Hello Mike,
Thanks for the quick reply  I'll try "path.simplify" as you suggest.
My actual data is pretty big and unruly, but I wrote a bit of code
that demonstrates the point dropping. This code plots three
singlepointwide peaks on a baseline of noise that is 'length' points
long. For smaller values of 'length' all three points are visible,
but for larger values some or all of the points disappear. Maybe it's
unrealistic to think that all singlepoint outliers should always be
visible at any scale, but in this case these three points are
significantly different from all the baseline points and dropping them
obviously makes for a much different looking plot. My actual data
doesn't have singlepoint peaks like this, but it does have
~50pointwide peaks in a ~1,000,000 point plot, and many of those
peaks are routinely shortened or eliminated in the zoomedout plot of
my data, only to reappear when adequately zoomedin.
Tell me if there's any thing else I can provide you with, or if this
is just the way things are when plotting big data sets. Thanks again,
 Will
###########
import numpy
import pylab
# When length = 2000, this usually plots all 3 peaks
# When length = 5000, this plots 3, 2, 1, or 0 peaks
length = 2000
x = numpy.arange(length)
y = numpy.random.normal(loc=0.0, scale=1.0, size=length)
y[int(length*0.4)] = 100.0
y[int(length*0.5)] = 100.0
y[int(length*0.6)] = 100.0
pylab.plot(x,y)
pylab.show()
###########
On Wed, May 27, 2009 at 6:32 AM, Michael Droettboom <mdroe@...> wrote:
> You can set the rcParam "path.simplify" to False to turn off this behavior.
>
> However, the goal is that the simplification is not noticable  if it is
> that may be a bug. Are you able to share your data so I can look into this
> further?
>
> Cheers,
> Mike
>
> Will Grover wrote:
>>
>> Hello matplotlib users,
>>
>> I'm using matplotlib to plot some large data sets (1 million x,y
>> pairs) and I've noticed that, when zoomed out to view the whole plot,
>> it looks as if only every Nth point is being plotted, maybe in an
>> attempt to improve plotting performance in complex plots. When I zoom
>> in I can see points that were clearly missing in the zoomedout view.
>> Is there any way to override this so that the plot really does show
>> all the points, regardless of zoom? I've included my really simple
>> plotting code below, and I'm using the "scipy superpack" (python 2.5,
>> matplotlib0.98.6) on an OS X 10.5.7 Mac.
>>
>> Many thanks for any help!
>>
>> Will
>>
>>
>>
>> import pylab
>> import smr
>> import sys
>> for freqs, stats, chronos in smr.loadData(sys.argv[1:]): # loads data
>> into numpy.arrays
>> pylab.plot(chronos, freqs)
>> pylab.show()
>>
>>
>> 
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>
> 
> Michael Droettboom
> Science Software Branch
> Operations and Engineering Division
> Space Telescope Science Institute
> Operated by AURA for NASA
>
>
