matplotlib-users Mailing List for matplotlib

I would also like to point out that you can specify "auto" for a location,
and matplotlib will attempt to find a good location for you (within the
plot area). It isn't perfect, but it can be useful.

Cheers!
Ben Root


On Fri, Jan 31, 2014 at 7:02 AM, Skip Montanaro <sk...@po...> wrote:

> > 1. PNG file of figure without legend.
> > 2. PNG file of legend only.
> >
> > The end user would import both images into another tool (e.g. microsoft
> > power point) and arrange figure and legend interactively for the final
> > product.
>
> As someone pointed out to me not long ago, you can call
>
>     my_legend.draggable(True)
>
> then drag the legend where you want (in normal pointer mode). Then you
> just need to save the figure and not worry about fiddling with it
> later.
>
> Skip Montanaro
>
>
> ------------------------------------------------------------------------------
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> security issues and trends.  Skip the complicated setup - simply import
> a virtual appliance and go from zero to informed in seconds.
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> 1. PNG file of figure without legend.
> 2. PNG file of legend only.
>
> The end user would import both images into another tool (e.g. microsoft
> power point) and arrange figure and legend interactively for the final
> product.

As someone pointed out to me not long ago, you can call

    my_legend.draggable(True)

then drag the legend where you want (in normal pointer mode). Then you
just need to save the figure and not worry about fiddling with it
later.

Skip Montanaro

Hi Peter,

just get the legend handlers and labels with

    handles,labels = ax.get_legend_handles_labels()

then create an empty plot with axes `axe` and do

    axe.legend(handles, labels, loc=loc)

If you want to hide the axis:

    axe.xaxis.set_visible(False)
    axe.yaxis.set_visible(False)

and/or

    for v in axe.spines.values():
        v.set_visible(False)

Enjoy,

Fra


2014-01-31 Peter Van Wieren <p_...@sb...>

>
> I would like to ask if there is a way to print only the legend box of a
> figure.
>
> The motiviation for wanting to do this is a work around to the problem of
> having the legend box obscuring data without resorting to "outside"
> placement of the legend.   The idea here is that matplotlib would provide
> two images:
>
> 1. PNG file of figure without legend.
> 2. PNG file of legend only.
>
> The end user would import both images into another tool (e.g. microsoft
> power point) and arrange figure and legend interactively for the final
> product.
>
> Example follows:
>
> import numpy as np
> import matplotlib.pyplot as plt
>
> x = np.linspace(0, 1)
> fig, (ax)  = plt.subplots(nrows=1)
> ax.plot( x , np.sin(2*np.pi*x) , label='Curve1')
> ax.plot( x , np.sin(2*np.pi*x+0.2) , label='Curve2')
> ax.set_title('Set default color cycle to rgby')
> plt.savefig('without_legend.png',dpi=75)
>
> if True: # Difficult to automatically make a location choice robust
>   ax.legend(loc='upper left') # in this particular case, a poor choice for
> placement
> else:
>   ax.legend(loc='upper right') # in this particular case, a good choice
> for placement
>
> plt.savefig('with_legend.png',dpi=75)
>
> # worst case solution could be post processing these files with imagemagick
> #   begin with "composite without_legend.png with_legend.png -compose
> difference alpha_channel.png"
> #    ... then filter with alpha_channel.png against with_legend.png
> #    ... finally crop this to get "legend_only.png"
>
>
>
> ------------------------------------------------------------------------------
> WatchGuard Dimension instantly turns raw network data into actionable
> security intelligence. It gives you real-time visual feedback on key
> security issues and trends.  Skip the complicated setup - simply import
> a virtual appliance and go from zero to informed in seconds.
>
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>
>

I would like to ask if there is a way to print only the legend box of a figure.  


The motiviation for wanting to do this is a work around to the problem of having the legend box obscuring data without resorting to "outside" placement of the legend.   The idea here is that matplotlib would provide two images:

1. PNG file of figure without legend.
2. PNG file of legend only.

The end user would import both images into another tool (e.g. microsoft power point) and arrange figure and legend interactively for the final product.  


Example follows:

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 1)
fig, (ax)  = plt.subplots(nrows=1)
ax.plot( x , np.sin(2*np.pi*x) , label='Curve1')
ax.plot( x , np.sin(2*np.pi*x+0.2) , label='Curve2')
ax.set_title('Set default color cycle to rgby')
plt.savefig('without_legend.png',dpi=75)

if True: # Difficult to automatically make a location choice robust
  ax.legend(loc='upper left') # in this particular case, a poor choice for placement
else:
  ax.legend(loc='upper right') # in this particular case, a good choice for placement

plt.savefig('with_legend.png',dpi=75)

# worst case solution could be post processing these files with imagemagick
#   begin with "composite without_legend.png with_legend.png -compose difference alpha_channel.png"
#    ... then filter with alpha_channel.png against with_legend.png
#    ... finally crop this to get "legend_only.png"

Thanks Eric and Kio - ive been trying for a couple of days and i just cant
seem to get my head around the interpolation or masked arrays. Would it be
possible for anyone to give me a few pointers on where to start editing the
script.

Ive tried digesting these tutorials the first one seems to be relevant to
what im trying to achieve by using a Laplace filter but im still having
trouble installing all the modules to be able to play with it more 

http://www.trondkristiansen.com/?page_id=846
<http://www.trondkristiansen.com/?page_id=846>  

http://www.geophysique.be/2010/05/05/matplotlib-basemap-tutorial-part-03-masked-arrays-zoom/
<http://www.geophysique.be/2010/05/05/matplotlib-basemap-tutorial-part-03-masked-arrays-zoom/>  

And reading all of the toolkit doc....several times!

Thanks again



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On 2014/01/30 1:10 AM, Alexis Praga wrote:
> Hi,
>
> I've attached a reproducible example : when clabel is used, there are some empty (i.e white) triangles in the countour.
> It does not occur without clabel.

Thanks for the report--but clabel is intended to be used only with 
contour, not with contourf.  Typically one would call contourf, and then 
call contour, perhaps with a subset of the levels used in contourf.  The 
ContourSet resulting from the contour call would then be used in the 
call to clabel.  Example:

http://matplotlib.org/examples/pylab_examples/contourf_demo.html

In this example the contour lines are black, but if you don't want the 
lines to show up at all, you could make them transparent, and then 
include a "colors" kwarg in the clabel call.

Eric

>
> Tested with matplotlib 1.2.0, python 2.7 on Fedora 14, 64 bits.
>
> Cheers,
>

Hi, 

I've attached a reproducible example : when clabel is used, there are some empty (i.e white) triangles in the countour.
It does not occur without clabel.

Tested with matplotlib 1.2.0, python 2.7 on Fedora 14, 64 bits.

Cheers,

-- 
Alexis Praga, PhD Student (CERFACS)
GPG key : AD4A AF6D BB5C 042F 9422  1223 06E1 C1BF E287 65D0 

IMHO that's the most straightforward approach.
He can use masked array for empty blocks (if contour data doesn't
already contain the holes as masked array) and apply inpainting, then
draw the land.
For more details about inpainting: http://stackoverflow.com/a/17125125/992005


On Wed, Jan 29, 2014 at 6:22 PM, Eric Firing <ef...@ha...> wrote:
> On 2014/01/29 5:41 AM, A Short wrote:
>> Is there any work around so it looks like the below image?
>
> It looks like with any reasonable contouring algorithm, this would
> require interpolating into land regions, contouring, and then plotting
> the land on top.  The key is the interpolation, not the plotting.  The
> example you show might have been interpolated to a finer grid
> everywhere, not just in the missing value regions.

On 2014/01/29 5:41 AM, A Short wrote:
> Is there any work around so it looks like the below image?

It looks like with any reasonable contouring algorithm, this would 
require interpolating into land regions, contouring, and then plotting 
the land on top.  The key is the interpolation, not the plotting.  The 
example you show might have been interpolated to a finer grid 
everywhere, not just in the missing value regions.

I can't comment on the file itself.

Eric

>
> Could anyone confirm that this would be the correct grib file for The North
> Atlantic..?
> ftp://ftpprd.ncep.noaa.gov/pub/data/nccf/com/wave/prod/wave.20140129/nww3.t06z.grib.grib2
>
> Thanks for all the help
>
> <http://matplotlib.1069221.n5.nabble.com/file/n42798/figure_1.png>
>
>
>
>
>
> --
> View this message in context: http://matplotlib.1069221.n5.nabble.com/Plotting-NOAA-grib2-data-in-basemap-tp42698p42798.html
> Sent from the matplotlib - users mailing list archive at Nabble.com.
>
> ------------------------------------------------------------------------------
> WatchGuard Dimension instantly turns raw network data into actionable
> security intelligence. It gives you real-time visual feedback on key
> security issues and trends.  Skip the complicated setup - simply import
> a virtual appliance and go from zero to informed in seconds.
> http://pubads.g.doubleclick.net/gampad/clk?id=123612991&iu=/4140/ostg.clktrk
> _______________________________________________
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>

On 2014/01/28 11:40 PM, Ian Thomas wrote:
> On 29 January 2014 03:21, Eric Firing <ef...@ha...
> <mailto:ef...@ha...>> wrote:
>
>     On 2014/01/28 10:01 AM, A Short wrote:
>      > Hi - Ive now improved my code and confirmed the use of the right
>     grib file
>      > but i cant for the life of me figure out the missing data near the
>      > coastline..? Could anyone help?
>
>     The present contouring algorithm works with rectangular blocks, and if
>     any corner has missing data, nothing is filled for that block.
>
>
> This will improve shortly, cutting off the corners of some of those
> empty blocks. I am currently testing the new algorithm for this prior to
> submitting it for others' approval.

Ian,

I'm glad to hear that!  One possibility would be to use a temporary 
rcParam (temporary in that it might be phased out after a couple 
releases) to allow switching between the two algorithms.  This would 
make it much easier to test, and it would also allow a transition during 
which people could reproduce results obtained with earlier mpl.  It 
would also be a safety measure, in case someone hits a corner case which 
the new algorithm doesn't handle but the old one does--not that I'm 
expecting such cases to arise.

Eric

>
> Ian

Is there any work around so it looks like the below image?

Could anyone confirm that this would be the correct grib file for The North
Atlantic..? 
ftp://ftpprd.ncep.noaa.gov/pub/data/nccf/com/wave/prod/wave.20140129/nww3.t06z.grib.grib2

Thanks for all the help

<http://matplotlib.1069221.n5.nabble.com/file/n42798/figure_1.png> 





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On 29 January 2014 03:21, Eric Firing <ef...@ha...> wrote:

> On 2014/01/28 10:01 AM, A Short wrote:
> > Hi - Ive now improved my code and confirmed the use of the right grib
> file
> > but i cant for the life of me figure out the missing data near the
> > coastline..? Could anyone help?
>
> The present contouring algorithm works with rectangular blocks, and if
> any corner has missing data, nothing is filled for that block.
>

This will improve shortly, cutting off the corners of some of those empty
blocks. I am currently testing the new algorithm for this prior to
submitting it for others' approval.

Ian

On 2014/01/28 10:01 AM, A Short wrote:
> Hi - Ive now improved my code and confirmed the use of the right grib file
> but i cant for the life of me figure out the missing data near the
> coastline..? Could anyone help?

The present contouring algorithm works with rectangular blocks, and if 
any corner has missing data, nothing is filled for that block.

Eric

>
> `import Nio
> from mpl_toolkits.basemap import Basemap
> import matplotlib.pyplot as plt
> import numpy as np
>
> f = Nio.open_file('nww3.t12z.grib(2).grib2')
> lons = f.variables['lon_0'][:]
> lats = f.variables['lat_0'][::-1] # flip latitudes so data goes S-->N
> times = f.variables['forecast_time0'][:]
> ntime = 5
> data = f.variables['HTSGW_P0_L1_GLL0'][ntime,::-1]
>
> fig = plt.figure(figsize=(16,16))
> m = Basemap(llcrnrlon=-35.,llcrnrlat=42.,urcrnrlon=5.,urcrnrlat=65.,
>              projection='lcc',lat_1=10.,lat_2=15.,lon_0=10.,
>              resolution ='h',area_thresh=1000.)
>
> x, y = m(*np.meshgrid(lons, lats))
> m.fillcontinents(color='#477519')
> m.drawcoastlines(linewidth=0.5, color='k', antialiased=1, ax=None,
> zorder=None )
>
> m.contourf(x, y, data, np.arange(0,9.9,0.1))
> plt.show() `
>
> Resulting plot is here
> <http://matplotlib.1069221.n5.nabble.com/file/n42790/figure_7.png>
>
>
>
> --
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> Sent from the matplotlib - users mailing list archive at Nabble.com.
>
> ------------------------------------------------------------------------------
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> security intelligence. It gives you real-time visual feedback on key
> security issues and trends.  Skip the complicated setup - simply import
> a virtual appliance and go from zero to informed in seconds.
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>

Hi - Ive now improved my code and confirmed the use of the right grib file
but i cant for the life of me figure out the missing data near the
coastline..? Could anyone help?

`import Nio
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import numpy as np

f = Nio.open_file('nww3.t12z.grib(2).grib2')
lons = f.variables['lon_0'][:]
lats = f.variables['lat_0'][::-1] # flip latitudes so data goes S-->N
times = f.variables['forecast_time0'][:]
ntime = 5
data = f.variables['HTSGW_P0_L1_GLL0'][ntime,::-1]

fig = plt.figure(figsize=(16,16))
m = Basemap(llcrnrlon=-35.,llcrnrlat=42.,urcrnrlon=5.,urcrnrlat=65.,
            projection='lcc',lat_1=10.,lat_2=15.,lon_0=10.,
            resolution ='h',area_thresh=1000.)

x, y = m(*np.meshgrid(lons, lats))
m.fillcontinents(color='#477519')
m.drawcoastlines(linewidth=0.5, color='k', antialiased=1, ax=None,
zorder=None )

m.contourf(x, y, data, np.arange(0,9.9,0.1))
plt.show() `

Resulting plot is here 
<http://matplotlib.1069221.n5.nabble.com/file/n42790/figure_7.png> 



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Many thanks for the fix as well as for the info!
I didn't know, there are built in fonts like this in matplotlib; this
would explain the issue - the character support of Bitstream Vera Sans
is indeed rather limited;
morover the special "defaulting" status of this font hopefully means,
that this shouldn't happen with other fonts, hence, I won't need to
account for other unknown fonts, as I was worried about initially.
Thanks again and regards
   vbr


2014-01-27 Michael Droettboom <md...@st...>:
> Thanks for the report.
>
> Indeed, you are correct in that the root of this problem is that "Bitstream
> Vera Sans" does not contain these characters, yet it is being selected
> erroneously.
>
> It does appear that there is a bug in the font selection algorithm, that
> "Bitstream Vera Sans" gets selected as a perfect match even when it is not
> the first font in the requested list.  Vera Sans ships with matplotlib and
> is the "default fallback font", even though it is not installed as a system
> font on your computer.
>
> I have a fix here: https://github.com/matplotlib/matplotlib/pull/2771
>
> In the meantime, the solution you arrived at is the probably the best we can
> do for now.
>
> Mike
>
>
> On 01/27/2014 11:21 AM, Phil Elson wrote:
>
> Thanks for this Vlastimil, looks like there is either a subtlety beyond my
> font knowledge or a bug here - mdboom, did you have any ideas? Otherwise I
> think we need a github issue for this.
>
> Cheers,
>
>
> On 4 January 2014 19:37, Vlastimil Brom <vla...@gm...> wrote:
>>
>> Hi all,
>> after upgrading to matplotlib 1.3.1, I noticed some display errors on
>> the plots with regard to accented characters (such as carons etc.).
>> As I recall, I had similar problem in the past and could work around
>> them by modifying rcParams, however, this fix doesn't work as expected
>> in 1.3.1. (with python 2.7.6, 32bit on Win 7, Czech - with both WXAgg
>> and TKAgg backends).
>> >From the usual Czech diacritics   áčďéěíňóřšťúůýž some are not
>> displayed  (ďěňřťů) - replacement squares are shown instead.
>>
>> Simply prepending a suitable font at the beginning of the list
>> rcParams['font.sans-serif'] doesn't help in 1.3.1.
>> I eventually found out, that "Bitstream Vera Sans" (which is not
>> installed on this computer) is somehow offending - as long as this
>> item is in the list (even at the end), the mentioned characters aren't
>> displayed.
>>
>> The problem can be observed in the following simple pylab script:
>> ==============
>> #! Python
>> # -*- coding: utf-8 -*-
>>
>> # with implicit fonts "ďěňřťů" are not displayed properly in the plot
>> title
>> from matplotlib import rcParams
>> rcParams['font.family'] = 'sans-serif'
>> if "Bitstream Vera Sans" in rcParams['font.sans-serif']:
>>     rcParams['font.sans-serif'].remove("Bitstream Vera Sans")
>>
>> # after appending the "offending" font even at the end of the list (by
>> uncommenting the following line), ďěňřťů are not displayed again
>> # rcParams['font.sans-serif'].append("Bitstream Vera Sans")
>>
>> import pylab
>> pylab.title(u"abcd áčďéěíňóřšťúůýž äöüß ê xyz")
>> pylab.show()
>> ==============
>>
>> Is there something special in the resolution of the font items in
>> rcParams?
>> This individual issue seems to be fixed with removing the single font,
>> but I'd like to understand this more generally, as the installed fonts
>> on different computers differ.
>>
>> Thanks in advance
>>               Vlastimil Brom
>>
>>
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>
>
>
>
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Thanks for the report.

Indeed, you are correct in that the root of this problem is that 
"Bitstream Vera Sans" does not contain these characters, yet it is being 
selected erroneously.

It does appear that there is a bug in the font selection algorithm, that 
"Bitstream Vera Sans" gets selected as a perfect match even when it is 
not the first font in the requested list. Vera Sans ships with 
matplotlib and is the "default fallback font", even though it is not 
installed as a system font on your computer.

I have a fix here: https://github.com/matplotlib/matplotlib/pull/2771

In the meantime, the solution you arrived at is the probably the best we 
can do for now.

Mike

On 01/27/2014 11:21 AM, Phil Elson wrote:
> Thanks for this Vlastimil, looks like there is either a subtlety 
> beyond my font knowledge or a bug here - mdboom, did you have any 
> ideas? Otherwise I think we need a github issue for this.
>
> Cheers,
>
>
> On 4 January 2014 19:37, Vlastimil Brom <vla...@gm... 
> <mailto:vla...@gm...>> wrote:
>
>     Hi all,
>     after upgrading to matplotlib 1.3.1, I noticed some display errors on
>     the plots with regard to accented characters (such as carons etc.).
>     As I recall, I had similar problem in the past and could work around
>     them by modifying rcParams, however, this fix doesn't work as expected
>     in 1.3.1. (with python 2.7.6, 32bit on Win 7, Czech - with both WXAgg
>     and TKAgg backends).
>     >From the usual Czech diacritics   ác(d(ée(ín(ór(s(t(úu*ýz( some
>     are not
>     displayed  (d(e(n(r(t(u*) - replacement squares are shown instead.
>
>     Simply prepending a suitable font at the beginning of the list
>     rcParams['font.sans-serif'] doesn't help in 1.3.1.
>     I eventually found out, that "Bitstream Vera Sans" (which is not
>     installed on this computer) is somehow offending - as long as this
>     item is in the list (even at the end), the mentioned characters aren't
>     displayed.
>
>     The problem can be observed in the following simple pylab script:
>     ==============
>     #! Python
>     # -*- coding: utf-8 -*-
>
>     # with implicit fonts "d(e(n(r(t(u*" are not displayed properly in
>     the plot title
>     from matplotlib import rcParams
>     rcParams['font.family'] = 'sans-serif'
>     if "Bitstream Vera Sans" in rcParams['font.sans-serif']:
>         rcParams['font.sans-serif'].remove("Bitstream Vera Sans")
>
>     # after appending the "offending" font even at the end of the list (by
>     uncommenting the following line), d(e(n(r(t(u* are not displayed again
>     # rcParams['font.sans-serif'].append("Bitstream Vera Sans")
>
>     import pylab
>     pylab.title(u"abcd ác(d(ée(ín(ór(s(t(úu*ýz( äöüß ê xyz")
>     pylab.show()
>     ==============
>
>     Is there something special in the resolution of the font items in
>      rcParams?
>     This individual issue seems to be fixed with removing the single font,
>     but I'd like to understand this more generally, as the installed fonts
>     on different computers differ.
>
>     Thanks in advance
>                   Vlastimil Brom
>
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Thanks for this Vlastimil, looks like there is either a subtlety beyond my
font knowledge or a bug here - mdboom, did you have any ideas? Otherwise I
think we need a github issue for this.

Cheers,


On 4 January 2014 19:37, Vlastimil Brom <vla...@gm...> wrote:

> Hi all,
> after upgrading to matplotlib 1.3.1, I noticed some display errors on
> the plots with regard to accented characters (such as carons etc.).
> As I recall, I had similar problem in the past and could work around
> them by modifying rcParams, however, this fix doesn't work as expected
> in 1.3.1. (with python 2.7.6, 32bit on Win 7, Czech - with both WXAgg
> and TKAgg backends).
> From the usual Czech diacritics   áčďéěíňóřšťúůýž some are not
> displayed  (ďěňřťů) - replacement squares are shown instead.
>
> Simply prepending a suitable font at the beginning of the list
> rcParams['font.sans-serif'] doesn't help in 1.3.1.
> I eventually found out, that "Bitstream Vera Sans" (which is not
> installed on this computer) is somehow offending - as long as this
> item is in the list (even at the end), the mentioned characters aren't
> displayed.
>
> The problem can be observed in the following simple pylab script:
> ==============
> #! Python
> # -*- coding: utf-8 -*-
>
> # with implicit fonts "ďěňřťů" are not displayed properly in the plot title
> from matplotlib import rcParams
> rcParams['font.family'] = 'sans-serif'
> if "Bitstream Vera Sans" in rcParams['font.sans-serif']:
>     rcParams['font.sans-serif'].remove("Bitstream Vera Sans")
>
> # after appending the "offending" font even at the end of the list (by
> uncommenting the following line), ďěňřťů are not displayed again
> # rcParams['font.sans-serif'].append("Bitstream Vera Sans")
>
> import pylab
> pylab.title(u"abcd áčďéěíňóřšťúůýž äöüß ê xyz")
> pylab.show()
> ==============
>
> Is there something special in the resolution of the font items in
>  rcParams?
> This individual issue seems to be fixed with removing the single font,
> but I'd like to understand this more generally, as the installed fonts
> on different computers differ.
>
> Thanks in advance
>               Vlastimil Brom
>
>
> ------------------------------------------------------------------------------
> Rapidly troubleshoot problems before they affect your business. Most IT
> organizations don't have a clear picture of how application performance
> affects their revenue. With AppDynamics, you get 100% visibility into your
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This is a bit of a surprise. Sounds like it could have something to do with
matplotlib's build, or that of some of its dependencies, so may need
reporting to Gentoo once we've dug a little further. It could be a really
tricky one to diagnose without being able to reproduce locally, but - is
the loop significant? Does the number of figures matter? Essentially, try
to boil it down to as little code as possible (do you need to produce a
line plot to reproduce etc.).

Cheers,


On 6 January 2014 22:18, tenspd137 . <dcd...@gm...> wrote:

> Hi all,
>
> I am running a script that cranks out multiple plots in a loop.  The
> script has plt.show() as the very last line as I think you are supposed to
> do.  All plots show up, but I get a seg fault (sometimes a bus error - I
> haven't figured why it occasionally does that) when I close the last plot
> and the script exits.  I was wondering if someone could help me figure out
> what info to grab to determine what is causing it.  I use gentoo and
> recently did an upgrade world, so I am guessing some new library is not
> playing nicely as this always seemed to work before.  Also, when I switch
> to Qt4Agg backend,
> everything works as expected, but if I can help iron out a bug, I would
> like to - I really think that matplotlib is an excellent piece of software.
>
> Pertinent info:
>
> uname -a:
> Linux dayd 3.10.15-gentoo #6 SMP Sat Dec 14 15:53:47 MST 2013 x86_64
> Intel(R) Xeon(R) CPU E5-2620 0 @ 2.00GHz GenuineIntel GNU/Linux
>
> Matplotlib version - 1.3.1
>
> matplotlibrc:
> backend: TkAgg (Qt4Agg works as expected)
> interactive: False
>
> because it segfaults
>  python3.3 testplot.py --verbose-helpful > output.txt
> outputs nothing
>
> gcc --version:
> gcc (Gentoo 4.8.2 p1.0, pie-0.5.8) 4.8.2
> Copyright (C) 2013 Free Software Foundation, Inc.
> This is free software; see the source for copying conditions.  There is NO
> warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
>
> script to reproduce the problem:
>
> import sys
> import matplotlib.pyplot as plt
>
> def main():
>     for x in range(6):
>         plt.figure()
>         plt.title(x)
>         plt.plot([1,1],[1,1],'r.')
>     plt.show()
>
> if __name__ == "__main__":
>     sys.exit(main())
>
> I found some instructions on how to get debug info when you install a
> package in gentoo.  If anyone else can recreate this or need some more info
> from me - please let me know.  I will do what I can.
>
> Thanks!
>
>
>
>
>
> ------------------------------------------------------------------------------
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> organizations don't have a clear picture of how application performance
> affects their revenue. With AppDynamics, you get 100% visibility into your
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>

As with most other artists, you should be able to just call remove on the
resulting artist.

e.g.

im = plt.imshow(...)
...
im.remove()


HTH




On 2 January 2014 11:58, flambert <fra...@ya...> wrote:

> Hi,
>
> Does somebody knows how can I remove a backgroundimage. I set the image
> with
> imshow.
>
> regards,
>     flambert
>
>
>
> --
> View this message in context:
> http://matplotlib.1069221.n5.nabble.com/Remove-backgroundimage-tp42658.html
> Sent from the matplotlib - users mailing list archive at Nabble.com.
>
>
> ------------------------------------------------------------------------------
> Rapidly troubleshoot problems before they affect your business. Most IT
> organizations don't have a clear picture of how application performance
> affects their revenue. With AppDynamics, you get 100% visibility into your
> Java,.NET, & PHP application. Start your 15-day FREE TRIAL of AppDynamics
> Pro!
> http://pubads.g.doubleclick.net/gampad/clk?id=84349831&iu=/4140/ostg.clktrk
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>

Hi Kai,

I'm afraid I've never heard of this one. Do you have a full error log?

Thanks,


On 26 January 2014 02:40, <ka...@ge...> wrote:

>
>
> Hi,
>
> I'm trying to use matplotlib to generate pictures for my website view. The
> framwork I use is pyramid. But I got an error when I try to refresh my page
> two or more times. The message is as follow:
> "This application has requested the Runtime to terminate it in an unusual
> way. Please contact the application's support team for more information."
>
> Is it a win32 error? I use python27 win32 and matplotlib 1.2.
>
> Thx
>
>
> Kai Wang
>
>
>
>
>
>
> ------------------------------------------------------------------------------
> CenturyLink Cloud: The Leader in Enterprise Cloud Services.
> Learn Why More Businesses Are Choosing CenturyLink Cloud For
> Critical Workloads, Development Environments & Everything In Between.
> Get a Quote or Start a Free Trial Today.
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>

Hi,


I'm trying to use matplotlib to generate pictures for my website view. The framwork I use is pyramid. But I got an error when I try to refresh my page two or more times. The message is as follow:
"This application has requested the Runtime to terminate it in an unusual way. Please contact the application's support team for more information."


Is it a win32 error? I use python27 win32 and matplotlib 1.2.


Thx




Kai Wang

On 2014/01/22 1:51 PM, geo_leeman wrote:
> Hello all,
>
> Several of us have been stumped on how to create a map with basemap that
> doesn't have a rectangular bounding box.  I've attached an example of what
> we are trying to create (done with GMT and not ours).  Browsing the docs I
> thought it may be possible with a floating axis as in the gallery, but that
> doesn't do the trick either.  Is there a way to create such a plot with
> basemap?

I don't think so. Not easily, with labeled meridians and parallels.

Eric

>
> Thanks,
> J.L.
>
> <http://matplotlib.1069221.n5.nabble.com/file/n42766/GMT-contour.jpg>
>

Is there an easy way to get pyplot to treat calls to text() or
annotate() as if they were "data", so that it automatically expanded
the axis limits to include the text within the plot boundaries (i.e.,
not in the margin)?  My current workaround involves creating the text,
calling draw(), getting the text's bbox patch extents, transforming
those extents to data coordinates, and manually changing the ylim of
the axes object to something bigger than the transformed upper extent.
This seems rather roundabout to me, and I'm wondering if there's an
easier way.  Here is a link to a github gist of an MWE illustrating
the problem, and my current workaround:

https://gist.github.com/drammock/8570568

thanks
-- dan

Daniel McCloy
http://dan.mccloy.info/
Postdoctoral Research Fellow
Institute for Learning and Brain Sciences
University of Washington

Hello all,

Several of us have been stumped on how to create a map with basemap that
doesn't have a rectangular bounding box.  I've attached an example of what
we are trying to create (done with GMT and not ours).  Browsing the docs I
thought it may be possible with a floating axis as in the gallery, but that
doesn't do the trick either.  Is there a way to create such a plot with
basemap?

Thanks,
J.L.  

<http://matplotlib.1069221.n5.nabble.com/file/n42766/GMT-contour.jpg> 



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On 01/22/2014 09:43 AM, Benjamin Root wrote:
>
>
>
> On Wed, Jan 22, 2014 at 9:21 AM, Daryl Herzmann <ak...@gm... 
> <mailto:ak...@gm...>> wrote:
>
>     Hello,
>
>     I'm wondering why stuff plotted with ax.text() does not get
>     "clipped" by the axes bounds on the plot.  Here's a simple
>     example, run with 1.3.1:
>
>     import matplotlib.pyplot as plt
>
>     (fig, ax) = plt.subplots(1,1)
>
>     for i in range(5):
>       for j in range(5):
>         ax.text(i,j, "%sx%s" % (i,j), ha='center', va='center')
>     ax.plot([0,8],[0,8])
>     ax.set_xlim(0,2.8)
>     ax.set_ylim(0,2.8)
>     fig.savefig('test.png')
>
>     and attached output.  This causes me lots of grief with basemap as
>     well.  Is there a non-brute-force trick to get these values
>     plotted outside the axes bounds removed?
>
>     daryl
>
>
> I can't quite remember what the original issue was, but I do seem to 
> recall that this behavior was made intentional for some reason. I 
> honestly can't remember why, though, and I can't fathom what 
> circumstances that this would be desirable...

Often, the text is an annotation that you would not want to have clipped.

```
ax.text(i,j, "%sx%s" % (i,j), ha='center', va='center').set_clip_on(True)
```

will turn the clipping on for the text.

Mike

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