On Fri, Mar 27, 2009 at 5:11 PM, John Hunter <jdh2...@gmail.com> wrote:
> On Fri, Mar 27, 2009 at 1:23 PM, Karen Tracey <kmtra...@gmail.com> wrote: > >> With the above change to make the texd and _fontd caches per-instance, the >> script has finished successfully 4 times. Seems pretty convincing evidence >> that it fixes the problem. >> > > OK, I made this change to svn r7008. We probably do not gain *that much* > by caching across renderers anyhow. > > Cool, thanks! > >> >> Also, make sure you have disabled usetex in matplotlibrc, since the use of >>> the filesystem for caching the tex datafiles is probably not thread safe. >>> My guess is that the font cache on the file system is not thread safe >>> either, but this may only affect the first run of mpl after a clean install. >>> >> >> Not sure what matplotlibrc is? I found a file >> /usr/share/matplotlib/matplotlib.conf that has usetex set to False. Is that >> it? If so I guess it's been disabled all along, this is not something I >> have fiddled with. >> > > matplotlib.conf is an experimental config that is no longer in use (but it > won't hurt you to have it lying around). See > http://matplotlib.sourceforge.net/users/customizing.html for details on > the matplotlibrc file > Hmm, the Ubuntu packaging for matplotlib seems to put a copy of matplotlibrc only in /etc, where, I gather, it will not ever be used by matplotlib? I guess one is supposed to copy it to one's home directory and do per-user customization there. For my case, where the code is running under Apache, I'd guess no matplotlibrc is being found so all defaults are being used. > > No need for data files -- just use np.random.rand to make up some random > data for plotting. That keeps things simple and small, and you can post the > script to the list, and hopefully we can find a home for it in our unit > tests. > OK, I reduced it to a bare minimum, using random data. I removed stuff that was in my code like customizing colors, highlighting a particular bar, and even setting of the title and axis labels since it turns out none of that is necessary to trip the exception. I'll append below a script that reliably reproduces the error on my machine. 8 threads at 50 iterations seems sure to hit it, fewer threads or fewer iterations may not. Hope this is helpful, Karen #! /usr/bin/python import os import threading import traceback import numpy as np from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas from matplotlib.figure import Figure thread_count = 8 max_iterations = 50 exception_raised = False def png_thread(tn): png_fname = 'out%d.png' % tn vals = 100 + 15 * np.random.randn(10000) i = 0 excp = None global exception_raised while not exception_raised and i < max_iterations: i += 1 png_f = open(png_fname, 'wb') try: fig = Figure() ax = fig.add_subplot(111) ax.hist(vals, 50) FigureCanvas(fig).print_png(png_f) except Exception, excp: pass png_f.close() if excp: print 'png_thread %d failed on iteration %d:' % (tn, i) print traceback.format_exc(excp) exception_raised = True else: print 'png_thread %d completed iteration %d.' % (tn, i) os.unlink(png_fname) def main(tc): threads = [] for i in range(tc): threads.append(threading.Thread(target=png_thread, args=(i+1,))) for t in threads: t.start() for t in threads: t.join() if not exception_raised: msg = 'Success! %d threads completed %d iterations with no exceptions raised.' else: msg = 'Failed! Exception raised before %d threads completed %d iterations.' print msg % (tc, max_iterations) if __name__== "__main__": main(thread_count)
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