Mailman 3 May 2022 - SciPy-User

How to display a RGB image (MFISH)?
by jp April 3, 2023

April 3, 2023

Hi, I have written a script to try to combine five images into a three channels RGB images<http://dip4fish.blogspot.com/2011/05/trying-to-combine-mfish-images-into-rg…> . The resulting RGB image looks like a grey scale image instead of a color one. I have three np.array Rnorm, Gnorm, Bnorm which are copied into a rgb array: *rgb = np.zeros((shape[0],shape[1],3),dtype=float) mxr=np.max(R) mxg=np.max(G) mxb=np.max(B) Rnorm=np.uint8((255*(R/mxr)))Gnorm=np.uint8((255*(R/mxg)))Bnorm=np.uint8((255*(R/mxb)))#copy each RGB component in an RGB array rgb[:,:,0]=Rnorm rgb[:,:,1]=Gnorm rgb[:,:,2]=Bnorm* *pylab.subplot(224, aspect='equal',frameon=False, xticks=[], yticks=[]) pylab.imshow(rgb) pylab.show()* Any advice? Thank you Jean-Patrick

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Invitation to connect on LinkedIn
by Jelle Feringa via LinkedIn July 28, 2022

July 28, 2022

LinkedIn ------------ Jelle Feringa requested to add you as a connection on LinkedIn: ------------------------------------------ Jose, I'd like to add you to my professional network on LinkedIn. - Jelle Accept invitation from Jelle Feringa http://www.linkedin.com/e/-3wy1w2-gpkzwpgn-5n/Q6WKH0LACopGJkAw_6fSqajo6R7VM… View invitation from Jelle Feringa http://www.linkedin.com/e/-3wy1w2-gpkzwpgn-5n/Q6WKH0LACopGJkAw_6fSqajo6R7VM… ------------------------------------------ DID YOU KNOW your LinkedIn profile helps you control your public image when people search for you? Setting your profile as public means your LinkedIn profile will come up when people enter your name in leading search engines. Take control of your image! http://www.linkedin.com/e/-3wy1w2-gpkzwpgn-5n/ewp/inv-22/ -- (c) 2011, LinkedIn Corporation

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NumPy 1.23.0rc2 released
by Charles R Harris May 30, 2022

May 30, 2022

Hi All, On behalf of the NumPy team, I'm pleased to announce the release of NumPy 1.23.0rc2. The NumPy 1.23.0 release continues the ongoing work to improve the handling and promotion of dtypes, increase the execution speed, clarify the documentation, and expire old deprecations. The highlights are: - Implementation of ``loadtxt`` in C, greatly improving its performance. - Exposing DLPack at the Python level for easy data exchange. - Changes to the promotion and comparisons of structured dtypes. - Improvements to f2py. The Python versions supported in this release are 3.8-3.10, 3.11 will be supported when it comes out. Note that 32 bit wheels are only provided for Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit OpenBLAS. Wheels can be downloaded from PyPI <https://pypi.org/project/numpy/1.23.0rc2/>; source archives, release notes, and wheel hashes are available on Github <https://github.com/numpy/numpy/releases/tag/v1.23.0rc2>. *Contributors* A total of 150 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - @DWesl - @GalaxySnail + - @code-review-doctor + - @h-vetinari - Aaron Meurer - Alexander Shadchin - Alexandre de Siqueira - Allan Haldane - Amrit Krishnan - Andrei Batomunkuev - Andrew J. Hesford + - Andrew Murray + - Andrey Andreyevich Bienkowski + - André Elimelek de Weber + - Andy Wharton + - Arryan Singh - Arushi Sharma - Bas van Beek - Bharat Raghunathan - Bhavuk Kalra + - Brigitta Sipőcz - Brénainn Woodsend + - Burlen Loring + - Caio Agiani + - Charles Harris - Chiara Marmo - Cornelius Roemer + - Dahyun Kim + - Damien Caliste - David Prosin + - Denis Laxalde - Developer-Ecosystem-Engineering - Devin Shanahan + - Diego Wang + - Dimitri Papadopoulos Orfanos - Ding Liu + - Diwakar Gupta + - Don Kirkby + - Emma Simon + - Eric Wieser - Evan Miller + - Evgeni Burovski - Evgeny Posenitskiy + - Ewout ter Hoeven + - Felix Divo - Francesco Andreuzzi + - Ganesh Kathiresan - Gaëtan de Menten - Geoffrey Gunter + - Hans Meine - Harsh Mishra + - Henry Schreiner - Hood Chatham + - Ilhan Polat - Inessa Pawson - Isuru Fernando - Ivan Gonzalez + - Ivan Meleshko + - Ivan Yashchuk + - Janus Heide + - Jarrod Millman - Jason Thai + - Jeremy Volkman + - Jesús Carrete Montaña + - Jhong-Ken Chen (陳仲肯) + - John Kirkham - John-Mark Gurney + - Jonathan Deng + - Joseph Fox-Rabinovitz - Jouke Witteveen + - Junyan Ou + - Jérôme Richard + - Kassian Sun + - Kazuki Sakamoto + - Kenichi Maehashi - Kevin Sheppard - Kilian Lieret + - Kushal Beniwal + - Leo Singer - Logan Thomas + - Lorenzo Mammana + - Margret Pax - Mariusz Felisiak + - Markus Mohrhard + - Mars Lee - Marten van Kerkwijk - Masamichi Hosoda + - Matthew Barber - Matthew Brett - Matthias Bussonnier - Matthieu Darbois - Matti Picus - Melissa Weber Mendonça - Michael Burkhart + - Morteza Mirzai + - Motahhar Mokf + - Muataz Attaia + - Muhammad Motawe + - Mukulika Pahari - Márton Gunyhó + - Namami Shanker + - Nihaal Sangha + - Niyas Sait - Omid Rajaei + - Oscar Gustafsson + - Ovee Jawdekar + - P. L. Lim + - Pamphile Roy + - Pantelis Antonoudiou + - Pearu Peterson - Peter Andreas Entschev - Peter Hawkins - Pierre de Buyl - Pieter Eendebak + - Pradipta Ghosh + - Rafael Cardoso Fernandes Sousa + - Raghuveer Devulapalli - Ralf Gommers - Raphael Kruse - Raúl Montón Pinillos - Robert Kern - Rohit Goswami - Ross Barnowski - Ruben Garcia + - Sadie Louise Bartholomew + - Saswat Das + - Sayed Adel - Sebastian Berg - Serge Guelton - Simon Surland Andersen + - Siyabend Ürün + - Somasree Majumder + - Soumya + - Stefan van der Walt - Stefano Miccoli + - Stephan Hoyer - Stephen Worsley + - Tania Allard - Thomas Duvernay + - Thomas Green + - Thomas J. Fan - Thomas Li + - Tim Hoffmann - Ting Sun + - Tirth Patel - Toshiki Kataoka - Tyler Reddy - Warren Weckesser - Yang Hau - Yoon, Jee Seok + Cheers, Charles Harris Reply allReplyForward <https://drive.google.com/u/0/settings/storage?hl=en&utm_medium=web&utm_sour…> <https://www.google.com/intl/en/policies/terms/> <https://www.google.com/intl/en/policies/privacy/> <https://www.google.com/gmail/about/policy/>

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NumPy 1.23.0rc1 released
by Charles R Harris May 27, 2022

May 27, 2022

Hi All, On behalf of the NumPy team, I'm pleased to announce the release of NumPy 1.23.0rc1. The NumPy 1.23.0 release continues the ongoing work to improve the handling and promotion of dtypes, increase the execution speed, clarify the documentation, and expire old deprecations. The highlights are: - Implementation of ``loadtxt`` in C, greatly improving its performance. - Exposing DLPack at the Python level for easy data exchange. - Changes to the promotion and comparisons of structured dtypes. - Improvements to f2py. The Python versions supported in this release are 3.8-3.10, 3.11 will be supported when it comes out. Note that 32 bit wheels are only provided for Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit OpenBLAS. Wheels can be downloaded from PyPI <https://pypi.org/project/numpy/1.23.0rc1/>; source archives, release notes, and wheel hashes are available on Github <https://github.com/numpy/numpy/releases/tag/v1.23.0rc1>. *Contributors* A total of 150 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - @DWesl - @GalaxySnail + - @code-review-doctor + - @h-vetinari - Aaron Meurer - Alexander Shadchin - Alexandre de Siqueira - Allan Haldane - Amrit Krishnan - Andrei Batomunkuev - Andrew J. Hesford + - Andrew Murray + - Andrey Andreyevich Bienkowski + - André Elimelek de Weber + - Andy Wharton + - Arryan Singh - Arushi Sharma - Bas van Beek - Bharat Raghunathan - Bhavuk Kalra + - Brigitta Sipőcz - Brénainn Woodsend + - Burlen Loring + - Caio Agiani + - Charles Harris - Chiara Marmo - Cornelius Roemer + - Dahyun Kim + - Damien Caliste - David Prosin + - Denis Laxalde - Developer-Ecosystem-Engineering - Devin Shanahan + - Diego Wang + - Dimitri Papadopoulos Orfanos - Ding Liu + - Diwakar Gupta + - Don Kirkby + - Emma Simon + - Eric Wieser - Evan Miller + - Evgeni Burovski - Evgeny Posenitskiy + - Ewout ter Hoeven + - Felix Divo - Francesco Andreuzzi + - Ganesh Kathiresan - Gaëtan de Menten - Geoffrey Gunter + - Hans Meine - Harsh Mishra + - Henry Schreiner - Hood Chatham + - Ilhan Polat - Inessa Pawson - Isuru Fernando - Ivan Gonzalez + - Ivan Meleshko + - Ivan Yashchuk + - Janus Heide + - Jarrod Millman - Jason Thai + - Jeremy Volkman + - Jesús Carrete Montaña + - Jhong-Ken Chen (陳仲肯) + - John Kirkham - John-Mark Gurney + - Jonathan Deng + - Joseph Fox-Rabinovitz - Jouke Witteveen + - Junyan Ou + - Jérôme Richard + - Kassian Sun + - Kazuki Sakamoto + - Kenichi Maehashi - Kevin Sheppard - Kilian Lieret + - Kushal Beniwal + - Leo Singer - Logan Thomas + - Lorenzo Mammana + - Margret Pax - Mariusz Felisiak + - Markus Mohrhard + - Mars Lee - Marten van Kerkwijk - Masamichi Hosoda + - Matthew Barber - Matthew Brett - Matthias Bussonnier - Matthieu Darbois - Matti Picus - Melissa Weber Mendonça - Michael Burkhart + - Morteza Mirzai + - Motahhar Mokf + - Muataz Attaia + - Muhammad Motawe + - Mukulika Pahari - Márton Gunyhó + - Namami Shanker + - Nihaal Sangha + - Niyas Sait - Omid Rajaei + - Oscar Gustafsson + - Ovee Jawdekar + - P. L. Lim + - Pamphile Roy + - Pantelis Antonoudiou + - Pearu Peterson - Peter Andreas Entschev - Peter Hawkins - Pierre de Buyl - Pieter Eendebak + - Pradipta Ghosh + - Rafael Cardoso Fernandes Sousa + - Raghuveer Devulapalli - Ralf Gommers - Raphael Kruse - Raúl Montón Pinillos - Robert Kern - Rohit Goswami - Ross Barnowski - Ruben Garcia + - Sadie Louise Bartholomew + - Saswat Das + - Sayed Adel - Sebastian Berg - Serge Guelton - Simon Surland Andersen + - Siyabend Ürün + - Somasree Majumder + - Soumya + - Stefan van der Walt - Stefano Miccoli + - Stephan Hoyer - Stephen Worsley + - Tania Allard - Thomas Duvernay + - Thomas Green + - Thomas J. Fan - Thomas Li + - Tim Hoffmann - Ting Sun + - Tirth Patel - Toshiki Kataoka - Tyler Reddy - Warren Weckesser - Yang Hau - Yoon, Jee Seok + Cheers, Charles Harris

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Large difference in output of optimize_scalar and brent
by ashwin .D May 24, 2022

May 24, 2022

Hello, I have enclosed a minimum reproducible example with data (as SO demands) and I am trying to use two methods in the scipy optimize package - https://docs.scipy.org/doc/scipy/reference/optimize.html One is minimize_scalar and the other is Brent's method. But both the outputs have large differences. Can anybody explain why ? Also I get a runtime error while running Brent- test.py:29: RuntimeWarning: invalid value encountered in power ls = np.sum((x1[1:] - x1[:-1]*np.sign(a)*a**dt)**2) Additionally the Brent one has another one if I specify a triple interval ala - dum = brent(func,brack=(-1,0,1),tol=3.0e-8) ValueError : Not a bracketing interval. https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.brent.h… But docs say that I can specify a triplet in the bracketing interval. I could have asked this on SO (and I still can) but this is more of a discussion oriented question so hence posted here. If a bug please advise appropriately as I can open on github. Regards, Ashwin.

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NumPy 1.22.4 released
by Charles R Harris May 21, 2022

May 21, 2022

Hi All, On behalf of the NumPy team, I'm pleased to announce the release of NumPy 1.22.4. NumPy 1.22.4 is a maintenance release that fixes bugs discovered after the 1.22.3 release. In addition, the wheels for this release are built using the recently released Cython 0.29.30, which should fix the reported problems with debugging <https://github.com/numpy/numpy/issues/21008>. The Python versions supported in this release are 3.8-3.10. Wheels can be downloaded from PyPI <https://pypi.org/project/numpy/1.22.4>; source archives, release notes, and wheel hashes are available on Github <https://github.com/numpy/numpy/releases/tag/v1.22.4>. Note that the Mac wheels are based on OS X 10.15 rather than 10.9 that was used in previous NumPy release cycles. *Contributors* A total of 12 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Alexander Shadchin - Bas van Beek - Charles Harris - Hood Chatham - Jarrod Millman - John-Mark Gurney + - Junyan Ou + - Mariusz Felisiak + - Ross Barnowski - Sebastian Berg - Serge Guelton - Stefan van der Walt *Pull requests merged* A total of 22 pull requests were merged for this release. - #21191: TYP, BUG: Fix ``np.lib.stride_tricks`` re-exported under the... - #21192: TST: Bump mypy from 0.931 to 0.940 - #21243: MAINT: Explicitly re-export the types in ``numpy._typing`` - #21245: MAINT: Specify sphinx, numpydoc versions for CI doc builds - #21275: BUG: Fix typos - #21277: ENH, BLD: Fix math feature detection for wasm - #21350: MAINT: Fix failing simd and cygwin tests. - #21438: MAINT: Fix failing Python 3.8 32-bit Windows test. - #21444: BUG: add linux guard per #21386 - #21445: BUG: Allow legacy dtypes to cast to datetime again - #21446: BUG: Make mmap handling safer in frombuffer - #21447: BUG: Stop using PyBytesObject.ob_shash deprecated in Python 3.11. - #21448: ENH: Introduce numpy.core.setup_common.NPY_CXX_FLAGS - #21472: BUG: Ensure compile errors are raised correctly - #21473: BUG: Fix segmentation fault - #21474: MAINT: Update doc requirements - #21475: MAINT: Mark ``npy_memchr`` with ``no_sanitize("alignment")`` on clang - #21512: DOC: Proposal - make the doc landing page cards more similar... - #21525: MAINT: Update Cython version to 0.29.30. - #21536: BUG: Fix GCC error during build configuration - #21541: REL: Prepare for the NumPy 1.22.4 release. - #21547: MAINT: Skip tests that fail on PyPy. Cheers, Charles Harris

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Reg scipy-1.8.1-cp310-cp310-win32.whl release
by rameshkrishna.ambati＠gmail.com May 19, 2022

May 19, 2022

Could we expect scipy-1.8.1-cp310-cp310-win32.whl package in the near future.

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Wanting to take a FFT transform of a irregularly spaced sample
by ashwin .D May 18, 2022

May 18, 2022

Hello, I have looked at both these answers from SO - https://stackoverflow.com/questions/34428886/discrete-fourier-transformatio… and https://stackoverflow.com/questions/25735153/plotting-a-fast-fourier-transf… My question is somewhat similar. I have data from a CSV file that has measurements of a mean sea level pressure. The data is available every 5 minutes. That means 8928 sample points over a month. But during a hurricane event there was a power failure and only 8867 data points are available. I am short by 61 points to get a uniformly spaced sample. I am wanting to take an FFT of the data in order to check for periodicity, waves and frequencies there of. What are my best options ? Best regards, Ashwin.

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