Hi matplotlib users and developers,
I am trying to run a web application using matplotlib in a memory constrained
environment. I have therefore tried to figure out what memory overhead
matplotlib incurs. When I run the following method prior to and after importing
pylab and matplotlib respectively I get:
def report_memory():
import os
pid = os.getpid()
a2 = os.popen('ps -p %d -o rss,vsz,%%mem' % pid).readlines()
print a2[1],
return int(a2[1].split()[1])
import numpy
report_memory()
#import pylab
#import matplotlib
report_memory()
$ python test.py
5976 17872 0.5
15608 41924 1.5
$ python test.py
5972 17824 0.5
7608 20608 0.7
I am importing numpy separately since I need it for other purposes. So pylab
uses ~24 MB while matplotlib uses 2.8 MB. Does this mean that I should rewrite
my application so that it does not depend on pylab or will the matplotlib
memory usage ramp up as I import sub modules? What is your experience?
Regards,
Jesper
-------------------------------------------------------------------------
This SF.net email is sponsored by: Microsoft
Defy all challenges. Microsoft(R) Visual Studio 2008.
http://clk.atdmt.com/MRT/go/vse0120000070mrt/direct/01/
_______________________________________________
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users
