Re: [Matplotlib-users] to much points

[Michael D. <md...@st...>]

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<fel...@gm...>  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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