matplotlib-users Mailing List for matplotlib

You have plotted three lines, but only provided legend labels for two of 
them.  Try:

plt.legend(('Model length', 'Data length', 'Something else'),
             'best', shadow=True, fancybox=True)


Mike

On 08/24/2010 06:33 AM, xyz wrote:
> Hello,
> the following script creates a legend for only two instead of three
> datasets.
> -----------
> from pylab import *
> import matplotlib.pyplot as plt
>
> fig = plt.figure()
> ax = fig.add_subplot(111)
>
> for i in [[2,2], [2,3], [4.2,3.5]]:
>     print i[0],i[1]
>     plt.plot(i[0],i[1],'o')
>
> ax.grid(True)
> plt.legend(('Model length', 'Data length'),
>              'best', shadow=True, fancybox=True)
>
> plt.show()
> -----------------
>
> What did I wrong.
>
> Thank you in advance.
>
> ------------------------------------------------------------------------------
> Sell apps to millions through the Intel(R) Atom(Tm) Developer Program
> Be part of this innovative community and reach millions of netbook users
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>    


-- 
Michael Droettboom
Science Software Branch
Space Telescope Science Institute
Baltimore, Maryland, USA

Hello,
the following script creates a legend for only two instead of three 
datasets.
-----------
from pylab import *
import matplotlib.pyplot as plt

fig = plt.figure()
ax = fig.add_subplot(111)

for i in [[2,2], [2,3], [4.2,3.5]]:
   print i[0],i[1]
   plt.plot(i[0],i[1],'o')

ax.grid(True)
plt.legend(('Model length', 'Data length'),
            'best', shadow=True, fancybox=True)

plt.show()
-----------------

What did I wrong.

Thank you in advance.

Hello, Benjamin,
    Thanks for your quick response ! I found that I only need use clf(), and 
then everything is fine ! The code can be run quickly and I can exit ipython 
gracefully afterwards. So it is not a problem of backend, just of clearing the 
existing figures properly ! (close() is not good because the figures are not 
displayed.)
    cheers,

xiaoni


________________________________
From: Benjamin Root <ben...@ou...>
To: xiaoni <wa...@ya...>
Cc: mat...@li...
Sent: Tue, August 24, 2010 2:29:32 AM
Subject: Re: [Matplotlib-users] a question about backend, matplotlib and ipython


On Mon, Aug 23, 2010 at 1:53 PM, xiaoni <wa...@ya...> wrote:

Hello,   
>     I got a problem with backend in matplotlib.
>     I used ipython for launching the codes and           the backend of 
>matplotlib is GTKAgg.   I have a code.py with a for loop for processing data, 
>and in each           iteration I read and plot and save the figures. Because 
>there           are so many figures, I set the non-interative mode and not using 
>"show()" in the code. Then the memory is used more and more as the           
>iteration number increases, and the most memory is           due to write_png 
>function. I guess that  the figures           (though not shown on the screen) 
>from each iteration take the memory, and try to close the figures produced at 
>each           iteration.
>what I did:
>modify the backend to Agg in the code
>add "close('all')" before each iteration finish.
>
>   This works for removing the memory problem. But a new issue           arrive. 
>After the run is finished, the ipython command window           has no response 
>to any keyboard input for a few seconds, then a warning message appear:
>   "Warning: Timeout for mainloop thread exceeded switching to           
>nonthreaded mode (until mainloop wakes up again)",
>and when I tried to quit ipython afterwards, it is stuck there           and the 
>ipython is crashed.
>   But if I tried using "python code.py" , then it works well : no warnings. 
>   Does it mean that we can not use ipython and a backend non-GUI at the same 
>time ?
>
>   Any one would like to explain a bit ? Thanks in advance !!
>
>
>xiaoni
>
>

xiaoni,

For the way that you appear to be using ipython, it might be better to just use 
regular python instead.  ipython is very useful for interactive systems and 
other advanced topics, but for a simple, loop-driven image generator, python 
will work just fine.

As for your memory usage, doing a clf() should be helpful to keep it under 
control.  I should also note that ipython have been known to cause memory use to 
grow due to the extra references it holds to the figure data, although I don't 
know if this is still true in the latest version that is currently being worked 
on.

I hope this helps,
Ben Root



      

And if you have mutually prime numbers of colors,
  linestyles, widths, you can automatically generate
more distinct lines than I can distinguish... If there's any
wxcuse for treating them as a series, I replot
when I know how many I have, and space the
colors through a colorbar.


&C
Away from home, checking mail rarely.

On Aug 23, 2010, at 2:11 PM, John Salvatier  
<jsalvati@u.washington.edu> wrote:

> By the way, I found that the following generator expression made  
> things easy:
>
> def styles():
>     return ( {'c' : color, 'ls' : style, 'lw' : width} for color,  
> style, width in itertools.product(colors, linestyles, linewidths))
>
> then you can do something like
>
> for result, style in zip(results, styles()):
>     pylab.plot(result[i], **style)
>
> On Mon, Aug 23, 2010 at 1:22 PM, John Salvatier <jsalvati@u.washington.edu 
> > wrote:
> Thanks!
>
>
> On Mon, Aug 23, 2010 at 12:38 PM, Aman Thakral  
> <ama...@gm...> wrote:
> Hi John,
>
> Here is a simple way to do it.
>
> import matplotlib.pyplot as plt
> import numpy as np
> fig = plt.figure()
> ax = fig.add_subplot(111)
>
> colors = ('red','green','blue','yellow','orange')
> linestyles = ('-','--',':')
> linewidths = (0.5,2)
>
> y = np.random.randn(100,30)
> x = range(y.shape[0])
> i = 0
>
> for c in colors:
>     for ls in linestyles:
>         for lw in linewidths:
>             ax.plot(x,y[:,i],c=c,ls=ls,lw=lw)
>         i+=1
> plt.show()
>
>
>
> On 10-08-23 03:06 PM, John Salvatier wrote:
>> Hello,
>>
>> I have a plot with lots of curves on it (say 30), and I would like  
>> to have some way of distinguishing the curves from each other. Just  
>> plotting them works well for a few curves because they come out as  
>> different colors unless you specify otherwise, but if you do too  
>> many you start getting repeats is there a way to have matplotlib  
>> also vary the line style that it automatically assigns? Or perhaps  
>> someone has another way of distinguishing lots of curves?
>>
>> Best Regards,
>> John
>>
>>
>> --- 
>> --- 
>> --- 
>> ---------------------------------------------------------------------
>> Sell apps to millions through the Intel(R) Atom(Tm) Developer Program
>> Be part of this innovative community and reach millions of netbook  
>> users
>> worldwide. Take advantage of special opportunities to increase  
>> revenue and
>> speed time-to-market. Join now, and jumpstart your future.
>> http://p.sf.net/sfu/intel-atom-d2d
>>
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>
>
>
> --- 
> --- 
> --- 
> ---------------------------------------------------------------------
> Sell apps to millions through the Intel(R) Atom(Tm) Developer Program
> Be part of this innovative community and reach millions of netbook  
> users
> worldwide. Take advantage of special opportunities to increase  
> revenue and
> speed time-to-market. Join now, and jumpstart your future.
> http://p.sf.net/sfu/intel-atom-d2d
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

On Mon, Aug 23, 2010 at 1:53 PM, xiaoni <wa...@ya...> wrote:

> Hello,
>      I got a problem with backend in matplotlib.
>      I used ipython for launching the codes and the backend of matplotlib
> is GTKAgg.   I have a code.py with a for loop for processing data, and in
> each iteration I read and plot and save the figures. Because there are so
> many figures, I set the non-interative mode and not using "show()" in the
> code. Then the memory is used more and more as the iteration number
> increases, and the most memory is due to write_png function. I guess that
> the figures (though not shown on the screen) from each iteration take the
> memory, and try to close the figures produced at each iteration.
> what I did:
> modify the backend to Agg in the code
> add "close('all')" before each iteration finish.
>
>    This works for removing the memory problem. But a new issue arrive.
> After the run is finished, the ipython command window has no response to any
> keyboard input for a few seconds, then a warning message appear:
>    "Warning: Timeout for mainloop thread exceeded switching to nonthreaded
> mode (until mainloop wakes up again)",
> and when I tried to quit ipython afterwards, it is stuck there and the
> ipython is crashed.
>    But if I tried using "python code.py" , then it works well : no
> warnings.
>    Does it mean that we can not use ipython and a backend non-GUI at the
> same time ?
>
>    Any one would like to explain a bit ? Thanks in advance !!
>
>
> xiaoni
>
>
>
xiaoni,

For the way that you appear to be using ipython, it might be better to just
use regular python instead.  ipython is very useful for interactive systems
and other advanced topics, but for a simple, loop-driven image generator,
python will work just fine.

As for your memory usage, doing a clf() should be helpful to keep it under
control.  I should also note that ipython have been known to cause memory
use to grow due to the extra references it holds to the figure data,
although I don't know if this is still true in the latest version that is
currently being worked on.

I hope this helps,
Ben Root