Wrapped smoothing
24 visualizzazioni (ultimi 30 giorni)
Mostra commenti meno recenti
I have some data that lies on a wrapped dimension (e.g. 0 to 360) and I want to smooth it using something like lowess etc. However, I want the smoothing to wrap so that points near 360 smooth with points near 0. Any quick and easy way to get this done?
0 Commenti
Risposte (4)
Teja Muppirala
il 1 Giu 2011
Step 1. Rescale from (0,360) to (-pi,+pi)
Step 2. Unwrap the data using UNWRAP
Step 3. Smooth it
Step 4. Rescale from (-pi,+pi) back to (0,360)
Step 5. Rewrap the data using MOD
(Steps 4 and 5 are swappable).
%%Step 0 - Make some phony data
ph = 360*interpft(randn(1,5),1000);
ph = ph+10*randn(size(ph));
ph = mod(ph,360);
figure(1);
plot(ph);
%%Step 1
ph = ph*pi/180-pi;
figure(2);
plot(ph);
%%Step 2
ph = unwrap(ph);
figure(3);
plot(ph);
%%Step 3
ph = smooth(ph,25);
hold on;
plot(ph,'r');
%%Step 4
ph = 180/pi*ph+180;
%%Step 5
ph = mod(ph,360);
figure(1);
hold on;
plot(ph,'r');
Walter Roberson
il 31 Mag 2011
If you rescale the values first, you could use the unwrap() function to get continuous values; un-rescale and then do your smoothing.
0 Commenti
John D'Errico
il 31 Mag 2011
You can use my SLM tools, with knots defined over 0-360 degrees, but specify periodic end conditions.
For example, this fit works nicely:
X = rand(100,1)*360;
Y = sind(X) + randn(size(X))/5;
slm = slmengine(X,Y,'knots',linspace(0,360,7), ...
'endconditions','periodic','plot','on', ...
'concavedown',[0,150],'concaveup',[210,360])
0 Commenti
Walter Roberson
il 2 Giu 2011
The easiest way might be to replicate the initial data at the end, using as many duplicate points as your smoothing window is wide. Smoothing done, clip off those extra points.
You would have to figure out what to do about the point for 360 being at the same place as the point for 0; possibly drop the last point if it is at 360 or higher.
3 Commenti
Walter Roberson
il 2 Giu 2011
If your measured value for 0 is different from the measured value for 360 to beyond the noise level, getting periodicity would require fudging the numbers.
Vedere anche
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!