I have some figures with multiple axes stacked on top of each other,
generated with Figure.add_subplot(). In each figure, some sets of these
axes are logically grouped together, and I need some visual clue of which
axes are more closely related.
The right way is probably to use GridSpec [
http://m
On Thu, Dec 15, 2011 at 12:33 PM, Chao YUE wrote:
> Dear matplotlib users,
>
> How can I surpress the figure pop out when I make plot within the ipython
> interactive shell?
> suppose I make a figure first and I want to save it:
>
> fig=plt.figure()
> ax=fig.add_subplot(111)
> ax.plot(np.arange(1
On Fri, Oct 28, 2011 at 6:31 AM, Paul Hilscher wrote:
> Dear all,
> first of all thank you for the this awesome plotting library :D.
> I have a logarithmic plot where I want to stress out a specific range using
> a line like
> y Something
> | |---|
> | ___
> | /
On Thu, Jul 14, 2011 at 3:57 PM, T. Tofus von Blisstein
wrote:
> Hi,
>
> how can I invert the colors of axes/background from black/white to
> white/black?
>
> thanks... I have been googling for a while...
If you want to do it for all your plots, you can mess with all of the
'color*' settings in
On Wed, Jul 13, 2011 at 6:49 PM, Benjamin Root wrote:
> On Wednesday, July 13, 2011, Justin McCann wrote:
>> $ ipython -pylab
>> #
>> from matplotlib.collections import LineCollection
>> f = figure()
>> plot()
>> ax = gca()
>> vec = numpy.random.
2011/7/13 SULSEUNG-JIN :
> Thanks, Justin
>
> I think I made a confusing example code. Here comes new one:
Maybe you just need to force a call to draw() and set your x/y limits.
This works for me on matplotlib 1.0.1
$ ipython -pylab
#
from matplotlib.collections import LineCollection
f = fig
2011/7/13 SULSEUNG-JIN :
> Hi,
>
> I'm plotting thousands of short lines on a plot. Because "plot" and "Line2D"
> are quite slow for this case, I'm trying to use lineCollection. Here comes
> the part of my testing code:
>
> ...
> segs = []
>
> # Manual set for testing
> x2 = np.zero
On Tue, Jun 21, 2011 at 1:50 PM, Frank wrote:
> matplotlib python: How do you change the background color of a line plot
> according to a given column? Say I have the following data file
>...
> 2. 1
> 3. 1
> 3. 2
>
> The first column represents the y-values, and the 2nd column should control
> the
On Mon, Jun 13, 2011 at 8:37 AM, Andrea Crotti wrote:
>
> I found this question asked other times, but trying myself there is no
> way that I get something working..
>
> So I just want to generate a pdf from a plot with the smallest possible
> margin, and I was trying for example this:
>
>fig
On Wed, May 18, 2011 at 3:01 PM, Neal Becker wrote:
> Using scatter, it seems less probably (numerous) points show just as much
> as
> more probable points. Can anyone suggest a good way to emphasize the more
> probable points?
>
> I was thinking maybe the easy way is just scale down the markers
On Wed, May 11, 2011 at 1:59 PM, Benjamin Root wrote:
> ...
> Most things, we do know the sizes of. It is my understanding that it is
> the text objects that is the unknown. If this could be solved, then a
> layout engine would be much more feasible. The problem is that even LaTeX
> has to re-
You'll want to use event handling to figure out where the user clicked, and
then you have a couple of options: Axes.vlines(), or pylab.axvline(). It
seems like pylab.axvline() will always span the entire y-axis by default,
but with Axes.vlines() you need to specify the ymin/ymax. Maybe someone else
On Wed, Dec 1, 2010 at 11:58 AM, Justin McCann wrote:
> Is there a straightforward way to limit the legend only to lines that
> appear within the current display limits? I have a plot that has too
> many separate data series to show on the legend at once, but once I
> zoom in it woul
Is there a straightforward way to limit the legend only to lines that
appear within the current display limits? I have a plot that has too
many separate data series to show on the legend at once, but once I
zoom in it would be good to re-set the legend to show only the visible
data points/lines.
I
On Wed, Nov 3, 2010 at 1:18 AM, David Frey wrote:
> ...
> My data in the y-axis (address space usage) is fairly uniform (0-2000 MB
> values), but my data in the x-axis (the time at which the the trace statements
> were executed) is highly clustered. For example, I have approximately 150
> data po
On Fri, Oct 8, 2010 at 11:10 PM, Jae-Joon Lee wrote:
> The label_mode need to be capital "L", instead of "l". I guess this
> will fix your first problem.
> While we make "l" same as "L", but I think it actually degrade the
> readability of the code, and I;m inclined to leave it as is. Let me
> kno
I just refactored some custom code to make use of
axes_grid1.ImageGrid, and I think I've come across a bug (see below).
It looks like the tick labelsize doesn't get passed properly to the
parasite axes.
I'm using Python2.6, matplotlib-1.0.0 release, and the Qt4Agg backend.
Also, I noticed that th
On Thu, Oct 7, 2010 at 4:08 PM, Benjamin Root wrote:
> ...
>> On Thu, Oct 7, 2010 at 3:09 PM, Justin McCann wrote:
>>
>>> ...
>>
>> I'd like to annotate across all of the subplots by placing a vertical line
>>> (or vspan) across the entire fig
Sorry about that; don't know what key combo I pushed. Completed email is
below.
On Thu, Oct 7, 2010 at 3:09 PM, Justin McCann wrote:
> I have several heatmap images, which I place in subplots stacked
> vertically. I've been using
>ax = figure.add_subplot(nplots, 1, plot
I have several heatmap images, which I place in subplots stacked vertically.
I've been using
ax = figure.add_subplot(nplots, 1, plotnum)
ax.imshow(...)
to add each subsequent heatmap, and then place
--
Beautiful is w
On Mon, Oct 4, 2010 at 4:50 PM, Sanjay Kairam wrote:
> Hi there,
>
> I'm having a problem installing matplotlib, I'm guessing that I am missing
> some dependency, but I am having trouble figuring out what the issue is (I
>...
> REQUIRED DEPENDENCIES
> numpy: 1.5.0
> f
On Wed, Sep 29, 2010 at 9:58 PM, Jason Grout
wrote:
>...
> I made the FAQ entry code a little more general (and hopefully more
> robust) a while ago. I don't know if it takes care of the problem
> you're talking about, though.
>
> I posted it to the matplotlib-devel mailing list here:
>
> http://
Not to pile on the "auto-adjust to make labels fit" bandwagon, but
I've been following the FAQ on adjusting the subplot locations to make
room for too-long tick labels:
http://matplotlib.sourceforge.net/faq/howto_faq.html#automatically-make-room-for-tick-labels
and have found that the FAQ cod
Here are a couple of functions you might try, with a few colors and line
styles I use:
import itertools
from pylab import *
COLORS = ['#990033', '#FF', '#00FF00', '#F79E00',
'#ff00ff', '#0080FF', '#FF', '#2D0668',
'#2EB42E', '#ff6633', '#8000ff', '#33',
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