Mailman 3 November 2020 - SciPy-Dev

Cannot generate very large very sparse random matrix
by Emanuele Olivetti 19 Jan '21

19 Jan '21

Hi, I've just noticed that it is not possible to generate very large very sparse random matrices with scipy.sparse.random(). For example: scipy.sparse.random(1_000_000, 1_000_000, density = 1e-11) should create a sparse matrix with only 10 non-zero values... but instead triggers a MemoryError: ---- MemoryError Traceback (most recent call last) <ipython-input-8-eb81d3aec480> in <module> ----> 1 scipy.sparse.random(1_000_000, 1_000_000, density = 1e-11) ~/miniconda3/envs/lap/lib/python3.8/site-packages/scipy/sparse/construct.py in random(m, n, density, format, dtype, random_state, data_rvs) 787 data_rvs = partial(random_state.uniform, 0., 1.) 788 --> 789 ind = random_state.choice(mn, size=k, replace=False) 790 791 j = np.floor(ind * 1. / m).astype(tp, copy=False) mtrand.pyx in numpy.random.mtrand.RandomState.choice() mtrand.pyx in numpy.random.mtrand.RandomState.permutation() MemoryError: Unable to allocate 7.28 TiB for an array with shape (1000000000000,) and data type int64 ---- Here is the problematic line in current master branch of SciPy: https://github.com/scipy/scipy/blob/master/scipy/sparse/construct.py#L806 In short, the issue is due to random_state.choice(... replace=False) which needs to allocate the humongous array in order to pick the ten random numbers... I understand the technical difficulty of generating random numbers without replacement, but it is quite counterintuitive that in order to generate a sparse random matrix it is necessary to create an equally large but *dense* vector first. Is there a solution to this problem? Thanks in advance, Emanuele -- -- Le informazioni contenute nella presente comunicazione sono di natura privata e come tali sono da considerarsi riservate ed indirizzate esclusivamente ai destinatari indicati e per le finalità strettamente legate al relativo contenuto. Se avete ricevuto questo messaggio per errore, vi preghiamo di eliminarlo e di inviare una comunicazione all’indirizzo e-mail del mittente. -- The information transmitted is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material. If you received this in error, please contact the sender and delete the material.

2 4

Proposed 1.6.0 Release Schedule
by Tyler Reddy 23 Dec '20

23 Dec '20

Hi, SciPy 1.5.0 was released June 21 (~5 months ago), and I think we'd like to keep a roughly biannual release cadence. I'd like to propose the following schedule for 1.6.0: - November 17: branch 1.6.x - November 20: rc1 - December 1: rc2 (if needed) - December 10: final release As always, it is a good idea to start tagging things that should be in 1.6.0 & please do help with reviewing PRs/issues that are tagged--current counts are: - PRs: 45 open with 1.6.0 milestone - issues: 25 open with 1.6.0 milestone While helping with that, also great if the release notes wiki is updated for appropriate changes: https://github.com/scipy/scipy/wiki/Release-note-entries-for-SciPy-1.6.0 Thoughts/objections for the schedule? Best wishes, Tyler

5 10

Shapelet Functions
by Michelle Teplitski 29 Nov '20

29 Nov '20

Hi scipy-dev community, I am working on a library to generate shapelet functions for use in image processing. Applications range from analyzing images of galaxies to finding defects in nano-structured materials. Would the community be interested in this as a contribution to scipy? Thanks, Michelle Teplitski

2 1

Proposal to add two new linesearch strategies to scipy.optimize
by Ihno Schrot 26 Nov '20

26 Nov '20

Hi all, I would like to propose to add two new linesearch strategies to scipy.optimize(.linesearch.py), namely the "Restrictive Monotonicity Test" (RMT) [1] and the "Backward Step Control" (BSC) [2]. It is well known that Newton-type methods for rootfinding or optimization problems can be forced to converge globally in a domain where the Jacobian or Hessian, respectively, is nonsingular. However, with linesearch strategies which are based on descent arguments with classical merit functions one usually has to pay the price of taking unnecessarily small stepsizes even in the domain where full steps would lead to convergence. This is also the case for the existing linesearch strategies in SciPy. The suggested linesearch strategies were developed to achieve global convergence of Newton-type methods while avoiding too small step sizes. The RMT already has shown good performance in many practical applications. The BSC is a rather novel strategy but the numerical results available so far are promising and the BSC is proven to enable global convergence under reasonable assumptions. Moreover, I have done extensive numerical tests of both linesearch strategies in my master thesis. Although the tests have been focussed on comparing the two strategies, I also compared them to SciPys linesearch strategy that is based on the Wolfe condition and found that the RMT and BSC can outperform SciPys linesearch strategy in terms of the number of benchmark problems that can be solved. Therefore, I believe that adding the BSC and the RMT to SciPy benefits a wide range of users by providing modern powerful linesearch strategies. Especially, users would have two more linesearch strategies to apply to their problems, which can be helpful given that it is problem dependent which linesearch strategy works the best. If the community thinks that adding those two strategies is an useful enhancement, colleagues and I are happy to improve and eventually add our code to SciPy. Of course, we are also happy to answer any questions from the community regarding this proposal. Greetings from Heidelberg, Ihno [1] https://doi.org/10.1007/978-0-387-35514-6_3 [2] https://doi.org/10.1137/140968586 -- Ihno Schrot Institute for Applied Mathematics Heidelberg University E-Mail: ihno.schrot(a)uni-heidelberg.de

2 1

Re: [SciPy-Dev] SciPy-Dev Digest, Vol 205, Issue 14
by frank.home＠sbcglobal.net 22 Nov '20

22 Nov '20

It's worth some effort to see what happens with the inquiries, even if just to learn more about how others want to handle these types of situations. But I feel there are enough of us willing to chip in to keep it running short term, and time is better spent on scipy code quality, so if it gets to the point that the inquiries/discussions get frustrating or time consuming, maybe just let us know how to chip in? On Sunday, November 22, 2020, 12:24:33 PM PST, scipy-dev-request(a)python.org <scipy-dev-request(a)python.org> wrote: Send SciPy-Dev mailing list submissions to scipy-dev(a)python.org To subscribe or unsubscribe via the World Wide Web, visit https://mail.python.org/mailman/listinfo/scipy-dev or, via email, send a message with subject or body 'help' to scipy-dev-request(a)python.org You can reach the person managing the list at scipy-dev-owner(a)python.org When replying, please edit your Subject line so it is more specific than "Re: Contents of SciPy-Dev digest..." Today's Topics: 1. Re: Proposed 1.6.0 Release Schedule (Tyler Reddy) 2. Re: Proposed 1.6.0 Release Schedule (Ilhan Polat) We may need to delay the release a bit. Mostly because of the disruption to the Travis CI service (not running/credit limit), which would probably affect the wheels repo before a final release too. I've tried to move a few of the simpler jobs to Azure, but probably running out of steam for that effort this weekend. I've reached out to Travis CI support and asked NumFOCUS informally what we might do here. A few kind folks have offered to chip in to keep the CI running short-term. Let's see what happens with the former inquiries first? Open PR count is currently 26 for the 1.6.0 milestone, though probably a few more I can bump to next milestone. Best wishes,Tyler On Mon, 9 Nov 2020 at 00:12, Evgeni Burovski <evgeny.burovskiy(a)gmail.com> wrote: How about shifting the release towards January then? пн, 9 нояб. 2020 г., 1:43 Tyler Reddy <tyler.je.reddy(a)gmail.com>: Ok, I'll bump it by a week then. - November 24: branch maintenance/1.6.x - November 27: rc1 - December 8: rc2 (if needed) - December 17: final release I was trying to avoid the overlap with US Thanksgiving and a final release in late December near Winter Break, but I'll manage. Tyler On Sun, 8 Nov 2020 at 14:53, Ralf Gommers <ralf.gommers(a)gmail.com> wrote: On Sat, Nov 7, 2020 at 10:48 PM Tyler Reddy <tyler.je.reddy(a)gmail.com> wrote: Hi, SciPy 1.5.0 was released June 21 (~5 months ago), and I think we'd like to keep a roughly biannual release cadence. I'd like to propose the following schedule for 1.6.0:- November 17: branch 1.6.x - November 20: rc1 - December 1: rc2 (if needed) - December 10: final release As always, it is a good idea to start tagging things that should be in 1.6.0 & please do help with reviewing PRs/issues that are tagged--current counts are: - PRs: 45 open with 1.6.0 milestone- issues: 25 open with 1.6.0 milestone While helping with that, also great if the release notes wiki is updated for appropriate changes: https://github.com/scipy/scipy/wiki/Release-note-entries-for-SciPy-1.6.0 Thoughts/objections for the schedule? It does seem like there's a lot of PRs open, having only one weekend left seems optimistic. The majority can be bumped to 1.7.0, but there's a bit of a backlog of nice PRs that have been ready for a while and would be nice to get in. For example: - KDTree/cKDTree feature parity: https://github.com/scipy/scipy/pull/12852- HiGHS solver as linprog method: https://github.com/scipy/scipy/pull/12043- Balanced cut tree: https://github.com/scipy/scipy/pull/10730- Andrew's set of optimize PRs that he brought up on the mailing list recently- Greg's set of ndimage PRs, complex kernels and the boundary handling ones (#12725, #12767, #12776) If it's possible, given your time constraints, to bump the schedule by one week then that may be useful. Cheers, Ralf _______________________________________________ SciPy-Dev mailing list SciPy-Dev(a)python.org https://mail.python.org/mailman/listinfo/scipy-dev _______________________________________________ SciPy-Dev mailing list SciPy-Dev(a)python.org https://mail.python.org/mailman/listinfo/scipy-dev _______________________________________________ SciPy-Dev mailing list SciPy-Dev(a)python.org https://mail.python.org/mailman/listinfo/scipy-dev I don't mean to disrupt your flow but please feel free to assign some dummy work to us if need be. Given the pandemic and all, it's much easier to get overwhelmed with stuff these days. On Sun, Nov 22, 2020 at 8:14 PM Tyler Reddy <tyler.je.reddy(a)gmail.com> wrote: We may need to delay the release a bit. Mostly because of the disruption to the Travis CI service (not running/credit limit), which would probably affect the wheels repo before a final release too. I've tried to move a few of the simpler jobs to Azure, but probably running out of steam for that effort this weekend. I've reached out to Travis CI support and asked NumFOCUS informally what we might do here. A few kind folks have offered to chip in to keep the CI running short-term. Let's see what happens with the former inquiries first? Open PR count is currently 26 for the 1.6.0 milestone, though probably a few more I can bump to next milestone. Best wishes,Tyler On Mon, 9 Nov 2020 at 00:12, Evgeni Burovski <evgeny.burovskiy(a)gmail.com> wrote: How about shifting the release towards January then? пн, 9 нояб. 2020 г., 1:43 Tyler Reddy <tyler.je.reddy(a)gmail.com>: Ok, I'll bump it by a week then. - November 24: branch maintenance/1.6.x - November 27: rc1 - December 8: rc2 (if needed) - December 17: final release I was trying to avoid the overlap with US Thanksgiving and a final release in late December near Winter Break, but I'll manage. Tyler On Sun, 8 Nov 2020 at 14:53, Ralf Gommers <ralf.gommers(a)gmail.com> wrote: On Sat, Nov 7, 2020 at 10:48 PM Tyler Reddy <tyler.je.reddy(a)gmail.com> wrote: Hi, SciPy 1.5.0 was released June 21 (~5 months ago), and I think we'd like to keep a roughly biannual release cadence. I'd like to propose the following schedule for 1.6.0:- November 17: branch 1.6.x - November 20: rc1 - December 1: rc2 (if needed) - December 10: final release As always, it is a good idea to start tagging things that should be in 1.6.0 & please do help with reviewing PRs/issues that are tagged--current counts are: - PRs: 45 open with 1.6.0 milestone- issues: 25 open with 1.6.0 milestone While helping with that, also great if the release notes wiki is updated for appropriate changes: https://github.com/scipy/scipy/wiki/Release-note-entries-for-SciPy-1.6.0 Thoughts/objections for the schedule? It does seem like there's a lot of PRs open, having only one weekend left seems optimistic. The majority can be bumped to 1.7.0, but there's a bit of a backlog of nice PRs that have been ready for a while and would be nice to get in. For example: - KDTree/cKDTree feature parity: https://github.com/scipy/scipy/pull/12852- HiGHS solver as linprog method: https://github.com/scipy/scipy/pull/12043- Balanced cut tree: https://github.com/scipy/scipy/pull/10730- Andrew's set of optimize PRs that he brought up on the mailing list recently- Greg's set of ndimage PRs, complex kernels and the boundary handling ones (#12725, #12767, #12776) If it's possible, given your time constraints, to bump the schedule by one week then that may be useful. Cheers, Ralf _______________________________________________ SciPy-Dev mailing list SciPy-Dev(a)python.org https://mail.python.org/mailman/listinfo/scipy-dev _______________________________________________ SciPy-Dev mailing list SciPy-Dev(a)python.org https://mail.python.org/mailman/listinfo/scipy-dev _______________________________________________ SciPy-Dev mailing list SciPy-Dev(a)python.org https://mail.python.org/mailman/listinfo/scipy-dev _______________________________________________ SciPy-Dev mailing list SciPy-Dev(a)python.org https://mail.python.org/mailman/listinfo/scipy-dev _______________________________________________ SciPy-Dev mailing list SciPy-Dev(a)python.org https://mail.python.org/mailman/listinfo/scipy-dev

1 0

Travis CI credits exceeded
by Tyler Reddy 21 Nov '20

21 Nov '20

Hi, Note that Travis CI is no longer running in our test matrix because we're out of open source credits: https://github.com/scipy/scipy/issues/13109 So, probably good to use some caution in merging MRs as it will just be silently absent. We'll need to continue migrating matrix entries to other services. Best wishes, Tyler

1 0

proposal to drop Python 3.6 and NumPy 1.14 / 1.15
by Ralf Gommers 14 Nov '20

14 Nov '20

Hi all, Python 3.9 is coming out before the next SciPy release, and NEP 29 recommends to support only Python >=3.7 and NumPy >= 1.16 from last month onwards [1]. I think supporting 3 Python versions and 5 NumPy versions in SciPy 1.6.0 is easily enough. That would also bring us back in line with SciPy on conda-forge, which built against NumPy 1.16 for 1.5.2. Any objections? Cheers, Ralf [1] https://numpy.org/neps/nep-0029-deprecation_policy.html#support-table

10 21

Add remove method to scipy.spatial.cKDTree
by Omar Younis 08 Nov '20

08 Nov '20

I've sent a pull request to add remove method to scipy.spatial.cKDTree. You can find it here: https://github.com/scipy/scipy/pull/13050

1 0

ANN: SciPy 1.5.4
by Tyler Reddy 05 Nov '20

05 Nov '20

Hi all, On behalf of the SciPy development team I'm pleased to announce the release of SciPy 1.5.4, which is a bug fix release that includes Python 3.9 wheels and a more complete fix for build issues on XCode 12. Sources and binary wheels can be found at: https://pypi.org/project/scipy/ and at: https://github.com/scipy/scipy/releases/tag/v1.5.4 One of a few ways to install this release with pip: pip install scipy==1.5.4 ===================== SciPy 1.5.4 Release Notes ===================== SciPy 1.5.4 is a bug-fix release with no new features compared to 1.5.3. Importantly, wheels are now available for Python 3.9 and a more complete fix has been applied for issues building with XCode 12. Authors ====== * Peter Bell * CJ Carey * Andrew McCluskey + * Andrew Nelson * Tyler Reddy * Eli Rykoff + * Ian Thomas + A total of 7 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete. Issues closed for 1.5.4 ------------------------------- * `#12763 <https://github.com/scipy/scipy/issues/12763>`__: ndimage.fourier_ellipsoid segmentation fault * `#12789 <https://github.com/scipy/scipy/issues/12789>`__: TestConvolve2d.test_large_array failing on Windows ILP64 CI job * `#12857 <https://github.com/scipy/scipy/issues/12857>`__: sparse A[0,:] = ndarray is ok, A[:,0] = ndarray ValueError from... * `#12860 <https://github.com/scipy/scipy/issues/12860>`__: BUG: Build failure with Xcode 12 * `#12935 <https://github.com/scipy/scipy/issues/12935>`__: Failure to build with Python 3.9.0 on macOS * `#12966 <https://github.com/scipy/scipy/issues/12966>`__: MAINT: lint_diff.py on some backport PRs * `#12988 <https://github.com/scipy/scipy/issues/12988>`__: BUG: Highly multi-dimensional \`gaussian_kde\` giving \`-inf\`... Pull requests for 1.5.4 ------------------------------ * `#12790 <https://github.com/scipy/scipy/pull/12790>`__: TST: Skip TestConvolve2d.test_large_array if not enough memory * `#12851 <https://github.com/scipy/scipy/pull/12851>`__: BUG: sparse: fix inner indexed assignment of a 1d array * `#12875 <https://github.com/scipy/scipy/pull/12875>`__: BUG: segfault in ndimage.fourier_ellipsoid with length-1 dims * `#12937 <https://github.com/scipy/scipy/pull/12937>`__: CI: macOS3.9 testing * `#12957 <https://github.com/scipy/scipy/pull/12957>`__: MAINT: fixes XCode 12/ python 3.9.0 build for 1.5.x maint branch * `#12959 <https://github.com/scipy/scipy/pull/12959>`__: CI: add Windows Python 3.9 to CI * `#12974 <https://github.com/scipy/scipy/pull/12974>`__: MAINT: Run lint_diff.py against the merge target and only for... * `#12978 <https://github.com/scipy/scipy/pull/12978>`__: DOC: next_fast_len output doesn't match docstring * `#12979 <https://github.com/scipy/scipy/pull/12979>`__: BUG: fft.next_fast_len should accept keyword arguments * `#12989 <https://github.com/scipy/scipy/pull/12989>`__: BUG: improved the stability of kde for highly (1000s) multi-dimension... * `#13017 <https://github.com/scipy/scipy/pull/13017>`__: BUG: Add explicit cast to _tmp sum. * `#13022 <https://github.com/scipy/scipy/pull/13022>`__: TST: xfail test_maxiter_worsening() Checksums ========= MD5 ~~~ 09a446e10033c3132f1f257e3f4d9735 scipy-1.5.4-cp36-cp36m-macosx_10_9_x86_64.whl 25e58fde2fd4eb6c7717719db85e368b scipy-1.5.4-cp36-cp36m-manylinux1_i686.whl 2c9705cd57788ad79ea0c1015208f41f scipy-1.5.4-cp36-cp36m-manylinux1_x86_64.whl d0fb84f3ff45e4149698fbc662ac4d47 scipy-1.5.4-cp36-cp36m-manylinux2014_aarch64.whl f94f0e274cd2960ecb2d8751632e098c scipy-1.5.4-cp36-cp36m-win32.whl f56f4d5b67fccc49fb64331c28bdf7d1 scipy-1.5.4-cp36-cp36m-win_amd64.whl 33e0843f8619b78547866579134a733b scipy-1.5.4-cp37-cp37m-macosx_10_9_x86_64.whl 6720a406d82bd08c4370b665d5eddeb9 scipy-1.5.4-cp37-cp37m-manylinux1_i686.whl eafc3bc8a12d41cb348c73b54ad25ad5 scipy-1.5.4-cp37-cp37m-manylinux1_x86_64.whl 1174418ae0614d621acdb49faeaadcb8 scipy-1.5.4-cp37-cp37m-manylinux2014_aarch64.whl 5ca53c5cd6828498c0a41c3ae747a34b scipy-1.5.4-cp37-cp37m-win32.whl cdb91a7db9cf79b7446680f8d106aabc scipy-1.5.4-cp37-cp37m-win_amd64.whl 02a29a4eec9c61c30aef7439138fe1b3 scipy-1.5.4-cp38-cp38-macosx_10_9_x86_64.whl ce8e02167763493374c4bea807139a1b scipy-1.5.4-cp38-cp38-manylinux1_i686.whl 65ec027bfa6bed805dac62744b45c693 scipy-1.5.4-cp38-cp38-manylinux1_x86_64.whl c358b4b332cc9dbcd1eadc229d8b019e scipy-1.5.4-cp38-cp38-manylinux2014_aarch64.whl 492ec3bfe082229076a83d74cfa51d7e scipy-1.5.4-cp38-cp38-win32.whl d5d12211502429f3bc3074b12ca1f541 scipy-1.5.4-cp38-cp38-win_amd64.whl da25e7ac777e8b1b6cd7f117f163e6d2 scipy-1.5.4-cp39-cp39-macosx_10_9_x86_64.whl 12275e3578eb17065081d83d329d18db scipy-1.5.4-cp39-cp39-manylinux1_i686.whl 6778d670f75f536921c3d38e44517280 scipy-1.5.4-cp39-cp39-manylinux1_x86_64.whl efda61c74b29ffe714b6b842ec369a19 scipy-1.5.4-cp39-cp39-manylinux2014_aarch64.whl 107204c14328df879c5fc941e7829389 scipy-1.5.4-cp39-cp39-win32.whl ed6970f7538d38dd91a42950bd6843b7 scipy-1.5.4-cp39-cp39-win_amd64.whl 293401ee7ac354a2f2313373b497f40e scipy-1.5.4.tar.gz d446ec7a6b0bc44484389ab7589eccf5 scipy-1.5.4.tar.xz 47d0dabdc684475bc2aac7e8db9eea6f scipy-1.5.4.zip SHA256 ~~~~~~ 4f12d13ffbc16e988fa40809cbbd7a8b45bc05ff6ea0ba8e3e41f6f4db3a9e47 scipy-1.5.4-cp36-cp36m-macosx_10_9_x86_64.whl a254b98dbcc744c723a838c03b74a8a34c0558c9ac5c86d5561703362231107d scipy-1.5.4-cp36-cp36m-manylinux1_i686.whl 368c0f69f93186309e1b4beb8e26d51dd6f5010b79264c0f1e9ca00cd92ea8c9 scipy-1.5.4-cp36-cp36m-manylinux1_x86_64.whl 4598cf03136067000855d6b44d7a1f4f46994164bcd450fb2c3d481afc25dd06 scipy-1.5.4-cp36-cp36m-manylinux2014_aarch64.whl e98d49a5717369d8241d6cf33ecb0ca72deee392414118198a8e5b4c35c56340 scipy-1.5.4-cp36-cp36m-win32.whl 65923bc3809524e46fb7eb4d6346552cbb6a1ffc41be748535aa502a2e3d3389 scipy-1.5.4-cp36-cp36m-win_amd64.whl 9ad4fcddcbf5dc67619379782e6aeef41218a79e17979aaed01ed099876c0e62 scipy-1.5.4-cp37-cp37m-macosx_10_9_x86_64.whl f87b39f4d69cf7d7529d7b1098cb712033b17ea7714aed831b95628f483fd012 scipy-1.5.4-cp37-cp37m-manylinux1_i686.whl 25b241034215247481f53355e05f9e25462682b13bd9191359075682adcd9554 scipy-1.5.4-cp37-cp37m-manylinux1_x86_64.whl fa789583fc94a7689b45834453fec095245c7e69c58561dc159b5d5277057e4c scipy-1.5.4-cp37-cp37m-manylinux2014_aarch64.whl d6d25c41a009e3c6b7e757338948d0076ee1dd1770d1c09ec131f11946883c54 scipy-1.5.4-cp37-cp37m-win32.whl 2c872de0c69ed20fb1a9b9cf6f77298b04a26f0b8720a5457be08be254366c6e scipy-1.5.4-cp37-cp37m-win_amd64.whl e360cb2299028d0b0d0f65a5c5e51fc16a335f1603aa2357c25766c8dab56938 scipy-1.5.4-cp38-cp38-macosx_10_9_x86_64.whl 3397c129b479846d7eaa18f999369a24322d008fac0782e7828fa567358c36ce scipy-1.5.4-cp38-cp38-manylinux1_i686.whl 168c45c0c32e23f613db7c9e4e780bc61982d71dcd406ead746c7c7c2f2004ce scipy-1.5.4-cp38-cp38-manylinux1_x86_64.whl 213bc59191da2f479984ad4ec39406bf949a99aba70e9237b916ce7547b6ef42 scipy-1.5.4-cp38-cp38-manylinux2014_aarch64.whl 634568a3018bc16a83cda28d4f7aed0d803dd5618facb36e977e53b2df868443 scipy-1.5.4-cp38-cp38-win32.whl b03c4338d6d3d299e8ca494194c0ae4f611548da59e3c038813f1a43976cb437 scipy-1.5.4-cp38-cp38-win_amd64.whl 3d5db5d815370c28d938cf9b0809dade4acf7aba57eaf7ef733bfedc9b2474c4 scipy-1.5.4-cp39-cp39-macosx_10_9_x86_64.whl 6b0ceb23560f46dd236a8ad4378fc40bad1783e997604ba845e131d6c680963e scipy-1.5.4-cp39-cp39-manylinux1_i686.whl ed572470af2438b526ea574ff8f05e7f39b44ac37f712105e57fc4d53a6fb660 scipy-1.5.4-cp39-cp39-manylinux1_x86_64.whl 8c8d6ca19c8497344b810b0b0344f8375af5f6bb9c98bd42e33f747417ab3f57 scipy-1.5.4-cp39-cp39-manylinux2014_aarch64.whl d84cadd7d7998433334c99fa55bcba0d8b4aeff0edb123b2a1dfcface538e474 scipy-1.5.4-cp39-cp39-win32.whl cc1f78ebc982cd0602c9a7615d878396bec94908db67d4ecddca864d049112f2 scipy-1.5.4-cp39-cp39-win_amd64.whl 4a453d5e5689de62e5d38edf40af3f17560bfd63c9c5bd228c18c1f99afa155b scipy-1.5.4.tar.gz 5c87347bfe2db6e23d391aa226584f6b280248c0ca71e08f26f1faf9d7a76bc9 scipy-1.5.4.tar.xz e0bcc10c133a151937550bb42301c56439d34098b1b8f9dd18c5919d604edd37 scipy-1.5.4.zip

1 0

Re: [SciPy-Dev] Chirp Z-transform
by Martin Reinecke 04 Nov '20

04 Nov '20

(resending this; I sent this yesterday already but the mail was rejected because I was not subscribed.) Hi all, is this implmentation related to the new ICZT algorithm? (https://www.nature.com/articles/s41598-019-50234-9) This is absolutely fascinating stuff, but there also seems to be a patent on the algorithm: https://patentscope.wipo.int/search/en/detail.jsf?docId=WO2019023220 Maybe that's no problem at all (I haven't researched what the licensing terms are), but it might need careful checking. Cheers, Martin

3 3