Out of memory only by a matrix transpose

Question

I have a cell, Data, it contains three double arrays,

 Data = 

[74003x253 double]    [8061x253 double]    [7241x253 double]

I'm using a loop to read these arrays and perform some functions,

for ii = 1 : 3
    D = Data {ii} ;
    m = mean (D') ;
    // rest of the code
end

Which gets a warning for mean and says:

consider using different DIMENSION input argument for MEAN

However when I change it to,

for ii = 1 : 3
    D = Data {ii}' ;
    m = mean (D) ;
    // rest of the code
end

I get Out of memory error.

Comparing two codes, can someone explain what happens?

It seems that I get the error only with a Complex conjugate transpose (my data is real valued).

Answer 1

To take the mean for the n:th dimension it is possible use mean(D,n) as already stated. Regarding the memory consumption, I did some tests monitoring with the windows resource manager. The output was kind of expected.

When doing the operation D=Data{ii} only minimum memory is consumed since here matlab does no more than copying a pointer. However, when doing a transpose, matlab needs to allocate more memory to store the matrix D, which means that the memory consumption increases.

However, this solely does not cause a memory overflow, since the transpose is done in both cases.

Case 1

Separately inD = Data{ii}';

Case 2

in D = Data {ii}; m = mean(D');

The difference is that in case 2 matlab only creates a temporary copy of Data{ii}' which is not stored in the workspace. The memory allocated is the same in both cases, but in case 1 Data{ii}' is stored in D. When the memory later increases this can cause a memory overflow.

The memory consumption of D is not that bad (< 200 Mb), but the guess is that the memory got high already and that this was enough to give memory overflow.