How to efficiently compute normal to a surface given surface points

Hi everyone,

I am struggling to understand how to compute normal to a surface on ML.

I have a very simple geometry made by a cone divided both in height and along the circumference, and what I would like as outputs for every area in which the cone is divided are:

• The centroid of every single area;
• The normal to the area centered on the centroid.

The output I would like is formed by a matrix for the centroids and a matrix for the normals in which each row is formed by a triplet X, Y, Z of the coordinates and values of the centroids and normals respectively.

I attach part of the code for generating a simple cone.

n = 36;                         % Number of divisions along the circumference
hi = 1;                         % Number of divisions along the height of the cone (needed for another part of the code)
H = 5;                          % Height of the cone
r = zeros (1,H/hi);
R = 3;                          % Base radius

for i = 1:H/hi
    r(i) = (1-i*hi/H)*R;
end

[x,y,z] = cylinder(r,n);
z = z*H;

Answer 1

[darova]

try surfnorm

[alegio20]

Thanks, i have alredy tried surfnorm but it doesn't calculates where I need to and just calculates it at intesections between areas. Not in the centers.

[darova]

You can calculate vector field (u,v,w) and interpolate it where you need

[u,v,w] = surfnorm(x,y,z);
u1 = interp2(x,y,u,x1,y1);
v1 = interp2(x,y,v,x1,y1);
w1 = interp2(x,y,w,x1,y1);