Correct.
On Tue, May 28, 2013 at 9:42 AM, zetah wrote:
> Albert Kottke wrote:
> >
> >I had this problem as well. I think my solution was to tell the
> >garbage collector to collect.
> >
> >import gc
> >import numpy as np
> >import matplotlib.pyplot as plt
> >
> >def draw_fig(arr, fn):
> >fi
Albert Kottke wrote:
>
>I had this problem as well. I think my solution was to tell the
>garbage collector to collect.
>
>import gc
>import numpy as np
>import matplotlib.pyplot as plt
>
>def draw_fig(arr, fn):
>fig = plt.figure()
>ax = fig.add_subplot(111)
>ax.contourf(arr)
>plt.s
I had this problem as well. I think my solution was to tell the garbage
collector to collect.
import gc
import numpy as np
import matplotlib.pyplot as plt
def draw_fig(arr, fn):
fig = plt.figure()
ax = fig.add_subplot(111)
ax.contourf(arr)
plt.savefig(fn)
plt.close(fig)
gc
"zetah" wrote:
>
>Eric Firing wrote:
>>
>>plt.close(fig) # that should take care of it
>
>Thanks for your quick reply.
>
>I tried before posting `plt.close()` and it didn't work, but also
>`plt.close(fig)` doesn't change memory pumping with every loop.
>BTW, I'm on Windows with Matplotlib
Eric Firing wrote:
>
>plt.close(fig) # that should take care of it
Thanks for your quick reply.
I tried before posting `plt.close()` and it didn't work, but also
`plt.close(fig)` doesn't change memory pumping with every loop.
BTW, I'm on Windows with Matplotlib 1.2.1
-
On 2013/05/27 9:51 PM, zetah wrote:
> Hi,
>
> if I use something like this:
>
> ==
> import numpy as np
> import matplotlib.pyplot as plt
>
> def draw_fig(arr, fn):
> fig = plt.figure()
> ax = fig.add_subplot(111)
> ax.contourf(arr)
>
On Sunday, March 13, 2011, onet wrote:
> On Fri, 2011-03-11 at 17:08 -1000, Eric Firing wrote:
>> On 03/11/2011 02:54 PM, onet wrote:
>> > Using matplotlib I try to plot satellite observations, which consists of
>> > roughly one million patches that are not gridded regularly.
>> > I first collect
On Fri, 2011-03-11 at 17:08 -1000, Eric Firing wrote:
> On 03/11/2011 02:54 PM, onet wrote:
> > Using matplotlib I try to plot satellite observations, which consists of
> > roughly one million patches that are not gridded regularly.
> > I first collect the vertices (corner points of the observation
On 03/11/2011 02:54 PM, onet wrote:
> Hi,
>
> Using matplotlib I try to plot satellite observations, which consists of
> roughly one million patches that are not gridded regularly.
> I first collect the vertices (corner points of the observations) and
> colors and then use PolyCollection and ax.add
Thank you for your help. I upgraded to the latest development version,
and as you said, memory use dropped a ton. I will have to test more to
confirm that the problem is completely gone, but this appears to bring
memory usage down to something quite manageable (at least on my 8gb box
...).
T
Tom,
I just went through this, though with version 1.01 of mpl, so it may be
different. You can read the
very long thread at:
http://www.mail-archive.com/matplotlib-users@lists.sourceforge.net/msg20031.html
Those who maintain mpl don't think there is a memory leak. What I found was
that imsh
No problem. This caught me out a long time ago and has also caught out
a few people I know.
On Fri, Jan 14, 2011 at 8:23 PM, CASOLI Jules wrote:
> Hooo, well done! This is it.
>
> I didn't knew about caching...
> I was indeed using ipython, but I did led some test using the basic python
> interp
Hooo, well done! This is it.
I didn't knew about caching...
I was indeed using ipython, but I did led some test using the basic python
interpreter,with same results, so I did not mention this point.
In fact, python's basic interpreter still records the last three outputs. As my
tests were really
You're not doing this from ipython are you? It's cache hangs onto the
plot object references and stops python's garbage collector from
releasing them. If so, you can disable the cache as a workaround. A
better option would be if ipython implemented an option to avoid
caching references to matplotli
On Thu, Jan 13, 2011 at 7:54 AM, CASOLI Jules wrote:
> Hello to all,
>
> This is yet another question about matplotlib not freeing memory, when
> closing a figure (using close()).
> Here is what I'm doing (tried with several backends, on MacOSX and Linux,
> with similar results):
> --
2010/8/16 Craig Lyndon :
> If data sets are indeed stored in RAM, is there a way to discard the
> plot data after a plot had been created to leave just a static image?
> Or, read and store data points directly from a file?
You can render to PIL using the Agg backend, and display this via
PIL.Image
Hi Michael,
Thanks for your explanation. It turns out that it is a combination of
(1) and (3). I hadn't thought about (1) and I hadn't done enough
playing to see the python interpreter releasing blocks of memory. As
you suggested, the "solution" is to limit the iPython cache by using
the iPython -
There are at least three possible causes of what you're seeing here:
1) ipython stores references to all results in the console. (ipython
maintains a history of results so they can easily be accessed later). I
don't recall the details, but it may be possible to turn this feature
off or limit
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