Using three 60000 x 1 double matrices, how to make the 3D graph efficiently in the form of 2D

Hello, Simply, I need to make use 3 matrices which are 60000 x 1 size each. When I use the code below, I have a serious performance problem and I cannot complete the meshgrid because of the large matrices. How can I implement what I need to do? Thanks

        clc
        clear all
        a=rand(60000,1);
        b=rand(60000,1);
        c=rand(60000,1);
        [X,Y]=meshgrid(a,b);
        Z=griddata(a,b,c,X,Y,'cubic');
        mesh(X,Y,Z)

Answer 1

[Kelly Kearney]

Right now, your meshgird command is attempting to create 2 60000x60000 matrices... which are going to require around 26 GB each. However, luckily, that's not actually what you want to do.

Is your real data actually completely scattered, as in this example? Or does it already lie on a grid, but is simply stored in vectors?

If it's truly scattered:

F = scatteredInterpolant(x,y,z);
[x,y] = meshgrid(linspace(min(a),max(a),100), linspace(min(b),max(b),100));
z = F(x,y);
mesh(x,y,z);

If it lies on a grid already, you can eliminate the triagulation and simply rearrange your data into the appropriate grids.

[Kelly Kearney]

The edge effects are probably due to extrapolation. By default, scatteredInterpolant performs linear interpolation and extrapolation, and linear extrapolation can run away like that if your edge points are noisy. You might want to try nearest neighbor extrapolation instead:

F = scatteredInterpolant(x,y,'linear','nearest');

[SAMET YILDIZ]

Thank you, it helped a lot