Hi Gang,
I was plotting some data collected from an ADC and noticed an odd aliasing
issue. Please see the images on the following site.
http://assorted-experience.blogspot.com/2008/12/odd-aliasing-issue-with-matplotlib.html
I wonder if there is any way to avoid this kind of aliasing. I vaguely
On Sat, Dec 27, 2008 at 10:29 AM, Kaushik Ghose
kaushik_gh...@hms.harvard.edu wrote:
Hi Gang,
I was plotting some data collected from an ADC and noticed an odd aliasing
issue. Please see the images on the following site.
Hi John,
OK. I've managed to pare it down to the following pattern:
import pylab
N = 1000
x = pylab.zeros(200)
x[1] = .5
x[2:24] = 1.0
x[24] = .5
x[26] = -.5
x[27:49] = -1.0
x[49] = -.5
x = pylab.tile(x, 100)
pylab.plot(x)
The above code is sufficient to repeat the glitch (just resize the
PS. In the code just disregard the line N = 1000 - it does nothing.
Ghose, Kaushik wrote:
Hi John,
OK. I've managed to pare it down to the following pattern:
import pylab
N = 1000
x = pylab.zeros(200)
x[1] = .5
x[2:24] = 1.0
x[24] = .5
x[26] = -.5
x[27:49] = -1.0
x[49] = -.5
x =
It seems that I just cannot grasp the way the data needs to be formatted for
this to work...
I've used the griddata sample that James posted but it takes about 10
minutes to prep the data for plotting so that solution seems to be out of
discussion.
I guess my issue is that I don't know what type
