Matplotlib runs out of memory when plotting in a loop
I have a fairly simple plotting routine that looks like this:
from __future__ import division
import datetime
import matplotlib
matplotlib.use('Agg')
from matplotlib.pyplot import figure, plot, show, legend, close, savefig, rcParams
import numpy
from globalconstants import *
def plotColumns(columnNumbers, t, out, showFig=False, filenamePrefix=None, saveFig=True, saveThumb=True):
lineProps = ['b', 'r', 'g', 'c', 'm', 'y', 'k', 'b--', 'r--', 'g--', 'c--', 'm--', 'y--', 'k--', 'g--', 'b.-', 'r.-', 'g.-', 'c.-', 'm.-', 'y.-', 'k.-']
rcParams['figure.figsize'] = (13,11)
for i in columnNumbers:
plot(t, out[:,i], lineProps[i])
legendStrings = list(numpy.zeros(NUMCOMPONENTS))
legendStrings[GLUCOSE] = 'GLUCOSE'
legendStrings[CELLULOSE] = 'CELLULOSE'
legendStrings[STARCH] = 'STARCH'
legendStrings[ACETATE] = 'ACETATE'
legendStrings[BUTYRATE] = 'BUTYRATE'
legendStrings[SUCCINATE] = 'SUCCINATE'
legendStrings[HYDROGEN] = 'HYDROGEN'
legendStrings[PROPIONATE] = 'PROPIONATE'
legendStrings[METHANE] = "METHANE"
legendStrings[RUMINOCOCCUS] = 'RUMINOCOCCUS'
legendStrings[METHANOBACTERIUM] = "METHANOBACTERIUM"
legendStrings[BACTEROIDES] = 'BACTEROIDES'
legendStrings[SELENOMONAS] = 'SELENOMONAS'
legendStrings[CLOSTRIDIUM] = 'CLOSTRIDIUM'
legendStrings = [legendStrings[i] for i in columnNumbers]
legend(legendStrings, loc='best')
dt = datetime.datetime.now()
dtAsString = dt.strftime('%d-%m-%Y_%H-%M-%S')
if filenamePrefix is None:
filenamePrefix = ''
if filenamePrefix != '' and filenamePrefix[-1] != '_':
filenamePrefix += '_'
if saveFig:
savefig(filenamePrefix+dtAsString+'.eps')
if saveThumb:
savefig(filenamePrefix+dtAsString+'.png', dpi=300)
if showFig: f.show()
close('all')
When I plot this in single iterations, it works fine. However, the moment I put it in a loop, matplotlib throws a hissy fit...
Traceback (most recent call last):
File "c4hm_param_variation_h2_conc.py", line 148, in <module>
plotColumns(columnNumbers, timeVector, out, showFig=False, filenamePrefix='c
4hm_param_variation_h2_conc_'+str(hydrogen_conc), saveFig=False, saveThumb=True)
File "D:\phdproject\alexander paper\python\v3\plotcolumns.py", line 48, in plo
tColumns
savefig(filenamePrefix+dtAsString+'.png', dpi=300)
File "C:\Python25\lib\site-packages\matplotlib\pyplot.py", line 356, in savefi
g
return fig.savefig(*args, **kwargs)
File "C:\Python25\lib\site-packages\matplotlib\figure.py", line 1032, in savef
ig
self.canvas.print_figure(*args, **kwargs)
File "C:\Python25\lib\site-packages\matplotlib\backend_bases.py", line 1476, i
n print_figure
**kwargs)
File "C:\Python25\lib\site-packages\matplotlib\backends\backend_agg.py", line
358, in print_png
FigureCanvasAgg.draw(self)
File "C:\Python25\lib\site-packages\matplotlib\backends\backend_agg.py", line
314, in draw
self.figure.draw(self.renderer)
File "C:\Python25\lib\site-packages\matplotlib\artist.py", line 46, in draw_wr
apper
draw(artist, renderer, *kl)
File "C:\Python25\lib\site-packages\matplotlib\figure.py", line 773, in draw
for a in self.axes: a.draw(renderer)
File "C:\Python25\lib\site-packages\matplotlib\artist.py", line 46, in draw_wr
apper
draw(artist, renderer, *kl)
File "C:\Python25\lib\site-packages\matplotlib\axes.py", line 1735, in draw
a.draw(renderer)
File "C:\Python25\lib\site-packages\matplotlib\artist.py", line 46, in draw_wr
apper
draw(artist, renderer, *kl)
File "C:\Python25\lib\site-packages\matplotlib\legend.py", line 374, in draw
bbox = self._legend_box.get_window_extent(renderer)
File "C:\Python25\lib\site-packages\matplotlib\offsetbox.py", line 209, in get
_window_extent
px, py = self.get_offset(w, h, xd, yd)
File "C:\Python25\lib\site-packages\matplotlib\offsetbox.py", line 162, in get
_offset
return self._offset(width, height, xdescent, ydescent)
File "C:\Python25\lib\site-packages\matplotlib\legend.py", line 360, in findof
fset
return _findoffset(width, height, xdescent, ydescent, renderer)
File "C:\Python25\lib\site-packages\matplotlib\legend.py", line 325, in _findo
ffset_best
ox, oy = self._find_best_position(width, height, renderer)
File "C:\Python25\lib\site-packages\matplotlib\legend.py", line 817, in _find_
best_position
verts, bboxes, lines = self._auto_legend_data()
File "C:\Python25\lib\site-packages\matplotlib\legend.py", line 669, in _auto_
legend_data
tpath = trans.transform_path(path)
File "C:\Python25\lib\site-packages\matplotlib\transforms.py", line 1911, in t
ransform_path
self._a.transform_path(path))
File "C:\Python25\lib\site-packages\matplotlib\transforms.py", line 1122, in t
ransform_path
return Path(self.transform(path.vertices), path.codes,
File "C:\Python25\lib\site-packages\matplotlib\transforms.py", line 1402, in t
ransform
return affine_transform(points, mtx)
MemoryError: Could not allocate memory for path
This happens on iteration 2 (counting from 1), if that makes a difference. The code is running on Windows XP 32-bit with python 2.5 and matplotlib 0.99.1, numpy 1.3.0 and scipy 0.7.1.
EDIT: The code has now been updated to reflect the fact that the crash actually occurs at the call to legend()
. Commenting that call out solves the problem, though obviously, I would still like to be able to put a legend on my graphs...
Is each loop supposed to generate a new figure? I don't see you closing it or creating a new figure instance from loop to loop.
This call will clear the current figure after you save it at the end of the loop:
pyplot.clf()
I'd refactor, though, and make your code more OO and create a new figure instance on each loop:
from matplotlib import pyplot
while True:
fig = pyplot.figure()
ax = fig.add_subplot(111)
ax.plot(x,y)
ax.legend(legendStrings, loc = 'best')
fig.savefig('himom.png')
# etc....
I've also run into this error. what seems to have fixed it is
while True:
fig = pyplot.figure()
ax = fig.add_subplot(111)
ax.plot(x,y)
ax.legend(legendStrings, loc = 'best')
fig.savefig('himom.png')
#new bit here
pylab.close(fig) #where f is the figure
running my loop stably now with fluctuating memory but no consistant increase
Answer from ninjasmith worked for me too - pyplot.close()
enabled my loops to work.
From the pyplot tutorial, Working with multiple figures and axes:
You can clear the current figure with
clf()
and the current axes withcla()
. If you find this statefulness, annoying, don’t despair, this is just a thin stateful wrapper around an object oriented API, which you can use instead (see Artist tutorial)If you are making a long sequence of figures, you need to be aware of one more thing: the memory required for a figure is not completely released until the figure is explicitly closed with
close()
. Deleting all references to the figure, and/or using the window manager to kill the window in which the figure appears on the screen, is not enough, because pyplot maintains internal references untilclose()
is called.