Mailman 3 February 2020 - SciPy-User

How to display a RGB image (MFISH)?
by jp 03 Apr '23

03 Apr '23

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 28 Jul '22

28 Jul '22

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 14 Mar '22

14 Mar '22

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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[ANN] pvlib participating in GSoC
by Dr. Mark Alexander Mikofski PhD 27 Feb '20

27 Feb '20

Excited to announce that pvlib python <https://pvlib-python.readthedocs.io/en/latest/> is participating in its first ever Google Summer of Code GSoC under the NumFOCUS umbrella. If you are a student interested in modeling renewable solar energy please apply: https://summerofcode.withgoogle.com/organizations/4727917315096576/ For project ideas, take a look at the pvlib github wiki: https://summerofcode.withgoogle.com/organizations/4727917315096576/ and reach out on our Google Groups forum: https://groups.google.com/forum/#!forum/pvlib-python We look forward to hearing from you! -- Mark Mikofski, PhD (2005) *Fiat Lux*

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[ANN] 13ᵗʰ Advanced Scientific Programming in Python in Ghent, Belgium, 31 August—5 September, 2020
by Tiziano Zito 13 Feb '20

13 Feb '20

13ᵗʰ Advanced Scientific Programming in Python ============================================== a Summer School by the ASPP faculty and the Ghent University https://aspp.school Scientists spend more and more time writing, maintaining, and debugging software. While techniques for doing this efficiently have evolved, only few scientists have been trained to use them. As a result, instead of doing their research, they spend far too much time writing deficient code and reinventing the wheel. In this course we will present a selection of advanced programming techniques and best practices which are standard in the industry, but especially tailored to the needs of a programming scientist. Lectures are devised to be interactive and to give the students enough time to acquire direct hands-on experience with the materials. Students will work in pairs throughout the school and will team up to practice the newly learned skills in a real programming project — an entertaining computer game. We use the Python programming language for the entire course. Python works as a simple programming language for beginners, but more importantly, it also works great in scientific simulations and data analysis. We show how clean language design, ease of extensibility, and the great wealth of open source libraries for scientific computing and data visualization are driving Python to become a standard tool for the programming scientist. This school is targeted at Master or PhD students and Post-docs from all areas of science. Competence in Python or in another language such as Java, C/C++, MATLAB, or R is absolutely required. Basic knowledge of Python and of a version control system such as git, subversion, mercurial, or bazaar is assumed. Participants without any prior experience with Python and/or git should work through the proposed introductory material before the course. We are striving hard to get a pool of students which is international and gender-balanced. Date & Location =============== 31 August–5 September, 2020. Ghent, Belgium. Application =========== You can apply online: https://aspp.school/wiki/applications Application deadline: 23:59 UTC, Sunday 24 May, 2020 There will be no deadline extension, so be sure to apply on time. Be sure to read the FAQ before applying: https://aspp.school/wiki/faq Participation is for free, i.e. no fee is charged! Accommodation in the student residence comes at no costs for participants. We are trying to arrange financial coverage for food expenses too, but this may not work. Participants however should take care of travel expenses by themselves. Program ======= • Version control with git and how to contribute to open source projects with GitHub • Best practices in data visualization • Testing and debugging scientific code • Advanced NumPy • Organizing, documenting, and distributing scientific code • Advanced scientific Python: context managers and generators • Writing parallel applications in Python • Profiling and speeding up scientific code with Cython and numba • Programming in teams Faculty ======= • Caterina Buizza, Personal Robotics Lab, Imperial College London UK • Lisa Schwetlick, Experimental and Biological Psychology, Universität Potsdam Germany • Nelle Varoquaux, CNRS, TIMC-IMAG, University Grenoble Alpes France • Nicolas P. Rougier, Inria Bordeaux Sud-Ouest, Institute of Neurodegenerative Disease, University of Bordeaux France • Pamela Hathway, Neural Reckoning, Imperial College London UK • Pietro Berkes, NAGRA Kudelski, Lausanne Switzerland • Rike-Benjamin Schuppner, Institute for Theoretical Biology, Humboldt-Universität zu Berlin Germany • Tiziano Zito, Department of Psychology, Humboldt-Universität zu Berlin Germany • Zbigniew Jędrzejewski-Szmek, Red Hat Inc., Warsaw Poland Organizers ========== Head of the organization for ASPP and responsible for the scientific program: • Tiziano Zito, Department of Psychology, Humboldt-Universität zu Berlin Germany Local team: • Nina Turk, Photonics Research Group, INTEC, Ghent University – imec Belgium • Freya Acar, Office for Data and Information, City of Ghent Belgium • Joan Juvert Institutional organizers: • Wim Bogaerts, Photonics Research Group, INTEC, Ghent University –imec Belgium • Sven Degroeve, VIB-UGent Center for Medical Biotechnology, Ghent Belgium • Jeroen Famaey, Department of Mathematics and Computer Science, University of Antwerp – iMinds Belgium • Bernard Manderick, Artificial Intelligence Lab, Vrije Universiteit Brussel Belgium Website: https://aspp.school Contact: info(a)aspp.school

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[ANN] 13ᵗʰ Advanced Scientific Programming in Python in Ghent, Belgium, 31 August—5 September, 2020
by ASPP 13 Feb '20

13 Feb '20

13ᵗʰ Advanced Scientific Programming in Python ============================================== a Summer School by the ASPP faculty and the Ghent University https://aspp.school Scientists spend more and more time writing, maintaining, and debugging software. While techniques for doing this efficiently have evolved, only few scientists have been trained to use them. As a result, instead of doing their research, they spend far too much time writing deficient code and reinventing the wheel. In this course we will present a selection of advanced programming techniques and best practices which are standard in the industry, but especially tailored to the needs of a programming scientist. Lectures are devised to be interactive and to give the students enough time to acquire direct hands-on experience with the materials. Students will work in pairs throughout the school and will team up to practice the newly learned skills in a real programming project — an entertaining computer game. We use the Python programming language for the entire course. Python works as a simple programming language for beginners, but more importantly, it also works great in scientific simulations and data analysis. We show how clean language design, ease of extensibility, and the great wealth of open source libraries for scientific computing and data visualization are driving Python to become a standard tool for the programming scientist. This school is targeted at Master or PhD students and Post-docs from all areas of science. Competence in Python or in another language such as Java, C/C++, MATLAB, or R is absolutely required. Basic knowledge of Python and of a version control system such as git, subversion, mercurial, or bazaar is assumed. Participants without any prior experience with Python and/or git should work through the proposed introductory material before the course. We are striving hard to get a pool of students which is international and gender-balanced. Date & Location =============== 31 August–5 September, 2020. Ghent, Belgium. Application =========== You can apply online: https://aspp.school/wiki/applications Application deadline: 23:59 UTC, Sunday 24 May, 2020 There will be no deadline extension, so be sure to apply on time. Be sure to read the FAQ before applying: https://aspp.school/wiki/faq Participation is for free, i.e. no fee is charged! Accommodation in the student residence comes at no costs for participants. We are trying to arrange financial coverage for food expenses too, but this may not work. Participants however should take care of travel expenses by themselves. Program ======= • Version control with git and how to contribute to open source projects with GitHub • Best practices in data visualization • Testing and debugging scientific code • Advanced NumPy • Organizing, documenting, and distributing scientific code • Advanced scientific Python: context managers and generators • Writing parallel applications in Python • Profiling and speeding up scientific code with Cython and numba • Programming in teams Faculty ======= • Caterina Buizza, Personal Robotics Lab, Imperial College London UK • Lisa Schwetlick, Experimental and Biological Psychology, Universität Potsdam Germany • Nelle Varoquaux, CNRS, TIMC-IMAG, University Grenoble Alpes France • Nicolas P. Rougier, Inria Bordeaux Sud-Ouest, Institute of Neurodegenerative Disease, University of Bordeaux France • Pamela Hathway, Neural Reckoning, Imperial College London UK • Pietro Berkes, NAGRA Kudelski, Lausanne Switzerland • Rike-Benjamin Schuppner, Institute for Theoretical Biology, Humboldt-Universität zu Berlin Germany • Tiziano Zito, Department of Psychology, Humboldt-Universität zu Berlin Germany • Zbigniew Jędrzejewski-Szmek, Red Hat Inc., Warsaw Poland Organizers ========== Head of the organization for ASPP and responsible for the scientific program: • Tiziano Zito, Department of Psychology, Humboldt-Universität zu Berlin Germany Local team: • Nina Turk, Photonics Research Group, INTEC, Ghent University – imec Belgium • Freya Acar, Office for Data and Information, City of Ghent Belgium • Joan Juvert Institutional organizers: • Wim Bogaerts, Photonics Research Group, INTEC, Ghent University –imec Belgium • Sven Degroeve, VIB-UGent Center for Medical Biotechnology, Ghent Belgium • Jeroen Famaey, Department of Mathematics and Computer Science, University of Antwerp – iMinds Belgium • Bernard Manderick, Artificial Intelligence Lab, Vrije Universiteit Brussel Belgium Website: https://aspp.school Contact: info(a)aspp.school

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How to create a request to change a function?
by Augusto Dufloth 01 Feb '20

01 Feb '20

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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