Mailman 3 April 2019 - Matplotlib-devel

What is draw_path's transform's destination?
by Rob McDonald Sept. 24, 2019

Sept. 24, 2019

I'm implementing a custom path effect by inheriting from AbstractPathEffect and implementing draw_path as instructed here <https://matplotlib.org/api/patheffects_api.html#matplotlib.patheffects.Abst…>. That link references RenderBase.draw_path <https://matplotlib.org/api/backend_bases_api.html#matplotlib.backend_bases.…> to define the required interface. Unfortunately, I can't find anywhere in the associated documentation that tells me what the transform argument really entails. I've also read the transforms tutorial <https://matplotlib.org/tutorials/advanced/transforms_tutorial.html>, and while that explains the pipeline and all the intermediate transformations, it doesn't really settle what I have available to me in draw_path. It is clear that I can use it to transform coordinates from data to something -- but I don't know what to. For the big picture -- I am implementing a path effect to allow drawing hatched lines similar to this <https://www.mathworks.com/matlabcentral/fileexchange/29121-hatched-lines-an…>, which I did years ago in Matlab. Years before that, I've also done this in Java Graphics2D by implementing a custom stroke. (The Java approach is more applicable to the path effect approach, but I can't point to that code online anywhere.) Anyway, I have things mostly working -- and I am using the transform to go from data coordinates to something that looks orthogonal and reasonable on-screen. So, for minimum functionality, it works. However, I want to give the user the ability to control the length and spacing of the hatches -- which is in a coordinate system after the transformation is applied. So, in order to document this thing, I need to know what it is. Or, if there is a way to get intermediate stages of the transformation pipeline, that would work too. As for the user interface -- it seems to make the most sense to specify the hatch length and spacing in terms of something similar to a line width (typically points) or a marker size. I'm new to Python and matplotlib -- what is the Pythonic unit a user would expect to specify this in (and how do I achieve that with what is available in draw_path)? Thanks, Rob

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High priority for 3.2: figure cleanup
by Eric Firing April 20, 2019

April 20, 2019

In today's weekly meeting, with Hannah, Thomas, and myself, we discussed https://github.com/matplotlib/matplotlib/issues/8519, which points to the long-standing problem that matplotlib relies on garbage collection to release memory after a figure is closed. With some work-flows the automatic collection doesn't happen often enough and the user must explicitly trigger it. It would be better if pyplot cleaned up after itself, breaking reference cycles when a figure is closed. I think it is time to make this change, so I marked the issue "Release-critical". I am hoping we can get this done as a high-priority task, *early* in the 3.2 cycle. The central point is that closing a figure should clear it, and clearing it should recursively walk through the children, breaking connections and reference cycles all the way down. One possibility would be to modify or replace the figure object such that any attempt to operate on the figure after closing would fail by raising an informative exception. Question: should closing the gui window also close the figure? No, because that would prevent the user from calling savefig on it. This would interfere with a reasonable use-case, in which plt.show is used in blocking mode, the window is closed, and the figure is saved via savefig. Problem: if closing the gui window doesn't close the figure, how can it ever be closed? This leads to the suggestion that the pyplot state manager keep a list of "latent figures" which are no longer displayed in a gui window but have not been closed. They could then be explicitly closed by "plt.close('all')". This also opens the possibility for an API allowing one to re-display a figure after closing its gui window. For example, one might do a calculation, show it in a figure in a blocking window with "plt.show", close the window, do additional calculations, add them to the same figure, and bring the figure back in a new gui window. This might be done in a loop, incrementing the contents of the figure. See also: https://github.com/matplotlib/matplotlib/issues/6793 https://github.com/matplotlib/matplotlib/issues/6982 Eric

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[Ann] Matplotlib 3.1.0rc1 tagged
by Thomas Caswell April 19, 2019

April 19, 2019

Folks, I have (finally) tagged 3.1.0rc1 ! See https://matplotlib.org/devdocs/api/api_changes.html and https://matplotlib.org/devdocs/users/whats_new.html for drafts of the api changes and whats new. A big thanks to Hannah Aizenman and David Stansby for pulling the documentation together! As this is a pre-release I am going to put the tarball up on pypi without waiting for the wheels. The wheels and the conda-forge packages will go up as they are ready (and will announce more widely at that point). Let's aim from 3.1.0 final in the first week of May. Tom -- Thomas Caswell tcaswell(a)gmail.com

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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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NetworkX 2.3rc3 released (Python 3 only)
by Jarrod Millman April 5, 2019

April 5, 2019

I am happy to announce the third **release candidate** for NetworkX 2.3! NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. This release supports Python 3.5-3.7 (i.e., this is our first **Python 3 only** release). Please try out the pre-release and let us know about any problems you find. If no major issues arise, we will release 2.3 final next week. Please see the draft of the 2.3 release announcement: https://networkx.github.io/documentation/latest/release/release_dev.html Since this is a pre-release, pip won't automatically install it. So $ pip install networkx still installs networkx-2.2. But $ pip install --pre networkx will install networkx-2.3rc3. If you already have networkx installed then you need to do $ pip install --pre --upgrade networkx For more information, please visit our `website <http://networkx.github.io/>`_ and our `gallery of examples <https://networkx.github.io/documentation/latest/auto_examples/index.html>`_. Please send comments and questions to the `networkx-discuss mailing list <http://groups.google.com/group/networkx-discuss>`_. Best regards, Jarrod

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