matplotlib-users Mailing List for matplotlib

On Wed, Jun 17, 2009 at 5:31 PM, Alexandar Hansen<vio...@gm...> wrote:
> Hello,
>
> I've been having fun using hexbin, but I'd like to have consistent bin sizes
> and plot ranges for different sets of data. What I'm finding is that the bin
> sizes are primarily determined by the input data mins and maxes. For
> instance, I'm plotting data with something like:
Instead of a "something like" could you please post a complete example
that we can run so we can replicate the error. This saves us a lot of
time. Also, please report any version info, as described at
http://matplotlib.sourceforge.net/faq/troubleshooting_faq.html#report-a-problem
For example, the following runs for me using mpl svn:
import numpy as np
import matplotlib.cm as cm
import matplotlib.pyplot as plt
n = 100000
x = np.random.standard_normal(n)
y = 2.0 + 3.0 * x + 4.0 * np.random.standard_normal(n)
xmin = x.min()
xmax = x.max()
ymin = y.min()
ymax = y.max()
plt.subplots_adjust(hspace=0.5)
plt.subplot(121)
plt.hexbin(x,y, cmap=cm.jet, extent=[xmin, xmax, ymin, ymax])
plt.axis([xmin, xmax, ymin, ymax])
plt.title("Hexagon binning")
cb = plt.colorbar()
cb.set_label('counts')
plt.subplot(122)
plt.hexbin(x,y,bins='log', cmap=cm.jet)
plt.axis([xmin, xmax, ymin, ymax])
plt.title("With a log color scale")
cb = plt.colorbar()
cb.set_label('log10(N)')
plt.show()

On Wed, Jun 17, 2009 at 5:27 PM, Elan Pavlov<ep...@gm...> wrote:
> Hi,
> I'm using an animated graph in which most of the time I don't want it
> to autoscale (due to speed). Once in a while I want it to change the
> limits of the y-axis. In order to do this I use set_ylim and follow by
> a canvas.draw(). However it does not actually redraw the canvas and
> the old tick labels remain (although the scales are reset). When I
> manually resize the canvas in updates the tick labels. Any ideas what
> I'm doing wrong?
This doesn't sound right -- a call to canvas.draw should redraw the
whole canvas cleanly, with the exception of Artists where the animated
property is set. Can you reduce your code to a free-standing example
that we can run?
JDH

Hello,
I've been having fun using hexbin, but I'd like to have consistent bin sizes
and plot ranges for different sets of data. What I'm finding is that the bin
sizes are primarily determined by the input data mins and maxes. For
instance, I'm plotting data with something like:
# import matplotlib.pyplot as plt
# plt.hexbin(x,y, cmap=cm.hot, gridsize=(50,50))
# plt.axis([xmin, xmax, ymin, ymax])
# plt.title("2D Histogram")
# cb = plt.colorbar()
# cb.set_label('counts')
# plt.show()
where xmin, etc are a fixed range. If my data sets span sizeably different
ranges, then the hexagon sizes come out completely different. I'd like to
avoid increasing the gridsize in one or both dimensions too much as that
would require very large grids in some instances.
I thought my solution to the problems would be to use the extent function in
hexbin but when I try, for instance:
# plt.hexbin(x,y, cmap=cm.hot, gridsize=(50,50),
extent=[xmin,xmax,ymin,ymax])
I get these strange errors:
 File "HexPlotLog.py", line 64, in <module>
 plt.hexbin(x,y, cmap=cm.hot, gridsize=(50,50), extent=[xmin, xmax, ymin,
ymax])
 File "/usr/lib64/python2.5/site-packages/matplotlib/pyplot.py", line 1920,
in hexbin
 ret = gca().hexbin(*args, **kwargs)
 File "/usr/lib64/python2.5/site-packages/matplotlib/axes.py", line 5447,
in hexbin
 collection.update(kwargs)
 File "/usr/lib64/python2.5/site-packages/matplotlib/artist.py", line 548,
in update
 raise AttributeError('Unknown property %s'%k)
AttributeError: Unknown property extent
The other thing I'd like to do is to set the background color of the plot to
black, or otherwise the same color as a bin of zero. I imagine this is
something I can find in the manuals, but since I'm asking questions, may as
well include it :)
I appreciate any help that can be offered.
Best,
Alex

Hi,
I'm using an animated graph in which most of the time I don't want it
to autoscale (due to speed). Once in a while I want it to change the
limits of the y-axis. In order to do this I use set_ylim and follow by
a canvas.draw(). However it does not actually redraw the canvas and
the old tick labels remain (although the scales are reset). When I
manually resize the canvas in updates the tick labels. Any ideas what
I'm doing wrong?
Elan
-- 
If I knew that a man was coming to my house with the conscious design
of doing me good, I should run for my life.
- Henry David Thoreau

For those who haven't seen the article on slashdot:
A Visual Expedition Inside the Linux File
Systems<http://cs.jhu.edu/%7Erazvanm/fs-expedition/>
Some figures are highly eye-catching. Some of which I haven't seen in
matplotlib gallery nor could be produced with.
Gökhan

Thanks. The svn trunk worked for me.
-----Original Message-----
From: Michael Droettboom [mailto:md...@st...] 
Sent: Wednesday, June 17, 2009 9:27 AM
To: Yeates, Mathew C
Cc: mat...@li...
Subject: Re: [Matplotlib-users] drawing a line segment wjhen using polar coordinates
You can pass "resolution=1" to the axes function. Unfortunately, when 
doing that you will lose the grid lines. This is a known bug. 
Better yet, update to SVN trunk which does this by default and has 
working grid lines.
Mike
Yeates, Mathew C wrote:
>
> The following produces an arc instead of a line. What am I doing wrong?
>
> 
>
> ax = axes(polar=True,rmax=1.0)
>
> polar([1,2],[0.2,0.3]) #or plot([1,2],[0.2,0.3])
>
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>
> ------------------------------------------------------------------------------
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-- 
Michael Droettboom
Science Software Branch
Operations and Engineering Division
Space Telescope Science Institute
Operated by AURA for NASA

You can pass "resolution=1" to the axes function. Unfortunately, when 
doing that you will lose the grid lines. This is a known bug. 
Better yet, update to SVN trunk which does this by default and has 
working grid lines.
Mike
Yeates, Mathew C wrote:
>
> The following produces an arc instead of a line. What am I doing wrong?
>
> 
>
> ax = axes(polar=True,rmax=1.0)
>
> polar([1,2],[0.2,0.3]) #or plot([1,2],[0.2,0.3])
>
> ------------------------------------------------------------------------
>
> ------------------------------------------------------------------------------
> Crystal Reports - New Free Runtime and 30 Day Trial
> Check out the new simplified licensing option that enables unlimited
> royalty-free distribution of the report engine for externally facing 
> server and web deployment.
> http://p.sf.net/sfu/businessobjects
> ------------------------------------------------------------------------
>
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> 
-- 
Michael Droettboom
Science Software Branch
Operations and Engineering Division
Space Telescope Science Institute
Operated by AURA for NASA

The following produces an arc instead of a line. What am I doing wrong?
ax = axes(polar=True,rmax=1.0)
polar([1,2],[0.2,0.3]) #or plot([1,2],[0.2,0.3])

Andrew Straw wrote:
> Zane Selvans wrote:
> 
>> Yep, looks like the trunk has fixed the contourf() issue.
>>
>> Unfortunately there also seems to be some new incompatibility with the
>> Basemap toolkit, even after re-installing Basemap from source. I get:
>>
>> AttributeError: Axes.frame was removed in favor of Axes.spines
>> 
>
>
> It appears Basemap hasn't caught up with the new Axes.spines usage.
>
> Can you change mpl_toolkits/basemap/__init__.py line 1265 from::
>
> ax.frame.set_linewidth(linewidth)
>
> to::
>
> for spine in ax.spines.itervalues():
> spine.set_linewidth(linewidth)
>
> There may be more issues, here -- this is just the first one and based
> off your traceback.
>
> Jeff: I had to drop the Axes.frame to implement spines that could be
> moved relative to the Axes boundary. I made sure this worked with the
> custom projection examples in the main MPL distribution, so I imagine it
> won't take too much to convert basemap. Please see svn r7144, 7145, and
> 7170 for my changes to lib/matplotlib/projections/geo.py
>
> -Andrew
> 
Andrew: This is now fixed in SVN.
BTW: basemap predates the custom projection support in matplotlib, so it 
actually doesn't use it. 
-Jeff