Maximizing along n-1 dimensions of an n-dimensional array without a for loop

I have an n-dimensional array, VV, which I would like to maximize along all dimensions for each element in the first dimension. I would also like to obtain the associated linear indices so that I can evaluate related arrays at those locations. I have to do this a large amount of times, so I need to figure out a way to do this without a for loop.

Here is an example for an n=3 dimensional array, but with a loop:

VV=rand(10,10,10);

for ii=1:size(VV,1)

Vtemp = squeeze(VV(ii,:,:));

[V(ii) I(ii)] = max(Vtemp(:));

end

[~,ind] = ismember(V,VV);

Any help would be appreciated.

Answer 1

[Jan]

VV = rand(8, 9, 10);
for ii = 1:size(VV,1)
  Vtemp          = squeeze(VV(ii, :, :));
  [V(ii), I(ii)] = max(Vtemp(:));
end
[~,ind] = ismember(V, VV);
ind

ind = 1×10

1161 12 293 1004 415 746 307 1228 479 620

s = size(VV, 1);
W = reshape(VV, s, []);
[maxV, Index] = max(W, [], 2);
ind2 = sub2ind(size(W), 1:s, Index.')

ind2 = 1×10

1161 12 293 1004 415 746 307 1228 479 620

[Brandon]

This works for me. Thanks so much!

Answer 2

[Steven Lord]

VV=randi(1000, 5, 5, 5);
[values, locations] = max(VV, [], 1:ndims(VV)-1, 'linear');
check = [reshape(values, [], 1), reshape(VV(locations), [], 1)]

check = 5×2

904 904 984 984 973 973 981 981 975 975

[Jan]

Thanks for pointing to the new 'linear' output. It was introduced in R2019a.