How to perform elementwise multiplication between two matrices with different size or summation between two matrices with the same size
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Hello, imagine I have the following array:
f = 1:10;
x = -22:1:22;
y = -22:1:22;
[u,v] = meshgrid(x,y);
I wish to perform elementwise multiplication operation between 'f' and 'u' (I mean the final array must have numel(f)*numel(u) elements.) . How can I fo this efficiently (definitely I know how to do this using "for loop". this is time consuming.)? Moreover, Imagine that I want to sum "u" and "v" elementwisely which both of them have the same size (so the final array must have numel(u)*numel(v) elements.) . How to do this in order to have high speed?
Accepted Answer
Let's look at the sizes of the arrays in question.
f = 1:10;
x = -22:1:22;
y = -22:1:22;
[u,v] = meshgrid(x,y);
whos f x y u v
I wish to perform elementwise multiplication operation between 'f' and 'u' (I mean the final array must have numel(f)*numel(u) elements.)
So do you specifically want the size of the output to be [10 45*45] = [10, 2025]? Since you're using a release that supports implicit expansion this is not that difficult.
A = reshape(f, numel(f), 1).*reshape(u, 1, numel(u));
whos A
How can I fo this efficiently (definitely I know how to do this using "for loop". this is time consuming.)? Moreover, Imagine that I want to sum "u" and "v" elementwisely which both of them have the same size (so the final array must have numel(u)*numel(v) elements.) . How to do this in order to have high speed?
So you want to just normally add u and v?
B = u+v;
whos B
Or do you want to add each element of u to each element of v, not just corresponding elements?
C = reshape(u, numel(u), 1) + reshape(v, 1, numel(v));
whos C
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