Compute Average Matrix from Cell Array of Matrices

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Mat
Mat le 3 Déc 2014
Commenté : Guillaume le 3 Déc 2014
I have a cell array of matrices of different sizes and constant length:
ABC = [(122x21) (124x21) (117x21)....]
I would like to create a new matrix, where each element contains the average of each element from each of my array matrices.
NewMat = (124x21)
where element (1,1) = mean of all of the 1,1 elements in my primary matrices element (1,2) = the mean of all of the 1,2 elements in my primary matrices
Edited to upload starting cell array
  5 commentaires
Mat
Mat le 3 Déc 2014
Thorsten.... Would like the mean to be 8... Thanks.
Trying to incorporate your proposed code into my own atm, some teething issues. Also for Anzi's
Thorsten
Thorsten le 3 Déc 2014
Then you need to modify Azzi's solution, I think, that would return 8/3 in the above example.

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Azzi Abdelmalek
Azzi Abdelmalek le 3 Déc 2014
If you fill your missing data with zeros
a={rand(122,21), rand(124,21) , rand(117,21)} % Example
n=max(cellfun(@(x) size(x,1),a))
b=cellfun(@(x) [x ; zeros(n-size(x,1),21)],a,'un',0)
out=mean(cat(3,b{:}),3)
  1 commentaire
Mat
Mat le 3 Déc 2014
HI Azzi, thanks, I have some trouble converting into my script... supplied additional info below...
Error received is
??? Error using ==> vertcat CAT arguments dimensions are not consistent.
Error in ==> run>@(x)[x;zeros(n-size(x,1),21)]
Error in ==> FindGoldenBatchesAz at 23 b=cellfun(@(x) [x ; zeros(n-size(x,1),21)],ABC2,'un',0)
Error in ==> run at 57 evalin('caller', [s ';']);

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Plus de réponses (3)

Thorsten
Thorsten le 3 Déc 2014
Modifié(e) : Thorsten le 3 Déc 2014
The idea is to create a 124x21xN matrix 'Anew' with missing values filled with NaNs, and then take the nanmean along the third dimension of 'Anew':
A = {rand(122,21), rand(124,21), rand(117,21)};
[nrows ncols] = cellfun(@size, A);
if any(ncols - 21)
error('Not all arrays have 21 columns.')
end
maxrows = max(nrows);
for i = 1:numel(A)
X = A{i};
if size(X, 1) < maxrows
X(maxrows, 21) = NaN;
end
Anew(:,:,i) = X;
end
M = nanmean(Anew, 3);
  1 commentaire
Mat
Mat le 3 Déc 2014
??? Conversion to cell from double is not possible.
Error in ==> FindGoldenBatches at 30 X(maxrows, 21) = 0;
I get this error when converting into my code, I've posted below for further details on my data that might be the issue.

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Guillaume
Guillaume le 3 Déc 2014
You don't have a cell array of matrices, but a cell array of cell arrays that should be matrices:
This will work (based on Azzi's answer):
maxrows = max(cellfun(@(c) size(c, 1), ABC3));
numcols = cellfun(@(c) size(c, 2), ABC3);
assert(all(diff(numcols) == 0)) %just make sure
resized = cellfun(@(c) [cell2mat(c); NaN(maxrows-size(c, 1), numcols(1))], ABC3, 'UniformOutput', false);
out = nanmean(cat(3, resized{:}), 3)
  2 commentaires
Mat
Mat le 3 Déc 2014
BIG thanks!!
See, I had tried to ensure ABC3 was cell array of matrices using ABC4=cell2mat(ABC3)
This returned an error so I assumed it wouldn't work.
I am trying to see how this code works around that- any pointers or advice much appreciated!
Guillaume
Guillaume le 3 Déc 2014
ABC4 = cellfun(@(c) cell2mat(c), 'UniformOutput', false);
It's the individual cells in the main cell array that you want to convert to matrices, not the main cell array.
My code does just the above ( cell2mat) when it comes to resize the matrix to match the maximum height.

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Mat
Mat le 3 Déc 2014
Both of these codes work great, but am struggling to fit both to my code.
Matrices in my array will have strings in the first two columns. E.g.
Timestamp ID Var1 Var2 Var3 Var4
Could this be impacting when I try to use on my own code?
  2 commentaires
Thorsten
Thorsten le 3 Déc 2014
Modifié(e) : Thorsten le 3 Déc 2014
You should get rid of the first two columns in my example when you create the Anew matrix.
Mat
Mat le 3 Déc 2014
I've done this, but still can't get either working... I'm loading my ABC matrix so that folk can have a closer look.
Racked my brains on this and can't see where the difference is between my cell array and the ones you've provided in the examples; I'm clearly missing something though

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