Hello all,
So, I am getting to the point where I need to implement a color cycling
mechanism throughout pyplot. So, before I get too deep in implementing it,
I have some thoughts that I need feedback on.
1) Not all plotting functions use color cycling right now. Currently, only
plot() and any function that calls plot in its process (such as
errorbar()). Glaring omissions are bar() and scatter(), and pie() could
also benefit from having a uniform cycling mechanism. So, the issue going
forward is, do we want to enable common cycling for all the pyplot/axes
plotting functions which would require updating the test images and break
backwards compatibility (in a sense), or do we want to have a per-function
default rcparams that would contain one-element cycles that would
effectively maintain current drawing results?
2) I also have the need to implement line-style cycling for b&w
publications. Of course if I implement that, then why not hatch-cycling?
marker-cycling? I have seen use-cases for all of these, and I am
considering how to have a generalized framework for this. So my question
is, what attributes would we like to see cycle-able? Here is a short list
and some usecases I have come up with. Please extend this with ideas of
your own.
color - plot(), errorbar(), scatter(), bar(), hist(), pie(), stem()
linestyle - plot(), errorbar(), stem()
hatch - bar(), hist(), pie()
marker - plot(), errorbar(), scatter(), stem()
linewidth? facecolor/edgecolor? joinstyle?
3) rcparam names. I was thinking about how to name these cycles in the
matplotlibrc file. Possibly:
cycle.colors
cycle.linestyles
cycle.hatches
cycle.markers
And these would represent the global default, meanwhile, function-specific
cycles could be given by:
cycle.colors.pie
cycle.colors.bar
cycle.linestyles.plot
cycle.linestyles.errorbar
I was thinking that in code, one would access the full name attribute for
the function, and I would extend the __get__ function to intelligently fall
back to the global default if the full-name attribute is not specified.
However, would there be confusion in a situation such as a person who
wanted to use barh() but only had specified cycle.colors.bar?
4) Ultimately, my goal is to be able to create some typical profiles that
have useful cycle specs, and possibly make some available as convenience
functions, such as a b&w mode. Such a mode would set the default colormap
to a grayscale-friendly colorscale, and use line style, hatch and marker
cycles instead of a full color cycle.
Thoughts? Comments?
Cheers!
Ben Root
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