How to fit a surface to 3D dta points

Please find the attached. I want to fit a surface to show the trends of the 3d data points but I got an error that 'Z must be a matrix, not a scalar or vector'.

Answer 1

[Stephen23]

Your data are scattered, not gridded:

https://www.mathworks.com/help/matlab/math/overview-of-interpolation-techniques.html

surf only plots gridded data. To use surf you will either have to

1. interpolate the values onto a grid, or
2. fit a curve get gridded values and plot them.

Another option would be to use a Delaunay triangulation to plot the scattered data directly:

trisurf(delaunay(IM,Z50),IM,Z50,MnXdisp)

Gives:

This blog gives an nice explanation of options for scattered data:

http://wspr.io/matlab/delaunay-surf

[Mos_bad]

the data abe been like these first : Z50_ = linspace(0,20,20); IM_ = linspace(0.0025,1.2,20); [IM, Z50] = meshgrid(IM_, Z50_); Therefore, at each IM or Z50, there are 10 data from MnXdisp data set. I wonder if it is possible to fit 20 curves and then plot a surface.

[Stephen23]

@Mos_bad: well, the data you gave us might have been gridded at some point in history, but is now missing many data points. If you have data then of course you can fit curves to it (if that has any meaning depends on the data and what it represents).

Answer 2

[KSSV]

% Unstructred data plot 
dt = delaunayTriangulation(IM,Z50) ;
t = dt.ConnectivityList ;
p = dt.Points ;

figure (1);
plot3(IM,Z50,MnXdisp,'b*');
hold on; 
trisurf(t,p(:,1),p(:,2),MnXdisp')
title('unstructured')
% structured plot 
x = IM ; y = Z50 ; z = MnXdisp ;
N = 50 ;
xi = linspace(min(x),max(x),N) ;
yi = linspace(min(y),max(y),N) ;
[X,Y] = meshgrid(xi,yi) ;
Z = griddata(x,y,z,X,Y) ;

figure (2);
plot3(IM,Z50,MnXdisp,'b*');
hold on; 
surf(X,Y,Z)
title('structured')