Fastest way to convert nested cell arrays into a Matrix?
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Chris Heyman
le 9 Août 2023
Modifié(e) : Bruno Luong
le 10 Août 2023
I have a set of cell arrays of size 1000x1
Each element of one of these cell arrays is a cell of size 1806x1
Each element of the nested 1806x1 cells is a matrix of doubles of size 8x1
For a given cell array, I would like to create a 1000x1806x8 matrix of the contained values.
For some cell arrays, I had needed to check on data as it was extracted with conditional statements, so I used nested loops. However, for the rest of my data, I just to extract/convert the data as fast as possible.
A consistent order of the data needs to be maintained (IE it should be 1000 of 1806x8 organized in the same fashion across all 1000 rows).
I currently have something like the following:
%Initialize
A_Length=length(ExampleCellArray);
B_Length=length(ExampleCellArray{1, 1});
C_Length=length(ExampleCellArray{1, 1}{1,1});
OutputMatrix=zeros([A_Length,B_Length,C_Length])+NaN ;
%Extract
for A=1:A_Length
for B=1:B_Length
for C=1:C_Length
OutputMatrix(A,B,C)=ExampleCellArray{A, 1}{B,1}(C);
end
end
end
What is the fastest (and most efficient) way to convert my data to matrix form?
I've done some searching but there seems to be a few methods and I’m not sure which is fastest. Also, I don’t see any specific examples which include nested cells like this.
…Yes, this is a horrible implementation of nested cells but it's the form I have and thus I want to convert the data to matrices before further manipulations.
Bonus question: Why does the a parallelized version (IE parfor A=1:A_Length ) of the above example run more slowly than a traditional for loop?
Thanks!
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Bruno Luong
le 9 Août 2023
Modifié(e) : Bruno Luong
le 9 Août 2023
If the deep nested arrays are column vectors
Tmp=cat(2,ExampleCellArray{:})';
OutputMatrix=reshape(cat(2,Tmp{:})', [A_Length B_Length C_Length]);
If the deep nested arrays are row vectors
Tmp=cat(2,ExampleCellArray{:})';
OutputMatrix=reshape(cat(1,Tmp{:}), [A_Length B_Length C_Length]);
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