matplotlib-users Mailing List for matplotlib

Hi! Quick question about pylab.annotate:
Is it supposed to take keyword args such as fontsize?
Thanks,
William

> Alan said:
>> Ideally I'd be able to do something like 
>> lgd.set_items(lgd.get_items()[slice])
On 5/5/2009 1:35 PM Jae-Joon Lee apparently wrote:
> It is quite hard to modify the order of items once the legend is created. 
> Thus, I recommend you to order your items before creating the legend. 
> For example, 
> ax = subplot(111)
> ... plot some lines
> lines = ax.get_lines()
> labels = [l.get_label() for l in lines]
> legend(lines[::-1], labels[::-1]
> I just committed some changes to the svn which makes this kind of 
> thing more handy. The legend guide is also updated with this. 
> http://dl.getdropbox.com/u/178748/mpl/legend_guid/html/legend.html#adjusting-the-order-of-legend-items 
Cool. Also, the way you demo above beats the
approach I took, so thanks for that too.
Alan

> Alan G Isaac wrote:
>> I'm not understanding facecolor and edgecolor. 
>> In the code below (on Windows, with TkAgg)
>> I get the facecolor displayed [onscreen] but not the 
>> edgecolor, and the saved figure shows *neither*. Why? 
>> (version is 0.98.1)
On 5/5/2009 2:48 PM Eric Firing apparently wrote:
> It looks to me like a bug plus a feature. The bug is that in the screen 
> display, the edgecolor can get lost, presumably clipped. On my system 
> (linux, gtkagg) the edgecolor is visible only along the top. 
> The feature is that by design, the figure edgecolor and facecolor have 
> to be specified separately for saving versus screen display. This 
> prevents the screen default grey background from being printed. Maybe 
> there needs to be a savefig option, possibly set via rcParams, to defeat 
> this behavior and simply use the screen settings. At present, you can 
> set the savefig colors in rcParams or via savefig kwargs. Is this adequate? 
OK, we agree that edge color can be lost in onscreen
display, apparently a bug in figure clipping.
Now for the "feature".
I did notice that savefig takes keyword args allowing
us to set facecolor and edgecolor. I would call this
"adequate" in some sense, but it is confusing. It is too
implicit; I was not able to easily determine why may
changes to the **figure** did not affect the file. (Note
that I may not even view an onscreen display for some figures.)
So I do not think it is a problem that the screen display
and savefig have different defaults, presumably invoked but
a default of None. But if the user sets the figure values,
this should override the defaults (in both cases).
Does that seem right?
Thank you,
Alan

Alan G Isaac wrote:
> I'm not understanding facecolor and edgecolor.
> In the code below (on Windows, with TkAgg)
> I get the facecolor displayed but not the
> edgecolor, and the saved figure shows *neither*.
> Why? (version is 0.98.1)
It looks to me like a bug plus a feature. The bug is that in the screen 
display, the edgecolor can get lost, presumably clipped. On my system 
(linux, gtkagg) the edgecolor is visible only along the top.
The feature is that by design, the figure edgecolor and facecolor have 
to be specified separately for saving versus screen display. This 
prevents the screen default grey background from being printed. Maybe 
there needs to be a savefig option, possibly set via rcParams, to defeat 
this behavior and simply use the screen settings. At present, you can 
set the savefig colors in rcParams or via savefig kwargs. Is this adequate?
Eric
> 
> Thanks,
> Alan Isaac
> 
> import matplotlib.pyplot as plt
> import numpy as np
> 
> fig1 = plt.figure(1)
> fig1.set_frameon(True)
> fig1.set_facecolor('r')
> fig1.set_edgecolor('b')
> 
> ax1 = fig1.gca()
> ax1.plot([1,2,3])
> 
> fig1.savefig('c:/temp/temp.eps')
> 
> plt.show()
> 
> 
> ------------------------------------------------------------------------------
> The NEW KODAK i700 Series Scanners deliver under ANY circumstances! Your
> production scanning environment may not be a perfect world - but thanks to
> Kodak, there's a perfect scanner to get the job done! With the NEW KODAK i700
> Series Scanner you'll get full speed at 300 dpi even with all image 
> processing features enabled. http://p.sf.net/sfu/kodak-com
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

On Tue, May 5, 2009 at 1:04 PM, Ryan May <rm...@gm...> wrote:
> On Tue, May 5, 2009 at 11:47 AM, Jose Gomez-Dans <jgo...@gm...>
> wrote:
>>
>> Hi,
>> I would like to plot a density slice scatter plot (when you have lots of
>> points superimposed, it's very useful). An example from IDL/envi is here:
>> <http://www2.geog.ucl.ac.uk/%7Eplewis/geog2021/practical1/scatter3.gif>
>>
>> My rustic approach to solving this problem has been to bin all my data
>> points into a 2D array (each point that falls in a given cell adds one to
>> that cell), and then use the c argument in scatterplot to map the color to
>> the number of samples in the corresponding bin. Is there a better way of
>> achieving this, as I need a fair bit of tweaking to get the color scales
>> right?
>
> You might try looking at pyplot.hexbin:
>
> http://matplotlib.sourceforge.net/examples/pylab_examples/hexbin_demo.html
>
> Ryan
I've also had some luck with scipy.histogramdd and pylab.imshow (you
have to work with the extent and aspect parameters to get the plot you
want). I don't have a standalone demo of this, but if you try it and
have trouble let me know and I'll try to make one.

On Tue, May 5, 2009 at 11:47 AM, Jose Gomez-Dans <jgo...@gm...>wrote:
> Hi,
> I would like to plot a density slice scatter plot (when you have lots of
> points superimposed, it's very useful). An example from IDL/envi is here: <
> http://www2.geog.ucl.ac.uk/%7Eplewis/geog2021/practical1/scatter3.gif>
>
> My rustic approach to solving this problem has been to bin all my data
> points into a 2D array (each point that falls in a given cell adds one to
> that cell), and then use the c argument in scatterplot to map the color to
> the number of samples in the corresponding bin. Is there a better way of
> achieving this, as I need a fair bit of tweaking to get the color scales
> right?
You might try looking at pyplot.hexbin:
http://matplotlib.sourceforge.net/examples/pylab_examples/hexbin_demo.html
Ryan
-- 
Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma

Hi,
I would like to plot a density slice scatter plot (when you have lots of
points superimposed, it's very useful). An example from IDL/envi is here: <
http://www2.geog.ucl.ac.uk/%7Eplewis/geog2021/practical1/scatter3.gif>
My rustic approach to solving this problem has been to bin all my data
points into a 2D array (each point that falls in a given cell adds one to
that cell), and then use the c argument in scatterplot to map the color to
the number of samples in the corresponding bin. Is there a better way of
achieving this, as I need a fair bit of tweaking to get the color scales
right?
Thanks!
J

> I believe that it is just moved to another directory 
> (lib/matplotlib/sphinxext).
Yes, thanks.
Its here:
http://matplotlib.svn.sourceforge.net/viewvc/matplotlib/
trunk/matplotlib/lib/matplotlib/sphinxext/

On Mon, May 4, 2009 at 10:47 PM, Alan G Isaac <ala...@gm...> wrote:
> The docs
> http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.legend
> suggest that
> loc=(0.5,0.5)
> is equivalent to
> loc='center'
> but it is not. How can I center the legend
> relative to the x-axis?
>
As you may have noticed, loc with a tuple of two floats is interpreted
as a coordinate for the lower-left corner.
> It seems to me that I need to be able to set
> not only the coordinates but also what part
> of the legend box is placed at those coordinates.
> (Along the lines of LaTeX box placement.)
> Can I do that?
>
You can, but with mpl from svn trunk. For example,
 legend(bbox_to_anchor=(0.5, 0.5), loc="center")
For some more details, take a look at the link below, which is my
work-in-progress legend guide.
http://dl.getdropbox.com/u/178748/mpl/legend_guid/html/legend.html#legend-location
Regards,
-JJ
> Thanks,
> Alan Isaac
>
> ------------------------------------------------------------------------------
> The NEW KODAK i700 Series Scanners deliver under ANY circumstances! Your
> production scanning environment may not be a perfect world - but thanks to
> Kodak, there's a perfect scanner to get the job done! With the NEW KODAK i700
> Series Scanner you'll get full speed at 300 dpi even with all image
> processing features enabled. http://p.sf.net/sfu/kodak-com
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

The docs
http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.legend
suggest that
loc=(0.5,0.5)
is equivalent to
loc='center'
but it is not. How can I center the legend
relative to the x-axis?
It seems to me that I need to be able to set
not only the coordinates but also what part
of the legend box is placed at those coordinates.
(Along the lines of LaTeX box placement.)
Can I do that?
Thanks,
Alan Isaac