- load each file in turn, use indexing to extract a subset of the loaded matrix, store this in an ND array, once all have been extracted take the mean. Then repeat for the next subset.
- use tall arrays to access data directly from the harddrive, use indexing to extract a subset of the loaded matrix, store this in an ND array, once all have been extracted take the mean. Then repeat for the next subset.

# Calculating a mean matrix from a large number of matrices

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I have been trying to calculate an average matrix from 50 matrices. Using squeeze and cat, i have calculated the mean to two matrices. My question was; how is it possible to get the mean of 50 matrices. I have a code to open the files from a folder and reformat and bin them.

myFolder = uigetdir('C:\Users\c13459232\Documents\MATLAB');

if ~isdir(myFolder)

errorMessage = sprintf('Error: the following folder does not exist: \n%s', myFolder);

uiwait(warndlg(errorMessage));

return;

end

outFolder = fullfile(myFolder, 'output');

mkdir(outFolder);

filePattern = fullfile(myFolder, '*.asc');

Files = dir(filePattern);

for k = 1 : length(Files)

baseFileName = Files(k).name;

FileName = fullfile(myFolder, baseFileName);

fprintf(1, 'Now reading %s\n', FileName);

fid = fopen(FileName);

Cell = textscan( fid, '%d', 'delimiter', ';')

fclose(fid);

Data = cell2mat(Cell);

N = 1024;

skip = 2;

Finish0 = reshape(Data, N, [])';

Finish1 = Finish0(1:skip:end, 1:skip:end);

newFileName = fullfile(outFolder, ['finish_' sprintf('%03d', k) '.txt']);

dlmwrite(newFileName, Finish0, ';');

eval(['finish_' sprintf('%03d', k) ' = Finish1;']);

disp([':: Now writing ' newFileName]);

end

Where could i insert squeeze(cat()) to average all of these matrices. The example I found to get the mean of two matrices is:

c2 = squeeze(mean(cat(3,finish_002,finish_004), 3));

Would you suggest a variation on this code or is there a better way to get an average matrix?

##### 9 Commenti

Stephen23
il 14 Mar 2017

@Aaron Smith: using indexing is going to be much easier to work with.

If you want to know why, read that link I gave you.

Guillaume
il 14 Mar 2017

Modificato: Guillaume
il 14 Mar 2017

"You see, when each full matrix is saved as a single cell in a cell array, I'm not sure if this will give me the freedom i need to plot each one individually and to bin each one individually"

It's the exact opposite. Having all the matrices as cells of a cell array gives you the freedom to treat each them individually any way you want. Use a fixed index in your cell array, and the freedom to operate on all them at once. Having individually named matrices you sacrifice the latter and don't gain anything in return.

As a rule, if you're numbering variables you're doing something wrong. These numbered variables are obviously related so they should be stored together in a container of some sort (matrix, cell array, containers.map, whatever).

This would make your question dead easy to solve:

%finish: cell array of matrices

meanofallmatrices = mean(cat(3, finish{:}), 3); %no need for squeeze

And since all the matrices are obviously the same size, you could store them directly as a 3D array instead of cell array (with again no loss of freedom)

Stephen is right, eval is completely the wrong approach. Here be dragons!

### Risposte (1)

Thorsten
il 13 Mar 2017

Modificato: Thorsten
il 14 Mar 2017

In the for-loop, you can just use

if k == 1,

M = 1/length(Files)*Data;

else

M = M + 1/length(Files)*Data;

end

Then after the loop, M is the mean of the matrices.

##### 10 Commenti

Guillaume
il 15 Mar 2017

Modificato: Guillaume
il 15 Mar 2017

You've got a closing bracket in the wrong location, the second 3 is an argument to mean, not cat.

mean(cat(3, finishCell{:}), 3);

%bracket goes here ------^

That second 3 tells mean to average across pages instead of the default across rows as you saw.

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