I know a MemoryError doesn't help the user much more than a segfault, but it always makes me feel better to get a real Python exception rather than exploding ;)

Mike

On 07/01/2009 03:16 PM, Jae-Joon Lee wrote:

On Wed, Jul 1, 2009 at 2:34 PM, Michael Droettboom<mdroe@stsci.edu> wrote:I agree with Jae-Joon here -- try to reduce the number of points before passing it to matplotlib. However, I'm a little concerned about the segfault -- I'd rather matplotlib give a MemoryError exception if that's in fact what is happening. Jae-Joon -- can you share your test that causes the segfault? The snippet below completely hogs my machine for a few minutes, but then, correctly, aborts with a MemoryError. This is on FC11 i586, Python 2.6, Numpy 1.3. ==== from matplotlib.pyplot import * import numpy as np points = np.random.random((50000000, 2)) plot(points) show()Yes, I also got MemoryError in this case during the plot() call. But I got segfault for the code below. x=random(50e6) y=random(50e6) plt.plot(x, y) plt.show() In this case, plot() runs fine, but segfault during show(). The segfault happens in the _path_module::affine_transform method of src/_path.cpp. I wonder if you can reproduce this. -JJ==== Mike On 07/01/2009 01:34 PM, Jae-Joon Lee wrote: A snippet of code does not help much. Please try to post a small concise standalone example that we can run and test. A general advise is to try to reduce the number of plot call, i.e., plot as may points as possible with a single plot call. However, 50million points seems to be awful a lot. 6 inch x 6 inch figure with dpi=100 has 0.36 million number of pixels. My guess is that it makes little sense to plot 50 million points here. Anyhow, plotting 50million points with a single plot call dies with some segfault error in my machine. So, I feel that matplotlib may not be suitable for your task. But, John or others may have some insight how to deal with. Regards, -JJ On Tue, Jun 30, 2009 at 1:22 PM, Markus Feldmann<feldmann_markus@gmx.de> wrote: Hi All, my program lets slow down my cpu. This only appears if i plot to much points. I am not sure how many point i need to get this, normally i plot 3*14e6 + 8e3, that is round about 50million points. My system is a dual core 2GHz cpu with 2Gbyte Ram. Here is my method to plot, def drawtransientall(self,min): self.subplot = self.figure.add_subplot(111) self.subplot.grid(True) list_t1,list_peaks,t2,list_samples = self.computetransientall(min,min+self.maxitems) offset = 0 color = ['green','red','blue','magenta','cyan'] markerPeaks = ['v','<','1','3','s'] markerSamples = ['^','>','2','4','p'] self.plots=[[],[]] for i in range(len(self.showBands)): self.plots[0] += self.subplot.plot(list_t1[i],list_peaks[i],color=color[i],marker=markerPeaks[i], linestyle='None') self.plots[1] += self.subplot.plot(t2,list_samples[i]+offset,color=color[i], marker=markerSamples[i],linestyle='None') offset +=1 self.subplot.set_xlim(t2[0]-np.abs(t2[-1]-t2[0])/100,t2[-1]+np.abs(t2[-1]-t2[0])/100) ymax = np.amax(list_samples) ymin = np.amin(list_samples) self.subplot.set_ylim([ymin-np.abs(ymin)*0.1, ymax*1.2 + 2]) self.subplot.set_ylabel("abs(Sample(t)) und abs(Peak(t)+Offset)-->",fontsize = 12) self.subplot.set_xlabel("Zeit in Sek. -->",fontsize = 12) Any ideas how to avoid the slow down of my cpu ? regards Markus ------------------------------------------------------------------------------ _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users ------------------------------------------------------------------------------ _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users