I am looking for a \'good\' way to find a matrix (pattern) in a larger matrix (arbitrary number of dimensions).
Example:
total = rand(3,4,5);
sub = t
Here is low-performance, but (supposedly) arbitrary dimensional function. It uses find to create a list of (linear) indices of potential matching positions in total and then just checks if the appropriately sized subblock of total matches sub.
function loc = matrixFind(total, sub)
%matrixFind find position of array in another array
% initialize result
loc = [];
% pre-check: do all elements of sub exist in total?
elements_in_both = intersect(sub(:), total(:));
if numel(elements_in_both) < numel(unique(sub))
% if not, return nothing
return
end
% select a pivot element
% Improvement: use least common element in total for less iterations
pivot_element = sub(1);
% determine linear index of all occurences of pivot_elemnent in total
starting_positions = find(total == pivot_element);
% prepare cell arrays for variable length subscript vectors
[subscripts, subscript_ranges] = deal(cell([1, ndims(total)]));
for k = 1:length(starting_positions)
% fill subscript vector for starting position
[subscripts{:}] = ind2sub(size(total), starting_positions(k));
% add offsets according to size of sub per dimension
for m = 1:length(subscripts)
subscript_ranges{m} = subscripts{m}:subscripts{m} + size(sub, m) - 1;
end
% is subblock of total equal to sub
if isequal(total(subscript_ranges{:}), sub)
loc = [loc; cell2mat(subscripts)]; %#ok
end
end
end