Plotting the outcome of a 3D fit

4 visualizaciones (últimos 30 días)
Saeid
Saeid el 21 de Ag. de 2023
Comentada: Saeid el 21 de Ag. de 2023
I have a set of data in the form [X Y Z] where X, Y and Z are column arrays. I can plot these data using scatter3. However, when I do the fit and then try to plot a surface of the fit with new Xf & Yf values in a range that is a bit beyond the original X & Y, I try this:
XYZFitCoefficinets=fit([X Y],Z,"poly22")
Xf=linspace(0,30,100)'; Yf=linspace(40,140,100)';
Zf=feval(XYZFitCoefficinets,[Xf, Yf])
I get another column array that just shows the calculated points, whereas I need a surface. I know that I need to use the surf function and turn Xf and Yf into mesh grids, but apparently it is not possible to use the feval with meshgridded X & Y. So what can i do?

Respuesta aceptada

Torsten
Torsten el 21 de Ag. de 2023
Editada: Torsten el 21 de Ag. de 2023
x = 0:0.1:1;
y = -1:0.1:1;
[X,Y] = meshgrid(x,y);
Z = X.^2+Y.^2+0.1*(-1+2*rand(size(X)));
[Xout,Yout,Zout] = prepareSurfaceData(X,Y,Z);
S = fit([Xout,Yout],Zout,"poly22")
Linear model Poly22: S(x,y) = p00 + p10*x + p01*y + p20*x^2 + p11*x*y + p02*y^2 Coefficients (with 95% confidence bounds): p00 = 0.01879 (-0.001415, 0.039) p10 = -0.02596 (-0.1119, 0.05996) p01 = -0.007346 (-0.02993, 0.01523) p20 = 1.018 (0.9357, 1.101) p11 = 0.009983 (-0.02819, 0.04815) p02 = 0.9853 (0.963, 1.008)
xq = 0:0.01:0.5;
yq = -1:0.01:0;
[Xq,Yq] = meshgrid(xq,yq);
S(Xq,Yq)
ans = 101×51
1.0115 1.0112 1.0112 1.0113 1.0117 1.0122 1.0130 1.0140 1.0151 1.0165 1.0181 1.0199 1.0218 1.0240 1.0264 1.0290 1.0318 1.0348 1.0380 1.0414 1.0450 1.0489 1.0529 1.0571 1.0615 1.0662 1.0710 1.0760 1.0813 1.0867 0.9918 0.9915 0.9915 0.9916 0.9920 0.9926 0.9933 0.9943 0.9955 0.9968 0.9984 1.0002 1.0022 1.0044 1.0067 1.0093 1.0121 1.0151 1.0184 1.0218 1.0254 1.0292 1.0332 1.0374 1.0419 1.0465 1.0513 1.0564 1.0616 1.0671 0.9723 0.9721 0.9720 0.9722 0.9725 0.9731 0.9738 0.9748 0.9760 0.9774 0.9789 0.9807 0.9827 0.9849 0.9873 0.9899 0.9927 0.9957 0.9989 1.0023 1.0059 1.0097 1.0138 1.0180 1.0224 1.0270 1.0319 1.0369 1.0422 1.0476 0.9530 0.9528 0.9527 0.9529 0.9532 0.9538 0.9546 0.9555 0.9567 0.9581 0.9597 0.9614 0.9634 0.9656 0.9680 0.9706 0.9734 0.9764 0.9796 0.9830 0.9866 0.9905 0.9945 0.9987 1.0031 1.0078 1.0126 1.0177 1.0229 1.0283 0.9339 0.9337 0.9336 0.9338 0.9341 0.9347 0.9355 0.9364 0.9376 0.9390 0.9406 0.9424 0.9443 0.9465 0.9489 0.9515 0.9543 0.9573 0.9605 0.9640 0.9676 0.9714 0.9754 0.9796 0.9841 0.9887 0.9935 0.9986 1.0038 1.0093 0.9150 0.9148 0.9147 0.9149 0.9153 0.9158 0.9166 0.9176 0.9187 0.9201 0.9217 0.9235 0.9255 0.9277 0.9300 0.9326 0.9355 0.9385 0.9417 0.9451 0.9487 0.9525 0.9565 0.9608 0.9652 0.9698 0.9747 0.9797 0.9850 0.9904 0.8964 0.8961 0.8961 0.8962 0.8966 0.8971 0.8979 0.8989 0.9000 0.9014 0.9030 0.9048 0.9068 0.9090 0.9114 0.9140 0.9168 0.9198 0.9230 0.9264 0.9300 0.9338 0.9379 0.9421 0.9465 0.9512 0.9560 0.9611 0.9663 0.9718 0.8779 0.8776 0.8776 0.8777 0.8781 0.8786 0.8794 0.8804 0.8816 0.8829 0.8845 0.8863 0.8883 0.8905 0.8929 0.8955 0.8983 0.9013 0.9045 0.9079 0.9115 0.9154 0.9194 0.9236 0.9281 0.9327 0.9375 0.9426 0.9478 0.9533 0.8595 0.8593 0.8593 0.8594 0.8598 0.8603 0.8611 0.8621 0.8633 0.8646 0.8662 0.8680 0.8700 0.8722 0.8746 0.8772 0.8800 0.8830 0.8862 0.8896 0.8933 0.8971 0.9011 0.9053 0.9098 0.9144 0.9193 0.9243 0.9296 0.9350 0.8414 0.8412 0.8412 0.8413 0.8417 0.8422 0.8430 0.8440 0.8452 0.8465 0.8481 0.8499 0.8519 0.8541 0.8565 0.8591 0.8619 0.8649 0.8681 0.8716 0.8752 0.8790 0.8830 0.8873 0.8917 0.8963 0.9012 0.9062 0.9115 0.9169
surf(Xq,Yq,S(Xq,Yq))
  1 comentario
Saeid
Saeid el 21 de Ag. de 2023
Thank you Torsten, that's exactly what I wanted!

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