I'm using matplotlib to generate many plots of the results of a numerical simulation. The plots are used as frames in a video, and so I'm generating many of them by repeatedly calling a function similar to this one:
from pylab import *
def plot_density(filename,i,t,psi_Na):
figure(figsize=(8,6))
imshow(abs(psi_Na)**2,origin = 'lower')
savefig(filename + '_%04d.png'%i)
clf()
The problem is that the memory usage of the python process grows by a couple of megabytes with every call to this function. For example if I call it with this loop:
if __name__ == "__main__":
x = linspace(-6e-6,6e-6,128,endpoint=False)
y = linspace(-6e-6,6e-6,128,endpoint=False)
X,Y = meshgrid(x,y)
k = 1000000
omega = 200
times = linspace(0,100e-3,100,endpoint=False)
for i,t in enumerate(times):
psi_Na = sin(k*X-omega*t)
plot_density('wavefunction',i,t,psi_Na)
print i
then the ram usage grows with time to 600MB. If however I comment out the line figure(figsize=(8,6))
in the function definition, then the ram usage stays steady at 52MB. (8,6)
is the default figure size and so identical images are produced in both cases. I'd like to make different sized plots from my numerical data without running out of ram. How might I force python to free up this memory?
I've tried gc.collect()
each loop to force garbage collection, and I've tried f = gcf()
to get the current figure and then del f
to delete it, but to no avail.
I'm running CPython 2.6.5 on 64 bit Ubuntu 10.04.