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From: John H. <jdh...@ac...> - 2003-10-19 19:25:17
|
I just uploaded a new release to http://matplotlib.sourceforge.net. * Several bug fixes in the GTK backend which affected interactive mode and figure resizing. See examples/interactive2.py in the new src release. * The legend command from CVS has been added. See examples/legend_demo.py * Some bugs regarding alternate ways of specifying colors have been ironed out (you can now use hex strings or 0-1 RGB tuples anywhere a color format string is supported ). See examples/color_demo.py Let me know of any problems you find. John |
|
From: John H. <jdh...@ac...> - 2003-10-19 18:52:15
|
>>>>> "Barry" == Barry Drake <bl...@ad...> writes:
Barry> Update on the interactive mode: I found the interactive2.py
Barry> on the website and tried that rather than the
Barry> interactive.py that was included with the .29 dist. That
Barry> worked. However,
Barry> 1. it can't find ShowOn (NameError) so I just typed show()
Barry> at the command prompt
I made several bug fixes that have restored interactive2.py
functionality. When I added support for other outputs (PS and GD) a
few bugs crept into the GTK output that I was unaware of, and tracking
down your problems made them clear to me.
I just uploaded a new file release to the sourceforge site that
reflects these changes to the GTK backend and interactive2.py, as well
as the new legend command. The version is 0.29.1, so you should grab
a copy and give it a try. Note you'll need the src distribution (zip
or tar.gz) to get the new examples/interactive2.py file.
Barry> 2. and it doesn't exit using ctrl-z <enter> ; I used the
Barry> close box.
This one is still on the TODO list.
Hope this helps,
John Hunter
|
|
From: John H. <jdh...@ac...> - 2003-10-19 15:01:09
|
>>>>> "Andrew" == Andrew Straw <as...@in...> writes:
Andrew> Sorry to ask for the Nth time, but as essentially all of
Andrew> my plots require at least one log10 axis and as matplotlib
Andrew> looks better and better, I'm wondering about the status of
Andrew> log axes.
No need to apologize, pestering is a good thing since it motivates me
to do the things I already want to do when I know people want them.
Andrew> This has even brought me to the point of delving into the
Andrew> innards of matplotlib just to see how easy (or hard) it
Andrew> would be. So far, it looks possibly like overriding the
Andrew> various Artist.transform_*() methods and some additions to
Andrew> axes.py. Is this the case? Would I be duplicating effort
Andrew> if I jumped in at this point? I can't tell at this point
Andrew> how much work it looks to be -- any estimation?
This is certainly the core change. Other considerations are to get
tick labels to work properly (using exponential or some suitable
notation) and to get the tick locs right (choose them on the decades,
probably using some preset decade choices for the most common use
cases). And the changes need to be consistent with handle graphics,
so that the user can say, for example
set(gca(), 'xscale', 'log') or
set(gca(), 'xscale', 'linear)
and have the desired effect. The latter will happen automagically if
the Axes class defines a set_xscale and set_yscale method expecting
the string arg, which the then forwards the calls to a set_scale
method of the Axes._xaxis or Axes._yaxis instances.
I have been busier than anticipated over the last week so haven't been
able to address this issue as I had hoped, but have been tinkering
with it and thinking about it. If you look at CVS axes class, you'll
see the results of my tickering in the _scale, _scalemap, _scalefunc
attributes of the Axis class. I'm not at all convinced this is the
right design, though. One thing to consider is to factor the tick
loc-ing and labeling into a separate class to clean up the Axis
design.
As far as your helping, that would be great. As far as how much time
it would take, I think it would take me anywhere from half a day to
two days to get it just right, but I'm inclined to the lower
estimates. Let me know how you want to proceed: I can envision
anything from you making the required changes and checking them into
CVS, to us collaborating on the design and implementation, to me just
getting off my ass and doing it. I would certainly welcome some input
from you, and know from the quality of your work on vision egg that it
would improve matplotlib. Which given your impending move to the
Dickinson lab, might be a good thing for you too :-)
Andrew> However, I think "ticks = asarray(ticks)" would be
Andrew> cleaner, and probably little faster, too.
Right, I wrote some of the code a long time ago and would do this
differently now. My original thought was that in many of the use
cases the sequences would already be arrays and the try/except thing
would avoid a performance hit of creating a new array, but have since
learned that this is the purpose of asarray. If you decide to do the
log scaling thing, feel free to make these kinds of changes as you
go. The examples dir currently serves as my poor-man's unit testing
framework so you can validate your changes against them.
Note that I made several minor changes to the code last night so be
sure to grab the latest CVS if you want to do any development.
John
|
|
From: Andrew S. <as...@in...> - 2003-10-19 05:48:13
|
Sorry to ask for the Nth time, but as essentially all of my plots
require at least one log10 axis and as matplotlib looks better and
better, I'm wondering about the status of log axes.
This has even brought me to the point of delving into the innards of
matplotlib just to see how easy (or hard) it would be. So far, it looks
possibly like overriding the various Artist.transform_*() methods and
some additions to axes.py. Is this the case? Would I be duplicating
effort if I jumped in at this point? I can't tell at this point how
much work it looks to be -- any estimation?
As a mostly-trivial side-note, while looking through axes.py, I saw a
few lines like:
try: ticks.shape
except AttributeError: ticks = array(ticks)
However, I think "ticks = asarray(ticks)" would be cleaner, and probably
little faster, too.
Cheers!
Andrew
|