Hi,
your example code does not work. Bsxfun cannot operate on those arrays. When X (as in your case) is an Nx2 matrix, and you want to calculate the distance of every new point (no matter what distance) in
newpoints
you need to permute it into a 1x2xM matrix, with M being the number of new points.
In the line to calculate the Chebyshev distance, you used the max command wrong, because what you need is the maximum of the distances in each dimension (as far as I understand the definition of that distance correctly). Have a look at
doc max
to see what i mean.
So this is what I came up with:
load fisheriris
oldpoints = meas(:,3:4);
newpoints = [5 1.45; 7 2; 4 2.5; 2 3.5];
newpoints = permute(newpoints, [3,2,1]);
% Euclidean distance
dists_euclid = sqrt(sum(bsxfun(@minus, newpoints, oldpoints).^2, 2));
% Chebyshev distance
dists_cheby = max(abs(bsxfun(@minus, oldpoints, newpoints)),[],2);
after that you can use the command
squeeze
or (better)
permute
to get a two dimensional array again (might be easier to handle) and do the sorting stuff.
Hope this helps!
