I have a fairly simple plotting routine that looks like this:

from __future__ import division
import datetime
import matplotlib
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[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: 

        if saveThumb:
            savefig(filenamePrefix+dtAsString+'.png', dpi=300)

        if showFig: f.show()


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
    savefig(filenamePrefix+dtAsString+'.png', dpi=300)
  File "C:\Python25\lib\site-packages\matplotlib\pyplot.py", line 356, in savefi
    return fig.savefig(*args, **kwargs)
  File "C:\Python25\lib\site-packages\matplotlib\figure.py", line 1032, in savef
    self.canvas.print_figure(*args, **kwargs)
  File "C:\Python25\lib\site-packages\matplotlib\backend_bases.py", line 1476, i
n print_figure
  File "C:\Python25\lib\site-packages\matplotlib\backends\backend_agg.py", line
358, in print_png
  File "C:\Python25\lib\site-packages\matplotlib\backends\backend_agg.py", line
314, in draw
  File "C:\Python25\lib\site-packages\matplotlib\artist.py", line 46, in draw_wr
    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
    draw(artist, renderer, *kl)
  File "C:\Python25\lib\site-packages\matplotlib\axes.py", line 1735, in draw
  File "C:\Python25\lib\site-packages\matplotlib\artist.py", line 46, in draw_wr
    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
    px, py = self.get_offset(w, h, xd, yd)
  File "C:\Python25\lib\site-packages\matplotlib\offsetbox.py", line 162, in get
    return self._offset(width, height, xdescent, ydescent)
  File "C:\Python25\lib\site-packages\matplotlib\legend.py", line 360, in findof
    return _findoffset(width, height, xdescent, ydescent, renderer)
  File "C:\Python25\lib\site-packages\matplotlib\legend.py", line 325, in _findo
    ox, oy = self._find_best_position(width, height, renderer)
  File "C:\Python25\lib\site-packages\matplotlib\legend.py", line 817, in _find_
    verts, bboxes, lines = self._auto_legend_data()
  File "C:\Python25\lib\site-packages\matplotlib\legend.py", line 669, in _auto_
    tpath = trans.transform_path(path)
  File "C:\Python25\lib\site-packages\matplotlib\transforms.py", line 1911, in t
  File "C:\Python25\lib\site-packages\matplotlib\transforms.py", line 1122, in t
    return Path(self.transform(path.vertices), path.codes,
  File "C:\Python25\lib\site-packages\matplotlib\transforms.py", line 1402, in t
    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:


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.legend(legendStrings, loc="best")
  # 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.legend(legendStrings, loc="best")
    #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 with cla(). 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 until close() is called.