Mailman 3 November 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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NumPy 1.23.2 release
by Charles R Harris March 22, 2023

March 22, 2023

Hi All, On behalf of the NumPy team, I am pleased to announce the release of NumPy 1.23.2. NumPy 1.23.2 is a maintenance release that fixes bugs discovered after the 1.23.1 release. Notable features are: - Typing changes needed for Python 3.11 - Wheels for Python 3.11.0rc1 The Python versions supported for this release are 3.8-3.11. Wheels can be downloaded from PyPI <https://pypi.org/project/numpy/1.23.2>; source archives, release notes, and wheel hashes are available on Github <https://github.com/numpy/numpy/releases/tag/v1.23.2>. *Contributors* A total of 9 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Alexander Grund + - Bas van Beek - Charles Harris - Jon Cusick + - Matti Picus - Michael Osthege + - Pal Barta + - Ross Barnowski - Sebastian Berg *Pull requests merged* A total of 15 pull requests were merged for this release. - #22030: ENH: Add ``__array_ufunc__`` typing support to the ``nin=1`` ufuncs - #22031: MAINT, TYP: Fix ``np.angle`` dtype-overloads - #22032: MAINT: Do not let ``_GenericAlias`` wrap the underlying classes'... - #22033: TYP,MAINT: Allow ``einsum`` subscripts to be passed via integer... - #22034: MAINT,TYP: Add object-overloads for the ``np.generic`` rich comparisons - #22035: MAINT,TYP: Allow the ``squeeze`` and ``transpose`` method to... - #22036: BUG: Fix subarray to object cast ownership details - #22037: BUG: Use ``Popen`` to silently invoke f77 -v - #22038: BUG: Avoid errors on NULL during deepcopy - #22039: DOC: Add versionchanged for converter callable behavior. - #22057: MAINT: Quiet the anaconda uploads. - #22078: ENH: reorder includes for testing on top of system installations... - #22106: TST: fix test_linear_interpolation_formula_symmetric - #22107: BUG: Fix skip condition for test_loss_of_precision[complex256] - #22115: BLD: Build python3.11.0rc1 wheels. Cheers, Charles Harris

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NumPy 1.24.0rc1 released
by Charles R Harris Nov. 24, 2022

Nov. 24, 2022

Hi All, On behalf of the NumPy team, I'm pleased to announce the release of NumPy 1.24.0rc1. The NumPy 1.24.0 release continues the ongoing work to improve the handling and promotion of dtypes, increase execution speed, and clarify the documentation. There are also a large number of new and expired deprecations due to changes in promotion and cleanups. This might be called a deprecation release. Highlights are - Many new deprecations. - Many expired deprecations. - New f2py features and fixes. - New "dtype" and "casting" keywords for stacking functions. The Python versions supported in this release are 3.8-3.11 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. Wheels can be downloaded from PyPI <https://pypi.org/project/numpy/1.24.0rc1/>; source archives, release notes, and wheel hashes are available on Github <https://github.com/numpy/numpy/releases/tag/v1.24.0rc1>. The Python 3.8 aarch64 wheel is missing from this pre-release due to build problems. *Contributors* A total of 174 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - @DWesl - @h-vetinari - Aaron Meurer - Aayush Agrawal + - Adam Knapp + - Adarsh Singh + - Al-Baraa El-Hag - Alban Desmaison + - Ales Crocaro + - Alex + - Alexander Grund + - Alexander Kanavin + - Andras Deak - Angéllica Araujo + - Anselm Hahn + - Ari Cooper Davis + - Axel Huebl + - Bas van Beek - Bhavuk Kalra - Bram Ton + - Brent Tan + - Brigitta Sipőcz - Callum O'Riley + - Charles Harris - Chiara Marmo - Christoph Reiter - Damien Caliste - Dan Schult + - Daniel da Silva - DanielHabenicht + - Dave Goel + - David Gilbertson + - Developer-Ecosystem-Engineering - Digya Acharya + - Dimitri Papadopoulos Orfanos - Eric-Shang + - Evgeni Burovski - Ewout ter Hoeven - Felix Hirwa Nshuti + - Frazer McLean + - Ganesh Kathiresan - Gavin Zhang + - Gaëtan de Menten - Greg Lucas - Greg Sadetsky + - Gregory P. Smith [Google LLC] + - Hameer Abbasi - Hannah Aizenman + - Hood Chatham - I-Shen Leong - Iantra Solari + - Ikko Ashimine + - Inessa Pawson - Jake Bowhay + - Jake Close + - Jarrod Millman - Jason Thai - Jessé Pires + - Jhonatan Cunha + - Jingxuan He + - Johnathon Cusick + - Jon Morris - Jordy Williams + - Josh Wilson - João Fontes Gonçalves + - Juan Luis Cano Rodríguez - Jyn Spring 琴春 + - KIU Shueng Chuan - Karl Otness + - Kevin Sheppard - Kinshuk Dua + - Leo Fang - Leona Taric + - Lev Maximov + - Lillian Zha + - Loïc Estève - M. Eric Irrgang + - Mariusz Felisiak - Mark Harfouche - Martin Zacho + - Matheus Santana Patriarca + - Matt Williams + - Matteo Raso + - Matthew Barber - Matthew Brett - Matthew Sterrett + - Matthias Bussonnier - Matthias Koeppe + - Matti Picus - Meekail Zain + - Melissa Weber Mendonça - Michael Osthege + - Michael Siebert + - Mike Toews - Miki Watanabe + - Miles Cranmer + - MilesCranmer + - Monika Kubek + - Muhammad Jarir Kanji + - Mukulika Pahari - Namami Shanker - Nathan Goldbaum + - Nathan Rooy + - Navpreet Singh + - Noritada Kobayashi + - Oleksiy Kononenko + - Omar + - Pal Barta + - Pamphile Roy - Patrick Hoefler + - Pearu Peterson - Pedro Nacht + - Petar Mlinarić + - Pey Lian Lim - Pieter Eendebak - Pradipta Ghosh - Pranab Das + - Precision Wordcraft LLC + - PrecisionWordcraft + - Rafael CF Sousa + - Rafael Cardoso Fernandes Sousa - Rafael Sousa + - Raghuveer Devulapalli - Ralf Gommers - Rin Cat (鈴猫) + - Robert Kern - Rohit Davas + - Rohit Goswami - Ross Barnowski - Ruth Comer + - Sabiha Tahsin Soha + - Sachin Krishnan T V + - Sanjana M Moodbagil + - Sanya Sinha + - Sarah Coffland + - Saransh Chopra + - Satish Kumar Mishra + - Satish Mishra + - Sayed Adel - Schrijvers Luc + - Sebastian Berg - Serge Guelton - Seva Lotoshnikov + - Shashank Gupta + - Shoban Chiddarth + - Shreya Singh + - Shreyas Joshi + - Sicheng Zeng + - Simran Makandar + - Srimukh Sripada + - Stefan van der Walt - Stefanie Molin + - Stuart Archibald - Tania Allard - Thomas A Caswell - Thomas Kastl + - Thomas Mansencal + - Tony Newton / Teng Liu + - Toshiki Kataoka - Tyler Reddy - Vardhaman Kalloli + - Warren Weckesser - Will Ayd + - William Stein + - XinRu Lin + - Yin Li + - Yulv-git + - Yunika Bajracharya + - Zachary Blackwood + - amagicmuffin + - dg3192 + - juztamau5 + - swagatip + - 渡邉美希 + Cheers, Charles Harris

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How to add an if statement in an objective function in scipy.optimize
by Zeina Abu-Aisheh Nov. 23, 2022

Nov. 23, 2022

I have data (x) that represents some angles that looks like: [20, 30, 48, 46, 50, 70, 100], and a categorical ground truth which has two classes (0 and 1) e.g. [0, 0, 0, 0, 1, 1, 1]. I want to find a threshold that decides when an angle belongs to the class 0 or 1. I was doing the following: from scipy.optimize import curve_fit def objective(x, threshold): if x > threshold: return 1 else: return 0 # curve fit threshold, _ = curve_fit(objective, x, y) however, this code didn't work and I got this error: ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() it seems that the problem was in having the if statement in the objective function, how could I use optimise to get the best threshold in such a case? Thanks

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Release of NumPy 1.23.5
by Charles R Harris Nov. 20, 2022

Nov. 20, 2022

Hi All, On behalf of the NumPy team, I am pleased to announce the release of NumPy 1.23.5. NumPy 1.23.5 is a maintenance release that fixes bugs discovered after the 1.23.4 release and keeps the build infrastructure current. The Python versions supported for this release are 3.8-3.11. Wheels can be downloaded from PyPI <https://pypi.org/project/numpy/1.23.5>; source archives, release notes, and wheel hashes are available on Github <https://github.com/numpy/numpy/releases/tag/v1.23.5>. *Contributors* A total of 7 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - @DWesl - Aayush Agrawal + - Adam Knapp + - Charles Harris - Navpreet Singh + - Sebastian Berg - Tania Allard *Pull requests merged* A total of 10 pull requests were merged for this release. - #22489: TST, MAINT: Replace most setup with setup_method (also teardown) - #22490: MAINT, CI: Switch to cygwin/cygwin-install-action@v2 - #22494: TST: Make test_partial_iteration_cleanup robust but require leak... - #22592: MAINT: Ensure graceful handling of large header sizes - #22593: TYP: Spelling alignment for array flag literal - #22594: BUG: Fix bounds checking for ``random.logseries`` - #22595: DEV: Update GH actions and Dockerfile for Gitpod - #22596: CI: Only fetch in actions/checkout - #22597: BUG: Decrement ref count in gentype_reduce if allocated memory... - #22625: BUG: Histogramdd breaks on big arrays in Windows Cheers, Charles Harris

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Minimize problem-can i get a help to code
by Cuneyt Ugur Nov. 5, 2022

Nov. 5, 2022

Decision variables x3 x1 x2 Constraints x1+ x2 ≤ x3 Objective function min (x1)*(30-x1) -3*x1 + x2*(50-2*x2)- 2*x2 -x3*10

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dplyr-like Python library
by David Hagen Nov. 1, 2022

Nov. 1, 2022

I wrote a dplyr-like wrapper for Polars <https://github.com/drhagen/tabeline/> that some of you might find interesting. Tabeline is in the early stages, but it already has a documentation website <https://tabeline.drhagen.com/> and decent test coverage. It uses Polars underneath to get the speed, but does a lot of work to smooth out Polars's edge cases. It can convert to/from Pandas and to/from Polars, so it is easy to slot into an existing workflow. Obviously, bug reports and other ideas are welcome!

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ANN: pvlib-0.9.2 released
by Dr. Mark Alexander Mikofski PhD Nov. 1, 2022

Nov. 1, 2022

Dear Pythonistas and solar power enthusiasts, The maintainers are happy to announce a new release of pvlib python: software for simulating performance of photovoltaic solar energy systems. *See what's new for v0.9.2:* ** *https://pvlib-python.readthedocs.io/en/stable/whatsnew.html *Releases are available from PyPI and the conda-forge channel:* * https://pypi.org/project/pvlib/ * https://anaconda.org/conda-forge/pvlib * https://anaconda.org/conda-forge/pvlib-python *Note: you can now install from conda-forge using either "pvlib" or "pvlib-python"* *Read the Documentation:* * https://pvlib-python.readthedocs.io/en/stable/index.html *Report issues & contribute:* * https://github.com/pvlib/pvlib-python *Highlights:* * Albedo can be entered as a column in weather DataFrame when running a model chain. This can be used to enter a time series instead of just monthly values. * A new function calc_surface_orientation() returns tracker surface tilt and azimuth when given tracker rotation and axis tilt. * There's a new example in the gallery to calculate backside irradiance using pvfactors. * Dropped support for Python-3.6 and increased required pandas to v0.25.0 * A new build system that conforms to PEP 517 & PEP518 * There were several new contributors. *Thank you for using pvlib python!* -- Mark Mikofski, PhD (2005) *Fiat Lux*

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NumPy 1.23. 3 Release
by Charles R Harris Nov. 1, 2022

Nov. 1, 2022

Hi All, On behalf of the NumPy team, I am pleased to announce the release of NumPy 1.23.3. NumPy 1.23.3 is a maintenance release that fixes bugs discovered after the 1.23.2 release. There is no major theme for this release, the main improvements are for some downstream builds and some annotation corner cases. The Python versions supported for this release are 3.8-3.11. Wheels can be downloaded from PyPI <https://pypi.org/project/numpy/1.23.3>; source archives, release notes, and wheel hashes are available on Github <https://github.com/numpy/numpy/releases/tag/v1.23.3>. Note that we will move to MacOS 11 for the NumPy 1.23.4 release, the 10.15 version currently used will no longer be supported by our build infrastructure at that point. *Contributors* A total of 16 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Aaron Meurer - Bas van Beek - Charles Harris - Ganesh Kathiresan - Gavin Zhang + - Iantra Solari+ - Jyn Spring 琴春 + - Matti Picus - Rafael Cardoso Fernandes Sousa - Rafael Sousa + - Ralf Gommers - Rin Cat (鈴猫) + - Saransh Chopra + - Sayed Adel - Sebastian Berg - Serge Guelton *Pull requests merged* A total of 14 pull requests were merged for this release. - #22136: BLD: Add Python 3.11 wheels to aarch64 build - #22148: MAINT: Update setup.py for Python 3.11. - #22155: CI: Test NumPy build against old versions of GCC(6, 7, 8) - #22156: MAINT: support IBM i system - #22195: BUG: Fix circleci build - #22214: BUG: Expose heapsort algorithms in a shared header - #22215: BUG: Support using libunwind for backtrack - #22216: MAINT: fix an incorrect pointer type usage in f2py - #22220: BUG: change overloads to play nice with pyright. - #22221: TST,BUG: Use fork context to fix MacOS savez test - #22222: TYP,BUG: Reduce argument validation in C-based ``__class_getitem__`` - #22223: TST: ensure ``np.equal.reduce`` raises a ``TypeError`` - #22224: BUG: Fix the implementation of numpy.array_api.vecdot - #22230: BUG: Better report integer division overflow (backport) Cheers, Charles Harris

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ANN: pvlib-0.9.3 released
by Dr. Mark Alexander Mikofski PhD Nov. 1, 2022

Nov. 1, 2022

Dear Pythonistas and solar power enthusiasts, The maintainers are happy to announce a new release of pvlib python: software for simulating performance of photovoltaic solar energy systems. *See what's new for v0.9.3:* ** *https://pvlib-python.readthedocs.io/en/stable/whatsnew.html *Releases are available from PyPI and the conda-forge channel:* * https://pypi.org/project/pvlib/ * https://anaconda.org/conda-forge/pvlib * https://anaconda.org/conda-forge/pvlib-python *Note: you can now install from conda-forge using either "pvlib" or "pvlib-python"* *Read the Documentation:* * https://pvlib-python.readthedocs.io/en/stable/index.html *Report issues & contribute:* * https://github.com/pvlib/pvlib-python *Highlights:* * Anton Driesse has joined the maintainers. Anton has been a consistent contributor, a frequent poster on Google Groups, and a fixture in the PV modeling community for many years. We gladly welcome Anton and are grateful for his support. * Several new functions to calculate spectral mismatch <https://pvlib-python.readthedocs.io/en/stable/reference/generated/pvlib.spe…> of photovoltaic devices between incident and reference spectra. Compare this to the existing FSLR spectral mismatch function. * The Townsend snow loss model <https://pvlib-python.readthedocs.io/en/stable/reference/generated/pvlib.sno…> is now available. Compare this with the existing snow loss model from Marion. * A new generic linear temperature model <https://pvlib-python.readthedocs.io/en/stable/reference/generated/pvlib.tem…> function and class that can convert between PVsyst, Faiman, and SAPM thermal model coefficients. * A new altitude look-up function <https://pvlib-python.readthedocs.io/en/stable/reference/generated/pvlib.loc…> using public data from Mapzen, a project for open map data hosted by AWS. * There were four new first time contributors! Thank you! * There was a training using JupyterHub at PVPMC 2022 <https://pvsc-python-tutorials.github.io/PVPMC_2022>. Check it out! *Thank you for using pvlib python!* -- Mark Mikofski, PhD (2005) *Fiat Lux*

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