Example in 2D
% Data
x = rand(1,100)*10;
y = rand(1,100)*5;
r = zeros(size(x)); % group index
r(x>0 & x<=5 & y>0 & y<=2.5) = 1;
r(x>5 & x<=10 & y>0 & y<=2.5) = 2;
r(x>0 & x<=5 & y>2.5 & y<=5) = 3;
r(x>5 & x<=10 & y>2.5 & y<=5) = 4;
figure(), gscatter(x,y,r)
hold on, axis padded, legend off
xline(5), yline(2.5)
Here I'm using conditions > as well as <= so that you can select one edge, eg 5 instead of switching between 5 and 5.1 etc, though if you need to modify from this then do so as required.
Example in 3D
% Additional data for z
z = rand(1,100)*5;
% E for Edges
xE = [0 5 10];
yE = [0 2.5 5];
zE = [0 2.5 5]; % You can see why just one value for the edge is useful.
% Group the data according to the edges (r gives the groups).
idx = 1;
for ii = 1:numel(xE)-1
for jj = 1:numel(yE)-1
for kk = 1:numel(zE)-1
r(x>xE(ii) & x<=xE(ii+1) & y>yE(jj) & y<=yE(jj+1) & z>zE(kk) & z<=zE(kk+1)) = idx;
idx = idx + 1;
end
end
end
cmap = jet(8);
figure(), scatter3(x,y,z,80,cmap(r,:),'filled')
Not the best visualisation but you can see that it does the job.
