Mailman 3 February 2019 - Matplotlib-devel

matplotlib qt trading terminal; finance sample
by cerberus cerberus April 19, 2019

April 19, 2019

Hello Lists, I will park my matplotlib source code for a trading terminal written in python2/matplotlib/pyqt4 here in case one needs reasonable good reference code about how to plot financial candlestick charts and indicators with matplotlib and qt. A sample of a combined orderbook for several crypto currency exchanges is included, see attached screenshot. Google Notice: Wavetrend Robot. With Kind Regards, Aktiophi

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plot confidence ellipse
by Carsten Schelp Feb. 23, 2019

Feb. 23, 2019

Hello, Quite some time ago I had to plot confidence ellipses for two-dimensional datasets. There was no out-of-the-box solution in the libraries I used, then. Also, all the solutions that I found when searching online seemed cumbersome or did not even work well. So I brewed my own. You can see the result of my effort in this blogpost here (python, using numpy and matplotlib): https://carstenschelp.github.io/2018/09/14/Plot_Confidence_Ellipse_001.html - along with an explanation how and why it works. If you guys think that this functionality might be useful within matplotlib, I would happily prepare this approach - pythonic-checks, tests and all - and send a patch or pull request. I consider the confidence ellipse a kind of "cousin" to the "scatter(...)" function. Maybe it is appropriate to place it next to "scatter" - but that is still to be discussed, I think. Do you think that a function to plot the confidence ellipse of a two-dimensional dataset should be part of matplotlib? I am curious to hear your opinion. If the answer is "yes" I will make time to get the existing code "matplotlib-ready". (Sorry, I am posting this for the second time. First time, I sent an html message which messed up the readability in the list) Kind regards, Carsten

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master branch protection
by Thomas Caswell Feb. 23, 2019

Feb. 23, 2019

Folks, I turned up the protection on the master branch a bit to require 1 review and no change requests before the UI will let you merge. Lets see how it goes, please provide feedback on how this is. Tom -- Thomas Caswell tcaswell(a)gmail.com

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created v3.1.x branch
by Thomas Caswell Feb. 23, 2019

Feb. 23, 2019

Folks, Created the 3.1.x and set up the bot to backport to PRs in the v3.1.0 milestone. We have ~170 open issues / pull requests labeled for 3.1.0. If you have time please help finish up the review and triage any release critical bugs / move to 3.2. Tom -- Thomas Caswell tcaswell(a)gmail.com

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2019 John Hunter Excellence in Plotting Contest Organizers
by Thomas Caswell Feb. 18, 2019

Feb. 18, 2019

Folks, We need a volunteer or two to help run the JHEPC competition this year (Nelle Varoquaux and Michael Droettboom ran it last year) The role involves : - making sure the announcement goes out - collecting a panel of judges (starting from last years) - organizing the collection of the submissions - sending the judging packet out to the judges and collecting the results - collating the results from the judges The timeline is: - get announcement out (late March / Early April) - collect submissions and distribute to judges (late May / early June) - final tally of results (July 10-12 to be announced at SciPy) The time commitment is 10-20 hours total between now and July. Tom -- Thomas Caswell tcaswell(a)gmail.com

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Event handling callbacks call order
by Daniele Nicolodi Feb. 14, 2019

Feb. 14, 2019

Hello, I have an application where I let the user place Patches on the canvas via mouse events. To do so I have a "button_press_event" callback registered to the canvas. I now would like to allow to drag the drawn patches to change their position. To do so I register other callbacks on the canvas like in the examples at https://matplotlib.org/users/event_handling.html. The problem is that the callbacks are called in the order they are registered and I haven't found a way to inhibit execution of callbacks down the stack from previously called callback. This results in the fact that patches are drawn on top of the old ones when the user tries to drag those around. I can see (quite convoluted) ways to avoid this in my code, but I would think that correctly handling this is a common occurrence and that there could be a solution built into matplotlib. However, I haven't found it. I am missing something? Thank you! Cheers, Dan

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plot confidence ellipse
by Carsten Schelp Feb. 11, 2019

Feb. 11, 2019

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Release and branching plans for {2.2.4, 3.0.3, 3.1.0}
by Thomas Caswell Feb. 5, 2019

Feb. 5, 2019

Folks, First an apology, this should have gone out last week. Paul Ivanov has agreed to co-manage this release cycle with me. The rough plan is to do the bug fix releases at the end of this week (aiming for Feb 11 to have 2.2.4 and 3.0.3 released and available on pypi). I don't think we need to do RCs for these. At the same time as we tag 3.0.3 we will delete the 3.0.x and the 3.0.2-doc branch, create the 3.0.2-doc branch, and fork a 3.1.x branch off of master. This will be feature-freeze for 3.1 and we will then use the back-port bot to move any remaining PR- for 3.1 to the 3.1.x branch. I propose we aim for an RC1 sometime between Feb 18 and Feb 25 and a final release March 4. Similarly when we tag 2.2.4 we will delete the 2.2.3-doc branch and create 2.2.4-doc (again, conserving the number of active branches we have). If you have the power to add labels / milestones please mark things that you think must go in for 3.1 as release critical and re-milestone things you don't think will be done is the next few weeks as 3.2 (or needs-sorting). So in summary: Feb 11: release 2.2.4, 3.0.3 Feb 18: 3.1.0rc1 Mar 4: 3.1.0 Branches to be removed from matplotlib/matplotlib - v3.0.x - v3.0.2-doc - v2.2.3-doc Branches to be added: - v3.1.x - v3.0.3-doc (we need this at least temporarily to put the DOI on after we tag) - v3.1.0-doc - v2.2.4-doc Milestones to be closed: - v2.2.4 - v3.1.0 - v3.0.3 - v3.0.2-doc Milestones to be added: - v2.2.5 - v3.1.1 - v3.1-doc Milestones to have their backport-targets changed: - v2.2-doc Tom -- Thomas Caswell tcaswell(a)gmail.com

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SciPy 2019 Conference - 10 days left for submissions, registration now open
by Paul Ivanov Feb. 5, 2019

Feb. 5, 2019

SciPy 2019, the 18th annual Scientific Computing with Python conference, will be held July 8-14, 2019 in Austin, Texas. The annual SciPy Conference brings together over 800 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 abstracts for SciPy 2019 for talks, posters and tutorials is now open. The original deadline for submissions has been extended and the new deadline is February 15, 2019. Conference Website: https://www.scipy2019.scipy.org/ Submission Website: https://easychair.org/conferences/?conf=scipy2019 *Talks and Posters (July 10-12, 2019)* In addition to the general track, this year will have specialized tracks focused on: - Data Driven Discoveries (including Machine Learning and Data Science) - Open Source Communities (Sustainability) *Mini Symposia* - Science Communication through Visualization - Neuroscience and Cognitive Science - Image Processing - Earth, Ocean, Geo and Atmospheric Science There will also be a SciPy Tools Plenary Session each day with 2 to 5 minute updates on tools and libraries. *Tutorials (July 8-9, 2019)* Tutorials should be focused on covering a well-defined topic in a hands-on manner. We are looking for useful 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. -- _ / \ A* \^ - ,./ _.`\\ / \ / ,--.S \/ \ / `"~,_ \ \ __o ? _ \<,_ /:\ --(_)/-(_)----.../ | \ --------------.......J Paul Ivanov http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7

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feature request : new rc parameters in matplotlibrc
by joe manix Feb. 4, 2019

Feb. 4, 2019

Hi there, I'm new to matplotlib, come from the ROOT world (https://root.cern.ch) and miss the following rc parameters : - legend.fontfamily - legend.fontstyle - legend.fontweight only legend.fontsize is implemented - axes.xlabelpad (or axes.xlabel.pad) - axes.ylabelpad (or axes.ylabel.pad) only a generic axes.labelpad exists Could you please add these new rc parameters to matplotlibrc? Cheers, Z

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