[Matplotlib-devel] (no subject)

Tue Jun 7 03:22:12 EDT 2016

I actually was able to achieve the desired behavior by creating my own
projection based on my modified Axes class and adding that projection to
the projection registry.

On Mon, Jun 6, 2016 at 11:01 AM, Daniel McNeela <daniel.mcneela at gmail.com>
wrote:

> Thank you OceanWolf and Federico. I was previously unaware of the gid
> property of Artists and the new ToolManager classes, and it looks like what
> I have been doing is pretty similar to what is contained therein. You can
> take a look at my progress here:
>
> https://github.com/mcneela/Retina/tree/master/retina
>
> (The code is a bit messy as I haven't gotten around to cleaning it up yet.)
>
> Basically I just have a layer dictionary associated with each axes in
> which I can update, set, and delete properties. If you interactively run
> the two examples included in that folder, you can type in commands at the
> Python interpreter and watch the plots change in response. For example,
> with the basic_layer_demo, you could run the following
>
> >>> subplots.hide("cubic")    # Hides the 'cubic' layer while keeping the
> 'quadratic' layer displayed
>
> >>> subplots.show("cubic")    # Redisplays the "cubic" layer
>
> >>> subplots.set_style("cubic", 'ro')    # Changes the style of the cubic
> layer
> >>> subplots.build_layers()         # Rebuilds the layers so that the new
> styling takes effect
>
> Is this something that you think would have utility if directly
> incorporated into Matplotlib's axes class, or is better to just have it
> built out on top as is done with the ToolManager classes?
>
> On Mon, Jun 6, 2016 at 5:34 AM, OceanWolf <juichenieder-nabb at yahoo.co.uk>
> wrote:
>
>> Hi Daniel,
>> I like your ideas.  As Fedrico said, the group part has already exists,
>> see http://matplotlib.org/examples/user_interfaces/toolmanager.html for
>> an example of this, the toolmanager part we still consider as experimental
>> until at least 2.1 when we hope to have gotten it working with all backends
>> together with http://matplotlib.org/devel/MEP/MEP27.html, refactoring
>> the FigureManager so as to decouple pyplot from the backends, a project
>> that I have been working on.
>>
>> The other parts, http://matplotlib.org/devel/MEP/MEP26.html which looks
>> at creating Cascading Artist Style Sheets, based upon the CSS language spec
>> for websites.  I don't think anyone has started working on this, and may
>> need some more definition and working out; then I started creating another
>> MEP to figure out how to refactor the Axes and related classes into a more
>> coherent and readably understandable structure, you can see the limited
>> progress i have made at defining the document here...
>> https://github.com/matplotlib/matplotlib/pull/5029 I have a few more
>> ideas I want to put into this, just needing to find time to get back to it,
>> probably once we have the backend refactor finished.
>>
>> Of course, matplotlib works as a fully opensource project, fully
>> collaborative, so any source code changes you would like to see, make them
>> in a fork, and PR them back to the matplotlib (or as I got started, forking
>> Federico's toolmanager fork, and PRing back to him and his PR before
>> merging into master, as part of MEP22).  And of course, feel free to get
>> involved in any of this stuff if you like it, the more the merrier :).
>>
>> Best,
>> OceanWolf
>>
>> ------------------------------
>> *From:* Federico Ariza <ariza.federico at gmail.com>
>> *To:* Daniel McNeela <daniel.mcneela at gmail.com>
>> *Cc:* matplotlib development list <matplotlib-devel at python.org>
>> *Sent:* Monday, 6 June 2016, 12:19
>> *Subject:* Re: [Matplotlib-devel] (no subject)
>>
>> I have done similar things (hiding groups of artists) using the tool
>> manager and custom build tools.
>> In general I just use the gid property of each artist to keep track of
>> different groups and on trigger I hide a specific group.
>> Also I use it to pop-up an artist-styler to change colors, linestyle
>> etc...
>> It is indirect but allows to perform operations without touching base
>> classes.
>> I know this is not what you asked but hope it helps
>> Federico
>> On Jun 5, 2016 10:38 PM, "Daniel McNeela" <daniel.mcneela at gmail.com>
>> wrote:
>>
>> Basically I'm adding a "layer" construct to the Axes model that allows
>> users to define groups of Matplotlib artists that can be manipulated,
>> hidden, displayed, styled, etc. in tandem without affecting those artists
>> which are on other layers. It's sort of analogous to the way in which
>> layers work in Photoshop.
>>
>> The issue with simply subclassing the Matplotlib Axes is that I want my
>> subclass to fully integrate with pyplot and other modules. For example, if
>> a user has my module imported and runs
>>
>> >>> fig = plt.figure()
>> >>> subplot = plt.subplot(111)
>>
>> I'd like for subplot to be an instance of my subclassed Axes rather than
>> of the default one provided by Matplotlib.
>>
>> On Sun, Jun 5, 2016 at 5:31 PM, Thomas Caswell <tcaswell at gmail.com>
>> wrote:
>>
>> Simply sub-classing any of those classes in your code would reasonable.
>>
>> I am curious about what sort of extensions you are adding?  I think in
>> many cases writing functions that take in `Axes` (or `Figure` if that is
>> the right scope) objects and operate on them.
>>
>> An example of a project that is sub-classing `Axes` is
>> https://github.com/scls19fr/windrose .
>>
>> Tom
>>
>> On Sun, Jun 5, 2016 at 5:16 PM Daniel McNeela <daniel.mcneela at gmail.com>
>> wrote:
>>
>> Hi All,
>>
>> I'm currently developing a Python package built on top of Matplotlib, and
>> I'd like to add custom functionality to the Axes class while still
>> retaining all of the default Matplotlib syntax and commands. To do this,
>> I'd like to subclass matplotlib.axes.Axes (or possibly
>> matplotlib.axes._base._AxesBase) and add additional class attributes and
>> methods. Ideally, I'd like to do this without forking Matplotlib and
>> directly editing the source so as to maintain compatibility with future
>> Matplotlib releases. I see that in pyplot.py, calls to figure() accept an
>> optional FigureClass argument which I could use to pass a custom subclass
>> of Figure. I was thinking I could subclass Figure such that the subclass
>> overrides methods such as Figure.add_subplot() by calling the superclass's
>> method and passing my custom Axes subclass in as an optional argument. But
>> I'm not sure which methods I'd have to override, or how deep the rabbit
>> hole goes, as Axes objects seem to be generated in a number of places
>> throughout the Matplotlib source.
>>
>> If anyone who is familiar with the code base might be able to suggest a
>> simple way in which I could accomplish this desired behavior, I would
>> greatly appreciate it! Right now, I'm adding the desired functionality via
>> a function that accepts Matplotlib Axes instances and binds custom
>> attributes/methods to these instances via Python's type.MethodType, but
>> this seems like a rather clunky and un-Pythonic approach to building what
>> will likely be an extensive application.
>>
>> Thank you in advance for your help!
>>
>> Best,
>>
>> Daniel McNeela
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>
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