How can I find the peaks of a cfit object?
12 Ansichten (letzte 30 Tage)
Ältere Kommentare anzeigen
Montgomery
am 15 Apr. 2014
Kommentiert: Chenhan
am 24 Dez. 2018
Hi, I am trying to find the peaks of a fitted curve that I have got using the curve fitting toolbox. I have a fitting function that is doing this:
ft = fittype( 'smoothingspline' );
opts = fitoptions( 'Method', 'SmoothingSpline' );
opts.SmoothingParam = 1.5029271581647606E-4;
fitresult, gof] = fit( xData, yData, ft, opts );
And a main function that I'm trying to get working using something like this
[fit,gof] = findfit(Z2);
test = coeffvalues(fit);
peaks = findpeaks(test.coefs);
with an error: "Expected X to be a vector"
I think my question boils down to, how do I use something like findpeaks() on a cfit object that I get returned from my graphing function.
Thanks for all your help.
Edit: It might be worthwhile to know Z2 3x295(3 principle components per column), test.coefs 884 x 4. The purpose of using the smoothed curve is that prior to this the curve was too 'jagged' and so I would not be able to build something that easily finds the peaks & troughs of a signal. Apologies if this is simple, I'm a beginner.
0 Kommentare
Akzeptierte Antwort
Matt Tearle
am 15 Apr. 2014
test.coefs is giving you the coefficients of the cubic splines that make up the fit. If I interpret your intention correctly, you're wanting the actual fitted curve. To do that, use feval:
yFitted = feval(fit,xData);
Now you can use findpeaks on yFitted (assuming that yData was a vector originally, so this is a 1-D fit).
xData = sort(rand(295,1));
yData = sin(6*pi*xData) + 0.1*randn(295,1);
ft = fittype( 'smoothingspline' );
opts = fitoptions( 'Method', 'SmoothingSpline' );
opts.SmoothingParam = 0.9999;
[fitresult, gof] = fit( xData, yData, ft, opts );
yfitted = feval(fitresult,xData);
plot(xData,yData,xData,yfitted)
[ypk,idx] = findpeaks(yfitted);
xpk = xData(idx);
hold on
plot(xpk,ypk,'o')
1 Kommentar
Weitere Antworten (2)
Montgomery
am 15 Apr. 2014
Bearbeitet: Montgomery
am 15 Apr. 2014
1 Kommentar
Matt Tearle
am 18 Apr. 2014
My code was just as an example to show how feval would work. The lines xData = ... and yData = ... are just making some example data (since I don't have access to yours).
Your function is mostly fine, except that you define xData in there as a local variable, and you need that for feval. So you may want to modify findfit to something like this:
function [fitresult, gof,yFitted] = find(Z2)
[xData, yData] = prepareCurveData( [], Z2 );
ft = fittype( 'smoothingspline' );
opts = fitoptions( 'Method', 'SmoothingSpline' );
opts.SmoothingParam = 1.5029271581647606E-4;
[fitresult, gof] = fit( xData, yData, ft, opts );
yFitted = feval(fitresult,xData);
Then in your calling code,
[fit,gof,yFit] = findfit(Z2);
peaks = findpeaks(yFit);
Siehe auch
Kategorien
Mehr zu Linear and Nonlinear Regression finden Sie in Help Center und File Exchange
Produkte
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!