A = [1 2 3; 7 6 5]
B = [3 7];
A-B = [1-3 2-3 3-3; 7-7 6-7 5-7];
ans =[-2 -1 0; 0 -1 -2]
This is the operation I want to have done. How could I do it by matrix functions other than the iterative solutions?
A = [1 2 3; 7 6 5]
B = [3 7];
A-B = [1-3 2-3 3-3; 7-7 6-7 5-7];
ans =[-2 -1 0; 0 -1 -2]
This is the operation I want to have done. How could I do it by matrix functions other than the iterative solutions?
You do this most conveniently with bsxfun
, which automatically expands the arrays to match in size (so that you don't need to use repmat
). Note that I need to transpose B
so that it's a 2-by-1 array.
A = [1 2 3; 7 6 5]
B = [3 7];
result = bsxfun(@minus,A,B')
result =
-2 -1 0
0 -1 -2
I think that Jonas answer is the best. But just for the record, here is the solution using an explicit repmat
:
A = [1 2 3; 7 6 5];
B = [3 7];
sz = size(A);
C = A - repmat(B', [1 sz(2:end)]);
Not only is Jonas' answer simpler, it is actually faster by a factor of 2 for large matrices on my machine.
It's also interesting to note that in the case where A is an n-d array, both these solutions do something quite reasonable. The matrix C
will have the following property:
C(k,:,...,:) == A(k,:,...,:) - B(k)
In fact, Jonas' answer will run, and very likely do what you want, in the case where B is m-d, as long as the initial dimensions of A
and B'
have the same size. You can change the repmat solution to mimic this ... at which point you are starting to reimplement bsxfun
!
Normally you can't. Iterative solutions will be necessary, because the problem is poorly defined. Matrix addition/subtraction is only defined for matrices of the same dimensions.
ie:
A = | 1 2 3 |
| 7 6 5 |
B = | 3 7 |
It makes no sense to subtract a 1x2 matrix from a 2x3 matrix.
However, if you multiplied B by some intermediate matrix to make the result a 2x3 matrix, that would work, ie:
B' * Y = | 3 3 3 |
| 7 7 7 |
eg:
B' = diag(B)
= | 3 0 |
| 0 7 |
B' * Y = | 3 3 3 |
| 7 7 7 |
Y = | 1 1 1 |
| 1 1 1 |
Therefore, A-B'*Y
gives a valid, non-iterative solution.
A-(B'*Y) = | 1 2 3 | - | 3 3 3 |
| 7 6 5 | | 7 7 7 |
= A - (diag(B) * Y )
The only "cheat" here is the use of the diag()
function, which converts a vector to a strictly-diagonal-matrix. There is a way to manually decompose a set of matrix/vector multiplication operations to manually re-create the diag()
function, but that would be more work than my solution above itself.
Good luck!