Multi tool use

Why is my logical mask not working on a 2D matrix in matlab properly?

X(100,371)
%% contains 100 datapoints for 371 variables


I want to keep only the data which are within mean+standard deviation:mean-standard deviation.

This is how I am proceeding:

mx=mean(X);sx=std(X);
%%generate mean, std
%%this generates mx(1,371) and sx(1,371)

mx=double(repmat(mx,100,1));
%%this fills a matrix with the same datapoints,
%%100 times
sx=double(repmat(sx,100,1));
%% this gives mx(100,371) and sx(100,371)


g=X>mx-sx & X<mx+sx;
%%this creates a logical mask g(100,371)
%%filled with 1s and 0s

test(g)=X(g);
%%this should give me test(100,371), but I get
%%test(37100), which is wrong as it doesnt maintain
%%the shape of X

test=reshape(test,100,371)
%% but when I compare this to the my original matrix
%% X(100,371) I hardly see a difference (datapoints
%% in test are still outside the range I want.


What am I doing wrong?

1 Answer
1

There is just a little bit of syntax issue with the line

test(g) = X(g);


When the compiler executes X(g) it returns all the elements in X for which g indicates 1, and at the assignment when it executes test(g) it creates a test variable good enough in size to be indexed by g which is 1x37100 and then assigns all the elements at the right places. Long story short before the assignment you can add something like:

X(g)

X

g

test(g)

test

g

test = zeros(size(X));


While we are at this, you could use bsxfun to get the logical indexing without having to do repmat

g = bsxfun(@gt,X,mx - sx) & bsxfun(@lt,X,mx + sx)


In R2016b or recent there is implicit bsxfun expansion

g = X > mx - sx & X < mx + sx


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