cython test (#15170)
* `#15220 <https://github.com/numpy/numpy/pull/15220>`__: BUG: distutils: fix msvc+gfortran openblas handling corner case
* `#15221 <https://github.com/numpy/numpy/pull/15221>`__: BUG: remove -std=c99 for c++ compilation (#15194)
* `#15222 <https://github.com/numpy/numpy/pull/15222>`__: MAINT: unskip test on win32
* `#15223 <https://github.com/numpy/numpy/pull/15223>`__: TST: add BLAS ILP64 run in Travis & Azure
* `#15245 <https://github.com/numpy/numpy/pull/15245>`__: MAINT: only add --std=c99 where needed
* `#15246 <https://github.com/numpy/numpy/pull/15246>`__: BUG: lib: Fix handling of integer arrays by gradient.
* `#15247 <https://github.com/numpy/numpy/pull/15247>`__: MAINT: Do not use private Python function in testing
* `#15250 <https://github.com/numpy/numpy/pull/15250>`__: REL: Prepare for the NumPy 1.18.1 release.

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Contributors
============
A total of 5 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Charles Harris
* Ganesh Kathiresan +
* Matti Picus
* Sebastian Berg
* przemb +
Pull requests merged
====================
A total of 7 pull requests were merged for this release.
* `#15675 <https://github.com/numpy/numpy/pull/15675>`__: TST: move _no_tracing to testing._private
* `#15676 <https://github.com/numpy/numpy/pull/15676>`__: MAINT: Large overhead in some random functions
* `#15677 <https://github.com/numpy/numpy/pull/15677>`__: TST: Do not create gfortran link in azure Mac testing.
* `#15679 <https://github.com/numpy/numpy/pull/15679>`__: BUG: Added missing error check in `ndarray.__contains__`
* `#15722 <https://github.com/numpy/numpy/pull/15722>`__: MAINT: use list-based APIs to call subprocesses
* `#15729 <https://github.com/numpy/numpy/pull/15729>`__: REL: Prepare for 1.18.2 release.
* `#15734 <https://github.com/numpy/numpy/pull/15734>`__: BUG: fix logic error when nm fails on 32-bit

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Contributors
============
A total of 6 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Charles Harris
* Max Balandat +
* @Mibu287 +
* Pan Jan +
* Sebastian Berg
* @panpiort8 +
Pull requests merged
====================
A total of 5 pull requests were merged for this release.
* `#15916 <https://github.com/numpy/numpy/pull/15916>`__: BUG: Fix eigh and cholesky methods of numpy.random.multivariate_normal
* `#15929 <https://github.com/numpy/numpy/pull/15929>`__: BUG,MAINT: Remove incorrect special case in string to number...
* `#15930 <https://github.com/numpy/numpy/pull/15930>`__: BUG: Guarantee array is in valid state after memory error occurs...
* `#15954 <https://github.com/numpy/numpy/pull/15954>`__: BUG: Check that `pvals` is 1D in `_generator.multinomial`.
* `#16017 <https://github.com/numpy/numpy/pull/16017>`__: BUG: Alpha parameter must be 1D in `generator.dirichlet`

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Contributors
============
A total of 4 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
* Charles Harris
* Matti Picus
* Sebastian Berg
* Warren Weckesser
Pull requests merged
====================
A total of 6 pull requests were merged for this release.
* `#16055 <https://github.com/numpy/numpy/pull/16055>`__: BLD: add i686 for 1.18 builds
* `#16090 <https://github.com/numpy/numpy/pull/16090>`__: BUG: random: ``Generator.integers(2**32)`` always returned 0.
* `#16091 <https://github.com/numpy/numpy/pull/16091>`__: BLD: fix path to libgfortran on macOS
* `#16109 <https://github.com/numpy/numpy/pull/16109>`__: REV: Reverts side-effect changes to casting
* `#16114 <https://github.com/numpy/numpy/pull/16114>`__: BLD: put openblas library in local directory on windows
* `#16132 <https://github.com/numpy/numpy/pull/16132>`__: DOC: Change import error "howto" to link to new troubleshooting...

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