Hi All,
On behalf of the NumPy team I am pleased to announce the release of NumPy
1.20.1. NumPy 1.20.1 is a rapid bugfix release fixing several bugs and
regressions reported after the 1.20.0 release. The Python versions
supported for this release are 3.7-3.9. Wheels can be downloaded from PyPI
<https://pypi.org/project/numpy/1.20.1/>; source archives, release notes,
and wheel hashes are available on Github
<https://github.com/numpy/numpy/releases/tag/v1.20.1>. Linux users will
need pip >= 0.19.3 in order to install manylinux2010 and manylinux2014
wheels.
*Highlights*
- The distutils bug that caused problems with downstream projects is
fixed.
- The ``random.shuffle`` regression is fixed.
*Contributors*
A total of 8 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.
- Bas van Beek
- Charles Harris
- Nicholas McKibben +
- Pearu Peterson
- Ralf Gommers
- Sebastian Berg
- Tyler Reddy
- @Aerysv +
*Pull requests merged*
A total of 15 pull requests were merged for this release.
- gh-18306: MAINT: Add missing placeholder annotations
- gh-18310: BUG: Fix typo in ``numpy.__init__.py``
- gh-18326: BUG: don't mutate list of fake libraries while iterating
over...
- gh-18327: MAINT: gracefully shuffle memoryviews
- gh-18328: BUG: Use C linkage for random distributions
- gh-18336: CI: fix when GitHub Actions builds trigger, and allow ci
skips
- gh-18337: BUG: Allow unmodified use of isclose, allclose, etc. with
timedelta
- gh-18345: BUG: Allow pickling all relevant DType types/classes
- gh-18351: BUG: Fix missing signed_char dependency. Closes #18335.
- gh-18352: DOC: Change license date 2020 -> 2021
- gh-18353: CI: CircleCI seems to occasionally time out, increase the
limit
- gh-18354: BUG: Fix f2py bugs when wrapping F90 subroutines.
- gh-18356: MAINT: crackfortran regex simplify
- gh-18357: BUG: threads.h existence test requires GLIBC > 2.12.
- gh-18359: REL: Prepare for the NumPy 1.20.1 release.
Cheers,
Charles Harris
Hi everyone,
This is an odd ball of an subject so bear with me for a paragraph.
Currently we have lots of control related functions on scipy.signal with
varying production grade some are there almost just as a placeholder some
are pretty good. However, many things don't come with the box such as MIMO
support, internal delay representations, time and bode plotting (properly
spaced and considerably dense) and so on. Now of course we have
python-control and (shameless plug) harold packages that can do some and
fail to do others. Frankly in my particular case scipy is eating all my OSS
time. And python-control has their own roadmap. I provide lots of MIMO
stuff but lacking the academic catalogue functions like root-locus and
other academic torture tools and python-control is mostly lacking MIMO
support and a bit short of advanced stuff.
In the mean time, there is a very nice Fortran library SLICOT which also
powers some matlab functions in production however it is not open source.
But they moved to GitHub recently and released its earlier version 5.7
under BSD3. Previously 5.0 was released under GPL and that was the one
python-control vendored but 5.7 is already pretty capable and actually
caused me to write this up. This library is quite diverse and written by
very very high caliber researchers. The reason why I always avoided was
obviously GPL but apparently they changed their mind which is personally
fantastic news for me.
So coming back to the meat of this discussion: I have looked at the LTI
parts and very very closely and I don't see any way to overhaul them
without extremely painful deprecation cycles and breakage. But I sincerely
believe that together with PocketFFT scipy can serve a better quality LTI
tools. In its current state it's a bit academic-ish and not production
ready. So this brings us to three concrete options
1- Status quo : I don't like touching that many funcs and waking the
sleeping dogs
2- Whatever we do we do it on the current functions: It doesn't matter if
it takes 4 years, we don't want any adventures
3- Make a new module and lighten up the signal module which was probably
not exactly the right place.
Please make it as blunt as possible, no hard feelings but I think this
discussion has to be done at least once and maybe for all. A tiny bit of it
has already happened last year in https://github.com/scipy/scipy/pull/4515
but it barely grazed.
Cheers,
ilhan
Current catalogue
https://docs.scipy.org/doc/scipy/reference/signal.html
python-control vendored version
https://github.com/python-control/Slycot
New BSD3 version
https://github.com/SLICOT/SLICOT-Reference
Hello everyone,
I am working with a student (Arthur Volant) on his first contribution to SciPy,
It looks like his mails are not reaching the mailing list (they do not
currently appear in archive[0]).
Does anybody have access to the moderation panel to see if they are
stuck in moderation or if something else is rejecting them ? Or is
there a problem on mailman which does not display them, but
subscribers to the mailing list still did receive them ?
Below is attached a copy of the messages sent.
Thanks,
--
Matthias
from: arthurvolant(a)gmail.com
Hello Scipy-dev,
I have been working for a couple of days now on the following PR[1].
The origin of this PR is this issue[2], asking to add Barnard and
Boschloo test, which are two exact statistical tests.
While working on it, I found that Fisher's exact test was already implemented.
Barnard and Boshloo are two tests more powerful than Fisher's one.
My `barnard_exact` implementation is so far working well. It is a
little bit slower than Fisher exact test, but not that much, with an
average execution time of 1.12 ms
I was wondering though where to put my codes. It seems that there are
two possible files :
either in `scipy/stats/_hypotests.py` or either in
`scipy/stats/contingency.py` which contains already `chi2_contingency`
function. What would you advise me to do?
I thank you for your time and answers,
Arthur
0: https://mail.python.org/pipermail/scipy-dev/2021-February/date.html#start
1: https://github.com/scipy/scipy/pull/13441
2: https://github.com/scipy/scipy/issues/11014
