select columns from one matrix according to values in a second matrix

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Tom Wright
Tom Wright 2011년 5월 25일
Hi, I'm trying to teach myself matlab by converting some code I originally wrote in R. The idea is to select columns from one matrix using values stored in another matrix and average them together.
I think the code below should work but I'm not sure how to handle the NaN values. In R I could use a which() statement but I'm not sure how to address this in matlab.
Any advice (or more elegant solutions)?
Thanks tom
x=magic(4)
y=[1 NaN NaN;2 3 4; 5 NaN NaN] %artificial example but rows need to be different lengths
out=zeros(size(x,1),size(y,1))
for i=1:size(y,1)
out(:,i)=mean(x(:,y(i,:)))
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Sean de Wolski
Sean de Wolski 2011년 5월 25일
Perhaps you could show the expected result for the above, since the code probably does not do what you want.

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답변 (2개)

Oleg Komarov
Oleg Komarov 2011년 5월 25일
That's the only way the averaging is consistent with the output matrix:
x = magic(5);
y = [1 NaN NaN
2 3 4
5 NaN NaN];
szY = size(y);
out = zeros(size(x,1),szY(1));
for i = 1:szY(1)
idx = y(i,:);
out(:,i) = mean(x(:,idx(~isnan(idx))),2);
end
EDIT
So, there's the accumarray alternative but also the arrayfun which is basically a hidden loop:
out2 = arrayfun(@(z) mean(x(:,y(z,~isnan(y(z,:)))),2), 1:size(y,1),'un',0);
[out2{:}]
  댓글 수: 3
Sean de Wolski
Sean de Wolski 2011년 5월 25일
Look at the dimensional argument to mean (the 2 at the end).
Oleg Komarov
Oleg Komarov 2011년 5월 25일
@Tom: mean directly cannot be applied since you change the columns you select, one option is accumarray but you will need to build subs and vals which is not the most trivial thing here, considering that the loop would be IMHO the best solution in terms of performance (speed and memory) and readability.

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Sean de Wolski
Sean de Wolski 2011년 5월 25일
doc isnan
Might be of some use.
  댓글 수: 3
Sean de Wolski
Sean de Wolski 2011년 5월 25일
so
mean(x(:,y(i,~isnan(y(i,:))))
?
Sean de Wolski
Sean de Wolski 2011년 5월 25일
We'll be able to see the operation more easily if you show us the expected result and logic.

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