I have a matrix of N
rows of binary vectors, i.e.
mymatrix = [ 1 0 0 1 0;
1 1 0 0 1;
0 1 1 0 1;
0 1 0 0 1;
0 0 1 0 0;
0 0 1 1 0;
.... ]
where I'd like to find the combinations of rows that, when added together, gets me exactly:
[1 1 1 1 1]
So in the above example, the combinations that would work are 1/3
, 1/4/5
, and 2/6
.
The code I have for this right now is:
i = 1;
for j = 1:5
C = combnk([1:N],j); % Get every possible combination of rows
for c = 1:size(C,1)
if isequal(ones(1,5),sum(mymatrix(C(c,:),:)))
combis{i} = C(c,:);
i = i+1;
end
end
end
But as you would imagine, this takes a while, especially because of that combnk
in there.
What might be a useful algorithm/function that can help me speed this up?
M = [
1 0 0 1 0;
1 1 0 0 1;
0 1 1 0 1;
0 1 0 0 1;
0 0 1 0 0;
0 0 1 1 0;
1 1 1 1 1
];
% Find all the unique combinations of rows...
S = (dec2bin(1:2^size(M,1)-1) == '1');
% Find the matching combinations...
matches = cell(0,1);
for i = 1:size(S,1)
S_curr = S(i,:);
rows = M(S_curr,:);
rows_sum = sum(rows,1);
if (all(rows_sum == 1))
matches = [matches; {find(S_curr)}];
end
end
To display your matches in a good stylized way:
for i = 1:numel(matches)
match = matches{i};
if (numel(match) == 1)
disp(['Match found for row: ' mat2str(match) '.']);
else
disp(['Match found for rows: ' mat2str(match) '.']);
end
end
This will produce:
Match found for row: 7.
Match found for rows: [2 6].
Match found for rows: [1 4 5].
Match found for rows: [1 3].
In terms of efficiency, in my machine this algoritm is completing the detection of matches in about 2 milliseconds
.
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