From ralf.gommers at gmail.com Sat Dec 1 17:24:46 2018 From: ralf.gommers at gmail.com (Ralf Gommers) Date: Sat, 1 Dec 2018 14:24:46 -0800 Subject: [SciPy-Dev] Preparing project proposal for GSoC 2019 In-Reply-To: References: Message-ID: On Fri, Nov 30, 2018 at 12:10 PM Gregory Lee wrote: > > On Fri, Nov 30, 2018 at 1:39 AM Ralf Gommers > wrote: > >> >> >> On Sun, Nov 25, 2018 at 5:22 AM Sourav Singh >> wrote: >> >>> Hello, >>> >>> >>>> >>>> On Sat, Nov 24, 2018 at 11:26 AM Ralf Gommers >>>> wrote: >>>> >>>>> Hi Sourav, >>>>> >>>>> >>>>> On Mon, Nov 19, 2018 at 5:47 AM Sourav Singh >>>>> wrote: >>>>> >>>>>> Hello, >>>>>> >>>>>> I am writing the mail regarding project proposal for GSoC 2019. >>>>>> >>>>>> I am interested in working with SciPy for the upcoming Google Summer >>>>>> of Code and I am interested in either working on enhancing the randomized >>>>>> numerical linear algebra functionality or fixing the scipy.fftpack module. >>>>>> >>>>>> I understand that it is quite early to talk, since the organization >>>>>> proposals haven't started yet, but I would like to know if a project >>>>>> proposal can be started right now so that the proposals can be better >>>>>> fleshed out by the time the application period starts? >>>>>> >>>>> >>>>> That's the earliest start I've seen (which is a good thing)! >>>>> >>>>> I suspect that we'll have trouble finding a mentor for the randomized >>>>> linear algebra, however fftpack could be a good topic. Have you seen >>>>> https://github.com/numpy/numpy/pull/11888? I suspect that by the time >>>>> GSoC starts, we'll have merged that into NumPy, and would like to take it >>>>> over for SciPy. A related topic would be to add a backend system for fft >>>>> implementations (pyfftw, mkl-fft). >>>>> >>>> >>>> And a third topic would be to make the APIs of numpy.fft and >>>> scipy.fftpack agree. That would be the lowest on my list because it's hard >>>> (requiring lots of discussion on impact on users if we deprecate things >>>> etc.), but it's an important one as well. >>>> >>> >>> I am interested in adding pocketfft to scipy, which is linked in the >>> numpy PR. Would it be possible to combine this with the backend system >>> project for scipy? >>> >> >> Yes, this would be possible - that certainly should fit in a single GSoC. >> It's also possible that Pocketfft will already be merged by then, given >> that the author of Pocketfft is quite proactive. The NumPy PR is only >> waiting for the branching of the 1.16.x release, after which it can in >> principle be merged (C99 is the blocker now). In that case, implementing a >> backend system + working on matching signatures for numpy and scipy would >> still be a nice project. >> >> Cheers, >> Ralf >> > > I would be happy to help mentor an FFT-related project and think having a > backend system would be very nice. > Awesome, thanks Greg! pyFFTW's scipy interfaces are mostly complete, aside from some real-valued > transforms for which work was started in: > https://github.com/pyFFTW/pyFFTW/pull/95 > There were also GPU-based FFTs matching the scipy API proposed recently in > https://github.com/cupy/cupy/pull/1745 > Interesting:) Ralf -------------- next part -------------- An HTML attachment was scrubbed... URL: From ssouravsingh12 at gmail.com Mon Dec 3 15:39:20 2018 From: ssouravsingh12 at gmail.com (Sourav Singh) Date: Tue, 4 Dec 2018 02:09:20 +0530 Subject: [SciPy-Dev] Preparing project proposal for GSoC 2019 In-Reply-To: References: Message-ID: Hello, I am creating a new conversation since I have created a draft proposal for the project here- https://goo.gl/S3J9Kg I would be glad to know your views about the proposal and what needs to be done to improve the proposal. I also have a few questions- 1) Would it be fine if I create a PR to SciPy's codebase to adopt pocketfft? The PR could give me an understanding of how to contribute to SciPy's fftpack module. 2) I noticed that scipy.ffitpack has fortran sources. What kind of knowledge of fortran is expected of me for this project? I have a basic knowledge of fortran, but I am not very confident enough to write high-level code in the language. Regards, Sourav -------------- next part -------------- An HTML attachment was scrubbed... URL: From charlesr.harris at gmail.com Mon Dec 3 20:25:11 2018 From: charlesr.harris at gmail.com (Charles R Harris) Date: Mon, 3 Dec 2018 18:25:11 -0700 Subject: [SciPy-Dev] Dropping Python 3.4 Message-ID: Hi All, Currently, NumPy has dropped Python 3.4 support for the 1.16 release while the upcoming SciPy 1.2 version is still supporting it. It looks like current NumPy master still works for Python 3.4, but I wasn't planning to build any wheels for it. Will that be a problem? Chuck -------------- next part -------------- An HTML attachment was scrubbed... URL: From ralf.gommers at gmail.com Mon Dec 3 20:49:57 2018 From: ralf.gommers at gmail.com (Ralf Gommers) Date: Mon, 3 Dec 2018 17:49:57 -0800 Subject: [SciPy-Dev] Dropping Python 3.4 In-Reply-To: References: Message-ID: On Mon, Dec 3, 2018 at 5:25 PM Charles R Harris wrote: > Hi All, > > Currently, NumPy has dropped Python 3.4 support for the 1.16 release while > the upcoming SciPy 1.2 version is still supporting it. It looks like > current NumPy master still works for Python 3.4, but I wasn't planning to > build any wheels for it. Will that be a problem? > Sounds fine to me. Python 3.4 is pretty much irrelevant at this point, and SciPy supporting it for one more release doesn't imply anything for NumPy. Ralf -------------- next part -------------- An HTML attachment was scrubbed... URL: From tyler.je.reddy at gmail.com Tue Dec 4 13:02:38 2018 From: tyler.je.reddy at gmail.com (Tyler Reddy) Date: Tue, 4 Dec 2018 10:02:38 -0800 Subject: [SciPy-Dev] SciPy 1.2.0 release schedule In-Reply-To: References: Message-ID: Wheel builds off the tip of the 1.2.0rc2 branch are erroring out on Travis: https://travis-ci.org/MacPython/scipy-wheels/builds/463460018 On Thu, 29 Nov 2018 at 19:33, Ralf Gommers wrote: > > > On Wed, Nov 28, 2018 at 10:05 AM Tyler Reddy > wrote: > >> I'm tentatively suggesting that we do a second release candidate, rc2, on >> or at least close to December 3rd. >> > > Yes, that makes sense. There's enough changes to justify a new release > candidate. > > Ralf > > >> My notes currently show the PRs/ issues below on the "backport radar." In >> particular, I think Ralf noticed >> an API inconsistency in one of the big optimize enhancements. >> >> https://github.com/scipy/scipy/pull/9541 >> https://github.com/scipy/scipy/issues/9547 >> https://github.com/scipy/scipy/pull/9550 >> >> On Wed, 21 Nov 2018 at 15:07, Ralf Gommers >> wrote: >> >>> >>> >>> On Wed, Nov 21, 2018 at 9:32 AM Tyler Reddy >>> wrote: >>> >>>> I've pushed the v1.2.x wheels branch -- initially this will aim to >>>> confirm that SciPy master branch is now passing the Travis & Appveyor wheel >>>> builds. >>>> >>>> If that is the case, I will proceed with the 3 connected backport PRs >>>> to the maintenance branch. >>>> >>>> Then, I will point the v.1.2.x wheels branch to an appropriate commit >>>> on the patched maintenance branch for release candidate wheel builds. >>>> >>> >>> Sounds like a plan! >>> >>> Ralf >>> >>> >>>> >>>> On Sat, 17 Nov 2018 at 10:27, Ilhan Polat wrote: >>>> >>>>> Good stuff Tyler. I have to also add to that list the recent pypy3 run >>>>> failures appearing sporadically (though consistent on my PRs). >>>>> >>>>> I am trying triangulate the cause but probably will have to wait until >>>>> at least tomorrow. Feedback is more than welcome. They seem to be related >>>>> to cython/numpy versions but one can never be sure. >>>>> >>>>> ?lhan >>>>> >>>>> >>>>> On Fri, Nov 16, 2018, 19:35 Tyler Reddy >>>>> wrote: >>>>> >>>>>> Current delays / issues I'm working on--feel free to chime in on >>>>>> those: >>>>>> >>>>>> - a few test failures in wheel building matrix: >>>>>> https://github.com/MacPython/scipy-wheels/pull/37 >>>>>> - hard-to-understand putative patch for one of the failures: >>>>>> https://github.com/scipy/scipy/pull/9486 >>>>>> >>>>>> On Fri, 9 Nov 2018 at 08:40, Tyler Reddy >>>>>> wrote: >>>>>> >>>>>>> I branched 1.2.x around 8:30 am Pacific time on Nov. 9, 2018. >>>>>>> >>>>>>> Working on the follow up master branch PR to bump version number / >>>>>>> notes file, etc. now. >>>>>>> >>>>>>> On Thu, 8 Nov 2018 at 22:49, Tyler Reddy >>>>>>> wrote: >>>>>>> >>>>>>>> Release note PR is hopefully taking shape now -- I'll allow >>>>>>>> (another) delay for the branch until tomorrow (morning?) for some >>>>>>>> (hopefully final) checks on that. >>>>>>>> >>>>>>>> On Thu, 8 Nov 2018 at 14:35, Tyler Reddy >>>>>>>> wrote: >>>>>>>> >>>>>>>>> There are 0 remaining PRs with a 1.2.0 milestone. >>>>>>>>> >>>>>>>>> There is one issue left with a 1.2.0 milestone: >>>>>>>>> https://github.com/scipy/scipy/issues/9441 >>>>>>>>> >>>>>>>>> Please do take a look over the release notes WIP PR based on the >>>>>>>>> wiki: https://github.com/scipy/scipy/pull/9461 >>>>>>>>> >>>>>>>>> Target is to branch in 5-6 hours or so. Let me know if you see any >>>>>>>>> issues of course -- Ralf has been coaching >>>>>>>>> me through pretty well so far I think. >>>>>>>>> >>>>>>>>> On Wed, 7 Nov 2018 at 09:52, Ilhan Polat >>>>>>>>> wrote: >>>>>>>>> >>>>>>>>>> Hang in there Tyler :) >>>>>>>>>> >>>>>>>>>> Awesome job so far. >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> On Wed, Nov 7, 2018, 06:08 Ralf Gommers >>>>>>>>>> wrote: >>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> On Tue, Nov 6, 2018 at 9:03 PM Tyler Reddy < >>>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>>> >>>>>>>>>>>> 7 PRs : >>>>>>>>>>>> https://github.com/scipy/scipy/pulls?q=is%3Aopen+is%3Apr+milestone%3A1.2.0 >>>>>>>>>>>> 3 issues: >>>>>>>>>>>> https://github.com/scipy/scipy/issues?q=is%3Aopen+is%3Aissue+milestone%3A1.2.0 >>>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> Awesome, getting there:) >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>>> Target: branch sometime on November 8th >>>>>>>>>>>> >>>>>>>>>>>> On Mon, 5 Nov 2018 at 05:42, Tyler Reddy < >>>>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>>>> >>>>>>>>>>>>> Alright, I'll extend to Thursday Nov. 8th & see if I can >>>>>>>>>>>>> reduce that list a bit >>>>>>>>>>>>> >>>>>>>>>>>>> On Sun, 4 Nov 2018 at 22:27, Ralf Gommers < >>>>>>>>>>>>> ralf.gommers at gmail.com> wrote: >>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> On Fri, Oct 26, 2018 at 7:03 PM Mark Alexander Mikofski < >>>>>>>>>>>>>> mikofski at berkeley.edu> wrote: >>>>>>>>>>>>>> >>>>>>>>>>>>>>> Hi Tyler and others, >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> Thanks for managing the v1.2 release. >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> I think PR #8431, Cython optimize zeros API, is ready, >>>>>>>>>>>>>>> hopefully, to merge. It's been through several rounds of reviews and I >>>>>>>>>>>>>>> think I've accommodated all of the recommendations, all tests are passing, >>>>>>>>>>>>>>> and there's been strong support. Anyone please take a look. >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> https://github.com/scipy/scipy/pull/8431 >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> Thanks, >>>>>>>>>>>>>>> Mark >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> On Fri, Oct 26, 2018, 2:38 PM Ralf Gommers < >>>>>>>>>>>>>>> ralf.gommers at gmail.com> wrote: >>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> On Thu, Oct 25, 2018 at 12:55 PM Tyler Reddy < >>>>>>>>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> Hi all, >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> It is almost 6 months after the 1.1.0 release on May 5, so >>>>>>>>>>>>>>>>> probably time to plan the 1.2.0 release. It would be a good idea to look >>>>>>>>>>>>>>>>> over the PRs with a 1.2.0 milestone >>>>>>>>>>>>>>>>> , >>>>>>>>>>>>>>>>> and tag anything else that should have this milestone appropriately. >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> I'd like to propose the following schedule: >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> Nov. 5: branch 1.2.x >>>>>>>>>>>>>>>>> Nov. 8: rc1 >>>>>>>>>>>>>>>>> Nov. 21: rc2 (if needed) >>>>>>>>>>>>>>>>> Nov. 30: final release >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> Thoughts? >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> This looks like a good schedule to me. We'll probably >>>>>>>>>>>>>>>> struggle to get some PRs marked for 1.2.0 merged, but that's always the >>>>>>>>>>>>>>>> case. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>> >>>>>>>>>>>>>> Hi Tyler, could we shift the branch date by 2-3 days (or up >>>>>>>>>>>>>> to a week)? There's a couple of PRs that I'd really like to see merged or >>>>>>>>>>>>>> decided on (for optimize and stats mainly), and there's right now still 18 >>>>>>>>>>>>>> open PRs marked for 1.2.0. >>>>>>>>>>>>>> >>>>>>>>>>>>>> A note on the open PRs: what we want to aim for is to have >>>>>>>>>>>>>> the list of open PRs and open blocking issues at zero, and have at most >>>>>>>>>>>>>> some non-blocking issues under the milestone left. Normally the release >>>>>>>>>>>>>> manager starts making those decisions, or pinging people, if other >>>>>>>>>>>>>> reviewers haven't done so in time. Of course it would be ideal if everyone >>>>>>>>>>>>>> has another look at >>>>>>>>>>>>>> https://github.com/scipy/scipy/pulls?q=is%3Aopen+is%3Apr+milestone%3A1.2.0 >>>>>>>>>>>>>> and bumps or finished off PRs he/she is involved in. >>>>>>>>>>>>>> >>>>>>>>>>>>>> Cheers, >>>>>>>>>>>>>> Ralf >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>>>>> >>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>>> >>>>>>>>>>> _______________________________________________ >>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>> >>>>>>>>>> _______________________________________________ >>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>> >>>>>>>>> _______________________________________________ >>>>>> SciPy-Dev mailing list >>>>>> SciPy-Dev at python.org >>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>> >>>>> _______________________________________________ >>>>> SciPy-Dev mailing list >>>>> SciPy-Dev at python.org >>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>> >>>> _______________________________________________ >>>> SciPy-Dev mailing list >>>> SciPy-Dev at python.org >>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>> >>> _______________________________________________ >>> SciPy-Dev mailing list >>> SciPy-Dev at python.org >>> https://mail.python.org/mailman/listinfo/scipy-dev >>> >> _______________________________________________ >> SciPy-Dev mailing list >> SciPy-Dev at python.org >> https://mail.python.org/mailman/listinfo/scipy-dev >> > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > -------------- next part -------------- An HTML attachment was scrubbed... URL: From rmay31 at gmail.com Tue Dec 4 17:08:52 2018 From: rmay31 at gmail.com (Ryan May) Date: Tue, 4 Dec 2018 15:08:52 -0700 Subject: [SciPy-Dev] Cubic interpolation with SciPy 1.2.0rc1 Message-ID: Hi, I just noticed our test suite is failing with SciPy 1.2.0rc1 on any test involving cubic interpolation through griddata. The differences aren't huge, at most 2.5%. I'm working on reducing one of the tests to a simple example. In the mean time, is there any reason to expect changes to the results from cubic interpolation? I didn't see anything in the release notes, and a quick search on GitHub didn't bring any obvious issues/PRs. Ryan -- Ryan May -------------- next part -------------- An HTML attachment was scrubbed... URL: From pav at iki.fi Tue Dec 4 18:10:14 2018 From: pav at iki.fi (Pauli Virtanen) Date: Wed, 05 Dec 2018 00:10:14 +0100 Subject: [SciPy-Dev] Cubic interpolation with SciPy 1.2.0rc1 In-Reply-To: References: Message-ID: <2bda2b2d2468660db53dbf9f047986c31bf536f1.camel@iki.fi> ti, 2018-12-04 kello 15:08 -0700, Ryan May kirjoitti: > In the mean time, is there any reason to expect changes to the > results from cubic interpolation? I didn't see anything in the > release notes, and a quick search on GitHub didn't bring any obvious > issues/PRs. There was a bug for triangles on the boundary, resulting to weird choice of free degrees of freedom: https://github.com/scipy/scipy/pull/9176 From tyler.je.reddy at gmail.com Tue Dec 4 18:30:50 2018 From: tyler.je.reddy at gmail.com (Tyler Reddy) Date: Tue, 4 Dec 2018 15:30:50 -0800 Subject: [SciPy-Dev] Cubic interpolation with SciPy 1.2.0rc1 In-Reply-To: <2bda2b2d2468660db53dbf9f047986c31bf536f1.camel@iki.fi> References: <2bda2b2d2468660db53dbf9f047986c31bf536f1.camel@iki.fi> Message-ID: Anything I should consider here for rc2, since that's delayed slightly (again)? Presumably the bug fix is higher priority than the modest behavior change? On Tue, 4 Dec 2018 at 15:12, Pauli Virtanen wrote: > ti, 2018-12-04 kello 15:08 -0700, Ryan May kirjoitti: > > In the mean time, is there any reason to expect changes to the > > results from cubic interpolation? I didn't see anything in the > > release notes, and a quick search on GitHub didn't bring any obvious > > issues/PRs. > > There was a bug for triangles on the boundary, resulting to weird > choice of free degrees of freedom: > https://github.com/scipy/scipy/pull/9176 > > > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > -------------- next part -------------- An HTML attachment was scrubbed... URL: From tyler.je.reddy at gmail.com Wed Dec 5 01:10:42 2018 From: tyler.je.reddy at gmail.com (Tyler Reddy) Date: Tue, 4 Dec 2018 22:10:42 -0800 Subject: [SciPy-Dev] SciPy 1.2.0 release schedule In-Reply-To: References: Message-ID: After the gh-9572 reversion, updated scipy 1.2.0rc2 wheel builds are now running -- fingers crossed -- I'll check on them in the morning. On Tue, 4 Dec 2018 at 10:02, Tyler Reddy wrote: > Wheel builds off the tip of the 1.2.0rc2 branch are erroring out on > Travis: https://travis-ci.org/MacPython/scipy-wheels/builds/463460018 > > > On Thu, 29 Nov 2018 at 19:33, Ralf Gommers wrote: > >> >> >> On Wed, Nov 28, 2018 at 10:05 AM Tyler Reddy >> wrote: >> >>> I'm tentatively suggesting that we do a second release candidate, rc2, >>> on or at least close to December 3rd. >>> >> >> Yes, that makes sense. There's enough changes to justify a new release >> candidate. >> >> Ralf >> >> >>> My notes currently show the PRs/ issues below on the "backport radar." >>> In particular, I think Ralf noticed >>> an API inconsistency in one of the big optimize enhancements. >>> >>> https://github.com/scipy/scipy/pull/9541 >>> https://github.com/scipy/scipy/issues/9547 >>> https://github.com/scipy/scipy/pull/9550 >>> >>> On Wed, 21 Nov 2018 at 15:07, Ralf Gommers >>> wrote: >>> >>>> >>>> >>>> On Wed, Nov 21, 2018 at 9:32 AM Tyler Reddy >>>> wrote: >>>> >>>>> I've pushed the v1.2.x wheels branch -- initially this will aim to >>>>> confirm that SciPy master branch is now passing the Travis & Appveyor wheel >>>>> builds. >>>>> >>>>> If that is the case, I will proceed with the 3 connected backport PRs >>>>> to the maintenance branch. >>>>> >>>>> Then, I will point the v.1.2.x wheels branch to an appropriate commit >>>>> on the patched maintenance branch for release candidate wheel builds. >>>>> >>>> >>>> Sounds like a plan! >>>> >>>> Ralf >>>> >>>> >>>>> >>>>> On Sat, 17 Nov 2018 at 10:27, Ilhan Polat >>>>> wrote: >>>>> >>>>>> Good stuff Tyler. I have to also add to that list the recent pypy3 >>>>>> run failures appearing sporadically (though consistent on my PRs). >>>>>> >>>>>> I am trying triangulate the cause but probably will have to wait >>>>>> until at least tomorrow. Feedback is more than welcome. They seem to be >>>>>> related to cython/numpy versions but one can never be sure. >>>>>> >>>>>> ?lhan >>>>>> >>>>>> >>>>>> On Fri, Nov 16, 2018, 19:35 Tyler Reddy >>>>>> wrote: >>>>>> >>>>>>> Current delays / issues I'm working on--feel free to chime in on >>>>>>> those: >>>>>>> >>>>>>> - a few test failures in wheel building matrix: >>>>>>> https://github.com/MacPython/scipy-wheels/pull/37 >>>>>>> - hard-to-understand putative patch for one of the failures: >>>>>>> https://github.com/scipy/scipy/pull/9486 >>>>>>> >>>>>>> On Fri, 9 Nov 2018 at 08:40, Tyler Reddy >>>>>>> wrote: >>>>>>> >>>>>>>> I branched 1.2.x around 8:30 am Pacific time on Nov. 9, 2018. >>>>>>>> >>>>>>>> Working on the follow up master branch PR to bump version number / >>>>>>>> notes file, etc. now. >>>>>>>> >>>>>>>> On Thu, 8 Nov 2018 at 22:49, Tyler Reddy >>>>>>>> wrote: >>>>>>>> >>>>>>>>> Release note PR is hopefully taking shape now -- I'll allow >>>>>>>>> (another) delay for the branch until tomorrow (morning?) for some >>>>>>>>> (hopefully final) checks on that. >>>>>>>>> >>>>>>>>> On Thu, 8 Nov 2018 at 14:35, Tyler Reddy >>>>>>>>> wrote: >>>>>>>>> >>>>>>>>>> There are 0 remaining PRs with a 1.2.0 milestone. >>>>>>>>>> >>>>>>>>>> There is one issue left with a 1.2.0 milestone: >>>>>>>>>> https://github.com/scipy/scipy/issues/9441 >>>>>>>>>> >>>>>>>>>> Please do take a look over the release notes WIP PR based on the >>>>>>>>>> wiki: https://github.com/scipy/scipy/pull/9461 >>>>>>>>>> >>>>>>>>>> Target is to branch in 5-6 hours or so. Let me know if you see >>>>>>>>>> any issues of course -- Ralf has been coaching >>>>>>>>>> me through pretty well so far I think. >>>>>>>>>> >>>>>>>>>> On Wed, 7 Nov 2018 at 09:52, Ilhan Polat >>>>>>>>>> wrote: >>>>>>>>>> >>>>>>>>>>> Hang in there Tyler :) >>>>>>>>>>> >>>>>>>>>>> Awesome job so far. >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> On Wed, Nov 7, 2018, 06:08 Ralf Gommers >>>>>>>>>>> wrote: >>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> On Tue, Nov 6, 2018 at 9:03 PM Tyler Reddy < >>>>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>>>> >>>>>>>>>>>>> 7 PRs : >>>>>>>>>>>>> https://github.com/scipy/scipy/pulls?q=is%3Aopen+is%3Apr+milestone%3A1.2.0 >>>>>>>>>>>>> 3 issues: >>>>>>>>>>>>> https://github.com/scipy/scipy/issues?q=is%3Aopen+is%3Aissue+milestone%3A1.2.0 >>>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> Awesome, getting there:) >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>>> Target: branch sometime on November 8th >>>>>>>>>>>>> >>>>>>>>>>>>> On Mon, 5 Nov 2018 at 05:42, Tyler Reddy < >>>>>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>>>>> >>>>>>>>>>>>>> Alright, I'll extend to Thursday Nov. 8th & see if I can >>>>>>>>>>>>>> reduce that list a bit >>>>>>>>>>>>>> >>>>>>>>>>>>>> On Sun, 4 Nov 2018 at 22:27, Ralf Gommers < >>>>>>>>>>>>>> ralf.gommers at gmail.com> wrote: >>>>>>>>>>>>>> >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> On Fri, Oct 26, 2018 at 7:03 PM Mark Alexander Mikofski < >>>>>>>>>>>>>>> mikofski at berkeley.edu> wrote: >>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Hi Tyler and others, >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Thanks for managing the v1.2 release. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> I think PR #8431, Cython optimize zeros API, is ready, >>>>>>>>>>>>>>>> hopefully, to merge. It's been through several rounds of reviews and I >>>>>>>>>>>>>>>> think I've accommodated all of the recommendations, all tests are passing, >>>>>>>>>>>>>>>> and there's been strong support. Anyone please take a look. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> https://github.com/scipy/scipy/pull/8431 >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Thanks, >>>>>>>>>>>>>>>> Mark >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> On Fri, Oct 26, 2018, 2:38 PM Ralf Gommers < >>>>>>>>>>>>>>>> ralf.gommers at gmail.com> wrote: >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> On Thu, Oct 25, 2018 at 12:55 PM Tyler Reddy < >>>>>>>>>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> Hi all, >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> It is almost 6 months after the 1.1.0 release on May 5, >>>>>>>>>>>>>>>>>> so probably time to plan the 1.2.0 release. It would be a good idea to look >>>>>>>>>>>>>>>>>> over the PRs with a 1.2.0 milestone >>>>>>>>>>>>>>>>>> , >>>>>>>>>>>>>>>>>> and tag anything else that should have this milestone appropriately. >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> I'd like to propose the following schedule: >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> Nov. 5: branch 1.2.x >>>>>>>>>>>>>>>>>> Nov. 8: rc1 >>>>>>>>>>>>>>>>>> Nov. 21: rc2 (if needed) >>>>>>>>>>>>>>>>>> Nov. 30: final release >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> Thoughts? >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> This looks like a good schedule to me. We'll probably >>>>>>>>>>>>>>>>> struggle to get some PRs marked for 1.2.0 merged, but that's always the >>>>>>>>>>>>>>>>> case. >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>> Hi Tyler, could we shift the branch date by 2-3 days (or up >>>>>>>>>>>>>>> to a week)? There's a couple of PRs that I'd really like to see merged or >>>>>>>>>>>>>>> decided on (for optimize and stats mainly), and there's right now still 18 >>>>>>>>>>>>>>> open PRs marked for 1.2.0. >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> A note on the open PRs: what we want to aim for is to have >>>>>>>>>>>>>>> the list of open PRs and open blocking issues at zero, and have at most >>>>>>>>>>>>>>> some non-blocking issues under the milestone left. Normally the release >>>>>>>>>>>>>>> manager starts making those decisions, or pinging people, if other >>>>>>>>>>>>>>> reviewers haven't done so in time. Of course it would be ideal if everyone >>>>>>>>>>>>>>> has another look at >>>>>>>>>>>>>>> https://github.com/scipy/scipy/pulls?q=is%3Aopen+is%3Apr+milestone%3A1.2.0 >>>>>>>>>>>>>>> and bumps or finished off PRs he/she is involved in. >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> Cheers, >>>>>>>>>>>>>>> Ralf >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>>>>>> >>>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>>>> >>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>>> >>>>>>>>>>> _______________________________________________ >>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>> >>>>>>>>>> _______________________________________________ >>>>>>> SciPy-Dev mailing list >>>>>>> SciPy-Dev at python.org >>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>> >>>>>> _______________________________________________ >>>>>> SciPy-Dev mailing list >>>>>> SciPy-Dev at python.org >>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>> >>>>> _______________________________________________ >>>>> SciPy-Dev mailing list >>>>> SciPy-Dev at python.org >>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>> >>>> _______________________________________________ >>>> SciPy-Dev mailing list >>>> SciPy-Dev at python.org >>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>> >>> _______________________________________________ >>> SciPy-Dev mailing list >>> SciPy-Dev at python.org >>> https://mail.python.org/mailman/listinfo/scipy-dev >>> >> _______________________________________________ >> SciPy-Dev mailing list >> SciPy-Dev at python.org >> https://mail.python.org/mailman/listinfo/scipy-dev >> > -------------- next part -------------- An HTML attachment was scrubbed... URL: From tyler.je.reddy at gmail.com Wed Dec 5 13:35:59 2018 From: tyler.je.reddy at gmail.com (Tyler Reddy) Date: Wed, 5 Dec 2018 10:35:59 -0800 Subject: [SciPy-Dev] ANN: SciPy 1.2.0rc2 -- please test Message-ID: -----BEGIN PGP SIGNED MESSAGE----- Hash: SHA256 Hi all, On behalf of the SciPy development team I'm pleased to announce the release candidate SciPy 1.2.0rc2. Please help us test out this release candidate -- the 1.2.x series will be an LTS release and the last to support Python 2.7. Sources and binary wheels can be found at: https://pypi.org/project/scipy/ and at: https://github.com/scipy/scipy/releases/tag/v1.2.0rc2 One of a few ways to install the release candidate with pip: pip install scipy==1.2.0rc2 ========================== SciPy 1.2.0 Release Notes ========================== Note: Scipy 1.2.0 is not released yet! SciPy 1.2.0 is the culmination of 6 months of hard work. It contains many new features, numerous bug-fixes, improved test coverage and better documentation. There have been a number of deprecations and API changes in this release, which are documented below. All users are encouraged to upgrade to this release, as there are a large number of bug-fixes and optimizations. Before upgrading, we recommend that users check that their own code does not use deprecated SciPy functionality (to do so, run your code with ``python -Wd`` and check for ``DeprecationWarning`` s). Our development attention will now shift to bug-fix releases on the 1.2.x branch, and on adding new features on the master branch. This release requires Python 2.7 or 3.4+ and NumPy 1.8.2 or greater. Note: This will be the last SciPy release to support Python 2.7. Consequently, the 1.2.x series will be a long term support (LTS) release; we will backport bug fixes until 1 Jan 2020. For running on PyPy, PyPy3 6.0+ and NumPy 1.15.0 are required. Highlights of this release --------------------------- - 1-D root finding improvements with a new solver, ``toms748``, and a new unified interface, ``root_scalar`` - New ``dual_annealing`` optimization method that combines stochastic and local deterministic searching - A new optimization algorithm, ``shgo`` (simplicial homology global optimization) for derivative free optimization problems - A new category of quaternion-based transformations are available in `scipy.spatial.transform` New features ============ `scipy.ndimage` improvements --------------------------------- Proper spline coefficient calculations have been added for the ``mirror``, ``wrap``, and ``reflect`` modes of `scipy.ndimage.rotate` `scipy.fftpack` improvements --------------------------------- DCT-IV, DST-IV, DCT-I, and DST-I orthonormalization are now supported in `scipy.fftpack`. `scipy.interpolate` improvements --------------------------------- `scipy.interpolate.pade` now accepts a new argument for the order of the numerator `scipy.cluster` improvements ----------------------------- `scipy.cluster.vq.kmeans2` gained a new initialization method, kmeans++. `scipy.special` improvements ----------------------------- The function ``softmax`` was added to `scipy.special`. `scipy.optimize` improvements ------------------------------ The one-dimensional nonlinear solvers have been given a unified interface `scipy.optimize.root_scalar`, similar to the `scipy.optimize.root` interface for multi-dimensional solvers. ``scipy.optimize.root_scalar(f, bracket=[a ,b], method="brenth")`` is equivalent to ``scipy.optimize.brenth(f, a ,b)``. If no ``method`` is specified, an appropriate one will be selected based upon the bracket and the number of derivatives available. The so-called Algorithm 748 of Alefeld, Potra and Shi for root-finding within an enclosing interval has been added as `scipy.optimize.toms748`. This provides guaranteed convergence to a root with convergence rate per function evaluation of approximately 1.65 (for sufficiently well-behaved functions.) ``differential_evolution`` now has the ``updating`` and ``workers`` keywords. The first chooses between continuous updating of the best solution vector (the default), or once per generation. Continuous updating can lead to faster convergence. The ``workers`` keyword accepts an ``int`` or map-like callable, and parallelises the solver (having the side effect of updating once per generation). Supplying an ``int`` evaluates the trial solutions in N parallel parts. Supplying a map-like callable allows other parallelisation approaches (such as ``mpi4py``, or ``joblib``) to be used. ``dual_annealing`` (and ``shgo`` below) is a powerful new general purpose global optizimation (GO) algorithm. ``dual_annealing`` uses two annealing processes to accelerate the convergence towards the global minimum of an objective mathematical function. The first annealing process controls the stochastic Markov chain searching and the second annealing process controls the deterministic minimization. So, dual annealing is a hybrid method that takes advantage of stochastic and local deterministic searching in an efficient way. ``shgo`` (simplicial homology global optimization) is a similar algorithm appropriate for solving black box and derivative free optimization (DFO) problems. The algorithm generally converges to the global solution in finite time. The convergence holds for non-linear inequality and equality constraints. In addition to returning a global minimum, the algorithm also returns any other global and local minima found after every iteration. This makes it useful for exploring the solutions in a domain. `scipy.optimize.newton` can now accept a scalar or an array ``MINPACK`` usage is now thread-safe, such that ``MINPACK`` + callbacks may be used on multiple threads. `scipy.signal` improvements ---------------------------- Digital filter design functions now include a parameter to specify the sampling rate. Previously, digital filters could only be specified using normalized frequency, but different functions used different scales (e.g. 0 to 1 for ``butter`` vs 0 to ? for ``freqz``), leading to errors and confusion. With the ``fs`` parameter, ordinary frequencies can now be entered directly into functions, with the normalization handled internally. ``find_peaks`` and related functions no longer raise an exception if the properties of a peak have unexpected values (e.g. a prominence of 0). A ``PeakPropertyWarning`` is given instead. The new keyword argument ``plateau_size`` was added to ``find_peaks``. ``plateau_size`` may be used to select peaks based on the length of the flat top of a peak. ``welch()`` and ``csd()`` methods in `scipy.signal` now support calculation of a median average PSD, using ``average='mean'`` keyword `scipy.sparse` improvements ---------------------------- The `scipy.sparse.bsr_matrix.tocsr` method is now implemented directly instead of converting via COO format, and the `scipy.sparse.bsr_matrix.tocsc` method is now also routed via CSR conversion instead of COO. The efficiency of both conversions is now improved. The issue where SuperLU or UMFPACK solvers crashed on matrices with non-canonical format in `scipy.sparse.linalg` was fixed. The solver wrapper canonicalizes the matrix if necessary before calling the SuperLU or UMFPACK solver. The ``largest`` option of `scipy.sparse.linalg.lobpcg()` was fixed to have a correct (and expected) behavior. The order of the eigenvalues was made consistent with the ARPACK solver (``eigs()``), i.e. ascending for the smallest eigenvalues, and descending for the largest eigenvalues. The `scipy.sparse.random` function is now faster and also supports integer and complex values by passing the appropriate value to the ``dtype`` argument. `scipy.spatial` improvements ----------------------------- The function `scipy.spatial.distance.jaccard` was modified to return 0 instead of ``np.nan`` when two all-zero vectors are compared. Support for the Jensen Shannon distance, the square-root of the divergence, has been added under `scipy.spatial.distance.jensenshannon` An optional keyword was added to the function `scipy.spatial.cKDTree.query_ball_point()` to sort or not sort the returned indices. Not sorting the indices can speed up calls. A new category of quaternion-based transformations are available in `scipy.spatial.transform`, including spherical linear interpolation of rotations (``Slerp``), conversions to and from quaternions, Euler angles, and general rotation and inversion capabilities (`spatial.transform.Rotation`), and uniform random sampling of 3D rotations (`spatial.transform.Rotation.random`). `scipy.stats` improvements --------------------------- The Yeo-Johnson power transformation is now supported (``yeojohnson``, ``yeojohnson_llf``, ``yeojohnson_normmax``, ``yeojohnson_normplot``). Unlike the Box-Cox transformation, the Yeo-Johnson transformation can accept negative values. Added a general method to sample random variates based on the density only, in the new function ``rvs_ratio_uniforms``. The Yule-Simon distribution (``yulesimon``) was added -- this is a new discrete probability distribution. ``stats`` and ``mstats`` now have access to a new regression method, ``siegelslopes``, a robust linear regression algorithm `scipy.stats.gaussian_kde` now has the ability to deal with weighted samples, and should have a modest improvement in performance Levy Stable Parameter Estimation, PDF, and CDF calculations are now supported for `scipy.stats.levy_stable`. The Brunner-Munzel test is now available as ``brunnermunzel`` in ``stats`` and ``mstats`` `scipy.linalg` improvements --------------------------- `scipy.linalg.lapack` now exposes the LAPACK routines using the Rectangular Full Packed storage (RFP) for upper triangular, lower triangular, symmetric, or Hermitian matrices; the upper trapezoidal fat matrix RZ decomposition routines are now available as well. Deprecated features =================== The functions ``hyp2f0``, ``hyp1f2`` and ``hyp3f0`` in ``scipy.special`` have been deprecated. Backwards incompatible changes ============================== LAPACK version 3.4.0 or later is now required. Building with Apple Accelerate is no longer supported. The function ``scipy.linalg.subspace_angles(A, B)`` now gives correct results for all angles. Before this, the function only returned correct values for those angles which were greater than pi/4. Support for the Bento build system has been removed. Bento has not been maintained for several years, and did not have good Python 3 or wheel support, hence it was time to remove it. The required signature of `scipy.optimize.lingprog` ``method=simplex`` callback function has changed. Before iteration begins, the simplex solver first converts the problem into a standard form that does not, in general, have the same variables or constraints as the problem defined by the user. Previously, the simplex solver would pass a user-specified callback function several separate arguments, such as the current solution vector ``xk``, corresponding to this standard form problem. Unfortunately, the relationship between the standard form problem and the user-defined problem was not documented, limiting the utility of the information passed to the callback function. In addition to numerous bug fix changes, the simplex solver now passes a user-specified callback function a single ``OptimizeResult`` object containing information that corresponds directly to the user-defined problem. In future releases, this ``OptimizeResult`` object may be expanded to include additional information, such as variables corresponding to the standard-form problem and information concerning the relationship between the standard-form and user-defined problems. The implementation of `scipy.sparse.random` has changed, and this affects the numerical values returned for both ``sparse.random`` and ``sparse.rand`` for some matrix shapes and a given seed. `scipy.optimize.newton` will no longer use Halley's method in cases where it negatively impacts convergence Other changes ============= Authors ======= * @endolith * @luzpaz * Hameer Abbasi + * akahard2dj + * Anton Akhmerov * Joseph Albert * alexthomas93 + * ashish + * atpage + * Blair Azzopardi + * Yoshiki V?zquez Baeza * Bence Bagi + * Christoph Baumgarten * Lucas Bellomo + * BH4 + * Aditya Bharti * Max Bolingbroke * Fran?ois Boulogne * Ward Bradt + * Matthew Brett * Evgeni Burovski * Rafa? Byczek + * Alfredo Canziani + * CJ Carey * Luc?a Cheung + * Poom Chiarawongse + * Jeanne Choo + * Robert Cimrman * Graham Clenaghan + * cynthia-rempel + * Johannes Damp + * Jaime Fernandez del Rio * Dowon + * emmi474 + * Stefan Endres + * Thomas Etherington + * Piotr Figiel * Alex Fikl + * fo40225 + * Joseph Fox-Rabinovitz * Lars G * Abhinav Gautam + * Stiaan Gerber + * C.A.M. Gerlach + * Ralf Gommers * Todd Goodall * Lars Grueter + * Sylvain Gubian + * Matt Haberland * David Hagen * Will Handley + * Charles Harris * Ian Henriksen * Thomas Hisch + * Theodore Hu * Michael Hudson-Doyle + * Nicolas Hug + * jakirkham + * Jakob Jakobson + * James + * Jan Schl?ter * jeanpauphilet + * josephmernst + * Kai + * Kai-Striega + * kalash04 + * Toshiki Kataoka + * Konrad0 + * Tom Krauss + * Johannes Kulick * Lars Gr?ter + * Eric Larson * Denis Laxalde * Will Lee + * Katrin Leinweber + * Yin Li + * P. L. Lim + * Jesse Livezey + * Duncan Macleod + * MatthewFlamm + * Nikolay Mayorov * Mike McClurg + * Christian Meyer + * Mark Mikofski * Naoto Mizuno + * mohmmadd + * Nathan Musoke * Anju Geetha Nair + * Andrew Nelson * Ayappan P + * Nick Papior * Haesun Park + * Ronny Pfannschmidt + * pijyoi + * Ilhan Polat * Anthony Polloreno + * Ted Pudlik * puenka * Eric Quintero * Pradeep Reddy Raamana + * Vyas Ramasubramani + * Ramon Vi?as + * Tyler Reddy * Joscha Reimer * Antonio H Ribeiro * richardjgowers + * Rob + * robbystk + * Lucas Roberts + * rohan + * Joaquin Derrac Rus + * Josua Sassen + * Bruce Sharpe + * Max Shinn + * Scott Sievert * Sourav Singh * Strahinja Luki? + * Kai Striega + * Shinya SUZUKI + * Mike Toews + * Piotr Uchwat * Miguel de Val-Borro + * Nicky van Foreest * Paul van Mulbregt * Gael Varoquaux * Pauli Virtanen * Stefan van der Walt * Warren Weckesser * Joshua Wharton + * Bernhard M. Wiedemann + * Eric Wieser * Josh Wilson * Tony Xiang + * Roman Yurchak + * Roy Zywina + A total of 137 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete. Issues closed for 1.2.0 ------------------------ * `#9520 `__: signal.correlate with method='fft' doesn't benefit from long... * `#9547 `__: signature of dual_annealing doesn't match other optimizers * `#9540 `__: SciPy v1.2.0rc1 cannot be imported on Python 2.7.15 * `#1240 `__: Allowing multithreaded use of minpack through scipy.optimize... * `#1432 `__: scipy.stats.mode extremely slow (Trac #905) * `#3372 `__: Please add Sphinx search field to online scipy html docs * `#3678 `__: _clough_tocher_2d_single direction between centroids * `#4174 `__: lobpcg "largest" option invalid? * `#5493 `__: anderson_ksamp p-values>1 * `#5743 `__: slsqp fails to detect infeasible problem * `#6139 `__: scipy.optimize.linprog failed to find a feasible starting point... * `#6358 `__: stats: docstring for `vonmises_line` points to `vonmises_line`... * `#6498 `__: runtests.py is missing in pypi distfile * `#7426 `__: scipy.stats.ksone(n).pdf(x) returns nan for positive values of... * `#7455 `__: scipy.stats.ksone.pdf(2,x) return incorrect values for x near... * `#7456 `__: scipy.special.smirnov and scipy.special.smirnovi have accuracy... * `#7492 `__: scipy.special.kolmogorov(x)/kolmogi(p) inefficient, inaccurate... * `#7914 `__: TravisCI not failing when it should for -OO run * `#8064 `__: linalg.solve test crashes on Windows * `#8212 `__: LAPACK Rectangular Full Packed routines * `#8256 `__: differential_evolution bug converges to wrong results in complex... * `#8443 `__: Deprecate `hyp2f0`, `hyp1f2`, and `hyp3f0`? * `#8452 `__: DOC: ARPACK tutorial has two conflicting equations * `#8680 `__: scipy fails compilation when building from source * `#8686 `__: Division by zero in _trustregion.py when x0 is exactly equal... * `#8700 `__: _MINPACK_LOCK not held when calling into minpack from least_squares * `#8786 `__: erroneous moment values for t-distribution * `#8791 `__: Checking COLA condition in istft should be optional (or omitted) * `#8843 `__: imresize cannot be deprecated just yet * `#8844 `__: Inverse Wishart Log PDF Incorrect for Non-diagonal Scale Matrix? * `#8878 `__: vonmises and vonmises_line in stats: vonmises wrong and superfluous? * `#8895 `__: v1.1.0 `ndi.rotate` documentation ? reused parameters not filled... * `#8900 `__: Missing complex conjugation in scipy.sparse.linalg.LinearOperator * `#8904 `__: BUG: if zero derivative at root, then Newton fails with RuntimeWarning * `#8911 `__: make_interp_spline bc_type incorrect input interpretation * `#8942 `__: MAINT: Refactor `_linprog.py` and `_linprog_ip.py` to remove... * `#8947 `__: np.int64 in scipy.fftpack.next_fast_len * `#9020 `__: BUG: linalg.subspace_angles gives wrong results * `#9033 `__: scipy.stats.normaltest sometimes gives incorrect returns b/c... * `#9036 `__: Bizarre times for `scipy.sparse.rand` function with 'low' density... * `#9044 `__: optimize.minimize(method=`trust-constr`) result dict does not... * `#9071 `__: doc/linalg: add cho_solve_banded to see also of cholesky_banded * `#9082 `__: eigenvalue sorting in scipy.sparse.linalg.eigsh * `#9086 `__: signaltools.py:491: FutureWarning: Using a non-tuple sequence... * `#9091 `__: test_spline_filter failure on 32-bit * `#9122 `__: Typo on scipy minimization tutorial * `#9135 `__: doc error at https://docs.scipy.org/doc/scipy/reference/tutorial/stats/discrete_poisson.html * `#9167 `__: DOC: BUG: typo in ndimage LowLevelCallable tutorial example * `#9169 `__: truncnorm does not work if b < a in scipy.stats * `#9250 `__: scipy.special.tests.test_mpmath::TestSystematic::test_pcfw fails... * `#9259 `__: rv.expect() == rv.mean() is false for rv.mean() == nan (and inf) * `#9286 `__: DOC: Rosenbrock expression in optimize.minimize tutorial * `#9316 `__: SLSQP fails in nested optimization * `#9337 `__: scipy.signal.find_peaks key typo in documentation * `#9345 `__: Example from documentation of scipy.sparse.linalg.eigs raises... * `#9383 `__: Default value for "mode" in "ndimage.shift" * `#9419 `__: dual_annealing off by one in the number of iterations * `#9442 `__: Error in Defintion of Rosenbrock Function * `#9453 `__: TST: test_eigs_consistency() doesn't have consistent results Pull requests for 1.2.0 ------------------------ * `#9526 `__: TST: relax precision requirements in signal.correlate tests * `#9507 `__: CI: MAINT: Skip a ckdtree test on pypy * `#9512 `__: TST: test_random_sampling 32-bit handling * `#9494 `__: TST: test_kolmogorov xfail 32-bit * `#9486 `__: BUG: fix sparse random int handling * `#9550 `__: BUG: scipy/_lib/_numpy_compat: get_randint * `#9549 `__: MAINT: make dual_annealing signature match other optimizers * `#9541 `__: BUG: fix SyntaxError due to non-ascii character on Python 2.7 * `#7352 `__: ENH: add Brunner Munzel test to scipy.stats. * `#7373 `__: BUG: Jaccard distance for all-zero arrays would return np.nan * `#7374 `__: ENH: Add PDF, CDF and parameter estimation for Stable Distributions * `#8098 `__: ENH: Add shgo for global optimization of NLPs. * `#8203 `__: ENH: adding simulated dual annealing to optimize * `#8259 `__: Option to follow original Storn and Price algorithm and its parallelisation * `#8293 `__: ENH add ratio-of-uniforms method for rv generation to scipy.stats * `#8294 `__: BUG: Fix slowness in stats.mode * `#8295 `__: ENH: add Jensen Shannon distance to `scipy.spatial.distance` * `#8357 `__: ENH: vectorize scalar zero-search-functions * `#8397 `__: Add `fs=` parameter to filter design functions * `#8537 `__: ENH: Implement mode parameter for spline filtering. * `#8558 `__: ENH: small speedup for stats.gaussian_kde * `#8560 `__: BUG: fix p-value calc of anderson_ksamp in scipy.stats * `#8614 `__: ENH: correct p-values for stats.kendalltau and stats.mstats.kendalltau * `#8670 `__: ENH: Require Lapack 3.4.0 * `#8683 `__: Correcting kmeans documentation * `#8725 `__: MAINT: Cleanup scipy.optimize.leastsq * `#8726 `__: BUG: Fix _get_output in scipy.ndimage to support string * `#8733 `__: MAINT: stats: A bit of clean up. * `#8737 `__: BUG: Improve numerical precision/convergence failures of smirnov/kolmogorov * `#8738 `__: MAINT: stats: A bit of clean up in test_distributions.py. * `#8740 `__: BF/ENH: make minpack thread safe * `#8742 `__: BUG: Fix division by zero in trust-region optimization methods * `#8746 `__: MAINT: signal: Fix a docstring of a private function, and fix... * `#8750 `__: DOC clarified description of norminvgauss in scipy.stats * `#8753 `__: DOC: signal: Fix a plot title in the chirp docstring. * `#8755 `__: DOC: MAINT: Fix link to the wheel documentation in developer... * `#8760 `__: BUG: stats: boltzmann wasn't setting the upper bound. * `#8763 `__: [DOC] Improved scipy.cluster.hierarchy documentation * `#8765 `__: DOC: added example for scipy.stat.mstats.tmin * `#8788 `__: DOC: fix definition of optional `disp` parameter * `#8802 `__: MAINT: Suppress dd_real unused function compiler warnings. * `#8803 `__: ENH: Add full_output support to optimize.newton() * `#8804 `__: MAINT: stats cleanup * `#8808 `__: DOC: add note about isinstance for frozen rvs * `#8812 `__: Updated numpydoc submodule * `#8813 `__: MAINT: stats: Fix multinomial docstrings, and do some clean up. * `#8816 `__: BUG: fixed _stats of t-distribution in scipy.stats * `#8817 `__: BUG: ndimage: Fix validation of the origin argument in correlate... * `#8822 `__: BUG: integrate: Fix crash with repeated t values in odeint. * `#8832 `__: Hyperlink DOIs against preferred resolver * `#8837 `__: BUG: sparse: Ensure correct dtype for sparse comparison operations. * `#8839 `__: DOC: stats: A few tweaks to the linregress docstring. * `#8846 `__: BUG: stats: Fix logpdf method of invwishart. * `#8849 `__: DOC: signal: Fixed mistake in the firwin docstring. * `#8854 `__: DOC: fix type descriptors in ltisys documentation * `#8865 `__: Fix tiny typo in docs for chi2 pdf * `#8870 `__: Fixes related to invertibility of STFT * `#8872 `__: ENH: special: Add the softmax function * `#8874 `__: DOC correct gamma function in docstrings in scipy.stats * `#8876 `__: ENH: Added TOMS Algorithm 748 as 1-d root finder; 17 test function... * `#8882 `__: ENH: Only use Halley's adjustment to Newton if close enough. * `#8883 `__: FIX: optimize: make jac and hess truly optional for 'trust-constr' * `#8885 `__: TST: Do not error on warnings raised about non-tuple indexing. * `#8887 `__: MAINT: filter out np.matrix PendingDeprecationWarning's in numpy... * `#8889 `__: DOC: optimize: separate legacy interfaces from new ones * `#8890 `__: ENH: Add optimize.root_scalar() as a universal dispatcher for... * `#8899 `__: DCT-IV, DST-IV and DCT-I, DST-I orthonormalization support in... * `#8901 `__: MAINT: Reorganize flapack.pyf.src file * `#8907 `__: BUG: ENH: Check if guess for newton is already zero before checking... * `#8908 `__: ENH: Make sorting optional for cKDTree.query_ball_point() * `#8910 `__: DOC: sparse.csgraph simple examples. * `#8914 `__: DOC: interpolate: fix equivalences of string aliases * `#8918 `__: add float_control(precise, on) to _fpumode.c * `#8919 `__: MAINT: interpolate: improve error messages for common `bc_type`... * `#8920 `__: DOC: update Contributing to SciPy to say "prefer no PEP8 only... * `#8924 `__: MAINT: special: deprecate `hyp2f0`, `hyp1f2`, and `hyp3f0` * `#8927 `__: MAINT: special: remove `errprint` * `#8932 `__: Fix broadcasting scale arg of entropy * `#8936 `__: Fix (some) non-tuple index warnings * `#8937 `__: ENH: implement sparse matrix BSR to CSR conversion directly. * `#8938 `__: DOC: add @_ni_docstrings.docfiller in ndimage.rotate * `#8940 `__: Update _discrete_distns.py * `#8943 `__: DOC: Finish dangling sentence in `convolve` docstring * `#8944 `__: MAINT: Address tuple indexing and warnings * `#8945 `__: ENH: spatial.transform.Rotation [GSOC2018] * `#8950 `__: csgraph Dijkstra function description rewording * `#8953 `__: DOC, MAINT: HTTP -> HTTPS, and other linkrot fixes * `#8955 `__: BUG: np.int64 in scipy.fftpack.next_fast_len * `#8958 `__: MAINT: Add more descriptive error message for phase one simplex. * `#8962 `__: BUG: sparse.linalg: add missing conjugate to _ScaledLinearOperator.adjoint * `#8963 `__: BUG: sparse.linalg: downgrade LinearOperator TypeError to warning * `#8965 `__: ENH: Wrapped RFP format and RZ decomposition routines * `#8969 `__: MAINT: doc and code fixes for optimize.newton * `#8970 `__: Added 'average' keyword for welch/csd to enable median averaging * `#8971 `__: Better imresize deprecation warning * `#8972 `__: MAINT: Switch np.where(c) for np.nonzero(c) * `#8975 `__: MAINT: Fix warning-based failures * `#8979 `__: DOC: fix description of count_sort keyword of dendrogram * `#8982 `__: MAINT: optimize: Fixed minor mistakes in test_linprog.py (#8978) * `#8984 `__: BUG: sparse.linalg: ensure expm casts integer inputs to float * `#8986 `__: BUG: optimize/slsqp: do not exit with convergence on steps where... * `#8989 `__: MAINT: use collections.abc in basinhopping * `#8990 `__: ENH extend p-values of anderson_ksamp in scipy.stats * `#8991 `__: ENH: Weighted kde * `#8993 `__: ENH: spatial.transform.Rotation.random [GSOC 2018] * `#8994 `__: ENH: spatial.transform.Slerp [GSOC 2018] * `#8995 `__: TST: time.time in test * `#9007 `__: Fix typo in fftpack.rst * `#9013 `__: Added correct plotting code for two sided output from spectrogram * `#9014 `__: BUG: differential_evolution with inf objective functions * `#9017 `__: BUG: fixed #8446 corner case for asformat(array|dense) * `#9018 `__: MAINT: _lib/ccallback: remove unused code * `#9021 `__: BUG: Issue with subspace_angles * `#9022 `__: DOC: Added "See Also" section to lombscargle docstring * `#9034 `__: BUG: Fix tolerance printing behavior, remove meaningless tol... * `#9035 `__: TST: improve signal.bsplines test coverage * `#9037 `__: ENH: add a new init method for k-means * `#9039 `__: DOC: Add examples to fftpack.irfft docstrings * `#9048 `__: ENH: scipy.sparse.random * `#9050 `__: BUG: scipy.io.hb_write: fails for matrices not in csc format * `#9051 `__: MAINT: Fix slow sparse.rand for k < mn/3 (#9036). * `#9054 `__: MAINT: spatial: Explicitly initialize LAPACK output parameters. * `#9055 `__: DOC: Add examples to scipy.special docstrings * `#9056 `__: ENH: Use one thread in OpenBLAS * `#9059 `__: DOC: Update README with link to Code of Conduct * `#9060 `__: BLD: remove support for the Bento build system. * `#9062 `__: DOC add sections to overview in scipy.stats * `#9066 `__: BUG: Correct "remez" error message * `#9069 `__: DOC: update linalg section of roadmap for LAPACK versions. * `#9079 `__: MAINT: add spatial.transform to refguide check; complete some... * `#9081 `__: MAINT: Add warnings if pivot value is close to tolerance in linprog(method='simplex') * `#9084 `__: BUG fix incorrect p-values of kurtosistest in scipy.stats * `#9095 `__: DOC: add sections to mstats overview in scipy.stats * `#9096 `__: BUG: Add test for Stackoverflow example from issue 8174. * `#9101 `__: ENH: add Siegel slopes (robust regression) to scipy.stats * `#9105 `__: allow resample_poly() to output float32 for float32 inputs. * `#9112 `__: MAINT: optimize: make trust-constr accept constraint dict (#9043) * `#9118 `__: Add doc entry to cholesky_banded * `#9120 `__: eigsh documentation parameters * `#9125 `__: interpolative: correctly reconstruct full rank matrices * `#9126 `__: MAINT: Use warnings for unexpected peak properties * `#9129 `__: BUG: Do not catch and silence KeyboardInterrupt * `#9131 `__: DOC: Correct the typo in scipy.optimize tutorial page * `#9133 `__: FIX: Avoid use of bare except * `#9134 `__: DOC: Update of 'return_eigenvectors' description * `#9137 `__: DOC: typo fixes for discrete Poisson tutorial * `#9139 `__: FIX: Doctest failure in optimize tutorial * `#9143 `__: DOC: missing sigma in Pearson r formula * `#9145 `__: MAINT: Refactor linear programming solvers * `#9149 `__: FIX: Make scipy.odr.ODR ifixx equal to its data.fix if given * `#9156 `__: DOC: special: Mention the sigmoid function in the expit docstring. * `#9160 `__: Fixed a latex delimiter error in levy() * `#9170 `__: DOC: correction / update of docstrings of distributions in scipy.stats * `#9171 `__: better description of the hierarchical clustering parameter * `#9174 `__: domain check for a < b in stats.truncnorm * `#9175 `__: DOC: Minor grammar fix * `#9176 `__: BUG: CloughTocher2DInterpolator: fix miscalculation at neighborless... * `#9177 `__: BUILD: Document the "clean" target in the doc/Makefile. * `#9178 `__: MAINT: make refguide-check more robust for printed numpy arrays * `#9186 `__: MAINT: Remove np.ediff1d occurence * `#9188 `__: DOC: correct typo in extending ndimage with C * `#9190 `__: ENH: Support specifying axes for fftconvolve * `#9192 `__: MAINT: optimize: fixed @pv style suggestions from #9112 * `#9200 `__: Fix make_interp_spline(..., k=0 or 1, axis<0) * `#9201 `__: BUG: sparse.linalg/gmres: use machine eps in breakdown check * `#9204 `__: MAINT: fix up stats.spearmanr and match mstats.spearmanr with... * `#9206 `__: MAINT: include benchmarks and dev files in sdist. * `#9208 `__: TST: signal: bump bsplines test tolerance for complex data * `#9210 `__: TST: mark tests as slow, fix missing random seed * `#9211 `__: ENH: add capability to specify orders in pade func * `#9217 `__: MAINT: Include ``success`` and ``nit`` in OptimizeResult returned... * `#9222 `__: ENH: interpolate: Use scipy.spatial.distance to speed-up Rbf * `#9229 `__: MNT: Fix Fourier filter double case * `#9233 `__: BUG: spatial/distance: fix pdist/cdist performance regression... * `#9234 `__: FIX: Proper suppression * `#9235 `__: BENCH: rationalize slow benchmarks + miscellaneous fixes * `#9238 `__: BENCH: limit number of parameter combinations in spatial.*KDTree... * `#9239 `__: DOC: stats: Fix LaTeX markup of a couple distribution PDFs. * `#9241 `__: ENH: Evaluate plateau size during peak finding * `#9242 `__: ENH: stats: Implement _ppf and _logpdf for crystalball, and do... * `#9246 `__: DOC: Properly render versionadded directive in HTML documentation * `#9255 `__: DOC: mention RootResults in optimization reference guide * `#9260 `__: TST: relax some tolerances so tests pass with x87 math * `#9264 `__: TST Use assert_raises "match" parameter instead of the "message"... * `#9267 `__: DOC: clarify expect() return val when moment is inf/nan * `#9272 `__: DOC: Add description of default bounds to linprog * `#9277 `__: MAINT: sparse/linalg: make test deterministic * `#9278 `__: MAINT: interpolate: pep8 cleanup in test_polyint * `#9279 `__: Fixed docstring for resample * `#9280 `__: removed first check for float in get_sum_dtype * `#9281 `__: BUG: only accept 1d input for bartlett / levene in scipy.stats * `#9282 `__: MAINT: dense_output and t_eval are mutually exclusive inputs * `#9283 `__: MAINT: add docs and do some cleanups in interpolate.Rbf * `#9288 `__: Run distance_transform_edt tests on all types * `#9294 `__: DOC: fix the formula typo * `#9298 `__: MAINT: optimize/trust-constr: restore .niter attribute for backward-compat * `#9299 `__: DOC: clarification of default rvs method in scipy.stats * `#9301 `__: MAINT: removed unused import sys * `#9302 `__: MAINT: removed unused imports * `#9303 `__: DOC: signal: Refer to fs instead of nyq in the firwin docstring. * `#9305 `__: ENH: Added Yeo-Johnson power transformation * `#9306 `__: ENH - add dual annealing * `#9309 `__: ENH add the yulesimon distribution to scipy.stats * `#9317 `__: Nested SLSQP bug fix. * `#9320 `__: MAINT: stats: avoid underflow in stats.geom.ppf * `#9326 `__: Add example for Rosenbrock function * `#9332 `__: Sort file lists * `#9340 `__: Fix typo in find_peaks documentation * `#9343 `__: MAINT Use np.full when possible * `#9344 `__: DOC: added examples to docstring of dirichlet class * `#9346 `__: DOC: Fix import of scipy.sparse.linalg in example (#9345) * `#9350 `__: Fix interpolate read only * `#9351 `__: MAINT: special.erf: use the x->-x symmetry * `#9356 `__: Fix documentation typo * `#9358 `__: DOC: improve doc for ksone and kstwobign in scipy.stats * `#9362 `__: DOC: Change datatypes of A matrices in linprog * `#9364 `__: MAINT: Adds implicit none to fftpack fortran sources * `#9369 `__: DOC: minor tweak to CoC (updated NumFOCUS contact address). * `#9373 `__: Fix exception if python is called with -OO option * `#9374 `__: FIX: AIX compilation issue with NAN and INFINITY * `#9376 `__: COBLYA -> COBYLA in docs * `#9377 `__: DOC: Add examples integrate: fixed_quad and quadrature * `#9379 `__: MAINT: TST: Make tests NumPy 1.8 compatible * `#9385 `__: CI: On Travis matrix "OPTIMIZE=-OO" flag ignored * `#9387 `__: Fix defaut value for 'mode' in 'ndimage.shift' in the doc * `#9392 `__: BUG: rank has to be integer in rank_filter: fixed issue 9388 * `#9399 `__: DOC: Misc. typos * `#9400 `__: TST: stats: Fix the expected r-value of a linregress test. * `#9405 `__: BUG: np.hstack does not accept generator expressions * `#9408 `__: ENH: linalg: Shorter ill-conditioned warning message * `#9418 `__: DOC: Fix ndimage docstrings and reduce doc build warnings * `#9421 `__: DOC: Add missing docstring examples in scipy.spatial * `#9422 `__: DOC: Add an example to integrate.newton_cotes * `#9427 `__: BUG: Fixed defect with maxiter #9419 in dual annealing * `#9431 `__: BENCH: Add dual annealing to scipy benchmark (see #9415) * `#9435 `__: DOC: Add docstring examples for stats.binom_test * `#9443 `__: DOC: Fix the order of indices in optimize tutorial * `#9444 `__: MAINT: interpolate: use operator.index for checking/coercing... * `#9445 `__: DOC: Added missing example to stats.mstats.kruskal * `#9446 `__: DOC: Add note about version changed for jaccard distance * `#9447 `__: BLD: version-script handling in setup.py * `#9448 `__: TST: skip a problematic linalg test * `#9449 `__: TST: fix missing seed in lobpcg test. * `#9456 `__: TST: test_eigs_consistency() now sorts output Checksums ========= MD5 ~~~ 8d056b1b8aabbbcb34116af4f132688c scipy-1.2.0rc2-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 53097b88fa71ca0d8bf1105f431682bf scipy-1.2.0rc2-cp27-cp27m-manylinux1_i686.whl 180c35a669c61f5aa487dcb0cb18f8ab scipy-1.2.0rc2-cp27-cp27m-manylinux1_x86_64.whl 0d4008cb8e25953b1e23a32c660684bd scipy-1.2.0rc2-cp27-cp27m-win32.whl 35d2091830466b6e37a672f59eae2f54 scipy-1.2.0rc2-cp27-cp27m-win_amd64.whl 0b6f7b8c0b8f1324ef2d87b7846fa6c5 scipy-1.2.0rc2-cp27-cp27mu-manylinux1_i686.whl c91784a0889bb921b524555c68e224eb scipy-1.2.0rc2-cp27-cp27mu-manylinux1_x86_64.whl 748d952957be7c48def5e77ccfbfa9fe scipy-1.2.0rc2-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl ea7db734b9e87aa8c694a23f50da261d scipy-1.2.0rc2-cp34-cp34m-manylinux1_i686.whl 897af31662c9d9bfeab4e34a8da8f7b0 scipy-1.2.0rc2-cp34-cp34m-manylinux1_x86_64.whl c9a0789bb8c2cdf1c1a6b44f7f6958ff scipy-1.2.0rc2-cp34-cp34m-win32.whl 34515d46edd4fc39ac97841c0ffdc535 scipy-1.2.0rc2-cp34-cp34m-win_amd64.whl cb445d88d28a8df870442f8b75b1f076 scipy-1.2.0rc2-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 3107ddaec0337c99285d7ae7cd517c44 scipy-1.2.0rc2-cp35-cp35m-manylinux1_i686.whl e801ee5e915ecc47d5800d36a62609ed scipy-1.2.0rc2-cp35-cp35m-manylinux1_x86_64.whl 3282fa4b3088d18fb5d8a4176911f88c scipy-1.2.0rc2-cp35-cp35m-win32.whl 7178e87b7407f10232c0ec45c53d299b scipy-1.2.0rc2-cp35-cp35m-win_amd64.whl ad5747f5295b4e7feb98233211d28fba scipy-1.2.0rc2-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 57b1c8ae77febceee7f1453be210b888 scipy-1.2.0rc2-cp36-cp36m-manylinux1_i686.whl 2eb66820f6806f6b7a7f8e1e66b7ffe6 scipy-1.2.0rc2-cp36-cp36m-manylinux1_x86_64.whl 3cfbf4618f40d79a52caa03eb66eff4b scipy-1.2.0rc2-cp36-cp36m-win32.whl 55a837b1d6bc1bac44f9d02fe71220fb scipy-1.2.0rc2-cp36-cp36m-win_amd64.whl 17bed5da01da6157d33215a8e3d4676f scipy-1.2.0rc2-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl e8fe35c2017709d36f4fcb3ad7499782 scipy-1.2.0rc2-cp37-cp37m-manylinux1_i686.whl d670611d03945419b272c38ac109c542 scipy-1.2.0rc2-cp37-cp37m-manylinux1_x86_64.whl cc5a920ee31c68404ccb947a08d8825d scipy-1.2.0rc2-cp37-cp37m-win32.whl eb3fd215b6a39af8d6ef5f44c5b0b6ce scipy-1.2.0rc2-cp37-cp37m-win_amd64.whl 7fd5310c5b19a6faa32f845bba35208b scipy-1.2.0rc2.tar.gz 1fd898bfbbb2ec2afb155ada32c4ed20 scipy-1.2.0rc2.tar.xz 6022906c840d14272c8000f5d48113be scipy-1.2.0rc2.zip SHA256 ~~~~~~ 3b08d5ed06d3518f4cee22536d18b3b33b94265f902a0daf9238ce286e481fb9 scipy-1.2.0rc2-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 3b2a24b91e1570a10f65cdcebf90bd8186738ba25d934be38385f6ad5e56997f scipy-1.2.0rc2-cp27-cp27m-manylinux1_i686.whl f3add2b81868de7b3ec147019a6d2a32227dae1366e447ff69ea2744c6d59a3d scipy-1.2.0rc2-cp27-cp27m-manylinux1_x86_64.whl b61606b5bb3d4706362d468b3581952cb5f702bd237510d6ef3347a99a6f2ed4 scipy-1.2.0rc2-cp27-cp27m-win32.whl 1498d3b296075b2281524c42706be6d8f41112edda105eb0f5aa3355cee51a21 scipy-1.2.0rc2-cp27-cp27m-win_amd64.whl 01a32acb43729219cf583ba50fd7f77e6ccadd37c6fb835a5a3695c2c51aceb1 scipy-1.2.0rc2-cp27-cp27mu-manylinux1_i686.whl 368fce2d186120a89d6e7ac6ed374fa0418f92c502a54f5b6c462036254496e0 scipy-1.2.0rc2-cp27-cp27mu-manylinux1_x86_64.whl 06a81e1d99f6b02c3f6ef54827dd4bacf53d014988dbc09b954f4124e6c414e1 scipy-1.2.0rc2-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl a859de1cd744f51ffb7870c52b3982e0b78b9ca25f3036a83aae106cd57eb8ab scipy-1.2.0rc2-cp34-cp34m-manylinux1_i686.whl e60239d88fd2e094b0369a268b4480750c3c8b37b222dd4da22d53e4a7dc25b3 scipy-1.2.0rc2-cp34-cp34m-manylinux1_x86_64.whl 69ce63646a13b24fb35549dfb4c9daf4ff7dacc964e1720cf8bccb4db54e4aba scipy-1.2.0rc2-cp34-cp34m-win32.whl 58efa4bfe146e949d1b9a5c772ccb524a8f939e82423fd1129745bcdd029961a scipy-1.2.0rc2-cp34-cp34m-win_amd64.whl 597c1fded8f49019ed03d1e3648d296d56de8a5d5530ca698addd5707f729048 scipy-1.2.0rc2-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 25735065cfc8a3fc9b6575945c6a130b1dd71d6e096a35288a3c39be87040934 scipy-1.2.0rc2-cp35-cp35m-manylinux1_i686.whl 749262355e689e1f3828cb530496202d9d6cd88a7734f6908266df05e8debad7 scipy-1.2.0rc2-cp35-cp35m-manylinux1_x86_64.whl 2b3d9c56ec70e9be1a8e0a3e483f0bf7f9998d4cd37e9a91d6352ac168de1d3d scipy-1.2.0rc2-cp35-cp35m-win32.whl dcd05569a7dd0fc267eadec54d416ab728db3f30447fdc078d536166637a993f scipy-1.2.0rc2-cp35-cp35m-win_amd64.whl 6957a26d95be2b41dfb6bb0ede0b0d8826827954fdfbe8cf02e7a94fa29243e2 scipy-1.2.0rc2-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 42cd83178ab4ca83b8aa3a0001462895ada61b1ff656c6f6e455a6c9eb8d268a scipy-1.2.0rc2-cp36-cp36m-manylinux1_i686.whl e540be156010dac4b89e10b83193e6e700b58113781f20f627a83faafa335d79 scipy-1.2.0rc2-cp36-cp36m-manylinux1_x86_64.whl a320b6f5cb059c7376ded4a9b464030de972dbf4e58807baf0145e042301a8b0 scipy-1.2.0rc2-cp36-cp36m-win32.whl 37d0352e786d28095df81ced7e68eea2724c6ae66dd2f74c0c59edfbf0427d3e scipy-1.2.0rc2-cp36-cp36m-win_amd64.whl 6baa1c0242f41dabf3e4ab1be808c793cbd7ed494bff750fafe88546c0015bfb scipy-1.2.0rc2-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 9c2b534675ee8b07b7778d27daafdee06343dc8c96061d45bd646e34663003c1 scipy-1.2.0rc2-cp37-cp37m-manylinux1_i686.whl 8a086063621a531f797188a17b99620b2a3a35153618dac30c8325e8b8eb13ae scipy-1.2.0rc2-cp37-cp37m-manylinux1_x86_64.whl d018053c116e9e26334f0a00cf3ef835f725dd168ccb1affeebe2f44c8724003 scipy-1.2.0rc2-cp37-cp37m-win32.whl 1b6b10e7b8b236efb98f51297cd8c73944d1e3f6bec13269b9a22531b298b5eb scipy-1.2.0rc2-cp37-cp37m-win_amd64.whl 689c5ffb7634560e2a3671f3bac3c2a9926c87bc4d84d8bc7c54ca4695ca3552 scipy-1.2.0rc2.tar.gz 54b3a2f66c36f3cee1803ae843e249c85d814c2d4c4f18452059cdfa28b748af scipy-1.2.0rc2.tar.xz 6d77e355a517847131c645ccd95e4dcbb6569288eef3ddd8d811cca711cf296f scipy-1.2.0rc2.zip -----BEGIN PGP SIGNATURE----- iQIzBAEBCAAdFiEEgfAqrOuERrV4fwr6XCLdIy4FKasFAlwID4kACgkQXCLdIy4F Kau2rRAAsTZRG9W1yCcIY3Oi7XY2XGdYdWQZ9JLQpMWpcjttXjA8N/sJ3mZIlWO8 Lwm8iWsLELmhgk19TxRIR38pu1Uofsqtm96X4HxcTg24G6nGvEABxh+QyOp8dQMX wARy1Ji8JwJqydg/Vg3885BNf6Ti2fpOCS1avFqf16FueukjSFDYlBVY/tvDjd+j q+Tv0ByjA0NXqh5HlJuVkiNXHsa/OUuVUaBFb4RE6VZPWHd4J47d3rkcpyActa2G JF0OyLqx34xmC5Q8IhCEFNAvwU7EpzTo/4gtZf3SoRuF3326Z/RUvalBu5u1zkio 17p6Wzfu/AXSq82AD9FoujLIvss52Ne26xqqtgR/Fc+1XkoxWuF7fNFvdX4AApK8 quCLp5W+NsoQjkCjnmvYxRmBa5lsvtxoiTGrC25gRbxg2SGpVC6c65egCE9xoFza 6HarIXnVQ2mzo+7PUX2czHOJx6XYgCwIUqrOMmymRH4NCGWLPp6+wfVJ4mENWAZ/ GFcQhVoHw8AV07wHnaM6MXN7BBFcg8ZqYZaGPf0RYdVqN+crh410i2atG9GHZiMi i7+5JwN75rK133KCn7p5wyZylm/7RyEGTs6ElhkapQ5/NRcYnjpG36qTJnTFQYzL f9F5NnadP2+pEc97ZTOo9j/g9QIz3DZFHFFILy22enmq/4VcFD8= =doxZ -----END PGP SIGNATURE----- -------------- next part -------------- An HTML attachment was scrubbed... URL: From rth.yurchak at pm.me Wed Dec 5 15:05:01 2018 From: rth.yurchak at pm.me (Roman Yurchak) Date: Wed, 05 Dec 2018 20:05:01 +0000 Subject: [SciPy-Dev] Dropping Python 3.4 In-Reply-To: References: Message-ID: <6C2xzWHT3IM54nxGCae42DJ7ra6nDkiEJ5Kfg2lTupuMgZZCqrWEdXbhKgwnVbYE6g29If2V7PBgW9G7qSz9G6paQZX1kI5PtfGYMZZozSA=@pm.me> On 04/12/2018 02:49, Ralf Gommers wrote: > Sounds fine to me. Python 3.4 is pretty much irrelevant at this point, > and SciPy supporting it for one more release doesn't imply anything for > NumPy. Also Python 3.4 end of life date is in 4 month anyway, https://devguide.python.org/#status-of-python-branches -- Roman From rmay31 at gmail.com Thu Dec 6 21:52:31 2018 From: rmay31 at gmail.com (Ryan May) Date: Thu, 6 Dec 2018 19:52:31 -0700 Subject: [SciPy-Dev] Cubic interpolation with SciPy 1.2.0rc1 In-Reply-To: References: <2bda2b2d2468660db53dbf9f047986c31bf536f1.camel@iki.fi> Message-ID: The fix seems fine. It just took a little bit to find the fix Pauli linked to--it's a bit of a leap from griddata to CloughTocher2DInterpolator. Just wanted to double check before updating my tests. Ryan On Tue, Dec 4, 2018 at 4:31 PM Tyler Reddy wrote: > Anything I should consider here for rc2, since that's delayed slightly > (again)? > > Presumably the bug fix is higher priority than the modest behavior change? > > On Tue, 4 Dec 2018 at 15:12, Pauli Virtanen wrote: > >> ti, 2018-12-04 kello 15:08 -0700, Ryan May kirjoitti: >> > In the mean time, is there any reason to expect changes to the >> > results from cubic interpolation? I didn't see anything in the >> > release notes, and a quick search on GitHub didn't bring any obvious >> > issues/PRs. >> >> There was a bug for triangles on the boundary, resulting to weird >> choice of free degrees of freedom: >> https://github.com/scipy/scipy/pull/9176 >> >> >> _______________________________________________ >> SciPy-Dev mailing list >> SciPy-Dev at python.org >> https://mail.python.org/mailman/listinfo/scipy-dev >> > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > -- Ryan May -------------- next part -------------- An HTML attachment was scrubbed... URL: From ralf.gommers at gmail.com Fri Dec 7 01:14:59 2018 From: ralf.gommers at gmail.com (Ralf Gommers) Date: Thu, 6 Dec 2018 22:14:59 -0800 Subject: [SciPy-Dev] Preparing project proposal for GSoC 2019 In-Reply-To: References: Message-ID: On Mon, Dec 3, 2018 at 12:41 PM Sourav Singh wrote: > Hello, > > I am creating a new conversation since I have created a draft proposal for > the project here- https://goo.gl/S3J9Kg > Hi Sourav, thanks for writing that up, that's a good start. Before submission you'll have to add a lot more detail about how to go about the implementation, but there's time for that. I would suggest to focus on how to approach the backend system, because there's a lot of options to do that. > I would be glad to know your views about the proposal and what needs to be > done to improve the proposal. I also have a few questions- > > 1) Would it be fine if I create a PR to SciPy's codebase to adopt > pocketfft? The PR could give me an understanding of how to contribute to > SciPy's fftpack module. > I would prefer to wait a little bit with that. The branching of 1.16.x in the NumPy repo is imminent (1-3 weeks I expect), and at that point Pocketfft can be merged into NumPy. Then we'll be able to have a discussion with the author, and port things to SciPy. I think having two PRs for Pocketfft integration going on in parallel is a bit much and likely will lead to duplicate work. If you want to try your hand on something in fftpack now, this is probably the best choice of all the open issues: https://github.com/scipy/scipy/issues/5986#issuecomment-313889128 > 2) I noticed that scipy.ffitpack has fortran sources. What kind of > knowledge of fortran is expected of me for this project? I have a basic > knowledge of fortran, but I am not very confident enough to write > high-level code in the language. > That's a good question. I think it's limited. For the set of function we're replacing, we just dont use the Fortran implementation at all anymore, and instead just have a C implementation. So you'll have to be comfortable in C, as well as in dealing with the build system, but I won't expect you having to make significant changes in Fortran code. Cheers, Ralf -------------- next part -------------- An HTML attachment was scrubbed... URL: From grlee77 at gmail.com Fri Dec 7 14:45:42 2018 From: grlee77 at gmail.com (Gregory Lee) Date: Fri, 7 Dec 2018 14:45:42 -0500 Subject: [SciPy-Dev] Preparing project proposal for GSoC 2019 In-Reply-To: References: Message-ID: On Fri, Dec 7, 2018 at 1:15 AM Ralf Gommers wrote: > > > On Mon, Dec 3, 2018 at 12:41 PM Sourav Singh > wrote: > >> >> 1) Would it be fine if I create a PR to SciPy's codebase to adopt >> pocketfft? The PR could give me an understanding of how to contribute to >> SciPy's fftpack module. >> > > I would prefer to wait a little bit with that. The branching of 1.16.x in > the NumPy repo is imminent (1-3 weeks I expect), and at that point > Pocketfft can be merged into NumPy. Then we'll be able to have a discussion > with the author, and port things to SciPy. I think having two PRs for > Pocketfft integration going on in parallel is a bit much and likely will > lead to duplicate work. > > If you want to try your hand on something in fftpack now, this is probably > the best choice of all the open issues: > https://github.com/scipy/scipy/issues/5986#issuecomment-313889128 > > I think the suggested SciPy issue above is a good one. Last week I rebased the real-to-real transforms PR in pyFFTW on current master so it is up to date and ready for continued work. There are still a few open items in the checklist at https://github.com/pyFFTW/pyFFTW/pull/256 if you are interested. However, as your project would be under SciPy, I think your time is probably better spent working on a SciPy PR such as the one Ralph suggested. -------------- next part -------------- An HTML attachment was scrubbed... URL: From tyler.je.reddy at gmail.com Tue Dec 11 13:34:36 2018 From: tyler.je.reddy at gmail.com (Tyler Reddy) Date: Tue, 11 Dec 2018 10:34:36 -0800 Subject: [SciPy-Dev] SciPy 1.2.0 release schedule In-Reply-To: References: Message-ID: My notes don't show any substantial issues reported for 1.2.0rc2 so far. I'm currently thinking it might be nice to target 1.2.0 release for ~Dec. 17th, which is just short of two weeks after rc2 & just before Holiday distractions get a bit busier on my end. I think there are at least two additional things for the release proper: building docs & scipy.org stuff, which hopefully aren't too painful. On Tue, 4 Dec 2018 at 22:10, Tyler Reddy wrote: > After the gh-9572 reversion, updated scipy 1.2.0rc2 wheel builds are now > running -- fingers crossed -- I'll check on them in the morning. > > On Tue, 4 Dec 2018 at 10:02, Tyler Reddy wrote: > >> Wheel builds off the tip of the 1.2.0rc2 branch are erroring out on >> Travis: https://travis-ci.org/MacPython/scipy-wheels/builds/463460018 >> >> >> On Thu, 29 Nov 2018 at 19:33, Ralf Gommers >> wrote: >> >>> >>> >>> On Wed, Nov 28, 2018 at 10:05 AM Tyler Reddy >>> wrote: >>> >>>> I'm tentatively suggesting that we do a second release candidate, rc2, >>>> on or at least close to December 3rd. >>>> >>> >>> Yes, that makes sense. There's enough changes to justify a new release >>> candidate. >>> >>> Ralf >>> >>> >>>> My notes currently show the PRs/ issues below on the "backport radar." >>>> In particular, I think Ralf noticed >>>> an API inconsistency in one of the big optimize enhancements. >>>> >>>> https://github.com/scipy/scipy/pull/9541 >>>> https://github.com/scipy/scipy/issues/9547 >>>> https://github.com/scipy/scipy/pull/9550 >>>> >>>> On Wed, 21 Nov 2018 at 15:07, Ralf Gommers >>>> wrote: >>>> >>>>> >>>>> >>>>> On Wed, Nov 21, 2018 at 9:32 AM Tyler Reddy >>>>> wrote: >>>>> >>>>>> I've pushed the v1.2.x wheels branch -- initially this will aim to >>>>>> confirm that SciPy master branch is now passing the Travis & Appveyor wheel >>>>>> builds. >>>>>> >>>>>> If that is the case, I will proceed with the 3 connected backport PRs >>>>>> to the maintenance branch. >>>>>> >>>>>> Then, I will point the v.1.2.x wheels branch to an appropriate commit >>>>>> on the patched maintenance branch for release candidate wheel builds. >>>>>> >>>>> >>>>> Sounds like a plan! >>>>> >>>>> Ralf >>>>> >>>>> >>>>>> >>>>>> On Sat, 17 Nov 2018 at 10:27, Ilhan Polat >>>>>> wrote: >>>>>> >>>>>>> Good stuff Tyler. I have to also add to that list the recent pypy3 >>>>>>> run failures appearing sporadically (though consistent on my PRs). >>>>>>> >>>>>>> I am trying triangulate the cause but probably will have to wait >>>>>>> until at least tomorrow. Feedback is more than welcome. They seem to be >>>>>>> related to cython/numpy versions but one can never be sure. >>>>>>> >>>>>>> ?lhan >>>>>>> >>>>>>> >>>>>>> On Fri, Nov 16, 2018, 19:35 Tyler Reddy >>>>>>> wrote: >>>>>>> >>>>>>>> Current delays / issues I'm working on--feel free to chime in on >>>>>>>> those: >>>>>>>> >>>>>>>> - a few test failures in wheel building matrix: >>>>>>>> https://github.com/MacPython/scipy-wheels/pull/37 >>>>>>>> - hard-to-understand putative patch for one of the failures: >>>>>>>> https://github.com/scipy/scipy/pull/9486 >>>>>>>> >>>>>>>> On Fri, 9 Nov 2018 at 08:40, Tyler Reddy >>>>>>>> wrote: >>>>>>>> >>>>>>>>> I branched 1.2.x around 8:30 am Pacific time on Nov. 9, 2018. >>>>>>>>> >>>>>>>>> Working on the follow up master branch PR to bump version number / >>>>>>>>> notes file, etc. now. >>>>>>>>> >>>>>>>>> On Thu, 8 Nov 2018 at 22:49, Tyler Reddy >>>>>>>>> wrote: >>>>>>>>> >>>>>>>>>> Release note PR is hopefully taking shape now -- I'll allow >>>>>>>>>> (another) delay for the branch until tomorrow (morning?) for some >>>>>>>>>> (hopefully final) checks on that. >>>>>>>>>> >>>>>>>>>> On Thu, 8 Nov 2018 at 14:35, Tyler Reddy < >>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>> >>>>>>>>>>> There are 0 remaining PRs with a 1.2.0 milestone. >>>>>>>>>>> >>>>>>>>>>> There is one issue left with a 1.2.0 milestone: >>>>>>>>>>> https://github.com/scipy/scipy/issues/9441 >>>>>>>>>>> >>>>>>>>>>> Please do take a look over the release notes WIP PR based on the >>>>>>>>>>> wiki: https://github.com/scipy/scipy/pull/9461 >>>>>>>>>>> >>>>>>>>>>> Target is to branch in 5-6 hours or so. Let me know if you see >>>>>>>>>>> any issues of course -- Ralf has been coaching >>>>>>>>>>> me through pretty well so far I think. >>>>>>>>>>> >>>>>>>>>>> On Wed, 7 Nov 2018 at 09:52, Ilhan Polat >>>>>>>>>>> wrote: >>>>>>>>>>> >>>>>>>>>>>> Hang in there Tyler :) >>>>>>>>>>>> >>>>>>>>>>>> Awesome job so far. >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> On Wed, Nov 7, 2018, 06:08 Ralf Gommers >>>>>>>>>>>> wrote: >>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> On Tue, Nov 6, 2018 at 9:03 PM Tyler Reddy < >>>>>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>>>>> >>>>>>>>>>>>>> 7 PRs : >>>>>>>>>>>>>> https://github.com/scipy/scipy/pulls?q=is%3Aopen+is%3Apr+milestone%3A1.2.0 >>>>>>>>>>>>>> 3 issues: >>>>>>>>>>>>>> https://github.com/scipy/scipy/issues?q=is%3Aopen+is%3Aissue+milestone%3A1.2.0 >>>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> Awesome, getting there:) >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>>> Target: branch sometime on November 8th >>>>>>>>>>>>>> >>>>>>>>>>>>>> On Mon, 5 Nov 2018 at 05:42, Tyler Reddy < >>>>>>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>>>>>> >>>>>>>>>>>>>>> Alright, I'll extend to Thursday Nov. 8th & see if I can >>>>>>>>>>>>>>> reduce that list a bit >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> On Sun, 4 Nov 2018 at 22:27, Ralf Gommers < >>>>>>>>>>>>>>> ralf.gommers at gmail.com> wrote: >>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> On Fri, Oct 26, 2018 at 7:03 PM Mark Alexander Mikofski < >>>>>>>>>>>>>>>> mikofski at berkeley.edu> wrote: >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> Hi Tyler and others, >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> Thanks for managing the v1.2 release. >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> I think PR #8431, Cython optimize zeros API, is ready, >>>>>>>>>>>>>>>>> hopefully, to merge. It's been through several rounds of reviews and I >>>>>>>>>>>>>>>>> think I've accommodated all of the recommendations, all tests are passing, >>>>>>>>>>>>>>>>> and there's been strong support. Anyone please take a look. >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> https://github.com/scipy/scipy/pull/8431 >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> Thanks, >>>>>>>>>>>>>>>>> Mark >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> On Fri, Oct 26, 2018, 2:38 PM Ralf Gommers < >>>>>>>>>>>>>>>>> ralf.gommers at gmail.com> wrote: >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> On Thu, Oct 25, 2018 at 12:55 PM Tyler Reddy < >>>>>>>>>>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> Hi all, >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> It is almost 6 months after the 1.1.0 release on May 5, >>>>>>>>>>>>>>>>>>> so probably time to plan the 1.2.0 release. It would be a good idea to look >>>>>>>>>>>>>>>>>>> over the PRs with a 1.2.0 milestone >>>>>>>>>>>>>>>>>>> , >>>>>>>>>>>>>>>>>>> and tag anything else that should have this milestone appropriately. >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> I'd like to propose the following schedule: >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> Nov. 5: branch 1.2.x >>>>>>>>>>>>>>>>>>> Nov. 8: rc1 >>>>>>>>>>>>>>>>>>> Nov. 21: rc2 (if needed) >>>>>>>>>>>>>>>>>>> Nov. 30: final release >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> Thoughts? >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> This looks like a good schedule to me. We'll probably >>>>>>>>>>>>>>>>>> struggle to get some PRs marked for 1.2.0 merged, but that's always the >>>>>>>>>>>>>>>>>> case. >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Hi Tyler, could we shift the branch date by 2-3 days (or up >>>>>>>>>>>>>>>> to a week)? There's a couple of PRs that I'd really like to see merged or >>>>>>>>>>>>>>>> decided on (for optimize and stats mainly), and there's right now still 18 >>>>>>>>>>>>>>>> open PRs marked for 1.2.0. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> A note on the open PRs: what we want to aim for is to have >>>>>>>>>>>>>>>> the list of open PRs and open blocking issues at zero, and have at most >>>>>>>>>>>>>>>> some non-blocking issues under the milestone left. Normally the release >>>>>>>>>>>>>>>> manager starts making those decisions, or pinging people, if other >>>>>>>>>>>>>>>> reviewers haven't done so in time. Of course it would be ideal if everyone >>>>>>>>>>>>>>>> has another look at >>>>>>>>>>>>>>>> https://github.com/scipy/scipy/pulls?q=is%3Aopen+is%3Apr+milestone%3A1.2.0 >>>>>>>>>>>>>>>> and bumps or finished off PRs he/she is involved in. >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Cheers, >>>>>>>>>>>>>>>> Ralf >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>>>>> >>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>>>> >>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>>> >>>>>>>>>>> _______________________________________________ >>>>>>>> SciPy-Dev mailing list >>>>>>>> SciPy-Dev at python.org >>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>> >>>>>>> _______________________________________________ >>>>>>> SciPy-Dev mailing list >>>>>>> SciPy-Dev at python.org >>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>> >>>>>> _______________________________________________ >>>>>> SciPy-Dev mailing list >>>>>> SciPy-Dev at python.org >>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>> >>>>> _______________________________________________ >>>>> SciPy-Dev mailing list >>>>> SciPy-Dev at python.org >>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>> >>>> _______________________________________________ >>>> SciPy-Dev mailing list >>>> SciPy-Dev at python.org >>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>> >>> _______________________________________________ >>> SciPy-Dev mailing list >>> SciPy-Dev at python.org >>> https://mail.python.org/mailman/listinfo/scipy-dev >>> >> -------------- next part -------------- An HTML attachment was scrubbed... URL: From ralf.gommers at gmail.com Tue Dec 11 22:01:48 2018 From: ralf.gommers at gmail.com (Ralf Gommers) Date: Tue, 11 Dec 2018 19:01:48 -0800 Subject: [SciPy-Dev] SciPy 1.2.0 release schedule In-Reply-To: References: Message-ID: On Tue, Dec 11, 2018 at 10:35 AM Tyler Reddy wrote: > My notes don't show any substantial issues reported for 1.2.0rc2 so far. > > I'm currently thinking it might be nice to target 1.2.0 release for ~Dec. > 17th, which is just short of two weeks after rc2 & just before Holiday > distractions get a bit busier on my end. > Sounds good. I think it's ready to go. > I think there are at least two additional things for the release proper: > building docs & scipy.org stuff, which hopefully aren't too painful. > Shouldn't be too painful. - A PR like https://github.com/scipy/scipy.org/pull/274/files to update scipy.org front page - A PR like https://github.com/scipy/docs.scipy.org/commit/2a9a8b34451 to update the docs.scipy.org front page - building the docs should be a matter of `make dist` You won't be able to upload the results of any of those to the doc server, so feel free to ping me when you do the release. Cheers, Ralf > On Tue, 4 Dec 2018 at 22:10, Tyler Reddy wrote: > >> After the gh-9572 reversion, updated scipy 1.2.0rc2 wheel builds are now >> running -- fingers crossed -- I'll check on them in the morning. >> >> On Tue, 4 Dec 2018 at 10:02, Tyler Reddy >> wrote: >> >>> Wheel builds off the tip of the 1.2.0rc2 branch are erroring out on >>> Travis: https://travis-ci.org/MacPython/scipy-wheels/builds/463460018 >>> >>> >>> On Thu, 29 Nov 2018 at 19:33, Ralf Gommers >>> wrote: >>> >>>> >>>> >>>> On Wed, Nov 28, 2018 at 10:05 AM Tyler Reddy >>>> wrote: >>>> >>>>> I'm tentatively suggesting that we do a second release candidate, rc2, >>>>> on or at least close to December 3rd. >>>>> >>>> >>>> Yes, that makes sense. There's enough changes to justify a new release >>>> candidate. >>>> >>>> Ralf >>>> >>>> >>>>> My notes currently show the PRs/ issues below on the "backport radar." >>>>> In particular, I think Ralf noticed >>>>> an API inconsistency in one of the big optimize enhancements. >>>>> >>>>> https://github.com/scipy/scipy/pull/9541 >>>>> https://github.com/scipy/scipy/issues/9547 >>>>> https://github.com/scipy/scipy/pull/9550 >>>>> >>>>> On Wed, 21 Nov 2018 at 15:07, Ralf Gommers >>>>> wrote: >>>>> >>>>>> >>>>>> >>>>>> On Wed, Nov 21, 2018 at 9:32 AM Tyler Reddy >>>>>> wrote: >>>>>> >>>>>>> I've pushed the v1.2.x wheels branch -- initially this will aim to >>>>>>> confirm that SciPy master branch is now passing the Travis & Appveyor wheel >>>>>>> builds. >>>>>>> >>>>>>> If that is the case, I will proceed with the 3 connected backport >>>>>>> PRs to the maintenance branch. >>>>>>> >>>>>>> Then, I will point the v.1.2.x wheels branch to an appropriate >>>>>>> commit on the patched maintenance branch for release candidate wheel builds. >>>>>>> >>>>>> >>>>>> Sounds like a plan! >>>>>> >>>>>> Ralf >>>>>> >>>>>> >>>>>>> >>>>>>> On Sat, 17 Nov 2018 at 10:27, Ilhan Polat >>>>>>> wrote: >>>>>>> >>>>>>>> Good stuff Tyler. I have to also add to that list the recent pypy3 >>>>>>>> run failures appearing sporadically (though consistent on my PRs). >>>>>>>> >>>>>>>> I am trying triangulate the cause but probably will have to wait >>>>>>>> until at least tomorrow. Feedback is more than welcome. They seem to be >>>>>>>> related to cython/numpy versions but one can never be sure. >>>>>>>> >>>>>>>> ?lhan >>>>>>>> >>>>>>>> >>>>>>>> On Fri, Nov 16, 2018, 19:35 Tyler Reddy >>>>>>>> wrote: >>>>>>>> >>>>>>>>> Current delays / issues I'm working on--feel free to chime in on >>>>>>>>> those: >>>>>>>>> >>>>>>>>> - a few test failures in wheel building matrix: >>>>>>>>> https://github.com/MacPython/scipy-wheels/pull/37 >>>>>>>>> - hard-to-understand putative patch for one of the failures: >>>>>>>>> https://github.com/scipy/scipy/pull/9486 >>>>>>>>> >>>>>>>>> On Fri, 9 Nov 2018 at 08:40, Tyler Reddy >>>>>>>>> wrote: >>>>>>>>> >>>>>>>>>> I branched 1.2.x around 8:30 am Pacific time on Nov. 9, 2018. >>>>>>>>>> >>>>>>>>>> Working on the follow up master branch PR to bump version number >>>>>>>>>> / notes file, etc. now. >>>>>>>>>> >>>>>>>>>> On Thu, 8 Nov 2018 at 22:49, Tyler Reddy < >>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>> >>>>>>>>>>> Release note PR is hopefully taking shape now -- I'll allow >>>>>>>>>>> (another) delay for the branch until tomorrow (morning?) for some >>>>>>>>>>> (hopefully final) checks on that. >>>>>>>>>>> >>>>>>>>>>> On Thu, 8 Nov 2018 at 14:35, Tyler Reddy < >>>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>>> >>>>>>>>>>>> There are 0 remaining PRs with a 1.2.0 milestone. >>>>>>>>>>>> >>>>>>>>>>>> There is one issue left with a 1.2.0 milestone: >>>>>>>>>>>> https://github.com/scipy/scipy/issues/9441 >>>>>>>>>>>> >>>>>>>>>>>> Please do take a look over the release notes WIP PR based on >>>>>>>>>>>> the wiki: https://github.com/scipy/scipy/pull/9461 >>>>>>>>>>>> >>>>>>>>>>>> Target is to branch in 5-6 hours or so. Let me know if you see >>>>>>>>>>>> any issues of course -- Ralf has been coaching >>>>>>>>>>>> me through pretty well so far I think. >>>>>>>>>>>> >>>>>>>>>>>> On Wed, 7 Nov 2018 at 09:52, Ilhan Polat >>>>>>>>>>>> wrote: >>>>>>>>>>>> >>>>>>>>>>>>> Hang in there Tyler :) >>>>>>>>>>>>> >>>>>>>>>>>>> Awesome job so far. >>>>>>>>>>>>> >>>>>>>>>>>>> >>>>>>>>>>>>> On Wed, Nov 7, 2018, 06:08 Ralf Gommers < >>>>>>>>>>>>> ralf.gommers at gmail.com> wrote: >>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> On Tue, Nov 6, 2018 at 9:03 PM Tyler Reddy < >>>>>>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>>>>>> >>>>>>>>>>>>>>> 7 PRs : >>>>>>>>>>>>>>> https://github.com/scipy/scipy/pulls?q=is%3Aopen+is%3Apr+milestone%3A1.2.0 >>>>>>>>>>>>>>> 3 issues: >>>>>>>>>>>>>>> https://github.com/scipy/scipy/issues?q=is%3Aopen+is%3Aissue+milestone%3A1.2.0 >>>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> Awesome, getting there:) >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>>> Target: branch sometime on November 8th >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> On Mon, 5 Nov 2018 at 05:42, Tyler Reddy < >>>>>>>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Alright, I'll extend to Thursday Nov. 8th & see if I can >>>>>>>>>>>>>>>> reduce that list a bit >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> On Sun, 4 Nov 2018 at 22:27, Ralf Gommers < >>>>>>>>>>>>>>>> ralf.gommers at gmail.com> wrote: >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> On Fri, Oct 26, 2018 at 7:03 PM Mark Alexander Mikofski < >>>>>>>>>>>>>>>>> mikofski at berkeley.edu> wrote: >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> Hi Tyler and others, >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> Thanks for managing the v1.2 release. >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> I think PR #8431, Cython optimize zeros API, is ready, >>>>>>>>>>>>>>>>>> hopefully, to merge. It's been through several rounds of reviews and I >>>>>>>>>>>>>>>>>> think I've accommodated all of the recommendations, all tests are passing, >>>>>>>>>>>>>>>>>> and there's been strong support. Anyone please take a look. >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> https://github.com/scipy/scipy/pull/8431 >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> Thanks, >>>>>>>>>>>>>>>>>> Mark >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> On Fri, Oct 26, 2018, 2:38 PM Ralf Gommers < >>>>>>>>>>>>>>>>>> ralf.gommers at gmail.com> wrote: >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> On Thu, Oct 25, 2018 at 12:55 PM Tyler Reddy < >>>>>>>>>>>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> Hi all, >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> It is almost 6 months after the 1.1.0 release on May 5, >>>>>>>>>>>>>>>>>>>> so probably time to plan the 1.2.0 release. It would be a good idea to look >>>>>>>>>>>>>>>>>>>> over the PRs with a 1.2.0 milestone >>>>>>>>>>>>>>>>>>>> , >>>>>>>>>>>>>>>>>>>> and tag anything else that should have this milestone appropriately. >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> I'd like to propose the following schedule: >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> Nov. 5: branch 1.2.x >>>>>>>>>>>>>>>>>>>> Nov. 8: rc1 >>>>>>>>>>>>>>>>>>>> Nov. 21: rc2 (if needed) >>>>>>>>>>>>>>>>>>>> Nov. 30: final release >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> Thoughts? >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> This looks like a good schedule to me. We'll probably >>>>>>>>>>>>>>>>>>> struggle to get some PRs marked for 1.2.0 merged, but that's always the >>>>>>>>>>>>>>>>>>> case. >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> Hi Tyler, could we shift the branch date by 2-3 days (or >>>>>>>>>>>>>>>>> up to a week)? There's a couple of PRs that I'd really like to see merged >>>>>>>>>>>>>>>>> or decided on (for optimize and stats mainly), and there's right now still >>>>>>>>>>>>>>>>> 18 open PRs marked for 1.2.0. >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> A note on the open PRs: what we want to aim for is to have >>>>>>>>>>>>>>>>> the list of open PRs and open blocking issues at zero, and have at most >>>>>>>>>>>>>>>>> some non-blocking issues under the milestone left. Normally the release >>>>>>>>>>>>>>>>> manager starts making those decisions, or pinging people, if other >>>>>>>>>>>>>>>>> reviewers haven't done so in time. Of course it would be ideal if everyone >>>>>>>>>>>>>>>>> has another look at >>>>>>>>>>>>>>>>> https://github.com/scipy/scipy/pulls?q=is%3Aopen+is%3Apr+milestone%3A1.2.0 >>>>>>>>>>>>>>>>> and bumps or finished off PRs he/she is involved in. >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> Cheers, >>>>>>>>>>>>>>>>> Ralf >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>>>>>> >>>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>>>>> >>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>>>> >>>>>>>>>>>> _______________________________________________ >>>>>>>>> SciPy-Dev mailing list >>>>>>>>> SciPy-Dev at python.org >>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>> >>>>>>>> _______________________________________________ >>>>>>>> SciPy-Dev mailing list >>>>>>>> SciPy-Dev at python.org >>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>> >>>>>>> _______________________________________________ >>>>>>> SciPy-Dev mailing list >>>>>>> SciPy-Dev at python.org >>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>> >>>>>> _______________________________________________ >>>>>> SciPy-Dev mailing list >>>>>> SciPy-Dev at python.org >>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>> >>>>> _______________________________________________ >>>>> SciPy-Dev mailing list >>>>> SciPy-Dev at python.org >>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>> >>>> _______________________________________________ >>>> SciPy-Dev mailing list >>>> SciPy-Dev at python.org >>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>> >>> _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > -------------- next part -------------- An HTML attachment was scrubbed... URL: From matteoravasi at gmail.com Wed Dec 12 14:24:33 2018 From: matteoravasi at gmail.com (Matteo Ravasi) Date: Wed, 12 Dec 2018 20:24:33 +0100 Subject: [SciPy-Dev] LinearOperator and new solver Message-ID: <4E9CFEAC-3740-4F53-9F76-98811E4AF9BC@gmail.com> Dear Scipy-dev community, I would like to bring forward two proposals related to your scipy.sparse.linalg.LinearOperator class and linear solvers in general: LinearOperator: I am the main developer and maintainer of the PyLops library that has been recently open-sourced (git repo: https://github.com/Statoil/pylops, doc: https://pylops.readthedocs.io/en/latest/index.html). As you will see I heavily rely on your LinearOperator class and build on top of it creating various basic linear operators and more specific ones for signal processing and geoscience applications of inverse problems. When I started working on this I was surprised to find very little information and examples online on how to use your LinearOperator and the possibility to subclass it was only mentioned in one line of your documentation and nowhere else online to my knowledge. I wonder if you would consider pointing to PyLops in your documentation to facilitate users i) to know how to get started with LinearOperator, ii) avoid rebuilding the wheel if what they are after can be done or is done already in PyLops. I find your class fantastic and saved me lots of time but I feel is one of those things that few people realize exist and understand how to use it ;) Solvers: I would like to know if you would be interested to add a new solver to your suite of linear solvers. Specifically the solver is called SPGL1 and it is a very popular solver in the mathematical community for sparsity-promoting linear optimization. It was developed at UBC (University of British Columbia) https://www.cs.ubc.ca/~mpf/spgl1/ and has a Matlab open-source code. I have been thinking about porting it to python for a while and recently another python user started a git repo called https://github.com/drrelyea/SPGL1_python_port. However this is something I would more naturally see as part of scipy instead of an indipendent library. I am willing to contact the author of this repo and help him out directly to finish the porting and make it to (or close to) scipy standards... so far the code and repo is not ready to be included in professional code like scipy in my opinion. But I would like to hear what you think, if you would consider adding this to scipy once in good shape or if you think this is not in the scope of scipy library :) Looking forward to hearing from you, Best wishes MR -------------- next part -------------- An HTML attachment was scrubbed... URL: From ralf.gommers at gmail.com Wed Dec 12 19:50:44 2018 From: ralf.gommers at gmail.com (Ralf Gommers) Date: Wed, 12 Dec 2018 16:50:44 -0800 Subject: [SciPy-Dev] LinearOperator and new solver In-Reply-To: <4E9CFEAC-3740-4F53-9F76-98811E4AF9BC@gmail.com> References: <4E9CFEAC-3740-4F53-9F76-98811E4AF9BC@gmail.com> Message-ID: On Wed, Dec 12, 2018 at 11:24 AM Matteo Ravasi wrote: > Dear Scipy-dev community, > > I would like to bring forward two proposals related to your > scipy.sparse.linalg.LinearOperator class and linear solvers in general: > > > > - LinearOperator: I am the main developer and maintainer of the PyLops > library that has been recently open-sourced (git repo: > https://github.com/Statoil/pylops, doc: > https://pylops.readthedocs.io/en/latest/index.html) > . As you will see > I heavily rely on your LinearOperator class and build on top of it creating > various basic linear operators and more specific ones for signal processing > and geoscience applications of inverse problems. When I started working on > this I was surprised to find very little information and examples online on > how to use your LinearOperator and the possibility to subclass it was only > mentioned in one line of your documentation and nowhere else online to my > knowledge. I wonder if you would consider pointing to PyLops in your > documentation to facilitate users i) to know how to get started with > LinearOperator, ii) avoid rebuilding the wheel if what they are after can > be done or is done already in PyLops. I find your class fantastic and saved > me lots of time but I feel is one of those things that few people realize > exist and understand how to use it ;) > > That sounds like a good idea to me. A link from the See Also part of the LinearOperator seems appropriate to me. I don't see a good place in the tutorial section of our docs to put a link, because LinearOperator isn't really mentioned there. If you'd like to write a short section in, e.g., the ARPACK tutorial and add a link there too, that would be great. > > - Solvers: I would like to know if you would be interested to add a > new solver to your suite of linear solvers. Specifically the solver is > called SPGL1 and it is a very popular solver in the mathematical community > for sparsity-promoting linear optimization. It was developed at UBC > (University of British Columbia) https://www.cs.ubc.ca/~mpf/spgl1/ and > has a Matlab open-source code. > > That code is GPL licensed, so we cannot accept any code derived from it. If the original author wouldn't mind relicensing or giving explicit permission for the Python port to be BSD or MIT licensed, then we can consider it. Cheers, Ralf > > - I have been thinking about porting it to python for a while and > recently another python user started a git repo called > https://github.com/drrelyea/SPGL1_python_port. However this is > something I would more naturally see as part of scipy instead of an > indipendent library. I am willing to contact the author of this repo and > help him out directly to finish the porting and make it to (or close to) > scipy standards... so far the code and repo is not ready to be included in > professional code like scipy in my opinion. But I would like to hear what > you think, if you would consider adding this to scipy once in good shape or > if you think this is not in the scope of scipy library :) > > > Looking forward to hearing from you, > > Best wishes > > MR > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > -------------- next part -------------- An HTML attachment was scrubbed... URL: From matteoravasi at gmail.com Thu Dec 13 01:34:21 2018 From: matteoravasi at gmail.com (Matteo Ravasi) Date: Thu, 13 Dec 2018 07:34:21 +0100 Subject: [SciPy-Dev] LinearOperator and new solver In-Reply-To: References: <4E9CFEAC-3740-4F53-9F76-98811E4AF9BC@gmail.com> Message-ID: Thanks a lot for your feedback. Will have a go and add a link to PyLops in documentation. Is the ?See Also? the most appropriate place or maybe in the ?Notes?? Generally I see that See Also has proper links to other routines in the module (or other modules) but I don?t think you want to make pylops a dependency of scipy so I?m not sure the link would work fine? And I will also try out eigs on one of my operator a add a small section in the ARPARK tutorial :) To the solver, I see the point but since you would consider it, I will get in touch with the authors and see how they feel about changing license :) Thank you! iMR > On 13 Dec 2018, at 01:50, Ralf Gommers wrote: > > > >> On Wed, Dec 12, 2018 at 11:24 AM Matteo Ravasi wrote: >> Dear Scipy-dev community, >> I would like to bring forward two proposals related to your scipy.sparse.linalg.LinearOperator class and linear solvers in general: >> >> LinearOperator: I am the main developer and maintainer of the PyLops library that has been recently open-sourced (git repo: https://github.com/Statoil/pylops, doc: https://pylops.readthedocs.io/en/latest/index.html). As you will see I heavily rely on your LinearOperator class and build on top of it creating various basic linear operators and more specific ones for signal processing and geoscience applications of inverse problems. When I started working on this I was surprised to find very little information and examples online on how to use your LinearOperator and the possibility to subclass it was only mentioned in one line of your documentation and nowhere else online to my knowledge. I wonder if you would consider pointing to PyLops in your documentation to facilitate users i) to know how to get started with LinearOperator, ii) avoid rebuilding the wheel if what they are after can be done or is done already in PyLops. I find your class fantastic and saved me lots of time but I feel is one of those things that few people realize exist and understand how to use it ;) > That sounds like a good idea to me. A link from the See Also part of the LinearOperator seems appropriate to me. I don't see a good place in the tutorial section of our docs to put a link, because LinearOperator isn't really mentioned there. If you'd like to write a short section in, e.g., the ARPACK tutorial and add a link there too, that would be great. > >> Solvers: I would like to know if you would be interested to add a new solver to your suite of linear solvers. Specifically the solver is called SPGL1 and it is a very popular solver in the mathematical community for sparsity-promoting linear optimization. It was developed at UBC (University of British Columbia) https://www.cs.ubc.ca/~mpf/spgl1/ and has a Matlab open-source code. > That code is GPL licensed, so we cannot accept any code derived from it. If the original author wouldn't mind relicensing or giving explicit permission for the Python port to be BSD or MIT licensed, then we can consider it. > > Cheers, > Ralf > >> I have been thinking about porting it to python for a while and recently another python user started a git repo called https://github.com/drrelyea/SPGL1_python_port. However this is something I would more naturally see as part of scipy instead of an indipendent library. I am willing to contact the author of this repo and help him out directly to finish the porting and make it to (or close to) scipy standards... so far the code and repo is not ready to be included in professional code like scipy in my opinion. But I would like to hear what you think, if you would consider adding this to scipy once in good shape or if you think this is not in the scope of scipy library :) >> >> Looking forward to hearing from you, >> Best wishes >> MR >> _______________________________________________ >> SciPy-Dev mailing list >> SciPy-Dev at python.org >> https://mail.python.org/mailman/listinfo/scipy-dev > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev -------------- next part -------------- An HTML attachment was scrubbed... URL: From ralf.gommers at gmail.com Fri Dec 14 01:12:08 2018 From: ralf.gommers at gmail.com (Ralf Gommers) Date: Thu, 13 Dec 2018 22:12:08 -0800 Subject: [SciPy-Dev] LinearOperator and new solver In-Reply-To: References: <4E9CFEAC-3740-4F53-9F76-98811E4AF9BC@gmail.com> Message-ID: On Wed, Dec 12, 2018 at 10:34 PM Matteo Ravasi wrote: > Thanks a lot for your feedback. Will have a go and add a link to PyLops in > documentation. Is the ?See Also? the most appropriate place or maybe in the > ?Notes?? Generally I see that See Also has proper links to other routines > in the module (or other modules) but I don?t think you want to make pylops > a dependency of scipy so I?m not sure the link would work fine? > Ah yes. It may be possible to add full reST links, but I'm not sure. And I indeed wouldn't want to talk to PyLops via intersphinx. So Notes sounds good. And I will also try out eigs on one of my operator a add a small section in > the ARPARK tutorial :) > Great! > To the solver, I see the point but since you would consider it, I will get > in touch with the authors and see how they feel about changing > license :) > Cool, let us know what the outcome is. Cheers, Ralf > Thank you! > iMR > > On 13 Dec 2018, at 01:50, Ralf Gommers wrote: > > > > On Wed, Dec 12, 2018 at 11:24 AM Matteo Ravasi > wrote: > >> Dear Scipy-dev community, >> >> I would like to bring forward two proposals related to your >> scipy.sparse.linalg.LinearOperator class and linear solvers in general: >> >> >> >> - LinearOperator: I am the main developer and maintainer of the >> PyLops library that has been recently open-sourced (git repo: >> https://github.com/Statoil/pylops, doc: >> https://pylops.readthedocs.io/en/latest/index.html) >> . As you will see >> I heavily rely on your LinearOperator class and build on top of it creating >> various basic linear operators and more specific ones for signal processing >> and geoscience applications of inverse problems. When I started working on >> this I was surprised to find very little information and examples online on >> how to use your LinearOperator and the possibility to subclass it was only >> mentioned in one line of your documentation and nowhere else online to my >> knowledge. I wonder if you would consider pointing to PyLops in your >> documentation to facilitate users i) to know how to get started with >> LinearOperator, ii) avoid rebuilding the wheel if what they are after can >> be done or is done already in PyLops. I find your class fantastic and saved >> me lots of time but I feel is one of those things that few people realize >> exist and understand how to use it ;) >> >> That sounds like a good idea to me. A link from the See Also part of the > LinearOperator seems appropriate to me. I don't see a good place in the > tutorial section of our docs to put a link, because LinearOperator isn't > really mentioned there. If you'd like to write a short section in, e.g., > the ARPACK tutorial and add a link there too, that would be great. > > >> >> - Solvers: I would like to know if you would be interested to add a >> new solver to your suite of linear solvers. Specifically the solver is >> called SPGL1 and it is a very popular solver in the mathematical community >> for sparsity-promoting linear optimization. It was developed at UBC >> (University of British Columbia) https://www.cs.ubc.ca/~mpf/spgl1/ >> and has a Matlab open-source code. >> >> That code is GPL licensed, so we cannot accept any code derived from it. > If the original author wouldn't mind relicensing or giving explicit > permission for the Python port to be BSD or MIT licensed, then we can > consider it. > > Cheers, > Ralf > > >> >> - I have been thinking about porting it to python for a while and >> recently another python user started a git repo called >> https://github.com/drrelyea/SPGL1_python_port. However this is >> something I would more naturally see as part of scipy instead of an >> indipendent library. I am willing to contact the author of this repo and >> help him out directly to finish the porting and make it to (or close to) >> scipy standards... so far the code and repo is not ready to be included in >> professional code like scipy in my opinion. But I would like to hear what >> you think, if you would consider adding this to scipy once in good shape or >> if you think this is not in the scope of scipy library :) >> >> >> Looking forward to hearing from you, >> >> Best wishes >> >> MR >> _______________________________________________ >> SciPy-Dev mailing list >> SciPy-Dev at python.org >> https://mail.python.org/mailman/listinfo/scipy-dev >> > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > -------------- next part -------------- An HTML attachment was scrubbed... URL: From einstein.edison at gmail.com Fri Dec 14 17:06:42 2018 From: einstein.edison at gmail.com (Hameer Abbasi) Date: Fri, 14 Dec 2018 23:06:42 +0100 Subject: [SciPy-Dev] PyData/Sparse Webinar Hosted by Quansight Message-ID: <86bc8939-f6b0-4878-ab02-b28d8d016ade@Canary> Hello, everyone! I?ll be speaking about PyData/Sparse in a webinar hosted by Quansight. It?ll include a project demo, in case you?re interested, as well as the directions the project can take. You can register for the webinar at https://app.livestorm.co/quansight/ Best Regards, Hameer Abbasi -------------- next part -------------- An HTML attachment was scrubbed... URL: From tyler.je.reddy at gmail.com Mon Dec 17 14:14:36 2018 From: tyler.je.reddy at gmail.com (Tyler Reddy) Date: Mon, 17 Dec 2018 11:14:36 -0800 Subject: [SciPy-Dev] SciPy 1.2.0 release schedule In-Reply-To: References: Message-ID: Currently waiting on 1.2.0 wheel builds as of this morning. Appveyor can take about 4.5 hours to handle that. On Tue, 11 Dec 2018 at 19:02, Ralf Gommers wrote: > > > On Tue, Dec 11, 2018 at 10:35 AM Tyler Reddy > wrote: > >> My notes don't show any substantial issues reported for 1.2.0rc2 so far. >> >> I'm currently thinking it might be nice to target 1.2.0 release for ~Dec. >> 17th, which is just short of two weeks after rc2 & just before Holiday >> distractions get a bit busier on my end. >> > > Sounds good. I think it's ready to go. > > >> I think there are at least two additional things for the release proper: >> building docs & scipy.org stuff, which hopefully aren't too painful. >> > > Shouldn't be too painful. > - A PR like https://github.com/scipy/scipy.org/pull/274/files to update > scipy.org front page > - A PR like https://github.com/scipy/docs.scipy.org/commit/2a9a8b34451 to > update the docs.scipy.org front page > - building the docs should be a matter of `make dist` > > You won't be able to upload the results of any of those to the doc server, > so feel free to ping me when you do the release. > > Cheers, > Ralf > > > >> On Tue, 4 Dec 2018 at 22:10, Tyler Reddy >> wrote: >> >>> After the gh-9572 reversion, updated scipy 1.2.0rc2 wheel builds are now >>> running -- fingers crossed -- I'll check on them in the morning. >>> >>> On Tue, 4 Dec 2018 at 10:02, Tyler Reddy >>> wrote: >>> >>>> Wheel builds off the tip of the 1.2.0rc2 branch are erroring out on >>>> Travis: https://travis-ci.org/MacPython/scipy-wheels/builds/463460018 >>>> >>>> >>>> On Thu, 29 Nov 2018 at 19:33, Ralf Gommers >>>> wrote: >>>> >>>>> >>>>> >>>>> On Wed, Nov 28, 2018 at 10:05 AM Tyler Reddy >>>>> wrote: >>>>> >>>>>> I'm tentatively suggesting that we do a second release candidate, >>>>>> rc2, on or at least close to December 3rd. >>>>>> >>>>> >>>>> Yes, that makes sense. There's enough changes to justify a new release >>>>> candidate. >>>>> >>>>> Ralf >>>>> >>>>> >>>>>> My notes currently show the PRs/ issues below on the "backport >>>>>> radar." In particular, I think Ralf noticed >>>>>> an API inconsistency in one of the big optimize enhancements. >>>>>> >>>>>> https://github.com/scipy/scipy/pull/9541 >>>>>> https://github.com/scipy/scipy/issues/9547 >>>>>> https://github.com/scipy/scipy/pull/9550 >>>>>> >>>>>> On Wed, 21 Nov 2018 at 15:07, Ralf Gommers >>>>>> wrote: >>>>>> >>>>>>> >>>>>>> >>>>>>> On Wed, Nov 21, 2018 at 9:32 AM Tyler Reddy < >>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>> >>>>>>>> I've pushed the v1.2.x wheels branch -- initially this will aim to >>>>>>>> confirm that SciPy master branch is now passing the Travis & Appveyor wheel >>>>>>>> builds. >>>>>>>> >>>>>>>> If that is the case, I will proceed with the 3 connected backport >>>>>>>> PRs to the maintenance branch. >>>>>>>> >>>>>>>> Then, I will point the v.1.2.x wheels branch to an appropriate >>>>>>>> commit on the patched maintenance branch for release candidate wheel builds. >>>>>>>> >>>>>>> >>>>>>> Sounds like a plan! >>>>>>> >>>>>>> Ralf >>>>>>> >>>>>>> >>>>>>>> >>>>>>>> On Sat, 17 Nov 2018 at 10:27, Ilhan Polat >>>>>>>> wrote: >>>>>>>> >>>>>>>>> Good stuff Tyler. I have to also add to that list the recent pypy3 >>>>>>>>> run failures appearing sporadically (though consistent on my PRs). >>>>>>>>> >>>>>>>>> I am trying triangulate the cause but probably will have to wait >>>>>>>>> until at least tomorrow. Feedback is more than welcome. They seem to be >>>>>>>>> related to cython/numpy versions but one can never be sure. >>>>>>>>> >>>>>>>>> ?lhan >>>>>>>>> >>>>>>>>> >>>>>>>>> On Fri, Nov 16, 2018, 19:35 Tyler Reddy >>>>>>>>> wrote: >>>>>>>>> >>>>>>>>>> Current delays / issues I'm working on--feel free to chime in on >>>>>>>>>> those: >>>>>>>>>> >>>>>>>>>> - a few test failures in wheel building matrix: >>>>>>>>>> https://github.com/MacPython/scipy-wheels/pull/37 >>>>>>>>>> - hard-to-understand putative patch for one of the failures: >>>>>>>>>> https://github.com/scipy/scipy/pull/9486 >>>>>>>>>> >>>>>>>>>> On Fri, 9 Nov 2018 at 08:40, Tyler Reddy < >>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>> >>>>>>>>>>> I branched 1.2.x around 8:30 am Pacific time on Nov. 9, 2018. >>>>>>>>>>> >>>>>>>>>>> Working on the follow up master branch PR to bump version number >>>>>>>>>>> / notes file, etc. now. >>>>>>>>>>> >>>>>>>>>>> On Thu, 8 Nov 2018 at 22:49, Tyler Reddy < >>>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>>> >>>>>>>>>>>> Release note PR is hopefully taking shape now -- I'll allow >>>>>>>>>>>> (another) delay for the branch until tomorrow (morning?) for some >>>>>>>>>>>> (hopefully final) checks on that. >>>>>>>>>>>> >>>>>>>>>>>> On Thu, 8 Nov 2018 at 14:35, Tyler Reddy < >>>>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>>>> >>>>>>>>>>>>> There are 0 remaining PRs with a 1.2.0 milestone. >>>>>>>>>>>>> >>>>>>>>>>>>> There is one issue left with a 1.2.0 milestone: >>>>>>>>>>>>> https://github.com/scipy/scipy/issues/9441 >>>>>>>>>>>>> >>>>>>>>>>>>> Please do take a look over the release notes WIP PR based on >>>>>>>>>>>>> the wiki: https://github.com/scipy/scipy/pull/9461 >>>>>>>>>>>>> >>>>>>>>>>>>> Target is to branch in 5-6 hours or so. Let me know if you see >>>>>>>>>>>>> any issues of course -- Ralf has been coaching >>>>>>>>>>>>> me through pretty well so far I think. >>>>>>>>>>>>> >>>>>>>>>>>>> On Wed, 7 Nov 2018 at 09:52, Ilhan Polat >>>>>>>>>>>>> wrote: >>>>>>>>>>>>> >>>>>>>>>>>>>> Hang in there Tyler :) >>>>>>>>>>>>>> >>>>>>>>>>>>>> Awesome job so far. >>>>>>>>>>>>>> >>>>>>>>>>>>>> >>>>>>>>>>>>>> On Wed, Nov 7, 2018, 06:08 Ralf Gommers < >>>>>>>>>>>>>> ralf.gommers at gmail.com> wrote: >>>>>>>>>>>>>> >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> On Tue, Nov 6, 2018 at 9:03 PM Tyler Reddy < >>>>>>>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> 7 PRs : >>>>>>>>>>>>>>>> https://github.com/scipy/scipy/pulls?q=is%3Aopen+is%3Apr+milestone%3A1.2.0 >>>>>>>>>>>>>>>> 3 issues: >>>>>>>>>>>>>>>> https://github.com/scipy/scipy/issues?q=is%3Aopen+is%3Aissue+milestone%3A1.2.0 >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> Awesome, getting there:) >>>>>>>>>>>>>>> >>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> Target: branch sometime on November 8th >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>> On Mon, 5 Nov 2018 at 05:42, Tyler Reddy < >>>>>>>>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> Alright, I'll extend to Thursday Nov. 8th & see if I can >>>>>>>>>>>>>>>>> reduce that list a bit >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> On Sun, 4 Nov 2018 at 22:27, Ralf Gommers < >>>>>>>>>>>>>>>>> ralf.gommers at gmail.com> wrote: >>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> On Fri, Oct 26, 2018 at 7:03 PM Mark Alexander Mikofski < >>>>>>>>>>>>>>>>>> mikofski at berkeley.edu> wrote: >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> Hi Tyler and others, >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> Thanks for managing the v1.2 release. >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> I think PR #8431, Cython optimize zeros API, is ready, >>>>>>>>>>>>>>>>>>> hopefully, to merge. It's been through several rounds of reviews and I >>>>>>>>>>>>>>>>>>> think I've accommodated all of the recommendations, all tests are passing, >>>>>>>>>>>>>>>>>>> and there's been strong support. Anyone please take a look. >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> https://github.com/scipy/scipy/pull/8431 >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> Thanks, >>>>>>>>>>>>>>>>>>> Mark >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> On Fri, Oct 26, 2018, 2:38 PM Ralf Gommers < >>>>>>>>>>>>>>>>>>> ralf.gommers at gmail.com> wrote: >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> On Thu, Oct 25, 2018 at 12:55 PM Tyler Reddy < >>>>>>>>>>>>>>>>>>>> tyler.je.reddy at gmail.com> wrote: >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>> Hi all, >>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>> It is almost 6 months after the 1.1.0 release on May >>>>>>>>>>>>>>>>>>>>> 5, so probably time to plan the 1.2.0 release. It would be a good idea to >>>>>>>>>>>>>>>>>>>>> look over the PRs with a 1.2.0 milestone >>>>>>>>>>>>>>>>>>>>> , >>>>>>>>>>>>>>>>>>>>> and tag anything else that should have this milestone appropriately. >>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>> I'd like to propose the following schedule: >>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>> Nov. 5: branch 1.2.x >>>>>>>>>>>>>>>>>>>>> Nov. 8: rc1 >>>>>>>>>>>>>>>>>>>>> Nov. 21: rc2 (if needed) >>>>>>>>>>>>>>>>>>>>> Nov. 30: final release >>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>>> Thoughts? >>>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>>> This looks like a good schedule to me. We'll probably >>>>>>>>>>>>>>>>>>>> struggle to get some PRs marked for 1.2.0 merged, but that's always the >>>>>>>>>>>>>>>>>>>> case. >>>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> Hi Tyler, could we shift the branch date by 2-3 days (or >>>>>>>>>>>>>>>>>> up to a week)? There's a couple of PRs that I'd really like to see merged >>>>>>>>>>>>>>>>>> or decided on (for optimize and stats mainly), and there's right now still >>>>>>>>>>>>>>>>>> 18 open PRs marked for 1.2.0. >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> A note on the open PRs: what we want to aim for is to >>>>>>>>>>>>>>>>>> have the list of open PRs and open blocking issues at zero, and have at >>>>>>>>>>>>>>>>>> most some non-blocking issues under the milestone left. Normally the >>>>>>>>>>>>>>>>>> release manager starts making those decisions, or pinging people, if other >>>>>>>>>>>>>>>>>> reviewers haven't done so in time. Of course it would be ideal if everyone >>>>>>>>>>>>>>>>>> has another look at >>>>>>>>>>>>>>>>>> https://github.com/scipy/scipy/pulls?q=is%3Aopen+is%3Apr+milestone%3A1.2.0 >>>>>>>>>>>>>>>>>> and bumps or finished off PRs he/she is involved in. >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> Cheers, >>>>>>>>>>>>>>>>>> Ralf >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>>>>>>>>> >>>>>>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>>>>>>> >>>>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>>>>>> >>>>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>>>>>> >>>>>>>>>>>>> _______________________________________________ >>>>>>>>>> SciPy-Dev mailing list >>>>>>>>>> SciPy-Dev at python.org >>>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>>> >>>>>>>>> _______________________________________________ >>>>>>>>> SciPy-Dev mailing list >>>>>>>>> SciPy-Dev at python.org >>>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>>> >>>>>>>> _______________________________________________ >>>>>>>> SciPy-Dev mailing list >>>>>>>> SciPy-Dev at python.org >>>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>>> >>>>>>> _______________________________________________ >>>>>>> SciPy-Dev mailing list >>>>>>> SciPy-Dev at python.org >>>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>>> >>>>>> _______________________________________________ >>>>>> SciPy-Dev mailing list >>>>>> SciPy-Dev at python.org >>>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>>> >>>>> _______________________________________________ >>>>> SciPy-Dev mailing list >>>>> SciPy-Dev at python.org >>>>> https://mail.python.org/mailman/listinfo/scipy-dev >>>>> >>>> _______________________________________________ >> SciPy-Dev mailing list >> SciPy-Dev at python.org >> https://mail.python.org/mailman/listinfo/scipy-dev >> > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > -------------- next part -------------- An HTML attachment was scrubbed... URL: From charlesr.harris at gmail.com Mon Dec 17 20:43:56 2018 From: charlesr.harris at gmail.com (Charles R Harris) Date: Mon, 17 Dec 2018 18:43:56 -0700 Subject: [SciPy-Dev] SciPy 1.2.0 release schedule In-Reply-To: References: Message-ID: On Mon, Dec 17, 2018 at 12:15 PM Tyler Reddy wrote: > Currently waiting on 1.2.0 wheel builds as of this morning. Appveyor can > take about 4.5 hours to handle that. > > I like to start the builds in the evening, then go to bed :) Chuck -------------- next part -------------- An HTML attachment was scrubbed... URL: From tyler.je.reddy at gmail.com Tue Dec 18 11:57:02 2018 From: tyler.je.reddy at gmail.com (Tyler Reddy) Date: Tue, 18 Dec 2018 08:57:02 -0800 Subject: [SciPy-Dev] ANN: SciPy 1.2.0 Message-ID: -----BEGIN PGP SIGNED MESSAGE----- Hash: SHA256 Hi all, On behalf of the SciPy development team I'm pleased to announce the release of SciPy 1.2.0. This is an LTS release and the last to support Python 2.7. Sources and binary wheels can be found at: https://pypi.org/project/scipy/ and at: https://github.com/scipy/scipy/releases/tag/v1.2.0 One of a few ways to install this release with pip: pip install scipy==1.2.0 ========================== SciPy 1.2.0 Release Notes ========================== SciPy 1.2.0 is the culmination of 6 months of hard work. It contains many new features, numerous bug-fixes, improved test coverage and better documentation. There have been a number of deprecations and API changes in this release, which are documented below. All users are encouraged to upgrade to this release, as there are a large number of bug-fixes and optimizations. Before upgrading, we recommend that users check that their own code does not use deprecated SciPy functionality (to do so, run your code with ``python -Wd`` and check for ``DeprecationWarning`` s). Our development attention will now shift to bug-fix releases on the 1.2.x branch, and on adding new features on the master branch. This release requires Python 2.7 or 3.4+ and NumPy 1.8.2 or greater. Note: This will be the last SciPy release to support Python 2.7. Consequently, the 1.2.x series will be a long term support (LTS) release; we will backport bug fixes until 1 Jan 2020. For running on PyPy, PyPy3 6.0+ and NumPy 1.15.0 are required. Highlights of this release --------------------------- - 1-D root finding improvements with a new solver, ``toms748``, and a new unified interface, ``root_scalar`` - New ``dual_annealing`` optimization method that combines stochastic and local deterministic searching - A new optimization algorithm, ``shgo`` (simplicial homology global optimization) for derivative free optimization problems - A new category of quaternion-based transformations are available in `scipy.spatial.transform` New features ============ `scipy.ndimage` improvements --------------------------------- Proper spline coefficient calculations have been added for the ``mirror``, ``wrap``, and ``reflect`` modes of `scipy.ndimage.rotate` `scipy.fftpack` improvements --------------------------------- DCT-IV, DST-IV, DCT-I, and DST-I orthonormalization are now supported in `scipy.fftpack`. `scipy.interpolate` improvements --------------------------------- `scipy.interpolate.pade` now accepts a new argument for the order of the numerator `scipy.cluster` improvements ----------------------------- `scipy.cluster.vq.kmeans2` gained a new initialization method, kmeans++. `scipy.special` improvements ----------------------------- The function ``softmax`` was added to `scipy.special`. `scipy.optimize` improvements ------------------------------ The one-dimensional nonlinear solvers have been given a unified interface `scipy.optimize.root_scalar`, similar to the `scipy.optimize.root` interface for multi-dimensional solvers. ``scipy.optimize.root_scalar(f, bracket=[a ,b], method="brenth")`` is equivalent to ``scipy.optimize.brenth(f, a ,b)``. If no ``method`` is specified, an appropriate one will be selected based upon the bracket and the number of derivatives available. The so-called Algorithm 748 of Alefeld, Potra and Shi for root-finding within an enclosing interval has been added as `scipy.optimize.toms748`. This provides guaranteed convergence to a root with convergence rate per function evaluation of approximately 1.65 (for sufficiently well-behaved functions.) ``differential_evolution`` now has the ``updating`` and ``workers`` keywords. The first chooses between continuous updating of the best solution vector (the default), or once per generation. Continuous updating can lead to faster convergence. The ``workers`` keyword accepts an ``int`` or map-like callable, and parallelises the solver (having the side effect of updating once per generation). Supplying an ``int`` evaluates the trial solutions in N parallel parts. Supplying a map-like callable allows other parallelisation approaches (such as ``mpi4py``, or ``joblib``) to be used. ``dual_annealing`` (and ``shgo`` below) is a powerful new general purpose global optizimation (GO) algorithm. ``dual_annealing`` uses two annealing processes to accelerate the convergence towards the global minimum of an objective mathematical function. The first annealing process controls the stochastic Markov chain searching and the second annealing process controls the deterministic minimization. So, dual annealing is a hybrid method that takes advantage of stochastic and local deterministic searching in an efficient way. ``shgo`` (simplicial homology global optimization) is a similar algorithm appropriate for solving black box and derivative free optimization (DFO) problems. The algorithm generally converges to the global solution in finite time. The convergence holds for non-linear inequality and equality constraints. In addition to returning a global minimum, the algorithm also returns any other global and local minima found after every iteration. This makes it useful for exploring the solutions in a domain. `scipy.optimize.newton` can now accept a scalar or an array ``MINPACK`` usage is now thread-safe, such that ``MINPACK`` + callbacks may be used on multiple threads. `scipy.signal` improvements ---------------------------- Digital filter design functions now include a parameter to specify the sampling rate. Previously, digital filters could only be specified using normalized frequency, but different functions used different scales (e.g. 0 to 1 for ``butter`` vs 0 to ? for ``freqz``), leading to errors and confusion. With the ``fs`` parameter, ordinary frequencies can now be entered directly into functions, with the normalization handled internally. ``find_peaks`` and related functions no longer raise an exception if the properties of a peak have unexpected values (e.g. a prominence of 0). A ``PeakPropertyWarning`` is given instead. The new keyword argument ``plateau_size`` was added to ``find_peaks``. ``plateau_size`` may be used to select peaks based on the length of the flat top of a peak. ``welch()`` and ``csd()`` methods in `scipy.signal` now support calculation of a median average PSD, using ``average='mean'`` keyword `scipy.sparse` improvements ---------------------------- The `scipy.sparse.bsr_matrix.tocsr` method is now implemented directly instead of converting via COO format, and the `scipy.sparse.bsr_matrix.tocsc` method is now also routed via CSR conversion instead of COO. The efficiency of both conversions is now improved. The issue where SuperLU or UMFPACK solvers crashed on matrices with non-canonical format in `scipy.sparse.linalg` was fixed. The solver wrapper canonicalizes the matrix if necessary before calling the SuperLU or UMFPACK solver. The ``largest`` option of `scipy.sparse.linalg.lobpcg()` was fixed to have a correct (and expected) behavior. The order of the eigenvalues was made consistent with the ARPACK solver (``eigs()``), i.e. ascending for the smallest eigenvalues, and descending for the largest eigenvalues. The `scipy.sparse.random` function is now faster and also supports integer and complex values by passing the appropriate value to the ``dtype`` argument. `scipy.spatial` improvements ----------------------------- The function `scipy.spatial.distance.jaccard` was modified to return 0 instead of ``np.nan`` when two all-zero vectors are compared. Support for the Jensen Shannon distance, the square-root of the divergence, has been added under `scipy.spatial.distance.jensenshannon` An optional keyword was added to the function `scipy.spatial.cKDTree.query_ball_point()` to sort or not sort the returned indices. Not sorting the indices can speed up calls. A new category of quaternion-based transformations are available in `scipy.spatial.transform`, including spherical linear interpolation of rotations (``Slerp``), conversions to and from quaternions, Euler angles, and general rotation and inversion capabilities (`spatial.transform.Rotation`), and uniform random sampling of 3D rotations (`spatial.transform.Rotation.random`). `scipy.stats` improvements --------------------------- The Yeo-Johnson power transformation is now supported (``yeojohnson``, ``yeojohnson_llf``, ``yeojohnson_normmax``, ``yeojohnson_normplot``). Unlike the Box-Cox transformation, the Yeo-Johnson transformation can accept negative values. Added a general method to sample random variates based on the density only, in the new function ``rvs_ratio_uniforms``. The Yule-Simon distribution (``yulesimon``) was added -- this is a new discrete probability distribution. ``stats`` and ``mstats`` now have access to a new regression method, ``siegelslopes``, a robust linear regression algorithm `scipy.stats.gaussian_kde` now has the ability to deal with weighted samples, and should have a modest improvement in performance Levy Stable Parameter Estimation, PDF, and CDF calculations are now supported for `scipy.stats.levy_stable`. The Brunner-Munzel test is now available as ``brunnermunzel`` in ``stats`` and ``mstats`` `scipy.linalg` improvements --------------------------- `scipy.linalg.lapack` now exposes the LAPACK routines using the Rectangular Full Packed storage (RFP) for upper triangular, lower triangular, symmetric, or Hermitian matrices; the upper trapezoidal fat matrix RZ decomposition routines are now available as well. Deprecated features =================== The functions ``hyp2f0``, ``hyp1f2`` and ``hyp3f0`` in ``scipy.special`` have been deprecated. Backwards incompatible changes ============================== LAPACK version 3.4.0 or later is now required. Building with Apple Accelerate is no longer supported. The function ``scipy.linalg.subspace_angles(A, B)`` now gives correct results for all angles. Before this, the function only returned correct values for those angles which were greater than pi/4. Support for the Bento build system has been removed. Bento has not been maintained for several years, and did not have good Python 3 or wheel support, hence it was time to remove it. The required signature of `scipy.optimize.lingprog` ``method=simplex`` callback function has changed. Before iteration begins, the simplex solver first converts the problem into a standard form that does not, in general, have the same variables or constraints as the problem defined by the user. Previously, the simplex solver would pass a user-specified callback function several separate arguments, such as the current solution vector ``xk``, corresponding to this standard form problem. Unfortunately, the relationship between the standard form problem and the user-defined problem was not documented, limiting the utility of the information passed to the callback function. In addition to numerous bug fix changes, the simplex solver now passes a user-specified callback function a single ``OptimizeResult`` object containing information that corresponds directly to the user-defined problem. In future releases, this ``OptimizeResult`` object may be expanded to include additional information, such as variables corresponding to the standard-form problem and information concerning the relationship between the standard-form and user-defined problems. The implementation of `scipy.sparse.random` has changed, and this affects the numerical values returned for both ``sparse.random`` and ``sparse.rand`` for some matrix shapes and a given seed. `scipy.optimize.newton` will no longer use Halley's method in cases where it negatively impacts convergence Other changes ============= Authors ======= * @endolith * @luzpaz * Hameer Abbasi + * akahard2dj + * Anton Akhmerov * Joseph Albert * alexthomas93 + * ashish + * atpage + * Blair Azzopardi + * Yoshiki V?zquez Baeza * Bence Bagi + * Christoph Baumgarten * Lucas Bellomo + * BH4 + * Aditya Bharti * Max Bolingbroke * Fran?ois Boulogne * Ward Bradt + * Matthew Brett * Evgeni Burovski * Rafa? Byczek + * Alfredo Canziani + * CJ Carey * Luc?a Cheung + * Poom Chiarawongse + * Jeanne Choo + * Robert Cimrman * Graham Clenaghan + * cynthia-rempel + * Johannes Damp + * Jaime Fernandez del Rio * Dowon + * emmi474 + * Stefan Endres + * Thomas Etherington + * Piotr Figiel * Alex Fikl + * fo40225 + * Joseph Fox-Rabinovitz * Lars G * Abhinav Gautam + * Stiaan Gerber + * C.A.M. Gerlach + * Ralf Gommers * Todd Goodall * Lars Grueter + * Sylvain Gubian + * Matt Haberland * David Hagen * Will Handley + * Charles Harris * Ian Henriksen * Thomas Hisch + * Theodore Hu * Michael Hudson-Doyle + * Nicolas Hug + * jakirkham + * Jakob Jakobson + * James + * Jan Schl?ter * jeanpauphilet + * josephmernst + * Kai + * Kai-Striega + * kalash04 + * Toshiki Kataoka + * Konrad0 + * Tom Krauss + * Johannes Kulick * Lars Gr?ter + * Eric Larson * Denis Laxalde * Will Lee + * Katrin Leinweber + * Yin Li + * P. L. Lim + * Jesse Livezey + * Duncan Macleod + * MatthewFlamm + * Nikolay Mayorov * Mike McClurg + * Christian Meyer + * Mark Mikofski * Naoto Mizuno + * mohmmadd + * Nathan Musoke * Anju Geetha Nair + * Andrew Nelson * Ayappan P + * Nick Papior * Haesun Park + * Ronny Pfannschmidt + * pijyoi + * Ilhan Polat * Anthony Polloreno + * Ted Pudlik * puenka * Eric Quintero * Pradeep Reddy Raamana + * Vyas Ramasubramani + * Ramon Vi?as + * Tyler Reddy * Joscha Reimer * Antonio H Ribeiro * richardjgowers + * Rob + * robbystk + * Lucas Roberts + * rohan + * Joaquin Derrac Rus + * Josua Sassen + * Bruce Sharpe + * Max Shinn + * Scott Sievert * Sourav Singh * Strahinja Luki? + * Kai Striega + * Shinya SUZUKI + * Mike Toews + * Piotr Uchwat * Miguel de Val-Borro + * Nicky van Foreest * Paul van Mulbregt * Gael Varoquaux * Pauli Virtanen * Stefan van der Walt * Warren Weckesser * Joshua Wharton + * Bernhard M. Wiedemann + * Eric Wieser * Josh Wilson * Tony Xiang + * Roman Yurchak + * Roy Zywina + A total of 137 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete. Issues closed for 1.2.0 ------------------------ * `#9520 `__: signal.correlate with method='fft' doesn't benefit from long... * `#9547 `__: signature of dual_annealing doesn't match other optimizers * `#9540 `__: SciPy v1.2.0rc1 cannot be imported on Python 2.7.15 * `#1240 `__: Allowing multithreaded use of minpack through scipy.optimize... * `#1432 `__: scipy.stats.mode extremely slow (Trac #905) * `#3372 `__: Please add Sphinx search field to online scipy html docs * `#3678 `__: _clough_tocher_2d_single direction between centroids * `#4174 `__: lobpcg "largest" option invalid? * `#5493 `__: anderson_ksamp p-values>1 * `#5743 `__: slsqp fails to detect infeasible problem * `#6139 `__: scipy.optimize.linprog failed to find a feasible starting point... * `#6358 `__: stats: docstring for `vonmises_line` points to `vonmises_line`... * `#6498 `__: runtests.py is missing in pypi distfile * `#7426 `__: scipy.stats.ksone(n).pdf(x) returns nan for positive values of... * `#7455 `__: scipy.stats.ksone.pdf(2,x) return incorrect values for x near... * `#7456 `__: scipy.special.smirnov and scipy.special.smirnovi have accuracy... * `#7492 `__: scipy.special.kolmogorov(x)/kolmogi(p) inefficient, inaccurate... * `#7914 `__: TravisCI not failing when it should for -OO run * `#8064 `__: linalg.solve test crashes on Windows * `#8212 `__: LAPACK Rectangular Full Packed routines * `#8256 `__: differential_evolution bug converges to wrong results in complex... * `#8443 `__: Deprecate `hyp2f0`, `hyp1f2`, and `hyp3f0`? * `#8452 `__: DOC: ARPACK tutorial has two conflicting equations * `#8680 `__: scipy fails compilation when building from source * `#8686 `__: Division by zero in _trustregion.py when x0 is exactly equal... * `#8700 `__: _MINPACK_LOCK not held when calling into minpack from least_squares * `#8786 `__: erroneous moment values for t-distribution * `#8791 `__: Checking COLA condition in istft should be optional (or omitted) * `#8843 `__: imresize cannot be deprecated just yet * `#8844 `__: Inverse Wishart Log PDF Incorrect for Non-diagonal Scale Matrix? * `#8878 `__: vonmises and vonmises_line in stats: vonmises wrong and superfluous? * `#8895 `__: v1.1.0 `ndi.rotate` documentation ? reused parameters not filled... * `#8900 `__: Missing complex conjugation in scipy.sparse.linalg.LinearOperator * `#8904 `__: BUG: if zero derivative at root, then Newton fails with RuntimeWarning * `#8911 `__: make_interp_spline bc_type incorrect input interpretation * `#8942 `__: MAINT: Refactor `_linprog.py` and `_linprog_ip.py` to remove... * `#8947 `__: np.int64 in scipy.fftpack.next_fast_len * `#9020 `__: BUG: linalg.subspace_angles gives wrong results * `#9033 `__: scipy.stats.normaltest sometimes gives incorrect returns b/c... * `#9036 `__: Bizarre times for `scipy.sparse.rand` function with 'low' density... * `#9044 `__: optimize.minimize(method=`trust-constr`) result dict does not... * `#9071 `__: doc/linalg: add cho_solve_banded to see also of cholesky_banded * `#9082 `__: eigenvalue sorting in scipy.sparse.linalg.eigsh * `#9086 `__: signaltools.py:491: FutureWarning: Using a non-tuple sequence... * `#9091 `__: test_spline_filter failure on 32-bit * `#9122 `__: Typo on scipy minimization tutorial * `#9135 `__: doc error at https://docs.scipy.org/doc/scipy/reference/tutorial/stats/discrete_poisson.html * `#9167 `__: DOC: BUG: typo in ndimage LowLevelCallable tutorial example * `#9169 `__: truncnorm does not work if b < a in scipy.stats * `#9250 `__: scipy.special.tests.test_mpmath::TestSystematic::test_pcfw fails... * `#9259 `__: rv.expect() == rv.mean() is false for rv.mean() == nan (and inf) * `#9286 `__: DOC: Rosenbrock expression in optimize.minimize tutorial * `#9316 `__: SLSQP fails in nested optimization * `#9337 `__: scipy.signal.find_peaks key typo in documentation * `#9345 `__: Example from documentation of scipy.sparse.linalg.eigs raises... * `#9383 `__: Default value for "mode" in "ndimage.shift" * `#9419 `__: dual_annealing off by one in the number of iterations * `#9442 `__: Error in Defintion of Rosenbrock Function * `#9453 `__: TST: test_eigs_consistency() doesn't have consistent results Pull requests for 1.2.0 ------------------------ * `#9526 `__: TST: relax precision requirements in signal.correlate tests * `#9507 `__: CI: MAINT: Skip a ckdtree test on pypy * `#9512 `__: TST: test_random_sampling 32-bit handling * `#9494 `__: TST: test_kolmogorov xfail 32-bit * `#9486 `__: BUG: fix sparse random int handling * `#9550 `__: BUG: scipy/_lib/_numpy_compat: get_randint * `#9549 `__: MAINT: make dual_annealing signature match other optimizers * `#9541 `__: BUG: fix SyntaxError due to non-ascii character on Python 2.7 * `#7352 `__: ENH: add Brunner Munzel test to scipy.stats. * `#7373 `__: BUG: Jaccard distance for all-zero arrays would return np.nan * `#7374 `__: ENH: Add PDF, CDF and parameter estimation for Stable Distributions * `#8098 `__: ENH: Add shgo for global optimization of NLPs. * `#8203 `__: ENH: adding simulated dual annealing to optimize * `#8259 `__: Option to follow original Storn and Price algorithm and its parallelisation * `#8293 `__: ENH add ratio-of-uniforms method for rv generation to scipy.stats * `#8294 `__: BUG: Fix slowness in stats.mode * `#8295 `__: ENH: add Jensen Shannon distance to `scipy.spatial.distance` * `#8357 `__: ENH: vectorize scalar zero-search-functions * `#8397 `__: Add `fs=` parameter to filter design functions * `#8537 `__: ENH: Implement mode parameter for spline filtering. * `#8558 `__: ENH: small speedup for stats.gaussian_kde * `#8560 `__: BUG: fix p-value calc of anderson_ksamp in scipy.stats * `#8614 `__: ENH: correct p-values for stats.kendalltau and stats.mstats.kendalltau * `#8670 `__: ENH: Require Lapack 3.4.0 * `#8683 `__: Correcting kmeans documentation * `#8725 `__: MAINT: Cleanup scipy.optimize.leastsq * `#8726 `__: BUG: Fix _get_output in scipy.ndimage to support string * `#8733 `__: MAINT: stats: A bit of clean up. * `#8737 `__: BUG: Improve numerical precision/convergence failures of smirnov/kolmogorov * `#8738 `__: MAINT: stats: A bit of clean up in test_distributions.py. * `#8740 `__: BF/ENH: make minpack thread safe * `#8742 `__: BUG: Fix division by zero in trust-region optimization methods * `#8746 `__: MAINT: signal: Fix a docstring of a private function, and fix... * `#8750 `__: DOC clarified description of norminvgauss in scipy.stats * `#8753 `__: DOC: signal: Fix a plot title in the chirp docstring. * `#8755 `__: DOC: MAINT: Fix link to the wheel documentation in developer... * `#8760 `__: BUG: stats: boltzmann wasn't setting the upper bound. * `#8763 `__: [DOC] Improved scipy.cluster.hierarchy documentation * `#8765 `__: DOC: added example for scipy.stat.mstats.tmin * `#8788 `__: DOC: fix definition of optional `disp` parameter * `#8802 `__: MAINT: Suppress dd_real unused function compiler warnings. * `#8803 `__: ENH: Add full_output support to optimize.newton() * `#8804 `__: MAINT: stats cleanup * `#8808 `__: DOC: add note about isinstance for frozen rvs * `#8812 `__: Updated numpydoc submodule * `#8813 `__: MAINT: stats: Fix multinomial docstrings, and do some clean up. * `#8816 `__: BUG: fixed _stats of t-distribution in scipy.stats * `#8817 `__: BUG: ndimage: Fix validation of the origin argument in correlate... * `#8822 `__: BUG: integrate: Fix crash with repeated t values in odeint. * `#8832 `__: Hyperlink DOIs against preferred resolver * `#8837 `__: BUG: sparse: Ensure correct dtype for sparse comparison operations. * `#8839 `__: DOC: stats: A few tweaks to the linregress docstring. * `#8846 `__: BUG: stats: Fix logpdf method of invwishart. * `#8849 `__: DOC: signal: Fixed mistake in the firwin docstring. * `#8854 `__: DOC: fix type descriptors in ltisys documentation * `#8865 `__: Fix tiny typo in docs for chi2 pdf * `#8870 `__: Fixes related to invertibility of STFT * `#8872 `__: ENH: special: Add the softmax function * `#8874 `__: DOC correct gamma function in docstrings in scipy.stats * `#8876 `__: ENH: Added TOMS Algorithm 748 as 1-d root finder; 17 test function... * `#8882 `__: ENH: Only use Halley's adjustment to Newton if close enough. * `#8883 `__: FIX: optimize: make jac and hess truly optional for 'trust-constr' * `#8885 `__: TST: Do not error on warnings raised about non-tuple indexing. * `#8887 `__: MAINT: filter out np.matrix PendingDeprecationWarning's in numpy... * `#8889 `__: DOC: optimize: separate legacy interfaces from new ones * `#8890 `__: ENH: Add optimize.root_scalar() as a universal dispatcher for... * `#8899 `__: DCT-IV, DST-IV and DCT-I, DST-I orthonormalization support in... * `#8901 `__: MAINT: Reorganize flapack.pyf.src file * `#8907 `__: BUG: ENH: Check if guess for newton is already zero before checking... * `#8908 `__: ENH: Make sorting optional for cKDTree.query_ball_point() * `#8910 `__: DOC: sparse.csgraph simple examples. * `#8914 `__: DOC: interpolate: fix equivalences of string aliases * `#8918 `__: add float_control(precise, on) to _fpumode.c * `#8919 `__: MAINT: interpolate: improve error messages for common `bc_type`... * `#8920 `__: DOC: update Contributing to SciPy to say "prefer no PEP8 only... * `#8924 `__: MAINT: special: deprecate `hyp2f0`, `hyp1f2`, and `hyp3f0` * `#8927 `__: MAINT: special: remove `errprint` * `#8932 `__: Fix broadcasting scale arg of entropy * `#8936 `__: Fix (some) non-tuple index warnings * `#8937 `__: ENH: implement sparse matrix BSR to CSR conversion directly. * `#8938 `__: DOC: add @_ni_docstrings.docfiller in ndimage.rotate * `#8940 `__: Update _discrete_distns.py * `#8943 `__: DOC: Finish dangling sentence in `convolve` docstring * `#8944 `__: MAINT: Address tuple indexing and warnings * `#8945 `__: ENH: spatial.transform.Rotation [GSOC2018] * `#8950 `__: csgraph Dijkstra function description rewording * `#8953 `__: DOC, MAINT: HTTP -> HTTPS, and other linkrot fixes * `#8955 `__: BUG: np.int64 in scipy.fftpack.next_fast_len * `#8958 `__: MAINT: Add more descriptive error message for phase one simplex. * `#8962 `__: BUG: sparse.linalg: add missing conjugate to _ScaledLinearOperator.adjoint * `#8963 `__: BUG: sparse.linalg: downgrade LinearOperator TypeError to warning * `#8965 `__: ENH: Wrapped RFP format and RZ decomposition routines * `#8969 `__: MAINT: doc and code fixes for optimize.newton * `#8970 `__: Added 'average' keyword for welch/csd to enable median averaging * `#8971 `__: Better imresize deprecation warning * `#8972 `__: MAINT: Switch np.where(c) for np.nonzero(c) * `#8975 `__: MAINT: Fix warning-based failures * `#8979 `__: DOC: fix description of count_sort keyword of dendrogram * `#8982 `__: MAINT: optimize: Fixed minor mistakes in test_linprog.py (#8978) * `#8984 `__: BUG: sparse.linalg: ensure expm casts integer inputs to float * `#8986 `__: BUG: optimize/slsqp: do not exit with convergence on steps where... * `#8989 `__: MAINT: use collections.abc in basinhopping * `#8990 `__: ENH extend p-values of anderson_ksamp in scipy.stats * `#8991 `__: ENH: Weighted kde * `#8993 `__: ENH: spatial.transform.Rotation.random [GSOC 2018] * `#8994 `__: ENH: spatial.transform.Slerp [GSOC 2018] * `#8995 `__: TST: time.time in test * `#9007 `__: Fix typo in fftpack.rst * `#9013 `__: Added correct plotting code for two sided output from spectrogram * `#9014 `__: BUG: differential_evolution with inf objective functions * `#9017 `__: BUG: fixed #8446 corner case for asformat(array|dense) * `#9018 `__: MAINT: _lib/ccallback: remove unused code * `#9021 `__: BUG: Issue with subspace_angles * `#9022 `__: DOC: Added "See Also" section to lombscargle docstring * `#9034 `__: BUG: Fix tolerance printing behavior, remove meaningless tol... * `#9035 `__: TST: improve signal.bsplines test coverage * `#9037 `__: ENH: add a new init method for k-means * `#9039 `__: DOC: Add examples to fftpack.irfft docstrings * `#9048 `__: ENH: scipy.sparse.random * `#9050 `__: BUG: scipy.io.hb_write: fails for matrices not in csc format * `#9051 `__: MAINT: Fix slow sparse.rand for k < mn/3 (#9036). * `#9054 `__: MAINT: spatial: Explicitly initialize LAPACK output parameters. * `#9055 `__: DOC: Add examples to scipy.special docstrings * `#9056 `__: ENH: Use one thread in OpenBLAS * `#9059 `__: DOC: Update README with link to Code of Conduct * `#9060 `__: BLD: remove support for the Bento build system. * `#9062 `__: DOC add sections to overview in scipy.stats * `#9066 `__: BUG: Correct "remez" error message * `#9069 `__: DOC: update linalg section of roadmap for LAPACK versions. * `#9079 `__: MAINT: add spatial.transform to refguide check; complete some... * `#9081 `__: MAINT: Add warnings if pivot value is close to tolerance in linprog(method='simplex') * `#9084 `__: BUG fix incorrect p-values of kurtosistest in scipy.stats * `#9095 `__: DOC: add sections to mstats overview in scipy.stats * `#9096 `__: BUG: Add test for Stackoverflow example from issue 8174. * `#9101 `__: ENH: add Siegel slopes (robust regression) to scipy.stats * `#9105 `__: allow resample_poly() to output float32 for float32 inputs. * `#9112 `__: MAINT: optimize: make trust-constr accept constraint dict (#9043) * `#9118 `__: Add doc entry to cholesky_banded * `#9120 `__: eigsh documentation parameters * `#9125 `__: interpolative: correctly reconstruct full rank matrices * `#9126 `__: MAINT: Use warnings for unexpected peak properties * `#9129 `__: BUG: Do not catch and silence KeyboardInterrupt * `#9131 `__: DOC: Correct the typo in scipy.optimize tutorial page * `#9133 `__: FIX: Avoid use of bare except * `#9134 `__: DOC: Update of 'return_eigenvectors' description * `#9137 `__: DOC: typo fixes for discrete Poisson tutorial * `#9139 `__: FIX: Doctest failure in optimize tutorial * `#9143 `__: DOC: missing sigma in Pearson r formula * `#9145 `__: MAINT: Refactor linear programming solvers * `#9149 `__: FIX: Make scipy.odr.ODR ifixx equal to its data.fix if given * `#9156 `__: DOC: special: Mention the sigmoid function in the expit docstring. * `#9160 `__: Fixed a latex delimiter error in levy() * `#9170 `__: DOC: correction / update of docstrings of distributions in scipy.stats * `#9171 `__: better description of the hierarchical clustering parameter * `#9174 `__: domain check for a < b in stats.truncnorm * `#9175 `__: DOC: Minor grammar fix * `#9176 `__: BUG: CloughTocher2DInterpolator: fix miscalculation at neighborless... * `#9177 `__: BUILD: Document the "clean" target in the doc/Makefile. * `#9178 `__: MAINT: make refguide-check more robust for printed numpy arrays * `#9186 `__: MAINT: Remove np.ediff1d occurence * `#9188 `__: DOC: correct typo in extending ndimage with C * `#9190 `__: ENH: Support specifying axes for fftconvolve * `#9192 `__: MAINT: optimize: fixed @pv style suggestions from #9112 * `#9200 `__: Fix make_interp_spline(..., k=0 or 1, axis<0) * `#9201 `__: BUG: sparse.linalg/gmres: use machine eps in breakdown check * `#9204 `__: MAINT: fix up stats.spearmanr and match mstats.spearmanr with... * `#9206 `__: MAINT: include benchmarks and dev files in sdist. * `#9208 `__: TST: signal: bump bsplines test tolerance for complex data * `#9210 `__: TST: mark tests as slow, fix missing random seed * `#9211 `__: ENH: add capability to specify orders in pade func * `#9217 `__: MAINT: Include ``success`` and ``nit`` in OptimizeResult returned... * `#9222 `__: ENH: interpolate: Use scipy.spatial.distance to speed-up Rbf * `#9229 `__: MNT: Fix Fourier filter double case * `#9233 `__: BUG: spatial/distance: fix pdist/cdist performance regression... * `#9234 `__: FIX: Proper suppression * `#9235 `__: BENCH: rationalize slow benchmarks + miscellaneous fixes * `#9238 `__: BENCH: limit number of parameter combinations in spatial.*KDTree... * `#9239 `__: DOC: stats: Fix LaTeX markup of a couple distribution PDFs. * `#9241 `__: ENH: Evaluate plateau size during peak finding * `#9242 `__: ENH: stats: Implement _ppf and _logpdf for crystalball, and do... * `#9246 `__: DOC: Properly render versionadded directive in HTML documentation * `#9255 `__: DOC: mention RootResults in optimization reference guide * `#9260 `__: TST: relax some tolerances so tests pass with x87 math * `#9264 `__: TST Use assert_raises "match" parameter instead of the "message"... * `#9267 `__: DOC: clarify expect() return val when moment is inf/nan * `#9272 `__: DOC: Add description of default bounds to linprog * `#9277 `__: MAINT: sparse/linalg: make test deterministic * `#9278 `__: MAINT: interpolate: pep8 cleanup in test_polyint * `#9279 `__: Fixed docstring for resample * `#9280 `__: removed first check for float in get_sum_dtype * `#9281 `__: BUG: only accept 1d input for bartlett / levene in scipy.stats * `#9282 `__: MAINT: dense_output and t_eval are mutually exclusive inputs * `#9283 `__: MAINT: add docs and do some cleanups in interpolate.Rbf * `#9288 `__: Run distance_transform_edt tests on all types * `#9294 `__: DOC: fix the formula typo * `#9298 `__: MAINT: optimize/trust-constr: restore .niter attribute for backward-compat * `#9299 `__: DOC: clarification of default rvs method in scipy.stats * `#9301 `__: MAINT: removed unused import sys * `#9302 `__: MAINT: removed unused imports * `#9303 `__: DOC: signal: Refer to fs instead of nyq in the firwin docstring. * `#9305 `__: ENH: Added Yeo-Johnson power transformation * `#9306 `__: ENH - add dual annealing * `#9309 `__: ENH add the yulesimon distribution to scipy.stats * `#9317 `__: Nested SLSQP bug fix. * `#9320 `__: MAINT: stats: avoid underflow in stats.geom.ppf * `#9326 `__: Add example for Rosenbrock function * `#9332 `__: Sort file lists * `#9340 `__: Fix typo in find_peaks documentation * `#9343 `__: MAINT Use np.full when possible * `#9344 `__: DOC: added examples to docstring of dirichlet class * `#9346 `__: DOC: Fix import of scipy.sparse.linalg in example (#9345) * `#9350 `__: Fix interpolate read only * `#9351 `__: MAINT: special.erf: use the x->-x symmetry * `#9356 `__: Fix documentation typo * `#9358 `__: DOC: improve doc for ksone and kstwobign in scipy.stats * `#9362 `__: DOC: Change datatypes of A matrices in linprog * `#9364 `__: MAINT: Adds implicit none to fftpack fortran sources * `#9369 `__: DOC: minor tweak to CoC (updated NumFOCUS contact address). * `#9373 `__: Fix exception if python is called with -OO option * `#9374 `__: FIX: AIX compilation issue with NAN and INFINITY * `#9376 `__: COBLYA -> COBYLA in docs * `#9377 `__: DOC: Add examples integrate: fixed_quad and quadrature * `#9379 `__: MAINT: TST: Make tests NumPy 1.8 compatible * `#9385 `__: CI: On Travis matrix "OPTIMIZE=-OO" flag ignored * `#9387 `__: Fix defaut value for 'mode' in 'ndimage.shift' in the doc * `#9392 `__: BUG: rank has to be integer in rank_filter: fixed issue 9388 * `#9399 `__: DOC: Misc. typos * `#9400 `__: TST: stats: Fix the expected r-value of a linregress test. * `#9405 `__: BUG: np.hstack does not accept generator expressions * `#9408 `__: ENH: linalg: Shorter ill-conditioned warning message * `#9418 `__: DOC: Fix ndimage docstrings and reduce doc build warnings * `#9421 `__: DOC: Add missing docstring examples in scipy.spatial * `#9422 `__: DOC: Add an example to integrate.newton_cotes * `#9427 `__: BUG: Fixed defect with maxiter #9419 in dual annealing * `#9431 `__: BENCH: Add dual annealing to scipy benchmark (see #9415) * `#9435 `__: DOC: Add docstring examples for stats.binom_test * `#9443 `__: DOC: Fix the order of indices in optimize tutorial * `#9444 `__: MAINT: interpolate: use operator.index for checking/coercing... * `#9445 `__: DOC: Added missing example to stats.mstats.kruskal * `#9446 `__: DOC: Add note about version changed for jaccard distance * `#9447 `__: BLD: version-script handling in setup.py * `#9448 `__: TST: skip a problematic linalg test * `#9449 `__: TST: fix missing seed in lobpcg test. * `#9456 `__: TST: test_eigs_consistency() now sorts output Checksums ========= MD5 ~~~ 0bb53a49e77bca11fb26698744c60f97 scipy-1.2.0-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 39e215ac7e8d6de33d939486987dcba4 scipy-1.2.0-cp27-cp27m-manylinux1_i686.whl d6e33b2c05ffbcf9790628d656c8e61f scipy-1.2.0-cp27-cp27m-manylinux1_x86_64.whl a463a12d77b87df0a2d202323771a908 scipy-1.2.0-cp27-cp27m-win32.whl 3dc17a11c7dd211ce51a338cfe30eb48 scipy-1.2.0-cp27-cp27m-win_amd64.whl 82b1ecbecadfeddd2be1c6d616491029 scipy-1.2.0-cp27-cp27mu-manylinux1_i686.whl 65021ade783f1416b1920d2a2cc39d4d scipy-1.2.0-cp27-cp27mu-manylinux1_x86_64.whl 7cc2cdbc9b421ef10695b898cdc241e7 scipy-1.2.0-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 2a4ccbfcccb9395fa7554a82db40e454 scipy-1.2.0-cp34-cp34m-manylinux1_i686.whl 662dc35acd6f588565cd6467465fc742 scipy-1.2.0-cp34-cp34m-manylinux1_x86_64.whl a19bd9969bb5b92595e82d924b8272f9 scipy-1.2.0-cp34-cp34m-win32.whl 5f1eaa3745956db0da724f83dd174559 scipy-1.2.0-cp34-cp34m-win_amd64.whl d32a4c31d0a188f3550c1306d20b03c7 scipy-1.2.0-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 34f4a7f04abfda87fac8ab38a9a70a77 scipy-1.2.0-cp35-cp35m-manylinux1_i686.whl bd4d56910802870072e3c5ded69a8f08 scipy-1.2.0-cp35-cp35m-manylinux1_x86_64.whl cb3fb7ddd3992928f9173e4eb489d23e scipy-1.2.0-cp35-cp35m-win32.whl 68f5ddcb6e592b1d9cba95f24faee7b5 scipy-1.2.0-cp35-cp35m-win_amd64.whl c0e110f3a935731782c96a13cc264ea2 scipy-1.2.0-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 9d898924498abbe2d26dd18b3413fb11 scipy-1.2.0-cp36-cp36m-manylinux1_i686.whl dd9ae664cbe7de54828d83c772e24da3 scipy-1.2.0-cp36-cp36m-manylinux1_x86_64.whl 8dea8432610bb3c63114eb6469c5f99a scipy-1.2.0-cp36-cp36m-win32.whl ebda830aec7b60193772741f85fee28c scipy-1.2.0-cp36-cp36m-win_amd64.whl 0e8b7a7908c50e635e639d2c69901140 scipy-1.2.0-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 56719437a821f9f2f98f069225e70c87 scipy-1.2.0-cp37-cp37m-manylinux1_i686.whl 93d9d978855516ec38fa08620ef3443c scipy-1.2.0-cp37-cp37m-manylinux1_x86_64.whl fff3d66b877b6e6b9984b84ae9e4d76c scipy-1.2.0-cp37-cp37m-win32.whl 3defb2c8b2f69057919ee3b0c92de65c scipy-1.2.0-cp37-cp37m-win_amd64.whl e57011507865b0b702aff6077d412e03 scipy-1.2.0.tar.gz 8eb6c1d7ceae0d06aef474f7801b8fca scipy-1.2.0.tar.xz b0fb16b09319d3031d27ccf21a3ef474 scipy-1.2.0.zip SHA256 ~~~~~~ d1ae77b79fd5e27a10ba7c4e7c3a62927b9d29a4dccf28f6905c25d983aaf183 scipy-1.2.0-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 4b1f0883cb9d8ee963cf0a31c87341e9e758abb2cf1e5bcc0d7b066ef6b17573 scipy-1.2.0-cp27-cp27m-manylinux1_i686.whl c5eae911cf26b3c7eda889ec98d3c226f312c587acfaaf02602473f98b4c16d6 scipy-1.2.0-cp27-cp27m-manylinux1_x86_64.whl 58f0435f052cb60f1472c77f52a8f6642f8877b70559e5e0b9a1744f33f5cbe5 scipy-1.2.0-cp27-cp27m-win32.whl 4cce25c6e7ff7399c67dfe1b5423c36c391cf9b4b2be390c1675ab410f1ef503 scipy-1.2.0-cp27-cp27m-win_amd64.whl 02cb79ea38114dc480e9b08d6b87095728e8fb39b9a49b449ee443d678001611 scipy-1.2.0-cp27-cp27mu-manylinux1_i686.whl 7dc4002f0a0a688774ef04878afe769ecd1ac21fe9b4b1d7125e2cf16170afd3 scipy-1.2.0-cp27-cp27mu-manylinux1_x86_64.whl 7994c044bf659b0a24ad7673ec7db85c2fadb87e4980a379a9fd5b086fe3649a scipy-1.2.0-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 72bd766f753fd32f072d30d7bc2ad492d56dbcbf3e13764e27635d5c41079339 scipy-1.2.0-cp34-cp34m-manylinux1_i686.whl 3132a9fab3f3545c8b0ba15688d11857efdd4a58d388d3785dc474f56fea7138 scipy-1.2.0-cp34-cp34m-manylinux1_x86_64.whl 7413080b381766a22d52814edb65631f0e323a7cea945c70021a672f38acc73f scipy-1.2.0-cp34-cp34m-win32.whl 6f791987899532305126309578727c0197bddbafab9596bafe3e7bfab6e1ce13 scipy-1.2.0-cp34-cp34m-win_amd64.whl 937147086e8b4338bf139ca8fa98da650e3a46bf2ca617f8e9dd68c3971ec420 scipy-1.2.0-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 63e1d5ca9e5e1984f1a275276991b036e25d39d37dd7edbb3f4f6165c2da7dbb scipy-1.2.0-cp35-cp35m-manylinux1_i686.whl 03c827cdbc584e935264040b958e5fa0570a16095bee23a013482ba3f0e963a2 scipy-1.2.0-cp35-cp35m-manylinux1_x86_64.whl bc294841f6c822714af362095b181a853f47ed5ce757354bd2e4776d579ff3a4 scipy-1.2.0-cp35-cp35m-win32.whl cca33a01a5987c650b87a1a910aa311ffa44e67cca1ff502ef9efdae5d9a8624 scipy-1.2.0-cp35-cp35m-win_amd64.whl 8608316d0cc01f8b25111c8adfe6efbc959cbba037a62c784551568d7ffbf280 scipy-1.2.0-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl fb36064047e6bf87b6320a9b6eb7f525ef6863c7a4aef1a84a4bbfb043612617 scipy-1.2.0-cp36-cp36m-manylinux1_i686.whl 854bd87cc23824d5db4983956bc30f3790e1c7448f1a9e6a8fb7bff7601aef87 scipy-1.2.0-cp36-cp36m-manylinux1_x86_64.whl fc1a19d95649439dbd50baca676bceb29bbfcd600aed2c5bd71d9bad82a87cfe scipy-1.2.0-cp36-cp36m-win32.whl 8f5fcc87b48fc3dd6d901669c89af4feeb856dffb6f671539a238b7e8af1799c scipy-1.2.0-cp36-cp36m-win_amd64.whl bc6a88b0009a1b60eab5c22ac3a006f6968d6328de10c6a64ebb0d64a05548d3 scipy-1.2.0-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 64b2c35824da3ef6bb1e722216e4ef28802af6413c7586136500e343d34ba179 scipy-1.2.0-cp37-cp37m-manylinux1_i686.whl 78a67ee4845440e81cfbfabde20537ca12051d0eeac951fe4c6d8751feac3103 scipy-1.2.0-cp37-cp37m-manylinux1_x86_64.whl 04f2b23258139c109d0524f111597dd095a505d9cb2c71e381d688d653877fa3 scipy-1.2.0-cp37-cp37m-win32.whl 5706b785ca289fdfd91aa05066619e51d140613b613e35932601f2315f5d8470 scipy-1.2.0-cp37-cp37m-win_amd64.whl 51a2424c8ed80e60bdb9a896806e7adaf24a58253b326fbad10f80a6d06f2214 scipy-1.2.0.tar.gz 1cfafc64e1c1c0b6d040d35780ba06f01e9cb44f3bacd8f33a5df6efe5a144a6 scipy-1.2.0.tar.xz 5b3d4b1654b4723431ad7f47b4556498a86a53d2fdb86e85a45c3da0c2a72a4b scipy-1.2.0.zip -----BEGIN PGP SIGNATURE----- iQIzBAEBCAAdFiEEgfAqrOuERrV4fwr6XCLdIy4FKasFAlwYY1YACgkQXCLdIy4F KauihhAAo0fk+a4U4ilFXeZrUTuZTeqqHtD60yV8Z2pZvqQyH1BBP8BKksV/v3bP 6ckl+upWaolMjZgehWhAKyGgE2oUHDu6RxaRS97Kbbns580M+wWduPX7kjf7OKoX KFX1a8/GlBWTQKIMj6P2oShT7rvYB+WABvyoTxXKbHG0/ArOtOqqAYJFKLeOYB6m o0+qajqt9syV2iqBFlHnrPKQ8qjtfPxqCP9KHhNIbHd17305YwJc58CBhpulIjaP HIhJOuP7xigELX9yCzJ2qFGBjTd2HNvBQWIRjNDfbox6mhWO4no30c+OamG3MAr7 n9TDzSIjxkRedvBzMRJwA/Q5/Mou/R16BF+ZzvCVZnp/h6LrXQg4ENfR304Byyy3 NlYzmQKlV0XvP4oYewBnLfq6hcXAum7rf3L8ene8mu0OWJumW7Yr6PWfDNECDKvX sPWSwkNu01Pzg/KUUkrS9w6m9bZTj4UP15L2Z8JSVdp/wxCHGh8txJWjOenoZBnD BPyitzsgbuW+pd7+WmjZoJpr8QjL/Uw8vpUwlvKAvvVfFnVeVh3X1awK+D6iba69 LbyfhOG3R846WkxHh458uvNxmYUbm6sqaZ7lzY91bD8z61jS6PCvpR8BJcwmpP7Y q/duWsaakRWLe35CE8KuvKCgVFhhStX2sZ/hRkNsvm2/hEAtNW0= =3Enc -----END PGP SIGNATURE----- -------------- next part -------------- An HTML attachment was scrubbed... URL: From evgeny.burovskiy at gmail.com Tue Dec 18 14:13:45 2018 From: evgeny.burovskiy at gmail.com (Evgeni Burovski) Date: Tue, 18 Dec 2018 22:13:45 +0300 Subject: [SciPy-Dev] ANN: SciPy 1.2.0 In-Reply-To: References: Message-ID: Thanks Tyler for managing this release! ??, 18 ???. 2018 ?., 19:57 Tyler Reddy : > -----BEGIN PGP SIGNED MESSAGE----- > Hash: SHA256 > > Hi all, > > On behalf of the SciPy development team I'm pleased to announce > the release of SciPy 1.2.0. This is an LTS release and the > last to support Python 2.7. > > Sources and binary wheels can be found at: > https://pypi.org/project/scipy/ > and at: > https://github.com/scipy/scipy/releases/tag/v1.2.0 > > One of a few ways to install this release with pip: > > pip install scipy==1.2.0 > > ========================== > SciPy 1.2.0 Release Notes > ========================== > > SciPy 1.2.0 is the culmination of 6 months of hard work. It contains > many new features, numerous bug-fixes, improved test coverage and better > documentation. There have been a number of deprecations and API changes > in this release, which are documented below. All users are encouraged to > upgrade to this release, as there are a large number of bug-fixes and > optimizations. Before upgrading, we recommend that users check that > their own code does not use deprecated SciPy functionality (to do so, > run your code with ``python -Wd`` and check for ``DeprecationWarning`` s). > Our development attention will now shift to bug-fix releases on the > 1.2.x branch, and on adding new features on the master branch. > > This release requires Python 2.7 or 3.4+ and NumPy 1.8.2 or greater. > > Note: This will be the last SciPy release to support Python 2.7. > Consequently, the 1.2.x series will be a long term support (LTS) > release; we will backport bug fixes until 1 Jan 2020. > > For running on PyPy, PyPy3 6.0+ and NumPy 1.15.0 are required. > > Highlights of this release > --------------------------- > > - 1-D root finding improvements with a new solver, ``toms748``, and a new > unified interface, ``root_scalar`` > - New ``dual_annealing`` optimization method that combines stochastic and > local deterministic searching > - A new optimization algorithm, ``shgo`` (simplicial homology > global optimization) for derivative free optimization problems > - A new category of quaternion-based transformations are available in > `scipy.spatial.transform` > > New features > ============ > > `scipy.ndimage` improvements > --------------------------------- > > Proper spline coefficient calculations have been added for the ``mirror``, > ``wrap``, and ``reflect`` modes of `scipy.ndimage.rotate` > > `scipy.fftpack` improvements > --------------------------------- > > DCT-IV, DST-IV, DCT-I, and DST-I orthonormalization are now supported in > `scipy.fftpack`. > > `scipy.interpolate` improvements > --------------------------------- > > `scipy.interpolate.pade` now accepts a new argument for the order of the > numerator > > `scipy.cluster` improvements > ----------------------------- > > `scipy.cluster.vq.kmeans2` gained a new initialization method, kmeans++. > > `scipy.special` improvements > ----------------------------- > > The function ``softmax`` was added to `scipy.special`. > > `scipy.optimize` improvements > ------------------------------ > > The one-dimensional nonlinear solvers have been given a unified interface > `scipy.optimize.root_scalar`, similar to the `scipy.optimize.root` > interface > for multi-dimensional solvers. ``scipy.optimize.root_scalar(f, bracket=[a > ,b], > method="brenth")`` is equivalent to ``scipy.optimize.brenth(f, a ,b)``. > If no > ``method`` is specified, an appropriate one will be selected based upon the > bracket and the number of derivatives available. > > The so-called Algorithm 748 of Alefeld, Potra and Shi for root-finding > within > an enclosing interval has been added as `scipy.optimize.toms748`. This > provides > guaranteed convergence to a root with convergence rate per function > evaluation > of approximately 1.65 (for sufficiently well-behaved functions.) > > ``differential_evolution`` now has the ``updating`` and ``workers`` > keywords. > The first chooses between continuous updating of the best solution vector > (the > default), or once per generation. Continuous updating can lead to faster > convergence. The ``workers`` keyword accepts an ``int`` or map-like > callable, > and parallelises the solver (having the side effect of updating once per > generation). Supplying an ``int`` evaluates the trial solutions in N > parallel > parts. Supplying a map-like callable allows other parallelisation > approaches > (such as ``mpi4py``, or ``joblib``) to be used. > > ``dual_annealing`` (and ``shgo`` below) is a powerful new general purpose > global optizimation (GO) algorithm. ``dual_annealing`` uses two annealing > processes to accelerate the convergence towards the global minimum of an > objective mathematical function. The first annealing process controls the > stochastic Markov chain searching and the second annealing process > controls the > deterministic minimization. So, dual annealing is a hybrid method that > takes > advantage of stochastic and local deterministic searching in an efficient > way. > > ``shgo`` (simplicial homology global optimization) is a similar algorithm > appropriate for solving black box and derivative free optimization (DFO) > problems. The algorithm generally converges to the global solution in > finite > time. The convergence holds for non-linear inequality and > equality constraints. In addition to returning a global minimum, the > algorithm also returns any other global and local minima found after every > iteration. This makes it useful for exploring the solutions in a domain. > > `scipy.optimize.newton` can now accept a scalar or an array > > ``MINPACK`` usage is now thread-safe, such that ``MINPACK`` + callbacks may > be used on multiple threads. > > `scipy.signal` improvements > ---------------------------- > > Digital filter design functions now include a parameter to specify the > sampling > rate. Previously, digital filters could only be specified using normalized > frequency, but different functions used different scales (e.g. 0 to 1 for > ``butter`` vs 0 to ? for ``freqz``), leading to errors and confusion. With > the ``fs`` parameter, ordinary frequencies can now be entered directly into > functions, with the normalization handled internally. > > ``find_peaks`` and related functions no longer raise an exception if the > properties of a peak have unexpected values (e.g. a prominence of 0). A > ``PeakPropertyWarning`` is given instead. > > The new keyword argument ``plateau_size`` was added to ``find_peaks``. > ``plateau_size`` may be used to select peaks based on the length of the > flat top of a peak. > > ``welch()`` and ``csd()`` methods in `scipy.signal` now support calculation > of a median average PSD, using ``average='mean'`` keyword > > `scipy.sparse` improvements > ---------------------------- > > The `scipy.sparse.bsr_matrix.tocsr` method is now implemented directly > instead > of converting via COO format, and the `scipy.sparse.bsr_matrix.tocsc` > method > is now also routed via CSR conversion instead of COO. The efficiency of > both > conversions is now improved. > > The issue where SuperLU or UMFPACK solvers crashed on matrices with > non-canonical format in `scipy.sparse.linalg` was fixed. The solver wrapper > canonicalizes the matrix if necessary before calling the SuperLU or UMFPACK > solver. > > The ``largest`` option of `scipy.sparse.linalg.lobpcg()` was fixed to have > a correct (and expected) behavior. The order of the eigenvalues was made > consistent with the ARPACK solver (``eigs()``), i.e. ascending for the > smallest eigenvalues, and descending for the largest eigenvalues. > > The `scipy.sparse.random` function is now faster and also supports integer > and > complex values by passing the appropriate value to the ``dtype`` argument. > > `scipy.spatial` improvements > ----------------------------- > > The function `scipy.spatial.distance.jaccard` was modified to return 0 > instead > of ``np.nan`` when two all-zero vectors are compared. > > Support for the Jensen Shannon distance, the square-root of the > divergence, has > been added under `scipy.spatial.distance.jensenshannon` > > An optional keyword was added to the function > `scipy.spatial.cKDTree.query_ball_point()` to sort or not sort the returned > indices. Not sorting the indices can speed up calls. > > A new category of quaternion-based transformations are available in > `scipy.spatial.transform`, including spherical linear interpolation of > rotations (``Slerp``), conversions to and from quaternions, Euler angles, > and general rotation and inversion capabilities > (`spatial.transform.Rotation`), and uniform random sampling of 3D > rotations (`spatial.transform.Rotation.random`). > > `scipy.stats` improvements > --------------------------- > > The Yeo-Johnson power transformation is now supported (``yeojohnson``, > ``yeojohnson_llf``, ``yeojohnson_normmax``, ``yeojohnson_normplot``). > Unlike > the Box-Cox transformation, the Yeo-Johnson transformation can accept > negative > values. > > Added a general method to sample random variates based on the density > only, in > the new function ``rvs_ratio_uniforms``. > > The Yule-Simon distribution (``yulesimon``) was added -- this is a new > discrete probability distribution. > > ``stats`` and ``mstats`` now have access to a new regression method, > ``siegelslopes``, a robust linear regression algorithm > > `scipy.stats.gaussian_kde` now has the ability to deal with weighted > samples, > and should have a modest improvement in performance > > Levy Stable Parameter Estimation, PDF, and CDF calculations are now > supported > for `scipy.stats.levy_stable`. > > The Brunner-Munzel test is now available as ``brunnermunzel`` in ``stats`` > and ``mstats`` > > `scipy.linalg` improvements > --------------------------- > > `scipy.linalg.lapack` now exposes the LAPACK routines using the Rectangular > Full Packed storage (RFP) for upper triangular, lower triangular, > symmetric, > or Hermitian matrices; the upper trapezoidal fat matrix RZ decomposition > routines are now available as well. > > Deprecated features > =================== > The functions ``hyp2f0``, ``hyp1f2`` and ``hyp3f0`` in ``scipy.special`` > have > been deprecated. > > > Backwards incompatible changes > ============================== > > LAPACK version 3.4.0 or later is now required. Building with > Apple Accelerate is no longer supported. > > The function ``scipy.linalg.subspace_angles(A, B)`` now gives correct > results for all angles. Before this, the function only returned > correct values for those angles which were greater than pi/4. > > Support for the Bento build system has been removed. Bento has not been > maintained for several years, and did not have good Python 3 or wheel > support, > hence it was time to remove it. > > The required signature of `scipy.optimize.lingprog` ``method=simplex`` > callback function has changed. Before iteration begins, the simplex solver > first converts the problem into a standard form that does not, in general, > have the same variables or constraints > as the problem defined by the user. Previously, the simplex solver would > pass a > user-specified callback function several separate arguments, such as the > current solution vector ``xk``, corresponding to this standard form > problem. > Unfortunately, the relationship between the standard form problem and the > user-defined problem was not documented, limiting the utility of the > information passed to the callback function. > > In addition to numerous bug fix changes, the simplex solver now passes a > user-specified callback function a single ``OptimizeResult`` object > containing > information that corresponds directly to the user-defined problem. In > future > releases, this ``OptimizeResult`` object may be expanded to include > additional > information, such as variables corresponding to the standard-form problem > and > information concerning the relationship between the standard-form and > user-defined problems. > > The implementation of `scipy.sparse.random` has changed, and this affects > the > numerical values returned for both ``sparse.random`` and ``sparse.rand`` > for > some matrix shapes and a given seed. > > `scipy.optimize.newton` will no longer use Halley's method in cases where > it > negatively impacts convergence > > Other changes > ============= > > > Authors > ======= > > * @endolith > * @luzpaz > * Hameer Abbasi + > * akahard2dj + > * Anton Akhmerov > * Joseph Albert > * alexthomas93 + > * ashish + > * atpage + > * Blair Azzopardi + > * Yoshiki V?zquez Baeza > * Bence Bagi + > * Christoph Baumgarten > * Lucas Bellomo + > * BH4 + > * Aditya Bharti > * Max Bolingbroke > * Fran?ois Boulogne > * Ward Bradt + > * Matthew Brett > * Evgeni Burovski > * Rafa? Byczek + > * Alfredo Canziani + > * CJ Carey > * Luc?a Cheung + > * Poom Chiarawongse + > * Jeanne Choo + > * Robert Cimrman > * Graham Clenaghan + > * cynthia-rempel + > * Johannes Damp + > * Jaime Fernandez del Rio > * Dowon + > * emmi474 + > * Stefan Endres + > * Thomas Etherington + > * Piotr Figiel > * Alex Fikl + > * fo40225 + > * Joseph Fox-Rabinovitz > * Lars G > * Abhinav Gautam + > * Stiaan Gerber + > * C.A.M. Gerlach + > * Ralf Gommers > * Todd Goodall > * Lars Grueter + > * Sylvain Gubian + > * Matt Haberland > * David Hagen > * Will Handley + > * Charles Harris > * Ian Henriksen > * Thomas Hisch + > * Theodore Hu > * Michael Hudson-Doyle + > * Nicolas Hug + > * jakirkham + > * Jakob Jakobson + > * James + > * Jan Schl?ter > * jeanpauphilet + > * josephmernst + > * Kai + > * Kai-Striega + > * kalash04 + > * Toshiki Kataoka + > * Konrad0 + > * Tom Krauss + > * Johannes Kulick > * Lars Gr?ter + > * Eric Larson > * Denis Laxalde > * Will Lee + > * Katrin Leinweber + > * Yin Li + > * P. L. Lim + > * Jesse Livezey + > * Duncan Macleod + > * MatthewFlamm + > * Nikolay Mayorov > * Mike McClurg + > * Christian Meyer + > * Mark Mikofski > * Naoto Mizuno + > * mohmmadd + > * Nathan Musoke > * Anju Geetha Nair + > * Andrew Nelson > * Ayappan P + > * Nick Papior > * Haesun Park + > * Ronny Pfannschmidt + > * pijyoi + > * Ilhan Polat > * Anthony Polloreno + > * Ted Pudlik > * puenka > * Eric Quintero > * Pradeep Reddy Raamana + > * Vyas Ramasubramani + > * Ramon Vi?as + > * Tyler Reddy > * Joscha Reimer > * Antonio H Ribeiro > * richardjgowers + > * Rob + > * robbystk + > * Lucas Roberts + > * rohan + > * Joaquin Derrac Rus + > * Josua Sassen + > * Bruce Sharpe + > * Max Shinn + > * Scott Sievert > * Sourav Singh > * Strahinja Luki? + > * Kai Striega + > * Shinya SUZUKI + > * Mike Toews + > * Piotr Uchwat > * Miguel de Val-Borro + > * Nicky van Foreest > * Paul van Mulbregt > * Gael Varoquaux > * Pauli Virtanen > * Stefan van der Walt > * Warren Weckesser > * Joshua Wharton + > * Bernhard M. Wiedemann + > * Eric Wieser > * Josh Wilson > * Tony Xiang + > * Roman Yurchak + > * Roy Zywina + > > A total of 137 people contributed to this release. > People with a "+" by their names contributed a patch for the first time. > This list of names is automatically generated, and may not be fully > complete. > > Issues closed for 1.2.0 > ------------------------ > > * `#9520 `__: > signal.correlate with method='fft' doesn't benefit from long... > * `#9547 `__: signature of > dual_annealing doesn't match other optimizers > * `#9540 `__: SciPy v1.2.0rc1 > cannot be imported on Python 2.7.15 > * `#1240 `__: Allowing > multithreaded use of minpack through scipy.optimize... > * `#1432 `__: > scipy.stats.mode extremely slow (Trac #905) > * `#3372 `__: Please add > Sphinx search field to online scipy html docs > * `#3678 `__: > _clough_tocher_2d_single direction between centroids > * `#4174 `__: lobpcg > "largest" option invalid? > * `#5493 `__: anderson_ksamp > p-values>1 > * `#5743 `__: slsqp fails to > detect infeasible problem > * `#6139 `__: > scipy.optimize.linprog failed to find a feasible starting point... > * `#6358 `__: stats: > docstring for `vonmises_line` points to `vonmises_line`... > * `#6498 `__: runtests.py is > missing in pypi distfile > * `#7426 `__: > scipy.stats.ksone(n).pdf(x) returns nan for positive values of... > * `#7455 `__: > scipy.stats.ksone.pdf(2,x) return incorrect values for x near... > * `#7456 `__: > scipy.special.smirnov and scipy.special.smirnovi have accuracy... > * `#7492 `__: > scipy.special.kolmogorov(x)/kolmogi(p) inefficient, inaccurate... > * `#7914 `__: TravisCI not > failing when it should for -OO run > * `#8064 `__: linalg.solve > test crashes on Windows > * `#8212 `__: LAPACK > Rectangular Full Packed routines > * `#8256 `__: > differential_evolution bug converges to wrong results in complex... > * `#8443 `__: Deprecate > `hyp2f0`, `hyp1f2`, and `hyp3f0`? > * `#8452 `__: DOC: ARPACK > tutorial has two conflicting equations > * `#8680 `__: scipy fails > compilation when building from source > * `#8686 `__: Division by > zero in _trustregion.py when x0 is exactly equal... > * `#8700 `__: _MINPACK_LOCK > not held when calling into minpack from least_squares > * `#8786 `__: erroneous > moment values for t-distribution > * `#8791 `__: Checking COLA > condition in istft should be optional (or omitted) > * `#8843 `__: imresize cannot > be deprecated just yet > * `#8844 `__: Inverse Wishart > Log PDF Incorrect for Non-diagonal Scale Matrix? > * `#8878 `__: vonmises and > vonmises_line in stats: vonmises wrong and superfluous? > * `#8895 `__: v1.1.0 > `ndi.rotate` documentation ? reused parameters not filled... > * `#8900 `__: Missing complex > conjugation in scipy.sparse.linalg.LinearOperator > * `#8904 `__: BUG: if zero > derivative at root, then Newton fails with RuntimeWarning > * `#8911 `__: > make_interp_spline bc_type incorrect input interpretation > * `#8942 `__: MAINT: Refactor > `_linprog.py` and `_linprog_ip.py` to remove... > * `#8947 `__: np.int64 in > scipy.fftpack.next_fast_len > * `#9020 `__: BUG: > linalg.subspace_angles gives wrong results > * `#9033 `__: > scipy.stats.normaltest sometimes gives incorrect returns b/c... > * `#9036 `__: Bizarre times > for `scipy.sparse.rand` function with 'low' density... > * `#9044 `__: > optimize.minimize(method=`trust-constr`) result dict does not... > * `#9071 `__: doc/linalg: add > cho_solve_banded to see also of cholesky_banded > * `#9082 `__: eigenvalue > sorting in scipy.sparse.linalg.eigsh > * `#9086 `__: > signaltools.py:491: FutureWarning: Using a non-tuple sequence... > * `#9091 `__: > test_spline_filter failure on 32-bit > * `#9122 `__: Typo on scipy > minimization tutorial > * `#9135 `__: doc error at > https://docs.scipy.org/doc/scipy/reference/tutorial/stats/discrete_poisson.html > * `#9167 `__: DOC: BUG: typo > in ndimage LowLevelCallable tutorial example > * `#9169 `__: truncnorm does > not work if b < a in scipy.stats > * `#9250 `__: > scipy.special.tests.test_mpmath::TestSystematic::test_pcfw fails... > * `#9259 `__: rv.expect() == > rv.mean() is false for rv.mean() == nan (and inf) > * `#9286 `__: DOC: Rosenbrock > expression in optimize.minimize tutorial > * `#9316 `__: SLSQP fails in > nested optimization > * `#9337 `__: > scipy.signal.find_peaks key typo in documentation > * `#9345 `__: Example from > documentation of scipy.sparse.linalg.eigs raises... > * `#9383 `__: Default value > for "mode" in "ndimage.shift" > * `#9419 `__: dual_annealing > off by one in the number of iterations > * `#9442 `__: Error in > Defintion of Rosenbrock Function > * `#9453 `__: TST: > test_eigs_consistency() doesn't have consistent results > > > Pull requests for 1.2.0 > ------------------------ > > * `#9526 `__: TST: relax > precision requirements in signal.correlate tests > * `#9507 `__: CI: MAINT: Skip a > ckdtree test on pypy > * `#9512 `__: TST: > test_random_sampling 32-bit handling > * `#9494 `__: TST: > test_kolmogorov xfail 32-bit > * `#9486 `__: BUG: fix sparse > random int handling > * `#9550 `__: BUG: > scipy/_lib/_numpy_compat: get_randint > * `#9549 `__: MAINT: make > dual_annealing signature match other optimizers > * `#9541 `__: BUG: fix > SyntaxError due to non-ascii character on Python 2.7 > * `#7352 `__: ENH: add Brunner > Munzel test to scipy.stats. > * `#7373 `__: BUG: Jaccard > distance for all-zero arrays would return np.nan > * `#7374 `__: ENH: Add PDF, CDF > and parameter estimation for Stable Distributions > * `#8098 `__: ENH: Add shgo for > global optimization of NLPs. > * `#8203 `__: ENH: adding > simulated dual annealing to optimize > * `#8259 `__: Option to follow > original Storn and Price algorithm and its parallelisation > * `#8293 `__: ENH add > ratio-of-uniforms method for rv generation to scipy.stats > * `#8294 `__: BUG: Fix slowness > in stats.mode > * `#8295 `__: ENH: add Jensen > Shannon distance to `scipy.spatial.distance` > * `#8357 `__: ENH: vectorize > scalar zero-search-functions > * `#8397 `__: Add `fs=` > parameter to filter design functions > * `#8537 `__: ENH: Implement > mode parameter for spline filtering. > * `#8558 `__: ENH: small > speedup for stats.gaussian_kde > * `#8560 `__: BUG: fix p-value > calc of anderson_ksamp in scipy.stats > * `#8614 `__: ENH: correct > p-values for stats.kendalltau and stats.mstats.kendalltau > * `#8670 `__: ENH: Require > Lapack 3.4.0 > * `#8683 `__: Correcting kmeans > documentation > * `#8725 `__: MAINT: Cleanup > scipy.optimize.leastsq > * `#8726 `__: BUG: Fix > _get_output in scipy.ndimage to support string > * `#8733 `__: MAINT: stats: A > bit of clean up. > * `#8737 `__: BUG: Improve > numerical precision/convergence failures of smirnov/kolmogorov > * `#8738 `__: MAINT: stats: A > bit of clean up in test_distributions.py. > * `#8740 `__: BF/ENH: make > minpack thread safe > * `#8742 `__: BUG: Fix division > by zero in trust-region optimization methods > * `#8746 `__: MAINT: signal: > Fix a docstring of a private function, and fix... > * `#8750 `__: DOC clarified > description of norminvgauss in scipy.stats > * `#8753 `__: DOC: signal: Fix > a plot title in the chirp docstring. > * `#8755 `__: DOC: MAINT: Fix > link to the wheel documentation in developer... > * `#8760 `__: BUG: stats: > boltzmann wasn't setting the upper bound. > * `#8763 `__: [DOC] Improved > scipy.cluster.hierarchy documentation > * `#8765 `__: DOC: added > example for scipy.stat.mstats.tmin > * `#8788 `__: DOC: fix > definition of optional `disp` parameter > * `#8802 `__: MAINT: Suppress > dd_real unused function compiler warnings. > * `#8803 `__: ENH: Add > full_output support to optimize.newton() > * `#8804 `__: MAINT: stats > cleanup > * `#8808 `__: DOC: add note > about isinstance for frozen rvs > * `#8812 `__: Updated numpydoc > submodule > * `#8813 `__: MAINT: stats: Fix > multinomial docstrings, and do some clean up. > * `#8816 `__: BUG: fixed _stats > of t-distribution in scipy.stats > * `#8817 `__: BUG: ndimage: Fix > validation of the origin argument in correlate... > * `#8822 `__: BUG: integrate: > Fix crash with repeated t values in odeint. > * `#8832 `__: Hyperlink DOIs > against preferred resolver > * `#8837 `__: BUG: sparse: > Ensure correct dtype for sparse comparison operations. > * `#8839 `__: DOC: stats: A few > tweaks to the linregress docstring. > * `#8846 `__: BUG: stats: Fix > logpdf method of invwishart. > * `#8849 `__: DOC: signal: > Fixed mistake in the firwin docstring. > * `#8854 `__: DOC: fix type > descriptors in ltisys documentation > * `#8865 `__: Fix tiny typo in > docs for chi2 pdf > * `#8870 `__: Fixes related to > invertibility of STFT > * `#8872 `__: ENH: special: Add > the softmax function > * `#8874 `__: DOC correct gamma > function in docstrings in scipy.stats > * `#8876 `__: ENH: Added TOMS > Algorithm 748 as 1-d root finder; 17 test function... > * `#8882 `__: ENH: Only use > Halley's adjustment to Newton if close enough. > * `#8883 `__: FIX: optimize: > make jac and hess truly optional for 'trust-constr' > * `#8885 `__: TST: Do not error > on warnings raised about non-tuple indexing. > * `#8887 `__: MAINT: filter out > np.matrix PendingDeprecationWarning's in numpy... > * `#8889 `__: DOC: optimize: > separate legacy interfaces from new ones > * `#8890 `__: ENH: Add > optimize.root_scalar() as a universal dispatcher for... > * `#8899 `__: DCT-IV, DST-IV > and DCT-I, DST-I orthonormalization support in... > * `#8901 `__: MAINT: Reorganize > flapack.pyf.src file > * `#8907 `__: BUG: ENH: Check > if guess for newton is already zero before checking... > * `#8908 `__: ENH: Make sorting > optional for cKDTree.query_ball_point() > * `#8910 `__: DOC: > sparse.csgraph simple examples. > * `#8914 `__: DOC: interpolate: > fix equivalences of string aliases > * `#8918 `__: add > float_control(precise, on) to _fpumode.c > * `#8919 `__: MAINT: > interpolate: improve error messages for common `bc_type`... > * `#8920 `__: DOC: update > Contributing to SciPy to say "prefer no PEP8 only... > * `#8924 `__: MAINT: special: > deprecate `hyp2f0`, `hyp1f2`, and `hyp3f0` > * `#8927 `__: MAINT: special: > remove `errprint` > * `#8932 `__: Fix broadcasting > scale arg of entropy > * `#8936 `__: Fix (some) > non-tuple index warnings > * `#8937 `__: ENH: implement > sparse matrix BSR to CSR conversion directly. > * `#8938 `__: DOC: add > @_ni_docstrings.docfiller in ndimage.rotate > * `#8940 `__: Update > _discrete_distns.py > * `#8943 `__: DOC: Finish > dangling sentence in `convolve` docstring > * `#8944 `__: MAINT: Address > tuple indexing and warnings > * `#8945 `__: ENH: > spatial.transform.Rotation [GSOC2018] > * `#8950 `__: csgraph Dijkstra > function description rewording > * `#8953 `__: DOC, MAINT: HTTP > -> HTTPS, and other linkrot fixes > * `#8955 `__: BUG: np.int64 in > scipy.fftpack.next_fast_len > * `#8958 `__: MAINT: Add more > descriptive error message for phase one simplex. > * `#8962 `__: BUG: > sparse.linalg: add missing conjugate to _ScaledLinearOperator.adjoint > * `#8963 `__: BUG: > sparse.linalg: downgrade LinearOperator TypeError to warning > * `#8965 `__: ENH: Wrapped RFP > format and RZ decomposition routines > * `#8969 `__: MAINT: doc and > code fixes for optimize.newton > * `#8970 `__: Added 'average' > keyword for welch/csd to enable median averaging > * `#8971 `__: Better imresize > deprecation warning > * `#8972 `__: MAINT: Switch > np.where(c) for np.nonzero(c) > * `#8975 `__: MAINT: Fix > warning-based failures > * `#8979 `__: DOC: fix > description of count_sort keyword of dendrogram > * `#8982 `__: MAINT: optimize: > Fixed minor mistakes in test_linprog.py (#8978) > * `#8984 `__: BUG: > sparse.linalg: ensure expm casts integer inputs to float > * `#8986 `__: BUG: > optimize/slsqp: do not exit with convergence on steps where... > * `#8989 `__: MAINT: use > collections.abc in basinhopping > * `#8990 `__: ENH extend > p-values of anderson_ksamp in scipy.stats > * `#8991 `__: ENH: Weighted kde > * `#8993 `__: ENH: > spatial.transform.Rotation.random [GSOC 2018] > * `#8994 `__: ENH: > spatial.transform.Slerp [GSOC 2018] > * `#8995 `__: TST: time.time in > test > * `#9007 `__: Fix typo in > fftpack.rst > * `#9013 `__: Added correct > plotting code for two sided output from spectrogram > * `#9014 `__: BUG: > differential_evolution with inf objective functions > * `#9017 `__: BUG: fixed #8446 > corner case for asformat(array|dense) > * `#9018 `__: MAINT: > _lib/ccallback: remove unused code > * `#9021 `__: BUG: Issue with > subspace_angles > * `#9022 `__: DOC: Added "See > Also" section to lombscargle docstring > * `#9034 `__: BUG: Fix > tolerance printing behavior, remove meaningless tol... > * `#9035 `__: TST: improve > signal.bsplines test coverage > * `#9037 `__: ENH: add a new > init method for k-means > * `#9039 `__: DOC: Add examples > to fftpack.irfft docstrings > * `#9048 `__: ENH: > scipy.sparse.random > * `#9050 `__: BUG: > scipy.io.hb_write: fails for matrices not in csc format > * `#9051 `__: MAINT: Fix slow > sparse.rand for k < mn/3 (#9036). > * `#9054 `__: MAINT: spatial: > Explicitly initialize LAPACK output parameters. > * `#9055 `__: DOC: Add examples > to scipy.special docstrings > * `#9056 `__: ENH: Use one > thread in OpenBLAS > * `#9059 `__: DOC: Update > README with link to Code of Conduct > * `#9060 `__: BLD: remove > support for the Bento build system. > * `#9062 `__: DOC add sections > to overview in scipy.stats > * `#9066 `__: BUG: Correct > "remez" error message > * `#9069 `__: DOC: update > linalg section of roadmap for LAPACK versions. > * `#9079 `__: MAINT: add > spatial.transform to refguide check; complete some... > * `#9081 `__: MAINT: Add > warnings if pivot value is close to tolerance in linprog(method='simplex') > * `#9084 `__: BUG fix incorrect > p-values of kurtosistest in scipy.stats > * `#9095 `__: DOC: add sections > to mstats overview in scipy.stats > * `#9096 `__: BUG: Add test for > Stackoverflow example from issue 8174. > * `#9101 `__: ENH: add Siegel > slopes (robust regression) to scipy.stats > * `#9105 `__: allow > resample_poly() to output float32 for float32 inputs. > * `#9112 `__: MAINT: optimize: > make trust-constr accept constraint dict (#9043) > * `#9118 `__: Add doc entry to > cholesky_banded > * `#9120 `__: eigsh > documentation parameters > * `#9125 `__: interpolative: > correctly reconstruct full rank matrices > * `#9126 `__: MAINT: Use > warnings for unexpected peak properties > * `#9129 `__: BUG: Do not catch > and silence KeyboardInterrupt > * `#9131 `__: DOC: Correct the > typo in scipy.optimize tutorial page > * `#9133 `__: FIX: Avoid use of > bare except > * `#9134 `__: DOC: Update of > 'return_eigenvectors' description > * `#9137 `__: DOC: typo fixes > for discrete Poisson tutorial > * `#9139 `__: FIX: Doctest > failure in optimize tutorial > * `#9143 `__: DOC: missing > sigma in Pearson r formula > * `#9145 `__: MAINT: Refactor > linear programming solvers > * `#9149 `__: FIX: Make > scipy.odr.ODR ifixx equal to its data.fix if given > * `#9156 `__: DOC: special: > Mention the sigmoid function in the expit docstring. > * `#9160 `__: Fixed a latex > delimiter error in levy() > * `#9170 `__: DOC: correction / > update of docstrings of distributions in scipy.stats > * `#9171 `__: better > description of the hierarchical clustering parameter > * `#9174 `__: domain check for > a < b in stats.truncnorm > * `#9175 `__: DOC: Minor > grammar fix > * `#9176 `__: BUG: > CloughTocher2DInterpolator: fix miscalculation at neighborless... > * `#9177 `__: BUILD: Document > the "clean" target in the doc/Makefile. > * `#9178 `__: MAINT: make > refguide-check more robust for printed numpy arrays > * `#9186 `__: MAINT: Remove > np.ediff1d occurence > * `#9188 `__: DOC: correct typo > in extending ndimage with C > * `#9190 `__: ENH: Support > specifying axes for fftconvolve > * `#9192 `__: MAINT: optimize: > fixed @pv style suggestions from #9112 > * `#9200 `__: Fix > make_interp_spline(..., k=0 or 1, axis<0) > * `#9201 `__: BUG: > sparse.linalg/gmres: use machine eps in breakdown check > * `#9204 `__: MAINT: fix up > stats.spearmanr and match mstats.spearmanr with... > * `#9206 `__: MAINT: include > benchmarks and dev files in sdist. > * `#9208 `__: TST: signal: bump > bsplines test tolerance for complex data > * `#9210 `__: TST: mark tests > as slow, fix missing random seed > * `#9211 `__: ENH: add > capability to specify orders in pade func > * `#9217 `__: MAINT: Include > ``success`` and ``nit`` in OptimizeResult returned... > * `#9222 `__: ENH: interpolate: > Use scipy.spatial.distance to speed-up Rbf > * `#9229 `__: MNT: Fix Fourier > filter double case > * `#9233 `__: BUG: > spatial/distance: fix pdist/cdist performance regression... > * `#9234 `__: FIX: Proper > suppression > * `#9235 `__: BENCH: > rationalize slow benchmarks + miscellaneous fixes > * `#9238 `__: BENCH: limit > number of parameter combinations in spatial.*KDTree... > * `#9239 `__: DOC: stats: Fix > LaTeX markup of a couple distribution PDFs. > * `#9241 `__: ENH: Evaluate > plateau size during peak finding > * `#9242 `__: ENH: stats: > Implement _ppf and _logpdf for crystalball, and do... > * `#9246 `__: DOC: Properly > render versionadded directive in HTML documentation > * `#9255 `__: DOC: mention > RootResults in optimization reference guide > * `#9260 `__: TST: relax some > tolerances so tests pass with x87 math > * `#9264 `__: TST Use > assert_raises "match" parameter instead of the "message"... > * `#9267 `__: DOC: clarify > expect() return val when moment is inf/nan > * `#9272 `__: DOC: Add > description of default bounds to linprog > * `#9277 `__: MAINT: > sparse/linalg: make test deterministic > * `#9278 `__: MAINT: > interpolate: pep8 cleanup in test_polyint > * `#9279 `__: Fixed docstring > for resample > * `#9280 `__: removed first > check for float in get_sum_dtype > * `#9281 `__: BUG: only accept > 1d input for bartlett / levene in scipy.stats > * `#9282 `__: MAINT: > dense_output and t_eval are mutually exclusive inputs > * `#9283 `__: MAINT: add docs > and do some cleanups in interpolate.Rbf > * `#9288 `__: Run > distance_transform_edt tests on all types > * `#9294 `__: DOC: fix the > formula typo > * `#9298 `__: MAINT: > optimize/trust-constr: restore .niter attribute for backward-compat > * `#9299 `__: DOC: > clarification of default rvs method in scipy.stats > * `#9301 `__: MAINT: removed > unused import sys > * `#9302 `__: MAINT: removed > unused imports > * `#9303 `__: DOC: signal: > Refer to fs instead of nyq in the firwin docstring. > * `#9305 `__: ENH: Added > Yeo-Johnson power transformation > * `#9306 `__: ENH - add dual > annealing > * `#9309 `__: ENH add the > yulesimon distribution to scipy.stats > * `#9317 `__: Nested SLSQP bug > fix. > * `#9320 `__: MAINT: stats: > avoid underflow in stats.geom.ppf > * `#9326 `__: Add example for > Rosenbrock function > * `#9332 `__: Sort file lists > * `#9340 `__: Fix typo in > find_peaks documentation > * `#9343 `__: MAINT Use np.full > when possible > * `#9344 `__: DOC: added > examples to docstring of dirichlet class > * `#9346 `__: DOC: Fix import > of scipy.sparse.linalg in example (#9345) > * `#9350 `__: Fix interpolate > read only > * `#9351 `__: MAINT: > special.erf: use the x->-x symmetry > * `#9356 `__: Fix documentation > typo > * `#9358 `__: DOC: improve doc > for ksone and kstwobign in scipy.stats > * `#9362 `__: DOC: Change > datatypes of A matrices in linprog > * `#9364 `__: MAINT: Adds > implicit none to fftpack fortran sources > * `#9369 `__: DOC: minor tweak > to CoC (updated NumFOCUS contact address). > * `#9373 `__: Fix exception if > python is called with -OO option > * `#9374 `__: FIX: AIX > compilation issue with NAN and INFINITY > * `#9376 `__: COBLYA -> COBYLA > in docs > * `#9377 `__: DOC: Add examples > integrate: fixed_quad and quadrature > * `#9379 `__: MAINT: TST: Make > tests NumPy 1.8 compatible > * `#9385 `__: CI: On Travis > matrix "OPTIMIZE=-OO" flag ignored > * `#9387 `__: Fix defaut value > for 'mode' in 'ndimage.shift' in the doc > * `#9392 `__: BUG: rank has to > be integer in rank_filter: fixed issue 9388 > * `#9399 `__: DOC: Misc. typos > * `#9400 `__: TST: stats: Fix > the expected r-value of a linregress test. > * `#9405 `__: BUG: np.hstack > does not accept generator expressions > * `#9408 `__: ENH: linalg: > Shorter ill-conditioned warning message > * `#9418 `__: DOC: Fix ndimage > docstrings and reduce doc build warnings > * `#9421 `__: DOC: Add missing > docstring examples in scipy.spatial > * `#9422 `__: DOC: Add an > example to integrate.newton_cotes > * `#9427 `__: BUG: Fixed defect > with maxiter #9419 in dual annealing > * `#9431 `__: BENCH: Add dual > annealing to scipy benchmark (see #9415) > * `#9435 `__: DOC: Add > docstring examples for stats.binom_test > * `#9443 `__: DOC: Fix the > order of indices in optimize tutorial > * `#9444 `__: MAINT: > interpolate: use operator.index for checking/coercing... > * `#9445 `__: DOC: Added > missing example to stats.mstats.kruskal > * `#9446 `__: DOC: Add note > about version changed for jaccard distance > * `#9447 `__: BLD: > version-script handling in setup.py > * `#9448 `__: TST: skip a > problematic linalg test > * `#9449 `__: TST: fix missing > seed in lobpcg test. > * `#9456 `__: TST: > test_eigs_consistency() now sorts output > > Checksums > ========= > > MD5 > ~~~ > > 0bb53a49e77bca11fb26698744c60f97 > scipy-1.2.0-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 39e215ac7e8d6de33d939486987dcba4 > scipy-1.2.0-cp27-cp27m-manylinux1_i686.whl > d6e33b2c05ffbcf9790628d656c8e61f > scipy-1.2.0-cp27-cp27m-manylinux1_x86_64.whl > a463a12d77b87df0a2d202323771a908 scipy-1.2.0-cp27-cp27m-win32.whl > 3dc17a11c7dd211ce51a338cfe30eb48 scipy-1.2.0-cp27-cp27m-win_amd64.whl > 82b1ecbecadfeddd2be1c6d616491029 > scipy-1.2.0-cp27-cp27mu-manylinux1_i686.whl > 65021ade783f1416b1920d2a2cc39d4d > scipy-1.2.0-cp27-cp27mu-manylinux1_x86_64.whl > 7cc2cdbc9b421ef10695b898cdc241e7 > scipy-1.2.0-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 2a4ccbfcccb9395fa7554a82db40e454 > scipy-1.2.0-cp34-cp34m-manylinux1_i686.whl > 662dc35acd6f588565cd6467465fc742 > scipy-1.2.0-cp34-cp34m-manylinux1_x86_64.whl > a19bd9969bb5b92595e82d924b8272f9 scipy-1.2.0-cp34-cp34m-win32.whl > 5f1eaa3745956db0da724f83dd174559 scipy-1.2.0-cp34-cp34m-win_amd64.whl > d32a4c31d0a188f3550c1306d20b03c7 > scipy-1.2.0-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 34f4a7f04abfda87fac8ab38a9a70a77 > scipy-1.2.0-cp35-cp35m-manylinux1_i686.whl > bd4d56910802870072e3c5ded69a8f08 > scipy-1.2.0-cp35-cp35m-manylinux1_x86_64.whl > cb3fb7ddd3992928f9173e4eb489d23e scipy-1.2.0-cp35-cp35m-win32.whl > 68f5ddcb6e592b1d9cba95f24faee7b5 scipy-1.2.0-cp35-cp35m-win_amd64.whl > c0e110f3a935731782c96a13cc264ea2 > scipy-1.2.0-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 9d898924498abbe2d26dd18b3413fb11 > scipy-1.2.0-cp36-cp36m-manylinux1_i686.whl > dd9ae664cbe7de54828d83c772e24da3 > scipy-1.2.0-cp36-cp36m-manylinux1_x86_64.whl > 8dea8432610bb3c63114eb6469c5f99a scipy-1.2.0-cp36-cp36m-win32.whl > ebda830aec7b60193772741f85fee28c scipy-1.2.0-cp36-cp36m-win_amd64.whl > 0e8b7a7908c50e635e639d2c69901140 > scipy-1.2.0-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 56719437a821f9f2f98f069225e70c87 > scipy-1.2.0-cp37-cp37m-manylinux1_i686.whl > 93d9d978855516ec38fa08620ef3443c > scipy-1.2.0-cp37-cp37m-manylinux1_x86_64.whl > fff3d66b877b6e6b9984b84ae9e4d76c scipy-1.2.0-cp37-cp37m-win32.whl > 3defb2c8b2f69057919ee3b0c92de65c scipy-1.2.0-cp37-cp37m-win_amd64.whl > e57011507865b0b702aff6077d412e03 scipy-1.2.0.tar.gz > 8eb6c1d7ceae0d06aef474f7801b8fca scipy-1.2.0.tar.xz > b0fb16b09319d3031d27ccf21a3ef474 scipy-1.2.0.zip > > SHA256 > ~~~~~~ > > d1ae77b79fd5e27a10ba7c4e7c3a62927b9d29a4dccf28f6905c25d983aaf183 > scipy-1.2.0-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 4b1f0883cb9d8ee963cf0a31c87341e9e758abb2cf1e5bcc0d7b066ef6b17573 > scipy-1.2.0-cp27-cp27m-manylinux1_i686.whl > c5eae911cf26b3c7eda889ec98d3c226f312c587acfaaf02602473f98b4c16d6 > scipy-1.2.0-cp27-cp27m-manylinux1_x86_64.whl > 58f0435f052cb60f1472c77f52a8f6642f8877b70559e5e0b9a1744f33f5cbe5 > scipy-1.2.0-cp27-cp27m-win32.whl > 4cce25c6e7ff7399c67dfe1b5423c36c391cf9b4b2be390c1675ab410f1ef503 > scipy-1.2.0-cp27-cp27m-win_amd64.whl > 02cb79ea38114dc480e9b08d6b87095728e8fb39b9a49b449ee443d678001611 > scipy-1.2.0-cp27-cp27mu-manylinux1_i686.whl > 7dc4002f0a0a688774ef04878afe769ecd1ac21fe9b4b1d7125e2cf16170afd3 > scipy-1.2.0-cp27-cp27mu-manylinux1_x86_64.whl > 7994c044bf659b0a24ad7673ec7db85c2fadb87e4980a379a9fd5b086fe3649a > scipy-1.2.0-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 72bd766f753fd32f072d30d7bc2ad492d56dbcbf3e13764e27635d5c41079339 > scipy-1.2.0-cp34-cp34m-manylinux1_i686.whl > 3132a9fab3f3545c8b0ba15688d11857efdd4a58d388d3785dc474f56fea7138 > scipy-1.2.0-cp34-cp34m-manylinux1_x86_64.whl > 7413080b381766a22d52814edb65631f0e323a7cea945c70021a672f38acc73f > scipy-1.2.0-cp34-cp34m-win32.whl > 6f791987899532305126309578727c0197bddbafab9596bafe3e7bfab6e1ce13 > scipy-1.2.0-cp34-cp34m-win_amd64.whl > 937147086e8b4338bf139ca8fa98da650e3a46bf2ca617f8e9dd68c3971ec420 > scipy-1.2.0-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 63e1d5ca9e5e1984f1a275276991b036e25d39d37dd7edbb3f4f6165c2da7dbb > scipy-1.2.0-cp35-cp35m-manylinux1_i686.whl > 03c827cdbc584e935264040b958e5fa0570a16095bee23a013482ba3f0e963a2 > scipy-1.2.0-cp35-cp35m-manylinux1_x86_64.whl > bc294841f6c822714af362095b181a853f47ed5ce757354bd2e4776d579ff3a4 > scipy-1.2.0-cp35-cp35m-win32.whl > cca33a01a5987c650b87a1a910aa311ffa44e67cca1ff502ef9efdae5d9a8624 > scipy-1.2.0-cp35-cp35m-win_amd64.whl > 8608316d0cc01f8b25111c8adfe6efbc959cbba037a62c784551568d7ffbf280 > scipy-1.2.0-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > fb36064047e6bf87b6320a9b6eb7f525ef6863c7a4aef1a84a4bbfb043612617 > scipy-1.2.0-cp36-cp36m-manylinux1_i686.whl > 854bd87cc23824d5db4983956bc30f3790e1c7448f1a9e6a8fb7bff7601aef87 > scipy-1.2.0-cp36-cp36m-manylinux1_x86_64.whl > fc1a19d95649439dbd50baca676bceb29bbfcd600aed2c5bd71d9bad82a87cfe > scipy-1.2.0-cp36-cp36m-win32.whl > 8f5fcc87b48fc3dd6d901669c89af4feeb856dffb6f671539a238b7e8af1799c > scipy-1.2.0-cp36-cp36m-win_amd64.whl > bc6a88b0009a1b60eab5c22ac3a006f6968d6328de10c6a64ebb0d64a05548d3 > scipy-1.2.0-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 64b2c35824da3ef6bb1e722216e4ef28802af6413c7586136500e343d34ba179 > scipy-1.2.0-cp37-cp37m-manylinux1_i686.whl > 78a67ee4845440e81cfbfabde20537ca12051d0eeac951fe4c6d8751feac3103 > scipy-1.2.0-cp37-cp37m-manylinux1_x86_64.whl > 04f2b23258139c109d0524f111597dd095a505d9cb2c71e381d688d653877fa3 > scipy-1.2.0-cp37-cp37m-win32.whl > 5706b785ca289fdfd91aa05066619e51d140613b613e35932601f2315f5d8470 > scipy-1.2.0-cp37-cp37m-win_amd64.whl > 51a2424c8ed80e60bdb9a896806e7adaf24a58253b326fbad10f80a6d06f2214 > scipy-1.2.0.tar.gz > 1cfafc64e1c1c0b6d040d35780ba06f01e9cb44f3bacd8f33a5df6efe5a144a6 > scipy-1.2.0.tar.xz > 5b3d4b1654b4723431ad7f47b4556498a86a53d2fdb86e85a45c3da0c2a72a4b > scipy-1.2.0.zip > -----BEGIN PGP SIGNATURE----- > > iQIzBAEBCAAdFiEEgfAqrOuERrV4fwr6XCLdIy4FKasFAlwYY1YACgkQXCLdIy4F > KauihhAAo0fk+a4U4ilFXeZrUTuZTeqqHtD60yV8Z2pZvqQyH1BBP8BKksV/v3bP > 6ckl+upWaolMjZgehWhAKyGgE2oUHDu6RxaRS97Kbbns580M+wWduPX7kjf7OKoX > KFX1a8/GlBWTQKIMj6P2oShT7rvYB+WABvyoTxXKbHG0/ArOtOqqAYJFKLeOYB6m > o0+qajqt9syV2iqBFlHnrPKQ8qjtfPxqCP9KHhNIbHd17305YwJc58CBhpulIjaP > HIhJOuP7xigELX9yCzJ2qFGBjTd2HNvBQWIRjNDfbox6mhWO4no30c+OamG3MAr7 > n9TDzSIjxkRedvBzMRJwA/Q5/Mou/R16BF+ZzvCVZnp/h6LrXQg4ENfR304Byyy3 > NlYzmQKlV0XvP4oYewBnLfq6hcXAum7rf3L8ene8mu0OWJumW7Yr6PWfDNECDKvX > sPWSwkNu01Pzg/KUUkrS9w6m9bZTj4UP15L2Z8JSVdp/wxCHGh8txJWjOenoZBnD > BPyitzsgbuW+pd7+WmjZoJpr8QjL/Uw8vpUwlvKAvvVfFnVeVh3X1awK+D6iba69 > LbyfhOG3R846WkxHh458uvNxmYUbm6sqaZ7lzY91bD8z61jS6PCvpR8BJcwmpP7Y > q/duWsaakRWLe35CE8KuvKCgVFhhStX2sZ/hRkNsvm2/hEAtNW0= > =3Enc > -----END PGP SIGNATURE----- > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > -------------- next part -------------- An HTML attachment was scrubbed... URL: From mikofski at berkeley.edu Tue Dec 18 14:49:30 2018 From: mikofski at berkeley.edu (Mark Alexander Mikofski) Date: Tue, 18 Dec 2018 11:49:30 -0800 Subject: [SciPy-Dev] ANN: SciPy 1.2.0 In-Reply-To: References: Message-ID: Yay! Congratulations and thanks Tyler and all other contributors for your hard work! On Tue, Dec 18, 2018, 8:58 AM Tyler Reddy -----BEGIN PGP SIGNED MESSAGE----- > Hash: SHA256 > > Hi all, > > On behalf of the SciPy development team I'm pleased to announce > the release of SciPy 1.2.0. This is an LTS release and the > last to support Python 2.7. > > Sources and binary wheels can be found at: > https://pypi.org/project/scipy/ > and at: > https://github.com/scipy/scipy/releases/tag/v1.2.0 > > One of a few ways to install this release with pip: > > pip install scipy==1.2.0 > > ========================== > SciPy 1.2.0 Release Notes > ========================== > > SciPy 1.2.0 is the culmination of 6 months of hard work. It contains > many new features, numerous bug-fixes, improved test coverage and better > documentation. There have been a number of deprecations and API changes > in this release, which are documented below. All users are encouraged to > upgrade to this release, as there are a large number of bug-fixes and > optimizations. Before upgrading, we recommend that users check that > their own code does not use deprecated SciPy functionality (to do so, > run your code with ``python -Wd`` and check for ``DeprecationWarning`` s). > Our development attention will now shift to bug-fix releases on the > 1.2.x branch, and on adding new features on the master branch. > > This release requires Python 2.7 or 3.4+ and NumPy 1.8.2 or greater. > > Note: This will be the last SciPy release to support Python 2.7. > Consequently, the 1.2.x series will be a long term support (LTS) > release; we will backport bug fixes until 1 Jan 2020. > > For running on PyPy, PyPy3 6.0+ and NumPy 1.15.0 are required. > > Highlights of this release > --------------------------- > > - 1-D root finding improvements with a new solver, ``toms748``, and a new > unified interface, ``root_scalar`` > - New ``dual_annealing`` optimization method that combines stochastic and > local deterministic searching > - A new optimization algorithm, ``shgo`` (simplicial homology > global optimization) for derivative free optimization problems > - A new category of quaternion-based transformations are available in > `scipy.spatial.transform` > > New features > ============ > > `scipy.ndimage` improvements > --------------------------------- > > Proper spline coefficient calculations have been added for the ``mirror``, > ``wrap``, and ``reflect`` modes of `scipy.ndimage.rotate` > > `scipy.fftpack` improvements > --------------------------------- > > DCT-IV, DST-IV, DCT-I, and DST-I orthonormalization are now supported in > `scipy.fftpack`. > > `scipy.interpolate` improvements > --------------------------------- > > `scipy.interpolate.pade` now accepts a new argument for the order of the > numerator > > `scipy.cluster` improvements > ----------------------------- > > `scipy.cluster.vq.kmeans2` gained a new initialization method, kmeans++. > > `scipy.special` improvements > ----------------------------- > > The function ``softmax`` was added to `scipy.special`. > > `scipy.optimize` improvements > ------------------------------ > > The one-dimensional nonlinear solvers have been given a unified interface > `scipy.optimize.root_scalar`, similar to the `scipy.optimize.root` > interface > for multi-dimensional solvers. ``scipy.optimize.root_scalar(f, bracket=[a > ,b], > method="brenth")`` is equivalent to ``scipy.optimize.brenth(f, a ,b)``. > If no > ``method`` is specified, an appropriate one will be selected based upon the > bracket and the number of derivatives available. > > The so-called Algorithm 748 of Alefeld, Potra and Shi for root-finding > within > an enclosing interval has been added as `scipy.optimize.toms748`. This > provides > guaranteed convergence to a root with convergence rate per function > evaluation > of approximately 1.65 (for sufficiently well-behaved functions.) > > ``differential_evolution`` now has the ``updating`` and ``workers`` > keywords. > The first chooses between continuous updating of the best solution vector > (the > default), or once per generation. Continuous updating can lead to faster > convergence. The ``workers`` keyword accepts an ``int`` or map-like > callable, > and parallelises the solver (having the side effect of updating once per > generation). Supplying an ``int`` evaluates the trial solutions in N > parallel > parts. Supplying a map-like callable allows other parallelisation > approaches > (such as ``mpi4py``, or ``joblib``) to be used. > > ``dual_annealing`` (and ``shgo`` below) is a powerful new general purpose > global optizimation (GO) algorithm. ``dual_annealing`` uses two annealing > processes to accelerate the convergence towards the global minimum of an > objective mathematical function. The first annealing process controls the > stochastic Markov chain searching and the second annealing process > controls the > deterministic minimization. So, dual annealing is a hybrid method that > takes > advantage of stochastic and local deterministic searching in an efficient > way. > > ``shgo`` (simplicial homology global optimization) is a similar algorithm > appropriate for solving black box and derivative free optimization (DFO) > problems. The algorithm generally converges to the global solution in > finite > time. The convergence holds for non-linear inequality and > equality constraints. In addition to returning a global minimum, the > algorithm also returns any other global and local minima found after every > iteration. This makes it useful for exploring the solutions in a domain. > > `scipy.optimize.newton` can now accept a scalar or an array > > ``MINPACK`` usage is now thread-safe, such that ``MINPACK`` + callbacks may > be used on multiple threads. > > `scipy.signal` improvements > ---------------------------- > > Digital filter design functions now include a parameter to specify the > sampling > rate. Previously, digital filters could only be specified using normalized > frequency, but different functions used different scales (e.g. 0 to 1 for > ``butter`` vs 0 to ? for ``freqz``), leading to errors and confusion. With > the ``fs`` parameter, ordinary frequencies can now be entered directly into > functions, with the normalization handled internally. > > ``find_peaks`` and related functions no longer raise an exception if the > properties of a peak have unexpected values (e.g. a prominence of 0). A > ``PeakPropertyWarning`` is given instead. > > The new keyword argument ``plateau_size`` was added to ``find_peaks``. > ``plateau_size`` may be used to select peaks based on the length of the > flat top of a peak. > > ``welch()`` and ``csd()`` methods in `scipy.signal` now support calculation > of a median average PSD, using ``average='mean'`` keyword > > `scipy.sparse` improvements > ---------------------------- > > The `scipy.sparse.bsr_matrix.tocsr` method is now implemented directly > instead > of converting via COO format, and the `scipy.sparse.bsr_matrix.tocsc` > method > is now also routed via CSR conversion instead of COO. The efficiency of > both > conversions is now improved. > > The issue where SuperLU or UMFPACK solvers crashed on matrices with > non-canonical format in `scipy.sparse.linalg` was fixed. The solver wrapper > canonicalizes the matrix if necessary before calling the SuperLU or UMFPACK > solver. > > The ``largest`` option of `scipy.sparse.linalg.lobpcg()` was fixed to have > a correct (and expected) behavior. The order of the eigenvalues was made > consistent with the ARPACK solver (``eigs()``), i.e. ascending for the > smallest eigenvalues, and descending for the largest eigenvalues. > > The `scipy.sparse.random` function is now faster and also supports integer > and > complex values by passing the appropriate value to the ``dtype`` argument. > > `scipy.spatial` improvements > ----------------------------- > > The function `scipy.spatial.distance.jaccard` was modified to return 0 > instead > of ``np.nan`` when two all-zero vectors are compared. > > Support for the Jensen Shannon distance, the square-root of the > divergence, has > been added under `scipy.spatial.distance.jensenshannon` > > An optional keyword was added to the function > `scipy.spatial.cKDTree.query_ball_point()` to sort or not sort the returned > indices. Not sorting the indices can speed up calls. > > A new category of quaternion-based transformations are available in > `scipy.spatial.transform`, including spherical linear interpolation of > rotations (``Slerp``), conversions to and from quaternions, Euler angles, > and general rotation and inversion capabilities > (`spatial.transform.Rotation`), and uniform random sampling of 3D > rotations (`spatial.transform.Rotation.random`). > > `scipy.stats` improvements > --------------------------- > > The Yeo-Johnson power transformation is now supported (``yeojohnson``, > ``yeojohnson_llf``, ``yeojohnson_normmax``, ``yeojohnson_normplot``). > Unlike > the Box-Cox transformation, the Yeo-Johnson transformation can accept > negative > values. > > Added a general method to sample random variates based on the density > only, in > the new function ``rvs_ratio_uniforms``. > > The Yule-Simon distribution (``yulesimon``) was added -- this is a new > discrete probability distribution. > > ``stats`` and ``mstats`` now have access to a new regression method, > ``siegelslopes``, a robust linear regression algorithm > > `scipy.stats.gaussian_kde` now has the ability to deal with weighted > samples, > and should have a modest improvement in performance > > Levy Stable Parameter Estimation, PDF, and CDF calculations are now > supported > for `scipy.stats.levy_stable`. > > The Brunner-Munzel test is now available as ``brunnermunzel`` in ``stats`` > and ``mstats`` > > `scipy.linalg` improvements > --------------------------- > > `scipy.linalg.lapack` now exposes the LAPACK routines using the Rectangular > Full Packed storage (RFP) for upper triangular, lower triangular, > symmetric, > or Hermitian matrices; the upper trapezoidal fat matrix RZ decomposition > routines are now available as well. > > Deprecated features > =================== > The functions ``hyp2f0``, ``hyp1f2`` and ``hyp3f0`` in ``scipy.special`` > have > been deprecated. > > > Backwards incompatible changes > ============================== > > LAPACK version 3.4.0 or later is now required. Building with > Apple Accelerate is no longer supported. > > The function ``scipy.linalg.subspace_angles(A, B)`` now gives correct > results for all angles. Before this, the function only returned > correct values for those angles which were greater than pi/4. > > Support for the Bento build system has been removed. Bento has not been > maintained for several years, and did not have good Python 3 or wheel > support, > hence it was time to remove it. > > The required signature of `scipy.optimize.lingprog` ``method=simplex`` > callback function has changed. Before iteration begins, the simplex solver > first converts the problem into a standard form that does not, in general, > have the same variables or constraints > as the problem defined by the user. Previously, the simplex solver would > pass a > user-specified callback function several separate arguments, such as the > current solution vector ``xk``, corresponding to this standard form > problem. > Unfortunately, the relationship between the standard form problem and the > user-defined problem was not documented, limiting the utility of the > information passed to the callback function. > > In addition to numerous bug fix changes, the simplex solver now passes a > user-specified callback function a single ``OptimizeResult`` object > containing > information that corresponds directly to the user-defined problem. In > future > releases, this ``OptimizeResult`` object may be expanded to include > additional > information, such as variables corresponding to the standard-form problem > and > information concerning the relationship between the standard-form and > user-defined problems. > > The implementation of `scipy.sparse.random` has changed, and this affects > the > numerical values returned for both ``sparse.random`` and ``sparse.rand`` > for > some matrix shapes and a given seed. > > `scipy.optimize.newton` will no longer use Halley's method in cases where > it > negatively impacts convergence > > Other changes > ============= > > > Authors > ======= > > * @endolith > * @luzpaz > * Hameer Abbasi + > * akahard2dj + > * Anton Akhmerov > * Joseph Albert > * alexthomas93 + > * ashish + > * atpage + > * Blair Azzopardi + > * Yoshiki V?zquez Baeza > * Bence Bagi + > * Christoph Baumgarten > * Lucas Bellomo + > * BH4 + > * Aditya Bharti > * Max Bolingbroke > * Fran?ois Boulogne > * Ward Bradt + > * Matthew Brett > * Evgeni Burovski > * Rafa? Byczek + > * Alfredo Canziani + > * CJ Carey > * Luc?a Cheung + > * Poom Chiarawongse + > * Jeanne Choo + > * Robert Cimrman > * Graham Clenaghan + > * cynthia-rempel + > * Johannes Damp + > * Jaime Fernandez del Rio > * Dowon + > * emmi474 + > * Stefan Endres + > * Thomas Etherington + > * Piotr Figiel > * Alex Fikl + > * fo40225 + > * Joseph Fox-Rabinovitz > * Lars G > * Abhinav Gautam + > * Stiaan Gerber + > * C.A.M. Gerlach + > * Ralf Gommers > * Todd Goodall > * Lars Grueter + > * Sylvain Gubian + > * Matt Haberland > * David Hagen > * Will Handley + > * Charles Harris > * Ian Henriksen > * Thomas Hisch + > * Theodore Hu > * Michael Hudson-Doyle + > * Nicolas Hug + > * jakirkham + > * Jakob Jakobson + > * James + > * Jan Schl?ter > * jeanpauphilet + > * josephmernst + > * Kai + > * Kai-Striega + > * kalash04 + > * Toshiki Kataoka + > * Konrad0 + > * Tom Krauss + > * Johannes Kulick > * Lars Gr?ter + > * Eric Larson > * Denis Laxalde > * Will Lee + > * Katrin Leinweber + > * Yin Li + > * P. L. Lim + > * Jesse Livezey + > * Duncan Macleod + > * MatthewFlamm + > * Nikolay Mayorov > * Mike McClurg + > * Christian Meyer + > * Mark Mikofski > * Naoto Mizuno + > * mohmmadd + > * Nathan Musoke > * Anju Geetha Nair + > * Andrew Nelson > * Ayappan P + > * Nick Papior > * Haesun Park + > * Ronny Pfannschmidt + > * pijyoi + > * Ilhan Polat > * Anthony Polloreno + > * Ted Pudlik > * puenka > * Eric Quintero > * Pradeep Reddy Raamana + > * Vyas Ramasubramani + > * Ramon Vi?as + > * Tyler Reddy > * Joscha Reimer > * Antonio H Ribeiro > * richardjgowers + > * Rob + > * robbystk + > * Lucas Roberts + > * rohan + > * Joaquin Derrac Rus + > * Josua Sassen + > * Bruce Sharpe + > * Max Shinn + > * Scott Sievert > * Sourav Singh > * Strahinja Luki? + > * Kai Striega + > * Shinya SUZUKI + > * Mike Toews + > * Piotr Uchwat > * Miguel de Val-Borro + > * Nicky van Foreest > * Paul van Mulbregt > * Gael Varoquaux > * Pauli Virtanen > * Stefan van der Walt > * Warren Weckesser > * Joshua Wharton + > * Bernhard M. Wiedemann + > * Eric Wieser > * Josh Wilson > * Tony Xiang + > * Roman Yurchak + > * Roy Zywina + > > A total of 137 people contributed to this release. > People with a "+" by their names contributed a patch for the first time. > This list of names is automatically generated, and may not be fully > complete. > > Issues closed for 1.2.0 > ------------------------ > > * `#9520 `__: > signal.correlate with method='fft' doesn't benefit from long... > * `#9547 `__: signature of > dual_annealing doesn't match other optimizers > * `#9540 `__: SciPy v1.2.0rc1 > cannot be imported on Python 2.7.15 > * `#1240 `__: Allowing > multithreaded use of minpack through scipy.optimize... > * `#1432 `__: > scipy.stats.mode extremely slow (Trac #905) > * `#3372 `__: Please add > Sphinx search field to online scipy html docs > * `#3678 `__: > _clough_tocher_2d_single direction between centroids > * `#4174 `__: lobpcg > "largest" option invalid? > * `#5493 `__: anderson_ksamp > p-values>1 > * `#5743 `__: slsqp fails to > detect infeasible problem > * `#6139 `__: > scipy.optimize.linprog failed to find a feasible starting point... > * `#6358 `__: stats: > docstring for `vonmises_line` points to `vonmises_line`... > * `#6498 `__: runtests.py is > missing in pypi distfile > * `#7426 `__: > scipy.stats.ksone(n).pdf(x) returns nan for positive values of... > * `#7455 `__: > scipy.stats.ksone.pdf(2,x) return incorrect values for x near... > * `#7456 `__: > scipy.special.smirnov and scipy.special.smirnovi have accuracy... > * `#7492 `__: > scipy.special.kolmogorov(x)/kolmogi(p) inefficient, inaccurate... > * `#7914 `__: TravisCI not > failing when it should for -OO run > * `#8064 `__: linalg.solve > test crashes on Windows > * `#8212 `__: LAPACK > Rectangular Full Packed routines > * `#8256 `__: > differential_evolution bug converges to wrong results in complex... > * `#8443 `__: Deprecate > `hyp2f0`, `hyp1f2`, and `hyp3f0`? > * `#8452 `__: DOC: ARPACK > tutorial has two conflicting equations > * `#8680 `__: scipy fails > compilation when building from source > * `#8686 `__: Division by > zero in _trustregion.py when x0 is exactly equal... > * `#8700 `__: _MINPACK_LOCK > not held when calling into minpack from least_squares > * `#8786 `__: erroneous > moment values for t-distribution > * `#8791 `__: Checking COLA > condition in istft should be optional (or omitted) > * `#8843 `__: imresize cannot > be deprecated just yet > * `#8844 `__: Inverse Wishart > Log PDF Incorrect for Non-diagonal Scale Matrix? > * `#8878 `__: vonmises and > vonmises_line in stats: vonmises wrong and superfluous? > * `#8895 `__: v1.1.0 > `ndi.rotate` documentation ? reused parameters not filled... > * `#8900 `__: Missing complex > conjugation in scipy.sparse.linalg.LinearOperator > * `#8904 `__: BUG: if zero > derivative at root, then Newton fails with RuntimeWarning > * `#8911 `__: > make_interp_spline bc_type incorrect input interpretation > * `#8942 `__: MAINT: Refactor > `_linprog.py` and `_linprog_ip.py` to remove... > * `#8947 `__: np.int64 in > scipy.fftpack.next_fast_len > * `#9020 `__: BUG: > linalg.subspace_angles gives wrong results > * `#9033 `__: > scipy.stats.normaltest sometimes gives incorrect returns b/c... > * `#9036 `__: Bizarre times > for `scipy.sparse.rand` function with 'low' density... > * `#9044 `__: > optimize.minimize(method=`trust-constr`) result dict does not... > * `#9071 `__: doc/linalg: add > cho_solve_banded to see also of cholesky_banded > * `#9082 `__: eigenvalue > sorting in scipy.sparse.linalg.eigsh > * `#9086 `__: > signaltools.py:491: FutureWarning: Using a non-tuple sequence... > * `#9091 `__: > test_spline_filter failure on 32-bit > * `#9122 `__: Typo on scipy > minimization tutorial > * `#9135 `__: doc error at > https://docs.scipy.org/doc/scipy/reference/tutorial/stats/discrete_poisson.html > * `#9167 `__: DOC: BUG: typo > in ndimage LowLevelCallable tutorial example > * `#9169 `__: truncnorm does > not work if b < a in scipy.stats > * `#9250 `__: > scipy.special.tests.test_mpmath::TestSystematic::test_pcfw fails... > * `#9259 `__: rv.expect() == > rv.mean() is false for rv.mean() == nan (and inf) > * `#9286 `__: DOC: Rosenbrock > expression in optimize.minimize tutorial > * `#9316 `__: SLSQP fails in > nested optimization > * `#9337 `__: > scipy.signal.find_peaks key typo in documentation > * `#9345 `__: Example from > documentation of scipy.sparse.linalg.eigs raises... > * `#9383 `__: Default value > for "mode" in "ndimage.shift" > * `#9419 `__: dual_annealing > off by one in the number of iterations > * `#9442 `__: Error in > Defintion of Rosenbrock Function > * `#9453 `__: TST: > test_eigs_consistency() doesn't have consistent results > > > Pull requests for 1.2.0 > ------------------------ > > * `#9526 `__: TST: relax > precision requirements in signal.correlate tests > * `#9507 `__: CI: MAINT: Skip a > ckdtree test on pypy > * `#9512 `__: TST: > test_random_sampling 32-bit handling > * `#9494 `__: TST: > test_kolmogorov xfail 32-bit > * `#9486 `__: BUG: fix sparse > random int handling > * `#9550 `__: BUG: > scipy/_lib/_numpy_compat: get_randint > * `#9549 `__: MAINT: make > dual_annealing signature match other optimizers > * `#9541 `__: BUG: fix > SyntaxError due to non-ascii character on Python 2.7 > * `#7352 `__: ENH: add Brunner > Munzel test to scipy.stats. > * `#7373 `__: BUG: Jaccard > distance for all-zero arrays would return np.nan > * `#7374 `__: ENH: Add PDF, CDF > and parameter estimation for Stable Distributions > * `#8098 `__: ENH: Add shgo for > global optimization of NLPs. > * `#8203 `__: ENH: adding > simulated dual annealing to optimize > * `#8259 `__: Option to follow > original Storn and Price algorithm and its parallelisation > * `#8293 `__: ENH add > ratio-of-uniforms method for rv generation to scipy.stats > * `#8294 `__: BUG: Fix slowness > in stats.mode > * `#8295 `__: ENH: add Jensen > Shannon distance to `scipy.spatial.distance` > * `#8357 `__: ENH: vectorize > scalar zero-search-functions > * `#8397 `__: Add `fs=` > parameter to filter design functions > * `#8537 `__: ENH: Implement > mode parameter for spline filtering. > * `#8558 `__: ENH: small > speedup for stats.gaussian_kde > * `#8560 `__: BUG: fix p-value > calc of anderson_ksamp in scipy.stats > * `#8614 `__: ENH: correct > p-values for stats.kendalltau and stats.mstats.kendalltau > * `#8670 `__: ENH: Require > Lapack 3.4.0 > * `#8683 `__: Correcting kmeans > documentation > * `#8725 `__: MAINT: Cleanup > scipy.optimize.leastsq > * `#8726 `__: BUG: Fix > _get_output in scipy.ndimage to support string > * `#8733 `__: MAINT: stats: A > bit of clean up. > * `#8737 `__: BUG: Improve > numerical precision/convergence failures of smirnov/kolmogorov > * `#8738 `__: MAINT: stats: A > bit of clean up in test_distributions.py. > * `#8740 `__: BF/ENH: make > minpack thread safe > * `#8742 `__: BUG: Fix division > by zero in trust-region optimization methods > * `#8746 `__: MAINT: signal: > Fix a docstring of a private function, and fix... > * `#8750 `__: DOC clarified > description of norminvgauss in scipy.stats > * `#8753 `__: DOC: signal: Fix > a plot title in the chirp docstring. > * `#8755 `__: DOC: MAINT: Fix > link to the wheel documentation in developer... > * `#8760 `__: BUG: stats: > boltzmann wasn't setting the upper bound. > * `#8763 `__: [DOC] Improved > scipy.cluster.hierarchy documentation > * `#8765 `__: DOC: added > example for scipy.stat.mstats.tmin > * `#8788 `__: DOC: fix > definition of optional `disp` parameter > * `#8802 `__: MAINT: Suppress > dd_real unused function compiler warnings. > * `#8803 `__: ENH: Add > full_output support to optimize.newton() > * `#8804 `__: MAINT: stats > cleanup > * `#8808 `__: DOC: add note > about isinstance for frozen rvs > * `#8812 `__: Updated numpydoc > submodule > * `#8813 `__: MAINT: stats: Fix > multinomial docstrings, and do some clean up. > * `#8816 `__: BUG: fixed _stats > of t-distribution in scipy.stats > * `#8817 `__: BUG: ndimage: Fix > validation of the origin argument in correlate... > * `#8822 `__: BUG: integrate: > Fix crash with repeated t values in odeint. > * `#8832 `__: Hyperlink DOIs > against preferred resolver > * `#8837 `__: BUG: sparse: > Ensure correct dtype for sparse comparison operations. > * `#8839 `__: DOC: stats: A few > tweaks to the linregress docstring. > * `#8846 `__: BUG: stats: Fix > logpdf method of invwishart. > * `#8849 `__: DOC: signal: > Fixed mistake in the firwin docstring. > * `#8854 `__: DOC: fix type > descriptors in ltisys documentation > * `#8865 `__: Fix tiny typo in > docs for chi2 pdf > * `#8870 `__: Fixes related to > invertibility of STFT > * `#8872 `__: ENH: special: Add > the softmax function > * `#8874 `__: DOC correct gamma > function in docstrings in scipy.stats > * `#8876 `__: ENH: Added TOMS > Algorithm 748 as 1-d root finder; 17 test function... > * `#8882 `__: ENH: Only use > Halley's adjustment to Newton if close enough. > * `#8883 `__: FIX: optimize: > make jac and hess truly optional for 'trust-constr' > * `#8885 `__: TST: Do not error > on warnings raised about non-tuple indexing. > * `#8887 `__: MAINT: filter out > np.matrix PendingDeprecationWarning's in numpy... > * `#8889 `__: DOC: optimize: > separate legacy interfaces from new ones > * `#8890 `__: ENH: Add > optimize.root_scalar() as a universal dispatcher for... > * `#8899 `__: DCT-IV, DST-IV > and DCT-I, DST-I orthonormalization support in... > * `#8901 `__: MAINT: Reorganize > flapack.pyf.src file > * `#8907 `__: BUG: ENH: Check > if guess for newton is already zero before checking... > * `#8908 `__: ENH: Make sorting > optional for cKDTree.query_ball_point() > * `#8910 `__: DOC: > sparse.csgraph simple examples. > * `#8914 `__: DOC: interpolate: > fix equivalences of string aliases > * `#8918 `__: add > float_control(precise, on) to _fpumode.c > * `#8919 `__: MAINT: > interpolate: improve error messages for common `bc_type`... > * `#8920 `__: DOC: update > Contributing to SciPy to say "prefer no PEP8 only... > * `#8924 `__: MAINT: special: > deprecate `hyp2f0`, `hyp1f2`, and `hyp3f0` > * `#8927 `__: MAINT: special: > remove `errprint` > * `#8932 `__: Fix broadcasting > scale arg of entropy > * `#8936 `__: Fix (some) > non-tuple index warnings > * `#8937 `__: ENH: implement > sparse matrix BSR to CSR conversion directly. > * `#8938 `__: DOC: add > @_ni_docstrings.docfiller in ndimage.rotate > * `#8940 `__: Update > _discrete_distns.py > * `#8943 `__: DOC: Finish > dangling sentence in `convolve` docstring > * `#8944 `__: MAINT: Address > tuple indexing and warnings > * `#8945 `__: ENH: > spatial.transform.Rotation [GSOC2018] > * `#8950 `__: csgraph Dijkstra > function description rewording > * `#8953 `__: DOC, MAINT: HTTP > -> HTTPS, and other linkrot fixes > * `#8955 `__: BUG: np.int64 in > scipy.fftpack.next_fast_len > * `#8958 `__: MAINT: Add more > descriptive error message for phase one simplex. > * `#8962 `__: BUG: > sparse.linalg: add missing conjugate to _ScaledLinearOperator.adjoint > * `#8963 `__: BUG: > sparse.linalg: downgrade LinearOperator TypeError to warning > * `#8965 `__: ENH: Wrapped RFP > format and RZ decomposition routines > * `#8969 `__: MAINT: doc and > code fixes for optimize.newton > * `#8970 `__: Added 'average' > keyword for welch/csd to enable median averaging > * `#8971 `__: Better imresize > deprecation warning > * `#8972 `__: MAINT: Switch > np.where(c) for np.nonzero(c) > * `#8975 `__: MAINT: Fix > warning-based failures > * `#8979 `__: DOC: fix > description of count_sort keyword of dendrogram > * `#8982 `__: MAINT: optimize: > Fixed minor mistakes in test_linprog.py (#8978) > * `#8984 `__: BUG: > sparse.linalg: ensure expm casts integer inputs to float > * `#8986 `__: BUG: > optimize/slsqp: do not exit with convergence on steps where... > * `#8989 `__: MAINT: use > collections.abc in basinhopping > * `#8990 `__: ENH extend > p-values of anderson_ksamp in scipy.stats > * `#8991 `__: ENH: Weighted kde > * `#8993 `__: ENH: > spatial.transform.Rotation.random [GSOC 2018] > * `#8994 `__: ENH: > spatial.transform.Slerp [GSOC 2018] > * `#8995 `__: TST: time.time in > test > * `#9007 `__: Fix typo in > fftpack.rst > * `#9013 `__: Added correct > plotting code for two sided output from spectrogram > * `#9014 `__: BUG: > differential_evolution with inf objective functions > * `#9017 `__: BUG: fixed #8446 > corner case for asformat(array|dense) > * `#9018 `__: MAINT: > _lib/ccallback: remove unused code > * `#9021 `__: BUG: Issue with > subspace_angles > * `#9022 `__: DOC: Added "See > Also" section to lombscargle docstring > * `#9034 `__: BUG: Fix > tolerance printing behavior, remove meaningless tol... > * `#9035 `__: TST: improve > signal.bsplines test coverage > * `#9037 `__: ENH: add a new > init method for k-means > * `#9039 `__: DOC: Add examples > to fftpack.irfft docstrings > * `#9048 `__: ENH: > scipy.sparse.random > * `#9050 `__: BUG: > scipy.io.hb_write: fails for matrices not in csc format > * `#9051 `__: MAINT: Fix slow > sparse.rand for k < mn/3 (#9036). > * `#9054 `__: MAINT: spatial: > Explicitly initialize LAPACK output parameters. > * `#9055 `__: DOC: Add examples > to scipy.special docstrings > * `#9056 `__: ENH: Use one > thread in OpenBLAS > * `#9059 `__: DOC: Update > README with link to Code of Conduct > * `#9060 `__: BLD: remove > support for the Bento build system. > * `#9062 `__: DOC add sections > to overview in scipy.stats > * `#9066 `__: BUG: Correct > "remez" error message > * `#9069 `__: DOC: update > linalg section of roadmap for LAPACK versions. > * `#9079 `__: MAINT: add > spatial.transform to refguide check; complete some... > * `#9081 `__: MAINT: Add > warnings if pivot value is close to tolerance in linprog(method='simplex') > * `#9084 `__: BUG fix incorrect > p-values of kurtosistest in scipy.stats > * `#9095 `__: DOC: add sections > to mstats overview in scipy.stats > * `#9096 `__: BUG: Add test for > Stackoverflow example from issue 8174. > * `#9101 `__: ENH: add Siegel > slopes (robust regression) to scipy.stats > * `#9105 `__: allow > resample_poly() to output float32 for float32 inputs. > * `#9112 `__: MAINT: optimize: > make trust-constr accept constraint dict (#9043) > * `#9118 `__: Add doc entry to > cholesky_banded > * `#9120 `__: eigsh > documentation parameters > * `#9125 `__: interpolative: > correctly reconstruct full rank matrices > * `#9126 `__: MAINT: Use > warnings for unexpected peak properties > * `#9129 `__: BUG: Do not catch > and silence KeyboardInterrupt > * `#9131 `__: DOC: Correct the > typo in scipy.optimize tutorial page > * `#9133 `__: FIX: Avoid use of > bare except > * `#9134 `__: DOC: Update of > 'return_eigenvectors' description > * `#9137 `__: DOC: typo fixes > for discrete Poisson tutorial > * `#9139 `__: FIX: Doctest > failure in optimize tutorial > * `#9143 `__: DOC: missing > sigma in Pearson r formula > * `#9145 `__: MAINT: Refactor > linear programming solvers > * `#9149 `__: FIX: Make > scipy.odr.ODR ifixx equal to its data.fix if given > * `#9156 `__: DOC: special: > Mention the sigmoid function in the expit docstring. > * `#9160 `__: Fixed a latex > delimiter error in levy() > * `#9170 `__: DOC: correction / > update of docstrings of distributions in scipy.stats > * `#9171 `__: better > description of the hierarchical clustering parameter > * `#9174 `__: domain check for > a < b in stats.truncnorm > * `#9175 `__: DOC: Minor > grammar fix > * `#9176 `__: BUG: > CloughTocher2DInterpolator: fix miscalculation at neighborless... > * `#9177 `__: BUILD: Document > the "clean" target in the doc/Makefile. > * `#9178 `__: MAINT: make > refguide-check more robust for printed numpy arrays > * `#9186 `__: MAINT: Remove > np.ediff1d occurence > * `#9188 `__: DOC: correct typo > in extending ndimage with C > * `#9190 `__: ENH: Support > specifying axes for fftconvolve > * `#9192 `__: MAINT: optimize: > fixed @pv style suggestions from #9112 > * `#9200 `__: Fix > make_interp_spline(..., k=0 or 1, axis<0) > * `#9201 `__: BUG: > sparse.linalg/gmres: use machine eps in breakdown check > * `#9204 `__: MAINT: fix up > stats.spearmanr and match mstats.spearmanr with... > * `#9206 `__: MAINT: include > benchmarks and dev files in sdist. > * `#9208 `__: TST: signal: bump > bsplines test tolerance for complex data > * `#9210 `__: TST: mark tests > as slow, fix missing random seed > * `#9211 `__: ENH: add > capability to specify orders in pade func > * `#9217 `__: MAINT: Include > ``success`` and ``nit`` in OptimizeResult returned... > * `#9222 `__: ENH: interpolate: > Use scipy.spatial.distance to speed-up Rbf > * `#9229 `__: MNT: Fix Fourier > filter double case > * `#9233 `__: BUG: > spatial/distance: fix pdist/cdist performance regression... > * `#9234 `__: FIX: Proper > suppression > * `#9235 `__: BENCH: > rationalize slow benchmarks + miscellaneous fixes > * `#9238 `__: BENCH: limit > number of parameter combinations in spatial.*KDTree... > * `#9239 `__: DOC: stats: Fix > LaTeX markup of a couple distribution PDFs. > * `#9241 `__: ENH: Evaluate > plateau size during peak finding > * `#9242 `__: ENH: stats: > Implement _ppf and _logpdf for crystalball, and do... > * `#9246 `__: DOC: Properly > render versionadded directive in HTML documentation > * `#9255 `__: DOC: mention > RootResults in optimization reference guide > * `#9260 `__: TST: relax some > tolerances so tests pass with x87 math > * `#9264 `__: TST Use > assert_raises "match" parameter instead of the "message"... > * `#9267 `__: DOC: clarify > expect() return val when moment is inf/nan > * `#9272 `__: DOC: Add > description of default bounds to linprog > * `#9277 `__: MAINT: > sparse/linalg: make test deterministic > * `#9278 `__: MAINT: > interpolate: pep8 cleanup in test_polyint > * `#9279 `__: Fixed docstring > for resample > * `#9280 `__: removed first > check for float in get_sum_dtype > * `#9281 `__: BUG: only accept > 1d input for bartlett / levene in scipy.stats > * `#9282 `__: MAINT: > dense_output and t_eval are mutually exclusive inputs > * `#9283 `__: MAINT: add docs > and do some cleanups in interpolate.Rbf > * `#9288 `__: Run > distance_transform_edt tests on all types > * `#9294 `__: DOC: fix the > formula typo > * `#9298 `__: MAINT: > optimize/trust-constr: restore .niter attribute for backward-compat > * `#9299 `__: DOC: > clarification of default rvs method in scipy.stats > * `#9301 `__: MAINT: removed > unused import sys > * `#9302 `__: MAINT: removed > unused imports > * `#9303 `__: DOC: signal: > Refer to fs instead of nyq in the firwin docstring. > * `#9305 `__: ENH: Added > Yeo-Johnson power transformation > * `#9306 `__: ENH - add dual > annealing > * `#9309 `__: ENH add the > yulesimon distribution to scipy.stats > * `#9317 `__: Nested SLSQP bug > fix. > * `#9320 `__: MAINT: stats: > avoid underflow in stats.geom.ppf > * `#9326 `__: Add example for > Rosenbrock function > * `#9332 `__: Sort file lists > * `#9340 `__: Fix typo in > find_peaks documentation > * `#9343 `__: MAINT Use np.full > when possible > * `#9344 `__: DOC: added > examples to docstring of dirichlet class > * `#9346 `__: DOC: Fix import > of scipy.sparse.linalg in example (#9345) > * `#9350 `__: Fix interpolate > read only > * `#9351 `__: MAINT: > special.erf: use the x->-x symmetry > * `#9356 `__: Fix documentation > typo > * `#9358 `__: DOC: improve doc > for ksone and kstwobign in scipy.stats > * `#9362 `__: DOC: Change > datatypes of A matrices in linprog > * `#9364 `__: MAINT: Adds > implicit none to fftpack fortran sources > * `#9369 `__: DOC: minor tweak > to CoC (updated NumFOCUS contact address). > * `#9373 `__: Fix exception if > python is called with -OO option > * `#9374 `__: FIX: AIX > compilation issue with NAN and INFINITY > * `#9376 `__: COBLYA -> COBYLA > in docs > * `#9377 `__: DOC: Add examples > integrate: fixed_quad and quadrature > * `#9379 `__: MAINT: TST: Make > tests NumPy 1.8 compatible > * `#9385 `__: CI: On Travis > matrix "OPTIMIZE=-OO" flag ignored > * `#9387 `__: Fix defaut value > for 'mode' in 'ndimage.shift' in the doc > * `#9392 `__: BUG: rank has to > be integer in rank_filter: fixed issue 9388 > * `#9399 `__: DOC: Misc. typos > * `#9400 `__: TST: stats: Fix > the expected r-value of a linregress test. > * `#9405 `__: BUG: np.hstack > does not accept generator expressions > * `#9408 `__: ENH: linalg: > Shorter ill-conditioned warning message > * `#9418 `__: DOC: Fix ndimage > docstrings and reduce doc build warnings > * `#9421 `__: DOC: Add missing > docstring examples in scipy.spatial > * `#9422 `__: DOC: Add an > example to integrate.newton_cotes > * `#9427 `__: BUG: Fixed defect > with maxiter #9419 in dual annealing > * `#9431 `__: BENCH: Add dual > annealing to scipy benchmark (see #9415) > * `#9435 `__: DOC: Add > docstring examples for stats.binom_test > * `#9443 `__: DOC: Fix the > order of indices in optimize tutorial > * `#9444 `__: MAINT: > interpolate: use operator.index for checking/coercing... > * `#9445 `__: DOC: Added > missing example to stats.mstats.kruskal > * `#9446 `__: DOC: Add note > about version changed for jaccard distance > * `#9447 `__: BLD: > version-script handling in setup.py > * `#9448 `__: TST: skip a > problematic linalg test > * `#9449 `__: TST: fix missing > seed in lobpcg test. > * `#9456 `__: TST: > test_eigs_consistency() now sorts output > > Checksums > ========= > > MD5 > ~~~ > > 0bb53a49e77bca11fb26698744c60f97 > scipy-1.2.0-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 39e215ac7e8d6de33d939486987dcba4 > scipy-1.2.0-cp27-cp27m-manylinux1_i686.whl > d6e33b2c05ffbcf9790628d656c8e61f > scipy-1.2.0-cp27-cp27m-manylinux1_x86_64.whl > a463a12d77b87df0a2d202323771a908 scipy-1.2.0-cp27-cp27m-win32.whl > 3dc17a11c7dd211ce51a338cfe30eb48 scipy-1.2.0-cp27-cp27m-win_amd64.whl > 82b1ecbecadfeddd2be1c6d616491029 > scipy-1.2.0-cp27-cp27mu-manylinux1_i686.whl > 65021ade783f1416b1920d2a2cc39d4d > scipy-1.2.0-cp27-cp27mu-manylinux1_x86_64.whl > 7cc2cdbc9b421ef10695b898cdc241e7 > scipy-1.2.0-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 2a4ccbfcccb9395fa7554a82db40e454 > scipy-1.2.0-cp34-cp34m-manylinux1_i686.whl > 662dc35acd6f588565cd6467465fc742 > scipy-1.2.0-cp34-cp34m-manylinux1_x86_64.whl > a19bd9969bb5b92595e82d924b8272f9 scipy-1.2.0-cp34-cp34m-win32.whl > 5f1eaa3745956db0da724f83dd174559 scipy-1.2.0-cp34-cp34m-win_amd64.whl > d32a4c31d0a188f3550c1306d20b03c7 > scipy-1.2.0-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 34f4a7f04abfda87fac8ab38a9a70a77 > scipy-1.2.0-cp35-cp35m-manylinux1_i686.whl > bd4d56910802870072e3c5ded69a8f08 > scipy-1.2.0-cp35-cp35m-manylinux1_x86_64.whl > cb3fb7ddd3992928f9173e4eb489d23e scipy-1.2.0-cp35-cp35m-win32.whl > 68f5ddcb6e592b1d9cba95f24faee7b5 scipy-1.2.0-cp35-cp35m-win_amd64.whl > c0e110f3a935731782c96a13cc264ea2 > scipy-1.2.0-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 9d898924498abbe2d26dd18b3413fb11 > scipy-1.2.0-cp36-cp36m-manylinux1_i686.whl > dd9ae664cbe7de54828d83c772e24da3 > scipy-1.2.0-cp36-cp36m-manylinux1_x86_64.whl > 8dea8432610bb3c63114eb6469c5f99a scipy-1.2.0-cp36-cp36m-win32.whl > ebda830aec7b60193772741f85fee28c scipy-1.2.0-cp36-cp36m-win_amd64.whl > 0e8b7a7908c50e635e639d2c69901140 > scipy-1.2.0-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 56719437a821f9f2f98f069225e70c87 > scipy-1.2.0-cp37-cp37m-manylinux1_i686.whl > 93d9d978855516ec38fa08620ef3443c > scipy-1.2.0-cp37-cp37m-manylinux1_x86_64.whl > fff3d66b877b6e6b9984b84ae9e4d76c scipy-1.2.0-cp37-cp37m-win32.whl > 3defb2c8b2f69057919ee3b0c92de65c scipy-1.2.0-cp37-cp37m-win_amd64.whl > e57011507865b0b702aff6077d412e03 scipy-1.2.0.tar.gz > 8eb6c1d7ceae0d06aef474f7801b8fca scipy-1.2.0.tar.xz > b0fb16b09319d3031d27ccf21a3ef474 scipy-1.2.0.zip > > SHA256 > ~~~~~~ > > d1ae77b79fd5e27a10ba7c4e7c3a62927b9d29a4dccf28f6905c25d983aaf183 > scipy-1.2.0-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 4b1f0883cb9d8ee963cf0a31c87341e9e758abb2cf1e5bcc0d7b066ef6b17573 > scipy-1.2.0-cp27-cp27m-manylinux1_i686.whl > c5eae911cf26b3c7eda889ec98d3c226f312c587acfaaf02602473f98b4c16d6 > scipy-1.2.0-cp27-cp27m-manylinux1_x86_64.whl > 58f0435f052cb60f1472c77f52a8f6642f8877b70559e5e0b9a1744f33f5cbe5 > scipy-1.2.0-cp27-cp27m-win32.whl > 4cce25c6e7ff7399c67dfe1b5423c36c391cf9b4b2be390c1675ab410f1ef503 > scipy-1.2.0-cp27-cp27m-win_amd64.whl > 02cb79ea38114dc480e9b08d6b87095728e8fb39b9a49b449ee443d678001611 > scipy-1.2.0-cp27-cp27mu-manylinux1_i686.whl > 7dc4002f0a0a688774ef04878afe769ecd1ac21fe9b4b1d7125e2cf16170afd3 > scipy-1.2.0-cp27-cp27mu-manylinux1_x86_64.whl > 7994c044bf659b0a24ad7673ec7db85c2fadb87e4980a379a9fd5b086fe3649a > scipy-1.2.0-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 72bd766f753fd32f072d30d7bc2ad492d56dbcbf3e13764e27635d5c41079339 > scipy-1.2.0-cp34-cp34m-manylinux1_i686.whl > 3132a9fab3f3545c8b0ba15688d11857efdd4a58d388d3785dc474f56fea7138 > scipy-1.2.0-cp34-cp34m-manylinux1_x86_64.whl > 7413080b381766a22d52814edb65631f0e323a7cea945c70021a672f38acc73f > scipy-1.2.0-cp34-cp34m-win32.whl > 6f791987899532305126309578727c0197bddbafab9596bafe3e7bfab6e1ce13 > scipy-1.2.0-cp34-cp34m-win_amd64.whl > 937147086e8b4338bf139ca8fa98da650e3a46bf2ca617f8e9dd68c3971ec420 > scipy-1.2.0-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 63e1d5ca9e5e1984f1a275276991b036e25d39d37dd7edbb3f4f6165c2da7dbb > scipy-1.2.0-cp35-cp35m-manylinux1_i686.whl > 03c827cdbc584e935264040b958e5fa0570a16095bee23a013482ba3f0e963a2 > scipy-1.2.0-cp35-cp35m-manylinux1_x86_64.whl > bc294841f6c822714af362095b181a853f47ed5ce757354bd2e4776d579ff3a4 > scipy-1.2.0-cp35-cp35m-win32.whl > cca33a01a5987c650b87a1a910aa311ffa44e67cca1ff502ef9efdae5d9a8624 > scipy-1.2.0-cp35-cp35m-win_amd64.whl > 8608316d0cc01f8b25111c8adfe6efbc959cbba037a62c784551568d7ffbf280 > scipy-1.2.0-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > fb36064047e6bf87b6320a9b6eb7f525ef6863c7a4aef1a84a4bbfb043612617 > scipy-1.2.0-cp36-cp36m-manylinux1_i686.whl > 854bd87cc23824d5db4983956bc30f3790e1c7448f1a9e6a8fb7bff7601aef87 > scipy-1.2.0-cp36-cp36m-manylinux1_x86_64.whl > fc1a19d95649439dbd50baca676bceb29bbfcd600aed2c5bd71d9bad82a87cfe > scipy-1.2.0-cp36-cp36m-win32.whl > 8f5fcc87b48fc3dd6d901669c89af4feeb856dffb6f671539a238b7e8af1799c > scipy-1.2.0-cp36-cp36m-win_amd64.whl > bc6a88b0009a1b60eab5c22ac3a006f6968d6328de10c6a64ebb0d64a05548d3 > scipy-1.2.0-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 64b2c35824da3ef6bb1e722216e4ef28802af6413c7586136500e343d34ba179 > scipy-1.2.0-cp37-cp37m-manylinux1_i686.whl > 78a67ee4845440e81cfbfabde20537ca12051d0eeac951fe4c6d8751feac3103 > scipy-1.2.0-cp37-cp37m-manylinux1_x86_64.whl > 04f2b23258139c109d0524f111597dd095a505d9cb2c71e381d688d653877fa3 > scipy-1.2.0-cp37-cp37m-win32.whl > 5706b785ca289fdfd91aa05066619e51d140613b613e35932601f2315f5d8470 > scipy-1.2.0-cp37-cp37m-win_amd64.whl > 51a2424c8ed80e60bdb9a896806e7adaf24a58253b326fbad10f80a6d06f2214 > scipy-1.2.0.tar.gz > 1cfafc64e1c1c0b6d040d35780ba06f01e9cb44f3bacd8f33a5df6efe5a144a6 > scipy-1.2.0.tar.xz > 5b3d4b1654b4723431ad7f47b4556498a86a53d2fdb86e85a45c3da0c2a72a4b > scipy-1.2.0.zip > -----BEGIN PGP SIGNATURE----- > > iQIzBAEBCAAdFiEEgfAqrOuERrV4fwr6XCLdIy4FKasFAlwYY1YACgkQXCLdIy4F > KauihhAAo0fk+a4U4ilFXeZrUTuZTeqqHtD60yV8Z2pZvqQyH1BBP8BKksV/v3bP > 6ckl+upWaolMjZgehWhAKyGgE2oUHDu6RxaRS97Kbbns580M+wWduPX7kjf7OKoX > KFX1a8/GlBWTQKIMj6P2oShT7rvYB+WABvyoTxXKbHG0/ArOtOqqAYJFKLeOYB6m > o0+qajqt9syV2iqBFlHnrPKQ8qjtfPxqCP9KHhNIbHd17305YwJc58CBhpulIjaP > HIhJOuP7xigELX9yCzJ2qFGBjTd2HNvBQWIRjNDfbox6mhWO4no30c+OamG3MAr7 > n9TDzSIjxkRedvBzMRJwA/Q5/Mou/R16BF+ZzvCVZnp/h6LrXQg4ENfR304Byyy3 > NlYzmQKlV0XvP4oYewBnLfq6hcXAum7rf3L8ene8mu0OWJumW7Yr6PWfDNECDKvX > sPWSwkNu01Pzg/KUUkrS9w6m9bZTj4UP15L2Z8JSVdp/wxCHGh8txJWjOenoZBnD > BPyitzsgbuW+pd7+WmjZoJpr8QjL/Uw8vpUwlvKAvvVfFnVeVh3X1awK+D6iba69 > LbyfhOG3R846WkxHh458uvNxmYUbm6sqaZ7lzY91bD8z61jS6PCvpR8BJcwmpP7Y > q/duWsaakRWLe35CE8KuvKCgVFhhStX2sZ/hRkNsvm2/hEAtNW0= > =3Enc > -----END PGP SIGNATURE----- > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > -------------- next part -------------- An HTML attachment was scrubbed... URL: From charlesr.harris at gmail.com Tue Dec 18 17:08:43 2018 From: charlesr.harris at gmail.com (Charles R Harris) Date: Tue, 18 Dec 2018 15:08:43 -0700 Subject: [SciPy-Dev] ANN: SciPy 1.2.0 In-Reply-To: References: Message-ID: Congratulations. May there be many more :) Chuck On Tue, Dec 18, 2018 at 9:57 AM Tyler Reddy wrote: > -----BEGIN PGP SIGNED MESSAGE----- > Hash: SHA256 > > Hi all, > > On behalf of the SciPy development team I'm pleased to announce > the release of SciPy 1.2.0. This is an LTS release and the > last to support Python 2.7. > > Sources and binary wheels can be found at: > https://pypi.org/project/scipy/ > and at: > https://github.com/scipy/scipy/releases/tag/v1.2.0 > > One of a few ways to install this release with pip: > > pip install scipy==1.2.0 > > ========================== > SciPy 1.2.0 Release Notes > ========================== > > SciPy 1.2.0 is the culmination of 6 months of hard work. It contains > many new features, numerous bug-fixes, improved test coverage and better > documentation. There have been a number of deprecations and API changes > in this release, which are documented below. All users are encouraged to > upgrade to this release, as there are a large number of bug-fixes and > optimizations. Before upgrading, we recommend that users check that > their own code does not use deprecated SciPy functionality (to do so, > run your code with ``python -Wd`` and check for ``DeprecationWarning`` s). > Our development attention will now shift to bug-fix releases on the > 1.2.x branch, and on adding new features on the master branch. > > This release requires Python 2.7 or 3.4+ and NumPy 1.8.2 or greater. > > Note: This will be the last SciPy release to support Python 2.7. > Consequently, the 1.2.x series will be a long term support (LTS) > release; we will backport bug fixes until 1 Jan 2020. > > For running on PyPy, PyPy3 6.0+ and NumPy 1.15.0 are required. > > Highlights of this release > --------------------------- > > - 1-D root finding improvements with a new solver, ``toms748``, and a new > unified interface, ``root_scalar`` > - New ``dual_annealing`` optimization method that combines stochastic and > local deterministic searching > - A new optimization algorithm, ``shgo`` (simplicial homology > global optimization) for derivative free optimization problems > - A new category of quaternion-based transformations are available in > `scipy.spatial.transform` > > New features > ============ > > `scipy.ndimage` improvements > --------------------------------- > > Proper spline coefficient calculations have been added for the ``mirror``, > ``wrap``, and ``reflect`` modes of `scipy.ndimage.rotate` > > `scipy.fftpack` improvements > --------------------------------- > > DCT-IV, DST-IV, DCT-I, and DST-I orthonormalization are now supported in > `scipy.fftpack`. > > `scipy.interpolate` improvements > --------------------------------- > > `scipy.interpolate.pade` now accepts a new argument for the order of the > numerator > > `scipy.cluster` improvements > ----------------------------- > > `scipy.cluster.vq.kmeans2` gained a new initialization method, kmeans++. > > `scipy.special` improvements > ----------------------------- > > The function ``softmax`` was added to `scipy.special`. > > `scipy.optimize` improvements > ------------------------------ > > The one-dimensional nonlinear solvers have been given a unified interface > `scipy.optimize.root_scalar`, similar to the `scipy.optimize.root` > interface > for multi-dimensional solvers. ``scipy.optimize.root_scalar(f, bracket=[a > ,b], > method="brenth")`` is equivalent to ``scipy.optimize.brenth(f, a ,b)``. > If no > ``method`` is specified, an appropriate one will be selected based upon the > bracket and the number of derivatives available. > > The so-called Algorithm 748 of Alefeld, Potra and Shi for root-finding > within > an enclosing interval has been added as `scipy.optimize.toms748`. This > provides > guaranteed convergence to a root with convergence rate per function > evaluation > of approximately 1.65 (for sufficiently well-behaved functions.) > > ``differential_evolution`` now has the ``updating`` and ``workers`` > keywords. > The first chooses between continuous updating of the best solution vector > (the > default), or once per generation. Continuous updating can lead to faster > convergence. The ``workers`` keyword accepts an ``int`` or map-like > callable, > and parallelises the solver (having the side effect of updating once per > generation). Supplying an ``int`` evaluates the trial solutions in N > parallel > parts. Supplying a map-like callable allows other parallelisation > approaches > (such as ``mpi4py``, or ``joblib``) to be used. > > ``dual_annealing`` (and ``shgo`` below) is a powerful new general purpose > global optizimation (GO) algorithm. ``dual_annealing`` uses two annealing > processes to accelerate the convergence towards the global minimum of an > objective mathematical function. The first annealing process controls the > stochastic Markov chain searching and the second annealing process > controls the > deterministic minimization. So, dual annealing is a hybrid method that > takes > advantage of stochastic and local deterministic searching in an efficient > way. > > ``shgo`` (simplicial homology global optimization) is a similar algorithm > appropriate for solving black box and derivative free optimization (DFO) > problems. The algorithm generally converges to the global solution in > finite > time. The convergence holds for non-linear inequality and > equality constraints. In addition to returning a global minimum, the > algorithm also returns any other global and local minima found after every > iteration. This makes it useful for exploring the solutions in a domain. > > `scipy.optimize.newton` can now accept a scalar or an array > > ``MINPACK`` usage is now thread-safe, such that ``MINPACK`` + callbacks may > be used on multiple threads. > > `scipy.signal` improvements > ---------------------------- > > Digital filter design functions now include a parameter to specify the > sampling > rate. Previously, digital filters could only be specified using normalized > frequency, but different functions used different scales (e.g. 0 to 1 for > ``butter`` vs 0 to ? for ``freqz``), leading to errors and confusion. With > the ``fs`` parameter, ordinary frequencies can now be entered directly into > functions, with the normalization handled internally. > > ``find_peaks`` and related functions no longer raise an exception if the > properties of a peak have unexpected values (e.g. a prominence of 0). A > ``PeakPropertyWarning`` is given instead. > > The new keyword argument ``plateau_size`` was added to ``find_peaks``. > ``plateau_size`` may be used to select peaks based on the length of the > flat top of a peak. > > ``welch()`` and ``csd()`` methods in `scipy.signal` now support calculation > of a median average PSD, using ``average='mean'`` keyword > > `scipy.sparse` improvements > ---------------------------- > > The `scipy.sparse.bsr_matrix.tocsr` method is now implemented directly > instead > of converting via COO format, and the `scipy.sparse.bsr_matrix.tocsc` > method > is now also routed via CSR conversion instead of COO. The efficiency of > both > conversions is now improved. > > The issue where SuperLU or UMFPACK solvers crashed on matrices with > non-canonical format in `scipy.sparse.linalg` was fixed. The solver wrapper > canonicalizes the matrix if necessary before calling the SuperLU or UMFPACK > solver. > > The ``largest`` option of `scipy.sparse.linalg.lobpcg()` was fixed to have > a correct (and expected) behavior. The order of the eigenvalues was made > consistent with the ARPACK solver (``eigs()``), i.e. ascending for the > smallest eigenvalues, and descending for the largest eigenvalues. > > The `scipy.sparse.random` function is now faster and also supports integer > and > complex values by passing the appropriate value to the ``dtype`` argument. > > `scipy.spatial` improvements > ----------------------------- > > The function `scipy.spatial.distance.jaccard` was modified to return 0 > instead > of ``np.nan`` when two all-zero vectors are compared. > > Support for the Jensen Shannon distance, the square-root of the > divergence, has > been added under `scipy.spatial.distance.jensenshannon` > > An optional keyword was added to the function > `scipy.spatial.cKDTree.query_ball_point()` to sort or not sort the returned > indices. Not sorting the indices can speed up calls. > > A new category of quaternion-based transformations are available in > `scipy.spatial.transform`, including spherical linear interpolation of > rotations (``Slerp``), conversions to and from quaternions, Euler angles, > and general rotation and inversion capabilities > (`spatial.transform.Rotation`), and uniform random sampling of 3D > rotations (`spatial.transform.Rotation.random`). > > `scipy.stats` improvements > --------------------------- > > The Yeo-Johnson power transformation is now supported (``yeojohnson``, > ``yeojohnson_llf``, ``yeojohnson_normmax``, ``yeojohnson_normplot``). > Unlike > the Box-Cox transformation, the Yeo-Johnson transformation can accept > negative > values. > > Added a general method to sample random variates based on the density > only, in > the new function ``rvs_ratio_uniforms``. > > The Yule-Simon distribution (``yulesimon``) was added -- this is a new > discrete probability distribution. > > ``stats`` and ``mstats`` now have access to a new regression method, > ``siegelslopes``, a robust linear regression algorithm > > `scipy.stats.gaussian_kde` now has the ability to deal with weighted > samples, > and should have a modest improvement in performance > > Levy Stable Parameter Estimation, PDF, and CDF calculations are now > supported > for `scipy.stats.levy_stable`. > > The Brunner-Munzel test is now available as ``brunnermunzel`` in ``stats`` > and ``mstats`` > > `scipy.linalg` improvements > --------------------------- > > `scipy.linalg.lapack` now exposes the LAPACK routines using the Rectangular > Full Packed storage (RFP) for upper triangular, lower triangular, > symmetric, > or Hermitian matrices; the upper trapezoidal fat matrix RZ decomposition > routines are now available as well. > > Deprecated features > =================== > The functions ``hyp2f0``, ``hyp1f2`` and ``hyp3f0`` in ``scipy.special`` > have > been deprecated. > > > Backwards incompatible changes > ============================== > > LAPACK version 3.4.0 or later is now required. Building with > Apple Accelerate is no longer supported. > > The function ``scipy.linalg.subspace_angles(A, B)`` now gives correct > results for all angles. Before this, the function only returned > correct values for those angles which were greater than pi/4. > > Support for the Bento build system has been removed. Bento has not been > maintained for several years, and did not have good Python 3 or wheel > support, > hence it was time to remove it. > > The required signature of `scipy.optimize.lingprog` ``method=simplex`` > callback function has changed. Before iteration begins, the simplex solver > first converts the problem into a standard form that does not, in general, > have the same variables or constraints > as the problem defined by the user. Previously, the simplex solver would > pass a > user-specified callback function several separate arguments, such as the > current solution vector ``xk``, corresponding to this standard form > problem. > Unfortunately, the relationship between the standard form problem and the > user-defined problem was not documented, limiting the utility of the > information passed to the callback function. > > In addition to numerous bug fix changes, the simplex solver now passes a > user-specified callback function a single ``OptimizeResult`` object > containing > information that corresponds directly to the user-defined problem. In > future > releases, this ``OptimizeResult`` object may be expanded to include > additional > information, such as variables corresponding to the standard-form problem > and > information concerning the relationship between the standard-form and > user-defined problems. > > The implementation of `scipy.sparse.random` has changed, and this affects > the > numerical values returned for both ``sparse.random`` and ``sparse.rand`` > for > some matrix shapes and a given seed. > > `scipy.optimize.newton` will no longer use Halley's method in cases where > it > negatively impacts convergence > > Other changes > ============= > > > Authors > ======= > > * @endolith > * @luzpaz > * Hameer Abbasi + > * akahard2dj + > * Anton Akhmerov > * Joseph Albert > * alexthomas93 + > * ashish + > * atpage + > * Blair Azzopardi + > * Yoshiki V?zquez Baeza > * Bence Bagi + > * Christoph Baumgarten > * Lucas Bellomo + > * BH4 + > * Aditya Bharti > * Max Bolingbroke > * Fran?ois Boulogne > * Ward Bradt + > * Matthew Brett > * Evgeni Burovski > * Rafa? Byczek + > * Alfredo Canziani + > * CJ Carey > * Luc?a Cheung + > * Poom Chiarawongse + > * Jeanne Choo + > * Robert Cimrman > * Graham Clenaghan + > * cynthia-rempel + > * Johannes Damp + > * Jaime Fernandez del Rio > * Dowon + > * emmi474 + > * Stefan Endres + > * Thomas Etherington + > * Piotr Figiel > * Alex Fikl + > * fo40225 + > * Joseph Fox-Rabinovitz > * Lars G > * Abhinav Gautam + > * Stiaan Gerber + > * C.A.M. Gerlach + > * Ralf Gommers > * Todd Goodall > * Lars Grueter + > * Sylvain Gubian + > * Matt Haberland > * David Hagen > * Will Handley + > * Charles Harris > * Ian Henriksen > * Thomas Hisch + > * Theodore Hu > * Michael Hudson-Doyle + > * Nicolas Hug + > * jakirkham + > * Jakob Jakobson + > * James + > * Jan Schl?ter > * jeanpauphilet + > * josephmernst + > * Kai + > * Kai-Striega + > * kalash04 + > * Toshiki Kataoka + > * Konrad0 + > * Tom Krauss + > * Johannes Kulick > * Lars Gr?ter + > * Eric Larson > * Denis Laxalde > * Will Lee + > * Katrin Leinweber + > * Yin Li + > * P. L. Lim + > * Jesse Livezey + > * Duncan Macleod + > * MatthewFlamm + > * Nikolay Mayorov > * Mike McClurg + > * Christian Meyer + > * Mark Mikofski > * Naoto Mizuno + > * mohmmadd + > * Nathan Musoke > * Anju Geetha Nair + > * Andrew Nelson > * Ayappan P + > * Nick Papior > * Haesun Park + > * Ronny Pfannschmidt + > * pijyoi + > * Ilhan Polat > * Anthony Polloreno + > * Ted Pudlik > * puenka > * Eric Quintero > * Pradeep Reddy Raamana + > * Vyas Ramasubramani + > * Ramon Vi?as + > * Tyler Reddy > * Joscha Reimer > * Antonio H Ribeiro > * richardjgowers + > * Rob + > * robbystk + > * Lucas Roberts + > * rohan + > * Joaquin Derrac Rus + > * Josua Sassen + > * Bruce Sharpe + > * Max Shinn + > * Scott Sievert > * Sourav Singh > * Strahinja Luki? + > * Kai Striega + > * Shinya SUZUKI + > * Mike Toews + > * Piotr Uchwat > * Miguel de Val-Borro + > * Nicky van Foreest > * Paul van Mulbregt > * Gael Varoquaux > * Pauli Virtanen > * Stefan van der Walt > * Warren Weckesser > * Joshua Wharton + > * Bernhard M. Wiedemann + > * Eric Wieser > * Josh Wilson > * Tony Xiang + > * Roman Yurchak + > * Roy Zywina + > > A total of 137 people contributed to this release. > People with a "+" by their names contributed a patch for the first time. > This list of names is automatically generated, and may not be fully > complete. > > Issues closed for 1.2.0 > ------------------------ > > * `#9520 `__: > signal.correlate with method='fft' doesn't benefit from long... > * `#9547 `__: signature of > dual_annealing doesn't match other optimizers > * `#9540 `__: SciPy v1.2.0rc1 > cannot be imported on Python 2.7.15 > * `#1240 `__: Allowing > multithreaded use of minpack through scipy.optimize... > * `#1432 `__: > scipy.stats.mode extremely slow (Trac #905) > * `#3372 `__: Please add > Sphinx search field to online scipy html docs > * `#3678 `__: > _clough_tocher_2d_single direction between centroids > * `#4174 `__: lobpcg > "largest" option invalid? > * `#5493 `__: anderson_ksamp > p-values>1 > * `#5743 `__: slsqp fails to > detect infeasible problem > * `#6139 `__: > scipy.optimize.linprog failed to find a feasible starting point... > * `#6358 `__: stats: > docstring for `vonmises_line` points to `vonmises_line`... > * `#6498 `__: runtests.py is > missing in pypi distfile > * `#7426 `__: > scipy.stats.ksone(n).pdf(x) returns nan for positive values of... > * `#7455 `__: > scipy.stats.ksone.pdf(2,x) return incorrect values for x near... > * `#7456 `__: > scipy.special.smirnov and scipy.special.smirnovi have accuracy... > * `#7492 `__: > scipy.special.kolmogorov(x)/kolmogi(p) inefficient, inaccurate... > * `#7914 `__: TravisCI not > failing when it should for -OO run > * `#8064 `__: linalg.solve > test crashes on Windows > * `#8212 `__: LAPACK > Rectangular Full Packed routines > * `#8256 `__: > differential_evolution bug converges to wrong results in complex... > * `#8443 `__: Deprecate > `hyp2f0`, `hyp1f2`, and `hyp3f0`? > * `#8452 `__: DOC: ARPACK > tutorial has two conflicting equations > * `#8680 `__: scipy fails > compilation when building from source > * `#8686 `__: Division by > zero in _trustregion.py when x0 is exactly equal... > * `#8700 `__: _MINPACK_LOCK > not held when calling into minpack from least_squares > * `#8786 `__: erroneous > moment values for t-distribution > * `#8791 `__: Checking COLA > condition in istft should be optional (or omitted) > * `#8843 `__: imresize cannot > be deprecated just yet > * `#8844 `__: Inverse Wishart > Log PDF Incorrect for Non-diagonal Scale Matrix? > * `#8878 `__: vonmises and > vonmises_line in stats: vonmises wrong and superfluous? > * `#8895 `__: v1.1.0 > `ndi.rotate` documentation ? reused parameters not filled... > * `#8900 `__: Missing complex > conjugation in scipy.sparse.linalg.LinearOperator > * `#8904 `__: BUG: if zero > derivative at root, then Newton fails with RuntimeWarning > * `#8911 `__: > make_interp_spline bc_type incorrect input interpretation > * `#8942 `__: MAINT: Refactor > `_linprog.py` and `_linprog_ip.py` to remove... > * `#8947 `__: np.int64 in > scipy.fftpack.next_fast_len > * `#9020 `__: BUG: > linalg.subspace_angles gives wrong results > * `#9033 `__: > scipy.stats.normaltest sometimes gives incorrect returns b/c... > * `#9036 `__: Bizarre times > for `scipy.sparse.rand` function with 'low' density... > * `#9044 `__: > optimize.minimize(method=`trust-constr`) result dict does not... > * `#9071 `__: doc/linalg: add > cho_solve_banded to see also of cholesky_banded > * `#9082 `__: eigenvalue > sorting in scipy.sparse.linalg.eigsh > * `#9086 `__: > signaltools.py:491: FutureWarning: Using a non-tuple sequence... > * `#9091 `__: > test_spline_filter failure on 32-bit > * `#9122 `__: Typo on scipy > minimization tutorial > * `#9135 `__: doc error at > https://docs.scipy.org/doc/scipy/reference/tutorial/stats/discrete_poisson.html > * `#9167 `__: DOC: BUG: typo > in ndimage LowLevelCallable tutorial example > * `#9169 `__: truncnorm does > not work if b < a in scipy.stats > * `#9250 `__: > scipy.special.tests.test_mpmath::TestSystematic::test_pcfw fails... > * `#9259 `__: rv.expect() == > rv.mean() is false for rv.mean() == nan (and inf) > * `#9286 `__: DOC: Rosenbrock > expression in optimize.minimize tutorial > * `#9316 `__: SLSQP fails in > nested optimization > * `#9337 `__: > scipy.signal.find_peaks key typo in documentation > * `#9345 `__: Example from > documentation of scipy.sparse.linalg.eigs raises... > * `#9383 `__: Default value > for "mode" in "ndimage.shift" > * `#9419 `__: dual_annealing > off by one in the number of iterations > * `#9442 `__: Error in > Defintion of Rosenbrock Function > * `#9453 `__: TST: > test_eigs_consistency() doesn't have consistent results > > > Pull requests for 1.2.0 > ------------------------ > > * `#9526 `__: TST: relax > precision requirements in signal.correlate tests > * `#9507 `__: CI: MAINT: Skip a > ckdtree test on pypy > * `#9512 `__: TST: > test_random_sampling 32-bit handling > * `#9494 `__: TST: > test_kolmogorov xfail 32-bit > * `#9486 `__: BUG: fix sparse > random int handling > * `#9550 `__: BUG: > scipy/_lib/_numpy_compat: get_randint > * `#9549 `__: MAINT: make > dual_annealing signature match other optimizers > * `#9541 `__: BUG: fix > SyntaxError due to non-ascii character on Python 2.7 > * `#7352 `__: ENH: add Brunner > Munzel test to scipy.stats. > * `#7373 `__: BUG: Jaccard > distance for all-zero arrays would return np.nan > * `#7374 `__: ENH: Add PDF, CDF > and parameter estimation for Stable Distributions > * `#8098 `__: ENH: Add shgo for > global optimization of NLPs. > * `#8203 `__: ENH: adding > simulated dual annealing to optimize > * `#8259 `__: Option to follow > original Storn and Price algorithm and its parallelisation > * `#8293 `__: ENH add > ratio-of-uniforms method for rv generation to scipy.stats > * `#8294 `__: BUG: Fix slowness > in stats.mode > * `#8295 `__: ENH: add Jensen > Shannon distance to `scipy.spatial.distance` > * `#8357 `__: ENH: vectorize > scalar zero-search-functions > * `#8397 `__: Add `fs=` > parameter to filter design functions > * `#8537 `__: ENH: Implement > mode parameter for spline filtering. > * `#8558 `__: ENH: small > speedup for stats.gaussian_kde > * `#8560 `__: BUG: fix p-value > calc of anderson_ksamp in scipy.stats > * `#8614 `__: ENH: correct > p-values for stats.kendalltau and stats.mstats.kendalltau > * `#8670 `__: ENH: Require > Lapack 3.4.0 > * `#8683 `__: Correcting kmeans > documentation > * `#8725 `__: MAINT: Cleanup > scipy.optimize.leastsq > * `#8726 `__: BUG: Fix > _get_output in scipy.ndimage to support string > * `#8733 `__: MAINT: stats: A > bit of clean up. > * `#8737 `__: BUG: Improve > numerical precision/convergence failures of smirnov/kolmogorov > * `#8738 `__: MAINT: stats: A > bit of clean up in test_distributions.py. > * `#8740 `__: BF/ENH: make > minpack thread safe > * `#8742 `__: BUG: Fix division > by zero in trust-region optimization methods > * `#8746 `__: MAINT: signal: > Fix a docstring of a private function, and fix... > * `#8750 `__: DOC clarified > description of norminvgauss in scipy.stats > * `#8753 `__: DOC: signal: Fix > a plot title in the chirp docstring. > * `#8755 `__: DOC: MAINT: Fix > link to the wheel documentation in developer... > * `#8760 `__: BUG: stats: > boltzmann wasn't setting the upper bound. > * `#8763 `__: [DOC] Improved > scipy.cluster.hierarchy documentation > * `#8765 `__: DOC: added > example for scipy.stat.mstats.tmin > * `#8788 `__: DOC: fix > definition of optional `disp` parameter > * `#8802 `__: MAINT: Suppress > dd_real unused function compiler warnings. > * `#8803 `__: ENH: Add > full_output support to optimize.newton() > * `#8804 `__: MAINT: stats > cleanup > * `#8808 `__: DOC: add note > about isinstance for frozen rvs > * `#8812 `__: Updated numpydoc > submodule > * `#8813 `__: MAINT: stats: Fix > multinomial docstrings, and do some clean up. > * `#8816 `__: BUG: fixed _stats > of t-distribution in scipy.stats > * `#8817 `__: BUG: ndimage: Fix > validation of the origin argument in correlate... > * `#8822 `__: BUG: integrate: > Fix crash with repeated t values in odeint. > * `#8832 `__: Hyperlink DOIs > against preferred resolver > * `#8837 `__: BUG: sparse: > Ensure correct dtype for sparse comparison operations. > * `#8839 `__: DOC: stats: A few > tweaks to the linregress docstring. > * `#8846 `__: BUG: stats: Fix > logpdf method of invwishart. > * `#8849 `__: DOC: signal: > Fixed mistake in the firwin docstring. > * `#8854 `__: DOC: fix type > descriptors in ltisys documentation > * `#8865 `__: Fix tiny typo in > docs for chi2 pdf > * `#8870 `__: Fixes related to > invertibility of STFT > * `#8872 `__: ENH: special: Add > the softmax function > * `#8874 `__: DOC correct gamma > function in docstrings in scipy.stats > * `#8876 `__: ENH: Added TOMS > Algorithm 748 as 1-d root finder; 17 test function... > * `#8882 `__: ENH: Only use > Halley's adjustment to Newton if close enough. > * `#8883 `__: FIX: optimize: > make jac and hess truly optional for 'trust-constr' > * `#8885 `__: TST: Do not error > on warnings raised about non-tuple indexing. > * `#8887 `__: MAINT: filter out > np.matrix PendingDeprecationWarning's in numpy... > * `#8889 `__: DOC: optimize: > separate legacy interfaces from new ones > * `#8890 `__: ENH: Add > optimize.root_scalar() as a universal dispatcher for... > * `#8899 `__: DCT-IV, DST-IV > and DCT-I, DST-I orthonormalization support in... > * `#8901 `__: MAINT: Reorganize > flapack.pyf.src file > * `#8907 `__: BUG: ENH: Check > if guess for newton is already zero before checking... > * `#8908 `__: ENH: Make sorting > optional for cKDTree.query_ball_point() > * `#8910 `__: DOC: > sparse.csgraph simple examples. > * `#8914 `__: DOC: interpolate: > fix equivalences of string aliases > * `#8918 `__: add > float_control(precise, on) to _fpumode.c > * `#8919 `__: MAINT: > interpolate: improve error messages for common `bc_type`... > * `#8920 `__: DOC: update > Contributing to SciPy to say "prefer no PEP8 only... > * `#8924 `__: MAINT: special: > deprecate `hyp2f0`, `hyp1f2`, and `hyp3f0` > * `#8927 `__: MAINT: special: > remove `errprint` > * `#8932 `__: Fix broadcasting > scale arg of entropy > * `#8936 `__: Fix (some) > non-tuple index warnings > * `#8937 `__: ENH: implement > sparse matrix BSR to CSR conversion directly. > * `#8938 `__: DOC: add > @_ni_docstrings.docfiller in ndimage.rotate > * `#8940 `__: Update > _discrete_distns.py > * `#8943 `__: DOC: Finish > dangling sentence in `convolve` docstring > * `#8944 `__: MAINT: Address > tuple indexing and warnings > * `#8945 `__: ENH: > spatial.transform.Rotation [GSOC2018] > * `#8950 `__: csgraph Dijkstra > function description rewording > * `#8953 `__: DOC, MAINT: HTTP > -> HTTPS, and other linkrot fixes > * `#8955 `__: BUG: np.int64 in > scipy.fftpack.next_fast_len > * `#8958 `__: MAINT: Add more > descriptive error message for phase one simplex. > * `#8962 `__: BUG: > sparse.linalg: add missing conjugate to _ScaledLinearOperator.adjoint > * `#8963 `__: BUG: > sparse.linalg: downgrade LinearOperator TypeError to warning > * `#8965 `__: ENH: Wrapped RFP > format and RZ decomposition routines > * `#8969 `__: MAINT: doc and > code fixes for optimize.newton > * `#8970 `__: Added 'average' > keyword for welch/csd to enable median averaging > * `#8971 `__: Better imresize > deprecation warning > * `#8972 `__: MAINT: Switch > np.where(c) for np.nonzero(c) > * `#8975 `__: MAINT: Fix > warning-based failures > * `#8979 `__: DOC: fix > description of count_sort keyword of dendrogram > * `#8982 `__: MAINT: optimize: > Fixed minor mistakes in test_linprog.py (#8978) > * `#8984 `__: BUG: > sparse.linalg: ensure expm casts integer inputs to float > * `#8986 `__: BUG: > optimize/slsqp: do not exit with convergence on steps where... > * `#8989 `__: MAINT: use > collections.abc in basinhopping > * `#8990 `__: ENH extend > p-values of anderson_ksamp in scipy.stats > * `#8991 `__: ENH: Weighted kde > * `#8993 `__: ENH: > spatial.transform.Rotation.random [GSOC 2018] > * `#8994 `__: ENH: > spatial.transform.Slerp [GSOC 2018] > * `#8995 `__: TST: time.time in > test > * `#9007 `__: Fix typo in > fftpack.rst > * `#9013 `__: Added correct > plotting code for two sided output from spectrogram > * `#9014 `__: BUG: > differential_evolution with inf objective functions > * `#9017 `__: BUG: fixed #8446 > corner case for asformat(array|dense) > * `#9018 `__: MAINT: > _lib/ccallback: remove unused code > * `#9021 `__: BUG: Issue with > subspace_angles > * `#9022 `__: DOC: Added "See > Also" section to lombscargle docstring > * `#9034 `__: BUG: Fix > tolerance printing behavior, remove meaningless tol... > * `#9035 `__: TST: improve > signal.bsplines test coverage > * `#9037 `__: ENH: add a new > init method for k-means > * `#9039 `__: DOC: Add examples > to fftpack.irfft docstrings > * `#9048 `__: ENH: > scipy.sparse.random > * `#9050 `__: BUG: > scipy.io.hb_write: fails for matrices not in csc format > * `#9051 `__: MAINT: Fix slow > sparse.rand for k < mn/3 (#9036). > * `#9054 `__: MAINT: spatial: > Explicitly initialize LAPACK output parameters. > * `#9055 `__: DOC: Add examples > to scipy.special docstrings > * `#9056 `__: ENH: Use one > thread in OpenBLAS > * `#9059 `__: DOC: Update > README with link to Code of Conduct > * `#9060 `__: BLD: remove > support for the Bento build system. > * `#9062 `__: DOC add sections > to overview in scipy.stats > * `#9066 `__: BUG: Correct > "remez" error message > * `#9069 `__: DOC: update > linalg section of roadmap for LAPACK versions. > * `#9079 `__: MAINT: add > spatial.transform to refguide check; complete some... > * `#9081 `__: MAINT: Add > warnings if pivot value is close to tolerance in linprog(method='simplex') > * `#9084 `__: BUG fix incorrect > p-values of kurtosistest in scipy.stats > * `#9095 `__: DOC: add sections > to mstats overview in scipy.stats > * `#9096 `__: BUG: Add test for > Stackoverflow example from issue 8174. > * `#9101 `__: ENH: add Siegel > slopes (robust regression) to scipy.stats > * `#9105 `__: allow > resample_poly() to output float32 for float32 inputs. > * `#9112 `__: MAINT: optimize: > make trust-constr accept constraint dict (#9043) > * `#9118 `__: Add doc entry to > cholesky_banded > * `#9120 `__: eigsh > documentation parameters > * `#9125 `__: interpolative: > correctly reconstruct full rank matrices > * `#9126 `__: MAINT: Use > warnings for unexpected peak properties > * `#9129 `__: BUG: Do not catch > and silence KeyboardInterrupt > * `#9131 `__: DOC: Correct the > typo in scipy.optimize tutorial page > * `#9133 `__: FIX: Avoid use of > bare except > * `#9134 `__: DOC: Update of > 'return_eigenvectors' description > * `#9137 `__: DOC: typo fixes > for discrete Poisson tutorial > * `#9139 `__: FIX: Doctest > failure in optimize tutorial > * `#9143 `__: DOC: missing > sigma in Pearson r formula > * `#9145 `__: MAINT: Refactor > linear programming solvers > * `#9149 `__: FIX: Make > scipy.odr.ODR ifixx equal to its data.fix if given > * `#9156 `__: DOC: special: > Mention the sigmoid function in the expit docstring. > * `#9160 `__: Fixed a latex > delimiter error in levy() > * `#9170 `__: DOC: correction / > update of docstrings of distributions in scipy.stats > * `#9171 `__: better > description of the hierarchical clustering parameter > * `#9174 `__: domain check for > a < b in stats.truncnorm > * `#9175 `__: DOC: Minor > grammar fix > * `#9176 `__: BUG: > CloughTocher2DInterpolator: fix miscalculation at neighborless... > * `#9177 `__: BUILD: Document > the "clean" target in the doc/Makefile. > * `#9178 `__: MAINT: make > refguide-check more robust for printed numpy arrays > * `#9186 `__: MAINT: Remove > np.ediff1d occurence > * `#9188 `__: DOC: correct typo > in extending ndimage with C > * `#9190 `__: ENH: Support > specifying axes for fftconvolve > * `#9192 `__: MAINT: optimize: > fixed @pv style suggestions from #9112 > * `#9200 `__: Fix > make_interp_spline(..., k=0 or 1, axis<0) > * `#9201 `__: BUG: > sparse.linalg/gmres: use machine eps in breakdown check > * `#9204 `__: MAINT: fix up > stats.spearmanr and match mstats.spearmanr with... > * `#9206 `__: MAINT: include > benchmarks and dev files in sdist. > * `#9208 `__: TST: signal: bump > bsplines test tolerance for complex data > * `#9210 `__: TST: mark tests > as slow, fix missing random seed > * `#9211 `__: ENH: add > capability to specify orders in pade func > * `#9217 `__: MAINT: Include > ``success`` and ``nit`` in OptimizeResult returned... > * `#9222 `__: ENH: interpolate: > Use scipy.spatial.distance to speed-up Rbf > * `#9229 `__: MNT: Fix Fourier > filter double case > * `#9233 `__: BUG: > spatial/distance: fix pdist/cdist performance regression... > * `#9234 `__: FIX: Proper > suppression > * `#9235 `__: BENCH: > rationalize slow benchmarks + miscellaneous fixes > * `#9238 `__: BENCH: limit > number of parameter combinations in spatial.*KDTree... > * `#9239 `__: DOC: stats: Fix > LaTeX markup of a couple distribution PDFs. > * `#9241 `__: ENH: Evaluate > plateau size during peak finding > * `#9242 `__: ENH: stats: > Implement _ppf and _logpdf for crystalball, and do... > * `#9246 `__: DOC: Properly > render versionadded directive in HTML documentation > * `#9255 `__: DOC: mention > RootResults in optimization reference guide > * `#9260 `__: TST: relax some > tolerances so tests pass with x87 math > * `#9264 `__: TST Use > assert_raises "match" parameter instead of the "message"... > * `#9267 `__: DOC: clarify > expect() return val when moment is inf/nan > * `#9272 `__: DOC: Add > description of default bounds to linprog > * `#9277 `__: MAINT: > sparse/linalg: make test deterministic > * `#9278 `__: MAINT: > interpolate: pep8 cleanup in test_polyint > * `#9279 `__: Fixed docstring > for resample > * `#9280 `__: removed first > check for float in get_sum_dtype > * `#9281 `__: BUG: only accept > 1d input for bartlett / levene in scipy.stats > * `#9282 `__: MAINT: > dense_output and t_eval are mutually exclusive inputs > * `#9283 `__: MAINT: add docs > and do some cleanups in interpolate.Rbf > * `#9288 `__: Run > distance_transform_edt tests on all types > * `#9294 `__: DOC: fix the > formula typo > * `#9298 `__: MAINT: > optimize/trust-constr: restore .niter attribute for backward-compat > * `#9299 `__: DOC: > clarification of default rvs method in scipy.stats > * `#9301 `__: MAINT: removed > unused import sys > * `#9302 `__: MAINT: removed > unused imports > * `#9303 `__: DOC: signal: > Refer to fs instead of nyq in the firwin docstring. > * `#9305 `__: ENH: Added > Yeo-Johnson power transformation > * `#9306 `__: ENH - add dual > annealing > * `#9309 `__: ENH add the > yulesimon distribution to scipy.stats > * `#9317 `__: Nested SLSQP bug > fix. > * `#9320 `__: MAINT: stats: > avoid underflow in stats.geom.ppf > * `#9326 `__: Add example for > Rosenbrock function > * `#9332 `__: Sort file lists > * `#9340 `__: Fix typo in > find_peaks documentation > * `#9343 `__: MAINT Use np.full > when possible > * `#9344 `__: DOC: added > examples to docstring of dirichlet class > * `#9346 `__: DOC: Fix import > of scipy.sparse.linalg in example (#9345) > * `#9350 `__: Fix interpolate > read only > * `#9351 `__: MAINT: > special.erf: use the x->-x symmetry > * `#9356 `__: Fix documentation > typo > * `#9358 `__: DOC: improve doc > for ksone and kstwobign in scipy.stats > * `#9362 `__: DOC: Change > datatypes of A matrices in linprog > * `#9364 `__: MAINT: Adds > implicit none to fftpack fortran sources > * `#9369 `__: DOC: minor tweak > to CoC (updated NumFOCUS contact address). > * `#9373 `__: Fix exception if > python is called with -OO option > * `#9374 `__: FIX: AIX > compilation issue with NAN and INFINITY > * `#9376 `__: COBLYA -> COBYLA > in docs > * `#9377 `__: DOC: Add examples > integrate: fixed_quad and quadrature > * `#9379 `__: MAINT: TST: Make > tests NumPy 1.8 compatible > * `#9385 `__: CI: On Travis > matrix "OPTIMIZE=-OO" flag ignored > * `#9387 `__: Fix defaut value > for 'mode' in 'ndimage.shift' in the doc > * `#9392 `__: BUG: rank has to > be integer in rank_filter: fixed issue 9388 > * `#9399 `__: DOC: Misc. typos > * `#9400 `__: TST: stats: Fix > the expected r-value of a linregress test. > * `#9405 `__: BUG: np.hstack > does not accept generator expressions > * `#9408 `__: ENH: linalg: > Shorter ill-conditioned warning message > * `#9418 `__: DOC: Fix ndimage > docstrings and reduce doc build warnings > * `#9421 `__: DOC: Add missing > docstring examples in scipy.spatial > * `#9422 `__: DOC: Add an > example to integrate.newton_cotes > * `#9427 `__: BUG: Fixed defect > with maxiter #9419 in dual annealing > * `#9431 `__: BENCH: Add dual > annealing to scipy benchmark (see #9415) > * `#9435 `__: DOC: Add > docstring examples for stats.binom_test > * `#9443 `__: DOC: Fix the > order of indices in optimize tutorial > * `#9444 `__: MAINT: > interpolate: use operator.index for checking/coercing... > * `#9445 `__: DOC: Added > missing example to stats.mstats.kruskal > * `#9446 `__: DOC: Add note > about version changed for jaccard distance > * `#9447 `__: BLD: > version-script handling in setup.py > * `#9448 `__: TST: skip a > problematic linalg test > * `#9449 `__: TST: fix missing > seed in lobpcg test. > * `#9456 `__: TST: > test_eigs_consistency() now sorts output > > Checksums > ========= > > MD5 > ~~~ > > 0bb53a49e77bca11fb26698744c60f97 > scipy-1.2.0-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 39e215ac7e8d6de33d939486987dcba4 > scipy-1.2.0-cp27-cp27m-manylinux1_i686.whl > d6e33b2c05ffbcf9790628d656c8e61f > scipy-1.2.0-cp27-cp27m-manylinux1_x86_64.whl > a463a12d77b87df0a2d202323771a908 scipy-1.2.0-cp27-cp27m-win32.whl > 3dc17a11c7dd211ce51a338cfe30eb48 scipy-1.2.0-cp27-cp27m-win_amd64.whl > 82b1ecbecadfeddd2be1c6d616491029 > scipy-1.2.0-cp27-cp27mu-manylinux1_i686.whl > 65021ade783f1416b1920d2a2cc39d4d > scipy-1.2.0-cp27-cp27mu-manylinux1_x86_64.whl > 7cc2cdbc9b421ef10695b898cdc241e7 > scipy-1.2.0-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 2a4ccbfcccb9395fa7554a82db40e454 > scipy-1.2.0-cp34-cp34m-manylinux1_i686.whl > 662dc35acd6f588565cd6467465fc742 > scipy-1.2.0-cp34-cp34m-manylinux1_x86_64.whl > a19bd9969bb5b92595e82d924b8272f9 scipy-1.2.0-cp34-cp34m-win32.whl > 5f1eaa3745956db0da724f83dd174559 scipy-1.2.0-cp34-cp34m-win_amd64.whl > d32a4c31d0a188f3550c1306d20b03c7 > scipy-1.2.0-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 34f4a7f04abfda87fac8ab38a9a70a77 > scipy-1.2.0-cp35-cp35m-manylinux1_i686.whl > bd4d56910802870072e3c5ded69a8f08 > scipy-1.2.0-cp35-cp35m-manylinux1_x86_64.whl > cb3fb7ddd3992928f9173e4eb489d23e scipy-1.2.0-cp35-cp35m-win32.whl > 68f5ddcb6e592b1d9cba95f24faee7b5 scipy-1.2.0-cp35-cp35m-win_amd64.whl > c0e110f3a935731782c96a13cc264ea2 > scipy-1.2.0-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 9d898924498abbe2d26dd18b3413fb11 > scipy-1.2.0-cp36-cp36m-manylinux1_i686.whl > dd9ae664cbe7de54828d83c772e24da3 > scipy-1.2.0-cp36-cp36m-manylinux1_x86_64.whl > 8dea8432610bb3c63114eb6469c5f99a scipy-1.2.0-cp36-cp36m-win32.whl > ebda830aec7b60193772741f85fee28c scipy-1.2.0-cp36-cp36m-win_amd64.whl > 0e8b7a7908c50e635e639d2c69901140 > scipy-1.2.0-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 56719437a821f9f2f98f069225e70c87 > scipy-1.2.0-cp37-cp37m-manylinux1_i686.whl > 93d9d978855516ec38fa08620ef3443c > scipy-1.2.0-cp37-cp37m-manylinux1_x86_64.whl > fff3d66b877b6e6b9984b84ae9e4d76c scipy-1.2.0-cp37-cp37m-win32.whl > 3defb2c8b2f69057919ee3b0c92de65c scipy-1.2.0-cp37-cp37m-win_amd64.whl > e57011507865b0b702aff6077d412e03 scipy-1.2.0.tar.gz > 8eb6c1d7ceae0d06aef474f7801b8fca scipy-1.2.0.tar.xz > b0fb16b09319d3031d27ccf21a3ef474 scipy-1.2.0.zip > > SHA256 > ~~~~~~ > > d1ae77b79fd5e27a10ba7c4e7c3a62927b9d29a4dccf28f6905c25d983aaf183 > scipy-1.2.0-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 4b1f0883cb9d8ee963cf0a31c87341e9e758abb2cf1e5bcc0d7b066ef6b17573 > scipy-1.2.0-cp27-cp27m-manylinux1_i686.whl > c5eae911cf26b3c7eda889ec98d3c226f312c587acfaaf02602473f98b4c16d6 > scipy-1.2.0-cp27-cp27m-manylinux1_x86_64.whl > 58f0435f052cb60f1472c77f52a8f6642f8877b70559e5e0b9a1744f33f5cbe5 > scipy-1.2.0-cp27-cp27m-win32.whl > 4cce25c6e7ff7399c67dfe1b5423c36c391cf9b4b2be390c1675ab410f1ef503 > scipy-1.2.0-cp27-cp27m-win_amd64.whl > 02cb79ea38114dc480e9b08d6b87095728e8fb39b9a49b449ee443d678001611 > scipy-1.2.0-cp27-cp27mu-manylinux1_i686.whl > 7dc4002f0a0a688774ef04878afe769ecd1ac21fe9b4b1d7125e2cf16170afd3 > scipy-1.2.0-cp27-cp27mu-manylinux1_x86_64.whl > 7994c044bf659b0a24ad7673ec7db85c2fadb87e4980a379a9fd5b086fe3649a > scipy-1.2.0-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 72bd766f753fd32f072d30d7bc2ad492d56dbcbf3e13764e27635d5c41079339 > scipy-1.2.0-cp34-cp34m-manylinux1_i686.whl > 3132a9fab3f3545c8b0ba15688d11857efdd4a58d388d3785dc474f56fea7138 > scipy-1.2.0-cp34-cp34m-manylinux1_x86_64.whl > 7413080b381766a22d52814edb65631f0e323a7cea945c70021a672f38acc73f > scipy-1.2.0-cp34-cp34m-win32.whl > 6f791987899532305126309578727c0197bddbafab9596bafe3e7bfab6e1ce13 > scipy-1.2.0-cp34-cp34m-win_amd64.whl > 937147086e8b4338bf139ca8fa98da650e3a46bf2ca617f8e9dd68c3971ec420 > scipy-1.2.0-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 63e1d5ca9e5e1984f1a275276991b036e25d39d37dd7edbb3f4f6165c2da7dbb > scipy-1.2.0-cp35-cp35m-manylinux1_i686.whl > 03c827cdbc584e935264040b958e5fa0570a16095bee23a013482ba3f0e963a2 > scipy-1.2.0-cp35-cp35m-manylinux1_x86_64.whl > bc294841f6c822714af362095b181a853f47ed5ce757354bd2e4776d579ff3a4 > scipy-1.2.0-cp35-cp35m-win32.whl > cca33a01a5987c650b87a1a910aa311ffa44e67cca1ff502ef9efdae5d9a8624 > scipy-1.2.0-cp35-cp35m-win_amd64.whl > 8608316d0cc01f8b25111c8adfe6efbc959cbba037a62c784551568d7ffbf280 > scipy-1.2.0-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > fb36064047e6bf87b6320a9b6eb7f525ef6863c7a4aef1a84a4bbfb043612617 > scipy-1.2.0-cp36-cp36m-manylinux1_i686.whl > 854bd87cc23824d5db4983956bc30f3790e1c7448f1a9e6a8fb7bff7601aef87 > scipy-1.2.0-cp36-cp36m-manylinux1_x86_64.whl > fc1a19d95649439dbd50baca676bceb29bbfcd600aed2c5bd71d9bad82a87cfe > scipy-1.2.0-cp36-cp36m-win32.whl > 8f5fcc87b48fc3dd6d901669c89af4feeb856dffb6f671539a238b7e8af1799c > scipy-1.2.0-cp36-cp36m-win_amd64.whl > bc6a88b0009a1b60eab5c22ac3a006f6968d6328de10c6a64ebb0d64a05548d3 > scipy-1.2.0-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl > 64b2c35824da3ef6bb1e722216e4ef28802af6413c7586136500e343d34ba179 > scipy-1.2.0-cp37-cp37m-manylinux1_i686.whl > 78a67ee4845440e81cfbfabde20537ca12051d0eeac951fe4c6d8751feac3103 > scipy-1.2.0-cp37-cp37m-manylinux1_x86_64.whl > 04f2b23258139c109d0524f111597dd095a505d9cb2c71e381d688d653877fa3 > scipy-1.2.0-cp37-cp37m-win32.whl > 5706b785ca289fdfd91aa05066619e51d140613b613e35932601f2315f5d8470 > scipy-1.2.0-cp37-cp37m-win_amd64.whl > 51a2424c8ed80e60bdb9a896806e7adaf24a58253b326fbad10f80a6d06f2214 > scipy-1.2.0.tar.gz > 1cfafc64e1c1c0b6d040d35780ba06f01e9cb44f3bacd8f33a5df6efe5a144a6 > scipy-1.2.0.tar.xz > 5b3d4b1654b4723431ad7f47b4556498a86a53d2fdb86e85a45c3da0c2a72a4b > scipy-1.2.0.zip > -----BEGIN PGP SIGNATURE----- > > iQIzBAEBCAAdFiEEgfAqrOuERrV4fwr6XCLdIy4FKasFAlwYY1YACgkQXCLdIy4F > KauihhAAo0fk+a4U4ilFXeZrUTuZTeqqHtD60yV8Z2pZvqQyH1BBP8BKksV/v3bP > 6ckl+upWaolMjZgehWhAKyGgE2oUHDu6RxaRS97Kbbns580M+wWduPX7kjf7OKoX > KFX1a8/GlBWTQKIMj6P2oShT7rvYB+WABvyoTxXKbHG0/ArOtOqqAYJFKLeOYB6m > o0+qajqt9syV2iqBFlHnrPKQ8qjtfPxqCP9KHhNIbHd17305YwJc58CBhpulIjaP > HIhJOuP7xigELX9yCzJ2qFGBjTd2HNvBQWIRjNDfbox6mhWO4no30c+OamG3MAr7 > n9TDzSIjxkRedvBzMRJwA/Q5/Mou/R16BF+ZzvCVZnp/h6LrXQg4ENfR304Byyy3 > NlYzmQKlV0XvP4oYewBnLfq6hcXAum7rf3L8ene8mu0OWJumW7Yr6PWfDNECDKvX > sPWSwkNu01Pzg/KUUkrS9w6m9bZTj4UP15L2Z8JSVdp/wxCHGh8txJWjOenoZBnD > BPyitzsgbuW+pd7+WmjZoJpr8QjL/Uw8vpUwlvKAvvVfFnVeVh3X1awK+D6iba69 > LbyfhOG3R846WkxHh458uvNxmYUbm6sqaZ7lzY91bD8z61jS6PCvpR8BJcwmpP7Y > q/duWsaakRWLe35CE8KuvKCgVFhhStX2sZ/hRkNsvm2/hEAtNW0= > =3Enc > -----END PGP SIGNATURE----- > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > -------------- next part -------------- An HTML attachment was scrubbed... URL: From einstein.edison at gmail.com Wed Dec 19 10:49:41 2018 From: einstein.edison at gmail.com (Hameer Abbasi) Date: Wed, 19 Dec 2018 16:49:41 +0100 Subject: [SciPy-Dev] ANN: PyData/Sparse 0.6.0 Message-ID: Hi everyone, Apologies in advance for the cross-post. On behalf of all the contributors, I?m pleased to announce that PyData/Sparse 0.6.0 has been released. The wheel is up on PyPI and the conda-forge package should be up before the end of the day. The wheels and sources can be found at: https://github.com/pydata/sparse/releases/tag/0.6.0 https://pypi.org/project/sparse/#files The documentation for this package is available at http://sparse.pydata.org/en/0.6.0/ This is mainly a bug-fix release. The changelog can be found at: http://sparse.pydata.org/en/latest/changelog.html The main highlight is that we changed the default behaviour to raise an exception when using functions meant for NumPy arrays which would densify the array. This is also configurable via the SPARSE_AUTO_DENSIFY environment variable before importing the module. Best Regards, Hameer Abbasi -------------- next part -------------- An HTML attachment was scrubbed... URL: From einstein.edison at gmail.com Wed Dec 19 10:50:25 2018 From: einstein.edison at gmail.com (Hameer Abbasi) Date: Wed, 19 Dec 2018 16:50:25 +0100 Subject: [SciPy-Dev] PyData/Sparse Webinar Hosted by Quansight In-Reply-To: <86bc8939-f6b0-4878-ab02-b28d8d016ade@Canary> References: <86bc8939-f6b0-4878-ab02-b28d8d016ade@Canary> Message-ID: This is just a reminder that the webinar starts in little over an hour. Best Regards, Hameer Abbasi > On Friday, Dec 14, 2018 at 11:06 PM, Hameer Abbasi wrote: > Hello, everyone! > > I?ll be speaking about PyData/Sparse in a webinar hosted by Quansight. It?ll include a project demo, in case you?re interested, as well as the directions the project can take. You can register for the webinar at https://app.livestorm.co/quansight/ > > Best Regards, > Hameer Abbasi > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From einstein.edison at gmail.com Wed Dec 19 16:22:01 2018 From: einstein.edison at gmail.com (Hameer Abbasi) Date: Wed, 19 Dec 2018 22:22:01 +0100 Subject: [SciPy-Dev] PyData/Sparse Webinar Hosted by Quansight In-Reply-To: References: <86bc8939-f6b0-4878-ab02-b28d8d016ade@Canary> Message-ID: <790ef551-b2a5-4c71-915f-1ec7fdda259f@Canary> Hello everyone! In case you missed it here?s the recording for the webinar. https://www.youtube.com/watch?v=AtVZX9EPZmM Best Regards, Hameer Abbasi > On Wednesday, Dec 19, 2018 at 4:50 PM, Hameer Abbasi wrote: > This is just a reminder that the webinar starts in little over an hour. > > Best Regards, > Hameer Abbasi > > > > On Friday, Dec 14, 2018 at 11:06 PM, Hameer Abbasi wrote: > > Hello, everyone! > > > > I?ll be speaking about PyData/Sparse in a webinar hosted by Quansight. It?ll include a project demo, in case you?re interested, as well as the directions the project can take. You can register for the webinar at https://app.livestorm.co/quansight/ > > > > Best Regards, > > Hameer Abbasi > > > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From charlesr.harris at gmail.com Thu Dec 20 11:16:50 2018 From: charlesr.harris at gmail.com (Charles R Harris) Date: Thu, 20 Dec 2018 09:16:50 -0700 Subject: [SciPy-Dev] NumPy 1.16.0rc1 released Message-ID: Hi All, On behalf of the NumPy team I'm pleased to announce the release of NumPy 1.16.0rc1. This is the last NumPy release to support Python 2.7 and will be maintained as a long term release with bug fixes until 2020. This release has seen a lot of refactoring and features many bug fixes, improved code organization, and better cross platform compatibility. Not all of these improvements will be visible to users, but they should help make maintenance easier going forward. Highlights are - Experimental support for overriding numpy functions in downstream projects. - The matmul function is now a ufunc and can be overridden using __array_ufunc__. - Improved support for the ARM and POWER architectures. - Improved support for AIX and PyPy. - Improved interoperation with ctypes. - Improved support for PEP 3118. The supported Python versions are 2.7 and 3.5-3.7, support for 3.4 has been dropped. The wheels on PyPI are linked with OpenBLAS v0.3.4+, which should fix the known threading issues found in previous OpenBLAS versions. Downstream developers building this release should use Cython >= 0.29 and, if linking OpenBLAS, OpenBLAS > v0.3.4. Wheels for this release can be downloaded from PyPI , source archives are available from Github . *Contributors* A total of 111 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Alan Fontenot + - Allan Haldane - Alon Hershenhorn + - Alyssa Quek + - Andreas Nussbaumer + - Anner + - Anthony Sottile + - Antony Lee - Ayappan P + - Bas van Schaik + - C.A.M. Gerlach + - Charles Harris - Chris Billington - Christian Clauss - Christoph Gohlke - Christopher Pezley + - Daniel B Allan + - Daniel Smith - Dawid Zych + - Derek Kim + - Dima Pasechnik + - Edgar Giovanni Lepe + - Elena Mokeeva + - Elliott Sales de Andrade + - Emil Hessman + - Eric Schles + - Eric Wieser - Giulio Benetti + - Guillaume Gautier + - Guo Ci - Heath Henley + - Isuru Fernando + - J. Lewis Muir + - Jack Vreeken + - Jaime Fernandez - James Bourbeau - Jeff VanOss - Jeffrey Yancey + - Jeremy Chen + - Jeremy Manning + - Jeroen Demeyer - John Darbyshire + - John Zwinck - Jonas Jensen + - Joscha Reimer + - Juan Azcarreta + - Julian Taylor - Kevin Sheppard - Krzysztof Chomski + - Kyle Sunden - Lars Gr?ter - 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 Brum? + - Moshe Looks + - Muhammad Kasim + - Nathaniel J. Smith - Nikita Titov + - Paul M?ller + - Paul van Mulbregt - Pauli Virtanen - Pierre Glaser + - Pim de Haan - Ralf Gommers - Robert Kern - Robin Aggleton + - Rohit Pandey + - Roman Yurchak + - Ryan Soklaski - Sebastian Berg - Sho Nakamura + - Simon Gibbons - Stan Seibert + - Stefan Otte - Stefan van der Walt - Stephan Hoyer - Stuart Archibald - Taylor Smith + - Tim Felgentreff + - Tim Swast + - Tim Teichmann + - Toshiki Kataoka - Travis Oliphant - Tyler Reddy - Uddeshya Singh + - Warren Weckesser - Weitang Li + - Wenjamin Petrenko + - William D. Irons - Yannick Jadoul + - Yaroslav Halchenko - Yug Khanna + - Yuji Kanagawa + - Yukun Guo + - lerbuke + - @ankokumoyashi + Cheers, Charles Harris -------------- next part -------------- An HTML attachment was scrubbed... URL: From ralf.gommers at gmail.com Sat Dec 22 18:55:57 2018 From: ralf.gommers at gmail.com (Ralf Gommers) Date: Sat, 22 Dec 2018 15:55:57 -0800 Subject: [SciPy-Dev] fiscal sponsorship agreement with NumFOCUS Message-ID: Hi all, To start with the idea: I propose that SciPy applies for comprehensive project sponsorship with NumFOCUS, and sign a fiscal sponsorship agreement (FSA) to that effect. Why? ---- We're already an "affiliated project", which lets us participate in the small development grants program, the NumFOCUS project mailing list and Slack channel, and a few other benefits. The main difference that comprehensive sponsorship will make is that it will allow us to accept donations, grants and other kinds of funding as a project. In addition we get funding for a representative of the project to attend the yearly NumFOCUS Summit, some hours of high-quality legal help in case we need that (for example in case of licensing questions), and probably a few other things that I'm forgetting right now. NumFOCUS sets a higher bar for comprehensive sponsorship than for affiliation, but we should easily clear that bar. We'll be joining most other core scientific Python projects, who are already sponsored [1]. I'll also steal some language from Nathaniel when he made the same proposal for NumPy [2]: The basic idea here is that there are times when you really need some kind of corporation to represent the project -- the legal system for better or worse does not understand "a bunch of folks on a mailing list" as a legal entity capable of accepting donations, or holding funds or other assets like domain names. The obvious solution is to incorporate a company to represent the project -- but incorporating a company involves lots of super-annoying paperwork. (Like, *super* annoying.) So a standard trick is that a single non-profit corporation acts as an umbrella organization providing these services to multiple projects at once, and this is called "fiscal sponsorship". You can read more about it here: https://en.wikipedia.org/wiki/Fiscal_sponsorship How? ---- We form a subcommittee of 5 people that will sign the sponsorship agreement. Those people mostly should be part of the SciPy Steering Council; there can be an external member. The job of that group is basically to interface with NumFOCUS (in practice there will be 1-2 people as first contacts), and to ensure that if we use funds, that they are used in agreement with the mission and nonprofit status of NumFOCUS. Once we have those 5 people, we can send in a formal application. In practice that takes very little time - probably no more than an hour per year, except for the 1-2 first contacts (they get 1-2 emails per month that need responding to). For more background and details on the how and why, see https://numfocus.org/information-fiscal-sponsorship. Thoughts? Questions? Volunteers to be on the subcommittee? Cheers, Ralf [1] https://numfocus.org/sponsored-projects [2] https://mail.python.org/pipermail/numpy-discussion/2015-October/073889.html -------------- next part -------------- An HTML attachment was scrubbed... URL: From larson.eric.d at gmail.com Sun Dec 23 00:07:48 2018 From: larson.eric.d at gmail.com (Eric Larson) Date: Sun, 23 Dec 2018 00:07:48 -0500 Subject: [SciPy-Dev] fiscal sponsorship agreement with NumFOCUS In-Reply-To: References: Message-ID: Thanks for the detailed explanation. Sounds like a great idea. I'd be happy to be on the subcommittee. Eric On Sat, Dec 22, 2018, 18:56 Ralf Gommers Hi all, > > To start with the idea: I propose that SciPy applies for comprehensive > project sponsorship with NumFOCUS, and sign a fiscal sponsorship agreement > (FSA) to that effect. > > Why? > ---- > We're already an "affiliated project", which lets us participate in the > small development grants program, the NumFOCUS project mailing list and > Slack channel, and a few other benefits. The main difference that > comprehensive sponsorship will make is that it will allow us to accept > donations, grants and other kinds of funding as a project. In addition we > get funding for a representative of the project to attend the yearly > NumFOCUS Summit, some hours of high-quality legal help in case we need that > (for example in case of licensing questions), and probably a few other > things that I'm forgetting right now. NumFOCUS sets a higher bar for > comprehensive sponsorship than for affiliation, but we should easily clear > that bar. We'll be joining most other core scientific Python projects, who > are already sponsored [1]. > > I'll also steal some language from Nathaniel when he made the same > proposal for NumPy [2]: > The basic idea here is that there are times when you really need some kind > of corporation to represent the project -- the legal system for better or > worse does not understand "a bunch of folks on a mailing list" as a legal > entity capable of accepting donations, or holding funds or other assets > like domain names. The obvious solution is to incorporate a company to > represent the project -- but incorporating a company involves lots of > super-annoying paperwork. (Like, *super* > annoying.) So a standard trick is that a single non-profit corporation > acts as an umbrella organization providing these services to multiple > projects at once, and this is called "fiscal sponsorship". You can read > more about it here: https://en.wikipedia.org/wiki/Fiscal_sponsorship > > How? > ---- > We form a subcommittee of 5 people that will sign the sponsorship > agreement. Those people mostly should be part of the SciPy Steering > Council; there can be an external member. The job of that group is > basically to interface with NumFOCUS (in practice there will be 1-2 people > as first contacts), and to ensure that if we use funds, that they are used > in agreement with the mission and nonprofit status of NumFOCUS. Once we > have those 5 people, we can send in a formal application. In practice that > takes very little time - probably no more than an hour per year, except for > the 1-2 first contacts (they get 1-2 emails per month that need responding > to). > > For more background and details on the how and why, see > https://numfocus.org/information-fiscal-sponsorship. > > Thoughts? Questions? Volunteers to be on the subcommittee? > > Cheers, > Ralf > > > [1] https://numfocus.org/sponsored-projects > [2] > https://mail.python.org/pipermail/numpy-discussion/2015-October/073889.html > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > -------------- next part -------------- An HTML attachment was scrubbed... URL: From haberland at ucla.edu Sun Dec 23 13:17:33 2018 From: haberland at ucla.edu (Matt Haberland) Date: Sun, 23 Dec 2018 10:17:33 -0800 Subject: [SciPy-Dev] fiscal sponsorship agreement with NumFOCUS In-Reply-To: References: Message-ID: Thanks, Ralf. I'd like to volunteer, too. On Sat, Dec 22, 2018 at 9:09 PM Eric Larson wrote: > Thanks for the detailed explanation. Sounds like a great idea. I'd be > happy to be on the subcommittee. > > Eric > > On Sat, Dec 22, 2018, 18:56 Ralf Gommers >> Hi all, >> >> To start with the idea: I propose that SciPy applies for comprehensive >> project sponsorship with NumFOCUS, and sign a fiscal sponsorship agreement >> (FSA) to that effect. >> >> Why? >> ---- >> We're already an "affiliated project", which lets us participate in the >> small development grants program, the NumFOCUS project mailing list and >> Slack channel, and a few other benefits. The main difference that >> comprehensive sponsorship will make is that it will allow us to accept >> donations, grants and other kinds of funding as a project. In addition we >> get funding for a representative of the project to attend the yearly >> NumFOCUS Summit, some hours of high-quality legal help in case we need that >> (for example in case of licensing questions), and probably a few other >> things that I'm forgetting right now. NumFOCUS sets a higher bar for >> comprehensive sponsorship than for affiliation, but we should easily clear >> that bar. We'll be joining most other core scientific Python projects, who >> are already sponsored [1]. >> >> I'll also steal some language from Nathaniel when he made the same >> proposal for NumPy [2]: >> The basic idea here is that there are times when you really need some >> kind of corporation to represent the project -- the legal system for >> better or worse does not understand "a bunch of folks on a mailing list" as >> a legal entity capable of accepting donations, or holding funds or other >> assets like domain names. The obvious solution is to incorporate a company >> to represent the project -- but incorporating a company involves lots of >> super-annoying paperwork. (Like, *super* >> annoying.) So a standard trick is that a single non-profit corporation >> acts as an umbrella organization providing these services to multiple >> projects at once, and this is called "fiscal sponsorship". You can read >> more about it here: https://en.wikipedia.org/wiki/Fiscal_sponsorship >> >> How? >> ---- >> We form a subcommittee of 5 people that will sign the sponsorship >> agreement. Those people mostly should be part of the SciPy Steering >> Council; there can be an external member. The job of that group is >> basically to interface with NumFOCUS (in practice there will be 1-2 people >> as first contacts), and to ensure that if we use funds, that they are used >> in agreement with the mission and nonprofit status of NumFOCUS. Once we >> have those 5 people, we can send in a formal application. In practice that >> takes very little time - probably no more than an hour per year, except for >> the 1-2 first contacts (they get 1-2 emails per month that need responding >> to). >> >> For more background and details on the how and why, see >> https://numfocus.org/information-fiscal-sponsorship. >> >> Thoughts? Questions? Volunteers to be on the subcommittee? >> >> Cheers, >> Ralf >> >> >> [1] https://numfocus.org/sponsored-projects >> [2] >> https://mail.python.org/pipermail/numpy-discussion/2015-October/073889.html >> _______________________________________________ >> SciPy-Dev mailing list >> SciPy-Dev at python.org >> https://mail.python.org/mailman/listinfo/scipy-dev >> > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > -- Matt Haberland Assistant Adjunct Professor in the Program in Computing Department of Mathematics 6617A Math Sciences Building, UCLA -------------- next part -------------- An HTML attachment was scrubbed... URL: From ilhanpolat at gmail.com Sun Dec 23 16:07:03 2018 From: ilhanpolat at gmail.com (Ilhan Polat) Date: Sun, 23 Dec 2018 22:07:03 +0100 Subject: [SciPy-Dev] GitHub services are deprecated - switch to app/webhook Message-ID: As of 31-jan-2019 github will stop the services hence Travis CI runs are affected from this. https://developer.github.com/changes/2018-04-25-github-services-deprecation/ At the same time Travis is moving from .org to .com with renewed service which provides the App and `checks` functionality. https://docs.travis-ci.com/user/legacy-services-to-github-apps-migration-guide/ I don't know if SciPy is eligible for automigration but can be as easy as clicking a button if it is so. Since this is only for the admin/owner access level users, gentle reminder about this detail. -------------- next part -------------- An HTML attachment was scrubbed... URL: From einstein.edison at gmail.com Sun Dec 23 16:55:18 2018 From: einstein.edison at gmail.com (Hameer Abbasi) Date: Sun, 23 Dec 2018 22:55:18 +0100 Subject: [SciPy-Dev] GitHub services are deprecated - switch to app/webhook In-Reply-To: References: Message-ID: It seems migration has been pushed back, see: https://docs.travis-ci.com/user/open-source-on-travis-ci-com/#existing-open-source-repositories-on-travis-ciorg Best Regards, Hameer Abbasi > On Sunday, Dec 23, 2018 at 10:07 PM, Ilhan Polat wrote: > As of 31-jan-2019 github will stop the services hence Travis CI runs are affected from this. https://developer.github.com/changes/2018-04-25-github-services-deprecation/ > > At the same time Travis is moving from .org to .com with renewed service which provides the App and `checks` functionality. https://docs.travis-ci.com/user/legacy-services-to-github-apps-migration-guide/ I don't know if SciPy is eligible for automigration but can be as easy as clicking a button if it is so. > > Since this is only for the admin/owner access level users, gentle reminder about this detail. > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev -------------- next part -------------- An HTML attachment was scrubbed... URL: From njs at pobox.com Sun Dec 23 17:45:52 2018 From: njs at pobox.com (Nathaniel Smith) Date: Sun, 23 Dec 2018 14:45:52 -0800 Subject: [SciPy-Dev] GitHub services are deprecated - switch to app/webhook In-Reply-To: References: Message-ID: It's really unclear what's going on here ? Github is saying that you have to migrate, but Travis is saying that you can't migrate, and there haven't been any updates for months now. This isn't specific to scipy; every project using Travis is in the same position. I can only assume there are people at both companies holding panicked conference calls. I don't think there's anything we can do except wait for Github/Travis to get their act together and tell us what's happening. -n -------------- next part -------------- An HTML attachment was scrubbed... URL: From evgeny.burovskiy at gmail.com Sun Dec 23 18:01:00 2018 From: evgeny.burovskiy at gmail.com (Evgeni Burovski) Date: Mon, 24 Dec 2018 02:01:00 +0300 Subject: [SciPy-Dev] fiscal sponsorship agreement with NumFOCUS In-Reply-To: References: Message-ID: Hi Ralf, Great idea, thanks for pushing it through! Count me in for the subcommittee. Cheers, Evgeni On Sun, Dec 23, 2018 at 9:18 PM Matt Haberland wrote: > > Thanks, Ralf. I'd like to volunteer, too. > > On Sat, Dec 22, 2018 at 9:09 PM Eric Larson wrote: >> >> Thanks for the detailed explanation. Sounds like a great idea. I'd be happy to be on the subcommittee. >> >> Eric >> >> On Sat, Dec 22, 2018, 18:56 Ralf Gommers >> >>> Hi all, >>> >>> To start with the idea: I propose that SciPy applies for comprehensive project sponsorship with NumFOCUS, and sign a fiscal sponsorship agreement (FSA) to that effect. >>> >>> Why? >>> ---- >>> We're already an "affiliated project", which lets us participate in the small development grants program, the NumFOCUS project mailing list and Slack channel, and a few other benefits. The main difference that comprehensive sponsorship will make is that it will allow us to accept donations, grants and other kinds of funding as a project. In addition we get funding for a representative of the project to attend the yearly NumFOCUS Summit, some hours of high-quality legal help in case we need that (for example in case of licensing questions), and probably a few other things that I'm forgetting right now. NumFOCUS sets a higher bar for comprehensive sponsorship than for affiliation, but we should easily clear that bar. We'll be joining most other core scientific Python projects, who are already sponsored [1]. >>> >>> I'll also steal some language from Nathaniel when he made the same proposal for NumPy [2]: >>> The basic idea here is that there are times when you really need some kind of corporation to represent the project -- the legal system for better or worse does not understand "a bunch of folks on a mailing list" as a legal entity capable of accepting donations, or holding funds or other assets like domain names. The obvious solution is to incorporate a company to represent the project -- but incorporating a company involves lots of super-annoying paperwork. (Like, *super* >>> annoying.) So a standard trick is that a single non-profit corporation acts as an umbrella organization providing these services to multiple projects at once, and this is called "fiscal sponsorship". You can read more about it here: https://en.wikipedia.org/wiki/Fiscal_sponsorship >>> >>> How? >>> ---- >>> We form a subcommittee of 5 people that will sign the sponsorship agreement. Those people mostly should be part of the SciPy Steering Council; there can be an external member. The job of that group is basically to interface with NumFOCUS (in practice there will be 1-2 people as first contacts), and to ensure that if we use funds, that they are used in agreement with the mission and nonprofit status of NumFOCUS. Once we have those 5 people, we can send in a formal application. In practice that takes very little time - probably no more than an hour per year, except for the 1-2 first contacts (they get 1-2 emails per month that need responding to). >>> >>> For more background and details on the how and why, see https://numfocus.org/information-fiscal-sponsorship. >>> >>> Thoughts? Questions? Volunteers to be on the subcommittee? >>> >>> Cheers, >>> Ralf >>> >>> >>> [1] https://numfocus.org/sponsored-projects >>> [2] https://mail.python.org/pipermail/numpy-discussion/2015-October/073889.html >>> _______________________________________________ >>> SciPy-Dev mailing list >>> SciPy-Dev at python.org >>> https://mail.python.org/mailman/listinfo/scipy-dev >> >> _______________________________________________ >> SciPy-Dev mailing list >> SciPy-Dev at python.org >> https://mail.python.org/mailman/listinfo/scipy-dev > > > > -- > Matt Haberland > Assistant Adjunct Professor in the Program in Computing > Department of Mathematics > 6617A Math Sciences Building, UCLA > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev From einstein.edison at gmail.com Mon Dec 24 05:23:31 2018 From: einstein.edison at gmail.com (Hameer Abbasi) Date: Mon, 24 Dec 2018 11:23:31 +0100 Subject: [SciPy-Dev] GitHub services are deprecated - switch to app/webhook In-Reply-To: References: Message-ID: <1458cd31-8f37-4415-ba13-6d1b30b0b951@Canary> If it helps, I just tried the follow the docs in the first message in this thread for PyData/Sparse, and it wouldn?t let me activate the repo on .com, saying it was already active on .org. You can see the discussion here: https://github.com/pydata/sparse/issues/224 Best Regards, Hameer Abbasi > On Sunday, Dec 23, 2018 at 11:47 PM, Nathaniel Smith wrote: > It's really unclear what's going on here ? Github is saying that you have to migrate, but Travis is saying that you can't migrate, and there haven't been any updates for months now. This isn't specific to scipy; every project using Travis is in the same position. I can only assume there are people at both companies holding panicked conference calls. I don't think there's anything we can do except wait for Github/Travis to get their act together and tell us what's happening. > > -n _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev -------------- next part -------------- An HTML attachment was scrubbed... URL: From ilhanpolat at gmail.com Mon Dec 24 06:27:16 2018 From: ilhanpolat at gmail.com (Ilhan Polat) Date: Mon, 24 Dec 2018 12:27:16 +0100 Subject: [SciPy-Dev] fiscal sponsorship agreement with NumFOCUS In-Reply-To: References: Message-ID: So nice to see this kind of structure coming through! I'm not in the steering committee but I can help if need be. On Mon, Dec 24, 2018 at 12:02 AM Evgeni Burovski wrote: > Hi Ralf, > > Great idea, thanks for pushing it through! > Count me in for the subcommittee. > > Cheers, > > Evgeni > > On Sun, Dec 23, 2018 at 9:18 PM Matt Haberland wrote: > > > > Thanks, Ralf. I'd like to volunteer, too. > > > > On Sat, Dec 22, 2018 at 9:09 PM Eric Larson > wrote: > >> > >> Thanks for the detailed explanation. Sounds like a great idea. I'd be > happy to be on the subcommittee. > >> > >> Eric > >> > >> On Sat, Dec 22, 2018, 18:56 Ralf Gommers >>> > >>> Hi all, > >>> > >>> To start with the idea: I propose that SciPy applies for comprehensive > project sponsorship with NumFOCUS, and sign a fiscal sponsorship agreement > (FSA) to that effect. > >>> > >>> Why? > >>> ---- > >>> We're already an "affiliated project", which lets us participate in > the small development grants program, the NumFOCUS project mailing list and > Slack channel, and a few other benefits. The main difference that > comprehensive sponsorship will make is that it will allow us to accept > donations, grants and other kinds of funding as a project. In addition we > get funding for a representative of the project to attend the yearly > NumFOCUS Summit, some hours of high-quality legal help in case we need that > (for example in case of licensing questions), and probably a few other > things that I'm forgetting right now. NumFOCUS sets a higher bar for > comprehensive sponsorship than for affiliation, but we should easily clear > that bar. We'll be joining most other core scientific Python projects, who > are already sponsored [1]. > >>> > >>> I'll also steal some language from Nathaniel when he made the same > proposal for NumPy [2]: > >>> The basic idea here is that there are times when you really need some > kind of corporation to represent the project -- the legal system for > better or worse does not understand "a bunch of folks on a mailing list" as > a legal entity capable of accepting donations, or holding funds or other > assets like domain names. The obvious solution is to incorporate a company > to represent the project -- but incorporating a company involves lots of > super-annoying paperwork. (Like, *super* > >>> annoying.) So a standard trick is that a single non-profit corporation > acts as an umbrella organization providing these services to multiple > projects at once, and this is called "fiscal sponsorship". You can read > more about it here: https://en.wikipedia.org/wiki/Fiscal_sponsorship > >>> > >>> How? > >>> ---- > >>> We form a subcommittee of 5 people that will sign the sponsorship > agreement. Those people mostly should be part of the SciPy Steering > Council; there can be an external member. The job of that group is > basically to interface with NumFOCUS (in practice there will be 1-2 people > as first contacts), and to ensure that if we use funds, that they are used > in agreement with the mission and nonprofit status of NumFOCUS. Once we > have those 5 people, we can send in a formal application. In practice that > takes very little time - probably no more than an hour per year, except for > the 1-2 first contacts (they get 1-2 emails per month that need responding > to). > >>> > >>> For more background and details on the how and why, see > https://numfocus.org/information-fiscal-sponsorship. > >>> > >>> Thoughts? Questions? Volunteers to be on the subcommittee? > >>> > >>> Cheers, > >>> Ralf > >>> > >>> > >>> [1] https://numfocus.org/sponsored-projects > >>> [2] > https://mail.python.org/pipermail/numpy-discussion/2015-October/073889.html > >>> _______________________________________________ > >>> SciPy-Dev mailing list > >>> SciPy-Dev at python.org > >>> https://mail.python.org/mailman/listinfo/scipy-dev > >> > >> _______________________________________________ > >> SciPy-Dev mailing list > >> SciPy-Dev at python.org > >> https://mail.python.org/mailman/listinfo/scipy-dev > > > > > > > > -- > > Matt Haberland > > Assistant Adjunct Professor in the Program in Computing > > Department of Mathematics > > 6617A Math Sciences Building, UCLA > > _______________________________________________ > > SciPy-Dev mailing list > > SciPy-Dev at python.org > > https://mail.python.org/mailman/listinfo/scipy-dev > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > -------------- next part -------------- An HTML attachment was scrubbed... URL: From ilhanpolat at gmail.com Mon Dec 24 06:35:13 2018 From: ilhanpolat at gmail.com (Ilhan Polat) Date: Mon, 24 Dec 2018 12:35:13 +0100 Subject: [SciPy-Dev] GitHub services are deprecated - switch to app/webhook In-Reply-To: <1458cd31-8f37-4415-ba13-6d1b30b0b951@Canary> References: <1458cd31-8f37-4415-ba13-6d1b30b0b951@Canary> Message-ID: > > If it helps, I just tried the follow the docs in the first message in this > thread for PyData/Sparse, and it wouldn?t let me activate the repo on .com, > saying it was already active on .org > I had the same problem and if you don't want the build history (which probably you don't care) you can email them. I did and they replied as below. So maybe someone with higher priviledges can start the discussion by emailing them. > Hi Ilhan, > > Thanks for wriiting in! > > I have activated our beta migration feature for your personal account. > Please let me know if this is something you'd also like to have activated > in one or more of your organizations and I'll set it up for your team. > > To help you start migrating your open source repositories to travis-ci.com, > we have created this guide > https://docs.travis-ci.com/user/open-source-repository-migration/ that > contains the instructions to transfer a project as well as some other > details we thought might be useful, including what does it look like to > work with a repository once it's been migrated. > > We're here for any questions or comments you might have. We'll continue > shipping improvements to the beta, and if you find something that can help > us improve, we?d love to hear what you think. > > Thank you, and happy building! > Carla > So apparently there is a beta process going on already. > I can only assume there are people at both companies holding panicked > conference calls. I don't think there's anything we can do except wait for > Github/Travis to get their act together and tell us what's happening > I would use a slightly different tone :) but I agree in general. We are kind of taking their availability for granted however it is nice that we can still use these tools for free hence I would grant some screw-up buffer to them. Maybe it's the Microsoft effect or other CEO issues; who knows. On Mon, Dec 24, 2018 at 11:24 AM Hameer Abbasi wrote: > If it helps, I just tried the follow the docs in the first message in this > thread for PyData/Sparse, and it wouldn?t let me activate the repo on .com, > saying it was already active on .org. You can see the discussion here: > https://github.com/pydata/sparse/issues/224 > > Best Regards, > Hameer Abbasi > > On Sunday, Dec 23, 2018 at 11:47 PM, Nathaniel Smith > wrote: > It's really unclear what's going on here ? Github is saying that you have > to migrate, but Travis is saying that you can't migrate, and there haven't > been any updates for months now. This isn't specific to scipy; every > project using Travis is in the same position. I can only assume there are > people at both companies holding panicked conference calls. I don't think > there's anything we can do except wait for Github/Travis to get their act > together and tell us what's happening. > > -n > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > -------------- next part -------------- An HTML attachment was scrubbed... URL: From mikofski at berkeley.edu Wed Dec 26 11:35:19 2018 From: mikofski at berkeley.edu (Mark Alexander Mikofski) Date: Wed, 26 Dec 2018 08:35:19 -0800 Subject: [SciPy-Dev] fiscal sponsorship agreement with NumFOCUS In-Reply-To: References: Message-ID: I think this is a really good idea. Although I'm not on the steering committee, I'm happy to help if I can. Thanks! On Sat, Dec 22, 2018, 9:08 PM Eric Larson Thanks for the detailed explanation. Sounds like a great idea. I'd be > happy to be on the subcommittee. > > Eric > > On Sat, Dec 22, 2018, 18:56 Ralf Gommers >> Hi all, >> >> To start with the idea: I propose that SciPy applies for comprehensive >> project sponsorship with NumFOCUS, and sign a fiscal sponsorship agreement >> (FSA) to that effect. >> >> Why? >> ---- >> We're already an "affiliated project", which lets us participate in the >> small development grants program, the NumFOCUS project mailing list and >> Slack channel, and a few other benefits. The main difference that >> comprehensive sponsorship will make is that it will allow us to accept >> donations, grants and other kinds of funding as a project. In addition we >> get funding for a representative of the project to attend the yearly >> NumFOCUS Summit, some hours of high-quality legal help in case we need that >> (for example in case of licensing questions), and probably a few other >> things that I'm forgetting right now. NumFOCUS sets a higher bar for >> comprehensive sponsorship than for affiliation, but we should easily clear >> that bar. We'll be joining most other core scientific Python projects, who >> are already sponsored [1]. >> >> I'll also steal some language from Nathaniel when he made the same >> proposal for NumPy [2]: >> The basic idea here is that there are times when you really need some >> kind of corporation to represent the project -- the legal system for >> better or worse does not understand "a bunch of folks on a mailing list" as >> a legal entity capable of accepting donations, or holding funds or other >> assets like domain names. The obvious solution is to incorporate a company >> to represent the project -- but incorporating a company involves lots of >> super-annoying paperwork. (Like, *super* >> annoying.) So a standard trick is that a single non-profit corporation >> acts as an umbrella organization providing these services to multiple >> projects at once, and this is called "fiscal sponsorship". You can read >> more about it here: https://en.wikipedia.org/wiki/Fiscal_sponsorship >> >> How? >> ---- >> We form a subcommittee of 5 people that will sign the sponsorship >> agreement. Those people mostly should be part of the SciPy Steering >> Council; there can be an external member. The job of that group is >> basically to interface with NumFOCUS (in practice there will be 1-2 people >> as first contacts), and to ensure that if we use funds, that they are used >> in agreement with the mission and nonprofit status of NumFOCUS. Once we >> have those 5 people, we can send in a formal application. In practice that >> takes very little time - probably no more than an hour per year, except for >> the 1-2 first contacts (they get 1-2 emails per month that need responding >> to). >> >> For more background and details on the how and why, see >> https://numfocus.org/information-fiscal-sponsorship. >> >> Thoughts? Questions? Volunteers to be on the subcommittee? >> >> Cheers, >> Ralf >> >> >> [1] https://numfocus.org/sponsored-projects >> [2] >> https://mail.python.org/pipermail/numpy-discussion/2015-October/073889.html >> _______________________________________________ >> SciPy-Dev mailing list >> SciPy-Dev at python.org >> https://mail.python.org/mailman/listinfo/scipy-dev >> > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > -------------- next part -------------- An HTML attachment was scrubbed... URL: From cimrman3 at ntc.zcu.cz Wed Dec 26 19:31:19 2018 From: cimrman3 at ntc.zcu.cz (Robert Cimrman) Date: Thu, 27 Dec 2018 01:31:19 +0100 Subject: [SciPy-Dev] ANN: SfePy 2018.4 Message-ID: I am pleased to announce release 2018.4 of SfePy. Description ----------- SfePy (simple finite elements in Python) is a software for solving systems of coupled partial differential equations by the finite element method or by the isogeometric analysis (limited support). It is distributed under the new BSD license. Home page: http://sfepy.org Mailing list: https://mail.python.org/mm3/mailman3/lists/sfepy.python.org/ Git (source) repository, issue tracker: https://github.com/sfepy/sfepy Highlights of this release -------------------------- - better support for eigenvalue problems - improved MUMPS solver interface - support for logging and plotting of complex values For full release notes see [1]. Cheers, Robert Cimrman [1] http://docs.sfepy.org/doc/release_notes.html#id1 --- Contributors to this release in alphabetical order: Robert Cimrman Vladimir Lukes Matyas Novak Jan Heczko Lubos Kejzlar From ralf.gommers at gmail.com Thu Dec 27 01:00:49 2018 From: ralf.gommers at gmail.com (Ralf Gommers) Date: Wed, 26 Dec 2018 22:00:49 -0800 Subject: [SciPy-Dev] fiscal sponsorship agreement with NumFOCUS In-Reply-To: References: Message-ID: Thanks all for the positive replies and for volunteering! I suggest we wait till the end of 2018 before taking any action, to give everyone the chance to reply, but so far so good. On Mon, Dec 24, 2018 at 3:27 AM Ilhan Polat wrote: > So nice to see this kind of structure coming through! > > I'm not in the steering committee but I can help if need be. > You've been a core developer for just over a year now and have done a lot of heavy lifting, so that will likely change soon:) Cheers, Ralf > On Mon, Dec 24, 2018 at 12:02 AM Evgeni Burovski < > evgeny.burovskiy at gmail.com> wrote: > >> Hi Ralf, >> >> Great idea, thanks for pushing it through! >> Count me in for the subcommittee. >> >> Cheers, >> >> Evgeni >> >> On Sun, Dec 23, 2018 at 9:18 PM Matt Haberland >> wrote: >> > >> > Thanks, Ralf. I'd like to volunteer, too. >> > >> > On Sat, Dec 22, 2018 at 9:09 PM Eric Larson >> wrote: >> >> >> >> Thanks for the detailed explanation. Sounds like a great idea. I'd be >> happy to be on the subcommittee. >> >> >> >> Eric >> >> >> >> On Sat, Dec 22, 2018, 18:56 Ralf Gommers > wrote: >> >>> >> >>> Hi all, >> >>> >> >>> To start with the idea: I propose that SciPy applies for >> comprehensive project sponsorship with NumFOCUS, and sign a fiscal >> sponsorship agreement (FSA) to that effect. >> >>> >> >>> Why? >> >>> ---- >> >>> We're already an "affiliated project", which lets us participate in >> the small development grants program, the NumFOCUS project mailing list and >> Slack channel, and a few other benefits. The main difference that >> comprehensive sponsorship will make is that it will allow us to accept >> donations, grants and other kinds of funding as a project. In addition we >> get funding for a representative of the project to attend the yearly >> NumFOCUS Summit, some hours of high-quality legal help in case we need that >> (for example in case of licensing questions), and probably a few other >> things that I'm forgetting right now. NumFOCUS sets a higher bar for >> comprehensive sponsorship than for affiliation, but we should easily clear >> that bar. We'll be joining most other core scientific Python projects, who >> are already sponsored [1]. >> >>> >> >>> I'll also steal some language from Nathaniel when he made the same >> proposal for NumPy [2]: >> >>> The basic idea here is that there are times when you really need some >> kind of corporation to represent the project -- the legal system for >> better or worse does not understand "a bunch of folks on a mailing list" as >> a legal entity capable of accepting donations, or holding funds or other >> assets like domain names. The obvious solution is to incorporate a company >> to represent the project -- but incorporating a company involves lots of >> super-annoying paperwork. (Like, *super* >> >>> annoying.) So a standard trick is that a single non-profit >> corporation acts as an umbrella organization providing these services to >> multiple projects at once, and this is called "fiscal sponsorship". You >> can read more about it here: >> https://en.wikipedia.org/wiki/Fiscal_sponsorship >> >>> >> >>> How? >> >>> ---- >> >>> We form a subcommittee of 5 people that will sign the sponsorship >> agreement. Those people mostly should be part of the SciPy Steering >> Council; there can be an external member. The job of that group is >> basically to interface with NumFOCUS (in practice there will be 1-2 people >> as first contacts), and to ensure that if we use funds, that they are used >> in agreement with the mission and nonprofit status of NumFOCUS. Once we >> have those 5 people, we can send in a formal application. In practice that >> takes very little time - probably no more than an hour per year, except for >> the 1-2 first contacts (they get 1-2 emails per month that need responding >> to). >> >>> >> >>> For more background and details on the how and why, see >> https://numfocus.org/information-fiscal-sponsorship. >> >>> >> >>> Thoughts? Questions? Volunteers to be on the subcommittee? >> >>> >> >>> Cheers, >> >>> Ralf >> >>> >> >>> >> >>> [1] https://numfocus.org/sponsored-projects >> >>> [2] >> https://mail.python.org/pipermail/numpy-discussion/2015-October/073889.html >> >>> _______________________________________________ >> >>> SciPy-Dev mailing list >> >>> SciPy-Dev at python.org >> >>> https://mail.python.org/mailman/listinfo/scipy-dev >> >> >> >> _______________________________________________ >> >> SciPy-Dev mailing list >> >> SciPy-Dev at python.org >> >> https://mail.python.org/mailman/listinfo/scipy-dev >> > >> > >> > >> > -- >> > Matt Haberland >> > Assistant Adjunct Professor in the Program in Computing >> > Department of Mathematics >> > 6617A Math Sciences Building, UCLA >> > _______________________________________________ >> > SciPy-Dev mailing list >> > SciPy-Dev at python.org >> > https://mail.python.org/mailman/listinfo/scipy-dev >> _______________________________________________ >> SciPy-Dev mailing list >> SciPy-Dev at python.org >> https://mail.python.org/mailman/listinfo/scipy-dev >> > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > -------------- next part -------------- An HTML attachment was scrubbed... URL: From tyler.je.reddy at gmail.com Fri Dec 28 13:10:12 2018 From: tyler.je.reddy at gmail.com (Tyler Reddy) Date: Fri, 28 Dec 2018 10:10:12 -0800 Subject: [SciPy-Dev] fiscal sponsorship agreement with NumFOCUS In-Reply-To: References: Message-ID: This all sounds great -- +1 from my end. On Wed, 26 Dec 2018 at 22:01, Ralf Gommers wrote: > Thanks all for the positive replies and for volunteering! > > I suggest we wait till the end of 2018 before taking any action, to give > everyone the chance to reply, but so far so good. > > > On Mon, Dec 24, 2018 at 3:27 AM Ilhan Polat wrote: > >> So nice to see this kind of structure coming through! >> >> I'm not in the steering committee but I can help if need be. >> > > You've been a core developer for just over a year now and have done a lot > of heavy lifting, so that will likely change soon:) > > Cheers, > Ralf > > > >> On Mon, Dec 24, 2018 at 12:02 AM Evgeni Burovski < >> evgeny.burovskiy at gmail.com> wrote: >> >>> Hi Ralf, >>> >>> Great idea, thanks for pushing it through! >>> Count me in for the subcommittee. >>> >>> Cheers, >>> >>> Evgeni >>> >>> On Sun, Dec 23, 2018 at 9:18 PM Matt Haberland >>> wrote: >>> > >>> > Thanks, Ralf. I'd like to volunteer, too. >>> > >>> > On Sat, Dec 22, 2018 at 9:09 PM Eric Larson >>> wrote: >>> >> >>> >> Thanks for the detailed explanation. Sounds like a great idea. I'd be >>> happy to be on the subcommittee. >>> >> >>> >> Eric >>> >> >>> >> On Sat, Dec 22, 2018, 18:56 Ralf Gommers >> wrote: >>> >>> >>> >>> Hi all, >>> >>> >>> >>> To start with the idea: I propose that SciPy applies for >>> comprehensive project sponsorship with NumFOCUS, and sign a fiscal >>> sponsorship agreement (FSA) to that effect. >>> >>> >>> >>> Why? >>> >>> ---- >>> >>> We're already an "affiliated project", which lets us participate in >>> the small development grants program, the NumFOCUS project mailing list and >>> Slack channel, and a few other benefits. The main difference that >>> comprehensive sponsorship will make is that it will allow us to accept >>> donations, grants and other kinds of funding as a project. In addition we >>> get funding for a representative of the project to attend the yearly >>> NumFOCUS Summit, some hours of high-quality legal help in case we need that >>> (for example in case of licensing questions), and probably a few other >>> things that I'm forgetting right now. NumFOCUS sets a higher bar for >>> comprehensive sponsorship than for affiliation, but we should easily clear >>> that bar. We'll be joining most other core scientific Python projects, who >>> are already sponsored [1]. >>> >>> >>> >>> I'll also steal some language from Nathaniel when he made the same >>> proposal for NumPy [2]: >>> >>> The basic idea here is that there are times when you really need >>> some kind of corporation to represent the project -- the legal system for >>> better or worse does not understand "a bunch of folks on a mailing list" as >>> a legal entity capable of accepting donations, or holding funds or other >>> assets like domain names. The obvious solution is to incorporate a company >>> to represent the project -- but incorporating a company involves lots of >>> super-annoying paperwork. (Like, *super* >>> >>> annoying.) So a standard trick is that a single non-profit >>> corporation acts as an umbrella organization providing these services to >>> multiple projects at once, and this is called "fiscal sponsorship". You >>> can read more about it here: >>> https://en.wikipedia.org/wiki/Fiscal_sponsorship >>> >>> >>> >>> How? >>> >>> ---- >>> >>> We form a subcommittee of 5 people that will sign the sponsorship >>> agreement. Those people mostly should be part of the SciPy Steering >>> Council; there can be an external member. The job of that group is >>> basically to interface with NumFOCUS (in practice there will be 1-2 people >>> as first contacts), and to ensure that if we use funds, that they are used >>> in agreement with the mission and nonprofit status of NumFOCUS. Once we >>> have those 5 people, we can send in a formal application. In practice that >>> takes very little time - probably no more than an hour per year, except for >>> the 1-2 first contacts (they get 1-2 emails per month that need responding >>> to). >>> >>> >>> >>> For more background and details on the how and why, see >>> https://numfocus.org/information-fiscal-sponsorship. >>> >>> >>> >>> Thoughts? Questions? Volunteers to be on the subcommittee? >>> >>> >>> >>> Cheers, >>> >>> Ralf >>> >>> >>> >>> >>> >>> [1] https://numfocus.org/sponsored-projects >>> >>> [2] >>> https://mail.python.org/pipermail/numpy-discussion/2015-October/073889.html >>> >>> _______________________________________________ >>> >>> SciPy-Dev mailing list >>> >>> SciPy-Dev at python.org >>> >>> https://mail.python.org/mailman/listinfo/scipy-dev >>> >> >>> >> _______________________________________________ >>> >> SciPy-Dev mailing list >>> >> SciPy-Dev at python.org >>> >> https://mail.python.org/mailman/listinfo/scipy-dev >>> > >>> > >>> > >>> > -- >>> > Matt Haberland >>> > Assistant Adjunct Professor in the Program in Computing >>> > Department of Mathematics >>> > 6617A Math Sciences Building, UCLA >>> > _______________________________________________ >>> > SciPy-Dev mailing list >>> > SciPy-Dev at python.org >>> > https://mail.python.org/mailman/listinfo/scipy-dev >>> _______________________________________________ >>> SciPy-Dev mailing list >>> SciPy-Dev at python.org >>> https://mail.python.org/mailman/listinfo/scipy-dev >>> >> _______________________________________________ >> SciPy-Dev mailing list >> SciPy-Dev at python.org >> https://mail.python.org/mailman/listinfo/scipy-dev >> > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev at python.org > https://mail.python.org/mailman/listinfo/scipy-dev > -------------- next part -------------- An HTML attachment was scrubbed... URL: