Vectorizing loop containing multiplication of a scalar and a matrix

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Masa
Masa 2022-2-4
评论： Masa 2022-2-4
How to implement the following algorithm in a vectorized manner? (Preferably without using functions other than `mat`)
mat = @(i) [i-1, i, 0; i, i+1, 0; 0, 0, 1];
w = [0.2,0.5,1,0.5,0.2];
s = 0;
for j = 1:5
s = s + w(j)*mat(j);
end
the result is
s =
4.8 7.2 0.0
7.2 9.6 0.0
0.0 0.0 2.4

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Bruno Luong
Bruno Luong 2022-2-4
编辑：Bruno Luong 2022-2-4
Ran in:
w = [0.2,0.5,1,0.5,0.2];
i=reshape(1:length(w),1,1,[]);
z = zeros(size(i));
s=sum([i-1, i, 0+z; i, i+1, 0+z; 0+z, 0+z, 1+z].*reshape(w,size(i)),3)
s = 3×3
4.8000 7.2000 0 7.2000 9.6000 0 0 0 2.4000
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Bruno Luong
Bruno Luong 2022-2-4
编辑：Bruno Luong 2022-2-4
Ran in:
"so in such situations using for loop is inevitable."
No you can use ARRAYFUN but that is no better (worse) than the for-loop
mat = @(i) [i-1, i, 0; i, i+1, 0; 0, 0, 1];
w = [0.2,0.5,1,0.5,0.2];
i = 1:5;
M=arrayfun(mat, i, 'unif', 0);
wdM = arrayfun(@(w,mc) w*mc{1}, w, M, 'unif', 0);
s=sum(cat(3,wdM{:}),3)
s = 3×3
4.8000 7.2000 0 7.2000 9.6000 0 0 0 2.4000
If you prefer such cryptic code instead of for-loop just go ahead.
Masa
Masa 2022-2-4
Thanks, of course I'd rather using loops. I thought there might be some workaround using built-in functions of MATLAB (except 'arrayfun') to do the summation mentioned in the code more efficiently.

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