Mailman 3 January 2020 - 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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Help required regding Eigenvectors
by Sudheer Phani March 14, 2022

March 14, 2022

Hello All, I have been encountering some strange problems with the calculation of eigen vectors using python. The problem is with the sign of the eigen vectors calculated. On Very few occasions the eigen vectors calculated using python have an opposite sign than the actual eigenvectors, though the magnitude is correct. Can any one of you plz help me in this regard and suggest me some solution if you have encoutered similar problems . Any help in this regd is appreciated Thanks in Advace regds Sudheer

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How to create a request to change a function?
by Augusto Dufloth Feb. 1, 2020

Feb. 1, 2020

Hello, I have a request to change one of scipy’s function. I am trying to use odeint to integrate a set of equations of motion. My state equations rely on time dependent inputs. And these inputs are numpy arrays. When I do a flight path reconstruction, the inputs comes from the inertial system of the aircraft and I plug it into the state equations, so I get the deterministic position of the aircraft and than I can compare it to the measured values. The issue is that I can’t input an array. Searching stackoverflow I saw solutions using for-loops and assigning an arg for each time step. This is counter productive and create a huge time calculation for long arrays. I created my own C-dll to deal with this for loop issue, but it’s super counter productive. Can we get an option that the input args are arrays if same size of t, and as the state is integrated, the index of the arg follows the states? Thanks for your help Augusto -- "The greatest challenge to any thinker is stating the problem in a way that will allow a solution." - Bertrand Russell

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SciPy 2020 Call for Submissions is open!
by Melissa Mendonça Jan. 29, 2020

Jan. 29, 2020

Apologies for crossposting. ===== SciPy 2020, the 19th annual Scientific Computing with Python conference, will be held July 6-12, 2020 in Austin, Texas. The annual SciPy Conference brings together over 900 participants from industry, academia, and government to showcase their latest projects, learn from skilled users and developers, and collaborate on code development. The call for SciPy 2020 talks, posters, and tutorials is now open through February 11, 2020. Talks and Posters (July 8-10, 2020) In addition to the general track, this year will have the following specialized tracks, mini symposia, and sessions: Tracks High Performance Python Machine Learning and Data Science Mini Symposia Astronomy and Astrophysics Biology and Bioinformatics Earth, Ocean, Geo and Atmospheric Science Materials Science Special Sessions Maintainers Track SciPy Tools Plenary Session For additional details and instructions, please see the conference website. <https://www.scipy2020.scipy.org/> Tutorials (July 6-7, 2020) Tutorials should be focused on covering a well-defined topic in a hands-on manner. We are looking for awesome techniques or packages, helping new or advanced Python programmers develop better or faster scientific applications. We encourage submissions to be designed to allow at least 50% of the time for hands-on exercises even if this means the subject matter needs to be limited. Tutorials will be 4 hours in duration. In your tutorial application, you can indicate what prerequisite skills and knowledge will be needed for your tutorial, and the approximate expected level of knowledge of your students (i.e., beginner, intermediate, advanced). Instructors of accepted tutorials will receive a stipend. For examples of content and format, you can refer to tutorials from past SciPy tutorial sessions (SciPy 2018 <https://na-admin.eventscloud.com/emarketing/go.php?i=735095&e=amlsbGNAZW50a…>, SciPy2019 <https://na-admin.eventscloud.com/emarketing/go.php?i=735095&e=amlsbGNAZW50a…> ) and some accepted submissions <https://na-admin.eventscloud.com/emarketing/go.php?i=735095&e=amlsbGNAZW50a…>. For additional details and instructions see the conference website <https://na-admin.eventscloud.com/emarketing/go.php?i=735095&e=amlsbGNAZW50a…> . Submission page: https://easychair.org/conferences/?conf=scipy2020 Submission Deadline: February 11, 2020 - Melissa Weber Mendonça Diversity Committee Co-Chair

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How to read row_name, col_name, value format TSV into a sparse matrix?
by Peng Yu Jan. 29, 2020

Jan. 29, 2020

Suppose that I have a TSV file in the following format. ``` row_name<TAB>col_name<TAB>value ``` Is there an easy way to read it into a sparse matrix format in scipy? Thanks. I don't see such examples in the doc. https://docs.scipy.org/doc/scipy/reference/sparse.html -- Regards, Peng

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[ANN] pvlib python v0.7.1: predicting power for solar energy
by Dr. Mark Alexander Mikofski PhD Jan. 21, 2020

Jan. 21, 2020

pvlib has a new minor release, v0.7.1 Release Notes: https://pvlib-python.readthedocs.io/en/v0.7.1/whatsnew.html PyPI: https://pypi.org/project/pvlib/ Read the Docs: https://pvlib-python.readthedocs.io/en/latest/ GitHub: https://github.com/pvlib/pvlib-python New examples gallery: https://pvlib-python.readthedocs.io/en/stable/auto_examples/index.html -- Mark Mikofski, PhD (2005) *Fiat Lux*

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Building Python wheels with Fortran on Windows 10 under Python 3.8
by Johann Rohwer Jan. 13, 2020

Jan. 13, 2020

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ANN: Astropy v4.0 released
by Erik Tollerud Jan. 9, 2020

Jan. 9, 2020

Dear colleagues, We are very happy to announce the v4.0 release of the Astropy package, a core Python package for Astronomy: http://www.astropy.org Astropy is a community-driven Python package intended to contain much of the core functionality and common tools needed for astronomy and astrophysics. It is part of the Astropy Project, which aims to foster an ecosystem of interoperable astronomy packages for Python. New and improved major functionality in this release includes: * Support for Planck 2018 Cosmological Parameters * Improved Consistency of Physical Constants and Units * Scientific enhancements to the Galactocentric Frame * New ymdhms Time Format * New Context Manager for plotting time values * Dynamic and improved handling of leap second * Major Improvements in Compatibility of Quantity Objects with NumPy Functions * Multiple interface improvements to WCSAxes * Fitting of WCS to Pairs of Pixel/World Coordinates * Support for WCS Transformations between Pixel and Time Values * Improvements to Folding for Time Series * New Table Methods and significant performance improvements for Tables * Improved downloading and caching of remote files In addition, hundreds of smaller improvements and fixes have been made. An overview of the changes is provided at: http://docs.astropy.org/en/stable/whatsnew/4.0.html The Astropy v4.0.x series now replaces v2.0.x as the long term support release, and will be supported until the end of 2021. Also note that the Astropy 4.x series only supports Python 3. Python 2 users can continue to use the 2.x series but as of now it is no longer supported (as Python 2 itself is no longer supported). For assistance converting Python 2 code to Python 3, see the Python 3 for scientists conversion guide. Instructions for installing Astropy are provided on our website, and extensive documentation can be found at: http://docs.astropy.org If you make use of the Anaconda Python Distribution, you can update to Astropy v4.0 with: conda update astropy Whereas if you usually use pip, you can do: pip install astropy --upgrade Please report any issues, or request new features via our GitHub repository: https://github.com/astropy/astropy/issues Over 350 developers have contributed code to Astropy so far, and you can find out more about the team behind Astropy here: http://www.astropy.org/team.html If you use Astropy directly for your work, or as a dependency to another package, please remember to acknowledgment it by citing the appropriate Astropy paper. For the most up-to-date suggestions, see the acknowledgement page, but as of this release the recommendation is: This research made use of Astropy, a community-developed core Python package for Astronomy (Astropy Collaboration, 2018). Special thanks to the coordinator for this release: Brigitta Sipocz. We hope that you enjoy using Astropy as much as we enjoyed developing it! Erik Tollerud, Tom Robitaille, Kelle Cruz, and Tom Aldcroft on behalf of The Astropy Collaboration https://www.astropy.org/announcements/release-4.0.html

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NumPy 1.18.1 released
by Charles R Harris Jan. 6, 2020

Jan. 6, 2020

Hi All, On behalf of the NumPy team I am pleased to announce that NumPy 1.18.1 has been released. This release contains fixes for bugs reported against NumPy 1.18.0. Two bugs in particular that caused widespread problems downstream were: - The cython random extension test was not using a temporary directory for building, resulting in a permission violation. Fixed. - Numpy distutils was appending -std=c99 to all C compiler runs, leading to changed behavior and compile problems downstream. That flag is now only applied when building numpy C code. The Python versions supported in this release are 3.5-3.8. Downstream developers should use Cython >= 0.29.14 for Python 3.8 support and OpenBLAS >= 3.7 to avoid errors on the Skylake architecture. Wheels for this release can be downloaded from PyPI <https://pypi.org/project/numpy/1.18.1>, source archives and release notes are available from Github <https://github.com/numpy/numpy/releases/tag/v1.18.1>. *Contributors* A total of 7 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Charles Harris - Matti Picus - Maxwell Aladago - Pauli Virtanen - Ralf Gommers - Tyler Reddy - Warren Weckesser *Pull requests merged* A total of 13 pull requests were merged for this release. - `#15158 <https://github.com/numpy/numpy/pull/15158>`__: MAINT: Update pavement.py for towncrier. - `#15159 <https://github.com/numpy/numpy/pull/15159>`__: DOC: add moved modules to 1.18 release note - `#15161 <https://github.com/numpy/numpy/pull/15161>`__: MAINT, DOC: Minor backports and updates for 1.18.x - `#15176 <https://github.com/numpy/numpy/pull/15176>`__: TST: Add assert_array_equal test for big integer arrays - `#15184 <https://github.com/numpy/numpy/pull/15184>`__: BUG: use tmp dir and check version for cython test. - `#15220 <https://github.com/numpy/numpy/pull/15220>`__: BUG: distutils: fix msvc+gfortran openblas handling corner case - `#15221 <https://github.com/numpy/numpy/pull/15221>`__: BUG: remove -std=c99 for c++ compilation - `#15222 <https://github.com/numpy/numpy/pull/15222>`__: MAINT: unskip test on win32 - `#15223 <https://github.com/numpy/numpy/pull/15223>`__: TST: add BLAS ILP64 run in Travis & Azure - `#15245 <https://github.com/numpy/numpy/pull/15245>`__: MAINT: only add --std=c99 where needed - `#15246 <https://github.com/numpy/numpy/pull/15246>`__: BUG: lib: Fix handling of integer arrays by gradient. - `#15247 <https://github.com/numpy/numpy/pull/15247>`__: MAINT: Do not use private Python function in testing - `#15250 <https://github.com/numpy/numpy/pull/15250>`__: REL: Prepare for the NumPy 1.18.1 release. Cheers, Charles Harris

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