matplotlib-users Mailing List for matplotlib (Page 12)

Scott,

This is fixed now in svn.  (I will probably go back shortly and make 
another change to improve efficiency.)  There was a one-line bug in 
contour.py, but the fundamental problem was that colors.ColorConverter 
(which handles color inputs for collections, among other things) was 
stripping off the alpha value and replacing it with 1.0.

Thanks for highlighting the bug.

Eric

Scott Ransom wrote:
> Hi Eric,
> 
> This shows what I'm talking about:
> 
> --------------------
> from pylab import *
> 
> delta = 0.025
> x = arange(-3.0, 3.0, delta)
> y = arange(-2.0, 2.0, delta)
> X, Y = meshgrid(x, y)
> Z1 = bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
> Z2 = bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
> # difference of Gaussians
> Z = 10.0 * (Z2 - Z1)
> 
> contourf(X, Y, sin(Y)*cos(X),
>          alpha=0.2)
> hot()
> contour(X, Y, Z, 6,
>         linewidths=4,
>         colors=('r', 'green', 'blue', (1,1,0), '#afeeee', '0.5'),
>         alpha=0.4)
> show()
> 
> -------------------
> 
> On Thursday 31 August 2006 13:50, Eric Firing wrote:
>> Scott,
>>
>> Please send a minimal example that I can use as a test case.  This
>> sounds vaguely familiar.
>>
>> Thanks.
>>
>> Eric
>>
>> Scott Ransom wrote:
>>> Hi All,
>>>
>>> I'm using matplotlib (with agg backends) from recent svn:
>>>
>>> In [63]: matplotlib.__version__
>>> Out[63]: '0.87.4'
>>>
>>> and I can't seem to get contour() or contourf() to utilize the
>>> alpha keyword.  No matter what value I set, alpha=1.0 on the
>>> output.  Alpha in general works fine, as the scatter_demo2.py
>>> example gives very nicely alpha-channeled output.
>>>
>>> Any ideas?  Thanks a bunch,
>>>
>>> Scott
> 

Hi all,

I'm trying to generate a plot that contains 3 subplots:
2 line plots and a basemap plot showing location.  I'm
generating about 200 such plots however my script
doesn't get to complete because it encounters a MemoryError.

I found the test script at 
http://matplotlib.sourceforge.net/faq.html#LEAKS (which
BTW generates a plot with 4 subplots) and it succeeded
beautifully with no memory issues.  However I changed the
last subplot to be a basemap plot and I was able to see
the memory leak.  Below is the modified leak test script
I used and the abbreviated output from it.  I would truly
appreciate any help on this.

Thanks,

Gerald

################################################
#memory leak test
################################################
import os, sys, time
import matplotlib
matplotlib.use('Agg')
from pylab import *
from matplotlib.toolkits.basemap import Basemap

def report_memory(i):
     pid = os.getpid()
     a2 = os.popen('ps -p %d -o rss,sz' % pid).readlines()
     print i, '  ', a2[1],
     return int(a2[1].split()[1])



# take a memory snapshot on indStart and compare it with indEnd
indStart, indEnd = 30, 150
for i in range(indEnd):
     ind = arange(100)
     xx = rand(len(ind))

     figure(1)
     subplot(221)
     plot(ind, xx)

     subplot(222)
     X = rand(50,50)

     imshow(X)
     subplot(223)
     scatter(rand(50), rand(50))
     subplot(224)
     #pcolor(10*rand(50,50))
     m = Basemap(0, -85, 360, 85)
     m.plot((50,), (20,), 'ro', markersize=12, label='gps')
     m.drawcoastlines()

     savefig('tmp%d' % i, dpi = 75)
     close(1)


     val = report_memory(i)
    # wait a few cycles for memory usage to stabilize
     if i==indStart: start = val

end = val
print 'Average memory consumed per loop: %1.4fk bytes ' % \
       ((end-start)/float(indEnd-indStart))


################################################
#abbreviated results
################################################
0    42724 12739
1    65068 18359
2    83036 22924
3    100980 27463
4    118928 32027
5    136872 36577
6    154828 41129
7    172784 45681
8    190736 50156
9    208692 54711
10    226644 59272
11    244592 63824
12    262548 68375
13    280496 72926
14    298440 77478
15    316392 81964
.
.
.
143    1771824 663458
144    1788924 668010
145    1791316 672561
146    1771104 677112
147    1775644 681599
148    1787288 686166
149    1791604 690718
Average memory consumed per loop: 4505.0833k bytes