Mailman 3 May 2016 - SciPy-User

How to display a RGB image (MFISH)?
by jp April 2, 2023

April 2, 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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EuroSciPy 2016
by Pierre de Buyl June 7, 2016

June 7, 2016

Dear NumPy and SciPy communities, No annoucement was made here for EuroSciPy 2016 I believe. The call for contributions (talks, posters, sprints) is still open for a few days. EuroSciPy 2016 takes place in Erlangen, Germany, from the 23 to the 27 of August and consists of two days of tutorials (beginner and advanced tracks) and two days of conference representing many fields of science, with a focus on Python tools for science. A day of sprints follows (sprints TBA). The keynote speakers are Gaël Varoquaux and Abby Cabunoc Mayes and we can expect a rich tutorial and scientific program! Videos from previous years are available at https://www.youtube.com/playlist?list=PLYx7XA2nY5GeQCCugyvtnHMVLdhYlrRxH and https://www.youtube.com/playlist?list=PLYx7XA2nY5Gcpabmu61kKcToLz0FapmHu Visit us, register and submit an abstract on our website! https://www.euroscipy.org/2016/ SciPythonic regards, The EuroSciPy 2016 team

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usage of symiirorder1
by Neal Becker May 27, 2016

May 27, 2016

symiirorder1 (and 2) are lacking in documentation. I suggest the basic usage might be: set a time constant k: k = 0.001 r = symiirorder1(np.abs(error), (k**2), 1-k) with this choice of parameters, the filter gain will be unity

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Numpy 1.11.1rc1 release
by Charles R Harris May 26, 2016

May 26, 2016

Hi All, I am pleased to announce the release of Numpy 1.11.1rc1. The sources may be found on sourceforge <https://sourceforge.net/projects/numpy/files/NumPy/1.11.1rc1/> and wheels for OS X, Windows, and Linux will be available on pypi sometime in the next few days. The pypi release is delayed due to the decision that the wheels should go up before the sources in order that people not get a source install when what they want are wheels. The Python versions supported are 2.6-2.7 and 3.2-3.5. This release has mostly small fixes and build enhancements and should be good out of the starting gate, but prudence requires a release candidate as there are a few bits not tested in master. The following fixes have been applied: - #7506 BUG: Make sure numpy imports on python 2.6 when nose is unavailable. - #7530 BUG: Floating exception with invalid axis in np.lexsort. - #7535 BUG: Extend glibc complex trig functions blacklist to glibc < 2.18. - #7551 BUG: Allow graceful recovery for no compiler. - #7558 BUG: Constant padding expected wrong type in constant_values. - #7578 BUG: Fix OverflowError in Python 3.x. in swig interface. - #7590 BLD: Fix configparser.InterpolationSyntaxError. - #7597 BUG: Make np.ma.take work on scalars. - #7608 BUG: linalg.norm(): Don't convert object arrays to float. - #7638 BLD: Correct C compiler customization in system_info.py. - #7654 BUG: ma.median of 1d array should return a scalar. - #7656 BLD: Remove hardcoded Intel compiler flag -xSSE4.2. - #7660 BUG: Temporary fix for str(mvoid) for object field types. - #7665 BUG: Fix incorrect printing of 1D masked arrays. - #7670 BUG: Correct initial index estimate in histogram. - #7671 BUG: Boolean assignment no GIL release when transfer needs API. - #7676 BUG: Fix handling of right edge of final histogram bin. - #7680 BUG: Fix np.clip bug NaN handling for Visual Studio 2015. The following people have contributed to this release - Allan Haldane - Amit Aronovitch - Charles Harris - Eric Wieser - Evgeni Burovski - Loïc Estève - Mathieu Lamarre - Matthew Brett - Matthias Geier - Nathaniel J. Smith - Nikola Forró - Ralf Gommers - Robert Kern - Sebastian Berg - Simon Conseil - Simon Gibbons - Sorin Sbarnea - chiffa Chuck

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AUTO: Leon Woo is out of the office (returning 06/06/2016)
by Leon Woo May 26, 2016

May 26, 2016

I am out of the office until 06/06/2016. For standard requests within the scope of EMG PWM Berlin, please write to EMG PWM Berlin@DBEMEA. For non-standard requests, please cc Hien Pham-Thu. Note: This is an automated response to your message "SciPy-User Digest, Vol 153, Issue 15" sent on 26.05.2016 14:00:01. This is the only notification you will receive while this person is away.-- Informationen (einschließlich Pflichtangaben) zu einzelnen, innerhalb der EU tätigen Gesellschaften und Zweigniederlassungen des Konzerns Deutsche Bank finden Sie unter http://www.deutsche-bank.de/de/content/pflichtangaben.htm. Diese E-Mail enthält vertrauliche und/ oder rechtlich geschützte Informationen. Wenn Sie nicht der richtige Adressat sind oder diese E-Mail irrtümlich erhalten haben, informieren Sie bitte sofort den Absender und vernichten Sie diese E-Mail. Das unerlaubte Kopieren sowie die unbefugte Weitergabe dieser E-Mail ist nicht gestattet. Please refer to http://www.db.com/en/content/eu_disclosures.htm for information (including mandatory corporate particulars) on selected Deutsche Bank branches and group companies registered or incorporated in the European Union. This e-mail may contain confidential and/or privileged information. If you are not the intended recipient (or have received this e-mail in error) please notify the sender immediately and delete this e-mail. Any unauthorized copying, disclosure or distribution of the material in this e-mail is strictly forbidden.

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*** SPAM *** that is not a joke!
by Samuel Thibault May 25, 2016

May 25, 2016

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ANN: glue v0.8
by Thomas Robitaille May 25, 2016

May 25, 2016

Hi everyone, We are happy to announce the release of glue v0.8, along with glue-vispy-viewers v0.4, which adds experimental 3D viewers (powered by VisPy) to glue. ### About glue Glue is a Python library to explore relationships within and among related datasets. Its main features include: * Linked Statistical Graphics: with glue, users can create scatter plots, histograms, images, and now 3D representations of their data, as well as create their own custom viewers. Glue is focused on the brushing and linking paradigm, where selections in any graph propagate to all others. * Flexible linking across data: glue uses the logical links that exist between different data sets to overlay visualizations of different data, and to propagate selections across data sets. These links are specified by the user, and are arbitrarily flexible. * Full scripting capability: glue is written in Python, and built on top of its standard scientific libraries (i.e., Numpy, Pandas, Matplotlib, Scipy and others). Users can easily integrate their own python code for data input, cleaning, and analysis. For a 2-minute preview of glue, you can watch the following video: https://www.youtube.com/watch?v=qO3RQiRjWA4 Find out more about glue at http://www.glueviz.org! ### Changes in glue v0.8 An overview of the main changes in this release is available here: http://glueviz.org/en/stable/whatsnew/0.8.html#whatsnew-08 These include: * Playback controls for animating views of cube slices in the image viewer * An improved window for creating new components, which allows math and numpy functions to be used, and also includes on-the-fly syntax validation * The ability to more easily add data to existing glue sessions, for example those started with the qglue function. * A new preferences dialog, with new settings to control the foreground/background color in viewers as well as the default color and transparency for data. * Improved feedback and bug report windows which now allow you to provide your email address so that we can follow up any issues you may be having * The ability to use circular and polygonal regions to extract spectra from cubes (this is mainly for astronomy users) In addition, many bug fixes and small improvements have been made since the v0.7 series of releases. ### Installing/updating glue (new instructions!) You can find installation instructions at the following page: http://glueviz.org/en/stable/installation.html including information on using conda to install the latest version of glue. ### About glue-vispy-viewers The glue-vispy-viewers package is a plugin that adds 3D viewers to glue. You can find out more about this plugin here: http://www.glueviz.org/en/stable/whatsnew/experimental_3d.html#experimental… This includes both 3D scatter plots and volume renderings, and support selections using a variety of region types. Please note that these viewers are still experimental. ### Reporting issues/getting help Please let us know if you run into any issues using the issue trackers on GitHub: https://github.com/glue-viz/glue/issues https://github.com/glue-viz/glue-vispy-viewers/issues You can also join the glue-viz mailing list to have any discussions related to glue and/or get help: https://groups.google.com/forum/#!forum/glue-viz ### Getting involved Interested in contributing new features or helping maintain glue or the 3D viewers? Please let me know (by replying off-list to this email), and I can help you get started! Thanks to everyone who contributed to these releases! (including Penny Qian, Robin Wilson, Pey-Lian Lim, and Brett Morris) Thanks, Tom

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SciPy 2016 Conference (Scientific Computing with Python): Tutorials and Talks Announced
by Courtenay Godshall (Enthought) May 19, 2016

May 19, 2016

**ANN: SciPy 2016 Conference (Scientific Computing with Python): Tutorials and Talks Announced** We're excited to announce this year's accepted Talks <http://scipy2016.scipy.org/ehome/146062/332963/> & Posters and Tutorial Schedule <http://scipy2016.scipy.org/ehome/146062/332960/> ! This year's 3 major talk tracks include Python in Data Science, High Performance Computing, and general Scientific Computing. Our six mini-symposia include: Earth and Space Science, Engineering, Medicine and Biology, Case Studies in Industry, Education, and Reproducibility. For tutorials, you can choose from <http://scipy2016.scipy.org/ehome/146062/332960/> 18 different SciPy tutorials, including a <https://katyhuff.github.io/2016-07-11-scipy> 1 day Software Carpentry Scientific Python course that assumes some programming experience but no Python knowledge, or a 2-day Software Carpentry Instructor Training. We hope you'll join us - early bird registration ENDS May 22, 2016. Register at: http://scipy2016.scipy.org/ehome/146062/332936/ About SciPy 2016 SciPy 2016 <http://www.scipy2016.scipy.org> , the 15th annual Scientific Computing with Python conference, will be held July 11-17, 2016 in Austin, Texas. SciPy is a community dedicated to the advancement of scientific computing through open source Python software for mathematics, science, and engineering. The annual SciPy Conference brings together over 650 participants from industry, academia, and government to showcase their latest projects, learn from skilled users and developers, and collaborate on code development. The full program will consist of <http://scipy2016.scipy.org/ehome/146062/332960/> 2 days of tutorials (July 11-12), <http://scipy2016.scipy.org/ehome/146062/332963/> 3 days of talks (July 13-15), and 2days of <http://scipy2016.scipy.org/ehome/146062/332969/?&&> developer sprints (July 16-17). More info is available on the conference website at <http://www.scipy2016.scipy.org> http://scipy2016.scipy.org (where you can sign up for the mailing list); or follow <https://twitter.com/scipyconf> @scipyconf on Twitter.

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