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()
====
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_mar...@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
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