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

single-point-wide 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 single-point 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 single-point peaks like this, but it does have

~50-point-wide peaks in a ~1,000,000 point plot, and many of those

peaks are routinely shortened or eliminated in the zoomed-out plot of

my data, only to reappear when adequately zoomed-in.

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@...86...> 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 zoomed-out 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,

matplotlib-0.98.6) 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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