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How to speed up data processing when extracting from a large cell array?

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Raju Kumar
Raju Kumar el 19 de Sept. de 2023
Comentada: Dyuman Joshi el 19 de Sept. de 2023
I am dealing with a large cell array (e.g., 3826341x1 cell). I would like merge the data or matrix from each cell. Using 'cell2mat' takes so much of time. Is there any alternative to cell2mat to process the data faster? Any leads will be highly appreciated. Thanks.
  5 comentarios
Raju Kumar
Raju Kumar el 19 de Sept. de 2023
Hi @Dyuman Joshi, I have attached a file of small size. The actaul file is a way bigger, but can not be uploadded here because Matlab allows only up to 5MB.
Dyuman Joshi
Dyuman Joshi el 19 de Sept. de 2023
With the inbuilt functions, vertcat is the fastest option.
load('array.mat')
whos
Name Size Bytes Class Attributes alphaClusterAll 14879x1 24311128 cell ans 1x34 68 char cmdout 1x33 66 char
f1=@(x) cell2mat(x);
f2=@(x) vertcat(x{:});
f3=@(x) cat(1,x{:});
F1 = @()f1(alphaClusterAll);
F2 = @()f2(alphaClusterAll);
F3 = @()f3(alphaClusterAll);
fprintf('Time taken by cell2mat = %f seconds', timeit(F1))
Time taken by cell2mat = 0.009412 seconds
fprintf('Time taken by vertcat = %f seconds', timeit(F2))
Time taken by vertcat = 0.003332 seconds
fprintf('Time taken by cat = %f seconds', timeit(F3))
Time taken by cat = 0.005746 seconds
isequal(F1(),F2(),F3())
ans = logical
1
You can try this FEX submission - Cell2Vec

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